In older adults, functional fitness is characterized by the ability to perform activities of daily living1 and declines approximately 2.7% per year.2 Currently, 50% of older adults report at least 1 functional limitation3 resulting in reduced quality of life,2 increased entry into long-term care facilities, and increased risk of falls.4–6 While various assessments are used to determine functional fitness, including chair-rise performance,1 walking speed,7 and stair-climb power,8,9 a single, universal measure accepted among all clinicians and practitioners does not exist.
Muscular power is positively correlated with measures of functional fitness10,11 and is defined as the ability of a muscle to produce force quickly.10,12 With age, muscular power decreases and is nearly 50% lower in 80-year-old adults when compared with adults in their 20s.2,10,13 Muscular power is required to perform activities of daily living such as crossing the street, rising from a chair, and maneuvering through the house; therefore, maintenance of muscular power throughout the lifespan is imperative. While various assessments exist to measure muscular power, many may not be appropriate for use with older adults (ie, vertical jump). Recently, stair-ascension performance, a field measure of lower-limb muscular power, was identified as a clinically relevant assessment of functional fitness.8,9,14 In fact, older adults with stair-climb power in the highest quartile had nearly a 7-fold decrease in moderate mobility disability.9 Assessment of lower-limb muscular power may assist clinicians in making decisions about their prognosis and therapeutic modalities.
In addition to functional fitness, muscular power is directly associated with walking velocity, a well-known measure of mobility disability.7,15,16 In terms of self-selected walking velocity, mobility disability has been defined as a value less than 1.0 m/s of adults older than 65 years15; however, discrepancies exist. Walking velocities of community-dwelling older adults without known functional limitations range from 1.0 to 1.4 m/s;17–24 yet, values as high as 1.2 m/s have been associated with moderate mobility limitations among older adults.25 Mobility disability manifests over time and is preceded by preclinical disability not detected with traditional assessments.26 With the wide range of scores and no definitive value for higher-functioning older adults, additional measures of functional fitness are warranted.
Further examination of the gait patterns of older adults may provide additional information about subtle changes occurring throughout the aging process. Various parameters of gait (ie, double support time, cadence, velocity) have been associated with falling,5,27 mobility disability,7,28 all-cause mortality,17 and survival rate among older adults.29–31 While previous research has examined gait parameters of older adults, the extent to which functional fitness of the aging adult impacts these gait parameters is unclear.19,28,31–39 It is important to examine the influence of functional fitness on mobility among older adults. Therefore, the purpose of the present study was to investigate differences in selected parameters of habitual walking between high and low functionally fit older adults.
Twenty older adults (8 males and 12 females) volunteered for the present investigation. Participants were recruited from Northwest Arkansas via posted flyers at local community centers, e-mail notification, and word of mouth. All participants were free from uncontrolled cardiovascular, metabolic, and pulmonary diseases. Each participant signed a previously approved informed consent from the University of Arkansas. Demographic information is given in Table 1. The average age of the sample was 71.6 (SD = 5.6) years and 60% of the total sample were women. No sex differences existed for any variable.
Upon arrival to the laboratory, all participants were screened for cognitive impairment using the Mini-Mental State Examination40 before any other assessments were performed. A cutoff value of 2441 was used for the current investigation; no participant scored less than this value. A health history questionnaire and informed consent were completed before any physical measures were obtained to ensure that no participant had an uncontrolled cardiovascular, metabolic, or pulmonary issue. Initially, height and weight were measured using a physician's balance scale and stadiometer (Detecto, Webb City, Missouri). Body composition was determined by dual energy x-ray absorptiometry (GE, Madison, Wisconsin).
