Diabetologia · 2026
Association of long-term exposure to air pollution, built environment and air temperature with the incidence of prediabetes phenotypes, and prediabetes remission and progression to type 2 diabetes: a longitudinal study in the KORA cohort.
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Xi Yue, Thorand Barbara, Schneider Alexandra, Wolf Kathrin, Dallavalle Marco, Nikolaou Nikolaos, Linkohr Birgit, Kronenberg Florian, Rathmann Wolfgang, Schlesinger Sabrina, Herder Christian, Schwettmann Lars, Zeller Tanja, Jumpertz von Schwartzenberg Reiner, Breitner-Busch Susanne, Peters Annette
Аннотация
AIMS/HYPOTHESIS: Environmental exposures have been adversely associated with the risk of diabetes but their role in the remission and progression of prediabetes (impaired glucose tolerance [IGT] and/or impaired fasting glucose [IFG]), especially different phenotypes, is poorly understood. This study aimed to investigate the relationship between environmental exposures and remission or progression of prediabetes phenotypes.
METHODS: Data were derived from the KORA (Cooperative Health Research in the Region of Augsburg) cohort in Southern Germany (2006-2022). Glucose tolerance status was defined according to the 1999/2006 WHO criteria. We included annual values of particulate matter (PM), light at night (LAN), normalised difference vegetation index (NDVI), imperviousness (IMP) and air temperature variation (Tsd). We fitted complementary log-log regression models for associations between IQR changes in exposures and the incidence of prediabetes phenotypes (isolated impaired fasting glucose [iIFG], isolated impaired glucose tolerance [iIGT], or their combination [IFG+IGT]), remission to normal glucose tolerance (NGT) or progression to type 2 diabetes. We also applied Quantile g-computation regression models for joint association analysis.
RESULTS: During the follow-up, 370/1618 participants developed prediabetes (124 iIFG, 199 iIGT and 47 IFG+IGT). Among participants with prediabetes, 136/367 (without medication) regressed to NGT and 133/420 progressed to type 2 diabetes. We observed consistent associations of air pollutants and the built environment with iIGT or IFG+IGT. For example, an IQR increase in PM2.5 (aerodynamic diameter ≤2.5 μm) showed an HR of 1.89 (95% CI 1.07, 3.31) for the risk of IFG+IGT and 1.59 (95% CI 1.03, 2.46) with a decrease in NDVI. Co-exposure to environmental mixtures (higher air pollution, Tsd, IMP and LAN, and lower NDVI) was associated with increased risks of iIFG, iIGT and IFG+IGT. Additionally, lower NDVI (HR 0.52 [95% CI 0.28, 0.96]), higher LAN (HR 0.22 [95% CI 0.08, 0.62]) and higher IMP were associated with reduced remission of iIFG but we found no statistically significant associations with the progression to type 2 diabetes.
CONCLUSIONS/INTERPRETATION: The findings indicate potential heterogeneity in environmental exposures and prediabetes phenotypes. Specifically, they are associated with increased incidence of IGT and decreased remission of iIFG.
METHODS: Data were derived from the KORA (Cooperative Health Research in the Region of Augsburg) cohort in Southern Germany (2006-2022). Glucose tolerance status was defined according to the 1999/2006 WHO criteria. We included annual values of particulate matter (PM), light at night (LAN), normalised difference vegetation index (NDVI), imperviousness (IMP) and air temperature variation (Tsd). We fitted complementary log-log regression models for associations between IQR changes in exposures and the incidence of prediabetes phenotypes (isolated impaired fasting glucose [iIFG], isolated impaired glucose tolerance [iIGT], or their combination [IFG+IGT]), remission to normal glucose tolerance (NGT) or progression to type 2 diabetes. We also applied Quantile g-computation regression models for joint association analysis.
RESULTS: During the follow-up, 370/1618 participants developed prediabetes (124 iIFG, 199 iIGT and 47 IFG+IGT). Among participants with prediabetes, 136/367 (without medication) regressed to NGT and 133/420 progressed to type 2 diabetes. We observed consistent associations of air pollutants and the built environment with iIGT or IFG+IGT. For example, an IQR increase in PM2.5 (aerodynamic diameter ≤2.5 μm) showed an HR of 1.89 (95% CI 1.07, 3.31) for the risk of IFG+IGT and 1.59 (95% CI 1.03, 2.46) with a decrease in NDVI. Co-exposure to environmental mixtures (higher air pollution, Tsd, IMP and LAN, and lower NDVI) was associated with increased risks of iIFG, iIGT and IFG+IGT. Additionally, lower NDVI (HR 0.52 [95% CI 0.28, 0.96]), higher LAN (HR 0.22 [95% CI 0.08, 0.62]) and higher IMP were associated with reduced remission of iIFG but we found no statistically significant associations with the progression to type 2 diabetes.
CONCLUSIONS/INTERPRETATION: The findings indicate potential heterogeneity in environmental exposures and prediabetes phenotypes. Specifically, they are associated with increased incidence of IGT and decreased remission of iIFG.