How dieting makes some fatter: from a perspective of human body composition autoregulation

Dieting makes you fat – the title of a book published in 1983 – embodies the notion that dieting to control body weight predisposes the individual to acquire even more body fat. While this notion is controversial, its debate underscores the large gap that exists in our understanding of basic physiological laws that govern the regulation of human body composition. A striking example is the key role attributed to adipokines as feedback signals between adipose tissue depletion and compensatory increases in food intake. Yet, the relative importance of fat depletion per se as a determinant of post-dieting hyperphagia is unknown. On the other hand, the question of whether the depletion of lean tissues can provide feedback signals on the hunger–appetite drive is rarely invoked, despite evidence that food intake during growth is dominated by the impetus for lean tissue deposition, amidst proposals for the existence of protein–static mechanisms for the regulation of growth and maintenance of lean body mass. In fact, a feedback loop between fat depletion and food intake cannot explain why human subjects recovering from starvation continue to overeat well after body fat has been restored to pre-starvation values, thereby contributing to ‘fat overshooting’. In addressing the plausibility and mechanistic basis by which dieting may predispose to increased fatness, this paper integrates the results derived from re-analysis of classic longitudinal studies of human starvation and refeeding. These suggest that feedback signals from both fat and lean tissues contribute to recovering body weight through effects on energy intake and thermogenesis, and that a faster rate of fat recovery relative to lean tissue recovery is a central outcome of body composition autoregulation that drives fat overshooting. A main implication of these findings is that the risk of becoming fatter in response to dieting is greater in lean than in obese individuals.

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Effect of increasing dietary calcium through supplements and dairy food on body weight and body composition: a meta-analysis of randomised controlled trials

British Journal Of Nutrition ◽

10.1017/s0007114515001518 ◽

2015 ◽

Vol 114 (7) ◽

pp. 1013-1025 ◽

Cited By ~ 34

Author(s):

Alison O. Booth ◽

Catherine E. Huggins ◽

Naiyana Wattanapenpaiboon ◽

Caryl A. Nowson

Keyword(s):

Body Composition ◽

Body Weight ◽

Food Intake ◽

Body Fat ◽

Randomised Controlled Trials ◽

Meta Analysis ◽

Controlled Trials ◽

Dairy Food ◽

Affect Body Weight ◽

Randomised Controlled

This meta-analysis of randomised controlled trials assessed the effect of Ca on body weight and body composition through supplementation or increasing dairy food intake. Forty-one studies met the inclusion criteria (including fifty-one trial arms; thirty-one with dairy foods (n 2091), twenty with Ca supplements (n 2711). Ca intake was approximately 900 mg/d higher in the supplement groups compared with control. In the dairy group, Ca intake was approximately 1300 mg/d. Ca supplementation did not significantly affect body weight (mean change ( − 0·17, 95 % CI − 0·70, 0·37) kg) or body fat (mean change ( − 0·19, 95 % CI − 0·51, 0·13) kg) compared to control. Similarly, increased dairy food intake did not affect body weight ( − 0·06, 95 % CI − 0·54, 0·43) kg or body fat change ( − 0·36, 95 % CI − 0·80, 0·09) kg compared to control. Sub-analyses revealed that dairy supplementation resulted in no change in body weight (nineteen studies, n 1010) ( − 0·32, 95 % CI − 0·93, 0·30 kg, P= 0·31), but a greater reduction in body fat (thirteen studies, n 564) ( − 0·96, 95 % CI − 1·46, − 0·46 kg, P < 0·001) in the presence of energy restriction over a mean of 4 months compared to control. Increasing dietary Ca intake by 900 mg/d as supplements or increasing dairy intake to approximately 3 servings daily (approximately 1300 mg of Ca/d) is not an effective weight reduction strategy in adults. There is, however, an indication that approximately 3 servings of dairy may facilitate fat loss on weight reduction diets in the short term.

