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Original Investigation |

White Rice, Brown Rice, and Risk of Type 2 Diabetes in US Men and Women FREE

Qi Sun, MD, ScD; Donna Spiegelman, ScD; Rob M. van Dam, PhD; Michelle D. Holmes, MD, DrPH; Vasanti S. Malik, MSc; Walter C. Willett, MD, DrPH; Frank B. Hu, MD, PhD
[+] Author Affiliations

Author Affiliations: Departments of Nutrition (Drs Sun, van Dam, Willett, and Hu and Ms Malik), Epidemiology (Drs Spiegelman, van Dam, Holmes, Willett, and Hu and Ms Malik), and Biostatistics (Dr Spiegelman), Harvard School of Public Health; the Channing Laboratory (Drs van Dam, Holmes, Willett, and Hu), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School; all at Boston, Massachusetts.


Arch Intern Med. 2010;170(11):961-969. doi:10.1001/archinternmed.2010.109.
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Published online

Background  Because of differences in processing and nutrients, brown rice and white rice may have different effects on risk of type 2 diabetes mellitus. We examined white and brown rice consumption in relation to type 2 diabetes risk prospectively in the Health Professionals Follow-up Study and the Nurses' Health Study I and II.

Methods  We prospectively ascertained and updated diet, lifestyle practices, and disease status among 39 765 men and 157 463 women in these cohorts.

Results  After multivariate adjustment for age and other lifestyle and dietary risk factors, higher intake of white rice (≥5 servings per week vs <1 per month) was associated with a higher risk of type 2 diabetes: pooled relative risk (95% confidence interval [CI]), 1.17 (1.02-1.36). In contrast, high brown rice intake (≥2 servings per week vs <1 per month) was associated with a lower risk of type 2 diabetes: pooled relative risk, 0.89 (95% CI, 0.81-0.97). We estimated that replacing 50 g/d (uncooked, equivalent to one-third serving per day) intake of white rice with the same amount of brown rice was associated with a 16% (95% CI, 9%-21%) lower risk of type 2 diabetes, whereas the same replacement with whole grains as a group was associated with a 36% (30%-42%) lower diabetes risk.

Conclusions  Substitution of whole grains, including brown rice, for white rice may lower risk of type 2 diabetes. These data support the recommendation that most carbohydrate intake should come from whole grains rather than refined grains to help prevent type 2 diabetes.

Figures in this Article

Rice has been a staple food in Asian countries for centuries. By the 20th century, the advance of grain-processing technology made large-scale production of refined grains possible.1Through refining processes, the outer bran and germ portions of intact rice grains (ie, brown rice) are removed to produce white rice that primarily consists of starchy endosperm. Although findings are not entirely consistent, consumption of white rice, in general, generates a stronger postprandial blood glucose response as measured by the glycemic index (GI) than the same amount of brown rice. A systematic review found that the mean (SD) GI was 64 (7) for white rice and 55 (5) for brown rice.2 Higher dietary GI has been consistently associated with elevated risk of type 2 diabetes (T2D) in prospective cohort studies.36 In addition, brown rice consumption may impart beneficial effects on T2D risk by virtue of its high content of multiple nutrients, such as fiber, vitamins, and minerals, the majority of which are lost during refining and milling processes.7 In line with these observations, high intake of white rice was associated with a monotonically elevated risk of developing T2D in a Chinese population, in which white rice consumption was the primary source of carbohydrate (74% of dietary glycemic load).6

Compared with Asian countries, rice consumption is much lower in the United States but is increasing rapidly. According to the US Department of Agriculture 2009 food supply and disappearance data, rice consumption has increased more than 3-fold since the 1930s to reach 20.5 lbs (9.3 kg) per capita, and more than 70% of rice consumed is white rice.8 However, little is known about whether rice intake is associated with diabetes risk in US populations. We therefore evaluated the associations between intake of white rice and brown rice and risk of T2D in 3 large cohort studies with repeated prospective dietary assessments. We have previously observed an inverse association between whole grain consumption and risk of T2D in these cohorts.9,10 In the present study, we extended the follow-up of these previously reported studies and evaluated whether substituting whole grains for white rice is associated with a lower risk of diabetes.

STUDY POPULATIONS

We used data from 3 prospective cohort studies: the Health Professionals Follow-up Study (HPFS; age range, 32-87 years) and the Nurses' Health Study (NHS) I (age range, 37-65 years) and II (age range, 26-45 years). Detailed descriptions of these 3 cohorts were introduced elsewhere.1113 In all 3 cohort studies, questionnaires were administered at baseline, as well as biennially after baseline, to collect and update information on lifestyle practice and occurrence of chronic diseases. The follow-up rates of the participants in these cohorts are all greater than 90%.

In the current analysis, we excluded men and women who had diagnoses of diabetes, cardiovascular disease, and cancer at baseline for the dietary analyses (1986 for HPFS, 1984 for NHS I, and 1991 for NHS II, when we first assessed white rice and brown rice consumption in these cohorts). In addition, we excluded HPFS participants who left more than 70 of the 131 food items blank on the baseline food frequency questionnaire (FFQ) or who reported unusual total energy intake levels (ie, daily energy intake <800 or >4200 kcal/d). For NHS I and II participants, we excluded those who left more than 10 (NHS I) or 9 (NHS II) items blank on baseline FFQs or whose total energy intake was less than 500 or greater than 3500 kcal/d. After exclusions, data from 39 765 (of 51 530) HPFS participants, 69 120 (of 81 755) NHS I participants, and 88 343 (of 95 452) NHS II participants were available for the analysis.

The study was approved by the Human Research Committee of Brigham and Women's Hospital and the Human Subjects Committee Review Board of Harvard School of Public Health. The completion of the self-administered questionnaire was considered to imply informed consent.

