Stretch-shortening cycle potentiation and resistance training-induced changes in walking economy/ease and activity-related energy expenditure in older women

Abstract

Background:

Use of elastic energy to improve economy and ease of walking may be important for older adults.

Aims:

The purpose of this investigation was to determine if baseline (i.e., untrained) stretch-shortening cycle potentiation (SSCP), was associated with potential changes in free-living activity-related energy expenditure (AEE) following supervised exercise training.

Methods:

Sedentary, postmenopausal women (n = 64) between 60–74 years of age were evaluated before and after 16 weeks of combined aerobic and resistance training. Assessments included: 1) body composition (dual-energy X-ray absorptiometry), 2) resting energy expenditure (indirect calorimetry), 3) submaximal and maximal walking (treadmill / indirect calorimetry), 4) total energy expenditure (doubly-labeled water), 5) one repetition maximum performed on an incline leg press and SSCP (calculated as the difference between concentric and counter-movement leg press throw).

Results:

Results indicated baseline SSCP was related (r = −0.29; p < 0.02) to changes in AEE. However, participants who possessed a high baseline SSCP did not increase SSCP or AEE, whereas participants with low to moderate baseline SSCP demonstrated a significant increase in both SSCP (low +0.54 and moderate +0.47 m/s) and AEE (low +158 and moderate +333 kcal/d) post-training (all p less than 0.05).

Discussion/Conclusion:

Our findings suggest, among participants with low to moderate baseline SSCP, 16 weeks of combined aerobic and resistance training can increase SSCP and free-living AEE. On the other hand, participants with high baseline SSCP may require tailored exercise to increase SSCP and possibly AEE.

INTRODUCTION

Insufficient physical activity, especially among older adults, contributes to a range of detrimental health consequences including obesity, cardio-metabolic dysregulation, and poor quality-of-life (24). Alternatively, aerobic and/or resistance exercise training have been frequently shown to promote greater engagement in spontaneous free-living physical activity (10). However, there is considerable variation to the extent from which exercise training can invoke a positive shift in activity-related energy expenditure (AEE) (10, 13, 25). Prior work has demonstrated some exercise training programs result in no change (1) or even a decrease (4, 32) in AEE. Still, even among exercise programs that successfully increase AEE, considerable between-participant variation exists in response to the exercise training (3). Indeed, some participants exhibit marked increases while others do not change – despite similar improvement in aerobic fitness and muscle strength (3). Hence, it is of interest to identify modifiable factors that may be responsive to exercise training and thus possibly influential to AEE.

Walking economy and ease are known factors related to increased physical activity engagement, and accordingly AEE (2, 7). In recent work, our group has reported a negative relationship between net oxygen uptake (V̇O₂; inverse of economy) during steady-state walking and stretch-shortening cycle potentiation (SSCP) among older adults (28). The implications being that SSCP may favorably affect physical activity engagement via improved walking economy (8, 23, 28); however, it remains unclear if baseline (i.e., untrained) SSCP is related to potential changes in AEE. During walking and running, previous work shows the muscle-tendon complex of the ankle joint resembles a spring-like mechanism, wherein stored elastic energy at foot contact is rapidly released during push off (5, 6, 18). This feature might lower the energy requirement for locomotion, and in turn, improve walking economy via enhanced utilization of stored elastic energy (i.e., ↑SSCP) (26). However, the use of SSCP varies considerably between younger (23) and older adults (28). Taken together, it is possible that variation in the functionality of SSCP may be influential to free-living AEE. Given that inherent synchrony between muscle-tendon complex for walking, it is probable that exercise training interventions can influence the potential for improving SSCP. However, it currently remains unclear if the magnitude of improvement (attributed to exercise training) in walking economy/ease, SSCP, and AEE are influenced by baseline SSCP. The primary purpose of the present work was to determine if baseline SSCP was related to changes in walking economy/ease, SSCP, and AEE among a cohort of older women. It is hypothesized that participants with low to moderate baseline SSCP will increase SSCP and AEE to a greater extent than those with higher baseline SSCP.

