Developmental contributions to macronutrient selection: a randomized controlled trial in adult survivors of malnutrition

Evidence for protein leverage on total energy intake, but not body mass index, in a large cohort of older adults

BACKGROUND

Protein leverage (PL) is the phenomenon of consuming food until absolute intake of protein approaches a 'target value', such that total energy intake (TEI) varies passively with the ratio of protein: non-protein energy (fat + carbohydrate) in the diet. The PL hypothesis (PLH) suggests that the dilution of protein in energy-dense foods, particularly those rich in carbohydrates and fats, combines with protein leverage to contribute to the global obesity epidemic. Evidence for PL has been reported in younger adults, children and adolescents. This study aimed to test for PL and the protein leverage hypothesis (PLH) in a cohort of older adults.

METHODS

We conducted a retrospective analysis of dietary intake in a cohort of 1699 community-dwelling older adults aged 67-84 years from the NuAge cohort. We computed TEI and the energy contribution (EC) from each macronutrient. The strength of leverage of macronutrients was assessed through power functions ( TEI = μ * EC L ). Body mass index (BMI) was calculated, and mixture models were fitted to predict TEI and BMI from macronutrients' ECs.

RESULTS

In this cohort of older adults, 53% of individuals had obesity and 1.5% had severe cases. The mean TEI was 7673 kJ and macronutrients' ECs were 50.4%, 33.2% and 16.4%, respectively for carbohydrates, fat, and protein. There was a strong negative association (L = -0.37; p < 0.001) between the protein EC and TEI. Each percent of energy intake from protein reduced TEI by 77 kJ on average, ceteris paribus. However, BMI was unassociated with TEI in this cohort.

CONCLUSIONS

Findings indicate clear evidence for PL on TEI, but not on BMI, likely because of aging, body composition, sarcopenia, or protein wasting.

Accumbal μ-opioid receptors and salt taste-elicited hedonic responses in a rodent model of prenatal adversity, and their correlates using human functional genomics

Prenatal adversity is associated with behavioral obesogenic features such as preference for palatable foods. Salt appetite may play a role in the development of adiposity and its consequences in individuals exposed to prenatal adversity, and sodium consumption involves individual differences in accumbal µ-opioid receptors function. We investigated the hedonic responses to salt and the levels of µ-opioid receptors and tyrosine hydroxylase in the nucleus accumbens (Nacc) of pups from an animal model of prenatal dietary restriction. In children, we evaluated the interaction between fetal growth and the genetic background associated with the accumbal µ-opioid receptor gene (OPRM1) expression on sodium consumption during a snack test. Sprague-Dawley dams were randomly allocated from pregnancy day 10 to receive an ad libitum (Adlib) or a 50% restricted (FR) diet. The pups' hedonic responses to a salt solution (NaCl 2%) or water were evaluated on the first day of life. FR and Adlib pups differ in their hedonic responses to salt, and there were decreased levels of accumbal µ-opioid and p-µ-opioid receptors in FR pups. In humans, a test meal and genotyping from buccal epithelial cells were performed in 270 children (38 intrauterine growth restricted-IUGR) at 4 years old from a Canadian prospective cohort (MAVAN). The OPRM1 genetic score predicted the sodium intake in IUGR children, but not in controls. The identification of mechanisms involved in the brain response to prenatal adversity and its consequences in behavioral phenotypes and risk for chronic diseases later in life is important for preventive and therapeutic purposes.

Toward reconciling the roles of FGF21 in protein appetite, sweet preference, and energy expenditure

Fibroblast growth factor 21 (FGF21), an endocrine signal robustly increased by protein restriction independently of an animal's energy status, exerts profound effects on feeding behavior and metabolism. Here, we demonstrate that considering the nutritional contexts within which FGF21 is elevated can help reconcile current controversies over its roles in mediating macronutrient preference, food intake, and energy expenditure. We show that FGF21 is primarily a driver of increased protein intake in mice and that the effect of FGF21 on sweet preference depends on the carbohydrate balance of the animal. Under no-choice feeding, FGF21 infusion either increased or decreased energy expenditure depending on whether the animal was fed a high- or low-energy diet, respectively. We show that while the role of FGF21 in mediating feeding behavior is complex, its role in promoting protein appetite is robust and that the effects on sweet preference and energy expenditure are macronutrient-state-dependent effects of FGF21.

