Aging Clin Exp Res (2014) 26:137–146 DOI 10.1007/s40520-013-0132-8
ORIGINAL ARTICLE
Prevalence of sarcopenia among healthy ambulatory subjects: the sarcopenia begins from 45 years Patrick Cherin • Elena Voronska • Nadia Fraoucene Christophe de Jaeger
•
Received: 18 March 2013 / Accepted: 9 August 2013 / Published online: 16 October 2013 Ó Springer International Publishing Switzerland 2013
Abstract Background and aims Sarcopenia has been indicated as a reliable marker of frailty and poor prognosis among the oldest individuals. There are only few data on sarcopenia in healthy general population. We evaluated the prevalence of sarcopenia and its association with functional and clinical status in a population of healthy ambulatory subjects over 45 years living at home, in Paris (France). Methods This study was conducted selecting all ambulatory participants (n = 1,445) aged 45 years and older from October 2008 to September 2011, consulting in the Institute of Physiology (Institut de Jaeger) from Paris (France) for a functional and muscular evaluation, and did not have limitations to moderate physical exercise. All were healthy people. All subjects performed a medical examination, associated with evaluation of muscle mass (body composition assessment using dual-energy X-ray absorptiometry) and of muscle function (by hand grip strength). Diagnosis of sarcopenia required the documentation of low muscle mass with low muscle strength according to the current international consensus definition of sarcopenia. Results From 1,421 participants (553 males and 868 females) definitively enrolled, 221 subjects (135 females and 86 males) (15.5 %) were identified as sarcopenic. Results from multivariate logistic regression models showed that sarcopenia was inversely associated with BMI
P. Cherin (&) Service de Me´decine Interne I, CHU Pitie´-Salpe´trie`re, 47 bd de l’hoˆpital, 75013 Paris, France e-mail: [email protected] E. Voronska N. Fraoucene C. de Jaeger Institut de Jaeger Center, 4 rue de Galliena, 75116 Paris, France
with those participants with BMI higher than 22 kg/m2 showing a lower risk of sarcopenia relative to those with BMI less than 21 kg/m2 (OR 0.72; 95 % CI 0.60–0.91). Similarly, probability of sarcopenia was lower among subjects involved in leisure physical activities for 3 h or more per week (OR 0.45; 95 % CI 0.24–0.93). According to the category of age [45–54; 55–64; 65–74; 75–84 and 85 years or more], the prevalence of sarcopenia in women increase from 9.1; 12.7; 14.5; 19.4; to 33.3 %, respectively. For the men, the percentage of sarcopenia increase with aging from 8.6; 15.6; 13.6; 63.8 to 45.5 %, respectively. Conclusions The present study suggests that among healthy ambulatory subjects over 45 years living at home, sarcopenia is frequent, even to the youngest subjects of the studied population, taking place from 9 % from 45 years, until 64.3 % for the subjects over 85 years. Our findings support the hypothesis that muscle mass and function are associated with BMI and physical activity, whatever the age of the subject. Keywords Sarcopenia Obesity Physical activity DXA Hand grip
Introduction Human muscle undergoes constant changes. The progressive decreased skeletal muscle mass with human aging is named sarcopenia, since the first description in 1989 by Irwin Rosenberg to describe the age-related decrease of muscle mass (Greek ‘‘sarx’’ = flesh ? ‘‘penia’’ = loss) [1, 2]. Sarcopenia has since been defined as the loss of skeletal muscle mass and strength that occurs with advancing age [3]. Since this time, a lot of scientific works were published to define the functional consequences and biologic
123
138
mechanisms of sarcopenia [4]. Sarcopenia, directly and causally linked to both muscle weakness and physical disability, has considerable societal consequences and is responsible of frailty, disability, and health care [4]. The reasons for these changes are complex and multifactorial, including physical activity, nutritional status (protein intake, energy intake, and vitamin D status), denervation of motor units, hormonal changes (especially reduction of serum testosterone and growth hormone), insulin resistance, genetic heritability, changes in circulating pro-inflammatory cytokines, and a net conversion of fast type II muscle fibers into slow type I fibers with resulting loss in muscle power necessary for activities of daily living [4, 5]. In addition, lipids are deposited in the muscle, but these changes do not usually lead to a loss in body weight. Sarcopenia may lead to frailty, but not all patients with sarcopenia are frail. In essence, sarcopenia is about twice as common as frailty [5, 6]. Many different methodologies have been used over the last 20 years, and new techniques are still being introduced. Depending on the population studied, definition and techniques used, sarcopenia is estimated to occur in 5–45 % of older adults [7, 8]. On average, it is estimated that 5–13 % of elderly people aged 60–70 years are affected by sarcopenia, and the numbers increase to 11–50 % for those aged 80 or above. The broadness in the range of sarcopenia prevalence is partly due to the heterogenecity of study populations, but also due to the different techniques used until now to assess muscle mass. Dual-energy X-ray absorptiometry (DEXA) is currently considered the gold standard [9]. Other methods used to measure muscle mass include bioelectrical impedance, computed tomography, magnetic resonance imaging, urinary excretion of creatinine, anthropometric assessments, and neutron activation assessments [6]. Depending on the actual technique used in different studies and on the cutoff values chosen, the prevalence of muscle mass may vary considerably. Now, however, the measurement of muscle mass is insufficient to define sarcopenia. It must be associated with evaluation of muscle function. Physical performance can be analyzed using simple and easy-to-do tests such as the short physical performance battery test [10], usual gait speed [11], the timed get-up-and-go test [12], or the stair climb power test [13]. But many institutions use handgrip strength as a standard measure for assessing muscle strength. At present, there are very few data from representative large samples on the epidemiology of sarcopenia in outcome subjects using new criteria [14]. According to current international consensus definition of sarcopenia [15, 16], we conducted an observational cross-sectional study to evaluate the prevalence of sarcopenia and its association
123
Aging Clin Exp Res (2014) 26:137–146
with clinical and functional domains in a large population of outcome patients living in Paris (France). We used for the diagnosis of sarcopenia, an objectively measured low muscle mass (body composition assessment using dualenergy X-ray absorptiometry) associated with low muscle function (evaluated by hand grip strength).
Methods Study population This study was prospectively conducted between October 2008 and September 2011 in the Institute of Physiology (Institut de Jaeger) from Paris (France) in ambulatory subjects, living at home independently, who voluntarily participated in a functional and muscular evaluation, and did not have limitations to moderate physical exercise. All were healthy people. The written informed consent was elaborated and used for each included patient. Patients were ambulatories, with no restriction for physical performance. They were included in the study group after determining eligibility according to the inclusion criteria and medical screening by a physician. These patients had no history of severe disease, had no contraindications to exercise, and understood the procedures of the DEX study. More specifically, to avoid the possible interference of neurological impairments in the measure of muscle function, participants with a diagnosis of stroke, severe Parkinson’s disease, peripheral neuropathy, and significant cognitive impairment (Mini Mental State Examination Score B21) were excluded, as well as patient with recent fractures (during the preceding 12 months), important alcohol consume, or marked decline in the basic activities of daily living. All participants without exclusion criteria consulting during the time period, aged 45 years and older were invited to be included in the study (n = 1,508). All subjects performed a medical examination, cardiac exploration associated with evaluation of muscle mass (body composition assessment using dual-energy X-ray absorptiometry) and of muscle function (by hand grip strength). Data collection Ambulatory subjects come in the Physiologic Institute de Jaeger (Paris) for medical check-up. All the participants enrolled in the present study were evaluated using standardized procedures, by the same trained assessors. The baseline examination was performed in the center by a trained geriatric physician. A physical examination and comorbid conditions were recorded using standardized health status questionnaire [hypertension, diabetes,
Aging Clin Exp Res (2014) 26:137–146
coronary heart disease, cerebrovascular disease, dementia, Parkinson disease, chronic bronchitis, myopathy, cancer, depression, other chronic disease, osteoarthritis, pain, alcohol intake, drugs and smoking (previous or current)]. Each leisure physical activities (walking, swimming, gymnastics, cycling, gardening or other) were noted, with their frequency, and duration. Subjects were considered physically active if they regularly practiced at least one physical activity for 1 h or more per day, at least 3 days per week. Covariates Body weight was measured while wearing light clothes using a calibrated medical balance. Body height was measured using a standard stadiometer. Body weight and height were measured to the nearest 0.1 kg and 0.1 cm, respectively. Body mass index (BMI) was defined as weight (kg) divided by the square of height (m). Assessment of sarcopenia For the present study, we adopted the international consensus definition of sarcopenia with the European Working Group on Sarcopenia in Older People (EWGSOP) criteria [16]. According to these new recommendations, we use for the diagnosis of sarcopenia, an objectively measured low muscle mass (body composition assessment using dualenergy X-ray absorptiometry) associated with low muscle function (evaluated by hand grip strength). Anthropometric measures and assessment techniques of muscle mass Anthropometric measurements (weight and height) were performed using standardized techniques [17]. For our study, muscle mass was evaluated by dual-energy X-ray absorptiometry (DXA, Lunar Prodigy Advance, GE Lunar, Madison, WI, USA), which is the preferred method for research and clinical use [16]. DXA measurements were performed by a trained technician, and the DXA machine was regularly calibrated. According to European consensus, sarcopenia was based for our work, on appendicular skeletal muscular mass (ASM) measures [18]. ASM corresponds to the sum of the 2 upper and lower limb muscular masses in kilogram. For the purpose of this study, skeletal muscle mass (ASM) in kilograms relative to height squared in meters was calculated as an index of relative skeletal muscle mass (SMI in kg/m2) (ASM/height2) as suggested by Baumgartner et al. [7]. The cutoff to define sarcopenic patients was based on previous work (low muscle mass was defined as the
139
skeletal muscle index of 2 SDs or more below the normal sex-specific means for young persons [7, 19–22]. Patients were classified as sarcopenic if their relative skeletal muscle mass was 2 SDs below the mean of a reference population from the Rosetta Study, which included 229 healthy Americans aged 18–40 years [23]. The cutoff correspond to 5.45 kg/m2 in women and 7.26 kg/m2 in men [7, 24, 25]. Muscle strength measure—hand grip Muscle strength was assessed by hand grip strength, which was measured using a dynamometer (North Coast Hydraulic Hand Dynamometer; North Coast Medical Inc, Morgan Hill, CA, USA). Isometric grip strength was measured three times in each hand, alternating between right and left hands. The participants were verbally encouraged to perform to their maximum, and the best performance of the strongest hand from three trials was recorded. Using the cutoff points indicated in the EWGSOP consensus paper [16], low muscle strength was classified as hand grip less than 30 and 20 kg in men and women, respectively. These cut-points were similar to that obtained among 1,030 subjects (469 men and 561 women, age range from 20 to 102 years) described in the InCHIANTI study population [19]. Statistical analysis Subjects with sarcopenia were identified using the definition proposed by the EWGSOP [16]. Data were analyzed to obtain descriptive statistics. Continuous variables are presented as mean and standard deviation. Several statistical analysis were used to evaluate differences in sociodemographic, functional, and clinical characteristics between subjects with sarcopenia and subjects without sarcopenia. Quantitative parameters with normal distribution were tested by one-way analysis of variance. If abnormal distribution was present, a nonparametric test (Kruskal–Wallis rank test) was used. Categorical variables were analyzed by the c2 test. A statistical significance was defined for p \ 0.05 level. The relationship between sarcopenia and clinical and functional variables was estimated by multiple logistic regression models. Sarcopenia identified by the EWGSOP definition was included as dependent variable in such models. Age, gender, diagnosis of dementia, Parkinson’s disease, cerebrovascular disease, hypertension, diabetes, chronic obstructive pulmonary disease, cancer, osteoarthritis, physical activity, and BMI were considered as factors potentially associated with sarcopenia and were considered as covariates in the logistic model.
