It is well known that up to one-third of community-dwelling older adults fall each year in the United States1 and that risk of falling increases with age.2,3 By 2050, an estimated 88.5 million individuals will be aged 65 years or older,4 making the identification of those at risk for falling a pressing area of concern for health care providers.5 For many older adults, a fall, the fear of falling (FoF), or other risk factors may perpetuate a cycle of fall risk, leading to further functional decline and increasing fall risk and poor health.6,7
The early identification of individuals at risk for falling and subsequent intervention has proven to be very effective8 and has the potential to break such a cycle. Exercise programs and residential modifications significantly reduce the risk of falling and the rate of fall occurrence.8 One successful example is a program known as Stepping On9; however, accurate identification of individuals at risk is a necessary first priority.
In an effort to increase awareness of identification and intervention, the National Council on Aging has designated the first day of fall as Fall Prevention Awareness Day.10 In September 2011, the University of Nebraska-Lincoln (UNL) Dizziness and Balance Disorders Laboratory contributed to the initiative by providing free fall risk screenings. The human balance system is multisensory, including inputs from the vestibular, visual, and somatosensory/proprioception systems. Appropriate central integration and motor responses elicited from those sensory inputs must be properly effected to maintain upright stance and avoid a fall. Dizziness and balance issues are common among individuals who fall or are at increased risk for falling and these issues significantly increase falling risk.10–13 Objective evidence of vestibular dysfunction in almost 75% of individuals seen in a fall risk clinic has been documented by one study.14 The screening protocol, therefore, was designed to encompass many facets of the balance system, which, when impaired, may result in a fall. The purpose of this article was to retrospectively evaluate the clinical utility of the protocol components used that day in determining history of a recent fall. We hypothesized that this multifaceted balance protocol would demonstrate good clinical utility in the identification of individuals who had sustained a recent fall (within the previous 12 months).
A free fall risk screening day was advertised within the community and was provided as a clinical service. Retrospective analysis of the clinical data was approved by the UNL institutional review board (#12211). All participants received fall-prevention counseling and a recommendation for further evaluation if deemed necessary by a clinically certified audiologist. The protocol included a short case history, Activities-Specific Balance Confidence (ABC) Scale, modified Clinical Test of Sensory Interaction on Balance (mCTSIB), Timed Up and Go (TUG), and Dynamic Visual Acuity (DVA) tests.
Participants completed the case history form and ABC Scale in a waiting area before undergoing the performance-based screening measures. They completed the mCTSIB and TUG with an audiologist in a quiet, well-lit room with ample space and a firm tile floor; all participants wore a gait belt as a safety precaution. In a separate room, a second audiologist performed the DVA, reviewed all results, and provided counseling and recommendations for further fall risk assessment and prevention.
Each participant provided age and gender information and responded “yes” or “no” to a list of current balance problems (imbalance, dizziness, lightheadedness), lifetime history of falls, history of fall injury, and FoF. If a participant indicated a fall history, he or she was asked how many total falls were sustained and whether or not any falls had occurred within the previous 12 months (ie, a recent fall). Subjects received clarification as necessary to any questions that arose from the case history form.
The ABC Scale measures balance confidence for 16 daily activities, expressed as percent confidence 0 to 100%. Total ABC Scale score is an average of all 16 responses.15 Low balance confidence and significant fall risk are indicated by scores of 80%16 or less and 67% or less,17 respectively.
Modified Clinical Test of Sensory Interaction on Balance
The mCTSIB is a low-technology balance test with 4 increasingly challenging static balance conditions (C1-C4). The participant stands upright with feet together (wearing socks or disposable booties) and arms across the chest for a maximum of 20 seconds, first on a firm surface with and without vision, then on a medium density foam pad (18 in × 18 in × 5 in) with and without vision. Each condition is scored on the basis of the amount of sway. A normal test result (score = 0) is indicative of little to no postural sway, whereas scores of 1 to 3 indicate mild sway, moderate sway, and inability to perform the task (ie, a fall reaction or moving out of position), respectively.18
Timed Up and Go
To perform the TUG, the patient sits back in a sturdy chair with arms, stands at the “go” command, walks a distance of 10 feet, turns around, and returns to sit in the chair.19 A standard size chair was used for the TUG (the chair used had a seat height of approximately 19 in [seat dimensions: 19 in × 17 in], seatback height of approximately 33 in, and arm height of approximately 27 in). Participants were given one practice trial to ensure that they understood all directions. A stopwatch was used to record time in seconds from the participant's chair rise to chair return. Specific directions were provided prior to each trial: “When I say ‘go’ I want you to stand up and walk to the line, turn, and then walk back to the chair and sit down again. Walk at your normal pace.” For this screening protocol, a TUG time greater than 13 seconds was considered a reasonable indicator of reduced mobility and risk of falling, given the wide range of scores (8.1-16 seconds) reported in the literature for the simple TUG at a normal pace.20
Dynamic Visual Acuity
For DVA, the participant sat 10 feet from a Snellen eye chart, reading the lowest line possible (>50% accuracy) with head still (ie, static visual acuity [SVA]). Then the examiner moved the participant's head from behind in the yaw (ie, horizontal) plane at approximately 2 Hz, ±15° excursions to the right and left of center, while the participant again read the lowest line possible (>50% accuracy) to measure DVA.18 A DVA change greater than 2 lines from SVA indicates decreased visual acuity with head movements, a known indicator of falling risk.21 The screening was performed with both eyes and best corrected vision. Case history did not include information such as history of last eye examination, type of corrective lenses, or history of visual disorders.
