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Carbohydrate quality and quantity and risk of coronary heart disease among US women and men.
AlEssa, HB, Cohen, R, Malik, VS, Adebamowo, SN, Rimm, EB, Manson, JE, Willett, WC, Hu, FB
The American journal of clinical nutrition. 2018;(2):257-267
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Abstract
BACKGROUND The carbohydrate-to-fiber ratio is a recommended measure of carbohydrate quality; however, its relation to incident coronary heart disease (CHD) is not currently known. OBJECTIVE We aimed to assess the relation between various measures of carbohydrate quality and incident CHD. DESIGN Data on diet and lifestyle behaviors were prospectively collected on 75,020 women and 42,865 men participating in the Nurses' Health Study (NHS) and the Health Professionals Follow-Up Study (HPFS) starting in 1984 and 1986, respectively, and every 2-4 y thereafter until 2012. All participants were free of known diabetes mellitus, cancer, or cardiovascular disease at baseline. Cox proportional hazards regression models were used to assess the relation between dietary measures of carbohydrate quality and incident CHD. RESULTS After 1,905,047 (NHS) and 921,975 (HPFS) person-years of follow-up, we identified 7,320 cases of incident CHD. In models adjusted for age, lifestyle behaviors, and dietary variables, the highest quintile of carbohydrate intake was not associated with incident CHD (pooled-RR = 1.04; 95% CI: 0.96, 1.14; P-trend = 0.31). Total fiber intake was not associated with risk of CHD (pooled-RR = 0.94; 95% CI: 0.85, 1.03; P-trend = 0.72), while cereal fiber was associated with a lower risk for incident CHD (pooled-RR = 0.80; 95% CI: 0.74, 0.87; P-trend < 0.0001). In fully adjusted models, the carbohydrate-to-total fiber ratio was not associated with incident CHD (pooled-RR = 1.04; 95% CI: 0.96, 1.13; P-trend = 0.46). However, the carbohydrate-to-cereal fiber ratio and the starch-to-cereal fiber ratio were associated with an increased risk for incident CHD (pooled-RR = 1.20; 95% CI: 1.11, 1.29; P-trend < 0.0001, and pooled-RR = 1.17; 95%CI: 1.09, 1.27; P-trend < 0.0001, respectively). CONCLUSION Dietary cereal fiber appears to be an important component of carbohydrate quality. The carbohydrate-to-cereal fiber ratio and the starch-to-cereal fiber ratio, but not the carbohydrate-to-fiber ratio, was associated with an increased risk for incident CHD. Future research should focus on how various measures of carbohydrate quality are associated with CHD prevention. This trial was registered at clinicaltrials.gov as NCT03214861.
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Carbohydrate quality and quantity and risk of type 2 diabetes in US women.
AlEssa, HB, Bhupathiraju, SN, Malik, VS, Wedick, NM, Campos, H, Rosner, B, Willett, WC, Hu, FB
The American journal of clinical nutrition. 2015;(6):1543-53
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Abstract
BACKGROUND Carbohydrate quality may be an important determinant of type 2 diabetes (T2D); however, relations between various carbohydrate quality metrics and T2D risk have not been systematically investigated. OBJECTIVE The purpose of this study was to prospectively examine the association between carbohydrates, starch, fibers, and different combinations of these nutrients and risk of T2D in women. DESIGN We prospectively followed 70,025 women free of cardiovascular disease, cancer, and diabetes at baseline from the Nurses' Health Study (1984-2008). Diet information was collected with the use of a validated questionnaire every 4 y. Cox regression was used to evaluate associations with incident T2D. RESULTS During 1,484,213 person-years of follow-up, we ascertained 6934 incident T2D cases. In multivariable analyses, when extreme quintiles were compared, higher carbohydrate intake was not associated with T2D (RR = 0.98; 95% CI: 0.89, 1.08; P-trend = 0.84), whereas starch was associated with a higher risk (RR = 1.23; 95% CI: 1.12, 1.35; P-trend <0.0001). Total fiber (RR = 0.80; 95% CI: 0.72, 0.89; P-trend < 0.0001), cereal fiber (RR = 0.71, 95% CI: 0.65, 0.78; P-trend < 0.0001), and fruit fiber (RR = 0.79; 95% CI: 0.72, 0.85; P-trend < 0.0001) were associated with a lower T2D risk. The ratio of carbohydrate to total fiber intake was marginally associated with a higher risk of T2D (RR = 1.09; 95% CI: 1.00, 1.20; P-trend = 0.04). On the other hand, we found positive associations between the ratios of carbohydrate to cereal fiber (RR = 1.28; 95% CI: 1.17, 1.39; P-trend < 0.0001), starch to total fiber (RR = 1.12; 95% CI: 1.02, 1.23; P-trend = 0.03), and starch to cereal fiber (RR = 1.39; 95% CI: 1.27, 1.53; P-trend < 0.0001) and T2D. CONCLUSIONS Diets with high starch, low fiber, and a high starch-to-cereal fiber ratio were associated with a higher risk of T2D. The starch-to-cereal fiber ratio of the diet may be a novel metric for assessing carbohydrate quality in relation to T2D.