Functional fitness was measured using a stair-climb test.8,42 Each participant was instructed to ascend 1 flight of stairs (9 steps) as “quickly as safely possible.” They were instructed to use only the handrail if they felt that it was needed for safety and stability. The participants were positioned at the bottom of the stairs and began on the command “Go,” when the time was started; the time was stopped when both feet touched the landing. Three trials were repeated and the best trial was used in the analysis. Stair-climb power (watts) was calculated by the product of vertical height of the stairs (meter) and the body weight of the participant (newton), divided by their best time (second). Relative power (watt per kilogram) was calculated by dividing power by their body mass (kilogram). Relative power was used to create the 2 functional fitness groups. These groups were determined on the basis of previously published results.8 A cut point of 3.76 W/kg was determined as a value that represented community-dwelling older adults with mobility limitations (Short Physical Performance Battery [SPPB] 4-10).8 Test-retest reliability was r = 0.99 elsewhere8 and 0.93 in the present investigation.
Habitual gait velocity was calculated over a 20-m distance.43 The floor was marked with tape to indicate the start (0 m) and stop (20 m) points. Participants were asked to walk at their “usual walking speed” for 20 m in a well-lit hallway. All participants wore comfortable footwear. The participants were instructed to stand with their toes just behind the start line and to begin walking on the command “Go.” Gait velocity was measured with an infrared control system attached to a timer/counter (Lafayette Instruments, Lafayette, Indiana); the timer started when the participants passed through the first timing gate (0 m) and stopped when they passed through the last timing gate (20 m). Two trials were completed and the fastest time was recorded. Test-retest reliability ranged from 0.90 to 0.9843 and was 0.84 in the present study.
The temporal-spatial and kinetic variables of gait were collected using a computerized, multi-step Walkway system (TekScan Inc, South Boston, Massachusetts). The Walkway extended from 7.0 to 13.0 m and was covered with a thin (0.64 cm) mat to protect the sensors from the participants' footwear. The Walkway software (version 7.02, TekScan Inc) calculated gait variables from the number of recorded footfalls on the walkway. The 2 walking trials were averaged in the software. The following gait variables were obtained from the Walkway software: average of right and left step length, cadence, average of right and left propulsion time, impulse, and maximum ground reaction force (mGRF). Impulse and mGRF were reported relative to body mass. The kinetic reliability of the TekScan Walkway was comparable to other commercially available walkways.44 The percentage of time in swing, percentage of time in stance, and time spent in double support were obtained from the first complete gait cycle captured on the Walkway.
On the basis of the study design, a priori analyses were performed to determine differences in various parameters of gait based on the 2 levels of functional fitness. The power calculations were determined on the basis of previous results,45 comparing gait (velocity, step length, and cadence) between high- and low-functioning older adults. With 8 participants per group, this study was designed to have a power of 80% with an α level of .05. All statistical analyses were conducted using SPSS version 19.0 (IBM Corporation, Chicago, Illinois). Values are reported as mean (SD). To determine level of functional fitness, the participants were divided into 2 groups on the basis of their relative stair-climb power. Analysis of variance was conducted to determine statistical differences between the high and low functional fitness groups on relative stair-climb power and on other descriptive variables (age, weight, height, and body fat). Multivariate analysis of variance was conducted to determine main effects for the following dependent variables: walking velocity, step length, cadence, propulsion time, relative impulse, relative maximal vertical ground reaction force (mGRF), percentage of swing, percentage of stance, and double stance time between groups. Because of the multiple dependent variables, the Bonferroni correction was used to guard against making a type I error. All variables were normally distributed (P > .05).
The groups did not differ on age, weight, height, or body fat (Table 1). The mean stair-climb power for the lower-functioning group was 3.22 W/kg compared with 4.76 W/kg in the higher-functioning group. Individuals in the higher-functioning group produced significantly more relative power than the lower-functioning group (1.54 W/kg; F = 42.31, P = .00). When the parameters of gait were examined, only gait speed was different between groups (F = 6.39, P = .02; Table 2). However, the data suggest the higher-functioning group scored more favorably on all other parameters of gait.
