Shape up! Kids

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Investigator: John Shepherd, PhD
Sponsor: NIH National Institute of Diabetes and Digestive and Kidney Diseases

Location(s): United States

Description

The proposed research is relevant to public health because they have the potential to provide a better understanding of what children are at high risk of metabolic consequences of obesity. Thus, the advances proposed are expected to have a high impact to the health and wellbeing of all US citizens because metabolic diseases, such as obesity and its complications, are currently the number one killers of adults, and are becoming epidemic in children as well. This is relevant to the part of NIH's mission which focuses on the prevention of disease by supporting research in the diagnosis of human diseases.

 
Of all markers of pediatric health, the most intuitive is body shape. Human and animal studies indicate that weight loss/gain correlates closely with increasing/decreasing insulin sensitivity, respectively. Anthropometry and regional composition measures such as waist circumference, waist to hip ratio (WHR), and visceral adipose tissue area are better predictors of obesity-related diseases and mortality risk than pediatric body mass index Z-score. Dual-energy X-ray absorptiometry can quantify regional adiposity in more detail than these measures but is underutilized for many reasons including the sensitivity to children to ionizing radiation, cost, and training. A study is needed to take advantage of rapid technological developments in optical technology to better describe phenotypes of pediatric body shape and its relation to metabolic risks (obesity, “failure to thrive”) and bone density and size. If successful, sophisticated obesity phenotype profiles could be constructed to clarify the underlying associations of body composition with disease, genetics, lifestyle exposures, metabolomics, and be highly assessable using self-assessment technology. The long term goal of the Shape Up! Kids Study is 1) to provide pediatric phenotype descriptors of health using body shape, and 2) to provide the tools to visualize and quantify body shape in research, clinical practice, and personal health assessment. Our overall approach is to first derive predictive models of how body shape relates to regional and total body composition (subcutaneous fat, visceral fat, muscle mass, lean mass, and percent fat) and bone mineral density (BMD) over a wide range of ages (5 to 18 years), weights and heights, stratified by sex, and ethnicity. Our central hypothesis is that optical estimates with shape classification of soft tissue composition and bone density better predict fracture and metabolic risk factors than anthropometry (WC, WHR, and BM) alone. The Investigators will highly leverage existing data from the National Health and Nutrition Examination Survey and Bone Mineral Density in Children Study. Our specific aims are: 1) Identify the unique associations of body shape to body composition and bone density indices in a pediatric population that represents the variance found in the US population, 2) Describe the precision and accuracy of optical scans to monitor change in body composition, bone density, 3) Estimate the level of association of optical scans to common health indicators including metabolic risk factors. Our exploratory aim is to investigate holistic, high-resolution descriptors of 3D body shape as direct predictors of body composition and metabolic risk using statistical shape models and Latent Class Analysis. By the end of this study, we expect to have models of the shape and composition suitable for self-assessment technologies that are capable of representing over 95% of the shape variance in the US pediatric population, and to define how these models relate to important metabolic status indicators. The positive impact of these outcomes will be the immediate applicability to other researcher studies and clinicians using the automated tools and models developed here for 3D optical images.