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Dietary Insulin Load and Cancer Recurrence and Survival in Patients With Stage III Colon Cancer: Findings From CALGB 89803 (Alliance).
Morales-Oyarvide, V, Yuan, C, Babic, A, Zhang, S, Niedzwiecki, D, Brand-Miller, JC, Sampson-Kent, L, Ye, X, Li, Y, Saltz, LB, et al
Journal of the National Cancer Institute. 2019;(2):170-179
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Abstract
BACKGROUND Evidence suggests that diets inducing postprandial hyperinsulinemia may be associated with increased cancer-related mortality. The goal of this study was to assess the influence of postdiagnosis dietary insulin load and dietary insulin index on outcomes of stage III colon cancer patients. METHODS We conducted a prospective observational study of 1023 patients with resected stage III colon cancer enrolled in an adjuvant chemotherapy trial who reported dietary intake halfway through and six months after chemotherapy. We evaluated the association of dietary insulin load and dietary insulin index with cancer recurrence and survival using Cox proportional hazards regression adjusted for potential confounders; statistical tests were two-sided. RESULTS High dietary insulin load had a statistically significant association with worse disease-free survival (DFS), comparing the highest vs lowest quintile (adjusted hazard ratio [HR] = 2.77, 95% confidence interval [CI] = 1.90 to 4.02, Ptrend < .001). High dietary insulin index was also associated with worse DFS (highest vs lowest quintile, HR = 1.75, 95% CI = 1.22 to 2.51, Ptrend= .01). The association between higher dietary insulin load and worse DFS differed by body mass index and was strongest among patients with obesity (HR = 3.66, 95% CI = 1.88 to 7.12, Pinteraction = .04). The influence of dietary insulin load on cancer outcomes did not differ by mutation status of KRAS, BRAF, PIK3CA, TP53, or microsatellite instability. CONCLUSIONS Patients with resected stage III colon cancer who consumed a high-insulinogenic diet were at increased risk of recurrence and mortality. These findings support the importance of dietary management following resection of colon cancer, and future research into underlying mechanisms of action is warranted.
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Effects of human milk and formula on postprandial glycaemia and insulinaemia.
Wright, CJ, Atkinson, FS, Ramalingam, N, Buyken, AE, Brand-Miller, JC
European journal of clinical nutrition. 2015;(8):939-43
Abstract
BACKGROUND/OBJECTIVES Consumption of formula in place of human milk may produce differences in postprandial glycaemia and insulinaemia that contribute to metabolic programming in the first year of life. The objective of the current study was to determine glycaemic and insulinaemic responses to human milk compared with a typical commercial formula, and then compare 11 other formulas. SUBJECTS/METHODS On separate mornings in random order, 10 healthy breastfeeding mothers consumed 25 g available carbohydrate portions of their own milk, a formula and reference food (25 g glucose on two occasions). In the second study, 10 different healthy subjects consumed 25 g available carbohydrate portions of 11 different commercial formulas and three reference foods (25 g glucose on three occasions). Fingerpick blood samples were taken at regular intervals over 2 h, and the glycaemic index (GI) and insulin index determined according to a standardised protocol. RESULTS There were no significant differences in postprandial glycaemia or insulinaemia after human milk vs a typical formula (P = 0.3). Both produced a low GI (mean ± s.e.m.: 38 ± 7 vs 34 ± 7, respectively) and high insulin index (87 ± 14 vs 94 ± 16). The GI and insulin indices of the other formulas ranged from 18 ± 3 to 67 ± 6 and 53 ± 9 to 209 ± 33, respectively. CONCLUSIONS Human milk and a typical formula elicit similar postprandial glycaemic and insulinaemic responses, but there is a wide range of responses to other formulas.
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Validation of the food insulin index in lean, young, healthy individuals, and type 2 diabetes in the context of mixed meals: an acute randomized crossover trial.
