European Journal of Clinical Nutrition (2015), 1–4 © 2015 Macmillan Publishers Limited All rights reserved 0954-3007/15 www.nature.com/ejcn

ORIGINAL ARTICLE

Muscle function-dependent sarcopenia and cut-off values of possible predictors in community-dwelling Turkish elderly: calf circumference, midarm muscle circumference and walking speed S Akın1, S Mucuk2, A Öztürk3, M Mazıcıoğlu4, Ş Göçer5, S Arguvanlı6 and ED Şafak7 BACKGROUND/OBJECTIVES: The aim of this study was to determine the prevalence of muscle strength-based sarcopenia and to determine possible predictors. SUBJECTS/METHODS: This is a cross-sectional population-based study in the community-dwelling Turkish elderly. Anthropometric measurements, namely body height, weight, triceps skin fold (TSF), mid upper arm circumference (MUAC), waist circumference (WC) and calf circumference (CC), were noted. The midarm muscle circumference (MAMC) was calculated by using MUAC and TSF measurement. Sarcopenia was assessed, adjusted for body mass index (BMI) and gender, according to muscle strength. Physical performance was determined by 4 m walking speed (WS; m/s). The receiver operating curve analysis was performed to determine cut-offs of CC, MAMC and 4 m WS. RESULTS: A total of 879 elderly subjects, 50.1% of whom were female, were recruited. The mean handgrip strength (HGS) and s.d. was 24.2 (8.8) kg [17.9 (4.8) female, 30.6 (7.1) male]. The muscle function-dependent sarcopenia was 63.4% (female 73.5%, male 53.2%). The muscle mass-dependent sarcopenia for CC (o 31 cm) and MAMC( o21.1 cm in males, o 19.9 cm in females) was 6.7% and 7.3%, respectively. The prevalence of low 4 m WS (≤0.8 m/s) was 81.8% (91.3% in females and 72.3% in males, respectively). We compared MAMC, CC and 4 m WS and found that AUC for 4 m WS was the best predictor of sarcopenia. CONCLUSIONS: An adequate muscle mass may not mean a reliable muscle function. Muscle function may describe sarcopenia better compared with muscle mass. The CC, MAMC and 4 m WS cut-offs may be used to assess sarcopenia in certain age groups. European Journal of Clinical Nutrition advance online publication, 18 March 2015; doi:10.1038/ejcn.2015.42

INTRODUCTION Sarcopenia is a highly prevalent condition in the elderly, which is defined as a geriatrics syndrome, and is characterised by progressive and generalized loss of skeletal muscle mass and strength. Sarcopenia leads to impaired functional status, excessive use of health care resources and increased hospitalization and mortality.1 There may be several reasons for the decrease in muscle mass from 20 to 80 years of age (~30%).2 Genetics, impaired nutritional status, decreased physical activity, hormonal changes (decline in anabolic hormones such as serum testosterone and growth hormone), increased insulin resistance, atheroscelorosis and an increase in circulating pro-inflammatory cytokine burden may be the cause of age-dependent muscle mass loss.3 According to the European Working Group on Sarcopenia in Older People (EWGSOP), the prevalence of sarcopenia is 5–13% in 60–70-year old and 11–50% after 80 years of age.1 This high variation may be related with ethnicity, geographical location, increased age and the methods of assessment and instruments used.3,4 The prevalence of sarcopenia in the community-dwelling Turkish elderly is not well documented. Researchers used different

methods and existing reports depend on the data of the elderly living in nursing homes. In a report by Halil et al.5 the muscle function-dependent sarcopenia (determined by body mass index (BMI) adjusted HGS) was 68% in the Turkish elderly living in nursing homes. Bahat et al.6 reported the prevalence of sarcopenia as 85.4% in male elderly individuals living in a nursing home, which was assessed by muscle mass detected with bioimpedance. The aim of this study was to determine the prevalence of muscle function-dependent sarcopenia (determined by BMI adjusted HGS) in the Turkish community-dwelling elderly. In addition, we planned to determine the cut-offs of independent anthropometric measurements for sarcopenia. SUBJECTS AND METHODS This is a cross-sectional population-based study in which data were extracted from the ‘Kayseri Elderly Health Study (KEHES)’. Data were collected between August 2013 and December 2013. The KEHES study protocol is described in detail elsewhere.7 We extracted data from the above-mentioned study in which the community-dwelling elderly population living in the urban area of Kayseri/Turkey was examined. At least 1% of the community-dwelling elderly population was included from a region in

