Validity of non‐traditional measures of obesity compared to total body fat across the life course: A systematic review and meta‐analysis
Bibliographic record
Abstract
Summary IntroductionTraditional obesity measures including body mass index, waist circumference, waist‐to‐hip ratio, and waist‐to‐height ratio have limitations. The primary objective of this study was to identify and review the validity of non‐traditional obesity measures, using measures of total body fat as the reference standard, that have been used across multiple life stages. MethodsWe conducted a systematic review and searched MEDLINE, Embase, and PsycINFO. We included observational studies published from 2013 to October 2023 among “the general population” for any life stage that reported the validity of non‐traditional obesity measures compared to total body fat reference standards. Separate meta‐analyses were performed to pool correlation coefficients and mean differences for non‐traditional obesity measures that were evaluated at multiple life stages. ResultsA total of 123 studies were included, and 55 validated non‐traditional obesity measures were identified. Of these, 13 were evaluated at multiple life stages. Two‐dimensional (2D) digital imaging technologies, three‐dimensional (3D) body scanners, relative fat mass (RFM), and mid‐upper arm circumference had high or moderate validity (pooled correlation coefficient >0.70). Pooled mean differences were small (<6%) between total body fat percentage from reference standards and from RFM, 2D digital imaging technologies, 3D body scanners, and the body adiposity index. Heterogeneity (I 2 ) was >75% in most meta‐analyses. ConclusionNumerous validated non‐traditional obesity measures were identified; relatively few were evaluated at multiple life stages and did not consider health risks associated with adiposity. More research is needed to define valid obesity measures across all life stages that assess health and adiposity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.072 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.031 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".