Indicators of Absolute and Relative Changes in Skeletal Muscle Mass during Adulthood and Ageing

Milivoj Dopsaj, Filip Kukić, Marina Đorđević-Nikić, Nenad Koropanovski, Dragan Radovanović, Dragan Miljuš, Dane Subošić, Milena Tomanić and Violeta Dopsaj
Additional contact information
Milivoj Dopsaj: Faculty of Sport and Physical Education University of Belgrade, 11030 Belgrade, Serbia
Filip Kukić: Faculty of Sport and Physical Education University of Belgrade, 11030 Belgrade, Serbia
Marina Đorđević-Nikić: Faculty of Sport and Physical Education University of Belgrade, 11030 Belgrade, Serbia
Nenad Koropanovski: Department of Criminalistics, University of Criminal Investigation and Police Studies, 11080 Belgrade, Serbia
Dragan Radovanović: Faculty of Sport and Physical Education University of Nis, 18000 Nis, Serbia
Dragan Miljuš: Epidemiology and Surveillance Department, Institute of Public Health of Serbia “Dr Milan Jovanović Batut”, 11000 Belgrade, Serbia
Dane Subošić: Department of Criminalistics, University of Criminal Investigation and Police Studies, 11080 Belgrade, Serbia
Milena Tomanić: Institute of Hygiene and Medical Ecology, Medical Faculty University of Belgrade, 11000 Belgrade, Serbia
Violeta Dopsaj: Department of Biochemistry, Faculty of Pharmacy University of Belgrade, 11221 Belgrade, Serbia

IJERPH, 2020, vol. 17, issue 16, 1-13

Abstract: This study aimed to explore the set of variables related to skeletal muscle mass (SMM) in both sexes, and to create age- and sex-related models of changes in SMM, using the most representative indicator of muscular status. Body composition was assessed in 8733 subjects (? = 3370 and ? = 5363), allocated into subsamples according to age: 18–29.9, 30–39.9, 40–49.9, 50–59.9, 60–69.9, and 70.0–79.9 years. Nine variables were used: protein mass, protein percent, protein mass index, SMM, percent of SMM, SMM index, fat-free mass, fat-free mass index, and protein/fat index. Univariate and multivariate analysis of variance (ANOVA and MANOVA) were used to determine between- and within-sex difference in all variables by age. Correlation analysis established the relationship between age and muscularity variables. Principal Component Analysis extracted the variables that loaded highest in explaining muscularity, while regression analysis determined the linearity of association between the age and indicators of muscular status. Variables SMMI and PSMM were extracted as the most sensitive to age, with SMMI being gender-independent while showing the parabolic and sinusoidal form of change as function of ageing in males and females, respectively; and PSMM being sex-dependent while showing a linear trend of decrease in both sexes.

Keywords: proteins; skeletal muscle loss; sarcopenia; physical activity; quality of life (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://www.mdpi.com/1660-4601/17/16/5977/pdf (application/pdf)
https://www.mdpi.com/1660-4601/17/16/5977/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:17:y:2020:i:16:p:5977-:d:400258

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().