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Metrics that matter: Identifying endpoints for capturing the broad health impacts of prevention of obesity

  • Jonathan Pearson-Stuttard*
  • , Sara Holloway
  • , Jamie Kettle
  • , Hugo Harper
  • , Irina Pokhilenko
  • , Manuel Gomez
  • , Louis Garrison
  • , Ricardo Reynoso
  • , Katherine Byrne
  • , Jutta Kloppenborg Heick Skau
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Aims: The link between health and economic prosperity is well established, yet quantifying the value of illness prevention remains challenging due to lack of comprehensive metrics. Obesity exemplifies this issue, having widespread societal and health care impacts but limited prevention funding. Existing metrics often fail to capture broader effects of prevention of obesity. This study aimed to identify key components for a holistic metric to assess obesity and cardiometabolic health progression, better articulating value of prevention.

Materials and Methods: We conducted a targeted literature review to identify existing individual and composite metrics for prevention in adults, agnostic of disease or risk factor. We categorized endpoints into: (i) holistic composite measures; (ii) user-centred composite measures; (iii) health outcome composite measures; (iv) single clinical endpoints. Metrics were evaluated against eight criteria including holistic outcome, cardiometabolic relevance, data feasibility, geographical generalizability, established outcome, economic modelling methodology, stakeholder relevance and preventive value; alongside semi-structured review from six clinical, health economics and policy experts.

Results: Cardiometabolic endpoints numbering 74 were identified: 7 holistic composites, 16 user-centred composites, 31 health-based composites and 20 single clinical endpoints. Five endpoints were shortlisted according to assessment criteria and expert input: waist-to-height ratio, low-density lipoprotein cholesterol, systolic and diastolic blood pressure, blood glucose and the 12-Item Short Form Health Survey (SF-12). These endpoints collectively reflected physiological cardiometabolic risk factors with an adverse association with obesity, while SF-12 provided health-related quality-of-life measurement.

Conclusions: We developed a novel framework that shortlisted five key cardiometabolic outcome measures for assessing obesity primary prevention benefits, with potential applications in health economic modelling and public health.
Original languageEnglish
JournalDiabetes, obesity & metabolism
Early online date25 Aug 2025
DOIs
Publication statusE-pub ahead of print - 25 Aug 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • cardiovascular disease
  • obesity care
  • obesity therapy
  • weight control

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