Metabolic Adaptations to Weight Loss: A Brief Review : The Journal of Strength & Conditioning Research

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Brief Review

Metabolic Adaptations to Weight Loss: A Brief Review

Martínez-Gómez, Mario G.1; Roberts, Brandon M.2

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Journal of Strength and Conditioning Research: October 2022 - Volume 36 - Issue 10 - p 2970-2981
doi: 10.1519/JSC.0000000000003991
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Energy balance could be described as the resultant difference from the number of calories consumed by an individual through food intake and the energy expended to maintain his metabolic and physiological functions and support physical activity and exercise demands (76). If we conceive the human body as a bioenergetic system, this concept would align with the first law of thermodynamics, which postures that the total energy of a system is constant, where energy can be transformed from one form to another but cannot be created nor destroyed. Thus, modifications over the course of time in energy balance would be the prime determinant of body mass variation in humans (77). Alongside this concept, successful body mass loss in an individual can be achieved by creating what is known as a caloric deficit or energy deficit, which, broadly speaking, consists of expending more calories or energy than those ingested through food either by increasing physical activity or decreasing one's caloric intake (181). Despite the promotion of different types of diets for body mass loss (68,135), the weekly application of the aforementioned principle (energy deficit) is common among all of them and remains the prime determinant factor for body mass reduction (188). Nonetheless, this process is not expected to occur linearly (66,96) because it is well documented that macronutrient distribution can affect the magnitude of losses in the short term (100) and that a series of homeostatic and metabolic adaptations, such as adaptive thermogenesis (AT) (172), changes in mitochondrial efficiency (14), or alterations in the levels of circulating hormones occur during periods of energy restriction (147). The severity of these changes will depend on the duration of the dieting period, where longer durations will increase adaptations; the magnitude of the energy deficit, where higher deficits will promote larger homeostatic responses; or previous body composition, where lower body fat levels before the intervention will result in more drastic metabolic adaptations (159,194). It also remains unclearly answered whether certain nutritional interventions can reduce the severity of the adaptations to body mass loss because the available evidence is reduced, restricted to specific populations (overweight individuals) and many studies are performed in mice (71,74). Inferring practical applications from these data may be of relevance for both researchers and practitioners to achieve successful body mass loss in populations who might struggle at manipulating body mass for various reasons (obese individuals, athletes, etc).

It is thus important to understand (a) the dynamic nature of energy balance, (b) how these series of “metabolic adaptations” can affect body mass loss and body mass regain over time, and (c) what are the possible nutritional solutions proposed to mitigate these phenomena. These will be the main aims of this review.

