Difference in weight loss based on ethnicity, age and comorbidity status in a publicly funded adult weight management centre: 1‐year results
Bibliographic record
Abstract
Limited evidence is available on the effectiveness of publicly funded weight loss (WL) clinics. We examined the 1-year WL outcomes and investigated predictors of WL and discontinuation of 1566 overweight and obese adults, who attended the Wharton Medical Clinic (WMC) weight management centre for at least 6 months. Overall, 42.7% (n = 669) of the entire sample achieved a ≥5%WL over the entire follow-up period from July 2008 to February 2012. On average, patients lost 5.6 ± 7.2 kg (5.0 ± 6.3%) of initial body weight (BW), while a subsample of patients attending the clinic for at least 1 year had a mean weight reduction of 6.6 ± 7.9 kg (5.9 ± 7.2%) of BW. Older patients were more likely to achieve a greater WL in comparison with young patients while White patients and those without type 2 diabetes (T2D) lost almost twice as much weight and %BW in comparison with Asian patients and patients with T2D, respectively (P < 0.05). Discontinuing patients did not differ in terms of sex, body mass index, education and smoking status from those who continued treatment (P > 0.05). Results of this study demonstrate that the WMC provides a practical model for clinically effective lifestyle-based treatment, accessible to a wide range of demographically diverse adults.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".