The pre-season preparation aim is to improve the components of physical performance through the changes in training intensity, gradual increment in volume, variation in training frequency and optimizing the body composition. The problem in team sports is the lack of individualization, because most coaches in team sports focus their training on the group and not on improving each player’s strengths and weaknesses. The aim of this study is to identify differences in the body composition and physical performance of young ice-hockey players (15-18 years) with different pre-season training approaches (collective vs. individual). This longitudinal study monitored 13 ice-hockey players with collective training and 8 ice-hockey players with individual training during their pre-season preparation. Body composition was measured by bioimpedance analyzer BIA 101 (Akern, S.R.L.) and the Myotest PRO determined player physical performance in power, force and velocity. Performance and body composition comparisons showed gradual increase in the differences between the two studied groups during the training process. This increase escalated to significant differences in the final output test results and was especially noted in the upper limbs power and force (p=0.016; p<0.001) and lower limbs power and force (p=0.029; p=0.001) with better performance results by individual training approach. Stepwise linear regression also showed significant relationship between upper limbs power, resistance (p<0.001) and fat mass (p<0.001). The upper limbs force was significantly associated with intra-cellular (p<0.001) and extra-cellular water (p=0.026), body cell mass index (p<0.001), basal metabolic rate (p<0.001) and training approach (p<0.001), while the lower limbs power was significantly associated with total body water (p<0.001), training approach (p=0.033) and the pre-season preparation phase (p<0.001). In addition, the training approach (p<0.001), preparation phase (p<0.001), player position (p=0.012) and fat free mass (p<0.001) were significantly associated with lowers limb force. Our results indicate the importance of using an individual training approach and optimal body composition in physical performance progression.

Various changes in body composition and body fat distribution are accompaniments of biological ageing, presented mostly in the middle age and significantly notable during the menopause transition. This study aimed to examine the effect of menopausal status on body composition characteristics in 368 apparently healthy women aged 38-61 years. Bioelectrical parameters were measured with a bioimpedance monofrequency analyser (BIA 101) and bioelectric impedance vector analysis (BIVA) was used to analyse tissue electric properties. Data dealing with menopausal status and symptoms as well as life style variables were obtained by the Menopause specific questionnaire. Statistical analysis adjusted for age did not show differences either in the body composition characteristics or in the nutrition and obesity indices between pre-and post-menopausal women. Regression analyses pointed on statistically significant effect (p<0.05) of physical exercise on Xc (B=2.353), FM % (B=-1.746) and MM % (B=1.201), of hypertension on R (B=-22.381), FM % (B=4.468), MM % (B=-2.306), of smoking on Xc (B=1.835), FM % (B=-1.227), MM % (B=0.767), of muscle and joint ache on the FM % (B=1.923) and on MM % (B=-1.061). The age had impact on Xc (B=-13.468) and on the phase angle (B=-1.320).To conclude, in our study group of pre-and postmenopausal Slovak women, age, health and life style factors seem to have more important effect on the body composition characteristics than menopausal status alone.

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Objective: This study investigated the association of the Leu432Val and Asn453Ser CYP1B1 polymorphisms and selected environmental biomarkers with hypertension (HT) in Slovak midlife women. Methods: We studied 575 women. Divided according to their blood pressure status: 255 with HT and 320 without HT. All data was obtained by using standard anthropometric, genetic methods and analyzed by regression models to adjust for HT risk factors such as age, obesity, smoking, and level of education. Results: Our findings revealed that CYP1B1 Leu432Val polymorphism was associated with HT, whereas no association was found between Asn453Ser polymorphism and HT. Women with at least one Val allele had significantly higher odds of HT compared to women with the Leu/Leu genotype in the total sample (Exp(B) = 1.82, CI 1.16-2.84, P = 0.009). After dividing women by menopausal status and the presence of HT environmental risk factor, the association between CYP1B1 polymorphism and HT was observed in pre/perimenopausal women (Exp(B), 2.36; 95% CI 1.13-4.92; P = 0.02), smokers (Exp(B), 3.40; 95% CI 1.48-7.82; P = 0.004), abdominal obesity (Exp(B), 2.41; 95% CI 1.23-4.75; P = 0.01) and in women with only basic education (Exp(B), 4.20, 95% CI 1.12-15.71; P = 0.03). However, general linear models did not reveal a statistically significant interactions between CYP1B1, menopausal status, and HT risk factors and their common association with HT (P > 0.05). Conclusions: In this pilot study, we have provided novel data that supports the significant association of CYP1B1 Leu432Val gene polymorphism with HT in Slovak midlife women.

This pilot study revealed a significant association of the CYP1B1 Asn453Ser genotypes with the plasma levels of HDL-cholesterol and of apolipoprotein A1 in postmenopausal women and less unequivocal findings in premenopausal women. Because of study limitations, these results need to be examined in a larger study.