Evolutionary Origins and Models to Metabolic Adaptation

The question still arises as to why our species have been endowed with these modifications to our physiology during periods of energy restriction. Although the answer is still inconclusive and mostly dependent on multiple factors, some hypotheses related to our evolutionary past have been postulated. The “Thrifty gene hypothesis” states that several thousand years back, environmental pressures and natural selection would favor those who were able to survive long periods of famine when food was scarce, and thus are the ones who prevailed and conform our genetic heritage, a heritage that when thrown in our modern “obesogenic environment” lead us to chronic disease (155). In simple words, “Our ancient savior has become our modern issue.” Although this theory is an oversimplification that takes a determinist standpoint and only provides a causal genetic factor for the development of obesity in our era, it can be used as a conceptual framework to understand why metabolic adaptation occurs and where it could have come from. Another hypothesis that aligns with this last one to explain the issue at hand is the existence of a “hypothalamic feeding center,” more commonly referred as “adipostat,” an axis between all of our organs and our central nervous system that would tightly control food intake in the long term (40,180). This system would receive afferent signals ranging from hormones (leptin, ghrelin, insulin, etc) to the gut or adipose tissue that would help to establish a “set-point” of energy reserves primarily in the form of adipose tissue and hepatic and muscular glycogen storage thresholds (105,110). This hypothesis has been generally accepted by the scientific community as a theoretical model to understand the self-regulation of food intake but presents several limitations to explain certain diseases, such as obesity (30). The focus of the theoretical models for food intake regulation, however, has not only been placed on adipose tissue; Millward proposed the existence of a “protein-stat” that would suggest food intake to be regulated through the needs for maintenance of lean mass (145). According to Millward, the impetus for lean tissue growth and the need for muscle tissue repletion after malnourishment conditions become key variables in determining appetite and meal size. Although, the evidence for this hypothesis is largely based on mechanistic data, later studies have established a strong relationship between fat-free mass (FFM) losses and compensatory responses to body mass loss. Regarding AT, Keys et al. were the first ones to define this event (146). Adaptive thermogenesis is explained as a spontaneous decrease in energy expenditure (EE) during body mass loss, potentially coming from reductions in the metabolic rate of some relevant organs (heart, kidneys, brain, or liver) and tissues contained within the FFM (141). In another important study on this topic (150), it was reported the magnitude of the adaptation to be around 70–100 kcal·d−1. Although clinically significant, we must take these data with caution because FFM is widely varied in respect to its composition (193), and adjusting for variables such as the water content of different organs and tissues might affect the previous calculation. Several methodological limitations arise when accounting for the evaluation of AT (20). Interindividual variability was also observed in the Minnesota experiment (150), where higher baseline EE was associated with higher AT, supporting the notion that the magnitude of body mass loss can be proportional to AT. Nonetheless, the EE component (which will be further explained in better detail) where this reduced EE might come from remains unclear because AT might be explained from decreases in the nonresting energy compartment of EE (nonvoluntary reductions in EE through decreases in physical activity), as other models have proposed (173). Considering this, whether AT is relevant itself or even actually measurable as part of the metabolic adaptation to body mass loss remains disputed (56). In fact, recent studies by Martins et al. (139,140) support the idea that AT is only appreciable when subjects are in energy restriction conditions and that its magnitude is not sufficient to explain body mass relapse in the long term.

Components of Energy Expenditure

A sustained energy deficit over time will lead to body mass loss, thus it is important to describe the total daily EE (TDEE) of an individual (132). We can describe at least 2 major components that determine an individual's TDEE. The first one, resting EE (REE), refers to the basal metabolic rate and will be the largest constituent of TDEE in most cases, with an average contribution of 70% to TDEE (127). This value will depend on many variables such as sex, height, age, physical activity, and other factors (2,46,91). It is mostly static through an individual's lifetime, with losses or gains in metabolically active tissue such as lean body mass (LBM) contributing to a small effect (141) along with variations in REE (118,151). Other factors, such as resistance exercise, can minimally increase REE (131). For research purposes, it should be minded that after approximately 2 days of fasting, transient increases in this component (5–10%) can be observed because of an increase in the gluconeogenesis rate (185).

The second component is non-REE that is further divided into other 3 contributors: exercise activity thermogenesis (EAT), non-EAT (NEAT), and the thermic effect of food (TEF).

Thermic effect of food refers to the energy expended during the digestion of food, and its contribution to TDEE is estimated to be around 10%. However, it should be noted that different macronutrients as well as other variables (size of meals, processing of foods, and duration) contribute separately to this effect, where bigger meals and higher carbohydrate and protein contents can have a larger impact on TEF (25). This factor might be of consideration when accounting for the TDEE of specific populations, for instance, high-protein diets for some athletes (156). However, some metabolic chamber studies in overweight subjects show that even high-protein feedings may not pose a significant difference in TDEE (17), contrary to what could be expected. A commonly held myth regarding TEF is that a higher frequency of meals will result in increased thermogenesis, but research does not support this claim (114), and in fact, some may suggest the opposite (167).

Exercise activity thermogenesis would refer to the energy expended during daily, programmed exercise sessions. This value accounts for little for TDEE (5–10%) and remains unchanged for the most part unless exercise is ceased or the body mass of an individual is reduced significantly (54), thus needing less energy to support the locomotion required to perform.

