Recent evidence suggests an innovative approach to muscle conditioning: focal knee joint cooling (FKJC) appears to improve quadriceps function, including static (isometric) strength. However, there is limited evidence on the effects of FKJC on dynamic (concentric and eccentric) strength. Thus, the purpose of the study was to examine dynamic quadriceps strength following FKJC as well as static strength. Twenty-one college-aged participants volunteered. They randomly underwent 20 min of FKJC and control condition at least 72 h apart. FKJC involves two ice bags, placed on the anterior and posterior surfaces of the knee, whereas the control condition received a plastic ice bag filled with candy corn. We assessed isometric and isokinetic (concentric and eccentric) quadriceps strength at two different velocities (60°/s and 180°/s). Participants performed three maximal voluntary contractions for each mode of muscle contraction, before and after each treatment (immediately, 20, and 40 min after). The outcome variable was maximum knee extension peak torque. FKJC did not change peak torque during any mode of muscle contraction (p > 0.05). The current findings suggest that 20 min of FKJC does not change static (isometric) or dynamic (isokinetic) strength of the quadriceps. FKJC was neither beneficial nor harmful to static or dynamic muscular strength.

Introduction: Aging is often accompanied by decreased muscle mass, strength, and physical function. Resistance exercise may mitigate this loss; however, data are lacking that compare physical function of younger and older community-dwelling adults who do or do not include resistance training in their health and fitness routine. Therefore, the purpose of this study was to determine how skeletal muscle mass, strength, and physical function differ by age and resistance training status in community-dwelling adults. Methods: For this cross-sectional study, healthy younger (23.8 ± 0.4 yr) and older (68.7 ± 1.2 yr) adults (n = 76) were categorized into four groups based on resistance training status: younger resistance trained (YRT; n = 22), younger not resistance trained (YNT; n = 16), older resistance trained (ORT; n = 17), and older not resistance trained (ONT; n = 21). Participants performed stair climb, 30-s sit-to-stand, 6-min walk, and grip strength tests and had dual energy x-ray absorptiometry scans to measure skeletal muscle mass. Results: For stair climb, YRT, YNT, and ORT were faster than ONT (P ≤ 0.05). For 30-s sit-to-stand, YRT and ORT completed more reps than ONT and YNT (P ≤ 0.05; ORT vs ONT: d = 1.468; YRT vs YNT: d = 1.767). For 6-min walk, ORT, YRT, and YNT walked farther than ONT (P ≤ 0.05; ORT vs ONT: d = 1.007), and YRT walked farther than YNT (d = 0.764). Thirty-second sit-to-stand and 6-min walk were not different between ORT and YRT, 6-min walk and stair climb were not different between ORT and YNT, and grip strength and lean leg mass were not different between ONT and ORT (P > 0.05). Conclusion: Older adults who engage in regular resistance training can maintain physical function levels similar to that of younger adults. Additionally, these data provide evidence-based support that resistance training performed by community-dwelling adults on their own based on American College of Sports Medicine guidelines translates to real-world benefits to mitigate age-related functional decline.

Introduction: Older adults are at risk for sarcopenia, which can negatively impact health-related quality of life (HRQoL). Resistance training may improve HRQoL; however, data using sarcopenia-specific HRQoL assessments are lacking. The purpose of this cross-sectional study was to determine whether HRQoL differs by age group (younger: age 20–29 yr; older: age 60–85 yr) and resistance training exercise status. Methods: Participants (n = 76) were categorized into four groups based on age and whether they met the American College of Sports Medicine guidelines for resistance training: younger resistance trained (YRT), younger not resistance trained (YNT), older resistance trained (ORT), and older not resistance trained (ONT). Participants completed the Sarcopenia and Quality of Life questionnaire (SarQoL®), which assessed total SarQoL® and seven domains: physical and mental health, locomotion, body composition, functionality, activities of daily living (ADLs), leisure activities, and fears. Results: ORT and YNT were not significantly different on total SarQoL® and all seven domains (P ≥ 0.05), despite the age difference; small to medium effect sizes indicated that ORT had higher scores on four domains compared to YNT (d = 0.21–0.66). ORT scored higher than ONT on total SarQoL® and physical and mental health (P < 0.05); these effect sizes were large (d = 0.95 and 0.88, respectively). YRT scored higher than YNT on total SarQoL®, physical and mental health, functionality, ADLs, and leisure activities (P < 0.05) with large effect sizes (d = 0.86–1.13). Conclusion: Findings suggest that resistance training may be an effective modality to attenuate age-related decline in HRQoL. Findings inform evidence-based practice for healthcare and fitness professionals working with older adults with concerns regarding feelings of weakness, loss of muscle mass, difficulty during physical effort, and feelings of frailty.

Resting metabolic rate (RMR) prediction models have traditionally focused on inclusion of several body size and composition variables to estimate RMR; however, little is known regarding the inclusion of circumference measurements for estimating RMR. Purpose: The purpose of this study was to examine the use of circumference measures and other easily obtainable measures to develop a generalizable RMR model. Methods: Subjects included 140 men and women aged 19–65 yr. RMR was measured through indirect calorimetry. Predictor variables investigated included the following: waist (WC) and hip circumference, percent body fat by air displacement plethysmography and bioelectrical impedance, body weight, height, body mass index, age, sex, race, waist-to-hip ratio, waist-to-height ratio (WHtR), and fat mass and fat-free mass calculated from percent body fat. Multiple regression analysis was used to develop a generalized model for predicting RMR, and cross-validation was used to confirm the accuracy of the model and compare to previously published models. Results: This study showed WC and WHtR to be significant predictors of RMR; however, they did not account for as much variance in RMR as other more easily obtained measures. Variables included as predictors in the final RMR model were weight (r = 0.61), sex (r = 0.43), age (r = −0.37), and race (r = 0.19). The final derived model for estimating RMR is as follows: RMR (kcal·d⁻¹) = 878.59 + (204.81 × sex, men = 1, women = 0) + (8.75 × weight) − (5.97 × age) + (72.48 × race, Caucasian = 1, non-Caucasian = 0). Conclusions: Although this study supports a contribution of WC and WHtR in the prediction of RMR, the data suggest that physicians and fitness professionals can use the final RMR model derived with routinely collected information (weight, sex, age, and race) to quickly and easily provide patients and clients with a superior estimation of RMR for immediate translation to evidence-based clinical practice.