背景:酒精营销暴露之间的关系,酒精使用,和购买已经被广泛研究。然而,使用移动健康工具在现实环境中考察因果关系的前瞻性研究是有限的.
目的:我们使用生态瞬时评估(EMA)来检查酒精营销暴露对任何酒精使用的人内和人之间的影响,酒精使用量,任何酒精购买,以及大学生购买酒精的频率。
方法:从2020年1月至6月,我们通过EMA在报告当前饮酒的香港大学生中进行了一项前瞻性队列研究。连续14天,每个参与者完成5个固定间隔,每天通过智能手机应用程序向EMA发送信号。每个EMA都询问了酒精营销暴露的数量和类型,使用的酒精的数量和类型,以及是否购买了酒精,都在过去3小时内。我们使用了两部分模型,包括多级逻辑回归和多级伽马回归,检查酒精营销暴露的数量是否与随后的酒精使用和酒精购买有关。
结果:共有49名学生参加,33%(16/49)是男性。平均年龄为22.6(SD2.6)岁。他们完成了2360个EMA(完成率:2360/3430,68.8%)。参与者报告接触酒精营销的比例为5.9%(140/2360),酒精使用率为6.1%(145/2360),和酒精购买占所有EMA的2.4%(56/2360)。在人与人之间,暴露于更多的酒精营销预测第二天使用酒精的可能性更高(调整后的奇数比[AOR]=3.51,95%CI1.29-9.54),购买酒精的可能性更高(AOR=4.59,95%CI1.46-14.49).接触更多的酒精营销并没有增加使用或购买酒精的参与者第二天的酒精使用量或酒精购买频率。在个人层面,接触更多的酒精营销与更高的饮酒可能性无关,酒精使用量,购买酒精的可能性更高,或第二天购买酒精的频率(所有Ps>0.05)。在1周内每增加一次酒精营销,就会预测下一周酒精饮料的消费量增加0.85(调整后的B=0.85,95%CI0.09-1.61)。在报告饮酒的日子里,3项酒精营销接受度指标与更多酒精使用或购买无关(所有P>.05).
结论:通过使用EMA,我们提供了第一个证据,证明酒精营销暴露对当前饮酒大学生开始饮酒和饮酒的影响.我们的发现为减少年轻人的酒精使用和购买提供了酒精营销监管的证据。
BACKGROUND: The relationships between alcohol marketing exposure, alcohol use, and purchase have been widely studied. However, prospective studies examining the causal relationships in real-world settings using mobile health tools are limited.
OBJECTIVE: We used ecological momentary assessment (EMA) to examine both the within-person- and between-person-level effects of alcohol marketing exposure on any alcohol use, amount of alcohol use, any alcohol purchase, and frequency of alcohol purchase among university students.
METHODS: From January to June 2020, we conducted a prospective cohort study via EMA among university students in Hong Kong who reported current drinking. Over 14 consecutive days, each participant completed 5 fixed-interval, signal-contingent EMAs daily via a smartphone app. Each EMA asked about the number and types of alcohol marketing exposures, the amount and types of alcohol used, and whether any alcohol was purchased, all within the past 3 hours. We used 2-part models, including multilevel logistic regressions and multilevel gamma regressions, to examine if the number of alcohol marketing exposure was associated with subsequent alcohol use and alcohol purchase.
RESULTS: A total of 49 students participated, with 33% (16/49) being male. The mean age was 22.6 (SD 2.6) years. They completed 2360 EMAs (completion rate: 2360/3430, 68.8%). Participants reported exposure to alcohol marketing in 5.9% (140/2360), alcohol use in 6.1% (145/2360), and alcohol purchase in 2.4% (56/2360) of all the EMAs. At the between-person level, exposure to more alcohol marketing predicted a higher likelihood of alcohol use (adjusted odd ratio [AOR]=3.51, 95% CI 1.29-9.54) and a higher likelihood of alcohol purchase (AOR=4.59, 95% CI 1.46-14.49) the following day. Exposure to more alcohol marketing did not increase the amount of alcohol use or frequency of alcohol purchases the following day in participants who used or purchased alcohol. At the within-person level, exposure to more alcohol marketing was not associated with a higher likelihood of alcohol use, amount of alcohol use, higher likelihood of alcohol purchase, or frequency of alcohol purchases the following day (all Ps>.05). Each additional exposure to alcohol marketing within 1 week predicted an increase of 0.85 alcoholic drinks consumed in the following week (adjusted B=0.85, 95% CI 0.09-1.61). On days of reporting alcohol use, the 3 measures for alcohol marketing receptivity were not associated with more alcohol use or purchase (all Ps>.05).
CONCLUSIONS: By using EMA, we provided the first evidence for the effect of alcohol marketing exposure on initiating alcohol use and purchase in current-drinking university students. Our findings provide evidence of the regulation of alcohol marketing for the reduction of alcohol use and purchase among young adults.