Evidence map›Paper›PMID 31007613›Full record

ArticleSocial theory & health : STH2018

In BMI We Trust: Reframing the Body Mass Index as a Measure of Health.

Iliya Gutin

Abstract read
In one paragraph

Article in Social theory & health : STH, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 110 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
110citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

110 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Effects ofNutrients · 2024
    Trial
  4. Trial
  5. Trial
  6. Article
  7. Article
  8. Article
  9. Article
  10. Observational
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article

50 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Iliya GutinThe University of North Carolina-Chapel Hill, 155 Hamilton Hall, Chapel Hill, NC 27514.

Funding

Research Services CoreP2CHD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN B GUZZO · 2015 to 2026
$9.6M
NICHD NIH HHS P2C HD050924
6 · The paper itself

Abstract

Recent work in medical sociology has provided critical insights into distinguishing between obesity as a condition with severe individual- and population-level health consequences, and obesity as a socially undesirable, stigmatizing construct opposing thinness as the healthy ideal. Less often considered is the role of Body Mass Index (BMI) as the standard by which obesity and healthy weight are measured and defined. Addressing this issue, I begin by distinguishing between BMI as an empirical, objective measure of health, and BMI as an arbitrary, subjective label for categorizing the population. I further consider how BMI is empowered as a measurable quantity through the lens of medicalization and evidence-based medicine, and introduce the "performativity" of BMI as a superior framework for confronting the measure's conceptual limitations. Emphasizing key parallels between BMI and self-rated health as measures with high predictive validity, yet unspecified mechanisms of action, I propose an epistemological shift away from classifying BMI as a biomarker and toward a more flexible view of the measure as a holistic appraisal of health. In closing, I argue that researchers may continue to leverage BMI's ease of collection and interpretation, provided they are attuned to its definitional ambiguity across diverse research methods and contexts.

Indexed as

BMIMeasurementPerformativitySelf-rated healthValidity

Identifiers

PMID31007613
PMCPMC6469873

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.