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Original Research Communications |
1 From the Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis; the Department of Epidemiology, Harvard School of Public Health, Boston; and the Department of Food Science and Nutrition, University of Minnesota, St Paul.
2 Supported by the National Institutes of Health (research grant R01 CA-39742). 3 Address reprint requests to AR Folsom, Division of Epidemiology, School of Public Health, University of Minnesota, Suite 300, 1300 South Second Street, Minneapolis, MN 55454-1015. E-mail: folsom{at}epi.umn.edu.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Objective: We examined the relations of baseline intake of carbohydrates, dietary fiber, dietary magnesium, and carbohydrate-rich foods and the glycemic index with incidence of diabetes.
Design: This was a prospective cohort study of 35988 older Iowa women initially free of diabetes. During 6 y of follow-up, 1141 incident cases of diabetes were reported.
Results: Total grain, whole-grain, total dietary fiber, cereal fiber, and dietary magnesium intakes showed strong inverse associations with incidence of diabetes after adjustment for potential nondietary confounding variables. Multivariate-adjusted relative risks of diabetes were 1.0, 0.99, 0.98, 0.92, and 0.79 (P for trend: 0.0089) across quintiles of whole-grain intake; 1.0, 1.09, 1.00, 0.94, and 0.78 (P for trend: 0.005) across quintiles of total dietary fiber intake; and 1.0, 0.81, 0.82, 0.81, and 0.67 (P for trend: 0.0003) across quintiles of dietary magnesium intake. Intakes of total carbohydrates, refined grains, fruit and vegetables, and soluble fiber and the glycemic index were unrelated to diabetes risk.
Conclusion: These data support a protective role for grains (particularly whole grains), cereal fiber, and dietary magnesium in the development of diabetes in older women.
Key Words: Type 2 diabetes • non-insulin-dependent diabetes mellitus • diet • nutrition • prospective studies • carbohydrates • dietary fiber • sugar • glycemic index • grains • magnesium • Iowa Women's Health Study • women
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Findings from metabolic and epidemiologic studies on the relations between carbohydrates and dietary fiber and diabetes are inconsistent. Evidence from metabolic studies supports beneficial (3), detrimental (4, 5), and neutral (6) effects of a highcarbohydrate diet relative to high-fat diets on glycemic response. The results of ecologic and cross-sectional studies support decreased prevalences of diabetes with high intakes of carbohydrate (7–9), whereas the results of cohort studies do not support an association between diabetes and total dietary carbohydrate (10–13). Dietary fiber is reported to improve the postprandial glycemic response and insulin concentrations, most likely by slowing the digestion and absorption of food and by regulating several metabolic hormones (14, 15). However, results on dietary fiber and diabetes from prospective and case-control studies have been mixed (7, 11, 12, 16). Magnesium is a component of grains and is found in the fibrous component of cereal plants. Dietary magnesium was inversely related to incident type 2 diabetes in some (11, 12), but not all (17), prospective cohort studies.
Clinical work on the glycemic index and the glycemic load supports the notion that the form and content of carbohydrate and fat in foods may be important determinants of the short-term glycemic response (18). The glycemic index and glycemic load were directly related to diabetes risk in 2 large cohort studies (11, 12). In addition, recent attention has been directed to the potential effects of whole compared with refined grains on the glycemic response (19). The long-term effect of whole-grain compared with refined-grain food intake on incident diabetes has not been widely examined in the epidemiologic literature.
We examined the relations between incident diabetes and carbohydrate-related dietary variables in the Iowa Women's Health Study, a large cohort study of older women. Detailed dietary information collected at baseline enabled us to examine the long-term effects on diabetes incidence of several variables, including dietary carbohydrates, dietary fiber, the glycemic index and load, dietary magnesium, and carbohydrate-rich foods such as whole grains. These findings contribute to the long-standing discussion of the importance of carbohydrates and dietary fiber in the etiology of diabetes as well as to the relatively recent focus on glycemic index, the glycemic load, and whole-grain intake.
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SUBJECTS AND METHODS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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0.4, were 3 mo older, and were more likely to live in rural, less-affluent counties (20).
Women were excluded from these analyses if they reported implausibly high (> 20920 kJ) or low (<2510 kJ) energy intakes (n = 538), left 
30 items blank on the food-frequency questionnaire (n = 2782), or had diabetes at baseline (n = 3121). Women were considered diabetic at baseline if they responded "yes" or "don't know" to the following questions: Have you ever been told by a doctor that you have sugar diabetes (diabetes mellitus)? (n = 2947) and Have you ever taken insulin or pills for sugar diabetes (or to lower blood sugar)? (n = 2747). A total of 35988 women remained eligible for the study. The study was approved by the Human Subjects Review Committee at the University of Minnesota.
Data collection
The baseline questionnaire included questions on known or suspected risk factors for diabetes, including age, BMI, waist-to-hip ratio (WHR), physical activity, and smoking history. BMI was calculated from weight and height measurements provided by the participants. WHR was calculated as the average of 2 measurements taken by the participant's spouse or a friend using a paper tape measure included with the questionnaire (21). A 3-level physical activity score was created by combining questions on the frequency of moderate and vigorous leisure-time activity. Pack-years of smoking (number of packs of cigarettes smoked daily times the number of years smoked) were calculated from information on the intensity and duration of cigarette smoking.
The principal dietary exposure of interest was intake of carbohydrates, including dietary fiber. This variable was examined by analyzing food sources of carbohydrates, subtypes of carbohydrates, components of carbohydrates, and the glycemic index and load. The food groups analyzed included grains, vegetables, fruit, and legumes. Total grain intake was subdivided into refined and whole grains as outlined previously (22). In addition to total dietary carbohydrates, starch, sucrose, glucose, fructose, maltose, and lactose were analyzed individually. Because the physiologic effects of fiber may relate to subtype (23), soluble and insoluble fiber were analyzed separately. Also, total dietary fiber was divided into mutually exclusive categories representing fiber contributed to the diet by cereals, fruit, vegetables, and legumes.
