Share this article on:

Predictors of Fat Mass Changes in Response to Aerobic Exercise Training in Women

Sawyer, Brandon J.; Bhammar, Dharini M.; Angadi, Siddhartha S.; Ryan, Dana M.; Ryder, Justin R.; Sussman, Elizabeth J.; Bertmann, Farryl M.W.; Gaesser, Glenn A.

The Journal of Strength & Conditioning Research: February 2015 - Volume 29 - Issue 2 - p 297–304
doi: 10.1519/JSC.0000000000000726
Original Research

Sawyer, BJ, Bhammar, DM, Angadi, SS, Ryan, DM, Ryder, JR, Sussman, EJ, Bertmann, FMW, and Gaesser, GA. Predictors of fat mass changes in response to aerobic exercise training in women. J Strength Cond Res 29(2): 297–304, 2015—Aerobic exercise training in women typically results in minimal fat loss, with considerable individual variability. We hypothesized that women with higher baseline body fat would lose more body fat in response to exercise training and that early fat loss would predict final fat loss. Eighty-one sedentary premenopausal women (age: 30.7 ± 7.8 years; height: 164.5 ± 7.4 cm; weight: 68.2 ± 16.4 kg; fat percent: 38.1 ± 8.8) underwent dual-energy x-ray absorptiometry before and after 12 weeks of supervised treadmill walking 3 days per week for 30 minutes at 70% of

. Overall, women did not lose body weight or fat mass. However, considerable individual variability was observed for changes in body weight (−11.7 to +4.8 kg) and fat mass (−11.8 to +3.7 kg). Fifty-five women were classified as compensators and, as a group, gained fat mass (25.6 ± 11.1 kg to 26.1 ± 11.3 kg; p < 0.001). The strongest correlates of change in body fat at 12 weeks were change in body weight (r = 0.52) and fat mass (r = 0.48) at 4 weeks. Stepwise regression analysis that included change in body weight and body fat at 4 weeks and submaximal exercise energy expenditure yielded a prediction model that explained 37% of the variance in fat mass change (R 2 = 0.37, p < 0.001). Change in body weight and fat mass at 4 weeks were moderate predictors of fat loss and may potentially be useful for identification of individuals who achieve less than expected weight loss or experience unintended fat gain in response to exercise training.

School of Nutrition and Health Promotion, Healthy Lifestyles Research Center, Arizona State University, Phoenix, Arizona

Address correspondence to Glenn A. Gaesser,

Back to Top | Article Outline


Exercise training without caloric restriction is not considered a very effective means of weight loss on a group level (8,18,34). After exercise training, the magnitude of weight loss typically is much less than that predicted from the cumulative energy expenditure of the exercise training sessions (34). Although mean weight or body fat loss is relatively small, considerable variability in weight change occurs at the individual level (1–3,6–7,18–22,24,28,31,34). In fact, a significant percentage of women may actually gain body weight or fat mass in response to the exercise training (6,8,22,24). The marked heterogeneity in individual responses to exercise training reveals responders (or noncompensators), who lose at least as much weight or body fat as expected from the energy expended during training sessions, and nonresponders (or compensators), who either lose less weight or body fat than expected or actually gain weight or body fat during exercise training (1,3,6,8,18–22,24,28,34).

Reasons for the heterogeneous weight loss response to exercise are largely unknown. Downregulation of free-living spontaneous physical activity during a structured exercise intervention has been reported in some studies (4,13,24,27,29), but not in others (15,25). Individual variability in energy intake in response to exercise training could also contribute to the heterogeneity of exercise training–induced weight loss (2,18,33,41,43,44). Variation in subject adherence to exercise training could also play a role (16).

Preintervention body weight and body fat are the only baseline characteristics that have been shown to be even moderately correlated with overall weight or fat change in response to exercise training (9,18,19,41) or caloric restriction (14,30,36,38–40), with higher baseline body weight generally associated with greater weight loss. During caloric restriction, early weight loss has been shown to predict subsequent weight loss (32). It is not known whether this holds true for exercise programs. Such information might be useful in exercise programs that have weight loss as a primary outcome and in interventions with the intention to improve overall health.