METHODS

Experimental Approach to the Problem

Secondary analyses were performed on prior work designed to evaluate the cardio-metabolic effects of 16 weeks of combined aerobic and resistance training (14).

Participants

Sixty-four postmenopausal women between 60–74 years of age were evaluated before and after 16 weeks of supervised exercise training. All participants were non-smokers, self-reported sedentary, as defined by exercising less than one time per week. In compliance with guidelines established by the Declaration of Helsinki, all study procedures were approved by the local Institutional Review Board. Verbal and written informed consent was obtained from all participants prior to testing.

Procedures

Instrumentation

Body composition.

Total body fat percent was estimated before and after the intervention period using customary procedures for dual-energy X-ray absorptiometry (Lunar DPX-L densitometer; LUNAR Radiation, Madison, Adult Software v1.33, WI).

Resting Oxygen Uptake.

Following an overnight fast, resting oxygen uptake (V̇O₂) was measured for 40 minutes via open-circuit, indirect calorimetry (DeltaTrac II: Sensor Medics, Yorba, CA, USA). The final 20 minutes of the measurement period were used for resting V̇O₂.

Free-living total energy expenditure.

Doubly-labeled water (DLW) was used to measure total energy expenditure, as previously described (30). Briefly, participants provided a baseline urine sample. A loading dose of DLW (10% H₂¹⁸O and 8% ²H₂O) was administered at a ratio equating to approximately 1.1 grams per kilogram body mass. To permit proper isotopic dilution, two additional urine samples were collected at +3 and +4 hours post-DLW dosing. Fourteen days later, two urine samples were collected in the morning hours. Urine samples were evaluated in duplicate via isotope ratio-mass spectrometry. Based on the equation by Speakman et al. (29), CO₂ rates (rCO₂) were determined using a fixed-constant for the dilution space ratio (1.0427): rCO₂ (mol/d) = 0.4554N(1.01K₀ - 1.04K_h); where N is total body water (mol) and K₀ and K_h are H₂¹⁸O and ²H₂O turnover rates (d⁻¹), respectively. Using the rCO₂, TEE was calculated from the following equation from Weir (31): TEE (kcal/d) = 3.9(rCO₂/FQ) + 1.1 rCO_2; where rCO₂ is rate of CO₂ production (L/d) and food quotient (0.88). The coefficient of variation for total energy expenditure in our laboratory is 4.3%. Activity related energy expenditure (AEE) was calculated by subtracting 10 percent of the TEE (for thermogenesis related to eating) and REE from TEE (AEE = - (.1 * TEE) – REE) (27).

Maximal oxygen uptake (V̇O_2max) and walking economy.

A graded exercise test consistent with a modified-Balke protocol (Max-1 Cart; Physio-Dyne Instrument Corporation, Quogue, NY) was performed on a treadmill to voluntary exhaustion was used to measure V̇O_2max. Heart rate was continuously measured using a 12-lead electrocardiogram. The highest 20 second V̇O₂ was considered V̇O_2max (mL∙kg⁻¹∙min⁻¹). On a separate day, walking net V̇O₂ (inverse of walking economy) was measured during a submaximal treadmill test at a fixed walking speed of 0.89 m/s. Average V̇O₂ and heart rate for the 4^th minute were used to confirm steady-state. If V̇O₂ and/or heart rate increased during the 4^th minute (above that during the 3^rd minute), an additional 5^th minute was used. Net V̇O₂ was calculated by subtracting resting V̇O₂ from steady-state V̇O₂.

Maximum muscle strength assessment.

Participants performed a one-repetition maximum (1RM) test following the initial two exercise sessions (to permit overall familiarization). Notably, we have previously revealed a high test-retest reliability for measurements performed in our laboratory involving strength assessments (9). Determination of muscle strength included the incline leg press, squat, leg extension, leg curl, elbow flexion, lateral pull-down, bench press, and military press. Lower back extension and bent leg sit-ups were performed with no weight according to methods previously described (9).

Stretch-shortening Cycle Potentiation.

