Air pollution and incident bladder cancer: A risk assessment

膀胱癌 空气污染 逻辑回归 环境卫生 医学 条件logistic回归 统计 队列 癌症 队列研究 环境科学 数学 人口 内科学 化学 有机化学
作者
Tomoyuki Kawada
出处
期刊:International Journal of Cancer [Wiley]
卷期号:145 (11): 3177-3177 被引量:2
标识
DOI:10.1002/ijc.32633
摘要

I have read with interest the article entitled “Ambient air pollution and incident bladder cancer risk: Updated analysis of the Spanish Bladder Cancer Study” by Turner et al.1 that evaluated the association between ambient particulate matter within a diameter of 2.5 (PM2.5), nitrogen dioxide (NO2) and bladder cancer incidence. Although there were no significant associations of ambient PM2.5 and NO2 concentrations with incident bladder cancer, some cautions should be paid to the methodology of their research. First, the authors adopted single pollutant and two pollutant models by using estimation data from residential areas and a dependent variable was personal information on incident bladder cancer. As there is a variation of ambient PM2.5 and NO2 within the same study area, individual exposure levels of ambient PM2.5 and NO2 should be used instead of estimated values, although there are difficulties of measuring individual data. Second, the authors adopted unconditional logistic regression models for the analysis. I suppose that case–control matching data were canceled and conservative results would be derived by their statistical procedure.2 Although there are some stronger factors than air pollutions for incident bladder cancer, conditional logistic regression models can be applied to case–control matching data. Finally, the authors cited a meta-analysis of cohort studies, presenting no significant association between air pollution and incident bladder cancer. The air pollution data were gathered by the same method, and I speculate that personal lifestyle factors would greatly contribute to the risk of bladder cancer.3, 4 Yours sincerely Tomoyuki Kawada
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
1秒前
yumieer完成签到,获得积分10
2秒前
2秒前
zhq发布了新的文献求助10
3秒前
3秒前
领导范儿应助哈哈哈哈采纳,获得10
3秒前
顾矜应助Meng采纳,获得10
4秒前
soufle完成签到,获得积分10
4秒前
yan完成签到,获得积分10
4秒前
量子星尘发布了新的文献求助10
4秒前
5秒前
英俊的铭应助开朗龙猫采纳,获得10
5秒前
6秒前
6秒前
qwe完成签到,获得积分10
6秒前
7秒前
8秒前
8秒前
8秒前
ily.发布了新的文献求助10
8秒前
欣喜亚男完成签到,获得积分10
8秒前
HHHHH发布了新的文献求助10
8秒前
雪夜003完成签到 ,获得积分10
9秒前
我是老大应助呆子采纳,获得10
9秒前
可爱大地关注了科研通微信公众号
9秒前
10秒前
淡淡的向雁完成签到,获得积分10
10秒前
Nemo发布了新的文献求助10
10秒前
10秒前
11秒前
11秒前
kk_汤齐完成签到,获得积分20
11秒前
12秒前
vicin完成签到,获得积分10
12秒前
无花果应助你们才来采纳,获得10
13秒前
科研通AI6应助Litesco采纳,获得10
13秒前
自由的飞发布了新的文献求助10
14秒前
haha发布了新的文献求助10
15秒前
刻苦鸭子发布了新的文献求助10
15秒前
ZhouZhou发布了新的文献求助10
15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
List of 1,091 Public Pension Profiles by Region 1001
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 500
On the application of advanced modeling tools to the SLB analysis in NuScale. Part I: TRACE/PARCS, TRACE/PANTHER and ATHLET/DYN3D 500
L-Arginine Encapsulated Mesoporous MCM-41 Nanoparticles: A Study on In Vitro Release as Well as Kinetics 500
Haematolymphoid Tumours (Part A and Part B, WHO Classification of Tumours, 5th Edition, Volume 11) 400
Virus-like particles empower RNAi for effective control of a Coleopteran pest 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5468653
求助须知:如何正确求助?哪些是违规求助? 4571995
关于积分的说明 14333271
捐赠科研通 4498777
什么是DOI,文献DOI怎么找? 2464700
邀请新用户注册赠送积分活动 1453311
关于科研通互助平台的介绍 1427921