Body Composition and Sarcopenia Indicator among Elderly in the

Nursing Home

Farapti Farapti

1,2

, Amelliya N. Heriyana

Purwita W. Laksmi

, Muhammad Miftahussurur

Department of Nutrition, Faculty of Public Health, Universitas Airlangga, Surabaya, Indonesia

Post Graduate Doctoral Program, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia

Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia

Keywords: Body Composition, Sarcopenia Indicator, Elderly, Nutritional Status.

Abstract: Sarcopenia is definite as the age-related loss of muscle mass and muscle function with the highest prevalence

was reported in institutionalized older adults. Body composition consisted of many compartments of muscle

mass and types of fat mass. This study aims to analyse the association between body composition (muscle

mass and fat mass) and physical performance as sarcopenia indicator among elderly in the nursing home. We

examined the skeletal muscle mass index (SMI), grip strength (GS) and walking speed (WS) as sarcopenia

indicator. For muscle mass area, we measured whole, arms, legs, and trunk skeletal. We also measured body

fat, visceral fat, and subcutaneous fat as component of fat mass. A total of 54 elderly (75.9 % was female)

participated with mean age was 71 ± 8.2 years. The prevalence rates of sarcopenia were 98% based on three

indicators of sarcopenia. Almost of muscle mass areas except trunk were associated with SMI and GS,

meanwhile all areas of subcutaneous fat were correlated with GS. Among elderly nursing home, the

prevalence of sarcopenia was high. Muscle mass area and subcutaneous fat was correlated with sarcopenia

indicators.

1 INTRODUCTION

Nowadays, the pace of population ageing around the

world is increasing dramatically. Between 2015 and

2050, the proportion of people aged 60 years will

increase from 12% to 22%. It means the number of

older will be expected to total 2 billion by 2050 and

80% of elderly will be living in low and middle

income countries (World Health Organization, 2018).

Based on the central bureau of statistics data, it is

stated that Indonesia's life expectancy rate increased

from 71.20 years in 2018 to 71.34 years in 2019 with

an average life expectancy for men is 69.44 years and

for women is 73.33 years (Central Bureau of

Statistics, 2020a, 2020b). The fruitfulness of the

government to increasing life expectancy certainly be

in line with the increase in the dependency ratio of the

productive age against the unproductive age, where

the unproductive age is assumed with elderly

(Ministry of Health, 2014). The physical and

psychological conditions of the elderly who have

setbacks will cause them to will have dependency on

productive groups (Central Bureau of Statistics,

2017). Like we know that the elderly has many health

problems such as hearing loss, cataracts, back and

neck pain, depression, and dementia (World Health

Organization, 2018). Furthermore, mostly of elderly

often suffer non-communicable disease or non-

communicable disease (Cicih, 2019).

The emergence of various diseases and other

health problems that suffered by the elderly can be

caused by aging factors and comorbidities that the

elderly had previously suffered before entering old

age (Favora-Moreira et al,. 2016; Fatmawati &

Imron, 2017). A lot of health problems that suffered

by elderly due to physiological and pathological

problems can cause a decrease of normal body

function and adversely affect to body composition,

physiological function, and other clinical impacts

(Sttraton et al., 2003; Favora-Moreira et al., 2016).

Physiological functions changes of the body due to

aging can affect to function of vital organs of the

body, such as a decrease in cardiac output in a resting

state, maximum respiratory capacity, kidney filtration

rate, and nerve conduction velocity (JafariNasabian et

al., 2017; Strait & Lakatta, 2012). Changes in body

composition in the elderly that are often encountered

are a decrease in bone mass, decrease in muscle mass

Farapti, F., Heriyana, A., Laksmi, P. and Miftahussurur, M.

Body Composition and Sarcopenia Indicator among Elderly in the Nursing Home.

DOI: 10.5220/0010757000003235

In Proceedings of the 3rd International Conference on Social Determinants of Health (ICSDH 2021), pages 18-26

ISBN: 978-989-758-542-5

and strength and an increase in body fat (Ilich et al.,

2014; Schlenker & Roth, 2013).

Body composition changes that occur in the

proportion of muscle and body fat both have

contradictory differences. Muscle mass and strength

tend to decrease with age, whereas body fat tends to

increase with age (JafariNasabian et al., 2017).

Muscle mass will decrease about 1-2% after a person

enters to 50 years and muscle strength will decrease

around 12-15% every 10 years after entering the age

of 50 years (Papa et al., 2017; Quittan, 2016). A

longitudinal study that had conducted on Caucasian

men with age 70 years-over showed that fat-free mass

decreased by 0.5-0.8% per year (Dey et al., 2009;

Kemmler et al., 2019). Similar with this, other studies

have shown that a decrease also occurs in the thigh

muscle mass of both men and women aged 70 years

(Cameron et al., 2020). Aging factors can interfere

with homeostasis in skeletal muscles with be caused

an imbalance between anabolic and catabolic

pathways in muscle protein (Cruz-Jentoft et al.,

2019). The imbalance is mediated by the presence of

pro inflammatory cytokines such as TNF-α and IL-6

which have been shown to be abundant in the skeletal

muscles of the elderly (Dhillon & Hasni, 2017). In

this case, skeletal muscles are important and very

influential in muscle strength in the elderly.

