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High consumption of refined grains, particularly white rice, has been reported to be associated with a higher risk of type 2 diabetes. Therefore, in the present study, we evaluated the association between rice and noodle consumption and markers of glucose homeostasis, inflammation and dyslipidaemia in an Asian population. We carried out a population-based cross-sectional study in 2728 Singaporean Chinese men and women aged between 24 and 92 years. Rice and noodle intake was assessed using a validated FFQ and studied in relation to glycaemic (fasting glucose, glycated Hb, homeostasis model assessment (HOMA) index for insulin resistance (HOMA-IR) and HOMA index for β-cell function (HOMA-β)), inflammatory (plasma adiponectin and C-reactive protein (CRP)) and lipid (fasting TAG and HDL-cholesterol (HDL-C)) markers. We used multiple linear regression analyses with adjustment for total energy intake and sociodemographic, anthropometric (BMI and waist:hip ratio) and lifestyle factors. Higher rice consumption was found to be associated with higher fasting glucose concentrations (0·81 % higher values per portion increment; 95 % CI 0·09, 1·54) and HOMA-IR (4·62 %; 95 % CI 1·29, 8·07). Higher noodle consumption was also found to be significantly associated with higher fasting glucose concentrations (1·67 %; 95 % CI 0·44, 2·92), HOMA-IR (6·17 %; 95 % CI 0·49, 12·16) and fasting TAG concentrations (9·17 %; 95 % CI 3·44, 15·22). No significant association was observed between rice and noodle consumption and adiponectin, CRP and HDL-C concentrations or HOMA-β in the fully adjusted model. These results suggest that high consumption of rice and noodles may contribute to hyperglycaemia through greater insulin resistance and that this relationship is independent of adiposity and systemic inflammation.
Nutrigenomics is the study of how constituents of the diet interact with genes, and their products, to alter phenotype and, conversely, how genes and their products metabolise these constituents into nutrients, antinutrients, and bioactive compounds. Results from molecular and genetic epidemiological studies indicate that dietary unbalance can alter gene–nutrient interactions in ways that increase the risk of developing chronic disease. The interplay of human genetic variation and environmental factors will make identifying causative genes and nutrients a formidable, but not intractable, challenge. We provide specific recommendations for how to best meet this challenge and discuss the need for new methodologies and the use of comprehensive analyses of nutrient–genotype interactions involving large and diverse populations. The objective of the present paper is to stimulate discourse and collaboration among nutrigenomic researchers and stakeholders, a process that will lead to an increase in global health and wellness by reducing health disparities in developed and developing countries.
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