Profile and Reference Values for Body Fat and Skeletal Muscle

1286

Int. J. Morphol.,

37(4):1286-1293, 2019.

Profile and Reference Values for Body Fat and Skeletal

Muscle Mass Percent at Females, Aged from 18.0 to 69.9,

Measured by Multichannel Segmental Bioimpedance Method:

Serbian Population Study

Perfil y Valores de Referencia del Porcentaje de Grasa Corporal y Masa Muscular en

Mujeres, con Edades Comprendidas entre 18,0 y 69,9 Años, Medido por el Método de

Bioimpedancia Segmentaria Multicanal: Estudio en Población Serbia

Rakic Sladjana

; Dopsaj Milivoj

1,5

; Djordjevic-Nikic Marina

; Vasiljevic Nadja

;

Dopsaj Violeta

; Maksimovic Milos

; Tomanic, S. Milena

& Miljus Dragan

RAKIC, S.; DOPSAJ, M.; DJORDJEVIC-NIKIC, M.; VASILJEVIC, N.; DOPSAJ, V.; MAKSIMOVIC, M.; TOMANIC, S. M.

& MILJUS, D. Profile and reference values for body fat and skeletal muscle mass percent at females, aged from 18.0 to 69.9, measured

by multichannel segmental bioimpedance method: Serbian population study. Int. J. Morphol., 37(4):1286-1293, 2019.

SUMMARY: Profile and standards for the diagnostics of percent of body fat and muscles were defined on a sample of 1924

women from the Republic of Serbia, aged 18.0 to 69.9, where the body structure of subjects was measured by applying multichannel

segmental bioimpedance. Total sample was divided into six age groups, for the purpose of the definition of standard with regards to age.

When it comes to body fat percentage results have shown that the average value of the total sample was 28.51±9.26 %, and between the

range of 23.81 and 39.94 % for age groups 18.0-19.9 yr and 60.0-69.9 yr, respectively. Regression analysis results have shown that the

constant of body fat percentage increase by trend of 3.417 % per decade, and that 25.1 % of mutual variance trend was explained by the

model, with prediction error of 4.55 %. With regards to the percentage of skeletal muscles in the body, the results have shown that the

average value of the total sample was 39.30±5.25 %, and within the range of 42.25 to 32.58 % for age groups 18.0-19.9 yr and 60.0-69.9

yr, respectively. Regression analysis results have shown that the constant of the skeletal muscles decrease by tend of -2.016 % per decade

and that the model explained 23.8 % of mutual variance trend with prediction error of 8.08 %.

KEY WORDS: Females; Body Composition Profile; Bioimpedance; Body Fat; Skeletal Muscle Mass.

INTRODUCTION

It is a global fact that the modern way of life is

characterized by sedentariness or insufficient level of

physical activity (Haskell et al., 2007; Owen et al., 2010;

Maksimovic et al., 2016). Being very useful on the one hand,

technical achievements of civilization negatively impact life

quality on the other hand, which relates to the health aspect

in particular, where non-infectious diseases are concerned.

Unfortunately, the business aspect and business sector to

which the modern man belongs, condition increasing

physical passivity, because thanks to workplace

modernization all the work is being done in a sitting position.

On the other side, even though the modern age man has an

ever increasing amount of free time, the population has

become increasingly physically inactive, the main reasons

being computer use, the Internet, mobile phones and

watching television (Hallal et al., 2012). Additionally, via

the phenomenon of the cause-effect connection, lack of

physical activity has as a consequence led to decreased

motivation for practicing it (Sallis et al., 2015).

Unfortunately, overabundant and irregular diet, in addition

to physical activity that is inconsistent and of insufficient

scope, are increasingly becoming dominant habits and a

comprising part of modern man’s life (Menotti et al., 2014;

Maksimovic et al.).

Faculty of Sport and Physical Education, University of Belgrade, Belgrade, Serbia.

Institute of Hygiene and Medical Ecology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia.

Pharmaceutical Faculty, University of Belgrade, Belgrade, Serbia.

Institute of Public Health of Serbia “Dr Milan Jovanovic Batut”, Belgrade, Serbia.

SUSU, South Ural State University, Institute of Sport, Tourism and Service, Chelyabinsk, Russia.

