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Nutritional Epidemiology

Intake of Vegetables, Legumes, and Fruit, and Risk for All-Cause, Cardiovascular, and Cancer Mortality in a European Diabetic Population^1,2

³ Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, 14558 Germany; ⁴ Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, 3508 The Netherlands; ⁵ Department of Hygiene and Epidemiology, University of Athens Medical School, Athens, 11527 Greece; ⁶ Nutritional Epidemiology Unit, Istituto Nazionale dei Tumori, Milan, 20133 Italy; ⁷ Institute of Cancer Epidemiology, Danish Cancer Society, Copenhagen, DK-2100 Denmark; ⁸ Cancer Registry, Azienda Ospedaliera "Civile M.P. Arezzo", Ragusa, 97100 Italy; ⁹ Department of Clinical and Experimental Medicine, Federico II University, Naples, I-80131 Italy; ¹⁰ Molecular and Nutritional Epidemiology Unit, CSPO-Scientific Institute of Tuscany, Florence, 50139 Italy; ¹¹ Inserm, (Institut National de la Santé et de la Recherche Médicale), ERI 20, Villejuif, F-94805 France; ¹² Division of Clinical Epidemiology, German Cancer Research Centre, Heidelberg, 69120 Germany; ¹³ Institute of Epidemiology and Social Medicine, University of Aarhus, Aarhus, DK-9100 Denmark; ¹⁴ Department of Public Health of Guipuzkoa, San Sebastian, 4-20013 Spain; ¹⁵ Public Health Institute of Navarra, Pamplona, 31003 Spain; ¹⁶ Department of Epidemiology, Catalan Institute of Oncology, Barcelona (ICO-IDIBELL), 08907 Spain; ¹⁷ Epidemiology Department, Murcia Health Council, CIBER en Epidemiologia y Salud Publica (CIBERESP), E-30008 Spain; ¹⁸ Medical Research Council Dunn Human Nutrition Unit, Cambridge, CB1 8RN UK; ¹⁹ Department of Public Health and Primary Care, University of Cambridge, CB2 2QQ UK; ²⁰ Cancer Epidemiology Unit, University of Oxford, Oxford, OX3 7LF UK; ²¹ Imperial College London, London, W2 1PG UK; ²² International Agency for Research on Cancer, Lyon, 69372 France; ²³ National Institute for Public Health and the Environment, Bilthoven, 3720 The Netherlands; ²⁴ Department of Medicine, Lund University, Malmö University Hospital, Malmö, 20502 Sweden; ²⁵ Department of Clinical Sciences, Lund University, Malmö, SE-20502 Sweden; ²⁶ Department of Public Health and Clinical Medicine, Nutritional Research, Umea University, Umea, 90187 Sweden; ²⁷ Department of Odontology, Cariology, Umea University, Umea, 90187 Sweden; and ²⁸ Department of Preventive Medicine, Institute of Community Medicine, University of Tromsø, Tromsø, 9037 Norway

^* To whom correspondence should be addressed. E-mail: ute.noethlings{at}dife.de.

	ABSTRACT

TOP ABSTRACT Introduction Subjects, Materials, and Methods Results Discussion LITERATURE CITED

 
We examined the associations of intake of vegetables, legumes and fruit with all-cause and cause-specific mortality in a population with prevalent diabetes in Europe. A cohort of 10,449 participants with self-reported diabetes within the European Prospective Investigation into Cancer and Nutrition study was followed for a mean of 9 y. Intakes of vegetables, legumes, and fruit were assessed at baseline between 1992 and 2000 using validated country-specific questionnaires. A total of 1346 deaths occurred. Multivariate relative risks (RR) for all-cause mortality were estimated in Cox regression models and RR for cause-specific mortality were derived in a competing risk model. An increment in intake of total vegetables, legumes, and fruit of 80 g/d was associated with a RR of death from all causes of 0.94 [95% CI 0.90–0.98]. Analyzed separately, vegetables and legumes were associated with a significantly reduced risk, whereas nonsignificant inverse associations for fruit intake were observed. Cardiovascular disease (CVD) mortality and mortality due to non-CVD/non-cancer causes were significantly inversely associated with intake of total vegetables, legumes, and fruit (RR 0.88 [95% CI 0.81–0.95] and 0.90 [0.82–0.99], respectively) but not cancer mortality (1.08 [0.99–1.17]). Intake of vegetables, legumes, and fruit was associated with reduced risks of all-cause and CVD mortality in a diabetic population. The findings support the current state of evidence from general population studies that the protective potential of vegetable and fruit intake is larger for CVD than for cancer and suggest that diabetes patients may benefit from a diet high in vegetables and fruits.

