Journal ofGerontology: BIOLOGICAL SCIENCES
1999,Vol. 54A, No.5, 8207-8218
In the Public Domain
Muscle Quality and Age:
Cross-Sectional and Longitudinal Comparisons
E. Jeffrey Metter,' Nicole Lynch,':' Robin Conwit,' Rosemary Lindle,':' Jordan Tobin,' and Ben Hurley'
'The NationalInstitute on Aging, GerontologyResearch Center,Baltimore,Maryland.
2The Departmentof Neurology, Bayview Medical Center,The Johns Hopkins Schoolof Medicine, Baltimore,Maryland.
"Department of Kinesiology, Universityof Maryland,College Park.
We addressed whether muscle quality (force per unit muscle mass) changes with age in cross-sectional and longitudinal
analysesfrom three groups from the Baltimore Longitudinal Study ofAging: (1) Isometric arm strength studied cross-sectionally in 617 subjects with muscle mass estimated by cross-sectional area (CSA) from arm circumference and by 24-hour
urinary creatinine excretion (CREAT); (2) longitudinal study for 10 to 25 years in 412 men using the same measures as the
first group; and (3) isometric knee extensor strength studied cross-sectionally in 675 subjects; muscle mass estimated by
CREAT, CSAfrom thigh circumference, and leg nonosseousfatfree mass (FFM)from dual energy x-rayabsorptiometry.
Muscle quality declined in both arm and leg with age in cross-sectional analyses using CSA and FFM, but not CREAT. No
age-associated arm muscle quality declines were observed longitudinally using CREAT or CSA. The relationship between
muscle quality and age is dependent on how muscle mass is estimated and on whether subjects are studied cross-sectionaliy
or longitudinally. In addition, CREAT may measure a muscle properly not accountedfor by CSA or FFM.
AGING is associated with the loss of muscle strength (1-6), but
1""\. the decline with age differs by age range and muscle group
(4). Muscular strength peaks at ages 20-35 and plateaus or shows
early declines from approximately ages 35-50. Definite declines
in strength become apparent at about the age of 50 with more
rapid declines above the age of 65 years (3-6).
The factors causing age-associated declines in strength are
not well understood. One hypothesis is that changes in strength
result strictly from loss of muscle mass. For this hypothesis to
be true, strength generated per unit of muscle mass (that we
have termed muscle quality) should remain constant throughout
the adult life span. However, this issue remains unresolved.
Some studies report no age-associated changes in muscle quality (7-11), whereas others find consistent declines (2,12-14).
Few studies have examined the relationship of strength to muscle mass longitudinally in the same subjects (3).
Possible explanations for the discrepancy in the reports of
muscle quality include differences in study populations, gender,
muscle groups studied, strength measures, and the methods used
to estimate muscle mass. At least 21 studies have examined muscle quality in relationship to age and/or gender (2,3,6-24). The
studies examined strength in different muscle groups using isometric, concentric isokinetic, or eccentric isokinetic measures.
Muscle mass was estimated either for a specific region or for the
total body. Regional estimates included anthropometry to measure cross-sectional area (CSA) or circumference; computed tomography (CT), ultrasound, or magnetic resonance imaging
(MRI) for cross-sectional area; and dual x-ray absorptiometry
(DXA) for regional mass. Total body muscle mass or total fat
free mass was evaluated by DXA, bioimpedence, hydrostatic
weighing, or creatinine excretion. Many of these methods give
indirect estimates of muscle mass which can make accurate assessment problematic (25,26). Each method is based on assumptions that are critical to the accuracy of the estimate (19). Many
of the assumptions do not consider age-associated alterations in
tissue composition; e.g., measures of subcutaneous and intramuscular fat are often not accounted for when using anthropometric techniques. However, some of the more indirect methods
are often the only available way to examine large samples of
subjects at reasonable costs. Estimating muscle quality by using
total body muscle mass estimates seems to offer further interpretation problems when explaining strength in a specific muscle
group. However, reasonable correlations are found between total
and regional body estimates of muscle mass (3,27).
The present study relates muscle quality to age using cross-sectional and longitudinal data on upper and lower body strength in
men and women from the Baltimore Longitudinal Study ofAging
(BLSA). It compiles muscle quality measurements from the
BLSA, adds new measurements to the isometric strength of the
knee extensors and DXA reported by Lindle and colleagues (6),
and adds to the creatinine measurements reported by Tzankoff
and Norris (28). The following questions were addressed: (a) Does
muscle quality change with age? (b) Does muscle mass account
for the age-associated losses of strength? (c) Do age changes in
muscle quality differ by gender? (d) Do different methods of muscle mass estimation lead to different conclusions regarding age-associated changes in muscle quality? and (e) Do cross-sectional
and longitudinal designs lead to the same conclusions? Strength
has been measured in the BLSA using two distinct protocols.
From 1960 to 1985, isometric strength was measured in the arms
(5), allowing for longitudinal analysis of BLSA men who were
retested over a period up to 25 years. Since 1992, arm and leg
isokinetic strengths have been measured using the Kin-Com dynamometer. Isometric strength is measured in the knee extensors.
Several methods were used to estimate muscle mass. From 1960
to 1985, 24-hour urinary creatinine excretion (CREAT) and arm
circumference assessed by anthropometry were used. Since 1992,
DXA has been added, allowing for a currently accepted accurate
method to assess nonosseous fat free mass (FFM). In order to
keep strength measures as similar as possible in estimating muscle
B207
B208
METTER ET AL.
quality over the two time periods, we chose to use the isometric
strength available for the knee extensors to examine muscle quality based on DXA, and to compare how FFM estimated by DXA
compared to the older methods of estimation. Parts of this data
have previously been reported (3-6,28,29); however,none of these
reports focused on both cross-sectional and longitudinal changes
in isometric strength in relationship to several estimators of musclemass.
METHODS
Subjects
Subjects consisted of men and women participants in the
BLSA (30), who are examined every 1 to 2 years. They tend to
be well educated with over two thirds having some college education. No exclusionary health criteria were used in this study, as
health factors were not found to have an important role in explaining muscle strength in these subjects (5). Because of concerns regarding the potential impact of impaired renal function
on the use of 24-hour creatinine excretion for estimating muscle
mass, the subjects were examined for aberrant serum creatinines.
No subject was found to have a creatinine level during any visit
where serum creatinine was measured that exceeded 1.5.
Furthermore, only six subjects had a history of a renal diagnosis
that would potentially affect creatinine excretion. No subject was
in acute or chronic renal failure during the course of the study.
