The spatial epidemiology of inadequate MDD
The majority of children (four out of every five children) did not meet the adequate MDD criteria. A minimum of three out of every five children and a maximum of nine out of every 10 children have inadequate MDD. All SSA countries had inadequate MDD coverage. South Africa and Kenya had better child feeding practices than others, with 34.9%(28%-36.6%)and 36.3%(34.6%-38.3%) of their children receiving adequate MDD, respectively.The three countries with the highest prevalence of inadequate MDD were Brukina Faso(95.2%), Ivory Coast(92.1%), and Nigeria(91.8%) (Table 1). Burkina Faso, Ivory Coast, Ethiopia, Gambia, Liberia, Lesotho, Niger, and Chad were among the eight countries where less than 15% of children were receiving adequate MDD. In the remaining 23 countries, between 15–29% of children had adequate MDD. More than half of children in each country consumed grains, roots, and tubers, as well as breast milk (except Gabon and South Africa). Almost all countries have low feeding habits for legumes and nuts, eggs, and other fruits and vegetables compared to other food groups (Table 1).
Angolan children received adequate MDD in 29.1%, 80% consumed breast milks, 76% consumed grains, roots, and tubers, 22% consumed legumes and nuts, 26% consumed dairy products, 38% consumed flesh foods, 14% consumed eggs, 48% consumed vitamin—A rich fruits and vegetables, and 20% consumed other fruits and vegetables. The amazing one is that 97% of Burundi children, 96% of Rwanda children, 95% of Burkina Faso and Niger children did not consume eggs; further, 96% of Ivory Coast children and 97% of Guinian children did not take legumes and nuts (Table 1).
Table 1 Proportion of children meeting the minimum dietary diversity and food groups consumed
As showen from the table above the percentage of children who met adequate MDD color indicates, green 60%, bright green 45% to 59% , yellow 30% to 44% , red 15% to 29%, and dark red less than 15% of children met adequate MDD.
Spatial epidemiology of the consumetion of number of food groups: Only 0.94%, 13.4%, 20.8%, 25.26%, 19.5%, 11%, 5.6%, 2.6%, and 1.1% of children took food from the zero to eight food groups, respectively. Children in SSA took a maximum of two, three, or four food groups, respectively, in 34.94%, 60.2%, and 79.9% of their children (Figure 1).
When the changes in meeting adequate MDD from the most recent two rounds of the DHS were examined, it was discovered that meeting adequate MDD increased in 17 of the 21 countries while decreasing in the remaining four. Ghana, Sierra Leone, Guinea, and Tanzania made the most progress, increasing 10% and more, despite being the fastest growing countries, but only made minor progress in terms of child adequate MDD coverage (Figure 1).
Spatial epidemiology of adequate MDD by residence and age: Except for Benin and Mozambique (a few proportion more in rural), children in urban areas had a higher proportion of meeting adequate MDD. In SSA, 28% (27%,29%) of urban children and 17% (16%,17%) of rural children had adequate MDD.
Children from urban area of Kenya, Rwanda, and Malawi had the highest percentages of children receiving adequate MDD, accounting for 50%, 44%, and 41%, respectively. In comparison, only 9% of children in Burkina Faso, 14% in Liberia, and 15% in Ivory Coast had adequate MDD, the lowest proportion of any country. When compared to other countries, Kenya, Mozambique, and South Africa had the highest proportion of children with adequate MDD, accounting for 28% of their children consumed. In comparison to other countries, children from Ivory Coast, Burkina Faso, and Niger had the lowest percentage of meeting adequate MDD, accounting for less than 5% of them being consumed. Burundi and Namibia had the greatest percentage difference between urban and rural areas, with 25% or more of urban children meeting adequate MDD than rural children. (Fig. 2).
Children aged 6—11 months and 12—23 months had 15% (14%,15%) and 24% (23%, 24%) of them are meeting adequate MDD, respectively. Children aged 12—23 months had a higher proportion of consuming adequate MDD than children aged 6—11 months across all SSA countries. In comparison to other countries, South African children aged 6 to 11 months had the highest percentage (27%) of children meeting adequate MDD, followed by Kenya (26%) and Uganda (23%). In 6—11 months age groups, 3 percent of children in Burkina Faso, 4 percent in Chad, and 5 percent in Niger met adequate MDD, the lowest proportion in comparison to other countries. Kenya, South Africa, and Angola had the highest proportions of children aged 12 to 23 months with adequate MDD, accounting for 42 percent, 38 percent, and 34 percent, respectively. Similarly, only 6% of Burkina Faso children, 9% of Ivory Coast children, and 10% of Niger children met the adequate MDD, which were the lowest proportion among other countries (Fig. 2).
When examining the relationships between national levels of meeting adequate MDD and gross domestic product (GDP) per capital, meeting adequate MDD in children was strongly correlated with an increase in a country's GDP per capita or GDP per capital (Fig. 3).
