Cutpoints for Low Appendicular Lean Mass That Identify Older Adults With Clinically Significant Weakness

Abstract

Low lean mass is potentially clinically important in older persons, but criteria have not been empirically validated. As part of the FNIH (Foundation for the National Institutes of Health) Sarcopenia Project, this analysis sought to identify cutpoints in lean mass by dual-energy x-ray absorptiometry that discriminate the presence or absence of weakness (defined in a previous report in the series as grip strength <26kg in men and <16kg in women).
In pooled cross-sectional data stratified by sex (7,582 men and 3,688 women), classification and regression tree (CART) analysis was used to derive cutpoints for appendicular lean body mass (ALM) that best discriminated the presence or absence of weakness. Mixed-effects logistic regression was used to quantify the strength of the association between lean mass category and weakness.
In primary analyses, CART models identified cutpoints for low lean mass (ALM <19.75kg in men and <15.02kg in women). Sensitivity analyses using ALM divided by body mass index (BMI: ALMBMI) identified a secondary definition (ALMBMI <0.789 in men and ALMBMI <0.512 in women). As expected, after accounting for study and age, low lean mass (compared with higher lean mass) was associated with weakness by both the primary (men, odds ratio [OR]: 6.9 [95% CI: 5.4, 8.9]; women, OR: 3.6 [95% CI: 2.9, 4.3]) and secondary definitions (men, OR: 4.3 [95% CI: 3.4, 5.5]; women, OR: 2.2 [95% CI: 1.8, 2.8]).
ALM cutpoints derived from a large, diverse sample of older adults identified lean mass thresholds below which older adults had a higher likelihood of weakness.

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Journals of Gerontology: MEDICAL SCIENCES
Cite journal as: J Gerontol A Biol Sci Med Sci 2014 May;69(5):567–575
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Special Article
Cutpoints for Low Appendicular Lean Mass That Identify
Older Adults With Clinically Signicant Weakness
Peggy M.Cawthon,1 Katherine W.Peters,1 Michelle D.Shardell,2 Robert R.McLean,3
Thuy-Tien L.Dam,4 Anne M.Kenny,5 Maren S.Fragala,5,6 Tamara B.Harris,7 Douglas P.Kiel,3,8
Jack M.Guralnik,2 LuigiFerrucci,7 Stephen B.Kritchevsky,9 Maria T.Vassileva,10
Stephanie A.Studenski,11,12 and Dawn E.Alley2
1California Pacic Medical Center Research Institute, San Francisco.
2Department of Epidemiology and Public Health, University of Maryland School of Medicine, College Park.
3Division of Gerontology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts.
4Department of Medicine, Columbia University, New York, New York.
5Center on Aging, University of Connecticut Health Center, Farmington.
6University of Central Florida, Orlando.
7National Institute on Aging, Bethesda, Maryland.
8Institute for Aging Research, Hebrew Senior Life Institute for Aging Research, Boston, Massachusetts.
9The Sticht Center on Aging and Department of Internal Medicine, Wake Forest University, North Carolina.
10Foundation for the NIH Biomarkers Consortium, Bethesda, Maryland.
11Department of Internal Medicine, University of Pittsburgh, Pennsylvania.
12VA Pittsburgh Healthcare System, Pennsylvania.
Address correspondence to Peggy M.Cawthon, PhD, MPH, California Pacic Medical Center Research Institute, 185 Berry Street,
Suite 5700, San Francisco, CA 94107-1762. Email: pcawthon@sfcc-cpmc.net
Background. Low lean mass is potentially clinically important in older persons, but criteria have not been empirically
validated. As part of the FNIH (Foundation for the National Institutes of Health) Sarcopenia Project, this analysis sought
to identify cutpoints in lean mass by dual-energy x-ray absorptiometry that discriminate the presence or absence of weak-
ness (dened in a previous report in the series as grip strength <26 kg in men and <16 kg in women).
Methods. In pooled cross-sectional data stratied by sex (7,582 men and 3,688 women), classication and regression
tree (CART) analysis was used to derive cutpoints for appendicular lean body mass (ALM) that best discriminated the
presence or absence of weakness. Mixed-effects logistic regression was used to quantify the strength of the association
between lean mass category and weakness.
