Bone Health in Newcomer Children Compared to Canadian-Born Children
Bibliographic record
Abstract
College of Kinesiology Research Theme: Child and Youth Health and Development Introduction: Bone health is crucial during childhood, as this period is essential for achieving optimal peak bone mass, which can reduce the risk of osteoporosis and fractures later in life. While research exists on the determinants of bone health, suggesting newcomer children may be at risk of impaired skeletal development, little is known of the bone health of newcomer children. The purpose of this study was to evaluate if there were differences in bone health between newcomer and Canadian-born children. Methods: Our cross-sectional study recruited forty-five children (12 newcomers, 33 Canadian-born) from 5 to 11 years of age. Bone health was assessed using high-resolution peripheral quantitative computed tomography (HR-pQCT) to measure total bone area (Tt.Ar), cortical area (Ct.Ar), trabecular area (Tb.Ar), total volumetric bone mineral density (Tt.vBMD), cortical density (Ct.vBMD), cortical thickness (Ct.Th), trabecular density (Tb.vBMD), trabecular thickness (Tb.Th), trabecular bone volume fraction (Tb.BV/TV), trabecular number (Tb.N), and trabecular separation (Tb.Sp) at the distal radius and tibia. Anthropometric measures were recorded, and physical activity (PA) was evaluated using the Childhood Physical Activity Questionnaire. Multivariate analysis of covariance (MANCOVA) was used to assess differences in HR-pQCT bone outcomes between groups while controlling for age, sex, height, weight, and PA. Statistical significance was set at p < 0.05. Results: Newcomer children had significantly greater Ct.Ar (p = 0.02), Ct.vBMD (p = 0.02), and Ct.Th (p = 0.01) at the distal tibia compared to their Canadian-born peers. No significant differences were observed at the radius between groups (p > 0.05). Conclusion: Contrary to previous literature, this pilot study did not find that newcomer children had impaired bone health. Instead, newcomer children demonstrated greater values for cortical bone at the distal tibia. This may be explained by our potentially healthier newcomer sample, which reported higher vitamin D intake, more educated parents, and possibly favourable premigration factors. Future research should explore the impact of refugee status, acculturation, healthcare access, PA, and diet with a larger and more ethnically diverse sample to better understand bone development of newcomer children.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".