Dietary Fat and the Risk of Clinical Type 2 Diabetes

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1 American Journal of Epidemiology Copyright 2004 by the Johns Hopkins Bloomberg School of Public Health All rights reserved Vol. 159, No. 1 Printed in U.S.A. DOI: /aje/kwh004 Dietary Fat and the Risk of Clinical Type 2 Diabetes The European Prospective Investigation of Cancer-Norfolk Study Anne-Helen Harding 1, Nicholas E. Day 2, Kay-Tee Khaw 2, Sheila Bingham 2,3, Robert Luben 2, Ailsa Welsh 2, and Nicholas J. Wareham 1 1 Medical Research Council Epidemiology Unit, Cambridge, United Kingdom. 2 Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge, Cambridge, United Kingdom. 3 Medical Research Council Dunn Human Nutrition Unit, Cambridge, United Kingdom. Received for publication November 12, 2002; accepted for publication July 2, The role of dietary fat in the etiology of type 2 diabetes remains uncertain. The authors investigated the association between dietary fat composition and risk of clinical type 2 diabetes in the European Prospective Investigation of Cancer-Norfolk study and identified food consumption patterns associated with dietary fat composition. Diet was assessed at baseline ( ) using a semiquantitative food frequency questionnaire. From multiple sources of information, 414 incident cases of diabetes were identified among 23,631 men and women aged years during 3 7 years of follow-up. The capture-recapture ascertainment level was 99%. The energy-adjusted dietary polyunsaturated:saturated fat ratio was inversely associated with the risk of diabetes (odds ratio (OR) = 0.84 per standard deviation change, 95% confidence interval (CI): 0.75, 0.94). Adjustment for age, sex, family history of diabetes, smoking, physical activity, total fat, protein, and alcohol attenuated the association (OR = 0.88, 95% CI: 0.78, 0.99), and it was no longer statistically significant after including body mass index and the waist:hip ratio (OR = 0.91, 95% CI: 0.81, 1.03). This prospective study showed that an increased dietary polyunsaturated:saturated fat ratio was associated with a reduced risk of diabetes, independent of age, sex, family history of diabetes, and other lifestyle factors. diabetes mellitus; dietary fats; prospective studies Abbreviations: CI, confidence interval; EPIC, European Prospective Investigation of Cancer; HbA 1c, glycated hemoglobin; OR, odds ratio; P:S ratio, polyunsaturated:saturated fat ratio. The possibility that diet may be a cause of diabetes has been recognized for many years, although the specific dietary factors that are involved are yet to be determined. The balance of evidence suggests that changes in the quantity and quality of dietary fat affect diabetes risk (1, 2). Plausible mechanisms linking dietary fat with the risk of type 2 diabetes have been identified in animal and clinical studies (3). A high-fat diet has been associated with obesity, increased body fat for a given weight, and altered fat distribution, and each of these changes has been associated with change in glucose metabolism (4). In addition, the fatty acid composition of cell membranes could affect membrane fluidity or insulin-mediated signal transduction and insulin action (5). There is evidence that n-3 polyunsaturated fatty acids reduce serum lipids and lipoproteins, impair platelet aggregation, and lower blood pressure, properties that may confer beneficial effects on the risk of type 2 diabetes (1). Positive associations have been found between the risk of type 2 diabetes and total fat intake in cross-sectional (4, 6) and prospective (7, 8) studies. Positive associations have also been reported with the consumption of saturated fat (7) and animal fat (9). A reduced risk of diabetes was associated with increased vegetable fat intake and polyunsaturated fat intake in the US Nurses Health Study (10, 11). In a number of other studies, there were no reported associations between dietary fat intake and the risk of diabetes (12 16). The Correspondence to Dr. N. J. Wareham, Medical Research Council Epidemiology Unit, Strangeways Research Laboratories, Worts Causeway, Cambridge CB1 8RN, United Kingdom ( njw1004@medschl.cam.ac.uk). 73