A 127-item food-frequency questionnaire similar to that used in the 1984 Nurses' Health Study was used to assess typical food intake over the previous year (24). The validity of the food-frequency questionnaire was evaluated in this cohort by comparing nutrient values determined from the questionnaire with values estimated from the average of five 24-h dietary recall surveys in 44 study participants. Energy-adjusted Pearson's correlation coefficients for total carbohydrates and crude fiber were 0.45 and 0.24, respectively (25).
The glycemic index and glycemic load variables measure the glycemic response and insulin demand that result from specific carbohydrate-containing foods. The glycemic index and load values were available for most foods and were calculated as described by Salmerón et al (11, 12). The average dietary glycemic index for each individual was calculated as follows:
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Similarly, a glycemic load score was obtained for each individual as follows:
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Diabetes incidence was determined by an affirmative response to the following question on one of the follow-up surveys: Since (baseline or respective follow-up), were you diagnosed for the first time by a doctor as having sugar diabetes? Over 6 y of follow-up, 1141 women reported having diabetes in the 3 follow-up surveys administered in 1987 (n = 344), 1989 (n = 331), and 1992 (n = 466). Response rates for the 3 follow-up surveys were 91%, 86%, and 79%, respectively.
A validation study of self-reported diabetes was conducted with 85 cohort participants in 1988 after the first follow-up survey (26). Subjects tended to overreport diabetes: of 44 women who reported diabetes at baseline, 28 (64%) were confirmed as being diabetic by their physician. All 41 women who reported not having diabetes at baseline were confirmed as not being diabetic.
Statistical analysis
Person-time of follow-up was calculated for each study participant as follows. For those women who did not report a diagnosis of diabetes, person-time was calculated from baseline to the date of the last completed questionnaire. For women who reported having been diagnosed with diabetes on one of the follow-up surveys, person-time was calculated as the sum of the known disease-free period and half of the period during which the diagnosis was first made. Mortality status was determined annually through linkage with the State Health Registry of Iowa. In addition, nonrespondents to the 3 follow-up surveys and emigrants from Iowa were linked with the National Death Index.
Dietary variables were categorized as appropriate for analysis. Relative risks calculated with proportional hazards regression are comparisons between the upper categories of intake and the lowest category. Trend analyses weighted each category of intake by the median intake for that category. Nutrient intakes were adjusted for total energy by the method described by Willett and Stampfer (27). Initial analyses were adjusted only for age and total energy. Further analyses were also adjusted for potential confounders of the observed diet-diabetes associations, including physical activity, BMI, WHR, smoking, alcohol intake, and education. Additional analyses excluded women who reported having cancer (n = 3202) or heart disease (n = 3110) at baseline (because these women may have recently modified their diets) and controlled for reported family history of diabetes in a first-degree relative (mother, father, brother, or sister), which was asked only in the third follow-up. The SAS package was used (28).
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RESULTS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The distribution of these risk factors across quintiles of whole-grain and energy-adjusted dietary fiber intake are shown in Table 1
. Trends in most covariates across quintiles of dietary intakes were statistically significant. However, this was assuredly due to the large sample size, and the trends of only some covariates can be presumed to be clinically relevant. For example, women who reported higher intakes of whole grains and dietary fiber at baseline were appreciably more likely to have engaged in vigorous physical activity, have graduated from high school, have been nonsmokers, and have had low WHRs. In addition, the prevalence of abstinence from alcohol was 11% higher for women in the highest category of dietary fiber intake than for women in the lowest category of intake.
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. After adjustment for potential confounding variables, total carbohydrates, starch, lactose, and maltose were unrelated to incidence of diabetes. RRs across total carbohydrate quintiles were 1.0, 1.05, 0.98, 0.90, 0.93 (P for trend: 0.22). Sucrose was inversely associated with incidence of diabetes. Women in the highest quintile of sucrose intake had an RR of 0.81 compared with women in the lowest quintile. Glucose and fructose intakes were positively associated with diabetes risk. The RRs comparing the highest quintile of intake with the lowest were 1.30 and 1.27 for glucose and fructose, respectively. Age- and energy-adjusted risk estimates were similar to the multivariate-adjusted findings, except that total carbohydrate intake showed a stronger inverse relation to type 2 diabetes in the age- and energy-adjusted model. The RR estimates in the age- and energy-adjusted model were 1.00, 1.06, 0.96, 0.84, and 0.86 (P for trend: 0.018) across quintiles of intake.
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). The pattern of risk across quintiles of glycemic index was inconsistent; RRs first rose to 1.22 in quintile 3 and then dropped to 0.84 in quintile 5. Glycemic load was nonsignificantly inversely related to diabetes. These findings did not appear to have been due to confounding or effect modification by dietary fiber intake. Relative risk estimates were similar in age- and energy-adjusted analyses.
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. In the multivariate analysis, total dietary fiber was inversely associated with diabetes risk (RR = 0.78 comparing the fifth with the first quintile of intake; P for trend: 0.005). Intake of insoluble fiber was inversely associated with diabetes risk, whereas intake of soluble fiber did not appear to be strongly related to diabetes risk. Women in the highest quintile of intake had RRs of 0.89 and 0.75 for soluble and insoluble fiber, respectively, compared with women in the first quintile of intake. Fiber derived from cereals was also inversely associated with diabetes (RR = 0.64 for the highest versus the lowest quintile). Fiber derived from fruit, vegetables, or legumes was unrelated to diabetes risk. Also shown in Table 4 are the multivariate-adjusted RRs of diabetes across quintiles of intake of dietary magnesium, which is found in the fibrous component of cereal plants. There was an inverse relation between dietary magnesium and type 2 diabetes.
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and the age- and energy-adjusted analyses did not differ appreciably. Exceptions to this were an inverse relation between diabetes and soluble fiber and the lack of an association between diabetes and fiber from fruit in the age- and energy-adjusted analyses. Relative risks in the age- and energy-adjusted analysis were 1.00, 0.91, 0.94, 0.86, and 0.77 (P for trend: 0.0046) across quintiles of soluble fiber intake and 1.00, 0.96, 1.12, 0.97, and 1.05 (P for trend: 0.63) across quintiles of fiber intake from fruit.
