Time to revisit the passive overconsumption hypothesis? Humans show sensitivity to calories in energy-rich meals

BACKGROUND

A possible driver of obesity is insensitivity (passive overconsumption) to food energy density (ED, kcal/g); however, it is unclear whether this insensitivity applies to all meals.

OBJECTIVES

We assessed the influence of ED on energy intake (kcal) across a broad and continuous range of EDs comprised of noncovertly manipulated, real-world meals. We also allowed for the possibility that the association between energy intake and ED is nonlinear.

METHODS

We completed a secondary analysis of 1519 meals which occurred in a controlled environment as part of a study conducted by Hall and colleagues to assess the effects of food ultra-processing on energy intake. To establish the generalizability of the findings, the analyses were repeated in 32,162 meals collected from free-living humans using data from the UK National Diet and Nutrition Survey (NDNS). Segmented regressions were performed to establish ED "breakpoints" at which the association between consumed meal ED and mean centered meal caloric intake (kcal) changed.

RESULTS

Significant breakpoints were found in both the Hall et al. data set (1.41 kcal/g) and the NDNS data set (1.75 and 2.94 kcal/g). Centered meal caloric intake did not increase linearly with consumed meal ED, and this pattern was captured by a 2-component ("volume" and "calorie content" [biologically derived from the sensing of fat, carbohydrate, and protein]) model of physical meal size (g), in which volume is the dominant signal with lower energy-dense foods and calorie content is the dominant signal with higher energy-dense foods.

CONCLUSIONS

These analyses reveal that, on some level, humans are sensitive to the energy content of meals and adjust meal size to minimize the acute aversive effects of overconsumption. Future research should consider the relative importance of volume and calorie-content signals, and how individual differences impact everyday dietary behavior and energy balance.

The energy balance model of obesity: beyond calories in, calories out

A recent Perspective article described the "carbohydrate-insulin model (CIM)" of obesity, asserting that it "better reflects knowledge on the biology of weight control" as compared with what was described as the "dominant energy balance model (EBM)," which fails to consider "biological mechanisms that promote weight gain." Unfortunately, the Perspective conflated and confused the principle of energy balance, a law of physics that is agnostic as to obesity mechanisms, with the EBM as a theoretical model of obesity that is firmly based on biology. In doing so, the authors presented a false choice between the CIM and a caricature of the EBM that does not reflect modern obesity science. Here, we present a more accurate description of the EBM where the brain is the primary organ responsible for body weight regulation operating mainly below our conscious awareness via complex endocrine, metabolic, and nervous system signals to control food intake in response to the body's dynamic energy needs as well as environmental influences. We also describe the recent history of the CIM and show how the latest "most comprehensive formulation" abandons a formerly central feature that required fat accumulation in adipose tissue to be the primary driver of positive energy balance. As such, the new CIM can be considered a special case of the more comprehensive EBM but with a narrower focus on diets high in glycemic load as the primary factor responsible for common obesity. We review data from a wide variety of studies that address the validity of each model and demonstrate that the EBM is a more robust theory of obesity than the CIM.

The energy balance model of obesity: beyond calories in, calories out

A recent Perspective article described the "carbohydrate-insulin model (CIM)" of obesity, asserting that it "better reflects knowledge on the biology of weight control" as compared with what was described as the "dominant energy balance model (EBM)," which fails to consider "biological mechanisms that promote weight gain." Unfortunately, the Perspective conflated and confused the principle of energy balance, a law of physics that is agnostic as to obesity mechanisms, with the EBM as a theoretical model of obesity that is firmly based on biology. In doing so, the authors presented a false choice between the CIM and a caricature of the EBM that does not reflect modern obesity science. Here, we present a more accurate description of the EBM where the brain is the primary organ responsible for body weight regulation operating mainly below our conscious awareness via complex endocrine, metabolic, and nervous system signals to control food intake in response to the body's dynamic energy needs as well as environmental influences. We also describe the recent history of the CIM and show how the latest "most comprehensive formulation" abandons a formerly central feature that required fat accumulation in adipose tissue to be the primary driver of positive energy balance. As such, the new CIM can be considered a special case of the more comprehensive EBM but with a narrower focus on diets high in glycemic load as the primary factor responsible for common obesity. We review data from a wide variety of studies that address the validity of each model and demonstrate that the EBM is a more robust theory of obesity than the CIM.

