Whole-Body Aerobic Resistance Training Circuit Improves Aerobic Fitness and Muscle Strength in Sedentary Young Females
Bibliographic record
Abstract
This study aimed to determine whether a time-effective whole-body aerobic resistance training circuit using only body weight exercises is as effective in improving aerobic and anaerobic fitness, as well as muscular strength and endurance as a traditional concurrent style training combining resistance and endurance training. Thirty-four sedentary females (20.9 ± 3.2 years; 167.6 ± 6.4 cm; 65.0 ± 15.2 kg) were assigned to either: (a) a combined resistance and aerobic exercise group (COMBINED; n = 17) or (b) a circuit-based whole-body aerobic resistance training circuit group (CIRCUIT; n = 17). Training was 3 days per week for 5 weeks. Pre- and post-training measures included a (Equation is included in full-text article.)test, anaerobic Wingate cycling test, and muscular strength and endurance tests. After training, (Equation is included in full-text article.)improved with CIRCUIT by 11% (p = 0.015), with no change for COMBINED (p = 0.375). Both relative peak power output and relative average power output improved with CIRCUIT by 5% (p = 0.027) and 3.2% (p = 0.006), respectively, and with COMBINED by 5.3% (p = 0.025) and 5.1% (p = 0.003). Chest and hamstrings 1 repetition maximum (1RM) improved with CIRCUIT by 20.6% (p = 0.011) and 8.3% (p = 0.022) and with COMBINED by 35.6% (p < 0.001) and 10.2% (p = 0.004), respectively. Only the COMBINED group improved back (11.7%; p = 0.017) and quadriceps (9.6%; p = 0.006) 1RM. The COMBINED group performed more repetitions at 60% of their pretraining 1RM for back (10.0%; p = 0.006) and hamstring (23.3%; p = 0.056) vs. CIRCUIT. Our results suggest that a circuit-based whole-body aerobic resistance training program can elicit a greater cardiorespiratory response and similar muscular strength gains with less time commitment compared with a traditional resistance training program combined with aerobic exercise.
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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 | 0.000 |
| 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".