Statistical analyses were performed using Microsoft Excel 2007 (Microsoft Corporation) and SPSS Version 21 (SPSS Inc, Chicago, Illinois). Descriptive statistics (mean, standard deviation [SD], ranges, frequency) were calculated. The clinical utility of each fall risk indicator was evaluated in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), and negative likelihood ratio (LR−), using self-report of recent history of falls as the comparison. This approach has been adopted by others13,15,17,21 for clinical utility analysis of falling risk measures. Sensitivity is a value of test accuracy to identify a condition, while specificity is a value of test accuracy to identify absence of a condition.22 Predictive value is the probability of the presence or absence of a condition, given a positive or negative test result, respectively.22 In addition, LR+ and LR− are measures of how likely an individual will have the condition given a positive test or not have the condition given a negative test result.22 Fall risk measures were evaluated using a binary logistic regression analysis, using history of recent falls as the dependent variable. Significance levels for model inclusion and exclusion were P < .05 and P > .10, respectively. Logistic regression analysis can be biased when using smaller sample sizes.23 As such, the results of this analysis were used to determine the variables most helpful in identifying recent history of falls. Fall risk indicators included in the model were further analyzed using a receiver operating characteristic (ROC) curve, area under the curve (AUC), Cohen d, and Spearman correlation coefficients. An ROC curve is a plot of false alarm rate (1 − specificity, x-axis) and sensitivity (y-axis).22 An ROC curve in the upper left corner and an AUC of 1.0 represents a superior test for identifying a condition. An inferior test has an ROC curve closer to the chance (diagonal) line of the graph and AUC closer to 0.5.22 The Cohen d was calculated, with higher d values indicating better group discrimination.24 Finally, Spearman correlations (rs) were used to characterize the relationship of important fall risk predictors with group characteristics and other screening measures.25
Thirty adults participated in the 10- to 15-minute fall risk screening protocol. Table 1 outlines participant characteristics and screening results. The majority of the participants were older adults and women. The majority of individuals who self-referred were women (70.0%) and older adults (mean = 77.2 years). Almost half of participants reported a history of falling in their lifetime (46.7%), which was more prevalent in women (52.4%) than in men (33.3%). Average total number of lifetime falls was approximately one fall per person for women, men, and both combined. One female participant reported “several” falls per year but could not recall specific numbers; this participant was excluded from all fall number calculations. The number of individuals who reported having sustained at least 1 recent fall (within the previous 12 months) was similar to lifetime fall prevalence (women: 42.9%; men: 33.3%). One-third of participants reported a fall-related injury. More women than men reported a fall injury (women: 38.1%; men: 22.2%).
A majority of participants reported FoF (70.0%), which was more prevalent in women. Reports of dizziness (36.7%) and lightheadedness (56.7%) were fairly common. More women than men reported dizziness; however, reports of lightheadedness were roughly the same between genders. All 30 participants reported current imbalance.
Table 2 outlines the screening results. Average ABC Scale score (66.3%) for all participants was lower than the 67% cutoff value for fall risk17 and group averages were less than the 80% balance confidence cutoff.16 Fourteen participants had an ABC Scale score at 67% or less (12 women). Women had lower balance confidence (mean [SD] = 62.7% [16.0]) than men (mean [SD] = 74.6% [17.9]). Six participants (2 women) scored more than 80% on the ABC Scale.