Associations between diabetes and food groups that contribute carbohydrates and fiber to the diet were also examined (Table 5). Consistent with the finding for cereal fiber, total grain intake was inversely related to incident diabetes. The multivariate-adjusted RR comparing the fifth and first quintiles of total grain intake was 0.68 (95% CI: 0.54, 0.87). Whole grains were more strongly inversely associated with risk of diabetes than were refined grains. Women in the highest quintile of whole grain intake had an adjusted RR of 0.79 (95% CI: 0.65, 0.96) compared with women in the lowest quintile (P for trend: 0.0089). Intakes of fruit, vegetables, and legumes were not strongly related to diabetes risk. These findings from the multivariate analysis differed only slightly from the age- and energy-adjusted estimates and the interpretation of findings did not change with adjustment for potential confounding factors. For example, age- and energy-adjusted RRs for whole grain intake were 1.00, 0.86, 0.92, 0.83, and 0.70 (P for trend: 0.0029) across quintiles of intake.
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. To control for recent dietary changes, multivariate models were also run that excluded women who reported cancer or heart disease at baseline. Relative risk estimates were not appreciably changed by these exclusions.
Results from multivariate regression models that included more than one of the dietary components under study are shown in Table 6. Dietary intakes of foods and nutrients are highly correlated and these models were intended to help distinguish the effects of dietary variables that appeared related to type 2 diabetes in these data. Each of the 4 models was adjusted for the covariates listed in the footnote as well as for the dietary components listed below the model headings. Because our findings were strongest for grain intake, these analyses focused on the effects of adjusting grains for cereal fiber and dietary magnesium, 2 components of grains that were strongly related to type 2 diabetes in these data. Results for total grains and whole grains were attenuated after the models were adjusted for cereal fiber. For example, RRs were 1.00, 1.01, 1.02, 1.01, and 0.93 (P for trend: 0.46) across quintiles of whole-grain intake. However, both cereal fiber and dietary magnesium remained significantly and inversely related to type 2 diabetes. Simultaneous adjustment for grains, cereal grains, and dietary magnesium attenuated the findings for cereal fiber and dietary magnesium, but inverse dose-response relations were still apparent for these 2 grain components. For example, RRs from model 4 were 1.00, 0.93, 0.90, 0.80, and 0.71 (P for trend: 0.0017) across quintiles of cereal fiber intake and 1.00, 0.82, 0.86, 0.88, and 0.76 (P for trend: 0.048) across quintiles of dietary magnesium intake. Overall, these findings suggest that the inverse relation between whole-grain intake and type 2 diabetes may be due to fiber and components of whole grains that are highly correlated with fiber.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The relation between dietary fiber and diabetes has received much attention (11, 12, 14–16, 29–36). Fiber, particularly soluble fiber, has repeatedly been shown to decrease postprandial glucose and insulin concentrations both in persons with diabetes and in those without (36). In addition, several cross-sectional epidemiologic studies reported inverse associations of serum insulin with fiber intake (30–34).
In the present study, women in the highest quintile of dietary fiber intake had a 22% lower risk of developing diabetes than did women in the lowest quintile. These data corroborate a report from the Nurses' Health Study in which a similar magnitude of diabetes risk was associated with dietary fiber intake (11). In contrast, in a cohort of male health professionals, no association was found between diabetes risk and total dietary fiber intake (12). Similarly, no association was seen in a case-control study of 702 men and women (16). The 20-y follow-up of the Finnish and Dutch cohorts of the Seven Countries Study yielded no association of dietary fiber with impaired glucose tolerance or diagnosed diabetes (35).
The plasma glucose–lowering effects of fiber are attributed primarily to soluble fiber, which slows the absorption of food by creating a gel-like substance in the stomach (14, 36). For this reason, a stronger inverse association between soluble fiber and diabetes risk than between insoluble fiber and diabetes risk was expected. Insoluble fiber may also slow the absorption of food (36). The finding that insoluble fiber, but not soluble fiber, was inversely associated with diabetes risk is consistent with previous reports from other cohort studies. The Nurses' Health Study reported that of the associations of diabetes with different sources of dietary fiber, only the inverse association between cereal fiber and diabetes remained statistically significant after multivariate adjustment (11). In the Health Professionals' Follow-up Study, cereal fiber was inversely associated with diabetes risk, whereas fiber from fruit and vegetables was unrelated to diabetes risk (12). The findings from these prospective cohort studies, all of which used a similar questionnaire, support a stronger association of insoluble fiber than of soluble fiber with diabetes risk.
Our findings indicate a strong inverse relation between dietary magnesium intake—a component of grains—and risk of type 2 diabetes. This finding remained after adjustment for cereal fiber and grain intakes. In clinical studies, low plasma magnesium concentrations were associated with insulin resistance (37), and magnesium supplementation was shown to improve glucose handling (38). Findings from 2 large prospective studies suggested strong inverse relations between magnesium intake and incident type 2 diabetes (11, 12) and fasting insulin concentrations (39). For example, Salmerón et al (11, 12) reported a 38% decreased risk of diabetes for persons in the highest quintile of magnesium intake compared with the lowest quintile of intake. Investigators with the Atherosclerosis Risk in Communities Study reported that incident diabetes was inversely associated with serum magnesium but not with dietary magnesium intake (17).
The associations of insoluble fiber and cereal fiber intakes with diabetes risk were consistent with the analysis of food groups (Table 5), suggesting that whole-grain cereals were more strongly inversely related to disease risk than were refined cereals. Whole and refined grains contain similar amounts of carbohydrate, but whole grains contain substantially more dietary fiber and magnesium (40). It is important to note that what was included as whole grains herein may have consisted largely of whole meal. It has been shown that particle size may be important in the glycemic response (19) and thus the beneficial effects of whole grain reported here may have been more striking in a population that consumed grains primarily in an intact form.
