Penny Rumbold

Breakfast and exercise contingently affect postprandial metabolism and energy balance in physically active males

The present study examined the impact of breakfast and exercise on postprandial metabolism, appetite and macronutrient balance. A sample of twelve (blood variables n 11) physically active males completed four trials in a randomised, crossover design comprising a continued overnight fast followed by: (1) rest without breakfast (FR); (2) exercise without breakfast (FE); (3) breakfast consumption (1859 kJ) followed by rest (BR); (4) breakfast consumption followed by exercise (BE). Exercise was continuous, moderate-intensity running (expending approximately 2·9 MJ of energy). The equivalent time was spent sitting during resting trials. A test drink (1500 kJ) was ingested on all trials followed 90 min later by an ad libitum lunch. The difference between the BR and FR trials in blood glucose time-averaged AUC following test drink consumption approached significance (BR: 4·33 (SEM 0·14) v. FR: 4·75 (SEM 0·16) mmol/l; P=0·08); but it was not different between FR and FE (FE: 4·77 (SEM 0·14) mmol/l; P=0·65); and was greater in BE (BE: 4·97 (SEM 0·13) mmol/l) v. BR (P=0·012). Appetite following the test drink was reduced in BR v. FR (P=0·006) and in BE v. FE (P=0·029). Following lunch, the most positive energy balance was observed in BR and least positive in FE. Regardless of breakfast, acute exercise produced a less positive energy balance following ad libitum lunch consumption. Energy and fat balance is further reduced with breakfast omission. Breakfast improved the overall appetite responses to foods consumed later in the day, but abrogated the appetite-suppressive effect of exercise.

Effect of calcium intake on fat oxidation in adults: a meta-analysis of randomized, controlled trials

Calcium intake is likely to increase body fat loss during energy restriction. Part of this effect may be explained by increased fat oxidation in the presence of a similar energy balance, yet studies have not provided a conclusive answer. Therefore a meta‐analysis was performed to determine whether chronic or acute high calcium intake increases fat oxidation. Randomized controlled trials of high calcium intake in human adults where measures of fat oxidation were taken were included. A random‐effects meta‐analysis was performed on outcomes expressed as standardized mean differences. Chronic high calcium intake increased fat oxidation by a standardized mean difference of 0.42 (95% confidence intervals: 0.14, 0.69; P = 0.003; estimated to correspond to an 11% increase), displaying low heterogeneity (I2 = 18%), which was more prominent when habitual calcium intake was low (<700 mg d−1). Acute high calcium intake increased fat oxidation by a standardized mean difference of 0.41 (0.04, 0.77; P = 0.03), with low heterogeneity (I2 = 19%), yet sensitivity analysis revealed that this effect was relatively weak. In conclusion, chronic high calcium intake is likely to increase rates of fat oxidation. The effects of acute high calcium intake appear to point in the same direction, but further work is needed to permit a greater degree of certainty.

Assessment of Energy Intake and Energy Expenditure of Male Adolescent Academy-Level Soccer Players during a Competitive Week

This study investigated the energy intake and expenditure of professional adolescent academy-level soccer players during a competitive week. Over a seven day period that included four training days, two rest days and a match day, energy intake (self-reported weighed food diary and 24-h recall) and expenditure (tri-axial accelerometry) were recorded in 10 male players from a professional English Premier League club. The mean macronutrient composition of the dietary intake was 318 ± 24 g·day−1 (5.6 ± 0.4 g·kg−1 BM) carbohydrate, 86 ± 10 g·day−1 (1.5 ± 0.2 g·kg−1 BM) protein and 70 ± 7 g·day−1 (1.2 ± 0.1 g·kg−1 BM) fats, representing 55% ± 3%, 16% ± 1%, and 29% ± 2% of mean daily energy intake respectively. A mean daily energy deficit of −1302 ± 1662 kJ (p = 0.035) was observed between energy intake (9395 ± 1344 kJ) and energy expenditure (10679 ± 1026 kJ). Match days (−2278 ± 2307 kJ, p = 0.012) and heavy training days (−2114 ± 2257 kJ, p = 0.016) elicited the greatest deficits between intake and expenditure. In conclusion, the mean daily energy intake of professional adolescent academy-level soccer players was lower than the energy expended during a competitive week. The magnitudes of these deficits were greatest on match and heavy training days. These findings may have both short and long term implications on the performance and physical development of adolescent soccer players.

Agreement between two methods of dietary data collection in female adolescent netball players

The accuracy of a combined dietary data collection method (self-reported, weighed food diary and 24-h recall technique) in 13 female, adolescent netball players (14-16 years) was explored. The girls were observed for a 12 h period (08:00-20:00), during which food and drink items were available ad libitum throughout the day and for the period between 20:00 and 08:00 the following morning. All items were covertly weighed before and after consumption to calculate observed energy intake. To calculate participant reported energy intake, food and drink items were weighed and recorded in a food diary by the participants, which was then supplemented with information from the 24-h recall the following morning. Agreement between observed and participant reported energy intake was calculated using the Bland and Altman technique. The mean difference between observed and participant reported energy intake was 0.46 MJ d(-1) (change in mean of 4.2%) indicating a slight bias towards over-reporting using the combined dietary data collection method. There was good agreement at the group level with the confidence interval for bias ranging from 0.00 to 0.92 MJ d(-1). The combined dietary data collection method is an effective technique to employ in 14-16-year old, female adolescent netball players when quantifying energy intake.