Cross-sectional analyses were performed based on the most
recent visit in which strength measures were collected. Subjects
included 511 men (age range 19.7-92.6 years) and 106 women
(age range 17.6-84.4 years) for the arm strength comparisons.
Isometric knee extensor measures were obtained on 353 men
(age range 19.9-90.0 years) and 322 women (age range
20.2-92.2 years) of whom 210 men and 251 women had FFM
estimated by DXA.
Longitudinal analyses of arm isometric strength were restricted
to 412 male subjects who had follow-up strength measurements
for more than 10 years. A minimum of 10 years was selected to
give better estimates of individual change. Examination of all men
with longitudinal measures yielded similar findings. Longitudinal
data in women were available for an average of 2 years, but are
not reported here.
StrengthTesting
Two different strength protocols have been used in the BLSA.
Isometric muscle strength was tested in the arm over a 25-year
period from 1960 to 1985. The second protocol incorporated in
1992 included assessment of isometric knee extensor strength.
Isometric strengthtesting ofthe ann.-Muscle strength was
tested in an apparatus designed to measure four tangential components of arm movement. The methods are described in detail
by Shock and Norris (29) and Metter and colleagues (5).
Subjects were seated with shoulders supported by a rigid back
and straps with the upper arms perpendicular to the floor, parallel to the midline axes of the body, and forearms parallel to the
floor. Wooden handgrips were connected to a rigid strain-gauge
force transducer attached through bridge circuits to an oscillographic recorder. The transducers were calibrated by using a
spring balance and known weights. Subjects pulled against the
grips in four directions: up, down, forward, and backward along
the axis of the forearm. Each direction was tested three times
with the highest value accepted. A 10-second rest period occurred between trials. In addition, handgrip strength was tested
using an adjustable Smedley hand dynamometer (C.H. Stoelting
Co., Wood Dale, IL) as previously described (3). A total arm
strength score was calculated by summing the five measures
from both arms. Test-retest reliability for the total arm strength
score was estimated by taking measurements on consecutive
days from 29 subjects with a correlation of .87 (N = 29, p <
.001). No evidence was found for a learning effect associated
with the procedure as the average strength on day 1 was 166.52
and day 2 was 168.24 (difference = 1.72 ± 14.74,p =NS).
Isometric knee extensor strength.-Quadriceps strength was
tested on the Kin-Com Model 125E dynamometer. Subjects were
tested in the seated position with the back supported against a
backrest and strapped at the waist, thigh, and chest. Average
torque was measured isometrically at 120 degrees (from full flexion) during attempted leg extension. The methods for these tests
are described in detail by Lindle and colleagues (6).
MuscleMass Estimation
Muscle mass estimators have included 24-hour creatinine
excretion (CREAT) and anthropometric estimates of extremity
cross-sectional area (CSA) over the entire course of the BLSA,
and DXA has been implemented over the past 5 years. Total
arm CSA for both arms was calculated from mid-arm circumference adjusting for skinfold thickness. Arm circumference
was measured with the forearm relaxed at the widest point and
the hand in an open position. The arm CSA was corrected by
skinfold thickness using the equations for men and women
from Heymsfield and colleagues (31). Thigh CSA was calculated from thigh circumference, but no adjustment could be
made for skinfold thickness.
Total body muscle mass was estimated by CREAT using standard clinical procedures as previously reported (3,29). To examine the degree of variability in CREAT in our study, we examined the residuals from within-subject regression analyses of
CREAT by age from those who had longitudinal measurements.
The total squared residual was 67296862 for 3254 observations,
implying an average mean residual of 143. The average creatinine value for the 3254 measures was 1682 mg per 24 hours.
The mean residual was 8.5% of the mean, which is within the
test-retest variability range reported in the literature (27,32).
Leg nonosseous fat free mass (FFM) was estimated by DXA
(Model DPX-L, LUNAR Radiation Corp., Madison, WI) using
the LUNAR Corporation Version 1.2i DPX-L software. DXA
has been used to estimate body composition since 1992 in the
BLSA. The leg region was defined as the area below the greater
trochanter of the dominant leg.
DXA has been shown to strongly relate to muscle mass by examination of meat blocks by DXA and chemical analysis (33).
DXA reliability was assessed in 12 older men (>65 years of age)
by performing two total body scans, 6 weeks apart. Serial values
were 52.94 ± 1.23 versus 53.03 ± 1.36 kg for muscle mass, representing a difference between the two scans of approximately
0.01% (4,6). The scanner was calibrated daily prior to testing. In
a separate study involving muscle volume, responses to unilateral
strength training and detraining were assessed in 11 young men
(25 ± 3 years, range 21-29 years), 11 young women (26 ± 2
AGEAND MUSCLE QUAliTY
years, range 23-28 years), 12 older men (69 ± 3 years, range
65-75 years), and 11 older women (68 ± 2 years, range 65-73
years). At baseline, after strength training and detraining, a very
strong positive linear relationship was found between DXA estimated thigh muscle mass and MRI measured muscle volume (r
= .95, .95, and .93, respectively;p < .01)(34).
DataAnalysis
Statistical analyses were performed using SPSS 7.5 for
Windows (SPSS, Chicago). Preliminary data exploration examined for evidence of systematic drift in the variables over the 25
years that the arm strength protocol was included in the BLSA.
A small drift was found in the arm isometric strength (r = .04)
and creatinine excretion (r = .03) with time. Therefore, these
variables were adjusted by regressing each variable on date and
relating them to the first 5 years of the study for men and 4
years for women. To better understand the relationships between the muscle mass estimators and strength, variables were
normalized by converting to a percentage of the average value
for young adults in their 20s. This is a standard approach that is
used in studies examining age-associated changes in strength.
Cross-sectional analyses were carried out using analysis of
variance (ANOVA) for age group comparisons, with post hoc
multiple comparisons by Tukey b. Tukey b is a range test that
gives subsets of age groups that are not statistically different.
Any age decade can be in several subsets that represent unique
combinations of age decades, e.g., 30-year-olds could form a
subset with 20-year-olds, and a separate subset with 40- and
50-year-olds, meaning that 30-year-olds do not statistically differ from 20-,40- or 50-year-olds, whereas 20-year-olds differ
significantly from 40- and 50-year-olds. Multiple regression
analyses of strength and muscle mass measures were examined
by age and age-squared. Analyses were done separately for men
and women and/or in a combined model. Significance level
was set to p < .05 for all analyses.
