BibTex format
@article{Chacky:2026:10.1186/s12889-026-27799-y,
author = {Chacky, F and Rumisha, SF and Remiji, MJ and Aaron, S and Makori, N and Molteni, F and Walker, PG and Kyatikila, WA and Mwingira, F and Wilson, B and Machafuko, P and Mpinga, AA and Moshi, G and Jumbe, T and Bundala, N and Kawishe, E and Hicks, JT and Mchau, G and Kiware, S and Leyna, G and Mchwampaka, W and Saitot, W and Kimaro, O and Silao, J and Ainan, S and Makenga, G and Mkali, H and Kc, A and Chaki, P and Ngasala, B and Nhiga, SL and Snow, RW and Van, Geertruyden J-P and Mmbando, BP},
doi = {10.1186/s12889-026-27799-y},
journal = {BMC Public Health},
title = {Trends in prevalence and predictors of anemia among school-aged children in Tanzania: analysis of 2019-2023 cross-sectional surveys using a multilevel logistic regression model.},
url = {http://dx.doi.org/10.1186/s12889-026-27799-y},
volume = {26},
year = {2026}
}
RIS format (EndNote, RefMan)
TY - JOUR
AB - BACKGROUND: Anemia constitutes a major global public health challenge among school-aged children with documented impacts on psychomotor development, academic achievement, susceptibility to infections, and long-term economic productivity. This study presents nationally representative findings on the prevalence and determinants of anemia among school children aged 5-16 years in mainland Tanzania. METHODS: Data were collected as part of the cross-sectional Tanzania School Malaria Parasitological Survey (SMPS) in 2019, 2021, and 2023. Hemoglobin concentration was assessed using the HemoCue Hb 201 + analyzer, and anemia status was classified according to the 2024 WHO thresholds. Candidate predictors associated with anemia (p < 0.2 in univariable analyses) were included in a multivariable multilevel logistic regression model to assess the contribution of predictor variables to anemia prevalence and to calculate adjusted odds ratios (AOR) and 95% confidence intervals (CI). RESULTS: The study surveyed 47,366 school-aged children from 810 schools across three survey rounds. Generally, anemia prevalence was 45.5% (mild: 18.5%, moderate: 25.4%, severe: 1.5%). On multivariable regression of anemia risk, a statistically significant interaction was observed between age and sex. While odds of anemia were similar between sexes in lower age groups (5-11 and 12-14 years), male children aged 15-16 years old had almost three times the odds of anemia compared to female children in the same age group (AOR 2.96 [95%CI 2.18-4.02]). Malaria infection significantly increased anemia odds (AOR 1.88 [95%CI 1.75-2.01]). Regional disparities were noted, with the Lake [AOR 1.77 (95%CI 1.38-2.26)] and Western [AOR 1.78 (95%CI 1.34-2.37)] zones having highest odds of anemia compared to the Central zone. Over time, anemia risk decreased, with a notable reduction in 2023 (AOR 0.75 [95%CI 0.70-0.80]) compared to reference year (2019). CONCLUSIONS: Anemia in school-aged ch
AU - Chacky,F
AU - Rumisha,SF
AU - Remiji,MJ
AU - Aaron,S
AU - Makori,N
AU - Molteni,F
AU - Walker,PG
AU - Kyatikila,WA
AU - Mwingira,F
AU - Wilson,B
AU - Machafuko,P
AU - Mpinga,AA
AU - Moshi,G
AU - Jumbe,T
AU - Bundala,N
AU - Kawishe,E
AU - Hicks,JT
AU - Mchau,G
AU - Kiware,S
AU - Leyna,G
AU - Mchwampaka,W
AU - Saitot,W
AU - Kimaro,O
AU - Silao,J
AU - Ainan,S
AU - Makenga,G
AU - Mkali,H
AU - Kc,A
AU - Chaki,P
AU - Ngasala,B
AU - Nhiga,SL
AU - Snow,RW
AU - Van,Geertruyden J-P
AU - Mmbando,BP
DO - 10.1186/s12889-026-27799-y
PY - 2026///
TI - Trends in prevalence and predictors of anemia among school-aged children in Tanzania: analysis of 2019-2023 cross-sectional surveys using a multilevel logistic regression model.
T2 - BMC Public Health
UR - http://dx.doi.org/10.1186/s12889-026-27799-y
UR - https://www.ncbi.nlm.nih.gov/pubmed/42204515
VL - 26
ER -