Abstract

ObjectivesClinical interpretability of the gait speed and 5-times sit-to-stand (5-STS) tests is commonly established by comparing older adults with and without self-reported mobility limitations (SRML) on gait speed and 5-STS performance, and estimating clinical cutpoints for SRML using the receiver operating characteristics (ROC) method. Accumulating evidence, however, suggests that the adjusted predictive modeling (APM) method may be more appropriate to estimate these interpretational cutpoints. Thus, we aimed to compare, in community-dwelling older adults, gait speed and 5-STS cutpoints estimated using the ROC and APM methods. DesignCross-sectional study. Setting and ParticipantsThis study analyzed data from 955 community-dwelling independently walking older adults (73%women) aged ≥60 years (mean, 68; range, 60–88). MethodsParticipants completed the 10-metre gait speed and 5-STS tests. Participants were classified as having SRML if they responded "Yes" to either of the 2 questions regarding walking and stair climbing difficulty. Cutpoints for SRML and its component questions were estimated using ROC analysis with Youden criterion and the APM method. ResultsThe proportions of participants with self-reported walking difficulty, self-reported stair climbing difficulty, and SRML were 10%, 19%, and 22%, respectively. Gait speed and 5-STS time were moderately correlated with each other (r=-0.56) and with the self-reported measures (absolute r-values, 0.39–0.44). ROC-based gait speed cutpoints were 0.14 to 0.16 m/s greater than APM-based cutpoints (P < 0.05) whilst ROC-based 5-STS time cutpoints were 0.8 to 3.3 s lower than APM-based cutpoints (P < 0.05 for walking difficulty). Compared with ROC-based cutpoints, APM-based cutptoints were more precise and they varied monotonically with self-reported walking difficulty, self-reported stair climbing difficulty, and SRML. Conclusions and implicationsIn a sample of 955 older adults, our findings of precise and biologically plausible gait speed and 5-STS cutpoints for SRML estimated using the APM method indicate that this promising method could potentially complement or even replace traditional ROC methods.

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