Association between anthropometric-based and food-based nutritional failure among children in India, 2015.
William JoeSunil RajpalRockli KimAvula LaxmaiahRachakulla HarikumarNimmathota ArlappaIndrapal MeshramNagalla BalakrishnaMadhari RadhikaSoumya SwaminathanSankaran Venkata SubramanianPublished in: Maternal & child nutrition (2019)
Inadequate dietary intake is a critical underlying determinant of child undernutrition. This study examined the association between anthropometric-based and food-based nutritional failure among children in India. We used the 2015-2016 National Nutrition Monitoring Bureau data where anthropometric outcomes and food intake were both measured for each child. We followed the World Health Organization child growth reference standards to define anthropometric failures (i.e., height-for-age z score < -2 SD for stunting, weight-for-age z score < -2 SD for underweight, and weight-for-height z score < -2 SD for wasting), and the Indian Council of Medical Research recommended dietary allowance (RDA) to define adequacy in intake of calorie, protein, and fat. We used descriptive and regression-based assessments to test the association between the two indicators of nutritional failure and also computed the area under the receiver operating characteristic curve (AUC). The prevalence of stunting, underweight, and wasting was 28.6%, 24.3%, and 12.8%, respectively, whereas 78.2%, 27.4%, and 50.8% of the children had below RDA norms consumption of calorie, protein, and fat, respectively. We found weak-to-null correlation between anthropometric failures and food failures (Pearson correlation ranging from -0.013 to 0.147) and poor discriminatory accuracy (AUC < 0.62), suggesting that in the Indian context, anthropometric failures are not directly associated with food intake. This finding highlights the need for improving adequate intake of macronutrients and draws attention toward adopting a multifactorial approach to improve child nutrition in India. Poor food intake itself merits exclusive policy focus as it is an important nutrition and health concern.
Keyphrases
- body composition
- mental health
- physical activity
- body mass index
- healthcare
- weight loss
- young adults
- weight gain
- public health
- adipose tissue
- human health
- protein protein
- fatty acid
- binding protein
- magnetic resonance imaging
- magnetic resonance
- computed tomography
- quality improvement
- type diabetes
- risk assessment
- climate change
- metabolic syndrome
- small molecule
- big data
- amino acid
- deep learning
- artificial intelligence
- insulin resistance
- skeletal muscle
- glycemic control