Energy balance and calorie intake -
Whereas this effect could be observable in longer-term outpatient trials and observational studies, causal inference from these data may be limited by poor adherence to test diets and confounding.
Furthermore, few studies have focused on childhood, a dynamic stage of obesity development [ 50 ]. Although animal studies can elucidate mechanisms, their translation to humans remains problematic.
For these reasons, the vast literature on obesity pathogenesis can be selectively cited to make opposing points, as each side of this debate has claimed of the other.
In this section, we do not aim to provide a comprehensive review of the literature, but rather highlight main disagreements with Hall et al. Table 1 summarizes key features distinguishing the models to facilitate this assessment. Although rodents and humans have not evolved to eat the same diets, experimental animal research has been considered in this debate.
Hall et al. Similarly, a recent study with 5 mouse strains concluded that increasing dietary fat, but not carbohydrate or protein, was associated with greater variations in food intake and body weight [ 68 ].
However, Tordoff and Ellis [ 69 ] found that rodent diets with equal amounts by energy of carbohydrate and fat were most obesogenic and deviations in either direction reduced weight gain. Adding to this heterogeneity, Kennedy et al. Clearly, this research must be extrapolated to humans with caution, in view of well described limitations involving idiosyncrasies of inbred strains, confounding from uncontrolled dietary exposures and dissimilar nutrition requirements of rodents and humans [ 71 , 72 , 73 , 74 ].
For instance, saturated fat and sugar often comprise most calories on high-fat rodent diets, a combination that causes hypothalamic inflammation and systemic insulin resistance [ 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 ]. These methodological issues can be avoided by direct examination of causal direction.
Whereas hormonal responses to macronutrients may differ among species due to evolutionarily divergence, biological mechanisms affecting fat storage are highly conserved, enhancing potential translation of rodent studies to humans [ 83 , 84 , 85 ].
In the EBM, diet drives fat deposition by increasing food consumption. Therefore, when animals on an obesogenic diet are pair-fed to littermates on an isocaloric control diet, ensuring the same energy intake, effects on body composition should be identical. This prediction often fails.
Petro et al. Similar calorie-independent effects have been observed with high-sugar diets [ 90 , 91 , 92 , 93 ]. Although one could challenge the implications of these data by arguing rodents are more susceptible to such metabolic effects, that argument would undermine the validity of rodent macronutrient studies for understanding human obesity in the first place.
Studies of glycemic index GI offer another way to circumvent species-specific differences in macronutrient metabolism. In a line of investigation involving several rodent strains and species, the effects of GI were examined by substitution of starch type, controlling for macronutrients, saturated fat, sugar, and micronutrients [ 82 , 94 , 95 , 96 , 97 ].
These studies demonstrate the following changes among animals consuming high- vs. low-GI diets, in this sequence: hyperinsulinemia, a shift in substrate partitioning favoring fat deposition, decreased energy expenditure, increased adiposity and weight gain — all prior to an increase in energy intake.
When energy intake was restricted to prevent weight gain, the high-GI group still developed abnormal body composition.
Despite consuming fewer calories, these animals had more body fat at the expense of lean body tissues [ 96 ]. Although multiple mechanisms e. Finally, Hall et al. In the CIM, greater insulin secretion promotes fat storage through direct peripheral mechanisms [ 8 ].
The EBM, with its focus on the central actions of hormones, seems to predict the opposite, in view of the anorectic actions of insulin in the brain [ 98 , 99 , , , ].
These studies of adiposity, involving chronic insulin administration and genetic models of reduced insulin secretion, support the CIM [ , , , , , , ]. Downplaying the significance of these findings—that the peripheral calorie-independent actions dominate central calorie-dependent ones—risks creating an EBM so general as to be untestable, especially as Hall et al.
Indeed, effects of dietary composition on body composition consistent with the CIM manifest commonly among animal models of obesity, as exemplified in Table 2.
In some of these models, excessive adiposity spontaneously develops without increased food intake or body weight. These findings seem at odds with a common interpretation of human genetic studies that attributes the greater prevalence of obesity-related polymorphisms in the brain vs.
adipocyte as evidence for the EBM. Only a small component of this heritability can be explained by known common variation at ~ single-nucleotide polymorphisms and the physiological consequences of most of these polymorphisms remain unknown. In some cases e. Some implicated genes are expressed widely in the brain and others are ubiquitously expressed e.
Still others are more prominently expressed outside the brain e. MSX1 , TMEM18 , SEC16B , ADCY3. For polymorphisms cited by Hall et al. Homozygous mutations in ATGL , for instance, resulting in defective lipolysis do not appear to increase risk for obesity.
However, this mutation also impairs lipogenesis, resulting in not only less fat mobilization, but also less fat storage. As Schreiber et al. Thus, the genetics studies indicate pathways involving obesity that operate within and outside the brain; in many cases, these appear consistent with the CIM.
