Benefits of pedometer-measured habitual physical activity in healthy women
Bibliographic record
Abstract
This cross-sectional study aimed at (i) characterizing pedometer-determined physical activity and (ii) examining its associations with dietary intake and anthropometric and metabolic profile in healthy women. Anthropometric and metabolic profile was evaluated in 68 healthy women of reproductive age. Habitual physical activity was assessed using a pedometer for 6 consecutive days, including weekends. Participants were stratified into active and inactive according to the mean steps·day(-1) (≥6000 and <6000, respectively). Food consumption was evaluated by 24-h recall in a subsample of 35 participants. Thirty-eight women were defined as active and had significantly lower body mass index (BMI), fat percentage, waist circumference, sum of skinfold thickness, insulin, and HOMA than the sedentary group. Mean BMI was 27 kg·m(-2) (overweight) in active participants and 31 kg·m(-2) (class I obesity) in inactive participants. Active women consumed more carbohydrates (55.5% ± 9.4% vs. 46.3% ± 7.6%) and calories (2138 ± 679 vs. 1664 ± 558 kcal), and less protein (15.4% ± 4.2% vs. 19.9% ± 5.8%) and lipids (29.0% ± 7.2% vs. 33.8% ± 6.2%) than inactive individuals (p < 0.05). Fiber, cholesterol, and fatty acid intake was similar in both groups. The number of steps was lower on Sunday than on weekdays for the overall group. Using a pedometer for 3 days was sufficient to determine habitual physical activity (sensitivity: 94%; specificity 91% vs. 6 days of pedometer use). In the present study, nonstructured physical activity was associated with more adequate dietary consumption and contributed toward a healthier anthropometric and metabolic profile in young women, despite the high prevalence of overweight.
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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 | 0.002 |
| 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".