Association between Short-Term Exposure to Air Pollution and Dyslipidemias among Type 2 Diabetic Patients in Northwest China: A Population-Based Study

Minzhen Wang, Shan Zheng, Yonghong Nie, Jun Weng, Ning Cheng, Xiaobin Hu, Xiaowei Ren, Hongbo Pei and Yana Bai
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Minzhen Wang: School of Public Health, Lanzhou University, Lanzhou 730000, China
Shan Zheng: School of Public Health, Lanzhou University, Lanzhou 730000, China
Yonghong Nie: Jinchang Center for Disease Prevention and Control, Jinchang 737100, China
Jun Weng: School of Public Health, Lanzhou University, Lanzhou 730000, China
Ning Cheng: College of Basic Medicine, Lanzhou University, Lanzhou 730000, China
Xiaobin Hu: School of Public Health, Lanzhou University, Lanzhou 730000, China
Xiaowei Ren: School of Public Health, Lanzhou University, Lanzhou 730000, China
Hongbo Pei: School of Public Health, Lanzhou University, Lanzhou 730000, China
Yana Bai: School of Public Health, Lanzhou University, Lanzhou 730000, China

IJERPH, 2018, vol. 15, issue 4, 1-13

Abstract: 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 , SO 2 , NO 2 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 SO 2 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 NO 2 and LDL-C was found ( p _non-lin-association < 0.0001). A J-shaped non-linear relationship between PM 10 and TC, HDL-C ( p _non-lin-association = 0.0173, 0.0367) was also revealed. In linear regression analyses, a 10 μg/m 3 increment in SO 2 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/m 3 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 NO 2 , an increment of 10 μg/m 3 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 SO 2 and NO 2 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.

Keywords: air pollution; diabetes; total cholesterol; triglycerides; low-density lipoprotein cholesterol; decreased high-density lipoprotein cholesterol (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
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