Although design limitations preclude a direct test of causal mechanisms in the EBM vs CIM with observational research, these studies can still be informative if interpreted with the necessary caution. Countries with high carbohydrate intake, for instance, tend to be poor, with a substantial proportion of the population undernourished, malnourished, and engaged in subsistence agriculture.
Moreover, Hall et al. disregard a long and rich history of observations linking the emergence of common chronic disorders, obesity among them, to population-wide nutrition transitions that typically include increased consumption of highly refined grains, sugar, and sugary beverages [ , ].
In the USA, BMI increased most rapidly from to , also concurrent with marked increases in consumption of refined grains, sugar, and total carbohydrate [ , ]. These secular trends, though, may be confounded by changes in physical activity and other relevant behaviors.
Prospective cohort studies provide greater ability to control for confounding factors, notably including socioeconomic status, although residual confounding may remain.
In addition, body weight and other measures of adiposity are especially susceptible to reverse causation the tendency for people to change their diets as a result, rather than a cause, of weight gain or obesity.
Furthermore, the typical prospective design comparing baseline diet with future weight change will not detect prior changes that have reached steady state by the time of the dietary assessment. In this situation, bias toward null associations may ensue; thus, the lack of consistent association involving GI and GL in cohort studies is difficult to interpret [ ].
To better simulate an interventional study, the relationship of change in diet to change in weight over time can be examined. In such analyses, higher intakes of refined grains, potato products, and sugar-sweetened beverages—the main contributors to GL—were associated with greater weight gain in three large cohorts after extensive adjustment for potentially confounding dietary and lifestyle factors [ ].
Red and processed meats were also associated with greater weight gain in these studies. Based on nationally representative surveys, Mozaffarian notes that energy intake has plateaued or declined since , and physical activity has increased moderately, even as rates of obesity continue to rise.
Because of disproportionate increases in waist circumference in women, obesity trends as assessed by BMI may underestimate the extent to which the epidemic has advanced since [ ].
These trends, he argues, call for consideration of alternative causal explanations, including those involving metabolic dysfunction. A recent meta-analysis of behavioral trials reported no difference in long-term weight loss among macronutrient-focused diets [ ], as cited by Hall et al.
high-carbohydrate diets suggest a significant, if modest, advantage to the former [ , , , ]. However, interpretation of this evidence tends to conflate efficacy with behavioral implementation [ ].
Most behavioral weight loss trials lack sufficient intervention intensity to obtain strong contrasts in macronutrient intakes between groups, and initial differences in weight loss between groups wane rapidly.
Maintenance of dietary change can be difficult in the modern food environment, but this challenge is not insurmountable.
With better knowledge of efficacy, more powerful behavioral and environmental interventions can be designed to facilitate long-term adherence. Among the few trials that employed intensive interventions e. high-GL diets for the duration of the protocols [ , ]. The limitations of free-living trials can be, in principle, circumvented by metabolic ward trials that maintain strict control over adherence and confounding factors.
However, due to cost and logistical challenges, these trials are usually short in duration, raising concern for unfounded inference involving chronic effects. The need for trials of at least several months duration was recognized by Hall [ 20 ], who observed that:.
Using current body composition methods, it would require a sustained period of about days to detect such a difference in body fat. Nevertheless, this possibility requires further investigation.
Furthermore, metabolic adaptations to macronutrient changes may require several weeks to months [ , , , , , , ]. high-carbohydrate diets [ ]. The artificial setting of a metabolic ward may also affect eating behavior independently of underlying physiological mechanisms. Furthermore, the initial difference in energy intake was fully attributable to the large difference in energy density, a factor that affects short-term, but not chronic, intake see below.
Related to this concern is the inability to distinguish crucial macronutrient mechanisms. Whereas the extent of food processing greatly affects digestion rate, hormonal response, and health impacts of high-carbohydrate foods, processing has lesser physiological significance for high-fat and high-protein foods Table 3 —implying that the adverse effects of ultra-processed foods can be better explained by the CIM than by the EBM.
A similar pattern of effect attenuation, potentially related to metabolic adaptation and energy density, was observed in a second 2-week ward trial comparing low-fat vs.
low-carbohydrate diets [ ]. Pending definitive research, it seems prudent not to assume that these waning effects would stabilize and influence body weight over the long term. A dominant role of insulin on adipocyte physiology, including lipogenesis and lipolysis, has been recognized for decades [ ].
In patients with diabetes, insulin and drugs that increase insulin secretion or action on adipose tissue metabolism cause weight gain [ ]. Some of these effects may involve other mechanisms compatible with EBMs, such as reduced glycosuria.
However, the weight loss induced by drugs that lower secretion [ ] suggests that the action of insulin on fat storage seen in rodents [ , , , , , , ] occurs in humans. Drugs that lower insulin secretion in people without diabetes also cause weight loss [ ].
Furthermore, two new studies suggest that insulin suppresses adipose mitochondrial respiration in humans [ , ]. However, GLP-1 has other relevant biological actions, including reduced gastric emptying rate which lowers glycemic response [ ]. In fact, GLP-1 receptor agonists chronically reduce measures of total insulin secretion [ , ], although whether this effect is direct or indirect remains unclear.
