Abstract
Aim
Sarcopenia is recognized with its adverse functional outcomes. We aimed to report the prevalence of European Working Group on Sarcopenia in Older People (EWGSOP) defined sarcopenia and its individual components in community dwelling outpatient older adults and study the correlations of EWGSOP defined sarcopenia, muscle mass, muscle strength, and physical performance with functional status.
Material and methods
The subjects were prospectively recruited from the geriatrics outpatient clinics of our university hospital. Body composition was assessed with bioimpedance analysis. Muscle strength was assessed by measurement of hand grip strength with hydraulic hand dynamometer, physical performance was assessed by 4 meter usual gait speed (UGS). Impaired muscle function was defined as presence of low muscle strength and or slow gait speed. As a measure of functionality, modified version of Katz activities of daily living (ADL) and Lawton instrumental activities of daily living (IADL) were assessed.
Results
A total of 242 community dwelling outpatients with mean age of 79.4 ± 5.7 years were enrolled. 31.8% were male. Prevalence of low muscle mass was 2.1% and impaired muscle function was 71.1%. Prevalence of EWGSOP defined sarcopenia was 0.8% (1.3% in men and 0.6% in women). Most correlated parameter with ADL and IADL was the usual gait speed (r = 0.49, r = 0.63; p < .001, respectively). Grip strength was also correlated with ADL and IADL (r = 0.28, r = 0.35; p < .001). However, the skeletal muscle mass index (SMMI) was not correlated with ADL, IADL (p = .22, p = .22, respectively). In regression analysis, both ADL score and IADL scores were most related to UGS (beta = 0.5 and 0.6, p < .001), age (beta = –0.25 and –0.2, p < .001) and then sarcopenia (beta = 0.1 and 0.1, p < .05) but was not related to hand grip strength or SMMI.
Conclusions
The prevalence of sarcopenia was low as 0.8% albeit the presence of impaired muscle function in more than 2/3 of the cases. We have found that EWGSOP defined sarcopenia had association with ADL and IADL. The gait speed component of sarcopenia had the strongest associations with functional measures but SMMI component did not have any relation. We suggest that although low muscle mass may be a parameter related to worse functionality, it should not be regarded prerequisite for presence of sarcopenia analogous to low bone mineral density for osteoporosis.
1. Introduction
Sarcopenia has first been described as the age-related decrease in muscle mass [Citation1]. It is recognized for its association with mobility disorders, increased risk of falls and fractures, impaired ability to perform activities of daily living (ADL), disabilities, loss of independence, and increased risk of death [Citation2]. However, the studies analyzing the impact of reduced muscle mass and/or muscle function (i.e. the muscle strength and physical performance) on functionality have generally reported significant association of functionality with muscle function while weaker or no association with muscle mass [Citation3]. Hence, over the last decade, the sarcopenia definition has evolved to include decreases in muscle function [Citation4]. Albeit, it remains unclear whether a decline in physical performance results from the loss of muscle mass and/or the functional quality of muscle [Citation2]. The age-associated loss of strength is not completely explained by the loss of muscle mass [Citation5] which may in turn differentiate the impact of loss of muscle mass and muscle function on adverse outcomes related to sarcopenia.
The prevalence of sarcopenia varies widely between studies and is difficult to compare because the methods used and the selected diagnostic criteria often differ [Citation6]. The European Working Group on Sarcopenia in Older People (EWGSOP) has developed a practical definition and consensus diagnostic criteria for sarcopenia in 2010 [Citation7]. The universal use of such an accepted sarcopenia definition would aid to correct the confusion in its prevalence. They proposed cutoff points depending upon the measurement technique chosen and on the availability of reference studies and recommended use of normative data of the particular study population where available [Citation7]. Accordingly, we recently reported Turkish reference populations to define muscle mass and muscle function cutoff points [Citation8]. Here, we aimed to report prevalence of sarcopenia and its individual components in community-dwelling older adults admitting to geriatric outpatient clinic. We also aimed to study the correlations of EWGSOP-defined sarcopenia and its components with functional status.
2. Material and methods
2.1. Population and setting
Community-dwelling older outpatients ≥ 65 years old were prospectively recruited from the geriatrics outpatient clinics of our university hospital. This outpatient clinic accepts all patients ≥60 years regardless of their illness, co-morbidities and their living settings.However; because the clinic is located far from the nursing homes, older patients from institutions rarely present and were not included. Subjects were recruited between December 2012 and April 2014.In this period, among 1203 assessed outpatients, 446 patients could not be reached by the study staff; 324 patients did not give consent; and 27 had acute problems and excluded from the study. 242 subjects had full assessment of functionality composing the present study population.
