It is estimated that only about 20% of individuals who experience significant weight loss are able to maintain their lost weight [ 7 ]. Data from participants in the Biggest Loser Television program demonstrate the difficulty in maintaining lost weight over time. The average weight loss of the 14 participants during the 30-week intervention was 58 kg, but six years later, the contestants had regained an average of 70% of their lost weight (41 kg) [ 25 ]. The lack of successful weight loss maintenance for many dieting individuals could largely stem from behavioral issues—the inability of the individual to permanently adopt long-term lifestyle habits that promote a reduced body weight in the face of an obesogenic environment. The availability of a highly palatable, relatively inexpensive food supply coupled with a living environment that requires little physical work to carry out daily tasks could stand in the way of permanent changes in dietary and physical activity patterns. Lack of successful treatment then would stem from the inability to permanently alter behavioral responses to environmental conditioning and pressures. However, there is evidence that metabolic factors can contribute substantially to poor treatment outcomes—in response to weight loss, regulatory physiological responses are invoked that can effectively work to re-establish positive energy balance leading to weight regain toward a pre-established body weight set point [ 26 ]. While the voluntary behavior (conscious choices) versus biological determinism (pre-programmed set-point with tight control) debate is of keen interest to researchers in the field, the two are not mutually exclusive—behavioral and metabolic factors are inextricably intertwined, and both pose significant obstacles to long-term weight loss maintenance.

MacLean et al. [ 27 28 ] and others [ 29 ] have reviewed the metabolic adaptations that accompany weight loss, primarily based on data from animal studies, but with probable relevance to the human condition. As depicted in Figure 1 , calorie restriction leading to weight loss causes discordance between appetite and energy requirements, a concept referred to as the “energy gap“, in which the biologic pressure to regain the lost weight occurs as a function of the increased hunger and the reduced energy expenditure that accompany diet-induced weight loss. In response to weight loss, signals of both energy and nutrient deprivation are sent from the periphery to brain networks in the hypothalamus and hindbrain, which by way of second order neurons increase hunger and decrease energy expenditure, resulting in more calories being desired (Ein) than are required (Eout). The occurrence of these responses among individuals living in an obesogenic environment can promote the re-establishment of positive energy balance and regain of body weight and fat toward their pre-diet levels.

3.2. How Does Weight Loss Affect Hunger and Satiety?

27,28, Many metabolic factors contribute to the energy gap following dietary restriction. Observed changes in adiposity-related signals (leptin and insulin), hypothalamic neuronal activity and neuropeptide expression, and gut peptide expression are thought to play a role in the increased hunger in response to weight loss. An exhaustive review of these factors is beyond the scope of this paper. The interested reader is referred to comprehensive reviews on this topic [ 14 30 ].

32,33, The hypothalamus integrates many signals from the periphery, including liver, gut, and adipose tissue to regulate energy expenditure and the initiation, termination, and frequency of eating. Homeostatic regulation of food intake occurs such that severe caloric energy restriction leading to weight loss results in a strong internal drive to eat, whereas an overabundance of food intake and weight gain may be followed by a reduction in food intake. Insulin and leptin are putative players in this regard [ 31 34 ]. They circulate in proportion to body fat mass and bind receptors in hypothalamic neurons, promoting expression of the anorexigenic peptides, pro-opiomelanocortin (POMC) and cocaine-amphetamine related transcript (CART), and inhibiting expression of the orexigens, neuropeptide Y (NPY) and Agouti-related peptide (AgRP). Acting through second-order neurons, these leptin- and insulin-stimulated neuropeptide changes result in reduced food intake and increased sympathetic nervous system activity and energy expenditure [ 31 34 ]. Because increasing fat mass results in incremental increases in circulating leptin, the majority of obese children and adults present with hyperleptinemia [ 35 ]. However, this elevation in blood leptin concentrations occurs without an ensuing decrease in food intake, indicating the presence of leptin resistance among individuals who exhibit obesity. While the higher circulating leptin and insulin coincident with increasing adiposity should theoretically limit weight gain, cellular resistance to these hormones occurs suggesting that protection against weight gain may be less robust than protection against weight loss [ 32 ]).

37,37, Speakman [ 36 38 ] has argued that human survival against risk of starvation (i.e., body energy stores insufficient for reproduction and life) and risk of predation (i.e., excess body mass impairs the ability to escape predators) is delimited by dual (upper and lower) intervention points and environmental and behavioral pressures exert the primary influences on body weight within the range between them. In accord with this view, for most individuals who exhibit body weight between the upper and lower intervention points, the availability of food would be a primary determinant of food intake. However, as weight falls outside this range, genetically-driven (and/or epigenetic) physiologic changes occur that promote restoration of body energy stores that support survival. Therefore, when inadequate food availability (whether due to intentional energy restriction, as with dieting, or involuntary severe energy deficit, as with famine) results in weight loss that reaches the lower intervention point, homeostatic metabolic changes are invoked that promote weight regain. Conversely, as body weight increases (in today’s society, this would be largely due to the obesogenic environment) and reaches the upper intervention point, homeostatic adjustments should theoretically come into play to decrease energy intake and increase energy expenditure, thus limiting weight gain and risk of predation. However, Speakman [ 36 38 ] argues that owing to a substantial reduction in predatory risk within the human population today, genetic shifts have occurred such that there is a decidedly less robust defense against weight gain than weight loss. Weight gain that exceeds the upper intervention point produces, at best, only modest reductions in hunger and increases in energy expenditure, in part due to the aforementioned leptin resistance. On the other hand, when body weight falls below the lower intervention point, leptin and insulin rapidly decrease causing increased food intake and reduced energy expenditure. This is not unexpected given the decrease in fat mass. However, the magnitude of the decrement in circulating leptin is much greater than the magnitude of fat loss [ 39 ], a phenomenon that may be one of the primary drivers of weight regain. During weight loss maintenance, leptin concentrations slightly increase relative to the dynamic weight loss state [ 35 40 ]; however, these levels remain significantly reduced even when adjusted for changes in fat mass after one [ 39 40 ] and two years of weight maintenance [ 41 ].

