Below are facts that will help you guide your clients through weight loss and management and better answer their questions.
FACT 1: -3,500 KCALS ≠ 1 LB BODY WEIGHT LOSS
You probably learned that a reduction of 3,500 kcals will result in a pound of weight loss. Where did this number come from? Does it work for everyone regardless of body size and level of activity?
In 1958, Max Wishnofsky, M.D., reviewed the literature on weight loss in obese sedentary individuals who typically consumed low-calorie, high-protein diets within a clinical setting. Under these conditions, he concluded that “the caloric equivalent of 1 lb of body weight lost is approximately 3,500 kcals (21).” Across the years, we have transformed this number into a rule, without questioning whether it holds true for all individuals regardless of body size, level of physical activity, age, sex, or genetics. We now know the number of kilocalories required for 1 lb of weight loss changes depending on how long the dieting period lasts, what type of diet is fed, and whether participants engage in physical activity. For example, researchers at the Pennington Biomedical Research Institute (6) examined weight loss in overweight men and women who dieted until they lost 15% of their body weight. They either consumed a very-low-calorie diet (890 kcals per day) or reduced energy intake by 25%. Participants were not doing physical activity. They found that, during the early phases of weight loss (weeks 1 to 4), the energy equivalent for a pound of weight loss was 2,208 kcals. However, as the diet extended to weeks 6 and beyond, the energy reduction required for a pound of weight loss approached Wishnofsky’s rule (Figure 1). Researchers hypothesized that, during the early phases of weight loss, water, glycogen, protein, and fat are lost, whereas toward the later part of the diet, a greater percentage of weight loss is from fat. Adipose tissue is approximately 85% fat (4), thus, the energy content of 1 lb of body fat is approximately 3,470 kcals. Conversely, if the majority of the weight loss is caused by water, lean tissue, and glycogen losses, the energy content of these components is low. For example, the energy content of muscle, which is approximately 65% to 70% water, is approximately 550 kcals per pound. Thus, the energy content of weight loss will depend on the composition of the weight loss and how the body is adapting to the energy restriction placed on it. The impact of adding physical activity to an energy-restricted weight loss program also can change the composition of weight loss, energy substrates used, and how quickly weight loss occurs.
FACT 2: DURING PERIODS OF WEIGHT LOSS, ENERGY BALANCE IS DYNAMIC
During periods of weight loss, energy balance is dynamic — not static. This fallacy is illustrated in the following example (17): A 75-kg man consumes an extra 100 kcals per day for 40 years. The amount of extra energy consumed is equal to 1.46 million kilocalories, with an estimated weight gain of 417 lbs (∼190 kg) during the 40-year period (e.g., 1.46 million divided by 3,500 kcals per pound). As a health professional, you intuitively know that this would not happen, yet how do you explain the results? This static energy balance approach is assuming that, by changing the diet, no other components of energy balance changed, but this isn’t true. As extra energy is consumed and weight is gained, energy expenditure would increase. This weight gain increases the resting metabolic rate, which subsequently increases total energy expenditure because there is a greater energy cost in moving and maintaining a larger body. As one consistently consumes the extra 100 kcals per day, body weight would increase until energy expenditure eventually balanced the increased demand for energy (e.g., the extra 100 kcals per day). Thus, the individual would eventually become weight stable at a higher body weight, which might represent a more realistic 6-lb (∼2.7 kg) weight gain. However, to maintain this larger body size, the individual would need to continue to eat the extra 100 kcals per day. For any one person, the actual amount of weight gained will depend on a number of individual factors, including the extra kilocalories consumed, composition of the diet, body composition, type of exercise, and level of daily physical activity.
The concept of dynamic energy balance and some of the key factors that influence each side of the energy balance equation are illustrated in Figure 2. How each individual responds to changes in each factor will depend on genetics, regulatory hormones that control energy balance and appetite, gut health, and the food and exercise environment that can drive eating, exercise, and body composition. See Galgani and Ravussin (3) for more details on these factors.
FACT 3. PREDICTING WEIGHT LOSS DURING PERIODS OF ENERGY RESTRICTION IS DIFFICULT
Wishnofsky’s 3,500-kcals-per-pound rule is still reported widely in the research literature and used to predict weight loss for adults, regardless of body size or composition, level of physical activity, sex, or age. We now know that predicting weight loss or gain is not that simple. Researchers at the National Institutes of Health (NIH) (5) and the Pennington Biomedical Research Center (PBRC) (18) have spent years developing mathematical models to better predict weight change using the dynamic energy balance model. As one changes energy intake or expenditure, these models take into account changes in resting metabolic rate, body size, fat and lean tissue mass, voluntary physical activity, spontaneous physical activity, the thermic effect of food, and the energy costs of fat and protein synthesis. For example, as you lose weight, body composition can change, which alters energy expenditure. In addition, the energy cost of moving a smaller body is less, thus, one has to work harder or longer to expend the same amount of energy in physical activity compared with when one’s body weight was higher. These models calculate these changes for you. Using the PBRC prediction model for weight change and data from well-controlled weight loss studies (6,11), researchers showed that their model predicted within 2.2 kg of the actual weight loss, while using the Wishnofsky’s rule, there was a 11-kg bias (19). However, it is important to remember that these prediction models were developed using the results from weight loss studies with overweight and obese individuals. If you are working with active individuals who are leaner and capable of much higher levels of exercise, you may need to adapt your results to fit your client’s unique characteristics. Regardless of their limitations, these models will help you do a better job of estimating the time required for weight changes to occur and provide your clients with more realistic weight loss goals for a designated period.
