| | Which Impairments Are Most Associated With High Mobility Performance in Older Adults? Implications for a Rehabilitation PrescriptionAbstract Bean JF, Kiely DK, LaRose S, Leveille SG. Which impairments are most associated with high mobility performance in older adults? Implications for a rehabilitation prescription. ObjectiveTo test which rehabilitative impairments are associated with higher mobility performance among community-dwelling, mobility-limited older adults. DesignCross-sectional analysis of baseline data from participants within a randomized controlled trial. SettingOutpatient rehabilitation research center. ParticipantsCommunity-dwelling older adults (N=138; mean age, 75.4y) with mobility limitations as defined by the Short Physical Performance Battery (SPPB). InterventionsNot applicable. Main Outcome MeasuresBalance measured via the Berg Balance Scale, leg strength, leg velocity, submaximal aerobic capacity, body mass index (BMI), and mobility performance as measured by the SPPB. ResultsEach of the 5 physiologic attributes (unipedal balance, leg strength, leg velocity, submaximal aerobic capacity, BMI) was categorized into tertiles by using lower values as reference for impairment status. Within an adjusted model, measures associated with higher SPPB performance (>9) included a BBS score greater than or equal to 54 (odds ratio [OR]=4.54; 95% confidence interval [CI], 1.11–18.60), leg strength greater than or equal to 21.5N/kg (OR=30.35; 95% CI, 5.48–168.09), leg velocity .0101 to .0129m·s−1·kg−1 (OR=5.31; 95% CI, 1.25–22.57), and leg velocity greater than or equal to .0130m·s−1·kg−1 (OR=22.86; 95% CI, 3.88–134.75). ConclusionsOur investigation highlights the importance of rehabilitative impairments in leg strength, leg velocity, and balance as being associated with mobility status as measured by the SPPB. In our sample of participants within an exercise trial, submaximal aerobic capacity and BMI status were not associated with mobility performance. These findings suggest that the augmentation of not only leg strength and balance but also leg velocity may be important in the rehabilitative care of mobility-limited older adults. List of Abbreviations: BBS, Berg Balance Scale, BMI, body mass index, CI, confidence interval, DLP40, double leg press power measured at 40%, ETT, exercise tolerance test, OR, odds ratio, RM, repetitions maximum, SPPB, Short Physical Performance Battery MOBILITY PERFORMANCE testing, defined as the measurement of observed performance of a physical task under standardized conditions, has been advocated as an important screening test for older adults in the primary care setting.1, 2 This emphasis stems mainly from reports that scores on performance tests are predictive of subsequent adverse outcomes such as falls, mortality, institutionalization, and disability even after controlling for disease status and comorbidity.2, 3, 4 The SPPB is perhaps the most well-characterized physical performance test. Independent of age and sex, SPPB scores are predictive of multiple adverse outcomes including hospitalizations, nursing home admission, disability, and mortality.3, 4 Furthermore, these findings have been observed among both healthy and disabled cohorts of older adults.3, 4 Subsequent investigations have explored the use of the SPPB within routine primary care.5, 6 Consequently, if patients were indeed screened for performance on the SPPB, those who perform poorly would likely be referred for rehabilitative care to enhance mobility. Currently, however, there is no consensus on which impairments should be prioritized in the rehabilitative care for older adults with mobility problems. It is important to understand disablement terminology when considering the role of rehabilitation. Impairments represent deficits at the level of an organ system, which cause limitations in the performance of a physical task.7 When limitations become too profound for a person to fulfill their normal domestic or societal role, he/she is considered disabled. Ideally, rehabilitation will treat impairments that are modifiable through care, thereby correcting physical limitations and potentially ameliorating disability. We term these impairments as rehabilitative impairments. Impairment-based care is more than theoretic. For example, Gill et al8 showed that an impairment-based approach to homecare can ameliorate activities of daily living-related disability among older adults at risk for disability. They coined this approach to disability prevention as “prehabilitation.” Another recent investigation by Pahor et al9 showed improvements in SPPB performance with community-based exercise programs. Both of these intervention studies investigated rehabilitative impairments in strength, endurance, and balance. However, other rehabilitative impairments not targeted by Gill or Pahor have been identified as important. Leg muscle power, the product of leg strength (force) and leg velocity has been identified as more relevant to mobility performance than leg muscle strength alone.10 Also, although obesity has been characterized as a disease by some,11 other investigations12, 13, 14 have recognized that because obesity may be modifiable through physical activity, it may also be considered a