Use of Stance Time Variability for Predicting Mobility Disability in Community-Dwelling Older Persons: A Prospective Study

INTRODUCTION

Gait variability, defined as fluctuations in gait characteristics from step to step, has been shown to be related to future falls and mobility disability in older adults.^1–4 Specific measures of gait variability can reflect any of a number of spatial (step length, step width) or temporal (stance time, stride time) gait characteristics. Prior studies have reported on step length,^4–6 step width,^6–9 stride time^5,7,10 and stance time^2,10 variability. Stance time variability (i.e. the variability in the time from initial foot-floor contact until final foot-floor contact) has been shown to be related with the central nervous system and psychomotor function,¹¹ and with future mobility disability.² Brach et al. (2007) investigated the ability of stance time variability (STV) to predict incident mobility disability (self-reported ability to walk ½ mile) in a cohort of community-dwelling older adults. Greater STV was found to be related to incident mobility disability; however a specific cut-point of STV related to mobility disability was not established.²

Physical therapists often perform evaluations on their patients to guide clinical decision making for current intervention and prevention of future disability. In order for STV to be a useful indicator of mobility disability, the magnitude (cut-point) of STV that discriminates mobility disability must be determined. A cut-point of STV would provide useful diagnostic and prognostic information to clinicians for distinguishing patients with current mobility disability problems and for assisting in predicting which patients are at risk for developing future mobility disability. Developing the measure of STV is accomplished by establishing the construct and predictive validity for mobility disability using validity indices [sensitivity, specificity, receiver operating characteristic (ROC) curve and area under the curve (AUC)] to establish meaningful cut-point values.

Mobility disability is a serious and frequent adverse health outcome associated with aging and is often a result of chronic disease.¹² Establishing a specific value of STV that can be used to identify and predict mobility disability and who may benefit from interventions to improve gait variability would provide physical therapists with a valuable clinical tool for early detection and intervention of this serious health outcome.

The purpose of this study was to: 1) determine the magnitude of STV that discriminates individuals who currently have mobility disability (prevalent mobility disability) and 2) determine the magnitude of STV that predicts a new onset of mobility disability at one year (incident mobility disability).

METHOD

RESULTS

Baseline subject characteristics are shown in Table 1. The mean age of the sample was 79.4 years (SD=4.1), 60.9% were female and 22.8% were African American. The perceived health of the sample was quite good, with 31.5% reporting their health as very good or excellent and 54.7% reporting their health as good. The sample had good mobility with only 63 of the 552 participants (11.4%) using an assistive device and a mean gait speed of 1.01 m/s (SD=0.23).

Of the 552 individuals included in the study, 125 or 22.6% reported difficulty walking one half mile at baseline and were classified as having prevalent mobility disability. Of the 427 individuals who did not report mobility disability at baseline, 399 individuals had 1-year follow- up mobility disability data available (28 or 7% lost to follow-up). Of these 399 individuals, 59 or 14.8% reported difficulty walking one half mile at the 1 year follow-up (incident mobility disability).

As determined from the ROC analysis, the optimal cut-off score for STV (maximizing sensitivity and specificity) for prevalent mobility disability was 0.037 sec (AUC = 0.70) and for incident 1 year mobility disability was 0.034 sec(AUC = 0.65); figures 1 and 2. Sensitivity and specificity values for mobility disability at the optimal cut-off value determined from the ROC curve and for additional values of STV that maximize either sensitivity or specificity and positive and negative predictive values are shown in Table 2.

Across the intervals of STV for the outcome of prevalent mobility disability (Table 3), the risk for disability increased as the values of STV increased: disability risk (for each range of STV the number of participants with mobility disability/number of participants at that range of STV) started at 3% (1/40) for STV <0.019 sec and increased for each consecutively higher band at 13% (11/87), 14% (15/105), 21% (17/80), 26% (18/69), 29% (13/45), 33% (14/43), 40% (12/30), and 53% (24/45) for STV values > 0.066 s. The data correspond to likelihood ratio estimates demonstrating an increased risk for disability from baseline risk with STV values 0.037 to .042 (likelihood ratio = 1.21) and increasing progressively as the values of STV increase.

For the outcome of incident 1 year mobility disability (Table 4), the risk for disability also demonstrated an overall increasing gradient from the lowest to the highest STV values with some fluctuation of values at the middle intervals: disability risk was 5% (3/66) for STV values <.022 secand increased for each higher band at 14% (13/90), 10% (6/61), 13% (8/62), 20% (8/41), and 27% (21/79) for STV values >0.045 s. The transition point for increased risk according to likelihood ratios started at STV values of 0.040–0.045 sec(likelihood ratio = 1.4), and there was increase for values > 0.045 sec(likelihood ratio = 2.12).

