Data exploratory
Table 3 depicts the prevalence of under-nutrition of sampled children using each of the anthropometric measures separately and a single composite measure respectively. For instance, about 38.3% of sampled children were stunted (21.0% moderately and 17.3% severely). According to composite index of failure, out of sampled children in Ethiopia about 46.6% of children were undernourished. The single composite index of anthropometric indicators showed that 49.0% of sample children were undernourished (19.8% moderately and 29.2% severely).
Table 3: the prevalence of undernourished children by each anthropometric and a single composite measure
Anthropometric indicators
|
Nourished
|
Moderately undernourished
|
Severely undernourished
|
Stunting
|
5857 (61.7)
|
1990 (21.0)
|
1647 (17.3)
|
Wasting
|
8535 (89.9)
|
677 (7.1)
|
282 (3.0)
|
Underweight
|
7247 (76.3)
|
1616 (17.0)
|
631 (6.7)
|
New single Composite
|
4846 (51.0)
|
1880 (19.8)
|
2768 (29.2)
|
N.B.: numbers in each cell are frequencies and percentages are in the parentheses.
|
Ordinal logistic regression models
As, the Brant test of parallel regression assumption violated (Chi-Square = 90.27, p-value=0.000), proportional odds were excluded and generalized ordered logit model and partial proportional odds model were fitted to the data. Finally, a comparison of the models made (Table 4). The model which represents the best fit according to AIC and BIC is PPOM as it has the smallest AIC and BIC (Table 4) and it is also more parsimonious. Thus, PPOM was used to identify significant determinants of under-nutrition and parameter estimates of the PPOM are presented and interpreted for the significant predictors (at 5% significance level).
Table 4: Log-likelihood and likelihood ratio estimates
Model
|
Obs
|
LL(null)
|
LL (model)
|
DF
|
LR chi2
|
P-Value
|
AIC
|
BIC
|
GOLM
|
7910
|
-8049.26
|
-7269.13
|
84
|
1560.27
|
<0.000
|
14710.26
|
15310.18
|
PPOM
|
7910
|
-8049.26
|
-7283.19
|
54
|
1532.15
|
<0.000
|
14678.37
|
15069.02
|
Results of Partial Proportional Odds Model
Table 5 and 6 show two result panels. The first (Table 5) contrasts the moderately and severely undernourished. In contrast to the remaining two categories of under-nutrition, signs of the coefficients in the first panel imply how likely nourishment of the child is.
Table 5: Maximum likelihood estimates of Partial proportional odds model
Predictors
|
Moderate and severe undernourished versus nourished
|
Coefficient
|
Std. Error
|
Z
|
P>|z|
|
Odds ratio
|
95% CI for OR
|
Region
|
Afar
|
-0.060
|
0.114
|
-0.53
|
0.597
|
0.942
|
(0.754, 1.177)
|
Amhara
|
0.328
|
0.101
|
3.25
|
0.001
|
1.389
|
(1.140, 1.693)
|
Oromia
|
-0.372
|
0.096
|
-3.86
|
0.000
|
0.689
|
(0.571, 0.833)
|
Somali
|
-0.670
|
0.108
|
-6.21
|
0.000
|
0.512
|
(0.414, 0.632)
|
Benishangul
|
0.117
|
0.112
|
1.05
|
0.295
|
1.124
|
(0.903, 1.401)
|
SNNPR
|
-0.355
|
0.100
|
-3.54
|