2.2. Measurements
Height and weight were measured using a regularly standardized stadiometer with subjects wearing light clothing and no shoes. Body weight and height were measured to the nearest 0.1 kg and 0.1 cm. Body mass index (BMI), calculated as weight (kilograms) divided by height (meters)2.
Body composition was assessed with bioimpedance analysis (BIA) via Tanita BC 532 model body analysis monitor. Assessment of body composition by using BIA has been validated by underwater weighing and dual energy X-ray absorptiometry (DXA) and BIA is one of the suggested tools to assess muscle mass in primary care setting [Citation9]. In addition, Tanita BC 532 device that was used has been reported accurate in the estimation of body composition, especially FFM, against the dual energy X-ray absorptiometry and magnetic resonance imaging [Citation10]. Fat free mass was measured by BIA and skeletal muscle mass (SMM) was calculated by the following equation: SMM (kg) = 0.566*FFM (fat free mass). The formula (SMM (kg) = 0.566*FFM was validated on individual and group data reported in the literature [Citation11]. Consequently, skeletal muscle mass index (SMMI) was calculated by skeletal muscle mass (kg)/[height (m)2]. Muscle mass threshold for skeletal muscle mass indexes were considered according to our national data i.e. 9.2 kg/m2 and 7.4 kg/m2 in males and females, respectively [Citation8].
Muscle strength was assessed by measurement of hand grip strength with the Jamar hydraulic hand dynamometer using a validated protocol [Citation12]. Grip strength was measured while sitting, elbow being in 90° flexion and wrist in neutral position. Participants applied the maximum grip strength for three trials with left and right hands. At least 30 s resting intervals were allowed between measurements. Maximum measured grip strength was regarded as the grip strength. Usual gait speed was analyzed by 4 meters usual gait speed test at usual pace and <0.8 m/s was regarded as slow gait speed.The cutoffs for hand grip strength were regarded according to our national data i.e. 32 kg and 22 kg in males and females, respectively [Citation8].
As a measure of functionality, modified Katz-activities of daily living and Lawton instrumental ADL were assessed. The components of Activities of Daily-Living(ADL) were; feeding, continence, transferring, toileting, dressing, bathing [Citation13] and Instrumental Activities of Daily-Living (IADL) were; using the telephone, shopping, preparing food, housekeeping, doing laundry, using transportation, handling medications, handling finances [Citation14]. The scores were modified to document intermediate functional scores (i.e. independent, partially dependent and dependent) i.e. for each item, the subject was asked whether they did the activity without help (3 points), with some help (2 points), or they did not do the activity at all or they were completely dependent on someone to do the activity for them (1 point) [Citation15]. Accordingly, the possible range of scores for ADL was 6 to 18, with 18 indicating complete independence in all six ADL items. The possible range of scores for IADL was 8 to 24, with 24 indicating complete independence in all eight IADL items. All of the measurements were made by the single qualified geriatric physiotherapist.
This study was conducted according to the guidelines laid down in the Declaration of Helsinki. Informed consent was obtained from all participants and/or their related conservators. Approval for the study was obtained from the Istanbul University Istanbul Medical Faculty Ethical Committee.
2.3. Statistical analysis
The variables were investigated using visual (histograms and probability plots) and analytical methods to determine whether they are normally distributed. Numerical variables were given as mean ± standard deviation for normally distributed variables and as median for skew-distributed continuous variables. Descriptive statistics were generated for all study variables including relative frequencies for categorical (qualitative) variables. Two groups were compared with independent sample t-test or Mann Whitney U test when necessary. Correlations between numerical parameters were analyzed with Pearson or Spearman correlation test. The variables detected as significant in univariate analyses were analyzed with linear regression analyses. The multicollinearity among the possible regression analyses independent variables were checked with Pearson, Spearman or Kendall’s tau-b correlation analyses. p < .05 was considered statistically significant. The statistical analysis was performed with the statistical package SPSS Version 21.0 for Windows (SPSS Inc, Chicago, IL, USA).
