Rossato Luana T, Barbosa Cinthia D, Nahas Paula C, Orsatti Fábio L, de Oliveira Erick P
School of Medicine, Federal University of Uberlandia (UFU), Uberlandia, Minas Gerais, Brazil.
Exercise Biology Research Group (BioEx), Federal University of Triangulo Mineiro (UFTM), Brazil; Department of Sport Sciences, Federal University of Triangulo Mineiro, Uberaba, MG, Brazil.
Clin Nutr ESPEN. 2018 Apr;24:58-61. doi: 10.1016/j.clnesp.2018.01.069. Epub 2018 Feb 15.
Low strength and/or lean mass quality are associated with higher hospitalization and mortality. The aim of this study was to evaluate the main demographic and anthropometric predictors of strength and lean mass quality in hospitalized patients.
We evaluated 136 patients (18-86 years) of both sexes, admitted in a public hospital. Waist circumference (WC) was measured using an inelastic tape, lean mass (LM) was assessed by bioimpedance, and handgrip strength (HGS) was performed using a dynamometer. Lean mass quality (HGS/LM) was also calculated.
We noted that LM predicted 33.1% of HGS, whereas WC was not associated with HGS. Evaluating LM and WC in the same statistical model, WC (β = -0.249, p = 0.001) increased the prediction of HGS by 4.7% when compared to LM alone. Accessing LM, WC, age, and sex in the same model an increase in the prediction of HGS by 7.3% was noted when compared to LM alone, but only LM and sex were significant. In addition, WC predicted the lean mass quality by 4% (β = -0.205, p = 0.016) and when WC, sex, and age were placed in the same model; WC (β = -0.172, p = 0.035) and sex (β = 0.332, p < 0.001) explained the variations in lean mass quality by 15%.
The main predictor of lower HGS was lower LM, whereas sex showed a low association. Furthermore, although a low association was found, higher abdominal obesity and sex predicted lower lean mass quality.
低强度和/或瘦体重质量与较高的住院率和死亡率相关。本研究的目的是评估住院患者力量和瘦体重质量的主要人口统计学和人体测量学预测因素。
我们评估了一家公立医院收治的136例年龄在18至86岁之间的男女患者。使用无弹性卷尺测量腰围（WC），通过生物电阻抗评估瘦体重（LM），并使用测力计测量握力（HGS）。还计算了瘦体重质量（HGS/LM）。
我们发现LM可预测33.1%的HGS，而WC与HGS无关。在同一统计模型中评估LM和WC时，与单独使用LM相比，WC（β = -0.249，p = 0.001）使HGS的预测增加了4.7%。在同一模型中纳入LM、WC、年龄和性别，与单独使用LM相比，HGS的预测增加了7.3%，但只有LM和性别具有显著性。此外，WC可预测4%的瘦体重质量（β = -0.205，p = 0.016），当将WC、性别和年龄纳入同一模型时；WC（β = -0.172，p = 0.035）和性别（β = 0.332, p < 0.001）可解释15%的瘦体重质量变化。
较低的HGS的主要预测因素是较低的LM，而性别与之关联较弱。此外，尽管关联较弱，但较高的腹部肥胖和性别可预测较低的瘦体重质量。
