Association between particle components and inpatient Parkinson's hospitalizations among people ages 40 years and up in the U.S. using Bayesian kernel machine regression (BKMR)

百分位 医学 空气污染物 不利影响 人口学 空气污染 环境卫生 统计 内科学 化学 数学 社会学 有机化学
作者
Bryan N. Vu,Xinye Qiu,Joel Schwartz
出处
期刊:Environmental health perspectives [National Institute of Environmental Health Sciences]
卷期号:2022 (1)
标识
DOI:10.1289/isee.2022.p-1107
摘要

BACKGROUND: Recent studies have shown that air pollutants may have adverse effects on neurological disorders. However, few studies have investigated the long-term exposure of particle components in conjunction with PM2.5 and ozone to assess their individual and additive effects on Parkinson's disease. AIM: We aim to utilize a Bayesian Kernel machine regression (BKMR) to assess the individual and join effects of air pollutants including 15 different particle components such as organic carbon (OC), elemental carbon (EC), copper (Cu), and zinc (Z), along with PM2.5 and ozone, on counts of inpatient Parkinson's hospitalizations for adults ages 40 years and up. METHODS: Inpatient records were collected from the State Inpatient Databases which included hospitals from 12 U.S. states ranging in years from 2000 through 2016. We also included temperature from Daymet and variables from the U.S. census to control for socio-economic status. All variables were aggregated to the annual level. RESULTS: We observed a decrease of 0.05 (95%CI: 0.03,-0.14), 0.04 (95%CI: 0.05,-0.14), and an increase of 0.03 (95%CI: -0.07,0.12) in the number of Parkinson's inpatient hospitalizations each year at the 25th, 50th, and 75th percentiles of pollutant mixture, respectively. At the 90th and 95th percentile, there is a significant increase of 0.12 (95%CI: 0.01,0.22) and 0.17 (95%CI: 0.06,0.28) annual Parkinson's cases, respectively. CONCLUSIONS: Our results contribute to the growing body of literature on air pollution and neurological disorders. KEYWORDS: Parkinson's Disease, PM Components, PM2.5, Ozone, BKMR

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