Nutritional Status of Orphaned and Separated Children and Adolescents Living in Community and Institutional Environments in Uasin Gishu County, Kenya
Bibliographic record
Abstract
Objective To describe the nutritional status of orphaned and separated children and adolescents (OSCA) living in households in the community (HH), on the street, and those in institutional environments in western Kenya. Methods The study enrolled OSCA from 300 randomly selected households (HH), 19 Charitable Children's Institutions (CCIs), and 100 street-involved children. Measures of malnutrition were standardized with Z-scores using World Health Organization criteria; Z-scores ≤-2 standard deviations (sd) were moderate-severe malnutrition. Data were analyzed using multivariable logistic regression adjusting for child age, sex, HIV status, whether the child had been hospitalized in the previous year, time living with current guardian, and intra-household clustering for adequacy of diet and moderate-severe malnutrition. Results Included are data from 2862 participants (1337 in CCI's, 1425 in HH's, and 100 street youth). The population was 46% female with median age at enrolment of 11.1 years. Only 4.4% of households and institutions reported household food security; 93% of children in HH reported an adequate diet vs. 95% in CCI's and 99% among street youth. After adjustment, OSCA in HH were less likely to have an adequate diet compared to those in CCI's (AOR 0.4, 95% CI 0.2–1.0). After adjustment, there were no differences between the categories of children on weight-for-age, weight-for-height, or BMI-for-age. Children living in HH (AOR 2.6, 95% CI: 2.0–3.4) and street youth (AOR: 5.9, 95% CI: 3.6–9.5) were more likely than children in CCI's to be low height-for-age. Conclusion OSCA in HH are less likely to have an adequate diet compared to children in CCI's. They and street children are more likely to be moderately-severely low height-for-age compared to children in CCI's, suggesting chronic malnutrition among them.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".