White Rice Consumption and Risk of Type 2 Diabetes Meta-analysis and Systematic Review
White rice consumption and risk of type two diabetes: meta-analysis and systematic review
Emily A Hu
1Department of Nutrition, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, Us
An Pan
1Department of Diet, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA
Vasanti Malik
1Department of Nutrition, Harvard School of Public Wellness, 655 Huntington Avenue, Boston, MA 02115, The states
Qi Sun
1Department of Nutrition, Harvard Schoolhouse of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA
2Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston
- Supplementary Materials
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Supplementary figures
GUID: DEB0E9D4-8FB2-4D05-8A0B-DD0A47E1502B
Supplementary table
GUID: 231A45A4-041C-4D95-8879-5E7298716472
Abstract
Objectives To summarise evidence on the association betwixt white rice consumption and take a chance of type 2 diabetes and to quantify the potential dose-response relation.
Pattern Meta-assay of prospective cohort studies.
Data sources Searches of Medline and Embase databases for articles published upwards to January 2012 using keywords that included both rice intake and diabetes; further searches of references of included original studies.
Written report option Included studies were prospective cohort studies that reported hazard estimates for blazon 2 diabetes by rice intake levels.
Data synthesis Relative risks were pooled using a random effects model; dose-response relations were evaluated using data from all rice intake categories in each report.
Results Four articles were identified that included 7 distinct prospective accomplice analyses in Asian and Western populations for this study. A total of 13 284 incident cases of type two diabetes were ascertained amidst 352 384 participants with follow-up periods ranging from iv to 22 years. Asian (Chinese and Japanese) populations had much college white rice consumption levels than did Western populations (average intake levels were iii to 4 servings/day versus ane to 2 servings/week). The pooled relative risk was ane.55 (95% confidence interval 1.20 to ii.01) comparison the highest with the lowest category of white rice intake in Asian populations, whereas the respective relative risk was 1.12 (0.94 to 1.33) in Western populations (P for interaction=0.038). In the total population, the dose-response meta-analysis indicated that for each serving per day increment of white rice intake, the relative risk of blazon 2 diabetes was 1.11 (1.08 to ane.14) (P for linear trend<0.001).
Determination Higher consumption of white rice is associated with a significantly increased risk of type 2 diabetes, especially in Asian (Chinese and Japanese) populations.
Introduction
Humans have a long history of cultivating rice crops; rice was starting time domesticated approximately 8000 to 9000 years ago by people living in the region of the Yangtze River valley in Prc.1 ii 3 Rice is now grown worldwide and provides food for more than half of the globe's population, especially those living in some of the nigh populous countries, such every bit Mainland china, India, and Japan. Polished rice or white rice, which primarily consists of starch, is produced through a serial of mechanised processes including hulling and milling,4 and it is the predominant type of rice consumed worldwide.5 6 7 Although the glycaemic alphabetize value of a specific white rice diversity depends on the degree of processing, cooking time, and amylose content, the glycaemic index values of white rice are higher on average than those of whole grains.8 For example, the mean glycaemic index values were 64 (SD 7) for white rice, 55 (5) for brown rice, 41 (three) for whole wheat, and 25 (1) for barley in a previous meta-analysis.8 In addition, white rice is the primary contributor to dietary glycaemic load for populations that consume rice equally a staple food.5 7
In big scale man observational studies among various populations, diets with a loftier glycaemic index or glycaemic load were associated with increased risk of developing blazon 2 diabetes.vii 9 10 11 A significant positive association between white rice consumption and risk of diabetes was observed among ii cohorts of Chinese and Japanese women,v 7 although the clan was non meaning for Japanese men.5 Two investigations in Western populations with much lower consumption levels than Asian populations too generated mixed results.12 xiii These studies were heterogeneous with respect to sample size, white rice intake levels, and other characteristics that may contribute to inconsistencies in the literature. In addition, whether any dose-response relation exists between white rice consumption and risk of diabetes is unknown. Therefore, we did a meta-assay on all published prospective cohort studies evaluating white rice intake and incidence of type ii diabetes and quantified dose-response relations between intake of white rice and risk of blazon 2 diabetes.
Methods
Search strategy
We did a literature search (up to January 2012) of Medline and Embase for prospective cohort studies examining the association betwixt rice intake and take a chance of type 2 diabetes. The search terms were ("Diabetes Mellitus"[Mesh] OR "diabetes"[All Fields]) AND ("Oryza sativa"[Mesh] OR "rice" OR "grain") for Medline and ('diabetes'/exp OR diabetes) AND ('rice'/exp OR rice OR 'grain'/exp OR grain) for Embase. Nosotros supplemented this search with a transmission search of references cited by selected articles. One investigator (QS) did this literature search.