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Prediction of postprandial glycemia and insulinemia in lean, young, healthy adults: glycemic load compared with carbohydrate content alone.
Bao, J, Atkinson, F, Petocz, P, Willett, WC, Brand-Miller, JC
The American journal of clinical nutrition. 2011;(5):984-96
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Abstract
BACKGROUND Dietary glycemic load (GL; defined as the mathematical product of the glycemic index and carbohydrate content) is increasingly used in nutritional epidemiology. Its ability to predict postprandial glycemia and insulinemia for a wide range of foods or mixed meals is unclear. OBJECTIVE Our objective was to assess the degree of association between calculated GL and observed glucose and insulin responses in healthy subjects consuming isoenergetic portions of single foods and mixed meals. DESIGN In study 1, groups of healthy subjects consumed 1000-kJ portions of 121 single foods in 10 food categories. In study 2, healthy subjects consumed 2000-kJ servings of 13 mixed meals. Foods and meals varied widely in macronutrient content, fiber, and GL. Glycemia and insulinemia were quantified as area under the curve relative to a reference food (= 100). RESULTS Among the single foods, GL was a more powerful predictor of postprandial glycemia and insulinemia than was the available carbohydrate content, explaining 85% and 59% of the observed variation, respectively (P < 0.001). Similarly, for mixed meals, GL was also the strongest predictor of postprandial glucose and insulin responses, explaining 58% (P = 0.003) and 46% (P = 0.01) of the variation, respectively. Carbohydrate content alone predicted the glucose and insulin responses to single foods (P < 0.001) but not to mixed meals. CONCLUSION These findings provide the first large-scale, systematic evidence of the physiologic validity and superiority of dietary GL over carbohydrate content alone to estimate postprandial glycemia and insulin demand in healthy individuals. This trial was registered at ANZCTR.org as ACTRN12610000484044.
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Dietary glycemic load and atherothrombotic risk.
Liu, S, Willett, WC
Current atherosclerosis reports. 2002;(6):454-61
Abstract
Hyperglycemia and hyperinsulinemia are central features of the metabolic syndrome and type 2 diabetes mellitus, which contribute to the pathogenesis of coronary heart disease (CHD). Recent data indicate that increased dietary glycemic load (GL) due to replacing fats with carbohydrates or increasing intake of rapidly absorbed carbohydrates (ie, high glycemic index) can create a self-perpetuating insulin resistance state and predicts greater CHD risk. In this paper, we discuss the historic development of the GI and GL concepts and summarize metabolic experiments and epidemiologic observations relating to clinical utilities of these measures. On balance, increased consumption of low-GI foods leads to improvements in glycemia and dyslipidemia in metabolic studies, and a low-GL diet has been associated with lower risk of type 2 diabetes and CHD in prospective cohort studies. We conclude that decreasing dietary GL by reducing the intake of high-glycemic beverages and replacing refined grain products and potatoes with minimally processed plant-based foods such as whole grains, fruits, and vegetables may reduce CHD incidence in sedentary individuals and populations with a high prevalence of overweight. Because of advances in food-processing technologies and changes in ingredients in our food supply, the composition and physiologic effects of foods are likely to change over time. Future efforts should continue to quantify and monitor the metabolic impacts of different foods, and such information should be routinely incorporated into long-term prospective studies to allow for the assessment of the interactive effects of diets and other metabolic determinants on chronic disease risk.