rehabilitative impairment that is relevant to mobility performance. For older patients vulnerable to fatigue and frailty, optimal rehabilitation should be directed toward those few rehabilitative impairments most influential to mobility performance. These factors should be the focus of a rehabilitative prescription.15 However, at the current time, the relative importance of different rehabilitative impairments believed to influence mobility is not known. Therefore, we conducted a cross-sectional analysis among community-dwelling, mobility-limited older adults undergoing both rehabilitative impairment testing and physical performance testing. We wished to identify rehabilitative impairments most strongly associated with SPPB score (fig 1). Methods  This study is a cross-sectional analysis of baseline data from a randomized controlled trial of exercise among 138 mobility-limited older adults. Our methods and procedures for this investigation were approved by the Partners Healthcare Institutional Review Board and conform to the Helsinki Declaration. Recruitment of Participants Initially, 590 inquiries were solicited via advertising in newspapers, direct mailings, referrals from primary care providers, and telephone screenings. Of these, 260 people were identified as potentially eligible and attended an initial screening assessment at our facility. Screening Process Participants included in the study were community-dwelling older adults (age, ≥65y) with SPPB scores between 4 and 10 who were able to climb a flight of stairs independently or using a device (eg, cane). This ensured that our study subjects did indeed manifest mobility limitations but were able to undergo our extensive physical performance testing. Exclusion criteria were unstable acute or chronic disease, a score of less than 23 on the Folstein Mini-Mental State Examination,16 a neuromusculoskeletal impairment limiting participation in further performance testing, participation in a resistance training program, or a treadmill ETT with positive findings for unstable cardiovascular disease. After providing informed consent, participants underwent a comprehensive history and physical examination that was conducted by a physiatrist with geriatrics expertise (J.B.). At the completion of the physical examination, all active medical conditions were recorded for each participant. Active medical conditions were defined as either: (1) any condition for which a participant was currently receiving treatment or (2) a condition requiring medical treatment within the past year. Medical records were requested from participants' primary care physicians to corroborate these findings. Specifically, the presence of diabetes mellitus and cardiovascular, neurologic, pulmonary, and musculoskeletal diseases was ascertained. Any other active medical condition was characterized as “other” disease. Cardiovascular disease was defined as (1) a chronic cardiovascular diagnosis and (2) a current daily medication indicated by class (eg, beta-blocker, angiotensin-converting enzyme inhibitor, and so on) for the treatment of cardiovascular disease. Depression was defined as a score of greater than or equal to 16 on the Center for Epidemiological Study Depression Scale.17 The use of prescription, over-the-counter, and herbal remedies and supplements was recorded by self-report. Medications were classified by indication to those that were provided to treat cardiovascular disease, depression and anxiety, osteoporosis, and pain (analgesics). Beta-blocker use was also separately noted. On completion of the initial screening, 92 people could not participate in the study because of exclusion criteria, and 30 chose not to commit to the study, leaving 138 participants. Performance testing was completed over 1 to 2 subsequent visits depending on participant availability. Measures used for this analysis were all completed within the first 2 visits, which were scheduled within 1 week of each other. For all measures, before testing, all participants received a full explanation of the procedures and were familiarized with the testing protocols including a demonstration by the examiner. Impairment Measures Lower-limb strength and power were measured by using a pneumatic double leg press resistance machinea as previously described.18 The machine calculates strength based on data from a pressure transducer mounted on a piston that moves as force is applied to the lever arm. Electronic software calculates the average power during a repetition by sampling the position of the piston 64 times per second. The highest power between 5% and 95% of the concentric phase is provided as output on the machine's display. Briefly, the 1 RM was determined by progressively increasing the resistance for successive repetitions until the participant could no longer move the lever arm 1 time through the full range of motion and was recorded in Newtons. Maximum power was measured as the best of 5 repetitions. Maximum power was obtained at 40% and 70% of the 1 RM, in which participants performed the concentric action of each repetition as quickly as possible. These 2 intensities were chosen to represent double leg press muscle power production in watts: (1) relatively high-force and low-velocity 70% 1 RM (double