Can Reverse Dieting Prevent Weight Regain After Weight Loss

George Mason University (GMU) logo

George Mason University (GMU)

Status

Completed

Conditions

Obesity

Treatments

Other: Reverse dieting

Study type

Observational

Funder types

Other

Identifiers

NCT03434431
905083-2

Details and patient eligibility

About

Introduction: It is known that weight loss results in decreased Resting Energy Expenditure (REE), due to a decrease in lean body mass (LBM), but also due to metabolic adaptation, resulting in a higher energy efficiency, responsible for weight regain. Powerlifting athletes submit themselves to caloric restriction before a competition to reach their desired weight category. After cessation of the restrictive diet body mass will quickly return to pre-diet values with a disproportionate gain of fat mass. To avoid fat gain 'reversed dieting' has become popular among athletes. This involves increasing caloric intake in a stepwise fashion with the assumption that the small increases in caloric intake might help to restore energy expenditure toward pre-dieting levels and decrease the chance of increasing fat mass. While anecdotal reports of successful reverse dieting are available, research is needed to evaluate its true efficacy. In addition, if the method would work in non-athletes this could be an important change in the risk of weight regain after a weight loss diet. . Aim: To test the effects of the reverse dieting protocol in the prevention of metabolic adaptation following a period of caloric restriction in weight training athletes. . Methods: A convenience sample of 3 powerlifters is used in this study. They are submitted to a 750kcal/day caloric deficit with a protein intake set at 2x bodyweight (kg) and 30%en from fat for 6 weeks, adjusted weekly. The reverse dieting protocol adds 100kcal during week 1-4 and 150kcal during week 5-8. REE is measured bi-weekly and body composition at day 1 of caloric restriction and day 1 and day 56 of reverse dieting. Exercise is kept constant during the entire period. .