1287

According to data from many scientific studies the

phenomenon of hypokinesis, i.e. insufficient physical

activity, has become the global public health problem in the

21st century (Hallal et al.), while epidemiological studies

have shown that three factors, such as: bad diet, stress

connected to the modern way of life and hypokinesis, are

the main cause of increase in the prevalence of non-infectious

diseases (Haskell et al.; Owen et al.; Menoti et al.).

A system for controlling the status of body

composition, through continued monitoring of the given state

of the organism, is increasingly becoming a part of the very

important health mechanism with the goal of tracking the

condition and ascertaining the trends of change in the given

conditions among the general populace (Gába & Pridalová,

2014; Ihász et al., 2015) or some specific population, such

as athletes, regardless of sex, age or type of sport (Dopsaj et

al., 2017; Bankovic et al., 2018). Also, defining the

characteristics of the model for the body composition status

condition among people represents an expert and scientific

attitude of decision making on whether a certain tissue

component is insufficiently, normally or predominantly

represented in the body (Bankovic et al.; Saraykin et al.,

2018), that is, if there exists an effect of an applied treatment

and how big it is, regardless whether it is diet correction or

physical activity treatment (Rocha et al., 2018). This is even

more pronounced with the advent of new technologies for

the measurement of body components, based on the principle

of bioimpedance, and especially new technology of

multichannel multisegment bioimpedance as being very

medically precise and easily available measurement

technology for all body composition characteristics (Ling

et al., 2011; Saraykin et al.).

From the perspective of anatomy, physiology and

biology the female organism is very specific. Cyclical

secretion of sex hormones during the reproductive period,

pregnancy, childbirth, maternity, menopause, professional

obligations and daily activities all have a great effect on body

status (Thompson et al., 2004; Kukic et al., 2019).

On the other hand, along with a considerable number

of published researches that tested body composition of

women of various ages by applying the method of segmental

multichannel bioimpedance (Gába & Pridalová; Ihász et al.;

Kukic et al., 2019) there are still no researches that define

the standards and normatives for evaluating the status of

two very important, if not the most important, body status

characteristics, and those are: percentage of body fat (PBF)

and percentage of skeletal muscles in the body (PSMM).

The goal of this paper is to define standards and

normatives for evaluation of body status among women of

various ages according to two variables: percentage of body

fat (PBF) and percentage of skeletal muscles in the body

(PSMM), measured by the method of segmental

multichannel bioimpedance. Acquired results will serve as

a qualitative and quantitative criterion for evaluation of given

variables among general population of healthy women of

various ages, with regards to the medical, health and

scientific aspect.

MATERIAL AND METHOD

This research belongs to the Transversal Survey

Study, whereas regarding meauserement it belongs to the

method of laboratory research with direct measurement. The

sample of respondents was gathered via a randomized

method with a combined approach to selecting the

respondents (measurement announcements were given

through the media, personal acquaintances and systematic

testing of different companies).

Subjects Sample. The research was conducted on a sample

of 1924 women (Ages = 35.5±10.8 yr, BH = 168.3±7.2 cm,

BM=68.1±14.5 kg, BMI = 24.08±5.2 km•m-2; 47.6 % of

respondents were from the urban, 34.8 % from suburban

and 17.6 % from rural areas; also, 46.3 % were from the

central, 33.9 % from the southern, and 19.8 % from the

northern part of Republic of Serbia). At the time of the

measurement all respondents were without acute clinical

health problems. Measurements for the purpose of this study

were conducted in the period between 2015 and 2018 using

the same apparatus (InBody720) and applying the same

measurement technology in two institutions: University of

Belgrade’s Faculty of Sport and Physical Education’s and

Faculty of Medicine’s Institute for Hygiene and Medical

Ecology in Belgrade. During the research period both

measurement instruments were regularly maintenanced and

calibrated according to the manufacturer’s instructions.

All respondents have been informed as to the purpose

of the research and have willingly consented to it. The

research was realized in accordance with the roles of

Declaration of Helsinki: Recommendations Guiding

Physicians in Biomedical Research Involving Human

Subjects (Christie, 2000).

