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An environmental justice analysis of air pollution in India.
deSouza, Priyanka N; Chaudhary, Ekta; Dey, Sagnik; Ko, Soohyeon; Németh, Jeremy; Guttikunda, Sarath; Chowdhury, Sourangsu; Kinney, Patrick; Subramanian, S V; Bell, Michelle L; Kim, Rockli.
Afiliação
  • deSouza PN; Department of Urban and Regional Planning, University of Colorado Denver, Denver, CO, USA. priyanka.desouza@ucdenver.edu.
  • Chaudhary E; Centre for Atmospheric Sciences, Indian Institute of Technology (IIT) Delhi, New Delhi, India. priyanka.desouza@ucdenver.edu.
  • Dey S; Centre for Atmospheric Sciences, Indian Institute of Technology (IIT) Delhi, New Delhi, India.
  • Ko S; Centre for Atmospheric Sciences, Indian Institute of Technology (IIT) Delhi, New Delhi, India.
  • Németh J; Centre of Excellence for Research on Clean Air, IIT Delhi, New Delhi, India.
  • Guttikunda S; School of Public Policy, IIT Delhi, New Delhi, India.
  • Chowdhury S; Department of Public Health Sciences, Graduate School of Korea University, Seoul, South Korea.
  • Kinney P; Interdisciplinary Program in Precision Public Health, Department of Public Health Sciences, Graduate School of Korea University, Seoul, South Korea.
  • Subramanian SV; Department of Urban and Regional Planning, University of Colorado Denver, Denver, CO, USA.
  • Bell ML; Transportation Research and Injury Prevention (TRIP) Centre, Indian Institute of Technology, New Delhi, 110016, India.
  • Kim R; Urban Emissions, New Delhi, 110019, India.
Sci Rep ; 13(1): 16690, 2023 10 04.
Article em En | MEDLINE | ID: mdl-37794063
ABSTRACT
Due to the lack of timely data on socioeconomic factors (SES), little research has evaluated if socially disadvantaged populations are disproportionately exposed to higher PM2.5 concentrations in India. We fill this gap by creating a rich dataset of SES parameters for 28,081 clusters (villages in rural India and census-blocks in urban India) from the National Family and Health Survey (NFHS-4) using a precision-weighted methodology that accounts for survey-design. We then evaluated associations between total, anthropogenic and source-specific PM2.5 exposures and SES variables using fully-adjusted multilevel models. We observed that SES factors such as caste, religion, poverty, education, and access to various household amenities are important risk factors for PM2.5 exposures. For example, we noted that a unit standard deviation increase in the cluster-prevalence of Scheduled Caste and Other Backward Class households was significantly associated with an increase in total-PM2.5 levels corresponding to 0.127 µg/m3 (95% CI 0.062 µg/m3, 0.192 µg/m3) and 0.199 µg/m3 (95% CI 0.116 µg/m3, 0.283 µg/m3, respectively. We noted substantial differences when evaluating such associations in urban/rural locations, and when considering source-specific PM2.5 exposures, pointing to the need for the conceptualization of a nuanced EJ framework for India that can account for these empirical differences. We also evaluated emerging axes of inequality in India, by reporting associations between recent changes in PM2.5 levels and different SES parameters.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluentes Atmosféricos / Poluição do Ar Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans País/Região como assunto: Asia Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluentes Atmosféricos / Poluição do Ar Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans País/Região como assunto: Asia Idioma: En Ano de publicação: 2023 Tipo de documento: Article