Total daily energy expenditure (TEE) is an important contributor to metabolic health (12). In addition, free living activity-related energy expenditure (AEE) is related to reduced weight gain (32,35), whereas exercise training reduces weight regain after weight loss (13). However, on the average, older individuals have lower AEE than younger individuals (37). The ability to perform daily tasks reaches a peak at 30 yr but declines thereafter (15). This decline seems to be a result of declining physical activity, reduced strength, and independent effects of aging itself (15).
Lower levels of physical activity in older adults are at least partly explained by lower maximum oxygen uptake (V˙O2max) and increased difficulty in performing daily tasks (18). In addition, muscular strength is associated with increased physical activity and is predictive of reduced 1-yr weight gain (35). Thus, the maintenance of both aerobic fitness and strength seems to be important for the maintenance of total energy expenditure (TEE).
Increased aerobic fitness and strength adjusted for body weight, ease of performing daily tasks such as walking, stair climbing, and carrying a simulated box of groceries are related to increased AEE (36), suggesting that increased ease of physical activity may lead to a more active lifestyle. Indeed, resistance training results in increased ease in walking, stair climbing, carrying a small load, and rising from a chair (17,20). However, older women who resistance train intensely three times per week increase less in ease of performing daily tasks (20) and hypertrophy less (2,10) than women who resistance train intensely less frequently. In addition, subjective feelings of fatigue increase and vigor decreases when training volume increases in competitive swimmers (27,29). Taken together, these results suggest that resistance training may be important for maintaining ease during daily tasks such as walking, stair climbing, carrying, and rising from a chair; however, training too intensely too frequently may result in increased fatigue and a reduced training adaptation in older women.
Training less than twice a week for any particular modality (strength training once a week or aerobic training once a week) is usually felt to be sufficient for maintaining fitness but of insufficient frequency to improve fitness. However, a program in which older adults aerobic and resistance trained once a week for 16 wk resulted in similar increases in strength and aerobic fitness as twice a week aerobic and resistance training (21), suggesting that older adults may require less frequent training than younger adults.
It is not clear what effect exercise training has on TEE in older adults. TEE and AEE have been shown to be elevated in chronically active compared with chronically inactive women, 49–70 yr old (38). TEE increases after resistance training in younger males (34) and older women with coronary heart disease (1). However, TEE did not increase after an 8-wk high-intensity aerobic training program (9) for 58–78 yr old men and women, suggesting a reduction in nonexercise training activity-related thermogenesis (NEAT). The high intensity (85% V˙O2max) and short duration may have led to reduced NEAT because of overtraining in the untrained older adults.
Some studies suggest increases in NEAT (24) after exercise training. Resistance training in nonalcoholic fatty liver disease patients resulted in more steps per day (11). In addition, 24 wk of resistance training program increased TEE, with a trend toward an increase in NEAT (19). To our knowledge, no one has examined the effects of combined training on TEE and NEAT in older adults. Because training volume and time will be doubled with combined training compared with either resistance or aerobic training alone, it is possible that training too frequently may lead to overstress.
Intense exercise can cause muscle damage (4,5) with an up-regulation of acute inflammation (30). Too frequent training may lead to chronic inflammation and production of circulating proinflammatory cytokines such as interleukin 1β (IL-1β), tumor necrosis factor α, and IL-6 (33). A growing body of literature suggests that elevated proinflammatory cytokines provide a link between the blood and the brain (25), causing mood changes favoring inactivity.
Consistent with the concept that overstress may lead to mood changes, muscle soreness was accompanied by increases in depression, anger, and fatigue in collegiate swimmers (27). Despite an improvement in overall mood resulting from 24 wk of resistance training in older adults (26), increased training volume in a combined resistance and aerobic training program resulted in increased depression, decreased vigor (28), and increased fatigue (27). Thus, proinflammatory cytokine production and changes in mood may explain the reduction in NEAT in some studies and the inverse relationship between exercise intensity and improvement after 16 wk of high-intensity resistance training (16).
