Background: Although the sit-to-stand (STS) test score has been shown to relate to the strength and size of the quadriceps femoris (QF) for elderly population, it is unknown whether this relationship is influenced by a posture (i.e., the trunk being allowed to stoop or not) during the STS test. The present study investigated the relationship between STS test score and QF anatomical cross-sectional area (ACSA) in the middle-aged and elderly population with regard to the difference in the posture during STS test, and aimed to develop an accurate predicting equation of the QF ACSA from the STS test score. Methods: 105 males (40-81 years) and 113 females (41-79 years) participated in the present study, then the subjects were divided at random as validation and cross-validation groups. Mid-thigh QF ACSA was determined by magnetic resonance imaging. Subjects performed a 10-repeated STS as fast as possible in two conditions: (1) with the trunk being allowed to stoop during the sitting phases, and (2) kept upright throughout the test. A power index of the STS test score was calculated based on an equation obtained in a previous study using the time taken for each test condition, the thigh and shank lengths, and body mass. In the validation group (n = 109), a stepwise multiple linear regression analysis was performed to create a predictive model of the ACSA with sex, age, the STS time, and power for both conditions as independent variables. The formulated predictive equation was examined in the cross-validation group (n = 109). Results: In the validation group, a stepwise regression analysis revealed that STS power with upright trunk condition, sex, and age but not with the stooping condition, were selected as variables to predict QF ACSA (R 2 = 0.64, P < 0.001). There was no systematic error for the relationship between predicted and measured values in the cross-validation group. Conclusions: These results indicate that STS test score with upright trunk condition is one of the indices of QF muscle size of the middle-aged and elderly population. The estimated predicting equation should be useful in clinical and practical settings for the health promotion.
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