Effect of Low‐Glycemic Index/Load Diets on Body Weight: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Objective It is unclear whether low glycemic index and load diets contribute to weight loss. To synthesize the evidence of the effect of low glycemic index/load (GI/GL) diets on body weight in order to inform clinical practice guidelines, we conducted a systematic review and meta‐analysis of randomized controlled trials. Methods We searched Medline, EMBASE, and the Cochrane Library (through June 2 2015). We included randomized controlled trials ≥12 weeks investigating the effect of a low‐GI or low‐GL intervention compared with an isocaloric control diet on body weight in participants that are overweight or obese (BMI >25 kg/m 2 ). Two independent reviewers extracted all relevant data, assessed risk of bias of individual trials using the Cochrane Risk of Bias Tool. Data were pooled using the generic inverse variance method and expressed as mean differences (MD) with 95% confidence intervals (CIs). Heterogeneity was assessed by the Cochran Q statistic and quantified by the I 2 statistic. Results Eligibility criteria were met by 19 randomized controlled trials (RCTs) (22 comparisons) involving 1,577 overweight or obese participants. Low GI/GL diets resulted in a non‐significant decrease in body weight compared with higher GI/GL control diets (MD= −0.32 kg (95% CIs −0.86 kg, 0.23 kg) with evidence of substantial inter‐study heterogeneity (I 2 =57%, p<0.001). Limitations Most of the trials were of moderate duration (<6 months) and there was substantial unexplained inter‐study heterogeneity. Conclusion Low GI/GL diets do not lead to significantly more weight loss than higher GI/GL diets over the moderate term in overweight or obese people. To address the sources of uncertainty, there is a need for larger, longer, higher quality trials. Support or Funding Information Financial support for this work given by The Canadian Institutes of Health Research (funding reference number, 129920) through the Canada‐wide Human Nutrition Trialists’ Network (NTN), the PSI foundation, and the Canadian Diabetes Association.
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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 | 0.021 | 0.045 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.035 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 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".