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Impaired balance is associated with falls in older adults. However, there is no accepted gold standard on how balance should be measured. Few studies have examined measures of postural sway and clinical balance concurrently in large samples of community-dwelling older adults. We examined the associations among four types of measures of laboratory- and clinic-based balance in a large population-based cohort of older adults.
We evaluated balance measures in the MOBILIZE Boston Study (276 men, 489 women, 64–97 years). Measures included: (1) laboratory-based anteroposterior (AP) path length and average sway speed, mediolateral (ML) average sway and root-mean-square, and area of ellipse postural sway; (2) Short Physical Performance Battery (SPPB); (3) Berg Balance Scale; and (4) one-leg stand. Spearman Rank Correlation Coefficients (r) were assessed among the balance measures.
Area of ellipse sway was highly correlated with the ML sway measures (r >0.9, p < 0.0001), and sway speed was highly correlated with AP sway (r=0.97, p < 0.0001). The Berg Balance Scale was highly correlated with SPPB (r=0.7, p<0.001), and one-leg stand (r=0.8, p<0.001). Correlations between the laboratory- and clinic-based balance measures were low but statistically significant (0.2 < r < 0.3, p<0.0001).
Clinic-based balance measures, and laboratory-based measures comparing area of ellipse with ML sways or sway speed with AP sway, are highly correlated. Clinic- with laboratory-based measures are less correlated. As both laboratory- and clinic-based measures inform balance in older adults but are not highly correlated with each other, future work should investigate the differences.
One-third of U.S. adults, 65 years or older, have one or more falls each year (1). Nearly 40% of these falls result in hospitalization due to a fall-related injury (2). Impaired balance in older adults has been shown to increase the risk of falls (3,4,5) yet there is no consensus on the best way to measure balance (i.e., laboratory- or clinic-based) in this population. Laboratory-based balance tests (e.g. force plate measurements) are conducted in a research setting owing to specialized equipments and typically include multiple series of data collected from platform measurements of sway from center of pressure (COP) in different directions, and require extensive post-measurement data processing. Clinical performance-based measures (e.g., Short Physical Performance Battery (SPPB), Berg Balance Scale, one-leg stand, among others) may be performed in the field and typically would require completion of multiple but common tasks with often less time commitment compared with laboratory measures.
Some studies have suggested that the laboratory-based tests of balance should serve as the gold standard, being that they are more sensitive to slight changes in postural sway (6). However, the clinical tests of balance are often more accessible to clinicians and researchers as they do not require specialized equipment. The Berg Balance Score has gained widespread support for use as a clinical measure of balance, given its documented validity and reliability (7). Some studies have used both the laboratory and the clinical measures of balance (8,9) but this approach may not be feasible in a study of older adults who may tire easily. The issue of respondent burden in elderly participants is also possible with the Berg Balance Scale or the SPPB as each is comprised of multiple time-consuming tasks.
Although the Berg Balance Scale and other clinical balance measures have been compared with platform (laboratory-based) balance measures in small studies of elderly participants (10,11), in individuals who have experienced a stroke (12,13) and in elderly nursing home residents (14), there has been no comprehensive evaluation of the SPPB, Berg Balance Scale, and laboratory-based measures of balance in a large sample of community-dwelling older adults. In addition, there are conflicting results regarding possible sex differences in some of the balance measures (15). The purpose of this study is to compare several laboratory-based and clinical measures of balance to determine: 1) if the clinical tests are equivalent to the laboratory-based measures; 2) whether simpler clinical measures such as the SPPB or the one-leg stand are comparable to the Berg Balance Scale in measuring balance; and 3) whether measures of balance differ by sex in a population-based cohort of older adults. We would expect high correlation within clinic-based measures and among laboratory-based measures but they may differ between clinic-based and laboratory-based measures.
Participants in the current analysis were members of the MOBILIZE Boston Study, a longitudinal study designed to examine novel risk factors for falls in a population-based sample of older adults living around Boston, Massachusetts, USA. Details of the MOBILIZE Boston Study cohort have been previously reported (16,17). In brief, between 2005 and 2008, the study enrolled 765 participants 70 years or older (including 16 of their spouses 64 to 69 years of age) who were able to communicate in English, lived within the Boston area, could walk 20 feet unassisted, and were deemed cognitively intact (i.e., Mini-Mental Status Examination score of 18 or higher).
