Energy expenditure responses to exercise training in older women

No evidence for metabolic adaptation during exercise-related energy compensation

The constrained energy model posits that the increased total daily energy expenditure (TDEE) in response to exercise is often less than the energy cost of the exercise prescribed. The mechanisms behind this phenomenon, coined "exercise-related energy compensation" (ExEC), are poorly understood, and it is unknown if ExEC is coupled with metabolic adaptation. Using a randomized controlled 24-week exercise intervention, individuals who demonstrated ExEC were identified. Changes to all components of TDEE and metabolic adaptation were assessed using doubly labeled water over 14 days and room calorimetry over 24-h 48% of individuals exhibited ExEC (-308 ± 158 kcals/day). There were no statistically significant differences in sex, age, or BMI between ExEC and non-ExEC. ExEC was associated with baseline TDEE (r = -0.50, p = 0.006). There were no statistically significant differences in metabolic adaptations for 24 h, sleep, or resting expenditures. These findings reveal that ExEC occurs independent of metabolic adaptation in sedentary components of EE.

Development and validation of age-specific predictive equations for total energy expenditure and physical activity levels for older adults

BACKGROUND

Predicting energy requirements for older adults is compromised by the underpinning data being extrapolated from younger adults.

OBJECTIVES

To generate and validate new total energy expenditure (TEE) predictive equations specifically for older adults using readily available measures (age, weight, height) and to generate and test new physical activity level (PAL) values derived from 1) reference method of indirect calorimetry and 2) predictive equations in adults aged ≥65 y.

METHODS

TEE derived from "gold standard" methods from n = 1657 (n = 1019 females, age range 65-90 y), was used to generate PAL values. PAL ranged 1.28-2.05 for males and 1.26-2.06 for females. Physical activity (PA) coefficients were also estimated and categorized (inactive to very active) from population means. Nonlinear regression was used to develop prediction equations for estimating TEE. Double cross-validation in a randomized, sex-stratified, age-matched 50:50 split, and leave one out cross-validation were performed. Comparisons were made with existing equations.

RESULTS

Equations predicting TEE using the Institute of Medicine method are as follows: For males, TEE = -5680.17 - 17.50 × age (years) + PA coefficient × (6.96 × weight [kilograms] + 44.21 × height [centimeters]) + 1.13 × resting metabolic rate (RMR) (kilojoule/day). For females, TEE = -5290.72 - 8.38 × age (years) + PA coefficient × (9.77 × weight [kilograms] + 41.51 × height [centimeters]) + 1.05 × RMR (kilojoule/day), where PA coefficient values range from 1 (inactive) to 1.51 (highly active) in males and 1 to 1.44 in females respectively. Predictive performance for TEE from anthropometric variables and population mean PA was moderate with limits of agreement approximately ±30%. This improved to ±20% if PA was adjusted for activity category (inactive, low active, active, and very active). Where RMR was included as a predictor variable, the performance improved further to ±10% with a median absolute prediction error of approximately 4%.

CONCLUSIONS

These new TEE prediction equations require only simple anthropometric data and are accurate and reproducible at a group level while performing better than existing equations. Substantial individual variability in PAL in older adults is the major source of variation when applied at an individual level.

The intensity paradox: A systematic review and meta-analysis of its impact on the cardiorespiratory fitness of older adults

AIM

The present systematic review and meta-analysis aimed to compare the effect of moderate- versus high-intensity aerobic exercise on cardiorespiratory fitness (CRF) in older adults, taking into account the volume of exercise completed.

METHODS

The databases MEDLINE (Ovid), EMBASE (Ovid), and CENTRAL (Cochrane Library) were searched to identify randomized controlled trials (RCTs). Two reviewers extracted data and assessed bias. Comprehensive Meta-Analysis software calculated overall effect size, intensity differences, and performed meta-regression analyses using pre-to-post intervention or change scores of peak oxygen uptake (V̇O2 peak). The review included 23 RCTs with 1332 older adults (intervention group: n = 932; control group: n = 400), divided into moderate-intensity (435 older adults) and high-intensity (476 older adults) groups.

RESULTS

Meta-regression analysis showed a moderate, but not significant, relationship between exercise intensity and improvements in V̇O2 peak after accounting for the completed exercise volume (β = 0.31, 95% CI = [-0.04; 0.67]). Additionally, studies comparing moderate- versus high-intensity revealed a small, but not significant, effect in favor of high-intensity (Hedges' g = 0.20, 95% CI = [-0.02; 0.41]). Finally, no significant differences in V̇O2 peak improvements were found across exercise groups employing various methods, modalities, and intensity monitoring strategies.

