Gelatinisation and milling whole-wheat increases postprandial blood glucose: randomised crossover study of adults with type 2 diabetes.

AIMS/HYPOTHESES: We examined the effects of milling and cooking whole grains in water to achieve starch gelatinisation on postprandial blood glucose using a randomised crossover open-label design. Participants were adults with type 2 diabetes whose body weight or medications had not changed in at least 3 months. METHODS: Postprandial blood glucose (measured as incremental AUC [iAUC]) was measured following consumption of four nutrient-matched whole-wheat porridge test-meals. Test-meals included gelatinised or native starch and were made with either finely milled or intact whole-wheat. RESULTS: Eighteen adults (63.1 ± 9.8 years, HbA1c 57.0 ± 11.5 mmol/mol [7.4 ± 3.2%]) completed the study. iAUC was higher following cooked meals (gelatinised starch) than following uncooked meals (native starch) (mean difference [MD] 268, 95% CI 188, 348 mmol/l × min). Consuming finely milled whole-wheat produced a higher iAUC compared with intact whole-wheat (MD 173, 95% CI 80, 266 mmol/l × min). There was no evidence of an interaction effect (p = 0.841). CONCLUSIONS: Both the nature of starch and the grain structure of whole-wheat influence the glycaemic response of adults with type 2 diabetes mellitus. FUNDING: Baking Industry Research Trust of New Zealand and the Riddet Centre of Research Excellence. TRIAL REGISTRATION: www.anzctr.org.au ACTRN12617000328370.

Factors Influencing Energy Drink Consumption in Participants and Viewers of Extreme Sports.

OBJECTIVE: To quantify energy drink consumption and influences affecting consumption in those who participate in or watch extreme sports. METHODS: An online survey, informed by focus groups, was administered via Quadrics®. Advertisement was via social media, emailing extreme sport clubs, flyers at extreme sport locations, and word of mouth. Participation was limited to those >18 y who watched and/or participated in extreme sports. The study was conducted in New Zealand, with international online availability. Variables measured comprised age, sex, energy drink consumption, reasons for their use, extreme sport viewing, advertising, and sponsorship. Logistic regression models were utilised. RESULTS: Amongst participants who completed the questionnaire (n = 247), the mean (SD) age was 26.2 (8.2) y, 40.5% were female, 57.9% consumed energy drinks, and 25.5% consumed >one per week. For every year older, odds of consuming energy drinks were 3.1% lower (p=0.04). A 31% increase in energy drink consumption for every single increase of viewing extreme sport per week was observed (p=0.009); however, reported viewing of advertising was not associated with increased consumption. CONCLUSIONS: A large proportion of extreme sport enthusiasts regularly consume energy drinks, especially younger adults. Extreme sport viewing, where energy drink sponsorship is common, appears to increase their consumption, even if not considered advertising by the viewers themselves.

Energy utilisation and postprandial responses during sitting interrupted by regular activity breaks.

Interrupting sedentary behaviour with regular activity breaks benefits glycaemic control; however, the influence of the energy utilised during these activity breaks on postprandial metabolic response is relatively unknown. Therefore, the aim of this study was to investigate whether the energy utilisation of regular (every 30 min) short (1 min 40 s or 2 min) activity breaks was associated with the lowering of postprandial glycaemia, insulinemia and lipidemia.Using separate data from two previously performed studies (ALPhA Study n = 65, age 25.7 (5.2) y, 40% male, BMI 23.6 (4.1) kg · m-2. ABPA study n = 35, age 25.1 (3.7) y, 31% male, BMI 23.4 (3.2) kg · m-2) we investigated the association between energy utilisation (measured by indirect calorimetry) and postprandial glucose, insulin and triglycerides during prolonged sitting, and regular activity breaks.Results.Mixed effects regression models indicated that energy utilisation was not consistently associated with postprandial glucose, insulin or triglyceride responses (p > 0.05 for all). Additionally, there was some indication that energy utilisation was obscuring (mildly suppressing) the effects of regular activity breaks on glucose, insulin and triglyceride iAUC.Conclusions.If energy utilisation does not mediate the association between regular activity breaks and postprandial glycaemic response, it is possible that it is the frequency of the activity breaks that is beneficial.

Device-Measured Sedentary Behavior Patterns in Office-Based University Employees.