The purpose of the study was to examine differences between higher and lower functionally fit community-dwelling older adults on gait velocity and selected gait parameters. Our definition of functional fitness was based on performance from a stair-climb test. On the basis of results from Bean and colleagues,8 the average power produced for a group of community-dwelling older adults with moderate mobility disability is 3.76 W/kg. This value was used as a cut point to define high and low functionally fit older adults. In the present investigation, the mean of the lower-functioning group was 3.22 W/kg, while individuals in the higher-functioning group averaged 4.76 W/kg.
Among community-dwelling older adults considered to have high levels of functional fitness, habitual walking velocity ranges from 1.10 to 1.33 m/s.19,37,38,46 In our study, the average walking velocity for the low- and high-functioning groups was 1.24 and 1.42 m/s, respectively. It should be noted that most clinicians assessing habitual walking velocity as a single determinant of functional fitness would consider the entire study sample a high-functioning group. However, functional fitness is multifactorial and gait velocity alone may not be sensitive enough to detect subclinical detriments in mobility of community-dwelling older adults.
Effective and safe movement patterns are vital to older adults' independence.39,47 Greater deviation from a normal gait pattern has been associated with a higher incidence of institutionalization, death,35 and certain chronic diseases.31 In addition, slower gait speed has been related to greater risk for functional decline and mortality.41 In the present investigation, older adults classified as low-functioning walked 13% slower and produced less power. Strategies to minimize the decline in gait speed associated with aging are of clinical and applied importance. Therefore, recognizing declines in mobility and developing ways to improve functional fitness as one ages is imperative. Earlier detection of such variations will help clinicians identify adults with subclinical deviations and could potentially prevent mobility disability.
Other parameters of gait have not been assessed regarding functional fitness. In addition to walking slower, previous studies have reported decreases in cadence and step length with age with no mention of functional status.18,19,38,39,46 Community-dwelling older adults without mobility limitations have cadence values ranging from 85 to 122 steps/min.18,48,49 However, these particular studies did not assess functional fitness nor mobility limitations among participants. In the present investigation, cadence during habitual walking was 118 steps/min with no statistical differences between groups. These results suggest that cadence does not change with decrements in functional fitness among community-dwelling older adults.
In addition to cadence, step length is another contributor to walking speed. Step length of community-dwelling older adults ranges from 0.43 to 0.71 m.18,37,38 We found a trend (P = .11) that revealed greater step length for participants in the high-functioning group (8%). The slight decrease in step length of the lower-functioning group may be associated with the reduced walking speed as a means to improve stability. This is the first study of its kind assessing differences between older adults with higher and lower levels of functional fitness; thus, further study is warranted.
Increased double support time represents clinical and potentially subclinical decrements in physical function and is used to increase stability. In the present study, the lower-functioning group spent more time in double support and less time in the swing phase by 6% and 9%, respectively. Begg and Sparrow37 found elderly adults spent 62% of the gait cycle in stance and 38% in swing. In the present investigation, participants in the low-functioning group were in stance phase for 61% and in swing phase 39% of the gait cycle, while the high-functioning group spent less time in stance (58%) and more time in swing (42%). Even though there was not a statistically significant difference between the groups on these variables, lower-functioning individuals demonstrated decreases in factors suggesting the adoption of a more stable gait pattern.
Despite the contribution of ground reaction force to the propulsive aspect of gait, only a few studies have addressed kinetic analysis in older adults. Although no significant difference existed between the groups, relative impulse was higher in the lower functionally fit participants by 13.1%. This increase can be attributed to the longer time spent in stance by the lower functionally fit group. In addition, no statistical difference between the high- and low-functioning groups on the relative mGRF was generated during stance; conversely, it was 8% higher in the lower-functioning group. Qualitative examination of the mGRF revealed that it occurred during the heel strike for most participants (78%) in the present study. Furthermore, more participants in the lower-functioning group demonstrated a higher mGRF at initial contact than in the higher-functioning group, 86% and 73%, respectively.
