Obesity and Body Segment Parameters in Working Adults

描述(由申请人提供)：人体测量数据的来源，特别是身体部位的惯性参数，在人体工程学和职业生物力学中至关重要。目前预测这些人体测量变量的模型是基于在正常体重的年轻人中收集的数据开发的。然而，超过60%的美国员工超重或肥胖，而且随着年龄的增长，肥胖流行病加剧，超过75%的60岁以上的员工超重或肥胖。因此，需要生成新的模型来预测更好地反映工作人群的身体部分参数。我们建议使用双能X射线吸收(DXA)方法开发新的身体部分参数数据集，其中包括身体质量指数(BMI)作为跨年龄工作成年人的一个因素。更具体地说，该项目的目标有两个：(1)量化肥胖对21至70岁全职工作人员身体部位参数的影响(目标1)；(2)开发特定于BMI的回归模型，用于预测同一人群的身体部位参数(目标2)。为了实现这些目标，将招募21岁至70岁的全职工人参与拟议的项目。他们将被邀请来参观一次。在这次访问期间，将进行全身DXA扫描 以得出人体节段参数的活体测量结果。还将收集人体尺寸。将使用标准的多元回归模型来实现拟议项目的目标。总而言之，随着美国劳动力老龄化和肥胖和超重在这一人群中的流行率，我们必须开发经过验证的模型，在考虑到体重和年龄的情况下，准确预测在职成年人的身体部分参数。拟议的项目将解决人体工程学和职业生物力学文献中的这一差距。

DESCRIPTION (provided by applicant): Sources of anthropometric data, specifically body segment inertial parameters, are of critical importance in ergonomics and occupational biomechanics. Current models predicting such anthropometric variables are developed based on data collected in normal-weight young adults. Yet, over 60% of all US workers are either overweight or obese and this obesity epidemic worsens with increasing age with more than 75% of workers over the age of 60 years old being overweight or obese. Thus, there is a need to generate new models to predict body segment parameters that better reflect the working population. We propose to develop new datasets of body segment parameters that include body mass index (BMI) as a factor across the age span of working adults using Dual Energy X-Ray Absorption (DXA) methods. More specifically, the goal of the proposed project is two-fold: (1) quantify the impact of obesity on body segment parameters in full-time workers aged 21 to 70 years old (Aim #1), and (2) develop BMI-specific regression models for the prediction of body segment parameters in the same population (Aim #2). To achieve these aims, full-time workers between the ages of 21 and 70 years old will be recruited for participation in the proposed project. They will be asked to come in for one visit. During this visit, a whole-body DXA scan will be collected to derive in-vivo measures of body segment parameters. Body measurements will also be collected. Standard multivariate regression models will be used to achieve the aims of the proposed project. In summary, with the aging of the US workforce and prevalence rates of obesity and overweight in this population, it is critical that we develop validated models that accurately predict body segment parameters in working adults, taking into account body mass and age. The proposed project will address this gap in the ergonomics and occupational biomechanics literature.