4.7 Article

Attributable risk and economic cost of hospital admissions for mental disorders due to PM2.5 in Beijing

Journal

SCIENCE OF THE TOTAL ENVIRONMENT
Volume 718, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scitotenv.2020.137274

Keywords

Attributable risk; Economic cost; Hospital admissions; Mental disorders; PM2.5

Funding

  1. National Natural Science Foundation of China [41761144056]
  2. China Scholarship Council [201806010385]
  3. Yale Macmillan Center Faculty Research Fund
  4. US Federal PEPPER Center Scholar Award [P30AG021342]
  5. NIH/National Institute on Aging [R03AG048920, K01AG053408]

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Background: Few studies have estimated the attributable risk and economic cost of mental disorders (MDs) due to particulate matters with aerodynamic diameter of <2.5 mu m (PM2.5) exposure in Beijing. Objectives: This study aims to identify the possible correlation between PM2.5 and risk of hospital admissions (HAs) for MDs in Beijing and calculate the attributable risk and economic cost. Methods: A generalized additive model (GAM) with controlling for time trend, meteorological conditions, holidays and day of the week was used to estimate the associations. Stratified analyses were performed by age, gender and season. We further estimated the health and economic burden of HAs for MDs attributable to PM2.5. Findings: A total of 17,252 HAs for MDs were collected. A 10 mu g/m(3) daily increase in PM2.5 was associated with a statistically significant risk increase of 3.55% for HAs for MDs. The effects of PM2.5 exposures on HAs for MDs were more pronounced in males, elderly (>= 65 years old) individuals and in cold seasons. Using WHO's air quality guidelines as the reference, 15.12% of HAs and 16.19% of the related medical expenses for MDs were attributed to PM2.5 during the study period. Novelty: PM2.5 accounts for substantial morbidity and economic burden of MDs for both the society and households, which shows environmental protections arc essential to improve mental health status of the population. (C) 2020 Elsevier B.V. All rights reserved.

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