Therefore, the purpose of this study was to examine the effects of three different frequencies (1 d·wk−1 of aerobic and 1 d·wk−1 of resistance [1 + 1] versus 2 d·wk−1 of aerobic and 2 d·wk−1 resistance [2 + 2] versus 3 d·wk−1 aerobic and 3 d·wk−1 resistance [3 + 3]) of 16 wk of combined resistance and aerobic training has on proinflammatory cytokines, subjective feelings of fatigue/depression/vigor, TEE, AEE, and NEAT in a group of older women. We hypothesize the 2 + 2 group will have larger increases in strength, aerobic fitness, TEE, AEE, and NEAT than either the 1 + 1 or 2 + 2 training groups. In addition, we hypothesize that the 3 + 3 group will exhibit indicators of increased overstress such as increased depression and fatigue, reduced vigor, and increased proinflammatory cytokines whereas the 2 + 2 and the 1 + 1 groups will not.
Seventy-two women, 60–74 yr old, participated in a 16-wk combined aerobic and resistance training program. All subjects were healthy, free of any metabolic disorders, not taking medications that may affect energy expenditure, nonsmokers, and sedentary (defined as exercising less than once per week for the past year). Institutional review board–approved informed consent was obtained before participation in the study in compliance with the Department of Health and Human Services Regulations for Protection of Human Research Subjects. Subjects were evaluated before and after 16 wk of combined resistance and aerobic training. Subjects were randomly assigned to one of three training groups (1 + 1, 26 subjects; 2 + 2, 26 subjects; or 3 + 3, 22 subjects).
Training sessions lasted 50 min in a facility dedicated to research and under the supervision of exercise physiologists. Each session began with a 3- to 4-min warm-up on a cycle ergometer or treadmill and 3–4 min of stretching.
During the first week, subjects performed 20 min of continuous exercise at 67% maximum heart rate. Each week, the intensity and duration were increased as follows: weeks 2–5 duration increased 5 min each week so that by week 5, subjects were working at 67% maximum heart rate for 40 min. Exercise heart rate increased to 71% maximum heart rate at week 6, but duration decreased to 30 min. Week 7 duration increased to 40 min. Exercise heart rate increased to 75% maximum heart rate at week 8 but duration decreased to 30 min. Week 9 exercise duration increased to 40 min. Exercise heart rate increased to 80% maximum heart rate at week 10, but duration decreased to 30 min. Week 11 duration increased to 40 min. The subjects then trained at 80% maximum heart rate for 40 min each training session for the remainder of the study. Exercise modalities included both cycle ergometer and treadmill exercise. At least 50% of the training time was performed on the treadmill.
Strength exercises included leg press, squats, leg extension, leg curl, elbow flexion, lateral pull-down, bench press, military press, lower back extension, and bent leg sit-ups. Each exercise consisted of two sets of 10 repetitions with a 1.5- to 2-min rest between sets. The intensity began at 60% of the maximum weight the subject could lift at one time (one-repetition maximum [1RM]) and was gradually increased to 80% of 1RM at week 8. Subject 1RM was determined every fifth week to ensure that intensity was increased appropriately.
For the first two exercise sessions, the subjects trained with a resistance that allowed them to become familiar with both the equipment and the exercises. On the third session, the subjects performed a 1RM test on all resistance exercises except lower back extension and bent leg sit-ups (in which no weight was used) using methods previously described (22). 1RM testing was repeated during the last scheduled exercise session. Depending on the type of 1RM test, the test–retest reliability in our laboratory for 1RM testing varies from 0.95 to 0.99 for intraclass correlation coefficients with the SE of measurements varying from 1.5 to 4.0 kg for samples that have SD values that vary from 9 to 22 kg (22).
Maximal aerobic exercise testing was physician supervised and conducted using the modified Balke treadmill test protocol. A metabolic cart, calibrated before testing (Max-1 Cart; Physio-Dyne Instrument Corporation, Quogue, NY), was used to evaluate ventilatory expired gases. Monitoring consisted of 12-lead electrocardiogram, and BP measurements were taken every 2 min (Omron Blood Pressure Monitor, model HEM-780; Omron Healthcare, Inc., Bannockburn, IL). The testing commenced with treadmill walking at 2 mph for 2 min. Treadmill grade was increased 3.5% every 2 min until minute 12, at which time grade was decreased to 12% and speed was increased to 3 mph. The grade then increased 2.5% each minute until exhaustion. Blood pressure, heart rate, and oxygen uptake were recorded during the last 20 s of each level. Participants were encouraged to exercise to fatigue. Termination criteria for testing followed the American Heart Association/American College of Cardiology guidelines (6,7). Maximum oxygen uptake (V˙O2max, mL·kg−1·min−1), maximum RER, and maximum heart rate were defined as the highest 20-s averaged value. The criteria for obtaining maximum oxygen uptake were heart rate within 10 beats of age predicted maximum, plateauing of oxygen uptake, and RER 1.1 or larger.