CONCLUSION

Findings challenge the notion that high-intensity exercise is inherently superior and indicate that regular aerobic exercise, irrespective of the specific approach and intensity, provides the primary benefits to CRF in older adults. Future RCTs should prioritize valid and reliable methodologies for monitoring and reporting exercise volume and adherence among older adults.

Effect of Exercise Training on Lipoprotein Subclass Particle Concentrations and Sizes in Older Women: Results from a Randomized Controlled Trial

BACKGROUND

Evidence suggests that lipoprotein subclass particles are critical markers of cardiovascular disease (CVD) risk. Older women have increased CVD risk related to age. The purpose of this study was to determine whether low and moderate doses of exercise influence lipoprotein subclasses.

METHODS

Women (60-75 years) were randomized into groups for 16 weeks of moderate-intensity exercise training at a low or moderate dose (33.6 and 58.8 kJ/kg body weight weekly, respectively). Lipoprotein subclasses were determined by nuclear magnetic resonance spectroscopy before and after the training.

RESULTS

The average weekly exercise duration was 109 and 164 min, for low- and moderate-dose groups, respectively. In the low-dose group, high-density lipoprotein particle (HDL-P) concentration decreased (Δ = -1.9 ± 3.1 µmol/L, mean ± SD, p = 0.002) and mean HDL-P size increased (Δ = 0.1 ± 0.3 nm, p = 0.028). In the moderate-dose group, mean HDL-P size (Δ = 0.1 ± 0.2 nm; p = 0.024) and low-density lipoprotein particle size increased (Δ = 0.4 ± 3.9 nm; p = 0.007). Baseline body mass index, peak oxygen consumption and age were associated with changes in a few lipoprotein subclasses.

CONCLUSIONS

In this sample of inactive older women, moderate-intensity exercise training at a dose equivalent to or even lower than the minimally recommended level by public health agencies induced changes in lipoprotein subclasses in line with reduced CVD risk. However, higher doses are encouraged for greater health benefits.

Development and validation of new predictive equations for the resting metabolic rate of older adults aged ≥65 y

BACKGROUND

The aging process alters the resting metabolic rate (RMR), but it still accounts for 50%-70% of the total energy needs. The rising proportion of older adults, especially those over 80 y of age, underpins the need for a simple, rapid method to estimate the energy needs of older adults.

OBJECTIVES

This research aimed to generate and validate new RMR equations specifically for older adults and to report their performance and accuracy.

METHODS

Data were sourced to form an international dataset of adults aged ≥65 y (n = 1686, 38.5% male) where RMR was measured using the reference method of indirect calorimetry. Multiple regression was used to predict RMR from age (y), sex, weight (kg), and height (cm). Double cross-validation in a randomized, sex-stratified, age-matched 50:50 split and leave one out cross-validation were performed. The newly generated prediction equations were compared with the existing commonly used equations.

RESULTS

The new prediction equation for males and females aged ≥65 y had an overall improved performance, albeit marginally, when compared with the existing equations. It is described as follows: RMR (kJ/d) = 31.524 × W (kg) + 25.851 × H (cm) - 24.432 × Age (y) + 486.268 × Sex (M = 1, F = 0) + 530.557. Equations stratified by age (65-79.9 y and >80 y) and sex are also provided. The newly created equation estimates RMR within a population mean prediction bias of ∼50 kJ/d (∼1%) for those aged ≥65 y. Accuracy was reduced in adults aged ≥80 y (∼100 kJ/d, ∼2%) but was still within the clinically acceptable range for both males and females. Limits of agreement indicated a poorer performance at an individual level with 1.96-SD limits of approximately ±25%.

CONCLUSIONS

The new equations, using simple measures of weight, height, and age, improved the accuracy in the prediction of RMR in populations in clinical practice. However, no equation performs optimally at the individual level.

Associations between Sleep and Body Composition in Older Women and the Potential Role of Physical Function

Purpose

The relationship between sleep and adiposity in older women remains unclear partly due to the reliance of body mass index as a measure of adiposity. The purpose of this study was to investigate associations between objectively measured sleep characteristics and body composition measured by dual energy x-ray absorptiometry (DXA) in older women. A secondary purpose was to examine if physical function mediates this relationship.

