Assessment of maximal oxygen uptake (V˙O2max) during an exercise test provides information related to overall health and is considered to be the “gold standard” for cardiorespiratory (aerobic) fitness (8,9,21). However, there are well-known limitations associated with maximal exercise testing such as expensive equipment and trained personnel, motivation of the participant to meet V˙O2max criterion, early onset of fatigue, physician availability for at-risk populations, and exercise device (4,6,8–10,13,14,21). Assessment of cardiorespiratory fitness and response to varying levels of exercise intensity is important and should be considered before the start of an exercise rehabilitation program. Submaximal exercise testing provides physical therapists, physicians, coaches, and health fitness professionals the opportunity to estimate V˙O2peak by determining the HR response to work rate (4,21). V˙O2peak can be estimated by extrapolating HR response to a given workload (4,17) or by using a prediction equation that could include variables such as HR, age, or weight (1).
Submaximal exercise tests have been developed for over ground walking, treadmill, cycle, and recumbent ergometers. The submaximal test used should be based on the needs of the participants and the functional, cardiorespiratory, or metabolic limitations that may affect test performance (13,19,21,22). As noted in a review article by Noonan et al. (21), “there is a need for standardized submaximal ergometer tests” for people with various physical impairments whether because of poor balance, obesity, or musculoskeletal and neuromuscular deficits. In recent reports, the total body recumbent steppers (TBRS) have been the exercise modality of choice for older adults (18) and are frequently used in exercise and rehabilitation settings because they accommodate a variety of physical impairments (10,12,20). The increasing interest in using a TBRS has prompted investigators to examine the reliability of the exercise device to produce accurate values for METs across various submaximal workloads (12,20) when compared with those values generated by a portable metabolic unit (20).
However, there is still a need to use a standardized submaximal exercise test on the TBRS to inform health care professionals and clinical exercise physiologists about cardiorespiratory health. In addition, the submaximal exercise test may be used to test and measure the effectiveness of exercise programs for older adults and clinical populations. Therefore, the aim of the study was to develop a metabolic equation for estimating V˙O2peak from the Young Men’s Christian Association (YMCA) (15) submaximal exercise test using the TBRS (experiment 1). We hypothesized that a five-element model calculated from the submaximal TBRS exercise test would predict (R2 = 0.80) the measured V˙O2peak. A cross-validation study with an independent sample was then conducted to determine the accuracy of the new prediction equation (experiment 2).
One hundred twelve individuals were recruited from the community to participate in this study. During the screening process, only one individual did not meet the study criteria (high cardiac risk) and was not enrolled. One person signed the consent but then requested not to participate leaving 110 individuals with low to moderate cardiac risk (4) to participate in the study. Participant demographics are presented in Table 1. Inclusion criteria included (a) men and women between 18 and 60 yr, (b) absence of physical limitations that would preclude them from participating in exercise testing, and (c) the ability to travel to two separate exercise testing sessions. Individuals were excluded if they presented with (a) high cardiac risk according to ACSM risk stratification categories (4), (b) physical limitations on the treadmill or recumbent stepper, (c) a diagnosis of cardiovascular or respiratory disease, and (d) a bone or joint problem that may be aggravated by maximal exercise testing. The procedures used in this study were approved by the Institutional Review Board at Kansas University Medical Center. Written informed consent was obtained from all individuals before study participation.
Each individual was screened for cardiovascular risk to determine eligibility into the study. Eligible participants consented to the study, and they then selected their physical activity level based on a nonexercise estimate of V˙O2peak (16). Participants were scheduled for both the maximal and the submaximal exercise testing sessions. The maximal exercise test was scheduled initially, followed by the submaximal exercise test. The submaximal exercise test was scheduled between 24 h and 5 d after maximal testing. Individuals were scheduled for both tests at similar times of the day. Participants were informed not to consume food or drink (except water) within 2–3 h of the exercise tests and avoid caffeinated products for 6 h before the exercise test. Participants were asked to avoid vigorous physical activity for 24 h before maximal testing. All participants were familiar with treadmill walking and running. However, not all participants were familiar with the TBRS, and everyone had an opportunity to use the exercise device to practice the alternating, reciprocal movement pattern and step rate. This was performed before the submaximal exercise testing day.
