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Sarcopenia, Sarcopenic Obesity and Insulin Resistance

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Muscle Mass Changes with Aging. Peak muscle mass occurs between the ages of 20 and 30 years, and naturally declines as one ages. Declining function parallels the concept of sarcopenia. Sarcopenia comes from the Greek word, “Sarcos” meaning flesh, and ‘penia’ meaning lack of. This age-related decline in lean body mass can affect ambulation, mobility, and functional independence (Morley et al. 2001). An analogy often used is the age-related decline in bone mass, where, once it reaches a critical level, one’s risk of fracture is increased. Sarcopenia can be conceptualized on the spectrum of frailty and disability and has been shown to be increasingly prevalent with age. More recently, the concept of declining strength has been incorporated into the definition, although, a widely accepted definition of sarcopenia has yet to be established (Cruz-Jentoft et al. 2010)). Sarcopenia indeed can be considered a geriatric syndrome. These are common, complex and costly entities of impaired health in elderly individuals which involve multiple systems, have a myriad of interactions, and have varied phenotypes. Falls, urinary incontinence and delirium are but some examples of such. Sarcopenia has also been associated with malnutrition and diminished physical function, both of which are associated with geriatric functional decline and mortality. The loss of muscle mass during the aging process is important clinically as it reduces strength and exercise capacity, both which are needed to perform one’s activity of daily living. It is hypothesized that subjects reach a given threshold at which impairment in function occurs. Absolute loss of muscle mass leads to reduced muscle function and hence physical performance measures are increasingly being used in the definition and identification of sarcopenia. There are a number of definitions outlined in the literature making standardization, particularly in clinical practice, rather difficult (Baumgartner et al. 1998; Bouchard, Dionne, and Brochu 2009; Davison et al. 2002; Zoico et al. 2004) . Prevalence rates can vary dramatically and is the subject of current investigation. This syndrome has a number of risk factors, a number that are
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Sarcopenia, Sarcopenic Obesity and
Insulin Resistance
John A. Batsis1 and Silvio Buscemi2
1Dartmouth Medical School, Dartmouth-Hitchcock Medical Center
2University of Palermo, Departmentof Internal Medicine,
Cardiovascular and Kidney Diseases
1United States
2Italy
1. Introduction
The number of people greater than 65 years old will increase from 35.9 million in 2003
(12.4%) to 71.5 million (20%) by the year 2030. Current estimates in the United States
demonstrate that this population is numbered at 39.6million, representing 12.6% of the
population, or one in every eight Americans. Women tend to outnumber men and their life
expectancy is undoubtedly longer. These numbers reflect predominantly the influx of baby
boomers into this age group (Spillman and Lubitz 2000).
Since the early part of 1900, the elderly age group has nearly tripled from 4.1% in 1900 to 12.9%
in 2009, and the number of individuals has increased over thirteen times (from 3.1 to 39.6
million). The ‘old old’, persons aged >80 are one of the fastest growing segments of the
population (A Profile of Older Americans 2010). In addition, life expectancy in the elderly has
been increasing in the past few decades and continues to do so (Lubitz et al. 2003). For
instance, those reaching the age of 65 years, had a mean life expectancy of 19.9 and 17.2 years,
respectively, for females and males. Framed alternatively, life expectancy at birth in 2007 was
77.9 years, approximately 30 years longer than a child born in 1900. Compounded with a
reduced death rate due to medical advances, patients are living longer than they previously
were, much of this due to improved survival from cardiovascular and cerebrovascular
diseases (Ford et al. 2007). Figure #1 demonstrates data on the aging population in the United
States, and Figure #2 demonstrates estimates from worldwide figures.
In a report published by the Organisation for Economic Co-operation and Development
(OECD) in 2007, these trends observed in the United States are paralleled elsewhere. In certain
countries, specifically Italy and Japan, one out of every five people is aged 65+ (Trends in Severe
Disability Among Elderly People: Assessing the Evidence in 12 OECD Countries and the Future
Implications 2007). As in the United States, Table #1 illustrates the proportion of people that
will be 85+, which is the fastest growing segment of the population. Understandably these are
worrisome trends as these individuals are, from a public health standpoint, the ones with the
most number of chronic conditions, disabilities and greatest long-term care needs. It is believed
that unless there are significant improvements in functional awareness and improvement, this
group poses the largest burden on existing healthcare resources.
Medical Complications of Type 2 Diabetes
234
Data obtained from the US Census Bureau from the year 2000. www.census.gov
Fig. 1. Projected Elderly Population of the United States: 2000-2050
Fig. 2. Population in OECD Countries of Elderly >65 years old. Proportion of People >65
years old in a sample of Organisation for Economic Co-operation and Development (OECD)
countries from 1960 to projects at 2050. Lafortune, G. and G. Balestat (2007), "Trends in
Severe Disability Among Elderly People: Assessing the Evidence in 12 OECD Countries and
the Future Implications", OECD Health Working Papers, No. 26,
http://dx.doi.org/10.1787/217072070078
Country 1960 1980 2000 2030 2050
Australia 0.4 0.7 1.3 3.2 5.7
Canada 0.4 0.8 1.3 2.7 5.8
France 0.7 1.1 2.1 3.8 7.6
Greece 0.4 0.9 1.3 2.9 4.9
Italy 0.5 0.8 2.1 4.7 7.9
Japan 0.2 0.5 1.8 7.4 10.2
Norway 0.7 1.1 1.9 2.6 4.5
OECD 0.4 0.7 1.4 3.0 5.2
Table 1. Proportion of Patients Aged >85 years in OECD Countries. All numbers in the table
above are percentages Lafortune, G. and G. Balestat (2007), "Trends in Severe Disability
Among Elderly People: Assessing the Evidence in 12 OECD Countries and the Future
Implications", OECD Health Working Papers, No. 26,
http://dx.doi.org/10.1787/217072070078
Sarcopenia, Sarcopenic Obesity and Insulin Resistance
235
2. Health needs as one gets older
As patients age, health needs escalate, resulting in disproportionate consumption of health
care resources (Lakdawalla, Goldman, and Shang 2005). According to a 1995 US Bureau of
Census publication, approximately 80% of >65 year olds will have a minimum of one
chronic medical illness, with many suffering multiple. A number of elderly subjects report a
type of disability, including hearing impairment, visual impairment, cognitive impairment,
self-care troubles, or needing higher level of care. A number of studies have demonstrated
the impact of aging on disability. An early study by Vita et al (Vita et al. 1998) studied 1,741
university alumni, first surveyed in 1962 (mean age 43 years) and then annually in 1986.
Cumulative disability was determined using a health-assessment questionnaire. Those with
high health risks at baseline had earlier onset of disability and had a lower follow-up
disability index. The onset of disability was postponed by more than 5 years in the low-risk
subject group than those with high risk behaviors. Predictors of subsequent disability
included smoking, body mass index and exercise patterns in midlife and late-adulthood.
These authors concluded that although disability is inevitable, the time frame was
compressed into fewer years at the end of life.
In one study the number of geriatric conditions was related to dependency in activities of
daily living (Cigolle et al. 2007). These authors used data from the Health and Retirement
study survey administered in 2000 on subjects >65 years (n=11,093) residing either in the
community or in nursing homes, and assessed the number of geriatric syndromes and
dependency of activities of daily living (ADL)s. Of those >65 years, ~49.9% had at least one
geriatric syndrome, prevalence rates that were as common as heart disease and diabetes.
