Bone Architecture and Strength in the Growing Skeleton: The Role of Sedentary Time
Bibliographic record
Abstract
PURPOSE: Today's youths spend close to 60% of their waking hours in sedentary activities; however, we know little about the potentially deleterious effects of sedentary time on bone health during this key period of growth and development. Thus, our objective was to determine whether sedentary time is associated with bone architecture, mineral density, and strength in children, adolescents, and young adults. METHODS: We used high-resolution peripheral quantitative computed tomography (Scanco Medical) to measure bone architecture (trabecular and cortical microstructure and bone macrostructure) and cortical and total bone mineral density (BMD) at the distal tibia (8% site) in 154 males and 174 females (9-20 yr) who were participants in the University of British Columbia Healthy Bones III study. We applied finite element analysis to high-resolution peripheral quantitative computed tomography scans to estimate bone strength. We assessed self-reported screen time in all participants using a questionnaire and sedentary time (volume and patterns) in a subsample of participants with valid accelerometry data (89 males and 117 females; ActiGraph GT1M). We fit sex-specific univariate multivariable regression models, controlling for muscle cross-sectional area, limb length, maturity, ethnicity, dietary calcium, and physical activity. RESULTS: We did not observe independent effect of screen time on bone architecture, BMD, or strength in either sex (P > 0.05). Likewise, when adjusted for muscle cross-sectional area, limb length, maturity, ethnicity, dietary calcium, and physical activity, accelerometry-derived volume of sedentary time and breaks in bouts of sedentary time were not a determinant of bone architecture, BMD, or strength in either sex (P > 0.05). CONCLUSIONS: Further study is warranted to determine whether the lack of association between sedentary time and bone architecture, BMD, and strength at the distal tibia is also present at other skeletal sites.
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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 | 0.001 | 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".