Resistance training can alter a number of health-related and performance variables. These alterations include beneficial effects on body composition, blood pressure, and blood lipids and enhanced maximum strength, rate of force development, and power. These enhancements may translate into a better quality of life. As a result, resistance training can be used as a valuable tool in ameliorating the effects of a sedentary lifestyle, including those associated with metabolic syndrome. Nineteen subjects (10 metabolic syndrome, 9 previously sedentary nonmetabolic syndrome) underwent 8 weeks of supervised resistance training. After training, strength and V̇O2 peak increased by approximately 10% in the metabolic and nonmetabolic syndrome groups and the male and female groups. Percent body fat decreased in subjects with the metabolic syndrome and in females. Additionally, lean body mass increased in all groups (p<0.05). Eight weeks of resistance training improves several cardiovascular risk factors of metabolic syndrome.

This thesis explores the available resources and research pertaining to the process of athlete monitoring as well as how this information can be used to build an internet based athlete monitoring system. There is currently no system available that provides proper communication tools while also providing the means to track numerous variables to include strength and conditioning programs, performance testing, competition performance, injuries, therapy, pharmaceuticals, medical procedures, psychological status, and academic standing. The objective of this thesis is twofold. First, is to review the literature and determine the needs of a web based athlete monitoring system. Second, is to provide a business plan that will be used in the process of web development and raising capital. This thesis has identified the needs of a web based athlete monitoring system, a business plan for commercial use has been created, and based upon this business plan web development is currently in progress.

Background: Visual food stimuli have been shown to influence desire to eat and may influence overall energy intake. The purpose of this study was to determine the influence, if any, that time of day has on the neural response to visual food stimuli, as measured by functional magnetic resonance imaging (fMRI). Methods: Using a crossover design, 15 healthy women were scanned using fMRI while presented with low- and high-energy pictures of food, once in the morning (6:30–8:30 am) and once in the evening (5:00–7:00 pm). Diets were identical on both days of the fMRI scans and were verified using weighed food records. Pictures used were based on the work of Sweet et al. (2012). Visual analog scales were used to record subjective perception of hunger and preoccupation with food prior to each fMRI scan. Results: Nine brain regions showed significantly higher activation for high energy stimuli compared to low energy stimuli (p < 0.05). Six areas of the brain showed lower activation in the evening to both high and low energy stimuli including parts of some reward pathways (p < 0.05). Subjectively, participants reported no difference in hunger by time of day (F(1, 14) = 1.84, p = 0.19), but felt they could eat more (F = 4.83, p = 0.04) and were more preoccupied with thoughts of food (F = 5.51, p = 0.03) in the evening compared to the morning. Conclusions: High energy food stimuli tended to produce greater fMRI responses than low energy foods in specific areas of the brain, regardless of time of day. However, evening scans showed a lower response to both food categories in some areas of the brain compared to the morning. These data may have clinical implications for fMRI measurement and practical implications for sensitivity to food cues and eating behavior.

