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A-30 Free Communication/Slide - Determinants of Body Weight and Weight Loss

Medicine & Science in Sports & Exercise: May 2013 - Volume 45 - Issue 5S - p 12–14
doi: 10.1249/01.mss.0000433605.38858.62

May 29, 2013, 9:30 AM - 11:00 AM

Room: Wabash 3

119 Chair: Ellen Evans, FACSM. University of Georgia, Athens, GA.

(No relationships reported)

120 May 29, 9:30 AM - 9:45 AM

Effect of a Lifestyle Intervention Prior to Bariatric Surgery on Objectively Measured Physical Activity in Severely Obese Adults

John M. Jakicic, FACSM, Melissa A. Kalarchian, Marsha D. Marcus, Anita P. Courcoulas, Michele D. Levine. University of Pittsburgh, Pittsburgh, PA.

(No relationships reported)

It is common for obese adults to be required to engage in a weight loss intervention prior to undergoing bariatric surgery. Few studies have quantified the effect that this requirement has on changes in objectively measured physical activity prior to bariatric surgery.

PURPOSE: To examine the effect of a 6-month behavioral lifestyle intervention (BLI) on physical activity compared to usual care (UC) prior to bariatric surgery.

METHODS: Data from 97 severely obese adults (BMI=47.0±5.9 kg/m2) seeking bariatric surgery were used for this study. These 97 subjects are a subset from a larger trial who provided complete physical activity and weight data. Subjects were randomized to UC (N=46) or BLI (N=51) for 6 months prior to approval for surgery. UC completed a non-standardized, physician supervised diet and activity program in the context of routine pre-surgical care. BLI consisted of 12 in-person sessions and 12 telephone contacts delivered over 6 months, and a diet and physical activity prescription of 1200-1400 kcal/d and 30 minutes per day, 5 days per week. Weight and objectively measured physical activity (SenseWear Pro Armband) were assessed at 0 and 6 months. Moderate-to-vigorous intensity physical activity (MVPA) was defined as bouts that were >10 minutes in duration and >3.0 METS (MVPA-10) and total minutes >3 METS (MVPA-TOT). Light physical activity (LPA) was defined as total minutes of activity between 1.5 to <3.0 METS.

RESULTS: MVPA-10 and MVPA-TOT increased in BLI (+24.4 min/wk and 39.4 min/wk, respectively) and decreased in UC (-11.0 min/wk and -53.7 min/wk, respectively) (p>0.005). LPA increased in BLI (+71.7 min/wk) and decreased in UC (-117.2 min/wk) (p=0.005). Weight loss was significantly greater in BLI (-9.6±7.7kg; -7.3±5.8%) versus UC (-3.8±5.3kg; -3.0±4.2%) (p<0.001).

CONCLUSION: In severely obese adults, participation in BLI resulted in modest increases in LPA and MVPA, which may have prevented decreases in MVPA and LPA as observed in UC. This may have contributed to the improved weight loss observed in BLI compared to UC. Further investigation is needed to determine whether these differences in physical activity pre-bariatric surgery influence weight loss success and physical activity behavior post-bariatric surgery.

Supported by the National Institutes of Health (R01 DK077102)

121 May 29, 9:45 AM - 10:00 AM

Energy Intake, Non-exercise Physical Activity And Successful Weight Loss: The Midwest Exercise Trial-2 (met-2)

Stephen D. Herrmann, Jeffery J. Honas, Erik A. Willis, Richard A. Washburn, FACSM, Joseph E. Donnelly, FACSM. University of Kansas Medical Center, Kansas City, KS.

(No relationships reported)

Changes in energy intake (EI) or non-exercise physical activity (NEPA) may affect the weight loss response to aerobic exercise training.

PURPOSE: To evaluate differences in EI and NEPA between responders (RS; weight loss ≥ 5%) and non-responders (NR; weight loss < 5%) performing 10 months of supervised aerobic exercise training.