Maximal exercise testing.
The maximal exercise testing session was held at the University of Kansas Medical Center Research in Exercise and Cardiovascular Health Laboratory. Height, weight, HR, and blood pressure (BP) were obtained before exercise testing. A motorized treadmill was used for the maximal exercise test with a Bruce or modified Bruce protocol. Oxygen uptake was measured and analyzed through collection of expired gases using the ParvoMedics metabolic measurement system (ParvoMedics, Inc., Sandy, UT). Gas and flowmeter calibrations were performed on the metabolic cart according to the specifications of the manufacturer. The same individual (10 yr of experience) performed calibration procedures for all exercise tests. The frequency of calibration was performed each morning and afternoon that testing was conducted. Room temperature and humidity were recorded for each test.
Each participant was familiarized with the exercise equipment, testing protocol and the Borg RPE Scale. A 12-lead ECG was used to monitor HR and rhythm continuously during the maximal exercise test. BP, HR, V˙O2, and Borg’s RPE were recorded during the last 30 s of each 3-min stage. A two-way nonrebreathing valve, a headgear, a mouthpiece, and a nose clip were worn by the participants. Expired gases were collected continuously and oxygen uptake (V˙O2) and carbon dioxide (V˙CO2) production was averaged at 15-s intervals. American College of Sports Medicine guidelines (3) were used to determine test termination points. An advanced registered nurse practitioner was on call for all maximal exercise tests while the cardiology fellow was present for those individuals with moderate cardiovascular risk.
Submaximal exercise test.
Participants were fitted with a Polar HR monitor (Polar, Kempele, Finland) for continuous use during the submaximal exercise test. HR and BP were assessed before testing. Individuals were instructed to maintain a constant speed of 100 steps per minute (SPM). The YMCA protocol (Table 2) was adapted for the TBRS (NuStep, Inc., Ann Arbor, MI). Participants started the test at 30 W, and resistance was increased every 3 min according to the protocol until volitional fatigue (4) or when 85% of age-predicted HR max was achieved. Participants were not given feedback regarding HR response in the first stage and “protocol track” to minimize anticipation of performance. Ten seconds before the end of the second and third minutes of each stage, HR was recorded. If these two HR measures were within 5 bpm of each other, participants progressed to the next stage (4). If the difference was greater than 5 bpm, an additional minute was performed to ensure a steady state. On completion of the exercise test, the individual continued to step at a comfortable self-selected speed with resistance at 25 W for 2 min or until HR returned to near baseline levels.
Sample size justification.
Submaximal protocol development studies in adults have enrolled between 15 and 120 participants (7,11,12,20,23). Our initial intent was to enroll 50 participants as we proposed a five-element model. After we reached the initial enrollment goals, we then targeted our enrollment to increase the number of older adults to expand the usefulness of a predictive model into a more clinically relevant age range.
The arithmetic mean and SD were used for descriptive statistics. Independent variables selected a priori for the regression were physical characteristics (body weight, sex, and age) (4,8) and outcomes from the submaximal exercise test (HR and work rate (W)). Histograms for each variable were assessed for normal distributions, and scatterplots were examined for outliers. A stepwise multiple regression model with the five variables was calculated for V˙O2peak. The validity of the model was assessed through analysis of colinearity statistics and Q–Q plots of unstandardized residuals. Paired t-tests were used to determine differences between testing environments. All analyses were conducted using SPSS statistical software (Version 17; SPSS, Inc., Chicago, IL) with the α level <0.05.
All data were normally distributed, and no outliers were identified. No cardiac adverse event was reported during or after the graded exercise test. Participant effort was excellent with the mean RER value reported at 1.2 (5). Mean values for exercise testing variables are reported in Table 1. Because we performed the maximal and submaximal exercise tests in two different rooms, we recorded temperature and humidity. Although the temperature and humidity were controlled in each room, there were statistically significant differences. The temperature of the exercise testing laboratory was 21.4°C ± 2.3°C, and the exercise room for submaximal testing was 21.9°C ± 1.5°C, P = 0.002. Humidity in the exercise testing laboratory was 44.3% ± 7.5%, whereas the exercise room was 42.0% ± 5.8%, P < 0.001.
