The purpose of this study was to examine the influence of the energy cost of swimming, body composition, and technical parameters on swimming performance in young swimmers. Twenty-nine swimmers, 15 prepubertal (11.9 +/- 0.3 years; Tanner Stages 1-2) and 14 pubertal (14.3 +/- 1.4 years; Tanner Stages 3-4) boys participated in the study. The energy cost of swimming (Cs) and stroking parameters were assessed over maximal 400-m front-crawl swimming in a 25-m swimming pool. The backward extrapolation technique was used to evaluate peak oxygen consumption (VO2peak). A stroke index (SI; m2 . s(-1) . cycles(-1)) was calculated by multiplying the swimming speed by the stroke length. VO2peak results were compared with VO2peak test in the laboratory (bicycle, 2.86 +/- 0.74 L/min, vs. in water, 2.53 +/- 0.50 L/min; R2 = .713; p = .0001). Stepwise-regression analyses revealed that SI (R2 = .898), in-water VO2peak (R2 = .358), and arm span (R2 = .454) were the best predictors of swimming performance. The backward-extrapolation method could be used to assess VO2peak in young swimmers. SI, arm span, and VO2peak appear to be the major determinants of front-crawl swimming performance in young swimmers.

The association of body fat mass (FM) with bone mineral mass (BMC) and bone mineral density (BMD) has been attributed to a mechanical load exerted on the skeleton by FM and by the effect of different hormones. The aim of the present study was to determine whether there is a relationship between ghrelin, adiponectin, and leptin with BMC and BMD in healthy postmenopausal women (n = 88; age, 68.9 +/- 6.8 years; body mass index, 27.4 +/- 3.6 kg/m(2)). Body composition, BMC, and BMD were derived by dual-energy X-ray absorptiometry. Waist-to-hip (WHR) and waist-to-thigh (WTR) ratios were also obtained. Ghrelin was associated with total BMC (beta = -0.945; P = 0.0001), total BMD (beta = -0.959; P = 0.0001), lumbar spine BMD (beta = -0.945; P = 0.0001), and femoral neck BMD (beta = -0.957; P = 0.0001), and remained associated (P < 0.041) in different analyses that controlled for measured body composition and hormonal and insulin resistance values. However, the associations between ghrelin and measured bone mineral values were no longer significant (P > 0.149) when adjusted for body fat distribution values (WHR, WTR). Adiponectin was significantly related to total BMC (beta = -0.931; P = 0.0001), total BMD (beta = -0.940; P = 0.0001), lumbar spine BMD (beta = -0.937; P = 0.0001), and femoral neck BMD (beta = -0.940; P = 0.0001) values, and these relationships remained significant (P < 0.019) after adjusting for measured body fat, hormonal, and insulin resistance values but not when adjusted for fat-free mass (FFM; P > 0.106). In addition, significant associations of leptin with total BMC (beta = 0.912; P = 0.0001), total BMD (beta = 0.907; P = 0.0001), lumbar spine BMD (beta = 0.899; P = 0.0001), and femoral neck BMD (beta = 0.906; P = 0.0001) were found. These associations remained significant (P < 0.010) in different analyses that controlled for hormonal and insulin resistance values, but the associations between leptin and bone mineral values were no longer significant (P > 0.145) when adjusted for specific body composition values (WHR, WTR, FM, and FFM). In conclusion, it appears that the influence of plasma ghrelin, adiponectin, and leptin levels on BMC and BMD values is mediated or confounded by the specific body composition parameters in healthy postmenopausal women.

Variation in anthropometry highly determined the variance observed in impedance in children, and the girths were the best predictors of impedance. Selected skinfold thicknesses highly predicted fat mass measured by DXA for total body, trunk, arms and legs.

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The aim of this study was to investigate the possible relationships between adiponectin and leptin with blood lipids (CHOL, HDL-C, LDL-C, and TG) in physically active postmenopausal women. One hundred and thirty-four physically active practicing gymnastics (2-3 times per week) women between the ages of 51 to 85 years participated in this cross-sectional study. Body height, body mass, waist-to-hip circumference ratio (WHR), and BMI were used as anthropometrical parameters. Body composition parameters (fat%, fat mass, fat free mass) were measured by DXA. The fasting adiponectin, leptin, CHOL, HDL-C, LDL-C, and TG were measured. From the anthropometrical and body composition parameters, only WHR correlated significantly with adiponectin (r = -0.306). In addition, adiponectin correlated with TG (r = -0.277) and leptin (r = -0.381). Leptin was positively related to body mass (r = 0.261), and BMI (r = 0.274) from anthropometrical parameters and body fat% (r = 0.288) and fat mass (r = 0.298) from body composition variables. No relationships emerged between leptin and blood lipids. We found that there are some significant relationships between adiponectin, leptin and anthropometrical and body composition parameters in physically active postmenopausal females. From blood lipids, only TG correlated significantly with adiponectin.