Abstract
Focus and outcomes for participants
Long periods between exposures and outcomes pose a number of challenges for life course epidemiological research, including unmeasured confounding factors (e.g.; familial factors) and mediation by other covariates, which make it difficult to unequivocally establish associations let alone causality. In this symposium we will present a number of different studies based on big data utilizing a variety of methods to overcome some of the issues encountered in research across long time frames or generations. Our focus will be on the different methods, the solutions they provide as well as their limitations. The methods presented were applied in the context of life course epidemiology and include: mediation analyses; genetic epidemiology; well-established and novel family designs including twins, siblings and cousins, and a method comparable to Mendelian randomization - ICE FALCON (Inference on Causation from Examination of Familial Confounding) which is part of a more general approach called ICE CRiSTAL (Inference on Causation from Examining Changes in Regression coefficients in STatistical AnaLsyes). The intended outcomes for the audience are to increase awareness of the challenges imposed by the data frequently used in this field of research and present possible solutions to (at least partly) address those. It is our intention to generate discussion and encourage other researchers to share their experiences and solutions to increase knowledge collectively.
Rationale for the symposium, including for its inclusion in the Congress
The main theme of the conference is ‘Methodological Innovations in Epidemiology’. Our symposium includes six different methods to strengthen causal inferences in epidemiology. While some of the presented methods are well established in classic epidemiology research (i.e. mediation analyses), others are more commonly found in different disciplines such as the expanding genetic epidemiology field (e.g. alternative twin designs and measured genetic risk approaches). In addition, we are presenting a new method for making inference about causation developed by Prof. John Hopper and Dr Shuai Li and co-workers called ICE FALCON, which applies to twin and family data and is part of a more general approach called ICE CRiSTAL. These methods use observational data to infer or rebut causality between measured variables, similar to Mendelian randomization (without relying on genetic information or strong assumptions). All the work presented is either nearing publication or has been published in the last two years and each presenter is intimately involved with the analysis and methods they will be presenting. Beyond a range of methods and study designs we have also a diversity of researchers and research questions in our symposium by including: researchers at different stages in their career and from around the world (ranging from early Postdoctoral Fellows over Senior Research Fellows/Assistant professors to Professors); a variety of research questions and diseases; and a range of population context including Indigenous Australians, babies, children, and adults, in order to appeal to a wider audience.
Presentation program
6 talks of 8 minutes each with 2 minutes for questions followed by a general discussion facilitated by the chair.
Names of presenters
Dr Miriam A Mosing1,2
1057Addressing challenges in life-course epidemiology: established and novel approaches using big data and twin/family studies
