Interrupted time series analyses to assess the impact of alcohol control policy on socioeconomic inequalities in mortality in Lithuania: a study protocol
TL;DR: In this paper, the authors used a generalized additive mixed model to test the impact of the 2017 increase in alcohol excise taxes for beer and wine, which was linked to lower all-cause mortality rates in previous analyses, will reduce socioeconomic mortality inequalities.
Abstract: IntroductionAlcohol use is a major risk factor for mortality. Previous studies suggest that the alcohol-attributable mortality burden is higher in lower socioeconomic strata. This project will test the hypothesis, that the 2017 increase of alcohol excise taxes for beer and wine, which was linked to lower all-cause mortality rates in previous analyses, will reduce socioeconomic mortality inequalities. Methods and analysisData on all causes of deaths will be obtained from Statistics Lithuania. Record linkage will be implemented using personal identifiers combining data from 1) the 2011 whole-population census, 2) death records between March 1, 2011 (census date) and December 31, 2019, and 3) emigration records, for individuals aged 30 to 70 years. The analyses will be performed separately for all-cause and for alcohol-attributable deaths. Monthly age-standardized mortality rates will be calculated by sex, education, and three measures of socioeconomic status. Inequalities in mortality will be assessed using absolute and relative indicators between low and high SES groups. We will perform interrupted time series analyses, and test the impact of the 2017 rise in alcohol excise taxation using generalized additive mixed models. In these models, we will control for secular trends for economic development. Ethics and disseminationThis work is part of project grant 1R01AA028224-01 by the National Institute on Alcohol Abuse and Alcoholism. It has been granted research ethics approval 050/2020 by CAMH Research Ethics Board on April 17, 2020, renewed on March 30, 2021. Strengths and limitations of this studyO_LICensus-linked mortality data will cover the entire population of Lithuania aged 30 to 70 years C_LIO_LIThree different definitions of socioeconomic groupings will allow for a comprehensive description of mortality inequalities in Lithuania between 2011 and 2019. C_LIO_LIThe results will indicate if and to what extent an increase of alcohol excise taxes may be effective for reducing of health inequalities, thus closing the evidence gap of modelling studies predicting alcohol taxation to be an effective tool to reduce health inequalities. C_LIO_LIInterpretation of the effects will depend on identifying relevant confounders. C_LIO_LIAn important limitation of census-linked studies is that the socioeconomic grouping is fixed at the census baseline. C_LI
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TL;DR: This tutorial uses a worked example to demonstrate a robust approach to ITS analysis using segmented regression and describes the main methodological issues associated with ITS analysis: over-dispersion of time series data, autocorrelation, adjusting for seasonal trends and controlling for time-varying confounders.
Abstract: Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been implemented at a clearly defined point in time. It is increasingly being used to evaluate the effectiveness of interventions ranging from clinical therapy to national public health legislation. Whereas the design shares many properties of regression-based approaches in other epidemiological studies, there are a range of unique features of time series data that require additional methodological considerations. In this tutorial we use a worked example to demonstrate a robust approach to ITS analysis using segmented regression. We begin by describing the design and considering when ITS is an appropriate design choice. We then discuss the essential, yet often omitted, step of proposing the impact model a priori. Subsequently, we demonstrate the approach to statistical analysis including the main segmented regression model. Finally we describe the main methodological issues associated with ITS analysis: over-dispersion of time series data, autocorrelation, adjusting for seasonal trends and controlling for time-varying confounders, and we also outline some of the more complex design adaptations that can be used to strengthen the basic ITS design.
1,778 citations
University of Lausanne1, University of Helsinki2, King's College London3, Harvard University4, Columbia University5, Imperial College London6, University of Porto7, French Institute of Health and Medical Research8, University of Toulouse9, Paris Descartes University10, Cancer Council Victoria11, Trinity College, Dublin12, University College London13, Erasmus University Medical Center14
TL;DR: Socioeconomic circumstances, in addition to the 25 × 25 factors, should be targeted by local and global health strategies and health risk surveillance to reduce mortality.
