Hipp J Aaron, Chalise Nishesh
Brown School, Washington University in St Louis, Campus Box 1196, One Brookings Dr, St Louis, MO 63130. Email:
Brown School, Washington University in St. Louis, St. Louis, Missouri.
Prev Chronic Dis. 2015 Jan 22;12:E08. doi: 10.5888/pcd12.140404.
Information on the relationship between diabetes prevalence and built environment attributes could allow public health programs to better target populations at risk for diabetes. This study sought to determine the spatial prevalence of diabetes in the United States and how this distribution is associated with the geography of common diabetes correlates.
Data from the Centers for Disease Control and Prevention and the US Census Bureau were integrated to perform geographically weighted regression at the county level on the following variables: percentage nonwhite population, percentage Hispanic population, education level, percentage unemployed, percentage living below the federal poverty level, population density, percentage obese, percentage physically inactive, percentage population that cycles or walks to work, and percentage neighborhood food deserts.
We found significant spatial clustering of county-level diabetes prevalence in the United States; however, diabetes prevalence was inconsistently correlated with significant predictors. Percentage living below the federal poverty level and percentage nonwhite population were associated with diabetes in some regions. The percentage of population cycling or walking to work was the only significant built environment-related variable correlated with diabetes, and this association varied in magnitude across the nation.
Sociodemographic and built environment-related variables correlated with diabetes prevalence in some regions of the United States. The variation in magnitude and direction of these relationships highlights the need to understand local context in the prevention and maintenance of diabetes. Geographically weighted regression shows promise for public health research in detecting variations in associations between health behaviors, outcomes, and predictors across geographic space.
有关糖尿病患病率与建成环境属性之间关系的信息，可使公共卫生项目更好地针对糖尿病高危人群。本研究旨在确定美国糖尿病的空间患病率，以及这种分布与常见糖尿病相关因素的地理情况之间的关联。
整合了美国疾病控制与预防中心以及美国人口普查局的数据，以在县一级对以下变量进行地理加权回归分析：非白人人口百分比、西班牙裔人口百分比、教育水平、失业率、生活在联邦贫困线以下的人口百分比、人口密度、肥胖百分比、身体不活动的百分比、骑自行车或步行上班的人口百分比，以及邻里食物匮乏地区的百分比。
我们发现美国县级糖尿病患病率存在显著的空间聚集现象；然而，糖尿病患病率与显著预测因素之间的相关性并不一致。在某些地区，生活在联邦贫困线以下的人口百分比和非白人人口百分比与糖尿病有关。骑自行车或步行上班的人口百分比是唯一与糖尿病相关的显著建成环境变量，且这种关联在全国范围内的程度有所不同。
社会人口统计学和与建成环境相关的变量在美国某些地区与糖尿病患病率相关。这些关系在程度和方向上的差异凸显了在糖尿病预防和管理中了解当地情况的必要性。地理加权回归在检测健康行为、结果和预测因素在地理空间上的关联差异方面，对公共卫生研究具有前景。
