Effects of Honey on Metabolic Risk Factors in Healthy Adults: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Excess calories from free sugars have been implicated in the epidemics of obesity and type 2 diabetes. Honey has been lumped into the category of free sugars according to the World Health Organization but is considered a healthy alternative to sugar by many in the public. The objective of this study was to assess the effect of honey on cardiometabolic risk factors by conducting a systematic review and meta-analysis of controlled trials using GRADE. MEDLINE, Embase, and Cochrane Library were searched up to 4 January 2021 for controlled trials of ≥1 weeks’ duration assessing the effect of oral honey intake on adiposity, glycemic control, lipids, blood pressure, uric acid, inflammatory markers, and markers of non-alcoholic fatty liver disease. Trial designs were prespecified based on energy control: substitution (energy matched replacement of honey by other macronutrients); addition (excess energy from honey added to diets); subtraction (energy from honey subtracted from diets); and ad libitum (energy from honey freely replaced by other macronutrients) trials. Independent reviewers extracted data and assessed risk of bias. Data were pooled using the inverse variance method and expressed as mean differences (MDs) with 95% CIs. Certainty of evidence was assessed using the GRADE approach. (PROSPERO identifier, CRD42015023580) We included 17 controlled trials (29 trial comparisons, n = 1073) assessing the effect of honey across two energy levels, substitution and addition. Honey reduced glycated hemoglobin (mean difference (MD), −0.27%, [95% confidence interval (CI), −0.50 to −0.04%], P = 0.019), LDL cholesterol (MD, −0.34 mmol/L, [95% CI, −0.67 to −0.042 mmol/L], P = 0.040), and fasting triglycerides (MD, −0.15 mmol/L, [95% CI, −0.30 to −0.00 mmol/L], P = 0.043) in addition trials. No effects of honey were seen in substitution trials on any of the outcomes assessed. The overall certainty of the evidence was low to very low for most comparisons. The available evidence provides some indication that honey might have a benefit for glycemic control and lipid levels when consumed in a healthy dietary pattern. More high-quality randomized controlled trials are needed to improve our estimates. CIHR, Diabetes Canada, PSI, Banting & Best Diabetes Centre, Toronto 3D foundation.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.034 |
| Bibliometrics | 0.006 | 0.007 |
| 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) | 0.004 | 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".