2 74 Harding et al. pattern of dietary fat intake may be represented by the polyunsaturated:saturated fat ratio (P:S ratio). The US Health Professionals Follow-up Study (16) found no evidence of an association between the P:S ratio and the risk of diabetes, whereas in the US Nurses Health Study (17) the risk of diabetes decreased with an increasing P:S ratio. The first objective of our study was to investigate how total dietary fat intake and the pattern of fat intake affected the risk of developing clinical type 2 diabetes in a population of Caucasian men and women aged years. The second objective was to identify food consumption patterns associated with different dietary fat compositions. MATERIALS AND METHODS Study population The European Prospective Investigation of Cancer (EPIC) is an international multicenter cohort study designed to investigate the relation among diet, nutritional, and metabolic characteristics, various lifestyle factors, and the risk of cancer (18). The Norfolk arm of the study broadened its scope to include chronic diseases other than cancer. Details of the study design have been reported previously (19). The local research ethics committee gave approval for the study. EPIC-Norfolk is a population-based cohort study that recruited volunteers from March 1993 to the end of 1997 (19). General practices in the city of Norwich and in surrounding small towns were invited to enroll in the study. Individuals aged years in each of the 35 participating general practices were approached. Those who consented were invited to attend for a health check. Of the 77,630 individuals invited, 39 percent consented to take part, and 25,631 (33 percent) attended the health check, which was close to the target recruitment number of 25,000. Volunteers were asked to complete a postal questionnaire after 18 months follow-up and between 1998 and 2000 were invited to attend a second health check. Data collection Standardized health checks were carried out by research nurses at the EPIC clinic between 1993 and 1998 and between 1998 and 2000 for the follow-up phase. Anthropometric measurements were taken with participants dressed in light clothing and no shoes. Waist circumference was measured to the nearest 0.1 cm at the smallest circumference between the ribs and iliac crest with the volunteers standing with abdomen relaxed, or at the level of the umbilicus if there was no natural waistline. Hips were measured to the nearest 0.1 cm at the maximum circumference between the iliac crest and the crotch. The waist:hip ratio was calculated from these measurements. Height was measured to the nearest 0.1 cm using a stadiometer, and weight was measured to the nearest 100 g using Salter scales (Salter Brecknell Weighing Products, Fairmont, Minnesota). Body mass index was calculated as weight (kg)/height (m) 2. A sample of ethylenediaminetetraacetic acid-anticoagulated blood was taken for a glycated hemoglobin (HbA 1c ) assay using high-performance liquid chromatography on a Bio- Rad Diamat analyzer (Bio-Rad, Richmond, California) (20, 21). Participants were asked to bring any current medications to the health check to show to the research nurse. A detailed health and lifestyle questionnaire was completed at baseline, at 18 months follow-up, and at the time of the second health check. It included questions on personal and family history of diabetes, smoking, physical activity, medication, and diet. Three questions addressed the respondent s personal history of diabetes: they were asked whether a physician had ever told them they had diabetes; whether they had modified their diet in the past year because of diabetes; and whether they followed a diabetic diet. Family history of diabetes was covered in a question asking whether any of the respondent s immediate family had diabetes. Smoking history was derived from two questions: one asked whether the respondent had ever smoked as much as one cigarette a day for as long as 1 year; and the second asked whether the respondent was a current smoker. The health and lifestyle questionnaire addressed occupational and nonoccupational physical activity, and a four-point physical activity index that incorporated both components of physical activity was used as a measure of physical activity level (22). The questionnaire also requested the respondent to list any medications being taken. At baseline, habitual diet during the past year was assessed using a self-completion semiquantitative food frequency questionnaire. The food frequency questionnaire was based on the questionnaire developed for the US Nurses Health Study (23). The frequency categories remained unchanged, but taking information from the British National Food Survey, the lists of foods were modified to reflect important sources of nutrients in the average British diet. Food and nutrient intakes in grams were estimated from the food intake reported in the food frequency questionnaire. Twentyfive major food groups were defined for use in identifying patterns of food consumption. A validation study involving 127 women compared the food frequency questionnaire with 16-day weighed food records (24). The correlation of total fat intakes estimated by food frequency questionnaire and by 16-day weighed food