Resting Energy Expenditure
Resting energy expenditure (REE) was measured between 6:00 and 8:00 a.m. after a 12-h fast. Subjects were not allowed to sleep, and measurements were made in a quiet, softly lit, well-ventilated room. Temperature was maintained between 22°C and 24°C. Measurements were made supine on a comfortable bed, with the head enclosed in a Plexiglas canopy. Posttraining REE was measured 41 h after the last resistance exercise session. After resting for 15 min, REE was measured for 30 in with a computerized, open-circuit, indirect calorimetry system with a ventilated canopy (Delta Trac II; Sensor Medics, Yorba Linda, CA). The last 20 min of measurement was used for analysis. Oxygen uptake (V˙O2) and carbon dioxide production (CO2) were measured continuously and values were averaged at 1-min intervals. Energy expenditure and RER were calculated from the V˙O2 and CO2 data.
Estimated Energy Cost of Exercise Training
Net oxygen uptake (exercise oxygen uptake − resting oxygen uptake) was measured (Max-1 Cart; Physio-Dyne Instrument Corporation) while walking at a grade that was within 5 beats per minute of heart rate that subjects trained during the 2-wk period that TEE was measured during the posttraining evaluation (no exercise training was taking place during the pretraining evaluation). Oxygen uptake was measured during the first 5 min of exercise, between the 20th and the 25th min of exercise and between the 35th and the 40th min of exercise and averaged. Oxygen uptake was converted to kilocalories per session (5 kcal·L−1 O2·min−1 × 40 min).
We measured the energy cost of the resistance training and 15 min of recovery on a subset of 25 subjects (COSMED K4 b2 portable metabolic system; COSMED srl, Rome, Italy). On the basis of these measured values, we developed a regression equation for estimating energy expenditure for the rest of the subjects based on the amount of weight lifted in each of the exercises use in the resistance training. We then validated the equation using a different set of older women (n = 14) and found the R2 between predicted and actual energy expenditure to be 0.95 (SEE = 11 kcal) using methods we have previously described (21). Actual measured resistance training energy expenditures were used for the 25 subjects that had measured resistance training energy expenditures, whereas estimated energy expenditures were generated from the regression equation for those remaining subjects.
Dual-Energy X-ray Absorptiometry
Dual-energy x-ray absorptiometry (Lunar DPX-L densitometer; LUNAR Radiation, Madison WI) in the Department of Nutrition Sciences at UAB was used to determine total fat and lean mass. Adult Software, version 1.33, was used to analyze the scans.
TEE was measured before and during the last 2 wk of resistance training using the doubly labeled water technique as previously described (35). Four timed urine samples were collected after oral dosing of the doubly labeled water: two urine samples were collected in the morning after dosing and two more urine samples were collected 14 d later with a loading dose of 1 g of premixture (10% H218O and 8% 2H2O) per kilogram of body weight. The isotopic dilution spaces were calculated from the H218O and 2H2O enrichments in the body by the extrapolation of the log enrichments back to zero time using the following equation: dilution space (L) = d / 20.02 × 18.02 × 1 / R × E, where d is grams of H218O and 2H2O given, R is the standard ratio for 18O:16O (0.002005) and 2H:1H (0.00015576), E is the enrichment of the H218O and 2H2O at the extrapolated zero time (the percentage above background). The rate of carbon dioxide production (rCO2) was calculated from the equation by Schoeller et al. (31): rCO2 = 0.4554 N (1.01 K0 – 1.04 Kh), where rCO2 is the amount of CO2 produced (mol·d−1) corrected for fractionation, N is the total body water (mol), K0 and Kh are the turnover rates of H218O and 2H2O (d–1), respectively. TEE was then calculated from CO2 production using the equation from de Weir (2): TEE (kcal·d−1) = 3.9 (rCO2 / FQ) + 1.1 rCO2, where TEE is the TEE (kcal·d−1), rCO2 is the rate of carbon dioxide production (L·d−1 where 1 mol of CO2 is equivalent to 22.4 L), and FQ is the food quotient. Samples were analyzed in triplicate for H218O and 2H2O by isotope ratio mass spectrometry at the University of Alabama at Birmingham as previously described (8). Samples for H218O and 2H2O were reanalyzed in seven subjects; the values of TEE between days were in close agreement (coefficient of variation = 4.3%), thus demonstrating a high level of reproducibility.
