One form of exercise training that is commonly prescribed by healthcare professionals is a walking program because of its simplicity, low cost, and relationship to functional tasks. Walking programs have been shown to lead to increases in cardiorespiratory health, gains in lower-extremity strength, and improved function (7,16). Some individuals, however, may not receive the benefits of a walking program. Those with dysfunctions that limit walking speed may not be able to safely achieve an exercise intensity that would facilitate cardiorespiratory or musculoskeletal system improvements. On the other end of the spectrum are some individuals who have an above average fitness level and who will not receive a training effect from walking because of its lower intensity. Although walking is an ideal form of exercise training for many persons, alternations to a walking program have to be made for other individuals to realize its health benefits.
Osteoporosis is a metabolic bone disease characterized by low bone mass and microarchitectural deterioration of bone tissue, leading to bone fragility and an increased fracture risk (5). Exercise is one component of a prevention and treatment plan for osteoporosis (14). It has been recommended that exercise programs designed to prevent or slow declines in bone mineral density (BMD) need to involve dynamic loading at levels greater than customarily experienced (21,22). The magnitude of forces experienced by the bone and the rate of loading are thought to have the greatest influence on maintenance of bone health (11,15,23). The ability to increase BMD through a walking program is questionable because of the low compressive forces associated with gait (6). Exercises that place higher stresses on the skeletal system (e.g., jumping, running, and weight lifting) may be more effective in maintaining bone health (20). These types of exercises may not be appropriate, however, for older adults or those in poor health because of limitations in balance, coordination, strength, and confidence.
One modification to a walking program that has the potential to address these limitations is the use of a weighted vest. A weighted vest is worn around an individual's torso; it provides a progressive overload during activity and requires little training to use. Incorporating a weighted vest into a walking program could be an ideal way to increase the exercise intensity for those unable to reach higher walking speeds and also for those who are no longer challenged by walking alone. Because of the added mass and the likely greater impact forces placed on the lumbar spine and lower extremities, a weighted vest could also be used to load the skeletal system for those with goals of increasing or preserving BMD.
In previous research studies, weighted vests have been used with walking programs, stair-climbing programs, lower-extremity strengthening exercises, high-impact jumping routines, and daily activities (4,8,9,12,19). Some studies have found improvements in BMD, strength, power, balance, endurance, and bodily pain (4,8,12,18,19). Other studies found no change in BMD, endurance, or strength through weighted vest interventions (9,18,19). Because of limitations in these studies, it is a challenge to draw conclusions about how beneficial weighted vests are during exercise.
One limitation in previous studies that have used weighted vests as a mode of exercise training has been inconsistencies in the amount of mass used in the vests. Some researchers limited the vest mass to 3% of body mass (BM), whereas in other studies, subjects are progressed to 15-20% BM over a 9-month period (9,18). Other limitations of previous studies include combining the weighted vest exercises with other forms of exercise, making examination of the impact of weighted vest exercise impossible. Information on the metabolic responses and changes in forces placed on the skeletal system while using a weighted vest during a walking program would be helpful in designing exercise programs for specific populations and would provide insight into the potential therapeutic benefits of a weighted vest exercise program.
This study examined the how oxygen consumption, relative exercise intensity, vertical ground reaction forces (VGRF), and loading rate (LR) are affected while using a weighted vest during treadmill walking. The changes in the dependent variables (oxygen consumption, relative exercise intensity, VGRF, and LR) were examined across a range of functional walking velocities using a four different weighted vest conditions (0, 10, 15, and 20% BM). It was hypothesized that as greater amounts of mass were used in a weighted vest during walking, the dependent variables would significantly increase.
A total of 10 subjects (7 women and 3 men) recruited at the University of Iowa, Iowa City, IA were included in this study (Table 1). Subjects were able to walk for at least 20 min up to a speed of 1.79 m·s−1 on a treadmill, were free of cardiovascular disease, had no gait abnormalities, and had no recent orthopedic injuries that would likely worsen by walking with a weighted vest. Subjects were required to maintain a body mass within a 0.91-kg range because weighted vest conditions were based on each subject's body mass. Because the researchers were interested in the effects of walking with a weighted vest set at 20% of the subject's body mass, and the weighted vests could only hold 18.18 kg, only subjects with a body mass of 90.91 kg or less were invited to participate in the study. The institutional review board at the University of Iowa approved this study. All subjects signed written informed consent documents before their participation in the study.
This study was a two-factor (weighted vest condition, walking speed) repeated-measures design that required subjects to complete a standardized walking test on a instrumented motorized treadmill (Kistler Instrument Co., Amherst, NY) under four different weighted vest conditions (0, 10, 15, and 20% BM). Independent variables were weighted vest condition and walking speed. Dependent variables were oxygen consumption, relative exercise intensity, VGRF, and LR. Each weighted vest condition was performed on separate days, requiring a minimum of 48 h of rest between test sessions to limit the effects of fatigue on performance. The testing order of each weighted vest condition was randomly assigned for each subject.
