Sperandio Evandro Fornias, Arantes Rodolfo Leite, da Silva Rodrigo Pereira, Matheus Agatha Caveda, Lauria Vinícius Tonon, Bianchim Mayara Silveira, Romiti Marcello, Gagliardi Antônio Ricardo de Toledo, Dourado Victor Zuniga
Department of Human Movement Sciences, Universidade Federal de São Paulo, Santos, São Paulo, Brazil.
Department of Cardiovascular Medicine, Angiocorpore Institute of Cardiovascular Medicine, Santos, São Paulo, Brazil.
Sao Paulo Med J. 2016 Jan-Feb;134(1):56-62. doi: 10.1590/1516-3180.2015.00871609.
Accelerometry provides objective measurement of physical activity levels, but is unfeasible in clinical practice. Thus, we aimed to identify physical fitness tests capable of predicting physical inactivity among adults.
Diagnostic test study developed at a university laboratory and a diagnostic clinic.
188 asymptomatic subjects underwent assessment of physical activity levels through accelerometry, ergospirometry on treadmill, body composition from bioelectrical impedance, isokinetic muscle function, postural balance on a force platform and six-minute walk test. We conducted descriptive analysis and multiple logistic regression including age, sex, oxygen uptake, body fat, center of pressure, quadriceps peak torque, distance covered in six-minute walk test and steps/day in the model, as predictors of physical inactivity. We also determined sensitivity (S), specificity (Sp) and area under the curve of the main predictors by means of receiver operating characteristic curves.
The prevalence of physical inactivity was 14%. The mean number of steps/day (≤ 5357) was the best predictor of physical inactivity (S = 99%; Sp = 82%). The best physical fitness test was a distance in the six-minute walk test and ≤ 96% of predicted values (S = 70%; Sp = 80%). Body fat > 25% was also significant (S = 83%; Sp = 51%). After logistic regression, steps/day and distance in the six-minute walk test remained predictors of physical inactivity.
The six-minute walk test should be included in epidemiological studies as a simple and cheap tool for screening for physical inactivity.
加速度计可客观测量身体活动水平,但在临床实践中不可行。因此,我们旨在确定能够预测成年人身体活动不足的体能测试。
在大学实验室和诊断诊所开展的诊断性测试研究。
188名无症状受试者接受了以下评估:通过加速度计测量身体活动水平、在跑步机上进行运动心肺功能测试、通过生物电阻抗测量身体成分、等速肌肉功能测试、在测力平台上进行姿势平衡测试以及六分钟步行测试。我们进行了描述性分析和多因素逻辑回归分析,将年龄、性别、摄氧量、体脂、压力中心、股四头肌峰值扭矩、六分钟步行测试中的行走距离以及每天步数纳入模型,作为身体活动不足的预测因素。我们还通过受试者工作特征曲线确定了主要预测因素的敏感性(S)、特异性(Sp)和曲线下面积。
身体活动不足的患病率为14%。每天步数均值(≤5357步)是身体活动不足的最佳预测因素(S = 99%;Sp = 82%)。最佳的体能测试是六分钟步行测试中的距离≤预测值的96%(S = 70%;Sp = 80%)。体脂>25%也具有显著性(S = 83%;Sp = 51%)。经过逻辑回归分析后,每天步数和六分钟步行测试中的距离仍然是身体活动不足的预测因素。
六分钟步行测试应作为一种简单且廉价的身体活动不足筛查工具纳入流行病学研究。