TY - JOUR
T1 - Association of physical activity and air pollution exposure with the risk of type 2 diabetes
T2 - a large population-based prospective cohort study
AU - Li, Zhi Hao
AU - Zhong, Wen Fang
AU - Zhang, Xi Ru
AU - Chung, Vincent Ch
AU - Song, Wei Qi
AU - Chen, Qing
AU - Wang, Xiao Meng
AU - Huang, Qing Mei
AU - Shen, Dong
AU - Zhang, Pei Dong
AU - Liu, Dan
AU - Zhang, Yu Jie
AU - Chen, Pei Liang
AU - Cheng, Xin
AU - Yang, Hai Lian
AU - Cai, Miao Chun
AU - Gao, Xiang
AU - Kraus, Virginia Byers
AU - Mao, Chen
N1 - Funding Information:
This work was supported by the National Natural Science Foundation of China (82204115, 82103931, 82003443, and 81973109), the Project Supported by the Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2019), the Construction of High-level University of Guangdong (G820332010, G618339167, and G618339164), the Guangdong Basic and Applied Basic Research Foundation (2022A1515012085, 2021A1515011629, and 2021A1515110230), the Guangzhou Science and Technology Project (202002030255), and the Young Elite Scientists Sponsorship Program by CAST (2021QNRC001 and 2019QNRCO01). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - Background: The interplay between physical activity (PA) and air pollution in relation to type 2 diabetes (T2D) remains largely unknown. Based on a large population-based cohort study, this study aimed to examine whether the benefits of PA with respect to the risk of T2D are moderated by exposure to air pollution. Methods: UK Biobank participants (n = 359,153) without diabetes at baseline were included. Information on PA was obtained using the International Physical Activity Questionnaire short form. Exposure to air pollution, including PM2.5, PMcoarse (PM2.5−10), PM10, and NO2, was estimated from land use regression models. Cox regression models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs). Results: During a median of 8.9 years of follow-up, 13,706 T2D events were recorded. Compared with a low PA level, the HRs for the risk of T2D among individuals with moderate and high PA were 0.82 (95% CI, 0.79–0.86) and 0.73 (95% CI, 0.70–0.77), respectively. Compared with low levels of air pollution, the HRs for risk of T2D for high levels of air pollution (PM2.5, PMcoarse, PM10, and NO2) were 1.19 (1.14–1.24), 1.06 (1.02–1.11), 1.13 (1.08–1.18), and 1.19 (1.14–1.24), respectively. There was no effect modification of the associations between PA and T2D by air pollution (all P-interactions > 0.05). The inverse associations between PA and T2D in each air pollution stratum were generally consistent (all P for trend < 0.05). Conclusion: A higher PA and lower air pollution level were independently associated with a lower risk of T2D. The beneficial effects of PA on T2D generally remained stable among participants exposed to different levels of air pollution. Further studies are needed to replicate our findings in moderately and severely polluted areas.
AB - Background: The interplay between physical activity (PA) and air pollution in relation to type 2 diabetes (T2D) remains largely unknown. Based on a large population-based cohort study, this study aimed to examine whether the benefits of PA with respect to the risk of T2D are moderated by exposure to air pollution. Methods: UK Biobank participants (n = 359,153) without diabetes at baseline were included. Information on PA was obtained using the International Physical Activity Questionnaire short form. Exposure to air pollution, including PM2.5, PMcoarse (PM2.5−10), PM10, and NO2, was estimated from land use regression models. Cox regression models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs). Results: During a median of 8.9 years of follow-up, 13,706 T2D events were recorded. Compared with a low PA level, the HRs for the risk of T2D among individuals with moderate and high PA were 0.82 (95% CI, 0.79–0.86) and 0.73 (95% CI, 0.70–0.77), respectively. Compared with low levels of air pollution, the HRs for risk of T2D for high levels of air pollution (PM2.5, PMcoarse, PM10, and NO2) were 1.19 (1.14–1.24), 1.06 (1.02–1.11), 1.13 (1.08–1.18), and 1.19 (1.14–1.24), respectively. There was no effect modification of the associations between PA and T2D by air pollution (all P-interactions > 0.05). The inverse associations between PA and T2D in each air pollution stratum were generally consistent (all P for trend < 0.05). Conclusion: A higher PA and lower air pollution level were independently associated with a lower risk of T2D. The beneficial effects of PA on T2D generally remained stable among participants exposed to different levels of air pollution. Further studies are needed to replicate our findings in moderately and severely polluted areas.
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U2 - 10.1186/s12940-022-00922-3
DO - 10.1186/s12940-022-00922-3
M3 - Article
C2 - 36336676
AN - SCOPUS:85141409717
SN - 1476-069X
VL - 21
JO - Environmental Health: A Global Access Science Source
JF - Environmental Health: A Global Access Science Source
IS - 1
M1 - 106
ER -
