Diet quality of Marshallese mothers of young children in Northwest Arkansas: an exploratory study
Bibliographic record
Abstract
OBJECTIVE: To characterize the dietary patterns of Marshallese mothers of young children in Northwest Arkansas, informing the cultural adaptation of nutrition education curricula. DESIGN: An exploratory cross-sectional study was conducted, in which Marshallese women with children under 12 months completed 3 telephone-administered 24-hour dietary recalls with a trained bilingual Marshallese interviewer. Diet quality was characterized using the Healthy Eating Index (HEI)-2020. A food-level analysis identified top food groupings contributing to total energy and HEI-2020 components. SETTING: Northwest Arkansas. PARTICIPANTS: Marshallese mothers with children < 12 months. RESULTS: 29 women were recruited, 20 completed 2 or 3 dietary recalls. Median age was 25·5 years. Diet quality by HEI-2020 was 46·4 (max score 100). White rice was the top contributor to total energy; high seafood/plant protein and fatty acid diet quality component scores were influenced by high fish intakes. CONCLUSIONS: Diet quality was low. Key adaptations include reducing rice portion sizes, while emphasizing lean proteins and fruits/vegetables. Cultural adaptation of nutrition education is essential to improve diet quality among communities with varying dietary practices.
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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 | 0.000 |
| 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".