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Fitness-fatness index (FFI) is used to identify those at high risk of developing type 2 diabetes and cardiovascular events. It is measured as the ratio between an individual's cardiorespiratory fitness (CRF) and waist-to-height ratio. Studies suggest that CRF and waist-to-height ratio are modifiable and can be improved by exercise. However, there is limited evidence surrounding a personalized approach to exercise prescription. This study investigated the impact of a 12-week personalized exercise program on FFI among sedentary individuals. It was hypothesized that the intervention would be effective in improving FFI in this cohort. One hundred and forty-two participants were randomized into two groups: i) personalised community-based intervention (n = 70); or ii) control (n = 72). Both groups underwent baseline anthropometric testing and a submaximal 'talk-test' to determine individual exercise intensities and baseline FFI. During the intervention, the control group underwent normal activities, whilst the treatment group received a 12-week personalised exercise program based on the American Council on Exercise (ACE) Integrated Fitness Training (IFT) guidelines. After 12-weeks, the treatment group demonstrated a significant increase in FFI (+13%), whilst the control group (-2%) showed a slight decrease (between-group difference, p = < 0.001). Both CRF (+12%) and waist-to-height (-2%) also showed significant favourable changes in the treatment group, with no change in the control group (between group difference, p = 0.01). These findings indicate that a personalised approach to exercise prescription using the ACE IFT guidelines are beneficial in reducing FFI. Consequently, FFI could be implemented within standardized approaches to exercise to help reduce the risk of developing chronic conditions. [ABSTRACT FROM AUTHOR]

The purpose of this study was to assess and quantify the health outcomes associated with a moderate-intensity (50% [Vo.sub.2]R) exercise program designed to achieve the American College of Sports Medicine net caloric expenditure guideline of 1,000 kcal * [wk.sup.-1]. Fifteen apparently healthy but sedentary premenopausal women with the baseline characteristics (mean [+ or -] SD age, height, weight, body composition, and [Vo.sub.2]max: 37.4 [+ or -] 6.3 yr, 166.2 [+ or -] 6.2 cm, 72.1 [+ or -] 11.2 kg, 32.5 [+ or -] 5.8%, and 34.8 [+ or -] 5.8 mL * [kg.sup.-1] * [min.sup.-1], respectively) participated in and completed the study. Exercise training was performed 3-4 days per week for 10 weeks in a progressive manner at moderate intensity (50% [Vo.sub.2]R). There were significant (P < 0.05) improvements in [Vo.sub.2]max (+2.5 mL * [kg.sup.-1] * [min.sup.-1]), systolic (-13.7 mm Hg) and diastolic (-6.4 mm Hg) blood pressure, high-density lipoprotein cholesterol (+3.2 mg * [dL.sup.-1]), fasting blood glucose (-4.9 mg * [dL.sup.-1]), and percent body fat (-1.6%). Although the American College of Sports Medicine specifies that the energy expenditure goal should be a net caloric expenditure of 1,000 kcal * [wk.sup.-1] and classifies relative moderate intensity as 40-59% of heart rate reserve or [Vo.sub.2]R, we are unaware of any previous investigations that have examined the specific health outcomes associated with an exercise program fulfilling these requirements. Results indicate that significant health benefits will be conferred to previously sedentary, premenopausal women who engage in a moderate-intensity, 10-week exercise program designed to fulfill the net energy expenditure guideline of 1,000 kcal * [wk.sup.-1]. KEY WORDS maximal oxygen consumption ([Vo.sub.2]max), oxygen uptake reserve ([Vo.sub.2]R), exercise prescription, dose-response, intensity, cholesterol

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