Dataset Information

Associations of long-term exposure to PM₁, PM_2.5, NO₂ with type 2 diabetes mellitus prevalence and fasting blood glucose levels in Chinese rural populations.

ABSTRACT:

Objectives

To evaluate the associations between long-term exposure to particulate matter with an aerodynamic diameter ≤1.0 μm and ≤2.5 μm (PM₁ and PM_2.5), nitrogen dioxide (NO₂) and type 2 diabetes prevalence and fasting blood glucose levels in Chinese rural populations.

Material and methods

A total of 39, 259 participants were enrolled in The Henan Rural Cohort study. Questionnaires and medical examination were conducted from July 2015 to September 2017 in rural areas of Henan province, China. Three-year average residential exposure levels of PM₁, PM_2.5, NO₂ for each subject were estimated by a spatiotemporal model. Logistic regression and linear regression models were applied to estimate the associations between PM₁, PM_2.5, NO₂ exposure and type 2 diabetes prevalence and fasting blood glucose levels.

Results

The mean 3-year residential exposure concentrations of PM₁, PM_2.5 and NO₂ was 57.4 μg/m³, 73.4 μg/m³ and 39.9 μg/m³, respectively. Higher exposure concentrations of PM₁, PM_2.5, NO₂ by 1 μg/m³ was positively related to a 4.0% (95%CIs: 1.026, 1.054), 6.8% (1.052, 1.084) and 5.0% (1.039, 1.061) increase in odds of type 2 diabetes in the final adjusted models. Besides, a 1 μg/m³ increase of PM₁, PM_2.5 and NO₂ was related to a 0.020 mmol/L (95%CIs: 0.014, 0.026), 0.036 mmol/L (95%CIs: 0.030, 0.042) and 0.030 mmol/L (95%CIs: 0.026, 0.034) mmol/L higher fasting blood glucose levels.

Conclusions

Higher exposure concentrations of air pollutants were positively related to the increased odds of type 2 diabetes, as well as higher fasting blood glucose levels in Chinese rural populations.

SUBMITTER: Liu F

PROVIDER: S-EPMC6853163 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Associations of long-term exposure to PM<sub>1</sub>, PM<sub>2.5</sub>, NO<sub>2</sub> with type 2 diabetes mellitus prevalence and fasting blood glucose levels in Chinese rural populations.

Liu Feifei F Guo Yuming Y Liu Yisi Y Chen Gongbo G Wang Yuxin Y Xue Xiaowei X Liu Suyang S Huo Wenqian W Mao Zhenxing Z Hou Yitan Y Lu Yuanan Y Wang Chongjian C Xiang Hao H Li Shanshan S

Environment international 20191022 Pt B

<h4>Objectives</h4>To evaluate the associations between long-term exposure to particulate matter with an aerodynamic diameter ≤1.0 μm and ≤2.5 μm (PM<sub>1</sub> and PM<sub>2.5</sub>), nitrogen dioxide (NO<sub>2</sub>) and type 2 diabetes prevalence and fasting blood glucose levels in Chinese rural populations.<h4>Material and methods</h4>A total of 39, 259 participants were enrolled in The Henan Rural Cohort study. Questionnaires and medical examination were conducted from July 2015 to Septembe ...[more]

PMID: 31654916

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Project description:BackgroundSubstantial increases in wildfire activity have been recorded in recent decades. Wildfires influence the chemical composition and concentration of particulate matter ≤2.5 μm in aerodynamic diameter (PM2.5). However, relatively few epidemiologic studies focus on the health impacts of wildfire smoke PM2.5 compared with the number of studies focusing on total PM2.5 exposure.ObjectivesWe estimated the associations between cardiorespiratory acute events and exposure to smoke PM2.5 in Colorado using a novel exposure model to separate smoke PM2.5 from background ambient PM2.5 levels.MethodsWe obtained emergency department visits and hospitalizations for acute cardiorespiratory outcomes from Colorado for May-August 2011-2014, geocoded to a 4 km geographic grid. Combining ground measurements, chemical transport models, and remote sensing data, we estimated smoke PM2.5 and non-smoke PM2.5 on a 1 km spatial grid and aggregated to match the resolution of the health data. Time-stratified, case-crossover models were fit using conditional logistic regression to estimate associations between fire smoke PM2.5 and non-smoke PM2.5 for overall and age-stratified outcomes using 2-day averaging windows for cardiovascular disease and 3-day windows for respiratory disease.ResultsPer 1 μg/m3 increase in fire smoke PM2.5, statistically significant associations were observed for asthma (OR = 1.081 (1.058, 1.105)) and combined respiratory disease (OR = 1.021 (1.012, 1.031)). No significant relationships were evident for cardiovascular diseases and smoke PM2.5. Associations with non-smoke PM2.5 were null for all outcomes. Positive age-specific associations related to smoke PM2.5 were observed for asthma and combined respiratory disease in children, and for asthma, bronchitis, COPD, and combined respiratory disease in adults. No significant associations were found in older adults.DiscussionThis is the first multi-year, high-resolution epidemiologic study to incorporate statistical and chemical transport modeling methods to estimate PM2.5 exposure due to wildfires. Our results allow for a more precise assessment of the population health impact of wildfire-related PM2.5 exposure in a changing climate.

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Dataset Information

Associations of long-term exposure to PM₁, PM_2.5, NO₂ with type 2 diabetes mellitus prevalence and fasting blood glucose levels in Chinese rural populations.

Objectives

Material and methods

Results

Conclusions

Publications

Associations of long-term exposure to PM<sub>1</sub>, PM<sub>2.5</sub>, NO<sub>2</sub> with type 2 diabetes mellitus prevalence and fasting blood glucose levels in Chinese rural populations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Associations of long-term exposure to PM1, PM2.5, NO2 with type 2 diabetes mellitus prevalence and fasting blood glucose levels in Chinese rural populations.

Objectives

Material and methods

Results

Conclusions

Publications

Associations of long-term exposure to PM<sub>1</sub>, PM<sub>2.5</sub>, NO<sub>2</sub> with type 2 diabetes mellitus prevalence and fasting blood glucose levels in Chinese rural populations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Associations of long-term exposure to PM₁, PM_2.5, NO₂ with type 2 diabetes mellitus prevalence and fasting blood glucose levels in Chinese rural populations.