Strategies for weight maintenance in adult populations treated for overweight and obesity: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Once weight loss is achieved, the challenge is to maintain this benefit. This review reports on the effectiveness of programs for weight-loss maintenance, as part of a larger review examining treatments for overweight and obese adults. METHODS: We updated the search of a 2011 review on screening and management of overweight and obese adults. Four databases were searched. For inclusion, participants had to have lost weight in treatment and then been randomly assigned to a weight-maintenance intervention or control conditions. Studies from the 2011 review that met the criteria were included. Data were extracted and pooled (where possible) for outcomes related to weight-loss maintenance. RESULTS: Eight studies were included. Compared with control participants, intervention participants regained less weight (mean difference [MD] -1.44 kg, 95% confidence interval [CI] -2.42 to -0.47), regardless of whether the intervention was behavioural (MD-1.56 kg, 95% CI -3.10 to -0.02) or pharmacologic plus behavioural (MD -1.39 kg, 95% CI -2.86 to 0.08). Intervention participants also showed better weight maintenance than the control participants in terms of waist circumference (MD -2.30 cm, 95% CI -3.45 to -1.15) and body mass index (MD -0.95 kg/m(2), 95% CI -1.67 to -0.23). Participants undergoing pharmacologic plus behavioural interventions were more likely to maintain a loss of 5% or more of initial body weight than those in the control group (risk ratio [RR] 1.33, 95% CI 1.15 to 1.54); no difference was found for maintaining a weight loss of 10% or more (RR 1.76, 95% CI 0.75 to 4.12). INTERPRETATION: Moderate quality evidence shows that overweight and obese adults can benefit from interventions for weight maintenance following weight loss. However, there is insufficient evidence on the long-term sustainability of these benefits. REGISTRATION: PROSPERO no. CRD42012002753.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.026 |
| Bibliometrics | 0.005 | 0.005 |
| 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) | 0.005 | 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".