	Introduction

TOP ABSTRACT Introduction Subjects, Materials, and Methods Results Discussion LITERATURE CITED

Vegetable and fruit intakes have been extensively investigated as risk factors for cancer (10), CVD (11,12), or mortality (13–15) in the general population; however, data on associations between dietary behavior, including vegetables and fruit intake, and disease outcomes in diabetic populations are scarce (2). Therefore, we analyzed data from the European Prospective Investigation into Cancer and Nutrition (EPIC) study to examine the associations between intake of vegetables, legumes, and fruit, and risk for all-cause and cause-specific mortality in a population of diabetic individuals.

	Subjects, Materials, and Methods

TOP ABSTRACT Introduction Subjects, Materials, and Methods Results Discussion LITERATURE CITED

 
EPIC is an ongoing multicenter prospective cohort study designed to investigate associations between diet and other lifestyle behaviors with chronic diseases, especially cancer. A detailed description of the study design and methods used can be found elsewhere (16). In brief, between 1992 and 2000, >500,000 study participants were recruited in 23 study centers located in 10 European countries to be followed for cancer incidence and cause-specific mortality. Participants ranging from 35 to 70 y were recruited in study centers in France, Germany, Greece, Italy, The Netherlands, Spain, United Kingdom, Sweden, Denmark, and Norway. Study populations were population-based samples from designated geographic areas (e.g. town or province), with the exceptions of France (members of the health insurance for state school employees), subsamples of the Italian and Spanish cohort (blood donors), Utrecht (The Netherlands), Florence (Italy; women invited for breast cancer screening), and a subsample in Oxford (health-conscious group, vegetarians). Individuals signed informed consent forms, after which self-administered diet and lifestyle questionnaires were mailed to the participants. In the Spanish centers, Ragusa, Naples, and Greece, interviewer-administered questionnaires were used. All participants were invited to a study center for an examination that included anthropometric and blood pressure measurements. Approval for this study was obtained from the ethical review boards of the International Agency for Research on Cancer and from all local institutions where subjects had been recruited for the EPIC study.

    Study population. The study population for this study was the group of participants in the EPIC cohort reporting a diagnosis of diabetes mellitus at baseline (n = 13,838). After exclusion of diabetic participants missing dietary questionnaire information (n = 144) or date of death (n = 3) or with implausible energy intake (top or bottom 1% of the ratio of energy intake:energy requirement; n = 437), a total of 13,254 participants with self-reported diabetes mellitus were identified. Of this population, 1718 participants missing information on age at diabetes diagnosis that included the cohorts from Norway and Umea (Sweden) and 1087 participants without information on waist-to-hip ratio were excluded. A total of 10,449 participants with self-reported diabetes mellitus were identified for this analysis.

    Dietary assessment. Dietary intake during the previous 12 mo was assessed at baseline by means of country-specific instruments that had been developed and validated in a series of studies within the various source populations (17). Extensive quantitative dietary questionnaires with up to 300–350 food items were used in Italy, The Netherlands, Germany, Greece, France, and Spain. Semiquantitative questionnaires were used in Denmark and Naples. Combined dietary methods of food records and questionnaires were used in the UK and Malmö (16).

In addition, a highly standardized reference dietary measurement was taken from an 8% age-stratified random sample of the cohort using a computerized 24-h dietary recall (18,19).

To evaluate associations between fruit and vegetable consumption and mortality risk, total vegetables, legumes, and fruit intake were considered separately and combined. Soy products were included in the legumes food group. Furthermore, vegetable subgroups were analyzed: fruiting, root (not including potatoes), leafy vegetables, cabbages, mushrooms, and garlic/onion vegetables. A detailed description of the food groups and their consumption in the EPIC study has been described in (20).

