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Application of mendelian randomization to investigate the association of body mass index with health care costs.

Med. Decis. Making 40, 156-169 (2020)
Publ. Version/Full Text Postprint DOI
Open Access Green
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, a method that is often called Mendelian randomization (MR). We describe the assumptions, available methods, and potential pitfalls of using genetic information and how to address them. We estimate the effect of body mass index (BMI) on total health care costs using data from a German observational study and from published large-scale data. In a meta-analysis of several MR approaches, we find that models using genetic instruments identify additional annual costs of euro280 for a 1-unit increase in BMI. This is more than 3 times higher than estimates from linear regression without instrumental variables (euro75). We found little evidence of a nonlinear relationship between BMI and health care costs. Our results suggest 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.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Bodymass Index ; Health Care Costs ; Mendelian Randomization ; Obesity; Instrumental Variables Estimation; Invalid Instruments; Genetic-variants; Childhood Obesity; Weight; Inference; Impact; Lasso; Risk; Bias
ISSN (print) / ISBN 0272-989X
e-ISSN 1552-681X
Quellenangaben Volume: 40, Issue: 2, Pages: 156-169 Article Number: , Supplement: ,
Publisher Sage
Publishing Place 2455 Teller Rd, Thousand Oaks, Ca 91320 Usa
Reviewing status Peer reviewed