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Abstract

BACKGROUND:

Life expectancy among older adults has dramatically increased and they are one of the fastest growing populations worldwide. Maintaining quality of life and the ability to live independently are often of greater importance than overall life expectancy.

OBJECTIVE:

To present reference values for tests of muscle function, and to study the relationship to a commonly used tool of generic health related quality of life (HRQL) in older Swedish adults.

METHODS:

The study consisted of 192 individuals (105 women) aged between 65 and 80. The tests included hand grip and isometric knee extension strength measurements, the standing heel rise test and a 30 m walking test. Health-related quality of life (HRQOL) was evaluated using the SF-36.

RESULTS:

Reference values for the measured parameters are presented. There were high correlations ( $n=$ 192) between handgrip and leg extension strength ( $r=$ 0.72–0.75; $p<$ 0.01). The walking test’s self-selected speed demonstrated the strongest correlation with the physical component summary of the SF-36 ( $r=$ 0.57; $p<$ 0.01) and with maximal speed, moderate correlations were demonstrated with muscle strength ( $r=$ 0.43–0.56; $p<$ 0.01) and the heel rise test ( $r=$ 0.45; $p<$ 0.01).

CONCLUSIONS:

This study presents reference values for simple tests of muscle function which are relatively easy to perform, used in a Swedish clinical setting performing screening for older adults.

Keywords

Aging hand grip strength muscle strength SF-36

1. Introduction

In the past century life expectancy has dramatically increased and with that, the number of adults over the age of 65. This age group is one of the fastest growing populations worldwide. In many countries, including the USA and Sweden, persons 65 years of age and older compose or are close to making up, 15% of the population.

The World Health Organization (WHO) recommends that individuals participate in at least 30 minutes of moderate intensity activity 5 days of the week. Older adults who participate in 20–30 minutes of moderate intensity exercise on most days of the week have better physical function than older persons who are inactive [1]. Physical activity is a viable strategy for increasing or maintaining the health-related quality of life (HRQOL) of older adults [2, 3, 4, 5, 6]. Furthermore there are indicators that older adults need to participate in physical activity in order to improve and/or maintain HRQOL [7].

Muscle strength is a critical component in maintaining physical function, mobility, and vitality in older age [8]. The loss of muscle mass (sarcopenia) and strength (dynapenia) with age are major contributors to decreased function in older adults [9]. Sarcopenia has also been linked to gait and balance problems, increased risk of falling and loss of functional independence [10, 11].

Changes in lower body function during the aging process are often caused by significant declines in muscle strength and power and this in turn is related to the need for support services, long term care and reduced quality of life (QOL) [10, 12, 13].

The unfortunate result of impaired functioning in older adults is loss of independence and decreased well-being. A previous study suggests that a significant proportion of disability seen in older adults is preventable [14]. Therefore, the WHO recommendations of at least 30 minutes of moderate intensity activity 5 days a week is based on good evidence.

It is our belief that simple tests of muscle function administered annually, for example in a primary care setting, could reveal functional problems in the ageing population during the earliest stages of decline and interventions could be put in place to prevent further deterioration. Such tests can theoretically not only serve as screening tools, they might also be a stimulus for the individual to start and maintain physical activity.

The purpose of this study was to present reference values for simple tests of muscle function relating to older adults in Sweden and to study their relationship with health related quality of life scores.

2. Methods

2.1 Study population

Nine hundred women and men between 65 and 80 years of age living in the Gothenburg municipality were randomly selected from the Swedish National Register and were invited by mail to take part in the study. The subjects who accepted the invitation were then contacted by a research nurse who conducted the first screening by phone. Persons with severe chronic disease or disability were excluded. A total of 192 persons fulfilled the criteria and were able to participate in the study. The Regional Ethical Review Board, Gothenburg, Sweden previously approved the procedures used in the study.

2.2 Study design

Data collection was done at the University Hospital. The subjects visited the hospital on two different occasions.

2.2.1 Body characteristics assessment

Body weight was measured in bare feet and underwear on a calibrated digital scale. Body height was taken with a measuring stick attached to the wall in bare feet. Body Mass Index (BMI) was calculated as weight (kg)/height ${}^{2}$ (m).

