Health Over Muscle:
Exploring the
Relationship Between Sarcopenia and Quality
of Life
Author
Sebastiaan Kam (500700801) Thesis code
2018207
Practice supervisor and supervising lecturer Jantine van den Helder
Examinator Halime Ozturk
Hogeschool van Amsterdam Voeding en Diëtetiek
Health Over Muscle: Exploring the Relationship Between Sarcopenia and Quality of Life
Sebastiaan Kam
Thesis code: 2018207
Practice supervisor: Jantine van den Helder Supervising lecturer: Jantine van den Helder Examiner: Halime Ozturk
PREFACE
This thesis embodies the knowledge and insights I gained during the past four years of the bachelor study Nutrition and Dietetics at the University of Applied Sciences Amsterdam. The importance of the courses regarding research, critical arguing and multidisciplinary approaches for dieticians, is confirmed during my last semester.
Over the past semester I contributed to the VITAMIN-trial that takes place at the Amsterdam Nutritional Assessment Center. As a cooperating student I had the opportunity to gain insight in the different aspects of a randomized controlled trial. As a cooperating student during this period, I gained insight on the ins and outs of a randomized controlled trial.
Therefore, I would like to thank Jantine van den Helder, for her guidance and role as supervising and practice lecturer. Her enthusiasm about statistics and critical feedback were great motivators during the writing of this thesis. I would also like to thank the research assistant Jorinde Scholten, for extra feedback and lessons about the writing process.
The knowledge and experience I have gained during this final semester will be very useful in my future career. In my opinion, a reliable dietician works according to the latest proven insights science has to offer. Within evidence based practice, knowledge and experience in clinical research and statistics are invaluable. During my time working as a cooperating student and writing my thesis, I gained my first hands-on experience in research. The result is this thesis.
ABSTRACT
Introduction
The Dutch Central Bureau of Statistics (CBS) predicts there will be 4,6 million people aged 65 years and older living in the Netherlands in 2040. As our life expectancy rises, so do age-related health problems, chronic diseases and co-morbidities.
Age-related decline in muscle mass and strength are characteristics of sarcopenia which is strongly correlated with hospitalization, death risk and the need for long-term care. Improving physical functioning and muscle mass are proven to be effective strategies against sarcopenia and its effects on health care costs. However, regarding overall health perception, there might be more domains to focus on.
The aim of this cross-sectional quantitative study was to assess whether there is a relationship between the parameters used in diagnosing sarcopenia according to the European Working Group on Sarcopenia and health related quality of life (QoL) in Dutch community dwelling older aged adults. All baseline data from the Dutch VITAMIN-trial was used in this study.
Methods
Information regarding education, health related QoL, physical activity level, protein intake and other characteristics were obtained. Objective
measurements of handgrip strength and physical functioning as well as bodyweight and lean mass were done at the Amsterdam Nutritional Assessment Center. For statistics, multivariate regression analyses were used.
Results
This study found handgrip strength and gait speed to be significantly
correlated with self-perceived physical functioning from the RAND-36 health survey (p <.001). These findings confirm the importance of muscle strength and physical functioning on self-perceived physical functioning. Initially, gait speed and mental health were correlated but these findings did not last after correcting for confounders. However, other research found significant
relationships between sarcopenia domains regarding health related QoL that don't revolve around physical functioning.
Conclusion
The importance of physical functioning in ageing is well established. Future research should emphasize more on improving self-perceived functioning next to measuring (qualitative) values. Future interventions revolving sarcopenia could be optimized if a multidisciplinary team focuses on the overall health related patient’s needs derived from health-related QoL-survey outcomes rather than focusing merely on physical performance outcome measurements since this seems to be related to health related QoL. Key words: community dwelling, older adults, sarcopenia, handgrip strength, gait speed
INTRODUCTION
The World Health Organization states that 'for the first time in history, most people can expect to live into their 60s and beyond' (1). The amount of elderly will continue to rise in the upcoming years. The Dutch Central Bureau of Statistics (CBS) predicts there will be 4,6 million people aged 65 years and older living in the Netherlands in 2040 (2). As our life expectancy rises, so do age-related health problems, chronic diseases and co-morbidities (3).
