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Nutritional Epidemiology

Dietary Patterns and Glucose Tolerance Abnormalities in Japanese Men¹

Tetsuya Mizoue^*,2, Taiki Yamaji^*, Shinji Tabata^*,, Keizo Yamaguchi^*,**, Shinsaku Ogawa, Masamichi Mineshita^** and Suminori Kono^*

^* Department of Preventive Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan; Self-Defense Forces, Fukuoka Hospital, Kasuga, Japan; and ^** Self-Defense Forces, Kumamoto Hospital, Kumamoto, Japan

² To whom correspondence should be addressed. E-mail: mizoue{at}phealth.med.kyushu-u.ac.jp.

	ABSTRACT

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The Western dietary pattern appears to confer diabetes risk, but the role of dietary patterns in Asian populations remains unclear. We investigated the association between major dietary patterns and the glucose tolerance status of Japanese men. Abnormalities included impaired fasting glucose, impaired glucose tolerance, and type 2 diabetes. Subjects were 2106 Japanese men who were administered a 75-g oral glucose tolerance test at their preretirement health check-ups. Information about diet was obtained using a 74-item FFQ before the test. Three dietary patterns were generated by factor analysis: 1) a high-dairy, high-fruit and -vegetable, high-starch, low-alcohol pattern; 2) an animal food pattern; and 3) a Japanese pattern. We used logistic regression analysis to estimate odds ratios (OR) with adjustment for potential confounding variables. A significant inverse association was found for the high-dairy, high-fruit and -vegetable, high-starch, low-alcohol pattern (P for trend < 0.0001); the OR of having a glucose tolerance abnormality (impaired fasting glucose, impaired glucose tolerance, or type 2 diabetes) for the 2nd, 3rd, and 4th quartiles were 0.80 (95% CI = 0.62–1.04), 0.71 (95% CI = 0.54–0.92), and 0.51 (95% CI = 0.38–0.67), respectively, compared with the lowest quartile. The inverse association was consistent for each glucose tolerance abnormality as well as across subgroups stratified by risk factors for diabetes. The Japanese dietary pattern was positively associated with impaired glucose tolerance (P for trend = 0.048). A dietary pattern characterized by frequent consumption of dairy products and fruits and vegetables but low alcohol intake may be associated with a decreased risk of developing a glucose tolerance abnormality.

KEY WORDS: • dietary pattern • factor analysis • impaired fasting glucose • impaired glucose tolerance • type 2 diabetes

The prevalence of type 2 diabetes is increasing worldwide (1). A recent Japanese survey showed that 9% of the adult population have known or suspected diabetes, and another 11% may also have diabetes (2). The age-specific prevalence of diabetes in Japanese subjects is slightly higher than that in European populations (3,4). The results of these surveys seem peculiar in light of the fact that obesity is not as prevalent in Japanese patients with type 2 diabetes as in Caucasian patients (5). This may be attributable in part to a high genetic susceptibility to type 2 diabetes of Japanese individuals (6); however, little is known about the role of diets typically consumed by the Japanese.

Analysis of dietary patterns has received much attention as a method of investigating the role of diet in studies of chronic diseases. Approaches of this sort, focusing on a combination of several foods, can overcome problems arising from the close intercorrelation and potential effect modulation among numerous foods or nutrients (7,8). Of factor-analysis studies among Western populations (9–12), some (11,12) indicated that a Western dietary pattern characterized by a greater consumption of high-energy, high-fat foods predicts diabetes risk. However, dietary patterns generated by factor analysis may differ across populations with different dietary cultures. The high consumption of rice, fish, and soybean products in Japan (13) suggests several different dietary patterns in Japanese populations.

The aim of the present study was therefore to investigate dietary patterns in relation to glucose tolerance status, using data from preretirement health examinations of Japanese men who were self-defense officials.

	SUBJECTS AND METHODS

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    Study procedure. The data used were derived from the Self-Defense Forces Health Study, a cross-sectional survey of men who were self-defense officials and participated in a preretirement health check-up at 2 hospitals (Fukuoka and Kumamoto) in Japan. The study procedure was described elsewhere (14–16). Study questionnaires regarding smoking, drinking, leisure-time physical activity, diet, and other health-related information were distributed before the test to male examinees on d 1 of hospital admission for examination. For leisure-time physical activity, the men were asked about the weekly frequency and the duration of each activity on each occasion for up to 3 types of activity. Research assistants checked the questionnaire and, if necessary, sought clarification from the study subjects. Results of physical measurements and laboratory tests were extracted from clinical reports. Written informed consent was obtained from study participants. The study protocol was approved by the ethics committee of Kyushu University.

