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Comparisons of Sarcopenia Defined by IWGS and EWGSOP Criteria Among Older People: Results From the I-Lan Longitudinal Aging Study
JAMDA 14 (2013) 528.e1e528.e7
JAMDA journal homepage: www.jamda.com
Original Study
Comparisons of Sarcopenia Defined by IWGS and EWGSOP Criteria Among Older People: Results From the I-Lan Longitudinal Aging Study Wei-Ju Lee MD a, b, Li-Kuo Liu MD b, c, Li-Ning Peng MD, MSc b, c, Ming-Hsien Lin MD b, c, Liang-Kung Chen MD, PhD, FRCP a, c, *, and the ILAS Research Group a
Aging and Health Research Center, National Yang Ming University, Taipei, Taiwan Department of Family Medicine, Taipei Veterans General Hospital Yuanshan Branch, I-Lan County, Taiwan c Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan b
a b s t r a c t Keywords: Sarcopenia skeletal muscle mass handgrip strength walking speed obesity
Objective: To compare clinical characteristics of sarcopenia defined by the International Working Group on Sarcopenia (IWGS) and European Working Group on Sarcopenia in Older People (EWGSOP) criteria among older people in Taiwan. Design: A prospective population-based community study. Setting: I-Lan County of Taiwan. Participants: A total of 100 young healthy volunteers and 408 elderly people. Intervention: None. Measurements: Anthropometry, skeletal muscle mass measured by dual x-ray absorptiometry, relative appendicular skeletal muscle index (RASM), percentage skeletal muscle index (SMI), 6-meter walking speed, and handgrip strength. Results: The prevalence of sarcopenia was 5.8% to 14.9% in men and 4.1% to 16.6% in women according to IWGS and EWGSOP criteria by using RASM or SMI as the muscle mass indices. The agreement of sarcopenia diagnosed by IWGS and EWGSOP criteria was only fair by using either RASM or SMI (kappa ¼ 0.448 by RASM, kappa ¼ 0.471 by SMI). The prevalence of sarcopenia was lower by the IWGS definition than the EWGSOP definition, but it was remarkably lower by using RASM than SMI in both criteria. Overall, sarcopenic individuals defined by SMI were older, had a higher BMI but similar total skeletal muscle mass, and had poorer muscle strength and physical performance than nonsarcopenic individuals. However, by using RASM, sarcopenic individuals had less total skeletal muscle mass but similar BMI than nonsarcopenic individuals. Multivariable logistic regression showed that age was the strongest associative factor for sarcopenia in both IWGS and EWGSOP criteria. Obesity played a neutral role in sarcopenia when it is defined by using RASM, but significantly increased the risk of sarcopenia in both criteria by using SMI. Conclusion: The agreement of sarcopenia defined by IWGS and EWGSOP was only fair, and the prevalence varied largely by using different skeletal muscle mass indices. Proper selections for cutoff values of handgrip strength, walking speed, and skeletal muscle indices with full considerations of gender and ethnic differences were of critical importance to reach the universal diagnostic criteria for sarcopenia internationally. Copyright Ó 2013 - American Medical Directors Association, Inc.
Sarcopenia, first proposed by Rosenberg and Roubenoff,1 was described as the age-related loss of skeletal muscle. Evidence suggests that up to 40% of muscle mass may be lost between the ages of 20 and 70 years.2 The decline of skeletal muscle mass may accelerate along with aging, which is 6% per decade between 30 and
The authors declare no conflicts of interest. * Address correspondence to Liang-Kung Chen, MD, PhD, FRCP, Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, No. 201, Section 2, ShihPai Road, Taipei, Taiwan. E-mail address: [email protected] (L.-K. Chen).
70 years of age,3 1.4% to 2.5% per year after age 60, and could start as early at 35 years of age.4 Overall, sarcopenia was common in the elderly population,5 and was associated with adverse health outcomes, such as falls, frailty, limited physical function, disability, and loss of independence.6e9 In addition, sarcopenia was associated with mortality 10 and increased health care expenditures. 11 Currently, sarcopenia is considered as a new geriatric syndrome,12 and may result in a heavy health care burden to the world. Although sarcopenia has gained extensive interest, an ideal operational definition covering different ethnic backgrounds is still under development.13
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W.-J. Lee et al. / JAMDA 14 (2013) 528.e1e528.e7
The International Working Group on Sarcopenia (IWGS) proposed an operational definition of sarcopenia in 2009,14 which was targeted to individuals with functional decline, mobility-related difficulties, history of recurrent falls, recent unintentional body weight loss, posthospitalization, and chronic conditions (such as type 2 diabetes, chronic heart failure, chronic obstructive pulmonary disease, chronic kidney disease, rheumatoid arthritis, and cancer), and was more suitable in clinical settings. On the other hand, the European Working Group on Sarcopenia in Older People (EWGSOP) proposed another diagnostic definition for sarcopenia in 2010,15 which recommended screening for sarcopenia in all people 65 years and older. Unlike earlier definitions of sarcopenia, focusing on measurements of low muscle mass only, IWGS and EWGSOP definitions both added measurements of physical performance (EWGSOP definition also considered muscle strength) based on several longitudinal studies.10,16 Some researchers proposed a new term, “dynapenia,” to emphasize the importance of muscle function and performance over muscle mass.17,18 To date, researchers took a combined approach for sarcopenia diagnosis as the coexistence of low muscle mass and low physical performance (slow walking speed and/or low muscle strength, eg, handgrip strength), knee flexion/ extension, or peak expiratory flow. In muscle mass measurement, the fundamental process of diagnosis of sarcopenia, appendicular skeletal muscle mass adjusted by either height19 or weight,20,21 was the most recommended approach to determine the relative skeletal muscle. Nevertheless, Woods et al22 argued that the 2 common indices of sarcopenia eventually defined different populations. Moreover, there may be ethnic differences in the previously mentioned measurements of muscle mass, strength, or physical performance in the diagnosis of sarcopenia.23 Although sarcopenia has become a research focus in the world, little was known relating to the differences of clinical characteristics of sarcopenia diagnosed by IWGS and EWGSOP criteria and different skeletal muscle indices among older people in Taiwan. Therefore, the main purpose of this study was to compare the differences of sarcopenia diagnosed by IWGS and EWGSOP criteria and different skeletal muscle indices among older people in Taiwan. Methods Participants The I-Lan Longitudinal Ageing Study (ILAS), a population-based aging cohort study, consisted of long-living middle-aged and elderly people in the I-Lan County of Taiwan. The ILAS intended to explore the complex interrelationship among aging, frailty, sarcopenia, and decline of cognitive function. Community-dwelling people aged 50 years and older were randomly sampled through the household registration data from I-Lan County. Research nurses invited sampled individuals to participate in the study via mail or telephone. All participants fully consented and completed a written informed consent. Individuals with the following conditions were excluded from the study: (1) unable to communicate with research nurses or to grant a permit, (2) unable to walk for 6 meters within a reasonable period of time, (3) not likely to live for more than 6 months because of a major illness, (4) unable to receive magnetic resonance imaging because of a mechanical implant, and (5) institutionalized currently. Data of 408 individuals 65 years and older from the ILAS were retrieved for this study, and 22 of them were excluded because of incomplete data. The study was approved by the institutional review board of the Taipei Veterans General Hospital and National Yang Ming University. Anthropometry Body weight and standing height of all participants were measured when they were wearing light indoor clothing and no shoes. Body