Protein appetite as an integrator in the obesity system: the protein leverage hypothesis

Despite the large volume and extensive range of obesity research, there is substantial disagreement on the causes and effective preventative strategies. We suggest the field will benefit from greater emphasis on integrative approaches that examine how various potential contributors interact, rather than regarding them as competing explanations. We demonstrate the application of nutritional geometry, a multi-nutrient integrative framework developed in the ecological sciences, to obesity research. Such studies have shown that humans, like many other species, regulate protein intake more strongly than other dietary components, and consequently if dietary protein is diluted there is a compensatory increase in food intake-a process called protein leverage. The protein leverage hypothesis (PLH) proposes that the dilution of protein in modern food supplies by fat and carbohydrate-rich highly processed foods has resulted in increased energy intake through protein leverage. We present evidence for the PLH from a variety of sources (mechanistic, experimental and observational), and show that this mechanism is compatible with many other findings and theories in obesity research. This article is part of a discussion meeting issue 'Causes of obesity: theories, conjectures and evidence (Part II)'.

Testing for Protein Leverage in Patients with Gastric Bypass: A Pilot Study

INTRODUCTION

Protein leverage (PL) is the phenomenon whereby a dominant appetite for protein drives overconsumption of energy with a decline in the ratio of protein to fat and carbohydrate in the diet. PL has been independently verified in several randomized control trials, and its predictions are supported by diet surveillance data. Our aim in the present study was to test whether surgical intervention through gastric bypass will ameliorate the PL effect.

METHODS

Ten patients with gastric bypass (2-5 years postsurgical time) were given ad libitum access to study food comprising 10%, 15%, or 25% protein and no access to other foods for 3 days while controlling food palatability and variety. Food intake was measured, and energy and nutrient intakes were calculated. Body weight, blood chemistry, lipid profile, hormones (insulin, leptin, and ghrelin), and creatinine were determined before and after each experimental period.

RESULTS

The gastric bypass patients in our study did not show evidence for protein intake regulation as predicted under PL but ate to constant total energy intake on the 10%, 15%, and 25% protein diets with protein intake varying significantly. Patients lost weight in the three study periods, but significant weight loss was observed only on the 15% protein diet.

CONCLUSION

Our results suggest that gastric bypass might disengage the PL mechanism, thus ameliorating an appetite-specific mechanism that drives energy overconsumption in modern food environments.

The effect of wasting and stunting during severe acute malnutrition in infancy on insulin sensitivity and insulin clearance in adult life

Adults who had non-edematous severe acute malnutrition (SAM) during infancy (i.e., marasmus) have worse glucose tolerance and beta-cell function than survivors of edematous SAM (i.e., kwashiorkor). We hypothesized that wasting and/or stunting in SAM is associated with lower glucose disposal rate (M) and insulin clearance (MCR) in adulthood.We recruited 40 nondiabetic adult SAM survivors (20 marasmus survivors (MS) and 20 kwashiorkor survivors (KS)) and 13 matched community controls. We performed 150-minute hyperinsulinaemic, euglycaemic clamps to estimate M and MCR. We also measured serum adiponectin, anthropometry, and body composition. Data on wasting (weight-for-height) and stunting (height-for-age) were abstracted from the hospital records.Children with marasmus had lower weight-for-height z-scores (WHZ) (-3.8 ± 0.9 vs. -2.2 ± 1.4; P < 0.001) and lower height-for-age z-scores (HAZ) (-4.6 ± 1.1 vs. -3.4 ± 1.5; P = 0.0092) than those with kwashiorkor. As adults, mean age (SD) of participants was 27.2 (8.1) years; BMI was 23.6 (5.0) kg/m². SAM survivors and controls had similar body composition. MS and KS and controls had similar M (9.1 ± 3.2; 8.7 ± 4.6; 6.9 ± 2.5 mg.kg^-1.min^-1 respectively; P = 0.3) and MCR. WHZ and HAZ were not associated with M, MCR or adiponectin even after adjusting for body composition.Wasting and stunting during infancy are not associated with insulin sensitivity and insulin clearance in lean, young, adult survivors of SAM. These data are consistent with the finding that glucose intolerance in malnutrition survivors is mostly due to beta-cell dysfunction.

Macronutrient (im)balance drives energy intake in an obesogenic food environment: An ecological analysis

OBJECTIVE

The protein leverage hypothesis (PLH) postulates that strong regulation of protein intake drives energy overconsumption and obesity when human diets are diluted by fat and carbohydrates. The two predictions of the PLH are that humans (i) regulate intake to maintain protein within a narrow range and that (ii) energy intake is an inverse function of percentage energy from protein because absolute protein intake is maintained within narrow limits.

