Abstract
Globally, mothers are increasingly combining breastfeeding with formula milk, fresh animal milk, or powdered milk in different proportions in the world including Ethiopia. However, the spatial evidence of mixed milk feeding practice (MMFP) and its spatial predictors among mothers with 0–6 months of children is limited in Ethiopia. Hence, this study aimed to map MMFP and its spatial predictors among mothers with children aged 0–6 months in Ethiopia. A secondary data analysis was carried out using a weighted sample of 550 mothers with children aged 0–6 months. Spatial analysis techniques were employed to identify geographic hotspots and predictors of mixed milk feeding practices (MMFP) among mothers of children aged 0–6 months in Ethiopia. Statistical significance was determined at a p-value < 0.05, and the geographic weighted regression coefficients were reported. The spatial autocorrelation analysis, with a global Moran’s I value of 0.41 and a p-value < 0.001, revealed a significant clustering of MMFP in Ethiopia. Spatial hotspot analysis revealed clusters of MMFP in regions such as Addis Ababa, Dire Dawa, Amhara, Afar, Oromia, and Somali. Interpolated MMFP prevalence was observed to be high in Somalia, Afar, Addis Ababa, and Dire Dawa. Geographically weighted regression analysis indicated that higher maternal education, female-headed households, urban residence, community-level maternal literacy, wealthier households, multiple births, and child age (4–6 months) were associated with an increased likelihood of MMFP. In contrast, antenatal care (ANC) visits were associated with a reduced likelihood of MMFP with distinct geographically dependent relationships in specific regions of Ethiopia. The spatial hotspot revealed that MMFP clustered in Ethiopia specifically in urban areas of Somali, Addis Ababa, Afar, Amara, Diredawa, and Oromo regions. The geographically weighted regression analysis revealed that the educational status of mothers, female household heads, urban residents, community-level maternal literacy, rich households, multiple births, and children aged 4–6 months increases the likelihood of MMFP in Ethiopia. However, ANC visits reduce the likelihood of MMFP with distinct geographic dependent relationships in a specific region of Ethiopia. The study highlights the need to tailor region/space-specific intervention based on these geographically identified predictors in specific regions.
figure 1
Sampling procedure and sample size determination process from the 2019 Mini-EDHS.
Fig. 2
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Mapping of the spatial distribution, autocorrelation, and hotspot of mixed milk feeding practice in Ethiopia. (A) is spatial distribution (B) spatial autocorrelation (C) Spatial hotspot. Source: Shapefile from CSA, Ethiopia 2013; URL:https://africaopendata.org/dataset/ethiopia-shapefiles.This figure was created by the authors in Arch GIS software (Arch GIS version 10.7.1). Available at https://support.esri.com/en-us/patches-updates/2020/arcgis-desktop-engine-server-10-7-1-spatial-analyst-com-7828
Fig. 3
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The spatial interpolation and SaTscan analysis of mixed milk feeding practice in Ethiopia using 2019 Mini EDHS. (A) Spatial interpolation (B) Spatial SaTscan analysis. Key: SNNP: Southern Nation Nationality and People. Source: Shapefile from CSA, Ethiopia 2013; URL:https://africaopendata.org/dataset/ethiopia-shapefiles This figure was created by the authors in Arch GIS software (Arch GIS version 10.7.1). Available at https://support.esri.com/en-us/patches-updates/2020/arcgis-desktop-engine-server-10-7-1-spatial-analyst-com-7828 and Sat scan analysis figure was created by the authors in SaTScan statistical software (SaTScan version 9.6 statistical software). Available at https://satscan.software.informer.com/9.6/#google_vignette
Fig. 4
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Mapping of the geographic weighted regression analysis for spatial relationships of maternal higher educational status and household wealth index with mixed milk feeding practice in Ethiopia using 2019 Mini EDHS. (A) Geographic weighted regression analysis of maternal higher education status with mixed milk feeding (B) Geographic weighted regression analysis of richest household wealth index with mixed milk feeding. Key: GWR: Geographically weighted regression, SNNP: Southern Nation Nationality and People. Source: Shapefile from CSA, Ethiopia 2013; URL:https://africaopendata.org/dataset/ethiopia-shapefiles.This figure was created by the authors in Arch GIS software (Arch GIS version 10.7.1). Available at https://support.esri.com/en-us/patches-updates/2020/arcgis-desktop-engine-server-10-7-1-spatial-analyst-com-7828.
Fig. 5
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Mapping of the geographic weighted regression analysis for spatial relationships of the place of residence and ANC visit with mixed milk feeding practice in Ethiopia using 2019 Mini EDHS. (A) Geographic weighted regression analysis of place of residence with mixed milk feeding (B) Geographic weighted regression analysis of ANC visit with mixed milk feeding. Key: SNNP: Southern Nation Nationality and People. Source: Shapefile from CSA, Ethiopia 2013; URL:https://africaopendata.org/dataset/ethiopia-shapefiles. This figure was created by the authors in Arch GIS software (Arch GIS version 10.7.1). Available at https://support.esri.com/en-us/patches-updates/2020/arcgis-desktop-engine-server-10-7-1-spatial-analyst-com-7828
Fig. 6
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Mapping of the geographic weighted regression analysis for spatial relationships of female households and community-level maternal literacy with mixed milk feeding practice in Ethiopia using 2019 Mini EDHS. (A) Geographic weighted regression analysis of female household head with mixed milk feeding (B) Geographic weighted regression analysis of community-level maternal literacy with mixed milk feeding. Key: SNNP: Southern Nation Nationality and People. Source: Shapefile from CSA, Ethiopia 2013; URL:https://africaopendata.org/dataset/ethiopia-shapefiles. This figure was created by the authors in Arch GIS software (Arch GIS version 10.7.1). Available at https://support.esri.com/en-us/patches-updates/2020/arcgis-desktop-engine-server-10-7-1-spatial-analyst-com-7828.
Fig. 7
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Mapping the geographic weighted regression analysis for spatial relationships of home delivery and multiple births with mixed milk feeding practice in Ethiopia using 2019 Mini EDHS. (A) Geographic weighted regression analysis of home delivery with mixed milk feeding (B) Geographic weighted regression analysis of multiple (twine birth) with mixed milk feeding. Key: SNNP: Southern Nation Nationality and People. Source: Shapefile from CSA, Ethiopia 2013; URL: https://africaopendata.org/dataset/ethiopia-shapefiles. This figure was created by the authors in Arch GIS software (Arch GIS version 10.7.1). Available at https://support.esri.com/en-us/patches-updates/2020/arcgis-desktop-engine-server-10-7-1-spatial-analyst-com-7828
Fig. 8
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Mapping of the geographic weighted regression analysis for spatial relationships of children’s age and mixed milk feeding practice in Ethiopia using 2019 Mini EDHS. Key: SNNP: Southern Nation Nationality and People. Source: Shapefile from CSA, Ethiopia 2013; URL: https://africaopendata.org/dataset/ethiopia-shapefiles.This figure was created by the authors in Arch GIS software (Arch GIS version 10.7.1). Available at https://support.esri.com/en-us/patches-updates/2020/arcgis-desktop-engine-server-10-7-1-spatial-analyst-com-7828.