Social determinants of dietary patterns, food basket costs and expenditure on alcohol and tobacco amongst Greenland Inuit
Bibliographic record
Abstract
OBJECTIVE: Dietary transition, obesity and risky use of alcohol and tobacco are challenges to public health among indigenous peoples. The aim of the article was to explore the role of social position in dietary patterns and expenditures on food and other commodities. DESIGN: Countrywide population health survey. SETTING: Greenland. PARTICIPANTS: 2436 Inuit aged 15+ years. RESULTS: Less than half of the expenditures on commodities (43 %) were used to buy nutritious food, and the remaining to buy non-nutritious food (21 %), alcoholic beverages (18 %) and tobacco (18 %). Participants were classified according to five dietary patterns. The cost of a balanced diet and an unhealthy diet was similar, but the cost per 1000 kJ was higher and the energy consumption was lower for the balanced diet. Participants with low social position chose the unhealthy pattern more often than those with high social position (40 % v. 24 %; P < 0·0001), whereas those with high social position more often chose the balanced alternative. Participants with low social position spent less money on the total food basket than those with high social position but more on non-nutritious food, alcohol and tobacco. CONCLUSIONS: Cost seems to be less important than other mechanisms in the shaping of social dietary patterns and the use of alcohol and tobacco among the Inuit in Greenland. Rather than increasing the price of non-nutritious food or subsidising nutritious food, socially targeted interventions and public health promotion regarding food choice and prevention of excessive alcohol use and smoking are needed to change the purchase patterns.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".