Results. In primary analyses, CART models identied cutpoints for low lean mass (ALM <19.75 kg in men and
<15.02 kg in women). Sensitivity analyses using ALM divided by body mass index (BMI: ALMBMI) identied a second-
ary denition (ALMBMI <0.789 in men and ALMBMI <0.512 in women). As expected, after accounting for study and age,
low lean mass (compared with higher lean mass) was associated with weakness by both the primary (men, odds ratio
[OR]: 6.9 [95% CI: 5.4, 8.9]; women, OR: 3.6 [95% CI: 2.9, 4.3]) and secondary denitions (men, OR: 4.3 [95% CI: 3.4,
5.5]; women, OR: 2.2 [95% CI: 1.8, 2.8]).
Conclusions. ALM cutpoints derived from a large, diverse sample of older adults identied lean mass thresholds
below which older adults had a higher likelihood of weakness.
Key Words: Muscle—Sarcopenia—Cutpoints.
Received June 19, 2013; Accepted January 21, 2014
Decision Editor: Roger Fielding, PhD
EARLY efforts to create an operational denition of sar-
copenia (including the creation of cutpoints) have relied
on distributional denitions of lean mass (1), with sarcopenia
dened as a value of appendicular lean mass (ALM)/height2
(derived from whole-body dual-energy x-ray absorptiometry
[DXA]) below the young adult mean level of lean mass or was
based on denitions that further account for body size or fat-
ness (2–4). More recent efforts have added functional and/or
strength measures to lean mass to dene sarcopenia (5,6), but
no approaches thus far have proposed and validated cutpoints
and denitions based on discriminative and predictive ability
using a data-driven approach from a variety of cohort studies.

568 CAWTHON ETAL.
The overarching goal of this set of concurrent reports
from the Foundation for the National Institutes of Health
(FNIH) Sarcopenia Project was to determine preliminary
data-driven criteria for clinically relevant weakness and low
lean mass. The conceptual framework was based on a clini-
cian making a “differential diagnosis” of mobility impair-
ment, dened as slow gait speed. The clinician understands
that there are many causes of slow walking, one of which
is weakness. Similarly, low lean mass may be considered a
potential contributing factor to the development of weak-
ness (7). Data from multiple large cohort studies of aging
were pooled for this effort (7). The rst stage of analyses
identied sex-specic cutpoints for weakness that discrimi-
nated slow participants (walking speed <0.8 m/s) from
those who walked faster (8). In the second stage of the anal-
yses, reported herein, we aimed to identify cutpoints in lean
mass that discriminated those who were weak (grip strength
<16 kg in women or <26 kg in men) from those who were
stronger. The ndings from this work were used to address
subsequent goals of the Project, so it is important to con-
sider these results within the context of all other articles in
this series.
Methods
Participants
The cohort studies and the clinic visit used in this phase
of the FNIH Sarcopenia Project analysis included: the
Study of Osteoporotic Fractures (SOF), both the original
cohort (study Visit 6) (9) and African American cohort
(study Visit 1) (10); the Osteoporotic Fractures in Men
Study (MrOS, baseline visit) (11); the Health, Aging and
Body Composition Study (Health ABC, Year 6 Clinic
Visit) (12); the Framingham Study Offspring Cohort
(exam cycles 6 and 7, 1996–2001) (13) and Framingham
Original cohort (exam cycle 22, 1992–1993) (14); the
Boston Puerto Rican Health Study (BPRHS, baseline
visit) (15); Rancho Bernardo (study Visit 7) (16); and
several smaller clinical trials led by Dr. Anne Kenny at
University of Connecticut (randomization visit for all
studies) (17–22). To be included in these analyses, par-
ticipants must have completed, at the time point identi-
ed above, the following measures: objectively measured
height and weight; body mass index (BMI); ALM (sum of
lean mass in the arms and legs), leg lean mass (LLM), and
total fat by DXA; and grip strength. Of the 26,625 par-
ticipants aged 65years and older in the FNIH Consortium
pooled data, 7,069 were ineligible because they were in
studies that did not have DXA scans; 6,364 were not eli-
gible for DXA scans within their study; 1,170 were eli-
gible but missing DXA data; and an additional 752 were
missing data for other covariates, yielding a nal sample
size of 11,270 (7,582 men and 3,688 women). Participants
excluded due to missing data were older, slower, weaker,
had lower BMI, and were more likely to be women than
those included in the analyses.
Assessment of LeanMass
ALM, LLM, and total body fat (TBF) were assessed
using DXA, on Hologic 4500 machines in MrOS, Rancho
Bernardo, and Health ABC; on Hologic 2000 machines in
SOF (both the original and African American cohorts); and
Lunar Prodigy machines in Framingham (both the Original
and Offspring cohorts), BPRHS, and the clinical trials at the
University of Connecticut.
