1984-2020年美国个人和人群酒精使用水平的改进估计。

IF 1 Q4 BEHAVIORAL SCIENCES
Charlotte Buckley, Alan Brennan, William C Kerr, Charlotte Probst, Klajdi Puka, Robin C Purshouse, Jürgen Rehm
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引用次数: 1

摘要

目的:虽然具有全国代表性的酒精调查是公共卫生监测的支柱,但它们低估了人口水平的消费量。本文演示了如何使用人均酒精总量(APC)数据调整个人水平的调查数据,以改进个人和人口水平的消费估计。设计和方法:1984-2020年期间,来自美国行为风险因素监测系统(BRFSS)的参与者(18岁以上)过去30天内自我报告的酒精消费数据。使用2005年全国酒精调查数据,每月戒酒者被重新划分为终身戒酒者、前饮酒者和12个月饮酒者。为了纠正酒精使用的覆盖不足,我们根据国家和州一级的酒精使用数据,通过增加酒精使用的数量(平均克数/天)和频率(饮酒天数/周),对APC和调查数据进行了三角测量。结果提供了美国作为一个整体和选定的州代表不同的饮酒模式。调查结果:上述更正改善了调查和APC数据之间的对应关系。按照我们的程序,全国酒精含量估计值从APC估计值的45%增加到77%。饮酒的数量和频率都上升了;通过提高到APC的90%,我们能够适应各州和美国APC模式的趋势和分布。结论:获得了一个更准确地反映美国公民饮酒情况的个人层面数据集。该数据集作为研究工具以及对美国酒精控制政策的规划和评估将是非常宝贵的。所描述的方法也可用于调整其他地理环境中的个人水平酒精调查数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Improved estimates for individual and population-level alcohol use in the United States, 1984-2020.

Improved estimates for individual and population-level alcohol use in the United States, 1984-2020.

Aims: While nationally representative alcohol surveys are a mainstay of public health monitoring, they underestimate consumption at the population level. This paper demonstrates how to adjust individual-level survey data using aggregated alcohol per capita (APC) data for improved individual- and population-level consumption estimates.

Design and methods: For the period 1984-2020, data on self-reported alcohol consumption in the past 30 days were taken from the Behavioral Risk Factor Surveillance System (BRFSS) involving participants (18+ years) in the United States (US). Monthly abstainers were reallocated into lifetime abstainers, former drinkers, and 12-month drinkers using the 2005 National Alcohol Survey data. To correct for under-coverage of alcohol use, we triangulated APC and survey data by upshifting quantity (average grams/day) and frequency (drinking days/week) of alcohol use based on national- and state-level APC data. Results were provided for the US as a whole and for selected states to represent different drinking patterns.

Findings: The corrections described above resulted in improved correspondence between survey and APC data. Following our procedure, national estimates of alcohol quantity increased from 45% to 77% of APC estimates. Both quantity and frequency of alcohol use were upshifted; by upshifting to 90% of APC, we were able to fit trends and distributions in APC patterns for individual states and the US.

Conclusions: An individual-level dataset which more accurately reflects the alcohol use of US citizens was achieved. This dataset will be invaluable as a research tool and for the planning and evaluation of alcohol control policies for the US. The methodology described can also be used to adjust individual-level alcohol survey data in other geographical settings.

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