Testing. Body composition was measured using the

standardized method of multichannel bioelectrical

impedance analysis (BIA). BIA machine InBody 720

(Biospace, Co., Ltd), with tetra-polar 8-point tactile electrode

system sends bioelectrical currents of different frequencies,

each of which estimates the amount of the corresponding

RAKIC, S.; DOPSAJ, M.; DJORDJEVIC-NIKIC, M.; VASILJEVIC, N.; DOPSAJ, V.; MAKSIMOVIC, M.; TOMANIC, S. M. & MILJUS, D. Profile and reference values for body fat and

skeletal muscle mass percent at females, aged from 18.0 to 69.9, measured by multichannel segmental bioimpedance method: Serbian population study. Int. J. Morphol., 37(4):1286-1293, 2019.

1288

tissue by the electrical resistance that certain tissue provides.

InBody 720 was shown measurement reliability with ICC =

0.97, and comparing to DXA method correlate with r = 0.93

overall and segmental body composition in female (Ling et

al.; Esco et al., 2015).

Variables. Only two variables were chosen for the purpose

of this research, these being standardly used in defining the

body status, and they represent relative values of the total

mass of fat tissue and total mass of skeletal muscle tissue in

relation to voluminosity dependence. All variables were

analyzed with regards to the following six age groups: 18.0-

19.9 yr, 20.0-29.9 yr, 30.0-39.9 yr, 40.0-49.9 yr, 50.0-59.9

yr, and 60.-69.9 yr, and the given variables were:

1. PBF – percentage of body fat mass, calculated as: relation

between body fat (BF) and body mass (BM) in kg,

expressed in %;

2. PSMM – percentage of skeletal muscle mass, calculated

as: relation between skeletal muscle mass (SMM) and

body mass (BM) in kg, expressed in %.

Statistics. After the measurement all the results were

transferred to Microsoft Excel database, where logical data

verification was performed. After that they were subjected

to basic descriptive analysis to calculate mean value

(MEAN), standard deviation (SD), variation coefficient (cV

%), minimum and maximum values (Min and Max), as well

as 95 % confidence intervals of variables. For the purpose

of defining measurement precision, as result validation of

this multicentric study, standard measurement error (SEM)

was calculated in relative values (in %). Criteria values of

distribution classes were defined at the level of 2.5, 5.0, 10.0,

25.0, 50.0, 75.0, 90.0, 95.0 and 97.5 percentiles, while

procedure according to Zactsiorsky (Zatsiorsky, 1982) was

used in relation to the athletic metrological criterion of

qualitative definition of seven part normative (Zatsiorsky).

Differences between analyzed age groups were established

by applying a single variant variance analysis ANOVA,

whereas Bonferoni post-hoc criterion was used for

establishing the differences between individual pair groups.

Trend analysis of observed phenomena in the function of

age groups was defined with the help of linear regression

analysis. The Statistical Package for Social Sciences (IBM,

SPSS Statistics 20) was used for all statistical analyses, while

the significance level was set at 95 % level of confidence at

p < 0.05 (Hair et al., 1998).

RESULTS

Basic descriptive results are shown in Table I.

Results showed that PBF among respondents is in

the range of 23.81 to 39.94 % for age groups 18.0-19.9 yr

and 60.0-69.9 yr, respectively, with result variation at the

level of 32.48 %, and standard measurement error of 1.71

%. For the variable PSMM it was established that values are

in the range of 42.25 to 32.58 % for age groups 18.0-19.9 yr

and 60.0-69.9 %, respectively, with result variation at the

level of 13.36 %, and standard measurement error of only

0.82 %.

* 18-19.9 vs 20-29.9, 30-39.9, 40-49.9, 50-59.9, 60-69.9, p ≤ 0.05; £ 20-29.9 vs 30-39.9, 40-49.9, 50-59.9, 60-69.9, p ≤ 0.05;¤ 30-39.9 vs 40-49.9,

50-59.9, 60-69.9, p ≤ 0.05; ¥ 40-49.9 vs 50-59.9, 60-69.9, p ≤ 0.05; # 50-59.9 vs 60-69.9, p ≤ 0.05.

