Sleep disorders have been verified to be associated with adverse health outcomes. Recent studies have linked ambient air pollution to sleep disorders. However, evidence with large sample size and especially prospective studies is very limited. We used data from a prospective cohort study established from 2015 to 2018 in Ningbo, China. Participants were followed-up after baseline survey through linkage to the regional Health Information System (HIS). Sleep disorders were defined based on International Classification of Disease 10 (ICD-10). Spatial-temporal land-use regression (LUR) models were used to estimate the annual exposure to particulate matter with diameter ≤ 2.5 µm (PM2.5), ≤ 10 µm (PM10) and nitrogen dioxides (NO2). The associations between long-term exposure to air pollutants and prevalence of sleep disorders were examined using logistic regression models, and Cox regression models for the effects of air pollution on the incidence of sleep disorders. A generalized weighted quantile sum (gWQS) regression was used in the multipollutant analysis. A total of 38,775 participants were included in the final analysis. Based on baseline data, we observed significant positive associations between air pollution exposure and increased odds of prevalent sleep disorders (Odds Ratio (OR)= 1.48, 95% confidence interval (CI): 1.41-1.55 for PM2.5; OR= 1.47,95%CI:1.38-1.57 for PM10; OR= 1.38, 95%CI:1.31-1.46 for NO2). In the longitudinal analysis, hazard ratios for incident sleep disorders associated with per interquartile range (IQR) increase in PM2.5, PM10 and NO2 were 1.14 (1.03, 1.25), 1.13 (1.01, 1.27) and 1.13 (1.04, 1.23), respectively. A gWQS regression analysis showed significant association between air pollution mixture and incident sleep disorders (OR=1.11, 95%CI: 1.03-1.20). Long-term exposure to PM2.5, PM10 and NO2 were associated with increased risk of sleep disorders in a Chinese population. Our findings could provide evidence for a more general role in the adverse health impact of air pollution.

A poor diet cannot fully explain the prevalence of obesity. Other environmental factors (e.g., heavy metals) have been reported to be associated with obesity. However, limited evidence is available for the combined effect of these factors on obesity. Therefore, we conducted a cross-sectional study and used the data from the National Health and Examination Survey (2007–2018) to explore the associations between diet quality and heavy metals and obesity. Diet quality was evaluated by the Healthy Eating Index-2015 (HEI-2015) score. Heavy metals included serum cadmium (Cd), lead (Pb), and mercury (Hg). We included 15,959 adults, with 5799 of obesity (body mass index ≥ 30 kg/m²). After adjustment for covariates, every interquartile range increase in HEI-2015 scores, Pb, Cd and Hg was associated with a 35% (odds ratios [OR] = 0.65, 95% confidence interval [CI]: 0.60, 0.70), 11% (OR = 0.89, 95% CI: 0.82, 0.98), 9% (OR = 0.91, 95% CI: 0.87, 0.96), 5% (OR = 0.85, 95% CI: 0.82, 0.89) reduction in risk of peripheral obesity, respectively. In addition, the association between the HEI-2015 scores and peripheral obesity was attenuated by higher levels of heavy metals (All p _interaction < 0.05). Results remained similar for abdominal obesity. Our study reveals the distinct effects of a high-quality diet and heavy metals on obesity prevalence, and the beneficial effect of a high-quality diet could be weakened by higher levels of heavy metals.