In any event, dietary GL strongly affects the incretin secretion profile and incretins have direct actions on adipocyte insulin sensitivity. For these reasons, GLP-1 lies on the central causal pathway in the CIM [ 8 ]. Regarding inhibition of lipolysis, Hall et al. However, this nicotinic acid receptor agonist has biological actions that complicate interpretation of the trials.
Acipimox increases counter-regulatory hormone secretion, promotes protein breakdown, and induces a compensatory increase in glucose oxidation [ ].
Of note, inhibition of fatty acid oxidation with various agents stimulates food intake in experimental animals and humans [ , , , , , ]. To summarize evidence pertaining to the two models, the animal data demonstrate that excessive fat deposition can evidently be disassociated from energy intake, opposing a fundamental premise of the EBM.
In animal models involving not only diet, but also brain pathways considered to mediate food intake, obesity can occur without increased food intake.
However, the human data have major methodological limitations that have, so far, precluded a definitive test of the two models. Both sides of this debate agree that fundamental changes in the food environment have driven the obesity pandemic.
The implicit advice, to avoid junk foods, has been advocated for years [ 56 , , , , , ]. Of particular concern, causal relationships with chronic weight gain have not been demonstrated for the dietary factors targeted by Hall et al. The remaining EBM-specific dietary targets include:.
Energy density. Acute changes in energy density affect short-term intake. For example, Bell et al. low-energy-density conditions over 2 days. In one interventional study [ ], 97 women with obesity were counseled to decrease fat intake alone or to decrease fat intake and increase low-energy-density fruits and vegetables.
After 1 year, completers in the low-energy density group lost 1. The groups did not differ in total fat mass or waist circumference. In another interventional study [ ], adults were counseled to follow energy-restricted diets, with some instructed to consume varying amounts of low-energy-density soups vs.
high-energy-density solid snacks. Here again, there was a modest difference in body weight at 1 year. Regarding observational data on energy density [ ], Bes-Rastrollo et al. Dietary fat. Assumptions about the role of energy density in obesity motivated, in large measure, the focus on reducing dietary fat in public health recommendations from the late twentieth century [ , , , , ].
However, low-fat diets have not shown superiority for obesity-related outcomes [ , , ], and some meta-analyses conclude inferiority vs. higher-fat diets for weight loss [ , , ].
The USDA has virtually abandoned the public health campaign to reduce total dietary fat [ ]. Food processing. A systematic review of observational data by Poti et al. Although the continuing increases in obesity prevalence might be attributable to lack of public adoption rather than any inherent deficiency of the EBM itself, the results of EBM-guided treatment throughout the last century suggest otherwise.
If the patient lost weight as predicted, this merely confirmed the comfortable feeling that treatment of obesity was really a pretty simple matter. However, if, as so often happened, the patient failed to lose weight, he was dismissed as uncooperative or chastized as gluttonous.
It was the rare physician who entertained the possibility that failure to follow a regimen might in itself be a medical problem. In , the National Institutes of Health sponsored a Consensus Development Conference on Methods for Voluntary Weight Loss and Control, including many of the leading experts in obesity.
However, the Consensus Conference found little evidence that obesity treatment achieved much better outcomes that those reviewed by Stunkard and McLaren-Hume [ ]. Axiomatically, disease treatment focused on causal drivers upstream along the mechanistic pathway should be more effective, and more sustainable for the patient, than those targeting downstream consequences and manifestations.
This treatment would work temporarily if one could convince a febrile patient to try it , but the body would compensate for the heat loss by severe shivering and blood vessel constriction. Once the patient got out of the cold shower, the fever would return.
Antipyretics work more effectively, and more pleasantly for the patient, by addressing the biological driver of heat accumulation. Similarly, if obesity results from a disorder of fuel partitioning, then measures to treat that problem e.
Maintaining the contrast between these competing models is critical to clarify thinking, inform a research agenda, and identify effective means of prevention and treatment.
This claim belies the most fundamental possible differences among models: causal direction and mechanisms of causality Fig. To subsume the CIM in this way requires construing the EBM so broadly as to make it unfalsifiable, and consequently useless as a scientific hypothesis.
However, this characterization was not made by CIM proponents and offers a false distinction. The control of adipose tissue biology by multiple hormonal, autonomic and other influences has been recognized for decades [ 27 ].
Indeed, the physiological actions of high-GL and high-sugar diets have long been conceptualized as involving integrated relationships among multiple organs beyond adipose tissue and numerous hormones beyond insulin [ 6 , 29 ]. For scientific models to remain relevant, they must grow as knowledge accrues.
Even as Hall et al. Lack of explicit testable hypotheses. How will key steps along the causal pathway be interrogated?
What studies will differentiate the proposed causal pathway overeating drives chronic weight gain from the contrasting hypothesis in the CIM? When humans or animals are experimentally overfed, they gain weight initially.
But changes in hunger and energy expenditure oppose ongoing weight change; after the force-feeding ends, individuals characteristically undereat until body weight returns to baseline [ , , , , , ].
