SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

Sundhedsudvalget 2020-21
SUU Alm.del Bilag 102
Offentligt

København, 17. november 2020

Forberedende materiale til foretræde for Folketingets Sundhedsudvalg 19. november kl. 16

Ved foretrædet vil repræsentanter fra nogle af organisationerne bag initiativet Drukfri Ungdom

fortælle, hvorfor de 23 organisationer bag initiativet samlet peger på en 18-årsgrænse for salg af al

alkohol, som det vigtigste første skridt til at ændre danske unges alkoholkultur, så den bliver

sundere, tryggere og mere inkluderende.

Drukfri Ungdom er et initiativ fra 23 organisationer, som tæller interesseorganisationer, sundheds-

og børnefaglige organisationer, regioner og kommuner samt brancheforeninger for hhv.

alkoholindustrien og restaurationsbranchen, der samlet opfordrer Folketinget til at vedtage en ny

aldersgrænse på 18 år for salg af al alkohol.

Som forberedelse til foretrædet er her:

•

Drukfri Ungdoms fælles holdningspapir.

•

To grafer fra Vidensråd for Forebyggelse, som professor Morten Grønbæk vil tage

udgangspunkt i på foretrædet. Graferne viser hhv. aldersgrænser for salg af alkohol i

Europa, og hvilken type alkohol, danske unge drikker.

•

Den Europæiske Skolebørnsundersøgelse af Alkohol og Stoffer (ESPAD), der udkom torsdag

den 12. november 2020. Den viser, at danske unge stadig indtager stadig en ærgerlig

førsteplads på de fleste parametre i forhold til alkohol – nemlig rusdrikkeri (fem eller flere

genstande ved en lejlighed, s. 67), fuldskab de seneste 30 dage (s. 47), indtaget mængde

ren alkohol sidst de drak (s. 14 og s. 63), samt opfattelse af, hvor let det er at skaffe alkohol

(s. 37).

•

Undersøgelsen Alkoholforbrug og forekomsten af ulykker og vold blandt unge, som Statens

Institut for Folkesundhed udgav ultimo oktober 2020. Undersøgelsen viser, at unge, som

drikker mest alkohol, har markant større risiko for at komme til skade og ende på

hospitalet.

Hvis Sundhedsudvalgets medlemmer har spørgsmål til Drukfri Ungdom-initiativet før eller efter

foretrædet, er de meget velkomne til at kontakte undertegnede.

De bedste hilsner

Ida Fabricius Bruun

Koordinator, Drukfri Ungdom

E-mail:

[email protected]

Telefon: 29 80 77 66

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

Drukfri Ungdom

Tiden er moden

– indfør en ensartet aldersgrænse

for salg af alkohol på 18 år

Vores børn og unge drikker alt for meget og alt for tidligt. Sådan har det været i årtier, men det skal

og bør ikke fortsætte. Tiden er moden til at tage ansvar for at skabe sundere og tryggere rammer for

vores børn. At indføre en ensartet 18-årsgrænse for salg af alkohol vil være at tage et sådant ansvar.

Dårligste alkoholkultur i Europa

Danske unge er langt oftere fulde end andre unge i

Europa

. Det har været situationen i årevis. De senere

år har vi ganske vist konstateret et fald i børn og unges

alkoholforbrug, men de nyeste opgørelser viser, at den

positive udvikling er vendt

Det høje og frekvente forbrug skyldes først og frem-

mest, at børn og unges alkoholkultur er en ”beruselses-

kultur”

. De drikker for at blive fulde. Det er bl.a. et

resultat af, at alkohol i flere tilfælde er adgangsbillet

og omdrejningspunkt for sociale relationer; takker

man nej til rusen, vender man fællesskabet ryggen

De unges høje forbrug kan have store konsekvenser.

Forskningen viser, at alkohol er forbundet med uheld,

ulykker, vold og sex, der fortrydes

. Derudover øger et

højt alkoholforbrug risikoen for senere i livet at udvikle

alkoholproblemer og afhængighed – og dermed

alkoholrelaterede sygdomme

. Forskningen viser

desuden, at de mest udsatte børn bliver hårdest ramt

af de negative konsekvenser af et højt forbrug

Danske unge er oftere fulde

(andel af de 15-årige, som har drukket sig fuld

inden for de seneste 30 dage)

40%

35%

30%

25%

20%

15%

10%

n et

n rk

n ig

s n t l a n l a n a t i o k ki a u e l a n ni e s t r g a r a r i e m a

g o je

t s k ve Ø U n l g

Li Ty lo

Le En Kr T

Bu D

Kilde: WHO, 2020. Figuren viser medianen af andelen af henholdsvis

drenge og piger, som har været fulde inden for de seneste 30 dage.

De 11 lande med den højeste andel samt gennemsnittet er vist.

Kurven knækker

(Andel af 15- og 16-årige danske unge, som har

været fuld de seneste 30 dage)

40%

18-årsgrænse er et effektivt, målrettet

værktøj

Vidensråd for Forebyggelse peger på, at en hævet salgs-

aldersgrænse på 18 år er et veldokumenteret, målrette-

de værktøj, hvis man ønsker at udskyde debutalderen

og gøre op med fuldskabskulturen. Der er talrige gode

argumenter for indførelse af en ensartet 18-årssalgs-

aldersgrænse:

•

Erfaringerne er gode.

Knapt halvt så mange 15-årige

lykkedes med at købe alkohol efter, aldersgrænsen i

Danmark blev hævet fra 15 til 16 år i 2004

37%

32%

30%

20%

10%

2011

Kilde: Sundhedsstyrelsen, 2020.

2015

2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

Tilsvarende betød en forhøjelse af aldersgrænsen fra

16 til 18 år i Holland i 2014 en kraftig stigning i antallet

af butikker, som overholdt reglerne

50%

15-årige, som købte alkohol,

før hhv. efter aldersgrænsen blev

hævet til 16 år i 2004 i Danmark

Drenge

Piger

40%

•

Danskerne efterlyser en 18-årsgrænse.

Under-

søgelser har gentagene gange vist, at der er flertal i

befolkningen for en 18-årsgrænse

•

En 18-årsgrænse vil være et argument og hjælp til

forældrene,

fordi de bedre kan påvirke og holde styr

på deres børns alkoholforbrug. I dag kan de 16-årige

selv gå ud og købe alkohol, selvom forældrene har

sagt nej.

•

En 18-årsgrænse vil følge europæisk norm.

Danmark er ét af kun fem lande i EU, som holder fast

i, at 16-årige kan købe alkohol

•

En ensartet aldersgrænse vil gøre reglerne

simplere og nemmere at håndhæve.

Der er i dag

flere forskellige aldersgrænser, som skal håndteres

•

En 18-årsgrænse eliminerer de modsatrettede

alkohol-signaler, samfundet i dag sender til børn

og unge.

På den ene side har vi besluttet, at det er

ulovligt at udskænke en øl til en 16-årig på en café fra

en voksen. Omvendt tillader vi, at selvsamme 16-årige

kan gå i supermarkedet ved siden af og købe en kasse

øl eller alkoholsodavand på egen hånd.

30%

20%

10%

2004

Kilde: Statens Institut for Folkesundhed, 2006.

2005

1. WHO, 2020: Spotlight on adolescent health and well-being.

2. Sundhedsstyrelsen, 2020: Den Europæiske Rusmiddelundersøgelse (ESPAD) 2019.

3. Vidensråd for Forebyggelse, 2019: Unges alkoholkultur – et bidrag til debatten.

4. WHO, 2019: Status report on alcohol consumption, harm and policy responses in

30 European countries – 2019.

5. Statens Institut for Folkesundhed, 2006: Evaluering af forbuddet mod salg af

alkohol til personer under 16 år.

6. Schelleman-Offermans et. Al., 2017: Increased minimum legal age for the sale of

alcohol in the Netherlands as of 2014: The effect on alcohol sellers’ compliance

after one and two years.

7. Fx Epinion på vegne af Alkohol & Samfund, som viser, at 53 procent af danskerne

støtter en 18 års grænse: www.alkohologsamfund.dk/nyheder/befolkningen-

oensker-samlet-18-aars-alkoholgraense eller Epinion for Retail Institute

Scandinavia, som viser et flertal på 73 procent: www.berlingske.dk/politik/

danskere-vil-haeve-graensen-for-at-koebe-oel-fra-16-til-18-aar eller Megafon for

TV2, som viser et flertal på 63 procent: nyheder.tv2.dk/samfund/2019-08-05-

de-unge-drikker-alt-for-tidligt-mener-4-ud-af-5-danskere.

8. European Union Agency for Fundamental Rights, 2017.

9. En undersøgelse fra Alkohol & Samfund (Tak fordi du spørger, 2019) viser, at

personalet i Irma finder den dobbelte aldersgrænse svær at håndtere.

Tiden er moden til at påtage sig et større ansvar for børn og unges

alkoholforbrug. Indfør en 18-årssalgsaldersgrænse, der utvetydigt

fastslår, at alkohol ikke er for børn.

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALDERSGRÆNSER FOR SALG AF ALKOHOL

ØSTRIG

BELGIEN

DANMARK

TYSKLAND

LUXEMBOURG

SAN MARINO

SCHWEIZ

CYPERN

MALTA

ALBANIEN

ANDORRA

ARMENIEN

ASERBAJDSJAN

HVIDERUSLAND

BULGARIEN

KROATIEN

TJEKKIET

ESTLAND

FINLAND

FRANKRIG

GEORGIEN

GRÆKENLAND

UNGARN

IRLAND

ISRAEL

ITALIEN

KIRGISISTAN

LETLAND

LITAUEN

MONTENEGRO

HOLLAND

NORGE

POLEN

PORTUGAL

MOLDOVA

RUMÆNIEN

RUSLAND

SERBIEN

SLOVAKIET

SLOVENIEN

SPANIEN

SVERIGE

TADSJIKISTAN

JUGOSLAVIEN

TYRKIET

UKRAINE

STORBRITANNIEN

KAZAKHSTAN

MONACO

TURKMENISTAN

ISLAND

USBEKISTAN

BOSNIEN-HERCEGOVINA

ALDER

VIDENSRÅD FOR FOREBYGGELSE

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALKOHOLFORBRUGET DEN SIDSTE DAG MAN DRAK ALKOHOL

PROCENT

Elever i 9. klasse adspurgt om, hvor mange genstande de drak af hhv. øl, cider,

alkoholsodavand, vin og spiritus den sidste dag, hvor de drak alkohol.

ALLE

DRENGE

PIGER

ØL

›

23,5

›

35,0

›

CIDER

4,9

0,6

9,5

ALKOHOLSODAVAND

24,4

28,0

VIN

6,3

4,6

SPIRITUS

30,9

28,8

32,9

I ALT

00,0

KILDE: ESPAD

20 9

VIDENSRÅD FOR FOREBYGGELSE

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ESPAD Report

2019

Results from the European

School Survey Project on

Alcohol and Other Drugs

e ESPAD Group

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

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SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ESPAD Report

2019

Results from the European

School Survey Project on

Alcohol and Other Drugs

ESPAD Group

Sabrina Molinaro, Julian Vicente, Elisa Benedetti, Sonia Cerrai, Emanuela Colasante,

Sharon Arpa, Pavla Chomynová, Ludwig Kraus, Karin Monshouwer, Stanislas Spilka,

Ársæll Már Arnarsson, Olga Balakireva, Begoña Brime Beteta, Elin Kristin Bye, Anina

Chileva, Luke Clancy, Zamira Hyseni Duraku, Tatijana

Đurišić,

Ola Ekholm, Zsuzsanna

Elekes, Silvia Florescu, Biljana Kilibarda, Anna Kokkevi, Elsa Lavado, Tanja Urdih

Lazar, Martina Markelić, Alojz Nociar, Silvana Oncheva, Kirsimarja Raitasalo, Liudmila

Rupšienė, Janusz Sierosławski, Julian Strizek, Lela Sturua, Johan Svensson, Diāna

Vanaga, Kyriakos Veresies, Sigrid Vorobjov, Pál Weihe, Rodolfo Cotichini, Loredana

Fortunato and Kateřina

Škařupová

ESPAD Coordination

Sabrina Molinaro and Julian Vicente

Steering Committee

Sharon Arpa, Pavla Chomynová, Ludwig Kraus, Sabrina Molinaro, Karin Monshouwer, Stanislas Spilka and Julian Vicente

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

Legal notice

This

publication of the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) and the European School

Survey Project on Alcohol and Other Drugs (ESPAD) is protected by copyright.

The

EMCDDA and ESPAD accept no

responsibility or liability for any consequences arising from the use of the data contained in this document.

The

contents of

this publication do not necessarily reflect the official opinions of of the partners of the EMCDDA and ESPAD, any EU Member

State or any agency or institution of the European Union.

Luxembourg: Publications Office of the European Union, 2020

PDF

ISBN 978-92-9497-547-8

ISBN 978-92-9497-546-1

doi:10.2810/970957

doi:10.2810/877033

TD-03-20-531-EN-C

TD-03-20-531-EN-N

Reproduction is authorised provided the source is acknowledged.

For any use or reproduction of photos or other material that is not under the EMCDDA copyright, permission must be sought

directly from the copyright holders.

Photo credits: Envato Elements.

Recommended citation: ESPAD Group (2020),

ESPAD Report 2019: Results from the European School Survey Project on

Alcohol and Other Drugs,

EMCDDA Joint Publications, Publications Office of the European Union, Luxembourg.

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ON ELEMENTAL CHLORINE-FREE BLEACHED PAPER

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YEARS OF

MONITORING

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SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

Contents

Preface .............................................................................................................................. 7

List of authors .................................................................................................................. 9

Summary.........................................................................................................................12

Introduction ....................................................................................................................20

Background ...................................................................................................................................................... 21

The

2019 ESPAD report .............................................................................................................................. 23

Methodology ..................................................................................................................26

ESPAD 2019 .................................................................................................................................................... 26

Trend analysis.................................................................................................................................................. 33

Reporting........................................................................................................................................................... 34

e situation in 2019 ...................................................................................................36

Perceived availability of substances ...................................................................................................... 36

Early onset of substance use .................................................................................................................... 39

Cigarette use ................................................................................................................................................... 42

E-cigarette use ................................................................................................................................................ 44

Alcohol use ....................................................................................................................................................... 46

Illicit drug use .................................................................................................................................................. 48

Other substance use .................................................................................................................................... 51

Patterns of current use ................................................................................................................................ 56

Gambling and online gambling ................................................................................................................ 76

Social media use and gaming .................................................................................................................. 81

Trends 1995-2019........................................................................................................88

Trends across 30 countries ........................................................................................................................ 90

Country-specific trends ............................................................................................................................... 96

Discussion and conclusion ...................................................................................... 108

Cigarette and e-cigarette use................................................................................................................. 108

Alcohol use .................................................................................................................................................... 110

Cannabis use ................................................................................................................................................ 111

New psychoactive substance use ........................................................................................................ 112

Pharmaceutical use for non-medical purposes.............................................................................. 114

Gambling........................................................................................................................................................ 114

Social media use and gaming ............................................................................................................... 116

Limitations ..................................................................................................................................................... 117

Conclusion..................................................................................................................................................... 117

Acknowledgements ................................................................................................... 119

Collaborating persons ............................................................................................................................... 120

Funding agencies and supporting organisations........................................................................... 121

References................................................................................................................... 123

Scientific literature based on ESPAD data........................................................................................ 129

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

Tables

Table 1.

Table 2.

Table 3a.

Table 3b.

Overview of countries participating in ESPAD data collections 1995-2019

Sampling characteristics of ESPAD 2019

Perceived availability of substances: prevalence of students responding substance

‘fairly easy’ or ‘very easy’ to obtain (cigarettes, alcohol, cannabis and ecstasy) (percentage) 37

Perceived availability of substances: prevalence of students responding substance

‘fairly easy’ or ‘very easy’ to obtain (amphetamines, methamphetamines, cocaine

and crack) (percentage)

Early onset of substance use: prevalence of students experiencing substance use

(cigarettes, daily smoking, e-cigarettes, daily e-cigarettes, alcohol, intoxication) at the

age of 13 or younger (percentage)

Early onset of substance use: prevalence of students experiencing substance use

(cannabis, ecstasy, amphetamine/methamphetamine, cocaine/crack) at the age of 13

or younger (percentage)

Cigarette use: prevalence of lifetime and 30-day use (percentage)

E-cigarette use: prevalence of lifetime and 30-day use (percentage)

Alcohol use: prevalence of lifetime use, 30-day use and intoxication (percentage)

Illicit drug use: lifetime prevalence of the use of any drug, cannabis, ecstasy,

amphetamine and methamphetamine (percentage)

Illicit drug use: lifetime prevalence of the use of cocaine, crack, LSD or other

hallucinogens, heroin and GHB (percentage)

Inhalants, new psychoactive substances (NPS) and pharmaceuticals: prevalence

of lifetime use (percentage)

New psychoactive substances (NPS): lifetime prevalence of the use of synthetic

cannabinoids and synthetic cathinones (percentage)

Pharmaceuticals: lifetime prevalence of the use of painkillers to get high, tranquillisers

or sedatives without prescription and anabolic steroids (percentage)

Gambling for money and online gambling: prevalence in the last 12 months (percentage)

Proportions of different types of gamblers among those having gambled for money

in the past 12 months (percentage)

Estimation of excessive and problem gamblers among those having gambled in the

past 12 months by gender (percentage)

Average number of hours spent on social media in the last 7 days (modal class)

on a typical school day by gender (percentage)

Average number of hours spent on social media in the last 7 days (modal class)

on a typical non-school day by gender (percentage)

Average number of hours spent on gaming in the last 30 days (modal class)

on a typical school day by gender (percentage)

Average number of hours spent on gaming in the last 30 days (modal class)

on a typical non-school day by gender (percentage)

Self-perceived high risk of problems with social media use and gaming (percentage)

Overview of ESPAD surveys conducted between 1995 and 2019 by country contained

in the ESPAD trend database 1995-2019. Sample size.

Table 4a.

Table 4b.

Table 5.

Table 6.

Table 7.

Table 8a.

Table 8b.

Table 9.

Table 10a.

Table 10b.

Table 11a.

Table 11b.

Table 11c.

Table 12a.

Table 12b.

Table 12c.

Table 12d.

Table 12e.

Table 13.

Table 14.

ESPAD average for selected indicators based on 30 countries: 1995-2019 (percentage) 91

Figures

Figure 1a.

Figure 1b.

Figure 2a.

Figure 2b.

Figure 3a.

Figure 3b.

Daily cigarette use: prevalence in the last 30 days (percentage)

Daily cigarette use: prevalence in the last 30 days by gender (percentage)

E-cigarette use: prevalence in the last 30 days (percentage)

E-cigarette use: prevalence in the last 30 days by gender (percentage)

Frequency of alcohol intake in the last 30 days by gender (mean number of occasions

among users)

Frequency of alcohol intake in the last 30 days (mean number of occasions among users) 60

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

Figure 4a.

Figure 4b.

Figure 5.

Figure 6a.

Average alcohol intake on the last drinking day among users (centilitres of ethanol)

Average alcohol intake on the last drinking day among users by gender (centilitres of

ethanol)

Alcoholic beverage preferences on the last drinking day: contribution of each beverage

to the total amount of pure alcohol consumed (percentage)

Prevalence of heavy episodic drinking (five or more drinks on one occasion; one drink

contains approximately

2 centilitres of ethanol) at least once in the last 30 days (percentage)

Prevalence of heavy episodic drinking (five or more drinks on one occasion; one drink

contains approximately 2 centilitres of ethanol) at least once in the last 30 days by

gender (percentage)

Prevalence of cannabis use in the last 30 days (percentage)

Prevalence of cannabis use in the last 30 days by gender (percentage)

Frequency of cannabis use in the last 12 months (mean number of occasions among

users)

Figure 6b.

Figure 7a.

Figure 7b.

Figure 8a.

Figure 8b.

Figure 9a.

Figure 9b.

Figure 10a.

Figure 10b.

Figure 11.

Figure 12.

Figure 13.

Figure 14.

Figure 15.

Figure 16.

Figure 17.

Figure 18.

Figure 19.

Figure 20.

Figure 21.

Figure 22.

Figure 23.

Figure 24.

Figure 25.

Figure 26.

Figure 27.

Figure 28.

Figure 29.

Figure 30.

Figure 31.

Figure 32.

Figure 33.

Figure 34.

Frequency of cannabis use in the last 12 months by gender (mean number of occasions

among users)

Prevalence of high-risk cannabis users (percentage)

Prevalence of high-risk cannabis users by gender (percentage)

NPS use: prevalence in the last 12 months (percentage)

NPS use: prevalence in the last 12 months by gender (percentage)

Countries included in the 30-country average

Perceived availability of cannabis by gender: students responding cannabis ‘fairly easy’

or ‘very easy’ to obtain — 30-country trend 1995-2019 (percentage)

Daily cigarette use at the age of 13 or younger by gender: 30-country trend 1995-2019

(percentage)

Cannabis use at the age of 13 or younger by gender: 30-country trend 1995-2019

(percentage)

Lifetime use of cigarettes by gender: 30-country trend 1995-2019 (percentage)

Cigarette use in the last 30 days by gender: 30-country trend 1995-2019 (percentage)

Daily cigarette use by gender: 30-country trend 1995-2019 (percentage)

Lifetime alcohol use by gender: 30-country

trend 1995-2019 (percentage)

Alcohol use in the last 30 days by gender: 30-country trend 1995-2019 (percentage)

Heavy episodic drinking (five or more drinks on one occasion) during the last

30 days by gender: 30-country trend 1995-2019 (percentage)

Lifetime use of illicit drugs by gender: 30-country trend 1995-2019 (percentage)

Lifetime use of cannabis by gender: 30-country trend 1995-2019 (percentage)

Cannabis use in the last 30 days by gender: 30-country trend 1995-2019 (percentage)

Lifetime use of illicit drugs other than cannabis by gender: 30-country trend

1995-2019 (percentage)

Lifetime use of inhalants by gender: 30-country trend 1995-2019 (percentage)

Lifetime use of tranquillisers or sedatives without a doctor’s prescription by gender:

30-country trend 1995-2019 (percentage)

Lifetime use of cigarettes by country: 1995-2019 (percentage)

Daily use of cigarettes by country: 1995-2019 (percentage)

Lifetime use of alcohol by country: 1995-2019 (percentage)

Heavy episodic drinking (five or more drinks on one occasion) during the

last 30 days by country: 1995-2019 (percentage)

Lifetime use of cannabis by country: 1995-2019 (percentage)

Current use of cannabis by country: 1995-2019 (percentage)

Lifetime use of illicit drugs other than cannabis by country: 1995-2019 (percentage)

Lifetime use of tranquillisers or sedatives without a doctor’s prescription by country:

1995-2019 (percentage)

100

101

102

103

104

105

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

Preface

This

report presents the results of the seventh data-collection wave of the European School

Survey Project on Alcohol and Other Drugs (ESPAD).

The

data collection took place in 2019,

marking the 24th anniversary of ESPAD data collection (1995-2019). Each wave of the project

increases the value of the information presented, not only from a European perspective but

also for the participating countries.

This

report is based primarily on the information provided in 2019 by 99 647 students from 35

European countries, 25 of them being Member States of the European Union. Nearly 700 000

students have participated in the seven successive ESPAD data-collection waves, making the

project the most extensive harmonised data collection on substance use and risk behaviours

in Europe.

The

ESPAD database is available also to researchers outside the ESPAD network,

who may apply for access.

The

overall purpose of ESPAD is to offer a solid, reliable and comparable information

base that can help contribute towards formulating and increasingly, evaluating policies,

in particular those focused on adolescents.

This

group represents a key population for the

initiation of substance use and other behaviours; and policies and interventions addressing

these issues need quality information for their formulation, monitoring and evaluation.

ESPAD has been a successful project for 24 years, with a dynamic history, an increasing

value both at the national and European level, and a promising future.

The

project was

initiated and coordinated by the Swedish Council for Information on Alcohol and Other Drugs

(CAN), following initial work carried out by the Pompidou Group of the Council of Europe.

The

EMCDDA has progressively increased its support to the project, and since 2013, at the

request of Sweden, the EU Member States and the European Commission, has been involved

in the coordination of ESPAD, facilitating the transition and development of the project.

Since 2016, with the election of the new ESPAD Coordinator, the National Research Council

of Italy has actively contributed to the coordination work and drafting the report.

The

EMCDDA

has continued to support the project in a number of ways, including through coordination

activities, the provision of essential resources for some national participants, and by the

production of this report.

The

2019 wave can be considered an encouraging success and is largely the result of an

extensive and positive collaboration.

The

results provided here include valuable contributions

from many, including the national experts (principal investigators), their teams and the

national institutions that supported and funded the data collection.

The

report would have

not been possible without the participation of the many European schools, teachers, research

assistants and, notably, students, who volunteered to give their time and information to

ESPAD, so that we could obtain a better understanding of European students’ substance use,

their attitudes towards it, and some of the factors that explain the use.

Alexis Goosdeel

EMCDDA Director

Sabrina Molinaro

ESPAD Coordinator

ESPAD Report 2019

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SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

List of authors

Sabrina Molinaro

Julian Vicente

Elisa Benedetti

Sonia Cerrai

Emanuela Colasante

Sharon Arpa

National Research Council, Institute of Clinical Physiology

(CNR-IFC), Pisa, Italy

European Monitoring Centre for Drugs and Drug Addiction

(EMCDDA), Lisbon, Portugal

National Research Council, Institute of Clinical Physiology

(CNR-IFC), Pisa, Italy

National Research Council, Institute of Clinical Physiology

(CNR-IFC), Pisa, Italy

National Research Council, Institute of Clinical Physiology

(CNR-IFC), Pisa, Italy

Aġenzija Sedqa (National Agency against Drug and Alcohol Abuse

and Compulsive Gambling), Foundation for Social Welfare Services,

Santa Venera, Malta

Czech National Monitoring Centre for Drugs and Addictions, Office

of the Government of the Czech Republic (NMC); National Institute

of Mental Health (NIMH), Prague, Czechia

IFT Institut für

Therapieforschung,

Munich, Germany

Trimbos Institute, Utrecht, the Netherlands

French Monitoring Centre for Drugs and Drug Addiction (OFDT),

Paris, France

University of Iceland, Akureyri, Iceland

Department for Monitoring Research on Socio-economic

Transformations, Institute for Economics and Forecasting, National

Academy of Sciences of Ukraine (IEF NASU), Kiev, Ukraine

Spanish Observatory on Drugs and Addictions, Government

Delegation for the National Plan on Drugs, Ministry of Health,

Consumer Affairs and Social Welfare, Madrid, Spain

Norwegian Institute of Public Health (NIPH), Oslo, Norway

National Center of Public Health and Analyses, Sofia, Bulgaria

TobaccoFree Research Institute Ireland, Focas Research Institute,

Technological University Dublin, Ireland

Faculty of Philosophy and Department of Psychology, University of

Prishtina ‘Hasan Prishtina’, Prishtina, Kosovo

Public Health Institute of Montenegro, Podgorica, Montenegro

National Institute of Public Health, University of Southern Denmark,

Copenhagen, Denmark

Institute of Sociology and Social Policy, Corvinus University of

Budapest, Budapest, Hungary

National School of Public Health, Management and Professional

Development, Bucharest, Romania

Institute of Public Health of Serbia (IPHS), Belgrade, Serbia

Athens University Mental Health, Neurosciences and Precision

Medicine Research Institute (UMHRI), Athens, Greece

General-Directorate for Intervention on Addictive Behaviours and

Dependencies (SICAD-Ministry of Health), Lisbon, Portugal

Pavla Chomynová

Ludwig Kraus

Karin Monshouwer

Stanislas Spilka

Ársæll Már Arnarsson

Olga Balakireva

Begoña Brime Beteta

Elin Kristin Bye

Anina Chileva

Luke Clancy

Zamira Hyseni Duraku

Tatijana

Đurišić

Ola Ekholm

Zsuzsanna Elekes

Silvia Florescu

Biljana Kilibarda

Anna Kokkevi

Elsa Lavado

ESPAD Report 2019

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Tanja Urdih Lazar

Martina Markelić

Alojz Nociar

Silvana Oncheva

Kirsimarja Raitasalo

Liudmila Rupšienė

Janusz Sierosławski

Julian Strizek

Lela Sturua

Johan Svensson

Diāna Vanaga

Kyriakos Veresies

Sigrid Vorobjov

Pál Weihe

Rodolfo Cotichini

Loredana Fortunato

Kateřina

Škařupová

Clinical Institute of Occupational, Traffic and Sports Medicine,

University Medical Centre Ljubljana, Ljubljana, Slovenia

Croatian Institute of Public Health (CIPH), Zagreb, Croatia

St Elizabeth College of Health and Social Work, Bratislava, Slovakia

Institute of Public Health, Skopje, North Macedonia

Finnish Institute for Health and Welfare, Helsinki, Finland

Klaipėda University, Klaipėda, Lithuania

Institute of Psychiatry and Neurology (IPiN), Warsaw, Poland

Gesundheit Österreich GmbH, Vienna, Austria

National Center for Disease Control and Public Health, Tiblisi,

Georgia

Swedish Council for Information on Alcohol and Other Drugs (CAN),

Stockholm, Sweden

Centre for Disease Prevention and Control, Riga, Latvia

Center for Education about Drugs and Treatment of Drug Addicted

Persons, Nicosia, Cyprus

National Institute for Health Development, Tallinn, Estonia

Department of Occupational Medicine and Public Health, Tórshavn,

Faroe Islands

National Research Council, Institute of Clinical Physiology

(CNR-IFC), Pisa, Italy

National Research Council, Institute of Clinical Physiology

(CNR-IFC), Pisa, Italy

European Monitoring Centre for Drugs and Drug Addiction

(EMCDDA), Lisbon, Portugal

ESPAD Report 2019

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Summary

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

Summary

The

main purpose of the European School Survey Project on

Alcohol and Other Drugs (ESPAD) is to collect comparable

data on substance use and other forms of risk behaviour

among 15- to 16-year-old students in order to monitor trends

within, as well as between, countries. Between 1995 and

2019, seven waves of data collection were conducted across

49 European countries.

This

report presents selected key results.

The

full set of data

on which the current report is based, including all of the

standard tables, is available online (http://www.espad.org).

All tables can be downloaded in Excel format and used for

further analysis.

The

report provides information on the perceived availability

of substances, early onset of substance use and prevalence

estimates of substance use (cigarettes, alcohol, illicit

drugs, inhalants, new psychoactive substances and

pharmaceuticals).

The

descriptive information includes

indicators of intensive and high-risk substance use,

prevalence estimates of gambling for money, including

online gambling, estimates of the proportion of students

who gamble and display excessive or problem gambling

behaviour, and prevalence estimates of social media use

and gaming, as well as of self-perceived problem use, by

both country and gender. In addition, overall ESPAD trends

between 1995 and 2019 are presented. For selected

indicators, ESPAD trends are shown based on data from

30 countries that participated in at least four (including the

2019 data collection) of the seven surveys. Finally, for some

indicators, country-specific trends are shown.

For the 2019 ESPAD data collection, 99 647 students took

part from 35 countries: Austria, Bulgaria, Croatia, Cyprus,

Czechia, Denmark, Estonia, the Faroes, Finland, France,

Georgia, Germany, Greece, Hungary, Iceland, Ireland, Italy,

Kosovo (

), Latvia, Lithuania, Malta, Monaco, Montenegro, the

Netherlands, North Macedonia, Norway, Poland, Portugal,

Romania, Serbia, Slovakia, Slovenia, Spain, Sweden and

Ukraine. For comparative reasons, the tables in this report

contain, in addition to country-specific estimates, averages

based on all 35 unweighted country-level estimates.

and who are present in the classroom on the day of the

survey. Students who were enrolled in regular, vocational,

general or academic studies were included; those who

were enrolled in either special schools or special classes for

students with learning disorders or severe disabilities were

excluded.

A homogeneous and standardised sampling design was

used to select the target population in all participating

countries except the Faroes, Iceland, Malta, Monaco and

Montenegro, where all target students born in 2003 were

included.

Data were collected by self-administered questionnaires.

All countries used a paper-and-pencil questionnaire except

for Austria, Denmark, France, Iceland, the Netherlands

and Norway, where students answered a web-based

questionnaire, and the Faroes and Italy, where a mixed

administration mode (paper and pencil and web-based)

was used.

The

students answered the questionnaires

anonymously in the classroom. All samples had national

geographical coverage, except for those from Cyprus (only

government-controlled areas were included), Kosovo (less

than 4 % of the target population enrolled in schools in

Northern Kosovo under the parallel structures and working

within the plans of the Ministry of Education of Serbia were

excluded), Georgia (the occupied territories of Abkhazia and

South Ossetia were excluded) and Germany (only the federal

state of Bavaria was included). Sample sizes varied between

428 in Monaco and 5 988 in Greece.

Cigarette use

Cigarettes are one of the most easily accessible substances,

with about 60 % of the students in the participating countries

reporting that it would be ‘fairly easy’ or ‘very easy’ (hereafter

referred to as ‘easy’) for them to get hold of cigarettes if they

wanted to. Students in Denmark were most likely to

find

them easy to obtain (79 %). In Sweden, Poland, Slovakia and

Czechia, the perceived availability was also comparatively

high, with over 70 % of the students reporting access to be

easy. Perceived availability was lowest in Kosovo (24 %),

and

figures

of less than 50 % were observed in

five

other

countries: Romania (39 %), Ukraine (42 %), Georgia (45 %),

Iceland (47 %) and North Macedonia (49 %). Gender

differences for perceived availability were small at the

aggregate level (61 % for boys versus 59 % for girls).

More than one in six ESPAD students (18 %) had smoked

cigarettes at age 13 or younger.

The

proportions varied

Methodology

The

ESPAD target population is defined as students who

reach the age of 16 years in the calendar year of the survey

(

)

This designation is without prejudice to positions on status, and is in line

with UNSCR 1244/1999 and the ICJ Opinion on the Kosovo declaration of

independence.

ESPAD Report 2019

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considerably across countries, from 5.4-8.5 % in Iceland,

Malta and Norway to 31-33 % in Latvia and Lithuania. Both

on average and in almost all participating countries, more

boys than girls had smoked cigarettes at age 13 or younger.

On average, 2.9 % of the students began smoking cigarettes

on a daily basis at age 13 or younger.

The

rates were highest

in Slovakia (6.0 %) and Bulgaria (5.8 %) and lowest in

the Netherlands (0.9 %), followed by Iceland, Greece and

Slovenia (1.2-1.4 %).

In ESPAD countries 41 % of students had smoked cigarettes

at least once in their lifetime, and one

fifth

of the sample

(20 %) could be considered to be current smokers, i.e. had

smoked cigarettes during the last 30 days.

The

average

lifetime prevalence of cigarette smoking was about the

same among boys (43 %) and girls (40 %). Furthermore, on

average, 10 % of students reported that they had smoked

daily in the last 30 days.

The

rates of daily cigarette smoking

ranged from 1.9 % in Iceland and Norway to 22 % in Bulgaria.

No differences were found in the average rates of daily

smoking between boys and girls.

Trend data indicate an overall constant decrease since 1995

in lifetime, last-30-day and daily cigarette use. However,

if the 2019 cigarette and electronic cigarette (e-cigarette)

use is analysed as a combined value (ESPAD 2019 is the

first

data collection in which information about e-cigarettes

is available for all countries), the prevalence is higher than

in 2015 (when the item for nicotine consumption did not

distinguish between the use of traditional cigarettes and

the use of e-cigarettes). In fact, considering them together,

for the

first

time we seem to observe a trend reversal for

cigarette consumption, with consumption starting to grow

again, reaching 54 % for lifetime use, 27 % for current use

and 12 % for daily use.

Lifetime prevalence rates for the use of e-cigarettes ranged

between 18 % in Serbia and 65 % in Lithuania, with an

ESPAD average of 40 %. In nine of the 35 ESPAD countries

more than half of the students had tried e-cigarettes at least

once. Boys were generally more likely than girls to have tried

e-cigarettes (boys 46 % versus girls 34 %). On average, one

in seven students (14 %) reported having used e-cigarettes

during the last 30 days, with the highest rate found in

Monaco (41 %) and the lowest in Serbia (5.4 %). Concerning

gender differences, the average rate for boys (16 %) was

higher than that for girls (11 %). With regard to the frequency

of use in the last 30 days, overall, 10 % of students reported

e-cigarette use less than once per week, 4.1 % reported use

at least once a week and 3.1 % reported use almost every

day or every day, with the highest rate of daily or almost daily

use reported in Lithuania (14 %).

Alcohol use

Alcoholic beverages are perceived to be easy to obtain

compared with other substances, with almost 80 % of

ESPAD students stating that they would

find

it easy to get to

hold of an alcoholic beverage if they wanted to. In Denmark,

Germany and Greece, this percentage rises to more than

90 %.

The

lowest proportions were found in Kosovo (38 %),

which was also the only country where the proportion was

less than 50 %, followed by Lithuania (61 %), Iceland (62 %)

and Romania (63 %). Overall, alcohol was perceived to be

easily available by slightly more girls than boys (79 % for girls

versus 77 % for boys), although in most countries the rates

among boys and girls were rather similar.

Over one third of the students who participated in the

ESPAD study (33 %) had

first

tried an alcoholic drink at age

13 or younger.

The

highest proportions of students reporting

alcohol use at an early age were found in Georgia (60 %) and

Latvia (48 %).

The

countries with the lowest rates of early

alcohol use were Iceland (7.1 %), Kosovo (12 %) and Norway

(13 %). In almost all ESPAD countries, boys were more likely

than girls to have

first

tried alcohol at an early age.

On average, 6.7 % of students had experienced alcohol

intoxication at age 13 or younger.

This

proportion varied

substantially across countries, from 1.8 % in Iceland to 25 %

in Georgia. Higher rates were more likely to be found in the

eastern part of Europe and, in general, more boys than girls

reported intoxication at an early age (ESPAD average: 8.0 %

for boys versus 5.4 % for girls).

In all ESPAD countries except Kosovo (29 %) and Iceland

(37 %), over half of the students reported having consumed

alcohol at least once during their lifetime.

The

ESPAD

average was 79 % (range 29-95 %).

The

highest rates of

lifetime alcohol use (more than 90 %) were found in Hungary,

Electronic cigarette use

More than one in 10 ESPAD students (11 %) had tried

e-cigarettes at age 13 or younger, with

figures

varying across

countries, from 4.3 % in Montenegro and 4.4 % in Serbia

to 19 % in Lithuania and 20 % in Estonia. Boys were more

likely than girls to have used e-cigarettes early in life in the

vast majority of countries. On average, 1.7 % of students

had begun using e-cigarettes on a daily basis at age 13 or

younger.

The

highest rates were found in Kosovo (3.2 %),

Cyprus (3.1 %), Slovakia and Ukraine (2.8 % each), Lithuania

(2.7 %) and Bulgaria (2.5 %). In all ESPAD countries the

rate of early onset of daily e-cigarette use was higher for

boys than girls; however, because of the small proportion of

students reporting onset of daily e-cigarette use at an early

age, gender differences were generally small.

ESPAD Report 2019

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Denmark and Czechia. In addition to Kosovo and Iceland,

Norway and Sweden had relatively low rates of lifetime

alcohol use (less than 60 %). Overall, more than one in 10

students (13 %) reported having been intoxicated in the last

30 days.

Students who reported alcohol use in the last 30 days drank

alcohol on 5.6 occasions on average. Among this group,

students from Germany and Cyprus consumed alcohol

on 8.0 and 7.5 occasions, respectively, and students from

Sweden, Finland, Lithuania, Iceland, Estonia, Latvia and

Norway drank alcohol on fewer than four occasions on

average. In most countries, boys who drank in the last month

did so more frequently than girls, with a difference of more

than three occasions in Germany, Serbia and Montenegro.

One in three students (34 %) reported heavy episodic

drinking (five or more glasses of alcoholic beverages on

one occasion at least once in the past month).

This

drinking

pattern was found more often in Denmark, Germany and

Austria, where it was reported by between 49 % and 59 % of

students.

The

lowest

figures

were found in Iceland (7.6 %),

followed by Kosovo (14 %) and Norway (16 %).

The

difference

between boys and girls was about 3 percentage points on

average, with generally higher

figures

for boys. Students

had drunk an average of 4.6 centilitres of alcohol on the

last drinking day.

The

amount of alcohol consumed was

highest in Denmark (8.8 centilitres), followed by Norway

(6.7 centilitres) and the Netherlands (6.6 centilitres),

and was lowest in Kosovo (2.5 centilitres) and Romania

(3.0 centilitres). Boys reported consuming higher volumes

than girls in the majority of countries. On average, spirits

(38 %) and beer (31 %) were the preferred alcoholic

beverages. In Spain (83 %), Portugal (59 %), Lithuania

(57 %), Sweden (52 %) and Malta (51 %), more than half

of the students who drank alcohol preferred spirits, while

a similar preference was found for beer in Kosovo (62 %),

Serbia (52 %), Poland and North Macedonia (49 % each).

Wine was preferred over spirits and beer in Ukraine (26 %),

over spirits but not over beer in Georgia (36 %), and over

beer but not over spirits in Slovakia (27 %). Premixed drinks

accounted for about one quarter of the alcohol consumed

in Germany (26 %), Finland and Denmark (each 23 %). In

the Faroes, Ireland, Norway and Sweden, cider accounted

for at least one quarter of the alcohol consumed. In these

countries, cider was the second most preferred alcoholic

beverage after spirits.

Despite alcohol consumption remaining very popular,

temporal trends between 1995 and 2019 indicate a slow but

steady general decrease in both lifetime and last-30-day use

of alcohol. A positive development can be observed in the

temporal trend of heavy episodic drinking, with the ESPAD

average peaking in 2007 and then starting to decrease,

reaching its lowest level in 2019. Comparing the 2019 rate

with the 1995 rate, an overall increase in heavy episodic

drinking can be noted among girls (from 30 % to 34 %) and

a decrease among boys (from 41 % to 36 %), resulting in

a narrowing of the gender difference over time.

Illicit drug use

Cannabis is perceived to be the easiest illicit substance to

get hold of, with around one third of ESPAD students (32 %)

rating cannabis as easily obtainable. More students in the

Netherlands, Denmark, Czechia, Slovenia and Slovakia than

in the other ESPAD countries perceived cannabis to be easily

available (rates from 45 % to 51 %).

The

countries with the

lowest perceived availability of cannabis were Kosovo (11 %),

Ukraine (13 %), Romania (16 %) and North Macedonia

(19 %). Boys were more likely than girls to consider cannabis

to be easily available (ESPAD average: 34 % for boys versus

30 % for girls).

Compared with cannabis, perceived availability was low

for ecstasy (MDMA) (14 %), cocaine (13 %), amphetamine

(10 %) and methamphetamine (8.5 %).

These

drugs were

perceived to be more easily available in Bulgaria, Sweden

and Denmark than elsewhere in Europe.

The

perceived availability of ecstasy was highest (over 20 %)

in Slovakia, Czechia, Slovenia and the Netherlands, whereas

for cocaine it was highest in Denmark and Ireland (22 %

each).

The

countries with the lowest perceived availability of

nearly all illicit drugs were Kosovo, Georgia and Romania.

On average, 2.4 % of the ESPAD students reported having

used cannabis for the

first

time at age 13 or younger.

The

highest proportions were found in France (4.5 %), Italy

(4.4 %), Latvia (3.8 %), Cyprus (3.6 %) and Estonia (3.5 %).

Rates of early onset of amphetamine/methamphetamine

use were lower (ESPAD average: 0.5 %), with the highest

proportion in Bulgaria (1.8 %). Boys were more likely

than girls to have used cannabis or amphetamine/

methamphetamine at age 13 or younger. Similar results were

found for early onset of ecstasy and cocaine use.

The

average prevalence of lifetime use of illicit drugs was

17 %, with considerable variation across ESPAD countries.

It should be noted that this mainly relates to cannabis

use (average lifetime prevalence of 16 %).

The

highest

proportions of students reporting lifetime use of any illicit

drug were found in Czechia (29 %), Italy (28 %), Latvia (27 %)

and Slovakia (25 %). Particularly low levels (10 % or less) of

lifetime illicit drug use were noted in Kosovo, Iceland, North

Macedonia, Ukraine, Serbia, Sweden, Norway, Greece and

Romania.

In most ESPAD countries, the prevalence rates were higher

among boys than among girls. On average, 19 % of boys

ESPAD Report 2019

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and 14 % of girls had used illicit drugs at least once during

their lifetime. Noticeable gender differences were found in

Georgia (24 % for boys versus 8.8 % for girls), Monaco (29 %

versus 17 %), Cyprus (17 % versus 7.0 %) and Ireland (25 %

versus 15 %).

Considering the ESPAD average, the lifetime prevalence

of illicit drug use increased from 1995 to 2011 and has

declined since then.

Cannabis was the most widely used illicit drug in all ESPAD

countries. On average, 16 % of students had used cannabis

at least once in their lifetime.

The

countries with the highest

prevalence of cannabis use were Czechia (28 %), Italy (27 %)

and Latvia (26 %).

The

lowest levels of cannabis use (2.9-

7.3 %) were reported in Kosovo, North Macedonia, Iceland

and Serbia. On average, boys reported cannabis use to

a larger extent than girls (18 % versus 13 %).

This

was the

case in all countries except Bulgaria, Slovakia, Malta, the

Netherlands and Czechia.

Among all students who had used cannabis in the last 12

months (13 % of the total), the drug was used on average on

about 10 occasions (9.9). In France, Italy, Serbia, Austria and

Cyprus, cannabis was used once a month on average (12 or

more occasions).

The

lowest average frequency of cannabis

use was found in the Faroes (4.4 occasions). Overall, boys

reported a higher frequency of cannabis use than girls.

Overall, 7.1 % of the students had used cannabis in the

last 30 days. A high variability was found among ESPAD

countries, with the maximum rate observed in Italy (15 %)

and the minimum in Kosovo (1.4 %). More boys than girls

reported cannabis use in the last 30 days (boys 8.5 %

versus girls 5.8 % on average), with statistically significant

gender differences found in more than two thirds of ESPAD

countries.

To estimate the risk of cannabis-related problems, a core

module, the CAST (Cannabis Abuse Screening Test) scale,

was included in the ESPAD questionnaire.

The

prevalence

of high-risk cannabis users (see the methodology section

for a definition) ranged from 1.4 % to 7.3 % across countries,

with an average of 4.0 %. Overall, the prevalence of high-risk

cannabis users was higher among boys than girls (4.7 %

versus 3.3 %). At the country level, statistically significant

gender differences with higher rates among boys were found

in 16 ESPAD countries.

Trends in cannabis use indicate a general increase in both

lifetime and last-30-day use between 1995 and 2019, from

11 % to 16 % and from 4.1 % to 7.4 %, respectively. Both

prevalence rates reached their highest levels in 2011, with

lifetime use slightly decreasing thereafter and current use

levelling off.

On average, 1-2 % of the ESPAD students had ever used an

illicit drug other than cannabis at least once. After cannabis,

the most widely used illicit drugs were ecstasy (MDMA),

LSD (lysergic acid diethylamide) or other hallucinogens,

cocaine and amphetamine. Lifetime prevalence rates

for methamphetamine, crack, heroin and GHB (gamma-

hydroxybutyrate) were lower than those for the other illicit

drugs (about 1.0 % on average). At the country level, higher

rates of lifetime use were found in Estonia and Latvia

(lifetime use of ecstasy, LSD or other hallucinogens of about

5.0 %).

Other substance use

On average, the lifetime prevalence of use of new

psychoactive substances (NPS) was 3.4 %, with the

highest rates observed in Estonia (6.6 %) and Latvia (6.4 %)

and the lowest rates observed in Finland, Portugal and

North Macedonia (about 1 %).

The

average prevalence of

lifetime use was the same for boys and girls, and gender

differences within ESPAD countries were generally small.

With regard to specific substances, 3.1 % of the ESPAD

students (average calculated across 20 out of 35 countries)

reported having used synthetic cannabinoids at least once

in their lifetime, ranging from 1.1 % in Slovakia to 5.2 % in

France. Similarly, 1.1 % of students reported lifetime use of

synthetic cathinones (average calculated across 19 out of 35

countries), with the highest

figures

found in Ireland (2.5 %)

and Cyprus (2.4 %). On average, boys had a slightly higher

prevalence of use than girls of both types of substance.

Lifetime use of inhalants was reported by 7.2 % of the

students, with large differences between countries.

The

countries with the highest proportions of students who had

tried inhalants were Latvia (16 %), Germany and Croatia

(15 % each).

The

lowest rate was found in Kosovo (0.5 %).

No gender differences were observed.

The

trend in the

use of inhalants shows a steady increase until 2011, with

a decrease observed thereafter.

The

gender-specific curves

from 1995 to 2019 reveal a progressive narrowing of the

gender gap, which has disappeared since 2011.

There

was a wide variation between countries in the

prevalence of lifetime use of pharmaceuticals for non-

medical purposes (which include tranquillisers and sedatives

without a prescription, painkillers taken to get high and

anabolic steroids), ranging from 2.8 % to 23 %.

The

average

rate was 9.2 % and the rates were highest in Slovakia (23 %),

Latvia (22 %) and Lithuania (21 %).

The

lowest levels of non-

prescription use of tranquillisers or sedatives (approximately

2.0 %) were reported by students from Ukraine, Romania,

Bulgaria and Croatia. With regard to the use of painkillers

in order to get high, the ESPAD countries with the highest

prevalence rates were Slovakia (18 %) and Czechia (10 %).

ESPAD Report 2019

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Both on average and in the vast majority of the ESPAD

countries, girls were more likely than boys to have tried

pharmaceuticals for non-medical purposes. Few students in

the participating countries reported use of anabolic steroids

(ESPAD average: 1.0 %).

The

highest proportions were found

in Montenegro (2.7 %), followed by Cyprus, Bulgaria, Malta,

Poland and Ireland (about 2.0 % each).

a definition) among those who had gambled in the last 12

months was 5.0 %, which corresponds to a prevalence of

1.4 % among the total ESPAD sample.

The

highest proportion of students who had gambled in the

last year and met the criteria for problem gambling behaviour

was reported in Georgia (12 %), whereas the lowest

proportion was found in the Netherlands (1.3 %). In about

one third of the ESPAD countries the proportion of students

who had engaged in problem gambling among those who

had gambled in the last 12 months was higher than 5.0 %.

In almost all countries, the proportion of students who had

gambled in the last 12 months and who were liable to have

a problem gambling behaviour was higher among boys than

girls (6.3 % for boys versus 2.4 % for girls on average).

Gambling and online gambling

On average, 22 % of students reported gambling for money

(gambling money on games of chance) on at least one type

of game in the last 12 months. Among students who had

gambled in the last 12 months, the predominant gambling

activities were lotteries, reported by nearly half of gamblers,

followed by sports or animal race betting (45 %) and cards

or dice (44 %).

The

least popular gambling activity was slot

machines (reported by 21 % of gamblers).

The

highest rates of students with gambling experience in

the last 12 months were found in Greece and Cyprus (33 %),

followed by Italy and Montenegro (32 %) and Finland (30 %).

Gambling for money was not as common in Malta (14 %),

Georgia (13 %), Denmark (12 %) and Kosovo (11 %). In all

countries, considerably more boys than girls reported having

gambled in the last 12 months (29 % for boys versus 15 %

for girls on average).

Almost 7.9 % of students reported having gambled for

money on the internet in the last 12 months.

The

highest

rates of students reporting gambling online were found in

Cyprus (17 %) and Kosovo (16 %).

The

lowest rates (below

5 %) were found in Germany, Malta, Norway, Iceland, Spain

and Austria. In all countries, considerably more boys than

girls had gambled online in the last 12 months (13 % for

boys versus 2.7 % for girls).

The

estimated proportion of students who had engaged in

excessive gambling activity (see the methodology section

for a definition) among those who had gambled in the last

12 months was 15 %, which corresponds to a prevalence of

3.8 % among the total ESPAD sample.

The

highest proportion of students who had engaged in

excessive gambling activity was found in Montenegro (35 %),

whereas the lowest proportions (less than 10 %) were found

in the Netherlands, Iceland, Greece and Malta. Overall,

a higher proportion of boys than girls who had gambled in

the last 12 months had engaged in excessive gambling (see

the methodology section for a definition) (19 % for boys

versus 5.9 % for girls).

