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首页> 外文期刊>Occupational and environmental medicine >A structural approach to address the healthy-worker survivor effect in occupational cohorts: An application in the trucking industry cohort
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A structural approach to address the healthy-worker survivor effect in occupational cohorts: An application in the trucking industry cohort

机译：解决职业队列中健康工人幸存者效应的结构方法：在卡车运输行业队列中的应用

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Background: Occupational cohort studies are often challenged by the Healthy Worker Survivor Effect, which may bias standard methods of analysis. G-estimation of structural failure time models is an approach for reducing this type of bias. Accelerated failure time models have recently been applied in an occupational cohort but cumulative failure time models have not. Methods: We used g-estimation of a cumulative failure time model to assess the effect of working as a long-haul driver on ischaemic heart disease mortality in a cohort of 30 448 men employed in the unionised US trucking industry in 1985. Exposure was defined by job title and based on work records. We also applied g-estimation of an accelerated failure time model as a sensitivity analysis and approximated HRs from both models to compare them. Results: The risk ratio (RR) obtained from the cumulative failure time model, comparing the observed risk under no intervention to the risk had nobody ever been exposed as a long-haul driver, was 1.09 (95% CI 1.02 to 1.16). The RR comparing the risk had everyone been exposed as long-haul driver for 8 years to the risk had nobody ever been exposed was 1.20 (95% CI 1.04 to 1.46). After HR approximations, accelerated failure time model results were similar. Conclusions: The cumulative failure time model can effectively control time-varying confounding by Healthy Worker Survivor Effect, and provides an easily interpretable effect estimate. RRs estimated from the cumulative failure time model indicate an elevated ischaemic heart disease mortality risk for long-haul drivers in the US trucking industry.
机译：背景：职业队列研究通常受到“健康工人幸存者效应”的挑战，这可能会偏离标准的分析方法。结构失效时间模型的G估计是一种减少此类偏差的方法。加速故障时间模型最近已在职业队列中应用，但累积故障时间模型尚未应用。方法：我们使用累积失效时间模型的g估计来评估1985年在美国工会联合卡车行业雇用的30 448名队列中长期驾驶驾驶员对缺血性心脏病死亡率的影响。根据职务和工作记录。我们还将加速失效时间模型的g估计应用为敏感性分析，并从这两个模型中近似得出HR进行比较。结果：从累积故障时间模型中获得的风险比（RR）为1.09（95％CI为1.02至1.16），将未干预下观察到的风险与没有人被暴露为长途驾驶员的风险进行了比较。如果将所有人都作为长途司机暴露8年，则将风险进行比较的RR与未曾暴露的风险相比较的RR为1.20（95％CI为1.04至1.46）。 HR近似后，加速故障时间模型的结果相似。结论：累积故障时间模型可以有效地控制“健康工人幸存者效应”对时变的混淆，并提供易于理解的效应估计。根据累积故障时间模型估算的RR表明，美国卡车运输行业中长途驾驶员的缺血性心脏病死亡风险升高。

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