leg press power measured at 70%) and (2) low-force and high-velocity 40% 1 RM (DLP40). This methodology has been reported to be both valid and reliable.19 The maximal leg velocity was derived from the maximal power measurement at DLP40 by the following formula: maximal limb velocity equals maximal power recorded at DLP40/.40(1 RM). Both strength and velocity were normalized per kilogram body mass. Balance was assessed by the BBS.20, 21 Briefly, the BBS is a commonly used balance test in which the patient is asked to complete 14 tasks that are scored on a scale of 0 (cannot perform) to 4 (normal performance) with a maximum achievable score of 56. The BBS includes activities encountered in daily life such as sitting, standing, leaning over, and stepping and is a valid measure of fall risk.20, 21 Participants underwent the screening ETT on a treadmill and the duration of the test (measured in minutes) served as a measure of submaximal aerobic capacity. This approach has been used successfully in previous investigations among similar cohorts.22, 23 For safety purposes, participants were required to hold on to a horizontal bar at the front of the treadmill with at least 1 arm at all times. All exercise stages were 3 minutes in duration. The first 3 stages were tested at the participant's habitual gait speed at 0%, 5%, and 10% grades of inclination, respectively. Habitual gait speed was measured as the mean of 2 trials by using an ultrasonic gait speed monitorb. Thereafter, treadmill speed was increased to 125% of habitual gait speed at 12% grade, increasing grade by 2% increments each subsequent stage until test termination. At the end of each stage, blood pressure was recorded, and perceived exertion was measured by using the Borg Scale.24 Testing was terminated when a participant achieved a Borg Scale rating of 17 or greater, representing perceived exertion of “very hard.” Testing was stopped before this point in time if a participant experienced significant fatigue or any adverse symptoms. One participant refused to perform the ETT. Their data were retained with respect to all other measures. Height and weight were measured during the initial physical examination by using a calibrated scale and stadiometer. The participant wore only undergarments during this aspect of testing. BMI was calculated by the formula mass (kg)/height (m)2. Weight status was characterized by using standard cut points: overweight (BMI ≥25kg/m2 to <30kg/m2) and obesity (BMI ≥30kg/m2).11 Outcome The SPPB is a well-established, reliable, and valid measure of lower-extremity performance. Testing involves an assessment of standing balance, the timed usual pace 4.0-m walk, and timed test of 5 repetitions of rising from a chair and sitting down. All times are measured to the nearest 0.01 second by using a stopwatch. Each of the 3 aforementioned tests is scored between 0 and 4 and summed (0 [disabled]–12 [independent]). The SPPB has been found to predict hospitalizations, mortality, and disability over 1 to 6 years in several older populations.3, 4 SPPB was measured in each of 2 sessions within a 2-week period, and the average of the 2 SPPB scores was used in this analysis. SPPB scores were categorized according to validated cut points by Guralnik et al4 in which scores greater than 9 were considered to be consistent with mild-no mobility limitation. Covariates Covariates that were evaluated for inclusion in the analytic models included general patient characteristics (age, sex), general factors associated with health status (number of chronic conditions, number of medications), presence of specific medical conditions (neurologic disease, musculoskeletal disease, diabetes, cardiovascular disease, depression, respiratory disease), and presence of specific types of medications (cardiovascular, beta-blockers, depression). Because there are different conceptual views of BMI, we decided that if obesity status was not a significant predictor as a rehabilitative impairment, we would evaluate its role as covariate when analyzed as a continuous measure. Data Analysis In the first step of our statistical analysis, frequencies, means, SDs, and ranges of all variables were calculated, and the distribution of all variables was inspected. Variables were categorized based on their distribution and clinical significance. Strength and velocity per kilogram body mass, endurance, and balance were grouped within tertiles based on the distribution of the data. Our outcome measure was evaluated as a dichotomous measure, which was an SPPB score greater than 9. Although we recognize statistical limitations in evaluating our predictors in tertiles and using our outcome as a dichotomous variable, we conducted our investigation in this fashion for 4 main reasons: (1) we wished to evaluate our predictors relative to a low category of performance, which is conceptually consistent with the definition of impairment; (2) we wished to predict higher mobility status above a threshold associated with a minimal risk for adverse outcomes to mirror a rehabilitative context in which the goal of treatment would be to achieve a clinically relevant level of function; (3) to be consistent with the prior literature, which evaluated impairments as cut points25, 26; and (4) to frame our study conceptually in a fashion that would be easy for clinicians to interpret. Reference categories were the category of the lowest values; for all measures, higher scores indicated better performance. Initially, all predictors (rehabilitative impairments) were evaluated for their bivariate association with the outcome (SPPB score, >9). Additionally, the bivariate relationships of all rehabilitative impairments were evaluated for any significant collinearity, which could influence inclusion in a multivariate model. In a second step, consistent with the aims of the investigation, all 5 rehabilitative impairments were included in a logistic regression model predicting the outcome without inclusion of any covariates. Those rehabilitative impairments that did not achieve statistical significance were eliminated from the model. Next, we individually evaluated each potential covariate in a model including those predictors that achieved statistical significance. A covariate was defined as statistically significant if the resulting model manifested a greater than 10% change in the coefficient estimates of any of the significant independent variables. The final multivariate logistic model was then created from the significant predictors from among the 5 impairments and any potential covariates that met criteria for inclusion. The residuals were inspected to ensure that the final model was consistent with its statistical assumptions. SASc was used in all analyses.27 Final results were considered statistically significant if they achieved a significance level of P less than .05. Results As shown in table 1, participants had a mean age of 75.4 years and were predominately women (69%) and white (83% vs 14% black and 3% other). On average, participants had 5.6 chronic conditions and used 4.3 prescription medications. Only 14% of patients did not have at least 1 musculoskeletal condition, and 25%, 30%, and 31% of the participants manifested 1, 2, or greater than or equal to 3 musculoskeletal conditions, respectively. Twenty-five percent of participants did not carry a cardiovascular diagnosis, and three quarters of participants had 1 or more cardiovascular conditions. The prevalence of diabetes, neurologic disease, respiratory disease, or depression (Center for Epidemiologic Studies score >16) was 13%, 25%, 10%, and 13%, respectively. Nearly two thirds of participants were taking 1 or more cardiovascular medications. The average baseline SPPB score ± SD was 8.7±1.5. The average BMI of the cohort was 27.8kg/m2, and 28% were obese. The mean BBS score was 50.6, with the tertile cut points being less than 50 and greater than or equal to 54. The average baseline values of leg strength were (18.9N/kg) and leg velocity (.0119m·s−1·kg−1). The tertile cut points for strength were 12.9 and 21.5N/kg, and for velocity they were .0101 and .0130m·s−1·kg−1. The average ETT duration was 9.4 minutes with tertile cut points of 8.3 and 10.3 minutes. Rehabilitative impairments (table 2) were weakly correlated with one another (r≤.31).28 SPPB status also had a weak association with BBS (r=.35), leg strength (r=.23), and leg velocity (r=.23). Table 3 represents the final multivariate logistic regression model. Among the potential covariates, only age, sex, use of cardiovascular medications, and presence of depression met statistical criteria for inclusion in our adjusted multivariate model. Also, although BMI did not meet criteria for inclusion as an independent variable, it did meet statistical criteria as a covariate. Within the unadjusted model, both the second and third tertiles of balance (BBS score, 50–53: OR=4.28; 95% CI, 1.50–12.26; BBS score ≥54: OR=6.48; 95% CI, 2.13–19.71), leg velocity (leg velocity, .0101–.0129m·s−1·kg−1: OR=3.30; 95% CI, 1.08–10.10; leg velocity, ≥.0130m·s−1·kg−1: OR=6.66; 95% CI, 1.91–23.30), and the highest tertile of leg strength (leg strength ≥21.5N/kg: OR=6.84; 95% CI, 2.27–20.65) were significant predictors. Within the adjusted multivariate model, rehabilitative impairment measures associated with higher SPPB performance included BBS score greater than or equal to 54 (OR=4.54; 95% CI, 1.11–18.60), leg strength greater than or equal to 21.5N/kg (OR=30.35; 95% CI, 5.48–168.09), leg velocity .0101 to .0130m·s−1·kg−1 (OR=5.31; 95% CI, 1.25–22.57), and leg velocity greater than or equal to .0130m·s−1·kg−1 (OR=22.86; 95% CI, 3.88–134.75). Age and sex were statistically significant covariates. Additionally, no interaction existed between leg strength and leg velocity in association with the SPPB score (data not shown). Also, all analyses were reevaluated, with exclusion of the 1 subject who did not complete the baseline ETT. This did not materially alter the findings. Discussion The major finding of this study was that, among well-established rehabilitative impairments associated with mobility status, leg strength, leg velocity, and balance were most strongly associated with mobility performance. In considering subsequent risk for disability, morbidity, and mortality determined by the SPPB, values have been grouped to describe mobility status as follows: disabled (0–3), severe limitation (4–6), moderate limitation (7–9), and mild or no limitation (10–12).4 If indeed, the SPPB