Mapping Health Fragility and Vulnerability in Air Pollution-Monitoring Networks in Dallas-Fort Worth.

Environmental air pollution remains a major contributor to negative health outcomes and mortality, but the relationship between socially vulnerable populations and air pollution is not well understood. Although air pollution potentially affects everyone, the combination of underlying health, socioeconomic, and demographic factors exacerbate the impact for socially vulnerable population groups, and the United States Clean Air Act (CAA) describes an obligation to protect these populations. This paper seeks to understand how air pollution monitor placement strategies and policy may neglect social vulnerabilities and therefore potentially underestimate exposure burdens in vulnerable populations. Multivariate logistic regression models were used to assess the association between being in an ozone-monitored area or not on 15 vulnerability indicators. It was found that the odds of not being in an ozone-monitored area (not covered, outside) increased for the predictor mobile homes (OR = 4.831, 95% CI [2.500-9.338] and OR = 8.066, 95% CI [4.390-14.820] for the 10 and 20 km spatial units, respectively) and decreased for the predictor multiunit structures (OR = 0.281, 95% CI [0.281-0.548] and OR = 0.130, 95% CI [0.037, 0.457] for the 10 and 20 km spatial units, respectively) and the predictor speaks English "less than well" (OR = 0.521, 95% CI [0.292-0.931] for 10 km). These results indicate that existing pollution sensor coverage may neglect areas with concentrations of highly vulnerable populations in mobile homes, and future monitoring placement policy decisions must work to address this imbalance.

Evaluating spatial patterns of seasonal ozone exposure and incidence of respiratory emergency room visits in Dallas-Fort Worth.

BACKGROUND: In urban environments, environmental air pollution poses significant risks to respiratory health. Moreover, the seasonal spatial variability of the air pollutant ozone, and respiratory illness within Dallas-Fort Worth (DFW) is not well understood. We examine the relationships between spatial patterns of long-term ozone exposure and respiratory illness to better understand impacts on health outcomes. We propose that this study will establish an enhanced understanding of the spatio-temporal characteristics of ozone concentrations and respiratory emergency room visits (ERV) incidence. METHODS: Air pollution data (ozone) and ERV incidence data from DFW was used to evaluate the relationships between exposures and outcomes using three steps: (1) develop a geostatistical model to produce quarterly maps of ozone exposure for the DFW area; (2) use spatial analysis techniques to identify clusters of zip codes with high or low values of ozone exposure and respiratory ERV incidence; and (3) use concentration-response curves to evaluate the relationships between respiratory ERV incidence and ozone exposure. RESULTS: Respiratory ERV incidence was highest in quarters 1 and 4, while ozone exposure was highest in quarters 2 and 3. Extensive statistically significant spatial clusters of ozone regions were identified. Although the maps revealed that there was no regional association between the spatial patterns of high respiratory ERV incidence and ozone exposure, the concentration-response analysis suggests that lower levels of ozone exposure may still contribute to adverse respiratory outcomes.