Geospatial distribution and multilevel determinants of inadequate minimum dietary diversity and its consequences for children aged 6-23 months in Sub-Saharan Africa

Abstract

Background: Inadequate minimum dietary diversity (MMD) is the leading cause of malnutrition among young children in Sub-Saharan Africa (SSA). The evidence of geospatial distribution and multilevel determinants of inadequate MDD and its consequence among children is important for the Sustainable Development Goal (SDG0) 2030 agenda. Therefore, this study aimed to determine the geospatial distribution and multilevel determinants of inadequate MDD and its consequences among children in SSA.

Method: The study utilized recent Demographic and Health Surveys data including 57,912 children. Spatial and multilevel analyses were employed, and variables significantly associated with inadequate MDD and undernutrition with MDD consumption were assessed and significance was declared using a p-value threshold of <0.05. Adjusted odds ratio (AOR) with 95% confidence interval (CI) was reported.

Results: The prevalence of inadequate MDD was 80.3% with distinct spatial variation. Spatial distribution showed that; Gabon, Cameron, Ethiopia, Democratic Republic of Congo, Chad, Mali, Burkina Faso, Ivory Coast, Liberia, and Senegal had a very high burden of inadequate MDD. Factors like children's age, maternal age, educational status, antenatal care (ANC)/ postnatal care (PNC) visits, no media exposure, wealth status, maternal stunting and wasting, and distance from health facilities were associated with inadequate MDD in SSA. The risk of anemia, stunting, and wasting were significantly associated with inadequate MDD among children in SSA.

Conclusion: The prevalence of inadequate MDD in SSA is high. Spatial distribution revealed that inadequate MDD was prevalent in most areas of the Western, Northern, Eastern, and Central parts of SSA. Maternal and children's age, educational status, ANC/ PNC visits, no media exposure, wealth status, maternal stunting and wasting, and distance from health facilities were determinants of inadequate MDD in SSA. The spatial clustering of inadequate MDD in certain regions of SSA, suggests the need for geographically targeted interventions to address the determinants of inadequate MDD in these high-burden areas. The study revealed strategies should focus on promoting frequent ANC/ PNC visits, improving maternal nutrition, reducing poverty, and improving maternal employment status to reduce inadequate MDD among children. This study highlights a significant association between MDD and anemia, stunting, and wasting in children aged 6--23 months. To address these critical issues, it is essential to improve MDD among children, as this intervention can play a vital role in achieving SDG target 2.2, which aims to end all forms of malnutrition by 2030.

Fig 1. The relationship of MDD consumption among children 6–23 months and GDP per capita in countries of SSA.

Fig 2. The spatial distribution of inadequate MDD among children 6–23 months in each region (admin 1) of SSA countries.

Fig 3. The spatial hot spot analysis of inadequate Minimum Dietary Diversity (MDD) among children aged 6–23 months in Sub-Saharan Africa (SSA).

Each polygon on the map corresponds to a single administrative region or province within SSA. The color scheme indicates the level of MDD inadequacy: High (Red): represents areas with a high rate of inadequate MDD, forming hot spots. Low (Blue): indicates regions with a low rate of inadequate MDD, forming cold spots.

Fig 4. The interpolation of inadequate MDD among children 6–23 months in SSA.

The interpolated continuous images were made in inadequate MDD using standard ordinary kriging interpolation. The transition from bold blue to bold red reflects an increase in the burden of inadequate MDD.

Fig 5. The spatial scan statistics analysis of inadequate Minimum Dietary Diversity (MDD) among children aged 6–23 months in Sub-Saharan Africa (SSA) using the Poisson model.

The analysis identified red circular windows that represent hotspot areas with high rates of inadequate MDD Cl: Cluster number corresponding to the circular window on the map. O: Observed cases of inadequate MDD, E: Expected cases of inadequate MDD, RR: Relative risk, Pre: Prevalence, P: p-value abbreviations were used.

Fig 6. Logistic regression analysis of the consequences of inadequate MDD among children aged 6–23 months in SSA.