Department of Epidemiology, University of Florida, Gainesville, Florida, USA.
Division of Infectious Diseases, University of Miami, Miami, Florida, USA.
Alcohol Clin Exp Res. 2021 Sep;45(9):1804-1811. doi: 10.1111/acer.14665. Epub 2021 Aug 2.
Transdermal alcohol biosensors can objectively monitor alcohol use by measuring transdermal alcohol concentration (TAC). However, it is unclear how sociodemographic and clinical factors that influence alcohol metabolism are associated with TAC. The main aim of this study was to examine how sociodemographic factors (sex, age, race/ethnicity) and clinical factors (body mass index, liver enzymes: alanine aminotransferase [ALT] and aspartate transaminase [AST]), alcohol use disorder, and HIV status were associated with TAC while controlling for level of alcohol use.
We analyzed data from a prospective study involving contingency management for alcohol cessation among persons living with and without human immunodeficiency virus (HIV) that used the Secure Continuous Remote Alcohol Monitoring (SCRAM) biosensor. Forty-three participants (M = 56.6 years; 63% male; 58% people living with HIV) yielded 183 SCRAM-detected drinking days. Two indices derived from SCRAM: peak TAC (reflecting level of intoxication) and TAC area under the curve (TAC-AUC; reflecting alcohol volume)-were the main outcomes. Self-reported alcohol use (drinks/drinking day) measured by Timeline Followback was the main predictor. To examine whether factors of interest were associated with TAC, we used individual generalized estimating equations (GEE), followed by a multivariate GEE model to include all significant predictors to examine their associations with TAC beyond the effect of self-reported alcohol use.
Number of drinks per drinking day (B = 0.29, p < 0.01) and elevated AST (B = 0.50, p = 0.01) were significant predictors of peak TAC. Positive HIV status, female sex, elevated AST, and number of drinks per drinking day were positively associated with TAC-AUC at the bivariate level, whereas only self-reported alcohol use (B = 0.85, p < 0.0001) and female sex (B = 0.67, p < 0.05) were significant predictors of TAC-AUC at the multivariate level.
HIV status was not independently associated with TAC. Future studies should consider the sex and liver function of the participant when using alcohol biosensors to measure alcohol use.
经皮酒精生物传感器可通过测量经皮酒精浓度(TAC)客观监测酒精使用情况。然而,目前尚不清楚影响酒精代谢的社会人口学和临床因素与 TAC 有何关联。本研究的主要目的是在控制饮酒量的情况下,研究社会人口学因素(性别、年龄、种族/民族)和临床因素(体重指数、肝酶:丙氨酸氨基转移酶[ALT]和天冬氨酸氨基转移酶[AST])、酒精使用障碍和 HIV 状态与 TAC 的关系。
我们分析了一项涉及使用安全持续远程酒精监测(SCRAM)生物传感器对艾滋病毒感染者和非感染者进行酒精戒断的条件性管理的前瞻性研究的数据。43 名参与者(M=56.6 岁;63%为男性;58%为艾滋病毒感染者)提供了 183 个 SCRAM 检测到的饮酒日。SCRAM 得出的两个指标:峰值 TAC(反映醉酒程度)和 TAC 曲线下面积(TAC-AUC;反映酒精量)是主要结果。使用 Timeline Followback 测量的自我报告饮酒量(饮酒量/饮酒日)是主要预测因子。为了检查感兴趣的因素是否与 TAC 相关,我们使用了个体广义估计方程(GEE),然后使用多元 GEE 模型纳入所有显著预测因子,以检查它们与 TAC 的关联,而不仅仅是自我报告饮酒量的影响。
每日饮酒量(B=0.29,p<0.01)和升高的 AST(B=0.50,p=0.01)是峰值 TAC 的显著预测因子。阳性 HIV 状态、女性、AST 升高和每日饮酒量与 TAC-AUC 在双变量水平上呈正相关,而只有自我报告的饮酒量(B=0.85,p<0.0001)和女性(B=0.67,p<0.05)是 TAC-AUC 的多变量水平上的显著预测因子。
HIV 状态与 TAC 无独立相关性。未来的研究在使用酒精生物传感器测量酒精使用情况时,应考虑参与者的性别和肝功能。