Download Relationships Among Age-Associated Strength Changes and

Journal of Gerontology: BIOLOGICAL SCIENCES
2000, Vol. 55A, No. 6, B264–B273
Copyright 2000 by The Gerontological Society of America
Relationships Among Age-Associated Strength
Changes and Physical Activity Level, Limb
Dominance, and Muscle Group in Women
Sandra K. Hunter,1 Martin W. Thompson,1 and Roger D. Adams2
Schools of 1Exercise and Sport Science and 2Physiotherapy, Faculty of Health Sciences, The University of Sydney, Australia.
This study investigated the magnitude and rate of age-associated strength reductions in Australian independent
urban-dwelling women and the relationship to muscle groups, limb dominance, and physical activity level. Independent urban-dwelling women aged 20 to 89 years (N ⫽ 217) performed maximal voluntary contractions with
the dominant and nondominant knee extensors, plantar flexors, and handgrip. Anthropometric measurements
were made and questionnaire responses used to obtain current physical activity levels. Trend analysis within
analysis of variance and regression analysis on strength was performed. Limb muscle strength was found to be
associated with increased age, muscle group, limb dominance, and activity. Self-reported physical activity levels
declined with age but women who were more physically active for their age group were stronger in all muscle
groups and had more lean body mass and lean thigh and leg cross-sectional area than relatively inactive women.
Slopes of the linear reductions of maximal voluntary strength of the knee extensors, plantar flexors, and handgrip with age were significantly different ( p ⬍ .05) at 9.3%, 7.4%, and 6.2% per decade, respectively. The limb
muscle strength of healthy Australian independent and urban-dwelling women aged 20 to 89 years was found to
be associated with age and three aspects of disuse: muscle group, relative levels of physical activity, and limb
dominance.
T
HE physiological changes in the human musculoskeletal
system with increasing chronological age have occupied
both poets and physiologists over the centuries. Shakespeare’s
“shrunk shank” depiction of the age-related loss of gastrocnemius muscle volume (1) is in agreement with numerous studies
that show that the aging process is associated with loss of skeletal muscle mass and subsequent weakness (2). Lower limb
weakness experienced by many older men and women is related to a loss of mobility in activities such as ambulation, rising
from a chair, and stair climbing (3–7). Some older individuals,
in particular women, are so weak that they have a limited physiological reserve of strength (8), and tasks such as rising from a
chair may require close to or all their maximal leg strength (6,9).
The onset and the magnitude of muscle weakness in older
adults have been described by a large number of cross-sectional studies for various populations, with a range of conclusions reached. Although some studies have concluded
that isometric strength declines in upper- and lower-limb
muscles around the fifth to sixth decade of life (10–14),
other data have shown that the strength decrement begins as
early as 30 years of age in some muscle groups (15,16). The
discrepancy may be a result of the range of muscles tested
and the varying degrees of disuse specific to individual
muscle groups and/or the populations studied.
Several cross-sectional studies have reported that the
greatest decrement in strength is experienced in the lower
limb muscle groups of an older individual (17–19). Bemben
and colleagues (16), however, measured the strength of a
number of upper- and lower-limb muscle groups in 153
men, aged 20 to 74 years, and they reported the greatest reduction in the elbow extensors compared with the plantar
flexors (PFs), dorsiflexors, thumb abductors, and finger
B264
flexors. Further, a longitudinal study of 70- to 75-year-old
men and women showed that, although reductions in the
maximal isometric strength of handgrip (HG), arm flexion,
trunk flexion, and trunk extension ranged between 5% and
16% over a 5-year period, knee extensor (KE) strength in
both men and women increased significantly by 4% over
the same time period in these older individuals (20).
A potential confounding factor in defining the strength
decrements across age groups is the physical activity level
of the sample group assessed. Older adult volunteers in particular will tend to be more active and healthy (21) and not
representative of the broader older population. We revisited
this issue of muscle-specific strength reductions that occur
with age in a group of Australian independent and urbandwelling women aged 20 to 89 years. These women were
representative in their physical activity levels of a broader
sample of Australian women who had been randomly surveyed by the National Heart Foundation (22). Further, we
investigated the interaction of relative disuse on limb
strength. It is well established that participation in physical
activity is reduced in older men and women compared with
younger individuals (22). If disuse is a major determinant of
muscle strength, then strength changes with increasing
chronological age should be associated with the physical activity level of the individual and their preference for using
a particular limb (dominance). We aimed to determine
whether those women who were relatively more active for
their age had a strength advantage that could be functionally
significant.
Thus the purpose of this study was to investigate the
magnitude and the rate of age-associated strength reductions in Australian independent urban-dwelling women and
LIMB STRENGTH WITH AGE, PHYSICAL ACTIVITY, AND LIMB DOMINANCE
the relationship among different muscle groups, limb dominance, and physical activity level. We expected that there
would be a difference in the rate and the magnitude of
strength reduction among muscle groups with increasing
age and that strength would be greater in the preferred
(dominant) limb and also in women who were relatively
more active for their age.
METHODS
Subjects
A total of 217 independent community-dwelling women
aged 20 to 89 years responded to a newspaper advertisement and volunteered for this study. Subjects were recruited
from the metropolitan area of Sydney, Australia, and had
controlled blood pressure, with no recent history of myocardial infarction or musculoskeletal disorder. This study was
approved by The University of Sydney Human Ethics Committee.
The women were required to attend a university laboratory for one session of testing. The experimental procedures
of the study were as follows.
Anthropometric Measurements
Height and body weight were measured and used to calculate body mass index (BMI). The percentage of body fat
was estimated with Siri’s equation (23) along with an estimation of body density. Body density was calculated with
four skinfold thickness measurements and regression equations according to Durnin and Womersley (24). The four
skinfold thicknesses were measured to the nearest millimeter by an experienced anthropometrist who used skinfold
calipers (Harpenden Caliper, British Indicators Ltd) at the
following sites on the right-hand side of the body: biceps,
triceps, suprascapular, and suprailiac. Lean body mass
(LBM) was calculated by subtraction of the estimated body
fat weight from the gross body weight. Lean mass crosssectional area (CSA) of the midthigh and thickest portion of
the lower leg were calculated by use of girths and subtraction of the estimated subcutaneous fat calculated from skinfolds.
Physical Activity Rating
Current level of physical activity was assessed with the
National Heart Foundation Prevalence Risk Study Questionnaire (22). By use of this information, each subject was
scored on a 6-point physical scale. The rating was as follows:
1. No regular form of exercise or recreational activities.
2. One to two sessions of recreational activities per
week that did not cause the subject to huff and puff
for a period of greater than 20-minutes duration per
session, e.g., slow walking, slow swimming, golfing,
bowling.