METHODS

Multidimensional nutritional geometry was used to test the predictions of the PLH using dietary data from the Australian National Nutrition and Physical Activity Survey.

RESULTS

Both predictions of the PLH were confirmed in a population setting: the mean protein intake was 18.4%, and energy intake decreased with increasing energy from protein (L = -0.18, p &lt; 0.0001). It was demonstrated that highly processed discretionary foods are a significant diluent of protein and associated with increased energy but not increased protein intake.

CONCLUSIONS

These results support an integrated ecological and mechanistic explanation for obesity, in which low-protein highly processed foods lead to higher energy intake because of the biological response to macronutrient imbalance driven by a dominant appetite for protein. This study supports a central role for protein in the obesity epidemic, with significant implications for global health.

A Comparison of the Australian Dietary Guidelines to the NOVA Classification System in Classifying Foods to Predict Energy Intakes and Body Mass Index

NOVA classification distinguishes foods by level of processing, with evidence suggesting that a high intake of ultra-processed foods (UPFs, NOVA category 4) leads to obesity. The Australian Dietary Guidelines, in contrast, discourage excess consumption of “discretionary foods” (DFs), defined according to their composition. Here, we (i) compare the classification of Australian foods under the two systems, (ii) evaluate their performance in predicting energy intakes and body mass index (BMI) in free-living Australians, and (iii) relate these outcomes to the protein leverage hypothesis of obesity. Secondary analysis of the Australian National Nutrition and Physical Activity Survey was conducted. Non-protein energy intake increased by 2.1 MJ (p < 0.001) between lowest and highest tertiles of DF intake, which was significantly higher than UPF (0.6 MJ, p < 0.001). This demonstrates that, for Australia, the DF classification better distinguishes foods associated with high energy intakes than does the NOVA system. BMI was positively associated with both DFs (−1. 0, p = 0.0001) and UPFs (−1.1, p = 0.0001) consumption, with no difference in strength of association. For both classifications, macronutrient and energy intakes conformed closely to the predictions of protein leverage. We account for the similarities and differences in performance of the two systems in an analysis of Australian foods.

Testing the protein-leverage hypothesis using population surveillance data

It is hypothesized that humans exhibit 'protein leverage' (PL), whereby regulation of absolute protein intake results in the over-consumption of non-protein food on low percentage protein diets. Testing for PL using dietary surveillance data involves seeking evidence for a negative association between total energy intake and percentage energy from protein. However, it is unclear whether such an association might emerge without PL due to the structure of intake data (protein and non-protein intakes have different means and variances and covary). We derive a set of models that describe the association between the expected estimate of PL and the distributions of protein and non-protein intake. Models were validated via simulation. Patterns consistent with PL will not emerge simply because protein intake has a lower mean and/or variance than non-protein. Rather, evidence of PL is observed where protein has a lower index of dispersion (variance/mean) than non-protein intake. Reciprocally, the stronger PL is the lower the index of dispersion for protein intake becomes. Disentangling causality is ultimately beyond the power of observational data alone. However, we show that one can correct for confounders (e.g. age) in generating signals of PL, and describe independent measures that can anchor inferences around the role of PL.

An integrative approach to dietary balance across the life course

Animals require specific blends of nutrients that vary across the life course and with circumstances, e.g., health and activity levels. Underpinning and complicating these requirements is that individual traits may be optimized on different dietary compositions leading to nutrition-mediated trade-offs among outcomes. Additionally, the food environment may constrain which nutrient mixtures are achievable. Natural selection has equipped animals for solving such multi-dimensional, dynamic challenges of nutrition, but little is understood about the details and their theoretical and practical implications. We present an integrative framework, nutritional geometry, which models complex nutritional interactions in the context of multiple nutrients and across levels of biological organization (e.g., cellular, individual, and population) and levels of analysis (e.g., mechanistic, developmental, ecological, and evolutionary). The framework is generalizable across different situations and taxa. We illustrate this using examples spanning insects to primates and settings (laboratory, and the wild), and demonstrate its relevance for human health.

