Mendelian Randomization analysis of the causal effect of adiposity on hospital costs

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. Most estimates of this association are affected by endogeneity bias. We use a novel identification strategy exploiting Mendelian Randomization - random germline genetic variation modelled using instrumental variables - to identify the causal effect of BMI on inpatient hospital costs. Using data on over 300,000 individuals, the effect size per person per marginal unit of BMI per year varied according to specification, including 21.22 pound (95% confidence interval (CI): 14.35- pound 28.07) pound for conventional inverse variance weighted models to 18.85 pound (95% CI: 9.05- pound 28.65) pound for penalized weighted median models. Effect sizes from Mendelian Randomization models were larger in most cases than noninstrumental variable multivariable adjusted estimates (13.47 pound, 95% CI: 12.51- pound 14.43) pound. There was little evidence of non-linearity. Within-family estimates, intended to address dynastic biases, were imprecise. (C) 2020 The Authors. Published by Elsevier B.V.