Defining metabolically healthy obesity in children: a scoping review
Bibliographic record
Abstract
We conducted a scoping review to identify definitions of metabolically healthy obesity (MHO), describe gaps in the literature, and establish a universal definition of MHO in children. We searched electronic databases from January 1980 to June 2017 and grey literature. Experimental, quasi-experimental, or observational studies were eligible for inclusion if they (i) included a definition of MHO that identified risk factors, cut-off values, and the number of criteria used to define MHO, and (ii) classified 2-18 year olds as overweight or obese. Two reviewers independently screened 1,711 papers for relevance and quality; we extracted data from 39 individual reports that met inclusion criteria. Most (31/39; 79%) definitions of MHO included an absence of cardiometabolic risk factors. Heterogeneity across MHO definitions, obesity criteria, and sample sizes/characteristics resulted in variable prevalence estimates (3-80%). Finally, we convened an international panel of 46 experts to complete a 4-round Delphi process to generate a consensus-based definition of MHO. Based on consensus (≥ 80% agreement), our definition of MHO included: high density lipoprotein-cholesterol > 40 mg/dl (or > 1.03 mmol/l), triglycerides ≤ 150 mg/dl (or ≤ 1.7 mmol/l), systolic and diastolic blood pressure ≤ 90th percentile, and a measure of glycemia. This definition of MHO holds potential universal value to enable comparisons between studies and inform clinical decision-making for children with obesity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.046 | 0.150 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.028 | 0.025 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| 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".