3. Results
Study population was composed of 77 (31.8%) male and 165 (68.2%) female with a mean age of 79.4 ± 5.7 years. By using the Turkish normative reference population derived cutoff values, there were 2.1% patients with decreased muscle mass, 50% patients with decreased grip strength. About half of the participants had slow usual gait speed. About 1/3 of the patients had both decreased muscle mass and grip strength. There were 71.1% patients accounting to more than 2/3 of the cases that had impaired muscle function (either decreased grip strength or slow usual gait speed). About 15–20% of the patients had only one impairment in muscle function (either low grip strength or slow UGS). According to EWGSOP criterion, sarcopenia prevalence was 0.8%. The details of the data are outlined in .
Table 1. The study parameters across the genders (n = 242).
Sarcopenia and its components were analyzed in their relation to ADL and IADL. The most correlated parameter with ADL and IADL was the usual gait speed (r = 0.54, r = 0.68; p < .001, respectively). Grip strength was correlated with ADL and IADL (r = 0.28, r = 0.35; p < .001). However, the skeletal muscle mass index was not correlated with ADL, IADL or gait speed (p = .22, p = .22, p = .30, respectively) but it was correlated with grip strength (r = 0.22; p < .001). Usual gait speed and grip strength were also correlated in between (r = 0.56, p < .001). When the patients with and without sarcopenia were compared, sarcopenic participants had significantly lower HGS (18 kg vs 25.7 kg; p = .046). The ADL scores (16.6 vs 18) and IADL (20.2 vs 22) scores and UGS (0.84 vs 0.56 m/s) were lower in the sarcopenic subjects but this was not statistically significant (p > 0.05). ADL (r = –0.45), IADL (r = –0.44), grip strength (r = –0.25) and gait speed (r = –0.58) were correlated with age (p < .001 for each) while SSMI was not (p = .11). Regression analyses were performed for ADL and IADL. In ADL regression analysis, ADL was the dependent variable and SMMI, HGS, UGS, sarcopenia and age were the independent variables.In this analysis, ADL score was most related to UGS (beta = 0.5, p < .001), age (beta = –0.25, p < .001) and then sarcopenia (beta = 0.1, p = .01) but was not related to grip strength (p = .7) or SMMI (p = .16) (). In IADL regression analysis, IADL was the dependent variable and SMMI, HGS, UGS, sarcopenia and age were the independent variables. This analysis also revealed that IADL score was most related to UGS (beta = 0.6, p < .001), age (beta = –0.2, p < .001), and then sarcopenia (beta = 0.1, p = .04), but was not related to HGS (p = .4) or SMMI (p = .13) ().
Table 2. Regression analyses for ADL.
Table 3. Regression analyses for IADL.
4. Discussion
Our study documented the first EWGSOP criterion defined sarcopenia prevalence in a group of community-dwelling Turkish older adult population. The most prevalent sarcopenia component was slow gait speed in slightly more than half of the patients (55.8%) followed by low grip strength in half of the patients. More than 2/3 of the patients (71.1%) had impaired at least one muscle function. However, in case of decreased muscle mass, prevalence was quite low, as 2.1%. This figure reflected as also a quite low prevalence of sarcopenia: 0.8%, albeit the presence of impaired muscle function in most of the cases.
There are limited number of studies reporting EWGSOP defined sarcopenia prevalence in the community-dwelling older adults [Citation16–21]. The prevalence of EWGSOP-defined sarcopenia was reported as low as 0.2% using the national cutoffs and DXA in the Finnish population [Citation17] and as much as 22% in the Japanese population by Japanese cutoffs and BIA [Citation18]. Our reported prevalence of 0.8% sarcopenia is, hence, in line with the literature, close to the lower end. Our study population was composed of 65–99 years of age community dwelling elderly outpatients but they were mostly functional elderly. More than half were completely independent in their ADL and IADL. Maybe the presence of relatively low prevalence of sarcopenia could be in part due to this high functional profile. Both the low sarcopenia prevalence Finnish study [Citation17] and high sarcopenia prevalence Japanese study [Citation18] were in the community dwelling independently living older adults. The Finnish study [Citation17] included older women between 70 and 80 years of age that had experienced at least one fall in the previous year which may be represent a more vulnerable population but documented the lowest sarcopenia prevalence. On the other hand, Japanese study [Citation18] included heathy older adults excluding patients with even risk of falls but documented the highest prevalence. Hence, these data provide insight that the prevalence of sarcopenia differs significantly in between the populations. For comparison, the studies reporting EWGSOP defined sarcopenia in community dwelling older adults that had been performed with BIA from different nations are outlined . Our prevalence of sarcopenia again stands at the lower end of the spectrum. The next step may be the investigation of the factors responsible from this significant difference i.e. intrinsic factors e.g. the ethnic differences and the external factors such as nutritional components and physical activity comparatively in these countries.