Energy compensation and metabolic adaptation: "The Biggest Loser" study reinterpreted

"The Biggest Loser" weight-loss competition offered a unique opportunity to investigate human energy metabolism and body composition before, during, and after an extreme lifestyle intervention. Here, I reinterpret the results of "The Biggest Loser" study in the context of a constrained model of human energy expenditure. Specifically, "The Biggest Loser" contestants engaged in large, sustained increases in physical activity that may have caused compensatory metabolic adaptations to substantially decrease resting metabolic rate and thereby minimize changes in total energy expenditure. This interpretation helps explain why the magnitude of persistent metabolic adaptation was largest in contestants with the greatest increases in sustained physical activity and why weight-loss interventions involving lower levels of physical activity have not measured similarly large metabolic adaptations. Additional longitudinal studies quantifying the interrelationships between various components of energy expenditure and energy intake are needed to better understand the dynamics of human body weight regulation.

Eliminate or reformulate ultra-processed foods? Biological mechanisms matter

Increased ultra-processed foods (UPFs) in the food supply have plausibly caused the rise in obesity prevalence and related chronic diseases. To address this public health concern, policies targeting reformulation or elimination of UPF categories will require improved understanding of the biological mechanisms whereby UPFs lead to overconsumption and poor health.

Neonatal exposure to a wild-derived microbiome protects mice against diet-induced obesity

Obesity and its consequences are among the greatest challenges in healthcare. The gut microbiome is recognized as a key factor in the pathogenesis of obesity. Using a mouse model, we show here that a wild-derived microbiome protects against excessive weight gain, severe fatty liver disease and metabolic syndrome during a 10-week course of high-fat diet. This phenotype is transferable only during the first weeks of life. In adult mice, neither transfer nor severe disturbance of the wild-type microbiome modifies the metabolic response to a high-fat diet. The protective phenotype is associated with increased secretion of metabolic hormones and increased energy expenditure through activation of brown adipose tissue. Thus, we identify a microbiome that protects against weight gain and its negative consequences through metabolic programming in early life. Translation of these results to humans may identify early-life therapeutics that protect against obesity.

Describing the Weight-Reduced State: Physiology, Behavior, and Interventions

Although many persons with obesity can lose weight by lifestyle (diet and physical activity) therapy, successful long-term weight loss is difficult to achieve, and most people who lose weight regain their lost weight over time. The neurohormonal, physiological, and behavioral factors that promote weight recidivism are unclear and complex. The National Institute of Diabetes and Digestive and Kidney Diseases convened a workshop in June 2019, titled "The Physiology of the Weight-Reduced State," to explore the mechanisms and integrative physiology of adaptations in appetite, energy expenditure, and thermogenesis that occur in the weight-reduced state and that may oppose weight-loss maintenance. The proceedings from the first session of this workshop are presented here. Drs. Michael Rosenbaum, Kevin Hall, and Rudolph Leibel discussed the physiological factors that contribute to weight regain; Dr. Michael Lowe discussed the biobehavioral issues involved in weight-loss maintenance; Dr. John Jakicic discussed the influence of physical activity on long-term weight-loss maintenance; and Dr. Louis Aronne discussed the ability of drug therapy to maintain weight loss.

Effect of a plant-based, low-fat diet versus an animal-based, ketogenic diet on ad libitum energy intake

The carbohydrate-insulin model of obesity posits that high-carbohydrate diets lead to excess insulin secretion, thereby promoting fat accumulation and increasing energy intake. Thus, low-carbohydrate diets are predicted to reduce ad libitum energy intake as compared to low-fat, high-carbohydrate diets. To test this hypothesis, 20 adults aged 29.9 ± 1.4 (mean ± s.e.m.) years with body mass index of 27.8 ± 1.3 kg m^-2 were admitted as inpatients to the National Institutes of Health Clinical Center and randomized to consume ad libitum either a minimally processed, plant-based, low-fat diet (10.3% fat, 75.2% carbohydrate) with high glycemic load (85 g 1,000 kcal^-1) or a minimally processed, animal-based, ketogenic, low-carbohydrate diet (75.8% fat, 10.0% carbohydrate) with low glycemic load (6 g 1,000 kcal^-1) for 2 weeks followed immediately by the alternate diet for 2 weeks. One participant withdrew due to hypoglycemia during the low-carbohydrate diet. The primary outcomes compared mean daily ad libitum energy intake between each 2-week diet period as well as between the final week of each diet. We found that the low-fat diet led to 689 ± 73 kcal d^-1 less energy intake than the low-carbohydrate diet over 2 weeks (P < 0.0001) and 544 ± 68 kcal d^-1 less over the final week (P < 0.0001). Therefore, the predictions of the carbohydrate-insulin model were inconsistent with our observations. This study was registered on ClinicalTrials.gov as NCT03878108 .

