总结环境化学混合物的暴露负担分数:为交叉研究协调,报告反馈和精确环境健康创建公平和共同的尺度。

IF 7.4 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Shelley H Liu, Katherine E Manz, Jessie P Buckley, Leah Feuerstahler
{"title":"总结环境化学混合物的暴露负担分数:为交叉研究协调,报告反馈和精确环境健康创建公平和共同的尺度。","authors":"Shelley H Liu, Katherine E Manz, Jessie P Buckley, Leah Feuerstahler","doi":"10.1007/s40572-024-00467-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose of review: </strong>Environmental health researchers are increasingly concerned about characterizing exposure to environmental chemical mixtures (co-exposure to multiple chemicals simultaneously). We discuss approaches for quantifying an overall summary score or index that reflects an individual's total exposure burden to components of the mixture. We focus on unsupervised methods, in which the summary score is not computed in relation to a pre-specified health outcome.</p><p><strong>Recent findings: </strong>Sum-scores and principal components analysis (PCA) are common approaches for quantifying a total exposure burden metric but have several limitations: 1) they require imputation when using exposure biomarkers with high frequency of non-detection, 2) they do not account for exposure heterogeneity, 3) sum-scores assume the same measurement error for all people, while there is no error term inherent to the PCA model as its primary purpose is dimension reduction, and 4) in pooled analyses, both approaches are limited to analyzing the set of exposure variables that are in common across all studies, potentially discarding valuable information. Meanwhile, item response theory (IRT) is a novel and promising alternative to calculate an exposure burden score that addresses the above limitations. It allows for the inclusion of exposure analytes with high frequency of non-detects without the need for imputation. It can account for exposure heterogeneity to calculate fair metrics for all people, through assessment of differential item functioning and mixture IRT. IRT also quantifies measurement errors of the exposure burden score that are individual-specific, such that it appropriately assigns a larger standard error to an individual who has missing data on one or more exposure variables. Lastly, IRT enhances cross-study harmonization by enabling the creation of exposure burden calculators to set a common scale across studies, and allows for the inclusion of all exposure variables within a chemical class, even if they were only measured in a subset of participants. Summarizing total exposure burden, through the creation of fair and informative index scores, is a promising tool for environmental health research as environmental exposures are increasingly used for biomonitoring and clinical recommendations.</p>","PeriodicalId":10775,"journal":{"name":"Current Environmental Health Reports","volume":"12 1","pages":"13"},"PeriodicalIF":7.4000,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11923795/pdf/","citationCount":"0","resultStr":"{\"title\":\"Exposome Burden Scores to Summarize Environmental Chemical Mixtures: Creating a Fair and Common Scale for Cross-study Harmonization, Report-back and Precision Environmental Health.\",\"authors\":\"Shelley H Liu, Katherine E Manz, Jessie P Buckley, Leah Feuerstahler\",\"doi\":\"10.1007/s40572-024-00467-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose of review: </strong>Environmental health researchers are increasingly concerned about characterizing exposure to environmental chemical mixtures (co-exposure to multiple chemicals simultaneously). We discuss approaches for quantifying an overall summary score or index that reflects an individual's total exposure burden to components of the mixture. We focus on unsupervised methods, in which the summary score is not computed in relation to a pre-specified health outcome.</p><p><strong>Recent findings: </strong>Sum-scores and principal components analysis (PCA) are common approaches for quantifying a total exposure burden metric but have several limitations: 1) they require imputation when using exposure biomarkers with high frequency of non-detection, 2) they do not account for exposure heterogeneity, 3) sum-scores assume the same measurement error for all people, while there is no error term inherent to the PCA model as its primary purpose is dimension reduction, and 4) in pooled analyses, both approaches are limited to analyzing the set of exposure variables that are in common across all studies, potentially discarding valuable information. Meanwhile, item response theory (IRT) is a novel and promising alternative to calculate an exposure burden score that addresses the above limitations. It allows for the inclusion of exposure analytes with high frequency of non-detects without the need for imputation. It can account for exposure heterogeneity to calculate fair metrics for all people, through assessment of differential item functioning and mixture IRT. IRT also quantifies measurement errors of the exposure burden score that are individual-specific, such that it appropriately assigns a larger standard error to an individual who has missing data on one or more exposure variables. Lastly, IRT enhances cross-study harmonization by enabling the creation of exposure burden calculators to set a common scale across studies, and allows for the inclusion of all exposure variables within a chemical class, even if they were only measured in a subset of participants. Summarizing total exposure burden, through the creation of fair and informative index scores, is a promising tool for environmental health research as environmental exposures are increasingly used for biomonitoring and clinical recommendations.</p>\",\"PeriodicalId\":10775,\"journal\":{\"name\":\"Current Environmental Health Reports\",\"volume\":\"12 1\",\"pages\":\"13\"},\"PeriodicalIF\":7.4000,\"publicationDate\":\"2025-02-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11923795/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Environmental Health Reports\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s40572-024-00467-2\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Environmental Health Reports","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s40572-024-00467-2","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0