It is known that sarcopenia is associated with

decreased function and disability in the elderly which

can have an impact on decreasing quality of life

(Vitriana et al., 2016). On progress, many studies

were carried out to analyze various things related to

sarcopenia. At 2010, the Working Group on Older

People (EWGSOP) included muscle mass, gait speed

and hand grip strength as the main parameters in

diagnosing sarcopenia and then in 2018 EWGSOP

revised it to EWGSOP2 by changing the step strength

criteria as criteria for diagnosing normal sarcopenia

(Cruz-Jentoft et al., 2010, 2019). Until now,

Indonesia does not yet have a decision to diagnose

sarcopenia. However, the Asian Working Group for

Sarcopenia (AWGS) conducted a study related to the

diagnosis of sarcopenia that can be carried out for

Asian populations including Indonesia by using the

EWGSOP approcach. Nevertheless since its

inception, muscle mass is an indicator that constantly

used to diagnose sarcopenia (Cederholm et al., 2011;

Reiss et al., 2019). Eventually, based on the

EWGSOP has assigned muscle mass, gait speed, and

hand grip strength are the main indicators (Cruz-

Jentoft et al., 2019). To diagnosis, skeletal muscle

becomes the main variable in determining the muscle

mass index used in diagnosing sarcopenia (Vitriana et

al., 2016). As we know that skeletal muscles are

responsible for the movement of the body, so

automatically the skeletal muscles will play an

important role in optimizing physical performance

(Tieland et al., 2018). Another side, various studies

show that as getting older there will also be an

increase in body fat mass (Reid & Fielding, 2012).

Since body composition consisted of many

compartments of muscle mass and types of fat mass

and changes with aging have effect on poor physical

performance. Furthermore, it is known that the

highest prevalence of sarcopenia was reported in

institutionalized older adults. It is important to

analyze the association between body composition

(muscle mass and fat mass) and physical performance

as sarcopenia indicator among elderly in the nursing

home (Benzinger et al., 2020).

2 MATERIALS AND METHODS

The research was conducted in October - November

2020, located at UPTD Griya Werdha Surabaya using

a cross sectional research design. Respondents were

selected by purposive sampling from elderly residing

at Griya Wredha. Elderly who fulfill study criteria

were selected as subjects in this study. Researchers

have determined several inclusion criteria for

respondents who are allowed to participate in the

study, including elderly people aged ≥ 60 years, fully

aware, not bed rest, and able to communicate with

them. As for the exclusion criteria, including

respondents who resigned, were sick or bedrest at the

time when the data were collecting, and were not

cooperative in the study. Total samples in the study

were 54 elderly people. This study has an ethical

number: 183 / HRECC.FODM / III / 2020.

Primary and secondary data were collected.

Primary data was conducted to obtain data in the form

of anthropometry and sarcopenia indicators in the

form of skeletal muscle mass index (SMI), hand-grip

strength (HS), and walking speed (WS). Secondary

data of medical record were disease history, length of

stay in the institution, and age. The skeletal muscle

mass index (SMI) was calculated by measuring the

mass of skeletal muscles by bioelectrical impedance

analysis (BIA Karada Scan HBF375). The hand-grip

strength (HS) was measured using a handgrip

dynamometer (Camry EH 101) in kilograms.

Subjects were instructed to hold the dynamometer as

hard as they could while seated in an upright posture

with arms by their sides and elbows flexed 90

degrees. The measurement was performed twice,

each the left and right hand and the maximum value

was taken. In the measurement of walking speed,

Body Composition and Sarcopenia Indicator among Elderly in the Nursing Home

subjects are tested on a 3-meter walked, then travel

time is measured and calculated to be the speed of

walking time in meters per second (m/s).

Cut-off point value for diagnosis of sarcopenia on

three parameters, namely muscle mass index (kg/m2)

<7.0 (male) and <5.7 (female); the standard values of

handgrip strength (kg) were <26 (male) and <18

(female); walking speed (m/s) ≤0.8 (Vitriana et al.,

2016). In addition, the way to diagnose sarcopenia are

as follows: (1) Measurement of handgrip strength and

gait speed; (2) If handgrip strength and gait speed are

normal based on cut-off then the respondent don’t

have sarcopenia but if handgrip and/or gait speed are

low then the next measurement to diagnosis have to

done; (3) Measurement of muscle mass, that if the

measurement is normal then respondent don’t have

sarcopenia and vice versa. All measurement is then

carried out an approach according to the cut-off on

the AWGS (Asian Working Group for Sarcopenia)

parameter because Indonesia does not yet have the

most determined diagnosis of sarcopenia. The AWGS

determination has referred to the EWGSOP

(European Working Group on Sarcopenia in Older

People) and has been adapted to the conditions of the

Asian community. Therefore, researchers chose

AWGS in making the diagnosis of sarcopenia in this

study. This study was a cross-sectional observational

analytic study. To analyze correlation of body

composition and sarcopenia indicators in elderly all

statistical analyses were performed using IBM SPSS

Statistics 20.0 version. The distributed variables are

shown as mean ± standard deviation while the

correlation analysis using Pearson Correlation

Coefficient. As for the significance value of the

analysis results if the p-value <0.05.

3 RESULTS AND DISCUSSION

Distribution about characteristics of subject showed

in Table 1. It is known that most of the respondents

are female (75.9%) with average of age about 71 ±

8.2 years old, continuous mean of long stayed in

nursing home 21.6 ± 17.2 month.

