Resistance Training Combined With Diet Decreases ...

“Resistance Training Combined With Diet Decreases Body Fat While Preserving Lean Mass Independent of Resting Metabolic Rate: A Randomized Trial” by Miller T et al. International Journal of Sport Nutrition and Exercise Metabolism © 2017 Human Kinetics, Inc.

Note: This article will be published in a forthcoming issue of the International Journal of Sport Nutrition and Exercise Metabolism. This article appears here in its accepted, peerreviewed form; it has not been copyedited, proofed, or formatted by the publisher. Section: Original Research Article Title: Resistance Training Combined With Diet Decreases Body Fat While Preserving Lean Mass Independent of Resting Metabolic Rate: A Randomized Trial Authors: Todd Miller1, Stephanie Mull1, Alan Albert Aragon2, James Krieger3, and Brad Jon Schoenfeld4 Affiliations: 1George Washington University, Milken School of Public Health, Washington, D.C. 2California State University, Northridge, CA. 3Weightology, LLC, Issaquah, WA. 4CUNY Lehman College, Department of Health Sciences, Bronx, NY. Running Head: Resistance training effects on fat loss Journal: International Journal of Sport Nutrition and Exercise Acceptance Date: August 17, 2017 ©2017 Human Kinetics, Inc.

DOI: https://doi.org/10.1123/ijsnem.2017-0221


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RUNNING TITLE: Resistance training effects on fat loss

Resistance training combined with diet decreases body fat while preserving lean mass independent of resting metabolic rate: A randomized trial Todd Miller1 Stephanie Mull1 Alan Albert Aragon2 James Krieger3 Brad Jon Schoenfeld4 1

George Washington University, Milken School of Public Health, Washington, D.C. California State University, Northridge, CA 3 Weightology, LLC, Issaquah, WA, USA 4 CUNY Lehman College, Department of Health Sciences, Bronx, NY 2

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Funding: The study was funded by a grant from the Sumner M. Redstone Global Center for Prevention and Wellness. The authors declare no conflicts of interest.


Abstract The purpose of this study was to determine the effects of resistance training only (RT n=10), dietary intervention only (DIET n=10), resistance training plus diet (RT+DIET n=10) and control (CON n=10) on body composition and resting metabolic rate (RMR) in a cohort of 40 premenopausal female volunteers. Subjects in DIET and RT+DIET were provided with daily


macronutrient and calorie goals based on DXA and RMR tests, with protein maintained at 1.4 g/kg/day. Subjects in the RT and RT+DIET groups performed a supervised progressive RT program consisting of exercises for all the major muscle groups of the body. Results showed a significant month-by-group interaction for change in fat mass with no significant linear trend for control. The three treatment groups all showed significant linear decreases in fat mass, but the slope of the decrease became progressively steeper from the RT, to DIET, to RT+DIET. A significant linear increase for lean mass was seen for resistance training-only. There was a nonsignificant increase in RMR in all groups from Month 0 to Month 4 but no significant month by group interaction. In conclusion, significant reductions in fat mass were achieved by all experimental groups, but results were maximized by RT+DIET. Only the RT group showed significant increases in lean mass. Keywords: Body composition, strength training, fat-free mass


Introduction Aerobic exercise (AE) is commonly recommended as the most effective exercise modality for weight loss (Haskell et al., 2007). The American College of Sports Medicine (ACSM) position stand on physical activity for weight loss recommends 150-250 minutes per week of moderate intensity physical activity (Donnelly et al., 2009). While the ACSM promotes resistance training


(RT) as a means of increasing fat free mass, which should lead to improved body composition, it does not promote RT for losing significant amounts of body fat. Similarly, the United States Public Health Service physical activity guidelines for weight loss do not mention RT at all as a viable exercise modality for weight loss. This is not surprising, as there is a paucity of research examining the effects of RT on weight loss. Furthermore, the few studies that have explored RT for weight loss generally show that it is ineffective (Olson, Dengel, Leon, & Schmitz, 2007; Willis et al., 2012). Indeed, the effectiveness of any weight loss program is dependent on the size of the caloric deficit that is created over time, and since AE generally burns more calories per unit of time than RT (Donnelly et al., 2009), it stands to reason that AE would be the most commonly prescribed type of exercise for losing weight. Contributing to the exclusion of RT for weight loss is a widespread belief among dietitians, nutritionists and exercise professionals that it is not possible to induce hypertrophy while in a caloric deficit, and since the creation of a caloric deficit is essential for fat loss, the use of RT for muscle growth in a caloric deficit is counter-intuitive. These beliefs continue to exist despite emerging evidence to the contrary (Josse, Atkinson, Tarnopolsky, & Phillips, 2011; Longland, Oikawa, Mitchell, Devries, & Phillips, 2016). RT has been shown to elevate resting metabolism for an extended period of time following cessation of the training session (Stiegler & Cunliffe, 2006). Additionally, having a greater muscle mass should lead to a greater resting metabolism (Gallagher et al., 1998). Unlike RT, chronic AE