Therefore, the primary purposes of this study were to assess the effect of baseline body weight and composition on body fat change in response to a 12-week aerobic exercise program in premenopausal women and to determine whether changes in body weight or composition during the first 4 weeks of the program were predictive of changes at the end of the program. We hypothesized that women with higher baseline body fat percentage would lose more body fat and would be less likely to compensate than leaner women and that early fat loss would predict final fat loss.

A secondary aim was to determine if any baseline exercise testing variables predict energy compensation during exercise training. Although aerobic capacity has been reported to be similar in compensators and noncompensators (24), whether other physiologic responses to exercise (e.g., pulmonary ventilation, energy expenditure as an index of economy) are predictive of weight loss or energy compensation has not been reported. Such information could potentially be useful for identification of individuals who achieve less than expected weight loss or experience unintended fat gain in response to exercise training. A recent review recommended that identification of individuals who are susceptible to compensation should be a high priority for researchers and clinicians (28).

Back to Top | Article Outline


Experimental Approach to the Problem

We conducted a 12-week supervised aerobic exercise training program. The study was designed as an exercise-only program to evaluate the body fat changes that occur in response to an aerobic exercise dose slightly above the current minimum public health recommendations for vigorous-intensity exercise (12). Although higher exercise doses may be necessary for significant weight loss (5), most U.S. adults do not meet even the minimum public health recommendation for either moderate- or vigorous-intensity activity (37). Therefore, we felt that it would be important to test our hypotheses with a more modest, and possibly more attainable, exercise dose. A priori power calculations using previous data (36) showed that to achieve statistical significance with a 3-predictor regression model that explained at least 20% of the variance in our dependent variable (change in fat mass), we would need 73 subjects to achieve 90% power. We overenrolled by 9 subjects to account for subject attrition. Similar to other studies (2,4,20–22,24), we chose aerobic exercise as our independent variable with no control group because significant fat change is not expected over a 12-week period without lifestyle change. Our primary dependent variable was change in body fat mass.

Back to Top | Article Outline


Eighty-two women, aged 19-45 years, read and signed an informed consent form approved by the Arizona State University institutional review board. Of these 82 women, 81 completed all 36 exercise training sessions (described below) and all the requirements of the study and were therefore included in the analyses. Subjects were nonsmoking, nonpregnant healthy women who were not currently, or within the previous 3 months, meeting the public health guidelines for physical activity (37) or trying to lose weight. We ensured through written questionnaire that all subjects were not engaged in any regular (more than 1–2 days per week) aerobic or resistance exercise training, not currently training for a specific athletic event, and not dieting. Furthermore, subjects were required to be willing to not change their current diet and eating habits for the course of the study. Other exclusion criteria included hypertension, history of cardiac arrhythmia, stroke, myocardial infarction, or current use of heart medications. All participants were asked to abstain from other activities outside of the study and to not make any changes to dietary intake. Participants were frequently reminded to not change diet or physical activity routines throughout the course of the study.

Back to Top | Article Outline


Height was assessed by a standing wall-mounted stadiometer (Seca, Chino, CA, USA). Weight was assessed using a calibrated electronic scale (COSMED, Rome, Italy) with subjects in a bathing suit. Waist circumference was taken at the umbilicus using a standard Gulick tape measure. The same research assistant took all the circumference measurements. Body composition was determined at baseline and 12 weeks using dual-energy x-ray absorptiometry (DXA, Lunar Prodigy; GE Medical Systems Lunar, Madison, WI, USA). All DXA scans were analyzed using enCORE 2011 software, version 13.6, to determine total percentage of fat and lean tissue. A certified radiology technician calibrated the DXA before each day of testing and performed all DXA scans. Subjects wore no metal and removed all jewelry before each test. Dual-energy x-ray absorptiometry has been shown to be highly reliable (coefficient of variation ranging from 0.8 to 2.8%) and valid (1–2% difference from the 4-compartment model) for measuring body fat and for detecting small changes in body fat (35).

