Despite a growing literature for complex air quality models, scientific evidence lacks of the influences of varying exposure assessments and air quality data sources on the estimated mortality risks. This case-crossover study estimated cardiovascular mortality risks from fine particulate matter (PM2.5) and ozone (O3) exposures, using varying exposure methods, to aid understanding of the impact of exposure methods in the health risk estimation. We used individual-level cardiovascular mortality data in the city of Rio de Janeiro, 2012–2016. PM2.5 and O3 exposure levels (from the date of death to seven prior days [lag0–7]) were estimated at the individual level or district level using either the WRF-Chem modeling data or monitoring data, resulting in a total of 10 exposure methods. The exposure-response relationships were estimated using multiple logistic regressions. The changes in cardiovascular mortality were represented as an odds ratio (OR) and 95% confidence intervals (CIs) for an interquartile range (IQR) increase in the exposures. Results showed that socioeconomically more advantaged populations had lower access to the stationary monitoring networks. Higher variance in the estimated exposure levels across the 10 exposure methods was found for PM2.5 than O3. PM2.5 exposure was not associated with mortality risk in any exposure methods. WRF-Chem-based O3 exposure estimated for each individual of the entire population found a significant mortality risk (OR = 1.06, 95% CI: 1.01, 1.11), but not the other exposure methods. Higher risks for females and older populations were suggested for O3 estimates estimated for each individual using the WRF-Chem data. Findings indicate that decisions on exposure methods and data sources can lead to substantially varying implications for air pollution risks and highlight the need for comprehensive exposure and health impact assessments to aid local decision-making for air pollution and public health.
Read full abstract