Abstract
Background: A growing number of epidemiological studies show associations between environmental factors and impaired cardiometabolic health. However, evidence is scarce concerning these risk factors and their impact on metabolic syndrome (MetS). This analysis aims to investigate associations between long-term exposure to air pollution, road traffic noise, residential greenness, and MetS. Methods: We used data of the first (F4, 2006-2008) and second (FF4, 2013-2014) follow-up of the population based KORA S4 survey in the region of Augsburg, Germany, to investigate associations between exposures and MetS prevalence at F4 (N = 2883) and MetS incidence at FF4 (N = 1192;average follow-up: 6.5 years). Residential long-term exposures to air pollution - including particulate matter (PM) with a diameter < 10 mu m (PM10), PM < 2.5 mu m (PM2.5), PM between 2.5 and 10 mu m (PMcoarse), absorbance of PM2.5 (PM2.5(abs)), particle number concentration (PNC), nitrogen dioxide (NO2), ozone (O-3) - and road traffic noise were modeled by land-use regression models and noise maps. For greenness, the Normalized Difference Vegetation Index (NDVI) was obtained. We estimated Odds Ratios (OR) for single and multi-exposure models using logistic regression and generalized estimating equations adjusted for confounders. Joint Odds Ratios were calculated based on the Cumulative Risk Index. Effect modifiers were examined with interaction terms. Results: We found positive associations between prevalent MetS and interquartile range (IQR) increases in PM10 (OR: 1.15;95% confidence interval [95% CI]: 1.02, 1.29), PM2.5 (OR: 1.14;95% CI: 1.02, 1.28), PMcoarse (OR: 1.14;95% CI: 1.02, 1.27), and PM(2.5)abs (OR: 1.17;95% CI: 1.03, 1.32). Results further showed negative, but non-significant associations between exposure to greenness and prevalent and incident MetS. No effects were seen for exposure to road traffic noise. Joint Odds Ratios from multi-exposure models were higher than ORs from models with only one exposure.
Item Type: | Journal article |
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Faculties: | Medicine |
Subjects: | 600 Technology > 610 Medicine and health |
ISSN: | 0160-4120 |
Language: | English |
Item ID: | 102858 |
Date Deposited: | 05. Jun 2023, 15:41 |
Last Modified: | 17. Oct 2023, 15:12 |