The glycemic index was devised to measure the effect of various foods on postprandial glycemic responses. Energy sources that are slowly absorbed have low glycemic indexes and have been shown to result in better short-term glycemic control in clinical studies than energy sources with high glycemic indexes (18). Two prospective studies showed positive relations between the glycemic index and diabetes risk (11, 12). However, the present analyses do not support a consistent, dose-response relation between glycemic index and risk of type 2 diabetes. The RR estimates increased through the third quintile of intake and then dropped in the fourth and fifth quintiles. The findings of positive relations between both fructose and glucose and diabetes similarly do not support the hypothesis of a positive relation between the glycemic index and diabetes risk. Fructose has a glycemic index of 26 and glucose has a glycemic index of 138 when white bread is used as the reference (18). However, in this study, both the high correlation (r = 0.94) between fructose and glucose intake—which makes it difficult to differentiate their associations with diabetes—and the typically poor measurement of sugars hinders clear interpretation of these data.
There is a long-standing debate regarding the effect of sugar intake, particularly sucrose, on diabetes risk. Clinical studies have generally reported an effect of sucrose on postprandial glycemic response similar to that of potatoes or white bread (18, 41). In nondiabetic subjects, increased fructose consumption did not alter fasting or postprandial glucose concentrations in one study (42) and improved glycemic response in others (43). Among diabetic subjects, improved glycemic response has generally been associated with increased consumption of fructose (43, 44).
Results of the few epidemiologic studies of the relation between sugars and diabetes risk are inconsistent. Cross-sectional studies showed both similar intakes of fructose and sucrose in subjects with and without diabetes (9) and decreased intakes of refined carbohydrates in those with compared with those without diabetes (8). A cross-sectional study of persons of Japanese descent living in Hawaii or Japan reported a positive association between intake of sugars and prevalent diabetes (7). Colditz et al (10) reported no association of sucrose with diabetes incidence in either lean or obese women. The present analysis suggests that, despite its high glycemic index, sucrose does not increase the risk of diabetes.
We found no evidence for an effect of total carbohydrate intake on diabetes risk, consistent with the results of previous cohort studies. Over separate follow-up periods, investigators with the Nurses' Health Study twice reported no association between intake of total carbohydrate and risk of diabetes (11, 12). Similarly, a study of 1462 Swedish women found no significant differences between intakes of carbohydrates in those who developed diabetes and those who did not over 12 y of follow-up (13). Overall, these findings argue against an independent effect of total carbohydrate intake in the etiology of diabetes.
Errors in the measurement of dietary intake, diabetes incidences, and the covariates in this study may have limited our ability to obtain accurate RR estimates. The food-frequency questionnaire was completed only once by study participants and no effort was made to examine potential dietary changes over the course of follow-up. Also, the baseline dietary survey was assumed to represent the participants' predisease diet. Although data were not available to examine the effects of inaccurate dietary assessment, random measurement error in dietary exposures most frequently attenuates risk estimates (45). There remains the potential for residual confounding by poorly measured covariates or by unmeasured differential changes in covariates over the course of follow-up.
It was not feasible to measure glucose concentrations in the study participants; incident cases of diabetes were ascertained by self-report. However, a validation study in this cohort showed low accuracy in the self-report of diabetes (26), consistent with findings from one study in which 29 of 44 (66%) positive reports of diabetes were validated with medical records (46). Several studies have provided evidence that nonvalidated positive reports may nevertheless reflect some level of diabetes. One study found that of 6 persons with nonvalidated positive reports of diabetes, 3 persons had renal glycosuria and 2 had been diagnosed with glycosuria at some point in the past, but no longer had glycosuria (47). This suggests that nondiabetic concentrations of blood glucose may not be entirely benign and that women who falsely reported a diagnosis of diabetes may still have had some level of underlying disease, such as impaired glucose tolerance, which had been mentioned to them in the past. This possibility is underscored by a recent change in the diagnostic criteria for diabetes to include lower concentrations of fasting glucose (48). Assuming that the error in diabetes ascertainment was independent and nondifferential, the present findings would only be strengthened by more accurate ascertainment of disease.
Data from this prospective study of older women support inverse associations between total and whole-grain intake and risk of incident diabetes. These findings are consistent with those of several other published studies of the health effects of whole grains. Inverse associations were also observed for dietary fiber, cereal fiber, and dietary magnesium intake. These findings suggest a role for diet in the development of diabetes that is independent of diet's effect on body weight.
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ACKNOWLEDGMENTS |
