J Endocrinol Invest DOI 10.1007/s40618-013-0011-3

ORIGINAL ARTICLE

Sarcopenia and sarcopenic obesity and their association with dyslipidemia in Korean elderly men: the 2008–2010 Korea National Health and Nutrition Examination Survey S. J. Baek • G. E. Nam • K. D. Han • S. W. Choi • S. W. Jung A. R. Bok • Y. H. Kim • K. S. Lee • B. D. Han • D. H. Kim



Received: 11 May 2013 / Accepted: 17 November 2013 Ó Italian Society of Endocrinology (SIE) 2013

Abstract Background Recently, aging has been shown to be associated with sarcopenic obesity (SO), of which decreased muscle mass and increased fat mass are features. Sarcopenia and obesity alone are known to be associated with abnormal lipid metabolism. However, it remains unclear whether SO has greater adverse effects on dyslipidemia than on sarcopenia or obesity alone. Aim We aimed to investigate the association between SO and dyslipidemia in elderly Koreans. Subjects and methods This study was based on data collected during the 2008–2010 Korea National Health and Nutrition Examination Survey. We included 1,466 men and 2,017 women aged 65 years and over. Sarcopenia was indicated in participants with height- or weight-adjusted S. J. Baek and G. E. Nam authors contributed equally to this work. S. J. Baek  G. E. Nam  S. W. Choi  S. W. Jung  A. R. Bok  Y. H. Kim  B. D. Han  D. H. Kim Department of Family Medicine, Korea University College of Medicine, Seoul, South Korea K. D. Han Department of Biostatistics, Catholic University College of Medicine, Seoul, South Korea K. S. Lee Department of Family Medicine, Wonkwang University Sanbon Hospital, Wonkwang University College of Medicine, 1142, 1126-1 Sanbon-dong, Gunpo-si, Gyeonggi-do 435-040, South Korea D. H. Kim (&) Department of Family Medicine, Korea University Ansan Hospital, Korea University College of Medicine, 516 Gojan-dong, Danwon-gu, Ansan-si, Gyeonggi-do 425-707, South Korea e-mail: [email protected]

appendicular skeletal muscle that was 1 standard deviation below the sex-specific mean for the young reference group, and obesity was defined as a body mass index C25 kg/m2. Dyslipidemia was defined according to the National Cholesterol Education Program-Adult Treatment Panel III. Results After adjusting for confounding factors, the SO group had a higher risk for dyslipidemia [odds ratio (OR) 2.82 (95 % confidence interval 1.76–4.51)] than the obese group [2.12 (1.11–4.07)] and sarcopenic group [1.46 (1.01–2.11)] (p \ 0.001) only in men. Furthermore, the SO group in men had the highest OR for hypercholesterolemia, hypertriglyceridemia, hypo-high-density lipoprotein cholesterolemia, hyper-low-density lipoprotein cholesterolemia, and a high ratio of triglyceride to high-density lipoprotein cholesterol even after further adjustments. Conclusions In Korean elderly men, SO was associated with an increased risk for dyslipidemia compared with sarcopenia or obesity alone. Keywords Sarcopenia  Obesity  Sarcopenic obesity  Dyslipidemia Abbreviations ASM Appendicular skeletal muscle BMI Body mass index DBP Diastolic blood pressure FBG Fasting blood glucose HDL-C High-density lipoprotein cholesterol HOMA-IR Homeostasis model assessment of insulin resistance Ht Height KNHANES Korea National Health and Nutrition Examination Survey LDL-C Low-density lipoprotein cholesterol SBP Systolic blood pressure

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SO TC TG WC Wt

Sarcopenic obesity Total cholesterol Triglyceride Waist circumference Weight

2008–2010 Korea National Health and Nutrition Examination Survey (KNHANES).

Materials and methods Overview of survey and study participants

Introduction Currently, with the extension of the average lifetime span, the elderly population is rapidly increasing in Korea. Furthermore, due to a westernized diet and decreased physical activity, the prevalence of metabolic syndrome (MetS) has dramatically increased in recent years [1]. Thus, the prevention of risk factors for cardiovascular diseases (CVD) such as obesity and dyslipidemia has become an important challenge for the elderly Korean population [2]. Aging is associated with decreased muscle mass or strength, known as sarcopenia, and increased fat mass even in the absence of significant changes to the body mass index (BMI) [3]. A combination of both obesity and sarcopenia, recently termed ‘‘sarcopenic obesity (SO)’’, may potentiate each other and have greater synergistic effects on health outcomes, including physical disability, metabolic disorders, and CVD, than either sarcopenia or obesity alone [4– 6]. Previous studies have hypothesized that the loss of muscle mass leads to a reduction in both the resting metabolic rate and physical activity, leading to an increase in fat based on positive energy balance. This fat gain causes further loss of muscle mass by protein catabolism directly via cytokines such as leptin and tumor necrosis factor (TNF), and indirectly via insulin resistance [7]. Therefore, both obesity and sarcopenia should be considered together in the elderly population, and SO is an important issue that should be addressed in the elderly Korean population to minimize age-related chronic health problems. Despite the growing importance of sarcopenia and SO, studies evaluating the prevalence of sarcopenia and SO are limited, and have been performed only in Caucasian populations. Moreover, there are few reports about the relationship between SO and metabolic disorders. Several studies have attempted to investigate the relationship among sarcopenia, SO, MetS [6, 8, 9] and CVD risk factors [10], but findings have varied according to the reference group, how sarcopenia was defined in the study and the study population. Furthermore, a limited number of studies have examined the effect of sarcopenia and SO on lipid profiles and the prevalence of dyslipidemia in elderly Koreans. Therefore, this study aimed to investigate the prevalence of sarcopenia and SO and their association with the risk for dyslipidemia in elderly Koreans. We used data from the

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This study was based on data collected from the 2008–2010 KNHANES. The KNHANES consists of a health interview survey, a nutrition survey, and a health examination survey. The sample was selected using a stratified, multistage cluster sampling design with proportional allocation based on the National Census Registry. In total, 9,307, 10,078, and 8,473 individuals participated in the health interviews and health examination surveys in 2008, 2009, and 2010, respectively. Of these, the body compositions of 3,583, 7,920, and 7,043 participants in 2008, 2009, and 2010, respectively, were assessed using dualenergy X-ray absorptiometry (DXA). This study analyzed the data from 1,466 men and 2,017 women aged C65 years whose body compositions were examined. All participants in this survey provided written informed consent, and the institutional review board of the Korea Centers for Disease Control and Prevention approved the study protocol. Description of demographic variables The demographic variables that were expected as confounding factors in this study were age, education level, household income level, alcohol consumption, smoking status, physical activity, sleep duration, and daily energy (caloric) and fat intakes. Education level was categorized as less than a high school diploma or high school diploma and higher. Household income level was assessed according to the equivalized gross household income per month (equivalized income was calculated as the household income divided by the number of individuals in the family) and grouped into quartiles. Subjects were categorized into two groups based on the frequency of drinking over the past year: nondrinkers, less than once a month; drinkers, once or more a month. If the subjects had any history of cigarette smoking, they were considered ever-smokers; never-smokers were subjects who had never smoked. Subjects who exercised moderately more than five times weekly for [30 min per session or who exercised vigorously more than three times weekly for [20 min per session were defined as regular exercisers. Anthropometric measurements Height (Ht) and weight (Wt) were measured with the subject wearing light clothing but no shoes. The BMI was

