Dietary Patterns and the Incidence of Type 2 Diabetes
Jukka Montonen1 ,
Paul Knekt1,2,
Tommi Härkänen1,
Ritva Järvinen3,
Markku Heliövaara1,
Arpo Aromaa1 and
Antti Reunanen1
1 National Public Health Institute, Helsinki, Finland.
2 Social Insurance Institution, Helsinki and Turku, Finland.
3 University of Kuopio, Kuopio, Finland.
Received for publication March 26, 2004; accepted for publication July 15, 2004.
 |
ABSTRACT
|
---|
Major dietary patterns were studied for the ability to predict type 2 diabetes mellitus in a cohort of 4,304 Finnish men and women aged 4069 years and free of diabetes at baseline in 19671972. Factor analysis was used to identify dietary patterns from dietary data that were collected using a 1-year dietary history interview. A total of 383 incident cases of type 2 diabetes occurred during a 23-year follow-up. Two major dietary patterns were identified. The pattern labeled "prudent" was characterized by higher consumption of fruits and vegetables, and the pattern labeled "conservative" was characterized by consumption of butter, potatoes, and whole milk. The relative risks (adjusted for nondietary confounders) between the extreme quartiles of the pattern scores were 0.72 (95% confidence interval: 0.53, 0.97; ptrend = 0.03) for the prudent pattern and 1.49 (95% confidence interval: 1.11, 2.00; ptrend = 0.01) for the conservative pattern. Thus, the prudent dietary pattern score was associated with a reduced risk and the conservative pattern score was associated with an increased risk of type 2 diabetes. In light of these results, it appears conceivable that the risk of developing type 2 diabetes can be reduced by changing dietary patterns.
diabetes mellitus, type 2; diet; food habits; prospective studies
Abbreviations:
CI, confidence interval.
 |
INTRODUCTION
|
---|
The main interest in the link between dietary factors and risk of type 2 diabetes has been focused on individual nutrients or food items (1). However, this approach is apparently confounded by the effect of dietary patterns (2). Instead of isolated nutrients, people eat meals mixing different foods, giving several nutrients a chance to interact. These interactions between nutrients may potentially confound dietary studies. Multicollinearity between nutrients has also made it extremely difficult to separate the effect of individual nutrients in observational dietary studies. The effect of the overall diet beyond that of single foods and nutrients can be studied with dietary pattern analyses.
Analysis of food consumption patterns has become a common tool for studying the associations between diet and health. Three main approaches have been used to define dietary patterns: factor analysis, cluster analysis, and dietary indices (3). Factor analysis and cluster analysis are the predominant a posteriori methods. Both are used in identifying the major dietary patterns independently of their relevance to disease, whereas the a priori approach is used to describe the ideal diet for disease prevention based on available evidence of the disease.
A pattern characterized by higher intake of fruits and vegetables (prudent pattern) and a pattern characterized by higher intake of foods typical of Western diets (Western pattern) were similarly observed in previous a posteriori analyses (411).
Despite the growing interest in the relations between dietary patterns and disease, data on the ability of dietary patterns to predict the occurrence of type 2 diabetes are still sparse. A Western dietary pattern predicted an increased and a prudent pattern predicted a reduced risk of type 2 diabetes in a large prospective study of male health professionals (12). Prospective studies among women are still lacking. We studied whether the patterns observed in a large cohort of Finnish men and women had a predictive value for type 2 diabetes risk.
 |
MATERIALS AND METHODS
|
---|
The Finnish Mobile Clinic Health Examination Survey carried out health examinations in various regions of Finland during 19661972. Selection and characteristics of the population examined were described previously (1315). A dietary history interview of 10,054 citizens, 15 years of age or more, was included in the study in 1967 (16). The study population comprised 4,344 men and women, after including only individuals 4069 years of age who were free of diabetes. After exclusion of those who reported a daily energy intake of less than 800 kcal or more than 6,000 kcal or those who were pregnant, the final study population comprised 4,304 persons.
