Modelling Studies for a \u2018Whole of Society (WoS)\u2019 Framework to monitor Cardio-Metabolic Risk among Children (6 to 18 years)

In the World Health Assembly (WHA) 2013, India was among the first country to adapt global framework for monitoring non-communicable diseases (NCD) - Government of India (GOI) has set targets to halt the prevalence of diabetes and obesity by 2025. To halt the prevalence of major NCDs it is necessary to protect children from becoming obese or overweight. Childhood obesity is a precursor of adulthood obesity and attendant cardio-metabolic risk. In last 15 years the prevalence of overweight and obesity increased almost four times (4 to 15%). This translates in to approximately 58 million obese and 122 million overweight children in the country. Studies have reported at least one cardiovascular risk factor among 70 per cent of these children. It is frightening to know that, unit percentage rise in its prevalence in India shall add at least another five million children into the cardiovascular risk pool. Body Mass Index (BMI) [Weight (kg)/Height (m2)] is the most widely used definition for monitoring overweight and obesity; among children BMI-for-age based growth curves (centile values) are used. There are number of BMI-for age based guidelines with varying cut offs (like IOTF, WHO, CDC etc.) \u2013 in India, the growth curves published Indian Association of Pediatrics (IAP), 2015 is considered as the standard. Despite BMI\u2019s large scale application in clinical and public health programs it has many inherent problems. Firstly, BMI cannot distinguish between fat and fat free mass. Excess body fat is an independent risk factor for cardio vascular and metabolic diseases. In an individual with BMI of 20, body fat may range from 5%-40% whereas for body fat content of 20% BMI may vary from 15-30 points. Validity studies using BMI to identify children with excess adiposity have generally documented low to moderate sensitivities (6-46%). Secondly, BMI is not independent on height of the individuals. BMI may not be a sensitive measure in children at the extremes of the height due to unusual fat distribution or highly developed muscles. BMI preferentially classifies taller children and adolescents as overweight. Finally, the definition of childhood overweight and obesity is arbitrary as it is extrapolated from adult reference data and not based on its association with health outcomes. Considering these variations, there has been a growing concern about using single standard to define overweight and obesity which may be appropriate for many sub-populations in the world. Methods: Overall aim of this study was to develop a monitoring mechanism that correlates with cardio-metabolic risk factors among Indian children aged 6-18 yrs. Primary objective of the study was to relate health outcomes, i.e. measures of cardio-metabolic risk, to body fatness and to 4 measure its distribution. Under this overarching goal specific objectives were finalized as mentioned in section 1.4 (Page no.40). Quantitative data was collected from schools in 3 regions (New Delhi, Shillong and Hyderabad) from a representative sample of 3242 children between 6 to 18 years of age. Detailed assessments were done on; a) anthropometry; b) pubertal staging; c) blood biochemistry (fasting plasma insulin, fasting plasma glucose, lipid profile and sub-fractions uric acid) using semi-automated analyzer), d) body composition by bio impedance (BIA) (InBody 720, body composition analyzer, Biospace\ua9), e) body composition using DEXA (Hologic QDR 4500A) on selected sub samples, f) socio-economic status (standard of living index), g) media and market exposures, h) food frequency and dietary recalls, and i) physical activity recalls. The results are presented as: \uf0b7 Study 1: Assessment of whole-body composition using bioelectrical impedance analysis (BIA) among children 6 to 18 years: Validation with Dual X-Ray Absorptiometry (DEXA) \uf0b7 Study 2: Reference values and Percentile curves for cardio-metabolic risk factors among Indian children (6 to 18 years) \uf0b7 Study 3: Clustering of Bio-chemical Markers of Cardio-metabolic Risk among Indian Children: An Imperative for Continuous Monitoring of Risk Factors \uf0b7 Study 4: A multi-level framework for monitoring cardio-metabolic risk: proximal & distal factors associated with clustering of bio-chemical marker