performed in a caloric deficit (which is often the recommendation for effective weight loss) has the potential to lead to significant decreases in muscle mass, thereby hampering improvements in body composition (Swift, Johannsen, Lavie, Earnest, & Church, 2014). Ideally, a program designed to improve body composition should do so through the loss of fat alone, with muscle mass being maintained or increased. This is particularly important to premenopausal females, as


it has been reported that major weight gain occurs in women at a rate twice that of men, and is highest in persons aged 25-34 (Williamson, Kahn, Remington, & Anda, 1990). Moreover, women have lower baseline levels of muscle mass compared to men, and thus are at greater risk of negative complications when muscle proteins are lost during dieting. Several reasons could exist for the lack of effectiveness of RT reported in most weight loss studies (Donnelly et al., 2009). Possible explanations include, but are not limited to, 1) a lack of control and/or measurement of caloric intake; 2) failure to adjust dietary protein needs to support muscle growth; and 3) an inadequate RT stimulus. Case studies of clients from our laboratory have routinely demonstrated that substantial decreases in body fat can be induced with RT as the exclusive form of exercise. Furthermore, these decreases in body fat occur with concomitant increases in muscle mass, while in a caloric deficit. The purpose of this study was threefold: 1) To determine whether RT combined with dietary intervention (RT+DIET) results in greater improvements in body composition compared with RT or DIET alone in overweight/obese premenopausal women; 2) To determine whether RT combined with dietary intervention (RT+DIET) results in greater improvements in fat mass in the visceral depot compared with RT or DIET alone, and; 3) To determine whether concomitant increases in muscle mass and decreases in fat mass can occur while in a caloric deficit.


Methods Subjects Subjects were a convenience sample of 40 female volunteers (Body mass = 87.4±12.6; Height = 165.7±7; Age = 32.3±4.8; BMI = 31.9±4.4). The sample size was based on previous research by Jabekk (Jabekk, Moe, Meen, Tomten, & Hostmark, 2010) using change in fat mass as


the outcome measure with a target effect size difference of 0.4, alpha of 0.05 and minimum power of 0.80. Recruitment took place from 4/1/16 to 5/14/16, and follow up took place from 8/15/16 to 9/16/16. The following inclusion criteria had to be met for participation: 1) women between 25-40 years of age; 2) regular menstrual cycle; 3) body fat >30%; 4) normally active; 5) not currently meeting CDC physical activity guidelines; 6) no organized weight training within past 1 year; 7) not currently dieting or food logging. Exclusion criteria included: 1) Subjects who do not have the ability to exercise based on a Physical Activity Readiness questionnaire; 2) history of an eating disorder; injury or medical issue that would prohibit them from resistance training; 3) pregnant or nursing. Following recruitment, subjects were given a screening questionnaire either in-person, electronically (via email), or verbally (via phone), in order to determine whether they were viable candidates. Informed consent was obtained at the time of screening. The study was conducted according to the Declaration of Helsinki, and was approved by the local University Ethics Committee. Random sequences were generated by the PI using a random number generator app from https://www.random.org/. A 40 number sequence was randomly produced by the app. Subjects were then asked by the PI to press the button on the app, and were randomly assigned to one of 4 groups based on the following result from the app: 0-10 = Control (CON n=10); 11-20=