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mass index (BMI) was calculated as weight (kg) divided by height (m) squared. Status of obesity was determined by the World Health Organization Asia-Pacific criteria of obesity as follows: underweight (BMI <18.5 kg/m2), normal weight (BMI 18.5e22.9 kg/m2), overweight (BMI 23.0e27.4 kg/m2), and obese (BMI 27.5 kg/m2).24 Handgrip Strength A well-trained research nurse completed handgrip strength measurements for all participants. Handgrip strength was measured by using a dynamometer (Smedlay’s Dynamometer, TTM, Tokyo, Japan) 3 times. Participants were allowed a pretest trial in an upright standing position with arms straight down to their sides. All participants were instructed to hold the dynamometer with a dominant hand without squeezing arms to the body. The best performance was taken for analysis. A previous study in Taiwan found that handgrip strength in Taiwanese individuals was about 25.4% lower in men and 27.4% lower in women than that of Caucasians,25 and we modified the cutoff points of low handgrip strength in EWGSOP criteria15 to less than 22.4 kg for men and less than 14.3 kg for women. Physical Performance In this study, gait speed was assessed by the 6-meter walk.26,27 Participants walked at their usual speed with a static start without deceleration throughout a 6-meter straight line in an examination room that was more than 8 meters in length. The time was measured by a same study nurse using a stop watch (HS-70W; Casio Computer Co, LTC, Tokyo, Japan). Skeletal Muscle Mass Measurement A total of 100 healthy adult volunteers (50 men and 50 women) aged 20 to 40 years were invited for skeletal muscle measurements as the reference group. All participants and the reference young adults received whole-body dual-energy x-ray absorptiometry (DXA) scans to obtain total fat mass, percentage of fat-free lean body mass (LBM), and bone mineral density using the standardized procedures of the period calibrated manufacturers (Prodigy; GE Lunar, Madison, WI, and DPX-NT, Madison, WI). Appendicular skeletal muscle mass (ASM) was calculated as the sum of LBM of all 4 limbs.28 Relative skeletal muscle mass index (RASM) was defined as ASM divided by body height in meters squared.19 Kim et al29 proposed equations to estimate total skeletal muscle mass (SMM) and the relative sarcopenia condition from a Korean cohort as follows: 1. Total SMM (kg) ¼ (1.13 ASM) (0.02 age) þ (0.61 sex) þ 0.97, where sex ¼ 0 for women and 1 for men. 2. Percentage skeletal muscle index (SMI%) ¼ SMM/weight (kg) 100 The lower 20th percentile of RASM and SMI from the mean of the young reference group was used to establish cutoff points of sarcopenia.30 Diagnosis of Sarcopenia In this study, sarcopenia defined by EWGSOP and IWGS criteria was compared. In EWGSOP criteria,15 sarcopenia was defined as low muscle mass plus low muscle strength (measured by handgrip strength, knee extensor, or peak expiratory flow) or low physical performance (measured by the Short Physical Performance Battery, usual gait speed, timed get-up-and-go test, or stair-climb power test). According to the case finding algorithm of EWGSOP, all study
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participants were screened by walking speed first, and DXA would be performed for muscle mass measurements if the individuals had lower handgrip strength or slow walking speed. On the other hand, IWGS criteria screened study individuals by the walking speed of 1.0 m/s, and individuals with slow walking speed were recommended for skeletal muscle measurements.14 Height-adjusted ASM proposed by Baumgartner et al,19 and weight-adjusted ASM proposed by Janssen et al,31 were used for comparisons in this study. Other Associated Clinical Characteristics In ILAS, the autonomy assessment scale (SMAF), a functional assessment tool of a 29-item scale ranging from 0 to 87 points, was used to describe the physical function of all study individuals.32 SMAF measured activities of daily living, instrumental activities of daily living, mental function, mobility, and communications. The MiniNutrition Assessment was used to evaluate nutritional status in this study.33 Previous falls, defined as any fall event within 3 months, were recorded. Current medication use was evaluated, and polypharmacy was defined as using 5 or more medications.34 The Charlson Comorbidity Index, a list of comorbidities weighted from 1 to 6, was used to describe the severity of underlying medical conditions.35 Statistical Analysis In this study, continuous variables in the text and tables were expressed by mean SD and categorical variables were expressed by number (percentage). Comparisons between continuous variables were performed by Student t test and comparisons of categorical data were done by chi-square test or Fisher exact test when appropriate. Comparisons of clinical numerical characteristics between different category variables were done by 1-way analysis of variance. Multivariable logistic regression was used to identify independent risk factors of sarcopenia by different definitions. All statistical analysis was done by commercial statistical software (SPSS 16.0; IBM Corporation, Chicago, IL). A P value less than .05 (2-tailed) was considered statistically significant.
Table 1 Demographic Characteristics of Healthy Young Reference Group for Determination of Cutoff Values of Sarcopenia Men (n ¼ 50) Age, y Anthropometric measurements Height, cm Weight, kg Body mass index, kg/m2 Dual-energy x-ray absorptiometry Total body fat percentage, % Total body fat, kg Appendicular skeletal muscle mass, kg Total skeletal muscle mass, kg Relative skeletal muscle index Lower 20th percentile skeletal muscle index Percentage skeletal muscle index (SMI%) Lower 20th percentile SMI%
31.0 5.3
174.4 6.0 73.7 13.3 24.2 3.8
159.3 5.7 56.8 10.8 22.3 3.7
25.0 6.9 18.6 8.0 24.9 3.3
36.9 6.2 21.0 7.4 15.1 2.6
29.1 3.7 8.2 0.9
17.4 2.9 5.9 0.8
7.27
5.44
40.0 3.9
31.0 3.9
37.4
28.0
(7.8% vs 4.1%, P < .001 by RASM, and 16.6% vs 11.1%, P < .001 by SMI), but the agreement between IWGS and EWGSOP criteria was only fair (kappa ¼ 0.448 by RASM, and kappa ¼ 0.471 by SMI). Table 3 summarizes comparisons between sarcopenia diagnosed by IWGS and EWGSOP using either RASM or SMI, which showed that the prevalence of sarcopenia was lower using IWGS than EWGSOP criteria in general, but was even lower by using RASM than SMI in both criteria. In Figure 2, multivariable logistic regression denoted that age was a strong predictor of sarcopenia in both IWGS and EWGSOP criteria. By using RASM, the odds ratio of sarcopenia per increase in 10 years of age was 2.4 by IWGS criteria (P ¼ .005) and was 3.2 by EWGSOP criteria (P < .001). On the other hand, the odds ratio of sarcopenia was
Table 2 Characteristics of Study Individuals in the I-Lan Longitudinal Ageing Study Participants
Results Among 100 young reference adults, the mean RASM (ASM/ht2) was 8.2 kg/m2 for men and 5.9 kg/m2 for women; and the mean SMI was 40% for men and 31% for women. The lower 20th percentiles of these measurements were defined as cutoff points of lower muscle mass, which were 7.27 kg/m2 for men and 5.44 kg/m2 for women by RASM and 37.4% for men and 28.0% for women by SMI (Table 1). Overall, data of 386 elderly participants (mean age: 73.7 5.6 years, 57.8% men) were retrieved for analysis. Table 2 summarizes the comparisons of demographic characteristics between men and women. In general, men possessed more total skeletal muscle mass, less total body fat, and lower BMI than women, although men were somewhat older than women. In muscle strength and physical performance, men walked faster and had more muscle strength than women. In muscle mass measurements, men were significantly higher than women in both muscle indices (ie, RASM and SMI). Figure 1 compares the prevalence of sarcopenia by using RASM and SMI as the definition of low muscle mass. The prevalence of low muscle mass was significantly lower in women than in men in both muscle indices (6.7% vs 42.9% by RASM, P < .001; and 32.9% vs 67.3% by SMI, P < .001). Sarcopenia diagnosed by RASM was more common in lean people (P for trend < .001 in both genders), but was more prevalent in obese people by using SMI (P for trend < .001 in both genders). Compared with sarcopenia diagnosed by IWGS, prevalence of sarcopenia diagnosed by EWGSOP criteria was significantly higher
Women (n ¼ 50)
30.3 5.1
Men (n ¼ 223) Age, y Anthropometric measurements Height, cm Weight, kg Body mass index, kg/m2 Walking speed, m/s Handgrip strength, kg Dual-energy x-ray absorptiometry Total body fat percentage, % Total body fat, kg Appendicular skeletal muscle mass, kg Total skeletal muscle mass, kg Relative skeletal muscle index Percentage skeletal muscle index Alcohol consumption, % Current smoker, % Falls, % Polypharmacy, % Neuropsychiatric medication, % Sleep pills, % Functional Autonomy Measurement System Charlson Comorbidity Index Mini-nutrition assessment
74.4 6.1
72.8 4.9
.004 <.001 <.001 .023 <.001 <.001
26.4 7.5 16.4 6.3 19.9 2.7
34.7 7.8 20.4 6.8 14.6 1.9
<.001 <.001 <.001
22.6 3.0 7.6 0.8
16.0 2.2 6.4 0.6
<.001 <.001
35.7 3.8
28.4 3.7
<.001
37.7 39.5 6.3 16.6 9.0 3.1 0.6 3.1
12.9 4.3 8.0 19.6 8.6 2.5 0.5 3.1
<.001 <.001 .549 .502 1.000 .766 .821
0.3 0.7 26.9 2.1
0.4 0.8 26.8 2.2
.209 .732
6.5 9.5 3.2 0.4 7.2
150.8 57.1 25.1 1.2 18.9
P Value
5.1 9.2 3.7 0.4 4.9
161.7 63.3 24.3 1.4 29.9
Women (n ¼ 163)
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Fig. 1. Comparisons of study individuals with different obesity status and gender according to the cutoff values of skeletal muscle mass determined by healthy young reference group by using (A) RASM and (B) SMI.