Non-EAT is defined as the energy required to support nonexercise-related tasks, such as walking and other leisure time activities (38,124). This component has gathered a lot of attention in recent years due to its large and variable contribution to TDEE. Non-EAT has also been shown to downregulate during periods of energy restriction (126) and even maintain that state afterward, potentially contributing to body mass regain (202). However, a recent review on the topic (184), aimed to examine the response of NEAT to diet interventions to promote body mass loss, concluding, despite having relevant limitations and a high risk of bias, did not support a significant reduction in these components. All TDEE contributors are subjected to some degree of both interindividual and within-individual variability (53), where the largest variations in TDEE are dictated by changes in NEAT. If we were to take NEAT into perspective with the other components, it could represent 15% of TDEE in sedentary subjects and up to 50% in more active individuals (124,125). Figure 1 visually summarizes the different components of EE.

Figure 1.:
Components of TDEE and their reported coefficients of variation. Note how daily exercise activity thermogenesis (EAT) is a far-less relevant contributor to TDEE than nonprogrammed activity (NEAT), despite the common belief. Thermic effect of food reports a high variability because it might be dependent on the properties of food ingested. Adapted from various sources (53,132,194). TDEE = total daily energy expenditure; REE = resting energy expenditure; TEF = thermic effect of food.

Physiological Responses to Body Mass Loss and Endocrine Modulation of Food Intake

The energy balance equation remains undisputed for explaining changes in an individual's body mass. However, a series of physiological and endocrine alterations occur in response to an energy deficit that can drive the behavioral response of an individual regarding appetite, satiety, and food intake, potentially closing the gap between the prescribed energy deficit and the actual caloric intake. Some of the extreme attempts to reduce body mass can be observed in sports where body mass or esthetic appearance is relevant for performance outcomes (combat sports, gymnastics, and bodybuilding). A series of observational and case-report data show many endocrine and hormonal alterations in athletes who undergo these practices (99,157,174). These endocrine profile changes are generally relegated to increases in orexigenic signals and decreases in anorexigenic pathways to promote food ingestion and restoration of energy homeostasis (132,189) (Figure 2).

Figure 2.:
Schematic representation of the endocrine control of energy balance. TDEE = total daily energy expenditure; EAT = exercise-activity thermogenesis; REE/BMR = Resting energy expenditure/basal metabolic rate; NEAT = non-exercise activity thermogenesis; TEF = Thermic effect of food; FM = fat mass; FFM = fat-free mass; CCK = cholecystokinin; PYY = peptide YY; GLP-1 = glucagon-like peptide 1. Adapted from various sources (132,97,34,73,133).

It was with the discovery of leptin (211) and its relation with the fat mass (FM) that a possible endocrine role on energy intake was elucidated. We can take leptin, thyroid hormone, insulin, or ghrelin as examples: Postprandial leptin levels have been shown to vary over the course of weeks depending on adipose stores (69). These variations result in increased satiety after a meal (increased leptin levels/replete adipose stores scenario) or decreased satiety (decreased leptin levels/depleted adipose stores scenario), potentially regulating subsequential food intake beyond the conscious control of an individual (137). Leptin has also been shown to modulate hunger by other means such as inhibiting neuropeptide Y (NPY) and agouti-related protein (AgRP) neurons or stimulating proopiomelanocortin neurons in the hypothalamus (41,61).

The thyroid gland hormones, particularly T3, are also of relevance when accounting for the EE of an individual (108). In a cohort of obese children (168), reductions in T3 and T4 levels were observed after body mass losses in the long term, with no variation to thyroid stimulating hormone. It is important to note that the levels of these hormones were altered at baseline among some of the subjects included in the study (twofold above the SD for their age) and thus it could be debated if restoration of metabolic homeostasis through reductions in excessive FM was attributable for that outcome instead of body mass loss per se. In another study of nonoverweight subjects (3), it was reported that those who lost >5% of body mass experienced significant reductions in T3 as well as in the T3: T4 ratio. Thyroid hormone has also been shown to stimulate brown adipose tissue (19), which can make small contributions to EE (29) and is likely less present in obese individuals (206).

