{"title":"医疗放射工作者中健康工作者幸存者偏见的组成协会","authors":"Won Jin Lee, Jaeho Jeong, Young Min Kim","doi":"10.1002/ajim.23727","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>The healthy worker survivor bias may vary by sex. This study investigated three component associations necessary for this bias to determine the origins of sex differences in this bias among male and female workers.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>We analyzed a data set of 93,918 South Korean diagnostic medical radiation workers registered in the National Dose Registry from 1996 to 2011, linked with mortality and cancer incidence data. Component associations were assessed using Cox regression to estimate hazard ratios (HRs) and logistic regression with generalized estimating equations to estimate odds ratios (ORs).</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>A significant association between prior cumulative exposure and employment status was observed for all-cause mortality in male (HR 1.06, 95% CI 1.02–1.10), whereas an inverse association was noted in female workers (HR 0.82, 95% CI 0.78–0.87). Adjusted ORs for employment status and subsequent exposure for all-cause mortality, as well as HRs for employment status and survival time, demonstrated associations in the same direction in both males and females.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Our findings demonstrate that sex-specific differences in healthy worker survivor bias were primarily driven by the association between prior exposure and employment status. To improve bias mitigation in occupational cohort studies, sex-specific components should be incorporated.</p>\n </section>\n </div>","PeriodicalId":7873,"journal":{"name":"American journal of industrial medicine","volume":"68 6","pages":"552-556"},"PeriodicalIF":2.7000,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajim.23727","citationCount":"0","resultStr":"{\"title\":\"Component Associations of the Healthy Worker Survivor Bias in Medical Radiation Workers\",\"authors\":\"Won Jin Lee, Jaeho Jeong, Young Min Kim\",\"doi\":\"10.1002/ajim.23727\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>The healthy worker survivor bias may vary by sex. This study investigated three component associations necessary for this bias to determine the origins of sex differences in this bias among male and female workers.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>We analyzed a data set of 93,918 South Korean diagnostic medical radiation workers registered in the National Dose Registry from 1996 to 2011, linked with mortality and cancer incidence data. Component associations were assessed using Cox regression to estimate hazard ratios (HRs) and logistic regression with generalized estimating equations to estimate odds ratios (ORs).</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>A significant association between prior cumulative exposure and employment status was observed for all-cause mortality in male (HR 1.06, 95% CI 1.02–1.10), whereas an inverse association was noted in female workers (HR 0.82, 95% CI 0.78–0.87). Adjusted ORs for employment status and subsequent exposure for all-cause mortality, as well as HRs for employment status and survival time, demonstrated associations in the same direction in both males and females.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>Our findings demonstrate that sex-specific differences in healthy worker survivor bias were primarily driven by the association between prior exposure and employment status. 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引用次数: 0
摘要
健康工人幸存者偏见可能因性别而异。本研究调查了这种偏见所必需的三个组成部分的关联,以确定这种偏见在男性和女性工人中性别差异的起源。方法我们分析了1996年至2011年在国家剂量登记处注册的93,918名韩国诊断医疗放射工作者的数据集,与死亡率和癌症发病率数据相关。采用Cox回归估计风险比(hr),采用广义估计方程进行logistic回归评估优势比(ORs)。结果在男性全因死亡率中,既往累积暴露与就业状况之间存在显著相关性(HR 1.06, 95% CI 1.02-1.10),而在女性全因死亡率中存在负相关(HR 0.82, 95% CI 0.78-0.87)。调整就业状态和随后暴露导致的全因死亡率的ORs,以及就业状态和生存时间的hr,在男性和女性中都显示出相同方向的关联。我们的研究结果表明,健康工人幸存者偏见的性别差异主要是由先前暴露与就业状况之间的关联驱动的。为了改善职业队列研究中的偏倚缓解,应纳入性别特异性成分。
Component Associations of the Healthy Worker Survivor Bias in Medical Radiation Workers
Background
The healthy worker survivor bias may vary by sex. This study investigated three component associations necessary for this bias to determine the origins of sex differences in this bias among male and female workers.
Methods
We analyzed a data set of 93,918 South Korean diagnostic medical radiation workers registered in the National Dose Registry from 1996 to 2011, linked with mortality and cancer incidence data. Component associations were assessed using Cox regression to estimate hazard ratios (HRs) and logistic regression with generalized estimating equations to estimate odds ratios (ORs).
Results
A significant association between prior cumulative exposure and employment status was observed for all-cause mortality in male (HR 1.06, 95% CI 1.02–1.10), whereas an inverse association was noted in female workers (HR 0.82, 95% CI 0.78–0.87). Adjusted ORs for employment status and subsequent exposure for all-cause mortality, as well as HRs for employment status and survival time, demonstrated associations in the same direction in both males and females.
Conclusions
Our findings demonstrate that sex-specific differences in healthy worker survivor bias were primarily driven by the association between prior exposure and employment status. To improve bias mitigation in occupational cohort studies, sex-specific components should be incorporated.
期刊介绍:
American Journal of Industrial Medicine considers for publication reports of original research, review articles, instructive case reports, and analyses of policy in the fields of occupational and environmental health and safety. The Journal also accepts commentaries, book reviews and letters of comment and criticism. The goals of the journal are to advance and disseminate knowledge, promote research and foster the prevention of disease and injury. Specific topics of interest include: occupational disease; environmental disease; pesticides; cancer; occupational epidemiology; environmental epidemiology; disease surveillance systems; ergonomics; dust diseases; lead poisoning; neurotoxicology; endocrine disruptors.