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Lack of association between particulate air pollution and blood glucose levels and diabetic status in peri-urban India
BACKGROUND: Limited evidence exists on the effect of particulate air pollution on blood glucose levels. We evaluated the associations of residential and personal levels of fine particulate matter (PM(2.5)) and black carbon (BC) with blood glucose and diabetic status among residents of 28 peri-urban...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6718580/ https://www.ncbi.nlm.nih.gov/pubmed/31376594 http://dx.doi.org/10.1016/j.envint.2019.105033 |
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author | Curto, Ariadna Ranzani, Otavio Milà, Carles Sanchez, Margaux Marshall, Julian D. Kulkarni, Bharati Bhogadi, Santhi Kinra, Sanjay Wellenius, Gregory A. Tonne, Cathryn |
author_facet | Curto, Ariadna Ranzani, Otavio Milà, Carles Sanchez, Margaux Marshall, Julian D. Kulkarni, Bharati Bhogadi, Santhi Kinra, Sanjay Wellenius, Gregory A. Tonne, Cathryn |
author_sort | Curto, Ariadna |
collection | PubMed |
description | BACKGROUND: Limited evidence exists on the effect of particulate air pollution on blood glucose levels. We evaluated the associations of residential and personal levels of fine particulate matter (PM(2.5)) and black carbon (BC) with blood glucose and diabetic status among residents of 28 peri-urban villages in South India. METHODS: We used cross-sectional data from 5065 adults (≥18 years, 54% men) included in the Andhra Pradesh Children and Parents Study. Fasting plasma glucose was measured once in 2010–2012 and prevalent prediabetes and diabetes were defined following the American Diabetes Association criteria. We estimated annual ambient PM(2.5) and BC levels at residence using land-use regression models and annual personal exposure to PM(2.5) and BC using prediction models based on direct measurements from a subsample of 402 participants. We used linear and logistic nested mixed-effect models to assess the association between exposure metrics and health outcomes. For personal exposures, we stratified analyses by sex. RESULTS: Mean (SD) residential PM(2.5) and BC were 32.9 (2.6) μg/m(3) and 2.5 (2.6) μg/m(3), respectively; personal exposures to PM(2.5) and BC were 54.5 (11.5) μg/m(3) and 5.8 (2.5) μg/m(3), respectively. Average (SD) fasting blood glucose was 5.3 (1.3) mmol/l, 16% of participants had prediabetes, and 5.5% had diabetes. Residential PM(2.5) and BC were not associated with higher blood glucose levels. Personal PM(2.5) (20 μg/m(3) increase) and BC (1 μg/m(3) increase) were negatively associated with blood glucose levels in women (PM(2.5): −1.93, 95%CI: −3.12, −0.73; BC: −0.63, 95%CI: −0.90, −0.37). In men, associations were negative for personal PM(2.5) (−1.99, 95%CI: −3.56, −0.39) and positive for personal BC (0.49, 95%CI: −0.44, 1.43). We observed no evidence of associations between any exposure and prevalence of prediabetes/diabetes. CONCLUSIONS: Our results do not provide evidence that residential exposures to PM(2.5) or BC are associated with blood glucose or prevalence of prediabetes/diabetes in this population. Associations with personal exposure may have been affected by unmeasured confounding, highlighting a challenge in using personal exposure estimates in air pollution epidemiology. These associations should be further examined in longitudinal studies. |
format | Online Article Text |
id | pubmed-6718580 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-67185802019-10-01 Lack of association between particulate air pollution and blood glucose levels and diabetic status in peri-urban India Curto, Ariadna Ranzani, Otavio Milà, Carles Sanchez, Margaux Marshall, Julian D. Kulkarni, Bharati Bhogadi, Santhi Kinra, Sanjay Wellenius, Gregory A. Tonne, Cathryn Environ Int Article BACKGROUND: Limited evidence exists on the effect of particulate air pollution on blood glucose levels. We evaluated the associations of residential and personal levels of fine particulate matter (PM(2.5)) and black carbon (BC) with blood glucose and diabetic status among residents of 28 peri-urban villages in South India. METHODS: We used cross-sectional data from 5065 adults (≥18 years, 54% men) included in the Andhra Pradesh Children and Parents Study. Fasting plasma glucose was measured once in 2010–2012 and prevalent prediabetes and diabetes were defined following the American Diabetes Association criteria. We estimated annual ambient PM(2.5) and BC levels at residence using land-use regression models and annual personal exposure to PM(2.5) and BC using prediction models based on direct measurements from a subsample of 402 participants. We used linear and logistic nested mixed-effect models to assess the association between exposure metrics and health outcomes. For personal exposures, we stratified analyses by sex. RESULTS: Mean (SD) residential PM(2.5) and BC were 32.9 (2.6) μg/m(3) and 2.5 (2.6) μg/m(3), respectively; personal exposures to PM(2.5) and BC were 54.5 (11.5) μg/m(3) and 5.8 (2.5) μg/m(3), respectively. Average (SD) fasting blood glucose was 5.3 (1.3) mmol/l, 16% of participants had prediabetes, and 5.5% had diabetes. Residential PM(2.5) and BC were not associated with higher blood glucose levels. Personal PM(2.5) (20 μg/m(3) increase) and BC (1 μg/m(3) increase) were negatively associated with blood glucose levels in women (PM(2.5): −1.93, 95%CI: −3.12, −0.73; BC: −0.63, 95%CI: −0.90, −0.37). In men, associations were negative for personal PM(2.5) (−1.99, 95%CI: −3.56, −0.39) and positive for personal BC (0.49, 95%CI: −0.44, 1.43). We observed no evidence of associations between any exposure and prevalence of prediabetes/diabetes. CONCLUSIONS: Our results do not provide evidence that residential exposures to PM(2.5) or BC are associated with blood glucose or prevalence of prediabetes/diabetes in this population. Associations with personal exposure may have been affected by unmeasured confounding, highlighting a challenge in using personal exposure estimates in air pollution epidemiology. These associations should be further examined in longitudinal studies. Elsevier Science 2019-10 /pmc/articles/PMC6718580/ /pubmed/31376594 http://dx.doi.org/10.1016/j.envint.2019.105033 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Curto, Ariadna Ranzani, Otavio Milà, Carles Sanchez, Margaux Marshall, Julian D. Kulkarni, Bharati Bhogadi, Santhi Kinra, Sanjay Wellenius, Gregory A. Tonne, Cathryn Lack of association between particulate air pollution and blood glucose levels and diabetic status in peri-urban India |
title | Lack of association between particulate air pollution and blood glucose levels and diabetic status in peri-urban India |
title_full | Lack of association between particulate air pollution and blood glucose levels and diabetic status in peri-urban India |
title_fullStr | Lack of association between particulate air pollution and blood glucose levels and diabetic status in peri-urban India |
title_full_unstemmed | Lack of association between particulate air pollution and blood glucose levels and diabetic status in peri-urban India |
title_short | Lack of association between particulate air pollution and blood glucose levels and diabetic status in peri-urban India |
title_sort | lack of association between particulate air pollution and blood glucose levels and diabetic status in peri-urban india |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6718580/ https://www.ncbi.nlm.nih.gov/pubmed/31376594 http://dx.doi.org/10.1016/j.envint.2019.105033 |
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