Division of Epidemiology, College of Public Health (J.J.W., J.I.R.), The Ohio State University, Columbus.
Department of Neurology, Wexner Medical Center (J.F.B.), The Ohio State University, Columbus.
Stroke. 2023 Dec;54(12):3128-3137. doi: 10.1161/STROKEAHA.123.043929. Epub 2023 Nov 9.
Both social service resources and stroke prevalence vary by geography, and health care resources are scarcer in rural areas. We assessed whether distributions of resources relevant to stroke survivors were clustered around areas of the highest stroke prevalence in Ohio and whether this is varied by rurality using an ecological study design.
Census tract (CT)-level self-reported stroke prevalence estimates (Centers for Disease Control and Prevention PLACES-2019 Behavioral Risk Factor Surveillance System) were linked with sociodemographic and rurality data (2019 American Community Survey) and geographic density of resources in Ohio (2020 findhelp data). Resources were grouped into categories: housing, in-home, financial, transportation, education, and therapy. Negative binomial regression models estimated the mean number of resources within 25 miles and 30 minutes of a CT centroid and quartiles of stroke prevalence for each resource group by rurality status (rural, urban, and suburban). Models were sequentially adjusted for total population and CT demographics.
In Ohio, stroke prevalence was 3.9% (0.4%-14.2%). The highest stroke prevalence quartile (versus lowest) was associated with fewer resources within 25 miles overall (resource ratio [RR], 0.57-0.98). The most pronounced disparities were in rural CT; rural CTs with the highest quartile stroke prevalence had fewer housing (RR, 0.49 [95% CI, 0.32-0.75]), in-home (RR, 0.31 [95% CI, 0.20-0.49]), and therapy (RR, 0.23 [95% CI, 0.13-0.43]) resources compared with those with the lowest quartile stroke prevalence (reference: mean, 1.2 housing, 5.1 in-home, and 4.9 therapy resources, respectively). Rural disparities no longer persisted after adjustment for federal poverty limit (rural: housing [RR, 0.69 (95% CI, 0.40-1.20)], in-home [RR, 0.65 (95% CI, 0.34-1.23)], and therapy [RR, 0.66 (95% CI, 0.33-1.32)]).
Stroke social service resources are inversely distributed relative to stroke prevalence in Ohio, particularly in rural areas. This inverse link in rural Ohio is likely explained by geographic differences in poverty. Stroke-specific resource-related interventions may be needed and should consider the roles of rurality and poverty.
社会服务资源和中风患病率因地理位置而异,农村地区的医疗保健资源更为稀缺。我们使用生态研究设计评估了俄亥俄州资源分布是否与中风患病率最高的地区相关联,以及这种分布是否因农村地区而异。
将普查区(CT)级别的自我报告中风患病率估计数(疾病控制和预防中心 PLACES-2019 行为风险因素监测系统)与社会人口统计学和农村地区数据(2019 年美国社区调查)以及俄亥俄州的地理资源密度(2020 年 findhelp 数据)相关联。资源分为以下几类:住房、家庭内、财务、交通、教育和治疗。使用负二项回归模型,根据农村、城市和郊区的农村地区状况,估算了每个资源组在 CT 质心 25 英里和 30 分钟内的资源数量的平均值,以及每个资源组的中风患病率的四分位数。模型依次按总人口和 CT 人口统计学进行调整。
在俄亥俄州,中风患病率为 3.9%(0.4%-14.2%)。最高中风患病率四分位数(与最低四分位数相比)与 25 英里范围内的资源总数较少相关(资源比 [RR],0.57-0.98)。最明显的差异存在于农村 CT 中;中风患病率最高的农村 CT 拥有的住房(RR,0.49 [95% CI,0.32-0.75])、家庭内(RR,0.31 [95% CI,0.20-0.49])和治疗(RR,0.23 [95% CI,0.13-0.43])资源少于中风患病率最低的 CT(参考值:平均分别为 1.2 个住房、5.1 个家庭内和 4.9 个治疗资源)。调整联邦贫困线后,农村地区的差异不再持续(农村地区:住房 [RR,0.69(95% CI,0.40-1.20])、家庭内 [RR,0.65(95% CI,0.34-1.23])和治疗 [RR,0.66(95% CI,0.33-1.32]))。
俄亥俄州的中风社会服务资源与中风患病率呈负相关,特别是在农村地区。俄亥俄州农村地区这种负相关关系可能是由贫困的地理差异造成的。可能需要针对特定中风的资源相关干预措施,并且应该考虑农村地区和贫困的作用。