123
140
Aging Clin Exp Res (2014) 26:137–146
Results A total of 1,508 subjects followed in the Institute were invited to take part to the study. Sixty-three subjects declined for personal reasons. 1,445 subjects aged 45 years and older initially have benefited of a physical evaluation, including evaluation of muscle mass (body composition assessment using dual-energy X-ray absorptiometry) and of muscle function (by hand grip strength). Twenty-three participants (1.6 %) were excluded because of incomplete body composition or muscle information (weight, height, grip test) (n = 14), informed consent not obtained (n = 4), severe cognitive involvement (n = 2), congestive cardiac failure (n = 2), acute flu (n = 1). This selection resulted in a final sample of 1,421 participants (553 males and 868 females) who were definitively enrolled. Mean age of study participants was 63.1 (standard deviation 10.2) years, and the mean BMI was 24.5 ± 4.0 kg/m2. The descriptive characteristics of the 1,421 participants are summarized in Table 1. 869 subjects (61.1 %) were women (mean age 62.7 ± 10.2 years, mean BMI 23.8 ± 4.2 kg/m2) and 552 were men (mean age 63.6 ± 10.1 years, mean BMI 25.6 ± 3.3 kg/m2). The mean SMI (ASM/height2) was 5.8 ± 0.7 kg/m2 for the 869 women and 7.7 ± 1.0 kg/m2 for the 552 men. Using the EWGSOP-suggested conceptual stages of sarcopenia, subjects with only reduced muscle mass were defined as pre-sarcopenic, and subjects with associated reduced muscle mass and low muscle strength (hand grip) were defined as sarcopenic [16]. Forty two subjects (25 males, 17 females) were considered as pre-sarcopenic, defined by reduced muscle mass on DXA and normal muscle strength with hand grip dynamometer. Table 1 Descriptive characteristics of study participants, n = 1,421 Characteristics
Mean (SD)
Range
Age (years)
63.1 (10.2)
45.1–83.0
Weight (kg)
68.0 (13.9)
44.5–116.8
Height (cm)
159.8 (5.8)
142.0–177.8
BMI (kg/m2)
24.5 (4.0)
18.6–45.1
Total body fat (%)
39.2 (7.4)
22.5–55.8
Total body fat mass (kg)
26.7 (8.6)
4.9–52.9
Total body lean mass (kg)
41.3 (5.8)
18.9–79.0
ASM (kg)
22.0 (4.2)
9.6–27.9
7.4 (0.9)
4.0–10.9
33.4 (8.8)
6.0–62.0
Body composition
SMI (ASM/height2) (kg/m2) Functional performance Mean dominant hand grip strength (kg)
123
A total of 221 subjects (135 females and 86 males) (15.5 %) were identified as affected by sarcopenia. Forty two subjects (25 males, 17 females) were considered as pre-sarcopenic, defined by reduced muscle mass on DXA and normal muscle strength with hand grip dynamometer. The mean age of these pre-sarcopenic subjects was 64.1 ± 8.7 years. The BMI was 22.4 ± 3.0 and the mean ASM was 14.8 ± 2.2 kg, with a mean dominant hand grip strength evaluated at 32.7 ± 2.1 kg. Only 28.8 % of these pre-sarcopenic population declared at least 3 h per week of leisure physically activities. The characteristics of study participants according to the presence of sarcopenia are summarized in Tables 2 and 3. The percentage of sarcopenia in our overall population of outcome subjects over 45 years old was similar between men and women (15.6 vs 15.5 %, respectively), but there are significant differences according to the categories of age. Compared with subjects without sarcopenia, those diagnosed with sarcopenia showed lower BMI (mean BMI 21.7 vs 25.1 kg/m2, p = 0.03, respectively). Subjects with sarcopenia showed a statistically significant lower skeletal muscle index compared with participants without sarcopenia (5.0 vs 7.1 kg/m2, p \ 0.05, respectively). Similarly, sarcopenic subjects had significantly lower muscle strength compared with non-sarcopenic (24.1 vs 36.3 kg, p \ 0.05, respectively). Also, relative to non-sarcopenic subjects, those with sarcopenia were less likely to be involved in leisure physically activities (C3 h/week) (42.5 vs 70.6 %, p = 0.03, respectively). Multivariate logistic regression models showed that the mean number of diseases, the frequency of Parkinson’s disease, dementia, cerebrovascular diseases, chronic obstructive pulmonary disease, cancer, osteoarthritis and number of medications were similar between sarcopenic and non-sarcopenic subjects. After adjusting for potential confounders, sarcopenia was inversely associated with BMI with those participants with BMI higher than 22 kg/ m2 showing a lower risk of sarcopenia relative to those with BMI less than 21 kg/m2 (OR 0.72; 95 % CI 0.60–0.91). Similarly, probability of sarcopenia was lower among subjects involved in leisure physical activities for 3 h or more per week (OR 0.45; 95 % CI 0.24–0.93). The mean age of sarcopenic men was significantly higher than in non-sarcopenic participants (69.3 ± 11.3 vs 62.4 ± 9.5 years, p \ 0.05). The mean BMI was lower in sarcopenic male subjects (23.0 vs 26.2 kg/m2, p \ 0.05). The mean SMI (ASM/height2) was 6.73 ± 0.36 kg/m2 in sarcopenic subjects versus 8.27 ± 0.67 kg/m2 in non-sarcopenic males (p \ 0.05). In sarcopenic women, the difference between the mean age of sarcopenic and non-sarcopenic subjects was non significant (65.3 ± 10.0 vs 62.3 ± 10.1 years, respectively, p [ 0.05). Like in male, the mean BMI was
Aging Clin Exp Res (2014) 26:137–146 Table 2 Characteristics of study participants according to the presence of sarcopenia
141
Characteristics [mean (SD)] N
Sarcopenia
No sarcopenia
221
1,158a
p
F/M
135/86
716/442
NS
Age (years)
66.9 (10.7)
62.3 (9.9)
0.05
Weight (kg)
68.0 (13.9)
69.6 (13.7)
NS
Height (cm)
159.8 (5.8)
165 (9.0)
NS
BMI (kg/m2)
21.7 (2.7)
25.1 (4.0)
0.03
Leisure physically activities (C3 h/week) (%)
94 (42.5 %)
818 (70.6 %)
0.03
Body composition
a
Pre-sarcopenic subjects were excluded
Table 3 Main co-morbidities of study participants according to the presence of sarcopenia
a
Pre-sarcopenic subjects were excluded
ASM (kg)
14.0 (1.8)
19.9 (4.8)
0.01
SMI (ASM/height2) (kg/m2)
5.0 (0.8)
7.1 (1.1)
0.01
24.1 (5.7)
36.3 (9.1)
0.01
Functional performance Mean dominant hand grip strength (kg)
Medical history
Sarcopenia
No sarcopenia
p
N
221
1,158a
F/M
135/86
716/442
Current smoker (%)
28.1 %
28.9 %
NS
Mild Parkinson (%)
2.1 %
1.9 %
NS
Mild cognitive impairment (%)
1.4 %
1.2 %
NS
Cerebrovascular diseases (%)
0.9 %
0.7 %
NS
Chronic obstructive pulmonary disease (%)
1.2 %
1.3 %
NS
Cancer (%)
2.1 %
2.2 %
NS
Osteoarthritis (%)
18.8 %
16.9 %
NS
Mean number of medications
2.3
2.1
NS
NS
Statins (%)
13.9 %
14.6 %
NS
Neuroleptic, anti-depressive and CNS drugs (%)
9.1 %
8.6 %
NS
Other potential myotoxic drugs
0.4 %
0.5 %
NS
significantly lower in sarcopenic women subjects (20.9 vs 24.4 kg/m2, p \ 0.05). The mean SMI was 5.14 ± 0.33 kg/m2 in sarcopenic subjects versus 6.39 ± 0.69 kg/m2 in non-sarcopenic females (p \ 0.05). The main characteristics of study participants according to the age and the presence of sarcopenia are given in Table 4. According to the category of age, the prevalence of sarcopenia was 9 % in the population between 45 and 54 years, 13.5 % in the categories of 55–64 years, 16.5 % for the 65–74 years old subjects, 30.9 % for the population age between 75 and 84 years, and 64.3 % for the patients over 85 years. Whatever the sex, the SMI gradually decreases with the advance in age. Sarcopenia is predominant in women between 45 and 74 years old, then sarcopenia become prevalent in men (Table 4). In our population, the prevalence of sarcopenia in women, according to the age bracket [45–54; 55–64; 65–74; 75–84 and 85 years or more] increase of 9.1; 12.7; 14.5; 19.4; and 33.3 %, respectively. For the men, the
percentage of sarcopenia increase with aging from 8.6; 15.6; 13.6; 63.8 and 45.5 %, respectively.
Discussion Sarcopenia is henceforth a major problem of public health. Depending on the population studied and definition used, sarcopenia is estimated to occur in 5–45 % of older adults [2, 7, 8, 19, 26–30]. Low levels of muscle mass have been linked with poor health outcomes that include functional impairments [31], severe physical disability [22], association with metabolic problems such as insulin resistance, type 2 diabetes, obesity [32–35] and mortality [36, 37]. In the elderly, sarcopenia is frequent and may lead to frailty [5]. However, the prevalence of sarcopenia in young ambulatory subjects, using the new criteria was not reported. In our study, sarcopenia affected the subjects from 45 years, despite daily activities.