The

estimated proportion of students who had engaged

in problem gambling (see the methodology section for

Social media and gaming

About 94 % of the ESPAD students reported use of social

media (e.g. WhatsApp, Twitter, Facebook, Skype, Blogs,

Snapchat, Instagram, Kik) in the last 7 days. On average,

users spent 2-3 hours on social media on a typical school

day and about 6 or more hours on a typical non-school

day. Fewer online hours on a non-school day were reported

in Austria, Czechia, Iceland, Slovenia, Denmark, Kosovo,

Georgia, Bulgaria, Cyprus, North Macedonia and Slovakia. In

total, 10 % or more of the students reported no use of social

media on any day in Kosovo, Georgia and Bulgaria. In most of

the countries girls reported using social media on non-school

days more frequently than boys.

About 60 % of the ESPAD students reported having played

digital games on a typical school day within the last 30 days,

with 69 % reporting playing digital games on a non-school

day within the last 30 days.

The

exceptions were Bulgaria

and Sweden, where almost 70 % and almost 80 % of

students reported having played games on school days and

non-school days, respectively. In the majority of countries,

the most commonly reported amount of time spent on

gaming on a typical school day was half an hour or less,

while the most commonly reported amount of time spent on

gaming on a typical non-school day was 2-3 hours.

Overall, boys reported more frequent use of digital games

than girls, on both school days and non-school days, with

boys spending twice as much time gaming than girls in most

countries.

With regard to potentially risky levels of social media use and

gaming, almost half of the students (46 %) scored 2-3 points

on the self-perceived risk scale for social media use (see

the methodology section for a description of this measure),

suggesting a higher risk of problems related to social media

use; this ranged from 31-32 % in Denmark, Poland and

ESPAD Report 2019

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Iceland to 63 % in Montenegro. On the other hand, 21 % of

students scored 2-3 points on the self-perceived risk scale

for gaming (see the methodology section for a description of

this measure), suggesting a higher risk of problems related

to gaming; this ranged from 12 % in Denmark to 44 % in

Georgia.

Acknowledgments

The

ESPAD Group, in collaboration with the European

Monitoring Centre for Drugs and Drug Addiction

(EMCDDA), would like to acknowledge the contributions

made to this report. In particular, we are grateful to the

national authorities that funded the national ESPAD

studies; the European Commission for supporting the

participation of 10 countries in the study; and the Italian

National Research Council (CNR), which, in partnership

with the EMCDDA, guaranteed

financial

and scientific

support for the report’s coordination, data management

and analytical activities. Finally, we express our immense

gratitude to the schools, teachers and students without

whose participation this report would not have been

possible (a full list of acknowledgements can be found on

page 119).

ESPAD Report 2019

Introduction

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Introduction

The

European School Survey Project on Alcohol and Other

Drugs (ESPAD) is a cross-sectional study of substance

use and other forms of risk behaviour among students in

Europe aged 15-16 years that is carried out every 4 years.

ESPAD is an independent research project owned by the

national institutions and the researchers involved. It was

first

conducted in 1995, with the number of participating

countries increasing progressively to 35 until 2007 and

remaining stable since then.

Adolescent substance use and other forms of risk behaviour

have proved to be a rapidly changing phenomenon, requiring

close monitoring and frequent assessment. Against this

background, ESPAD is committed to providing the best

available evidence to support the development of informed

policies and actions targeting adolescents to meet the

challenges that lie ahead. In fact, the protection of young

people’s health and well-being and a reduction in the

negative impacts of the use of psychoactive substances

remain major policy objectives, at both national and

international levels. In recent years, these priorities have

been a focus for the World Health Organization (WHO)

global strategy to reduce the harmful use of alcohol and the

European action plan to reduce the harmful use of alcohol

2012-2020, the WHO Framework Convention on Tobacco

Control (FCTC) and the EU Tobacco Products Directive, the

United Nations special session on the world drug problem in

2016 and the EU drugs strategy (2013-20).

The

main purpose of ESPAD is to collect comparable data

on substance use and some forms of risk behaviour (such

as gambling and gaming) from 15- to 16-year-old students

in as many European countries as possible.

The

target group

consists of students who reach the age of 16 years during

the year of data collection, which for the 2019 data collection

meant students born in 2003.

The

survey is conducted in

schools in participating countries over the same period and

using a standard methodology, which is described in the

methodology section of this report and detailed further in the

ESPAD 2019 methodology report.

To keep up with the emergence of new risk behaviours

among young people throughout Europe, the ESPAD

questionnaire is constantly adapted to include new topics,

while maintaining a set of core questions to track key long-

term trends.

Since 2015 new sections have been added to cover social

media use as well as gaming and gambling. Furthermore,

following the emergence of non-controlled drugs on the

European drugs market, the questionnaire has included

specific questions investigating the use of new psychoactive

substances (NPS). Given the global rise in the use of

electronic nicotine delivery systems, the 2019 ESPAD

questionnaire included a new section on e-cigarette

smoking. Lastly, screening instruments were included to

assess the more risky patterns of cannabis use, gambling

and use of social media, based on the recognition that

students who engage in these behaviours have different

levels of risk.

The

2019 ESPAD survey involved 99 647

students in 35 countries.

The first

results based on the 2019

survey, including the new topics, are presented in this report.

The

ESPAD data have been and will be used by the

research community for in-depth analyses to deepen the

understanding of adolescent risk behaviours. Because

of the common methodology employed by participating

countries, analyses based on ESPAD data have contributed

substantially to the

field

of substance use and addictive

behaviours. For instance, studies have been conducted on

survey-specific methodological issues, the evaluation of

substance use, the relationship between socioeconomic

factors and patterns of use, risk, resilience and mediating

factors, risk perceptions, polysubstance use and doping,

gambling and gaming (see ‘Scientific literature based on

ESPAD data’, page 129, for a full list of publications). In

addition, ESPAD results have been used for the development

of national and international action plans and strategies

related to tobacco, alcohol and other drugs, as well as

gambling, and in this way have had an impact on public

discussions and served as a basis for policy measures and

preventive activities targeting young people.

The

strength of the ESPAD project lies not only in its

ability to provide a comprehensive picture and deepen

the understanding of adolescent substance use, risk

behaviours and related risk and protective factors, but also

in allowing comparisons across countries and over time. In

fact, although the comparison of cross-sectional data on

substance use across similar populations in countries of

various social, economic and cultural origins is important,

the ability to investigate temporal changes across the

majority of European countries is quite unique.

The

ESPAD

project provides data that can be used to monitor trends in

substance use and other risk behaviours within and between

European countries.

The

data gathered from the surveys carried out from 1995

to the present by the ESPAD community have recently been

merged to create an inclusive trend database. To increase

the use of this exceptional collection of information, this

valuable tool has been made accessible to the scientific

ESPAD Report 2019

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Introduction

community, with both ESPAD and non-ESPAD researchers

able to apply to use the data.

Including the 2019 survey, ESPAD data cover a period of

24 years. In 1995 information was collected in 26 countries

(Hibell et al., 1997). In the second wave, in 1999, data were

collected in 30 countries (Hibell et al., 2000), and the surveys

of 2003 and 2007 covered 35 countries each (Hibell et

al., 2004, 2009), with

five

countries additionally collecting

data in 2008.

The

number of participating countries rose to

36 in the 2011 survey (Hibell et al., 2012), with three more

countries collecting data in the autumn of that year (Hibell

and Guttormsson, 2013), and the number of participating

countries decreasing slightly to 35 in 2015 (ESPAD Group,

2016).

The

number of countries participating in the 2019

survey was also 35, with some countries from previous

surveys not participating and Spain participating for the

first

time.

The

aim of the present report is to provide the main

findings

of the 2019 survey.

This

overview of the data can

serve as a useful tool, both for the interested reader and

for policymakers and practitioners who wish to base their

intervention strategies and assessments on the most

recently available information.

In 2008, a cooperation framework was set up between

the European Monitoring Centre for Drugs and Drug

Addiction (EMCDDA) and the ESPAD Group to deepen the

collaboration that had already existed on an ad hoc basis

since the mid-1990s. ESPAD data have been regularly

included in the EMCDDA’s annual reporting on the drug

situation in Europe.

These

data have provided crucial

information on substance use among 15- to 16-year-old

students, allowing trends over time to be assessed.

The

areas of collaboration covered in the cooperation framework

included (1) the integration of the ESPAD approach into

the broader data collection system at EU level; (2) the

encouragement of countries’ participation in ESPAD; (3)

an agreement on the analytical use of ESPAD data, by

placing them in the context of EMCDDA data; and (4)

contact between ESPAD experts and population survey

experts working within the EMCDDA network. Furthermore,

it was agreed to enhance the exchange of information and

expertise, improve the availability, quality and comparability

of school survey data and gain maximum analytical insight

from the data available in this area.

To enhance the effectiveness of decision-making within

the ESPAD Group, the ESPAD Assembly held in Pisa in

2017 approved a revision of the ESPAD constitution,

which identified the EMCDDA as the main international

partner. Following the rules set out in that document, the

coordination of ESPAD is assured jointly by the ESPAD

coordinator and the EMCDDA representative.

The

ESPAD

coordinator is now an elected position and the

first

elections

took place in 2016.

The

work involved in the ESPAD coordination is supported

by the Steering Committee, which also appoints principal

investigators (PIs) in each country.

The

highest decision-making body in ESPAD is the Assembly,

in which all ESPAD PIs, including the coordinator, and the

EMCDDA representative have voting rights and which

gathers on a yearly basis.

The

main researcher in each participating country is

referred to either as a ‘principal investigator’ or as an

‘ESPAD associate researcher’. Each PI or ESPAD associate

researcher should raise funds in his or her country and

participate in ESPAD and the assemblies independently

and at the expense of the national funding body.

The

data

collected in the framework of ESPAD are owned by each

country independently, in particular by the institution hosting

the PI (see ‘Acknowledgements’).

The

PI or ESPAD associate

researcher is responsible for the use of his or her national

data set. Table 1 provides an overview of the countries that

have participated in data collection since 1995 and the

responsible persons.

Background

In the 1980s, a subgroup of collaborating investigators

was formed within the Pompidou Expert Committee

on Drug Epidemiology of the Council of Europe to

develop a standardised school survey questionnaire and

methodology.

The

purpose of the work was to produce

a standard survey instrument that would enable different

countries to compare alcohol and drug use in student

populations. A common questionnaire was used by eight

countries, but the pilot study differed in sample size,

representativeness and age range, and was not performed

at the same time.

The

survey instrument, however, proved

to be valid and reliable (Johnston et al., 1994). With the

exception of Sweden, where school surveys had already

been conducted on an annual basis since 1971, only a few

countries conducted school surveys related to substance

use on a regular basis. In the light of the growing interest in

school surveys in general and cross-country comparisons in

particular, the Swedish Council for Information on Alcohol

and Other Drugs (CAN) initiated a collaborative project in

1993 by contacting researchers in most European countries

to explore the possibility of conducting simultaneous school

surveys on tobacco, alcohol and drug use in association

with the Pompidou Group.

This

enterprise resulted in the

first

ESPAD study in 1995. Since then, the survey has been

repeated every 4 years, with a large number of countries in

Europe involved in the project.

ESPAD Report 2019

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Introduction

Table 1.

Country

Albania

Armenia

Austria

Overview of countries participating in ESPAD data collections 1995-2019

PI/associate researcher

Ervin Toci

Vacant

Julian Strizek

Vacant

Aida Pilav

Sladjana Siljak

Anina Chileva

Martina Markelić

Kyriakos Veresies

Pavla Chomynová

Ola Ekholm

Sigrid Vorobjov

Pál Weihe

Kirsimarja Raitasalo

Stanislas Spilka

Lela Sturua

Ludwig Kraus

Anna Kokkevi

Vacant

Zsuzsanna Elekes

Ársæll Már Arnarsson

Luke Clancy

Vacant

Sabrina Molinaro

Kaltrina Kelmendi

Diana Vanaga

Esther Kocsis

Liudmila Rupšienė

Sharon Arpa

Igor Conrad

Stanislas Spilka

Tatijana Djurisic

Karin Monshouwer

Elena Kjosevska

Elin K. Bye

Janusz Sieroslawski

Elsa Lavado

Silvia Florescu

Eugenia Koshkina

Biljana Kilibarda

Alojz Nociar

Tanja Urdih Lazar

Begoña Brime Beteta

Johan Svensson

Vacant

Nesrin Dilbaz

Olga Balakireva

Vacant

1995

–

Yes

–

Yes

–

Yes

–

Yes

–

Yes

–

Yes

–

Yes

–

Yes

–

Istanbul

Yes

1999

–

Yes

–

Yes

–

Yes

–

Yes

–

Yes

–

Yes

Moscow

–

Yes

–

Yes

–

Yes

2003

–

Yes

–

Yes

–

6 federal

states

Yes

–

Yes

–

Yes

–

Yes

–

Yes

Moscow

–

Yes

–

Yes

6 cities

Yes

2007

–

Yes

Yes (

)

–

Yes (

)

Yes (

)

Yes

–

7 federal

states

Yes

–

Yes

–

Yes

–

Yes

Yes (

)

Yes

Yes (

)

Yes

Yes (

)

Yes

–

Yes

–

Yes

(

)

2011

Yes

–

Yes (

)

–

Yes (

)

Yes

–

5 federal

states

Yes

–

Yes

Yes (

)

Yes

–

Yes

Moscow

Yes

–

Yes

–

Yes

(

)

(

)

2015

Yes

–

Yes

Yes (

)

–

Yes

Yes (

)

–

Yes

–

Yes

–

Yes

–

Yes

Yes (

)

Yes

–

Yes

–

Yes

–

Yes

–

2019

–

Yes

–

Yes

Yes (

)

Yes

1 federal

state

Yes

–

Yes

–

Yes

–

Yes

–

Yes

Yes (

)

Yes

–

Yes

–

Yes

–

Belgium (Flanders)

Belgium (Wallonia)

Bosnia and

Herzegovina (FBiH)

Bosnia and

Herzegovina (RS)

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Greenland

Hungary

Iceland

Ireland

Isle of Man

Italy

Kosovo

Latvia

Liechtenstein

Lithuania

Malta

Moldova

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Russia

Serbia

Slovakia

Slovenia

Spain

Sweden

Switzerland

Turkey

Ukraine

United Kingdom

(

) Data collected in autumn.

(

) Data collected in previous autumn.

(

) Data collected in spring 2008.

(

) Data collected in spring 2018.

(

) Data collected but not delivered.

ESPAD Report 2019

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Introduction

e 2019 ESPAD report

This

report presents the key results of the 2019 ESPAD

survey conducted in 35 countries: Austria, Bulgaria, Croatia,

Cyprus, Czechia, Denmark, Estonia, the Faroes, Finland,

France, Georgia, Germany, Greece, Hungary, Iceland,

Ireland, Italy, Kosovo, Latvia, Lithuania, Malta, Monaco,

Montenegro, the Netherlands, North Macedonia, Norway,

Poland, Portugal, Romania, Serbia, Slovakia, Slovenia,

Spain, Sweden and Ukraine. First, the report presents

information on the perceived availability of substances and

early onset of substance use and prevalence estimates

of substance use (cigarettes and e-cigarettes, alcohol,

cannabis, other illicit drugs, NPS and pharmaceuticals).

The

descriptive information also includes prevalence estimates

of problematic cannabis use, gambling, including excessive

and problem gambling behaviour, social media use and

gaming by country and gender, as well as estimates of

perceived problems related to social media use and gaming.

In addition, overall ESPAD trends between 1995 and 2019

are presented. For selected indicators, ESPAD trends are

shown based on data from 30 countries that participated in

at least four (including the 2019 data collection) of the seven

surveys. Finally, for some indicators, country-specific trends

are shown. For comparative reasons the 2019 ESPAD results

tables contain, in addition to country-specific estimates,

unweighted averages across all participating countries.

This

means that they provide a comparable picture at the country

level but do not describe prevalence or trends in terms of the

overall number of young people in the European countries

participating in this survey.

The

present report contains only the main methodological

information. A comprehensive methodological report is

available at http://www.espad.org.

It is important to highlight that this report contains selected

key results rather than the full range of results and tables (

All results tables and the ESPAD master questionnaire are

available on the ESPAD website (http://www.espad.org).

The

tables can be downloaded in Excel format and used for

further analysis.

(

)

It has to be noted that for descriptive purposes in this report all result

figures are rounded. Sometimes this might give the impression of minor

discrepancies between the comments and the figures that appear in the

tables, which are uniquely due to this operation.

ESPAD Report 2019

Methodology

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Methodology

ESPAD 2019

Sample

The

ESPAD target population is defined as students who

reach the age of 16 years in the calendar year of the survey

and who are present in the classroom on the day of the

survey. Students who were enrolled in regular, vocational,

general or academic studies were included; those who

were enrolled in either special schools or special classes

for students with learning disorders or severe physical

disabilities were excluded. Table 2 shows the main sample

characteristics.

The

methods used are largely comparable

across all countries, although some characteristics, such

as sample type, mode of administration and time of data

collection, may differ in a limited number of countries.

The

study was carried out on a representative sample of

the target population in all participating countries except

the Faroes, Iceland, Malta, Monaco and Montenegro, where

all 2003-born target students were included. Data were

collected by self-administered questionnaires. All countries

used a paper-and-pencil questionnaire except for Austria,

Denmark, France, Iceland, the Netherlands and Norway,

where students answered a web-based questionnaire, and

the Faroes (in only three schools) and Italy, where a mixed

administration mode (paper and pencil and web based) was

used. Comparability between traditional paper-and-pencil

and computerised administration modes was assessed in

a methodological study conducted in Italy; no significant

mode effect in the reporting of sensitive information was

detected and comparability was considered satisfactory

(Colasante et al., 2019a).

The

students answered the questionnaires anonymously

in the classroom, with teachers or research assistants

functioning as survey leaders.

The

questionnaires were

handed to students by school staff (teachers, teacher

assistants, psychologists, etc.) in 15 countries, by external

staff (researchers, research assistants, staff from the

organisation conducting the study) in 17 countries, and by

school or external staff in three countries. In the majority of

countries, data collection took place between March and

May 2019; the exceptions were France, where data collection

took place from April to June 2018, and the Netherlands,

where data were collected between October and November

2019. In most countries, where sampling occurred, class

was the last unit in a multistage stratified random sampling

process.

Data were collected from 99 647 students in 35 countries.

Sample sizes ranged from 428 in Monaco to 5 988 in

Greece. All samples had national geographical coverage,

except for those from Cyprus (only government-controlled

areas were included), Kosovo (less than 4 % of the target

population enrolled in schools in Northern Kosovo under the

parallel structures and working with plans of the Ministry of

Education of Serbia was excluded), Georgia (the occupied

territories of Abkhazia and South Ossetia were excluded) and

Germany (only the federal state of Bavaria was included).

The

school participation rate (share of selected schools

taking part in the survey) was generally high, at 81 % on

average, ranging from 20 % in Denmark to 100 % in Bulgaria,

Georgia and Lithuania.

The

class participation rate (share of

selected classes participating) was also generally high, at

85 % on average, ranging from 21 % in Denmark to 100 %

in Bulgaria, the Faroes, Latvia, Monaco and Montenegro.

The

proportion of students in the selected classes who were

present on the day of the survey and who answered the

questionnaire was high (86 % on average).

The

coverage of

students was very high, with 32 countries reaching 90 % or

more of the target population.

The

lowest rates were reported

in Serbia (86 %) and Germany (88 %). Data were weighted in

11 countries to adjust the sample to the sociodemographic

composition of the target population (

). Weights were

usually calculated to account for gender (two countries)

and geographical distribution of the target population (six

countries), type and size of schools (seven countries) and

immigrant background (one country).

Measures

The

questionnaire covers young people’s awareness of and

experience with different licit and illicit substances, gambling

for money, and social media and gaming.

The

questions are

designed to collect information on these behaviours over

different time frames: lifetime and the last 12 months, last

30 days and last 7 days prior to the survey. Questions on

consumption patterns, such as frequency or quantity (e.g.

volume, hours), and questions that allow for screening of

high-risk and problematic behaviour are also included.

(

)

It has to be noted that there might be minor inconsistencies between the

figures related to Norway in this report and those that can be obtained

from the ESPAD international database, since weights applied to the

Norwegian sample had to be adjusted by the Principal Investigator during

the production of this report.

ESPAD Report 2019

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Methodology

Table 2.

Sampling characteristics of ESPAD 2019

Geo-

graphical

coverage

National

Data

collection

mode

Web

based

Sample

type

Sampling

unit(s)

Class

Data

weight-

Yes

Student

Class par- Students'

represent-

Weight type

ticipation presence

ativeness

rate (%) (

) rate (%) (

)

(%) (

)

School type

and gender

–

100

Country

Austria

4 334

Bulgaria

Croatia

Cyprus

Multistage

stratified

random

National

Paper and Multistage

pencil

stratified

random

National

Paper and Stratified

pencil

random

) Paper and Multistage

National (

pencil

random

National

Paper and Multistage

pencil

stratified

random

Web

Stratified

based

random

Paper and Stratified

pencil

random

Class

2 864

Class

School

Yes

–

Geographical

area and

school type

School type

100

2 772

1 214

Czechia

Class

Yes

> 95 (

)

92 (

)

2 778

Denmark

Estonia

Faroes

Finland

National

School

Class

No sample

Class

Yes

Geographical

area

–

Immigrant

background

–

100

2 487

2 520

511

4 541

France (

)

Georgia

Germany

Greece

Hungary

Mixed

Total

mode (

)

National (

) Paper and Multistage

pencil

stratified

random

National

Web

Multistage

based

stratified

random

)

Paper and Multistage

National (

pencil

random

1 federal

Paper and Systematic

state (

)

pencil

random

National

Paper and Stratified

pencil

clustered

random

National

Paper and Stratified

pencil

random

Class

100

2 588

Class

Yes

–

School type

and grade

Geographical

area

Geographical

area, school

type and

grade

–

100

3 092

1 459

5 988

Class

Yes

2 355

Iceland

Ireland

National

Italy

National

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

National (

)

National

Web

Total

based

Paper and Stratified

pencil

systematic

random

Mixed

Multistage

mode

stratified

random

Paper and Multistage

pencil

random

Paper and Stratified

pencil

random

Paper and Simple

pencil

random

Paper and Total

pencil

Paper and Total

pencil

Paper and Total

pencil

No sample

Class

–

2 534

1 940

Class

–

2 542

Class

No sample

–

100

1 756

2 743

2 393

3 043

428

5 700

ESPAD Report 2019

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Methodology

Country

Geo-

graphical

coverage

Data

collection

mode

Web

based

Paper and

pencil

Web

based

Paper and

pencil

Paper and

pencil

Paper and

pencil

Paper and

pencil

Paper and

pencil

Paper and

pencil

Paper and

pencil

Paper and

pencil

Paper and

pencil

Sample

type

Multistage

random

Systematic

random

Multistage

stratified

random

Stratified

random

Stratified

random

Multistage

random

Multistage

stratified

random

Stratified

random

Stratified

random

Multistage

stratified

random

Multistage

random

Multistage

stratified

random

Sampling

unit(s)

Class

Data

weight-

Yes

Netherlands (

)

National

North

Macedonia

Norway

National

Student

Class par- Students'

represent-

Weight type

ticipation presence

ativeness

rate (%) (

) rate (%) (

)

(%) (

)

–

School type

35 (

)

and gender

–

Geographical

area and

school type

Geographical

area

–

1 288

2 930

4 313

Poland

Portugal

Romania

Serbia

National

Class

Yes

100

90 (

)

–

2 372

4 365

3 764

3 529

Slovakia

Slovenia

Spain

National

School (

)

Class

–

94 (

)

100

2 258

3 413

3 557

Sweden

Ukraine

National

National (

)

Class

–

98 (

)

2 546

2 731

Average or sum

(

) Proportion of ESPAD target students covered by the sampling frame.

(

) Proportion of selected classes participating in the survey.

(

) Proportion of students of participating classes answering the questionnaire.

(

) Only government-controlled areas were covered by the sampling frame.

(

) Estimations by the PI.

(

) School participation rate (class participant rate unknown).

(

) Web-based administration was used in three schools.

(

)

The

Åland Islands were not covered by the sampling frame.

(

) Data collected in spring 2018.

(

)

The

occupied territories of Abkhazia and South Ossetia were not covered by the sampling frame

(

)

The

sampling frame covered only the federal state of Bavaria.

96 783

(

) 4 % of the target population enrolled in schools in Northern Kosovo and/or functioning under the parallel structures of the Ministry of Education of

Serbia within the other Serbian municipalities were not covered by the sampling frame.

(

) Data collected in autumn instead of spring.

(

) Sampling unit was school, and classes included in the survey were selected randomly by assistants in the last step of selection at schools before

the survey.

(

) Autonomous Republic of Crimea was not included in the survey, nor were the territories of Donetsk and Luhansk, which are not controlled by the

Ukrainian government.

ESPAD Report 2019

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Methodology

Availability of substances

The

perceived availability of substances is a proxy measure

for how easy or difficult it is for students to obtain a particular

substance (cigarettes, alcohol and illicit drugs). Students

were asked how difficult they thought it would be to obtain

a particular substance if they wanted to.

The

response

categories were ‘impossible’, ‘very difficult’, ‘fairly difficult’,

‘fairly easy’, ‘very easy’ and ‘don’t know’.

The

proportions of

students in each country answering ‘fairly easy’ or ‘very easy’

were merged to provide an indication of easy availability.

The

availability of each type of alcoholic beverage (beer, wine and

spirits) was investigated separately. If considered relevant,

countries included other alcoholic beverages such as cider

or premixed drinks in the questionnaire. Alcohol availability

was calculated as at least one among each

five

types of

beverage indicated as ‘fairly easy’ or ‘very easy’ to obtain.

were ‘not at all’, ‘less than once per week’, ‘at least once

a week’ and ‘almost every day or every day’. Students were

also asked about their previous experience with tobacco use

at the time of their

first

use of e-cigarettes and, optionally, in

some countries, about the main motives for starting to use

e-cigarettes and about the content of the

first

e-cigarette.

The

response options for the question on the content of

e-cigarettes were ‘nicotine’, ‘flavouring’, ‘don’t know’ and ‘I

have never tried e-cigarettes’. Lifetime prevalence and last-

30-day prevalence were calculated based on use on at least

one occasion.

Alcohol use

Students were asked on how many occasions they had

consumed alcoholic beverages and had been intoxicated in

their lifetime, during the last 12 months and during the last

30 days.

The

response categories were ‘0’, ‘1-2’, ‘3-5’, ‘6-9’,

‘10-19’, ‘20-39’ and ‘40 or more’.

The

average number of

occasions was calculated based on the mean value for each

response category, for example 29.5 times for the category

‘20-39’. For the category ‘40 or more’ a value of 41 was used.

The

prevalence of any use (lifetime, last 12 months and last

30 days) and prevalence of experiencing any intoxication

were also calculated. Heavy episodic drinking was defined

as drinking a minimum of

five

glasses of alcoholic beverages

on one occasion at least once in the last 30 days, which

corresponds to a cut-off of approximately 9 centilitres of pure

alcohol.

The

volume of alcohol intake was calculated as the

total volume of pure ethanol summed across the different

alcoholic beverage types (beer, wine, spirits, premixed drinks

and cider, with the last two being optional).

The

relative

contribution of each beverage (in centilitres of ethanol) to

the total amount of alcohol consumed on the last drinking

day was taken as an indicator of preference for alcoholic

beverages.

Age at

first

substance use

Students were asked how old they were when they used

a particular substance for the

first

time, started to use it

on a daily basis (cigarettes, e-cigarettes) and experienced

excessive use (alcohol intoxication).

The

response categories

ranged from ‘9 years old or less’ to ’16 years or older’, in

increments of 1 year, and included the category ‘never’. An

age at initiation of 13 years or younger was defined as an

indicator of early onset; rates of early onset of substance

use were calculated separately for cigarettes, e-cigarettes,

alcohol and illicit drugs.

Cigarette use

Students were asked on how many occasions they had

ever smoked cigarettes (excluding e-cigarettes), with the

response categories being ‘0’, ‘1-2’, ‘3-5’, ‘6-9’, ‘10-19’,

‘20-39’ and ‘40 or more’.

The

frequency of smoking and

number of cigarettes smoked in the last 30 days were also

collected.

The

response categories were ‘not at all’, ‘less

than 1 cigarette per week’, ‘less than 1 cigarette per day’,

‘1-5 cigarettes per day’, ‘6-10 cigarettes per day’, ‘11-20

cigarettes per day’ and ‘more than 20 cigarettes per day’.

Lifetime prevalence and last-30-day prevalence (any use)

were calculated. Daily use of cigarettes was considered as

having smoked a minimum of one cigarette per day in the

last 30 days.

Cannabis use

Students were asked on how many occasions they had used

cannabis in their lifetime, during the last 12 months and

during the last 30 days.

The

response categories were ‘0’,

‘1-2’, ‘3-5’, ‘6-9’, ‘10-19’, ‘20-39’ and ‘40 or more’. Lifetime

prevalence and last-30-day prevalence (any use) were

calculated.

The

average frequency of cannabis use in the last

12 months was calculated using the mean value for each

response category, for example 29.5 for the category ‘20-39’.

For ‘40 or more’ a value of 41 was used.

The

Cannabis Abuse Screening Test (CAST) was used to

screen for possible cannabis-related problems (Legleye et

al., 2007, 2011).

The

six items of the CAST are worded as

follows: (1) ‘Have you smoked cannabis before midday?’, (2)

Electronic cigarettes

Students were asked about lifetime, last-year and last-30-

day use of e-cigarettes. Frequency of e-cigarette use in the

last 30 days was also collected.

The

response categories

ESPAD Report 2019

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Methodology

‘Have you smoked cannabis when you were alone?’, (3) ‘Have

you had memory problems when you smoke cannabis?’, (4)

‘Have friends or members of your family told you that you

ought to reduce your cannabis use?’, (5) ‘Have you tried to

reduce or stop your cannabis use without succeeding?’ and

(6) ‘Have you had problems because of your use of cannabis

(arguments,

fights,

accidents, bad results at school, etc.)?’ All

of these questions refer to the past 12 months.

The

response

categories for the CAST are ‘never’, ‘rarely’, ‘from time to

time’, ‘fairly often’ and ‘very often’.

The

possible scores for

each item are 0 or 1, with the threshold for scoring 1 point

being ‘from time to time’ for the

first

two items and ‘rarely’ for

the remaining items (which refer to more serious problems).

A total score of 2 or more points (range 0-6) is considered to

indicate high-risk use.

This

cut-off score has been shown to

best distinguish individuals at high risk of cannabis-related

problems from individuals at low risk of such problems in

community samples (Legleye et al., 2007, 2011). It should

be noted that there is an ongoing debate about the validity of

screening tests, including the CAST. With regard to the CAST

specifically, over time, different coding systems and cut-

off scores have been validated on representative samples

(Bastiani et al., 2013; Legleye et al., 2007, 2011, 2013, 2107)

and there is no definitive agreement about the best system

or scores to use. Clearly, different computation methods will

generate different prevalence results.

In this report, we adopted the binary computation of the

score with a cut-off of 2 or more points used to indicate high-

risk use’, which has been proposed in adolescent samples

(Gyepesi et al., 2014; Legleye et al., 2011) and which allows

comparability with the CAST results published in the 2011

ESPAD report for some countries (Hibell et al., 2012).

When used in the context of self-reported surveys, the CAST

may allow the early identification of adolescents who are

liable to present with problem cannabis use or dependence.

It should be noted, however, that this test is a screening

tool — it can be used to make comparisons and perform

epidemiological analyses, but cannot provide a clinical

diagnosis.

This

report provides prevalence estimates of high-risk users

in the total sample based on the CAST instrument.

The

additional tables available on the ESPAD website provide

estimates of the proportion of high-risk users among those

students who answered positively to the introductory

question of the CAST (i.e. claimed to have used cannabis in

the year prior to the survey); the frequency of responses for

each of the six CAST items among 12-month users; and the

CAST item averages presented separately for each country

using a continuous

five-point

scale from 1, ‘never’, to 5, ‘very

often’.

Other illicit drug use

To measure experience with other illicit drugs, students

were asked on how many occasions they had tried different

drugs in their lifetime and during the last 12 months, with

response categories of ‘0’, ‘1-2’ and ‘3 or more’. Frequency

of use was asked separately for ecstasy, amphetamine,

methamphetamine, cocaine, crack, heroin, LSD or other

hallucinogens, and GHB (gamma-hydroxybutyrate). Lifetime

prevalence (any use) for each substance was based on

intake on at least one occasion.

Inhalant use

Students were asked how often they had used inhalants in

their lifetime, during the last 12 months and during the last

30 days, with response categories of ‘0’, ‘1-2’ and ‘3 or more’.

Prevalence of any use of inhalants was based on intake on at

least one occasion (i.e. students reporting use on ‘1-2’ or ‘3

or more’ occasions).

New psychoactive substance use

New psychoactive substances (NPS) were defined as

‘substances that imitate the effects of illicit drugs such

as cannabis or ecstasy and are sometimes called “legal

highs”, “ethnobotanicals” or “research chemicals” and can

come in different forms (herbal mixtures, powders, crystals

or tablets)’. Countries could provide the nationally used

descriptions and terminology, which could have an impact

on the

findings

in different countries. Students were asked

about the number of occasions they had used NPS in

their lifetime and during the last 12 months, with response

categories of ‘0’, ‘1-2’, ‘3 or more’ and ‘don’t know/not sure’.

Prevalence of any use of NPS was based on intake on at

least one occasion (i.e. students reporting use on ‘1-2’ or ‘3

or more’ occasions). Optionally, in some countries, students

were also asked on how many occasions in their lifetime they

had used synthetic cannabinoids (asked in 20 countries) and

synthetic cathinones (asked in 19 countries), with response

categories of ‘0’, ‘1-2’, ‘3 or more’. Prevalence of any use

of synthetic cannabinoids and synthetic cathinones was

also based on intake on at least one occasion. In addition,

prevalence of any use of NPS in the last 12 months was also

calculated. Students who reported using NPS in the last 12

months were asked about the types of NPS used according

to the following answer options: ‘herbal smoking mixtures

with drug-like effects’, ‘powders, crystals or tablets with drug-

like effects’, ‘liquids with drug-like effects’ or ‘other’. Data

on the proportions of users in the last 12 months reporting

having used the different types of NPS are provided in the

text, and prevalence results are available in the additional

tables that can be accessed online.

ESPAD Report 2019

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Methodology

Use of pharmaceuticals for non-medical purposes

To measure lifetime use of pharmaceuticals for non-medical

purposes, students were asked on how many occasions

they had used tranquillisers or sedatives without a doctor’s

prescription, anabolic steroids or painkillers in order to get

high, with response categories of ‘0’, ‘1-2’ and ‘3 or more’.

Prevalence of lifetime use was based on intake of any of

these substances on at least one occasion.

Gambling

Gambling for money was assessed by asking students about

both the frequency of their gambling activity in general and

the types of games played (slot machines, cards or dice,

lotteries or betting on sports/animals) in the last 12 months.

The

response categories for these questions were ‘I have

not gambled’, ‘monthly or less’, ‘2-4 times a month’ and

‘2-3 times or more a week’. As the response options provide

a frequency interval, an overall index of gambling activity was

created by dichotomising the response options (‘yes’/’no’),

with any response other than ‘I have not gambled’ coded

as ‘yes’ for each of the four games. In this report, gambling

prevalence was calculated as the rate of those who had

gambled for money on at least one of the four games of

chance (playing on slot machines, playing cards or dice for

money, playing the lottery, betting on sports or animal races)

in the last 12 months. On this basis, the proportions playing

the different types of games among those who had gambled

for money in the past 12 months were also calculated.

The

method used to compute gambling prevalence in this

report is different from that used in 2015, when a direct

question, ‘How often (if ever) did you gamble for money

in the last 12 months?’, was asked.

Therefore,

a direct

comparison of this measure between the 2019 results and

the 2015 results is not possible.

The

approach used in 2019

is believed to produce a more reliable estimate of gambling

prevalence than the 2015 approach (Molinaro et al., 2018).

Online gambling was assessed by asking students how often

they had gambled for money in the last 12 months using the

internet.

The

prevalence of online gambling in the last 12

months was calculated as the percentage who had gambled

on the internet ‘seldom’ or more often.

Furthermore, two specific screening tools were used to

assess for the presence of excessive gambling and problem

gambling behaviour.

An adapted version of the Consumption Screen for

Problem Gambling (CSPG; Rockloff, 2012), a three-item

test assessing the intensity of gambling, was used to

calculate the proportion of gamblers displaying excessive

gambling behaviour.

The

three questions measure (1)

gambling frequency — ‘How often (if ever) have you

gambled for money in the last 12 months?’, reported on

the following scale: ‘I have not gambled for money’ = 0,

‘monthly or less’ = 1, ‘2-4 times a month’ = 2, ‘2-3 times or

more a week’ = 3; (2) time spent on gambling — ‘How much

time did you spend gambling on a typical day in which you

gambled in the last 12 months?’, reported on the following

scale: ‘I have not gambled for money’ = 0 and ‘less than

30 min’ = 0, ‘between 30 min and 1 hour’ = 1, ‘between 1

and 2 hours’ = 2, ‘between 2 and 3 hours’ = 3, ‘3 hours or

more’ = 4; and (3) gambling intensity — ‘How often did you

spend more than 2 hours gambling (on a single occasion)

in the last 12 months?’, reported on the following scale: ‘I

have not gambled for money’ = 0 and ‘never’ = 0, ‘less than

monthly’ = 1, ‘monthly’ = 2, ‘weekly’ = 3, ‘daily or almost

daily’ = 4. A score of 4 or more points was considered to

indicate excessive gambling.

The

Lie/Bet Questionnaire (Johnson et al., 1997), a two-

question screening tool, was used to assess the proportion

of gamblers with a problem gambling behaviour.

The

two

questions used in the tool are ‘Have you ever lied to family

and friends about how much money you have spent on

gambling?’ and ‘Have you ever felt that you needed to

gamble for more and more money?’; both questions have the

response categories ‘yes’ = 1 and ‘no’ = 0, and the Lie/Bet

sum score therefore ranges from 0 to 2. A score of 2 points

was considered to indicate problem gambling.

Prevalence estimates of excessive gambling and problem

gambling are provided in the additional tables that are

available online.

Social media use and gaming

To assess patterns of social media use, students were

asked how many hours on average during the last 7 days

they had spent communicating with others on social media

(e.g. WhatsApp, Twitter, Facebook, Skype, blogs, Snapchat,

Instagram, Kik), distinguishing between school days and

non-school days (weekends, holidays). Gaming patterns

were assessed by asking students about the number of days

in the last week and the average number of hours during

the last 30 days they had spent playing games on electronic

devices (i.e. computers, tablets, consoles, smartphones

or other electronic devices), again distinguishing between

school and non-school days.

The

answer options for the

questions on the average number of hours spent during

the last 7 days on social media and during the last 30 days

on gaming were ‘none’, ‘half an hour or less’, ‘about 1 hour’,

‘about 2-3 hours’, ‘about 4-5 hours’ and ‘6 hours or more’.

Prevalence of use and average and modal class of mean

number of hours spent on social media and gaming were

ESPAD Report 2019

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Methodology

reported separately for a typical school day and a typical

non-school day for the last 7 days and the last 30 days,

respectively.

In addition, a specific screening tool (Holstein et al., 2014)

was adapted to assess for the presence of self-perceived

problems related to two distinct behaviours: (1) social media

use and (2) gaming.

This

tool is a non-clinical instrument

focusing on a student’s perception of problems related to

three items: too much time spent on these activities, bad

feelings because of restricted access and parents’ concerns

related to the time spent on these activities. Students were

asked to what extent they agreed with the above three

statements, with the response categories being ‘strongly

agree’, ‘partly agree’, ‘neither agree nor disagree’, ‘partly

disagree’ and ‘strongly disagree’. Positive answers (‘strongly

agree’ and ‘partly agree’) were summed to produce an

index score. An index score of 0-1 points was considered to

indicate a low level of self-perceived problems, and a score

of 2-3 points was considered to indicate a high level of self-

perceived problems related to social media use and gaming.

A few countries experienced modest methodological

problems, but not of a big enough magnitude to seriously

hinder the comparability of the results. Compared with the

ESPAD averages, higher rates of inconsistencies indicate

a somewhat lower data quality for the samples from

Bulgaria, Cyprus and Georgia.

Low school/class participation rates in Denmark (21 %),

Austria (30 %), the Netherlands (35 %) and Ireland

(39 %) resulted in relatively small net sample sizes. In the

Netherlands (8.8 %), Sweden (4.3 %) and Cyprus (4.2 %),

a relatively high proportion of cases had to be discarded

during the central data-cleaning process. In the case of

Sweden this was primarily because a third response option,

‘other gender identity’, was provided for the question on

gender.

In general, the coverage of the target student population was

over 90 %, except in Germany and Serbia (both 88 %).

Finally, a relatively high proportion of parents in Cyprus

(12 %) and Portugal (11 %) refused permission for their child

to participate in the survey.

More details on the ESPAD methodology are available online

(http://www.espad.org).

Data processing and data quality

Data were centrally cleaned using two steps. First, logical

substitution of missing values was performed in a rather

conservative way. In cases where students indicated that

they had never used a specific substance and did not

respond to other questions about such use, any missing

values were substituted with no use for that particular

substance. However, no substitutions were made if any

contradictory indications of use were reported.

Overall, this generated minor changes in the data. For

example, for seven selected substance use variables, the

average reduction in the non-response rate resulting from

logical substitution was rather small, ranging from 0.1 % to

0.3 %.

The

single highest country-specific reduction was

found in Kosovo, where the non-response rate for lifetime

intoxication from alcoholic beverages was reduced by

1.8 percentage points.

The

logical substitution of missing

values had the biggest impact in Kosovo and North

Macedonia. However, the reductions in non-responses had

only minor effects on the

final

prevalence estimates.

Second, all cases with missing information on gender were

excluded from the database.

The

other major reason for

exclusion was poor data quality. All cases with responses

to less than half of the core items were discarded, as were

all cases where the respondent appeared to have followed

patterns involving repetitive marking of extreme values.

Across all ESPAD countries, an average of 1.5 % (range: 0.1-

8.8 %) of cases were excluded because of poor data quality

or missing information on gender.

Analysis

Prevalence estimates and means were calculated for each

participating country, taking weights into account where

necessary (see Table 2). In the majority of tables, totals and

gender-specific estimates for boys and girls are presented

by country. Gender differences reported in Figures 1b-10b

were tested using either simple linear regression for quasi-

continuous frequency measures or logistic regression for

prevalence, with gender as a predictor.

The

ESPAD average is based on 35 countries, with an equal

weight assigned to each country. All percentages in the

report were calculated on the basis of valid responses and

are shown for the total samples, boys and girls. With the

exception of the frequency of alcohol intake (Figures 3a,

3b), average alcohol intake (Figures 4a, 4b), preferences

for alcoholic beverages (Figure 5), frequency of cannabis

use (Figures 8a, 8b), proportion of high-risk cannabis users

(Figures 9a, 9b), types of games chosen by those who had

gambled for money in the past 12 months (Table 11b) and

proportions of excessive and problem gamblers (Table 11c),

for which the estimates are based on consumers of

a particular substance or students engaging in a particular

risk behaviour, all estimates are based on the total sample

and represent population estimates.

ESPAD Report 2019

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Methodology

Trend analysis

For temporal trends, country estimates were averaged across

30 countries with valid estimates on at least four (including

2019) out of seven time points. It should be noted that in this

report, trends for selected indicators were calculated using

the ESPAD 1995-2019 trend database, which includes data

from all of the national survey waves since the inception of

the ESPAD project.

The

ESPAD trend database was created in 2017 according

to the following procedure. For the years 1995, 1999

and 2003, national raw datasets were provided by each

participating country, as at the time of these surveys

participating countries were requested to deliver to the

ESPAD coordination standard information in predefined data

tables, but no ESPAD international datasets were produced.

The

available national raw datasets from 1995, 1999 and

2003 were centrally cleaned using the ESPAD 2015 routines

in order to harmonise the data. For the years from 2007 to

2019, the ESPAD international databases were used, as

for these data collections each participating country had to

provide its raw dataset to the ESPAD coordination, which

then prepared unique international datasets. It should

be noted that, for the years 1995, 1999 and 2003, some

countries were not able to provide the national dataset

for a specific year for various reasons (e.g. changes in the

PI representing the country), even though the survey was

conducted. In these cases data could not be included in the

ESPAD trend database, nor in the trend estimates shown in

the ‘Trends 1995-2019’ section of this report. In other cases

the datasets provided for the ESPAD trend database had

a different number of observations or were provided in a non-

standard format; in the latter case some information could

not be included.

Because of these issues, it is possible that the results

presented in ‘Trends 1995-2019’ differ slightly from those

presented in the same section of the 2015 report, as at the

time the ESPAD trend database had not yet been

finalised

and the trend estimates were produced using the results

published in the previous ESPAD reports.

The

30 countries included in the trend analysis were Austria,

Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia,

the Faroes, Finland, France, Germany (Bavaria), Greece,

Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Malta,

Monaco, Montenegro, the Netherlands, Norway, Poland,

Portugal, Romania, Slovakia, Slovenia, Sweden and Ukraine.

The

averages across the 30 country means were calculated

using a weight of 1, and data for each survey year were

summed and divided by the number of countries with valid

data for that particular year.

In the 1995-2019 trend database, data across all seven time

points are available for 14 countries. Data from 15 countries

are missing in 1995, data from nine countries are missing

in 1999 and data from three countries are missing in 2003.

In 2011, data from only one country were missing. A full

description is provided in Table 13 in the ‘Trends 1995-2019’

section of this report.

Trends across the 30 countries are shown for a selected

number of indicators by gender. Country-specific trends are

shown for all countries that participated in the 2019 data

collection and that have at least two valid data points over

the period 1995-2019. Country-specific temporal trends

were estimated based on the ESPAD 1995-2019 trend

database using analysis of variance to test for significant

changes, with the survey year as the independent variable

in the model.

The

test was made only for countries with at

least three valid data points over the period 1995-2019. Post

hoc tests (Tukey or Games-Howell, depending on whether or

not the variances were homogeneous) were used to assess

which years were responsible for changes in prevalence.

Trends are illustrated graphically, with statistically significant

decreases between successive surveys indicated in green,

statistically significant increases in red and unchanged

situations in yellow.

Comparability of variables

After the 2003 survey, a working group was set up to

improve and revise some of the questions that had caused

problems in the previous surveys. Modified questions were

tested on differences in outcome using a split-half design

in eight countries. In general, most of the revised questions

were found to be comparable with the earlier versions

(Hibell and Bjarnason, 2008). In the following surveys, other

modifications were made to some questions, which we

briefly report here.

Availability of substances

In the surveys until 2003, the perceived availability of

substances was assessed using a single question. Since

2007, the questionnaire has contained separate questions

for each substance. A questionnaire test in eight countries

showed some differences between the two versions.

Nicotine use

In the 2019 survey, the questionnaire module on ‘cigarette

smoking’ was modified to ‘tobacco smoking’ by specifying

that it refers to cigarettes, including rolled cigarettes, and

excludes e-cigarettes. A new module was added to assess

ESPAD Report 2019

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Methodology

the use of smoking and nicotine products, including

e-cigarettes (e-cigs, vapes and mods) and water pipes. In

2015, lifetime and last-12-month use of e-cigarettes, as well

as the age at

first

use and

first

daily use, had been asked only

in 21 countries and 17 countries, respectively.

The

lifetime

and last-12-month use of water pipes had been included in

20 countries.

to the following two sets of substances: (1) LSD or other

hallucinogens, ‘magic mushrooms’, GHB and drugs by

injection with a needle (e.g. heroin, cocaine, amphetamine)

and (2) tranquillisers or sedatives (without a doctor’s

prescription), anabolic steroids, alcohol together with pills

and painkillers in order to get high. In 2019, use of heroin

was assessed using a separate question, and for the

first

time use in the last 12 months was also examined.

For all of the above substances and time frames, response

categories were changed from ‘0’, ‘1-2’, ‘3-5’, ‘6-9’,’10-19’,

‘20-39’ and ‘40 or more’ to ‘0’, ‘1-2’ and ‘3 or more’.

Alcohol use

In the surveys until 2003, the question on heavy episodic

drinking read, ‘How many times (if any) have you had

five

or more drinks in a row? A “drink” is a glass of wine

(approximately 15 centilitres), a bottle or can of beer

(approximately 50 centilitres), a shot glass of spirits

(approximately 5 centilitres) or a mixed drink.’ Cider or

alcopops were not included. Since 2007, the definition

has read, ‘How many times (if any) have you had

five

more drinks on one occasion? A “drink” is a glass/bottle/

can of beer (approximately 50 centilitres), a glass/bottle/

can of cider (approximately 50 centilitres), two glasses/

bottles of alcopops (approximately 50 centilitres),

a glass of wine (approximately 15 centilitres), a glass of

spirits (approximately 5 centilitres) or a mixed drink.’

The

questionnaire test revealed no significant differences

between the two versions. In the 2019 questionnaire, a ‘drink’

is defined as a glass/bottle/can of beer (33 centilitres),

a glass of wine (approximately 15 centilitres), a glass of

spirits (approximately 4 centilitres), a glass/bottle of cider

(33 centilitres) or a glass/bottle of premixed drinks (spritz,

alcopops etc.) (33 centilitres) (the inclusion of cider or

premixed drinks was optional).

Inhalant use

In the earliest rounds of the survey, the question on inhalant

use was ‘Did you try inhalants (glue, etc.) to get high?’.

In 2007, the question was rephrased to refer to ‘the use

of inhalants to get high’.

The

questionnaire test found no

significant differences between the old and new versions.

Since 2011, countries have been instructed to add nationally

relevant examples in the questionnaire.

Reporting

Based on the 2019 ESPAD data, selected substance use

indicators are presented comprising students’ perceptions

of the availability of cigarettes, alcohol and illicit drugs,

early onset of substance use and prevalence estimates of

substance use. In addition, patterns of current drug use

among users of the specific substances are presented

for cigarettes (prevalence of daily smoking), e-cigarettes

(prevalence in the last 30 days), alcohol (mean number

of occasions of alcohol use in the last 30 days; beverage

preference and average alcohol volume intake on the last

drinking occasion; prevalence of heavy episodic drinking,

defined as consumption of

five

or more drinks on at least

one occasion, in the last 30 days), cannabis (prevalence in

the last 30 days; mean number of occasions of cannabis use

in the last 12 months; proportion of high-risk users among

those having used cannabis in the past 12 months) and NPS

(prevalence in the last 12 months).

The

average results by

country are presented using maps, and gender differences

by country are shown using bar charts (Figures 1a-10b),

including tests for significance (p < 0.05).

In the ‘Trends 1995-2019’ section, temporal trends between

1995 and 2019 are presented for the averages across the 30

country means and for all ESPAD countries separately.

Illicit drugs other than cannabis

The

questionnaire collects data on the use of illicit drugs

other than cannabis, including amphetamine, cocaine, crack,

ecstasy, LSD or other hallucinogens, heroin, GHB (since

2007) and methamphetamine (since 2015). In 2015 crack

was not included in the surveys carried out in Denmark,

Estonia, Finland and Sweden, while in 2019 it was included

for all countries.

In 2019, lifetime use and last-12-month use

of amphetamine, cocaine, crack, ecstasy and

methamphetamine were assessed using a single question,

while in 2015 separate questions were asked for each

substance. Lifetime use of other substances, which in 2015

was assessed using a single question (including heroin),

was assessed using two questions in 2019, according

ESPAD Report 2019

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e situation

in 2019

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e situation in 2019

This

chapter presents selected indicators for substance use and

other risk behaviours in the 35 ESPAD countries participating

in the 2019 survey. Each results section begins with a table

containing a summary of the main results, including the ESPAD

average estimate and country range (minimum (min.) and

maximum (max.)) for each selected measure.

appeared to be higher for girls than boys (Table 3a). On

average, more than three in four students (78 %) stated that

they would

find

it easy to acquire alcoholic beverages if they

wanted to. In Denmark, Germany and Greece, more than 90 %

of students reported easy access.