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R. Villegas, S. Liu, Y.-T. Gao, G. Yang, H. Li, W. Zheng, and X. O. Shu Prospective Study of Dietary Carbohydrates, Glycemic Index, Glycemic Load, and Incidence of Type 2 Diabetes Mellitus in Middle-aged Chinese Women Arch Intern Med, November 26, 2007; 167(21): 2310 - 2316. [Abstract] [Full Text] [PDF]
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A. W. Barclay, V. M. Flood, E. Rochtchina, P. Mitchell, and J. C. Brand-Miller Glycemic Index, Dietary Fiber, and Risk of Type 2 Diabetes in a Cohort of Older Australians Diabetes Care, November 1, 2007; 30(11): 2811 - 2813. [Full Text] [PDF]
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J. M. W. Wong and D. J. A. Jenkins Carbohydrate Digestibility and Metabolic Effects J. Nutr., November 1, 2007; 137(11): 2539S - 2546S. [Abstract] [Full Text] [PDF]
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L. Djousse and J. M. Gaziano Breakfast Cereals and Risk of Heart Failure in the Physicians' Health Study I Arch Intern Med, October 22, 2007; 167(19): 2080 - 2085. [Abstract] [Full Text] [PDF]
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A. Mosdol, D. R Witte, G. Frost, M. G Marmot, and E. J Brunner Dietary glycemic index and glycemic load are associated with high-density-lipoprotein cholesterol at baseline but not with increased risk of diabetes in the Whitehall II study Am. J. Clinical Nutrition, October 1, 2007; 86(4): 988 - 994. [Abstract] [Full Text] [PDF]
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T. T. Fung, M. McCullough, R. M. van Dam, and F. B. Hu A Prospective Study of Overall Diet Quality and Risk of Type 2 Diabetes in Women Diabetes Care, July 1, 2007; 30(7): 1753 - 1757. [Abstract] [Full Text] [PDF]
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J. Hlebowicz, G. Darwiche, O. Bjorgell, and L.-O. Almer Effect of cinnamon on postprandial blood glucose, gastric emptying, and satiety in healthy subjects Am. J. Clinical Nutrition, June 1, 2007; 85(6): 1552 - 1556. [Abstract] [Full Text] [PDF]
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D. R Jacobs Jr, L. F. Andersen, and R. Blomhoff Whole-grain consumption is associated with a reduced risk of noncardiovascular, noncancer death attributed to inflammatory diseases in the Iowa Women's Health Study Am. J. Clinical Nutrition, June 1, 2007; 85(6): 1606 - 1614. [Abstract] [Full Text] [PDF]
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C.-Y. O. Chen, P. E. Milbury, F. W. Collins, and J. B. Blumberg Avenanthramides Are Bioavailable and Have Antioxidant Activity in Humans after Acute Consumption of an Enriched Mixture from Oats J. Nutr., June 1, 2007; 137(6): 1375 - 1382. [Abstract] [Full Text] [PDF]
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A. Andersson, S. Tengblad, B. Karlstrom, A. Kamal-Eldin, R. Landberg, S. Basu, P. Aman, and B. Vessby Whole-Grain Foods Do Not Affect Insulin Sensitivity or Markers of Lipid Peroxidation and Inflammation in Healthy, Moderately Overweight Subjects J. Nutr., June 1, 2007; 137(6): 1401 - 1407. [Abstract] [Full Text] [PDF]
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J. Montonen, R. Jarvinen, P. Knekt, M. Heliovaara, and A. Reunanen Consumption of Sweetened Beverages and Intakes of Fructose and Glucose Predict Type 2 Diabetes Occurrence J. Nutr., June 1, 2007; 137(6): 1447 - 1454. [Abstract] [Full Text] [PDF]
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M. B. Schulze, M. Schulz, C. Heidemann, A. Schienkiewitz, K. Hoffmann, and H. Boeing Fiber and Magnesium Intake and Incidence of Type 2 Diabetes: A Prospective Study and Meta-analysis Arch Intern Med, May 14, 2007; 167(9): 956 - 965. [Abstract] [Full Text] [PDF]
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M. Nilsson, J. J Holst, and I. M. Bjorck Metabolic effects of amino acid mixtures and whey protein in healthy subjects: studies using glucose-equivalent drinks Am. J. Clinical Nutrition, April 1, 2007; 85(4): 996 - 1004. [Abstract] [Full Text] [PDF]
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 A. M. Hodge, D. R. English, K. O'Dea, and G. G. Giles Dietary Patterns and Diabetes Incidence in the Melbourne Collaborative Cohort Study Am. J. Epidemiol., March 15, 2007; 165(6): 603 - 610. [Abstract] [Full Text] [PDF]
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M. J. Franz The Evidence Is In: Lifestyle Interventions Can Prevent Diabetes American Journal of Lifestyle Medicine, March 1, 2007; 1(2): 113 - 121. [Abstract] [PDF]
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M. B. Schulze, K. Hoffmann, H. Boeing, J. Linseisen, S. Rohrmann, M. Mohlig, A. F.H. Pfeiffer, J. Spranger, C. Thamer, H.-U. Haring, et al. An Accurate Risk Score Based on Anthropometric, Dietary, and Lifestyle Factors to Predict the Development of Type 2 Diabetes Diabetes Care, March 1, 2007; 30(3): 510 - 515. [Abstract] [Full Text] [PDF]
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American Diabetes Association Nutrition Recommendations and Interventions for Diabetes: A position statement of the American Diabetes Association Diabetes Care, January 1, 2007; 30(suppl_1): S48 - S65. [Full Text] [PDF]
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M. Hallikainen, L. Toppinen, H. Mykkanen, J. J Agren, D. E Laaksonen, T. A Miettinen, L. Niskanen, K. S Poutanen, and H. Gylling Interaction between cholesterol and glucose metabolism during dietary carbohydrate modification in subjects with the metabolic syndrome Am. J. Clinical Nutrition, December 1, 2006; 84(6): 1385 - 1392. [Abstract] [Full Text] [PDF]
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M. E. Rumawas, N. M. McKeown, G. Rogers, J. B. Meigs, P. W.F. Wilson, and P. F. Jacques Magnesium Intake Is Related to Improved Insulin Homeostasis in the Framingham Offspring Cohort J. Am. Coll. Nutr., December 1, 2006; 25(6): 486 - 492. [Abstract] [Full Text] [PDF]