A modified Balke incremental exercise test was used at baseline and after 4, 8, and 12 weeks of exercise training to assess

. A Parvomedics Truemax 2400 metabolic cart (Parvomedics, Sandy, UT, USA) and Polar heart rate monitor (Polar, Lake Success, NY, USA) were used to measure gas exchange, pulmonary ventilation (VE), and heart rate continuously. The protocol consisted of 1 minute at 1.5 mph and 0% incline, followed by an increase in speed to 3.3 mph for 1 minute. After 1 minute at 3.3 mph and 0% incline, the treadmill grade increased to 2% and then increased again 1% each minute until volitional exhaustion was reached. Verbal encouragement was given throughout each test. The metabolic cart was calibrated before each test or every 4 hours per manufacturer recommendation. Peak oxygen uptake was calculated by taking average of the 2 highest consecutive 15-second

values. The

-heart rate relationship was used to identify the heart rate that elicited 70% of

at each testing period. The ventilation threshold was determined using ventilation and gas exchange as previously described (11). Submaximal VE and energy expenditure were calculated using minutes 2–4 of the

test. The ventilation threshold was used to ensure that our VE and energy expenditure values were below the ventilation threshold. Body weight was also assessed at each of these visits.

The exercise program consisted of 12 weeks of treadmill walking at a heart rate that elicited approximately 70% of

(∼80% of HRmax) 3 days a week for 30 minutes. Each training session included a 5-minute warm-up and 5-minute cooldown. All subjects completed 36 supervised exercise sessions over the 12-week period. Exercise sessions were completed on nonconsecutive days. Treadmill speed stayed constant throughout the 12 weeks, and incline was increased to elicit the desired heart rate. Based on

changes at 4 and 8 weeks, target HR was adjusted to elicit 70% of the new

. To ensure that the target intensity was maintained during each training session, subjects wore a Polar heart rate monitor and recorded their heart rate every 5 minutes under the supervision of research assistants.

Back to Top | Article Outline

Statistical Analyses

Total exercise energy expenditure (ExEE) for the 12-week study was estimated using 70% of

, adjusted every 4 weeks, minus predicted resting

(using 3.5 ml·kg−1·min−1), and an assumed respiratory exchange ratio of 0.85 (i.e., 4.86 kcal·L−1 of O2) using the equation below:

Based on body composition changes after the 12-week exercise program, standard values for the energy equivalents of fat (9,540 kcal·kg−1) and lean tissue (1,100 kcal·kg−1) (20) were used to determine energy balance (EB):

Therefore, total energy compensation (EEcomp, in kilocalories) was calculated by the sum of ExEE and EB. Subjects who had positive values for EEcomp were considered compensators and those with negative values were considered noncompensators. All statistical analyses were performed using SPSS Statistics 20 (IBM, Armonk, NJ, USA). Independent samples t-tests were used to compare baseline characteristics between groups. A 2-way repeated-measures analysis of variance was conducted to detect group, time, and group × time differences in each outcome variable. Paired samples t-tests were used to detect significant changes in the outcome variables in the groups separately. We conducted a Holm-Bonferroni sequential correction on the p values from t-tests to correct for p value inflation. Pearson's correlations were used to determine the relationships between fat mass change and other variables. Stepwise multiple linear regression analysis was used to determine predictors of fat mass change. All dependent variables were checked for normality using the Shapiro-Wilk test. An alpha level of p ≤ 0.05 was considered statistically significant.

Back to Top | Article Outline


Changes in Body Composition

Results of the Shapiro-Wilk test showed that all dependent variables were normally distributed, therefore meeting the assumptions of the parametric statistics used. Overall, there were no significant reductions in body weight, body fat, or waist circumference. Conversely, there was a significant increase in lean body mass (Table 1). More importantly, there was considerable individual variability in the changes in body weight (−11.7 to +4.8 kg), fat mass (−11.8 to +3.7 kg), and lean mass (−3.6 to +4.0 kg) (Figure 1).

