Regular Physical Activity Increases the Systolic Blood Pressure Response to Acute Caffeine Ingestion in Nonhabitual Caffeine Consumers
Bibliographic record
Abstract
Background: Physical activity and caffeine consumption induce adaptations to the cardiovascular system, which can change basal and postcaffeine blood pressure (BP) and heart rate (HR) parameters. We hypothesized that physical activity would attenuate the pressor effects of acute caffeine ingestion regardless of caffeine consumption level. Methods: We evaluated the influence of regular physical activity and chronic caffeine consumption on basal and post-caffeine ingestion BP and HR. Sixty subjects (19–50 years old) participated in an interventional study. To evaluate the influence of regular physical activity and caffeine consumption, the participants were divided into four groups: sedentary nonhabitual caffeine consumers (S), sedentary habitual heavy caffeine consumers (SC), physically active nonhabitual caffeine consumers (A), and physically active habitual heavy caffeine consumers (AC). All groups had BP and HR assessed before (basal) and one hour after (post) caffeine ingestion (6 mg.kg−1 of body mass). Results: We found that group A had an increased systolic blood pressure (SBP) from 119.2 ± 11.3 to 124.2 ± 14.3 mmHg after acute caffeine ingestion. Lack of regular physical activity was associated with a significant increase in diastolic BP after caffeine ingestion (group S; 69.1 ± 7.7 vs. 73.8 ± 8.3 and group SC; 71.6 ± 9.5 vs. 75.3 ± 8.4). Group AC showed lower basal DBP than group SC (64.61 ± 8.1 and 71.5 ± 7.8 mmHg, respectively). Conclusion: Acute caffeine ingestion increases the SBP in physically active nonhabitual caffeine consumers.
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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 | 0.000 |
| 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) | 0.001 | 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".