This study took place at the University of Iowa Hospital and Health Clinics' Physical Therapy and Orthopedic Gait Analysis Laboratory, Iowa City, IA. Subjects' mass was recorded at the beginning of each session to set the mass for the vest. The weighted vest was a commercially available vest with 38 internal pouches equally distributed throughout the vest (Netfitco, Brattleboro, VT). The vest could range from 1.5 kg (mass of vest with no weight in pouches) up to a maximum of 18.18 kg, with each pouch holding one to two 0.23-kg rubber weights. Equal weight was distributed in the front and back side of the vest. A specific pattern of loading the vest was used, with the lower pouches filled with one rubber weight first and then progressively filling the higher pouches. Once all the pouches were filled with one rubber weight, a second rubber weight was added to the pouches as needed following the same pattern. Subjects were blinded to the amount of weight in the vest. Before each test session, subjects had the opportunity to practice walking with the weighted vest to allow familiarization. The test protocol involved 2 min of standing rest on the treadmill, followed by five, 4-min walking stages at 0.89, 1.12, 1.34, 1.56, and 1.79 m·s−1 (2.0, 2.5, 3.0, 3.5, and 4.0 mph).
An online automated computerized system, Medgraphics Cardio2 metabolic cart (Medical Graphics Corp, St. Paul, MN) was used to determine oxygen consumption based on 60-s averaging of individual breath-by-breath analysis. The metabolic cart, CO2 and O2 gas analyzers, and the pneumotachograph were calibrated before each test session according to the manufacturer's specified calibration protocols. Heart rate was monitored by an electrocardiograph (ECG) radiotelemetry system that was interfaced with the Medgraphics metabolic cart. A Polar Heart Rate Monitor (Polar Electro Inc., Port Washington, NY) was used concurrently to confirm telemetry measurements because of occasion electrical interference experienced in the research laboratory during this study. Oxygen consumption values were expressed as milliliters per kilogram per minute. The heart rate data were used to determine relative exercise intensity by calculating the percentage of age-predicted maximal heart rate (%APMHR). Age-predicted maximal heart rate was expressed using the formula (exercise heart rate/age-predicted maximal heart rate) × 100. Oxygen consumption and relative exercise intensity data from the fourth minute of each stage was used for analysis.
Vertical ground reaction force measurements.
The Kistler Treadmill was fabricated by the manufacturer with two piezoelectric force plates mounted one in front of the other under the belt of the treadmill to allow the measurement of VGRF. Use of an instrumented treadmill has been shown to demonstrate high reliability and accurate measurements of VGRF (13,24). Data were collected at 150 Hz for 20-s time periods during the last 2 min of each walking stage under all WV conditions (13). Each data set was visually examined to remove any incorrectly measured force curves attributable to both feet being on one force plate at concurrent times. The first eight contacts for the right foot and the first eight contacts for the left foot at each speed were used for analysis (3). All VGRF force data were normalized to body mass. For each VGRF curve, the first peak of the VGRF curve (F1) and the second peak of the VGRF curve (F2) were identified (Fig. 1). F1 represents heel strike and the loading of the lower extremity during weight acceptance. F2 signifies the push-off phase of gait and the active transfer of force generated by the lower-extremity musculature. Loading rate was defined as the change in force over time from heel strike to impact peak force (Fig. 1). The slope of this line was calculated using data from between 20 and 80% of the upward curve and was expressed as BM·s−1. Because no difference in VGRF values were seen between lower extremities during pilot work, and researchers were interested in a global assessment of VGRF, values for the eight right and eight left lower extremities at each walking speed under each weighted vest condition were averaged for analysis.
Statistical analysis was performed using SPSS Version 12.0 for Windows (SPSS Inc., Chicago, IL). Means and standard deviations were calculated for all variables. A two-way repeated-measures ANOVA was used to test for main effects and interaction of walking speed and weighted vest condition. Because understanding the overall effects of vest mass on the dependent factors was deemed important for this study, and metabolic data typically demonstrate a curvilinear relationship across walking velocity, it was determined a priori that if interactions were present, main effects would be examined in addition to simple effects. Post hoc Tukey tests were used for all follow-up tests. Significance level was set at P < 0.05.
All subjects completed the testing protocol without complication. The relative exercise-intensity data for one subject were excluded from analysis because of contamination of results caused by electrical interference of the ECG radiotelemetry signal. Another subject's kinetic data were excluded in the analysis because of instrumentation malfunction during one of the testing sessions.