Government spending on elderly care in the Netherlands will continue to rise (4). Longer independently living is therefore encouraged by the Dutch
government (5). This poses a challenge, since half of the Dutch population of community-dwelling older adults has at least one chronic disease (6).
Additionally, self-reliance and the ability for people to live independently are at risk, since 10 to 50 percent of Dutch older adults are becoming vulnerable as a result of losing muscle mass (7).
Age-related decline in muscle mass and strength are characteristics of the geriatric syndrome named sarcopenia (8). Low muscle mass is associated with functional impairment, disability and increased mortality (9)(10). Sarcopenia is a 'key element underlying most frailty definitions' (11)(12). Both diseases are known to seriously increase risk of falling, losing physical functioning, and to increase hospitalization. This has a strong and
consequent effect on health costs (13)(14)(15).
Diagnosing sarcopenia is done through assessing muscle mass, strength and physical performance measurements. The European Working Group on Sarcopenia in Older People (EWGSOP) has reached consensus on diagnostic criteria (16). Depending on costs, availability and ease of use, various techniques available to assess sarcopenia in both research and clinical settings. The role of a nutritionist might be crucial, since they actively combine evidence based knowledge with practice.
Interventions to slow the progression of sarcopenia focus on maintaining and increasing both muscle mass and physical functioning through exercise and diet (17)(18). The Dutch VITAMIN (VITal AMsterdam older adults IN the city) trial currently investigates 'the impact of home-based exercise training
supported by tablet computer and coaching on physical functioning and the impact of increased dietary protein intake during home-based exercise training supported by tablet computer and coaching on physical functioning in community dwelling older adults.' Next to anthropometry and physical
functioning, the VITAMIN-trial also measures cognitive functioning and QoL(19).
The World Health Organization (WHO) describes QoL as "A state of complete
physical, mental, and social well-being not merely the absence of disease"
(20). In community-dwelling elderly, several aspects that predict wellbeing are at risk of decline. Sarcopenia is strongly correlated with hospitalization, death risk and the need for long-term care (14). This contributes to declining factors measured in QoL surveys (11)(21).
Improving physical functioning and muscle mass have proven to be effective strategies against sarcopenia and its effects on health care costs.
(14)(17)(18) However, future interventions against sarcopenia might need to lay emphasis on more than just health care costs and physical functioning. Social and personal costs remain high (7)(22)(23).
Less is known about the effects of sarcopenia and the individual parameters to diagnose its effect on QoL. In example, the Hertfordshire Cohort Study discovered a strong relationship between hand grip strength and QoL after correcting for various factors (24). Social participation and autonomy seem to be QoL parameters at risk in frail and prefrail community-dwelling elderly (25). If individual parameters are proven to affect QoL, future interventions might be more successful if more domains determining QoL are improved. The aim of this study is to assess whether there is a relationship between the three parameters used in diagnosing sarcopenia (muscle mass, hand grip strength and gait speed) and self-reported QoL (RAND-36) in Dutch community dwelling elderly aged 55 years and older. Shifting focus to individual factors possibly correlated to QoL might bring health care professionals to new insights and protocols regarding treatment and prevention of multifactorial geriatric syndromes such as sarcopenia and frailty.
MATERIALS AND METHODS
Study design
The design of this study was a cross-sectional quantitative study exploring the possible relationship between parameters used to assess sarcopenia and three domains describing QoL amongst 203 community-dwelling older adults living in Amsterdam. All baseline data from the VITAMIN-trial is used in this study.
VITAMIN-trial: VITal AmsterdaM older adults IN thE city (Dutch: VITale AMsterdamse ouderen IN dE stad)
The VITAMIN-trial is a Randomized Controlled Trial investigating the effectiveness of home-based tablet computer training programs, protein intake and coaching on physical functioning in community dwelling older adults. The control group, home-based training program group supported by tablet computer and the home based training program group supported by tablet computer + dietary protein counseling group, were randomly assigned. Baseline, 6 months and 12 months follow-up measurements were scheduled and contained anthropometrics, cognitive functioning and physical
performance tests (16). Study Population
The initial study population consisted of 240 older adults, recruited through exercise groups ‘More Physical Activity for Seniors’ (Meer Bewegen voor Ouderen (MBvO) in Dutch).