As previously described (16–18), enrollment included door-to-door recruitment and telephone screening. A group of 4,303 potential participants 70 years of age or older were identified from 5,655 households sampled. Among these 4,303 participants, 1,581 were ineligible and 1,973 could not be located or refused to participate. The standard Council of American Research Organization (CASRO) response rate was 52% after screening for eligibility criteria, and 30% for the door-to-door phase. In comparison with US Census data for the population aged 65 and older in the Boston area, the study sample was representative of Boston area elders in terms of age, sex, race and ethnicity. Participants were examined by research nurses at the MOBILIZE Boston study clinic. The Institutional Review Board at the Hebrew Rehabilitation Center approved the study and all participants provided informed consent.
Trained clinical staff assessed balance among the participants during study visits. Measures of balance included laboratory-based COP data using the Kistler force plate (Model 9286AA, Kistler Instrument Corp., Amherst, NY), and clinical balance tests such as the timed balance component from the SPPB, the score from the Berg Balance Scale, and the ability to stand on one-leg for up to 20 seconds.
Prior to measuring balance using the laboratory-based force plate tests, we performed a daily calibration trial where we placed a 50-lb weight on the force plate and collected data for 30 seconds to ensure accuracy. We then asked participants to stand comfortably in bare feet, approximately hip-width apart, with their arms at their sides, eyes open, and looking straight ahead. For each participant, we conducted 5 trials of “quiet standing” during which COP trajectory data were collected with a single force plate, with each trial lasting 30 seconds in duration. Traditional sway parameters were used to describe the direction, distance, and velocity of a participant’s trajectory, with greater sway indicating poorer balance. Five traditional sway measures have been shown in prospective studies to predict falls (19,20,21,22,23,24). Thus, the current study examined these following measures: (1) mediolateral (ML) average sway, which is the length (mm) of mediolateral sway from geometric center averaged across the COP data; (2) ML RMS, which is the mediolateral root mean square or the standard deviation of all mediolateral measurements (mm); (3) area of ellipse, which is the area that fits 95% of the sway data points (mm2); (4) anteroposterior (AP) path length, which is the overall anteroposterior movement over 30 seconds (mm); and (5) sway speed, which is the combination of AP and ML path length divided by time (mm/s). These measures have been shown to have high inter-rater and test-retest reliability, with intra-class correlation coefficients (ICC) ranging from 0.70 to 0.89 (25). For the majority of the study participants, all measures were averaged across the five trials; in less than 10 participants, the measures were averaged across 4 trials to obtain acceptable reliability (26).
Participants were also asked to perform several clinical balance tests while wearing their own typical shoe-wear (no participants wore high heels during this test). The balance component of the SPPB (27,28) included 10-second timed measurements of unsupported standing with feet in a side-by-side parallel stand (score of 1=able to hold for 10 seconds, 0=unable), semi-tandem foot stand with the heel of one foot placed to the side of the big toe of the other foot (score of 1=able to hold for 10 seconds, 0=unable), and tandem foot stand with the heel of one foot placed directly in front of the toes of the other foot (score of 2=able to hold for 10 seconds, 1=able to hold 3–9 seconds, 0=unable), for a total scored range of 0 to 4. The balance component of the SPPB has been shown to have good reliability with ICCs ranging from 0.70 to 0.82 (29).
The Berg Balance Scale (30) has an overall range of 0 to 56, and is comprised of 14 items (or tasks) with each item score ranging from 0 to 4. The Scale includes timed tests of: 1) able to place feet together independently and standing unsupported for up to 1 minute; 2) standing unsupported one foot in front of the other for up to 30 seconds; 3) sitting to standing/single chair stand; 4) transferring from one chair to another; 5) turning 360 degrees; 6) reaching forward with outstretched arm while standing; 7) standing unsupported for up to 2 minutes without holding onto anything for support; 8) sitting with back unsupported and feet supported on floor or on a stool; 9) standing to sitting; 10) standing unsupported with eyes closed for 10 seconds; 11) picking up an object from the floor and returning to a standing position; 12) turning to look behind over left and right shoulder while standing; 13) placing alternate foot on step or stool while standing unsupported; and 14) standing on one leg for up to 20 seconds. The following is an example of the scoring technique for item 1, placing the feet together independently and standing unsupported for up to 1 minute. The participant would have a code of 0 if the person needed help to attain position and unable to hold for 15 seconds; 1 if needed help to attain position but able to stand 15 seconds feet together; 2 if able to place feet together independently but unable to hold for 30 seconds; 3 if able to place feet together independently and stand 1 minute with supervision; 4 if able to place feet together independently and stand 1 minute safely. The Berg Balance Scale has been shown to have high inter and intra-rater reliability with ICCs of 0.98 and 0.99, respectively (31).