ASSESSMENT OF RICE CONSUMPTION

In 1984, a 116-item FFQ was administered among the NHS I participants to collect information on their usual intake of foods and beverages in the previous year. During 1986 through 2002, similar but expanded FFQs were sent to these participants to update their diet information every 4 years. By means of the expanded FFQ used in the NHS I, dietary data were collected every 4 years during 1986 through 2002 among the HPFS participants and during 1991 through 2003 among the NHS II participants. In all FFQs, we asked the participants how often, on average, they consumed each food of a standard portion size. In the current study, on the basis of the distribution of responses to rice intake questions, we categorized participants into 5 categories (<1 serving per month, 1-3 servings per month, 1 serving per week, 2-4 servings per week, and ≥5 servings per week) of white rice intake and 3 categories (<1 serving per month, 1-4 servings per month, and ≥2 servings per week) of brown rice intake to warrant appropriate variation in rice consumption while preserving enough statistical power to make stable estimates for each category. The reproducibility and validity of these FFQs have been demonstrated in detail elsewhere.1417 In a validation study conducted among a subsample of HPFS participants, assessments of white rice and brown rice intake were moderately correlated with diet record assessments. The corrected Pearson correlation coefficients between these 2 assessments were 0.53 for white rice and 0.41 for brown rice.14 Assessment of whole grain intake was described in detail elsewhere.9 We considered any intact or milled form of grain that consisted of the expected proportions of bran, germ, and endosperm as whole grains. By definition, brown rice is a whole grain.

STUDY OUTCOME

The study outcome was incident T2D that occurred between the return of the baseline FFQ and January 31, 2006 (HPFS), June 30, 2006 (NHS I), or June 30, 2005 (NHS II). In all 3 cohorts, men and women who reported a diagnosis of T2D in the biennial follow-up questionnaires were sent a supplementary questionnaire to confirm the diagnosis. In this supplementary questionnaire, information on symptoms, diagnostic tests, and treatment was collected. We used the criteria from the National Diabetes Data Group to confirm self-reported diagnosis of T2D.18 For cases of T2D identified after 1998, we applied the American Diabetes Association criteria.19 The validity of the supplementary questionnaire for the diagnosis of diabetes has been described previously.20,21 Of a random sample of 62 nurses reporting type 2 diabetes in the supplementary questionnaire, in 61 (98%) of them the diagnosis was confirmed after their medical records were reviewed by an endocrinologist blinded to the supplementary questionnaire information.20 In another validation study conducted in HPFS participants, 97% (57 of 59) of self-reported type 2 diabetes cases were confirmed by means of medical record review.21 Deaths were identified by reports from next of kin or postal authorities or by searching the National Death Index. At least 98% of deaths among the study participants were identified.22

STATISTICAL ANALYSIS

We counted each individual's person-years of follow-up from the date of return of the baseline FFQ to the date of death, the date of diagnosis of T2D, or January 31, 2006 (HPFS), June 30, 2006 (NHS I), or June 30, 2005 (NHS II), whichever came first. The relative risks (RRs) were estimated by Cox proportional hazards regression,23 in which we stratified the analysis jointly by age in months at baseline and calendar year to control for confounding by these factors as finely as possible. In multivariate analysis, we further adjusted for ethnicity, body mass index, smoking status, alcohol intake, multivitamin use, physical activity, and family history of diabetes. Among nurses, we adjusted for oral contraceptive use (NHS II participants only), postmenopausal status, and hormone use. To minimize confounding by other dietary factors, we further adjusted for total energy intake and intake of red meat, fruits and vegetables, coffee, and whole grains. All of these covariates are established risk factors for type 2 diabetes and were correlated with white rice or brown rice consumption in these cohorts.

To address missing values of dietary variables in the follow-up FFQs, we replaced missing values with valid ones from a previous FFQ. On average, 12.7% of NHS I, 11.3% of NHS II, and 23.1% of HPFS participants had missing data after baseline assessment. To better represent long-term diet and to minimize the within-person variation, we created cumulative averages of food and nutrient intake from baseline to the censoring events.24 We stopped updating diet when participants first reported having a diagnosis of hypertension, hypercholesterolemia, cardiovascular disease, or cancer. For these participants, we carried forward the cumulative averages of dietary intake before the occurrence of these diseases to represent diet for later follow-up. We have used this approach in our previous studies to avoid systematic errors in dietary assessment due to potential biased recall after occurrence of chronic diseases.24,25 To estimate the association of substituting brown rice intake for the same amount of white rice, we included both white rice and brown rice intake as continuous variables (50 g/d, equivalent to one-third serving of white rice per day) in the same multivariate model. We used the difference between regression coefficients for brown rice and white rice to derive the RR measuring this association of substitution. We used the same approach to examine such an association for whole grains treated as a single food item. This method was used in our previous studies.26

Tests for trend were conducted by assigning the median value to each category and modeling this value as a continuous variable. To summarize the estimates of association across the 3 studies, we conducted a meta-analysis using fixed-effects models. P values for heterogeneity of study results were calculated by using the Cochran Q test.27 All P values were 2-sided. We calculated 95% confidence intervals (CIs) for RRs. Data were analyzed with the SAS package, version 9.1 (SAS Institute Inc, Cary, North Carolina). The pooling analysis was conducted with STATA 10.0 (StataCorp, College Station, Texas).

We documented 2648 incident T2D cases during 20 years of follow-up in the HPFS, 5500 cases during 22 years in the NHS I, and 2359 cases during 14 years in the NHS II. Table 1 describes the distribution of baseline characteristics according to intake of white rice and brown rice. Men and women who had high white rice intake were less likely to have European ancestry or to smoke and more likely to have a family history of diabetes. In addition, high white rice intake was associated with high fruit and vegetable intake and low intake of whole grains, cereal fiber, and trans fat. In contrast, brown rice intake was not associated with ethnicity but with a more health-conscious lifestyle and dietary profile. For example, participants with higher brown rice intake were more physically active, leaner, and less likely to smoke or have a family history of diabetes and had higher intake of fruits, vegetables, and whole grains and lower intake of red meat and trans fat. Both white rice and brown rice intake was positively associated with a higher glycemic load in all 3 cohorts.

