Classifying Alcohol Control Policies with Respect to Expected Changes in Consumption and Alcohol-Attributable Harm: The Example of Lithuania, 2000–2019

Jürgen Rehm, Mindaugas Štelemėkas, Carina Ferreira-Borges, Huan Jiang, Shannon Lange, Maria Neufeld, Robin Room, Sally Casswell, Alexander Tran and Jakob Manthey
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Jürgen Rehm: Institute for Mental Health Policy Research, Centre for Addiction and Mental Health (CAMH), 33 Ursula Franklin Street, Toronto, ON M5S 2S1, Canada
Mindaugas Štelemėkas: Health Research Institute, Faculty of Public Health, Lithuanian University of Health Sciences, Tilžės Str. 18, 47181 Kaunas, Lithuania
Carina Ferreira-Borges: WHO European Office for Prevention and Control of Noncommunicable Diseases, Leontyevsky Pereulok 9, 125009 Moscow, Russia
Huan Jiang: Institute for Mental Health Policy Research, Centre for Addiction and Mental Health (CAMH), 33 Ursula Franklin Street, Toronto, ON M5S 2S1, Canada
Shannon Lange: Institute for Mental Health Policy Research, Centre for Addiction and Mental Health (CAMH), 33 Ursula Franklin Street, Toronto, ON M5S 2S1, Canada
Maria Neufeld: Institute for Mental Health Policy Research, Centre for Addiction and Mental Health (CAMH), 33 Ursula Franklin Street, Toronto, ON M5S 2S1, Canada
Robin Room: Centre for Alcohol Policy Research, Building NR-1, La Trobe University, Plenty Rd. x Kingsbury Rd., Bundoora, VIC 3086, Australia
Sally Casswell: SHORE and Whariki Research Centre, College of Health, Massey University, 90 Symonds Street, Auckland 1010, New Zealand
Alexander Tran: Institute for Mental Health Policy Research, Centre for Addiction and Mental Health (CAMH), 33 Ursula Franklin Street, Toronto, ON M5S 2S1, Canada
Jakob Manthey: Center for Clinical Epidemiology and Longitudinal Studies, Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Chemnitzer Str. 46, 01187 Dresden, Germany

IJERPH, 2021, vol. 18, issue 5, 1-13

Abstract: Due to the high levels of alcohol use, alcohol-attributable mortality and burden of disease, and detrimental drinking patterns, Lithuania implemented a series of alcohol control policies within a relatively short period of time, between 2008 and 2019. Based on their expected impact on alcohol consumption and alcohol-attributable harm, as well as their target population, these policies have been classified using a set of objective criteria and expert opinion. The classification criteria included: positive vs. negative outcomes, mainly immediate vs. delayed outcomes, and general population vs. specific group outcomes. The judgement of the alcohol policy experts converged on the objective criteria, and, as a result, two tiers of intervention were identified: Tier 1—highly effective general population interventions with an anticipated immediate impact; Tier 2—other interventions aimed at the general population. In addition, interventions directed at specific populations were identified. This adaptable methodological approach to alcohol control policy classification is intended to provide guidance and support for the evaluation of alcohol policies elsewhere, to lay the foundation for the critical assessment of the policies to improve health and increase life expectancy, and to reduce crime and violence.

Keywords: alcohol control policy; best buys; classification; evaluation; taxation; availability; marketing; Lithuania (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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