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Record W4408106306 · doi:10.1101/2025.02.28.25323109

Prevalence and Determinants of Double and Triple Burden of Malnutrition Among School Going Children and Adolescents in Zanzibar, 2022

2025· preprint· en· W4408106306 on OpenAlexfundno aff
Esther Ngadaya, Anna Mosses, Germana Leyna, David Solomon, Hawa Msola, Fatma Ally Said, Hope Masanja, Gibson Kagaruki, Ramadhani S. Mwiru, Asha Salmin, Kahabi Isangula, Miriam Kiyungai, Kombo Mdachi Kombo, Geofrey Mchau, Joyce Ngegba, Patrick Codjia

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
FundersUniversity of Health and Allied SciencesMuhimbili University of Health and Allied SciencesNelson Mandela UniversityOntario Council on Graduate Studies, Council of Ontario UniversitiesMinisterio de Educación y Formación ProfesionalUNICEF
KeywordsMalnutritionDouble burdenEnvironmental healthPsychologyPediatricsDevelopmental psychologyMedicineInternal medicineOverweight

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.270
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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