Association between Short-Term Exposure to Air Pollution and Dyslipidemias among Type 2 Diabetic Patients in Northwest China

A Population-Based Study

Bibliographic Data

ID15468385
AuthorsMinzhen Wang (0000-0002-5839-3949, Lanzhou University), Shan Zheng (0000-0002-0901-7031, Lanzhou University), Yonghong Nie (0009-0003-6421-1560, Nanchang Center for Disease Control and Prevention), Jun Weng (0000-0002-8295-3459, Lanzhou University), Ning Cheng (0000-0002-1124-9093, Lanzhou University), Xiaobin Hu (0000-0002-9680-6302, Lanzhou University), Xiaowei Ren (0000-0002-8316-2755, Lanzhou University), Hongbo Pei (Lanzhou University), Yana Bai (0000-0002-9563-1723, Lanzhou University, corresponding author)
Year2018
Volume15
Issue4
Pages631-631
Publication date2018-03-30
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph15040631
PMID29601472
OpenAlexW2795342803
LanguageEN
Citations received1
References cited35

Air pollution exposure may play an adverse role in diabetes. However, little data are available directly evaluating the effects of air pollution exposure in blood lipids of which dysfunction has been linked to diabetes or its complications. We aimed to evaluate the association between air pollution and lipids level among type 2 diabetic patients in Northwest China. We performed a population-based study of 3912 type 2 diabetes patients in an ongoing cohort study in China. Both spline and multiple linear regressions analysis were used to examine the association between short-term exposure to PM 10 , SO2, NO2 and total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). By spline analyses, we observed that the relationship between SO2 and HDL-C and LDL-C was shown to be non-linear ( p _non-lin-association = 0.0162 and 0.000). An inverted U-shaped non-linear relationship between NO2 and LDL-C was found ( p _non-lin-association 10 and TC, HDL-C ( p _non-lin-association = 0.0173, 0.0367) was also revealed. In linear regression analyses, a 10 μg/m3 increment in SO2 was associated with 1.31% (95% CI: 0.40-2.12%), 3.52% (95% CI: 1.07-6.03%) and 7.53% (95% CI: 5.98-9.09%) increase in TC, TG and LDL-C, respectively. A 10 μg/m3 increment in PM 10 was associated with 0.45% (95% CI: 0.08-0.82%), 0.29% (95% CI: 0.10-0.49%) and 0.83% (95% CI: 0.21-1.45%) increase in TC, HDL-C and LDL-C, respectively. For NO2, an increment of 10 μg/m3 was statistically associated with -3.55% (95% CI: -6.40-0.61%) and 39.01% (95% CI: 31.43-47.03%) increase in HDL-C and LDL-C. The adverse effects of air pollutants on lipid levels were greater in female and elder people. Further, we found SO2 and NO2 played a more evident role in lipid levels in warm season, while PM 10 appeared stronger in cold season. The findings suggest that exposure to air pollution has adverse effects on lipid levels among type 2 diabetes patients, and vulnerable people may pay more attention on severe air pollution days

Cholesterol · Diabetes mellitus · Environmental health · Linear regression · Population · Type 2 diabetes · Type 2 Diabetes Mellitus · Air Quality and Health Impacts · Climate Change and Health Impacts · Energy, Environment, and Transportation Policies · Mathematics · Medicine · Endocrinology · Internal Medicine

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