Dietary intervention only (DIET n=10); 21-30 = Resistance Training only (RT n=10); 31-40 = Resistance Training plus Diet (RT+DIET n=10). Testing: Subjects meeting criteria as defined by the screening survey reported to the University lab for secondary screening at 9:00 a.m. following an overnight fast. Body composition was then


measured via Dual Energy X-ray Absorptiometry (iDXA, Lunar; GE Medical Systems, Madison, WI, USA). All DXA scans were analyzed using enCORE 2012 software, version 14.1 to determine total percentage of fat and lean tissue, bone mineral content and visceral adipose tissue. Subjects were instructed to report to the lab after an overnight fast having refrained from exercise for 48 hours and to remain normally hydrated prior to body composition and RMR assessment. After DXA scanning, subjects underwent testing for resting metabolic rate (RMR) via indirect calorimetry to determine daily resting caloric expenditure. Subjects sat quietly in a reclined position and breathed normally for 10-12 minutes through a one-way valve with the nose plugged. The subject inhaled normal room air, and exhaled air was continuously collected and sent to a KorrReeVue indirect calorimeter (Korr Medical Technologies, Salt Lake City, UT USA). RMR was calculated by the calorimeter (Korr ReeVue, Salt Lake City, UT), which automatically begins collecting gas when it detects the first breath into the machine and then stops automatically once the collection time is complete. Follow-up DXA scans were obtained at weeks 4, 8, 12 and 16 and RMR testing was repeated at week 16.


Diet Subjects in DIET and RT+DIET groups met individually with a registered dietitian and were given daily macronutrient and calorie goals based on their DXA and RMR tests. Calculation of daily caloric intake was based on the Harris-Benedict equation as follows with the objective of energy-restriction: If the RMR was within 10% of the predicted RMR, intake was set at the RMR;


if the RMR was greater than 10% over the predicted, intake was set at 10% below the measured RMR; if the RMR was greater than 10% below the predicted, intake was set at 10% above the measured RMR. Fat intake was set at 20% of total calories. Protein intake was calculated using a factor of 3.1 g of protein per kg of fat free mass (Helms, Zinn, Rowlands, & Brown, 2014). Carbohydrate made up the balance of the remaining calories. Subjects in the DIET and RT+DIET groups began following the prescribed caloric and macronutrient goals as established in their meeting with the dietitian within one week of the initial meeting and continued this regimen over the entire course of the study. To track nutritional consumption, subjects were familiarized with the usage of a phone app & website for food logging (fatsecret.com). During the course of the study, subjects logged all of their foods daily into the fatsecret app and the data were then analyzed to determine total energy and macronutrient intake. Exercise Within two weeks following initial screening, subjects in the RT and RT+DIET groups reported to Power Train Sports and Fitness (www.powertrainsports.com) for an exercise familiarization session. Subjects met with a certified trainer from Power Train who walked them through the exercise program, taught proper exercise form, and establish appropriate training loads.


The RT intervention began within one week following the exercise familiarization session. All training sessions were performed under the individual supervision of a certified personal trainer from Power Train. Training sessions continued at a rate of 2-3 per week (depending on training phase) for 16 weeks. The RT intervention consisted of two separate workout complexes that were alternated


every 4 weeks for the duration of the 16-week study. Exercise complex one consisted of Squats, Romanian Deadlifts, Swiss Ball Squats, Bench Press, Lat Pulldown, Dumbbell Shoulder Press, Incline Dumbbell Fly, Seated Row, Dumbbell Lateral Raise and Low Back Hyperextensions. Exercise complex two consisted of Deadlifts, Leg Curls, Leg Extensions, Incline Dumbbell Press, Close Grip Pulldowns, Arnold Press, Cable Crossover, Chest Supported Dumbbell Row, Face Pulls and Low Back Hyperextension. Each exercise was completed for 4 sets of 10-12RM. Rest periods between sets were between 60-90 seconds. Subjects trained 3 times per week for weeks 13 of each month, then trained twice weekly during the 4th week of each month. Training loads for a given exercise were increased when the subject could complete greater than 12 reps on the first set, or when she could complete 12 reps on all 4 sets. Loads were progressively increased in order to keep the RM in the 10-12 range. Statistics Data were modeled using a linear mixed model for repeated measures, estimated by a restricted maximum likelihood algorithm, with drop-outs removed from the dataset. Diet intervention (control, diet, resistance training, resistance training + diet) was included as the between-subject factor, month (0, 1, 2, 3, 4) was included as the repeated within-subjects factor, month x intervention was included as the interaction, and subject was included as a random effect. In cases where significant interactions were present, linear time trends of within-group changes


were analyzed using linear mixed models for repeated measures. Comparisons of statistically significant slopes for linear time trends were done using t-tests with a Holm-Bonferonni correction for multiple comparisons.. Degrees of freedom were calculated using a Satterthwaite approximation. Comparisons between self-reported dietary data were performed using independent t-tests. All analyses were performed using package lmertest in R version 3.3.1 (The