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Transcriptional profiling of hypothalamus during development of adiposity in genetically selected fat and lean chickens

Physiological Genomics ◽

10.1152/physiolgenomics.00029.2010 ◽

2010 ◽

Vol 42 (2) ◽

pp. 157-167 ◽

Cited By ~ 21

Author(s):

Mardi S. Byerly ◽

Jean Simon ◽

Larry A. Cogburn ◽

Elisabeth Le Bihan-Duval ◽

Michel J. Duclos ◽

...

Keyword(s):

Body Composition ◽

Body Weight ◽

Food Intake ◽

Body Fat ◽

Transcriptional Profiling ◽

Taste Receptor ◽

Sweet Taste ◽

Glucose Sensing ◽

Expression Of Genes ◽

Regulatory Controls

The hypothalamus integrates peripheral signals to regulate food intake, energy metabolism, and ultimately growth rate and body composition in vertebrates. Deviations in hypothalamic regulatory controls can lead to accumulation of excess body fat. Many regulatory genes involved in this process remain unidentified, and comparative studies may be helpful to unravel evolutionarily conserved mechanisms controlling body weight and food intake. In the present study, divergently selected fat (FL) and lean (LL) lines of chickens were used to characterize differences in hypothalamic gene expression in these unique genetic lines that develop differences in adiposity without differences in food intake or body weight. Hypothalamic transcriptional profiles were defined with cDNA microarrays before and during divergence of adiposity between the two lines. Six differentially expressed genes identified in chickens are related to genes associated with control of body fat in transgenic or knockout mice, supporting the importance of these genes across species. We identified differences in expression of nine genes involved in glucose metabolism, suggesting that alterations in hypothalamic glycolysis might contribute to differences in levels of body fat between genotypes. Expression of the sweet taste receptor ( TAS1R1), which in mammals is involved in glucose sensing and energy uptake, was also higher in FL chickens, suggesting that early differences in glucose sensing might alter the set point for subsequent body composition. Differences in expression of genes associated with tumor necrosis factor (TNF) signaling were also noted. In summary, we identified alterations in transcriptional and metabolic processes within the hypothalamus that could contribute to excessive accumulation of body fat in FL chickens in the absence of differences in food intake, thereby contributing to the genetic basis for obesity in this avian model.

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Changes in body composition after thermal injury in the rat

British Journal Of Nutrition ◽

10.1079/bjn19790126 ◽

1979 ◽

Vol 42 (3) ◽

pp. 367-375 ◽

Cited By ~ 7

Author(s):

G. A. Al Shamma ◽

C. C. Goll ◽

T. B. Baird ◽

J. Broom ◽

G. A. Nicholas ◽

...

Keyword(s):

Weight Loss ◽

Wound Healing ◽

Body Composition ◽

Body Weight ◽

Food Intake ◽

Body Fat ◽

Wistar Rats ◽

Thermal Injury ◽

Energy Deficit ◽

Male Wistar Rats

1. The effects on body composition, measured by direct techniques, of a controlled 25% body-surfacearea thermal injury have been studied in two groups of forty male Wistar rats.2. The extent of weight loss in the animals was directly related to their energy deficit resulting from a combination of injury, food intake and rate of wound healing.3. Body fat proved the most labile source of tissue energy, decreasing to a minimum of approximately 30 g/kg body-weight.4. Relationships between water and fat, and water and protein seen in control animals were not significantly different in the traumatized group.

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Sensitivity of bioelectrical impedance to detect changes in human body composition

Journal of Applied Physiology ◽

10.1152/jappl.1989.67.4.1643 ◽

1989 ◽

Vol 67 (4) ◽

pp. 1643-1648 ◽

Cited By ~ 36

Author(s):

R. Ross ◽

L. Leger ◽

P. Martin ◽

R. Roy

Keyword(s):

