Rice intake and type 2 diabetes in Japanese men and women: the Japan Public Health Center based Prospective Study 1 3

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1 Rice intake and type 2 diabetes in Japanese men and women: the Japan Public Health Center based Prospective Study 1 3 Akiko Nanri, Tetsuya Mizoue, Mitsuhiko Noda, Yoshihiko Takahashi, Masayuki Kato, Manami Inoue, and Shoichiro Tsugane for the Japan Public Health Center based Prospective Study Group ABSTRACT Background: Refined carbohydrates have been suggested to deteriorate glucose metabolism; however, whether persons with elevated intakes of white rice, which is a major staple food for the Japanese, experience increased risk of developing type 2 diabetes remains unclear. Objective: We prospectively investigated the association between white rice intake and risk of type 2 diabetes. Design: Participants were 25,666 men and 33,622 women aged y who participated in the second survey of the Japan Public Health Center based Prospective Study and who had no prior history of diabetes. We ascertained food intake by using a validated 147-item food-frequency questionnaire. Odds ratios of self-reported, physician-diagnosed type 2 diabetes over 5 y were estimated by using logistic regressions. Results: A total of 1103 new cases of type 2 diabetes were selfreported. There was a significant association between rice intake and an increased risk of type 2 diabetes in women; the multivariateadjusted odds ratio for the highest compared with lowest quartiles of rice intake was 1.65 (95% CI: 1.06, 2.57; P for trend = 0.005). In men, the association was unclear, although there was a suggestion of a positive association in persons who were not engaged in strenuous physical activity (P for trend = 0.08). Conclusions: Elevated intake of white rice is associated with an increased risk of type 2 diabetes in Japanese women. The finding that is suggestive of a positive association of rice intake in physically inactive men deserves further investigation. Am J Clin Nutr 2010;92: role of environmental factors, particularly dietary factors, that might account for the epidemic of type 2 diabetes in Japanese. Japanese studies have shown that a low calcium intake, which is typical of Japanese populations (6), was associated with an elevated risk of type 2 diabetes (7), and a dietary pattern characterized by a high intake of traditional Japanese foods, such as soybean products, seaweed, Japanese pickles, and green tea, was associated with an increased prevalence of glucose intolerance (8). These previous findings suggested that a traditional Japanese diet may be associated with the high prevalence of diabetes in Japanese populations. White rice is a major staple food of Japanese and forms the basis of the Japanese diet. Although rice consumption in Japan has decreased over the past several decades, nearly 30% of total energy intake for Japanese is still derived from rice (6). Compared with brown rice, white rice contains less dietary fiber and fewer vitamins and minerals (9), which are potentially protective against type 2 diabetes. In some (10 15) but not all (16) studies, foods such as white rice, which are rich in refined carbohydrates, have been implicated in the deterioration of glucose metabolism, with a subsequent increasing risk of type 2 diabetes. However, few such studies have been conducted in Asian populations (15), which are known to consume large amounts of rice. Thus far, the only prospective study in Asia (China) (15) reported results for women, and the association in Asian men remains unclear. Therefore, we prospectively examined the association between white rice intake and risk of type 2 diabetes in Japanese adults by using data from a large-scale population-based cohort study in INTRODUCTION The prevalence of type 2 diabetes has been increasing worldwide (1). In particular, the prevalence of diabetes in Japan increased from 13.7 to 22.1 million between 1997 and 2007 (2). Such an increase might be ascribed to an energy imbalance, which develops easily in individuals who live a sedentary life and, in many cases, accompanies obesity. Although the prevalence of obesity [body mass index (BMI; in kg/m 2 ).30] in the Japanese is lower than in Westerners (Japan: 3% in both men and women; United States: 31% in men and 33% in women) (3), the prevalence of type 2 diabetes in Japanese populations is not dramatically lower than that in Western populations (Japan: 7.3%; United Kingdom: 4.9%; United States: 12.3%) (4). This has been attributed to a genetic difference between Asian and white populations (5), with limited evidence available regarding the 1 From the Department of Epidemiology and International Health, International Clinical Research Center (AN and TM), and the Department of Diabetes and Metabolic Medicine (MN and YT), National Center for Global Health and Medicine, Tokyo, Japan; the Japan Foundation for the Promotion of International Medical Research Cooperation, Tokyo, Japan (MK); and the Epidemiology and Prevention Division, Research Center for Cancer Prevention and Screening, National Cancer Center, Tokyo, Japan (MI and ST). 2 Supported by Grants-in-Aid for Cancer Research (19shi-2) and a Health Sciences Research Grant (Research on Comprehensive Research on Cardiovascular Diseases H19-016) from the Ministry of Health, Labor, and Welfare of Japan. 3 Address correspondence to A Nanri, Department of Epidemiology and International Health, International Clinical Research Center, National Center for Global Health and Medicine, Toyama, Shinjuku-ku, Tokyo , Japan. nanri@ri.ncgm.go.jp. Received March 14, Accepted for publication September 26, First published online October 27, 2010; doi: /ajcn Am J Clin Nutr 2010;92: Printed in USA. Ó 2010 American Society for Nutrition