increased to 4.3 by IWGS criteria (P < .001) and 3.8 by EWGSOP criteria (P < .001) using SMI. Although obesity played a neutral role in sarcopenia in both IWGS and EWGSOP criteria, overweight was protective for EWGSOP-defined sarcopenia by using RASM (odds ratio 0.3, P ¼ .005). Unlike RASM, obesity was a significant risk factor for sarcopenia in both criteria by using SMI, and the prevalence of sarcopenia was higher in obese than in lean individuals by using SMI in both criteria. Demographic characteristics, BMI, physical performance, and skeletal muscle mass evaluated by different muscle indices in IWGS and EWGSOP criteria were compared. The consistency group was defined as individuals having the same diagnosis, either sarcopenia or nonsarcopenia, by IWGS and EWGSOP definitions. The discrepancy group was defined as individuals having different sarcopenia entities by the IWGS and EWGSOP definitions. By using either RASM or SMI, age, BMI, physical performance, and muscle strength of the discrepancy group were significantly different from the consistency group. Figure 3 compares muscle strength and walking speed between the Table 3 Prevalence of Sarcopenia According to Definition of IWGS and EWGSOP by RASM and Percentage SMI in Different Age Groups Age, y
Men 65e74 75e84 85 Subtotal Women 65e74 75e84 85 Subtotal Total
RASM, kg/m2
SMI, %
IWGS, n (%)
EWGSOP, n (%)
IWGS, n (%)
EWGSOP, n (%)
3 10 0 13
(2.3) (11.9) (0) (5.8)*
5 17 2 24
(3.9) (20.2) (18.2) (10.8)*
6 15 3 24
(4.7) (17.9) (27.3) (10.8)y
8 23 2 33
(6.3) (27.7) (18.2) (14.9)y
1 2 0 3 16
(0.9) (4.1) (0) (1.8)* (4.1)*
2 4 0 6 30
(1.8) (8.2) (0) (3.7)* (7.8)*
9 9 1 19 43
(8.0) (18.4) (50) (11.7)y (11.1)y
13 17 1 31 64
(11.6) (34.7) (50) (19)y (16.6)y
EWGSOP, European Working Group on Sarcopenia in Older People; IWGS, International Working Group on Sarcopenia; RASM, relative skeletal mass index; SMI, skeletal muscle index. *Compared with IWGS and EWGSOP by RASM: P < .001. y Compared with IWGS and EWGSOP by SMI: P < .001.
discrepancy group and consistency group. As for walking speed, men walked faster than women in the consistent nonsarcopenia group by RASM (1.4 0.4 m/s for men and 1.2 0.4 m/s for women, P < .001), but were similar in other groups. However, by using SMI, men walked faster than women in the consistent nonsarcopenia group (1.5 0.4 m/s for men and 1.3 0.3 m/s for women by IWGS, P < .001) or the discrepancy group (sarcopenia by EWGSOP criteria and nonsarcopenia by IWGS group) (1.3 0.3 m/s for men and 1.0 0.3 m/s for women, P ¼ .003). So, a potential gender difference in walking speed may exist, which may differ when the SMI was used. Discussion Currently, the prevalence of sarcopenia varies extensively when different definitions, instruments of measurements, methods of determining cutoff values, and gender are considered,14,36e39 which supports the need for a universal consensus of sarcopenia with full considerations of the aforementioned factors. Diagnostic criteria of IWGS and EWGSOP were the 2 commonly used definitions for sarcopenia; however, little was known regarding the evaluations of the consistency of the IWGS and EWGSOP criteria. Although skeletal muscle mass measurements were critically important in both criteria, no single SMI was universally recommended. Woods and colleagues22 argued that the 2 commonly used muscle indices (ie, RASM and SMI), eventually defined 2 different populations. In this study, the agreement of sarcopenia diagnosed by IWGS and EWGSOP was only fair, whether using RASM or SMI. Previous studies have shown that the prevalence of sarcopenia was lower in Asian than in Caucasian and Hispanic populations.40e42 In a national survey of Korea, only 0.1% of women were considered sarcopenic by using RASM.41 Results of the Korean study were similar to this study in that hardly any of the women would be considered sarcopenic if low muscle mass was defined as 2 SDs below the mean of young reference adults. The cutoff value of low muscle mass in this study was defined as less than the 20th percentile of that in healthy young adults, which has been used in other studies.14,30 Although current studies support the existence of differences in body composition among people with different ethnic backgrounds, selection of proper diagnostic instruments and
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Fig. 2. The odds ratio of independent associate factors for sarcopenia defined by (A) IWGS definition using RASM muscle index, (B) EWGSOP definition using RASM muscle index, (C) IWGS definition by SMI muscle index, and (D) EWGSOP definition using SMI muscle index.
cutoff values should be determined by outcome-based trials. The cutoff points of relative SMI in this study (men: 7.27 kg/m2, women: 5.44 kg/m2) were similar to the Rosetta study19 (men: 7.26 kg/m2, women: 5.45 kg/m2) and Health ABC study43 (men: 7.25 kg/m2, women: 5.67 kg/m2), but higher than the report from Hong Kong40 (men: 5.72 kg/m2, women: 4.82 kg/m2) and lower than another group from Taipei of a Taiwanese population42 (men: 8.87 kg/m2, women: 6.42 kg/m2 using bioimpedance analysis). Domiciano et al39 reported that RASM may underestimate the prevalence of sarcopenia in overweight and obese people and more than 95% of sarcopenic individuals defined by RASM were lean. However, RASM was a better mobility predictor than SMI.43 Similar to previous studies, in this study, low muscle mass defined by RASM was most in lean people and was more common in overweight and obese people by using SMI. Compared with the IWGS definition, the prevalence of sarcopenia in older people was higher in the EWGSOP definition in both genders, and was even higher when low muscle mass was defined by SMI than RASM. The differences in the prevalence of sarcopenia may vary from 4.1% in IWGS criteria using RASM to 16.6% in EWGSOP criteria using SMI. The prevalence of sarcopenia in older men was 5.8% to 14.9%, and 4.1% to 16.6% in older women by combinations of different criteria in our study. Compared with the classical definition of sarcopenia, modern diagnostic criteria added considerations of muscle strength and physical performance to the muscle mass, which lowered the prevalence of sarcopenia. However, the agreement of
sarcopenia diagnosis between IWGS and EWGSOP criteria was only fair.44 Yet, no outcome-based trials compare the IWGS and EWGSOP criteria to formulate the most optimal strategy for sarcopenia diagnosis. It was not surprising that prevalence of sarcopenia defined by EWGSOP was higher than that by IWGS because low muscle strength with low muscle mass without low physical performance would be classified as sarcopenia in EWGSOP but not in IWGS. This study clearly demonstrated that the prevalence of sarcopenia may vary extensively through different methodologies. The biggest discrepancy between IWGS and EWGSOP criteria may have resulted from the selection of muscle indices. When the study individuals were lean, diagnosis of sarcopenia by EWGSOP and IWGS using RASM would be more inconsistent. Therefore, the discrepancy of the 2 diagnostic criteria may be strongly affected by the differences of demographic characteristics of study populations.39 Slow walking speed, the most characteristic indicator of sarcopenia, was associated with cardiovascular death,30 cognitive function decline,45 and other adverse health outcomes.46 However, walking speed was strongly affected by leg length, which may result in differences of cutoff values in different genders and ethnicities.47 Adjustment for gender and ethnicity in sarcopenia may be needed to prevent underestimation in Asian populations, but only outcomebased studies with gender and ethnic considerations can sufficiently define appropriate cutoff values. In EWGSOP criteria, individuals with low muscle mass and either low handgrip strength or slow walking
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Fig. 3. Comparisons of walking speed between discrepancy and consistency group of sarcopenia defined by IWGS and EWGSOP criteria by (A) RASM muscle index and (B) SMI muscle index. IGWS (0): nonsarcopenia by IWGS criteria; EWGSOP (0): nonsarcopenia by EWGSOP criteria; IGWS (1): sarcopenia by IWGS criteria; EWGSOP (1): sarcopenia by EWGSOP.
