Food and Nutrient Intake in African American Children and Adolescents Aged 5 to 16 Years in Baltimore City
Bibliographic record
Abstract
OBJECTIVE: This study aimed to describe food and nutrient intake for low-income, urban African American children and adolescents, to highlight the need for further nutrition intervention programs and appropriate tools to address overweight and obesity. METHODS: This was a cross-sectional study using interviewer-administered single 24-hour dietary recalls. Participants were low-income African American boys and girls aged 5-16 years or their caregivers in Baltimore City. Frequency of food consumption and dietary intakes were analyzed by gender and age groups. RESULTS: Eighty-one participants were included for analysis. Mean daily energy intakes exceeded Dietary Reference Intakes (DRIs) from 10% to 71% across all gender-age groups: 2304 kcal for children aged 5-8 years; 2429 kcal and 2732 kcal for boys and girls aged 9-13 years, respectively; and 3339 kcal and 2846 kcal for boys and girls aged 14-16 years, respectively. The most frequently reported consumed foods were sweetened drinks, chips, candies, and milk across all age groups. The majority of participants (79-100%) did not meet the DRIs for dietary fiber and vitamin E across all gender-age groups. Milk accounted for 14%, 17%, and 21% of energy, fat, and protein intake, respectively, among children 5-8 years of age, while pizza was the top source of energy, fat, and protein (11%, 13%, and 18%, respectively) among 14-to 16-year-old adolescents. Sweetened drinks and sweetened juices were major sources of sugar, contributing 33% for 5-8 year olds, 29% for 9-13 year olds, and 35% for 14-16 year olds. CONCLUSIONS: Mean daily energy intake exceeded dietary recommendations across all gender-age groups. This study has provided previously unavailable information on diet and highlights foods to be targeted in nutrition intervention programs.
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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 | 0.001 | 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".