Quantifying body shape in pediatric clinical research

项目概要/摘要。过度肥胖与代谢变化有关， 患上13种癌症的风险据估计，高达20%的癌症病例是由肥胖引起的 而预防肥胖在降低癌症发病率方面可发挥重要作用。肥胖人群中 在青少年中，体重增加最快的年龄是2 - 6岁。尽管有明确 这些因素与肥胖风险之间的联系，儿童早期肥胖的研究受到缺乏 适合这个年龄段的身体组成技术。长期目标是塑造！Keiki是1） 提供从高速扫描仪的详细体型扫描得出的儿科健康表型描述符， 和高深度分辨率3D相机，以及2）提供可视化和量化身体形状的工具， 研究和临床实践。我们的方法解决了阻碍身体组成的技术问题 在这个年龄范围内的研究，包括参与者不能保持不动，遵循方向，身材矮小，快速， 液体转移。为了开发我们的身体组成模型，我们将招募360名从出生到 按性别和BMI-Z分层的5年。我们的中心假设是，身体组成的光学估计适当 代表了一个5室（5C）的身体组成模型，用于研究幼儿的肥胖和健康 并且上级简单的人体测量学和人口统计学。我们的具体目标和次级目标是 如下：1）从3DO扫描中识别最能代表5室体的统计形状描述符 组成的种族多样化的儿科人群，1（a）确定的关系，最好的链接3DO形状 身体亚区域（手臂、腿、躯干）的描述符，以及匹配的体积和身体组成测量，1（B） 将自动3DO人体测量校准到临床相关的围长和长度，探索性）识别可访问性 3DO和TBW的组合，其可以被校准到脂肪和水合作用的标准5C测量，2）识别 定义可访问的3D光学身体组成估计的精度的因素，以监测 身体成分和代谢健康干预，3）对比体型，3DO和5C的关联 儿童健康指标的标准身体组成，包括临床相关暴露（SES，护理 持续时间、出生方法、营养）和发育。这项研究的基本原理是，早期生活中获得准确的 身体成分数据将有助于识别增加肥胖、代谢疾病和癌症的因素 风险，并提供一种手段，针对那些将受益的干预措施。预期的结果是， 研究结果将立即适用于现代游戏和成像传感器 电脑

Project Summary/Abstract. Excess adiposity is associated with metabolic changes that significantly increase the risk of developing 13 types of cancer. It is estimated that up to 20% of cancer cases are caused by obesity and that obesity prevention can play a significant role in the reduction of cancer incidence. Among obese adolescents, the most rapid weight gain has been shown to occur between 2 and 6 years of age. Despite clear connections between these factors and obesity risk, the study of obesity in early childhood is limited by the lack of body composition technologies appropriate for this age range. The long term goal of the Shape Up! Keiki is 1) to provide pediatric phenotype descriptors of health derived from detailed body shape scans from high-speed and high depth resolution 3D cameras, and 2) to provide the tools to visualize and quantify body shape in research and clinical practice. Our approach addresses technology issues that have hindered body composition research in this age range including participants' inability to hold still, follow directions, small body size, and rapid fluid shifts. To develop our body composition models, we will recruit 360 ethnically-diverse children from birth to 5 years stratified by sex and BMI-Z. Our central hypothesis is that optical estimates of body composition suitably represent a 5-compartment (5C) body composition model for studies of adiposity and health in young children and are superior to that of simple anthropometry and demographics. Our specific aims and subaims are as follows: 1) identify the statistical shape descriptors from 3DO scans that best represent 5-compartment body composition in an ethnically-diverse pediatric population, 1(a) identify the relationships that best link 3DO shape descriptors of body subregions (arms, legs, trunk), and matching volumes and body composition measures, 1(b) calibrate automated 3DO anthropometry to clinically relevant girths and lengths, Exploratory) identify accessible combinations of 3DO and TBW that can be calibrated to criterion 5C measures of fat and hydration, 2) identify the factors that define the precision of accessible 3D optical body composition estimates to monitor change in body composition and metabolic health interventions, 3) contrast the association of body shape, 3DO, and 5C criterion body composition to pediatric health indicators including clinically relevant exposures (SES, nursing duration, birth method, nutrition) and development. The rationale for this study is that early life access to accurate body composition data will enable identification of factors that increase obesity, metabolic disease, and cancer risk, and provide a means to target interventions to those that would benefit. The expected outcome is that our findings would be immediately applicable to accessible gaming and imaging sensors found on modern computers.