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Apply It!: • Training programs that combine aerobic exercise and resistance exercise have more profound health benefits than either modality alone. • Hybrid training programs, such as circuit weight training, combine aerobic and resistance exercise in time-efficient sessions. • Peripheral heart action training is a simple application of circuit weight training that may improve aerobic fitness, body composition, blood pressure, heart rate variability, and muscular strength. [ABSTRACT FROM AUTHOR]

Realzola, RA, Mang, ZA, Millender, DJ, Beam, JR, Bellovary, BN, Wells, AD, Houck, JM, and Kravitz, L. Metabolic profile of reciprocal supersets in young, recreationally active females and males. J Strength Cond Res 36(10): 2709–2716, 2022—Reciprocal supersets (RSSs) are a time-efficient style of resistance exercise (RE) that consist of performing 2 consecutive exercises with opposing muscle groups while limiting rest times between them. Previous research in men indicates a RSS has an increased physiological response when compared with traditional RE (TRAD). No between-sex comparison of metabolic data for RSSs exists. The purpose of this study was to create a metabolic profile for RSSs in men and women. Eighteen resistance-trained individuals underwent 2 bouts of volume-load equated RE: RSS and TRAD. Reciprocal superset exercises were split into 3 clusters: (a) hexagonal bar deadlift superset with leg press, (b) chest press superset with seated row, and (c) overhead dumbbell press superset with latissimus dorsi pull-downs. The TRAD protocol, doing the same exercises, emulated hypertrophy emphasis training. Oxygen uptake (V̇ o 2), heart rate (HR), blood lactate ([BLa]), rate of perceived exertion (RPE), and excess post-exercise oxygen consumption (EPOC) were measured. Aerobic and anaerobic energy expenditure were estimated using V̇ o 2 and lactate, respectively. The level of significance set for this study was p ≤ 0.05. Regardless of sex, a RSS elicited significantly greater average V̇ o 2, HR, [BLa], RPE, and anaerobic and aerobic energy expenditures, and was completed in a shorter time compared with TRAD (p ≤ 0.05). When compared with women, men had significantly greater EPOC, average [BLa], and anaerobic and aerobic energy expenditures during RSSs (p ≤ 0.05). The average [BLa] and aerobic energy expenditure of the men were also significantly greater than the women during TRAD (p ≤ 0.05). This study suggests that a RSS is a metabolically demanding RE session that may elicit increases in musculoskeletal, cardiorespiratory, and physiological adaptations while decreasing the duration of exercise. [ABSTRACT FROM AUTHOR]

This investigation examined the accuracy of the BOD POD on a group of Division I collegiate track and field female athletes (N = 30). Hydrostatic weighing (HW) was used as the gold standard method. Body density (Db) values obtained from the BOD POD ([Db.sub.BP]) were compared with those determined by HW ([Db.sub.HW]). Both Db values were converted to percent body fat (%BF) using the Siri equation for comparison. Percent body fat values obtained from the BOD POD ([BF.sub.BP]) were also compared with those obtained from dual-energy X-ray absorptiometry (DXA, [BF.sub.DXA]) and skinfold (SF, [BF.sub.SF]). The validity of the BOD POD was assessed using repeated-measures analysis of variance (ANOVA), and the relationship between the methods was examined through Pearson correlation. Average [Db.sub.BP] was 0.00890 g x [cm.sup.-3] lower (p < 0.05) than [Db.sub.HW], resulting in a significant overestimation of %BF (p < 0.05) by the BOD POD. Values for [BF.sub.DXA] and [BF.sub.BP] also differed significantly (p < 0.05). On the other hand, [BF.sub.SF] and [BF.sub.BP] were not significantly different. The correlation between percent body fat values obtained from HW ([BF.sub.HW]) and [BF.sub.BP] was good (r = 0.88, SEE = 2.30) as well as between [BF.sub.SF] and [BF.sub.BP] (r = 0.85, SEE = 2.05). Conversely, the correlation between [BF.sub.DXA] and [BF.sub.BP] was poor (r = 0.25, SEE = 5.73). The strong correlation between [BF.sub.BP] and [BF.sub.HW] presented here suggests that the BOD POD has the potential to be used as a body composition analysis tool for female athletes. The advantages of the BOD POD over HW encourage further investigation of this instrument. However, the fact that the BOD POD and SF results did not differ significantly might suggest that the SF could be used in its place until a better rate of accuracy for this instrument is established. KEY WORDS air-displacement plethysmography, body composition

