The relationship between muscle strength and bone mineral content (BMC) and bone mineral density (BMD) is supposed from the assumption of the mechanical stress influence on bone tissue metabolism. However, the direct relationship is not well established in younger men, since the enhancement of force able to produce effective changes in bone health, still needs to be further studied. This study aimed to analyze the influence of muscle strength on BMC and BMD in undergraduate students. Thirty six men (24.9 ± 8.6 y/o) were evaluated for regional and whole-body composition by dual energy X-ray absorptiometry (DXA). One repetition maximum tests (1RM) were assessed on flat bench-press (BP), lat-pull down (LPD), leg-curl (LC), knee extension (KE), and leg-press 45° (LP45) exercises. Linear regression modelled the relationships of BMD and BMC to the regional body composition and 1RM values. Measurements of dispersion and error (R2adj and standard error of estimate (SEE)) were tested, setting ρ at ≤0.05. The BMD mean value for whole-body was 1.12±0.09 g/cm2 and BMC attained 2477.9 ± 379.2 g. The regional lean mass (LM) in upper-limbs (UL) (= 6.80±1.21 kg) was related to BMC and BMD for UL (R2adj = 0.74, p<0.01, SEE = 31.0 g and R2adj = 0.63, SEE = 0.08 g/cm2), and LM in lower-limbs (LL) (= 19.13±2.50 kg) related to BMC and BMD for LL (R2adj = 0.68, p<0,01, SEE = 99.3 g and R2adj = 0.50, SEE = 0.20 g/cm2). The 1RM in BP was related to BMD (R2adj = 0.51, SEE = 0.09 g/cm2), which was the strongest relationship among values of 1RM for men; but, 1RM on LPD was related to BMC (R2adj = 0.47, p<0.01, SEE = 44.6 g), and LC was related to both BMC (R2adj = 0.36, p<0.01, SEE = 142.0 g) and BMD (R2adj = 0.29, p<0.01, SEE = 0.23 g/cm2). Hence, 1RM for multi-joint exercises is relevant to BMC and BMD in young men, strengthening the relationship between force and LM, and suggesting both to parametrizes bone mineral health.

This study assessed the energy cost in swimming (C) during short and middle distances to analyze the sex-specific responses of C during supramaximal velocity and whether body composition account to the expected differences. Twenty-six swimmers (13 men and 13 women: 16.7 ± 1.9 vs. 15.5 ± 2.8 years old and 70.8 ± 10.6 vs. 55.9 ± 7.0 kg of weight) performed maximal front crawl swimming trials in 50, 100, and 200 m. The oxygen uptake (V˙O2) was analyzed along with the tests (and post-exercise) through a portable gas analyser connected to a respiratory snorkel. Blood samples were collected before and after exercise (at the 1st, 3rd, 5th, and 7th min) to determine blood lactate concentration [La–]. The lean mass of the trunk (LMTrunk), upper limb (LMUL), and lower limb (LMLL) was assessed using dual X-ray energy absorptiometry. Anaerobic energy demand was calculated from the phosphagen and glycolytic components, with the first corresponding to the fast component of the V˙O2 bi-exponential recovery phase and the second from the 2.72 ml × kg–1 equivalent for each 1.0 mmol × L–1 [La–] variation above the baseline value. The aerobic demand was obtained from the integral value of the V˙O2 vs. swimming time curve. The C was estimated by the rate between total energy releasing (in Joules) and swimming velocity. The sex effect on C for each swimming trial was verified by the two-way ANOVA (Bonferroni post hoc test) and the relationships between LMTrunk, LMUL, and LMLL to C were tested by Pearson coefficient. The C was higher for men than women in 50 (1.8 ± 0.3 vs. 1.3 ± 0.3 kJ × m–1), 100 (1.4 ± 0.1 vs. 1.0 ± 0.2 kJ × m–1), and 200 m (1.0 ± 0.2 vs. 0.8 ± 0.1 kJ × m–1) with p &lt; 0.01 for all comparisons. In addition, C differed between distances for each sex (p &lt; 0.01). The regional LMTrunk (26.5 ± 3.6 vs. 20.1 ± 2.6 kg), LMUL (6.8 ± 1.0 vs. 4.3 ± 0.8 kg), and LMLL (20.4 ± 2.6 vs. 13.6 ± 2.5 kg) for men vs. women were significantly correlated to C in 50 (R2adj = 0.73), 100 (R2adj = 0.61), and 200 m (R2adj = 0.60, p &lt; 0.01). Therefore, the increase in C with distance is higher for men than women and is determined by the lean mass in trunk and upper and lower limbs independent of the differences in body composition between sexes.