While arguing that opponents of the EBM confuse physics with pathophysiology, Hall et al. These tautologies provide no mechanistic insight.
Paucity of mechanisms involving key model components. How does the new EBM explain the rapid population-level increase in weight, and large variations within individuals over time? Physiologically regulated variables e. What studies would distinguish the putative mediators e. Moreover, if pleasure-related responses to tasty foods cause chronic overconsumption, why has it been so difficult to demonstrate an independent effect of palatability on obesity [ , , , , , , , ]?
Disregard of well-established metabolic mechanisms. For individuals with obesity, energy restriction elicits hallmarks of the starvation response including reduced energy expenditure long before body fat stores reach a normal level.
How do the hedonic and reward aspects of palatable food trigger metabolic responses? Difficulty accounting for the natural history of obesity. The secular increase in energy intake from to the present in the U. Considering the psychosocial and other burdens of excessive weight, why do so few people successfully compensate by conscious control for these small daily effects?
After all, adults routinely resist pleasurable temptations e. Reliance on assumptions that do not differentiate among models. The new EBM interprets evidence that the brain controls body weight as supporting a causal role of overeating in obesity.
As considered above, the brain also influences virtually all aspects of energy metabolism and adipocyte biology. For intractable public health problems, the purpose of scientific models is to guide the design of informative research and, by helping to elucidate causal mechanisms, suggest effective approaches to prevention or treatment.
The new EBM does neither. At a minimum, future formulations should 1 specify testable, mechanistically oriented predictions that examine the causal pathway; 2 explain why the increased population-level BMI is defended by metabolic responses; and 3 demonstrate how calorie-independent effects of diet suggested by clinical research and demonstrated by animal models can be integrated in this model.
The EBM and its precursors have dominated thinking for nearly a century [ 7 ]—influencing scientific design, interpretation of experimental findings, public health guidelines, and clinical treatment—largely to the exclusion of other views.
For instance, the NIH has sponsored numerous multi-center trials of low-fat diets for obesity-related outcomes [ , , ] all with negative primary outcomes , but nothing comparable for low-GL diets.
With the inability of conventional strategies to stem the rising toll of obesity-related disease, new causal models should be studied, not suppressed by hyperbolic claims of having disproven them [ 2 , 9 , 18 , 19 , 57 , 58 , , , ].
Admittedly, debate on complicated scientific questions may polarize, with a tendency for both sides to cite selectively from inconclusive evidence. This problem is exacerbated by difficulties in studying the small daily effects that characterize the natural history of obesity.
In the interests of scientific advancement and public health, all sides of this debate should work together to formulate mutually acceptable versions of competing models and design unbiased studies that would put them to a rigorous test.
A constructive paradigm clash may be facilitated with the recognition that evidence for one model in certain experimental settings does not invalidate the other model in all settings, and that obesity pathogenesis in humans may entail elements of both. Finally, we would emphasize that this paradigm clash should not delay public health action.
Refined grains and added sugars comprise about one-third of energy intake in the US and Europe. Both models target these highly processed carbohydrates—albeit for different reasons—as major drivers of weight gain.
Regardless of how this debate may evolve, common ground now exists on the need to replace these products with minimally processed carbohydrates or healthful fats in the prevention and treatment of obesity.
Kuhn TS. The structure of scientific revolutions. Chicago: The University of Chicago Press; Google Scholar. Schwartz MW, Seeley RJ, Zeltser LM, Drewnowski A, Ravussin E, Redman LA, et al. Obesity pathogenesis: an Endocrine Society Scientific Statement.
Endocr Rev. Expert Panel Report: Guidelines for the management of overweight and obesity in adults. Ludwig DS, Sorensen TIA. An integrated model of obesity pathogenesis that revisits causal direction. Nat Rev Endocrinol. Article PubMed Google Scholar. Sorensen TI.
Challenges in the study of causation of obesity. Proc Nutr Soc. Lustig RH. Childhood obesity: behavioral aberration or biochemical drive?
Reinterpreting the First Law of Thermodynamics. Nat Clin Pract Endocrinol Metab. Article CAS PubMed Google Scholar. Taubes G. Good calories, bad calories: fats, carbs, and the controversial science of diet and health.
New York: Knopf; Ludwig DS, Aronne LJ, Astrup A, de Cabo R, Cantley LC, Friedman MI, et al. The carbohydrate-insulin model: a physiological perspective on the obesity pandemic. Am J Clin Nutr. Article PubMed PubMed Central Google Scholar. Hall KD, Farooqi IS, Friedman JM, Klein S, Loos RJF, Mangelsdorf DJ, et al.
The energy balance model of obesity: beyond calories in, calories out. Carpenter RH. Homeostasis: a plea for a unified approach. Adv Physiol Educ.
Modell H, Cliff W, Michael J, McFarland J, Wenderoth MP, Wright A. Bray GA, Champagne CM. Beyond energy balance: there is more to obesity than kilocalories. J Am Diet Assoc. Hill JO, Wyatt HR, Peters JC.