A questionnaire yielded information on occupational group, current pregnancy, babies born with birth weight over 4,500 g, family history of diabetes, previous and current illnesses, consumption of medicines, and health-related habits, such as smoking (15). Occupation was grouped into nine categories according to the Nordic Standard Classification of Occupations (17). Body weight and height were measured, and body mass index was calculated (kg/m2). Casual blood pressure was measured with the auscultatory method. Four hypertension categories were formed based on systolic blood pressure, diastolic blood pressure, and antihypertensive medication (15). Persons with systolic blood pressure of 170 mmHg or more and diastolic blood pressure of 100 mmHg or more and persons using antihypertensive medication were considered definitely hypertensive. Persons with systolic blood pressure of 160 mmHg or more and diastolic blood pressure of 95 mmHg or more but not defined as hypertensive were considered to have mild hypertension, and those with systolic blood pressure of less than 140 mmHg and diastolic blood pressure of less than 90 mmHg were considered normotensive. All persons with intermediate values were considered to have borderline hypertension. The serum cholesterol concentration was determined with an autoanalyzer modification of the Liebermann-Burchard reaction (18). Known cases of diabetes were identified by information given by the participants. A glucose tolerance test was carried out to diagnose new diabetes at baseline, using diagnostic criteria of the World Health Organization (19). Previously known or new persons with diabetes at baseline were excluded from the analyses.
Total habitual food consumption during the previous year was estimated using a dietary history interview (16). Trained interviewers used a questionnaire listing over 100 food items and mixed dishes common to the Finnish diet. Consumption of foods was estimated per day, week, month, or year according to the choice of the respondent. Individual consumption of food items was converted to grams per day. The food items were grouped into 23 food groups based on nutrient profile and culinary use of the item (table 1). Short- and long-term reproducibility of the food consumption data has been reported previously (20). The intraclass correlation coefficients for short-term repeatability were 0.63 for vegetables, 0.55 for fruits and berries, 0.68 for milk products, and 0.72 for meat products. The corresponding long-term repeatability coefficients for 47 years were 0.47 for vegetables, 0.39 for fruits and berries, 0.54 for milk products, and 0.47 for meat products.
View this table:
[in this window]
[in a new window]
|
TABLE 1. Food grouping used in dietary pattern analyses, Finnish Mobile Clinic Health Examination Survey, 19661972, with 23-year follow-up
|
|
To identify dietary patterns, we applied the principal component method with Varimax rotation in the factor analysis and used SAS software for the analyses (21, 22). We labeled two factors with eigenvalues of greater than 2.5 as the "prudent" pattern and the "conservative" pattern and discarded other factors with eigenvalues of less than 1.5 on the basis of the results of a scree test and interpretability of the factors (23). The factor-loading matrix for these two retained dietary patterns is shown in table 2. The factor score for each pattern was computed by summing the observed variables multiplied with their factor loadings. These scores were used to rank participants according to the degree to which they conformed to each dietary pattern.
View this table:
[in this window]
[in a new window]
|
TABLE 2. Factor-loading matrix for the major dietary patterns identified, Finnish Mobile Clinic Health Examination Survey, 19661972, with 23-year follow-up
|
|
During a 23-year follow-up, a total of 164 male and 219 female incident cases were identified from a nationwide registry of patients receiving drug reimbursement, which is maintained by the Social Insurance Institution (14). Participants in the present study were linked to this register by unique Social Security codes assigned to each Finnish citizen.
Nutrient intakes as well as dietary pattern scores were adjusted for total energy (12) using the residual method described by Willett and Stampfer (24). Relative risks of type 2 diabetes with 95 percent confidence intervals between quartiles of scores were calculated using Coxs model (25). Potential confounding and effect-modifying factors were entered into the model. Tests for trends based on the likelihood ratio test, including variables as continuous variables in the model, were carried out.
 |
RESULTS
|
---|
The factor we labeled as the prudent dietary pattern was characterized by consumption of fruits and vegetables, whereas the factor labeled as the conservative dietary pattern was characterized by consumption of butter, potatoes, and whole milk (table 2). Baseline characteristics of the study sample according to categories of dietary pattern scores are presented in table 3. Persons having higher prudent dietary pattern scores were less likely to be men or smokers, whereas persons with higher conservative dietary pattern scores were more likely to be men or current smokers. Higher intakes of polyunsaturated fat, vitamin E, and beta-carotene were associated with higher prudent pattern scores and lower conservative pattern scores. The prudent pattern was inversely associated with intake of saturated fat. Of the food items, processed meat and canned or frozen fish, poultry, margarine and oil, regular and reduced-fat dairy products, fruits and berries, and vegetables were directly associated with prudent pattern scores but not with conservative pattern scores. Higher conservative pattern scores were directly associated and prudent pattern scores inversely associated with higher intakes of butter and potatoes.
