Physical activity plays an important role for achieving healthy aging by promoting independence and increasing the quality of life. However, current guidelines for physical activity in older adults may be difficult to achieve in an older population. Indeed, there is evidence to suggest that increasing exercise intensity in older adults may be associated with greater reductions in the risk of cardiovascular disease and mortality. Therefore, the idea prescribing high-intensity exercise protocols such as high-intensity interval training and high-intensity resistance training becomes an intriguing strategy for healthy aging. Collectively, the literature review in this viewpoint will briefly focus on summarizing alternative/novel time-efficient approaches in physical activity toward healthy aging. Our goal is to hopefully open a discussion on possibly revising the current physical activity guidelines in older adults.
Guy El Hajj Boutros, José A. Morais, and Antony D. Karelis
Tiago M. Barbosa, Jorge E. Morais, Mário J. Costa, José Goncalves, Daniel A. Marinho, and António J. Silva
The aim of this article has been to classify swimmers based on kinematics, hydrodynamics, and anthropometrics. Sixty-seven young swimmers made a maximal 25 m front-crawl to measure with a speedometer the swimming velocity (v), speed-fluctuation (dv) and dv normalized to v (dv/v). Another two 25 m bouts with and without carrying a perturbation device were made to estimate active drag coefficient (CD a). Trunk transverse surface area (S) was measured with photogrammetric technique on land and in the hydrodynamic position. Cluster 1 was related to swimmers with a high speed fluctuation (ie, dv and dv/v), cluster 2 with anthropometrics (ie, S) and cluster 3 with a high hydrodynamic profile (ie, CD a). The variable that seems to discriminate better the clusters was the dv/v (F = 53.680; P < .001), followed by the dv (F = 28.506; P < .001), CD a (F = 21.025; P < .001), S (F = 6.297; P < .01) and v (F = 5.375; P = .01). Stepwise discriminant analysis extracted 2 functions: Function 1 was mainly defined by dv/v and S (74.3% of variance), whereas function 2 was mainly defined by CD a (25.7% of variance). It can be concluded that kinematics, hydrodynamics and anthropometrics are determinant domains in which to classify and characterize young swimmers’ profiles.