After adjusting for demographic characteristics and chronic diseases, the risk ratio for
dependence on ADLs were 2.1 [95%CI: 1.9-2.4] for one geriatric condition, 3.6 [3.1-4.1] for
two conditions, and 6.6 [5.6-7.6] for greater than 3 conditions. This important study
highlights the similar prevalences of geriatric conditions to chronic diseases in elderly adults
and their strong association to disability. As the authors note, these are often overlooked in
the care of older adults. One’s reported disability increases with age. In a study by the
Administration on Aging in the United States, approximately 56% of persons >80years
reported a severe disability and 29% reported the need for some type of assistance (A Profile
of Older Americans 2010). This is of course impairs one self-reported health status and may
lead to institutionalization.
3. Muscle changes with aging – Sarcopenia
As one ages, there are changes in body composition. As patients age, there is a reduction in
lean mass and a progressive increase in fat mass. This normally occurs after the age of 20-30
years and can be extensive, involving up to 40% of a population (Baumgartner et al. 1995;
Flynn et al. 1989; Gallagher et al. 1997; Muller et al. 1996). As is demonstrated in Figure #3,
maximal fat free mass (muscle mass) is usually reached at about 20 years of age and fat mass
peaks at the ages between 60 and 70 years (Baumgartner et al. 1995; Gallagher et al. 1997).
Particularly after the age of 70 years, there is a redistribution of body fat and fat free mass,
with reductions in peripheral skeletal muscle (Beaufrere and Morio 2000), increases in
intramuscular and intrahepatic fat, both of which are associated with insulin resistance
(Cree et al. 2004).
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236
Fig. 3. Muscle Mass Changes with Aging.
Peak muscle mass occurs between the ages of 20 and 30 years, and naturally declines as one
ages.
Declining function parallels the concept of sarcopenia. Sarcopenia comes from the Greek
word, “Sarcos” meaning flesh, and ‘penia’ meaning lack of. This age-related decline in
lean body mass can affect ambulation, mobility, and functional independence (Morley et
al. 2001). An analogy often used is the age-related decline in bone mass, where, once it
reaches a critical level, one’s risk of fracture is increased. Sarcopenia can be
conceptualized on the spectrum of frailty and disability and has been shown to be
increasingly prevalent with age. More recently, the concept of declining strength has
been incorporated into the definition, although, a widely accepted definition of
sarcopenia has yet to be established (Cruz-Jentoft et al. 2010)). Sarcopenia indeed can be
considered a geriatric syndrome. These are common, complex and costly entities of
impaired health in elderly individuals which involve multiple systems, have a myriad of
interactions, and have varied phenotypes. Falls, urinary incontinence and delirium are
but some examples of such. Sarcopenia has also been associated with malnutrition and
diminished physical function, both of which are associated with geriatric functional
decline and mortality. The loss of muscle mass during the aging process is important
clinically as it reduces strength and exercise capacity, both which are needed to perform
one’s activity of daily living. It is hypothesized that subjects reach a given threshold at
which impairment in function occurs. Absolute loss of muscle mass leads to reduced
muscle function and hence physical performance measures are increasingly being used
in the definition and identification of sarcopenia. There are a number of definitions
outlined in the literature making standardization, particularly in clinical practice, rather
difficult (Baumgartner et al. 1998; Bouchard, Dionne, and Brochu 2009; Davison et al.
2002; Zoico et al. 2004) . Prevalence rates can vary dramatically and is the subject of
current investigation. This syndrome has a number of risk factors, a number that are
Sarcopenia, Sarcopenic Obesity and Insulin Resistance
237
modifiable over the course of one’s life span, but can have profound impact on one’s
overall state of health and quality of life.
The trajectory of one’s muscle loss can be altered by physical exercise and/or the
environment. Muscle mass develops up to the age of 20 and 30 years, and is relatively
maintained throughout adult life. As one ages, muscle mass decreases and one reaches a
threshold whereby low muscle mass will inevitably lead to disability and future
complications (Sayer et al. 2008).
Assessing sarcopenia has been a challenge in the research literature. There are a number
of definitions that have been proposed, yet they have been developed on different
populations and ethnicities, factors which are known to affect body composition.
Additionally, muscle quality and strength have yet to be incorporated into such
definitions. Recently, there was a European consensus on the definition and diagnosis on
Sarcopenia (Cruz-Jentoft et al. 2011). This taskforce suggested the use of both low muscle
mass and low muscle function (strength or performance) for the diagnosis of sarcopenia.
The rationale for using these criteria include that muscle mass and muscle strength are not
directly correlated to each other (Goodpaster et al. 2006; Janssen et al. 2004). DEXA
scanning is unique in that it not only allows ascertainment of muscle mass but can be used
concurrently to assess bone density as well. Bioelectrical impedance on the other hand is
inexpensive, and easily reproducible with prediction equations available to calculate
various measures of body composition (Chumlea et al. 2002) and has been considered as a
portable alternative to DEXA. Body water can affect these results, though, and elders’
changes in body composition, both in health and disease, may affect such estimates.
Unfortunately, the relative availability and cost of DEXA in particular can be prohibitively
expensive, not portable, and would be impractical to use for routine use in an office
setting (Chien, Kuo, and Wu 2010). Other measures, including grip strength, knee
strength, or gait speed have been proposed but no studies have validated such measures.
Figure #4 (Cruz-Jentoft et al. 2011) illustrates the proposed mechanisms of sarcopenia. These
vary over one’s lifespan and are impacted by each other, with interactions that are poorly
understood.
4. Aging and obesity
Along with the rise in the number of elderly patients, the number of patients diagnosed
with overweight and obesity are increasing. Obesity is defined by the World Health
Organization (WHO) as a body mass index (BMI) greater than or equal to over 30kg/m2,
calculated as the body weight in kilograms divided by the height in meters squared
(Quetelet 1871). Little attention has been given to the obese elder, largely due to a paucity
of studies including elderly (>65 years old) patients. Yet, current estimates, specifically in
the United States population, indicate that the prevalence of obesity continues to rise, and
exceeds 35% of the general population, a trend that is also observed in elderly subjects.
The prevalence of obesity has increased almost three-fold from 1960-2008, and continues
to rise at a frightening rate (Flegal et al. 2011). Latest estimates illustrate by using body
mass index as a surrogate for obesity estimates, that 33.6% of women and 37.1% of males
are classified as having obesity over the age of 60years (Flegal et al. 2010). These numbers
are remarkably higher than estimates in 1999 whereby 31.8% of males were obese, yet
prevalence estimates seem to be similar in females. However, trends demonstrate rises in
Medical Complications of Type 2 Diabetes
238
prevalence rates, in particular subjects with morbid obesity (BMI >40kg/m2). Figure #5
illustrates these trends.
Fig. 4. Mechanisms of Sarcopenia. The Sarcopenia taskforce did conclude the importance of
identifying such mechanisms to better understand the underlying pathophysiology, and to
allow the identifications of interventions these targets.