Full description

Rationale: About 66% of the adults in the United States are overweight or obese [Ogden 2006]. Multiple factors are likely to be involved in the development of this epidemic, including increased dietary fat and caloric intake, as well as decreased levels of physical activity. Public health efforts have emphasized the role of preventing weight gain as a means of preventing the complications of obesity such as a number of adverse medical conditions [Allison 1999], lower quality of life [Kolotkin 2001] and reduced life expectancy [Allison 1999]. Obesity is the result of a long term condition of positive energy balance. Energy expenditure is on the output side of the equation while food intake or caloric intake is on the input side of the equation. Total Daily Energy Expenditure (TDEE) exists of three components, Resting Energy Expenditure (REE), the minimum amount of energy spent to maintain bodily functions, which on average is responsible for 60-70% of TDEE, the Thermic Effect of Food (TEF), the energy necessary for the absorption and digestion of the food we eat, which takes up about 10%, and Physical Activity related energy expenditure, which varies largely from day to day depending on the amount of activity performed [de Jonge 1997]. This includes Non-Exercise Activity Thermogenesis (NEAT), the energy expenditure from fidgeting or moving (Levine, 2004). A low REE has been shown to be a predictor of weight gain over time [Ravussin 1993]. It is well known that weight loss results in a decrease of REE, due in part to a decrease in lean body mass, the strongest predictor of REE [Tataranni 1995], but also due to a metabolic adaptation to the caloric restriction, resulting in a higher energy efficiency which serves to prevent further weight loss and conserve energy. However, this energy conservation is also responsible for the weight regain after weight loss [Martin 2007]. Many obesity treatments are therefore focused on limiting the decrease in REE as much as possible whether is by diet, exercise, medication or a combination of the three in order to slow down the process of weight regain. The applicant's research program has focused on the prevention of weight regain and metabolic adaptation to changes in diet and energy balance over the past 20 years. Physique and powerlifting athletes often submit themselves to periods of caloric restriction in the weeks before a competition or a meet in order to reach their desired leanness or weight category. In the period shortly after cessation of the restrictive diet body mass will quickly return to pre-diet values with a disproportionate gain of fat mass. To avoid this rapid fat gain 'reverse dieting' has become popular among athletes. This involves slowly increasing caloric intake in a slow, stepwise fashion. The theory behind this is that the small increase in caloric intake might help to restore energy expenditure toward pre-dieting levels and decrease the chance of increasing fat mass. While anecdotal reports of successful reverse dieting have led to an increase in popularity, research is needed to evaluate its true efficacy. In addition, only reports in trained athletes are available at this moment while, if the method would work in non-athlete individuals, this could be an important change in the risk of weight regain after a weight loss diet. However, since this method has been used in the weight training population, the proposed study will use this population to test the feasibility and fine tune the measurement schedule. The aim of the proposed project is therefore twofold: To test the feasibility of the reverse dieting protocol in the prevention of weight gain and body fat gain following a period of caloric restriction in weight training athletes. To fine tune a measurement schedule for the reverse dieting protocol. Methods Study population: A convenience sample of 3 male weight training athletes aged 20-25yrs from the GMU campus who have verbally showed interest in taking part in the study will be used as our population in this feasibility study. Study design: Upon enrollment and signing of the consent form, maintenance energy intake will be estimated using REE values as measured by metabolic cart multiplied by an estimated activity factor as assessed by the Baeke physical activity questionnaire. The estimated energy intake will be verified and adjusted during one week of daily weigh-ins. Once maintenance energy intake has been established, baseline REE, body composition and body strength will be assessed and a 6 week period of diet restriction will start using the protocol described below. Body weight will be measured weekly, but tracked daily by participants. After 6 weeks of caloric restriction of REE leading to an estimated 4kg weight loss, body composition and strength will be assessed again and a period of 8 weeks of refeeding will start using the protocol below. During this period, REE will be assessed every two weeks and body weight will be assessed weekly. Body composition will be assessed at 4 weeks and 8 weeks and strength will be reassessed after 8 weeks of refeeding Diet Prescription: Period of restriction: Prescription for period of restriction will be determined by the evidence-based recommendations for natural bodybuilding contest preparation by Eric Helms and Alan Aragon (Helms, Aragon, & Fitschen). Starting caloric intake will be calculated as maintenance energy intake, assessed by multiplying REE by an activity factor, minus 750 kcal, resulting in an approximate weight loss of .68 kg / week. Calories will be manipulated by adding or subtracting only fats and CHO, protein intake will remain the same throughout the entire intervention. Fats and carbs will be manipulated with a 1:5 ratio; meaning for every drop of 1g of fat there will be a drop of 5g in CHO. Protein Intake: Determined by the following equation and will remain the same throughout the entire intervention: (Body weight in kg * 2) + 30. Starting Fat Intake: 30% of calories will be from fats. Will be determined by the following equation: (kcal * 0.3) / 9. CHO Intake: CHO will make up the remaining calories. Will be determined by the following equation: [kcal - (Starting Fat Intake * 9) - (Protein Intake * 4)] / 4. Reverse diet Protocol: Ending calories from the period of restriction is the starting point of the reverse diet which will be executed as follows: Weeks 1 to 4: Increase 100 kcal (+ 16g CHO, + 4g Fat) / week Weeks 5 to 8: Increase 150 kcal (+ 25g CHO, + 5g Fat) / week Specific Methods: Anthropometry: Body weight will be assessed at baseline and on a weekly basis thereafter using a Healthometer 752KL scale (Perspective Enterprise, Portage MI). Body weight will be tracked by participants on an individual level with an in home scale. Body Composition: Whole body soft tissue composition (body fat and lean mass) will be measured using dual energy x-ray absorptiometry (DXA; Hologic). DXA is regarded as the criterion method of body composition. Both total body fat (expressed as kg and %) and trunk fat (kg) values are available from the DXA software. This measure is rapid, taking a total of 3 minutes x-ray time and the low radiation (<10 µSV) will not exceed limits for x-ray exposure. In comparison, individuals are exposed to ~6 µSV of naturally occurring background radiation daily in the US (epa.gov). Energy expenditure and substrate oxidation : Resting energy expenditure will be assess by indirect calorimetry using a ventilated hood system (Quark RMR, Cosmed Inc., Rome, Italy). The Quark RMR measures oxygen consumption and CO2 production via a breath by breath technique using a paramagnetic oxygen analyzer and an infrared CO2 analyzer. Energy expenditure and substrate oxidations will be calculated from oxygen consumption, CO2 production and urinary nitrogen by using the equations of Acheson et al [Acheson 1984]. Dietary Intake: Dietary Intake will be assessed weekly using the web-based Automated Self-Administered 24H dietary recall (ASA-24) (Subar 2012). Nutrient and food group data collected from the 24-hour recalls will be used to assess participants' changes in dietary patterns. Participants will be sent weekly e-mail reminders to complete the 24 hour recalls. Additionally, participants will track diet with Myfitnesspal every day. This will be monitored by the team of researchers. Macronutrient and caloric intakes will be assessed weekly using data from myfitnesspal. Physical activity: Physical activity will be assessed using the Baeke physical activity questionnaire [Baeke 1982]. Strength Assessments: Strength will be assessed at 3 time points; the beginning of diet restriction, the end of diet restriction and at the end of the study using the following scheme: 3 attempts on squat 1 rep max 3 attempts on bench 1 rep max 3 attempts on deadlift 1 rep max The three lifts will then be added together to determine the participants total. This order and amount of attempts directly mimics that of a powerlifting meet. Ethics: The study will be approved by GMU Human Subjects Institutional Review Board and informed consent will be obtained before enrollment in the study. Significance & Future Directions This work will help establish the feasibility of conducting a refeeding protocol and fine tune the measurement schedule. It will be the first study to describe the physiology behind the refeeding approach to prevent weight gain and will support future research efforts and aid in the establishment of the applicant's research program at GMU. The results will be used to develop a randomized clinical trial to test the applicability of the reversed dieting approach to prevent weight gain after weight loss, as opposed to the conventional methods, in a non-strength training population. The results will be used to seek external research funds to develop this clinical trial which could lead to a change in the approach to weight loss and the risk of weight regain.

Enrollment

3 patients

Sex

Male

Ages

20 to 25 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

member of the GMU powerlifting team

Exclusion criteria

no member of the GMU powerlifting team

Trial contacts and locations

0

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Data sourced from clinicaltrials.gov

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