OBJECTIVE: The aim of this study was to describe device-measured patterns of sedentary behavior in self-identified sedentary university employees. METHODS: Participants (n = 78) wore the ActiGraph GT3X+ and the activPAL3 for 7 days. Data from the ActiGraph were used to identify time in sedentary behavior, light-intensity, and moderate-to-vigorous physical activity. Data from the activPAL identified time sitting/lying, standing, and stepping. Breaks in sedentary time and prolonged sedentary bouts were described. RESULTS: During workdays, participants spent 65% to 79% of time sedentary, 16% in light-intensity physical activity, and 4% in moderate-to-vigorous physical activity, 76% of time was spent sitting/lying, 16% standing, and 8% stepping. Between 10 and 12 breaks in sedentary time were accumulated. CONCLUSION: Office-based university employees spend a high proportion of their time sedentary, but accumulate a high number of breaks. Whether these breaks are appropriate in timing, duration, and intensity to elicit health benefits seen in laboratory studies requires further investigation.

Interrupting Prolonged Sitting with Regular Activity Breaks does not Acutely Influence Appetite: A Randomised Controlled Trial.

Regular activity breaks increase energy expenditure; however, this may promote compensatory eating behaviour. The present study compared the effects of regular activity breaks and prolonged sitting on appetite. In a randomised, cross-over trial, 36 healthy adults (BMI (Body Mass Index) 23.9 kg/m² (S.D. = 3.9)) completed four, two-day interventions: two with prolonged sitting (SIT), and two with sitting and 2 min of walking every 30 min (RAB). Standardized meals were provided throughout the intervention, with an ad libitum meal at the end of Day 2. Appetite and satiety were assessed throughout both days of each intervention using five visual analogue scales. The five responses were combined into a single appetite response at each time point. The area under the appetite response curve (AUC) was calculated for each day. Intervention effects for appetite response AUC and ad libitum meal intake were tested using linear mixed models. Appetite AUC did not differ between interventions (standardised effect of RAB compared to SIT: Day 1: 0.11; 95% CI: -0.28, 0.06; p = 0.212; Day 2: 0.04; 95% CI: -0.15, 0.24; p = 0.648). There was no significant difference in energy consumed at the ad libitum lunch meal on Day 2 between RAB and SIT. Interrupting prolonged sitting with regular activity breaks does not acutely influence appetite or volume of food consumed, despite inferred increases in energy expenditure. Longer-term investigation into the effects of regular activity breaks on energy balance is warranted.

Vitamin D3 Supplementation Does Not Improve Sprint Performance in Professional Rugby Players: A Randomized, Placebo-Controlled, Double-Blind Intervention Study.

Vitamin D insufficiency is common in athletes and may lower physical performance. Many cross-sectional studies associate vitamin D status with physical performance in athletes; however, there have been few prospective randomized controlled trials with adequate statistical power to test this relationship, and none in the southern hemisphere. Thus, a prospective double-blind, randomized, placebo-controlled intervention trial was conducted involving 57 professional rugby union players in New Zealand. Participants were randomized to receive 50,000 IU of cholecalciferol (equivalent to 3,570 IU/day) or placebo once every two weeks over 11-12 weeks. Serum 25(OH)D concentrations and physical performance were measured at baseline, weeks 5-6, and weeks 11-12. Mean (SD) serum 25(OH)D concentrations for all participants at baseline was 94 (18) nmol/L, with all players above 50 nmol/L. Vitamin D supplementation significantly increased serum 25(OH)D concentrations compared to placebo, with a 32 nmol/L difference between groups at 11-12 weeks (95% CI, 26-38; p < 0.001). Performance in five of the six tests at study completion, including the primary outcome variable of 30-m sprint time, did not differ between the vitamin D supplemented and placebo groups (p > 0.05). Performance on the weighted reverse-grip chin up was significantly higher in players receiving vitamin D compared with placebo, by 5.5 kg (95% CI, 2.0-8.9; p = 0.002). Despite significantly improving vitamin D status in these professional rugby union players, vitamin D supplementation had little impact on physical performance outcomes. Thus, it is unlikely that vitamin D supplementation is an ergogenic aid in this group of athletes.

Sedentary Behavior and Body Weight and Composition in Adults: A Systematic Review and Meta-analysis of Prospective Studies.

