Dietary Patterns and Risk for Type 2 Diabetes Mellitus in U.S. Men

The prevalence of type 2 diabetes mellitus is rapidly increasing in the United States (1, 2) and worldwide (3). Ecologic studies (4), migration studies (4, 5), and analyses of secular trends (4, 6) suggest that adoption of a western diet may be associated with increased incidence of type 2 diabetes. However, these studies could not separate the effects of diet from those of other risk factors, such as obesity and physical activity. Studies of the relation between diet and incidence of type 2 diabetes on an individual level have predominantly focused on intake of macronutrients and fiber (7). However, these dietary factors alone probably explain only part of the effect of diet on glucose metabolism. Other nutrients, additives, contaminants, and unknown compounds and the physical properties of foods and interactions between nutrients (for example, with respect to bioavailability) may play a role in the deterioration of glucose metabolism. Hence, the examination of effects of food consumption may be an important complementary approach. Recently, the analysis of patterns of food consumption by using factor analysis has emerged as a useful tool for elucidating relationships between diet and health (8-11). The overall dietary pattern may affect health more than individual foods and nutrients do. Furthermore, dietary patterns reflect the way foods are consumed in reality, which may provide insight into possibilities for dietary changes and may facilitate the translation of findings to public health recommendations. Recent dietary intervention studies have indicated that interventions focused on dietary patterns can decrease blood pressure (12) and reduce cardiovascular complications (13). Data on dietary patterns and risk for type 2 diabetes are sparse. Although two cross-sectional studies of dietary patterns and diabetes have been conducted (11, 14), these studies incompletely controlled for confounding by other lifestyle factors. Therefore, we prospectively examined the association between major dietary patterns and risk for type 2 diabetes in a large prospective study of U.S. professional men with extensive, repeatedly obtained information on diet and other lifestyle factors. Methods Participants The Health Professionals Follow-up Study started in 1986, when 51 529 male health professionals (dentists, veterinarians, pharmacists, optometrists, osteopathic physicians, and podiatrists) completed a detailed mailed questionnaire on medical history, diet, and other potential risk factors for major diseases. The participants lived in all 50 U.S. states, were predominantly white, and were 40 to 75 years of age in 1986. We excluded from the current analysis 1595 men who did not satisfy the a priori criteria of reporting daily energy intake of 3.3 to 17.6 MJ (800 to 4200 kcal/24 h) and leaving fewer than 70 responses blank of the 131 food items on the diet questionnaire (<5% had >11 blanks). We also excluded men who reported having diabetes, cardiovascular disease (myocardial infarction, angina pectoris, coronary artery surgery, or stroke), or cancer (except nonmelanoma skin cancer) at baseline because having these diagnoses may affect diet or reporting of diet. After exclusions, the study sample comprised 42 504 men, who were followed for incidence of type 2 diabetes and other diseases for 12 years (1986 to 1998). Every 2 years, the participants received questionnaires by mail that asked for updated information on exposures and newly diagnosed diseases. The follow-up rate for potential person-years was about 97% for nonfatal events. We identified deaths by reports from family members, coworkers, or postal authorities or through systematic searches of the National Death Index. Assessment of Dietary Patterns To assess dietary intake, we used a 131-item semiquantitative food-frequency questionnaire in 1986, 1990, and 1994. The questionnaire specified for each food a commonly used unit or portion size, and the participants were asked to indicate how often, on average, they had consumed a given amount of the specified food during the past year. Each such item provided nine possible responses, ranging from never or less than once a month to 6 or more times per day. To reduce within-respondent variation and to best represent long-term dietary habits, we averaged the dietary intakes from all available dietary questionnaires up to the start of each follow-up interval (the average of the 1986 and 1990 dietary intakes was related to incidence of type 2 diabetes between 1990 and 1994) (15). To identify dietary patterns, we applied factor analysis to data from the food-frequency questionnaire. First, we grouped the food items on the questionnaire into 37 predefined food groups. We combined food items that were similar in nutrient profile and culinary use (for example, spinach, iceberg or head lettuce, and romaine or leaf lettuce were combined into green leafy vegetables). We classified a food item