Differences in geriatric anthropometric data between DXA-based subject-specific estimates and non-age-specific traditional regression models.
Differences in geriatric anthropometric data between DXA-based subject-specific estimates and non-age-specific traditional regression models.
复制标题
DOI：
10.1123/jab.27.3.197
复制
发表时间：
2011-08
影响因子：
1.4
通讯作者：
Cham R
中科院分区：
文献类型：
--
作者：
Chambers AJ;Sukits AL;McCrory JL;Cham R
年龄、肥胖和性别会对65岁及以上的成年人的人体测量学产生重大影响。这项研究的目的是研究两种方法得出的人体节段参数的差异：(1)双能X射线吸收测量法(DXA)特定受试者的方法和(2)传统回归模型。研究了年龄、性别和肥胖对这些方法之间潜在差异的影响。83名健康的老年人被招募参加。受试者接受了全身DXA扫描(HOLOGIC QDR 1000/W)。确定了每个节段的质量、长度、质心和旋转半径。此外，还使用传统的回归方法来估计这些参数。采用混合线性回归模型(α=0.0 5)。除前臂节段质量外，方法类型在所有感兴趣的变量中均有显著意义。我们观察到的肥胖和性别差异转化为与使用传统回归预测老龄化人口中的人体测量变量有关的差异。我们的数据表明，在利用人体测量数据集时，需要考虑年龄、肥胖和性别，并开发回归模型，考虑性别和肥胖，准确预测老年人群的身体部分参数。
Age, obesity, and gender can have a significant impact on the anthropometrics of adults aged 65 and older. The aim of this study was to investigate differences in body segment parameters derived using two methods: (1) a dual-energy x-ray absorptiometry (DXA) subject-specific method and (2) traditional regression models. The impact of aging, gender, and obesity on the potential differences between these methods was examined. Eighty-three healthy older adults were recruited for participation. Participants underwent a whole-body DXA scan (Hologic QDR 1000/W). Mass, length, center of mass, and radius of gyration were determined for each segment. In addition, traditional regressions were used to estimate these parameters. A mixed linear regression model was performed (α = 0.05). Method type was significant in every variable of interest except forearm segment mass. The obesity and gender differences that we observed translate into differences associated with using traditional regressions to predict anthropometric variables in an aging population. Our data point to a need to consider age, obesity, and gender when utilizing anthropometric data sets and to develop regression models that accurately predict body segment parameters in the geriatric population, considering gender and obesity.