1 Department of Internal Medicine, Division of Geriatrics, Erciyes School of Medicine, Erciyes University, Melikgazi, Kayseri, Turkey; 2Department of Nursing, Faculty of Health Sciences, Erciyes University, Melikgazi, Kayseri, Turkey; 3Department of Biostatistics, Erciyes School of Medicine, Erciyes University, Melikgazi, Kayseri, Turkey; 4Department of Familiy Medicine, Erciyes School of Medicine, Erciyes University, Melikgazi, Kayseri, Turkey; 5Public Health Center, Hacilar, Kayseri, Turkey; 6Department of Nursing, Faculty of Health Sciences, Melikşah University, Kayseri, Turkey and 7Department of Familiy Medicine, Erciyes School of Medicine, Erciyes University, Melikgazi, Kayseri, Turkey. Correspondence: S Akın, Department of Internal Medicine, Division of Geriatrics, Erciyes School of Medicine, Erciyes University, Melikgazi 38090, Kayseri, Turkey. E-mail: [email protected] Received 3 December 2014; revised 29 January 2015; accepted 10 February 2015

Sarcopenia prevalence in community-dwelling Turkish elderly S Akın et al

2 which 88% of the general population live in the urban area. This is one of the leading industrialized metropolitan cities in Turkey, and it receives a great deal of immigration from all the other regions of Turkey. The entire study protocol was approved by the local ethics committee and the Ministry of Health; individual consent was obtained from all the elderly participants. Height (cm) and weight (kg) were measured with the subjects wearing light clothing and no shoes, and BMI was calculated from weight and height (kg/m2). Calf circumference (CC) was measured with a non-elastic tape on the non-dominant leg, at the point of greatest circumference, in a sitting position with the knee and ankle in a right angle and the feet resting on the floor. Muscle strength was assessed by HGS with a dynamometer (Takei TKK 5401 Digital Handgrip Dynamometer, Takei, Niigata-City, Japan). HGS is a good simple measure of muscle strength and has a good correlation with lower extremity strength.1 The participants were asked to stand up and hold the dynamometer in the dominant hand with the arm flexed at 900, and the forearm was parallel to the floor, whereas the upper arm was held close to the body. Handgrip strength was expressed in kg with one decimal. The HGS score was defined as the best performance of three trials. Sarcopenia was assessed, adjusted for BMI and gender, according to muscle strength defined by Cardiovascular Health Study criteria.8 Waist circumference was measured to the nearest 1 mm at the mid level of the lower rib margin and the iliac crest, using a non-elastic tape measure, during mid-expiration. The TSF was measured (Holtain T/W Skinfold Caliper, Holtain Ltd., Crosswell, UK) with the person standing upright, at the midway level between the lateral projection of the acromion process of the scapula and the inferior margin of the olecranon process. The mean of three measurements was noted to the nearest 0.1 mm. Mid upper arm circumference was measured with the subject’s left arm flexed at 90° and the forearm parallel to the floor at the level at which the TSF measurement was carried out with a non-elastic type to the nearest 0.1 cm. Physical performance was assessed with 4 m walking speed (WS; m/s) over a 4 m course. The midarm muscle circumference (MAMC) was calculated using the following standard formula (MAMC = midarm circumference (cm) − 3.142 × TSF thickness (cm)).9 Elderly individuals who had muscle function-dependent sarcopenia according to the Cardiovascular Health Study criteria and subsequently had BMI ⩾30 kg/m2 were determined as sarcopenic obese (SO). The receiver operating curve analysis was performed both to determine the best cut-off values of CC, MAMC and 4 m WS and to assess and compare these parameters to determine sarcopenia.

RESULTS A total of 879 urban community-dwelling elderly who had handgrip data from the KEHES study were recruited. Of these, 50.1% were female. The mean age and s.d. of elderly was 71.5 (5.6) years. The means and SDs for BMI, muscle mass (CC, MAMC), fat mass (waist circumference, mid upper arm circumference, TSF) and muscle function (4 m WS) according to gender and age groups are shown in Table 1.

Table 1.