The

lowest proportions

reporting easy access were found in Kosovo (38 %), which is

also the only country with a figure of less than 50 %, followed

by Lithuania (61 %), Iceland (62 %) and Romania (63 %).

A considerable gender difference was found in Kosovo

(12 percentage points), with a higher rate among boys than

girls, and in Lithuania, Monaco and Sweden (8-11 percentage

points), with higher rates among girls than boys.

Perceived availability of substances

ESPAD average

Perceived availability of substances (%) (

)

Average

Cigarettes

Alcohol

Cannabis

Ecstasy

Amphetamine

Methamphetamine

Cocaine

Crack

8.5

8.1

Min.

4.7

2.8

2.9

4.2

2.7

Max.

Illicit drugs

About three in 10 students (32 %) rated cannabis to be easily

obtainable (Table 3a). More students in the Netherlands

(51 %) than in any other ESPAD country perceived cannabis

to be easily available. High proportions were also found

in Denmark (48 %) Czechia (47 %) Slovenia (46 %) and

Slovakia (45 %).

The

countries with the lowest perceived

availability of cannabis were Kosovo (11 %), Ukraine (13 %),

Romania (16 %) and North Macedonia (19 %). Boys were

more likely than girls to consider cannabis to be easily

available (ESPAD average: 34 % versus 30 %).

This

was the

case in most countries, with gender differences of up to

15 percentage points.

The

countries in which more girls than

boys reported easy availability of cannabis were Bulgaria

Czechia, Faroes, Malta, Slovakia and Ukraine.

On average, the perceived availability of other illicit drugs

was relatively low (Tables 3a and b), with the proportions

of students reporting easy access being 14 % for ecstasy,

13 % for cocaine, 10 % for amphetamine and 8.5 % for

methamphetamine. Illicit drugs were perceived to be more

easily available overall in Austria, Bulgaria, Sweden and

Denmark than elsewhere in Europe.

The

perceived availability

of ecstasy was highest in Slovakia, Czechia, Slovenia and

the Netherlands (over 20 %), and the perceived availability

of cocaine was highest in Denmark and Ireland (22 % each).

The

countries with the lowest perceptions of availability for

nearly all illicit drugs were Kosovo, Georgia and Romania.

Noticeable gender differences for ecstasy availability were

found in the Netherlands, Monaco and Ireland (rates were

5 or more percentage points higher for boys than girls). In

Slovakia higher rates were found for girls than boys for both

ecstasy availability and cocaine availability. Other countries

with gender differences of at least 5 percentage points

for cocaine were Bulgaria, Portugal and Malta, with higher

figures

for girls than boys, and Monaco with higher

figures

for

boys than girls.

(

) Percentage of students rating a substance as either ‘fairly easy’ or

‘very easy’ to obtain.

Cigarettes

On average, 60 % of students in the participating countries

reported that they would

find

it ‘fairly easy’ or ‘very easy’

(hereafter referred to as ‘easy’) to get hold of cigarettes if they

wanted to (Table 3a). Students in Denmark were most likely to

find

it easy (79 %). In Sweden, Poland, Slovakia and Czechia,

the perceived availability was also comparatively high, with over

70 % of the students reporting access to be easy.

The

perceived

availability was lowest in Kosovo (24 %) and

figures

of less than

50 % were observed in

five

other countries: Romania (39 %),

Ukraine (42 %), Georgia (45 %), Iceland (47 %), and North

Macedonia (49 %). Gender differences were negligible at the

aggregate level (61 % for boys versus 59 % for girls). Where

differences were observed,

figures

were higher for boys than

girls in the majority of countries, with the highest difference

(13 percentage points) found in Kosovo. In 11 countries, the

perceived availability was slightly higher for girls than boys, with

the difference reaching 5 percentage points in Bulgaria.

Alcohol

Alcoholic beverages were perceived to be easily available

in most countries and, in general, the perceived availability

ESPAD Report 2019

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e situation in 2019

Table 3a.

Perceived availability of substances: prevalence of students responding substance ‘fairly easy’ or ‘very easy’ to

obtain (cigarettes, alcohol, cannabis and ecstasy) (percentage)

Cigarettes

Alcohol

Boys

Girls

Cannabis

Boys

Girls

7.3

Ecstasy

Boys

6.4

7.8

8.6

6.0

5.5

5.0

Girls

5.1

7.5

5.7

7.3

5.6

3.9

5.0

5.9

7.7

6.1

3.9

Cigarettes

Alcohol

Cannabis

Ecstasy

Boys

Girls

5.8

7.6

7.0

9.5

5.8

4.7

8.4

5.7

8.8

5.6

4.7

Country

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

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e situation in 2019

Table 3b.

Perceived availability of substances: prevalence of students responding substance ‘fairly easy’ or ‘very easy’ to

obtain (amphetamines, methamphetamines, cocaine and crack) (percentage)

Amphet-

amine

5.3

6.1

8.0

3.1

7.2

5.4

2.8

8.8

6.8

8.0

4.4

9.1

7.9

6.4

2.8

Meth-

amphet-

amine

9.2

8.7

4.8

4.9

7.6

3.2

6.4

6.2

9.0

8.7

4.3

2.9

8.3

7.5

8.8

4.8

9.5

6.1

–

7.1

4.1

9.3

7.4

5.3

8.5

2.9

Amphetamine

Cocaine

6.5

5.7

4.2

9.1

5.0

7.5

6.9

4.6

4.2

Crack

Boys

–

4.3

–

2.7

6.8

–

9.1

8.0

6.2

3.6

–

7.2

–

4.4

–

9.1

7.5

4.1

–

4.2

8.1

2.7

8.4

8.8

5.6

6.6

8.1

3.8

8.8

5.4

3.1

8.8

3.5

6.9

6.8

3.9

8.5

5.8

3.1

Girls

8.6

5.1

5.6

7.9

2.5

5.7

8.9

5.5

2.7

8.9

5.5

6.8

9.0

4.8

8.0

7.4

7.0

2.5

Metham-

phetamine

Boys

7.6

4.4

5.3

8.2

3.6

7.1

7.9

9.4

4.8

2.8

8.2

7.9

8.6

4.1

5.9

–

6.4

3.8

9.4

8.0

5.2

8.5

2.8

Girls

8.2

5.1

4.5

7.0

3.0

5.7

4.5

8.3

8.0

3.8

3.0

8.3

7.2

9.0

5.5

8.0

6.2

–

7.8

4.4

9.2

6.8

5.4

8.4

3.0

Cocaine

Boys

8.2

6.8

5.0

4.9

8.9

4.8

8.7

8.6

7.3

9.4

4.9

4.1

Girls

6.3

6.4

3.6

9.3

5.1

7.7

9.0

5.1

3.6

Crack

Boys

–

4.4

–

3.5

6.2

–

7.9

6.3

3.3

–

8.6

–

5.1

–

9.2

6.4

3.7

–

4.1

3.3

Girls

–

4.3

–

2.1

7.3

–

8.4

8.1

6.1

3.9

–

6.0

–

3.8

–

9.0

8.3

4.5

–

4.3

2.1

Country

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

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e situation in 2019

Early onset of substance use

ESPAD average

Early onset of substance use (%) (

)

Average

Cigarettes

Daily smoking

E-cigarettes

Daily e-cigarettes

Alcohol

Intoxication

Cannabis

Ecstasy

Amphetamine/methamphetamine

Cocaine/crack

2.9

1.7

6.7

2.4

0.5

0.4

Min.

5.4

0.9

4.3

0.7

7.1

1.8

1.0

0.0

0.2

0.0

Max.

6.0

3.2

4.5

1.5

1.8

1.5

rates varying across countries, from 4.3 % in Montenegro

and 4.4 % in Serbia to 19 % in Lithuania and 20 % in Estonia.

Boys were more likely than girls to have used e-cigarettes

early in life in the vast majority of countries.

The

largest

gender differences (more than 10 percentage points)

were found in Cyprus, Kosovo, Finland and the Faroes.

The

prevalence rate for boys varied from 4.4 % in Serbia to 23 %

in Finland and Estonia and 24 % in Lithuania, while for girls

the prevalence rate ranged from 3.0 % in Norway and 3.1 %

in Montenegro to 15 % in Lithuania and 16 % in Estonia.

The

ESPAD average prevalence rate for students who

began using e-cigarettes on a daily basis at age 13 or

younger was 1.7 %.

The

highest rates were found in Kosovo

(3.2 %), Cyprus (3.1 %), Slovakia and Ukraine (2.8 % each),

Lithuania (2.7 %) and Bulgaria (2.5 %). Because of the small

proportion of students reporting onset of daily e-cigarette

use at an early age, gender differences were generally less

than 3 percentage points (on average: boys 2.4 %, girls

0.9 %). In all ESPAD countries, the rate of early onset of daily

e-cigarette use was higher for boys than girls.

The

highest

prevalence rates for boys were found in Cyprus (5.4 %) and

Kosovo (5.3 %), while for girls the highest rates were found in

Slovakia (1.8 %) and Lithuania and Iceland (1.7 % each).

(

) Percentage of students using substance at age 13 or younger.

Cigarettes

More than one in six ESPAD students (18 %) had smoked

cigarettes at age 13 or younger (Table 4a).

The

proportions

varied considerably across countries, from 5.4 % in Iceland,

7.4 % in Malta and 8.5 % in Norway to 31 % in Latvia

and 33 % in Lithuania. Both on average and in almost all

participating countries, more boys than girls had smoked

cigarettes at age 13 or younger.

The

largest gender difference

was found in Kosovo and the Faroes (boys 33 % versus

girls 14 %). After Lithuania, which reported the highest

rate among both boys (37 %) and girls (29 %), the highest

proportion among boys was recorded in Latvia (36 %)

and the highest proportions among girls were recorded in

Slovakia (28 %) and Czechia and Latvia (27 % each).

The

ESPAD average rate for students who began smoking

cigarettes on a daily basis at age 13 or younger was 2.9 %.

The

rates were highest in Slovakia (6.0 %) and Bulgaria

(5.8 %) and lowest in the Netherlands (0.9 %), followed by

Iceland, Greece and Slovenia (1.2-1.4 %). Apart from Kosovo,

where the gender difference was 5 percentage points (boys

5.8 % versus girls 0.8 %), because of the small proportion of

students reporting onset of daily smoking at an early age,

gender differences were generally less than 2 percentage

points (ESPAD average: boys 3.4 % versus girls 2.4 %).

Nevertheless, in the majority of countries more boys than

girls reported early onset of daily smoking.

The

countries

with the highest prevalence estimates for boys were Bulgaria

(6.2 %), Kosovo and Latvia (5.8 % each) and Ukraine (5.7 %).

Among girls, Slovakia (5.7 %), Bulgaria (5.5 %) and Romania

(4.8 %) reported the highest rates of early onset of smoking.

Alcohol

One in three ESPAD students (33 %) reported alcohol use at

age 13 or younger (Table 4a).

The

highest rates of students

reporting alcohol use at an early age were found in Georgia

(60 %) and Latvia (48 %).

The

countries with the lowest rates

were Iceland (7.1 %), Kosovo (12 %) and Norway (13 %). In

almost all countries, boys were more likely than girls to have

used alcohol at age 13 or younger, with the highest gender

differences found in Romania (boys 45 % versus girls 27 %),

Georgia (69 % versus 52 %) and Cyprus (45 % versus 29 %).

Notably, in Lithuania, more girls than boys reported early use

of alcohol (girls 36 % versus boys 30 %).

On average, one in 15 ESPAD students (6.7 %) reported

alcohol intoxication at age 13 or younger, with proportions

ranging from 1.8 % in Iceland to 25 % in Georgia. Higher rates

were more likely to be found in the eastern part of Europe

and, in general, more boys than girls reported intoxication at

an early age (ESPAD average: boys 8.0 % versus girls 5.4 ).

The

highest gender difference was found in Georgia (boys

34 % versus girls 18 %).

Illicit drugs

Electronic cigarettes

On average, more than one in 10 ESPAD students (11 %)

had used e-cigarettes at age 13 or younger (Table 4a), with

On average, 2.4 % of the ESPAD students reported that they

had

first

used cannabis at age 13 or younger (Table 4b).

The

highest rates were found in France (4.5 %), Italy (4.4 %),

ESPAD Report 2019

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e situation in 2019

Latvia (3.8 %), Cyprus (3.6 %) and Estonia (3.5 %). Rates of

early onset of amphetamine/methamphetamine use were

lower (ESPAD average: 0.5 %), with the highest rate found

in Bulgaria (1.8 %). Boys were more likely than girls to have

used cannabis or amphetamine/methamphetamine at age

13 or younger, even though gender differences were less

than 4 percentage points. Similar results were found for early

onset of ecstasy and cocaine/crack use.

Table 4a.

Early onset of substance use: prevalence of students experiencing substance use (cigarettes, daily smoking,

e-cigarettes, daily e-cigarettes, alcohol, intoxication) at the age of 13 or younger (percentage)

Daily

smok-

ing

2.5

5.8

4.1

3.0

3.2

2.3

4.8

2.9

2.7

2.6

2.5

1.8

1.3

3.1

1.2

2.4

3.4

3.1

4.4

3.5

1.7

1.9

2.5

0.9

2.6

2.5

3.0

2.7

5.0

1.7

6.0

1.4

2.3

2.2

4.8

2.9

0.9

6.0

Daily

E-ciga-

e-ciga-

rettes

8.6

8.8

8.6

7.2

4.9

4.3

6.8

6.0

–

6.0

7.8

4.4

9.4

4.3

1.5

2.5

2.2

3.1

1.2

2.3

0.8

1.1

1.0

2.0

1.2

1.3

1.7

2.0

2.3

2.1

3.2

1.8

2.7

1.0

1.6

0.7

1.0

0.8

1.8

–

0.7

1.5

0.9

2.8

1.5

1.1

2.1

2.8

1.7

0.7

3.2

Ciga-

rettes

Daily

smoking

E-ciga-

rettes

Daily

e-ciga-

rettes

2.2

3.7

2.9

5.4

1.8

3.4

0.8

1.8

1.1

3.1

1.9

2.1

1.9

2.3

3.6

3.3

5.3

3.0

3.8

1.0

2.4

1.1

1.9

1.3

2.6

0.9

2.2

1.0

3.8

2.2

1.4

2.8

4.3

2.4

0.0

5.4

0.8

1.4

1.3

0.6

0.7

1.3

0.8

0.4

0.9

1.0

0.5

1.5

1.7

1.0

0.7

1.5

0.6

1.7

0.9

0.2

0.3

1.1

0.6

0.9

0.8

1.8

0.9

0.8

1.4

0.9

0.0

1.8

Intoxi-

cation

Country

Ciga-

rettes

5.4

7.4

8.5

5.4

Alco-

hol

7.1

Intoxi-

cation

5.8

8.0

7.1

7.2

5.3

7.4

4.4

3.5

6.8

1.8

5.3

3.9

2.2

9.3

6.6

6.3

2.3

4.6

3.3

6.1

2.9

4.3

4.5

7.0

6.3

6.6

4.4

7.7

6.7

1.8

Alcohol

Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North

Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

6.2

6.8

6.2

8.1

8.7

4.5

8.0

9.4

8.4

5.5

4.5

3.1

6.2

5.2

3.4

3.3

2.4

5.0

3.6

3.3

2.6

4.0

2.2

1.8

3.3

1.2

3.3

3.7

5.8

3.5

1.7

1.4

3.6

1.6

4.1

3.3

3.8

3.3

5.2

2.0

5.3

1.2

1.9

2.7

5.7

3.4

1.2

6.2

1.9

5.5

3.0

2.6

3.0

2.1

4.5

2.3

2.1

2.7

1.3

1.5

0.8

2.8

1.2

1.6

3.1

0.8

3.0

3.4

1.7

2.3

1.4

0.3

1.1

1.7

2.3

2.1

4.8

1.3

5.7

1.6

2.7

1.7

3.9

2.4

0.3

5.7

5.5

9.1

7.4

4.4

0.0

6.4

8.8

8.1

6.5

7.6

9.1

4.9

8.4

3.9

9.0

6.4

8.8

4.5

4.3

3.1

4.6

3.0

4.7

5.1

4.4

6.7

7.9

0.0

8.3

6.1

6.7

6.1

6.2

8.1

6.4

7.9

5.6

5.0

8.2

2.3

7.2

4.8

3.6

6.7

6.3

1.9

7.1

4.4

7.7

3.5

5.0

4.7

9.0

8.4

6.3

4.4

8.2

8.0

1.9

5.3

8.6

5.2

4.6

6.1

4.2

7.0

3.2

2.0

5.3

1.2

3.4

2.8

1.0

8.9

6.5

6.3

2.7

2.0

2.3

4.6

2.3

3.6

4.3

4.5

4.1

4.4

6.9

4.3

7.3

5.4

1.0

ESPAD Report 2019

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e situation in 2019

Table 4b.

Early onset of substance use: prevalence of students experiencing substance use (cannabis, ecstasy,

amphetamine/methamphetamine, cocaine/crack) at the age of 13 or younger (percentage)

Amphetamine/

Cocaine/

Ecstasy

metham-

crack

phetamine

–

1.5

0.7

–

0.2

0.3

0.9

0.0

0.2

–

0.5

0.3

–

0.5

–

0.9

0.5

0.2

0.4

0.6

0.5

0.0

0.6

–

0.6

–

0.7

0.5

0.3

0.4

–

0.3

–

0.1

0.5

0.0

1.5

–

1.8

0.8

–

0.3

0.2

0.6

0.2

0.3

–

0.7

0.5

–

0.6

–

0.8

0.3

0.2

0.4

0.5

0.7

–

0.6

–

1.1

0.4

0.3

0.4

–

0.3

0.2

–

0.2

0.5

0.2

1.8

–

1.5

0.6

–

0.1

0.3

0.6

0.0

0.2

–

0.5

0.1

–

0.6

–

0.7

0.6

0.1

0.2

0.3

0.6

0.2

0.7

–

0.7

–

0.9

0.4

0.3

0.4

–

0.2

0.3

–

0.3

0.4

0.0

1.5

Amphetamine/

metham-

phetamine

Boys

–

2.5

1.0

–

0.1

0.3

0.7

0.4

0.5

–

0.8

0.7

–

0.8

–

1.4

0.4

0.2

0.6

0.8

0.0

1.0

–

0.7

–

1.6

0.4

0.5

–

0.3

–

0.3

0.6

0.0

2.5

Girls

–

1.1

0.5

–

0.4

0.1

0.5

0.0

0.1

–

0.6

0.3

–

0.3

–

0.2

0.3

0.9

0.5

–

0.6

–

0.6

0.4

0.1

0.4

–

0.2

–

0.1

0.4

0.0

1.1

Cannabis

Boys

Girls

1.9

2.7

2.2

2.5

3.1

1.3

3.0

0.4

0.7

2.8

1.3

2.0

0.5

1.0

1.2

2.1

2.7

0.5

2.4

1.7

1.5

2.3

1.3

1.4

0.7

0.8

1.7

1.9

0.5

1.1

3.5

2.7

3.0

0.7

1.3

1.7

0.4

3.5

Ecstasy

Boys

–

2.1

0.9

–

0.1

0.6

1.0

0.0

0.4

–

0.7

0.3

–

0.7

–

1.4

0.7

0.2

0.4

0.8

0.6

0.0

1.0

–

0.8

–

1.1

0.2

0.3

0.5

–

0.4

–

0.1

0.6

0.0

2.1

Girls

–

1.0

0.5

–

0.3

0.1

0.8

0.0

–

0.3

0.4

–

0.3

–

0.4

0.2

0.4

0.3

0.0

0.2

–

0.5

–

0.4

0.7

0.3

–

0.2

0.1

–

0.1

0.3

0.0

1.0

Cocaine/crack

Boys

–

2.2

0.9

–

0.0

0.4

1.0

0.0

0.3

–

0.8

0.0

–

0.8

–

1.2

0.8

0.2

0.4

1.0

0.0

1.0

–

0.8

–

1.2

0.4

0.6

–

0.2

–

0.4

0.6

0.0

2.2

Girls

–

0.8

0.4

–

0.3

0.2

0.3

0.0

–

0.3

0.1

–

0.5

–

0.3

0.5

0.0

0.1

0.2

0.3

0.5

–

0.6

–

0.6

0.4

0.3

0.1

–

0.3

–

0.1

0.3

0.0

0.8

Country

Cannabis

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

2.5

3.0

2.8

3.6

3.2

2.1

3.5

1.0

1.5

4.5

2.7

2.9

1.2

1.3

1.7

3.1

4.4

1.7

3.8

2.0

2.1

2.8

2.1

2.6

1.2

1.3

2.9

2.3

1.0

1.2

3.1

3.2

3.4

1.4

1.7

2.4

1.0

4.5

3.1

3.3

5.1

3.4

2.9

4.1

1.6

2.4

6.2

4.4

3.9

1.9

1.5

2.3

4.3

6.0

3.1

5.0

2.2

2.7

3.4

2.9

3.7

1.6

1.8

4.2

2.7

1.5

1.3

2.7

3.7

3.9

2.1

3.2

1.3

6.2

ESPAD Report 2019

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e situation in 2019

Cigarette use

ESPAD average

Cigarette use (%) (

)

Average

Lifetime

Last 30 days

Min.

5.1

Max.

27 %). Where girls reported higher rates than boys, the

largest gender differences were found in Bulgaria (girls 54 %

versus boys 45 %) and Slovakia (62 % versus 53 %).

Last 30 days

On average, 20 % of the ESPAD students had used

cigarettes during the last 30 days.

The

highest rates of

current smokers were found in Italy and Bulgaria (32 % each)

and Romania (31 %). Countries that reported a last-30-day

prevalence of 10 % or lower included Iceland (5.1 %), Norway

and Malta (10 % each). Italy (31 %), Romania (30 %) and

Croatia (29 %) reported a high smoking rate for boys and

Bulgaria (36 %), Italy (34 %) and Slovakia (33 %) reported

a high smoking rate for girls.

The

average ESPAD rates for

boys and girls were about the same, and the rates for boys

and girls were also similar in most countries. Countries with

noticeably higher rates among boys than girls were Kosovo

(boys 21 % versus girls 11 %), Georgia (17 % versus 7.1 %),

the Faroes (22 % versus 13 %) and Ukraine (25 % versus

18 %). Rates were higher among girls than boys in Bulgaria

(girls 36 % versus boys 27 %), Slovakia (33 % versus 26 %)

and Spain (25 % versus 18 %).

(

) Percentage of students reporting use of cigarettes.

Lifetime

On average, 41 % of students in ESPAD countries had

ever smoked cigarettes, with the lifetime prevalence rate

ranging from 15 % in Iceland to 58 % in Slovakia (Table 5).

In 10 of the 35 ESPAD countries, at least half of the

students had tried cigarette smoking in their lifetime.

The

average prevalence of cigarette smoking was slightly higher

among boys (43 %) than girls (40 %). In about half of the

participating countries, boys were generally more likely

than girls to have tried cigarettes. Countries with the largest

gender differences were the Faroes (boys 57 % versus girls

34 %), Kosovo (53 % versus 31 %) and Georgia (46 % versus

ESPAD Report 2019

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e situation in 2019

Table 5.

Country

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

Cigarette use: prevalence of lifetime and 30-day use (percentage)

Lifetime use

30-day use

5.1

Lifetime use

Boys

Girls

30-day use

Boys

4.3

9.5

4.3

Girls

7.1

5.9

7.9

5.9

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

ESPAD Report 2019

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e situation in 2019

E-cigarette use

ESPAD average

E-cigarette use (%) (

)

Average

Lifetime

Last 30 days

Min.

5.4

Max.

Except for Iceland, Malta, Romania, Slovakia and Bulgaria,

boys were generally more likely than girls to have tried

e-cigarettes, with gender differences ranging between 5

percentage points in Poland and Serbia and 28 percentage

points in Kosovo.

Last 30 days

On average, 14 % of students in ESPAD countries had used

e-cigarettes during the last 30 days. In 11 countries the

last-30-day prevalence was less than 10 %, with the lowest

prevalence observed in Serbia (5.4 %).

The

highest rate was

found in Monaco (41 %), followed by Lithuania (31 %) and

Poland (30 %).

Concerning gender differences, on average the 30-day

prevalence for boys (16 %) was higher than that for

girls (11 %).

This

pattern was confirmed in most ESPAD

participating countries, with the most noticeable difference

found in Kosovo (17 % for boys versus 4.7 % for girls). Iceland

was the only country where the last-30-day prevalence of

e-cigarette use was slightly higher among girls than boys

(18 % for girls versus 15 % for boys).

(

) Percentage of students reporting use of e-cigarettes.

Lifetime

Lifetime prevalence rates for the use of e-cigarettes ranged

between 18 % and 65 %, with an ESPAD country average of

40 % (Table 6).

In nine of the 35 ESPAD countries more than half of the

students had tried e-cigarettes at least once.

These

high-

prevalence countries are predominantly located in the

eastern part of Europe.

The

highest prevalence rate was found in Lithuania (65 %),

followed by Monaco (63 %) and Czechia (60 %).

The

lowest

rates were found in Serbia (18 %) and Montenegro (20 %).

ESPAD Report 2019

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e situation in 2019

Table 6.

Country

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

E-cigarette use: prevalence of lifetime and 30-day use (percentage)

Lifetime use

30-day use

Boys

8.3

7.5

6.7

7.1

7.0

9.3

7.1

6.1

5.4

9.4

6.2

5.4

Girls

Boys

9.5

7.7

9.2

8.2

6.9

8.3

6.9

Girls

9.2

8.9

7.5

4.7

5.4

3.6

7.6

4.7

6.5

4.3

8.0

5.0

6.6

4.4

4.0

8.0

7.9

4.1

8.4

3.6

30-day use

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

ESPAD Report 2019

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e situation in 2019

Alcohol use

ESPAD average

Alcohol use (%) (

)

Average

Lifetime

Last 30 days

Intoxication (

)

Min.

2.7

Max.

Last 30 days

Overall, 47 % of the students in ESPAD countries reported

alcohol use during the 30 days prior to the survey. In

Hungary, Greece, Czechia, Austria, Germany and Denmark

more than three

fifths

(61-74 %) had consumed alcohol in

the last 30 days. Particularly low prevalence rates were found

in Kosovo (10 %) and Iceland (11 %). Low rates (30 % or less)

were also reported for most of the Nordic countries (25 %

each for Sweden and Norway and 30 % for Finland), as well

as for Lithuania (27 %). On average, no gender difference

in alcohol use during the last 30 days was found (47 % for

boys versus 46 % for girls). At the country level, particularly

large gender differences, with higher rates for boys than girls

(differences of more than 10 percentage points), were found

in Romania, Georgia, Kosovo and Montenegro. Conversely,

higher rates were found among girls than boys in Latvia and

Ukraine (difference of 10 percentage points).

(

) Percentage of students reporting use of alcohol.

(

) Percentage of students having been intoxicated at least once in the

last 30 days.

Lifetime

In all ESPAD countries except in Kosovo (29 %) and Iceland

(37 %), over half of the students reported consuming alcohol

at least once during their lifetime (Table 7).

The

ESPAD

average was 79 % (range 29-95 %).

The

highest rates of

lifetime alcohol use (more than 90 %) were found in Hungary,

Denmark and Czechia. In addition to Kosovo and Iceland, the

countries with the lowest rates (less than 60 %) were Norway

and Sweden.

The

largest difference between boys and girls

was observed in Kosovo (41 % for boys versus 18 % for girls).

In 16 countries the rate for girls was higher than that for

boys, particularly in Lithuania (83 % for girls versus 75 % for

boys) and Ukraine (89 % versus 81 %).

Intoxication

An average of 13 % of the ESPAD students reported having

been intoxicated in the last 30 days prior to the survey.

Denmark had the highest prevalence, with two

fifths

of the

students (40 %) reporting intoxication. Kosovo, Iceland,

Lithuania, Montenegro, Estonia, Norway, North Macedonia

and Sweden had rates of less than 10 %. On average,

slightly more boys (14 %) than girls (13 %) reported that they

had been intoxicated in the last 30 days, with the highest

differences found in Serbia (15 % for boys versus 10 %

for girls) and Montenegro (10 % versus 4.7 %). In Spain

noticeably more girls than boys reported intoxication in the

last 30 days (19 % for girls versus 14 % for boys).

ESPAD Report 2019

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e situation in 2019

Table 7.

Alcohol use: prevalence of lifetime use, 30-day use and intoxication (percentage)

Intoxication,

last 30 days

8.4

3.8

2.7

6.7

7.6

8.7

8.6

9.4

2.7

Lifetime use

Boys

Girls

30-day use

Boys

9.4

Girls

5.2

Intoxication,

last 30 days

Boys

7.9

3.1

4.1

7.4

9.1

8.1

8.5

3.1

Girls

8.6

8.9

4.5

1.5

6.0

4.7

8.2

9.1

7.3

1.5

Country

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

Lifetime use

30-day use

ESPAD Report 2019

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e situation in 2019

Illicit drug use

ESPAD average

Lifetime use of illicit drugs (%) (

)

Drug

Any illicit drug

Cannabis

Ecstasy

Amphetamine

Methamphetamine

Cocaine

Crack

LSD or other hallucinogens

Heroin

GHB

Average

2.3

1.7

1.1

1.9

1.1

2.1

0.9

0.7

Min.

4.2

2.9

0.9

0.5

0.4

0.5

0.2

0.8

0.4

0.2

Max.

5.2

3.4

2.5

3.8

3.1

4.9

2.6

2.2

Cannabis use

Cannabis was the most widely used illicit drug in all ESPAD

countries. On average, 16 % of students had used cannabis

at least once in their lifetime (Table 8a).

The

countries with

the highest prevalence of cannabis use were Czechia (28 %),

Italy (27 %) and Latvia (26 %).

The

lowest levels of cannabis

use (2.9-7.3 %) were reported in Kosovo, North Macedonia,

Iceland and Serbia. On average, boys reported cannabis use

to a larger extent than girls (boys 18 % versus girls 13 %).

This

was the case in nearly all countries except for Bulgaria,

Slovakia, Malta, the Netherlands and Czechia, where rates

were about the same for boys and girls.

The

largest gender

differences (more than 10 percentage points, with higher

rates among boys) were found in Georgia and Monaco.

Other illicit drug use

Some students had also used other illicit substances,

although their rates of use were substantially lower than

those for cannabis.

The

most widely used illicit drugs

were ecstasy, amphetamine, cocaine and LSD or other

hallucinogens (Table 8a and b). In the case of illicit

drugs other than cannabis, on average, about 5.0 % of

the ESPAD students reported having used them at least

once during their lifetime. Lifetime prevalence rates for

methamphetamine, crack, heroin and GHB were lower than

those for the other illicit drugs (about 1.0 % on average). At

the country level, higher rates of lifetime use (about 5.0 %)

were found in Estonia and Latvia for ecstasy and LSD or

other hallucinogens.

The

most marked gender differences

were found in Cyprus for the use of methamphetamine

(5.2 % for boys and 0.4 % for girls), cocaine (6.3 % for boys

versus 1.8 % for girls) and heroin (5.6 % for boys versus 0.3 %

for girls).

(

) Percentage of students reporting use of illicit drugs.

Any drug use

Lifetime use of illicit drugs varied considerably across the

ESPAD countries (Table 8a). On average, 17 % of ESPAD

students reported having used any illicit drug at least once.

The

highest percentage of students reporting lifetime use

of any illicit drug was found in Czechia (29 %), followed by

Italy (28 %), Latvia (27 %) and Slovakia (25 %). Particularly

low levels (10 % or less) of illicit drug use were noted in

Kosovo, Iceland, North Macedonia, Ukraine, Serbia, Sweden,

Norway, Greece and Romania. On average, 19 % of boys and

14 % of girls had used illicit drugs at least once during their

lifetime. In most ESPAD countries, the prevalence rate was

higher among boys than girls. Noticeable gender differences

were found in Georgia (24 % for boys versus 8.8 % for girls),

Monaco (29 % versus 17 %), Cyprus (17 % versus 7.0 %) and

Ireland (25 % versus 15 %).

ESPAD Report 2019

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e situation in 2019

Table 8a.

Illicit drug use: lifetime prevalence of the use of any drug, cannabis, ecstasy, amphetamine and

methamphetamine (percentage)

Am-

phet-

amine

2.2

3.1

1.9

2.4

1.2

1.5

2.7

1.4

1.5

1.0

2.0

1.1

3.3

1.8

2.0

1.1

0.8

1.8

1.3

0.8

2.1

2.0

1.4

0.6

1.6

3.4

1.7

0.5

1.7

1.3

1.0

1.8

1.4

1.7

0.5

3.4

Meth-

am-

phet-

amine

1.0

2.2

1.3

2.5

1.5

0.6

1.5

0.4

0.6

1.3

0.8

0.7

1.0

0.8

1.6

0.8

1.0

0.9

1.3

0.7

0.4

–

2.4

1.1

0.6

1.2

1.3

2.0

0.8

1.0

1.1

0.4

2.5

Any drug

Boys

8.1

7.1

Girls

7.0

8.8

6.2

6.5

1.6

7.7

5.1

6.4

8.6

7.6

6.7

7.4

1.6

Cannabis

Boys

7.2

5.5

11.4

8.2

9.8

8.1

9.1

5.5

Girls

5.0

8.5

9.4

6.8

5.2

5.7

0.7

7.3

4.2

6.1

7.6

6.6

5.7

6.8

0.7

Ecstasy

Boys

2.4

2.6

2.2

4.4

3.5

2.0

5.2

1.6

1.7

2.2

2.5

1.8

1.7

3.4

1.4

3.7

1.7

1.4

5.0

2.7

1.3

1.4

3.4

3.6

1.1

2.2

3.4

3.9

1.3

1.9

2.5

3.1

0.9

2.5

1.6

2.5

0.9

5.2

Girls

2.9

2.6

2.0

1.8

3.8

1.2

5.3

1.2

1.0

1.2

1.9

2.0

0.5

3.2

1.2

2.0

0.8

0.9

5.0

3.3

0.9

2.3

2.0

3.4

1.1

1.2

1.8

2.6

1.1

2.3

3.9

2.8

0.9

1.2

0.6

2.1

0.5

5.3

Amphetamine

Boys

2.4

3.2

2.1

4.6

0.9

1.9

2.6

2.0

1.2

1.6

2.1

1.7

4.1

1.8

2.8

1.2

1.3

2.0

1.6

1.1

2.0

2.4

2.2

0.7

2.1

3.6

1.8

0.7

2.1

0.9

1.2

1.0

2.4

1.8

2.0

0.7

4.6

Girls

2.0

3.0

1.7

0.6

1.4

1.1

2.9

0.8

1.0

1.7

0.5

1.9

0.6

2.6

1.9

1.3

1.0

0.3

1.6

0.9

0.5

2.3

1.6

0.6

0.4

1.0

3.2

1.6

0.3

1.3

1.7

1.3

0.9

1.1

1.2

1.4

0.3

3.2

Metham-

phetamine

Boys

1.1

2.4

1.3

5.2

1.3

0.8

1.5

0.8

1.3

1.5

0.6

1.7

1.1

0.9

2.6

1.1

1.4

1.2

1.1

1.0

0.5

1.6

1.1

0.6

–

2.4

1.2

0.7

1.6

1.0

2.1

1.0

1.2

1.4

0.5

5.2

Girls

0.8

2.1

1.3

0.4

1.6

0.3

1.5

0.0

0.4

1.3

0.3

0.8

0.5

0.9

0.8

0.7

0.6

0.7

0.9

0.7

1.4

1.1

0.3

0.1

–

2.3

1.1

0.6

0.9

1.7

2.0

0.6

0.9

0.0

2.3

Country

Any

drug

9.4

7.3

4.2

7.3

9.4

9.5

8.6

9.2

8.6

4.2

Can-

nabis

8.4

9.4

8.2

6.4

2.9

9.3

6.1

8.7

7.3

8.0

7.9

2.9

Ec-

stasy

2.6

2.1

2.9

3.6

1.6

5.2

1.4

1.3

1.7

2.2

1.9

1.1

3.3

1.3

2.8

1.3

1.1

5.0

3.0

1.1

1.9

2.7

3.5

1.1

1.7

2.6

3.2

1.2

2.1

3.3

2.9

0.9

1.8

1.1

2.3

0.9

5.2

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North

Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

ESPAD Report 2019

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e situation in 2019

Table 8b.

Illicit drug use: lifetime prevalence of the use of cocaine, crack, LSD or other hallucinogens, heroin and GHB

(percentage)

LSD or

other hal-

lucinogens

2.2

2.4

1.9

2.3

3.5

1.5

4.8

1.2

1.1

1.9

2.3

1.3

1.7

1.4

2.7

1.2

0.8

4.9

2.6

1.3

2.6

2.0

1.8

0.8

1.7

2.6

1.8

1.7

1.5

4.1

3.2

1.2

1.8

1.1

2.1

0.8

4.9

Cocaine

Heroin

0.6

1.7

1.3

2.6

0.5

0.4

0.8

1.2

0.4

1.1

1.0

0.6

1.0

0.8

1.2

0.8

0.6

0.8

1.2

1.6

0.5

0.9

1.5

1.1

0.7

1.1

0.7

0.6

0.9

0.4

2.6

GHB

Boys

1.1

1.4

0.7

2.2

0.2

0.5

0.9

0.4

0.2

1.0

0.6

1.4

0.6

1.2

0.4

1.1

0.5

0.6

0.3

0.5

0.4

1.2

0.7

0.8

0.2

1.0

0.9

0.6

0.4

0.8

0.3

0.6

0.5

0.6

0.3

0.7

0.2

2.2

3.7

2.4

6.3

1.6

2.5

2.7

0.8

1.1

2.5

2.0

1.5

2.3

2.6

1.6

4.6

2.3

0.9

1.7

2.1

2.4

3.9

2.0

1.5

2.2

2.1

1.4

1.9

0.8

3.0

2.1

2.3

1.1

2.2

0.8

6.3

Girls

2.3

2.6

1.9

1.8

1.6

1.4

2.1

1.2

0.7

2.8

0.7

1.1

0.7

2.4

1.3

2.0

2.3

0.2

1.9

2.2

1.8

2.3

2.0

1.4

0.3

0.9

2.3

2.2

1.2

1.5

2.8

2.1

0.7

0.8

1.6

0.2

2.8

Boys

0.9

2.2

1.4

5.6

0.8

1.1

1.3

2.0

–

2.6

1.4

0.4

1.6

1.0

0.6

2.4

1.9

1.0

–

1.3

1.7

1.0

1.9

1.1

0.4

–

1.4

1.9

0.6

1.5

0.7

1.0

1.1

1.4

1.2

1.4

0.4

5.6

Girls

0.7

1.1

0.9

1.2

0.8

1.1

0.4

–

1.5

0.3

0.1

0.3

0.6

0.8

1.2

0.8

0.2

–

0.6

0.7

1.8

0.8

0.2

0.0

–

0.5

1.2

0.6

0.3

0.8

0.7

0.6

0.4

0.7

0.0

1.8

Crack

LSD or other

hallucinogens

Boys

2.4

2.7

2.2

3.1

3.3

2.0

6.1

1.2

1.3

1.4

3.0

2.9

1.9

2.0

1.9

3.5

1.4

1.0

5.1

2.7

1.8

1.9

2.4

2.5

1.0

2.3

3.2

2.1

2.0

1.5

3.5

1.4

2.5

1.2

2.4

1.0

6.1

Girls

2.0

2.1

1.5

1.8

3.7

1.1

3.5

1.2

0.8

1.0

1.8

0.6

1.4

1.0

1.9

0.8

0.5

4.7

2.4

0.8

3.2

1.7

1.1

0.5

1.1

2.1

1.5

1.4

1.5

4.7

2.9

1.0

1.1

1.0

1.7

0.5

4.7

Heroin

Boys

0.8

2.2

1.5

5.6

0.6

0.9

1.6

0.5

1.3

1.7

0.8

1.3

0.9

0.8

1.6

0.8

1.0

0.4

0.7

1.0

1.4

2.1

0.9

1.5

1.7

1.2

0.6

1.5

0.6

0.4

0.8

1.1

0.8

1.2

0.4

5.6

Girls

0.5

1.3

1.1

0.3

0.5

0.2

0.7

0.8

0.2

0.9

0.4

0.7

1.1

0.8

0.7

0.2

1.1

0.8

0.7

0.9

1.2

0.2

0.1

0.3

1.4

1.0

0.7

0.8

0.7

1.0

0.5

0.1

0.4

0.7

0.1

1.4

GHB

Boys

1.0

2.2

0.9

4.0

0.2

0.8

0.4

1.6

1.1

1.0

1.3

1.4

0.5

1.6

0.8

0.3

0.6

0.5

1.4

1.0

0.8

0.2

1.5

1.6

0.7

1.1

0.5

0.4

0.8

1.0

0.3

1.0

0.2

4.0

Girls

1.2

0.6

0.5

0.7

0.2

0.9

0.4

0.1

0.4

0.2

1.9

0.0

1.0

0.3

0.6

0.2

0.4

0.3

0.9

0.5

0.8

0.2

0.4

0.2

0.6

0.2

0.6

0.1

0.7

0.3

0.2

0.5

0.0

1.9

Country

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North

Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

Cocaine Crack

2.2

3.1

2.2

3.8

1.6

1.9

2.3

1.0

0.9

2.7

1.3

1.5

2.5

1.4

3.3

2.3

0.5

1.8

2.2

2.0

2.3

2.9

1.7

0.9

1.6

2.3

2.1

1.8

1.5

1.2

2.9

2.1

1.5

0.9

1.9

0.5

3.8

0.8

1.7

1.2

3.1

0.8

0.9

1.2

–

2.1

0.8

0.3

0.9

0.8

0.7

1.8

1.4

0.6

–

0.9

1.2

1.4

0.6

0.2

–

0.9

1.5

0.6

1.0

0.5

0.9

1.0

0.8

1.1

0.2

3.1

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e situation in 2019

Other substance use

Inhalant use

ESPAD average

Lifetime use (%) (

)

Average

Inhalants

NPS

Pharmaceuticals

7.2

3.4

9.2

Min.

0.5

0.9

2.8

Max.

6.6

(

) Percentage of students reporting use.

The

ESPAD average for lifetime inhalant use was 7.2 %, with

large differences between countries (Table 9).

The

country with

the highest proportion of students who had tried inhalants

was Latvia (16 %), followed by Germany and Croatia (15 %

respectively).

The

lowest proportion was found in Kosovo

(0.5 %), followed by North Macedonia (1.9 %), Italy (2.0 %),

Bulgaria (2.3 %) and Spain (2.5 %).

The

average prevalence

of lifetime inhalant use among ESPAD students was almost

the same for boys and girls. Similar rates for both genders

were found in most countries. A 5-percentage-point gender

difference was reported in Monaco (10 % for boys versus 5.0 %

for girls) and Croatia (17 % for girls versus 12 % for boys).

Table 9.

Country

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

Inhalants, new psychoactive substances (NPS) and pharmaceuticals: prevalence of lifetime use (percentage)

Inhalants

2.3

6.6

4.9

5.4

6.3

5.7

6.2

4.9

6.5

2.8

2.0

0.5

8.4

5.3

7.5

6.1

7.1

1.9

4.5

8.4

4.5

2.8

6.1

8.2

2.5

9.2

7.2

0.5

NPS

4.0

3.2

5.1

3.6

6.0

2.0

6.6

3.9

0.9

–

2.8

3.8

2.8

3.7

1.8

4.7

3.1

1.5

6.4

5.6

3.0

4.7

2.6

1.5

1.0

3.1

5.9

0.9

3.2

1.8

3.6

4.3

1.8

2.1

3.2

3.4

0.9

6.6

Pharma-

ceuticals

8.0

4.3

7.2

6.6

4.1

9.5

8.2

3.9

8.0

7.9

7.6

4.7

5.9

7.2

8.7

5.6

7.4

6.9

7.1

5.1

4.6

7.8

2.8

9.2

2.8

Inhalants

Boys

3.0

7.7

5.1

6.5

8.4

5.5

6.3

5.1

6.8

2.8

2.0

0.6

5.5

6.4

8.4

2.3

5.1

7.9

4.3

2.6

5.0

7.0

3.0

7.3

0.6

Girls

1.6

5.8

4.7

4.3

4.2

5.9

6.1

4.7

6.2

2.7

2.0

0.3

7.1

5.1

5.0

5.8

5.9

1.5

4.0

8.8

4.6

3.0

7.0

9.3

2.0

7.1

0.3

Boys

3.8

3.1

5.1

4.6

5.8

2.2

7.0

3.2

0.9

–

4.6

2.9

4.1

3.8

2.1

6.6

2.5

2.9

5.1

4.8

2.8

4.8

3.1

2.2

1.1

3.7

6.1

0.9

2.8

1.9

2.3

3.4

1.6

2.4

2.7

3.4

0.9

7.0

NPS

Girls

4.2

3.2

5.1

2.8

6.2

1.8

6.3

4.6

0.9

–

1.2

4.7

1.6

3.6

1.6

2.9

3.8

0.3

7.8

6.3

3.2

4.5

2.0

0.8

1.0

2.4

5.8

0.9

3.5

1.7

4.7

5.2

1.9

1.7

3.6

3.3

0.3

7.8

Pharmaceuticals

Boys

7.1

5.0

5.2

6.4

4.0

7.4

7.7

4.1

6.7

8.5

8.9

7.2

7.8

3.6

5.7

5.5

7.2

4.1

7.2

5.3

8.2

4.5

3.5

4.2

6.4

2.1

7.4

2.1

Girls

8.9

3.6

9.4

6.7

4.2

8.6

3.7

13.4

7.4

8.5

7.5

5.9

6.0

6.4

7.3

7.1

7.5

8.3

9.4

6.6

4.9

9.2

3.4

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

ESPAD Report 2019

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e situation in 2019

New psychoactive substance use

ESPAD average

Lifetime use of NPS (%) (

)

Average

NPS

Synthetic cannabinoids (

)

Synthetic cathinones (

)

3.4

3.1

1.1

Min.

0.9

1.1

0.2

Max.

6.6

5.2

2.5

(

) Percentage of students reporting use of NPS.

(

) Average calculated in 20 out of 35 ESPAD countries.

(

) Average calculated in 19 out of 35 ESPAD countries.

The

ESPAD average for lifetime NPS use was 3.4 % (Table 9),

with the highest rates reported in Estonia (6.6 %) and

Latvia (6.4 %) and the lowest rates reported in Finland,

Portugal and North Macedonia (about 1 %).

The

average

prevalence of lifetime use was the same for boys and girls.

Gender differences within ESPAD countries were generally

small, with an average difference of 0.1 % and a difference

of over 2 percentage points in only six countries. When

asking students specifically about the consumption of

synthetic substances, 3.1 % of the ESPAD students (average

calculated in 20 countries out of 35) reported having used

synthetic cannabinoids at least once in their lifetime, ranging

from 1.1 % in Slovakia to 5.2 % in France (Table 10a).

Similarly, 1.1 % of the ESPAD students reported lifetime use

of synthetic cathinones (average calculated in 19 countries

out of 35), with the highest rates found in Ireland (2.5 %)

and Cyprus (2.4 %) (Table 10a). On average, boys had

a slightly higher prevalence of use than girls for synthetic

cannabinoids (boys 3.5 % versus girls 2.7 %) and synthetic

cathinones (boys 1.4 % versus girls 0.8 %), even though

no noticeable gender differences were found for individual

countries for either synthetic cannabinoid use or synthetic

cathinone use.

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

e situation in 2019

Table 10a.

New psychoactive substances (NPS): lifetime prevalence of the use of synthetic cannabinoids and synthetic

cathinones (percentage)

Synthetic

cannabinoids

3.7

4.3

2.9

4.2

–

5.2

1.3

2.6

3.3

4.9

–

1.7

2.8

–

1.9

4.3

4.0

4.7

–

1.4

–

1.8

3.9

–

1.1

–

1.8

–

3.1

1.1

5.2

Synthetic

cathinones

1.3

1.8

–

2.4

–

0.4

0.8

1.1

0.8

1.9

–

2.5

0.4

–

1.1

0.9

0.6

0.2

–

0.8

–

0.9

1.2

–

0.4

–

0.6

–

1.1

0.2

2.5

Synthetic cannabinoids

Boys

Girls

4.8

2.6

4.4

4.2

3.0

2.8

5.3

3.3

–

5.2

5.1

2.2

0.5

2.1

3.1

4.6

2.1

4.7

5.2

–

2.4

1.0

3.0

2.5

–

1.8

1.9

4.0

4.5

3.4

4.5

6.2

3.2

–

1.7

1.2

–

2.7

1.1

4.2

3.7

–

1.5

0.7

–

2.0

1.6

–

3.5

1.5

6.2

2.7

0.5

5.2

Synthetic cathinones

Boys

Girls

1.9

0.6

2.3

1.3

–

4.2

1.0

–

0.7

0.2

1.6

0.2

1.2

1.0

1.3

0.2

2.2

1.7

–

2.7

2.3

0.6

0.3

–

0.7

1.5

1.1

0.7

0.5

0.0

–

0.9

0.7

–

1.2

0.6

1.1

1.2

–

0.5

0.3

–

0.9

0.4

–

1.4

0.5

4.2

0.8

0.0

2.3

Country

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

e situation in 2019

Pharmaceutical use for non-medical purposes

ESPAD average

Lifetime use of pharmaceuticals for non-medical purposes (%) (

)

Average

Pharmaceuticals

Tranquillisers or sedatives

without a prescription

Painkillers to get high

Anabolic steroids

9.2

6.6

4.0

1.0

Min.

2.8

1.7

0.8

0.3

Max.

2.7

Lithuania (20 %).

The

lowest levels of non-prescription use

of tranquillisers or sedatives (approximately 2.0 %) were

reported by students from Ukraine, Romania, Bulgaria and

Croatia. On average, more girls than boys reported the use of

tranquillisers or sedatives without prescription (8.0 % for girls

versus 5.1 % for boys).

The

highest gender differences were

found in Lithuania, Latvia and Poland, where more girls than

boys had used non-prescription tranquillisers or sedatives,

with differences of more than 10 percentage points.

(

) Percentage of students reporting use of pharmaceuticals.

Painkillers

On average, the use of painkillers in order to get high was

reported by 4.0 % of the ESPAD students.

The

countries

with the highest prevalence rates were Slovakia (18 %) and

Czechia (10 %). Like tranquillisers, slightly more girls (4.8 %)

than boys (3.3 %) reported lifetime use of painkillers. A large

gender difference was found in Slovakia (24 % for girls

versus 13 % for boys).

The

ESPAD average for lifetime pharmaceutical use for

non-medical purposes was 9.2 %, ranging from 2.8 % to

23 % (Table 10b).

The

highest proportion of students who

had used pharmaceuticals for non-medical purposes was

found in Slovakia (23 %), followed by Latvia (22 %) and

Lithuania (21 %).

The

lowest rates were found in Ukraine

(2.8 %), Georgia (3.9 %), the Faroes (4.1 %), Bulgaria (4.3 %),

Spain (4.6 %) and Italy (4.7 %). Both on average and in the

vast majority of the ESPAD countries, girls were more likely

than boys to have tried pharmaceuticals for non-medical

purposes.

The

highest gender differences were reported in

Lithuania (29 % for girls versus 12 % for boys) and Latvia,

Slovakia and Poland (more than 10 percentage points).

Anabolic steroids

Few students in the participating countries reported the use

of anabolic steroids (ESPAD average: 1.0 %).

The

highest

rate was found in Montenegro (2.7 %), followed by Cyprus,

Bulgaria, Malta, Poland and Ireland (about 2.0 %). In general,

slightly more boys than girls reported use of anabolic

steroids, even though no appreciable gender differences

were seen within individual countries except for Cyprus,

Bulgaria and Greece.

Tranquillisers and sedatives without a doctor’s

prescription

The

use of tranquillisers or sedatives without a doctor’s

prescription was most prevalent in Latvia (21 %) and

ESPAD Report 2019

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e situation in 2019

Table 10b.

