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Long-term exposure to air pollution, road traffic noise, residential greenness, and prevalent and incident metabolic syndrome: Results from the population-based KORA F4/FF4 cohort in Augsburg, Germany
Highlights We analyzed associations between air pollution, noise, greenness, and metabolic syndrome. PM10, PMcoarse, PM2.5, PM2.5abs were positively associated with prevalent metabolic syndrome. No significant associations were observed for incident metabolic syndrome.
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 µm (PM10), PM < 2.5 µm (PM2.5), PM between 2.5 and 10 µm (PMcoarse), absorbance of PM2.5 (PM2.5abs), particle number concentration (PNC), nitrogen dioxide (NO2), ozone (O3) – 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 PM2.5abs (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.
Long-term exposure to air pollution, road traffic noise, residential greenness, and prevalent and incident metabolic syndrome: Results from the population-based KORA F4/FF4 cohort in Augsburg, Germany
Highlights We analyzed associations between air pollution, noise, greenness, and metabolic syndrome. PM10, PMcoarse, PM2.5, PM2.5abs were positively associated with prevalent metabolic syndrome. No significant associations were observed for incident metabolic syndrome.
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 µm (PM10), PM < 2.5 µm (PM2.5), PM between 2.5 and 10 µm (PMcoarse), absorbance of PM2.5 (PM2.5abs), particle number concentration (PNC), nitrogen dioxide (NO2), ozone (O3) – 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 PM2.5abs (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.
Long-term exposure to air pollution, road traffic noise, residential greenness, and prevalent and incident metabolic syndrome: Results from the population-based KORA F4/FF4 cohort in Augsburg, Germany
Voss, Stephan (author) / Schneider, Alexandra (author) / Huth, Cornelia (author) / Wolf, Kathrin (author) / Markevych, Iana (author) / Schwettmann, Lars (author) / Rathmann, Wolfgang (author) / Peters, Annette (author) / Breitner, Susanne (author)
2020-12-21
Article (Journal)
Electronic Resource
English
Metabolic syndrome , Environmental epidemiology , Air pollution , Road traffic noise , Greenness , 33CCHS , 33 Communities Chinese Health Study , BMI , body mass index , CI , confidence interval , CRI , Cumulative Risk Index , DAG , directed acyclic graph , dB , decibel , GEE , generalized estimating equation , HDL , high-density lipoprotein , HNR Study , Heinz Nixdorf Recall Study , HR , hazard ratio , IDF , International Diabetes Federation , IQR , interquartile range , JOR , joint odds ratio , LUR model , land-use regression model , MetS , metabolic syndrome , N , number , NDVI , Normalized Difference Vegetation Index , NO<inf>2</inf> , nitrogen dioxide , O<inf>3</inf> , ozone , OR , Odds Ratio , PM , particulate matter , PM<inf>10</inf> , PM with aerodynamic diameter < 10 µm , PM<inf>2.5</inf> , PM with aerodynamic diameter < 2.5 µm , PM<inf>coarse</inf> , PM with aerodynamic diameter 2.5–10 µm , PM<inf>2.5</inf>abs , absorbance of PM<inf>2.5</inf> , PNC , particle number concentration , SD , standard deviation , WHR , waist-to-hip ratio
| Elsevier | 2024