Table Graphic Jump LocationTable 1. Baseline Characteristics of Study Participants by Levels of White Rice and Brown Rice Intake

Table 2 shows the RRs of T2D according to white rice intake. In age-adjusted models, white rice intake was associated with an elevated risk of developing T2D across the 3 studies. After multivariate adjustment for lifestyle and dietary risk factors, these associations were attenuated, but a trend of increased risk associated with high white rice intake remained. After the multivariate estimates were summarized across the 3 studies, in comparison with those in the lowest category of white rice intake, participants who ate at least 5 servings of white rice per week had a 17% (95% CI, 2%-36%; P for trend <.001) higher risk of developing T2D.

Table Graphic Jump LocationTable 2. Risk of Type 2 Diabetes Mellitus According to White Rice Intake in the HPFS, NHS I, and NHS II

In contrast to white rice, brown rice intake was associated with a lower risk of T2D in age-adjusted models (Table 3). After multivariate adjustment for covariates, these associations were attenuated but the statistical significance remained. When compared with the participants who ate less than 1 serving of brown rice per month, the pooled RR (95% CI) of T2D was 0.89 (0.81-0.97) for intake of 2 or more servings per week, with a P for trend of .005.

Table Graphic Jump LocationTable 3. Risk of Type 2 Diabetes Mellitus According to Brown Rice Intake in the HPFS, NHS I, and NHS II

We observed a monotonically decreasing risk of diabetes associated with increasing consumption of whole grains, including brown rice (Table 4). In comparison with the lowest quintile, the pooled RR (95% CI) for the highest quintile of whole grains was 0.73 (0.68-0.78; P for trend <.001). We further estimated the RRs of T2D associated with bran and germ intake (Table 4). Bran intake, but not germ intake, was associated with a lower risk of developing T2D. In comparison with those in the lowest quintile of bran intake, men and women in the highest quintile had a pooled RR (95% CI) of 0.76 (0.71-0.82; P for trend <.001). For germ intake, the corresponding RR was 0.95 (0.88-1.03; P for trend = .40).

Table Graphic Jump LocationTable 4. Risk of Type 2 Diabetes Mellitus According to Whole Grain, Bran, or Germ Intake in the HPFS, NHS I, and NHS II

We subsequently examined the RR associated with the replacement of 50 g (one-third serving) of white rice per day with the same amount of brown rice intake. In all 3 cohorts, substituting brown rice for white rice was consistently associated with a lower risk of T2D (Figure). In the pooled analysis, each 50-g/d intake of brown rice replacing white rice was associated with an RR (95% CI) of 0.84 (0.79-0.91). We further examined the RR associated with replacing 50 g of white rice intake per day with the same amount of whole grains: the RR (95% CI) was 0.64 (0.58-0.70).

Place holder to copy figure label and caption
Figure.

Pooled fixed-effects relative risk and 95% confidence interval (CI) of type 2 diabetes mellitus from substituting intake of brown rice (A) or whole grains (B), 50 g/d, for the same amount of white rice intake. Bars indicate 95% CIs. Pvalues are P for heterogeneity. Individual associations were controlled for the same set of covariates as for model 3 in Table 3. HPFS, Health Professionals Follow-up Study; NHS, Nurses' Health Study.

Graphic Jump Location

Because ethnicity was associated with both white rice consumption and diabetes risk,28 the observed associations can be a consequence of confounding by ethnicity. However, in secondary analyses when we repeated these associations among white participants only, we found similar results. For example, after nonwhite participants (African American, Hispanic, and Asian) were excluded, the pooled RRs (95% CIs) of T2D associated with white rice intake were 1.00 (0.93-1.07) for 1 to 3 servings per month, 1.04 (0.96-1.13) for 1 serving per week, 1.10 (1.01-1.19) for 2 to 4 servings per week, and 1.19 (1.00-1.41; P for trend <.001) for 5 or more servings per week. The pooled RRs (95% CIs) for brown rice intake levels were 0.94 (0.90-0.99) for 1 to 4 servings per month and 0.87 (0.79-0.96; P for trend = .003) for 2 or more servings per week. Among white participants, the pooled RRs (95% CIs) of T2D were 0.84 (0.78-0.92; P < .001) for replacing 50 g of white rice intake per day with the same amount of brown rice, and 0.64 (0.58-0.71; P < .001) for substituting 50 g of whole grains per day for the same amount of white rice. When we restricted our analysis within minority groups only, although we observed largely similar results, most associations became nonsignificant because of the dramatically diminished power (we identified 624 cases of T2D among 9644 nonwhite participants).

When we used more recent intake of white rice or brown rice instead of the cumulative average in the analyses, the results did not substantially change. For example, the pooled RR (95% CI) was 1.25 (1.08-1.45; P for trend = .001) for white rice intake of 2 or more servings per week vs less than 1 serving per month, 0.90 (0.85-0.95; P < .001) for replacing 50 g of white rice intake per day with the same amount of brown rice, and 0.76 (0.71-0.82; P < .001) for substituting 50 g of whole grains per day for the same amount of white rice. Because rice consumption for most of our study participants was relatively stable over time (data not shown), these results indicated that the cumulative averages could better represent long-term rice consumption because of reduced random within-person measurement errors.24 Finally, we did not find any interactions between rice consumption and other diabetes risk factors, including age, body mass index, and various comorbidities.