Methods

Non-obese older women (ages 60-75 years, n=102) were included in the study. Total sleep time (TST), time in bed (TIB), sleep efficiency (SE), and wake after sleep onset (WASO) were determined by actigraphy. A battery of tests was used to assess physical function.

Results

With adjustment for age, there was a negative association between TST and TIB with lean mass. Both grip strength and dominant leg extension were associated with TST, TIB, and lean mass; the associations between TST and TIB with lean mass were lost after adjusting for grip strength or leg extension strength. Additionally, SE was negatively associated with total, gynoid, and trunk lean mass, and there was a positive association between TST and percent trunk fat, and WASO and gynoid lean mass, with age adjusted.

Conclusions

Sleep characteristics, TST, TIB, SE, and WASO, were associated body composition measures in this sample of older women. The relationship between TST and TIB with body composition was mediated, in part, by grip strength and leg extension strength.

The fire of evolution: energy expenditure and ecology in primates and other endotherms

Total energy expenditure (TEE) represents the total energy allocated to growth, reproduction and body maintenance, as well as the energy expended on physical activity. Early experimental work in animal energetics focused on the costs of specific tasks (basal metabolic rate, locomotion, reproduction), while determination of TEE was limited to estimates from activity budgets or measurements of subjects confined to metabolic chambers. Advances in recent decades have enabled measures of TEE in free-living animals, challenging traditional additive approaches to understanding animal energy budgets. Variation in lifestyle and activity level can impact individuals' TEE on short time scales, but interspecific differences in TEE are largely shaped by evolution. Here, we review work on energy expenditure across the animal kingdom, with a particular focus on endotherms, and examine recent advances in primate energetics. Relative to other placental mammals, primates have low TEE, which may drive their slow pace of life and be an evolved response to the challenges presented by their ecologies and environments. TEE variation among hominoid primates appears to reflect adaptive shifts in energy throughput and allocation in response to ecological pressures. As the taxonomic breadth and depth of TEE data expand, we will be able to test additional hypotheses about how energy budgets are shaped by environmental pressures and explore the more proximal mechanisms that drive intra-specific variation in energy expenditure.

The role of physical activity in the regulation of body weight: The overlooked contribution of light physical activity and sedentary behaviors

The role of physical activity (PA) in the regulation of body weight is still a major topic of debate. This may be because studies have essentially focused on the effects of moderate/vigorous PA (MVPA) on body weight while overlooking the other components of PA, namely, light-intensity PA (LPA, daily life activities) and sedentary behaviors (SB, too much sitting). In this review, we will (i) describe the history of changes in PA behaviors that occurred with modernization; (ii) review data from cross-sectional and longitudinal studies that examined the associations between PA, SB, and measures of obesity; (iii) review interventional studies that investigated the effects of changes in PA and SB on body weight and adiposity; and (iv) discuss experimental studies that addressed potential biological mechanisms underlying the effects of PA and SB on weight regulation. Overall recent findings support the importance of considering all components of PA to better understand the regulation of energy balance and suggest an important role for LPA and SB in addition to MVPA on body weight regulation. Longitudinal large-scale rigorous studies are needed to advance our knowledge of the role of PA/SB in combating the obesity epidemic.

Measurement of Physical Activity with Wrist-Worn ActiGraph GT3X+ in Older Women

Higher wear compliance has been seen with wrist placed accelerometers versus hip placed. Performance of wrist placed ActiGraph GT3X+ accelerometer (GT3X+, ActiGraph LLC, Pensacola, FL) in assessing physical activity (PA) remains unclear.

PURPOSE

This study examined GT3X+'s performance in measuring PA energy expenditure (PAEE) and classifying PA intensity in older women.

METHODS

Women [n = 89, age = 65.6 (4.3)] wore GT3X+ and SenseWear Armband Mini (SWAM, BodyMedia Inc. Pittsburgh, PA) for 2 weeks. Concurrently, doubly labeled water (DLW) determined total daily energy expenditure (TDEE). Resting energy expenditure (REE) was determined by Indirect Calorimetry. Data was processed using manufacturer-provided software. Bivariate correlations, Intra Class Correlations, and Bland-Altman plots were performed to evaluate agreement between GT3X+ and criterion measures for sedentary time, light and moderate-to-vigorous PA (determined by SWAM) and PAEE (determined by SWAM and by DLW and REE). Epoch-by-epoch analysis evaluated discrepancy and agreement of PA intensity classification between GT3X+ and SWAM.

