Divergent body mass index trajectories between aboriginal and non‐aboriginal canadians 1994–2009—an exploration of age, period, and cohort effects
Bibliographic record
Abstract
OBJECTIVES: Aboriginal Canadians have a high burden of obesity and obesity-related chronic conditions. Body mass index (BMI) trajectories from 1994 to 2009 were estimated for Aboriginal and non-Aboriginal Canadians using self-reported height and weight data from the National Population Health Survey to explore age, period, and cohort effects of BMI change. METHODS: Linear growth curve models were estimated for 311 Aboriginal and 10,967 non-Aboriginal respondents divided into five birth cohorts born in the 1940s, 50s, 60s, 70s, and 80s. RESULTS: Overall, Aboriginal Canadians experienced higher rates of BMI increase over the 14-year period. Rate of BMI increase was specifically higher for Aboriginal adults born in the 1960s and 1970s when compared with non-Aboriginal adults. At ages 25, 35, and 45, recent-born cohorts had consistently higher BMIs compared with earlier-born cohorts with magnitudes of differences typically larger in the Aboriginal population. Recent-born cohorts also exhibited steeper BMI trajectories. CONCLUSIONS: Cohort effects may be responsible for the divergent BMI trajectories between Aboriginal and non-Aboriginal Canadians born in the 1960s and 1970s. Aboriginal Canadians, particularly of more recent-born cohorts, experienced faster increases in BMI from 1994 to 2009 than non-Aboriginal Canadians, suggesting that prevalence of obesity will continue to rise in this population without intervention.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".