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Exercise for Weight Loss: Further Evaluating Energy Compensation with Exercise.

ABSTRACT: PURPOSE:This study assessed how individuals compensate for energy expended during a 12-wk aerobic exercise intervention, elucidating potential mechanisms and the role exercise dose plays in the compensatory response. PARTICIPANTS AND DESIGN:Three-arm, randomized controlled trial among sedentary adults age 18 to 40 yr, body mass index of 25 to 35. Groups included six exercise sessions per week, two sessions per week, and sedentary control. METHODS:Rate of exercise energy expenditure was calculated from a graded exercise test averaged across five heart rate zones. Energy compensation was calculated as the difference between expected weight loss (based on exercise energy expenditure) and changes in fat and fat-free mass (DXA). Resting energy expenditure was assessed via indirect calorimetry and concentrations of acylated ghrelin, leptin, insulin, and Glucagon-like peptide 1 (GLP-1) were assessed fasting and postprandial (six timepoints over 2 h). RESULTS:The 6-d·wk group expended more energy (2753.5 kcal) and exercised longer (320.5 min) per week than the 2-d·wk group (1490.7 kcal, 1888.8 min, P < 0.05), resulting in greater fat loss compared with the 2-d or control groups (P < 0.05). Exercise groups did not differ in the % or total kcal compensated. Greater decreases in area under the curve (AUC) for acylated ghrelin predicted greater fat loss, regardless of group, energy expended per week, exercise duration, or exercise intensity. Changes in leptin AUC was the only independent predictor for energy compensation, with a greater decrease in leptin AUC predicting less energy compensation. Exercise frequency, energy expended, duration, or intensity did not influence energy compensation. CONCLUSIONS:Leptin is an important factor in successful weight loss through exercise, with greater postprandial decreases promoting less compensation. Greater amounts of exercise do not influence the compensatory response to an exercise-induced energy deficit.

SUBMITTER: Flack KD

PROVIDER: S-EPMC7556238 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Exercise for Weight Loss: Further Evaluating Energy Compensation with Exercise.

Flack Kyle D KD Hays Harry M HM Moreland Jack J Long Douglas E DE

Medicine and science in sports and exercise 20201101 11

<h4>Purpose</h4>This study assessed how individuals compensate for energy expended during a 12-wk aerobic exercise intervention, elucidating potential mechanisms and the role exercise dose plays in the compensatory response.<h4>Participants and design</h4>Three-arm, randomized controlled trial among sedentary adults age 18 to 40 yr, body mass index of 25 to 35. Groups included six exercise sessions per week, two sessions per week, and sedentary control.<h4>Methods</h4>Rate of exercise energy exp ...[more]

PMID: 33064415

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Project description:Background/objectivesCircadian physiology has been linked to body weight regulation and obesity. To date, few studies have assessed the association between exercise timing and weight related outcomes. The aim of this secondary analysis was to explore the impact of exercise timing (i.e., 24 h clock time of exercise session) on weight loss and components of energy balance.Subjects/methodsOverweight/obese (BMI 25.0-39.9 kg/m2), physically inactive, young adults (~51% female) completed a 10-month supervised exercise program (400 or 600 kcal/session for 5 days/week) or served as non-exercise controls (CON). Participants were categorized based on the time of day in which they completed exercise sessions (Early-Ex: >50% of sessions completed between 7:00 and 11:59 am; (n = 21), Late-Ex: >50% of sessions completed between 3:00 and 7:00 pm; (n = 25), Sporadic-Ex: <50% of sessions completed in any time category; (n = 24), and CON; (n = 18)). Body weight, energy intake (EI; digital photography), and non-exercise physical activity (NEPA; accelerometer) were assessed at baseline, 3.5, 7, and 10 months. Total daily energy expenditure (TDEE; doubly labeled water), was assessed at baseline and 10 months.ResultsAt month 10, weight loss was significantly greater in both Early-EX (-7.2 ± 1.2%; p < 0.001) and Sporadic-EX (- 5.5 ± 1.2%; p = 0.01) vs CON (+0.5 ± 1.0%), and Early-EX vs Late-EX (-2.1 ± 1.0%; p < 0.001). There were no between group differences for change in TDEE, EI, and non-exercise energy expenditure (P > 0.05). A significant group × time interaction (p = 0.02) was observed for NEPA (counts/min), however, after adjusting for multiple comparisons, group effects were no longer significant.ConclusionsDespite minimal differences in components of energy balance, Early-EX lost significantly more weight compared with Late-Ex. Although the mechanisms are unclear, the timing of exercise may be important for body weight regulation.