123
142 Table 4 Characteristics of study participants according to the age and the presence of sarcopenia
Aging Clin Exp Res (2014) 26:137–146
Characteristic (mean)
Sarcopenia (mean ± SD)
No sarcopeniaa (mean ± SD)
p
Age 45–54 years old N
28
284
F/M (%)
19 (66 %)/9
189 (66.5 %)/95
Age (years)
50.1 ± 3.0
50.3 ± 2.8
NS
BMI (kg/m2)
21.1 ± 2.8
24.5 ± 3.1
0.05
SMI (ASM/height2) (kg/m2)
5.13 ± 0.4
7.2 ± 0.5
0.01
Age 55–64 years old N
65
417
F/M (%)
44 (67.7 %)/21
303 (72.7 %)/114
59.3 ± 2.7
59.6 ± 2.5
Age (years) 2
NS
BMI (kg/m )
21.4 ± 2.4
24.9 ± 2.5
0.05
SMI (ASM/height2) (kg/m2)
5.14 ± 0.3
7.1 ± 0.3
0.03
Age 65–74 years old N
63
318
F/M (%) Age (years)
42 (66.7 %)/11 68.9 ± 2.8
248 (78 %)/70 69.2 ± 2.9
2
NS
BMI (kg/m )
21.8 ± 2.9
25.6 ± 3.0
0.03
SMI (ASM/height2) (kg/m2)
5.04 ± 0.2
7.1 ± 0.4
0.01
Age 75–84 years old N
56
125
F/M (%)
26 (46.4 %)/30
108 (86.4 %)/17
Age (years)
78.6 ± 2.6
79 ± 2.9
BMI (kg/m2)
22.3 ± 2.8
25.8 ± 2.9
NS 0.05
SMI (ASM/height2) (kg/m2)
5.10 ± 0.4
7.0 ± 0.3
0.03
N
9
14
F/M (%)
4 (44.4 %)/5
8 (57.1 %)/6
Age (years)
88.3 ± 2.1
87.7 ± 2.4
BMI (kg/m2)
22.5 ± 3.1
25.3 ± 2.9
0.05
SMI (ASM/height2) (kg/m2)
4.92 ± 0.3
6.7 ± 0.3
0.03
Age [85 years old
a
Pre-sarcopenic subjects were excluded
The estimated direct healthcare cost attributable to sarcopenia in the United States in 2000 was $18.5 billion ($10.8 billion in men, $7.7 billion in women), which represented about 1.5 % of total healthcare expenditures for that year [38]. The yearly economic cost of sarcopenia much more rose than that of osteoporotic fractures in the United States (estimated to $16.3 billion per year) [39]. Healthcare expenditures due to sarcopenia cost roughly $900 per person per year [40]. The United States spends more than $26 billion annually on additional health care costs for people over 65 who lose their ability to live independently over the course of a single year [41]. A 10 % reduction in the sarcopenic population would save $1.1 billion each year [38]. We have estimated the prevalence of sarcopenia and the association of comorbid conditions in a general population of ambulatory subjects over 45 years old. Our study population consisted only of subjects living at home
123
NS
independently, who voluntarily participated in a functional and muscular evaluation, and did not have limitations to moderate physical exercise. Sarcopenia is an evolving concept and the current definition of sarcopenia includes both a loss of muscle strength and loss of muscle mass. For our muscular evaluation, we usually perform DEXA and handgrip strength measured with a handgrip strength dynamometer. Dual-energy X-ray absorptiometry is currently considered the gold standard for the evaluation of muscle mass. The name is derived from the fact that two X-ray beams are used with different energy levels of minimal intensity [9]. DEXA is an attractive method both for research and for clinical use to distinguish lean tissues, fat, and bone mineral. The main disadvantage of DEXA equipment is not portable, which may limit its use in older adults with functional limitations living at home or in institution [7]. Cross-sectional body composition data can predict loss of
Aging Clin Exp Res (2014) 26:137–146
fat-free mass among older people [42]. These changes in body composition and fat distribution are especially dependent on sex [43]. Other methods used to measure muscle mass include bioelectrical impedance analysis (BIA) [44], computed tomography, magnetic resonance imaging, urinary excretion of creatinine, anthropometric assessments, and neutron activation assessments [6], but there are very few studies and no consensus for evaluation of muscle mass with these different techniques. The BIA measurement techniques, used under standard conditions, have been found to correlate well with magnetic resonance imaging measures [20, 45]. The main limitation of BIA is the underestimation or overestimation of fat-free mass with hydration, problem usually observed over aging [46]. Many institutions use handgrip strength as a standard measure for assessing muscle strength. Physical performance can be analyzed using simple and easy-to-do tests such as the short physical performance battery test [10], usual gait speed [11], the timed get-up-and-go test [12], or the stair climb power test [13]. Isometric hand grip strength is strongly related with lower extremity muscle power, knee extension torque and calf cross-sectional muscle area [19]. Isometric hand grip strength is well correlated with muscle strength of shoulders, lower arms or legs [16]. Handgrip strength is a good clinical marker of mobility [19, 47]. Low handgrip strength is a better predictor of disability for activities of daily living [48, 49] and of clinical outcomes than low muscle mass [19]. Handgrip strength measured with a handgrip strength dynamometer is well correlated with poorer scores in functional, psychological and social health domain in elderly [50]. Our findings show that sarcopenia, using the EWGSOP definition [16], is relatively frequent in a healthy general population over 45 years living at home. Despite daily activities, 15.5 % of our whole population had sarcopenia. The prevalence of sarcopenia was 9 % for the subjects between 45 and 54 years, 13.5 % between 55 and 64 years, 16.5 % for the 65–74 years old subjects, 30.9 % for the age bracket located between 75 and 84 years, and 64.3 % in those aged 85 years or older. Sarcopenia was predominant in women between 45 and 64 years old, then sarcopenia becomes prevalent in men starting from the age brackets beyond 65 years. After adjustment for potential confounders, no specific diseases were directly associated with the presence of sarcopenia. Landi et al. [51], in a study evaluating the prevalence of sarcopenia in a population of elderly persons aged 70 years and older living in nursing homes, Parkinson’s disease, cerebrovascular diseases, chronic obstructive pulmonary disease, and osteoarthritis were more common among residents with sarcopenia relative to non-sarcopenic residents. The age, much less raised, and the rarity of these
143
diseases in our studied population probably explains our results. However, in the present study, participants with BMI higher than 22 kg/m2 and those involved in leisure physical activity for 3 h or more per week showed the lowest risk to be sarcopenic, regardless of age, gender, and other confounding factors. Aging is associated with significant changes in body composition, especially with a substantial reduction in fatfree mass and an increase in visceral fat and modification of cellular hydratation [4]. The prevalence of sarcopenia varies across diverse populations and according to age, gender, and living setting [52]. However, sarcopenia is highly prevalent among the population over the age of 65 years and more. Based on findings from previous studies, the prevalence of sarcopenia ranges between 5 and 13 % among 60- to 70-year-old individuals and between 11 and 50 % in those aged 80 years or older [6], depending on the adopted definition for such condition. Sarcopenia is one of the four main reasons for loss of muscle mass, with cachexia, anorexia and dehydration [6]. However, prevalence of sarcopenia was especially studied in elderly, in nursing home subjects or living in institution. Studies of sarcopenia in nursing homes were frequently conducted on small samples of subjects with different measurement techniques only evaluating muscle mass, showing high prevalence [51, 53–56]. Furthermore, no research article that relies on the accepted sarcopenia criteria in nursing home subjects has been published [21, 22]. In this population, sarcopenia may lead to frailty, but not all patients with sarcopenia are frail. In essence, sarcopenia is about twice as common as frailty [5]. The evaluation of sarcopenia in healthy communitydwelling elderly was more rarely studied. In Spain, Masanes et al. [57] prospectively evaluated sarcopenia by BIA a series of 200 healthy elderly in the community with preserved functional capacity and absence of cognitive impairment. The prevalence of sarcopenia observed was 33 % for elderly women and 10 % for males, results differs from other studies. Study of prevalence of sarcopenia in cohort including young subjects, from 45 years, age estimated by the beginning of sarcopenia in the general population, was rarely realized. In the New Mexico Elder Health Survey (NMEHS), sarcopenia (defined as an appendicular muscle mass index less than 2 SD below the mean of a young reference population) was observed in 15–25 % under the age of 70 years, and in 40 % of women and 50 % of men over 80 [7]. Janssen et al. [27] in the NHANES III (USA) study, studied the prevalence of sarcopenia in 14,818 subjects over 18 years old by BIA. In subjects aged [60 years: sarcopenia class I (defined as skeletal muscle mass 1–2 SD) was observed by BIA in 45 % of male, 59 %
123
144
of female; and sarcopenia class II (skeletal muscle mass[2 SD) in 7 % of male and 10 % of female [27]. Lauretani et al. [19] evaluated prevalence of sarcopenia in 1,030 subjects (range 20–102 years) by calf muscle cross-sectional area (defined by more than 2 SD below population mean in CT scan) (InCHIANTI study, Italy). The prevalence of sarcopenia was age-related ranging from 20 % at 65 years to 70 % at 85 and over in men and from 5 % at 65 years to 15 % at 85 years and over in women. In France, Tichet et al. assessed muscle mass by BIA in 782 healthy adults to determine skeletal mass index (SMI, muscle mass*100/weight) and muscle mass index (MMI, muscle mass/height2). Prevalence of sarcopenia was estimated in 888 middle aged (40–59 years) and 218 seniors (60–78 years). All were healthy people [58]. For the authors, women mean-2 SD were 6.2 kg/m2 (MMI) and 26.6 % (SMI); for men limits were 8.6 kg/m2 (MMI) and 34.4 % (SMI). In middle aged persons a small number of them were identified as sarcopenic. In healthy seniors, 2.8 % of women and 3.6 % of men were sarcopenic (MMI). The prevalence was 23.6 % in women and 12.5 % in men with SMI. For the authors, MMI and SMI identified different sarcopenic populations, leaner subjects for MMI while fatter subjects for SMI, and found a prevalence of sarcopenia different from that in the US population [58]. Finally, Bastiaanse et al. [59] recently evaluated muscle mass in 884 persons with intellectual disabilities, aged 50 years and over. The prevalence of sarcopenia was 14.3 % in the total group. In the age group 50–64 years prevalence was 12.7 %. Sarcopenia was positively associated with mobility impairment and inflammation and negatively with BMI. Our study had several limitations. This was an open cross-sectional study and it was not possible to determine the temporal nature of the observed associations for which controlled prospective data are needed. It’s a monocentric study which can be responsible on bias for geographical, climatic or ethnic selection. It is possible that those invited, but declined to take part, may have differed from those who participated so that the assessments may be an over- or underestimate of the results from the total population. However, the number of subjects who refused to participate to the study was weak. So caution is needed in interpretation of the data. However, any such non-response bias would be unlikely to have influenced the association between BMI, life-style characteristics (exercise) and muscle parameters. Finally, our results relate to a group of predominantly Caucasian European subjects and cannot be extrapolated beyond this group. A better knowledge of the age’s onset of sarcopenia is necessary for an optimal putting of the nutritional and physical programs of prevention [60, 61].
123
Aging Clin Exp Res (2014) 26:137–146
The present study suggests that among healthy ambulatory subjects over 45 years living at home, sarcopenia is frequent, even to the youngest subjects of the studied population, taking place from 9 % from 45 years, until 64.3 % for the subjects over 85 years. Our findings support the hypothesis that muscle mass and function are associated with BMI and physical activity, whatever the age of the subject. Conflict of interest
None.
