Traditional food patterns are associated with better diet quality and improved dietary adequacy in <scp>A</scp>boriginal peoples in the <scp>N</scp>orthwest <scp>T</scp>erritories, <scp>C</scp>anada
Bibliographic record
Abstract
BACKGROUND: Traditionally, the Arctic diet has been derived entirely from locally harvested animal and plant species; however, in recent decades, imported foods purchased from grocery stores have become widely available. The present study aimed to examine Inuvialuit, traditional or nontraditional dietary patterns; nutrient density of the diet; dietary adequacy; and main food sources of energy and selected nutrient intakes. METHODS: This cross-sectional study used a culturally appropriate quantitative food frequency questionnaire to assess diet. Traditional and nontraditional eaters were classified as those consuming more or less than 300 g of traditional food daily. Nutrient densities per 4184 kJ (1000 kcal) were determined. Dietary adequacy was determined by comparing participants' nutrient intakes with the Dietary Reference Intakes. RESULTS: The diet of nontraditional eaters contained, on average, a lower density of protein, niacin, vitamin B12 , iron, selenium, zinc, omega-3 fatty acids (P ≤ 0.0001), vitamin B6 , potassium, thiamin, pantothenic acid (P ≤ 0.001), riboflavin and magnesium (P ≤ 0.05). Inadequate nutrient intake was more common among nontraditional eaters for calcium, folate, vitamin C, zinc, thiamin, pantothenic acid, vitamin K, magnesium, potassium and sodium. Non-nutrient-dense foods (i.e. high fat and high sugar foods) contributed to energy intake in both groups, more so among nontraditional eaters (45% versus 33%). Traditional foods accounted for 3.3% and 20.7% of total energy intake among nontraditional and traditional eaters, respectively. CONCLUSIONS: Diet quality and dietary adequacy were better among Inuvialuit who consumed more traditional foods. The promotion of traditional foods should be incorporated in dietary interventions for 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".