View this table:
[in this window]
[in a new window]
|
TABLE 3. Mean values and baseline characteristics according to quartile of energy-adjusted dietary pattern scores, Finnish Mobile Clinic Health Examination Survey, 19661972, with 23-year follow-up
|
|
During the 23-year follow-up, higher prudent pattern scores predicted a lower risk of type 2 diabetes while, in contrast, higher conservative pattern scores predicted an increased diabetes risk (table 4). When the highest and lowest quartiles of the prudent pattern scores were compared, the relative risk of type 2 diabetes was 0.72 (95 percent confidence interval (CI): 0.53, 0.97; ptrend = 0.03), after adjustment for age, sex, body mass index, energy intake, smoking, family history of diabetes, geographic area, serum cholesterol, and hypertension. The corresponding value between extreme categories of conservative pattern scores was 1.49 (95 percent CI: 1.11, 2.00; ptrend = 0.01).
View this table:
[in this window]
[in a new window]
|
TABLE 4. Relative risks* of type 2 diabetes among quartiles of dietary pattern scores, Finnish Mobile Clinic Health Examination Survey, 19661972, with 23-year follow-up
|
|
To study the potential interaction between dietary patterns, we cross-tabulated the pattern scores and compared the relative risks across the categories. We noted that the association between a conservative pattern score and risk of type 2 diabetes was higher than that among persons with a lower prudent pattern score (figure 1). On the other hand, a higher prudent pattern score did not predict reduced diabetes risk among persons with low conservative pattern scores. However, the interaction term was not significant (pinteraction = 0.38).

View larger version (20K):
[in this window]
[in a new window]
|
FIGURE 1. Relative risk (adjusted for age, sex, body mass index, energy, smoking, family history of diabetes, geographic area, serum cholesterol, and hypertension) for type 2 diabetes, according to combinations of dietary pattern scores, Finnish Mobile Clinic Health Examination Survey, 19661972, with 23-year follow-up.
|
|
In additional analyses, we included occupational group in the model to study whether sociodemographic factors could explain the associations found between the prudent pattern and diabetes risk. The relative risk of 0.73 (95 percent CI: 0.53, 1.01; ptrend = 0.05) indicated no notable effect on the results. We also included dietary fiber, vitamin E, vitamin C, beta-carotene, and folic acid individually in the model. The relative risks were 0.76 (95 percent CI: 0.55, 1.04; ptrend = 0.07 ), 0.85 (95 percent CI: 0.61, 1.20; ptrend = 0.30), 0.76 (95 percent CI: 0.52, 1.11; ptrend = 0.13), 0.75 (95 percent CI: 0.54, 1.05; ptrend = 0.08), and 0.79 (95 percent CI: 0.55, 1.13; ptrend = 0.17), respectively. In the final model containing fiber, vitamin E, vitamin C, beta-carotene, and folic acid in the same model, the relative risk for type 2 diabetes was 0.93 (95 percent CI: 0.61, 1.42; ptrend = 0.63).
To shed light on the possible modifying effect of potential interacting variables, we also analyzed categories pertaining to age, sex, body mass index, and smoking (table 5). Although no significant interactions were found, we noted that the prudent pattern scores were associated with a lower risk of type 2 diabetes among older persons, women, persons with higher body mass index, and nonsmokers. Among these subgroups, higher conservative pattern scores predicted an increased risk of type 2 diabetes.
View this table:
[in this window]
[in a new window]
|
TABLE 5. Relative risk* for type 2 diabetes between the highest and lowest quartiles of energy-adjusted dietary pattern scores in strata of potential effect-modifying factors, Finnish Mobile Clinic Health Examination Survey, 19661972, with 23-year follow-up
|
|
 |
DISCUSSION
|
---|
In the present study, we identified two major dietary patterns in a large cohort of Finns. The prudent dietary pattern, which was rich in fruits and vegetables, was associated with a reduced risk of type 2 diabetes. In contrast, the conservative pattern, which was rich in butter, potatoes, red meat, and whole milk, was associated with a higher risk of type 2 diabetes. The findings appeared to be more pronounced among older persons, women, nonsmokers, and individuals with a relatively high body mass index, although none of the interaction terms was significant.
