Literature DB >> 32109812

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

Ziting Wu1, Xi Chen2, Guoxing Li3, Lin Tian4, Zhan Wang5, Xiuqin Xiong6, Chuan Yang7, Zijun Zhou8, Xiaochuan Pan9.   

Abstract

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 μm (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 μg/m3 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 are essential to improve mental health status of the population.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Attributable risk; Economic cost; Hospital admissions; Mental disorders; PM(2.5)

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Year:  2020        PMID: 32109812      PMCID: PMC9429815          DOI: 10.1016/j.scitotenv.2020.137274

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   10.753


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