were to be used as a clinical “vital sign” as advocated,2 then reduction of limitations or even “achievement” of less severe limitation would be an appropriate rehabilitative goal, which is the reason we created our statistical models to predict higher mobility status. Clinical experience suggests that mobility rehabilitation is very heterogeneous. No specific impairment-based guidelines exist. Therefore, knowledge that these rehabilitative impairments are important may be clinically useful if our findings are replicated in other studies and eventually tested in a randomized trial. Strength and balance are known to be important targets in rehabilitative care of older adults with mobility problems.8, 15, 29 Besides being identified as important rehabilitative impairments individually, these impairments also behave synergistically as coimpairments, leading to an even greater risk for disability.26, 30 In contrast, clinicians rarely prioritize velocity of movement, an important component of muscle power. Only a few recent reports31, 32 have considered the velocity of movement in the context of mobility concerns. Training methods emphasizing the velocity of movement are the basis of intervention studies prioritizing the enhancement of muscle power.31, 33 Our findings further support the key relevance of these methods, which are not components of either nationally advocated exercise programs or a recent multicenter trial of exercise among elderly patients.9, 34 It is interesting that only the lowest tertile of strength and balance were significantly associated with mobility status, suggesting a possible threshold effect. More specifically, this implies that impairment changes among those who are most impaired may have a very direct impact on physical function improvements, although changes in impairment among those less impaired, (eg, among healthier individuals) have little effect on physical function. Similar findings were observed in a previous investigation of the InCHIANTI population and support the reported effect that these impairments may have curvilinear association with mobility status.25, 35 Interestingly, both tertiles of leg velocity had a significant influence on functional performance, suggesting that improvements in leg velocity may have functional consequences for a broader range of individuals. Our study is one of the first to separate out the components of leg power (strength and velocity), showing a sufficiently low level of correlation (r≤.31) making it possible to examine the 2 measures within the same statistical model. A limitation of many prior investigations was that leg power was measured on devices that do not allow for the corresponding values of strength and power to be measured, and analyses were limited because strength and power could not be included in the same statistical model given their high level of correlation.10, 25 Muscle power is gaining recognition as an important factor influencing both mobility and falls.32, 36 Separate investigations have shown that muscle power is more influential on mobility and fall status than strength.25, 36 A challenge in making such comparisons statistically has been that strength is a component of power (power = strength × velocity) and that both characteristics were most effectively evaluated in separate statistical models because of high collinearity. Our investigation builds on other reports evaluating falls that attempted to address these same impairments but did not measure both components in the lower extremities with respect to SPPB performance.32, 36 It is somewhat surprising that BMI status was not associated with mobility performance, especially given reports showing that obesity is associated with disability.37 It did, however, meet statistical criteria for inclusion in our multivariate model as a covariate. We previously mentioned in the introduction the contrasting views as to whether obesity is best characterized as an impairment or a disease. Our findings may support the latter view. Of note, previous studies have suggested that other factors related to obesity including fat mass and weight history may be more important than BMI in predicting physical performance.38, 39 It is also important to recognize that aerobic capacity was not significantly associated with higher mobility performance in our study. This is supported by previous reports addressing multiple factors influencing mobility status40 but may be influenced by our recruitment of volunteers. The impact of obesity and aerobic capacity should be evaluated among a population-based sample before any further mechanistic speculation can be seriously considered. We specifically used empirically derived cut points for both leg strength and leg velocity because clinically relevant cut points using these methods are not yet established. Recent investigations41 have attempted to identify clinically meaningful cut points for strength but were determined by using isokinetic testing. Balance was also categorized into tertiles, and the lowest cut point (BBS<50) corresponded to a score separating low risk from higher risk for subsequent falls.21 Balance is a component of the SPPB and although the standing balance component of the SPPB and the Berg are different