R Foundation for Statistical Computing, Vienna, Austria). Effects were considered significant at P ≤ 0.05. Data are reported as x ± SD unless otherwise specified. Results A total of 31 subjects completed the study, with 9 dropouts (Control: n=8; RT: n=9; DIET: n=9; RT+DIET: n=5). The reasons for the dropouts are as follows: 1 subject got deployed; 1 subject moved; 2 subjects suffered work-related injuries not connected to the study; and 5 subjects ceased participation for unknown personal reasons. Outcomes for all variables are presented in Table 1. One-way ANOVA was used to compare baseline characteristics between groups. There were no significant differences in age (P = 0.73), body mass (P = 0.67), fat mass (P = 0.81), FFM (P = 0.63), BMC (P = 1.0), or RMR (P = 0.83). Based on review of self-report dietary logs and estimates of energy expenditure, diet-only achieved a daily energy restriction of ~502 kcal while training+diet achieved a daily energy restriction of ~632 kcal.

Body Weight There was a significant month by group interaction (P = 0.02). There was no significant linear trend for control (β = 0.41; 95% CI = -1.08, 1.90; P = 0.58) or resistance-training-only groups (β = 0.18; 95% CI = -0.36, 0.73; P = 0.51). There were similar significant linear decreases for the diet-only (β = -1.35; 95% CI = -2.03, -0.67; P = 0.0004) and resistance training+diet groups (β = 1.68; 95% CI = -2.51, -0.85; P = 0.0006). See Figure 1.


Percent Fat There was a significant month by group interaction (P = 0.004). There was no significant linear trend for control (β = 0.07; 95% CI = -0.12, 0.26; P = 0.45). There were similar significant linear decreases for the diet-only (β = -0.40; 95% CI = -0.54, -0.26; P = 0.0), resistance-training only (β = -0.38; 95% CI = -0.57, -0.19; P = 0.0003), and resistance-training+diet groups (β = -


0.53; CI = -0.74, -0.33; P < 0.0001). See Figure 2. Fat Mass There was a significant month by group interaction (P = 0.003). There was no significant linear trend for control (β = 0.38; 95% CI = -0.62, 1.37; P = 0.46). The three treatment groups all showed significant linear decreases in fat mass, but the slope of the decrease became progressively steeper from the resistance-training only group, to the diet-only group, to the resistancetraining+diet group (resistance training-only: β = -0.58; 95% CI = -1.02, -0.14; P = 0.01; dietonly: β = -1.35; 95% CI = -1.87, -0.83; P = 0.0; resistance training+diet: β = -1.80; 95% CI = 2.43, -1.17; P < 0.0001). See Figure 3. When comparing the three statistically significant slopes for fat mass using t-tests corrected for multiple comparisons by Holm-Bonferroni, resistance training+diet showed a significantly greater slope than resistance training-only (P = 0.0019 tested at 0.017 Holm-Bonferonni threshold); diet-only showed a non-significantly greater slope than resistance training-only (P = 0.027 tested at 0.025 Holm-Bonferonni threshold). There was no significant difference between resistance training+diet and diet-only (P = 0.29). Lean Mass There was nearly a significant month by group interaction (P = 0.052). There was no significant linear trend for control (β = 0.03; 95% CI = -0.52, 0.57; P = 0.93), diet-only (β = -0.004; CI = -0.30, 0.29; P = 0.98), or resistance training+diet (β = 0.11; 95% CI = -0.40, 0.62; P = 0.67).


There was a significant linear increase for resistance training-only (β = 0.76; 95% CI = 0.32, 1.2; P = 0.002). See Figure 4. Bone Mineral Content There was no significant month by group interaction (P = 0.077). There were no significant linear trends for any groups (Control: β = -0.003; 95% CI = -0.01, 0.01; P = 0.60; Diet-Only: β =


-0.01; 95% CI = -0.03, 0.004; P = 0.16; Resistance Training-Only: β = 0.009; 95% CI = -0.004, 0.02; P = 0.17; Resistance Training+Diet: β = 0.008; 95% CI = -0.01, 0.03; P = 0.46). VAT There was no significant month by group interaction (P = 0.20), group effect (P = 0.86), or month effect (P = 0.14) for VAT. Resting Metabolic Rate (RMR) There was no significant month by group interaction (P = 0.79) or group effect (P = 0.76). There was a non-significant (P = 0.092) increase in RMR in all groups from Month 0 to Month 4. There were no significant interactions or main effects for RMR as a percentage of the predicted value, with p-values ranging from 0.28 – 0.58 (pertaining to both the interaction term in the model, and the two main effects)