    Assessment of anthropometric and lifestyle exposure. In all EPIC centers, except for Oxford and France, height, weight, and waist and hip circumference were measured on all subjects using similar protocols. In Oxford, measurements were available only for a restricted number of participants, but self-reported weight, height, and waist and hip circumference were obtained from all individuals. Gender- and age-specific anthropometric values were predicted from subjects with measured and self-reported body measures using linear regression models as described previously (21). For France, only participants with measured waist and hip circumferences were included.

Further lifestyle- and health-related variables were collected using nondietary questionnaires. These included questions on smoking history, education, occupational history, physical activity, and medical history, including diabetes mellitus, heart attack, cancer, hypertension, and hyperlipidemia. In most centers, the assessment of physical activity covered core questions about recreational physical activities (cycling, walking, gardening, sports) and household activities (housekeeping and do-it-yourself) (22). Variables were assigned metabolic equivalent task-h/wk and metabolic equivalent task scores were calculated. Furthermore, diabetic participants were asked whether or not they used insulin.

    Outcome ascertainment. Causes and dates of deaths were ascertained using record linkages with local, regional, or central cancer registries, boards of health, death indexes (Denmark, Italy, the Netherlands, Spain, the United Kingdom), or by active follow-up (Germany, Greece, France). France, Germany, and Greece identified deceased subjects with follow-up mailings and subsequent inquiries to municipality registries, regional health departments, physicians, or hospitals. Participants were followed from study entry until death, emigration, withdrawal, or end of follow-up period. Mortality data were coded following the rules of the 10th revision of the International Statistical Classification of Diseases, Injuries and Causes of Death (ICD-10), where the underlying cause is the official cause of death. On March 1, 2007, 1346 deaths had been registered among 10,449 diabetic EPIC participants. For the cause-specific analysis, death due to circulatory diseases as CVD (ICD-10 I00-I99; n = 517), death due to cancer (ICD-10 C00-C97; n = 319), and death due to all other specified causes were grouped (n = 323); 187 of deceased diabetic participants for whom no information on the specific cause of death was available were excluded from the cause-specific analysis but were included in the analysis for total mortality.

    Statistical analysis. Food intakes were analyzed as predicted by regression calibration. Dietary intakes for the total cohort were calibrated using a fixed effects linear model in which gender- and center-specific 24-h dietary recall data were regressed on the questionnaire data controlling for covariates (weight, height, age, and season of administration of dietary questionnaires). A set of weights was used to model the effect of season and the day (weekdays vs. weekend days) when the 24-h recall was obtained. Zero consumption values in the dietary questionnaire were excluded from the regression calibration models and kept as 0 values. Single values negative after the calibration procedure were set to 0 as well. Details of the calibration procedure and its rationale can be found in (23,24).

For the analysis of all-cause mortality, hazard rate ratios were estimated as relative risks (RR) using Cox proportional hazard models with center and age at enrolment in 1-y categories as stratum variables to control for differences in questionnaire design, follow-up procedures, and other nonmeasured center effects, and to be more robust against violation of the proportionality assumption. Age was used as the primary time variable with entry time defined as the subject's age in days at recruitment and exit time defined as the subject's age in days at death or censoring (lost to follow-up or end of follow-up period). Participants have been followed for 9 y with a range of <1 to >14 y. Hazard rate ratios of specific causes of death estimated as RR were derived from a competing risk model (25,26) with CI derived from robust estimates of the covariance matrix (27). This method is adequate when the exposure is investigated in relation to multiple outcomes simultaneously. In this model, RR estimates were mutually controlled for the association of vegetable, legume, or fruit intake with all other outcomes.

Multivariate regression models were adjusted for sex; smoking status defined as never, former (quit >10 y ago; 10 y ago, or unknown), current (<20, or unknown; 20 cigarettes smoked per day); self-reported heart attack, hypertension, or cancer at baseline (yes, no/unknown); waist-to-hip ratio (continuous); insulin treatment (yes, no/unknown); age at diabetes diagnosis (continuous); energy intake (continuous); and alcohol intake (continuous). To examine if associations for intake of total vegetables, legumes, and fruit differ between individuals who are at different mortality risk per se, potential interactions with sex, smoking status, age at diabetes diagnosis, or waist-to-hip ratio were analyzed with the respective interaction terms in regression models. As a further sensitivity analysis, we restricted the study population to participants 60 y of age.