Insulin is similar to leptin in the sense that both regulate body mass and/or food ingestion through negative feedback (45) and both have been reported to decrease during periods of energy restriction (138). Insulin acts in the brain as a potent anorexigenic hormone signaling “energy availability,” whereas peripherally lowers blood glucose levels, driving food intake (12,123). Insulin is also known for its anticatabolic properties (171). This is relevant because, as Millward hypothesized (145), reductions in FFM have been shown to possess a strong orexigenic effect (58) and are now being considered as a potent tonic appetite signal and a strong driver of food intake after body mass loss (16,97). Ghrelin was discovered in 1999 (109) in the stomach, whose main function is to regulate food intake and serve as an orexigenic signal. Ghrelin levels have been shown to increase after diet-induced body mass loss (44) as well as upregulate during energy restriction (18). It is thus commonly stated that these transient orexigenic signals in response to body mass loss can drive food consumption and increase appetite (207). Contrary to leptin, increases in ghrelin production underlie rises in AgRP and NPY neuropeptides, contributing to its orexigenic effect (5). Regarding ghrelin, this study (117) reported how the response in circulating levels of ghrelin to meals with different calories was not equal between obese and lean subjects. Whereas ghrelin levels decreased after high-calorie meals in the lean group and responsively increased after low-calorie meals (as expected), obese subjects didn't exhibit meaningful variations in ghrelin levels at all (117). This finding highlights how persistent endocrine alterations (obesity, in this case) can influence the outcomes of studies examining metabolic adaptation (163). Mechanisms for both leptin and ghrelin resistance in obesity have been reported elsewhere (42,43).

Other Hormones Involved in Physiological Adaptations to Body Mass Loss

Multiple additional alterations can be observed in the endocrine profile of other hormones related to appetite and satiety such as gastric-inhibitory polypeptide (189) or amylin (169,189) with body mass loss. Peptide YY (PYY) and cholecystokinin are gastrointestinal GI peptides that can have an anorexigenic role regarding appetite (205). Their production is sensitive to size, caloric content, and macronutrient composition of meals (187). Intervention studies in obese humans report reductions in their respective circulating levels after a weight loss intervention (35,64,161), suggesting the notion that these hormones might play a role in weight regain. Glucagon-like peptide 1 (GLP-1) is secreted in the small intestine in response to a nutrient load and has direct implications in the regulation of appetite (183). A study by De Luis et al. (49), which aimed to examine the effect of body mass loss on GLP-1 levels, found a positive relationship between the degree of body mass loss and reductions in GLP-1. In a different study (1), similar results were observed, where GLP-1 levels decreased after body mass loss compared with baseline. Thus, more research is warranted in this area.

To sum up the information displayed in this section; evidence has been presented to suggest that reductions in the circulating levels of hormones that might possess an anorexigenic effect and increments in the ones whose role is mostly orexigenic have been reported in body mass loss intervention trials, both in the short term and long term. This might be reflective of our body's attempt to restore energy homeostasis. We must not forget that samples pertaining to the available studies are not always representative of the general population, let it be the clinically obese or athletes. Thus, effect size and scientific relevance of the findings cannot be always reliably assessed. The psychological, behavioral, and environmental aspects regarding body mass loss and metabolic adaptation are out of the scope of this review; however, a proper understanding and management of these variables is of high relevance (130,175,191) to achieve successful body mass loss. Figure 3 visually presents an integrative model of the endocrine regulation of appetite and the feedback regulatory mechanisms that play a role in the dynamic nature of energy balance.

Figure 3.:
A theoretical framework of metabolic adaptation. Note how increases in hunger and slight reductions in TDEE after long periods of energy restriction exert negative feedback on the initial deficit, attenuating the degree of weight loss. Adapted from Trexler et al. (194). TDEE = total daily energy expenditure.

Nutritional Strategies to Reduce Metabolic Adaptation to Body Mass Loss

To determine the most adequate nutritional interventions to reduce the deleterious effects of metabolic adaptation to body mass loss, we must target the main issues responsible for this phenomenon, which are increased hunger coupled with decreased EE (34,142,194). Figure 4 summarizes the “energy gap concept,” which explains why hunger and EE are the key drivers to design interventions to reduce metabolic adaptation to body mass loss. High protein intakes, fiber, and intermittent energy restriction (IER) protocols (diet refeeds and breaks) have been proposed as nutritional strategies to have either a direct or a nondirect effect on sustained and successful body mass loss. Other factors such as increasing physical activity to maintain diet-induced body mass loss are of utmost importance to reduce our body's compensatory responses (143), although this review will focus on the nutritional interventions.