BACKGROUND: The cumulative effect of too much sedentary behavior may contribute to weight gain and obesity. OBJECTIVE: The aim of this study was to conduct a systematic review and meta-analysis of prospective cohorts and randomized controlled studies to determine the association between sedentary behavior and body weight and obesity in adults. DATA SOURCES AND STUDY SELECTION: Relevant studies were identified from searches of the MEDLINE, Embase, AMED and PubMed databases up to May 2017, and by manual searches of in-text citations. Studies that evaluated the association in adults between sedentary behavior and body weight or obesity, while controlling for physical activity, were included. Overall, 31 publications met the eligibility criteria, including 23 prospective cohort studies with data that could be extracted for a quantitative meta-analysis, and a single randomized controlled trial. RESULTS: There were no significant associations between sedentary behavior and any measure of body weight or obesity, with the exception of waist circumference. For the latter outcome, over a 5-year follow-up period, each 1 h per day increase-from baseline to follow-up-in sedentary behavior was associated with a 0.02 mm [95% confidence interval (CI) 0.01-0.04; p = 0.001) increase in waist circumference. The odds ratio of becoming overweight or obese was 1.33 (95% CI 1.11-1.60; p = 0.001) in the highest compared with lowest categories of sedentary behavior. CONCLUSIONS: Meta-analysis of data from prospective cohort studies showed small, inconsistent and non-significant associations between sedentary behavior and body weight.

Regular activity breaks combined with physical activity improve postprandial plasma triglyceride, nonesterified fatty acid, and insulin responses in healthy, normal weight adults: A randomized crossover trial.

BACKGROUND: Compared with prolonged sitting, regular activity breaks immediately lower postprandial glucose and insulin, but not triglyceride responses. Postprandial triglycerides can be lowered by physical activity but the effect is often delayed by ∼12 to 24 hours. OBJECTIVE: The objective of the study was to determine whether regular activity breaks affect postprandial triglyceride response in a delayed manner similar to physical activity. METHODS: In a randomized crossover trial, 36 adults (body mass index 23.9 kg/m2 [standard deviation 3.9]) completed four 2-day interventions: (1) prolonged sitting (SIT); (2) prolonged sitting with 30 minutes of continuous walking (60% VO2max), at the end of Day 1 (SIT + PAD1); (3) Sitting with 2 minutes of walking (60% VO2max) every 30 minutes (RAB); (4) A combination of the continuous walking and regular activity breaks in 2 and 3 above (RAB + PAD1). Postprandial plasma triglyceride, nonesterified fatty acids, glucose, and insulin responses were measured in venous blood over 5 hours on Day 2. RESULTS: Compared with SIT, both RAB (difference: -43.61 mg/dL·5 hours; 95% confidence interval [CI] -83.66 to -2.67; P = .035) and RAB + PAD1 (-65.86 mg/dL·5 hours; 95% CI -112.14 to -19.58; P = .005) attenuated triglyceride total area under the curve (tAUC). RAB + PAD1 produced the greatest reductions in insulin tAUC (-23%; 95% CI -12% to -31%; P < .001), whereas RAB resulted in the largest increase in nonesterified fatty acids (tAUC, 10.08 mg/dL·5 hours; 95% CI 5.60-14.84; P < .001). There was no effect on glucose tAUC (P = .290). CONCLUSIONS: Postprandial triglyceride response is attenuated by regular activity breaks, when measured ∼24 hours after breaks begin. Combining regular activity breaks with 30 minutes of continuous walking further improves insulinemic and lipidemic responses.

Diet app use by sports dietitians: a survey in five countries.

BACKGROUND: Despite the hundreds of diet apps available for use on smartphones (mobile phones), no studies have examined their use as tools for dietary assessment and tracking in sports nutrition. OBJECTIVE: The aim is to examine the prevalence and perceptions of using smartphone diet apps for dietary assessment and tracking among sports dietitians. METHODS: A cross-sectional online survey to examine the use and perception of diet apps was developed and distributed to sports dietitians in Australia, Canada, New Zealand, the United Kingdom, and the United States (US). RESULTS: The overall response rate from the 1709 sports dietitians invited to participate was 10.3% (n=180). diet apps were used by 32.4% (57/176) of sports dietitians to assess and track the dietary intake of athletes. Sports dietitians from the US were more likely to use smartphone diet apps than sports dietitians from other countries (OR=5.61, 95% CI 1.84-17.08, P=.002). Sports dietitians used 28 different diet apps, with 56% (32/57) choosing MyFitnessPal. Overall, sports dietitians held a positive perception of smartphone diet apps, with the majority of respondents viewing diet apps as "better" (25/53, 47%) or "equivalent" (22/53, 41%) when compared with traditional dietary assessment methods. CONCLUSIONS: Nearly one-third of sports dietitians used mobile phone diet apps in sports nutrition practice, and viewed them as useful in helping to assess and track the dietary intake of athletes.

