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Effects Of High-Intensity Interval Training On Cardiometabolic Risk Factors And Motivation To Exercise In Women With Abdominal Obesity

2020· article· en· W3041295904 on OpenAlexaff
Patricia Blackburn, Bruno Martel, Maxime St-Pierre, Claudie Émond, Jacques Plouffe

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsMedicineHigh-intensity interval trainingInterval trainingContinuous trainingAnthropometryAbdominal obesityObesityHeart ratePopulationPhysical therapyVO2 maxInternal medicineWaistBlood pressureEnvironmental health

Abstract

fetched live from OpenAlex

There has been recent interest in high-intensity interval training (HIIT) as an alternative to moderate-intensity continuous training (MICT) to reduce body composition, adiposity and cardiometabolic risk factors in obese patients. Despite the promising evidence supporting HIIT in this population, there is limited research targeting women with abdominal obesity. PURPOSE: The objective of this study was to compare the effects of MICT and energy-matched HIIT on cardiometabolic risk factors in women characterized by abdominal obesity. METHODS: Twenty abdominally obese women (age range, 28-56 years) were submitted to 12 weeks of intervention and were randomly allocated into 2 groups: MICT (n=10) and HIIT (n=10). The MICT group performed a 38 to 62-minute continuous exercise at 70 % of the maximal heart rate. The HIIT group training performed 3 to 6 sets of 4-minute bouts at a running velocity corresponding to 90 % maximal heart rate, interspersed by a 4-min active recovery period at 50 % maximal heart rate. Anthropometric parameters, maximal oxygen uptake (VO2max) and cardiometabolic risk variables were measured at the beginning and after 12 weeks. Self-determined motivation toward physical activity was also evaluated with a validated questionnaire. RESULTS: MICT intervention led to significant improvements in VO2max (29.9 to 32.7 ml O2*kg-1*min-1, p=0.005), with no change in HIIT group. However, at the beginning of the study, VO2max was significantly lower in the MICT group when compared to the HIIT group (p=0.04). During the intervention, no significant difference was found in cardiometabolic risk factors in the MICT group. However, HIIT resulted in statistically significant reduction in triglycerides levels (1.91 to 1.58 mmol/l, p=0,046) even though waist circumference was significantly increased (98.0 to 100.7 cm, p=0.038) after the 12-week intervention program. In addition, the HIIT group increased self-determined motivation toward physical activity in a greater magnitude when compared with the MICT group (p=0.016). CONCLUSION: HIIT appears to provide greater benefits to MICT for improving triglyceride levels. In addition, as HIIT is associated with a greater improvement in self-determined motivation toward physical activity, HIIT could be associated with promising long-term adherence to exercise.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.013
GPT teacher head0.241
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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
Published2020
Admission routes1
Has abstractyes

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