Energy balance and obesity. Levin BE, Routh VH. Role of the brain in energy balance and obesity. Am J Physiol. CAS PubMed Google Scholar.
Millward DJ. Energy balance and obesity: a UK perspective on the gluttony v. sloth debate. Nutr Res Rev. Prentice AM, Jebb SA. Obesity in Britain: gluttony or sloth? Article CAS PubMed PubMed Central Google Scholar. Lenard NR, Berthoud HR. Central and peripheral regulation of food intake and physical activity: pathways and genes.
Hall KD, Kahan S. Maintenance of lost weight and long-term management of obesity. Med Clin N Am. Hall KD, Guo J. Obesity energetics: body weight regulation and the effects of diet composition. Hall KD.
Modeling metabolic adaptations and energy regulation in humans. Annu Rev Nutr. Silver S, Bauer J. Obesity, constitutional or endocrine. Am J Med Sci.
Article Google Scholar. Wilder RM, Wilbur DL. Diseases of metabolism and nutrition: review of certain recent contributions. Arch Intern Med. Article CAS Google Scholar.
Pennington AW. An alternate approach to the problem of obesity. J Clin Nutr. Hetherington AW, Ranson SW. The spontaneous activity and food intake of rats with hypothalamic lesions. Thorpe GL. Treating overweight patients. J Am Med Assoc. Astwood EB. The heritage of corpulence. Friedman MI.
Fuel partitioning and food intake. Ludwig DS. The glycemic index: physiological mechanisms relating to obesity, diabetes, and cardiovascular disease. Watts AG, Kanoski SE, Sanchez-Watts G, Langhans W.
The physiological control of eating: signals, neurons, and networks. Physiol Rev. Ludwig DS, Ebbeling CB. JAMA Intern Med. Ludwig DS, Friedman MI. Increasing adiposity: consequence or cause of overeating? Shimy KJ, Feldman HA, Klein GL, Bielak L, Ebbeling CB, Ludwig DS.
Effects of dietary carbohydrate content on circulating metabolic fuel availability in the postprandial state. J Endocr Soc. Article PubMed PubMed Central CAS Google Scholar. Walsh CO, Ebbeling CB, Swain JF, Markowitz RL, Feldman HA, Ludwig DS.
Effects of diet composition on postprandial energy availability during weight loss maintenance. PLoS ONE. Holsen LM, Hoge WS, Lennerz BS, Cerit H, Hye T, Moondra P, et al. Diets varying in carbohydrate content differentially alter brain activity in homeostatic and reward regions in adults.
J Nutr. Lennerz BS, Alsop DC, Holsen LM, Stern E, Rojas R, Ebbeling CB, et al. Effects of dietary glycemic index on brain regions related to reward and craving in men. Bremer AA, Mietus-Snyder M, Lustig RH. Toward a unifying hypothesis of metabolic syndrome.
Johnson RJ, Sanchez-Lozada LG, Andrews P, Lanaspa MA. Perspective: a historical and scientific perspective of sugar and its relation with obesity and diabetes. Adv Nutr. Lyssiotis CA, Cantley LC. Metabolic syndrome: F stands for fructose and fat. Taylor SR, Ramsamooj S, Liang RJ, Katti A, Pozovskiy R, Vasan N, et al.
Dietary fructose improves intestinal cell survival and nutrient absorption. Unger RH. Glucagon physiology and pathophysiology. N Engl J Med. Shukla AP, Dickison M, Coughlin N, Karan A, Mauer E, Truong W, et al. The impact of food order on postprandial glycaemic excursions in prediabetes. Diabetes Obes Metab.
de Cabo R, Mattson MP. Effects of intermittent fasting on health, aging, and disease. Erion KA, Corkey BE. Hyperinsulinemia: a cause of obesity? Curr Obes Rep.
Heindel JJ, Howard S, Agay-Shay K, Arrebola JP, Audouze K, Babin PJ, et al. Obesity II: establishing causal links between chemical exposures and obesity.
Biochem Pharmacol. Article PubMed CAS Google Scholar. Ludwig DS, Ebbeling CB, Rimm EB. Diabetes Care. Astley CM, Todd JN, Salem RM, Vedantam S, Ebbeling CB, Huang PL, et al.
Genetic evidence that carbohydrate-stimulated insulin secretion leads to obesity. Clin Chem. Hjorth MF, Ritz C, Blaak EE, Saris WH, Langin D, Poulsen SK, et al. Pretreatment fasting plasma glucose and insulin modify dietary weight loss success: results from 3 randomized clinical trials.
Virtue S, Vidal-Puig A. Adipose tissue expandability, lipotoxicity and the Metabolic Syndrome—an allostatic perspective. Biochim Biophys Acta.
Simmonds M, Llewellyn A, Owen CG, Woolacott N. Predicting adult obesity from childhood obesity: a systematic review and meta-analysis. Obes Rev. Guyenet SJ, Schwartz MW. Clinical review: Regulation of food intake, energy balance, and body fat mass: implications for the pathogenesis and treatment of obesity.