DISCUSSION

Diagnosis is a process in which patient data are collected and evaluated in order to classify a condition, determine prognosis, and identify possible interventions.²¹ Diagnostic tests, such as STV, can be used to assist in the classification process. We identified two different values of STV for identifying individuals with prevalent mobility disability (0.037 sec) and at risk for developing mobility disability one year later (0.034 sec). It is not surprising that the cut- point identified for predicting mobility disability at one year was lower than the cut-point for identifying individuals with prevalent mobility disability (i.e. 0.034 sec versus 0.037 sec) since individuals with prevalent mobility disability have greater STV and were removed for the incident mobility disability analyses.

The values for sensitivity, specificity, area under the ROC curve (AUC), positive predictive value, and positive likelihood ratio were quite modest, thus potentially limiting their clinical usefulness. The area under the ROC curve (AUC) is a measure of the overall performance of a diagnostic test or the accuracy of the diagnostic test. The AUC has values ranging from 0 to 1 with the closer the AUC is to 1 the better overall diagnostic performance of the test. An AUC value of .5 represents an uninformative test.²² Our AUC values for prevalent mobility disability and incident mobility disability (i.e. AUC = .70 and .65 respectively) indicate only fair discriminate value for those outcomes.

Correct diagnosis relies, in part, on the ability to minimize error during the testing process to avoid false positive or false negative results.²¹ The measure of STV that we evaluated had only fair test-retest reliability.¹⁶ The reliability of STV may be influenced by the number of steps used to calculate the measure. Including a greater number of steps in the calculation of STV could potentially improve the reliability and potentially the diagnostic characteristics of the measure as well.²³

The PPV, which is used to judge whether or not a patient has the condition of interest, was quite low. The PPV of a diagnostic test should be interpreted with caution since it is dependent on the overall prevalence of the condition. In this study, a relatively small number of subjects had mobility disability at baseline (i.e. 23%) and an even smaller number of individuals developed incident mobility disability over the 1-year follow-up (i.e. 15%). The one year incidence of mobility disability was similar to that reported in the Iowa EPESE sample which has been described as not representative of older adults in general, other samples in the EPESE study had incident rates closer to 20–25%.¹⁷

A reoccurring question in the field of gait variability is if greater variability is associated with negative outcomes. In this study, the likelihood ratios suggest a risk gradient for progressive (increasing) values of STV for prevalent mobility disability, thus suggesting that greater values of STV are undesirable. Greater values of STV have also been associated with poor perception of health, difficulty performing activities of daily living, and lower levels of physical activity.¹⁶ Further research is needed to determine if interventions that can decrease STV during usual walking can also reduce or prevent mobility disability.

Stance time variability was measured using a computerized gait analysis system that may not be available for most clinicians interested in identify older adults who are at risk for mobility disability. Recent work has demonstrated that an observational rating of gait variability (the Modified Gait Abnormality Rating Scale variability item, GARSM) is an acceptable alternative measure of gait variability for identifying older adults at risk for mobility disability in clinical settings.²⁴ However, the ability to have a computerized gait analysis system in the clinic should not be overlooked as lower cost alternatives become available.

When interpreting our results the following limitations should be considered. The outcome of interest, mobility disability, was based on self-report that may not accurately reflect a persons’ ability. However, self-report of walking ½ mile has been used to adequately represent mobility disability in several studies of older adults.^17–19 A performance-based measure of disability, such as the long distance corridor walk, may be a more appropriate outcome to investigate.^25;26 A gradient of increasing risk with increasing STV was demonstrated for prevalent mobility disability. The gradient for incident 1-year mobility disability was not continuous across the STV values and was nearly equal for STV values between 0.022 and 0.045 s. This result is most likely attributable to the small number of individuals who developed incident mobility disability (i.e. 15%) resulting in unstable estimates.

The current, prospective study is the first to evaluate the predictive validity of STV for mobility disability at one year using comprehensive validity indices of sensitivity, specificity, ROC curves, AUC, positive and negative predictive values, and likelihood ratios. The relatively modest values on the validity indices could possibly be improved by increasing the reliability of the measurement of STV. Given the modest values for the validity indices for STV clinicians should not consider our suggestions for cut-off values of STV as defined boundaries for indicating who is at risk for developing mobility disability. Clinicians should interpret the values liberally and use STV in conjunction with other measures until further work is completed to validate STV as an indicator of mobility disability. We have shown an increasing risk for mobility disability associated with greater values of STV during usual walking. This suggests that irregular timing of gait is a predictor of mobility disability and future efforts are needed to determine if interventions aimed at reducing STV could also prevent mobility disability.