3. Three or more sessions of recreational activities per
week that did not cause the subject to huff and puff
for a period of greater than 20-minutes duration per
session, e.g., slow walking, slow swimming, golfing,
bowling.
B265
4. One to two sessions of exercise per week that caused
the subject to huff and puff for a period of greater
than 20-minutes duration per session.
5. Three to four sessions of exercise per week that
caused the subject to huff and puff for a period of
greater than 20-minutes duration per session.
6. Five or more sessions of exercise per week that
caused the subject to huff and puff for a period of
greater than 20-minutes duration per session.
Maximal Voluntary Isometric Strength
The maximal voluntary strength of the KEs, PFs, and HG
was assessed on both the dominant and the nondominant
sides in random order. Each subject performed a minimum
of three verbally encouraged maximal voluntary contractions (MVCs) for each muscle group, with one minute rest
between contractions. After the third MVC, the contractions
were repeated until it was apparent that the subject was unable to improve further. Each MVC lasted 2–5 seconds and
the largest recorded MVC was used for analysis.
Force transducers (X Tran 1000 N and 2000 N; Applied
Measurement Technology, Australia) set within steel frameworks designed for each muscle group, recorded the isometric force of the KE, PF, and HG. The electrical signal from
each force transducer was amplified (Applied Measurement
Technology) and digitized by a DT2801A analog-to-digital
card (Data Translation, Malboro, USA). Data was sampled
at a frequency of 1000 Hz and analyzed on computer.
The isometric force of the KE was measured while the subject was seated in a steel-framed chair with a hip angle of 90
deg and a knee joint angle of 60 deg from full knee extension.
Sixty degrees from full knee extension corresponds to the angle for optimal force on the KE length–force curve (25). The
PF MVC was measured with the foot positioned at a joint angle of 10 deg dorsiflexion, corresponding to the optimal region on the length–tension curve for the PF (5–15-deg dorsiflexion) (26). The subject performed the HG MVC while in a
standing position with arm straightened by their side.
Reliability of MVC
The test–retest reliability of MVC performance was determined on 107 of the subject population ranging in age between 20 and 82 years [mean ⫾ standard error (SE), age
52.0 ⫾ 1.4 years; height 162.7 ⫾ 0.6 cm; weight 64.8 ⫾ 0.9
kg]. The women returned to the laboratory 1–2 weeks after
their first visit to perform a retest MVC of the dominant and
nondominant KE, PF, and HG. A minimum of 10 women
were retested from each decade up to 80 years.
Statistical Analysis
The subjects were grouped into 5-year age brackets for
analysis (with the exception of the 80–89-year-old subjects).
The main effects of age, physical activity, and limb dominance were analyzed by trend analysis within 13 ⫻ 2 ⫻ 2
(age group ⫻ activity level ⫻ dominance) analysis of variance (ANOVA) (27) conducted across the age groups. The
women in each of the 5-year age groups were divided into
those subjects who were relatively active (ACT: equal to or
above the mean activity rating of their age group) or inactive
for their age (INACT: activity rating below the mean score of
B266
HUNTER ET AL.
their age group). The main effect of muscle group (KE, PF,
and HG) on strength across age groups was analyzed by trend
analysis within ANOVA (13 ⫻ 3) by use of relative strength
scores (strength as a percentage of 20–24-year age group of
the dominant and the nondominant sides averaged). Linear
and quadratic regression analysis was used to determine the
line of best fit when the linear/quadratic trend component
with age was significant for a dependent variable. Pearsonproduct moment correlations were used to assess the association among a range of variables including age, physical characteristics, and strength of the muscle groups. Stepwise linear
multiple-regression models were used to determine the predictive nature and contribution of age, physical activity levels, and anthropometric measures to the total variation of
muscle strength. For all results, data are expressed as mean ⫾
SE and significance accepted at p ⬍ .05.
RESULTS
The 217 women were grouped in 5-year age brackets
(with the exception of 80–89-year-old subjects), and the
numbers in each group reported in Table 1.
Sample Representation
To determine how representative the present study sample
was of a larger Australian population sample, physical activity levels of the women from the present study were compared with those reported by The National Heart Foundation
of Australia Risk Factor Prevalence Study (22). The National
Heart Foundation surveyed 4,740 women aged between 20
and 69 years who had been selected at random from eight major cities around Australia. Because the age range was 20–69
years for the National Heart Foundation study, comparisons
of physical activity levels between the two samples were conducted in women between 20 and 69 years of age.
A comparison of physical activity was based on whether
the subject had participated in any vigorous exercise within
the two weeks prior to answering the questionnaire (22).
The proportion of women aged 20–69 years who had participated in vigorous exercise from the present study sample
and the National Heart Foundation study was 26.1% (N ⫽
176) and 30.2% (N ⫽ 4,740), respectively (Figure 1). Of the
10 age group categories from the present study, 9 were
Figure 1. Proportion of women sampled in the National Heart
Foundation Study (22) (NHF, N ⫽ 4,740)] and the present study
(Present Study, N ⫽ 176) who had participated in vigorous activity
within the two weeks before the physical activity questionnaire.
within 5.8% of the National Heart Foundation Study (22)
whereas the 35–39-year-old group deviated by 8.4%.
Physical Characteristics: Age and Physical Activity
The means (⫾SE) according to age categories for body
weight, standing height, BMI, LBM, and percentage of
body fat are shown in Table 1. The correlation matrices of
physical characteristics, strength, and physical activity levels are shown in Table 2.
Weight, height, and BMI.—Body weight increased in a
quadratic trend upwards [F(1,204) ⫽ 4.6, p ⬍ .05] and
height decreased linearly [F(1,204) ⫽ 24, p ⬍ .001] across
age groups. BMI increased across age categories in a linear
trend [F(1,204) ⫽ 7.4, p ⬍ .01]. There was no significant
difference between the BMI scores of ACT and INACT
subjects.