References 1. Rosenberg I (1989) Summary comments: epidemiological and methodological problems in determining nutritional status of older persons. Am J Clin Nutr 50:1231–1233 2. Rosenberg IH (1997) Sarcopenia: origins and clinical relevance. J Nutr 127:990S–991S 3. Morley JE, Baumgartner RN, Roubenoff R et al (2001) Sarcopenia. J Lab Clin Med 137:231–243 4. Cruz-Jentoft AJ, Landi F, Topinkova´ E, Michel JP (2010) Understanding sarcopenia as a geriatric syndrome. Curr Opin Clin Nutr Metab Care. 13:1–7 5. Morley JE, Kim MJ, Haren MT, Kevorkian R, Banks WA (2005) Frailty and the aging male. Aging Male. 8:135–140 6. Morley JE (2008) Sarcopenia: diagnosis and treatment. J Nutr Health Aging. 12:452–456 7. Baumgartner RN, Koehler KM, Gallagher D et al (1998) Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 147:755–763 8. Abellan van Kan G (2009) Epidemiology and consequences of sarcopenia. J Nutr Health Aging 13:708–712 9. Blake GM, Fogelman I (2010) An update on dual-energy X-ray absorptiometry. Semin Nucl Med 40:62–73 10. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG et al (1994) A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol. 49:M85–M94 11. Buchner DM, Larson EB, Wagner EH, Koepsell TD, de Lateur BJ (1996) Evidence for a non-linear relationship between leg strength and gait speed. Age Ageing 25:386–391 12. Podsiadlo D, Richardson S (1991) The timed ‘‘up & go’’: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 39:142–148 13. Bean JF, Kiely DK, LaRose S, Alian J, Frontera WR (2007) Is stair climb power a clinically relevant measure of leg power impairments in at-risk older adults? Arch Phys Med Rehabil 88:604–609 14. Patil R, Uusi-Rasi K, Pasanen M, Kannus P, Karinkanta S, Sieva¨nen H (2012) Sarcopenia and osteopenia among 70–80year-old home-dwelling Finnish women: prevalence and association with functional performance. Osteoporos Int (Epub ahead of print) 15. Fielding RA, Vellas B, Evans WJ, Bhasin S, Morley JE, Newman AB, Abellan van Kan G, Andrieu S, Bauer J, Breuille D, Cederholm T, Chandler J, De Meynard C, Donini L, Harris T, Kannt A, Keime Guibert F, Onder G, Papanicolaou D, Rolland Y, Rooks D, Sieber C, Souhami E, Verlaan S, Zamboni M (2011) Sarcopenia: an undiagnosed condition in older adults. Current consensus definition: prevalence, etiology, and consequences.
Aging Clin Exp Res (2014) 26:137–146
16.
17. 18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
International working group on sarcopenia. J Am Med Dir Assoc 12:249–256 Cruz-Jentoft AJ, Baeyens JP, Bauer JM, European Working Group on Sarcopenia in Older People et al (2010) Sarcopenia: European con-sensus on definition and diagnosis: report of the European Working Group on Sarcopenia in Older People. Age Ageing 39:412–423 Lohman TG, Roche AF, Martorell R (eds) (1988) Anthropometric standardization reference manual. Human Kinetics Inc., Champaign Heymsfield SB, Smith R, Aulet M et al (1990) Appendicular skeletal muscle mass: measurement by dual-photon absorptiometry. Am J Clin Nutr 52:214–218 Lauretani F, Russo CR, Bandinelli S, Bartali B, Cavazzini C, Di Iorio A et al (2003) Age-associated changes in skeletal muscles and their effect on mobility: an operational diagnosis of sarcopenia. J Appl Physiol 95:1851–1860 Lukaski HC, Johnson PE, Bolonchuk WW et al (1985) Assessment of fat-free mass using bioelectrical impedance measurements of the human body. Am J Clin Nutr 41:810–817 Janssen I, Heymsfield SB, Baumgartner RN et al (2000) Estimation of skeletal muscle mass by bioelectrical impedance analysis. J Appl Physiol 89:465–471 Janssen I, Baumgartner RN, Ross R, Rosenberg IH, Roubenoff R (2004) Skeletal muscle cutpoints associated with elevated physical disability risk in older men and women. Am J Epidemiol 159:413–421 Gallagher D, Visser M, De Meersman RE et al (1997) Appendicular skeletal muscle mass: effects of age, gender, and ethnicity. J Appl Physiol 83:229–239 Newman A, Kupelian V, Visser M et al (2003) Sarcopenia: alternative definitions and association with lower extremity function. J Am Geriatr Soc 51:1602–1609 Delmonico MJ, Harris TB, Lee JS et al (2007) Alternative definitions of sarcopenia, lower extremity performance, and functional impairment with aging in older men and women. J Am Geriatr Soc 55:769–774 Chien MY, Huang TY, Wu YT (2008) Prevalence of sarcopenia estimated using a bioelectrical impedance analysis prediction equation in community-dwelling elderly people in Taiwan. J Am Geriatr Soc 56:1710–1715 Janssen I, Heymsfield SB, Ross R (2002) Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc 50:889–896 Janssen I (2006) Influence of sarcopenia on the development of physical disability: the cardiovascular health study. J Am Geriatr Soc 54:56–62 Rolland Y, Lauwers-Cances V, Cournot M, Nourhashe´mi F, Reynish W, Rivie`re D et al (2003) Sarcopenia, calf circumference, and physical function of elderly women: a cross-sectional study. J Am Geriatr Soc 51:1120–1124 Hwang B, Lim JY, Lee J, Choi JK, Ahn YO, Park BJ (2012) Prevalence rate and associated factors of sarcopenic obesity in Korean elderly population. J Korean Med Sci 27:748–755 Reid KF, Naumova EN, Carabello RJ et al (2008) Lower extremity muscle mass predicts functional performance in mobility-limited elders. J Nutr Health Aging 12:493–498 Rivas DA, Fielding RA (2011) Sarcopenia and other chronic conditions. In: Lynch GS (ed) Sarcopenia—age-related muscle wasting and weakness. Springer, Berlin Dufour AB, Hannan MT, Murabito JM, Kiel DP, McLean RR (2013) Sarcopenia definitions considering body size and fat mass are associated with mobility limitations: the Framingham study. J Gerontol A Biol Sci Med Sci 68(2):168–174 Li Z, Heber D (2012) Sarcopenic obesity in the elderly and strategies for weight management. Nutr Rev 70:57–64
145 35. Waters DL, Baumgartner RN (2011) Sarcopenia and obesity. Clin Geriatr Med 27:401–421 36. Rantanen T, Harris T, Leveille SG, Visser M, Foley D, Masaki K, Guralnik JM (2000) Muscle strength and body mass index as long-term predictors of mortality in initially healthy men. J Gerontol A Biol Sci Med Sci 55(3):M168–M173 37. Kimyagarov S, Klid R, Levenkrohn S, Fleissig Y, Kopel B, Arad M, Adunsky A (2010) Body mass index (BMI), body composition and mortality of nursing home elderly subjects. Arch Gerontol Geriatr 51:227–230 38. Janssen I, Shepard DS, Katzmarzyk PT, Roubenoff R (2004) The healthcare costs of sarcopenia in the United States. J Am Geriatr Soc 52:80–85 39. Ray NF, Chan JK, Thamer M, Melton LJ 3rd (1997) Medical expenditures for the treatment of osteoporotic fractures in the United States in 1995: report from the National Osteoporosis Foundation. J Bone Miner Res 12:24–35 40. Marcell TJ (2003) Sarcopenia: causes, consequences, and preventions. J Gerontol 58:M911–M916 41. Alliance for Aging Research. The Silver Book: chronic disease and medical innovation in an Aging Nation. http://silverbook.org/ fact/31. Accessed 29 Sept 2011 42. Bunout D, de la Maza MP, Barrera G, Leiva L, Gattas V, Hirsch S (2007) Assessment of sarcopenia: longitudinal versus cross sectional body composition data. Aging Clin Exp Res. 19:295–299 43. Zamboni M, Zoico E, Scartezzini T, Mazzali G, Tosoni P, Zivelonghi A, Gallagher D, De Pergola G, Di Francesco V, Bosello O (2003) Body composition changes in stable-weight elderly subjects: the effect of sex. Aging Clin Exp Res. 15:321–327 44. Tengvall M, Ellega˚rd L, Malmros V, Bosaeus N, Lissner L, Bosaeus I (2009) Body composition in the elderly: reference values and bioelectrical impedance spectroscopy to predict total body skeletal muscle mass. Clin Nutr. 28:52–58 45. Sayer AA, Dennison EM, Syddall HE, Jameson K, Martin HJ, Cooper C (2008) The developmental origins of sarcopenia: using peripheral quantitative computed tomography to assess muscle size in older people. J Gerontol A Biol Sci Med Sci 63:835–840 46. Kyle UG, Genton L, Karsegard L et al (2001) Single prediction equation for bioelectrical impedance analysis in adults aged 20–94 years. Nutrition. 17:248–253 47. Hicks GE, Shardell M, Alley DE, Miller RR, Bandinelli S, Guralnik J, Lauretani F, Simonsick EM, Ferrucci L (2012) Absolute strength and loss of strength as predictors of mobility decline in older adults: the InCHIANTI Study. J Gerontol A Biol Sci Med Sci 67:66–73 48. Al Snih S, Markides K, Ottenbacher K et al (2004) Hand grip strength and incident ADL disability in elderly Mexican Americans over a seven-year period. Aging Clin Exp Res 16:481–486 49. Rantanen T, Guralnik JM, Foley D, Masaki K, Leveille S, Curb JD, White L (1999) Midlife hand grip strength as a predictor of old age disability. JAMA 281:558–560 50. Taekema DG, Gussekloo J, Maier AB, Westendorp RGJ, De Craen AJM (2010) Handgrip strength as a predictor of functional, psychological and social health. A prospective population-based study among the oldest old. Age Ageing 39:331–337 51. Landi F, Liperoti R, Fusco D, Mastropaolo S, Quattrociocchi D, Proia A, Russo A, Bernabei R, Onder G (2012) Prevalence and risk factors of sarcopenia among nursing home older residents. J Gerontol A Biol Sci Med Sci 67:48–55 52. Bauer JM, Kaiser MJ, Sieber CC (2008) Sarcopenia in nursing home residents. J Am Med Dir Assoc. 9:545–551 53. von Haehling S, Anker SD (2010) Cachexia as a major underestimated and unmet medical need: facts and numbers. J Cachexia Sarcopenia Muscle. 1:1–5 54. Shaver HJ, Loper JA, Lutes RA (1980) Nutritional status of nursing home patients. J Parenter Enteral Nutr. 4:367–370
123
146 55. Alhamdan AA (2004) Nutritional status of Saudi males living in the Riyadh nursing home. Asia Pac J Clin Nutr. 13:372–376 56. Bahat G, Saka B, Tufan F, Akin S, Sivrikaya S, Yucel N, Erten N, Karan MA (2010) Prevalence of sarcopenia and its association with functional and nutritional status among male subjects in a nursing home in Turkey. Aging Male. 13:211–214 57. Masanes F, Culla A, Navarro-Gonzalez M, Navarro-Lopez M, Sacanella E, Torres B, Lopez-Soto A (2012) Prevalence of sarcopenia in healthy community-dwelling elderly in an urban area of Barcelona (Spain). J Nutr Health Aging. 16:184–187 58. Tichet J, Vol S, Goxe D, Salle A, Berrut G, Ritz P (2008) Prevalence of sarcopenia in the French senior population. J Nutr Health Aging. 12:202–206
123
Aging Clin Exp Res (2014) 26:137–146 59. Bastiaanse LP, Hilgenkamp TI, Echteld MA, Evenhuis HM (2012) Prevalence and associated factors of sarcopenia in older adults with intellectual disabilities. Res Dev Disabil 33:2004–2012 60. Reid KF, Callahan DM, Carabello RJ, Phillips EM, Frontera WR, Fielding RA (2008) Lower extremity power training in elderly subjects with mobility limitations: a randomized controlled trial. Aging Clin Exp Res. 20:337–343 61. Abe T, Mitsukawa N, Thiebaud RS, Loenneke JP, Loftin M, Ogawa M (2012) Lower body site-specific sarcopenia and accelerometer-determined moderate and vigorous physical activity: the HIREGASAKI study. Aging Clin Exp Res. 24:657–662
ORIGINAL ARTICLE
Prevalence of sarcopenia among healthy ambulatory subjects: the sarcopenia begins from 45 years Patrick Cherin • Elena Voronska • Nadia Fraoucene Christophe de Jaeger
•
Received: 18 March 2013 / Accepted: 9 August 2013 / Published online: 16 October 2013 Ó Springer International Publishing Switzerland 2013
Abstract Background and aims Sarcopenia has been indicated as a reliable marker of frailty and poor prognosis among the oldest individuals. There are only few data on sarcopenia in healthy general population. We evaluated the prevalence of sarcopenia and its association with functional and clinical status in a population of healthy ambulatory subjects over 45 years living at home, in Paris (France). Methods This study was conducted selecting all ambulatory participants (n = 1,445) aged 45 years and older from October 2008 to September 2011, consulting in the Institute of Physiology (Institut de Jaeger) from Paris (France) for a functional and muscular evaluation, and did not have limitations to moderate physical exercise. All were healthy people. All subjects performed a medical examination, associated with evaluation of muscle mass (body composition assessment using dual-energy X-ray absorptiometry) and of muscle function (by hand grip strength). Diagnosis of sarcopenia required the documentation of low muscle mass with low muscle strength according to the current international consensus definition of sarcopenia. Results From 1,421 participants (553 males and 868 females) definitively enrolled, 221 subjects (135 females and 86 males) (15.5 %) were identified as sarcopenic. Results from multivariate logistic regression models showed that sarcopenia was inversely associated with BMI
