14 research outputs found
Testing Protein Leverage in Lean Humans: A Randomised Controlled Experimental Study
A significant contributor to the rising rates of human obesity is an increase in energy intake. The ‘protein leverage hypothesis’ proposes that a dominant appetite for protein in conjunction with a decline in the ratio of protein to fat and carbohydrate in the diet drives excess energy intake and could therefore promote the development of obesity. Our aim was to test the ‘protein leverage hypothesis’ in lean humans by disguising the macronutrient composition of foods offered to subjects under ad libitum feeding conditions. Energy intakes and hunger ratings were measured for 22 lean subjects studied over three 4-day periods of in-house dietary manipulation. Subjects were restricted to fixed menus in random order comprising 28 foods designed to be similar in palatability, availability, variety and sensory quality and providing 10%, 15% or 25% energy as protein. Nutrient and energy intake was calculated as the product of the amount of each food eaten and its composition. Lowering the percent protein of the diet from 15% to 10% resulted in higher (+12±4.5%, p = 0.02) total energy intake, predominantly from savoury-flavoured foods available between meals. This increased energy intake was not sufficient to maintain protein intake constant, indicating that protein leverage is incomplete. Urinary urea on the 10% and 15% protein diets did not differ statistically, nor did they differ from habitual values prior to the study. In contrast, increasing protein from 15% to 25% did not alter energy intake. On the fourth day of the trial, however, there was a greater increase in the hunger score between 1–2 h after the 10% protein breakfast versus the 25% protein breakfast (1.6±0.4 vs 25%: 0.5±0.3, p = 0.005). In our study population a change in the nutritional environment that dilutes dietary protein with carbohydrate and fat promotes overconsumption, enhancing the risk for potential weight gain
Data from: Meta-analysis of variance: an illustration comparing the effects of two dietary interventions on variability in weight
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
Associations between protein to non-protein ratio and intakes of other dietary components in a cohort aged 65–75 years: the Nutrition for Healthy Living Study
Abstract
Objective:
Diets with a low proportion of energy from protein have shown to cause overconsumption of non-protein energy, known as Protein Leverage. Older adults are susceptible to nutritional inadequacy. The aim was to investigate associations between protein to non-protein ratio (P:NP) and intakes of dietary components and assess the nutritional adequacy of individuals aged 65–75 years from the Nutrition for Healthy Living (NHL) Study.
Design:
Cross-sectional. Nutritional intakes from seven-day weighed food records were compared with the Nutrient Reference Values for Australia and New Zealand, Australian Guide to Healthy Eating, Australian Dietary Guidelines and World Health Organisation Free Sugar Guidelines. Associations between P:NP and intakes of dietary components were assessed through linear regression analyses.
Setting:
NHL Study.
Participants:
113 participants.
Results:
Eighty-eight (59 female and 29 male) with plausible dietary data had a median (interquartile range) age of 69 years (67–71), high education level (86 %) and sources of income apart from the age pension (81 %). Substantial proportions had intakes below recommendations for dairy and alternatives (89 %), wholegrain (89 %) and simultaneously exceeded recommendations for discretionary foods (100 %) and saturated fat (92 %). In adjusted analyses, P:NP (per 1 % increment) was associated with lower intakes of energy, saturated fat, free sugar and discretionary foods and higher intakes of vitamin B12, Zn, meat and alternatives, red meat, poultry and wholegrain % (all P < 0·05).
Conclusions:
Higher P:NP was associated with lower intakes of energy, saturated fat, free sugar and discretionary. Our study revealed substantial nutritional inadequacy in this group of higher socio-economic individuals aged 65–75 years
Postnatal nutrition alters body composition in adult offspring exposed to maternal protein restriction
Raised FGF-21 and Triglycerides Accompany Increased Energy Intake Driven by Protein Leverage in Lean, Healthy Individuals: A Randomised Trial
<div><p>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 <i>ad libitum</i> 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 <i>ad libitum</i> 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% <i>ad libitum</i> 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 <i>ad libitum</i> in-house feeding period and may be important in regulation of dietary protein intake.</p><p>Trial Registration</p><p>Australia New Zealand Clinical Trials Registry <a href="http://www.anzctr.org.au/ACTRN12616000144415.aspx" target="_blank">ACTRN12616000144415</a></p></div
Baseline characteristics of the participants.
<p>Baseline characteristics of the participants.</p
Fixed effects estimates from mixed model linear regression analysis for fasting serum lipids in response to percent dietary protein.
<p>Fixed effects estimates from mixed model linear regression analysis for fasting serum lipids in response to percent dietary protein.</p
Fixed effects estimates from mixed model linear regression analysis for glucose control in response to 10, 15 and 25% protein diets.
<p>Fixed effects estimates from mixed model linear regression analysis for glucose control in response to 10, 15 and 25% protein diets.</p