BODY COMPOSITION METHOD FOR THE ELDERLY

拟议研究的目的是解决以下方面的独特需要： 流行病学研究的非侵入性，简单，但可靠的方法， 估计65岁以上老年人的身体组成和模式 年龄术语“身体组成”是指总身体脂肪（TBF）， 脂肪重量百分比（%BF）、无脂肪质量（FFM）、总身体水分 (TBW)和细胞外液（ECF）。“脂肪模式化”（FP）是指 皮下脂肪组织的解剖分布。重大变化 在身体组成和脂肪模式，有重要的健康相关 随着年龄的增长，这些变化的知识是很重要的， 老年人的诊断、诊断和治疗。数据很少， 然而，对于老年人的身体成分和脂肪模式， 传统的方法已经很难适用于技术，概念 或成本原因。拟议的研究将侧重于完善 卧位人体测量、生物电阻抗和B型成像 用于估计身体成分和脂肪模式的超声方法， 将适合流行病学研究。潜在的假设 该研究的一个重要特点是，这些方法的组合可以用来估计 身体组成和指数脂肪模式在老年人的新的方式， 规避限制应用的因素，如流动性降低， 常规人体测量和/或生物电阻抗方法。的 拟议研究的第一阶段将涉及开发和 验证预测人体成分和脂肪模式的方法， 400例门诊老年男性和女性的横断面样本。第二 阶段将包括交叉验证这些方法使用的数据， 两个独立样本

The purpose of the proposed study is to address the distinct need in epidemiologic studies for noninvasive, simple, but reliable methods for estimating body composition and patterning in elderly persons 65+ years of age. The term "body composition" refers to total body fat (TBF), the percent of weight that is fat (%BF), fat-free mass (FFM), total body water (TBW), and extra-cellular fluid (ECF). "Fat patterning" (FP) refers to the anatomical distribution of subcutaneous adipose tissue. Significant changes in body composition and fat patterning that have important health related effects occur with aging and knowledge of these changes is important for diagnoses, prognoses, and treatment of the elderly. There are few data, however, for body composition and fat patterning in the elderly because traditional methods have been difficult to apply for technical, conceptual or cost reasons. The proposed study will focus on the refinement of recumbent anthropometry, bioelectric impedance, and B-mode imaging ultrasound methods for estimating body composition and fat pattering that would be appropriate for epidemiologic studies. The underlying hypothesis of the study is that a combination of these methods can be used to estimate body composition and index fat patterning in the elderly in novel ways that circumvent factors, such as reduced mobility, that limit the application of conventional anthropometric and/or bioelectric impedance approaches. The first phase of the proposed research will involve the development and validation of methods for predicting body composition and fat pattern for a cross-sectional sample of 400 ambulatory, elderly men and women. The second phase will consist of the cross-validation of these methods using data from two independent samples.