Sarcopenia, Sarcopenic Obesity and Insulin Resistance
239
Obesity is associated with an increased number of medical conditions and complications,
and is a recognized independent cardiovascular risk factor. Obesity is associated with an
increased risk of both physical and cognitive disability (Beydoun, Beydoun, and Wang 2008;
Jensen 2005). Houston et al used data from the Health, Aging and Body Composition Study
in looking the association between overweight and/or obesity in young, middle, and late
adulthood and its cumulative effect on incident mobility limitation in 2,845 community
dwelling US adults (Houston et al. 2009). The authors identified mobility limitations as
difficulty walking ¼ mile or climbing 10 steps over a 7-year of follow-up. Men and women
who were overweight or obese at all three time points had increased risk of mobility
limitations compared to normal weights (HR 1.61 [1.25-2.06], and 2.85 [2.15-3.78]. There
appeared to be a graded response (P<0.001) on risk of mobility limitations on the cumulative
effect of obesity in men and women. Earlier onset of obesity in life contributed to increased
mobility limitations of old age (Houston et al. 2009). This is also observed in Figure #6.
Fig. 5. Obesity in the United States, 1960-2008.Trends in the obesity epidemic in the United
States in both males and females over the age of 60 years. In males, the trajectory of multiple
epidemiological surveys is that of an increase. In females, there was an initial drop, but
subsequent, yet steady increase
Medical Complications of Type 2 Diabetes
240
Caption: Hazard ratios and 95% confidence intervals for incident mobility limitation among Men (A)
and women (B) by history of overweight or obesity (BMI >25kg/m2), the Health, Aging and Body
Composition Study, 7 years of followup. Models were adjusted for age, race, field center, education,
smoking status, alcohol consumption, and physical activity at study baseline. (Houston et al. 2009)
Fig. 6. Mobility Limitations and Body Size
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241
A recent study using NHANES data demonstrated a J or U-shaped association between
overweight/obesity and years of life lost, with the study authors concluding that obesity
appears to decrease life expectancy (Figure #7) (Flegal et al. 2005). In addition, recent meta-
analyses using body mass index as a surrogate for obesity have demonstrated that
regardless of age, mortality is increased in patients with a BMI <22kg/m2 and those who are
morbidly obese (BMI>35kg/m2) [Figure #8] (Whitlock et al. 2009). Continued debate in the
literature with regard to associations of mortality with BMIs between 25 and 35 continue
and will not be reviewed here. Obesity has also been demonstrated to be associated with
disability, lower quality of life, and increased resource utilization, particularly in elderly
subjects (Guralnik, Fried, and Salive 1996). Obesity is associated with nursing home
admissions and increasing one’s risk to be homebound (Jensen et al. 2006; Valiyeva et al.
2006; Zizza et al. 2002). These issues all create a worrisome public health concern in that, in
one study, 9% of all total excess healthcare costs may be attributable to overweight or
obesity (Finkelstein, Fiebelkorn, and Wang 2003).
Caption: BMI indicates body mass index, measured as weight in kilograms divided by the square of
height in meters. The reference category with relative risk 1.0 is BMI 18 to <25. Error bars indicate 95%
confidence intervals. Copryight © American medical Association, JAMA 2005;293:1861-1867, All Rights
Reserved. (Flegal et al. 2005)
Fig. 7. Relative Risks of Mortality by Body Mass Index Category by Epidemiological Survey
Data
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Fig. 8. All-cause mortality vs. Body Mass Index.
These studies demonatrate J-shaped curves in all age groups, in the range 15-50kg/m2 by
age at risks (excluding the first 5 years of followup) (Whitlock et al. 2009)
5. Sarcopenic obesity – A subset of sarcopenia and obesity
Often times, we consider sarcopenia in the context of weight loss and cachexia; but sarcopenia
can occur with obesity. The impact of obesity on sarcopenia continues to be a subject of
investigation and emerging as a public health problem. In subjects who gain weight, there is
proportionally an increase in fat mass as compared to lean mass. As described above, both
entities lead to disability and the synergistic effects lead to worsening disability. These subjects
can also be considered ‘fat frail’ who suffer from increased weakness from sarcopenia and the
requirement to carry additional weight from obesity (Launer et al. 1994).
Common inflammatory pathways have linked sarcopenia and obesity yet the interplay
between these two entities is poorly understood. One author hypothesized that both
sarcopenia and obesity are similar behaviorally and biologically (Roubenoff 2000). One of
the most trophic effects on muscle is physical activity, which normally falls as people age.
Concurrently, there is a positive energy balance and weight gain, predominantly fat in
nature. Additionally, this loss of fat-free mass (muscle) lowers the amount of tissues that can
respond to insulin targeting, thereby promoting insulin resistance, metabolic syndrome and
obesity (Reaven 1988). Muscle and fat are both metabolically active, the latter producing
TNF-a, IL-6 and adipokines all of which have a direct catabolic effect on the former, and
promote insulin resistance. Leptin and low adiponectin concentrations have been found to
Sarcopenia, Sarcopenic Obesity and Insulin Resistance
243
negatively impact muscle mass and lead to a decline in muscle quality (Hamrick et al. 2010).
On a biological level, macrophages in adipocytes or in adipose tissue, produce such
proinflammatory cytokines (Fantuzzi 2005) which can upregulate the inflammatory
response. Cesari et al. evaluated the relationship between body-composition measures and
inflammatory markers, using data from the Trial of Angiotensin Converting Enzyme
Inhibition and Novel Cardiovascular Risk Factors study (Cesari et al. 2005). These authors
demonstrated the positive association of CRP and IL-6 with BMI (p=0.03 and p<0.001) and
total fat mass (<0.001 and <0.001), and inverse association with fat-adjusted appendicular
lean mass (p<0.002 and p=0.02). Using data from the INChianti study, global and central
obesity directly affect inflammation, negatively affects muscle strength and can contribute to
the development and progression of sarcopenic obesity (Schrager et al. 2007).
This cycle continues until the development of disability and medical illnesses. Furthermore,
compounding the decline in neuronal and hormonal signals that occur with aging,
malnutrition, and loss of a-motor units and changes in gene expression, further increase the
risk of this entity in occurring (Doherty et al. 1993; Marcell 2003; Morley et al. 2001). This
pro-inflammatory state leads to a perpetuating cycle of reduced muscle strength among
obese subjects inevitably further contributing to functional decline. The aging process also
itself leads to elevated IL-6 levels, TNF-α and CRP as well. While a number of chronic
medical conditions prevalent in elders, including cancer, COPD and heart failure are
associated with elevated pro-inflammatory levels and can lead to loss of muscle mass, the
process of age-related sarcopenia is a natural phenomenon and differs from such.
Baumgartner et al. defined sarcopenic obesity as a muscle mass index less than two standard
deviations below the sex-specific reference for a young healthy population (Baumgartner
2000). Alternative definitions have been used by other authors (Bouchard, Dionne, and Brochu
2009; Davison et al. 2002; Zoico et al. 2004), yet a harmonious definition has yet to be solidified
at this time. More recently, the incorporation of muscle quality into these definitions has been
proposed (Cruz-Jentoft et al. 2010). The debate is outside the scope of this chapter.
A number of studies have outlined the differences between those with and without
sarcopenia or obesity. In one of the pivotal studies, 52 subjects matched obese elderly, non-
obese frail, and non-obese, non-frail were evaluated on objective measures of functional
status and health-related quality of life and differences in body composition (Villareal et al.
2004). They discovered that obese and non-obese frail groups had lower and similar scores
in physical function, functional status and impairments in strength and walking speed. They
concluded that physical frailty in obese elders was associated with lower fat free mass (lean
mass), poor muscle quality and worsening quality of life.
