Literature DB >> 31634043

Association of Sarcopenia with Metabolic Syndrome in Korean Population Using 2009-2010 Korea National Health and Nutrition Examination Survey.

Seong-Joon Park1, So-Yeon Ryu2, Jong Park2, Seong-Woo Choi2.   

Abstract

Background: Some studies have investigated the relationship between sarcopenia and metabolic syndrome, and they have focused mainly on older subjects. Therefore, we assessed the association between sarcopenia and metabolic syndrome in South Korean adults 20 years of age or older using data from the 2009-2010 Korean National Health and Nutrition Examination Survey (KNHANES).
Methods: This study involved 12,256 (5350 males and 6906 females) participants from the 2009-2010 KNHANES 20 years of age or older. Appendicular skeletal muscle mass (ASM) was measured by dual X-ray absorptiometry. Sarcopenia index (SI) was calculated as ASM/body mass index and sarcopenia was defined as an SI of <0.789 in males and <0.521 in females. Metabolic syndrome was defined by the presence of at least three of the following abnormalities: abdominal obesity, high blood pressure, high blood glucose level, high triglyceride level, and low high-density lipoprotein cholesterol level.
Results: After adjustment for covariates, the association between sarcopenia and metabolic syndrome was significant (odds ratio [OR] 2.06, 95% confidence interval [CI] 1.74-2.45). In addition, when stratified by age groups, the significant associations between sarcopenia and metabolic syndrome remained in all age groups (20-39 years: OR 2.13, 95% CI 1.08-4.19; 40-64 years: OR 2.13, 95% CI 1.68-2.71; ≥65 years: OR 1.98, 95% CI 1.54-2.54).
Conclusion: The association between sarcopenia and metabolic syndrome was significant in South Korean adults. Moreover, the significant associations were present in every age group evaluated.

Entities:  

Keywords:  central obesity; dyslipidemia; hypertension; impaired fasting glucose; sarcopenia

Mesh:

Year:  2019        PMID: 31634043      PMCID: PMC6892432          DOI: 10.1089/met.2019.0059

Source DB:  PubMed          Journal:  Metab Syndr Relat Disord        ISSN: 1540-4196            Impact factor:   1.894


Introduction

The prevalence of metabolic syndrome is increasing globally.[1] The prevalence was ∼34.7% in 2011–2012 in the United States,[2] and ∼23% of Japanese adults in their 30s or older were diagnosed with metabolic syndrome in 2011.[3] The prevalence of metabolic syndrome in Korea increased steadily from 27.5% in 2008 to 28.9% in 2013.[4] As a result, the cost of medical treatment for metabolic syndrome in Korea increased from 3.7 trillion won in 2010 to 4.7 trillion won in 2014, with an expected increase of 6.2% per year.[5] Insulin resistance is the major cause of metabolic syndrome.[6] As blood glucose levels increase in response to an increase in insulin resistance, insulin secretion further increases and results in hyperinsulinemia, and hyperinsulinemia restricts sodium excretion in the kidneys, resulting in hypertension.[7] It also increases triglyceride (TG) and decreases high-density lipoprotein cholesterol (HDL-C) levels, resulting in dyslipidemia.[8] Sarcopenia is defined as reductions in muscle mass and muscle strength due to changes in body composition.[9] The prevalence of sarcopenia was estimated to be more than 50 million adults worldwide in 2000 and is expected to increase to more than 200 million by 2040.[10] The 2008–2011 Korea National Health and Nutrition Examination Survey (KNHANES) estimated the prevalence of sarcopenia in Korea to be 26.8%.[11] The mechanism of sarcopenia has not yet been clarified, but it has been associated with various factors such as aging, malnutrition, lack of exercise, and reduced levels of hormones such as testosterone and cortisol.[12] Furthermore, increased body fat resulting from decreased muscle mass seen in patients with sarcopenia is associated with cardiovascular and metabolic diseases.[13] However, the relationship between sarcopenia and metabolic syndrome is still unclear. Several authors have reported an association between sarcopenia and metabolic syndrome,[14] whereas others found no such association,[15] and yet others reported that the association differs depending on sex.[16] In addition, previous studies on the association between sarcopenia and metabolic syndrome have focused mainly on older subjects.[14,17] However, the prevalence of metabolic syndrome is also increasing in younger populations.[18] Therefore, we investigated the association between sarcopenia and metabolic syndrome in all adults in Korea using the 2009–2010 KNHANES.

