ArticleOccupational and environmental medicine2024
Estimating impacts of reducing acrylonitrile exposure on lung cancer mortality in an occupational cohort with the parametric g-formula.
Article in Occupational and environmental medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Impact of interventions to prevent asbestos-related respiratory disease in an exposed worker registry using a simplified G-computation.American journal of epidemiology · 2026Article
- Re: Adjustment for duration of employment in occupational epidemiology.Annals of epidemiology · 2024Article
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6 authors.
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Abstract
objectivesTo inform the potential human carcinogenicity of acrylonitrile, we estimate associations between acrylonitrile exposures and lung cancer mortality in US workers with the objectives of (1) assessing potential for healthy worker survivor bias and (2) adjusting for this bias while assessing the expected lung cancer mortality under different hypothetical occupational exposure limits on acrylonitrile exposure using the parametric g-formula.
methodsWe used data from a cohort of 25 460 workers at facilities making or using acrylonitrile in the USA. We estimated HRs to quantify associations between employment and lung cancer mortality, and exposure and leaving employment. Using the parametric g-formula, we estimated cumulative lung cancer mortality at hypothetical limits on acrylonitrile exposure.
resultsRecent and current employment was associated with lung cancer, and exposure was associated with leaving employment, indicating potential for healthy worker survivor bias. Relative to no intervention, reducing the historical exposure under limits of 2.0, 1.0 and 0.45 parts per million would have been expected to reduce lung cancer mortality by age 90 by 4.46 (95% CI 0.78 to 8.15), 5.03 (95% CI 0.96 to 9.11) and 6.45 (95% CI 2.35 to 10.58) deaths per 1000 workers, respectively. A larger lung cancer mortality reduction would be expected under elimination of exposure: 7.21 (95% CI 2.72 to 11.70) deaths per 1000 workers.
conclusionsHealthy worker survivor bias likely led to underestimation of excess risk. Our results corroborate previous study findings of an excess hazard of lung cancer among the highest exposed workers.
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