The fatter, the better in old age: the current understanding of a difficult relationship

Sarcopenia is thought to be accompanied by increased muscle fat infiltration. However, no longitudinal studies have examined concomitant changes in muscle mass, strength, or fat infiltration in older adults. We present longitudinal data on age-related changes in leg composition, strength, and muscle quality (MQ) in ambulatory, well-functioning men and women. We hypothesized that muscle cross-sectional area (CSA) and strength would decrease and muscular fat infiltration would increase over 5 y. Midthigh muscle, subcutaneous fat (SF), and intermuscular fat (IMF) CSAs and isokinetic leg muscle torque (MT) and MQ (MT/quadriceps CSA) were examined over 5 y in the Health, Aging, and Body Composition study cohort (n = 1678). Men experienced a 16.1% loss of MT, whereas women experienced a 13.4% loss. Adjusted annualized decreases in MT were 2-5 times greater than the loss of muscle CSA in those who lost weight and in those who remained weight-stable. Weight gain did not prevent the loss of MT, despite a small increase in muscle CSA. Only those who gained weight had an increase in SF (P < 0.001), whereas those who lost weight also lost SF (P < 0.001). There was an age-related increase in IMF in men and women (P < 0.001), and IMF increased in those who lost weight, gained weight, or remained weight-stable (all P < 0.001). Loss of leg MT in older adults is greater than muscle CSA loss, which suggests a decrease in MQ. Additionally, aging is associated with an increase in IMF regardless of changes in weight or SF.

Abstract Background Osteosarcopenia, the presence of osteopenia/osteoporosis and sarcopenia, is an emerging geriatric giant, which poses a serious global health burden. Methods and results The prevalence of osteosarcopenia ranges in community‐dwelling older adults [5–37% (≥65 years)] with the highest rates observed in those with fractures (low‐trauma fracture: ~46%; hip fracture: 17.1–96.3%). Among 2353 community‐dwelling adults, risk factors associated with osteosarcopenia include older age [men: 14.3% (60–64 years) to 59.4% (≥75 years); women: 20.3% (60–64 years) to 48.3% (≥75 years), P < 0.05], physical inactivity [inverse relationship: 0.64, 95% confidence interval (CI) 0.46–0.88 (sexes combined)], low body mass index (inverse relationship: men: 0.84, 95% CI 0.81–0.88; women: 0.77, 95% CI 0.74–0.80), and higher fat mass (men: 1.46, 95% CI 1.11–1.92; women: 2.25, 95% CI 1.71–2.95). Among 148 geriatric inpatients, osteosarcopenic individuals demonstrate poorer nutritional status (mini‐nutritional assessment scores: 8.50 ± 2.52 points, P < 0.001) vs. osteoporosis or sarcopenia alone, while among 253 older Australians, osteosarcopenia is associated with impaired balance and functional capacity [odds ratios (ORs): 2.56–7.19; P < 0.05] vs. non‐osteosarcopenia. Osteosarcopenia also associates with falls (ORs: 2.83–3.63; P < 0.05), fractures (ORs: 3.86–4.38; P < 0.05), and earlier death [hazard ratio (1‐year follow‐up): 1.84, 95% CI; 0.69–4.92, P = 0.023] vs. non‐osteosarcopenia. Conclusions This syndrome is expected to grow in age‐related and disease‐related states, a likely consequence of immunosenescence coinciding with increased sedentarism, obesity, and fat infiltration of muscle and bone. Evidence suggests the pathophysiology of osteosarcopenia includes genetic polymorphisms, reduced mechanical loading, and impaired endocrine functioning, as well as altered crosstalk between muscle, bone, and fat cells. Clinicians should screen for osteosarcopenia via imaging methods (i.e. dual‐energy X‐ray absorptiometry) to quantify muscle and bone mass, in addition to assessing muscle strength (i.e. grip strength) and functional capacity (i.e. gait speed). A comprehensive geriatric assessment, including medical history and risk factors, must also be undertaken. Treatment of this syndrome should include osteoporotic drugs [bone anabolics/antiresorptives (i.e. teriparatide, denosumab, bisphosphates)] where indicated, and progressive resistance and balance exercises (at least 2‐3 times/week). To maximize musculoskeletal health, nutritional recommendations [protein (1.2–1.5 g/kg/day), vitamin D (800–1000 IU/day), calcium (1300 mg/day), and creatine (3–5 g/day)] must also be met. It is anticipated that diagnosis and treatment for osteosarcopenia will become part of routine healthcare in the future. However, further work is required to identify biomarkers, which, in turn, may increase diagnosis, risk stratification, and targeted treatments to improve health outcomes.

Abstract Obesity is associated with an increased risk of developing cardiovascular disease (CVD), particularly heart failure (HF) and coronary heart disease (CHD). The mechanisms through which obesity increases CVD risk involve changes in body composition that can affect hemodynamics and alters heart structure. Pro-inflammatory cytokines produced by the adipose tissue itself which can induce cardiac dysfunction and can promote the formation of atherosclerotic plaques. When obesity and HF or CHD coexist, individuals with class I obesity present a more favorable prognosis compared to individuals who are normal or underweight. This phenomenon has been termed the “obesity paradox.” Obesity is defined as an excess fat mass (FM), but individuals with obesity typically also present with an increased amount of lean mass (LM). The increase in LM may explain part of the obesity paradox as it is associated with improved cardiorespiratory fitness (CRF), a major determinant of clinical outcomes in the general population, but particularly in those with CVD, including HF. While increased LM is a stronger prognosticator in HF compared to FM, in patients with CHD excess FM can exert protective effects particularly when not associated with increased systemic inflammation. In the present review, we discuss the mechanisms through which obesity may increase the risk for CVD, and how it may exert protective effects in the setting of established CVD, with a focus on body composition. We also highlight the importance of measuring or estimating CRF, including body composition-adjusted measures of CRF (ie, lean peak oxygen consumption) for an improved risk status stratification in patients with CVD and finally, we discuss the potential non-pharmacologic therapeutics, such as exercise training and dietary interventions, aimed at improving CRF and perhaps clinical outcomes.