Spatial epidemiology of meeting adequate MDD by region (admin1)
In almost every country, the heterogeneity of meeting adequate MDD within-country is high. The three highest magnitudes of the range (the difference between the maximum and minimum in the region) of percentage based on regions occurred in Mozambique, Angola, and Cameron, which account for 57%, 52%, and 46%, respectively. A Nassau region in Mozambique had the highest proportion of children meeting adequate MDD at 60%, Free State in South Africa had 58%, Greater Accra region in Ghana had 54%, Western Cape in South Africa had 54%, and Malanje in Angola had 54%. Almost all children in Angola's Cunene region, Burkina Faso's Almost all regions, Chad's Mayo Kebbi East region, Congo's Likouala region, Ethiopia's Somalia region, Guinea's Mamu region, Ivory Coast's Sud Oust region, and Lesotho's Qachis Nek region did not meet adequate MDD requirements. Some regions in SSA had 5% or fewer of their children meeting adequate MDD. Such as the Lunda Norte region in Angola, the North region in Cameron, the (Mandoul, Ouaddawa, Salamat, Tandjila, Wadi Fira) region in Chad, the Afar region in Ethiopia, the (Janijanbureh, Kuntaur) region in Gambia, the N'zRaKaora region in Guinea, the Mohale's Hoek region in Lesotho, the Cabo Delg (Fig. 4).
Hot spot analysis
The proportion of those with high inadequate MDD clusters and those with low inadequate MDD clusters varies substantially within and between countries. High-inadequate MDD clusters and low-inadequate MDD clusters varied substantially by region (province); the high inadequate MDD clusters were found in most areas of Western SSA as well as the same norther part of eastern and central SSA. The Southern SSA, as well as the Eastern and Central SSA in the direction of the South, had low inadequate MDD (Fig. 5).
High-value inadequate MDD cluster using the Poisson model
Only 18 of the 33 clusters with P-values less than 0·05 in SaTScan had statistically significant circular windows. The most likely primary circular windows(cluster 1) discovered by SaTScan were in Congo, Chad, Cameroon, and Gabon. In this cluster, 3799 cases were expected, but 4323 were discovered, with 93% of children having inadequate MDD and a relative risk (RR) of 1.2. The second significant cluster (cluster 2) was found in Liberia, Ivory Coast, Guinea, and neighboring countries. The estimated number of inadequate MDD in this cluster was 2763, but we observed 368 cases that were higher than expected. The relative risk was 1.1, and 92% of the children identified in this circular window had inadequate MDD. The third cluster of suspected primary circular windows (cluster 3) was discovered in Burkina Faso. The predicted number of cases in this cluster was 1164, but we found 1385, with a RR of 1.2 and 97% of children at risk of inadequate MDD. The fourth most significant circular windows discovered in Ethiopia. In this cluster, 856 cases were obtained, despite the fact that 736 cases were expected. The relative risk was 1.2, and 95% of the children in this area were at risk of having inadequate MDD (Fig. 6).
Spatial interpolation
Spatial interpolation study found that Gabon, Cameron, Ethiopia, the Democratic Republic of Congo, Chad, Mali, Burkina Faso, Ivory Coast, Liberia, and Senegal all had a very high burden of inadequate MDD. Similarly, the other countries were not awful in comparison to these countries, but they were not good in terms of coverage. Where at least 60% of their children were suffering from inadequate MDD (Fig. 7).
Multilevel logistic regression for the factors of inadequate MDD
After controlling of confounding factors in the household level child age, mother's age, media exposure, Antenatal Care(ANC) and/or Postnatal Care(PNC), maternal working status, maternal and partner education level, and maternal stunting and wasting; and in the community level household wealth and distance to health facility were statistically significant predictors. Children born to overlapping (both stunting and wasting) moms were 43% more likely to didn’t eat adequate MDD than children born to neither stunted nor wasted moms. Children of secondary and higher educated mothers were 23% and 49% less likely to have inadequate MDD, respectively, than children of uneducated mothers(Table 2).
Table 2
Sample size, prevalence, and multilevel regression for inadequate MDD.