Longitudinal data were examined using a two-stage model
(35). Regression functions, which included a quadratic term for
B209
age, were defined for each subject, allowing for the determination of predicted values at each visit. For measurements of
strength, CREAT, and CSA, the quadratic term was not significant and only the linear model was examined. For muscle quality, the quadratic term was significant and included in the analysis. Subjects were grouped by age decade based on age at first
measurement. The slopes, initial age, and time of follow-up
were averaged by age group. The resulting average equation
was used to plot the data from the average first visit age to average last visit age for each age decade.
A random-effects model was tested using the statistical program MIXREG (36) for strength per unit of muscle mass comparisons. The basic form of the model was
strength/mass, = (~o + rQi) + (~l + r 1i) X time + (~z + rZi) X
time' + ~3 X agegrouPj + ei
where time is the time from the first measurement and agegrouPj are dummy variables for the age decades. ~o, ~l' ~z, and
~3 are standard regression coefficients for the fixed group effects. The random effects are represented by rQi, r 1i , and r Zi ,
which are the deviations from the betas for each individual. The
random-effects model estimates the betas, and tests whether rQi'
rJj, and rZi' the individual effects, differ from zero. If the rs differ
then there are individual differences that may need to be considered in understanding the relationships.
REsULTS
Cross-Sectional Analysis
Arm isometric strength. -Arm muscle strength and muscle
mass by age group are shown in Table 1. The strength and creatinine excretion data are a subset from a previous publication (5).
The 80-year-old and older group included 33 men (21 between
80 and 82 years, 10 between 83 and 87 years, one aged 89, and
one aged 92 years), and 5 women (all 84 years or younger). Oneway ANOVA revealed age group differences at p < .001 for all
Table 1. Cross-Sectional Age Differences in Arm Strengthand Muscle Mass
Age (years)
Women
Strength (kg)
N
Mean
SD
CREAT(mg/24 hr)
Mean
SD
Ann CSA (em')
Mean
SD
Men
Strength (kg)
N
Mean
SD
CREAT(mg/24 hr)
Ann CSA (em')
Mean
SD
Mean
SD
20-29
30-39
40-49
50-59
60-69
70-79
80+
11
2311
42
11701
242
65.7
13.3
31
2161
37
101412
239
60.3
12.4
13
2161
38
105412
173
54.7
9.3
19
1941
36
95212
260
57.6
15.6
17
17912
42
8482.3
169
60.9
20.6
10
1472
47
7982,3
215
63.8
31.8
5
1442
22
6533
170
55.5
21.4
46
4361
53
17911
327
113.41
23.6
80
4461
56
176812
288
123.01
22.7
60
4261,2
58
169612
323
125.11
27.7
94
3992
54
15982
236
120.11
23.3
108
3693
57
14333
90
33<t
33
289-'
47
11465
235
86.23
232
114.63
26.0
52
12874
289
99.02
17.9
19.2
By one way ANOVAsignificantage differencesfound at p < .001 for all variablesexcept women arm CSA (p =.54). Post hoc analysisby Tukey b gives homogeneous groupsthat do not significantly differat p < .05 for the variable. Each subsetis representedwith a superscriptnumber.For example,for strengthin women, the 20,
30,40,50 and 60 year decadesrepresentone group with no significant differences between the age decades(superscripted by 1),and the 60, 70, and 80+ decades form a
separategroup (superscripted by 2). Up to fivegroups were found in the comparisons in this table for CREATin men (superscripted by 1-5). See Resultssection.
B210
METTER ETAL.
variables except for women's cross-sectional arm area. Post hoc
analysis using Tukey b showed no differences in arm isometric
strengthbetween20-,30-,40-,50-, and 60-year-old women (subset 1), and no differences between 60-, 70-, and 80-year-old or
older women (subset 2) (p < .05, r = .32). Arm strength in 20-,
30-, and 40-year-oldmen did not differ (subset 1),whereas older
age decades were significantlydifferent from each other and the
younger individuals (subsets 3, 4, 5) (p < .05, r = .44). The age
group relationships were very similar for CREAT as for muscle
strength. Arm CSA showed less age-associatedchanges than either strengthor CREAT.
Age differences in arm strength, CSA, and CREATare shown
in Figure 1 as regression equationswith a quadratic fit for age. All
variables are expressed as a percentage of the average values for
2D-29.9-year-old women and men. Significant gender (p = .04)
and quadratic age effects (p < .01) were observedfor strengthexpressed as a percentage of the 20-year-olds, but with no gender-
A
120
"C
(5
L-
eu
..--"--
100
Strength
--....
Men -Arm
.......... <,
<,
<,
<,
<,
CREAT
>.
-...
_---_
""/< ..
a>
0
N
---
CSA
rJ)
80
<,
-,
-,
0
c::
a>
0
L-
-,
.....
-,
-,
........ ~
60
a>
a..
40
20
40
60
80
Age (Yrs)
B
120
VJ
Women -Arm
"C
(5
L-
eu
100
---
>.
-...
0
N
-
/"'
a>
» - > CSA
r
80
0
c::
a>
~
60
a>
a..
40
+----,------,-----,--.----,-----,--------1
20
30
40
50
60
70
80
90
Age (yr)
Figure 1. Age-associated changes for arm isometric strength, CREAT, and
arm CSA in men (A) and women (B) using a quadratic term in the regression.
The distribution of the data is shown in Table 1. Data are presented as a percentage of the average value for 20-29.9-year-old subjects. (A) Significant age
effects were found in men for strength (,-2 .44, p < .(01), CREAT in men (,-2
.30, p < .001), and arm CSA (,-2 = .21, p < .001). The quadratic curves for
strength and CREAT did not differ with age, whereas strength and arm CSA
differed with age (p < .01). (B) Significant age effects were found in women for
strength (,-2 =.30,p < .(01) and CREAT (,-2 = .19,p < .(01), but not arm CSA
(,-2 =.006, p =NS). The quadratic curves for strength and CREAT did not differ
with age (p = .42), whereas strength and arm CSA differed with age (p < .01).
=
by-age interaction, implying a similar age-associated percentile
changein strengthfor women and men.The percentagechangein
CREATfollowed a similar course with increasing age, with both
women and men showing a 50-60% decline by age 80 to 90, a
significant quadratic age effect (p < .01) and gender effect (p <
.001),but no interaction. On the other hand, in women, there was
no age-associatedchange in arm CSA (p = NS). In men, CSA increased into the 40s before startingto decline. In comparing arm
CSA with arm strength, CSA declined to a lesser degree than
strength over the lifespan (p < .001), and the difference became
significant in the 4O-year and olderage groups.