An electronic goniometer was attached to the knee of the participant prior to testing. The leg press sled was connected to a linear position transducer. Both the electric goniometer and linear position transducer were synced with a National Instruments system with a customized LabVIEW (Laboratory Virtual Instrument Engineering Workbench, v7.1) software connected to a 16-channel 12-bit data acquisition system. Before each test, calibration of linear position transducer and goniometer were performed. Data were collected at 1 kHz. A low-pass fourth order Butterworth filter was applied with a cutoff frequency of 50 Hz. The transducer tracked the position of the leg press sled. Using finite-difference technique the displacement data of sled was used to calculate velocity (23). After a 3-minute warm-up on a cycle ergometer a ballistic leg press was performed with a weight equivalent to 100% of the participant’s body mass at baseline and post-training. Concentric only (CO) velocity during a static leg press throw was evaluated after holding the weight for 3 seconds at a 90° knee joint angle, after which, participants extended their knees and hips as rapidly as possible. Velocity was also measured during a counter-movement (CM) leg press throw, wherein participants initiated the move with their legs straighten then lowered the weight to a 90° knee joint angle. To confirm the correct position upon lowering, the computer gave an audible signal indicating 90° knee joint angle had been reached. Immediately, upon hearing the signal, participants extended their knees and hips as rapidly as possible. The difference between CM and CO velocities was defined as SSCP. Following initial statistical inquires participants were stratified by tertiles based on baseline SSCP (Low group ≤ 0.09 ms⁻¹, n = 21; Middle group, > 0.09 and ≤ 0.14 ms⁻¹, n = 22; and high group, > 0.14 ms⁻¹, n = 21).

Exercise Training.

Participants performed aerobic and resistance training wherein the order of exercise mode alternated each training session. Participants completed a 3–4-minute warm-up on a treadmill or cycle ergometer followed by 3–4 minute of stretching prior to each exercise session. Participants stretched muscles to maximum comfort – holding the stretch for 8–10 seconds. Stretching exercises included: standing calf stretch, standing quadriceps stretch, seated hamstring stretch, standing inner groin stretch, buttocks stretch, and cat trunk stretch. All training sessions were supervised by an exercise physiologist in a facility dedicated to research. The mode of aerobic exercise included a treadmill or cycle ergometer with at least 50% of training completed on the treadmill. Week one commenced with 20 minutes of continuous aerobic exercise corresponding to ≈67% of maximal heart rate (MHR; previously measured during the modified-Balke protocol). Participants wore a heart rate monitor during exercise training sessions to assure target heart rate. Weekly volume and intensity gradually increased so that at the end of week 10, participants were continuously training for 40 minutes at an intensity of ≈80% of MHR. The resistance training protocol began with two sets of 10 repetitions at an intensity matching 60% of measured 1RM with 90 to 120 second rest period between sets. Resistance training progressed to 80% 1RM at week 8 (9), while between-set recovery was kept to 60–120 seconds.

Statistical Analyses.

Data are reported as means and standard deviations unless noted otherwise. Data were assessed for normality using the Shapiro-Wilk test. Univariate analysis of variance (ANOVA) was used to evaluate between-group differences in age, whereas independent ANOVAs with repeated-measures for time (i.e., pre- / post-) were used to detect group differences for separate variables. Among the repeated-measured ANOVAs performed, Mauchly’s test indicated the assumption of sphericity was not violated in any instance. Dependent t-tests with Bonferroni correction (based on number of group pair-wise comparisons) were used to examine critical post hoc comparisons. Substantive differences were assessed using partial eta squared (η_p²) and Cohen’s d as a measure of effect size for ANOVAs and post hoc comparisons, respectively. Effect sizes were qualitatively considered using the following: (η_p²) 0.01 as small; 0.06 as medium; 0.14 as large and (d) 0.2 as small; 0.5 as moderate; and 0.8 as large (20). Equal variance was confirmed for all variables with the Levene test. Bivariate relationships were determined using Pearson product-moment correlations on variables of interest. Following preliminary inquiries, a negative relationship between baseline SSCP and changes in AEE were detected. To further elucidate this observation, participants were subsequently stratified by tertiles based on baseline SSCP (Low group < 0.09 ms⁻¹, n = 21; Middle group, > 0.09 and < 0.14 ms⁻¹, n = 22; and high group, > 0.14 ms⁻¹, n = 21). All data were analyzed using the Statistical Package for the Social Science (SPSS v 25.0; IBM, Armonk, NY). Statistical significance was set a priori with a p-value equal to or less than 0.05.

