Mapping distance-decay of cardiorespiratory disease risk related to neighborhood environments

Neighborhood characteristics affect an individual's quality of life. Although several studies have examined the relationship between neighborhood environments and human health, we are unaware of studies that have examined the distance-decay of this effect and then presented the risk results spatially. Our study is unique in that is explores the health effects in a less developed country compared to most studies that have focused on developed countries. The objective of our study is to quantify the distance-decay cardiorespiratory diseases risk related to 28 neighborhood aspects in the Federal District, Brazil and present this information spatially through risk maps of the region. Toward this end, we used a quantile regression model to estimate risk and GIS modeling techniques to create risk maps. Our analysis produced the following findings: i) a 2500 m increase in highway length was associated with a 46% increase in cardiorespiratory diseases; ii) 46,000 light vehicles in circulation (considering a buffer of ≤500 m from residences) was associated with 6 hospital admissions (95% CI: 2.6, 14.6) per cardiorespiratory diseases; iii) 74,000 m2 of commercial areas (buffer ≤1700 m) was associated with 12 hospital admissions (95% CI: 2.2, 20.8); iv) 1 km2 increase in green areas intra urban was associated with less two hospital admissions, and; vi) those who live ≤500 m from the nearest point of wildfire are more likely to have cardiorespiratory diseases that those living >500 m. Our findings suggest that the approach used in this study can be an option to improve the public health policies.