Caffeine ingestion impairs insulin sensitivity in a dose-dependent manner in both men and women
Bibliographic record
Abstract
The effects of alkaloid caffeine on insulin sensitivity have been investigated primarily in men, and with a single caffeine dose most commonly of 5-6 mg·kg(-1) of body weight (BW). It is unknown if the effects of caffeine on glucose homeostasis are sex-specific and (or) dose-dependent. This study examined whether caffeine ingestion would disrupt glucose homeostasis in a dose-dependent or threshold manner. It also examined whether sex-specific responses to caffeine exist. It was hypothesized that women would have an exaggerated response to caffeine, and that caffeine would only impair glucose metabolism once a threshold was reached. Twenty-four healthy volunteers (12 males, 12 females) participated in 4 trials, in a crossover, randomized, and double-blind fashion. They ingested caffeine (1, 3, or 5 mg·kg(-1) of BW) or placebo followed, 1 h later, by a 2-h oral glucose tolerance test. Glucose, insulin, C-peptide area under the curve (AUC), and insulin sensitivity index data were fitted to a segmented linear model to determine dose-responses. There were no differences between sexes for any endpoints. Regression slopes were significantly different from zero (p < 0.05) for glucose, insulin, and C-peptide AUCs, with thresholds being no different from zero. Increasing caffeine consumption by 1 mg·kg(-1) of BW increased insulin and C-peptide AUCs by 5.8% and 8.7%, respectively. Despite this exaggerated insulin response, glucose AUC increased by 11.2 mmol per 120 min·L(-1) for each mg·kg(-1) BW consumed. These results showed that caffeine ingestion disrupted insulin sensitivity in a dose-dependent fashion beginning at very low doses (0-1 mg·kg(-1) BW) in both healthy men and women.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".