Table 1

Table 1

Figure 1

Figure 1

Fifty-five (68%) of the 81 women were classified as compensators, i.e., having an energy value of fat and lean body mass changes that was less than the net ExEE (Table 2 and Figure 1). There were no significant differences between compensators and noncompensators for baseline body weight, body mass index, fat mass, body fat percentage, lean mass, waist circumference, or

(Table 2). Net ExEE did not differ between the 2 groups. Peak oxygen uptake increased in both compensators and noncompensators (p < 0.01), but there was no group × time interaction in the

change (p = 0.65). There were significant group × time interactions for body weight, body mass index, fat mass, and body fat percentage because of decreases in noncompensators and increases in compensators (Table 2).

Table 2

Table 2

Back to Top | Article Outline

Predictors of Fat Loss

Baseline body weight, fat mass, body fat percentage, lean mass,

and net ExEE were not significantly correlated with change in fat mass (Table 3). However, baseline submaximal exercise VE (r = −0.25) and energy expenditure (in kilocalories per minute) (r = −0.23) during minutes 2–4 of the baseline

test were significantly inversely correlated with the change in fat mass at 12 weeks (Table 3). Changes in body weight (r = 0.52), fat mass (r = 0.48), and body fat percentage (r = 0.27) at 4 weeks were also significantly correlated with change in fat mass at 12 weeks. Stepwise regression analysis that included all variables that were significantly correlated with change in fat mass at 12 weeks yielded a prediction model that explained 37% of the variance in fat mass change (R 2 = 0.37, p < 0.001) (Table 4). Changes in body weight and body fat mass at 4 weeks, as well as submaximal ExEE, were included in the final model, whereas submaximal exercise ventilation and change in body fat percentage at 4 weeks were excluded (Table 4).

Table 3

Table 3

Table 4

Table 4

Back to Top | Article Outline


Contrary to our hypothesis, fat mass change after 12 weeks of exercise training in premenopausal women was not related to initial body weight or fat mass. A number of exercise and caloric restriction studies reported that loss of body weight or fat was positively correlated with baseline body fat (9,14,17–19,40). Our results show that no baseline anthropometric measure was a significant predictor of fat loss. One potentially important finding was that the changes in body weight and fat mass at 4 weeks were moderately correlated (r = 0.52 and 0.48, respectively) with change in body fat mass at 12 weeks. During energy-restricted weight loss programs, early weight loss has been reported to be a significant predictor of subsequent weight loss (32). Our results suggest that this may also be true for exercise training. If so, monitoring weight or fat changes during the initial weeks of an exercise program might enable identification of potential compensators. Additional research may be able to demonstrate feasibility of using data on changes in body weight and body fat to address compensation and perhaps reduce overcompensation (i.e., unintended gain in body fat) with exercise training. In our study, compensators comprised approximately two-thirds of our study sample and, as a group, actually gained fat mass during exercise training (Table 2). As suggested in a recent review on resistance to exercise-induced weight loss (28), there is a need to identify factors that could be used to address the overcompensation phenomenon.

A novel finding of the current study is that VE and energy expenditure during minutes 2–4 of the incremental exercise test at baseline were negatively correlated with the change in body fat mass, i.e., higher VE and energy expenditure during the submaximal stages of the baseline incremental exercise test were associated with greater fat loss. Higher ExEE reflects reduced economy of walking, and this could conceivably offset compensatory factors that impede weight loss. The fact that submaximal ExEE, but not VE, remained in the final stepwise regression model suggests that walking economy may influence body fat loss in response to aerobic exercise training.

