Association between sarcopenia level and metabolic syndrome

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

doi:10.1371/journal.pone.0248856

Association between sarcopenia level and metabolic syndrome

PLoS One. 2021 Mar 19;16(3):e0248856. doi: 10.1371/journal.pone.0248856. eCollection 2021.

Authors

Su Hwan Kim^{1

2}, Ji Bong Jeong¹, Jinwoo Kang¹, Dong-Won Ahn¹, Ji Won Kim¹, Byeong Gwan Kim¹, Kook Lae Lee¹, Sohee Oh³, Soon Ho Yoon⁴, Sang Joon Park⁴, Doo Hee Lee⁵

Affiliations

¹ Department of Internal Medicine, Seoul National University College of Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, Republic of Korea.
² Health Care Center, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, Republic of Korea.
³ Medical Research Collaborating Center, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, Republic of Korea.
⁴ Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
⁵ Department of Research and Development, MEDICALIP Co, Ltd., Seoul, Korea.

Abstract

Aims: Metabolic syndrome (MetS) increases the risk of diabetes mellitus (DM), cardiovascular disease (CVD), cancer, and mortality. Sarcopenia has been reported as a risk factor for MetS, non-alcoholic fatty liver disease, and CVD. To date, the association between sarcopenia and MetS has been investigated. However, there have been few studies on the dose-response relationship between sarcopenia and MetS. We investigated the association between sarcopenia and the prevalence of MetS. We also aimed to analyze the dose-response relationship between skeletal muscle mass and the prevalence of MetS.

Methods: We enrolled 13,620 participants from October 2014 to December 2019. Skeletal muscle mass was measured using bioelectrical impedance analysis (BIA). Appendicular skeletal muscle mass (ASM) was divided by body weight (kg) and was expressed as a percentage (ASM x 100/Weight, ASM%). The quartiles of ASM% were calculated for each gender, with Q1 and Q4 being the lowest and highest quartiles of ASM%, respectively. The quartiles of ASM% were calculated for each gender, with Q1 and Q4 being the lowest and highest quartiles of ASM%, respectively. Linear regression and logistic regression analyses were used to compare the clinical parameters according to ASM%, adjusted for age, sex, obesity, hypertension (HT), DM, dyslipidemia (DL), smoking, alcohol intake, and C-reactive protein (CRP). Multiple logistic regression analysis was performed to determine the risk of MetS in each group.

Results: A dose-response relationship was identified between ASM% and MetS. Sarcopenia was associated with an increased prevalence of MetS. After adjustment for age, sex, obesity, HT, DM, DL, smoking, alcohol intake, and CRP, sarcopenia remained significantly associated with MetS. For each 1 quartile increment in ASM%, the risk of MetS decreased by 56% (P< 0.001). After adjusting for age, sex, obesity, HT, DM, DL, smoking, alcohol intake, and CRP, the risk of MetS decreased by 25% per 1Q increment in ASM% (P < 0.001).

Conclusions: Sarcopenia by BIA is independently associated with the risk of MetS and has a dose-response relationship.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Abdominal Fat / diagnostic imaging
Abdominal Fat / pathology
Adult
Female
Humans
Male
Metabolic Syndrome / complications*
Metabolic Syndrome / epidemiology
Middle Aged
Muscles / diagnostic imaging
Muscles / pathology
Organ Size
Prevalence
Sarcopenia / complications*
Sarcopenia / epidemiology
Tomography, X-Ray Computed

Grants and funding

MEDICALIP Co, Ltd. provided support in the form of salaries for author DHL, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.