Introduction:The Timed Up and Go test (TUG) is widely used and valid in chronic patients, but rarely addressed in asymptomatic individuals. Objective: To assess the reliability, the age-related changes and the correlation between TUG and the Functional Exercise Capacity (FEC) adjusted for non-institutionalized middle-aged and elderly women. Methods: Ninety-eight women (57 ± 10 years) were selected and stratified into age groups. We have performed the tests TUG, Berg Balance Scale (BBS) and evaluation of usual gait speed (UGS). Fifty-eight participants (57 ± 10 years) also performed incremental shuttle walk test (ISWT). Results: Worse performance in TUG (p < 0,05) for participants aged ≥ 70 years for age groups 40-49 and 50-59 years. The reliability of TUG was excellent between the first and second TUG (intraclass correlation coefficient, 0.933; confidence interval of 95%, from 0.901 to 0.955) and between the second and third TUG (0.958, 0.938 to 0.972). The group of 58 participants who underwent further the ISWT, TUG correlated significantly (p <0.05) with ISWT (r = -0.72), VUM (r = -0.54) and BBS (r= 0.58). A multiple linear regression analysis selected TUG (R 2 = 0.517) and VUM (R 2 = 0.083) as determinants of FEC. Conclusion: TUG adapted
Background: The handgrip strength is a practical, valid, reliable, low-cost tool that presents strong correlations with several health conditions. However, handgrip strength may be inaccurate to prospectively predict the variability of muscular function since the decrease in muscular strength over the years varies according to a muscular group or between upper and lower limbs. Our hypothesis is that the handgrip strength cannot explain the variance of muscle function prospectively. Purpose: The aim of this study was to evaluate the cross-sectional and prospective association between handgrip strength and isokinetic muscle function of the knee and elbow in 780 asymptomatic adults. Methods: In a sample of 780 adults, we obtained handgrip strength and elbow and knee muscle function (for both flexion and extension at 60°/s and 300°/s) using, respectively, a hydraulic dynamometer and an isokinetic dynamometer. In a cross-sectional analysis, we analyzed the data obtained from baseline assessment. Then, we calculated the absolute change as a result of the variation data between the baseline and the 1-year follow-up assessment of each participant. The correlations were analyzed using Pearson or Spearman coefficients. We used multivariate models to investigate the association between handgrip strength and isokinetic muscle function. Results and Discussion: The cross-sectional correlations were significantly moderate-to-strong ( r = 0.41–0.71, p < 0.01), but became weak-to-moderate ( r = 0.26–0.34, p < 0.01) prospectively. In the cross-sectional analysis, the handgrip strength was selected as a strong predictor for isokinetic variables (∆ R2 = 0.171–0.583, p < 0.05) as expected. Although handgrip strength was also selected as a significant predictor in prospective analysis, it explained only a little variance in isokinetic muscle function of the knee (∆ R2 = 0.7–0.117, p < 0.05). Regarding the predictive models for the elbow, handgrip strength was not selected prospectively. Conclusion: The 1-year absolute change of the handgrip strength cannot explain the variance of the isokinetic muscle function. Thus, specific measures are required for assessing muscle function in epidemiological studies.
BackgroundThere are currently more than 200 million smartphones in Brazil. The potential of mobile technologies for favorable changes in health behavior such as physical activity has been previously described in the literature. Results of surveys in developed countries indicate that applications (APPs) are developed for people who are better educated, younger, and with higher incomes compared to non-users. However, the profile of users in developing countries like Brazil is not well-known. Understanding the profile of APP users might ease the development turned to physically inactive people and those at higher cardiovascular risk. Furthermore, the physiological and functional factors associated with the use of such APP are unknown.ObjectivesTo characterize the profile of APP users to monitor the physical activity level (PAL) and assess the demographic, socioeconomic, clinical, physiological, and functional characteristics associated with the use of smartphone APPs to monitor physical activity in Brazilian adults.MethodsWe assessed 176 asymptomatic men and 178 women (43 ± 12 years; 27 ± 5 kg/m2). We initially asked participants about their current use of a smartphone APP containing PAL monitoring functionality, such as exercise session logs and/or step counts. In a cross-sectional design, we investigated schooling, socioeconomic status (Critério Brasil), and classic self-reported cardiovascular risk factors. We evaluated several physiological and functional variables such as maximum O2 consumption on a treadmill (VO2 max), blood pressure, body composition (bioelectrical impedance), handgrip strength, and isokinetic muscle strength of the dominant lower limb. Participants used a triaxial accelerometer for 7 days to quantify daily physical activity. We also assessed health-related quality of life (WHOQOL BREF), perceived stress (PSS14 Scale), and the built environment (NEWS Scale). We compared continuous variables using the Student's t-test and categorical variables using the χ2 test, between APP users and non-users. After univariate analysis, we included the main variables associated with the use of APP in a multiple logistic regression model.ResultsOne hundred and two participants (28.3%), unrelated to gender, reported using a smartphone APP for physical activity at the time of assessment. Except for perceived stress and the built environment that were not associated with the use of APP, users of APP were younger and had higher education, lower cardiovascular risk, better socioeconomic status, a better quality of life, better cardiorespiratory function, better body composition, greater physical fitness and more moderate to vigorous physical activity in daily life. The results of the multiple logistic regression showed that age, hypertension, VO2 max, socioeconomic status (Critério Brasil), and quality of life (WHOQOL BREF total score) were the variables most significantly associated with the use of the APP.ConclusionsOur results indicate that smartphone APPs to monitor physical activity are developed for younger adults with better socioeconomic status, lower cardiovascular risk, higher quality of life, and greater cardiorespiratory fitness. Greater efforts are needed to develop a science-based APP for people who most need this technology, enabling greater potential to prevent undesirable health outcomes in asymptomatic adults.
There appears to be no dose-response relationship between SL and cardiopulmonary fitness in adult smokers with preserved pulmonary function, after adjusting the analysis for age and cardiovascular risk. Our results suggest that smoking cessation might be useful as the primary strategy to prevent cardiopulmonary fitness decline in smokers, regardless of smoking load. Thus, even a very low dose of tobacco use must be avoided in preventive strategies focusing on becoming people more physically active and fit.
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