RR were estimated for quartiles of vegetables, legumes, and fruit intakes based on the distribution of intakes in diabetic participants. As a test for trend, median values for quartiles were analyzed as continuous variables in the respective regression models. Models were also fit on a continuous scale. Additionally, restricted cubic spline regression (28,29) was used to examine nonlinearity of the RR functions.

All statistical tests were 2-tailed and P < 0.05 was considered significant. Analyses were performed using SAS 9.1 (SAS Institute).

	Results

TOP ABSTRACT Introduction Subjects, Materials, and Methods Results Discussion LITERATURE CITED

 
Mean age at baseline ranged from 56 to 59 y across quartiles of vegetable, legume, and fruit intake, not showing a trend (Table 1). The percentage of diabetic participants treated with insulin was inversely associated with intake of vegetables, legumes, and fruit, ranging from 32% in the lowest quartile to 16% in the highest. The percentage of diabetics with a self-reported heart attack at baseline was also inversely associated with intake of total vegetables, legumes, and fruit. There was a positive association with self-reported absence of hypertension at baseline and hyperlipidemia with vegetable, legume, and fruit intake. A total of 1346 deaths occurred, 517 due to circulatory diseases, 319 due to cancer, and 323 due to other specified causes.

Analyses of vegetable subgroups showed intake of root vegetables was associated with a significantly decreased RR (0.91 [95% CI 0.84–0.99]) for an increase in intake of 20 g/d (Table 3). Associations for the remaining vegetable subgroups, except mushrooms, were inverse but not significant (Table 3).

	Discussion

TOP ABSTRACT Introduction Subjects, Materials, and Methods Results Discussion LITERATURE CITED

To our knowledge, only 3 prospective studies investigated food intakes as risk factors for disease incidence or mortality in diabetic populations to date (30–32) and only one of those evaluated vegetables, legumes, and fruit (32). In that study, overall mortality and cardiovascular mortality was investigated in the Greek arm of the EPIC study, analyzing data of a subgroup of 1013 participants who took drugs for diabetes mellitus and did not report any comorbidities at enrollment (32). Estimated RR for total mortality and vegetables (1.10 [95% CI 0.80–1.51]), legumes and potatoes (0.85 [95% CI 0.63–1.13]), and fruits and nuts (0.93 [95% CI 0.69–1.26]) were not significant. The associations between vegetables and fruit intake and CVD and cancer have been extensively investigated in the general population and have been found to be inverse for CVD (11,12,33–36). Findings for cancer were less consistent (10,33).

Of note, inverse associations seemed to be stronger for vegetables and legumes than for fruit intake in the regression models for all-cause mortality and cause-specific mortality, suggesting that consumption of vegetables and legumes is more beneficial for diabetes patients than consumption of fruit.

Our findings seem plausible, because type 2 diabetes often is associated with overweight or obesity. Modest weight loss has been shown to improve insulin sensitivity and reduces the CVD risk factors associated with type 2 diabetes (37–39). A diet high in vegetables, legumes, and fruit might help diabetic patients lose weight (39). However, numerous possible mechanisms explaining the effect of fruits and vegetables on health outcomes have been discussed, e.g. the antioxidative effects of vitamins, minerals, or polyphenols, a homocysteine-reducing effect of folate and B vitamins, or the enhancement of detoxification enzymes (12,40).

The question arises whether amounts of vegetables and legumes consumed by diabetic men and women differ from those consumed by the nondiabetic population. A comparison of intakes assessed in the EPIC study showed that vegetable and legume intakes, as well as intake of fruit, were slightly higher in the diabetic than the nondiabetic population (data not shown). However, different studies have reported that the majority of adults with type 2 diabetes did not follow guidelines for fruit and vegetable consumption (41) and healthy foods might be overreported, because dietary energy intake has been shown to be underreported in obese diabetic patients (42). Although this type of misreporting would not be of concern for risk assessments within the diabetic population, absolute intakes as reported in our study should be interpreted cautiously.