Daily protein prioritization and long-term nutrient balancing in a dietary generalist, the blue monkey

Animals make dietary choices to achieve adequate nutrient intake; however, it is challenging to study such nutritional strategies in wild populations. We explored the nutritional strategy of a generalist social primate, the blue monkey (Cercopithecus mitis). We hypothesized that females balance intake of nutrients, specifically non-protein energy and protein, both on a daily and long-term basis. When balancing was not possible, we expected subjects to prioritize constant protein intake, allowing non-protein energy to vary more. To understand the ecology of nutrient balancing, we examined how habitat use, food availability, diet composition, social dominance rank, and reproductive demand influenced nutrient intake. Over 9 months, we conducted 371 all-day focal follows on 24 subjects in Kakamega Forest, Kenya. Females exhibited short- and long-term nutritional strategies. Daily, they balanced non-protein energy to protein intake but when balancing was impossible, monkeys prioritized protein intake. Longer term, they balanced non-protein energy:protein intake in a 3.8:1 ratio. The ratio related positively to fruit in the diet and negatively to time in near-natural forest, but we found no evidence that it related to food availability, reproductive demand, or dominance rank. Lower-ranked females had broader daily diets, however, which may reflect behavioral feeding strategies to cope with social constraints. Overall, females prioritized daily protein, allowing less variation in protein intake than other aspects such as non-protein energy:protein ratio and non-protein energy intake. The emerging pattern in primates suggests that diverse dietary strategies evolved to allow adherence to a nutrient balance of non-protein energy:protein despite various social and environmental constraints.

Protein Leverage: Theoretical Foundations and Ten Points of Clarification

Much attention has been focused on fats and carbohydrates as the nutritional causes of energy overconsumption and obesity. In 2003, a model of intake regulation was proposed in which the third macronutrient, protein, is not only involved but is a primary driver of calorie intake via its interactions with carbohydrates and fats. This model, called protein leverage, posits that the strong regulation of protein intake causes the overconsumption of fats and carbohydrates (hence total energy) on diets with a low proportion of energy from protein and their underconsumption on diets with a high proportion of protein. Protein leverage has since been demonstrated in a range of animal studies and in several studies of human macronutrient regulation, and its potential role in contributing to the obesity epidemic is increasingly attracting discussion. Over recent years, however, several misconceptions about protein leverage have arisen. Our aim in this paper is to briefly outline some key aspects of the underlying theory and clarify 10 points of misunderstanding that have the potential to divert attention from the substantive issues.

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.

Neonatal Nutrition Predicts Energy Balance in Young Adults Born Preterm at Very Low Birth Weight

Epidemiological studies and animal models suggest that early postnatal nutrition and growth can influence adult health. However, few human studies have objective recordings of early nutrient intake. We studied whether nutrient intake and growth during the first 9 weeks after preterm birth with very low birth weight (VLBW, <1500 g) predict total energy intake, resting energy expenditure (REE), physical activity and food preferences in young adulthood. We collected daily nutritional intakes and weights during the initial hospital stay from hospital records for 127 unimpaired VLBW participants. At an average age 22.5 years, they completed a three-day food record and a physical activity questionnaire and underwent measurements of body composition (dual X-ray absorptiometry; n = 115 with adequate data) and REE (n = 92 with adequate data). We used linear regression and path analysis to investigate associations between neonatal nutrient intake and adult outcomes. Higher energy, protein and fat intakes during the first three weeks of life predicted lower relative (=per unit lean body mass) energy intake and relative REE in adulthood, independent of other pre- and neonatal factors. In path analysis, total effects of early nutrition and growth on relative energy intake were mostly explained by direct effects of early life nutrition. A path mediated by early growth reached statistical significance only for protein intake. There were no associations of neonatal intakes with physical activity or food preferences in adulthood. As a conclusion, higher intake of energy and nutrients during first three weeks of life of VLBW infants predicts energy balance after 20 years. This association is partly mediated through postnatal growth.

Ultra-processed foods, protein leverage and energy intake in the USA

OBJECTIVE

Experimental studies have shown that human macronutrient regulation minimizes variation in absolute protein intake and consequently energy intake varies passively with dietary protein density ('protein leverage'). According to the 'protein leverage hypothesis' (PLH), protein leverage interacts with a reduction in dietary protein density to drive energy overconsumption and obesity. Worldwide increase in consumption of ultra-processed foods (UPF) has been hypothesized to be an important determinant of dietary protein dilution, and consequently an ecological driving force of energy overconsumption and the obesity pandemic. The present study examined the relationships between dietary contribution of UPF, dietary proportional protein content and the absolute intakes of protein and energy.

