Therapeutic for Sports Medicine and Athletic Training Modalities

 

NUTRITION AND SKELETAL MUSCLE

Skeletal Muscle Mass Indices in Healthy Adults Heliodoro Alema´n-Mateo1 and Roxana E. Ruiz Valenzuela2 1 Departamento de Nutricio´n y Metabolismo, Coordinacio´n de Nutricio´n, Centro de Investigacio´n en Alimentacio´n y Desarrollo (CIAD), A.C. Hermosillo, Sonora, Me´xico 2 Departamento de Salud, Universidad Iberoamericana, Ciudad de Me´xico-Tijuana, Tijuana, Baja California, Me´xico INTRODUCTION Skeletal muscle (SM) increases during postnatal development through a process of hypertrophy of the individual muscle fibers; a similar process may be induced in adult SM in response to contractile activity like strength exercises, and to androgens and β-adrenergic agonists [1]. SM remains relatively constant during the third and fourth decades of life but begins to decline at B45 years of age in both genders [2]. In other words, age exerts a strong influence on SM, but gender does as well [3
8]. Several studies have demonstrated the effects of age and gender on SM, and some have examined the effects on its distribution [2,5
6]. Perhaps the most relevant study on this issue was published by Janssen et al. [2], who used an in vivo method to study body composition using, particularly, magnetic resonance imaging (MRI) to provide precise and reliable measurements of SM and its distribution in a broad sample of Caucasian men and women. The results of this study reported new findings on the behavior of SM mass during the lifecycle in both men and women subjects. Due to the growing awareness of the importance of SM on functionality and other clinical entities in older age groups [9
16], there is a need to establish reference values for relative SM in young adult populations using the most precise and accurate methods available, and considering the factors of age, gender, and ethnicity. It is important to stress that few countries have been able to conduct national-level studies of this kind [10,17
19]. Some published works based on small samples of healthy young adult subjects reported data on SM [2,6,20
21] and proposed cutoff points for diagnosing sarcopenia—i.e., low SM mass—and sarcopenia syndrome [9,10,17,22
42]. To our knowledge, 21 cutoff points 3 Nutrition and Skeletal Muscle DOI: https://doi.org/10.1016/B978-0-12-810422-4.00001-4 © 2019 Elsevier Inc. All rights reserved. based on SM exist; specifically, 17 dual-energy X-ray absorptiometry (DXA)-derived appendicular skeletal muscle mass (ASM) indices, 3 DXA-derived total SM (TSM) indices, and one DXA-derived total lean body mass (LBM) index for younger adult populations around the world [9,17,22
36], together with seven indices derived from bioelectrical impedance analysis (BIA) [10,37
42], one that used an ultrasound technique [43], and one MRI-derived TSM index (TSMI) [19]. Before presenting the main results of the published ASM, TSM, and LBM indices, we will first review the biological bases that underlie them. THE BIOLOGICAL BASES THAT UNDERLIE THE INDICES Indices are association measurements that can be very useful in classifying nutritional status or, as in the present case, the stadia of SM, evaluating the chronicity of the skeletal muscle loss and assessing the efficacy of nutrition on loss of SM during the intervention therapy. They may also serve to quantify various components of body mass. Indices of this kind are usually divided into (1) those relative to weight and height and (2) those relative to body composition. SM indices are the ones most closely related to body composition that are used to diagnose presarcopenia and sarcopenia syndrome in geriatric populations. As mentioned above, SM tissue is dependent on age, gender, body weight, height, and ethnicity [2,5
6]. It is important to note that much of our current understanding of SM is based on studies that used DXA and MRI, two in vivo methods for analyzing body composition [2,5
6] that can accurately measure total or regional SM. DXA- derived lean tissue in arms and legs or ASM account for .75% of total SM [44], which constitutes the primary portion of SM involved in ambulation, physical activities, and functionality across the lifespan. To clarify the origin of an index, particularly ASM, we examined the main findings reported by Gallagher et al. [6], who assessed SM components by DXA in 148 healthy adult women (80 African-Americans, 68 Caucasians) and 136 healthy adult men (72 African-Americans, 64 Caucasians) with an age range of 21.1
67.5 years. First, they noted a significant negative correlation between ASM and age in all four groups. After adjusting for age, they determined that ASM was significantly and positively correlated with body weight and height in both ethnic groups, and in both men and women. Using multiple regression models, they then explored the independent effects of height, weight, age, gender, and ethnicity on ASM. In their predicted ASM model, height and weight explained 64% and 67%, respectively, of ASM variance in the African-American and Caucasian women, and 63% and 39%, respectively, in the African-American and Caucasian men. Smaller contributions were found for age. Interestingly, after adjusting for height, body weight, and age, an effect of gender was also found, as the men were found to have greater ASM than the women in both groups of subjects across the entire age range. Finally, a significant effect of ethnicity on ASM was found, as the African-American men and women had greater adjusted ASM than the Caucasian subjects [6]. Three years later, Janssen et al. [2] examined the influence of age, gender, body weight, and height on TSM assessed by whole body MRI in a large, heterogeneous sample of 468 men and women aged 18
