ReviewSarcopenic obesity: A Critical appraisal of the current evidence
Introduction
Healthy ageing is associated with physiological, gender-specific changes in body composition which impose an overall minimal load on the control of metabolic and cardiovascular functions.1, 2 A significant deviation from a healthy trajectory of body composition may increase the incidence rate of adverse health events.3 The assessment of body composition is commonly performed by quantifying fat (FM) and fat free mass (FFM) components. These components are often utilized to assess the risk for adverse health outcomes in conditions characterized by abnormal modifications of body composition (e.g., obesity, anorexia, cancer).4 However, in recent years the study of the loss of muscle mass (sarcopenia) has experienced a revitalized research interest,5 promoted by the specific application of in vivo body composition methods (dual energy X-ray absorptiometry (DXA), imaging and spectroscopic methods) for the assessment of the quantitative and qualitative characteristics of skeletal muscle mass.6, 7, 8
The predictive value of sarcopenia for health outcomes relates to the metabolic and functional relationship between muscle mass (MM) and physical strength, mobility and vitality.9, 10, 11 Sarcopenia is associated with an increased risk for age-related decline in muscular strength and functional ability,12, 13 as such as it has been labelled a “silent crippler” because of its association with physical disability, falls, fractures and frailty.9, 10, 11, 14, 15 Loss of MM in older individuals is significantly associated with extended hospital stays, infectious and non-infectious complications and overall mortality.9, 14, 16, 17, 18
However, sarcopenia often co-occurs with an increase in FM, a scenario termed sarcopenic obesity (SO), which may carry the cumulative risk derived from each of the two individual body composition phenotypes.19, 20 On its own, excess adiposity may generate significant adverse health effects (e.g., hypertension, dyslipidaemia, insulin resistance). However, evidence increasingly suggests that these risks may be elevated with the addition of low MM.
The prevalence of SO in older-aged individuals is increasing21, 22, 23 and its impact on physical, metabolic and cardiovascular functions is becoming a primary concern amongst nutritionists, geriatricians and public health officers. The ethio-pathogenesis of SO is complex and multi-factorial factors can interplay, including lifestyle (diet, physical activity, smoking), endocrine (corticosteroids, growth factors, insulin, catecholamines), vascular (endothelial function, coagulation), and immunological (inflammation, reactive oxygen species) factors.24, 25 A unanimous view on the direction of the causality of the associations between these factors is not established.
A simple example of the multi-factorial origin of SO is illustrated in Fig. 1. The diagram describes two hypothetical metabolic scenarios conducive to the onset of the same sarcopenic obese phenotype, which is, however, derived from two different metabolic trajectories, i.e., weight gain and weight loss. Weight gain normally occurs alongside a variable rate of accretion of FFM which can potentially give origin to either an obese (normal FFM accretion) or to a SO (low FFM accretion) phenotype. The direction of the model can be reversed when, for example, morbidly obese subjects (body mass index (BMI) > 40 kg/m2) lose a significant amount of weight but not sufficient to move subjects into the overweight category (BMI < 30 kg/m2), a scenario habitually observed with non-surgical weight loss treatments. Weight loss in these subjects could induce a variable rate of FFM loss and therefore determine the onset of a SO phenotype in obese subjects with more prominent losses in lean tissue mass. The between-subject variability in the composition of the tissue in both positive and negative energy balance has been demonstrated in overfeeding and underfeeding experimental, controlled studies able to control for potential confounding factors such as physical activity or dietary intake. For example, Siervo et al.,26 showed that lean healthy subjects gained 6.0 ± 1.3 kg in body weight after a 9-week stepwise overfeeding and the contribution of FM, measured using a 4-compartment model, to total weight change varied between 11% and 98%. Similarly, two groups of obese men who lost 10% (−10.9 ± 2.6 kg) of their baseline weight following either a VLCD or LCD and the contribution of FM to total weight loss varied between 73% and 106%.27 Additional factors can further add to the variability of body composition changes in states of energy imbalance such as physical activity, dietary macronutrient composition, rate of weight loss, genetics, menopausal state, immobilization, endocrine dysfunctions, inflammatory disorders or pharmacological treatments.28, 29, 30, 31, 32 Recent advances in the allometric modelling of these changes could provide a roadmap for the evaluation of the effects of interventions on body composition.33 These models, along with models of the change in visceral fat with weight/fat change could define the trajectory of the expected changes in fat and lean with weight gain and loss and the ability of specific interventions to modify body composition when weight changes. Unfortunately, these models have not been validated in SO and this should be a priority for future clinical studies.
Section snippets
Diagnosis of sarcopenic obesity
The lack of a unanimous view on the criteria to apply to define low MM and high FM in order to identify cases of SO represents a major clinical and research drawback. The criteria are somewhat arbitrary and study-specific, which may have minimized the predictive value of SO as a health risk factor.12 One of the most commonly used indexes for the definition of sarcopenia is the total appendicular skeletal muscle (ASM) index assessed by DXA.34 Individuals with either an ASM index (kg/m2) lower
Sarcopenic obesity and health risks
In a large longitudinal study of community-dwelling older individuals cardiovascular disease event rates were 23% higher in those with SO compared to either sarcopenic or obese individuals.36 In post-menopausal women SO was associated with lower physical function (gait speed) and cardio-pulmonary fitness (peak VO2 and ventilatory threshold).53 Data from the New Mexico Elder Health Survey showed that SO preceded disability.23 Sarcopenic obesity has also been related to a decline in functional
Sarcopenic obesity: a critical appraisal
The analysis of the literature has highlighted a wide heterogeneity of the criteria applied for the classification of SO, resulting in inconsistent associations between SO and disease risk. A systematic appraisal of this heterogeneity has been conducted and categorized into: 1) methodology (body composition methods utilised); 2) classification (the body composition component and the cut-off points used for the classification of sarcopenia and obesity); 3) adjustment (the methods adopted to
Future directions
Based on epidemiological data there is concern surrounding weight loss in elderly patients. However, to date there have been no studies exploring the effects of moderate weight loss on muscle mass in patients with SO. If excess adipose tissue is providing a lipotoxic pro-inflammatory milieu which is part of the etio-pathology of SO, then weight loss with its attendant reduction in FFA and inflammation should be helpful. This is a major gap in the literature.
Although the mechanism(s) of the
Conclusions
The expected increase in lifespan and childhood obesity represent primary predictors of a forecasted increase of obesity in older subjects, which emphasize the urgency to understand the ethio-pathogenesis of SO for the early prevention of potentially associated health risks. A strategic research agenda which includes mechanistic, epidemiologic and clinical approaches must be prioritized to operationalise the diagnostic criteria and define the causality and the strength of risk associations.
Statement of authorship
The manuscript was conceived by CMP and MS. They discussed the manuscript with all the other authors (JCK, SSR, BCMS) and co-wrote the manuscript. All authors contributed to subsequent analyses and interpretation. All authors contributed to the final revision of the manuscript. The corresponding author (MS) is the guarantor for the manuscript and had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis reported
Conflict of interest
All authors have no conflicts of interest to declare.
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