Siqi Zhang1, Sarah Mwiberi2, Regina Pickford3, Susanne Breitner4, Cornelia Huth5, Wolfgang Koenig6, Wolfgang Rathmann7, Christian Herder8, Michael Roden8, Josef Cyrys3, Annette Peters9, Kathrin Wolf5, Alexandra Schneider5. 1. Institute of Epidemiology, Helmholtz Centre Munich, German Research Centre for Environmental Health, Neuherberg, Germany. Electronic address: siqi.zhang@helmholtz-muenchen.de. 2. Institute of Epidemiology, Helmholtz Centre Munich, German Research Centre for Environmental Health, Neuherberg, Germany; Research Unit of Radiation Cytogenetics, Helmholtz Centre Munich, German Research Centre for Environmental Health, Neuherberg, Germany. 3. Institute of Epidemiology, Helmholtz Centre Munich, German Research Centre for Environmental Health, Neuherberg, Germany. 4. Institute of Epidemiology, Helmholtz Centre Munich, German Research Centre for Environmental Health, Neuherberg, Germany; Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig Maximilians University Munich, Munich, Germany. 5. Institute of Epidemiology, Helmholtz Centre Munich, German Research Centre for Environmental Health, Neuherberg, Germany; German Centre for Diabetes Research, DZD, Munich-Neuherberg, Germany. 6. German Heart Centre Munich, Technical University of Munich, Munich, Germany; German Centre for Cardiovascular Research, DZHK, Partner Site Munich, Munich, Germany; Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany. 7. German Centre for Diabetes Research, DZD, Munich-Neuherberg, Germany; Institute for Biometrics and Epidemiology, German Diabetes Centre, Leibniz Centre for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany. 8. German Centre for Diabetes Research, DZD, Munich-Neuherberg, Germany; Institute for Clinical Diabetology, German Diabetes Centre, Leibniz Centre for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany. 9. Institute of Epidemiology, Helmholtz Centre Munich, German Research Centre for Environmental Health, Neuherberg, Germany; Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig Maximilians University Munich, Munich, Germany; German Centre for Diabetes Research, DZD, Munich-Neuherberg, Germany; German Centre for Cardiovascular Research, DZHK, Partner Site Munich, Munich, Germany.
Abstract
BACKGROUND: Impaired insulin sensitivity could be an intermediate step that links exposure to air pollution to the development of type 2 diabetes. However, longitudinal associations of air pollution with insulin sensitivity remain unclear. Our study investigated the associations of long-term air pollution exposure with the degree and rate of change of insulin sensitivity. METHODS: In this longitudinal study, we analysed data from the Cooperative Health Research in the Region of Augsburg (KORA) cohort from Augsburg, Germany, which recruited participants aged 25-74 years in the survey between 1999 and 2001 (KORA S4), with two follow-up examinations in 2006-08 (KORA F4) and 2013-14 (KORA FF4). Serum concentrations of fasting insulin and glucose, and homoeostasis model assessment of insulin resistance (HOMA-IR, a surrogate measure of insulin sensitivity) and β-cell function (HOMA-B, a surrogate marker for fasting insulin secretion) were assessed at up to three visits between 1999 and 2014. Annual average air pollutant concentrations at the residence were estimated by land-use regression models. We examined the associations of air pollution with repeatedly assessed biomarker levels using mixed-effects models, and we assessed the associations with the annual rate of change in biomarkers using quantile regression models. FINDINGS: Among 9620 observations from 4261 participants in the KORA cohort, we included 6008 (62·5%) observations from 3297 (77·4%) participants in our analyses. Per IQR increment in annual average air pollutant concentrations, HOMA-IR significantly increased by 2·5% (95% CI 0·3 to 4·7) for coarse particulate matter, by 3·1% (0·9 to 5·3) for PM2·5, by 3·6% (1·0 to 6·3) for PM2·5absorbance, and by 3·2% (0·6 to 5·8) for nitrogen dioxide, and borderline significantly increased by 2·2% (-0·1 to 4·5) for ozone, whereas it did not significantly increase for the whole range of ultrafine particles. Similar positive associations in slightly smaller magnitude were observed for HOMA-B and fasting insulin levels. In addition, air pollutant concentrations were positively associated with the annual rate of change in HOMA-IR, HOMA-B, and fasting insulin. Neither the level nor the rate of change of fasting glucose were associated with air pollution exposure. INTERPRETATION: Our study indicates that long-term air pollution exposure could contribute to the development of insulin resistance, which is one of the key factors in the pathogenesis of type 2 diabetes. FUNDING: German Federal Ministry of Education and Research.
BACKGROUND: Impaired insulin sensitivity could be an intermediate step that links exposure to air pollution to the development of type 2 diabetes. However, longitudinal associations of air pollution with insulin sensitivity remain unclear. Our study investigated the associations of long-term air pollution exposure with the degree and rate of change of insulin sensitivity. METHODS: In this longitudinal study, we analysed data from the Cooperative Health Research in the Region of Augsburg (KORA) cohort from Augsburg, Germany, which recruited participants aged 25-74 years in the survey between 1999 and 2001 (KORA S4), with two follow-up examinations in 2006-08 (KORA F4) and 2013-14 (KORA FF4). Serum concentrations of fasting insulin and glucose, and homoeostasis model assessment of insulin resistance (HOMA-IR, a surrogate measure of insulin sensitivity) and β-cell function (HOMA-B, a surrogate marker for fasting insulin secretion) were assessed at up to three visits between 1999 and 2014. Annual average air pollutant concentrations at the residence were estimated by land-use regression models. We examined the associations of air pollution with repeatedly assessed biomarker levels using mixed-effects models, and we assessed the associations with the annual rate of change in biomarkers using quantile regression models. FINDINGS: Among 9620 observations from 4261 participants in the KORA cohort, we included 6008 (62·5%) observations from 3297 (77·4%) participants in our analyses. Per IQR increment in annual average air pollutant concentrations, HOMA-IR significantly increased by 2·5% (95% CI 0·3 to 4·7) for coarse particulate matter, by 3·1% (0·9 to 5·3) for PM2·5, by 3·6% (1·0 to 6·3) for PM2·5absorbance, and by 3·2% (0·6 to 5·8) for nitrogen dioxide, and borderline significantly increased by 2·2% (-0·1 to 4·5) for ozone, whereas it did not significantly increase for the whole range of ultrafine particles. Similar positive associations in slightly smaller magnitude were observed for HOMA-B and fasting insulin levels. In addition, air pollutant concentrations were positively associated with the annual rate of change in HOMA-IR, HOMA-B, and fasting insulin. Neither the level nor the rate of change of fasting glucose were associated with air pollution exposure. INTERPRETATION: Our study indicates that long-term air pollution exposure could contribute to the development of insulin resistance, which is one of the key factors in the pathogenesis of type 2 diabetes. FUNDING: German Federal Ministry of Education and Research.
Authors: Noémie Letellier; Steven Zamora; Chad Spoon; Jiue-An Yang; Marion Mortamais; Gabriel Carrasco Escobar; Dorothy D Sears; Marta M Jankowska; Tarik Benmarhnia Journal: Environ Res Date: 2022-02-01 Impact factor: 8.431