Jürgen Rehm1,2,3,4,5,6,7, Jakob Manthey6,8, Shannon Lange1, Robertas Badaras9,10, Ingrida Zurlyte11, Jonathon Passmore12, João Breda13, Carina Ferreira-Borges13, Mindaugas Štelemėkas14,15. 1. Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, Ontario, Canada. 2. Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada. 3. Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada. 4. Faculty of Medicine, Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada. 5. Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada. 6. Institute of Clinical Psychology and Psychotherapy and Center of Clinical Epidemiology and Longitudinal Studies (CELOS), Technische Universität Dresden, Dresden, Germany. 7. Department of International Health Projects, Institute for Leadership and Health Management, I. M. Sechenov First Moscow State Medical University, Moscow, Russia. 8. Center for Interdisciplinary Addiction Research (ZIS), Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany. 9. Clinic of Anaesthesiology and Intensive Care, Faculty of Medicine, Centre of Toxicology, Vilnius University, Vilnius, Lithuania. 10. Vilnius University Emergency Hospital, Vilnius, Lithuania. 11. WHO Country Office Lithuania, Vilnius, Lithuania. 12. WHO Regional Office for Europe, Copenhagen, Denmark. 13. WHO European Office for Prevention and Control of Noncommunicable Diseases, Moscow, Russia. 14. Health Research Institute, Faculty of Public Health, Lithuanian University of Health Sciences, Kaunas, Lithuania. 15. Department of Preventive Medicine, Faculty of Public Health, Lithuanian University of Health Sciences, Kaunas, Lithuania.
Abstract
AIMS: To study the impact of alcohol control policy measures (i.e. increases in taxation, restrictions on availability, including minimum purchasing age regulations, legislation on drink driving and advertisement bans) on alcohol-related traffic harm in Lithuania between January 2004 and February 2019. DESIGN: Analyses of trend data on the proportion of alcohol-related collisions and crashes, injury and mortality, adjusting for secular trends, seasonality, periods of alcohol control measure implementation and economic development. Generalized additive mixed models were used. Multiple sensitivity analyses were conducted. SETTING: Lithuania. CASES: Monthly number of alcohol-related cases of traffic collisions and crashes, injuries and deaths. INTERVENTIONS AND COMPARATORS: Periods of time during which new alcohol control measures were implemented and/or augmented compared to periods when they were not. MEASUREMENTS: Monthly data for 2004 to 2019 from routine statistics of the Lithuanian Road Police Service. FINDINGS: All indicators decreased consistently and significantly after the implementation of alcohol control measures, including increased taxation, reduction of availability and a ban on advertisement, starting in 2014. On average, each implemented policy measure permanently reduced the proportion of alcohol-attributable crashes by 0.55% [95% confidence interval (CI) = 0.21-0.90%; P = 0.002], the proportion of alcohol-attributable injuries by 0.60% (95% CI = 0.24-0.97%; P = 0.001) and the proportion of alcohol-attributable deaths by 0.13% (95% CI = 0.10-0.15%; P < 0.001). CONCLUSIONS: Alcohol control policy measures, including measures to reduce overall level of alcohol consumption, were associated with a marked decrease in alcohol-related traffic harm.
AIMS: To study the impact of alcohol control policy measures (i.e. increases in taxation, restrictions on availability, including minimum purchasing age regulations, legislation on drink driving and advertisement bans) on alcohol-related traffic harm in Lithuania between January 2004 and February 2019. DESIGN: Analyses of trend data on the proportion of alcohol-related collisions and crashes, injury and mortality, adjusting for secular trends, seasonality, periods of alcohol control measure implementation and economic development. Generalized additive mixed models were used. Multiple sensitivity analyses were conducted. SETTING: Lithuania. CASES: Monthly number of alcohol-related cases of traffic collisions and crashes, injuries and deaths. INTERVENTIONS AND COMPARATORS: Periods of time during which new alcohol control measures were implemented and/or augmented compared to periods when they were not. MEASUREMENTS: Monthly data for 2004 to 2019 from routine statistics of the Lithuanian Road Police Service. FINDINGS: All indicators decreased consistently and significantly after the implementation of alcohol control measures, including increased taxation, reduction of availability and a ban on advertisement, starting in 2014. On average, each implemented policy measure permanently reduced the proportion of alcohol-attributable crashes by 0.55% [95% confidence interval (CI) = 0.21-0.90%; P = 0.002], the proportion of alcohol-attributable injuries by 0.60% (95% CI = 0.24-0.97%; P = 0.001) and the proportion of alcohol-attributable deaths by 0.13% (95% CI = 0.10-0.15%; P < 0.001). CONCLUSIONS: Alcohol control policy measures, including measures to reduce overall level of alcohol consumption, were associated with a marked decrease in alcohol-related traffic harm.
Authors: Alexander Tran; Huan Jiang; Shannon Lange; Michael Livingston; Jakob Manthey; Maria Neufeld; Robin Room; Mindaugas Štelemėkas; Tadas Telksnys; Janina Petkevičienė; Ričardas Radišauskas; Jürgen Rehm Journal: Alcohol Alcohol Date: 2022-07-09 Impact factor: 3.913
Authors: Laura Miščikienė; Nijolė Goštautaitė Midttun; Lukas Galkus; Gražina Belian; Janina Petkevičienė; Justina Vaitkevičiūtė; Mindaugas Štelemėkas Journal: Int J Environ Res Public Health Date: 2020-05-15 Impact factor: 3.390
Authors: Charlotte Probst; Jakob Manthey; Maria Neufeld; Jürgen Rehm; João Breda; Ivo Rakovac; And Carina Ferreira-Borges Journal: Int J Environ Res Public Health Date: 2020-05-14 Impact factor: 3.390
Authors: Carolin Kilian; Jakob Manthey; Jacek Moskalewicz; Janusz Sieroslawski; Jürgen Rehm Journal: Int J Environ Res Public Health Date: 2019-11-13 Impact factor: 3.390
Authors: Nino Berdzuli; Carina Ferreira-Borges; Antoni Gual; Jürgen Rehm Journal: Int J Environ Res Public Health Date: 2020-11-04 Impact factor: 3.390
Authors: Jürgen Rehm; Mindaugas Štelemėkas; Carina Ferreira-Borges; Huan Jiang; Shannon Lange; Maria Neufeld; Robin Room; Sally Casswell; Alexander Tran; Jakob Manthey Journal: Int J Environ Res Public Health Date: 2021-03-02 Impact factor: 3.390