Tracy L. Perry

Determination of the glycaemic index of foods: interlaboratory study.

Objective: Practical use of the glycaemic index (GI), as recommended by the FAO/WHO, requires an evaluation of the recommended method. Our purpose was to determine the magnitude and sources of variation of the GI values obtained by experienced investigators in different international centres.Design: GI values of four centrally provided foods (instant potato, rice, spaghetti and barley) and locally obtained white bread were determined in 8–12 subjects in each of seven centres using the method recommended by FAO/WHO. Data analysis was performed centrally.Setting: University departments of nutrition.Subjects: Healthy subjects (28 male, 40 female) were studied.Results: The GI values of the five foods did not vary significantly in different centres nor was there a significant centre×food interaction. Within-subject variation from two centres using venous blood was twice that from five centres using capillary blood. The s.d. of centre mean GI values was reduced from 10.6 (range 6.8–12.8) to 9.0 (range 4.8–12.6) by excluding venous blood data. GI values were not significantly related to differences in method of glucose measurement or subject characteristics (age, sex, BMI, ethnicity or absolute glycaemic response). GI values for locally obtained bread were no more variable than those for centrally provided foods.Conclusions: The GI values of foods are more precisely determined using capillary than venous blood sampling, with mean between-laboratory s.d. of approximately 9.0. Finding ways to reduce within-subject variation of glycaemic responses may be the most effective strategy to improve the precision of measurement of GI values.

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.

Lifestyle intervention in people with insulin-dependent diabetes mellitus (IDDM)

Objective: To investigate the impact of intensive lifestyle education on dietary practices, exercise and metabolic measurements in people with insulin-dependent diabetes mellitus (IDDM).Design: Sixty-one volunteer subjects with IDDM were randomised to intensive (Group 1) or standard (Group 2) education programmes for six months. During a second six month period of observation Group 1 subjects received routine surveillance for their condition and those in Group 2 were given intensive advice (phase 2). Current insulin regimens were modified to optimise glycaemic control before the start of the intervention phase. Nutrient intakes, weight, blood pressure, glycated haemoglobin (HbA), plasma lipids, lipoproteins and maximal oxygen consumption (VO max) were measured at the time of recruitment and at three monthly intervals during the trial and phase 2.Setting: Department of Human Nutrition at the University of Otago.Results: Glycated haemoglobin decreased significantly in both groups between recruitment and randomisation, the improvement being sustained during the six months of the randomised trial and for group 1 during the six months of post trial observation. A further decrease was seen in Group 2 during the second six month period when they were given intensive advice. Comparable changes were seen with total and low density lipoprotein (LDL) cholesterol in Group 1 during the trial, but significant decreases were only seen in Group 2 in association with intensive intervention (phase 2). These changes occurred in parallel with increases in intakes of carbohydrate and monounsaturated fatty acids, a reduction in intakes of total and saturated fat, and an improvement in maximum oxygen consumption.Conclusions: A lifestyle programme for people with IDDM results in modest changes in diet and exercise habits sufficient to improve measures of glycaemic control and lipoprotein mediated risk of coronary heart disease independent of changes in insulin regime. More innovative approaches to achieve lifestyle changes are required to meet current recommendations which in turn are likely to produce even greater beneficial changes than those observed here.Sponsorship: This study was supported by the Eli Lilly Research Grant (Eli Lilly and Company (New Zealand) Ltd), The Deans Research Grant (Otago Medical School, New Zealand) and The New Zealand Dietetic Association (Abbott Award).

The effect of increasing consumption of pulses and wholegrains in obese people: a randomized controlled trial.

