Search

Exposure to air pollution disproportionately affects racial/ethnic minorities that could contribute to health inequalities including metabolic disorders. However, most existing studies used a static assessment of air pollution exposure (mostly using the residential address) and do not account for activity space when modelling exposure to air pollution. The aim of this study is to understand how exposure to air pollution impacts metabolic disorders biomarkers, how this effect differs according to ethnicity, and for the first time compare these findings with two methods of exposure assessment: dynamic and static measures. Among the Community of Mine study, a cross-sectional study conducted in San Diego County, insulin resistance, diabetes, hypertension, obesity, dyslipidemia, and metabolic syndrome (MetS) were assessed. Exposure to air pollution (PM 2.5 , NO 2 , traffic) was calculated using static measures around the home, and dynamic measures of mobility derived from Global Positioning Systems (GPS) traces using kernel density estimators to account for exposure variability across space and time. Associations of air pollution with metabolic disorders were quantified using generalized estimating equation models to account for the clustered nature of the data. Among 552 participants (mean age 58.7 years, 42% Hispanic/Latino), Hispanics/Latinos had a higher exposure to PM 2.5 compared to non-Hispanics using static measures. In contrast, Hispanics/Latinos had less exposure to PM 2.5 using dynamic measures. For all participants, higher dynamic exposure to PM 2.5 and NO 2 was associated with increased insulin resistance and cholesterol levels, and increased risk of obesity, dyslipidemia and MetS (RR 1.17, 95% CI: 1.07–1.28; RR 1.21, 95% CI: 1.12–1.30, respectively). The association between dynamic PM 2.5 exposure and MetS differed by Hispanic/Latino ethnicity. These results highlight the importance of considering people's daily mobility in assessing the impact of air pollution on health. • Static exposure to air pollution does not consider total exposure throughout the day or time spent in other locations, potentially underestimating pollution effects on health. • Metabolic disorders biomarkers and Global Positioning Systems (GPS) traces were measured in an ethnically diverse population in San Diego, CA. • Ethnic inequalities in exposure to air pollution varied according to the type of air pollution assessment, static or dynamic measures. • Only dynamic exposures to air pollutants (PM 2.5 and NO 2) were associated with insulin resistance and metabolic syndrome. • Not considering daily mobility and spatial variability of air pollution could lead to differential exposure misclassification and thus to biased effect estimates. ABTRACT. [ABSTRACT FROM AUTHOR]