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calculated as Wt (kg) divided by the squared Ht (m2). Waist circumference (WC) was measured midway between the inferior margin of the lowest rib and the iliac crest on a horizontal plane. Blood pressure (BP) was measured with a mercury sphygmomanometer (Baumanometer; WA Baum Co., Inc., Copiague, NY, USA) after the subject had rested for 5 min in a seated position. Biochemical measurements Blood samples were collected in the morning after an at least 8-h fasting and transported in cold storage to the central testing institute in a certified laboratory on the same day. Serum total cholesterol (TC), triglyceride (TG), highdensity lipoprotein cholesterol (HDL-C), and fasting blood glucose (FBG) were measured with a Hitachi Automatic Analyzer 7600 (Hitachi, Tokyo, Japan) using enzymatic methods with commercially available kits (Daiichi, Tokyo, Japan). The level of low-density lipoprotein cholesterol (LDL-C) was calculated using Friedewald’s formula in subjects with a TG level B400 mg/dL, and was measured directly using commercially available kits (CholestestÒ LDL; Sekisui Medical, Tokyo, Japan) when the TG level [400 mg/dL. The level of non-HDL-C was calculated as TC minus HDL-C, and high levels of non-HDL-C were defined as C160 mg/dL [11]. In addition, the ratio of TG to HDL-C was used as a measure of dyslipidemia because a ratio [3.8—is known to correlate with LDL-C phenotype B, which is a reliable predictor of CVD risk [12]. The TC/ HDL-C ratio was calculated and high levels were defined as a ratio C4, which could predict the occurrence of CVD events better than any other lipid profiles measurements [13]. Insulin levels were determined using a gamma counter (1470 Wizard, Perkin Elmer) with an immunoradiometric assay using an INS-IRMA kit (Biosource, Belgium). The homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as fasting insulin (lU/mL) 9 FBG (mg/dL)/405 [14]. Insulin resistance was defined as a value greater than the 75th percentile of the HOMA-IR [15]. Additionally, MetS was defined using the National Cholesterol Education Program Adult Treatment Panel III (NCEP/ATP III) criteria [16]. The cutoff established for Korean adults, as proposed by ‘‘The Korean Society for the Study of Obesity’’, was adopted for the criterion of abdominal obesity [17]. Subjects with three or more of the following parameters were considered as having MetS: (1) WC C90 cm for men and C85 cm for women, (2) TG level C150 mg/dL, (3) HDL-C level \40 mg/dL for men and \50 mg/dL for women, (4) systolic BP (SBP) or diastolic BP (DBP) C130/85 mmHg or use of antihypertensive medication, (5) FBG C100 mg/dL or the use of diabetic medication.

Definition of sarcopenia, obesity, sarcopenic obesity and dyslipidemia Several definitions of sarcopenia have been proposed in Western countries. This study used the Ht-adjusted appendicular skeletal muscle mass (ASM) and Wt-adjusted ASM [18, 19]. DXA (Lunar Corp., Madison, WI, USA) was used to measure body composition. ASM was calculated as the sum of muscle mass in both arms and legs, assuming that all non-fat and non-bone tissue was skeletal muscle. The sex-specific mean and standard deviation (SD) of the ASM/Ht2 and ASM/Wt 9 100 of the young reference group (healthy men and women aged 20–39 years) were used as the cutoff values of sarcopenia. Of 5,343 participants aged 20–39 years, 1,151 were excluded based on a history of diabetes, stroke, coronary artery diseases, thyroid disease, arthritis, osteoporosis, tuberculosis, asthma, chronic obstructive lung disease, liver cirrhosis, or any cancer [5]. The remaining 4,192 individuals made up the young reference group. Subjects with Ht- or Wtadjusted ASM more than 1 SD below the sex-specific mean of the young reference group were placed in the normal group. Sarcopenia was indicated in subjects whose Ht- or Wt-adjusted ASM was 1 SD below the mean of the young reference group [6, 19]. Obesity was defined as a BMI C25 kg/m2 according to the Asia-Pacific Guidelines [20]. We first classified the subjects as sarcopenic or non-sarcopenic. The subjects were further classified into sarcopenic obesity (SO group), sarcopenic non-obesity (sarcopenia group), non-sarcopenic obesity (obesity group), and non-sarcopenic non-obesity (normal group). Dyslipidemia was defined as the presence of C1 of the following abnormal lipid profiles: hypercholesterolemia, hypo-HDL-cholesterolemia, hyper-LDL-cholesterolemia, or hypertriglyceridemia, according to the NCEP/ATP III criteria [16, 21]. Hypercholesterolemia was defined as: (1) TC level C240 mg/dL from a fasting blood test, (2) use of lipid-lowering drugs, or (3) physician-diagnosed dyslipidemia. HDL-C levels \40 mg/dL were defined as hypoHDL-cholesterolemia. Hyper-LDL-cholesterolemia was defined as: (1) LDL-C level [160 mg/dL, (2) the use of lipid-lowering drugs, or (3) physician-diagnosed dyslipidemia. Hypertriglyceridemia was defined as a TG level C200 mg/dL. Statistical analysis Statistical analyses were performed using SAS version 9.2 for Windows (SAS Institute, Cary, NC, USA) and twosided p \ 0.05 was considered statistically significant. As per the SAS survey procedure, all statistical values generated in this study used weighted stratified variables for

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sampling. The cutoff values of sarcopenia were calculated according to the previously described definitions. Data are expressed as mean ± standard error (SE) for continuous variables and as percentages (SE) for categorical variables. Differences in anthropometric parameters and cardiovascular risk factors were compared by Student’s t test. The v2 test was used to investigate differences in the prevalence of dyslipidemia. Pearson’s partial correlation analysis adjusting for age was used to determine the relationship between lipid profiles and ASM, ASM/Ht2, and ASM/Wt. One-way analysis of covariance (ANCOVA) was used to determine the adjusted mean ± SE of each lipid measurement according to body composition status. TG levels were analyzed after logarithmic transformation to improve normality. Multivariate logistic regression models were used to compare the prevalence, adjusted odds ratio (OR), and 95 % confidence interval (CI) of dyslipidemia among body composition categories after adjusting for potentially confounding variables. Multivariate analyses of the prevalence and adjusted ORs of dyslipidemia were first adjusted for age (model 1) and then age plus WC (model 2). Model 3 was adjusted for the variables in model 2 plus education level, household income, smoking status, alcohol consumption, physical activity, total energy intake, and fat intake (%). Additionally, the ORs and 95 % CIs for insulin resistance according to the HOMA-IR across body composition groups were calculated using logistic regression analysis after adjusting for identical confounding variables.

Results This study enrolled 1,466 men and 2,017 women aged C65 years, with a mean age of 71.8 years in men and 72 years in women. The cutoff values of sarcopenia were 6.96 kg/m2 for men and 4.96 kg/m2 for women according to the Ht-adjusted definition and 30.65 % for men and 23.9 % for women per the Wt-adjusted definition (Fig. 1). According to the Ht-adjusted definition, the prevalence of sarcopenia was 43 and 46.6 % per the Wt-adjusted definition for men, and 9.9 and 44.7 % for women, respectively. The prevalence of SO was 2.6 % in men and 1.6 % in women with sarcopenia as defined using ASM/Ht2, but 18.3 % in men and 26.6 % in women when sarcopenia was defined using ASM/Wt. Approximately, 44.7 % of men and 85.4 % of women defined as sarcopenic using ASM/ Wt had central obesity. The general characteristics of the subjects, categorized according to body composition status using two different methods, are detailed in Table 1. When sarcopenia was defined using ASM/Ht2, the obese group had a higher BMI than the other groups both in men and women. However,

