Islamic fasting and weight loss: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Studies on the effects of Ramadan fasting on weight changes have been contradictory. We brought together all published data to comprehensively examine the effects in a systematic review and meta-analysis. DESIGN: Relevant studies were obtained through searches of PubMed and CINAHL and by independent screening of reference lists and citations without any time restriction. All searches were completed between October and November 2011. SETTING: Changes in body weight during and after Ramadan were extracted from thirty-five English-language studies and were meta-analysed. Most of the studies were conducted in West Asia (n 19); the remainder were conducted in Africa (n 7), East Asia (n 3) and North America/Europe (n 4). SUBJECTS: Healthy adults. RESULTS: Fasting during Ramadan resulted in significant weight loss (-1·24 kg; 95% CI -1·60, -0·88 kg). However, most of the weight lost was regained within a few weeks and only a slight decrease in body weight was observed in the following weeks after Ramadan compared with that at the beginning of Ramadan. Weight loss at the end of Ramadan was significant in both genders (-1·51 kg for men and -0·92 kg for women); but again the weight loss lasted no longer than 2 weeks after Ramadan. Weight loss during Ramadan was greater among Asian populations compared with Africans and Europeans. CONCLUSIONS: Weight changes during Ramadan were relatively small and mostly reversed after Ramadan, gradually returning to pre-Ramadan status. Ramadan provides an opportunity to lose weight, but structured and consistent lifestyle modifications are necessary to achieve lasting weight loss.
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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 | 0.019 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.034 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".