Prevalence and Determinants of Double and Triple Burden of Malnutrition Among School Going Children and Adolescents in Zanzibar, 2022
Bibliographic record
Abstract
ABSTRACT Background Malnutrition stands as a profound global health concern, and its dimensions are evolving. In Zanzibar, the burden of malnutrition especially among school going children is not well unknown, as such, this study was conducted to assess the prevalence and factors associated with double and triple burden of malnutrition among school going children and adolescents in Zanzibar. Methods This was a School-based cross-sectional study involving mainly quantitative data collection method. Data was collected as part of the National School Health and Nutrition Survey of 2022, which included primary and secondary school children and adolescents aged 5-19 years, from Zanzibar. Anthropometric measurements and hemoglobin levels of selected students were collected. A multinomial regression model was used to assess factors associated with double burden of malnutrition (DBM) and the triple burden of malnutrition (TBM). Z-scores for weight, height and body mass index for the scholars aged 5-19 years were generated using WHO AnthroPlus and data analysis was done using Stata Version 17. Results A total of 2556 primary and secondary school children were enrolled, 51.7% (n= 1,322) were girls. Almost 2 in 5 were individuals with 10-14 years, and most of them were from primary schools. Slightly over 5 in 10 were residing in urban areas. Overall, the prevalence of malnutrition defined as malnutrition of any kind (stunting or underweight/thinness or overweight or anemia) in Zanzibar was 58.4 per cent. The overall prevalence of DBM defined by the coexistence of both undernutrition and over-malnutrition in Zanzibar was 12.0 per cent. Similarly, the overall prevalence of TBM defined as the coexistence of undernutrition, anemia, and overnutrition in Zanzibar was 1.8%. In an adjusted multinomial regression model, the prevalence of DBM was 30% lower if the child was 5 to 9 years 0.7 (95% CI, 0.5–0.9), p = 0.02), and 1.5-fold greater if the student was living in a lowest wealth quantile family (1.5(95%CI, 1.01-2.3), p=0.04). In the contrary, the prevalence of single malnutrition was 1.4-fold greater if the student was a girl (1.4(95%CI,1.2-1.6); p=0.001). Proportion of students with TBM was 2.0-fold greater if there were no school deworming education (2.0(95%CI, 1.0-3.9); p=0.05 Conclusion Over half of the students in Zanzibar are malnourished, with a significant burden of DBM, indicating the need for stringent actions to reduce the prevalence of malnutrition in the country.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".