Similar Postexercise Hypotension After MICT, HIIT, and SIT Exercises in Middle-Age Adults
Bibliographic record
Abstract
INTRODUCTION: Acute bouts of moderate-intensity continuous training (MICT) and high-intensity interval training (HIIT) transiently lower systolic blood pressure (SBP) and diastolic blood pressure (DBP) in the hours after termed postexercise hypotension (PEH); however, the effects of sprint interval training (SIT) exercise have yet to be explored in middle-age adults. Although previous work has found no effect of exercise intensity on PEH, no study has compared submaximal, near maximal, and supramaximal intensities, specifically in middle-age adults where blood pressure (BP) management strategies may be of greater importance. PURPOSE: This study examined the effects of MICT, HIIT, and SIT exercises on PEH in the immediate (≤2 h) and 24 h after exercise specifically in middle-age adults. METHODS: Fourteen participants (10 female; age, 46 ± 9 yr; SBP, 116 ± 11 mm Hg; DBP, 67 ± 6 mm Hg; one hypertensive, four prehypertensive, nine normotensive) had their BP measured before, immediately (15, 30, 60, 120 min), and over 24 h after four experimental sessions: 1) 30-min MICT exercise (65% maximal oxygen consumption), 2) 20-min HIIT exercise (10 × 1 min at 90% maximum heart rate with 1-min rest), 3) 16-min SIT exercise (8 × 15 s all-out sprints with 2-min rest), and 4) no-exercise control. Postexercise BP was compared with no-exercise control. RESULTS: PEH was similar for all exercise sessions for SBP ( P = 0.388, = 0.075) and DBP ( P = 0.206, = 0.108). Twenty-four-hour average SBP was similar for all sessions P = 0.453, = 0.069), and DBP was similar over 24 h except after MICT exercise compared with HIIT exercise ( P = 0.018, d = 1.04). CONCLUSIONS: In middle-age adults, MICT, HIIT, and SIT exercises are effective at reducing SBP; however, the effects on DBP are smaller, and neither reductions are sustained over 24 h.
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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 | 0.000 |
| 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".