Timed Up and Go (TUG) times varied widely (range: 8.0-37.0 seconds). Women had slower TUG times (mean [SD] = 14.6 [6.2] seconds, range: 9.0-29.5 seconds) than men (mean [SD]= 13.9 [8.9] seconds, range: 8.0-37.0 seconds). Seven participants (6 women) had TUG times that exceeded the 13-second cutoff value used in our laboratory.
Some participants were unable to or elected not to perform SVA (n = 1) or DVA (n = 4). Therefore, DVA loss values are based on 26 participants. Average SVA for both groups was line 7.9 on the eye chart (approximately 20/30). Seven participants (5 women) had SVA poorer than 20/30. The majority of individuals who underwent DVA testing had more than 2 lines change from SVA (n = 19; 15 women; range: 20/50 to 20/125).
The majority of participants had no more than mild sway (score = 0) in mCTSIB C1 (0: 96.7%; mild sway [score = 1]: 3.3%) and C2 (0: 56.7%; 1: 33.3%). The more challenging foam conditions (C3 and C4) resulted in increased body sway. Almost half (46.7%) of all participants scored a 3 (eg, severe sway or fall reaction) on C3, and 80.0% scored a 3 on C4.
Screening results were separated into 2 different groups: those who had sustained a recent fall (Fall Group, 40.0%) and those who had not (No Fall Group, 60.0%) (Table 3). The Fall Group was younger on average (73.9 years) than the No Fall Group (79.4 years). Both groups had similar gender proportions. Average total falls were higher for the Fall Group (2.8 falls/person) than for the No Fall Group (0.1 falls/person), as was the percentage who reported a fall injury (58.3% vs 11.1%). Case history–based FoF was similarly present in both groups: 75.0% (Fall Group) and 66.7% (No Fall Group). Dizziness and lightheadedness were higher in the No Fall Group (50.0% and 66.7%, respectively) than in the Fall Group (16.7% and 41.7%, respectively).
For both the ABC Scale 67% and TUG 13-second cutoffs, 50.0% of the Fall Group was identified as at risk for falling. These measures had a 71.4% agreement on hit rate (both measures missed 1 individual correctly identified by the other). In the No Fall Group, ABC and TUG identified 38.9% and 16.7%, respectively, of the individuals as at-risk for falling. Average ABC Scale score for the Fall Group was 61.8% (SD: 20.0; range: 30-90.6%) compared with 69.3% in the No Fall Group (SD: 14.9; range: 42.5-95.6%). Both scores were low based on the 80% balance confidence cutoff; however, the No Fall Group, on average, was not at risk for falling based on the 67% cutoff. Average TUG time for the Fall Group was 18.2 seconds with wide variance (SD: 9.3, range: 8.0-37.0), compared with 11.8 seconds (SD: 3.2, range: 9.0-22.2) for the No Fall Group. The DVA test identified approximately the same percentage of individuals for the Fall Group (70.0%) and the No Fall Group (83.3%), as did the mCTSIB. In mCTSIB C3, the percentage of the Fall Group versus No Fall Group who scored a 1 (16.7% vs 22.2%), 2 (moderate sway, 8.3% vs 11.1%), or 3 (50.0% vs 44.4%) differed very little. Condition 4 also had similar percentages for each score in the Fall and No Fall Groups: score of 1 (16.7% vs 5.6%), 2 (0% in both groups), and 3 (75.0% vs 83.3%). All individuals who participated in the screening protocol were deemed at risk for falling. Recommendations included a referral to a medical or other health care professional (n = 11; 36.7%), a comprehensive fall risk assessment (n = 6; 20.0%), or both (n = 13; 43.3%).
Clinical utility indices are indicated in Table 3. In all cases, a trade-off between sensitivity and specificity is available. Those measures that had good sensitivity had poor specificity, such as the presence of FoF (sensitivity: 75.0%; specificity: 29.9%). Conversely, those measures that had good specificity had poor sensitivity, such as the TUG test (sensitivity: 50.0%; specificity: 83.3%). When evaluating the individual measures, all had poor clinical performance for identifying a recent fall. The highest performing measure was history of a fall injury (sensitivity: 68.8%; specificity: 81.3%; PPV: 70.0%; NPV: 72.2%; LR+: 3.11; LR−: 0.51); however, the majority of individuals who sustained a fall injury (n = 6) had sustained only 1 fall in their lifetime. The TUG test was the next highest performing screening measure (sensitivity: 50.0%; specificity: 83.3%; PPV: 66.7%; NPV: 71.4%; LR+: 3.00; LR−: 0.60).
