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Associations of Autism Spectrum Disorder with PM2.5 Components: A Comparative Study Using Two Different Exposure Models.
Rahman, Md Mostafijur; Carter, Sarah A; Lin, Jane C; Chow, Ting; Yu, Xin; Martinez, Mayra P; Chen, Zhanghua; Chen, Jiu-Chiuan; Rud, Daniel; Lewinger, Juan P; van Donkelaar, Aaron; Martin, Randall V; Eckel, Sandrah Proctor; Schwartz, Joel; Lurmann, Fred; Kleeman, Michael J; McConnell, Rob; Xiang, Anny H.
Afiliação
  • Rahman MM; Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California 90032, United States.
  • Carter SA; Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California 91101, United States.
  • Lin JC; Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California 91101, United States.
  • Chow T; Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California 91101, United States.
  • Yu X; Spatial Science Institute, University of Southern California, Los Angeles, California 90089, United States.
  • Martinez MP; Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California 91101, United States.
  • Chen Z; Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California 90032, United States.
  • Chen JC; Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California 90032, United States.
  • Rud D; Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California 90032, United States.
  • Lewinger JP; Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California 90032, United States.
  • van Donkelaar A; Department of Energy, Environmental & Chemical Engineering, Washington University at St. Louis, St. Louis, Missouri 63130, United States.
  • Martin RV; Department of Energy, Environmental & Chemical Engineering, Washington University at St. Louis, St. Louis, Missouri 63130, United States.
  • Eckel SP; Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California 90032, United States.
  • Schwartz J; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States.
  • Lurmann F; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States.
  • Kleeman MJ; Sonoma Technology, Inc., Petaluma, California 94954, United States.
  • McConnell R; Department of Civil and Environmental Engineering, University of California, Davis, Davis, California 95616, United States.
  • Xiang AH; Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California 90032, United States.
Environ Sci Technol ; 57(1): 405-414, 2023 01 10.
Article em En | MEDLINE | ID: mdl-36548990
ABSTRACT
This retrospective cohort study examined associations of autism spectrum disorder (ASD) with prenatal exposure to major fine particulate matter (PM2.5) components estimated using two independent exposure models. The cohort included 318 750 mother-child pairs with singleton deliveries in Kaiser Permanente Southern California hospitals from 2001 to 2014 and followed until age five. ASD cases during follow-up (N = 4559) were identified by ICD codes. Prenatal exposures to PM2.5, elemental (EC) and black carbon (BC), organic matter (OM), nitrate (NO3-), and sulfate (SO42-) were constructed using (i) a source-oriented chemical transport model and (ii) a hybrid model. Exposures were assigned to each maternal address during the entire pregnancy, first, second, and third trimester. In single-pollutant models, ASD was associated with pregnancy-average PM2.5, EC/BC, OM, and SO42- exposures from both exposure models, after adjustment for covariates. The direction of effect estimates was consistent for EC/BC and OM and least consistent for NO3-. EC/BC, OM, and SO42- were generally robust to adjustment for other components and for PM2.5. EC/BC and OM effect estimates were generally larger and more consistent in the first and second trimester and SO42- in the third trimester. Future PM2.5 composition health effect studies might consider using multiple exposure models and a weight of evidence approach when interpreting effect estimates.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Poluentes Atmosféricos / Poluição do Ar / Poluentes Ambientais / Transtorno do Espectro Autista Tipo de estudo: Observational_studies / Risk_factors_studies Limite: Female / Humans / Pregnancy Idioma: En Revista: Environ Sci Technol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Poluentes Atmosféricos / Poluição do Ar / Poluentes Ambientais / Transtorno do Espectro Autista Tipo de estudo: Observational_studies / Risk_factors_studies Limite: Female / Humans / Pregnancy Idioma: En Revista: Environ Sci Technol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos