Search

There is a positive association between physical activity (PA) and improved health in older adults. The objective of this study was to assess the prevalence and determinants of meeting recommended levels of PA among older adults with multimorbidity. Data has been derived from the nationally representative Scottish Health Surveys (2014&ndash, 2017). A sub-sample of 2230 older adults (aged 65+) with multimorbidity were the study participants. Physical activity was evaluated using current recommended guidelines. Overall, 32.3% of the participants met the recommended levels of PA. Independent predictors of meeting the recommended levels of PA include male gender [odds ratio (OR) 2.00 (95% confidence interval (CI) 1.58&ndash, 2.54)], living in the least deprived areas [OR 1.79 (95% CI 1.20&ndash, 2.69)], being a non-smoker [OR 2.22 (95% CI 1.48&ndash, 3. 34)]. Also, meeting recommended PA decreased with age [OR 0.92 (95% CI 0.90&ndash, 0.94)] and body mass index [OR 0.93 (95% CI 0.91&ndash, 0.95], but increased per additional portion of fruit and vegetables taken [OR 1.19 (95% CI 1.12&ndash, 1.25)] and with increase in well-being scale score [OR 1.05 (95% CI 1.03 to 1.06)]. Adherence to PA guidelines seems to be more related to age, BMI, gender (i.e. higher PA adherence in men vs. women), social support (i.e. social deprivation), dietary habits (i.e. fruit and vegetable intake) and social isolation among the elderly. In the one-third of older population, adherence to PA was associated to better mental health. Therefore, adaptation of PA guideline to suit theses determinants factors would reduce the gap difference among older adults with multimorbidity and enhance their mental well-being.

This study investigated the effect of motor learning with informational feedback into response to anaerobic exercises with and without motor learning tasks in handball physical education university students. Participants were randomly divided into two groups: experimental group (EG, n = 10) and control group (CG, n = 10). Measurements of T-half test, 15-m and 30-m sprints, and ZIG-ZAG test were assessed in both groups before (T1), between (T2) a 4-week intervention program, and after (T3) an 8-week intervention program, which included agility and speed teaching with (EG) or without (CG) informational feedback (i.e., verbal instruction). The test-retest reliability for all tests was excellent, and the ICC ranged from 0.76 (ZIG-ZAG test) to 0.99 (Agility T test). The interday measurement error was clearly below 1% in all tests (CV range: 0.2–0.8). Time effects for the Agility T test (p = 0.012, ηp2 = 0.245) and the 15-m sprint (p = 0.035, ηp2 = 0.190) were found. For the Agility T test, a total interaction effect (p = 0.001, ηp2 = 0.380) and a partial interaction effect were calculated between T2 and T3 (p < 0.001, ηp2 = 0.603). A large effect size (d = 0.87) was observed in the EG from T2 to T3. The second relevant (d ≥ 0.5) effect size was calculated for the parameter sprint 30 m. The CG showed a significant sprint performance reduction from T2 to T3 (d = −0.60; parameter: sprint 30 m). All other effect sizes were less than 0.44. The ZIG-ZAG test revealed the largest main and partial effect sizes for all parameters. The EG showed the largest improvement (d = 2.00) between T2 and T3. The results demonstrate that motor learning with informational feedback improves performances of Agility T test, sprint, and ZIG-ZAG performance. It appears that a well-formulated verbal instruction may induce performance enhancement in young trainees in educational environment.

Obesity is a medical condition that constitutes the major risk factor for the development of insulin resistance, type 2 diabetes and subsequent diabetes-related complications such as micro- and macrovascular disease [1, 2]. Chronic low grade inflammation has been described as a fundamental component of adipose tissue expansion in obesity. Inflamed adipose tissue is characterized by enhanced secretion of cytokines and recruitment of leukocytes, in particular macrophages [3]. Current evidence suggests that these cytokines, often referred to as Adipokines, including Resistin, Visfatin, Apelin, Omentin, Chemerin, IL-6, MCP-1, PAI-1, or TNF-α link obesity to the development of systemic insulin resistance [4]. Emerging evidences suggested that Osteopontin (OPN) is a main regulator of adipose tissue inflammation, insulin resistance and diabetes mellitus. Osteopontin (OPN), a glycoprotein was first identified in 1986 in osteoblasts. Osteopontin is a multifunctional protein, highly expressed in bone. The prefix of word ‘osteo’ indicates that the protein is expressed in bone, the suffix ‘pontin’ is derived from ‘pons’ the Latin word for bridge that signifies osteopontin’s role as a linking protein [5]. Osteopontin is also known as bone sialoprotein I (BSPI), early T-lymphocyte activation (ETA-I), Urinary stone protein, Nephropontin and Uropontin secreted phosphoprotein 1(SPP 1) and Rickettisia resistance (Ric) 44 K BPP (bone phosphoprotein) is a human gene product. Osteopontin, an extracellular structural protein is composed of ~ 300 amino acids residues and has ~ 30 carbohydrate residues attached including ten sialic acid residues. The protein is rich in acidic residues 30 – 36 % are either aspartic or glutamic acid residues. The high concentration of Osteopontin could be responsible for a number of changes within the atherosclerotic plaque that would promote plaque instability. Many key regulators of bone formation and bone structural proteins are expressed in atherosclerotic plaques, including bone morphogenetic protein-2, matrix-carboxyglutamic acid protein and OPN [6]. OPN mediates attachment of both osteoblasts and osteoclasts to bone mineral through interaction with integrin. It appears to be the result of mineralization and is involved in the inhibition of vascular calcification [7]. Chronic inflammation is a central characteristic of atherosclerosis, where oxidized lipids are considered important inflammatory stimuli. OPN is a marker of coronary artery disease activity and actively involved in plaque progression, calcification and stability [8]. Interestingly, OPN plasma levels are increased in overweight. OPN mRNA and protein are expressed in omental adipose tissue [9]. Authors observed that plasma OPN levels were increased in overweight and obese patients with the latter being further elevated in obesity associated diabetes. They demonstrated weight loss after low caloric diet, which was associated with a reduction of OPN plasma levels in obese patients. Up- regulation of OPN gene expression was demonstrated in murine obesity [10]. Obesity is associated with the development of nonalcoholic fatty liver disease. Findings suggest that in patients with severe steatosis and insulin resistance, the hepatic OPN gene expression as well as the expression of its receptor CD44 were markedly increased and related to the severity of hepatic steatosis. This progressive up-regulation of the hepatic OPN gene was significantly associated with liver injury and hepatic insulin resistance [11]. In a recent study authors demonstrated that anti-body mediated neutralization decreased obesity associated inflammation in adipose tissue and liver and reversed signal transduction related to insulin resistance and glucose homeostasis. The authors speculated that targeting OPN could provide a novel approach for the treatment of obesity related metabolic disorders [12]. Obesity is often solely attributed to lack of exercise. Exercise-induced weight loss is considered as a safe method to prevent obesity-related diseases. It was, therefore, important to explain how regular exercise modulates obesity-mediated inflammation [13]. The anti-inflammatory effects of regular exercise may be mediated via a reduction in the visceral fat mass (with a subsequent decrease in adipokines release) and the stimulation of an anti‑inflammatory environment with each exercise session [14, 15]. You JS et al (2013) reported that exercise-induced fat loss is associated with reduction of serum osteopontin concentration but was not correlated with body fat percentage in obese subjects [16]. It has been also demonstrated that OPN expression in cardiomyocytes was significantly correlated with the impaired function of the left ventricle, which was the main source of circulating OPN plasma levels [17]. Furthermore, adipokines is involved either directly or indirectly in the regulation of bone remodeling [18]. You JS et al (2013) in their study noted the change in serum leptin level induced by exercise may induce the change of bone remodeling and the change of bone metabolism may affect the serum OPN levels. In addition, caloric restriction‑induced weight loss appears to be a risk factor for rapid bone loss. However, physical activity-induced weight loss preserves bone mineral density [19]. In conclusion, serum OPN levels may be regulated by various physiological factors. Thus, the elevated expression of OPN in adipose tissues may not be correlated with serum OPN levels. Instead, other tissues or physiological factors may have a greater contribution to serum OPN levels as compared to fat mass. Thus, the correla­tion between serum OPN levels and body fat loss remains to be elucidated. The study of OPN as a main biomarker, may provide changes in lipid metabolism in exercise-induced weight loss in obese subjects. We encourage exercise immunology and physiology researchers to examine the theoretical constructs present here and test the hypothesis put forward.