GIS-Based Retrospective Assessment of Traffic-Related Air Pollution Exposures, and Social-Environmental Influences on Childhood Asthma

Abstract

SM5-PD-05 Introduction: Asthma disproportionately impacts children in lower-income urban communities, where environmental exposures such as traffic-related air pollution and social stressors including exposure to violence (ETV) are elevated. Stress may disrupt biologic systems related to inflammation through mechanisms overlapping those altered by physical pollutants, making those individuals dually exposed most susceptible to asthma. However, few studies have been able to incorporate both elements, in part because data and methods have not been available for retrospective exposure assessment. For this study, we used GIS-based land-use regression (LUR) techniques to retrospectively assign estimates of residential exposures to traffic-related air pollutants, taking account of temporal variability in exposures, in order to examine the effect of multiple exposures on asthma outcomes, including interactions between social and physical exposures. Methods: Intracommunity spatial and temporal variability in pollution concentrations was examined using monthly nitrogen dioxide (NO2) measurements for 13 sites over 19 years in East Boston and surrounding neighborhoods. Temporally specified LUR models were then developed to create residence-based and time-specific estimates of long-term exposure trajectories for a community-based pregnancy cohort recruited between 1986 and 1992, taking account of residential history and the time course of disease development. Residence-based pollution estimates were merged with individual-level questionnaire data on age, sex, race, socioeconomic position, tobacco smoke exposure, exposure to violence (ETV), and asthma/wheeze phenotypes ascertained at cohort enrollment and follow-up. Using multivariate logistic regression, we examined the relative and multiplicative contributions of ETV and NO2 indicators on childhood asthma/wheeze outcomes. Results: LUR models indicated that NO2 concentrations were associated with distance to major road, kernel-weighted traffic density within 500 m, and population density, with strong temporal stability in spatial patterns. Preliminary analyses indicate elevated univariate odds ratios for diagnosis of bronchitis and wheeze only among children in the highest tertiles at follow-up for both ETV and NO2 exposure (OR = 1.33; 1.01–1.75 and 1.22; 1.004–1.49, respectively). Likewise, using backward elimination, only male sex and the interaction term between ETV and NO2 exposure were significant (P < 0.10) in predicting bronchitis [OR = 2.11 (0.86–5.15) and OR = 3.26 (1.06–10.0), respectively]. Only the interaction term between ETV and NO2 was significant in predicting wheeze [OR = 2.02 (0.84–4.83), comparing highest to lowest quartile]. Discussion: Our findings demonstrate the viability of GIS-based land-use regression for retrospective long-term exposure estimation, and suggest a possible multiplicative effect between ETV and traffic-related air pollution in the expression of asthma/wheeze phenotypes.