RESULTS

Figure 1 illustrates the unadjusted relationship between baseline SSCP and changes in AEE (r = −0.29; p < 0.02). Table 1 contains mean values for all study variables divided into tertiles for SSCP. Apart from SSCP, no significant between-group differences were found among other reported variables. Significant time effects were observed for body weight (reduced, η_p² = 0.064), percent body fat (reduced, η_p² = 0.317), V̇O_2max (increased, η_p² = 0.102), leg press strength (increased, η_p² = 0.549), net walking V̇O₂ (reduced, η_p² = 0.124), walking heart rate (reduced, η_p² = 0.450) and AEE (increased, η_p² = 0.121). Changes in SSCP (η_p² = 0.250) and AEE (η_p² = 0.119) displayed the only time by group interactions (SSCP η_p² = 0.205 and AEE η_p² = 0.067).

Figure 1:

Unadjusted relationship between baseline SSCP and change (Δ) in AEE (r = −0.29, p < 0.02). Note that low/moderate baseline SSCP tended to exhibit a larger increase in free-living AEE post-training.

Table 1.

Study variables in the Low, Middle, and High SSCP groups.

	Low SSCP n = 21	Middle SSCP n = 22	High SSCP n = 21	P-value
Age (y)	64 ± 4	66 ± 4	64 ± 3	G = 0.09
Body Weight (kg)				T < 0.04
Baseline	72.8 ± 9.0	72.4 ± 9.4	75.5 ± 14.8	G = 0.84
Post-Training	72.1 ± 7.8	71.6 ± 9.8	74.6 ± 13.1	T x G = 0.99
Body fat (%)				T < 0.01
Baseline	42.9 ± 5.7	41.9 ± 4.6	43.1 ± 7.7	G = 0.74
Post-Training	41.5 ± 5.4	40.4 ± 5.6	42.0 ± 7.7	T x G = 0.77
V̇O2max (ml/kg/min)				T < 0.02
Baseline	21.6 ± 4.1	24.2 ± 3.5	22.4 ± 5.7	G = 0.13
Post-Training	21.9 ± 5.0	25.3 ± 3.9	23.8 ± 5.2	T x G = 0.48
Leg press strength adjusted for body weight (kg/kg/d)				T < 0.01
Baseline	2.90 ± 0.64	2.77 ± 0.63	2.82 ± 0.78	G = 0.60
Post-Training	3.50 ± 0.90	3.25 ± 0.66	3.66 ± 1.05*	T x G =0.06
Net walking V̇O2 (ml/kg/min)				T < 0.02
Baseline	7.4 ± 1.0	7.7 ± 1.1	6.9 ±1.3	G = 0.33
Post-Training	6.8 ± 1.2 Ŧ	7.0 ± 1.3 Ŧ	6.7 ± 1.9	T x G = 0.43
Walking heart rate (beats/min)				T < 0.01
Baseline	102 ± 13	100 ± 13	105 ± 12	G = 0.46
Post-Training	96 ± 9 Ŧ	93 ± 14 Ŧ	96 ± 10Ŧ	T x G = 0.43
SSCP (m/s)				T = 0.21
Baseline	0.050 ± 0.019	0.107 ± 0.017	0.212 ± 0.061	G < 0.01
Post-Training	0.104 ± 0.061 Ŧ	0.151 ± 0.068 Ŧ	0.155 ± 0.087*	T x G < 0.01
AEE (kcal/day)				T < 0.01
Baseline	484 ± 381	556 ± 240	637 ± 285	G = 0.22
Post-Training	642 ± 442 Ŧ	889 ± 365 Ŧ	645 ± 249*	T x G < 0.02

^*Different from pooled Low SSCP and Middle SSCP Groups p < 0.05.

^(Ŧ)denotes significant post-hoc difference from baseline.