No significantage effect was observed for muscle quality expressed as strength per kilogram CREAT,whereas strength per
CSA showed a significant age-associated quadratic decline for
men (p < .001) (Figure 2). Over the age range from 20 to 80
years, muscle quality estimated by CSA declined by 16.8% in
men and 33% in women. The analysis was repeated with subjects who survived for at least 10 years after the test to examine
the potentialeffect of death on decreasingmuscle quality. Again,
muscle quality declined in relationship to CSA but not CREAT.
To test the effect of potential outliers on the analyses, the regression analysiswas repeated usingonly subjectswithin two or three
standarddeviationsof the mean for women and men. Restricting
the sample size by either criterion did not affect the overall conclusion, nor alter the regressioncoefficients to any great degree.
The age-related differences for CSA and CREAT suggest
that they relate to strength differently. The correlation between
arm CSA and CREAT was good (r = .70); however, it was strikingly different for women (r = .15) than men (r = .56).
Multiple-regressionanalysis was used to examine which factors
had independent contributions to arm strength. A series of models was tested starting with age and gender. Subsequent models
added arm CSA, CREAT, or both mass estimators. Table 2
shows the tested regression models. Each column represents a
single model with the independent variables that were included
listed at the top. Each row gives the individual variable or interaction term and the significance level (if p < .05) for the variable included in the model. Age and gender accounted for most
of the explained variance (Table 2, Arm Strength, fourth column, r = 73), whereas CSA and CREAT each only modestly
improved the model; with both terms included, = .80 (Table
2, Arm Strength, last column). This finding implies that both
CSA and CREAT have features associated with muscle strength
that are independent of age and gender.
=
Leg isometric strength.-As in the arm, isometric strength in
the leg extensors (Table 3) declined by age decade in women (p
< .001) and men (p < .001).The isometricand DXA data include
subiects reported by Lindle and colleagues (6) and more recent
measurements. The 80-year-oldand older group included30 men
(10 between 80 and 82 years, 16 between 83 and 87 years, and 4
between 88 and 90 years) and 13 women (8 between 80 and 82
years, 1 between 83 and 87 years, and 4 between 88 and 90
years). In women, post hoc analysis by Tukey b revealed no age
differences in leg strength for 20- through 50-year age groups
(subset 1), with subsequent declinesin older age groups (subsets
2 and 3). Post hoc analysis in men found strength was similar in
20-, 30-, and 40-year-old men (subset 1),and in 30-, 40-, and 50year-oldmen (subset 2), implying that the 50-year-old men were
weaker than 20-year-old men. For thigh CSA in women, the 20-
AGE AND MUSCLE QUALITY
A
B211
250 . . . - - - - - - - - - - - - - - - - - - - - - - - - - - - - - ,
;e
o
-
0::J
e
........ Strength/CREAT
200
o
o
_ _ Strength/CSA
Q)
00
(=.08, p<.OOO
C>
o
o
(=.00, p=ns
C>
CO
"C
o
Men
o
o
150
0
o
o
o
o
0
~
CO
Q)
~
o
N
100
'0
Q)
C>
....c:CO
~
Q)
50
a..
O-+-------r--------.--------r-----.......,..-----~
o
40
20
60
80
100
Age (years)
B
--
200 , . . . . - - - - - - - - - - - - - - - - - - - - - - - - - - - - - ,
Women
'#.
0:J
e
C>
Q)
•
o
o
•
o
o
........ Strength/CREAT
~=.02, p=ns
150 _ _ Strength/CSA
~=.16, p<.001
o
o
•
•
• •
•
•
o
o
C>
co
-0
o
~
CO
Q)
100
~
o
N
'5
Q)
C>
!1
c:
50
~
•
Q)
a..
OL------------------------------.. .
o
10
20
30
40
50
60
70
80
90
100
Age (years)
Figure 2. Ann muscle quality changes with age. Muscle quality is shown when expressed in relationship to creatinine excretion (CREAT) (open circles and dashed
lines) and for cross-sectional area (CSA) (filled circles and solid lines). Muscle quality in men (A) and women (B) is expressed as the percentage of the 20-year-old
group. Regression lines are shown with 95% confidence intervals on the regression.
METTER ETAL.
B212
Table2. Comparison of MultipleRegressionModelsfor Arm or Leg IsometricStrength
Variables in Each Model
Age
Group
Variables
Age Group
Gender
Age Group X Gender
ArmCSA
Age Group X Arm CSA
Gender X Arm CSA
CREAT
Age Group X CREAT
Gender X CREAT
R2
Gender
Gender,CSA
orFFM
Age Group,
Gender
Ann strength
.000
.000
.025
.000
.000
.000
.52
.69
.000
Leg strength
.000
.000
.014
.000
.000
Age Group
Gender
Age Group X Gender
ThighFFM
Age Group X Thigh FFM
Gender X Thigh FFM
CREAT
Age Group X CREAT
Gender X CREAT
R2
Gender,
CREAT
.000
.000
.000
Age Group,
Age Group,
Gender,
Gender,CSA
CREAT or FFM, CREAT
.000
.000
.000
.000
.000
.000
.000
.002
.67
.036
.76
.80
.021
.000
.003
.000
.13
Age Group,
Gender,CSA
orFFM
.73
.79
.010
.004
.055
.000
.007
.003
.000
.006
.000
.11
.25
.47
.48
.61
.34
.51
.67
Each column represents a regression model, with significantp values presented for each variable in the model on the corresponding row.A dash means that the
variable was entered but was not significantat p < .05. Absence of a value means that the variablewas not included in the model. CSA or FFM means that CSA was
used in the arm models, and FFM in the leg models.