Pharmaceuticals: lifetime prevalence of the use of painkillers to get high, tranquillisers or sedatives without

prescription and anabolic steroids (percentage)

Tranquillisers/

sedatives

5.6

2.0

2.3

6.6

4.7

2.7

7.1

6.4

3.1

7.7

3.5

7.6

6.8

2.6

4.3

4.5

3.1

5.9

8.3

4.2

5.8

6.0

1.7

5.8

3.8

4.0

6.4

1.7

6.6

1.7

Painkillers

4.3

2.5

5.7

6.3

3.2

3.8

2.9

4.8

3.3

1.0

4.4

5.0

6.7

3.0

5.4

0.8

2.3

3.2

2.1

2.6

2.8

2.4

1.3

2.0

3.3

6.4

1.8

9.3

3.1

2.1

1.1

2.8

1.4

4.0

0.8

Anabolic

steroids

0.7

2.4

1.5

2.4

0.7

0.6

0.8

0.6

0.3

0.5

1.0

0.4

1.2

0.9

0.7

1.9

0.8

0.7

0.8

1.4

2.1

0.7

2.7

0.3

0.6

1.0

2.0

0.8

0.5

1.1

0.9

0.5

0.4

0.8

0.4

1.0

0.3

2.7

Tranquillisers/

sedatives

Boys

Girls

5.3

5.9

2.2

1.7

1.4

3.2

7.3

6.1

5.2

7.9

4.1

5.2

2.8

2.7

5.9

8.4

5.9

6.9

3.2

3.1

4.9

4.0

3.1

6.0

9.3

6.2

7.3

2.9

2.4

3.0

5.6

4.2

4.8

2.5

3.8

6.3

5.5

8.5

7.2

9.4

2.5

5.9

5.7

5.9

9.2

4.4

7.4

1.6

1.8

3.6

7.9

6.5

2.8

4.8

3.5

4.4

5.3

7.5

1.2

2.2

5.1

1.2

8.0

1.7

Painkillers

Boys

3.8

2.7

3.7

6.0

7.1

3.3

2.8

3.2

3.1

2.9

1.5

2.9

5.0

4.9

2.5

4.8

1.0

2.5

1.9

1.4

2.7

2.4

2.2

1.3

1.6

3.1

4.1

1.2

7.1

1.8

1.0

1.3

2.9

1.3

3.3

1.0

Girls

4.8

2.4

7.9

6.5

3.0

4.6

2.7

6.4

3.8

0.5

5.8

5.0

8.6

3.5

6.0

0.6

2.2

4.6

2.7

2.5

3.2

2.7

1.4

2.3

3.4

8.5

2.3

4.3

3.1

0.9

2.7

1.5

4.8

0.5

Anabolic steroids

Boys

1.1

3.7

1.9

4.7

0.9

1.1

0.7

1.2

0.5

0.9

1.5

0.4

2.3

1.3

0.9

2.7

1.5

0.8

0.7

1.8

2.6

1.0

3.1

0.5

0.6

1.7

2.4

1.1

0.9

1.3

1.4

0.7

0.6

1.3

0.6

3.3

1.0

Girls

0.3

1.1

0.7

0.5

0.1

0.8

0.0

0.1

0.2

0.7

0.4

0.2

0.6

0.5

1.2

0.2

0.7

1.0

1.1

1.5

0.5

2.3

0.2

0.5

0.3

1.7

0.6

0.1

1.0

0.4

0.3

0.2

0.3

0.6

0.0

2.3

Country

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

e situation in 2019

Patterns of current use

Daily smoking

Overall, 10 % of the ESPAD students had smoked cigarettes

every day in the last 30 days (Figure 1a). When considering

both cigarettes and e-cigarettes this proportion was 12 %

(see Additional Table 104). Daily cigarette smoking ranged

from 1.9 % in Iceland and 2.5 % in Norway to 22 % in

Bulgaria. High rates of daily smoking were also found in

Croatia and Italy (19 % each) and Romania, Slovakia and

Hungary (18 % each). No differences were found in the

country average rates of daily smoking between boys and

girls (10 %), while slight gender differences were seen when

considering both cigarette smoking and e-cigarette smoking

(13 % for boys versus 11 % for girls) (see Additional Table

104). At the country level, significant gender differences in

daily cigarette use (p < 0.05) were found, with higher rates in

boys than girls in Kosovo, Georgia, Ukraine, North Macedonia,

Montenegro, Ireland, the Netherlands, Norway and Greece,

and with higher rates in girls than boys in Bulgaria, Slovakia,

Spain, Hungary and Sweden (Figure 1b).

Figure 1a.

Daily cigarette use: prevalence in the last 30 days (percentage)

≤

4.9 %

5.0-9.5 %

9.6-14 %

15-19 %

≥

20 %

Non-participating country

or data not available

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

e situation in 2019

Figure 1b.

Daily cigarette use: prevalence in the last 30 days by gender (percentage)

Boys

All students

Bulgaria

(22)

Croatia

(19)

Italy

(19)

8.8

8.5

9.2

9.1

8.4

7.1

9.1

6.5

3.9

3.4

5.4

7.2

5.4

4.0

3.9

6.1

3.4

1.4

2.0

Girls

Two-sample proportion

test (p-value)

0.00

0.49

0.91

0.04

0.93

0.00

0.47

0.35

0.11

0.27

0.00

0.39

0.31

0.65

0.00

0.89

0.97

0.00

0.57

0.00

0.10

0.37

0.09

0.00

0.18

0.14

0.96

0.04

0.01

0.04

0.50

0.00

0.68

9.4

9.2

7.2

9.2

9.0

6.7

9.1

8.4

6.1

5.5

6.6

6.5

4.2

3.8

3.6

1.8

Hungary

(18)

Romania

(18)

Slovakia

(18)

Austria

(12)

France

(12)

Latvia

(12)

Serbia

(12)

Ukraine

(12)

North Macedonia

(11)

Poland

(11)

Czechia

(10)

Denmark

(10)

Montenegro

(10)

Slovenia

(9.3)

Estonia

(9.2)

Spain

(9.0)

Germany

(8.8)

Greece

(8.1)

Lithuania

(8.0)

Monaco

(7.9)

Cyprus

(7.6)

Georgia

(7.5)

Kosovo

(7.1)

Faroes

(6.9)

Finland

(6.7)

Portugal

(5.5)

Netherlands

(5.3)

Ireland

(5.2)

Sweden

(5.1)

Malta

(3.6)

Norway

(2.5)

Iceland

(1.9)

Colour indicates signi cant

difference between

boys

and

girls

Statistical signi cance levels are reported for each country.

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

e situation in 2019

Electronic cigarette current use

On average, 14 % of the ESPAD students reported the

use of e-cigarettes in the last 30 days (Figure 2a). Current

e-cigarette use ranged from 5.4 % in Serbia to 41 % in

Monaco. High rates of current users were also found in

Lithuania (31 %) and Poland (30 %).

With regard to the frequency of use in the last 30 days,

overall, 10 % of students reported e-cigarette use less than

once per week, 4.1 % reported use at least once a week and

3.1 % reported use almost every day or every day, with the

highest rate of daily or almost daily use reported in Lithuania

(14 %).

Noticeable gender differences in e-cigarette use were found

in the majority of ESPAD countries, with average rates of

17 % in boys and 11 % in girls.

The

highest gender difference

was found in Kosovo, where 17 % of boys reported use of

e-cigarettes in the last month compared with 4.7 % of girls

(Figure 2b).

Figure 2a.

E-cigarette use: prevalence in the last 30 days (percentage)

≤

6.9 %

7.0-9.5 %

9.6-14 %

15-20 %

≥

20 %

Non-participating country

or data not available

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

e situation in 2019

Figure 2b.

E-cigarette use: prevalence in the last 30 days by gender (percentage)

Boys

All students

Monaco

(41)

Girls

9.3

8.9

8.4

7.6

4.7

7.5

8.0

6.6

7.9

8.0

4.6

5.4

5.1

6.6

4.4

4.1

4.3

4.5

4.0

Wald (test

(p-value)

0.83

0.00

0.01

0.00

0.03

0.00

9.4

7.7

8.5

7.1

Lithuania

(31)

Poland

(30)

Hungary

(21)

Czechia

(20)

Slovakia

(18)

Iceland

(17)

Latvia

(17)

Germany

(16)

France

(16)

Ireland

(15)

Estonia

(15)

Denmark

(14)

Austria

(14)

Romania

(14)

Bulgaria

(13)

Italy

(13)

Croatia

(12)

Ukraine

(11)

Greece

(11)

Kosovo

(11)

Cyprus

(10)

Slovenia

(10)

Norway

(10)

Spain

(9.4)

Netherlands

(9.3)

Faroes

(8.4)

Finland

(7.5)

North Macedonia

(7.2)

Malta

(7.2)

Montenegro

(7.1)

Georgia

(7.1)

Sweden

(6.4)

Portugal

(6.3)

Serbia

(5.4)

0.66

0.15

0.01

0.00

0.10

0.00

0.19

0.00

Colour indicates signi cant

difference between

boys

and

girls

Statistical signi cance levels are reported for each country.

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

e situation in 2019

Frequency of alcohol use in the last 30 days

Among all students who had used alcohol, alcohol was

consumed on 5.6 occasions on average in the last 30 days

(Figure 3a). Students from Germany and Cyprus consumed

alcohol on 8.0 and 7.5 occasions, respectively, and students

from Sweden, Finland, Lithuania, Iceland, Estonia, Latvia

and Norway drank alcohol on fewer than four occasions

on average. In most countries, boys who drank did so

more frequently than girls who drank, with differences of

more than three occasions in the last 30 days in Germany,

Serbia and Montenegro (Figure 3b). In most countries, the

difference between boys and girls in the number of drinking

occasions was significant.

Figure 3a.

Frequency of alcohol intake in the last 30 days (mean number of occasions among users)

≤

3.9 occasions

4.0-4.9 occasions

5.0-5.9 occasions

6.0-6.9 occasions

≥

7.0 occasions

Non-participating country

or data not available

ESPAD Report 2019

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e situation in 2019

Figure 3b.

Frequency of alcohol intake in the last 30 days by gender (mean number of occasions among users)

Boys

All students

Germany

(8.0)

Girls

6.4

6.5

6.8

5.6

5.2

5.7

6.3

5.5

5.3

5.2

5.6

5.5

5.4

4.6

5.8

4.4

4.7

4.9

4.6

4.7

4.3

3.8

4.2

4.4

3.4

3.7

3.3

3.5

3.6

3.3

2.8

Fisher's F-test

(p-value)

0.00

0.25

0.00

0.49

0.00

0.02

0.00

0.01

0.00

0.28

0.01

0.00

0.71

0.20

0.36

0.00

0.04

9.7

8.6

8.4

7.9

9.0

8.7

8.2

7.8

7.9

8.0

7.1

7.3

7.6

7.4

7.3

6.1

6.2

6.1

5.8

5.5

5.9

5.4

5.8

5.4

5.2

5.7

5.1

4.6

4.4

3.7

4.1

3.7

3.9

3.5

Cyprus

(7.5)

Denmark

(7.4)

Austria

(7.4)

Serbia

(7.3)

Montenegro

(7.2)

Italy

(7.0)

Malta

(7.0)

Croatia

(6.8)

France

(6.7)

Kosovo

(6.6)

North Macedonia

(6.5)

Netherlands

(6.5)

Bulgaria

(6.4)

Slovenia

(6.0)

Slovakia

(5.9)

Romania

(5.4)

Portugal

(5.4)

Poland

(5.3)

Greece

(5.2)

Spain

(5.1)

Ukraine

(5.0)

Hungary

(4.9)

Georgia

(4.9)

Czechia

(4.8)

Monaco

(4.8)

Faroes

(4.5)

Ireland

(4.4)

Norway

(3.9)

Latvia

(3.9)

Estonia

(3.6)

Iceland

(3.6)

Lithuania

(3.5)

Finland

(3.3)

Sweden

(3.1)

Colour indicates signi cant

difference between

boys

and

girls

Statistical signi cance levels are reported for each country.

ESPAD Report 2019

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e situation in 2019

Alcohol intake on the last drinking occasion

The

amount of alcohol consumed was calculated as the

average volume of ethanol (in centilitres) consumed on

the last drinking day.

The

students had drunk an average of

4.6 centilitres of alcohol on the last drinking day (Figure 4a).

The

amount of alcohol consumed was highest in Denmark

(8.8 centilitres), followed by Norway (6.7 centilitres) and

the Netherlands (6.6 centilitres), and was lowest in Kosovo

(2.5 centilitres) and Romania (3.0 centilitres). Boys reported

consuming higher volumes than girls in the majority of

countries (Figure 4b). On average, the difference between

boys and girls in the amount of alcohol consumed was

0.7 centilitres, with the highest differences reported in

Georgia (2.1 centilitres), the Faroes (1.8 centilitres) and

Montenegro (1.6 centilitres).

Figure 4a.

Average alcohol intake on the last drinking day among users (centilitres of ethanol)

≤

2.9 cl

3.0-3.9 cl

4.0-4.9 cl

5.0-5.9 cl

≥

6.0 cl

Non-participating country

or data not available

ESPAD Report 2019

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e situation in 2019

Figure 4b.

Average alcohol intake on the last drinking day among users by gender (centilitres of ethanol)

Boys

All students

Denmark

(8.8)

Girls

8.4

6.3

7.1

5.2

5.1

5.5

5.2

4.7

5.4

4.8

4.5

4.6

4.1

4.2

4.3

3.5

3.9

3.8

3.4

4.0

3.5

3.2

4.1

3.6

3.3

3.5

3.2

3.0

2.7

2.8

2.4

1.9

Fisher's F-test

(p-value)

0.00

0.25

0.00

0.01

0.00

0.04

0.07

0.12

0.00

0.89

0.81

0.00

0.04

0.02

0.00

0.02

0.00

0.31

0.00

0.28

0.35

0.00

0.33

0.00

0.33

0.00

0.01

0.00

9.2

7.1

6.2

7.0

6.5

6.1

6.2

5.9

5.1

5.0

5.3

5.5

4.8

4.7

5.2

4.9

4.8

5.5

5.0

4.7

4.8

4.2

4.6

4.8

3.8

4.3

4.2

3.8

4.0

3.7

3.8

3.6

3.5

2.9

Norway

(6.7)

Netherlands

(6.6)

Faroes

(6.1)

Austria

(5.8)

Finland

(5.8)

Ireland

(5.7)

Croatia

(5.3)

Sweden

(5.3)

Portugal

(5.2)

Germany

(5.0)

Hungary

(5.0)

Estonia

(4.7)

Slovakia

(4.7)

Slovenia

(4.6)

Poland

(4.6)

Czechia

(4.5)

Georgia

(4.5)

France

(4.5)

Latvia

(4.5)

Cyprus

(4.2)

Serbia

(4.2)

Spain

(4.1)

Bulgaria

(4.0)

Montenegro

(4.0)

Iceland

(4.0)

Ukraine

(3.9)

Italy

(3.8)

Malta

(3.6)

Greece

(3.6)

Monaco

(3.3)

North Macedonia

(3.2)

Lithuania

(3.2)

Romania

(3.2)

Kosovo

(2.5)

Colour indicates signi cant

difference between

boys

and

girls

Statistical signi cance levels are reported for each country.

ESPAD Report 2019

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e situation in 2019

Alcoholic beverage preferences on the last

drinking day

The

relative contribution of each beverage (in centilitres of

ethanol) to the total amount of alcohol consumed on the

last drinking day was taken as an indicator of preference

for alcoholic beverages. On average, spirits (38 %) and beer

(31 %) were the preferred alcoholic beverages (Figure 5).

In Spain (83 %), Portugal (59 %), Lithuania (57 %), Sweden

(52 %) and Malta (51 %), more than half of the students who

had drunk alcohol preferred spirits, while a similar preference

for beer was found in Kosovo (62 %), Serbia (52 %), Poland

and North Macedonia (49 % each). Wine was preferred over

spirits and beer in Ukraine (26 %), over spirits but not beer

in Georgia (36 %) and over beer but not spirits in Slovakia

(27 %). Premixed drinks accounted for about one quarter of

the total amount of alcohol consumed in Germany (26 %),

Finland and Denmark (23 % each). In the Faroes, Ireland,

Norway and Sweden, cider accounted for about one third

to one quarter of the total amount of alcohol consumed. In

the Faroes cider was the most preferred alcoholic beverage,

while in the other countries it was ranked second after spirits.

In more than half of the ESPAD countries, boys preferred

beer (overall average: 40 %) over other alcoholic beverages

(see Additional Table 26b). In Spain, Lithuania, Monaco,

Portugal, Sweden, Malta, Slovakia, Bulgaria, Estonia, Latvia,

Greece, Iceland, Hungary, Norway, Czechia and France,

boys preferred spirits over beer. Among girls, the preferred

alcoholic beverage was spirits in the large majority of

countries (see Additional Table 26c). In Kosovo, Poland,

Serbia and Montenegro, beer was the most preferred

alcoholic beverage among girls, while in Ukraine (33 %)

and Georgia (40 %) it was wine. In Germany girls preferred

premixed drinks (29 %) together with wine (27 %), while

in Italy beer (30 %) and premixed drinks (28 %) were the

preferred alcoholic beverages.

The

preference was generally higher among girls than boys

for spirits (girls 40 % versus boys 36 %), wine (20 % versus

12 %), premixed drinks (10 % versus 6.7 %) and cider (8.4 %

versus 5.9 %).

ESPAD Report 2019

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e situation in 2019

Figure 5.

Alcoholic beverage preferences on the last drinking day: contribution of each beverage to the total amount of

pure alcohol consumed (percentage)

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Beer

Cider

Premixed drinks

Wine

Spirits

ESPAD Report 2019

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e situation in 2019

Heavy episodic drinking in the last 30 days

One in three students (34 %) reported heavy episodic

drinking during the last 30 days (Figure 6a).

This

drinking

pattern was widespread in Denmark, Germany and Austria,

with between 49 % and 59 % of students reporting heavy

episodic drinking.

The

lowest rate was found in Iceland

(7.6 %).

The

difference between boys and girls was about

3 percentage points on average, with generally higher

rates found for boys (Figure 6b). Significant gender

differences were found in half of the countries, with the

largest differences in Cyprus (44 % for boys versus 31 %

for girls), Georgia (52 % versus 39 %), Montenegro (34 %

versus 22 %) and Romania (43 % versus 31 %). However,

in Spain, significantly more girls than boys reported heavy

episodic drinking at least once in the last 30 days (38 % for

girls versus 30 % for boys).

This

was also the case in Latvia,

Austria and Lithuania.

Figure 6a.

Prevalence of heavy episodic drinking (five or more drinks on one occasion; one drink contains approximately

2 centilitres of ethanol) at least once in the last 30 days (percentage)

≤

19 %

20-29 %

30-39 %

40-49 %

≥

50 %

Non-participating country

or data not available

ESPAD Report 2019

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e situation in 2019

Figure 6b.

Prevalence of heavy episodic drinking (five or more drinks on one occasion; one drink contains approximately

2 centilitres of ethanol) at least once in the last 30 days by gender (percentage)

Boys

All students

Denmark

(59)

Girls

9.7

8.3

Wald test

(p-value)

0.95

0.19

0.00

0.13

0.00

0.06

0.37

0.01

0.80

0.00

0.01

0.00

0.42

0.13

0.00

0.39

0.38

0.67

0.09

0.00

0.04

0.00

0.48

0.06

0.58

0.15

0.57

0.00

0.17

6.8

Germany

(54)

Austria

(49)

Slovakia

(46)

Georgia

(45)

Croatia

(45)

Netherlands

(42)

Bulgaria

(42)

Hungary

(41)

Malta

(40)

Slovenia

(40)

Czechia

(39)

Romania

(37)

Cyprus

(37)

Serbia

(36)

Latvia

(36)

Italy

(35)

Spain

(34)

Poland

(34)

France

(34)

North Macedonia

(33)

Ukraine

(33)

Faroes

(32)

Ireland

(32)

Estonia

(32)

Greece

(32)

Lithuania

(28)

Montenegro

(28)

Monaco

(27)

Portugal

(24)

Finland

(22)

Sweden

(20)

Norway

(16)

Kosovo

(14)

Iceland

(7.6)

Colour indicates signi cant

difference between

boys

and

girls

Statistical signi cance levels are reported for each country.

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

e situation in 2019

Current cannabis use

Overall, 7.1 % of the students had used cannabis in the last

30 days (Figure 7a). A high variability was found among

ESPAD countries, with the lowest rate observed in Kosovo

(1.4 %), and the highest rate seen in Italy (15 %), followed

by France and the Netherlands (13 % each), where the

percentage of students having used cannabis at least once

in the last month was about twice the ESPAD average.

More boys than girls reported cannabis use in the last 30

days (8.5 % versus 5.8 % on average). In more than two

thirds of countries, statistically significant (p < 0.05) gender

differences were found, with boys reporting higher use

than girls in all cases (Figure 7b).

The

largest differences

were found in Monaco, Germany, France, Georgia and Italy

(5-8 percentage points).

Figure 7a.

Prevalence of cannabis use in the last 30 days (percentage)

≤

2.5 %

2.6-6.5 %

6.6-10 %

11-14 %

≥

15 %

Non-participating country

or data not available

ESPAD Report 2019

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e situation in 2019

Figure 7b.

Prevalence of cannabis use in the last 30 days by gender (percentage)

Boys

All students

Italy

(15)

France

(13)

Girls

7.7

9.4

7.7

8.6

7.0

8.7

6.7

7.3

6.3

5.8

6.2

4.9

5.3

4.9

3.4

4.1

3.4

4.6

2.9

3.2

2.3

3.1

2.9

2.6

1.4

1.9

1.7

1.5

0.4

Two-sample proportion

test (p-value)

0.00

0.51

0.01

0.97

0.95

0.02

0.00

0.04

0.00

0.43

0.00

0.10

0.00

0.06

0.00

0.01

0.21

0.00

0.01

0.00

0.98

0.00

0.58

0.24

0.03

0.00

0.01

0.04

0.00

9.2

9.1

8.0

8.4

7.4

6.1

7.9

6.5

6.0

4.7

6.5

4.9

5.4

4.0

3.6

3.9

4.3

3.6

3.3

2.7

2.5

Netherlands

(13)

Monaco

(12)

Spain

(12)

Czechia

(12)

Slovenia

(11)

Austria

(11)

Germany

(10)

Latvia

(10)

Georgia

(9.4)

Croatia

9.2

Ireland

(9.0)

Slovakia

(8.3)

Poland

(8.1)

Denmark

(7.4)

Bulgaria

(7.1)

Estonia

(6.6)

Portugal

(6.2)

Lithuania

(5.5)

Cyprus

(5.3)

Hungary

(5.3)

Montenegro

(4.7)

Malta

(4.7)

Greece

(4.6)

Finland

(4.1)

Norway

(3.8)

Faroes

(3.5)

Romania

(3.3)

Serbia

(3.2)

Sweden

(2.9)

North Macedonia

(2.7)

Ukraine

(2.4)

Iceland(2.1)

Kosovo

(1.4)

Colour indicates signi cant

difference between

boys

and

girls

Statistical signi cance levels are reported for each country.

ESPAD Report 2019

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e situation in 2019

Frequency of cannabis use in the last 12 months

Among all students who had used cannabis in the last 12

months (13 % of the total), on average the drug was used

on 9.9 occasions (Figure 8a). In France, Italy, Serbia, Austria

and Cyprus, cannabis was used once a month (12 or more

times).

The

lowest average frequency of cannabis use was

found in the Faroes (4.4 occasions). Overall, boys reported

a higher frequency of cannabis use than girls (Figure 8b),

with significant gender differences in Monaco, Georgia, the

Netherlands, Italy, Ukraine, Sweden, Norway, Poland, Greece,

Montenegro, Estonia, France, Finland, Croatia, Lithuania,

Slovenia, Latvia and Spain.

In Kosovo, the Faroes, Denmark and Iceland, cannabis was

used more frequently by girls than boys, although these

differences were not statistically significant.

Figure 8a.

Frequency of cannabis use in the last 12 months (mean number of occasions among users)

≤

5.9 occasions

6.0-7.9 occasions

8.0-9.9 occasions

10.0-10.9 occasions

≥

11.0 occasions

Non-participating country

or data not available

ESPAD Report 2019

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e situation in 2019

Figure 8b.

Frequency of cannabis use in the last 12 months by gender (mean number of occasions among users)

Boys

All students

France

(15)

Italy

(13)

8.7

9.2

7.7

8.1

9.6

6.2

8.4

7.7

8.7

4.9

9.6

7.5

8.1

6.7

8.3

7.2

6.0

7.2

4.8

6.1

6.4

5.2

4.6

Girls

Fisher’s F-test

test (p-value)

0.04

0.00

0.28

0.11

0.35

0.08

0.01

0.18

0.02

0.00

0.03

0.22

0.03

0.96

0.59

0.78

0.02

0.01

0.02

0.00

0.09

0.88

0.02

0.17

0.00

0.43

0.11

0.00

0.45

0.01

0.39

0.02

0.82

12.4

12.1

12.5

8.2

9.2

9.8

9.0

9.2

8.2

9.9

8.5

7.7

7.8

4.2

Serbia

(13)

Austria

(12)

Cyprus

(12)

Germany

(11)

Greece

(11)

North Macedonia

(11)

Sweden

(11)

Slovenia

(11)

Netherlands

(11)

Spain

(11)

Portugal

(11)

Monaco

(11)

Ireland

(11)

Malta

(10)

Denmark

(10)

Montenegro

(10)

Norway

(10)

Croatia

(10)

Georgia

(9.6)

Kosovo

(9.6)

Iceland

(9.4)

Finland

(9.1)

Bulgaria

(8.9)

Poland

(8.8)

Czechia

(8.7)

Slovakia

(8.1)

Estonia

(7.7)

Romania

(7.7)

Ukraine

(7.7)

Latvia

(7.4)

Hungary

(7.2)

Lithuania

(6.6)

Faroes

(4.4)

Colour indicates signi cant

difference between

boys

and

girls

Statistical signi cance levels are reported for each country.

ESPAD Report 2019

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e situation in 2019

High-risk cannabis use

As described in the methodology section, the Cannabis Abuse

Screening Test (CAST) score, which measures the possible

presence and extent of cannabis-related problems, was

calculated only for participants who gave a valid response to

the introductory question of the CAST module, which asks

about cannabis use in the last 12 months.

In this section, country-level prevalence estimates of high-risk

cannabis users in the total sample of students are reported.

Detailed estimates of the proportions of high-risk users among

the group of students having used cannabis in the past 12

months are provided online (see Additional Table 61a-c).

Prevalence of cannabis use in the past 12 months based

on the introductory question of the CAST module, as well

as averages for each of the six CAST items, presented

separately by country, are also available online (see Additional

Tables 55-61).

Among the total ESPAD sample (both users and non-users

of cannabis in the last 12 months), 4.0 % of students were

Figure 9a.

classified as high-risk cannabis users using this measure.

This

result is consistent with the prevalence of 5.0 % found

in the 2011 ESPAD study, although only 13 countries were

included in 2011. In 2019, the lowest rates were observed in

North Macedonia (1.4 %), Ukraine and Kosovo (1.5 % each),

the Faroes (1.6 %) and Hungary (1.7 %).

The

highest rates were

observed in France (7.3 %), Germany (7.0 %), Czechia (6.4 %),

Slovenia (6.3 %) and Italy (6.2 %) (Figure 9a).

Overall, the prevalence of high-risk cannabis use was higher

among boys (4.7 %) than girls (3.3 %). At the country level,

statistically significant gender differences were found in 16

ESPAD countries, with the highest differences in terms of

percentage points reported in Monaco (9.1 % for boys versus

2.7 % for girls), Georgia (4.8 % versus 0.8 %), Germany (8.8 %

versus 5.3 %), Greece (4.3 % versus 1.5 %), Slovenia (7.6 %

versus 5.1 %), Ireland (7.0 % versus 4.5 %), Kosovo (2.8 %

versus 0.4 %), Italy (7.2 % versus 5.1 %), Cyprus (3.9 % versus

1.9 %) and Estonia (5.3 % versus 3.3 %) (Figure 9b). In four

countries high-risk cannabis use was more prevalent among

girls than boys, although these differences were not statistically

significant.

Prevalence of high-risk cannabis users (percentage)

≤

1.9 %

2.0-2.9 %

3.0-4.9 %

5.0-5.9 %

≥

6.0 %

Non-participating country

or data not available

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

e situation in 2019

Figure 9b.

Prevalence of high-risk cannabis users by gender (percentage)

Logistic regression

(p-value)

6.3

5.3

6.6

5.1

5.5

2.7

5.1

4.5

5.3

4.5

4.6

5.4

4.4

3.3

4.0

3.3

3.5

2.5

1.5

1.9

0.8

1.7

1.9

1.5

2.4

1.7

1.8

1.5

0.4

1.3

1.0

0.05

0.01

0.98

0.00

0.02

0.19

0.01

0.10

0.01

0.37

0.31

0.39

0.28

0.22

0.63

0.02

0.99

0.05

0.84

0.04

0.00

0.02

0.00

0.61

0.10

0.25

0.23

0.96

0.00

0.44

0.04

Boys

8.3

8.8

6.4

7.6

7.2

6.3

9.1

6.6

7.0

6.0

5.8

5.4

4.5

5.4

4.9

5.3

5.2

4.0

4.4

3.3

3.5

4.3

3.9

4.8

3.2

2.9

3.3

2.2

2.5

2.4

1.9

1.6

2.8

1.6

1.9

All students

France

(7.3)

Germany

(7.0)

Czechia

(6.5)

Slovenia

(6.3)

Italy

(6.2)

Austria

(6.0)

Monaco

(5.8)

Latvia

(5.8)

Ireland

(5.7)

Spain

(5.6)

Netherlands

(5.1)

Slovakia

(5.0)

Bulgaria

(4.9)

Denmark

(4.9)

Croatia

(4.7)

Estonia

(4.2)

Poland

(4.2)

Lithuania

(4.0)

Portugal

(3.8)

Malta

(3.4)

Finland

(3.0)

Greece

(2.9)

Cyprus

(2.8)

Georgia

(2.6)

Sweden

(2.5)

Montenegro

(2.4)

Norway

(2.4)

Serbia

(2.3)

Romania

(2.1)

Iceland

(2.1)

Hungary

(1.7)

Faroes

(1.6)

Kosovo

(1.5)

Ukraine

(1.5)

North Macedonia

(1.4)

Girls

Colour indicates signi cant

difference between

boys

and

girls

Statistical signi cance levels are reported for each country.

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

e situation in 2019

New psychoactive substance use

Overall, an average of 2.5 % of the students had used NPS at

least once in the last 12 months, with the highest prevalence

reported in Czechia, Latvia, Estonia, Poland and Monaco

(4.0-4.9 %) and the lowest prevalence reported in North

Macedonia, Finland and Portugal ( 0.4-0.8 %; Figure 10a).

Generally, differences in NPS use between boys and girls

were small; however, significantly more boys than girls

reported the use of NPS in Cyprus, Georgia, Greece, Ireland,

Montenegro, Norway and Serbia, and significantly more girls

than boys reported the use of NPS in Latvia and Slovenia

(Figure 10b).

Among all students who had used NPS in the last 12

months, the majority (54 %) reported use of herbal synthetic

substances; 27 % reported use of NPS in the form of

powders or tablets, 13 % reported the use of NPS in the form

of liquids and 17 % reported the use of NPS in other forms.

Only a few countries reported higher rates of use of NPS

in forms other than herbal smoking mixtures. In particular,

powders/tablets were used by the majority of last-year NPS

users in Finland (64 %) and Norway (54 %), liquids were

reported by 36 % of the users in the Netherlands, and the

use of NPS in other forms was reported by half of the users

in North Macedonia. Even though on average the differences

between boys and girls in the reported appearance of NPS

used in the last 12 months were low, in most individual

countries noticeable gender differences were found.

Focusing only on differences higher than 15 percentage

points, with regard to herbal NPS, boys reported higher

prevalence rates than girls in Romania, Georgia, Finland,

Ireland and the Netherlands, while girls reported higher rates

in Bulgaria, Ukraine, Slovakia and Lithuania; for powders/

tablets, girls reported higher prevalence rates in many

countries (Kosovo, Georgia, Slovakia, Serbia, Spain, Sweden,

Ireland and Portugal), while a higher rate was found among

boys in Cyprus; and higher prevalence rates were found for

liquid forms of NPS among male users than female users in

Portugal, Slovakia, Sweden, Lithuania and North Macedonia,

with girls reporting higher rates in the Netherlands and

Finland (see Additional Table 71a and b).

Figure 10a.

NPS use: prevalence in the last 12 months (percentage)

≤

0.9 %

1.0-1.9 %

2.0-2.9 %

3.0-3.9 %

≥

4.0 %

Non-participating country

or data not available

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

e situation in 2019

Figure 10b.

NPS use: prevalence in the last 12 months by gender (percentage)

Boys

All students

Czechia

(4.9)

3.4

Latvia

(4.7)

Estonia

(4.7)

Poland

(4.5)

Monaco

(4.0)

3.5

Croatia

(3.7)

Ireland

(3.7)

3.0

Lithuania

(3.6)

Cyprus

(3.6)

3.2

2.7

3.0

3.1

2.1

2.6

2.4

3.3

3.0

2.1

2.3

1.9

3.0

1.7

1.8

2.0

1.5

1.6

1.2

1.5

1.7

0.9

0.5

0.7

Faroes

(3.5)

Slovenia

(3.3)

Austria

(3.0)

Bulgaria

(2.9)

Germany

(2.8)

Hungary

(2.6)

Ukraine

(2.5)

Norway

(2.4)

Greece

(2.2)

Italy

(2.2)

Malta

(2.2)

Romania

(2.2)

Georgia

(1.9)

Slovakia

(1.9)

Denmark

(1.5)

Montenegro

(1.5)

Serbia

(1.5)

Spain

(1.5)

Sweden

(1.5)

Iceland

(1.1)

Kosovo

(1.1)

Netherlands

(1.1)

Portugal

(0.8)

Finland

(0.6)

North Macedonia

(0.5)

1.4

1.1

1.0

1.5

1.4

1.0

0.6

0.7

0.3

0.8

2.3

2.0

2.5

1.5

2.5

2.7

2.5

3.5

3.1

1.8

3.9

4.0

2.4

4.2

3.6

4.0

4.2

4.9

Girls

5.1

6.0

Logistic regression

(p-value)

0.81

0.00

0.63

0.59

0.71

0.45

0.00

0.10

0.00

0.69

0.05

0.78

0.34

0.09

0.80

0.86

0.00

0.45

0.55

0.26

0.00

0.27

0.49

0.03

0.02

0.91

0.74

0.73

0.09

0.31

0.40

0.10

4.8

4.5

4.7

4.4

5.0

5.8

Colour indicates signi cant

difference between

boys

and

girls

Statistical signi cance levels are reported for each country.

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e situation in 2019

Gambling and online gambling

ESPAD average

Gambling and online gambling in last 12 months:

prevalence of excessive and problem gambling (%)

Average

Gambling (

)

Slot

Cards or dice (

)

Lotteries (

)

Sport or animal betting (

)

Online gambling (

)

Estimated excessive gambling (

)

Estimated problem gambling (

)

machines (

)

7.9

5.0

Min.

7.4

3.2

7.1

1.3

Max.

(

) Percentage of students having gambled with money on at least one

game in the last 12 months.

(

) Proportion of slot machine gamblers: percentage of gamblers in the

past 12 months.

(

) Proportion of cards or dice gamblers: percentage of gamblers in the

past 12 months.

(

) Proportion of lottery gamblers: percentage of gamblers in the past 12

months.

(

) Proportion of sport or animal betting gamblers: percentage of

gamblers in the past 12 months.

(

) Percentage of students involved in online gambling with money in

the last 12 months.

(

) Estimation of excessive gamblers based on the CSPG scale, adopted

from Rockloff (2012): percentage of gamblers in the past 12 months.

(

) Estimation of problem gamblers based on the Lie/Bet Questionnaire,

adapted from Johnson (1997): percentage of gamblers in the past 12

months.

explain the difference between this rate and the rate of

14 % found in 2015 for last-year gambling prevalence. As

shown in Table 11a, the highest prevalence of gambling

among students in 2019 was found in Greece and Cyprus

(33 % each), followed by Italy and Montenegro (32 % each)

and Finland (30 %). Despite the different approach used

compared with the previous survey wave, these countries

were also among those with the highest prevalence rates

in 2015. On the other hand, Table 11a shows that the

lowest rates of gambling for money were found in Malta

(14 %), Georgia (13 %), Denmark (12 %) and Kosovo

(11 %). In all European countries, in 2019 considerably

more boys than girls reported having gambled in the last 12

months (29 % versus 15 % on average).

The

countries with

gender differences higher than 20 percentage points were

Montenegro, Cyprus, Croatia, Greece, Serbia and Finland.

The

smallest gender differences were found in Malta,

Sweden and Czechia.

With regard to online gambling, overall, 7.9 % of ESPAD

students reported having spent money on games on the

internet in the last 12 months.

The

highest rates of students

reporting gambling online were found in Cyprus and Kosovo

(16 %) and in countries of the Balkan peninsula (Montenegro

13 %, Serbia and Bulgaria 11 % each).

The

highest difference

in online gambling engagement between boys and girls was

observed in Cyprus (29 % for boys versus 7.3 % for girls).

Other countries with gender differences higher than 15

percentage points were Denmark, Montenegro and Serbia.

The

two countries with the smallest gender differences (less

than 5 percentage points) were Malta and Germany.

As shown in Table 11b, lottery gambling (including scratch

cards, bingo and keno games) was the predominant

gambling activity; this was reported by between 19 %

(Germany) and 74 % (Greece) of the students who had

gambled in the past 12 months. Rates of 30 % or lower were

found in some eastern European countries (Georgia, 27 %;

Ukraine, 28 %; Slovakia and Romania 29 % each, and Kosovo

30 %).

Slightly less than half of the students who gambled had

spent money on sports or animal races (45 %) and playing

cards or dice (44 %). Sports or animal betting was chosen

by more than 70 % of the students who gambled in Croatia

and Montenegro, and by less than 30 % of the students who

gambled in the Netherlands, Czechia, Finland, Malta, Austria,

Germany and Lithuania. Cards (e.g. poker and bridge) or dice

games were preferred by more than 60 % of the students

who gambled in Georgia, Romania and Germany, while they

were less popular (rates of less than 30 %) in Montenegro,

Serbia, North Macedonia and Portugal.

The

least popular gambling activity among students was

slot machines, which on average were chosen by one in

five

adolescent gamblers (21 %). In some countries (Czechia and

As described in the methodology section, in this report the

prevalence of gambling for money includes engagement in

at least one of the following gambling activities in the last

12 months: playing on slot machines, playing cards or dice

for money, playing the lottery or betting on sports or animal

races.

This

methodological approach is different from the

one used in the 2015 survey, in which a direct question,

‘How often (if ever) did you gamble for money in the last 12

months?’, was used to compute the gambling prevalence. In

fact, students might have an ambiguous self-perception of

gambling, leading to an admission that they indeed engaged

in gambling activities even though they did not consider

themselves to be gambling or to be gamblers (Lange, 2001).

Therefore,

a comparison between the results shown in

Table 11a and the result from the 2015 survey cannot be

performed directly and differences in average and country-

specific prevalence rates between the two survey waves

should be interpreted with caution.

This

choice was made

as it is believed to produce more reliable estimates of

gambling prevalence than using a direct question asking

for engagement in any gambling for money (Molinaro et al.,

2018).

In 2019, 22 % of ESPAD students reported having gambled

for money on at least one type of game in the last 12 months.

The

methodological approach used in 2019 might partially

ESPAD Report 2019

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e situation in 2019

Greece), the proportion of gamblers playing at slot machines

was less than 10 %. On the other hand, rates above 30 %

were found in Georgia (40 %), Ireland (37 %), Romania

(35 %) and Montenegro (35 %). Finland reported the highest

proportion of slot machine gamblers among those who had

gambled in the last 12 months (60 %).

Table 11a.

Country

Gambling for money and online gambling: prevalence in the last 12 months (percentage)

Gambling

Boys

Girls

9.3

4.1

–

7.8

7.0

–

4.1

Total

–

Boys

8.3

9.3

–

5.6

9.0

7.2

5.2

8.8

6.8

7.1

5.2

Online gambling

Girls

1.3

4.6

2.1

7.3

1.8

1.2

2.1

2.8

2.1

–

3.3

0.8

1.1

1.7

1.2

2.5

2.6

2.9

1.5

2.4

2.8

4.2

1.9

4.8

1.2

2.3

1.0

2.4

3.2

2.1

1.8

1.5

2.6

2.7

0.8

Total

4.9

8.7

5.7

9.5

7.4

7.9

–

7.6

3.1

4.9

7.3

4.1

6.0

7.6

8.5

7.3

3.8

9.4

5.3

8.9

4.1

7.4

5.7

8.6

6.7

8.3

4.2

8.1

9.5

7.9

3.1

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

–

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e situation in 2019

Table 11b.

Proportions of different types of gamblers among those having gambled for money in the past 12 months

(percentage)

Slot machines

7.4

–

7.5

–

7.4

Cards or dice

–

Lotteries

–

Sports or animal betting

–

Country

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

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e situation in 2019

Excessive gambling

As described in the methodology section, the CSPG

(Rockloff, 2012) was added to the 2019 ESPAD

questionnaire to measure the intensity of gambling activity

among students. In this section, estimates of the proportions

of excessive gamblers in the group of students who had

gambled in the past 12 months are reported.

Country-level prevalence estimates of students gambling

excessively in the total sample of students are available

online (see Additional Table 101a).

Considering the prevalence in the student population, 3.8 %

of ESPAD students reported a gambling behaviour that could

be considered to be excessive gambling. Lower rates were

found in Malta (1.3 %), Iceland and Slovakia (1.9 % each).

Rates of about 5 % were found in North Macedonia, Ukraine,

Italy, Cyprus and Romania.

The

highest rates were found in

Kosovo (7.9 %) and Montenegro (12 %).

On the other hand, considering the proportion of excessive

gamblers among those who had gambled in the last 12

months only, the average across all ESPAD countries was

15 %. As shown in Table 11c, rates below 10 % were found in

the Netherlands (9.0 %), Iceland (8.3 %), Greece (7.7 %) and

Malta (7.1 %).

The

highest rates were found in Montenegro

(35 %), Kosovo (24 %) and Denmark (21 %), followed by

Georgia, Bulgaria, Romania, Ukraine and Lithuania (all 20 %).

Overall, the proportion of excessive gamblers among

12-month gamblers was much higher among boys than

girls (19 % versus 5.9 %).

The

largest gender differences

(20 percentage points or more) were found in Lithuania,

Georgia, Denmark, Bulgaria and Kosovo.

The

smallest gender

differences (4-6 percentage points) were found in Slovakia,

Malta and Croatia.

Problem gambling

As described in the methodology section, the Lie/Bet

screening instrument (Johnson et al., 1997) was used in

the 2019 ESPAD questionnaire to assess the presence

of possible problem gambling behaviour. In Table 11c,

estimates of the proportions of problem gamblers in the

group of students who had gambled in the past 12 months

are reported.

Reference to country-level prevalence estimates among the

total sample is only made in detail in the online additional

result tables (see Additional Table 90). Considering the

ESPAD prevalence, 1.4 % of students were classified as

problem gamblers.

The

prevalence of problem gambling was

below 1 % in the Netherlands, Germany, Austria, Iceland,

Spain, Malta and Estonia.

The

prevalence was higher than

2 % in Montenegro, Romania, the Faroes, Bulgaria and

Cyprus.

Among students who had gambled in the last 12 months, the

proportion of problem gamblers across all ESPAD countries

was 5.0 %. As shown in Table 11c, the lowest proportion of

students who had gambled in the past year and met the

criteria for problem gambling behaviour was found in the

Netherlands (1.3 %), while the highest proportion was found

in Georgia (12 %), followed by Denmark (9.1 %) and Romania

(8.5 %). In 12 ESPAD countries the proportion of problem

gamblers among 12-month gamblers was higher than 5.0 %.

Overall, the proportion of 12-month gamblers displaying

problems related to their gambling was higher among boys

than girls, both on average (6.3 % versus 2.4 %) and in the

majority of countries.

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e situation in 2019

Table 11c.

Estimation of excessive and problem gamblers among those having gambled in the past 12 months by gender

(percentage)

Excessive

gambling

–

7.7

7.1

9.0

–

7.1

Problem

gambling

2.3

7.4

6.1

6.6

3.1

9.1

4.1

7.8

3.9

–

3.9

4.6

2.8

2.1

5.7

3.9

6.9

4.0

4.5

5.2

4.6

7.6

1.3

4.5

–

6.8

3.2

8.5

4.5

2.7

4.2

3.2

2.9

4.5

5.0

1.3

Excessive gambling

Boys

–

9.4

–

9.4

Girls

3.3

6.8

2.9

4.5

3.5

6.6

8.1

2.4

–

5.0

7.3

1.4

7.2

4.1

4.5

8.1

4.6

2.1

3.8

2.8

2.3

2.0

–

4.1

4.6

8.1

7.2

6.7

4.8

5.8

1.8

9.5

5.9

1.4

Problem gambling

Boys

2.2

9.4

6.6

9.3

4.2

5.9

8.9

5.4

–

5.3

6.5

4.0

2.4

7.6

5.0

6.2

5.6

6.1

6.3

5.7

7.9

1.5

5.8

–

9.2

4.5

5.9

4.0

5.4

4.0

5.0

5.5

6.3

1.5

Girls

2.6

3.8

4.1

2.0

1.4

0.0

1.3

5.4

0.6

–

4.8

1.4

1.1

0.5

1.7

2.8

1.6

8.2

1.4

3.6

2.6

6.9

1.0

2.3

–

3.2

0.6

3.9

1.2

0.0

1.7

1.9

0.0

2.7

2.4

0.0

8.2

Country

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

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e situation in 2019

Social media use and gaming

ESPAD average

Social media use and gaming

None (

a,b

)

(%)

Mode

(hours/

day)

Min.

(hours/

day)

Max.

(hours/

day)

Social media use (mean) (

)

Hours on a school day

Hours on a non-school day

Gaming (mean) (

)

Hours on a school day

Hours on a non-school day

Self-perceived problems

index (mean) (

)

Social media use

Gaming

80 % on a non-school day had engaged in gaming. In

Bulgaria, the modal class was represented by 6 or more

hours on a non-school day, and in Sweden the modal class

was represented by 2-3 hours per day on a non-school day.

Among gamers, the modal class was represented on average

by half an hour or less on a typical school day and 2-3 hours

on a non-school day (Table 12b).

Noticeable gender differences were observed in the large

majority of countries, with boys more frequently engaged in

gaming than girls, both on a typical school day and a typical

non-school day; boys reported spending twice as much time

on gaming than girls in most countries. In some countries,

such as Finland, Denmark and Estonia, the percentage of

boys engaged in gaming on a school day was up to 4-5 times

higher than the percentage of girls engaged in gaming on

a school day.

These

differences become even more evident

when looking at the engagement in gaming among boys and

girls on non-school days (Table 12b).

6.4

4.4

2-3

0.5

2-3

Average

0.5

Min.

Max.

(

) Percentage of students who spent no hours on social media in the last

7 days.

(

) Percentage of students who spent no hours on gaming in the last 30

days.

(

) Modal class of mean number of hours spent on social media in the

last 7 days among those who used social media.

(

) Modal class of mean number of hours spent gaming in the last 30

days among those who played games.

(

) Self-perceived problems with computer gaming and internet use

based on a short non-clinical scale, adapted from Holstein et al., 2014:

percentage of high-risk problem users.

Self-perceived problems with social media use

and gaming

Two summary indexes for the estimation of perceived risks

related to social media use and gaming were calculated

(range 0-3).

These

non-clinical screening tools (Holstein

et al., 2014) focus on a student’s perception of problems

related to time spent on these activities, of bad feelings

in case of restricted access and of family concerns. Index

scores of 0-1 and 2-3 were considered to be indicative

of self-perceived low and high risks of problem use,

respectively. For more details, see the methodology section.

On average, 46 % of students scored 2-3 points on the

index for self-perceived problems with social media use,

suggesting a high risk of problems related to social media

use; this ranged from 31-32 % in Denmark, Poland and

Iceland, to 63 % in Montenegro. Similarly, on average, 21 %

of students scored 2-3 points on the index for self-perceived

problems with gaming, suggesting a high risk of problems

related to gaming; this ranged from 12 % in Denmark to 44 %

in Georgia (Table 12c).

Noticeable gender differences, albeit in different directions,

were found for both self-perceived problems with social

media use and self-perceived problems with gaming. Higher

rates of problems related to social media use were found

among girls than among boys in all countries except Kosovo

(51 % for boys versus 47 % for girls); the gender difference

was more than 10 percentage points in all countries except

Georgia and Kosovo. Particularly large gender differences

were observed in the Faroes (66 % for girls versus 40 % for

boys), Slovakia (57 % versus 33 %) and Serbia (67 % versus

45 %).

Social media use

About 94 % of the ESPAD students reported use of social

media in the last 7 days. In all participating countries, the

most commonly reported amount of time spent on social

media, on a typical school day within the last 7 days, was on

average 2-3 hours a day (Table 12a).

The

comparative

figure

for a typical non-school day was 6 or more hours (Table 12b).

The

frequency of use on a non-school day was lower in

Austria, Czechia, Denmark, Iceland and Slovenia (2-3 hours),

as well as in Estonia, Germany, Spain and Sweden (4-5

hours). In many ESPAD countries, girls spent more time on

social media than boys, particularly on a typical non-school

day. On school days, girls spent more time than boys using

social media in North Macedonia, Montenegro, Romania,

Ukraine (2-3 hours for boys versus 6 or more hours for girls)

and Georgia (none for boys versus 2-3 hours for girls), as well

as in Czechia and Monaco (about 1 hour versus 2-3 hours)

and Finland (2-3 hours versus 4-5 hours).

Gaming

With regard to gaming activities, 41 % of the ESPAD students

reported not having played digital games on a typical school

day within the last 30 days, and 32 % reported not having

played digital games on a non-school day within the last

30 days.

The

exceptions to this were Bulgaria and Sweden,

where almost 70 % of students on a school day and almost

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e situation in 2019

Contrary to this, all ESPAD countries reported higher rates

of self-perceived problems with gaming among boys than

among girls.

The

highest gender differences were observed

in Portugal (43 % for boys versus 7.3 % for girls) and the

Faroes (40 % versus 8.6 %).

Table 12a.

Average number of hours spent on social media in the last 7 days (modal class) on a typical school day by

gender (percentage)

Social media hours last week: school day

Country

About 1

Half About

None

Half an hour

2-3 hours

4-5 hours

6+ hours

2-3 4-5

hour

None an

hours hours hours

hour hour

Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls

4.5

3.8

5.1

1.8

3.6

3.0

1.4

–

2.2

5.9

4.9

7.6

3.6

5.4

2.8

6.0

8.6

2.8

6.4

3.0

4.0

6.0

3.9

6.9

5.0

2.9

3.6

6.5

6.9

6.4

8.7

7.7

8.8

1.7

–

8.0

6.2

5.5

8.1

7.0

6.3

6.8

7.8

6.9

8.6

8.3

4.7

8.9

8.6

–

9.4

–

7.2

5.8

7.0

2.9

5.3

2.6

–

3.4

7.6

6.9

5.3

7.4

4.6

8.7

5.3

3.8

6.3

8.0

5.9

8.8

7.5

4.0

5.4

8.9

1.8

1.7

5.6

3.2

0.9

2.1

0.8

0.1

–

1.1

4.3

2.9

4.4

2.0

3.2

0.9

3.4

5.5

0.5

2.9

2.3

1.8

4.2

2.2

5.0

2.6

9.5

1.8

1.9

3.2

3.0

4.0

2.6

–

8.1

7.0

9.3

7.0

9.2

5.9

8.7

8.9

5.0

5.1

6.8

6.6

5.9

0.7

–

6.2

6.1

7.9

4.4

4.0

8.3

4.7

4.5

5.5

4.5

6.0

4.7

6.1

4.8

8.3

3.5

9.1

7.4

6.7

9.0

5.7

–

4.9

–

8.5

–

8.9

–

9.2

–

8.2

9.2

–

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Modal class

All students

Boys

Girls

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e situation in 2019

Table 12b.

