Spatiotemporal models with confounding effects: application on under-five mortality across four sub-Saharan African countries
BackgroundDifferent strategies have been developed to minimize under-five mortality (U5M) in sub-Saharan African (sSA) countries; however, it is still a major health concern for children in the region. Spatiotemporal modeling is important for areal data collected over time. However, when the number...
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Frontiers Media S.A.
2025-01-01
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1408680/full |
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| author | Haile Mekonnen Fenta Haile Mekonnen Fenta Ding-Geng Chen Ding-Geng Chen Temesgen T. Zewotir Najmeh Nakhaei Rad |
| author_facet | Haile Mekonnen Fenta Haile Mekonnen Fenta Ding-Geng Chen Ding-Geng Chen Temesgen T. Zewotir Najmeh Nakhaei Rad |
| author_sort | Haile Mekonnen Fenta |
| collection | DOAJ |
| description | BackgroundDifferent strategies have been developed to minimize under-five mortality (U5M) in sub-Saharan African (sSA) countries; however, it is still a major health concern for children in the region. Spatiotemporal modeling is important for areal data collected over time. However, when the number of time points and spatial areas is large and the areas are disconnected, fitting the model becomes computationally complex because of the high number of required parameters to be estimated. Therefore, the main aim of this study is to adopt a spatiotemporal dynamic model that includes the confounding effects between time, space, and their interactions with fixed covariates, with a special emphasis on U5M across disconnected sSA countries.MethodWe used nationally publicly representative Demographic and Health Survey (DHS) data for the period from 2000 to 2020. Bayesian spatiotemporal hierarchical modeling with an integrated nested Laplace approximation (INLA) program was used to model the spatiotemporal distribution of U5M among children across 37 districts located in four disconnected sSA regions: Ethiopia, Nigeria, Zimbabwe, and Ghana.ResultsA total of 170,356 under-five children from 37 districts were considered, and 15,467 died before the age of five. The relative risk of U5M in the first DHS was 2.02, which sharply decreased to 0.5 in the recent phase. The proportion of improved access to water, sanitation, clean fuel use, urbanization, and access to health facilities in the district had a significant negative association with U5M. The higher the proportion of these covariates, the lower is the prevalence of childhood mortality.ConclusionThis study revealed evidence of strong spatial, temporal, and interaction effects that influence under-five mortality risk across districts. Improving the women’s literacy index, access to improved water, the use of clean fuel, and the wealth index are associated with an improvement in the risk of mortality among under-five children across the districts. Districts in Nigeria and Ethiopia have the highest risk of U5M; hence, districts in these countries require special attention. |
| format | Article |
| id | doaj-art-430fdb7d64634a398e76ac0f3e6f86ce |
| institution | Kabale University |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Public Health |
| spelling | doaj-art-430fdb7d64634a398e76ac0f3e6f86ce2025-01-22T12:18:43ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-01-011310.3389/fpubh.2025.14086801408680Spatiotemporal models with confounding effects: application on under-five mortality across four sub-Saharan African countriesHaile Mekonnen Fenta0Haile Mekonnen Fenta1Ding-Geng Chen2Ding-Geng Chen3Temesgen T. Zewotir4Najmeh Nakhaei Rad5Department of Statistics, University of Pretoria, Pretoria, South AfricaDepartment of Statistics, Bahir Dar University, Bahir Dar, EthiopiaDepartment of Statistics, University of Pretoria, Pretoria, South AfricaCollege of Health Solutions, Arizona State University, Phoenix, AZ, United StatesSchool of Mathematics, Statistics and Computer Science, College of Agriculture Engineering and Science, University of KwaZulu-Natal, Durban, South AfricaDepartment of Statistics, University of Pretoria, Pretoria, South AfricaBackgroundDifferent strategies have been developed to minimize under-five mortality (U5M) in sub-Saharan African (sSA) countries; however, it is still a major health concern for children in the region. Spatiotemporal modeling is important for areal data collected over time. However, when the number of time points and spatial areas is large and the areas are disconnected, fitting the model becomes computationally complex because of the high number of required parameters to be estimated. Therefore, the main aim of this study is to adopt a spatiotemporal dynamic model that includes the confounding effects between time, space, and their interactions with fixed covariates, with a special emphasis on U5M across disconnected sSA countries.MethodWe used nationally publicly representative Demographic and Health Survey (DHS) data for the period from 2000 to 2020. Bayesian spatiotemporal hierarchical modeling with an integrated nested Laplace approximation (INLA) program was used to model the spatiotemporal distribution of U5M among children across 37 districts located in four disconnected sSA regions: Ethiopia, Nigeria, Zimbabwe, and Ghana.ResultsA total of 170,356 under-five children from 37 districts were considered, and 15,467 died before the age of five. The relative risk of U5M in the first DHS was 2.02, which sharply decreased to 0.5 in the recent phase. The proportion of improved access to water, sanitation, clean fuel use, urbanization, and access to health facilities in the district had a significant negative association with U5M. The higher the proportion of these covariates, the lower is the prevalence of childhood mortality.ConclusionThis study revealed evidence of strong spatial, temporal, and interaction effects that influence under-five mortality risk across districts. Improving the women’s literacy index, access to improved water, the use of clean fuel, and the wealth index are associated with an improvement in the risk of mortality among under-five children across the districts. Districts in Nigeria and Ethiopia have the highest risk of U5M; hence, districts in these countries require special attention.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1408680/fullspatial random effectsconfoundingspatiotemporal modelsspace-time interactionsvariance partitioning |
| spellingShingle | Haile Mekonnen Fenta Haile Mekonnen Fenta Ding-Geng Chen Ding-Geng Chen Temesgen T. Zewotir Najmeh Nakhaei Rad Spatiotemporal models with confounding effects: application on under-five mortality across four sub-Saharan African countries Frontiers in Public Health spatial random effects confounding spatiotemporal models space-time interactions variance partitioning |
| title | Spatiotemporal models with confounding effects: application on under-five mortality across four sub-Saharan African countries |
| title_full | Spatiotemporal models with confounding effects: application on under-five mortality across four sub-Saharan African countries |
| title_fullStr | Spatiotemporal models with confounding effects: application on under-five mortality across four sub-Saharan African countries |
| title_full_unstemmed | Spatiotemporal models with confounding effects: application on under-five mortality across four sub-Saharan African countries |
| title_short | Spatiotemporal models with confounding effects: application on under-five mortality across four sub-Saharan African countries |
| title_sort | spatiotemporal models with confounding effects application on under five mortality across four sub saharan african countries |
| topic | spatial random effects confounding spatiotemporal models space-time interactions variance partitioning |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1408680/full |
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