One of the more pivotal studies by Baumgartner’s group demonstrated the combined effect
of obesity and muscle mass or strength on physical functioning or disability (Baumgartner
2000). Baumgartner’s group examined the impact of sarcopenic obesity and incident
instrumental ADL disability in the New Mexico elder health survey and New Mexico aging
process study (Baumgartner et al. ). This study ascertained ADLs in patients longitudinally
and assigned points (0-2) depending on whether someone could not perform an
instrumental activities of daily living, could do it with difficulty, or could do it
independently. Their primary outcome was time to a drop in ADL, defined as a drop in 2
points. As can be seen in the Figure #9 below, only those with sarcopenic obesity had a
markedly shorter time to drop in ADLs. The other three groups were no different from each
other (sarcopenic non-obese, obese non-sarcopenic, and non-obese non-sarcopenic).
Medical Complications of Type 2 Diabetes
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SO – sarcopenic obesity; S – sarcopenia; O – obesity; NS – non-sarcopenic; NO – non-obese
Fig. 9. Incident Disabilty over Time.
The data demonstrate that subjects with Sarcopenic Obesity have worsened disability, than
subjects with sarcopenia alone, obesity alone, or neither sarcopenia nor
obesity(Baumgartner et al. 2004).
Other cross-sectional studies have demonstrated conflicting results based on NHANES III
(Davison et al. 2002) and a sample of elder females in Verona (Zoico et al. 2004). Davison’s
study looked at 1,526 females and 1,391 males who were 70 years and older. These authors
observed that women in the highest quintile for percent body fat were twice as likely to
report functional limitations than in the other comparison groups, and weaker but similar
relationships were observed in men. Low muscle mass and sarcopenia with obesity, in this
study were not associated with additional limitations. In Zoico’s cross-sectional study of 167
females, aged 67-78, those in the highest quintile of body fat demonstrated a significantly
higher prevalence of functional limitation, but 40% of sarcopenic elderly women and 50% of
elderly women with high body fat and normal muscle mass were functionally limited
(Figure #10). Functional limitation increased in those with a higher degree of sarcopenia.
They demonstrated that isometric leg strength was significantly lower in subjects with
sarcopenia and sarcopenic obesity. These two studies used the same categorization to define
these entities. It was felt that using muscle mass instead of a functional measure such as
strength as an indicator of sarcopenia may have explained the lack of results.
Fig. 10. Self-Reported Functional Limitations
Sarcopenia, Sarcopenic Obesity and Insulin Resistance
245
There were no differences between subjects in this cohort on self-reported functional
limitations with regard to body composition measures (Zoico et al. 2004).
There are other studies that have demonstrated the relationship between sarcopenic
obesity and higher degrees of functional limitations. Stenholm et al (Stenholm et al. 2008)
examined the association between different obesity indicators and walking limitations in
examining the role of C-reactive protein and handgrip strength. This cross-sectional study
of a Finnish population looked at subjects >55 years, and demonstrated that the highest
two quartiles of body fat percent and C-reactive protein and the lowest two quartiles of
handgrip strength were significantly associated with greater risk of walking limitations
after adjusting for chronic diseases and other pertinent co-variates. The prevalence of
walking limitations were higher in persons who had high fat and low handgrip (61%)
than in those with low fat and high handgrip (7%). Their results are better observed in the
figure below:
Fig. 11. Walking Limitations, C-reactive Protein and Handgrip Strength.
Age- and sex-adjusted prevalence of walking limitations according to body fat percentage
levels according to C-reactive protein (CRP) and handgrip strength. Low, medium and high
levels of body fat percentage, CRP and handgrip strength were defined by recoding
quartiles of each variable in to three categories by combining quartiles II and III. Numbers
inside the bars indicate the number of subjects in each category (Stenholm et al. 2008).
Finally, Cesari’s group (Cesari et al. 2009), using the InCHIANTI study, analyzed data from
934 participants aged 65 years and older with at least 6 years of follow-up. In unadjusted
analyzes, muscle density (HR 0.78 [0.69-0.88]), muscle area (HR 0.75 [0.66-0.86]) and fat area
(HR 0.82 [0.73-0.92) were associated with mortality. However, adjusting for confounders,
these associations were no longer significant. Walking speed was associated with mortality
risk (HR 0.73 [0.60-0.88]). The relationship with mortality, though, has been examined by
other others. Rantanen (Rantanen et al. 2000). Those who were overweight in the lowest grip
strength tertile had 1.4 times higher mortality risk compared to normal weight persons in
the highest grip strength. Muscle strength has been previously examined as a predictor of
mortality (Gale et al. 2007; Newman et al. 2006; Rantanen et al. 2003) and that of obesity has
been fully described previously.
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6. Aging, sarcopenia, insulin and insulin resistance
There are hormonal changes linking age-related decline in muscle strength and mass,
which include insulin, growth hormone, and catecholamines as a few examples. On a
cellular level, animal studies have demonstrated a relationship between obesity-related
insulin resistance and insulin receptor signaling pathway. A low grade inflammation
often is present in most obese patients which is a result of chronic activation of the innate
immune system, leading to insulin resistance, impaired fasting glucose and diabetes. The
involvement of cytokines and inflammation in obesity in relation to glucose metabolism
continues to be controversial. Both IL-6 and TNF- alter insulin sensitivity by impacting
given steps in the insulin signaling pathway. In animal models, resistin induces insulin
resistance, but whether this occurs in humans is unclear. Subjects with obesity-related
insulin resistance, type 2 diabetes and coronary heart disease have low levels of
adiponectin. This hormone is known to inhibit liver gluconeogenesis and can promote
fatty acid oxidation in skeletal muscle. These cytokines also are known to impact NF-kB
and JNK systems (Zamboni et al. 2007).
With aging, muscle can be infiltrated with fat, and this may eventually perpetuate
insulin resistance. In a large study of 2,964 elderly subjects with a mean age of 73.6 years,
despite similar amounts of subcutaneous thigh fat, intermuscular fat was higher in
subjects with type 2 diabetes and impaired glucose tolerance than in subjects with
normal glucose tolerance (p<0.001) (Goodpaster et al. 2003). As expected higher rates of
intermuscular fat and visceral abdominal fat were associated with higher fasting insulin
levels. This study concluded that elderly men and women with normal body weight may
be at risk for metabolic abnormalities, including type 2 diabetes if they possess an
inordinate amount of muscle fat or visceral abdominal fat. A smaller study by the same
group elucidated whether thigh fat was a determinant of insulin resistance. They
compared a small number of subjects and confirmed that muscle composition reflected
increased fat content was associated with insulin resistance (Goodpaster, Thaete, and
Kelley 2000).
Furthermore, insulin is well known to be an anabolic hormone which may have a
pleiotrophic effect on muscle tissue and protein metabolism. Lower protein synthesis
and higher insulin levels occur in elderly subjects compared to younger subjects after
food intake. Previous studies have shown that subjects with insulin resistance can
negatively predict muscle strength, often seen in elderly subjects with diabetes. The
correlation between insulin resistance and muscle strength is quite poor and accelerates
the loss of leg muscle strength and quality. In a pilot study examining this relationship
examined the homeostasis model assessment (HOMA-IR) in type 2 diabetes,
demonstrated that knee extension, adjusted for body weight was significantly correlated
with HOMA-IR in both sexes and that this relationship persisted as an independent
determinant in a stepwise regression model (Nomura et al. 2007). In another study, the
degree of insulin resistance was evaluated using HOMA-IR and muscle strength using
handgrip strength. BMI-adjusted handgrip strength correlated positively with physical
activity, muscle area, and muscle density (Abbatecola et al. 2005). Physical activity has a
positive effect on muscle mass and quality specifically with resistance training
(Goodpaster and Brown 2005). This latter activity is also known to improve insulin
sensitivity and glycemic control.