Further post hoc evaluations revealed the Low (d = 0.545) and Middle (d = 0.583) SSCP groups decreased net walking V̇O₂. Walking heart rate also significantly decreased in the Low (d = 0.545), Middle (d = 0.636), and High (d = 0.818) groups. SSCP increased in the Low (d = 0.14) and Middle SSCP (d = 0.11) groups, and additionally, the Low (d =0.383) and Middle (d = 1.100) groups increased AEE.

DISCUSSION

The purpose of this investigation was to determine if baseline (i.e., untrained state) SSCP in older women related to changes in AEE following 16 weeks of combined aerobic and resistance training. Results indicated participants who possessed a high SSCP prior to training did not increase AEE, whereas participants with low, and to a greater extent moderate SSCP prior to training, increased AEE post-training. These differences in physical activity gain occurred despite similar increases in aerobic fitness and strength for all groups post-training. Importantly, women with lower SSCP prior to training showed an increase in SSCP and walking economy (i.e., decreased net V̇O₂ during the submaximal walk), while those with the highest baseline SSCP did not increase either SSCP or walking economy. These results demonstrate that older women who possess low SSCP prior to training (i.e., baseline) are able to increase SSCP, increase walking economy, and increase AEE whereas older women who possess relatively higher SSCP prior to training may not exhibit positive changes in SSCP, walking economy or free-living physical AEE. These findings are suggestive that increases in SSCP can favorably influence walking economy/ease and participation in free-living physical activity. Further work is needed to determine if other training modalities (i.e., plyometrics) can elicit similar effects.

Increased utilization of elastic energy leads to greater force-generation without adding to the metabolic burden (26). This elastic energy induced force-generation may enhance economy of walking. Fukunaga et al (5, 6) and Kubo et al (17, 18) have shown that the muscle-tendon complex of the ankle joint is stretched during single support; then rapidly recoiled during the push-off. Thus, the muscle-tendon complex of the ankle joint acts as a spring-like mechanism through the storage and release of elastic-strain energy during locomotion. Longer Achilles tendons have higher compliance in the muscle-tendon complex and greater ability to store and utilize mechanical energy (19). Thus, the spring-like action of the muscle-tendon complex reduces the energy needed for muscle shortening (i.e., concentric contraction) during walking and running. Consistent with this premise, we have previously shown that economy during running (15) and walking (28) is positively associated with SSCP, and that Achilles tendon length is positively associated with improved walking economy (22) – likely attributed to enhanced SSCP.

Low levels of physical activity partially contribute to increased obesity and poor metabolic health (16). This may be especially the case for older adults. Previously, we have shown that ease of walking (i.e., decreased heart rate for a given workload) enhances physical activity in older adults (7, 11, 12), whereas improved walking economy improves ease of locomotion (12, 21). Indeed, modifiable lifestyle factors like exercise training represent one of the most effective strategies to combat the loss of function with advancing age. SSCP has been previously shown to be associated with free-living physical activity, possibly by affecting walking economy and ease of locomotion. This is supported by recent evidence revealing a positive relationship between SSCP and walking economy in older women (28). Participants in this study who had relatively high SSCP prior to training did not increase SSCP, walking economy or AEE. Alternatively, participants with a comparatively moderate SSCP prior to training increased SSCP, walking economy and AEE – suggesting improvements in SSCP may be important for improved AEE following exercise training. However, it also implies there may be a ceiling effect for SSCP. For example, improvement in SSCP (due to combined aerobic and resistance training) was not observed in the high SSCP group and the high SSCP group did not increase AEE following post-training. It is possible improvements in SSCP above a certain level may necessitate tailored, more specific exercise training to enhance walking economy and perhaps AEE in older women.

In conclusion, our findings suggest, among participants with low to moderate baseline SSCP, 16 weeks of combined aerobic and resistance training can increase SSCP and free-living AEE. On the other hand, participants with high baseline SSCP may require tailored exercise to increase SSCP and possibly AEE.

Practical Applications

These results suggest that measurement of SSCP may be of value among older adults. While it is advisable for older adults to incorporate both aerobic and resistance exercise training, additional research should determine if inclusion of plyometrics may be enhance SSCP and possibly AEE in older adults.