Body Composition ◽

Human Body ◽

Correlation Coefficients ◽

Bioelectrical Impedance ◽

Mean Values ◽

Significance Level ◽

Exercise Regimen ◽

Before And After ◽

Hydrostatic Weighing ◽

Human Body Composition

The purpose of this study was to compare the estimates of lean body mass (LBM) and percent body fat (%BF), as predicted by bioelectrical impedance (BIA) and sum of skinfolds (SF), with those derived by hydrostatic weighing (HW) obtained before and after a 10-wk diet and exercise regimen. The experimental (E) group consisted of 17 healthy male subjects; 20 healthy males served as the control (C) group. Post hoc Scheffe contrasts computed on E group data indicated that, for both LBM and %BF, the Lukaski and Segal BIA equations, as well as the Durnin SF equation, derived mean values that were not significantly different (0.05 significance level) from HW in both pre- and postregimen conditions. For LBM, the same equations derived the following significant (P less than 0.01) correlation coefficients for both pre- and postregimen data: Lukaski, 0.87 and 0.85; Segal, 0.89 and 0.87; and Durnin, 0.90 and 0.88. For %BF, the correlation coefficients were slightly lower but remained statistically significant (P less than 0.01). The findings of this study suggest that the BIA method, by use of either the Lukaski or Segal prediction equations, is a valid means of predicting changes in human body composition as measured by the Siri transformation of body density.

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Multifrequency bioelectrical impedance analysis to assess human body composition

Nutrition Research ◽

10.1016/s0271-5317(99)00079-2 ◽

1999 ◽

Vol 19 (8) ◽

pp. 1179-1188 ◽

Cited By ~ 4

Author(s):

Sufia Islam ◽

Iqbal Kabir ◽

Mohammad A. Wahed ◽

Michael I. Goran ◽

Dilip Mahalanabis ◽

...

Keyword(s):

Body Composition ◽

Human Body ◽

Bioelectrical Impedance Analysis ◽

Bioelectrical Impedance ◽

Impedance Analysis ◽

Human Body Composition

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Development of a MATLAB-based Predictive System for Human Body Composition using Wenner Method

Proceedings of the 2020 10th International Conference on Biomedical Engineering and Technology ◽

10.1145/3397391.3397422 ◽

2020 ◽

Author(s):

Analyn N. Yumang ◽

Ericson D. Dimaunahan ◽

Jose B. Lazaro ◽

Dean Henry S. Guerrero ◽

Christine S. Lapada ◽

...

Keyword(s):

Body Composition ◽

Human Body ◽

Human Body Composition

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Protein appetite is increased after central leptin-induced fat depletion

AJP Regulatory Integrative and Comparative Physiology ◽

10.1152/ajpregu.00322.2007 ◽

2007 ◽

Vol 293 (4) ◽

pp. R1468-R1473 ◽

Cited By ~ 3

Author(s):

Michael F. Wiater ◽

Bryan D. Hudson ◽

Yvette Virgin ◽

Sue Ritter

Keyword(s):

Body Weight ◽

Food Intake ◽

Body Fat ◽

Caloric Intake ◽

Sprague Dawley ◽

Body Protein ◽

Macronutrient Selection ◽

Daily Diet ◽

Nadir Point ◽

And Control

Leptin reduces body fat selectively, sparing body protein. Accordingly, during chronic leptin administration, food intake is suppressed, and body weight is reduced until body fat is depleted. Body weight then stabilizes at this fat-depleted nadir, while food intake returns to normal caloric levels, presumably in defense of energy and nutritional homeostasis. This model of leptin treatment offers the opportunity to examine controls of food intake that are independent of leptin's actions, and provides a window for examining the nature of feeding controls in a “fatless” animal. Here we evaluate macronutrient selection during this fat-depleted phase of leptin treatment. Adult, male Sprague-Dawley rats were maintained on standard pelleted rodent chow and given daily lateral ventricular injections of leptin or vehicle solution until body weight reached the nadir point and food intake returned to normal levels. Injections were then continued for 8 days, during which rats self-selected their daily diet from separate sources of carbohydrate, protein, and fat. Macronutrient choice differed profoundly in leptin and control rats. Leptin rats exhibited a dramatic increase in protein intake, whereas controls exhibited a strong carbohydrate preference. Fat intake did not differ between groups at any time during the 8-day test. Despite these dramatic differences in macronutrient selection, total daily caloric intake did not differ between groups except on day 2. Thus controls of food intake related to ongoing metabolic and nutritional requirements may supersede the negative feedback signals related to body fat stores.

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