Moving Beyond Static Body Composition Paradigms to Assessments of Change, Plasticity, and Function
Article first published online: 27 JAN 2010
© 2010, Copyright the Authors. Journal compilation © 2010, The American Geriatrics Society
Journal of the American Geriatrics Society
Volume 58, Issue 2, pages 377–379, February 2010
How to Cite
Duque, G. and Kuchel, G. A. (2010), Moving Beyond Static Body Composition Paradigms to Assessments of Change, Plasticity, and Function. Journal of the American Geriatrics Society, 58: 377–379. doi: 10.1111/j.1532-5415.2009.02687.x
- Issue published online: 27 JAN 2010
- Article first published online: 27 JAN 2010
Body weight is one of the most commonly and easily performed measurements in a physician's office. Rapid weight loss provides clear grounds for concern, yet the interpretation of stable or gradually changing weight and its relevance to older individuals' future health status represents a far more complex clinical issue.1 As for other important clinical questions in geriatric medicine, research findings relating body weight to clinical outcomes in younger populations cannot be simply transferred to older adults. For example, aging-related losses in lean muscle mass, especially when accompanied by modest gains in fat mass, may take place even in the absence of changes in total body weight.2 Furthermore, changes in body composition in older persons not necessarily associated with weight loss may predict poor outcomes, including disability and death. Thus, it is not surprising that lower3 and upper4 extremes in body weight have emerged as risk factors for frailty.
As a result, many unresolved questions remain, and no formulas or tables exist that would permit the clinician to confidently recommend “optimum” target weights to individual older patients. Technologies designed to measure body composition offer the ability to identify older adults whose lean muscle, fat, or bone mass lies outside of population-based norms, but with the exception of dual energy X-ray absorptiometry (DXA)-derived measurements of bone mineral density (BMD), assessments of body composition have failed to affect everyday clinical geriatric practice. DXA was first developed to measure bone mineral content (BMC), yet even though it has also been validated as a reliable research tool for measuring fat and lean mass in older adults,5 clinicians do not use it for these purposes, and even in the case of BMD, growing evidence indicates that, with aging, the importance of low bone mass as a predictor of a hip fracture diminishes, and other risk factors such as a history of a previous fracture, difficulty rising from a chair without use of arms, poor depth perception, use of long-acting benzodiazepines6,7 and recent weight loss8 begin to outweigh it.
Efforts at expanding older adults' overall “healthspan” and functional independence through clinically realistic strategies designed to prevent or postpone disability lie at the core of modern geriatric practice.9–11 The article by Koster and colleagues12 addresses many of these issues from the perspective of a 7-year prospective observational cohort study involving nearly 3,000 older adults enrolled in the Health, Aging and Body Composition (Health ABC) Study. Koster and colleagues12 evaluated the ability of physical fitness to predict subsequent changes in body composition and muscle strength. The observation that physical fitness (as measured according to ability and time needed to complete a 400-m walk)13,14 is related to differences in body composition and muscle strength is interesting but not particularly surprising. The major novel contribution of this study lies in the investigators' capacity to provide longitudinal data that, when stratified according to physical fitness, provides a dramatic illustration of the tremendous physiological variability and plasticity that different subsets of older adults experience as they age.12 Not only is physical fitness associated with current and future differences in body composition, but analysis of the differences in the longitudinal changes involving specific body composition parameters suggests the presence of significant variability in the nature of the specific physiological factors that may promote or hinder homeostatic responses,15 thus affecting the maintenance of function in different subsets of older adults.12 Moreover, because a long-distance walk test could be incorporated into a typical outpatient clinical encounter, such an approach might ultimately be used to offer older adults more-individualized interventions. These could be selected in a manner designed to target specific populations based on knowledge gained regarding the nature of the underlying physiological mechanisms that place those particular individuals at a greater risk of future disability.
Aging is associated with a large number of now well-defined changes in body composition.16 These involve alterations in relative or absolute amounts of tissue, as well as qualitative changes that affect tissue quality and performance.16 Some changes, such as mild age-related accumulations of abdominal fat or modest declines in femoral bone mass, become so common in late life that they are typically viewed as representing normal or usual aging, leading in some cases to the development of age-adjusted nomograms. Other categories of altered body composition have been viewed as being more pathological in nature. Examples include quantitative abnormalities involving excessive fatty deposits in regions (e.g., abdomen) that may occur at any age1,16 and qualitative abnormalities with de novo fatty infiltration (e.g., skeletal muscle) that are seen in aging-related sarcopenia and specific categories of muscle diseases.17
With aging, there is a fat redistribution in which fat progressively infiltrates tissues such as pancreas, muscle, and bone that are not usually fatty.18 It has been proposed that this progressive fat infiltration results from an imbalance in pro-adipogenic factors that stimulate the differentiation of fat precursors present in these organs. The final consequence of this process has been associated with sarcopenia,16 osteopenia,19 and diabetes mellitus.20 DXA evidence provided by Koster and colleagues supports the notion that less-fit individuals have greater fat mass. Although computed tomography measurements and muscle biopsy information were not provided, less-fit individuals would also probably demonstrate a higher predisposition for fat infiltration at the expense of muscle lean mass. Thus, more-fit individuals may have lower pro-adipogenic factor levels and therefore could be better prepared for the changes in tissue distribution that happen at older age (Figure 1).