Materials and Methods

Study population

This study used data from the 2009–2010 KNHANES. As previously published in detail,[19] the KNHANES is a nationwide cross-sectional survey conducted annually by the Korea Centers for Disease Control and Prevention (KCDCP). The KNHANES uses a rolling sampling design involving a complex, stratified, multistage probability-cluster survey of a representative sample of the noninstitutionalized Korean citizens residing in Korea. KNHANES consisted with three component surveys: the health interview, health examination, and nutrition survey. The health interview and nutrition survey questionnaires are administered by trained interviewers, and the health examinations are performed by trained medical staff. The KCDCP Ethics Committee approved the study protocol (2009-01CON-03-2C, 2010-02CON-21-C), and written informed consent was obtained from all subjects or their parents. The number of participants in the 2009–2010 KNHANES was 19,491 (10,533 in 2009 and 8958 in 2010), among whom, 14,963 (7920 in 2009 and 7043 in 2010) people participated in both the health interview and the health examination, including whole body dual-energy X-ray absorptiometry (DXA) scans, and 13,201 were older than 20 years. In total, 12,256 participants (5350 males and 6906 females) were analyzed, after excluding 272 subjects with missing appendicular skeletal muscle mass (ASM) data and 673 who did not undergo blood testing.

Data collection

Trained investigators interviewed the subjects individually using a questionnaire. Monthly household income was divided into quartiles. Educational level was divided into <6, 7–9, 10–12, and ≥13 years. Marriage status was classified as unmarried or married, and area of residence was classified as urban or rural. Current smoking was defined as smoking frequently or occasionally, and monthly drinking was defined as one or more drinks during the last month. Physical activity was defined as walking for >30 min at a time at least six times per week. Strength training was defined as exercising the muscles more than once per week. Weight was measured to the nearest 0.1 kg, while the subjects were dressed in light clothes, and height was measured to the nearest 0.1 cm in stocking feet. Waist circumference was measured to the nearest 0.1 cm at expiration through a horizontal plane around the abdomen midway between the lowest rib and iliac crest. Blood pressure was measured after the subject had rested for 5 min in a sitting position. Three readings each of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were recorded, and the average values were used in the analyses. Number of co-morbidities was categorized as diagnosis of 0, 1, 2, or ≥3 of hypertension, diabetes, dyslipidemia, stroke, myocardial infarction, angina pectoris, cancer, cirrhosis, and kidney failure. The blood samples were collected by a trained nurse and transported daily to the central laboratory of NEODIN Medical Institute (Seoul, Korea). The total cholesterol, TG, and HDL-C levels were determined using the Hitachi Automatic Analyzer 7600 (Hitachi Ltd., Tokyo, Japan) according to standard procedures.

Sarcopenia

ASM was measured by dual X-ray absorptiometry (QDR 4500A; Hologic, Inc., Bedford, MA). The sarcopenia index (SI) was calculated as ASM (kg)/body mass index (BMI, kg/m2), and sarcopenia was defined as an SI of <0.789 in males and <0.521 in females based on the criteria of the Sarcopenia Project.[20]

Metabolic syndrome

A diagnosis of metabolic syndrome was defined as the presence of three or more of the following five components: high blood pressure, high blood glucose level, high TG level, and lower HDL-C level using the diagnostic criteria of the National Cholesterol Education Program Adult Treatment panel III (NCEP-ATP III) based on common clinical measures,[21] and the abdominal obesity using the criteria of the Korean Society for the Study of Obesity.[22] Among the metabolic syndrome components, abdominal obesity was defined as a waist circumference ≥90 cm for males or ≥80 cm for females, high blood pressure as SBP ≥130 mmHg or DBP ≥85 mmHg or the use of antihypertensive medication, high blood glucose as a fasting blood glucose (FBG) level ≥100 mg/dL or the use of diabetic medication, a high TG level as ≥150 mg/dL or the use of dyslipidemia medication, and a low HDL-C level as <40 mg/dL for males or <50 mg/dL for females, or the use of dyslipidemia medication.