records was 0.55 (24) and, for saturated and polyunsaturated fat intakes, the correlations were 0.56 and 0.37, respectively (S. Bingham, unpublished data). Identification of cases Prevalent, self-reported cases of diabetes were excluded from the study (table 1). A priori, a new case was defined by a physician s diagnosis of type 2 diabetes with no insulin prescribed within the first year following diagnosis and/or an HbA 1c level of greater than 7 percent at the baseline or follow-up health check. This definition permitted previously undiagnosed and incident cases to be included as incident cases in the study, but it also included cases not self-reported at baseline. It is unlikely that the reported diet of volunteers with previously undiagnosed diabetes was affected by their diabetic status. Cases of diabetes were identified using multiple sources of information. The data collected by EPIC- Norfolk used to identify cases included the self-report of diabetes from the first and second follow-up health and lifestyle questionnaires, self-report of diabetes-specific medica-

3 Dietary Fat and Incident Diabetes 75 TABLE 1. Sources of information used to identify prevalent and new cases of diabetes, European Prospective Investigation of Cancer-Norfolk, Prevalent, self-reported cases of diabetes at baseline Responses in baseline health and lifestyle questionnaire Previously informed by physician that they had diabetes? (yes) Modified diet in the past year because of diabetes? (yes) Follow a diabetic diet? (yes) Diabetes-specific medication reported Diabetes-specific medication brought to baseline health check Previously unknown and incident cases of diabetes* Responses in follow-up 1 and/or 2 health and lifestyle questionnaires Informed by physician that they had diabetes? (yes) Diabetes-specific medication reported Diabetes-specific medication brought to follow-up health check HbA 1c > 7% at baseline or follow-up health check General practice diabetes register Norfolk and Norwich Hospital diabetes register Death certificates * Years of follow-up estimated as time from the baseline health check to the first report of diabetes from any of these sources. HbA 1c, glycated hemoglobin. tion in either of the two follow-up questionnaires or diabetes-specific medication brought to the follow-up health check, and an HbA 1c level of greater than 7 percent at either the baseline or follow-up health check. In addition, data that would help in tracing all cases of diabetes were obtained from four independent non-epic sources. EPIC participants who were listed on their general practice diabetes register or on the Norfolk and Norwich Hospital diabetes register were identified. Hospital admissions data for EPIC-Norfolk participants were screened to identify those who were admitted to a hospital for a diabetes-related condition. Office of National Statistics death certificate data with coding for diabetes were also used. A matrix containing the data from the seven sources was drawn up, and each record with a positive response for any of the variables listed was examined to determine whether, according to the a priori definition, it represented a new case of diabetes. In many instances, an individual had several positive indicators of diabetes. A validation exercise to assess the soundness of this method of case ascertainment was undertaken at 12 of the 35 participating general practices. Medical records of cases identified only through the general practice diabetes register and of cases identified only through self-report, together with matched controls, were reviewed using a standardized process. The reviewer was blinded to the case or control status of the participants. Statistical methods The case ascertainment level was estimated by capturerecapture analysis, using a log-linear model (25). Personyears of follow-up were estimated for each participant from the data available. Age-adjusted, sex-specific incidence rates per 1,000 person-years of follow-up were calculated using Poisson regression. Food frequency questionnaires were excluded if 10 or more lines had not been completed. The dietary fat was expressed as a percentage of total energy intake, and the composition of dietary fat intake was represented by the P:S ratio. The relations between the potential confounding variables and both exposures and outcome were explored by correlation analysis and regression methods. Logistic regression was used to investigate whether the risk of diabetes was associated with dietary fat intake. The simplest model included only the P:S ratio adjusted for total energy intake. The final model included the dietary fat variables adjusted for total energy intake, age, sex, family history of