Improving Models of Alcohol Consumption Mismeasurement and Burden of Disease

项目摘要/摘要 酒精是许多疾病的诱因，包括许多癌症，而且有证据表明 与酒精相关的疾病会带来巨大的医疗和经济成本 发病率。然而，目前的证据基础存在两个弱点。首先，估计酒精含量- 归因性疾病发病率需要准确测量酒精暴露的流行率，以及 研究人员用来测量酒精暴露流行率的监测数据来源很可能是 容易出错。其次，大多数研究估计酒精引起的疾病发病率和相应的 医疗和经济成本主要集中在事件案例和在没有人参与的情况下可以避免的成本 人们饮酒，这是一个不合理的饮酒减少目标。 这项研究将首先开发一种新的贝叶斯估计方法来解决这两个弱点 来自自我报告调查数据的酒精暴露的流行率，然后将这种方法应用于一种新的 研究以下情况可能对疾病负担和相应经济成本产生的潜在影响 在不同的分组中实现了酒精使用量的适度减少(例如，基于饮酒 频率和人口统计数据)。因此，这项研究将产生有价值的方法学进步和新的 将更好地告知如何最好地采用公共卫生战略，以减少 与饮酒有关的疾病。

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.