Assessing the impact of non-nutritive sweeteners on anthropometric indices and leptin levels in adults: A GRADE-assessed systematic review, meta-analysis, and meta-regression of randomized clinical trials
Bibliographic record
Abstract
In today’s world, non-nutritive sweeteners (NNSs) are recognized as substitutes for sugar or other high-calorie sweeteners, and their consumption is increasing dramatically. However, there is ongoing debate regarding the impact of NNSs on anthropometric indices. To fill this gap in knowledge, the current GRADE-assessed systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to evaluate the effects of artificial- and stevia-based sweeteners consumption on anthropometric indices and serum leptin level which is known as an appetite-regulating hormone. A comprehensive search was conducted on the Scopus, PubMed, and Embase databases up to November 2022 to identify randomized controlled trials (RCTs) investigating the effects of NNSs on anthropometric indices and serum leptin levels. Data extraction from qualified studies was performed independently by two researchers. A random- or fixed-effects model was used to estimate weighted mean differences (WMDs) and 95% confidence intervals (CIs) for anthropometric indices such as body weight (BW), body mass index (BMI), fat mass (FM), fat-free mass (FFM), waist circumference (WC) and serum leptin level. Heterogeneity between studies was assessed using Cochran’s Q test and quantified using the I2 statistic. From a pool of 3212 studies initially identified, 20 studies with a total sample size of 2158 subjects were included in the analysis. Results of the pooled analysis showed that NNSs consumption had a significant reducing effect on BW (WMD: −1.02, 95% CI: −1.57, −0.46 Kg), FM (WMD: −1.09, 95% CI: −1.90, −0.29), and FFM (WMD: −0.83, 95% CI: −1.42, −0.23), but did not have any significant effect on BMI (WMD: −0.16, 95% CI: −0.35, 0.02), WC (WMD: −1.03, 95% CI: −2.77, 0.72), or serum leptin level (WMD: −2.17, 95% CI: −4.98, 0.65). The findings of this study indicate that the consumption of artificial- and stevia-based sweeteners may lead to a reduction in body weight, fat mass, and free fat mass.
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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 | 0.033 | 0.076 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.028 | 0.051 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.003 |
| 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".