Table I. Basic descriptive results of examined variables for the function of age groups

RAKIC, S.; DOPSAJ, M.; DJORDJEVIC-NIKIC, M.; VASILJEVIC, N.; DOPSAJ, V.; MAKSIMOVIC, M.; TOMANIC, S. M. & MILJUS, D. Profile and reference values for body fat and

skeletal muscle mass percent at females, aged from 18.0 to 69.9, measured by multichannel segmental bioimpedance method: Serbian population study. Int. J. Morphol., 37(4):1286-1293, 2019.

PBF

(

)

95 % Conf. Int.

Mean ( %) SD (%) cV ( %) SEM (%) Min (%) Max (%)

Low. Upper.

All 28.51 9.26 32.48 1.71 5.82 55.75 27.54 29.48

18.0-19.9

r 23.81 6.77 28.43 2.42 9.98 52.47 22.68 24.94

20.0-29.9

r 24.77 7.40 29.87 1.26 5.82 55.28 24.16 25.38

30.0-39.9

r 28.14*

,£

9.25 32.87 1.31 7.04 55.75 27.42 28.87

40.0-49.9

r 32.42*

,£,_

8.27 25.51 1.41 11.92 55.18 31.53 33.32

50.0-59.9

r 36.33*

,£,_,¥

7.90 21.75 1.64 13.58 51.82 35.16 37.49

60.0-69.9

r 39.94*

,£,_,¥,#

7.91 19.80 2.23 19.94 55.15 38.20 41.69

PSMM

(

)

All 39.30 5.25 13.36 0.82 19.35 55.10 38.67 39.93

18.0-19.9

r 42.25 3.83 9.07 0.77 27.11 50.74 41.62 42.89

20.0-29.9

r 41.37 4.30 10.39 0.42 24.80 55.10 41.03 41.72

30.0-39.9

r 39.47*

,£

5.18 13.12 0.53 19.35 51.51 39.07 39.88

40.0-49.9

r 37.17*

,£,_

4.58 12.32 0.69 25.18 51.84 36.66 37.67

50.0-59.9

r 34.73*

,£,_,¥

4.35 12.53 0.96 23.94 47.17 34.08 35.39

60.0-69.9

r 32.58*

,£,_,¥,#

4.19 12.86 1.54 24.94 49.84 31.60 33.56

1289

ANOVA results with differences between the

examined age groups for the function of individual varia-

bles are shown in Table II.

It was established that there are statistically significant

differences between groups in relation to both examined

variables at the level of p = 0.000, where the variable PBF

carries 24.6 %, and variable PSMM carries 25.6 % of

established differences between age groups, with the power

analysis at the level of 100 %, respectively (Table II).

Results of percentile distribution of all variables for

the function of examined age groups as well as qualitative-

normative values of examined variables were presented

within Tables III and IV.

Trends of change of analysed variables for the

function of age groups are shown in Figures 1 and 2, with

defined prediction models.

