Universidad Peruana Cayetano Heredia

Air pollution and metabolic disorders: Dynamic versus static measures of exposure among Hispanics/Latinos and non-Hispanics

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dc.contributor.author Letellier, Noémie
dc.contributor.author Zamora, Steven
dc.contributor.author Spoon, Chad
dc.contributor.author Yang, Jiue-An
dc.contributor.author Mortamais, Marion
dc.contributor.author Carrasco Escobar, Gabriel
dc.contributor.author Sears, Dorothy D.
dc.contributor.author Jankowska, Marta M.
dc.contributor.author Benmarhnia, Tarik
dc.date.accessioned 2022-02-17T19:23:12Z
dc.date.available 2022-02-17T19:23:12Z
dc.date.issued 2022
dc.identifier.uri https://hdl.handle.net/20.500.12866/11374
dc.description.abstract 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. en_US
dc.language.iso eng
dc.publisher Elsevier
dc.relation.ispartofseries Environmental Research
dc.rights info:eu-repo/semantics/restrictedAccess
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject Biomarkers en_US
dc.subject Ethnic inequalities en_US
dc.subject Geographic information systems (GIS) en_US
dc.subject Spatial Analysis en_US
dc.subject Mobility en_US
dc.subject Pollution inequity en_US
dc.title Air pollution and metabolic disorders: Dynamic versus static measures of exposure among Hispanics/Latinos and non-Hispanics en_US
dc.type info:eu-repo/semantics/article
dc.identifier.doi https://doi.org/10.1016/j.envres.2022.112846
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#1.05.08
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#3.03.05
dc.relation.issn 1096-0953


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