2 RICE INTAKE AND TYPE 2 DIABETES 1469 Japan. We also examined whether the association was modified by known risk factors for type 2 diabetes. SUBJECTS AND METHODS Study population The Japan Public Health Center based Prospective (JPHC) Study was launched in 1990 for cohort I and in 1993 for cohort II (17) and involved residents of 11 public health centers aged y at each baseline survey. Study participants were informed of the objectives of the study, and participants who responded to the questionnaire survey were regarded as consenting to participate in the study. A questionnaire survey was conducted at baseline and at the 5- and 10-y follow-ups. Information on medical histories and health-related lifestyles, such as smoking, drinking, and dietary habits, was obtained at each survey. This study was approved by the Institutional Review Board of the National Cancer Center of Japan. From the study population at baseline (n = 140,420), we excluded subjects who resided in 2 public health center areas because of differences in recruitment criteria. Of the remaining 116,672 eligible subjects, 95,373 (81.7%) subjects responded to the questionnaire survey at baseline. Of these subjects, 80,128 (84.0%) subjects responded to the 5-y follow-up survey (second survey), including the diet-related portion, and 71,075 (74.5%) of those subjects responded to the subsequent 10-y follow-up survey (third survey). We excluded any subject who reported a history of type 2 diabetes (n = 5183) or severe diseases (n = 6284), including cancer, cerebrovascular disease, myocardial infarction, chronic liver disease, and renal disease, at the baseline or second surveys. An additional 556 subjects with missing information for rice intake and 537 subjects who reported extreme total energy intakes (outside of the mean 6 3 SD according to sex) were excluded, which left a total of 59,288 subjects (25,666 men and 33,622 women) who were ultimately enrolled in our analysis. Food-frequency questionnaire At baseline, second, and third surveys, participants completed a self-administered questionnaire. During data analyses in the current study, we used data from the second survey as baseline data because the questionnaire used for the second survey more comprehensively inquired about food intakes than that used for the baseline survey. At the second survey, a food-frequency questionnaire (FFQ) was used to assess the average intake of 147 food and beverage items over the previous year (18). For rice (japonica rice; round and short grain), participants were asked to denote their usual rice-bowl size from 3 options (small, medium, and large) and the number of bowls consumed daily from 9 options that ranged from,1 to10/d. One bread item and 4 noodle items (Japanese, buckwheat, Okinawa, and Chinese noodles) were also included in the FFQ. For most food items, including the bread and noodle items, 9 response options were available to describe consumption frequency, which ranged from rarely (,1 time/mo) to 7 times/d. A standard portion size was specified for each food, and respondents were asked to denote their usual portion size from 3 options (less than one-half, standard, or.1.5 times). We calculated the daily intake of staple foods by multiplying daily consumption frequency by the typical portion size. For the calculation of food and nutrient intakes, the missing of consumption frequency and usual portion size of all food items were set as zero and a standard portion size, respectively. The validity of the FFQ was assessed in subsamples by using either 14- or 28-d dietary records. Spearman s correlation coefficients between intake values for rice, bread, and noodles derived from the FFQ and those derived from dietary records were 0.67, 0.67, and 0.42, respectively, in men and 0.55, 0.63, and 0.43, respectively, in women. With regard to the reproducibility of estimations between the 2 FFQs administered 1 y apart, the respective Spearman s correlation coefficients for intake of rice, bread, and noodles were 0.79, 0.70, and 0.49 in men and 0.69, 0.67, and 0.57 in women. Ascertainment of type 2 diabetes Type 2 diabetes newly diagnosed during the 5-y period after the second survey was determined by a self-administered questionnaire at the third survey. At the third survey, study participants were asked if they had ever been diagnosed with diabetes, and if so, when the initial diagnosis had been made. Because we used the second survey as the starting point of observation for the incidence of type 2 diabetes, only those subjects who were diagnosed after 1995 for cohort I and after 1998 for cohort II were regarded as incident cases during follow-up. Details regarding the assessment of the validity of self-reported diabetes have been described elsewhere (19). In a previous study (19) that we conducted, 94% of self-reported diabetes cases were confirmed as such by medical records. Upon application of these data to the survey results obtained from a JPHC subpopulation (health-checkup participants) whose plasma glucose data were available, the sensitivity and specificity of self-reported diabetes were estimated to be 85.5% and 99.7%, respectively, in men and 79.3% and 99.7%, respectively, in women. Physical activity To assess daily physical