|
Inadequate MDD (Prevalance)
|
Odds Ratio (95%CI)
|
Total
|
57291(79·9)
|
Crude
|
Adjusteda
|
Child age(Ref. 12—23)
|
37903(76.6)
|
1
|
1
|
6 to 11
|
20915(85.5)
|
2(1.9,2.2)
|
⋅ 2(1.84,2.18)**
|
Mother age(Ref. older/35—49)
|
11336(80.5)
|
1
|
1
|
Middle(25—34)
|
27385(78.4)
|
0.9(0.8,0.9)
|
0.89(0.8,0.98)**
|
Younger(< 25)
|
20097(81.1)
|
1.08(1,1.2)
|
1.03(0.92,1.15)
|
Media(Ref. Exposed)
|
37716(76)
|
1
|
1
|
Not exposed
|
20990(86.4)
|
1.9(1.8,2)
|
1.38(1.26,1.52)**
|
ANC/PNC(Ref. Both)
|
14359(75.2)
|
1
|
1
|
Either
|
28093(81.4)
|
1.4(1.3,1.5)
|
1.17(1.06,1.28)**
|
Neither
|
10457(83.9)
|
1.7(1.5,1.8)
|
1.35(1.19,1.52)**
|
Mother work(Ref. Have no work)
|
23523(81.8)
|
1
|
1
|
Have work
|
35236(78.4)
|
0.7(0.7,0.8)
|
0.81(0.74,0.88)**
|
Maternal education (Ref. No education)
|
22949(84.9)
|
1
|
1
|
Primary
|
19695(80.5)
|
0.8(0.7,0.8)
|
0.93(0.83,1.04)
|
Secondary
|
14362(73.6)
|
0.5(0.5,0.6)
|
0.77(0.67,0.87)**
|
Higher
|
1807(55.6)
|
0.2(0.2,0.3)
|
0.51(0.4,0.64)**
|
Sex of household head(Ref. Male)
|
44671(79.6)
|
1
|
1
|
Female
|
12147(80.3)
|
1.09(1.02,1.16)
|
1.05(0.94,1.17)
|
Birth in last 5 years(Ref. one)
|
26658(77.9)
|
1
|
1
|
Two
|
28350(81)
|
1.2(1.1,1.2)
|
0.99(0.91,1.08)
|
above two
|
3810(83.1)
|
1.3(1.2,1.5)
|
0.99(0.84,1.18)
|
Partner education (Ref. No education)
|
18231(85.4)
|
1
|
1
|
Primary
|
15408(79.7)
|
0.65(0.6,0.7)
|
1.02(0.9,1.14)
|
Secondary
|
14216(75.8)
|
0.5(0.46,0.54)
|
0.99 (0.87,1.12)
|
Higher
|
3409(62.7)
|
0.26(0.23,0.29)
|
0.82(0.68,0.98)**
|
Mother stunting and wasting(Ref. Normal)
|
38781(80.1)
|
1
|
1
|
Stunted
|
6316(80.3)
|
1.1(1,1.2)
|
1.09(0.98,1.23)
|
Wasted
|
2775(85.2)
|
1.4(1.2,1.6)
|
1.11(0.93,1.32)
|
Overlap
|
653(87.6)
|
1.7(1.3,2.2)
|
1.43(1.01,2.04)**
|
Wealth(Ref. Poorest)
|
13193(86)
|
1
|
1
|
Poorer
|
12724(84.3)
|
0.8(0.8,0.9)
|
0.92(0.81,1.05)
|
Middle
|
11958(81.4)
|
0.7(0.6,0.7)
|
0.82(0.72,0.94)**
|
Richer
|
11204(76.5)
|
0.5(0.4,0.5)
|
0.61(0.53,0.7)**
|
Richest
|
9740(66.9)
|
0.3(0.3,0.31)
|
0.42(0.36,0.5)**
|
Residence(Ref. Urban)
|
18631(71.8)
|
1
|
1
|
Rural
|
40187(83.4)
|
2.3(2.1,2.5)
|
1.05(0.92,1.19)
|
Ecology (Ref. Highland/>2300)
|
793(82.2)
|
1
|
1
|
Temperate(1501—2300 masl)
|
5597(81.2)
|
0.7(0.5,1)
|
0.91(0.62,1.33)
|
Lowland(501—1500 masl)
|
15813(78.7)
|
0.7(0.5,0.9)
|
0.83(0.57,1.2)
|
Subtropical(< 501 masl)
|
23996(77.7)
|
0.7(0.5,0.9)
|
0.84(0.58,1.21)
|
Distance of health facility(Ref. Big problem)
|
22660(82.1)
|
1
|
1
|
Not big problem
|
33149(77.2)
|
0.7(0.7,0.8)
|
0.84(0.77,0.92)**
|
** statistically significant at P - values < 0·05; aAdjusted for x, y, z; ANC = Antenatal Care; PNC = Postnatal Care |
The consequences of inadequate MDD: After controlling for confounding factors, children who are not meeting adequate MDD experience 2.5 times as much anemia, 1.30 times as much wasting, and 1.12 times as much stunting as their counterparts. (Fig. 8).
The most effective food group and combinations of food groups for improving adequate MDD: Higher egg affordability and availability, which increased by 17% above the average (20% ) of adequate MDD, which was the most important factor for improving adequate MDD. When three food groups (eggs, other fruits & vegetables and legumes & nuts) enhanced simultaneously at least improvement 48% reaches 68%, the greatest improvement was 64%, and riches to 84% of children would have appropriate MDD(Fig. 9).
Limitations of the study
The enumeration areas are not visible on the interpolated map, Because the point of the enumeration area of some countries was dense, all areas under prediction are hidden.
The DHS data was collected in a variety of years, depending on the country. The analysis did not take into account the differences in collecting time frames; instead, it combined everything into one.
Another limitation is that the question does not specify whether the child consumes processed or unprocessed food.
The lack of nutrition refers to a wide range of cases in the consequence model. Only a subset of them was included in this study. The data used in this analysis are cross-sectional, and the children who are living in this consequence shadow due to a lack of nutrition or other factors are unsure or unable to determine which comes first.