Average number of hours spent on social media in the last 7 days (modal class) on a typical non-school day by

gender (percentage)

Social media hours last

week: non-school day

Social media hours last week: non-school day

Country

About 1

Half About

None

Half an hour

2-3 hours

4-5 hours

6+ hours

2-3 4-5

hour

None an

hours hours hours

hour hour

Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls

5.0

3.9

6.8

4.5

2.1

3.2

2.4

1.5

–

1.1

2.9

3.7

7.9

2.7

3.7

2.4

4.6

2.9

0.9

6.0

2.8

7.2

2.8

5.8

3.1

6.3

3.5

3.2

2.6

1.9

4.2

6.2

4.4

9.4

4.5

6.5

3.3

6.2

7.0

5.4

1.6

–

6.9

5.6

3.5

5.5

5.7

2.8

3.3

3.9

6.4

3.1

3.0

5.4

4.0

1.4

4.2

5.0

6.8

5.7

3.4

4.4

6.3

7.2

3.4

4.2

7.1

9.4

9.0

7.8

4.0

–

9.0

5.7

7.6

5.6

6.0

8.9

9.4

9.1

8.3

–

7.5

6.0

5.6

3.3

5.0

4.5

2.9

–

1.8

4.3

5.2

3.9

5.5

4.3

6.2

4.1

1.9

9.2

3.8

9.0

4.4

8.0

4.5

8.4

5.9

5.1

3.6

3.0

6.5

2.5

6.3

1.7

3.2

3.3

0.9

1.5

0.4

0.1

–

6.7

0.5

1.6

2.2

4.4

1.5

1.7

9.4

0.5

2.9

1.5

0.0

2.8

1.9

5.6

1.2

3.8

1.9

4.3

1.3

1.4

1.7

0.8

1.8

2.4

2.5

6.2

8.8

5.1

7.5

9.1

7.8

2.5

–

9.0

8.5

4.6

6.9

7.9

4.5

4.6

3.9

9.2

5.3

3.7

8.3

5.5

2.0

5.1

7.1

9.1

7.7

4.4

7.5

8.7

4.9

5.6

5.9

2.9

4.0

2.0

5.0

5.1

3.1

0.6

–

5.0

2.8

2.4

4.1

3.6

1.3

1.9

3.9

3.7

1.0

2.3

2.7

2.6

0.8

3.3

3.0

4.7

3.9

2.5

1.6

4.1

4.4

2.0

2.9

3.5

5.8

–

7.1

8.6

5.7

6.3

5.1

7.9

8.0

5.5

2.3

–

7.7

6.7

5.5

6.3

7.3

4.4

7.5

8.0

5.1

4.2

7.3

6.7

3.4

7.1

6.5

9.1

7.3

6.3

5.9

8.1

5.3

8.1

8.4

–

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Modal class

All students

Boys

Girls

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e situation in 2019

Table 12c.

Average number of hours spent on gaming in the last 30 days (modal class) on a typical school day by gender

(percentage)

Gaming hours last 30 days: school day

Country

About 1

None

Half an hour

2-3 hours

4-5 hours

6+ hours

Half

hour

About 2-3 4-5

None an

1 hour hours hours hours

hour

Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls

–

7.5

6.3

6.6

4.5

2.9

6.9

9.2

8.5

7.3

8.6

–

3.8

5.1

4.3

4.1

8.5

4.3

3.8

2.2

6.8

6.6

5.4

5.0

4.0

3.5

8.1

8.9

4.8

5.6

3.5

3.9

3.5

3.0

6.6

8.7

6.4

9.8

6.5

3.8

4.4

5.9

9.0

6.9

–

3.9

5.7

3.7

5.5

3.9

4.1

3.6

8.0

7.2

6.3

5.2

6.7

4.3

6.8

7.2

5.5

5.8

4.1

5.4

2.7

3.2

6.2

9.6

9.2

7.7

–

8.8

9.4

–

6.7

–

8.9

6.9

8.7

6.7

7.8

7.4

8.3

–

6.0

6.9

6.1

7.4

9.4

–

6.3

7.6

3.7

6.6

2.4

6.1

3.7

7.7

7.1

6.4

6.1

8.4

4.3

6.8

4.9

5.0

6.0

4.6

4.0

4.2

9.3

8.6

7.0

3.6

–

6.0

8.3

7.2

6.4

7.3

5.4

3.2

8.8

8.2

5.8

5.4

8.5

9.2

5.7

6.7

6.2

4.4

3.2

4.6

1.8

2.4

1.8

2.6

2.9

1.9

2.8

–

1.9

2.0

1.6

1.7

3.7

1.6

2.0

1.4

2.1

3.6

4.3

1.4

1.8

2.1

1.8

2.1

3.4

1.6

2.0

1.4

1.3

1.0

1.7

2.6

5.3

6.2

7.6

–

6.6

6.4

9.0

6.6

6.7

6.1

7.7

6.2

6.9

8.9

7.0

5.0

5.9

3.2

6.8

2.7

2.1

1.1

1.6

3.2

2.7

1.9

–

1.5

1.2

1.9

3.1

1.3

1.4

2.0

2.5

2.8

2.7

2.3

2.5

1.9

3.6

1.2

2.8

1.3

1.1

0.6

0.8

1.9

5.0

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Modal class

All students

Boys

Girls

Among gamers

Among male gamers

Among female gamers

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e situation in 2019

Table 12d.

Average number of hours spent on gaming in the last 30 days (modal class) on a typical non-school day by

gender (percentage)

Gaming hours last 30 days:

non-school day

Gaming hours last 30 days: non-school day

Country

Half an

About 1

Half About

None

2-3 hours 4-5 hours

6+ hours

2-3 4-5

hour

None an

hours hours hours

hour hour

Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls

–

9.3

–

9.3

9.0

8.9

–

9.3

8.9

9.7

–

9.9

–

9.3

8.6

6.3

8.4

9.0

9.2

8.5

9.6

–

9.1

7.9

8.4

6.8

6.2

5.6

–

7.7

9.1

9.4

8.4

8.6

–

7.5

7.1

9.0

7.3

9.5

6.9

6.2

4.9

6.6

–

8.4

7.1

6.3

5.5

6.9

8.7

8.5

5.3

6.8

4.8

7.8

4.6

5.7

5.0

8.5

9.5

8.2

5.7

4.6

8.7

–

8.9

–

8.9

8.6

6.6

–

8.1

7.4

7.2

9.8

–

6.6

8.8

8.9

–

5.8

6.9

5.9

9.3

9.8

8.2

8.0

9.4

9.5

8.3

9.5

7.5

6.6

–

9.7

5.0

8.4

4.0

5.2

4.2

5.8

7.2

4.7

5.9

–

5.2

5.5

3.3

5.0

5.5

2.5

4.0

3.4

4.0

8.2

6.0

2.7

4.3

5.4

3.9

5.5

3.4

3.3

4.7

3.2

2.7

4.4

6.5

7.4

–

5.3

3.5

5.4

2.5

3.1

5.7

1.6

3.6

–

4.7

3.0

5.3

3.5

2.6

3.4

3.1

3.6

5.9

7.4

5.9

3.7

6.1

4.7

4.0

5.3

3.5

4.0

4.2

3.4

1.7

3.0

6.1

8.1

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Modal class

All students

Boys

Girls

Among gamers

Among male gamers

Among female gamers

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e situation in 2019

Table 12e.

Country

Austria

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany

Greece

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lithuania

Malta

Monaco

Montenegro

Netherlands

Self-perceived high risk of problems with social media use and gaming (percentage)

Social media

–

Gaming

–

Social media

Boys

–

Girls

–

Boys

–

Gaming

Girls

4.3

3.9

2.5

3.8

8.6

3.6

–

5.7

8.2

8.3

6.6

7.0

6.2

5.0

6.6

7.3

5.1

6.9

5.0

2.5

North Macedonia

Norway

Poland

Portugal

Romania

Serbia

Slovakia

Slovenia

Spain

Sweden

Ukraine

Average

Min.

Max.

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Trends

1995-2019

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Trends 1995-2019

This

chapter presents changes in selected indicators of

substance use from 1995 to 2019.

The

indicators covered

include students’ perceptions of substance availability,

early onset of substance use, prevalence and patterns

of substance use. Trends in the selected indicators were

calculated using the ESPAD 1995-2019 trend database,

which includes data from all of the available national

survey waves since the inception of the ESPAD project.

It is therefore possible that the results presented in this

section differ slightly from those in the 2015 report, as

at the time no such database existed and the trends in

selected indicators of substance use were calculated using

the survey prevalence results reported in previous ESPAD

reports. It is also possible that for specific years data from

some countries were not included because, even though

the survey was conducted, the respective dataset was not

available to be merged into the ESPAD 1995-2019 trend

database. For more detailed information on the ESPAD

1995-2019 trend database, see the methodology section.

Sample sizes for all countries that participated in the 2019

data collection are shown in Table 13.

Table 13.

Overview of ESPAD surveys conducted between 1995 and 2019 by country contained in the ESPAD trend

database 1995-2019. Sample size.

Country

1995

–

– (

)

– (

)

2 946

2 216

– (

)

480

2 160

–

8 801

3 668

1 839

–

1 437

–

1999

–

– (

)

3 555

– (

)

3 543

1 546

– (

)

413

3 005

2 266

–

2 195

– (

)

2 383

3 457

– (

)

–

4 073

–

2003

–

2 354

1 291

973

–

2 666

2 852

2 142

3 149

2 504

2 431

582

3 219

2 277

–

811

3 058

1 891

502

2 647

3 313

– (

)

710

4 818

–

2007

–

4 055

2 571

1 889 (

)

–

2 973 (

)

2 609 (

)

2 353

3 008

6 340

3 901

877 (

)

2 372

552

4 988

2 918

–

814

5 011

3 060

–

2 816

3 510

2 221

740

9 981

–

2011

3 189

–

1 797 (

)

–

4 528 (

)

3 132

2 217

3 002

4 243

3 913

2 181

2 460

557

3 744

2 572

–

724

2 796

1 706

–

3 063

3 333

2 207

– (

)

4 837

2 324 (

)

2015

2 553

–

3 694 (

)

1 771 (

)

–

2 922

2 558

2 098

2 773

1 670

2 452

511

4 049

2 714

1 966 (

)

862

–

3 202

–

2 647

2 663

1 470

–

4 059

–

2019

–

4 334 (

)

–

2 864

2 772

1 224

2 778

2 487 (

)

2 520

511 (

)

4 541

2 588 (

a,h

)

3 092

1 459

–

5 988

–

2 355

2 534 (

)

1 940

–

2 542 (

)

1 756

Albania

Armenia

Austria

Belgium (Flanders)

Belgium (Wallonia)

Bosnia and Herzegovina

(FBiH)

Bosnia and Herzegovina (RS)

Bulgaria

Croatia

Cyprus

Czechia

Denmark

Estonia

Faroes

Finland

France

Georgia

Germany (Bavaria) (

)

Germany (

)

Greece

Greenland

Hungary

Iceland

Ireland

Isle of Man

Italy

Kosovo

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Trends 1995-2019

Country

Latvia

Liechtenstein

Lithuania

Malta

Moldova

Monaco

Montenegro

Netherlands

North Macedonia

Norway

Poland

Portugal

Romania

Russia (Moscow district)

Russia (excluding Moscow)

Serbia

Slovakia

Slovenia

Spain

Sweden

Switzerland

Turkey

Ukraine

United Kingdom

1995

– (

)

–

– (

)

– (

)

–

3 887

4 898

2 032

–

2 385

2 410

–

3 467

–

– (

)

6 624

7 674

1999

2 289

–

– (

)

3 635

–

2 581

– (

)

3 753

2 328

3 577

2 368

2 918

–

2 437

2 347

–

3 271

–

2 778

2 583

2003

2 816

–

5 028

3 443

–

2 070

–

3 745

3 798

2 919

4 330

1 883

–

2 122

2 758

–

3 212

2 572

3 909

4 102

2 003

2007

2 275

–

2 411

3 668

3 176 (

)

393

5 823 (

)

2 088

2 452 (

)

3 484

2 120

3 141

2 292

1 973

1 966

6 156 (

)

2 468

3 085

–

3 179

2 499

–

2 443

2 179

2011

2 622

366

2 476

3 377

2 162

401

3 387

2 044 (

)

–

2 927

2 472

1 965

2 772

1 757

–

6 084

2 009

3 186

–

2 569

–

2 210

1 683 (

)

2015

1 119 (

a,f,h

)

316 (

)

2 573

3 326

2 586

397

3 844

1 684 (

a,d

)

2 428

2 575

3 289

3 456

3 500

–

2 208

3 484

–

2 551

–

2 472

–

2019

2 743

–

2 393

3 043

–

428

5 700

1 288 (

a,d

)

2 930

4 313 (

)

2 372

4 365

3 764

–

3 529

2 258

3 413

3 557

2 546

–

2 731

–

(

) Data collected online (web survey).

(

) Data collected in the autumn of the previous year.

(

) Data collected in 2008 instead of 2007.

(

) Data collected in the autumn of the same year.

(

) Data collected but not delivered.

(

) Limited comparability.

(

) Data collected with a mixed mode (paper and pencil and web based).

(

) Data collected in 2018 instead of 2019.

(

) In Germany the study was performed: in 2003 in 6 federal states; in 2007 in 7 federal states; in 2011 in 5 federal states; in 2015 and 2019 in the

Bavaria federal state only. For comparative reasons in the ESPAD trend database the data related to Bavaria have been extracted to compute

trends.

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Trends 1995-2019

Trends across 30 countries

In this section, overall trends measured using country-

specific means from 30 countries are reported between

1995 and 2019.

The

30 countries included were Austria,

Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia,

the Faroes, Finland, France, Germany (Bavaria), Greece,

Countries included in the 30-country average

Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Malta,

Monaco, Montenegro, the Netherlands, Norway, Poland,

Portugal, Romania, Slovakia, Slovenia, Sweden and Ukraine

(Figure 11). Trends for 15 key variables are shown in

Table 14 and trends by gender are graphically depicted in

Figures 12-26.

Figure 11.

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Trends 1995-2019

Table 14.

ESPAD average for selected indicators based on 30 countries: 1995-2019 (percentage)

Measure

1995

–

1.6

3.3

4.1

7.4

1999

–

9.3

2.6

6.3

6.7

8.0

7.3

2003

–

3.5

5.2

7.0

9.0

6.1

2007

7.3

3.7

7.0

6.4

8.8

6.7

2011

7.1

3.3

6.3

7.6

6.9

2015

4.2

3.2

5.2

7.2

7.8

6.3

2019 (

)

3.0

2.5

5.1

7.4

7.9

7.0

4.0

2019 cigarette

and/or e-cig-

arette use (

)

Perceived availability of cannabis (

)

Early onset of daily cigarette use

Early onset of cannabis use

Lifetime use of cigarettes

Current cigarette use

Daily cigarette use

Lifetime alcohol use

Current alcohol use

Heavy episodic drinking

Lifetime illicit drug use

Lifetime cannabis use

Lifetime use of illicit drugs other than cannabis

Current cannabis use

Lifetime inhalant use

Lifetime use of tranquillisers or sedatives

without a doctor's prescription

(

) In the ESPAD 2019 questionnaire questions about cigarette smoking specifically exclude e-cigarettes. Prevalence estimates for 2019 are therefore

reported separately for cigarette use and cigarette and/or e-cigarette use.

(

) In 1995-2003 cannabis was combined with other substances but since 2007 cannabis availability has been measured separately. A 2006 ques-

tionnaire test in eight countries showed significant differences in results between the two approaches; hence, trends cannot be compared be-

tween the years before 2007 and the years after 2007.

Perceived availability of cannabis

The

average percentage of students reporting that they

would

find

it easy (combined positive responses of ‘very

easy’ and ‘fairly easy’) to obtain cannabis if they wanted

to remained substantially stable between 2007 and 2019.

Rates among boys were slightly higher than those among

girls (Figure 12). Overall, the perceived availability of

cannabis increased between 2007 and 2019 from 34 % to

35 % among boys and from 31 % to 32 % among girls.

of early onset of daily smoking (3.5 % for boys and 2.6 %

for girls), while if e-cigarette use is included the rate was

2 percentage points higher among boys than among girls

(Figure 13).

Cannabis use

On average, the rate of early onset of cannabis use (at age

13 or younger) increased slightly between 1995 and 2007

and slowly decreased thereafter (Table 14). Trends by gender

are almost parallel, with the rate among girls being slightly

lower than the rate among boys (Figure 14).

Early onset of substance use

Daily smoking

On average, between 1995 and 2003 the rate of early

onset of daily cigarette smoking (at age 13 or younger)

was relatively stable at about 10 %, with the rate dropping

thereafter by 2019 to 3 % if cigarettes only are considered

(or to 4 % if e-cigarettes are included).

This

general trend

indicates a large decrease in the rate of early onset of daily

smoking over the last 10 years (Table 14). Gender-specific

trends are almost parallel, with slightly lower rates among

girls than among boys. In 2019, if only cigarette smoking is

considered, there was a small gender difference in the rate

Cigarette use

On average, lifetime prevalence of cigarette use showed

a stable trend between 1995 and 2003 and decreased

thereafter (Table 14). Interestingly, if both cigarette and

e-cigarette use are analysed as a combined value, the 2019

rate is higher (by 7 percentage points) than the 2015 rate,

almost reaching the level observed in 2011. It should be

borne in mind that in 2015 and 2011 specific information

on e-cigarette use was not collected in all countries and so

a combined value is not available for comparison.

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Trends 1995-2019

Lifetime cigarette use rates were generally higher among

boys than among girls, but the gender gap visible in 1995

narrowed in 2019 (Figure 15). However, if both cigarette use

and e-cigarette use are considered as a combined variable,

in 2019, the lifetime prevalence rate among boys was far

higher than that among girls compared with previous years

(57 % versus 50 %).

Similar trends can be observed for current cigarette use and

daily cigarette use (Table 14).

The

rate of current (last-30-

day) use decreased by 13 percentage points between 1995

and 2019 (Table 14 and Figure 16), and the reduction in daily

use between 1995 and 2019 amounted to 10 percentage

points (Table 14 and Figure 17). For both indicators, if

e-cigarette use is also considered, in 2019, the prevalence

rate increases to 27 % for current use and 12 % for daily use

(Table 14).

occurred between 1995 and 1999. Since 2011, the

prevalence has started to decrease slowly.

The

lifetime

prevalence of illicit drug use among boys and girls follows

a parallel trend, with the rate among girls being about

5-6 percentage points lower than that among boys

(Figure 21). As cannabis is the most widely used illicit drug,

the trend for lifetime cannabis use is similar to the trend for

any illicit drug use, with rates of the former being only slightly

lower across all years (Table 14).

The

prevalence rate of

lifetime cannabis use among boys peaked in 2003, remained

stable until 2011 and started to decrease thereafter.

The

prevalence rate of lifetime cannabis use among girls peaked

in 2003 and stabilised thereafter (Figure 22).

The

rate of

current (last-30-day) use of cannabis reached its highest

level in 2011, stabilising thereafter, with gender differences

of 2-3 percentage points across all years (Table 14 and

Figure 23).

Lifetime use of illicit drugs other than cannabis rose to

a peak in 2007 (Table 14). After 2007, the rate decreased

slightly until 2015 and then stabilised in 2019.

The

same

trend is observed among boys and girls, with a gender gap of

1-2 percentage points across all years (Figure 24).

Alcohol use

The

prevalence of lifetime use and prevalence of current

(last-30-day) use of alcohol increased until 2003 before

declining, reaching their lowest level in 2019 (Table 14).

No gender differences in trends can be observed. However,

while lifetime alcohol use rates among boys and girls were

almost equal throughout the whole 1995-2019 period

(Figure 18), current alcohol use rates among boys were

generally higher than those among girls until 2011, when the

gender gap started to narrow, with the gap disappearing in

2019 (Figure 19).

The

prevalence of heavy episodic drinking peaked in 2007

and has decreased since then, reaching its lowest level in

2019 (Table 14). Comparing 2019 with 1995 rates, there was

an overall increase in heavy episodic drinking among girls

(from 30 % to 34 %) and a decrease among boys (from 41 %

to 36 %), resulting in a narrowing of the gender difference

over time (Figure 20).

Inhalant use

The

lifetime use of inhalants increased steadily until

2011, with a decrease observed thereafter (Table 14).

The

gender-specific curves over the period 1995-2019 reveal

a progressive narrowing of the gender gap, which has almost

disappeared since 2011 (Figure 25).

Pharmaceuticals for non-medical use:

tranquillisers and sedatives without a doctor’s

prescription

The

lifetime prevalence rate for the use of tranquillisers or

sedatives without a doctor’s prescription shows a rather

stable trend, with slight

fluctuations

between 1995 and

2007 (Table 14). Trends for both genders are similar, with

tranquillisers or sedatives being the only psychoactive

substances for which overall prevalence rates are higher

among girls than boys (Figure 26).

Illicit drug use

Generally, between 1995 and 2011, there was an increase

in the lifetime prevalence of illicit drug use, most of which

ESPAD Report 2019

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Trends 1995-2019

Figure 12.

Perceived availability of cannabis by gender:

students responding cannabis ‘fairly easy’ or

‘very easy’ to obtain — 30-country trend 1995-

2019 (percentage) (

)

Girls

Figure 13.

Daily cigarette use at the age of 13 or younger

by gender: 30-country trend 1995-2019

(percentage)

Girls

Boys

1995

1999

2003

Boys

2007

2011

2015

2019

1995

1999

2003

2007

2011

2015

2019 (

)

(

) In 1995-2003 cannabis was combined with other substances but

since 2007 cannabis availability has been measured separately.

A 2006 questionnaire test in eight countries showed significant differences

in results between the two approaches; hence, trends cannot be compared

between the years before 2007 and the years after 2007.

(

) In the ESPAD 2019 questionnaire questions about cigarette smoking

specifically exclude e-cigarettes. Prevalence estimates for 2019 are

therefore reported separately for cigarette use (solid line) and cigarette

and/or e-cigarette use (dashed line, data not comparable).

Figure 14.

Cannabis use at the age of 13 or younger

by gender: 30-country trend 1995-2019

(percentage)

Girls

Figure 15.

Lifetime use of cigarettes by gender: 30-country

trend 1995-2019 (percentage)

Girls

Boys

1995

1999

2003

Boys

2007

2011

2015

2019

1995

1999

2003

2007

2011

2015

2019 (

)

(

) In the ESPAD 2019 questionnaire, questions about cigarette smoking

specifically exclude e-cigarettes. Prevalence estimates for 2019 are

therefore reported separately for cigarette use (solid line) and cigarette

and/or e-cigarette use (dashed line, data not comparable).

Figure 16.

Boys

1995

1999

Cigarette use in the last 30 days by gender:

30-country trend 1995-2019 (percentage)

Girls

Figure 17.

Boys

Daily cigarette use by gender: 30-country trend

1995-2019 (percentage)

Girls

2003

2007

2011

2015

2019 (

)

1995

1999

2003

2007

2011

2015

2019 (

)

(

) In the ESPAD 2019 questionnaire, questions about cigarette smoking

specifically exclude e-cigarettes. Prevalence estimates for 2019 are

therefore reported separately for cigarette use (solid line) and cigarette

and/or e-cigarette use (dashed line, data not comparable).

(a) In the ESPAD 2019 questionnaire, questions about cigarette smoking

specifically exclude e-cigarettes. Prevalence estimates for 2019 are

therefore reported separately for cigarette use (solid line) and cigarette

and/or e-cigarette use (dashed line, data not comparable).

ESPAD Report 2019

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Trends 1995-2019

Figure 18.

Boys

100

1995

Lifetime alcohol use by gender: 30-country

trend 1995-2019 (percentage)

Girls

Figure 19.

Boys

Alcohol use in the last 30 days by gender:

30-country trend 1995-2019 (percentage)

Girls

1999

2003

2007

2011

2015

2019

1995

1999

2003

2007

2011

2015

2019

Figure 20.

Heavy episodic drinking (five or more drinks

on one occasion (

)) during the last 30 days

by gender: 30-country trend 1995-2019

(percentage) (

)

Girls

Figure 21.

Lifetime use of illicit drugs (

) by gender:

30-country trend 1995-2019 (percentage)

Boys

1995

Boys

1995

Girls

1999

2003

2007

2011

2015

2019

1999

2003

2007

2011

2015

2019

(

)

National examples are given so that a ‘drink’ is understood to contain

roughly the same amount of pure alcohol as a glass of wine.

(

) In 1995-2003 the question referred to ‘five or more drinks in a row’ and

neither cider nor premixed drinks were included among the examples.

A 2006 questionnaire test in eight countries found no significant differ-

ences between the two approaches.

(a) Includes cannabis, amphetamine, cocaine, crack, ecstasy, LSD or other

hallucinogens, heroin and (since 2007) GHB. Amphetamines were not

included in 1995 in Czechia. Crack and LSD or other hallucinogens

were not included in 1999 in the Netherlands. Crack was not includ-

ed in 2015 in Denmark, Estonia, Finland and Sweden and in 2019

in Finland, Latvia and Norway. Cannabis was not included in 1995 in

Denmark.

Figure 22.

Boys

1995

Lifetime use of cannabis by gender: 30-country

trend 1995-2019 (percentage)

Girls

Figure 23.

Boys

1995

Cannabis use in the last 30 days by gender:

30-country trend 1995-2019 (percentage)

Girls

1999

2003

2007

2011

2015

2019

1999

2003

2007

2011

2015

2019

ESPAD Report 2019

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Trends 1995-2019

Figure 24.

Lifetime use of illicit drugs (

) other than

cannabis by gender: 30-country trend

1995-2019 (percentage)

Girls

Figure 25.

Lifetime use of inhalants by gender: 30-country

trend 1995-2019 (percentage)

Girls

Boys

1995

Boys

1995

1999

2003

2007

2011

2015

2019

1999

2003

2007

2011

2015

2019

(a) Includes amphetamine, cocaine, crack, ecstasy, LSD or other hallucino-

gens, heroin and (since 2007) GHB. Amphetamines were not included

in 1995 in Czechia. Crack and LSD or other hallucinogens were not

included in 1999 in the Netherlands. Crack was not included in 2015 in

Denmark, Estonia, Finland and Sweden and in 2019 in Finland, Latvia

and Norway.

Figure 26.

Lifetime use of tranquillisers or sedatives

without a doctor’s prescription by gender:

30-country trend 1995-2019 (percentage)

Girls

Boys

1995

1999

2003

2007

2011

2015

2019

ESPAD Report 2019

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Trends 1995-2019

Country-specific trends

Individual country trends for eight key substance use

variables for available years between 1995 and 2019 are

shown in Figures 27-34 (see Additional Tables 102, 104,

106, 114, 118, 120, 122, 124 for the corresponding values).

Trends, illustrated graphically, were estimated using analysis

of variance, with survey year as the independent variable

in the model. Post hoc tests (Tukey or Games-Howell,

depending on the homogeneity of the variances) were used

to assess which years were responsible for the changes in

prevalence. Temporal changes in countries with only two

data points should be interpreted with caution.

Lifetime alcohol use

The

prevalence of lifetime alcohol use showed an overall

decline between 2015 and 2019 in 13 countries (Figure 29).

In Lithuania and Sweden, substantial reductions of

7-8 percentage points have been observed since 2015.

The

only countries where alcohol use increased were

North Macedonia, with the prevalence of alcohol use

rising by 10 percentage points since 2015, and Portugal

and Romania, with an increase of 4-5 percentage points

with respect to the prevalence observed in 2015. Lifetime

prevalence remained relatively stable in the other ESPAD

countries.

Lifetime cigarette use

Considering only tobacco smoking, a general decreasing

trend in lifetime prevalence can be observed in the last

survey years. Between 2015 and 2019 a significant

decrease was found in 18 countries.

The

greatest decrease

was observed in Czechia and Estonia, with a reduction in

prevalence of 12 percentage points, followed by Monaco

(11 percentage points) and France, Germany, Lithuania

and Slovenia (9-10 percentage points each) (Figure 27).

In Denmark, the Faroes, Hungary, Iceland, Ireland, North

Macedonia, Norway, Portugal, Serbia, Slovakia and Ukraine,

there was no change since 2015. Only three countries (Italy,

Montenegro and Romania) do not follow the overall trend

of a decline in tobacco smoking, instead displaying stable

prevalence rates over the last three surveys. When looking

at the cumulative prevalence of cigarette and/or e-cigarette

use, 20 countries showed a significant increase between

2015 and 2019.

Heavy episodic drinking

North Macedonia, Portugal and Ireland also show an

increasing trend in heavy episodic drinking in the last 30

days between 2015 and 2019 (Figure 30). In 11 countries

a decreasing trend can be observed between 2015 and

2019, particularly in Cyprus, with a substantial reduction

of 14 percentage points, and Greece, Malta, Latvia and

Lithuania, with a reduction of 7-8 percentage points.

In the majority of ESPAD countries the prevalence of heavy

episodic drinking in the last 30 days remained relatively

stable.

Lifetime cannabis use

In most participating countries, the prevalence of lifetime

cannabis use increased between 1995 and 2003/2007

(Figure 31). In 2007 an increase was registered in

five

ESPAD countries, while a decrease was shown in 10

countries. In 2015 lifetime prevalence rates increased

significantly in six countries and decreased significantly in

seven. After this, decreases in prevalence occurred in 2019

in Bulgaria, Czechia, Estonia, Finland, France, Monaco and

Portugal. In contrast, increases since 2015 occurred in

Denmark and Norway. Lower rates of lifetime cannabis use

in 2019 compared with 1995 can be observed in the Faroes,

Iceland, Ireland and Ukraine.

Daily cigarette use

The

trends in the prevalence of daily cigarette use follow the

pattern observed for lifetime cigarette smoking, showing

a decrease in 15 countries between 2015 and 2019 and no

significant changes in the remaining countries (Figure 28).

Reductions of 6-7 percentage points can be observed in

Austria, Czechia, the Netherlands, Lithuania and Monaco

with respect to 2015 prevalence rates.

When considering cigarette and/or e-cigarette use,

the majority of countries show no significant change

in prevalence rate since 2015; eight countries show

a statistically significant decrease in rate, while Iceland,

Ireland, Lithuania and Norway show a statistically significant

increase.

Current cannabis use

The

prevalence of current cannabis use has been quite

stable in more than two thirds of the countries from 1995 to

2019 (Figure 32). Increasing rates with respect to the 2015

prevalence can be observed in Austria, Croatia, Finland,

Latvia, Montenegro and Norway. Since 2015 decreases

of 4-5 percentage points can be observed in Bulgaria and

France.

ESPAD Report 2019

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Trends 1995-2019

Lifetime use of illicit drugs other than cannabis

The

prevalence of lifetime use of illicit drugs other than

cannabis increased significantly in 2007 compared with

the previous survey year (Table 14), reaching a peak in the

majority of ESPAD countries. Since 2007, the rates appear

to have slightly decreased or stabilised, except in Estonia,

Montenegro and Portugal (Figure 33). Compared with 2015,

a significant reduction in prevalence was observed in 2019

in Bulgaria, North Macedonia, Italy, Malta, Montenegro,

Poland and Romania. Estonia and Portugal are the only two

countries where a significant increase in prevalence was

observed compared with 2015.

Lifetime use of tranquillisers or sedatives without

a doctor’s prescription

The

prevalence of lifetime use of tranquillisers or sedatives

without a doctor’s prescription was generally stable across

years in the large majority of ESPAD countries. Between

2015 and 2019, a significant decrease in prevalence was

observed in Bulgaria, Croatia, Czechia and North Macedonia.

In contrast, Austria, Denmark, Estonia, Latvia, Lithuania and

Slovakia showed a significant increase in prevalence over the

same time period (Figure 34).

ESPAD Report 2019

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Trends 1995-2019

Figure 27.

Lifetime use of cigarettes by country: 1995-2019 (

) (percentage)

Austria

Bulgaria

Croatia

Cyprus

95 99 03 07 11 15 19

Czechia

99 03 07 11 15

Denmark

95 99 03 07 11 15 19

Estonia

95 99 03 07 11 15 19

Faroes

95 99 03 07 11 15 19

Finland

95 99 03 07 11 15 19

France

95 99 03 07 11 15 19

Georgia

95 99 03 07 11 15 19

Germany (Bavaria)

95 99 03 07 11 15 19

Greece

95 99 03 07 11 15 19

Hungary

95 99 03 07 11 15 19

Iceland

95 99 03 07 11 15 19

Ireland

95 99 03 07 11 15 19

Italy

95 99 03 07 11 15 19

Kosovo

95 99 03 07 11 15 19

Latvia

95 99 03 07 11 15 19

Lithuania

95 99 03 07 11 15 19

Malta

95 99 03 07 11 15 19

Monaco

95 99 03 07 11 15 19

Montenegro

95 99 03 07 11 15 19

Netherlands

95 99 03 07 11 15 19

North Macedonia

95 99 03 07 11 15 19

Norway

95 99 03 07 11 15 19

Poland

95 99 03 07 11 15 19

Portugal

95 99 03 07 11 15 19

Romania

95 99 03 07 11 15 19

Serbia

95 99 03 07 11 15 19

Slovakia

95 99 03 07 11 15 19

Slovenia

95 99 03 07 11 15 19

Spain

95 99 03 07 11 15 19

Sweden

95 99 03 07 11 15 19

Ukraine

95 99 03 07 11 15 19

Signi cantly lower

Not signi cantly different

Signi cantly higher

95 99 03 07 11 15 19

(

) In the ESPAD 2019 questionnaire, questions about cigarette smoking speci cally exclude e-cigarettes. Prevalence estimates for 2019

are therefore reported separately for cigarette use (solid line) and cigarette and/or e-cigarette use (dashed line, data not comparable).

ESPAD Report 2019

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Trends 1995-2019

Figure 28.

Daily use of cigarettes by country: 1995-2019 (

) (percentage)

Austria

Bulgaria

Croatia

Cyprus

95 99 03 07 11 15 19

Czechia

99 03 07 11 15

Denmark

95 99 03 07 11 15 19

Estonia

95 99 03 07 11 15 19

Faroes

95 99 03 07 11 15 19

Finland

95 99 03 07 11 15 19

France

95 99 03 07 11 15 19

Georgia

95 99 03 07 11 15 19

Germany (Bavaria)

95 99 03 07 11 15 19

Greece

95 99 03 07 11 15 19

Hungary

95 99 03 07 11 15 19

Iceland

95 99 03 07 11 15 19

Ireland

95 99 03 07 11 15 19

Italy

95 99 03 07 11 15 19

Kosovo

95 99 03 07 11 15 19

Latvia

95 99 03 07 11 15 19

Lithuania

95 99 03 07 11 15 19

Malta

95 99 03 07 11 15 19

Monaco

95 99 03 07 11 15 19

Montenegro

95 99 03 07 11 15 19

Netherlands

95 99 03 07 11 15 19

North Macedonia

95 99 03 07 11 15 19

Norway

95 99 03 07 11 15 19

Poland

95 99 03 07 11 15 19

Portugal

95 99 03 07 11 15 19

Romania

95 99 03 07 11 15 19

Serbia

95 99 03 07 11 15 19

Slovakia

95 99 03 07 11 15 19

Slovenia

95 99 03 07 11 15 19

Spain

95 99 03 07 11 15 19

Sweden

95 99 03 07 11 15 19

Ukraine

95 99 03 07 11 15 19

Signi cantly lower

Not signi cantly different

Signi cantly higher

95 99 03 07 11 15 19

(

) In the ESPAD 2019 questionnaire, questions about cigarette smoking speci cally exclude e-cigarettes. Prevalence estimates for 2019

are therefore reported separately for cigarette use (solid line) and cigarette and/or e-cigarette use (dashed line, data not comparable).

ESPAD Report 2019

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Trends 1995-2019

Figure 29.

100

Lifetime use of alcohol by country: 1995-2019 (percentage)

Austria

100

Bulgaria

100

Croatia

100

Cyprus

95 99 03 07 11 15 19

Czechia

99 03 07 11 15

Denmark

95 99 03 07 11 15 19

Estonia

95 99 03 07 11 15 19

Faroes

95 99 03 07 11 15 19

Finland

95 99 03 07 11 15 19

France

95 99 03 07 11 15 19

Georgia

95 99 03 07 11 15 19

Germany (Bavaria)

95 99 03 07 11 15 19

Greece

95 99 03 07 11 15 19

Hungary

95 99 03 07 11 15 19

Iceland

95 99 03 07 11 15 19

Ireland

95 99 03 07 11 15 19

Italy

100

95 99 03 07 11 15 19

Kosovo

95 99 03 07 11 15 19

Latvia

95 99 03 07 11 15 19

Lithuania

95 99 03 07 11 15 19

Malta

100

95 99 03 07 11 15 19

Monaco

95 99 03 07 11 15 19

Montenegro

95 99 03 07 11 15 19

Netherlands

95 99 03 07 11 15 19

North Macedonia

95 99 03 07 11 15 19

Norway

95 99 03 07 11 15 19

Poland

95 99 03 07 11 15 19

Portugal

95 99 03 07 11 15 19

Romania

95 99 03 07 11 15 19

Serbia

95 99 03 07 11 15 19

Slovakia

95 99 03 07 11 15 19

Slovenia

95 99 03 07 11 15 19

Spain

100

95 99 03 07 11 15 19

Sweden

95 99 03 07 11 15 19

Ukraine

95 99 03 07 11 15 19

Signi cantly lower

Not signi cantly different

Signi cantly higher

95 99 03 07 11 15 19

100

ESPAD Report 2019

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Trends 1995-2019

Figure 30.

100

Heavy episodic drinking (five or more drinks on one occasion (a)) during the last 30 days by country: 1995-

2019 (percentage) (

)

Austria

100

Bulgaria

100

Croatia

100

Cyprus

95 99 03 07 11 15 19

Czechia

99 03 07 11 15

Denmark

95 99 03 07 11 15 19

Estonia

95 99 03 07 11 15 19

Faroes

95 99 03 07 11 15 19

Finland

95 99 03 07 11 15 19

France

95 99 03 07 11 15 19

Georgia

95 99 03 07 11 15 19

Germany (Bavaria)

95 99 03 07 11 15 19

Greece

95 99 03 07 11 15 19

Hungary

95 99 03 07 11 15 19

Iceland

95 99 03 07 11 15 19

Ireland

95 99 03 07 11 15 19

Italy

100

95 99 03 07 11 15 19

Kosovo

95 99 03 07 11 15 19

Latvia

95 99 03 07 11 15 19

Lithuania

95 99 03 07 11 15 19

Malta

100

95 99 03 07 11 15 19

Monaco

95 99 03 07 11 15 19

Montenegro

95 99 03 07 11 15 19

Netherlands

95 99 03 07 11 15 19

North Macedonia

95 99 03 07 11 15 19

Norway

95 99 03 07 11 15 19

Poland

95 99 03 07 11 15 19

Portugal

95 99 03 07 11 15 19

Romania

95 99 03 07 11 15 19

Serbia

95 99 03 07 11 15 19

Slovakia

95 99 03 07 11 15 19

Slovenia

95 99 03 07 11 15 19

Spain

100

95 99 03 07 11 15 19

Sweden

95 99 03 07 11 15 19

Ukraine

95 99 03 07 11 15 19

Signi cantly lower

Not signi cantly different

Signi cantly higher

95 99 03 07 11 15 19

(

) National examples are given so that a 'drink' is understood to contain roughly the same amount of pure alcohol as a glass of wine.

(

) In 1995-2003 the question referred to ' ve or more drinks in a row' and neither cider nor premixed drinks were included among the

examples. A 2006 questionnaire test in eight countries found no signi cant differences between the two approaches.

ESPAD Report 2019

101

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Trends 1995-2019

Figure 31.

Lifetime use of cannabis by country: 1995-2019 (percentage)

Austria

Bulgaria

Croatia

Cyprus

95 99 03 07 11 15 19

Czechia

99 03 07 11 15

Denmark

95 99 03 07 11 15 19

Estonia

95 99 03 07 11 15 19

Faroes

95 99 03 07 11 15 19

Finland

95 99 03 07 11 15 19

France

95 99 03 07 11 15 19

Georgia

95 99 03 07 11 15 19

Germany (Bavaria)

95 99 03 07 11 15 19

Greece

95 99 03 07 11 15 19

Hungary

95 99 03 07 11 15 19

Iceland

95 99 03 07 11 15 19

Ireland

95 99 03 07 11 15 19

Italy

95 99 03 07 11 15 19

Kosovo

95 99 03 07 11 15 19

Latvia

95 99 03 07 11 15 19

Lithuania

95 99 03 07 11 15 19

Malta

95 99 03 07 11 15 19

Monaco

95 99 03 07 11 15 19

Montenegro

95 99 03 07 11 15 19

Netherlands

95 99 03 07 11 15 19

North Macedonia

95 99 03 07 11 15 19

Norway

95 99 03 07 11 15 19

Poland

95 99 03 07 11 15 19

Portugal

95 99 03 07 11 15 19

Romania

95 99 03 07 11 15 19

Serbia

95 99 03 07 11 15 19

Slovakia

95 99 03 07 11 15 19

Slovenia

95 99 03 07 11 15 19

Spain

95 99 03 07 11 15 19

Sweden

95 99 03 07 11 15 19

Ukraine

95 99 03 07 11 15 19

Signi cantly lower

Not signi cantly different

Signi cantly higher

95 99 03 07 11 15 19

102

ESPAD Report 2019

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Trends 1995-2019

Figure 32.

Current use of cannabis by country: 1995-2019 (percentage)

Austria

Bulgaria

Croatia

Cyprus

95 99 03 07 11 15 19

Czechia

99 03 07 11 15

Denmark

95 99 03 07 11 15 19

Estonia

95 99 03 07 11 15 19

Faroes

95 99 03 07 11 15 19

Finland

95 99 03 07 11 15 19

France

95 99 03 07 11 15 19

Georgia

95 99 03 07 11 15 19

Germany (Bavaria)

95 99 03 07 11 15 19

Greece

95 99 03 07 11 15 19

Hungary

95 99 03 07 11 15 19

Iceland

95 99 03 07 11 15 19

Ireland

95 99 03 07 11 15 19

Italy

95 99 03 07 11 15 19

Kosovo

95 99 03 07 11 15 19

Latvia

95 99 03 07 11 15 19

Lithuania

95 99 03 07 11 15 19

Malta

95 99 03 07 11 15 19

Monaco

95 99 03 07 11 15 19

Montenegro

95 99 03 07 11 15 19

Netherlands

95 99 03 07 11 15 19

North Macedonia

95 99 03 07 11 15 19

Norway

95 99 03 07 11 15 19

Poland

95 99 03 07 11 15 19

Portugal

95 99 03 07 11 15 19

Romania

95 99 03 07 11 15 19

Serbia

95 99 03 07 11 15 19

Slovakia

95 99 03 07 11 15 19

Slovenia

95 99 03 07 11 15 19

Spain

95 99 03 07 11 15 19

Sweden

95 99 03 07 11 15 19

Ukraine

95 99 03 07 11 15 19

Signi cantly lower

Not signi cantly different

Signi cantly higher

95 99 03 07 11 15 19

ESPAD Report 2019

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Trends 1995-2019

Figure 33.

Lifetime use of illicit drugs other than cannabis (

) by country: 1995-2019 (percentage)

Austria

Bulgaria

Croatia

Cyprus

95 99 03 07 11 15 19

Czechia

99 03 07 11 15

Denmark

95 99 03 07 11 15 19

Estonia

95 99 03 07 11 15 19

Faroes

95 99 03 07 11 15 19

Finland

95 99 03 07 11 15 19

France

95 99 03 07 11 15 19

Georgia

95 99 03 07 11 15 19

Germany (Bavaria)

95 99 03 07 11 15 19

Greece

95 99 03 07 11 15 19

Hungary

95 99 03 07 11 15 19

Iceland

95 99 03 07 11 15 19

Ireland

95 99 03 07 11 15 19

Italy

95 99 03 07 11 15 19

Kosovo

95 99 03 07 11 15 19

Latvia

95 99 03 07 11 15 19

Lithuania

95 99 03 07 11 15 19

Malta

95 99 03 07 11 15 19

Monaco

95 99 03 07 11 15 19

Montenegro

95 99 03 07 11 15 19

Netherlands

95 99 03 07 11 15 19

North Macedonia

95 99 03 07 11 15 19

Norway

95 99 03 07 11 15 19

Poland

95 99 03 07 11 15 19

Portugal

95 99 03 07 11 15 19

Romania

95 99 03 07 11 15 19

Serbia

95 99 03 07 11 15 19

Slovakia

95 99 03 07 11 15 19

Slovenia

95 99 03 07 11 15 19

Spain

95 99 03 07 11 15 19

Sweden

95 99 03 07 11 15 19

Ukraine

95 99 03 07 11 15 19

Signi cantly lower

Not signi cantly different

Signi cantly higher

95 99 03 07 11 15 19

(

) Includes amphetamine, cocaine, crack, ecstasy, LSD or other hallucinogens, heroin and (since 2007) GHB. Amphetamines were not

included in 1995 in Czechia. Crack and LSD or other hallucinogens were not included in 1999 in the Netherlands. Crack was not

included in 2015 in Denmark, Estonia, Finland and Sweden and in 2019 in Finland, Latvia and Norway.

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Trends 1995-2019

Figure 34.

Lifetime use of tranquillisers or sedatives without a doctor’s prescription by country: 1995-2019 (percentage)

Austria

Bulgaria

Croatia

Cyprus

95 99 03 07 11 15 19

Czechia

99 03 07 11 15

Denmark

95 99 03 07 11 15 19

Estonia

95 99 03 07 11 15 19

Faroes

95 99 03 07 11 15 19

Finland

95 99 03 07 11 15 19

France

95 99 03 07 11 15 19

Georgia

95 99 03 07 11 15 19

Germany (Bavaria)

95 99 03 07 11 15 19

Greece

95 99 03 07 11 15 19

Hungary

95 99 03 07 11 15 19

Iceland

95 99 03 07 11 15 19

Ireland

95 99 03 07 11 15 19

Italy

95 99 03 07 11 15 19

Kosovo

95 99 03 07 11 15 19

Latvia

95 99 03 07 11 15 19

Lithuania

95 99 03 07 11 15 19

Malta

95 99 03 07 11 15 19

Monaco

95 99 03 07 11 15 19

Montenegro

95 99 03 07 11 15 19

Netherlands

95 99 03 07 11 15 19

North Macedonia

95 99 03 07 11 15 19

Norway

95 99 03 07 11 15 19

Poland

95 99 03 07 11 15 19

Portugal

95 99 03 07 11 15 19

Romania

95 99 03 07 11 15 19

Serbia

95 99 03 07 11 15 19

Slovakia

95 99 03 07 11 15 19

Slovenia

95 99 03 07 11 15 19

Spain

95 99 03 07 11 15 19

Sweden

95 99 03 07 11 15 19

Ukraine

95 99 03 07 11 15 19

Signi cantly lower

Not signi cantly different

Signi cantly higher

95 99 03 07 11 15 19

ESPAD Report 2019

105

Discussion

and conclusion

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Discussion and conclusion

The

effects of tobacco, alcohol and drug use, as well as other

forms of risk behaviour (i.e. gambling, gaming and internet

addiction), are recognised both on an individual level and on

a societal level, and local and national governments, as well

as major international bodies, e.g. the United Nations and the

European Union, continually seek policy measures to reduce

their negative impact.

The

well-being of young people is of special concern in all

societies and constant efforts are being made to reduce

all types of risk behaviour.

These

include many aspects of

the consumption of tobacco, alcohol and different types

of illicit drugs, and, additionally today, online and gaming

addictions, which may also have negative consequences. All

countries have laws in place that restrict the availability of

psychoactive substances, and despite the legal frameworks

varying between countries they often include restrictions

specifically intended to protect young people.

Globally, as well as among adolescent students, the two

most common substances of use or abuse continue to be

alcohol and tobacco. Over past decades, international and

national control policies targeting prices, age restrictions

and availability for minors have been implemented. It has

been observed that alcohol and tobacco use among young

Europeans has declined in parallel somewhat in recent years.

The

proportion of young people who use illicit drugs has

remained rather stable over the past two decades.

This

primarily because of a stable trend in cannabis use. In spite

of the many school and community prevention activities,

the repeated messages from policymakers and the media,

and coordinated efforts to decrease the availability of illegal

drugs and implement reforms in national drug policies, the

ESPAD results show that in 2019 one in six adolescents

aged 15-16 years in Europe has used an illicit drug in their

lifetime.

An important challenge in monitoring drug use in Europe is

that it now encompasses a wider range of substances than

in the past, for example NPS such as synthetic cannabinoids

and synthetic cathinones. While consumption levels of

NPS among adolescents in Europe seem to be low, the

emergence of these new substances has raised particular

concerns, with the real extension in use being difficult to

measure. Furthermore, the non-medical use of prescription

drugs, such as tranquilisers or sedatives, has rapidly gained

popularity among adolescents, to the point that these drugs

are now the second most often reported misused substance,

excluding tobacco and alcohol, to get high; this is followed by

painkillers.

In addition, concerns related to the excessive use of social

media, gaming and gambling among young people have

been expressed by professionals, as they have been shown

to have a similar potential for addiction as psychoactive

substances.

ESPAD is committed to contributing to the systematic

collection and reporting of information about substance use

and addictive behaviours among adolescents in Europe,

and helping to understand the patterns and trends that are

critical for designing robust, more targeted policies.

This

has led the ESPAD community to extend the scope of the

2019 survey to include new substances and new forms of

risk behaviour compared with previous data collections.

NPS use, social media use, gaming and gambling patterns

and self-perceived problems related to their use, together

with a wider investigation of high-risk cannabis use, have

therefore received special attention.

Cigarette and e-cigarette use

Progress in reducing tobacco consumption has been

registered in many European areas (GBD 2015 Tobacco

Collaborators, 2017; WHO, 2019a) and the results of the

2019 ESPAD survey provide evidence in the same direction.

In 2019 the majority of ESPAD students had never smoked

traditional cigarettes (58 %) and one

fifth

of the sample

(20 %) reported being a current smoker. With regard to

national patterns, the highest prevalence of current tobacco

smoking (32 %) was reported in Bulgaria and Italy, followed

by Romania (31 %). Iceland reported by far the lowest

prevalence rate (5.1 %), followed by Norway and Malta (10 %

each).

Looking at the overall ESPAD trends for cigarette smoking,

gender differences seem to have narrowed over time. In

1995 boys showed higher rates than girls with regard to all

indicators. In 2019 these differences were negligible at the

overall level and usually rather small in most countries.

On average, 3 % of the ESPAD students said that they had

smoked cigarettes daily at age 13 or younger. It is important

to note that the proportion of adolescents who initiated daily

smoking at a very early age has decreased over the last 24

years. Exceptions exist to this general pattern, however; for

example, in Bulgaria and Slovakia the percentage of students

who started smoking daily at age 13 or younger was two

times higher (about 6 % for both) than the ESPAD average.

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Discussion and conclusion

The

decreasing trend in smoking may be considered to

be at least partially driven by policy measures, including

restrictions on the underage purchase of tobacco products

and restrictions on tobacco advertising, that have been

implemented in the majority of European countries in the

context of the FCTC (Shibuya et al., 2003). A recent study

based on 2007-2015 European ESPAD data, comparing

European countries that did and did not implement a point-

of-sale display ban on tobacco products, concluded that the

implementation of such regulations was associated with

a stronger decrease in regular youth smoking (Van Hurck et

al., 2019).

Although cigarette smoking is the most common form of

tobacco use worldwide, considering only this may lead to an

underestimation of current nicotine consumption because

of the growing use of alternative products and new nicotine

delivery technologies. For this reason, in the 2019 survey,

questions asking about cigarette smoking were reformulated

to explicitly exclude e-cigarettes, and new questions on

the use of e-cigarettes and other nicotine-based products

were introduced. Even though this partially restricts

direct comparisons with earlier ESPAD data, as previous

respondents may have included those using e-cigarettes,

the changes implemented are useful to capture and better

describe contemporary patterns of nicotine consumption.

Introduced on the European market in the last 10 years,

e-cigarettes allow the inhalation of a vaporised chemical

liquid mixture, which may or may not contain nicotine, in

different concentrations (Clapp and Jaspers, 2017). Even

though electronic nicotine delivery systems have been

argued to be safer than traditional tobacco cigarettes,

especially for those who switch from traditional tobacco

products, research has suggested that they may not be

without risk and potential long-term consequences. It has

been reported that aerosols may sometimes contain high

levels of nicotine and detectable levels of heavy metals and

carcinogens (Farsalinos and Polosa, 2014; Olmedo, et al.,

2014).

