Usual nutrient intake adequacy among young, rural Zambian children
Bibliographic record
Abstract
Inadequate nutrient intakes put children at risk for impaired growth and development. We described diet, usual intakes of energy and macro- and micronutrients and prevalence of nutrient intake adequacies among 4-8-year-old Zambian children. Children not yet in school and living in Mkushi District, Central Province, Zambia were enrolled into an efficacy trial of pro-vitamin A biofortified maize. Children in the non-intervened arm were included in this analysis (n 202). Dietary intake data were collected by tablet-based 24-h recall on a monthly basis over the 6-month trial. Observed nutrient intakes were derived from reported food quantities, standard recipes and food composition tables. Usual nutrient intake distributions were modelled based on observed intakes. Prevalence of inadequacy was estimated by comparing the usual nutrient intake distribution to the nutrient requirement distribution. Frequency and quantity of consumption of commonly reported foods were described and key sources of energy and nutrients were identified. Median usual energy intake was 6422 kJ/d (1535 kcal/d). Most childrens' macronutrient intakes fell within recommended ranges (74-98 %). Estimated prevalences of inadequate intakes of Fe, folate, vitamin B12 and Ca were 25, 57, 76 and >99 %, respectively. Estimated prevalences of inadequacy for other micronutrients were low (0·1-2·2 %). Commonly consumed foods included maize, vegetable oil, tomatoes, rape leaves and small fish (>0·6 servings/d), whereas meat, eggs or dairy were rarely eaten (<0·2 servings/d). These findings suggest that the heavily plant-based diet of rural Zambian children provides inadequate Ca, folate, vitamin B12 and Fe to meet recommended nutrient intakes.
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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 | 0.002 |
| 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".