2.2.2 Questionnaire

Health related quality of life (HRQOL) was evaluated by a widely used generic instrument the Medical Outcomes Study 36-Item Short Form Health Survey – SF-36. This questionnaire is divided into two major domains physical and mental health, the physical component summary (PCS) and the mental component summary (MCS). The SF-36 measures eight health related concepts, four of which are under physical health with the other four under the mental health domain. The physical health summary score includes measurements from physical function (PF), role-physical (RP), bodily pain (BP), and general health (GH). The mental health summary score includes measurements from vitality (VT), social functioning (SF), role emotional (RE) and mental health (MH). The higher the SF-36 score the greater the HRQOL [15, 16, 17, 18, 19].

2.2.3 Physical function

Hand grip strength was measured with an electronic instrument using a cylindrical grip, Grippit ${}^{\@setsize{\scriptsize}{8pt}{\viipt}{\@viipt}\textregistered}$ (AB Detector, Gothenburg, Sweden). The grip device and arm support were mounted on a portable base. The subject sat in a chair without armrest as close as possible to a 90 ${}^{\circ}$ hip flexion with feet firmly planted on the floor. The elbow was at a 90 ${}^{\circ}$ angle with the hand in a neutral position. Three trials were performed on each hand always starting with the right hand. The time between each trial was approximately 30 s. The recordings were taken during a 10 s maximum voluntary contraction (MVC), giving an average value of 10 s as the MVC value used in the present study. The highest MVC value of each hand was used for analysis [20, 21, 22, 23].

Table 1
Characteristics of study subjects (mean (sd))

	Total group ( $n=$ 192)	Females ( $n=$ 85)	Males ( $n=$ 87)	$p$ (Fvs.M)
Age (years)	72.13 (4.7)	72.0 (4.7)	72.3 (4.6)	0.62
Body weight (kg)	74.6 (13.3)	68.1 (11.4)	82.4 (11.1)	$<$ 0.01
Body height (cm)	170.0 (9.8)	163.3 (0.1)	177.5 (0.7)	$<$ 0.01
BMI (kg/m ${}^{2}$ )	25.8 (3.6)	25.5 (4.1)	26.1 (2.9)	0.27

F $=$ female, M $=$ male.

Quadriceps muscle strength was measured using an apparatus Stig Starke ${}^{\@setsize{\scriptsize}{8pt}{\viipt}{\@viipt}\textregistered}$ (Steve Strong type SSA2DL, Stig Starke HB, Växjö, Sweden) comprising of a strain gauge attached to a nylon strap and an ankle cuff. The digital display showed measurement values between 0 and 999 N. The subject sat in a supine position with approximately 90–100 ${}^{\circ}$ hip flexion. Knees were approximately at a 90 ${}^{\circ}$ angle hanging perpendicular to the floor. The strap with the strain gauge ran horizontal to the floor and was attached to the seat so that adjustments could be made for people of varying heights. A small back rest supported the subject and their thighs were strapped down with a Velcro ${}^{\@setsize{\scriptsize}{8pt}{\viipt}{\@viipt}\textregistered}$ belt. The loop was attached to the subject’s ankle with the lower part of the cuff on the proximal lateral malleolus. The subjects were asked to keep their arms crossed over their chest when performing a maximal contraction of the quadriceps muscle for a 5 second duration. Three readings per side were recorded and the highest value for each leg was stored for the analysis [24, 25].

The 30 meter walking test was performed from a quiet standing with the participant behind a starting line marked with tape. Timing started once the subject initiated walking and their first foot passed the starting line and stopped once the subject’s first foot passed the line on the floor marking the 30 m distance. Subjects were told they would walk 30 m twice down a straight corridor. The first trial was conducted at the subject’s self/selected speed while in the second she/he were instructed to walk as fast as possible without running. The examiner walked beside and behind each subject without interference. No other activities or people were in the corridor when these tests were conducted. The time for each trial was recorded in seconds with a stopwatch and the walking speed was calculated in meters/second (m/s) [26, 27]. No verbal encouragement was given during any of the physical performance tests.

The standing heel-rise test was performed with the subject standing on a 10 ${}^{\circ}$ tilted wedge on one foot. Footwear was standardized. The balance was kept by touching the wall with the fingertips of both hands at shoulder level. During the performance a metronome was set at a beat corresponding to an angular velocity of approximately 60 ${}^{\circ}$ /s. After a couple of trials with the left foot to allow the subjects to familiarize themselves with the procedure, the heel-rise test always started with the right foot. The subject was instructed to lift the heel as high as possible at the preset frequency until no further heel-rises could be performed. The procedure was repeated with the left foot. One trial per foot was conducted. The correct number of heel rises performed was documented for each foot [28, 29].