These two prediction models are Web-based for simple use. Below is a brief description of each model:
- The NIH model (7) can be found at the NIH Web site: http://bwsimulator.niddk.nih.gov. This model has two options: 1) setting a goal weight or 2) indicating what diet and physical activity changes you want to make to achieve a designated weight loss or gain goal. Age, sex, height, and current body weight and physical activity level are required. If the goal weight option is selected, the goal weight and the number of days to reach this weight goal are given. The calculator then indicates how much of a change in energy intake or expenditure are needed to reach the goal weight in the designated time frame. The model provides the number of calories needed to maintain the new body weight at the designated level of physical activity. If the lifestyle change option is selected, the diet and physical activity changes to be made and the period are added. The model then predicts the level of change required in each category to reach the goal.
- The Pennington model (18) can be found at the PBRC Web site: https://www.pbrc.edu/research-and-faculty/calculators/. This model requires that age, sex, height, and current weight be entered, along with the daily energy-deficient (kilocalories per day) goal. A graph and table then show how long it will take to achieve the goal weight based on the energy deficit entered. This Web site does not ask about current physical activity level or how exercise energy expenditure may change during the designated period. Because physical activity is not part of this model, its application to active individuals is limited.
FACT 4. DURING PERIODS OF ENERGY RESTRICTION, PROTEIN NEEDS INCREASE
When individuals restrict energy intake for weight loss, protein intake typically decreases unless specific attention has been given to consuming more protein. During periods of energy restriction, some proteins will be used for energy, depending on the level of energy restriction and the type and amount of physical activity being performed. Thus, protein needs increase with energy restriction, both absolute (grams per kilogram body weight per day) and relative amounts (percentage of total energy from protein). The current Recommended Dietary Allowance for protein is 0.8 g/kg body weight per day or 20% to 35% of total energy intake (8), with higher recommendations for active individuals (1.4-1.7 g/protein per kilogram per day) (12). During periods of energy restriction, the goal is to meet or exceed these same absolute levels of protein intake to help preserve lean tissue. If energy is severely restricted and/or individuals are physically active, the need for protein may be even higher (10). For example, researchers placed 20 healthy resistance-trained male athletes (body mass index, 23 to 24 kg/m2) on an energy-restricted diet (60% of habitual energy intake) (9). During this time, they were assigned randomly to either a control (1 g/protein per kilogram body weight; n = 10) or treatment group (2.3 g/protein per kilogram body weight; n = 10). Results showed that loss of lean mass was greater in the control group (-1.6 kg in 1 week) compared with that in the treatment group (-0.3 kg). Thus, the higher protein intake (∼35% of energy intake) helped preserve lean tissue when energy intake was severely restricted for a short time. However, there currently are no data supporting intakes higher than 2.5 g protein per kilogram per day when dieting for weight loss in the general population (10).
Timing of protein intake also is important especially if physical activity is included as part of the weight loss program. Spreading food and protein intake throughout the day ensures that adequate protein is available for building, repair, and maintenance of lean tissue. In addition, higher protein diets have been associated with increased satiety and reductions in energy intake. For example, researchers fed 19 healthy sedentary individuals (body mass index [BMI] range, 22.5 to 30.1 kg/m2) three different diets in sequential order (20). First, they consumed a weight-maintaining diet for 2 weeks (energy distribution = 15% protein, 35% fat, and 50% carbohydrate). Second, they consumed an isocaloric diet (30% of energy from protein, 25% fat, and 50% carbohydrate) for 2 weeks. Finally, they were fed an ad libitum diet (energy distribution = 30% protein, 20% fat, and 50% carbohydrate) for 12 weeks. When subjects were allowed to eat ad libitum on the high-protein diet (30% of energy intake), they spontaneously decreased energy intake (-441 ± 64 kcals per day) during the 12-week period. Thus, the higher protein diet was more satiating, leading to lower total energy intake, even while carbohydrate was held constant.
