12 research outputs found

    The Effects of Resistance Deception on Muscular Strength, Muscular Endurance, and Perceived Exertion

    Get PDF
    Resistance deception during training is a lightly researched topic and is seen as a modification that can potentially act on central control during exercise. Studies that have observed effects of deception while training have yielded mixed results. The effects of deception on strength, muscular endurance, and perceived exertion and the mechanisms of action that may elicit changes are still unclear. Therefore, the purpose of this study is to determine the effects of resistance deception on muscular strength, muscular endurance, and perceived exertion in a trained population. Eight participants finished the study and underwent four trials, one of which was a baseline trial, that consisted of one-rep max and repetitions to failure testing, with 60% of one-rep max, on bench press. Ensuing three experimental trials consisted of the bench press tests but in deceived/masked conditions. One trial was a 5% increase in weight, one trial was a 5% decrease in weight, and the third trial consisted of a weight that was equivalent to that of baseline. Repetitions, bar speed, and perceived exertion were monitored during each trial. During the deceived equivalent weight trial, participants significantly increased the number of repetitions and mean bar speed during the repetitions to failure test and experienced significantly decreased perceived exertion during the one-rep max lift. These findings indicate deception during training can acutely enhance performance outcomes. Key words: Resistance deception, muscular strength, perceived exertion, muscular enduranc

    Attempting to Acutely Manipulate Ground Contact Time Imbalances Impairs Running Economy

    Get PDF
    Running economy (RE) is a key performance determinant. Biomechanical markers have been linked to RE, including ground contact time (GCT), cadence, and vertical oscillation (VO). Recently, we showed a strong relationship between GCT imbalances and RE. Because these markers can be tracked real-time with consumer-wearable devices, runners now have access to instant feedback concerning their mechanics. PURPOSE: Determine if attempting to correct GCT imbalances real-time alters mechanics and RE. METHODS: 7 recreational runners (38 ± 15 years, 24.7 ± 2.8 kg/m2, 5 male) completed 2, 10-minute running trials (9.65 km/hr) on separate days. For both trials, subjects ran with a heart rate (HR) monitor/watch that measured GCT, GCT imbalances, cadence, and VO. For the control (CT) trial, subjects were not permitted to receive feedback from the watch. During the feedback (FB) trial, the watch was set to display GCT imbalances, and subjects were prompted every 20-30 seconds to monitor/attempt to correct any imbalances. Both trials were preceded by a dynamic warmup and 5-minute jog. For the FB trial warmup, subjects were acclimated to the watch and allowed to experiment with manipulating their GCT imbalances. VO2 was monitored continuously throughout each 10-minute trial, and average values from 6 to 9 minutes were determined for each trial. Average values for all running biomechanical variables were calculated from 0.5 minutes to 9.5 minutes. Comparisons between trials were made with a dependent sample t-test. RESULTS: The FB trial elicited a significantly higher (p = .011) working VO2 (35.5 ± 1.6 ml/kg/min) compared to the CT trial (33.4 ± 1.8 ml/kg/min). There were no other significant differences between trials for the other measured variables. Average values for each variable by trial were as follows: RER (CT: .91 ± .04; FB: .92 ± .05), HR (CT: 159 ± 26 bpm; FB: 163 ± 24 bpm), GCT % difference (CT: 1.69 ± .67%; FB: 1.70 ± 1.70%), GCT absolute difference (CT: 9 ± 3 ms; FB: 8 ± 7 ms), GCT (CT: 272 ± 26 ms; FB: 268 ± 31 ms), Cadence (CT: 165 ± 9 steps/min; FB: 167 ± 9 steps/min); VO (CT: 9.3 ± 2.0 cm; FB: 9.2 ± 1.9 cm), VO ratio (CT: 9.5 ± 1.6 cm/m; FB: 9.5 ± 1.6 cm/m). CONCLUSIONS: Acutely attempting to correct GCT imbalances did not result in improved mechanics and actually impaired RE. Altering mechanics based on real-time feedback from consumer-wearable devices may impair performance in the short term. Given that GCT imbalances have been linked to impaired RE, future research should determine how to better correct these imbalances rather than attempting to acutely manipulate them

    Relationship Between Body Composition, Body Fat Distribution, and Blood Lipids Among Law Enforcement Officers: Part 1