43, A host of other anorexigenic peptides originate in the gut and typically increase in circulation in response to feeding, which then communicate with the hypothalamus to terminate food intake, increase satiety, and increase satiation between meals [ 42 44 ]. These peptides include cholecystokinin, peptide YY, amylin, pancreatic polypeptide, and glucagon-like peptide-1 (GLP-1). There is increasing evidence of a sustained, long-term decrease in anorexigenic signals in response to diet-induced weight loss, with the decrement being greater than the decline in body weight [ 40 ]. Such physiological changes could result in a metabolic milieu that readily promotes weight regain following weight loss.

Ghrelin is an orexigenic hormone, primarily produced by oxyntic cells of the stomach and is the endogenous ligand for the growth hormone secretagogues receptor type 1a (GHS-R1a) [ 45 46 ]. The GHS-R1a is located throughout the body including the hypothalamus, pituitary, neuroendocrine tissues, pancreas, stomach, and vagus nerve [ 47 ]. The presence of intact vagal afferents is essential for the centrally mediated effects of ghrelin on hunger and satiety. In lean individuals, plasma ghrelin concentrations rise during fasting and drop with meal ingestion proportional to the calorie content of the meals [ 48 ]. Obese individuals may not display the same suppression of ghrelin in response to calorie ingestion [ 49 50 ]. Weight loss leads to an elevation of plasma ghrelin in obese adolescents [ 51 ] and adults [ 52 ], which is thought to be a compensatory adjustment designed to increase energy intake in an attempt to return body fat stores to their initial levels. The available data suggest that the increase in circulating ghrelin that accompanies weight loss and persists into the weight maintenance phase could contribute to increased hunger and the energy gap.

2) with no history of obesity—and “reduced-obese” participants, who were overweight or obese (BMI 27–32 kg/m2) but recently lost weight in a weight-loss program. The study was designed to analyze brain responses to food images in the overfed state versus eucaloric state. Among thin individuals, overfeeding attenuated neural activation compared to that observed during the eucaloric state. This response to overfeeding did not occur among reduced-weight overweight/obese individuals. In the baseline fasting state, thin individuals had a much more robust neuronal response to food-related visual cues than reduced-obese individuals. Overfeeding resulted in significant attenuation of the response to visual foods cues in thin but not reduced-obese individuals. Additionally, compared with normal-weight individuals with no history of obesity, individuals who are overweight or obese, but have lost weight, have a different neural response to overfeeding [ 53 ]. In a randomized crossover study involving a two-day eucaloric feeding condition and a two-day 30% overfeeding condition, Cornier and colleagues [ 53 ] used Functional Magnetic Resonance Imaging (fMRI) to compare the neuronal responses to viewing images of food among “thin” participants—normal-weight individuals (BMI 19–23 kg/m) with no history of obesity—and “reduced-obese” participants, who were overweight or obese (BMI 27–32 kg/m) but recently lost weight in a weight-loss program. The study was designed to analyze brain responses to food images in the overfed state versus eucaloric state. Among thin individuals, overfeeding attenuated neural activation compared to that observed during the eucaloric state. This response to overfeeding did not occur among reduced-weight overweight/obese individuals. In the baseline fasting state, thin individuals had a much more robust neuronal response to food-related visual cues than reduced-obese individuals. Overfeeding resulted in significant attenuation of the response to visual foods cues in thin but not reduced-obese individuals.

Much of the research on body weight/composition regulation has been adipocentric—that is the control of energy intake and expenditure has focused on adiposity-related signals as discussed above. However, recent studies have demonstrated that fat-free mass (FFM) and resting metabolic rate (RMR) are positively associated with energy intake [ 54 55 ]. FFM is the strongest predictor of RMR and this relation suggests the possibility of a link between FFM-driven energy requirements and the homeostatic control of energy intake. In other words, the large amount of metabolically active lean tissue found in most obese individuals could provide signals to drive the high energy intake necessary to sustain the obese state. However, there is also evidence that the FFM depletion (along with loss of body fat) resulting from caloric restriction fails to dampen appetite, but instead contributes to hyperphagia. Dulloo et al. [ 56 57 ] have suggested that the relation between FFM and energy intake is, in fact, U-shaped, such that the large FFM associated with obesity ‘passively’ drives high energy intake, but the decrement in FFM associated with diet-induced weight loss enhances the drive to eat. Further, they suggest that the reduced FFM that occurs with weight loss stimulates increased energy intake in order to restore the FFM, but also causes increased fat deposition, a phenomenon they describe as ‘collateral fattening’. If during weight regain following weight loss, the restoration of FFM lags behind fat restoration, hyperphagia could persist beyond the fat mass “catch up” and result in greater body fat storage than existed prior to dieting. Thus, weight loss-induced reductions in FFM could contribute to both aspects of the energy gap—a reduction in energy expenditure and increased hunger, both of which could contribute to weight regain.