Interval training and cardiometabolic health in reproductive-aged females
Bibliographic record
Abstract
Physical activity and exercise training are especially important for reproductive-aged females as exercise-induced health benefits can also affect their infants. However, levels of physical inactivity remain high among females in this age group, before, during, and after pregnancy. There is a great need for practical and feasible exercise modes to increase adherence to exercise in this population, and interval training may be a time-efficient training modality. Interval training is a form of exercise involving intermittent bouts of intense effort interspersed with recovery periods of rest or lower-intensity exercise. A substantial amount of research indicates that interval training induces superior cardiometabolic health benefits compared with iso-energetic moderate-intensity continuous exercise. This review provides a comprehensive overview of research on interval training interventions in reproductive-aged females across various life stages, focusing on the cardiometabolic health benefits. We discuss the potential role of interval training in premenopausal females with overweight/obesity, polycystic ovary syndrome, and subfertility, as well as the potential influence of oral contraceptives on cardiometabolic adaptations to interval training. Furthermore, this review also highlights recent findings supporting the beneficial role of high-intensity interval training for cardiometabolic health outcomes during pregnancy. In summary, the existing evidence suggests that interval training can improve several cardiometabolic and reproductive outcomes in females spanning different life stages. However, more research is needed to further strengthen the evidence-base for physical activity recommendations for females in their reproductive years of life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".