speed would be categorized as sarcopenic, but sarcopenia defined by the IWGS criteria allowed only individuals with concomitant slow walking speed and low muscle mass. Some people diagnosed as sarcopenic by IWGS criteria may be nonsarcopenic by EWGSOP criteria (1.3% by using RASM and 3.6 % by using SMI, respectively), which indicated that individuals with slower walking speed may still possess sufficient muscle strength of upper limbs. Moreover, the EWGSOP criteria categorized people with normal walking speed (cutoff value of 0.8 m/s) and handgrip strength as nonsarcopenic without needing muscle mass measurements, which may miss some sarcopenic individuals using IWGS criteria (walking speed between 0.8 to 1 m/s with the presence of low muscle mass). Compared with Caucasians with the same BMI, Asian women tend to have higher adiposity under the same BMI status,48 which may partly explain the differences in skeletal muscle mass measurements in this study and the previous Korean report. Whether sarcopenia was really a rare condition of older Asian women remained unclear, but certain adjustments to define sarcopenia in Asian people are needed. Although a recent study indicated that handgrip strength and walking speed did not play the same role in mortality prediction,49 sarcopenia can be considered for clinical use in addition to research.50 In this study, there are several limitations. First, although the sample size was satisfactory compared with other studies, a larger sample may provide more information because the prevalence of sarcopenia in older women was low in most Asian studies. Second, the cross-sectional design of this study limited the possibilities of determining the most optimal cutoff values of muscle strength, physical performance, and muscle mass measurements through outcome-based approaches. Nevertheless, ILAS was a longitudinal study, which may provide more in-depth information in the future. Third, this study recruited individuals with relatively better health by excluding people with poor communication ability, inability to walk 6 meters in a reasonable time, and institutionalized elders from the recruitment. Therefore, all measurements regarding sarcopenia may be better than the general elderly population. Fourth, the study individuals were relatively younger, especially in women, than in other sarcopenia studies, which may limit the extrapolation of the results to the oldest-old population. In conclusion, different
diagnostic approaches and cutoff values of sarcopenia have made a substantial impact on the epidemiology of sarcopenia. Proper selections for cutoff values of handgrip strength, walking speed, and SMIs with full considerations of gender and ethnic differences were of critical importance to reach the universal diagnostic criteria for sarcopenia internationally. References 1. Rosenberg IH, Roubenoff R. Stalking sarcopenia. Ann Intern Med 1995;123: 727e728. 2. Rogers MA, Evans WJ. Changes in skeletal muscle with aging: Effects of exercise training. Exerc Sport Sci Rev 1993;21:65e102. 3. Fleg JL, Lakatta EG. Role of muscle loss in the age-associated reduction in VO2 max. J Appl Physiol 1988;65:1147e1151. 4. Frontera WR, Hughes VA, Fielding RA, et al. Aging of skeletal muscle: A 12-yr longitudinal study. J Appl Physiol 2000;88:1321e1326. 5. Walston JD. Sarcopenia in older adults. Curr Opin Rheumatol 2012;24: 623e627. 6. Marsh AP, Rejeski WJ, Espeland MA, et al. Muscle strength and BMI as predictors of major mobility disability in the Lifestyle Interventions and Independence for Elders pilot (LIFE-P). J Gerontol A Biol Sci Med Sci 2011;66: 1376e1383. 7. Xue QL, Walston JD, Fried LP, et al. Prediction of risk of falling, physical disability, and frailty by rate of decline in grip strength: The Women’s Health and Aging Study. Arch Intern Med 2011;171:1119e1121. 8. Goodpaster BH, Park SW, Harris TB, et al. The loss of skeletal muscle strength, mass, and quality in older adults: The health, aging and body composition study. J Gerontol A Biol Sci Med Sci 2006;61:1059e1064. 9. Woo J, Leung J, Sham A, et al. Defining sarcopenia in terms of risk of physical limitations: A 5-year follow-up study of 3,153 chinese men and women. J Am Geriatr Soc 2009;57:2224e2231. 10. Cesari M, Pahor M, Lauretani F, et al. Skeletal muscle and mortality results from the InCHIANTI Study. J Gerontol A Biol Sci Med Sci 2009;64:377e384. 11. Janssen I, Shepard DS, Katzmarzyk PT, et al. The healthcare costs of sarcopenia in the United States. J Am Geriatr Soc 2004;52:80e85. 12. Cruz-Jentoft AJ, Landi F, Topinkova E, et al. Understanding sarcopenia as a geriatric syndrome. Curr Opin Clin Nutr Metab Care 2010;13:1e7. 13. Wang C, Bai L. Sarcopenia in the elderly: Basic and clinical issues. Geriatr Gerontol Int 2012;12:388e396. 14. Fielding RA, Vellas B, Evans WJ, et al. Sarcopenia: An undiagnosed condition in older adults. Current consensus definition: Prevalence, etiology, and consequences. International Working Group on Sarcopenia. J Am Med Dir Assoc 2011;12:249e256. 15. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010;39:412e423.
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16. Newman AB, Kupelian V, Visser M, et al. Strength, but not muscle mass, is associated with mortality in the health, aging and body composition study cohort. J Gerontol A Biol Sci Med Sci 2006;61:72e77. 17. Clark BC, Manini TM. Functional consequences of sarcopenia and dynapenia in the elderly. Curr Opin Clin Nutr Metab Care 2010;13:271e276. 18. Clark BC, Manini TM. Sarcopeniasdynapenia. J Gerontol A Biol Sci Med Sci 2008;63:829e834. 19. Baumgartner RN, Koehler KM, Gallagher D, et al. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 1998;147:755e763. 20. Jassen I, Ross R. Linking age-related changes in skeletal muscle mass and composition with metabolism and disease. J Nutr Health Aging 2005;9:408e419. 21. Estrada M, Kleppinger A, Judge JO, et al. Functional impact of relative versus absolute sarcopenia in healthy older women. J Am Geriatr Soc 2007;55: 1712e1719. 22. Woods JL, Iuliano-Burns S, King SJ, et al. Poor physical function in elderly women in low-level aged care is related to muscle strength rather than to measures of sarcopenia. Clin Interv Aging 2011;6:67e76. 23. Chen LK. Sarcopenia: Have we reached the consensus? J Frailty Aging 2012;1: 99e101. 24. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363:157e163. 25. Wu SW, Wu SF, Liang HW, et al. Measuring factors affecting grip strength in a Taiwan Chinese population and a comparison with consolidated norms. Appl Ergon 2009;40:811e815. 26. Dumurgier J, Elbaz A, Ducimetiere P, et al. Slow walking speed and cardiovascular death in well functioning older adults: Prospective cohort study. BMJ 2009;339:b4460. 27. Munoz-Mendoza CL, Cabanero-Martinez MJ, Millan-Calenti JC, et al. Reliability of 4-m and 6-m walking speed tests in elderly people with cognitive impairment. Arch Gerontol Geriatr 2011;52:e67ee70. 28. Heymsfield SB, Smith R, Aulet M, et al. Appendicular skeletal muscle mass: Measurement by dual-photon absorptiometry. Am J Clin Nutr 1990;52: 214e218. 29. Kim J, Wang Z, Heymsfield SB, et al. Total-body skeletal muscle mass: Estimation by a new dual-energy X-ray absorptiometry method. Am J Clin Nutr 2002;76:378e383. 30. Newman AB, Kupelian V, Visser M, et al. Sarcopenia: Alternative definitions and associations with lower extremity function. J Am Geriatr Soc 2003;51: 1602e1609. 31. Janssen I, Heymsfield SB, Ross R. Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc 2002;50:889e896. 32. Hebert R, Carrier R, Bilodeau A. The Functional Autonomy Measurement System (SMAF): Description and validation of an instrument for the measurement of handicaps. Age Ageing 1988;17:293e302. 33. Guigoz Y. The Mini Nutritional Assessment (MNA) review of the literatured What does it tell us? J Nutr Health Aging 2006;10:466e485. discussion 85e87.
