MétaCan
Menu
Back to cohort

Effects of a 30-Day Fitness Challenge on Body Composition and Health Markers in Sedentary Women

2011· article· en· W2808591042 on OpenAlexaboutno aff
Claire N. Canon, J Culbertson, M Byrd, C Rasmussen, Y Jung, Deepesh Khanna, M Koozehchian, M Mardock, Jonathan M. Oliver, S Simbo, Richard B. Kreider

Bibliographic record

VenueThe Journal of Strength and Conditioning Research · 2011
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsBioelectrical impedance analysisMedicineCircuit trainingPhysical therapyHeart rateWaistPopulationPhysical fitnessAnthropometryResistance trainingBody mass indexGerontologyBlood pressureInternal medicine

Abstract

fetched live from OpenAlex

Numerous studies have documented the value of exercise in controlled clinical trials. However, few large scale studies have evaluated the effects of initiation of resistance-training programs. PURPOSE: To evaluate the impact of a 30-day international fitness intervention on fitness and health behaviors in a large-scale population. METHODS: 72,870 sedentary women (44.0 ± 13 yrs, 83.3 ± 19.7 kg, 31.9 ± 7 kg/m2 BMI, 37.9 ± 7% fat) responding to advertisements for a 30-day fitness challenge at Curves® clubs in the United States and Canada volunteered to participate in this study. Subjects gave online consent and then completed exercise, food frequency, and physical activity-related questionnaires. In addition, baseline body composition, obtained using a handheld bioelectrical impedance analyzer (BIA), blood pressure, and circumference measurements were taken by trained personnel. Participants followed the Curves 30-min circuit training program 3 d/wk. Each circuit-style workout consisted of 14 hydraulic resistance-exercises that targeted opposing muscle groups in a concentric-only fashion. Subjects performed the resistance-exercise for 30-sec followed by performing floor-based callisthenic (e.g. walking/skipping in place, arm circles, etc.) exercises for a 30-sec time period in an effort to maintain heart rate between 60% and 85% of age-predicted maximum heart rate. Participants were also encouraged to walk on non-training days and make positive changes in their diet. After 4-wks, subjects repeated questionnaires and had post-measurements recorded. Data were analyzed by dependent T-tests and are presented as mean ± SD changes from baseline. RESULTS: Post-study results were obtained on 34,677 participants. Participants experienced significant (p < 0.05) decreases in body weight (−0.86 ± 2.2 kg, −1.1%; n = 34,667), percent fat (−0.7 ± 2.5%, −1.9%; n = 34,349), total centimeters (−7.62 ± 17.78 cm, −1.5%; n = 33,899), BMI (−0.47 ± 2.7 kg/m2, −1.5%; n = 12,167), systolic BP (−2.6 ± 12.5 mm Hg, −2.1%; n = 11,767), and diastolic BP (−2.3 ± 9.0 mm Hg, −2.9%; n = 11,711), as well as an increase in fat-free weight (0.05kg ± 2.4 kg, 0.1%; n = 34,312). Participants also reported significantly less (p<0.05) weekly (−10%) and monthly (−17%) alcohol consumption, sugar intake (−24%), and fat intake (−22%) with greater calcium intake (5.3%), and fiber intake (6.8%). CONCLUSIONS: Significant improvements in body composition, markers of health, and positive health behaviors can be achieved through short-term circuit training fitness initiatives. PRACTICAL APPLICATIONS: Short-term circuit-training programs can be effectively used to promote positive changes in fitness and attitudes about health. ACKNOWLEDGMENTS: This study was supported by Curves International, Waco TX and Avon Inc., New York NY.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.064
GPT teacher head0.376
Teacher spread0.312 · 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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Strength and Conditioning ResearchSame topicPhysical Activity and HealthFrench-language works237,207