activity, subjects were asked about the average amount of time spent per day engaging in 3 types of physical activity at work and during leisure time: strenuous physical activity (none,,1, or 1 h), sitting (,3, 3 to,8, or 8 h), and standing or walking (,1, 1 to,3, or 3 h). Details regarding the calculation of total physical activity level (metabolic equivalent task hours [MET-h]/d) have been described elsewhere (20). The validity of the total METs per day was assessed in subsamples by using 4-d, 24-h physical activity records from 2 different seasons. Spearman s correlation coefficients between total METs per day and the physical activity records were 0.53 in men and 0.35 in women (20). Statistical analyses Participants were classified into quartiles of rice, bread, and noodle intake by sex. In the analysis for bread and noodle intake, subjects with a missing for consumption frequency for these foods were excluded in each analysis. Confounding variables considered were as follows: age (y, continuous), study area (9 areas), BMI (,21, , , , or 27), smoking habit (lifetime nonsmoker, former smoker, or current smoker with a consumption of either,20 or 20 cigarettes/d), alcohol

3 1470 NANRI ET AL TABLE 1 Baseline characteristics of subjects according to categories of rice, bread, and noodle intake 1 Quartiles of rice intake Quartiles of bread intake Quartiles of noodle intake Lowest Highest P for trend 2 Lowest Highest P for trend 2 Lowest Highest P for trend 2 Men n Age (y) , , ,0.01 BMI (kg/m 2 ) , ,0.01 Current smoker (%) , , ,0.01 Alcohol consumption 1 d/wk (%) , ,0.01 Total physical activity (MET-h/d) , Strenuous physical activity 1 h/d (%) 4, , Occupation (primary industries) (%) , , ,0.01 Family history of diabetes (%) 7 9, History of hypertension (%) 20 14, , Food and nutrient intake Total energy intake (kcal/d) , , ,0.01 Protein (g/d) , , ,0.01 Fat (g/d) , , Carbohydrate (g/d) , , ,0.01 Calcium (mg/d) , , ,0.01 Magnesium (mg/d) , , ,0.01 Dietary fiber (g/d) , , ,0.01 Rice (g/d) , , ,0.01 Bread (g/d) , , ,0.01 Noodles (g/d) , , ,0.01 Fruit (g/d) , , ,0.01 Vegetable (g/d) , , ,0.01 Fish (g/d) , , ,0.01 Coffee consumption 1 cup/d (%) , , ,0.01 Women n Age (y) , ,0.01 BMI (kg/m 2 ) ,0.01 Current smoker (%) 4 5 4, ,0.01 Alcohol consumption 1 d/wk (%) , ,0.01 Total physical activity (MET-h/d) , , ,0.01 Strenuous physical activity 1 h/d (%) 4, , Occupation (primary industries) (%) , , Family history of diabetes (%) , History of hypertension (%) , ,0.01 Food and nutrient intake Total energy intake (kcal/d) , , ,0.01 Protein (g/d) , , ,0.01 Fat (g/d) , , ,0.01 Carbohydrate (g/d) , , ,0.01 Calcium (mg/d) , , ,0.01 Magnesium (mg/d) , , Dietary fiber (g/d) , ,0.01 Rice (g/d) , , ,0.01 Bread (g/d) , , ,0.01 Noodles (g/d) , ,0.01 Fruit (g/d) , , ,0.01 Vegetable (g/d) , ,0.01 Fish (g/d) , , ,0.01 Coffee consumption 1 cup/d (%) , , , MET-h, metabolic equivalent task hours. n = 59,288 (25,666 men and 33,622 women). For bread intake, 850 men and 1155 women with missing data were excluded. For noodle intake, 2924 men and 4303 women with missing data were excluded. 2 On the basis of the Mantel-Haenszel s chi-square test for categorical variables and linear regression analysis for continuous variables with assignment of ordinal numbers 0 3 to categories of rice, bread, or noodle intake. 3 Mean 6 SD (all such values). 4 Subjects with missing information were excluded (BMI: n = 514 in men, n = 821 in women; smoking status: n = 597 in men, n = 2201 in women; alcohol consumption: n = 564 in men, n = 1120 in women; total physical activity: n = 4444 in men, n = 6137 in women; strenuous physical activity: n = 3396 in men, n = 4838 in women; occupation: n =838 in men, n = 1197 in women; coffee consumption: n = 1374 in men, n = 1803 in women). 5 Strenuous physical activity at work or during leisure time. consumption (nondrinker, occasional drinker, or drinker with a consumption of,150, , , or 450 g ethanol/ wk for men and,150 or 150 g ethanol/wk for women), total physical activity level (MET-h/d, quartiles), history of hypertension (yes or no), family history of diabetes mellitus (yes or no), occupation (agriculture, forestry, or fishery; salaried, self-

4 RICE INTAKE AND TYPE 2 DIABETES 1471 employed, or professional; or housework, unemployed, or retired), total energy intake (kcal/d, continuous), coffee consumption (almost never,,1, 1, or 2 cups/d), calcium intake (mg/d, continuous), magnesium intake (mg/d, continuous), dietary fiber intake (g/d, continuous), fruit intake (g/d, continuous), vegetable intake (g/d, continuous), and fish intake (g/d, continuous). An indicator variable for missing data was created for each covariate. Trend associations between confounding factors and rice, bread, or noodle intakes were tested by using Mantel- Haenszel s chi-square test for categorical variables and linear regression analysis for continuous variables. Odds ratios and 95% CIs of type 2 diabetes for categories of rice, bread, and noodle intakes were estimated by using multiple logistic regression analysis by taking the lowest category as a reference. The first model was adjusted for age and study area, and the second model was further adjusted for smoking habit, alcohol consumption, total physical activity, history of hypertension, family history of diabetes, occupation, total energy intake, and dietary factors including coffee consumption and intakes of calcium, magnesium, dietary fiber, fruit, vegetable, and fish, which were mutually adjusted for rice, bread, and noodle