METHODS: Seventy-four overweight/obese (BMI 25-39.9) sedentary young adults (18-30 years) completed a 10-month trial (i.e., ≥ 90% scheduled exercise sessions) of treadmill exercise (5 d.wk-1,70-80% max heart rate, supervised ≥4 d.wk-1) at either 2,000 (n = 37; 19 females) or 3,000 (n = 37; 18 females) kcal.wk-1. EI (kcal.d-1) was measured by picture-plate-waste and NEPA (min.d-1 of sedentary and moderate-to-vigorous activity [MVPA]) were assessed by Actigraph GT1M accelerometer over 7 consecutive days at baseline, and at months 3.5, 7, and 10. Participants were instructed to maintain baseline EI and NEPA during the 10 month intervention. T-tests for independent samples and Chi-Squares were used to assess statistical significance.

RESULTS: Mean weight change was -9.1 ± 3.7% and -0.7 ± 2.7% for RS and NR, respectively (p < 0.01). There were no significant baseline differences (p = 0.17) in EI (kcal.d-1) between RS (2817 ± 645) and NR (3036 ± 694). However, EI (kcal.d-1) during the intervention was significantly higher (p = 0.02) in NR (3065 ± 805) compared with RS (2669 ± 650). There were no significant differences (p > 0.05) between RS and NR for NEPA ( at baseline for either sedentary time (sedentary: RS = 604 ± 81, NR = 600 ± 101) or time spent in MVPA (MVPA: RS = 35 ± 17, NR = 40 ± 24), or during the 10 month intervention (sedentary: RS = 572 ± 63, NR = 571 ± 98), (MVPA: RS = 37 ± 11, NR = 36 ± 12). The proportion of participants classified as RS or NR did not differ by gender (χ2 (1) = 0.10, p = 0.75) or intervention group (2,000 kcal.wk-1 vs. 3,000 kcal.wk-1; χ2 (1) = 1.96, p = 0.16).

CONCLUSION: These results suggest that overweight and obese young adults who fail to achieve clinically significant weight loss (≥ 5%) in response to aerobic exercise training had a higher EI throughout the study than RS while NEPA remains unchanged in both groups. This may support targeting a modest EI deficit (∼300-500 kcal.d-1) in exercise NR.

Supported by NIH R01 DK49181

122 May 29, 10:00 AM - 10:15 AM

Changes In Three-Factor Eating Questionnaire Scores As Predictors Of Success In Weight Loss And Maintenance

Kate Lambourne, Stephen Herrmann, Amanda Szabo, Richard Washburn, FACSM, Joseph Donnelly, FACSM. University of Kansas Medical Center, Lawrence, KS.

(No relationships reported)

Weight loss is associated with decreased disinhibition and increased dietary restraint measured by the Three Factor Eating Questionnaire (TFEQ). However, it is not known if these eating behaviors are differentially associated with weight loss success and maintenance during a long-term weight management program.

PURPOSE: To examine changes in TFEQ scores as predictors of weight loss success (loss of 10% initial body weight) and weight maintenance (maintaining 10% loss) in an 18-month weight management trial.

METHODS: 395 overweight and obese adults (BMI 25-39.9, age 18-65) participated in 6 months of weight loss targeting ∼1,200-1,500 kcal/day and 300 min/week of moderate-to-vigorous exercise with a goal of accumulating 10,000 steps/day assessed by pedometer. Participants attended weekly clinics consisting of lessons on exercise, nutrition, and lifestyle modification. The participants then completed a 12-month maintenance phase in which they were provided with an energy intake prescription to maintain weight loss and the frequency of meetings was gradually reduced to once every two months. Logistic regression was used to examine whether TFEQ scores (retraint, hunger, disinhibition) predicted treatment success after controlling for baseline weight.

RESULTS: Increased restraint from baseline to 6 months was predictive of weight loss success (beta=-0.14, p < 0.001; R-square = 11.4%). Decreased disinhibition (beta=0.16, p = 0.009) and increased restraint (beta=-0.18, p < 0.001) from baseline to month 18 were predictive of success with weight maintenance at month 18 (R-square = 25.9%).

CONCLUSIONS: Dietary restraint was associated with greater weight loss success and both restraint and disinhibition were predictive of success with weight maintenance. These findings suggest that weight management strategies to modify eating behaviors may differ based on the treatment phase. While restraint is important during both weight loss and maintenance, it may be important to emphasize reducing opportunistic eating during maintenance because decreased disinhibition is associated with improved maintenance of weight loss.