3. Results

The total group consisted of 192 persons out of which 105 were women. There were significant differences between gender concerning height and weight, but not BMI. Characteristics of the subjects are shown in Table 1. Data from the performance based tests for the total group, as well as for women and men separately, are described in Table 2. Results from the two separate components of the SF-36, the physical component summary (PCS) and the mental component summary (MCS) are also shown in Table 2.

Table 2
Data showing mean and standard deviation (sd) for all measured variables for the total group ( $n=$ 192), females (F) ( $n=$ 105) and males (M) ( $n=$ 87)

	Total group	Females	Males	$P$ (Fvs.M)
Heel rise test right (n)	10 (8) ( $n=$ 176)	10 (8) ( $n=$ 95)	11 (8) ( $n=$ 81)	0.57
Heel rise test left (n)	9 (8) ( $n=$ 175)	9 (8) ( $n=$ 95)	10 (9) ( $n=$ 80)	0.58
Leg extension muscle strength, right leg (N)	338 (116) ( $n=$ 191)	277 (83) ( $n=$ 104)	412 (108) ( $n=$ 87)	$<$ 0.01
Leg extension muscle strength, left leg (N)	331 (118) ( $n=$ 190)	270 (87) ( $n=$ 103)	403 (108) ( $n=$ 87)	$<$ 0.01
Maximal hand grip strength, right hand (N)	305 (115) ( $n=$ 191)	225 (63) ( $n=$ 104)	402 (85) ( $n=$ 87)	$<$ 0.01
Maximal hand grip strength, left hand (N)	290 (112) ( $n=$ 191)	213 (63) ( $n=$ 104)	381 (87) ( $n=$ 87)	$<$ 0.01
30 m walk test, self-selected speed (m/s)	1.38 (0.21) ( $n=$ 192)	1.37 (0.23) ( $n=$ 104)	1.38 (0.19) ( $n=$ 87)	0.68
30 m walk test, max speed (m/s)	1.96 (0.36) ( $n=$ 192)	1.87 (0.32) ( $n=$ 104)	2.06 (0.39) ( $n=$ 87)	$<$ 0.01
Physical component summary, SF-36	47.1 (9.3) ( $n=$ 191)	45.6 (10.2) ( $n=$ 105)	48.9 (7.8) ( $n=$ 86)	0.011
Mental component summary, SF-36	52.9 (8.2) ( $n=$ 191)	51.9 (9.5) ( $n=$ 105)	54 (6.2) ( $n=$ 86)	0.074

The physical component summary SF-36 and the mental component summary SF-36 in relation to hand grip strength measurements and leg extension muscle strength assessments are shown in Table 3. The correlations for the physical component summary SF-36 and hand grip strength ranged between $r=$ 0.34–0.36; $p<$ 0.01 for the right and left sides respectively. The correlations for the physical component summary SF-36 and leg extension muscle strength ranged between $r=$ 0.36–0.43; $p<$ 0.01 for the right and left sides respectively. There were no significant differences between men and women concerning the physical or mental component summary of the SF-36.

Table 3

Correlations are shown between the physical component summary SF-36 (PCS) and the mental component summary SF-36 (MCS) and the tests of physical function ( $n=$ 192)

	Hand grip strength right	Leg extension muscle strength right	30 m walking test self-selected speed	30 meter walking test maximal speed
PCS SF-36	0.34 ${}^{**}$	0.36 ${}^{**}$	0.57 ${}^{**}$	0.51 ${}^{**}$
MCS SF-36	0.20 ${}^{**}$	0.24 ${}^{**}$	0.08	0.16 ${}^{*}$

${}^{*}p<$ 0.05, ${}^{**}p<$ 0.01.

Table 4

Correlations are shown for the 30 m walking test and the performance based tests for all study participants ( $n=$ 192)

	Hand grip strength right	Hand grip strength left	Leg extension muscle strength right	Leg extension muscle strength left
30 m walking test self-selected speed	0.26 ${}^{**}$	0.33 ${}^{**}$	0.32 ${}^{**}$	0.40 ${}^{**}$
30 m walking test maximal speed	0.43 ${}^{**}$	0.49 ${}^{**}$	0.49 ${}^{**}$	0.56 ${}^{**}$

${}^{**}p<$ 0.01.