34. Gnjidic D, Hilmer SN, Blyth FM, et al. Polypharmacy cutoff and outcomes: Five or more medicines were used to identify community-dwelling older men at risk of different adverse outcomes. J Clin Epidemiol 2012;65:989e995. 35. Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 1987;40:373e383. 36. Janssen I. The epidemiology of sarcopenia. Clin Geriatr Med 2011;27:355e363. 37. Abellan van Kan G. Epidemiology and consequences of sarcopenia. J Nutr Health Aging 2009;13:708e712. 38. Sanada K, Miyachi M, Tanimoto M, et al. A cross-sectional study of sarcopenia in Japanese men and women: Reference values and association with cardiovascular risk factors. Eur J Appl Physiol 2010;110:57e65. 39. Domiciano DS, Figueiredo CP, Lopes JB, et al. Discriminating sarcopenia in community-dwelling older women with high frequency of overweight/ obesity: The Sao Paulo Ageing & Health Study (SPAH). Osteoporos Int 2013;24: 595e603. 40. Lau EM, Lynn HS, Woo JW, et al. Prevalence of and risk factors for sarcopenia in elderly Chinese men and women. J Gerontol A Biol Sci Med Sci 2005;60: 213e216. 41. Kim YS, Lee Y, Chung YS, et al. Prevalence of sarcopenia and sarcopenic obesity in the Korean population based on the Fourth Korean National Health and Nutritional Examination Surveys. J Gerontol A Biol Sci Med Sci 2012;67: 1107e1113. 42. Chien MY, Huang TY, Wu YT. Prevalence of sarcopenia estimated using a bioelectrical impedance analysis prediction equation in community-dwelling elderly people in Taiwan. J Am Geriatr Soc 2008;56:1710e1715. 43. Delmonico MJ, Harris TB, Lee JS, et al. Alternative definitions of sarcopenia, lower extremity performance, and functional impairment with aging in older men and women. J Am Geriatr Soc 2007;55:769e774. 44. Sim J, Wright CC. The kappa statistic in reliability studies: Use, interpretation, and sample size requirements. Phys Ther 2005;85:257e268. 45. Buracchio T, Dodge HH, Howieson D, et al. The trajectory of gait speed preceding mild cognitive impairment. Arch Neurol 2010;67:980e986. 46. Abellan van Kan G, Rolland Y, Andrieu S, et al. Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older people. International Academy on Nutrition and Aging (IANA) Task Force. J Nutr Health Aging 2009;13:881e889. 47. Studenski S, Perera S, Patel K, et al. Gait speed and survival in older adults. JAMA 2011;305:50e58. 48. Lim U, Ernst T, Buchthal SD, et al. Asian women have greater abdominal and visceral adiposity than Caucasian women with similar body mass index. Nutr Diabetes 2011;1:e6. 49. Chen PJ, Lin MH, Peng LN, et al. Predicting cause-specific mortality of older men living in the Veteran Home by handgrip strength and walking speed: A 3-year prospective cohort study in Taiwan. J Am Med Dir Assoc 2012;13:517e521. 50. Cesari M, Vellas B. Sarcopenia: A novel clinical condition or still a matter for research? J Am Med Dir Assoc 2012;13:766e767.
JAMDA journal homepage: www.jamda.com
Original Study
Comparisons of Sarcopenia Defined by IWGS and EWGSOP Criteria Among Older People: Results From the I-Lan Longitudinal Aging Study Wei-Ju Lee MD a, b, Li-Kuo Liu MD b, c, Li-Ning Peng MD, MSc b, c, Ming-Hsien Lin MD b, c, Liang-Kung Chen MD, PhD, FRCP a, c, *, and the ILAS Research Group a
Aging and Health Research Center, National Yang Ming University, Taipei, Taiwan Department of Family Medicine, Taipei Veterans General Hospital Yuanshan Branch, I-Lan County, Taiwan c Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan b
a b s t r a c t Keywords: Sarcopenia skeletal muscle mass handgrip strength walking speed obesity
Objective: To compare clinical characteristics of sarcopenia defined by the International Working Group on Sarcopenia (IWGS) and European Working Group on Sarcopenia in Older People (EWGSOP) criteria among older people in Taiwan. Design: A prospective population-based community study. Setting: I-Lan County of Taiwan. Participants: A total of 100 young healthy volunteers and 408 elderly people. Intervention: None. Measurements: Anthropometry, skeletal muscle mass measured by dual x-ray absorptiometry, relative appendicular skeletal muscle index (RASM), percentage skeletal muscle index (SMI), 6-meter walking speed, and handgrip strength. Results: The prevalence of sarcopenia was 5.8% to 14.9% in men and 4.1% to 16.6% in women according to IWGS and EWGSOP criteria by using RASM or SMI as the muscle mass indices. The agreement of sarcopenia diagnosed by IWGS and EWGSOP criteria was only fair by using either RASM or SMI (kappa ¼ 0.448 by RASM, kappa ¼ 0.471 by SMI). The prevalence of sarcopenia was lower by the IWGS definition than the EWGSOP definition, but it was remarkably lower by using RASM than SMI in both criteria. Overall, sarcopenic individuals defined by SMI were older, had a higher BMI but similar total skeletal muscle mass, and had poorer muscle strength and physical performance than nonsarcopenic individuals. However, by using RASM, sarcopenic individuals had less total skeletal muscle mass but similar BMI than nonsarcopenic individuals. Multivariable logistic regression showed that age was the strongest associative factor for sarcopenia in both IWGS and EWGSOP criteria. Obesity played a neutral role in sarcopenia when it is defined by using RASM, but significantly increased the risk of sarcopenia in both criteria by using SMI. Conclusion: The agreement of sarcopenia defined by IWGS and EWGSOP was only fair, and the prevalence varied largely by using different skeletal muscle mass indices. Proper selections for cutoff values of handgrip strength, walking speed, and skeletal muscle indices with full considerations of gender and ethnic differences were of critical importance to reach the universal diagnostic criteria for sarcopenia internationally. Copyright Ó 2013 - American Medical Directors Association, Inc.
Sarcopenia, first proposed by Rosenberg and Roubenoff,1 was described as the age-related loss of skeletal muscle. Evidence suggests that up to 40% of muscle mass may be lost between the ages of 20 and 70 years.2 The decline of skeletal muscle mass may accelerate along with aging, which is 6% per decade between 30 and
The authors declare no conflicts of interest. * Address correspondence to Liang-Kung Chen, MD, PhD, FRCP, Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, No. 201, Section 2, ShihPai Road, Taipei, Taiwan. E-mail address: [email protected] (L.-K. Chen).