A higher exercise dose is likely to increase the chances of fat loss in response to training (2,6–8,26). However, regardless of the exercise dose, there is considerable individual variability in weight change after exercise training. Compensation is routinely observed in exercise training studies, but the mechanisms are not well understood. Downregulation of spontaneous physical activity has been reported in some (4,13,24,27,29) but not all studies (15,25). Increases in energy intake may also account for compensation (18,21,43,44). Woo et al. (44) reported that lean women may be more likely than obese women to increase energy intake in response to exercise training. If so, it could be expected that women with a greater fat mass or body fat percentage would be more likely to lose body weight or fat. Our results do not support this scenario because there were no statistically significant differences between compensators and noncompensators in baseline fat mass or body fat percentage. Furthermore, baseline body fat mass and body fat percentage were not correlated with changes in fat mass in our study. Additionally, both groups had the same amount of lean body mass, which suggests that lean body mass is not an important factor in determining compensatory responses to exercise training.

Net energy expenditure during exercise training sessions did not correlate with changes in fat mass, despite a more than 2.5-fold difference between low and high ends of the range of net ExEE among women (3,754–9,903 kcal). Similarly, a 13-week exercise program in overweight sedentary men showed that a cumulative exercise dose of approximately 27,000 kcal resulted in similar fat loss (−4.0 kg) as a dose of approximately 52,000 kcal (−3.8 kg) (31). This suggests that compensatory factors may be so dominant that ExEE cannot reliably be used to predict loss of fat mass with exercise training. In the DREW study, the highest exercise dose (12 kcal·kg−1·wk−1) resulted in energy compensation, whereas the lower exercise dosages (4 and 8 kcal·kg−1·wk−1) produced weight loss equal to expectations (3). However, expected weight loss was based on the assumption that the composition of lost body weight consisted of 70% fat tissue and 30% lean tissue, providing an energy value of 7,700 kcal·kg−1 (10,42). Our data illustrate that an assumed composition and energy value of weight loss (e.g., 7,700 kcal·kg−1) does not reflect the considerable individual variability in changes in both fat mass and lean body mass after exercise training (Figure 1). Although higher levels of net ExEE can produce greater weight loss and reduce the number of individuals who actually gain body weight or body fat (2,7), considerable individual variability remains.

The strengths of our study include the fact that exercise training sessions were supervised with intensity monitored continuously by heart rate monitors, aerobic capacity was assessed every 4 weeks to adjust training HR accordingly, and there was 100% adherence to exercise sessions. Additionally, energy compensation was determined by using actual changes in fat and lean mass, rather than estimated on the basis of assumed composition of weight loss (10,42).

Our study also has limitations. We did not assess energy intake, although we instructed our subjects throughout the study not to intentionally change their diet. Compensators may have increased energy intake in response to exercise training, as has been reported by King et al. (19). However, most studies show that marked individual variability in body weight or body fat changes in response to exercise training is not predicted by changes in energy intake (2,3,6,7,22,24). Even studies using very detailed and rigorous 7-day food records (24) and multiple dietary assessments throughout the intervention (7,22) did not show any difference in dietary intake between compensators and noncompensators. These findings may reflect the fact that self-report dietary instruments have been shown to be unreliable for accurate quantitative assessment of energy intake (23). We also did not monitor free-living physical activity outside our formal exercise training. The exercise dose in our study was below the recommended level for weight loss (5), resulting in a relatively low net ExEE. However, our exercise dose of 90 minutes per week of vigorous-intensity exercise is higher than the minimum recommendation for adults of 75 minutes per week of vigorous-intensity activity (12). Furthermore, because our exercise dose produced considerable heterogeneity in weight change in response to exercise training, our study design was sufficient to test our hypotheses.

In conclusion, our results demonstrate considerable individual variability in body weight and composition changes in response to aerobic exercise training in premenopausal women and that changes in fat mass were not predicted by baseline body weight or body fat, aerobic fitness level, or net ExEE. Changes in fat mass after 12 weeks of exercise training were, however, moderately correlated with changes in body weight and fat mass at 4 weeks and less so with change in body fat percentage at 4 weeks and with baseline submaximal exercise VE and energy expenditure. Further research is necessary to determine whether knowledge of these predictors can be used to enhance effectiveness of aerobic exercise for weight control. The fact that two-thirds of the women demonstrated compensation, and as a group gained fat mass after an exercise program consistent with current public health recommendations (12), suggests that this should be a high priority.