0.000
|
0.701
|
(0.576, 0.853)
|
Gambela
|
-0.715
|
0.127
|
-5.65
|
0.000
|
0.489
|
(0.382, 0.627)
|
Harari
|
-0.213
|
0.127
|
-1.68
|
0.092
|
0.808
|
(0.630, 1.036)
|
Addis Ababa
|
-0.812
|
0.173
|
-4.69
|
0.000
|
0.444
|
(0.316, 0.624)
|
Dire Dawa
|
-0.097
|
0.138
|
-0.70
|
0.485
|
0.908
|
(0.692, 1.191)
|
Residence
|
Rural
|
-0.138
|
0.104
|
-1.32
|
0.186
|
0.871
|
(0.711, 1.069)
|
Mother’s education
|
Primary
|
-0.100
|
0.061
|
-1.62
|
0.105
|
0.905
|
(0.803, 1.021)
|
Secondary &>
|
-0.547
|
0.116
|
-4.72
|
0.000
|
0.579
|
(0.461, 0.726)
|
Drinking water
|
Unimproved
|
0.102
|
0.051
|
2.01
|
0.045
|
1.108
|
(1.002, 1.224)
|
House hold size
|
5-9
|
0.054
|
0.069
|
0.78
|
0.434
|
1.055
|
(0.922, 1.207)
|
10 and more
|
0.208
|
0.123
|
1.70
|
0.089
|
1.232
|
(0.969, 1.567)
|
No children <5 years
|
2
|
-0.144
|
0.076
|
-1.90
|
0.057
|
0.866
|
(0.746, 1.004)
|
3 and more
|
0.150
|
0.055
|
2.72
|
0.007
|
1.162
|
(1.043, 1.294)
|
Wealth index
|
Poorer
|
0.082
|
0.070
|
1.18
|
0.238
|
1.085
|
(0.947, 1.244)
|
Middle
|
-0.204
|
0.076
|
-2.67
|
0.008
|
0.815
|
(0.702, 0.947)
|
Richer
|
-0.453
|
0.083
|
-5.44
|
0.000
|
0.636
|
(0.540, 0.748)
|
Richest
|
-0.447
|
0.113
|
-3.96
|
0.000
|
0.639
|
(0.512, 0.798)
|
Anemia
|
Anemic
|
0.197
|
0.050
|
3.95
|
0.000
|
1.218
|
(1.105, 1.344)
|
Husband’s
Education
|
Primary
|
-0.087
|
0.059
|
-1.47
|
0.141
|
0.916
|
(0.816, 1.030)
|
Secondary &>
|
-0.171
|
0.086
|
-2.00
|
0.045
|
0.924
|
(0.769, 1.109)
|
Birth order
|
2-3
|
-0.059
|
0.074
|
-0.79
|
0.428
|
0.943
|
(0.816, 1.090)
|
4-5
|
-0.035
|
0.091
|
-0.38
|
0.701
|
0.966
|
(0.809, 1.154)
|
6 and more
|
-0.079
|
0.093
|
-0.85
|
0.395
|
0.924
|
(0.769, 1.109)
|
Multiple birth
|
1st of multiple
|
0.725
|
0.210
|
3.45
|
0.001
|
2.066
|
(1.369, 3.117)
|
2nd of multiple
|
0.796
|
0.222
|
3.58
|
0.000
|
2.216
|
(1.430, 3.427)
|
Sex
|
Female
|
-0.110
|
0.049
|
-2.26
|
0.024
|
0.895
|
(0.814, 0.985)
|
Age of child in month
|
6-11
|
0.583
|
0.123
|
4.74
|
0.000
|
1.792
|
(1.408, 2.281)
|
12-23
|
1.646
|
0.107
|
15.37
|
0.000
|
5.185
|
(4.203, 6.395)
|
24-35
|
2.057
|
0.107
|
19.19
|
0.000
|
7.819
|
(6.338, 9.647)
|
36-47
|
1.980
|
0.107
|
18.44
|
0.000
|
7.244
|
(5.869, 8.941)
|
48-59
|
1.859
|
0.107
|
17.33
|
0.000
|
6.415
|
(5.199, 7.916)
|
Had fever
|
Yes
|
0.237
|
0.077
|
3.06
|
0.002
|
1.267
|
(1.089, 1.475)
|
Had cough
|
Yes
|
-0.019
|
0.074
|
-0.26
|
0.793
|
0.981
|
(0.849, 1.133)
|
Mother’s age at 1st birth
|
20-34
|
-0.110
|
0.049
|
-2.24
|
0.025
|
0.895
|
(0.813, 0.986)
|
35-49
|
0.296
|
0.562
|
0.53
|
0.599
|
1.344
|
(0.447, 4.046)
|
BMI of mother
|
Normal
|
-0.349
|
0.055
|
-6.36
|
0.000
|
0.705
|
(0.633, 0.785)
|
Overweight
|
-0.939
|
0.106
|
-8.87
|
0.000
|
0.391
|
(0.318, 0.481)
|
Constant
|
-0.805
|
0.189
|
-4.26
|
0.000
|
0.447
|
(0.309, 0.647)
|
Similarly, the second panel (Table 6) contrasts the severely undernourished category with nourished and moderately undernourished.
