What question did this study set out to answer?

To review, evaluate, and develop flexible relative risk regression models that characterize the joint effects of multiple continuous and categorical exposures in occupational cohorts.

January 1, 1988American Journal of Industrial Medicine

Relative risk models for assessing the joint effects of multiple factors

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To review, evaluate, and develop flexible relative risk regression models that characterize the joint effects of multiple continuous and categorical exposures in occupational cohorts.
Reviewed generalized relative risk regression formulations based on Poisson probability models and cross-classified cohort data.
Assessed limitations in existing non-exponential relative risk models when modeling multiple simultaneous covariates, proposing alternative parameterizations.
Applied the regression frameworks to evaluate the combined exposure effects of radon progeny and tobacco smoking on lung cancer mortality among uranium miners.
Identified practical and mathematical limitations in previously proposed generalized relative risk models when applied to multiple continuous covariates.
Demonstrated that alternative Poisson regression frameworks can effectively capture non-multiplicative and non-exponential joint interactions between radon and tobacco use on lung cancer risk.

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Implication

Cohort analysis evaluates joint effects of radon and tobacco on lung cancer mortality in uranium miners, highlighting flexible relative risk modeling alternatives.

Cite This Study

Lubin et al. (1988) studied this question.

synapsesocial.com/papers/6a19967c196cd56b09ea6fe1 https://doi.org/10.1002/ajim.4700130110

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Implication

Cohort analysis evaluates joint effects of radon and tobacco on lung cancer mortality in uranium miners, highlighting flexible relative risk modeling alternatives.

Relative risk models for assessing the joint effects of multiple factors

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Discussion

Implication

Cite This Study

Relative risk models for assessing the joint effects of multiple factors

Key Points

Discussion

Implication

Cite This Study