Variables Percentile

PBF ( %) 2.5 5.0 10.0 25.0 50.0 75.0 90.0 95.0 97.5

All Sample 13.96 15.77 17.84 21.57 27.04 34.50 42.27 46.10 49.03

18.0-19.9 yr 13.62 14.96 16.58 19.58 23.08 26.72 31.07 35.82 45.89

20.0-29.9 yr 12.95 14.57 16.49 20.12 23.51 28.88 34.38 38.15 42.63

30.0-39.9 yr 13.74 15.06 17.81 21.34 26.56 33.89 41.46 46.15 50.34

40.0-49.9 yr 17.68 19.20 22.14 26.51 32.07 38.18 43.71 46.29 48.29

50.0-59.9 yr 22.22 23.32 26.34 30.60 36.13 42.34 47.17 49.97 50.81

60.0-69.9 yr 17.45 24.80 29.67 35.21 40.51 45.41 48.99 50.93 54.87

PSMM ( %) 2.5 5.0 10.0 25.0 50.0 75.0 90.0 95.0 97.5

All Sample 27.77 29.57 31.69 35.95 40.00 43.11 45.44 47.08 48.07

18.0-19.9 yr 30.43 35.36 37.67 40.38 42.48 44.81 46.50 47.66 48.58

20.0-29.9 yr 31.80 33.91 35.86 38.79 41.86 44.14 46.23 47.78 48.55

30.0-39.9 yr 27.39 29.83 32.24 36.08 40.27 43.27 45.17 47.30 47.96

40.0-49.9 yr 28.32 29.72 30.91 34.21 37.29 40.33 43.09 44.52 45.95

50.0-59.9 yr 26.84 27.54 28.90 31.39 34.82 37.83 39.80 41.70 43.06

60.0-69.9

r 25.07 26.99 27.36 29.64 32.43 34.79 38.07 39.59 42.71

Tests of Between-Subjects Effects

Source Type III Sum of Squares df Mean Square F Sig. Partial Eta

Observed Power

PBF 40398.958 5 8079.79 124.78 0.000 0.246 1.000

PSMM 13520.827 5 2704.17 131.51 0.000 0.256 1.000

Table IV. Qualitative-normative values of examined variables.

Table III. Results of percentile distribution of all variables for the function of examined age groups.

Table II. ANOVA results – differences between groups with regards to examined variables (PBF and PSMM).

RAKIC, S.; DOPSAJ, M.; DJORDJEVIC-NIKIC, M.; VASILJEVIC, N.; DOPSAJ, V.; MAKSIMOVIC, M.; TOMANIC, S. M. & MILJUS, D. Profile and reference values for body fat and

skeletal muscle mass percent at females, aged from 18.0 to 69.9, measured by multichannel segmental bioimpedance method: Serbian population study. Int. J. Morphol., 37(4):1286-1293, 2019.

18.0-19.9

r 20.0-29.9

r 30.0-39.9

r 40.0-49.9

r 50.0-59.9

r 60.0-69.9

PBF

(

)

Superior ≤ 10.2 ≤ 10.0 9.6 ≤ 15.8 ≤ 20.4 ≤ 24.1 ≤

Excellent 10.3-17.0 10.1-17.4 9.7-18.8 15.9-24.1 20.5-28.4 24.2-32.0

Above Av

. 17.1-20.4 17.5-21.1 18.9-23.5 24.2-28.2 28.5-32.3 32.1-35.9

Avera

e 20.5-27.2 21.2-28.5 23.6-32.7 28.3-36. 6 32.4-40.2 36.0-43.8

Under Avg. 27.3-30.5 28.6-32.2 32.8-37.3 36.7-40.6 40.3-44.2 43.9-47.8

Bad 30.6-37.3 32.3-39.6 37.4-46.6 40.70-48.9 44.3-52.1 47.9-55.6

Ver

Bad 37.4 ≥ 39.7 ≥ 46.7 ≥ 49.0 ≥ 52.2 ≥ 55.9 ≥

PSMM

(

)

erior ≥ 49.9 ≥ 49.9 49.8 ≥ 46.3 ≥ 43.4 ≥ 41.0 ≥

Excellent 49.8-46.1 49.8-45.7 49.7-44.6 46.2-41.8 43.3-39.1 40.9-36.8

Above Av

. 46.0-44.2 45.6-43.5 44.5-42.1 41.7-39.5 39.0-36.9 36.7-34.8

Avera

e 44.1-40.4 43.4-39.2 42.0-36.9 39.4-34.9 36.8-32.6 34.7-30.5

Under Av

. 40.3-38.4 39.1-37.1 36.8-34.3 34.8-32.6 32.5-30.4 30.4-28.4

Bad 38.3-34.6 37.0-32.7 34.2-29.1 32.5-28.1 30.3-26.1 28.3-24.2

Very Bad ≤ 34.5 ≤ 32.6 29.0 ≤ 28.0 ≤ 26.0 ≤ 24.1 ≤

1290

DISCUSSION

Besides basic morphologic variables, that is, variables providing

information about absolute measurements of body composition, index

(derived) variables that give data on the relative presence of a certain

element in the body have a great practical and medically diagnostic

value (De Rosa et al., 2015; Maksimovic et al., 2016). One of the most

valid index variables are partialized in relation to the extent of body

voluminosity by which body status is evaluated, along with variables

by which fat percentage and skeletal muscle percentage are defined

(PBF and PSMM, respectively) (Ling et al.; Gába & Pridalová; Bankovic

et al.).

