School of Public Health, Fujian Medical University, Fuzhou 350108, China.
Menzies School of Health Research, Royal Darwin Hospital Campus, Tiwi, NT 0810, Australia.
Int J Environ Res Public Health. 2023 Jan 31;20(3):2581. doi: 10.3390/ijerph20032581.
Many studies on the relationship between alcohol and health outcome focus primarily on average consumption over time and do not consider how heavy per-occasion drinking may influence apparent relationships. Improved methods concerning the most recent drinking occasion are essential to inform the extent of alcohol-related health problems. We aimed to develop a user-friendly and readily replicable computational model that predicts: (i) an individual's probability of consuming alcohol ≥2, 3, 4… drinks; and (ii) the total number of days during which consumption is ≥2, 3, 4… drinks over a specified period. Data from the 2010 and 2011 National Survey on Drug Use and Health (NSDUH) were used to develop and validate the model. Predictors used in model development were age, gender, usual number of drinks consumed per day, and number of drinking days in the past 30 days. Main outcomes were number of drinks consumed on the last drinking occasion in the past 30 days, and number of days of risky levels of consumption. The area under ROC curves ranged between 0.86 and 0.91 when predicting the number of drinks consumed. Coefficients were very close to 1 for all outcomes, indicating closeness between the predicted and observed values. This straightforward modelling approach can be easily adopted by public health behavioral studies.
许多关于酒精与健康结果之间关系的研究主要集中在一段时间内的平均饮酒量上，而没有考虑单次大量饮酒可能如何影响明显的关系。改进关于最近一次饮酒的最新方法对于了解与酒精相关的健康问题的程度至关重要。我们旨在开发一种用户友好且易于复制的计算模型，该模型可以预测：(i)个体摄入≥2、3、4...杯酒的概率；以及 (ii)在特定时间段内摄入≥2、3、4...杯酒的天数。该模型使用了 2010 年和 2011 年国家药物使用与健康调查 (NSDUH) 的数据进行开发和验证。模型开发中使用的预测因子包括年龄、性别、每天通常饮用的饮料数量以及过去 30 天的饮酒天数。主要结果是过去 30 天内最后一次饮酒时摄入的饮料数量以及摄入高风险水平的天数。当预测摄入的饮料数量时，ROC 曲线下的面积在 0.86 到 0.91 之间。对于所有结果，系数都非常接近 1，表明预测值与观察值之间的接近程度。这种简单直接的建模方法可以很容易地被公共卫生行为研究采用。