In these 3 prospective cohort studies of US men and women, we found that regular consumption of white rice was associated with higher risk of T2D, whereas brown rice intake was associated with lower risk. In addition, our data suggest that replacing white rice intake with the same amount of brown rice or whole grains was associated with a lower risk. These associations were independent of lifestyle and dietary risk factors for T2D, as well as ethnicity.

In Asian populations in which rice is a staple food, higher white rice consumption has been associated with elevated risk of diabetes or metabolic syndrome.6,29,30 For example, white rice consumption was prospectively associated with developing T2D in Chinese women living in Shanghai.6 In addition, in Asian Indians and Japanese, higher intake of refined grains including white rice was associated with metabolic risks in cross-sectional analyses.29,30 In comparison with Asian populations, white rice intake in Western populations was much lower. White rice consumption contributed, on average, less than 2% of total energy intake in our study populations. In contrast, in the aforementioned Chinese female population, white rice consumption accounted for 53.7% of total energy intake (Xiao-Ou Shum MD, MPH, PhD, e-mail communication).6 Likewise, according to the Japanese National Nutrition Survey, white rice accounted for 29% of daily total energy intake in the Japanese population.31 Consumption of rice or food groups consisting of rice in relation to risk of T2D was also evaluated in Western populations, but mixed results were observed.3234 However, brown rice was not separated from white rice or other refined grains in these studies.3234 To our knowledge, the current studies are the first prospective investigations conducted among Western populations that have specifically evaluated white rice and brown rice intake in relation to T2D risk. In our cohorts, only 0.9% (NHS I) to 2.2% (NHS II) of total participants reported having 5 or more servings of white rice per week (≥107 g/d), which was within the lowest reference level (<200 g/d) in the prospective study of Chinese women.6 However, by pooling data from the 3 studies, we detected a significant association for white rice intake. Our data are consistent with the Chinese study, in which white rice intake of 300 g/d or more (equivalent to 2 servings per day in our analysis) was associated with a 78% increased risk of T2D in comparison with intake levels of less than 200 g/d.6

We observed a moderate, inverse association for brown rice intake. Because brown rice consumption levels were rather low in our participants, we could not determine whether brown rice intake at much higher levels is associated with a further reduction of diabetes risk. Nonetheless, we found that substitution of brown rice for white rice was associated with a significantly lower risk of developing diabetes. Consistent with our previous analyses,9,10 we found a significant inverse association between whole grain consumption and diabetes risk. Substitution of whole grains for white rice was more strongly associated with diabetes risk than was the substitution of brown rice. This observation may result from the more reliable estimates of the association with diabetes for whole grains than those for brown rice because of the low overall consumption of brown rice. In addition, whole grains included multiple grains with various nutrient compositions and, thus, possibly various effects on glucose response. For example, whole wheat and barley generate lower glucose response than brown rice: the mean (SD) GI values were 41 (3) for whole wheat, 25 (1) for barley, and 55 (5) for brown rice.2 As a consequence, in comparison with whole wheat and barley, the same amount of brown rice likely bears a higher glycemic load, which is an established risk factor for T2D.35

Depending on the botanical structure, amylase contents, and processing methods, both white rice and brown rice demonstrated a wide variety of GI values,2,3638 which made it difficult to directly compare white rice with brown rice for effects on postprandial glucose response.2 Despite this inconsistency inherent to rice GI values, in general, white rice consumption generates a relatively stronger postprandial glucose response than the same amount of brown rice.2 This notion was corroborated by the observation that isocaloric replacement of white rice with whole grains (66.6%; primarily composed of brown rice and barley) and legume powder (22.2%) significantly decreased postprandial glucose and insulin levels in a randomized clinical trial.39 The high GI of white rice consumption is likely the consequence of disrupting the physical and botanical structure of rice grains during the refining process, in which almost all the bran and some of the germ are removed.40 The other consequence of the refining process includes loss of fiber, vitamins, magnesium and other minerals, lignans, phytoestrogens, and phytic acid,7 many of which may be protective factors for diabetes risk. Intact rice grains contain nearly exclusively insoluble fiber.7 In both observational and experimental studies, insoluble fiber intake was consistently associated with improved insulin sensitivity and decreased risk of developing T2D.4,5,41,42 In addition, higher magnesium intake has been consistently associated with reduced risk of T2D in cohort studies or improved glucose metabolism in clinical trials.4345 The combination of these mechanisms may explain the beneficial effects of replacing white rice with brown rice or other whole grains.

The strengths of the current study include a large sample size, high rates of follow-up, and repeated assessments of dietary and lifestyle information. The consistency of the results across all 3 cohorts indicates that our findings are unlikely to be due to chance. The current study was subject to a few limitations as well. First, our study populations primarily consisted of working health professionals with European ancestry. Although the homogeneity of socioeconomic status helps reduce confounding, the generalizability of the observed associations may be limited to similar populations. However, the biological mechanisms underlying the positive associations observed in both our study populations and the Chinese study6 are likely to be the same in other populations. Second, because diet was assessed by FFQs, some measurement error of rice intake assessment is inevitable. However, the FFQs used in these studies were validated against multiple diet records, and reasonable correlation coefficients between these assessments of rice intake were observed.14 Because we used a prospective study design, any measurement errors of rice intake are independent of study outcome ascertainment and, therefore, are likely to attenuate the associations toward the null. Moreover, we calculated cumulative averages of rice intake to minimize the random measurement errors caused by within-person variation. To minimize the possibility of systemic measurement error incurred by recall bias, we not only excluded participants with a history of major chronic diseases at baseline but also stopped updating dietary intake after participants reported having diagnoses of diseases that might influence their subsequent report of diet. Third, we did not perform oral glucose tolerance tests to confirm diabetes diagnoses because this is infeasible in large cohort studies. However, the supplementary questionnaire that we used for the confirmation of self-reported diabetes diagnoses has been demonstrated to be highly accurate.20,21Finally, although we adjusted for established and potential risk factors for T2D, residual confounding is still possible.