Statistical analysis

Data were analyzed using SPSS (version 23.0; IBM, Armonk, NY). The survey responses were weighted by reference to the multistage, complex, probability sampling design. Data were expressed as absolute number and estimated percentages (with standard errors) or as mean ± standard deviation (SD). The survey responses were weighted by reference to the multistage, complex probability sampling design. The χ2 test or Student's t-test was used to evaluate the differences in demographic and clinical characteristics according to sarcopenia. A multivariate logistic regression analysis was performed to investigate the association of sarcopenia with metabolic syndrome. Adjustment for sex, age, monthly household income, educational level, marital status, area of residence, current smoking, monthly drinking, physical activities and strength training, and number of co-morbidities were performed. A value of P < 0.05 was considered indicative of statistical significance.

Results

Baseline characteristics of subjects according to sarcopenia

The baseline characteristics of subjects according to sarcopenia are shown in Table 1. The prevalence of sarcopenia and metabolic syndrome was 9.5% and 24.7%. Among the subjects, 27.2% currently smoked, 59.9% had consumed alcohol in the past month, and 43.4% were physically active. The subjects with sarcopenia were older, had a lower monthly household income, had a lower educational level, were predominantly married, resided mainly in a rural area, smoked and drank less, and performed less strength training than those with nonsarcopenia (all P < 0.001, except P = 0.002 for residing in a rural area). The mean BMI, waist circumference, and levels of SBP, DBP, FBG, and TG were higher, whereas the HDL-C level was lower, in the subjects with sarcopenia than in those with nonsarcopenia (all P < 0.001).
Table 1.

Baseline Characteristics of Subjects According to Sarcopenia

 TotalSarcopeniaNonsarcopenia 
VariableNe% (SE) or mean ± SDNe% (SE) or mean ± SDNe% (SE) or mean ± SDP
Number12,256100.0 (0.0)14429.5 (0.5)10,81490.5 (0.5) 
Metabolic syndrome patient330524.7 (0.5)73951.1 (1.7)256621.9 (0.5)<0.001
Male535050.2 (0.5)60344.4 (1.5)474750.8 (0.5)<0.001
Age (years)      <0.001
 20–39390340.3 (0.9)11111.8 (1.2)379243.3 (1.0) 
 40–64579947.0 (0.8)59348.8 (1.6)520646.8 (0.8) 
 ≧65255412.7 (0.5)73839.4 (1.7)18169.9 (0.4) 
Monthly household income      <0.001
 Lowest240216.1 (0.6)51432.6 (1.7)188814.4 (0.6) 
 Medium-lowest294224.6 (0.8)38525.7 (1.7)255724.5 (0.8) 
 Medium-highest339329.7 (0.8)30825.1 (1.6)308530.2 (0.8) 
 Highest337729.5 (0.9)21416.6 (1.5)316330.9 (1.0) 
Education level      <0.001
 ≦Elementary school314918.9 (0.7)76647.6 (1.9)238315.9 (0.6) 
 Middle school138210.3 (0.4)21515.0 (1.2)11679.8 (0.4) 
 High school415038.6 (0.7)28623.5 (1.4)386440.1 (0.8) 
 ≧College349932.2 (0.9)16214.0 (1.3)333734.1 (0.9) 
Marital status      <0.001
 Married10,60079.9 (0.7)138593.9 (0.9)921578.4 (0.8) 
 Unmarried163820.1 (0.7)546.1 (0.9)158421.6 (0.8) 
Residence      0.002
 Urban931779.9 (2.0)100874.2 (3.0)830980.5 (2.0) 
 Rural293920.1 (2.0)43425.8 (3.0)250519.5 (2.0) 
Current smoking267027.2 (0.5)22319.5 (1.4)244728.0 (0.6)<0.001
Monthly drinking658059.9 (0.7)61748.5 (1.7)596361.1 (0.7)<0.001
Physically active[a]523743.4 (0.6)61641.4 (1.6)462143.6 (0.7)0.220
Strength training[b]314929.0 (0.6)24519.6 (1.4)290430.0 (0.6)<0.001
No. of co-morbidities[c]      <0.001
 0640357.8 (0.7)38828.6 (1.5)601560.9 (0.7) 
 1331025.7 (0.5)43932.1 (1.5)287125.0 (0.5) 
 2169511.5 (0.4)38725.6 (1.5)130810.0 (0.4) 
 ≧37995.0 (0.2)22213.6 (1.1)5774.1 (0.2) 
Height (cm) 164.0 ± 0.1 154.5 ± 0.3 165.0 ± 0.1<0.001
Weight (kg) 63.9 ± 0.1 62.0 ± 0.4 64.1 ± 0.1<0.001
BMI (kg/m2) 23.7 ± 0.0 25.9 ± 0.1 23.4 ± 0.0<0.001
Waist circumference (cm) 80.9 ± 0.2 86.6 ± 0.4 80.3 ± 0.2<0.001
SBP (mmHg) 116.5 ± 0.3 126.4 ± 0.6 115.5 ± 0.3<0.001
DBP (mmHg) 75.3 ± 0.2 77.5 ± 0.4 75.0 ± 0.2<0.001
FBG (mg/dL) 96.8 ± 0.3 105.9 ± 1.0 95.8 ± 0.3<0.001
TG (mg/dL) 135.8 ± 1.4 166.8 ± 4.2 132.5 ± 1.6<0.001
HDL-C (mg/dL) 48.1 ± 0.1 45.7 ± 0.4 48.4 ± 0.1<0.001