Breaking prolonged sitting reduces postprandial glycemia in healthy, normal-weight adults: a randomized crossover trial.

BACKGROUND: Sedentary behavior is a risk factor for cardiometabolic disease. Regularly interrupting sedentary behavior with activity breaks may lower this risk. OBJECTIVE: We compared the effects of prolonged sitting, continuous physical activity combined with prolonged sitting, and regular activity breaks on postprandial metabolism. DESIGN: Seventy adults participated in a randomized crossover study. The prolonged sitting intervention involved sitting for 9 h, the physical activity intervention involved walking for 30 min and then sitting, and the regular-activity-break intervention involved walking for 1 min 40 s every 30 min. Participants consumed a meal-replacement beverage at 60, 240, and 420 min. RESULTS: The plasma incremental area under the curve (iAUC) for insulin differed between interventions (overall P < 0.001). Regular activity breaks lowered values by 866.7 IU · L(-1) · 9 h(-1) (95% CI: 506.0, 1227.5 IU · L(-1) · 9 h(-1); P < 0.001) when compared with prolonged sitting and by 542.0 IU · L(-1) · 9 h(-1) (95% CI: 179.9, 904.2 IU · L(-1) · 9 h(-1); P = 0.003) when compared with physical activity. Plasma glucose iAUC also differed between interventions (overall P < 0.001). Regular activity breaks lowered values by 18.9 mmol · L(-1) · 9 h(-1) (95% CI: 10.0, 28.0 mmol · L(-1) · 9 h(-1); P < 0.001) when compared with prolonged sitting and by 17.4 mmol · L(-1) · 9 h(-1) (95% CI: 8.4, 26.3 mmol · L(-1) · 9 h(-1); P < 0.001) when compared with physical activity. Plasma triglyceride iAUC differed between interventions (overall P = 0.023). Physical activity lowered values by 6.3 mmol · L(-1) · 9 h(-1) (95% CI: 1.8, 10.7 mmol · L(-1) · 9 h(-1); P = 0.006) when compared with regular activity breaks. CONCLUSION: Regular activity breaks were more effective than continuous physical activity at decreasing postprandial glycemia and insulinemia in healthy, normal-weight adults. This trial was registered with the Australian New Zealand Clinical Trials registry as ACTRN12610000953033.

Insulin and fiber type in the offspring of T2DM subjects with resistance training and detraining.

PURPOSE: Effects of resistance training and detraining on glucose and insulin responses to an oral glucose load, muscle fiber type, and muscular performance in the offspring of those with type 2 diabetes (familial insulin resistant (FIR)) were investigated. METHODS: Six FIR participants and 10 controls (C) completed 9 wk of resistance training and 9 wk of detraining. Measures of strength and power, an oral glucose tolerance test, and a muscle biopsy to determine myosin heavy chain (MHC) fiber composition were taken at baseline (T1), after training (T2), and after detraining (T3). RESULTS: Three-repetition maximum increased (P ≤ 0.001) similarly in both groups in all strength measures, e.g., leg press (FIR T1, T2: 121 ± 34 kg, 186 ± 50 kg; C T1, T2: 137 ± 42 kg, 206 ± 64 kg, respectively (means ± SD)). Wingate peak power increased (FIR T1, T2: 505 ± 137 W, 523 ± 143 W; C T1, T2: 636 ± 211 W, 672 ± 223 W, respectively; P ≤ 0.005 (means ± SD)). Training reduced insulin area under the curve more (P = 0.050) in FIR (T1, T2: 1219 ± 734 pmol·L, 837 ± 284 pmol·L, respectively (means ± SD)) than that in C (T1, T2: 647 ± 268 pmol·L, 635 ± 258 pmol·L, respectively (means ± SD)). MHC distribution did not change with training. Strength (three-repetition maximum measures) decreased with detraining (P ≤ 0.001) although Wingate power did not. Detraining increased insulin area under the curve (P = 0.018) in FIR (T2, T3: 837 ± 285 pmol·L, 1040 ± 194 pmol·L, respectively (means ± SD)) but not in C (T2, T3: 635 ± 258 pmol·L, 625 ± 213 pmol·L, respectively (means ± SD)). MHC IIX fibers increased with detraining (P = 0.026). CONCLUSION: FIR appears to have exaggerated responses to resistance training and detraining, with a greater reduction in insulin release with glucose ingestion after training and increase when training ceases. Resistance training has a significant effect on insulin responses and may reduce future risk of type 2 diabetes mellitus among FIR.