This study shows that respondents have a mean of

body weight 51 ± 12.2 kg with a body mass index

(BMI) of 21.6 ± 4.5 kg/m

. The percentage of fat mass

and muscle mass in the elderly, respectively, has a

mean of 30.6 ± 7.25 (%) and 23.0 ± 2.8 (%), the

details are summarized in Table 2. Data that were

released states that fat in the elderly can reach 30%

while the Lean Body Mass (LBM) that consisting of

protein, water, and mineral mass is 12%, 53%, and

5%, respectively (Brown et al., 2011).

Table 1: Characteristics of subject.

Variable

Total (n) or

mean ±SD

Age (years)

Long stayed (month)

Body weight (kg)

71 ± 8.2

21.6 ± 17.2

51.1 ± 12.2

Gende

Male 13 24.1

Female 41 75.9

It is known that the elderly tends to have a higher

body fat mass when compared to their fat-free mass

including muscle mass in the elderly, it is because

when someone getting older, the fat mass tends to

increase while the muscle mass will decrease

(JafariNasabian et al., 2017; Kemmler et al., 2019). In

contrast, fat mass increases gradually around the age

of 20-25 years and peaks at around 60-70 years of age

(Cruz-Jentoft et al., 2019; JafariNasabian et al.,

2017). Muscle loss accompanied by an increase in fat

mass is common in the elderly, known as sarcopenia

obesity syndrome (JafariNasabian et al., 2017;

Kalyani et al., 2014). Physical activity, food intake,

and hormonal changes due to aging can all be

associated with changes in body composition in the

elderly (Brown et al., 2011).

In addition to changes in body composition due to

aging, other effects that can be caused by aging

include the limited physical performance of the

elderly which tends to decline so that they may have

limitations in movement (S. Kim et al., 2017;

Mikkola et al., 2020). Furthermore, various factors

that cause decreased body function in the elderly,

including physical performance are also associated

with sarcopenia (Sims et al., 2013). Sarcopenia is an

age-related change that effects to changes in body fat

and muscle. Muscle loss is even referred to as a

universal phenomenon that commonly occurs due to

increasing age even in healthy people (Amarya et al.,

2015). Association between age and aging factors,

skeletal muscles will also run into atrophy (Tieland et

al., 2018). A study conducted ina quantitative review

showed that the rate of reduction in muscle mass

during life was about 0.37% a year for women, and

0.47% a year for men (Mitchell et al., 2012). Based

on longitudinal research, it was found that the elderly

who are more than 75 years old, on average will lose

muscle mass of about 0.64-0.70% a year for women

and about 0.80-0.98% a year for men (Mitchell et al.,

2012). Skeletal muscles, also known as striated

muscles, are known to be numerous and attached to

the limbs of the body (Ministry of Health, 2017).

Table 3 describe a descriptive analysis of the

measurement results of several indicators of

ICSDH 2021 - International Conference on Social Determinants of Health

Table 2: Characteristics of body composition in elderly.

Characteristics

Total (n=54) Male (n=13) Female (n=41)

Mean ± SD Mean ± SD Mean ± SD

Body Mass Index (kg/m

)

21.6 ± 12.2 21.8 ± 3.5 21.5 ± 4.8

Body Fat (%)

30.6 ± 7.25 25.4 ± 7.1 32.2 ± 6.59

Visceral Fat (%) 6.6 ± 5.1 9.1 ± 5.3 5.8 ± 4.8

Subcutaneous Fat

Whole (%) 25.0 ± 6.8 18.3 ± 5.3 27.2 ± 6.09

Arms (%) 24.0 ± 8.7 17.6 ± 4.8 26.02 ± 8.6

Legs (%) 38.2 ± 10.8 23.1 ± 5.5 42.9 ± 7.03

Trunk (%) 31.3 ± 9.2 21.9 ± 6.8 34.3 ± 7.75

Muscle Mass

Whole (%) 23.0 ± 2.8 26.2 ± 2.8 21.9 ± 1.9

Arms (%) 18.2 ± 4.85 22.7 ± 7.4 16.7 ± 2.45

Legs (%) 28.3 ± 6.2 36.1 ± 4.9 25.8 ± 4.2

Trunk (%) 33.7 ± 7.5 37.6 ± 10.2 32.5 ± 6.05

sarcopenia which include the mean muscle mass

index (3.9 ± 1.05 kg / m2), handgrip strength (14.5 ±

5.1 kg), and gait speed (0.5 ± 0.19 m/s). Moreover,

based on gender it can be concluded that male

respondents tend to have higher mean results for each

indicator of sarcopenia when compared to female

respondents. It is in line with a study conducted by

measuring muscle mass between male and female

respondents and the results showed that male muscle

mass (31.23 ± 4.19 kg) was higher when compared to

elderly female respondents (21.01 ± 3.20 kg)

(Krzymińska-Siemaszko et al., 2014). Likewise, the

results of research conducted in Indonesia found that

the muscle mass index, physical performance and

muscle strength of men tended to be higher than that

of women (Vitriana et al., 2016). The differences that

occur can be caused by various factors such as age,

body weight, protein intake, menopause, and

hormones (Chen et al., 2016; Lowe et al., 2010;

Skrzek et al., 2012). Men will tend to have higher

muscle mass it can be caused by the hormone

testosterone which can affect muscle building (Gentil

& Bottaro, 2010).