The purpose of this study was to develop an accurate metabolic prediction equation for elliptical crosstrainer (ECT) exercise. Male and female (n = 40) subjects (M [+ or -] SD, age: 30 [+ or -] 7 yr.; height: 173 [+ or -] 11 cm; weight: 72.3 [+ or -] 13.8 kg; body composition: 18.3 [+ or -] 6.9%) completed two randomized testing sessions. Steady-state oxygen uptake ([VO.sub.2]) was measured, while subjects exercised on the ECT at nine separate workloads each testing session. Multiple regression analysis to predict steady-state [VO.sub.2] from ECT resistance, ECT cadence, and subjects' body mass resulted in the following model ([R.sup.2] = .783): Steady-state V[O.sub.2] = 3.5 + 0.15(Cadence) + 1.22 (Resistance) - 0.11(Weight). Both the standard error of the estimate (SEE) and total error (TE) for the prediction of steady state [VO.sub.2] under all ECT workload conditions combined were 2.8 mL/kg/min. The SEE and TE values are similar to those previously reported in the literature regarding the accuracy of metabolic equations for other exercise modalities. These findings support the use of the equation developed in the present study to predict steady-state [VO.sub.2] for ECT exercise.

The purpose of this study was to develop an equation to predict V[O.sub.2]max from a submaximal elliptical cross-trainer test. Fifty-four apparently healthy subjects (25 men and 29 women, mean [+ or -] SD age: 29.5 [+ or -] 7.1 years, height: 173.3 [+ or -] 12.6 cm, weight: 72.3 [+ or -] 7.9 kg, percent body fat: 17.3 [+ or -] 5.0%, and elliptical cross-trainer V[O.sub.2]max: 43.9 [+ or -] 7.2 ml x [kg.sup.-1] x [min.sup.-1]) participated in the study and were randomly assigned to an original sample group (n = 40) and a cross-validation group (n = 14). Each subject completed an elliptical cross-trainer submaximal (3 5-minute submaximal stages) and a V[O.sub.2]max test on the same day, with a 15-minute rest period in between. Stepwise multiple regression analyses were used to develop an equation for estimating elliptical cross-trainer V[O.sub.2]max from the data of the original sample group. The accuracy of the equation was tested by using data from the cross-validation group. Because there was no shrinkage in [R.sup.2] between the original sample group and the cross-validation group, data were combined in the final prediction equation ([R.sup.2] = 0.732, standard error of the estimate = 3.91 ml x [kg.sup.-1] x [min.sup.-1], p < 0.05): V[O.sub.2]max = 73.676 + 7.383(gender) - 0.317(weight) + 0.003957(age.cadence) - 0.006452(age heart rate at stage 2). The correlation coefficient between the predicted and measured V[O.sub.2]max values was r = 0.86. Dependent t-tests resulted in no significant differences (p > 0.05) between predicted (43.8 ml x [kg.sup.-1] x [min.sup.-1]) and measured (43.9 ml x [kg.sup.-1] x [min.sup.-1]) V[O.sub.2]max measurements. Results indicate that the protocol and equation develop ed in the current study can be used by exercise professionals to provide acceptably accurate estimates of V[O.sub.2]max in nonlaboratory-based settings. KEY WORDS. prediction, oxygen consumption, heart rate, multiple regression