Assessment of Grip Strength and the Denition of
Weakness
Maximum grip strength of either hand was meas-
ured by handheld dynamometers. In the first phase of
analyses (reported in an accompanying article) (8), the
cutpoint for grip strength as a discriminator of slow-
ness (defined as a walking speed of ≤0.8 m/s) was iden-
tified using classification and regression tree (CART)
analysis (23). Men with a grip strength less than 26 kg
and women with a grip strength less than 16 kg were
defined as “weak.” Asecondary cutpoint for weakness
based on grip strength standardized to body size (ie, the
ratio of grip strength to BMI, weaknessBMI) was identi-
fied for men (men with a ratio <1.0 defined as weak)
and women (women with a ratio of <0.56 defined as
weak.) Those analyses to identify a cutpoint in grip
strength included 20,847 participants, of whom 10,036
were also included in our analyses; 1,207 participants
were included our analyses but not included in the grip
strength analyses. Most of the exclusions from the grip
strength analyses were due to missing data for walk-
ing speed; and most of the exclusions from the present
analyses were due to missing values for body composi-
tion (ALM or body fat).
Statistical Analysis
LOESS plots were used to describe the overall shape
of the relationship between lean mass (both ALM and
ALMBMI) with grip strength and walking speed; Pearson
correlation coefcients were calculated.
CART analysis was then performed to derive clinically
meaningful cutpoints for lean mass as a discriminator of
weakness. CART is particularly advantageous to this study
because (i) the relationship between candidate predictors
and weakness does not require specication, (ii) CART can
identify complex multiway interactions between potentially
important variables (eg, BMI, height), and (iii) predictors
and cutpoints are selected to optimize discrimination of the
outcome (weakness).
CART analysis was performed using the rpart proce-
dure of R software (version 2.10.1), and cross-validation

LEAN MASS AND WEAKNESS IN OLDERADULTS 569
was used to “prune” less important splits to prevent
overfitting and produce a more parsimonious tree.
Cross-validation was performed by randomly parti-
tioning the pooled data into 10 equally sized mutually
exclusive data sets (ie, each set excluded 10% of the
original pooled data). The tree was then applied to 10
subsamples that contained 90% of the data (ie, 10%
of the data was left out of each subsample), and the
prediction error from each subsample was calculated.
The 10 prediction errors (error sum of squares) were
used to calculate the empirical standard error of the
prediction error. Following published guidelines (24),
the tree was pruned to the most parsimonious tree that
was within 1 SE of the tree with the smallest prediction
error. This pruned tree contains the final set of lean
mass cutpoints.
Several CART models were run. First, ALM and LLM
were entered into a CART model as the only potential dis-
criminators of weakness (dened as grip strength <26 kg
for men and <16 kg for women). Then, body size variables
(height, weight, BMI, TBF) were added to the model.
Third, measures of lean mass standardized to body size (the
ratio of ALM to each measure of body size) were added
and included ALMheight, ALMweight, ALMheight2, ALMBMI,
ALMTBF, LLMheight, LLMweight, LLMheight 2, LLMBMI, and
LLMTBF. Finally, we consider only ALMBMI and ALM as
potential discriminators of weakness.
We report the prevalence for low lean mass by various
subgroups in the cohorts (such as age, BMI, and history
of disease) and the likelihood of prevalent weakness by
low lean mass across these subgroups. We also report the
likelihood of slowness and inability to rise from a chair by
various weakness and low lean mass categories. These esti-
mates were derived using mixed-effects logistic regression
that included a random effect for cohort to account for the
heterogeneity between studies.
Results
ALM was positively correlated with grip strength in men
(r = .47, p < .001) and somewhat less strongly in women
(r = .33, p < .001) (Figure1). ALM was only modestly posi-
tively correlated with walking speed in men (r = .11, p <
.001) and was inversely correlated with walking speed in
women (r = −.20, p < .001). ALMBMI was positively cor-
related with grip strength (r = .42, p = <.001) and walking
speed (r = .24, p < .001) in men as well as in women (grip
strength, r = .22, p < .001 and walking speed, r = .07, p <
.001). Body weight was strongly correlated with ALM in
both men (r = .80, p < .001) and women (r = .81, p < .001).