AEE was estimated by subtracting REE from TEE after reducing TEE by 10% to account for the thermic response to meals. NEAT was calculated as NEAT = AEE − energy cost of exercise training (24).
Blood Draw and Cytokine Analysis
Blood was drawn after an overnight fast at least 40 h after the last exercise session. Inflammatory markers were assessed using enzyme-linked immunosorbent assay (ELISA). All samples were analyzed in duplicate. Tumor necrosis factor α was analyzed using the high-sensitivity ELISA kit (Quantikine HSTA00C; R&D Systems, Minneapolis, MN). IL-6 was assayed using the high-sensitivity ELISA kit (Quantikine HS600B; R&D Systems). C-reactive protein was assayed with the high-sensitivity ELISA kit (030–9710s, ALPCO, Windham, NH). We were not able to obtain data in either the pretraining and posttraining states for 24 subjects. Therefore, we have cytokine data for only 50 subjects.
Perceptions of Fatigue, Vigor, and Depression
The POMS standard assessment has been in use since 1971 and has exhibited high internal consistency and reasonable test–retest reliability on a variety of samples (23). The POMS consists of 65 adjectives that participants rate on a 5-point scale, ranging from 0 = not at all to 4 = extremely. Participants are instructed to choose the best answer for how they have felt within the past week. A POMS score for total mood disturbance consists of scores from the test’s six-factor analytically derived subscales: tension–anxiety, depression, anger–hostility, vigor–activity, fatigue, and confusion–bewilderment. Subscales may also be used individually for analysis. This report used the vigor, fatigue, and depression subscales. There was missing questionnaire data for 19 subjects in either the pretraining or the posttraining time points. Therefore, questionnaire data include only 55 subjects.
The purpose of this investigation was to evaluate the effects of three frequencies of combined resistance and aerobic training on TEE, AEE, and NEAT in older adults. Two-way repeated-measures ANOVA (training by group), with repeated measures for the training factor, were run for all variables except for age and height for which a one-way (group) ANOVA was run. Tukey post hoc tests were used to determine predifferences or postdifferences in energy expenditure variables for each of the three groups for variables in which there were significant time–group interactions. Significance was set at 0.05 for all statistical tests.
Descriptive data are presented in Table 1. No group differences were observed for height or age. There was a significant time effect showing a significant loss of weight (not more than 1.2 kg for any group, P < 0.04), percent fat (varying from −0.5% to −1.9%, P < 0.01), and fat mass (varying from −0.6 to −1.8 kg, P <0.01), but no time–group interaction. Fat-free mass increased significantly (varying from +0.4 kg to +0.7 kg, P < 0.01) with no time–group interaction. Strength in the leg press (P < 0.0.01) and bench press (P < 0.01) as well as V˙O2max (P < 0.0.01) increased significantly pretest to posttest, but there was no time–group interaction. No time or time–group interactions were observed for fatigue or depression, but vigor (P < 0.01) did increase significantly with no time–group interaction. No time, group, or time–group interactions were observed for any of the cytokines.
Energy expenditure values are contained in Table 2 and summarized in Figure 1. No significant time effect was observed for TEE; however, there was a significant time–group interaction (P < 0.02). Post hoc evaluation showed that the 2 + 2 group increased significantly (P < 0.01), but the 1 + 1 and the 3 + 3 groups did not significantly change. No time or time–group interactions were observed for REE. AEE increased (significant time effect, P < 0.02) whereas the time–group interaction was significant (P< 0.03). Post hoc evaluations showed that the 2 + 2 group increased significantly (P < 0.01) but the 1 + 1 and 3 + 3 groups did not. Because of the different training frequencies, average daily exercise energy expenditure (total exercise energy expenditure per week/7 d) during exercise training was significantly different between the three groups (P < 0.01). No time effect was observed for NEAT (AEE—average daily energy expenditure during exercise training); however, there was a significant time–group interaction (P < 0.01). Post hoc tests showed that the 1 + 1 group did not significantly change, but a significant increase for the 2 + 2 group (P < 0.01) and significant decrease for the 3 + 3 group (P < 0.05) were observed.