Table 1. Physical Characteristics of Subjects in Age Categories
Age (y)
20–24
25–29
30–34
35–39
40–44
45–49
50–54
55–59
60–64
65–69
70–74
75–79
80–89
Total/Mean
n
Mean Age (y)
Weight (kg)
Height (cm)
BMI (kg/m2)
Lean Body Mass (kg)
Body Fat (%)
12
16
14
13
16
15
23
18
23
26
17
15
9
217
22.7 ⫾ 0.3
27.0 ⫾ 0.9
32.0 ⫾ 0.4
37.3 ⫾ 0.4
42.0 ⫾ 0.4
47.7 ⫾ 0.4
51.8 ⫾ 0.3
57.0 ⫾ 0.4
61.7 ⫾ 0.3
66.4 ⫾ 0.2
71.6 ⫾ 0.4
77.0 ⫾ 0.4
82.9 ⫾ 1.1
53.0 ⫾ 1.2
62.9 ⫾ 2.4
61.9 ⫾ 2.0
62.7 ⫾ 2.3
66.1 ⫾ 2.5
67.8 ⫾ 3.5
68.9 ⫾ 3.1
65.8 ⫾ 1.4
68.2 ⫾ 2.0
65.5 ⫾ 1.6
61.9 ⫾ 1.9
66.9 ⫾ 3.1
65.8 ⫾ 3.6
61.3 ⫾ 3.2
65.1 ⫾ 0.7
166.1 ⫾ 1.9
163.1 ⫾ 1.5
163.3 ⫾ 1.8
165.7 ⫾ 1.5
165.8 ⫾ 1.9
161.1 ⫾ 1.2
165.1 ⫾ 1.3
163.4 ⫾ 1.1
159.8 ⫾ 0.8
161.5 ⫾ 1.3
161.6 ⫾ 1.3
156.6 ⫾ 1.4
159.3 ⫾ 1.2
162.5 ⫾ 0.4
22.8 ⫾ 0.6
23.3 ⫾ 0.7
23.6 ⫾ 0.9
24.1 ⫾ 0.8
24.6 ⫾ 1.1
26.5 ⫾ 1.1
24.2 ⫾ 0.5
25.5 ⫾ 0.7
25.7 ⫾ 0.6
23.8 ⫾ 0.8
25.6 ⫾ 1.1
26.7 ⫾ 1.3
24.2 ⫾ 1.3
24.7 ⫾ 0.3
46.8 ⫾ 1.6
44.9 ⫾ 1.2
45.2 ⫾ 1.4
46.1 ⫾ 1.3
44.4 ⫾ 2.0
43.4 ⫾ 1.3
40.8 ⫾ 1.0
41.0 ⫾ 1.0
39.8 ⫾ 0.6
39.9 ⫾ 0.9
40.7 ⫾ 1.6
40.3 ⫾ 1.3
40.8 ⫾ 1.1
42.4 ⫾ 0.4
25.5 ⫾ 1.3
27.1 ⫾ 1.3
27.6 ⫾ 1.1
29.8 ⫾ 1.7
34.0 ⫾ 1.3
36.4 ⫾ 1.4
37.9 ⫾ 0.9
39.7 ⫾ 0.8
39.0 ⫾ 0.8
35.2 ⫾ 0.9
38.8 ⫾ 0.9
37.7 ⫾ 1.5
34.2 ⫾ 1.5
34.7 ⫾ 0.4
Notes: Values are mean ⫾ standard error. BMI ⫽ body mass index.
LIMB STRENGTH WITH AGE, PHYSICAL ACTIVITY, AND LIMB DOMINANCE
Table 2. Matrix of Simple Correlations (r) Among Variables
(N ⫽ 217)
Age
KE MVC
PF MVC
HG MVC
Physical
activity
Body Fat
(%)
LBM
Weight
Height
Body Fat Physical
(%)
Activity
Height
Weight
LBM
⫺0.70***
⫺0.58***
⫺0.59***
0.45***
0.35***
0.54***
0.21**
0.25***
0.17*
0.56*** ⫺0.39*** 0.43***
0.50*** ⫺0.24*** 0.39***
0.51*** ⫺0.38*** 0.37***
⫺0.28***
0.20**
0.55*** ⫺0.24***
⫺0.39***
0.57***
0.03
0.32***
⫺0.31***
⫺0.04
0.20**
⫺0.32***
0.52*** ⫺0.15*
0.76***
Notes: Knee extensor (KE), plantar flexor (PF), and handgrip (HG) strengths
are the mean of the dominant and nondominant maximal voluntary contraction
(MVC) of each subject. LBM ⫽ lean body mass.
*p ⬍ .05; **p ⬍ .01; ***p ⬍ .0001.
LBM.—Estimated LBM decreased with age in a linear
trend [F(1,204) ⫽ 39, p ⬍ .001] (Table 1). ACT subjects
had significantly greater amounts of estimated LBM (43.3 ⫾
0.5 kg) than INACT subjects (41.3 ⫾ 0.5 kg) [F(1,204) ⫽
5.3, p ⬍ .05].
Percentage of body fat.—Estimated percentage of body
fat increased in a linear trend across age groups [F(1,204) ⫽
124, p ⬍ .001] with a significant quadratic trend component
[F(1,204) ⫽ 59, p ⬍ .001] representing a slowing down in
the rate of increase. ACT subjects had significantly less estimated body fat (33.4% ⫾ 0.7%) than INACT subjects
(35.7% ⫾ 0.5%) [F(1,191) ⫽ 10.2, p ⬍ .01]. There was no
significant interaction between any trend components with
age and physical activity, indicating that the shapes of the
age trend functions for body fat did not differ between activity groups.
CSA of midthigh (muscle and bone).—Estimated midthigh muscle and bone CSA (dominant and nondominant
legs averaged) were negatively associated with age (r ⫽
⫺0.25, p ⬍ .001) and positively associated with KE MVC
(r ⫽ ⫺0.45, p ⬍ .001) and physical activity (r ⫽ 0.32, p ⬍
.001). Midthigh lean mass CSA decreased with age in a linear trend [dominant F(1,204) ⫽ 10.2 ( p ⬍ .01) and nondominant F(1,204) ⫽ 12.3 ( p ⬍ .001)]. ACT women had
significantly larger lean mass CSA than INACT women
in both the dominant thigh [ACT, 139.6 ⫾ 2.0 cm2; and
INACT, 125.8 ⫾ 1.8 cm2; F(1,191) ⫽ 27.0, p ⬍ .001] and
nondominant thigh [ACT, 138.8 ⫾ 2.0 cm2; and INACT,
124.1 ⫾ 1.8 cm2; F(1,191) ⫽ 32.5, p ⬍ .001]. There was no
significant interaction between the trend components with
age and physical activity in thigh CSA, indicating that the
linear downward slope with age was similar for both ACT
and INACT groups.
