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Our findings suggest that pre-frailty, which is potentially reversible, is independently associated with a higher risk of older adults developing CVD. Among the physical domains of pre-frailty, low gait speed seems to be the best predictor of future CVD.

The assessment of body composition has important applications in the evaluation of nutritional status and estimating potential health risks. Bioelectrical impedance analysis (BIA) is a valid method for the assessment of body composition. BIA is an alternative to more invasive and expensive methods like dual-energy X-ray absorptiometry, computerized tomography, and magnetic resonance imaging. Bioelectrical impedance analysis is an easy-to-use and low-cost method for the estimation of fat-free mass (FFM) in physiological and pathological conditions. The reliability of BIA measurements is influenced by various factors related to the instrument itself, including electrodes, operator, subject, and environment. BIA assumptions beyond its use for body composition are the human body is empirically composed of cylinders, FFM contains virtually all the water and conducting electrolytes in the body, and its hydration is constant. FFM can be predicted by BIA through equations developed using reference methods. Several BIA prediction equations exist for the estimation of FFM, skeletal muscle mass (SMM), or appendicular SMM. The BIA prediction models differ according to the characteristics of the sample in which they have been derived and validated in addition to the parameters included in the multiple regression analysis. In choosing BIA equations, it is important to consider the characteristics of the sample in which it has been developed and validated, since, for example, age- and ethnicity-related differences could sensitively affect BIA estimates.

It is known that weakness in the lower limbs is associated with recurrent falls in old people. Among the tests routinely used to assess lower extremity strength, the Short Physical Performance Battery (SPPB) is one of those used most often, but its relationship with recurrent falls is poorly investigated. We aimed to determine if SPPB scores are related to recurrent falling in a sample of 2710 older-aged people, and to ascertain which test in the SPPB is most strongly associated with a higher rate of falls. In this cross-sectional study, we demonstrated that participants scoring 0-6 in the SPPB were more likely to be recurrent fallers than those scoring 10-12 (odds ratio [OR] = 3.46, 95% confidence interval [CI] 2.04-5.88 in women; OR = 3.82, 95% CI 1.77-8.52, in men). SPPB scores of 7-9 were only associated with women being more likely to be recurrent fallers (OR = 2.03, 95% CI 1.28-3.22). When the SPPB items were analyzed separately, even a lower score in gait speed for women was significantly associated with the presence of recurrent falls (OR = 2.11; 95% CI 1.04-4.30), whereas in men only a significant increase in the time taken to complete the five timed chair stands test was associated with a higher rate of falls (OR = 2.75; 95% CI 1.21-6.23). In conclusion, our study demonstrated that SPPB scores £ 6 are associated with a higher fall rate in old people of both genders; in females, even an SPPB score between 7 and 9 identifies subjects at a higher likelihood of being recurrent fallers. Among the single items of the SPPB, the most strongly associated with falls were gait speed in women and the five timed chair stands test in men.

The intermediate and advanced stages of Alzheimer's disease (AD) are frequently associated with weight loss (WL), but WL may even precede the onset of cognitive symptoms. This review focuses on the possible aetiologic and temporal relationships between AD and WL. When WL occurs some years before any signs of cognitive impairment, it may be a risk factor for dementia due to deficiency of several micronutrients, such as vitamins and essential fatty acids, and consequent oxidative tissue damage. The leptin reduction associated with WL may also facilitate cognitive decline. The mechanisms potentially inducing WL in AD include lower energy intake, higher resting energy expenditure, exaggerated physical activity, or combinations of these factors. A hypermetabolic state has been observed in animals with AD, but has not been confirmed in human subjects. This latter mechanism could involve amyloid assemblies that apparently increase the circulating cytokine levels and proton leakage in mitochondria. WL may be caused by patients' increased physical activity as they develop abnormal motor behaviour (restlessness and agitation) and waste energy while trying to perform daily activities. During the course of AD, patients usually find it increasingly difficult to eat, so they ingest less food. AD-related neurodegeneration also affects brain regions involved in regulating appetite. The caregiver has an important role in ensuring an adequate food intake and controlling behavioural disturbances. In conclusion, WL is closely linked to AD, making periodic nutritional assessments and appropriate dietary measures important aspects of an AD patient's treatment.Weight loss: Alzheimer's disease: Dietary intake: Energy expenditure: Malnutrition Alzheimer's disease (AD) is the most common neurodegenerative disease of the brain, representing more than 50% of all dementia cases (1) . It is characterized by multiple cognitive deficits and progressive deterioration in functional performance, and leads to increasing disability and mortality. AD is frequently associated also with nutritional disorders and weight loss (WL), which is considered as one of the criteria for the clinical diagnosis of dementia (2) . The loss of body weight gives rise to loss of muscle mass and strength, and a greater risk of falls, functional dependence and worsening quality of life (3) . To prevent these negative consequences, it is important for clinicians to detect weight variations early and plan appropriate nutritional intervention.The majority of studies report that AD patients lose weight especially in the intermediate and advanced stages of the disease (4) , but some studies suggest that WL may start even several years before dementia sets in, and others indicate that it may occur just before the cognitive symptoms become manifest (5) . This variability in the onset of WL vis-à-vis the clinical signs of dementia, combined with the long latency period of AD, makes it difficult to ascertain the relationship between WL and AD. The question is not only whether WL ...