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Conjunctivitis is an inflammatory disease of the conjunctival tissue caused by a variety of causes; despite the conjunctiva being directly exposed to the external atmospheric environment, the important role of air pollution is not fully evaluated, especially in areas with poor air quality undergoing rapid economic and industrial development. Information on 59,731 outpatient conjunctivitis visits from 1 January 2013 to 31 December 2020 was obtained from the Ophthalmology Department of the First Affiliated Hospital of Xinjiang Medical University (Urumqi, Xinjiang, China), and data on six air pollutants including particulate matter with a median aerometric diameter of less than 10 and 2.5 mm (PM 10 and PM 2.5 , respectively), carbon monoxide (CO), sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ) from eleven standard urban background fixed air quality monitors were also recorded. A time-series analysis design and a quasi-Poisson generalized linear regression model combined with a distributed lagged nonlinear model (DLNM) were used to fit the effect of exposure to air pollutants on the risk of conjunctivitis outpatient visits. Further subgroup analyses were conducted for gender, age, and season, as well as the type of conjunctivitis. Single and multi-pollutant models showed that exposure to PM 2.5 , PM 10 , NO 2 , CO, and O 3 was associated with increased risk of outpatient conjunctivitis visits on the lag 0 day and various other lag days. Variations in the effect estimates on direction and magnitude were found in different subgroup analyses. We conducted the first time-series analysis with the longest duration as well as the largest sample size in Northwest China, which provides evidence that outpatient conjunctivitis visits is significantly associated with air pollution in Urumqi, China. Meanwhile, our results demonstrate the effectiveness of SO 2 reduction in reducing the risk of outpatient conjunctivitis visits in the Urumqi region and reaffirm the need to implement special air pollution control measures., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Conjunctivitis is a common multifactorial inflammatory ocular surface disease characterized by symptoms such as congestion, edema, and increased secretion of conjunctival tissue, and the potential effects of meteorological factors as well as extreme meteorological factors on conjunctivitis and their lagging effects have not been fully evaluated. We obtained the electronic case information of 59,731 outpatients with conjunctivitis from the Ophthalmology Department of the First Affiliated Hospital of Xinjiang Medical University (Urumqi, Xinjiang, China) for the period from January 1, 2013, to December 31, 2020. Meteorological data for daily mean temperature (°C), daily relative humidity (%), daily average wind speed (m/s), and atmospheric pressure (hPa) were obtained from the China Meteorological Data Sharing Service. The air pollutant data were obtained from 11 standard urban background fixed air quality monitors. A time-series analysis design and a quasi-Poisson generalized linear regression model combined with a distributed lagged nonlinear model (DLNM) were used to fit the effects of exposure to different meteorological factors and extreme weather on conjunctivitis outpatient visits. Subgroup analyses were performed on gender, age and season, and type of conjunctivitis. Univariate and multifactorial model results indicated that each 10-unit increase in mean temperature and relative humidity was associated with an increased risk of conjunctivitis outpatient visits, while each 10-unit increase in atmospheric pressure was associated with a decreased risk. The results of the extreme weather analysis suggested that extremely low levels of atmospheric pressure and relative humidity as well as extreme levels of temperature were associated with an increased risk of outpatient conjunctivitis visits, and extreme wind speeds were associated with a decreased risk. The results of the subgroup analysis suggested gender, age, and seasonal differences. We conducted the first large sample size time-series analysis in the large city furthest from the ocean in the world and confirmed for the first time that elevated mean temperature and extreme low levels of relative humidity in Urumqi were risk factors for local conjunctivitis outpatient visits, while elevated atmospheric pressure and extreme low levels of wind speed were protective factors, and there were lagged effects of temperature and atmospheric pressure. Multicenter studies with larger sample sizes are needed., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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]