ArticlePopulation health metrics2010
Statistical modeling of volume of alcohol exposure for epidemiological studies of population health: the US example.
Article in Population health metrics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers, 6 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
88 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- The risk relationships between alcohol consumption, alcohol use disorder and alcohol use disorder mortality: A systematic review and meta-analysis.Addiction (Abingdon, England) · 2024Pooled it
- Alcohol use and burden for 195 countries and territories, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016.Lancet (London, England) · 2018Pooled it
- Sex-Specific Associations Between Alcohol Consumption and Incidence of Hypertension: A Systematic Review and Meta-Analysis of Cohort Studies.Journal of the American Heart Association · 2018Pooled it
- Alcohol consumption as a risk factor for tuberculosis: meta-analyses and burden of disease.The European respiratory journal · 2017Pooled it
- The relationship between different dimensions of alcohol use and the burden of disease-an update.Addiction (Abingdon, England) · 2017Pooled it
- Estimates of alcohol-related oesophageal cancer burden in Japan: systematic review and meta-analyses.Bulletin of the World Health Organization · 2015Pooled it
- Global and regional cancer burden attributable to modifiable risk factors to inform prevention.Nature medicine · 2026Article
- Using a return on investment analysis to estimate the economic impact of potential changes to alcohol control policies in Estonia.European journal of public health · 2026Article
- Defining exposure for estimating the global burden of alcohol consumption: plausibility testing of WHO methodology using ASEAN countries as a case study.Substance abuse treatment, prevention, and policy · 2026Article
- A return on investment analysis for the 2017 increase in alcohol excise taxation in Lithuania.Addiction (Abingdon, England) · 2025Article
- The economic costs of alcohol consumption in Lithuania, 2015-20.European journal of public health · 2025Article
- The role of alcohol control policies in the reversal of alcohol consumption levels and resulting attributable harms in China.Alcohol (Fayetteville, N.Y.) · 2024Review
- Trends of alcohol-attributable deaths in Lithuania 2001-2021: epidemiology and policy conclusions.BMC public health · 2024Article
- Article
- Using Direct and Indirect Estimates for Alcohol-Attributable Mortality: A Modelling Study Using the Example of Lithuania.European addiction research · 2023Article
- Predicting the Impact of Alcohol Taxation Increases on Mortality-A Comparison of Different Estimation Techniques.Alcohol and alcoholism (Oxford, Oxfordshire) · 2022Article
- Impact of introducing a minimum alcohol tax share in retail prices on alcohol-attributable mortality in the WHO European Region: A modelling study.The Lancet regional health. Europe · 2022Article
- Alcohol taxation, alcohol consumption and cancers in Lithuania: A case study.Nordisk alkohol- & narkotikatidskrift : NAT · 2022Article
- An integrated dual process simulation model of alcohol use behaviours in individuals, with application to US population-level consumption, 1984-2012.Addictive behaviors · 2022Article
- Improved estimates for individual and population-level alcohol use in the United States, 1984-2020.International journal of alcohol and drug research · 2022Article
28 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundAlcohol consumption is a major risk factor in the global burden of disease, with overall volume of exposure as the principal underlying dimension. Two main sources of data on volume of alcohol exposure are available: surveys and per capita consumption derived from routine statistics such as taxation. As both sources have significant problems, this paper presents an approach that triangulates information from both sources into disaggregated estimates in line with the overall level of per capita consumption.
methodsA modeling approach was applied to the US using data from a large and representative survey, the National Epidemiologic Survey on Alcohol and Related Conditions. Different distributions (log-normal, gamma, Weibull) were used to model consumption among drinkers in subgroups defined by sex, age, and ethnicity. The gamma distribution was used to shift the fitted distributions in line with the overall volume as derived from per capita estimates. Implications for alcohol-attributable fractions were presented, using liver cirrhosis as an example.
resultsThe triangulation of survey data with aggregated per capita consumption data proved feasible and allowed for modeling of alcohol exposure disaggregated by sex, age, and ethnicity. These models can be used in combination with risk relations for burden of disease calculations. Sensitivity analyses showed that the gamma distribution chosen yielded very similar results in terms of fit and alcohol-attributable mortality as the other tested distributions.
conclusionsModeling alcohol consumption via the gamma distribution was feasible. To further refine this approach, research should focus on the main assumptions underlying the approach to explore differences between volume estimates derived from surveys and per capita consumption figures.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.