This study analyzed whether 100- and 200-m interval training (IT) in swimming differed regarding temporal, perceptual, and physiological responses. The IT was performed at maximal aerobic velocity (MAV) until exhaustion and time spent near to maximalVO2 peak oxygen uptake (⩒O2peak), total time limit (tLim), peak blood lactate [La−] peak, ⩒O2 kinetics (⩒O2K), and rate of perceived exertion (RPE) were compared between protocols. Twelve swimmers (seven males 16.1 ± 1.1 and five females 14.2 ± 1 years) completed a discontinuous incremental step test for the second ventilatory threshold (VT2), ⩒O2peak, and MAV assessment. The swimmers subsequently completed two IT protocols at MAV with 100- and 200-m bouts to determine the maximal ⩒O2 (peak-⩒O2) and time spent ≥VT2, 90, and 95% of ⩒O2peak for the entire protocols (IT100 and IT200) and during the first 800-m of each protocol (IT8x100 and IT4x200). A portable apparatus (K4b2) sampled gas exchange through a snorkel and an underwater led signal controlled the velocity. RPE was also recorded. The Peak-⩒O2 attained during IT8x100 and IT4x200 (57.3 ± 4.9 vs. 57.2 ± 4.6 ml·kg−1·min−1) were not different between protocols (p = 0.98) nor to ⩒O2peak (59.2 ± 4.2 ml·kg−1·min−1, p = 0.37). The time constant of ⩒O2K (24.9 ± 8.4 vs. 25.1 ± 6.3-s, p = 0.67) and [La−] peak (7.9 ± 3.4 and 8.7 ± 1.5 mmol·L−1, p = 0.15) also did not differ between IT100 and IT200. The time spent ≥VT2, 90, and 95%⩒O2peak were also not different between IT8x100 and IT4x200 (p = 0.93, 0.63, and 1.00, respectively). The RPE for IT8x100 was lower than that for IT4x200 (7.62 ± 2 vs. 9.5 ± 0.7, p = 0.01). Both protocols are considered suitable for aerobic power enhancement, since ⩒O2peak was attained with similar ⩒O2K and sustained with no differences in tLim. However, the fact that only the RPE differed between the IT protocols suggested that coaches should consider that nx100-m/15-s is perceived as less difficult to perform compared with nx200-m/30-s for the first 800-m when managing the best strategy to be implemented for aerobic power training.

The challenge in the search for relationships between urban space, physical mobility, and health status, is detecting indicators able to link the environment with healthy life habits. Therefore, the objective was to design an urban index for the identification of urban environment propensity for physical activity (PA) and to determine how it relates to lifestyle and anthropometric parametrization of obesity. Participants (N = 318-60.4% women and 39.6% men) were recruited from a mid-sized city with epidemiology and morbidity rates below the average for the mid-west region of Brazil. Body mass index (BMI) was measured and a questionnaire was applied to gather information about PA and life habits. The spatial urban health index (SUHI) was designed in a geographic information system using data from demographic, environmental and urban physical features. The relationship between BMI and PA was verified with multiple linear regression, controlled for SUHI levels. Regarding the BMI of the population, 69.5% were classified in the eutrophic or overweight ranges, with no effect of gender and age. The SUHI classified 63.7% of the urban area favorable to PA. The PA routine was adequate (�3 sessions with �1 h each) for~80% of the population, as well as healthy habits such as non smoking (~94%) and non alcohol abuse (~55%). The SUHI strengthens the relationships of BMI to weekly frequency (r =-0.68; t =-9.4; p<0.001) and session duration (r =-0.66; t =-2.8; p<0.001) for the whole group by improving the explanatory coefficient in~25% (R 2 Adj = 0.61 to R 2 Adj = 0.85). The SUHI indicated that the urban environment is able to promote healthy life habits by diminishing the "obesogenic" features of the city when physical structures are planned to facilitate PA, whatever the gender and age group.

Incremental exercise testing is the standard means of assessing cardiorespiratory capacity of endurance athletes. While the maximal rate of oxygen consumption is typically used as the criterion measurement in this regard, two metabolic breakpoints that reflect changes in the dynamics of lactate production/consumption as the work rate is increased are perhaps more relevant for endurance athletes from a functional standpoint. Exercise economy, which represents the rate of oxygen consumption relative to performance of submaximal work, is also an important parameter to measure for endurance-athlete assessment. Ramp incremental tests comprising a gradual but rapid increase in work rate until the limit of exercise tolerance is reached are useful for determining these parameters. This type of test is typically performed on a cycle ergometer or treadmill because there is a need for precision with respect to work-rate incrementation. However, athletes should be tested while performing the mode of exercise required for their sport. Consequently, swimmers are typically assessed during free-swimming incremental tests where such precision is difficult to achieve. We have recently suggested that stationary swimming against a load that is progressively increased (incremental tethered swimming) can serve as a "swim ergometer" by allowing sufficient precision to accommodate a gradual but rapid loading pattern that reveals the aforementioned metabolic breakpoints and exercise economy. However, the degree to which the peak rate of oxygen consumption achieved during such a protocol approximates the maximal rate that is measured during free swimming remains to be determined. In the present article, we explain how this rapidly incremented tethered-swimming protocol can be employed to assess the cardiorespiratory capacity of a swimmer. Specifically, we explain how assessment of a short-distance competitive swimmer using this protocol revealed that his rate of oxygen uptake was 30.3 and 34.8 mL•min -1•kg -1 BM at his gas-exchange threshold and respiratory compensation point, respectively.