We hypothesized that consumption of high-fat (HF) ground beef (24% fat) would not affect plasma concentrations of high-density lipoprotein cholesterol (HDL-C) or low-density lipoprotein (LDL-C), whereas low-fat (LF) ground beef (5% fat) would decrease HDL-C and LDL-C concentrations. In a randomized 2-period crossover, controlled feeding trial, 25 men (mean age and body mass index, 40 years and 31.2) consumed 115-g HF or LF patties, 5/week for 5 weeks with a 4-week washout. The HF treatment increased % energy from fat (p = 0.006) and saturated fat (p = 0.004) and tended (p = 0.060) to depress % energy from carbohydrates. The HF and LF treatments decreased the plasma concentrations of HDL-C (p = 0.001) and LDL-C (p = 0.011). Both ground beef treatments decreased the abundance of HDL3a and increased the abundance of HDL3 (p ≤ 0.003); the LF treatment also decreased the abundance of HDL2b and HDL2a (p ≤ 0.012). The HF and LF treatments decreased the abundance of LDL3 and LDL4 (p ≤ 0.024) and the HF treatment also decreased LDL5 (p = 0.041). Contrary to our hypothesis, the HF treatment decreased plasma HDL-C and LDL-C concentrations despite increased saturated fat intake, and both treatments decreased the abundance of smaller, denser LDL subfractions.

In the use of dual x-ray absorptiometry (DXA) scans to obtain reliable measures of body composition, athletic staff must be aware of acute factors that may alter scan estimates. Although factors such as hydration status and food intake have been shown to alter DXA results (Tinsley, MSSE 2016), it is unknown whether an acute strength and conditioning (S&C) session will alter DXA scan estimates. PURPOSE: To determine if a strength and conditioning (S&C) training session, based upon what athletes regularly engage in, will alter body composition estimates (lean mass, fat mass, and bone mineral content) of a DXA scan. METHODS: The S&C session lasted ~ 90 minutes and consisted of upper and lower body resistance exercises and interval running. Twenty-two strength-trained subjects (15 men, 7 women, age 24 ± 2 yrs, height 174.2 ± 8.5 cm, weight 83.5 ± 15.0 kg) volunteered to participate in the study. A food log was distributed during the informed consent process, which participants maintained for 24 hours prior to the DXA scans. Each subject completed two standard DXA scans on the same day, before and within 45 minutes of completing the S&C session. Participants were instructed to consume a normal, free-living breakfast prior to the first scan, and to then avoid all food intake until completing the second scan. Throughout the S&C session, subjects were encouraged to drink water ad libitum. RESULTS: No significant difference was found on any of the total body measures between pre and post DXA body composition measurements except for total mass, which was found to be lower after the S&C session (pre to post: 83.8-83.5 kg). Compartmental results showed significant differences between pre and post scans in the arms, legs, and trunk. Arm and leg % fat were found to be lower (pre to post: arm % fat 20.5-19.9, leg % fat 23.2-22.6); arm total and lean mass, and leg lean mass were found to be higher (pre to post: arm total mass 10.8-11.0 kg, arm lean mass 8.3-8.5 kg, leg lean mass 21.5-21.8 kg); and trunk lean mass was found to be lower (pre to post: 28.7-28.2 kg) after the S&C session. CONCLUSION: Based on the results of the present study, the acute physiological effects of a S&C session alter body composition measures obtained by DXA scan. Thus, athletic staff should consider the timing of DXA scans in relation to S&C sessions.

The energy expenditure of resistance exercise (RE) is an important consideration for exercise prescription and weight management, yet prediction models are lacking. Purpose This study aimed to develop regression equations to predict energy expenditure (kcal) for RE involving each major muscle group using commonly measured demographic and exercise variables as predictors. Methods Fifty-two healthy, active subjects (27 men, 25 women, age 20–58 yr, height 174.1 ± 10.5 cm, weight 188.7 ± 42.6 kg, V˙O2max 36.8 ± 9.2 mL·kg−1⋅min−1) were strength tested to estimate their one-repetition maximum 1 wk before their experimental RE bout. The experimental RE bout consisted of a warm-up set followed by 2–3 sets (2-min turnover) of 8–12 reps at 60%–70% of predicted one-repetition maximum for leg press, chest press, leg curl, lat pull, leg extension, triceps push down, and biceps curl. Kilocalories were estimated from V˙O2 measured continuously throughout the RE bout via an automated metabolic cart. Total exercise volume (TV) was calculated as sets × reps × weight lifted. Multiple linear regression (stepwise removal) was used to determine the best model (highest adjusted R 2) to predict the kilocalorie consumption of the total workout and of the individual RE lifts. Results The derived regression equation for the net kilocalorie consumption of an RE bout was as follows: total net kilocalorie = 0.874 (height, cm) − 0.596 (age, yr) − 1.016 (fat mass, kg) + 1.638 (lean mass, kg) + 2.461 (TV × 10−3) − 110.742 (R 2 = 0.773, SEE = 28.5 kcal). Significant equations were also derived for individual lifts (R 2 = 0.62 to 0.83). Conclusions Net energy expenditure for a total RE bout and for individual RE can be reasonably estimated in adult men and women using commonly measured demographic and RE variables.

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For Reserve Officers' Training Corps (ROTC) cadets, body composition is used as a predictor of fitness, qualification for enlistment, determination of load carriage, and duty fulfillment. However, the current method of measuring body composition in the United States military lacks validity and has left a gap that challenges researchers to investigate methods of measuring body composition deemed suitable for the military population. PURPOSE: To compare body composition methods, including the military's method of circumference-based measurements, to identify a suitable method for Bowling Green State University's Air Force ROTC program. METHODS: Anthropometric data (height and weight) and body composition measurements (air displacement plethysmography (ADP), bioelectrical impedance analysis (BIA), skinfolds, and circumferences) were collected on 24 participants (Male: n = 21; Female: n=3). A repeated measure analysis of variance (ANOVA) was used to compare body composition measurement data. BMI and circumference results were displayed as a percentage of compliance according to the Air Force Instruction (AFI) guidelines. ADP was used as the "gold standard" of comparison for body composition. RESULTS: A significant difference between skinfolds and BIA occurred (p=0.025). According to BMI, seven cadets fell into the non-compliant category, while one cadet was non-compliant using the military's method of circumference-based measurements. The military's circumference-based method underestimated body fat compared the "gold standard" ADP, however these differences were not statistically significant. CONCLUSION: The findings from this investigation suggest that the military's circumference-based method can appropriately provide accurate body composition results amongst Air Force ROTC cadets. It is recommended that further research be conducted to continue to collect data on body composition methods that provide accurate results and are easy to implement for Air Force ROTC cadets.