The mean HGS was measured as 24.2 (8.8) kg, and genderspecific measurements were 17.9 (4.8) kg and 30.6 (7.1) kg for females and males, respectively. The muscle function-dependent sarcopenia was 63.4% (females 73.5%, males 53.2%). The muscle mass-dependent sarcopenia for CC and MAMC was 6.7% (7.7% in females; 5.6% in males) and 7.3% (8.0% in females; 6.6% in males). The prevalence of slow 4 m WS (≤0.8 m/s) was 81.8% (91.3% in female; 72.3% in male, respectively). The prevalence of SO was 35.7% (18.9% in males, 52.4% in females). The sarcopenic but not obese elderly prevalence was 27% (34.2% in males, 21.1% in females). Comparisons of age, gender, anthropometric measurement and indices of sarcopenic and non-sarcopenic elderly are shown in Table 2. We compared MAMC, CC and 4 m WS to reveal the best predictor of sarcopenia assessed by HGS, and we found that m WS was the best (Figure 1). Receiver operating curve analysis was performed to calculate gender and age group-specific cut-offs of MAMC, CC and 4 m WS for sarcopenia (Table 3). We found that the AUCs for CC, MAMC and 4 m WS for 75 years and older were all significant in the male community-dwelling elderly. In the female elderly, the AUCs for CC ⩾ 85 years, MAMC for 60–64 years and 4 m WS ⩾ 65 years were significant. The AUCs for CC

Table 2. Comparison of age, gender, anthropometric measurement and indices of sarcopenic and non-sarcopenic elderly according to handgrip strength Characteristics

Sarcopenia

Gender Female n (%) Male n (%) Age Groups 60–64 n (%) 65–74 n (%) 75–84 n (%) ⩾ 85 n (%) CC (cm)a WC (cm)a MUAC (cm)a TSF (cm)a BMI (kg/m2)a MAMC (cm)a 4 m WS (m/s)a

Non-sarcopenia

324 (73.5) 233 (53.2) 17 339 189 12 36.0 102.0 30.1 21.9 30.8 23.32 1.39

117 (26.5) 205 (46.8)

(50.0) (57.4) (79.7) (70.6) (4.2) (13.8) (3.9) (10.1) (5.6) (2.86) (0.8)

17 252 48 5 37.6 103.9 30.7 18.9 30.1 24.8 1.03

(50.0) (42.6) (20.3) (29.4) (8.7) (11.1) (3.7) (9.3) (4.7) (3.1) (0.6)

P-value o0.001

o0.001

o0.001 0.040 0.017 o0.001 0.048 0.064 o0.001

Abbreviations: BMI, body mass index; CC, calf circumference; MAMC, midarm muscle circumference; MUAC, mid upper arm circumference; TSF, triceps skin fold; WC, waist circumference; 4 m WS, 4 m walking speed. a mean (s.d).

BMI, anthropometrics measurements, fundemental determinants of sarcopenia according to gender and age groups Female (n = 440)

Variables Age groups 2 a

BMI (kg/m ) WC (cm)a MUAC (cm)a TSF (mm)a MAMC (cm)a CC (cm)a 4 m WS (m/s)a

Male (n = 439)

60–64 years

65–74 years

75–84 years

⩾ 85 years

60–64 years

65–74 years

75–84 years

⩾ 85 years

33.7 106.6 32.7 30.5 23.1 37.5 1.0

32.9 104 31.8 28.3 22.9 37.7 0.8

31.2 101.4 30.1 25.7 22.2 35.3 0.9

28.8 95.2 26.9 20.1 20.6 34.6 1.0

28.6 100.5 29.6 13.7 25.3 36.0 0.6

28.9 102.9 29.9 13.8 25.6 26.6 0.6

27.9 100.4 28.1 13.3 23.9 34.9 0.8

25.8 95.0 27.7 13.0 23.6 33.7 0.9

(4.9) (10) (2.4) (5.5) (1.7) (4.3) (0.0)

(5.3) (13.1) (3.7) (7.3) (2.7) (9.1) (0.3)

(5.2) (15.9) (3.7) (9.3) (2.7) (4.1) (0.1)

(3.7) (8.2) (3.9) (4.2) (4.1) (2.4) (0.0)

(4.0) (7.5) (1.5) (5.3) (1.6) (2.6) (0.4)

(4.3) (12.4) (3.6) (6.0) (2.9) (3.5) (0.4)

(4.6) (11.9) (3.0) (5.9) (2.3) (3.2) (0.3)

(5.9) (15.5) (4.3) (6.5) (2.7) (4.7) (0.3)

Abbreviations: BMI, body mass index; CC, calf circumference; MAMC, midarm muscle circumference; MUAC, mid upper arm circumference; TSF, triceps skin fold; WC, waist circumference; 4 m WS, 4 m walking speed. amean (s.d).

European Journal of Clinical Nutrition (2015) 1 – 4

© 2015 Macmillan Publishers Limited

Sarcopenia prevalence in community-dwelling Turkish elderly S Akın et al

⩾ 85 years, MAMC for 60–64 years and 4 m WS ⩾ 75 years in females were confirmed by the Youden index (40.4). In males, AUCs for CC and MAMC ⩾ 85 years and 4 m WS for 60–64 years and ⩾ 85 years were confirmed by the Youden index (40.4).

