The effects of long-term exposure to air pollution on incident mental disorders among patients with prediabetes and diabetes: Findings from a large prospective cohort

Sci Total Environ. 2023 Nov 1:897:165235. doi: 10.1016/j.scitotenv.2023.165235. Epub 2023 Jul 5.

Abstract

Background: The association between air pollution and mental disorders has been widely documented in the general population. However, the evidence among susceptible populations, such as individuals with prediabetes or diabetes, is still insufficient.

Methods: We analyzed data from 48,515 participants with prediabetes and 24,393 participants with diabetes from the UK Biobank. Annual pollution data were collected for fine particulate matter (PM2.5), inhalable particulate matter (PM10), nitrogen dioxide (NO2), and nitrogen dioxides (NOx) during 2006-2021. The exposure to air pollution and temperature for each participant were estimated by the bilinear interpolation approach and time-weighted method based on their geocoded home addresses and time spent at each address. We employed the generalized propensity score model based on the generalized estimating equation and the time-varying covariates Cox model to assess the effects of air pollution.

Results: We observed causal links between air pollutants and mental disorders among both prediabetic and diabetic participants, with stronger effects among those with diabetes than prediabetes. The hazard ratios were 1.18 (1.12, 1.24), 1.15 (1.10, 1.20), 1.18 (1.13, 1.23), and 1.15 (1.11, 1.19) in patients with prediabetes, and 1.21 (1.13, 1.29), 1.17 (1.11, 1.24), 1.19 (1.13, 1.25), and 1.17 (1.12, 1.23) in patients with diabetes per interquartile range elevation in PM2.5, PM10, NO2, and NOx. Furthermore, the effects were more pronounced among people who were older, alcohol drinkers, and living in urban areas.

Conclusions: Our study indicates the potential causal links between long-term exposure to air pollution and incident mental disorders among those with prediabetes and diabetes. Reducing air pollution levels would significantly benefit this vulnerable population by reducing the incidence of mental disorders.

Keywords: Air pollution; Causal inference; Diabetes; Mental disorders; Prediabetes.

MeSH terms

  • Air Pollutants* / adverse effects
  • Air Pollutants* / analysis
  • Air Pollution* / analysis
  • Diabetes Mellitus* / epidemiology
  • Environmental Exposure / analysis
  • Humans
  • Mental Disorders* / epidemiology
  • Nitrogen Dioxide / analysis
  • Particulate Matter / adverse effects
  • Particulate Matter / analysis
  • Prediabetic State* / epidemiology
  • Prospective Studies

Substances

  • Nitrogen Dioxide
  • Air Pollutants
  • Particulate Matter