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Dietary records are often biased, especially those of overweight individuals. The purpose of the study was to investigate underreporting among persons of normal weight with a very high energy intake (El).
The total energy expenditure (TEE) of 16 elite athletes (BMI 24 +/- 2 kg/m(2)) and 17 controls (BMI 23 3 kg/m2) was measured using the doubly-labeled water technique (DLW, 14d). El was estimated using 2 x 3-day dietary records. Underreporters were identified by BLACK'S cut-off (El:TEE < 0.76). 44% of athletes (El: 3584 824 kcal/d; TEE: 4621 1460 kcal/d) and 29% of controls (El: 2552 680 kcal/d; TEE: 3151 822 kcal/d) were identified as underreporters. TEE explains 52% of underreporting. In summary, a high energy intake seems to strongly predict underreporting. Prevalence and magnitude of underreporting increase with increasing energy intake.
Subcutaneous adipose tissue (SAT) measurements with ultrasound have recently been introduced to assess body fat in elite athletes. However, appropriate protocols and data on various groups of athletes are missing. We investigated intra-rater reliability of SAT measurements using ultrasound in elite canoe athletes. 25 international level canoeists (18 male, 7 female; 23 +/- 4 years; 81 +/- 11 kg; 1.83 +/- 0.09 m; 20 +/- 3 training h/wk) were measured on 2 consecutive days. SAT was assessed with B-mode ultrasound at 8 sites (ISAK): triceps, subscapular, biceps, iliac crest, supraspinal, abdominal, front thigh, medial calf, and quantified using image analysis software. Data was analyzed descriptively (mean +/- SD, [range]). Coefficient of variation (CV %), intraclass correlation coefficient (ICC, 2.1) and absolute (LoA) and ratio limits of agreement (RLoA) were calculated for day-to-day reliability. Mean sum of SAT thickness was 30.0 +/- 19.4 mm [8.0, 80.1 mm], with 3.9 +/- 1.8 mm [1.2 mm subscapular, 8.0 mm abdominal] for individual sites. CV for the sum of sites was 4.7 %, ICC 0.99, LoA 1.7 +/- 3.6 mm, RLoA 0.940 (*/divided by 1.155). Measuring SAT with ultrasound has proved to have excellent day-to-day reliability in elite canoe athletes. Recommendations for standardization of the method will further increase accuracy and reproducibility.
Background: The elderly need strength training more and more as they grow older to stay mobile for their everyday activities. The goal of training is to reduce the loss of muscle mass and the resulting loss of motor function. The dose-response relationship of training intensity to training effect has not yet been fully elucidated.
Methods: PubMed was selectively searched for articles that appeared in the past 5 years about the effects and dose-response relationship of strength training in the elderly.
Results: Strength training in the elderly (> 60 years) increases muscle strength by increasing muscle mass, and by improving the recruitment of motor units, and increasing their firing rate. Muscle mass can be increased through training at an intensity corresponding to 60% to 85% of the individual maximum voluntary strength. Improving the rate of force development requires training at a higher intensity (above 85%), in the elderly just as in younger persons. It is now recommended that healthy old people should train 3 or 4 times weekly for the best results; persons with poor performance at the outset can achieve improvement even with less frequent training. Side effects are rare.
Conclusion: Progressive strength training in the elderly is efficient, even with higher intensities, to reduce sarcopenia, and to retain motor function.
Test-retest-reliability of metabolic and cardiovascular load during isokinetic strength testing
(2012)
Tendon adaptation due to mechanical loading is controversially discussed. However, data concerning the development of tendon thickness in adolescent athletes is sparse. The purpose of this study was to examine possible differences in Achilles (AT) and patellar tendon (PT) thickness in adolescent athletes while considering age, gender and sport-specific loading. In 500 adolescent competitive athletes of 16 different sports and 40 recreational controls both ATs and PTs were sonographically measured. Subjects were divided into 2 age groups (< 13; ≥ 13 years) and 6 sport type categories (ball, combat, and water sports, combined disciplines, cycling, controls). In addition, 3 risk groups (low, moderate, high) were created according to the athlete’s risk of developing tendinopathy. AT and PT thickness did not significantly differ between age groups (AT/PT:<13: 5.4±0.7 mm/3.6±0.5 mm;≥13: 5.3±0.7 mm/3.6±0.5 mm). In both age groups males presented higher tendon thickness than females (p<0.001). AT thickness was highest in ball sports/cyclists and lowest in controls (p≤0.002). PT thickness was greatest in water sports and lowest in controls (p=0.02). High risk athletes presented slightly higher AT thickness compared to the low risk group (p=0.03). Increased AT and PT thickness in certain sport types compared to controls supports the hypothesis of structural tendon adaptation due to sport-specific loading.