Sarcopenia, Sarcopenic Obesity and Insulin Resistance
247
Fig. 12. Possible Mechanisms linking Ageing, Obesity, Sarcopenia and Insulin resistance
(Zamboni et al. 2008)
7. Growth hormone and insulin-like growth factor 1
Additional contributors to sarcopenia include insulin-like growth factor-1 (IGF-1) and
growth hormone (GH), both of which decline with age. Growth hormone is associated with
low fat mass, increased lean body mass and ideal metabolic profile, while IGF-1 can increase
protein synthesis in existing muscles. One study partially described the relationship of the
hypothalamic pituitary axis in subjects with sarcopenia and sarcopenic obesity. Using
DEXA, they ascertained 45 subjects with varying degrees of adiposity and lean mass and
measured pituitary function (Waters et al. 2008). They demonstrated that appendicular
skeletal muscle mass was independently and negatively correlated with leptin in all groups,
even after adjusting for body fat, and that subjects with sarcopenic obesity had lowered and
blunted GH responses. Low levels of this anabolic hormone has been proposed to be
positively associated with low muscle strength (Ceda et al. 2005). Using data from the
Longitudinal Ageing Study Amsterdam (LASA), among subjects aged 65-88 years, serum
testosterone levels were positively associated with muscle strength and physical
performance (Schaap et al. 2005). With respect to IGF-1 levels, physiologically one would
expect that the age-associated decline in IGF-1 levels would be associated with poorer
muscle strength and mobility. Data from 617 women from Women’s Health and Aging
Study were examined and demonstrated a positive association between IGF-1 levels and
knee extensor strength (p=0.004) and walking speed (P<0.001). A decline in IGF-1 levels was
associated with difficulty self-reported mobility tasks. It is hypothesized that the aging
muscle loses the capability of secreting GH and the responsiveness to IGF-1 is also likely
attenuated. Evidence suggests that exercise can reverse the latter. These may be molecular
targets in the future to promote muscle building and prevent sarcopenia.
8. Diabetes and geriatric syndromes
Diabetes is associated with an increased incidence of many geriatric syndromes. Many
studies have demonstrated the impact of diabetes on functional impairment, including
inability to ambulate and perform instrumental ADLs (Volpato et al. 2002; Gregg et al. 2002).
Medical Complications of Type 2 Diabetes
248
Diabetes itself, on a microvascular level can lead to functional impairment, but notably,
complications of diabetes have also been implicated. Diabetes has been implicated in fall
risk (Volpato et al. 2005), fractures (Schwartz et al. 2001), urinary incontinence (Ebbesen et
al. 2007) and depression (Anderson et al. 2001).
9. Diabetes and sarcopenia
There are a number of similarities between diabetes and sarcopenia. It is known that persons
with diabetes have an accelerated aging process leading to disability and frailty. Diabetes is
known to lead to each of the components of the operationalized definition of frailty and
insulin resistance appears to be a core factor in this pathophysiology (Morley 2008). In the
Health, Aging and Body Composition study, type 2 diabetes was associated with lower
skeletal muscle strength and quality, as well as excessive skeletal muscle mass loss (Park et al.
2006; Park et al. 2009). Loss of muscle mass has also been associated with type 2 diabetes in
elderly subjects. Low grip strength as a surrogate for sarcopenia is associated with features of
metabolic syndrome as well, post-prandial glucose levels and HOMA index/ insulin-
resistance. It is believed that hyperglycemia directly impairs skeletal muscle contractility and
force (Sayer et al. 2005) ; whether this is due to excessive toxicity of sugar alcohols on muscles
remains elusive at this time. Other hypotheses include the accumulation of lipids which may
affect insulin signaling (Janssen and Ross 2005; Furler et al. 2001; Shulman 2000), impaired rate
of synthesis of muscular proteins, seen in both ageing and insulin resistance (Nair 2005;
Rasmussen et al. 2006). Diabetics are at high risk for sarcopenia as there is a 1.5-2.0 fold
increased rate of skeletal muscle mass and strength loss (Park et al. 2007). There are a number
of similarities between metabolic syndrome and insulin resistance and one study by Sayer
examined the relationship between these entities and sarcopenia (Sayer et al. 2007). Their
findings suggested that impaired grip strength was associated, not only with individual
constructs of the metabolic syndrome but also the composite definition itself. Although the
authors acknowledge that further investigation is required to understand the underlying
mechanisms, the potential for using grip strength and interventions tested thereof to improve
muscle strength, could also potentially improve insulin resistance. The following figure
(Figure #13) demonstrates some of the potentiating cellular mechanisms observed in diabetes.
There are a number of emerging studies observing the relationship between sarcopenia,
obesity, sarcopenic obesity and diabetes. The Korean Sarcopenic Obesity Study examined
the prevalence of sarcopenia in Korean subjects with and without type 2 diabetes (Kim et al.
2000). The study included 810 subjects, of which 414 had diabetes and 396 were controls,
and demonstrated that the prevalence of sarcopenia was 15.7% and 6.9% in subjects with
and without diabetes. Skeletal muscle index (muscle mass adjusted for height squared), as a
measure of sarcopenia, was significantly lower in patients with diabetes compared to
subjects without diabetes. In their multiple logistic regression model, type 2 diabetes was
independently associated with sarcopenia (OR 3.06 [1.42-6.6.62)] than subjects without
diabetes after adjusting for age, sex, BMI, smoking, alcohol consumption, physical activity,
medications, blood pressure and lipid profiles. Quite interestingly, though, the prevalence
of type 2 diabetes was highest in Mexican Americans using NHANES III data with the
lowest prevalence of obesity and sarcopenia, while Whites had the highest prevalence of
sarcopenic obesity (Castaneda and Janssen 2005). This study challenges whether there
indeed is a relationship between sarcopenia and obesity. Whether ethnicities need to be
accounted for due to differences in body composition is a matter of further investigation.
Sarcopenia, Sarcopenic Obesity and Insulin Resistance
249
, decreased, increased; KT, active human protein kinase (protein kinase-B); FOXO, forkhead protein;
MURF, muscle ring finger protein; P13K, phosphatidyl inositol-3-kinase (Morley 2008).
Fig. 13. Biochemical Changes in Muscle in Diabetes
In other population, specifically, dialysis subjects, diabetes is thought to be a risk factor for
losing lean mass (Pupim et al. 2005). Muscle mass, particularly in dialysis patients, are
known to decline continuously and hence this study suggested that controlling a risk factor
for incipient sarcopenia (diabetes), would reduce this declining process. Many of the
changes suggested, in one editorial, were due to systemic inflammatory cytokines
previously described, often which are implicated in diabetes and insulin resistance (Kaysen
2005). This was echoed in another small study looking at changes in inflammatory cytokines
implicated in losing lean mass (Pedersen et al. 2003).
