The healthcare costs of increased body mass index–evidence from The Trøndelag Health Study

Abstract

Abstract Background Earlier studies have estimated the impact of increased body mass index (BMI) on healthcare costs. Various methods have been used to avoid potential biases and inconsistencies. Each of these methods measure different local effects and have different strengths and weaknesses. Methods In the current study we estimate the impact of increased BMI on healthcare costs using nine common methods from the literature: multivariable regression analyses (ordinary least squares, generalized linear models, and two-part models), and instrumental variable models (using previously measured BMI, offspring BMI, and three different weighted genetic risk scores as instruments for BMI). We stratified by sex, investigated the implications of confounder adjustment, and modelled both linear and non-linear associations. Results There was a positive effect of increased BMI in both males and females in each approach. The cost of elevated BMI was higher in models that, to a greater extent, account for endogenous relations. Conclusion The study provides solid evidence that there is an association between BMI and healthcare costs, and demonstrates the importance of triangulation.

Keywords

• Obesity
• Instrumental variables
• Regression models
• Estimation
• Health
• Mendelian randomization