Bayesian spatio-temporal modeling of childhood anemia in Tanzania: spatial distribution, determinants, and causal impact of malaria
- 1Department of Mathematics and ICT, College of Business Education
- 2College of Information and Communication Technologies, University of Dar Es Salaam (CoICT - UDSM)
- 3Dodoma Research Centre, National Institute for Medical Research
Abstract
Introduction: Childhood anemia remains a major public health challenge in low- and middle income countries, impairing growth, cognition, and child survival. In Tanzania, the burden remains persistently high, yet its spatial patterns, temporal trends, and links to infectious diseases, particularly malaria, are not well understood.
Methods: Using four rounds of the Tanzania Demographic and Health Survey (2007/08–2022) and a Bayesian spatio-temporal geostatistical framework with survey-weighted causal inference, we mapped anemia prevalence and quantified the impact of malaria through estimates of average causal effects (ACE), attributable fractions (AF), and numbers needed to treat (NNT).
Results: Anemia prevalence remained high (60.1% overall), with persistent clusters in the western, southern, and Lake Zone areas; prevalence declined from 2007/08 to 2015/16 before rising again in 2022. Malaria emerged as the strongest predictor of anemia, and its effect strengthened with child age: the odds ratio increased from 2.89 (95% CrI: 2.25–3.72) among children aged 6–23 months to 4.07 (3.53–4.71) among those aged 42–59 months. The ACE of malaria peaked at 0.266 in 2015/16, with an AF of 6.4% and the lowest NNT (3.93) recorded in the same year, indicating malaria prevention was most efficient during this period. Minimum temperature above approximately 18°C was associated with increased anemia risk, while precipitation showed no credible association once malaria status was already accounted for; anemia risk was lower at mid-range cluster altitudes (~1,000–1,600 m), consistent with reduced malaria transmission at these elevations. Lower maternal education, household poverty, larger household size, and younger maternal age were also associated with higher anemia risk.
Conclusion: These findings indicate that childhood anemia in Tanzania is driven by entrenched spatial heterogeneity and a strong, age-dependent, time-varying causal relationship with malaria, highlighting the need for geographically targeted, multisectoral strategies that integrate malaria control with broader social, economic, and environmental interventions.
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BibTeX
@article{njotto2026bayesian,
title = {{Bayesian spatio-temporal modeling of childhood anemia in Tanzania: spatial distribution, determinants, and causal impact of malaria}},
author = {Lembris Laanyuni Njotto and Wilfred Senyoni and Angelina Mageni Lutambi},
journal = {Frontiers in Public Health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1919182},
url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1919182/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Bayesian spatio-temporal modeling of childhood anemia in Tanzania: spatial distribution, determinants, and causal impact of malaria
AU - Lembris Laanyuni Njotto
AU - Wilfred Senyoni
AU - Angelina Mageni Lutambi
PY - 2026
DA - 2026/10/21
JO - Frontiers in Public Health
DO - 10.3389/fpubh.2026.1919182
UR - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1919182/full
AB - Introduction: Childhood anemia remains a major public health challenge in low- and middle income countries, impairing growth, cognition, and child survival. In Tanzania, the burden remains persistently high, yet its spatial patterns, temporal trends, and links to infectious diseases, particularly malaria, are not well understood. Methods: Using four rounds of the Tanzania Demographic and Health Survey (2007/08–2022) and a Bayesian spatio-temporal geostatistical framework with survey-weighted causal inference, we mapped anemia prevalence and quantified the impact of malaria through estimates of average causal effects (ACE), attributable fractions (AF), and numbers needed to treat (NNT). Results: Anemia prevalence remained high (60.1% overall), with persistent clusters in the western, southern, and Lake Zone areas; prevalence declined from 2007/08 to 2015/16 before rising again in 2022. Malaria emerged as the strongest predictor of anemia, and its effect strengthened with child age: the odds ratio increased from 2.89 (95% CrI: 2.25–3.72) among children aged 6–23 months to 4.07 (3.53–4.71) among those aged 42–59 months. The ACE of malaria peaked at 0.266 in 2015/16, with an AF of 6.4% and the lowest NNT (3.93) recorded in the same year, indicating malaria prevention was most efficient during this period. Minimum temperature above approximately 18°C was associated with increased anemia risk, while precipitation showed no credible association once malaria status was already accounted for; anemia risk was lower at mid-range cluster altitudes (~1,000–1,600 m), consistent with reduced malaria transmission at these elevations. Lower maternal education, household poverty, larger household size, and younger maternal age were also associated with higher anemia risk. Conclusion: These findings indicate that childhood anemia in Tanzania is driven by entrenched spatial heterogeneity and a strong, age-dependent, time-varying causal relationship with malaria, highlighting the need for geographically targeted, multisectoral strategies that integrate malaria control with broader social, economic, and environmental interventions.
SN - 2296-2565
ER -