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

International Journal of Obesity volume 46, pages 77–84 (2022)Cite this article

Subjects

Abstract

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.

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Fig. 1: Associations between parental all-cause mortality by offspring BMI in 1981 (age 23 years) and own BMI in 1969.

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Data availability

Access to the data from the 1958 British birth cohort can be obtained through the UK DATA Service (https://www.ukdataservice.ac.uk/).

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Acknowledgements

The authors thank the Centre for Longitudinal Studies (CLS), UCL Institute of Education, for the use of 1958-NCDS data and the UK Data Service for making them available. Neither CLS nor the UK Data Service bear any responsibility for the analysis or interpretation of these data.

Funding

This study was funded by the Wellcome trust (ref 059480/Z/99/A). EH was funded by Public Health Career Scientist Award from the Department of Health, UK. Statistical analyses were funded by the UK Medical Research Council (MRC grant G0601653). This work was supported by the National Institute for Health Research Biomedical Research Centre at Great Ormond Street Hospital for Children NHS Foundation Trust and University College London. The views expressed in the publication are those of the authors and not necessarily those of the Department of Health. GDS and DC work in a unit which receives funds from the UK Medical Research Council (grant numbers 2013-2018: MC_UU_12013/1 and MC_UU_12013/9 and 2018-2023: MC_UU_00011/1) and the University of Bristol.

Author information

Authors and Affiliations

  1. Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, North Terrace, Adelaide, SA, 5000, Australia

    Elina Hyppönen

  2. Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK

    Elina Hyppönen, Diane J. Berry & Chris Power

  3. South Australian Health and Medical Research Institute, North Terrace, Adelaide, SA, 5000, Australia

    Elina Hyppönen

  4. MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK

    David Carslake & George Davey Smith

  5. Population Health Sciences, Bristol Medical School, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK

    David Carslake & George Davey Smith

Authors
  1. Elina Hyppönen
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Contributions

EH, CP and GDS conceived the study. Data analysis was conducted by DC, DJB and EH. The manuscript was written by EH and all authors contributed to its revision and the interpretation of the results. EH had full access to all data in the study.

Corresponding author

Correspondence to Elina Hyppönen.

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Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

Ethical committee approval for the survey at 42 years of age was obtained from the North Thames Medical Research Ethics Committee (MREC) and for the survey at 44 years of age from the South East MREC. Ethical committee approval was not sought for the survey at 33 years of age, although cohort members were asked to give written consent for access to medical records. Ethical approval for the intergenerational research was obtained from the local research ethics committee (Great Ormond Street Hospital/Institute of Child Health, London).

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Hyppönen, E., Carslake, D., Berry, D.J. et al. Estimating the influence of body mass index (BMI) on mortality using offspring BMI as an instrumental variable. Int J Obes 46, 77–84 (2022). https://doi.org/10.1038/s41366-021-00962-8

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