Table 6: Maximum likelihood estimates of Partial proportional odds model
Predictors
|
Severely undernourished versus nourished and moderately undernourished
|
Coefficient
|
Std. Error
|
Z
|
P>|z|
|
Odds ratio
|
95% CI for OR
|
Region
|
Afar
|
0.198
|
0.115
|
1.73
|
0.084
|
1.219
|
(0.974, 1.525)
|
Amhara
|
0.328
|
0.101
|
3.25
|
0.001
|
1.389
|
(1.139, 1.693)
|
Oromia
|
-0.152
|
0.102
|
-1.49
|
0.136
|
0.859
|
(0.704, 1.049)
|
Somali
|
-0.312
|
0.113
|
-2.76
|
0.006
|
0.732
|
(0.586, 0.914)
|
Benshangul
|
0.293
|
0.114
|
2.57
|
0.010
|
1.341
|
(1.073, 1.677)
|
SNNPR
|
-0.007
|
0.105
|
-0.07
|
0.946
|
0.993
|
(0.808, 1.220)
|
Gambela
|
-0.439
|
0.141
|
-3.12
|
0.002
|
0.645
|
(0.489, 0.849)
|
Harari
|
-0.213
|
0.127
|
-1.68
|
0.092
|
0.808
|
(0.630, 1.036)
|
Addis Ababa
|
-0.812
|
0.173
|
-4.69
|
0.000
|
0.444
|
(0.316, 0.624)
|
Dire Dawa
|
0.237
|
0.143
|
1.66
|
0.097
|
1.267
|
(0.958, 1.676)
|
Residence
|
Rural
|
-0.138
|
0.104
|
-1.32
|
0.186
|
0.871
|
(0.711, 1.069)
|
Mother’ education
|
Primary
|
-0.100
|
0.061
|
-1.62
|
0.105
|
0.905
|
(0.803, 1.021)
|
Secondary &>
|
-0.547
|
0.116
|
-4.72
|
0.000
|
0.579
|
(0.461, 0.726)
|
Drinking water
|
Unimproved
|
0.102
|
0.051
|
2.01
|
0.045
|
1.108
|
(1.002, 1.224)
|
House hold size
|
5-9
|
0.054
|
0.069
|
0.78
|
0.434
|
1.055
|
(0.922, 1.207)
|
10 & more
|
0.208
|
0.123
|
1.70
|
0.089
|
1.232
|
(0.969, 1.566)
|
No children
< 5 years
|
2
|
-0.144
|
0.076
|
-1.90
|
0.057
|
0.866
|
(0.746, 1.004)
|
3 and more
|
0.150
|
0.055
|
2.72
|
0.007
|
1.162
|
(1.043, 1.294)
|
Wealth index
|
Poorer
|
0.082
|
0.070
|
1.18
|
0.238
|
1.085
|
(0.947, 1.244)
|
Middle
|
-0.204
|
0.076
|
-2.67
|
0.008
|
0.815
|
(0.702, 0.947)
|
Richer
|
-0.453
|
0.083
|
-5.44
|
0.000
|
0.636
|
(0.540, 0.748)
|
Richest
|
-0.612
|
0.121
|
-5.06
|
0.000
|
0.542
|
(0.428, 0.688)
|
Anemia
|
Anemic
|
0.197
|
0.050
|
3.95
|
0.000
|
1.218
|
(1.105, 1.343)
|
Husband’s education
|
Primary
|
-0.188
|
0.063
|
-3.01
|
0.003
|
0.828
|
(0.732, 0.936)
|
Secondary &>
|
-0.171
|
0.086
|
-2.00
|
0.045
|
0.843
|
(0.712, 0.996)
|
Birth order
|
2-3
|
-0.059
|
0.074
|
-0.79
|
0.428
|
0.943
|
(0.816, 1.090)
|
4-5
|
0.096
|
0.093
|
1.03
|
0.302
|
1.101
|
(0.917, 1.320)
|
6 and more
|
0.050
|
0.095
|
0.53
|
0.598
|
1.052
|
(0.872, 1.268)
|
Multiple birth
|
1st of multiple
|
0.725
|
0.210
|
3.45
|
0.001
|
2.066
|
(1.369, 3.112)
|
2nd of multiple
|
0.796
|
0.222
|
3.58
|
0.000
|
2.216
|
(1.433, 3.427)
|
Sex
|
Female
|
-0.214
|
0.053
|
-4.07
|
0.000
|
0.808
|
(0.729, 0.895)
|
Age of child in month
|
6-11
|
0.583
|
0.123
|
4.74
|
0.000
|
1.792
|
(1.408, 2.281)
|
12-23
|
1.646
|
0.107
|
15.37
|
0.000
|
5.185
|
(4.203, 6.395)
|
24-35
|
2.057
|
0.107
|
19.19
|
0.000
|
7.819
|
(6.338, 9.647)
|
36-34
|
1.980
|
0.107
|
0.000
|