Winter et al50 found an increase in power absorption and a decrease in propulsive power in healthy, older adults as compared with a young control group. The researchers explained that the increase in energy absorption at initial contact was associated with a shorter step length and reduced foot angle.50 In the present investigation, a trend for step length to decrease in the lower-functioning group was present. While the present experiment did not examine joint angles, previous research has suggested that older adults decrease plantar flexion of the ankle during push-off, creating a decrease in energy generation, and land more flatfooted, increasing the need for energy absorption at heel strike.37,50 The increase in mGRF at initial contact by the participants in the present study may have been an adaption used to increase stabilizing time at initial contact.50 Conversely, this may also suggest both of the groups demonstrated a reduction in plantar flexion power during push-off. Thus, it would be important to further examine kinetic gait parameters among older adults.
The findings of the present study may be limited by a small sample size, especially regarding the variables that had nonsignificant differences. However, statistical significance was achieved for gait velocity and sample size was similar to previous studies. When generalizing results to older adults, care should be taken. While stair-climb power has been correlated with well-known batteries of functional fitness, this has been confirmed only in adults with moderate mobility limitations.8,14 The volunteers in this study represent a higher-functioning subset of all older adults, with all participants walking at a velocity of more than 1.0 m/s. However, the individuals with a higher level of functional fitness did not demonstrate the same age-related changes in gait parameters as the older adults classified as lower-functioning.
It is imperative to maintain functional fitness throughout life and recognize declines in mobility, as it could hinder movement and independence. While gait speed is a simple measure to determine functional fitness, perhaps the components of gait are more specific to changes in mobility disability. Gait speed was statistically different between high- and low-functioning older adults. The lower-functioning group demonstrated changes suggesting the adoption of a more stable walking pattern: reduction in swing time and increase in double stance time. However, more research is needed, examining specific events in the gait cycle such as initial contact, mid-swing, and end contact to detect differences in low and high functionally fit older adults.
1. Rikli RE, Jones CJ Senior Fitness Test Manual. Champaign, IL: Human Kinetics; 2001.
2. Runge M, Rittweger J, Russo CR, Schiessl H, Felsenberg D Is muscle power output a key factor in the age-related decline in physical performance? A comparison of muscle cross section, chair-rising test, and jumping power. Clin Physiol Funct Imaging. 2004;24(6):335–340.
3. Seeman TE, Merkin SS, Crimmins EM, Karlamangla AS Disability trends among older Americans: National Health and Nutrition Examination Surveys, 1988-1994 and 1999-2004. Am J Public Health. 2010;100(1):100–107.
4. Rose DJ, Jones CJ, Lucchese N Predicting the probability of falls in community-residing older adults using the 8-foot up-and-go: a new measure of functional mobility. J Aging
Phys Activ. 2002;10(4):466–475.
5. Tinetti ME, Speechley M, Ginter SF Risk factors for falls among elderly persons living in the community. N Engl J Med. 1988;319(26):1701–1707.
6. Shumway-Cook A, Silver IF, LeMier M, York S, Cummings P, Koepsell TD Effectiveness of a community-based multifactorial intervention on falls and fall risk factors in community-living older adults: a randomized, controlled trial. J Gerontol Med Sci. 2007;62A(12):1420–1427.
7. Guralnik 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 short physical short performance battery. J Gerontol Med Sci. 2000;55A(4):M221–M231.
8. Bean 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(5):604–609.
9. Bean 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(8):728–733.
10. Foldvari M, Clark M, Laviolette LC, et al. Association of muscle power with functional status in community-dwelling elderly women. J Gerontol Med Sci. 2000;55A(4):M192–M199.
11. Bottaro M, Machado SN, Nogueira W, Scales R, Veloso J Effect of high versus low-velocity resistance training on muscular fitness and functional performance in older men. Eur J Appl Physiol. 2007;99(3):257–264.
12. Marsh AP, Miller ME, Saikin AM, et al. Lower extremity strength and power are associated with 400-meter walk time in older adults: the InCHIANTI study. J Gerontol Med Sci. 2006;61(11):1186–1193.