intakes (g/d, quartiles). In the analysis for rice intake, an indicator variable for missing of consumption frequency for bread and noodle items was created. In the final model, BMI was added to the third model. A trend association was assessed by assigning ordinal numbers 0 3 to the 4 categories of staple food consumption. We also analyzed the association between rice intake and type 2 diabetes by strenuous physical activity at work or during leisure time (,1 or1 h/d), age (,60 or 60 y), BMI (,25 or 25), occupation [primary industries (agriculture, forestry, or fishery) or others], smoking status in men only (nonsmoker or current smoker), and menopausal status in women only (pre- or postmenopausal). We also conducted a reanalysis after the exclusion of subjects who added minor cereals (foxtail millet, Japanese barnyard millet, or barley) to rice. An interaction term by multiplying rice intake (g/d, continuous) and the above stratifying variables (dichotomous) was created and added to the model to assess statistical interactions. A 2-sided P, 0.05 was regarded as statistically significant. All analyses were performed with Statistical Analysis System (SAS) version 9.1 software (SAS Institute, Cary, NC). RESULTS During the 5-y period, 1103 participants were newly diagnosed with diabetes (625 men and 478 women). The characteristics of study participants according to quartile categories of rice, bread, and noodle intake for men and women, separately, are shown in Table 1. Participants with relatively high intakes of rice, bread, or noodles were, on average, younger than participants with low intakes. Men with higher rice intakes tended to be current smokers, and women with high rice intakes were less likely to consume alcohol. Both men and women who consumed greater amounts of rice tended to have a lower BMI, were more likely to report higher levels of total physical activity, were more likely to be engaged in strenuous physical activity at work or during leisure time and to work in primary industries, and consumed less protein, fat, calcium, magnesium, dietary fiber, and coffee than participants with lower rice intakes. Men and women in the category of higher bread intake were less likely to work in primary industries. Men with increased bread intakes were less likely to be current smokers and alcohol drinkers. Bread intake was positively associated with the intake of fat, dietary fiber (men only), coffee, calcium (men only), and magnesium (men only). Men and women with higher noodle intakes were more likely to be alcohol drinkers and consumed greater amounts of dietary fiber but less calcium. In this population, carbohydrates from rice, bread, and noodle intakes accounted for 51.9%, 3.3%, and 7.4% of the total carbohydrate intake, respectively, in men and for 46.4%, 4.6%, and 6.3% of the total carbohydrate intake, respectively, in women. Odds ratios and 95% CIs of type 2 diabetes associated with intakes of each staple food are shown in Table 2. In women, rice intake was significantly and positively associated with the incidence of type 2 diabetes with adjustment for age and area (P for trend = 0.004); the odds ratio for the highest compared with lowest quartile category was 1.48 (95% CI: 1.03, 2.14). The association remained significant even after adjustment for other covariates (P for trend = 0.005), with a fully adjusted odds ratio for the highest compared with lowest quartile category of 1.65 (95% CI: 1.06, 2.57). In men, the incidence of type 2 diabetes tended to increase with rice intake after adjustment for lifestyle factors other than dietary factors (odds ratio for the highest compared with lowest quartile category: 1.31; 95% CI: 0.98, 1.77; P for trend = 0.06) (data not shown in Table 2). However, the association was attenuated on further adjustment for dietary factors and BMI (odds ratio for the highest compared with lowest quartile category: 1.19; 95% CI: 0.85, 1.68; P for trend = 0.32). We obtained similar results to those above after repeating the analysis by using energy-adjusted rice intake (by a residual method) rather than crude intake. The respective fully adjusted odds ratios (95% CIs) of type 2 diabetes for the lowest through highest quartile categories of energy-adjusted rice intake were 1.00 (reference), 1.22 (0.96, 1.56), 1.40 (1.09, 1.81), and 1.24 (0.92, 1.68), respectively, in men (P for trend = 0.09) and 1.00 (reference), 1.34 (1.01, 1.78), 1.51 (1.12, 2.05), and 1.55 (1.11, 2.17), respectively, in women (P for trend = 0.01). In analyses stratified by physically strenuous activity at work or during leisure time (Table 3), a marginally significant trend association between rice intake and type 2 diabetes was observed in men who were not engaged in strenuous physical activity (P for trend = 0.08), whereas such a trend association was not observed in men who were engaged in strenuous physical activity (P for trend = 0.85, P for interaction = 0.23). Likewise, a marginally significant, positive trend association between rice intake and type 2 diabetes was observed in women who were not engaged in any strenuous physical activity (P for trend = 0.08) but was not observed in women who were engaged in such activity (P for trend = 0.30, P for interaction = 0.27). Further, increased risk of type 2 diabetes associated with rice intake was more pronounced in both men and women who worked in jobs other than primary industries, in smoking men, and in women with BMI,25. In women but not men, the association was strengthened after the exclusion of subjects who sometimes or always added minor cereals to rice; fully adjusted odds ratios (95% CIs) of type 2 diabetes for the lowest to highest quartile categories of rice intake were 1.00 (reference), 1.29 (0.85, 1.97), 1.67 (1.08, 2.58), and 1.81 (1.03, 3.18), respectively (P for trend = 0.01). With regard to bread intake, the incidence of type 2 diabetes was lower in the age- and area-adjusted model in men in the

