Meynier Alexandra, Goux Aurélie, Atkinson Fiona, Brack Olivier, Vinoy Sophie
Nutrition Department, Mondelez International R&D,6 Rue René Razel - Bâtiment K,91400Saclay,France.
Human Nutrition Unit, School of Molecular Bioscience, University of Sydney,Sydney,NSW2006,Australia.
Br J Nutr. 2015 Jun 28;113(12):1931-9. doi: 10.1017/S0007114515001270. Epub 2015 May 22.
Cereal products exhibit a wide range of glycaemic indexes (GI), but the interaction of their different nutrients and starch digestibility on blood glucose response is not well known. The objective of this analysis was to evaluate how cereal product characteristics can contribute to GI and insulinaemic index and to the parameters describing glycaemic or insulinaemic responses (incremental AUC, maximum concentration and Δpeak). Moreover, interactions between the different cereal products characteristics and glycaemic response parameters were assessed for the first time. Relationships between the cereal products characteristics and the glycaemic response were analysed by partial least square regressions, followed by modelling. A database including 190 cereal products tested by the usual GI methodology was used. The model on glycaemic responses showed that slowly digestible starch (SDS), rapidly digestible starch (RDS) and fat and fibres, and several interactions involving them, significantly explain GI by 53 % and Δpeak of glycaemia by 60 %. Fat and fibres had important contributions to glycaemic response at low and medium SDS contents in cereal products, but this effect disappears at high SDS levels. We showed also for the first time that glycaemic response parameters are dependent on interactions between starch digestibility (interaction between SDS and RDS) and nutritional composition (interaction between fat and fibres) of the cereal products. We also demonstrated the non-linear effect of fat and fibres (significant effect of their quadratic terms). Hence, optimising both the formula and the manufacturing process of cereal products can improve glucose metabolism, which is recognised as strongly influential on human health.
谷物产品具有广泛的血糖生成指数（GI），但其不同营养素与淀粉消化率对血糖反应的相互作用尚不为人所知。本分析的目的是评估谷物产品特性如何影响血糖生成指数和胰岛素生成指数，以及描述血糖或胰岛素反应的参数（增量曲线下面积、最大浓度和Δ峰值）。此外，首次评估了不同谷物产品特性与血糖反应参数之间的相互作用。通过偏最小二乘回归分析谷物产品特性与血糖反应之间的关系，随后进行建模。使用了一个包含190种通过常规血糖生成指数方法测试的谷物产品的数据库。血糖反应模型表明，慢消化淀粉（SDS）、快消化淀粉（RDS）、脂肪和纤维，以及涉及它们的几种相互作用，可显著解释53%的血糖生成指数和60%的血糖Δ峰值。在谷物产品中SDS含量较低和中等时，脂肪和纤维对血糖反应有重要影响，但在SDS水平较高时这种影响消失。我们还首次表明，血糖反应参数取决于谷物产品淀粉消化率（SDS和RDS之间的相互作用）与营养成分（脂肪和纤维之间的相互作用）之间。我们还证明了脂肪和纤维的非线性效应（其二次项的显著效应）。因此，优化谷物产品的配方和制造工艺可改善葡萄糖代谢，这被认为对人类健康有重大影响。
