Daily Step Target to Measure Adherence to Physical Activity Guidelines in Children
Bibliographic record
Abstract
PURPOSE: There is a lack of robust evidence to support a daily step count target that equates to current physical activity guidelines in children and youth. This information would be useful to researchers and practitioners who are using pedometers to monitor physical activity. METHODS: Accelerometer and pedometer data collected on children and youth age 6-19 yr in the Canadian Health Measures Survey were used in this analysis (n = 1613). Correlation analyses of daily step counts and minutes of moderate-to-vigorous physical activity (MVPA) by age and sex were completed. The daily step count equivalent to 60 min of MVPA was derived using linear regression by age and sex. Cross-validation, including receiver operating curve analysis, was completed to compare the new cut points to one currently used as a proxy estimate of 60 min of daily MVPA (13,500 steps per day) as well as a range of possible step count targets between 8000 and 15,000 steps per day. RESULTS: Daily step counts were correlated with daily minutes of MVPA (r = 0.81, P < 0.0001). The step count equivalents to 60 min of MVPA ranged between 11,290 and 12,512 steps per day (R range = 0.59-0.74). A step count target of 12,000 steps per day resulted in closer population estimates of meeting the physical activity guideline (as measured as minutes of MVPA by accelerometer) as well as improved balance between sensitivity and specificity when compared with any cut point between 8000 and 15,000 steps per day, including the currently used daily step count target of 13,500 steps per day. CONCLUSIONS: We propose that 12,000 steps per day be used as a target to determine whether children and youth age 6-19 yr are meeting the current physical activity guideline of 60 min of daily MVPA.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".