Imprecision nutrition? Different simultaneous continuous glucose monitors provide discordant meal rankings for incremental postprandial glucose in subjects without diabetes

BACKGROUND

High postprandial glucose excursions may increase risk for disease. Individuals have widely varying glucose responses to different meals, and precision nutrition approaches often seek to personalize diets to minimize postprandial glycemic responses as measured by continuous glucose monitors (CGMs). However, it is unknown whether different CGM devices result in concordant meal rankings according to postprandial glycemic excursions.

OBJECTIVE

We explored whether meal rankings according to postprandial glycemic excursions differ between 2 simultaneously worn CGMs.

METHODS

We collected 27,489 simultaneous measurements from Dexcom G4 Platinum and Abbott Freestyle Libre Pro CGMs during 28 inpatient days in 16 adults without diabetes. Simultaneous glucose measurements obtained for 2 h following 760 ad libitum meals were used to compare within-subject meal rankings between the CGM devices according to their incremental glucose response.

RESULTS

Postprandial responses to ad libitum meals were highly variable, with the Abbott and Dexcom systems resulting in within-subject incremental mean ± SD glucose CVs of 91.7 ± 1.9% and 94.2 ± 2.7%, respectively. Within-subject meal rankings for incremental glycemic responses were relatively discordant between CGMs, with a mean Kendall rank correlation coefficient of 0.43 ± 0.05. Meals in the bottom compared with those in the top half of incremental glycemic responses ranked by Abbott resulted in 50 ± 10% (P = 0.0002) less glycemic reduction as measured by Dexcom, and vice versa. The missing glycemic reduction by eating meals ranked according to the discordant CGM was inversely correlated with each subject's Kendall rank correlation coefficient (r = -0.95; P < 0.0001).

CONCLUSIONS

Precision nutrition approaches that use CGMs to personalize meal recommendations for minimizing glycemic excursions may be premature given the discordance of within-subject meal rankings between simultaneous CGM devices. More research is needed to clarify the source of this imprecision. This trial was registered at clinicaltrials.gov as NCT03407053.

Ketogenic Diets Alter the Gut Microbiome Resulting in Decreased Intestinal Th17 Cells

Very low-carbohydrate, high-fat ketogenic diets (KDs) induce a pronounced shift in metabolic fuel utilization that elevates circulating ketone bodies; however, the consequences of these compounds for host-microbiome interactions remain unknown. Here, we show that KDs alter the human and mouse gut microbiota in a manner distinct from high-fat diets (HFDs). Metagenomic and metabolomic analyses of stool samples from an 8-week inpatient study revealed marked shifts in gut microbial community structure and function during the KD. Gradient diet experiments in mice confirmed the unique impact of KDs relative to HFDs with a reproducible depletion of bifidobacteria. In vitro and in vivo experiments showed that ketone bodies selectively inhibited bifidobacterial growth. Finally, mono-colonizations and human microbiome transplantations into germ-free mice revealed that the KD-associated gut microbiota reduces the levels of intestinal pro-inflammatory Th17 cells. Together, these results highlight the importance of trans-kingdom chemical dialogs for mediating the host response to dietary interventions.

Mouse Thermoregulation: Introducing the Concept of the Thermoneutral Point

Human and mouse thermal physiology differ due to dissimilar body sizes. Unexpectedly, in mice we found no ambient temperature zone where both metabolic rate and body temperature were constant. Body temperature began increasing once cold-induced thermogenesis was no longer required. This result reproduced in male, female, C57BL/6J, 129, chow-fed, diet-induced obese, and ob/ob mice as well as Trpv1-/-;Trpm8-/-;Trpa1-/- mice lacking thermal sensory channels. During the resting-light phase, the energy expenditure minimum spanned ∼4°C of ambient temperature, whereas in the active-dark phase it approximated a point. We propose the concept of a thermoneutral point (TNP), a discrete ambient temperature below which energy expenditure increases and above which body temperature increases. Humans do not have a TNP. As studied, the mouse TNP is ∼29°C in light phase and ∼33°C in dark phase. These observations inform how thermoneutrality is defined and how mice are used to model human energy physiology and drug development.