Table3. Cross-Sectional Age Differences in Leg Strength, FFM, CREAT, and ThighCSA
Age (years)
Women Strength (nm)
N
Mean
SD
CREAT (mg/24 hr)
N
Mean
SD
Thigh CSA (em')
N
Mean
SD
FFM(kg)
N
Mean
SD
Men Strength (nm)
N
Mean
SD
CREAT (mg/24 hr)
N
Mean
SD
Thigh CSA (em')
N
Mean
SD
FFM(kg)
N
Mean
SD
20-29
30-39
4Q-49
50-59
60-69
70-79
33
4471
102
14
11161,2,3
44
445 1
114
15
13341
214
40
3061
79
28
7.41
1.0
105
4251
105
46
11801,2
315
103
2991,2
68
90
6.72,3
66
3961
97
21
103Q2,3
297
64
2941,2
64
53
6.72
.9
39
3361,2
79
11
10132.3
166
38
2911,2
57
32
6.42.3
.9
22
3152
74
6
85P
96
20
2562
50
15
6.22,3
36
6631,2
148
16
16821,2
526
28
2972
66
20
10.11,2,3
67
6661,2
156
32
17041,2
441
66
63
59Q2
110
31
16971,2
407
60
2921,2
46
38
10.31
78
51Q3
117
43
14822
345
76
2641,2,3
57
49
9.32.3,4
54
4633
115
23
132Q2,3
285
49
2562,3
57
27
9.23,4
1.0
179
30
2841,2
61
22
6.821,2
1.1
25
6991
211
12
19421
658
23
2861,2
76
16
10.71
1.1
1.3
.9
29~
81
48
10.21
1.5
1.1
1.1
.8
80+
13
2382
59
1
299
13
2572
54
11
5.73
.3
30
3884
85
9
10753
314
28
2323
42
12
8.44
.9
One way ANOVArevealed age differences at p < .05 for all variables. Post hoc analysis by Tukey b gives homogeneous subsets that are represented with superscriptnumbers. A descriptionof interpretationof the superscriptsis given with Table 1.
AGE AND MUSCLE QUALITY
B213
to 60-year-old groups were similar (subset 1), with overlap with
the older age groups (subset 2). The findings suggest little age-associated change in thigh CSA. In men, thigh CSA showed little
change (subsets 1 and 2) until the 70-79-year-old age group (subset 3). Thigh FPM as assessed by DXA did not differ in men
through the 50-year-old group (subset 1), nor in the 60 and older
age range (subset 3). In women, the only significant differences
were among the 30-year-olds, and those 50 and older.
As shown in Figure 3, the percentage change in CREAT with
increasing age closely tracked the differences in strength in
men. The pattern is generally similar to that observed for the
arm. CSA as a percentage of the 20-year-old age group declined less than the percentage change in strength for both
women and men, as did the percentage change in FFM. A significant difference in FFM was found by gender (p = .03), with
no interaction with age. The difference between leg strength
and FFM began in the 50-year-old age group (p < .01) and became larger with increasing age (p < .001).
As shown in Figure 4, no significant age differences were
found for muscle quality when expressed as strength per kilogram
CREAT for either gender. However, a significant (p < .001) ageassociated linear decline was found when muscle quality was expressed as strength per CSA or strength per FFM (Figure 4). The
findings with respect to CSA and CREAT for the leg were similar
to what was observed for the arm. From age 20 years to age 80
years, muscle quality estimated by CSA declined by 30.6% in
men and 38.8% in women, and by 39.0% for men and 31.2% for
women when muscle quality was estimated by FFM.
The correlation between FFM and CREAT (r = .69) was
greater than that between CSA and CREAT (r = .27) and that
between FFM and CSA (r = .12). However, when men and
women were considered separately, the correlations were similar, i.e., FFM and CREAT (rwomen = .59, r men = .54), CSA and
CREAT (rwomen = .44, r men = .47), and FFM and CSA (rwomen =
.49, r men = .51). Multiple-regression analysis was used to identify the factors with an independent contributions on leg
strength (Table 2). Age, gender, and leg FFM accounted for
Longitudinal data were collected for an average of 15.4 ± 3.9
years (range 10.0-25.5) on 412 men. This is a subset of the men
previously reported (5) who had both strength and muscle mass
estimates. A regression line was developed for each man with
the predicted values used to determine average longitudinal
changes in arm strength, CREAT, and arm CSA by age decade
at the first measurement (Figure 5). For men who had their first
visit in their 20s and 30s, arm strength showed no longitudinal
declines, whereas longitudinal strength losses were seen in all
older age groups. CREAT showed a modest longitudinal decline
in the 20-year-old age group. In all other age groups CREATremained lower than strength. No significant difference was found
between the slopes for strength and CREAT. However, the relationship between strength and CSA differed from strength and
CREAT. In the 20- and 30-year-old groups, the longitudinal
changes in arm CSA were the same as those observed for arm
strength, whereas for older age groups, the decline in strength
was greater than the decline in CSA (p < .001).
To examine the longitudinal changes in muscle quality,
strength was expressed per gram CREAT (N = 284), and per
mm? CSA (N = 229) (Figure 6). In calculating the ratio for
CREAT, six clear outlying measurements were identified and
eliminated from the analysis from 1681 total measurements.
For the CSA data, only three men over age 70 (70-73 years of
age) had three or more measurements, which limited the analysis in the older age group. Therefore, the three men were included in the 60-year-old group. Cross-sectional analysis based
on age of first evaluation revealed a small but significant increase in muscle quality when expressed with CREAT (p < .001,
A 120 - , - - - - - - - - - - - - - - - - - - ,
B 120
en
~eo 100
------- --
Q)
>-
LongitudinalAnalysis
Women - Leg
en
Men - Leg
"0
61 % of the variance (Table 2, Leg Strength, fifth column),
whereas age, gender, and CREAT accounted for 51 % of the
variance (Table 2, Leg Strength, seventh column). Including
both FFM and CREAT (Table 2, Leg Strength, last column) accounted for 67% of the variance, 6% better than when FFM
was considered with age and gender.
"0
6 100
L-
.......
eo
Q)
.......
>-
- - - - -<,
. . <,
--
~ 80
o
~~
-a
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80
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c:
c:
~ 60
Q)
~
··..CREAT
60
Q)
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Strength
a..
a..
40
---+-----.,...-----.,...-----,----------1
20
40
60
Age (Yr)
80
100
40
20
40
60
80
100
Age (Yr)
Figure 3. Age-associated changes for leg isometric strength, CREAT, leg CSA, and leg FFM in men (A) and women (B) using a quadratic term in the regression. The
distribution ofthe data is shown in Table 3. Data are presented as a percentage of the average value for 2o-29.9-year-old subjects, (A) Significant age effects were
found in men for strength (r =.32,p < ,OOl),CREAT (r =.17,p < ,(01), leg CSA (r =.11,p < .(01), and FFM(r =.23,p < ,OOl).Differences between the quadratic
curves for strength and CREAT, CSA, and FFM increased with age (p < ,OI,p < ,OOI,p < ,001) respectively. (B) Significant age effects were found in women for
strength (r =.18,p < .(01), CREAT (r =.14,p < ,(01), leg CSA (r =.03,p < .05), and FFM (r =.11,p < .(01). Differences between the quadratic curves for strength
and CREAT did not increase with age (p =NS); however, differences between strength and CSA (p < ,OOl)and FFM (p < ,OOl)increased with age.