    Get PDF
    Law enforcement officers (LEOs) have a high-stress occupation which is prone to cardiovascular disease (CVD). In fact, data suggest that LEOs have a 1.7-fold higher CVD prevalence versus the general public, in addition to 40.5% of LEOs being classified as obese. However, research is lacking regarding the relationship between body composition, body fat distribution, and blood lipid panels as it pertains to CVD risk in LEOs. PURPOSE: To determine if body composition and fat distribution measures correlate with predictive lipid markers in LEOs. METHODS: Forty-three LEOs (age = 41.7±9.6 yrs; weight = 91.9±15.4 kg; height = 179.8±8.7 cm; VO2max: 37.0±6.16 ml/kg/min) from a local police department were evaluated. Fasting blood samples were collected to assess biomarkers of CVD risk: low-density lipoprotein (LDL), high-density lipoprotein (HDL), total cholesterol (TC), and triglycerides (TG). Dual-energy x-ray absorptiometry was used to measure body composition and body fat distribution. Bivariate Pearson correlation matrix was used to determine correlations (p\u3c0.05* and p\u3c0.01**). To further assess the relationship between body composition, fat distribution measures, and blood lipids, ordinary least square (OLS) regression analyses were used. RESULTS: Lower body weight correlated with greater HDL concentrations (r=-0.432**). Higher fat mass correlated with greater TG concentrations (r=0.338*), while greater lean mass was inversely correlated with HDL concentrations (r=-0.496**). Android and gynoid adiposity were positively correlated with greater TG (r=0.359*) and HDL (r=0.320*) concentrations, respectively. Lastly, higher visceral adipose tissue was correlated with greater TG concentrations (r=0.430**). The OLS regression analysis revealed (p\u3c0.05) 1) weight was inversely predictive of HDL, 2) Fat mass was positively predictive of TG, 3) lean mass was inversely predictive of HDL, 4) android adiposity was positively predictive of TG, 5) gynoid adiposity was positively predictive of HDL, and 6) visceral adipose tissue was positively predictive of TG. CONCLUSION: Measures of body composition seen in LEOs with increased body fat showed positive correlations with blood lipid markers (TG and HDL), which can be predictive of high CVD risk and other potential medical conditions. These data provide insight into the association of body composition and fat distribution with markers of CVD risk

    Global overview of the management of acute cholecystitis during the COVID-19 pandemic (CHOLECOVID study)

    Get PDF
    Background: This study provides a global overview of the management of patients with acute cholecystitis during the initial phase of the COVID-19 pandemic. Methods: CHOLECOVID is an international, multicentre, observational comparative study of patients admitted to hospital with acute cholecystitis during the COVID-19 pandemic. Data on management were collected for a 2-month study interval coincident with the WHO declaration of the SARS-CoV-2 pandemic and compared with an equivalent pre-pandemic time interval. Mediation analysis examined the influence of SARS-COV-2 infection on 30-day mortality. Results: This study collected data on 9783 patients with acute cholecystitis admitted to 247 hospitals across the world. The pandemic was associated with reduced availability of surgical workforce and operating facilities globally, a significant shift to worse severity of disease, and increased use of conservative management. There was a reduction (both absolute and proportionate) in the number of patients undergoing cholecystectomy from 3095 patients (56.2 per cent) pre-pandemic to 1998 patients (46.2 per cent) during the pandemic but there was no difference in 30-day all-cause mortality after cholecystectomy comparing the pre-pandemic interval with the pandemic (13 patients (0.4 per cent) pre-pandemic to 13 patients (0.6 per cent) pandemic; P = 0.355). In mediation analysis, an admission with acute cholecystitis during the pandemic was associated with a non-significant increased risk of death (OR 1.29, 95 per cent c.i. 0.93 to 1.79, P = 0.121). Conclusion: CHOLECOVID provides a unique overview of the treatment of patients with cholecystitis across the globe during the first months of the SARS-CoV-2 pandemic. The study highlights the need for system resilience in retention of elective surgical activity. Cholecystectomy was associated with a low risk of mortality and deferral of treatment results in an increase in avoidable morbidity that represents the non-COVID cost of this pandemic

    A Comparison of High-Intensity Interval Exercise and Continuous Moderate-Intensity Exercise on Postprandial Metabolism: A Pilot Analysis.