FACT 5. LOW-ENERGY DENSE FOOD AND HIGH-INTENSITY EXERCISE CAN ALTER SATIETY AND HUNGER
Changing eating behaviors is one of the most difficult challenges of any weight loss program; thus, a diet that increases satiety (fullness) could increase dietary adherence and potentially successful weight loss (15). Research by Rolls et al. (14) at Pennsylvania State University shows that following a low-energy dense diet plan can increase satiety while lowering total energy intake. A low-energy dense diet is high in whole fruits and vegetables and whole grains and incorporates low-fat dairy, legumes/beans, and lean meats. Overall, the diet is lower in fat and higher in fiber and water while reducing or eliminating energy-containing beverages, especially sweetened beverages and alcohol. This type of eating pattern means that an individual can consume a greater volume of food and feel satisfied while overall energy intake is lower. The energy density of a diet or a food is determined by measuring the amount of energy (kilocalories) for a given amount (grams) of food (kilocalories per gram). Evidence shows that a low-energy density eating plan is effective at reducing energy intake, facilitating weight loss and prevention of weight regain, and maintaining satiety in well-controlled feeding studies and in free-living conditions (2,13). Rolls et al. (1,16) have demonstrated the effectiveness of a low-energy density eating plan on energy intake and weight loss. They found that by reducing energy density by a designated amount (e.g., ∼25%) decreases energy intake by a similar percentage (23% to 24%; approximately -500 kcals per day deficit on a 2,000 kcals/day diet), yet participants reported similar levels of hunger and fullness ratings or enjoyment of the meals compared with control conditions. Thus, reducing the energy density of the diet can reduce energy intake dramatically while still feeling satisfied. A key component of a low-energy density eating plan is to increase intake of foods high in water and fiber to promote satiation while reducing both high-fat foods (i.e., potato chips, cheese, cookies) and low water and fiber foods (i.e., baked tortilla chips, pretzels). This dietary approach can help your clients better adhere to a healthier eating plan and lower energy intake, without counting calories.
Exercise type and intensity also can impact feelings of hunger and lower energy intake after exercise. We now know that acute exercise, especially high-intensity exercise (>60% V˙O2max), can suppress appetite by altering gut appetite-regulating hormones for 2 to 10 hours after exercise (7). However, research results are mixed and depend on subject characteristics (e.g., body fatness, level of fitness, age, or sex) and exercise duration, intensity, type, and mode. Overall, in exercise-trained males, it seems that higher-intensity exercise elicits suppression of gut appetite hormones, but studies in women are mixed (7). If appetite suppression does occur after exercise, it can lower energy intake at the next meal and potentially lower overall energy intake. Thus, encouraging your clients to combine some higher-intensity exercise with a low-energy dense diet may help them manage hunger and reduce total energy intake, especially if these two behaviors occur regularly throughout the week.
Weight loss is difficult. Thus, it is not surprising that many of your clients have been on numerous weight loss diets, with mixed results (Table 2). Understanding dynamic energy balance and applying this approach to your weight management plans will help you and your clients make more realistic goals and approaches for weight change. For weight loss, a reduction in energy intake is extremely important, but unless the energy deficit is altered across time to account for changes in body weight, weight loss will slow and eventually stop. Predicting weight loss results based on changes in diet and exercise is not a precise science. New mathematical prediction models are designed to predict weight change more accurately, based on the lifestyle changes implemented. During periods of energy restriction, protein needs increase, especially if physical activity increases. Thus, specific protein recommendations need to accompany any weight loss diet. Research suggests that high-intensity exercise can blunt appetite after exercise and lower total daily energy intake, but more research is needed before specific recommendations can be given. Finally, helping your clients eat a low-energy dense diet may not only help them lose weight and consume a healthier diet but also help them keep the weight off once weight loss is achieved.
BRIDGING THE GAP
Exercise and health professionals typically predict weight loss/gain for clients by using the static energy balance model, which does not apply during times of weight change. They also assume that 3,500 kilocalories equals 1 lb of weight loss/gain, which is not always true. When clients struggle to reach their designated weight goals, we often assume that the client is not following the program. New mathematical models, which incorporate the dynamic energy balance approach into their estimates of weight change, will produce more realistic estimates of actual weight changes during periods of weight gain or loss.
1. Bell EA, Castellanos VH, Pelkman CL, Thorwart ML, Rolls BJ. Energy density of foods affects energy intake
in normal-weight women. Am J Clin Nutr
. 1998; 67 (3): 412–20.
2. Ello-Martin JA, Ledikwe JH, Rolls BJ. The influence of food portion size and energy density on energy intake
: Implications for weight management. Am J Clin Nutr
. 2005; 82 (1): 236S–41S.
3. Galgani J, Ravussin E. Energy metabolism, fuel selection and body weight regulation. Int J Obesity (Lond)
. 2008; 32 (Suppl 7): S109–19.
