Roldós María Isabel
School of Public Health, Universidad San Francisco de Quito, Ecuador
J Drug Educ. 2014;44(1-2):34-50. doi: 10.1177/0047237915573524.
The purpose of this study was to investigate the longitudinal effect of marijuana and heavy alcohol use on the productivity status of nonmetropolitan African American young adults. This analysis was based on secondary data from the Family and Community Health Study. For alcohol, the study evaluated the effects on productivity status for individuals with heavy alcohol use trajectories from adolescence into young adulthood while marijuana effects were evaluated during the period when adolescents are more likely to have initiated usage (14-16 years of age). Productivity status was measured when study participants were between 18 and 21 years, for both alcohol and marijuana. Multivariate logistic regression models were used to test the association between subjects' drug use and productivity. Bivariate analysis of the effects of marijuana use indicate that marijuana users by age 16 are 35% less likely to be productive at age 21 than those who have not initiated marijuana use (p < .005). After controlling for individual, community, and family factors, the multivariate logistic models for alcohol and marijuana use suggest that early adolescence drug use (marijuana and heavy alcohol use) do not have an impact on productivity status during early adulthood. Analyzing and understanding the different drug use trajectories in relation to a productivity outcome is important for policies and research geared to preventing drug use and in identifying its relation with micro- and macro-level labor market outcomes.
本研究的目的是调查大麻和大量饮酒对非都市非裔美国青年成年人生产力状况的纵向影响。该分析基于家庭与社区健康研究的二手数据。对于酒精,研究评估了从青春期到青年期有大量饮酒轨迹的个体对生产力状况的影响,而大麻的影响则在青少年更有可能开始使用大麻的时期(14至16岁)进行评估。当研究参与者年龄在18至21岁之间时,对酒精和大麻的生产力状况进行了测量。使用多变量逻辑回归模型来检验受试者的药物使用与生产力之间的关联。对大麻使用影响的双变量分析表明,到16岁时使用大麻的人在21岁时具有生产力的可能性比未开始使用大麻的人低35%(p <.005)。在控制了个人、社区和家庭因素后,关于酒精和大麻使用的多变量逻辑模型表明,青春期早期的药物使用(大麻和大量饮酒)对成年早期的生产力状况没有影响。分析和理解与生产力结果相关的不同药物使用轨迹,对于旨在预防药物使用以及确定其与微观和宏观层面劳动力市场结果之间关系的政策和研究而言非常重要。