Role of walkability, bike infrastructure, and greenspace in combatting chronic diseases: A heterogeneous ecological analysis in the United States

Abstract

Associations of built and natural environment and bike infrastructure features with neighborhood-level hypertension and obesity prevalence across the U.S. are not well explored. Identifying the environmental determinants of neighborhood-level disease prevalence can support community-based nonpharmacologic interventions. Additionally, little is known about the extent of heterogeneity in built and natural environment impacts. Quantifying heterogeneity can help identify places where the greatest health gains can be obtained from infrastructural investments. Using a new neighborhood-level database, we assessed heterogeneous associations of neighborhood built and natural environment and bike infrastructure features with nationwide hypertension and obesity rates using a simultaneous quantile regression framework. A walkability index, access to green space, and bicycle infrastructure were negatively correlated with hypertension and obesity after controlling for social vulnerability. The associations of key environmental and bike infrastructure factors exhibited considerable heterogeneity. For a unit increase in the walkability index, the potential reduction in hypertension prevalence at the 10th percentile was 3.4 times the reduction at the 95th percentile. Likewise, the potential reduction in obesity prevalence at the 10th percentile was 1.8 times the reduction at the 95th percentile. Provision of on-street and off-street bike lanes was correlated with lower hypertension and obesity, although the impacts varied across the quantiles of health outcomes. Urban design policies promoting walkability, providing on-street and off-street bicycle facilities, and enhancing greenspace can be important strategies to combat hypertension and obesity. Our study underscores the importance of incorporating environmental features into future iterations of national disease prevalence data programs in the U.S.