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Relationship between mediation analysis and the structured life course approach.

ABSTRACT: Many questions in life course epidemiology involve mediation and/or interaction because of the long latency period between exposures and outcomes. In this paper, we explore how mediation analysis (based on counterfactual theory and implemented using conventional regression approaches) links with a structured approach to selecting life course hypotheses. Using theory and simulated data, we show how the alternative life course hypotheses assessed in the structured life course approach correspond to different combinations of mediation and interaction parameters. For example, an early life critical period model corresponds to a direct effect of the early life exposure, but no indirect effect via the mediator and no interaction between the early life exposure and the mediator. We also compare these methods using an illustrative real-data example using data on parental occupational social class (early life exposure), own adult occupational social class (mediator) and physical capability (outcome).

SUBMITTER: Howe LD

PROVIDER: S-EPMC5841634 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Relationship between mediation analysis and the structured life course approach.

Howe Laura D LD Smith Andrew D AD Macdonald-Wallis Corrie C Anderson Emma L EL Galobardes Bruna B Lawlor Debbie A DA Ben-Shlomo Yoav Y Hardy Rebecca R Cooper Rachel R Tilling Kate K Fraser Abigail A

International journal of epidemiology 20160801 4

Many questions in life course epidemiology involve mediation and/or interaction because of the long latency period between exposures and outcomes. In this paper, we explore how mediation analysis (based on counterfactual theory and implemented using conventional regression approaches) links with a structured approach to selecting life course hypotheses. Using theory and simulated data, we show how the alternative life course hypotheses assessed in the structured life course approach correspond t ...[more]

PMID: 27681097

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Project description:BackgroundRecent studies have suggested that patients treated in research-active institutions have better outcomes than patients treated in research-inactive institutions. However, little attention has been paid to explaining such effects, probably because techniques for mediation analysis existing so far have not been applicable to survival data.MethodsWe investigated the underlying mechanisms using a recently developed method for mediation analysis of survival data. Our analysis of the effect of research activity on patient survival was based on 352 patients who had been diagnosed with advanced ovarian cancer at 149 hospitals in 2001. All hospitals took part in a quality assurance program of the German Cancer Society. Patient outcomes were compared between hospitals participating in clinical trials and non-trial hospitals. Surgical outcome and chemotherapy selection were explored as potential mediators of the effect of hospital research activity on patient survival.ResultsThe 219 patients treated in hospitals participating in clinical trials had more complete surgical debulking, were more likely to receive the recommended platinum-taxane combination, and had better survival than the 133 patients treated in non-trial hospitals. Taking into account baseline confounders, the overall adjusted hazard ratio of death was 0.58 (95% confidence interval: 0.42 to 0.79). This effect was decomposed into a direct effect of research activity of 0.67 and two indirect effects of 0.93 each mediated through either optimal surgery or chemotherapy. Taken together, about 26% of the beneficial effect of research activity was mediated through the proposed pathways.ConclusionsMediation analysis allows proceeding from the question "Does it work?" to the question "How does it work?" In particular, we have shown that the research activity of a hospital contributes to superior patient survival through better use of surgery and chemotherapy. This methodology may be applied to analyze direct and indirect natural effects for almost any combination of variable types.

Dataset Information

Relationship between mediation analysis and the structured life course approach.

Publications

Relationship between mediation analysis and the structured life course approach.

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