Diet quality among Indigenous and non-Indigenous children and youth in Canada in 2004 and 2015: a repeated cross-sectional design
Bibliographic record
Abstract
OBJECTIVE: The objectives were to describe changes in diet quality between off-reserve Indigenous and non-Indigenous children and youth from 2004 to 2015 and examine the association between food security and diet quality. DESIGN: We utilised a repeated cross-sectional design using both the 2004 and 2015 nutrition-focused Canadian Community Health Surveys, including 24-h dietary recall. Diet quality was estimated according to the Healthy Eating Index (HEI). SETTING: The surveys were conducted off-reserve in Canada's ten provinces. PARTICIPANTS: Our analysis included children and youth 2-17 years old (n 18 189). Indigenous and non-Indigenous participants were matched, and using a general linear model, we tested time period and (non-)Indigenous identifiers, including their interaction effect, as predictors of HEI. RESULTS: Both Indigenous and non-Indigenous children and youth had significantly higher HEI scores in 2015 as compared to 2004. There was not a significant (non-)Indigenous and time period interaction effect, indicating the improvements in diet quality in 2015 were similar between both Indigenous and non-Indigenous populations. Improvements in diet quality are largely attributed to reductions in percentage energy from 'other' foods, though a disparity between Indigenous and non-Indigenous children and youth persisted in 2015. Overall, food security was lower among the Indigenous population and positively, and independently, associated with diet quality overall, though this relationship differed between boys and girls. CONCLUSIONS: School policies may have contributed to similar improvements in diet quality among Indigenous and non-Indigenous populations. However, an in-depth sex and gender-based analysis of the relationship between food security and diet quality is required.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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".