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A Systematic Review of Methods to Predict Weight Trajectories in Health Economic Models of Behavioral Weight-Management Programs: The Potential Role of Psychosocial Factors

Author

Listed:
  • Sarah Bates

    (School of Health and Related Research, University of Sheffield, Sheffield, South Yorkshire, UK)

  • Thomas Bayley

    (School of Health and Related Research, University of Sheffield, Sheffield, South Yorkshire, UK)

  • Paul Norman

    (Department of Psychology, University of Sheffield, Sheffield, South Yorkshire, UK)

  • Penny Breeze

    (School of Health and Related Research, University of Sheffield, Sheffield, South Yorkshire, UK)

  • Alan Brennan

    (School of Health and Related Research, University of Sheffield, Sheffield, South Yorkshire, UK)

Abstract

Objectives. There is limited evidence on the long-term effectiveness of behavioral weight-management interventions, and thus, when conducting health economic modeling, assumptions are made about weight trajectories. The aims of this review were to examine these assumptions made about weight trajectories, the evidence sources used to justify them, and the impact of assumptions on estimated cost-effectiveness. Given the evidence that some psychosocial variables are associated with weight-loss trajectories, we also aimed to examine the extent to which psychosocial variables have been used to estimate weight trajectories and whether psychosocial variables were measured within cited evidence sources. Methods. A search of databases (Medline, PubMed, Cochrane, NHS Economic Evaluation, Embase, PSYCinfo, CINAHL, EconLit) was conducted using keywords related to overweight, weight-management, and economic evaluation. Economic evaluations of weight-management interventions that included modeling beyond trial data were included. Results. Within the 38 eligible articles, 6 types of assumptions were reported (weight loss maintained, weight loss regained immediately, linear weight regain, subgroup-specific trajectories, exponential decay of effect, maintenance followed by regain). Fifteen articles cited at least 1 evidence source to support the assumption reported. The assumption used affected the assessment of cost-effectiveness in 9 of the 19 studies that tested this in sensitivity analyses. None of the articles reported using psychosocial factors to estimate weight trajectories. However, psychosocial factors were measured in evidence sources cited by 11 health economic models. Conclusions . Given the range of weight trajectories reported and the potential impact on funding decisions, further research is warranted to investigate how psychosocial variables measured in trials can be used within health economic models to simulate heterogeneous weight trajectories and potentially improve the accuracy of cost-effectiveness estimates.

Suggested Citation

  • Sarah Bates & Thomas Bayley & Paul Norman & Penny Breeze & Alan Brennan, 2020. "A Systematic Review of Methods to Predict Weight Trajectories in Health Economic Models of Behavioral Weight-Management Programs: The Potential Role of Psychosocial Factors," Medical Decision Making, , vol. 40(1), pages 90-105, January.
    • Handle: RePEc:sae:medema:v:40:y:2020:i:1:p:90-105
    DOI: 10.1177/0272989X19889897
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    References listed on IDEAS

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    1. Jayachandran N. Variyam & John Cawley, 2006. "Nutrition Labels and Obesity," NBER Working Papers 11956, National Bureau of Economic Research, Inc.
    2. Franco Sassi & Michele Cecchini & Jeremy Lauer & Dan Chisholm, 2009. "Improving Lifestyles, Tackling Obesity: The Health and Economic Impact of Prevention Strategies," OECD Health Working Papers 48, OECD Publishing.
    3. Alan Brennan & Stephen E. Chick & Ruth Davies, 2006. "A taxonomy of model structures for economic evaluation of health technologies," Health Economics, John Wiley & Sons, Ltd., vol. 15(12), pages 1295-1310, December.
    4. Alessandro Liberati & Douglas G Altman & Jennifer Tetzlaff & Cynthia Mulrow & Peter C Gøtzsche & John P A Ioannidis & Mike Clarke & P J Devereaux & Jos Kleijnen & David Moher, 2009. "The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-28, July.
    5. Drummond, Michael F. & Sculpher, Mark J. & Claxton, Karl & Stoddart, Greg L. & Torrance, George W., 2015. "Methods for the Economic Evaluation of Health Care Programmes," OUP Catalogue, Oxford University Press, edition 4, number 9780199665884.
    6. Carmen Galani & Heinz Schneider & Frans Rutten, 2007. "Modelling the lifetime costs and health effects of lifestyle intervention in the prevention and treatment of obesity in Switzerland," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 52(6), pages 372-382, December.
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    1. Hazel Squires & Michael P. Kelly & Nigel Gilbert & Falko Sniehotta & Robin C. Purshouse, 2023. "The long‐term effectiveness and cost‐effectiveness of public health interventions; how can we model behavior? A review," Health Economics, John Wiley & Sons, Ltd., vol. 32(12), pages 2836-2854, December.

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