Spatio-temporal distribution of influencing factors of cardiovascular disease in the United States - Lou, Wenhui; Zhang, Xiaoqian; Zhang, Yanchun; Wu, Xiangyang; Li, Yongnan; Zhang, Yanhua (Frontiers in Public Health, 2025)
IntroductionCardiovascular disease (CVD) is a major global health issue, contributing significantly to mortality and morbidity worldwide. The American Heart Association highlights primary prevention as a crucial strategy for mitigating the burden of CVD. This research aims to identify essential CVD drivers and support primary prevention efforts.MethodsThis study analyzed data on CVD incidence across 48 states in the United States (US) from 1991 to 2020, using data obtained from the Global Burden of Disease database. To investigate the spatial–temporal heterogeneity and drivers of CVD, we employed Global Moran’s I, hot spot analysis, GeoDetector, and Geographically Weighted Neural Network Weighted Regression (GTNNWR).ResultsGlobal Moran’s I analysis revealed significant clustering (Z-score > 2.58) of CVD rates across regions. The hotspot analysis identified significant clusters in the northeastern US. Factor detection indicated that population density, ambient particulate matter pollution, diet low in fruit, diet low in whole grain, diet high in sodium, and tobacco influenced CVD incidence. In contrast, total GDP was not statistically significant (p > 0.05). Interaction detection demonstrated that factors did not act independently, most interactions exhibited bilinear enhancement [q(X1, X2) > max(q(X1), q(X2))].ConclusionOur article reveals significant spatial clustering of CVD in the US, with population density, air pollution, poor dietary patterns, and smoking emerging as major contributors. The study provides important evidence for designing geographically targeted public health interventions.