Table 4. Studies performed by bioimpedance analyses that document prevalence of sarcopenia by EWGSOP Definition in community-dwelling elderly.
The prevalence of EWGSOP defined sarcopenia has been reported from a nursing home in Turkey recently [Citation24]. This study similarly used BIA to assess skeletal muscle mass but did not use the national cutoffs. In a total of 141 subjects over 65 years of age sarcopenia was found in 29% of the participants.The higher prevalence in this study seems to due to the different setting that include more fragile and functionally dependent older adults that require nursing. This nursing home study also documented that sarcopenic subjects had low scores for ADL but they did not analyzed association of ADL with components of sarcopenia.
In this study, as a significant output, we analyzed not only sarcopenia but also its individual components as well, in their relation to ADL and IADL. The most correlated parameter with ADL and IADL was the usual gait speed -having a moderate correlation followed by HGS -having a weak correlation. The SMMI was not correlated with ADL or IADL. Sarcopenic patients had lower ADL (16.6 vs 18) and IADL (20.2 vs 22) scores but did not reach statistical significance.On the other hand, in regression analyses, ADL score was most related to UGS (beta = 0.5, p < .001) and then sarcopenia (beta = 0.1, p = .01) but was not related to HGS or SMMI (). IADL score was also most related to UGS (beta = 0.6, p < .001), then sarcopenia (beta = 0.1, p = .04) and was not related to HGS or SMMI (). These results suggest that the gait speed component of sarcopenia had the strongest associations with ADL and IADL. EWGSOP-defined sarcopenia also had association with ADL and IADL but SMMI component as itself did not have association. Some studies failed to show an association of low muscle mass (LMM) (low SMMI) with functional status but some did. Another reason for this could be the use of different adjustment methods for adjusting the muscle mass. In our previous study among Turkish male nursing home residents, no significant association between low SMMI and functional status was found using the definition of LMM when muscle mass was adjusted by body surface area (-muscle mass weight (kg) divided by body surface area) [Citation25]. However, in the same population, when muscle mass was adjusted by height2 (m2) (-muscle mass (kg) divided by/height2), ADL scores were significantly different between residents with low SMMI and normal SMMI in those aged ≥70 years with Turkish normative reference cutoff value [Citation26].
In our study, HGS also did not have any association with ADL and IADL in regression analyses. This may be due to the fact that lower extremity function that is better analyzed with UGS and has more effect in performing ADL and IADLs. In a similar study, Patino-Villada et al. examined the correlations between the functional outcomes and muscle mass, HGS and gait speed cross-sectionally and noted that subjects with low HGS and gait speed presented lower values in functional outcomes but subjects with low muscle mass did not [Citation19].
Sarcopenia is recognized with its adverse effects on functionality and hence present study questions the implementation of low muscle mass criterion as a prerequisite for sarcopenia diagnosis. In this study, the prevalence of EWSGOP defined sarcopenia was low because low muscle mass was low and had been a prerequisite for sarcopenia diagnosis. However, there was highly prevalent impaired muscle function. It is apparent that the definition of sarcopenia that limits its presence to co-existence of low muscle mass and muscle function may end with failure to evaluate and treat such patients with impaired muscle function that may potentially add to the cost and functional consequences of sarcopenia. Accordingly, an analogous consideration of sarcopenia likewise the osteoporosis can be suggested [Citation27]. Osteoporosis also increases with ageing in both genders and has multiple diverse etiologies likewise sarcopenia [Citation28,Citation29]. Osteoporosis is defined as a systemic skeletal disease not only characterized by low bone mass but also by micro-architectural deterioration of bone tissue, with a consequent increase in bone fragility and susceptibility to fracture [Citation30,Citation31]. This micro-architectural change may not display reduced bone mass but only reduced bone strength against a fracture and therefore osteoporosis can be defined by the presence of a fragility fracture even if bone mineral density measurement is not below –2.5. Otherwise, failure to evaluate and treat such patients adds to the cost and consequences of osteoporosis. Analogously, we suggest that given the fact that muscle strength rather than the muscle mass is independently associated with muscle performance [Citation32] and hand grip predicts future disability as long as 25 year before [Citation33,Citation34], the definition of sarcopenia that limits its identification to the presence of both low muscle mass and muscle function may end with failure to evaluate and treat such patients. This would add to the cost and consequences of sarcopenia. The muscle mass-sarcopenia relation should be regarded as a parameter very similar to bone mineral density-osteoporosis relation. So, we suggest that although low muscle mass may be a parameter related to worse functionality, it should not be regarded prerequisite for presence of sarcopenia just as the same as low bone mineral density for osteoporosis. Universally, any patient with fragility fracture (indicating the impaired bone strength) is considered to have osteoporosis even if he does not have low bone mineral density score. Likewise, it can be suggested that the patients that have been documented to have impaired muscle function may better be considered to have sarcopenia even if he does not have low muscle mass.