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when sarcopenia was defined using ASM/Wt, the SO group had the highest BMI, WC, HOMA-IR, total body fat mass in both sexes. The prevalence of MetS was highest in the SO group in both sex groups regardless of how sarcopenia was defined (p \ 0.001). When sarcopenia was defined using ASM/Wt, total energy intake was highest in the obese group (p \ 0.001), but the proportion of fat in total energy intake was highest in the SO group both in men and women (p \ 0.001 in men and p = 0.032 in women). Table 2 presents the age-adjusted Pearson’s correlations between the anthropometric and biochemical measurements and ASM, ASM/Ht2, and ASM/Wt. ASM and ASM/ Ht2 were positively correlated with BMI, WC, DBP, insulin, and the HOMA-IR, while ASM/Wt was negatively correlated with these variables in both sexes. Furthermore, in contrast to ASM/Ht2, ASM/Wt showed significantly negative association with the level of TC, LDL-C, TG, non-HDL-C, and the TG/HDL-C and TC/HDL-C ratios, and positively correlated with HDL-C both in men and women. Table 3 lists the multivariate-adjusted mean levels of various dyslipidemic parameters according to body composition status. HDL-C and TG levels in men and TG level in women were significantly correlated with decreased muscle mass and increased fat mass (p \ 0.001). Additionally, when sarcopenia was defined by ASM/Wt, nonHDL-C, and the TG/HDL-C and TC/HDL-C ratios increased significantly with decreased muscle mass and increased fat mass in both sex groups. Table 4 presents the prevalence and ORs for dyslipidemia and parameters of dyslipidemia in the sarcopenia, obesity, and SO groups compared to the normal group after adjusting for the different confounders. The prevalence of dyslipidemia and all dyslipidemic parameters exhibited trends for increase with decreased muscle mass and increased BMI in men. In women, the prevalence of dyslipidemia and hypercholesterolemia, hyper-LDL-cholesterolemia, hypertriglyceridemia, high TG/HDL-C ratio and high TC/HDL-C ratio showed increasing trends. In men, the SO group had the highest OR for dyslipidemia among the four groups in model 1. The results were maintained after additional adjustment for WC (model 2), which is one of the most important confounding factors for dyslipidemia. Adjustment for additional confounding factors such as smoking status, alcohol consumption, physical activity, and total energy and fat intake did not change the results (p \ 0.001). The adjusted ORs for high TG/HDL-C ratio were significantly increased with decreased muscle mass and increased BMI even after further adjustments (p \ 0.001). Additionally, the SO group had the highest ORs for hypercholesterolemia, hypo-HDL-cholesterolemia and hypertriglyceridemia in all models, and for hyperLDL-cholesterolemia in model 1 and model 2. However,

J Endocrinol Invest Fig. 1 Cutoff values of sarcopenia based on the young reference group and the prevalence of sarcopenia defined using ASM/Wt and ASM/Ht2. The sex-specific mean and SD of the ASM/Ht2 and ASM/Wt 9 100 of the young reference group (healthy men and women aged 20–39 years) were used to establish the cutoff values of sarcopenia. Sarcopenia was defined as Ht- or Wt-adjusted ASM 1 SD below the sexspecific mean of the young reference group. In the young reference group, the mean Htadjusted ASM was 7.79 kg/m2 in men 5.6 kg/m2 in women and the mean Wt-adjusted ASM was 33.5 % in men and 26.3 % in women. The cutoff values of sarcopenia were determined as 6.96 kg/m2 for men and 4.96 kg/m2 for women according to the Ht-adjusted definition and 30.65 % in men and 23.9 % in women according to the Wt-adjusted definition. Using the Ht-adjusted definition, the prevalence of sarcopenia was 43 % for men and 9.9 % for women; that using the Wt-adjusted definition was 46.6 % for men and 44.7 % for women

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123 164 ± 0.3 61.0 ± 0.38

67.9 (2.1) 84.9 (1.6) 23.6 (2.1) 6.7 ± 0.07 164 ± 0.2 58.0 ± 0.35 21.3 ± 0.1 79.4 ± 0.3 126. 0 ± 0.9

Alcohol drinker (%)

Ever-smoker (%) Regular exerciser (%)

Sleep duration (h)

Ht (cm)

Wt (kg)

BMI (kg/m2)

WC (cm)

SBP (mmHg)

26.9 (2.3)

182.3 ± 2.2 110.2 ± 2.2

7.9 ± 0.1 2.0 ± 0.05 177.6 ± 1.4

Insulin (mIU/L)

HOMA-IR

TC (mg/dL)

73.9 ± 0.6

138.7 ± 2.2

N

Women 928

19.2 ± 0.1

ASM (kg)

14.5 ± 0.2

10.0 ± 0.2 40.9 ± 0.2

Total body fat mass (kg)

Skeletal muscle mass (kg)

26.0 (0.2)

18.7 (0.2)

Total body fat (%)

1,746.3 ± 35

329

17.6 ± 0.1

39.1 ± 0.3

12.6 (0.4)

1,923.0 ± 37 11.7 (0.2)

Total energy (kcal/day)

41 (2.9)

147.5 ± 5.2 3.7 ± 0.1

Fat (% of energy)

131.0 ± 1.4 23.7 (2)

Non-HDL-C (mg/dL)

3.9 ± 0.04

TC/HDL-C ratio

Metabolic syndrome (%)

4.3 ± 0.07

126.2 ± 4.2 3.0 ± 0.1

TG (mg/dL) TG/HDL-C ratio

47.2 ± 0.7

106.7 ± 1.4 50.7 ± 0.5

LDL-C (mg/dL)

HDL-C (mg/dL)

2.6 ± 0.1

9.6 ± 0.3

109.3 ± 1.9

73.4 ± 0.4 100 ± 0.9

DBP (mmHg)

FBG (mg/dL)

128.1 ± 1.2

84.5 ± 0.3

22.5 ± 0.1

6.6 ± 0.10

83.8 (1.9) 15.7 (2.2)

60.7 (2.8)

8.2 (1.7)

28.4 (2.2) 8.6 (1.4)

73.1 ± 0.3

415

Education (Chigh school, %)

71.5 ± 0.2

Age (year)

Sarcopenia

Income (highest quartile, %)

708

N

Men

Normal

Sarcopenia defined by ASM/Wt

250

23.3 ± 0.2

48.8 ± 0.5

15.4 ± 0.2

23.2 (0.3)

12.9 (0.7)

2,174.6 ± 90

62 (5.8)

138.9 ± 3.0

4.5 ± 0.13

155.4 ± 12 4.2 ± 0.4

44.3 ± 1.5

110.5 ± 3.1

180.1 ± 3.1

2.8 ± 0.1

10.8 ± 0.5

105.2 ± 2.1

75.6 ± 1.0

126.9 ± 1.6

92.0 ± 0.4

26.2 ± 0.1

72.2 ± 0.64

165 ± 0.6

6.7 ± 0.18

73.4 (5.5) 38.6 (6.2)

66.9 (5.3)

17 (5)

26 (5)

69.5 ± 0.4

101

Obesity

510

20.8 ± 0.1

46.1 ± 0.4

19.8 ± 0.2

29.1 (0.2)

14.4 (0.5)

1,892.2 ± 46

74.7 (3.2)

143.2 ± 2.6

4.7 ± 0.08

169.9 ± 7.4 4.6 ± 0.2

43.4 ± 0.7

110.8 ± 2.6

183.6 ± 2.7

3.3 ± 0.1

12.3 ± 0.4

109.4 ± 1.9

94.8 ± 0.4

130.3 ± 1.2

94.8 ± 0.4

27.1 ± 0.1

74.1 ± 0.49

165 ± 0.3

6.8 ± 0.12

79.3 (3.4) 23.9 (3.4)

63.2 (4.2)

15.5 (3)

44.1 (3.8)

71.4 ± 0.3

242

SO

20.5 ± 0.1

\0.001

1,105

11.9 ± 0.2 43.4 ± 0.2

\0.001

20.6 (0.3)

\0.001 \0.001

1,989.1 ± 37 12.2 (0.4)

\0.001 \0.001

136.2 ± 1.7 33.1 (2.4)

4.2 ± 0.1

\0.001 \0.001

135.6 ± 4.7 3.3 ± 0.1

\0.001 \0.001

\0.001

110.5 ± 1.8 48.9 ± 0.5

0.27 \0.001

181.3 ± 1.7

8.6 ± 0.2 2.2 ± 0.1

\0.001 \0.001 0.1

74.5 ± 0.5 102.6 ± 1.1

0.004 \0.001

127.2 ± 1

84 ± 0.3

\0.001 0.03

23 ± 0.1

62.8 ± 0.3

\0.001 \0.001

165.3 ± 0.3

6.7 ± 0.1

83.5 (1.9) 24.3 (2.4)

69.3 (2.5)

0.09

0.34

0.07 \0.001

0.23

8.9 (1.6)

30 (2.6)

\0.001 0.02

70.7 ± 0.2

517

Normal

152

17.1 ± 0.1

37.4 ± 0.2

11.5 ± 0.2

22.2 (0.4)

12.1 (0.3)