Self-Reported Dietary Data Self-reported dietary data are shown in Table 2. There were no significant differences between the diet-only and diet+training groups for self-reported calorie intake (P = 0.49), carbohydrate intake (P = 0.31), fat intake (P = 0.71), or protein intake (P = 0.62). There were also no significant differences between groups for percentage of goals for calorie intake or macronutrients (P = 0.23 – 0.75).


Group dietary time trends are shown in Table 2. There was no significant month by group interaction for calories (P = 0.40), protein (P = 0.77), or carbohydrate (P = 0.44). There were no main effects of group for calories (P = 0.45), protein (P = 0.44), or carbohydrate (P = 0.31), nor were there main effects of time for calories (P = 0.23), protein (P = 0.09), or carbohydrate (P = 0.41). There was a significant month by group interaction for fat (P = 0.02). There was a significant


linear trend for fat to decrease in the diet only group (β = -1.20; CI = -2.30, -0.10; P = 0.04), whereas there was no trend in the diet and training group (P = 0.51). Discussion The study produced several notable findings. First, while reductions in fat mass were achieved by all experimental groups, results were maximized by combining of RT and diet. Second, only the RT group showed significant increases in lean mass; combining RT with diet attenuated these increases. Finally, RMR remained unchanged over the course of the study period for all conditions; changes in lean mass did not significantly affect this outcome. The well-established negative effects of excess body fat on health and wellness underscore the importance of determining effective strategies for weight loss. All treatments produced significant reductions in fat mass over the 16 week study period, with the exception of RT-only, which showed a decrease in fat mass at months 1-3, but an increase in fat mass at month 4. These losses persisted in a linear fashion across each month of the study, with the slope of the decrease becoming progressively steeper from RT-only to DIET-only to RT+DIET. Although RT-only did not receive any nutritional prescription and were told not to make any modifications to their usual diet, this group apparently was in a hypocaloric state during the initial 3 months of the trial, perhaps inspired by a desire to realize additional benefits upon initiating an exercise program. The increase in fat mass at the fourth month may have reflected a lapse in eating restraint due to an absence of


dietary programming. These results reinforce the fact that nutritional intervention combined with exercise is paramount with respect to fat loss, with exercise providing a supplemental but important role in the process. Illustrating this point, a systematic review and meta-analysis by Clark (Clark, 2015) found that diet plus RT or a combination of RT and AE had a greater impact on improving body composition than diet alone. In a study specific to resistance training, Bouchard et al


(Bouchard, Soucy, Senechal, Dionne, & Brochu, 2009) compared the effects of caloric restriction (CR), resistance training (RT), or a combination of the two (CR + RT) in a cohort of obese postmenopausal women. Significant fat loss occurred in CR and CR + RT, but not RT alone. The maintenance of high levels of muscle mass has implications on physical function, and plays a role in the prevention of common pathologic conditions and chronic diseases (Wolfe, 2006). In this regard, only the RT group showed a significant increase in lean mass, with subjects gaining 2.2 kg over the 16 week study period. In the absence of caloric restriction, lean mass gains via resistance training are expected, especially in untrained subjects. In an investigation with a similar subject profile (obese women age 20-40 yrs in nondieting conditions), Jabekk et al (Jabekk et al., 2010) reported that the nondieting control group gained 1.5 kg FFM during 10 weeks of RT. Assuming the same rate of gain extended another 6 weeks to match the length of the present study, this would have amounted to 2.4 kg FFM; which is consistent with the gain of 2.2 kg seen in the present study. In contrast with recent studies (Josse et al., 2011; Longland et al., 2016), the RT+DIET group did not show significant increases in lean mass over the duration of the study. However, it should be noted that there was a linear increase over the first 12 weeks of the study, with an apparent loss of these gains during the final month. The reason for this finding is not readily apparent. An additional consideration is that water is the predominant and most widely fluctuating component of FFM due to varying glycogen concentrations, electrolyte balance


