Longitudinal associations of long-term exposure to ambient air pollution, residential greenness, and air temperature with type 2 diabetes subphenotypes: Results from the KORA cohort study.

OBJECTIVE

To examine the association between environmental exposures and specific type 2 diabetes (T2D) subphenotypes.

RESEARCH DESIGN AND

METHODS

We categorized T2D participants from the KORA F4 (2006-2008) and FF4 (2013-2014) study waves into three phenotypes using k-means clustering: Cluster A (insulin deficiency); Cluster B (age-related diabetes); and Cluster C (higher insulin resistance). The annual averages of fine particulate matter (PM2.5) and PM2.5 absorbance (PM2.5abs), annual air temperature mean (Tm) and standard deviations (Tsd), and greenness (NDVI), were assessed at participants' residences. Covariate-adjusted mixed multinomial logistic regression models were fitted to examine the effects of environmental exposures on diabetes subphenotypes. We also calculated joint odds ratios (ORs) to estimate the additive effects of exposure mixtures.

RESULTS

The longitudinal analysis showed that interquartile range (IQR) increases in PM2.5 (OR = 1.29, 95 % confidence interval [CI]: 1.01, 1.64) and PM2.5abs (OR = 1.30, 95 % CI: 1.01, 1.67) were associated with higher odds of being in T2D Cluster C, compared to normoglycemic individuals. Furthermore, we found that IQR increases in PM2.5 and Tsd, alongside with decreases in NDVI and Tm increased the odds of being in Cluster B (joint OR = 1.41, 95 % CI: 1.03, 1.93) and Cluster C (joint OR = 1.55, 95 % CI: 1.02, 2.36), while the combination of PM2.5abs with other exposures increased the odds of Cluster C (joint OR = 1.54, 95 % CI: 1.01, 2.33).

CONCLUSIONS

Our study contributes to an enhanced understanding of the associations between environmental exposures and diabetes, indicating increased risks for age-related and insulin-resistant diabetes.