752 citations
TL;DR: Based on these data, global goals for reducing the harmful use of alcohol are unlikely to be achieved, and known effective and cost-effective policy measures should be implemented to reduce alcohol exposure.
436 citations
TL;DR: As a leading risk factor for the burden of disease, alcohol use disproportionately affects people in low HDI countries and young people, and cost-effective local and national policy measures that can reduce alcohol use and the resultingurden of disease are needed, especially in low-income and middle-income countries.
Abstract: Summary Background Alcohol use has increased globally, with varying trends in different parts of the world. This study investigates gender, age, and geographical differences in the alcohol-attributable burden of disease from 2000 to 2016. Methods This comparative risk assessment study estimated the alcohol-attributable burden of disease. Population-attributable fractions (PAFs) were estimated by combining alcohol exposure data obtained from production and taxation statistics and from national surveys with corresponding relative risks obtained from meta-analyses and cohort studies. Mortality and morbidity data were obtained from the WHO Global Health Estimates, population data were obtained from the UN Population Division, and human development index (HDI) data were obtained from the UN Development Programme. Uncertainty intervals (UIs) were estimated using a Monte Carlo-like approach. Findings Globally, we estimated that there were 3·0 million (95% UI 2·6–3·6) alcohol-attributable deaths and 131·4 million (119·4–154·4) disability-adjusted life-years (DALYs) in 2016, corresponding to 5·3% (4·6–6·3) of all deaths and 5·0% (4·6–5·9) of all DALYs. Alcohol use was a major risk factor for communicable, maternal, perinatal, and nutritional diseases (PAF of 3·3% [1·9–5·6]), non-communicable diseases (4·3% [3·6–5·1]), and injury (17·7% [14·3–23·0]) deaths. The alcohol-attributable burden of disease was higher among men than among women, and the alcohol-attributable age-standardised burden of disease was highest in the eastern Europe and western, southern, and central sub-Saharan Africa regions, and in countries with low HDIs. 52·4% of all alcohol-attributable deaths occurred in people younger than 60 years. Interpretation As a leading risk factor for the burden of disease, alcohol use disproportionately affects people in low HDI countries and young people. Given the variations in the alcohol-attributable burden of disease, cost-effective local and national policy measures that can reduce alcohol use and the resulting burden of disease are needed, especially in low-income and middle-income countries. Funding None.
256 citations
TL;DR: Over the past two decades, trends in inequalities in mortality have been more favourable in most European countries than is commonly assumed.
Abstract: Objective To determine whether government efforts in reducing inequalities in health in European countries have actually made a difference to mortality inequalities by socioeconomic group. Design Register based study. Data source Mortality data by level of education and occupational class in the period 1990-2010, usually collected in a census linked longitudinal study design. We compared changes in mortality between the lowest and highest socioeconomic groups, and calculated their effect on absolute and relative inequalities in mortality (measured as rate differences and rate ratios, respectively). Setting All European countries for which data on socioeconomic inequalities in mortality were available for the approximate period between years 1990 and 2010. These included Finland, Norway, Sweden, Scotland, England and Wales (data applied to both together), France, Switzerland, Spain (Barcelona), Italy (Turin), Slovenia, and Lithuania. Results Substantial mortality declines occurred in lower socioeconomic groups in most European countries covered by this study. Relative inequalities in mortality widened almost universally, because percentage declines were usually smaller in lower socioeconomic groups. However, as absolute declines were often smaller in higher socioeconomic groups, absolute inequalities narrowed by up to 35%, particularly among men. Narrowing was partly driven by ischaemic heart disease, smoking related causes, and causes amenable to medical intervention. Progress in reducing absolute inequalities was greatest in Spain (Barcelona), Scotland, England and Wales, and Italy (Turin), and absent in Finland and Norway. More detailed studies preferably using individual level data are necessary to identify the causes of these variations. Conclusions Over the past two decades, trends in inequalities in mortality have been more favourable in most European countries than is commonly assumed. Absolute inequalities have decreased in several countries, probably more as a side effect of population wide behavioural changes and improvements in prevention and treatment, than as an effect of policies explicitly aimed at reducing health inequalities.
231 citations