Prevalence and predictors of undernutrition among underfive children in Arusha District, Tanzania
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Childhood undernutrition is a global health challenge impacting child growth and survival rates. This deficit in nutritional status contributes to the increasing chronic disease prevalence and economic burden in individuals and throughout developing contexts. A community‐based cross‐sectional study was conducted in Arusha District of Tanzania to determine the prevalence and predictors of undernutrition in 436 children. A structured questionnaire was used to collect data on demographic and socio‐economic factors as well as feeding practices and prevalence of preventable childhood diseases. Anthropometric data were collected through the measurement of length/height and weight of all children. The prevalence of undernutrition was estimated based on Z ‐scores indices below −2 SD of the reference population for weight for age (underweight), height for age (stunting), and weight for height (wasting). Fifty percent, 28%, and 16.5% of the children were stunted, underweight, and wasted, respectively. The age above 2 years and being a male were associated with stunting. The age above 2 years, nonexclusive breastfeeding children, and living at Seliani and Oturumeti were associated with being underweight. Similarly, morbidity, none exclusively breastfed children, living at Oturumeti, and being born to a mother 35 years and above were associated with wasting. In this study, we found the prevalence of child undernutrition in Arusha District is high in comparison with national and regional trends and appears to be associated with being a male. It is recommended that nutritionists and health planners should focus on these key predictors when planning nutrition interventions to address the problem of undernutrition among underfive children in Arusha District.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it