MétaCan
Menu
Back to cohort
Record W4410311518 · doi:10.1111/cob.70022

Ethnic differences in weight loss during a clinical obesity management program

2025· article· en· W4410311518 on OpenAlex
Jennifer L. Kuk, Parmis Mirzadeh, Sean Wharton

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueClinical Obesity · 2025
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsYork University
FundersYork University
KeywordsMedicineWeight lossEthnic groupObesityBody mass indexWeight managementIndigenousDemographyBody weightWeight changeInternal medicine

Abstract

fetched live from OpenAlex

Summary To examine ethnic differences in how individuals respond to obesity management therapies, a retrospective chart review of the Wharton Medical Weight Management Clinic electronic medical records was used ( n = 21 709; 14 695 patients with weight loss data). South and East Asian, Middle Eastern and Other ethnicities had a significantly lower body mass index (BMI) at enrollment than White adults (39.7 vs. 35.4–38.7 kg/m 2 ), with higher or similar BMIs in Indigenous and Black adults (39.9–42.2 kg/m 2 ). Whites, East Asians and Other Ethnicities had the greatest weight loss (4.3–4.9 kg), while Blacks (3.3 kg), Latin (3.0 kg), Middle Eastern (2.7 kg), and South Asians (3.5 kg) lost significantly less weight as compared to Whites (4.9 kg) ( p < .05). There were also weight loss differences between Black sub‐groups. African American females lost the least weight (1.4 kg), while West Indian Black females lost much more weight (4.3 kg, p = .01). African American males also lost the least amount of weight (0.9 kg), while African Black males lost the most (7.4 kg, p = 0.01). There are differences in the weight loss achieved during a clinical obesity management program between individuals of various ethnicities.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.216
GPT teacher head0.583
Teacher spread0.367 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it