The Effects of Strength Training Combined with Vitamin C and E Supplementation on Skeletal Muscle Mass and Strength: A Systematic Review and Meta-AnalysisRead the full article
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Interaction between Age, Sex, and Mental Health Status as Precipitating Factors for Symptom Presentation in Concussed Individuals
Concussions are among the most common neurological conditions, with emergency departments and sports injury clinics seeing hundreds of patients each year. The consideration of risk factors such as age, sex, and comorbid conditions are very important when looking at individual physiological and psychological outcomes after a concussion. The purpose of this study was to look at four comorbid conditions (depression, anxiety, behavioural disorder, or learning disability) and identify any interactions with age and sex in symptom presentation after suffering a concussion. A total of 4,865 participants from the CCMI (Complete Concussion Management Inc.) dataset were used with 1,577 self-identified with a diagnosis of anxiety, depression, a behavioural disorder, or a learning disability. Fixed-factor analyses of variance were used with age and sex as fixed, grouping factors and symptom total and severity as dependent measures. For the individuals who did not have one of the 4 mental health conditions (3,288 control participants), symptom total and symptom severity increased with age (), and females showed more symptoms and a higher symptom severity than males across all ages (). A diagnosis of anxiety or depression exacerbated total symptoms and symptom severity from 25–50% above control levels in the 19 and under age groups, while depression or anxiety exacerbated total symptoms and severity by 10–15% in males more than females over 20. A diagnosis of a behavioural disorder or a learning disability exacerbated symptom severity by approximately 50% above control levels in 13–19–year-old females and in males of 30 years and older. This study highlights how the presence of a mental health condition may alter concussion symptom presentation dependent on age and sex. The identification of risk factors and how they may interact can be of great value to health care providers who manage concussion symptoms and recovery.
Acute Neuromuscular Activity in Selected Injury Prevention Exercises with App-Based versus Personal On-Site Instruction: A Randomized Cross-Sectional Study
Introduction. A significant step towards sport-related injury prevention is the introduction of easily accessible smartphone applications (apps). However, it is unknown whether this type of app-based instruction facilitates similar acute neuromuscular and biomechanical characteristics of the preventive exercises as achieved when instructed on-site by an expert. Thus, the aim was to evaluate acute neuromuscular characteristics observed during a single bout of selected lower extremity injury preventive exercises instructed by an on-screen app versus on-site individual instruction provided by a physiotherapist. Methods. In a cross-sectional study design, 47 female football and handball players were randomly assigned to receive app instruction (APP group) or on-site instruction provided by a physiotherapist (PHY group) while performing five lower extremity injury preventive exercises. The exercises performed comprised (1) one-legged balance on Airex, (2) vertical drop jump, (3) one-legged horizontal jump onto floor, (4) one-legged horizontal jump onto Airex, and (5) two-hand Kettlebell Swing. Primary outcome was hamstring (biceps femoris and semitendinosus) muscle activity. Secondary outcomes were quadriceps (vastus lateralis and medialis) muscle activity, as well as hip and knee joint angles. Muscle activity was monitored by surface electromyography (EMG) and normalized to the peak amplitude obtained during a maximal voluntary isometric contraction (MVC). Hip and knee joint angles were recorded by a 3D motion analysis system. A linear mixed model was used to evaluate the differences between experimental conditions for each outcome variable. Results. Medial hamstring (semitendinosus) muscle activity was significantly higher during one-legged jump onto Airex (17 percentage points (95% CI 7 to 27)) and Kettlebell Swing (19 percentage points (95% CI 2 to 36)) in the PHY group than the APP group. Likewise, the PHY group demonstrated 18 percentage points (95% CI 1 to 35) and 19 percentage points (95% CI 0 to 38), greater lateral quadriceps muscle (vastus lateralis) activity during one-legged jump onto floor and one-legged jump onto Airex, respectively, compared with that of the APP group. Conclusions. Complex exercises, i.e., Kettlebell Swing and one-legged jump onto Airex, are characterized by lower neuromuscular activity when using app-based instructions compared with on-site instruction provided by a physiotherapist. However, the effectiveness of app-based instruction versus on-site individual instruction in injury prevention interventions remains to be investigated in future longitudinally studies.
