Login / Signup

Changes in attitudes toward alcohol control policies in Lithuania. Findings from two representative surveys in 2015 and 2020.

Daumantas StumbrysIlona TamutienėJacek MoskalewiczJanusz Sieroslawski
Published in: The American journal of drug and alcohol abuse (2023)
Background: A set of evidence-based alcohol control policy measures was adopted in the period 2016-2020 in Lithuania. The present study fills a knowledge gap on how changes in alcohol control policy are associated with attitudes toward different alcohol policy measures. Objective: This study aims to explore whether support for key alcohol control policy measures in Lithuania declined following implementation of alcohol control measures. Methods: Data came from the Standard European Alcohol Survey. Two representative surveys with the same questionnaire, were conducted in Lithuania in 2015 ( N  = 1513, 51.7% female, response rate was 38.9%) and 2020 ( N  = 1015, 50.6% female, response rate was 38.0%). Multi-stage stratified probability sampling was applied. Surveys were carried out using computer-assisted face-to-face interviews, descriptive statistics and multiple logistic regression analyses was applied. We used a binomial logistic regression analysis and the Pearson chi-square test. Results: There was a significant decline in a proportion of respondents who agreed that the number of alcohol selling places should be kept low (OR: 0.84, p  = .032), alcohol prices should be kept high (OR: 0.83, p  = .027), and the police should be allowed to randomly check whether the driver is sober (OR: 0.65, p  < .001). The proportion of respondents who agree that individuals are responsible enough with their drinking significantly declined (OR: 0.76, p  = .003). Conclusion: Support for restrictions on alcohol-selling points, increase in alcohol price, and random alcohol testing of drivers declined following the adoption of new alcohol control policy measures. Our findings might be beneficial for policy-makers planning alcohol control policies and information campaigns.
Keyphrases
  • alcohol consumption
  • public health
  • healthcare
  • cross sectional
  • mental health
  • primary care
  • electronic health record
  • machine learning
  • data analysis