The findings corroborate the previously reported results of the Health Professionals Follow-up Study (12). In that study, the Western dietary pattern (rich in processed meats, high-fat dairy products, french fries, and refined grains) was associated with an increased risk of type 2 diabetes, whereas the prudent dietary pattern (rich in vegetables, fruits, fish, poultry, and whole grains) was associated with a reduced risk. In a British cross-sectional study, a dietary pattern characterized by a high consumption of fruits and vegetables and a low consumption of processed meat and fried foods was inversely associated with type 2 diabetes risk (26). A pattern characterized by higher intakes of french fries, chocolate, cake, canned meat, and canned fruit was associated with a higher prevalence of type 2 diabetes in a Canadian cross-sectional study (27). A pattern identified by cluster analysis, including higher intakes of cheese, fatty meat, and cake, was associated with a higher risk of hyperglycemia among men in the European Prospective Investigation into CancerMalmö Study (28). The Western dietary pattern was reported to be associated with plasma insulin level and C-peptide level, biomarkers of developing type 2 diabetes (29). An a priori-formed pattern score based on the intake of cereal fiber, polyunsaturated fat, trans-fatty acids, and postprandial glycemic load was related to development of diabetes risk during a 16-year follow-up in the Nurses Health Study (30). A few dietary interventions have demonstrated a considerably lower risk of diabetes among the intervention group prescribed a healthy diet and exercise (3133).
In contrast to the study of individual nutrients or foods, dietary pattern analysis also considers the overall diet, reflecting more closely the real world. Complicated interactions among nutrients that occur together in common foods can be accounted for here. Our finding on the relation between the dietary pattern reflecting vegetable and fruit intake and diabetes risk is in line with results of previous studies, which have shown an inverse association between consumption of fruits and vegetables and the risk of type 2 diabetes (3436), although controversial results have also been shown (37). The preventive effects of fruits and vegetables have been hypothesized to be mediated by antioxidants, and results of some follow-up studies have supported this hypothesis (35, 3840). Magnesium has been related to reduced diabetes development since hypomagnesemia may impair insulin secretion and promote insulin resistance. Folic acid also has a potential reducing effect on the development of disease linked to metabolic syndrome and type 2 diabetes through a lower concentration of serum homocysteine (41). In the present study, adjustment for vitamin E, vitamin C, beta-carotene, or folic acid attenuated the association.
Dietary fiber has also been hypothesized to prevent development of type 2 diabetes by reducing postprandial insulin demand. We tested whether dietary fiber could have explained the finding and found that inclusion of fiber in the model did not notably alter the result. The fact that fiber, mainly derived from grain products (42), was included in the conservative pattern apparently biased the result for the conservative pattern. This underlines that the pattern analysis approach cannot be specific about the particular nutrients responsible for the observed association between dietary pattern and disease risk. In contrast to previous studies, the intake of whole grain (rye) was related to the conservative pattern in our data. The reason is that grain products, especially rye bread, were commonly eaten with butter. We suggest that this fact has diminished the difference between the two dietary patterns in predicting the risk of type 2 diabetes.
Since food consumption patterns reflect existing preferences and the foods available, it could be expected that the identified patterns differ by population and time. However, two similar major dietary patterns, prudent and Western, have been identified using factor analysis in several populations (5, 6, 911). The fact that several studies have resulted in more diverse patterns (7, 4353) cannot be excluded, however. The major dietary patterns that we observed among 10,054 Finns in 19671972 have similarities to those observed in the 1980s and 1990s in the United States, Denmark, and Sweden (6, 911, 54). In our analysis, the prudent dietary pattern was characterized by fruits, vegetables, and poultry, which were associated with a prudent or vegetable-rich pattern in these previous studies. The conservative pattern was characterized by butter, potatoes, processed meat, red meat, and whole milk, which previously have also been associated with Western or high-calorie patterns.