1,738.8 ± 34

27.3 (2.4)

131.7 ± 1.9

4.1 ± 0.1

132.5 ± 4.4 3.2 ± 0.1

50 ± 0.6

105.7 ± 1.8

177.6 ± 1.8

2.3 ± 0.1

8.6 ± 0.2

105.3 ± 1.5

72.9 ± 0.6

126.5 ± 1

79 ± 0.4

20.8 ± 0.1

56 ± 0.4

163.8 ± 0.3

6.7 ± 0.1

85.3 (1.7) 17.5 (1.9)

61.6 (2.4)

8 (1.4)

25.9 (2.2)

73.5 ± 0.3

606

Sarcopenia

Sarcopenia defined by ASM/Ht2

\0.001

p*

730

21.8 ± 0.2

47.2 ± 0.3

18.5 ± 0.3

27.2 (0.3)

14.2 (0.5)

1,993.6 ± 48

70.7 (2.9)

140.7 ± 2.2

4.6 ± 0.1

166.3 ± 6.6 4.5 ± 0.2

43.7 ± 0.7

109.1 ± 2.1

181.3 ± 2.2

3.1 ± 0.1

11.7 ± 0.4

107.5 ± 1.6

76.2 ± 0.6

129.3 ± 1

94 ± 0.4

27 ± 0.1

73.9 ± 0.4

165.4 ± 0.3

6.9 ± 0.1

77.8 (3.1) 28.5 (3.3)

65 (3.5)

17.7 (3)

42.3 (3.3)

70.8 ± 0.3

311

Obesity

Table 1 Demographic and clinical characteristics of subjects according to body composition as defined by ASM/Wt or ASM/Ht2 in the 2008–2010 KNHANES

30

18.2 ± 0.4

41.6 ± 0.8

20.2 ± 0.6

31.1 (0.7)

12.5 (1.3)

1,726.1 ± 90

77.5 (9.5)

153.8 ± 8

4.9 ± 0.3

163.5 ± 22 4.5 ± 0.8

43.9 ± 2

126.4 ± 8.7

194.6 ± 7.8

4 ± 0.4

14.1 ± 1.6

115.3 ± 5

75.8 ± 1.6

129.8 ± 2.9

95.7 ± 1

26.4 ± 0.4

71.8 ± 1.3

164.7 ± 1.0

6.4 ± 0.3

78.2 (7.3) 19.5 (6.8)

57.2 (12)

1.2 (1.3)

18.2 (7.3)

72.1 ± 1.5

32

SO

\0.001

\0.001

\0.001

\0.001

0.001

\0.001

\0.001

0.001

\0.001

\0.001 \0.001

\0.001

0.05

0.11

\0.001

\0.001

0.007

0.001

0.17

\0.001

\0.001

\0.001

\0.001

0.34

0.1 0.007

0.21

\0.001

\0.001

\0.001

p*

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52.5 ± 0.32 23.2 ± 0.1 82.4 ± 0.4

11.1 (1.5) 32.5 (2.0) 14.3 (1.5) 18.6 (1.5) 6.4 ± 0.07 150 ± 0.2 49.0 ± 0.26 21.6 ± 0.1

Income (highest quartile, %)

Alcohol drinker (%)

Ever-smoker (%)

Regular exerciser (%)

Sleep duration (h)

Ht (cm)

Wt (kg) BMI (kg/m2)

72.8 ± 0.4

3.6 ± 0.2 4.6 ± 0.1

3.4 ± 0.1

TG/HDL-C ratio

49.6 ± 0.9

11.8 ± 0.1

28.1 ± 0.2

10.6 (0.4)

68.4 (3.2) 1,334 ± 41

15.6 ± 0.1

34.8 ± 0.2

20.3 ± 0.2

35.9 ± 0.2

10.4 (0.5)

78.7 (3.2) 1,521.5 ± 42

152.9 ± 2.6

4.6 ± 0.1

3.6 ± 0.2

148.1 ± 8.2

49.1 ± 0.9

124.4 ± 2.5

198.1 ± 2.6

3.0 ± 0.1

11.4 ± 0.4

106 ± 1.5

77.1 ± 0.7

134.2 ± 1.3

89.6 ± 0.5

61.5 ± 0.4 26.7 ± 0.1

152 ± 0.4

6.3 ± 0.2

26.7 (3.3)

6.5 (1.5)

39.3 (3.4)

9.8 (2.4)

5.2 (1.9)

71.1 ± 0.3

Obesity

13.9 ± 0.1

32.7 ± 0.2

24.2 ± 0.2

41.5 ± 0.2

11.0 (0.3)

82.6 (2.3) 1,395.1 ± 30

157.7 ± 2.1

4.6 ± 0.1

3.9 ± 0.2

162.3 ± 5.0

49.4 ± 0.6

125.6 ± 1.9

203.1 ± 2.1

3.7 ± 0.2

13.4 ± 0.4

109.3 ± 1.9

76.7 ± 0.5

132.7 ± 0.9

92.4 ± 0.4

63.3 ± 0.4 27.8 ± 0.1

151 ± 0.3

6.5 ± 0.1

14.4 (1.8)

6.8 (1.3)

28.9 (2.4)

10.9 (1.8)

5.1 (1.3)

72.6 ± 0.3

SO

9.5 ± 0.2 2.4 ± 0.1

\0.001 \0.001

15.3 ± 0.2 29.5 ± 0.1 13.0 ± 0.1

\0.001 \0.001 \0.001

10.1 (0.2) 32.9 ± 0.3

0.032

55 (1.8) 1,421.5 ± 22

\0.001 0.002 \0.001

153.0 ± 1.4

4.5 ± 0.05

3.5 ± 0.1

145.3 ± 3.6

50.1 ± 0.5

124.6 ± 1.3

0.069

0.035

0.037

0.009

0.201

0.817

199.1 ± 1.4

100.6 ± 0.8

\0.001

0.184

74.8 ± 0.4

\0.001

78.8 ± 0.3

\0.001 130.6 ± 0.7

50.6 ± 0.2 22.3 ± 0.1

\0.001 \0.001 0.005

150 ± 0.2

6.3 ± 0.1

0.027

0.265

12.8 (1.3) 17.1 (1.5)

0.001

33.8 (1.8)

10.7 (1.3)

7.2 (0.9)

73.4 ± 0.2

Normal

14.5 ± 0.1

33.5 ± 0.2

22.9 ± 0.2

39.7 ± 0.2

10.9 (0.3)

80.9 (1.8) 1,438.4 ± 26

156.2 ± 1.7

4.6 ± 0.1

3.9 ± 0.1

158.7 ± 4.4

49.0 ± 0.5

125.1 ± 1.5

201.3 ± 1.7

3.5 ± 0.1

12.8 ± 0.3

108.3 ± 1.4

76.9 ± 0.4

133.2 ± 0.8

91.5 ± 0.3

62.8 ± 0.3 27.5 ± 0.1

151 ± 0.2

6.4 ± 0.1

17.8 (1.6)

6.9 (1.1)

32.8 (2)

10.6 (1.6)

5.1 (1.1)

72.0 ± 0.2

Obesity

10.3 ± 0.3

26.6 ± 0.9

23.0 ± 0.7

41.6 ± 1.3

9.4 (1.1)

91.4 (4.9) 1,335.6 ± 98

155.2 ± 6.8

4.2 ± 0.2

2.9 ± 0.4

136.3 ± 12.1

56.2 ± 4.1

127.9 ± 5.9

206.5 ± 6.6

3.3 ± 0.4

12.5 ± 1.0

105.9 ± 4.3

74.9 ± 1.5

131.8 ± 3.2

93.1 ± 1.0

60.5 ± 0.9 26.9 ± 0.2

150 ± 1.0

6.1 ± 0.4

28.1 (9.1)

1.1 (1.1)

17.8 (7.2)

8.9 (4.4)

5.2 (5.1)

