Recent studies suggest air pollution as an underlying factor to kidney disease. However, there is still limited knowledge about the short-term correlation between glomerulonephritis (GN) and air pollution. Thus, we aim to fill this research gap by investigating the short-term correlation between GN clinical visits and air pollution exposure.
Between 2015 and 2019, daily GN visit data from two grade A tertiary hospitals in Hefei City were collected, along with corresponding air pollution and meteorological data. A generalized linear model integrated with a distributed lag nonlinear model was employed to analyze the relationship between GN visits and air pollutants. Moreover, we incorporated a dual pollutant model to account for the combined effects of multiple pollutants. Furthermore, subgroup analyses were performed to identify vulnerable populations based on gender, age, and season.
The association between 23,475 GN visits and air pollutants was assessed, and significant positive associations were found between CO and NO2 exposure and GN visit risk. The single-day lagged effect model for CO showed increased risks for GN visits from lag0 (RR: 1.129, 95% CI: 1.031β1.236) to lag2 (RR: 1.034, 95% CI: 1.011β1.022), with the highest risk at lag0. In contrast, NO2 displayed a more persistent impact (lag1βlag4) on GN visit risk, peaking at lag2 (RR: 1.017, 95% CI: 1.011β1.022). Within the dual-pollutant model, the significance persisted for both CO and NO2 after adjusting for each other. Subgroup analyses showed that the cumulative harm of CO was greater in the cold-season and older adult groups. Meanwhile, the female group was more vulnerable to the harmful effects of cumulative exposure to NO2.
Our study indicated that CO and NO2 exposure can raise the risk of GN visits, and female and older adult populations exhibited greater susceptibility.