0.000
|
7.244
|
(5.869, 8.941)
|
48-59
|
1.859
|
0.107
|
17.33
|
0.000
|
6.415
|
(5.199, 7.916)
|
Fever
|
Yes
|
0.237
|
0.077
|
3.06
|
0.002
|
1.267
|
(1.089, 1.475)
|
Cough
|
Yes
|
-0.019
|
0.074
|
-0.26
|
0.793
|
0.981
|
(0.849, 1.133)
|
Mother’s age at birth
|
20-34
|
-0.110
|
0.049
|
-2.24
|
0.025
|
0.895
|
(0.813, 0.986)
|
35-49
|
0.296
|
0.562
|
0.53
|
0.599
|
1.344
|
(0.447, 4.046)
|
BMI of mother
|
Normal
|
-0.349
|
0.055
|
-6.36
|
0.000
|
0.705
|
(0.633, 0.785)
|
Overweight
|
-0.939
|
0.106
|
-8.87
|
0.000
|
0.391
|
(0.318, 0.481)
|
Constant
|
-1.929
|
0.191
|
10.09
|
0.000
|
0.145
|
(0.100, 0.211)
|
Key: the reference category for predictors is: Region (Tigray), Residence (urban), mother’s education (no education), source of drinking water (improved source), house hold size (1-4), number of children <5 years (1), wealth index (poorest), anemia (no), husband’s education (no education), birth order (1), multiple birth (single), sex (male), age of child (0-6), diarrhea (no), cough (no), fever (no), mother’s age at birth (<20), BMI (thin); BMI (Body mass index); Std. Error (Standard error); CI (confidence Interval) OR (Odds Ratio).
Hence, positive coefficients indicate that higher category values on the predictor make it more likely that the respondent will be in a higher category than the current one, while negative coefficients indicate that higher category values on the predictor increase the likelihood of being in the current or a lower category.
From partial proportional odds model the categories Afar, Oromia, Somali, SNNPR, Gambela, Harari, Dire Dawa; as well as richest wealth index; husband’s education, birth order and sex violated the parallel lines assumption. The model therefore allows the coefficients of these variables to vary across the two equations. From PPOM results, region, mother’s education and source of drinking water, number of under five children, wealth, anemia, multiple birth, age and sex of the child, had fever, mother’s age at first birth and body-mass index, and husband’s educational level were significantly related with under-nutrition.
Predictors that do not violate the parallel line assumption
The results of PPOM revealed that holding all variables constant, as compared to a child in Tigray, a child in Amhara was 1.4 (OR=1.4; CI: 1.14 - 1.69) times more likely to be in moderate or severe under-nutrition status. Similarly, compared to a child in Tigray, a child in Amhara was 1.4 (p-value =0.0001) times more likely to be in severe rather than in the moderate or nourished under-nutrition statuses. Holding other variables constant, the odds of being undernourished was worse, 2.3(OR=0.44; CI: 0.32-0.62) times in children of Tigray’s as compared to children of Addis Ababa.
