Effects of Caffeine and Menstrual Phase on Performance of Female Athletes during Heat Stress
Bibliographic record
Abstract
The effects of menstrual phase on athletic performance are controversial, but commonly ascribed to temperature‐related impairments in physical and cognitive performances. Caffeine stimulates the CNS to enhance endurance performance, and while effects persist for men exercising in the heat, little work has been done with women. Moreover, many female athletes use oral contraceptive steroids (OCS) to regulate their menstrual cycles, which may pronounce the effects of caffeine. The purpose of this study was to evaluate the effects of menstrual phase and caffeine supplementation on physical and cognitive performances of women exercising in the heat. Six recreationally active female subjects (20.3 ± 1.6 yr, 1.67 ± 0.05 m, 69.3 ± 5.5 kg, 49.8 ± 3.3 ml·kg − 1 ·min − 1 ) concurrently taking monophasic OCS volunteered for this study. Each subject completed four trials: in the early follicular (EF, days 3–5) and midfollicuar (MF, days 19–21) phases of the menstrual cycle, after administration of either a placebo (P, corn starch) or caffeine (C, 5.5 mg/kg). Placebo and caffeine were administered in 355 mL “diet” cranberry drink (0 kcal), 1 hour prior to performing a self‐paced 5km time trial (TT) in the heat (29.6 ± 0.1°C, 55.8 ± 1.5 % relative humidity). Heart rate was recorded continuously and RPE was collected at 1‐km intervals. Oral temperature, Profile of Mood States (POMS) questionnaires and 2 tests of reaction and cognition (FitLight) were performed immediately prior to and following exercise. Time trial performance was improved in the EF‐C trial vs. EF‐P, ML‐C and ML‐P (1883 ± 203 vs. 1918 ± 224, 1898 ± 196, 1907 ± 205 seconds). Oral temperature tended to be elevated post‐TT in EF‐C vs. all other trials (37.4 vs. ~37.0 °C), while HR AUC tended to be decreased in the EF trials (5404 ± 167 vs. 5544 ± 181 beats, p = 0.09). The POMS Fatigue index was significantly higher post‐TT in the ML‐C trial (15.0 ± 1.9 vs 12.7 ± 0.4, 10.8 ± 1.1, ±11.2 ± 1.0). RPE and cognitive test responses were not different between trials. In heat stress, caffeine improves time trial performance in the EF phase despite an increased post‐exercise oral temperature. While heart rate response tended to be lower in the EF phase, no differences were observed in any other physical or cognitive performance measure between trials. Support or Funding Information Scotia Scholars Award, Nova Scotia Health Research Foundation This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".