Short communication: Patterns of dairy consumption in free-living children and adolescents

According to national survey data, dairy food consumption has fallen in recent years and declines further with age, especially from childhood to adolescence. Dietary surveys typically rely on retrospective dietary assessment methods and use broad age groupings (4-10 yr; 11-18 yr), making it challenging to differentiate between middle-childhood and adolescence. Consequently, there is a need to assess dairy food consumption during middle-childhood and adolescence using more robust dietary assessment tools. Therefore, the present study aimed to describe and compare patterns of dairy consumption throughout middle-childhood and adolescence. Dairy food consumption was assessed during school term-time over 4 consecutive days, including 2 weekdays and 2 weekend days, in a sample of free-living children (9-11 yr, n=40) and adolescents (15-18 yr, n=35). For children, free-living dairy intake was evaluated through parental-weighed food records, and for adolescents, a combined weighed self-reported food record and 24-h dietary recall technique was utilized. Food records were explored to determine types, amounts, and frequency of dairy food consumption, and were analyzed for differences between middle-childhood and adolescence using a between group 2×2 (age×sex) ANOVA. Descriptive data suggested that milk was the most popular dairy product consumed by both children and adolescents. Statistical analysis revealed a main effect for sex on total milk consumption (mL) and number of daily milk portions consumed. No interaction or main effect was present for any other variable. The present study indicates that independent of age, boys consumed greater amounts of milk compared with girls. Contrary to existing literature, findings suggest no difference in milk-based dairy consumption between middle-childhood and adolescence.

Milk Consumption Following Exercise Reduces Subsequent Energy Intake in Female Recreational Exercisers

The aim of this study was to evaluate the effects of skimmed milk as a recovery drink following moderate–vigorous cycling exercise on subsequent appetite and energy intake in healthy, female recreational exercisers. Utilising a randomised cross-over design, nine female recreational exercisers (19.7 ± 1.3 years) completed a V˙O2peak test followed by two main exercise trials. The main trials were conducted following a standardised breakfast. Following 30 min of moderate-vigorous exercise (65% V˙O2peak), either 600 mL of skimmed milk or 600 mL of orange drink (475 mL orange juice from concentrate, 125 mL water), which were isoenergetic (0.88 MJ), were ingested, followed 60 min later with an ad libitum pasta meal. Absolute energy intake was reduced 25.2% ± 16.6% after consuming milk compared to the orange drink (2.39 ± 0.70 vs. 3.20 ± 0.84 MJ, respectively; p = 0.001). Relative energy intake (in relation to the energy content of the recovery drinks and energy expenditure) was significantly lower after milk consumption compared to the orange drink (1.49 ± 0.72 vs. 2.33 ± 0.90 MJ, respectively; p = 0.005). There were no differences in AUC (× 1 h) subjective appetite parameters (hunger, fullness and desire to eat) between trials. The consumption of skimmed milk following 30 min of moderate-vigorous cycling exercise reduces subsequent energy intake in female recreational exercisers.

Calcium Ingestion Suppresses Appetite and Produces Acute Overcompensation of Energy Intake Independent of Protein in Healthy Adults

BACKGROUND Prior evidence suggests that high-calcium intake influences postprandial appetite and insulinemia, possibly due to elevated incretins. In vitro and ex vivo models demonstrate that extracellular calcium and protein synergistically enhance secretion of incretins. This is yet to be shown in humans. OBJECTIVE This study was designed to assess energy intake compensation in response to protein and calcium ingestion. METHODS Twenty healthy adults (13 men; 7 women) completed 4 trials in a randomized, double-blind crossover design separated by ≥48 h. During the trials, each participant consumed a low-calcium and low-protein control preload [(CON); 4 g and 104 mg, respectively], a high-protein preload (PRO; 29 g), a high-calcium preload (CAL; 1170 mg), or a high-protein and high-calcium preload (PROCAL). Blood samples were collected at baseline and 15, 30, 45, and 60 min after preload ingestion to determine insulin and incretin hormone concentrations. Energy intake was assessed by a homogenous test meal 60 min after the preload. Visual analog scales were completed immediately before blood sampling to assess subjective appetite sensations. RESULTS Relative to the CON, the PRO produced 100% (95% CI: 85%, 115%) energy compensation, whereas the CAL produced significant overcompensation [118% (95% CI: 104%, 133%)], which was significantly more positive than with the PRO (P < 0.05). The PROCAL resulted in energy compensation of 109% (95% CI: 95%, 123%), which tended to be greater than with the PRO (P = 0.06). The mean difference in appetite sensations relative to the CON was not significantly different between the PRO (-3 mm; 95% CI: -8, 3 mm), CAL (-5 mm; 95% CI: -9, 0 mm), and PROCAL (-5 mm; 95% CI: -10, -1 mm) (P > 0.05). CONCLUSIONS The addition of protein to a preload results in almost perfect energy compensation, whereas the addition of calcium, with or without protein, suppresses appetite and produces overcompensation of subsequent energy intake. The role of circulating insulin and incretin concentrations in these responses, however, remains unclear. This trial was registered at clinicaltrials.gov as NCT01986036.

