Heart Rate Responses During Bodyweight Exercise And Walking In Women With Or At-risk For Diabetes
Bibliographic record
Abstract
Previous studies have used high-intensity interval exercise as a strategy to improve metabolic health. However, most studies have taken place in the lab and the feasibility of home-based unsupervised intervals is not widely characterized. PURPOSE: To characterize the self-selected exercise intensity of walking compared to low-volume bodyweight interval exercise (BWI) using heart rate responses under free-living conditions in women aged 50+ with or at risk for type 2 diabetes. METHODS: 52 women (age: 60 ± 6 yr, BMI: 31 ± 7 kg/m2) with (pre)diabetes or a moderate to high Canadian Diabetes Risk score (≥21 points) participated remotely across Ontario, Canada. In a randomized and counterbalanced order, participants performed a video-based 8 x 1-min BWI protocol (1-min rest, 15 min total) or a 30-min walk (WALK) 30 min following dinner on two separate days. Both exercise sessions were completed under free-living conditions without supervision. Participants were instructed to walk at a moderate pace for WALK and complete as many repetitions as possible during the BWI exercise intervals. A wrist worn physical activity monitor was used to measure HR during exercise. Exercise intensity in each session was characterized by percentage of heart rate reserve (%HRR). Mean and peak %HRR were calculated for BWI and WALK. Participants were stratified into two groups based on whether a higher mean %HRR was achieved in BWI or WALK. Between group differences in medical diagnoses that may present as a barrier to performing exercise (arthritis, osteoporosis, joint replacement, metabolic disease status) were examined. RESULTS: All sessions were completed without adverse events. Mean %HRR (59 ± 13 vs. 54 ± 11, p = 0.017) and peak %HRR (88 ± 14 vs. 75 ± 16, p = <0.0001) were higher in BWI vs. WALK. Participants whose self-selected intensity was lower in BWI vs WALK (n = 16, 30.8%) had a higher combined prevalence of arthritis, osteoporosis or joint replacement compared to participants who performed BWI at a higher exercise intensity (62.5% vs 30.4%, p = 0.005). CONCLUSIONS: Women with or at risk for diabetes can safely and effectively complete BWI at home. Arthritis, osteoporosis, and joint replacement may present a barrier to achieving a higher intensity with BWI.Supported by CCS and CIHR
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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".