Individual variations in steps per day for meeting physical activity guidelines in young adult women
Bibliographic record
Abstract
Cross-sectional studies have found a correlation between the duration or volume of moderate-to-vigorous physical activity (MVPA) and steps per day (STEP), but there is little information on why this relationship varies among individuals. No previous research has established whether STEP can be used to estimate the duration of physical activity (PA) at or above lactate threshold (≥LT), such as for maintaining cardiorespiratory fitness. This study explored the association among STEP, MVPA indices, and ≥LT under free-living conditions. Seventy young adult women measured their PA for 7 days using a validated accelerometer. The mean LT measured by an exercise test was 5.8 ± 1.0 METs. STEP, MVPA, METs×h, and ≥LT were 9324 ± 2677 steps/day, 231.9 ± 101.5 min/week, 16.6 ± 7.4 METs×h/week and 24.0 ± 22.2 min/week, respectively. Significant correlations were found between STEP and MVPA duration and between STEP and METs×h/week (r = 0.81 and r = 0.81); however, approximately 1600 steps/day of the standard error of estimates in the regression equations were found. Multiple stepwise regression analysis revealed that the percentage of total time spent at light-intensity PA (LPA) and MVPA were significant determinants of the percent deviation of STEP from the linear relationships between STEP and MVPA indices. No significant relationship was observed between ≥LT and STEP. The association between STEP and MVPA fluctuated depending on individual daily LPA and MVPA. Thus, consideration of both STEP and the PA at specific intensities are necessary to ensure the PA guidelines are met and the health benefits gained. STEP alone would be not a sufficient indicator for assessing the ≥LT.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".