diabetes, smoking status, physical activity, protein (percentage of total energy intake), alcohol (g/day), body mass index, and waist:hip ratio. Since there was no evidence of an interaction between sex and the dietary P:S ratio, regression analyses are presented for men and women combined. Patterns of food consumption that were positively associated with the P:S ratio were identified for men and women separately. For each of 25 composite food groups, the median intakes (g/day) by quintiles of the P:S ratio were calculated. If the Kruskal-Wallis test indicated that the median intake for a food group was significantly higher in any of the quintiles of the P:S ratio, then that food group was allocated to the pattern of food consumption associated with that quintile of the P:S ratio. RESULTS Of the 25,631 participants who attended the first health check, 845 (3.3 percent) reported having diabetes at baseline and were excluded from the analysis. A further 2,257 men and women who reported having had a myocardial infarction, stroke, or cancer were excluded since they may have altered their diet. After excluding those with incomplete data, a total of 9,611 men and 11,861 women were left in the analysis. The mean age of the study population at baseline was 58.6 years, and the mean body mass index was 26.2 kg/m 2 (table 2); 12.5 percent of the population had a family history of diabetes. There were relatively few current smokers (12 percent), but there were more former smokers among men (53 percent) than women (32 percent). Men tended to have higher physical activity levels than women. Dietary energy, fat, and alcohol intakes were higher and carbohydrate intake and the P:S ratio were lower in men than in women. Many of the baseline characteristics of the study participants showed distinct trends across the quintiles of the P:S ratio (table 3). Since the directions of the trends were similar for men and women, the data are presented combined. Compared with

4 76 Harding et al. TABLE 2. Baseline characteristics of the study population (n = 21,472) stratified by sex, European Prospective Investigation of Cancer-Norfolk, Men (n = 9,611) Women (n = 11,861) p value* Mean (SD ) Mean (SD) Age (years) 58.8 (9.22) 58.3 (9.21) <0.001 Body mass index (kg/m 2 ) 26.4 (3.25) 26.1 (4.26) <0.001 Waist:hip ratio (0.0586) (0.0629) <0.001 Total energy intake (kj) 9,250 (2,640) 8,110 (2,300) <0.001 P:S ratio (0.220) (0.221) <0.001 Carbohydrate 46.8 (6.31) 48.3 (5.94) <0.001 Protein 16.0 (2.85) 17.4 (3.20) <0.001 Total fat 33.1 (5.65) 32.1 (5.89) <0.001 Saturated fat 12.8 (3.27) 12.1 (3.33) <0.001 Monounsaturated fat 11.7 (2.33) 11.0 (2.37) <0.001 Polyunsaturated fat 5.87 (1.91) 5.80 (1.90) Alcohol (g/day) 6.96 ( ) 2.24 ( ) <0.001 No. (%) No. (%) Family history Positive 1,138 (12) 1,537 (13) Smoking status Never smoked 3,367 (35) 6,785 (57) <0.001 Former smoker 5,056 (53) 3,728 (32) Current smoker 1,188 (12) 1,348 (11) Physical activity Level 1 (low) 2,608 (27) 3,174 (27) <0.001 Level 2 2,432 (25) 3,914 (33) Level 3 2,284 (24) 2,765 (23) Level 4 2,287 (24) 2,008 (17) * The p values relate to a test for continuous variables, a Kruskal-Wallis test for skewed data, or a chi-squared test for count data. SD, standard deviation; P:S ratio, polyunsaturated:saturated fat ratio. those in the lowest quintile of the P:S ratio, those in the highest quintile tended to be younger, to have a lower HbA 1c level, and to have a smaller waist:hip ratio. In the top quintile, a lower proportion were current smokers and physically inactive. There was no trend in body mass index or in the proportion with a family history of diabetes across the quintiles of the P:S ratio. Those in the highest quintile of the P:S ratio had a lower total energy intake and tended to consume more carbohydrate, protein, and polyunsaturated fat, less fat overall, and less saturated fat, monounsaturated fat, and alcohol. High P:S ratios resulted from a combination of lower saturated fat and higher polyunsaturated fat intakes. Seven sources of information were used to identify cases (table 1), and 553 previously unknown or incident cases of diabetes were identified. The validation study indicated that those identified only through self-report of diabetes in a follow-up health and lifestyle questionnaire were unlikely to have diabetes. Of the 41 such cases reviewed, only three had any information in their medical records to indicate that they had diabetes. Consequently, all cases identified only through self-report during follow-up (n = 139) were not considered to be incident cases of diabetes. This left 414 cases; 341 of these did not report having had a myocardial infarction, stroke, or cancer at baseline and had complete data. There was no evidence that mean age, body mass index, waist:hip ratio, total energy intake, P:S ratio, or years of follow-up differed between cases identified only by a high HbA 1c level and those identified by a physician s diagnosis. Just three sources, general practice registers, HbA 1c level, and self-report of diabetes, detected 96 percent of all cases