Our data suggest that regular consumption of white rice is associated with an increased risk of T2D, whereas replacement of white rice by brown rice or other whole grains is associated with a lower risk. The current Dietary Guidelines for Americans identifies grains, including rice, as one of the primary sources for carbohydrate intake and recommends that at least half of carbohydrate intake come from whole grains.46 Rice consumption in the US population is increasing.8 However, most rice consumption is refined white rice,8 as seen in our studies. From a public health point of view, replacing refined grains such as white rice by whole grains, including brown rice, should be recommended to facilitate the prevention of T2D.

Correspondence: Qi Sun, MD, ScD, Department of Nutrition, Harvard School of Public Health, 665 Huntington Ave, Boston, MA 02115 (qisun@hsph.harvard.edu).

Accepted for Publication: December 19, 2009.

Author Contributions: Dr Hu had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Sun, Spiegelman, Holmes, and Hu. Acquisition of data: Spiegelman and Hu. Analysis and interpretation of data: Sun, Spiegelman, van Dam, Malik, Willett, and Hu. Drafting of the manuscript: Sun and Hu. Critical revision of the manuscript for important intellectual content: Sun, Spiegelman, van Dam, Holmes, Malik, Willett, and Hu. Statistical analysis: Sun, Spiegelman, van Dam, and Willett. Obtained funding: Spiegelman, Holmes, and Hu. Administrative, technical, and material support: Sun, Malik, and Hu. Study supervision: Spiegelman and Hu.

Financial Disclosure: None reported.

Funding/Support: This study was supported by research grants CA87969, CA055075, CA050385, and DK58845 from the National Institutes of Health. Dr Sun is supported by a postdoctoral fellowship from Unilever Corporate Research.

Role of the Sponsor: The National Institutes of Health had no role in the collection, analysis, and interpretation of the data or in the decision to submit the manuscript for publication.