    Study subjects. Among 2377 male self-defense officials who underwent the examination from April 1999 through March 2002, 2370 men aged 47–59 y (mean, 52.4 y) agreed to participate in the study. After excluding men with a history of cancer, stroke, myocardial infarction, coronary revascularization, inflammatory bowel diseases, colorectal surgery, or diabetes mellitus, 2141 men were included for the analysis of dietary patterns. After further exclusion of 35 men who had a history of gastrectomy, a condition that might affect the oral glucose tolerance test result, we analyzed the data for the remaining 2106 men to assess the association between dietary patterns and glucose tolerance status.

    Glucose measurements. All officials undergo a comprehensive health examination before retirement; the exam includes a 75-g oral glucose tolerance test as a routine procedure. After an overnight fast, venous blood was drawn for measurement of plasma glucose before and 2 h after the oral glucose load. Examinees whose fasting plasma glucose concentration at admission was 7.0 mmol/L or who were under medical care for diabetes were not given an oral glucose tolerance test. Plasma glucose concentrations were measured by the glucose oxidase method using commercial reagents (Shino Test).

    Dietary assessment. Information about diet was collected using a FFQ designed to assess the average intake of 74 foods, food groups, and food preparations over the previous year. The questionnaire was an expanded version of a 45-item FFQ that was developed on the basis of a published questionnaire (17) and was validated against four 7-d records, collected each season (18). The expansion of food items was done with reference to food consumption in the National Nutrition Survey (13) and a dietary questionnaire developed elsewhere in Japan (19). Participants were asked to choose from 7 response options for most dietary items, ranging from "never/<1 time/mo" to "2–3 times/d." Different response schemes were used for green tea, coffee, and rice (5 options), and alcoholic beverages (6 options). Daily consumers of green tea, coffee, or rice were asked about the number of cups or bowls consumed per day. Current drinkers, defined as those who consumed alcoholic beverages weekly for at least 1 y in their lifetime and who were drinking at the time of the survey, were asked about the frequency of consumption and the amount consumed per occasion of 5 alcoholic beverages, that is, sake (a Japanese wine), shochu (a Japanese distilled beverage), beer, whiskey, and wine. The amount consumed per occasion was used in the estimation of total ethanol intake from these alcoholic beverages, but only the frequency of consumption for each alcoholic beverage was used in the analysis of dietary patterns.

Before the analysis of dietary patterns, intakes of green tea, coffee, or rice were converted into units of cups or bowls per day, whereas those of other dietary items were quantified in terms of frequency per week. Five dietary questions that overlapped with or were duplicated by others (collective consumption of cooked vegetables, apple, tangerine, other orange, watermelon) and 3 questions about food spreads (butter, margarine, and jam/honey) were not included. Furthermore, some foods or food groups similar in nutritional contents or culinary use were combined (Appendix 1), leaving 39 food items for purposes of the present study.

    Statistical analysis. The method used in generating dietary patterns and the naming of the derived patterns were described in our previous study of colorectal adenomas (16). Dietary patterns were generated by factor analysis (principal components). Factor analysis is a technique used to reduce a number of variables into fewer independent factors. To simplify interpretation, a linear transformation called a "rotation" is normally performed on the initial factor solution. We used an orthogonal rotation procedure (varimax rotation), which maintains the uncorrelated nature of the factors. In determining the number of factors to retain, we considered the scree test and interpretability. The scree plot and postrotated factor loadings revealed that 3 factors described comprehensively the distinctive dietary patterns of the study population. We thus retained the 3 patterns and designated them as follows: 1) a high-dairy, high-starch, high-fruit and -vegetable, low-alcohol (DSFA)³ pattern; 2) an animal food pattern; and 3) a Japanese pattern, according to the food items showing high loading (absolute value) with respect to each dietary pattern (Table 1). We confirmed that these dietary factors emerged when all 74 food items in our questionnaire were simply included in factor analysis and that patterns of loading with the dietary factors were similar among foods or food groups combined. A factor score for each dietary pattern was calculated by weighting standardized consumption of each food item by the corresponding factor loading and summing the resulting values. This score ranked individuals in terms of how closely they conformed to the dietary pattern.

