Improving Models of Alcohol Consumption Mismeasurement and Burden of Disease

改进酒精消耗误测和疾病负担的模型

基本信息

批准号：
10245253
负责人：
Arnie Paul Aldridge
金额：
$ 25.84万
依托单位：
RESEARCH TRIANGLE INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-05 至 2023-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10245253
关键词：
Abstinence Address Adopted Adoption Alcohol consumption Alcohols Bayesian Method Bayesian Modeling Benchmarking Consumption Cost of Illness Data Data Sources Disease Epidemiology Exhibits Female Frequencies Gold Health Health Policy Health Resources Incidence Intervention Knowledge Lead Malignant Neoplasms Measurement Measures Medical Care Costs Methodology Methods Modeling Outcome Patient Self-Report Pattern Policies Population Prevalence Principal Investigator Public Health Publications Publishing Research Research Methodology Research Personnel Respondent Risk Sales Source Specific qualifier value Subgroup Surveys Techniques Testing Work alcohol epidemiology alcohol exposure alcohol measurement base burden of illness cost demographics drinking economic cost evidence base experience flexibility improved male malignant breast neoplasm national surveillance novel reduced alcohol use surveillance data

项目摘要

PROJECT SUMMARY/ABSTRACT Alcohol is a contributing factor for a number of diseases, including many cancers, and evidence suggests that there are substantial medical and economic costs associated with alcohol-attributable disease incidence. However, the current evidence base suffers from two weaknesses. First, estimating alcohol- attributable disease incidence requires accurate measurements of the prevalence of alcohol exposures, and the surveillance data sources researchers use to measure the prevalence of alcohol exposures are likely error prone. Second, most studies that estimate alcohol-attributable disease incidence and corresponding medical and economic costs focus on the incident cases and costs that could be avoided if no one in the population consumed alcohol, which is an unreasonable alcohol reduction target. This study will address these two weaknesses by first developing a new, Bayesian approach for estimating the prevalence of alcohol exposures from self-report survey data and then applying this approach to a novel study of the potential impacts on burden of illness and corresponding economic costs that could occur if modest reductions in alcohol use were achieved across different subgroups (e.g., based on drinking frequencies and demographics). Thus, this study will produce valuable methodological advances and new evidence that will better inform how best to adopt public health strategies for reducing the burden and cost of illness associated with alcohol use.

项目摘要/摘要酒精是许多疾病的促成因素，包括许多癌症，证据表明与酒精归因疾病有关的大量医疗和经济成本发病率。但是，当前的证据基础遭受了两个弱点。首先，估计酒精 - 可归因于疾病的发生率需要准确测量酒精暴露率，并且研究人员用来衡量酒精暴露率的监视数据可能是容易出错。第二，大多数研究估计可饮酒的疾病发生率和相应的研究医疗和经济成本集中在事件案件和成本上，如果没有人人口消耗酒精，这是一个不合理的减少酒精靶标。这项研究将通过首先开发一种估算新的贝叶斯方法来解决这两个弱点从自我报告调查数据中酒精暴露的普遍性，然后将这种方法应用于新颖研究对疾病负担的潜在影响以及可能发生的相应经济成本的影响在不同的亚组中实现了适度的饮酒（例如，基于饮酒）频率和人口统计学）。因此，这项研究将产生有价值的方法论进步和新可以更好地告知如何最好地采用公共卫生策略来减轻负担和成本的证据与饮酒有关的疾病。