Intraindividual double-burden of anthropometric undernutrition and “metabolic obesity” in Indian Children: A paradox that needs action

BACKGROUND: Intraindividual coexistence of anthropometrically defined undernutrition and “metabolic obesity”, characterised by presence of at least one abnormal cardiometabolic risk factor, is rarely investigated in young children and adolescents, particularly in Low-and-Middle-Income-Countries undergoing rapid nutrition transition. METHODS: Prevalence of biomarkers of metabolic obesity was related to anthropometric and socio-demographic characteristics in 5-19 years old participants from the population-based Comprehensive National Nutrition Survey in India (2016-2018). The biomarkers, serum lipid-profile (total cholesterol (TC), low density lipoprotein (LDL), high density lipoprotein (HDL) and triglycerides), fasting glucose, and glycosylated hemoglobin (HbA1C), and all jointly were analysed in 22567, 23192, 25962 and 19143 participants, respectively. RESULTS: Overall (entire dataset), the prevalence of abnormalities was low (4.3-4.5%) for LDL and TC, intermediate for dysglycemia (10.9-16.1%), and high for HDL and triglycerides (21.725.8%). Proportions with ≥1 abnormal metabolic obesity biomarker(s) were 56.2% overall, 54.2% in thin (BMI-for-age <-2SD) and 59.3% in stunted (height-for-age <-2SD) participants. Comparable prevalence was evident in mild undernutrition (-1 to -2 SD). Clustering of two borderline abnormalities occurred in one-third, warranting active life-style interventions. Metabolic obesity prevalence increased with BMI-for-age. Among those with metabolic obesity, only 9% were overweight/obese (>1SD BMI-for-age). Among poor participants, triglyceride, glucose and HDL abnormalities were higher. CONCLUSIONS: A paradoxical, counter-intuitive prevalence of metabolic obesity biomarker(s) exists in over half of anthropometrically undernourished and normal-weight Indian children and adolescents. There is a crucial need for commensurate investments to address overnutrition along with undernutrition. Nutritional status should be characterized through additional reliable biomarkers, instead of anthropometry alone.