AIR POLLUTION, POVERTY, AND HEALTH– ASSESSING INEQUITIES IN EXPOSURES AND HEALTH EFFECTS AMONG THE POOR - A CASE STUDY IN HCMC

Abstract:

In cooperation with an initiative of the Asian Development Bank, an interdisciplinary team of local and international experts is assessing the health effects of air pollution among the poor in HCMC. The project has two complementary components – a hospital-based study (discussed here) and a household-based study.

In the hospital study, we estimated the effect of short-term exposure to air pollution on hospital admissions for acute lower respiratory infections (ALRI) in young children in HCMC, and compare the magnitude of the effect of air pollution on poor children vs. other children using routinely collected data from 2003 – 2005. Admissions for ALRI were extracted from computerized records of Children’s Hospitals 1 and 2. HCMC Environmental Protection Agency provided daily, city-level exposure estimates of PM10, O3, NO2, and SO2. Meteorological information was also collected. Analysis was conducted using case-crossover and time-series methodologies. Effect modification by SEP was assessed in the case crossover analysis using individual and group level indicators of SEP. In general, increased concentrations of air pollutants are associated with increased hospital admissions for ALRI in young children of HCMC. Results were consistent across time series and case crossover analyses. Positive associations between PM10 and Ozone and increased ALRI admissions were observed in the dry season, and negative associations were observed in the rainy season. Ozone effects were consistently higher than PM effects. After controlling for the effect of PM10 exposure, increased concentrations of NO2 were associated with increased admissions in both the dry and rainy seasons, although the risk is more pronounced in the dry season. Neither the individual nor the district level analyses of SEP found that short term exposures to air pollution impact children from different socio-economic backgrounds differently. While these analyses did not suggest differential effects by SEP, there are several reasons why data limitations may hinder the ability to find such relationships.

The poor may experience higher actual exposures to air pollution than the non-poor, but this would not be reflected by the ambient monitors used to assess exposure in the hospital study. The objective of the household study is to assess determinants of personal exposure for the poor and non-poor, and to explore whether the use of ambient monitors as a surrogate for personal exposures results in differential exposure misclassification by socio-economic position (SEP). A household survey including detailed questions on household assets and expenditure, as well as the prevalence of chronic respiratory symptoms, was administered to 1000 households in Binh Thanh District and District 2. Based on the results of this survey, primary caregivers of young children (<5) in 64 households (32 from each district) from the lowest and fourth highest expenditure quintiles were selected to participate in the study. Between July 2007 and March 2008, 9 repeated measurements of daily average personal exposures to PM2.5, PM10, NO, and NO2 were made for each participant. Detailed information on exposure to potential sources of pollution, including traffic exposure, incense, cottage industries, and tobacco smoke, as well as time activity patterns, was collected during each measurement period. Personal monitoring equipment was collocated at ambient monitoring stations closest to the two districts to enable a comparison of personal exposures and ambient concentrations. Hypotheses addressed include whether the poor are more exposed to air pollution, and whether the exposures of the poor are more closely linked to ambient air pollution. Preliminary results suggest that personal exposures to PM2.5 do not vary much by district or SEP, although the poor experience slightly higher exposures than the non-poor in District 2. Daily average concentrations of PM2.5 and PM10 appear to be much better correlated with personal exposures of the non-poor than the poor.