Our study has several limitations. First is its reliance on self-reports of diabetes. However, in a different setting, a comparison between self-reports and medical records in a group of elderly men in the US has shown that concordance was excellent for diabetes ( = 0.84) and substantial for hypertension ( = 0.70) (43). Other studies in the US and Canada reported similar (44,45). Second, we were unable to distinguish between type 1 and 2 diabetes diagnoses. However, our sensitivity analysis using data of those individuals diagnosed at or after 40 y old showed the same inverse association as in the overall cohort. Third, we were unable to adjust for use of oral hypoglycemic medication and information on use of insulin was not available for all participants. We also lacked information about if and what kind of advice about diet diabetes patients might have received. Those participants reporting higher vegetable and fruit intake might comply better with other dietary and lifestyle recommendations and treatment, which could have affected the course of their diabetes. Fourth, information on prevalent heart attacks, hypertension, and cancer, which we adjusted for in our analysis, were also self-reported at baseline and the percentage of unknown conditions was higher for participants with low intake of fruit, vegetables, and legumes. We therefore cannot rule out residual confounding. However, substitution of self-reported hypertension by blood pressure measurement, which was available for about two-thirds of the diabetic population, did not change our conclusions. Also, after excluding participants with unknown status of prevalent heart attacks, hypertension, or cancer, the association with total vegetables, legumes, and fruit intake was significantly inverse. Finally, as described previously (24), categorical variables based on the predicted dietary intake distribution in the calibration model have to be interpreted with caution, because the predicted variation does not reflect true variation.

The most important strength of our study is its sample size. To our knowledge, this is the largest observational cohort of diabetic individuals that investigated associations between lifestyle factors and mortality. Furthermore, the multicentric design with centers spread across Europe enabled the coverage of a large variation in exposures. Also, we controlled for important risk factors in our analyses, including the age at diabetes diagnosis and treatment with insulin. Additionally, the application of a competing risk model allowed the evaluation of several outcomes at the same time without losing statistical power due to exclusion of subjects.

In conclusion, our study showed that a diet high in vegetables, legumes, and fruit was associated with a reduced risk of all-cause mortality in a European diabetic population. Vegetables, legumes and fruit seemed to have impact especially on CVD mortality, and not on cancer mortality. Our study lends support to the current state of evidence from general population studies that the protective potential of high vegetable and fruit intake is larger for CVD than for cancer. Furthermore, our study underlines the recommendation for the diabetic population to eat large amounts of vegetables, legumes, and fruit.

	FOOTNOTES

 
¹ Supported by the Community (Directorate-General SANCO: Directorate X-Public Health and Risk Assessment; grant agreement no. 2004126 to European Prospective Investigation into Cancer and Nutrition (EPIC) Elderly Network on Aging and Health (EPIC-Elderly NAH). Sole responsibility lies with the author and the Commission is not responsible for any use that may be made of the information contained herein. Financial support for the EPIC study from: European Commission: Public Health and Consumer Protection Directorate 1993-2004; Research Directorate-General 2005-; Ligue contre le Cancer, France; Société 3M, France; Mutuelle Générale de l'Education Nationale; Institut National de la Santé et de la Recherche Médicale; German Cancer Aid; German Cancer Research Center; German Federal Ministry of Education and Research; Danish Cancer Society; Health Research Fund of the Spanish Ministry of Health; the participating regional governments and institutions of Spain; Instituto de Salud Carlos III Network Red Centros de Investigación Cooperativa en Epidemiologia y Salud Pública, Spain grant C03/09; ISCIII, Red de Centros RCESP, C03/09, Spain; Cancer Research UK; Medical Research Council, UK; Food Standards Agency, UK; the Wellcome Trust, UK; Greek Ministry of Health; Greek Ministry of Education; Italian Association for Research on Cancer; Italian National Research Council; Dutch Ministry of Public Health, Welfare, and Sports; Dutch Ministry of Health; Dutch Prevention Funds; LK Research Funds; Dutch Zorg Onderzoek Nederland; World Cancer Research Fund; Swedish Cancer Society; Swedish Scientific Council; Regional Government of Skane, Sweden; and Norwegian Cancer Society.