RESULTS

For PAEE, GT3X+ showed moderate correlations with criterion measures (r = 0.413, 0.400 with SWAM; r = 0.564, 0.501 with DLW and REE), but Bland-Altman plots showed large variability. When estimating time spent in PA intensity, GT3X+ underestimated sedentary time and overestimated PA intensity compared to SWAM. During epoch-by-epoch analysis, GT3X+ misclassified light intensity PA as moderate-to-vigorous PA 72% of the time. Counts per minute showed strong correlations with criterion measures (r = 0.68, 0.625 for SWAM and DLW and REE respectively).

CONCLUSION

Current equations and cut points do not provide accurate measures of PA with wrist-worn GT3X+ in older women.

Balancing growth, reproduction, maintenance, and activity in evolved energy economies

Economic models predominate in life history research, which investigates the allocation of an organism's resources to growth, reproduction, and maintenance. These approaches typically employ a heuristic Y model of resource allocation, which predicts trade-offs among tasks within a fixed budget. The common currency among tasks is not always specified, but most models imply that metabolic energy, either from food or body stores, is the critical resource. Here, we review the evidence for metabolic energy as the common currency of growth, reproduction, and maintenance, focusing on studies in humans and other vertebrates. We then discuss the flow of energy to competing physiological tasks (physical activity, maintenance, and reproduction or growth) and its effect on life history traits. We propose a Ψ model of energy flow to these tasks, which provides an integrative framework for examining the influence of environmental factors and the expansion and contraction of energy budgets in the evolution of life history strategies.

Does sedentary time increase in older adults in the days following participation in intense exercise?

BACKGROUND

Older adults have the highest sedentary time across all age groups, and only a small portion is meeting the minimum recommendations for weekly physical activity. Little research to date has looked at how changes in one of these behaviours influences the other.

AIM

To assess changes in 24-h movement behaviours (sedentary time, light intensity physical activity (LPA), moderate-vigorous PA (MVPA) and sleep) over three consecutive days, following acute bouts of exercise of varying intensity in older adults.

METHODS

Participants (n = 28, 69.7 ± 6.5 years) completed a maximal exercise test and the following exercise protocols in random order: moderate continuous exercise (MOD), high-intensity interval exercise (HI) and sprint interval exercise (SPRT). A thigh-worn device (ActivPAL™) was used to measure movement behaviours at baseline and the 3 days following each exercise session.

RESULTS

Repeated measures analysis of variance indicated that compared to baseline, participants decreased MVPA in the 3 days following all exercise sessions and decreased LPA following HI and SPRT (p < 0.05). Over half of the sample had clinically meaningful increases in sedentary time (30 min/day) in the days following exercise participation.

DISCUSSION

Older adults who compensate for exercise participation by reducing physical activity and increasing sedentary time in subsequent days may require behavioural counseling to ensure that incidental and recreational physical activities are not reduced.

CONCLUSION

It appears that older adults compensate for acute exercise by decreasing MVPA and LPA, and increasing sedentary time in the days following exercise. Future research is needed to determine whether compensation persists with regular engagement.

Sedentary Time and Physical Activity in Older Women Undergoing Exercise Training

Older adults have low rates meeting the physical activity (PA) guidelines and high sedentary time. Low PA and excessive sedentary time have been linked to adverse health outcomes. Less is known about whether exercise training influences sedentary time and PA in various intensities.

PURPOSE

This study aimed to examine the effects of a 16-wk aerobic exercise training on time spent being sedentary and on light-intensity PA (LPA) and moderate- to vigorous-intensity PA (MVPA) and step numbers in older women.

METHODS

Inactive women (n = 61; age = 65.5 ± 4.3 yr) participated in moderate-intensity walking of either a low or a moderate dose (33.6 and 58.8 kJ·kg body weight per week, respectively). They wore a SenseWear Mini Armband at baseline and at end intervention to determine sedentary, LPA, and MVPA time and step numbers.

RESULTS

Time being sedentary, or spent on LPA and MVPA, did not change differently by exercise groups with different doses (all P values for group-time interaction >0.580). Overall, time being sedentary reduced from baseline to end intervention by approximately 39 min·d (P < 0.001), and LPA increased by 19 min·d (P = 0.003). MVPA time increased (P < 0.001), which was primarily accounted for by the supervised exercise. Interestingly, daily steps increased more in the moderate-dose than the low-dose group (P = 0.023 for group-time interaction; 33.6% and 19.8% median increase in moderate- and low-dose groups, respectively). Also, there were individual differences in these changes.