Inclusion criteria
To be eligible to participate in this study, a subject must meet all of the following criteria (16):
• 55 years or older
• Willingness that general practitioner will be notified on study participation.
• Written informed consent.
• Willingness to comply with the protocol.
• Ability to comply with the protocol in the opinion of the study
physician(s) (screening especially for any condition, medication, or circumstance that might interfere with the study protocol, to ensure safety for the participants).
Exclusion criteria A potential subject who meets any of the following criteria will be excluded from participation in this study:
• Inability to understand the Dutch language.
• Current alcohol or drug abuse in the opinion of the investigator. • Cognitive impairment (MMSE <15).
Identifying sarcopenia
In line with the 2010 guidelines published by the European Working Group on Sarcopenia (EWGSOP) (16), this study used three parameters and an
algorithm to identify sarcopenia. Skeletal muscle mass index (SMI), handgrip strength (HGS) and gait speed were assessed at the baseline visit.
Outcome parameters and instruments Dual X-ray absorptiometry (DXA)
Dual X-ray absorptiometry (DXA) was used to measure skeletal muscle mass. DXA is a non-invasive, safe and quick tool to assess body composition.
During the measurement two DXA scans were performed: a whole body scan and a hip scan. Outcomes are valid tools to track changes in appendicular muscle mass in smaller groups. DXA scans are widely used in sarcopenia research (26)(27)(28). Cutoff points for skeletal muscle mass index
(SMI)(Appendicular skeletal muscle mass/height2) are <7.26 kg/m2 for men
and <5.5 kg/m2 for women (15). Handgrip strength (HGS)
In order to measure muscle strength in individuals, a widely used and
accepted measure is handgrip strength. It is a non-invasive, quick and simple screening measure to investigate muscle strength (29). At baseline, three consecutive measurements were performed using a dynamometer (Jamar). The highest score of the dominant hand reflects muscle functioning (30). Men with a handgrip strength <30 kg are at risk of sarcopenia, whereas the cutoff point for women is <20 kg (15).
Gait speed
At baseline, the gait speed was calculated through scores obtained from The Short Physical Performance Battery (SPPB) test. The SPPB contains a 4-meter walking test to assess gait speed. The SPPB is internationally
recognized as a valid tool to measure physical performance (27)(31). A gait speed <0.8m/s is the first factor used in the algorithm to diagnose or screen for sarcopenia (16).
Quality of Life (QoL)
QoL was measured using the RAND-36 health survey filled in by participants. Advantages of this survey are its ease of use, its length, and the fact that the survey is not specifically focused on any disease. It is a consistent and stable tool covering the most important predictors of wellbeing (32)(33).
Outcomes cover eight domains: physical functioning, physical roles, bodily pain, general health mental health, emotional roles, social functioning, and vitality (34). For this study, the WHO definition on QoL is used. WHO states QoL as: "A state of complete physical, mental, and social well-being not
merely the absence of disease". Therefore, in this study RAND-36 outcomes
on physical functioning, mental health and social functioning have been used to describe QoL(20)(35). The Dutch manual was used to interpret the RAND-36 scores in this study.
Average RAND-36 scores on physical functioning (66.7), social functioning (83.2) and mental health (75.9) for people aged 65-75 years were used to compare this studies results. These scores derived from the Dutch RAND-36 guide (35).
Potential Confounders
In other sarcopenia trials, several factors possibly influence outcomes on appendicular muscle mass, muscle functioning and gait speed. This study included the following potentially confounding variables into the statistical analyses:
• Gender
Gender has a possible effect on muscle mass and strength in community-dwelling individuals aged 65 years and older (36).
• Highest level of education
Self-perceived health status is generally lower in populations with lower educational levels (37). Highest level of education was assessed at baseline.
• Weight
Weight itself might mask the loss of appendicular muscle mass in (pre) sarcopenic older adults (38).
• Physical activity level
Physical activity levels (PAL) were measured through 3-day activity records over one weekend day and two weekdays. Additionally, a Physical Acitivity Monitor (PAM) is used (39). "Physical activity is an important predictor of
muscle mass in both sexes"(40). Activity records were collected at their
measurement visit.