DESIGN

National representative cross-sectional study.

SETTING

National Health and Nutrition Examination Survey 2009-2010.

SUBJECTS

Participants (n 9042) aged ≥2 years with at least one day of 24 h dietary recall data.

RESULTS

We found a strong inverse relationship between consumption of UPF and dietary protein density, with mean protein content dropping from 18·2 to 13·3 % between the lowest and highest quintiles of dietary contribution of UPF. Consistent with the PLH, increase in the dietary contribution of UPF (previously shown to be inversely associated with protein density) was also associated with a rise in total energy intake, while absolute protein intake remained relatively constant.

CONCLUSIONS

The protein-diluting effect of UPF might be one mechanism accounting for their association with excess energy intake. Reducing UPF contribution in the US diet may be an effective way to increase its dietary protein concentration and prevent excessive energy intake.

Raised FGF-21 and Triglycerides Accompany Increased Energy Intake Driven by Protein Leverage in Lean, Healthy Individuals: A Randomised Trial

A dominant appetite for protein drives increased energy intake in humans when the proportion of protein in the diet is reduced down to approximately 10% of total energy. Compensatory feeding for protein is apparent over a 1–2 d period but the mechanisms driving this regulation are not fully understood. Fibroblast growth factor-21 (FGF-21) has been identified as a candidate protein signal as levels increase in the circulation when dietary protein is low. The aim of this randomised controlled trial was to assess whether changes in percent dietary protein over a 4 d ad libitum experimental period in lean, healthy participants influenced energy intake, metabolic health, circulating FGF-21 and appetite regulating hormones including ghrelin, glucagon like peptide-1 and cholecystokinin. Twenty-two lean, healthy participants were fed ad libitum diets containing 10, 15 and 25% protein, over three, 4 d controlled, in-house experimental periods. Reduced dietary protein intake from 25% to 10% over a period of 4 d was associated with 14% increased energy intake (p = 0.02) as previously reported, and a 6-fold increase in fasting circulating plasma FGF-21 levels (p<0.0001), a 1.5-fold increase in serum triglycerides (p<0.0001), and a 0.9-fold decrease in serum total cholesterol (p = 0.02). Serum HDL cholesterol was reduced with a reduction in dietary protein from 15% to 10% (p = 0.01) over 4 d but not from 25% to 10% (p = 0.1) and the change from baseline was not different between diets. Plasma fasting insulin levels following the 4 d study period were significantly lower following the 25% ad libitum study period compared to the 15% protein period (p = 0.014) but not the 10% protein period (p = 0.2). Variability in interstitial glucose during each study period increased with a decrease in dietary protein from 25% to 15% and 10% (p = 0.001 and p = 0.04, respectively). Ghrelin, glucagon-like peptide-1 and cholecystokinin were unchanged. Increases in energy intake, plasma FGF-21 and serum triglycerides were associated with reductions in percent dietary protein from 25% to 10% energy over a 4 d ad libitum in-house feeding period and may be important in regulation of dietary protein intake.

Meta-analysis of variance: an illustration comparing the effects of two dietary interventions on variability in weight

New meta-analysis methods from evolutionary biology allow us to ask how treatments affect variability, as opposed to just the average. Using these methods we demonstrate that low carbohydrate ad libitum diets may have more variable outcomes than calorie restricted diets.

Meta-analysis, which drives evidence-based practice, typically focuses on the average response of subjects to a treatment. For instance in nutritional research the difference in average weight of participants on different diets is typically used to draw conclusions about the relative efficacy of interventions. As a result of their focus on the mean, meta-analyses largely overlook the effects of treatments on inter-subject variability. Recent tools from the study of biological evolution, where inter-individual variability is one of the key ingredients for evolution by natural selection, now allow us to study inter-subject variability using established meta-analytic models. Here we use meta-analysis to study how low carbohydrate (LC) ad libitum diets and calorie restricted diets affect variance in mass. We find that LC ad libitum diets may have a more variable outcome than diets that prescribe a reduced calorie intake. Our results suggest that whilst LC diets are effective in a large proportion of the population, for a subset of individuals, calorie restricted diets may be more effective. There is evidence that LC ad libitum diets rely on appetite suppression to drive weight loss. Extending this hypothesis, we suggest that between-individual variability in protein appetite may drive the trends that we report. A priori identification of an individual’s target intake for protein may help define the most effective dietary intervention to prescribe for weight loss.