Back to Top | Article Outline

Practical Applications

Gain in body weight or body fat with aerobic exercise training is not considered a desirable outcome, yet is a consistent observation in controlled research settings and thus may be a common occurrence in clinical and professional practice. Since the change in body weight at 4 weeks was the strongest single correlate of body fat change after 12 weeks of exercise training, monitoring of body weight changes during the initial weeks of exercise training could prove to be useful in helping prevent unintended weight/fat gain in women who initiate an aerobic exercise program. Body weight is easy to measure and has the advantage over other predictors that may not be feasible outside a research setting (e.g., body composition testing, indirect calorimetry for assessment of energy expenditure) and therefore could potentially be used by coaches, personal trainers, and other professionals to assist individuals in achieving their weight loss goals and avoid unintended fat gain. Early identification of compensators through monitoring of body weight changes could lead to individualization of exercise programs to specifically fit the needs of each individual and prevent exercise-induced fat gain.

Back to Top | Article Outline


There are no conflicts of interest to report. No funding was received for this research. J.R.R. is supported by a training grant from the National Institute of Diabetes and Digestive and Kidney Diseases (T32-DK083250). The results of the present study do not constitute endorsement of the product by the authors or the National Strength and Conditioning Association.

Back to Top | Article Outline


1. Bouchard C, Tremblay A, Nadeau A, Dussault J, Despres J, Theriault G, Lupien P, Serresse O, Boulay M, Fournier G. Long-term exercise training with constant energy intake. 1: Effect on body composition and selected metabolic variables. Int J Obes 14: 57–73, 1990.
2. Caudwell P, Gibbons C, Hopkins M, King N, Finlayson G, Blundell J. No Sex difference in body fat in response to supervised and measured exercise. Med Sci Sports Exerc 45: 351–358, 2013.
3. Church TS, Martin CK, Thompson AM, Earnest CP, Mikus CR, Blair SN. Changes in weight, waist circumference and compensatory responses with different doses of exercise among sedentary, overweight postmenopausal women. PLoS One 4: e4515, 2009.
4. Colley RC, Hills AP, King NA, Byrne NM. Exercise-induced energy expenditure: Implications for exercise prescription and obesity. Patient Educ Couns 79: 327–332, 2010.
5. Donnelly JE, Blair SN, Jakicic JM, Manore MM, Rankin JW, Smith BK. American College of Sports Medicine Position Stand.Appropriate physical activity intervention strategies for weight loss and prevention of weight regain for adults. Med Sci Sports Exerc 41: 459–471, 2009.
6. Donnelly JE, Hill JO, Jacobsen DJ, Potteiger J, Sullivan DK, Johnson SL, Heelan K, Hise M, Fennessey PV, Sonko B. Effects of a 16-month randomized controlled exercise trial on body weight and composition in young, overweight men and women: The midwest exercise trial. Arch Intern Med 163: 1343–1350, 2003.
7. Donnelly JE, Honas JJ, Smith BK, Mayo MS, Gibson CA, Sullivan DK, Lee J, Herrmann SD, Lambourne K, Washburn RA. Aerobic exercise alone results in clinically significant weight loss for men and women: Midwest exercise trial 2. Obesity (Silver Spring) 21: E219–E228, 2013.
8. Donnelly JE, Smith BK. Is exercise effective for weight loss with ad libitum diet? Energy balance, compensation, and gender differences. Exerc Sport Sci Rev 33: 169–174, 2005.
