Estimating the influence of body mass index (BMI) on mortality using offspring BMI as an instrumental variable

Int J Obes (Lond). 2022 Jan;46(1):77-84. doi: 10.1038/s41366-021-00962-8. Epub 2021 Sep 8.


Objective: High body mass index (BMI) is an important predictor of mortality but estimating underlying causality is hampered by confounding and pre-existing disease. Here, we use information from the offspring to approximate parental BMIs, with an aim to avoid biased estimation of mortality risk caused by reverse causality.

Methods: The analyses were based on information on 9674 offspring-mother and 9096 offspring-father pairs obtained from the 1958 British birth cohort. Parental BMI-mortality associations were analysed using conventional methods and using offspring BMI as a proxy, or instrument, for their parents' BMI.

Results: In the conventional analysis, associations between parental BMI and all-cause mortality were U-shaped (Pcurvature < 0.001), while offspring BMI had linear associations with parental mortality (Ptrend < 0.001, Pcurvature > 0.46). Curvature was particularly pronounced for mortality from respiratory diseases and from lung cancer. Instrumental variable analyses suggested a positive association between BMI and mortality from all causes [mothers: HR per SD of BMI 1.43 (95% CI 1.21-1.69), fathers: HR 1.17 (1.00-1.36)] and from coronary heart disease [mothers: HR 1.65 (1.15-2.36), fathers: HR 1.51 (1.17-1.97)]. These were larger than HR from the equivalent conventional analyses, despite some attenuation by adjustment for social indicators and smoking.

Conclusions: Analyses using offspring BMI as a proxy for parental BMI suggest that the apparent adverse consequences of low BMI are considerably overestimated and adverse consequences of overweight are underestimated in conventional epidemiological studies.

MeSH terms

  • Adult
  • Body Mass Index*
  • Correlation of Data
  • Fathers / statistics & numerical data
  • Female
  • Genetic Predisposition to Disease / epidemiology
  • Genetic Predisposition to Disease / genetics
  • Humans
  • Male
  • Mortality / trends*
  • Mothers / statistics & numerical data
  • Parent-Child Relations
  • Risk Factors
  • United Kingdom / epidemiology