In our study, we also examined this last component of the Berg Balance Scale, the one-leg stand (time in seconds to stand on one leg without holding on for support), separately to determine its correlation with the overall Berg Balance Scale, as well as with the SPPB, and the force plate platform COP balance measures since the one-leg stand component has also been associated with falls in other studies of older adults (32,33). For all clinical balance measures examined in the current study, higher values indicated better balance.
Using balance data collected from participants at the baseline MOBILIZE Boston examination (entered and verified from October 2008), we generated descriptive statistics including medians, range, means and standard deviations of the balance measures for the overall group, and separately by sex. We compared differences in distributions between men and women using the Wilcoxon Rank Sum Tests. Spearman rank correlation coefficients were generated to determine associations among the different measures of COP-based static balance, among the different clinic-based measures of balance, and between the static balance and the clinic-based balance measures for the entire group and by sex. We also examined possible sex differences in the correlation coefficients after normalizing the static balance measures by accounting for height differences between men and women (34). More specifically, COP measures were divided by body height to account for different ranges of heights in women and men. Moreover, we used generalized linear regression to examine the association between COP-based static measures of balance with those from clinic-based measures, and to formally test for interaction between sex and clinic-based balance measures in predicting COP-based measures adjusting for height, weight, and age.
We used a two-sided p-value level of 0.05 to indicate statistical difference from zero or comparison to the reference group. All analyses were conducted using the SAS statistical analysis package, version 9.1 (SAS Institute, Cary, NC).
Baseline characteristics of study participants and balance measures are presented in Table 1. The mean age of participants was 78 years with a range of 64 to 97 years. In general, men had a higher degree of sway than women in three of the five COP measures, indicating poorer static balance. Specifically, men had higher ML average sway, ML RMS, and area ellipse sway than women (all p values < 0.0001). However, men had relatively better clinic-based balance measures as indicated by the balance component of SPPB, the Berg Balance Scale, and the one-leg balance measures (all p values < 0.002).
The unadjusted overall and sex-specific Spearman Rank correlation coefficients among the five COP static balance measures are presented in Table 2. All correlation coefficients among the different measures of balance were statistically significant (p<0.0001). Nonetheless, area of ellipse was highly correlated with ML (r = 0.91) and ML RMS sway (r = 0.92), but was less correlated with AP sway (r = 0.31). Sway speed was more highly correlated with AP sway (r=0.97) than with sways in the ML directions (0.34 ≤ r ≤ 0.35) and area of ellipse sways (0.36). Comparisons of the AP with the ML (r=0.27) and ML RMS (r=0.28) balance measures were less correlated. This general pattern was similar for both men and women. However, men had higher correlation coefficients than women when comparing sway speed with ML (r=0.44 vs. r=0.27), ML RMS (r=0.46 vs. r=0.28), and area of ellipse sways (r=0.48 vs. r=0.29). Similar sex differences were observed when comparing AP sway with sway in the ML directions and with area of ellipse sway. These sex-specific patterns remained even after normalizing the static balance measures by scaling them to account for height (data not shown).
The unadjusted overall and sex-specific Spearman rank correlation coefficients of the COP-based static balance measures with the clinical balance measures, and those among clinic-based measures, are presented in Table 3. Although all correlations were statistically significant, those between static measures and clinic-based measures of balance were generally low, with coefficients ranging from 0.16 to 0.29 overall. Among the clinic-based balance measures, the balance component of SPPB was highly correlated with Berg Balance Scale (r=0.74), and with the one-leg stand (r=0.62), as was the correlation between the Berg Balance Scale and the one-leg stand (r=0.82). These general patterns of associations were similar for both men and women. Again, coefficients were higher for men than women when comparing sway speed or AP sway with each of the clinic-based measures of balance. These sex-specific differences were observed even after the COP-based measures were normalized to account for height (data not shown).
