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Association between particulate matter 2.5 and diabetes mellitus: A meta‐analysis of cohort studies
AIMS/INTRODUCTION: The present meta‐analysis was carried out to assess the association between exposure to the level of atmospheric particulate matter 2.5 (PM2.5; fine particulate matter with aerodynamic diameter less than 2.5 μm) and type 2 diabetes mellitus or gestational diabetes mellitus (GDM)....
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5583950/ https://www.ncbi.nlm.nih.gov/pubmed/28122165 http://dx.doi.org/10.1111/jdi.12631 |
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author | He, Dian Wu, Shaowen Zhao, Haiping Qiu, Hongyan Fu, Yang Li, Xingming He, Yan |
author_facet | He, Dian Wu, Shaowen Zhao, Haiping Qiu, Hongyan Fu, Yang Li, Xingming He, Yan |
author_sort | He, Dian |
collection | PubMed |
description | AIMS/INTRODUCTION: The present meta‐analysis was carried out to assess the association between exposure to the level of atmospheric particulate matter 2.5 (PM2.5; fine particulate matter with aerodynamic diameter less than 2.5 μm) and type 2 diabetes mellitus or gestational diabetes mellitus (GDM). MATERIALS AND METHODS: We searched the Medline, EMBASE, Cochrane and Web of Science databases to obtain articles according to the responding literature search strategies. Among a total of 279 identified articles, 55 were reviewed in depth, of which 10 articles (11 cohort studies) satisfied the inclusion criteria. Only cohort studies that disclosed the association between PM2.5 and type 2 diabetes mellitus or GDM were included in this article. A fixed‐effects model was selected if P > 0.1 and I (2) < 50%; otherwise, a random‐effects model would be used to calculate the total effect value. Subgroup analysis was further carried out according to the types of diabetes mellitus (type 2 diabetes mellitus and GDM). The relative risk was used to estimate the association between PM2.5 and diabetes mellitus. RESULTS: The positive associations between PM2.5 and the incidence of type 2 diabetes mellitus were found in the long‐term exposure period (relative risk 1.25, 95% confidence interval 1.10–1.43), which showed that with every 10‐μg/m(3) increase in PM2.5, the risk of type 2 diabetes mellitus would increase by 25% in the long‐term exposure. Although the significant associations were not identified between maternal exposure to PM2.5 and GDM in the first trimester, the second trimester and the entire pregnancy periods, we could conclude that maternal exposure to PM2.5 in the entire pregnancy period would be more likely to lead to developing GDM (relative risk 1.162, 95% confidence interval 0.806–1.675) than the other two periods. CONCLUSIONS: Long‐term exposure to PM2.5 would be more likely to lead to developing type 2 diabetes mellitus, but more studies would be required to confirm the association between PM2.5 and GDM. It might be a wise to take effective measures to reduce PM2.5 exposure in vulnerable populations, especially for pregnant women. |
format | Online Article Text |
id | pubmed-5583950 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-55839502017-09-06 Association between particulate matter 2.5 and diabetes mellitus: A meta‐analysis of cohort studies He, Dian Wu, Shaowen Zhao, Haiping Qiu, Hongyan Fu, Yang Li, Xingming He, Yan J Diabetes Investig Articles AIMS/INTRODUCTION: The present meta‐analysis was carried out to assess the association between exposure to the level of atmospheric particulate matter 2.5 (PM2.5; fine particulate matter with aerodynamic diameter less than 2.5 μm) and type 2 diabetes mellitus or gestational diabetes mellitus (GDM). MATERIALS AND METHODS: We searched the Medline, EMBASE, Cochrane and Web of Science databases to obtain articles according to the responding literature search strategies. Among a total of 279 identified articles, 55 were reviewed in depth, of which 10 articles (11 cohort studies) satisfied the inclusion criteria. Only cohort studies that disclosed the association between PM2.5 and type 2 diabetes mellitus or GDM were included in this article. A fixed‐effects model was selected if P > 0.1 and I (2) < 50%; otherwise, a random‐effects model would be used to calculate the total effect value. Subgroup analysis was further carried out according to the types of diabetes mellitus (type 2 diabetes mellitus and GDM). The relative risk was used to estimate the association between PM2.5 and diabetes mellitus. RESULTS: The positive associations between PM2.5 and the incidence of type 2 diabetes mellitus were found in the long‐term exposure period (relative risk 1.25, 95% confidence interval 1.10–1.43), which showed that with every 10‐μg/m(3) increase in PM2.5, the risk of type 2 diabetes mellitus would increase by 25% in the long‐term exposure. Although the significant associations were not identified between maternal exposure to PM2.5 and GDM in the first trimester, the second trimester and the entire pregnancy periods, we could conclude that maternal exposure to PM2.5 in the entire pregnancy period would be more likely to lead to developing GDM (relative risk 1.162, 95% confidence interval 0.806–1.675) than the other two periods. CONCLUSIONS: Long‐term exposure to PM2.5 would be more likely to lead to developing type 2 diabetes mellitus, but more studies would be required to confirm the association between PM2.5 and GDM. It might be a wise to take effective measures to reduce PM2.5 exposure in vulnerable populations, especially for pregnant women. John Wiley and Sons Inc. 2017-05-03 2017-09 /pmc/articles/PMC5583950/ /pubmed/28122165 http://dx.doi.org/10.1111/jdi.12631 Text en © 2017 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial (http://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Articles He, Dian Wu, Shaowen Zhao, Haiping Qiu, Hongyan Fu, Yang Li, Xingming He, Yan Association between particulate matter 2.5 and diabetes mellitus: A meta‐analysis of cohort studies |
title | Association between particulate matter 2.5 and diabetes mellitus: A meta‐analysis of cohort studies |
title_full | Association between particulate matter 2.5 and diabetes mellitus: A meta‐analysis of cohort studies |
title_fullStr | Association between particulate matter 2.5 and diabetes mellitus: A meta‐analysis of cohort studies |
title_full_unstemmed | Association between particulate matter 2.5 and diabetes mellitus: A meta‐analysis of cohort studies |
title_short | Association between particulate matter 2.5 and diabetes mellitus: A meta‐analysis of cohort studies |
title_sort | association between particulate matter 2.5 and diabetes mellitus: a meta‐analysis of cohort studies |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5583950/ https://www.ncbi.nlm.nih.gov/pubmed/28122165 http://dx.doi.org/10.1111/jdi.12631 |
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