5 Dietary Fat and Incident Diabetes 77 TABLE 3. Baseline characteristics of the study population (n = 21,472) stratified by quintiles of the polyunsaturated:saturated fat ratio, European Prospective Investigation of Cancer-Norfolk, Quintiles of the polyunsaturated:saturated fat ratio < >0.666 Mean (SD ) Mean (SD) Mean (SD) Mean (SD) Mean (SD) * The p values relate to a nonparametric trend test for continuous variables or a chi-squared test for count data. SD, standard deviation; HbA 1c, glycated hemoglobin. A subset of 4,168 men and 5,180 women had HbA 1c measured at baseline. p value* Age (years) 60.5 (9.21) 58.7 (9.31) 57.6 (9.13) 57.8 (9.09) 57.0 (9.04) <0.001 HbA 1c (%) 5.32 (0.644) 5.27 (0.710) 5.19 (0.670) 5.19 (0.651) 5.18 (0.647) <0.001 Body mass index (kg/m 2 ) 26.1 (3.80) 26.4 (3.99) 26.4 (3.87) 26.3 (3.72) 26.0 (3.80) Waist:hip ratio (0.0948) (0.0910) (0.0914) (0.0909) (0.0895) <0.001 Total energy intake (kj) 8,860 (2,580) 8,870 (2,520) 8,860 (2,500) 8,560 (2,520) 8,460 (2,450) <0.001 Carbohydrate 45.8 (6.37) 47.6 (6.06) 48.0 (5.85) 48.3 (5.97) 48.5 (6.12) <0.001 Protein 15.9 (2.98) 16.7 (3.01) 17.2 (3.16) 17.1 (3.16) 16.9 (3.17) <0.001 Total fat 35.0 (5.53) 32.7 (5.44) 31.8 (5.53) 31.6 (5.74) 31.6 (6.07) <0.001 Saturated fat 16.2 (3.15) 13.1 (2.42) 11.9 (2.32) 11.0 (2.26) 9.72 (2.21) <0.001 Monounsaturated fat 11.8 (2.19) 11.6 (2.35) 11.3 (2.36) 11.0 (2.36) 10.6 (2.43) <0.001 Polyunsaturated fat 4.05 (0.787) 4.90 (0.912) 5.58 (1.11) 6.49 (1.36) 8.13 (1.97) <0.001 Alcohol (g/day) 4.67 ( ) 4.35 ( ) 4.68 ( ) 4.68 ( ) 4.13 ( ) No. (%) No. (%) No. (%) No. (%) No. (%) Family history Positive 495 (11.5) 538 (12.5) 563 (13.1) 547 (12.7) 534 (12.4) Smoking status Never smoked 1,782 (41) 1,963 (46) 2,089 (49) 2,156 (50) 2,162 (50) <0.001 Former smoker 1,737 (41) 1,774 (41) 1,743 (40) 1,753 (41) 1,777 (42) Current smoker 776 (18) 557 (13) 463 (11) 385 (9) 355 (8) Physical activity Level 1 (low) 1,395 (32) 1,207 (28) 1,073 (25) 1,085 (25) 1,022 (24) <0.001 Level 2 1,256 (29) 1,273 (30) 1,250 (29) 1,302 (31) 1,265 (29) Level (21) 994 (23) 1,057 (25) 1,040 (24) 1,067 (25) Level (18) 820 (19) 915 (21) 867 (20) 940 (22) (figure 1). Of the 414 cases identified, 67 percent were on the general practice diabetes registers, although this rose to 87 percent if cases identified by HbA 1c level only were excluded. One case was identified through death certificates and, since this case was not identified by any of the other sources, could not be included in the capture-recapture analysis. The analysis, based on six sources of information and an observed number of 413, estimated that the true number of cases of diabetes was 416 (95 percent confidence interval (CI): 412, 420), giving an ascertainment level of 99.3 percent. There were an estimated 43,918 years of follow-up in men and 54,196 years of follow-up in women. The age-adjusted incidence rate for men was 4.09/1,000 person-years, and for women, 2.40/1,000 person-years. Across the quintiles of the P:S ratio, there was some evidence of decreasing incidence with increasing P:S ratio (figure 2). In men the age-adjusted incidence rates in the lowest and highest quintiles of the P:S ratio were 4.35/1,000 person-years and 3.19/1,000 personyears, respectively, while in women they were 2.67/1,000 person-years and 1.71/1,000 person-years, respectively. Incident diabetes was associated with age, body mass index, waist:hip ratio, family history, physical activity, and, in women only, the P:S ratio and alcohol intake (table 4). Apart from the associations with physical activity and the P:S ratio, which were in the same direction but stronger in women than in men, the unadjusted odds ratios were similar for men and women. The P:S ratio, adjusted for total energy intake, was associated with a significantly reduced risk of

