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Open accessJournal ArticleDOI: 10.3390/IJERPH18052419

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

02 Mar 2021-International Journal of Environmental Research and Public Health (MDPI AG)-Vol. 18, Iss: 5, pp 2419
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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Topics: Population (55%), Life expectancy (51%), Psychological intervention (50%)

10 results found

Journal ArticleDOI: 10.1111/ADD.15470
10 Mar 2021-Addiction
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.

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Topics: Mortality rate (55%)

11 Citations

Open accessPosted ContentDOI: 10.1101/2021.04.07.21255080
Alexander Tran1, Jiang H2, Jiang H1, Shannon Lange1  +15 moreInstitutions (10)
10 Apr 2021-medRxiv
Abstract: Aims To determine the effect of an alcohol policy change, which increased the minimum legal drinking age (MLDA) from 18 years of age to 20 years of age on all-cause mortality rates in young adults in Lithuania. Methods An interrupted time series analysis was conducted on a dataset from 2001 to 2019 (n = 228 months). The model tested the effects of the MLDA on all-cause mortality rates (deaths per 100,000 individuals) in 3 age categories (15-17 years old, 18-19 years old, 20-22 years old). Additional models that included GDP as a covariate and taxation policy were tested as well. Results There was a significant effect of the MLDA on all-cause mortality rates in those 18-19 years old, when modelled alone. Additional analyses controlling for the mortality rate of other age groups showed similar findings. Inclusion of confounding factors (policies on alcohol taxation, GDP) eliminated the effects of MLDA. Conclusions Although there was a notable decline in all-cause mortality rates among young adults in Lithuania, a direct causal impact of MLDA on all-cause mortality rates in young adults was not definitively found. Short Summary We investigated the effect of an increase in minimum legal drinking age (MLDA) on all-cause mortality in young adults (aged 18-19). MLDA had a negative effect on all-cause mortality (even when controlling for mortality rates in other age groups), however when confounding factors were included, these effects were attenuated.

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Topics: Mortality rate (53%)

2 Citations

Open accessPosted ContentDOI: 10.1101/2021.03.23.21254181
Jiang H1, Jiang H2, Alexander Tran1, Gerhard Gmel3  +12 moreInstitutions (10)
26 Mar 2021-medRxiv
Abstract: Background Interrupted time series (ITS) are an important tool for determining whether alcohol control policies, as well as other policy interventions, are successful over and above secular trends or chance Subsequent to estimating whether a policy has had an effect, quantifying the key outcomes, such as the number of prevented deaths, is of primary practical importance The current paper compares the results of two different methodological approaches to quantify deaths averted using different two standard populations Methods Time series methodologies were used to estimate the effect size in deaths averted of a substantial increase in excise taxation in Lithuania in 2017 We compare the impact of a) using ITS methodology vs fitting the trend before the intervention to predict the following 12 months and comparing the predicted monthly estimates of deaths with the actual numbers; and b) adjusting the time series either using the World Health Organization standard or the age distribution of Lithuania in the month before the intervention The effect was estimated by sex Results The increase in excise taxation was associated with a substantial decrease in all-cause mortality in all models considered ITS methodology and using the age-distribution of Lithuania were consistently associated with higher estimates of deaths averted Although confidence and prediction intervals were highly overlapping, the point estimates differed substantially The taxation increase was associated with 1,155 deaths averted in the year following the intervention (95% prediction interval: 729, 1,582), corresponding to 280% of all deaths in Lithuania in the respective year, for the model selected as best for planning policy interventions in Lithuania Conclusions Fitting a time series model for the time until the intervention, and then comparing the predicted time points with the actual mortality, standardizing to country-specific weights, was chosen as the best way to derive practically relevant effect sizes

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1 Citations

Open accessPosted ContentDOI: 10.1101/2021.05.10.21256944
Jakob Manthey1, Domantas Jasilionis2, Domantas Jasilionis3, Jiang H4  +6 moreInstitutions (5)
14 May 2021-medRxiv
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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Topics: Alcohol abuse (50%)

Open accessPosted ContentDOI: 10.1101/2021.05.18.21257405
Jakob Manthey1, Adriana Solovei2, Peter J. Anderson3, Sinclair Carr4  +1 moreInstitutions (5)
20 May 2021-medRxiv
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.

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Topics: Brief intervention (65%), Population (52%)


35 results found

Journal ArticleDOI: 10.1037/1040-3590.6.4.284
Domenic V. Cicchetti1Institutions (1)
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.

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Topics: Psychological testing (58%), Test validity (54%), Standardized test (54%) ... read more

6,001 Citations

Journal ArticleDOI: 10.1097/01.PSY.0000127692.23278.A9
Michael A. Babyak1Institutions (1)
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.

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Topics: Overfitting (69%), Statistical model (51%)

1,597 Citations

Journal ArticleDOI: 10.1016/S0140-6736(13)60102-6
13 Apr 2013-The Lancet
Abstract: The financial crisis in Europe has posed major threats and opportunities to health. We trace the origins of the economic crisis in Europe and the responses of governments, examine the effect on health systems, and review the effects of previous economic downturns on health to predict the likely consequences for the present. We then compare our predictions with available evidence for the effects of the crisis on health. Whereas immediate rises in suicides and falls in road traffic deaths were anticipated, other consequences, such as HIV outbreaks, were not, and are better understood as products of state retrenchment. Greece, Spain, and Portugal adopted strict fiscal austerity; their economies continue to recede and strain on their health-care systems is growing. Suicides and outbreaks of infectious diseases are becoming more common in these countries, and budget cuts have restricted access to health care. By contrast, Iceland rejected austerity through a popular vote, and the financial crisis seems to have had few or no discernible effects on health. Although there are many potentially confounding differences between countries, our analysis suggests that, although recessions pose risks to health, the interaction of fiscal austerity with economic shocks and weak social protection is what ultimately seems to escalate health and social crises in Europe. Policy decisions about how to respond to economic crises have pronounced and unintended effects on public health, yet public health voices have remained largely silent during the economic crisis.

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Topics: Austerity (59%), Financial crisis (56%), Public health (56%) ... read more

1,082 Citations

Open accessJournal ArticleDOI: 10.2105/AJPH.2009.186007
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...

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Topics: Population (52%)

421 Citations

Open accessBook
Thad Dunning1Institutions (1)
08 Oct 2012-
Abstract: 1. Introduction: why natural experiments? Part I. Discovering Natural Experiments: 2. Standard natural experiments 3. Regression-discontinuity designs 4. Instrumental-variables designs Part II. Analyzing Natural Experiments: 5. Simplicity and transparency: keys to quantitative analysis 6. Sampling processes and standard errors 7. The central role of qualitative evidence Part III. Evaluating Natural Experiments: 8. How plausible is as-if random? 9. How credible is the model? 10. How relevant is the intervention? Part IV. Conclusion: 11. Building strong research designs through multi-method research.

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395 Citations

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