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      Dietary flavonoid intakes and risk of type 2 diabetes in US men and women.

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          Abstract

          Data from mechanistic studies support a beneficial effect of specific flavonoids on insulin sensitivity. However, few studies have evaluated the relation between intakes of different flavonoid subclasses and type 2 diabetes.

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          Most cited references15

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          Dietary fat and coronary heart disease: a comparison of approaches for adjusting for total energy intake and modeling repeated dietary measurements.

          Previous cohort studies of fat intake and risk of coronary heart disease (CHD) have been inconsistent, probably due in part to methodological differences and various limitations, including inadequate dietary assessment and incomplete adjustment for total energy intake. The authors analyzed repeated assessment of diet from the Nurses' Health Study to examine the associations between intakes of four major types of fat (saturated, monounsaturated, polyunsaturated, and trans fats) and risk of CHD during 14 years of follow-up (1980-1994) by using alternative methods for energy adjustment. In particular, the authors compared four risk models for energy adjustment: the standard multivariate model, the energy-partition model, the nutrient residual model, and the multivariate nutrient density model. Within each model, the authors compared four different approaches for analyzing repeated dietary measurements: baseline diet only, the most recent diet, and two different algorithms for calculating cumulative average diets. The substantive results were consistent across all models; that is, higher intakes of saturated and trans fats were associated with increased risk of CHD, while higher intakes of monounsaturated and polyunsaturated fats were associated with reduced risk. When nutrients were considered as continuous variables, the four energy-adjustment methods yielded similar associationS. However, the interpretation of the relative risks differed across models. In addition, within each model, the methods using the cumulative averages in general yielded stronger associations than did those using either only baseline diet or the most recent diet. When the nutrients were categorized according to quintiles, the residual and the nutrient density models, which gave similar results, yielded statistically more significant tests for linear trend than did the standard and the partition models.
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            Food-based validation of a dietary questionnaire: the effects of week-to-week variation in food consumption.

            The reproducibility and validity of responses for 55 specific foods and beverages on a self-administered food frequency questionnaire were evaluated. One hundred and seventy three women from the Nurses' Health Study completed the questionnaire twice approximately 12 months apart and also recorded their food consumption for seven consecutive days, four times during the one-year interval. For the 55 foods, the mean of correlation coefficients between frequencies of intake for first versus second questionnaire was 0.57 (range = 0.24 for fruit punch to 0.93 for beer). The mean of correlation coefficients between the dietary records and first questionnaire was 0.44 (range = 0.09 for yellow squash to 0.83 for beer and tea) and between the dietary records and the second questionnaire was 0.52 (range = 0.08 for spinach to 0.90 for tea). Ratios of within- to between-person variance for the 55 foods were computed using the mean four one-week dietary records for each person as replicate measurements. For most foods this ratio was greater than 1.0 (geometric mean of ratios = 1.88), ranging from 0.25 (skimmed milk) to 14.76 (spinach). Correlation coefficients comparing questionnaire and dietary record for the 55 foods were corrected for the within-person variation (mean corrected value = 0.55 for dietary record versus first questionnaire and 0.66 versus the second). Mean daily amounts of each food calculated by the questionnaire and by the dietary record were also compared; the observed differences suggested that responses to the questionnaire tended to over-represent socially desirable foods. This analysis documents the validity and reproducibility of the questionnaire for measuring specific foods and beverages, as well as the large within-person variation for food intake measured by dietary records. Differences in the degree of validity for specific foods revealed in this type of analysis can be useful in improving questionnaire design and in interpreting findings from epidemiological studies that use the instrument.
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              Impact of Dietary Polyphenols on Carbohydrate Metabolism

              Polyphenols, including flavonoids, phenolic acids, proanthocyanidins and resveratrol, are a large and heterogeneous group of phytochemicals in plant-based foods, such as tea, coffee, wine, cocoa, cereal grains, soy, fruits and berries. Growing evidence indicates that various dietary polyphenols may influence carbohydrate metabolism at many levels. In animal models and a limited number of human studies carried out so far, polyphenols and foods or beverages rich in polyphenols have attenuated postprandial glycemic responses and fasting hyperglycemia, and improved acute insulin secretion and insulin sensitivity. The possible mechanisms include inhibition of carbohydrate digestion and glucose absorption in the intestine, stimulation of insulin secretion from the pancreatic β–cells, modulation of glucose release from the liver, activation of insulin receptors and glucose uptake in the insulin-sensitive tissues, and modulation of intracellular signalling pathways and gene expression. The positive effects of polyphenols on glucose homeostasis observed in a large number of in vitro and animal models are supported by epidemiological evidence on polyphenol-rich diets. To confirm the implications of polyphenol consumption for prevention of insulin resistance, metabolic syndrome and eventually type 2 diabetes, human trials with well-defined diets, controlled study designs and clinically relevant end-points together with holistic approaches e.g., systems biology profiling technologies are needed.
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                Author and article information

                Journal
                Am. J. Clin. Nutr.
                The American journal of clinical nutrition
                American Society for Nutrition
                1938-3207
                0002-9165
                Apr 2012
                : 95
                : 4
                Affiliations
                [1 ] Department of Nutrition, Harvard School of Public Health, Boston, MA 02115, USA. nwedick@hsph.harvard.edu
                Article
                ajcn.111.028894
                10.3945/ajcn.111.028894
                3302366
                22357723
                c503bf29-ce79-4e79-9304-e5a1dd578b7b
                History

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