P. Cherin (&) Service de Me´decine Interne I, CHU Pitie´-Salpe´trie`re, 47 bd de l’hoˆpital, 75013 Paris, France e-mail: [email protected] E. Voronska N. Fraoucene C. de Jaeger Institut de Jaeger Center, 4 rue de Galliena, 75116 Paris, France
with those participants with BMI higher than 22 kg/m2 showing a lower risk of sarcopenia relative to those with BMI less than 21 kg/m2 (OR 0.72; 95 % CI 0.60–0.91). Similarly, probability of sarcopenia was lower among subjects involved in leisure physical activities for 3 h or more per week (OR 0.45; 95 % CI 0.24–0.93). According to the category of age [45–54; 55–64; 65–74; 75–84 and 85 years or more], the prevalence of sarcopenia in women increase from 9.1; 12.7; 14.5; 19.4; to 33.3 %, respectively. For the men, the percentage of sarcopenia increase with aging from 8.6; 15.6; 13.6; 63.8 to 45.5 %, respectively. Conclusions The present study suggests that among healthy ambulatory subjects over 45 years living at home, sarcopenia is frequent, even to the youngest subjects of the studied population, taking place from 9 % from 45 years, until 64.3 % for the subjects over 85 years. Our findings support the hypothesis that muscle mass and function are associated with BMI and physical activity, whatever the age of the subject. Keywords Sarcopenia Obesity Physical activity DXA Hand grip
Introduction Human muscle undergoes constant changes. The progressive decreased skeletal muscle mass with human aging is named sarcopenia, since the first description in 1989 by Irwin Rosenberg to describe the age-related decrease of muscle mass (Greek ‘‘sarx’’ = flesh ? ‘‘penia’’ = loss) [1, 2]. Sarcopenia has since been defined as the loss of skeletal muscle mass and strength that occurs with advancing age [3]. Since this time, a lot of scientific works were published to define the functional consequences and biologic
123
138
mechanisms of sarcopenia [4]. Sarcopenia, directly and causally linked to both muscle weakness and physical disability, has considerable societal consequences and is responsible of frailty, disability, and health care [4]. The reasons for these changes are complex and multifactorial, including physical activity, nutritional status (protein intake, energy intake, and vitamin D status), denervation of motor units, hormonal changes (especially reduction of serum testosterone and growth hormone), insulin resistance, genetic heritability, changes in circulating pro-inflammatory cytokines, and a net conversion of fast type II muscle fibers into slow type I fibers with resulting loss in muscle power necessary for activities of daily living [4, 5]. In addition, lipids are deposited in the muscle, but these changes do not usually lead to a loss in body weight. Sarcopenia may lead to frailty, but not all patients with sarcopenia are frail. In essence, sarcopenia is about twice as common as frailty [5, 6]. Many different methodologies have been used over the last 20 years, and new techniques are still being introduced. Depending on the population studied, definition and techniques used, sarcopenia is estimated to occur in 5–45 % of older adults [7, 8]. On average, it is estimated that 5–13 % of elderly people aged 60–70 years are affected by sarcopenia, and the numbers increase to 11–50 % for those aged 80 or above. The broadness in the range of sarcopenia prevalence is partly due to the heterogenecity of study populations, but also due to the different techniques used until now to assess muscle mass. Dual-energy X-ray absorptiometry (DEXA) is currently considered the gold standard [9]. Other methods used to measure muscle mass include bioelectrical impedance, computed tomography, magnetic resonance imaging, urinary excretion of creatinine, anthropometric assessments, and neutron activation assessments [6]. Depending on the actual technique used in different studies and on the cutoff values chosen, the prevalence of muscle mass may vary considerably. Now, however, the measurement of muscle mass is insufficient to define sarcopenia. It must be associated with evaluation of muscle function. Physical performance can be analyzed using simple and easy-to-do tests such as the short physical performance battery test [10], usual gait speed [11], the timed get-up-and-go test [12], or the stair climb power test [13]. But many institutions use handgrip strength as a standard measure for assessing muscle strength. At present, there are very few data from representative large samples on the epidemiology of sarcopenia in outcome subjects using new criteria [14]. According to current international consensus definition of sarcopenia [15, 16], we conducted an observational cross-sectional study to evaluate the prevalence of sarcopenia and its association
123
Aging Clin Exp Res (2014) 26:137–146
with clinical and functional domains in a large population of outcome patients living in Paris (France). We used for the diagnosis of sarcopenia, an objectively measured low muscle mass (body composition assessment using dualenergy X-ray absorptiometry) associated with low muscle function (evaluated by hand grip strength).
Methods Study population This study was prospectively conducted between October 2008 and September 2011 in the Institute of Physiology (Institut de Jaeger) from Paris (France) in ambulatory subjects, living at home independently, who voluntarily participated in a functional and muscular evaluation, and did not have limitations to moderate physical exercise. All were healthy people. The written informed consent was elaborated and used for each included patient. Patients were ambulatories, with no restriction for physical performance. They were included in the study group after determining eligibility according to the inclusion criteria and medical screening by a physician. These patients had no history of severe disease, had no contraindications to exercise, and understood the procedures of the DEX study. More specifically, to avoid the possible interference of neurological impairments in the measure of muscle function, participants with a diagnosis of stroke, severe Parkinson’s disease, peripheral neuropathy, and significant cognitive impairment (Mini Mental State Examination Score B21) were excluded, as well as patient with recent fractures (during the preceding 12 months), important alcohol consume, or marked decline in the basic activities of daily living. All participants without exclusion criteria consulting during the time period, aged 45 years and older were invited to be included in the study (n = 1,508). All subjects performed a medical examination, cardiac exploration associated with evaluation of muscle mass (body composition assessment using dual-energy X-ray absorptiometry) and of muscle function (by hand grip strength). Data collection Ambulatory subjects come in the Physiologic Institute de Jaeger (Paris) for medical check-up. All the participants enrolled in the present study were evaluated using standardized procedures, by the same trained assessors. The baseline examination was performed in the center by a trained geriatric physician. A physical examination and comorbid conditions were recorded using standardized health status questionnaire [hypertension, diabetes,
Aging Clin Exp Res (2014) 26:137–146
coronary heart disease, cerebrovascular disease, dementia, Parkinson disease, chronic bronchitis, myopathy, cancer, depression, other chronic disease, osteoarthritis, pain, alcohol intake, drugs and smoking (previous or current)]. Each leisure physical activities (walking, swimming, gymnastics, cycling, gardening or other) were noted, with their frequency, and duration. Subjects were considered physically active if they regularly practiced at least one physical activity for 1 h or more per day, at least 3 days per week. Covariates Body weight was measured while wearing light clothes using a calibrated medical balance. Body height was measured using a standard stadiometer. Body weight and height were measured to the nearest 0.1 kg and 0.1 cm, respectively. Body mass index (BMI) was defined as weight (kg) divided by the square of height (m). Assessment of sarcopenia For the present study, we adopted the international consensus definition of sarcopenia with the European Working Group on Sarcopenia in Older People (EWGSOP) criteria [16]. According to these new recommendations, we use for the diagnosis of sarcopenia, an objectively measured low muscle mass (body composition assessment using dualenergy X-ray absorptiometry) associated with low muscle function (evaluated by hand grip strength). Anthropometric measures and assessment techniques of muscle mass Anthropometric measurements (weight and height) were performed using standardized techniques [17]. For our study, muscle mass was evaluated by dual-energy X-ray absorptiometry (DXA, Lunar Prodigy Advance, GE Lunar, Madison, WI, USA), which is the preferred method for research and clinical use [16]. DXA measurements were performed by a trained technician, and the DXA machine was regularly calibrated. According to European consensus, sarcopenia was based for our work, on appendicular skeletal muscular mass (ASM) measures [18]. ASM corresponds to the sum of the 2 upper and lower limb muscular masses in kilogram. For the purpose of this study, skeletal muscle mass (ASM) in kilograms relative to height squared in meters was calculated as an index of relative skeletal muscle mass (SMI in kg/m2) (ASM/height2) as suggested by Baumgartner et al. [7]. The cutoff to define sarcopenic patients was based on previous work (low muscle mass was defined as the
139
skeletal muscle index of 2 SDs or more below the normal sex-specific means for young persons [7, 19–22]. Patients were classified as sarcopenic if their relative skeletal muscle mass was 2 SDs below the mean of a reference population from the Rosetta Study, which included 229 healthy Americans aged 18–40 years [23]. The cutoff correspond to 5.45 kg/m2 in women and 7.26 kg/m2 in men [7, 24, 25]. Muscle strength measure—hand grip Muscle strength was assessed by hand grip strength, which was measured using a dynamometer (North Coast Hydraulic Hand Dynamometer; North Coast Medical Inc, Morgan Hill, CA, USA). Isometric grip strength was measured three times in each hand, alternating between right and left hands. The participants were verbally encouraged to perform to their maximum, and the best performance of the strongest hand from three trials was recorded. Using the cutoff points indicated in the EWGSOP consensus paper [16], low muscle strength was classified as hand grip less than 30 and 20 kg in men and women, respectively. These cut-points were similar to that obtained among 1,030 subjects (469 men and 561 women, age range from 20 to 102 years) described in the InCHIANTI study population [19]. Statistical analysis Subjects with sarcopenia were identified using the definition proposed by the EWGSOP [16]. Data were analyzed to obtain descriptive statistics. Continuous variables are presented as mean and standard deviation. Several statistical analysis were used to evaluate differences in sociodemographic, functional, and clinical characteristics between subjects with sarcopenia and subjects without sarcopenia. Quantitative parameters with normal distribution were tested by one-way analysis of variance. If abnormal distribution was present, a nonparametric test (Kruskal–Wallis rank test) was used. Categorical variables were analyzed by the c2 test. A statistical significance was defined for p \ 0.05 level. The relationship between sarcopenia and clinical and functional variables was estimated by multiple logistic regression models. Sarcopenia identified by the EWGSOP definition was included as dependent variable in such models. Age, gender, diagnosis of dementia, Parkinson’s disease, cerebrovascular disease, hypertension, diabetes, chronic obstructive pulmonary disease, cancer, osteoarthritis, physical activity, and BMI were considered as factors potentially associated with sarcopenia and were considered as covariates in the logistic model.