measures, there is some overlap in tasks, which may overemphasize the association between the measures we used for balance and mobility. To address this concern, we did perform a post hoc analysis excluding balance (data not shown). This did not materially alter our findings with respect to the other rehabilitative impairments. Even so, this concern reinforces support for complementing physical performance testing with relevant self-report measures.42 Submaximal aerobic capacity has been recognized as more clinically relevant to mobility than maximal aerobic capacity.14, 43 It may be a more significant factor among individuals with more symptomatic cardiovascular or respiratory disease than our study group. Study Limitations Our investigation has limitations. We performed a cross-sectional analysis among individuals who chose to participate in an exercise study. These preliminary findings regarding the influence of rehabilitative impairments must be better understood through a longitudinal investigation of a population-based sample of older adults. Moreover, studying a larger cohort may be more productive in identifying the influence of other potential confounders. Also, a more definitive investigation would include other potentially important rehabilitative impairments recognized to influence mobility, including limited hip range of motion, pain, and muscle power asymmetry.44, 45, 46 Lastly, from a mechanistic standpoint, it is recognized that our leg velocity measure represents a derived measure and not a direct measurement. Additionally, leg velocity may be recorded at higher levels if the resistance was lower than 40% of the 1 RM. However, past investigations47 have characterized 2 critical resistance levels with respect to power output, those being 40% and 70% of the 1 RM, and were therefore used in our investigation. Leg velocity at 40% 1 RM represents the faster of the 2 available values, mirrors previous reports in the literature, and has recognized relevance to many gait-related mobility tasks.31, 47 It would be beneficial to conduct a prospective investigation encompassing a broader array of rehabilitative impairments, with outcomes using both self-report and observed physical functioning. Ultimately, however, the resulting findings of any observation study will need to be tested by using rehabilitative interventions in a randomized controlled trial. Despite these potential limitations, our study is 1 of the few to evaluate multiple rehabilitative impairments in a clinical context that mirrors normal rehabilitative care.40 It is only through a process of identifying those impairments patterns most responsible for mobility decline in older adults that evidence-based interventions can most effectively be developed and tested. Conclusions Our investigation highlights the importance of rehabilitative impairments in leg strength, leg velocity, and balance as being associated with higher SPPB status. Although strength and balance are well established as important rehabilitative impairments commonly targeted in rehabilitative care, our investigation additionally emphasized the importance of leg velocity, which is targeted less frequently by rehabilitative providers. Our study suggests that for older adults with mobility limitations, the rehabilitative prescription to most efficiently and effectively improve mobility should prioritize balance, leg strength, and leg velocity as important rehabilitative impairments. Suppliers References 1. 1Morley JE. Mobility performance: a high-tech test for geriatricians. J Gerontol A Biol Sci Med Sci Aug. 2003;58:712–714. 2. 2Studenski S, Perera S, Wallace D, et al. Physical performance measures in the clinical setting. J Am Geriatr Soc Mar. 2003;51:314–322. 3. 3Guralnik JM, Ferrucci L, Pieper CF, et al. Lower extremity function and subsequent disability: consistency across studies, predictive models, and value of gait speed alone compared with the short physical performance battery. J Gerontol A Biol Sci Med Sci. 2000;55:M221–M231. MEDLINE 4. 4Guralnik JM, Simonsick EM, Ferucci L, et al. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol. 1994;49:M85–M94. MEDLINE 5. 5Cavazzini C, Conti M, Bandinelli S, et al. Screening for poor performance of lower extremity in primary care: the Camucia Project. Aging Clin Exp Res. 2004;16:331–336. MEDLINE 6. 6Bandinelli S, Lauretani F, Boscherini V, et al. A randomized, controlled trial of disability prevention in frail older patients screened in primary care: the FRASI study (Design and baseline evaluation). Aging Clin Exp Res. 2006;18:359–366. MEDLINE 7. 7Verbrugge LM, Jette AM. The disablement process. Soc Sci Med. 1994;38:1–14. MEDLINE |
CrossRef
8. 8Gill TM, Baker DI, Gottschalk M, et al. A prehabilitation program for physically frail community-living older persons. Arch Phys Med Rehabil. 2003;84:394–404. Abstract |
Full-Text PDF (117 KB)
|
CrossRef
9. 9Pahor M, Blair SN, Espeland M, et al.Life Study Investigators Effects of a physical activity intervention on measures of physical performance: results of the lifestyle interventions and independence for Elders Pilot (LIFE-P) study [erratum appears in J Gerontol A Biol Sci Med Sci 2007;62:337]. J Gerontol A Biol Sci Med Sci. 2006;61:1157–1165. MEDLINE 10. 10Bean J, Kiely DK, Herman S, et al. The relationship between leg power and physical performance in mobility-limited elders. J Am Geriatr Soc. 2002;50:461–467. MEDLINE |