The aim of this study was to acquire static and dynamic foot geometry and loading in childhood, and to establish data for age groups of a population of 1-13 year old infants and children.
A total of 10,382 children were recruited and 7788 children (48% males and 52% females) were finally included into the data analysis. For static foot geometry foot length and foot width were quantified in a standing position. Dynamic foot geometry and loading were assessed during walking on a walkway with self selected speed (Novel Emed X, 100 Hz, 4 sensors/cm(2)). Contact area (CA), peak pressure (PP), force time integral (FTI) and the arch index were calculated for the total, fore-, mid- and hindfoot.
Results show that most static and dynamic foot characteristics change continuously during growth and maturation. Static foot length and width increased with age from 13.1 +/- 0.8 cm (length) and 5.7 +/- 0.4 cm (width) in the youngest to 24.4 +/- 1.5 cm (length) and 8.9 +/- 0.6 cm (width) in the oldest. A mean walking velocity of 0.94 +/- 0.25 m/s was observed. Arch-index ranged from 0.32 +/- 0.04 [a.u.] in the one-year old to 0.21 +/- 0.13 [a.u.] in the 5-year olds and remains constant afterwards.
This study provides data for static and dynamic foot characteristics in children based on a cohort of 7788 subjects. Static and dynamic foot measures change differently during growth and maturation. Dynamic foot measurements provide additional information about the children's foot compared to static measures.
Background: Athletes may differ in their resting metabolic rate (RMR) from the general population. However, to estimate the RMR in athletes, prediction equations that have not been validated in athletes are often used. The purpose of this study was therefore to verify the applicability of commonly used RMR predictions for use in athletes. Methods: The RMR was measured by indirect calorimetry in 17 highly trained rowers and canoeists of the German national teams (BMI 24 ± 2 kg/m2, fat-free mass 69 ± 15 kg). In addition, the RMR was predicted using Cunningham (CUN) and Harris-Benedict (HB) equations. A two-way repeated measures ANOVA was calculated to test for differences between predicted and measured RMR (α = 0.05). The root mean square percentage error (RMSPE) was calculated and the Bland-Altman procedure was used to quantify the bias for each prediction. Results: Prediction equations significantly underestimated the RMR in males (p < 0.001). The RMSPE was calculated to be 18.4% (CUN) and 20.9% (HB) in the entire group. The bias was 133 kcal/24 h for CUN and 202 kcal/24 h for HB. Conclusions: Predictions significantly underestimate the RMR in male heavyweight endurance athletes but not in females. In athletes with a high fat-free mass, prediction equations might therefore not be applicable to estimate energy requirements. Instead, measurement of the resting energy expenditure or specific prediction equations might be needed for the individual heavyweight athlete.
Background: Athletes may differ in their resting metabolic rate (RMR) from the general population. However, to estimate the RMR in athletes, prediction equations that have not been validated in athletes are often used. The purpose of this study was therefore to verify the applicability of commonly used RMR predictions for use in athletes. Methods: The RMR was measured by indirect calorimetry in 17 highly trained rowers and canoeists of the German national teams (BMI 24 +/- 2 kg/m(2), fat-free mass 69 +/- 15 kg). In addition, the RMR was predicted using Cunningham (CUN) and Harris-Benedict (HB) equations. A two-way repeated measures ANOVA was calculated to test for differences between predicted and measured RMR (alpha = 0.05). The root mean square percentage error (RMSPE) was calculated and the Bland-Altman procedure was used to quantify the bias for each prediction. Results: Prediction equations significantly underestimated the RMR in males (p < 0.001). The RMSPE was calculated to be 18.4% (CUN) and 20.9% (HB) in the entire group. The bias was 133 kcal/24 h for CUN and 202 kcal/24 h for HB. Conclusions: Predictions significantly underestimate the RMR in male heavyweight endurance athletes but not in females. In athletes with a high fat-free mass, prediction equations might therefore not be applicable to estimate energy requirements. Instead, measurement of the resting energy expenditure or specific prediction equations might be needed for the individual heavyweight athlete.