A binary logistic regression analysis was employed to determine the most useful indicators of fall risk. Given the lack of 1 superior measure, all screening measures were included in a forward, stepwise conditional regression analysis. Values for inclusion and exclusion into the model were P < .05 and P > .10, respectively, and the dependent variable was recent fall history. The screening measures used in the analysis included ABC, mCTSIB C1-C4, TUG, and DVA loss. The only screening measure included within the regression model was TUG time: although not a significant predictor itself (β = 0.276, SE = 0.159, df = 1, P = .084), removal would have resulted in a significant decrease in variance accounted for by the model (change in r2, P = .017). Therefore, the hypothesis that the screening protocol would efficiently identify individuals with a recent history of falling was rejected. Figure 1 displays the results of the ROC analysis for the regression model, with an AUC value of 0.712.
The TUG test was further analyzed for optimal clinical utility. A 12-second cutoff score increased sensitivity (83.3%), though, as expected, decreased specificity (61.1%). The TUG failed to identify only 2 individuals with a history of recent falls. Both were males, younger than the average age of 77.2 years, and other measures did not aid in detection, aside from one individual who had a DVA loss more than 2. All other TUG clinical utility indices were recalculated on the basis of the 12-second cutoff value (PPV: 58.8%; NPV: 84.6%; LR+: 2.14; and LR−: 0.27). For the TUG test, the Cohen d = 0.92, indicating a large effect size24 and good separation between the Fall and No Fall Groups. The 12-second cutoff score is indicated on Figure 1. A lower cutoff score resulted in poorer specificity with no increase in sensitivity.
Spearman correlations further evaluated the TUG's relationship to group characteristics and then with other screening measures. Correlation effect sizes were classified in accordance with standard cutoff guidelines (small: 0.1; medium: 0.3; and large: 0.5),26 and a significance level was set to P < .05 overall. The TUG had large correlations with total number falls (rs = 0.505; P = .005) so that as TUG time increased, total number of falls increased. Medium correlations were found with lifetime history of falls (rs = 0.406; P = .026), recent history of falls (rs = 0.460; P = .011), and FoF (rs = 0.371; P = .047). As TUG time increased, so did the presence of a lifetime history of falls, recent history of falls, and positive history of FoF. Small correlations were noted with age (rs = 0.290; P = .120), lightheadedness (rs = −0.130; P = .495), and dizziness (rs = −0.148; P = .442), so that as TUG scores increased, age increased and the absence of lightheadedness and dizziness were related to a small degree, but not significant. A weak correlation was noted with gender (rs = 0.044; P = .816) and history of fall injury (rs = 0.086; P = .662). Using a Bonferroni-adjusted alpha level for multiple correlations among patient characteristics,27 the significance level of P < .005 for 10 total correlations resulted in no significant correlations.
Spearman correlations evaluating the relationship between the TUG time and other screening measures were generally medium to large. Strong correlations were found between TUG time and ABC (rs = −0.507; P = .004), SVA (rs = −0.552; P = .002), mCTSIB C1 (rs = 0.614; P < .001), and mCTSIB C3 (rs = 0.513; P = .004), indicating that as balance confidence and SVA decreased and sway scores in vision-present conditions of the mCTSIB increased, so did TUG times. Modified CTSIB C2 and C4 had moderate (rs = 0.464; P = .010) and mild (rs = 0.276; P = .139) correlations, respectively, with TUG scores so that, again, as sway score increased so did TUG times. A weak correlation was noted between TUG and DVA loss (rs = −0.083; P = .687). Using the Bonferroni approach27 for the 6 comparisons (P < .0083), TUG correlations with ABC, SVA, mCTSIB C1, and mCTSIB C3 were considered significant.
The results reported herein have several implications for fall risk screenings. Individuals were typically women, older adults (mean age = 77.2 years), had FoF, and had sustained a recent fall. Perhaps most notably, all individuals reported current imbalance. It is possible that this type of patient would be amenable to fall-prevention efforts, potentially having an increased awareness of falls and knowing that they are at risk for falling.
Forty percent of participants reported a recent fall, which is slightly higher than the often-quoted US annual incidence of falls at approximately 1 in 3 (34%).1 In addition, this sample presented with a much higher fall-related injury rate (71.4%) relative to the 33% fall-related injury rate,28,29 plus a high rate of FoF at 70% relative to approximately 50%.30 These discrepancies may have several explanations. This sample had a 100% rate of imbalance, whereas this is likely not the case with other samples. In addition, the aforementioned statistics are from community-dwelling older adult samples. Living situation was not assessed during this screening; however, it did appear that the majority of participants resided with a spouse (who also participated in the screening) and had his or her own transportation to the clinic. In addition, it is common practice at UNL to clarify falls using a definition such as “unintentionally coming to rest on the ground, floor, or other lower level.”31(p300) However, given the retrospective nature of the data, it is uncertain whether the fall definition was used; this should be noted as a potential limitation with the frequency of falls reported. Regardless of these potential limitations, it does appear that older adults with current complaints of imbalance have a higher rate of falls, fall-related injury, and FoF.
