Environmental risk factors and nonpharmacological and nonsurgical interventions for obesity: An umbrella review of meta‐analyses of cohort studies and randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Multiple environmental factors have been implicated in obesity, and multiple interventions, besides drugs and surgery, have been assessed in obese patients. Results are scattered across many studies and meta-analyses, and they often mix obese and overweight individuals. MATERIALS AND METHODS: PubMed and Cochrane Database of Systematic Reviews were searched through 21 January 2017 for meta-analyses of cohort studies assessing environmental risk factors for obesity, and randomized controlled trials investigating nonpharmacological and nonsurgical therapeutic interventions for obesity. We excluded data on overweight participants. Evidence from observational studies was graded according to criteria that included the statistical significance of the random-effects summary estimate and of the largest study in a meta-analysis, the number of obesity cases, heterogeneity between studies, 95% prediction intervals, small-study effects and excess significance. The evidence of intervention studies for obesity was assessed with the GRADE framework. RESULTS: Fifty-four articles met eligibility criteria, including 26 meta-analyses of environmental risk factors (166 studies) and 46 meta-analyses of nondrug, nonsurgical interventions (206 trials). In adults, the only risk factor with convincing evidence was depression, and childhood obesity, adolescent obesity, childhood abuse and short sleep duration had highly suggestive evidence. Infancy weight gain during the first year of life, depression and low maternal education had convincing evidence for association with paediatric obesity. All interventions had low or very-low-quality evidence with one exception of moderate-quality evidence for one comparison (no differences in efficacy between brief lifestyle primary care interventions and other interventions for paediatric obesity). Summary effect sizes were mostly small across compared interventions (maximum 5.1 kg in adults and 1.78 kg in children) and even these estimates may be inflated. CONCLUSIONS: Depression, obesity in earlier age groups, short sleep duration, childhood abuse and low maternal education have the strongest support among proposed risk factors for obesity. Furthermore, there is no high-quality evidence to recommend treating obesity with a specific nonpharmacological and nonsurgical intervention among many available, and whatever benefits in terms of magnitude of weight loss appear small.
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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 | 0.049 | 0.119 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 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".