Mercer University School of Medicine, Department of Community Medicine, 1250 E 66(th) Street, Savannah, GA 31404, USA.
Johns Hopkins School of Medicine, Departments of Medicine and Pediatrics, Baltimore, MD 21205, USA.
J Subst Use Addict Treat. 2024 Jul;162:209336. doi: 10.1016/j.josat.2024.209336. Epub 2024 Mar 15.
The US opioid epidemic continues to escalate, with overdose deaths being the most-used metric to quantify its burden. There is significant geographic variation in opioid-related outcomes. Rural areas experience unique challenges, yet many studies oversimplify rurality characterizations. Contextual factors, such as area deprivation, are also important to consider when understanding a community's need for treatment services and prevention programming. This study aims to provide a geospatial snapshot of the opioid epidemic in Georgia using several metrics of opioid-related morbidity and mortality and explore differences by rurality across counties.
This was a spatial ecologic study. Negative binominal regression was used to model the relationship of county rurality with four opioid-related outcomes - overdose mortality, emergency department visits, inpatient hospitalizations, and overdose reversals - adjusting for county-level sex, racial/ethnic, and age distributions. Area Deprivation Index was also included.
There was significant geographic variation across the state for all four opioid-related outcomes. Counts remained highest among the metro areas. For rates, counties in the top quartile of rates varied by outcome and were often rural areas. In the final models, rurality designation was largely unrelated to opioid outcomes, with the exception of medium metro areas (inversely related to hospitalizations and overdose reversals) and non-core areas (inversely related to hospitalizations), as compared to large central metro areas. Higher deprivation was significantly related to increased ED visits and hospitalizations, but not overdose mortality and reversals.
When quantifying the burden of the opioid epidemic in a community, it is essential to consider multiple outcomes of morbidity and mortality. Understanding what outcomes are problematic for specific communities, in combination with their demographic and socioeconomic context, can provide insight into gaps in the treatment continuum and potential areas for intervention. Additionally, compared to demographic and socioeconomic factors, rurality may no longer be a salient predictor of the severity of the opioid epidemic in an area.
美国阿片类药物泛滥问题持续升级，过量用药致死人数是衡量其严重程度最常用的指标。阿片类药物相关结果存在显著的地域差异。农村地区面临独特的挑战，但许多研究对农村地区的特征过于简化。在了解社区对治疗服务和预防计划的需求时，背景因素（如区域贫困）也很重要。本研究旨在使用几种阿片类药物相关发病率和死亡率指标，通过各县的农村特征，提供佐治亚州阿片类药物流行情况的地理空间快照，并探讨各县农村特征的差异。
这是一项空间生态学研究。使用负二项回归模型来模拟县农村特征与四种阿片类药物相关结果（过量用药死亡、急诊就诊、住院治疗和过量用药逆转）之间的关系，同时调整了县一级的性别、种族/民族和年龄分布。还包括区域贫困指数。
全州四种阿片类药物相关结果均存在显著的地域差异。发病率最高的仍然是大都市区。对于发病率，排在前四分之一的县因结果而异，且通常是农村地区。在最终模型中，农村特征在很大程度上与阿片类药物结果无关，除了中等规模的大都市地区（与住院和过量用药逆转呈负相关）和非核心地区（与住院治疗呈负相关）与大规模中心大都市地区相比。较高的贫困程度与急诊就诊和住院治疗的增加显著相关，但与过量用药死亡和逆转无关。
在量化社区阿片类药物泛滥的负担时，必须考虑发病率和死亡率的多种结果。了解哪些结果对特定社区存在问题，结合他们的人口统计学和社会经济背景，可以深入了解治疗连续体中的差距和潜在的干预领域。此外，与人口统计学和社会经济因素相比，农村特征可能不再是衡量一个地区阿片类药物泛滥严重程度的重要指标。
