Food patterns and socioeconomic indicators of food consumption amongst Inuvialuit in the Canadian Arctic
Bibliographic record
Abstract
BACKGROUND: Inuvialuit in the Canadian Arctic have been experiencing a nutrition transition resulting in a decrease in nutrient-dense food consumption, which may, in part, explain this population's increasing chronic disease rates. Because the available literature is limited, the present study aimed to document the extent of this transition by examining current dietary patterns and socioeconomic factors affecting food group consumption. METHODS: This cross-sectional study was conducted in three Inuvialuit communities in the Northwest Territories between 2007 and 2008. A validated food frequency questionnaire determined intake frequency of fruit and vegetables (FV), traditional foods (TF) and non-nutrient-dense foods (NNDF). Socioeconomic status (SES) was assessed by questions on education, ownership of items in working condition used to create a Material Style of Life (MSL) scale and residents in household employed/on income support. Daily intake frequencies were compared by gender and age group using Wilcoxon rank sum test. SES association with food group intake was determined using logistic regression. RESULTS: The response rate was 65-85%. One hundred and seventy-five participants were female and 55 were male, aged 19-84 years [mean (SD) 44 (14)]. Mean frequencies of FV and TF consumption were 1.6 (1.5) and 1.6 (1.7) times per day, respectively. NNDF were reported 9.2 (3.0) times per day. The highest MSL score (>12) was significantly associated with higher fruit (≥0.7 times per day) and higher TF intake (≥1.1 times per day) compared with the lowest score (≤7). An intermediate MSL score (8-12) was related to higher vegetable consumption (≥0.4 times per day). CONCLUSIONS: NNDF were consumed approximately seven times more frequently than TF in the present study, indicating that the dietary transition is well underway amongst Inuvialuit. Participants with higher SES were more likely to consume nutrient-dense foods, suggesting possible cost barriers.
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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 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".