High-Intensity Drinking over the Life Course: Identifying High-Risk Subgroups through Event-based and Population-Based Approaches

生命历程中的高强度饮酒：通过基于事件和基于人群的方法识别高风险亚组

• 批准号: 10583491
• 负责人: Camillia K. Lui
• 金额: $ 17.72万
• 依托单位: PUBLIC HEALTH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 1981
• 资助国家: 美国
• 起止时间: 1981-07-01 至 2026-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10583491
• 关键词: Acute; Adult; Age; Alcohol abuse; Alcohol consumption; Alcoholic beverage heavy drinker; Alcohols; American; Attention; Beverages; Birth; Blood alcohol level measurement; Characteristics; Clinical; Cohort Effect; Consumption; Data; Development; Disparity; Disparity population; Early Intervention; Education; Elderly; Emergency department visit; Ensure; Epidemiology; Ethnic Origin; Event; Family history of; Future; Gender; General Population; Goals; Guidelines; Individual; Intake; Intervention; Knowledge; Life Cycle Stages; Location; Machine Learning; Measurement; Methodology; Mission; Modeling; National Institute on Alcohol Abuse and Alcoholism; Online Systems; Outcome; Pattern; Persons; Population; Prevalence; Prevention strategy; Public Health; Race; Recording of previous events; Recovery; Reporting; Research; Research Project Grants; Risk; Risk Assessment; Risk Estimate; Risk Factors; Sampling; Series; Shapes; Socioeconomic Factors; Statistical Methods; Subgroup; Surveys; Time trend; Woman; Work; adverse outcome; alcohol epidemiology; alcohol measurement; alcohol poisoning; alcohol related problem; alcohol use disorder; binge drinking; cohort; design; diaries; drinking; early screening; ethnic minority; high intensity drinking; high risk; high risk population; improved; machine learning method; machine learning model; men; middle age; population based; preference; protective factors; public health relevance; racial minority; response; social disparities; theories; translational impact; treatment strategy; trend; young adult

ABSTRACT: High-Intensity Drinking over the Life Course: Identifying high-risk subgroups through event-based and population-based approaches Binge or heavy episodic drinking (HED) of ≥4/ ≥5 drinks for women/men in a single occasion or day has been a key marker of harmful drinking in general and clinical populations and has been widely used in alcohol epidemiology to capture the public health burden from alcohol use. Yet critics have raised the issue that the HED threshold fails to capture the impact of high-intensity drinking (HID) and implies the same average risks to all heavy drinkers regardless of whether they consume 5 or 15 drinks. Recent studies have raised attention to HID of consuming double (8+/10+ drinks) or even triple (12+/15+ drinks) the HED amount. As amounts per day reach extreme levels, risks for consequences and alcohol use disorders (AUD) increase greatly, even when average intake remains the same. This proposed Center project will trace trends in harmful drinking patterns with special attention to HID occurrence and rates over a 40-year period, identify a range of alcohol-related precursors and problems through event-based and population-based approaches, and situate harmful patterns within contexts to inform early screening and interventions for high-risk groups. We will employ sophisticated statistical methods to examine associations and consequences involved with HED and HID, using two adult general population and two heavy drinker event-based samples, each type of data designed to generate complementary and new knowledge about HID. We carry forward ARG's rich history in alcohol epidemiology and measurement expertise, and the Center mission to reduce alcohol-related disparities, in all our study aims. In response to NIAAA's priorities, and to ensure direct translational impact of study findings, we incorporate specific theory and practice for each study aim. Our definitions of HED/HID include both threshold (5+, 8+ and 12+) and amounts drunk in any day (from 5-7, 8-11, and 12+ drinks). Aim 1 takes a life course perspective to document harmful drinking trends over time from 1984 to 2024 and by priority groups (e.g., women; middle-aged to older adults; socially disadvantaged groups including racial/ethnic minorities and those with lower education; and people with history of AUD treatment or in recovery). Aim 2 characterizes event-level factors that heighten the risks for HID compared to HED levels. Sensitivity analyses will compare whether adjustments for drink size/strength and drinking rate (estimated BAC) will improve accuracy of how HID predict alcohol problems (e.g., AUD). Aim 3 situates harmful drinking patterns involving HID within the socioecological model to examine risk and protective factors both currently and across the life course that are strongly associated with HID. Also in Aim 3 we assess the extent that HID elevates the public health burden of AUD and other problems above that of HED and non-HED levels for all drinkers and priority groups using risk models and machine learning methods. Study findings will help identify key population subgroups and risk/protective factors that can support future development of targeted interventions at the event, individual, and environmental levels to reduce heavy and high-intensity drinking and their associated consequences.

摘要：生活课程中的高强度饮酒：通过 基于事件和基于人群的方法 在一次或一天中，男女的暴饮暴食或大量饮酒（HED）≥4/≥5次饮料 一般饮酒的关键标志和临床人群的主要标记，已被广泛用于酒精 流行病学以捕获饮酒中的公共卫生燃烧。然而，批评提出了陷入困境的问题 阈值无法捕获高强度饮酒的影响（HID），并暗示与所有人相同的平均风险 重量饮酒者无论食用5饮料还是15杯。最近的研究引起了人们对HID的关注 消耗双重（8+/10+饮料），甚至三倍（12+/15+饮料）的HED量。每天的金额达到 极端水平，后果和酒精使用障碍的风险（AUD）大大增加，即使平均 进气保持不变。这个拟议的中心项目将通过特殊的有害饮酒方式追踪趋势 注意HID发生和40年期间的HID发生率，确定一系列与酒精相关的前体和 通过基于事件和基于人群的方法进行问题，并将有害模式放在上下文中 为高危群体提供早期筛查和干预措施。我们将采用复杂的统计数据 使用两个成人一般的方法来检查与HED和HID有关的关联和后果的方法 种群和两个基于事件的重型饮酒样品，每种类型的数据旨在生成 关于HID的补充和新知识。我们推进Arg在酒精流行病学方面的悠久历史 在我们所有的研究中，测量专业知识以及减少与酒精有关的差异的中心使命。 为了响应NIAAA的优先事项，并确保研究结果的直接翻译影响，我们合并了 每个研究目标的具体理论和实践。我们对HED/HID的定义包括阈值（5+，8+和 12岁以上），任何一天（从5-7、8-11和12+饮料）喝醉了。 AIM 1具有生命课程的观点 记录1984年至2024年和优先组的有害饮酒趋势（例如，妇女；中年 给老年人；包括种族/族裔少数群体和受教育程度较低的社会困扰的团体； 以及有AUD治疗史或康复史的人。目标2个字符的事件级因素增加 与HED水平相比，HID的风险。敏感性分析将比较是否进行饮料调整 大小/强度和饮酒率（估计的BAC）将提高隐藏酒精问题的准确性（例如， 奥德）。目标3情况有害饮酒模式，涉及藏在社会生态模型中以检查风险 以及当前和整个生命过程中的受保护因素与HID密切相关。也是目标 3我们评估了隐藏aud的公共卫生燃烧和其他问题的程度 使用风险模型和机器学习方法的所有饮酒者和优先组的HED和非HED水平。 研究结果将有助于确定可以支持未来的关键人群亚组和风险/保护因素 在活动，个人和环境水平上开发有针对性的干预措施，以减少重量和 高强度饮酒及其相关后果。