Figure 4.:
Visual representation of the energy gap concept. Lowering hunger and increasing energy expenditure potentially narrows the difference between what is ingested and what is expended, thus reducing the relative magnitude of the energy deficit, ensuring less metabolic adaptation overall while still losing body mass. Adapted from Melby et al. (142). EAT = exercise activity thermogenesis; NEAT = non-EAT.

Rate of Body Mass Loss

The speed at which body mass is lost has been thought to be of relevance when attempting to avoid metabolic adaptations and other undesirable outcomes while dieting. Although some evidence suggests a steady approach to body mass loss (92,129), others appeal to the benefits of short-term approaches (10,153,166). On this premise, it has been suggested that moderate-to-slow rates of body mass loss would result in greater FM losses and less FFM and REE declines compared with faster rates of body mass loss (9). Consequences associated with rapid body mass loss might include the worsening of specific health biomarkers (182) while the improvement of others (154,195) or detrimental body composition changes in athletes (70). However, because most of these studies are performed in obese or overweight individuals, it could be argued whether any of the benefits observed are because of the body mass loss rate or the absolute body mass loss per se (113). In a recent comprehensive systematic review on this topic (116), it was concluded that gradual rates of weight loss were associated with greater losses in FM and body fat percentage as well as an enhanced maintenance of REE. The authors highlighted the need for high quality studies with standardized interventions as well as delimitations on what constitutes aggressive and gradual energy restriction protocols to avoid heterogeneity (116). Besides, if potential body mass regain is a relevant outcome to measure, long-term high-quality trials are needed.


One of the main contributors to the increase in appetite and hunger during energy restriction is thought to be FFM losses, which increases central signaling for food intake (58). Protein is the most important macronutrient when accounting for the maintenance of FFM and consequently for overall health during lifespan (31,101) and our optimal needs might be increased during periods of dietary restriction (32,33). To either maintain or increase LBM (a component of FFM), the rates of muscle protein synthesis (MPS) must exceed muscle protein breakdown (MPB) rates (148). A deeper understanding of protein turnover is out of the scope of this review; the reader is redirected to other reviews on the topic (94,164). Given the fact that protein might possess a satiating effect (119,120) and has a higher thermic effect after consumption (196), theory supports increasing protein intake over usual consumption patterns to mitigate potential increases in hunger and appetite. In this trial with a randomized parallel design (201) in obese subjects who lost 5–10% of their total body mass in 3 months, those who consumed 48 g of protein over their usual intake regained less body mass after the follow-up and mainly in the form of FFM. In another study (122), adding 30 g·d−1 of protein to the diet during 7 months resulted in less body mass regained in overweight subjects. To the author's criteria, both these studies were well conducted and showed no important limitations; however, it is important to note the studies were conducted by the same research group and although the results may be extrapolated with ease, further replication of the findings is warranted. In the DIOGENES study (4), a randomized controlled trial performed in Europe with obese and overweight subjects on ad libitum diets, it was reported that after the initial body mass loss, those who consumed a higher amount of protein regained significantly less body mass than those with a lower intake. These results add up to the idea that increased protein might promote satiety and better body mass loss outcomes than a usual intake—at least in the long term (121). Several meta-analyses involving overweight and obese individuals suggest that 1.2–1.5 g·kg−1 is an appropriate daily protein intake range to maximize fat loss (107,112,208).