Applicability of Dmax Method on Heart Rate Variability to Estimate the Lactate Thresholds in Male Runners
Introduction. The purpose of this study was to evaluate the application of the Dmax method on heart rate variability (HRV) to estimate the lactate thresholds (LT), during a maximal incremental running test (MIRT). Methods. Nineteen male runners performed two MIRTs, with the initial speed at 8 km·h−1 and increments of 1 km·h−1 every 3 minutes, until exhaustion. Measures of HRV and blood lactate concentrations were obtained, and lactate (LT1 and LT2) and HRV (HRVTDMAX1 and HRVTDMAX2) thresholds were identified. ANOVA with Scheffe’s post hoc test, effect sizes (d), the bias ± 95% limits of agreement (LoA), standard error of the estimate (SEE), Pearson’s (r), and intraclass correlation coefficient (ICC) were calculated to assess validity. Results. No significant differences were observed between HRVTDMAX1 and LT1 when expressed for speed (12.1 ± 1.4 km·h−1 and 11.2 ± 2.1 km·h−1; ; d = 0.45; r = 0.46; bias ± LoA = 0.8 ± 3.7 km·h−1; SEE = 1.2 km·h−1 (95% CI, 0.9–1.9)). Significant differences were observed between HRVTDMAX2 and LT2 when expressed for speed (12.0 ± 1.2 km·h−1 and 14.1 ± 2.5 km·h−1; ; d = 1.21; r = 0.48; bias ± LoA = −1.0 ± 1.8 km·h−1; SEE = 1.1 km·h−1 (95% CI, 0.8–1.6)), respectively. Reproducibility values were found for the LT1 (ICC = 0.90; bias ± LoA = −0.7 ± 2.0 km·h−1), LT2 (ICC = 0.97; bias ± LoA = −0.1 ± 1.1 km·h−1), HRVTDMAX1 (ICC = 0.48; bias ± LoA = −0.2 ± 3.4 km·h−1), and HRVTDMAX2 (ICC = 0.30; bias ± LoA = 0.3 ± 3.5 km·h−1). Conclusions. The Dmax method applied over a HRV dataset allowed the identification of LT1 that is close to aerobic threshold, during a MIRT.
Factors Associated with Cardiorespiratory Fitness in a Swiss Working Population
Background. Good cardiorespiratory fitness (high ) has beneficial effects on morbidity and mortality. Therefore, a tool to estimate in daily clinical practice is of great value for preventing chronic diseases in healthy adults. This study aimed at exploring the cardiometabolic profile in a representative Swiss working population. Based on these insights, a regression model was derived revealing factors associated with . Methods. Cross-sectional data of 337 healthy and full-time employed adults recruited in the Basel region, Switzerland, were collected. Anthropometric measurements to compute body mass index (BMI) and waist circumference (WC) were performed. A 20-meter shuttle run test was conducted to determine individual . Heart rate (HR) was measured at rest, during maximal exertion, and two minutes after exercise. Systolic (SBP) and diastolic blood pressure (DBP) were assessed at rest and after exercise. A multiple linear regression model was built to identify a set of nonexercise predictor variables of . Results. Complete data of 303 individuals (63% male) aged 18 to 61 years (mean 33 ± 12 years) were considered for analysis. The regression model (adjusted R2 = 0.647, SE = 5.3) identified sex (β = -0.699, p < 0.001), WC (β = -0.403, p < 0.001), difference of maximal to resting HR (β = 0.234, p < 0.001), smoking (β = -0.171, p < 0.001), and age (β = -0.131, p < 0.01) as the most important factors associated with , while BMI, SBP, and DBP did not contribute to the regression model. Conclusions. This study introduced a simple model to evaluate based on nonexercise parameters as part of daily clinical routine without needing a time-consuming, cost-intense, and physically demanding direct assessment of . Knowledge about may help identifying individuals at increased cardiovascular risk and may provide the basis for health counselling and tailoring preventive measures.
Testing Bioimpedance to Estimate Body Fat Percentage across Different Hip and Waist Circumferences
Many studies have validated the use of bioimpedance analysis (BIA) to quantify body fat percentage (BF%). However, it is unknown if some model types (i.e., hand to hand, foot to foot, and hand to foot) are differing in their validity depending on hip and waist circumferences. The purpose of this study was to compare the difference in BF% between three BIA models (i.e., hand to hand, foot to foot, and hand to foot) against the Bod Pod across different hip and waist circumferences. A total of 92 people aged 19-72 years were recruited in this study. After following the pretesting procedures recommended for BIA measures, BF% was estimated using three BIA models and the Bod Pod. Hip and waist circumferences were obtained using standard procedures and tertiles were computed. The Bland-Altman was plotted and 1-sample T-test as well as correlation between the average measure and the difference between the two measures was tested. Within the entire sample, across all BIA models, the Bland-Altman analysis showed significant difference compared to 0 and a significant difference for the proportional. However, when stratified by tertiles, the two measurements were only significant for the highest tertiles of hip and waist for all BIA apparatus (all p <0.01) and the proportional bias was nonsignificant for all tertiles and across all BIA apparatus. For the highest tertile of waist and hip, the average difference was between 1.67% and 3.29% compared with the Bod Pod estimation. In conclusion, the three BIA models offer a BF% measurement agreeing with the estimation obtained with the Bod Pod with the exception of people having a greater waist or greater hip.
Gender Differences in Eating Disorder Risk among NCAA Division I Cross Country and Track Student-Athletes
Purpose. This study compared gender differences in eating disorder risk among NCAA Division I cross country and track distance running student-athletes. Methods. Six hundred thirty-eight male and female student-athletes competing at distances of 800m or greater completed the Eating Disorder Screen for Primary Care (ESP). Scores on the ESP were used as the risk of eating disorders. Results. Females screened positive at higher rates for risk of eating disorders than males on the ESP at a cutoff of 2 (sensitivity 90-100%, specificity 71%) with rates of and , respectively. Females were also screened positive at higher rates than males at a stricter cutoff of 3 (sensitivity 81%, specificity 92%), with rates of compared to , respectively. Conclusion. This study highlights that, among distance runners, both males and females are at risk of eating disorders, with females being at higher risk. It also emphasizes the need for screening for risk of eating disorders in this population.