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Table 2 Estimated regression coefficients of binary logistic regression model (BlogM) for child malnutrition status defined as height-for-age Z-score less than −2.00, the corresponding odds ratios (ORs), and adjusted predicted proportion (APP) of malnourished children from nominal-scale multiple classification analysis (NS-MCA) model, BDHS 2011

From: On exploring and ranking risk factors of child malnutrition in Bangladesh using multiple classification analysis

Background Characteristics Estimated regression coefficient of BlogM and OR Predicted proportion from NS-MCA
Β OR APP
Childs age in months (Reference Category: <12)
<12    20.83
12–23 1.406 4.081*** 48.89
24–35 1.314 3.722*** 46.78
36–47 1.284 3.610*** 46.13
48–59 1.027 2.792*** 40.42
Childs birth weight (Reference Category: Large)
Large    33.61
Average 0.318 1.374** 39.95
Small 0.753 2.123*** 49.47
Birth interval in months (Reference Category: 48+)
<24 0.383 1.467*** 47.35
24–47 0.208 1.231** 43.47
48+    38.90
Mothers education (Reference Category: Higher)
Illiterate 0.642 1.900*** 44.23
Primary 0.592 1.807*** 42.92
Secondary 0.418 1.519*** 39.08
Higher    32.10
Mothers BMI(kg/m2) (Reference Category: 18.5–24.99)
<18.5 0.270 1.310*** 45.91
18.5–24.99    39.81
25+ −0.346 0.708*** 33.19
Household economic status (Reference Category: Richest)
Poorest 1.109 3.031*** 51.26
Poorer 0.869 2.385*** 45.68
Middle 0.673 1.961*** 41.20
Richer 0.451 1.570*** 36.48
Richest    27.71
Family size (number of members) (Reference Category: Middle)
Small (<4) 0.173 1.189* 42.58
Middle (4–6)    39.00
Large (7+) 0.177 1.194** 42.80
Place of residence (Reference Category: Urban)
Urban    42.84
Rural −0.153 0.858* 39.71
Region (Division) (Reference Category: Barisal)
Barisal    41.29
Chittagong 0.011 1.011 41.54
Dhaka 0.108 1.114 43.65
Khulna −0.198 0.820 37.34
Rajshahi −0.400 0.671*** 33.12
Rangpur −0.057 0.944 40.12
Sylhet 0.158 1.171 44.60
Goodness-of-fit H-L test: \( {\chi}_{(8)}^2 \)=10.090; p-value: 0.259 F 26,7620  = 41.329; p-value < 0.001
Omnibus test: \( {\chi}_{(26)}^2 \)=1025.05; p-value < 0.001
R2 value 0.125 0.124
  1. *** P < 0.001; ** P < 0.01; * <0.05