Exercise also plays a relevant role in the maintenance of FFM and the maintenance of EE during body mass loss. In a randomized controlled trial by Verreijen et al. (198), 100 overweight subjects on hypocaloric conditions underwent either a 10-week program with a high-protein (1.3 g·kg−1) or a low-protein diet (0.8 g·kg−1) with or without resistance-type exercise. The results show how only the group with the combined intervention (high protein and resistance exercise) preserved a significant amount of FFM. After this idea, a recent meta-analysis (131) aimed to determine the effect of different types of exercise on EE, concluding that resistance exercise was slightly superior than endurance and aerobic exercise in increasing EE. It would also seem that in athletic populations, where the FFM component is generally larger than that of overweight and sedentary individuals, protein needs during body mass loss might be even higher and of more relevance (106,162) ranging from 1.2 to 2 g·kg−1 of body mass. Mettler et al. (144) found a better retention of LBM (skeletal muscle component of FFM) in individuals who consumed 2.3 g of protein·kg−1·d−1 vs. those who consumed 1 g·kg−1·d−1 during a body mass loss protocol. Intakes up to 3.4–4.4 g·kg−1 have been studied before in this population (6–8) with no deleterious health effects and improvements in body composition reported.

High-protein intakes should be recommended with caution because food choices to meet those goals may become difficult and adherence may be compromised. In studies that examined very high intakes (6,7), daily protein requirements were achieved by supplementing with whey or beef protein. Dropout rates from these studies were high (77 down to 48 and 40 down to 30, respectively), and the reason given by the subjects was their inability to adhere to such high intakes, gastrointestinal distress, or no reason at all. For a more personalized approach, it might be wise to estimate optimal protein needs based on FFM or LBM (88,89,152) instead of total body mass because adipose tissue demands for protein are lower than those of FFM (36). However, because most people do not have access to accurate methods to determine FFM, adhering to the upper range of recommendations (∼2 g·kg−1 of body mass) is advised for nonathletes with the goal of losing FM (101,106) with even higher recommendations for those who aim to maximize hypertrophic adaptation (170). To conclude, increasing protein intake over usual values might be wise to offset the negatives of dieting over long periods of time. It is important to understand that recommended dietary allowances establish a minimum, not an optimal intake (204) and thus should not be taken as a one-size-fits-all recommendation, especially during a caloric deficit. Combining high-protein intakes with a prescribed resistance exercise program seems to the best approach to avoid FFM losses rather than increasing protein alone (149), and they could improve the negative consequences of metabolic adaptation.

Carbohydrate and Fat

Outside protein, the carbohydrate-to-fat macronutrient composition of the diet has also been thought to play a role in potential body mass regain after dieting. More precisely, the mathematical sum of the glycemic index (GI) (which is defined as the ability of a specific food to rise glucose blood levels after a meal (103)) of the foods in someone's diet, also known as glycemic load (GL) (11), has received special attention due to the observed relationship between GI/GL and health outcomes (13,65).

Acute spikes in insulin secretion as a result of adhering to a high-GL diet have been proposed to be one of the main responsible factors that would favor body mass regain while dieting through an increase of food cravings during the day, leading to overconsumption of calories. This partly conforms the “carbohydrate-insulin” model of obesity (78). Although this model sounds great in theory, it falls in physiological reductionism and presents several flaws, as evidence to date fails to support it (78). In this line of thought, a few interventions have aimed to compare low-carbohydrate (LC) diets (which are by definition low-GL diets) to low-fat (LF) diets for body mass loss and body mass loss maintenance (67,178). The overall results of these interventions show more pronounced body mass losses during the early phases of the trial in the LC groups, which can be attributed to higher glycogen and water depletion rates (111), with attrition rates being high in both groups in the long term. In a randomized controlled trial by Ebbeling et al. (60), a LF diet, a low GI diet, and a LC diet were compared. After 10–15% body mass loss in overweight adults resulted in decreases in REE and TDEE in the LF group but no decline was observed in the LC/low-GI groups. This study presents several limitations; First, diets were not equated for protein, so it could be argued that differences in the TEF (25) might have accounted for the differences observed in TDEE between groups; Second, physical activity was reduced in the LF diet group (TDEE to REE ratio) while it experimented an increase in the LC respective to baseline levels (60). It has been previously reported how changes in spontaneous physical activity account for significant variations in TDEE (38,126,141,199) so this could help explain the results obtained. Overall, it seems that the distribution of carbohydrate and fat is of little relevance when designing a nutritional plan whose aim is to reduce metabolic adaptation and prevent body mass regain. We must not forgo the fact that most of these interventions were conducted in overweight subjects. For athletes/leaner subjects, biasing energy intake toward carbohydrate while providing enough energy from fat (10–25%) may help support exercise performance while on energy restriction conditions (22,170,192).