Measurement of the dietary data requires an appropriate instrument to capture the food items of interest. In our study, a 1-year dietary history interview applied to the nationwide sample allowed us to identify two major dietary patterns of Finns. Although the dietary history interview is considered a relatively accurate method, certain inaccuracies in the method tend to alter the associations observed between dietary exposure and outcome (55). In the present study, all the interviewers were trained nutrition professionals, and a preformed questionnaire was used to diminish differences among interviewers. The questions were open-ended and offered opportunities to specify the answers. Likewise, food models were used to reduce errors of recall. In general, the short-term repeatability of the dietary history method was favorable, but long-term reliability was rather poor because of changes in food consumption by Finns (16). The poor long-term reliability of dietary data has possibly weakened the associations between diet and diabetes. The conservative dietary pattern score was directly associated with smoking and inversely associated with hypertension. It is possible that some residual confounding has remained after adjustments because of inaccurate measurement of smoking status or blood pressure.
The information on incident diabetes cases was received from a nationwide registry of drug reimbursements. The registry does not include persons with diabetes undergoing dietary therapy only and, therefore, there may have been loss of statistical power. On the other hand, it is probable that in many cases diabetic patients undergoing only dietary therapy later proceed to a phase during which drug therapy is needed. Thus, it is probable that the cases included represent a group of patients with more severe disease of rather long duration. Unfortunately, as an apparent limitation of our study, we had no valid data available on baseline physical activity and intakes of alcoholic and nonalcoholic beverages. Since persons with healthier diets may be physically more active than other persons, the lack of physical activity data in particular may have confounded the results.
In conclusion, the prudent dietary pattern observed in our data predicted a reduced risk, and the conservative dietary pattern, reflecting an ordinary diet among Finns in 19671972, predicted an elevated risk of type 2 diabetes in persons free from the disease. In light of the present results, it seems conceivable that the risk of type 2 diabetes can be reduced by shifting from the conservative pattern to the prudent one. Since the patterns can be easily integrated into diets, they may be highly useful in public education.
 |
NOTES
|
---|
Reprint requests to J. Montonen, National Public Health Institute, Mannerheimintie 166, 00300 Helsinki, Finland (e-mail: jukka.montonen{at}ktl.fi). 
 |
REFERENCES
|
---|
- Virtanen SM, Aro A. Dietary factors in the aetiology of diabetes. Ann Med 1994;26:46978.[ISI][Medline]
- Ursin G, Ziegler RG, Subar AF, et al. Dietary patterns associated with a low-fat diet in the national health examination follow-up study: identification of potential confounders for epidemiologic analyses. Am J Epidemiol 1993;137:91627.[Abstract]
- Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 2002;13:39.[CrossRef][ISI][Medline]
- Nolan CC, Gray-Donald K, Shatenstein B, et al. Dietary patterns leading to high fat intake. Can J Public Health 1995;86:38991.[ISI][Medline]
- Slattery ML, Boucher KM, Caan BJ, et al. Eating patterns and risk of colon cancer. Am J Epidemiol 1998;148:416.[Abstract]
- Hu FB, Rimm EB, Stampfer MJ, et al. Prospective study of major dietary patterns and risk of coronary heart disease in men. Am J Clin Nutr 2000;72:91221.[Abstract/Free Full Text]
- Tseng M, DeVillis R. Correlates of the "Western" and "prudent" diet patterns in the US. Ann Epidemiol 2000;10:4812.
- Tseng M, DeVellis RF. Fundamental dietary patterns and their correlates among US whites. J Am Diet Assoc 2001;101:92932.[CrossRef][ISI][Medline]
- Fung TT, Willett WC, Stampfer MJ, et al. Dietary patterns and the risk of coronary heart disease in women. Arch Intern Med 2001;161:185762.[Abstract/Free Full Text]
- Osler M, Heitmann BL, Gerdes LU, et al. Dietary patterns and mortality in Danish men and women: a prospective observational study. Br J Nutr 2001;85:21925.[ISI][Medline]
- Terry P, Suzuki R, Hu FB, et al. A prospective study of major dietary patterns and the risk of breast cancer. Cancer Epidemiol Biomarkers Prev 2001;10:12815.[Abstract/Free Full Text]
- van Dam RM, Rimm EB, Willett WC, et al. Dietary patterns and risk for type 2 diabetes mellitus in U.S. men. Ann Intern Med 2002;136:2019.[Abstract/Free Full Text]
- Aromaa A. Epidemiology and public health impact of high blood pressure in Finland. (In Finnish with an English summary). Helsinki, Finland: Social Insurance Institution, 1981. (Series AL:17).
