• HEI Collaborative Working Group on Air Pollution, Poverty, and Health in Ho Chi Minh City, Truong Giang Le, Long Ngo, Sumi Mehta, Van Dzung Do, T Q Thach, Xuan Dan Vu, Dinh Tuan Nguyen, and Aaron Cohen.
• Department of Public Health, Vietnam.
• Res Rep Health Eff Inst. 2012 Jun 1(169):5-72; discussion 73-83.

AbstractThere is emerging evidence, largely from studies in Europe and North America, that economic deprivation increases the magnitude of morbidity and mortality related to air pollution. Two major reasons why this may be true are that the poor experience higher levels of exposure to air pollution, and they are more vulnerable to its effects--in other words, due to poorer nutrition, less access to medical care, and other factors, they experience more health impact per unit of exposure. The relations among health, air pollution, and poverty are likely to have important implications for public health and social policy, especially in areas such as the developing countries of Asia where air pollution levels are high and many live in poverty. The aims of this study were to estimate the effect of exposure to air pollution on hospital admissions of young children for acute lower respiratory infection (ALRI*) and to explore whether such effects differed between poor children and other children. ALRI, which comprises pneumonia and bronchiolitis, is the largest single cause of mortality among young children worldwide and is responsible for a substantial burden of disease among young children in developing countries. To the best of our knowledge, this is the first study of the health effects of air pollution in Ho Chi Minh City (HCMC), Vietnam. For these reasons, the results of this study have the potential to make an important contribution to the growing literature on the health effects of air pollution in Asia. The study focused on the short-term effects of daily average exposure to air pollutants on hospital admissions of children less than 5 years of age for ALRI, defined as pneumonia or bronchiolitis, in HCMC during 2003, 2004, and 2005. Admissions data were obtained from computerized records of Children's Hospital 1 and Children's Hospital 2 (CH1 and CH2) in HCMC. Nearly all children hospitalized for respiratory illnesses in the city are admitted to one of these two pediatric hospitals. Daily citywide 24-hour average concentrations of particulate matter (PM) < or =10 microm in aerodynamic diameter (PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2) and 8-hour maximum average concentrations of ozone (O3) were estimated from the HCMC Environmental Protection Agency (HEPA) ambient air quality monitoring network. Daily meteorologic information including temperature and relative humidity were collected from KTTV NB, the Southern Regional Hydro-Meteorological Center. An individual-level indicator of socioeconomic position (SEP) was based on the degree to which the patient was exempt from payment according to hospital financial records. A group-level indicator of SEP was based on estimates of poverty prevalence in the districts of HCMC in 2004, obtained from a poverty mapping project of the Institute of Economic Research in HCMC, in collaboration with the General Statistics Office of Vietnam and the World Bank. Poverty prevalence was defined using the poverty line set by the People's Committee of HCMC of 6 million Vietnamese dong (VND) annual income. Quartiles of district-level poverty prevalence were created based on poverty prevalence estimates for each district. Analyses were conducted using both time-series and case-crossover approaches. In the absence of measurement error, confounding, and other sources of bias, the two approaches were expected to provide estimates that differed only with regard to precision. For the time-series analyses, the unit of observation was daily counts of hospital admissions for ALRI. Poisson regression with smoothing functions for meteorologic variables and variables for seasonal and long-term trends was used. Case-crossover analyses were conducted using time-stratified selection of controls. Control days were every 7th day from the date of admission within the same month as admission. Large seasonal differences were observed in pollutant levels and hospital admission patterns during the investigation period for HCMC. Of the 15,717 ALRI admissions occurring within the study period, 60% occurred in the rainy season (May through October), with a peak in these admissions during July and August of each year. Average daily concentrations for PM10, O3, NO2, and SO2 were 73, 75, 22, and 22 microg/m3, respectively, with higher pollutant concentrations observed in the dry season (November through April) compared with the rainy season. As the time between onset of illness and hospital admission was thought to range from 1 to 6 days, it was not possible to specify a priori a single-day lag. We assessed results for single-day lags from lag 0 to lag 10, but emphasize results for an average of lag 1-6, since this best reflects the case reference period. Results were robust to differences in temperature