Controlled meal frequency without caloric restriction alters peripheral blood mononuclear cell cytokine production

<p>Abstract</p> <p>Background</p> <p>Intermittent fasting (IF) improves healthy lifespan in animals by a mechanism involving reduced oxidative damage and increased resistance to stress. However, no studies have evaluated the impact of controlled meal frequency on immune responses in human subjects.</p> <p>Objective</p> <p>A study was conducted to establish the effects of controlled diets with different meal frequencies, but similar daily energy intakes, on cytokine production in healthy male and female subjects.</p> <p>Design</p> <p>In a crossover study design with an intervening washout period, healthy normal weight middle-age male and female subjects (n = 15) were maintained for 2 months on controlled on-site one meal per day (OMD) or three meals per day (TMD) isocaloric diets. Serum samples and peripheral blood mononuclear cells (PBMCs) culture supernatants from subjects were analyzed for the presence of inflammatory markers using a multiplex assay.</p> <p>Results</p> <p>There were no significant differences in the inflammatory markers in the serum of subjects on the OMD or TMD diets. There was an increase in the capacity of PBMCs to produce cytokines in subjects during the first month on the OMD or TMD diets.</p> <p>Lower levels of TNF-α, IL-17, MCP-1 and MIP-1β were produced by PBMCs from subjects on the OMD versus TMD diet.</p> <p>Conclusions</p> <p>PBMCs of subjects on controlled diets exhibit hypersensitivities to cellular stimulation suggesting that stress associated with altered eating behavior might affect cytokine production by immune cells upon stimulation. Moreover, stimulated PBMCs derived from healthy individuals on a reduced meal frequency diet respond with a reduced capability to produce cytokines.</p

The Journal of Nutrition Nutrient Requirements and Optimal Nutrition Whey Protein but Not Soy Protein Supplementation Alters Body Weight and Composition in Free-Living Overweight and Obese Adults 1,2

Abstract A double-blind, randomized clinical trial was conducted to determine the effect of consumption of supplemental whey protein (WP), soy protein (SP), and an isoenergetic amount of carbohydrate (CHO) on body weight and composition in freeliving overweight and obese but otherwise healthy participants. Ninety overweight and obese participants were randoml

Comparison of two different physical activity monitors

<p>Abstract</p> <p>Background</p> <p>Understanding the relationships between physical activity (PA) and disease has become a major area of research interest. Activity monitors, devices that quantify free-living PA for prolonged periods of time (days or weeks), are increasingly being used to estimate PA. A range of different activity monitors brands are available for investigators to use, but little is known about how they respond to different levels of PA in the field, nor if data conversion between brands is possible.</p> <p>Methods</p> <p>56 women and men were fitted with two different activity monitors, the Actigraph™ (Actigraph LLC; AGR) and the Actical™ (Mini-Mitter Co.; MM) for 15 days. Both activity monitors were fixed to an elasticized belt worn over the hip, with the anterior and posterior position of the activity monitors randomized. Differences between activity monitors and the validity of brand inter-conversion were measured by <it>t</it>-tests, Pearson correlations, Bland-Altman plots, and coefficients of variation (CV).</p> <p>Results</p> <p>The AGR detected a significantly greater amount of daily PA (216.2 ± 106.2 vs. 188.0 ± 101.1 counts/min, P < 0.0001). The average difference between activity monitors expressed as a CV were 3.1 and 15.5% for log-transformed and raw data, respectively. When a conversion equation was applied to convert datasets from one brand to another, the differences were no longer significant, with CV's of 2.2 and 11.7%, log-transformed and raw data, respectively.</p> <p>Conclusion</p> <p>Although activity monitors predict PA on the same scale (counts/min), the results between these two brands are not directly comparable. However, the data are comparable if a conversion equation is applied, with better results for log-transformed data.</p

Preprandial ghrelin is not affected by macronutrient intake, energy intake or energy expenditure

BACKGROUND: Ghrelin, a peptide secreted by endocrine cells in the gastrointestinal tract, is a hormone purported to have a significant effect on food intake and energy balance in humans. The influence of factors related to energy balance on ghrelin, such as daily energy expenditure, energy intake, and macronutrient intake, have not been reported. Secondly, the effect of ghrelin on food intake has not been quantified under free-living conditions over a prolonged period of time. To investigate these effects, 12 men were provided with an ad libitum cafeteria-style diet for 16 weeks. The macronutrient composition of the diets were covertly modified with drinks containing 2.1 MJ of predominantly carbohydrate (Hi-CHO), protein (Hi-PRO), or fat (Hi-FAT). Total energy expenditure was measured for seven days on two separate occasions (doubly labeled water and physical activity logs). RESULTS: Preprandial ghrelin concentrations were not affected by macronutrient intake, energy expenditure or energy intake (all P > 0.05). In turn, daily energy intake was significantly influenced by energy expenditure, but not ghrelin. CONCLUSION: Preprandial ghrelin does not appear to be influenced by macronutrient composition, energy intake, or energy expenditure. Similarly, ghrelin does not appear to affect acute or chronic energy intake under free-living conditions

Estimates of adherence and error analysis of physical activity data collected via accelerometry in a large study of free-living adults

<p>Abstract</p> <p>Background</p> <p>Activity monitors (AM) are small, electronic devices used to quantify the amount and intensity of physical activity (PA). Unfortunately, it has been demonstrated that data loss that occurs when AMs are not worn by subjects (removals during sleeping and waking hours) tend to result in biased estimates of PA and total energy expenditure (TEE). No study has reported the degree of data loss in a large study of adults, and/or the degree to which the estimates of PA and TEE are affected. Also, no study in adults has proposed a methodology to minimize the effects of AM removals.</p> <p>Methods</p> <p>Adherence estimates were generated from a pool of 524 women and men that wore AMs for 13 – 15 consecutive days. To simulate the effect of data loss due to AM removal, a reference dataset was first compiled from a subset consisting of 35 highly adherent subjects (24 HR; minimum of 20 hrs/day for seven consecutive days). AM removals were then simulated during sleep and between one and ten waking hours using this 24 HR dataset. Differences in the mean values for PA and TEE between the 24 HR reference dataset and the different simulations were compared using paired <it>t</it>-tests and/or coefficients of variation.</p> <p>Results</p> <p>The estimated average adherence of the pool of 524 subjects was 15.8 ± 3.4 hrs/day for approximately 11.7 ± 2.0 days. Simulated data loss due to AM removals during sleeping hours in the 24 HR database (n = 35), resulted in biased estimates of PA (p < 0.05), but not TEE. Losing as little as one hour of data from the 24 HR dataset during waking hours results in significant biases (p < 0.0001) and variability (coefficients of variation between 7 and 21%) in the estimates of PA. Inserting a constant value for sleep and imputing estimates for missing data during waking hours significantly improved the estimates of PA.</p> <p>Conclusion</p> <p>Although estimated adherence was good, measurements of PA can be improved by relatively simple imputation of missing AM data.</p

The Journal of Nutrition Nutrient Requirements and Optimal Nutrition Whey Protein but Not Soy Protein Supplementation Alters Body Weight and Composition in Free-Living Overweight and Obese Adults 1,2

Abstract A double-blind, randomized clinical trial was conducted to determine the effect of consumption of supplemental whey protein (WP), soy protein (SP), and an isoenergetic amount of carbohydrate (CHO) on body weight and composition in freeliving overweight and obese but otherwise healthy participants. Ninety overweight and obese participants were randoml