- Reunanen A, Aromaa A, Pyörälä K, et al. The Social Insurance Institutions coronary heart disease study. Baseline data and 5-year mortality experience. Acta Med Scand Suppl 1983;673:1120.[Medline]
- Knekt P. Serum alpha-tocopherol and the risk of cancer. Helsinki, Finland: Social Insurance Institution, 1988. (Series ML:83).
- Järvinen R. Epidemiological follow-up study on dietary antioxidant vitamins. Results from the Finnish Mobile Clinic Health Examination Survey. Helsinki, Finland: Social Insurance Institution, 1996. (Studies in social security and health, 11).
- Brockington F. World health. Appendix VIII. The International Standard Classification of Occupations. London, United Kingdom: Churchill, 1967.
- Huang TC, Chen CP, Wefler V, et al. A stable reagent for the Lieberman-Burchard reaction. Application to rapid serum cholesterol determination. Anal Chem 1961;33:1405507.[ISI]
- World Health Organization. Diabetes mellitus: report of a WHO study group. Geneva, Switzerland: World Health Organization, 1985.
- Järvinen R, Seppänen R, Knekt P. Short-term and long-term reproducibility of dietary history interview data. Int J Epidemiol 1993;22:5207.[Abstract]
- SAS/STAT users guide, version 6. Cary, NC: SAS Institute, Inc, 1989.
- Hu FB, Rimm E, Smith-Warner SA, et al. Reproducibility and validity of dietary patterns assessed with a food-frequency questionnaire. Am J Clin Nutr 1999;69:2439.[Abstract/Free Full Text]
- Kim JO, Mueller C. Factor analysis statistical methods and practical issues. Beverly Hills, CA: Sage Publications, 1978.
- Willett W, Stampfer MJ. Total energy intake: implications for epidemiologic analyses. Am J Epidemiol 1986;124:1727.[Abstract]
- Cox D. Regression models and life tables (with discussion). J R Stat Soc (B) 1972;34:187220.[ISI]
- Williams DE, Prevost AT, Whichelow MJ, et al. A cross-sectional study of dietary patterns with glucose intolerance and other features of the metabolic syndrome. Br J Nutr 2000;83:25766.[ISI][Medline]
- Gittelsohn J, Wolever TM, Harris SB, et al. Specific patterns of food consumption and preparation are associated with diabetes and obesity in a Native Canadian community. J Nutr 1998;128:5417.[Abstract/Free Full Text]
- Wirfält E, Hedblad B, Gullberg B, et al. Food patterns and components of the metabolic syndrome in men and women: a cross-sectional study within the Malmö Diet and Cancer Cohort. Am J Epidemiol 2001;154:11509.[Abstract/Free Full Text]
- Fung TT, Rimm EB, Spiegelman D, et al. Association between dietary patterns and plasma biomarkers of obesity and cardiovascular disease risk. Am J Clin Nutr 2001;73:617.[Abstract/Free Full Text]
- Hu FB, Manson JE, Stampfer MJ, et al. Diet, lifestyle, and the risk of type 2 diabetes mellitus in women. N Engl J Med 2001;345:7907.[Abstract/Free Full Text]
- Pan XR, Li GW, Hu YH, et al. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study. Diabetes Care 1997;20:53744.[Abstract]
- Tuomilehto J, Lindström J, Eriksson JG, et al. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 2001;344:134350.[Abstract/Free Full Text]
- Knowler WC, Barrett-Connor E, Fowler SE, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002;346:393403.[Abstract/Free Full Text]
- Snowdon DA, Phillips RL. Does a vegetarian diet reduce the occurrence of diabetes? Am J Public Health 1985;75:50712.[Abstract]
- Feskens EJ, Virtanen SM, Räsänen L, et al. Dietary factors determining diabetes and impaired glucose tolerance. A 20-year follow-up of the Finnish and Dutch cohorts of the Seven Countries Study. Diabetes Care 1995;18:110412.[Abstract]
