Background: Ethiopia is one of the developing countries where child under-nutrition is prevalent. Prior studies employed three anthropometric indicators for identifying factors of children's under-nutrition. This study aimed at identifying the factors of child under-nutrition using a single composite index of anthropometric indicators. Methods: Data from Ethiopia's Demographic and Health Survey 2016 was the base for studying under-nutrition in a sample of 9494 children below 59 months. A single composite index of under-nutrition was created from three anthropometric indices through principal component analysis recoded into an ordinal outcome. In line with World Health Organization 2006 Child Growth Standards, the three anthropometric indices involve z-score of height-forage (stunting), weight-for-height (wasting) and weight-for-age (underweight). Partial proportional odds model was fitted and its relative performance compared with some other ordinal regression models to identify significant determinants of under-nutrition. Results: The single composite index of anthropometric indicators showed that 49.0% (19.8% moderately and 29.2% severely) of sampled children were undernourished. In the Brant-test of proportional odds model, the null hypothesis that the model parameters equal across categories was rejected. Compared to ordinal regression models, partial proportional odds model showed an improved fit. A child with mother's body mass index less than 18.5 kg, from poorest family and a husband without education, and male to be in a severe under-nutrition status was 1.4, 1.8 1.2 and 1.2 times more likely to be in worse under-nutrition status compared to its reference group respectively. Conclusion: Authors conclude that the fitted partial proportional odds model indicated that age and sex of the child, maternal education, region, source of drinking water, number of under five children, mother's body mass index and wealth index, anemic status of child, multiple births, fever of child before 2 months of the survey, mother's age at first birth, and husband's education were significantly associated with child under-nutrition. Thus, it is argued that interventions focus on improving household wealth index, food security, educating mothers and their spouses, improving maternal nutritional status, and increasing mothers' health care access.

Background Child undernutrition is a global health concern. Many studies have focused on the association of childhood undernutrition indicators with their predictors. A few studies have looked at relationship between the undernutrition indicators. This study aimed at investigating the possible association structures of childhood undernutrition indicators. Methods A log-linear model of cell counts of a three way table of stunting, wasting, and underweight was fitted based on the 2016 Ethiopia demographic health survey data. The variables of interest were generated based on the 2006 WHO Child Growth Standards as: stunted, wasted and underweight if z-scores of height-for-age, weight-for-height and weight-for age are below-2, respectively; otherwise not stunted, wasted and underweight. Results This study showed that 36.34, 12.09 and 24.87% were stunted, wasted and underweight out of sampled children respectively and the prevalence of total undernutrition in children was about 45.96%.The fitted log-linear model showed that underweight was associated with both stunting ( P -value< 0.001), and wasting ( P -value< 0.001). There was no association between stunting and wasting ( P -value = 0.999). Furthermore, the model showed that there is no a three way interaction among stunting, wasting, and underweight ( P -value = 1.000). Conclusion The authors conclude that there is lack of three way association of stunting, wasting, and underweight. This confirms that the three anthropometric indicators of children have multi-dimensional nature. Thus, the concerned body should consider the three undernutrition indicators simultaneously to estimate the actual burden of childhood undernourishment as they are not redundant of each other.

Background: Ethiopia is one of the developing countries where child under-nutrition is prevalent. Prior studies employed three anthropometric indicators for identifying factors of children’s under-nutrition. This study aimed at identifying factors of child under-nutrition using a single composite index of anthropometric indicator. Methods: Data from Ethiopia’s Demographic and Health Survey 2016 was the base for studying under-nutrition in a sample of 9494 children below 59 months. A single composite index of under-nutrition was created from three anthropometric indices through principal component analysis recoded into an ordinal outcome. In line with WHO 2006 Child Growth Standards, the three anthropometric indices involve z-score of height-for-age (stunting), weight-for-height (wasting) and weight-for-age (underweight). To identify significant determinants of under-nutrition , partial proportional odds model was fitted and its relative performance compared with some other ordinal regression models. Results: The single composite index of anthropometric indicators showed that 49.0% (19.8% moderately and 29.2% severely) of sampled children were undernourished. In the Brant-test of proportional odds model, the null hypothesis that the model parameters equal across categories was rejected. Compared to ordinal regression models that do not involve parallel regression assumption, and Akaike information criterion, partial proportional odds model showed an improved fit. A child with mother of body mass index less than 18.5 kg, from poorest family, a husband without education and male to be in a severe under-nutrition status was 1.4, 1.8 1.2 and 1.2 times more likely to be in worse under-nutrition status compared to its reference group respectively. Conclusion: The authors conclude that the fitted partial proportional odds model indicated that age and sex of the child, maternal education, region, source of drinking water, number of under five children, mother’s body mass index, wealth index, anemic status, multiple birth, fever before two months of survey, mother’s age at first birth, and husband’s education were significantly associated with child under-nutrition. Thus, it is argued that interventions focus on improving household wealth index, food security, educating mothers and their spouses, improving maternal nutritional status, and increasing mothers’ health care access.