CONCLUSION

Results indicated that, on average, older women did not reduce time of LPA or MVPA outside the exercise program or increase sedentary time as a result of participating in the exercise program.

Do older English adults exhibit day-to-day compensation in sedentary time and in prolonged sedentary bouts? An EPIC-Norfolk cohort analysis

INTRODUCTION

Compensatory behaviours may be one of the reasons for the limited success of sedentary time interventions in older adults, but this possibility remains unexplored. Activity compensation is the idea that if we change activity levels at one time we compensate for them at a later time to maintain a set point. We aimed to assess, among adults aged ≥60 years, whether sedentary time and time spent in prolonged sedentary bouts (≥30 mins) on one day were associated with sedentary time and time spent in prolonged sedentary bouts (≥30 mins) on the following day. We also sought to determine whether these associations varied by sociodemographic and comorbid factors.

METHODS

Sedentary time was assessed for seven days using hip-worn accelerometers (ActiGraph GT1M) for 3459 adults who participated in the EPIC-Norfolk Study between 2004 and 2011. We assessed day-to-day associations in total and prolonged bouts of sedentary time using multi-level regressions. We included interaction terms to determine whether associations varied by age, sex, smoking, body mass index, social class, retirement, education and comorbid factors (stroke, diabetes, myocardial infarction and cancer).

RESULTS

Participants (mean age = 70.3, SD = 6.8 years) accumulated 540 sedentary mins/day (SD = 80.1). On any given day, every 60 minutes spent in sedentary time was associated with 9.9 extra sedentary minutes on the following day (95% CI 9.0, 10.2). This association was greater in non-retired compared to retired participants (non-retired 2.57 extra minutes, p = 0.024) and in current compared to former and never-smokers (5.26 extra mins for current vs former; 5.52 extra mins for current vs never, p = 0.023 and 0.017, respectively). On any given day, every 60 minutes spent in prolonged bouts was associated with 7.8 extra minutes in these bouts the following day (95% CI 7.6, 8.4). This association was greater in older individuals (0.18 extra minutes/year of age, 95% CI 0.061, 0.29), and for retired versus non-retired (retired 2.74 extra minutes, 95% CI 0.21, 5.74).

CONCLUSION

Older adults did not display day-to-day compensation. Instead, individuals demonstrate a large stable component of day-to-day time spent sedentary and in prolonged bouts with a small but important capacity for positive variation. Therefore older adults appear to be largely habitual in their sedentary behaviour. Strategies to augment these patterns may be possible, given they may differ by age, smoking, and working status.

The Effect of Structured Exercise on Sleep During the Corresponding Night Among Older Women in an Exercise Program

This study investigated the acute effect of exercise on sleep outcomes among healthy older women by comparing days with structured exercise versus days without structured exercise during 4 months of exercise training. Participants (n = 51) in this study had wrist-worn actigraphic sleep data available following at least 3 days with structured exercise and 3 days without structured exercise at mid-intervention and at the end of intervention. The exercise intervention was treadmill walking. Multilevel models were used to examine whether structured exercise impacted sleep outcomes during the corresponding night. Overall, 1,362 nights of data were included in the analyses. In unadjusted and adjusted models, bedtimes were significantly earlier on evenings following an acute bout of structured exercise than on evenings without structured exercise. No other sleep parameters differed between exercise and nonexercise days. Understanding the effects of exercise on sleep in this understudied population may help to improve their overall sleep quality.

The influence of exercise training dose on fasting acylated ghrelin concentration in older women

This study investigated if exercise dose affected acylated ghrelin response to exercise training, and how body weight or fat mass changes might affect the responses. Non-obese older women (n = 49) were randomly assigned to 4-month moderate-intensity aerobic exercise of one of two doses (8 or 14 kcal kg-1 body weight weekly). Following exercise training, fasting acylated ghrelin concentrations changed differently between the two groups (p for group × time interaction = 0.050). It decreased in the moderate-dose (Cohen's d = 0.52, p = 0.019), but did not change in the low-dose exercise group. Adjustment for weight or fat changes did not affect these results. Therefore, exercise training dose can have specific effects on acylated ghrelin that are not dependent on weight or fat loss. However, whether the different acylated ghrelin changes are associated with differing degree of subsequent weight maintenance worth further investigation.