Exceptional Reported Effects and Data Anomalies Merit Explanation from "A randomized controlled trial of coordination exercise on cognitive function in obese adolescents" by

We read the recent article in Psychology of Sport and Exercise by Liu et al. ("A randomized controlled trial of coordination exercise on cognitive function in obese adolescents") with great interest. Our interest in the article stemmed from the extraordinary differences in obesity-related outcomes reported in response to a rope-jumping intervention. We requested the raw data from the authors to confirm the results and, after the journal editors reinforced our request, the authors graciously provided us with their data. We share our evaluation of the original data herein, which includes concerns that weight and BMI loss by the intervention appears extraordinary in both magnitude and aspects of the distributions. We request that the authors address our findings by providing explanations of the extraordinary data or correcting any errors that may have occurred in the original report, as appropriate.

Unintentional error in formula preparation and its simulated impact on infant weight and adiposity

BACKGROUND

Accelerated weight gain in infancy is a public health issue and is likely due to feeding behaviours.

OBJECTIVES

To test the accuracy of individuals to dispense infant formula as compared with recommended serving sizes and to estimate the effect of dispensing inaccuracy on infant growth.

METHODS

Fifty-three adults dispensed infant formula powder for three servings of 2, 4, 6, and 8 fl oz bottles, in random order. The weight of dispensed infant formula powder was compared with the recommended serving size weight on the nutrition label. A novel mathematical model was used to estimate the impact of formula dispensing on infant weight and adiposity.

RESULTS

Nineteen percent of bottles (20 of 636) prepared contained the recommended amount of infant formula powder. Three percent were underdispensed, and 78% of bottles were overdispensed, resulting in 11% additional infant formula powder. Mathematical modelling feeding 11% above energy requirements exclusively for 6 months for male and female infants suggested infants at the 50th percentile for weight at birth would reach the 75th percentile with increased adiposity by 6 months.

CONCLUSIONS

Inaccurate measurement of infant formula powder and overdispensing, which is highly prevalent, specifically, may contribute to rapid weight gain and increased adiposity in formula-fed infants.

The Potential Role of Protein Leverage in the US Obesity Epidemic

The protein leverage model of obesity posits that decreasing the protein fraction of the diet leads to compensatory increases in total energy intake in an attempt to maintain a target amount of absolute protein consumed. The resulting increased energy intake thereby causes weight gain. According to food balance sheets published by the Food and Agriculture Organization of the United Nations, while the absolute protein content of the US food supply has increased since the early 1970s, the fraction of available calories from protein has decreased by ~1% because of greater increases in available carbohydrate and fat. Counterintuitively, even such a small decrease in the protein fraction of the food supply has the potential to result in relatively large increases in energy intake according to the protein leverage model. Therefore, while the protein leverage effect is unlikely to fully explain the obesity epidemic, its potential contribution should not be ignored.

Ultra-Processed Diets Cause Excess Calorie Intake and Weight Gain: An Inpatient Randomized Controlled Trial of Ad Libitum Food Intake

We investigated whether ultra-processed foods affect energy intake in 20 weight-stable adults, aged (mean ± SE) 31.2 ± 1.6 years and BMI = 27 ± 1.5 kg/m². Subjects were admitted to the NIH Clinical Center and randomized to receive either ultra-processed or unprocessed diets for 2 weeks immediately followed by the alternate diet for 2 weeks. Meals were designed to be matched for presented calories, energy density, macronutrients, sugar, sodium, and fiber. Subjects were instructed to consume as much or as little as desired. Energy intake was greater during the ultra-processed diet (508 ± 106 kcal/day; p = 0.0001), with increased consumption of carbohydrate (280 ± 54 kcal/day; p < 0.0001) and fat (230 ± 53 kcal/day; p = 0.0004), but not protein (-2 ± 12 kcal/day; p = 0.85). Weight changes were highly correlated with energy intake (r = 0.8, p < 0.0001), with participants gaining 0.9 ± 0.3 kg (p = 0.009) during the ultra-processed diet and losing 0.9 ± 0.3 kg (p = 0.007) during the unprocessed diet. Limiting consumption of ultra-processed foods may be an effective strategy for obesity prevention and treatment.