100

80

Sensitivity

60

40

MAMC (cm) CC (cm) 4mWS (sec)

20

0 0

20

40 60 100-Specificity

80

100

Figure 1. Comparison of MAMC, CC and 4 m WS curves, which explains sarcopenia assessed by BMI adjusted handgrip strength. AUC for MAMC 0.646 (0.612–0.679), CC 0.575 (0.540–0.610) and 4 m WS 0.683 (0.650–0.715).

Table 3.

DISCUSSION In the present study, we determined the muscle mass-dependent sarcopenia in the urban community-dwelling Turkish elderly. The prevalence of sarcopenia was detected as 63.4% by HGS, 7.3% by MAMC, 6.7% by CC and 81.8% by 4 m WS. This is the first and relatively comprehensive study in community-dwelling Turkish elderly, which determines muscle function-dependent sarcopenia. The prevalences of muscle function-dependent sarcopenia (HGS, 4 m WS) are significantly higher compared with the prevalence of sarcopenia depending on muscle mass (CC and MAMC). There is a strong correlation between MAMC and DXA in the accurate assessment of lean mass.10 MAMC is proposed as a useful indicator of nutritional status and muscle mass. Measurement of MAMC can be easily performed by most clinicians as it requires minimal undressing and easy calculation (MAMC = midarm circumference (cm) − 3.142 × TSF thickness (cm)). In addition, it is less susceptible to distortion by fluid retention as edema in the lower extremities is more common.11 However, lymphoedema, generalized edema or extreme obesity in the upper extremities may lead to overestimation. According to the description by Landi et al.12 we classified low muscle mass as MAMC o 21.1 and 19.2 cm in males and females, respectively. We found that MAMC cut-offs were significant in early (60–64 years) elderly for females but in late (⩾85 years) elderly for males, and the corresponding cut-offs were 23.3 and 23.8 in females and males, respectively. In a comparison of our data with those of Landi et al.12 our cut-offs for MAMC are higher by 43 cm. We consider that the cause of this difference may either be the result of significant difference in BMI (~5 kg/m2 high in our study) or the method of calculating the MAMC cut-off for sarcopenia. Landi et al.12 describe sarcopenia as MAMC less than the first tertile, which is a very broad range. In our study, we calculated age groups and gender adjusted cut-offs, which were comfirmed by the Youden index. Therefore, we may

ROC analysis for sarcopenia to detect CC, MAMC and 4 m WS cut-offs in community-dwelling Turkish elderly

Gender Female CC

MAMC

4 m WS

Male CC

MAMC

4 m WS

Age groups

AUC (95% CI)

Cut-off

Sensitivity (95% CI)

Specificity (95% CI)

60–64 65–74 75–84 ≥ 85 60–64 65–74 75–84 ⩾ 85 60–64 65–74 75–84 ⩾ 85

0.479 0.578 0.558 0.800 0.808 0.565 0.528 0.500 0.517 0.626 0.695 0.600

(0.265–0.699) (0.521–0.634) (0.456–0.566) (0.367–0.974) (0.596–0.902) (0.507–0.622) (0.422–0.632) (0.143–0.857) (0.297–0.732) (0.570–0.681) (0.594–0.784) (0.207–0.910)

41.4 40.2 32.0 33.6a 23.3a 24.7 23.9 19.8 1.09 1.01b 1.36a 1.6a

30.0 81.6 82.0 60 90 79.6 81.4 40 30 68.5 51.76 40

(7.0–65.2) (75.9–86.6) (72.5–89.4) (15.4–93.5) (55.5–98.5) (73.6–84.8) (71.3–89.2) (6.5–84.6) (7.0–65.2) (61.9–74.7) (40.7–62.7) (6.5–84.6)

100 31.8 46.1 100 66.6 33.7 33.3 100 91.6 56.6 92.3 100

(73.4–100) (22.3–42.6) (19.3–74.8) (19.3–100) (34.9–89.9) (23.9–44.7) (10.1–65.1) (19.3–100) (61.5–98.6) (45.8–67.1) (63.9–98.7) (19.3–100)

60–64 65–74 75–84 ⩾ 85 60–64 65–74 75–84 ⩾ 85 60–64 65–74 75–84 ⩾ 85

0.586 0.583 0.630 0.619 0.533 0.597 0.614 0.619 0.700 0.651 0.633 0.619

(0.279–0.848) (0.523–0.642) (0.543–0.712) (0.279–0.887) (0.226–0.823) (0.533–0.658) (0.523–0.699) (0.279–0.887) (0.380–0.917) (0.592–0.707) (0.545–0.716) (0.279–0.887)