13. Metter EJ, Conwit R, Tobin J, Fozard JL Age-associated loss of power and strength in the upper extremities in women and men. J Gertontol Biol Sci. 1997;52A(5):B267–B276.
14. Suzuki T, Bean JF, Fielding RA Muscle power of the ankle flexors predicted functional performance in community-dwelling older women. J Am Geriatr Soc. 2001;49(9):1161–1167.
15. Cesari M, Kritchevsky SB, Penninx BWHJ, et al. Prognostic value of usual gait
speed in well-functioning older people—results from the Health, Aging
and Body Composition Study. J Am Geriatr Soc. 2005;53(10):1675–1680.
16. Kuo H, Leveille SG, Yen C, et al. Exploring how peak leg power and usual gait
speed are linked to late-life disability: data from the National Health and Nutrition Examination Survey (NHANES), 1999-2002. Am J Phys Med Rehabil. 2006;85(8):650–658.
17. Novaes RD, Miranda AS, Dourado VZ Usual gait
speed assessment in middle-aged and elderly Brazilian subjects. Rev Bras Fisioter. 2011;15(2):117–122.
18. Oberg T, Karsznia A, Oberg K Basic gait
parameters: reference data for normal subjects, 10-79 years of age. J Rehabil Res. 1993;30(2):210–223.
19. Bohannon RW Comfortable and maximum walking speed of adults aged 20-79 years: references values and determinants. Age Ageing. 1997;26(1):15–19.
20. Simonsick EM, Newman AB, Nevitt MC, et al. Measuring higher level physical function in well-functioning older adults: expanding familiar approaches in the health ABC study. J Gerontol Ser A Biol Sci Med Sci. 2001;56(10):M644–M649.
21. Steffen TM, Hacker TA, Mollinger L Age- and gender-related test performance in community-dwelling elderly people: Six-Minute Walk Test, Berg Balance Scale, Timed Up & Go Test, and gait
speeds. Phys Ther. 2002;82(2):128–137.
22. Hageman PA, Blanke DJ Comparison of gait
of young women and elderly women. Phys Ther. 1986;66(9):1382–1387.
23. Ostrosky KM, VanSwearingen JM, Burdett RG, Gee Z A comparison of gait
characteristics in young and old subjects. Phys Ther. 1994;74(7):637–644.
24. Blanke DJ, Hageman PA Comparison of gait
of young men and elderly men. Phys Ther. 1989;69(2):144–148.
25. Bean JF, Herman S, Kiely DK, et al. Weighted stair climbing in mobility-limited older people: a pilot study. J Am Geriatr Soc. 2002;50(4):663–670.
26. Fried LP, Bandeen-Roche K, Chaves PHM, Johnson BA Preclinical mobility disability predicts incident mobility disability in older women. J Gerontol Med Sci. 2000;55A(1):M43–M52.
27. Talbot L, Musiol R, Witham E, Metter EJ Falls in young, middle-aged and older community dwelling adults: perceived cause, environmental factors and injury. BMC Public Health. 2005;5(1):86.
28. Brach JS, Studenski SA, Perera S, VanSwearingen JM, Newman AB Gait
variability and the risk of incident mobility disability in community-dwelling older adults. J Gerontol Med Sci. 2007;62A(9):983–988.
29. Studenski S, Perera S, Patel K, et al. Gait
speed and survival in older adults. JAMA. 2011;305(1):50–58.
30. Van Kan GA, Rolland Y, Andrieu S, et al. Gait
speed at usual pace as a predictor of adverse outcomes in community-dwelling older people an International Academy on Nutrition and Aging
Task Force. J Nutr Health Aging
31. Verghese J, Le Valley A, Hall CB, Katz MJ, Ambrose AF, Lipton RB Epidemiology of gait
disorders in community-residing older adults. J Am Geriatr Soc. 2006;54(2):255–261.