	RESULTS

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Factor loadings are equivalent to simple correlations between the food items and the dietary patterns. A positive loading indicates that the food item is positively associated with the dietary pattern, and a negative loading indicates an inverse association with the dietary pattern. The DFSA dietary pattern was characterized by frequent intake of fermented dairy products, milk, confectioneries, bread, fruits, and vegetables, and infrequent intake of shochu, a local alcoholic beverage in the study area (Table 1). The animal food dietary pattern was characterized by various kinds of animal foods, including red meat, poultry, seafood excluding fish, processed meat and fish products, and fried or broiled foods. The Japanese dietary pattern was characterized by foods traditionally consumed in Japan (soybean products, seaweeds, pickles, and green tea), vegetables, and fish. The proportion of the total variance explained by the 3 factors was 24%.

The 3 dietary patterns were related to some of the potential confounding variables and alcohol consumption (Table 2). Examinees at Kumamoto hospital had a higher score for the Japanese dietary pattern but lower scores for the DFSA and animal food dietary patterns than those at Fukuoka hospital. Men with a higher score for the DFSA dietary pattern engaged in higher levels of leisure-time physical activity and consumed smaller amounts of alcohol; in addition, they had a higher proportion of nonsmokers than those with a lower score. Men with a higher score for the animal food dietary pattern had higher BMI and consumed larger amounts of alcohol. Men with a higher score for the Japanese dietary pattern engaged in higher levels of leisure-time physical activity, consumed greater amounts of alcohol, and had a higher proportion of nonsmokers than those with a lower score.

	DISCUSSION

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Our study has several strengths. Glucose tolerance status was determined on the basis of an oral glucose tolerance test. Selection bias in terms of study participation was unlikely because of nonselective recruitment for the preretirement health examination and high study participation rate. The questionnaire was distributed and collected before the oral glucose tolerance test, and the data for subjects with a history of diabetes were excluded; thus, recall bias associated with glucose tolerance status was also unlikely. We controlled for major known or suspected confounding factors. Moreover, because the study participants were homogeneous in terms of occupation, sex, and age, the results were less likely to be biased by unknown or unmeasured confounding factors.

The present study also has some limitations. According to the validation study for the former version of the dietary questionnaire (14), including questions and response options similar to those of the current questionnaire, most nutrients and foods demonstrated fairly good correlation between the dietary record and the questionnaire; the correlation coefficients (r) of 0.80, 0.77, and 0.58 for bread, fruits, and dairy products, major food items of the DFSA dietary pattern, were relatively high. Therefore, bias associated with nondifferential misclassification in dietary assessment may be minimal for the analysis of the DFSA dietary pattern. On the other hand, the correlation between the dietary record and the questionnaire was moderate for meat (r = 0.48), poultry (r = 0.59), fish (r = 0.51), fermented soybean (r = 0.52), and vegetables (r = 0.40), and this may be a reason for the lack of an apparent association for the animal food or Japanese dietary patterns. Another issue regarding dietary assessment is that the calculation and validation of total energy and nutrient intakes from the present questionnaire have yet not been completed. Men with a high score on a dietary pattern likely consumed more energy than those with a low score; high energy intake usually increases the risk of type 2 diabetes, and the lack of adjustment for energy intake may cause a superfluous positive association. However, energy adjustment only strengthens, rather than diminishes the inverse association between DSFA dietary pattern and glucose tolerance abnormalities, the major finding of the present study. However, we cannot exclude the possibility that the positive trend association between the Japanese dietary pattern and impaired glucose tolerance was a result of confounding by energy intake.

