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Journal ArticleDOI

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

TL;DR: In this article, a set of objective criteria and expert opinion were used to classify the alcohol control policies in Lithuania based on their expected impact on alcohol consumption and alcohol-attributable harm.
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.

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Journal ArticleDOI
TL;DR: In this article, the authors measured the association between Lithuania's alcohol control policies and adult all-cause mortality by means of general additive models, and found that during the period 2001-2018, 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.
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.

32 citations

Journal ArticleDOI
TL;DR: In this paper , the authors examined how standard analytical approaches to model mortality outcomes of alcohol use compare to the true results using the impact of the March 2017 alcohol taxation increase in Lithuania on all-cause mortality as an example.
Abstract: Abstract Aims To examine how standard analytical approaches to model mortality outcomes of alcohol use compare to the true results using the impact of the March 2017 alcohol taxation increase in Lithuania on all-cause mortality as an example. Methods Four methodologies were used: two direct methodologies: (a) interrupted time-series on mortality and (b) comparing predictions based on time-series modeling with the real number of deaths for the year following the implementation of the tax increase; and two indirect methodologies: (c) combining a regression-based estimate for the impact of taxation on alcohol consumption with attributable-fraction methodology and (d) using price elasticities from meta-analyses to estimate the impact on alcohol consumption before applying attributable-fraction methodology. Results and Conclusions While all methodologies estimated reductions in all-cause mortality, especially for men, there was substantial variability in the level of mortality reductions predicted. The indirect methodologies had lower predictions as the meta-analyses on elasticities and risk relations seem to underestimate the true values for Lithuania. Directly estimated effects of taxation based on the actual mortalities seem to best represent the true reductions in alcohol-attributable mortality. A significant increase in alcohol excise taxation had a marked impact on all-cause mortality in Lithuania.

9 citations

Journal ArticleDOI
TL;DR: In this paper , a simulation-based approach was used to estimate intervention effects under different assumptions, and the robustness of these two approaches was further investigated assuming misspecification of the models.
Abstract: Abstract Background A classic methodology used in evaluating the impact of health policy interventions is interrupted time-series (ITS) analysis, applying a quasi-experimental design that uses both pre- and post-policy data without randomization. In this paper, we took a simulation-based approach to estimating intervention effects under different assumptions. Methods Each of the simulated mortality rates contained a linear time trend, seasonality, autoregressive, and moving-average terms. The simulations of the policy effects involved three scenarios: 1) immediate-level change only, 2) immediate-level and slope change, and 3) lagged-level and slope change. The estimated effects and biases of these effects were examined via three matched generalized additive mixed models, each of which used two different approaches: 1) effects based on estimated coefficients ( estimated approach), and 2) effects based on predictions from models ( predicted approach). The robustness of these two approaches was further investigated assuming misspecification of the models. Results When one simulated dataset was analyzed with the matched model, the two analytical approaches produced similar estimates. However, when the models were misspecified, the number of deaths prevented, estimated using the predicted vs. estimated approaches, were very different, with the predicted approach yielding estimates closer to the real effect. The discrepancy was larger when the policy was applied early in the time-series. Conclusion Even when the sample size appears to be large enough, one should still be cautious when conducting ITS analyses, since the power also depends on when in the series the intervention occurs. In addition, the intervention lagged effect needs to be fully considered at the study design stage (i.e., when developing the models).

6 citations

Journal ArticleDOI
TL;DR: The effect of population‐level alcohol control policies on cirrhosis mortality rates in Lithuania is examined – a high‐income European Union country with high levels of alcohol consumption.
Abstract: 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.

5 citations

Posted ContentDOI
20 May 2021-medRxiv
TL;DR: In this article, the authors developed an open-access simulation model to estimate the impact of higher SBIRT delivery rates in German primary health care settings on population-level alcohol consumption.
Abstract: Background Screening, brief intervention and referral to treatment (SBIRT) is a programme to reduce alcohol consumption for drinkers with high alcohol consumption levels. Only 2.9% of patients in primary health care (PHC) are screened for their alcohol use in Germany, despite high levels of alcohol consumption and attributable harm. We developed an open-access simulation model to estimate the impact of higher SBIRT delivery rates in German PHC settings on population-level alcohol consumption. Methods and findings A hypothetical population of drinkers and non-drinkers was simulated by sex, age, and educational status for the year 2009 based on survey and sales data. Risky drinking persons receiving BI or RT were sampled from this population based on screening coverage and other parameters. Running the simulation model for a ten-year period, drinking levels and heavy episodic drinking (HED) status were changed based on effect sizes from meta-analyses. In the baseline scenario of 2.9% screening coverage, 2.4% of the adult German population received a subsequent intervention between 2009 and 2018. If every second PHC patient would have been screened for alcohol use, 21% of adult residents in Germany would have received BI or RT by the end of the ten-year simulation period. In this scenario, population-level alcohol consumption would be 12% lower than it was in 2018, without any impact on HED prevalence. Screening coverage rates below 10% were not found to have a measurable effect on drinking levels. Conclusions Large-scale implementation of SBIRT in PHC settings can yield substantial reductions of alcohol consumption in Germany. As high screening coverage rates may only be achievable in the long run, other effective alcohol policies are required to achieve short-term reduction of alcohol use and attributable harm in Germany. There is large potential to apply this open-access simulation model to other settings and for other alcohol interventions.