32. Shin S, Valentine RJ, Evans EM, Sosnoff JJ Lower extremity muscle quality and gait
variability in older adults. Age Ageing. 2012;41(5):595–599.
33. Hausdorff JM, Edelberg HK, Mitchell SL, Goldberger AL, Wei JY Increased gait
unsteadiness in community-dwelling elderly fallers. Arch Phys Med Rehabil. 1997;78(3):278–283.
34. Laufer Y Effect of age on characteristics of forward and backward gait
at preferred and accelerated walking speed. J Gerontol Med Sci. 2005;60A(5):627–632.
35. Verghese J, Holtzer R, Lipton RB, Wang C Quantitative gait
markers and incident fall risk in older adults. J Gerontol Med Sci. 2009;64A(8):896–901.
36. Puthoff ML, Janz KF, Nielson D The relationship between lower extremity strength and power to everyday walking behaviors in older adults with functional limitations. J Geriatr Phys Ther. 2008;31(1):24–31.
37. Begg RK, Sparrow WA Ageing effects on knee and ankle joint angles at key events and phases of the gait
cycle. J Med Eng Technol. 2006;30(6):382–389.
38. Ko S, Ling SM, Winers J, Ferrucci L Age-related mechanical work expenditure during normal walking: the Baltimore Longitudinal Study of Aging
. J Biomech. 2009;42(12):1834–1839.
39. Nelson AJ, Lembo LS, Lopez DA, Manfredonia EF, Vanichpong SK, Zwick D The functional ambulation performance of elderly fallers and non-fallers walking at their preferred velocity. NeuroRehabilitation. 1999;13(3):141–146.
40. Cockrell JR, Folstein MF Principles and practice of geriatric psychiatry. In:Copeland JRM, Abou-Saleh MT, Blazer DG eds. Principles and Practice of Geriatric Psychiatry. New York, NY: John Wiley & Sons; 2002:147–158.
41. Hardy S, Perera S, Roumani YF, Chandler JM, Studenski SA Improvement in usual gait
speed predicts better survival in older adults. J Am Geriatr Soc. 2007;55(11):1727–1734.
42. Bean JF, Kiely DK, Herman S, et al. The relationship between leg power and physical performance in mobility-limited older people. J Am Geriatr Soc. 2002;50(3):461–467.
43. Motyl JM, Driban JB, McAdams E, Price LL, McAlindon TE Test-retest reliability and sensitivity of the 20-Meter Walk Test among patients with knee osteoarthritis. BMC Musculoskelet Disord. 2013;14(14):166–173.
44. Zammit GV, Menz HB, Munteanu SE Reliability of the TekScan MatScan system for the measurement of plantar forces and pressures during barefoot level walking in healthy adults. J Foot Ankle Res. 2010;3(3):11–20.
45. Graf A, Judge JO, Ounpuu S, Thelen DG The effect of walking speed on lower-extremity joint powers among elderly adults who exhibit low physical performance. Arch Phys Med Rehabil. 2005;86(11):2177–2183.
46. Prince F, Corriveau H, Hebert R, Winter DA Gait
in the elderly. Gait
47. Teixeira-Salmela LF, Santiago L, Lima RCM, Lana DM, Camargos FFO, Cassiano JG Functional performance and quality of life related to training and detraining of community-dwelling elderly. Disabil Rehabil. 2005;27(17):1007–1012.
48. Wert DM, Brach J, Perera S, VanSwearingen JM Gait
biomechanics, spatial and temporal characteristics, and the energy cost of walking in older adults with impaired mobility. Phys Ther. 2010;90(7):977–985.
49. Paroczai R, Bejek Z, Illyes A, Kocsis L, Kiss RM Gait
parameters of healthy, elderly people. Phys Educ Sport. 2006;14(1):49–58.
50. Winter DA, Patla AE, Frank JS, Walt SE Biomechanical walking pattern changes in the fit and healthy elderly. Phys Ther. 1990;70(6):340–347.