The impact of monthly air pollution exposure and its interaction with individual factors: Insight from a large cohort study of comprehensive hospitalizations in Guangzhou area

Front Public Health. 2023 Mar 21:11:1137196. doi: 10.3389/fpubh.2023.1137196. eCollection 2023.

Abstract

Background: Although the association between short-term air pollution exposure and certain hospitalizations has been well documented, evidence on the effect of longer-term (e. g., monthly) air pollution on a comprehensive set of outcomes is still limited.

Method: A total of 68,416 people in South China were enrolled and followed up during 2019-2020. Monthly air pollution level was estimated using a validated ordinary Kriging method and assigned to individuals. Time-dependent Cox models were developed to estimate the relationship between monthly PM10 and O3 exposures and the all-cause and cause-specific hospitalizations after adjusting for confounders. The interaction between air pollution and individual factors was also investigated.

Results: Overall, each 10 μg/m3 increase in PM10 concentration was associated with a 3.1% (95%CI: 1.3%-4.9%) increment in the risk of all-cause hospitalization. The estimate was even greater following O3 exposure (6.8%, 5.5%-8.2%). Furthermore, each 10 μg/m3 increase in PM10 was associated with a 2.3%-9.1% elevation in all the cause-specific hospitalizations except for those related to respiratory and digestive diseases. The same increment in O3 was relevant to a 4.7%-22.8% elevation in the risk except for respiratory diseases. Additionally, the older individuals tended to be more vulnerable to PM10 exposure (P interaction: 0.002), while the alcohol abused and those with an abnormal BMI were more vulnerable to the impact of O3 (P interaction: 0.052 and 0.011). However, the heavy smokers were less vulnerable to O3 exposure (P interaction: 0.032).

Conclusion: We provide comprehensive evidence on the hospitalization hazard of monthly PM10 and O3 exposure and their interaction with individual factors.

Keywords: air pollution; effect modification; hospitalizations; particulate matter; time-dependent Cox proportional model.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Air Pollutants* / adverse effects
  • Air Pollutants* / analysis
  • Air Pollution* / adverse effects
  • Air Pollution* / analysis
  • Cohort Studies
  • Environmental Exposure / adverse effects
  • Hospitalization
  • Humans
  • Particulate Matter / adverse effects
  • Particulate Matter / analysis

Substances

  • Air Pollutants
  • Particulate Matter

Grants and funding

This work was supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China (grant number 2018ZX10715004), the National Natural Science Foundation of China (grant numbers 82204162 and 82204154), and the Natural Science Foundation of Guangdong Province (grant number 2022A1515010823).