Physically active was indicated as “yes” when the subject walked for more than 30 min at a time and more than five times per week.

Strength training was indicated as “yes” when the subject exercised strength training for more than 30 min at a time and more than one time per week.

Co-morbidities included hypertension, diabetics, dyslipidemia, cerebral vascular disease, arthritis, cancer, liver cirrhosis, and renal insufficiency.

BMI, body mass index; DBP, diastolic blood pressure; e%, estimated percentage; FBG, fasting blood glucose; HDL-C, high-density lipoprotein cholesterol; SBP, systolic blood pressure; SD, standard deviation; SE, standard error; TG, triglyceride.

Baseline Characteristics of Subjects According to Sarcopenia Physically active was indicated as “yes” when the subject walked for more than 30 min at a time and more than five times per week. Strength training was indicated as “yes” when the subject exercised strength training for more than 30 min at a time and more than one time per week. Co-morbidities included hypertension, diabetics, dyslipidemia, cerebral vascular disease, arthritis, cancer, liver cirrhosis, and renal insufficiency. BMI, body mass index; DBP, diastolic blood pressure; e%, estimated percentage; FBG, fasting blood glucose; HDL-C, high-density lipoprotein cholesterol; SBP, systolic blood pressure; SD, standard deviation; SE, standard error; TG, triglyceride.

Prevalence of metabolic syndrome according to sarcopenia

The prevalence of metabolic syndrome according to sarcopenia is shown in Table 2. The five components of metabolic syndrome (abdominal obesity, high blood pressure, high blood glucose level, high TG level, and low HDL-C level) were all higher in subjects with sarcopenia than in those with nonsarcopenia (all P < 0.001). In addition, metabolic syndrome prevalence was higher in the subjects with sarcopenia than in those with nonsarcopenia (P < 0.001).
Table 2.

Prevalence of Metabolic Syndrome According to Sarcopenia

VariableSarcopeniaNonsarcopeniaP
Abdominal obesity[a]49.2 (2.1)22.4 (0.6)<0.001
Higher blood pressure[b]54.6 (1.7)29.3 (0.7)<0.001
Higher blood glucose[c]45.9 (1.5)24.0 (0.6)<0.001
Higher triglyceride[d]43.6 (1.6)27.3 (0.5)<0.001
Lower HDL-C[e]54.3 (1.7)41.1 (0.6)<0.001
Metabolic syndrome51.3 (1.7)21.9 (0.5)<0.001

All values are presented as estimated percentage (SE).

Abdomal obesity is defined as waist circumference ≥90 cm (male) or ≥80 cm (female).

Higher blood pressure is defined as SBP ≥130 mmHg or DBP ≥85 mmHg.

Higher blood glucose is defined as FBG ≥100 mg/dL.

Higher triglyceride is defined as TG ≥150 mg/dL.

Lower HDL-C is defined as HDL-C < 40 mg/dL (male) or <50 mg/dL (female).