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 R. N. A. Black, M. Spence, R. O. McMahon, G. J. Cuskelly, C. N. Ennis, D. R. McCance, I. S. Young, P. M. Bell, and S. J. Hunter Effect of Eucaloric High- and Low-Sucrose Diets With Identical Macronutrient Profile on Insulin Resistance and Vascular Risk: A Randomized Controlled Trial Diabetes, December 1, 2006; 55(12): 3566 - 3572. [Abstract] [Full Text] [PDF]
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J. A. Nettleton, L. J. Harnack, C. G. Scrafford, P. J. Mink, L. M. Barraj, and D. R. Jacobs Jr. Dietary Flavonoids and Flavonoid-Rich Foods Are Not Associated with Risk of Type 2 Diabetes in Postmenopausal Women J. Nutr., December 1, 2006; 136(12): 3039 - 3045. [Abstract] [Full Text] [PDF]
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S. Bo, M. Durazzo, S. Guidi, M. Carello, C. Sacerdote, B. Silli, R. Rosato, M. Cassader, L. Gentile, and G. Pagano Dietary magnesium and fiber intakes and inflammatory and metabolic indicators in middle-aged subjects from a population-based cohort. Am. J. Clinical Nutrition, November 1, 2006; 84(5): 1062 - 1069. [Abstract] [Full Text] [PDF]
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M. A Pereira Weighing in on glycemic index and body weight. Am. J. Clinical Nutrition, October 1, 2006; 84(4): 677 - 679. [Full Text] [PDF]
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J. Halkjaer, A. Tjonneland, B. L Thomsen, K. Overvad, and T. I. Sorensen Intake of macronutrients as predictors of 5-y changes in waist circumference. Am. J. Clinical Nutrition, October 1, 2006; 84(4): 789 - 797. [Abstract] [Full Text] [PDF]
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C. Zhang, S. Liu, C. G. Solomon, and F. B. Hu Dietary Fiber Intake, Dietary Glycemic Load, and the Risk for Gestational Diabetes Mellitus Diabetes Care, October 1, 2006; 29(10): 2223 - 2230. [Abstract] [Full Text] [PDF]
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R. M. van Dam, F. B. Hu, L. Rosenberg, S. Krishnan, and J. R. Palmer Dietary Calcium and Magnesium, Major Food Sources, and Risk of Type 2 Diabetes in U.S. Black Women Diabetes Care, October 1, 2006; 29(10): 2238 - 2243. [Abstract] [Full Text] [PDF]
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 A. Bove, J. Hebreo, J. Wylie-Rosett, and C. R. Isasi Burger king and subway: key nutrients, glycemic index, and glycemic load of nutritionally promoted items. The Diabetes Educator, September 1, 2006; 32(5): 675 - 690. [Abstract] [Full Text] [PDF]
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American Diabetes Association Nutrition Recommendations and Interventions for Diabetes-2006: A position statement of the American Diabetes Association. Diabetes Care, September 1, 2006; 29(9): 2140 - 2157. [Full Text] [PDF]
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B. Ma, A. B. Lawson, A. D. Liese, R. A. Bell, and E. J. Mayer-Davis Dairy, Magnesium, and Calcium Intake in Relation to Insulin Sensitivity: Approaches to Modeling a Dose-dependent Association Am. J. Epidemiol., September 1, 2006; 164(5): 449 - 458. [Abstract] [Full Text] [PDF]
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A. W. Barclay and J. C. Brand-Miller Validity of Glycemic Index Estimates in the Insulin Resistance Atherosclerosis Study: Response to Liese et al. Diabetes Care, July 1, 2006; 29(7): 1718 - 1719. [Full Text] [PDF]
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N. R Sahyoun, X. L Zhang, P. F Jacques, N. M McKeown, and W. Juan Reply to A Esmaillzadeh and L Azadbakht and to K Esposito and D Giugliano Am. J. Clinical Nutrition, June 1, 2006; 83(6): 1441 - 1442. [Full Text] [PDF]
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D. Corella, L. Qi, E. S. Tai, M. Deurenberg-Yap, C. E. Tan, S. K. Chew, and J. M. Ordovas Perilipin Gene Variation Determines Higher Susceptibility to Insulin Resistance in Asian Women When Consuming a High-Saturated Fat, Low-Carbohydrate Diet. Diabetes Care, June 1, 2006; 29(6): 1313 - 1319. [Abstract] [Full Text] [PDF]
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A. Hozawa, D. R. Jacobs Jr., M. W. Steffes, M. D. Gross, L. M. Steffen, and D.-H. Lee Associations of Serum Carotenoid Concentrations with the Development of Diabetes and with Insulin Concentration: Interaction with Smoking: The Coronary Artery Risk Development in Young Adults (CARDIA) Study Am. J. Epidemiol., May 15, 2006; 163(10): 929 - 937. [Abstract] [Full Text] [PDF]
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 M. McCarl, L. Harnack, P. J. Limburg, K. E. Anderson, and A. R. Folsom Incidence of colorectal cancer in relation to glycemic index and load in a cohort of women. Cancer Epidemiol. Biomarkers Prev., May 1, 2006; 15(5): 892 - 896. [Abstract] [Full Text] [PDF]
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K. Murakami, S. Sasaki, Y. Takahashi, H. Okubo, Y. Hosoi, H. Horiguchi, E. Oguma, and F. Kayama Dietary glycemic index and load in relation to metabolic risk factors in Japanese female farmers with traditional dietary habits Am. J. Clinical Nutrition, May 1, 2006; 83(5): 1161 - 1169. [Abstract] [Full Text] [PDF]
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M. Schulz, A. D. Liese, F. Fang, T. S. Gilliard, and A. J. Karter Is the Association Between Dietary Glycemic Index and Type 2 Diabetes Modified by Waist Circumference? Diabetes Care, May 1, 2006; 29(5): 1102 - 1104. [Full Text] [PDF]
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T. L Halton, W. C Willett, S. Liu, J. E Manson, M. J Stampfer, and F. B Hu Potato and french fry consumption and risk of type 2 diabetes in women Am. J. Clinical Nutrition, February 1, 2006; 83(2): 284 - 290. [Abstract] [Full Text] [PDF]
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N. R Sahyoun, P. F Jacques, X. L Zhang, W. Juan, and N. M McKeown Whole-grain intake is inversely associated with the metabolic syndrome and mortality in older adults Am. J. Clinical Nutrition, January 1, 2006; 83(1): 124 - 131. [Abstract] [Full Text] [PDF]