We are not aware of any previous studies that have evaluated the effects of different frequencies of combined aerobic and resistance training on TEE in older adults. Consistent with our hypothesis, we found TEE increased more after the 2 + 2 combined training than either the 1 + 1 or 3 + 3 combined training (Fig. 1). This was especially the case for NEAT with the 3 + 3 group actually decreasing NEAT −192 kcal·d−1 during the last 2 wk of exercise training while the 1 + 1 showing a nonsignificant increase of +127 kcal·d−1 and the 2 + 2 group significantly increasing NEAT +224 kcal·d−1 (Fig. 1).
Subjects were asked to maintain weight, but as often happens with aerobic exercise training studies, a small weight loss occurred, suggesting that appetite was not increased proportional to the small increase in energy expended. Similar to other resistance training programs in older women (2,14), fat-free mass increased modestly (0.4–0.7 across the three groups), suggesting a blunted hypertrophic response when compared with older men (15). However, there was no time–group interaction, suggesting all groups changed similarly. The combination of the small weight loss and increased FFM induced a decrease in percent fat. Despite increased training frequency and volume, the 3 + 3 group did not increase FFM more than the other groups, suggesting that 1 + 1 training in older women is as sufficient a stimulus for hypertrophy as 2 + 2 or 3 + 3 training. Interestingly, there was also no difference in weight or FM decreases across the three groups despite the increased training frequency/volume and approximately tripled exercise training daily energy expenditure in the 3 + 3 group compared with the 1 + 1 group, probably because the 3 + 3 group compensated by reducing NEAT.
We originally hypothesized that the 1 + 1 group would have lower increases in fitness and TEE because of insufficient training frequency/volume, and the 3 + 3 group would have lower increases in fitness and TEE because of too frequent training frequency/volume. We also felt that the 3 + 3 group would have increased feelings of fatigue and depression and decreased vigor. Our original thinking on this topic was that the increased strength and aerobic fitness adaptations in the 2 + 2 group would lead to increased NEAT and the increased feelings of fatigue in the 3 + 3 group would lead to a reduction in NEAT. Contrary to our hypothesis, strength and aerobic fitness increased similarly in the three groups. None of our measures of increased stress, that is, cytokines and feelings of fatigue and depression, changed with training. Vigor not only did not decrease in the 3 + 3 group but also increased similarly in all three groups. It is unlikely the 3 + 3 d·wk−1 training overstressed these older women. Therefore, overstress/fatigue does not seem to be the reason for the reduced NEAT found with the 3 + 3 training. However, the 3 + 3 d·wk−1 training was very time consuming. The most consistent complaint for the 3 + 3 group was the very large time commitment needed for six exercise training sessions each week. It is possible the 3 + 3 group reduced NEAT during the week because of time restraints rather than fatigue. The 3 + 3 group should have experienced an increase in TEE if they simply decreased the time spent in being physically active in their free time (producing NEAT) for the extra time spent in aerobic and resistance training, likely because of the energy cost for each minute of exercise training being larger than the energy cost per minute during NEAT. NEAT was reduced more than the extra cost of training in the 3 + 3 group. This seems likely since the 3 + 3 group had 376 kcal·d−1 lower NEAT than the 2 + 2 group but only 40 kcal·d−1 higher energy cost of training. It is possible the 3 + 3 group perceived that the training was taking more of their time than it really was and thus overcompensated in time spent in NEAT. However, this is just speculation and offers an alternative hypothesis for explaining the decreased NEAT because our cytokine and perception of fatigue data do not support overstress and fatigue as the cause of the reduced NEAT for the 3 + 3 group. Future work should be conducted to test this hypothesis.
It is important to point out that the results of this study only apply to women age 60–74 yr who have performed combined training for a period of 16 wk. In addition, all the training was performed in our research gym, which adds to the time commitment by requiring transport time to and from the gym for each workout. It is possible results may have been different if men instead of women, older, or younger subjects had been used or if home exercise that presumably would have been less time consuming was used.
In conclusion, resistance and aerobic training conducted once a week on nonconsecutive days was as successful at improving body composition, strength, and aerobic fitness as training more frequently in these older women. However, aerobic training 2 d·wk−1 combined with 2 d·wk−1 resistance training induced larger increases in TEE, AEE, and NEAT than training less frequently or more frequently. In fact, aerobic training 3 d·wk−1 combined with resistance training 3 d·wk−1 reduced NEAT, probably because of the increased training frequency/time obligation. These results suggest that if one of the goals of a combined aerobic and resistance training program is to increase TEE, twice per week training is more successful than more frequent or less frequent training.