CSA of lean mass lower leg (muscle and bone).—Estimated lower-leg lean mass CSAs (dominant and nondominant legs averaged) were significantly associated with age
(r ⫽ ⫺0.39, p ⬍ .001), absolute strength of the PF MVC
B267
(r ⫽ 0.45, p ⬍ .001), and physical activity (r ⫽ 0.37, p ⬍
.001).
The dominant and the nondominant lower-leg lean mass
CSAs decreased with age in a linear trend, dominant
F(1,204) ⫽ 29 ( p ⬍ .001) and nondominant F(1,204) ⫽ 26
( p ⬍ .001). ACT women had significantly larger lean mass
CSA than INACT women in both the dominant lower leg
[ACT, 76.4 ⫾ 1.0 cm2; and INACT, 69.0 ⫾ 0.9 cm2;
F(1,191) ⫽ 31.3, p ⬍ .001] and nondominant thigh [ACT,
74.8 ⫾ 1.0 cm2; and INACT, 68.0 ⫾ 0.9 cm2; F(1,191) ⫽
25.0, p ⬍ .001]. There was no significant interaction between the linear trend components with age for physical activity in either lower-leg CSA, indicating that the difference
between the ACT and the INACT lower-leg lean mass CSA
remained consistent across age groups in both legs.
Reliability of MVC
The test–retest reliability of MVC performance was determined on 107 of the women subjects who returned to the
laboratory after 1–2 weeks for a second session of MVC
testing. Intraclass correlations (ICCs) of the test–retest reliability of the MVC of the dominant and nondominant KE,
PF, and HG ranged between ICC (2,1) ⫽ 0.91 and 0.95. The
coefficient of variation (CV) for test–retest of each muscle
group MVC was calculated from the largest MVC performed by each woman during each of the two testing sessions (%CV ⫽ standard deviation/mean ⫻ 100) and then
the CVs of the 107 women were averaged. The mean percent CVs for the dominant and the nondominant KE, PF,
and HG ranged between 4.4% and 7.1%.
The effect of age on the test–retest reliability of MVC
performance was determined by an independent t test to
compare the CVs of subjects aged 20–49 years (young, n ⫽
42) with the CVs of those aged 50–82 years (older, n ⫽ 65).
There was no difference in the CV of MVC between the
young and the older age group for the dominant KE (5.4%
and 6.3%, respectively, p ⬎ .05), nondominant KE (8.7%
and 6.1%, respectively, p ⬎ .05), dominant PF (5.2% and
6.9%, respectively, p ⬎ .05), nondominant PF (4.1% and
5.5%, respectively, p ⬎ .05), and the dominant HG (4.9%
and 4.9%, respectively, p ⬎ .05). In the nondominant HG
the older age group (50–82 years old) had a significantly
higher CV (5.1%) compared with that of the younger age
group (3.4%, p ⬍ .05).
Strength as a Function of Muscle Group with Age
The strengths of the dominant and the nondominant limbs
were averaged for this analysis. The single main effect of
muscle strength across age categories was a downward linear trend [F(1,204) ⫽ 167, p ⬍ .001]. The linear reduction
of the MVC in each muscle group of women aged between
20 and 89 years was KE, 0.93% per year; PF, 0.74% per
year; and HG, 0.62% per year. These linear slopes for MVC
were significantly different between the KE and the PF
[F(1,204) ⫽ 146, p ⬍ .001], KE and HG [F(1,204) ⫽ 185,
p ⬍ .001], and PF and HG [F(1,204) ⫽ 9.6, p ⬍ .01]. For
the PF and the HG there was a small but significant quadratic component with age (refer to Figure 2). Figure 3
shows the range (strongest and weakest woman) and group
means of the MVC for each 5-year age group for the KE,
B268
HUNTER ET AL.
Figure 2. Relative muscle group strength and age: the absolute
strength [maximal voluntary contraction (MVC)] of the knee extensors, plantar flexors, and handgrip as a percentage of the mean 20–24year-old MVC and as a function of age. Dominant and nondominant
MVCs of each muscle group have been averaged (N ⫽ 217). Shown
are the mean (⫾standard error) of age categories.
PF, and HG. The best-fit regression equations for each of
the muscle groups were
KE MVC (Nm) = 216 – 1.73 ( age )
PF MVC (N) = 1256 + 4.1 ( age ) – 0.136 ( age 2 )
HG MVC (N) = 351 + 0.31 ( age ) – 0.025 ( age 2 ).
Stepwise multiple regression analysis was conducted to
determine the most potent predictors of strength. Age,
LBM, level of physical activity, height, and the estimated
CSA of muscle and bone of the midthigh accounted for 65%
(adjusted r2) of the total variation in KE MVC:
KE MVC ( Nm ) = – 1.24 × age ( years ) + 1.57 ×
LBM ( kg ) + 5.70 × physical activity ( 1–6 rating ) +
2
0.29 × lean thigh CSA ( cm ) + 0.71 ×
height ( cm ) – 43.4.
Age, estimated CSA of muscle and bone of the lower
leg, height, body fat, and physical activity levels accounted
for 51% (adjusted r2) of the total variation in MVC of
the PF:
PF MVC ( N ) = – 8.25 × age ( years ) +
10.29 × lean leg CSA ( cm2 ) + 37.15 ×
physical activity ( 1–6 rating ) + 8.30 ×
body fat ( % ) + 365.2.
Age, height, physical activity levels, and LBM accounted
for 52% (adjusted r2) of the total variation in the absolute
strength of the HG:
HG MVC ( N ) = – 1.47 × age ( years ) + 3.11 ×
height ( cm ) + 8.52 × physical activity ( 1–6 rating ) +
1.80 × LBM ( kg ) – 235.4 .
Figure 3. The range (strongest and weakest woman) and mean
(⫾ standard error) maximal voluntary isometric contraction (MVC)
of A, the knee extensors (KEs); B, the plantar flexors (PFs); and C,
handgrip (HG) of women in 5-year age categories. Dominant and nondominant MVCs of each muscle group have been averaged (N ⫽ 217).
Strength as a Function of Age and Physical Activity
Physical activity levels and age.—Older women were
significantly less active than younger women. There was a
linear trend downward with age from a mean activity rating
of 4.1 ⫾ 0.4 at 20–24 years to 1.7 ⫾ 0.4 at 80–89 years
[F(1,204) ⫽ 14.5, p ⬍ .001].