The beginning stage of the YMCA protocol was modified to begin at 30 W rather than the 25 W because our pilot work (data not reported) indicated that the TBRS had difficulty keeping the 25-W work rate constant at 100 SPM. Rather than lower the step rate to 80 SPM, the protocol was started at 30 W.
There were no findings of multicollinearity with the variance inflation factor scores ranging from 1.1 to 2.8, suggesting that the variance of the predictor variables were not redundant. The Q–Q plot revealed that residual error was normally distributed. Using a stepwise regression, we found that V˙O2peak can be predicted using a five-element model including age, weight, sex, wattsend_submax, and HRend_submax (F5,69 = 70.31, P < 0.001). This model resulted in an adjusted R2 = 0.834, SEE = 4.09 mL·kg−1·min−1 (Table 3), and total error = 4.11 mL·kg−1·min−1. The contribution that each predictor variable made to predicting V˙O2peak is listed in Table 4. The predicted V˙O2peak values were strongly correlated to the actual values (Fig. 1).
Prediction equation was derived from the linear regression:
V˙O2peak (mL·kg−1·min−1) = 125.707 + (−0.476) (age) + (7.686) (sex [0 = female; 1 = male]) + (−0.451) (weight) + (0.179) (wattsend_submax) + (−0.415) (HRend_submax)
For the cross-validation study, we determined that using a regression model with five predictors and a small value for shrinkage (0.075), an additional 40 participants would be needed (2). Participants’ demographics and exercise testing results for experiment 2 are listed in Table 5. Testing was conducted during a 4-wk period after the initial prediction model was developed. Again, we monitored temperature and humidity in both testing rooms. The temperature of the exercise testing laboratory was 23.3°C ± 0.7°C, and the exercise room for submaximal testing was 22.9°C ± 0.5°C, P = 0.01. Humidity in the exercise testing laboratory was 34.2% ± 1.8%, whereas the exercise room was 37.4% ± 1.7%, P < 0.001. Values were entered into the V˙O2peak prediction model created in experiment 1. The coefficient of determination between the predicted and actual V˙O2peak values in experiment 2 was calculated. We then figured the amount of shrinkage (difference) between this coefficient of determination (R2 = 0.802) and the value (R2 = 0.846) from experiment 1. The cross-validation revealed shrinkage less than 0.075, confirming that the model was successful in predicting V˙O2peak in a new group of individuals.
This study sought to examine whether a metabolic equation for estimating V˙O2peak could be calculated from the YMCA submaximal exercise test using the TBRS. Our findings suggest that the YMCA submaximal exercise test using the TBRS can predict V˙O2peak in a group of heterogeneous individuals with low to moderate risk for cardiovascular disease.
Submaximal exercise testing can be used as a method for predicting peak exercise capacity and in the development of exercise prescription. Submaximal testing may be optimal in certain venues such as fitness centers, rehabilitation clinics, and assisted living facilities (20,21) where maximal testing is not feasible. Previous reports have stated that the TBRS is commonly used in a wide variety of clinical populations (10,20) in many different exercise/rehabilitation settings (12). Further, the TBRS was preferentially selected by older adults as the exercise modality for their exercise program (18). For these reasons, developing submaximal exercise tests using the TBRS will provide information to health care and fitness professionals regarding baseline fitness and the effectiveness of the exercise intervention.