• Habitual protein intake
Low dietary protein intake is positively correlated with low muscle mass in community-dwelling elderly (41)(42). Habitual dietary protein intake is assessed through 3-day dietary intake records over one weekend day and two weekdays prior to the visit.
Data collection
Students cooperating in the study were responsible for the collection of data. They were selected by interviews. Most data sources are paper Client Report Forms (CRFs) which students filled out into the e-CRFs of an internet-based database (De Research Manager).
All handled data entry was done through double data entry. Each pair of students independently filled in their collected data into identical databases. The practical supervisor checked for errors by analyzing both databases. This provided a higher chance on correct and consistent data. Students have been trained prior to participating in the study. Official study protocols and 'SOPs' (Standard Operating Procedures) were strictly complied.
Data validation
The practical supervisor made sure the students got regular checks on data entry. The VITAMIN team performed data checks on all the outcome values. After the dataset was subtracted from the Research Manager by the practical supervisor, the researcher performed checks on outliers and possible
incorrect data points. These were discussed with the practical supervisors. After completing, the dataset was ready for analyzing.
In this study, before statistical analyses were performed, cases with missing values were excluded from the dataset. This resulted in a remaining study population of 203 cases.
Statistical Methods SPSS
The dataset was analyzed with SPSS package version 24, available at the AUAS. The first step was a check of the outcome measurements on
normality. Second step was the regression analysis. This was done through a manual forward enter method, where confounders were added into the model if the effect on the Beta was 10% or more. A p-value less than 0,05 was the cut-off point for statistical significance.
Statistical tables were used to enhance assessable insight in the data and results, For descriptive statistics the mean, standard deviation, minimum and maximum were reported. In order to make comprehensive, visual
representations of the data and results, statistical tables were used.
Multivariable linear regression was used to assess the relationship between parameters used in defining sarcopenia and QoL scores, which are presented in tables 2, 3 and 4. The sarcopenia paramaters were used as dependent variables. The RAND-36 scores were used as independent variables. The tables consist of a crude model and a model 1, wherein possible confounders were added. These confounders were: gender, highest level of education, weight, PAL-level and habitual protein intake.
RESULTS
The study population consisted of 63 males (31%) and 140 females (69%) with an average age of 71.9 (± 6.3) years. More than half of the study population had a bachelor degree (39.9%) or higher (17.2%). The average RAND-36 score on physical functioning was 84.0 (± 17.0). The mean score on RAND-36 social functioning was 87.9 (± 17.3). The average RAND-36 score on mental health was 80.0 (± 13.8). The mean SMI was 7.4 kg per m2
(± 1.1). The average maximum HGS (dominant hand) was 31.8 kg (± 11.4) and the average fastest gait speed score was 1.3 m/s(± 0.4). The mean 3-day PAL was 1.50(± 0.2). The average amount of consumed protein per kilogram of bodyweight was 1.1 grams (± 0.3). According to the EWGSOP algorithm, one male participant met the criteria for sarcopenia.
Table 1: Baseline characteristics of the participants (N=203)
N Mean (±SD) min max
Gender Male (%) Female (%) 63 (31) 140 (69) - - - - - - Age 203 71.9 ± 6.3 55 91
Highest level of education Primary education (%) Secondary education (%) MBO (%) HBO (%) WO (%) 203 2 (1) 43 (21.2) 42 (20.7) 81 (39.9) 35 (17.2) - - - - - - - - - - - - - - - - - -
Physical functioning RAND-36 203 84.0 ± 17.0 25 100
Social functioning RAND-36 203 87.9 ± 17.3 25 100
Mental health RAND-36 203 80.0 ± 13.8 25 100
SMI (kg/m2) 203 7.4 ± 1.1 5.37 12.27
HGS maximum (kg) 203 31.8 ± 11.4 8.50 69
Gait speed (m/s) 203 1.3 ± 0.4 .53 2.80
Mean PAL (3 days) 203 1.5 ± 0.2 1.00 2.07
Protein per day (g/kg ) 203 1.1 ± 0.3 .22 2.26
Sarcopenic (%) 1 (0.5%) - - -
Notes: Mean ± standard deviation, unless otherwise noted.
