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The potential effects of air pollution on the ocular surface environment have not been fully evaluated, and even fewer studies have been conducted on the lagged effects of air pollution on dry eye disease (DED). The data of 9970 DED outpatients between 1 January 2013 and 31 December 2020, and data for six air pollutants, including PM10, PM2.5, carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3), were obtained from 11 standard urban background stationary air quality monitors in Urumqi, Xinjiang, China. Time series analysis design and quasi-Poisson generalized linear regression models combined with distributed lagged nonlinear models (DLNM) were used. Single- and multi-pollutant model results suggest that each additional per 10 μg/m3 of PM10, NO2, and SO2 is associated with an increased risk of outpatient DED on lag day 0 and PM2.5, NO2, and SO2 with other cumulative lag days; R software version 4.0.4 (15 February 2021) was used for the analysis. We conducted first time series analysis with a large sample size in northwest China (Xinjiang) and confirmed, for the first time, the impact of air pollution including particulate pollutants (PM10, PM2.5) and acidic gasses (SO2, NO2) on DED risk in the Urumqi region, and suggested the potential lagged effects of PM2.5, SO2, and NO2. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to elucidate the relationship between retinopathy status or severity and the all-cause and specific-cause mortality risk based on the updated National Health and Nutrition Examination Survey (NHANES) database and 2019 Public Access Link mortality file., Methods: In this prospective cohort study, a total of 6,797 participants aged over 40 years based on NHANES 2005-2008 were analyzed. The severity of retinopathy was classified into 4 grades-no retinopathy, mild non-proliferative retinopathy (NPR), moderate to severe NPR, and proliferative retinopathy (PR). Multiple covariate-adjusted Cox proportional hazards regression models and Fine and Gray competing risk regression models were used to assess the all-cause and cause-specific mortality risks, respectively. The propensity score matching (PSM) approach was also applied additionally to adequately balance between-group covariates to validate our findings., Results: A final total of 4,808 participants representing 18,282,772 United States (US) non-hospitalized participants were included for analysis, 50.27% were male ( n  = 2,417), 55.32% were non-hispanic white ( n  = 2,660), and mean [SE] age, 56.10 [0.40] years. After a median follow-up of 12.24 years (interquartile range, 11.16-13.49 years), 1,164 participants died of all-cause mortality, of which 941 (80.84%) died without retinopathy and 223 (19.16%) died with retinopathy at baseline. The presence of retinopathy was associated with increased all-cause mortality, cardiovascular disease (CVD), and diabetes mellitus (DM)-specific mortality, and the results remain consistent after PSM. Severity analysis showed that only mild NPR was associated with an increased all-cause mortality risk (hazard ratio (HR) = 2.01; 95% confidence interval (CI), 1.00-4.03), while increased CVD and DM-specific mortality risk were associated with all grades of retinopathy and were exponentially greater with increasing retinopathy severity, and the trend test was also significant (P for trend 0.004 and 0.04, respectively)., Discussion: Our findings suggest that the diagnosis of retinopathy is an independent risk factor for all-cause mortality in people over 40 years old. Retinopathy grading is significantly associated with the survival risk of patients with CVD or DM, it can be a valuable predictor in the stratified management and risk warning of CVD or DM patients, as well as in the monitoring of systemic vasculopathy status., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Gui, Wang, Qiao, Lin, Wang, Zhang, Xu, Huang, Tao, Hu, Tao, Jiang and Liu.)