influencing hydration, and other factors. Therefore, increases in FFM are not necessarily accompanied by directly proportional increases in contractile protein and do not necessarily reflect gains in muscle mass. Interestingly, the diet-only group did not lose any FFM over the 16 week intervention period. Research generally shows a loss of lean tissue concomitant to a caloric deficit. It is


conceivable that the high-protein content of the diet (3.1 g/kg/FFM) helped to offset any such losses. In support of this, a systematic review by Helms et al (Helms et al., 2014) reported that lean, resistance-trained subjects in hypocaloric conditions required a protein intake of 2.3-3.1 g/kg FFM in order to maximally protect against lean tissue losses. In addition, the present study did not involve particularly aggressive caloric restriction (1419 & 1505 kcal/day in DIET and RT + DIET, respectively). Despite rigorous efforts to ensure compliance to the diet (i.e. weekly review of food logs, ongoing email support for dietary tracking, and monthly meetings with the dietician to answer any diet-related questions), there nevertheless is the possibility of under-reporting of caloric intake. Lichtman et al (Lichtman et al., 1992) found that obese subjects under-reported their intake by an average of 47% (a group mean of 1053 kcal/day). Thus, in addition to the non-aggressively prescribed caloric deficit, the potential for under-reporting total energy combined with the high protein intake target could have spared FFM. There were no significant changes in RMR noted from pre- to post-study in any of the conditions studied. Our results on the topic concur with the body of literature, which shows that changes in lean mass do not necessarily parallel changes in RMR (Stiegler & Cunliffe, 2006). Although there is a clear metabolic cost of maintaining lean mass, the actual energy expenditure associated with skeletal muscle is rather low, estimated at only ~13 kcal/kg per day (Wang et al., 2011). Aristizabal et al. (Aristizabal et al., 2015) recently investigated the possibility of estimating


RMR responses in resistance-training subjects via DXA-measured changes in FFM. Although there was a large degree of interindividual variability, 9 months of resistance training and supplementation with either protein or carbohydrate increased RMR by an average of 5%, and FFM (among other factors) was positively correlated with this small but significant increase. In light of this finding, it is possible that the present study would need a longer duration to detect


significant changes in RMR. Our study had several notable limitations that must be considered when making evidencebased inferences from the data. First, although DXA is a well-established modality for estimating body composition, the measurement of lean mass is specific to all non-fat and bone-free components, and thus does not necessarily reflect changes in skeletal muscle. Second, given that the subjects were premenopausal women, menstrual changes may have altered observed changes in body composition. Third, the findings are specific to obese, premenopausal women and cannot necessarily be generalized to other populations. Finally, the sample size was rather small, thereby limiting statistical power for probability assessment. Conclusion Findings of this study indicate that a total-body RT program combined with a caloric deficit is a viable strategy for reducing body fat while preserving lean mass in obese, premenopausal women. Positive results do not appear to be related to increases in RMR. Given the health-related implications for carrying excess body fat, these findings indicate that diet is the paramount consideration for combating obesity and combining nutritional prescription with RT appears to help optimize changes in body composition.


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Figure 1. Effect of experimental conditions on changes in body weight in Diet Only, Resistance Training Only, and Resistance Training + Diet groups for each month across the duration of the study. * denotes significant linear trend



Figure 2. Effect of experimental conditions on changes in percent body fat in Diet Only, Resistance Training Only, and Resistance Training + Diet groups for each month across the duration of the study. * denotes significant linear trend



Figure 3. Effect of experimental conditions on changes in fat mass in Diet Only, Resistance Training Only, and Resistance Training + Diet groups for each month across the duration of the study. * denotes significant linear trend



Figure 4. Effect of experimental conditions on changes in lean mass in Diet Only, Resistance Training Only, and Resistance Training + Diet groups for each month across the duration of the study. * denotes significant linear trend


TABLE 1: Outcomes for all variables across time (mean ± SD) Outcome Body Weight (kgs)*


Percent Fat*

Fat Mass (kgs)*

Lean Mass (kgs)

BMC (kgs)

VAT (kgs)

RMR (kcal/d)

Group Control

Month 0 86.0 ± 15.2

Month 1

Month 2

Month 3

Month 4 86.8 ± 18.0

Diet** Training Training + Diet** Control Diet** Training** Training + Diet** Control

