Association of physical activity and air pollution exposure with the risk of type 2 diabetes: a large population-based prospective cohort study.

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.

Healthy Sleep Associated With Lower Risk of Hypertension Regardless of Genetic Risk: A Population-Based Cohort Study.

Background: Hypertension is a leading contributor to the global burden of disease and to mortality. The combined effects of sleep factors on the risk of hypertension are unclear. We aimed to evaluate the effect of combined sleep factors on the risk of hypertension and to explore whether this association is independent of genetic risk. Methods: This population-based prospective cohort study included 170,378 participants from the UK Biobank study. We conducted a healthy sleep score based on a combination of major five sleep factors and a genetic risk score based on 118 risk variants. Cox proportional hazard regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: A total of 170,378 participants were included. Compared to participants with a healthy sleep score of 0-1, those with healthy sleep scores of 2 (HR, 0.90; 95% CI, 0.83-0.98), 3 (HR, 0.81; 95% CI, 0.75-0.88), 4 (HR, 0.74; 95% CI, 0.68-0.81), or 5 (HR, 0.67; 95% CI, 0.59-0.77) had increasingly lower risks of hypertension (P for trend <0.001). Participants with high genetic risk and an unfavorable sleep pattern had a 1.80-fold greater risk of hypertension than participants with low genetic risk and a favorable sleep pattern. The association between sleep patterns and hypertension persisted in subgroup analysis, stratified by the genetic risk. Nearly 18.2% of hypertension events in this cohort could be attributed to unfavorable sleep pattern. Conclusions: Favorable sleep pattern was associated with a low risk of hypertension, regardless of genetic risk. These findings highlight the potential of sleep interventions to reduce risk of hypertension across entire populations.