individually if its composition differed substantially from that of other foods (for example, eggs or pizza) or if we suspected that it represents a particular dietary habit (for example, wine or French fries). Second, we applied the principal components program for factor analysis of SAS software (16) with varimax rotation to the 37 food groups. Factor analysis aggregates correlated variables. The obtained factors are linear combinations of the included variables, explaining as much of the variation in the original variables as possible. Our analysis retained two factors based on the eigenvalue of the factors, the Scree test, and the interpretability of the derived factors, and we labeled these diets as the prudent pattern and the western pattern (9). Third, for each participant, we calculated a prudent pattern score and a western pattern score by summing the standardized intake of foods, weighted by the factor loadings of the foods (17). We used these scores to rank participants according to the degree to which they conformed to each dietary pattern. We divided dietary pattern scores into quintiles; thus, on this basis of his scores, each participant was grouped in a prudent-pattern quintile and a western-pattern quintile. To test the validity and reproducibility of the assessment of the dietary pattern scores by the food-frequency questionnaire, we examined a subgroup of 127 participants (9). The Pearson correlation coefficient (corrected for week-to-week variation in the diet records) for a comparison between the responses to the food-frequency questionnaire and the diet records was 0.52 for the prudent dietary pattern and 0.74 for the western dietary pattern. Assessment of Nondietary Exposures The 1986 questionnaire and each biennial follow-up questionnaire assessed weight, smoking status, and physical activity. Participants provided information on age, diagnosis of hypertension and hypercholesterolemia, and height in 1986 and on family history of diabetes in 1987. The criterion for family history of type 2 diabetes was having at least one first-degree relative with a diagnosis of diabetes after 30 years of age. For each participant, we determined a physical activity level, measured in weekly metabolic equivalent hours, on the basis of reported time spent on various activities, which we weighted according to intensity level (18). The validity of self-reported weight (19) and physical activity (18) in this cohort has been reported previously. Ascertainment of Type 2 Diabetes Mellitus We mailed a supplementary questionnaire on symptoms, diagnostic tests, and medication use to participants who indicated on any biennial follow-up questionnaire that he had received a diagnosis of diabetes mellitus. Confirmation of diabetes required at least one of the following: 1) an elevated plasma glucose level (fasting plasma glucose level 7.8 mmol/L [ 140 mg/dL]; random plasma glucose level 11.1 mmol/L [ 200 mg/dL]; or plasma glucose level after 2 hours or more during an oral glucose tolerance test 11.1 mmol/L [ 200 mg/dL]) plus at least one classic symptom [excessive thirst, polyuria, weight loss, or hunger]; 2) at least two elevated plasma glucose levels measured on different occasions; or 3) treatment with insulin or oral hypoglycemic medication. We excluded men who reported having type 1 diabetes on the supplementary questionnaire. These criteria for diabetes are consistent with those from the World Health Organization in 1985 (20). We did not use the current diabetes classification of the American Diabetes Association (21) because among the men in our study, most cases of diabetes were diagnosed before these criteria were published. The validity of our assessment of type 2 diabetes was verified with medical records in a subsample of 71 participants. A physician blinded to the information on the supplementary questionnaire reviewed the records according to the diagnostic criteria. Of the 71 participants classified as having type 2 diabetes, 12 had incomplete medical recordsfor example, absent laboratory data (n = 2) or only one set of laboratory data (n = 9). We confirmed the classification of type 2 diabetes in 57 (97%) of the other 59 other men in the subsample. One participant denied having diabetes, and another participant lacked evidence of diabetes in his submitted records. Statistical Analysis We used pooled logistic regression analyses with 2-year intervals to estimate the adjusted relative risk for each quintile compared with the lowest quintile of intake. With short time intervals and low rates of events, this approach gives results very similar to those of Cox proportional-hazards analyses (22). Participants who died or received a diagnosis of diabetes during a 2-year cycle were censored at the end of that 2-year period and were not entered in any subsequent 2-year cycle. We used the cumulative average of available dietary assessments up to the start of each 2-year follow-up interval (15). We stopped updating a participant's dietary data