Prevalence of Metabolic Syndrome According to Sarcopenia All values are presented as estimated percentage (SE). Abdomal obesity is defined as waist circumference ≥90 cm (male) or ≥80 cm (female). Higher blood pressure is defined as SBP ≥130 mmHg or DBP ≥85 mmHg. Higher blood glucose is defined as FBG ≥100 mg/dL. Higher triglyceride is defined as TG ≥150 mg/dL. Lower HDL-C is defined as HDL-C < 40 mg/dL (male) or <50 mg/dL (female).

Odds ratios for sarcopenia according to metabolic syndrome

The odds ratios (ORs) for sarcopenia according to metabolic syndrome are shown in Table 3. The crude ORs for sarcopenia were statistically significant (OR 3.73, 95% confidence interval [CI] 3.21–4.33). After adjusting for sex, age, monthly household income, education level, marital status, residence, current smoking, monthly drinking, physical activities, strength training, and number of co-morbidities, the OR showed that the significant association between metabolic syndrome and sarcopenia remained (OR 2.06, 95% CI 1.74–2.45).
Table 3.

Odds Ratios for Sarcopenia According to Metabolic Syndrome

 NonadjustedAdjusted[a]
VariablesOR (95% CI)OR (95% CI)
Nonmetabolic syndromeReferenceReference
Metabolic syndrome3.73 (3.21–4.33)2.06 (1.74–2.45)

Adjusted by sex, age, monthly household income, education level, marital status, residence, current smoking, monthly drinking, physical activities, strength training, and number of co-morbidities.

CI, confidence interval; OR, odds ratio.

Odds Ratios for Sarcopenia According to Metabolic Syndrome Adjusted by sex, age, monthly household income, education level, marital status, residence, current smoking, monthly drinking, physical activities, strength training, and number of co-morbidities. CI, confidence interval; OR, odds ratio.

ORs for sarcopenia according to metabolic syndrome stratified by age group

The ORs for sarcopenia according to metabolic syndrome stratified by age group are shown in Table 4. After adjusting for same covariates, the association between metabolic syndrome and sarcopenia was significant in subjects 20–39 years (OR 2.13, 95% CI 1.08–4.19), 40–64 years (OR 2.13, 95% CI 1.68–2.71), and ≥65 years (OR 1.98, 95% CI 1.54–2.54) of age.
Table 4.

Odds Ratios for Sarcopenia According to Metabolic Syndrome Stratified by Age Group

  NonadjustedAdjusted[a]
Age (years)Metabolic syndromeOR (95% CI)OR (95% CI)
20–39Nonmetabolic syndromeReferenceReference
Metabolic syndrome3.42 (2.08–5.63)2.13 (1.08–4.19)
40–64Nonmetabolic syndromeReferenceReference
Metabolic syndrome2.53 (2.06–3.11)2.13 (1.68–2.71)
≥65Nonmetabolic syndromeReferenceReference
Metabolic syndrome2.07 (1.68–2.55)1.98 (1.54–2.54)

Adjusted by sex, monthly household income, education level, marital status, residence, current smoking, monthly drinking, physical activities, strength training, and number of co-morbidities.

Odds Ratios for Sarcopenia According to Metabolic Syndrome Stratified by Age Group Adjusted by sex, monthly household income, education level, marital status, residence, current smoking, monthly drinking, physical activities, strength training, and number of co-morbidities.