BACKGROUND: Food-related visual cues may affect eating behavior and energy intake. The purpose of this study was to determine the neural response to pictures of food and whether or not the neural responses were associated with energy intake. METHODS: Using a cross-sectional design, 60 adults participated in this study. Each participant reported to the laboratory in a fasted state, were fitted with a 128-electrode electroencephalogram (EEG) net, and were shown pictures grouped into three categories: high-calorie foods, low-calorie foods, and distractor pictures. These pictures were shown in random order. Furthermore, participants were shown these pictures in one passive condition and two active conditions (also in random order). The passive condition required participants to view pictures in a relaxed state while neural responses were recorded. The active conditions required participants to be actively engaged with the picture by pressing or withholding a specified button on a keyboard (go/no go task). The active conditions included only high- and low-calorie foods. Event Related Potentials (ERP) of interest were the N2, P300, and late positive potential (LPP). The National Cancer Institute's Automated Self-administered 24-hour Dietary Recall (ASA24) was used to assess energy and macronutrient intake. RESULTS: The N2 amplitude, when amplitude for high-calorie pictures is subtracted from the amplitude of low-calorie pictures, was significantly different for each active condition (F = 41.23; p < 0.0001). However, neural responses to picture-type for the N2, P300 and LPP were not different (p > 0.05). The difference in N2 amplitude, for the high-calorie no go condition that results from the amplitude for low and high-calorie pictures being subtracted from each other, was significantly associated with carbohydrate intake (r = -0.263) and significantly predicted carbohydrate intake (regression coefficient = -56.821; p = 0.043) but not energy, fat, or protein intake (p > 0.05). Neither the P300 nor the LPP was correlated with or predicted energy and macronutrient intake (p > 0.05). CONCLUSION: The N2 differentiates depending on the no go stimulus. The difference in N2 amplitude, for the high-calorie no go condition, may be an index of carbohydrate intake. The P300 and LPP do not appear to differentiate between pictures of high- and low-calorie foods, nor do they correlate with energy or macronutrient intake.

PURPOSE: The purpose of this study was to determine the effects of eating breakfast on energy intake, physical activity, body weight, and body fat in women who were nonhabitual breakfast eaters over a one-month period. METHODS: We tested 49 premenopausal, nonhabitual breakfast-eating women to compare the effects of eating breakfast versus not eating breakfast. Each participant was randomized to one of two conditions: breakfast or no breakfast. Breakfast eaters were required to eat within an hour and a half of awakening and had to be finished eating their breakfast meal by 8:30 A.M. Non-breakfast eaters were defined as not consuming a snack or meal (with the exception of water) until after 11:30 A.M. Participants assigned to the breakfast condition consumed at least 15% of their daily energy requirement for breakfast. Weight and body fat were assessed at the baseline and after one month of intervention. Body fat was measured by dual-energy x-ray absorptiometry (DXA). Participants completed seven 24-hour recalls to assess dietary intake during the intervention. Physical activity was measured by accelerometry for 32 consecutive days. RESULTS: On average, the participants randomized to eat breakfast consumed 266 ± 496 (F = 12.81; P = 0.0043) more calories per day over the course of the study and weighed 0.6 ± 0.81 kg (F = 7.81; p = 0.0076) more at the end of the intervention. There was no observed caloric compensation at subsequent meals and no change in self-reported hunger or satiety. There was also no physical activity compensation with the addition of breakfast. CONCLUSION: The findings of our study showed that requiring non-breakfast eaters to eat breakfast resulted in higher caloric intake and weight gain. Future research should evaluate this relationship for a longer period of time to see if adding breakfast to the diet of women who generally do not eat breakfast results in adaptive behavior change over time.

Bilateral deficit (BLD) is a phenomenon where the force generated from simultaneous bilateral limb contractions is less than the sum force generated by separate right and left limb contractions. There have been many BLD studies, but the measures of force generation have predominantly been with isometric and isokinetic contractions. There are, however, no dynamic upper body isotonic unilateral weight lifting studies on acute power output. The purpose of this study was to determine acute power output between bilateral and unilateral weight lifting under the conditions of traditional and circuit weight lifting. Seventeen male BYU rugby players (age = 21.8 ± 2.1 years; mass = 93.5 ± 12.5 kg; height = 181.9 ± 5.0 cm) participated in the study. Each subject participated in 4 randomized weight lifting testing sessions separated by at least 48 h. Each weight lifting protocol included 6 dumbbell lifts (bench press, bent over row, overhead press, bicep curls, front raise, and bent over raise) performed as explosively as possible for 5 sets of 5 repetitions at 40–50% of 1RM. GymAware [GYM] units measured power output for the right and left arms. Peak and mean power (of all lifts combined) was greatest in the unilateral traditional weight lifting (UTWL) group compared to all other groups (p < .0001 for each comparison). No significant differences in overall peak and mean power (all lifts combined) existed between the other 3 groups. UTWL peak and mean power outputs were significantly highest for all lifts. UTWL and bilateral traditional weight lifting (BTWL) generated the second or third highest peak power outputs for all lifts, but they were not statistically different from each other except for the bent over raise. Bilateral circuit weight lifting (BCWL) generated the lowest peak power output in all lifts, but was not statistically different from the third lowest peak power output except for the bent over raise. Our study determined that dynamic upper body isotonic unilateral movements generate significantly greater power output than dynamic upper body isotonic bilateral movements using free weights. It was also concluded that traditional weight lifting protocols generated greater power output than circuit weight lifting protocols.