J Clin Endocrinol Metab. Hill JO, Melanson EL, Wyatt HT. Dietary fat intake and regulation of energy balance: implications for obesity. Human obesity as a heritable disorder of the central control of energy balance.
Int J Obesity. Schutz Y. Macronutrients and energy balance in obesity. Swinburn B, Ravussin E. Energy balance or fat balance? Webber J. Energy balance in obesity. Howell S, Kones R. Am J Physiol Endocrinol Metab.
Speakman JR, Hall KD. Carbohydrates, insulin, and obesity. Archer E, Pavela G, McDonald S, Lavie CJ, Hill JO. Front Physiol. Fernandes AC, Rieger DK, Proenca RPC.
Perspective: public health nutrition policies should focus on healthy eating, not on calorie counting, even to decrease obesity. Lucan SC, DiNicolantonio JJ.
How calorie-focused thinking about obesity and related diseases may mislead and harm public health. An alternative. Public Health Nutr. Mozaffarian D. Foods, obesity, and diabetes-are all calories created equal?
Nutr Rev. Stenvinkel P. Obesity—a disease with many aetiologies disguised in the same oversized phenotype: has the overeating theory failed? Nephrol Dial Transplant. Torres-Carot V, Suarez-Gonzalez A, Lobato-Foulques C. The energy balance hypothesis of obesity: do the laws of thermodynamics explain excessive adiposity?
Eur J Clin Nutr. Wells JC. Obesity as malnutrition: the dimensions beyond energy balance. Wells JC, Siervo M. Obesity and energy balance: is the tail wagging the dog? The science of obesity: what do we really know about what makes us fat? An essay by Gary Taubes. BMJ ;f Wu Y, Hu S, Yang D, Li L, Li B, Wang L, et al.
Increased variation in body weight and food intake is related to increased dietary fat but not increased carbohydrate or protein in Mice. Front Nutr. Tordoff MG, Ellis HT. Physiol Behav. Kennedy AR, Pissios P, Otu H, Roberson R, Xue B, Asakura K, et al.
A high-fat, ketogenic diet induces a unique metabolic state in mice. Warden CH, Fisler JS. Comparisons of diets used in animal models of high-fat feeding. Cell Metab. Buettner R, Parhofer KG, Woenckhaus M, Wrede CE, Kunz-Schughart LA, Scholmerich J, et al.
Defining high-fat-diet rat models: metabolic and molecular effects of different fat types. J Mol Endocrinol. de Moura EDM, Dos Reis SA, da Conceicao LL, Sediyama C, Pereira SS, de Oliveira LL, et al. Diet-induced obesity in animal models: points to consider and influence on metabolic markers.
Diabetol Metab Syndr. Sholl J, Mailing LJ, Wood TR. Reframing nutritional microbiota studies to reflect an inherent metabolic flexibility of the human gut: a narrative review focusing on high-fat diets. Milanski M, Degasperi G, Coope A, Morari J, Denis R, Cintra DE, et al.
Saturated fatty acids produce an inflammatory response predominantly through the activation of TLR4 signaling in hypothalamus: implications for the pathogenesis of obesity. J Neurosci. Benoit SC, Kemp CJ, Elias CF, Abplanalp W, Herman JP, Migrenne S, et al. Palmitic acid mediates hypothalamic insulin resistance by altering PKC-theta subcellular localization in rodents.
J Clin Invest. Cintra DE, Ropelle ER, Moraes JC, Pauli JR, Morari J, Souza CT, et al. Unsaturated fatty acids revert diet-induced hypothalamic inflammation in obesity. Oliveira V, Marinho R, Vitorino D, Santos GA, Moraes JC, Dragano N, et al.
Diets containing alpha-linolenic omega3 or oleic omega9 fatty acids rescues obese mice from insulin resistance. Vijay-Kumar M, Vanegas SM, Patel N, Aitken JD, Ziegler TR, Ganji V.
Fish oil rich diet in comparison to saturated fat rich diet offered protection against lipopolysaccharide-induced inflammation and insulin resistance in mice. Nutr Metab. Dornellas AP, Watanabe RL, Pimentel GD, Boldarine VT, Nascimento CM, Oyama LM, et al.
Deleterious effects of lard-enriched diet on tissues fatty acids composition and hypothalamic insulin actions. Prostaglandins Leukot Essent Fatty Acids. Davis JE, Gabler NK, Walker-Daniels J, Spurlock ME. Tlr-4 deficiency selectively protects against obesity induced by diets high in saturated fat.
Ludwig DS, Ebbeling CB, Bikman BT, Johnson JD. Testing the carbohydrate-insulin model in mice: the importance of distinguishing primary hyperinsulinemia from insulin resistance and metabolic dysfunction. Mol Metab. Birsoy K, Festuccia WT, Laplante M. A comparative perspective on lipid storage in animals.