According to data published in the most

recent researches it has been shown that, year

after year, the level of PBF value is on the rise

among all the age categories of the population

in the area of Serbia (Boricic et al., 2014). In the

period between two researches, from 2006 and

2013, a significant degree of increase of obese

population was established (from 17.3 % to 21.2

%), especially in the age category of 45-84

(Boricic et al.). According to the results of this

research it was established (Table I) that the ave-

rage PBF value is at the level of 28.51±9.26 %

of body fat, from 23.81 % for the youngest (18.0-

19.9 yr of age) to 39.94 % for the oldest sample

(60.0-69.9 yr).

With regards to age groups, a high

statistically significant difference was found

between almost everyone (Table II, ANOVA F =

124.775, p = 0.000), in a way that apart from the

two youngest ones differing from each other

(18.0-19.9 yr and 20.0-29.9 yr) all the other

groups differ among themselves crosswise (Table

I). In other words, the percentage of body fat

among respondents was not different from 18.0

all until the age of 29.9, whereas after that age,

i.e. from 30.0 yr of age onwards, it increased in

a statistically significant way, decade after decade

all up to 69.9

yr of age. Regression analysis results

have shown that the constant of body fat

percentage increase amounted to 3.417 % per life

decade, and that the defined regression model

explains 25.1 % of mutual trend variance (Fig. 1).

However, only a 1⁄4 of the examined phenomenon

was explained by the defined equation model (PBF

= 3.417 • age group + 18.943). With the remaining

3⁄4 of the sample the PBF value change occ

urs

differently from the defined trend of 4.55 %, i.e.

either at a higher or a lower level. This only points

to the complexity of the examined phenomenon,

as well as to multidimensionality of factors that

influence body status in the sense of change in

the body fat in females during their life, and

especially after 30.0 yr of life. It was previously

found that different social, life and health factors,

such as raising a family, maternity status,

hormone status, professional-work environment

and obligations, level of physical activity, diet

habits etc. significantly influence variability fac-

tor of body composition changes among women

(Thompson et al.; Menotti et al.; Gába &

Pridalová; Sarayakin et al., 2018; Kukic et al.,

2019).

Fig. 1. PBF change trend in relation to examined age groups.

Fig. 2. PSMM change trend in relation to examined age groups

RAKIC, S.; DOPSAJ, M.; DJORDJEVIC-NIKIC, M.; VASILJEVIC, N.; DOPSAJ, V.; MAKSIMOVIC, M.; TOMANIC, S. M. & MILJUS, D. Profile and reference values for body fat and

skeletal muscle mass percent at females, aged from 18.0 to 69.9, measured by multichannel segmental bioimpedance method: Serbian population study. Int. J. Morphol., 37(4):1286-1293, 2019.

1291

In a research conducted using the same measurement

method and the same instrument, on a sample of women

from Czech Republic, an average PBF value at the level of

29.1±8.9 % was measured. Range of results in relation to

age groups was from 23.5±5.9 % for the group aged 18-29

yr, 26.3±7.2 % for the group aged 30-39 yr, 29.3±7.4 % for

the group aged 40-49 yr, 34.7±7.7 % for the group aged 50-

59 yr and 36.0±6.5 % for the group aged 60-69 yr (Gába &

Pridalová). Generally speaking, even though our results are

greater on average than the Czech by about 3.0 %, it can be

claimed that the results of both studies are still very similar

when it comes to PBF values. This only serves as proof of

the external scientific validity of our results in relation to

women from the Eastern European region. The established

difference in PBF of about 3.0 % among Serbian women

can most probably be ascribed to the fact that respondents

in this study were women 3.6 cm taller (168.3 vs 164.7 cm,

difference of 2.14 %) and 2.6 kg heavier (68.1 vs 65.5 kg,

difference 3.82 %), i.e. they were 2.98 % physically larger

than the women from the Czech research.

The next two researches performed using the same

measurement methodology and the application of the same

instrument, where some respondents were from the same

European region, i.e. Hungary (Ihász et al.), and the others

from the region of Arabian Peninsula, i.e. from the UAE,

Abu Dhabi to be precise (Kukic et al., 2019), showed that

the average PBF value among Hungarian women was at the

level of 34.32 %, and among those from UAE 40.09 %. When

compared to Serbian women, respondents from Hungary had

16.9 % more body fat on average, whereas the UAE

respondents had 28.9 % more, respectively.