The idea that dietary fiber might help control appetite is still controversial. As a public health strategy, it is indicated to increase fiber intake (98) because requirements are generally not met. Evidence from epidemiological studies reports higher-fiber intakes to be associated with improved body mass control, higher satiety, and overall lower-food intake (47,128,197). High-fiber foods generally possess a High satiety index (95). Possible explanatory mechanisms to this relation might reside in longer chewing periods to consume high-fiber foods as well as its low-energy density (86,209). A meta-analysis (39) examined the relationship between acute satiety and consumption of fiber, finding no clear relationship between these 2 variables in interventional studies. However, there is tremendous variability in the design and methodology of fiber trials, where different types of fiber may yield different outcomes (186). High-fiber meals can also modulate postprandial concentrations of anorexigenic gastrointestinal peptides such as GLP-1 and PYY (115), thus contributing to increased satiety after a meal. Gastric emptying rate (GER) is also affected by fiber ingestion as demonstrated by Geliebter et al. (72). In their study, it was reported how oatmeal significantly lowered GER compared with corn flakes (less fiber than oatmeal) and contributed to greater satiety after the meal. Different and varied fiber consumption might also contribute to a remodeling of the gut microbiota (93,134), which present numerous implications in the regulation of food intake and overall health, yet further investigation is needed to make conclusions. Overall, research on the satiating effects of fiber has been reported to present numerous methodological limitations and a lack of external validity (165). Randomized trials with subjects on hypocaloric conditions with high-fiber intakes through a whole-food approach are lacking. Thereby, designing an approach toward increasing fiber to attenuate the effects of metabolic adaptation is complex. Because high-fiber intakes have been reported to reduce the energy density of the diet (59) as well as allowing for larger volumes of food without drastically increasing calories (136), fiber could be a useful dietetic tool to attain an energy deficit.

Diet Refeeds and Diet Breaks

The current United States and European (104,210) guidelines recommend continuous energy restriction (CER) as an effective tool to lose body mass. On the other hand, IER includes a series of nutritional protocols that differ from the traditional approach of dieting in CER (159,177), in the sense that they alternate periods of overfeeding with periods of undereating, which still follow the principles of energy balance (76). The most common IER protocols used are diet breaks and refeeds. Diet refeeds could be defined as a specific dietetic strategy where calories and macronutrients are increased at energy maintenance levels or slightly above on specific days (1–2 days) over the course of a weekly deficit, predominantly achieved by increasing carbohydrate consumption (62,194).

There are several hypotheses to why increasing carbohydrate periodically could lead to improved body mass loss outcomes and better FFM retention; First, because circulating insulin levels have a role in the maintenance of FFM (171) responses in secretion to acute carbohydrate refeeds could help reduce MPB (15,75) as well as promote a more pronounced MPS response through the activation of the mTORC1 pathway (200). Second, leptin has been demonstrated to be especially responsive to carbohydrate intake (102). To test if overfeeding alone was solely responsible for the rise in leptin, a study (52) was conducted on lean healthy female subjects aimed to compare fat vs. carbohydrate refeeds. Plasma leptin levels were elevated after a carbohydrate overfeed but not a fat overfeed, suggesting carbohydrate to have a major impact on leptin levels. Overweight and obese subjects may benefit from this strategy because a series of hormonal alterations such as leptin resistance have been reported in this population (81). In another study (179), obese and overweight subjects were randomly allocated in either an IER group with refeeding every 5 days, a CER group, or a control group with no advice to restrict calories for 1 year. No significant differences were observed between the ICR and CER group in regards to body mass loss and multiple other biomarkers, concluding that both protocols were equally effective in body mass reduction and disease prevention (179). In another trial on obese and overweight subjects (190), similar results were observed; however, reported feelings of hunger were more common among the IER group after 1 year. One key aspect to consider when evaluating different dietary protocols is reported adherence (50,51). In both studies, the dropout rate from the subjects was reported to be less than 10%, suggesting adherence to IER is similar to CER.