6 78 Harding et al. FIGURE 1. The three largest sources of case ascertainment, European Prospective Investigation of Cancer-Norfolk, (n = 25,631). HbA 1c, glycated hemoglobin. Numbers within circles, number of cases identified by source and the overlap between sources. diabetes (odds ratio (OR) = 0.84 per standard deviation change, 95 percent CI: 0.75, 0.94) (table 5). Adjusting for age and then sex attenuated this association substantially, although it remained statistically significant (OR = 0.88, 95 percent CI: 0.79, 0.99). Adjusting further for family history of diabetes, smoking status, physical activity, total fat, protein, and alcohol had little effect on the association between the P:S ratio and risk of diabetes. The association was no longer statistically significant after adjusting for body mass index and waist:hip ratio (OR = 0.91, 95 percent CI: 0.81, 1.03). There was no indication that sex modified the effect of the dietary P:S ratio on the risk of diabetes (p = 0.50), or that the effect of the P:S ratio was nonlinear (p = 0.39 for the quadratic term). There was no evidence that total fat intake had any effect on the risk of developing diabetes. Adjusted only for total energy intake, the odds ratio for total fat intake was 1.01 (95 percent CI: 0.99, 1.03) and, in the fully adjusted model, was 1.00 (95 percent CI: 0.98, 1.02). The P:S ratio may give a direct indication of the ratio of types of fat in the diet, but it may also be a marker of an overall dietary pattern. To investigate this, we studied the dietary patterns associated with the quintiles of the P:S ratio. The foods that were most strongly associated with quintiles of the dietary P:S ratio were similar for men and women (table 6). The dietary pattern of men and women in the lowest quintile of the P:S ratio was distinguished by a high intake of alcoholic beverages, eggs, milk, processed and other meat, sugars, and tea. Those in the third quintile of the P:S ratio had a high intake of beverages, cakes, cereals, cheese, nondairy sauces, other dairy products, processed and other meat, offal, and potatoes. Men and women in the top quintile of the P:S ratio were differentiated by high consumption of bread, breakfast cereal, cheese, fish, fruit, legumes, spreadable fats (including butter and other spreadable fats), nondairy sauces, nuts, soups, vegetables, and vegetable dishes. The spreadable fat intake in the top quintile of the P:S ratio was more strongly correlated with polyunsaturated fat intake (r = 0.59) than in the lowest quintile (r = 0.28), indicating that the spreadable fats consumed by those FIGURE 2. Age-adjusted incidence rates per 1,000 person-years by quintiles of the dietary polyunsaturated:saturated fat ratio (P:S ratio), European Prospective Investigation of Cancer-Norfolk, (n = 21,472). The figure shows incidence rates with upper 95% confidence intervals.

7 Dietary Fat and Incident Diabetes 79 TABLE 4. Baseline characteristics of the study population (n = 21,472) stratified by incident diabetes status and sex, European Prospective Investigation of Cancer-Norfolk, With incident diabetes (n = 198) Men Without diabetes (n = 9,413) * p 0.05; ** p 0.01; *** p Odds ratios from simple logistic regression. SD, standard deviation; P:S ratio, polyunsaturated:saturated fat ratio. Odds ratio With incident diabetes (n = 143) Women Without diabetes (n = 11,718) Mean (SD ) Mean (SD) Mean (SD) Mean (SD) Age (years) 62.6 (7.92) 58.7 (9.23) 1.05*** 62.1 (8.89) 58.3 (9.20) 1.04*** Body mass index (kg/m 2 ) 28.9 (4.31) 26.4 (3.20) 1.20*** 31.2 (5.51) 26.0 (4.20) 1.20*** Waist:hip ratio (0.0600) (0.0582) *** (0.0714) (0.0623) *** Total energy intake (kj) 9,160 (2,840) 9,250 (2,630) ,000 (2,590) 8,110 (2,290) 1.00 P:S ratio (0.211) (0.220) (0.213) (0.221) 0.38* Carbohydrate 46.5 (6.77) 46.8 (6.30) (6.06) 48.3 (5.94) 1.01 Protein 16.2 (3.20) 16.0 (2.84) (3.36) 17.4 (3.19) 1.04 Total fat 33.4 (6.31) 33.1 (5.64) (5.77) 32.1 (5.90) 1.00 Saturated fat 13.1 (3.74) 12.8 (3.26) (3.34) 12.1 (3.33) 1.04 Monounsaturated fat 11.8 (2.45) 11.7 (2.33) (2.28) 11.0 (2.37) 1.00 Polyunsaturated fat 5.66 (1.84) 5.87 (1.91) (1.91) 5.80 (1.90) 0.92 Alcohol (g/day) 6.84 ( ) 6.98 ( ) (0 4.66) 2.32 ( ) 0.95*** Family history No. (%) No. (%) No. (%) No. (%) Positive 36 (18) 1,102 (12) 1.68** 31 (22) 1,505 (13) 1.87** Smoking status Never smoked 57 (29) 3,310 (35) (50) 6,713 (57) 1.00 Former smoker 121 (61) 4,935 (52) 1.42* 54 (38) 3,674 (31) 1.37 Current smoker 20 (10) 1,168 (12) (12) 1,331 (11) 1.19 Physical activity Level 1 (low) 75 (38) 2,533 (27) (46) 3,108 (27) 1.00 Level 2 49 (25) 2,383 (25) 0.69* 40 (28) 3,874 (33) 0.49*** Level 3 41 (20) 2,243 (24) 0.62* 20 (14) 2,745 (23) 0.34*** Level 4 33 (17) 2,254 (24) 0.49*** 17 (12) 1,991 (17) 0.40*** Odds ratio in the top quintile were likely to contain more polyunsaturated fat. DISCUSSION In this study we provide evidence of a consistent relation between the pattern of dietary fat intake and the risk of diabetes. A higher P:S ratio was associated with a reduced risk of diabetes, independent of age, sex, family history of diabetes, smoking status, physical activity, protein, and alcohol. However, the association was no longer statistically significant when also adjusted for body mass index and waist:hip ratio. Other observational studies