Edwards Jessie K, McGrath Leah J, Buckley Jessie P, Schubauer-Berigan Mary K, Cole Stephen R, Richardson David B
From the aDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC; and bDivision of Surveillance, Hazard Evaluations, and Field Studies, National Institute for Occupational Safety and Health, Cincinnati, OH.
Epidemiology. 2014 Nov;25(6):829-34. doi: 10.1097/EDE.0000000000000164.
Traditional regression analysis techniques used to estimate associations between occupational radon exposure and lung cancer focus on estimating the effect of cumulative radon exposure on lung cancer. In contrast, public health interventions are typically based on regulating radon concentration rather than workers' cumulative exposure. Estimating the effect of cumulative occupational exposure on lung cancer may be difficult in situations vulnerable to the healthy worker survivor bias.
Workers in the Colorado Plateau Uranium Miners cohort (n = 4,134) entered the study between 1950 and 1964 and were followed for lung cancer mortality through 2005. We use the parametric g-formula to compare the observed lung cancer mortality to the potential lung cancer mortality had each of 3 policies to limit monthly radon exposure been in place throughout follow-up.
There were 617 lung cancer deaths over 135,275 person-years of follow-up. With no intervention on radon exposure, estimated lung cancer mortality by age 90 was 16%. Lung cancer mortality was reduced for all interventions considered, and larger reductions in lung cancer mortality were seen for interventions with lower monthly radon exposure limits. The most stringent guideline, the Mine Safety and Health Administration standard of 0.33 working-level months, reduced lung cancer mortality from 16% to 10% (risk ratio = 0.67 [95% confidence interval = 0.61 to 0.73]).
This work illustrates the utility of the parametric g-formula for estimating the effects of policies regarding occupational exposures, particularly in situations vulnerable to the healthy worker survivor bias.
用于估计职业性氡暴露与肺癌之间关联的传统回归分析技术,着重于估计累积氡暴露对肺癌的影响。相比之下,公共卫生干预通常基于对氡浓度的监管,而非工人的累积暴露量。在易受健康工人幸存者偏差影响的情况下,估计累积职业暴露对肺癌的影响可能会很困难。
科罗拉多高原铀矿矿工队列中的工人(n = 4134)于1950年至1964年间进入该研究,并随访至2005年的肺癌死亡率。我们使用参数化g公式,将观察到的肺癌死亡率与在整个随访期间若实施3项限制每月氡暴露的政策中任何一项时的潜在肺癌死亡率进行比较。
在135275人年的随访期间有617例肺癌死亡。若不对氡暴露进行干预,估计到90岁时的肺癌死亡率为16%。对于所考虑的所有干预措施,肺癌死亡率均有所降低,且每月氡暴露限制较低的干预措施使肺癌死亡率降低幅度更大。最严格的指导方针,即美国矿山安全与健康管理局的0.33工作水平月标准,将肺癌死亡率从16%降至10%(风险比 = 0.67 [95%置信区间 = 0.61至0.73])。
这项工作说明了参数化g公式在估计职业暴露相关政策影响方面的实用性,尤其是在易受健康工人幸存者偏差影响的情况下。