If be observed at each characteristic indicator of

sarcopenia regardless of gender, most of the three

indicators will be categorized as low with a

percentage reached up to 90%. The low category of

respondents' muscle mass index variable reached

96.3%. It is known that the muscle mass index is

associated with height, physical activity, obesity, and

comorbidities (Bosy-Westphal & Müller, 2015;

Serra-Prat et al., 2017). A study that related with

muscle mass index states that only 39.3 ± 4.5% are

categorized as normal and the rest are known to have

moderate and low muscle mass index (Chang et al.,

2017). The indicators of hand grip strength and

walking speed, it is known that it is related to physical

performance. In line with the indicators on the muscle

mass index, indicators on physical performance also

have a very high percentage that reached up to 90%.

Several studies have stated that physical performance

will be related to the muscle mass in the thighs and in

the hand muscles which are represented by hand grip

strength (Altubasi, 2017; Kristiana et al., 2020). The

study also stated that 44.3% of respondents had

moderate physical performance (Kristiana et al.,

2020). Based on the mean value of three indicators of

sarcopenia, it can be concluded that most of the

elderly (> 90%) have values that are below the cut-off

point value for sarcopenia (Vitriana et al., 2016).

According to a systematic review and meta-analysis

study conducted to compare the prevalence of

sarcopenia in the population of community people,

hospitals, and nursing home, it was found that the

elderly who live in nursing home have the highest

prevalence of sarcopenia up to 38%, elderly people

who are hospitalized are 23%, while the elderly who

live in the community are only 10% of the total

respondents of 34.955 people (Papadopoulou et al.,

2020). Another study was stated that the prevalence

of sarcopenia in the elderly living in social

institutions reached 41% (Shen et al., 2019). This

prevalence is lower when compared to the results of

the sarcopenia study conducted by researchers, which

reached a prevalence of 98.1% of the elderly have

sarcopenia. However, in a different study conducted

in Japan, it was found that the prevalence of

sarcopenia in elderly people can reach 7.1-98.0% in

men and 19.8-88.0% in women (H. Kim et al., 2016).

Based on a comparative study that has been

Body Composition and Sarcopenia Indicator among Elderly in the Nursing Home

Table 3: Indicators of sarcopenia.

Characteristics

Total (n=54) Male (n=13) Female (n=41)

Mean ± SD Mean ± SD Mean ± SD

Skeletal Muscle Mass Index (kg/m

) 3.9 ± 1.05 5.09 ± 1.1 3.6 ± 0.7

Low (%) 96.3 92.3

97.6

Enough (%) 7.3 7.7

2.4

Handgrip Strength (kg) 14.5 ± 5.1 19.6 ± 5.5 12.98 ± 3.8

Low (%) 90.7 92.3 90.2

Enough (%) 9.3 7.7 9.8

Gait Speed (m/s) 0.5 ± 0.19 0.69 ± 0.16 0.45 ± 0.17

Low (%) 90.7 84.6 95.1

Enough (%) 9.3 15.4 4.9

Sarcopenia (person) 53 12 41

Prevalence (%) 98.1 92.3 100

conducted, it shows that the elderly who live with

the family tend to have a higher sense of

independence and are significantly different from the

elderly in the nursing home so that they tend to feel

capable of doing many activities while the elderly in

social institutions tend to feel that they are weak and

always needing other people (Putri et al., 2015).

Furthermore, the elderly often feel boredom while in

the orphanage due to the limited food choices they

can choose so that it can affect the elderly's food

intake and will significantly affect their body weight

(Crogan et al., 2013).

As we known that measurement of the indicators

of sarcopenia and the skeletal muscle of respondents

has been carried out by researchers with the

distribution results described in Table 3. Furthermore,

in Table 4. Researchers processed the data to see the

relationship between both of them, and it was found

that there was a significant relationship between

muscle mass index and the whole skeletal, skeletal

arms, and skeletal legs. In the indicator of handgrip

strength with whole skeletal, and skeletal legs, a

significant relationship was also found. The last, on

gait speed indicator with the whole skeletal, skeletal

arms, and skeletal legs are related to. From the

skeletal trunk data, it is known that there is no

relationship with the muscle mass index, hand grip,

and gait strength.

Muscle mass index calculated by involving the

proportion of total skeletal muscle in the body is

known to be associated with total skeletal muscles,

arm muscles, and leg muscles. It can be due to the

theory that most of the skeletal muscles are attached

to the bones of the limbs such as the limbs (Ministry

of Health, 2017). Skeletal muscle has the main

function to move such as in the hands, fingers, and

feet that there are many skeletal muscles in them

(Kedkar, 2016). In other studies, it was found that the

arm muscle mass index (arms SMI) was significantly

associated with the anthropometric index of muscle

mass (Shimono et al., 2020). Moreover, handgrip was

known to be positively associated with leg muscles (p

= 0.011). In line with the results of this study,

according to Fragala et al. (2016) mention that

handgrip strength is significantly related to the

strength of the leg's existence. In the variable of stride

strength with leg muscles, it is known to have a

positive relationship, which means that the lower of

gait speed, the weaker the leg muscles of the elderly.

In elderly, aging followed by the susceptibility of the

elderly to have health problems such as muscle

disorders will significantly reduce muscle strength in

the legs and ankles (World Health Organization,

2018; Zhao et al., 2018).