Limitations of factor analysis arise from arbitrary decisions (7,8) involved in selecting and grouping foods for analysis from the questionnaire, in determining the number of factors to retain, in choosing the method of rotation of the initial factors to increase the interpretability of dietary patterns, and in labeling dietary patterns according to their factor loadings. Using factor analysis, Masaki et al. (22) identified a Western breakfast dietary pattern (similar to the DFSA pattern) and an animal dietary pattern in a cohort of men in Tokyo. Kim et al. (23) identified 3 major dietary patterns in a nationwide cohort in Japan: a healthy dietary pattern (similar to the DFSA pattern), a traditional dietary pattern (similar to the Japanese pattern), and a Western dietary pattern (similar to the animal food pattern). These findings suggest the existence of dietary patterns common to the Japanese. However, we also found important differences in loading patterns among these studies. For example, soybean products and seaweeds, which were the most closely correlated with the Japanese dietary pattern in our study, had the highest loadings with a healthy dietary pattern (similar to the DFSA pattern) in another study (23). Therefore, further exploratory studies are required to clarify dietary patterns among the Japanese before this approach is used.

The inverse association between the DFSA pattern and glucose tolerance abnormalities may represent beneficial effects of each food or nutrient contributing to the dietary pattern on glucose metabolism. Results of prospective studies (24–27) suggested that the intake of fruits and/or vegetables is inversely related to the risk of developing type 2 diabetes. Substancesrich in fruits and vegetables that were linked to a decreased risk of diabetes or insulin resistance include fiber (28), carotenoids (29), and magnesium (30). Milk consumption was strongly associated with a decreased risk of developing obesity and the insulin resistance syndrome (31), which are key risk factors for type 2 diabetes. Calcium reduces insulin resistance (32), but other substances in milk may also play a role. In addition to independent effects, there may be complex interactions among food factors constituting the DFSA dietary pattern. Note that the DFSA pattern is similar to the Dietary Approaches to Stop Hypertension (DASH) dietary pattern (33) in that both are rich in fruits, vegetables, and dairy products, and that the DASH diet not only reduces blood pressure (33) but also improves insulin metabolism (34).

Both shochu and beer, 2 major alcohol beverages consumed by the study population, were inversely associated with the DFSA dietary pattern (Appendix 2), and men with the lowest quartile of the DFSA pattern score consumed considerably large amounts of alcohol (Table 2). Heavy drinking has been consistently related to increased diabetes risk, whereas moderate drinking may decrease the risk (35). The clear inverse gradient in alcohol consumption may thus account for the decreased odds of glucose tolerance abnormality among men with a higher score for the DFSA dietary pattern.

Confectionaries and soft drinks, which were positively related to the DFSA dietary pattern, may worsen the glucose metabolism due to the potentially detrimental effect of diets high in simple sugars on insulin sensitivity (36). However, epidemiologic evidence is conflicting (37,38). Furthermore, the effect of sugars on glycemic response is greatly attenuated when individuals consume >100 g of carbohydrates (39), as is the case for most Japanese (13) who eat rice as their staple food. Therefore, confectionaries and soft drinks may not play a large role in glucose metabolism in the study subjects. It would also be worth noting that not all food items associated with the DFSA pattern are necessarily causally related to outcome.

The Japanese dietary pattern was characterized by high consumption of traditional Japanese foods (soybean products, seaweeds, pickles, fish, and green tea) and vegetables. Because phytoestrogens in soy protein (40), polyphenols in green tea (41), and (n-3) PUFA rich in fish (42) are suggested to improve glucose metabolism, the Japanese dietary pattern may likely decrease the risk of type 2 diabetes. However, we found no such association; conversely, the Japanese dietary pattern showed a significant, positive association with impaired glucose tolerance. We have no ready reason for this outcome, but some nutritional characteristics of the Japanese diet (for instance, high in refined carbohydrate but low in protein) may adversely affect glucose metabolism beyond the aforementioned beneficial effects of Japanese foods.

Components of the animal food dietary pattern included meats and marine animal foods except fish. Higher scores of this pattern likely accompany greater consumption of fat, especially saturated fat, which may increase the risk of diabetes (42). Western studies (11,12) suggested that the Western dietary pattern, characterized by frequent red meat intake, confers a risk of type 2 diabetes. In the present study, however, the animal food dietary pattern was not apparently associated with an abnormality in glucose tolerance. The lack of an association may reflect moderate consumption of meat in the Japanese population; mean daily intake in men aged 40–49 y is 100 g for total meat (13). In the subjects in this study, the mean weekly frequency of consumption was only 1.8 and 1.0 for red and processed meat, respectively (Appendix 2).