5 1472 NANRI ET AL TABLE 2 Odds ratios (and 95% CIs) of type 2 diabetes according to quartile categories of rice, bread, and noodle intake Quartile Lowest Second Third Highest P for trend 1 Men Rice (g) (0 315) 420 ( ) 560 ( ) 700 (.560) No. of subjects , No. of cases Age and area adjusted 1.00 (reference) 1.25 (1.01, 1.54) 1.23 (0.95, 1.59) 1.16 (0.88, 1.53) 0.29 Multivariate adjusted (reference) 1.24 (0.99, 1.54) 1.25 (0.94, 1.68) 1.22 (0.86, 1.71) 0.26 Multivariate adjusted (reference) 1.24 (1.00, 1.55) 1.25 (0.93, 1.67) 1.19 (0.85, 1.68) 0.32 Bread (g) 2,5 0 (0 2) 4 (4 6) 12.9 (12 23) 47.1 (30) No. of subjects No. of cases Age and area adjusted 1.00 (reference) 1.08 (0.85, 1.37) 1.08 (0.84, 1.38) 0.81 (0.62, 1.05) 0.08 Multivariate adjusted (reference) 1.08 (0.84, 1.37) 1.09 (0.84, 1.40) 0.83 (0.62, 1.10) 0.19 Multivariate adjusted (reference) 1.08 (0.85, 1.39) 1.11 (0.85, 1.43) 0.85 (0.64, 1.14) 0.30 Noodles (g) 2, (0 44.6) 74.2 ( ) ( ) (.146.6) No. of subjects No. of cases Age and area adjusted 1.00 (reference) 1.01 (0.80, 1.28) 1.04 (0.82, 1.31) 0.93 (0.73, 1.18) 0.62 Multivariate adjusted (reference) 1.01 (0.79, 1.29) 1.03 (0.81, 1.32) 0.95 (0.73, 1.24) 0.80 Multivariate adjusted (reference) 0.99 (0.78, 1.26) 1.01 (0.79, 1.29) 0.89 (0.68, 1.17) 0.49 Women Rice (g) (0 278) 315 ( ) 420 ( ) 560 (437) No. of subjects ,551 13, No. of cases Age and area adjusted 1.00 (reference) 1.10 (0.83, 1.46) 1.40 (1.07, 1.83) 1.48 (1.03, 2.14) Multivariate adjusted (reference) 1.13 (0.84, 1.52) 1.49 (1.09, 2.04) 1.69 (1.08, 2.63) Multivariate adjusted (reference) 1.15 (0.85, 1.55) 1.48 (1.08, 2.02) 1.65 (1.06, 2.57) Bread (g) 2,5 4 (0 4) 12.9 (6 12) 30 (15 30) 60 (45) No. of subjects No. of cases Age and area adjusted 1.00 (reference) 0.99 (0.78, 1.27) 1.05 (0.80, 1.37) 0.88 (0.67, 1.14) 0.41 Multivariate adjusted (reference) 1.01 (0.78, 1.30) 1.10 (0.83, 1.46) 0.97 (0.72, 1.30) 0.99 Multivariate adjusted (reference) 1.00 (0.77, 1.28) 1.10 (0.83, 1.46) 0.99 (0.73, 1.34) 0.87 Noodles (g) 2, ( ) 45.0 ( ) 91.5 ( ) (114.1) No. of subjects No. of cases Age and area adjusted 1.00 (reference) 1.08 (0.81, 1.44) 1.29 (0.97, 1.71) 1.17 (0.87, 1.55) 0.17 Multivariate adjusted (reference) 1.09 (0.82, 1.46) 1.33 (1.00, 1.78) 1.21 (0.88, 1.66) 0.13 Multivariate adjusted (reference) 1.04 (0.78, 1.39) 1.27 (0.95, 1.70) 1.15 (0.83, 1.58) On the basis of multiple logistic regression analysis with assignment of ordinal numbers 0 3 to categories of rice, bread, or noodle intake. 2 Values are medians; ranges in parentheses. 3 Adjusted for age (y), study area (9 areas), smoking status (never, past, or current with a consumption of,20 or 20 cigarettes/d), alcohol consumption (for men: nondrinker, occasional drinker, or drinker with a consumption of,150, , , or 450 g ethanol/wk; for women: nondrinker, occasional drinker, or drinker with a consumption of,150 or 150 g ethanol/wk), family history of diabetes mellitus (yes or no), total physical activity (quartile of metabolic equivalent task hours per day), history of hypertension (yes or no), occupation (agriculture, forestry, or fishery; salaried, self-employed, or professional; or housework, unemployed, or retired), total energy intake (kcal/d), coffee consumption (almost never,,1, 1, or 2 cups/d), and intakes of calcium (mg/d), magnesium (mg/d), fiber (g/d), fruit (g/d), vegetables (g/d), fish (g/d). Intakes (according to g/d quartile) of rice, bread, and noodles were also mutually adjusted for. 4 Additionally adjusted for BMI (in kg/m 2 ;,21, , , , or 27). 5 Subjects with missing information were excluded (bread intake: n = 850 in men, n = 1155 in women; noodle intake: n = 2924 in men, n = 4303 in women). highest intake category compared with men in the lowest intake category (odds ratio: 0.81; 95% CI: 0.62, 1.05; P for trend = 0.08) (Table 2). However, the association was attenuated after adjustment for other covariates (fully adjusted odds ratio: 0.85; 95% CI: 0.64, 1.14; P for trend = 0.30). No association was observed between noodle intake and type 2 diabetes in either men or women. DISCUSSION In this large-scale, population-based, prospective study in Japanese adults, rice intake was shown to be associated with increased risk of type 2 diabetes in women. A significant increase in risk was observed in women with rice intakes 3 bowls (420 g)/d. The association between rice intake and type 2 diabetes risk was particularly pronounced in physically inactive women, nonobese