The fitted model showed that compared with children whose mother had secondary or higher education, children from uneducated mother have risk of an even worse under-nutrition status 1.8= (OR=0.58; CI: 0.46 - 0.73) compared with the children with illiterate fathers, children with secondary or higher educated fathers were around 8% (OR=0.92; p-value =0.045) and less likely to be in the worst under-nutrition status. The risk of being in an even worse under-nutrition status decreased by 11% (OR=0.89; p-value =0.025) in a child born from a mother aged 20-34 years as compared to a child born from a mother aged <20 years. Keeping all other variables constant, as opposed to a child who had normal and obese mother, a child with mother of BMI less than18.5 kg was 1.4 (OR=0.71; CI: 0.63 - 0 .79) and 2.6 (OR=0.39; CI: 0.31 - 0.65) times more likely to be in worse under-nutrition status respectively.
The results of this study revealed that as compared to children from families having a single child aged under five years, the odds of being in a worse under-nutrition status were 1.2 (OR=1.2; p-value =0.007) times higher for children from families having 3 or more under-five children. Children from households with poorest wealth index, the risk of undernourishment decreased by 18% (OR=0.82; p-value =0.008) and by 36% (OR=0.64; p-value=0.000) in children from families with middle wealth and richer wealth index respectively. The first and second born of the multiple children were 2.1 (OR=2.1; p-value =0.001) and 2.2 (OR=2.2; CI: 1.43-3.43) times more likely to have a respectively worse under-nutrition status as compared to children from a family of single birth. Holding all other variables constant, children aged 6-11, 12-23, 24-35, 36-47 and 48-59 months were respectively 1.8 (OR=1.8; CI: 1.4-2.3), 5.2 (CI: 4.2-6.4), 7.8 (CI: 6.3-9.6), 7.2 (CI: 5.9-8.9) and 6.4 (CI: 5.2-7.9) times more likely to be in a worse under-nutrition status as opposed to children aged 0-6 months.
Holding all variables constant, the fitted model indicated that the risk of having worse under-nutrition status was 1.2 (OR=1.2; CI: 1.1-1.3) times higher among anemic children when compared to the non-anemic children. Compared to children who had no fever, the risk of being in a worse under-nutrition status was 1.3 (OR=1.3; p-value=0.002) times higher among children who had fever in the last two weeks before the survey. Compared to children from household who have consumed water from improved source, the odds of being undernourished increased by 10% (OR=1.1; p-value=0.045) among children from households who have not consumed water from improved source.
Predictors that violate the parallel regression assumption
The results of PPOM showed that compared to a child from Oromia, Somali, SNNP and Gambella, a child from Tigray region was 1.4 (OR=0.69; CI: 0.58-0.83), 2 (OR=0.50; CI: 0.41-0.63), 1.4 (OR=0.70; CI: 0.58-0.85) and 2 (OR=0.49; CI: 0.38-0.63) times more likely to be in a moderate or severe under-nutrition. Compared to a child in Somali and Gambella, a child from Tigray region was 1.4 (p-value =0.006) and 1.5 (p-value =0.002) times more likely to be in a severe rather than in a nourished or moderate under-nutrition status. In Contrast to a child from Tigray region, a child from Benshangul region was 1.34 (p-value =0.01) times more likely to be in a severe under-nutrition status rather than in a nourished or moderate under-nutrition status. The children from families with poorest wealth index were found 1.5 (OR=0.64; CI: 0.51-0.80) times more likely to be in moderate or severe under-nutrition rather than in a nourished status when compared to children with richest wealth index households. Keeping all other variables constant, in contrast to children from families with richest wealth index, the children with families of poorest wealth index were 1.8 (OR=0.54; CI: 0.43-0.69) times more likely to be in a severe rather than nourished or moderate under-nutrition status. In comparison to females, the fitted model had showed that male children were 1.1 (p-value =0.024) times more likely to be in moderate or severe under-nutrition rather than in a nourished status. In contrast to female children, the risk of male children to be in a severe under-nutrition status was 1.2 (OR=0.81; CI: 0.73-0.89) times higher than those children in a nourished or moderate status as compared to children born to husband with secondary or higher education. Holding all other variables constant, the risk of children born from a husband without education to be in severe under-nutrition status was 1.2 (p-value =0.003) times higher than those in a nourished or moderate status.