Resistance training volume load with and without exercise displacement

Monitoring the resistance training volume load (VL) (sets × reps × load) is essential to managing resistance training and the recovery⁻adaptation process. Eight trained weightlifters, seven of which were at national level, participated in the study. VL was measured both with (VLwD) and without (VL) the inclusion of barbell displacement, across twenty weeks of training, in order to allow for comparisons to be made of these VL calculating methods. This consisted of recording the load, repetition count, and barbell displacement for every set executed. Comparisons were made between VL and VLwD for individual blocks of training, select training weeks, and select training days. Strong, statistically significant correlations (r ≥ 0.78, < 0.001) were observed between VL and VLwD between all training periods analyzed. -tests revealed statistically significant ( ≤ 0.018) differences between VL and VLwD in four of the seven training periods analyzed. The very strong relationship between VL and VLwD suggest that a coach with time constraints and a large number of athletes can potentially spare the addition of displacement. However, differences in percent change indicate that coaches with ample time should include displacement in VL calculations, in an effort to acquire more precise workload totals

Is exercise a therapeutic tool for improvement of cardiovascular risk factors in adolescents with type 1 diabetes mellitus? A randomised controlled trial

<p>Abstract</p> <p>Background</p> <p>Type 1 diabetes mellitus (T1DM) is associated with a high risk for early atherosclerotic complications especially risk of coronary heart disease.</p> <p>Objective</p> <p>To evaluate the impact of six months exercise prgram on glycemic control, plasma lipids values, blood pressure, severity and frequency of hypoglycemia, anthropometric measurements and insulin dose in a sample of adolescents with T1DM.</p> <p>Research design and methods</p> <p>A total of 196 type 1 diabetic patients participated in the study. They were classified into three groups: Group (A) did not join the exercise program(n = 48), group (B) attended the exercise sessions once/week (n = 75), group (C) attended the exercise sessions three times/week (n = 73). Studied parameters were evaluated before and six months after exercise programe.</p> <p>Results</p> <p>Exercise improved glycemic control by reducing HbA1c values in exercise groups (P = 0.03, P = 0.01 respectively) and no change in those who were not physically active (P = 0.2). Higher levels of HbA1c were associated with higher levels of cholesterol, LDL-c, and triglycerides (P = 0.000 each). In both groups, B and C, frequent exercise improved dyslipidemia and reduced insulin requirements significantly (P = 0.00 both), as well as a reduction in BMI (P = 0.05, P = 0.00 respectively) and waist circumference(P = 0.02, P = 0.00 respectively). The frequency of hypoglycemic attacks were not statistically different between the control group and both intervention groups (4.7 ± 3.56 and 4.82 ± 4.23, P = 0.888 respectively). Reduction of blood pressure was statistically insignificant apart from the diastolic blood presure in group C (P = 0.04).</p> <p>Conclusion</p> <p>Exercise is an indispensable component in the medical treatment of patients with T1DM as it improves glycemic control and decreases cardiovascular risk factors among them.</p

The benefits of strength training on musculoskeletal system health: practical applications for interdisciplinary care

Global health organizations have provided recommendations regarding exercise for the general population. Strength training has been included in several position statements due to its multi-systemic benefits. In this narrative review, we examine the available literature, first explaining how specific mechanical loading is converted into positive cellular responses. Secondly, benefits related to specific musculoskeletal tissues are discussed, with practical applications and training programmes clearly outlined for both common musculoskeletal disorders and primary prevention strategies

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

Alterations in Adiponectin, Leptin, Resistin, Testosterone, and Cortisol across Eleven Weeks of Training among Division One Collegiate Throwers: A Preliminary Study

Cytokine and hormone concentrations can be linked to the manipulation of training variables and to subsequent alterations in performance. Subjects: Nine D-1 collegiate throwers and 4 control subjects participated in this preliminary and exploratory report. Methods: Hormone (testosterone (T) and cortisol (C)) and adipokine (adiponectin, leptin, and resistin) measurements were taken at weeks 1, 7, and 11 for the throwers and weeks 1 and 11 for the control group. The throwers participated in an 11-week periodized resistance training and throws program during the fall preparatory period. Volume load was recorded throughout the study. Results: Hormone values did not exhibit statistically significant changes across time; however, there were notable changes for C, the testosterone to cortisol ratio (T:C), and adiponectin. Conclusions: T:C was increased as volume load decreased, and adiponectin increased in concert with decreases in C and increases in the T:C, possibly suggesting a lesser degree of obesity-related inflammation and a higher degree of “fitness” and preparedness