LIMB STRENGTH WITH AGE, PHYSICAL ACTIVITY, AND LIMB DOMINANCE
Strength and physical activity.—The absolute muscle
strength of ACT women was significantly greater in all
muscle groups (KE, PF, and HG) when compared with the
INACT women (refer to Figure 4). The ACT women were
significantly stronger than the INACT women when absolute strength of the leg muscles was normalized for body
B269
weight (KE and PF) and normalized for LBM in all three
muscle groups (Table 3). There was no interaction in linear
or quadratic trends between the ACT and the INACT for the
KE, PF, or HG. Linear regression analysis resulted in the
best line of fit for the ACT and the INACT KE MVCs with
increased age. Quadratic regression analysis resulted in the
best line of fit for both the ACT and the INACT PF and HG
MVCs with age. The regression equations were as follows:
Active KE MVC ( Nm ) = 240 – 1.92 ( age )
( r 2 = 0.66 , p < .001 ) ,
Inactive KE MVC ( Nm ) = 194 – 1.52 ( age )
( r 2 = 0.42 , p < .001 ) ,
Active PF MVC ( N ) = 1330 + 6.9 ( age ) – 0.174 ( age 2 )
( r 2 = 0.50 , p < .001 ),
Inactive PF MVC ( N ) = 1042 + 7.9 ( age ) – 0.159 ( age 2 )
( r 2 = 0.32 , p < .001 ),
Active HG MVC ( N ) = 393 – 0.80 ( age ) – 0.012 ( age 2 )
( r 2 = 0.36 , p < .001 ),
Inactive HG MVC ( N ) = 288 + 2.4 ( age ) – 0.045 ( age 2 )
( r 2 = 0.43 , p < .001 ).
Strength as a Function of Dominance
The dominant MVC was significantly greater than the
nondominant MVC for the KE [F(1,191) ⫽ 43.3, p ⬍ .001],
PF [F(1,191) ⫽ 7.4, p ⬍ .01)], and HG [F(1,191) ⫽ 313,
p ⬍ .001] (refer to Table 4). The dominance advantage remained significant when the MVC of each muscle group
was normalized to body weight (KE and PF only) and LBM
(all muscle groups). The dominance advantage also remained
significant when the KE MVC was normalized for midthigh
lean mass CSA (KE/CSA) but was eliminated for the PF/CSA.
DISCUSSION
This study found that limb muscle strength was specific
to the age of the individual, the muscle group assessed, the
individual’s physical activity level, and her limb preference
(dominance). The sample of women assessed in this study
was representative in the physical activity levels of a
broader sample of Australian women who had been randomly surveyed by the National Heart Foundation (1990)
Table 3. The Mean (⫾ Standard Error) Strength of Knee Extensors,
Plantar Flexors, and Handgrip in Physically Active
(ACT, n ⫽ 97) and Inactive Women (INACT, n ⫽ 120)
Muscle
Group
KE
PF
HG
Figure 4. The mean (⫾standard error) maximal voluntary contraction (MVC) for A, the knee extensors (KEs); B, the plantar flexors (PFs); and C, handgrip (HG) of active (n ⫽ 97) and inactive (n ⫽
120) women in 5-year age categories ( p ⬍ .0001).
ACT
INACT
% Difference
ACT
INACT
% Difference
ACT
INACT
% Difference
MVC
(Nm or N)
MVC/BW
(Nm/kg or N/kg)
MVC/LBM
(Nm/kg or N/kg)
140 ⫾ 4
114 ⫾ 4
22.9
1163 ⫾ 28
969 ⫾ 24
20.0
314 ⫾ 6
272 ⫾ 6
15.4
2.2 ⫾ 0.1
1.8 ⫾ 0.1
22.0
17.9 ⫾ 0.4
15.2 ⫾ 0.4
18.4
—
—
—
3.2 ⫾ 0.1
2.7 ⫾ 0.1
16.8
26.8 ⫾ 0.5
23.6 ⫾ 0.6
13.7
7.3 ⫾ 0.1
6.6 ⫾ 0.1
9.7
Notes: The dominant and nondominant strength scores are averaged for each
subject. MVC ⫽ maximal voluntary contraction [Nm for knee extensor (KE); N
for plantar flexor (PF) and handgrip (HG)]; MVC/BW ⫽ MVC normalized to body
weight; MVC/LBM, MVC normalized to lean body mass ( p ⬍ .0001 in all cases).
B270
HUNTER ET AL.
Table 4. The Mean (⫾ Standard Error) Strength of the Dominant
and Nondominant KE, PF, and HG in 217 Women
Muscle
Group
KE
PF
HG
Dominant
Nondominant
% Difference
Dominant
Nondominant
% Difference
Dominant
Nondominant
% Difference
MVC
(Nm or N)
MVC/BW
(Nm/kg or
N/kg)
MVC/LBM
(Nm/kg or
N/kg)
128.1 ⫾ 3
122.3 ⫾ 3*
4.7
1066 ⫾ 20
1046 ⫾ 19*
1.9
308 ⫾ 5
291 ⫾ 4*
6.0
2.0 ⫾ 0.1
1.9 ⫾ 0.0*
4.7
16.6 ⫾ 0.3
16.3 ⫾ 0.3*
1.9
—
—
—
3.0 ⫾ 0.1
2.9 ⫾ 0.1*
4.5
25.3 ⫾ 0.4
24.8 ⫾ 0.4*
1.9
7.3 ⫾ 0.1
6.5 ⫾ 0.1*
12.5
Notes: MVC ⫽ maximal voluntary contraction [Nm for knee extensor (KE);
N for plantar flexor (PF) and handgrip (HG)]; MVC/BW ⫽ MVC normalized to
body weight; MVC/LBM ⫽ MVC normalized to lean body mass.
*p ⬍ .01 between dominant and nondominant.
(22). To the authors’ knowledge this is the first time that the
strength of several muscle groups as a function of physical
activity level and limb dominance has been described in
Australian women.
Stepwise regression analysis indicated that the age of the
individual was the most potent predictor of limb strength.
Even the strongest women in each age group were unable to
maintain the strength of the young women (Figure 4). Although many studies have demonstrated a large decrement
of strength in older men and women for the KE (10,28–34),
PF (11,16,18,35,36), and HG (12,14,15,32,37–40), we were
able to report a comparison of the magnitude of weakness
for these muscle groups in women aged up to 89 years (Table 5).