88 years. It is important to mention that this study included two additional ethnic groups—Asians and Hispanics—in assessing TSM and its distribution [2]. As in the case of Gallagher et al. [6], these researchers also reported a significant 4 1. SKELETAL MUSCLE MASS INDICES IN HEALTHY ADULTS I. GENERAL ASPECTS: SKELETAL MUSCLE PHYSIOLOGY AND NUTRITION effect of height, body weight, age, and gender on total and regional or appendicular SM. In another significant finding related to this chapter, Janssen et al. [2], demonstrated that the substantial increase in body weight observed between 18 and 40 years of age was not associated with a corresponding increase in TSM. Instead, the absolute quantity of TSM was maintained into the fifth decade of life, but with noticeable losses thereafter. This finding is important so as not to limit the cutoff points for SM mass indices for people aged 18
40 years, as was originally proposed in Rosseta’s study [6], and the body composition reference values from National Health and Nutrition Examination Survey [17] or Korean studies [29,33
34]. Numerous body composition indices have been generated by considering the biological and statistical associations among certain aspects of body composition with age, and specific anthropometric variables; especially, the strong correlation between absolute SM and height. Originally, in order to define low SM mass or sarcopenia, it was necessary to have a measure related to the amount of existing SM [9], and as previously mentioned, the absolute values of SM correlates strongly with height. Therefore, ASM (kg) divided by height squared (ht2 ) produces an index of relative appendicular SM mass that serves as an indicator of muscularity. In fact, Baumgartner et al. [9] established that placing ht2 in the denominator constituted the best common power for minimizing the correlation of the index with height across all gender, ethnic and age groups, and study populations, since adjusting TSM or ASM for size eliminates the differences in the amount of SM associated with the greater height of young adults, as well as those related to gender and ethnicity. The resulting index permits better comparisons than absolute values of SM or any other parameter of body composition. SM has also been adjusted by body weight following the same principle as adjustment by ht2 . Following Janssen et al. [10], SM adjusted by body weight considered adjustments for both stature and the mass of non-SM tissues (i.e., fat, organs, and bones) under the assumption that most mobility tasks and daily living activities are strongly influenced by body size. In older people, in addition to the adjustment by height, SM has also been adjusted by fat mass. Originally, it was hypothesized that SM adjusted by height and fat mass would better identify subjects with sarcopenia or with low SM than an index adjusted only for ht2 and that individuals so identified as such might be at even greater risk for poor lower extremity functioning [45]. With respect to the adjustments of absolute SM values by ht2 , body weight, fat mass, or body mass index, a debate is ongoing as to which of these different indices is the best SM parameter and, therefore, the one that should be included in the criteria to define sarcopenia. Based on their results, Han et al. [42] proposed using absolute SM adjusted by height, because it correlated more closely with grip strength and with better muscular function than SM adjusted by body weight. Therefore, they recommended utilizing SM adjusted by height to diagnose sarcopenia syndrome. To the best of our knowledge, no established cutoff points adequately identify the level at which relative SM becomes deficient or low SM. In the most recent international consensus on the operational definition of presarcopenia and sarcopenia syndrome by the European Working Group on Sarcopenia in Older People (EWGSOP) [46], the International Working Group on Sarcopenia (IWGS) [47], and the Asian Working Group for Sarcopenia (AWGS) [48], the cutoff values for each gender were redefined, 

THE BIOLOGICAL BASES THAT UNDERLIE THE INDICES 

5 I. GENERAL ASPECTS: SKELETAL MUSCLE PHYSIOLOGY AND NUTRITION

 respectively, as values one or two standard deviations (SD) below the gender-specific mean values of the reference data of a healthy young adult population [9
10,46
48]. The usefulness of these criteria and their corresponding cutoff points is based on a normal distribution which assumes that 68% of cases would fall within one standard deviation from the mean, and that 95% of all cases would fall within two standard deviations. As a result, the ASM index (ASMI) not only adjusts ASM according to height but also takes into account the lower correlation between height and ASM; this means, a deficit, expressing low appendicular SM mass or presarcopenia, or an excess, suggestive of high appendicular lean tissue or muscularity, expressed as high ASM. Finally, this criterion (22 SD of the mean values of the gender
ethnic-specific SM indices from a young adult population) is the one most often used and associated with impaired physical performance and physical disability in geriatric populations 

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