6 RICE INTAKE AND TYPE 2 DIABETES 1473 women, women who worked in jobs other than primary industries, and women who did not add minor cereals to rice. The overall association in men was not clear, although there was a suggestion of increased risk of type 2 diabetes with rice intake in physically inactive men and smoking men. Bread or noodle intake was not associated with risk of type 2 diabetes. Regarding evidence of a rice type 2 diabetes association in Asia, our study replicated previous finding in Chinese women (15). The current finding of an increased risk of type 2 diabetes associated with increased rice consumption is consistent with a previous result noted in a population in China (15), where white rice is consumed as a major staple food. In that previous study (15), women who consumed 300 g rice/d had a 1.8-fold greater risk of developing type 2 diabetes than did women who consumed,200 g rice/d. A similar association between diabetes risk and white rice consumption was observed in a US study (14). Furthermore, our findings appeared to agree with dietary pattern analyses for Japanese populations. Nanri et al (21) reported a higher prevalence of elevated glycated hemoglobin concentrations in persons with a high dietary pattern score characterized by frequent rice intake than in those with a low score. Our finding of decreased risk of type 2 diabetes in men with greater bread intake in an age- and area-adjusted model also agreed with previous findings of a Japanese study (8, 21). However, in our current study, this inverse association became nonsignificant after adjustment for covariates, including calcium and coffee intake. Because milk and coffee are commonly consumed with bread by Japanese and have been linked to a decreased risk of type 2 diabetes (22, 23), the roles of these items as confounders may account for the seemingly protective association between bread intake and type 2 diabetes risk. Taken together, these data suggested that, in Japanese, greater rice consumption contributes to an increased risk of type 2 diabetes, whereas a bread-eating dietary pattern (but not necessarily bread per se) is related to a decreased risk. The mechanism by which increased rice consumption increases risk of type 2 diabetes remains unclear. As shown in Table 1, increased rice consumption was associated with relatively lower intakes of other foods linked to lower risk of type 2 diabetes such as coffee and nutrients, such as magnesium and calcium (22 24). However, the association between rice intake and type 2 diabetes risk remained significant even after adjustment for these food factors, which suggested an independent role of white rice in the pathogenesis of type 2 diabetes. One plausible explanation is that white rice has a high glycemic index (25), which is a measure of the effect of food intake on blood glucose concentrations (26) and has been shown to predict type 2 diabetes risk (27). In a study of diabetic and prediabetic Japanese adults, the administration of dietary advice to lower the dietary glycemic index successfully helped participants reduce their glycated hemoglobin concentrations, which supported the importance of the dietary glycemic index in the prevention of type 2 diabetes in Japanese (28). For Japanese, white rice is the major contributor to the dietary glycemic load (29), which has been shown to increase risk of type 2 diabetes (27). Furthermore, a number of beneficial nutrients including insoluble fiber and magnesium, which are potentially protective against type 2 diabetes, are removed when producing polished white rice (9). Subjects with a higher intake of rice tended to have a lower BMI than those with a lower intake of rice (Table 1), which suggested that rice or a rice-based diet, probably because of its low fat content, may aid in obesity prevention better than a diet with low rice consumption, at least from an ecologic standpoint. Nevertheless, we noted an increased risk of type 2 diabetes in persons who consumed greater amounts of rice, which suggested that a high intake of rice may increase type 2 diabetes independent of BMI. This paradoxical association appears to explain from a dietary point of view why the prevalence of type 2 diabetes in Japanese is similarly as high as in Western populations, despite the much lower prevalence of obesity in Japanese than in Western populations, and why the difference in BMIs between Japanese with and without type 2 diabetes is much smaller than that observed in Western populations (30). High rice intake may increase the risk of type 2 diabetes through mechanisms other than obesity-related ones. We observed a marginally significant trend association between rice consumption and type 2 diabetes risk in men and women who did not engage in strenuous physical activity at work or in leisure time but not in subjects who did engage in such activity. This result underscored the importance of physical activity in the assessment of the diet-diabetes risk relation. More specifically, low physical activity may be a prerequisite condition for rice consumption to influence type 2 diabetes risk. If a large proportion of glucose is taken up and metabolized in muscle, high levels of physical activity may counterbalance elevated rice intake. This may have been the situation in the Japanese society in the past, and we speculate that the association between rice consumption and risk of type 2 diabetes observed in the current study may have emerged as sedentary lifestyles became more prevalent in Japan. Besides being physically active, can dietary modification attenuate type 2 diabetes risk associated with rice consumption? Because minor cereals are rich in magnesium and fiber and are potentially important food factors in the regulation of glucose absorption and metabolism (31), the addition of these to rice is expected to help reduce type 2 diabetes risk. We observed a more pronounced association between rice intake and type 2 diabetes risk in women after the exclusion of subjects who added minor cereals to rice, a finding that may indirectly support the protective role of minor cereals. Although the small number of minor cereal consumers in