have reported beneficial effects of a higher dietary P:S ratio. The Ely Study reported an independent association between the P:S ratio and fasting insulin levels (26), and in this EPIC-Norfolk cohort, the P:S ratio was inversely associated with HbA 1c levels (21). A recent report from the US Nurses Health Study (17) shows a significant inverse association between the P:S ratio and the risk of diabetes, with a relative risk of approximately 0.80 for the highest compared with the lowest quintile of dietary P:S ratio. In our fully adjusted multivariate analysis, the odds ratio for those in the top quintile relative to the lowest quintile was The Ely Study and EPIC-Norfolk used the same food frequency questionnaire, which was based on the questionnaire used in the US Nurses Health Study. Intervention studies in which the dietary P:S ratio was increased, directly by substituting polyunsaturated

8 80 Harding et al. TABLE 5. Odds ratios for incident cases of type 2 diabetes associated with the polyunsaturated:saturated fat ratio, European Prospective Investigation of Cancer-Norfolk, (n = 21,472)* Terms included in the model Odds ratio 95% confidence interval P:S ratio, total energy intake , age , sex , family history + smoking + physical activity , total fat, protein, alcohol , body mass index, waist:hip ratio , 1.03 * Data are odds ratios for a 1-standard deviation change of 0.22 in the polyunsaturated:saturated fat ratio (P:S ratio) for 1) the basic model with the P:S ratio adjusted for total energy intake and 2) the more complex models developed by including additional potential confounding variables sequentially. For a change in the P:S ratio = 1, the odds ratios are 0.46, 0.59, 0.55, 0.59, 0.56, and 0.69, respectively. The odds ratio for the P:S ratio was unchanged if monounsaturated fat was included in the model instead of total fat. TABLE 6. Food groups associated with quintiles of the polyunsaturated: saturated fat ratio, European Prospective Investigation of Cancer-Norfolk, (n = 21,472) Quintile 1 Quintile 3 Quintile 5 Men Alcoholic beverages Beverages Bread Eggs Cakes Breakfast cereal Milk Cereals Cheese Other meat Cheese Fish Processed meat Nondairy sauces Fruit Sugars Other dairy products Legumes Tea Other meat Spreadable fats Offal Nondairy sauces Processed meat Nuts Potatoes Soups Tea Vegetables Vegetable dishes Vegetable dishes Women Alcoholic beverages Beverages Bread Eggs Cakes Breakfast cereal Spreadable fats Cereals Cereals Milk Cheese Cheese Processed meat Legumes Fish Sugars Nondairy sauces Fruit Tea Other dairy products Legumes Other meat Spreadable fats Offal Nondairy sauces Processed meat Nuts Potatoes Soups Soups Vegetables Vegetable dishes

9 Dietary Fat and Incident Diabetes 81 fat (27) for saturated fat or indirectly by substituting monounsaturated fat for saturated fat (28, 29), reported improved insulin sensitivity. Dietary modification and increasing exercise have reduced the risk of diabetes in various populations, but the dietary components were not sufficiently specific to identify the effect of the P:S ratio (30 32). The study demonstrated the importance of using multiple sources for the purpose of case ascertainment. Using the a priori definition of diabetes, 414 previously undiagnosed and incident cases were identified. Of the 277 participants on the general practice diabetes registers, 50 percent did not report having diabetes at follow-up. If the EPIC-Norfolk cohort is representative of other populations, studies relying on selfreport may underestimate the incidence of diabetes substantially. The definition of a case was strictly applied. As a result of the validation study, the 139 participants who reported having diabetes but for whom there was no other independent evidence to indicate that they were diabetic were not considered to be cases. The question of whether these respondents mistakenly reported having diabetes by ticking the wrong box in the follow-up questionnaires or whether they genuinely believed that they had diabetes could only have been resolved by contacting them. There may have been some who were truly diabetic among these 139 participants, and this would have led to some attenuation of the observed associations. The capture-recapture analysis indicated that 99 percent of cases had been identified, implying that the cases identified were representative of cases in this cohort. The few who were not identified may have been systematically different from those who were, but their numbers are likely to be too small to create a significant bias. Since HbA 1c was used to identify cases, both clinically diagnosed and previously undiagnosed cases of diabetes were included in the study. This gave the study a broader