The CART models for the primary denition of weak-
ness (grip strength <16 kg in women and <26 kg in men)
demonstrated that ALM was the best discriminator of weak-
ness, regardless of inclusion of body size variables (weight,
TBF, height, height2 or BMI) or lean mass variables stand-
ardized to body size, or both. (Figure2).
In men, a single cutpoint for ALM was found. Men with
an ALM less than 19.75 kg were dened as having low lean
mass; the prevalence of weakness was 18.3% in this group
compared with only 2.5% for men with higher lean mass
(ALM ≥ 19.75 kg).
In women, two cutpoints for ALM were found: one at
15.02 kg and another at 12.09 kg. For parsimony, and to
propose a denition analogous to that for men, we dened
two groups of women: those with low lean mass (ALM
< 15.02 kg) and higher lean mass (ALM ≥ 15.02 kg). The
prevalence of weakness for women with low lean mass was
29.8% compared with a prevalence of weakness of 11.0%
for women with higher leanmass.
In secondary analyses, for men, when ALMBMI and BMI
were the only potential discriminators of weakness, one
cutpoint in ALMBMI was found. In these secondary analy-
ses, we dened men with low lean mass as having a value
of ALMBMI less than 0.789 (prevalence of weakness was
Figure1. Scatterplots and correlation of appendicular lean mass (ALM) or ALM/body mass index (BMI) versus grip strength or walking speed for men and
women in the FNIH (Foundation for the National Institutes of Health) Sarcopenia Project.

570 CAWTHON ETAL.
11.8%); men with an ALMBMI more than or equal to 0.789
had higher lean mass and a prevalence of weakness of 2.4%
(Figure3).
In secondary analyses, for women, when ALMBMI and
BMI were the only potential discriminators of weakness
included in the CART model, one cutpoint in ALMBMI was
found: 0.512 (Figure3), and for those with ALMBMI more
than or equal to 0.512, a second cutpoint was found for BMI
(23.7 kg/m2). In the secondary analyses, we dened women
with low lean mass as having ALMBMI less than 0.512 (prev-
alence of weakness was 31.0%); women with ALMBMI more
than or equal to 0.512 had a prevalence of weakness 16.8%
(Figure3). Of the women with ALMBMI more than or equal
to 0.512, those who had a BMI less than 23.7 kg/m2 had
a prevalence of weakness of 12.0%, whereas those with a
BMI of more than or equal to 23.7 kg/m2 had a prevalence
of weakness of24.2%.
Men with low lean mass were more likely to be weak
compared with those with higher lean mass, after account-
ing for age and study by both the primary denition (odds
ratio [OR]: 6.9 [95% CI: 5.4, 8.9]) or secondary denition
(OR: 4.3 [95% CI: 3.4, 5.5]) (Table1). Similarly, women
with low lean mass were also more likely to be weak com-
pared with those with higher lean mass by the primary de-
nition (OR: 3.6 [95% CI: 2.9, 4.3]) or secondary denition
(OR: 2.2 [1.8, 2.8]), although the strength of the association
was smaller in magnitude than it was for men. For most
stratied analyses, the association between low lean mass
and weakness was signicant (p < .05), while the point esti-
mates varied by strata (although the interaction by stratify-
ing factors was not signicant for any model).
In men, when weakness and low lean mass were con-
sidered jointly in the same model with slowness as the
outcome, both factors were independently associated with
prevalence of slowness (Table 2). Men who were weak
(either by grip strength alone or by grip strength standard-
ized to BMI) were about 3- to 4.5-fold more likely to be
slow and 2.5- to 3.0-fold more likely to be unable to rise
from a chair than men who were not weak. Men with low
lean mass (either by ALM or ALMBMI) were about twice as
likely to be slow compared with men with higher lean mass.
Men with low lean mass by ALM, but not ALMBMI, were
about 1.3- to 1.6-fold more likely to be unable to rise from
a chair than men with higher leanmass.
In women, when weakness and low lean mass were
considered jointly in the same model with slowness as the
outcome, only weakness was consistently associated with
slowness. Women who were weak (either by grip strength
lone or by grip strength standardized to BMI) were 2- to
3-fold more likely to be slow than women who were not
weak. One the other hand, and in contrast to results for
men, women with low lean mass based on ALM had a
somewhat lower likelihood of being slow or unable to rise
from a chair compared with women with higher lean mass.