82.0 ± 11.3 85.9 ± 15.3 91.1 ± 4.4

80.9 ± 10.5 86.1 ± 15.2 90.1 ± 4.5

80.3 ± 10.3 86.1 ± 15.3 89.5 ± 4.6

79.5 ± 10.3 85.8 ± 15.3 88.8 ± 3.8

79.7 ± 10.2 88.3 ± 16.0 88.0 ± 4.0

42.7 ± 4.0 42.8 ± 5.9 42.9 ± 4.9

43.3 ± 6.5 42.2 ± 4.0 43.1 ± 6.6 43.3 ± 4.5

Diet** Training Training + Diet** Control

36.4 ± 7.9 38.6 ± 11.0 41.3 ± 5.1

Diet Training** Training + Diet Control Diet Training Training + Diet Control Diet Training Training + Diet Control Diet Training Training + Diet

43.0 ± 4.6 44.7 ± 6.4 47.1 ± 4.5

43.0 ± 4.6 45.6 ± 6.7 47.6 ± 4.5

43.0 ± 4.7 46.0 ± 6.7 47.6 ± 4.4

42.7 ± 4.5 45.8 ± 6.0 48.0 ± 4.3

43.1 ± 4.6 46.9 ± 6.5 47.1 ± 4.7

2.7 ± 0.3 2.7 ± 0.4 2.7 ± 0.5 5.9 ± 0.4

2.7 ± 0.4 2.7 ± 0.4 5.9 ± 0.3

2.7 ± 0.4 2.7 ± 1.0 5.9 ± 0.4

2.7 ± 0.4 2.7 ± 0.4 5.9 ± 0.4

2.7 ± 0.3 2.7 ± 0.5 2.7 ± 0.5 5.9 ± 0.3

0.9 ± 0.4 0.8 ± 0.5 0.8 ± 0.5 0.9 ± 0.4

0.7 ± 0.5 0.8 ± 0.5 0.9 ± 0.4

0.7 ± 0.4 0.8 ± 0.6 0.9 ± 0.4

0.7 ± 0.4 0.8 ± 0.5 0.8 ± 0.4

1.0 ± 0.5 0.7 ± 0.4 0.9 ± 0.6 0.8 ± 0.3

43.0 ± 6.0 44.0 ± 4.4 44.3 ± 6.0 45.3 ± 4.7

43.3 ± 4.5 43.4 ± 6.0 44.2 ± 4.7

42.9 ± 4.2 42.9 ± 5.7 43.8 ± 4.6

37.5 ± 10.5

38.1 ± 12.1 35.2 ± 7.4 37.8 ± 10.7 39.9 ± 5.0

34.7 ± 7.0 37.4 ± 10.5 39.2 ± 5.1

34.1 ± 7.0 37.3 ± 11.0 38.2 ± 5.2

45.9 ± 6.9

33.9 ± 6.8 38.6 ± 11.7 38.0 ± 4.4 46.0 ± 8.0

1494 ± 193 1484 ± 232 1525 ± 174 1595 ± 334

* = significant group x month interaction (P < 0.05) ** = significant linear time trend within group (P < 0.05)

1624 ± 301 1563 ± 216 1544 ± 190 1673 ± 175


TABLE 2: Self-Reported Dietary Intake of Energy and Macronutrients for Each Month of the Study (mean ± SD) Aggregate Dietary Data


Kcal Protein (g) Carbohydrate (g) Fat (g)

Kcal Protein (g) arbohydrate (g) Fat (g) *

Diet Diet+Training Diet Diet+Training Diet Diet+Training Diet** Diet+Training

Diet Only 1419 ± 183 114 ± 21 145 ± 24 42 ± 5 Dietary Data by Month

Diet + Training 1505 ± 223 120 ± 23 159 ± 22 41 ± 7

Month 1 1439 ± 104 1467 ± 319 108 ± 17 118 ± 27 147 ± 18 154 ± 36 46 ± 5 39 ± 8

Month 3 1397 ± 294 1533 ± 219 110 ± 34 122 ± 27 143 ± 32 164 ± 32 40 ± 8 42 ± 7

* = significant group x month interaction (P < 0.05) ** = significant linear time trend within group (P < 0.05)

Month 2 1441 ± 179 1574 ± 211 116 ± 20 130 ± 20 147 ± 27 165 ± 23 42 ± 6 42 ± 8

Month 4 1401 ± 186 1448 ± 198 108 ± 23 112 ± 29 143 ± 25 154 ± 25 42 ± 5 41 ± 6