Miller  GPrakash  ADecker  E Whole-Grain Foods in Health and Disease.  St Paul, MN American Association of Cereal Chemists2002;
Foster-Powell  KHolt  SHBrand-Miller  JC International table of glycemic index and glycemic load values: 2002. Am J Clin Nutr 2002;76 (1) 5- 56
PubMed
Schulze  MBLiu  SRimm  EBManson  JEWillett  WCHu  FB Glycemic index, glycemic load, and dietary fiber intake and incidence of type 2 diabetes in younger and middle-aged women. Am J Clin Nutr 2004;80 (2) 348- 356
PubMed
Salmerón  JAscherio  ARimm  EB  et al.  Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care 1997;20 (4) 545- 550
PubMed
Salmerón  JManson  JEStampfer  MJColditz  GAWing  ALWillett  WC Dietary fiber, glycemic load, and risk of non–insulin-dependent diabetes mellitus in women. JAMA 1997;277 (6) 472- 477
PubMed
Villegas  RLiu  SGao  YT  et al.  Prospective study of dietary carbohydrates, glycemic index, glycemic load, and incidence of type 2 diabetes mellitus in middle-aged Chinese women. Arch Intern Med 2007;167 (21) 2310- 2316
PubMed
Slavin  JLMartini  MCJacobs  DR  JrMarquart  L Plausible mechanisms for the protectiveness of whole grains. Am J Clin Nutr 1999;70 (3) ((suppl)) 459S- 463S
PubMed
Economic Research Service, US Department of Agriculture, Data sets. http://www.ers.usda.gov/Data/. Accessed June 16, 2009
de Munter  JSHu  FBSpiegelman  DFranz  Mvan Dam  RM Whole grain, bran, and germ intake and risk of type 2 diabetes: a prospective cohort study and systematic review. PLoS Med 2007;4 (8) e261
PubMed10.1371/journal.pmed.0040261
Fung  TTHu  FBPereira  MA  et al.  Whole-grain intake and the risk of type 2 diabetes: a prospective study in men. Am J Clin Nutr 2002;76 (3) 535- 540
PubMed
Wolf  AMHunter  DJColditz  GA  et al.  Reproducibility and validity of a self-administered physical activity questionnaire. Int J Epidemiol 1994;23 (5) 991- 999
PubMed
Belanger  CFHennekens  CHRosner  BSpeizer  FE The Nurses' Health Study. Am J Nurs 1978;78 (6) 1039- 1040
PubMed
Rimm  EBStampfer  MJColditz  GAGiovannucci  EWillett  WC Effectiveness of various mailing strategies among nonrespondents in a prospective cohort study. Am J Epidemiol 1990;131 (6) 1068- 1071
PubMed
Feskanich  DRimm  EBGiovannucci  EL  et al.  Reproducibility and validity of food intake measurements from a semiquantitative food frequency questionnaire. J Am Diet Assoc 1993;93 (7) 790- 796
PubMed
Rimm  EBGiovannucci  ELStampfer  MJColditz  GALitin  LBWillett  WC Reproducibility and validity of an expanded self-administered semiquantitative food frequency questionnaire among male health professionals. Am J Epidemiol 1992;135 (10) 1114- 1136
PubMed
Willett  WCSampson  LStampfer  MJ  et al.  Reproducibility and validity of a semiquantitative food frequency questionnaire. Am J Epidemiol 1985;122 (1) 51- 65
PubMed
Salvini  SHunter  DJSampson  L  et al.  Food-based validation of a dietary questionnaire: the effects of week-to-week variation in food consumption. Int J Epidemiol 1989;18 (4) 858- 867
PubMed
National Diabetes Data Group, Classification and diagnosis of diabetes mellitus and other categories of glucose intolerance. Diabetes 1979;28 (12) 1039- 1057
PubMed
Expert Committee on the Diagnosis and Classification of Diabetes Mellitus, Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 1997;20 (7) 1183- 1197
PubMed
Manson  JERimm  EBStampfer  MJ  et al.  Physical activity and incidence of non–insulin-dependent diabetes mellitus in women. Lancet 1991;338 (8770) 774- 778
PubMed
Hu  FBLeitzmann  MFStampfer  MJColditz  GAWillett  WCRimm  EB Physical activity and television watching in relation to risk for type 2 diabetes mellitus in men. Arch Intern Med 2001;161 (12) 1542- 1548
PubMed
Stampfer  MJWillett  WCSpeizer  FE  et al.  Test of the National Death Index. Am J Epidemiol 1984;119 (5) 837- 839
PubMed
Cox  DROakes  D Analysis of Survival Data.  London, England Chapman and Hall1984;
Hu  FBStampfer  MJRimm  E  et al.  Dietary fat and coronary heart disease: a comparison of approaches for adjusting for total energy intake and modeling repeated dietary measurements. Am J Epidemiol 1999;149 (6) 531- 540
PubMed
Sun  Qvan Dam  RMWillett  WCHu  FB Prospective study of zinc intake and risk of type 2 diabetes in women. Diabetes Care 2009;32 (4) 629- 634
PubMed
Halton  TLWillett  WCLiu  SManson  JEStampfer  MJHu  FB Potato and French fry consumption and risk of type 2 diabetes in women. Am J Clin Nutr 2006;83 (2) 284- 290
PubMed
Higgins  JPThompson  SG Quantifying heterogeneity in a meta-analysis. Stat Med 2002;21 (11) 1539- 1558
PubMed
Shai  IJiang  RManson  JE  et al.  Ethnicity, obesity, and risk of type 2 diabetes in women: a 20-year follow-up study. Diabetes Care 2006;29 (7) 1585- 1590
PubMed
Murakami  KSasaki  STakahashi  Y  et al.  Dietary glycemic index and load in relation to metabolic risk factors in Japanese female farmers with traditional dietary habits. Am J Clin Nutr 2006;83 (5) 1161- 1169
PubMed
Radhika  GVan Dam  RMSudha  VGanesan  AMohan  V Refined grain consumption and the metabolic syndrome in urban Asian Indians (Chennai Urban Rural Epidemiology Study 57). Metabolism 2009;58 (5) 675- 681
PubMed
Sugiyama  MTang  ACWakaki  YKoyama  W Glycemic index of single and mixed meal foods among common Japanese foods with white rice as a reference food. Eur J Clin Nutr 2003;57 (6) 743- 752
PubMed
Williams  DEWareham  NJCox  BDByrne  CDHales  CNDay  NE Frequent salad vegetable consumption is associated with a reduction in the risk of diabetes mellitus. J Clin Epidemiol 1999;52 (4) 329- 335
PubMed
Hodge  AMEnglish  DRO’Dea  KGiles  GG Glycemic index and dietary fiber and the risk of type 2 diabetes. Diabetes Care 2004;27 (11) 2701- 2706
PubMed
Liu  SManson  JEStampfer  MJ  et al.  A prospective study of whole-grain intake and risk of type 2 diabetes mellitus in US women. Am J Public Health 2000;90 (9) 1409- 1415
PubMed
Barclay  AWPetocz  PMcMillan-Price  J  et al.  Glycemic index, glycemic load, and chronic disease risk: a meta-analysis of observational studies. Am J Clin Nutr 2008;87 (3) 627- 637
PubMed
Larsen  HNChristensen  CRasmussen  OW  et al.  Influence of parboiling and physico-chemical characteristics of rice on the glycaemic index in non–insulin-dependent diabetic subjects. Eur J Clin Nutr 1996;50 (1) 22- 27
PubMed
Larsen  HNRasmussen  OWRasmussen  PH  et al.  Glycaemic index of parboiled rice depends on the severity of processing: study in type 2 diabetic subjects. Eur J Clin Nutr 2000;54 (5) 380- 385
PubMed
Miller  JBPang  EBramall  L Rice: a high or low glycemic index food? Am J Clin Nutr 1992;56 (6) 1034- 1036
PubMed
Jang  YLee  JHKim  OYPark  HYLee  SY Consumption of whole grain and legume powder reduces insulin demand, lipid peroxidation, and plasma homocysteine concentrations in patients with coronary artery disease: randomized controlled clinical trial. Arterioscler Thromb Vasc Biol 2001;21 (12) 2065- 2071
PubMed
Björck  IGranfeldt  YLiljeberg  HTovar  JAsp  NG Food properties affecting the digestion and absorption of carbohydrates. Am J Clin Nutr 1994;59 (3) ((suppl)) 699S- 705S
PubMed
Meyer  KAKushi  LHJacobs  DR  JrSlavin  JSellers  TAFolsom  AR Carbohydrates, dietary fiber, and incident type 2 diabetes in older women. Am J Clin Nutr 2000;71 (4) 921- 930
PubMed
Weickert  MOMohlig  MSchofl  C  et al.  Cereal fiber improves whole-body insulin sensitivity in overweight and obese women. Diabetes Care 2006;29 (4) 775- 780
PubMed
van Dam  RMHu  FBRosenberg  LKrishnan  SPalmer  JR Dietary calcium and magnesium, major food sources, and risk of type 2 diabetes in U.S. black women. Diabetes Care 2006;29 (10) 2238- 2243
PubMed
Schulze  MBSchulz  MHeidemann  CSchienkiewitz  AHoffmann  KBoeing  H Fiber and magnesium intake and incidence of type 2 diabetes: a prospective study and meta-analysis. Arch Intern Med 2007;167 (9) 956- 965
PubMed
Song  YHe  KLevitan  EBManson  JELiu  S Effects of oral magnesium supplementation on glycaemic control in type 2 diabetes: a meta-analysis of randomized double-blind controlled trials. Diabet Med 2006;23 (10) 1050- 1056
PubMed
US Dept of Health and Human Services and US Dept of Agriculture, Dietary guidelines for Americans, 2005. 6th ed.http://www.health.gov/dietaryguidelines/dga2005/document/. Accessed June 16, 2009

Figures

Place holder to copy figure label and caption
Figure.