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D. E Laaksonen, L. K Toppinen, K. S Juntunen, K. Autio, K.-H. Liukkonen, K. S Poutanen, L. Niskanen, and H. M Mykkanen Dietary carbohydrate modification enhances insulin secretion in persons with the metabolic syndrome Am. J. Clinical Nutrition, December 1, 2005; 82(6): 1218 - 1227. [Abstract] [Full Text] [PDF]
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M. Garsetti, S. Vinoy, V. Lang, S. Holt, S. Loyer, and J. C Brand-Miller The Glycemic and Insulinemic Index of Plain Sweet Biscuits: Relationships to in Vitro Starch Digestibility J. Am. Coll. Nutr., December 1, 2005; 24(6): 441 - 447. [Abstract] [Full Text] [PDF]
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A. D. Liese, M. Schulz, F. Fang, T. M.S. Wolever, R. B. D'Agostino Jr, K. C. Sparks, and E. J. Mayer-Davis Dietary Glycemic Index and Glycemic Load, Carbohydrate and Fiber Intake, and Measures of Insulin Sensitivity, Secretion, and Adiposity in the Insulin Resistance Atherosclerosis Study Diabetes Care, December 1, 2005; 28(12): 2832 - 2838. [Abstract] [Full Text] [PDF]
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X. Pi-Sunyer Do Glycemic Index, Glycemic Load, and Fiber Play a Role in Insulin Sensitivity, Disposition Index, and Type 2 Diabetes? Diabetes Care, December 1, 2005; 28(12): 2978 - 2979. [Full Text] [PDF]
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L. A. Bazzano, M. Serdula, and S. Liu Prevention of Type 2 Diabetes by Diet and Lifestyle Modification J. Am. Coll. Nutr., October 1, 2005; 24(5): 310 - 319. [Abstract] [Full Text] [PDF]
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N. R Sahyoun, A. L Anderson, A. M Kanaya, P. Koh-Banerjee, S. B Kritchevsky, N. de Rekeneire, F. A Tylavsky, A. V Schwartz, J. S. Lee, and T. B Harris Dietary glycemic index and load, measures of glucose metabolism, and body fat distribution in older adults Am. J. Clinical Nutrition, September 1, 2005; 82(3): 547 - 552. [Abstract] [Full Text] [PDF]
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M. B Schulze, K. Hoffmann, J. E Manson, W. C Willett, J. B Meigs, C. Weikert, C. Heidemann, G. A Colditz, and F. B Hu Dietary pattern, inflammation, and incidence of type 2 diabetes in women Am. J. Clinical Nutrition, September 1, 2005; 82(3): 675 - 684. [Abstract] [Full Text] [PDF]
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D. S. Sartorelli, R. D. Freire, S. R. G. Ferreira, M. A. Cardoso, and for the Japanese-Brazilian Diabetes Study Group Dietary Fiber and Glucose Tolerance in Japanese Brazilians Diabetes Care, September 1, 2005; 28(9): 2240 - 2242. [Full Text] [PDF]
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R. D. Freire, M. A. Cardoso, S. G.A. Gimeno, S. R.G. Ferreira, and for the Japanese-Brazilian Diabetes Study Group Dietary Fat Is Associated With Metabolic Syndrome in Japanese Brazilians Diabetes Care, July 1, 2005; 28(7): 1779 - 1785. [Abstract] [Full Text] [PDF]
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C. Lau, K. Faerch, C. Glumer, I. Tetens, O. Pedersen, B. Carstensen, T. Jorgensen, and K. Borch-Johnsen Dietary Glycemic Index, Glycemic Load, Fiber, Simple Sugars, and Insulin Resistance: The Inter99 study Diabetes Care, June 1, 2005; 28(6): 1397 - 1403. [Abstract] [Full Text] [PDF]
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 P. Parikh, M. C. McDaniel, M. D. Ashen, J. I. Miller, M. Sorrentino, V. Chan, R. S. Blumenthal, and L. S. Sperling Diets and Cardiovascular Disease: An Evidence-Based Assessment J. Am. Coll. Cardiol., May 3, 2005; 45(9): 1379 - 1387. [Abstract] [Full Text] [PDF]
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M. G. Huerta, J. N. Roemmich, M. L. Kington, V. E. Bovbjerg, A. L. Weltman, V. F. Holmes, J. T. Patrie, A. D. Rogol, and J. L. Nadler Magnesium Deficiency Is Associated With Insulin Resistance in Obese Children Diabetes Care, May 1, 2005; 28(5): 1175 - 1181. [Abstract] [Full Text] [PDF]
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K. Faerch, C. Lau, I. Tetens, O. B. Pedersen, T. Jorgensen, K. Borch-Johnsen, and C. Glumer A Statistical Approach Based on Substitution of Macronutrients Provides Additional Information to Models Analyzing Single Dietary Factors in Relation to Type 2 Diabetes in Danish Adults: the Inter99 Study J. Nutr., May 1, 2005; 135(5): 1177 - 1182. [Abstract] [Full Text] [PDF]
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 R. F. Kushner Low-Carbohydrate Diets, Con: The Mythical Phoenix or Credible Science? Nutr Clin Pract, February 1, 2005; 20(1): 13 - 16. [Abstract] [Full Text] [PDF]
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J. Montonen, P. Knekt, T. Harkanen, R. Jarvinen, M. Heliovaara, A. Aromaa, and A. Reunanen Dietary Patterns and the Incidence of Type 2 Diabetes Am. J. Epidemiol., February 1, 2005; 161(3): 219 - 227. [Abstract] [Full Text] [PDF]
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K. Oh, F. B. Hu, E. Cho, K. M. Rexrode, M. J. Stampfer, J. E. Manson, S. Liu, and W. C. Willett Carbohydrate Intake, Glycemic Index, Glycemic Load, and Dietary Fiber in Relation to Risk of Stroke in Women Am. J. Epidemiol., January 15, 2005; 161(2): 161 - 169. [Abstract] [Full Text] [PDF]
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 C. K. Roberts and R. J. Barnard Effects of exercise and diet on chronic disease J Appl Physiol, January 1, 2005; 98(1): 3 - 30. [Abstract] [Full Text] [PDF]
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S. Liu, M. Serdula, S.-J. Janket, N. R. Cook, H. D. Sesso, W. C. Willett, J. E. Manson, and J. E. Buring A Prospective Study of Fruit and Vegetable Intake and the Risk of Type 2 Diabetes in Women Diabetes Care, December 1, 2004; 27(12): 2993 - 2996. [Full Text] [PDF]
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P. Koh-Banerjee, M. Franz, L. Sampson, S. Liu, D. R Jacobs Jr, D. Spiegelman, W. Willett, and E. Rimm Changes in whole-grain, bran, and cereal fiber consumption in relation to 8-y weight gain among men Am. J. Clinical Nutrition, November 1, 2004; 80(5): 1237 - 1245. [Abstract] [Full Text] [PDF]
