The joint effects of physical activity and air pollution on type 2 diabetes in older adults

Abstract

Background: Older adults with type 2 diabetes are at higher risk of developing common geriatric syndromes and have a lower quality of life. To prevent type 2 diabetes in older adults, it's unclear whether the health benefits of physical activity (PA) will be influenced by the harms caused by increased exposure to air pollution during PA, especially in developing countries with severe air pollution problem. We aimed to investigate the joint effects of PA and long-term exposure to air pollution on the type 2 diabetes in older adults from China.

Methods: This cross-sectional study was based on the China Multi-Ethnic cohort (CMEC) study. The metabolic equivalent of PA was calculated according to the PA scale during the CMEC baseline survey. High resolution air pollution datasets (PM₁₀, PM_2.5 and PM₁) were collected from open products. The joint effects were assessed by the marginal structural mean model with generalized propensity score.

Results: A total of 36,562 participants aged 50 to 79 years were included in the study. The prevalence of type 2 diabetes was 10.88%. The mean (SD) level of PA was 24.93 (18.60) MET-h/d, and the mean (SD) level of PM₁₀, PM_2.5, and PM₁ were 70.00 (23.32) µg/m³, 40.45 (15.66) µg/m³ and 27.62 (6.51) µg/m³, respectively. With PM₁₀ < 92 µg/m³, PM_2.5 < 61 µg/m³, and PM₁ < 36 µg/m³, the benefit effects of PA on type 2 diabetes was significantly greater than the harms due to PMs when PA levels were roughly below 80 MET-h/d. With PM₁₀ ≥ 92 µg/m³, PM_2.5 ≥ 61 µg/m³, and PM₁ ≥ 36 µg/m³, the odds ratio (OR) first decreased and then rose rapidly with confidence intervals progressively greater than 1 and break-even points close to or even below 40 MET-h/d.

Conclusions: Our findings implied that for the prevention of type 2 diabetes in older adults, the PA health benefits outweighed the harms of air pollution except in extreme air pollution situations, and suggested that when the air quality of residence is severe, the PA levels should ideally not exceed 40 MET-h/d.

Keywords: Air pollution; Joint effects; Older adults; Physical activity; Type 2 diabetes.

Fig. 1

The geographical distribution of PM₁₀, PM_2.5 and PM₁ concentrations by participants’ address locations

Fig. 2

The balance results of covariates in the weighted (blue), and original observational population (red). The three subplots showed the ACs between covariates and PA and the corresponding pollutants before and after weighting with the bi-dimensional GPS model constructed for PA and PM₁₀, PA and PM_2.5, and PA and PM₁, respectively. Covariates were age, sex, marital status, education, annual household income, BMI, smoking, aMED score, sedentary time, etc., as detailed in the Methods

Fig. 3

The exposure–response relationship between PA and type 2 diabetes at different exposure levels of air pollution for older adults. The nine values in subplots A, B and C represented the different pollution concentrations (µg/m³) of PM₁₀, PM_2.5 and PM₁ respectively. The OR limit is set to 5, and the grey shaded area indicated the confidence interval (95% CI). The 95% CI not containing the value of 1, represented by the horizontal dashed line, indicated that the association is statistically significant. Covariates mentioned in the Methods section were integrated by the bi-dimensional GPS, which was combined in the outcome model