Subjects with diabetes are at higher risk of developing peripheral neuropathy, which leads
to a decrease in one’s motor end plates. This entity is important in maintaining muscle
homeostasis and coordination of muscle contraction, therefore their loss can perpetuate and
accelerate age-related decline in muscle mass. Diabetics also have impaired levels of growth
hormone and pro-inflammatory cytokines. Additionally, the microvascular damage from
hypoxia not only affects nerves, renal glomeruli and optic nerves, but also can lead to
muscle hypoxia. Macrovascularly, atherosclerosis can lead to diminished peripheral blood
flow to leg muscles leading to impaired strength. Other cellular entities are implicated, as
well as other endocrine changes as illustrated in the figure below. Undoubtedly there is a
relationship between the underlying pathophysiology of sarcopenia, insulin resistance and
diabetes.
10. Conclusion
A number of studies are increasingly confirming the relationship between sarcopenia and
reduced functional activities and disability. Sarcopenia and obesity are often thought as a
preludes to frailty, known to adversely predict hospitalizations, morbidity,
institutionalization and mortality (Figure #14). Reduced physical activity and a sedentary
lifestyle are important risk factors for developing sarcopenia, which subsequently leads to
physical disability and reduced physical performance (Figure #15). More importantly, those
Medical Complications of Type 2 Diabetes
250
with elevated fat mass with sarcopenia are at even high risk. The relationship between
sarcopenia, sarcopenic obesity and insulin resistance requires further investigation. The
clinical implications are not insignificance in that globally, sedentary lifestyles are becoming
the norm and the potential implications on utilization are not significant.
Fig. 14. Possible Consequence of sarcopenic obesity in the Elderly (Zamboni et al. 2008)
Fig. 15. Body Composition Changes Leading to Sarcopenic Obesity (Jarosz and Bellar 2009)
Sarcopenia, Sarcopenic Obesity and Insulin Resistance
251
11. Abbreviations
ADL – Activities of Daily Living
BMI – body mass index
BIA – bioelectrical impedance analysis;
DEXA – Dual Energy X-Ray Absorptiometry
HOMA – homeostatic model assessment
HOMA-IR – homeostasis model of assessment – insulin resistance
OECD – Organisation of Economic Cooperation and Development
US – United States
TNF- – tumor necrosis factor α
IL-6 – interleukine 6
GH – growth hormone
NK-kB - nuclear factor-kappa B
JNK - Jun N-terminal kinases
IGF-1 - insuline-like growth factor 1
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... 4 Furthermore, it may be underdiagnosed and have multiple causes 5 6 and is also associated with insulin resistance and low-grade inflammation. 7 Exercise, diet and nutritional interventions seem to have a preventive effect on the strengths and limitations of this study ► The study is designed as a randomised controlled trial, and the intervention is placebo controlled and double blinded. ► A strength of this study is the comprehensive data collection, with physical and anthropometric measures related to a thorough assessment of nutritional intake, nutritional status and view on nutrition. ...
... ► A strength of this study is the comprehensive data collection, with physical and anthropometric measures related to a thorough assessment of nutritional intake, nutritional status and view on nutrition. ► The intervention period for this study is [6][7][8][9][10][11][12] months, making the study appropriate for documenting potential preventive effects on age-related loss of muscle function or strength. ► A limitation of this study may be the anthropometric method used to assess muscle mass. ...
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Introduction Age-related loss of muscle mass, muscle strength and muscle function (sarcopenia) leads to a decline in physical performance, loss of independence and reduced quality of life. Nutritional supplements may delay the progression of sarcopenia. The aim of this randomised, double-blinded controlled trial including 100 participants (≥65 years) is to assess the effect of a marine protein hydrolysate (MPH) on sarcopenia-related outcomes like hand grip strength, physical performance or gait speed and to study the associations between physical performance and nutritional intake and status. Method and analysis The intervention group (n=50) will receive 3 g of MPH per day in 12 months. The control group (n=50) receive placebo. Assessments of Short Physical Performance Battery (SPPB), hand grip strength, anthropometric measurements, nutritional status as measured by the Mini Nutritional Assessment, dietary intake, supplement use, biomarkers of protein nutrition and vitamin D, and health-related quality of life (EQ-5D), will be performed at baseline and after 6 and 12 months of intervention. Linear mixed models will be estimated to assess the effect of MPH on SPPB, hand grip strength and quality of life, as well as associations between physical performance and nutrition. Ethics and dissemination The study has been approved by the Regional Committee in Ethics in Medical Research in Mid-Norway in September 2016 with the registration ID 2016/1152. The results will be actively disseminated through peer-reviewed journals, conference presentations, social media, broadcast media and print media. Trial registration number NCT02890290 .
... Diminution des performances avec l'âge(Batsis and Buscemi 2011) ...
Thesis
Un des problèmes majeurs contribuant à la réduction de la mobilité chez la personne âgée est la hausse de l’occurrence des chutes. La capacité à maintenir l’équilibre ou la stabilité posturale a été précédemment associée à la structure et aux propriétés mécaniques des tendons du membre inférieur. Cette étude fut menée afin d’évaluer les effets de l’intensité d’entrainement et de l’âge sur les changements de l’architecture tendineuse et ses propriétés mécaniques ainsi que sur les adaptations musculaires du membre inférieur. Ce projet avait ainsi pour objectif de comparer les effets de deux conditions d’entrainement pour un volume équivalent (intensité modérée (55% d’une répétition maximale (1RM) vs élevée (80% de 1RM)) sur deux groupes musculaires différents (quadriceps vs triceps sural), sur les adaptations des tendons d’Achille et patellaire associés aux adaptations de ces groupes musculaires respectifs. Enfin, le dernier objectif de cette étude était de montrer si des changements de la balance posturale et de la capacité de mouvement pouvaient s’expliquer par les évolutions de l’architecturale et de propriétés mécaniques des structures musculaires et tendineuses avec l’âge. Dix hommes jeunes (Age : 24.8 ± 3.6) et 27 séniors (Age : 69.9 ± 4.5) sédentaires ont été recrutés et ont participé à un programme d’entrainement en résistance de 12 semaines (3 fois/semaine) sur les muscles du triceps sural et du quadriceps. Le groupe de jeunes (n=10) ainsi qu’un groupe de séniors (n=13) ont participé à un programme d’entrainement modéré correspondant à 55% de 1RM, tandis qu’un deuxième groupe de seniors s’est vu imposer une intensité d’entrainement de 80% de 1RM (n=14). Chaque groupe a reçu exactement le même volume d'entraînement sur les muscles quadriceps et triceps sural en utilisant des machines de musculation guidées : la presse à jambes, l'extension des jambes et la machine à mollets assis. Afin de pouvoir obtenir les paramètres nécessaires à cette étude, l’utilisation d’ergomètres, d’images échographiques et IRM et d’un système de capture de mouvement ont été nécessaires. En comparant deux populations de jeunes et de séniors, cette étude a ainsi permis de quantifier une diminution de la force, couplée ou non suivant le tendon considéré à une diminution des propriétés intrinsèques du matériau tendineux. L’obtention de l’architecture musculaire a permis de construire les courbes d’évolutions de la section de chacun des muscles du quadriceps et du triceps sural pour les populations jeunes et séniors. Les deux conditions d’entrainement nous ont permis de mettre en évidence une amélioration des propriétés mécaniques des tendons d’Achille et patellaire, et plus sensiblement le tendon d’Achille, sur les deux populations jeunes et séniors sans toutefois observer de gain supplémentaire pour une intensité élevée. Des gains similaires suite à la période d’entrainement ont pu être observés chez les séniors sur les volumes des muscles du triceps sural et du quadriceps sans distinction de l’intensité considérée. L’analyse du mouvement nous a permis de mettre en évidence l’amélioration de la stabilité posturale et une évolution de la stratégie de flexion du tronc lors d’un lever de chaise suite à l’entrainement chez les séniors sans bénéfice supplémentaire entre une intensité modérée et élevée. De plus, les effets de l’âge sur les propriétés mécaniques des tendons ont pu être corrélés avec les performances liées aux exercices de stabilité posturale, de saut et de lever de chaise. Ce travail a donc permis de quantifier les effets de l’âge sur les capacités musculaires, tendineuses et de mouvement. Cette étude nous a également permis de mettre en évidence un seuil d’intensité d’entrainement (55% de 1RM) à partir duquel les personnes âgées ne semblent pas montrer de gain additionnel pour les systèmes musculaires et tendineux. Ce travail permet donc de proposer une optimisation de l’activité physique prescrite à la personne âgée ou vieillissante.