70 years of age,3 1.4% to 2.5% per year after age 60, and could start as early at 35 years of age.4 Overall, sarcopenia was common in the elderly population,5 and was associated with adverse health outcomes, such as falls, frailty, limited physical function, disability, and loss of independence.6e9 In addition, sarcopenia was associated with mortality 10 and increased health care expenditures. 11 Currently, sarcopenia is considered as a new geriatric syndrome,12 and may result in a heavy health care burden to the world. Although sarcopenia has gained extensive interest, an ideal operational definition covering different ethnic backgrounds is still under development.13
1525-8610/$ - see front matter Copyright Ó 2013 - American Medical Directors Association, Inc. http://dx.doi.org/10.1016/j.jamda.2013.03.019
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The International Working Group on Sarcopenia (IWGS) proposed an operational definition of sarcopenia in 2009,14 which was targeted to individuals with functional decline, mobility-related difficulties, history of recurrent falls, recent unintentional body weight loss, posthospitalization, and chronic conditions (such as type 2 diabetes, chronic heart failure, chronic obstructive pulmonary disease, chronic kidney disease, rheumatoid arthritis, and cancer), and was more suitable in clinical settings. On the other hand, the European Working Group on Sarcopenia in Older People (EWGSOP) proposed another diagnostic definition for sarcopenia in 2010,15 which recommended screening for sarcopenia in all people 65 years and older. Unlike earlier definitions of sarcopenia, focusing on measurements of low muscle mass only, IWGS and EWGSOP definitions both added measurements of physical performance (EWGSOP definition also considered muscle strength) based on several longitudinal studies.10,16 Some researchers proposed a new term, “dynapenia,” to emphasize the importance of muscle function and performance over muscle mass.17,18 To date, researchers took a combined approach for sarcopenia diagnosis as the coexistence of low muscle mass and low physical performance (slow walking speed and/or low muscle strength, eg, handgrip strength), knee flexion/ extension, or peak expiratory flow. In muscle mass measurement, the fundamental process of diagnosis of sarcopenia, appendicular skeletal muscle mass adjusted by either height19 or weight,20,21 was the most recommended approach to determine the relative skeletal muscle. Nevertheless, Woods et al22 argued that the 2 common indices of sarcopenia eventually defined different populations. Moreover, there may be ethnic differences in the previously mentioned measurements of muscle mass, strength, or physical performance in the diagnosis of sarcopenia.23 Although sarcopenia has become a research focus in the world, little was known relating to the differences of clinical characteristics of sarcopenia diagnosed by IWGS and EWGSOP criteria and different skeletal muscle indices among older people in Taiwan. Therefore, the main purpose of this study was to compare the differences of sarcopenia diagnosed by IWGS and EWGSOP criteria and different skeletal muscle indices among older people in Taiwan. Methods Participants The I-Lan Longitudinal Ageing Study (ILAS), a population-based aging cohort study, consisted of long-living middle-aged and elderly people in the I-Lan County of Taiwan. The ILAS intended to explore the complex interrelationship among aging, frailty, sarcopenia, and decline of cognitive function. Community-dwelling people aged 50 years and older were randomly sampled through the household registration data from I-Lan County. Research nurses invited sampled individuals to participate in the study via mail or telephone. All participants fully consented and completed a written informed consent. Individuals with the following conditions were excluded from the study: (1) unable to communicate with research nurses or to grant a permit, (2) unable to walk for 6 meters within a reasonable period of time, (3) not likely to live for more than 6 months because of a major illness, (4) unable to receive magnetic resonance imaging because of a mechanical implant, and (5) institutionalized currently. Data of 408 individuals 65 years and older from the ILAS were retrieved for this study, and 22 of them were excluded because of incomplete data. The study was approved by the institutional review board of the Taipei Veterans General Hospital and National Yang Ming University. Anthropometry Body weight and standing height of all participants were measured when they were wearing light indoor clothing and no shoes. Body
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mass index (BMI) was calculated as weight (kg) divided by height (m) squared. Status of obesity was determined by the World Health Organization Asia-Pacific criteria of obesity as follows: underweight (BMI <18.5 kg/m2), normal weight (BMI 18.5e22.9 kg/m2), overweight (BMI 23.0e27.4 kg/m2), and obese (BMI 27.5 kg/m2).24 Handgrip Strength A well-trained research nurse completed handgrip strength measurements for all participants. Handgrip strength was measured by using a dynamometer (Smedlay’s Dynamometer, TTM, Tokyo, Japan) 3 times. Participants were allowed a pretest trial in an upright standing position with arms straight down to their sides. All participants were instructed to hold the dynamometer with a dominant hand without squeezing arms to the body. The best performance was taken for analysis. A previous study in Taiwan found that handgrip strength in Taiwanese individuals was about 25.4% lower in men and 27.4% lower in women than that of Caucasians,25 and we modified the cutoff points of low handgrip strength in EWGSOP criteria15 to less than 22.4 kg for men and less than 14.3 kg for women. Physical Performance In this study, gait speed was assessed by the 6-meter walk.26,27 Participants walked at their usual speed with a static start without deceleration throughout a 6-meter straight line in an examination room that was more than 8 meters in length. The time was measured by a same study nurse using a stop watch (HS-70W; Casio Computer Co, LTC, Tokyo, Japan). Skeletal Muscle Mass Measurement A total of 100 healthy adult volunteers (50 men and 50 women) aged 20 to 40 years were invited for skeletal muscle measurements as the reference group. All participants and the reference young adults received whole-body dual-energy x-ray absorptiometry (DXA) scans to obtain total fat mass, percentage of fat-free lean body mass (LBM), and bone mineral density using the standardized procedures of the period calibrated manufacturers (Prodigy; GE Lunar, Madison, WI, and DPX-NT, Madison, WI). Appendicular skeletal muscle mass (ASM) was calculated as the sum of LBM of all 4 limbs.28 Relative skeletal muscle mass index (RASM) was defined as ASM divided by body height in meters squared.19 Kim et al29 proposed equations to estimate total skeletal muscle mass (SMM) and the relative sarcopenia condition from a Korean cohort as follows: 1. Total SMM (kg) ¼ (1.13 ASM) (0.02 age) þ (0.61 sex) þ 0.97, where sex ¼ 0 for women and 1 for men. 2. Percentage skeletal muscle index (SMI%) ¼ SMM/weight (kg) 100 The lower 20th percentile of RASM and SMI from the mean of the young reference group was used to establish cutoff points of sarcopenia.30 Diagnosis of Sarcopenia In this study, sarcopenia defined by EWGSOP and IWGS criteria was compared. In EWGSOP criteria,15 sarcopenia was defined as low muscle mass plus low muscle strength (measured by handgrip strength, knee extensor, or peak expiratory flow) or low physical performance (measured by the Short Physical Performance Battery, usual gait speed, timed get-up-and-go test, or stair-climb power test). According to the case finding algorithm of EWGSOP, all study
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participants were screened by walking speed first, and DXA would be performed for muscle mass measurements if the individuals had lower handgrip strength or slow walking speed. On the other hand, IWGS criteria screened study individuals by the walking speed of 1.0 m/s, and individuals with slow walking speed were recommended for skeletal muscle measurements.14 Height-adjusted ASM proposed by Baumgartner et al,19 and weight-adjusted ASM proposed by Janssen et al,31 were used for comparisons in this study. Other Associated Clinical Characteristics In ILAS, the autonomy assessment scale (SMAF), a functional assessment tool of a 29-item scale ranging from 0 to 87 points, was used to describe the physical function of all study individuals.32 SMAF measured activities of daily living, instrumental activities of daily living, mental function, mobility, and communications. The MiniNutrition Assessment was used to evaluate nutritional status in this study.33 Previous falls, defined as any fall event within 3 months, were recorded. Current medication use was evaluated, and polypharmacy was defined as using 5 or more medications.34 The Charlson Comorbidity Index, a list of comorbidities weighted from 1 to 6, was used to describe the severity of underlying medical conditions.35 Statistical Analysis In this study, continuous variables in the text and tables were expressed by mean SD and categorical variables were expressed by number (percentage). Comparisons between continuous variables were performed by Student t test and comparisons of categorical data were done by chi-square test or Fisher exact test when appropriate. Comparisons of clinical numerical characteristics between different category variables were done by 1-way analysis of variance. Multivariable logistic regression was used to identify independent risk factors of sarcopenia by different definitions. All statistical analysis was done by commercial statistical software (SPSS 16.0; IBM Corporation, Chicago, IL). A P value less than .05 (2-tailed) was considered statistically significant.