Study selection
We practical the post-obit inclusion criteria: prospective cohort study, patients with self reported prevalent diabetes excluded at baseline, and signal estimates of relative risk with 95% confidence intervals or standard errors available or derivable. Nosotros excluded animal studies, clinical trials, cross sectional studies, case-control studies, reviews, commentaries, letters, and studies that examined other associations. We also practical a criterion of study quality that all included accomplice studies should have a loss to follow-upward rate beneath 20%. Two investigators (EAH and AP) independently screened all studies by title or abstruse and then by a full text evaluation. Any discrepancy betwixt the two authors was solved by discussion with the senior investigator (QS).
Data extraction
We extracted the following information from each study: study's characteristics (study proper name, authors, yr of publication, journal, report location, elapsing of follow-up, person fourth dimension, and number of participants and incident cases), participants' characteristics (historic period and sexual practice), exposure (rice intake levels for each category) and dietary assessment method, reproducibility and validity of assessment method, outcome (type ii diabetes) observation, and analysis strategy (statistical models, covariates included in the models, and chance estimates in each category). For studies that reported rice intake as servings per week or day, we converted it to grams per day by assuming that each serving was equivalent to 158 chiliad of cooked rice. To convert raw rice intake levels to cooked rice consumption levels for Villegas et al's study, we multiplied raw intake levels by a gene of 2.5.7
2 investigators (EAH and AP) extracted data independently, and whatever discrepancies were resolved by give-and-take. For two studies that expressed information separately for men and women or included information from multiple cohorts,5 xiii we considered the analysis for each sex or accomplice as an independent report and extracted data separately. Equally per our asking, Hodge et al provided the number of cases and person years for each rice intake category in their study and confirmed that white rice accounted for the vast majority (approximately 95%) of total rice consumption in their study (Allison Hodge, electronic mail communication).12 To assess the quality of included studies, we derived a score that summarised 15 aspects of each study, including study design, response rate, follow-up rate, follow-up time, exposure and effect measurements, and statistical analysis (supplementary table A).
Statistical analysis
Hazard ratios (equivalent to relative risks in cohort studies) were used as the common measure out of association in all studies except for those by Nanri et al and Hodge et al, which used logistic regression to model the association of involvement. Because of the very low incidence of type two diabetes in these two studies (five year risk was 1.ix% for Nanri et al'south study and 1.2% for Hodge et al's report), nosotros considered odds ratios to be relatively accurate estimates of the true relative risks. We further derived estimates of person time for Nanri et al'south study by multiplying the number of participants by the follow-up time for each category of rice intake. We pooled all relative risks by using a random furnishings model comparing extreme categories of intake and set study weights to be equal to the inverse variance of each study's effect guess. Nosotros produced wood plots to assess the multivariate adapted relative risks and respective 95% conviction intervals visually across studies. We evaluated heterogeneity of relative risks across studies past using the Cochrane Q statistic (we considered P<0.05 to be indicative of statistically significant heterogeneity) and the I2 statistic. Nosotros did stratified analyses according to ethnicity (Asian versus Western). To evaluate potential interactions betwixt rice intake and ethnicity, we used Altman et al'due south method to evaluate whether the pooled relative risks differed between different ethnic groups.14 We too fitted a fixed effects model to examine the betwixt group heterogeneity and used the P value for heterogeneity to evaluate the interactions. We used Begg funnel plots and Egger'due south tests to assess potential publication bias.15
To evaluate a potential non-linear dose-response relation, we first used a restricted cubic spline regression model (Stata RC_SPLINE control) with three knots to create spline variables that we afterwards used in our assay to derive the generalised least squares trend estimation of pooled dose-response data (Stata GLST command).16 17 We then fitted another regression model without the spline terms. Lastly, we used the likelihood ratio examination to examine the significance of whatever non-linearity by comparing the model with the linear term but and the model with both the linear and the cubic spline terms. This assay used data from the relative risks and 95% confidence intervals, number of cases and person years, and median/mean of rice intake levels for each comparison grouping. Median intake levels for each rice consumption category were available in Nanri et al's study.v For all other studies that did not provide such data, we calculated the boilerplate of the two extreme values of each comparing group to determine mean rice intake levels. For the highest consumption category, nosotros assumed that the average consumption level was the cut-off signal plus a 25% increase, which was largely consistent with Nanri et al's study. Because of unstable estimators in a random effects cubic spline model equally a outcome of lack of power, nosotros used a fixed effects model to evaluate the dose-response relation. We calculated absolute risk differences as groundwork incidence rate×(relative risk−i).
We used Stata statistical software version 11.0 for all analyses. P values were two sided with a significance level of 0.05.
Results
Literature search
Figure i shows results from the literature search and study choice process. We identified 825 manufactures from the Medline database and 2453 articles from the Embase database. After exclusion of duplicate records and studies that did non meet our inclusion criteria, 36 articles remained, and we further evaluated the full texts of these publications. Of these, we excluded v studies considering they did not carve up rice from other carbohydrate sources, 16 because no original information could be extracted (reviews, letters, or cantankerous sectional studies), 10 that we accounted irrelevant, and ane that had a loss to follow-upwards charge per unit of 31.7%.18 Finally, four studies met the inclusion criteria and were included in the meta-analysis. A manual search of references cited by these studies did not yield new eligible articles. Amongst these four studies, Nanri et al'south written report examined men and women separately and Sun et al's study included data from iii independent cohorts. Therefore, we included vii comparisons in the meta-assay.
Fig 1 Literature search and study selection
Study characteristics
Tables 1 and 2 bear witness the characteristics of the included studies. All four studies were prospective cohort studies in participants who were free of cocky reported diabetes at baseline (total north=352 384). Hodge et al's report farther excluded any patients with diabetes whose engagement of diagnosis was earlier the study baseline even though they did not report having a diagnosis of diabetes at baseline interview. Amongst the participants, 13 284 incident cases of diabetes occurred during follow-up periods ranging from 4 to 22 years. 2 studies were done in Asian populations (China and Japan) and the other 2 studies in Western populations (the U.s. and Commonwealth of australia). Average rice intake levels varied dramatically across studies. For instance, in the Chinese study the mean intake level of cooked rice was approximately iv servings (625 one thousand) per day, whereas in the two studies done in the United States and Australia about (98% for the United states study and 71% for the Australian study) participants consumed less than five servings a week. In all studies, dietary intake was assessed by food frequency questionnaires, which were validated against multiple day nutrition records or 24 hour recalls. Moderate correlation coefficients of dietary intake of rice take been constitute (ranged from 0.53 to 0.66), supporting reasonably good validity of rice intake assessment in these studies. Results from our assessment of report quality showed that most studies achieved a score of 12 or above (the maximum score was 15) except for Hodge et al's written report, which accomplished a score of 7 (supplementary table A).
Table 1
Characteristics of prospective studies of white rice intake in relation to incident type 2 diabetes: participants, follow-upwardly, and exposures
| Writer | Study participants | Follow-up flow and person time | Exposure and cess method |
|---|---|---|---|
| Hodge et al 2004 | Melbourne Collaborative Cohort Study: total=31 641; cases=365; 41.1% male person; age 40-69 years; Melbourne, Commonwealth of australia | Follow-upwards four years; 129 190 person years* | Cooked rice assessed by FFQ consisting of 121 food items. Reproducibility and validity of rice intake assessments: NA |
| Villegas et al 2007 | Shanghai Women's Health Study: total=64 191; cases=1608; 100% female; age twoscore-70 years; Shanghai, China | Follow-upwards v years; 297 755 person years | Raw rice assessed past FFQ consisting of 77 food items. Validation written report for rice intake assessments: 191 Chinese women; correlation coefficient (r) for reproducibility 0.49 between two FFQs administered 1 year apart; r for validity 0.66 betwixt second FFQ and 24 hour recall assessments |
| Dominicus et al 2010 | Health Professionals Follow-up Study: total=39 765; cases=2648; 100% male; age 32-87 years; U.s.a. | Follow-up 20 years; 702 920 person years | Cooked rice assessed by FFQ consisting of 116-131 food items. Validation study for rice intake assessments: 127 Health Professionals Follow-upwardly Report participants; r for reproducibility 0.52 betwixt 2 FFQs administered 1 year autonomously; r for validity 0.53 between second FFQ and diet tape assessments |
| Sun et al 2010 | Nurses' Health Study: total=69 120; cases=5500; 100% female person; age 37-65 years; U.s.a. | Follow-up 22 years; 1 404 373 person years | Same as in a higher place |
| Sun et al 2010 | Nurses' Wellness Written report Two: total=88 343; cases=2359; 100% female; age 26-45 years; U.s.a. | Follow-upward 14 years; 1 210 903 person years | Same as above |
| Nanri et al 2010 | Nippon Public Health Center-based Prospective Study: total=25 666; cases=625; 100% male; historic period 45-75 years; Japan | Follow-upwards v years; 128 330 person years† | Cooked rice assessed by FFQ consisting of 147 food items. Validation study for rice intake assessments: No of participants unknown; r for reproducibility 0.69 between 2 FFQs administered ane year autonomously; r for validity 0.55 between FFQ and nutrition tape assessments |
| Nanri et al 2010 | Japan Public Health Centre-based Prospective Report: total=33 622; cases=478; 100% female person; age 45-75 years; Japan | Follow-up 5 years; 168 110 person years† | Same equally above |
Table ii
Characteristics of prospective studies of white rice intake in relation to incident type 2 diabetes: outcomes, relative risks, and covariates
| Study | Report outcome and observation | Comparison categories and corresponding relative gamble (95% CI) | Covariates in fully adjusted model |
|---|---|---|---|
| Hodge et al 2004 | Type two diabetes identified through self reports; 83% (303/365) cases confirmed by medical practitioners | <23 thousand/twenty-four hour period*†: 1.0 (referent); 23-32 one thousand/day: 0.77 (0.56 to 1.07); 33-55 g/day: 0.91 (0.67 to 1.22); ≥56 yard/day: 0.93 (0.68 to 1.27) | Age, sexual practice, state of nascency, physical action, family history of diabetes, booze, total energy intake, teaching, 5 year weight change, body mass index, and waist:hip ratio |
| Villegas et al 2007 | Type 2 diabetes identified through self reports; American Diabetes Association 1997 diagnostic criteria | <500 g/day‡: ane.0 (referent); 500-622 g/solar day: 1.04 (0.86 to i.25); 623-749 m/day: 1.29 (1.08 to 1.54); ≥750 k/day: 1.78 (one.48 to 2.15) | Age, body mass alphabetize, waist:hip ratio, smoking condition, alcohol consumption, physical activity, income level, education level, occupation, diagnosis of hypertension, and total energy |
| Lord's day et al 2010; Health Professionals Follow-upwards Study | Type 2 diabetes identified through self reports and confirmed by validated supplementary questionnaire; National Diabetes Data Group (earlier 1998) and American Diabetes Association 1997 (after 1998) diagnostic criteria | <5.3 g/day†: 1.0 (referent); v.3-fifteen.8 g/solar day: 1.09 (0.96 to ane.24); xv.ix-45.0 g/day: i.07 (0.93 to i.23); 45.1-112.9 m/day: 1.30 (ane.12 to ane.50); ≥112.9 g/solar day: one.02 (0.77 to 1.34) | Age; ethnicity (white, African-American, Hispanic, and Asian); torso mass index; smoking status; booze intake; multivitamin use; physical activity; family history of diabetes; total energy; intakes of red meat, fruits and vegetables, whole grains, and coffee |
| Sun et al 2010; Nurses' Health Written report | Aforementioned equally above | <5.3 g/day†: 1.0 (referent); v.3-15.8 g/twenty-four hours: 1.00 (0.90 to 1.11); 15.9-45.0 m/day: one.07 (0.96 to 1.20); 45.1-112.9 thou/mean solar day: 1.09 (0.97 to i.23); ≥112.9 yard/day: 1.eleven (0.87 to 1.43) | Aforementioned as above, plus further adjustments for postmenopausal status, hormone use, and oral contraceptive apply |
| Sunday et al 2010; Nurses' Wellness Study II | Same as to a higher place | <5.3 g/24-hour interval†: one.0 (referent); 5.three-15.8 grand/day: 0.93 (0.81 to ane.07); 15.9-45.0 g/day: 0.94 (0.81 to 1.x); 45.1-112.9 g/day: 0.95 (0.81 to 1.11); ≥112.9 g/twenty-four hours: i.40 (1.09 to 1.eighty) | Aforementioned as above |
| Nanri et al 2010 (males) | Type 2 diabetes identified through self reports and confirmed by medical records; Japan Diabetes Society 1982 diagnostic criteria | 0-315 k/day: 1.00 (referent); 315-420 m/day: one.24 (1.00 to 1.55); 420-560 yard/24-hour interval: i.25 (0.93 to one.67); >560 chiliad/mean solar day: i.19 (0.85 to 1.68) | Age; study area; smoking status; alcohol consumption; family unit history of diabetes mellitus; total physical activity; history of hypertension; occupation; total energy intake; intakes of calcium, magnesium, fibre, fruit, vegetables, fish, coffee, staff of life, and noodles; and body mass alphabetize |
| Nanri et al 2010 (females) | Same as above | 0-278 g/twenty-four hours: 1.00 (referent); 280-417 chiliad/day: i.xv (0.85 to i.55); 420-420 thou/mean solar day: 1.48 (1.08 to 2.02); ≥437 g/day: 1.65 (1.06 to 2.57) | Aforementioned as above |
White rice intake and take chances of type 2 diabetes
Figure 2 summarises the comparisons of the highest and lowest categories of white rice intake levels. Overall, the random furnishings model summarising all seven comparisons suggested a positive association; the pooled relative gamble was one.27 (95% confidence interval 1.04 to i.54), although significant heterogeneity was detected (Iii=72.2%; Cochrane Q exam P=0.001). With stratification by ethnicity, the association was stronger for Asian populations (pooled relative risk one.55, 1.xx to ii.01) than for Western populations (1.12, 0.94 to one.33). In both strata, the P for heterogeneity was not pregnant (P=0.17 and P=0.13). The departure in the pooled relative risks betwixt these 2 groups reached statistical significance (P=0.038), suggesting an interaction between rice intake and ethnicity. Similarly, when we used a stock-still effects model to examine betwixt ethnic group heterogeneity, nosotros found a significant P for heterogeneity (P<0.001). The funnel plot and Egger'southward test (P=0.30) did not suggest testify of publication bias (supplementary effigy A).
Fig two Pooled random effects relative run a risk (95% CI) of type 2 diabetes comparing high with low white rice consumption levels. P values are P for heterogeneity
Dose-response relation betwixt white rice intake and diabetes take chances
In a fixed effects cubic spline model that included all studies, we did not discover bear witness suggesting whatsoever non-linear relation between white rice consumption and risk of diabetes (P for non-linearity=0.51) (fig 3 ). For each serving per day increment of white rice consumption, the relative risk was ane.11 (1.08 to one.fourteen; P for linear trend<0.001). Using the incidence rate of diabetes in the centre aged US population (15.ii cases/thou population aged 45-64 years),19 we estimated that 167 cases of diabetes per 100 000 centre aged people would occur each year for each serving per twenty-four hour period increment in consumption of white rice. (These estimates may underestimate the hazard divergence for Asian populations that are experiencing an accelerated incidence rate of diabetes.20) To illustrate this, we further plotted the incidence rate of diabetes past intake levels for each comparing category in Asian and Western populations (supplementary figure B).
Fig iii Dose-response relation between white rice intake and risk of type 2 diabetes. Solid line represents point estimates of clan between white rice intake and diabetes risk; dashed lines are 95% CIs. Filled circles are relative risks corresponding to comparing categories in studies in Western populations; open up circles are for studies in Asian populations. Size of circle is in proportion to sample size for each comparing grouping
Secondary analysis
We did several secondary analyses to examine the robustness of the primary results. Firstly, we evaluated a potential interaction by sex. Because Hodge et al's did not separate men from women in their analysis, we excluded this study in this secondary analysis. The association was more pronounced among women (pooled relative risk ane.46, 1.xvi to 1.83) than men (i.08, 0.87 to 1.34) (supplementary figure C). Secondly, nosotros excluded Hodge et al's written report, which had a lower quality score than other studies and did not separate white rice from brown rice. This analysis yielded a pooled relative take chances of 1.17 (0.97 to 1.42) comparing the highest and lowest categories in Western populations. The relative risk was i.33 (1.09 to 1.63) for all populations, and a meaning P for heterogeneity (P=0.006) was still present in this assay. Lastly, when we included Yu et al'south study amongst Chinese people living in Hong Kong,18 which was excluded from the master analysis because of a high charge per unit of loss to follow-up, we found like associations; comparing the highest and the everyman categories, the pooled relative risk was 1.45 (1.11 to 1.89) for Asian populations and 1.24 (i.03 to one.50) for full populations.
Word
In this meta-assay of prospective cohort studies, we found that higher white rice consumption was associated with a significantly elevated take chances of type 2 diabetes. This clan seems to be stronger for Asians than for Western populations. A dose-response analysis showed that each serving per twenty-four hour period of white rice consumption was associated with an 11% increase in chance of diabetes in the overall population.
Strengths and limitations
Several caveats of this meta-analysis are worth discussing. Firstly, although the ethnicity stratified analysis did not show significant heterogeneity within each group, the limited number of studies may lead to diminished statistical power for detecting heterogeneity within each stratum. Secondly, although we included the results from only the fully adapted models, because all individual studies were observational in nature the results of these studies may yet be subject to residual confounding or other biases. Confounding past socioeconomic condition is of particular business organization considering this is both a take a chance factor for type 2 diabetes and a predictor of rice consumption in Asian and Western populations.5 7 21 22 23 24 Still, the Usa studies consisted of participants from the same professional person groundwork, and so misreckoning by socioeconomic status was probable to be small. In addition, other studies controlled for indicators of socioeconomic condition such equally income and education. Nonetheless, residuum misreckoning past socioeconomic condition cannot be completely ruled out in these studies. Depending on the nature of uncontrolled or residual misreckoning, the associations seen in these individual studies and our meta-analysis could exist biased in either direction. Large calibration pooling projects, in which covariate adjustments and statistical analysis can be standardised, are needed to ostend the findings of this meta-analysis. Likewise, the dose-response relation could exist more than precisely modelled in such pooling projects.
Thirdly, all studies used nutrient frequency questionnaires to assess levels of white rice intake. Although validation studies showed reasonable reproducibility and validity of cocky reported rice intake, measurement error is inevitable. Measurement error in assessment of exposure may lead to attenuation of true associations in a prospective study, peculiarly when the exposure was assessed before illness assessment. Fourthly, although all studies excluded cases of self-reported diabetes at baseline, some undiagnosed cases may however be included in the analysis. Still, the effect of such a bias is probable to be small. In the US studies, self reported diagnosis of diabetes was highly accurate; the Australian report farther excluded whatever cases with a diagnosis date earlier baseline, even if they did non written report diabetes at baseline interview; and in Asian studies, considering rice is a staple nutrient, substantial reduction of rice consumption after diagnosis of diabetes is unlikely. Lastly, we were unable to include brown rice in this meta-assay or to evaluate the effects of substituting brownish rice for white rice, because the association betwixt chocolate-brown rice and gamble of diabetes was examined but in Sun et al's study.13
The strengths of this meta-analysis include the large sample size and long duration of follow-up of the included studies. In add-on, most established risk factors for type two diabetes were adjusted for in the fully adapted models in these studies. Moreover, inclusion of studies in both Asian and Western countries allowed us to investigate the dose-response relation on the basis of a wide spectrum of white rice intake levels.
Results in relation to other studies
Several potential mechanisms could explicate the association between white rice consumption and risk of type ii diabetes. Amongst Asian populations, which swallow white rice as a staple nutrient, white rice is the predominant contributor to dietary glycaemic load. For case, in women living in Shanghai, white rice deemed for 73.ix% of dietary glycaemic loadseven; in Japanese women, white rice explained 58.v% of dietary glycaemic load.25 In a meta-analysis that pooled information from cohort studies primarily done in Western populations, dietary glycaemic load was consistently associated with increased risk of developing type two diabetes.26 Similarly, recent investigations in Chinese and Japanese populations likewise back up the hypothesis that high dietary glycaemic load is associated with increased hazard of diabetes.7 25 27 The relatively weaker clan for Western populations seen in this meta-analysis may exist due to the fact that white rice intake was much lower than in Asians and, therefore, was but a minor contributor to dietary glycaemic load. In add-on, the glycaemic index values of various white rice varieties depend on several factors including amylose content, other botanical structures, and processing methods.8 28 29 30 The contribution of white rice to dietary glycaemic load may vary essentially, peculiarly when consumption levels are depression. Nonetheless, high intake of white rice may also lead to increased risk of diabetes through mechanisms other than its contribution to dietary glycaemic load. Compared with minimally candy whole grains such as brown rice, white rice has a lower content of many nutrients including insoluble fibre, magnesium, vitamins, lignans, phytoestrogens, and phytic acrid, which are lost during the refining process.31 Some of these nutrients, especially insoluble fibre and magnesium, take been associated with lower risk of type ii diabetes in prospective accomplice studies.9 10 32 33 34 35 36 Thus, a loftier consumption of white rice may lead to increased risk of diabetes because of the depression intake of beneficial nutrients, in addition to its higher glycaemic load. Meanwhile, more than data are needed to shed light on whether the interaction by ethnicity is due simply to essentially different white rice intake levels or to other mechanisms.
Data on the association between dark-brown rice intake and type 2 diabetes are express. In Sun et al's work in Western populations, brown rice intake was associated with a modestly decreased adventure of type 2 diabetes, and the substitution of chocolate-brown rice or other whole grains for white rice was associated with a significantly lower take chances of diabetes.thirteen Because Asian populations eat white rice almost exclusively, no data on the relation between brown rice and risk of diabetes are available in these populations. Yet, a 16 week clinical trial in 76 Korean men showed that isocaloric replacement of white rice with whole grains and legume pulverization (composed of 66.6% whole grains, 22.2% legumes, 5.6% seeds, and v.6% vegetables) led to significant reductions in serum glucose and insulin concentrations, whereas body weight remained unchanged.37 Still, a recent study in Shanghai found that substituting brown rice for white rice for 16 weeks did not substantially affect metabolic markers in centre aged men and women, although high density lipoprotein cholesterol and diastolic blood pressure were significantly improved amidst people with diabetes through the chocolate-brown rice intervention.38 More studies with larger sample sizes and longer durations of follow-upwardly are warranted to examine the effects of substituting brownish rice for white rice on risk of diabetes.
Conclusions
In summary, this meta-analysis suggests that higher white rice intake is associated with a significantly elevated take chances of type 2 diabetes, especially among Asian populations. The recent transition in nutrition characterised by dramatically decreased physical activity levels and much improved security and diversity of nutrient has led to increased prevalence of obesity and insulin resistance in Asian countries.39 Although rice has been a staple food in Asian populations for thousands of years, this transition may return Asian populations more susceptible to the adverse effects of high intakes of white rice, as well as other sources of refined carbohydrates such every bit pastries, white staff of life, and carbohydrate sweetened beverages. In addition, the dose-response relations indicate that even for Western populations with typically low intake levels, relatively high white rice consumption may still modestly increase risk of diabetes.
Web Extra. Extra fabric supplied by the author
Notes
Nosotros thank Allison 1000 Hodge and Ruby Yu for providing data for the meta-analysis.
Contributors: EAH, AP, and QS searched the literature and extracted information. QS had the idea for the analysis. VM, AP, and QS provided statistical expertise. EAH and AP analysed the data. EAH wrote the get-go typhoon of the manuscript. All authors contributed to the estimation of the results and critical revision of the manuscript for important intellectual content and approved the final version of the manuscript. QS is the guarantor.
Funding: QS was supported by career development honour K99HL098459 from the US National Heart, Lung, and Claret Plant. The funding sources had no part in study design; in the collection, assay, and interpretation of data; in the writing of the report; or in the decision to submit the commodity for publication. The authors are non affiliated with the funding institutions.
Competing interests: All authors have completed the Unified Competing Interest grade at world wide web.icmje.org/coi_disclosure.pdf (bachelor on request from the corresponding author) and declare: no back up from whatsoever organisation for the submitted work; no financial relationships with whatsoever organisations that might have an involvement in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.
Upstanding approval: Not needed.
Information sharing: No additional data available.
Notes
Cite this as: BMJ 2012;344:e1454
References
1. Fuller D, Sato Y-I, Castillo C, Qin Fifty, Weisskopf A, Kingwell-Banham E, et al. Consilience of genetics and archaeobotany in the entangled history of rice. Archaeological and Anthropological Sciences 2010;2:115-31. [Google Scholar]
ii. Higham C, Lu TLD. The origins and dispersal of rice cultivation. Antiquity 1998;72:867-77. [Google Scholar]
3. Liu L, Lee G-A, Leping J, Juzhong Z. Evidence for the early start (c 9000 cal BP) of rice domestication in Communist china: a response. The Holocene 2007;17:1059-68. [Google Scholar]
4. Miller M, Prakash A, Decker E. Whole-grain foods in health and disease. American Clan of Cereal Chemists, 2002.
5. Nanri A, Mizoue T, Noda M, Takahashi Y, Kato K, Inoue M, et al. Rice intake and blazon 2 diabetes in Japanese men and women: the Japan Public Health Heart-based Prospective Written report. Am J Clin Nutr 2010;92:1468-77. [PubMed] [Google Scholar]
6. Economic Research Service, United States Department of Agronomics. Data sets. 2010. www.ers.usda.gov/Data/.
7. Villegas R, Liu Due south, Gao YT, Yang G, Li H, Zheng W, et al. Prospective written report of dietary carbohydrates, glycemic index, glycemic load, and incidence of type two diabetes mellitus in centre-aged Chinese women. Arch Intern Med 2007;167:2310-half-dozen. [PubMed] [Google Scholar]
8. Foster-Powell K, Holt SH, Make-Miller JC. International tabular array of glycemic index and glycemic load values: 2002. Am J Clin Nutr 2002;76:5-56. [PubMed] [Google Scholar]
nine. Salmeron J, Ascherio A, Rimm EB, Colditz GA, Spiegelman D, Jenkins DJ, et al. Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care 1997;20:545-50. [PubMed] [Google Scholar]
ten. Salmeron J, Manson JE, Stampfer MJ, Colditz GA, Wing AL, Willett WC. Dietary fiber, glycemic load, and take a chance of non-insulin-dependent diabetes mellitus in women. JAMA 1997;277:472-7. [PubMed] [Google Scholar]
xi. Schulze MB, Liu S, Rimm EB, Manson JE, Willett WC, Hu FB. Glycemic index, glycemic load, and dietary fiber intake and incidence of type two diabetes in younger and middle-anile women. Am J Clin Nutr 2004;lxxx:348-56. [PubMed] [Google Scholar]
12. Hodge AM, English DR, O'Dea Thousand, Giles GG. Glycemic alphabetize and dietary fiber and the risk of type ii diabetes. Diabetes Care 2004;27:2701-half-dozen. [PubMed] [Google Scholar]
13. Lord's day Q, Spiegelman D, van Dam RM, Holmes MD, Malik VS, Willett WC, et al. White rice, brown rice, and risk of type 2 diabetes in US men and women. Arch Intern Med 2010;170:961-9. [PMC free article] [PubMed] [Google Scholar]
xiv. Altman DG, Banal JM. Interaction revisited: the difference between two estimates. BMJ 2003;326:219. [PMC free article] [PubMed] [Google Scholar]
15. Egger M, Davey Smith Grand, Schneider K, Minder C. Bias in meta-assay detected past a simple, graphical exam. BMJ 1997;315:629-34. [PMC gratuitous article] [PubMed] [Google Scholar]
xvi. Harrell FE. Regression modeling strategies with applications to linear models, logistic regression and survival analysis. Springer-Verlag, 2001.
17. Greenland S, Longnecker MP. Methods for tendency estimation from summarized dose-response data, with applications to meta-analysis. Am J Epidemiol 1992;135:1301-9. [PubMed] [Google Scholar]
18. Yu R, Woo J, Chan R, Sham A, Ho S, Tso A, et al. Relationship between dietary intake and the development of blazon 2 diabetes in a Chinese population: the Hong Kong Dietary Survey. Public Health Nutr 2011;Apr v:one-9. [PubMed]
19. US Centers for Affliction Control and Prevention. Incidence of diagnosed diabetes per i,000 population anile xviii-79 years, by age, United states, 1980-2009. 2012. www.cdc.gov/diabetes/statistics/incidence/fig3.htm.