B214
METTER ETAL.
Men
A
200 .......-----------...., 200 . . , . - - - - - - - - - - - - .
r2=.03, p=NS
180
o~
-
r2=.11, p<.001
180
0
160
160
140
140
o
120
120
200 - r - - - - - - - - - - - - - - ,
Strength/CSA
Strength/CREAT
•
•
• •
• •
•
• •
• • • •
•• •
Strength/FFM
r2=.23, p<.001
180
160
.. .. ..
............ ...
..
.
....
.. ..
140
•
120
<, ......
100
100
-a·~·~·~o~
80
80
80
....
....
60
60
40
40
40
20
20
20
O-l-----r---~----r------J
40
20
60
80
O+------.-----r------.----'
20
40
60
80
200 ....--------------,
200
..
~.~.1r..~...... l' .........·o·t. ..
..
..
110
tt
' t."
..
......
..
-, ~
..
"'
O+------.------.----r------J
I
I
20
40
60
80
r2=.01, p=NS
180
200 r - - - - - - - - - - - - - - - ,
Strength/CSA
Strength/FFM
r2=.13, p<.001
180
180
a. 160
160
140
140
o 120
eu
~ 100
o
120
120
100
100
80
80
80
eu
60
60
60
~
40
40
40
20
20
20
r2=.15, P<.001
160
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Age (years)
-r-----------------,
Strength/CREAT
-e
..
Women
B
o~
.. ~
~~~t.
.. .. .(:..
..
..
Age (years)
Age (years)
..
.... .. ~
......
60
6:
~l'_..
..... :'~ .. :t ........
100 .... 1'\............. .. .. .. ...
140
"'C
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Q)
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0+------.---~-~---y----1
I
o
20
40
60
Age (years)
80
100
O-t----.-----,---,----r------l
o
20
40
60
Age (years)
80
100
O+---.-------r--.-----..---~
-T
o
20
40
60
80
100
Age (years)
Figure 4. Leg muscle quality changes with age. Muscle quality is expressed in relationship to CREAT, CSA, and PPM for (A) men and (B) women in separate
groups. Muscle quality is expressed as the percentage of the 20-year-old group. Regression lines are shown with 95% confidence intervals on the regression.
,-2 =.05), but no change was observed with CSA (p =ns, ,-2 =
.000). When based on the final evaluation, muscle quality did
not change significantly with age for either CREAT or CSA.
These findings are different from the cross-sectional analysis
for the entire group of 511 men where a decline in arm muscle
quality was found when estimated by CSA but not by CREAT.
AGEAND MUSCLE QUAUTY
Longitudinally, strength per CSA remained relatively constant
across the age decades, whereas strength per CREAT appeared to
increase particularly from the 20-year-olds to the 30-year-olds
(Figure 6). Using a random-effects model to examine the repeated measures, a significant age group effect was found for
strength per CREAT, with the 20-year-old subjects differing from
the other age decades except the 40-year-old group. Significant
random effects were found for the intercept (p < .00 1) and time
(p = .001), implying there were significant differences between
subjects for strength per CREAT initially and over time. For
strength per CSA, no significant age group differences were
found; however, the 6D-73-year-old group was borderline for a
main effect (p = .057). A significant random effect was observed
for the intercept (p < .001), but not for time or time squared.
120
~
:J
110 -
en
eu 100 Q)
...
90 -
u:
80 -
::2:
f!?
"C
0
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eu
Q)
>0
N
0~
~----
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:- . ~"
..
.
70 -
...... ......
.
'.
......
_ _ Arm Strength
ArmCSA
-:-:.-:-:.-:-:.-:-: CREAT
60 50 40
20
I
I
I
I
I
I
30
40
50
60
70
80
90
Age (yr)
Figure 5. Longitudinaldata from men studiedfor more than 10 years for arm
strength(solidlines),muscle massestimatedby CSA (dashedlines),and muscle
mass estimatedby CREAT(dottedlines).Subjectswere groupedby age decade
at first assessmentwith the length and location of the line based on averageinitial and final age for the age group.Valuesfor each variablewere expressedas a
percentage of the averagevaluesfor the initialvisitsof the 20-year-old group.
C
Q)
140
E
lI!
:::J
III
l'CI
E-?-~~
120
Q)
~
'U
5
Iii
Q)
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>0
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80
E
_
Arm Strength/CREAT
___ Arm Strength/Arm CSA
'0
Q)
Dl
~
~
60
Q)
c,
40
20
30
40
50
60
70
80
90
Age (years)
Figure 6. Longitudinal data from men studied for more than 10 years. The
ratio of arm isometricstrengthto CREAT(solidline) and to CSA (dashedlines)
are plotted against average first age to the average last age. Men are grouped
based on age decade at first visit.
B215
DISCUSSION
To the best of our knowledge, this study is the first report that
has combined cross-sectional and longitudinal designs to address the issue of muscle quality in both upper and lower extremity muscle groups across the entire adult age span. Several
reports have examined longitudinal changes in strength (1,37,38),
but none had as large a cohort followed for more than 10 years.
This study has addressed several questions: (a) Does muscle
quality change with age? (b) Does muscle mass account for the
age-associated losses of strength? (c) Do age changes differ by
gender? (d) Do different methods of muscle mass estimation
lead to different conclusions regarding age-associated changes
in muscle quality? and (e) Do cross-sectional and longitudinal
designs lead to the same conclusions? The study adds further information regarding strength and muscle mass with new data on
the isometric strength of knee extensors, creatinine excretion,
and DXA to previous reports from the BLSA (3-6,28,29).
Does Muscle Quality Change With Age?
Our study found a mixed response to the question. In the
cross-sectional analyses, muscle quality showed an age-associated decline when using CSA or FFM, but not with CREAT
(Figures 2 and 4). The longitudinal analysis of muscle quality
demonstrated less impressive changes for CSA (Figures 6)
than observed from cross-sectional analysis. One explanation
is that the cross-sectional and longitudinal cohorts had unrecognized differences which preserved muscle quality in the longitudinal subjects. One possibility was that less healthy subjects were included in the cross-sectional cohort. However,
when the cross-sectional analysis was repeated only with subjects who survived at least 10 years after the evaluation, the
age-associated differences persisted in muscle quality estimated by CSA.