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Background and aims Sarcopenia leads to metabolic and vascular abnormalities. However, little is known regarding the independent relationship between skeletal muscle mass and atherosclerosis in patients with type 2 diabetes mellitus (T2DM). This study aimed to evaluate the association between skeletal muscle mass and carotid atherosclerosis in men and women with T2DM. Methods In this cross-sectional study, a total of 8202 patients with T2DM were recruited from the Seoul Metabolic Syndrome cohort. Skeletal muscle mass was estimated using bioimpedance analysis, while skeletal muscle mass index (SMI, %) was defined as total skeletal muscle mass (kg)/body weight (kg) × 100. Both carotid arteries were examined by B-mode ultrasound. Carotid atherosclerosis was defined by having a carotid plaque or mean carotid intima-media thickness (IMT) ≥1.1 mm. Results Among the entire population, 4299 (52.4%) subjects had carotid atherosclerosis. The prevalence of carotid atherosclerosis increased with decreasing SMI quartiles for both sexes. The odds ratios for carotid atherosclerosis were 2.33 (95% confidence interval [CI], 1.17-4.63) and 2.24 (95% CI, 1.06-4.741) in the lowest versus highest SMI quartile in men and women, respectively, after the adjustment for clinical risk factors. In men, the risk of atherosclerosis increased linearly with decreasing SMI quartiles (p for trend = 0.036). Conclusions Low skeletal muscle mass was independently associated with the presence of carotid atherosclerosis in men and women with T2DM.
Chapter
Oxidative stress has been related to osteoporosis and other pathologies at the bone. Coenzyme Q10 (CoQ10), a lipid-soluble antioxidant present in cell membranes, has been suggested in vitro to reduce intracellular reactive oxygen species (ROS) production at the same time to prevent or reduce osteoclastogenesis. Also, it promotes osteoblast differentiation and proliferation and matrix mineralization. Thus it has been suggested that this effect on osteoclastogenesis could be a consequence of the reduction of intracellular ROS. The protective effect of CoQ10 against bone loss has been also demonstrated in rodents. Age-associated changes in systemic markers of oxidative damage in animals treated with CoQ10 suggest that this antioxidant can reduce not only intracellular ROS alleviating oxidative damage but also osteoclastogenesis and bone resorption triggered by different signals. Additionally, it has been suggested that oxidative stress is the main mechanism explaining bone alterations both in aged rodents and in those with acute sex steroid deficiency.
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Objective: Patients with type 2 diabetes mellitus (T2DM) are subject to progressive reduction of muscle strength especially in the lower limb. But the rate of progression of weakness is not clear yet. The aim of the study was to compare the isometric and concentric peak torque of knee extension and flexion in the T2DM more and less than 10 years of disease with healthy subjects that matched to patients with regards to sex, body mass index (BMI), ankle to brachial pressure index (ABI), and physical activity index (PAI). Materials and Methods: 30 T2DM patients categorized based on duration of disease in the two groups consist of 18 subjects with T2DM less than 10 years and 12 subjects with T2DM more than 10 years. The patients were compared with 20 sex, BMI, ABI and PAI - matched health subjects. Two- way ANCOVA analyzed the main and interaction effect of grouping and sex on the isometric maximum peak torque (IMPT) and concentric MPT (CMPT) of knee extension and flexion recorded by isokinetic instrument. The age was considered as covariate. Results: The results showed that both knee extensor and flexor IMPT and CMPT were significantly greater in the health subjects than both patient groups (P value<0.02). The amount of CMPT had also negative correlation with HbA1c percent (P value < 0.002). There was no significant interaction effect of sex and grouping and different between two diabetic groups in the all MPTs. the women were weaker than men (P value < 0.002). Conclusion: it is demonstrated that the T2DM patients in the both sexes had less knee strength than health subjects. The effect of duration of diabetes on muscle strength was seem very slowly overtime.
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The European Working Group on Sarcopenia in Older People (EWGSOP) developed a practical clinical definition and consensus diagnostic criteria for age-related sarcopenia. EWGSOP included representatives from four participant organisations, i.e. the European Geriatric Medicine Society, the European Society for Clinical Nutrition and Metabolism, the International Association of Gerontology and Geriatrics-European Region and the International Association of Nutrition and Aging. These organisations endorsed the findings in the final document. The group met and addressed the following questions, using the medical literature to build evidence-based answers: (i) What is sarcopenia? (ii) What parameters define sarcopenia? (iii) What variables reflect these parameters, and what measurement tools and cut-off points can be used? (iv) How does sarcopenia relate to cachexia, frailty and sarcopenic obesity? For the diagnosis of sarcopenia, EWGSOP recommends using the presence of both low muscle mass + low muscle function (strength or performance). EWGSOP variously applies these characteristics to further define conceptual stages as 'presarcopenia', 'sarcopenia' and 'severe sarcopenia'. EWGSOP reviewed a wide range of tools that can be used to measure the specific variables of muscle mass, muscle strength and physical performance. Our paper summarises currently available data defining sarcopenia cut-off points by age and gender; suggests an algorithm for sarcopenia case finding in older individuals based on measurements of gait speed, grip strength and muscle mass; and presents a list of suggested primary and secondary outcome domains for research. Once an operational definition of sarcopenia is adopted and included in the mainstream of comprehensive geriatric assessment, the next steps are to define the natural course of sarcopenia and to develop and define effective treatment.
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To examine the association between muscle strength and total and cause-specific mortality and the plausible contributing factors to this association, such as presence of diseases commonly underlying mortality, inflammation, nutritional deficiency, physical inactivity, smoking, and depression. Prospective population-based cohort study with mortality surveillance over 5 years. Elderly women residing in the eastern half of Baltimore, Maryland, and part of Baltimore County. Nine hundred nineteen moderately to severely disabled women aged 65 to 101 who participated in handgrip strength testing at baseline as part of the Women's Health and Aging Study. Cardiovascular disease (CVD), cancer, respiratory disease, other measures (not CVD, respiratory, or cancer), total mortality, handgrip strength, and interleukin-6. Over the 5-year follow-up, 336 deaths occurred: 149 due to CVD, 59 due to cancer, 38 due to respiratory disease, and 90 due to other diseases. The unadjusted relative risk (RR) of CVD mortality was 3.21 (95% confidence interval (CI) = 2.00-5.14) in the lowest and 1.88 (95% CI = 1.11-3.21) in the middle compared with the highest tertile of handgrip strength. The unadjusted RR of respiratory mortality was 2.38 (95% CI = 1.09-5.20) and other mortality 2.59 (95% CI = 1.59-4.20) in the lowest versus the highest grip-strength tertile. Cancer mortality was not associated with grip strength. After adjusting for age, race, body height, and weight, the RR of CVD mortality decreased to 2.17 (95% CI = 1.26-3.73) in the lowest and 1.56 (95% CI = 0.89-2.71) in the middle, with the highest grip-strength tertile as the reference. Further adjustments for multiple diseases, physical inactivity, smoking, interleukin-6, C-reactive protein, serum albumin, unintentional weight loss, and depressive symptoms did not materially change the risk estimates. Similar results were observed for all-cause mortality. In older disabled women, handgrip strength was a powerful predictor of cause-specific and total mortality. Presence of chronic diseases commonly underlying death or the mechanisms behind decline in muscle strength in chronic disease, such as inflammation, poor nutritional status, disuse, and depression, all of which are independent predictors of mortality, did not explain the association. Handgrip strength, an indicator of overall muscle strength, may predict mortality through mechanisms other than those leading from disease to muscle impairment. Grip strength tests may help identify patients at increased risk of deterioration of health.
