The effect of joint exposures: examining the presence of interaction

• Published in: Kidney international Vol. 75; no. 7; pp. 677 - 681
• Main Authors: de Mutsert, Renée, Jager, Kitty J., Zoccali, Carmine, Dekker, Friedo W.
• Format: Journal Article
• Language: English
• Published: Basingstoke Elsevier Inc 01.04.2009; Nature Publishing Group; Elsevier Limited
• Subjects: additivity; Analysis. Health state; Biological and medical sciences; Cardiovascular Diseases - epidemiology; Causality; Comorbidity; Epidemiologic Studies; Epidemiology; Female; General aspects; Humans; interaction; joint exposure; Kidney Failure, Chronic - epidemiology; Logistic Models; logistic regression; Male; Medical sciences; Models, Statistical; Nephrology. Urinary tract diseases; Practice Guidelines as Topic; Public health. Hygiene; Public health. Hygiene-occupational medicine; Risk Factors; interaction; additivity; epidemiology; joint exposure; logistic regression; Additivity; Human; Logistic regression; Nephrology; Statistical analysis; Disease; Interaction; Risk factor; Epidemiology; Public health; Urology
• ISSN: 0085-2538; 1523-1755
• DOI: 10.1038/ki.2008.645

Clinical epidemiological studies investigate whether an exposure, or risk factor, is causally related to the development or progression of a disease or mortality. It might be of interest to study whether this relation is different in different types of patients. To address such research questions, the presence of interaction among risk factors can be examined. Causal interaction between two risk factors is considered most clinically relevant in epidemiology. Causal interaction occurs when two risk factors act together in causing disease and is explicitly defined as a deviation from additivity on a risk difference scale. Statistical interaction can be evaluated on both an additive (absolute risk) and multiplicative (relative risk) scale, depending on the model that is used. When using logistic regression models, which are multiplicative models, several measures of additive interaction are presented to evaluate whether the magnitude of an association differs across subgroups: the relative excess risk due to interaction (RERI), the attributable proportion due to interaction (AP), or the synergy index (S). For a transparent presentation of interaction effects the recent Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement advises reporting the separate effect of each exposure as well as the joint effect compared with the unexposed group as a joint reference category to permit evaluation of both additive and multiplicative interaction.