Women with low lean mass (based on ALMBMI) had about a
50% increased likelihood of slowness after adjustment for
Figure2. Classication and regression tree models for measures of lean mass, body size, and lean mass standardized to body size discriminating weakness in
older men and women in the FNIH (Foundation for the National Institutes of Health) Sarcopenia Project. Model included the following potential discriminators of
weakness (grip strength <16 kg in women and <26 kg in men): ALM (appendicular lean mass), height, weight, height2, total body fat (TBF), BMI (body mass index),
ALMheight (ALM/height), ALMweight (ALM/weight), ALMheight 2 (ALM/height2), ALMBMI (ALM/BMI), ALMTBF (ALM/TBF), LLMheight (LLM/height; LLM=leg lean
mass), LLMweight (LLM/weight), LLMheight2 (LLM/height2), LLMTBF (LLM/TBF), and ALMBMI (LLM/BMI).

LEAN MASS AND WEAKNESS IN OLDERADULTS 571
weakness based on grip strength alone. However, when the
association between ALMBMI and slowness was adjusted
for weakness standardized to BMI, the association was not
signicant. ALMBMI was not signicantly associated with
inability to rise from a chair forwomen.
When we compare the prevalence of low lean mass by
our denition based on ALM with the prevalence of low
lean mass by Baumgartner, overall percent agreement was
83.0% for men and 75.4% in women (Table3). When we
compare the prevalence of low lean mass by our denition
based on ALMBMI with the prevalence of low lean mass by
Baumgartner, the overall percent agreement is 69.1% in
men and 70.7% inwomen.
Discussion
The goal of these analyses, using pooled data from sev-
eral large cohort studies of older men and women, was to
identity cutpoints in values of low lean mass that discrimi-
nated those who were weak from those who were not weak.
Primary analyses resulted in a denition of low lean mass
as ALM less than 19.75 kg in men and less than 15.02 kg in
women. Sensitivity analyses suggested an alternative deni-
tion using a value of ALM standardized to BMI (ALMBMI).
Men with a value of ALMBMI less than 0.789 and women
with a value of ALMBMI less than 0.512 were considered to
have low lean mass by this secondary denition.
While our analyses were not designed to dene or
evaluate “sarcopenic obesity,” our results suggest that
body size and potentially fatness inuence the association
between lean mass and weakness. This nding is similar
to another report (4) that found that low lean mass based
on the Baumgartner (1) criteria using ALM/height2 was
less strongly related to physical disability than a measure
of low lean mass that was adjusted for height and body fat
mass (2). On the other hand, measures of obesity were not
selected by the CART models as primary discriminators of
weakness in older people.
The associations between our denitions of low lean
mass and concurrent weakness are quite strong as would be
expected by our analytical methodology. Men who had low
lean mass by the primary denition based on ALM alone
were about 7 times more likely to be weak (grip strength
<26 kg) than men with higher lean mass. In women, the
association between low lean mass and weakness was some-
what lower but still substantial, as women with low lean
mass by the primary denition based on ALM alone were
about 4 times more likely to be weak (grip strength <16 kg)
than women with higher lean mass. However, the analysis
technique employed requires caution when interpreting
these data. The strong associations between our proposed
denitions of low lean mass and weakness are not surpris-
ing, because of the analysis method (CART) derived the
cutpoints to maximize the association between lean mass
and weakness. We expressed the association between our
lean mass cutpoints and weakness as ORs to further ease
the clinical interpretation of our results. To understand the
clinical implications of the proposed denitions of low lean
mass described here, further analyses must be completed,
including those of longitudinal data that would establish
the predictive validity of our cutpoints and the independ-
ent association of these cutpoints with clinical outcomes
thought to be related to weakness and low leanmass.
The association between low lean mass and slowness was
independent of weakness in men. Men who had low lean
mass (by either denition) were about 2–4.5 times more
likely to be slow when compared with men with higher
lean mass after accounting for weakness. On the other
hand, in women, the association between low lean mass and
Figure3. Classication and regression tree models for ALMBMI and BMI discriminating weakness in older men and women in the FNIH (Foundation for the
National Institutes of Health) Sarcopenia Project. Model included ALM and ALMBMI (ALM/BMI) as potential discriminators of weakness (grip strength <16 kg in
women and <26 kg in men). ALM=appendicular lean mass; BMI=body mass index.