Background: Ethiopia is one of the developing countries where child under-nutrition is prevalent. Prior studies employed three anthropometric indicators for identifying factors of children’s under-nutrition. This study aimed at identifying the factors of child under-nutrition using a single composite index of anthropometric indicators. Methods: Data from Ethiopia’s Demographic and Health Survey (EDHS) 2016 was the base for studying under-nutrition in a sample of 9494 children below 59 months. A single composite index of under-nutrition was created from three anthropometric indices through principal component analysis recoded into an ordinal outcome. In line with Child Growth Standards (WHO, 2006), the three anthropometric indices involve z-score of height-for-age (stunting), weight-for-height (wasting) and weight-for-age (underweight). To identify significant determinants of under-nutrition, partial proportional odds model was fitted and its relative performance compared with some other ordinal regression models. Results and conclusion: In the Brant test of proportional odds model, the null hypothesis that the model parameters were equal across categories was rejected. Compared to ordinal regression models that do not involve parallel regression assumption, and Akaike information criterion, partial proportional odds model showed an improved fit. The fitted partial proportional odds model indicated that age and sex of the child, maternal education, region, source of drinking water, number of under five children, mother’s body mass index, wealth index, anaemic status, multiple birth, fever, mother’s age at birth, and husband’s education significantly associated with child under-nutrition. It is argued that interventions focus on improving household wealth index, food security, educating mothers and their spouses, improving maternal nutritional status, and increasing mothers’ health care access. Keywords: Stunting; underweight; wasting; partial proportional odds model

Background: Ethiopia is one of the developing countries where child under-nutrition is prevalent. Prior studies employed three anthropometric indicators for identifying factors of children’s under-nutrition. This study aimed at identifying factors of child under-nutrition using a single composite index of anthropometric indicator. Methods: Data from Ethiopia’s Demographic and Health Survey 2016 was the base for studying under-nutrition in a sample of 9494 children below 59 months. A single composite index of under-nutrition was created from three anthropometric indices through principal component analysis recoded into an ordinal outcome. In line with WHO 2006 Child Growth Standards, the three anthropometric indices involve z-score of height-for-age (stunting), weight-for-height (wasting) and weight-for-age (underweight). To identify significant determinants of under-nutrition , partial proportional odds model was fitted and its relative performance compared with some other ordinal regression models. Results: The single composite index of anthropometric indicators showed that 49.0% (19.8% moderately and 29.2% severely) of sampled children were undernourished. In the Brant-test of proportional odds model, the null hypothesis that the model parameters equal across categories was rejected. Compared to ordinal regression models that do not involve parallel regression assumption, and Akaike information criterion, partial proportional odds model showed an improved fit. A child with mother of body mass index less than 18.5 kg, from poorest family, a husband without education and male to be in a severe under-nutrition status was 1.4, 1.8 1.2 and 1.2 times more likely to be in worse under-nutrition status compared to its reference group respectively. Conclusion: The authors conclude that the fitted partial proportional odds model indicated that age and sex of the child, maternal education, region, source of drinking water, number of under five children, mother’s body mass index, wealth index, anemic status, multiple birth, fever before two months of survey, mother’s age at first birth, and husband’s education were significantly associated with child under-nutrition. Thus, it is argued that interventions focus on improving household wealth index, food security, educating mothers and their spouses, improving maternal nutritional status, and increasing mothers’ health care access.