The effect of weighted vest condition and walking speed with respect to oxygen consumption data is graphically displayed in Figure 2. Under all four weighted vest conditions, a classic curvilinear relationship between walking speed and oxygen consumption was demonstrated. As the mass of the vest increased, there was an upward shift of the trend line. A significant interaction between weighted vest condition and speed (F = 9.30, P < 0.001) was found. Because of this significant interaction, the simple effects of weighted vest condition at each speed were examined (Fig. 3, Table 2). As speed increased, greater differences in oxygen consumption were present between the weighted vest conditions. For example, at 0.89 m·s−1 no difference was noted in oxygen consumption between 15 and 20% BM. When walking velocity reached 1.12 m·s−1, 15% BM was significantly different than 20% BM. Simple effects analysis also found that at no speed did a 5% increase in vest mass from 10 to 15% BM cause a change in oxygen consumption.
Because one of the main purposes of this project was to examine the overall effects of weighted vest condition on oxygen consumption, the main effect of weighted vest condition was examined despite the significant interaction. A significant main effect for weighted vest condition (F = 28.97, P < 0.001) was found. Follow-up testing on the weighted vest condition main effect for metabolic data are shown in Table 3.
The effect of weighted vest condition and speed on relative exercise intensity was similar to that seen for oxygen consumption. A significant interaction between weighted vest condition and speed (F = 4.06, P < 0.001) was present, in addition to a significant main effect for weighted vest condition (F = 4.82, P < 0.009). Figure 4 displays the effect of weighted vest condition on relative exercise intensity at each speed. Weighted vest condition had no significant effect on relative exercise intensity at a lower walking speed (0.89 m·s−1), but the effect of weighted vest condition became more pronounced at higher speeds with significant differences at 1.12, 1.34, 1.56, and 1.79 m·s−1 (Table 2). Examination of the main effects for weighted vest condition on relative exercise intensity is shown in Table 3.
Vertical ground reaction forces.
A change in both F1 and F2 was found as speed and vest mass increased. Figures 5 and 6 demonstrate the relationship between weighted vest conditions and walking speed on F1 and F2. No interaction between weighted vest condition and speed was found, whereas a significant main effect of weighted vest condition was shown for both F1 (F1 = 31.05, P < 0.001) and F2 (F = 102.56, P < 0.001). Results of follow-up testing for kinetic data are presented in Table 4.
No interaction between weighted vest condition and speed was shown for LR, whereas a significant main effect of weighted vest condition (vest weight) was demonstrated (F = 5.47, P = 0.005). Follow-up testing revealed using a weighted vest set at 15 and 20% BM led to greater LR than using a vest with no mass (Table 4).
The results of this study support the hypothesis that using a weighted vest increases the metabolic costs and the dynamic loading of the skeletal system during walking. In examining the metabolic data, a few important points can be made. First, the changes in oxygen consumption and relative exercise intensity are not linear as speed and vest mass increases. As walking velocity increased, the effect of vest mass had a greater effect on metabolic costs. Another important point is that a 5% change from 10 to 15% BM had no effect on metabolic costs, but an increase from 15 to 20% BM did cause a significant increase in oxygen consumption. These interactions between walking velocity and weighted vest condition have implications on the selection of vest mass during a walking program. For those who have a slow walking velocity, more weight may be needed to facilitate increases in metabolic costs, whereas those who walk at higher speeds will see greater increases in metabolic costs with smaller increases in vest mass. Also, as individuals tolerated greater amounts of mass in the vest, smaller adjustments will be needed to cause greater metabolic stresses.
Our study demonstrates that a weighted vest can increase the relative exercise intensity of walking to more therapeutic levels needed to facilitate cardiorespiratory exercise training adaptations. For example, at 1.56 m·s−1, our subjects' average relative exercise intensity at 0% BM was below 60%. By using a weighted vest set at 10% BM, relative exercise intensity reaches a level that is more appropriate to achieve improvements in aerobic fitness (Table 2) (2). Our data also show that, by using a weighted vest at lower speeds, exercise intensities similar to those experienced at higher speeds can be reached. The relative exercise intensity at 1.34 m·s−1 with a vest at 10% of BM is similar to the relative exercise intensity at 1.56 m·s−1 without any mass. This has practical implications for those who may not be able to walk at high velocities because of health problems, but who are seeking a way to achieve higher exercise intensities.
Based on the results shown in Table 3, the weighted vest conditions appear to have a greater influence on oxygen consumption than on relative exercise intensity. This is likely because our subjects were young and disease-free. Our subjects had a greater physiological reserve, so while the weighted vest affected their absolute energy expenditure at low vest weights and slower velocities, the added mass had little effect on relative energy expenditure. It is likely that individuals who were deconditioned would demonstrate significant changes in relative exercise intensity with smaller amounts of mass and at slower speeds than our subjects did.