36.6 33.4 36.4b 29.9a 24.9 24.7 23.8b 21.0a 0.71a 0.92b 1.09b 0.93a

71.4 26.2 76.0 42.8 66.6 45.0 53.7 42.8 85.7 58.8 48.4 42.8

(29.3–95.5) (18.6–35.2) (66.4–84.0) (10–81) (22.7–94.7) (35.6–54.8) (43.1–64.2) (10–81) (42.2–97.6) (49.4–67.8) (38.2–58.8) (10–81)

60 89.3 48.5 100 60 73.2 71.8 100 60 66.4 77.1 100

(15.4–93.5) (83.5–93.7) (31.4–66.0) (35.5–100) (15.4–93.5) (65.2–80.3) (53.3–86.2) (35.5–100) (15.4–93.5) (58.5–73.8) (59.9–89.5) (35.5–100)

Abbreviations: CC, calf circumference; MAMC, midarm muscle circumference; ROC, receiver operating curve; 4 m WS, 4 m walking speed. aYouden index 40.4. b Youden index o0.4.

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European Journal of Clinical Nutrition (2015) 1 – 4

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Sarcopenia prevalence in community-dwelling Turkish elderly S Akın et al

4 propose that muscle strength adjusted cut-offs for MAMC may be different and more informative compared with MAMC cut-offs derived from tertiles.12 CC is an another measure to estimate muscle mass primarily in the elderly population. It is a simple and easy to use method that can be used to detect sarcopenia both in clinical use and in population-based studies. The CC of less than 31 cm was proposed by Rolland et al.13 as the best clinical indicator of sarcopenia in a female sample that was associated with disability. As their study was conducted with females, it may be difficult to use this measurement for male gender. We consider that gender and age group adjusted CC should be used, as we did in the evaluation of MAMC. This consideration is supported by several other studies, in which years there were significant differences in anthropometric measurements at 60–64, 65–69, 70–74, 75–79 and ⩾ 80 years.14,15 In addition, age-related loss in muscle mass is well known.2 Because of this we analyzed our study group into four age groups (60–64, 65–74, 75–84, ⩾ 85 years) for each gender. We could only find significant cut-offs (AUC40.600) for CC in ⩾ 85-year-old females and ⩾ 75-year-old males elderly. Therefore, we can conclude that CC can be used as a marker of sarcopenia primarily in the late elderly community-dwelling Turkish population (Table 3). Cut-offs for CC can also be calculated according to muscle mass as in the study by Kawakami et al.16 They calculated CC cut-offs to predict sarcopenia as 34 cm (sensitivity 88%, specificity 91%) in male and 33 cm (sensitivity 76%, specificity 73%) in female elderly. When comparing the study by Kawakami et al.16 and our study, the CC cut-offs determined by muscle mass and muscle strength are similar. The broad age range (40–89 years) in the study of Kawakami et al.16 may be the cause of relatively high CC cut-offs. In addition, age-related reduction in muscle mass may lead age group-related alterations. The unique study, which was conducted by Halil et al.5 in our elderly population living in nursing homes, provides the CC cut-off as 35 cm, but it is neither gender nor age group specific; hence, it is difficult to compare with our results. The cross-sectional character of our study may be considered as a limitation. In interpretation of relatively high CC we may conclude that the magnitude of CC may be influenced by SO. The prevalences of SO in females and males were significantly different (71.3% vs. 35.6%). Then, we consider that in evaluation of muscle functiondependent sarcopenia gender-specific assesment is essential for community-dwelling elderly. There is a significant difference between muscle mass (CC and MAMC) and muscle function (HGS and 4 m WS)-based sarcopenia prevalence. Muscle mass-based sarcopenia assessment is several times lower compared with muscle function-based assessment. Therefore, we can conclude that muscle function is a much more definitive parameter to assess sarcopenia. An adequate muscle mass may not mean a reliable muscle function and both gender

European Journal of Clinical Nutrition (2015) 1 – 4

and age group adjusted evaluation would lead to a much more precise assessment for sarcopenia. CONFLICT OF INTEREST The authors declare no conflict of interest.

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Muscle function-dependent sarcopenia and cut-off values of possible predictors in community-dwelling Turkish elderly: calf circumference, midarm muscle circumference and walking speed.

The aim of this study was to determine the prevalence of muscle strength-based sarcopenia and to determine possible predictors...
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