In conclusion, the present results indicate that a dietary pattern characterized by frequent consumption of dairy products, confectionaries, fruits, and vegetables but a low intake of local alcoholic beverages may be associated with a reduced risk of impaired fasting glucose, impaired glucose tolerance, and type 2 diabetes in Japanese men. Although our finding must be confirmed by prospective studies including women and individuals with various occupational backgrounds, an intervention to change dietary patterns may decrease type 2 diabetes risk in the Japanese population, whose consumption of dairy foods and fruits is currently low (43).

	APPENDIX 1

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List of the combined food items

Food item Foods or food groups combined Seafood, except fish Cuttlefish/octopus, shrimp/crab, oyster/shellfish Soybean products Miso soup, tofu, natto (fermented soybeans) Pickles Pickled ume, pickled scallion, pickled vegetables Raw vegetables Tomato, cucumber, cabbage, lettuce, Chinese radish/turnip, onion Vegetable juice Tomato juice, other juice Heated vegetables Carrot, pumpkin, onion, green pepper, spinach, leek Seaweeds Wakame, hijiki/konbu Canned/dried fruits Canned fruits, dried fruits Fermented dairy products Yogurt, cheese Confectionary Chocolate, caramel/candy, cake, Japanese cake, sweetened bun Fried foods Tempura/other deep-fried foods, fried foods Broiled fish/broiled meat, all kinds Broiled fish, broiled red meat, broiled chicken

	APPENDIX 2

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Intakes of selected dietary items according to quartile of dietary pattern score among Japanese men¹

