Assessment of total and central adiposity in Canadian Aboriginal children and their Caucasian peers
Bibliographic record
Abstract
OBJECTIVE: Although Aboriginal children seem to be more susceptible to developing obesity and metabolic disorders than other ethnic groups in Canada, few studies have examined adiposity comprehensively in this population. The purpose of this study was to assess total and central adiposity in Canadian Aboriginal and Caucasian children matched by age, gender and maturity. METHODS: A total of 212 Aboriginal and 204 Caucasian children (8-17 years) were recruited. Heights, weights and waist circumferences were measured and classified using international standards. Dual energy x-ray absorptiometry (DXA) indicated relative total body and trunk fatness. Age of peak height velocity was predicted from somatic growth. Descriptives with independent t-tests and Chi-square analyses were run to detect ethnic differences. ANCOVA was used to assess differences in total body and trunk fatness (covariates height, chronological age and biological age) in girls and boys separately. RESULTS: Overweight/obesity and central adiposity were more prevalent in Aboriginal children compared with Caucasian children (p < 0.05). Ethnic differences in total body and trunk fatness were also significant, with Aboriginal girls and boys presenting, on average, 5.4% and 6.0% more total body fatness and 7.6% and 8.3% more trunk fatness, than Caucasian girls and boys, respectively (p < 0.01). CONCLUSION: Canadian Aboriginal children have greater prevalence of overweight/obesity and central adiposity, and higher relative total body fatness and trunk fatness than their Caucasian peers, which may predispose them to cardiovascular and metabolic disorders at a very young age. Longitudinal research is needed to confirm the associated health risks in this population.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".