Some limitations should be considered in our study. First, this is a cross-sectional study therefore we cannot state a definitive cause-effect relationship. Secondly, we evaluated body composition by BIA. It relies on estimation of muscle mass rather than exact measurement. However, it is recommended to evaluate muscle mass in research and clinical settings by the EWGSOP consensus [Citation7].
In conclusion, we documented the first EWGSOP criterion defined sarcopenia prevalence in a group of community-dwelling Turkish older adults. The prevalence of sarcopenia was low as 0.8% albeit the presence of impaired muscle function in more than 2/3 of the cases. We have found that EWGSOP-defined sarcopenia had association with ADL and IADL. The gait speed component of sarcopenia had the strongest associations with functional measures but skeletal muscle mass index component did not have any relation. We suggest that although low muscle mass may be a parameter related to worse functionality, it should not be regarded prerequisite for presence of sarcopenia, an approach analogous to the low bone mineral density for osteoporosis.
Disclosure statement
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Related Research Data
References
- Rosenberg IH. Sarcopenia: origins and clinical relevance. J Nutr. 1997;127:990S–9901.
- Rolland Y, Czerwinski S, Abellan Van Kan G. Sarcopenia: its assessment, etiology, pathogenesis, consequences and future perspectives. J Nutr Health Aging. 2008;12:433–450.
- da Silva Alexandre T, de Oliveira Duarte YA, Ferreira Santos JL, et al. Sarcopenia according to the european working group on sarcopenia in older people (EWGSOP) versus Dynapenia as a risk factor for disability in the elderly. J Nutr Health Aging. 2014;18:547–553.
- Abellan van Kan G. Epidemiology and consequences of sarcopenia. J Nutr Health Aging. 2009;13:708–712.
- Clark B, Manini T. Functional consequences of sarcopenia and dynapenia in the elderly. Curr Opin Clin Nutr Metab Care. 2010;13:271–276.
- Bijlsma AY, Meskers CG, Ling CH, et al. Defining sarcopenia: the impact of different diagnostic criteria on the prevalence of sarcopenia in a large middle aged cohort. Age (Dordr). 2012;35:871–881.
- Cruz-Jentoft AJ, Baeyens JP, Bauer JM, European Working Group on Sarcopenia in Older People, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing. 2010;39:412–423.
- Bahat G, Tufan A, Tufan F, et al. Cut-off points to identify sarcopenia according to European Working Group on Sarcopenia in Older People (EWGSOP) definition. Clin Nutr. 2016;35:1557–1563.
- Yilmaz O, Bahat G. Suggestions for assessment of muscle mass in primary care setting. Aging Male. 2017;20:168–169.
- Wang JG, Zhang Y, Chen HE, et al. Comparison of two bioelectrical impedance analysis devices with dual energy X-ray absorptiometry and magnetic resonance imaging in the estimation of body composition. J Strength Cond Res. 2013;27:236–243.
- Deurenberg P, Pietrobelli A, Wang ZM, et al. Prediction of total body skeletal muscle mass from fat-free mass or intra-cellular water. Int J Body Compos Res. 2004;2:107–113.
- Fess EE. Grip strength. In: Casanova JS, editors. Clinical assessment recommendations. 2nd ed. Chicago: American Society of Hand Therapists; 1992. p. 41–45.