CrossRef
11. 11National Heart LaBI. Clinical guidelines in the identification, evaluation and treatment of overweight and obesity in adults. Bethesda: National Institutes of Health; 1998;. 12. 12Messier SP, Gutekunst DJ, Davis C, DeVita P. Weight loss reduces knee-joint loads in overweight and obese older adults with knee osteoarthritis. Arthritis Rheum. 2005;52:2026–2032. MEDLINE |
CrossRef
13. 13Messier SP, Loeser RF, Miller GD, et al. Exercise and dietary weight loss in overweight and obese older adults with knee osteoarthritis: the Arthritis, Diet, and Activity Promotion Trial. Arthritis Rheum. 2004;50:1501–1510. MEDLINE |
CrossRef
14. 14Miller GD, Rejeski WJ, Williamson JD, et al. The Arthritis, Diet and Activity Promotion Trial (ADAPT): design, rationale, and baseline results. Control Clin Trials. 2003;24:462–480. Abstract | Full Text |
Full-Text PDF (170 KB)
|
CrossRef
15. 15Bean JF, Vora A, Frontera WR. Benefits of exercise for community-dwelling older adults. Arch Phys Med Rehabil. 2004;85(7 Suppl 3):S31–S42. MEDLINE 16. 16Folstein MF, Folstein SF, McHugh PR. “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. Psychiatr Res. 1975;12:189–198. 17. 17Radloff L, Lenore S. The CES-D scale: a self-reported depression scale for research in the general population. Applied Psychol Measurement. 1977;1:385–401. 18. 18Bean JF, Kiely DK, LaRose S, Alian J, Frontera WR. Is stair climb power a clinically relevant measure of leg power impairments in at-risk older adults?. Arch Phys Med Rehabil. 2007;88:604–609. Abstract | Full Text |
Full-Text PDF (129 KB)
|
CrossRef
19. 19Callahan D, Phillips E, Carabello R, Frontera WR, Fielding RA. Assessment of lower extremity muscle power in functionally-limited elders. Aging Clin Exp Res. 2007;19:194–199. MEDLINE 20. 20Berg KO, Wood-Dauphinee SL, Williams JI, Maki B. Measuring balance in the elderly: validation of an instrument. Can J Public Health. 1992;83(Suppl 2):S7–S11. 21. 21Shumway-Cook A, Baldwin M, Polissar NL, Gruber W. Predicting the probability for falls in community-dwelling older adults. Phys Ther. 1997;77:812–819. MEDLINE 22. 22Bean JF, Kiely DK, Leveille SG, et al. The 6-minute walk test in mobility-limited elders: what is being measured?. J Gerontol Med Sci. 2002;57:M751–M756. 23. 23Pu CT, Johnson MT, Forman DE, et al. Randomized trial of progressive resistance training to counteract the myopathy of chronic heart failure. J Appl Physiol. 2001;90:2341–2350. 24. 24Borg G. Perceived exertion as an indicator of somatic stress. Scand J Rehab Med. 1970;2:92–98. 25. 25Bean JF, Leveille SG, Kiely DK, Bandinelli S, Guralnik JM, Ferrucci L. A comparison of leg power and leg strength within the InCHIANTI study: which influences mobility more?. J Gerontol Med Sci. 2003;58A:728–733. 26. 26Rantanen T, Guralnik JM, Ferrucci L, Leveille S, Fried LP. Coimpairments: strength and balance as predictors of severe walking disability. J Gerontol A Biol Sci Med Sci. 1999;54:M172–M176. MEDLINE 27. 27SAS. SAS/STAT User's Guide, Version 9.0. Cary: SAS Institute Inc; 2005;. 28. 28Fliess JL. The design and analysis of clinical experiments. New York: Wiley; 1986;. 29. 29Fiatarone-Singh MA. Exercise comes of age: rationale and recomendations for a geriatric exercise prescription. J Gerontol Med Sci. 2002;57A:M262–M282. 30. 30Rantanen T, Guralnik JM, Ferrucci L, et al. Coimpairments as predictors of severe walking disability in older women. J Am Geriatr Soc. 2001;49:21–27. MEDLINE |
CrossRef
31. 31Sayers SP, Guralnik JM, Newman AB, Brach JS, Fielding RA. Concordance and discordance between two measures of lower extremity function: 400 meter self-paced walk and SPPB. Aging Clin Exp Res. 2006;18:100–106. MEDLINE 32. 32Shigematsu R, Rantanen T, Saari P, et al. Motor speed and lower extremity strength as predictors of fall-related bone fractures in elderly individuals. Aging Clin Exp Res. 2006;18:320–324. MEDLINE 33. 33Orr R, de Vos NJ, Singh NA, Ross DA, Stavrinos TM, Fiatarone-Singh MA. Power training improves balance in healthy older adults. J Gerontol A Biol Sci Med Sci. 2006;61:78–85. MEDLINE 34. 34National Institute on Aging. Exercise: a Guide from the National Institute in Aging. Bethesda: National Institute on Aging, National Institute of Health; 1999;. 35. 35Ferrucci L, Guralnik JM, Buchner D, et al. Departures from linearity in the relationship between measures of muscular strength and physical performance of the lower extremities: the Women's Health and Aging Study. J Gerontol A Biol Sci Med Sci. 1997;52:M275–M285. MEDLINE 36. 36Chan BK, Marshall LM, Winters KM, Faulkner KA, Schwartz AV, Orwoll ES. Incident fall risk and physical activity and physical performance among older men: the Osteoporotic Fractures in Men Study. Am J Epidemiol. 2007;165:696–703. MEDLINE |
CrossRef
37. 37Weil E, Wachterman M, McCarthy EP, et al. Obesity among adults with disabling conditions. JAMA. 2002;288:1265–1268. MEDLINE |
CrossRef
38. 38Houston DK, Ding J, Nicklas BJ, et al. The association between weight history and physical performance in the Health, Aging and Body Composition study. Int J Obes (Lond). 2007;31:1680–1687.