These differences, i.e. the greater amount of body fat

in the sample of

women from Hungary, are a probably

consequence of numerous factors, with different diet habits

being one of the most probable. Namely, according to the data

from a recently published epidemiological study (Grasgruber

et al., 2016), it was found that differences in diet significantly

influence prevalence, and also cause the rise in incidence of

non-infectious diseases in the context of citizens from different

European countries. It is stressed in the results that a more

significant connection among women than among men was

established with regards to total fat and animal protein intake

and other indicators of fat and protein intake, where it was

found that the level of total fat consumption among Hungarian

omen amounts to over 130 g/day, while it is at the level of

118 and 110 g/day among women from Czech Republic and

Serbia, respectively (Grasgruber et al.). When it comes to

the UAE women, aside from those already mentioned,

differences can also be ascribed to ethnicity in the sense of

social and cultural heritage, as well as to geographical and

climate environment (Kukic et al.).

In relation to results of skeletal muscle percentage in

the body (Table I, PSMM) it was established that the avera-

ge value is at the level of 39.30±5.25 %, and that it is within

range of 42.25 % for the youngest sample (18.0-19.9 yr of

age) to 32.58 % for the oldest sample (60.0-69.9 yr). In the

research conducted using the same measurement method and

instrument, on the sample of Hungarian women (Ihász et

al.) and UAE women (Kukic et al., 2019) an average PSMM

val

ue at the level of 35.79 % was measured, i.e. 32.73 %,

which is an 8.93 %, i.e. 20.06 % smaller percentage of skeletal

muscles in the body when compared to the results of this study,

which proves the validity of the variable in relation to

international researches of the skeletal muscle amount status

among women of different nationality and race.

A high statistically significant difference was found

between almost everyone (Table II, ANOVA F = 131.506, p =

0.000), and apart from the two youngest groups differing from

each other (18.0-19.9 and 20.0-29.9) all the other older age

groups differ crosswise (Table I). As in the case of PBF,

percentage of muscle presence in the body was similar with

respondents who are 18.0 all up to 29.9 yr of age, whereas it

decreased in a statistically significant way

after that age, i.e.

after 30.0 yr of life, decade after decade, all until 69.9 yr of life.

Regression analysis results showed that the constant

of decrease in percentage of skeletal muscle in the body

amounted to -2.016 % per life decade, and also that 23.8 %

of mutual variance trend was explained by the defined

regression model (Fig. 2). As in the case of PBF, only about

1⁄4 of the examined phenomenon was explained by the

defined equation model (PSMM = -2.016 • age group +

44.985), with evaluation error of 8.08 %, while with the

remaining 3⁄4 of the sample change in the value of PSMM

occurs differently from the defined trend. As in the case of

this variable, this only points to the complexity and

multidimensionality of the examined phenomenon, in a way

that a greater number of factors influence body status in the

sense of change in the amount of skeletal muscle in the

organism among women during their life, and especially after

30.0 yr of life. Generally speaking, this variable is directly

dependent on the total body mass and the amount of SMM

(since it belongs to it) which was previously established as

gradually declining, especially after the 30

year. Previous

results have shown that body mass declines at the rate of

between 3 % and 8 % for each life decade after the year 30,

while the degree of muscle mass loss is increased to 5 and

up to 10 % or about 0.4 kg a year per every life decade after

the 50

year (Janssen et al., 2000).

When the age effect on the variable PSMM is

concerned, it was found that between the 18 and 40 year it is

not connected to the absolute muscle mass in the body,

RAKIC, S.; DOPSAJ, M.; DJORDJEVIC-NIKIC, M.; VASILJEVIC, N.; DOPSAJ, V.; MAKSIMOVIC, M.; TOMANIC, S. M. & MILJUS, D. Profile and reference values for body fat and

skeletal muscle mass percent at females, aged from 18.0 to 69.9, measured by multichannel segmental bioimpedance method: Serbian population study. Int. J. Morphol., 37(4):1286-1293, 2019.