² Author disclosures: U. Nöthlings, M. B. Schulze, C. Weikert, H. Boeing, Y. T. van der Schouw, C. Bamia, V. Benetou, P. Lagiou, V. Krogh, J. W. J. Beulens, P. H. M. Peeters, J. Halkjær, A. Tjønneland, R. Tumino, S. Panico, G. Masala, F. Clavel-Chapelon, B. de Lauzon, M.-C. Boutron-Ruault, M.-N. Vercambre, R. Kaaks, J. Linseisen, K. Overvad, L. Arriola, E. Ardanaz, C. A. Gonzalez, M.-J. Tormo, S. Bingham, K.-T. Khaw, T. J. A. Key, P. Vineis, E. Riboli, P. Ferrari, P. Boffetta, H. B. Bueno-de-Mesquita, D. L. van der A, G. Berglund, E. Wirfält, G. Hallmans, I. Johansson, E. Lund, and A. Trichopoulou, no conflicts of interest.

²⁹ Abbreviations used: CVD, cardiovascular disease; EPIC, European Prospective Investigation into Cancer and Nutrition; ICD-10, 10th revision of the International Statistical Classification of Diseases, Injuries and Causes of Death; RR, relative risk.

Manuscript received 31 October 2007. Initial review completed 1 December 2007. Revision accepted 26 January 2008.

	LITERATURE CITED

TOP ABSTRACT Introduction Subjects, Materials, and Methods Results Discussion LITERATURE CITED

 

1. Nutrition Recommendations and Interventions for Diabetes. A position statement of the American Diabetes Association. Diabetes Care. 2007;30 Suppl 1:S48–65.[Free Full Text]

2. Moore H, Summerbell C, Hooper L, Cruickshank K, Vyas A, Johnstone P, Ashton V, Kopelman P. Dietary advice for treatment of type 2 diabetes mellitus in adults. Cochrane Database Syst Rev. 2004;CD004097.

3. American Diabetes Association. Standards of medical care in diabetes–2007. Diabetes Care. 2007;30 Suppl 1:S4–41.[Free Full Text]

4. Kannel WB, McGee DL. Diabetes and cardiovascular disease. The Framingham study. JAMA. 1979;241:2035–8.[Abstract/Free Full Text]

5. Woodward M, Zhang X, Barzi F, Pan W, Ueshima H, Rodgers A, MacMahon S. The effects of diabetes on the risks of major cardiovascular diseases and death in the Asia-Pacific region. Diabetes Care. 2003;26:360–6.[Abstract/Free Full Text]

6. Gu K, Cowie CC, Harris MI. Mortality in adults with and without diabetes in a national cohort of the U.S. population, 1971–1993. Diabetes Care. 1998;21:1138–45.[Abstract]

7. Larsson SC, Orsini N, Wolk A. Diabetes mellitus and risk of colorectal cancer: a meta-analysis. J Natl Cancer Inst. 2005;97:1679–87.[Abstract/Free Full Text]

8. Huxley R, Ansary-Moghaddam A, Berrington de Gonzalez A, Barzi F, Woodward M. Type-II diabetes and pancreatic cancer: a meta-analysis of 36 studies. Br J Cancer. 2005;92:2076–83.[CrossRef][Medline]

9. Bonovas S, Filioussi K, Tsantes A. Diabetes mellitus and risk of prostate cancer: a meta-analysis. Diabetologia. 2004;47:1071–8.[Medline]

10. Vainio H, Weiderpass E. Fruit and vegetables in cancer prevention. Nutr Cancer. 2006;54:111–42.[CrossRef][Medline]

11. Dauchet L, Amouyel P, Hercberg S, Dallongeville J. Fruit and vegetable consumption and risk of coronary heart disease: a meta-analysis of cohort studies. J Nutr. 2006;136:2588–93.[Abstract/Free Full Text]

12. Ness AR, Powles JW. Fruit and vegetables, and cardiovascular disease: a review. Int J Epidemiol. 1997;26:1–13.[Abstract/Free Full Text]

13. Steffen LM, Jacobs DR Jr, Stevens J, Shahar E, Carithers T, Folsom AR. Associations of whole-grain, refined-grain, and fruit and vegetable consumption with risks of all-cause mortality and incident coronary artery disease and ischemic stroke: the Atherosclerosis Risk in Communities (ARIC) Study. Am J Clin Nutr. 2003;78:383–90.[Abstract/Free Full Text]

14. Genkinger JM, Platz EA, Hoffman SC, Comstock GW, Helzlsouer KJ. Fruit, vegetable, and antioxidant intake and all-cause, cancer, and cardiovascular disease mortality in a community-dwelling population in Washington County, Maryland. Am J Epidemiol. 2004;160:1223–33.[Abstract/Free Full Text]

