Impact of vitamin D supplementation on insulin resistance and glycemic outcomes in adults with prediabetes: a systematic review
Bibliographic record
Abstract
Prediabetes affects hundreds of millions worldwide and represents a key opportunity for diabetes prevention. Vitamin D has biologic plausibility to modify glucose homeostasis, but trial results are heterogeneous. This systematic review was conducted in accordance with PRISMA 2020 guidelines. A comprehensive search of PubMed/MEDLINE, Embase, Web of Science, Cochrane CENTRAL, Google Scholar, and ScienceDirect was performed from database inception to 2024. Eligible studies included randomized controlled trials, prospective and retrospective cohort studies, and observational studies assessing the effects of vitamin D supplementation on insulin resistance or glycemic outcomes in adults with prediabetes. Outcomes of interest were fasting plasma glucose, HbA1c, 2-hour OGTT glucose, fasting insulin, HOMA-IR, clamp-derived insulin sensitivity, and progression to diabetes. Risk of bias was assessed using the MINORS, Newcastle–Ottawa, and Cochrane tools as appropriate. Vitamin D supplementation was consistently associated with improvements in serum 25(OH)D concentrations, but its effects on glycemic and insulin resistance outcomes were heterogeneous. Several trials reported modest reductions in fasting glucose, fasting insulin, and HOMA-IR, while others found no significant changes in insulin sensitivity, secretion, or long-term glycemic markers such as HbA1c. Observational data suggested potential protective associations between higher vitamin D levels and reduced risk of adverse glycemic trajectories, though these were often attenuated after adjustment for confounding factors. Vitamin D supplementation might improve insulin resistance in selected vitamin D–D-deficient prediabetic cohorts, but inconsistent randomized evidence and methodological heterogeneity limited broad recommendations. Larger, stratified RCTs with longer follow-up are needed. Standardized outcome definitions and follow-up clarify efficacy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".