Discussion

This study investigated the relationship between sarcopenia and metabolic syndrome in Korean adults using data from the 2009–2010 KNHANES. After adjustment for covariates, we found that sarcopenia was significantly associated with metabolic syndrome. In addition, after stratifying the study population by age, this significant association remained in all age groups. There is no consensus on clinical diagnostic standards for sarcopenia, and previous researchers have used different diagnostic criteria: ASM/height2,[23] ASM/weight,[24] and ASM/BMI.[20] Baumgartner et al.[23] diagnosed sarcopenia as an ASM/height2 > 2 SD below the mean in a young reference population and they reported that sarcopenia prevalence of 14% and >50% in those 65–69 and ≥80 years of age, respectively, in New Mexico. Janssen et al.[24] defined sarcopenia using ASM/weight and the sarcopenia prevalence was 7% and 11% in male and female ≥80 years of age. A problem associated with the various diagnostic methods in prior studies is the selection of a young healthy reference population. In addition, the ability to compare results is limited since the reference populations differ among studies. Therefore, to clarify the diagnostic criteria for sarcopenia, the Foundation for the National Institutes of Health (FNIH) Sarcopenia Project used data from nine cohorts and defined sarcopenia as an ASM/BMI of <0.789 for males and <0.521 for females, without comparison to a young reference population.[20] The prevalence of sarcopenia in South Koreans differed from study to study due to various diagnostic criteria. In this study using the FNIH definition, we found that the prevalence of sarcopenia was 9.5% (male 8.4% and female 10.7%) in ≥20 years of age and 14.1% (male 12.7% and female 15.4%) in ≥40 years of age. In a study using 2008–2009 KNHANES data, sarcopenia was defined according to two methods: ASM/height2 and ASM/weight that was greater than 2 SD below the mean in healthy individuals 20–39 years of age. The prevalence of sarcopenia in males and females >40 years of age was 12.4% and 0.1% according to ASM/height2 and 9.7% and 11.8% according to ASM/weight, respectively.[25] In another study based on 2008–2011 KNHANES data, sarcopenia was defined according to ASM/weight, and the prevalence of sarcopenia in subjects >20 years of age was 26.8%,[11] which was significantly higher than our results (9.5%). The reason for the higher prevalence of sarcopenia is that the authors used an ASM/weight >1 SD below the mean in a young reference population instead of an ASM/weight >2 SD as the diagnostic criteria for sarcopenia. In this study, after adjustment for other covariates, the association between sarcopenia and metabolic syndrome was significant. In a meta-analysis of middle-aged and older nonobese adults,[26] sarcopenia was significantly associated with metabolic syndrome (OR 2.01, 95% CI 1.63–2.47), which is consistent with our results. In a previous study involving 1971 elderly Japanese subjects ≥65 years of age,[16] metabolic syndrome was significantly associated with sarcopenia in males (OR 2.08, 95% CI 1.22–3.54), but not in females. In Korea, 4183 postmenopausal females were analyzed using the 2008–2011 KNHANES data,[14] and a statistically significant relationship was identified between sarcopenia and metabolic syndrome (OR 1.97, 95% CI 1.51–2.56). In this study, after stratifying the study population by age, the association between sarcopenia and metabolic syndrome was significant in all age groups evaluated (20–39, 40–64, and ≥65 years). In a previous study of 5300 adults 19–39 years of age, which used 2008–2010 KNHANES data, low muscle mass was defined according to ASM/weight and was significantly associated with metabolic syndrome in young adults, which is consistent with our results.[27] Most previous studies have evaluated the relationship between sarcopenia and metabolic syndrome in the elderly because muscle mass and muscle strength are assumed to decrease the most with age. However, it has been reported that the percentage of total lean body mass begins to decrease starting in the early 30s, and that sarcopenia can occur in younger populations.[28] However, in the case of sarcopenia, the pattern varies according to age. Sarcopenia in the elderly is accompanied by selective atrophy of type II muscle fibers, whereas sarcopenia in young adults is accompanied by an overall decrease in muscle mass.[29] Metabolic syndrome consists of five components: abdominal obesity, high blood pressure, high blood glucose level, high TG level, and low HDL-C level. Insulin resistance and inflammation are considered the central mechanisms responsible for metabolic syndrome.[30] Several mechanisms may underlie the association between sarcopenia and metabolic syndrome. First, skeletal muscle is the most important organ for systemic glucose homeostasis[31] and is responsible for ∼80% of normal glucose absorption and metabolism by insulin stimulation under normal conditions.[32] Second, a decrease in muscle mass leads to an increase in fat mass by reducing the basal metabolic rate.[33] Increased levels of fat increase the secretion of inflammatory cytokines such as tumor necrosis factor-alpha and interleukin (IL)-6[34] and increase insulin resistance, which can eventually lead to metabolic syndrome.[31,35] Third, skeletal muscle cells express and secrete many myokines, including IL-6, IL-8, IL-15, fibroblast growth factor 21, irisin, myonectin, and myostatin.[36] Most myokines are controlled primarily by exercise and muscle exertion. They offset the deleterious effects of inflammatory cytokines and have beneficial effects on glucose and lipid metabolism as well as inflammation.[37] The limitations of this study are as follows. First, it was difficult to clarify causality because of the cross-sectional design. Second, a new guideline of the European Working Group on Sarcopenia in Older People in 2018 recommended measuring muscle strength as well as muscle mass to diagnose sarcopenia.[10] However, the 2009–2010 KNHANES did not measure muscle strength. Nevertheless, this study is meaningful in that, it investigated the relationship between sarcopenia and metabolic syndrome in all adults older than 20 years using representative data from Korea. In conclusion, after adjusting for covariates, the association between sarcopenia and metabolic syndrome was significant in South Korean adults. Moreover, after stratifying by age groups, the significant associations between sarcopenia and metabolic syndrome remained in all age groups.
  34 in total