The fall risk screening protocol used was multifaceted; however, the TUG test was the most useful for determining a recent fall. The TUG test has significant correlations with other fall risk screening measures that support its use as a measure that incorporates major components of the balance system. When further analyzed, a 12-second cutoff score for the TUG provided optimal sensitivity and specificity. Inclusion of any other used measures did not increase the ability to identify individuals with a history of recent falls.
The American Geriatrics Society 2010 Clinical Practice Guideline for fall prevention in older adults indicates a balance or gait screening for those individuals who report a recent fall, recurrent falls, or balance complaints.32 The screening can be part of a multifactorial fall risk screening or alone, and the TUG is a recommended test for this screening because of its quick nature and inclusion of gait assessment.32 In the Centers for Disease Control and Prevention (CDC) Stopping Elderly Accidents Deaths and Injuries (STEADI) toolkit, the TUG test is a recommended measure following a positive response to previous screening questions (ie, presence of unsteadiness or falling concerns, a recent fall, a score of ≥ 4 on a published checklist).5 While the CDC recommends a 12-second cutoff TUG time for fall risk identification,5 evidence supporting the use of the TUG test is not considered strong. This is due to a lack of prospective evaluation and varied reports of sensitivity (30%-89%) and specificity (56%-100%).32
Previous reports have cautioned on the use of TUG for fall prediction. It is suggested that the heterogeneity in study samples and differences in how the TUG is carried out (eg, directions, distance, chair dimensions) contribute to the poor clinical performance of the TUG and a wide range of cutoff scores.22,33–35 The protocol reported herein adhered strictly to specific directions, distance, and dimensions, and the study sample was relatively homogenous in some respects (100% reported imbalance). However, since this was a retrospective review of clinical data from a walk-in community fall risk screening, it is uncertain if our subjects were all healthy community-dwelling older adults or older adults with poorer health and more limited mobility. Such heterogeneity in samples is of concern when recommending a cutoff value for using the TUG as a fall risk screening measure.33 In addition, these data did not find significant correlations between TUG times and other potential confounding factors, including age and gender, which are highlighted by a recent systematic review.20 From a community-wide screening standpoint, we found the TUG to be clinically useful to identify those with a history of a recent fall. On the basis of the probable heterogeneity of our sample, we would also recommend adopting the 12-second cutoff value, supporting the CDC's current recommendation.5
The retrospective nature of this study and reliance on patient report and self-referral are additional limitations. Patient recall of falls is not completely accurate; 13% of individuals fail to recall a recorded fall within a 12-month period.36 In addition, this entire sample was self-referred for a fall risk screening, indicating that they are possibly more aware of the risks of falling or consider themselves at risk for falling. The sensitivity and specificity values reported herein may be biased because of poor accuracy of participant self-report. Prospective studies continuously monitoring fall history are needed to further justify the use of TUG for individuals with imbalance, and its place within a multifaceted falling risk assessment. Considering these limitations, the TUG is still a useful fall risk screening measure for individuals who complain of current imbalance. A ≥ 12-second cutoff score is optimal, with a sensitivity of 83.3% and specificity of 61.1%.
This report documents important characteristics of older adults who self-refer for a fall risk assessment, which may be important for determining who is amenable to taking steps toward prevention. These individuals were generally older and female, with FoF and current balance complaints. The TUG test stood out among the protocol as the most clinically useful for this group of individuals with imbalance. Specifically, the TUG was the best measure to identify individuals with a recent history of falls. Although different TUG cutoff times or alternative fall risk measures may be more appropriate for older adults without complaints of current imbalance, this study supports the use of the TUG test for recent fall identification as well as the CDC's recommendation of a 12-second cutoff TUG time when applied to individuals with imbalance.
The authors thank those who assisted with the fall screening day: Jameson Hofker, Choongheon Lee, Jessie Patterson and Erin Schiltz; as well as those who provided statistical support: Matt Lambert, Houston Lester and Grant Orley. A portion of this publication was reproduced within Robin Criter's dissertation work with permission from the editor.37
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