Joint effects of air pollution and temperature on glycemia: An exposome analysis in European cohorts

The interdependent long-term effects of a climate-change relevant residential exposome on glycemia in persons without diabetes are not well understood. Applying the exposome analysis approach that we previously developed for lung function, the current analysis aims to identify exposome factors including their joint associations with glycated hemoglobin (HbA1c).

A pooled dataset of 33'989 measurements of HbA1ccollected between 1999 and 2021 from 21'259 participants in two mature birth cohorts and seven adult cohorts were used to assess cross-sectional associations with annual air pollution, greenness, and ambient temperature exposures. Elastic net regression was applied to identify influential exposome features based on a model that a priori included all linear and quadratic exposure terms and their two-way interactions. Elastic net regression results were put into the context of single and combined environmental scenarios (improvement ofair quality, improvement of greenness, climate change related alterations of ambient temperature).

Elastic net regression ofHbA1c stably identified non-zero coefficients for coarse particle concentrations (PM₁₀) and temperature (standard deviation of daily mean temperature) and for their interaction terms, indicating the potential importance of their joint effects. The environmental scenario of improving air quality predicted decreased HbA1c. The environmental scenario assuming climate change-related temperature changes predicted increased HbA1c. The predicted beneficial effects of improving air pollution on glycemia gained in relevance in the presence of climate change, in particular in non-smokers. No non-zero coefficients were found for greenness, neither as main effect nor in interactions with air pollution or temperature.

With respect to metabolic health, our results point to the increasing relevance of improving air quality and meeting WHO guideline values in the era of climate change, particularly in cities where high temperature levels, high levels of air pollution and a high diabetes risk co-occur.