Dietary Adequacy among Rural Yup’ik Women in Western Alaska
Bibliographic record
Abstract
OBJECTIVES: To assess (1) energy and nutrient intake; (2) dietary adequacy; (3) traditional and nontraditional foods consumed; and (4) main foods contributing to energy and selected nutrient intake among Yup'ik women in Western Alaska. METHODS: Up to 3 24-hour dietary recalls were collected to assess the dietary intake. Dietary adequacy was determined by comparing women's daily nutrient intakes to corresponding dietary reference intakes (DRIs). RESULTS: Mean daily energy intake for the women was 2172 kcal, exceeding the DRI for energy. The majority of women (90-100%) fell below the recommendations for dietary fiber, calcium, and vitamins D and E. More than 50% of women fell below the recommendations for vitamin A, and more than one third were below the DRI for zinc and vitamins C and B6. Juices/pop (including Tang, Kool-Aid, soda/pop, fruit juice, and energy drink), coffee, and traditional fish were the most frequently reported food items. Sweetened beverages and pop were the main contributors to energy, carbohydrate, and sugar intake. Traditional foods provided 34% of protein, 27% of iron, 23% of vitamin A, and 21% of zinc. CONCLUSIONS: Among Yup'ik women, juices/pop were the most frequently consumed foods contributing to the high energy intake. However, traditional food still contributes substantially to certain nutrients. These data contribute to an understanding of dietary adequacy in this population and will aid in the development of a nutritional intervention program.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".