Supported by NIH DK076063 and Health Management Resources, Boston, MA.

123 May 29, 10:15 AM - 10:30 AM

Anthropometric Predictors of Success in Behavioral Weight Loss Programs

Lynn A. Darby, FACSM1, Bonnie G. Berger1, Robert A. Carels1, Roberta L. Pohlman2, Kallie Hitchings1. 1Bowling Green State University, Bowling Green, OH. 2Wright State University, Dayton, OH.

(No relationships reported)

During behavioral weight loss programs (BWLPs) various anthropometric measurements [e.g., BMI, sagittal abdominal diameter (SAD) (Parr & Haight, 2006), waist and hip circumferences] are often used to monitor program success (Darby, Berger, Carels & Pohlman, 2012; Carels et al. 2008, 2009, 2010, 2011). Recently, Krakauer and Krakauer (2012) introduced a body shape index (ABSI) that uses waist circumference, BMI and height to include body size as well as body shape to track increased mortality risk. If an index such as ABSI can be used to predict weight loss, then BWLP’s may be designed to focus on those individuals who need “stepped care”.

PURPOSE: To investigate whether ABSI, SAD, or other anthropometric variables could be used to predict weight loss or desirable changes in physiological variables after BWLP’s.

METHODS: Data for four different BWLP’s (Carels et al. 2008-2011, Brownell, 2004) were combined to examine anthropometric changes in overweight and obese subjects [(N=127; Men, n=31; Women, n=96); Age=49±13 yr]. Dependent variables employed to measure program success were as follows: body weight (BW), ABSI, SAD, visceral adipose tissue (VAT), waist (WC) and hip (HC) circumferences, and Total Exercise Time (ExT) during a modified Balke treadmill GXT to ∼75% HR max.

RESULTS: All dependent variables changed significantly (ps < 0.05) pre- to post-program with the exception of WC/HC ratio and ABSI. Means ± S.D.’s for pre- and post-tests: BW (96.9±21.5, 92.9±21.5 kg); SAD (25.9±3.5, 24.3±3.5 cm); VAT (12.0±5.5, 10.3±4.8 lb); BMI (34.9±6.3, 33.5±6.4 kg/m2); % body fat (41.0±8.8, 38.6 ±9.2); WC (102 ±15, 98 ±15 cm); HC (119±15, 115±13 cm); ExT (567±256, 670±265 sec). Multiple regression analyses indicated that there were no significant anthropometric predictors of weight loss. Pre-BW was correlated with greater reductions in HC (r =0.19, p <0.003). In addition, pre-ABSI was correlated with SAD reduction (r =0.21; p <0.02) and VAT loss (r =0.26; p <0.003).

CONCLUSION: Although ABSI was not correlated with weight loss, both SAD and ABSI can be used to measure body shape changes in overweight and obese individuals.

124 May 29, 10:30 AM - 10:45 AM

Adaptive Thermogenesis in Response to Exercise-Induced Weight Loss Effects Both Energy Expenditure and Energy Intake

Mark Hopkins1, Catherine Gibbons1, Phillipa Caudwell1, Neil A. King2, Graham Finlayson1, John E. Blundell1. 1University of Leeds, Leeds, United Kingdom. 2Queensland University of Technology, Brisbane, Australia.

(No relationships reported)

A decline in resting energy expenditure (REE) above that expected based on body composition changes has been noted in some following dietary induced weight loss. However, it is unclear whether exercise induced weight loss is also characterised by a compensatory down regulation in REE, or whether this metabolic adaptation influences energy intake (EI).

PURPOSE: To examine the role of adaptive thermogenesis during exercise induced weight loss and its effect on compensatory eating during 12 weeks of aerobic exercise.

METHODS: Thirty overweight and obese women (BMI = 30.6 ± 3.6kg/m2) completed 12 weeks of supervised aerobic exercise (2500kcal.wk-1; 70% maximum heart rate). Body composition, REE, substrate oxidation, 24hr EI, subjective appetite and leptin were assessed at baseline and post intervention. To disclose adaptations in REE not explained by changes in fat mass (FM) and fat free mass (FFM), the difference between predicted and measured REE was calculated post intervention (metabolic adaptation; MA). REE was predicted from FM and FFM using an equation generated in a matched group of 66 overweight and obese women (BMI = 31.0 ± 3.9kg/m2).