our study hindered an interpretation of the null result in them with reasonable confidence, previous intervention trials in Japan have shown that supplementing rice with minor cereals significantly reduced postprandial glucose concentrations (32, 33). We observed a more pronounced association between rice intake and type 2 diabetes in smoking men and nonobese women. The intake of carbohydrates with a high glycemic index increases insulin resistance and the demand for insulin (34). Because smoking is known to decrease b cell function (35), smokers may be more likely than nonsmokers to have higher glucose concentrations after high rice intake. Contrary to the anticipated adverse effects of high glycemic index foods in overweight persons (34), we observed an association between rice intake and type 2 diabetes risk in nonobese women but not in obese women. One possible explanation for this finding is that glucose metabolism in nonobese individuals, who are less able to secrete insulin than obese individuals (36, 37), may be more easily deteriorated by an increased demand for insulin after rice intake. Major strengths of the current study included our large sample size, the population-based prospective design, the use of

7 1474 NANRI ET AL TABLE 3 Odds ratios (and 95% CIs) of type 2 diabetes according to rice intake by strenuous physical activity, occupation, age, BMI, smoking status, and menopausal status 1 Men Women Quartiles of rice intake Quartiles of rice intake Lowest Second Third Highest P for trend 2 Lowest Second Third Highest P for trend 2 Strenuous physical activity,1 h/d No. of cases/subjects 90/ / / / / / / /2006 Multivariable adjusted (ref) 1.26 (0.95, 1.68) 1.58 (1.09, 2.29) 1.36 (0.86, 2.17) (ref) 1.23 (0.86, 1.76) 1.39 (0.95, 2.03) 1.55 (0.90, 2.66) h/d No. of cases/subjects 29/ / / / /884 13/ /2193 9/656 Multivariable adjusted (ref) 1.49 (0.93, 2.39) 0.83 (0.44, 1.55) 1.20 (0.62, 2.33) (ref) 0.57 (0.24, 1.32) 1.27 (0.56, 2.87) 1.13 (0.35, 3.62) 0.30 P for interaction Occupation Primary industries No. of cases/subjects 24/ / / / /999 27/ / /1325 Multivariable adjusted (ref) 1.63 (0.99, 2.68) 1.36 (0.74, 2.50) 1.03 (0.51, 2.06) (ref) 1.11 (0.52, 2.39) 1.30 (0.61, 2.74) 0.91 (0.36, 2.32) 0.99 Other than primary industries No. of cases/subjects 116/ / / / / / / /1668 Multivariable adjusted (ref) 1.15 (0.89, 1.49) 1.19 (0.84, 1.68) 1.29 (0.86, 1.96) (ref) 1.17 (0.84, 1.63) 1.49 (1.04, 2.14) 1.87 (1.09, 3.20) P for interaction Age,60 y No. of cases/subjects 89/ / / / / / / /2072 Multivariable adjusted (ref) 1.17 (0.88, 1.56) 1.27 (0.89, 1.80) 1.17 (0.77, 1.78) (ref) 1.11 (0.72, 1.70) 1.63 (1.06, 2.52) 1.64 (0.90, 2.98) y No. of cases/subjects 58/ / / / / / / /1030 Multivariable adjusted (ref) 1.41 (0.98, 2.03) 1.15 (0.68, 1.94) 1.20 (0.65, 2.19) (ref) 1.18 (0.78, 1.80) 1.34 (0.85, 2.11) 1.51 (0.75, 3.02) 0.18 P for interaction BMI,25 kg/m 2 No. of cases/subjects 68/ / / / / / / /2207 Multivariable adjusted (ref) 1.37 (1.00, 1.88) 1.13 (0.74, 1.73) 1.28 (0.78, 2.10) (ref) 1.46 (0.88, 2.40) 2.59 (1.55, 4.32) 2.78 (1.38, 5.59), kg/m 2 No. of cases/subjects 79/ / / /978 49/ / / /848 Multivariable adjusted (ref) 1.12 (0.81, 1.53) 1.26 (0.84, 1.90) 1.18 (0.72, 1.92) (ref) 0.98 (0.66, 1.45) 1.04 (0.69, 1.58) 1.16 (0.63, 2.13) 0.63 P for interaction Smoking status Nonsmoker No. of cases/subjects 93/ / / /2029 Multivariable adjusted (ref) 1.01 (0.75, 1.37) 0.89 (0.58, 1.36) 0.94 (0.58, 1.54) 0.68 Current smoker No. of cases/subjects 52/ / / /2004 Multivariable adjusted (ref) 1.59 (1.12, 2.25) 1.70 (1.11, 2.59) 1.55 (0.94, 2.57) 0.11 P for interaction 0.06 (Continued)

8 RICE INTAKE AND TYPE 2 DIABETES 1475 TABLE 3 (Continued) Men Women Quartiles of rice intake Quartiles of rice intake Lowest Second Third Highest P for trend 2 Lowest Second Third Highest P for trend 2 Menopausal status Premenopausal women No. of cases/subjects 11/ / / /751 Multivariable adjusted (ref) 1.05 (0.47, 2.36) 2.01 (0.90, 4.48) 2.62 (0.93, 7.41) 0.02 Postmenopausal women No. of cases/subjects 61/ / / /2170 Multivariable adjusted (ref) 1.15 (0.82, 1.62) 1.47 (1.03, 2.11) 1.55 (0.92, 2.62) 0.02 P for interaction ref, reference. 2 On the basis of multiple logistic regression analysis with assignment of ordinal numbers 0 3 to categories of rice intake. 3 Adjusted for age (y), study area (9 areas), smoking status (never, past, or current with a consumption of,20 or 20 cigarettes/d), alcohol consumption (for men: nondrinker, occasional drinker, or drinker with a consumption of,150, , , or 450 g ethanol/wk; for women: nondrinker, occasional drinker, or drinker with a consumption of,150 or 150 g ethanol/wk), family history of diabetes mellitus (yes or no), history of hypertension (yes or no), occupation (agriculture, forestry, or fishery; salaried, self-employed, or professional; or housework, unemployed, or retired), total energy intake (kcal/d), coffee consumption (almost never,,1, 1, or 2 cups/d), and intakes of calcium (mg/d), magnesium (mg/d), fiber (g/d), fruit (g/d), vegetables (g/d), fish (g/d), bread (g/d quartile), noodles (g/d quartile), and BMI (in kg/m 2 ;,21, , , , or 27). 4 Adjusted for the same variables as in footnote 3 with the exception of occupation. 5 Adjusted for total physical activity (quartile of metabolic equivalent task hours per day) in addition to the same variables in footnote 3. 6 Adjusted for the same variables as in footnote 5, but BMI was used as a continuous variable. 7 Adjusted for the same variables as in footnote 5 with the exception of smoking.