The process of fat redistribution with aging may also, to some extent, be hormonally dependent. In Koster's study, the least-fit women were able to maintain similar rates of decline in muscle function as their more-fit contemporaries.12 This may be because they started with greater overall muscle mass,12 although because the least-fit women appeared to lose fat mass at a slower rate than the least-fit men,12 the process seems to be related to sex and therefore may be associated with estrogen status. Estrogen deficiency promotes adipocyte differentiation.21 Thus, declines in estrogen levels in postmenopausal women, along with greater adipocyte differentiation and fat distribution, may explain in part fat redistribution and lean mass loss in fit and unfit older women, as well as lower rates of decline in fat mass in the least-fit women than in the least-fit men, independent of their baseline body composition.
The above findings also provide additional evidence to support the concept that the trajectory taken toward disability or continued function taken by different subsets of older adults as they age is highly variable and may fall within a number of distinct patterns.22 Beyond purely descriptive differences in body composition experienced by least-fit women as opposed to least-fit men, the matter may also be viewed from the perspective of underlying physiological principles that permit different categories of older adults to maintain normal function when they are exposed to various challenges.15 Viewed in this manner, the least-fit older women may be able to maintain muscle function comparable with that of their more-fit counterparts (Table 1) by starting off with a higher lean muscle mass.12 In contrast, more-rapid loss of fat in the least-fit older men could help promote function by decreasing the amount of work that needs to be performed.12 These types of considerations could help contribute to the design of interventions that are more effective in their ability to prevent or slow the progression to disability precisely by virtue of their ability to target those compensatory mechanisms that are especially important in specific subpopulations of vulnerable older adults.
|Sex||Body Weight||Fat Mass||Lean Mass||Muscle Quality||Factor Contributing to Continued Function|
|Female||Heavier||More fat||More total muscle||Worse muscle quality||Greater functional reserve (total muscle mass)|
|Male||Heavier but more rapid loss with aging||More fat but more rapid loss with aging||Similar||Worse muscle quality||Decreased workload (greater fat loss)|
Another important question to be addressed regards the metabolic role of the fat that accumulates in different body compartments with aging. Aging is associated with declines in the ability of muscle mitochondria to handle free radicals and generate energy.23 More-fit individuals are generally more active and therefore use a significantly higher amount of body fat for energy than more-sedentary, unfit subjects. Several studies have suggested that age-related fat infiltration is associated with lower metabolic capacity, an effect that has been postulated to result from the toxic effects exerted on surrounding muscle tissues by inflammatory molecules released from these fat cells.20 In unfit individuals, a vicious cycle may include fat infiltration and redistribution, muscle and bone toxicity, and finally, more fat infiltration, which further perpetuates the process.
In summary, low fitness as evaluated using a simple measure of mobility was associated with higher body weight, higher fat mass, and a lower percentage of muscle mass in both sexes, although potential sex differences became apparent with follow-up. Overall rates of decline in muscle quality, evaluated as muscle strength per body weight, were similar in all subjects. Nevertheless, potential sex differences with effect on physical performance became apparent with follow-up. In the least-fit older men, fat mass visualized using DXA declines at a rate faster than that seen in their more-fit counterparts. It remains to be seen whether these declines in adiposity are associated with greater than expected fat infiltration within muscle tissues as might be demonstrated on a computed tomography scan (Figure 1). Such a change could result in poorer muscle quality while also providing evidence in support of the hypothesis that fat deposits within muscle tissues may result from infiltration by adipose cells as opposed to potential transdifferentiation whereby muscle cells might assume an adipogenic phenotype. Moreover, lower overall fat mass could decrease the amount of work required of muscle in these least-fit men. In contrast, although rate of fat loss in women did not appear to change with fitness status, the least-fit women had greater total lean mass than did their more-fit counterparts. Muscle mass represents merely one determinant of physical fitness, with muscle quality, body weight, and cardiorespiratory performance representing additional key contributors. It remains to be seen whether greater total muscle mass in the least-fit women may provide some degree of protection from declines involving other physiological contributors to fitness such as age-related fat redistribution and its consequences such as sarcopenia and osteopenia. Further studies examining the cellular differences between fit and unfit elderly subjects are also required.
Conflict of Interest: The editor in chief has reviewed the conflict of interest checklist provided by the authors and has determined that the authors have no financial or any other kind of personal conflicts with this paper.
Dr. Duque is supported by grants from the University of Sydney Medical Research Foundation and the Nepean Medical Research Foundation. Dr Kuchel is supported by grants from the National Institute of Health (AG028657, AR54713, AI068265) and by the Citicorp Chair in Geriatrics and Gerontology.
Author Contributions: Dr. Duque and Dr. Kuchel are sole contributors to this editorial.
Sponsor's Role: None.
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