9. Forbes GB. Body fat content influences the body composition response to nutrition and exercise. Ann N Y Acad Sci 904: 359–365, 2000.
10. Forbes GB, Kreipe RE, Lipinski B. Body composition and the energy cost of weight gain. Hum Nutr Clin Nutr 36: 485–487, 1982.
11. Gaesser GA, Poole DC. Lactate and ventilatory thresholds: Disparity in time course of adaptations to training. J Appl Physiol 61: 999–1004, 1986.
12. Garber CE, Blissmer B, Deschenes MR, Franklin BA, Lamonte MJ, Lee I, Nieman DC, Swain DP; American College of Sports Medicine. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: Guidance for prescribing exercise. Med Sci Sports Exerc 43: 1334–1359, 2011.
13. Goran MI, Poehlman ET. Endurance training does not enhance total energy expenditure in healthy elderly persons. Am J Physiol 263: E950–E957, 1992.
14. Hansen D, Astrup A, Toubro S, Finer N, Kopelman P, Hilsted J, Rössner S, Saris W, Van Gaal L, James W. Predictors of weight loss and maintenance during 2 years of treatment by sibutramine in obesity. Results from the European multi-centre STORM trial. Int J Obes Relat Metab Disord 25: 496–501, 2001.
15. Hollowell RP, Willis LH, Slentz CA, Topping JD, Bhakpar M, Kraus WE. Effects of exercise training amount on physical activity energy expenditure. Med Sci Sports Exerc 41: 1640–1644, 2009.
16. Jakicic JM, Winters C, Lang W, Wing RR. Effects of intermittent exercise and use of home exercise equipment on adherence, weight loss, and fitness in overweight women. JAMA 282: 1554–1560, 1999.
17. Jones P, Edwards D. Areas of fat loss in overweight young females following an 8-week period of energy intake reduction. Ann Hum Biol 26: 151–162, 1999.
18. King NA, Caudwell PP, Hopkins M, Stubbs JR, Naslund E, Blundell JE. Dual-process action of exercise on appetite control: Increase in orexigenic drive but improvement in meal-induced satiety. Am J Clin Nutr 90: 921–927, 2009.
19. King NA, Hopkins M, Caudwell P, Stubbs R, Blundell JE. Individual variability following 12 weeks of supervised exercise: Identification and characterization of compensation for exercise-induced weight loss. Int J Obes (Lond) 32: 177–184, 2008.
20. King NA, Hopkins M, Caudwell P, Stubbs RJ, Blundell JE. Beneficial effects of exercise: Shifting the focus from body weight to other markers of health. Br J Sports Med 43: 924–927, 2009.
21. King NA, Horner K, Hills AP, Byrne NM, Wood RE, Bryant E, Caudwell P, Finlayson G, Gibbons C, Hopkins M, Martins C, Blundell JE. Exercise, appetite and weight management: Understanding the compensatory responses in eating behavior and how they contribute to variability in exercise-induced weight loss. Br J Sports Med 46: 315–322, 2012.
22. Lamarche B, Despres JP, Pouliot MC, Moorjani S, Lupien PJ. Is body fat loss a determinant factor in the improvement of carbohydrate and lipid metabolism following aerobic exercise training in obese women? Metab Clin Exp 41: 1249–1256, 1992.
23. Lichtman S, Pisarska K, Berman E, Pestone M, Dowling H, Offenbacher E, Weisel H, Heshka S, Matthews D, Heymsfield S. Discrepancy between self-reported and actual caloric-intake and exercise in obese subjects. N Engl J Med 327: 1893–1898, 1992.
24. Manthou E, Gill JMR, Wright A, Malkova D. Behavioral compensatory adjustments to exercise training in overweight women. Med Sci Sports Exerc 42: 1121–1128, 2010.
25. McLaughlin R, Malkova D, Nimmo M. Spontaneous activity responses to exercise in males and females. Eur J Clin Nutr 60: 1055–1061, 2006.
26. McTiernan A, Sorensen B, Irwin ML, Morgan A, Yusui Y, Rudolph RE, Surawicz C, Lampe JW, Ayub K, Potter JD. Exercise effect on weight and body fat in men and women. Obesity (Silver Spring) 15: 1496–1512, 2007.