CrossRef
39. 39Lebrun CE, van der Schouw YT, de Jong FH, Grobbee DE, Lamberts SW. Fat mass rather than muscle strength is the major determinant of physical function and disability in postmenopausal women younger than 75 years of age. Menopause. 2006;13:474–481. MEDLINE |
CrossRef
40. 40Sakari-Rantala R, Era P, Rantanen T, Heikkinen E. Associations of sensory-motor functions with poor mobility in 75- and 80-year-old people. Scand J Rehabil Med. 1998;30:121–127. MEDLINE |
CrossRef
41. 41Manini TM, Visser M, Won-Park S, et al. Knee extension strength cutpoints for maintaining mobility. J Am Geriatr Soc. 2007;55:451–457. MEDLINE |
CrossRef
42. 42Reuben DB, Seeman TE, Keeler E, et al. Refining the categorization of physical functional status: the added value of combining self-reported and performance-based measures. J Gerontol A Biol Sci Med Sci. 2004;59:1056–1061. MEDLINE 43. 43Alexander NB, Dengel DR, Olson RJ, Krajewski KM. Oxygen-uptake (VO2) kinetics and functional mobility performance in impaired older adults. J Gerontol A Biol Sci Med Sci. 2003;58:734–739. MEDLINE 44. 44Kerrigan DC, Todd MK, Della Croce U, Lipsitz LA, Collins JJ. Biomechanical gait alterations independent of speed in the healthy elderly: evidence for specific limiting impairments. Arch Phys Med Rehabil. 1998;79:317–322. Abstract |
Full-Text PDF (785 KB)
|
CrossRef
45. 45Leveille SG, Bean J, Ngo L, McMullen W, Guralnik JM. The pathway from musculoskeletal pain to mobility difficulty in older disabled women. Pain. 2007;128:69–77. Abstract | Full Text |
Full-Text PDF (312 KB)
|
CrossRef
46. 46Skelton DA, Kennedy J, Rutherford OM. Explosive power and asymmetry in leg muscle function in frequent fallers and non-fallers aged over 65. Age Ageing. 2002;31:119–125. MEDLINE |
CrossRef
47. 47Cuoco A, Callahan DM, Sayers S, Frontera WR, Bean J, Fielding RA. Impact of muscle power and force on gait speed in disabled older men and women. J Gerontol A Biol Sci Med Sci. 2004;59:1200–1206. MEDLINE a Departments of Physical Medicine and Rehabilitation and Medicine, Harvard Medical School, Boston, MA b Spaulding Rehabilitation Hospital, Boston, MA c Hebrew Senior Life, Boston, MA d Division of Primary Care, Beth Israel Deaconess Medical Center, Boston, MA  Reprint requests to Jonathan F. Bean, MD, MS, MPH Spaulding Cambridge Outpatient Center, 1575 Cambridge St, Box 9, Cambridge, MA 02138
No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the authors or on any organization with which the authors are associated. PII: S0003-9993(08)01487-1 doi:10.1016/j.apmr.2008.04.029 © 2008 American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved. | |
|
FULL TEXT01487-1/journalimage?img=PIIS0003999308014871.gr1.lrg.gif&fig=fig1&kwhquery=&issn=0003-9993&ishighres=false&allhighres=false&free=yes','journalimage');)