Purpose: To compare muscle architecture variables between sport and sex in competitive athletes, and to compare muscle architecture with performance variables in strong versus weak athletes, and good versus poor jumpers. Methods: The vastus lateralis (VL) and lateral gastrocnemius (LG) muscles of 139 collegiate athletes were collected using ultrasonography to determine muscle thickness (MT), pennation angle (PA), fascicle length (FL), and relative fascicle length (FLrel). Absolute and relative peak power, absolute and relative isometric peak force, and jump height were measured in a subset of baseball and soccer athletes. A 5x2 factorial analysis of variance (ANOVA) was used to investigate differences in group means between sex and sport for muscle architecture variables in the larger cohort. A 2x2 factorial ANOVA was used in the in the smaller cohort to investigate differences between strong and weak athletes, and good and poor jumpers. Results: Significant main effects were observed for sex in VL muscle thickness (MT), VL pennation angle (PA), LG MT, and LG fascicle length (FL). Significant main effects were observed for sport in VL MT, VL FL, VL relative fascicle length (FLrel) and LG MT. Significant interaction effects were observed for LG PA and LG FLrel. Muscle architecture profiles were significantly different between strong and weak, and good and poor jumpers in baseball, but not soccer athletes. Soccer athletes had greater PA but smaller FL than baseball athletes. Conclusions: Muscle architecture may play a role in sport selection, undergoes directed adaptation to sport specific training demands, and may differentiate between high and low performers in more anaerobic athletes. Males had greater muscle thickness than females. Patterns of PA and FL values between sport and sex differed between VL and LG. More aerobic athletes such as soccer athletes may have greater VL PA and smaller VL FL than more anaerobic athletes such as baseball athletes.

In the sport of track and field, sprinting and distance running represent two major categories of athletes. Sprinting is associated with power and speed, whereas distance running focuses on the economy of movement. With distance running there are elements of sprint technique that overlap. With distance events, there comes a time near the end of the race where economy gives way to speed. If the distance runners knew how to alter their technique in a way to become more sprint-like, this process could possibly be more successful. PURPOSE: This study compared the differences in technique between sprinters and distance runners while running at equal and maximal speeds. METHODS: Subjects for the study consisted of 10 Division I collegiate distance runners, 10 Division I collegiate sprinters, and 10 healthy non-runners. The subjects performed two tests, with each consisting of a 60 meter run completed on the track. Test 1 was run at a pace of 5.81 m/s (4:37 min/mile), while Test 2 was completed at maximal speed. Video footage of each trial was collected at 180 Hz, monitoring hip, knee, thigh, and shank positions, as well as stride length, and contact time. RESULTS: Significant differences (p < .05) between the sprint and distance groups at maximal speed were found in the following areas: speed, minimum hip angle, knee extension at toe-off, stride length, contact time, and the position of the recovery knee at touchdown. Sprinters and distance runners exhibited a significantly lower minimum knee angle than those in the control group. Significant differences between the sprint and control group existed at the minimum hip angle, speed, stride length, contact time, and the position of the recovery knee at touchdown. Regarding the paced trial, the sprinters and distance runners showed significant difference concerning the minimum hip angle, center of mass at touchdown, and recovery knee at touchdown. Sprinters differed significantly from the control group in contact time, the center of mass at touchdown and the position of the recovery knee at touchdown. CONCLUSION: As distance runners attempt to sprint, the desired adaptations do not necessarily occur. The development of economical distance form is a fairly natural process that occurs with the miles of training. Sprinting, however, is a separate, learned technique that often requires specific feedback. When attempting maximal speed, distance runners may benefit by focusing on one characteristic of technique. If knee extension at toe-off could be trained to become more sprint-like, the other characteristics unique to sprinters may follow.