123
140
Aging Clin Exp Res (2014) 26:137–146
Results A total of 1,508 subjects followed in the Institute were invited to take part to the study. Sixty-three subjects declined for personal reasons. 1,445 subjects aged 45 years and older initially have benefited of a physical evaluation, including evaluation of muscle mass (body composition assessment using dual-energy X-ray absorptiometry) and of muscle function (by hand grip strength). Twenty-three participants (1.6 %) were excluded because of incomplete body composition or muscle information (weight, height, grip test) (n = 14), informed consent not obtained (n = 4), severe cognitive involvement (n = 2), congestive cardiac failure (n = 2), acute flu (n = 1). This selection resulted in a final sample of 1,421 participants (553 males and 868 females) who were definitively enrolled. Mean age of study participants was 63.1 (standard deviation 10.2) years, and the mean BMI was 24.5 ± 4.0 kg/m2. The descriptive characteristics of the 1,421 participants are summarized in Table 1. 869 subjects (61.1 %) were women (mean age 62.7 ± 10.2 years, mean BMI 23.8 ± 4.2 kg/m2) and 552 were men (mean age 63.6 ± 10.1 years, mean BMI 25.6 ± 3.3 kg/m2). The mean SMI (ASM/height2) was 5.8 ± 0.7 kg/m2 for the 869 women and 7.7 ± 1.0 kg/m2 for the 552 men. Using the EWGSOP-suggested conceptual stages of sarcopenia, subjects with only reduced muscle mass were defined as pre-sarcopenic, and subjects with associated reduced muscle mass and low muscle strength (hand grip) were defined as sarcopenic [16]. Forty two subjects (25 males, 17 females) were considered as pre-sarcopenic, defined by reduced muscle mass on DXA and normal muscle strength with hand grip dynamometer. Table 1 Descriptive characteristics of study participants, n = 1,421 Characteristics
Mean (SD)
Range
Age (years)
63.1 (10.2)
45.1–83.0
Weight (kg)
68.0 (13.9)
44.5–116.8
Height (cm)
159.8 (5.8)
142.0–177.8
BMI (kg/m2)
24.5 (4.0)
18.6–45.1
Total body fat (%)
39.2 (7.4)
22.5–55.8
Total body fat mass (kg)
26.7 (8.6)
4.9–52.9
Total body lean mass (kg)
41.3 (5.8)
18.9–79.0
ASM (kg)
22.0 (4.2)
9.6–27.9
7.4 (0.9)
4.0–10.9
33.4 (8.8)
6.0–62.0
Body composition
SMI (ASM/height2) (kg/m2) Functional performance Mean dominant hand grip strength (kg)
123
A total of 221 subjects (135 females and 86 males) (15.5 %) were identified as affected by sarcopenia. Forty two subjects (25 males, 17 females) were considered as pre-sarcopenic, defined by reduced muscle mass on DXA and normal muscle strength with hand grip dynamometer. The mean age of these pre-sarcopenic subjects was 64.1 ± 8.7 years. The BMI was 22.4 ± 3.0 and the mean ASM was 14.8 ± 2.2 kg, with a mean dominant hand grip strength evaluated at 32.7 ± 2.1 kg. Only 28.8 % of these pre-sarcopenic population declared at least 3 h per week of leisure physically activities. The characteristics of study participants according to the presence of sarcopenia are summarized in Tables 2 and 3. The percentage of sarcopenia in our overall population of outcome subjects over 45 years old was similar between men and women (15.6 vs 15.5 %, respectively), but there are significant differences according to the categories of age. Compared with subjects without sarcopenia, those diagnosed with sarcopenia showed lower BMI (mean BMI 21.7 vs 25.1 kg/m2, p = 0.03, respectively). Subjects with sarcopenia showed a statistically significant lower skeletal muscle index compared with participants without sarcopenia (5.0 vs 7.1 kg/m2, p \ 0.05, respectively). Similarly, sarcopenic subjects had significantly lower muscle strength compared with non-sarcopenic (24.1 vs 36.3 kg, p \ 0.05, respectively). Also, relative to non-sarcopenic subjects, those with sarcopenia were less likely to be involved in leisure physically activities (C3 h/week) (42.5 vs 70.6 %, p = 0.03, respectively). Multivariate logistic regression models showed that the mean number of diseases, the frequency of Parkinson’s disease, dementia, cerebrovascular diseases, chronic obstructive pulmonary disease, cancer, osteoarthritis and number of medications were similar between sarcopenic and non-sarcopenic subjects. After adjusting for potential confounders, sarcopenia was inversely associated with BMI with those participants with BMI higher than 22 kg/ m2 showing a lower risk of sarcopenia relative to those with BMI less than 21 kg/m2 (OR 0.72; 95 % CI 0.60–0.91). Similarly, probability of sarcopenia was lower among subjects involved in leisure physical activities for 3 h or more per week (OR 0.45; 95 % CI 0.24–0.93). The mean age of sarcopenic men was significantly higher than in non-sarcopenic participants (69.3 ± 11.3 vs 62.4 ± 9.5 years, p \ 0.05). The mean BMI was lower in sarcopenic male subjects (23.0 vs 26.2 kg/m2, p \ 0.05). The mean SMI (ASM/height2) was 6.73 ± 0.36 kg/m2 in sarcopenic subjects versus 8.27 ± 0.67 kg/m2 in non-sarcopenic males (p \ 0.05). In sarcopenic women, the difference between the mean age of sarcopenic and non-sarcopenic subjects was non significant (65.3 ± 10.0 vs 62.3 ± 10.1 years, respectively, p [ 0.05). Like in male, the mean BMI was
Aging Clin Exp Res (2014) 26:137–146 Table 2 Characteristics of study participants according to the presence of sarcopenia
141
Characteristics [mean (SD)] N
Sarcopenia
No sarcopenia
221
1,158a
p
F/M
135/86
716/442
NS
Age (years)
66.9 (10.7)
62.3 (9.9)
0.05
Weight (kg)
68.0 (13.9)
69.6 (13.7)
NS
Height (cm)
159.8 (5.8)
165 (9.0)
NS
BMI (kg/m2)
21.7 (2.7)
25.1 (4.0)
0.03
Leisure physically activities (C3 h/week) (%)
94 (42.5 %)
818 (70.6 %)
0.03
Body composition
a
Pre-sarcopenic subjects were excluded
Table 3 Main co-morbidities of study participants according to the presence of sarcopenia
a
Pre-sarcopenic subjects were excluded
ASM (kg)
14.0 (1.8)
19.9 (4.8)
0.01
SMI (ASM/height2) (kg/m2)
5.0 (0.8)
7.1 (1.1)
0.01
24.1 (5.7)
36.3 (9.1)
0.01
Functional performance Mean dominant hand grip strength (kg)
Medical history
Sarcopenia
No sarcopenia
p
N
221
1,158a
F/M
135/86
716/442
Current smoker (%)
28.1 %
28.9 %
NS
Mild Parkinson (%)
2.1 %
1.9 %
NS
Mild cognitive impairment (%)
1.4 %
1.2 %
NS
Cerebrovascular diseases (%)
0.9 %
0.7 %
NS
Chronic obstructive pulmonary disease (%)
1.2 %
1.3 %
NS
Cancer (%)
2.1 %
2.2 %
NS
Osteoarthritis (%)
18.8 %
16.9 %
NS
Mean number of medications
2.3
2.1
NS
NS
Statins (%)
13.9 %
14.6 %
NS
Neuroleptic, anti-depressive and CNS drugs (%)
9.1 %
8.6 %
NS
Other potential myotoxic drugs
0.4 %
0.5 %
NS
significantly lower in sarcopenic women subjects (20.9 vs 24.4 kg/m2, p \ 0.05). The mean SMI was 5.14 ± 0.33 kg/m2 in sarcopenic subjects versus 6.39 ± 0.69 kg/m2 in non-sarcopenic females (p \ 0.05). The main characteristics of study participants according to the age and the presence of sarcopenia are given in Table 4. According to the category of age, the prevalence of sarcopenia was 9 % in the population between 45 and 54 years, 13.5 % in the categories of 55–64 years, 16.5 % for the 65–74 years old subjects, 30.9 % for the population age between 75 and 84 years, and 64.3 % for the patients over 85 years. Whatever the sex, the SMI gradually decreases with the advance in age. Sarcopenia is predominant in women between 45 and 74 years old, then sarcopenia become prevalent in men (Table 4). In our population, the prevalence of sarcopenia in women, according to the age bracket [45–54; 55–64; 65–74; 75–84 and 85 years or more] increase of 9.1; 12.7; 14.5; 19.4; and 33.3 %, respectively. For the men, the
percentage of sarcopenia increase with aging from 8.6; 15.6; 13.6; 63.8 and 45.5 %, respectively.
Discussion Sarcopenia is henceforth a major problem of public health. Depending on the population studied and definition used, sarcopenia is estimated to occur in 5–45 % of older adults [2, 7, 8, 19, 26–30]. Low levels of muscle mass have been linked with poor health outcomes that include functional impairments [31], severe physical disability [22], association with metabolic problems such as insulin resistance, type 2 diabetes, obesity [32–35] and mortality [36, 37]. In the elderly, sarcopenia is frequent and may lead to frailty [5]. However, the prevalence of sarcopenia in young ambulatory subjects, using the new criteria was not reported. In our study, sarcopenia affected the subjects from 45 years, despite daily activities.