Pooled fixed-effects relative risk and 95% confidence interval (CI) of type 2 diabetes mellitus from substituting intake of brown rice (A) or whole grains (B), 50 g/d, for the same amount of white rice intake. Bars indicate 95% CIs. Pvalues are P for heterogeneity. Individual associations were controlled for the same set of covariates as for model 3 in Table 3. HPFS, Health Professionals Follow-up Study; NHS, Nurses' Health Study.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Baseline Characteristics of Study Participants by Levels of White Rice and Brown Rice Intake
Table Graphic Jump LocationTable 2. Risk of Type 2 Diabetes Mellitus According to White Rice Intake in the HPFS, NHS I, and NHS II
Table Graphic Jump LocationTable 3. Risk of Type 2 Diabetes Mellitus According to Brown Rice Intake in the HPFS, NHS I, and NHS II
Table Graphic Jump LocationTable 4. Risk of Type 2 Diabetes Mellitus According to Whole Grain, Bran, or Germ Intake in the HPFS, NHS I, and NHS II

References

Miller  GPrakash  ADecker  E Whole-Grain Foods in Health and Disease.  St Paul, MN American Association of Cereal Chemists2002;
Foster-Powell  KHolt  SHBrand-Miller  JC International table of glycemic index and glycemic load values: 2002. Am J Clin Nutr 2002;76 (1) 5- 56
PubMed
Schulze  MBLiu  SRimm  EBManson  JEWillett  WCHu  FB Glycemic index, glycemic load, and dietary fiber intake and incidence of type 2 diabetes in younger and middle-aged women. Am J Clin Nutr 2004;80 (2) 348- 356
PubMed
Salmerón  JAscherio  ARimm  EB  et al.  Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care 1997;20 (4) 545- 550
PubMed
Salmerón  JManson  JEStampfer  MJColditz  GAWing  ALWillett  WC Dietary fiber, glycemic load, and risk of non–insulin-dependent diabetes mellitus in women. JAMA 1997;277 (6) 472- 477
PubMed
Villegas  RLiu  SGao  YT  et al.  Prospective study of dietary carbohydrates, glycemic index, glycemic load, and incidence of type 2 diabetes mellitus in middle-aged Chinese women. Arch Intern Med 2007;167 (21) 2310- 2316
PubMed
Slavin  JLMartini  MCJacobs  DR  JrMarquart  L Plausible mechanisms for the protectiveness of whole grains. Am J Clin Nutr 1999;70 (3) ((suppl)) 459S- 463S
PubMed
Economic Research Service, US Department of Agriculture, Data sets. http://www.ers.usda.gov/Data/. Accessed June 16, 2009
de Munter  JSHu  FBSpiegelman  DFranz  Mvan Dam  RM Whole grain, bran, and germ intake and risk of type 2 diabetes: a prospective cohort study and systematic review. PLoS Med 2007;4 (8) e261
PubMed10.1371/journal.pmed.0040261
Fung  TTHu  FBPereira  MA  et al.  Whole-grain intake and the risk of type 2 diabetes: a prospective study in men. Am J Clin Nutr 2002;76 (3) 535- 540
PubMed
Wolf  AMHunter  DJColditz  GA  et al.  Reproducibility and validity of a self-administered physical activity questionnaire. Int J Epidemiol 1994;23 (5) 991- 999
PubMed
Belanger  CFHennekens  CHRosner  BSpeizer  FE The Nurses' Health Study. Am J Nurs 1978;78 (6) 1039- 1040
PubMed
Rimm  EBStampfer  MJColditz  GAGiovannucci  EWillett  WC Effectiveness of various mailing strategies among nonrespondents in a prospective cohort study. Am J Epidemiol 1990;131 (6) 1068- 1071
PubMed
Feskanich  DRimm  EBGiovannucci  EL  et al.  Reproducibility and validity of food intake measurements from a semiquantitative food frequency questionnaire. J Am Diet Assoc 1993;93 (7) 790- 796
PubMed
Rimm  EBGiovannucci  ELStampfer  MJColditz  GALitin  LBWillett  WC Reproducibility and validity of an expanded self-administered semiquantitative food frequency questionnaire among male health professionals. Am J Epidemiol 1992;135 (10) 1114- 1136
PubMed
Willett  WCSampson  LStampfer  MJ  et al.  Reproducibility and validity of a semiquantitative food frequency questionnaire. Am J Epidemiol 1985;122 (1) 51- 65
PubMed
Salvini  SHunter  DJSampson  L  et al.  Food-based validation of a dietary questionnaire: the effects of week-to-week variation in food consumption. Int J Epidemiol 1989;18 (4) 858- 867
PubMed
National Diabetes Data Group, Classification and diagnosis of diabetes mellitus and other categories of glucose intolerance. Diabetes 1979;28 (12) 1039- 1057
PubMed
Expert Committee on the Diagnosis and Classification of Diabetes Mellitus, Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 1997;20 (7) 1183- 1197
PubMed
Manson  JERimm  EBStampfer  MJ  et al.  Physical activity and incidence of non–insulin-dependent diabetes mellitus in women. Lancet 1991;338 (8770) 774- 778
PubMed
Hu  FBLeitzmann  MFStampfer  MJColditz  GAWillett  WCRimm  EB Physical activity and television watching in relation to risk for type 2 diabetes mellitus in men. Arch Intern Med 2001;161 (12) 1542- 1548