572 CAWTHON ETAL.
Table1. Prevalence of Low Lean Mass (based on ALM or ALMBMI) and Likelihood of Weakness Across Various
Subsamples in the FNIH Sarcopenia Project*
N
Prevalence of
Weakness
OR (95% CI) for Weakness
Low Lean Mass
(based on ALM)
Low Lean Mass
(based on ALMBMI)
Men
Overall 7,582 0.04 6.9 (5.4, 8.9) 4.3 (3.4, 5.5)
Age
65–79 6,001 0.03 6.2 (4.4, 8.8) 3.9 (2.8, 5.5)
80 1,581 0.11 5.0 (3.5, 7.2) 3.3 (2.4, 4.7)
BMI
Normal weight/underweight 2,198 0.07 6.2 (4.2, 9.1) 7.5 (5.0, 11.1)
Overweight 3,848 0.04 8.6 (5.8, 12.8) 5.3 (3.7, 7.7)
Obese 1,536 0.03 10.3 (3, 35.7) 4.7 (2.3, 9.7)
Height
Tertile 1 (<1.7080 m) 2,524 0.09 4.4 (3.2, 6.0) 2.8 (2.0, 3.9)
Tertile 2 (≥1.708 m, <1.765 m) 2,514 0.03 3.6 (2.1, 6.4) 1.3 (0.7, 2.4)
Tertile 3 (≥1.7650 m) 2,544 0.01 13.7 (5.0, 37.7) 5.6 (2, 15.9)
Cancer
Ye s 1,791 0.03 6.8 (3.8, 12.1) 5.8 (3.3, 10.2)
No 5,578 0.05 7.8 (5.9, 10.4) 4.4 (3.3, 5.7)
CHF
Ye s 373 0.10 9.2 (4.2, 19.8) 4.7 (2.2, 10.0)
No 6,248 0.04 7.6 (5.6, 10.3) 4.7 (3.5, 6.2)
COPD
Ye s 625 0.04 5.2 (2.2, 12.4) 7.0 (2.8, 17.6)
No 5,357 0.03 8.9 (6.2, 12.8) 4.5 (3.2, 6.3)
Diabetes
Ye s 759 0.07 5.1 (2.4, 10.8) 2.7 (1.4, 5.1)
No 6,809 0.04 7.3 (5.6, 9.5) 4.5 (3.5, 5.9)
Women
Overall 3,688 0.19 3.6 (2.9, 4.3) 2.2 (1.8, 2.8)
Age
65–79 2,633 0.15 3.5 (2.7, 4.5) 2.4 (1.8, 3.1)
80 1,055 0.29 2.9 (2.1, 4.0) 2.0 (1.4, 2.9)
BMI
Normal weight 1,455 0.24 4.3 (3.0, 6.2) 2.9 (1.8, 4.7)
Overweight 1,299 0.17 3.2 (2.3, 4.5) 3.0 (2.1, 4.3)
Obese 934 0.14 3.6 (2.0.1, 6) 3.3 (2.2, 5.1)
Height
Tertile 1 (<1.560 m) 1,229 0.28 3.3 (2.3, 4.6) 1.3 (1.0, 1.8)
Tertile 2 (≥1.560 m, <1.610 m) 1,225 0.18 2.4 (1.7, 3.5) 1.8 (1.1, 2.8)
Tertile 3 (>1.610 m) 1,234 0.11 2.5 (1.7, 3.8) 2.4 (1.0, 5.7)
Cancer
Ye s 241 0.26 5.3 (2.7, 10.6) 1.8 (0.8, 3.9)
No 2,508 0.17 3.8 (2.9, 5) 2.4 (1.8, 3.1)
CHF
Ye s 136 0.26 6.3 (2.7, 14.6) 1.7 (0.7, 4.3)
No 2,481 0.23 3.4 (2.7, 4.2) 2.2 (1.7, 2.8)
COPD
Ye s 196 0.20 5.6 (2.6, 12.2) 2.5 (1.1, 5.9)
No 1,356 0.22 3.5 (2.6, 4.6) 2.5 (1.7, 3.6)
Diabetes
Ye s 277 0.21 2.5 (1.2, 4.9) 1.3 (0.6, 2.9)
No 3,313 0.19 3.7 (3, 4.5) 2.3 (1.9, 2.9)
Notes: ALM = appendicular lean mass; BMI = body mass index; CHF = congestive heart failure; COPD = chronic obstructive pulmonary disease;
FNIH=Foundation for the National Institutes of Health; OR=odds ratio.
