The impact of air pollutant exposure on diabetes hospital admissions in a city of Xinjiang

  • Zhicong Fu Shihezi University School of Medicine, Shihezi 832000, Xinjiang, China; Key Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, the Xinjiang Production and Construction Corps, Shihezi 832000, Xinjiang, China
  • Haoxuan Gong Shihezi University School of Medicine, Shihezi 832000, Xinjiang, China; Key Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, the Xinjiang Production and Construction Corps, Shihezi 832000, Xinjiang, China
  • Xiaopeng Hu Shihezi University School of Medicine, Shihezi 832000, Xinjiang, China; Key Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, the Xinjiang Production and Construction Corps, Shihezi 832000, Xinjiang, China
  • Yuting Xie Shihezi University School of Medicine, Shihezi 832000, Xinjiang, China; Key Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, the Xinjiang Production and Construction Corps, Shihezi 832000, Xinjiang, China
  • Dongsheng Rui * Shihezi University School of Medicine, Shihezi 832000, Xinjiang, China; Key Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, the Xinjiang Production and Construction Corps, Shihezi 832000, Xinjiang, China
Article ID: 4570
DOI: https://doi.org/10.18282/po4570
Keywords: air pollution; type 2 diabetes; hospital admissions; distributed hysteresis nonlinear model

Abstract

Objective: To explore the influence of air pollution on the daily hospitalization admissions of diabetic patients in a certain city of Xinjiang and the differences among the population, providing a reference basis for formulating prevention and control policies for diabetes in response to air pollution in the future. Methods: Daily hospitalization admissions of 10 comprehensive hospitals in a certain city of Xinjiang from 2021 to 2022 were collected, along with air pollutants and meteorological monitoring data during the same period. The relationship between air pollutant concentrations and the daily hospital admission rates of diabetes patients was analyzed using a distribution lag nonlinear model. Results: There was no statistically significant difference in the impact of PM2.5 and PM10 exposure on daily hospital admission rates, with RR values reaching peak values at lag5, lag0, as follows: 1.06 (95% CI: 1.00, 1.12), 1.08 (95% CI: 1.00, 1.16); NO, SO2, O3, and CO affected the daily hospital admission rate of diabetes patients, with RR values reaching peak values at lag6, lag1, lag2, and lag5 days, respectively, as follows: 1.21 (95% CI: 1.11, 1.31), 1.69 (95% CI: 1.43, 1.99), 1.23 (95% CI: 1.14, 1.34), 1.36 (95% CI: 1.21, 1.53). PM2.5 had no statistically significant impact on the daily hospital admission rates of each subpopulation; PM10 had an immediate effect only on the daily hospital admission rate of males, reaching a peak at lag0 day at 1.16 (95% CI: 1.05, 1.28); NO2 had the largest RR values for the daily hospital admission rates of males and those under 65 years of age, respectively, at 1.22 (95% CI: 1.09, 1.35) and 1.19 (95% CI: 1.08, 1.32); the largest RR values for females and those over 65 years of age were 1.26 (95% CI: 1.11, 1.44) and 1.23 (95% CI: 1.07, 1.41), respectively, and these were statistically significant. SO3 and O3 showed an increasing trend in the daily hospital admission rates of each subpopulation before decreasing, with peaks appearing in lag1–lag3, which were statistically significant. Conclusion: Exposure to NO2, SO2, O3, and CO increased the risk of hospitalization for diabetes. The diabetic population of women and those over 65 years of age were more vulnerable to exposure to NO2 and CO, resulting in an increased hospitalization risk. During the entire day and the period from 9 to 21 h, the trend of the influence of NO2 on the daily hospitalization admission of diabetic patients varies the most, while there is no obvious change trend for the other pollutants.

Published
2025-08-19

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