Finally, athletes might benefit more from intermittent refeeds than overweight subjects because this population has reported favorable results after this protocol (26). This might be due to carbohydrate being pertinent for sports performance outcomes (21,82). Although not all kinds of sports may require high amounts of carbohydrate to improve performance (37,63), they are undoubtedly needed for high-intensity efforts (79,85). In a very recent study by Campbell et al. (27), resistance-trained subjects followed either 21% CER or 26% IER for 7 weeks. Results showed similar reductions in body mass but higher retention in dry FFM on the IER group. There are, nonetheless, several methodological considerations to address when inferring conclusions from the evidence presented. Adherence was low (27 subjects completed the trial from the 58 who were instructed at baseline), the caloric restriction was different between groups (21 vs 26%), and results were highly heterogeneous, with subjects losing 3.5 kg of FFM and others gaining 2.5 kg within the IER group (potentially due to the body assessment methods used). This particular study caused a special interest in the community, with formal responses from both researchers in the field (160) and the main author of the study (28). Thus, conclusions should be interpreted cautiously. Diet breaks are similar to refeeds but differ in the amount of time where energy balance conditions are met (from 1 to 2 days up to weeks). Because metabolic adaptations have been shown to persist even after years after initial body mass loss (189), diet breaks are used on the premise that compensatory responses to body mass loss require longer periods in energy balance conditions to partially or completely return to baseline (23,90).

Evidence for the use of diet breaks is also mixed. In the MATADOR study (24), 51 obese subjects followed CER or IER alternating weeks of energy balance (14 weeks) with periods of energy restriction (16 weeks) during a total of 30 weeks. The results reported greater body mass loss among the subjects of the IER compared with the CER group, as other studies have also replicated (48). By contrast, another study (203) found no difference between diet break protocols over traditional caloric restriction after 14 weeks. An important consideration regarding the methodology of the previous study is that the CER group performed a 2-week break (was not strictly continuous), whereas the IER group followed a 6-week diet break. Because it is not well understood how much time of a break is needed to revert the compensatory adaptations to body mass loss (176), this factor could have played in favor of the CER group, thus resembling the outcome. Peos et al. (158) will examine the effect of IER strategies in the medium-to-long term in the ICECAP trial that is currently in the works whose results are expected to be released soon. To forge a more solid answer to the question, recent meta-analyses (80,83,84) examined the effects of IER to CER in regards to body mass loss, concluding that there was no significant difference between both protocols. It was also reported how the number of studies included was small and presented huge heterogeneity. In addition, most of them were at an unclear risk of bias, and most differences in secondary outcomes such as insulin sensitivity and other biomarkers could be solely attributed to body mass loss itself.

Practical Applications

Changes in EE during body mass loss occur, but are largely explained by involuntary changes in the non-exercise activity compartment (NEAT). Alongside changes in EE, endocrine and physiological alterations occurs to increase appetite, which represents the homeostatic drive to restore lost weight. High-protein diets ranging from 1.2 to 1.5 in overweight individuals and up to 2 are effective in lean athletes to preserve FFM. High-fiber foods, such as whole grains, fruits, and vegetables, are also recommended because they generate early satiation and allow for large volumes of food to be consumed while dieting. Concerning diet refeeds and diet breaks, the evidence is mixed and scarce. However, some positive results for IER have been reported in certain scenarios (24,27) where both athletes and overweight subjects might benefit from it as a part of a periodized body mass loss program. Nondietary interventions, such as increasing physical activity EE and engaging in programmed resistance training, are also advised as they minimize the deleterious effects of metabolic adaptation to body mass loss.


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body mass loss; caloric restriction; adaptative thermogenesis; appetite control; energy intake; metabolic rate; diet refeeds; diet breaks

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