Impairment of Strength with Age is Muscle
Group Dependent
Although large decrements were observed in the limb
strength of independent elderly women compared with that
of young women, the magnitude and the rate of strength
decrement across the age groups were specific to the muscle
group assessed. The reduction of maximal voluntary
strength of the KE, PF, and HG across age groups was predominantly linear in trend, with a small but significant quadratic component for PF and HG. The linear decline in
strength for the KE was at 9.3% per decade compared with
the PF (7.4% per decade) and HG (6.2% per decade), and
these reductions among muscle groups were significantly
different. Some studies that have compared the MVCs of
different muscles within the same individual report that reductions in strength across age groups are greatest in the leg
muscles (17,19,33). Others, however, have shown that leg
strength is relatively preserved compared with upper-limb
muscle groups in older men and women (16,20). This present
study demonstrated that in older Australian women, the greatest deterioration of maximal strength was in KE and greatest
preservation of HG. Thus the strength of a single muscle
group (whether lower or upper limb) cannot be taken as indicative of the status of all the muscles of an individual.
The KE showed the most consistent and rapid decline in
strength across the age groups from 25 years of age on, and
this was a linear trend. Other cross-sectional studies have
reported the decline in KE strength with increased age to be
curvilinear for men (10,34) and women (34,42), with a rapid
reduction in strength post-50 years of age. Given that the activity levels of our sample studied closely matched that of
the National Heart Foundation Study (22), which randomly
sampled 4750 women, we are confident that the magnitude
and the rate of strength decrements across the age groups
were representative of the healthy independent-dwelling
woman in urban Australia.
The reductions in strength of the PF and HG across age
groups was curvilinear in trend, with a relative preservation
of strength before a more rapid decline in women aged 50
years and over. In men, Bemben and colleagues (16) also
found that the reductions in strength across age groups of
PF and the finger flexors were explained by linear and quadratic trends. These results are also consistent with other
studies reporting the trend of strength decline for the PF
(11) and HG (12). The relative preservation of the HG and
PF strength in the middle years of life compared with the
KE may be due to the varying degree of muscle group use
and/or their fiber-type composition. At all ages in life, it is
essential for use of the hands to be maintained because of
their important role during daily tasks, independent of
whether the individual is mobile or not. The age-associated
decline in physical activity levels shown in this study indicated a reduction in mobility and therefore reduction in use
of the lower limbs. Further, the soleus, which is one of the
PF muscles, is often in a state of low activation even during
standing and has a relatively high number of type I (slow)
fibers (43,44). Type I fibers are not subject to the same
degree of age-associated atrophy as type II (fast) fibers
(45,46).
Reductions in lower-limb strength and power experienced by many sedentary older women have been associated with a loss of mobility in activities such as ambulation,
rising from a chair, and stair climbing (3,5,7,47). There is a
threshold of minimum strength that is required for performing daily living tasks for activities such as walking speed (4)
and rising from a chair (6,9). The torque required for rising
independently from a knee-height chair has been estimated
to be approximately 120 Nm (both legs) for healthy young
and older men and women (9,48). Using this estimation of
the KE torque, we calculated that 5% of the women from
this present study would have been completely unable to
perform the given task successfully because their maximum
KE torque was less than that required for rising from a
chair. This is a conservative estimate of the number of
women who would truly have difficulty in rising from a
chair independently because (i) the KE torques required for
rising from a chair were measured at chair stand takeoff
when the KEs were at an angle outside the optimal range of
force development (9,48), whereas in this present study we
measured the maximal strength at 60 deg from full knee extension at which higher torques are able to be developed; (ii)
in real life many chairs are lower than knee height and it is
well established that the required torque of the KE increases
as the chair height lowers (9); and finally (iii) there are secondary factors including feet width, ankle proprioception,
and range of movement that may confound the efforts of a
LIMB STRENGTH WITH AGE, PHYSICAL ACTIVITY, AND LIMB DOMINANCE
B271
Table 5. A Summary of the Reduction of Strength at Various Ages of Handgrip, Plantar Flexors, and Knee Extensors Relative to the
Strength of Young Population Samples in Cross-Sectional Studies
Percentage of Decline From Young (%)
Muscle Group
Source
Handgrip
Present Study
Burke et al., 1953 (15)
Kellor et al., 1971 (37)
Kellor et al., 1971 (37)
Mathiowetz et al., 1985 (38)
Mathiowetz et al., 1985 (38)
Kallman et al., 1990 (12)
Era et al., 1992 (32)
Present Study
McDonagh et al., 1984 (18)
Davies et al., 1986 (35)
Klein et al., 1988 (36)
Vandervoort et al., 1986 (11)
Vandervoort et al., 1986 (11)
Bemben et al., 1991 (16)
Present Study
Larsson et al., 1979 (10)
Murray et al., 1980 (41)
Clarkson et al., 1981 (28)
Young et al., 1990 (29)
Murray et al., 1985 (30)
Fisher et al., 1990 (31)
Fisher et al., 1990 (31)
Era et al., 1992 (32)
Bohannon et al., 1997 (33)
Bohannon et al., 1997 (33)
Plantar Flexors
Knee Extensors
Sex
50–59 Years
60–69 Years
70–79 Years
80–89 Years
F
M
M
F
M
F
M
M
F
M
F
M
M
F
M
F
M
M
M
F
F
F
F
M
M
F
16
17
—
—
11
19
9
18
16
—
—
22
19
—
—
25
31
16
—
28
—
28
31
21
20
—
41
25
—
47
—
—
—
—
—
34
42
35
41
35
26
38
35
29
38
37
40
—
38
—
—
—
—
—
37
—
55
—
—
29
22
37
50
—
45
—
35
38
41
34
48
36
56
45
55
—
56
—
—
—
—
—
woman who is near the torque threshold required for successfully rising from a chair independently (9).
Physically Active Women Have Delayed Impairment of
Muscle Strength with Age
There was a progressive decline in the reported physical
activity levels in women of increasing age. This is consistent with other studies reporting that older people in Western cultures engage in fewer regular exercise sessions and
spontaneous activities and expend less energy than younger
individuals (14,22,39,40,49).
The reduced participation of women in physical activity
was associated with different body compositions and
strength levels. The ACT women had significantly less
body fat (2.3%), more LBM (5%), and a larger muscle and
bone CSA of the thigh and lower leg compared with INACT
women, which was consistent across all age groups. The
different body compositions between the ACT and the INACT women could prove advantageous for ACT women.
The ACT women had a larger amount of muscle mass to
move a similar body mass. Therefore, during a given physical task, the ACT women would be able to function at a relatively lower work capacity than INACT women of the
same age.
