An instrumental variable analysis of body mass index and risk of long-term sick leave: the HUNT Study, Norway.

Abstract

A more comprehensive understanding of the causal relationships between body mass index (BMI) and sick leave is needed. We aimed to examine the effect of BMI on the risk of cause-specific and all-cause long-term sick leave using an instrumental variable approach. The study included 21,918 adults participating in the two latest surveys of the population-based HUNT Study (HUNT3, 2006-2008 and HUNT4, 2017-2019) linked with registry data on cause-specific sick leave, including musculoskeletal and mental disorders. We used Cox regression to estimate risk of long-term sick leave per standard deviation (SD) increase in z-score of BMI, applying both conventional analysis of own BMI and instrumental variable analysis based on offspring BMI. In the conventional analyses, hazard ratios per SD increase in z-score of BMI ranged from 1.04 (95% confidence interval (CI) 0.99-1.08) for mental health disorders in women to 1.17 (95% CI 1.13-1.22) for musculoskeletal disorders in men. The instrumental variable approach supported that higher BMI increased the risk of long-term sick leave, except for sick leave due to mental health disorders in men. The analyses suggested that offspring BMI as an instrument is not independent of shared confounding. The results from both the conventional and instrumental variable analyses show that higher BMI increases the risk of long-term sick leave, except for sick leave due to mental health disorders in men. The instrumental variable method is likely to remove bias due to reverse causation, but residual bias due to shared confounding factors cannot be ruled out.