Association of PM2.5 Exposure and Health Outcomes in a Representative Population Sample of the Mexico City Metropolitan Area Using Satellite and Monitor-Based Exposure Estimations

摘要

BACKGROUND: Air pollution is a key global public health challenge. The Mexico City Metropolitan Area (MCMA), a megalopolis of 23 million people, exceeds the WHO's recommendation for the annual average of PM2.5 level. AIM: To estimate the association of PM2.5 exposure and acute respiratory tract symptoms (ARTS) in children, and with ischemic heart disease (IHD) and hypertension (HT) in adults, in a representative sample of the MCMA population. METHODS: Participant health information was obtained from the National Survey of Health and Nutrition 2006 and 2012. Exposure to PM2.5 was estimated using 1, 3, 7, 14, 30 and 365-day averages before day-of-interview from the city monitoring network (MNW) and a satellite-based model (SM). We used logistic regression models, adjusted for age, sex and socio-economic status considering the sampling design RESULTS: The sample represented 3.1 and 3.6 million children and 12.7 and 13.8 million adults in 2006 and 2012, respectively. Annual PM2.5 estimation was higher using MNW vs SM (SM: 2006: 25.9; 2012: 24.8 pg/m3 vs MNW 2006: 29.0; 2012: 26.7 ug/m3). We saw decreased annual averages with both estimation methods, but they both double the Mexican standards. We found a positive association between 2-week PM2.5 exposure and ARTS, with both exposure methods, statistically significant in 2006 using the MNW (OR: 1.46, 95%CI: 1.00-2.15. Positive associations with IHD and previous year exposure were estimated using MNW, however they were non-significant for both surveys. The results using SM were inconclusive. For HT and previous year exposure, we observed a positive association using SM in both surveys, significant for 2012 (OR: 2.54; 95%CI: 1.12-5.77). The estimates using MNW were inconclusive. CONCLUSIONS: There were positive associations between PM2.5 exposure and acute and chronic diseases. For acute outcomes, MNW estimations seems to better capture the daily variability in PM2.5, whereas for chronic diseases both methods can be useful.