In addition, the researchers also included the

variables of body fat (body fat, visceral fat, and

subcutaneous fat) into the correlation analysis. From

the table above, it can be concluded that the variable

body fat which has a significant correlation with the

sarcopenia indicator tends to have a negative

relationship. This is because the main variable in

measuring sarcopenia is related to body muscles

(Cruz-Jentoft et al., 2019; Shimokata et al., 2018). In

elderly, it is known that body muscle tends to be

inversely related with body fat, meaning that the

elderly often sustain an increase in fat mass but a

decrease in muscle mass (Kemmler et al., 2019). The

condition of decreased muscle mass that followed

with increased of body fat in the elderly is known as

sarcopenic obesity (Hong & Choi, 2020). Based on a

cohort study using the National Health and Nutrition

Examination Survey (NHANES), the percentage of

obese sarcopenia in men reaches 12.6% and in

women is 33.5% and in the elderly who are over 80

years old it can increase to 27.5% in men and 48% in

women (Batsis et al., 2017).

ICSDH 2021 - International Conference on Social Determinants of Health

Table 4: Correlation between body composition with indicators of sarcopenia.

Characteristics

Indicators of Sarcopenia

(correlation, significance)

Skeletal Muscle Mass Index Handgrip Strength Gait Speed

Skeletal Muscle

Whole r=0.62 (p=0.000)* r=0.301 (p=0.027)* r=0.348 (p=0.010)*

Arms r=0.68 (p=0.000)* r=0.246 (p=0.073) r=0.336 (p=0.013)*

Legs r=0.58 (p=0.000)* r=0.342 (p=0.011)* r=0.405 (p=0.002)*

Trunk r=0.06 (p=0.668) r=0.196 (p=0.436) r=0.108 (p=0.436)

Body Fat r=-0.09 (p=0.516) r=-0.169 (p=0221) r=-0.252 (p=0.066)

Visceral Fat r=0.604 (p=0.000)* r=0.181 (p=0.191) r=0.147 (p=0.290)

Subcutaneous Fat

Whole r=-0.339 (p=0.012)* r=-0.265 (p=0,053) r=-0.308 (p=0.023)*

Arms r=-0.181 (p=0.191) r=-0.261 (p=0,056) r=-0.274 (p=0.045)*

Legs r=-0.510 (p=0.000)* r=-0.357 (p=0.008)* r=-0,395 (p=0.003)*

Trunk r=-406 (p=0.002)* r=-0.220 (p=0.109) r=-0.303 (p=0.026)*

A recent meta-analysis study showed that fat mass

can weaken the relationship of muscle mass and

function mobility in elderly adults (Schaap et al.,

2013). Furthermore, another research also states that

fat mass is known to be negatively related with

muscle performance in adults and the elderly, in this

case is using a jump strength test (Moore et al., 2020).

It can be caused by adipose tissue that can cause

muscle shortening that is not optimal and weaken the

calcium signal which can affect future muscle

formation (Rahemi et al., 2015; Tallis et al., 2018).

High of fat mass is also known to reduce the

activation of agonist muscles on the other hand, high

adipose will also increase the activity of body muscle

loss which can have an impact on reducing muscle

fiber formation (Moore et al., 2020). Adipose is also

associated with a higher infiltration of Adipose Tissue

of Skeletal Muscles (ATSM) which is associated with

decreased strength capacity and strength formation by

muscles leading to deterioration of muscle quality

(Moore et al., 2020; Tuttle et al., 2012). Even though,

there are many other factors that might affect it such

as age, weight, height, physical activity, etc.

The lack of this study is that it does not study

detailed information on the factors that cause

sarcopenia each individual. Although living in an

elderly nursing home with the same physical activity

and diet, data on physical activity and food intake per

individual may show different results. Other factors

such as stress levels, hormonal changes, other

comorbidities in the elderly may be the cause of

sarcopenia which still needs further investigation.

While the strengths of this study are to explore

sarcopenia data based on three indicators, namely

muscle mass index, hand grip strength, and walking

speed and also analyzes body composition in the form

of body fat (body fat, visceral fat, and subcutaneous

fat).

4 CONCLUSIONS

In summary, muscle mass area and subcutaneous fat

was correlated with sarcopenia indicators. The

important finding is the prevalence of sarcopenia was

high among elderly in the nursing home. Further

research is needed to investigate factors associated

with sarcopenia in the population. The most

important thing is implementing preventive strategies

and effective treatment to get better physical

performance and optimal health impact.

ACKNOWLEDGEMENTS

The authors would like to express our sincere

appreciation to the participants of this study. The

authors also wish to thank to all authors for involving

in data collection, data analysis until manuscript

preparation.

REFERENCES

Altubasi, I., 2017. Physical performance of elderly adults in

association with thigh tissue composition: a cross-

sectional study. J. Phys. Ther. Sci, 29, 2194–2198.

Amarya, S., Singh, K., & Sabharwal, M., 2015. Changes

during aging and their association with malnutrition.

Journal of Clinical Gerontology and Geriatrics, 6(3),

78–84.

Body Composition and Sarcopenia Indicator among Elderly in the Nursing Home

Batsis, J. A., Mackenzie, T. A., Emeny, R. T., Lopez-

Jimenez, F., & Bartels, S. J., 2017. Low Lean Mass

With and Without Obesity, and Mortality: Results From

the 1999-2004 National Health and Nutrition

Examination Survey. The Journals of Gerontology.