This work was supported by the National Institutes of Health (grant nos. R01AG027084-01, R01 AG27084-S, P30 DK56336, P60 DK079626, and UL 1RR025777).
The authors thank David Bryan, Bob Petri, and Paul Zuckerman for their help in data acquisition.
There is not conflict of interest for any of the authors.
The results of the present study do not constitute endorsement by the American College of Sports Medicine.
1. Ades PA, Savage PD, Brochu M, Tischler MD, Lee NM, Poehlman ET. Resistance training increases total daily energy expendiutre in disabled older women with coronary heart disease. J Appl Physiol
. 2005; 98: 1280–5.
2. Bamman MM, Hill VJ, Adams GR, et al. Gender differences in resistance-training-induced myofiber hypertrophy among older adults
. J Gerontol A Biol Sci Med Sci
. 2003; 58: 108–16.
3. de Weir JB. New methods for calculating metabolic rate with special reference to protein metabolism. J Physiol (London)
. 1949; 109: 1–9.
4. Fry AC. The role of training intensity in resistance exercise overtraining and overreaching. In: Kreider RB, Fry AC, O’Toole ML, editors. Overtraining in Sport
. Champaign (IL): Human Kinetics; 1998. pp. 107–27.
5. Fry AC, Kraemer WJ, Van Coppenolle H, et al. Performance decrements with high-intensity resistance exercise overtraining. Med Sci Sports Exerc
. 1994; 26 (9): 1165–73.
6. Gibbons RJ, Balady GJ, Beasley JW. ACC/AHA guidelines for exercise testing. A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee on Exercise Testing). J Am Coll Cardiol
. 1997; 30: 260–311.
7. Gibbons RJ, Balady GJ, Timothy BJ. ACC/AHA guidelines for exercise testing. A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee on Exercise testing). J Am Coll Cardiol
. 2002; 40: 1531–154.
8. Goran MI, Hunter GR, Nagy TR, Johnson R. Physical activity
related energy expenditure and fat mass in young children. Int J Obes Relat Metab Disord
. 1997; 21: 171–8.
9. Goran MI, Poehlman ET. Endurance training does not enhance total energy expenditure
in healthy elderly persons. Am J Physiol
. 1992; 263: E950–7.
10. Hakkinen K, Kraemer WJ, Newton RU, Alen M. Changes in electromyographic activity, muscle fibre and force production characteristics during heavy resistance/power strength training in middle-aged and older men and women. Acta Physiol Scand
. 2001; 171: 51–62.
11. Hallsworth K, Fatakhova G, Hollingswrth KG, et al. Resistance exercise reduces liver fat and its mediators in non-alcoholic fatty liver disease independent of weight loss. Gut
. 2011; 60: 1278–83.
12. Hunter GR. Comparison of nutrition versus exercise training for obese people. In: Benito Peinado PJ, Gonzalez-Gross M, Garcia Zapico A, Rivero Herraiz A, editors. International Congress for Overweight and Obesity Treatment: Nutrition and Physical Activity Programs
. Madrid: Impreso en Espana; 2011. pp. 60–2.
13. Hunter GR, Brock DW, Byrne NM, Chandler-Laney PC, Del-Correl PD, Gower BA. Exercise training prevents regain of visceral fat for 1 year following weight loss. Obesity
2010; 18: 982–6.
14. Hunter GR, Bryan DR, Wetzstein CJ, Zuckerman PA, Bamman MM. Resistance training and intra-abdominal adipose tissue in older men and women. Med Sci Sports Exerc
. 2002; 34 (6): 1023–8.
15. Hunter GR, McCarthy JP, Bamman MM. Effects of resistance training on older adults
. Sports Med
. 2004; 34: 329–48.
16. Hunter GR, Treuth MS. Relative training intensity and increases in strength in older women. J Strength Cond Res
. 1995; 9: 188–91.
17. Hunter GR, Treuth MS, Weinsier RL, et al. The effects of strength conditioning on older women’s ability to perform daily tasks. J Am Geriatr Soc
. 1995; 43: 756–60.