SMI= Skeletal muscle mass index, MBO = middelbaar beroepsonderwijs, HBO = hoger beroepsonderwijs, WO = wetenschappelijk onderwijs, HGS= Hand grip strength, PAL= Physical activity level.
Table 2: Outcomes of SMI with RAND-36 scores B p-Value 95% CIs Physical functioning Crude analysis -.001 .854 -.010 - .008 Model 1a .003 .294 -.002 - .008 Social functioning Crude analysis .008 .085 -.001 - .017 Model 1b .004 .312 -.004 - .011 Mental health Crude analysis .010 .089 -.001 - .021 Model 1c .000 .881 -.006 - .007
Notes: aCorrected for weight, gender and mean 3-day physical activity level bCorrected for gender and mean 3-day physical activity level
cCorrected for gender, protein intake and mean 3-day physical activity level.
Table 2 shows there were no significant relationships between skeletal muscle mass index and RAND-36 outcomes considering physical and social functioning, and mental health.
Table 3: Outcomes of hand grip strength with RAND-36 scores B p-Value 95% CIs Physical functioning Crude analysis .207 <.001** .118 - .295 Model 1a .171 <.001** .108 - .235 Social functioning Crude analysis .111 .016* .021 - .201 Model 1b .039 .236 -.026 - .104 Mental health Crude analysis .147 .011* .034 - .259 Model 1c .023 .573 -.057 - .103
Notes: *Correlation is significant at the 0.05 level, ** Correlation is
significant at the 0.01 level, a Corrected for weight, gender and mean 3-day
physical activity level b Corrected for gender and mean 3-day physical activity
level c Corrected for gender, weight, highest level of education and mean
3-day physical activity level.
Table 3 shows there was a significant relationship between hand grip
strength and the RAND-36 outcome on physical functioning, after correcting for weight, gender and mean 3-day PAL-level (p<.001). Crude scores for hand grip strength with social functioning and hand grip strength with mental health showed significant relationships. These however did not remain
Table 4: Outcomes of gait speed with RAND-36 scores B p-Value 95% CIs Physical functioning Crude analysis .006 <.001** .006 - .011 Model 1a .006 <.001** .004 - .009 Social functioning Crude analysis .002 .146 -.001 - .005 Model 1b .000 .855 -.003 - .003 Mental health Crude analysis .005 .004* .002 - .009 Model 1c .003 .068 .000 - .007
Notes: *Correlation is significant at the 0.05 level, ** Correlation is significant at the 0.01 level, a Corrected for mean 3-day physical activity
level, gender and highest level of education, Corrected for highest level of education, 3-day physical activity level and gender. c Corrected for mean
3-day physical activity level, gender and highest level of education.
Table 4 shows there was a significant relationship between gait speed and the RAND-36 outcome on physical functioning, after correcting for mean 3-day PAL-level, gender and highest level of education (p<.001). Gait speed and social functioning did not show a significant relationship. Gait speed and mental health were significantly related in the crude analysis (p<.005), but after adding the confounder highest level of education to the model,
DISCUSSION
The aim of this study was to investigate the possible relationship between sarcopenia and self-reported QoL outcomes. This cross-sectional study, involving 203 community dwelling older adults aged 55 years or older, indicated that physical parameters used to assess sarcopenia are correlated with outcomes on self-perceived functional capacity in QoL questionnaires. Handgrip strength and gait speed were significantly correlated with self-perceived physical functioning from the RAND-36 health survey (p <.001). These relationships remained significant after correcting for various
confounders. These findings confirm the importance of muscle strength and physical functioning on self-perceived physical functioning. Current
interventions to prevent sarcopenia revolve around these parameters. These relationships were found in similar studies (24)(43)(44)(45) and point out that physical functioning. In contrary, this study did not find a relationship between muscle mass and health-related QoL.
