Department of Preventive Medicine, Rush University Medical Center, 1700 W. Van Buren St., Suite 470, Chicago, IL, 60612, USA.
Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, 2150 W. Harrison St., Room 278, Chicago, IL, 60612, USA.
Aging Clin Exp Res. 2020 Sep;32(9):1739-1747. doi: 10.1007/s40520-019-01355-8. Epub 2019 Oct 4.
Body composition strongly influences physical function in older adults. Bioelectrical impedance analysis (BIA) differentiates fat mass from skeletal muscle mass, and may be more useful than body mass index (BMI) for classifying women on their likelihood of physical function impairment.
This study tested whether BIA-derived estimates of percentage body fat (%BF) and height-normalized skeletal muscle mass (skeletal muscle mass index; SMI) enhance classification of physical function impairment relative to BMI.
Black, White, Chinese, and Japanese midlife women (N = 1482) in the Study of Women's Health Across the Nation (SWAN) completed performance-based measures of physical function. BMI (kg/m) was calculated. %BF and SMI were derived through BIA. Receiver-operating characteristic (ROC) curve analysis, conducted in the overall sample and stratified by racial group, evaluated optimal cutpoints of BMI, %BF, and SMI for classifying women on moderate-severe physical function impairment.
In the overall sample, a BMI cutpoint of ≥ 30.1 kg/m correctly classified 71.1% of women on physical function impairment, and optimal cutpoints for %BF (≥ 43.4%) and SMI (≥ 8.1 kg/m) correctly classified 69% and 62% of women, respectively. SMI did not meaningfully enhanced classification relative to BMI (change in area under the ROC curve = 0.002; net reclassification improvement = 0.021; integrated discrimination improvement = - 0.003). Optimal cutpoints for BMI, %BF, and SMI varied substantially across race. Among Black women, a %BF cutpoint of 43.9% performed somewhat better than BMI (change in area under the ROC curve = 0.017; sensitivity = 0.69, specificity = 0.64).
Some race-specific BMI and %BF cutpoints have moderate utility for identifying impaired physical function among midlife women.
人体成分强烈影响老年人的身体功能。生物电阻抗分析（BIA）可区分脂肪量和骨骼肌量，与身体质量指数（BMI）相比，其用于分类女性身体功能受损的可能性可能更有用。
本研究旨在测试 BIA 衍生的体脂肪百分比（%BF）和身高归一化骨骼肌量（骨骼肌质量指数；SMI）估计值是否比 BMI 更能增强对身体功能受损的分类。
在全国妇女健康研究（SWAN）中，黑种人、白种人、中国和日本的中年女性（N=1482）完成了基于表现的身体功能测量。计算 BMI（kg/m）。通过 BIA 得出 %BF 和 SMI。在整个样本中以及按种族分层进行了接收者操作特征（ROC）曲线分析，评估了 BMI、%BF 和 SMI 的最佳切点，以对中重度身体功能受损的女性进行分类。
在整个样本中，BMI 切点≥30.1 kg/m 正确分类了 71.1%的身体功能受损女性，而 %BF（≥43.4%）和 SMI（≥8.1 kg/m）的最佳切点分别正确分类了 69%和 62%的女性。SMI 与 BMI 相比，分类能力没有显著提高（ROC 曲线下面积的变化=0.002；净重新分类改善=0.021；综合判别改善= -0.003）。BMI、%BF 和 SMI 的最佳切点在种族之间有很大差异。在黑人女性中，%BF 切点为 43.9%的效果略优于 BMI（ROC 曲线下面积的变化=0.017；敏感性=0.69，特异性=0.64）。
一些特定种族的 BMI 和 %BF 切点对于识别中年女性的身体功能受损具有中等效用。