5 citations

References
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Journal ArticleDOI
TL;DR: In this paper, the authors provide guidelines, guidelines, and simple rules of thumb to assist the clinician faced with the challenge of choosing an appropriate test instrument for a given psychological assessment.
Abstract: In the context of the development of prototypic assessment instruments in the areas of cognition, personality, and adaptive functioning, the issues of standardization, norming procedures, and the important psychometrics of test reliability and validity are evaluated critically. Criteria, guidelines, and simple rules of thumb are provided to assist the clinician faced with the challenge of choosing an appropriate test instrument for a given psychological assessment. Clinicians are often faced with the critical challenge of choosing the most appropriate available test instrument for a given psychological assessment of a child, adolescent, or adult of a particular age, gender, and class of disability. It is the purpose of this report to provide some criteria, guidelines, or simple rules of thumb to aid in this complex scientific decision. As such, it draws upon my experience with issues of test development, standardization, norming procedures, and important psychometrics, namely, test reliability and validity. As I and my colleagues noted in an earlier publication, the major areas of psychological functioning, in the normal development of infants, children, adolescents, adults, and elderly people, include cognitive, academic, personality, and adaptive behaviors (Sparrow, Fletcher, & Cicchetti, 1985). As such, the major examples or applications discussed in this article derive primarily, although not exclusively, from these several areas of human functioning.

7,254 citations

Journal ArticleDOI
TL;DR: The notion of overfitting is presented in terms of asking too much from the available data, and three common practices—automated variable selection, pretesting of candidate predictors, and dichotomization of continuous variables—are shown to pose a considerable risk for spurious findings in models.
Abstract: OBJECTIVE Statistical models, such as linear or logistic regression or survival analysis, are frequently used as a means to answer scientific questions in psychosomatic research. Many who use these techniques, however, apparently fail to appreciate fully the problem of overfitting, ie, capitalizing on the idiosyncrasies of the sample at hand. Overfitted models will fail to replicate in future samples, thus creating considerable uncertainty about the scientific merit of the finding. The present article is a nontechnical discussion of the concept of overfitting and is intended to be accessible to readers with varying levels of statistical expertise. The notion of overfitting is presented in terms of asking too much from the available data. Given a certain number of observations in a data set, there is an upper limit to the complexity of the model that can be derived with any acceptable degree of uncertainty. Complexity arises as a function of the number of degrees of freedom expended (the number of predictors including complex terms such as interactions and nonlinear terms) against the same data set during any stage of the data analysis. Theoretical and empirical evidence--with a special focus on the results of computer simulation studies--is presented to demonstrate the practical consequences of overfitting with respect to scientific inference. Three common practices--automated variable selection, pretesting of candidate predictors, and dichotomization of continuous variables--are shown to pose a considerable risk for spurious findings in models. The dilemma between overfitting and exploring candidate confounders is also discussed. Alternative means of guarding against overfitting are discussed, including variable aggregation and the fixing of coefficients a priori. Techniques that account and correct for complexity, including shrinkage and penalization, also are introduced.

1,730 citations

Journal ArticleDOI
TL;DR: Although there are many potentially confounding differences between countries, the analysis suggests that the interaction of fiscal austerity with economic shocks and weak social protection is what ultimately seems to escalate health and social crises in Europe.

1,161 citations

Journal ArticleDOI
TL;DR: The results suggest that doubling the alcohol tax would reduce alcohol-related mortality by an average of 35%, traffic crash deaths by 11%, sexually transmitted disease by 6%, violence by 2%, and crime by 1.4%.
Abstract: Objectives. We systematically reviewed the effects of alcohol taxes and prices on alcohol-related morbidity and mortality to assess their public health impact.Methods. We searched 12 databases, along with articles’ reference lists, for studies providing estimates of the relationship between alcohol taxes and prices and measures of risky behavior or morbidity and mortality, then coded for effect sizes and numerous population and study characteristics. We combined independent estimates in random-effects models to obtain aggregate effect estimates.Results. We identified 50 articles, containing 340 estimates. Meta-estimates were r = −0.347 for alcohol-related disease and injury outcomes, −0.022 for violence, −0.048 for suicide, −0.112 for traffic crash outcomes, −0.055 for sexually transmitted diseases, −0.022 for other drug use, and −0.014 for crime and other misbehavior measures. All except suicide were statistically significant.Conclusions. Public policies affecting the price of alcoholic beverages have si...

469 citations

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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