    Get PDF
    Both moderate-intensity continuous exercise (MICE) (performed for ≥ 1 hour) and high-intensity interval exercise (HIIE) (performed for ≤ 30 minutes) has been reported to reduce the magnitude of postprandial lipemia and glycemia. It is unclear if low-volume MICE and HIIE performed for a similar duration and expending similar amounts of energy would have a comparable or different effect on postprandial lipemia or glycemia. PURPOSE: Examine the effects of low-volume MICE and HIIE on postprandial glucose, insulin, and triglyceride (TG) concentration following a mixed meal (MM) ingested at 0.5 hours and 15.5 hours post-exercise. METHODS: Recreationally active men (n = 7; age = 22.2 ± 2.1 yrs; body mass = 93.7 ± 18.0 kg; body fat% = 29.2±8.1; WC = 91.3 ± 16.5) completed a 1) rest bout, 2) MICE bout, and 3) HIIE bout in a randomized order between 1500-1600 hours on the afternoon of Day1. Rest consisted of sitting quietly for 20 minutes. MICE required 20 minutes of continuous cycling at 60% maximal work rate (WRmax). HIIE consisted of performing 20 (15-second) cycling sprints (@ 130% WRmax) followed with 45 seconds of passive cycling. Thirty minutes following the completion of each trial, participants consumed a MM in the form of a milkshake providing 5.3 ± 0.7 kcal/kg BM (body mass) with a macronutrient composition of 50% carbohydrate (CHO), 15% protein, and 35% fat. Blood samples were acquired prior to each trial and at 0, 0.5, 1, and 2 hours post-MM. On the morning of Day2 (between 0730-0800 hours) following a 10-hr fast participants consumed a second MM providing 7.1 ± 0.8 kcal/kg BM. Blood samples were acquired at 0, 2, and 4 hours post-MM. Blood samples on Day1 were analyzed for glucose, insulin, and TG concentration. Blood samples on Day2 were analyzed for TG concentration. Postprandial responses were quantified via the incremental area under the curve (AUCI) using the trapezoidal method. Significant differences (pRESULTS: The average work performed over 20 minutes was similar between MICE (120.8 ± 30.8 W) and HIIE (115.6 ± 15.7 W) (p = .63, ES = .17). The energy expenditure was similar between MICE (159.1 ± 21.7 kcal) and HIIE (166.3 ± 42.4 kcal) (p = .63,ES = .33). Glucose AUCI on Day1 was reduced following HIIE (10.7 ± 14.8mg·dl-1·2hr-1) when compared to MICE (19.1 ± 14.0mg·dl-1·2hr-1) (p = .029, ES = .57). HIIE was not different from Rest (17.3 ± 25.9mg·dl-1·2hr-1) (p = .77, ES = .45). Insulin AUCI on Day1 was unchanged between trials, however HIIE did elicit the lowest AUCI (32.8 ± 31.8µIU·ml-1·2hr-1) compared to rest (51.6 ± 31.7µIU·ml-1·2hr-1) (p = .17, ES =.59) and MICE (52.4 ± 30.2µIU·ml-1·2hr-1) (p =.15, ES = .63). TG AUCI on Day1 was unchanged between trials. On Day2, TG AUCI was unchanged between trials, however both MICE (10.1 ± 11.9mg·dl-1·4hr-1; p = .51, ES = .78) and HIIE (12.8 ± 12.8mg·dl-1·4hr-1; p = .15, ES = .65) elicited moderate reductions when compared to Rest (25.9 ± 20.2mg·dl-1·4hr-1. CONCLUSION: While not significant, the results suggest that MICE and HIIE of similar volume and energy expenditure may elicit a similar effect on postprandial TG metabolism when performed the day before a mixed meal. In addition, HIIE may be advantageous over MICE when evaluating postprandial glucose and insulin metabolism when the exercise is performed shortly before a mixed meal. A larger sample size should clarify these trends as the current study included only a pilot sample of seven participants

    Evaluating ROTC Cadets Nutritional Competency, Dietary Habits, and Overall Health

    Get PDF
    Reserve Officer Training Corps (ROTC) cadets regularly have highly stressful and physically demanding training, making adequate nutritional knowledge and eating habits essential for optimal health and physical performance. However, there is limited work looking at the ROTC cadet’s nutritional knowledge, dietary patterns, and perceived health. PURPOSE: This study aimed to investigate ROTC cadets\u27 nutrition knowledge and perceived health. METHODS: Cross-sectional data were obtained from 174 ROTC cadets regarding nutritional knowledge and self-reported health via validated paper-based questionnaires, including the Perceived Barriers to Healthy Eating and a General Sports Nutrition Questionnaire. The questionnaire data were analyzed using SPSS version 29 software. Categorical data are reported as frequencies (n) and total percentages. A chi-square analysis was also used to determine independence (p\u3c0.05) between ethnic groups. RESULTS: Cadets were asked to report how healthy they had been over the last 12 months: 8 (4.6%) said very healthy, 77 (44.3%) said healthy, 54 (31.0%) said neutral, 31 (17.8%) said unhealthy, and 2 (1.1%) said very unhealthy. The majority of cadets successfully identified the following foods as “high in protein”: Chicken, 160 (91.9%); Kidney beans, 129 (74.1%); Tuna, 155 (89.0%); eggs, 156 (89.7%); and peanut butter, 143 (82.1%). As well, the majority successfully identified the following foods as “high in carbohydrates”: Pasta, 163 (93.7%); bread, 143 (82.2%); and candy, 100 (57.5%). When asked for “areas of improvement” cadets reported wanting to eat more fruits (124, 71.2%), fish (93, 53.4%), and vegetables (109, 62.6%) with 103 (59.2%) wanting to eat less sweets. Lastly, the chi-squared analysis showed no significant associations between ethnic groups (p\u3c0.05) as it pertains to nutritional knowledge, self-reported health, and willingness to improve eating behaviors. CONCLUSION: The ROTC cadets appear to have moderate knowledge of the macronutrient content of common foods and a desire to improve certain eating habits. These data may help to identify eating habits of ROTC cadets and potential areas for improvement and interventions
    corecore