Results from the generalized linear regression indicate that there are sex-differences in the associations between clinic-based and COP-based measures even after accounting for height, weight, and age (Table 4). The magnitude of the association between each of the clinic-based measures of balance and sway speed (as measured by the beta coefficients from the models), was seen to be nearly twice as great in men as in women (all p-interactions < 0.05). Beta coefficients were also higher in men than women between clinic-based measures and ellipse sway, though at borderline statistical significance for SPPB and one-leg stand.
In this cross-sectional analysis of balance measures in a population-based cohort of older adults, we found that within the measures of COP-based static balance, the area of ellipse sway was much more strongly correlated with the ML than with AP measure of balance while sway speed was more strongly correlated with AP than with ML measures. Moreover, these static balance measures were weakly correlated with the clinic-based balance measures, while the clinic-based balance tests were strongly correlated with each other, including the one-leg stand. Correlations were higher in men than in women when comparing sway speed or AP sway with ML, ML RMS, area of ellipse, and clinic-based measures of balance, even after accounting for differences in height.
Some of the correlation coefficients among balance measures were modest (range: 0.221 to 0.997 among COP-based measures) though all of them were statistically significant, possibly owing to the large sample size of the study population. Such modest correlation coefficients between COP-based static balance and clinical balance measures suggest that static posture and clinic-based balance instruments may capture different aspects of balance. For example, postural sway may be more sensitive to sensorimotor function or impairment than clinical measures of balance (35). Furthermore, Frykberg et al. (12) found poor correlations between total Berg Balance Scale with the quiet stand COP-based force plate measures in a group of twenty subjects (mean age 50 years) who had experienced a stroke more than 6 months prior to study participation. Once Frykberg and colleagues separated the Berg Balance Scale into components of “maintaining a position” (including standing or sitting unsupported or standing with eyes closed) and “dynamic balance” (including transfers or picking up objects) the correlation coefficient between the “maintaining a position” and the average AP sway speed increased to 0.5. They reported that the “maintaining a position” component of Berg Balance Scale would better mirror the static balance measures of the force plate. Yet, the SPPB, which should be similar to the “maintaining a position” component of the Berg Balance Scale, did not show a higher correlation with the COP-based static balance measures in our study. These results imply that the lab- and clinic-based measures may possibly measure different aspects of balance, that they may complement each other, or that one may be a poorer measure of balance than the other. It is also possible that one or the other might not truly be measuring balance. Further investigation of this matter appears to be warranted.
However, it is also possible that standing barefoot for static balance measures versus wearing shoes for the clinical balance measures may explain some of the differences between these measures. Although bare feet might allow greater sensory feedback, most researchers believe that wearing shoes improves balance (36) compared to bare feet; others believe it is the type of shoes that may improve balance (37,38). We are uncertain as to whether going barefoot or wearing shoes can entirely explain the lower correlation between COP-based static and clinical balance measures.
The high correlations among the various clinic-based balance tests were not unexpected. First, two of the three SPPB balance items (side-by-side and tandem balance) were also part of the 14-item Berg Balance Scale (items 1 and 2). Also, Berg Balance Scale was highly correlated with the timed one-leg stand possibly because the one-leg stand was one of the most challenging tasks among all the Berg Balance Scale items (9). It is entirely plausible that a participant’s ability to successfully complete the one-leg stand would enable a better overall BBS score.
It is unclear, however, why men had higher associations than women in our study when comparing AP or sway speed with ML and area of ellipse sways, as well as when comparing each of the clinical measures of balance with sway speed or ellipse sway, even after accounting for differences in height. While Bryant and colleagues (15) found no statistically significant differences between men and women in their average COP-based ML and AP sways when the participants’ eyes were opened (whether or not the data were normalized by height) we found statistically significant differences between men and women in their COP-based AP and ML sways with eyes opened, even after taking height into account (data not shown). There are several differences between our study and that from Bryant et al. For each of our COP-based measure of balance, we used the average of 5 trials while Bryant used the average of 3 trials. Moreover, Bryant’s study included 44 men and 53 women while our study included 276 men and 489 women. Thus, our study may have more stable estimates and better power to detect significant differences between men and women for some of these measures. Nevertheless, there may not be any biologic mechanism underlying the observed differences between men and women in the correlations between AP or sway speed with ML and area of ellipse sways, or between each of the clinical measures of balance with sway speed or ellipse sway.