73.3 ± 1.0

SO

\0.001

\0.001

\0.001

\0.001

0.157

\0.001 \0.001

0.314

0.018

\0.001

0.001

0.033

0.986

0.581

\0.001

\0.001

0.728

\0.001

0.013

\0.001

\0.001 \0.001

0.061

0.634

0.147

\0.001

0.175

0.636

0.436

\0.001

p*

* Obtained by the v2 test and Student’s t test

ASM appendicular skeletal muscle, Wt weight, Ht height, KNHANES Korea National Health and Nutrition Examination Survey, SO sarcopenic obesity, BMI body mass index, WC waist circumference, SBP systolic blood pressure, DBP diastolic blood pressure, FBG fasting blood glucose, HOMA-IR homeostasis model assessment of insulin resistance, TC total cholesterol, LDLC low-density lipoprotein cholesterol, HDL-C high-density lipoprotein cholesterol, TG triglyceride

10.6 ± 0.1

25.3 ± 0.2

14.9 ± 0.6

35.0 ± 0.9

10.3 (0.6)

44.7 (5.7) 1,230.5 ± 46

150.4 ± 3.8

4.3 ± 0.1

3.0 ± 0.2

129.7 ± 6.7

51.8 ± 1.3

124.6 ± 3.6

197.9 ± 3.9

2.2 ± 0.2

8.7 ± 0.3

101.5 ± 3.0

72.1 ± 0.9

128.2 ± 1.8

75.1 ± 0.9

46.0 ± 0.7 20.5 ± 0.3

150 ± 0.6

6.4 ± 0.2

10.9 (3.2)

16.7 (3.6)

27.4 (3.9)

14.6 (4.2)

9.2 (3.7)

74.3 ± 0.7

Sarcopenia

Sarcopenia defined by ASM/Ht2

\0.001

0.121

0.97

0.475

\0.001

p*

Data are expressed as mean ± SE for continuous variables and percentages ± SE for categorical variables

13.1 ± 0.1

ASM (kg)

18.6 ± 0.2

13.9 ± 0.2 29.4 ± 0.1

31 ± 0.2

Total body fat (%)

Total body fat mass (kg)

9.9 (0.2)

Fat (% of energy)

Skeletal muscle mass (kg)

38.7 ± 0.3

47.5 (2) 1,421.7 ± 23

Metabolic syndrome (%) Total energy (kcal/day)

155.5 ± 2.7

4.4 ± 0.1 151.5 ± 1.5

TC/HDL-C ratio

Non-HDL-C (mg/dL)

149.4 ± 5.3

50.6 ± 0.5 141 ± 4.0

HDL-C (mg/dL)

126 ± 2.6

201.2 ± 2.6

TG (mg/dL)

124 ± 1.3

LDL-C (mg/dL)

2.6 ± 0.1

2.3 ± 0.1 198 ± 1.5

10.3 ± 0.3

HOMA-IR

102.2 ± 1.6

100.1 ± 0.9 9.1 ± 0.2

FBG (mg/dL)

Insulin (mIU/L)

TC (mg/dL)

74.8 ± 0.7

74.2 ± 0.4

DBP (mmHg)

131.8 ± 1.3

76.7 ± 0.3 129.7 ± 0.7

WC (cm)

SBP (mmHg)

150 ± 0.3

6.2 ± 0.1

10.8 (2.1)

11.1 (2.4)

34.1 (3.4)

11.3 (2.6)

7.4 (1.9)

73.9 ± 0.3 7.4 (1.1)

Age (year)

Sarcopenia

Normal

Sarcopenia defined by ASM/Wt

Education (Chigh school, %)

Table 1 continued

J Endocrinol Invest

123

J Endocrinol Invest Table 2 Correlation analysis between ASM, ASM/Ht2, and ASM/Wt and clinical and dyslipidemic parameters ASM adjusted for age c

p

*

ASM/Ht2 adjusted for age c

p

*

ASM/Wt adjusted for age p*

c

Men BMI

0.59

\0.001

0.69

\0.001

-0.53

\0.001

WC

0.56

\0.001

0.53

\0.001

-0.55

\0.001 \0.001

SBP (mmHg)

0.05

0.05

0.06

0.025

-0.11

DBP (mmHg)

0.07

0.004

0.05

0.031

-0.1

\0.001

FBG (mg/dL)a

0.02

0.32

-0.02

0.459

-0.23

\0.001

Insulin (mIU/L)a HOMA-IRa

0.21 0.19

\0.001 \0.001

0.19 0.16

\0.001 \0.001

-0.39 -0.42

\0.001 \0.001 0.002

TC (mg/dL)

-0.01

0.47

0

0.768

-0.08

LDL-C (mg/dL)

0

0.94

0.02

0.39

-0.06

HDL-C (mg/dL)

-0.12

\0.001

0.01

-0.11

\0.001

0.26

\0.001

TG (mg/dL)a

0.06

0.02

0.06

0.011

-0.28

\0.001

TG/HDL-C ratioa

0.08

0.001

0.09

0.001

-0.31

\0.001

\0.001

-0.28

\0.001

0.097

-0.17

\0.001

TC/HDL-C ratio

0.08

0.001

0.1

Non-HDL-C (mg/dL)

0.01

0.47

0.04

Women BMI

0.52

\0.001

0.61

\0.001

-0.61

\0.001

WC SBP (mmHg)

0.49 0.03

\0.001 0.269

0.46 0.06

\0.001 0.018

-0.6 -0.08

\0.001 0.001

DBP (mmHg)

0.06

0.02

0.07

0.004

-0.1

\0.001

FBG (mg/dL)a

0.13

\0.001

0.09

\0.001

-0.15

\0.001

Insulin (mIU/L)a

0.2

\0.001

0.19

\0.001

-0.34

\0.001

HOMA-IRa

0.22

\0.001

0.19

\0.001

-0.34

\0.001

TC (mg/dL)

-0.05

0.023

-0.04

0.12

-0.14

\0.001

LDL-C (mg/dL)

-0.04

0.096

-0.02

0.471

-0.1

\0.001

HDL-C (mg/dL)

-0.1

\0.001

-0.1

\0.001

0.08

0.001

TG (mg/dL)a

0.03

0.261

0.01

0.714

-0.2

\0.001

TG/HDL-C ratioa

0.06

0.016

0.04

0.076

-0.18

\0.001

TC/HDL-C ratio

0.05

0.024

0.06

0.01

-0.16

\0.001

-0.03

0.256

-0.01

0.658

-0.16

\0.001

Non-HDL-C (mg/dL)

ASM appendicular skeletal muscle, Wt weight, Ht height, KNHANES Korea National Health and Nutrition Examination Survey, SO sarcopenic obesity, BMI body mass index, WC waist circumference, SBP systolic blood pressure, DBP diastolic blood pressure, FBG fasting blood glucose, HOMA-IR homeostasis model assessment of insulin resistance, TC total cholesterol, LDL-C low-density lipoprotein cholesterol, HDL-C highdensity lipoprotein cholesterol, TG triglyceride * Correlation coefficients (c) and p values were calculated using Pearson’s partial correlation analysis a

Data were calculated using natural logarithmic transformation

the adjusted ORs for high TC/HDL-C ratio were higher in the obese group than in the SO group, and the adjusted ORs for hyper-non-HDL-cholesterolemia were not significantly related to decreased muscle mass and increased BMI. In women, adjusted ORs for hypercholesterolemia were in increasing trends with decreased muscle and increased BMI after further adjustments. However, ORs for dyslipidemia, hypertriglyceridemia, hypo-HDL-cholesterolemia, hyper-LDL-cholesterolemia, high TC/HDL-C ratio, and high TG/HDL-C ratio showed increasing trends only in

123

model 1. These relationships were not persisted after further adjustments. Table 4 also illustrates the relationship between body composition status and insulin resistance. The ORs and 95 % CIs for insulin resistance in the SO group were higher than any other group both in men and women even after adjusting all co-variables (OR = 4.50; 95 % CI 2.73–7.42; p for trend \0.001 in men and OR = 3.19; 95 % CI 2.16–4.72; p for trend \0.001 in women).