15. Rissanen TH, Voutilainen S, Virtanen JK, Venho B, Vanharanta M, Mursu J, Salonen JT. Low intake of fruits, berries and vegetables is associated with excess mortality in men: the Kuopio Ischaemic Heart Disease Risk Factor (KIHD) Study. J Nutr. 2003;133:199–204.[Abstract/Free Full Text]

16. Riboli E, Hunt KJ, Slimani N, Ferrari P, Norat T, Fahey M, Charrondiere UR, Hemon B, Casagrande C, et al. European Prospective Investigation into Cancer and Nutrition (EPIC): study populations and data collection. Public Health Nutr. 2002;5:1113–24.[CrossRef][Medline]

17. Riboli E, Kaaks R. The EPIC Project: rationale and study design. European Prospective Investigation into Cancer and Nutrition. Int J Epidemiol. 1997;26 Suppl 1:S6–14.[Abstract/Free Full Text]

18. Slimani N, Ferrari P, Ocke M, Welch A, Boeing H, Liere M, Pala V, Amiano P, Lagiou A, et al. Standardization of the 24-hour diet recall calibration method used in the european prospective investigation into cancer and nutrition (EPIC): general concepts and preliminary results. Eur J Clin Nutr. 2000;54:900–17.[CrossRef][Medline]

19. Slimani N, Kaaks R, Ferrari P, Casagrande C, Clavel-Chapelon F, Lotze G, Kroke A, Trichopoulos D, Trichopoulou A, et al. European Prospective Investigation into Cancer and Nutrition (EPIC) calibration study: rationale, design and population characteristics. Public Health Nutr. 2002;5:1125–45.[CrossRef][Medline]

20. Agudo A, Slimani N, Ocke MC, Naska A, Miller AB, Kroke A, Bamia C, Karalis D, Vineis P, et al. Consumption of vegetables, fruit and other plant foods in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohorts from 10 European countries. Public Health Nutr. 2002;5:1179–96.[CrossRef][Medline]

21. Spencer EA, Appleby PN, Davey GK, Key TJ. Validity of self-reported height and weight in 4808 EPIC-Oxford participants. Public Health Nutr. 2002;5:561–5.[CrossRef][Medline]

22. Haftenberger M, Schuit AJ, Tormo MJ, Boeing H, Wareham N, Bueno-de-Mesquita HB, Kumle M, Hjartaker A, Chirlaque MD, et al. Physical activity of subjects aged 50–64 years involved in the European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr. 2002;5:1163–76.[CrossRef][Medline]

23. Ferrari P, Slimani N, Ciampi A, Trichopoulou A, Naska A, Lauria C, Veglia F, Bueno-de-Mesquita HB, Ocke MC, et al. Evaluation of under- and overreporting of energy intake in the 24-hour diet recalls in the European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr. 2002;5:1329–45.[Medline]

24. Ferrari P, Kaaks R, Fahey MT, Slimani N, Day NE, Pera G, Boshuizen HC, Roddam A, Boeing H, et al. Within- and between-cohort variation in measured macronutrient intakes, taking account of measurement errors, in the European Prospective Investigation into Cancer and Nutrition study. Am J Epidemiol. 2004;160:814–22.[Abstract/Free Full Text]

25. Lunn M, McNeil D. Applying Cox regression to competing risks. Biometrics. 1995;51:524–32.[CrossRef][Medline]

26. Glynn RJ, Rosner B. Comparison of risk factors for the competing risks of coronary heart disease, stroke, and venous thromboembolism. Am J Epidemiol. 2005;162:975–82.[Abstract/Free Full Text]

27. Lin DY, Wei LJ. The Robust Inference for the Proportional Hazards Model. JASA. 1989;84:1074–8.

28. Durrleman S, Simon R. Flexible regression models with cubic splines. Stat Med. 1989;8:551–61.[Medline]

29. Greenland S. Dose-response and trend analysis in epidemiology: alternatives to categorical analysis. Epidemiology. 1995;6:356–65.[Medline]