Mendelsohn et al. (20) used the YMCA submaximal exercise protocol with a group of older adults to evaluate whether the METs generated by the TBRS were similar to the data collected from a portable metabolic unit. Their findings demonstrated that data from the TBRS and metabolic unit were strongly correlated and not significantly different. The authors also examined reliability of the METS generated across workloads on different days with the same sample. The intraclass coefficient ranged between 0.87 and 0.91 for the test–retest reliability. Dalleck et al. (12) recently developed an equation to estimate steady-state oxygen uptake during submaximal exercise on the TBRS. The sample consisted of 20 men and 20 women ranging in age from 53 to 76 yr. Their results demonstrated an SEE and total error similar to that of other submaximal exercise tests. Further, in our previous work, we report that a maximal exercise testing protocol using the TBRS provided valid and reliable data in healthy adults (9). The results from the present study suggest the metabolic equation is valid for predicting V˙O2peak and support the use of the TBRS for submaximal exercise testing using the YMCA protocol. Although data are limited, the TBRS as an exercise modality is consistent and reliable regarding the information generated.
To our knowledge, the current study is the first to use the YMCA protocol to determine whether it is useful for prediction of V˙O2peak with the TBRS. We are also the first to study exercise testing using the NuStep T5xr. We chose to use this model for the submaximal exercise testing protocol for several reasons. First, this model has the availability of a menu option to display a constant power output. This is important during submaximal exercise testing because there is a linear relationship between work and HR. Maintaining constant power throughout the testing allowed the participants to reach a steady-state HR (within 5 bpm) (4) at the second and third minutes of each stage of the YMCA protocol. We found that the previous model of the TBRS (TRS4000) is less likely to keep the workload constant if the step rate was not consistently maintained. If the step rate changed, there was a concomitant change in the watts, which affects power output. With the T5xr in the constant power mode, we found that individuals at 100 SPM could vary approximately ±5 SPM, and the constant power could be maintained. Second, this exercise modality is preferential for older adults (18) and can accommodate a variety of physical impairments and those deconditioned by chronic disease and disability (10,12,20). Using the submaximal exercise protocol and the TBRS would allow health care providers and clinical exercise specialists to assess cardiorespiratory fitness and prescribe exercise in individuals who would benefit most from physical activity.
Our current work is different from the few studies available using the TBRS in that we tested this submaximal exercise testing protocol in a range of ages (20–60 yr) to predict V˙O2peak. These individuals were recruited from the community, university students, faculty and staff, and local gyms. We had a select group of individuals from all ages interested in exercising to exhaustion, and this may have biased our final prediction model. However, the metabolic equation derived from the regression final model is similar to those in the literature (4,12) and has a low SEE (<5 mL·kg−1·min−1) (1). We found that physical characteristics, weight, and sex along with age and performance measures such as HR and work rate were important variables in predicting V˙O2peak. As demonstrated by the cross-validation study, the final model retained accurate estimates of V˙O2peak. Statistically significant differences were found in temperature and humidity between the two testing rooms and may have influenced testing performance. However, we believe that these actual differences had minimal impact on performance.
In conclusion, these findings suggest that the YMCA submaximal exercise protocol can be successfully administered on the TBRS. The metabolic equation developed from this prediction model is useful in predicting V˙O2peak in individuals with low to moderate cardiovascular risk profiles according to ACSM standards. The YMCA submaximal protocol used in conjunction with the TBRS was easy to administer and did not require equipment other than the TBRS and HR monitor. Further studies are needed to determine whether this metabolic equation is appropriate to use in healthy adults >60 yr and clinical populations.
S.A.B. is supported in part by K01HD067318 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development and in part by Frontiers: The Heartland Institute for Clinical and Translational Research (University of Kansas Medical Center’s CTSA; UL1RR033179). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Eunice Kennedy Shriver National Institute of Child Health & Human Development or the National Institutes of Health. The KU Alzheimer’s Disease Center Clinical Core Participant Registry assisted in recruitment of healthy older adults (P30 AG035982). The Research in Exercise and Cardiovascular Health Laboratory space is supported by the Georgia Holland Endowment Fund.
The authors thank Kelsey Brucks, Abby Ashenden, and Anna Mattlage for their assistance with exercise testing, data collection and entry. The authors also thank the participants for their time and effort on the study.
The authors declare no conflict of interest related to this study.
The results of the present study do not constitute endorsement by the American College of Sports Medicine.
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