Series A, Biological Sciences and Medical Sciences,

72(10), 1445–1451.

Benzinger, P., Bauer, J. M., Schwenk, M., Grund, S., &

Goisser, S., 2020. Treatment of sarcopenia in nursing

home residents: A scoping review protocol. BMJ Open,

10(8).

Bosy-Westphal, A., & Müller, M. J., 2015. Identification of

skeletal muscle mass depletion across age and BMI

groups in health and disease--there is need for a unified

definition. International Journal of Obesity (2005),

39(3), 379–386.

Brown, J. E., Isaacs, J. S., Krinke, U. B., Lechtenberg, E.,

& Murtaugh, M. A., 2011. Nutrition Through The Life

Cycle Fourth Edition (4th ed.). Wadsworth Cengage

Learning.

Cameron, J., McPhee, J. S., Jones, D. A., & Degens, H.,

2020. Five-year longitudinal changes in thigh muscle

mass of septuagenarian men and women assessed with

DXA and MRI. Aging Clinical and Experimental

Research, 32(4), 617–624.

Cederholm, T. E., Bauer, J. M., Boirie, Y., Schneider, S.

M., Sieber, C. C., & Rolland, Y., 2011. Toward a

definition of sarcopenia. Clinics in Geriatric Medicine,

27(3), 341–353.

Central Bureau of Statistics, 2017. Profil Penduduk Lanjut

Usia Provinsi Jawa Timur 2017. Central Bureau of

Statistics of Republik Indonesia.

Central Bureau of Statistics, 2020a. Indikator Strategis-

Badan Pusat Statistik. Central Bureau of Statistics of

Republic Indonesia.

Central Bureau of Statistics, 2020b. Umur Harapan Hidup

Saat Lahir (UHH) Menurut Provinsi, 2010-2019.

Central Bureau of Statistics of Republic Indonesia.

Chang, J. S., Kim, T. H., Kim, H., Choi, E. H., Kim, N., &

Kong, I. D., 2017. Qualitative muscle mass index as a

predictor of skeletal muscle function deficit in Asian

older adults. Geriatrics & Gerontology International,

17(1), 99–107.

Chen, L.-K., Lee, W.-J., Peng, L.-N., Liu, L.-K., Arai, H.,

& Akishita, M., 2016. Recent Advances in Sarcopenia

Research in Asia: 2016 Update From the Asian

Working Group for Sarcopenia. Journal of the

American Medical Directors Association, 17(8),

767.e1-7.

Cicih, L. H. M., 2019. Info demografi. National Population

and Family Planning Agency.

Crogan, N. L., Dupler, A. E., Short, R., & Heaton, G., 2013.

Food choice can improve nursing home resident meal

service satisfaction and nutritional status. Journal of

Gerontological Nursing, 39(5), 38–45.

Cruz-Jentoft, A. J., Baeyens, J. P., Bauer, J. M., Boirie, Y.,

Cederholm, T., Landi, F., Martin, F. C., Michel, J.-P.,

Rolland, Y., Schneider, S. M., Topinková, E.,

Vandewoude, M., & Zamboni, M., 2010. Sarcopenia:

European consensus on definition and diagnosis:

Report of the European Working Group on Sarcopenia

in Older People. Age and Ageing, 39(4), 412–423.

Cruz-Jentoft, A. J., Bahat, G., Bauer, J., Boirie, Y., Bruyère,

O., Cederholm, T., Cooper, C., Landi, F., Rolland, Y.,

Sayer, A. A., Schneider, S. M., Sieber, C. C.,

Topinkova, E., Vandewoude, M., Visser, M., &

Zamboni, M., 2019. Sarcopenia: revised European

consensus on definition and diagnosis. Age and Ageing,

48(1), 16–31.

Dey, D. K., Bosaeus, I., Lissner, L., & Steen, B., 2009.

Changes in body composition and its relation to muscle

strength in 75-year-old men and women: a 5-year

prospective follow-up study of the NORA cohort in

Göteborg, Sweden. Nutrition (Burbank, Los Angeles

County, Calif.), 25(6), 613–619.

Dhillon, R. J. S., & Hasni, S., 2017. Pathogenesis and

Management of Sarcopenia. Clinics in Geriatric

Medicine, 33(1), 17–26.

Fatmawati, V dan Imron, M., 2017. Perilaku koping pada

lansia yang mengalami penurunan gerak dan fungsi.

Intuisi : Jurnal Psikologi Ilmiah, 9(1).

Favora-Moreira, NC., Krausch-Hofmann, S., Matthys, C.,

vereecken, C., et al., 2016. Risk Factors for

Malnutrition in Older Adults: A Systematic Review of

the Literature Based on Longitudinal Data. Adv. Nutr,

7(3), 507–522.

Fragala, M. S., Alley, D. E., Shardell, M. D., Harris, T. B.,

McLean, R. R., Kiel, D. P., Cawthon, P. M., Dam, T.-

T. L., Ferrucci, L., Guralnik, J. M., Kritchevsky, S. B.,

Vassileva, M. T., Gudnason, V., Eiriksdottir, G.,

Koster, A., Newman, A., Siggeirsdottir, K., Satterfield,

S., Studenski, S. A., & Kenny, A. M., 2016.