123
142 Table 4 Characteristics of study participants according to the age and the presence of sarcopenia
Aging Clin Exp Res (2014) 26:137–146
Characteristic (mean)
Sarcopenia (mean ± SD)
No sarcopeniaa (mean ± SD)
p
Age 45–54 years old N
28
284
F/M (%)
19 (66 %)/9
189 (66.5 %)/95
Age (years)
50.1 ± 3.0
50.3 ± 2.8
NS
BMI (kg/m2)
21.1 ± 2.8
24.5 ± 3.1
0.05
SMI (ASM/height2) (kg/m2)
5.13 ± 0.4
7.2 ± 0.5
0.01
Age 55–64 years old N
65
417
F/M (%)
44 (67.7 %)/21
303 (72.7 %)/114
59.3 ± 2.7
59.6 ± 2.5
Age (years) 2
NS
BMI (kg/m )
21.4 ± 2.4
24.9 ± 2.5
0.05
SMI (ASM/height2) (kg/m2)
5.14 ± 0.3
7.1 ± 0.3
0.03
Age 65–74 years old N
63
318
F/M (%) Age (years)
42 (66.7 %)/11 68.9 ± 2.8
248 (78 %)/70 69.2 ± 2.9
2
NS
BMI (kg/m )
21.8 ± 2.9
25.6 ± 3.0
0.03
SMI (ASM/height2) (kg/m2)
5.04 ± 0.2
7.1 ± 0.4
0.01
Age 75–84 years old N
56
125
F/M (%)
26 (46.4 %)/30
108 (86.4 %)/17
Age (years)
78.6 ± 2.6
79 ± 2.9
BMI (kg/m2)
22.3 ± 2.8
25.8 ± 2.9
NS 0.05
SMI (ASM/height2) (kg/m2)
5.10 ± 0.4
7.0 ± 0.3
0.03
N
9
14
F/M (%)
4 (44.4 %)/5
8 (57.1 %)/6
Age (years)
88.3 ± 2.1
87.7 ± 2.4
BMI (kg/m2)
22.5 ± 3.1
25.3 ± 2.9
0.05
SMI (ASM/height2) (kg/m2)
4.92 ± 0.3
6.7 ± 0.3
0.03
Age [85 years old
a
Pre-sarcopenic subjects were excluded
The estimated direct healthcare cost attributable to sarcopenia in the United States in 2000 was $18.5 billion ($10.8 billion in men, $7.7 billion in women), which represented about 1.5 % of total healthcare expenditures for that year [38]. The yearly economic cost of sarcopenia much more rose than that of osteoporotic fractures in the United States (estimated to $16.3 billion per year) [39]. Healthcare expenditures due to sarcopenia cost roughly $900 per person per year [40]. The United States spends more than $26 billion annually on additional health care costs for people over 65 who lose their ability to live independently over the course of a single year [41]. A 10 % reduction in the sarcopenic population would save $1.1 billion each year [38]. We have estimated the prevalence of sarcopenia and the association of comorbid conditions in a general population of ambulatory subjects over 45 years old. Our study population consisted only of subjects living at home
123
NS
independently, who voluntarily participated in a functional and muscular evaluation, and did not have limitations to moderate physical exercise. Sarcopenia is an evolving concept and the current definition of sarcopenia includes both a loss of muscle strength and loss of muscle mass. For our muscular evaluation, we usually perform DEXA and handgrip strength measured with a handgrip strength dynamometer. Dual-energy X-ray absorptiometry is currently considered the gold standard for the evaluation of muscle mass. The name is derived from the fact that two X-ray beams are used with different energy levels of minimal intensity [9]. DEXA is an attractive method both for research and for clinical use to distinguish lean tissues, fat, and bone mineral. The main disadvantage of DEXA equipment is not portable, which may limit its use in older adults with functional limitations living at home or in institution [7]. Cross-sectional body composition data can predict loss of
Aging Clin Exp Res (2014) 26:137–146
fat-free mass among older people [42]. These changes in body composition and fat distribution are especially dependent on sex [43]. Other methods used to measure muscle mass include bioelectrical impedance analysis (BIA) [44], computed tomography, magnetic resonance imaging, urinary excretion of creatinine, anthropometric assessments, and neutron activation assessments [6], but there are very few studies and no consensus for evaluation of muscle mass with these different techniques. The BIA measurement techniques, used under standard conditions, have been found to correlate well with magnetic resonance imaging measures [20, 45]. The main limitation of BIA is the underestimation or overestimation of fat-free mass with hydration, problem usually observed over aging [46]. Many institutions use handgrip strength as a standard measure for assessing muscle strength. Physical performance can be analyzed using simple and easy-to-do tests such as the short physical performance battery test [10], usual gait speed [11], the timed get-up-and-go test [12], or the stair climb power test [13]. Isometric hand grip strength is strongly related with lower extremity muscle power, knee extension torque and calf cross-sectional muscle area [19]. Isometric hand grip strength is well correlated with muscle strength of shoulders, lower arms or legs [16]. Handgrip strength is a good clinical marker of mobility [19, 47]. Low handgrip strength is a better predictor of disability for activities of daily living [48, 49] and of clinical outcomes than low muscle mass [19]. Handgrip strength measured with a handgrip strength dynamometer is well correlated with poorer scores in functional, psychological and social health domain in elderly [50]. Our findings show that sarcopenia, using the EWGSOP definition [16], is relatively frequent in a healthy general population over 45 years living at home. Despite daily activities, 15.5 % of our whole population had sarcopenia. The prevalence of sarcopenia was 9 % for the subjects between 45 and 54 years, 13.5 % between 55 and 64 years, 16.5 % for the 65–74 years old subjects, 30.9 % for the age bracket located between 75 and 84 years, and 64.3 % in those aged 85 years or older. Sarcopenia was predominant in women between 45 and 64 years old, then sarcopenia becomes prevalent in men starting from the age brackets beyond 65 years. After adjustment for potential confounders, no specific diseases were directly associated with the presence of sarcopenia. Landi et al. [51], in a study evaluating the prevalence of sarcopenia in a population of elderly persons aged 70 years and older living in nursing homes, Parkinson’s disease, cerebrovascular diseases, chronic obstructive pulmonary disease, and osteoarthritis were more common among residents with sarcopenia relative to non-sarcopenic residents. The age, much less raised, and the rarity of these
143
diseases in our studied population probably explains our results. However, in the present study, participants with BMI higher than 22 kg/m2 and those involved in leisure physical activity for 3 h or more per week showed the lowest risk to be sarcopenic, regardless of age, gender, and other confounding factors. Aging is associated with significant changes in body composition, especially with a substantial reduction in fatfree mass and an increase in visceral fat and modification of cellular hydratation [4]. The prevalence of sarcopenia varies across diverse populations and according to age, gender, and living setting [52]. However, sarcopenia is highly prevalent among the population over the age of 65 years and more. Based on findings from previous studies, the prevalence of sarcopenia ranges between 5 and 13 % among 60- to 70-year-old individuals and between 11 and 50 % in those aged 80 years or older [6], depending on the adopted definition for such condition. Sarcopenia is one of the four main reasons for loss of muscle mass, with cachexia, anorexia and dehydration [6]. However, prevalence of sarcopenia was especially studied in elderly, in nursing home subjects or living in institution. Studies of sarcopenia in nursing homes were frequently conducted on small samples of subjects with different measurement techniques only evaluating muscle mass, showing high prevalence [51, 53–56]. Furthermore, no research article that relies on the accepted sarcopenia criteria in nursing home subjects has been published [21, 22]. In this population, sarcopenia may lead to frailty, but not all patients with sarcopenia are frail. In essence, sarcopenia is about twice as common as frailty [5]. The evaluation of sarcopenia in healthy communitydwelling elderly was more rarely studied. In Spain, Masanes et al. [57] prospectively evaluated sarcopenia by BIA a series of 200 healthy elderly in the community with preserved functional capacity and absence of cognitive impairment. The prevalence of sarcopenia observed was 33 % for elderly women and 10 % for males, results differs from other studies. Study of prevalence of sarcopenia in cohort including young subjects, from 45 years, age estimated by the beginning of sarcopenia in the general population, was rarely realized. In the New Mexico Elder Health Survey (NMEHS), sarcopenia (defined as an appendicular muscle mass index less than 2 SD below the mean of a young reference population) was observed in 15–25 % under the age of 70 years, and in 40 % of women and 50 % of men over 80 [7]. Janssen et al. [27] in the NHANES III (USA) study, studied the prevalence of sarcopenia in 14,818 subjects over 18 years old by BIA. In subjects aged [60 years: sarcopenia class I (defined as skeletal muscle mass 1–2 SD) was observed by BIA in 45 % of male, 59 %
123
144
of female; and sarcopenia class II (skeletal muscle mass[2 SD) in 7 % of male and 10 % of female [27]. Lauretani et al. [19] evaluated prevalence of sarcopenia in 1,030 subjects (range 20–102 years) by calf muscle cross-sectional area (defined by more than 2 SD below population mean in CT scan) (InCHIANTI study, Italy). The prevalence of sarcopenia was age-related ranging from 20 % at 65 years to 70 % at 85 and over in men and from 5 % at 65 years to 15 % at 85 years and over in women. In France, Tichet et al. assessed muscle mass by BIA in 782 healthy adults to determine skeletal mass index (SMI, muscle mass*100/weight) and muscle mass index (MMI, muscle mass/height2). Prevalence of sarcopenia was estimated in 888 middle aged (40–59 years) and 218 seniors (60–78 years). All were healthy people [58]. For the authors, women mean-2 SD were 6.2 kg/m2 (MMI) and 26.6 % (SMI); for men limits were 8.6 kg/m2 (MMI) and 34.4 % (SMI). In middle aged persons a small number of them were identified as sarcopenic. In healthy seniors, 2.8 % of women and 3.6 % of men were sarcopenic (MMI). The prevalence was 23.6 % in women and 12.5 % in men with SMI. For the authors, MMI and SMI identified different sarcopenic populations, leaner subjects for MMI while fatter subjects for SMI, and found a prevalence of sarcopenia different from that in the US population [58]. Finally, Bastiaanse et al. [59] recently evaluated muscle mass in 884 persons with intellectual disabilities, aged 50 years and over. The prevalence of sarcopenia was 14.3 % in the total group. In the age group 50–64 years prevalence was 12.7 %. Sarcopenia was positively associated with mobility impairment and inflammation and negatively with BMI. Our study had several limitations. This was an open cross-sectional study and it was not possible to determine the temporal nature of the observed associations for which controlled prospective data are needed. It’s a monocentric study which can be responsible on bias for geographical, climatic or ethnic selection. It is possible that those invited, but declined to take part, may have differed from those who participated so that the assessments may be an over- or underestimate of the results from the total population. However, the number of subjects who refused to participate to the study was weak. So caution is needed in interpretation of the data. However, any such non-response bias would be unlikely to have influenced the association between BMI, life-style characteristics (exercise) and muscle parameters. Finally, our results relate to a group of predominantly Caucasian European subjects and cannot be extrapolated beyond this group. A better knowledge of the age’s onset of sarcopenia is necessary for an optimal putting of the nutritional and physical programs of prevention [60, 61].
123
Aging Clin Exp Res (2014) 26:137–146
The present study suggests that among healthy ambulatory subjects over 45 years living at home, sarcopenia is frequent, even to the youngest subjects of the studied population, taking place from 9 % from 45 years, until 64.3 % for the subjects over 85 years. Our findings support the hypothesis that muscle mass and function are associated with BMI and physical activity, whatever the age of the subject. Conflict of interest
None.