- Ford ES, Mokdad AH. Fruit and vegetable consumption and diabetes mellitus incidence among U.S. adults. Prev Med 2001;32:339.[CrossRef][ISI][Medline]
- Meyer KA, Kushi LH, Jacobs DR Jr, et al. Carbohydrates, dietary fiber, and incident type 2 diabetes in older women. Am J Clin Nutr 2000;71:92130.[Abstract/Free Full Text]
- Salonen JT, Nyyssönen K, Tuomainen TP, et al. Increased risk of non-insulin dependent diabetes mellitus at low plasma vitamin E concentrations: a four year follow up study in men. BMJ 1995;311:11247.[Abstract/Free Full Text]
- Reunanen A, Knekt P, Aaran RK, et al. Serum antioxidants and risk of non-insulin dependent diabetes mellitus. Eur J Clin Nutr 1998;52:8993.[CrossRef][ISI][Medline]
- Knekt P, Reunanen A, Marniemi J, et al. Low vitamin E status is a potential risk factor for insulin-dependent diabetes mellitus. J Intern Med 1999;245:99102.[CrossRef][ISI][Medline]
- Boushey CJ, Beresford SA, Omenn GS, et al. A quantitative assessment of plasma homocysteine as a risk factor for vascular disease. Probable benefits of increasing folic acid intakes. JAMA 1995;274:104957.[Abstract]
- Montonen J, Knekt P, Järvinen R, et al. Whole-grain and fiber intake and the incidence of type 2 diabetes. Am J Clin Nutr 2003;77:6229.[Abstract/Free Full Text]
- Schwerin HS, Stanton JL, Riley AM Jr, et al. Food eating patterns and health: a reexamination of the Ten-State and HANES I surveys. Am J Clin Nutr 1981;34:56880.[Abstract]
- Schwerin HS, Stanton JL, Smith JL, et al. Food, eating habits, and health: a further examination of the relationship between food eating patterns and nutritional health. Am J Clin Nutr 1982;35:131925.[ISI][Medline]
- Gex-Fabry M, Raymond L, Jeanneret O. Multivariate analysis of dietary patterns in 939 Swiss adults: sociodemographic parameters and alcohol consumption profiles. Int J Epidemiol 1988;17:54855.[Abstract]
- Nicklas TA, Webber LS, Thompson B, et al. A multivariate model for assessing eating patterns and their relationship to cardiovascular risk factors: the Bogalusa Heart Study. Am J Clin Nutr 1989;49:13207.[Abstract]
- Barker ME, McClean SI, Thompson KA, et al. Dietary behaviours and sociocultural demographics in Northern Ireland. Br J Nutr 1990;64:31929.[ISI][Medline]
- Randall E, Marshall JR, Graham S, et al. Patterns in food use and their associations with nutrient intakes. Am J Clin Nutr 1990;52:73945.[Abstract]
- Hebert JR, Kabat GC. Implications for cancer epidemiology of differences in dietary intake associated with alcohol consumption. Nutr Cancer 1991;15:10719.[ISI][Medline]
- Wolff CB, Wolff HK. Maternal eating patterns and birth weight of Mexican American infants. Nutr Health 1995;10:12134.[Medline]
- Beaudry M, Galibois I, Chaumette P. Dietary patterns of adults in Quebec and their nutritional adequacy. Can J Public Health 1998;89:34751.[ISI][Medline]
- Schulze MB, Hoffmann K, Kroke A, et al. Dietary patterns and their association with food and nutrient intake in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Br J Nutr 2001;85:36373.[ISI][Medline]
- Slimani N, Fahey M, Welch AA, et al. Diversity of dietary patterns observed in the European Prospective Investigation into Cancer and Nutrition (EPIC) project. Public Health Nutr 2002;5:131128.[CrossRef][ISI][Medline]
- Tseng M, DeVellis RF, Maurer KR, et al. Food intake patterns and gallbladder disease in Mexican Americans. Public Health Nutr 2000;3:23343.[Medline]
- Willett W. Nutritional epidemiology. New York, NY: Oxford University Press, 1998.