Alcohol control policy measures and all‐cause mortality in Lithuania: an interrupted time–series analysis

Abstract

Background and aims Alcohol use has been identified as a major risk factor for burden of mortality and disease, particularly for countries in eastern Europe. During the past two decades, several countries in this region have implemented effective alcohol policy measures to combat this burden. The aim of the current study was to measure the association between Lithuania's alcohol control policies and adult all‐cause mortality. Design Interrupted time–series methodology by means of general additive models. Setting Lithuania. Participants Adult population of Lithuania, aged 20 years and older. Measurements Alcohol control policies were ascertained via a document review of relevant legislation materials. Policy effects were evaluated as follows: (1) slope changes in periods of legislative (non‐)activity with regard to alcohol control policy (analysis 1); (2) level changes of three interventions following recommendations of the World Health Organization (analysis 2); and (3) level changes of seven interventions judged a priori by an international panel of experts (analysis 3). Mortality was measured by sex‐stratified and total monthly age‐standardized rates of all‐cause mortality for the adult population. Findings During the period 2001–18, effective alcohol control policy measures were implemented on several occasions, and in those years the all‐cause mortality rate declined by approximately 3.2% more than in years without such policies. In particular, the implementation of increased taxation in 2017 was associated with reduced mortality over and above the general trend for men and in total for all analyses, which amounted to 1452 deaths avoided (95% confidence interval = −166 to –2739) in the year following the implementation of the policy. Conclusions Alcohol control policies in Lithuania appear to have reduced the overall adult all‐cause mortality over and above secular trends.

Alcohol control policies add to secular trends in all-cause mortality rates in young adults

“…Furthermore, as per Hypothesis 2, for those 20–29 years old the 2009 alcohol control policy measures were most impactful, and for those 30–39 years old the 2017 alcohol policy was most impactful. The policies implemented in 2009 and 2017 added significant explanatory power to the joinpoint model across virtually all of the age groups (average increase of 1% variance), lending support for a causal interpretation of the findings by Štelemėkas et al 32 . This study strengthens the argument that alcohol control policies should be an important consideration when aiming to reduce all-cause mortality.…”

“…Štelemėkas and colleagues 32 showed that all-cause mortality, across the entire population, decreased following policies that resulted in higher taxation and reduced availability of alcohol. In their work, they used an interrupted time-series analysis to test a number of alcohol control policies that were selected by policy experts and were part of the “best buys” recommendations.…”

“…To address the challenge of determining causality in quasi-experimental designs and time series data, we employ a two-stage data analysis technique in which a base model (joinpoint analysis) containing the underlying secular trends is created. Building on this base model, and on the work of Štelemėkas and colleagues 32 , we aim to determine whether the effect of two specific sets of alcohol control policies implemented in Lithuania have an effect on all-cause mortality rates when secular trends are used as a covariate. One set of policies was implemented on the 1st of January 2009, including: (1) taxation (increase excise tax by 10–15%, removal of tax exemptions for small beer breweries) and (2) changes in the availability of alcohol (off-premise sales restricted at night, a ban on having opened alcohol beverages in cars).…”

“…One set of policies was implemented on the 1st of January 2009, including: (1) taxation (increase excise tax by 10–15%, removal of tax exemptions for small beer breweries) and (2) changes in the availability of alcohol (off-premise sales restricted at night, a ban on having opened alcohol beverages in cars). On the 1st of March 2017 another set of taxation policy changes (increase excise tax: 111–112% for wines and beer, 23% for ethyl alcohol) was introduced (see Štelemėkas et al 32 for more details on all alcohol policies introduced between 2001 and 2018 and Supplementary Table S1 for details on the two policy sets). Furthermore, we aim to explore the effect of these two sets of policies on mortality rates across different age groups.…”

Alcohol taxation, alcohol consumption and cancers in Lithuania: A case study

“…The increases in excise taxes in 2017 amounted to more than 100% for beer and wine, and 23% for spirits (for details, see Appendix Table A1 in the online supplementary material), increasing the retail price on average by 15.5% for local and imported beer, 20.7% for wines, and 7.6% for local and imported vodka (data were based on the two beer, two vodka and four wine subcategories in the Lithuanian official classification system; Lithuanian Department of Statistics, 2020b). These numbers were based on information on taxation policies in Lithuania separate by alcohol beverage type from the EU and Lithuanian government (European Commission Directorate-General Taxation and Customs Union, 2020; State Tax Inspectorate, 2020); the data on the mean price were obtained from the Statista webpage (Statista, 2020). An overview of all data and procedures can be found in the Appendix Table A2 online.…”