RESULTS: Body mass (-1.3 ± 2.7kg; p = 0.03) and FM (-2.1 ± 2.3kg; p = 0.03) decreased significantly post intervention, with FFM (+0.6 ± 1.1kg; p = 0.06) and REE remaining stable (+71.6 ±; p = 0.25). While predicted and measured REE were similar post intervention (; p = 0.71), large individual variability existed and 43% of participants experienced a greater than expected decline in REE (-102.9 ± MA was associated with the change in leptin (-12.8 ± 34.8%; r = 0.47; p = 0.04), and the change in resting fat (r = 0.52; p = 0.01) and carbohydrate oxidation (r = -0.44; p = 0.02). MA was also associated with the change in EI (-131.0 ±; r = -0.44; p = 0.01) and fasting fullness (-17.0 ± 23.6%; r = 0.43; p = 0.02) during the intervention.

CONCLUSION: Marked variability existed in the metabolic response to exercise, with some individuals experiencing a greater than expected decline in REE. These individuals also displayed increased EI and reduced fullness, indicating that adaptive thermogenesis includes both biological and behavioural components in response to exercise induced weight loss. Supported by BBSRC grant BB/G005524/1.

125 May 29, 10:45 AM - 11:00 AM

Determinants Of Body Weight And Body Composition- What Is The Role Of Moderate And Vigorous Physical Activity?

Robin P. Shook, Gregory Hand, Amanda Paluch, James Hebert, Steven Blair, FACSM. University of South Carolina, COLUMBIA, SC.

(No relationships reported)

PURPOSE:Despite considerable examinations of the topic, the determinants of body weight and body composition are imprecisely known. Specifically, the role of total energy expenditure (TEE) and its components (e.g. physical activity level (PAL), moderate energy expenditure (MEE) and vigorous energy expenditure (VEE)) on body weight and composition in the literature is highly variable and inconsistent. The purpose of this analysis is to determine the relationship between TEE, PAL, and MEE and VEE on body weight and body composition in young adults.

METHODS: TEE was assessed using an arm-based physical activity monitor worn at all times for 10 consecutive days. RMR was measured using a ventilated hood system after a 12hr fast. Participants rested in a supine position under a ventilated hood for 30 minutes, followed by a 30 minute RMR gas collection period. PAL, a method used to express TEE relative to RMR, was calculated as PAL=TEE/RMR. Body weight (BW) and height were measured and body fat (BF) was calculated as the percentage of total weight identified as fat tissue by dual x-ray absorptiometry (DXA). Energy intake (EI) was assessed over a 14-day period via interviewer-administered dietary recalls.

RESULTS: 424 healthy adults (208 males and 216 females; mean age±standard deviation 27.6±4 years) participated in the study. The mean BMI for the sample was 25.4±4 with a mean percent BF of 28.1 (men: 20.8±8.4; women: 35.1±8.1, p<0.0001). Mean relative RMR was 2.96±0.4 mL/kg/min (men: 3.05±0.3; women: 2.88±0.4 mL/kg/min, p<0.0001). The mean TEE was 2516±564 (men: 2917±470; women: 2130±328 kcal/day, p<0.0001) and mean PAL was 1.59±0.19 (men: 1.66±0.2; women: 1.52±0.2, p=0.0001). MEE was higher for men compared with women (759±362 vs. 439±214 kcals/day, p<0.0001), as was VEE (68±77 vs. 38±47 kcals/day, p<0.0001). Multivariate models were created for the entire cohort to predict both body weight and body fat. The final model for the combined cohort included RMR, EE, MEE, PAL, and BF and explained 97% of body weight. Sex, EI, fitness, and RMR explained 79% of body fat.

CONCLUSIONS: The results of this study suggest TEE and the intensity of physical activity play an important role in determining body weight amount young adults. The determinants of BF are more complex and are related to sex, EI, RMR, and fitness.

© 2013 American College of Sports Medicine