Diet quality indices in relation to metabolic syndrome in an Indigenous Cree (Eeyouch) population in northern Québec, Canada
Bibliographic record
Abstract
OBJECTIVE: To assess associations between three diet quality indices and metabolic syndrome (MetS) in the Cree (Eeyouch) of northern Québec, Canada, as well as to evaluate their pertinence in this Indigenous context. DESIGN: The alternative-Healthy Eating Index 2010 (aHEI-2010), the Food Quality Score (FQS) and the contribution of ultra-processed products (UPP) to total daily dietary energy intake using the NOVA classification were calculated from 24 h food recalls. MetS was determined with the latest harmonized definition. Logistic regressions assessed the relationship between quintiles of dietary quality scores with MetS and its components. SETTING: Study sample from the 2005-2009 cross-sectional Nituuchischaayihititaau Aschii Environment-and-Health Study. SUBJECTS: Eeyouch (n 811) from seven James Bay communities (≥18 years old). RESULTS: MetS prevalence was 56·6 % with 95·4 % abdominal adiposity, 50·1 % elevated fasting plasma glucose, 43·4 % hypertension, 38·6 % elevated TAG and 44·5 % reduced HDL cholesterol. Comparing highest and lowest quintiles of scores, adjusted OR (95 % CI) of MetS was 0·70 (0·39, 1·08; P-trend=0·05) for aHEI-2010, 1·06 (0·63, 1·76; P-trend=0·87) for FQS and 1·90 (1·14, 3·17; P-trend=0·04) for the contribution of UPP to total daily dietary energy intake. CONCLUSIONS: Although diet quality indices have been associated with cardiometabolic risk, only the dietary intake of UPP was significantly associated with MetS in the Eeyouch. Indices tailored to the food environment of northern communities are essential to further understand the impact of diet quality in this context.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".