Since their entrance on the market, the use of nicotine-

based electronic products, including e-cigarettes and heated

tobacco products, has spread widely in European countries;

they are increasingly used as a complement to or as an

alternative to traditional tobacco combustion products.

Analysing the relationship with tobacco smoking at

first

e-cigarette use, the ESPAD results show that, overall, 4.2 %

of students were regular tobacco smokers when they

first

tried e-cigarettes, 14 % were occasional tobacco smokers

and 23 % were non-smokers (see Additional Table 9a).

Possibly because of the alleged reduced harm related

to the use of these products, e-cigarettes and heat-not-

burn tobacco products have been shown to attract former

smokers and never smokers, particularly among youths

(Kong et al., 2017; Perikleous et al., 2018; WHO, 2019a;

Yoong et al., 2018), leading to an increase in the prevalence

of consumption when considering nicotine intake as

a broader category. Although regulation at European level

is fragmented and varied across countries, the prevention

of initiation of use of electronic nicotine and electronic non-

nicotine delivery systems by non-smokers, especially minors

and vulnerable groups, is one of the WHO recommendations

about these products, together with the prevention of

unproven health claims being made about such devices

(WHO, 2020).

The

2019 ESPAD results show an average lifetime

e-cigarette use of 40 % among 16-year-old students, ranging

from 18 % in Serbia to 65 % in Lithuania, with higher rates for

boys than girls, both on average (46 % for boys versus 34 %

for girls) and in most ESPAD countries. Moreover, 11 % and

1.7 % of the students reported

first

use and daily use at age

13 or younger, respectively.

In 2019 lifetime e-cigarette use among boys (46 %) was

even more prevalent than lifetime tobacco smoking (43 %)

(European average). Looking at both genders together,

lifetime e-cigarette use was more common than lifetime

tobacco smoking in 15 countries and last-30-day e-cigarette

use was more common than last-30-day tobacco smoking in

five

countries.

A marked increase in the development and use of electronic

nicotine delivery systems has been noted worldwide,

and

first-

and subsequent-generation e-cigarettes are

becoming more and more popular among adolescents

in many countries. For example, in the United States the

prevalence of use among young people (aged 10-24 years)

has increased substantially in the past 5 years (Cullen et

al., 2018), and the latest report of the Monitoring the Future

study estimated that more than one third of high school

students have used e-cigarettes in the past year (Johnston

et al., 2020).

E-cigarette use among adolescents is a concern because

the extent of any possible adverse health effects is not well

understood; there is an ongoing debate about both the

relative benefits and risks and the possible long-term health

implications of using these products. For these reasons, the

Forum of the International Respiratory Societies (FIRS) has

issued a position statement, noting that negative health

effects cannot be ruled out (Bals et al., 2019); similarly, the

WHO has stated that, even if it is too early to provide a clear

answer on the long-term impact of e-cigarette use, these

products are harmful to health and unsafe (WHO, 2019b,

2020).

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Discussion and conclusion

Although there is currently no scientific agreement on

whether or not electronic nicotine delivery systems can

be a gateway to tobacco smoking (Chyderiotis et al.,

2020; Liu et al., 2020), the ESPAD results suggest that

a substantial proportion of the adolescent population that

uses e-cigarettes does so without previous experience of

traditional cigarette smoking.

When considering cigarette and e-cigarette use together, the

prevalence of lifetime use rises to 53 % and that of current

users rises to 26 %.

Although gender differences in rates of cigarette smoking

have shown a gradual narrowing over time, once the use of

e-cigarettes is taken into account as a measure of nicotine

intake, male students show higher rates (from 5 up to

30 percentage points) in the majority of countries (see

Figures 15-16 and Additional Tables 102 and 103).

These

results may be possibly explained by

findings

from other studies suggesting that the acceptability of

smoking, which had been declining, appears to have been

re-normalised to some degree during the rapid growth in

use of e-cigarettes (Hallingberg, et al., 2020). As briefly

highlighted, arguments on the net potential costs and

benefits of the introduction of new nicotine delivery systems

are clearly complex. What the results from the ESPAD study

suggest is that the use of e-cigarettes in association with or

as a replacement for traditional tobacco products among

adolescents is a non-negligible phenomenon that should be

closely monitored.

adolescents is associated with a number of acute alcohol-

related harms (Hingson and White, 2014; Lees et al., 2020;

Petit et al., 2014; Windle and Windle, 2017).

Analysis of the previous six ESPAD waves and 28

participating countries highlighted that, up to 2015,

moderate decreasing trends in alcohol use were present for

both genders in all European regions except for the Balkan

countries (Kraus et al., 2018).

The

overall temporal changes

in the prevalence of current alcohol use, as well as heavy

episodic drinking, between the previous survey and the

present survey are negligible, indicating that the downwards

trend has levelled off and remains rather constant in 2019.

Nevertheless, Hungary, Ireland, Romania, Slovakia and

Ukraine reported an increase in current alcohol use of

five

or more percentage points and Austria, Bulgaria, Cyprus,

Czechia, Lithuania and Malta reported a decrease in current

alcohol use of

five

or more percentage points between

2015 and 2019. Comparable changes in the prevalence of

heavy episodic drinking were found in the Faroes, Germany

and North Macedonia (increase), and Austria, Bulgaria,

Cyprus, Greece, Latvia, Lithuania and Malta (decrease).

With an overall decrease of one percentage point in both

the prevalence of current alcohol use and prevalence of

heavy episodic drinking in boys and an increase of one

percentage point in the prevalence of current alcohol use

and a constant rate of heavy episodic drinking in girls

between 2015 and 2019, the gender gap in the prevalence

of heavy episodic drinking has almost closed (boys 36 %

versus girls 34 %) and that in prevalence of current use as

closed. Similar observations have been reported for the

United States. Results from the Monitoring the Future study

suggest that heavy episodic drinking is declining among

teens, with greater declines for boys than girls, leading to

gender convergence (Clark Goings et al., 2019; Johnston et

al., 2015).

Beverage preference, defined by the proportion of the

volumes of pure alcohol consumed in different types of

alcoholic beverages at the last drinking occasion, varies

across ESPAD countries. Overall, in terms of prevalence rates

and perception of availability, spirits have gained ground over

beer, particularly among female students.

The

literature on beverage choice shows associations

between beverage preference and drinking motives, quantity

of alcohol intake and frequency of heavy drinking. For

instance, beer and spirits are reported to be consumed in

larger amounts than wine on heavier drinking occasions

(Callinan and MacLean, 2016), and preference for beer

seems to be associated with risky drinking patterns and

illicit drug use (Dey et al., 2014). However, the likelihood of

negative alcohol-related consequences or the use of other

substances increased among people with risky drinking

behaviours, regardless of beverage preference (Dey et

Alcohol use

Even though alcohol use among adolescents seems to have

decreased in many ESPAD countries, it is still rather high,

with on average around 80 % of students reporting alcohol

use in their lifetime and almost half reporting use in the last

month.

There

are large variations between countries in the

prevalence of alcohol use in 2019, with the Nordic countries

(except Denmark) traditionally showing low rates of lifetime

and current consumption.

The

lowest rate was found in

Kosovo, but low rates were also observed in the Baltic states,

as well as in Montenegro and North Macedonia. Patterns of

alcohol use, such as frequency of intake, average ethanol

intake and heavy episodic drinking, are rather diverse across

ESPAD countries. For instance, high scores on all indicators

were observed in Austria, Denmark, Germany, Hungary

and the Netherlands. In the Mediterranean countries (Italy,

Greece and Spain), moderate to high frequencies of intake

are combined with low to moderate average quantities

of intake and moderate rates of heavy episodic drinking.

Although adolescents may generally drink less than

adults, excessive alcohol consumption of any form among

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Discussion and conclusion

al., 2014). While the differences in beverage preference

between countries may be explained by differences in

drinking culture, lifestyle factors and personal characteristics

(Flensborg-Madsen et al., 2008; Room and Mäkelä, 2000),

it is worthwhile noting that the distribution of preferred

beverages in adolescents diverges from the traditional

characterisation of drinking cultures (Iontchev, 1998; Room

and Mäkelä, 2000). Drinking characterised by a preference

for wine is typically associated with Mediterranean countries

(e.g. Italy or France), whereas a preference for beer drinking

is mainly associated with countries in central Europe

(e.g. Czechia). Northern countries, on the other hand, are

typically characterised by a preference for spirits (e.g.

Finland and Norway). Figure 5 clearly shows that traditional

characterisations of beverage choice may no longer be as

valid as they once were, especially among the adolescent

population (Bräker and Soellner, 2016).

The

current literature explains the generally observed

reduction in alcohol consumption among adolescents

across Europe, which is confirmed by the ESPAD data, as

a ‘devaluation’ of alcohol in concert with a change in the

social position of alcohol (Kraus et al., 2019). For example,

it has been argued that the cultural reputation of drinking

may have changed among young people in such a way that

drinking has lost its undisputed symbolic power as a rite of

passage to adulthood (Törrönen et al., 2019).

There

is also

some evidence that changes in drinking and intoxication

regulations applied at the national level have contributed

to the decline in alcohol use among youths (Raitasalo et al.,

2020). In a recent pooled analysis based on data from the

Global School-based Student Health Survey (GSHS) and the

ESPAD survey, strict policies targeting alcohol availability,

marketing and pricing were inversely associated with lifetime

alcohol use among adolescents, although not with current

alcohol consumption (Noel, 2019).

The

author reported that

pricing policies were also inversely correlated with current

binge drinking status among current drinkers.

However, Hendriks et al. (2020) have recently expressed

concerns about social media contexts, where alcohol-

related posts are frequently shared among influencers and

adolescents. Taking advantage of the influencers’ posts,

alcohol brands may

find

a way to circumvent norms that

prohibit advertising for minors. Moreover, teenagers continue

to be broadly exposed to alcohol adverts on a daily basis

(Gallopel-Morvan et al., 2017).

This

might partially explain the

still high prevalence of alcohol use observed in the ESPAD

data.

The

evidence for a strong link between exposure to

alcohol advertising and adolescent drinking behaviour has

led to the suggestion that stronger measures counteracting

the exposure of adolescents to alcohol advertisements might

act as an effective policy measure (Anderson et al., 2009;

Jernigan et al., 2016).

Cannabis use

Within Europe, and further afield, cannabis use continues

to generate significant policy and public interest. Demand

and supply indicators confirm that cannabis is still the

most widely used illicit drug in Europe and in other parts of

the world. In the European Union, it is estimated that 90.2

million adults aged 15-64 years, corresponding to 27.2 %

of this age group, have tried cannabis during their lives

(EMCDDA, 2020). Cannabis products account for the largest

share (39 %) of the European illicit drug retail market, with

an estimated minimum value of EUR 11.6 billion in 2017

(EMCDDA, 2019).

These

facts, as well as the increase in

the variety of cannabis products and their potency, have

triggered debate around how society should respond to this

substance. In recent years, many countries have reformed

laws on cannabis, and a number of jurisdictions, such

as Uruguay, Canada and some US states, have legalised

its recreational use. However, little is known about the

population-level effects of such reforms (Pacula et al.,

2015; Stevens, 2019; Waddell and Wilson, 2017) and,

while these legal changes are mainly intended for adults,

the potential effects on adolescent cannabis use are of

particular concern (Cerdá et al., 2017). When considering

changes in cannabis regulation in any direction, it is essential

to have comparable and representative information on the

prevalence and patterns of cannabis use in adolescents,

correlated (protective or risk) factors and temporal trends

across European countries.

Based on the 2019 ESPAD results, the average lifetime

prevalence of cannabis use among adolescents in

participating countries remained stable at the 2015 level

(16 %), with a high cross-country variability.

The

countries

with the highest prevalence of cannabis use were Czechia

(28 %), Italy (27 %) and Latvia (26 %). It is worth noting that

in Czechia, as well as in other countries (Bulgaria, France

and Monaco) characterised by high levels of lifetime use

in 2015, a decrease in lifetime use of up to 10 percentage

points was observed in 2019.

This

development warrants

further investigation to gain insights into possible factors

influencing the decreases. In Italy and Latvia, the rates

remained rather stable compared with the previous survey.

Low lifetime prevalence rates were found in four of the

Nordic countries (the Faroes, Iceland, Norway and Sweden),

several Balkan states (including Kosovo, North Macedonia,

Serbia, Montenegro and Romania) and Cyprus and Greece,

all with rates under 10 %. With respect to 2015, the average

ESPAD prevalence of use in the last year remained stable

at 13 %, with the lowest rate observed in Kosovo (2 %) and

the highest rate observed in Czechia (23 %).

The

average

prevalence of current use (last month) also remained

stable (6.6 % in 2015 and 7.1 % in 2019), with a significant

increase observed in six countries and a significant decrease

observed in Bulgaria and France.

The

high prevalence

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Discussion and conclusion

of current users (13 % or higher) in Italy, France and the

Netherlands has occurred despite the different cannabis

regulations in place in these three countries.

On average, 2.4 % of the ESPAD students reported that they

had

first

used cannabis at age 13 or younger.

This

prevalence

was slightly lower than in 2015 (3.1 %) and is consistent

with the slow increase in the age of onset of cannabis

use observed since 2011.

The

highest rates were found in

France (4.5 %) and Italy (4.4 %); however, whereas in France

a decrease of about 1.5 percentage points was observed

compared with 2015, in Italy no change between 2015 and

2019 was observed.

The

results of the CAST measure for cannabis high-risk

use suggest that, on average, 4.0 % of students in the

total ESPAD population can be considered to be at risk of

developing cannabis-related problems.

This

corresponds

to an average proportion of 35 % among students who

reported cannabis use in the last year, with a large variability

observed across countries. Interestingly, in Kosovo, Cyprus,

Montenegro, Serbia and Sweden, which were the countries

with the highest proportion of users at high risk of developing

cannabis-related problems, the prevalence of cannabis

use in the last 12 months was among the lowest in Europe,

whereas several of the countries with the highest prevalence

of last-year use (Netherlands, Latvia and Czechia) reported

some of the lowest proportions of users at high risk of

developing cannabis-related problems.

This

suggests that

there is not a simple and direct relation between cannabis

use and risky use, with potential influences of other factors,

such as quantities actually used, as well as broader social

and cultural factors.

These

factors may include how different

societies react to cannabis use, which may influence the

self-assessment of excessive use, the willingness to stop

using, the recommendations by others (e.g. parents or

teachers) to stop using and the development of conflicts in

relation to use (Philbin et al., 2019; Santaella-Tenorio et al.,

2019). It should be noted that the CAST results need to be

interpreted with caution. As pointed out in the methodology

section of this report, different coding systems and cut-off

scores have been applied since its initial validation in 2007.

For the purpose of comparison with the ESPAD 2011 results,

and based on previous research, in this report the binary

version with a cut-off score of 2 or more points has been

adopted, but it is clear that different computation methods

would produce different results. It is widely recognised that

further research is needed to reach a common agreement

on the best computation method for the CAST for different

target populations. In addition, it is necessary to investigate

the cross-cultural validity of the CAST scale in the context of

cross-national studies. In this respect, the fact that the 2019

survey was able to provide relevant data for all participating

countries is important for future studies in this area.

Based on the 30-country trend, the perceived availability

of cannabis increased slightly from 33 % in 2015, with an

average of 32 % of ESPAD students perceiving the substance

to be easy or fairly easy to obtain in 2019. It should be noted

that perceived availability is not automatically related to

cannabis use and problems. For instance, in the Netherlands

the proportion of last-year users classified by the CAST as

being at high risk of cannabis-related problems is among the

lowest in Europe (25 %), whereas in Kosovo this proportion is

among the highest (69 %).

Long-term trends in ESPAD average cannabis use indicate

an increase in both lifetime and last-month use between

1995 and 2019, from 11 % to 16 % and from 4.1 % to 7.4 %,

respectively. However, since 2011 a slow downwards trend

can be observed for lifetime use, while a stabilisation has

been observed in the rate of last-month cannabis use since

2007.

Overall, the 2019 data suggest that cannabis use and

its perceived availability vary widely among European

adolescents, with the large differences in these indicators

across ESPAD countries not showing any tendencies

towards convergence. As research shows, the links and

causal relationships between policy, availability and cannabis

use are still unclear (Shi et al., 2015; Stevens, 2019; van Ours

and Williams, 2015). In recent years, new forms of cannabis

have been developed as a result of advances in production

techniques, and cannabis products tend to be much more

potent than in the past (EMCDDA, 2019b).

This

means that,

even in countries where the prevalence of use underwent

limited changes, the potential health risks for adolescents

may have changed.

The

changing context depicted by the ESPAD results, as

well as the need to consider the complicated interplay

between national- or community-level and individual-level

characteristics (Burdzovic Andreas and Bretteville-Jensen,

2017), highlight the increasing challenges that policymaking

and prevention strategies are currently confronted with.

New psychoactive substance use

The

so-called NPS are generally defined as psychotropic

drugs not controlled by the United Nations drug conventions,

but which may pose a public health threat comparable

to that caused by substances listed in these conventions

(EU, 2017).

The

European Early Warning System, which

is operated by the EMCDDA and Europol and is designed

to identify NPS through a multidisciplinary network of 30

national early warning mechanisms, was monitoring around

790 such uncontrolled substances by the end of 2019

(EMCDDA, 2020). Some of these substances used to be, or

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Discussion and conclusion

still are, marketed as legal alternatives to traditional drugs

or, in some cases, as replacements for those drugs. In recent

years, European countries have legislated to control the trade

and sale of these substances.

These

national legislations

take different approaches but often use definitions of

chemical groups, so the common result is that many of the

identified substances are immediately under legal control.

Given the complexity of interpreting some of the groups,

coupled with the inaccurate labelling of substances, in many

cases users will not be aware of the exact legal status of the

substances they are using (EMCDDA, 2018).

The

advent of NPS has raised considerable concern at

international and European levels, notably because of the

high number of substances identified by the Early Warning

System every year. In addition, there have been reports

of a growing number of intoxicated people presenting in

emergency departments after use of NPS with adverse

somatic and psychiatric effects that sometimes seem to be

more severe than those induced by established drugs with

similar subjective effects (Brown et al., 2018; Logan, 2017).

In this context, it is essential to obtain epidemiologically

valid, reliable and comparable information on the prevalence

and patterns of NPS use, both among adults and among

children. However, while a range of studies have reported

on significant levels of NPS use or exposure, these tend to

have focused on selected samples (Bretteville-Jensen, 2014;

Weinstein et al., 2017), and there is very limited scientific

literature on the prevalence of NPS use in representative

samples of the general population. In this context, the

ESPAD study collected information on NPS use among

school students at a European level for the

first

time in 2015

(ESPAD Group, 2016). Information was collected again in

2019 for NPS in general and, in addition, specifically for

synthetic cannabinoid and synthetic cathinone use.

On average, 3.4 % of the ESPAD students surveyed had

tried NPS during their lifetime and 2.5 % had used them in

the past 12 months, which indicates higher levels of use

than for amphetamine, ecstasy, cocaine or LSD individually.

However, if stimulants (amphetamine, methamphetamine,

ecstasy, cocaine and crack) are combined (4.1 % lifetime

prevalence) (see Additional Table 63c), the level of use

of NPS is lower, as it is when compared with the use of

inhalants or psychoactive medicines. A salient characteristic

of NPS is that most users are in fact polysubstance users

(see Additional Table 69c), with 77 % of lifetime NPS users

also having engaged in heavy episodic drinking at least

once in the last 30 days and 88 % having tried at least

one illicit drug. In 84 % of cases NPS users had previous

experience with cannabis, and in 45 % of cases NPS users

had previous experience with stimulants (amphetamine/

methamphetamine or ecstasy or cocaine/crack).

These

findings

indicate that NPS use should not be viewed as an

isolated, specific phenomenon, but that it needs to be seen

as part of the broader phenomenon of polysubstance use.

Regarding the use of NPS in the last 12 months, several

countries reported a relatively high prevalence, for example

Czechia (4.9 %), Latvia and Estonia (both 4.7 %), Poland

(4.5 %) and Monaco (4.0 %), but in a substantial number of

countries (13) the prevalence was lower than 2.0 %, with

the lowest rates reported in North Macedonia, Finland and

Portugal (below 1.0 %).

The

results of the 2015 survey are

not fully comparable with the 2019 results because of the

different response categories. Bearing this in mind, the 2015

results were in a similar range to those of 2019, with slightly

higher values in 2015, when the average lifetime prevalence

was 4.2 % and the last-12-month prevalence was 2.9 %.

Seizure and other data suggest that the most common

NPS available on the European market are stimulants,

often cathinones, and synthetic cannabinoids (EMCDDA,

2020). To better investigate this, in some ESPAD countries

additional questions were asked about the consumption of

synthetic cannabinoids and cathinones.

The

average lifetime

prevalence of synthetic cannabinoid use, calculated across

20 out of 35 countries, was 3.1 %, whereas the consumption

of cathinones, calculated across 19 out of 35 countries, was

lower, with 1.1 % of the ESPAD students reporting lifetime

use. Among the last-12-month users of NPS, the most

frequently reported form of synthetic substance used was

herbal (54 %), followed by powders or tablets (27 %), liquids

(13 %) and other forms (17 %).

Since 2015 the ESPAD study has been one of the

first

international epidemiological studies to include NPS use.

There

is currently a lack of internationally comparable data

in this area. In the United States, despite concerns about the

use of ‘synthetic marijuana’, the Monitoring the Future study

has reported a steady and marked decrease in last-12 month

use among 8th, 10th and 12th grade students, from 4.4 %,

8.8 % and 11 % in 2012 to 2.7 %, 2.6 % and 3.3 % in 2019,

respectively (Johnston et al., 2020).

The

age of 10th grade

students in the United States is similar to that of students

included in ESPAD. Although caution should be exercised

when making comparisons, it is observed that levels of use of

synthetic cannabinoids are of the same order of magnitude,

with relatively low levels of use for both (3.1 % for lifetime use

in Europe and 2.6 % for last-year use in the United States).

This

report presents the basic data on NPS prevalence and

patterns of use, but this should be followed by more in-depth

analysis of patterns of use (notably polydrug use) and the

risk and protective factors related to NPS use.

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Discussion and conclusion

Pharmaceutical use for non-medical

purposes

The

use of pharmaceuticals for non-medical purposes is

considered globally as a major emerging problem that needs

to be monitored.

The

misuse of pharmaceuticals is defined

as the use of a medication that is not prescribed to a user or

that is taken in a manner not recommended by a doctor or

not in line with the medicine information leaflet (e.g. higher

doses, using non-approved routes of administration). It

also captures situations in which the medication is illegally

obtained (e.g. purchased from a dealer or via the internet)

or obtained under false pretences (e.g. doctor shopping or

feigning symptoms). Students may misuse pharmaceuticals

for a range of reasons, including to induce euphoria, to

enhance the effects of alcohol and other drugs, to self-

medicate illness or injury, to mitigate the symptoms of

withdrawal from alcohol and other drugs and to improve

school performance (Larance et al., 2011; McCabe et al.,

2017). On average, 9.2 % of the students reported lifetime

use of pharmaceuticals for non-medical purposes, with quite

large differences across countries (range: 2.8 % to 23 %).

The

highest prevalence was found in Slovakia (23 %), followed

by Latvia (22 %) and Lithuania (21 %).

The

lowest rates were

found in Ukraine (2.8 %) and Georgia, the Faroes, Bulgaria

and Italy (4-5 %). Both on average and in the vast majority

of ESPAD countries, girls were more likely than boys to have

used pharmaceuticals for non-medical purposes.

The

types of pharmaceuticals used most often were

tranquilisers or sedatives without a doctor’s prescription

(ESPAD average: 6.6 %), followed by painkillers in order to

get high (ESPAD average of 4.0 %). Only a few students

reported having used anabolic steroids (ESPAD average:

1.0 %). While in general the use of tranquillisers and

sedatives and of painkillers to get high was higher among

girls than boys, slightly more boys than girls reported the

use of anabolic steroids, even though no appreciable gender

differences were seen, both on average and within countries.

There

is some evidence suggesting that approximately one

third of young people who use prescription drugs for non-

medical purposes (for example, in order to get high) may

be at higher risk of developing symptoms of a prescription

drug use disorder (Chen, 2016; Schepis et al., 2008). At the

same time, research suggests that adolescents may seek

out controlled substances for the purposes of intoxication

because they believe that these substances are safer than

illicit drugs (McCabe et al., 2009; SAMHSA, 2017).

in many countries over the past few decades, coupled with

widespread access to new forms of gambling on the internet,

is raising concerns regarding adolescents’ participation in

gambling (Griffiths and Parke, 2010; Kingma, 2008; Volberg

et al., 2010).

This

is seen as a public health issue as it is

deemed that increasing gambling opportunities have led

to increases in adolescent gambling (Calado et al., 2017a;

Meyer et al., 2009) and even problem gambling (Delfabbro et

al., 2016).

The

2019 ESPAD results show that 22 % of adolescent

students in Europe reported gambling for money on at least

one game in the past 12 months. Cross-country comparisons

reveal important variations in the reported levels of past-year

gambling, ranging from 11 % in Kosovo to 33 % in Greece

and Cyprus. In all countries, considerably more boys than

girls engaged in gambling for money.

As described in the methodology section, in 2019 gambling

prevalence was calculated as the proportion engaging in at

least one gambling activity (playing on slot machines, playing

cards or dice for money, playing the lottery, betting on sports

or animal races) in the last 12 months.

The

2019 ESPAD results also show that the most popular

gambling activity was lotteries, reported by 49 % of last-

year gamblers. Interestingly, lottery gambling was the only

gambling activity that was more prevalent among female

gamblers (57 %) than male gamblers (45 %).

Young people often start gambling at a young age by buying

lottery tickets and scratch cards for themselves, despite

the age restrictions (Gosselt et al., 2013; St-Pierre et al.,

2011), which may account for the higher

figure

obtained

for lotteries than for the other gambling activities.

The

fact

that adolescents often have their

first

contact with gambling

through lottery products (Delfabbro et al., 2014; St-Pierre

et al., 2011), has led some to consider lottery gambling as

a ‘gateway’ to gambling among this age group (Malischnig

et al., 2020).

The

highest proportions of students reporting

past-year gambling activity who engaged in lotteries were

observed in Greece (74 %) and Cyprus (69 %), and this

mainly drives their position as the top European countries

in terms of gambling prevalence (33 %).

The

particularly

high proportion of students engaging in lottery gambling in

Greece, corresponding to 25 % of all 16-year-old students

in the country, has been previously explained by the high

degree of normalisation of gambling, especially lottery

playing (often not perceived as gambling), in society overall

(Molinaro et al., 2018).

Slightly less than half of the ESPAD students who gambled

spent money on sports or animal races (45 %) and playing

cards or dice (44 %).

The

highest sports betting proportions

were observed in Montenegro (75 %) and Croatia (76 %). In

Gambling

The

increased availability of gambling opportunities resulting

from the progressive liberalisation of the gambling sector

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Discussion and conclusion

Croatia the popularity of sports betting may be attributed to

the liberal approach of the national gambling policy, reflected

in the widespread and increasing availability of sports betting

points of sale (Ricijaš et al., 2016).

The

least prevalent gambling activity was slot machines,

which on average were played by one in

five

adolescent

gamblers (21 %). In some countries (Czechia and Greece)

the proportion of gamblers playing at slot machines was

less than 10 %. Finland reported the highest proportion of

slot machine gamblers (60 %). Interestingly, Finland and

Montenegro were also among the European countries

with the highest gambling prevalence (30 % and 32 %,

respectively). Finland has been reported as a case of

particular interest because of its exceptional decentralised

system of slot machines, guaranteeing easy access in

places of everyday life, such as supermarkets and cafés

(Raisamo et al., 2017). Although previous

findings

suggest

that raising the legal age for gambling to 18 years as of mid-

2011 significantly decreased the prevalence of slot machine

use among minors, the general availability of gambling

products was not reduced until early 2019 and enforcement

of regulations on minimum age is limited (Raisamo et al.,

2017; Warpenius et al., 2016).

This

might explain the 2019

ESPAD results, which indicate that in Finland slot machines

were the most prevalent type of game used by gamblers

and that almost one in

five

ESPAD students in the country

(18 %) gambled money on this game during the last year.

Finland was also the country with the highest prevalence of

slot machine use in 2015, for both offline (19.2 %) and online

(9.1 %) gambling (Molinaro et al., 2018).

With the introduction of the Lie/Bet screening test for

problem gambling in the core part of the ESPAD 2019

questionnaire, information on the extent of problem

gambling behaviour in all participating countries is now

available. On average, 5.0 % of students who had gambled

in the last 12 months met the criteria for problem gambling,

which corresponds to a prevalence of 1.4 % in the total

student population.

This

proportion was particularly high in

Georgia (12 %), followed by Denmark (9.1 %) and Romania

(8.5 %). Interestingly, Georgia (13 %) and Denmark (12 %)

were the countries with the second and third lowest

prevalence of gambling in the last year.

This

means that,

although gambling is not widespread among adolescents

in these two countries, more than one in 10 students who

gambled in the past year had already experienced problems

related to gambling.

This

is not the case for Romania,

where gambling seems to be a much more popular activity

among students (25 % prevalence of past-year gambling).

In fact, when looking at the estimated proportion of problem

gambling among all students, the prevalence found in

Romania (2.5 %) and Montenegro (2.6 %) were the highest.

In 2019, the core part of the ESPAD questionnaire also

included the CSPG (Rockloff, 2012), a test that is used to

assess the intensity of gambling. Based on the scores on the

CSPG, 15 % of students who gambled in the last 12 months

met the criteria for excessive gambling, which corresponds

to 3.8 % of all students participating in the survey. In line

with previous research (Calado et al., 2017b), like almost all

ESPAD

figures

concerning gambling, the extent of estimated

problem and excessive gambling was more prevalent among

boys.

It is interesting to note that the prevalence of gambling

participation and the prevalence of excessive and/or

problem gambling are not necessarily correlated, as shown

by the example of Greece. While this country ranks

first

terms of gambling prevalence, the results from the Lie/

Bet and CSPG screening tests suggest that the estimates

of problem and excessive gamblers, respectively, were not

particularly high, which indicates that most students gamble

recreationally.

This

is also consistent with the fact that the

most popular gambling type is lotteries, which the literature

indicates are least correlated with the development of

problem gambling behaviour (Rockloff, 2012).

In most countries gambling is legal and increasingly available

(Williams et al., 2012). Consequently, today’s youths are

growing up in an environment in which gambling is part

of everyday life and an activity that many adults engage in

(Volberg et al., 2010). Previous

findings

indicate that a high

proportion of children and adolescents start gambling at an

early age, between 10 and 12 years of age (Wynne et al.,

1996; Gupta and Derevensky, 1998).

Concerns about adolescent gambling (Calado et al., 2017a;

Gupta and Derevensky, 2014) and the resulting need

to analyse the comparative prevalence of gambling and

problem gambling rates across different countries and

across time have motivated the further investigation of the

various dimensions of gambling in this report.

The

association of excessive gambling with an increased

use of legal and illegal substances found in previous studies

(Cook et al., 2015;

Špolc

et al., 2019; Vieno et al., 2018) was

also observed in this study (see Additional Table 101b). It

has been hypothesised that this is because of the influence

of common underlying factors, such as impulsivity and

sensation seeking (Cosenza and Nigro, 2015; Nigro and

Cosenza, 2016), suggesting a potential effectiveness of

prevention and intervention programmes targeted at all

kinds of risk behaviours, focusing on the most prevalent risk

activities (Špolc et al., 2019).

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Discussion and conclusion

Social media use and gaming

Over the past three decades, the use of digital technologies

and the internet has become an integral part of the daily

life of European citizens. Internet use has continued to

spread worldwide, with a tenfold increase in

fixed

or mobile

subscriptions in 2019 compared with 20 years ago (4 131

million internet users worldwide in 2019 compared with 495

million in 2001) (ITU, 2019).

With the increase in internet access, online communication

has become widespread, especially for adolescents

(Bucksch et al., 2016; Livingstone et al., 2017). Although

there is concern about an association between adolescent

social media use and negative health implications, such as

sleep problems, anxiety, low self-esteem and depression

(Ehrenreich and Underwood, 2016; Hussain and Griffiths,

2018; Richards et al., 2015; Wong et al., 2020), as well as

the possibility that social media experiences may engender

feelings of exclusion or victimisation (Fabris et al., 2020;

Underwood and Ehrenreich, 2017), teenagers can also

experience benefits from social media, such as social

support, greater social connectedness and greater ease of

interaction (Barry et al., 2017; Berryman, 2018; Gerwin et al.,

2018; Kuss et al., 2017; Seabrook et al., 2016).

In 2019 within the last 7 days students had used social

media for 2-3 hours on a typical school day and for 6 or more

hours on a typical non-school day. Fewer online hours on

a non-school day were reported in Austria, Czechia, Iceland,

Slovenia and Denmark.

It is perhaps noteworthy that, in some countries, more than

10 % of students reported no use of social media on a typical

school day (such as Kosovo, Georgia, Bulgaria, Cyprus, North

Macedonia and Slovakia), as well as on a typical non-school

day (Kosovo, Georgia and Bulgaria).

Differences between countries in time spent online may

not necessarily reflect cultural differences; rather, they may

be due to differences in ability to access to the internet and

devices with internet capability, although wide coverage of

internet access in most countries in Europe can be assumed.

Moreover, as reported by the EU Kids Online 2020 report

(Smahel, 2020), which provides data from 19 European

countries, smartphones are now the preferred means of

accessing the internet for most children, meaning that they

have ‘anywhere, anytime’ connectivity, with the majority

of children reporting that they use their smartphone daily,

with time spent online each day almost doubling in many

countries in the last 10 years.

Even though no significant differences were found between

boys and girls in terms of social media use on a typical

school day in most ESPAD countries, when looking at non-

school days girls were slightly more likely than boys to spend

more time on social media.

These

results differ from those

reported by Smahel et al. (2020). A gender difference in

social media use was also found in the 2014 (HBSC) study,

with more girls than boys aged 13 and 15 years reporting

daily social media contact with friends (Inchley et al., 2016).

Over the last two decades, driven mainly by the increasing

popularity of smartphones and tablets, gaming has become

more popular and is increasingly played on these devices.

Since 2005 weekly use of gaming, both online and mobile,

has doubled (OFCOM, 2015). Nonetheless, with regard

to time spent on gaming activities, the majority of ESPAD

students reported not having played digital games within the

last 30 days, both on a typical school day and on a typical

non-school day.

Research on factors associated with excessive gaming

indicates that early-onset, opposite-sex friends and minimal

parental mediation increase the risk (Lissak, 2018; Müller et

al., 2015; Sugaya et al., 2019), as well as high impulsivity and

sensation-seeking personality traits (Griffiths et al., 2012;

Salvarli and Griffiths, 2019). Several studies have focused

on the negative health effects of gaming, ranging from

mental health problems, such as sleep disorders, anxiety and

depression, to addictive behaviours and health risks related

to sedentary behaviour (Mihara and Higuchi, 2017; Stockdale

and Coyne, 2018;

Throuvala

et al., 2020). An increased

engagement in gaming was also related to a higher rate of

bullying in boys and lower life satisfaction in girls (Brooks et

al., 2016) and a higher rate of social isolation and feelings of

loneliness among all students (Stockdale and Coyne, 2018;

van den Eijnden et al., 2018).

Even though country differences are considerable, and the

wide availability of game types is aimed at attracting boys as

well as girls, playing games is still associated with gender,

with boys spending more time than girls on gaming activities

in most countries, on both school days and non-school days.

Whether it represents a disorder, an underlying

psychopathological manifestation or a common behaviour

among adolescents, as well as information on hours spent

on social media or gaming, their individual perception of

problems related to time spent on these activities is of

particular interest.

To provide a better understanding of this issue, the ESPAD

questionnaire introduced two non-clinical screening tools,

adapted from Holstein et al. (2014), that focus on a student’s

perception of problems related separately to social media

use and gaming.

The

results based on these two different summary indexes

indicate a greater self-perception of high risk of problems

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Discussion and conclusion

related to the use of social media (46 % on average) than

gaming activities (21 %). Noticeable gender differences,

correlating with those found in the amount of time spent on

these activities, were in line with previous research (Holstein

et al., 2014; Kuss et al., 2012; Spilková et al., 2017): problems

related to social media use were more prevalent among girls

across all European countries, while those related to gaming

were more prevalent among boys.

As recent research concludes, the current patterns of

internet use (e.g. time spent online, young age of users,

number of technological devices and diverse online activities

engaged in) are associated with a risk of addiction (Lopez-

Fernandez and Kuss, 2019). Young people who frequently go

online for leisure purposes, in terms of both social media use

and gaming, are more likely to be engaged excessively and/

or display addiction symptoms. In this respect, it is important

to further monitor the topic of social media use and gaming

among adolescents, as the risks related to this behaviour

present a challenge for public health policies across Europe.

state of Bavaria. In Kosovo, 4 % of the target population

enrolled in schools in Northern Kosovo and/or functioning

under the parallel structures of the Ministry of Education

of Serbia within the other Serbian municipalities were not

covered by the sampling frame. In Ukraine, the Autonomous

Republic of Crimea was not included in the survey, nor

were the territories of Donetsk and Luhansk, which are not

controlled by the Ukrainian government. In these cases,

estimates represent only the population of the region where

the survey took place.

Conclusion

The

main lesson learned from the 2019 ESPAD data

collection is that it is essential to maintain a strong

commitment to the monitoring of relevant changes in long-

term trends, as well as the emergence of new substances

and new forms of substance use and risk behaviours among

adolescents.

The

data on tobacco consumption present a relevant

example. After seeing a decreasing use of tobacco for

decades, new growth in nicotine use can now be observed.

In fact, a number of devices that enable more diverse

consumption of this substance, i.e. e-cigarettes or heat-not-

burn tobacco devices, have entered the market in recent

years, and there are indications that nicotine consumption

among adolescent students is growing again. Although

the policies aimed at preventing and reducing cigarette

smoking have had long-term effects on adolescents in

a large number of European countries, these new fashions

and ways of consuming nicotine may challenge the progress

achieved and so it is essential to continue close monitoring,

particularly among young people.

Despite high levels of variation between countries, the overall

prevalence of alcohol use showed a slight decreasing trend

among adolescents, highlighting that the cultural reputation

of drinking has changed over the years among young people,

particularly following the technological revolution and

with the widespread change in social presentation and in

interactions between parents and children. However, despite

strict regulations concerning alcohol use in some countries,

adolescents still report that alcohol is relatively easy to

access and high rates of heavy episodic drinking are still

found, especially in central European countries.

The

2019 ESPAD data also confirm that cannabis continues

to be a readily available, established drug in Europe.

The

2019 survey included an important dimension of cannabis

monitoring, the assessment of risky use, which will provide

important insights to help formulate more targeted policies

and interventions. In many European countries cannabis use

is fairly widespread among adolescents, and interventions

Limitations

Although the ESPAD survey is based on a common

methodology, there are some limitations that may weaken

the validity of the estimates. First, in France, data were

collected a year earlier than in the majority of countries

(in the spring of the previous year); therefore, the target

population was defined as students who reach the age of

16 in 2018. In the Netherlands, data were collected half

a year later than in the majority of countries (in the autumn

of 2019) and students were on average half a year older.

The

target population was, however, redefined to give an

average age in line with the other participating countries

that collected data in spring. Second, the class/school

participation rates in Denmark (21 %) and the Netherlands

(35 %) were exceptionally low compared with the ESPAD

average of 85 %. Low participation rates, however, may not

necessarily lead to biased estimates, unless the behaviour

in question is unequally distributed across schools and

classes. A simulation study from Germany found that school

non-participation in surveys assessing substance use among

students is not as problematic as expected (Thrul et al.,

2016). Systematic exclusion of schools, based on the size

of the city, school or class, on the school environment or on

schools’ substance use policies, resulted in significant but

rather small changes in prevalence estimates.

Third,

in some

countries, sampling was possible only in particular regions

of the country. In Cyprus, data collection was restricted to

government-controlled areas, representing approximately

80 % of the population. In Finland, the Åland Islands were not

covered by the sampling frame and in Georgia the occupied

territories of Abkhazia and South Ossetia were not included.

In Germany, the sampling frame covered only the federal

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Discussion and conclusion

may be necessary not only to prevent any use but also to

prevent any potential progression from occasional use to

more risky or sustained patterns of use.

The

use of NPS continues to be a source of considerable

concern, but the 2015 and 2019 survey results show that

the prevalence of use is relatively low among European

adolescents, although not negligible. An important point

highlighted by the 2019 results is that NPS use is part of the

broader phenomenon of polydrug use, and that use of NPS is

markedly associated with alcohol and drug use. In any case,

the availability of NPS and adolescents’ access to, and use

of, these substances need to be monitored, considering the

ongoing emergence of new substances.

The

2019 ESPAD data confirm that gambling for money

has become a rather popular activity among European

students and that the emergence of problematic behaviours,

such as excessive and problem gambling, must also not

be underestimated in this young age group.

This

means

not only that enforcement of age limits for gambling and of

restrictions on gambling advertisements should be improved,

but also that prevention efforts should be made to instruct

young generations about gambling mechanisms and the

real probability of winning. In addition, particular attention

should be given to adolescents’ closest relationships, such

as with family members and reference adults. In fact, the

high degree of normalisation of gambling in societies and the

culture of gambling within the family environment have been

recognised as important drivers of gambling onset and youth

progression into problem gambling.

Over the past two decades, driven primarily by the growing

popularity of smartphones and tablets, social media and

online games have become increasingly popular and easily

accessible.

Young people are an important target group for many drug

and addictive behaviour prevention interventions.

They

are also the section of the population most familiar with

information and communication technologies and most

open to their use in many areas of their life.

These

two factors

mean that this group is most likely to be willing to accept

and benefit from the use of this technology for the delivery

of prevention interventions and, perhaps, some forms of

treatment adapted to adolescents.

With the 2019 data collection, ESPAD brings together

comparable information from over 30 European countries

over a period of 24 years.

This

places the project in a unique

position to continue to make a valuable contribution to

the development of credible and effective policies and

interventions to protect youth health and social well-

being in general. In this sense, throughout its lifetime,

ESPAD has proved its capacity to incorporate relevant new

developments, including what is possibly one of the main

21st-century developments in the

field

of addictions, the

behaviours (e.g. gambling) that can lead to similar personal

and social problems as those caused by psychoactive

substances. It has also been accepted that, because of the

methodology used, target age group and rather long time

cycle, ESPAD does not intend to identify every local or short-

lived drug issue. However, it is an essential tool for assessing

which developments have a real public health and social

relevance and which ones are of limited impact, with both

aspects being important for policy formulation.

From this perspective, ESPAD will strive to increase its

impact through closer cooperation with other relevant

international and national projects that focus on adolescent

health and substance use, either inside Europe (e.g. HBSC,

Mediterranean School Survey Project on Alcohol and Other

Drugs in Schools (MedSPAD)) or outside Europe (e.g.

Monitoring the Future).

In the coming years, ESPAD is committed not only to

continuing to monitor patterns of substance use but also to

assessing developments in internet use, as well as online

gaming and gambling. Furthermore, it will increase efforts to

promote research addressing the new challenges to increase

the understanding of substance use and risk behaviours and

provide evidence to develop and assess effective policies

and interventions.

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Acknowledgements

The

planning and implementation of the ESPAD 2019

project has been a collaborative effort between the

ESPAD Coordination Team and the research teams in

each participating country.

The

importance of the ESPAD

researchers and their supporting research groups and

institutions cannot be overestimated. As the project cannot

provide funding for data collection in the participating

countries, it relies on the ability of each PI and ESPAD

associate researcher to raise the necessary resources.

The

international coordination has been supported by the

Italian National Research Council (CNR) with co-funding

from the EMCDDA. Furthermore, CNR provided the

resources for the harmonisation of the national databases

and construction of the international 2019 database.

The

EMCDDA has supported the ESPAD project throughout the

2016-2020 cycle by co-funding and actively participating in

the international coordination, supporting preparatory work

including funding of the regional seminars and different

meetings, funding or co-funding data collection in Bulgaria,

Georgia, Germany (Bavaria), Greece, Kosovo, Montenegro,

Moldova, North Macedonia, Serbia and Ukraine and,

finally,

providing resources for the editing, layout and printing of this

report, including its online version.

The

Pompidou Group at the Council of Europe has supported

the project ever since the

first

project meeting in 1994. In

particular, during the 2016-2020 wave the

financial

support

of the Pompidou Group has enabled some researchers

from eastern and central parts of Europe to participate in

meetings.

The

ESPAD Coordination, consisting of Sabrina Molinaro

(Italy) and Julian Vicente (EMCDDA) supported by the

Italian ESPAD Coordination Team, coordinated the project

from 2016 to 2019.

The

Steering Committee, appointed by

the ESPAD researchers at the Assembly meetings, worked

together with the Coordination Team. All important decisions

relating to the planning of ESPAD meetings and the 2019

study were taken jointly with the Steering Committee.

Together with the two members of the Coordination

Committee, the Steering Committee consists of Sharon

Arpa (Malta), Pavla Chomynová (Czechia), Ludwig Kraus

(Germany), Håkan Leifman (resigned, Sweden), Karin

Monshouwer (the Netherlands) and Stanislas Spilka

(France).

The

Italian ESPAD Coordination Team at the National

Research Council, Institute of Clinical Physiology (CNR-

IFC) was responsible for coordinating the national data

collections, collecting country reports and datasets and

constructing the 2019 international database.

The

team also

produced results tables and text for the full online version

of the 2019 ESPAD report and the shorter print version of

the report, as well as for the ESPAD 2019 methodology

report.

The

Italian ESPAD Coordination Team consists of

Elisa Benedetti, Sonia Cerrai, Emanuela Colasante, Rodolfo

Cotichini, Loredana Fortunato and Sabrina Molinaro.

Those

at the EMCDDA supporting the ESPAD project and

its coordination are Julian Vicente, Kateřina

Škařupová,

Jean Mounteney, Paul Griffiths, Katarzyna Natoniewska and

Rosemary Martin de Sousa.

Each country was represented in the project by a principal

investigator (PI or ESPAD associate researcher), and these

PIs/associate researchers are contributing authors of this

report (see the title page). In addition, a number of other

people have carried out important work in the context of the

2019 ESPAD study. Special thanks go to Nikola Lanščak for

his valuable contribution to the revision of this report.

The

main people from the national research teams in the 35

countries participating in the 2019 data collection are listed

below.

This

is followed by a list of funding agencies and

supportive organisations.

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Acknowledgements

Collaborating persons

The

most important collaborators from each of the 35

countries that participated in the 2019 data collection are

listed below, beginning with the PIs.

Austria

Julian Strizek (PI), Markus Hojni, Jennifer Delcour, Alfred Uhl

Ireland

Luke Clancy (PI), Sheila Keogan, Salome Sunday, Joan Hanafin,

Hannah Byrne, Mark Ward, Zubair Kabir, Helen McAvoy

Italy

Sabrina Molinaro (PI); ESPAD Coordination Team: Elisa Benedetti,

Sonia Cerrai, Emanuela Colasante, Rodolfo Cotichini, Loredana

Fortunato; Italian ESPAD study group: Arianna Cutilli, Francesca

Denoth, Daniele Di Simone, Antonella Pardini, Roberta Potente,

Chiara Sbrana, Marco Scalese, Rita Taccini

Bulgaria

Anina Chileva (PI), Sophia Kandilarova-Georgieva, Alexander

Panayotov, Plamen Dimitrov, Juliya Andjekarska

Kosovo

Zamira Hyseni Duraku (PI), Kaltrina Kelmendi, Eurisa Rukovci

Croatia

Martina Markelić (PI), Ljiljana Muslić, Iva Pejnović Franelić, Sanja

Musić Milanović, Ivana Pavić

Šimetin,

Mario Hemen, Dijana Mayer,

Diana Jovičić Burić, Nikola Lanščak

Latvia

Diāna Vanaga-Arāja (PI), Laura Isajeva, Oksana

�½abko

Lithuania

Liudmila Rupšienė (PI), Sandra Valantiejienė, Regina Saveljeva,

Algimantas

Šimaitis

Cyprus

Kyriakos Veresies (PI), Ioanna Yiasemi (associate researcher),

Stelios Stylianou, Soula Ioannou

Malta

Sharon Arpa (PI), Petra Borg, Kay Xuereb, Sandra Cortis, Franceanne

Borg Orland, Karl Coleiro, Marjoe Abela, Lawrence Bonello, Emily

Chircop, Roslyn Spiteri, Ruth Stivala, Audrey Schembri, Antoine

Saliba, Daniela Bugeja, Shaun Bartolo, Gabrielle Bartoli, Christiana

Bajada, Isabelle Anastasi

Czechia

Pavla Chomynová (PI), Ladislav Csémy, Viktor Mravčík

Denmark

Ola Ekholm (PI), Heidi Amalie Rosendahl Jensen, Stine Rosenwein

Vork, Camilla Øst Cloos

Monaco

Stanislas Spilka (PI), Julie Marty, Sophie Vincent, Olivier Le Nézet

Estonia

Sigrid Vorobjov (PI)

Montenegro

Tatijana

Đurišić

(PI), Ljiljana Golubović, Boban Mugoša

Faroes

Pál Weihe (PI) and the staff of the Department of Occupational

Medicine and Public Health

Netherlands

Karin Monshouwer (PI), Marieke Rombouts, Saskia van Dorsselaer,

Marlous Tuithof

Finland

Kirsimarja Raitasalo (PI), Janne Härkönen

North Macedonia

Silvana Oncheva (PI), Elena Kosevska, Shaban Memeti, Vladimir

Mikik, Sanja Prosheva, Florije Fejzula, Daniela Dukovska, Vesna

Zafirovska, Jovanka Trpkovska, Jasmina Tahiri, Jasma Shakiri,

Nadica Totic, Stanislava Najdovska, Nadezda Lisinac, Marija

Vrckovska, Toda Krsteska, Petar Pecev, Aksinja Garbeska Kebakoska,

Vaska Kaleeva, Daniela Cingovska, Zagorka Josifova, Radmila

Maksimovska Simonovska, Marjan Denkovki, Eftim Dimitriev,

Viktorija Jordanova, Florija Hamid, Katarina Vidoeska, Marija

Postolovska

France

Stanislas Spilka (PI), Olivier Le Nézet, Eric Janssen

Georgia

Lela Sturua (PI), Natia Kakutia, Lela Kvachantiradze, Levan

Baramidze

Germany

Ludwig Kraus (PI), Nicki-Nils Seitz

Greece

Anna Kokkevi (PI), Anastasios Fotiou, Eleftheria Kanavou, Myrto

Stavrou, Clive Richardson

Norway

Elin Kristin Bye (PI)

Hungary

Zsuzsanna Elekes (PI), Tamás Domokos, Zsolt Demetrovics, Vanda

Pózner, Zita Szűcsné Kovács, Tamás Kosztolnyik

Poland

Janusz Sierosławski (PI),

Łukasz

Wieczorek, Katarzyna Dąbrowska

Portugal

Elsa Lavado (PI), Vasco Calado, Fernanda Feijão, Nuno Rodrigues,

Rui Lima, Suzete Frias, Nelson Carvalho

Iceland

Ársæll Már Arnarsson (PI), Ingibjörg Kjartansdóttir, Kristin

Hardardottir

Romania

Silvia Florescu (PI), Ruxanda Iliescu, Milica Georgescu, Cătălina

Chendea, Constanta Mihaescu-Pintia

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Acknowledgements

Serbia

Biljana Kilibarda (PI), Nadezda Nikolic, Jelena Gudelj Rakic, Verica

Jovanovic, Mirjana Tosic

Estonia

National Institute for Health Development; Estonian Ministry of

Social Affairs

Slovakia

Alojz Nociar (PI), Alena Kopanyiova, Jana Hamade, Maria Slovikova

Faroes

Ministry of Education, Research and Culture

Slovenia

Tanja Urdih Lazar (PI), Eva Stergar, Metoda Dodič Fikfak, Katja

Draksler, Nataša Dernovšček Hafner

Finland

Finnish Institute for Health and Welfare

France

French Monitoring Centre for Drugs and Drug Addiction (OFDT);

Ministry of National Education; Management of Programming and

Development (DEPP) of the Ministry of National Education; Ministry

of Agriculture and Food; French National Institute of Health and

Medical Research (Inserm)

Spain

Begoña Brime Beteta (PI), Marta Molina Olivas, Noelia Llorens

Aleixandre

Sweden

Johan Svensson (PI), Håkan Leifman, Ulf Guttormsson, Anna

Englund, Isabella Gripe, Siri

Thor

Georgia

National Center for Disease Control and Public Health with the

support of the EMCDDA; Ministry of Education, Science, Culture and

Sport of Georgia

Ukraine

Olga Balakireva (PI), Daria Pavlova, Tetiana Bondar, Dmytro

Dmytruk, Lidia Romanovska, Nam-Mykhailo Nguien, Nataliia

Yermolenko

Germany

IFT Institut für

Therapieforschung

with the support of the

Bayerisches Staatsministerium für Gesundheit und Pflege and the

EMCDDA

Funding agencies and supporting

organisations

For each of the 35 countries that participated in the 2019

data collection, the most important organisations and

funding agencies that were involved are listed below.

