INTRODUCTION:Postprandial hyperglycemia is a risk factor for type 2 diabetes. Insulin resistance (IR) might affect metabolic responses in non-fasting states. Dietary intake and food composition influence postprandial glucose homeostasis. The aims of this study were to evaluate the effects of different test foods varying in the macronutrient composition on postprandial glycemic responses and whether these outcomes are conditioned by the basal glycemic status in senior subjects. METHODS: In a randomized, controlled crossover design, thirty-four adults consumed a test food, a high protein product (n = 19) or ahigh carbohydrate (CHO) product (n = 15), using the oral glucose tolerance test (OGTT) as a reference. Blood glucose and insulin were measured at fasting and at 15, 30, 45, 60, 90, and 120 min after starting the food intake. For each type of food, the incremental area under the curve (iAUC) for glucose and insulin was calculated. IR was measured using the Homeostatic Model Assessment of IR (HOMA-IR). RESULTS: Consumption of a high protein product significantly lowered the peak and Δ blood glucose concentrations compared to the high CHO product (p < 0.001). Concerning the insulin response, no significant differences between both foods were observed. Fasting glucose was positively correlated with the glucose iAUC only for the high protein product. Positive associations of both fasting insulin and HOMA-IR with the insulin iAUC for all the cases were observed. Linear regression models showed significant positive associations between the glucose iAUC and fasting glucose after adjusting for age and sex. Regarding the insulin iAUC, positive associations were found with fasting insulin and HOMA-IR. Regression models also evidenced that both food test consumptions were able to decrease the glucose and insulin iAUC values when compared with the OGTT product. CONCLUSION: Our research found that not only is the nutritional composition of foods important, but also the baseline glycemic state of individuals when assessing glycemic index estimations and addressing precision nutritional strategies to prevent and treat IR-associated disturbances.
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INTRODUCTION: Postprandial hyperglycemia is a risk factor for type 2 diabetes. Insulin resistance (IR) might affect metabolic responses in non-fasting states. Dietary intake and food composition influence postprandial glucose homeostasis. The aims of this study were to evaluate the effects of different test foods varying in the macronutrient composition on postprandial glycemic responses and whether these outcomes are conditioned by the basal glycemic status in senior subjects. METHODS: In a randomized, controlled crossover design, thirty-four adults consumed a test food, a high protein product (n = 19) or a high carbohydrate (CHO) product (n = 15), using the oral glucose tolerance test (OGTT) as a reference. Blood glucose and insulin were measured at fasting and at 15, 30, 45, 60, 90, and 120 min after starting the food intake. For each type of food, the incremental area under the curve (iAUC) for glucose and insulin was calculated. IR was measured using the Homeostatic Model Assessment of IR (HOMA-IR). RESULTS: Consumption of a high protein product significantly lowered the peak and Δ blood glucose concentrations compared to the high CHO product (p < 0.001). Concerning the insulin response, no significant differences between both foods were observed. Fasting glucose was positively correlated with the glucose iAUC only for the high protein product. Positive associations of both fasting insulin and HOMA-IR with the insulin iAUC for all the cases were observed. Linear regression models showed significant positive associations between the glucose iAUC and fasting glucose after adjusting for age and sex. Regarding the insulin iAUC, positive associations were found with fasting insulin and HOMA-IR. Regression models also evidenced that both food test consumptions were able to decrease the glucose and insulin iAUC values when compared with the OGTT product. CONCLUSION: Our research found that not only is the nutritional composition of foods important, but also the baseline glycemic state of individuals when assessing glycemic index estimations and addressing precision nutritional strategies to prevent and treat IR-associated disturbances.
Authors: Fernando Vidal-Ostos; Omar Ramos-Lopez; Susan A Jebb; Angeliki Papadaki; Andreas F H Pfeiffer; Teodora Handjieva-Darlenska; Marie Kunešová; Ellen E Blaak; Arne Astrup; J Alfredo Martinez Journal: Nutr Metab (Lond) Date: 2022-10-19 Impact factor: 4.654