Co-Ingestion of Whey Protein with a Carbohydrate-Rich Breakfast Does Not Affect Glycemia, Insulinemia or Subjective Appetite Following a Subsequent Meal in Healthy Males

We aimed to assess postprandial metabolic and appetite responses to a mixed-macronutrient lunch following prior addition of whey protein to a carbohydrate-rich breakfast. Ten healthy males (age: 24 ± 1 years; body mass index (BMI): 24.5 ± 0.7 kg/m2) completed three trials in a non-isocaloric, crossover design. A carbohydrate-rich breakfast (93 g carbohydrate; 1799 kJ) was consumed with (CHO + WP) or without (CHO) 20 g whey protein isolate (373 kJ), or breakfast was omitted (NB). At 180 min, participants consumed a mixed-macronutrient lunch meal. Venous blood was sampled at 15 min intervals following each meal and every 30 min thereafter, while subjective appetite sensations were collected every 30 min throughout. Post-breakfast insulinemia was greater after CHO + WP (time-averaged area under the curve (AUC0–180 min): 193.1 ± 26.3 pmol/L), compared to CHO (154.7 ± 18.5 pmol/L) and NB (46.1 ± 8.0 pmol/L; p < 0.05), with no difference in post-breakfast (0–180 min) glycemia (CHO + WP, 3.8 ± 0.2 mmol/L; CHO, 4.2 ± 0.2 mmol/L; NB, 4.2 ± 0.1 mmol/L; p = 0.247). There were no post-lunch (0–180 min) effects of condition on glycemia (p = 0.492), insulinemia (p = 0.338) or subjective appetite (p > 0.05). Adding whey protein to a carbohydrate-rich breakfast enhanced the acute postprandial insulin response, without influencing metabolic or appetite responses following a subsequent mixed-macronutrient meal.

Agreement between two methods of dietary data collection in male adolescent academy-level soccer players

Collecting accurate and reliable nutritional data from adolescent populations is challenging, with current methods providing significant under-reporting. Therefore, the aim of the study was to determine the accuracy of a combined dietary data collection method (self-reported weighed food diary, supplemented with a 24-h recall) when compared to researcher observed energy intake in male adolescent soccer players. Twelve Academy players from an English Football League club participated in the study. Players attended a 12 h period in the laboratory (08:00 h–20:00 h), during which food and drink items were available and were consumed ad libitum. Food was also provided to consume at home between 20:00 h and 08:00 h the following morning under free-living conditions. To calculate the participant reported energy intake, food and drink items were weighed and recorded in a food diary by each participant, which was supplemented with information provided through a 24-h recall interview the following morning. Linear regression, limits of agreement (LOA) and typical error (coefficient of variation; CV) were used to quantify agreement between observer and participant reported 24-h energy intake. Difference between methods was assessed using a paired samples t-test. Participants systematically under-reported energy intake in comparison to that observed (p < 0.01) but the magnitude of this bias was small and consistent (mean bias = −88 kcal·day−1, 95% CI for bias = −146 to −29 kcal·day−1). For random error, the 95% LOA between methods ranged between −1.11 to 0.37 MJ·day−1 (−256 to 88 kcal·day−1). The standard error of the estimate was low, with a typical error between measurements of 3.1%. These data suggest that the combined dietary data collection method could be used interchangeably with the gold standard observed food intake technique in the population studied providing that appropriate adjustment is made for the systematic under-reporting common to such methods.

Consistency of metabolic responses and appetite sensations under postabsorptive and postprandial conditions

The present study aimed to investigate the reliability of metabolic and subjective appetite responses under fasted conditions and following consumption of a cereal-based breakfast. Twelve healthy, physically active males completed two postabsorption (PA) and two postprandial (PP) trials in a randomised order. In PP trials a cereal based breakfast providing 1859 kJ of energy was consumed. Expired gas samples were used to estimate energy expenditure and fat oxidation and 100mm visual analogue scales were used to determine appetite sensations at baseline and every 30 min for 120 min. Reliability was assessed using limits of agreement, coefficient of variation (CV), intraclass coefficient of correlation and 95% confidence limits of typical error. The limits of agreement and typical error were 292.0 and 105.5 kJ for total energy expenditure, 9.3 and 3.4 g for total fat oxidation and 22.9 and 8.3mm for time-averaged AUC for hunger sensations, respectively over the 120 min period in the PP trial. The reliability of energy expenditure and appetite in the 2h response to a cereal-based breakfast would suggest that an intervention requires a 211 kJ and 16.6mm difference in total postprandial energy expenditure and time-averaged hunger AUC to be meaningful, fat oxidation would require a 6.7 g difference which may not be sensitive to most meal manipulations.