50.4 ± 0.9

51.2 ± 0.9

153.3 ± 3.8

4.5 ± 0.1

3.5 ± 0.3

149.8 ± 8.8

50.5 ± 1.4

123.3 ± 3.6

199.7 ± 3.8

4.3 ± 0.1 138.8 ± 2.6

3.5 ± 0.3

141.4 ± 7.9

47.4 ± 0.9

111.0 ± 2.5

182.5 ± 2.6

Sarcopenia

152.6 ± 3.7

4.5 ± 0.1

3.7 ± 0.3

152.3 ± 9.2

49.5 ± 1.2

122.8 ± 3.5

198.1 ± 3.8

4.6 ± 0.2 140.4 ± 3.8

3.7 ± 0.3

140.0 ± 7.4

44.3 ± 1.7

111.1 ± 4.0

181.6 ± 3.8

Obesity

156.7 ± 3.4

4.6 ± 0.1

3.9 ± 0.3

162.6 ± 8.2

49.8 ± 1.1

124.2 ± 3.1

202.5 ± 3.5

4.7 ± 0.1 142.8 ± 3.3

4.6 ± 0.3

165.0 ± 9.1

42.8 ± 1.0

111.0 ± 3.0

182.7 ± 3.3

SO

48.4 ± 0.9

0.016

0.002

0.002

\0.001

0.138

0.513

150.3 ± 2.7

4.4 ± 0.1

3.4 ± 0.2

146.1 ± 6.9

50.8 ± 1.0

121.6 ± 2.6

197 ± 2.9

4.2 ± 0.1 138.5 ± 2.5

\0.001 \0.001

0.07

3.2 ± 0.2

\0.001

130.4 ± 6.3

\0.001 \0.001

113.2 ± 2.4

183.1 ± 2.6

Normal

145.6 ± 4.7

4.1 ± 0.2

2.8 ± 0.3

130 ± 9.4

52.9 ± 1.6

119.7 ± 4.3

194 ± 4.8

4.0 ± 0.1 131.3 ± 2.5

3.0 ± 0.2

127.6 ± 6.2

50.1 ± 0.9

105.8 ± 2.4

177.4 ± 2.6

Sarcopenia

Sarcopenia defined by ASM/Ht2

0.45

0.27

p*

155.2 ± 3.1

4.6 ± 0.1

3.8 ± 0.2

159.9 ± 7.3

49.4 ± 0.9

123.5 ± 2.9

200.6 ± 3.2

4.7 ± 0.1 141.6 ± 2.9

4.3 ± 0.2

157.7 ± 7

42.9 ± 0.9

109.9 ± 2.7

181.5 ± 2.9

Obesity

152.3 ± 8.5

4.1 ± 0.3

2.8 ± 0.4

131.7 ± 14.2

58.2 ± 4.6

125.7 ± 7.4

205.4 ± 8.1

4.8 ± 0.3 151.3 ± 8.4

4.8 ± 1.3

171.6 ± 31

44.7 ± 2.6

124.3 ± 8.7

192.8 ± 8.4

SO

0.072

0.004

0.001

0.004

0.01

0.626

0.175

\0.001 0.001

\0.001

\0.001

\0.001

0.03

0.12

p*

a

Data were calculated using natural logarithmic transformation

* Obtained by one-way analysis of covariance (ANCOVA) and were adjusted for age, education level, household income level, smoking status, alcohol consumption, physical activity, total energy intake, and total fat intake (%)

SO sarcopenic obesity, KNHANES Korea National Health and Nutrition Examination Survey, ASM appendicular skeletal muscle, Wt weight, Ht height, TC total cholesterol, LDL-C low-density lipoprotein cholesterol, HDL-C high-density lipoprotein cholesterol, TG triglyceride, HOMA-IR homeostasis model assessment of insulin resistance

148.6 ± 2.8

TC/HDL-C ratio

Non-HDL-C (mg/dL)

3.3 ± 0.2

4.3 ± 0.1

TG/HDL-C ratioa

142.4 ± 6.7

HDL-C (mg/dL)

TG (mg/dL)a

195.7 ± 3.0

120.8 ± 2.6

TC (mg/dL)

4.0 ± 0.1 131.9 ± 2.3

2.8 ± 0.2

LDL-C (mg/dL)

Women

TC/HDL-C ratio Non-HDL-C (mg/dL)

TG/HDL-C ratioa

120.6 ± 5.7

HDL-C (mg/dL)

TG (mg/dL)a

178.3 ± 2.5

107.9 ± 2.1

TC (mg/dL)

LDL-C (mg/dL)

Men

Normal

Sarcopenia defined by ASM/Wt

Table 3 Multivariate-adjusted mean dyslipidemic parameters in normal, sarcopenia, obesity, and SO groups in the 2008–2010 KNHANES

J Endocrinol Invest

123

J Endocrinol Invest Table 4 Prevalence and adjusted ORs and 95 % CIs of dyslipidemia and parameters of dyslipidemia in the normal, sarcopenia, obesity, and SO groups in the 2008–2010 KNHANES Sarcopenia defined by ASM/Wt

p for linear trend

Normal

Sarcopenia

Obesity

SO

7.2 (1.2)

14 (2.2)

9.3 (3.5)

15.7 (3.2)

0.01

Model 1a

1.00 (reference)

2.18 (1.36–3.51)

0.89 (0.35–2.26)

2.23 (1.25–3.96)

0.01

b

1.00 (reference)

2.23 (1.39–3.60)

0.97 (0.38–2.45)

2.45 (1.26–4.78)

0.006

Model 3c

1.00 (reference)

1.88 (1.15–3.10)

0.98 (0.38–2.50)

2.03 (1.06–3.91)

0.02

32.2 (2.1)

40.2 (2.8)

51.4 (6)

55.6 (3.8)

\0.001

Model 1a

1.00 (reference)

1.71 (1.08–2.72)

1.21 (0.61–2.41)

2.55 (1.52–4.28)

\0.001

b

1.00 (reference)

1.69 (1.06–2.69)

1.11 (0.53–2.32)

2.28 (1.32–3.96)

0.003

Model 3c

1.00 (reference)

1.34 (0.93–1.93)

2.73 (1.48–5.02)

3.02 (1.88–4.85)

\0.001

9.3 (1.4)

13.9 (2.2)

13.5 (4)

15.5 (3)

\0.001

Model 1a

1.00 (reference)

1.34 (0.97–1.85)

2.47 (1.42–4.31)

2.55 (1.82–3.59)

\0.001

Model 2b Model 3c

1.00 (reference) 1.00 (reference)

1.33 (0.96–1.85) 1.40 (0.88–2.24)

2.32 (1.27–4.26) 1.36 (0.61–3.04)

2.38 (1.56–3.64) 1.49 (0.80–2.78)

\0.001 0.39

13.4 (1.9)

20.3 (2.6)

17.6 (4.5)

29.6 (3.9)

0.001

Model 1a

1.00 (reference)

1.70 (1.07–2.69)

1.22 (0.61–2.42)

2.54 (1.52–4.26)

0.001

Model 2b

1.00 (reference)

1.68 (1.06–2.66)

1.12 (0.54–2.34)

2.30 (1.32–4.00)

0.003

Model 3c

1.00 (reference)

1.59 (0.99–2.57)

1.24 (0.57–2.66)

2.50 (1.39–4.49)

0.002

43.7 (2.3)

54.6 (3.1)

62.2 (5.8)

71.2 (3.7)

\0.001

Model 1a

1.00 (reference)

1.50 (1.08–2.10)

2.11 (1.18–3.80)

2.94 (1.98–4.37)

\0.001

Model 2b

1.00 (reference)

1.48 (1.05–2.07)

1.88 (0.99–3.55)

2.57 (1.62–4.08)

\0.001

Model 3c

1.00 (reference)

1.46 (1.01–2.11)

2.12 (1.11–4.07)

2.82 (1.76–4.51)

\0.001

Prevalence (%)

23 (2.2)

34.9 (3.1)

39.6 (5.6)

47.2 (3.7)

\0.001

OR (95 % CIs) Model 1a

Men Hypercholesterolemia Prevalence (%) OR (95 % CIs) Model 2

Hypo-HDL-cholesterolemia Prevalence (%) OR (95 % CIs) Model 2

Hyper-LDL-holesterolemia Prevalence (%) OR (95 % CIs)

