Patterns of multi-morbidity cluster for under five children in Tanzania

Background

Despite progress in child health interventions, anemia, malaria, and fever remain prominent public health concerns for children under five in Tanzania. Geographic variability may influence disease patterns, necessitating the identification of high-risk clusters to inform targeted interventions. This study aimed to assess the spatial clustering of these three conditions among Tanzanian under-five children using three nationally representative surveys.

Methods

A cross-sectional, survey-based design was employed using data from the 2007–08 and 2011–12 Tanzania HIV/AIDS and Malaria Indicator Surveys (THMIS) and the 2015–16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS). In total, 19,832 under-five children were included across the three surveys. Prevalences of anemia, malaria, and fever were determined, and spatial analyses were performed using STATA version 16, ArcGIS version 10.3, and SaTScan software. Moran’s I was calculated to test spatial autocorrelation, and the SaTScan Bernoulli model identified clusters with elevated risks.

Results

Overall, 5551 children from the 2007–08 THMIS, 6458 from the 2011–12 THMIS, and 7823 from the 2015–16 TDHS-MIS were analyzed. Anemia was the most prevalent condition, with rates ranging from 57.4 % to 69.7 %, followed by fever (18.6 % to 22.4 %), and malaria (9.3 % to 12.5 %). Spatial autocorrelation tests indicated non-random clustering for these conditions, with Moran’s I values ranging from 0.538 to 0.975 (p < 0.001). SaTScan analyses revealed recurrent high-risk clusters in Kigoma, Ruvuma, Lindi, and Mtwara across the three surveys. These clusters were statistically significant (p < 0.001) and highlighted persistent hotspots of childhood morbidity.

Conclusion

The study demonstrates pronounced spatial clustering of anemia, malaria, and fever among under-five children in Tanzania. Key regions including Kigoma, Ruvuma, Lindi, and Mtwara consistently emerged as hotspots. Targeted health interventions in these high-risk areas, including integrated approaches addressing multiple coexisting conditions, are critical for reducing disease burden and improving child health outcomes.