Table 5

Correlations are shown for standing heel-rise test and the 30 m Walking test and the physical component summary SF-36 (PCS) and the mental component summary SF-36 (MCS) for all study participants ( $n=$ 192)

	30 m walking test self-selected speed	30 m walking test maximal speed	PCS SF-36	MCS SF-36
Heel rise test right	0.26 ${}^{**}$	0.45 ${}^{**}$	0.30 ${}^{**}$	0.05
Heel rise test left	0.31 ${}^{**}$	0.42 ${}^{**}$	0.20 ${}^{**}$	0.04

PCS physical component summary, MCS mental component summary.

There were strong correlations between handgrip strength and leg extension muscle strength ( $r=$ 0.72–0.75; $p<$ 0.01) for both the left and right sides respectively. The correlations between the 30 m walking test at different speeds and the performance based tests are shown in Table 4 as well as for the standing heel rise test (Table 5).

There were significant ( $p<$ 0.01) differences between men and women in all tests of physical function and walking speed except for the self-selected speed. The 30 m walking test self -selected speed showed the strongest correlation with the physical component summary of the SF-36 for males ( $r=$ 0.61; $p<$ 0.01) and females ( $r=$ 0.58; $p<$ 0.01). The 30 m walking test with maximal speed also showed strong correlations with the physical component summary of the SF-36 for males ( $r=$ 0.47; $p<$ 0.01) as well as for females ( $r=$ 0.54; $p<$ 0.01).

4. Discussion

In research, muscle strength and function is often studied by time consuming and complicated procedures with expensive equipment [27, 30]. In this study we have used instead simple equipment as in the 30 meter walk test where only a stopwatch is needed. Previous studies of patients with COPD have shown that the tests can also be performed in patients with advanced disease [31]. Therefore, it should also be possible to apply these performance-based tests in primary health care settings with healthy individuals and those with chronic illnesses alike.

Loss of functionality is a strong independent predictor of adverse effects in community dwelling elders which is associated with a diminished quality of life in the affected group, in this case, the older adult [32]. Loss of function can be perceived through a decline in physical activity which sequentially brings about a loss of muscle function and loss of muscle mass: sarcopenia. There was a very strong correlation between muscle strength measurements in the upper and lower parts of the body. This finding is consistent with previous studies and suggests that either upper or lower body strength test may be used as a screening tool to assess a person’s total body strength [33]. Decrease in hand grip strength may be associated with a delayed response in the central nervous system that causes a delay in firing rate, thus decreasing the maximal power exerted by the subjects as shown on the Gripit apparatus [34].

In the present study we demonstrate that these tests have construct validity. Men are stronger than women but do not necessarily choose a faster everyday walking speed. We found significantly higher values for muscle strength and maximal walking speed in men but not a faster ordinary walking speed. This is in accordance with studies by Sunnerhagen et al. [27] and Danneskiold-Samsö [30] who also found differences in a gender perspective in this age group. Based on the results from our study and those studies referenced above, we conclude that muscle strength should be analysed by gender even when it comes to an elderly population.

In order for these tests to be considered valid they must show a strong relation to functional aspects of the health related quality of life (HRQL) questionnaire SF 36. As expected the correlation between the physical performance tests and the mental components (MCS) of SF-36 were weak. Interestingly the strongest correlation to the physical items was for the measurement of vitality especially for the 30 m walk test. Thus the pattern of correlations seen speaks in favour of the construct validity of the muscle function tests. The muscle function test that repeatedly showed the best correlation between HRQL and muscle testing was the 30 m walk test. Based on this finding we suggest using a walking test if only one test is to be used in a clinical setting. Overall, walking tests have been shown to be a valuable tool for screening muscle function in older adults in [35] as well as in different cultural settings [6].

The types of physical activity older adults are involved in may influence HRQL. We speculate that if they are involved in something they enjoy they may report a higher quality of life. The high correlation between PCS SF-36 and the 30 m walking (Table 3) test may be as a result of a feeling of wellbeing. Of all the tests, the walking speed test is most familiar to the subjects when compared to the other performance based tests. Therefore, they may have performed better due to a higher level of comfort and confidence.

The current study demonstrated a strong correlation between HRQL and the 30 m walking tests, specifically at the self-selected pace. Several studies have suggested that walking speed alone is the most sensitive physical performance measure for predicting the onset of health-related events [36, 37, 38, 39]. According to Rejeski and Mihalko the effect of physical activity on HRQL is likely to be less dramatic if the older adults are functioning at or above the norm [2]. They also found that the correlations between poor execution of physical function test and HRQL could be stronger than HRQL and measures of fitness.

