Rice is an important staple food for more than half of the world's population. Especially in Asian countries, rice is a major contributor to dietary glycaemic load (GL). Sustained consumption of higher-GL diets has been implicated in the development of chronic diseases such as type 2 diabetes mellitus. Given that a reduction in postprandial glycaemic and insulinaemic responses is generally seen as a beneficial dietary change, it is useful to determine the variation in the range of postprandial glucose (PPG) and insulin (PPI) responses to rice and the primary intrinsic and processing factors known to affect such responses. Therefore, we identified relevant original research articles on glycaemic response to rice through a systematic search of the literature in Scopus, Medline and SciFinder databases up to July 2014. Based on a glucose reference value of 100, the observed glycaemic index values for rice varieties ranged from 48 to 93, while the insulinaemic index ranged from 39 to 95. There are three main factors that appear to explain most of the variation in glycaemic and insulinaemic responses to rice: (1) inherent starch characteristics (amylose:amylopectin ratio and rice cultivar); (2) post-harvest processing (particularly parboiling); (3) consumer processing (cooking, storage and reheating). The milling process shows a clear effect when compared at identical cooking times, with brown rice always producing a lower PPG and PPI response than white rice. However, at longer cooking times normally used for the preparation of brown rice, smaller and inconsistent differences are observed between brown and white rice.
We report the fabrication of pH responsive switchable emulsions that quickly destabilize at acidic pH, but switch back to a stable state when pH is neutralized. The pH triggered fl occulation is further used to infl uence the assembly of droplets into predetermined shapes. Such systems, stabilised using natural non-toxic components, can fi nd important applications in the fi eld of green colloidal structuring.
PurposeType 2 diabetes (T2DM) is increasing, particularly in South-East Asia. Intake of high-glycaemic foods has been positively associated with T2DM, and feasible routes to reduce the glycaemic response to carbohydrate-rich staple foods are needed. The research question was whether different fibre and legume flour mixes in flatbreads lower postprandial glucose (PPG) responses.MethodsUsing a balanced incomplete block design, we tested the inclusion of guar gum (GG), konjac mannan (KM) and chickpea flour (CPF) in 10 combinations (2/4/6 g GG; 2/4 g KM; 15 g CPF, and 10 or 15 g CPF plus 2 or 4 g GG) in 100 g total of a control commercial high-fibre flatbread flour mix (“atta”) on PPG in 38 normal-weight adults. Self-reported appetite was an additional exploratory outcome. An in vitro digestion assay was adapted for flatbreads and assessed for prediction of in vivo PPG.ResultsFlatbreads with 6 g GG, 4 g KM, and 15 g CPF plus 2 or 4 g GG reduced PPG ≥30 % (p < 0.01), while no other combinations differed significantly from the control. A statistical model with four in vitro parameters (rate of digestion, %RDS, AUC, carbohydrate level) was highly predictive of PPG results (adjusted R 2 = 0.89). Test products were similar to the control for appetite-related measures.ConclusionsThe results confirm the efficacy of specific additions to flatbread flour mixes for reducing PPG and the value of the in vitro model as a predictive tool with these ingredients and product format.This trial is registered at ClinicalTrials.gov with identifier NCT02671214.Electronic supplementary materialThe online version of this article (doi:10.1007/s00394-016-1242-9) contains supplementary material, which is available to authorized users.
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