摘要

综述目的:环境卫生研究人员越来越关注暴露于环境化学混合物(同时共同暴露于多种化学物质)的特征。我们讨论了量化反映个人对混合物成分的总暴露负担的总体总结分数或指数的方法。我们专注于无监督的方法,其中汇总得分不计算与预先指定的健康结果有关。最近的发现:和分数和主成分分析(PCA)是量化总暴露负担指标的常用方法,但有一些局限性:1)当使用非检测频率高的暴露生物标志物时,它们需要归责;2)它们没有考虑暴露异质性;3)和分假设所有人的测量误差相同,而PCA模型没有固有的误差项,因为它的主要目的是降维;4)在合并分析中,这两种方法都局限于分析所有研究中共有的暴露变量集,可能会丢弃有价值的信息。同时,项目反应理论(IRT)是一种计算暴露负担分数的新方法,解决了上述局限性。它允许包含高频率的非检测暴露分析物,而无需插入。它可以解释暴露异质性,通过评估差异项目功能和混合IRT来计算所有人的公平指标。IRT还量化了个体特异性暴露负担评分的测量误差,因此,它适当地将较大的标准误差分配给缺少一个或多个暴露变量数据的个体。最后,IRT通过创建暴露负担计算器来设置跨研究的共同尺度,并允许在化学类别中包含所有暴露变量,即使它们仅在参与者的子集中进行测量,从而增强了交叉研究的协调。随着环境暴露越来越多地用于生物监测和临床建议,通过创建公平和信息丰富的指数分数来总结总暴露负担是一种很有前途的环境健康研究工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exposome Burden Scores to Summarize Environmental Chemical Mixtures: Creating a Fair and Common Scale for Cross-study Harmonization, Report-back and Precision Environmental Health.

Purpose of review: Environmental health researchers are increasingly concerned about characterizing exposure to environmental chemical mixtures (co-exposure to multiple chemicals simultaneously). We discuss approaches for quantifying an overall summary score or index that reflects an individual's total exposure burden to components of the mixture. We focus on unsupervised methods, in which the summary score is not computed in relation to a pre-specified health outcome.

Recent findings: Sum-scores and principal components analysis (PCA) are common approaches for quantifying a total exposure burden metric but have several limitations: 1) they require imputation when using exposure biomarkers with high frequency of non-detection, 2) they do not account for exposure heterogeneity, 3) sum-scores assume the same measurement error for all people, while there is no error term inherent to the PCA model as its primary purpose is dimension reduction, and 4) in pooled analyses, both approaches are limited to analyzing the set of exposure variables that are in common across all studies, potentially discarding valuable information. Meanwhile, item response theory (IRT) is a novel and promising alternative to calculate an exposure burden score that addresses the above limitations. It allows for the inclusion of exposure analytes with high frequency of non-detects without the need for imputation. It can account for exposure heterogeneity to calculate fair metrics for all people, through assessment of differential item functioning and mixture IRT. IRT also quantifies measurement errors of the exposure burden score that are individual-specific, such that it appropriately assigns a larger standard error to an individual who has missing data on one or more exposure variables. Lastly, IRT enhances cross-study harmonization by enabling the creation of exposure burden calculators to set a common scale across studies, and allows for the inclusion of all exposure variables within a chemical class, even if they were only measured in a subset of participants. Summarizing total exposure burden, through the creation of fair and informative index scores, is a promising tool for environmental health research as environmental exposures are increasingly used for biomonitoring and clinical recommendations.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
13.60
自引率
1.30%
发文量
47
期刊介绍: Current Environmental Health Reports provides up-to-date expert reviews in environmental health. The goal is to evaluate and synthesize original research in all disciplines relevant for environmental health sciences, including basic research, clinical research, epidemiology, and environmental policy.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信