Interactions and mediation in social epidemiology
Methods to address interaction and mediation in survival analysis are developed and applied in studies on social inequality in health.
The main objective of this research is to develop and apply methods of interaction and mediation in survival analysis based on absolute risk measures in order to broaden our understanding of the mechanisms driving social inequality in health.
From 2009 and ongoing
It is a wide held belief in public health and clinical decision making that interventions or preventive strategies should be aimed at patients or population sub-groups where most cases could potentially be prevented. In order to identify such sub-groups, deviation from additivity of absolute effects is a relevant measure of interest. Multiplicative survival models, such as the Cox proportional hazard model, are often used to estimate the association between exposure and development of disease in prospective studies. In Cox models, deviations from additivity have traditionally been assessed by estimating surrogate measures of additive interaction derived from multiplicative models; an approach which is both counter-intuitive and sometimes invalid. Instead we suggest the use of additive hazard models, where measures of deviation from risk additivity can be directly derived, evaluated and reported in applied survival analyses. A cornerstone in epidemiological and public health research is to understand the causal pathway from exposure to outcome.These models can also be utilized to develop simple and intuitive measures for mediation in survival analysis, which both have causal interpretations and are mathematical consistent.
The research is primarily based on data from the Social Inequality in Cancer (SIC) database, which is based on pooled data from seven Danish cohort studies: the Copenhagen City Heart Study; the Diet, Cancer and Health Study; and five cohort studies from the Glostrup Population Studies.
Finn Diderichsen, Ingelise Andersen, Ulla Arthur Hvidtfeldt, Helene Nordahl, Naja Hulvej Rod, Theis Lange, Merete Osler, Niels Keiding.
The SIC collaborators include the Department of Public Health at the University of Copenhagen, the Danish Cancer Institute cancer.dk, the Research Centre for Prevention and Health at Glostrup hospital regionh.dk and the Copenhagen City Heart Study at Bispebjerg University Hospital bispebjerghospital.dk.
Lange T, Hansen JV. Direct and indirect effects in a survival context. Epidemiology 2011; 22:575-581