The ACT women had a marked strength advantage at all
ages when strength was absolute or normalized for body
weight, LBM, or for the lean mass CSA of the legs. The
mean relative strength advantage of the ACT women was
—
—
18
31
11
24
—
—
22
—
—
25
19
30
—
—
—
—
22.9%, 20.5%, and 15.4% for the KE, PF, and HG MVC,
respectively, compared with that of the INACT women.
This consistent additive strength in the ACT women across
age groups resulted in considerable delay of age-associated
muscle weakness compared with that of INACT women of
the same age. Interestingly, because the women were divided into the ACT and the INACT group relative to the
mean activity score of their age group, the strength advantages in the active women were significant despite the older
active women’s being less active than many of the young
inactive women. This study does not establish a cause–
effect relationship between activity levels and strength;
however, we postulate that involvement in even minimal increases in habitual daily activity would be a stimulus for relative maintenance of strength levels into old age.
The additive strength in ACT women is functionally significant particularly for weaker older women. For example,
if the requirement of a given task of the KE was 100 Nm an
ACT woman would theoretically be able to perform that
task until she was 73 years of age (calculated from the predictive regression equations of the KE strength in ACT and
INACT women). However, an INACT woman would be
limited to lifting that load until she was 63 years of age. The
ACT woman would have a 10-year advantage over those
who were less active for their age. Thus the strength advantage of the physically active women could delay functional
impairment of mobility in older persons. The inability to
perform tasks of daily living may have even greater signifi-
B272
HUNTER ET AL.
cance in frail and dependent older women who were not included in this study. In recent years greater attention has
been focused on the functional benefits of strength recovery
in very frail and very weak older adults through strength
training interventions (5,50).
Strength with Age and Limb Dominance
The effect of dominance (limb preference) was common
to all muscle groups but greatest in the HG (6%) compared
with the KE (5%) and the PF (2%). The dominance difference in the HG was similar to that found by Bassey and
Harries (40) who reported a 6% difference between the right
and the left HG in women aged 65 years and over. Although
the dominance effect in all muscle groups was statistically
significant (because of the consistent dominance across all
age groups), the effect was relatively small, particularly in
the PF. The small difference in limb dominance strength for
all muscle groups may have minimal functional consequences for an individual, particularly in comparison with
the effect of age and physical activity. However, the dominance difference is consistent with the concept of more use
being associated with greater strength.
CONCLUSION
The limb muscle strength of healthy Australian independent- and urban-dwelling women aged 20 to 89 years was
found to be associated with increased age, muscle group,
relative levels of physical activity, and limb dominance.
Age was the most potent predictor of muscle strength, and
even the strongest women in each age group were unable to
maintain the strength of the young women. Consequently,
muscle strength was markedly reduced in the older women,
and we estimated that 5% of the total sample population assessed would be unable to rise unassisted from a kneeheight chair because of muscle weakness. However, those
who were relatively active for their age had a considerable
strength advantage that could be functionally beneficial into
old age. The small effect of limb dominance in women may
have little functional significance in comparison with the effects of age, physical activity, and muscle group; however,
it is consistent with the concept of more use being associated with greater strength.
Acknowledgment
Address correspondence to Sandra Hunter, PhD, Neural Control of
Movement Laboratory, Department of Kinesiology and Applied Physiology, University of Colorado at Boulder, Campus Box 354, Boulder, Colorado 80303-0354. E-mail: [email protected]
References
1. Shakeseare W. As You Like It. In: Clarke WG, Wright WA. The Plays
and Sonnets of William Shakespeare. Chicago, Encyclopaedia Britannica; 1952:1:597–626.
2. Hunter SK, White MJ, Thompson MW. Techniques to evaluate elderly
human muscle function: a physiological basis. J Gerontol Biol Sci.
1998;53A:B204–B216.
3. Bassey EJ, Fiatarone MA, O’Neill EF, Kelly M, Evans WJ, Lipsitz
LA. Leg extensor power and functional performance in very old men
and women. Clin Sci. 1992;82:321–327.
4. Buchner DM, Larson EB, Wagner EH, Koepsell TD, De Lateur BJ.
Evidence for a non-linear relationship between leg strength and gait
speed. Age Ageing. 1996;25:386–391.
5. Fiatarone M, Marks EC, Ryan ND, Meredith C, Lipsitz LA, Evans
WJ. High-intensity strength training in nonagenarians. JAMA. 1990;
263:3029–3034.
6. Hughes MA, Myers BS, Schenkman ML. The role of strength in rising
from a chair in the functionally impaired. J Biomech. 1996;29:1509–
1513.
7. Ferrucci L, Guralnik JM, Buchner D, Kasper J, Lamb SE, Simonsick
EM, Chaira Corti M, Bandeen-Roche K, Fried LP. 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 Med Sci. 1997;52A:M275–M285.
8. Wolfson L, Judge J, Whipple R, King M. Strength is a major factor in
balance, gait, and the occurrence of falls. J Gerontol Biol Sci. 1995;
50A(Special issue):B64–B67.
9. Alexander N, Schultz A, Ashton-Miller J, Gross M, Giordani B. Muscle strength and rising from a chair in older adults. Muscle Nerve.
1997;5:S56–S59.
10. Larsson L, Grimby G, Karlsson J. Muscle strength and speed of movement in relation to age and muscle morphology. J Appl Physiol. 1979;
46:451–456.
11. Vandervoort AA, McComas AJ. Contractile changes in opposing muscles of the human ankle joint with aging. J Appl Physiol. 1986;61:361–
367.
12. Kallman DA, Plato CC, Tobin JD. The role of muscle loss in the agerelated decline of grip strength: cross-sectional and longitudinal perspectives. J Gerontol Med Sci. 1990;45:M82–M88.
13. Narici MV, Bordini M, Cerretelli P. Effect of aging on human adductor pollicis. J Appl Physiol. 1991;71:1277–1281.
14. Metter EJ, Conwit R, Tobin J, Fozard JL. Age-associated loss of
power and strength in the upper extremities in women and men. J Gerontol Biol Sci. 1997;52A:B267–B276.
15. Burke WE, Tuttle WW, Thompson CW, Janney CD, Weber RJ. The
relation of grip strength and grip-strength endurance to age. J Appl
Physiol. 1953;5:628–630.
16. Bemben MG, Massey BH, Bemben DA, Misner JE, Boileau RA. Isometric muscle force production as a function of age in healthy 20- to
74-yr-old men. Med Sci Sports Exerc. 1991;23:1302–1310.
