Physical function after dietary weight loss in overweight and obese adults with osteoarthritis: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Osteoarthritis (OA) is associated with functional limitations that can impair mobility and reduce quality of life in affected individuals. Excess body weight in OA can exacerbate impaired physical function, highlighting the importance of weight management in this population. The aim of this systematic review was to compare the effects of different dietary interventions for weight loss on physical function in overweight and obese individuals with OA. DESIGN: A comprehensive search of five databases was conducted to identify relevant articles for inclusion. Studies were included that examined the effect of dietary weight loss interventions, with or without exercise, on physical function in adults with OA who were overweight or obese. Quality and risk of bias were assessed using the Quality Criteria Checklist for primary research. Primary and secondary outcomes were extracted, including change in weight and physical function which included performance-based and self-report measures. RESULTS: Nineteen relevant studies were included, which incorporated lifestyle interventions (n 8), diet in combination with meal replacements (DMR; n 5) and very low-energy diets (VLED; n 6) using meal replacements only. Pooled data for eight RCT indicated a mean difference in Western Ontario and McMaster Universities Arthritis Index (WOMAC) physical function of 12·4 and 12·5 % following DMR or VLED interventions, respectively; however, no statistically significant change was detected for lifestyle interventions. CONCLUSIONS: Our findings suggest that partial use of meal replacements is as effective as their sole use in the more restrictive VLED. Both dietary interventions are more effective than lifestyle programmes to induce significant weight loss and improvements in physical function.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.030 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".