18. Hunter GR, Weinsier RL, Zuckerman PA, Darnell BE. Aerobic fitness, physiologic difficulty and physical activity
in Black and White women. Int J Obes Relat Metab Disord
. 2004; 28: 1111–7.
19. Hunter GR, Wetzstein CJ, Fields DA, Brown A, Bamman MM. Resistance training increases total energy expenditure
and free-living physical activity
in older adults
. J Appl Phyisiol
. 2000; 89: 977–84.
20. Hunter GR, Wetzstein CJ, McLafferty CL, Zuckerman PA, Landers K, Bamman MM. High resistance versus variable resistance training in older adults
. Med Sci Sports Exerc
. 2001; 33 (10): 1759–64.
21. Izquerdo M, Ibanez J, Hakkinen K, Kraemer WJ, Larrion JL, Gorostiaga EM. Once weekly combined resistance and cardiovascular training in healthy older men. Med Sci Sports Exerc
. 2004; 36 (3): 435–43.
22. Kalb JS, Hunter GR. Weight training economy as a function of intensity of the squat and overhead press exercise. J Sports Med Phys Fitness
. 1991; 31: 154–60.
23. LeUnes A. Updated bibliography of the Profile of Mood States in sport and exercise psychology research. J Appl Sport Psychol
. 2000; 12: 110–3.
24. Levine JA, Eberhardt MS, Jensen MD. Role of nonexercise activity thermogenesis in resistance to fat gain in humans. Science
. 1999; 283: 212–4.
25. Maier SF, Watkins LR. Cytokines for psychologists: implications for bidirectional immune-tobrain communication for understanding behavior, mood, and cognition. Psychol Rev
. 1998; 105: 83–107.
26. McLafferty CL, Wetzstein CJ, Hunter GR. Resistance training is associated with improved mood in healthy older adults
. Percept Mot Skills
. 2004; 98: 947–57.
27. Morgan WP, Costill DL, Flynn MG, Raglin JS, O’Conner PJ. Mood disturbance following increased training in swimmers. Med Sci Sports Exerc
. 1988; 20 (4): 408–14.
28. Newton LEHG, Bammon M, Roney R. Changes in psychological State and self-reported diet during various phases of training in competitive bodybuilders. J Strength Cond Res
. 1993; 7: 153–8.
29. Raglin JS, Morgan WP, O’Connor PJ. Changes in mood states during training in female and male college swimmers. Int J Sports Med
. 1991; 12: 585–9.
30. Ryan GB, Majno G. Acute inflamation. Am J Pathol
. 1977; 86: 185–264.
31. Schoeller DA, Ravussin E, Schutz Y, Acheson KJ, Baertschi P, Jequier E. Energy expenditure by doubly labeled water: validation in humans and proposed calculation. Am J Physiol
. 1986; 250: R823–30.
32. Schoeller DA, Shay K, Kushner RF. How much physical activity
is neded to minimize weight gain in previously obese women? Am J Clin Nutr
. 1997; 66: 551–6.
33. Smith LL. Tissue trauma: the underlying cause of overtraining syndrome? J Strength Cond Res
. 2004; 18: 185–93.
34. Van Etten LM, Westerterp KR, Verstappen FT, Boon BJ, Saris WH. Effect of an 18-wk weight-training program on energy expenditure and physical activity
. J Appl Physiol
. 1997; 82: 298–304.
35. Weinsier RL, Hunter GR, Desmond RA, Byrne NM, Zuckerman PA, Darnell BE. Free-living activity energy expenditure in women successful and unsuccessful in maintaining a normal body weight. Am J Clin Nut
. 2002; 75: 499–504.
36. Weinsier RL, Hunter GR, Zuckerman PA, et al. Free-living physical activity
and energy expenditure in black and white women: comparison before and after weight loss. Am J Clin Nut
. 2000; 71: 1138–46.
37. Westerterp KR. Impact of vigorous and non-vigorous activity on daily energy expenditure. Proc Nutr Soc
. 2003; 62: 645–50.
38. Withers RT, Smith DA, Tucker RC, Brinkman M, Clark DG. Energy metabolism in sedentary and active 49- to 70-year-old women. J Appl Physiol
. 1998; 84: 1333–40.
Keywords:© 2013 American College of Sports Medicine
PHYSICAL ACTIVITY; OLDER ADULTS; TOTAL ENERGY EXPENDITURE; MAXIMUM OXYGEN UPTAKE