Austria

Gesundheit Österreich GmbH; Federal Ministry of Labour, Social

Affairs, Health, and Consumer Protection; Federal Ministry of

Education, Science and Research

Greece

Athens University Mental Health, Neurosciences and Precision

Medicine Research Institute (UMHRI) with the support of the

EMCDDA; Greek Organization Against Drugs (OKANA); Drug

Prevention Centres (OKANA/local authorities); Ministry of Health;

Ministry of Education (Directorate of Secondary Education); Greek

National Focal Point of the EMCDDA

Hungary

National Research, Development and Innovation Office: K 127947;

Department of Development Sociology, Kodolanyi Janos University;

Reitox Hungarian National Focal Point; Corvinus University of

Budapest

Bulgaria

National Center of Public Health and Analyses with the support

of the EMCDDA; National Center for Drug Addictions; Ministry of

Education and Science of Bulgaria; Centre for Providing Information

about Education

Iceland

Icelandic Directorate of Health; University of Iceland

Croatia

Croatian Institute of Public Health (CIPH); Ministry of Health;

Ministry of Science and Education

Ireland

TobaccoFree Research Institute Ireland; TU Dublin; Focas Research

Institute; Department of Health; Institute of Public Health in Ireland

(IPH)

Cyprus

Cyprus National Addictions Authority; Centre for Education About

Drugs and Treatment of Drug Addicted Persons; Ministry of

Education and Culture

Italy

National Research Council, Institute of Clinical Physiology (CNR-IFC)

Kosovo

Department of Psychology, Faculty of Philosophy, University of

Prishtina ‘Hasan Prishtina’ with the support of the EMCDDA;

Ministry of Education, Science, Technology and Innovation of

Kosovo; Municipal Education Directorate; Center for Global Health

Czechia

Czech National Monitoring Centre for Drugs and Addictions, Office

of the Government of the Czech Republic (NMC); National Institute

of Mental Health (NIMH)

Denmark

National Institute of Public Health, University of Southern Denmark;

Danish Health Authority; Ministry of Health

Latvia

Centre for Disease Prevention and Control; Baltic Institute of Social

Sciences (BISS)

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Acknowledgements

Lithuania

Ministry of Education, Science and Sport of the Republic of

Lithuania; Lithuanian National Agency for Education; Lithuanian

Educational Research Association

Portugal

General-Directorate for Intervention on Addictive Behaviours and

Dependencies (SICAD-Ministry of Health); General-Directorates of

Education Statistics and Education (Ministry of Education); Regional

Directorates for Prevention and Control of Dependencies and

Education and Culture of Azores Islands; Regional Secretaries of

Health and Education of Madeira Islands

Malta

Aġenzija Sedqa (National Agency against Drug and Alcohol Abuse

and Compulsive Gambling), Foundation for Social Welfare Services;

National School Support Services, Directorate for Educational

Services; Secretariat for Catholic Education; Independent Schools

Association and the participating independent schools

Romania

National Anti-drug Agency; Ministry of National Education;

National School of Public Health, Management and Professional

Development

Monaco

French Monitoring Center for Drugs and Drug Addiction (OFDT);

Monaco Statistics (Monegasque Institute of Statistics and

Economic Studies — IMSEE); Department of Education, Youth and

Sport of Monaco (DENJS)

Serbia

Ministry of Health of the Republic of Serbia; Institute of Public

Health of Serbia; Ministry of Education, Science and Technological

Development with the support of the EMCDDA

Montenegro

Public Health Institute of Montenegro with the support of the

EMCDDA; Ministry of Education of Montenegro; Ministry of Health of

Montenegro

Slovakia

Research Institute for Child Psychology and Pathopsychology; Office

of Public Health of the Slovak Republic; St Elizabeth College of

Health and Social Work; Slovak Centre of Scientific and Technical

Information; National Monitoring Centre for Drugs

Netherlands

Ministry of Health, Welfare and Sport; Regional Health Services;

Trimbos Institute

Slovenia

University Medical Centre Ljubljana, Institute of Occupational, Traffic

and Sports Medicine; Ministry of Education, Science and Sport

North Macedonia

Institute of Public Health with the support of the EMCDDA; Ministry

of Education and Science; Ministry of Health; Centers for Public

Health: Skopje, Kumanovo,

Štip,

Strumica, Veles, Prilep, Bitola,

Ohrid, Tetovo/Gostivar and Kočani

Spain

Spanish Observatory on Drugs and Addictions; Government

Delegation for the National Plan on Drugs; Ministry of Health

Sweden

Ministry of Health and Social Affairs; Swedish Council for

Information on Alcohol and Other Drugs (CAN)

Norway

Norwegian Institute of Public Health (NIPH)

Poland

National Bureau for Drug Prevention (KBPN); State Agency for

the Prevention of Alcohol-Related Problems (PARPA); Institute

of Psychiatry and Neurology (IPiN); Agency of Research and

Social Initiatives (PBIS); regional authorities of Dolnośląskie,

Kujawsko-Pomorskie, Lubelskie, Małopolskie, Mazowieckie,

Śląskie,

Świętokrzyskie

and Wielkopolskie regions; municipal authorities

of Bydgoszcz, Częstochowa, Płock, Kalisz, Sopot, Szczecinek and

Wrocław cities; Ministry of National Education

Ukraine

Ukrainian Institute for Social Research after Oleksandr Yaremenko

(UISR); Institute for Economics and Forecasting, National Academy

of Sciences of Ukraine (IEF NASU), with the support of the

EMCDDA; Social Monitoring Center (SMC); Ministry of Education

and Science of Ukraine; Center for Public Health, Ministry of Health

of Ukraine; United Nations Children’s Fund (UNICEF) in Ukraine

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130

ESPAD Report 2019

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

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SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

TD-03-20-531-EN-C

About this report

This

report presents the results from the seventh wave of data collection, conducted in 35

countries during the spring and autumn of 2019. It gives a comprehensive picture of the

present situation among European young people as regards the use of cigarettes, alcohol,

illicit drugs, inhalants, new psychoactive substances and pharmaceuticals, but also insights

into gambling, social media use and gaming.

The

report presents as well an overview of

trends in 1995-2019.

About the EMCDDA

The

European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) is the central

source and confirmed authority on drug-related issues in Europe. For 25 years, it has been

collecting, analysing and disseminating scientifically sound information on drugs and drug

addiction and their consequences, providing its audiences with an evidence-based picture of

the drug phenomenon at European level.

The

EMCDDA’s publications are a prime source of information for a wide range of audiences

including policymakers and their advisors; professionals and researchers working in the

drugs

field;

and, more broadly, the media and general public. Based in Lisbon, the EMCDDA

is one of the decentralised agencies of the European Union.

About ESPAD

The

European School Survey Project on Alcohol and Other Drugs (ESPAD) is a collaborative

effort of independent research teams in more than 40 European countries, making it the

largest cross-national research project on adolescent substance use in the world.

ESPAD was founded in 1993, on the initiative of the Swedish Council for Information on

Alcohol and Other Drugs (CAN) and with the support of the Pompidou Group at the Council

of Europe. In later years, ESPAD has also established increasingly close cooperation with

the EMCDDA, and at present the agency plays an important role in the coordination of the

ESPAD project.

Most of the European continent is now covered by ESPAD, meaning that it provides a reliable

overview of trends in substance use among 15- to 16-year-old European students. Data are

collected every 4 years.

ISBN 978-92-9497-547-8

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

Statens Institut for Folkesundhed

Alkoholforbrug og forekomsten

af ulykker og vold blandt unge

Data fra Ungdomsprofilen 2014 og Landspatientregistret

Louise Hjarnaa

Signe S. Hviid

Ulrik Becker

Bjarne Laursen

Janne S. Tolstrup

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALKOHOL OG ULYKKER BLANDT UNGE

Kolofon

Alkoholforbrug og forekomsten af ulykker og vold blandt unge

Data fra Ungdomsprofilen 2014 og Landspatientregistret

Louise Hjarnaa

Signe S Hviid

Ulrik Becker

Bjarne Laursen

Janne S Tolstrup

Internt review: Knud Juel

Statens Institut for Folkesundhed, SDU

Uddrag, herunder figurer og tabeller, er tilladt mod tydelig kildegengivelse.

Elektronisk udgave: ISBN 978-87-7899-518-6

Statens Institut for Folkesundhed

Studiestræde 6

1455 København K

www.sdu.dk/sif

Rapporten kan downloades fra www.sdu/sif

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALKOHOL OG ULYKKER BLANDT UNGE

Indhold

Sammenfatning .................................................................................................................. 5

Læsevejledning.................................................................................................................. 7

1. Introduktion .................................................................................................................... 8

2. Metode .......................................................................................................................... 10

2.1 Litteratursøgning ................................................................................................ 10

2.2 Kodning af ulykker og voldsepisoder baseret på Landspatientregistret .............. 12

2.3 Ungdomsprofil 2014-populationen ...................................................................... 14

2.4 Statistiske analyser ............................................................................................ 15

3. Beskrivelse af alkoholforbrug .................................................................................... 17

3.1 Alkoholindtag ............................................................................................................... 17

4. Forekomst af ulykker og vold ..................................................................................... 19

4.1 Fordelingen af ulykker og vold............................................................................ 19

4.2 Forekomst af ulykker i forhold til alkoholindtag ................................................... 21

4.3 Ulykker og vold fordelt på regioner ..................................................................... 22

4.4 Ulykker pr. person regionsfordelt........................................................................ 24

5. Sammenhæng mellem alkoholforbrug og ulykker .................................................... 25

5.1 Alle ulykker......................................................................................................... 25

5.2 Kønsspecifikke risici ........................................................................................... 27

5.3 Regionsspecifikke risici ...................................................................................... 29

5.4 Køretøjsulykker .................................................................................................. 31

5.5 Faldulykker......................................................................................................... 32

5.6 Sportsulykker ..................................................................................................... 34

5.7 Voldsepisoder .................................................................................................... 36

6. Diskussion.................................................................................................................... 38

Referencer ........................................................................................................................ 43

Bilag .................................................................................................................................. 46

Bilag 1: Søgematrice ................................................................................................ 47

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALKOHOL OG ULYKKER BLANDT UNGE

Forord

Danske unge har gennem mange år haft europarekorden i fuldskab og alkoholindtag. En tidlig

opstart og et stort forbrug af alkohol øger risikoen for at udvikle alkoholrelaterede problemer og

sygdomme senere i livet. Mange af disse problemer og sygdomme opstår først efter flere års højt

alkoholforbrug, hvorimod akutte konsekvenser som ulykker og voldshandlinger kan ske efter kort

tids forbrug og derfor i højere grad forekommer blandt unge.

På trods af viden om øget risikovillighed blandt unge og ved indtag af alkohol er det i Danmark

endnu ikke undersøgt, hvorvidt der er en sammenhæng mellem alkoholindtag og forekomsten af

ulykker. Formålet med denne rapport er derfor at belyse forekomsten af ulykker, der indebærer

hospitalskontakt, blandt unge fra gymnasiale uddannelser og erhvervsuddannelser i Danmark,

samt at undersøge hvorvidt der er en forskel i risikoen for at komme ud for en ulykke eller en

voldsepisode mellem unge med højt alkoholindtag og unge med et lavt alkoholindtag.

Rapporten bygger på den landsdækkende spørgeskemaundersøgelse Ungdomsprofilen 2014,

som omhandler sundhedsadfærd, helbred og trivsel blandt 75.000 unge på ungdomsuddannelser i

Danmark. Data omhandlende ulykker og voldsepisoder der har medført sygehuskontakt er

indhentet fra Landspatientregistret, som er et nationalt register, der indeholder oplysninger om alle

kontakter til danske offentlige sygehuse.

Rapporten er udarbejdet af en projektgruppe fra Statens Institut for Folkesundhed, med økonomisk

støtte fra Trygfonden og Alkohol & Samfund.

Venlig hilsen

Morten Grønbæk, direktør

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ALKOHOL OG ULYKKER BLANDT UNGE

Sammenfatning

I denne rapport anvendes der data fra Ungdomsprofilen 2014 og registerdata om ulykker fra

Landspatientregistret. Hver deltager blev fulgt i 4 år fra besvarelse af spørgeskemaet.

Forekomst af ulykker

Fordelingen af ulykker og vold

Blandt de 69.755 inkluderede unge er der i alt 28.019 ulykker og 910 voldsepisoder med

hospitalskontakt i perioden fra besvarelse af spørgeskemaet og 4 år frem. De hyppigst

forekommende ulykkestyper er sports- og faldulykker, som begge udgør ca. en fjerdedel af det

samlede antal ulykker. Køretøjsulykker udgør en tiendedel af alle ulykker, hvoraf de hyppigste er

cykel- og bilulykker. Drenge kommer oftere ud for en ulykke end piger, hvilket primært kan

tilskrives flere sportsulykker, knallertulykker og voldsepisoder.

Regional fordeling af ulykker

Fordelingen af ulykker mellem de forskellige ulykkestyper varierer på tværs af regionerne. Andelen

af fald- og sportsulykker er større i Region Nordjylland end i de øvrige regioner, mens andelen af

køretøjsulykker er højest i Region Syddanmark og Region Midtjylland. Halvdelen af ulykkerne i

Region Hovedstaden og Region Sjælland falder uden for de kategorier som er kategoriseret denne

rapport. Disse består blandt andet af ulykker, som er sket i hjemmet og under leg/fritidsaktivitet,

hvilket gælder mellem 33 % og 38 % i de øvrige regioner.

Ulykker pr. person

Fordelt efter ugentligt alkoholforbrug er antallet af ulykker højere i de grupper, som har det højeste

alkoholforbrug. Det gælder blandt både drenge og piger, dog kommer drenge oftere ud for en

ulykke end piger. Samme mønster findes for hyppighed af binge-drinking (indtag på 5+ genstande

ved samme lejlighed) og antal genstande indtaget ved sidste fest.

På regionsniveau er den højeste forekomst af ulykker i Region Sjælland, mens den laveste

forekomst af ulykker er i Region Midtjylland. I gennemsnit kommer hver 4. person i Region

Midtjylland ud for en ulykke, mens det gælder halvdelen i Region Sjælland.

Sammenhængen mellem alkoholforbrug og ulykker

Analysen af sammenhængen mellem alkoholforbrug og ulykker viser, at forholdet kan beskrives

som en dosis-respons-sammenhæng, hvor risiko for ulykker er højere blandt personer, som har et

højt indtag af alkohol, i forhold til dem, som har et lavt indtag, når der tages højde for forskelle i

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ALKOHOL OG ULYKKER BLANDT UNGE

gruppernes køns- og alderssammensætning, socioøkonomi, etnicitet, brug af rusmidler, m.m.

Samme tendens observeres for ugentligt alkoholforbrug, hyppighed af binge-drinking og antal

genstande indtaget ved sidste fest.

Kønsspecifik sammenhæng

Blandt både drenge og piger er der en højere risiko for ulykker i grupperne med højt alkoholforbrug

i forhold til grupperne med lavt alkoholforbrug. Blandt drenge er risikoen for ulykker højere for de

som har et hyppigt binge-indtag (>6 gange inden for de seneste 30 dage) og et højt antal

genstande indtaget ved sidste fest (> 16 genstande), sammenlignet med drenge som har binge-

drukket 0 gange eller indtaget 1-2 genstande ved sidste fest. Når de samme grupper

sammenlignes blandt pigerne, er der ligeledes en højere risiko for ulykker blandt pigerne med et

hyppigt binge-indtag og et højt antal genstande indtaget til sidste fest, dog er den relative forskel

mindre blandt pigerne end blandt drenge.

Regionsspecifik sammenhæng

Fordelt på regioner er resultaterne for sammenhængen mellem ugentligt alkoholindtag og

hyppighed af binge-drinking de samme som for hele populationen, og der er kun få regionale

forskelle.

Køretøjsulykker

Der ses ikke nogen sammenhæng mellem alkoholindtag og køretøjsulykker, når der blev taget

højde for forskelle i sammensætningen af grupperne med forskelligt alkoholforbrug.

Faldulykker

Generelt er der en øget risiko for faldulykker blandt unge med større alkoholforbrug i forhold til

unge med et lavt alkoholforbrug. Sammenhængen gælder for både ugentligt alkoholforbrug,

hyppighed af binge-drinking og antallet af genstande indtaget ved sidste fest. Her er risikoen

højere ved henholdsvis større ugentligt forbrug, hyppigere binge-druk og større antal genstande

indtaget ved sidste fest,

Sportsulykker

Der er ikke nogen tydelig sammenhæng mellem sportsulykker og alkoholforbrug. Dette gælder for

både ugentligt alkoholforbrug, hyppighed af binge-drinking og antal genstande indtaget ved sidste

fest.

Voldsepisoder

Generelt er der en højere risiko for skader som følge af voldsepisoder blandt unge med et større

ugentligt alkoholforbrug og hyppigere binge-drinking, end blandt unge med et lavt alkoholforbrug,

som ikke havde binge-drukket de seneste 30 dage. For antal genstande indtaget ved sidste fest er

der ikke nogen tydelig sammenhæng med voldsepisoder.

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Læsevejledning

Denne rapport tager udgangspunkt i selvrapporteret alkoholforbrug blandt deltagere i

Ungdomsprofilen 2014 og forekomsten af ulykker og voldsepisoder med hospitalskontakt

registreret i de følgende 4 år fra besvarelsen af spørgeskemaet. Ud fra ovenstående data

analyseres fordelingen af ulykker og sammenhængen mellem alkoholforbrug og ulykker blandt

unge fra gymnasiale uddannelser og erhvervsuddannelser i alderen 15-20 år.

Alle resultater er beregnet for alle deltagere i Ungdomsprofilen 2014 i alderen 15-20 år og er

desuden beregnet for henholdsvis drenge og piger for at fremhæve eventuelle kønsforskelle. I

resultatafsnittene angives fordelingen af ulykker som procentandelen af ulykker inden for den

konkrete gruppe, der analyseres (for eksempel drenge). I analysen af forskellen i risikoen for

ulykker mellem grupper med forskelligt alkoholforbrug er der for hver deltager set på, hvor lang tid

der går fra besvarelse af spørgeskemaet til den første ulykke indtræffer (førstegangsulykken). For

personer med flere ulykker er det derfor kun den første ulykke, der indgår i analysen.

Rapporten indledes af et baggrundsafsnit med en introduktion til alkoholforbrug og

sammenhængen mellem alkoholforbrug og ulykker blandt unge (kapitel 1). Herefter følger en

beskrivelse af metoden, som indeholder kodningen af ulykker, metoden bag Ungdomsprofilen

2014 og de statistiske analyser (kapitel 2). Efterfølgende præsenteres resultater, som beskriver

alkoholforbruget blandt unge fra Ungdomsprofilen 2014 (kapitel 3) samt forekomsten af ulykker

(kapitel 4). Derefter følger afsnittet om alkoholforbrug og risiko for ulykker (kapitel 5) og som det

sidste diskuteres rapportens resultater (kapitel 6).

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ALKOHOL OG ULYKKER BLANDT UNGE

1. Introduktion

Alkoholforbrug blandt unge i Danmark

Den Nationale Sundhedsprofil fra 2017 viser, at andelen som overskrider Sundhedsstyrelsens

lavrisikogrænse for

alkoholindtag (14 genstande for mænd og 7 for kvinder om ugen) i alderen 16-

24 år er

23,3 % blandt mænd og 30,9 % blandt kvinder(1). Ydermere viser en undersøgelse blandt

godt 29.000 danske unge fra 2019, at det ugentlige gennemsnitlige alkoholforbrug blandt de

deltagende gymnasieelever er henholdsvis 13,9 genstande for drenge og 9,3 genstande for piger,

mens 38 % af drengene og 24 % af pigerne har binge-drukket 4 eller flere gange inden for den

seneste måned (2). I en international undersøgelse finder man, at de danske unges alkoholforbrug

er det højeste i Europa. Blandt de danske 16-årige havde 73 % drukket alkohol og 32 % har været

berusede indenfor den seneste måned. Til sammenligning har 26 % af de svenske og 22 % af de

norske 16-årige drukket alkohol inden for den seneste måned, mens henholdsvis 8 % og 9 % har

været berusede (3).

Sammenholdt med andre europæiske lande er den danske alkoholkultur liberal med let adgang til

at købe alkohol og få restriktioner på tilgængeligheden af alkohol (4). Aldersgrænsen i Danmark for

salg af alkohol (med alkoholprocent op til 16,5 %) er 16 år, hvorimod den i de fleste andre

europæiske lande er 18 år. Til gymnasiefester er det for eksempel flere steder muligt at købe

alkohol uanset alder, hvormed unge på 15 år, som netop er begyndt på gymnasiet, kan købe

alkohol til billige priser (5). I Danmark skal man være 18 år for at købe stærkere typer af alkohol i

butikkerne og for at få serveret alkohol på værtshus, men aldersgrænserne håndhæves kun i

beskedent omfang (5).

Konsekvenser af højt alkoholindtag

Blandt unge er alkoholindtag forbundet med en række umiddelbare negative konsekvenser.

Alkohol er forbundet med øget risikovillighed og nedsat koordinationsevne, hvilket resulterer i

dårligere motorik og forlænget reaktionstid (6-8). Denne kombination kan medføre en øget

sandsynlighed for ulykker. En stor andel unge i Danmark har oplever at være involveret i ulykker,

komme i slagsmål eller gøre ting, som de senere fortryder, når de drikker alkohol (9), og flere

studier finder en positiv sammenhæng mellem alkoholpåvirkning og ulykker under færdsel (10-12).

Studier finder ligeledes en direkte sammenhæng mellem alkoholindtag og biluheld (13-17),

drukneulykker (18), vold (19), faldulykker (20) og kollisioner mellem fodgængere og tog (21). Et

stort alkoholforbrug kan have en række andre negative konsekvenser, men klassiske

alkoholrelaterede sygdomme som for eksempel skrumpelever, betændelse i bugspytkirtlen, kræft

eller lignende opstår først efter flere års højt alkoholforbrug og viser sig derfor ikke blandt unge.

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ALKOHOL OG ULYKKER BLANDT UNGE

Alkohol og ulykker

En national rapport, som belyser forekomsten af køretøjsulykker, arbejdsulykker og hjemme-

fritidsulykker, ud fra 21 års dataindsamling fra Ulykkesregistret, viser at risiko for ulykker generelt

er højest i aldersgruppen 10-24 år. Rapporten viser desuden, at antallet af hjemme-fritidsulykker,

som sker under påvirkning af alkohol, er større for 15-24-årige. Det samme gælder trafikulykker,

men her fordeler antallet sig mere ligeligt over hele populationen (22). Et studie fra 2013 fandt

desuden, at 252 ud af 840 voldsomme skader efter trafikulykker i Danmark i perioden 2007 til 2010

var relateret til alkohol, og at 31,6 % af disse involverede personer under 35 år (23). Herudover

viser en opgørelse over somatiske ambulante hospitalsbesøg, at der i årene 2010 til 2012 i

gennemsnit var 417 somatiske ambulante hospitalsbesøg blandt unge i alderen 16-24 år, hvor

enten aktions- eller bi-diagnose var alkoholrelateret (24).

Prædiktorer for alkoholrelaterede ulykker

Et dansk studie fra 2019 finder en dosis-respons-sammenhæng mellem mængde og frekvens af

alkoholindtag og involvering i en selvrapporteret ulykke (25). Undersøgelsen finder desuden, at det

at have forældre med lavere uddannelsesniveau, lavere indkomst i husstanden og forældre, der

ikke arbejder, er relateret til en øget risiko for skade i forbindelse med indtag af alkohol (25).

Studier fra USA og Spanien finder, at adfærdsproblemer før og efter 15-årsalderen samt tidlig

alkoholdebut er associeret med at køre bil under påvirkning af alkohol (26-28).

Mænd er generelt i større risiko for at blive impliceret i en trafikulykke end kvinder (22). Dansk

statistik fra perioden 2010-2018 viser, at især mænd i alderen 18-24 år er overrepræsenteret

blandt de tilskadekomne i spiritusrelaterede trafikuheld i forhold til kvinder (29). Dette stemmer

godt overens med resultater fra udenlandske studier (17, 18, 27, 30). Et amerikansk studie fra

2014 finder, at mænd, som enten har en depression eller et problematisk forhold til alkohol, i

højere grad er i risiko for at køre under påvirkning af alkohol i forhold til mænd uden disse faktorer

(28). Et studie fra Australien finder, at 12-24 årige mænd i højere grad bliver indlagt med eksterne

fysiske problematikker, som vold og trafikulykker, hvorimod kvinder i højere grad bliver indlagt som

følge af selvskade og alkoholforgiftning (31). Det kan tyde på, at der ikke bare er en kønsforskel i

hyppigheden af ulykker, men også i skadestype.

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ALKOHOL OG ULYKKER BLANDT UNGE

2. Metode

2.1 Litteratursøgning

I forbindelse med udarbejdelsen af denne rapport er der foretaget en systematisk litteratursøgning i

databaserne Cochrane Library, PubMed og Embase. Denne litteraturgennemgang danner

baggrundsforståelsen for rapporten. Cochrane Library blev benyttet grundet det høje

evidensniveau samt omfattende indhold af systematiske reviews. PubMed blev benyttet på

baggrund af et stort antal internationale tidsskrifter og fokus på natur- og sundhedsvidenskab.

Embase blev valgt på grund af dens biomedicinske fokus, og da den regnes som et vigtigt

supplement til blandt andet Pubmed. Det overordnede formål med undersøgelsen dannede

rammerne for de i søgematricen definerede søgeord, som blev benyttet i den systematiske

søgning (se bilag 1).

Litteratursøgningen i PubMed tog udgangspunkt i bloksøgning ud fra ovennævnte søgematrice og

udvalgte MeSH-termer og fritekstord. Søgning i Cochrane og Embase tog udgangspunkt i MeSH-

termer. Søgningen blev begrænset til tidsperioden 2010 til 2020 for at medtage den nyeste

forskning på området. Herudover blev søgningen begrænset til litteratur på engelsk, dansk, svensk

eller norsk.

I alt gav søgningen 3.233 hits, hvoraf 185 blev frasorteret som dubletter. De resterende 3.048

artikler blev gennemgået på titel, hvoraf 2.544 blev frasorteret grundet emne. Efterfølgende blev

formål med studierne gennemgået, hvoraf 376 hits blev sorteret fra. De resterende 128 blev

gennemgået på abstract, hvoraf 74 blev frasorteret på grund af målgruppe, geografi eller

eksponering. Af de 128 var der 54 studier tilbage, som blev gennemgået ved fuldtekstlæsning. Ud

af disse 54 studier blev 18 vurderet relevante til inklusion. Herudover blev der fundet yderligere 3

studier ved kædesøgning. Disse 21 studier blev benyttet til at danne baggrundforståelse for

undersøgelsen.

Ud over de fundne artikler bliver der i baggrundsforståelsen taget udgangspunkt i offentligt

tilgængelige overblik fra Danmarks Statistik samt danske rapporter, som blev udvalgt på baggrund

af temaerne; unge, alkohol og/eller ulykker.

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ALKOHOL OG ULYKKER BLANDT UNGE

Identificering

Referencer identificeret fra EMBASE,

PubMed og Cochrane Library:

n=3.233

Dubletter:

n=185

Referencer til screening af titel:

n=3.048

Ekskluderet ved fra screening af

titel:

n=2.544

Ekskluderet ved gennemgang af

formål:

Referencer til screening af formål:

Forkert studiepopulation

Forkert eksponering

Forkert udfaldsmål

n=376

Ekskluderet ved gennemlæsning

grundet:

Tidsperiode

Formål

Studiepopulation

Eksponering

Geografisk sammenlignelighed

n=74

Screening

n=504

Referencer til gennemgang af abstract:

n=128

Referencer til fuldtekst læsning:

n=54

Ekskluderet ved fuldtekst læsning:

n=36

Inklusion

Rapporter fra fritekstsøgning:

n=13

Artikler fra kædesøgning:

n=3

Antal referencer efter gennemlæsning:

Artikler: n=21

Rapporter: n=13

Figur 1. Flowchart over

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ALKOHOL OG ULYKKER BLANDT UNGE

2.2 Kodning af ulykker og voldsepisoder baseret på

Landspatientregistret

Opgørelsen af ulykker er baseret på data fra Landspatientregistret, som indeholder informationer

om alle kontakter til danske offentlige sygehuse (32). Hver gang, en person har en ny kontakt til

sygehuset, indsamles der en række oplysninger om kontakten og patienten, som efterfølgende

overføres til Landspatientregistret. Denne undersøgelse bygger på oplysninger om patientens

personnummer og kontaktens årsag samt oplysninger om ulykkens karakteristika og

omstændigheder. Kontaktens årsag definerer, hvilken af følgende grunde der har forårsaget

kontakten: ulykke, vold, selvmordsforsøg, senfølge, sygdom, eller øvrige grunde. I denne

undersøgelse er der set på alle kontakter med kontaktårsagen ulykke eller vold, hvor både

ambulante kontakter og indlæggelser er medtaget. Alle øvrige kontakter blev frasorteret. Ulykker er

defineret som alle kontakter med kontaktårsagen ulykke, mens vold er defineret som alle kontakter

med vold som årsag. For at sikre, at den enkelte kontakt kun indgår én gang i opgørelsen, kan

hver person kun have én ulykke- eller vold-kontakt pr. dag.

Landspatientregistret indeholder informationer om ulykkens art, ulykkessted, skadesmekanisme,

transportform ved køretøjsulykker m.m., som er registreret i form af ulykkeskoder. Hver ulykke har

typisk mellem 1-10 ulykkeskoder tilknyttet. For at kunne lave opgørelser over specifikke typer af

ulykker er ulykkeskoderne brugt til at definere en række ulykkeskategorier. Kategorierne er ikke

gensidigt udelukkende og overlap forekommer i større eller mindre grad. For eksempel kan

faldulykker, som er sket i forbindelse med transport eller sport, have både en ulykkeskode for fald

og en ulykkeskode for transport eller sport.

En rapport om kvaliteten af ulykkesinformationerne i Landspatientregistret viser, at en række

oplysninger om ulykker er mangelfuldt registreret, hvorfor brugen af ulykkeskoder til at kategorisere

ulykkerne indebærer en risiko for, at ulykkerne er fejlkategoriserede, ligesom antallet af nogle typer

af ulykker vil være underestimeret (33).

Kategorierne og ulykkeskoder, som danner grundlag for hver kategori, fremgår af Tabel 2.2.

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ALKOHOL OG ULYKKER BLANDT UNGE

Tabel 2.2

Navne, grundlag og definition af ulykkeskategorier

Kategori

(ulykker)

Fald

Type af oplysning

Hændelse og

mekanisme

Ulykkeskoder

EUHE

EUBA

EUBB

Definition

Alle kontakter med ulykkeskode ”EUHE0”

Hændelse: Fald

+ ”EUBA” =

Mekanisme: Fald og hop i niveau eller

under 1 meter

+ ”EUBB” =

Mekanisme:

Fald og hop over 1 meter

Køretøj

Transport

EUP

Alle kontakter med ulykkeskode ”EUP” =

EUM

Transportform for tilskadekommen

med

undtagelse af kontakter hvor

tilskadekomne har været til fods (kode:

”EUP1” =

Transportform for

tilskadekommen: Til fods)

og der enten

ikke har været en modpart (kode: ”EUM0”

Ingen modpart)

eller modparten også

har være til fods (kode: ”EUM1” =

Transportform for modpart: Til fods).

Tilskadekommen kan både være fører af

køretøjet eller passager.

Trafik

Transport og sted

EUP

Køretøjsulykker (se ovenstående) som har

EUM

fundet sted i et trafikområde (kode:

EUG

”EUG0” =

Sted: Offentlig vej og

parkeringsområde)

Cykel

Transport

EUP2

Alle kontakter med ulykkeskode ”EUP2” =

Transportform for tilskadekommen: På

cykel

Knallert

Transport

EUP3

Alle kontakter med ulykkeskode ”EUP3” =

Transportform for tilskadekommen: På

knallert

Bil

Transport

EUP5

Alle kontakter med ulykkeskode ”EUP5” =

Transportform for tilskadekommen: I

personbil

Løbehjul eller

Transport

EUP8C

Alle kontakter med ulykkeskode ”EUP8C”

skateboard

EUP8D

Transportform for tilskadekommen: På

løbehjul

Eller

”EUP8D” =

Transportform for

tilskadekommen: På skateboard

Fodgænger*

Transport

EUP1

Alle kontakter med ulykkeskode ”EUP1” =

Transportform for tilskadekommen: Til

fods

Arbejdsrelateret

Aktivitet

EUA1

Alle kontakter med ulykkeskode ”EUA1” =

Aktivitet: Lønnet arbejde

Sportsrelateret

Aktivitet

EUA5

Alle kontakter med ulykkeskode ”EUA5” =

Aktivitet: Sport og motion

*Fodgængerulykker omfatter alle køretøjsulykker, hvor en fodgænger kommer til skade som følge af en

person på et andet køretøj. Ulykker, hvor en fodgænger er faldet, uden at det har involveret et andet køretøj,

kan ikke betegnes som fodgængerulykker.

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ALKOHOL OG ULYKKER BLANDT UNGE

2.3 Ungdomsprofil 2014-populationen

Beskrivelsen af gymnasie- og erhvervsskoleelevers brug af alkohol er baseret på data fra den

landsdækkende spørgeskemaundersøgelse Ungdomsprofilen 2014, gennemført af Statens Institut

for Folkesundhed, SDU, og afrapporteret i 2015 (34). Via CPR-nummeret kan deltagerne i

Ungdomsprofilen 2014 kobles med nationale registre, heriblandt Landspatientregistret, som denne

undersøgelse er baseret på.

Elevgrundlag

Unge fra både gymnasiale uddannelser og erhvervsuddannelser er repræsenteret i

Ungdomsprofilen 2014. Blandt de gymnasiale uddannelser er alle landets 137 almene gymnasier

(STX og HF) inviteret til at deltage, og blandt erhvervsuddannelser er 12 af landets største

erhvervsskoler inviteret til at deltage med grundforløbshold (ud af i alt 91 erhvervsskoler i

Danmark). De 12 inviterede erhvervsskoler er udvalgt på baggrund af størrelse samt geografisk

placering for at styrke den regionale repræsentativitet.

Dataindsamling og spørgeskema

Spørgeskemaet i Ungdomsprofilen 2014 indeholdt omkring 250 kernespørgsmål, som belyste

sundhedsadfærd, helbred og trivsel.

Dataindsamlingen foregik fra januar 2014 til december 2014 via et internetbaseret spørgeskema,

som blev udfyldt i en af skolen valgt undervisningstime. Klasser/hold som havde få eller ingen

besvarelser blev efterfølgende rykket for besvarelse.

En nærmere beskrivelse af spørgeskema og dataindsamlingen findes i publikationen

”Ungdomsprofilen 2014. Sundhedsadfærd, helbred og trivsel blandt elever på

ungdomsuddannelser” (34).

Undersøgelsen af alkohol og ulykker bygger på data fra elever mellem 15-20 år, der kan kobles til

registre. Resultaterne i rapporten er således baseret på information fra 69.755 elever.

2.3

viser fordelingen af deltagerne fra denne undersøgelse opdelt på køn, alder og region. I

Tabel

tabellen fremgår det, at gennemsnitsalderen blandt de inkluderede elever er 17,4 år blandt

gymnasieelever og 17,7 år blandt erhvervsskoleelever.

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ALKOHOL OG ULYKKER BLANDT UNGE

Tabel 2.3.

Deltagere opdelt på køn, alder og region

I alt

Køn

Piger

Drenge

Alder

≤16 år

17 år

18 år

19 år

20 år

Region

Hovedstaden

Midtjylland

Syddanmark

Sjælland

Nordjylland

21.524

15.243

14.459

10.987

7.542

(31)

(22)

(21)

(16)

(11)

14.087

23.488

21.006

9.787

1.387

(20)

(34)

(30)

(14)

(2)

41.396

28.359

(59)

(41)

69.755

(%)

(100)

Gymnasier

66.577

41.396

28.359

13.547

22.412

20.315

9.287

1.016

20.717

14.648

13.649

10.250

7.313

(%)

(100)

(61)

(39)

(20)

(34)

(31)

(14)

(2)

(31)

(22)

(21)

(15)

(11)

Erhvervsuddannelser

3.178

685

2.493

540

1.076

691

500

371

807

595

810

737

229

(%)

(100)

(22)

(78)

(17)

(34)

(22)

(16)

(12)

(25)

(19)

(25)

(23)

(7)

Elever på HHX, HTX og særligt tilrettelagte ungdomsuddannelser er ikke repræsenteret i

undersøgelsen. Ungdomsprofilen 2014 inkluderer desuden ikke HF-enkeltfagselever, HF-elever fra

skoler, der ikke også tilbyder STX, samt elever på erhvervsuddannelsernes hovedforløb.

Herudover er unge, der ikke går på en ungdomsuddannelse, ikke repræsenteret i undersøgelsen.

Resultaterne fra Ungdomsprofilen 2014 kan således ikke generaliseres til danske unge som

helhed, men viser derimod et billede af de danske unge, der i 2014 gik på de udvalgte

ungdomsuddannelser; de almene gymnasier og erhvervsuddannelsernes grundforløb.

2.4 Statistiske analyser

I denne undersøgelse bliver der anvendt Cox regressionsanalyser til analysen af risiko for ulykker

for forskellige niveauer af alkoholindtag. Alle analyser baseres på data fra subpopulationen af

Ungdomsprofilen 2014, som er beskrevet ovenfor. Hver person følges fra datoen, hvor de

besvarede spørgeskemaet (baseline) til Ungdomsprofilen 2014, til datoen hvor de kom ud for en

ulykke, døde, flyttede ud af landet eller i maksimalt 4 år efter baseline. På grundlag af den periode,

hver enkelt person bidrager med (maksimalt 1.461 dage), og antallet af ulykker beregnes hazard

og hazard ratio (HR) med tilhørende 95 % konfidensintervaller mellem grupperne, som

sammenlignes. Hazard kan beskrives som sandsynligheden for at opleve en ulykke i en gruppe i

forhold til den tid, personerne i gruppen bidrager med, hvor en hazard på 0,1 betyder, at 10 % af

personerne kommer ud for en ulykke over en given tidsperiode, for eksempel et år. Sammenholdes

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ALKOHOL OG ULYKKER BLANDT UNGE

en gruppe med hazard på 0,1 med en gruppe med hazard på 0,05, vil hazard ratioen for den første

gruppe i forhold til den anden være 2, hvilket betyder, at andelen, som kommer ud for en ulykke

over en given tidsperiode, er dobbelt så stor. Generelt betyder en hazard ratio større end 1, at den

betragtede gruppe har større sandsynlighed end referencegruppen for at opleve det som

undersøges, for eksempel ulykke, mens et resultat under 1 betyder, at den betragtede gruppe har

mindre sandsynlighed end referencegruppen.

For at undersøge, om der er en forskel i sandsynligheden for ulykker og vold mellem grupper med

forskelligt alkoholindtag, kategoriseres populationen efter deres alkoholforbrug, hvor der ses på

ugentligt alkoholindtag, hyppighed af binge-drinking inden for de seneste 30 dage, og antal

genstande indtaget til sidste fest. Afhængig af hvilket parameter for alkoholforbrug der er i fokus,

sammenlignes hver gruppe med en referencegruppe, som har følgende forbrugsmønster: ugentligt

alkoholforbrug på 0 genstande, binge-drinking 0 gange inden for de seneste 30 dage, indtaget 0

genstande til sidste fest.

For hver kategori af alkoholforbrug beregnes hazard ratio for ulykke i forhold til referencegruppen.

Der kan dog være andre faktorer end alkoholforbrug, som har betydning for sandsynligheden for at

komme ud for en ulykke, for eksempel køn, brug af andre rusmidler, socioøkonomisk status, m.v.

For at tage højde for ubalancer i sammensætningen af grupperne med forskelligt alkoholindtag, er

resultaterne justeret for forskelle mellem grupper, der sammenlignes. I det første sæt af analyser

justeres der for køn, alder, ungdomsuddannelse, socioøkonomisk position og etnicitet. I det andet

sæt af analyser justeredes der yderligere for brug af cannabis, brug af stoffer, rygning, betydningen

af karakter og deltagelse i gymnasiefest. Faktorerne, der bliver justeret for, er valgt på grundlag af,

hvad tidligere studier har fundet, havde betydning for alkoholindtag og sandsynligheden for ulykker

(25, 35, 36)

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ALKOHOL OG ULYKKER BLANDT UNGE

3. Beskrivelse af

alkoholforbrug

3.1 Alkoholindtag

I Ungdomsprofilen 2014 har eleverne angivet, hvor mange genstande de drikker i gennemsnit på

en normal uge. Over halvdelen af deltagerne har angivet at de drikker imellem 1 til 13 genstande

pr. uge, mens 13 % har angivet at de drikker over 21 genstande. Eleverne er desuden blevet

spurgt til, hvor mange gange de har binge-drukket (indtaget 5 eller flere genstande ved samme

lejlighed) inden for de seneste 30 dage. Her har 35 % af de unge angivet, at de har binge-drukket

2-3 gange (tabel 3.1). Endelig er eleverne blevet spurgt til, hvor mange genstande de indtog ved

sidste fest. Her har 42 % angivet at de indtog 3-9 genstande.

Generelt er alkoholindtaget større blandt drengene i undersøgelsen end blandt pigerne. Andelen af

drenge, som har angivet at de drikker mere end 27 genstande om ugen, er næsten 3 gange større

end andelen af piger. Tilsvarende er der dobbelt så mange drenge som piger, der har angivet at de

har binge-drukket mere end 6 gange inden for de seneste 30 dage og næsten 3 gange så mange

drenge som piger, der har angivet at de indtog mere end 16 genstande ved sidste fest.

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Tabel 3.1

Fordeling af alkoholindtag blandt deltagerne i subpopulationen fra Ungdomsprofilen 2014,

total og fordelt efter køn

Total

Drenge

Piger

(N = 69.755)

(N =28.359)

(N = 41.396)

Ugentligt alkoholforbrug

Drikker ikke

0 genstande

1-7 genstande

8-13 genstande

14-20 genstande

21-27 genstande

>27 genstande

Binge-drinking (seneste 30 dage)

Drikker ikke

0 gange

1 gang

2-3 gange

4-6 gange

>6 gange

Genstande indtaget ved sidste fest

Drikker ikke

Aldrig deltaget i fest

0 genstande

1-2 genstande

3-9 genstande

10-15 genstande

16+ genstande

4.990

2.809

2.262

3.812

27.629

19.260

5.842

4.990

7.794

11.534

23.213

14.817

4.522

4.990

6.746

20.548

16.121

11.343

4.124

5.055

*828 har ikke angivet ugentligt alkoholforbrug, 2.885 har ikke angivet hyppighed af binge-drinking,

3.151 har ikke angivet antal genstande indtaget ved sidste fest

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ALKOHOL OG ULYKKER BLANDT UNGE

4. Forekomst af ulykker og

vold

I de følgende afsnit beskrives forekomsten af ulykker i perioden fra hver persons besvarelse af

spørgeskema og 4 år frem. Foruden det totale antal ulykker er der opgjort antal for hver

ulykkeskategori. Som nævnt i metodeafsnittet er kategorierne ikke gensidigt udelukkende, og

tallene kan derfor ikke summeres.

4.1 Fordelingen af ulykker og vold

Blandt de 69.755 inkluderede unge ses der i alt 28.019 ulykker i perioden fra besvarelse af

spørgeskemaet og 4 år frem. Tabel 4.1 viser den samlede fordelingen af ulykker efter ulykkestype

samt fordelingen af ulykker fordelt på henholdsvis drenge og piger. Den angivne procent er

andelen af alle ulykker i den givne gruppe, for eksempel udgjorde de 3.061 faldulykker blandt

drenge 22 % af det samlede antal (n=13.612) ulykker blandt drenge.

De hyppigst forekommende ulykkestyper er sports- og faldulykker, som begge udgør ca. en

fjerdedel af det samlede antal ulykker. Køretøjsulykker udgør en tiendedel af alle ulykker, hvoraf de

hyppigste er cykel- og bilulykker.

42 % af ulykkerne falder uden for de nævnte ulykkestyper. Denne gruppe indeholder blandt andet

ulykker, der er sket i hjemmet, og ulykker, der er opstået i forbindelse med leg eller fritidsaktivitet.

Generelt er der en større forekomst af ulykker blandt de deltagende drenge end blandt de

deltagende piger, ligesom der er flere voldsepisoder blandt drengene. Ligeledes er der en forskel i

forekomsten af de enkelte ulykkestyper blandt drenge og piger. Andelen af sportsulykker er større

blandt drenge end blandt piger, hvorimod bil- og faldulykker udgør en større andel af ulykker blandt

piger end blandt drenge.

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Tabel 4.1

Fordeling af ulykkesforekomst på forskellige ulykkestyper og vold i perioden fra baseline og 4 år

frem samlet og fordelt efter køn. Antal ulykker og andel af alle ulykker (% af den givne ulykkesforekomst)

Alle

Drenge

Piger

(N = 69.755)

(N =28.359)

(N = 41.396)

Alle ulykker (ekskl. vold)

Faldulykker

Køretøjsulykker

Cykelulykker

Knallertulykker

Bilulykker

Løbehjul, skateboard, m.m.

Andet transportmiddel

Sportsulykker

Arbejdsulykker

Ikke kategoriseret*

Vold

28.019

6.823

2.633

1.138

123

1.181

6.786

2.444

11.828

(24)

(9)

(4)

(0)

(4)

(0)

(24)

(9)

(42)

(%)

13.612

3.061

1.178

552

451

3.953

1.362

5.390

(22)

(9)

(4)

(1)

(3)

(0)

(29)

(10)

(40)

(%)

14.407

3.762

1.455

586

730

2.833

1.082

6.438

(26)

(10)

(4)

(0)

(5)

(0)

(20)

(8)

(45)

(%)

683

910

227

Kategorierne er ikke gensidigt udelukkende, og tallene kan ikke summeres

*Ikke kategoriserede ulykker består blandt andet af følgende type af ulykker: Leg/fritidsaktivitet, huslige

aktiviteter, ulykker i hjemmet, m.v.

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ALKOHOL OG ULYKKER BLANDT UNGE

4.2 Forekomst af ulykker i forhold til alkoholindtag

Tabel 4.2 giver et overblik over, hvor mange ulykker der i gennemsnit er sket pr. person igennem

de 4 års opfølgning fordelt efter alkoholindtag. Generelt ses der en større forekomst af ulykker i

gruppen som har angivet et højt indtag af alkohol, i forhold til grupperne der har angivet et lavere

indtag af alkohol. Blandt piger ses den laveste forekomst af ulykker i gruppen, der har angivet at de

ikke drrikker, mens den laveste forekomst af ulykker blandt drenge ses blandt de drenge der har

angivet at de drikker 1-7 genstande om ugen, har binge-drukket 1 gang inden for de seneste 30

dage eller indtog 3-9 genstande ved sidste fest. Generelt er hyppigheden af ulykker større blandt

drenge end blandt piger.

Tabel 4.2

Fordeling af antal ulykke i de første 4 år efter baseline pr. person efter alkoholindtag og køn,

gennemsnit

Total

Ulykker total

Drenge

Piger

(N =

(N = 28.019)

(N =28.359)

(N = 41.396)

69.755)

Antal

Gns.

personer

Ulykker

total

drenge

piger

Ugentligt alkoholforbrug

Drikker ikke

0 genstande

1-7 genstande

8-13 genstande

14-20 genstande

21-27 genstande

>27 genstande

4.990

6.746

20.548

16.121

11.343

4.124

5.055

1.657

2.974

7.216

5.904

4.718

2.059

3.153

0,33

0,44

0,35

0,37

0,42

0,50

0,62

0,44

0,50

0,41

0,43

0,47

0,53

0,68

0,27

0,39

0,32

0,33

0,37

0,46

0,52

Binge-drinking (seneste 30 dage)

Drikker ikke

4.990

0 gange

1 gang

2-3 gange

4-6 gange

>6 gange

7.794

11.534

23.213

14.817

4.522

1.657

2.970

4.158

8.886

6.355

2.436

0,33

0,38

0,36

0,38

0,43

0,54

0,44

0,45

0,42

0,45

0,49

0,61

0,27

0,34

0,33

0,34

0,37

0,45

Genstande indtaget ved sidste fest

Drikker ikke

4.990

Aldrig deltaget i fest

0 genstande

1-2 genstande

3-9 genstande

10-15 genstande

16+ genstande

2.809

2.262

3.812

27.629

19.260

5.842

1.657

1.280

1.021

1.350

9.044

7.982

3.137

0,33

0,46

0,45

0,35

0,33

0,41

0,54

0,44

0,46

0,53

0,39

0,37

0,45

0,57

0,27

0,46

0,40

0,34

0,31

0,38

0,48

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ALKOHOL OG ULYKKER BLANDT UNGE

4.3 Ulykker og vold fordelt på regioner

I tabel 4.3. ses ulykkesforekomst fordelt på regioner. Region Hovedstaden rummer den største

befolkning, hvorfor det totale antal ulykker er størst i denne region.

Fordelingen af de enkelte ulykkestyper varierer mellem regionerne. Da der i de foregående

resultater ikke ses nogle ulykker relateret til løbehjul, skateboard eller lignende, vil disse

fremadrettet ikke indgå i resultaterne.

I Region Nordjylland ses der en større andel af både fald- og sportsulykker end i de øvrige

regioner. Den største andel af køretøjsulykker ses i Region Syddanmark og Region Midtjylland

som følge af en højere andel cykel- og bilulykker.

Halvdelen af ulykkerne i Region Hovedstaden og Region Sjælland falder uden for de beskrevne

kategorier, hvilket er 10 procentpoint mere end i de øvrige regioner.

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Tabel 4.3

Ulykkesforekomst fordelt på ulykkestype og vold fordelt efter region i perioden fra baseline og 4 år frem, N (% af ulykker i den enkelte region)

Total

(N = 69.755)

Alle ulykker (ekskl. vold)

Faldulykker

Køretøjsulykker

Cykelulykker

Knallertulykker

Bilulykker

Andet transportmiddel

Sportsulykker

Arbejdsulykker

Ikke kategoriseret*

Vold

28.019

6.823

2.633

1.138

123

1.181

6.786

2.444

11.828

(%)

(100)

(24)

(9)

(4)

(0)

(4)

(0)

(24)

(9)

(42)

Hovedstaden

(N = 21.524)

9.615

2.318

781

409

274

2.119

757

4.388

(%)

(100)

(24)

(8)

(4)

(0)

(3)

(0)

(22)

(8)

(46)

Sjælland

(N =10.987)

5.692

1.173

448

152

244

1.077

591

2.743

(%)

(100)

(21)

(8)

(3)

(0)

(4)

(0)

(19)

(10)

(48)

Syddanmark

(N = 14.459)

6.532

1.634

755

323

351

1.706

645

2.487

(%)

(100)

(25)

(12)

(5)

(1)

(5)

(0)

(26)

(10)

(38)

Midtjylland

(N = 15.243)

3.957

1.048

446

189

211

1.103

300

1.473

(%)

(100)

(26)

(11)

(5)

(1)

(5)

(0)

(28)

(8)

(37)

Nordjylland

(N = 7.542)

2.223

650

203

101

781

151

737

(%)

(100)

(29)

(9)

(3)

(1)

(5)

(0)

(35)

(7)

(33)

207

910

418

180

Kategorierne er ikke gensidigt udelukkende, og tallene kan ikke summeres

*Ikke kategoriserede ulykker består blandt andet af følgende type af ulykker: Leg/fritidsaktivitet, huslige aktiviteter, ulykker i hjemmet, m.v.