- Katz S, Ford AB, Moskowitz RW, et al. Studies of illness in the Aged. The index of ADL: a standardized measure of biological and psychosocial function. JAMA. 1963;185:914–919.
- Lawton MP, Brody EM. Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9:179–186.
- Cho C-Y, Alessi CA, Cho M, et al. The association between chronic illness and functional change among participants in Comprehensive Geriatric Assessment Program. J Am Geriatr Soc. 1998;46:677–682.
- Yoshida D, Suzuki T, Shimada H, et al. Using two different algorithms to determine the prevalence of sarcopenia. Geriatr Gerontol Int. 2014;14 Suppl 1:46–51.
- Patil R, Uusi-Rasi K, Pasanen M, et al. Sarcopenia and osteopenia among 70-80-year-old home-dwelling Finnish women:prevalence and association with functional performance. Osteoporos Int. 2013;24:787–796.
- Yamada M, Nishiguchi S, Fukutani N, et al. Prevalence of sarcopenia in community-dwelling Japanese older adults. J Am Med Dir Assoc. 2013;14:911–915.
- Patiño Villada FA, Arboleda Franco SA, de Paz Fernández JA. Sarcopenia in community-dwelling persons over 60 years of age from a northern spanish city: relationship between diagnostic criteria and association with the functional performance. Nutr Hosp. 2015;31:2154–2160.
- Hashemi R, Shafiee G, Motlagh AD, et al. Sarcopenia and its associated factors in Iranian older individuals: Results of SARIR study. Arch Gerontol Geriatr. 2016;66:18–22.
- Espinel-Bermúdez MC, Ramírez-García E, García-Peña C, et al. Prevalence of sarcopenia in community-dwelling chilean elders according to an adapted version of the European Working Group on Sarcopenia in Older People (EWGSOP) Criteria. J Frailty Aging. 2017;2:12–17.
- Volpato S, Bianchi L, Cherubini A, et al. Prevalence and clinical correlates of sarcopenia in community-dwelling older people: application of the EWGSOP definition and diagnostic algorithm. J Gerontol A Biol Sci Med Sci. 2014;69:438–446.
- Legrand D, Vaes B, Matheï C, et al. The prevalence of sarcopenia in very old individuals according to the European consensus definition: insights from the BELFRAIL study. Age Ageing. 2013;42:727–734.
- Yalcin A, Aras S, Atmis V, et al. Sarcopenia prevalence and factors associated with sarcopenia in older people living in a nursing home in Ankara Turkey. Geriatr Gerontol Int. 2016;16:903–910.
- Bahat G, Saka B, Tufan F, et al. Prevalence of sarcopenia and its association with functional and nutritional status among male residents in a nursing home in Turkey. Aging Male. 2010;13:211–214.
- Tufan A, Bahat G, Ozkaya H, et al. Low skeletal muscle mass index is associated with function and nutritional status in residents in a Turkish nursing home. Aging Male. 2016;19:182–186.
- Bijlsma AY, Meskers CG, Westendorp RG, et al. Chronology of age-related disease definitions: osteoporosis and sarcopenia. Ageing Res Rev. 2012;11:320–324.
- Liu M, Zhang Y, Cheng X, et al. The effect of age on the changes in bone mineral density and osteoporosis detection rates in Han Chinese men over the age of 50. Aging Male. 2014;17:166–173.
- Martín-Fernández M, Martínez E, Díaz-Curiel M, et al. Effects of PTH (1-84) on bone quality in a validated model of osteoporosis due to androgenic deprivation. Aging Male. 2014;17:42–50.
- Consensus Development Conference. Diagnosis, prophylaxis and treatment of osteoporosis. Am J Med.1993;94:646–650.
- Kanis JA. Diagnosis of osteoporosis and assessment of fracture risk. Lancet. 2002;359:1929–1936.
- Visser M, Newman AB, Nevitt MC, et al. Reexamining the sarcopenia hypothesis. Muscle mass versus muscle strength. Health, Aging, and Body Composition Study Research Group. Ann N Y Acad Sci. 2000;904:456–461.
- Giampaoli S, Ferrucci L, Cecchi F, et al. Hand-grip strength predicts incident disability in non-disabled older men. Age Ageing. 1999;28:283–288.
- Rantanen T, Masaki K, Foley D, et al. Grip strength changes over 27 yr in Japanese-American men. J Appl Physiol. 1998;85:2047–2053.