Table 1 Demographic Characteristics of Healthy Young Reference Group for Determination of Cutoff Values of Sarcopenia Men (n ¼ 50) Age, y Anthropometric measurements Height, cm Weight, kg Body mass index, kg/m2 Dual-energy x-ray absorptiometry Total body fat percentage, % Total body fat, kg Appendicular skeletal muscle mass, kg Total skeletal muscle mass, kg Relative skeletal muscle index Lower 20th percentile skeletal muscle index Percentage skeletal muscle index (SMI%) Lower 20th percentile SMI%
31.0 5.3
174.4 6.0 73.7 13.3 24.2 3.8
159.3 5.7 56.8 10.8 22.3 3.7
25.0 6.9 18.6 8.0 24.9 3.3
36.9 6.2 21.0 7.4 15.1 2.6
29.1 3.7 8.2 0.9
17.4 2.9 5.9 0.8
7.27
5.44
40.0 3.9
31.0 3.9
37.4
28.0
(7.8% vs 4.1%, P < .001 by RASM, and 16.6% vs 11.1%, P < .001 by SMI), but the agreement between IWGS and EWGSOP criteria was only fair (kappa ¼ 0.448 by RASM, and kappa ¼ 0.471 by SMI). Table 3 summarizes comparisons between sarcopenia diagnosed by IWGS and EWGSOP using either RASM or SMI, which showed that the prevalence of sarcopenia was lower using IWGS than EWGSOP criteria in general, but was even lower by using RASM than SMI in both criteria. In Figure 2, multivariable logistic regression denoted that age was a strong predictor of sarcopenia in both IWGS and EWGSOP criteria. By using RASM, the odds ratio of sarcopenia per increase in 10 years of age was 2.4 by IWGS criteria (P ¼ .005) and was 3.2 by EWGSOP criteria (P < .001). On the other hand, the odds ratio of sarcopenia was
Table 2 Characteristics of Study Individuals in the I-Lan Longitudinal Ageing Study Participants
Results Among 100 young reference adults, the mean RASM (ASM/ht2) was 8.2 kg/m2 for men and 5.9 kg/m2 for women; and the mean SMI was 40% for men and 31% for women. The lower 20th percentiles of these measurements were defined as cutoff points of lower muscle mass, which were 7.27 kg/m2 for men and 5.44 kg/m2 for women by RASM and 37.4% for men and 28.0% for women by SMI (Table 1). Overall, data of 386 elderly participants (mean age: 73.7 5.6 years, 57.8% men) were retrieved for analysis. Table 2 summarizes the comparisons of demographic characteristics between men and women. In general, men possessed more total skeletal muscle mass, less total body fat, and lower BMI than women, although men were somewhat older than women. In muscle strength and physical performance, men walked faster and had more muscle strength than women. In muscle mass measurements, men were significantly higher than women in both muscle indices (ie, RASM and SMI). Figure 1 compares the prevalence of sarcopenia by using RASM and SMI as the definition of low muscle mass. The prevalence of low muscle mass was significantly lower in women than in men in both muscle indices (6.7% vs 42.9% by RASM, P < .001; and 32.9% vs 67.3% by SMI, P < .001). Sarcopenia diagnosed by RASM was more common in lean people (P for trend < .001 in both genders), but was more prevalent in obese people by using SMI (P for trend < .001 in both genders). Compared with sarcopenia diagnosed by IWGS, prevalence of sarcopenia diagnosed by EWGSOP criteria was significantly higher
Women (n ¼ 50)
30.3 5.1
Men (n ¼ 223) Age, y Anthropometric measurements Height, cm Weight, kg Body mass index, kg/m2 Walking speed, m/s Handgrip strength, kg Dual-energy x-ray absorptiometry Total body fat percentage, % Total body fat, kg Appendicular skeletal muscle mass, kg Total skeletal muscle mass, kg Relative skeletal muscle index Percentage skeletal muscle index Alcohol consumption, % Current smoker, % Falls, % Polypharmacy, % Neuropsychiatric medication, % Sleep pills, % Functional Autonomy Measurement System Charlson Comorbidity Index Mini-nutrition assessment
74.4 6.1
72.8 4.9
.004 <.001 <.001 .023 <.001 <.001
26.4 7.5 16.4 6.3 19.9 2.7
34.7 7.8 20.4 6.8 14.6 1.9
<.001 <.001 <.001
22.6 3.0 7.6 0.8
16.0 2.2 6.4 0.6
<.001 <.001
35.7 3.8
28.4 3.7
<.001
37.7 39.5 6.3 16.6 9.0 3.1 0.6 3.1
12.9 4.3 8.0 19.6 8.6 2.5 0.5 3.1
<.001 <.001 .549 .502 1.000 .766 .821
0.3 0.7 26.9 2.1
0.4 0.8 26.8 2.2
.209 .732
6.5 9.5 3.2 0.4 7.2
150.8 57.1 25.1 1.2 18.9
P Value
5.1 9.2 3.7 0.4 4.9
161.7 63.3 24.3 1.4 29.9
Women (n ¼ 163)
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Fig. 1. Comparisons of study individuals with different obesity status and gender according to the cutoff values of skeletal muscle mass determined by healthy young reference group by using (A) RASM and (B) SMI.
increased to 4.3 by IWGS criteria (P < .001) and 3.8 by EWGSOP criteria (P < .001) using SMI. Although obesity played a neutral role in sarcopenia in both IWGS and EWGSOP criteria, overweight was protective for EWGSOP-defined sarcopenia by using RASM (odds ratio 0.3, P ¼ .005). Unlike RASM, obesity was a significant risk factor for sarcopenia in both criteria by using SMI, and the prevalence of sarcopenia was higher in obese than in lean individuals by using SMI in both criteria. Demographic characteristics, BMI, physical performance, and skeletal muscle mass evaluated by different muscle indices in IWGS and EWGSOP criteria were compared. The consistency group was defined as individuals having the same diagnosis, either sarcopenia or nonsarcopenia, by IWGS and EWGSOP definitions. The discrepancy group was defined as individuals having different sarcopenia entities by the IWGS and EWGSOP definitions. By using either RASM or SMI, age, BMI, physical performance, and muscle strength of the discrepancy group were significantly different from the consistency group. Figure 3 compares muscle strength and walking speed between the Table 3 Prevalence of Sarcopenia According to Definition of IWGS and EWGSOP by RASM and Percentage SMI in Different Age Groups Age, y
Men 65e74 75e84 85 Subtotal Women 65e74 75e84 85 Subtotal Total
RASM, kg/m2
SMI, %
IWGS, n (%)
EWGSOP, n (%)
IWGS, n (%)
EWGSOP, n (%)
3 10 0 13
(2.3) (11.9) (0) (5.8)*
5 17 2 24
(3.9) (20.2) (18.2) (10.8)*
6 15 3 24
(4.7) (17.9) (27.3) (10.8)y
8 23 2 33
(6.3) (27.7) (18.2) (14.9)y
1 2 0 3 16
(0.9) (4.1) (0) (1.8)* (4.1)*
2 4 0 6 30
(1.8) (8.2) (0) (3.7)* (7.8)*
9 9 1 19 43
(8.0) (18.4) (50) (11.7)y (11.1)y
13 17 1 31 64
(11.6) (34.7) (50) (19)y (16.6)y
EWGSOP, European Working Group on Sarcopenia in Older People; IWGS, International Working Group on Sarcopenia; RASM, relative skeletal mass index; SMI, skeletal muscle index. *Compared with IWGS and EWGSOP by RASM: P < .001. y Compared with IWGS and EWGSOP by SMI: P < .001.