Studies have also shown a positive correlation between muscle strength and maximum walking speed [26, 40, 41, 42]. In a study conducted by Ostchega et. al. they were able to demonstrate that an increase in knee extensor strength was associated with significant increases in walking speed [41]. In our study there was a strong correlation between leg extension muscle strength and hand grip strength and walking speed, with the greatest correlation between leg strength and the 30 m maximal walking speed (Table 4). However, because loss of muscle strength tends to be generalized throughout the body it may be easier to measure hand/arm strength in the general population to better include those with disabilities [33].

Bohannon [42] strongly supports the idea that hand grip strength provides an important explanation for the over-all muscle strength and quality of life and can be recommended as a stand-alone measurement for identifying older adults at risk of poor health status. This is also supported in other studies [43, 44] where grip strength was used as an indicator of health related quality of life.

Hand grip strength is considered to be a reliable predictor of whole body strength in older adults, in line with the findings in the present study, However, few studies on muscle characteristics of people with different activity levels show that assessment of both upper and lower limb strength may be appropriate in persons with very high activity levels [45].

Sartor-Glittenberg et al. [46] found that fast gait speed contributed to the physical component summary (PCS) in SF-36, supporting the assessment of walking speed in community-dwelling older adults to gain insight into physical health status of the individuals. This was also confirmed in the present study as the walking test showed the highest correlation with the PCS.

Future considerations include, follow-up to confirm the predictive values of these simple tests of muscle function as indicators of future disability. Even though the literature shows that the ability to perform functional tasks could be used as indicator of HRQOL, these instruments are not often used in clinical practice because of the complexity, size and cost of equipment, therefore, future studies should take this into consideration [47]. Additional studies could also assess the benefits of interventions (strength training) on physical function tests and HRQL.

In terms of study limitations one wonders what is the significance of the participants compliance in taking part in the and thus whether the results from this study may be generalized to a larger population. Our ambition was to include persons from different areas in the city but due to limitations in the language skill, only persons versed in Swedish were eligible for testing. The study also included more women than men, a possible limitation of the study. Our results may therefore not be fully generalized to a larger population but serve as an indicator of a test battery for older adults.

5. Conclusions

This study presents reference values for simple tests of muscle function among apparently healthy elderly Swedish women and men. The tests are relatively easy to perform while indicating that walking is best correlated with the physical component summary of the SF-36 health related quality of life questionnaire.

Author contributions

CONCEPTION: Ulla Svantesson.

PERFORMANCE OF WORK: Cecilia Elam and Ulla Svantesson.

INTERPRETATION OR ANALYSIS OF DATA: Shikeira Whyte, Heather Lavender, Ulla Svantesson and Cecilia Elam.

PREPARATION OF THE MANUSCRIPT: Shikeira Whyte and Heather Lavender.

REVISION FOR IMPORTANT INTELLECTUAL CONTENT: Shikeira Whyte, Heather Lavender, Ulla Svantesson and Cecilia Elam.

SUPERVISION: Ulla Svantesson.

Ethical considerations

The Regional Ethics Review Board, Gothenburg, Sweden approved the study (Dnr: 140-07), 2007-09-11. All participants gave their informed consent according to the declaration of Helsinki before taking part in the study.

Funding

The study has been supported by grants from local R&D grants (Göteborg och Bohuslän), the Doktor Felix Neuberghs Foundation, The Swedish Research Council, the Hjalmar Svensson Foundation, the Askers Foundation and the MHIRT project (NIH nr. 9T37MD0014-09).

Footnotes

Acknowledgments

The authors would like to thank Professor Fannie Gaston-Johansson, Johns Hopkins University, Baltimore, MD, USA, head of the MHIRT project.

Conflict of interest

The authors declare no conflict of interest.

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Tests of muscle function and health related quality of life in healthy older adults in Sweden

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1. Introduction

2. Methods

2.1 Study population

2.2 Study design

2.2.1 Body characteristics assessment

2.2.2 Questionnaire

2.2.3 Physical function

Table 1 Characteristics of study subjects (mean (sd))

Table 2 Data showing mean and standard deviation (sd) for all measured variables for the total group ( n = 192), females (F) ( n = 105) and males (M) ( n = 87)

5. Conclusions

Author contributions

Ethical considerations

Funding

Footnotes

Acknowledgments

Conflict of interest

References

Table 1
Characteristics of study subjects (mean (sd))

Table 2
Data showing mean and standard deviation (sd) for all measured variables for the total group ( $n=$ 192), females (F) ( $n=$ 105) and males (M) ( $n=$ 87)