The longitudinal findings and the cross-sectional findings
with CREAT are consistent with the cross-sectional study by
Frontera and colleagues (9), who found little age-associated
change in muscle quality when using creatinine excretion and
hydrostatic weighing to estimate muscle mass and FFM.
Pearson and colleagues (8) used anthropometric measurements
to estimate CSA and found an age-associated decline in muscle
quality in older women but not in older men. However, Young
and colleagues (7) found no age differences in women using ultrasound to estimate CSA, but younger men showed a higher
ratio of strengthlCSA than younger women and both older
women and men. In part, the difference in young men may relate to greater physical activity, as peak torque per cross-sectional area has been shown to be higher in young adults who
participate in resistive training compared to those who do not
(24). Other cross-sectional studies have shown declines in muscle quality with age using a variety of methods to estimate muscle mass (2,12-14). These studies have reported findings similar to our observations for the cross-sectional analysis using
FFMandCSA.
Thus, whether muscle quality declines with age depends on
how muscle mass is estimated and on the study design. We
found evidence both for and against the decline. The strongest
evidence for a decline in muscle quality was from the crosssectional analysis which determined FFM by DXA, whereas
the strongest evidence against a decline was from the longitudinal analysis determined by CREAT.
B216
METTER IT AL.
Does Muscle MassAccountfor the Age-Associated Losses
ofStrength?
Previous studies suggest a strong link between strength
losses with age and a decline in muscle mass (2,12-14), although the link is less clear in our study. The time course of
age-associated changes in CREAT paralleled changes in muscle strength better than other muscle mass predictors in the
cross-sectional analysis. This was particularly true in the arm in
men and women, and in the knee extensors in men. CREAT
began to decline at an older age than knee extensor strength in
women. In addition, CREAT paralleled arm strength in early
adult life, a period when CSA was increasing in men (Figure
1). Furthermore, in multiple-regression analysis, age and gender encompassed essentially all the variance that was accounted
for by adding CREAT to the model (Table 2). One interpretation of this result is that CREAT is tightly linked to age, so that
adding CREAT to age does not improve the model. Frontera
and colleagues (6) also found little relative change in muscle
strength in relationship to creatinine excretion. CSA and PPM
had a stronger independent effect on both arm and leg strength
than CREAT (Table 2). The best regression models included
age, gender, and either CSA for the arm or FFM for the leg.
The correlation between PPM and leg strength (r = .69) was the
same as the correlation between gender and leg strength, suggesting that the gender differences in strength are related to
gender differences in PPM.
These findings suggest that age has an effect on strength
which is independent of muscle mass. Hakkinen and colleagues
(11) argued that the age-related strength loss in older subjects is
multifactorial and cannot be totally explained by changes in
CSA. They suggested that changes in neural drive or qualitative
changes in the muscle are likely to be important factors. Brooks
and Faulkner (39) noted that when muscle was examined in rodents, a 20% deficit in force remained after accounting for the
effects of CSA. They argue that the deficit was likely due to a
decrease in cross-bridges per area or force per cross-bridge.
Taken together, these observations demonstrate an association
between PPM and CSA with age-associated strength declines.
However, mass alone does not explain the age effect on strength.
Do Age ChangesDiffer by Gender?
Men were stronger and had greater muscle mass than women
as observed in all studies. Gender accounted for about half of
the variance in arm strength and a quarter of the variance in leg
strength (Table 2), whereas age and gender accounted for about
75% of the variance in arm strength and half the variance in leg
strength. The age-associated changes in muscle strength were
similar by gender with a 40-50% loss of strength in the arm and
knee extensors from age 20 to 90. However, age predicted
strength better in men (one way ANOVA model: arm r = .44,
leg r = .34) than in women (arm r = .32, leg r = .20). In other
analyses, we found the association between age and muscle
strength was greater in men than women in both the upper extremities (4,5) and in the knee extensors (4,6). Also, the relationship between mass and strength was greater in men as noted in
most (11,14), but not all, studies (40). The difference between
studies appears to be in the ages considered. Men show a greater
relationship to muscle mass when the entire adult lifespan is
considered, whereas studies showing no differences examined a
narrower age range, typically young or middle-aged subjects.
Thus the age-associated loss of strength appears to be proportionately similar in women and men, but the relationship is
stronger in men. In addition, differences exist in the relationship
between gender and the age-associated losses of muscle mass,
which suggest that the mechanisms causing strength losses may
differ by gender.
Do Different Methods ofMuscleMass Estimation Leadto
Different Conclusions Regarding Age-AssociatedChanges in
Muscle Quality?
Three methods were used to estimate muscle mass.
Methodological and theoretical issues related to each method
raise questions about their validity for estimating muscle quality.
CREAT and anthropometric measures have been used for
many years, but these methods do not have the precision and
reliability of more modern methods including DXA. CREAT
estimates muscle mass with 17 to 20 kg total body muscle mass
per gram urinary creatinine. This estimate is dependent on a
number of assumptions which raise questions about accuracy
(27). Further problems with the estimate include daily variation
in urinary excretion of 4-8% (29), strenuous exercise increasing the output by 5-10%, and high dietary intake of creatine increasing the variability of the measure (27,29).
Despite the methodological issues, CREAT closely paralleled age-associated changes in isometric muscle strength and
can be a useful measure in large cohorts. In addition, CREAT
shows good correlation to other muscle mass estimators (26)
including arm muscle area (27) and lean body mass estimated
by potassium 40 (12). Likewise, in the BLSA, Kallman and
colleagues (3) found a positive correlation between CREAT
and arm circumference in men. Murray and colleagues (41)
have shown a strong linear correlation in rat muscle between
creatinine and myofibrillar protein mass. This suggests that creatinine may closely parallel changes in muscle strength because
it reflects the contractile part of the muscle tissue. Furthermore,
muscles that are high in type II muscle fibers have higher concentration of phosphocreatine than muscle high in type I fibers
(42,43). Because type II fibers generate greater force than type I
fibers, higher proportions of type II fibers should yield higher
levels of creatinine and be associated with greater strength.
Anthropometry can be a reliable estimator of muscle mass.
Martin and colleagues (44) found strong correlations between
limb girth with total skeletal mass (e.g., rforeann = .96, rmidann = .82,
rmidthigh = .94) in an autopsy study of 12 men. The correlations
were somewhat higher after correcting for skinfold thickness.
