There is an ongoing debate on whether analyses of occupational studies should be adjusted for socioeconomic status (SES). In this paper directed acyclic graphs (DAGs) were used to evaluate common scenarios in occupational cancer studies with the aim of clarifying this issue. It was assumed that the occupational exposure of interest is associated with SES and different scenarios were evaluated in which (a) SES is not a cause of the cancer under study, (b) SES is not a cause of the cancer under study, but is associated with other occupational factors that are causes of the cancer, (c) SES causes the cancer under study and is associated with other causal occupational factors. These examples illustrate that a unique answer to the issue of adjustment for SES in occupational cancer studies is not possible, as in some circumstances the adjustment introduces bias, in some it is appropriate and in others both the adjusted and the crude estimates are biased. These examples also illustrate the benefits of using DAGs in discussions of whether or not to adjust for SES and other potential confounders.

Using directed acyclic graphs to consider adjustment for socioeconomic status in occupational cancer studies

BARONE ADESI, Francesco;MERLETTI, Franco;
2008-01-01

Abstract

There is an ongoing debate on whether analyses of occupational studies should be adjusted for socioeconomic status (SES). In this paper directed acyclic graphs (DAGs) were used to evaluate common scenarios in occupational cancer studies with the aim of clarifying this issue. It was assumed that the occupational exposure of interest is associated with SES and different scenarios were evaluated in which (a) SES is not a cause of the cancer under study, (b) SES is not a cause of the cancer under study, but is associated with other occupational factors that are causes of the cancer, (c) SES causes the cancer under study and is associated with other causal occupational factors. These examples illustrate that a unique answer to the issue of adjustment for SES in occupational cancer studies is not possible, as in some circumstances the adjustment introduces bias, in some it is appropriate and in others both the adjusted and the crude estimates are biased. These examples also illustrate the benefits of using DAGs in discussions of whether or not to adjust for SES and other potential confounders.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11579/70813
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