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

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科目三应助jiji采纳,获得10
刚刚
李健应助嘟噜嘟噜采纳,获得10
1秒前
六六发布了新的文献求助10
1秒前
1秒前
科研通AI6.2应助fengdengjin采纳,获得10
1秒前
wuwu发布了新的文献求助10
1秒前
乐雾发布了新的文献求助20
2秒前
ytom关注了科研通微信公众号
2秒前
2秒前
2秒前
vk完成签到,获得积分20
2秒前
阿桔发布了新的文献求助10
3秒前
SSSSSS完成签到 ,获得积分10
3秒前
3秒前
千叶落完成签到,获得积分10
3秒前
GJJ完成签到 ,获得积分10
3秒前
3秒前
RDhanz完成签到 ,获得积分10
4秒前
4秒前
夜染星空完成签到,获得积分10
5秒前
vividtry完成签到,获得积分10
5秒前
重生之学术裁缝逐梦学术圈完成签到,获得积分10
5秒前
周不游发布了新的文献求助10
5秒前
zzz关注了科研通微信公众号
5秒前
6秒前
松song完成签到,获得积分10
6秒前
6秒前
Ma完成签到,获得积分10
7秒前
整整完成签到,获得积分10
7秒前
8秒前
潇洒刚完成签到,获得积分10
8秒前
8秒前
Amphetamine发布了新的文献求助30
8秒前
Raye完成签到,获得积分10
8秒前
8秒前
无聊的剑心完成签到,获得积分10
8秒前
Hello应助雅若晨兮采纳,获得10
8秒前
ProfLi完成签到,获得积分10
8秒前
华仔应助生动煎饼采纳,获得10
8秒前
大个应助myfmmmm采纳,获得10
8秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Rosenblum, Global Change Biology 500
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
DIPPR Project 801 - Full Version 380
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7766854
求助须知:如何正确求助?哪些是违规求助? 9310725
关于积分的说明 20318962
捐赠科研通 7351983
什么是DOI,文献DOI怎么找? 3315202
关于科研通互助平台的介绍 2464635
邀请新用户注册赠送积分活动 2329840