Review 1.  Metabolic syndrome and risk of incident cardiovascular events and death: a systematic review and meta-analysis of longitudinal studies.

Authors:  Apoor S Gami; Brandi J Witt; Daniel E Howard; Patricia J Erwin; Lisa A Gami; Virend K Somers; Victor M Montori
Journal:  J Am Coll Cardiol       Date:  2007-01-12       Impact factor: 24.094

2.  Prevalence of sarcopenia and sarcopenic obesity in the Korean population based on the Fourth Korean National Health and Nutritional Examination Surveys.

Authors:  Young-Sang Kim; Yunhwan Lee; Yoon-Sok Chung; Duck-Joo Lee; Nam-Seok Joo; Doohee Hong; Go eun Song; Hyeon-Jeong Kim; Yong Jun Choi; Kwang-Min Kim
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2012-03-19       Impact factor: 6.053

3.  Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability.

Authors:  Ian Janssen; Steven B Heymsfield; Robert Ross
Journal:  J Am Geriatr Soc       Date:  2002-05       Impact factor: 5.562

4.  Sarcopenic obesity and inflammation in the InCHIANTI study.

Authors:  Matthew A Schrager; E Jeffrey Metter; Eleanor Simonsick; Alessandro Ble; Stefania Bandinelli; Fulvio Lauretani; Luigi Ferrucci
Journal:  J Appl Physiol (1985)       Date:  2006-11-09

5.  Low skeletal muscle mass is associated with insulin resistance, diabetes, and metabolic syndrome in the Korean population: the Korea National Health and Nutrition Examination Survey (KNHANES) 2009-2010.

Authors:  Seong-Su Moon
Journal:  Endocr J       Date:  2013-10-01       Impact factor: 2.349

6.  Increasing prevalence of metabolic syndrome in Korea: the Korean National Health and Nutrition Examination Survey for 1998-2007.

Authors:  Soo Lim; Hayley Shin; Jung Han Song; Soo Heon Kwak; Seon Mee Kang; Ji Won Yoon; Sung Hee Choi; Sung Il Cho; Kyong Soo Park; Hong Kyu Lee; Hak Chul Jang; Kwang Kon Koh
Journal:  Diabetes Care       Date:  2011-04-19       Impact factor: 19.112

7.  Obesity and metabolic syndrome in Korea.

Authors:  Sang Woo Oh
Journal:  Diabetes Metab J       Date:  2011-12-26       Impact factor: 5.376

8.  Metabolic syndrome, sarcopenia and role of sex and age: cross-sectional analysis of Kashiwa cohort study.

Authors:  Shinya Ishii; Tomoki Tanaka; Masahiro Akishita; Yasuyoshi Ouchi; Tetsuo Tuji; Katsuya Iijima
Journal:  PLoS One       Date:  2014-11-18       Impact factor: 3.240

9.  Objectively measured light-intensity lifestyle activity and sedentary time are independently associated with metabolic syndrome: a cross-sectional study of Japanese adults.

Authors:  Junghoon Kim; Kai Tanabe; Noriko Yokoyama; Hirofumi Zempo; Shinya Kuno
Journal:  Int J Behav Nutr Phys Act       Date:  2013-03-04       Impact factor: 6.457

10.  Data resource profile: the Korea National Health and Nutrition Examination Survey (KNHANES).

Authors:  Sanghui Kweon; Yuna Kim; Myoung-jin Jang; Yoonjung Kim; Kirang Kim; Sunhye Choi; Chaemin Chun; Young-Ho Khang; Kyungwon Oh
Journal:  Int J Epidemiol       Date:  2014-02       Impact factor: 7.196

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  11 in total

1.  Oculomics for sarcopenia prediction: a machine learning approach toward predictive, preventive, and personalized medicine.

