Dietary adequacy and dietary quality of Inuit in the Canadian Arctic who smoke and the potential implications for chronic disease
Bibliographic record
Abstract
OBJECTIVE: To compare dietary intake and quality among adult Inuit by smoking status. DESIGN: A cross-sectional study using data from a validated quantitative FFQ. SETTING: Three isolated communities in Nunavut, Canada. SUBJECTS: Adult Inuit (n 208), aged between 19 and 79 years, from randomly selected households. RESULTS: Average energy intake did not differ between male smokers (n 22) and non-smokers (n 14; 16 235 kJ and 13 503 kJ; P = 0·18), but was higher among female smokers (n 126) compared with non-smokers (n 46; 12 704 kJ and 8552 kJ; P < 0·0001). Average daily nutrient intakes were similar among men and higher among female smokers compared with non-smokers for all nutrients (P ≤ 0·05) except n-3 fatty acids, vitamin A, vitamin D and Se. Female smokers had lower intake densities of thiamin, niacin, vitamin B6, folate, Mg, Na (P ≤ 0·05), protein, n-3 fatty acids, cholesterol, Fe (P ≤ 0·01), vitamin B12 and Se (P ≤ 0·001). Between 20 % and 50 % of male and female smokers were below the Dietary Reference Intake (DRI) for Ca, folate, Mg and vitamins A and K, and more than 50 % were below the DRI for fibre and vitamin E. The proportion of smokers below the DRI was lower for all nutrients, except fibre and folate among men. Among smokers, non-nutrient-dense foods and traditional foods contributed less to energy (-2·1 % and -2·0 %, respectively). CONCLUSIONS: Adult smokers consumed fewer nutrient-dense, traditional foods, but had increased energy intake, which likely contributed to fewer dietary inadequacies compared with non-smokers. Promoting traditional food consumption supplemented with market-bought fruits and vegetables is important to improve dietary quality, especially among smokers.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".