Assessing dietary intake in a population undergoing a rapid transition in diet and lifestyle: the Arctic Inuit in Nunavut, Canada
Bibliographic record
Abstract
The aims of the present study were to (1) characterise the diets of adult Inuit; (2) highlight foods for a nutritional and lifestyle intervention programme; (3) develop a quantitative FFQ (QFFQ) to evaluate the programme and monitor changes in dietary intake in this population over time. A dietary survey using single 24-h dietary recalls was conducted among Inuit aged between 19 and 87 years in two communities in Nunavut, Canada. Eighty-seven subjects completed the recalls (response rate was approximately 73 %). The mean energy intake for men and women was 9530 and 6939 kJ, respectively. The intakes of dietary fibre and the majority of vitamins and minerals (especially vitamins A, D, and E, total folate and Ca) were far below the recommendations. Traditional foods contributed 40 and 42 %, respectively, to protein and Fe intakes. Non-nutrient-dense store-bought foods were consumed much more frequently than the nutrient-dense traditional foods. Foods high in fat and sugar were highlighted, and will be replaced by healthier, more nutrient-dense alternatives to address the dietary inadequacies for the nutritional intervention programme. A 154-item QFFQ was developed and pilot tested in the Arctic Inuit. The present study highlighted foods to be targeted for a nutritional and lifestyle intervention programme not previously undertaken in this population. This QFFQ is culturally appropriate and specific for evaluating the effectiveness of the programme, as well as monitoring nutritional transition 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 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".