DFSA dietary pattern Animal food dietary pattern Japanese dietary pattern Dietary item All subjects 1 (low) 2, 3 4 (high) 1 (low) 2, 3 4 (high) 1 (low) 2, 3 4 (high) n/wk Red meat 1.8 ± 1.4 1.9 ± 1.5 1.7 ± 1.3 1.9 ± 1.6 0.7 ± 0.6 1.8 ± 1.1 3.0 ± 1.5 1.9 ± 1.5 1.8 ± 1.3 1.7 ± 1.4 Processed meat 1.0 ± 1.2 0.8 ± 1.0 1.0 ± 1.2 1.3 ± 1.4 0.5 ± 0.6 0.9 ± 1.0 1.8 ± 1.6 1.1 ± 1.3 1.0 ± 1.1 1.0 ± 1.3 Poultry 1.5 ± 1.2 1.6 ± 1.4 1.5 ± 1.2 1.5 ± 1.2 0.7 ± 0.5 1.4 ± 1.0 2.6 ± 1.3 1.4 ± 1.1 1.5 ± 1.2 1.7 ± 1.4 Fish 3.2 ± 1.9 3.5 ± 2.4 3.1 ± 1.8 3.2 ± 1.8 2.5 ± 1.7 3.2 ± 1.8 3.9 ± 2.1 2.3 ± 1.3 3.1 ± 1.8 4.2 ± 2.3 Seafood, except fish (3)2 2.3 ± 2.2 2.0 ± 2.0 2.2 ± 2.0 2.8 ± 2.5 1.3 ± 1.2 2.1 ± 1.7 3.8 ± 2.8 1.8 ± 1.5 2.4 ± 2.2 2.8 ± 2.4 Egg 3.4 ± 2.6 3.3 ± 2.4 3.3 ± 2.7 3.6 ± 2.6 2.3 ± 2.2 3.4 ± 2.3 4.5 ± 2.9 2.7 ± 2.2 3.3 ± 2.4 4.1 ± 3.0 Milk 3.8 ± 3.6 2.2 ± 2.3 3.6 ± 3.3 5.6 ± 4.4 3.7 ± 3.9 3.7 ± 3.6 3.9 ± 3.2 3.2 ± 3.4 3.8 ± 3.5 4.3 ± 3.9 Fermented dairy products (2)2 2.2 ± 2.7 0.8 ± 1.0 1.8 ± 1.9 4.3 ± 3.9 2.3 ± 3.4 2.1 ± 2.5 2.3 ± 2.4 2.0 ± 2.8 2.0 ± 2.3 2.8 ± 3.3 Fruits, not canned/dried 2.7 ± 2.6 1.4 ± 1.6 2.6 ± 2.2 4.4 ± 3.3 2.5 ± 2.8 2.8 ± 2.6 2.9 ± 2.5 2.1 ± 2.2 2.7 ± 2.5 3.5 ± 3.0 Raw vegetables (6)2 14.6 ± 9.4 10.8 ± 6.4 13.8 ± 7.7 20.0 ± 12.1 13.2 ± 10.0 14.2 ± 9.5 16.6 ± 8.1 9.6 ± 6.0 13.7 ± 6.9 21.4 ± 12.2 Cooked vegetables (6)2 10.0 ± 7.2 7.4 ± 5.7 9.7 ± 6.5 13.1 ± 8.7 8.2 ± 7.3 9.6 ± 7.2 12.4 ± 6.7 5.8 ± 3.9 9.0 ± 5.5 16.0 ± 8.8 Seaweeds (2)2 3.7 ± 3.2 2.8 ± 2.6 3.6 ± 3.2 4.7 ± 3.4 3.4 ± 3.4 3.5 ± 3.0 4.4 ± 3.2 1.8 ± 1.5 3.4 ± 2.6 6.2 ± 3.8 Soybean products (3)2 13.6 ± 7.2 13.4 ± 6.8 13.2 ± 6.9 14.7 ± 8.0 13.8 ± 8.0 13.2 ± 6.7 14.4 ± 7.1 8.4 ± 4.5 13.2 ± 5.1 19.7 ± 8.4 Pickles (3)2 8.2 ± 6.0 7.4 ± 5.9 7.8 ± 5.4 9.6 ± 6.8 7.9 ± 6.8 8.0 ± 5.8 8.8 ± 5.4 4.7 ± 3.5 7.8 ± 4.9 12.3 ± 7.3 Rice3 3.0 ± 1.0 3.1 ± 1.0 3.0 ± 1.0 2.8 ± 1.0 3.1 ± 1.0 2.9 ± 1.0 3.0 ± 1.0 2.6 ± 1.0 3.0 ± 0.9 3.2 ± 0.9 Bread 1.5 ± 2.2 0.5 ± 0.8 1.3 ± 1.8 3.0 ± 2.9 1.4 ± 2.3 1.6 ± 2.1 1.6 ± 2.2 3.0 ± 3.0 1.2 ± 1.6 0.8 ± 1.4 Confectionary (5)2 2.6 ± 3.2 0.9 ± 1.2 2.3 ± 2.3 5.1 ± 4.4 1.9 ± 2.7 2.6 ± 3.0 3.4 ± 3.7 3.1 ± 3.4 2.5 ± 3.1 2.4 ± 3.1 Green tea4 3.3 ± 2.4 3.6 ± 2.5 3.3 ± 2.3 3.3 ± 2.4 3.8 ± 2.5 3.3 ± 2.4 3.0 ± 2.2 2.0 ± 1.7 3.3 ± 2.1 4.8 ± 2.7 Shochu 3.0 ± 2.9 4.7 ± 2.7 2.8 ± 2.8 1.5 ± 2.3 2.3 ± 2.8 3.0 ± 2.9 3.5 ± 2.9 1.8 ± 2.6 3.2 ± 2.9 3.7 ± 2.9 Beer 3.0 ± 2.8 3.9 ± 2.8 2.9 ± 2.7 2.4 ± 2.6 1.7 ± 2.3 3.2 ± 2.7 3.9 ± 2.7 2.8 ± 2.8 3.2 ± 2.8 3.0 ± 2.8

¹ Values are means ± SD.

² Combined food items (number of foods or food groups combined).

³ Bowls/d.

⁴ Cups/d.

	FOOTNOTES

 
¹ Funded by Grant-in-Aid for Scientific Research on Priority Areas (12218226) from the Ministry of Education, Culture, Sports, Science and Technology, Japan; and the Third Term Comprehensive 10-year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare, Japan.

³ Abbreviations used: DASH, Dietary Approaches to Stop Hypertension; DFSA, high-dairy, high-fruit and -vegetable, high-starch, low-alcohol (dietary pattern); MET, metabolic equivalent; OR, odds ratio.

Manuscript received 29 November 2005. Initial review completed 24 January 2006. Revision accepted 28 February 2006.

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