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ALKOHOL OG ULYKKER BLANDT UNGE

4.4 Ulykker pr. person regionsfordelt

Tabel 4.4 giver et overblik over, hvor mange ulykker der i gennemsnit er forekommet pr. person i de

enkelte regioner, samlet og fordelt på køn. Det gennemsnitlige antal ulykker pr. person er højest i

Region Sjælland efterfulgt af Region Hovedstaden og Region Syddanmark. Det samme regionale

mønster gør sig gældende når resultaterne opdeles efter køn, dog med en højere forekomst blandt

drenge end blandt piger.

Tabel 4.4

Fordeling af antal ulykke i de første 4 år efter baseline pr. person efter region (gennemsnit)

Total

(N = 69.755)

Antal

personer

ulykker

69.755

28.019

21.524

10.987

14.459

15.243

7.542

9.615

5.692

6.532

3.957

2.223

Drenge

(N =28.359)

Gns.

0,40

0,45

0,52

0,45

0,26

0,29

Gns.

0,48

0,53

0,61

0,53

0,31

0,35

Piger

(N = 41.396)

Gns.

0,35

0,38

0,46

0,39

0,23

0,26

Hele Landet

Hovedstaden

Sjælland

Syddanmark

Midtjylland

Nordjylland

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ALKOHOL OG ULYKKER BLANDT UNGE

5. Sammenhæng mellem

alkoholforbrug og ulykker

Dette afsnit indeholder resultater fra analysen af forskellen i risikoen for ulykker mellem grupper

med forskelligt indtag af alkohol. Analyserne er alle opdelt efter frekvens, mængde og indtag ved

sidste fest. Der ses på forskelle i hele populationen, fordelt på køn og region, samt forskelle i

risikoen for en række udvalgte ulykkestyper (køretøjsulykker, faldulykker, sportsulykker) og

voldsepisoder.

5.1 Alle ulykker

I tabel 5.1 ses risiko for ulykker fordelt efter henholdsvis ugentligt alkoholforbrug, hyppighed af

binge-drinking og alkoholindtag ved sidste fest. I alle analyser sammenlignes der med risiko for

ulykker i referencegrupperne der henholdsvis havde angivet at de indtog 0 genstande ugentligt,

havde binge-drukket 0 gange inden for de seneste 30 dage og havde angivet at de indtog 0

genstande til den sidste fest.

For at undersøge om sammenhængen mellem alkoholforbrug og ulykker bliver påvirket af andre

faktorer, justeres analysen ad to omgange. I den indledende analyse er der justeret for alder, køn,

ungdomsuddannelse, forældres uddannelse og etnicitet. Disse resultater fremgår af i kolonnen

med HR

. I den udvidede analyse er der lavet en yderligere justering for brug af cannabis, brug af

stoffer, rygning, betydning af karakter og deltagelse i gymnasiefest. Disse resultater fremgår af

kolonnen med HR

Ud fra resultaterne i tabel 5.1 ses det, at risikoen for ulykker er højere for grupperne der har

angivet at de har et højt ugentligt indtag af alkohol, har binge-drukket hyppigere de seneste 30

dage og indtaget flere genstande ved sidste fest i forhold til gruppen som har angivet at de har et

lavt ugentligt indtag, har binge-drukket 0 gange inden for de seneste 30 dage og indtog 0

genstande ved sidste fest, når der blev tages højde for forskelle i alder, køn, ungdomsuddannelse,

forældres uddannelse og etnicitet. Forskellen i risiko for ulykker, mellem grupperne med højt

alkoholindtag og grupperne med lavt alkoholindtag, er mindre når der ydermere tages højde for

forskelle i brug af cannabis og stoffer, rygning, betydning af gymnasiekarakter og deltagelse i fest.

Der ses en dosis-respons-sammenhæng mellem ugentligt alkoholindtag og ulykker, hvor den

højeste risiko for at opleve ulykke er i gruppen som har angivet at de drikker over 27 genstande pr.

uge når de sammenlignes med gruppen som har angivet at de indtager 0 genstande pr. uge

(Hazard Ratio (HR: 1,37). Gruppen som har angivet at de indtager over 27 genstande pr. uge, har

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ALKOHOL OG ULYKKER BLANDT UNGE

dermed 37 % flere ulykker i forhold til gruppen, med et ugentligt alkoholindtag på 0 genstande,

over en given tidsperiode.

Ligeledes ses den højeste risiko for ulykker blandt de, som har angivet at de har binge-drukket

mere end 6 gange indenfor de seneste 30 dage sammenlignet med dem som har angivet at de har

binge-drukket 0 gange (HR: 1,28). For indtag af genstande ved sidste fest er mønstret det samme.

Her ses den højeste risiko i gruppen, som har angivet at de indtog over 16 genstande ved sidste

fest sammenlignet med gruppen som har angivet at de indtog 0 genstande (HR: 1,13). Gruppen,

der har angivet at de slet ikke drikker, har den laveste risiko for ulykker sammenlignet med

referencegruppen (HR: 0,73).

Tabel 5.1

HR (95 % konfidensinterval) for ulykke i de første 4 år efter baseline i forhold til alkoholforbrug

Antal

Personer

ulykker

[95 %CI]

Ugentligt alkoholforbrug

N = 68.126

N = 62.406

Drikker ikke

0 genstande

1-7 genstande

8-13 genstande

14-20 genstande

21-27 genstande

>27 genstande

Binge-drinking (seneste 30 dage)

Drikker ikke

0 gange

1 gang

2-3 gange

4-6 gange

>6 gange

Genstande indtaget ved sidste fest

Drikker ikke

Aldrig deltaget i fest

0 genstande

1-2 genstande

3-9 genstande

10-15 genstande

16+ genstande

Justeret

4.990

6.746

20.548

16.121

11.343

4.124

5.055

4.990

7.794

11.534

23.213

14.817

4.522

4.990

2.809

2.262

3.812

27.629

19.260

5.842

1.144

1.860

5.159

4.242

3.351

1.388

1.996

N = 66.113

1.144

1.996

2.944

6.368

4.418

1.600

N = 65.848

1.144

801

655

934

6.729

5.627

2.076

0,84 [0,78;0,91]

1,00 (REF)

0,98 [0,93;1,04]

1,04 [0,99;1,10]

1,16 [1,09;1,23]

1,30 [1,21;1,40]

1,50 [1,41;1,60]

N = 60.839

0,88 [0,81;0,95]

1,00 (REF)

1,02 [0,96;1,08]

1,12 [1,07;1,18]

1,23 [1,17;1,30]

1,45 [1,36;1,55]

N = 62.964

0,72 [0,65;0,80]

0,90 [0,81;1,00]

1,00 (REF)

0,84 [0,75;0,92]

0,83 [0,76;0,90]

0,99 [0,91;1,08]

1,21 [1,11;1,33]

0,85 [0,78;0,93]

1,00 (REF)

0,96 [0,90;1,02]

0,99 [0,93;1,06]

1,09 [1,02;1,16]

1,20 [1,11;1,30]

1,37 [1,27;1,48]

N = 60.839

0,91 [0,83;0,99]

1,00 (REF)

1,02 [0,95;1,08]

1,09 [1,03;1,15]

1,14 [1,07;1,21]

1,28 [1,18;1,38]

N = 62.964

0,73 [0,66;0,81]

0,87 [0,78;0,98]

1,00 (REF)

0,83 [0,75;0,93]

0,81 [0,74;0,88]

0,95 [0,87;1,03]

1,13 [1,03;1,24]

Justeret for alder, køn, ungdomsuddannelse, forældres uddannelse, etnicitet

for alder, køn, ungdomsuddannelse, forældres uddannelse, etnicitet, brug af cannabis, brug af

stoffer, rygning, betydning af karakter og gymnasiefest

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALKOHOL OG ULYKKER BLANDT UNGE

5.2 Kønsspecifikke risici

I tabel 5.2 ses resultaterne fra analysen af risiko for at komme ud for en ulykke, opdelt på køn. For

begge køn ses der en dosis-respons-sammenhæng mellem indtag af alkohol i frekvens og

mængde og risiko for at opleve en ulykke. Det fremgår at risikoen for at opleve en ulykke er større

for dem der har angivet at de indtager over 27 genstande pr. uge, dem som har angivet at de har

binge-drukket mere end 6 gange de seneste 30 dage, og dem som har angivet at de indtog mere

end 16 genstande ved sidste fest sammenlignet med grupperne som har angivet et ugentligt

alkoholindtag på 0 genstande, 0 gange binge-drinking og 0 genstande indtaget ved sidste fest.

Generelt er forskellen i risikoen for ulykker mellem grupperne med forskelligt alkoholforbrug mindre

i den fulde justering, når der tages højde for forskelle mellem gruppernes brug af cannabis og

stoffer, rygning, betydningen af gymnasiekarakter og deltagelse i gymnasiefest.

For både drenge og piger gælder det at de som har angivet, at de indtager 27 genstande om ugen,

har en højere risiko for ulykker end de som har angivet et ugentligt alkoholindtag på 0 genstande

(HR

Drenge

= 1,38, HR

Piger

= 1,37). Risikoen er ligeledes højere i gruppen som har angivet at de

indtager 21-27 genstande om ugen sammenlignet med gruppen, som har angivet at de indtager 0

genstande. Her ses det, at den relative forskel var større blandt piger (HR = 1,29) end blandt

drenge (HR = 1,14). Blandt piger er risikoen for ulykker lavere blandt dem, som har angivet at de

ikke drikker, i forhold til referencegruppen (HR = 0,84), hvorimod der ikke ses nogen forskel blandt

drenge.

Blandt drenge ses der en højere risiko for ulykker blandt drenge, som har angivet at de har binge-

drukket 4-6 gange og mere end 6 gange inden for de seneste 30 dage, i forhold til drenge, som har

angivet at de har binge-drukket 0 gange inde for de seneste 30 dage. For piger ses der en øget

risiko for ulykker blandt de som har angivet at de har binge-drukket mere end 6 gange inden for de

seneste 30 dage i forhold til piger, som har angivet at de har binge-drukket 0 gange (HR = 1,22).

For drenge er risikoen for ulykker signifikant lavere for de som har angivet at de indtog 1-9

genstande ved sidste fest sammenlignet med drenge, som har angivet at de indtog 0 genstande.

For piger ses der en højere risiko for ulykke i gruppen af piger som har angivet at de indtog over 16

genstande ved sidste fest i forhold til gruppen, som har angivet at de indtog 0 genstande (HR =

1,26).

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALKOHOL OG ULYKKER BLANDT UNGE

Tabel 5.2

HR (95 % konfidensinterval) for ulykke i de første 4 år efter baseline i forhold til alkoholforbrug fordelt efter køn

Drenge

Ugentligt alkoholforbrug

Drikker ikke

0 genstande

1-7 genstande

8-13 genstande

14-20 genstande

21-27 genstande

>27 genstande

Drikker ikke

0 gange

1 gang

2-3 gange

4-6 gange

>6 gange

Drikker ikke

Aldrig deltaget i fest

0 genstande

1-2 genstande

3-9 genstande

10-15 genstande

16+ genstande

Justeret

Piger

HR [95 %CI]

N = 23.845

0,91 [0,80;1,04]

1,00 (REF)

0,95 [0,87;1,05]

1,01 [0,92;1,11]

1,09 [0,99;1,20]

1,14 [1,02;1,28]

1,38 [1,24;1,53]

N = 23.176

1,03 [0,90;1,18]

1,00 (REF)

1,07 [0,96;1,19]

1,20 [1,09;1,32]

1,29 [1,17;1,43]

1,40 [1,25;1,58]

N = 24.116

0,68 [0,59;0,80]

0,73 [0,62;0,86]

1,00 (REF)

0,68 [0,57;0,80]

0,72 [0,63;0,81]

0,83 [0,74;0,94]

1,00 [0,88;1,14]

524

349

311

286

2.258

2.838

1.389

524

798

1.180

2.748

2.327

996

524

949

1.925

1.674

805

1.385

HR [95 %CI]

N = 40.558

0,84 [0,75;0,94]

1,00 (REF)

0,98 [0,91;1,06]

1,02 [0,95;1,11]

1,15 [1,06;1,25]

1,41 [1,27;1,57]

1,51 [1,36;1,68]

N = 39.521

0,85 [0,77;0,95]

1,00 (REF)

1,0 [0,93;1,08]

1,06 [0,99;1,13]

1,15 [1,07;1,23]

1,38 [1,25;1,53]

N = 40.194

0,78 [0,68;0,90]

1,01 [0,88;1,17]

1,00 (REF)

0,95 [0,83;1,08]

0,90 [0,81;1,01]

1,08 [0,97;1,21]

1,34 [1,17;1,53]

HR [95 %CI]

N = 38.561

0,84 [0,74;0,94]

1,00 (REF)

0,96 [0,89;1,04]

0,98 [0,90;1,07]

1,08 [0,99;1,18]

1,29 [1,16;1,45]

1,37 [1,22;1,53]

N = 37.663

0,86 [0,77;0,97]

1,00 (REF)

0,98 [0,91;1,06]

1,02 [0,95;1,10]

1,04 [0,96;1,13]

1,22 [1,09;1,36]

N = 38.848

0,81 [0,70;0,93]

1,01 [0,86;1,17]

1,00 (REF)

0,96 [0,84;1,10]

0,89 [0,80;1,00]

1,05 [0,93;1,18]

1,26 [1,10;1,44]

HR [95 %CI]

N = 27.568

620

911

3.234

2.568

1.677

583

611

620

1.198

1.764

3.620

2.091

604

620

452

344

648

4.471

2.789

687

0,88 [0,79;0,98]

1,00 (REF)

0,98 [0,90;1,06]

1,07 [0,98;1,16]

1,17 [1,07;1,27]

1,24 [1,13;1,36]

1,51 [1,39;1,64]

N = 26.592

0,96 [0,86;1,08]

1,00 (REF)

1,05 [0,96;1,15]

1,22 [1,12;1,32]

1,35 [1,24;1,47]

1,55 [1,41;1,71]

N = 25.654

0,69 [0,60;0,80]

0,79 [0,68;0,92]

1,00 (REF)

0,69 [0,59;0,81]

0,74 [0,66;0,84]

0,89 [0,79;1,00]

1,09 [0,96;1,24]

Binge-drinking (de seneste 30 dage)

Genstande indtaget ved sidste fest

for alder, ungdomsuddannelse, forældres uddannelse, etnicitet

for alder, ungdomsuddannelse, forældres uddannelse, etnicitet, brug af cannabis, brug af stoffer, rygning, betydning af karakter og deltagelse i

gymnasiefest

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ALKOHOL OG ULYKKER BLANDT UNGE

5.3 Regionsspecifikke risici

I tabel 5.3 ses resultater fra analysen af risiko for ulykker opdelt på regioner.

Fordelt på regioner er resultaterne for sammenhængen mellem ugentligt alkoholindtag og

hyppighed af binge-drinking de samme som for hele populationen. I alle 5 regioner er der en øget

risiko for ulykker blandt personer som har angivet at de drikker over 21 genstande pr. uge, når de

sammenlignes med gruppen som har angivet at de drikker 0 genstande pr. uge. Risikoen for

ulykker er størst blandt dem, som har angivet at de drikker over 27 genstande ugentligt, i alle 5

regioner.

For binge-drinking gælder det, at de som har angivet, at de har binge-drukket mere end 2 gange

inden for de seneste 30, har en højere risiko for at komme ud for en ulykke i 4 ud af 5 regioner, når

de sammenlignes med gruppen som har angivet at de har binge-drukket 0 gange de seneste 30

dage. I alle regioner ses den største risiko blandt de, som har angivet at de har binge-drukket over

6 gange de seneste 30 dage, i forhold til de, som har angivet at de har binge-drukket 0 gange.

For antal genstande indtaget til sidste fest ses der kun en signifikant forskel i Region Sjælland,

hvor gruppen, som har angivet at de indtog 16+ genstande ved den sidste fest, har en højere risiko

for ulykker sammenlignet med gruppen, som har angivet at de indtog 0 genstande (HR = 1,21).

Når den statistiske usikkerhed medtages, er risikoen for ulykker over en given tidsperiode blandt

gruppen, som har indtaget 16+ genstande, mellem 3 % og 44 % højere end i gruppen, som har

indtaget 0 genstande.

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALKOHOL OG ULYKKER BLANDT UNGE

Tabel 5.3

HR (95 % konfidensinterval) for ulykke i de første 4 år efter baseline i forhold til alkoholforbrug fordelt efter region

Hovedstaden

(N = 21.524)

Ugentligt alkoholforbrug

Drikker ikke

0 genstande

1-7 genstande

8-13 genstande

14-20 genstande

21-27 genstande

>27 genstande

Drikker ikke

0 gange

1 gang

2-3 gange

4-6 gange

>6 gange

Drikker ikke

Aldrig deltaget i fest

0 genstande

1-2 genstande

3-9 genstande

10-15 genstande

16+ genstande

534

581

1.573

1.486

1.225

501

635

HR [95 %CI]

N=18.346

0,82 [0,71;0,95]

1,00 (REF)

0,89 [0,79;0,99]

0,95 [0,85;1,06]

1,08 [0,96;1,22]

1,19 [1,04;1,38]

1,26 [1,10;1,45]

N = 17.866

0,92 [0,80;1,06]

1,00 (REF)

0,99 [0,88;1,11]

1,08 [0,97;1,19]

1,16 [1,04;1,29]

1,26 [1,10;1,43]

N = 18.506

0,84 [0,71;0,99]

1,01 [0,82;1,24]

1,00 (REF)

0,72 [0,57;0,91]

0,69 [0,58;0,83]

0,84 [0,70;1,01]

150

127

138

156

1.129

1.086

150

391

577

1.254

737

275

135

276

860

693

519

219

321

Sjælland

(N =10.987)

HR [95 %CI]

N = 9.822

0,74 [0,59;0,94]

1,00 (REF)

0,93 [0,80;1,08]

0,94 [0,80;1,09]

1,04 [0,88;1,22]

1,09 [0,89;1,33]

1,42 [1,17;1,71]

N = 9.535

0,84 [0,66;1,05]

1,00 (REF)

0,99 [0,84;1,16]

1,19 [1,03;1,38]

1,19 [1,02;1,39]

1,46 [1,19;1,79]

N = 9.926

0,74 [0,58;0,94]

1,03 [0,80;1,31]

1,00 (REF)

0,97 [0,82;1,16]

0,94 [0,82;1,08]

1,09 [0,94;1,26]

278

192

152

224

1.496

1.237

278

505

784

1.484

912

262

278

438

1.310

915

710

291

411

Syddanmark

(N = 14.459)

HR [95 %CI]

N = 13.039

0,95 [0,79;1,13]

1,00 (REF)

1,05 [0,93;1,18]

1,05 [0,93;1,20]

1,14 [1,0;1,31]

1,24 [1,05;1,48]

1,45 [1,24;1,70]

N = 12.684

0,93 [0,78;1,11]

1,00 (REF)

1,09 [0,96;1,23]

1,04 [0,93;1,17]

1,11 [0,98;1,26]

1,13 [0,95;1,35]

N = 13.151

0,83 [0,67;1,03]

1,08 [0,86;1,34]

1,00 (REF)

0,83 [0,68;1,03]

0,83 [0,70;0,99]

0,96 [0,80;1,14]

135

132

124

979

1.010

135

288

471

1.107

704

233

135

276

860

693

519

219

321

Midtjylland

(N = 15.243)

HR [95 %CI]

N = 14.180

0,74 [0,59;0,94]

1,00 (REF)

0,93 [0,80;1,08]

0,94 [0,80;1,09]

1,04 [0,88;1,22]

1,09 [0,89;1,33]

1,42 [1,17;1,71]

N = 13.874

0,84 [0,66;1,05]

1,00 (REF)

0,99 [0,84;1,16]

1,19 [1,03;1,38]

1,19 [1,02;1,39]

1,46 [1,19;1,79]

N = 14.282

0,65 [0,49;0,87]

0,87 [0,65;1,15]

1,00 (REF)

0,79 [0,59;1,05]

0,78 [0,62;0,98]

1,02 [0,81;1,29]

509

586

171

278

625

342

118

160

465

378

303

165

Nordjylland

(N = 7.542)

HR [95 %CI]

N = 7.019

0,70 [0,48;1,01]

1,00 (REF)

1,06 [0,87;1,29]

1,13 [0,92;1,38]

1,18 [0,96;1,47]

1,15 [0,87;1,51]

1,53 [1,20;1,96]

N = 6.880

0,77 [0,53;1,12]

1,00 (REF)

1,18 [0,96;1,46]

1,24 [1,03;1,51]

1,31 [1,06;1,61]

1,56 [1,19;2,04]

N = 7.099

0,59 [0,38;0,91]

0,87 [0,60;1,28]

1,00 (REF)

0,77 [0,53;1,14]

0,82 [0,61;1,12]

1,04 [0,76;1,41]

Binge-drinking (de seneste 30 dage)

534

641

834

1.898

1.723

712

534

280

235

366

2.616

1.708

528

Genstande indtaget ved sidste fest

1,02 [0,84;1,24]

509

1,21 [1,03;1,44]

458

1,19 [0,98;1,45]

375

1,27 [0,99;1,63]

206

1,22 [0,88;1,70]

Justeret for alder, ungdomsuddannelse, forældres uddannelse, etnicitet

Justeret for alder, ungdomsuddannelse, forældres uddannelse, etnicitet, brug af cannabis, brug af stoffer, rygning, betydning af karakter og deltagelse i gymnasiefest

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALKOHOL OG ULYKKER BLANDT UNGE

5.4 Køretøjsulykker

I tabel 5.4 ses resultater fra analysen af risiko for køretøjsulykker fordelt efter ugentligt

alkoholforbrug, hyppighed af binge-drinking og antal genstande indtaget ved sidste fest.

Der ses indledningsvis en sammenhæng mellem ugentligt alkoholforbrug og hyppighed af binge-

drinking og køretøjsulykker, denne sammenhæng forsvinder dog, når der tages højde for forskelle i

brug af cannabis og stoffer, rygning, betydning af gymnasiekarakter og deltagelse i gymnasiefest.

For antal genstande indtaget til sidste fest er der ingen sammenhæng med køretøjsulykker.

Tabel 5.4

Sammenhæng mellem alkoholforbrug og HR (95 % konfidensinterval) for køretøjsulykker i de

første 4 år efter baseline

Antal

køretøjsulykker

[95 %CI]

Ugentligt alkoholforbrug

N = 68.126

N = 62.406

Drikker ikke

0 genstande

1-7 genstande

8-13 genstande

14-20 genstande

21-27 genstande

>27 genstande

Binge-drinking (de seneste 30 dage)

Drikker ikke

0 gange

1 gang

2-3 gange

4-6 gange

>6 gange

Antal genstande indtaget ved sidste fest

Drikker ikke

Aldrig deltaget i fest

0 genstande

1-2 genstande

3-9 genstande

10-15 genstande

16+ genstande

Justeret

165

250

687

574

411

166

230

165

265

410

789

565

194

165

104

142

895

668

213

0,96 [0,77;1,18]

1,00 (REF)

1,02 [0,88;1,19]

1,11 [0,95;1,30]

1,11 [0,94;1,30]

1,18 [0,96;1,44]

1,25 [1,04;1,50]

N = 66.113

1,02 [0,83;1,26]

1,00 (REF)

1,09 [0,93;1,27]

1,07 [0,93;1,23]

1,21 [1,04;1,40]

1,31 [1,09;1,58]

N = 65.848

0,83 [0,63;1,09]

0,90 [0,68;1,21]

1,00 (REF)

0,99 [0,75;1,29]

0,86 [0,69;1,08]

0,91 [0,73;1,14]

0,94 [0,73;1,21]

1,02 [0,86;1,21]

1,00 (REF)

0,99 [0,84;1,17]

1,02 [0,86;1,21]

1,0 [0,84;1,21]

1,05 [0,84;1,33]

1,04 [0,84;1,30]

N = 60.839

1,17 [0,93;1,48]

1,00 (REF)

1,16 [0,97;1,37]

1,08 [0,92;1,27]

1,15 [0,97;1,37]

1,11 [0,88;1,39]

N = 62.964

0,89 [0,67;1,18]

0,85 [0,62;1,16]

1,00 (REF)

0,98 [0,74;1,29]

0,84 [0,66;1,05]

0,87 [0,68;1,10]

0,86 [0,66;1,12]

for alder, køn, ungdomsuddannelse, forældres uddannelse, etnicitet

for alder, køn, ungdomsuddannelse, forældres uddannelse, etnicitet, brug af cannabis, brug af

stoffer, rygning, betydning af karakter og deltagelse i gymnasiefest

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALKOHOL OG ULYKKER BLANDT UNGE

5.5 Faldulykker

I tabel 5.5 ses resultater fra analysen af risiko for faldulykker fordelt efter ugentligt alkoholforbrug,

hyppighed af binge-drinking og antal genstande indtaget ved sidste fest.

Risikoen for faldulykker er større blandt personer, som har angivet at de drikker over 14 genstande

ugentligt, når de sammenlignes med personer som har angivet et at de indtager 0 genstande

ugentligt. Den største risiko ses i gruppen, som har angivet at de drikker over 27 genstande om

ugen (HR = 1,40). Ligeledes er risikoen for faldulykker højere i grupperne som har angivet at de

har binge-drukket 1 gang eller mere inden for de seneste 30 dage når de sammenlignes med

gruppen, som har angivet at de har binge-drukket 0 gange. Den største risiko ses i gruppen, som

har angivet at de har binge-drukket 6 gange eller mere inden for de seneste 30 dage (HR = 1,49). I

forhold til antal genstande indtaget ved sidste fest er der en større risiko blandt dem, som har

angivet at de indtog over 16 genstande ved sidste fest, når de sammenlignes med dem, som har

angivet at de indtog 0 genstande ved sidste fest (HR = 1,27).

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALKOHOL OG ULYKKER BLANDT UNGE

Tabel 5.5

HR (95 % konfidensinterval) for faldulykke i de første 4 år efter baseline i forhold til

alkoholforbrug

Antal

faldulykker

[95 %CI]

Ugentligt alkoholforbrug

Drikker ikke

0 genstande

1-7 genstande

8-13 genstande

14-20 genstande

21-27 genstande

>27 genstande

Binge-drinking (de seneste 30 dage)

Drikker ikke

0 gange

1 gang

2-3 gange

4-6 gange

>6 gange

Antal genstande indtaget ved sidste fest

Drikker ikke

Aldrig deltaget i fest

0 genstande

1-2 genstande

3-9 genstande

10-15 genstande

16+ genstande

Justeret

N = 68.126

258

409

1298

1152

922

362

434

0,87 [0,75;1,0]

1,00 (REF)

1,02 [0,92;1,13]

1,12 [1,01;1,25]

1,33 [1,20;1,48]

1,43 [1,26;1,62]

1,52 [1,35;1,72]

N = 66.113

258

454

741

1666

1185

409

0,94 [0,84;1,06]

1,00 (REF)

1,04 [0,95;1,14]

1,13 [1,04;1,22]

1,24 [1,14;1,34]

1,40 [1,27;1,56]

N = 65.848

258

201

128

197

1882

1500

475

0,80 [0,66;0,97]

1,13 [0,93;1,38]

1,00 (REF)

0,83 [0,68;1,0]

1,01 [0,87;1,19]

1,21 [1,04;1,42]

1,37 [1,16;1,63]

N = 62.406

0,85 [0,72;1,0]

1,00 (REF)

1,01 [0,91;1,13]

1,09 [0,97;1,22]

1,25 [1,11;1,41]

1,34 [1,16;1,55]

1,40 [1,22;1,61]

N = 60.839

0,91 [0,77;1,07]

1,00 (REF)

1,13 [1,01;1,27]

1,23 [1,11;1,36]

1,33 [1,19;1,49]

1,49 [1,30;1,71]

N = 62.964

0,81 [0,67;1,0]

1,12 [0,92;1,38]

1,00 (REF)

0,83 [0,68;1,01]

0,99 [0,84;1,16]

1,15 [0,97;1,35]

1,27 [1,06;1,51]

for alder, køn, ungdomsuddannelse, forældres uddannelse, etnicitet

for alder, køn, ungdomsuddannelse, forældres uddannelse, etnicitet, brug af cannabis, brug af

stoffer, rygning, betydning af karakter og deltagelse i gymnasiefest

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ALKOHOL OG ULYKKER BLANDT UNGE

5.6 Sportsulykker

I tabel 5.6 ses resultater fra analysen af risiko for sportsulykker fordelt efter ugentligt

alkoholforbrug, hyppighed af binge-drinking og antal genstande indtaget ved sidste fest.

Der ses ikke nogen forskel i risikoen for sportsulykker mellem gruppen, som har angivet at de

drikker 0 genstande ugentligt, og gruppen, som har angivet at de drikker over 27 genstande

ugentligt. Risikoen for sportsulykker er lavere for grupperne som har angivet at de drikker

henholdsvis 1-7 genstande og 8-13 genstande om ugen (HR

1-7 genstande

: 0,81; HR

8-13 genstande

: 0,82),

når de sammenlignes med gruppen, som har angivet at de drikker 0 genstande om ugen.

Ligeledes ses der en lavere risiko i gruppen, som har angivet at de ikke drikker (HR = 0,71).

I forhold til hyppighed af binge-drinking inden for de seneste 30 dage ses der ingen forskel i risiko

for sportsulykker mellem gruppen, som har angivet at de har binge-drukket 0 gange inden for de

seneste 30 dage, og gruppen, som har angivet at de har binge-drukket 6 gange. Risikoen for

sportsulykker er lidt højere blandt dem, som har angivet at de har binge-drukket 2-3 gange inden

for de seneste 30 dage, i forhold til gruppen, som har angivet at de har binge-drukket 0 gange (HR

= 1,11).

I forhold til antal genstande indtaget ved sidste fest ses der en lavere risiko for dem, som har

angivet at de ikke drikker, og grupperne, som har angivet at de indtog mellem 1-15 genstande, når

de sammenlignes med gruppen, som har angivet at de indtog 0 genstande ved sidste fest. For

gruppen, som har angivet at de indtog 16 eller flere genstande til sidste fest, ses der ingen

signifikant forskel i risiko for ulykker, når der sammenlignes med gruppen som har angivet at de

drak 0 genstande ved sidste fest.

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALKOHOL OG ULYKKER BLANDT UNGE

Tabel 5.6

HR (95 % konfidensinterval) for sportsulykke i de første 4 år efter baseline i forhold til

alkoholforbrug

Antal

sportsulykker

[95 %CI]

Ugentligt alkoholforbrug

N = 68.126

N = 62.406

Drikker ikke

0 genstande

1-7 genstande

8-13 genstande

14-20 genstande

21-27 genstande

>27 genstande

Binge-drinking (de seneste 30 dage)

Drikker ikke

0 gange

1 gang

2-3 gange

4-6 gange

>6 gange

Antal genstande indtaget ved sidste fest

Drikker ikke

Aldrig deltaget i fest

0 genstande

1-2 genstande

3-9 genstande

10-15 genstande

16+ genstande

Justeret

284

203

234

1570

1428

546

284

505

776

1577

972

301

284

203

234

1570

1428

546

0,74 [0,65;0,85]

1,00 (REF)

0,81 [0,73;0,89]

0,81 [0,73;0,90]

0,88 [0,79;0,99]

0,97 [0,84;1,12]

1,11 [0,97;1,27]

N = 66.113

0,94 [0,83;1,06]

1,00 (REF)

0,98 [0,90;1,07]

0,99 [0,91;1,07]

0,95 [0,87;1,03]

0,94 [0,84;1,05]

N = 65.848

0,64 [0,54;0,76]

0,73 [0,61;0,88]

1,00 (REF)

0,70 [0,59;0,83]

0,63 [0,55;0,72]

0,74 [0,65;0,85]

0,90 [0,78;1,05]

0,71 [0,61;0,83]

1,00 (REF)

0,81 [0,72;0,91]

0,82 [0,73;0,92]

0,88 [0,78;1,00]

0,97 [0,84;1,13]

1,11 [0,96;1,28]

N = 60.839

0,90 [0,77;1,05]

1,00 (REF)

1,06 [0,95;1,19]

1,11 [1,00;1,23]

1,09 [0,98;1,22]

1,14 [0,98;1,32]

N = 62.964

0,61 [0,51;0,73]

0,75 [0,62;0,91]

1,00 (REF)

0,69 [0,58;0,83]

0,66 [0,58;0,76]

0,81 [0,71;0,94]

1,05 [0,90;1,22]

for alder, køn, ungdomsuddannelse, forældres uddannelse, etnicitet

for alder, køn, ungdomsuddannelse, forældres uddannelse, etnicitet, brug af cannabis, brug af

stoffer, rygning, betydning af karakter og deltagelse i gymnasiefest

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALKOHOL OG ULYKKER BLANDT UNGE

5.7 Voldsepisoder

I tabel 5.7 ses resultater fra analysen af risiko for voldsepisoder fordelt efter ugentligt

alkoholforbrug, hyppighed af binge-drinking og antal genstande indtaget ved sidste fest.

Når der tages højde for forskelle i alder, køn, ungdomsuddannelse, forældres uddannelse og

etnicitet ses der en højere risiko for voldsepisoder i grupperne, som har angivet at de indtager over

14 genstande om ugen når de sammenlignes med gruppen som har angivet at de indtager 0

genstande ugentligt. Når der ydermere tages højde for forskelle i brug af cannabis og stoffer,

rygning, betydning af karakter og deltagelse i gymnasiefest, forsvinder sammenhængen, og der

ses kun en øget risiko i gruppen, som har angivet at de indtager over 21 genstande om ugen (HR

= 1,46).

Når der tages høje for alle forskelle mellem grupperne, ses der for binge-drinking en øget risiko for

voldsepisoder for dem som har angivet at de har binge-drukket 4 gange eller mere inden for de

seneste 30 dage. Den største risiko for voldsepisoder ses i gruppen, som har angivet at de har

binge-drukket over 6 gange indenfor de seneste 30 dage, når de sammenlignes med gruppen,

som har angivet at de har binge-drukket 0 gange indenfor de seneste 30 dage (HR = 2,62).

For antal genstande indtaget ved sidste fest er risikoen lavere for gruppen som har angivet at de

indtog 1-9 genstande, sammenlignet med gruppen, som har angivet at de indtog 0 genstande. For

de øvrige grupper var der ikke nogen øget i risiko.

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ALKOHOL OG ULYKKER BLANDT UNGE

Tabel 5.7

HR (95 % konfidensinterval) for voldsepisode i de første 4 år efter baseline i forhold til

alkoholforbrug

Antal

voldsepisoder

[95 %CI]

Ugentligt alkoholforbrug

N = 68.126

N = 62.406

Drikker ikke

0,82 [0,57;1,18]

0,93 [0,60;1,45]

0 genstande

1-7 genstande

8-13 genstande

14-20 genstande

21-27 genstande

>27 genstande

Binge-drinking (de seneste 30 dage)

Drikker ikke

0 gange

1 gang

2-3 gange

4-6 gange

>6 gange

Antal genstande indtaget ved sidste fest

Drikker ikke

Aldrig deltaget i fest

0 genstande

1-2 genstande

3-9 genstande

10-15 genstande

16+ genstande

Justeret

150

124

163

103

154

229

208

141

203

247

126

1,00 (REF)

0,94 [0,71;1,25]

1,03 [0,77;1,39]

1,66 [1,26;2,20]

2,51 [1,85;3,41]

2,49 [1,88;3,30]

N = 66.113

0,95 [0,79;1,15]

1,00 (REF)

0,97 [0,84;1,11]

1,0 [0,88;1,13]

1,08 [0,94;1,23]

1,42 [1,21;1,67]

N = 65.848

0,56 [0,35;0,89]

0,98 [0,60;1,59]

1,00 (REF)

0,60 [0,35;1,02]

0,72 [0,49;1,06]

1,03 [0,70;1,51]

1,39 [0,93;2,08]

1,00 (REF)

0,83 [0,59;1,16]

0,78 [0,55;1,11]

1,10 [0,78;1,54]

1,46 [1,01;2,12]

1,40 [0,98;1,99]

N = 60.839

1,38 [0,85;2,25]

1,00 (REF)

1,16 [0,77;1,76]

1,34 [0,92;1,95]

1,49 [1,02;2,19]

2,62 [1,75;3,93]

N = 62.964

0,66 [0,40;1,07]

0,66 [0,39;1,13]

1,00 (REF)

0,57 [0,33;0,98]

0,56 [0,38;0,84]

0,68 [0,46;1,01]

0,76 [0,50;1,16]

for alder, køn, ungdomsuddannelse, forældres uddannelse, etnicitet

for alder, køn, ungdomsuddannelse, forældres uddannelse, etnicitet, brug af cannabis, brug af

stoffer, rygning, betydning af karakter og deltagelse i gymnasiefest

SUU, Alm.del - 2020-21 - Bilag 102: Henvendelse af 17/11-20 fra Drukfri Ungdom vedr. foretræde om ny 18-årsgrænse for salg af al alkohol

ALKOHOL OG ULYKKER BLANDT UNGE

6. Diskussion

Den første del af rapportens resultater viser fordelingen af ulykker på populationen af deltagere i

Ungdomsprofilen 2014 mellem 15-20 år. Over perioden fra besvarelse af spørgeskemaet og 4 år

frem forekom der 28.019 ulykker blandt de 69.755 personer. Fordelt på kategorier er fald- og

sportsulykker de hyppigste, mens en mindre andel udgøres af køretøjsulykker og arbejdsulykker.

Godt 40 % af ulykkerne falder uden for de anvendte kategorier.

Fordelt efter alkoholforbrug er det gennemsnitlige antal ulykker pr. person højest blandt grupperne

med et højt ugentligt alkoholindtag, hyppig binge-drinking og et højt antal genstande indtaget til

sidste fest, og både alkoholforbruget og forekomsten af ulykker er højere blandt drenge end blandt

piger.

For antal genstande indtaget til sidste fest ses der desuden et højere antal ulykker i gruppen, som

har drukket 0 genstande, og gruppen, som ikke gik til fest, i forhold til grupperne som aldrig drikker

og grupperne som indtog 1-15 genstande ved sidste fest.

Fordelt efter regioner er det gennemsnitlige antal ulykker pr. person højest i Region Sjælland og

lavest i Region Nordjylland og Region Midtjylland. Denne forskel kan skyldes regionale forskelle i

håndteringen af ulykker, hvor ulykker i Region Nordjylland og Region Midtjylland hyppigere

behandles på skadeklinikker, da afstanden til et hospital er længere i disse regioner (37). Disse

ulykker indgår ikke i denne undersøgelse, som er afgrænset til ulykker, der indebærer

hospitalskontakt.

Den anden del af rapportens resultater omhandler sammenhængen mellem alkoholforbrug og

ulykker. Her sammenlignes risikoen for ulykke mellem grupper med henholdsvis højt og lavt

alkoholindtag. Resultaterne viser, at der er en større risiko for ulykker ved højt indtag af alkohol i

forhold til lavt indtag. Blandt elever med et højt ugentligt indtag af alkohol er risikoen for ulykker

større sammenlignet med elever med et ugentligt alkoholindtag på 0 genstande. Det samme

gælder hyppighed af binge-drinking og alkoholindtag ved fest, hvor der ses en højere risiko for

ulykker ved hyppig binge-drinking og et højt antal genstande ved fest i forhold til ingen binge-

drinking og 0 genstande indtaget til sidste fest. Højt ugentligt alkoholindtag og hyppig binge-

drinking er forbundet med en højere risiko for at komme ud for en ulykke blandt både drenge og

piger, når det sammenlignes med lavt ugentligt alkoholindtag og ingen binge-drinking. For antal

genstande indtaget til sidste fest er der kun sammenhæng med ulykker blandt drenge, hvilket kan

skyldes den tidligere nævnte, usikkerhed ved dette mål.

Fordelt på regioner er der ligeledes en øget risiko for ulykker ved et højt ugentligt alkoholindtag og

hyppig binge-drinking når der sammenlignes med grupper med et ugentligt alkoholindtag på 0

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ALKOHOL OG ULYKKER BLANDT UNGE

genstande og ingen binge-drinking. Der ses kun få regionale forskelle. For antal genstande

indtaget til sidste fest er der kun en signifikant højere risiko for ulykker for gruppen, som har

indtaget 16+ genstande, i forhold til gruppen, som har indtaget 0 genstande, i Region Sjælland,

mens der ikke ses nogen forskel i de øvrige regioner, når der blev tages højde for forskelle mellem

grupperne.

Foruden ulykker generelt ser rapporten på fire specifikke typer af ulykker. Her viser resultaterne for

faldulykker, at der er en højere risiko for faldulykker i grupperne med et højt ugentligt alkoholindtag

(>14 genstande) i forhold til gruppen med et ugentligt alkoholindtag på 0 genstande. Mønstret er

det samme for hyppighed af binge-drinking og antal genstande indtaget ved sidste fest, hvor

risikoen for faldulykker er højere i grupperne med hyppigere binge-drinking og indtag højere antal

genstande ved fest i forhold til gruppen, som havde binge-drukket 0 gange og indtaget 0

genstande ved den sidste fest.

For køretøjsulykker er der en højere risiko blandt grupperne med et højt ugentligt alkoholindtag og

hyppig binge-drinking, når de sammenlignes med gruppen med et ugentligt alkoholindtag på 0

genstande og gruppen, som ikke har binge-drukket de seneste 30 dage. Resultaterne er ikke

længere signifikante, når der tages højde for forskelle mellem grupperne. For antal genstande

indtaget til sidste fest ses der ikke nogen sammenhæng med køretøjsulykker. En mulig forklaring

på den manglende sammenhæng kan være en ændret holdning til spirituskørsel, da et stort flertal

af de adspurgte i flere nyere danske undersøgelser finder spirituskørsel uacceptabelt (38) .

For sportsulykker ses der ikke en øget risiko i gruppen med et højt ugentligt alkoholindtag i forhold

til gruppen med et ugentligt alkoholindtag på 0 genstande, ligesom der heller ikke ses forskel

mellem grupper med forskellig hyppighed af binge-drinking. Dette kan skyldes, at unge, som dyrker

meget sport, drikker mindre end andre unge. For antal genstande indtaget til sidste fest ses der en

signifikant lavere risiko i alle andre grupper end de som havde indtaget 16+ genstande, når der

sammenlignes med gruppen, som havde indtaget 0 genstande ved sidste fest.

For voldsepisoder er risikoen størst blandt de grupper, som har det højeste ugentlige alkoholindtag

(> 27 genstande) og som hyppigst binge-drikker (> 6 gange) i forhold til gruppen med et ugentligt

alkoholindtag på 0 genstande og gruppen, som havde binge-drukket 0 gange. For antal genstande

indtaget til fest ses der ikke en højere risiko for gruppen, der har det største alkoholindtag, i forhold

til gruppen med et alkoholindtag på 0 genstande, mens der ses en lavere risiko for grupperne, som

havde drukket 1-9 genstande.

Vores resultater vs. tidligere resultater

De fleste studier, som undersøger sammenhængen mellem alkohol og ulykker blandt unge, er

tværssnitsstudier, med fokus på én kategori af ulykker og omstændighederne omkring disse (12,

17, 39-41). Disse studier er derfor ikke direkte sammenlignelige med resultaterne fra denne

undersøgelse, som er en follow-up-undersøgelse med op til 4 års opfølgning fra tidspunktet hvor

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ALKOHOL OG ULYKKER BLANDT UNGE

der er indsamlet informationer om alkoholvaner. Et andet punkt, hvorpå vores undersøgelse

adskiller sig fra tidligere studier, er alderssammensætningen af populationen, som danner grundlag

for analysen, da personerne i denne undersøgelse er yngre end i de fleste tidligere studier

omhandlende alkohol og ulykker.

Fordelt efter type ses der i denne undersøgelse flest fald- og sportsulykker og en mindre andel

køretøjsulykker og arbejdsulykker. I en national rapport baseret på ulykker i perioden 1990-2009,

som indebar en sygehuskontakt blandt alle danske borgere finder man samme fordeling (22).

I denne rapport har 28 % af deltagerne (32 % af drenge og 25 % af piger) været ude for en ulykke

inden for de 4 års opfølgning. Lignende resultater ses i et australsk studie, som undersøger

forekomsten af alkoholrelaterede uheld blandt 558 unge australiere i alderen 17-18 år. De finder, at

33,3 % af de unge (35,9 % af drenge og 29,4 % af piger) har oplevet alkoholrelaterede uheld inden

for den seneste måned (42). To internationale studier, som undersøger tilstedeværelsen af alkohol

og andre stoffer blandt chauffører, der enten er blevet skadet eller slået ihjel i trafikken, finder, at

tilstedeværelsen af alkohol er højere blandt mænd end blandt kvinder (10-12). Disse studier

rapporterer desuden særskilte resultater fra Danmark, som viser, at 65 % af de alkoholpåvirkede

chauffører er mænd. Generelt ses der i flere studier en højere forekomst af alkoholrelaterede uheld

blandt mænd end blandt kvinder (16, 30). Disse studier har dog alle en ældre studiepopulation (18-

24 år) end den vores undersøgelse. I vores studie var der som i de andre studier en højere

forekomst af ulykker blandt drenge. Dog er vores undersøgelse baseret på alle ulykker frem for

kun at undersøge alkoholrelaterede ulykker.

Et studie af Hides et al., 2015 (31) rapporterer, at piger i højere grad har en risiko for selvpåførte

skader og alkoholforgiftning, hvorimod drenge har en overrepræsentation af mere fysiske og

eksternt påførte skader, såsom fald, trafikulykker og vold. Dette stemmer ikke overens med

resultaterne i vores undersøgelse, hvor fordelingen af ulykker imellem køn viser, at pigerne har en

større andel af køretøjsulykker og faldulykker end drengene. Forskellen i resultater kan blandt

andet skyldes, at studiet af Hides et al., 2015 udelukkende inkluderer alkoholrelaterede ulykker,

hvorimod vores undersøgelse inkluderer alle registrerede ulykker (31). Ydermere er

aldersgrænsen for studiepopulationen i Hides et al. bredere end i vores undersøgelse.

Undersøgelsens styrker og svagheder

Den anvendte metode i undersøgelsen har en række styrker. I forhold til tidligere studier bygger

denne undersøgelse på data fra en stor gruppe af unge, og er desuden baseret på information fra

de 69.755 elever der deltog i Ungdomsprofilen 2014. Det høje antal personer betyder, at

sikkerheden i resultaterne er større end i undersøgelser, der bygger på en mindre population.

Via CPR-nummeret kan deltagerne i Ungdomsprofilen 2014 kobles med nationale registre,

heriblandt Landspatientregistret, som denne undersøgelse er baseret på, hvormed vi er i stand til

at følge alle eleverne og identificere hvilke elever, der kom ud for en ulykke. Ungdomsprofilen 2014

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ALKOHOL OG ULYKKER BLANDT UNGE

indeholder spørgsmål om forskellige parametre for alkoholforbrug, hvorfor vi kan afdække

sammenhængen mellem risiko for ulykker og forskellige alkoholforbrugsmønstre. Foruden

alkoholforbrug indeholder spørgeskemaet i Ungdomsprofilen 2014 spørgsmål om forbrug af

cannabis og stoffer m.v. Det gør det muligt at vurdere forskellige faktorers betydning for

sammenhængen mellem alkoholforbrug og ulykker, ligesom der kan tages højde for forskelle i

socioøkonomi, etnicitet m.v. blandt grupperne som sammenlignes.

Tidligere studier har haft fokus på én bestemt ulykkestype, for eksempel køretøjsulykker. Denne

undersøgelse belyser sammenhængen mellem alkoholforbrug og forskellige typer af ulykker, hvor

der kun findes få studier af blandt andet faldulykker. Derfor bidrager denne rapport med ny viden

om de ulykkestyper, som der kun findes få studier af.

Undersøgelsen har nogle væsentlige metodiske svagheder. Analysen af alkoholforbrug og ulykker

er baseret på alle kontakter til sygehuset, som har ulykke eller vold som kontaktårsagen. Vi har

ikke mulighed for at vurdere, om der er nogle af disse ulykker, hvor personen var alkoholpåvirket.

For at kategorisere ulykkerne blev der anvendt ulykkeskoder, der som nævnt i metodeafsnittet er

mangelfuldt registreret i Landspatientregistret (33). Det er derfor sandsynligt, at en række ulykker

er fejlkategoriseret, ligesom der er en risiko for, at nogle ulykker ikke er registreret som

ulykkeskontakter. En anden svaghed ved den anvendte metode er, at den samme ulykke kan falde

inden for mere end én kategori. Fremtidige undersøgelser kan undersøge alternative metoder til,

hvordan kategorierne kan afgrænses på en meningsfuld måde.

I denne rapport defineres ulykker ud fra kontaktårsagen i Landspatientregistret. Ulykker kan dække

over vidt forskellige kontakter, hvor alvorligheden af skaden kan variere fra en overfladisk skade til

et livstruende traume. Vi har i denne undersøgelse ikke undersøgt alvorligheden af de forskellige

ulykker, hvorfor vi ikke kan vurdere, om der er forskel i alvorsgraden af ulykkerne mellem grupper

med forskelligt alkoholindtag. Fremtidige undersøgelser kan undersøge dette og anvende

diagnoser til at vurdere alvorsgraden af ulykkerne.

Sammenhængen mellem alkoholindtag og risikoen for ulykker er baseret på det alkoholindtag, som

eleven har angivet ved deltagelse i Ungdomsprofilen 2014, hvorefter ulykker blev undersøgt over

en 4-årig periode. Vi har ikke kendskab til elevens alkoholindtag umiddelbart op til ulykken og har

derfor ikke viden om, hvorvidt ulykken egentlig er alkoholrelateret. Den 4-årige opfølgningsperiode

indebærer desuden en risiko for, at en person kan have ændret alkoholforbrug flere gange, så det

ikke længere stemmer overens med de rapporterede oplysninger i Ungdomsprofilen 2014.

Målet ”antal genstande indtaget ved sidste fest” kan være forbundet med usikkerhed, da det kan

være svært for en person at huske, hvor mange genstande vedkommende drak. Ydermere er der

en mulighed for, at svaret er udtryk for en enkeltstående begivenhed, som kan afvige fra

personens normale forbrug af alkohol, hvorfor dette mål skal tages med forbehold.

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I analyserne af sammenhængen mellem alkoholforbrug og ulykker er der justeret for forskelle

mellem grupperne på køn, alder, ungdomsuddannelse, socioøkonomisk position og etnicitet i det

første sæt af analyser, mens der i det andet sæt af analyser desuden tages højde for brug af

cannabis, brug af stoffer, rygning, betydningen af karakter og deltagelse i gymnasiefest. Flere

studier viser, at rygning og alkoholforbrug hænger tæt sammen, hvormed de begge kan ses som

en indikator for risikoadfærd (43-45).

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ALKOHOL OG ULYKKER BLANDT UNGE

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Bilag

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Bilag 1: Søgematrice

Blok 1

Young adults

Adolescents

Young people

Teenagers

"Adolescent"[Mesh]

"Young Adult"[Mesh]

“Adolescent behavior”

[MeSH]

Blok 2

Alcohol

Ethanol

Liquor

Blood alcohol percent

"Ethanol"[Mesh]

"Alcohols"[Mesh]

"Alcoholic Intoxication"[Mesh]

Alcoholic Intoxication

“Blood alcohol Content” [MeSH]

alcohol drinking

Blok 3

Fatal accidents

Crash*

Fall*

"Accidents"[Mesh]

Drown*

"Accidental Falls"[Mesh]

"Drowning"[Mesh]

"Near Drowning"[Mesh]

“Accidental injuries”[Mesh]

AND