Alexander Tran1, Huan Jiang1,2, Shannon Lange1,3,4, Jakob Manthey5,6,7, Mindaugas Štelemėkas8,9, Robertas Badaras1,3,10,11, Janina Petkevičienė8,9, Ričardas Radišauskas12,13, Robin Room14,15, Jürgen Rehm1,2,4,5,6,16,17. 1. Centre for Addiction and Mental Health (CAMH), Institute for Mental Health Policy Research, Toronto, Ontario, Canada. 2. Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada. 3. Campbell Family Mental Health Research Institute, CAMH, Toronto, Ontario, Canada. 4. Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada. 5. Institute of Clinical Psychology and Psychotherapy & Center for Clinical Epidemiology and Longitudinal Studies, Technische Universität Dresden, Dresden, Germany. 6. Center for Interdisciplinary Addiction Research (ZIS), Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany. 7. Department of Psychiatry, Medical Faculty, University of Leipzig, Leipzig, Germany. 8. Health Research Institute, Faculty of Public Health, Lithuanian University of Health Sciences, Kaunas, Lithuania. 9. Department of Preventive Medicine, Faculty of Public Health, Lithuanian University of Health Sciences, Kaunas, Lithuania. 10. Clinic of Anaesthesiology and Intensive Care, Faculty of Medicine, Centre of Toxicology, Vilnius University, Vilnius, Lithuania. 11. Vilnius University Emergency Hospital, Vilnius, Lithuania. 12. Department of Environmental and Occupational Medicine, Faculty of Public Health, Lithuanian University of Health Sciences, Kaunas, Lithuania. 13. Institute of Cardiology, Lithuanian University of Health Sciences, Kaunas, Lithuania. 14. Centre for Alcohol Policy Research, La Trobe University, Bundoora, Victoria, Australia. 15. Centre for Social Research on Alcohol and Drugs, Department of Public Health Sciences, Stockholm University, Stockholm, Sweden. 16. Institute of Medical Science (IMS), University of Toronto, Medical Sciences Building, 1 King's College Circle, Toronto, Ontario, Canada. 17. Department of International Health Projects, Institute for Leadership and Health Management, I.M. Sechenov First Moscow State Medical University, Moscow, Russian Federation.
Abstract
BACKGROUND AND AIMS: The relationship between alcohol consumption and cirrhosis is well established. Policies that can influence population-level use of alcohol should, in turn, impact cirrhosis. We examined the effect of population-level alcohol control policies on cirrhosis mortality rates in Lithuania - a high-income European Union country with high levels of alcohol consumption. METHODS: Age-standardized, monthly liver mortality data (deaths per 100,000 adults, aged 15+) from Lithuania were analysed from 2001 to 2018 (n = 216 months) while controlling for economic confounders (gross domestic product and inflation). An interrupted time-series analysis was conducted to estimate the effect of three alcohol control policies implemented in 2008, 2017 and 2018 and the number of cirrhosis deaths averted. RESULTS: There was a significant effect of the 2008 (P < .0001) and 2017 (P = .0003) alcohol control policies but a null effect of the 2018 policy (P = .40). Following the 2008 policy, the cirrhosis mortality rate dropped from 4.93 to 3.41 (95% CI: 3.02-3.80) deaths per 100,000 adults, which equated to 493 deaths averted. Further, we found that following the 2017 policy, the mortality rate dropped from 2.85 to 2.01 (95% CI: 1.50-2.52) deaths per 100,000 adults, corresponding to 245 deaths averted. CONCLUSIONS: Our findings support the hypothesis that alcohol control policies can have a significant, immediate effect on cirrhosis mortality. These policy measures are cost-effective and aid in reducing the burden of liver disease.
BACKGROUND AND AIMS: The relationship between alcohol consumption and cirrhosis is well established. Policies that can influence population-level use of alcohol should, in turn, impact cirrhosis. We examined the effect of population-level alcohol control policies on cirrhosis mortality rates in Lithuania - a high-income European Union country with high levels of alcohol consumption. METHODS: Age-standardized, monthly liver mortality data (deaths per 100,000 adults, aged 15+) from Lithuania were analysed from 2001 to 2018 (n = 216 months) while controlling for economic confounders (gross domestic product and inflation). An interrupted time-series analysis was conducted to estimate the effect of three alcohol control policies implemented in 2008, 2017 and 2018 and the number of cirrhosis deaths averted. RESULTS: There was a significant effect of the 2008 (P < .0001) and 2017 (P = .0003) alcohol control policies but a null effect of the 2018 policy (P = .40). Following the 2008 policy, the cirrhosis mortality rate dropped from 4.93 to 3.41 (95% CI: 3.02-3.80) deaths per 100,000 adults, which equated to 493 deaths averted. Further, we found that following the 2017 policy, the mortality rate dropped from 2.85 to 2.01 (95% CI: 1.50-2.52) deaths per 100,000 adults, corresponding to 245 deaths averted. CONCLUSIONS: Our findings support the hypothesis that alcohol control policies can have a significant, immediate effect on cirrhosis mortality. These policy measures are cost-effective and aid in reducing the burden of liver disease.
Authors: D A Leon; L Chenet; V M Shkolnikov; S Zakharov; J Shapiro; G Rakhmanova; S Vassin; M McKee Journal: Lancet Date: 1997-08-09 Impact factor: 79.321
Authors: Witold A Zatoński; Urszula Sulkowska; Marta Mańczuk; Jürgen Rehm; Paolo Boffetta; Albert B Lowenfels; Carlo La Vecchia Journal: Eur Addict Res Date: 2010-07-02 Impact factor: 3.015
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: 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