Bell, KJ, Bao, J, Petocz, P, Colagiuri, S, Brand-Miller, JC
The American journal of clinical nutrition. 2015;(4):801-6
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BACKGROUND The Food Insulin Index (FII) is a novel classification of single foods based on insulin responses in healthy subjects relative to an isoenergetic reference food. OBJECTIVE Our aim was to compare day-long responses to 2 nutrient-matched diets predicted to have either high or low insulin demand in healthy controls and individuals with type 2 diabetes (T2DM). DESIGN Twenty adults (10 healthy adults and 10 adults with T2DM) were recruited. On separate mornings, subjects consumed either a high- or low-FII diet in random order. Diets consisted of 3 consecutive meals (breakfast, morning tea, and lunch), matched for macronutrients, fiber, and glycemic index (GI), but with 2-fold difference in insulin demand as predicted by the FII of the component foods. Postprandial glycemia and insulinemia were measured in capillary plasma at regular intervals over 8 h. RESULTS As predicted by their GI, there were no differences in glycemic responses between the 2 diets in either group (mean ± SEM; healthy: 6.2 ± 0.2 compared with 6.1 ± 0.1 mmol/L · min, P = 0.429; T2DM: 9.9 ± 1.3 compared with 10.3 ± 1.6 mmol/L · min, P = 0.485). Compared with the high-FII diet, mean postprandial insulin response over 8 h was 53% lower with the low-FII diet in healthy subjects (mean ± SEM; incremental AUCinsulin 31,900 ± 4100 pmol/L · min compared with 68,100 ± 11,400 pmol/L · min, P = 0.003) and 41% lower in subjects with T2DM (mean ± SEM; incremental AUCinsulin 11,000 ± 1800 pmol/L · min compared with 18,700 ± 3100 pmol/L · min, P = 0.018). Incremental AUCinsulin was statistically significantly different between diets when groups were combined (P = 0.001). CONCLUSIONS The FII algorithm may be a useful tool for reducing postprandial hyperinsulinemia in T2DM, thereby potentially improving insulin resistance and β-cell function. This trial was registered at the Australian New Zealand Clinical Trials Registry as ACTRN12611000654954.
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Improving the estimation of mealtime insulin dose in adults with type 1 diabetes: the Normal Insulin Demand for Dose Adjustment (NIDDA) study.
Bao, J, Gilbertson, HR, Gray, R, Munns, D, Howard, G, Petocz, P, Colagiuri, S, Brand-Miller, JC
Diabetes care. 2011;(10):2146-51
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Abstract
OBJECTIVE Although carbohydrate counting is routine practice in type 1 diabetes, hyperglycemic episodes are common. A food insulin index (FII) has been developed and validated for predicting the normal insulin demand generated by mixed meals in healthy adults. We sought to compare a novel algorithm on the basis of the FII for estimating mealtime insulin dose with carbohydrate counting in adults with type 1 diabetes. RESEARCH DESIGN AND METHODS A total of 28 patients using insulin pump therapy consumed two different breakfast meals of equal energy, glycemic index, fiber, and calculated insulin demand (both FII = 60) but approximately twofold difference in carbohydrate content, in random order on three consecutive mornings. On one occasion, a carbohydrate-counting algorithm was applied to meal A (75 g carbohydrate) for determining bolus insulin dose. On the other two occasions, carbohydrate counting (about half the insulin dose as meal A) and the FII algorithm (same dose as meal A) were applied to meal B (41 g carbohydrate). A real-time continuous glucose monitor was used to assess 3-h postprandial glycemia. RESULTS Compared with carbohydrate counting, the FII algorithm significantly decreased glucose incremental area under the curve over 3 h (-52%, P = 0.013) and peak glucose excursion (-41%, P = 0.01) and improved the percentage of time within the normal blood glucose range (4-10 mmol/L) (31%, P = 0.001). There was no significant difference in the occurrence of hypoglycemia. CONCLUSIONS An insulin algorithm based on physiological insulin demand evoked by foods in healthy subjects may be a useful tool for estimating mealtime insulin dose in patients with type 1 diabetes.
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Prediction of postprandial glycemia and insulinemia in lean, young, healthy adults: glycemic load compared with carbohydrate content alone.
Bao, J, Atkinson, F, Petocz, P, Willett, WC, Brand-Miller, JC
The American journal of clinical nutrition. 2011;(5):984-96
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BACKGROUND Dietary glycemic load (GL; defined as the mathematical product of the glycemic index and carbohydrate content) is increasingly used in nutritional epidemiology. Its ability to predict postprandial glycemia and insulinemia for a wide range of foods or mixed meals is unclear. OBJECTIVE Our objective was to assess the degree of association between calculated GL and observed glucose and insulin responses in healthy subjects consuming isoenergetic portions of single foods and mixed meals. DESIGN In study 1, groups of healthy subjects consumed 1000-kJ portions of 121 single foods in 10 food categories. In study 2, healthy subjects consumed 2000-kJ servings of 13 mixed meals. Foods and meals varied widely in macronutrient content, fiber, and GL. Glycemia and insulinemia were quantified as area under the curve relative to a reference food (= 100). RESULTS Among the single foods, GL was a more powerful predictor of postprandial glycemia and insulinemia than was the available carbohydrate content, explaining 85% and 59% of the observed variation, respectively (P < 0.001). Similarly, for mixed meals, GL was also the strongest predictor of postprandial glucose and insulin responses, explaining 58% (P = 0.003) and 46% (P = 0.01) of the variation, respectively. Carbohydrate content alone predicted the glucose and insulin responses to single foods (P < 0.001) but not to mixed meals. CONCLUSION These findings provide the first large-scale, systematic evidence of the physiologic validity and superiority of dietary GL over carbohydrate content alone to estimate postprandial glycemia and insulin demand in healthy individuals. This trial was registered at ANZCTR.org as ACTRN12610000484044.