17. Simonson E. Physical fitness and work capacity of older men. Geriatrics. 1947;2:110–119.
18. McDonagh MJN, White MJ, Davies CTM. Different effects of ageing
on the mechanical properties of human arm and leg muscles. Gerontology. 1984;30:49–54.
19. Asmussen A, Heeboll-Neilsen K. Isometric muscle strength in relation
to age in men and women. Ergonomics. 1962;5:167–169.
20. Rantanen T, Era P, Heikkinen E. Physical activity and the changes in
maximal isometric strength in men and women from the age of 75
years to 80 years. J Am Geriatr Soc. 1997;45:1439–1445.
21. Shephard RJ. Physical Activity and Aging. London: Croom Helm;
1987.
22. National Heart Foundation of Australia. Risk Factor Prevalence Study,
No. 3, 1989. Canberra: National Heart Foundation of Australia, 1990.
23. Pollack ML, Wilmore JH. Exercise in Health and Disease. Sydney:
Saunders; 1990.
24. Durnin JV, Womersley J. Body fat assessed from total body density
and its estimation from skinfold thickness: measurements on 481 men
and women from 16–72 years. Br J Nutrition. 1974;32:77–97.
25. Kulig K, Andrews JG, Hay JG. Human strength curves. Exerc Sport
Sci Rev. 1984;12:417–466.
26. Sale D, Quinlan J, Marsh E, McComas AJ, Belanger AY. Influence of
joint position on ankle plantarflexion in humans. J Appl Physiol. 1982;
52:1636–1642.
27. Winer BJ, Brown DR, Michels KM. Statistical Principles in Experimental Design. New York: McGraw-Hill, 1991.
28. Clarkson PM, Kroll W, Melchionda AM. Age, isometric strength, rate
of tension development and fiber type composition. Gerontology.
1981;36:648–653.
29. Young A, Stokes M, Crowe M. Size and strength of the quadriceps
muscles of old and young women. Eur J Clin Invest. 1984;14:282–
287.
30. Murray MP, Duthie EH, Gambert SR, Sepic SB, Mollinger LA. Agerelated differences in knee muscle strength in normal women. Gerontology. 1985;40:275–280.
31. Fisher NM, Pendergast DR, Calkins EC. Maximal isometric torque of
LIMB STRENGTH WITH AGE, PHYSICAL ACTIVITY, AND LIMB DOMINANCE
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
knee extension as a function of muscle length in subjects of advancing
age. Arch Phys Med Rehab. 1990;71:729–734.
Era P, Lyyra AL, Viitasalo J, Heikkinen E. Determinants of isometric
muscle strength in men of different ages. Eur J Appl Physiol. 1992;64:
84–91.
Bohannon RW. Reference values for the extremity muscle strength obtained by hand-held dynamometry from adults aged 20–79 years. Arch
Phys Med Rehab. 1997;78:26–32.
Lindle RS, Metter EJ, Lynch NA, Fleg JL, Fozard JL, Tobin J, Roy
TA, Hurley BF. Age and gender comparisons of muscle strength in
654 women and men aged 20–93 years. J Appl Physiol. 1997;83:
1581–1587.
Davies CTM, Thomas DO, White MJ. Mechanical properties of young
and elderly human muscle. Acta Med Scand. 1986;711(suppl):219–226.
Klein C, Cunningham DA, Paterson DH, Taylor AW. Fatigue and recovery contractile properties of young and elderly men. Eur J Appl
Physiol. 1988;57:684–690.
Kellor M, Frost J, Silerberg N, Iverson I, Cummings R. Hand strength
and dexterity. Am J Occ Ther. 1971;25:77–83.
Mathiowetz V, Kashman N, Volland G, Weber K, Dowe M, Rogers S.
Grip and pinch strength: normative data for adults. Arch Phys Med Rehab. 1985;66:69–74.
Cauley JA, Petrini AM, LaPorte RE, Black Sandler R, Bayles CM,
Robertson RJ, Slemenda CW. The decline of grip strength in the
menopause: relationship to physical activity, estrogen use and anthropometric factors. J Chron Diseases. 1987;40:115–120.
Bassey EJ, Harries UJ. Normal values for handgrip strength in 920
men and women aged over 65 years, and longitudinal changes over 4
years in 620 survivors. Clin Sci. 1993;84:331–337.
Murray MP, Gardner GM, Mollinger LA, Sepic SB. Strength of isometric and isokinetic contractions: knee muscle of men aged 20 to 86.
Phys Ther. 1980;60:412–419.
Hakkinen K, Hakkinen A. Muscle cross-sectional area, force produc-
43.
44.
45.
46.
47.
48.
49.
50.
B273
tion and relaxation characteristics in women at different ages. Eur J
Appl Physiol. 1991;62:410–414.
Johnson MA, Polgar J, Weightman D, Appleton D. Data on the distribution of fibre types in thirty-six human muscles: an autopsy study. J
Neurol Sci. 1973;18:111–129.
Edgerton VR, Smith JL, Simpson DR. Muscle fibre type populations
of human leg muscles. Histochemical J. 1975;7:259–266.
Lexell J, Taylor CC, Sjostrom M. What is the cause of ageing atrophy?
Total number, size and proportion of different fiber types studies in
whole vastus lateralis muscle from 15- to 83-year-old men. J Neurol
Sci. 1988;84:275–294.
Coggan AR, Spina RJ, King DS, Rogers MA, Brown M, Nemeth PM,
Holloszy JO. Histochemical and enzymatic comparison of the gastrocnemius muscle of young and elderly men and women. J Gerontol Biol
Sci. 1992;47:B71–B76.
Bassey EJ, Bendall MJ, Pearson M. Muscle strength in the triceps
surae and objectively measured customary walking activity in men and
women over 65 years of age. Clin Sci. 1988;74:85–89.
Schultz AB, Alexander NB, Ashton-Miller JA. Biomechanical analyses of rising from a chair. J Biomech. 1992;25:1383–1391.
Black-Sandler R, Burdett R, Zaleskiewicz M, Sprowls-Repcheck C,
Harwell M. Muscle strength as an indicator of the habitual level of
physical activity. Med Sci Sports Exerc. 1991;23:1375–1381.
Fiatarone MA, O’Neill EF, Ryan ND, Clements KM, Solaris GR, Nelson ME, Roberts SB, Kenhayias JJ, Lipsitz LA, Evans WJ. Exercise
training and nutritional supplementation for physical frailty in very
elderly people. N Engl J Med. 1994;330:1769–1775.
Received December 15, 1998
Accepted December 7, 1999
Decision Editor: Jay Roberts, PhD