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A. M. Hodge, D. R. English, K. O'Dea, and G. G. Giles Glycemic Index and Dietary Fiber and the Risk of Type 2 Diabetes Diabetes Care, November 1, 2004; 27(11): 2701 - 2706. [Abstract] [Full Text] [PDF]
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T. Wu, E. Giovannucci, T. Pischon, S. E Hankinson, J. Ma, N. Rifai, and E. B Rimm Fructose, glycemic load, and quantity and quality of carbohydrate in relation to plasma C-peptide concentrations in US women Am. J. Clinical Nutrition, October 1, 2004; 80(4): 1043 - 1049. [Abstract] [Full Text] [PDF]
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A. M. Hodge, D. R. English, K. O'Dea, and G. G. Giles Increased Diabetes Incidence in Greek and Italian Migrants to Australia: How much can be explained by known risk factors? Diabetes Care, October 1, 2004; 27(10): 2330 - 2334. [Abstract] [Full Text] [PDF]
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N. F. Sheard, N. G. Clark, J. C. Brand-Miller, M. J. Franz, F. X. Pi-Sunyer, E. Mayer-Davis, K. Kulkarni, and P. Geil Dietary Carbohydrate (Amount and Type) in the Prevention and Management of Diabetes: A statement by the American Diabetes Association Diabetes Care, September 1, 2004; 27(9): 2266 - 2271. [Full Text] [PDF]
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J. C Brand-Miller Postprandial glycemia, glycemic index, and the prevention of type 2 diabetes Am. J. Clinical Nutrition, August 1, 2004; 80(2): 243 - 244. [Full Text] [PDF]
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B. Sloth, I. Krog-Mikkelsen, A. Flint, I. Tetens, I. Bjorck, S. Vinoy, H. Elmstahl, A. Astrup, V. Lang, and A. Raben No difference in body weight decrease between a low-glycemic-index and a high-glycemic-index diet but reduced LDL cholesterol after 10-wk ad libitum intake of the low-glycemic-index diet Am. J. Clinical Nutrition, August 1, 2004; 80(2): 337 - 347. [Abstract] [Full Text] [PDF]
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M. B Schulze, S. Liu, E. B Rimm, J. E Manson, W. C Willett, and F. B Hu Glycemic index, glycemic load, and dietary fiber intake and incidence of type 2 diabetes in younger and middle-aged women Am. J. Clinical Nutrition, August 1, 2004; 80(2): 348 - 356. [Abstract] [Full Text] [PDF]
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K. Hoffmann, M. B. Schulze, A. Schienkiewitz, U. Nothlings, and H. Boeing Application of a New Statistical Method to Derive Dietary Patterns in Nutritional Epidemiology Am. J. Epidemiol., May 15, 2004; 159(10): 935 - 944. [Abstract] [Full Text] [PDF]
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L. S Gross, L. Li, E. S Ford, and S. Liu Increased consumption of refined carbohydrates and the epidemic of type 2 diabetes in the United States: an ecologic assessment Am. J. Clinical Nutrition, May 1, 2004; 79(5): 774 - 779. [Abstract] [Full Text] [PDF]
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J. W. Anderson, K. M. Randles, C. W. C. Kendall, and D. J. A. Jenkins Carbohydrate and Fiber Recommendations for Individuals with Diabetes: A Quantitative Assessment and Meta-Analysis of the Evidence J. Am. Coll. Nutr., February 1, 2004; 23(1): 5 - 17. [Abstract] [Full Text] [PDF]
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N. M. McKeown, J. B. Meigs, S. Liu, E. Saltzman, P. W.F. Wilson, and P. F. Jacques Carbohydrate Nutrition, Insulin Resistance, and the Prevalence of the Metabolic Syndrome in the Framingham Offspring Cohort Diabetes Care, February 1, 2004; 27(2): 538 - 546. [Abstract] [Full Text] [PDF]
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M. B. Schulze and F. B. Hu Dietary Approaches to Prevent the Metabolic Syndrome: Quality versus quantity of carbohydrates Diabetes Care, February 1, 2004; 27(2): 613 - 614. [Full Text] [PDF]
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W. K. Al-Delaimy, E. B. Rimm, W. C. Willett, M. J. Stampfer, and F. B. Hu Magnesium Intake and Risk of Coronary Heart Disease among Men J. Am. Coll. Nutr., February 1, 2004; 23(1): 63 - 70. [Abstract] [Full Text] [PDF]
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 E. Salazar-Martinez, W. C. Willett, A. Ascherio, J. E. Manson, M. F. Leitzmann, M. J. Stampfer, and F. B. Hu Coffee Consumption and Risk for Type 2 Diabetes Mellitus Ann Intern Med, January 6, 2004; 140(1): 1 - 8. [Abstract] [Full Text] [PDF]
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Y. Song, J. E. Manson, J. E. Buring, and S. Liu Dietary Magnesium Intake in Relation to Plasma Insulin Levels and Risk of Type 2 Diabetes in Women Diabetes Care, January 1, 2004; 27(1): 59 - 65. [Abstract] [Full Text] [PDF]
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R. Lopez-Ridaura, W. C. Willett, E. B. Rimm, S. Liu, M. J. Stampfer, J. E. Manson, and F. B. Hu Magnesium Intake and Risk of Type 2 Diabetes in Men and Women Diabetes Care, January 1, 2004; 27(1): 134 - 140. [Abstract] [Full Text] [PDF]
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J. L. Nadler A New Dietary Approach to Reduce the Risk of Type 2 Diabetes? Diabetes Care, January 1, 2004; 27(1): 270 - 271. [Full Text] [PDF]
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A. R. Folsom, Z. Demissie, and L. Harnack Correspondence re: C. R. Jonas et al., Dietary glycemic index, glycemic load, and risk of incident breast cancer in postmenopausal women. Cancer Epidemiol. Biomark. Prev., 12: 573-577, 2003 Cancer Epidemiol. Biomarkers Prev., December 1, 2003; 12(12): 1547 - 1547. [Full Text] [PDF]
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A. D Liese, A. K Roach, K. C Sparks, L. Marquart, R. B D'Agostino Jr, and E. J Mayer-Davis Whole-grain intake and insulin sensitivity: the Insulin Resistance Atherosclerosis Study Am. J. Clinical Nutrition, November 1, 2003; 78(5): 965 - 971. [Abstract] [Full Text] [PDF]
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