Article
With the onset of advancing age, muscle tissue is gradually lost, resulting in diminished mass and strength, a condition referred to as sarcopenia. The sequela of sarcopenia often contributes to frailty, decreased independence, and subsequently increased health care costs. The following was adapted from an introduction to the conference "Sarcopenia, Age-Related Muscle Loss-Causes, Consequences, and Prevention," sponsored by the Kronos Longevity Research Institute in June 2002. This brief review will introduce potential mechanisms that may contribute to sarcopenia, although no one mechanism has yet, and may not completely, define this process. The only agreed-upon intervention from these proceedings was regular physical exercise, stressing weight-training for elderly men and women. However, even those individuals who maintain their fitness through exercise do not appear to be immune to sarcopenia.
Article
Objectives: To study the association between different obesity indicators and walking limitation and to examine the role of C-reactive protein (CRP) and handgrip strength in that association. Design: A cross-sectional, population-based study. Setting: The Health 2000 Survey with a representative sample of the Finnish population. Participants: Subjects aged 55 and older with complete data on body composition, CRP, handgrip strength, and walking limitation (N=2,208). Measurements: Body composition, anthropometrics, CRP, medical conditions, handgrip strength, and maximal walking speed were measured in the health examination. Walking limitation was defined as maximal walking speed less than 1.2 m/s or difficulty walking half a kilometer. Results: The two highest quartiles of body fat percentage and CRP and the two lowest quartiles of handgrip strength were all significantly associated with greater risk of walking limitation when chronic diseases and other covariates were taken into account. In addition, high CRP and low handgrip strength partially explained the association between high body fat percentage and walking limitation, but the risk of walking limitation remained significantly greater in persons in the two highest quartiles than in those in the lowest quartile of body fat percentage (odds ratio (OR)=1.75, 95% confidence interval (CI)=1.19-2.57 and OR=2.80, 95% CI 1.89-4.16). The prevalence of walking limitation was much higher in persons who simultaneously had high body fat percentage and low handgrip strength (61%) than in those with a combination of low body fat percentage and high handgrip strength (7%). Using body mass index and waist circumference as indicators of obesity yielded similar results as body fat percentage. Conclusion: Low-grade inflammation and muscle strength may partially mediate the association between obesity and walking limitation. Longitudinal studies and intervention trials are needed to verify this pathway.
Article
Objective: Insulin resistance is closely associated with two disparate aspects of lipid storage: the intracellular lipid content of skeletal muscle and the magnitude of central adipose beds. Our aim was to determine their relative contribution to impaired insulin action. Research Methods and Procedures: Eighteen older (56 to 75 years of age) men were studied before elective knee surgery. Insulin sensitivity (M/ΔI) was determined by hyperinsulinemic–euglycemic clamp. Central abdominal fat (CF) was assessed by DXA. Skeletal muscle was excised at surgery and assayed for content of metabolically active long-chain acyl-CoA esters (LCAC). Results: Significant inverse relationships were observed between LCAC and M/ΔI (R2 = 0.34, p = 0.01) and between CF and M/ΔI (R2 = 0.38, p = 0.006), but not between CF and LCAC (R2 = 0.0005, p = 0.93). In a multiple regression model (R2 = 0.71, p < 0.0001), both CF (p = 0.0006) and LCAC (p = 0.0009) were independent statistical predictors of M/ΔI. Leptin levels correlated inversely with M/ΔI (R2 = 0.60, p = 0.0002) and positively with central (R2 = 0.41, p = 0.006) and total body fat (R2 = 0.63, p = 0.0001). Discussion: The mechanisms by which altered lipid metabolism in skeletal muscle influences insulin action may not be related directly to those linking central fat and insulin sensitivity. In particular, it is unlikely that muscle accumulation of lipids directly derived from labile central fat depots is a principal contributor to peripheral insulin resistance. Instead, our results imply that circulating factors, other than nonesterified fatty acids or triglyceride, mediate between central fat depots and skeletal muscle tissue. Leptin was not exclusively associated with central fat, but other factors, secreted specifically from central fat cells, could modulate muscle insulin sensitivity.
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Skeletal muscle lipid content has been associated with insulin resistance and type 2 diabetes. However, intramuscular triglycerides can also be a fuel source for healthy muscle during exercise. The balance between storage and use of muscle triglycerides is likely a key to the interaction between dysregulated fat and glucose metabolism by healthy and insulin resistant muscle.
Article
With the onset of advancing age, muscle tissue is gradually lost, resulting in diminished mass and strength, a condition referred to as sarcopenia. The sequela of sarcopenia often contributes to frailty, decreased independence, and subsequently increased health care costs. The following was adapted from an introduction to the conference "Sarcopenia, Age-Related Muscle Loss-Causes, Consequences, and Prevention," sponsored by the Kronos Longevity Research Institute in June 2002. This brief review will introduce potential mechanisms that may contribute to sarcopenia, although no one mechanism has yet, and may not completely, define this process. The only agreed-upon intervention from these proceedings was regular physical exercise, stressing weight-training for elderly men and women. However, even those individuals who maintain their fitness through exercise do not appear to be immune to sarcopenia.
Article
OBJECTIVES: To assess the association between functional limitations and body composition indices, including percentage of body fat, muscle mass, and body mass index (BMI). DESIGN: A cross-sectional, population-representative sample. SETTING: All noninstitutionalized people living in the United States (National Health and Nutrition Examination Survey). Data were collected between 1988 and 1994. PARTICIPANTS: One thousand five hundred twenty-six women and 1,391 men aged 70 and older. MEASUREMENTS: Independent variables included BMI, muscle mass, and percentage of body fat; the latter two were assessed using predictive equations. The dependent variable, functional limitations, was defined as difficulty in performing at least three of five functional living tasks, such as carrying a 10-pound bag of groceries. RESULTS: Women in the highest quintile for percentage of body fat and women with a BMI of 30 or greater were two times more likely to report functional limitations than women in the comparison groups. Similar, but weaker, relationships were found among men; men in the highest quintile for body fat and men with a BMI of 35 or greater were 1.5 times more likely to report limitations. Low muscle mass (sarcopenia) and sarcopenia in combination with high percentage of body fat (sarcopenic obesity) were not associated with a greater likelihood of reporting functional limitations. CONCLUSIONS: Prevention of excessive accumulation of body fat and maintenance of a BMI in the normal range may reduce the likelihood of functional limitations in old age.