9 1476 NANRI ET AL a validated FFQ, and adjustment for or stratification by potentially important confounding variables. Furthermore, gathering data from a Japanese population allowed us to assess any potential association at relatively extremely high amounts of rice consumption (rice intake for the highest category in men was.560 g/d). However, several limitations to the current study warrant mention. First, the diagnosis of type 2 diabetes was ascertained by self-report. However, a validation study conducted in our study population showed fairly good agreement between selfreported diabetes and diabetes as documented in medical records (94%), and the sensitivity of self-reported diabetes was reasonably high (83%). Nevertheless, the misclassification of outcomes may have distorted the results to some extent. Second, dietary intakes were measured only once and thus may not have reflected long-term intake. Repeated assessment of diet over a long period of time before disease onset will likely provide a better estimate of exposure status. Third, although whole-grain consumption has been reported to reduce risk of developing type 2 diabetes (38), we gathered no information about the type of grains consumed by our study population. However, because of the limited market for whole grains in Japan, the rice consumed in the current study population may have been only or largely white rice (refined grains). Finally, results obtained in subgroup analyses may be due to chance and, thus, should be interpreted with caution. The findings from this large-scale prospective study suggested that an increased intake of rice increases risk of developing type 2 diabetes in Japanese women. The rice-centered Japanese diet is characterized by low fat intakes and has major advantages over a Western-style diet in terms of contributing to cardiovascular health (39); however, the same may not be true for the prevention of type 2 diabetes. For Japanese or other populations who consume rice as a major staple food, dietary modification strategies should be explored to prevent type 2 diabetes without increasing risk of cardiovascular disease. Members of the JPHC Study group are as follows: S Tsugane, M Inoue, T Sobue, and T Hanaoka (National Cancer Center, Tokyo, Japan); J Ogata, S Baba, T Mannami, A Okayama, and Y Kokubo (National Cardiovascular Center, Osaka, Japan); K Miyakawa, F Saito, A Koizumi, Y Sano, I Hashimoto, T Ikuta, and Y Tanaba (Iwate Prefectural Ninohe Public Health Center, Iwate, Japan); Y Miyajima, N Suzuki, S Nagasawa, Y Furusugi, and N Nagai (Akita Prefectural Yokote Public Health Center, Akita, Japan); H Sanada, Y Hatayama, F Kobayashi, H Uchino, Y Shirai, T Kondo, R Sasaki, Y Watanabe, Y Miyagawa, and Y Kobayashi (Nagano Prefectural Saku Public Health Center, Nagano, Japan); Y Kishimoto, E Takara, T Fukuyama, M Kinjo, M Irei, and H Sakiyama (Okinawa Prefectural Chubu Public Health Center, Okinawa, Japan); K Imoto, H Yazawa, T Seo, A Seiko, F Ito, F Shoji, and R Saito (Katsushika Public Health Center, Tokyo, Japan); A Murata, K Minato, K Motegi, and T Fujieda (Ibaraki Prefectural Mito Public Health Center, Ibaraki, Japan); K Matsui, T Abe, M Katagiri, and M Suzuki (Niigata Prefectural Kashiwazaki and Nagaoka Public Health Center, Niigata, Japan); M Doi, A Terao, Y Ishikawa, and T Tagami (Kochi Prefectural Chuo-higashi Public Health Center, Kochi, Japan); H Sueta, H Doi, M Urata, N Okamoto, and F Ide (Nagasaki Prefectural Kamigoto Public Health Center, Nagasaki, Japan); H Sakiyama, N Onga, H Takaesu, and M Uehara (Okinawa Prefectural Miyako Public Health Center, Okinawa, Japan); F Horii, I Asano, H Yamaguchi, K Aoki, S Maruyama, M Ichii, and M Takano (Osaka Prefectural Suita Public Health Center, Osaka, Japan); Y Tsubono (Tohoku University, Miyagi, Japan); K Suzuki (Research Institute for Brain and Blood Vessels Akita, Akita, Japan); Y Honda, K Yamagishi, S Sakurai, and N Tsuchiya (Tsukuba University, Ibaraki, Japan); M Kabuto (National Institute for Environmental Studies, Ibaraki, Japan); M Yamaguchi, Y Matsumura, S Sasaki, and S Watanabe) National Institutes of Health and Nutrition, Tokyo, Japan); M Akabane (Tokyo University of Agriculture, Tokyo, Japan); T Kadowaki (Tokyo University, Tokyo, Japan); M Noda and T Mizoue (International Medical Center of Japan, Tokyo, Japan); Y Kawaguchi (Tokyo Medical and Dental University, Tokyo, Japan); Y Takashima and M Yoshida (Kyorin University, Tokyo, Japan); K Nakamura (Niigata University, Niigata, Japan); S Matsushima and S Natsukawa (Saku General Hospital, Nagano, Japan); H Shimizu (Sakihae Institute, Gifu, Japan); H Sugimura (Hamamatsu University, Shizuoka, Japan); S Tominaga (Aichi Cancer Center Research Institute, Aichi, Japan); H Iso (Osaka University, Osaka, Japan); M Iida, WAjiki, and A Ioka (Osaka Medical Center for Cancer and Cardiovascular Disease, Osaka, Japan); S Sato (Chiba Prefectural Institute of Public Health, Chiba, Japan); E Maruyama (Kobe University, Hyogo, Japan); M Konishi, K Okada, and I Saito (Ehime University, Ehime, Japan); N Yasuda (Kochi University, Kochi, Japan); and S Kono (Kyushu University, Fukuoka, Japan). 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