*Weakness dened as grip strength <26 kg in men and <16 kg in women; low lean mass based on ALM dened as <19.75 in men and <15.02 in women; low lean
mass based on ALMBMI dened as <0.789 in men and <0.512 in women. Medical conditions based on self-report of physician diagnosis. A total of 213 men and 939
women missing cancer information, 961 men and 1,071 women missing CHF information, 1,600 men and 2,136 women missing COPD information, and 14 men and
98 women missing diabetes status. No signicant interactions were found in the stratied analyses.

LEAN MASS AND WEAKNESS IN OLDERADULTS 573
slowness was inconsistent across denitions and was not
consistently independent of concurrent weakness. These
sex differences could be due to a number of factors. Men
and women have drastically different body types and body
composition, and women have more disability than men.
It is possible that the association between body size, lean
mass, weakness, and slowness truly differs between men
and women. Another possibility is that differences between
single-sex cohorts in the pooled data set (such as SOF and
MrOS, for example) explain the discrepant results.
Our results are not directly comparable to other proposed
denitions of low lean mass or sarcopenia, because these
other denitions have accounted for body size in a different
manner than our analyses. For example, the Baumgartner
denition (1) (which has been included in consensus state-
ments about sarcopenia) divides ALM by height2 to quan-
tify lean mass and then denes individuals as “sarcopenic”
if their value is at least 2 SDs below a young normal mean
value. This equates to 7.26 kg/m2 for men and 5.45 kg/
m2 for women. We found modest agreement between our
denitions and the Baumgartner denition of low lean
mass; thus, we conclude that our cutpoints and other sarco-
penia denitions, as discussed in an accompanying report
from this project (25), differentially classify individuals.
We could not compare our denition against others that
used non-DXA methods to determine lean mass (such as
bioelectrical impedance analysis [BIA]) (3), because BIA
was not available in most participating cohorts.
There are some limitations of these analyses. First,
CART, by denition, partitions data into groups, even
when the underlying relationship between the predictor
and outcome is linear. Second, our CART models did not
account for differences between studies included in the
model, although we did account for study in subsequent
logistic models. Third, while we accounted for cohort
study a random effect in the logistic models, we did not
specically correct or adjust values to account for differ-
ences across cohorts. For example, the cohorts used vari-
ous makes and models of DXA machines. There are no
methods aside from in vivo cross-calibration studies that
Table2. Likelihood of Slowness* or Inability to Complete Chair Stands† (OR, 95% CI)‡, by Weakness and low
Lean Mass in the FNIH Sarcopenia Project§
Men Women
Model 1 Weak Low lean mass (ALM) Weak Low lean mass (ALM)
Slowness 3.04 (2.11, 4.38) 1.56 (1.16, 2.09) 2.21 (1.72, 2.83) 0.74 (0.59, 0.92)
Inability to complete chair stands 2.46 (1.62, 3.73) 1.32 (0.94, 1.85) 2.05 (1.37, 3.08) 0.49 (0.36, 0.69)
Model 2 Weak Low lean mass (ALMBMI) Weak Low lean mass (ALMBMI)
Slowness 2.91 (2.02, 4.17) 2.12 (1.66, 2.71) 1.96 (1.53, 2.51) 1.55 (1.20, 2.02)
Inability to complete chair stands 2.35 (1.56, 3.55) 1.60 (1.21, 2.12) 1.62 (1.09, 2.40) 1.26 (0.86, 1.83)
Model 3 WeakBMI Low lean mass (ALM) WeakBMI Low lean mass (ALM)
Slowness 4.24 (3.20, 5.62) 1.71 (1.28, 2.28) 2.91 (2.31, 3.66) 0.86 (0.69, 1.07)
Inability to complete chair stands 2.90 (2.10, 4.01) 1.39 (0.99, 1.94) 2.40 (1.67, 3.46) 0.54 (0.39, 0.75)
Model 4 WeakBMI Low lean mass (ALMBMI) WeakBMI Low lean mass (ALMBMI)
Slowness 3.55 (2.64, 4.79) 1.71 (1.32, 2.22) 2.77 (2.18, 3.51) 1.27 (0.97, 1.66)
Inability to complete chair stands 2.63 (1.86, 3.70) 1.37 (1.02, 1.84) 2.31 (1.58, 3.39) 1.04 (0.70, 1.55)
Notes: ALM=appendicular lean mass; BMI=body mass index; FNIH=Foundation for the National Institutes of Health; OR=odds ratio.
*Slowness is walking speed ≤0.8 m/s. For men, N = 337 (4.7%); 7,113 men included in slowness models. For women, N = 673 (22.8%); 2,950 women included
in slowness models.
