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Padraig DixonAbstract: Estimates of the marginal effect of measures of adiposity such as body mass index (BMI) on healthcare costs are important for the formulation and evaluation of policies targeting adverse weight profiles. Many existing estimates of this association are affected by endogeneity bias caused by simultaneity bias, measurement error and omitted variables.

The contribution of this study is to avoid this bias by using a novel identification strategy – random germline genetic variation in an instrumental variable analysis – to identify the presence and magnitude of the causal effect of BMI on inpatient hospital costs. We use genetic variant-level data to undertake much richer testing of the sensitivity of results to potential violations of the instrumental variable assumptions than is possible with existing approaches. Using data on over 300,000 individuals, we found effect sizes for the marginal unit of BMI over 50% as large as multivariable effect sizes. These effects attenuated under sensitivity analyses, but effect sizes remained larger than multivariable estimates for all but one estimator. There was little evidence for non-linear effects of BMI on hospital costs. Within-family estimates, intended to address dynastic biases, were null but suffered from low power.

This paper is the first to use genetic variants in a Mendelian Randomization framework to estimate the causal effect of BMI (or any other disease/trait) on healthcare costs. This type of analysis can be used to inform the cost-effectiveness of interventions and policies targeting the prevention and treatment of overweight and obesity, and for setting research priorities.

Biography: Padraig is currently an MRC research fellow. His three-year programme of work (2017-2020) uses Mendelian Randomization to study the causal effect of obesity, coronary artery disease and other health conditions and traits on healthcare costs and on quality of life. Padraig holds degrees in Economics from Trinity College Dublin (BA) and Nuffield College, Oxford (MPhil and DPhil), and in Health Economics from the University of York (MSc). His interests include applied economic evaluations and related research undertaken alongside randomised controlled trials and in the context of observational research designs.