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Feasibility of remotely supervised home-based high intensity interval training and effects on aerobic fitness and body composition in healthy older adults

2024· article· en· W4398165693 on OpenAlexaff
C. Casella, Stephanie Lapierre-Nguyen, Jin‐Su Kim, Chatchamarn Soonhuae, Yasemin Sakarya, Éléonor Riesco, Katherine Robinson

Bibliographic record

VenuePhysiology · 2024
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHigh-intensity interval trainingInterval trainingAerobic exerciseInterval (graph theory)Composition (language)Training (meteorology)GerontologyPhysical fitnessMedicinePhysical therapyPhysical medicine and rehabilitationPsychologyBiologyDemographyMathematicsGeography

Abstract

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Aging is associated with declines in aerobic fitness and increases in adiposity, both of which increase the risk of cardiovascular disease in older adults. High intensity interval training is an effective strategy for cardiovascular disease risk reduction; however, this promising exercise regimen may be inaccessible to older adults due to weight-bearing limitations or inability to travel to a fitness center. To address these barriers, we have developed a remotely supervised, home-based exercise intervention using high intensity interval training on an all-extremity non-weight-bearing ergometer (HIIT-ANE). The purpose of this study was to investigate the hypotheses that remotely supervised home-based HIIT-ANE would be feasible and lead to improvements in aerobic fitness and body composition in healthy older adults. Twenty sedentary older adults free of major clinical disease (66±1 yrs, mean ± SE) participated in this study. HIIT-ANE was remotely delivered at home under supervision via video conferencing (Zoom) and live heart rate monitoring (Zephyr OmniSense, Medtronic). HIIT-ANE consisted of a 10-min warm-up, 4 × 4-min intervals at 90% HR max interspersed by 3 × 3-min bouts of active recovery at 70% HR max , and a 5-min cool down and was performed on 4 days/week. Feasibility was assessed throughout the 8 weeks of HIIT-ANE. Aerobic fitness (maximal oxygen consumption) and body composition (dual-energy x-ray absorptiometry) were assessed at baseline and following an 8-week control period of normal lifestyle and an 8-week HIIT-ANE period. We found that exercise compliance to HIIT-ANE — the number of completed sessions relative to the number of scheduled sessions — was 96±1% and there were no adverse events related to the exercise intervention. Aerobic fitness increased in response to HIIT-ANE (baseline vs. post-HIIT-ANE: 23.7±1.2 vs. 27.0±1.1 ml/kg/min, P=0.001; pre- and post-HIIT-ANE: 22.5±1.2 vs. 27.0±1.1 ml/kg/min, P<0.001), but decreased following the control period (23.7±1.2 vs. 22.5±1.2 ml/kg/min, P=0.04). Body fat % (36±2 vs. 35±2%, P=0.001) and fat mass (28.4±2.0 vs. 27.0±2.0 kg, P=0.003) decreased following HIIT-ANE, but fat free mass did not significantly change ( P=0.05 for time effect; 48.5±1.7 vs. 49.3±1.7 kg). Body weight and body mass index did not change throughout the study duration ( P≥0.8 for time effect). In conclusion, remotely supervised home-based HIIT-ANE was feasible and safe and was associated with improved aerobic fitness and body composition in healthy older adults. This work was supported by the National Institute of Aging grant AG063143. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.960
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.323
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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