Modelling the relationship between biomechanics and performance of young sprinting swimmers

The aim of this study was to compute a swimming performance confirmatory model based on biomechanical parameters. The sample included 100 young swimmers (overall: 12.3 ± 0.74 years; 49 boys: 12.5 ± 0.76 years; 51 girls: 12.2 ± 0.71 years; both genders in Tanner stages 1–2 by self-report) participating on a regular basis in regional and national-level events. The 100 m freestyle event was chosen as the performance indicator. Anthropometric (arm span), strength (throwing velocity), power output (power to overcome drag), kinematic (swimming velocity) and efficiency (propelling efficiency) parameters were measured and included in the model. The path-flow analysis procedure was used to design and compute the model. The anthropometric parameter (arm span) was excluded in the final model, increasing its goodness-of-fit. The final model included the throw velocity, power output, swimming velocity and propelling efficiency. All links were significant between the parameters included, but the throw velocity–power output. The final model was explained by 69% presenting a reasonable adjustment (model’s goodness-of-fit; x2/df = 3.89). This model shows that strength and power output parameters do play a mediator and meaningful role in the young swimmers’ performance.

Does an In-Season Detraining Period Affect the Shoulder Rotator Cuff Strength and Balance of Young Swimmers?

Aims: To compare the physical activity, sedentary activity and health-related quality of life (HRQoL) in institutionalized vs. non-institutionalized elderly, and to establish a pattern of relationship and prediction of physical and sedentary activity with physical and mental components of HRQoL. Methods: The sample consisted of 383 elderly with ≥ 75 years old (n=187 institutionalized and n=196 non-institutionalized). Were administered the International Physical Activity Questionnaire (IPAQ) and Short Form 36 Health Survey (SF-36) for evaluated the physical and sedentary activity and HRQoL. Also was used the Mini Mental State Examination (MMSE) as exclusion criteria for cognitive problems in the elderly. Results: Differences between institutionalized and non-institutionalized elderly were found in moderate-intensity activities and walking, a favour of non-institutionalized. The institutionalized elderly remain more minutes in sedentary activity. Also, were observed differences between both groups in physical component of HRQoL, a favour of non-institutionalized elderly. The mental component remained unchanged. The multivariate regression analyses showed that physical activity predicted the physical (8 to 12%) and mental (5 to 8%) components of HRQoL for institutionalized and non-institutionalized elderly. Conclusions: Non-institutionalized elderly were more physically active, spent less time in sedentary activity and showed better perception physical component of HRQoL that institutionalized elderly. An important and encouraging result of this study was that physical activity is a predictor of improved physical and mental component of HRQoL for institutionalized and non-institutionalized elderly.