coverage of diabetic cases than prospective studies that included only clinically diagnosed cases. Ideally, incident and prevalent diabetes cases would both be defined using the criteria established by the World Health Organization. However, this would necessitate undertaking oral glucose tolerance testing on all individuals not only at baseline but also at follow-up. Strictly speaking, the diagnosis would then be established using a confirmatory test on a separate occasion. This may be possible in small studies and is necessary for clinical practice, but it is unfeasible in a population study of the scale reported in this paper. Although a number of prospective studies have found no association between dietary fat and the risk of diabetes (13 16), others have reported associations with total fat and the specific types of fat (7, 10, 11). The studies used various methods for assessing diet, each with its own error structure, and if they adjusted for potential confounding variables, different confounders were included. Such differences may partly account for inconsistencies in the reported results. Attenuation through measurement error will also affect the results, so that any association that may exist with diet may not be observed, particularly if there is little dietary variation within a population. Confounding by other dietary factors and residual confounding by those included may also affect the results. There was evidence of some reporting bias in the EPIC-Norfolk food frequency questionnaire validation study (24). Individuals in the top quintile of the urine:dietary nitrogen ratio tended to be heavier and more obese, and they did not appear to be reporting their usual diet. In the food frequency questionnaire, these individuals reported significantly lower intakes of energy, protein, and carbohydrates than those in the lower four quintiles, but the difference in fat intake between these groups was not statistically significant. Obesity is the major known risk factor for diabetes. Crosssectionally at baseline and prospectively in those who attended the second health check, the age- and sex-adjusted P:S ratio was inversely associated with body mass index and waist:hip ratio. In our study, adjusting for body mass index and waist:hip ratio attenuated the association between the P:S ratio and the risk of diabetes substantially, which suggests that the association between the P:S ratio and diabetes risk was mediated in part by obesity. If obesity is on the causal pathway between the P:S ratio and diabetes, then adjusting for body mass index and waist:hip ratio may inappropriately remove evidence that the P:S ratio influences diabetes risk. Whether obesity lies on the causal pathway is still unclear, since obesity is neither necessary nor sufficient for developing diabetes. Intercorrelations between foods or nutrients have been used previously to identify food patterns and to investigate the associations between these patterns and the risk of diabetes (33 36). The actual food patterns reported are population specific, but healthy food patterns associated with a lower risk of diabetes were identified in each of the studies. Despite differences in study design and methodology, similar patterns and associations have been observed. In general, diets high in fatty, processed, or refined foods tend to increase the risk of hyperglycemia or diabetes, while diets rich in fruit, vegetables, fiber, and fish tend to be protective. In our study, we identified patterns of food consumption, broadly similar for men and women, that were associated with the quintiles of the dietary P:S ratio. Participants in the top quintile of the P:S ratio consumed a healthy diet, and those in the lowest quintile consumed a diet rich in fatty, processed, and refined foods. In conclusion, our study indicated that increasing the dietary P:S ratio independently reduced the risk of diabetes. A diet rich in bread, breakfast cereals, fish, fruit, spreadable fats rich in polyunsaturates, nuts, and vegetables, and low in alcoholic beverages, eggs, milk, processed and other meat, and sugars, distinguished men and women with a high dietary P:S ratio. Long-term (2 7 years) intervention studies relating to ischemic heart disease suggest that increasing the dietary P:S ratio to greater than 1.0 is feasible (37). Consequently, modifications in the composition of dietary fat may represent a realistic approach for reducing the risk of diabetes in the general population. ACKNOWLEDGMENTS The EPIC-Norfolk cohort is supported by grant funding from the Cancer Research Campaign, the Medical Research Council, the Stroke Association, the British Heart Founda-

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