J Cell Sci. DiAngelo JR, Birnbaum MJ. Regulation of fat cell mass by insulin in Drosophila melanogaster. Mol Cell Biol.
Watts JL. Fat synthesis and adiposity regulation in Caenorhabditis elegans. Trends Endocrinol Metab. Petro AE, Cotter J, Cooper DA, Peters JC, Surwit SJ, Surwit RS.
Oscai LB, Brown MM, Miller WC. Effect of dietary fat on food intake, growth and body composition in rats. So M, Gaidhu MP, Maghdoori B, Ceddia RB. Analysis of time-dependent adaptations in whole-body energy balance in obesity induced by high-fat diet in rats. Lipids Health Dis. Storlien LH, James DE, Burleigh KM, Chisholm DJ, Kraegen EW.
Fat feeding causes widespread in vivo insulin resistance, decreased energy expenditure, and obesity in rats. Oscai LB, Miller WC, Arnall DA. Effects of dietary sugar and of dietary fat on food intake and body fat content in rats. Reiser S, Hallfrisch J. Insulin sensitivity and adipose tissue weight of rats fed starch or sucrose diets ad libitum or in meals.
Rendeiro C, Masnik AM, Mun JG, Du K, Clark D, Dilger RN, et al. Fructose decreases physical activity and increases body fat without affecting hippocampal neurogenesis and learning relative to an isocaloric glucose diet. Sci Rep. Toida S, Takahashi M, Shimizu H, Sato N, Shimomura Y, Kobayashi I.
Effect of high sucrose feeding on fat accumulation in the male Wistar rat. Obes Res. Kabir M, Rizkalla SW, Quignard-Boulange A, Guerre-Millo M, Boillot J, Ardouin B, et al. A high glycemic index starch diet affects lipid storage-related enzymes in normal and to a lesser extent in diabetic rats.
Pawlak DB, Bryson JM, Denyer GS, Brand-Miller JC. High glycemic index starch promotes hypersecretion of insulin and higher body fat in rats without affecting insulin sensitivity. Pawlak DB, Kushner JA, Ludwig DS. Effects of dietary glycaemic index on adiposity, glucose homoeostasis, and plasma lipids in animals.
Scribner KB, Pawlak DB, Aubin CM, Majzoub JA, Ludwig DS. Long-term effects of dietary glycemic index on adiposity, energy metabolism, and physical activity in mice. Bruning JC, Gautam D, Burks DJ, Gillette J, Schubert M, Orban PC, et al. Role of brain insulin receptor in control of body weight and reproduction.
Brief DJ, Davis JD. Reduction of food intake and body weight by chronic intraventricular insulin infusion. Brain Res Bull. Choudhury AI, Heffron H, Smith MA, Al-Qassab H, Xu AW, Selman C, et al. The role of insulin receptor substrate 2 in hypothalamic and beta cell function. Tataranni PA, Gautier JF, Chen K, Uecker A, Bandy D, Salbe AD, et al.
Neuroanatomical correlates of hunger and satiation in humans using positron emission tomography. Proc Natl Acad Sci USA. Woods SC, Lotter EC, McKay LD, Porte D Jr.
Chronic intracerebroventricular infusion of insulin reduces food intake and body weight of baboons. Cusin I, Rohner-Jeanrenaud F, Terrettaz J, Jeanrenaud B.
Hyperinsulinemia and its impact on obesity and insulin resistance. Int J Obes Relat Metab Disord. Terrettaz J, Cusin I, Etienne J, Jeanrenaud B. Dallon BW, Parker BA, Hodson AE, Tippetts TS, Harrison ME, Appiah MMA, et al.
Insulin selectively reduces mitochondrial uncoupling in brown adipose tissue in mice. Biochem J. Mehran AE, Templeman NM, Brigidi GS, Lim GE, Chu KY, Hu X, et al. Hyperinsulinemia drives diet-induced obesity independently of brain insulin production.
Torbay N, Bracco EF, Geliebter A, Stewart IM, Hashim SA. Insulin increases body fat despite control of food intake and physical activity. Templeman NM, Skovso S, Page MM, Lim GE, Johnson JD. A causal role for hyperinsulinemia in obesity.
J Endocrinol. Page MM, Skovso S, Cen H, Chiu AP, Dionne DA, Hutchinson DF, et al. Reducing insulin via conditional partial gene ablation in adults reverses diet-induced weight gain. FASEB J. Manceau R, Majeur D, Alquier T.
Neuronal control of peripheral nutrient partitioning. Yi CX, la Fleur SE, Fliers E, Kalsbeek A. The role of the autonomic nervous liver innervation in the control of energy metabolism.
Munzberg H, Qualls-Creekmore E, Berthoud HR, Morrison CD, Yu S. Neural control of energy expenditure. Handb Exp Pharmacol. Nogueiras R, Lopez M, Dieguez C.