Hypertriglyceridemia Prevalence (%) OR (95 % CIs)

Dyslipidemia Prevalence (%) OR (95 % CIs)

High TG/HDL-C ratio

1.00 (reference)

1.91 (1.33–2.74)

2.09 (1.16–3.76)

3.20 (2.14–4.78)

\0.001

Model 2b

1.00 (reference)

1.89 (1.29–2.76)

1.95 (0.98–3.86)

2.95 (1.78–4.88)

\0.001

Model 3c

1.00 (reference)

1.77 (1.18–2.65)

2.08 (1.03–4.21)

3.18 (1.89–5.33)

\0.001

42.9 (2)

57.7 (3)

70.5 (5.9)

67.9 (3.4)

\0.001

Model 1a

1.00 (reference)

1.87 (1.39–2.52)

3.74 (1.95–7.16)

2.82 (1.97–4.04)

\0.001

Model 2b

1.00 (reference)

1.80 (1.32–2.44)

3.13 (1.60–6.11)

2.29 (1.49–3.52)

\0.001

Model 3c

1.00 (reference)

1.74 (1.26–2.41)

3.39 (1.73–6.67)

2.45 (1.55–3.89)

\0.001

27.2 (2.6)

21.2 (4.4)

30.8 (3.5)

\0.001

High TC/HDL-C ratio Prevalence (%) OR (95 % CIs)

Hyper-non-HDL-cholesterolemia Prevalence (%) OR (95 % CIs)

123

17.5 (1.8)

J Endocrinol Invest Table 4 continued Sarcopenia defined by ASM/Wt

p for linear trend

Normal

Sarcopenia

Obesity

SO

Model 1a

1.00 (reference)

2.02 (1.41–2.89)

1.36 (0.75–2.46)

2.20 (1.45–3.34)

\0.001

Model 2b

1.00 (reference)

1.83 (1.28–2.62)

0.94 (0.50–1.76)

1.44 (0.91–2.29)

0.112

c

1.00 (reference)

1.50 (1.04–2.17)

0.94 (0.50–1.76)

1.25 (0.79–1.97)

0.332

13.4 (1.7)

26.8 (2.9)

32.1 (5.3)

52.2 (3.6)

\0.001

Model 1a

1.00 (reference)

2.15 (1.38–3.35)

3.49 (2.13–5.70)

7.08 (4.74–10.58)

\0.001

b

1.00 (reference)

1.91 (1.21–3.02)

2.09 (1.21–3.61)

3.98 (2.46–6.43)

\0.001

Model 3c Women

1.00 (reference)

1.89 (1.19–2.99)

2.23 (1.28–3.88)

4.50 (2.73–7.42)

\0.001

27.5 (1.8)

33.8 (3.7)

32.5 (3.3)

34.6 (2.6)

\0.001

Model 1a

1.00 (reference)

1.81 (1.24–2.65)

2.11 (1.39–3.21)

1.89 (1.36–2.64)

\0.001

Model 2b

1.00 (reference)

1.67 (1.11–2.51)

1.77 (1.11–2.83)

1.60 (1.08–2.36)

0.028

Model 3c

1.00 (reference)

1.68 (1.12–2.54)

1.98 (1.22–3.21)

1.67 (1.10–2.53)

0.02

27.5 (1.8)

33.8 (3.7)

32.5 (3.3)

34.6 (2.6)

0.064

Model 1a

1.00 (reference)

1.30 (0.92–1.83)

1.27 (0.91–1.78)

1.38 (1.03–1.84)

0.029

Model 2b

1.00 (reference)

1.08 (0.75–1.54)

0.93 (0.64–1.34)

0.97 (0.69–1.37)

0.773

Model 3c

1.00 (reference)

1.07 (0.73–1.56)

0.95 (0.65–1.38)

1.02 (0.72–1.43)

0.998

16.7 (1.5)

30.8 (3.2)

28.2 (3.7)

26.2 (2.5)

Model 1a

1.00 (reference)

1.90 (1.34–2.68)

2.15 (1.45–3.19)

1.69 (1.22–2.36)

0.001

Model 2b

1.00 (reference)

1.71 (1.18–2.48)

1.73 (1.12–2.67)

1.36 (0.92–2.01)

0.167

Model 3c

1.00 (reference)

1.61 (1.10–2.35)

1.80 (1.14–2.85)

1.40 (0.94–2.09)

0.125

16.2 (1.7)

19.4 (3.2)

21 (3.9)

24.8 (2.6)

0.019

Model 1a

1.00 (reference)

1.19 (0.74–1.91)

1.36 (0.81–2.26)

1.60 (1.10–2.34)

0.012

Model 2b

1.00 (reference)

1.16 (0.71–1.91)

1.28 (0.73–2.25)

1.51 (0.97–2.37)

0.068

Model 3c

1.00 (reference)

1.19 (0.72–1.95)

1.31 (0.74–2.34)

1.53 (0.97–2.41)

0.073

44.5 (2)

62.8 (3.6)

57.6 (3.7)

58.5 (2.7)

\0.001

Model 1a

1.00 (reference)

1.84 (1.34–2.53)

1.74 (1.25–2.42)

1.62 (1.24–2.10)

\0.001

Model 2b Model 3c

1.00 (reference) 1.00 (reference)

1.59 (1.15–2.20) 1.52 (1.09–2.12)

1.31 (0.92–1.89) 1.32 (0.92–1.91)

1.20 (0.88–1.64) 1.26 (0.92–1.71)

0.347 0.203

28.8 (1.9)

30.2 (3.2)

34.2 (3.6)

38.1 (2.6)

0.01

Model 1a

1.00 (reference)

1.04 (0.73–1.47)

1.49 (1.02–2.16)

1.43 (1.07–1.93)

0.007

Model 2b

1.00 (reference)

0.88 (0.61–1.26)

1.08 (0.71–1.65)

1.00 (0.71–1.42)

0.875

c

1.00 (reference)

0.86 (0.59–1.24)

1.08 (0.71–1.64)

0.98 (0.69–1.40)

0.921

Model 3 HOMA-IR

Prevalence (%) OR (95 % CIs) Model 2

Hypercholesterolemia Prevalence (%) OR (95 % CIs)

Hypo-HDL-cholesterolemia Prevalence (%) OR (95 % CIs)

Hyper-LDL-holesterolemia Prevalence (%) OR (95 % CIs)

\0.001

Hypertriglyceridemia Prevalence (%) OR (95 % CIs)

Dyslipidemia Prevalence (%) OR (95 % CIs)

High TG/HDL-C ratio Prevalence (%) OR (95 % CIs)

Model 3

High TC/HDL-C ratio

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J Endocrinol Invest Table 4 continued Sarcopenia defined by ASM/Wt

p for linear trend

Normal

Sarcopenia

Obesity

SO

59.6 (2)

64.7 (3.7)

66.6 (3.6)

71.3 (2.5)

Model 1a

1.00 (reference)

1.31 (0.91–1.88)

1.47 (1.03–2.10)

1.64 (1.23–2.19)

\0.001

Model 2b

1.00 (reference)

1.08 (0.74–1.60)

0.99 (0.67–1.48)

1.07 (0.76–1.51)

0.756

Model 3c

1.00 (reference)

1.08 (0.72–1.63)

1.01 (0.68–1.51)

1.04 (0.72–1.48)

0.886

38.2 (2)

43.9 (3.7)

36.9 (4)

43.3 (2.9)

0.114

Model 1a Model 2b

1.00 (reference) 1.00 (reference)

1.40 (1.00–1.95) 1.20 (0.85–1.70)

1.00 (0.68–1.47) 0.74 (0.49–1.13)

1.35 (1.01–1.81) 1.01 (0.71–1.43)

0.085 0.768

Model 3c

1.00 (reference)

1.22 (0.84–1.75)

0.78 (0.52–1.18)

1.03 (0.72–1.48)

0.897

13.4 (1.5)

19.4 (2.7)

35.1 (3.9)