PubMed
Stampfer  MJWillett  WCSpeizer  FE  et al.  Test of the National Death Index. Am J Epidemiol 1984;119 (5) 837- 839
PubMed
Cox  DROakes  D Analysis of Survival Data.  London, England Chapman and Hall1984;
Hu  FBStampfer  MJRimm  E  et al.  Dietary fat and coronary heart disease: a comparison of approaches for adjusting for total energy intake and modeling repeated dietary measurements. Am J Epidemiol 1999;149 (6) 531- 540
PubMed
Sun  Qvan Dam  RMWillett  WCHu  FB Prospective study of zinc intake and risk of type 2 diabetes in women. Diabetes Care 2009;32 (4) 629- 634
PubMed
Halton  TLWillett  WCLiu  SManson  JEStampfer  MJHu  FB Potato and French fry consumption and risk of type 2 diabetes in women. Am J Clin Nutr 2006;83 (2) 284- 290
PubMed
Higgins  JPThompson  SG Quantifying heterogeneity in a meta-analysis. Stat Med 2002;21 (11) 1539- 1558
PubMed
Shai  IJiang  RManson  JE  et al.  Ethnicity, obesity, and risk of type 2 diabetes in women: a 20-year follow-up study. Diabetes Care 2006;29 (7) 1585- 1590
PubMed
Murakami  KSasaki  STakahashi  Y  et al.  Dietary glycemic index and load in relation to metabolic risk factors in Japanese female farmers with traditional dietary habits. Am J Clin Nutr 2006;83 (5) 1161- 1169
PubMed
Radhika  GVan Dam  RMSudha  VGanesan  AMohan  V Refined grain consumption and the metabolic syndrome in urban Asian Indians (Chennai Urban Rural Epidemiology Study 57). Metabolism 2009;58 (5) 675- 681
PubMed
Sugiyama  MTang  ACWakaki  YKoyama  W Glycemic index of single and mixed meal foods among common Japanese foods with white rice as a reference food. Eur J Clin Nutr 2003;57 (6) 743- 752
PubMed
Williams  DEWareham  NJCox  BDByrne  CDHales  CNDay  NE Frequent salad vegetable consumption is associated with a reduction in the risk of diabetes mellitus. J Clin Epidemiol 1999;52 (4) 329- 335
PubMed
Hodge  AMEnglish  DRO’Dea  KGiles  GG Glycemic index and dietary fiber and the risk of type 2 diabetes. Diabetes Care 2004;27 (11) 2701- 2706
PubMed
Liu  SManson  JEStampfer  MJ  et al.  A prospective study of whole-grain intake and risk of type 2 diabetes mellitus in US women. Am J Public Health 2000;90 (9) 1409- 1415
PubMed
Barclay  AWPetocz  PMcMillan-Price  J  et al.  Glycemic index, glycemic load, and chronic disease risk: a meta-analysis of observational studies. Am J Clin Nutr 2008;87 (3) 627- 637
PubMed
Larsen  HNChristensen  CRasmussen  OW  et al.  Influence of parboiling and physico-chemical characteristics of rice on the glycaemic index in non–insulin-dependent diabetic subjects. Eur J Clin Nutr 1996;50 (1) 22- 27
PubMed
Larsen  HNRasmussen  OWRasmussen  PH  et al.  Glycaemic index of parboiled rice depends on the severity of processing: study in type 2 diabetic subjects. Eur J Clin Nutr 2000;54 (5) 380- 385
PubMed
Miller  JBPang  EBramall  L Rice: a high or low glycemic index food? Am J Clin Nutr 1992;56 (6) 1034- 1036
PubMed
Jang  YLee  JHKim  OYPark  HYLee  SY Consumption of whole grain and legume powder reduces insulin demand, lipid peroxidation, and plasma homocysteine concentrations in patients with coronary artery disease: randomized controlled clinical trial. Arterioscler Thromb Vasc Biol 2001;21 (12) 2065- 2071
PubMed
Björck  IGranfeldt  YLiljeberg  HTovar  JAsp  NG Food properties affecting the digestion and absorption of carbohydrates. Am J Clin Nutr 1994;59 (3) ((suppl)) 699S- 705S
PubMed
Meyer  KAKushi  LHJacobs  DR  JrSlavin  JSellers  TAFolsom  AR Carbohydrates, dietary fiber, and incident type 2 diabetes in older women. Am J Clin Nutr 2000;71 (4) 921- 930
PubMed
Weickert  MOMohlig  MSchofl  C  et al.  Cereal fiber improves whole-body insulin sensitivity in overweight and obese women. Diabetes Care 2006;29 (4) 775- 780
PubMed
van Dam  RMHu  FBRosenberg  LKrishnan  SPalmer  JR Dietary calcium and magnesium, major food sources, and risk of type 2 diabetes in U.S. black women. Diabetes Care 2006;29 (10) 2238- 2243
PubMed
Schulze  MBSchulz  MHeidemann  CSchienkiewitz  AHoffmann  KBoeing  H Fiber and magnesium intake and incidence of type 2 diabetes: a prospective study and meta-analysis. Arch Intern Med 2007;167 (9) 956- 965
PubMed
Song  YHe  KLevitan  EBManson  JELiu  S Effects of oral magnesium supplementation on glycaemic control in type 2 diabetes: a meta-analysis of randomized double-blind controlled trials. Diabet Med 2006;23 (10) 1050- 1056
PubMed
US Dept of Health and Human Services and US Dept of Agriculture, Dietary guidelines for Americans, 2005. 6th ed.http://www.health.gov/dietaryguidelines/dga2005/document/. Accessed June 16, 2009

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