Association between vehicular emissions and cardiorespiratory disease risk in Brazil and its variation by spatial clustering of socio-economic factors

Many studies have suggested that socio-economic factors are strong modifiers of human vulnerability to air pollution effects. Most of these studies were performed in developed countries, specifically in the US and Europe. Only a few studies have been performed in developing countries, and analyzed small regions (city level) with no spatial disaggregation. The aim of this study was to assess the association between vehicle emissions and cardiorespiratory disease risk in Brazil and its modification by spatial clustering of socio-economic conditions. We used a quantile regression model to estimate the risk and a geostatistical approach (K means) to execute spatial cluster analysis. We performed the risk analysis in three stages. First, we analyzed the entire study area (primary analysis), and then we conducted a spatial cluster analysis based on various municipal-level socio-economic factors, followed by a sensitivity analysis. We studied 5444 municipalities in Brazil between 2008 and 2012. Our findings showed a significant association between cardiorespiratory disease risk and vehicular emissions. We found that a 15% increase in air pollution is associated with a 6% increase in hospital admissions rates. The results from the spatial cluster analysis revealed two groups of municipalities with distinct sets of socio-economic factors and risk levels of cardiorespiratory disease related to exposure to vehicular emissions. For example, for vehicle emissions of PM in 2008, we found a relative risk of 4.18 (95% CI: 3.66, 4.93) in the primary analysis; in Group 1, the risk was 0.98 (95% CI: 0.10, 2.05) while in Group 2, the risk was 5.56 (95% CI: 4.46, 6.25). The risk in Group 2 was 480% higher than the risk in Group 1, and 35% higher than the risk in the primary analysis. Group 1 had higher values (3rd quartile) for urbanization rate, highway density, and GDP; very high values (≥3rd quartile) for population density; median values for distance from the capital; and lower values (1st quartile) for rural population density. Group 2 had lower values (1st quartile) urbanization rate; median values for highway density, GDP, and population density; between median and third quartile values for distance from the capital; and higher values (3rd quartile) for rural population density. Our findings suggest that socio-economic factors are important modifiers of the human risk of cardiorespiratory disease due to exposure to vehicle emissions in Brazil. Our study provides support for creating effective public policies related to environmental health that are targeted to high-risk populations.