1292

because the increase of total body mass up to the 40th year

of age occurs based on the mechanism of fat tissue increase,

regardless of sex. Only after year 50 there occurs the

beginning of absolute decrease of skeletal muscle mass, i.e.

a real decline of PSMM, as such, where the decrease in SMM

approximated 1.9 and 1.1 kg/decade in the men and women,

respectively (Janssen et al.).

Based on the results of this research it can be stated

that the average value of body fat percentage among Serbian

women is at the level of 28.51±9.26 % and also that presence

of fat tissue in the body in examined women is increased by

a trend of 3.417 % per decade. A statistically significant

increase in the percentage of body fat starts after the year

30.0, i.e. from the third decade of life. When it comes to

presence of skeletal muscles in the body, it was found that

the average value was 39.30±5.25 %, and that the presence

of skeletal muscle tissue in the body of examined women is

decreasing by a trend of -2.016 % per decade. A statistically

significant decrease in the percentage of skeletal muscles in

the body starts after the year 30.0, i.e. from the third decade

of life on. Results of this study are in agreement with the

findings of previous researches in relation to change of given

variables depending on age, while the defined standards can

for now be used from a practical aspect as well, on a national

level, and also comparatively with regards to scientific needs

of international researches.

ACKNOWLEDGEMENTS

The paper is a part of the national project III47015,

funded by the Ministry of Education, Science and

Technological Development of the Republic of Serbia -

Scientific Project 2011-2019.

RAKIC, S.; DOPSAJ, M.; DJORDJEVIC-NIKIC, M.;

VASILJEVIC, N.; DOPSAJ, V.; MAKSIMOVIC, M.;

TOMANIC, S. M. & MILJUS, D. Perfil y valores de referencia

del porcentaje de grasa corporal y masa muscular en mujeres, con

edades comprendidas entre 18,0 y 69,9 años, medido por el méto-

do de bioimpedancia segmentaria multicanal: Estudio en pobla-

ción Serbia. Int. J. Morphol., 37(4):1286-1293, 2019.

RESUMEN: El perfil y estándares para el diagnóstico del

porcentaje de grasa corporal y masa muscular fueron definidos en

una muestra de 1924 mujeres de la República de Serbia, con eda-

des comprendidas entre 18,0 y 69,9 años, donde la composición

corporal de los sujetos fue medida por bioimpedancia segmentaria

multicanal. La muestra fue dividida en seis grupos, con el propósi-

to de definir los estándares respecto a la edad. Respecto al porcen-

taje de grasa corporal los resultados han mostrado que el valor

promedio de la muestra fue de 28,51±9,26 %, y entre los rangos de

23,81 y 39,94 para los grupos de edad de 18,0-19,9 años y 60,0-

69,9 años, respectivamente. Los resultados del análisis de regre-

sión mostraron que la constante del porcentaje de grasa corporal

aumentó 3,417 % por década, y que un 25,1 % de la varianza fue

explicada por el modelo, con un error de predicción de 4,55 %.

Con respecto al porcentaje de masa muscular, los resultados han

mostrado que el valor promedio de la muestra fue de 39,30±5,25

%, y entre los rangos de 42,24 y 32,58 para los grupos de edad de

18,0-19,9 años y 60,0-69,9 años, respectivamente. Los resultados

del análisis de regresión han mostrado que la constante de masa

muscular decreció -2,016 % por década y que el modelo explicó

23,8 % de la varianza con un error de predicción de 8,08 %.

PALABRAS CLAVE: Mujeres; Perfil de composición

corporal; Bioimpedancia; Grasa corporal; Masa muscular

esquelética.

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Corresponding author:

Sladjana Rakic

Faculty of Sport and Physical Education

University of Belgrade

Blagoja Parovica 156

Belgrade

SERBIA

Email: [email protected]

Received: 09-02-2019

Accepted: 23-05-2019

RAKIC, S.; DOPSAJ, M.; DJORDJEVIC-NIKIC, M.; VASILJEVIC, N.; DOPSAJ, V.; MAKSIMOVIC, M.; TOMANIC, S. M. & MILJUS, D. Profile and reference values for body fat and

skeletal muscle mass percent at females, aged from 18.0 to 69.9, measured by multichannel segmental bioimpedance method: Serbian population study. Int. J. Morphol., 37(4):1286-1293, 2019.