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Several changes in body composition occur with the aging process (e.g. a decrease in bone and muscle mass, and an increase in the proportion of fat).[1, 2] Lower muscle mass is associated with decreased strength, and might lead to the development of functional limitations and disability in old age.[3-6] Advanced skeletal muscle loss could also potentially have an impact on quality of life, the need for supportive services and ultimately the need for long-term care in older persons. Thus, it is important to develop a valid and feasible method to screen older adults for sarcopenia, and to establish a preventive strategy for sarcopenia in older people.
Although operative definitions and screening methods for sarcopenia have been proposed in previous studies, the opinions of researchers have been conflicting.[3, 7-10] Recently, a European working group on sarcopenia in older people (EWGSOP) published their recommendations for a clinical definition, and consensus diagnostic criteria, for sarcopenia. In that report, the EWGSOP suggested an algorithm using the presence of both low muscle mass and low muscle function, including strength and gait performance, for the diagnosis of sarcopenia. Low gait performance is the first step to identify sarcopenia in the EWSOP algorithm. Thus, it is possible that older adults with high gait performance would not be categorized as sarcopenic, even if they had evident muscle atrophy.
The term “sarcopenia” was coined by Rosenberg in 1989 to refer to the process of age-related loss of skeletal muscle mass. Originally, “sarcopenia” derives from the Greek words sarx (meaning flesh) and penia (meaning loss), and this term is used to refer specifically to the gradual loss of skeletal muscle mass and strength that occurs with advancing age. According to the original meaning, the definition and diagnosis of sarcopenia should be based on the reduction of muscle mass and strength. Furthermore, sarcopenia is a fundamental component of frailty, and it can be seen as one dimension of frailty. Frailty is a geriatric syndrome resulting from age-related cumulative declines across multiple physiological systems, and is characterized by the following five domains: unintended weight loss, self-reported exhaustion, weakness (reduced grip strength), slow gait speed and low levels of physical activity. If sarcopenia patients are screened according to gait speed, sarcopenia becomes roughly synonymous with frailty, and it could confuse interpretation of both sarcopenia and frailty.
The purpose of the present study was to compare the difference in prevalence of sarcopenia determined using two different algorithms: (i) the EWGSOP algorithm, using gait speed as the first step; and (ii) the muscle mass and strength algorithm, and to examine whether gait speed should be a critical component for screening sarcopenia.
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The EWGSOP recommends that cut-off values for handgrip strength were 30.0 kg in men and 20.0 kg in women. In a sample of Japanese older adults, Tanimoto et al. reported the cut-off values for low grip strength were 30.3 kg in men and 19.3 kg in women. However, the EWGSOP recommendations were based on results that included non-Japanese participants. Tanimoto et al. recruited regular attendees of welfare centers for the aged or community centers to their study. As a result, the generalizability of their results might be limited, and it may not be appropriate to apply their cut-off values in the present study. The present study, using a similar methodology as several previous studies, applied the lowest quintile of grip strength in a healthy subset of subjects (aged ≥65 years) as the cut-off point. The cut-off values for grip strength determined using this method were slightly lower than those published in previous studies. The validity of the cut-off points used in the present study remains to be determined.
We also used sex-specific quintile points (lowest 20%) as the cut-off values for SMI, and these values were similar to previously reported cut-off points of >2 standard deviations less than the mean value for young Japanese adults (7.0 kg/m2 in men and 5.8 kg/m2 in women). These results suggest that the lowest 20% of SMI in Japanese older adults could be a useful substitute for the value two standard deviations below the sex-specific mean SMI of young adults.
Using the EWGSOP-algorithm, 7.5% of all participants were classified as having sarcopenia. The prevalence of sarcopenia in older adults has been widely investigated in European and American countries, and most of these values ranged from 10% to 30%.[3, 5, 21, 22] Reports published on the prevalence of sarcopenia in older adults in Asian countries have tended to show a lower prevalence of sarcopenia in Japan (11.3% and 10.7% in men and women, respectively), Korea (12.1% and 11.9% in men and women, respectively), Hong Kong (12.3% and 7.6% in Chinese men and women, respectively) and Taiwan (23.6% and 18.6% in men and women, respectively). The present study found a similarly low prevalence of sarcopenia. Differences in the prevalence rate of sarcopenia between studies might be as a result of real differences between races and regions. However, because of differences in the operative definitions and screening methods used to detect sarcopenia, we could not directly compare our results with other studies. In addition, the cut-off values for grip strength that we used were slightly lower than those of previous studies. This might lead to an underestimation of the prevalence rate of sarcopenia in our sample. Additional studies are required not only to confirm the validity of cut-off points, but also to determine the standardized definition of sarcopenia.
We tested two screening methods for determining sarcopenia in the present study: (i) the EWGSOP-suggested algorithm using gait speed as the first step; and (ii) the muscle mass and strength algorithm. The resulting prevalence rates of sarcopenia corresponded closely. Although the EWGSOP-algorithm uses a measurement of gait speed as the first step with a cut-off point of 0.8 m/s, there were few people whose gait speed was below 0.8 m/s in our sample of community-dwelling older adults. In addition, most participants categorized as slow (gait speed <0.8 m/s) also had muscle weakness. In fact, Buchner et al. reported that the relationship between muscle strength and gait speed was non-linear, and small changes in muscle strength could have substantial effects on gait speed in frail adults, whereas large changes in muscle strength have little or no effect in healthy adults. The EWGSOP report does not specifically recommend a method for measuring gait speed, and variations in methodology exist (e.g. walking courses may or may not include acceleration and deceleration phases). Differences in the methodology used to measure gait speed could be one reason why a cut-off point of 0.8 m/s was too low for the present study. In any case, we consider that a cut-off value of 0.8 m/s will be too slow if the acceleration and deceleration phases are excluded from the measurement of gait speed. It is debatable whether gait speed is necessary for screening sarcopenic participants in community-dwelling older adults. Future research should examine the necessity of including gait speed in algorithms and the validity of cut-off values.
The present study had several limitations that should be recognized. First, the response rate to postal invitation was 35.7%, and as a result, it is possible that our study suffered from selection bias. Second, we estimated the appendicular skeletal muscle mass by BIA methods. Although BIA is reported to be a highly reliable and accurate method of assessing muscle mass, the accuracy of BIA measurement can be affected by factors such as hydration status, food intake and exercise. Older adults in particular can often have disturbances in water balance and/or extracellular water retention (e.g. edema). Yamada et al. suggested that extracellular water might mask actual muscle atrophy. More precise methods (dual-energy X-ray absorptiometry or magnetic resonance image) should be used in future to assess muscle mass. Third, we used pragmatic cut-off points for determining sarcopenia. It is currently unclear whether the sex-specific lowest 20% was the best value for screening sarcopenic participants. Additional longitudinal studies will be required to confirm the predictive validity of the cut-off values in the future.
The present study showed that the prevalence of sarcopenia in a representative sample of older Japanese adults was 8.2% for men and 6.8% for women based on the EWGSOP-algorithm. When compared with the muscle mass and strength algorithm, the EWSOP-algorithm classified seven additional people (0.15%) into sarcopenia. Future research should examine the necessity of including gait speed in algorithms and the validity of cut-off values.