†Inability to complete ve repeated chair stands. For men, N = 250 (3.5%); 7,095 men included in chair stand models (487 men were missing data for chair stands
ability). For women, N = 198 (6.7%); 2,971 women included in chair stand models (717 women were missing data for chair stands ability).
‡Both weakness and low lean mass included in the same model adjusted for age and study. Slowness models include study as a random effect. Chair stands models
include study as a covariate since the mixed-effects logistic regression models with study as a random effect did not converge.
§Weak dened as grip strength <26 kg in men and <16 kg in women; Weak BMI dened as grip strength/BMI as <1.001 in men; <0.56 in women; low lean mass
based on ALM dened as <19.75 kg in men and <15.02 kg in women; low lean mass based on ALMBMI dened as <0.789 in men and <0.512 in women.
Table3. Cross-Classication of Low Lean Mass by Baumgartner, ALM, and ALMBMI*
Baumgartner criterion ALM criterion ALMBMI criterion
Men Low lean mass High lean mass Low lean mass High lean mass
Low lean mass 5,510 (72.7%) 1,197 (15.8%) 4,657 (61.4%) 1,390 (18.3%)
High lean mass 97 (1.3%) 778 (10.3%) 950 (12.5%) 585 (7.7%)
Women Low lean mass High lean mass Low lean mass High lean mass
Low lean mass 2,050 (55.6%) 28 (0.8%) 2,462 (66.8%) 615 (16.7%)
High lean mass 879 (23.8%) 731 (19.8%) 467 (12.7% 144 (3.9%)
Notes: ALM=appendicular lean mass; BMI=body mass index.
*Low lean mass based on ALM criterion: <19.75 kg in men, <15.02 kg in women. Low lean mass based on ALMBMI criterion: <0.789 in men, <0.512 in women.
Baumgartner criteria: ALM/height2=7.26 kg/m2 in men and 5.45 kg/m2 in women.

574 CAWTHON ETAL.
can accurately compare soft tissue estimates across DXA
machines (26). As the machines included in this project
were located throughout the world, such a study was not
feasible. Additionally, unlike T-scores for bone mineral
density (BMD) in the diagnosis of osteoporosis (which are
used in part to account for machine differences in BMD
estimates), there are no population-based values for all the
DXA manufacturers for all the soft tissue compartments
that would allow calculation for T or Z scores. Finally, no
statistical model alone can identify a disease state. Thus,
further work is necessary to understand the biological
implications of these results.
We intend for the cutpoints in ALM and ALMBMI to be
used within the context of the larger analysis project we
describe in which we are trying to identify those older
persons who are slow and weak whose impairments are
likely attributable to lower levels of lean mass. We have
shown that there is a level of ALM and ALMBMI below
which strength is lower. In another report in this series,
the independent predictive validity of these lean mass cut-
points for future mobility impairment is evaluated. Given
the discordant literature that suggests that lean mass may
not be independently predictive of functional decline
once strength is known (27), these next analyses will be
imperative.
The conceptual framework we used for this larger pro-
ject—that there is a clinical syndrome that includes walking
speed, strength, and lean mass that identies individuals at
risk for disability—is similar to the framework described
by other consensus groups that have addressed this broad
topic of “sarcopenia.” However, there is not clear consen-
sus regarding which part or parts of this clinical syndrome
constitute “sarcopenia” and which should be designated by
some other distinction such as “mobility impairment with
clinically relevant weakness and low lean mass.” To avoid
confusion, we prefer terminology that precisely describes
the results. For example, we have identied values of low
lean mass that discriminate weakness in older adults.
In summary, we have identied cutpoints in lean mass
that discriminate those who are weak from those who are
stronger; secondary analyses suggest that adjustment for
body size may inuence the cutpoints selected. Different
values were found in men and women, given the sex differ-
ences in body size. Future analyses must evaluate the inde-
pendent predictive validity of these cutpoints.
F
Support for the conference and the consortium was provided by the
National Institute on Aging (1U13AG041583 and P30 AG024827), the
Food and Drug Administration, and through a grant from the Foundation
of the NIH, supported by funds from Abbott Nutrition, Amgen, Eli Lilly,
Merck, Novartis, and The Dairy Research Institute.
A
Additional acknowledgements for each contributing cohort and mem-
bers of the FNIH Sarcopenia Project can be found in an online supplement.
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