27. Meijer EP, Westerterp KR, Verstappen FTJ. Effect of exercise training on total daily physical activity in elderly humans. Eur J Appl Physiol Occup Physiol 80: 16–21, 1999.
28. Melanson EL, Keadle SK, Donnelly JE, Braun B, King NA. Resistance to exercise-induced weight Loss: Compensatory behavioral adaptations. Med Sci Sports Exerc 45: 1600–1609, 2013.
29. Morio B, Montaurier C, Pickering G, Ritz P, Fellmann N, Coudret N, Beaufrère B, Vermorel M. Effects of 14 weeks of progressive endurance training on energy expenditure in elderly people. Br J Nutr 80: 511–519, 1998.
30. Pasman WJ, Saris W, Westerterp-Plantenga MS. Predictors of weight maintenance. Obes Res 7: 43–50, 1999.
31. Rosenkilde M, Auerbach P, Reichkendler MH, Ploug T, Stallknecht BM, Sjodin A. Body fat loss and compensatory mechanisms in response to different doses of aerobic exercise-a randomized controlled trial in overweight sedentary males. Am J Physiol Regul Integr Comp Physiol 303: R571–R579, 2012.
32. Stubbs J, Whybrow S, Teixeira P, Blundell J, Lawton C, Westenhoefer J, Engel D, Shepherd R, Mcconnon A, Gilbert P, Raats M. Problems in identifying predictors and correlates of weight loss and maintenance: Implications for weight control therapies based on behavior change. Obes Rev 12: 688–708, 2011.
33. Stubbs RJ, Sepp A, Hughes DA, Johnstone AM, Horgan GW, King NA, Blundell JE. The effect of graded levels of exercise on energy intake and balance in free-living men, consuming their normal diet. Eur J Clin Nutr 56: 129–140, 2002.
34. Thomas D, Bouchard C, Church T, Slentz C, Kraus W, Redman L, Martin C, Silva A, Vossen M, Westerterp K. Why do individuals not lose more weight from an exercise intervention at a defined dose? an energy balance analysis. Obes Rev 13: 835–847, 2012.
35. Toombs RJ, Ducher G, Shepherd JA, De Souza MJ. The Impact of recent technological advances on the trueness and precision of DXA to assess body composition. Obesity (Silver Spring) 20: 30–39, 2012.
36. Torgerson JS, Carlsson B, Stenlöf K, Carlsson LMS, Bringman E, Sjöström L. A low serum leptin level at baseline and a large early decline in leptin predict a large 1-year weight reduction in energy-restricted obese humans. J Clin Endocrinol Metab 84: 4197–4203, 1999.
37. Troiano RP, Berrigan D, Dodd KW, Mâsse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc 40: 181, 2008.
38. Wadden TA, Bartlett S, Letizia KA, Foster GD, Stunkard AJ, Conill A. Relationship of dieting history to resting metabolic rate, body composition, eating behavior, and subsequent weight loss. Am J Clin Nutr 56: 203S–208S, 1992.
39. Wadden TA, Foster GD, Wang J, Pierson RN, Yang MU, Moreland K, Stunkard AJ, VanItallie T. Clinical correlates of short-and long-term weight loss. Am J Clin Nutr 56: 271S–274S, 1992.
40. Webster J, Garrow J. Weight loss in 108 obese women on a diet supplying 800 kcal/d for 21 d. Am J Clin Nutr 50: 41–45, 1989.
41. Westerterp KR, Meijer G, Janssen E, Saris W, Ten Hoor F. Long-term effect of physical activity on energy balance and body composition. Br J Nutr 68: 21–30, 1992.
42. Wishnofsky M. Caloric equivalents of gained or lost weight. Am J Clin Nutr 6: 542–546, 1958.
43. Woo R, Garrow J, Pi-Sunyer F. Voluntary food intake during prolonged exercise in obese women. Am J Clin Nutr 36: 478–484, 1982.
44. Woo R, Pi-Sunyer FX. Effect of increased physical activity on voluntary intake in lean women. Metabolism 34: 836–841, 1985.

weight loss; compensation; heterogeneity; walking; public health guidelines; vigorous-intensity exercise

Copyright © 2015 by the National Strength & Conditioning Association.