The influence of a walking program on bone health is controversial. Some studies have found significant changes in BMD with a walking program, and others have not (6,10). The criticism of walking programs is that peak forces and rate of loading experienced by the skeletal system are too low to increase BMD (6). Our study shows that walking with a weighted vest caused a significant increase in VGRF and LR over walking with no weight in a vest, and that there is a significant difference between the VGRF caused by vests set at 10, 15, and 20% BM. For a person who is currently involved in a walking program, adding a weighted vest set at 10% BM would cause a significant increase in VGRF, and increasing the vest mass in 5% BM increments would further increase the VGRF. It should also be noted that levels of peak VGRF with 20% are similar to those forces experienced during jogging (1). These findings have implications for individuals who want to improve bone health, but are unable to perform high-level activities.
The fact that our study demonstrated F1, F2, and LR all increased by using a weighted vest during walking is important. This shows that the passive peak loading of the skeletal system increases during weight acceptance along with the active forces generated by muscle contractions during push-off. Not only do the peak forces experienced during walking become greater with a weighted vest, but the rate of loading is also increased. Both rate of loading and the peak forces are thought to be vital to improving bone health (11,15,23). It may be possible that this level of increased stimulus would be sufficient to lead to improvements in BMD, but this is an issue that will have to be examined in future studies.
Some other important points can be drawn by comparing the main effects caused by weighted vest condition for the metabolic data and the VGRF. Increasing the vest mass from 0 to 20% caused a 22% increase in F1, a 14% increase in F2, and a 17% increase in LR (Table 4). The metabolic costs of increasing vest mass from 0 to 20% are much less clinically significant (a 0.64-MET increase or 9% increase relative exercise intensity) (Table 3). In addition, going from 10 to 15% BM in the weighted vest caused a significant increase in F1, with no significant change in the metabolic costs. This relationship demonstrates that a person could significantly increase the mechanical stresses placed on the skeletal system without experiencing undue physiological strain. This could have great importance for those who are limited in aerobic capacity, but are looking for a method to improve bone health.
One goal of this study was to determine a threshold of mass needed to cause increases in energy expenditure and VGRF. When examining the metabolic data, trying to define a threshold value is difficult because of the interaction of weighted vest condition and speed. At lower speeds, more weight is required to facilitate increases, whereas at higher speeds, less weight is needed. Examining the oxygen consumption data indicates that a vest weighing 10% BM is needed to increase oxygen consumption, but at higher speeds, a 5% increase significantly increases oxygen consumption.
Examining the VGRF and LR data is more straightforward because of the lack of interaction between weighted vest condition and walking speed. Using a weighted vest set at 10% BM increased F1 and F2. Increasing vest mass from 10 to 15% increased F2, and increasing from 15 to 20% increased F1.. Making 5% BM adjustments led to significant changes in either in F1 or F2. These findings are similar to those of Salem et al (17). They found that weighted vests set at 3 and 5% BM significantly increased peak VGRF, maximal peak plantar flexion moments, and knee extensor moments during self-selected walking velocity trials in comparison with walking without a weighted vest. LR were less responsive to changes in vest mass. Subjects need to walk with 15% BM to significantly increase this factor. This finding would support the goal of ideally progressing vest mass to 15% BM or more if the goal of exercise is to improve bone health.
One limitation of this study is that our subjects were young and disease-free. Individuals who have a lower aerobic capacity would likely experience greater physiological stresses with weighted vest walking. However, we selected a younger population because we were interested in how the outcome variables were affected by a vest weighing up to 20% BM. In our opinion, it was questionable if an older population with health problems would be able to safely tolerate walking at 4.0 mph with a 20% BM vest setting. Not having a 5% BM test condition in our study also makes it difficult to determine the minimal amount of weight needed to change our outcome measures. The decision to excluded 5% BM from the protocol, however, was made because most studies that have used weighted vest prescribe a weight that is greater than 10% BM (4,18). Another limitation is our sample's small size and lack of gender balance. Having more subjects and a more proportional number of men and women would have allowed us to examine if a gender effect was present. Finally, no kinematic data were collected in this study. This limited our ability to thoroughly determine whether using a weighted vest altered gait patterns, or to calculate changes in joint moments.
This study demonstrated that using a weighted vest while walking can significantly increase the metabolic costs, the passive loading of the skeletal system, the rate of loading, and the forces created by the lower-extremity musculature during walking. Whereas other studies have examined kinetic and kinematic changes caused by weighted vest walking, ours is the first to examine changes across multiple speeds and vest conditions, to differentiate how weighted vest walking affects the both peaks of the VGRF curve and the LR, and to consider metabolic changes (17). These results have direct implications in the design of exercise programs to facilitate improvements in cardiorespiratory health or to increase bone health. The results of this study can also be used to guide other researchers who seek to examine the effect of using different magnitudes of weight in the vests during an exercise program.
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