The purpose of this study was to determine whether or not differences exist in heart rate (HR) between jogging on the track and jogging on the treadmill at the same speed. Twenty-four college-age (19-31 years old) male (n = 12) and female (n = 12) recreational runners volunteered to participate in this study. Each participant performed a maximal graded exercise test (GXT) and four exercise sessions. During the first exercise session, participants completed a 1-mile steady-state jog on either the track or treadmill at a self-selected submaximal pace that could be maintained for 30 minutes. The following three exercise sessions were completed at the same pace as the first exercise session. Two of the exercise sessions were performed on the treadmill and two were performed on an indoor track. The order of the four sessions were counterbalanced. Participants were randomly assigned to an order of sessions. Heart rate was recorded every minute and the participants were asked to give an RPE at the end of every session. Statistical analysis revealed no significant differences in pace (mph) between the trials within the two track or two treadmill trials (p = 0.5812), in the HR response. Therefore, gender and trials were excluded from the final model, and the final model included only the treatment effect (track, treadmill). There was a significant treatment effect (F 1,94 = 39.126, p < 0.0001) indicating that significant differences in the HR responses between track and treadmill jogging at the same pace. Jogging on the treadmill elicited an average HR of 5.16 bpm (S.E. = 0.82) less than that observed while jogging on an indoor track at the same pace. We conclude that jogging on the treadmill and track at the same, self-selected speed results in HR values that differ significantly by 5 bpm. Differences in air resistance, biomechanics, and muscle activity most likely contributed to the observed differences in HR. The results of this study are applicable to various individuals who often train or exercise on the treadmill or overground. Use of a HR monitor is recommended to determine personal responses to exercise on a treadmill and overground.

Objective: To examine the influence of a 6-week training program on the electromechanical delay (EMD) and reaction time of the peroneus longus muscle. Design and Setting: The study was guided by a 2 x 2 factorial design with repeated measures on the time factor. The independent variables for this study were group (training and control) and time (pre- and post-training). Dependent variables for this study were muscle reaction time and electromechanical delay of the peroneus longus muscle. Subjects: Thirty-six healthy, physically active, college-age (21.8 ± 2.3 yr) male and female (M = 14, F = 28, height = 173.7 ± 11.2 cm, weight = 69.1 ± 18.4 kg) subjects were recruited for this study. Subjects had experienced no more than one ankle sprain to either ankle in their life, and had not sprained either ankle in the last year. Subjects were not currently experiencing any lower extremity pathology and had no history of serious injury to either lower extremity. Measurements: The EMD of the peroneus longus was determined by the onset of force contribution after a percutaneous electrical stimulation was administered, as measured by EMG and force plate data. Reaction time was measured after a perturbation during walking. Data was analyzed using two 2 X 2 X 2 ANOVAs. Group (treatment and control) and gender were between treatments factors, and time was a within treatments factor. Results: Upon initial examination, there was a trend in the EMD measurements to show an increase in EMD in the treatment group. However, this lacked statistical significance (F = 2.96, p = 0.0983). Reaction time demonstrated a trend towards a decrease in reaction time in the treatment group, but again, this lacked statistical significance (F = 2.88, p = 0.1025). Effect size for this reaction time was 1.2. Conclusions: The 6-week training program used in this study did not have a significant effect on the reaction time and electromechanical delay of the peroneus longus muscle.