The purpose of this study was to examine the accuracy of the American College of Sports Medicine (ACSM) walking equation at low walking speeds, altitude (1,550 m), and higher grades. Twenty men and women (mean [+ or -] SD, age, 28 [+ or -] 6 years; height, 171 [+ or -] 13 cm; weight, 67.8 [+ or -] 18.1 kg) completed 2 randomized testing sessions under altitude (AL) ([P.sub.1][O.sub.2] = 123.1 mm Hg [20.93%]) and sea level control (SLC) ([P.sub.1][O.sub.2] 147.3 mm Hg [25.00%]) conditions. Steady-state oxygen uptake ([Vo.sub.2]) was measured while subjects walked at 50 m*[min.sup.-1] at 8 separate grades (0, 5, 10, 15, 18, 21, 24, and 27%). Steady-state [Vo.sub.2] measurements from the last 2 minutes of each grade in AL and SLC were compared to the predicted [Vo.sub.2]. of each grade according to the ACSM walking equation. Mean [Vo.sub.2] differences between predicted and AL values ranged from -0.5 to 1.4 ml*[kg.sup.-1]*[min.sup.-1], averaged 0.1 ml*[kg.sup.-1]*[min.sup.-1] across all grades, and were significant (p < 0.051 at 0 percent grade. Mean [Vo.sub.2] differences between predicted and SLC values ranged from 0.6 to 3.0 ml*[kg.sup.-1]*[min.sup.-1], averaged 1.4 ml*[kg.sup.-1]*[min.sup.-1] across all grades, and were statistically significant (p < 0.05) at 0 and 5 percent. The standard error of the estimate (SEE) for the prediction of [Vo.sub.2] under AL and SLC were 2.2 and 2.0 ml*[kg.sup.-1]*[min.sup.-1], respectively. Total errors for the prediction of [Vo.sub.2]max under AL and SLC were 2.3 and 2.6 ml*[kg.sup.-1]*[min.sup.-1], respectively. Overall, the findings indicate that the current ACSM prediction equation for walking is appropriate for application at low speeds, moderate altitude, and higher grades. Key Words. oxygen consumption, prediction of [Vo.sub.2], sea level

Eighteen elite male power lifters performed 1-repetition maximum (1RM) and submaximal strength tests (70, 80, and 90% 1RM) to develop prediction equations for the squat (SQ), bench press (BP), and deadlift (DL) exercises. For each equation, stepwise multiple-regression prediction procedure included the maximum number of repetitions (REPS) completed at a given %1RM weight (REPWT). For SQ and BP the 70% 1RM yielded the best 1RM prediction equations: (1RM SQ [kg]) = 159.9 + (0.103 x REPS x REPWT) + (-11.552 x REPS), with a standard error of the estimate (SEE) of 5.06 kg; (1RM BP [kg]) = 90.66 + (0.085 x REPS x REPWT) + (-5.306 x REPS), with an SEE of 2.69 kg. For DL the 80% 1RM yielded the best prediction equation: (1RM DL [kg]) = 156.08 + (0.098 x REPS x REPWT) + (-12.106 x REPS), with an SEE of 4.97 kg. The athlete's years lifted (number of years of power lifting experience) was highly correlated with the 1RM strength for BP and DL (r > 0.70) but not for SQ (r < 0.70). No bodily structural dimension variable had a significant correlation with 1RM strength (r < 0.70). The results of this study indicate that 1RM SQ, BP, and DL may be predicted with an acceptable degree of accuracy in elite male high-school power lifter subjects. Key Words: prediction equations, squat, bench press, deadlift, elite

Eighteen trained volunteers (12 men and 6 women: age = 22.0 [+ or -] 2.8 years, height = 170.79 [+ or -] 7.67 cm, weight = 71.54 [+ or -] 12.63 kg) participated in 2-minute, randomized fitness boxing trials, wearing 0.34-kg punching gloves, at various tempos (60, 72, 84, 96, 108, and 120 b*[min.sup.-1]). During each trial, oxygen uptake (V[O.sub.2]), heart rate (HR), and ventilation (VE) were measured continuously. A rating of perceived exertion (RPE) was attained at the conclusion of each trial. Subjects were able to attain V[O.sub.2] values ranging from 26.83 to 29.75 ml*[kg.sup.-1]*[min.sup.-1], which correspond to 67.7-72.5% of V[O.sub.2]max. The HR responses yielded results ranging from 167.4 to 182.2 b*[min.sup.-1] or 85 to 93% of HRmax. No significant difference (p > 0.05) was seen with V[O.sub.2] between trials, although a significant difference (p < 0.05) was observed with HR, VE, and RPE. It appears that boxing speed is associated with increased VE, HR response, and perceived effort but not with V[O.sub.2]. Energy expenditure values ranged from 9.8 to 11.2 kcal*[min.sup.-1] for the boxing trials. These results suggest that fitness boxing programs compare favorably with other exercise modalities in cardiovascular response and caloric expenditure. Key Words: kickboxing, cardio-boxing, injury, oxygen uptake, heart rate, martial arts