With physical functioning being one of the eight domains contributing to QoL in the RAND-36 survey, it is important that this score remains high. Physical functioning also contributes to the physical role limitations and vitality, which are also important RAND-36 domains. (46)
Initially, gait speed and mental health from the RAND-36 health survey were significantly correlated (p .004). After adding 'highest level of education' as a confounder, this relationship did not last. This can be explained by the fact that level of education is related to mental health (47). Furthermore, the Longitudinal Aging Study Amsterdam, a 16-year prospective study, found gait speed to be a predictor of depression (48). This confirms that it is to be expected that the initial relationship between gait speed and mental health might be persistent in groups with lower physical functioning. A study by Garcia-Pinillos et al. establishes that gait speed is an important predictor of functional capacity (physical and mental functioning) in adults aged 65 and older.(49)Within this trial, physical functioning is relatively high. Physically fit participants are included. This explains that the relationship between gait speed and mental health did not persist.
SMI and RAND-36 outcomes showed no significant relationships. This might be explained by the fact that the population of this study was very sportive. The older adults participating in this study have been recruited through sports programs, and were generally in good health. Since only one
participant met the criteria for sarcopenia, it seems acceptable that no known effects of sarcopenia on QoL were present in this population. However, other studies with sarcopene or frail older adutls confirm that muscle mass and QoL are related (50). Espinoza et al. found an association between
sarcopenia and health-related QOL derived from the SF-36 questionnaire in both physical and mental components. (51)
Elaborating on these confirmed relationships, the various domains
determining QoL indicate that future interventions might need to shift their focus toward a multidisciplinary approach. With sarcopenia and its known physical challenges, improving an individuals overall perception on health seems equally important, rather than only aiming to improve muscle mass and physical performance.
A multidisciplinary team might benefit from working together in order to stay focused on other RAND-36 domains as well, such as pain, vitality, social functioning and role limitations (33). Future research elaborating on QoL related to sarcopenia and physical functioning is therefore advised.
Strengths of this study were the use of valid instruments. First, the Dual-X-Ray absorptiometry (DXA) was used for anthropometric measurements. The DXA scan is a convenient, reliable and non-invasive tool in assessing
appendicular lean mass. It is seen as the golden standard in sarcopenia research (52). Second, Handgrip strength was measured with the Jamar dynamometer (30), which is an internationally used tool and suggested by the European Working group on Sarcopenia (16). Third, QoL was assessed using the RAND-36 survey, which is recognized for its sensitivity and high validity. Finally, the strict logistics around data management and double data entry methods used in this study ensured the quality of the data.
Several limitations within this study were the changing groups of cooperating students. Every semester, a new group of students participated in data
collection. Although intense training and SOP's were used, there are interpersonal differences and measurement errors when instructions are interpreted differently. Besides this, the RAND-36 surveys gives an
impression of how one has been feeling over the past four weeks. This might result in the measured QoL not being the actual representative state of the participant.
CONCLUSION
This study confirms the importance of physical functioning and muscle strength on self-perceived outcomes considering physical ability in health related QoL surveys. With the current focus on muscle strength, muscle mass, physical performance and stability in sarcopenia interventions, health care professionals are headed in the right direction. However, there seems to be more to it than physical functioning. Further research is required to
confirm the relationship between sarcopenia and overall perceived health in a broader population. More domains regarding health related QoL should
therefore be taken into account.
Although various factors within ageing and its challenges are similar, and revolve around muscle mass and physical functioning, there might be too little focus on the other domains determining QoL. With a possible stronger relationship than this study reflects, other domains determining QoL in (pre)-frail and sarcopenic elderly should not be neglected. Eventually, "A state of
complete physical, mental, and social well-being not merely the absence of disease" (20) is what should be strived for.
Future interventions revolving sarcopenia could be optimized if a
multidisciplinary team focuses on the overall health related patient’s needs, rather than focusing merely on physical performance outcome
measurements. This requires cooperation from different professions like general practitioners, psychologists, personal trainers, dieticians, social workers and researchers. Working with older adults, a dietician could play a crucial role. For example, a dietician can collaborate with a physician in recommending individualized dietary advice in line with a personal exercise program provided by the physician. The dietician could also carry out active monitoring of other domains regarding QoL as a part of their intake routine. If a dietician notices a trend towards social and/or mental issues, the general practitioner can be advised to act accordingly. A first step could be including a health-related QoL survey to the intake.
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