Long-term NO2 exposure and mortality: A comprehensive meta-analysis

荟萃分析 漏斗图 出版偏见 置信区间 子群分析 随机效应模型 相对风险 医学 人口学 合并分析 内科学 社会学
作者
Xiaoshi Chen,Ling Qi,Sai Li,Xiaoli Duan
出处
期刊:Environmental Pollution [Elsevier BV]
卷期号:341: 122971-122971 被引量:7
标识
DOI:10.1016/j.envpol.2023.122971
摘要

In response to the World Health Organization's (WHO) revised annual mean nitrogen dioxide (NO2) standard from 40 μg/m3 to 10 μg/m3, reflecting the growing evidence linking long-term exposure to ambient NO2 and excess mortality, we conducted a comprehensive meta-analysis incorporating 11 new studies published since the WHO analysis. Our investigation involved a systematic search of three major databases (PubMed, Web of Science, and Scopus) for articles published until July 1, 2022. We employed random effects models to calculate summarized risk ratios (RR) along with 95% confidence intervals (CIs) for overall and subgroup analyses. Sensitivity analyses were conducted to assess result robustness, and publication bias was evaluated using funnel plots and Egger's linear regression. Out of 2799 identified articles, 56 were included in our meta-analysis. The findings indicate a heightened risk of all-cause, cardiovascular, and respiratory mortality associated with long-term exposure to ambient NO2, with pooled RR values of 1.03 (95% CI: 1.02, 1.05), 1.07 (95% CI: 1.04, 1.10), and 1.03 (95% CI: 1.02, 1.05) per 10 μg/m3 increase, respectively. Substantial heterogeneity (I2 = 84%-96%) among studies was observed. Subgroup analysis revealed significantly elevated RR values in Asia and Oceania (p-value <0.05). The aggregated values for all-cause and cardiovascular mortality were slightly larger than those reported in previous studies. Our study emphasizes the imperative to develop more patient cohorts and conduct age-refined analyses to explore the impact of existing chronic diseases on these associations. Further, additional cohorts in Asia and Oceania are essential to fortify evidence in these regions. Lastly, we recommend using fused multi-source data with higher spatiotemporal resolution for individual exposure representation to minimize heterogeneity among studies in future research.
最长约 10秒,即可获得该文献文件

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
jessie完成签到,获得积分10
刚刚
paipai完成签到,获得积分10
刚刚
刚刚
翁演鑫发布了新的文献求助10
刚刚
华仔应助erlangenbio采纳,获得10
1秒前
1秒前
杜子发布了新的文献求助10
1秒前
迷你的听荷完成签到,获得积分10
1秒前
sue发布了新的文献求助10
1秒前
XianshengJin完成签到,获得积分10
1秒前
笨笨以菱发布了新的文献求助10
1秒前
LL完成签到 ,获得积分10
1秒前
2秒前
2秒前
2秒前
石文莉发布了新的文献求助10
2秒前
2秒前
科研通AI6.4应助HNUSTqsj采纳,获得10
3秒前
李爱国应助亚鸭采纳,获得10
3秒前
SZHGYMC完成签到,获得积分10
3秒前
5秒前
5秒前
5秒前
wy.he应助科研通管家采纳,获得10
5秒前
小河应助科研通管家采纳,获得10
5秒前
5秒前
5秒前
共享精神应助清爽的雅青采纳,获得50
5秒前
xhc应助科研通管家采纳,获得10
5秒前
大法师应助科研通管家采纳,获得10
6秒前
英姑应助王彦清采纳,获得10
6秒前
xhc应助科研通管家采纳,获得10
6秒前
华仔应助zhuxl采纳,获得10
7秒前
彩色的蚂蚁完成签到,获得积分10
7秒前
123发布了新的文献求助10
7秒前
甜叶菊发布了新的文献求助10
7秒前
7秒前
充电宝应助cc采纳,获得10
7秒前
科目三应助猛禽猫头鹰采纳,获得20
8秒前
ding应助酷酷三问采纳,获得10
8秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(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
Arthritis and Related Conditions, An Issue of Orthopedic Clinics 1000
Development of a Bridge Weigh-In-Motion System: A technology to convert the bridge response to the passage of traffic into data on vehicle configurations, speeds, times of travel and weights 1000
ズームレンズの光学設計に関する研究 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7285756
求助须知:如何正确求助?哪些是违规求助? 8906171
关于积分的说明 18846482
捐赠科研通 6955355
什么是DOI,文献DOI怎么找? 3208199
关于科研通互助平台的介绍 2378341
邀请新用户注册赠送积分活动 2183789