Comparison of Handgrip and Leg Extension Strength in

Predicting Slow Gait Speed in Older Adults. Journal

of the American Geriatrics Society, 64(1), 144–150.

Gentil, P., & Bottaro, M., 2010. Influence of supervision

ratio on muscle adaptations to resistance training in

nontrained subjects. Journal of Strength and

Conditioning Research, 24(3), 639–643.

Hong, S.-H., & Choi, K. M., 2020. Sarcopenic Obesity,

Insulin Resistance, and Their Implications in

Cardiovascular and Metabolic Consequences.

International Journal of Molecular Sciences, 21(2).

Ilich, J. Z., Kelly, O. J., Inglis, J. E., Panton, L. B., Duque,

G., & Ormsbee, M. J., 2014. Interrelationship among

muscle, fat, and bone: connecting the dots on cellular,

hormonal, and whole body levels. Ageing Research

Reviews, 15, 51–60.

JafariNasabian, P., Inglis, J. E., Reilly, W., Kelly, O. J., &

Ilich, J. Z., 2017. Aging human body: changes in bone,

muscle and body fat with consequent changes in

nutrient intake. The Journal of Endocrinology, 234(1),

R37–R51.

Kalyani, R. R., Corriere, M., & Ferrucci, L., 2014. Age-

related and disease-related muscle loss: the effect of

diabetes, obesity, and other diseases. The Lancet.

Diabetes & Endocrinology, 2(10), 819–829.

Kedkar, C. dan K. G., 2016. Skeletal Muscle. The

Encyclopedia of Food and Health, 4, 795–801.

ICSDH 2021 - International Conference on Social Determinants of Health

Kemmler, W., von Stengel, S., & Schoene, D., 2019.

Longitudinal Changes in Muscle Mass and Function in

Older Men at Increased Risk for Sarcopenia - The

FrOST-Study. The Journal of Frailty & Aging, 8(2),

57–61.

Kim, H., Hirano, H., Edahiro, A., Ohara, Y., Watanabe, Y.,

Kojima, N., Kim, M., Hosoi, E., Yoshida, Y., Yoshida,

H., & Shinkai, S., 2016. Sarcopenia: Prevalence and

associated factors based on different suggested

definitions in community-dwelling older adults.

Geriatrics & Gerontology International, 16 Suppl 1,

110–122.

Kim, S., Leng, X. I., & Kritchevsky, S. B., 2017. Body

Composition and Physical Function in Older Adults

with Various Comorbidities. Innovation in Aging, 1(1).

Kristiana, T., Widajanti, N., & Satyawati, R., 2020.

Association between Muscle Mass and Muscle Strength

with Physical Performance in Elderly in Surabaya.

Surabaya Physical Medicine and Rehabilitation

Journal, 2(1), 24.

Krzymińska-Siemaszko, R., Czepulis, N., Suwalska, A.,

Dworak, L. B., Fryzowicz, A., Madej-Dziechciarow,

B., & Wieczorowska-Tobis, K., 2014. The significance

of body mass index in calculating the cut-off points for

low muscle mass in the elderly: methodological issues.

BioMed Research International, 2014, 450396.

Lowe, D. A., Baltgalvis, K. A., & Greising, S. M., 2010.

Mechanisms behind estrogen’s beneficial effect on

muscle strength in females. Exercise and Sport

Sciences Reviews, 38(2), 61–67.

Mikkola, T. M., Kautiainen, H., von Bonsdorff, M. B.,

Salonen, M. K., Wasenius, N., Kajantie, E., & Eriksson,

J. G., 2020. Body composition and changes in health-

related quality of life in older age: a 10-year follow-up

of the Helsinki Birth Cohort Study. Quality of Life

Research : An International Journal of Quality of Life

Aspects of Treatment, Care and Rehabilitation, 29(8),

2039–2050.

Ministry of Health, 2014. Infodatin: Situasi dan Analisis

Lanjut Usia. Ministry of Health Republic Indonesia.

Ministry of Health, 2017. Histologi dan Anatomi Fisiologi

Manusia. Ministry of Health Republic Indonesia.

Mitchell, W. K., Williams, J., Atherton, P., Larvin, M.,

Lund, J., & Narici, M., 2012. Sarcopenia, dynapenia,

and the impact of advancing age on human skeletal

muscle size and strength; a quantitative review.

Frontiers in Physiology, 3, 260.

Moore, B. A., Bemben, D. A., Lein, D. H., Bemben, M. G.,

& Singh, H., 2020. Fat Mass Is Negatively Associated

with Muscle Strength and Jump Test Performance. The

Journal of Frailty & Aging, 9

(4), 214–218.

Papa, E. V, Dong, X., & Hassan, M., 2017. Skeletal Muscle

Function Deficits in the Elderly: Current Perspectives

on Resistance Training. Journal of Nature and Science,

3(1).

Papadopoulou, S. K., Tsintavis, P., Potsaki, P., &

Papandreou, D., 2020. Differences in the Prevalence of

Sarcopenia in Community-Dwelling, Nursing Home

and Hospitalized Individuals. A Systematic Review

and Meta-Analysis. The Journal of Nutrition, Health &

Aging, 24(1), 83–90.

Putri, S. T., Fitriana, L. A., & Ningrum, A., 2015. Studi

Komparatif : Kualitas Hidup Lansia Yang Tinggal

Bersama Keluarga Dan Panti. Jurnal Pendidikan

Keperawatan Indonesia, 1(1), 1.