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Food insulin index: physiologic basis for predicting insulin demand evoked by composite meals.
Bao, J, de Jong, V, Atkinson, F, Petocz, P, Brand-Miller, JC
The American journal of clinical nutrition. 2009;(4):986-92
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BACKGROUND Diets that provoke less insulin secretion may be helpful in the prevention and management of diabetes. A physiologic basis for ranking foods according to insulin "demand" could therefore assist further research. OBJECTIVE We assessed the utility of a food insulin index (FII) that was based on testing isoenergetic portions of single foods (1000 kJ) in predicting the insulin demand evoked by composite meals. DESIGN Healthy subjects (n = 10 or 11 for each meal) consumed 13 different isoenergetic (2000 kJ) mixed meals of varying macronutrient content. Insulin demand predicted by the FII of the component foods or by carbohydrate counting and glycemic load was compared with observed insulin responses. RESULTS Observed insulin responses (area under the curve relative to white bread: 100) varied over a 3-fold range (from 35 +/- 5 to 116 +/- 26) and were strongly correlated with insulin demand predicted by the FII of the component foods (r = 0.78, P = 0.0016). The calculated glycemic load (r = 0.68, P = 0.01) but not the carbohydrate content of the meals (r = 0.53, P = 0.064) also predicted insulin demand. CONCLUSIONS The relative insulin demand evoked by mixed meals is best predicted by a physiologic index based on actual insulin responses to isoenergetic portions of single foods. In the context of composite meals of similar energy value, but varying macronutrient content, carbohydrate counting was of limited value.
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Can a low-glycemic index diet reduce the need for insulin in gestational diabetes mellitus? A randomized trial.
Moses, RG, Barker, M, Winter, M, Petocz, P, Brand-Miller, JC
Diabetes care. 2009;(6):996-1000
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OBJECTIVE A low-glycemic index diet is effective as a treatment for individuals with diabetes and has been shown to improve pregnancy outcomes when used from the first trimester. A low-glycemic index diet is commonly advised as treatment for women with gestational diabetes mellitus (GDM). However, the efficacy of this advice and associated pregnancy outcomes have not been systematically examined. The purpose of this study was to determine whether prescribing a low-glycemic index diet for women with GDM could reduce the number of women requiring insulin without compromise of pregnancy outcomes. RESEARCH DESIGN AND METHODS All women with GDM seen over a 12-month period were considered for inclusion in the study. Women (n = 63) were randomly assigned to receive either a low-glycemic index diet or a conventional high-fiber (and higher glycemic index) diet. RESULTS Of the 31 women randomly assigned to a low-glycemic index diet, 9 (29%) required insulin. Of the women randomly assigned to a higher-glycemic index diet, a significantly higher proportion, 19 of 32 (59%), met the criteria to commence insulin treatment (P = 0.023). However, 9 of these 19 women were able to avoid insulin use by changing to a low-glycemic index diet. Key obstetric and fetal outcomes were not significantly different. CONCLUSIONS Using a low-glycemic index diet for women with GDM effectively halved the number needing to use insulin, with no compromise of obstetric or fetal outcomes.
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Effect of the glycemic index of carbohydrates on day-long (10 h) profiles of plasma glucose, insulin, cholecystokinin and ghrelin.
Reynolds, RC, Stockmann, KS, Atkinson, FS, Denyer, GS, Brand-Miller, JC
European journal of clinical nutrition. 2009;(7):872-8
Abstract
BACKGROUND Low glycemic index (GI) carbohydrates have been linked to increased satiety. The drive to eat may be mediated by postprandial changes in glucose, insulin and gut peptides. OBJECTIVE To investigate the effect of a low and a high GI diet on day-long (10 h) blood concentrations of glucose, insulin, cholecystokinin (CCK) and ghrelin (GHR). DESIGN Subjects (n=12) consumed a high and a low GI diet in a randomized, crossover design, consisting of four meals that were matched for macronutrients and fibre, and differed only in carbohydrate quality (GI). Blood was sampled every 30-60 min and assayed for glucose, insulin, CCK and GHR. RESULTS The high GI diet resulted in significantly higher glucose and insulin mean incremental areas under the curve (IAUC, P=0.027 and P=0.001 respectively). CCK concentration was 59% higher during the first 7 h of the low GI diet (394+/-95 pmol/l min) vs the high GI diet (163+/-38 pmol/l min, P=0.046), but there was no difference over 10 h (P=0.224). GHR concentration was inversely correlated with insulin concentration (Pearson correlation -0.48, P=0.007), but did not differ significantly between the low and high GI diets. CONCLUSIONS Mixed meals of lower GI are associated with lower day-long concentrations of glucose and insulin, and higher CCK after breakfast, morning tea and lunch. This metabolic profile could mediate differences in satiety and hunger seen in some, but not all, studies.