discrepancy group and consistency group. As for walking speed, men walked faster than women in the consistent nonsarcopenia group by RASM (1.4 0.4 m/s for men and 1.2 0.4 m/s for women, P < .001), but were similar in other groups. However, by using SMI, men walked faster than women in the consistent nonsarcopenia group (1.5 0.4 m/s for men and 1.3 0.3 m/s for women by IWGS, P < .001) or the discrepancy group (sarcopenia by EWGSOP criteria and nonsarcopenia by IWGS group) (1.3 0.3 m/s for men and 1.0 0.3 m/s for women, P ¼ .003). So, a potential gender difference in walking speed may exist, which may differ when the SMI was used. Discussion Currently, the prevalence of sarcopenia varies extensively when different definitions, instruments of measurements, methods of determining cutoff values, and gender are considered,14,36e39 which supports the need for a universal consensus of sarcopenia with full considerations of the aforementioned factors. Diagnostic criteria of IWGS and EWGSOP were the 2 commonly used definitions for sarcopenia; however, little was known regarding the evaluations of the consistency of the IWGS and EWGSOP criteria. Although skeletal muscle mass measurements were critically important in both criteria, no single SMI was universally recommended. Woods and colleagues22 argued that the 2 commonly used muscle indices (ie, RASM and SMI), eventually defined 2 different populations. In this study, the agreement of sarcopenia diagnosed by IWGS and EWGSOP was only fair, whether using RASM or SMI. Previous studies have shown that the prevalence of sarcopenia was lower in Asian than in Caucasian and Hispanic populations.40e42 In a national survey of Korea, only 0.1% of women were considered sarcopenic by using RASM.41 Results of the Korean study were similar to this study in that hardly any of the women would be considered sarcopenic if low muscle mass was defined as 2 SDs below the mean of young reference adults. The cutoff value of low muscle mass in this study was defined as less than the 20th percentile of that in healthy young adults, which has been used in other studies.14,30 Although current studies support the existence of differences in body composition among people with different ethnic backgrounds, selection of proper diagnostic instruments and
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Fig. 2. The odds ratio of independent associate factors for sarcopenia defined by (A) IWGS definition using RASM muscle index, (B) EWGSOP definition using RASM muscle index, (C) IWGS definition by SMI muscle index, and (D) EWGSOP definition using SMI muscle index.
cutoff values should be determined by outcome-based trials. The cutoff points of relative SMI in this study (men: 7.27 kg/m2, women: 5.44 kg/m2) were similar to the Rosetta study19 (men: 7.26 kg/m2, women: 5.45 kg/m2) and Health ABC study43 (men: 7.25 kg/m2, women: 5.67 kg/m2), but higher than the report from Hong Kong40 (men: 5.72 kg/m2, women: 4.82 kg/m2) and lower than another group from Taipei of a Taiwanese population42 (men: 8.87 kg/m2, women: 6.42 kg/m2 using bioimpedance analysis). Domiciano et al39 reported that RASM may underestimate the prevalence of sarcopenia in overweight and obese people and more than 95% of sarcopenic individuals defined by RASM were lean. However, RASM was a better mobility predictor than SMI.43 Similar to previous studies, in this study, low muscle mass defined by RASM was most in lean people and was more common in overweight and obese people by using SMI. Compared with the IWGS definition, the prevalence of sarcopenia in older people was higher in the EWGSOP definition in both genders, and was even higher when low muscle mass was defined by SMI than RASM. The differences in the prevalence of sarcopenia may vary from 4.1% in IWGS criteria using RASM to 16.6% in EWGSOP criteria using SMI. The prevalence of sarcopenia in older men was 5.8% to 14.9%, and 4.1% to 16.6% in older women by combinations of different criteria in our study. Compared with the classical definition of sarcopenia, modern diagnostic criteria added considerations of muscle strength and physical performance to the muscle mass, which lowered the prevalence of sarcopenia. However, the agreement of
sarcopenia diagnosis between IWGS and EWGSOP criteria was only fair.44 Yet, no outcome-based trials compare the IWGS and EWGSOP criteria to formulate the most optimal strategy for sarcopenia diagnosis. It was not surprising that prevalence of sarcopenia defined by EWGSOP was higher than that by IWGS because low muscle strength with low muscle mass without low physical performance would be classified as sarcopenia in EWGSOP but not in IWGS. This study clearly demonstrated that the prevalence of sarcopenia may vary extensively through different methodologies. The biggest discrepancy between IWGS and EWGSOP criteria may have resulted from the selection of muscle indices. When the study individuals were lean, diagnosis of sarcopenia by EWGSOP and IWGS using RASM would be more inconsistent. Therefore, the discrepancy of the 2 diagnostic criteria may be strongly affected by the differences of demographic characteristics of study populations.39 Slow walking speed, the most characteristic indicator of sarcopenia, was associated with cardiovascular death,30 cognitive function decline,45 and other adverse health outcomes.46 However, walking speed was strongly affected by leg length, which may result in differences of cutoff values in different genders and ethnicities.47 Adjustment for gender and ethnicity in sarcopenia may be needed to prevent underestimation in Asian populations, but only outcomebased studies with gender and ethnic considerations can sufficiently define appropriate cutoff values. In EWGSOP criteria, individuals with low muscle mass and either low handgrip strength or slow walking
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Fig. 3. Comparisons of walking speed between discrepancy and consistency group of sarcopenia defined by IWGS and EWGSOP criteria by (A) RASM muscle index and (B) SMI muscle index. IGWS (0): nonsarcopenia by IWGS criteria; EWGSOP (0): nonsarcopenia by EWGSOP criteria; IGWS (1): sarcopenia by IWGS criteria; EWGSOP (1): sarcopenia by EWGSOP.
speed would be categorized as sarcopenic, but sarcopenia defined by the IWGS criteria allowed only individuals with concomitant slow walking speed and low muscle mass. Some people diagnosed as sarcopenic by IWGS criteria may be nonsarcopenic by EWGSOP criteria (1.3% by using RASM and 3.6 % by using SMI, respectively), which indicated that individuals with slower walking speed may still possess sufficient muscle strength of upper limbs. Moreover, the EWGSOP criteria categorized people with normal walking speed (cutoff value of 0.8 m/s) and handgrip strength as nonsarcopenic without needing muscle mass measurements, which may miss some sarcopenic individuals using IWGS criteria (walking speed between 0.8 to 1 m/s with the presence of low muscle mass). Compared with Caucasians with the same BMI, Asian women tend to have higher adiposity under the same BMI status,48 which may partly explain the differences in skeletal muscle mass measurements in this study and the previous Korean report. Whether sarcopenia was really a rare condition of older Asian women remained unclear, but certain adjustments to define sarcopenia in Asian people are needed. Although a recent study indicated that handgrip strength and walking speed did not play the same role in mortality prediction,49 sarcopenia can be considered for clinical use in addition to research.50 In this study, there are several limitations. First, although the sample size was satisfactory compared with other studies, a larger sample may provide more information because the prevalence of sarcopenia in older women was low in most Asian studies. Second, the cross-sectional design of this study limited the possibilities of determining the most optimal cutoff values of muscle strength, physical performance, and muscle mass measurements through outcome-based approaches. Nevertheless, ILAS was a longitudinal study, which may provide more in-depth information in the future. Third, this study recruited individuals with relatively better health by excluding people with poor communication ability, inability to walk 6 meters in a reasonable time, and institutionalized elders from the recruitment. Therefore, all measurements regarding sarcopenia may be better than the general elderly population. Fourth, the study individuals were relatively younger, especially in women, than in other sarcopenia studies, which may limit the extrapolation of the results to the oldest-old population. In conclusion, different
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