Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States.
Department of Epidemiology & Biostatistics, School of Public Health, Georgia State University, Atlanta, GA, United States.
Drug Alcohol Depend. 2021 Aug 1;225:108761. doi: 10.1016/j.drugalcdep.2021.108761. Epub 2021 May 21.
In the United States, the rate of drug overdose death has more than tripled over the past two decades, a trend that is often attributed to changes in opioid prescribing practices. We developed a novel, longitudinal metric to summarize the relationship between prescription opioid prescribing practices and drug overdose mortality and to assess if longitudinal changes in that relationship differ by characteristics of place.
We constructed a single county-level measure of overdose deaths per 100,000 opioid prescriptions annually from 2006 to 2018. We used latent profile analysis to classify all U.S. counties into classes based on demographic and socioeconomic characteristics and fit a mixed Poisson log-linear model to quantify temporal changes in our measure by county-type classes.
Latent profile analysis resulted in 7 classes with high separation between classes (overall entropy = 0.916). Across all groups, the average number of overdose deaths per opioid prescription remained steady from 2006 to 2011 and increased from 2012-2018. The largest increases were in the high GDP (average annual change: 18.1 %, 95 %CI: 17.5, 18.6) and high education classes (16.6 %, 95 %CI: 16.0, 17.1).
This novel summary metric enhances our understanding of the shift in overdose mortality and the role of geography and place characteristics.
在美国,过去二十年来,药物过量致死率增长了两倍多,这一趋势通常归因于阿片类药物处方实践的改变。我们开发了一种新颖的、纵向的指标来总结处方类阿片类药物的使用与药物过量死亡率之间的关系,并评估这种关系的纵向变化是否因地点特征的不同而有所不同。
我们构建了一个每年每 10 万张处方发生药物过量死亡的单一县级指标,从 2006 年到 2018 年。我们使用潜在剖面分析根据人口统计学和社会经济特征将所有美国县分为不同类别,并拟合混合泊松对数线性模型,以量化我们按县类别的指标的时间变化。
潜在剖面分析导致 7 个类别的分离度很高(总体熵=0.916)。在所有组别中,每例阿片类药物处方的药物过量死亡人数从 2006 年到 2011 年保持稳定,从 2012 年到 2018 年增加。增长最大的是高 GDP 组(平均年增长率:18.1%,95%CI:17.5, 18.6)和高教育组(16.6%,95%CI:16.0, 17.1)。
这种新颖的总结指标增强了我们对药物过量死亡率转变的理解,以及地理和地点特征的作用。