Interaction between two exposures: determining odds ratios and confidence intervals for risk estimates

TL;DR

This paper reviews methods for estimating interaction effects between two risk factors on disease outcomes, focusing on calculating odds ratios and confidence intervals using a single regression model on both additive and multiplicative scales.

Contribution

It introduces a unified approach for estimating interaction and confidence intervals for two exposures within a single regression framework, clarifying the relationship between measures.

Findings

Provides formulas for calculating interaction effects and confidence intervals.

Clarifies the relationship between additive and multiplicative interaction measures.

Offers guidance on estimating standard errors for combined exposure risks.

Abstract

In epidemiological research, it is common to investigate the interaction between risk factors for an outcome such as a disease and hence to estimate the risk associated with being exposed for either or both of two risk factors under investigation. Interactions can be estimated both on the additive and multiplicative scale using the same regression model. We here present a review for calculating interaction and estimating the risk and confidence interval of two exposures using a single regression model and the relationship between measures, particularly the standard error for the combined exposure risk group.