Quittan, M., 2016. Aspects of physical medicine and

rehabilitation in the treatment of deconditioned patients

in the acute care setting: the role of skeletal muscle.

Wien Med Wochenschr, 166, 28–38.

Rahemi, H., Nigam, N., & Wakeling, J. M., 2015. The

effect of intramuscular fat on skeletal muscle

mechanics: implications for the elderly and obese.

Journal of the Royal Society, Interface, 12(109),

20150365.

Reid, K. F., & Fielding, R. A., 2012. Skeletal muscle

power: a critical determinant of physical functioning in

older adults. Exercise and Sport Sciences Reviews,

40(1), 4–12.

Reiss, J., Iglseder, B., Alzner, R., Mayr-Pirker, B., Pirich,

C., Kässmann, H., Kreutzer, M., Dovjak, P., & Reiter,

R., 2019. Consequences of applying the new

EWGSOP2 guideline instead of the former EWGSOP

guideline for sarcopenia case finding in older patients.

Age and Ageing, 48(5), 719–724.

Schaap, L. A., Koster, A., & Visser, M., 2013. Adiposity,

muscle mass, and muscle strength in relation to

functional decline in older persons. Epidemiologic

Reviews, 35, 51–65.

Schlenker, E., & Roth, S. L., 2013. Williams’ Essentials of

Nutrition and Diet Therapy 10th edition. Mosby, Inc.

Serra-Prat, M., Papiol, M., Vico, J., Palomera, E.,

Bartolomé, M., & Burdoy, E., 2017. Factors Associated

with Poor Muscle Mass and Strength in A Community-

Dwelling Elderly Population: A Cross-Sectional Study.

Journal of Gerontology & Geriatric Research, 06(02).

Shen, Y., Chen, J., Chen, X., Hou, L., Lin, X., & Yang, M.,

2019. Prevalence and Associated Factors of Sarcopenia

in Nursing Home Residents: A Systematic Review and

Meta-analysis. Journal of the American Medical

Directors Association, 20(1), 5–13.

Shimokata, H., Shimada, H., Satake, S., Endo, N.,

Shibasaki, K., Ogawa, S., & Arai, H., 2018. Chapter 2

Epidemiology of sarcopenia. Geriatrics & Gerontology

International, 18 Suppl 1, 13–22.

Shimono, Y., Enomoto, H., Kishino, K., Moriwaki, E.-I.,

Nishikawa, H., Nishimura, T., Iwata, Y., Iijima, H., &

Nishiguchi, S., 2020. Arm Skeletal Muscle Mass Is

Associated With the Prognosis of Patients With

Cirrhosis. In Vivo (Athens, Greece), 34(3), 1165–1171.

Sims, S. T., Kubo, J., Desai, M., Bea, J., Beasley, J. M.,

Manson, J. E., Allison, M., Seguin, R. A., Chen, Z.,

Michael, Y. L., Sullivan, S. D., Beresford, S., &

Stefanick, M. L., 2013. Changes in physical activity and

body composition in postmenopausal women over time.

Medicine and Science in Sports and Exercise, 45(8),

1486–1492.

Skrzek, A., Ignasiak, Z., Kozieł, S., Sławińska, T., &

Rożek, K., 2012. Differences in muscle strength depend

Body Composition and Sarcopenia Indicator among Elderly in the Nursing Home

on age, gender and muscle functions. Isokinetics and

Exercise Science, 20, 229–235.

Strait, J. B., & Lakatta, E. G., 2012. Aging-associated

cardiovascular changes and their relationship to heart

failure. Heart Failure Clinics, 8(1), 143–164.

Sttraton, R. J., Green, C. J., & Elia, M., 2003. Disease-

Related Malnutrition: An EvidenceBased Approach to

Treatment. CABI Pub.

Tallis, J., James, R. S., & Seebacher, F., 2018. The effects

of obesity on skeletal muscle contractile function. The

Journal of Experimental Biology, 221(Pt 13).

Tieland, M., Trouwborst, I., & Clark, B. C., 2018. Skeletal

muscle performance and ageing. Journal of Cachexia,

Sarcopenia and Muscle, 9(1), 3–19.

Tuttle, L. J., Sinacore, D. R., & Mueller, M. J., 2012.

Intermuscular adipose tissue is muscle specific and

associated with poor functional performance. Journal

of Aging Research, 2012, 172957.

Vitriana, V., Defi, I. R., Irawan, G. N., & Setiabudiawan,

B., 2016. Prevalensi Sarkopenia pada Lansia di

Komunitas (Community Dwelling) berdasarkan Dua

Nilai Cut-off Parameter Diagnosis. Majalah

Kedokteran Bandung, 48(3), 164–170.

World Health Organization, 2018. Ageing and health.

https://www.who.int/news-room/fact-

sheets/detail/ageing-and-health

Zhao, X., Tsujimoto, T., Kim, B., Katayama, Y., & Tanaka,

K., 2018. Association of Foot Structure with the

Strength of Muscles that Move the Ankle and Physical

Performance. The Journal of Foot and Ankle Surgery :

Official Publication of the American College of Foot

and Ankle Surgeons, 57(6), 1143–1147.

ICSDH 2021 - International Conference on Social Determinants of Health