Likewise, Reid and colleagues (45) found reasonable correlations between anthropometric measures and muscle mass in
men, but not in women where the measurements were more sensitive to fat than to muscle content. A related problem is that
CSA cannot account for infiltration of fat into the muscle which
would contribute to the area measurement. Anthropometric approaches do not appear to be as reliable in women as in men. To
illustrate this point, arm CSA did not change with age in women
(Table I), whereas Lynch and colleagues (4) found a significant
decline in arm PPM in those women who were studied by DXA.
Imaging techniques have become standard methods in recent
years for estimating cross-sectional muscle area and FFM.
Techniques include CT, MR!, ultrasound, and DXA. They are
regarded as more accurate than anthropometric measures.
Engstrom and colleagues (46) comparing MR!, CT, and actual
AGEAND MUSCLE QUALITY
measures in three cadavers found MRI to be accurate in the
thigh, whereas CT consistently overestimated area. Recently,
DXA has been validated for measuring muscle mass (47,48).
For example, DXA accurately reflects FFM as estimated by
total body potassium with =.86 in 143 subjects (32). In our
analysis, FFM accounted for a greater percentage of the variancein muscle strengththan eitherCREAT or CSA, suggesting
that it is a bettermarkerof the contractile capability of the muscle or a more accurate estimator of muscle mass. However,
none of these techniques measure the amount of contractile
protein,which is actuallyresponsiblefor force generation. The
modem imaging methods seem to offer more accurate estimatesof muscle mass than earliertechniques.
Studies using CT, MRI, and ultrasound show declines in
strength per unit musclewith increasing age (2,11,14), although
some studies show mixed results, e.g., a decline in
strengthlCSA for isokinetic-concentric, but not isometric
strength(11). Kallman and colleagues(3) found a similarrelationship using forearm circumference with young men relatively stronger (whereas old men were relatively weaker) than
explainedby a simple regressionof forearm circumferenceon
grip strength. In contrast,Fronteraand colleagues(9) found little difference in muscle quality with age in some but not all
muscle groups using hydrodensitometry for body density and
muscle mass from CREAT. In our study,FFM based on DXA
peaks in the 40s before declining in older ages in the leg, but
the declines began later than the changes in strength in both
men and women. FFM assessed by DXA improved the estimate of leg isometric muscle strength when considered with
age and gender(Table 2).
A limitation withthe strength measurements wasthatvery differenttechniques were used to measureisometric strength in the
arm and leg.The arm used a custom-built systemthatdid not efficiently isolateindividual musclegroup actions. The leg extensorsweretestedon a commercially available and commonly used
device (Kin-Com) that has been shownto producereliable measurements (6). To give current relevanceto the isometric measurement, we found a correlation (r = .71)betweenarm strength
(lastcollectedin 1985)and currentisokineticconcentricelbow
flexion measurements in the arm usingthe Kin-Comin 265 subjeers studied approximately 10yearslater(unpublished analysis).
For comparison,a strong relationship between Kin-Comisokineticconcentricand isometricknee extensionmeasurements at
the same Kin-Com sitting was observed (r =86). Though the
correlations are somewhatdifferent, the arm isometric measurements used in this study can be directly related to currentlyacceptedmeasurements of upperbodystrength.
Thus the measure used to estimatemuscle mass could affect
the final interpretation.In particular,when using CSA, careful
attentionmust be taken in gender comparisons. Creatinineappearsto followa different time coursewith age than eitherCSA
or FFM. This suggests that the measures reflect different aspectsof musclemass that changeat different rates duringaging.
r
Do Cross-Sectional and Longitudinal Designs Lead
to the Same Conclusions?
Differences were observed betweencross-sectional and longitudinal analyses for CSA in our study. In the cross-sectional analysis, both CSA and FFM showed an age-associated decline in
musclequality. This was not observedin the longitudinal analy-
B217
sis. For CREAT, differences were observedbetween cross-sectional and longitudinalanalyses. No age effects were observed
cross-sectionally, whereas in the longitudinal analysis,
strengthlCREAT increased in the 20-year-old group and remainedhigherin the olderage groups. Several possible explanationscan be offered for the differences in findings between crosssectional and longitudinal analyses. First, in the longitudinal
analyses, the random-effects analysis foundsignificant individual
differences in musclequality. This implies that the measurement
of strength/CSA and strength/CREAT had greatervariability initially between subjects, which may have masked small group
changes, particularly for strength/CSA. Second, biasescan occur
because of subject differences in the two analyses. Cross-sectional studiescompare subjectsat one point in time, but cannot
address the degree that younger individualsare comparable to
healthyolder subjects. Wepreviously demonstrated the problem
by examining thisquestionin relationship to health estimatesin
60- and 80-year-oldmen. Using standardhealth requirements,
only 30% of 60-year-old men followed to age 80 met the health
criteriaused to selectthe 80-year-old men (49).In this studywe
addressed this issue by looking at individuals in the cross sectionalcohortwho survived for morethan 10years, and foundthe
samecross-sectional declines in muscle quality.
Cross-sectional and longitudinal studiesappearto give a different answer when studying muscle quality using CSA and
CREAT. The differencesmay result from a selection bias with
healthier subjectshaving longitudinalfollow-up; however,we
found no strong evidence for this possibility.More likely, the
differences resulted from a large intrasubjectvariability in the
musclequalityestimate.
Conclusions
We believethat the cross-sectional and longitudinal analyses
imply that muscle quality may decline with increasing age but
are dependenton methodology and researchdesign.The differences suggest that CREATmay measure a property of muscle
that is not accounted for by CSA and FFM. In addition, age had
an independent effect on strength after accounting for muscle
mass, suggesting the importance of other factors than mass.
The relationship betweenmusclequalityand age appearsto depend on how musclemass is estimated and on whethersubjects
are studiedcross-sectionally or longitudinally.
ACKNOWLEOOMENTS
We would like to thank National Institute on Aging, the participants and staff
of the Baltimore Longitudinal Study of Aging including Art Norris, Ray
Banner, Harry Carr, Edward Billips, and Dr. Nathan Shock, without whom this
study could not have been done.
Address correspondence to E. Jeffrey Metter, National Institute on Aging,
Intramural Research Program, Gerontology Research Center, 5600 Nathan
Shock Drive, Baltimore, MD 21224-6823. E-mail: [email protected]
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B218
METTER ETAL.
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ReceivedApril 30, 1998
AcceptedNovember 25, 1998