Regulation of lipid metabolism by energy availability: a role for the central nervous system. Bernard C. Leçons de physiologie expérimentale appliquée à la médecine, faites au Collège de France. Paris: J. Baillière et fils; Book Google Scholar. Wainschtein P, Jain D, Zheng Z, TOPMed Anthropometry Working Group, NHLBI Trans-Omics for Precision Medicine TOPMed Consortium, Cupples LA.
et al. Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data. Nat Genet. Loos RJF, Yeo GSH. The genetics of obesity: from discovery to biology. Nat Rev Genet. Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, et al. Genetic studies of body mass index yield new insights for obesity biology.
Schreiber R, Hofer P, Taschler U, Voshol PJ, Rechberger GN, Kotzbeck P, et al. Hypophagia and metabolic adaptations in mice with defective ATGL-mediated lipolysis cause resistance to HFD-induced obesity. Popkin BM, Adair LS, Ng SW. Global nutrition transition and the pandemic of obesity in developing countries.
Trowell HC, Burkitt DP. Western diseases: their emergence and prevention. London: Edward Arnold; Gross LS, Li L, Ford ES, Liu S. Increased consumption of refined carbohydrates and the epidemic of type 2 diabetes in the United States: an ecologic assessment.
Ford ES, Dietz WH. Trends in energy intake among adults in the United States: findings from NHANES. Gaesser GA, Miller Jones J, Angadi SS. Perspective: does glycemic index matter for weight loss and obesity prevention?
Mozaffarian D, Hao T, Rimm EB, Willett WC, Hu FB. Changes in diet and lifestyle and long-term weight gain in women and men. Obesity - an unexplained epidemic. Freedman DS, Ford ES. She advises following the American Institute for Cancer Research guidelines.
Fill at least two-thirds of your plate with plant-based foods, and no more than one-third of you plate with animal protein. Can you even the score with a jog around the block?
Levy says you need to compare calories burned with those consumed. For long-term success, focus on consuming a healthy diet and getting regular physical activity consistently.
Make sure your exercise routine includes strength training. This will help you build and maintain muscle, especially as you age. Muscle mass naturally decreases over time. If balancing your calorie intake is challenging, an activity tracker or app may help.
Request an appointment at MD Anderson's Lyda Hill Cancer Prevention Center online or call My Chart. Donate Today. Request an Appointment Request an Appointment New Patients Current Patients Referring Physicians.
Manage Your Risk Manage Your Risk Manage Your Risk Home Tobacco Control Diet Body Weight Physical Activity Skin Safety HPV Hepatitis. Family History Family History Family History Home Genetic Testing Hereditary Cancer Syndromes Genetic Counseling and Testing FAQs. Donate Donate Donate Home Raise Money Honor Loved Ones Create Your Legacy Endowments Caring Fund Matching Gifts.
Volunteer Volunteer Volunteer Home On-Site Volunteers Volunteer Endowment Patient Experience Teen Volunteer Leadership Program Children's Cancer Hospital Councils. Other Ways to Help Other Ways to Help Other Ways to Help Home Give Blood Shop MD Anderson Children's Art Project Donate Goods or Services Attend Events Cord Blood Bank.
Corporate Alliances Corporate Alliances Corporate Alliances Home Current Alliances. For Physicians. Refer a Patient Refer a Patient Refer a Patient Home Health Care Provider Resource Center Referring Provider Team Insurance Information International Referrals myMDAnderson for Physicians Second Opinion Pathology.
Clinical Trials Clinical Trials Clinical Trials Home. Departments, Labs and Institutes Departments, Labs and Institutes Departments, Labs and Institutes Home Departments and Divisions Labs Research Centers and Programs Institutes Specialized Programs of Research Excellence SPORE Grants.
Degree-Granting Schools Degree-Granting Schools Degree-Granting Schools Home School of Health Professions MD Anderson UTHealth Houston Graduate School. Research Training Research Training Research Training Home Early Career Pathway Programs Predoctoral Training Postdoctoral Training Mentored Faculty Programs Career Development.
Outreach Programs Outreach Programs Outreach Programs Home Project ECHO Observer Programs Comparative Effectiveness Training CERTaIN. December Energy balance: What is it, and how can you achieve it?
Previous Article. Next Article. December : Energy balance: What is it, and how can you achieve it? Food and energy balance If you are trying to achieve energy balance, first look at the energy density of the foods you eat.
Related Posts. More Stories From Focused on Health. The year in cancer prevention: 5 things you need to know.
Weight Loss Enerrgy. A ballance understanding of energy Energy balance and calorie intake is critical. This article will lay the Ennergy for what energy Energy balance and calorie intake is, how Online game resource recharge relates to metabolism, and how it can be changed. To cut straight to the point, as humans, we exist in the physical universe. This means that, fundamentally, human beings are just a complex system of mass, which is where we walk into the concept of energy balance. Energy balance is the concept that helps us understand how humans gain, lose, and maintain weight.
Nach meinem ist das Thema sehr interessant. Geben Sie mit Ihnen wir werden in PM umgehen.
entschuldigen Sie, es ist gelöscht
Ich tue Abbitte, es kommt mir ganz nicht heran.
Es nicht ganz, was mir notwendig ist.