Background: Wholegrain intake is inversely related to weight gain over time, but little information is available on the role of pulses in weight control. Objective: To compare weight loss, metabolic outcomes, and nutrient intakes in obese people assigned to a diet rich in pulses and wholegrains or a control diet. Methods: Randomized controlled study of 18 months with 113 volunteers (body mass index [BMI] ≥ 28 kg/m2). Diets were based on guidelines published by the National Heart Foundation of New Zealand. The intervention group was advised to consume 2 serves of pulses and 4 serves of wholegrain foods per day as substitutions for more refined carbohydrates. Results: Fiber intakes were higher, intakes of several vitamins and minerals were better maintained, and dietary glycemic index was lower in the intervention compared with the control group. Mean (standard error [SE]) weight loss at 6 months was 6.0 (0.7) kg and 6.3 (0.6) kg in the control and intervention groups, respectively, and was not different between groups (p > 0.05). Blood pressure, triglycerides, and glycemic load were lowered in both groups compared with baseline. Waist circumference was decreased at 18 months in the intervention compared with the control group (−2.8 cm; 95% confidence interval [CI]: −0.4, −5.1). Conclusions: Incorporation of pulses and wholegrain foods into a weight loss program resulted in a greater reduction in waist circumference compared with the group consuming a control diet, although no difference in weight loss was noted between groups. Retention of several nutrients was better with the pulse and wholegrain diet.

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.

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.

Glycaemic glucose equivalent: validation as a predictor of the relative glycaemic effect of foods.

Background: Glycaemic glucose equivalent (GGE) content of a quantity of a food, based on glycaemic index, food composition and food quantity, is the theoretical weight of glucose that would induce a glycaemic response equivalent to that induced by the given amount of food.Objectives: To test whether GGE content predicts glycaemic response to foods differing in glycaemic index, carbohydrate content and intake, over a practical range of carbohydrate intakes.Design: Controlled randomised study.Setting: Clinical trials unit at the Department of Human Nutrition, University of Otago, Dunedin, New Zealand.Subjects: In all, 12 volunteers with and 12 without type II diabetes were recruited. All but one subject completed the trial.Method: Yams, biscuits, white rice and porridge were consumed at 10 and 20 GGE doses, and 2-minute noodles at 24 and 48 GGE, following an overnight fast. Incremental areas under the blood glucose response curves (IAUC) over 3 h were calculated for each individual for all foods, and individual glycaemic responsiveness was determined as IAUC/GGE.Results: Within GGE dose, blood glucose responses to all foods, except rice, were similar. Doubling GGE dose approximately doubled glycaemic response. Relative glycaemic effects were accurately predicted by GGE intake after adjusting for individual glycaemic sensitivity (individual average IAUC/GGE). The accuracy of prediction of relative glycaemic effect from GGE intake was affected little by carbohydrate dose.Conclusion: GGE content predicted glycaemic impact of foods over a practical range of carbohydrate intakes, and may therefore be useful for accurate dietary management of glycaemia in diabetes mellitus. The predictive validity of GGE in mixed meals now needs to be tested.Sponsorship: Health Research Council of New Zealand contract 00/453.

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.

Glycaemic, insulinaemic, and immune responses to commercially available beverages consumed during recovery from rowing training

Abstract The consumption of carbohydrate and protein after exercise improves muscle glycogen synthesis and attenuates the decrease in immune function seen with endurance-type exercise. However, the impact of consuming commercially available beverages on glycaemic, insulinaemic, and immune responses during recovery from rowing training has not been investigated. Twenty-one male and female rowers completed four trials in a randomized order. Commercially available beverages were consumed in volumes providing 1.2 g carbohydrate · kg−1 body mass, upon completion of ~90 min of rowing at 60–70% maximum oxygen uptake, interspersed with up to five 5-min intervals at or above race pace. Blood samples were taken before and 15, 30, 45, 60, 90, and 120 min after consumption of the beverages for analysis of insulin and glucose and at 90 and 360 min for the analysis of cortisol and interleukin-6 (IL-6). The high-carbohydrate sports beverage and the meal replacement beverage produced a significantly larger (P<0.05) glucose incremental area under the curve than the sports-specific meal replacement beverage or the flavoured milk beverage. The high-carbohydrate sports beverage and the sports-specific meal replacement beverage produced a significantly lower (P<0.05) insulin incremental area under the curve than the meal replacement beverage or the flavoured milk beverage. The meal replacement beverage produced both a high glycaemic and insulinaemic response, suggesting that it may produce a higher rate of muscle glycogen resynthesis. There was a significant interaction between time and beverage for IL-6 (P=0.001), but not for cortisol (P=0.779). These results indicate that the impact of post-exercise nutrition on immune response may not be exclusively mediated by an attenuation of the cortisol response.

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.