污染源附近癌症风险研究的方法学方法:基于人群的儿童癌症病例对照研究的经验。

IF 3 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Javier García-Pérez, Diana Gómez-Barroso, Ibon Tamayo-Uria, Rebeca Ramis
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引用次数: 14

摘要

背景:环境暴露与某些类型癌症的风险有关,儿童是最脆弱的人群。本研究旨在介绍我们小组关于污染源(工业和城市场所)附近儿童癌症风险的论文中使用的方法方法。设计了一项以人群为基础的西班牙儿童癌症发病率病例对照研究及其与工业和城市地区居住邻近程度的关系。开发了两种使用混合多元无条件逻辑回归模型来估计优势比(ORs)和95%置信区间(95% ci)的方法:(a)“近与远”分析,评估离工业和城市地区近(“近”)和远(“远”)的儿童患癌症的风险;和(b)“风险梯度”分析,其中评估了工业附近的风险梯度。对于两种方法中的每一种,都实施了三种分析策略:“联合”、“分层”和“个性化”分析。事故病例来自西班牙儿童癌症登记处(1996年至2011年)。结果:应用该方法,与特定工业和城市区域的距离(≤2公里)与风险(OR;95% CI) (1.31;工业区1.04-1.65,1.28;城市地区1.00-1.53),神经母细胞瘤(2.12;工业和城市地区为1.18-3.83),肾脏地区为2.02;工业地区1.16-3.52)和骨骼(4.02;1.73-9.34(城市地区)。结论:这两种方法方法是一种非常有用和灵活的分析工业和城市地区附近儿童癌症过度风险的工具,可以外推和推广到其他癌症和慢性疾病,并适用于其他类型的污染源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Methodological approaches to the study of cancer risk in the vicinity of pollution sources: the experience of a population-based case-control study of childhood cancer.

Methodological approaches to the study of cancer risk in the vicinity of pollution sources: the experience of a population-based case-control study of childhood cancer.

Methodological approaches to the study of cancer risk in the vicinity of pollution sources: the experience of a population-based case-control study of childhood cancer.

Methodological approaches to the study of cancer risk in the vicinity of pollution sources: the experience of a population-based case-control study of childhood cancer.

Background: Environmental exposures are related to the risk of some types of cancer, and children are the most vulnerable group of people. This study seeks to present the methodological approaches used in the papers of our group about risk of childhood cancers in the vicinity of pollution sources (industrial and urban sites). A population-based case-control study of incident childhood cancers in Spain and their relationship with residential proximity to industrial and urban areas was designed. Two methodological approaches using mixed multiple unconditional logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) were developed: (a) "near vs. far" analysis, where possible excess risks of cancers in children living near ("near") versus those living far ("far") from industrial and urban areas were assessed; and (b) "risk gradient" analysis, where the risk gradient in the vicinity of industries was assessed. For each one of the two approaches, three strategies of analysis were implemented: "joint", "stratified", and "individualized" analysis. Incident cases were obtained from the Spanish Registry of Childhood Cancer (between 1996 and 2011).

Results: Applying this methodology, associations between proximity (≤ 2 km) to specific industrial and urban zones and risk (OR; 95% CI) of leukemias (1.31; 1.04-1.65 for industrial areas, and 1.28; 1.00-1.53 for urban areas), neuroblastoma (2.12; 1.18-3.83 for both industrial and urban areas), and renal (2.02; 1.16-3.52 for industrial areas) and bone (4.02; 1.73-9.34 for urban areas) tumors have been suggested.

Conclusions: The two methodological approaches were used as a very useful and flexible tool to analyze the excess risk of childhood cancers in the vicinity of industrial and urban areas, which can be extrapolated and generalized to other cancers and chronic diseases, and adapted to other types of pollution sources.

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来源期刊
International Journal of Health Geographics
International Journal of Health Geographics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -
CiteScore
10.20
自引率
2.00%
发文量
17
审稿时长
12 weeks
期刊介绍: A leader among the field, International Journal of Health Geographics is an interdisciplinary, open access journal publishing internationally significant studies of geospatial information systems and science applications in health and healthcare. With an exceptional author satisfaction rate and a quick time to first decision, the journal caters to readers across an array of healthcare disciplines globally. International Journal of Health Geographics welcomes novel studies in the health and healthcare context spanning from spatial data infrastructure and Web geospatial interoperability research, to research into real-time Geographic Information Systems (GIS)-enabled surveillance services, remote sensing applications, spatial epidemiology, spatio-temporal statistics, internet GIS and cyberspace mapping, participatory GIS and citizen sensing, geospatial big data, healthy smart cities and regions, and geospatial Internet of Things and blockchain.
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