20. Wild South, Roglic One thousand, Light-green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care 2004;27:1047-53. [PubMed] [Google Scholar]
21. Agardh Due east, Allebeck P, Hallqvist J, Moradi T, Sidorchuk A. Type 2 diabetes incidence and socio-economic position: a systematic review and meta-analysis. Int J Epidemiol 2011;forty:804-eighteen. [PubMed] [Google Scholar]
22. Batres-Marquez SP, Jensen HH, Upton J. Rice consumption in the United States: contempo prove from food consumption surveys. J Am Diet Assoc 2009;109:1719-27. [PubMed] [Google Scholar]
23. Gu D, Reynolds Thousand, Wu 10, Chen J, Duan 10, Reynolds RF, et al. Prevalence of the metabolic syndrome and overweight amongst adults in Cathay. Lancet 2005;365:1398-405. [PubMed] [Google Scholar]
24. Hayashino Y, Yamazaki S, Nakayama T, Sokejima S, Fukuhara Due south. The association between socioeconomic status and prevalence of diabetes mellitus in rural Japan. Curvation Environ Occup Wellness 2010;65:224-9. [PubMed] [Google Scholar]
25. Murakami K, Sasaki South, Takahashi Y, Okubo H, Hosoi Y, Horiguchi H, et al. Dietary glycemic alphabetize and load in relation to metabolic risk factors in Japanese female person farmers with traditional dietary habits. Am J Clin Nutr 2006;83:1161-9. [PubMed] [Google Scholar]
26. Barclay AW, Petocz P, McMillan-Cost J, Overflowing VM, Prvan T, Mitchell P, et al. Glycemic index, glycemic load, and chronic disease risk—a meta-analysis of observational studies. Am J Clin Nutr 2008;87:627-37. [PubMed] [Google Scholar]
27. Nanri A, Mizoue T, Yoshida D, Takahashi R, Takayanagi R. Dietary patterns and A1C in Japanese men and women. Diabetes Care 2008;31:1568-73. [PMC complimentary article] [PubMed] [Google Scholar]
28. Larsen HN, Christensen C, Rasmussen OW, Tetens IH, Choudhury NH, Thilsted SH, et al. Influence of parboiling and physico-chemical characteristics of rice on the glycaemic index in not-insulin-dependent diabetic subjects. Eur J Clin Nutr 1996;50:22-vii. [PubMed] [Google Scholar]
29. Larsen HN, Rasmussen OW, Rasmussen PH, Alstrup KK, Biswas SK, Tetens I, et al. Glycaemic index of parboiled rice depends on the severity of processing: report in blazon 2 diabetic subjects. Eur J Clin Nutr 2000;54:380-five. [PubMed] [Google Scholar]
30. Miller JB, Pang E, Bramall Fifty. Rice: a high or depression glycemic index food? Am J Clin Nutr 1992;56:1034-6. [PubMed] [Google Scholar]
31. Slavin JL, Martini MC, Jacobs DR Jr, Marquart Fifty. Plausible mechanisms for the protectiveness of whole grains. Am J Clin Nutr 1999;lxx(suppl 3):459-63S. [PubMed] [Google Scholar]
32. Meyer KA, Kushi LH, Jacobs DR Jr, Slavin J, Sellers TA, Folsom AR. Carbohydrates, dietary fiber, and incident type 2 diabetes in older women. Am J Clin Nutr 2000;71:921-30. [PubMed] [Google Scholar]
33. Schulze MB, Schulz Thousand, Heidemann C, Schienkiewitz A, Hoffmann K, Boeing H. Fiber and magnesium intake and incidence of blazon ii diabetes: a prospective study and meta-analysis. Arch Intern Med 2007;167:956-65. [PubMed] [Google Scholar]
34. Song Y, He K, Levitan EB, Manson JE, Liu S. Furnishings of oral magnesium supplementation on glycaemic command in type two diabetes: a meta-analysis of randomized double-blind controlled trials. Diabet Med 2006;23:1050-6. [PubMed] [Google Scholar]
35. Van Dam RM, Hu FB, Rosenberg L, Krishnan South, Palmer JR. Dietary calcium and magnesium, major food sources, and chance of type ii diabetes in The states black women. Diabetes Care 2006;29:2238-43. [PubMed] [Google Scholar]
36. Weickert MO, Mohlig Yard, Schofl C, Arafat AM, Otto B, Viehoff H, et al. Cereal cobweb improves whole-body insulin sensitivity in overweight and obese women. Diabetes Care 2006;29:775-lxxx. [PubMed] [Google Scholar]
37. Jang Y, Lee JH, Kim OY, Park HY, Lee SY. Consumption of whole grain and legume powder reduces insulin demand, lipid peroxidation, and plasma homocysteine concentrations in patients with coronary artery illness: randomized controlled clinical trial. Arterioscler Thromb Vasc Biol 2001;21:2065-71. [PubMed] [Google Scholar]
38. Zhang G, Pan A, Zong Grand, Yu Z, Wu H, Chen X, et al. Substituting white rice with brown rice for 16 weeks did not substantially bear upon metabolic run a risk factors in middle-anile Chinese men and women with diabetes or a high risk for diabetes. J Nutr 2011;141:1685-xc. [PubMed] [Google Scholar]
39. Popkin BM. The diet transition in low-income countries: an emerging crisis. Nutr Rev 1994;52:285-98. [PubMed] [Google Scholar]
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