lags with lag 0 and the average lag (1-6 days); results for lag 0 for temperature are presented. Results differed markedly when analyses were stratified by season, rather than simply adjusted for season. ALRI admissions were generally positively associated with ambient levels of PM10, NO2, and SO2 during the dry season (November-April), but not the rainy season (May-October). Positive associations between O3 and ALRI admissions were not observed in either season. We do not believe that exposure to air pollution could reduce the risk of ALRI in the rainy season and infer that these results could be driven by residual confounding present within the rainy season. The much lower correlation between NO2 and PM10 levels during the rainy season provides further evidence that these pollutants may not be accurate indicators of exposure to air pollution from combustion processes in the rainy season. Results were generally consistent across time-series and case-crossover analyses. In the dry season, risks for ALRI hospital admissions with average pollutant lag (1-6 days) were highest for NO2 and SO2 in the single-pollutant case-crossover analyses, with excess risks of 8.50% (95% CI, 0.80-16.79) and 5.85% (95% CI, 0.44-11.55) observed, respectively. NO2 and SO2 effects remained higher than PM10 effects in both the single-pollutant and two-pollutant models. The two-pollutant model indicated that NO2 confounded the PM10 and SO2 effects. For example, PM10 was weakly associated with an excess risk in the dry season of 1.25% (95% CI, -0.55 to 3.09); after adjusting for SO2 and O3, the risk estimate was reduced but remained elevated, with much wider confidence intervals; after adjusting for NO2, an excess risk was no longer observed. Though the effects seem to be driven by NO2, the statistical limitations of adequately addressing collinearity, given the high correlation between PM10 and NO2 (r = 0.78), limited our ability to clearly distinguish between PM10 and NO2 effects. In the rainy season, negative associations between PM10 and ALRI admissions were observed. No association with O3 was observed in the single-pollutant model, but O3 exposure was negatively associated with ALRI admissions in the two-pollutant model. There was little evidence of an association between NO2 and ALRI admissions. The single-pollutant estimate from the case-crossover analysis suggested a negative association between NO2 and ALRI admissions, but this effect was no longer apparent after adjustment for other pollutants. Although associations between SO2 and ALRI admissions were not observed in the rainy season, point estimates for the case-crossover analyses suggested negative associations, while time-series (Poisson regression) analyses suggested positive associations--an exception to the general consistency between case-crossover and time-series results. Results were robust to differences in seasonal classification. Inclusion of rainfall as a continuous variable and the seasonal reclassification of selected series of data did not influence results. No clear evidence of station-specific effects could be observed, since results for the different monitoring stations had overlapping confidence intervals. In the dry season, increased concentrations of NO2 and SO2 were associated with increased hospital admissions of young children for ALRI in HCMC. PM10 could also be associated with increased hospital admissions in the dry season, but the high correlation of 0.78 between PM10 and NO2 levels limits our ability to distinguish between PM10 and NO2 effects. Nevertheless, the results support the presence of an association between combustion-source pollution and increased ALRI admissions. There also appears to be evidence of uncontrolled negative confounding within the rainy season, with higher incidence of ALRI and lower pollutant concentrations overall. Exploratory analyses made using limited historical and regional data on monthly prevalence of respiratory syncytial virus (RSV) suggest that an unmeasured, time-varying confounder (RSV, in this case) could have, in an observational study like this one, created enough bias to reverse the observed effect estimates of pollutants in the rainy season. In addition, with virtually no RSV incidence in the dry season, these findings also lend some credibility to the notion that RSV could influence results primarily in the rainy season. Analyses were not able to identify differential effects by individual-level indicators of SEP, mainly due to the small number of children classified as poor based on information in the hospitals' financial records. Analyses assessing differences in effect by district-level indicator of SEP did not indicate a clear trend in risk across SEP quartiles, but there did appear to be a slightly higher risk among the residents of districts with the highest quartile of SEP. As these are the districts within the urban center of HCMC, results could be indicative of increased exposures for residents living within the city center. (ABSTRACT TRUNCATED)

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