Association of Obesity with Health Care Costs: A Mendelian Randomization study

Abstract

Causal effect estimates for the association of obesity with health care costs can be biased by reversed causation and omitted variables. In this study, we use genetic variants as instrumental variables to overcome these limitations. We estimate the effect of body mass index (BMI) and waist-to-hip ratio (WHR) on total health care costs using data from a German observational study. We find that the model using genetic instruments identifies additional annual costs of 189e for a one unit increase in BMI, and additional 1165e for a 0.1 unit increase in WHR. This is more than two times higher than estimates from linear regression without instrumental variables. We found little evidence of a non-linear relationship between BMI or WHR and health care costs. Our results imply that the use of genetic instruments can be a powerful tool for estimating causal effects in health economic evaluation that might be superior to other types of instruments where there is a strong association with a modifiable risk factor.