Association between Skeletal Mass Indices and Metabolic Syndrome in Brazilian Adults

Cristiane Junqueira de Carvalho; Giana Zarbato Longo; Adriana Maria Kakehasi; Patrícia Feliciano Pereira; Kátia Josiany Segheto; Leidjaira Lopes Juvanhol; Andréia Queiroz Ribeiro

doi:10.1016/j.jocd.2020.02.003

Association between Skeletal Mass Indices and Metabolic Syndrome in Brazilian Adults

J Clin Densitom. 2021 Jan-Mar;24(1):118-128. doi: 10.1016/j.jocd.2020.02.003. Epub 2020 Feb 24.

Authors

Cristiane Junqueira de Carvalho¹, Giana Zarbato Longo², Adriana Maria Kakehasi³, Patrícia Feliciano Pereira², Kátia Josiany Segheto², Leidjaira Lopes Juvanhol², Andréia Queiroz Ribeiro²

Affiliations

¹ Department of Medicine and Nursing, Federal University of Viçosa (UFV), Viçosa, Minas Gerais, Brazil; Postgraduate Program in Nutrition Science, Department of Nutrition and Health, Federal University of Viçosa (UFV), Viçosa, Minas Gerais, Brazil. Electronic address: cristiane.carvalho@ufv.br.
² Postgraduate Program in Nutrition Science, Department of Nutrition and Health, Federal University of Viçosa (UFV), Viçosa, Minas Gerais, Brazil.
³ Department of the Locomotor Apparatus, Medical School, Federal University of Minas Gerais (UFMG), Belo Horizonte, Minas Gerais, Brazil.

PMID: 32205007
DOI: 10.1016/j.jocd.2020.02.003

Abstract

Introduction: Skeletal muscle is the primary site of glucose uptake and its reduction would increase insulin resistance, which is a determinant factor for diseases such as type 2 diabetes mellitus, hypertension, and metabolic syndrome. However, the role of low skeletal muscle mass as a risk factor for metabolic syndrome and its association with cardiometabolic risk is still uncertain. We aimed to investigate the association between muscle mass (determined by different skeletal mass indices) and metabolic syndrome in Brazilian adults.

Methodology: We conducted a cross-sectional population-based study with 689 adults of both sexes aged between 20 and 59 years. Data were collected through questionnaires and assessment of body composition through dual-energy X-ray absorptiometry and anthropometric, clinical, and biochemical measurements.

Results: Older individuals, obese and those with metabolic syndrome predominated in the highest tertile of skeletal mass index adjusted by height (SMI_height), whereas using skeletal mass index adjusted by weight (SMI_weight) and skeletal mass index adjusted by body mass index (SMI_BMI) these individuals were the majority in the lowest tertile of these indices. In men and women, the adjusted logistic regression model revealed that the highest tertile of SMI_weight (odds ratio [OR]: 0.06; 95% confidence interval [CI]: 0.02-0.21 and OR: 0.27, 95% CI: 0.10-0.74) and SMI_BMI (OR: 0.14, 95% CI: 0.05-0.37 and OR: 0.34, 95% CI: 0.12-0.94) were negatively associated with metabolic syndrome. On the other hand, the highest tertile of SMI_height was positively associated with metabolic syndrome in both sexes (OR: 4.17, 95% CI: 1.80-9.66 and OR: 6.15, 95% CI: 2.31-16.37, respectively in men and women).

Conclusion: In adults, the muscle mass assessed from the skeletal mass index adjusted for body weight and body mass index is inversely associated with metabolic syndrome in both sexes.

Keywords: DXA; Sarcopenia; body composition; metabolic syndrome; skeletal muscle.

Publication types

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

MeSH terms

Absorptiometry, Photon
Adult
Body Composition
Body Mass Index
Cross-Sectional Studies
Diabetes Mellitus, Type 2*
Female
Humans
Male
Metabolic Syndrome* / epidemiology
Middle Aged
Muscle, Skeletal / diagnostic imaging
Sarcopenia*
Young Adult