References 1. Rosenberg I (1989) Summary comments: epidemiological and methodological problems in determining nutritional status of older persons. Am J Clin Nutr 50:1231–1233 2. Rosenberg IH (1997) Sarcopenia: origins and clinical relevance. J Nutr 127:990S–991S 3. Morley JE, Baumgartner RN, Roubenoff R et al (2001) Sarcopenia. J Lab Clin Med 137:231–243 4. Cruz-Jentoft AJ, Landi F, Topinkova´ E, Michel JP (2010) Understanding sarcopenia as a geriatric syndrome. Curr Opin Clin Nutr Metab Care. 13:1–7 5. Morley JE, Kim MJ, Haren MT, Kevorkian R, Banks WA (2005) Frailty and the aging male. Aging Male. 8:135–140 6. Morley JE (2008) Sarcopenia: diagnosis and treatment. J Nutr Health Aging. 12:452–456 7. Baumgartner RN, Koehler KM, Gallagher D et al (1998) Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 147:755–763 8. Abellan van Kan G (2009) Epidemiology and consequences of sarcopenia. J Nutr Health Aging 13:708–712 9. Blake GM, Fogelman I (2010) An update on dual-energy X-ray absorptiometry. Semin Nucl Med 40:62–73 10. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG et al (1994) A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol. 49:M85–M94 11. Buchner DM, Larson EB, Wagner EH, Koepsell TD, de Lateur BJ (1996) Evidence for a non-linear relationship between leg strength and gait speed. Age Ageing 25:386–391 12. Podsiadlo D, Richardson S (1991) The timed ‘‘up & go’’: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 39:142–148 13. Bean JF, Kiely DK, LaRose S, Alian J, Frontera WR (2007) Is stair climb power a clinically relevant measure of leg power impairments in at-risk older adults? Arch Phys Med Rehabil 88:604–609 14. Patil R, Uusi-Rasi K, Pasanen M, Kannus P, Karinkanta S, Sieva¨nen H (2012) Sarcopenia and osteopenia among 70–80year-old home-dwelling Finnish women: prevalence and association with functional performance. Osteoporos Int (Epub ahead of print) 15. Fielding RA, Vellas B, Evans WJ, Bhasin S, Morley JE, Newman AB, Abellan van Kan G, Andrieu S, Bauer J, Breuille D, Cederholm T, Chandler J, De Meynard C, Donini L, Harris T, Kannt A, Keime Guibert F, Onder G, Papanicolaou D, Rolland Y, Rooks D, Sieber C, Souhami E, Verlaan S, Zamboni M (2011) Sarcopenia: an undiagnosed condition in older adults. Current consensus definition: prevalence, etiology, and consequences.
Aging Clin Exp Res (2014) 26:137–146
16.
17. 18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
International working group on sarcopenia. J Am Med Dir Assoc 12:249–256 Cruz-Jentoft AJ, Baeyens JP, Bauer JM, European Working Group on Sarcopenia in Older People et al (2010) Sarcopenia: European con-sensus on definition and diagnosis: report of the European Working Group on Sarcopenia in Older People. Age Ageing 39:412–423 Lohman TG, Roche AF, Martorell R (eds) (1988) Anthropometric standardization reference manual. Human Kinetics Inc., Champaign Heymsfield SB, Smith R, Aulet M et al (1990) Appendicular skeletal muscle mass: measurement by dual-photon absorptiometry. Am J Clin Nutr 52:214–218 Lauretani F, Russo CR, Bandinelli S, Bartali B, Cavazzini C, Di Iorio A et al (2003) Age-associated changes in skeletal muscles and their effect on mobility: an operational diagnosis of sarcopenia. J Appl Physiol 95:1851–1860 Lukaski HC, Johnson PE, Bolonchuk WW et al (1985) Assessment of fat-free mass using bioelectrical impedance measurements of the human body. Am J Clin Nutr 41:810–817 Janssen I, Heymsfield SB, Baumgartner RN et al (2000) Estimation of skeletal muscle mass by bioelectrical impedance analysis. J Appl Physiol 89:465–471 Janssen I, Baumgartner RN, Ross R, Rosenberg IH, Roubenoff R (2004) Skeletal muscle cutpoints associated with elevated physical disability risk in older men and women. Am J Epidemiol 159:413–421 Gallagher D, Visser M, De Meersman RE et al (1997) Appendicular skeletal muscle mass: effects of age, gender, and ethnicity. J Appl Physiol 83:229–239 Newman A, Kupelian V, Visser M et al (2003) Sarcopenia: alternative definitions and association with lower extremity function. J Am Geriatr Soc 51:1602–1609 Delmonico MJ, Harris TB, Lee JS et al (2007) Alternative definitions of sarcopenia, lower extremity performance, and functional impairment with aging in older men and women. J Am Geriatr Soc 55:769–774 Chien MY, Huang TY, Wu YT (2008) Prevalence of sarcopenia estimated using a bioelectrical impedance analysis prediction equation in community-dwelling elderly people in Taiwan. J Am Geriatr Soc 56:1710–1715 Janssen I, Heymsfield SB, Ross R (2002) Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc 50:889–896 Janssen I (2006) Influence of sarcopenia on the development of physical disability: the cardiovascular health study. J Am Geriatr Soc 54:56–62 Rolland Y, Lauwers-Cances V, Cournot M, Nourhashe´mi F, Reynish W, Rivie`re D et al (2003) Sarcopenia, calf circumference, and physical function of elderly women: a cross-sectional study. J Am Geriatr Soc 51:1120–1124 Hwang B, Lim JY, Lee J, Choi JK, Ahn YO, Park BJ (2012) Prevalence rate and associated factors of sarcopenic obesity in Korean elderly population. J Korean Med Sci 27:748–755 Reid KF, Naumova EN, Carabello RJ et al (2008) Lower extremity muscle mass predicts functional performance in mobility-limited elders. J Nutr Health Aging 12:493–498 Rivas DA, Fielding RA (2011) Sarcopenia and other chronic conditions. In: Lynch GS (ed) Sarcopenia—age-related muscle wasting and weakness. Springer, Berlin Dufour AB, Hannan MT, Murabito JM, Kiel DP, McLean RR (2013) Sarcopenia definitions considering body size and fat mass are associated with mobility limitations: the Framingham study. J Gerontol A Biol Sci Med Sci 68(2):168–174 Li Z, Heber D (2012) Sarcopenic obesity in the elderly and strategies for weight management. Nutr Rev 70:57–64
145 35. Waters DL, Baumgartner RN (2011) Sarcopenia and obesity. Clin Geriatr Med 27:401–421 36. Rantanen T, Harris T, Leveille SG, Visser M, Foley D, Masaki K, Guralnik JM (2000) Muscle strength and body mass index as long-term predictors of mortality in initially healthy men. J Gerontol A Biol Sci Med Sci 55(3):M168–M173 37. Kimyagarov S, Klid R, Levenkrohn S, Fleissig Y, Kopel B, Arad M, Adunsky A (2010) Body mass index (BMI), body composition and mortality of nursing home elderly subjects. Arch Gerontol Geriatr 51:227–230 38. Janssen I, Shepard DS, Katzmarzyk PT, Roubenoff R (2004) The healthcare costs of sarcopenia in the United States. J Am Geriatr Soc 52:80–85 39. Ray NF, Chan JK, Thamer M, Melton LJ 3rd (1997) Medical expenditures for the treatment of osteoporotic fractures in the United States in 1995: report from the National Osteoporosis Foundation. J Bone Miner Res 12:24–35 40. Marcell TJ (2003) Sarcopenia: causes, consequences, and preventions. J Gerontol 58:M911–M916 41. Alliance for Aging Research. The Silver Book: chronic disease and medical innovation in an Aging Nation. http://silverbook.org/ fact/31. Accessed 29 Sept 2011 42. Bunout D, de la Maza MP, Barrera G, Leiva L, Gattas V, Hirsch S (2007) Assessment of sarcopenia: longitudinal versus cross sectional body composition data. Aging Clin Exp Res. 19:295–299 43. Zamboni M, Zoico E, Scartezzini T, Mazzali G, Tosoni P, Zivelonghi A, Gallagher D, De Pergola G, Di Francesco V, Bosello O (2003) Body composition changes in stable-weight elderly subjects: the effect of sex. Aging Clin Exp Res. 15:321–327 44. Tengvall M, Ellega˚rd L, Malmros V, Bosaeus N, Lissner L, Bosaeus I (2009) Body composition in the elderly: reference values and bioelectrical impedance spectroscopy to predict total body skeletal muscle mass. Clin Nutr. 28:52–58 45. Sayer AA, Dennison EM, Syddall HE, Jameson K, Martin HJ, Cooper C (2008) The developmental origins of sarcopenia: using peripheral quantitative computed tomography to assess muscle size in older people. J Gerontol A Biol Sci Med Sci 63:835–840 46. Kyle UG, Genton L, Karsegard L et al (2001) Single prediction equation for bioelectrical impedance analysis in adults aged 20–94 years. Nutrition. 17:248–253 47. Hicks GE, Shardell M, Alley DE, Miller RR, Bandinelli S, Guralnik J, Lauretani F, Simonsick EM, Ferrucci L (2012) Absolute strength and loss of strength as predictors of mobility decline in older adults: the InCHIANTI Study. J Gerontol A Biol Sci Med Sci 67:66–73 48. Al Snih S, Markides K, Ottenbacher K et al (2004) Hand grip strength and incident ADL disability in elderly Mexican Americans over a seven-year period. Aging Clin Exp Res 16:481–486 49. Rantanen T, Guralnik JM, Foley D, Masaki K, Leveille S, Curb JD, White L (1999) Midlife hand grip strength as a predictor of old age disability. JAMA 281:558–560 50. Taekema DG, Gussekloo J, Maier AB, Westendorp RGJ, De Craen AJM (2010) Handgrip strength as a predictor of functional, psychological and social health. A prospective population-based study among the oldest old. Age Ageing 39:331–337 51. Landi F, Liperoti R, Fusco D, Mastropaolo S, Quattrociocchi D, Proia A, Russo A, Bernabei R, Onder G (2012) Prevalence and risk factors of sarcopenia among nursing home older residents. J Gerontol A Biol Sci Med Sci 67:48–55 52. Bauer JM, Kaiser MJ, Sieber CC (2008) Sarcopenia in nursing home residents. J Am Med Dir Assoc. 9:545–551 53. von Haehling S, Anker SD (2010) Cachexia as a major underestimated and unmet medical need: facts and numbers. J Cachexia Sarcopenia Muscle. 1:1–5 54. Shaver HJ, Loper JA, Lutes RA (1980) Nutritional status of nursing home patients. J Parenter Enteral Nutr. 4:367–370
123
146 55. Alhamdan AA (2004) Nutritional status of Saudi males living in the Riyadh nursing home. Asia Pac J Clin Nutr. 13:372–376 56. Bahat G, Saka B, Tufan F, Akin S, Sivrikaya S, Yucel N, Erten N, Karan MA (2010) Prevalence of sarcopenia and its association with functional and nutritional status among male subjects in a nursing home in Turkey. Aging Male. 13:211–214 57. Masanes F, Culla A, Navarro-Gonzalez M, Navarro-Lopez M, Sacanella E, Torres B, Lopez-Soto A (2012) Prevalence of sarcopenia in healthy community-dwelling elderly in an urban area of Barcelona (Spain). J Nutr Health Aging. 16:184–187 58. Tichet J, Vol S, Goxe D, Salle A, Berrut G, Ritz P (2008) Prevalence of sarcopenia in the French senior population. J Nutr Health Aging. 12:202–206
123
Aging Clin Exp Res (2014) 26:137–146 59. Bastiaanse LP, Hilgenkamp TI, Echteld MA, Evenhuis HM (2012) Prevalence and associated factors of sarcopenia in older adults with intellectual disabilities. Res Dev Disabil 33:2004–2012 60. Reid KF, Callahan DM, Carabello RJ, Phillips EM, Frontera WR, Fielding RA (2008) Lower extremity power training in elderly subjects with mobility limitations: a randomized controlled trial. Aging Clin Exp Res. 20:337–343 61. Abe T, Mitsukawa N, Thiebaud RS, Loenneke JP, Loftin M, Ogawa M (2012) Lower body site-specific sarcopenia and accelerometer-determined moderate and vigorous physical activity: the HIREGASAKI study. Aging Clin Exp Res. 24:657–662