Authors:  Bo Ram Kim; Tae Keun Yoo; Hong Kyu Kim; Ik Hee Ryu; Jin Kuk Kim; In Sik Lee; Jung Soo Kim; Dong-Hyeok Shin; Young-Sang Kim; Bom Taeck Kim
Journal:  EPMA J       Date:  2022-08-08       Impact factor: 8.836

2.  Prevalence of Metabolic Syndrome and Association with Grip Strength in Older Adults: Findings from the HOPE Study.

Authors:  Reshma Aziz Merchant; Yiong Huak Chan; Jia Yi Lim; John E Morley
Journal:  Diabetes Metab Syndr Obes       Date:  2020-07-27       Impact factor: 3.168

Review 3.  Physical Exercise and Myokines: Relationships with Sarcopenia and Cardiovascular Complications.

Authors:  Sandra Maria Barbalho; Uri Adrian Prync Flato; Ricardo José Tofano; Ricardo de Alvares Goulart; Elen Landgraf Guiguer; Cláudia Rucco P Detregiachi; Daniela Vieira Buchaim; Adriano Cressoni Araújo; Rogério Leone Buchaim; Fábio Tadeu Rodrigues Reina; Piero Biteli; Daniela O B Rodrigues Reina; Marcelo Dib Bechara
Journal:  Int J Mol Sci       Date:  2020-05-20       Impact factor: 5.923

4.  Association between sarcopenia level and metabolic syndrome.

Authors:  Su Hwan Kim; Ji Bong Jeong; Jinwoo Kang; Dong-Won Ahn; Ji Won Kim; Byeong Gwan Kim; Kook Lae Lee; Sohee Oh; Soon Ho Yoon; Sang Joon Park; Doo Hee Lee
Journal:  PLoS One       Date:  2021-03-19       Impact factor: 3.240

Review 5.  Harnessing Muscle-Liver Crosstalk to Treat Nonalcoholic Steatohepatitis.

Authors:  Manu V Chakravarthy; Mohammad S Siddiqui; Mikael F Forsgren; Arun J Sanyal
Journal:  Front Endocrinol (Lausanne)       Date:  2020-12-23       Impact factor: 5.555

6.  A study of correlations between metabolic syndrome factors and osteosarcopenic adiposity.

Authors:  Yu-Hsiang Su; Yu-Ming Chang; Chih-Ying Kung; Chiu-Kuei Sung; Wei-Shin Foo; Mei-Hua Wu; Shang-Jyh Chiou
Journal:  BMC Endocr Disord       Date:  2021-10-29       Impact factor: 2.763

7.  Serum 25-hydroxy vitamin D and the risk of low muscle mass in young and middle-aged Korean adults.

Authors:  Yejin Kim; Yoosoo Chang; Seungho Ryu; In Young Cho; Min-Jung Kwon; Sarah H Wild; Christopher D Byrne
Journal:  Eur J Endocrinol       Date:  2022-03-08       Impact factor: 6.664

8.  An analysis study of sarcopenia and locomotive syndrome in the old people using evaluation tool.

Authors:  Myung-Chul Kim; Hang-Sik Park; Hae-In Kim; Jean-Kyung Paik; Dong-Kun Chung
Journal:  J Exerc Rehabil       Date:  2022-08-26

9.  The Association of Low Skeletal Muscle Mass with Complex Distal Radius Fracture.

Authors:  Chi-Hoon Oh; Junhyun Kim; Junhan Kim; Siyeong Yoon; Younghoon Jung; Hyun Il Lee; Junwon Choi; Soonchul Lee; Soo-Hong Han
Journal:  J Clin Med       Date:  2022-09-22       Impact factor: 4.964

10.  Additive Effect of Sarcopenia and Anemia on the 10-Year Risk of Cardiovascular Disease in Patients with Type 2 Diabetes.

Authors:  Feihui Zeng; Lingning Huang; Yongze Zhang; Xinyu Hong; Suiyan Weng; Ximei Shen; Fengying Zhao; Sunjie Yan
Journal:  J Diabetes Res       Date:  2022-01-24       Impact factor: 4.011

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