48 (2.8)

\0.001

Model 1a

1.00 (reference)

1.41 (0.92–2.16)

3.12 (2.07–4.71)

5.53 (3.94–7.75)

\0.001

Model 2b

1.00 (reference)

1.06 (0.69–1.63)

1.97 (1.26–3.07)

3.38 (2.30–4.97)

\0.001

Model 3c

1.00 (reference)

1.00 (0.65–1.54)

1.74 (1.09–2.77)

3.19 (2.16–4.72)

\0.001

Prevalence (%)

0.001

OR (95 % CIs)

Hyper-non-HDL-cholesterolemia Prevalence (%) OR (95 % CIs)

HOMA-IR Prevalence (%) OR (95 % CIs)

OR odds ratio, CI confidence interval, SO sarcopenic obesity, KNHANES Korea National Health and Nutrition Examination Survey, ASM appendicular skeletal muscle, Wt weight, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol, TG triglyceride, TC total cholesterol a

Adjusted for age

b

Adjusted for age and WC

c

Adjusted for variables in model 2 plus education level, household income level, smoking status, alcohol consumption, physical activity, total energy intake and total fat intake (%)

Figure 2 summarizes the proportions according to the number of lipid abnormalities in each body composition group. The proportion of subjects with mixed dyslipidemia with C2 lipid abnormalities (hypercholesterolemia, hyperLDL-cholesterolemia, hypo-HDL-cholesterolemia, or hypertriglyceridemia) was higher in the SO group (32.7 %) than in the sarcopenic or obese groups in men (p \ 0.001). In women, the proportion of subjects with mixed dyslipidemia was different among four groups (p \ 0.001); however, the proportion showed no significant difference among sarcopenia, obesity, and SO group.

Discussion Using simple and practical methods such as BMI measurement and DXA, this study demonstrated that SO was strongly associated with dyslipidemia in Korean elderly men. The results showed that, after adjusting for confounders, elderly men with SO as defined using ASM/Wt were at a 2.8-fold higher risk for dyslipidemia compared to those with sarcopenia or obesity. This finding implies that

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SO could be considered a risk factor for dyslipidemia in addition to sarcopenia and obesity alone. Only a few studies have reported the association between SO and dyslipidemia as components of MetS in Asia [5, 6, 8]. Lim et al. [6] used DXA and suggested that SO was more closely associated with MetS than either sarcopenia or obesity alone. However, in that study, the significant trend toward an association between SO and dyslipidemic parameters was only found in the serum TG levels in men. Using bioimpedance analysis, Lu et al. [8] found that SO individuals had a higher risk for MetS than those in the obese or sarcopenic groups, and that individual components, including serum TG and HDL-C levels, were independently associated with SO. The present study has several strengths that differentiate it from previous studies. First, it examined the relationship between SO and dyslipidemia as a separate issue rather than as a component of MetS. Second, the lipid ratios such as TC/HDL-C and TG/HDL-C were used as parameters of dyslipidemia with the goal of assessing whether SO related to these surrogate estimates of dyslipidemia. As mentioned above, the OR for a high TG/HDL-C ratio in the male SO

J Endocrinol Invest

Fig. 2 The prevalence of dyslipidemia according to the number of lipid abnormalities (0, 1, or C2 abnormalities) according to body composition group in elderly Korean men who participated in the 2008–2010 KNHANES. The percentage of individuals with mixed dyslipidemia, displaying C2 lipid abnormalities from among

hypercholesterolemia, hyper-LDL-cholesterolemia, hypo-HDL-cholesterolemia, and hypertriglyceridemia, was higher in the SO group (32.7 %) than in the sarcopenic or obese groups in men (p \ 0.001). p value represents differences among four groups as determined by ANCOVA

group (OR = 3.18) was higher than that for any other dyslipidemic parameter even after adjustment for confounders. Additionally, only the SO group had a TG/HDLC ratio C3.8 which typically correlates with LDL-C phenotype B, a reliable predictor of cardiovascular risk [12]. Consequently, this study demonstrated that the TG/HDL-C ratio could be served as an available parameter to identify dyslipidemia better than any other single lipid profile for predicting CVD in individuals with SO. Third, the present study scored the number of each component that satisfied the definition of dyslipidemia according to body composition status. The percentage of dyslipidemic subjects C2 of the criteria was highest in the male SO group compared to the other body composition groups (Fig. 2). In previous studies on the prevalence of dyslipidemia in the USA, adults with abnormal measurements for all three standard lipid parameters, i.e., high LDL-C, low HDL-C and high TG, were more likely to have diabetes mellitus or MetS [22]. Therefore, the finding of our study suggests that SO might be more predictive for cardiovascular risk and, therefore, SO individuals should be evaluated earlier and targeted for therapy on insulin resistance and dyslipidemia. The underlying mechanism for the relationship between SO and dyslipidemia has never been explored. Increased fat mass promotes the inflammatory process by increasing the secretion of pro-inflammatory cytokines such as TNF-a and interleukin-6 that further promote insulin resistance and TG infiltration into muscle [23, 24]. In addition, the loss of muscle mass reduces the mass of available insulinresponsive target tissue, promoting insulin resistance, which plays a key role in the pathogenesis of MetS and abnormal lipid metabolism leading to hypertriglyceridemia and hypo-HDL-cholesterolemia [25, 26]. Based on our results, subjects in the SO group had an increased

probability of insulin resistance compared to those in the sarcopenic and obese groups after adjusting for confounders, including WC, one of the strongest indicators of insulin resistance (Table 4). However, further research is necessary for better understanding of the linked pathogenesis. Universally accepted definitions of sarcopenia and SO have not been established, and the cutoff values vary with different studies. Previous studies have suggested that it may be appropriate to use different definitions of sarcopenia and obesity according to ethnicity because the typical amount of muscle mass in different ethnic groups can differ. Although many previous studies have defined sarcopenia as ASM/Ht2 2 SD below young reference groups [18], this only takes into account the absolute amount of muscle mass and does not consider body fat mass. ASM/ Ht2 is highly correlated with BMI and primarily identifies subjects with a low BMI as sarcopenic, and thus may underestimate sarcopenia in overweight or obese subjects [27]. Other studies have suggested that ASM/Wt might be a more appropriate method than ASM/Ht2 for defining sarcopenia [28], SO, and estimating metabolic disorders in elderly Koreans [6]. Similarly, the present study representing a single ethnic and age group demonstrated a highly significant positive relationship between ASM/Ht2 and BMI, WC, TG, TG/HDL-C ratio, TC/HDL-C ratio and the HOMA-IR even after adjusting for age. However, ageadjusted ASM/Wt was negatively correlated with BMI, lipid profiles, and the HOMA-IR in both sexes. This suggests that ASM/Wt is the more appropriate index for determining SO and for estimating the relationship between SO and dyslipidemia in elderly Koreans. There were several limitations to this study. First, its cross-sectional nature means that it would be impossible to

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interpret any cause-effect relationship between SO and dyslipidemia. Second, due to the lack of muscle strength data, we could not consider the new criteria for sarcopenia proposed in the European consensus, which include low muscle function (strength or performance) [29]. In conclusion, this study showed that the SO group defined using ASM/Wt had a higher risk for dyslipidemia and insulin resistance, and particularly, more lipid abnormalities than the group with obesity or sarcopenia alone among Korean elderly men. Additionally, TG/HDL-C ratio could be suggested a new parameter for dyslipidemia associated with sarcopenia and SO. The underlying mechanism for the relationship between SO and dyslipidemia warrants further research. Conflict of interest The authors S. J. Baek, G. E. Nam, K. D. Han, S. W. Choi, S. W. Jung, A. R. Bok, Y. H. Kim, K. S. Lee, B. D. Han, and D. H. Kim declare that they have no conflict of interest.

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Sarcopenia and sarcopenic obesity and their association with dyslipidemia in Korean elderly men: the 2008-2010 Korea National Health and Nutrition Examination Survey.

Recently, aging has been shown to be associated with sarcopenic obesity (SO), of which decreased muscle mass and increased fat mass are features. Sarc...
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