TY - JOUR
T1 - Air pollution and metabolic disorders
T2 - Dynamic versus static measures of exposure among Hispanics/Latinos and non-Hispanics
AU - Letellier, Noémie
AU - Zamora, Steven
AU - Spoon, Chad
AU - Yang, Jiue An
AU - Mortamais, Marion
AU - Escobar, Gabriel Carrasco
AU - Sears, Dorothy D.
AU - Jankowska, Marta M.
AU - Benmarhnia, Tarik
N1 - Funding Information:
This work was supported by the National Cancer Institute [ R01CA228147 ].
Publisher Copyright:
© 2022 The Authors
PY - 2022/6
Y1 - 2022/6
N2 - Introduction: 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. Methods: 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 (PM2.5, NO2, 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. Results: Among 552 participants (mean age 58.7 years, 42% Hispanic/Latino), Hispanics/Latinos had a higher exposure to PM2.5 compared to non-Hispanics using static measures. In contrast, Hispanics/Latinos had less exposure to PM2.5 using dynamic measures. For all participants, higher dynamic exposure to PM2.5 and NO2 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 PM2.5 exposure and MetS differed by Hispanic/Latino ethnicity. Conclusion: These results highlight the importance of considering people's daily mobility in assessing the impact of air pollution on health.
AB - Introduction: 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. Methods: 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 (PM2.5, NO2, 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. Results: Among 552 participants (mean age 58.7 years, 42% Hispanic/Latino), Hispanics/Latinos had a higher exposure to PM2.5 compared to non-Hispanics using static measures. In contrast, Hispanics/Latinos had less exposure to PM2.5 using dynamic measures. For all participants, higher dynamic exposure to PM2.5 and NO2 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 PM2.5 exposure and MetS differed by Hispanic/Latino ethnicity. Conclusion: These results highlight the importance of considering people's daily mobility in assessing the impact of air pollution on health.
KW - Biomarkers
KW - Ethnic inequalities
KW - Geographic information systems (GIS)
KW - Kernel density estimators (KDE)
KW - Mobility
KW - Pollution inequity
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U2 - 10.1016/j.envres.2022.112846
DO - 10.1016/j.envres.2022.112846
M3 - Article
C2 - 35120894
AN - SCOPUS:85123892500
SN - 0013-9351
VL - 209
JO - Environmental Research
JF - Environmental Research
M1 - 112846
ER -