Energy Constraint as a Novel Mechanism Linking Exercise and Health

Humans and other species adapt dynamically to changes in daily physical activity, maintaining total energy expenditure within a narrow range. Chronic exercise thus suppresses other physiological activity, including immunity, reproduction, and stress response. This exercise-induced downregulation improves health at moderate levels of physical activity but can be detrimental at extreme workloads.

The effect of moderate-intensity exercise on nightly variability in objectively measured sleep parameters among older women

Objective/Background: Exercise training has been demonstrated to beneficially influence mean-level measures of sleep; however, few studies have examined the impact of an exercise intervention on night-to-night variability in sleep. This study investigated whether four months of moderate-intensity exercise impacted night-to-night variability in sleep among older women. Methods: Participants (n = 49) were randomized to one of two moderate-intensity walking programs with different doses of energy expenditure: low-dose (n = 23: 8 kcal/kg of body weight per week) or high-dose (n = 26: 14 kcal/kg of body weight per week). Sleep parameters were assessed objectively via actigraphy at baseline, mid- (2 months), and postintervention (4 months). Nightly variability in each of the sleep parameters was calculated using the seven-day standard deviation (SD) and a coefficient of variation (SD/mean x 100%). Cardiorespiratory fitness (VO_2peak) was measured at baseline and postintervention using a graded treadmill test. Results: Both measures of nightly variability demonstrated a borderline to significantly lower amount of night-to-night variability in wake time after sleep onset (WASO) and number of awakenings at postintervention in comparison to baseline (p ≤ 0.05). Higher VO_2peak levels at baseline were associated with less time in bed and lower total sleep time variability throughout the exercise intervention (p < 0.05). Conclusion: Overall, participation in moderate-intensity exercise was observed to reduce the amount of nightly variability for WASO and number of awakenings over time in older women.

How much exercise should be promoted to raise total daily energy expenditure and improve health?

Despite longstanding recognition of the benefits of a physically active lifestyle, there remains ambiguity regarding exactly how much exercise should be promoted to raise total energy expenditure (TEE) and improve health. This review provides a brief summary of the dose-response relationship between physical activity and relative risk of morbidity and mortality; mechanisms through which exercise drives an increase in TEE; the highest reported levels of TEE measured via doubly labelled water; and the potential impact of non-compliance and confounders in moderating the contribution of exercise to increase TEE. Cohort studies provide a compelling argument that 'more is better' regarding the exercise dose for increasing TEE, that increasing TEE is protective for health, and that this is mediated through increased cardiorespiratory fitness. However, growing evidence shows that ever increasing volumes of weekly physical activity may reverse the cost-benefit seen with more modest doses. Animal and human studies show that the elevation in TEE associated with increasing exercise volume is commonly less than expected, due to physiological confounders. Further, there is considerable evidence of behavioural non-compliance to planned exercise in all but the most highly motivated athletes. Therefore, inbuilt defence mechanisms may safeguard against TEE being elevated to maximum levels.

Energy expenditure responses to exercise training in older women

Previous studies have shown inconsistent findings regarding how structured exercise affects energy expenditure (EE). This study was designed to determine the changes in EE and physical activity following exercise training in older women. Nonobese (body mass index = 25.8 ± 3.4 kg·m-2) women (60-75 years, n = 72) completed a 4-month supervised aerobic exercise training of lower- or higher-dose (33.6 and 58.8 kJ·kg-1 body weight weekly, respectively) at 50-55% of heart rate reserve. Total daily EE (TDEE) by the doubly labeled water method, resting metabolic rate (RMR) via indirect calorimetry, and physical activity by accelerometer were determined before and at the end of exercise training. Nonexercise activity thermogenesis (NEAT) was calculated. Following exercise training, the changes in components of TDEE and total physical activity did not differ by group. In the entire sample, TDEE, RMR, NEAT and total physical activity did not change (P > 0.05 for all). However, a significant baseline physical activity × time interaction was found for several of the variables. Data were therefore stratified into tertiles of baseline physical activity. In the high tertile, TDEE remained unchanged, but total physical activity decreased (P = 0.012). In contrast, in the middle and low tertiles, NEAT remained unchanged, and total physical activity increased (P < 0.05 for both). In conclusion, aerobic exercise training did not change TDEE, RMR, NEAT, or total physical activity in this sample of older women. Exercise dose did not, but baseline physical activity levels might, influence EE responses and total physical activity changes.