30. Hu FB, Cho E, Rexrode KM, Albert CM, Manson JE. Fish and long-chain omega-3 fatty acid intake and risk of coronary heart disease and total mortality in diabetic women. Circulation. 2003;107:1852–7.[Abstract/Free Full Text]

31. Qi L, van Dam RM, Rexrode K, Hu FB. Heme iron from diet as a risk factor for coronary heart disease in women with type 2 diabetes. Diabetes Care. 2007;30:101–6.[Abstract/Free Full Text]

32. Trichopoulou A, Psaltopoulou T, Orfanos P, Trichopoulos D. Diet and physical activity in relation to overall mortality amongst adult diabetics in a general population cohort. J Intern Med. 2006;259:583–91.[CrossRef][Medline]

33. Hung HC, Joshipura KJ, Jiang R, Hu FB, Hunter D, Smith-Warner SA, Colditz GA, Rosner B, Spiegelman D, et al. Fruit and vegetable intake and risk of major chronic disease. J Natl Cancer Inst. 2004;96:1577–84.[Abstract/Free Full Text]

34. Liu S, Manson JE, Lee IM, Cole SR, Hennekens CH, Willett WC, Buring JE. Fruit and vegetable intake and risk of cardiovascular disease: the Women's Health Study. Am J Clin Nutr. 2000;72:922–8.[Abstract/Free Full Text]

35. Joshipura KJ, Ascherio A, Manson JE, Stampfer MJ, Rimm EB, Speizer FE, Hennekens CH, Spiegelman D, Willett WC. Fruit and vegetable intake in relation to risk of ischemic stroke. JAMA. 1999;282:1233–9.[Abstract/Free Full Text]

36. Joshipura KJ, Hu FB, Manson JE, Stampfer MJ, Rimm EB, Speizer FE, Colditz G, Ascherio A, Rosner B, et al. The effect of fruit and vegetable intake on risk for coronary heart disease. Ann Intern Med. 2001;134:1106–14.[Abstract/Free Full Text]

37. Stumvoll M, Goldstein BJ, van Haeften TW. Type 2 diabetes: principles of pathogenesis and therapy. Lancet. 2005;365:1333–46.[CrossRef][Medline]

38. Buse JB, Ginsberg HN, Bakris GL, Clark NG, Costa F, Eckel R, Fonseca V, Gerstein HC, Grundy S, et al. Primary prevention of cardiovascular diseases in people with diabetes mellitus: a scientific statement from the American Heart Association and the American Diabetes Association. Diabetes Care. 2007;30:162–72.[Abstract/Free Full Text]

39. Klein S, Sheard NF, Pi-Sunyer X, Daly A, Wylie-Rosett J, Kulkarni K, Clark NG. Weight management through lifestyle modification for the prevention and management of type 2 diabetes: rationale and strategies: a statement of the American Diabetes Association, the North American Association for the Study of Obesity, and the American Society for Clinical Nutrition. Diabetes Care. 2004;27:2067–73.[Free Full Text]

40. Steinmetz KA, Potter JD. Vegetables, fruit, and cancer prevention: a review. J Am Diet Assoc. 1996;96:1027–39.[CrossRef][Medline]

41. Nelson KM, Reiber G, Boyko EJ. Diet and exercise among adults with type 2 diabetes: findings from the third national health and nutrition examination survey (NHANES III). Diabetes Care. 2002;25:1722–8.[Abstract/Free Full Text]

42. Salle A, Ryan M, Ritz P. Underreporting of food intake in obese diabetic and nondiabetic patients. Diabetes Care. 2006;29:2726–7.[Free Full Text]

43. Skinner KM, Miller DR, Lincoln E, Lee A, Kazis LE. Concordance between respondent self-reports and medical records for chronic conditions: experience from the Veterans Health Study. J Ambul Care Manage. 2005;28:102–10.[Medline]

44. Okura Y, Urban LH, Mahoney DW, Jacobsen SJ, Rodeheffer RJ. Agreement between self-report questionnaires and medical record data was substantial for diabetes, hypertension, myocardial infarction and stroke but not for heart failure. J Clin Epidemiol. 2004;57:1096–103.[CrossRef][Medline]

45. Robinson JR, Young TK, Roos LL, Gelskey DE. Estimating the burden of disease. Comparing administrative data and self-reports. Med Care. 1997;35:932–47.[CrossRef][Medline]

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