The MOBILIZE Boston population was a group with good balance on average compared to a hospital- or nursing home-based group of older adults. Thus it is possible that differences in variability or strength of associations between COP-based static balance and clinical balance measures could be observed in populations with clinical conditions. It is unclear what other aspects of balance could explain the significant but moderate correlations between the static and clinical balance measures, and possible sex differences in the correlations between sway speed or AP sway with many of the other measures of balance, as normalizing by height did not change the results. Future research should explore explanations for these differences.
Our study has several limitations. First, we chose the 5 COP-based sway measures because they have been reported to be highly correlated with falls in older adults (19–24). It is possible that results would have been different had we included other more comprehensive static balance measures. Nevertheless, as indicated in a systematic review by Ruhe et al.(26), no single COP measure is more reliable than the others, but any sway balance measures should include both a parameter of distance (e.g., area of ellipse) and time-distance (e.g., velocity or sway speed), as we did in our study. In addition, our measures of COP-based sway did not account for differences in base support or width of feet as these data were not collected; however, all participants were instructed to stand with legs approximately hip width apart so there were no extremes of the base of support. It is possible that not standing with feet together may account for the higher correlation between mediolateral laboratory measures, as the base of support affects ML sway differently from AP sway (39,40). Finally, our study did not formally address measures of possible reduction in burden to participants regarding time and effort in using the SPPB or the one-leg stand as a sole clinical balance measure instead of the Berg Balance Scale or the COP-based measures. The SPPB or the one-leg stand may be preferable to many clinicians given that the one-leg stand involves a single task, and the balance component of the SPPB involves 3 items to complete compared to the 14 items in the Berg Balance Scale; however, it is unclear whether it can reliably measure balance in relation to an outcome. Reducing patient burden by limiting the number of tasks in a balance study is appealing in terms of time, cost and retention of study participants. Clinical measures are more complex and integrated measures of balance than laboratory-based measures (which are often used to investigate mechanisms). We view our results as in agreement with choosing a clinic-based measures of balance for our purposes in future epidemiologic studies. Nonetheless, it is up to researchers to choose the appropriate clinic-based balance measure that will be sufficient for their study needs. Future studies could compare the validity and reliability of using as few measures of balance as possible to reduce burden on elderly participants, in particular examining whether the one-leg stand can be the sole clinical measure of balance in relation to a specific outcome.
Our study concurrently examined several comprehensive classes of balance measures using validated instruments, providing a unique opportunity to examine the associations between clinical and laboratory-bases balance measures. Results suggest that there may be sex differences when comparing sway speed or AP sway with measures of sway in the ML direction and area of ellipse, and with each of the clinic-based measures of balance. Moreover, our study participants were from a population-based sample of community-dwelling older men and women. Results that are generalizable to healthy older adults aging in place may be more useful in the creation of a “gold standard” than findings from studies conducted in institutional settings.
The study results show strong agreements among clinic-based balance measures (Berg, SPPB and one-leg stand) and among lab-based balance measures (AP with sway speed, and ML with area of ellipse sway), respectively. However, agreements between clinic and lab-based measures were modest, suggesting these two types of measures may capture different aspects of balance and likely complement each other. Since there exist neither consensus nor any guidance on how to choose these measures for research, further investigation on the relationships among these measures seems warranted.
The authors acknowledge the MOBILIZE Boston research team and study participants for the contribution of their time, effort, and dedication. We sincerely thank Dr. Jennifer Kelsey for her critical review of the manuscript drafts.
This work was funded with grant support from NIH grants AG026316, AG026316-03S1 and AG028738, as well as the HRCA/Harvard Research Nursing Home Program Project (NIH grant AG004390). The study sponsors, however, have no involvement in the study design, collection, analysis, or interpretation of the data; or in the writing and submission of this manuscript for publication.
Conflict of Interest Statement
The authors have no financial or personal relationships with other people or organizations that could bias our research.