Project description:Research shows a positive relationship between dietary energy density (ED) and body mass index (BMI), but dietary ED of weight loss maintainers is unknown. This preliminary investigation was a secondary data analysis that compared self-reported dietary ED and food group servings consumed in overweight adults (OW: BMI=27-45kg/m(2)), normal weight adults (NW: BMI=19-24.9 kg/m(2)), and weight loss maintainers (WLM: current BMI=19-24.9kg/m(2) [lost?10% of maximum body weight and maintained loss for ?5years]) participating in 2 studies, with data collected from July 2006 to March 2007. Three 24-h phone dietary recalls from 287 participants (OW=97, NW=85, WLM=105) assessed self-reported dietary intake. ED (kcal/g) was calculated by three methods (food+all beverages except water [F+AB], food+caloric beverages [F+CB], and food only [FO]). Differences in self-reported consumption of dietary ED, food group servings, energy, grams of food/beverages, fat, and fiber were assessed using one-way MANCOVA, adjusting for age, sex, and weekly energy expenditure from self-reported physical activity. ED, calculated by all three methods, was significantly lower in WLM than in NW or OW (FO: WLM=1.39±0.45kcal/g; NW=1.60±0.43 kcal/g; OW=1.83±0.42 kcal/g). Self-reported daily servings of vegetables and whole grains consumed were significantly higher in WLM compared to NW and OW (vegetables: WLM=4.9±3.1 servings/day; NW=3.9±2.0 servings/day; OW=3.4±1.7 servings/day; whole grains: WLM=2.2±1.8 servings/day; NW=1.4±1.2 servings/day; OW=1.3±1.3 servings/day). WLM self-reported consuming significantly less energy from fat and more fiber than the other two groups. Self-reported energy intake per day was significantly lower in WLM than OW, and WLM self-reported consuming significantly more grams of food/beverages per day than OW. These preliminary findings suggest that consuming a diet lower in ED, characterized by greater intake of vegetables and whole grains, may aid with weight loss maintenance and should be further tested in prospective randomized controlled trials.

Project description:Introduction: Free-living movement (physical activity [PA] and sedentary behavior [SB]) and eating behaviors (energy intake [EI] and food choice) affect energy balance and therefore have the potential to influence weight loss (WL). This study explored whether free-living movement and/or eating behaviors measured early (week 3) in a 14-week WL programme or their change during the intervention are associated with WL in women. Methods: In the study, 80 women (M ± SD age: 42.0 ± 12.4 years) with overweight or obesity [body mass index (BMI): 34.08 ± 3.62 kg/m2] completed a 14 week WL program focused primarily on diet (commercial or self-led). Body mass (BM) was measured at baseline, and again during week 2 and 14 along with body composition. Free-living movement (SenseWear Armband) and eating behavior (weighed food diaries) were measured for 1 week during week 3 and 12. Hierarchical multiple regression analyses examined whether early and early-late change in free-living movement and eating behavior were associated with WL. The differences in behavior between clinically significant weight losers (CWL; ≥5% WL) and non-clinically significant weight losers (NWL; ≤ 3% WL) were compared. Results: The energy density of food consumed [β = 0.45, p < 0.001] and vigorous PA [β = -0.30, p < 0.001] early in the intervention (regression model 1) and early-late change in light PA [β = -0.81 p < 0.001], moderate PA [β = -1.17 p < 0.001], vigorous PA [β = -0.49, p < 0.001], total energy expenditure (EE) [β = 1.84, p < 0.001], and energy density of food consumed [β = 0.27, p = 0.01] (regression model 2) significantly predicted percentage change in BM. Early in the intervention, CWL consumed less energy dense foods than NWL [p = 0.03]. CWL showed a small but significant increase in vigorous PA, whereas NWL showed a slight decrease in PA [p = 0.04]. Conclusion: Both early and early-late change in free-living movement and eating behaviors during a 14 week WL program are predictors of WL. These findings demonstrate that specific behaviors that contribute to greater EE (e.g., vigorous PA) and lower EI (e.g., less energy-dense foods) are related to greater WL outcomes. Interventions targeting these behaviors can be expected to increase the effectiveness of WL programs.

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Exercise for Weight Loss: Further Evaluating Energy Compensation with Exercise.

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Exercise for Weight Loss: Further Evaluating Energy Compensation with Exercise.

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