Physical activity and postprandial lipidemia: are energy expenditure and lipoprotein lipase activity the real modulators of the positive effect?

Historically, the link between elevated cholesterol and increased risk of cardiovascular disease has been based on fasting measurements. This is appropriate for total, low-density lipoprotein and high-density lipoprotein cholesterol. However, triglyceride concentrations vary considerably throughout the day in response to the regular consumption of food and drink. Recent findings indicate that postprandial triglyceride concentrations independently predict future cardiovascular risk. Potential modulators of postprandial lipidemia include meal composition and physical activity. Early cross sectional studies indicated that physically active individuals had a lower postprandial lipidemic response compared to inactive individuals. However, the effect of physical activity on postprandial lipidemia is an acute phenomenon, which dissipates within 60 h of a single bout of exercise. Total exercise induced energy expenditure, rather than duration or intensity of the physical activity is commonly reported to be a potent modulator of postprandial lipidemia. However, the pooled results of studies in this area suggest that energy expenditure exerts most of its influence on fasting triglyceride concentrations rather than on the incremental change in triglyceride concentrations seen following meal consumption. It seems more likely that energy expenditure is one component of a multifactorial list of mediators that may include local muscle contractile activity, and other yet to be elucidated mechanisms.

Glycemic index and endurance performance.

The aim of this review is to provide an up-to-date summary of the evidence surrounding glycemic index (GI) and endurance performance. Athletes are commonly instructed to consume low-GI (LGI) carbohydrate (CHO) before exercise, but this recommendation appears to be based on the results of only a few studies, whereas others have found that the GI of CHO ingested before exercise has no impact on performance. Only 1 study was designed to directly investigate the impact of the GI of CHO ingested during exercise on endurance performance. Although the results indicate that GI is not as important as consuming CHO itself, more research in this area is clearly needed. Initial research investigating the impact of GI on postexercise recovery indicated consuming high-GI (HGI) CHO increased muscle glycogen resynthesis. However, recent studies indicate an interaction between LGI CHO and fat oxidation, which may play a role in enhancing performance in subsequent exercise. Despite the fact that the relationship between GI and sporting performance has been a topic of research for more than 15 yr, there is no consensus on whether consuming CHO of differing GI improves endurance performance. Until further well-designed research is carried out, athletes are encouraged to follow standard recommendations for CHO consumption and let practical issues and individual experience dictate the use of HGI or LGI meals and supplements before, during, and after exercise.

Glycemic and insulinemic response to selected snack bars in trained versus sedentary individuals.

The purpose of this study was to determine whether glycemic index (GI) is influenced by training state. Participants were tested in a randomized order: twice with a reference solution containing 50 g glucose and once each with 2 commercially available snack bars (Griffin's Fruitli bar and Peak Fuel's Summit bar) containing 50 g available carbohydrate. Eleven of the participants (6 men and 5 women, M + or - SD age 20.8 + or - 2.0 yr) were endurance trained (ET; VO(2max) 57.5 + or - 8.4 ml x kg(-1) x min(-1) ), and 9 participants (2 men and 7 women, M + or - SD age 22.4 + or - 1.8 yr) were sedentary (SE; VO(2max) 43.7 + or - 9.1 ml x kg(-1) x min(-1) ). After an overnight fast, participants consumed either the glucose solution or snack bar, with blood samples taken before eating and at 15, 30, 45, 60, 90, and 120 min after eating began. The mean incremental area under the curve (IAUC) of the glucose reference was 31% lower (95% CI 3-52%, p = .03), and the Fruitli bar 38% lower (95% CI 0-61%, p = .05) in ET than in SE participants. There was a trend for the IAUC for the Summit bar to be 35% lower in ET than in SE participants (95% CI -7% to 61% p = .09). There was no significant interaction between training state and test food. The GIs of the Fruitli and Summit bars was not significantly different between ET and SE participants (p = .65 and .54, respectively). ET participants had a lower glycemic response than SE participants; however, training state did not influence GI.