4. Gropper SS, Smith J. Advanced Nutrition and Human Metabolism
. Belmont (CA): Wadsworth Cenagge Learning; 2013.
5. Hall KD, Sacks G, Chandramohan D, et al. Quantification of the effect of energy imbalance on bodyweight. Lancet
. 2011; 378 (9793): 826–37.
6. Heymsfield SB, Thomas D, Martin CK, et al Energy content of weight loss
: Kinetic features during voluntary caloric restriction. Metabolism
. 2012; 61 (7): 937–43.
7. Howe SM, Hand TM, Manore MM. Exercise
-trained men and women: Role of exercise
on appetite and energy intake
. 2014; 6 (11): 4935–60.
8. Institute of Medicine, Food and Nutrition Board. Standing Committee on the Scientific Evaluation of Dietary Intakes, National Research Council. Dietary Reference Intakes: Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids
. Washington (DC): National Academy Press; 2005.
9. Mettler S, Mitchell N, Tipton KD. Increased protein intake reduces lean body mass loss during weight loss
in athletes. Med Sci Sports Exerc
. 2010; 42 (2): 326–37.
10. Phillips SM. A brief review of higher dietary protein diets in weight loss
: A focus on athletes. Sports Med
. 2014; 44 (Suppl 2): S149–53.
11. Redman LM, Heilbronn LK, Martin CK, et al, Metabolic and behavioral compensations in response to caloric restriction: implications for the maintenance of weight loss
. PLoS ONE
. 2009; 4 (2): e4377.
12. Rodriguez NR, DiMarco NM, Langley S; American Dietetic Association; Dietitians of Canada; American College of Sports Medicine: Nutrition and Athletic Performance. Position of the American Dietetic Association, Dietitians of Canada, and the American College of Sports Medicine: Nutrition and athletic performance. J Am Diet Assoc
. 2009; 109 (3): 509–27.
13. Rolls BJ. The relationship between dietary energy density and energy intake
. Physiol Behav
. 2009; 97 (5): 609–15.
14. Rolls BJ. Plenary Lecture 1: Dietary strategies for the prevention and treatment of obesity. Proc Nutr Soc
. 2010; 69 (1): 70–9.
15. Rolls BJ. Dietary strategies for weight management. Nestle Nutr Inst Workshop Ser
. 2012; 73: 37–48.
16. Rolls BJ, Roe LS, Meengs JS. Reductions in portion size and energy density of foods are additive and lead to sustained decreases in energy intake
. Am J Clin Nutr
. 2006; 83 (1): 11–7.
17. Swinburn B, Ravussin E. Energy balance or fat balance? Am J Clin Nutr
. 1993; 57 (Suppl. 5): 766S–70S.
18. Thomas DM, Ciesla A, Levine JA, Stevens JG, Martin CK. A mathematical model of weight change with adaptation. Math Biosci Eng
. 2009; 6 (4): 873–87.
19. Thomas DM, Gonzalez MC, Pereira AZ, Redman LM, Heymsfield SB. Time to correctly predict the amount of weight loss
with dieting. J Acad Nutr Diet
. 2014; 114 (6): 857–61.
20. Weigle DS, Breen PA, Matthys CC, et al A high-protein diet
induces sustained reductions in appetite, ad libitum
caloric intake, and body weight despite compensatory changes in diurnal plasma leptin and ghrelin concentrations. Am J Clin Nutr
. 2005; 82 (1): 41–8.
21. Wishnofsky M. Caloric equivalents of gained or lost weight. Am J Clin Nutr
. 1958; 6 (5): 542–6.
Donnelly JE, Blair SN, Jakicic JM, Manore MM, Rankin JW, Smith BK. Appropriate physical activity intervention strategies for weight loss
and prevention of weight regain for adults. Med Sci Sports Exerc
. 2009; 41 (2): 459.
Galgani J, Ravussin E. Energy metabolism, fuel selection and body weight regulation. Int J Obesity
. 2008; 32( Suppl. 7): S109–19.
Manore MM. Weight management in the performance athlete. Nestlé Nutr Inst Workshop Ser
. 2013; 75: 123–33.
Shook RP, Hand GA, Blair SN. Top 10 research questions related to energy balance. Res Q Exerc Sport
. 2014; 85 (1): 49–58.
Sweat W, Manore MM. Dietary fiber: Simple steps for managing weight and improving health. ACSM Health Fitness J
. 2015; 19 (1), 9–16.
Sweat W, Manore MM. Too good to be true? Eating more and losing weight with a low energy dense diet
. ACSM Health Fitness J
. 2012; 16 (4), 22–8.
Keywords:© 2015 American College of Sports Medicine.
Weight Loss; Energy Intake; Dynamic Energy Balance; Exercise; Diet