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Colours of fruit and vegetables and 10-year incidence of CHD

Published online by Cambridge University Press:  08 June 2011

Linda M. Oude Griep*
Affiliation:
Division of Human Nutrition, Wageningen University, PO Box 8129, 6700 EVWageningen, The Netherlands
W. M. Monique Verschuren
Affiliation:
National Institute for Public Health and the Environment, PO Box 1, 3720 BABilthoven, The Netherlands
Daan Kromhout
Affiliation:
Division of Human Nutrition, Wageningen University, PO Box 8129, 6700 EVWageningen, The Netherlands
Marga C. Ocké
Affiliation:
National Institute for Public Health and the Environment, PO Box 1, 3720 BABilthoven, The Netherlands
Johanna M. Geleijnse
Affiliation:
Division of Human Nutrition, Wageningen University, PO Box 8129, 6700 EVWageningen, The Netherlands
*
*Corresponding author: L. M. Oude Griep, fax +31 317 483342, email [email protected]
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Abstract

The colours of the edible part of fruit and vegetables indicate the presence of specific micronutrients and phytochemicals. The extent to which fruit and vegetable colour groups contribute to CHD protection is unknown. We therefore examined the associations between fruit and vegetables of different colours and their subgroups and 10-year CHD incidence. We used data from a prospective population-based cohort including 20 069 men and women aged 20–65 years who were enrolled between 1993 and 1997. Participants were free of CVD at baseline and completed a validated 178-item FFQ. Hazard ratios (HR) for the association between green, orange/yellow, red/purple, white fruit and vegetables and their subgroups with CHD were calculated using multivariable Cox proportional hazards models. During 10 years of follow-up, 245 incident cases of CHD were documented. For each 25 g/d increase in the intake of the sum of all four colours of fruit and vegetables, a borderline significant association with incident CHD was found (HR 0·98; 95 % CI 0·97, 1·01). No clear associations were found for the colour groups separately. However, each 25 g/d increase in the intake of deep orange fruit and vegetables was inversely associated with CHD (HR 0·74; 95 % CI 0·55, 1·00). Carrots, their largest contributor (60 %), were associated with a 32 % lower risk of CHD (HR 0·68; 95 % CI 0·48, 0·98). In conclusion, though no clear associations were found for the four colour groups with CHD, a higher intake of deep orange fruit and vegetables and especially carrots may protect against CHD.

Type
Full Papers
Copyright
Copyright © The Authors 2011

Prospective cohort studies have shown that a high consumption of fruit and vegetables lowers the risk of CHD(Reference Dauchet, Amouyel and Hercberg1, Reference He, Nowson and Lucas2). Various subgroups of fruit and vegetables provide a different array of micronutrients and phytochemicals(Reference Pennington and Fisher3), which may underlie the observed association with CHD. Consistent evidence for subgroups of fruit and vegetables in relation to CHD is lacking since prospective cohort studies have focused on only a limited number of fruit and vegetables that were selected on the basis of their botanical family, content of one specific micronutrient or bioactive compound.

Previous cohort studies have shown inconsistent results for specific fruit and vegetables. Thus, two prospective cohort studies have observed inverse associations between intake of citrus fruit and incident CHD(Reference Joshipura, Hu and Manson4, Reference Dauchet, Ferrieres and Arveiler5), while two other studies have not found an association with fatal CHD(Reference Sahyoun, Jacques and Russell6, Reference Mink, Scrafford and Barraj7). Intake of berries was found to lower the risk of fatal CVD(Reference Mink, Scrafford and Barraj7Reference Sesso, Gaziano and Jenkins9), but not the risk of incident CHD in male smokers(Reference Hirvonen, Pietinen and Virtanen10). Also, two prospective cohort studies have found that apples were not significantly inversely related to fatal CHD(Reference Hertog, Feskens and Hollman11Reference Yochum, Kushi and Meyer13). Vegetables rich in carotenoids(Reference Liu, Lee and Ajani14), tomatoes and tomato-based products, however, were inversely related to fatal CVD(Reference Gaziano, Manson and Branch15) as well as to incident CVD(Reference Sesso, Liu and Gaziano16). Carrots were inversely associated with both fatal CHD(Reference Mann, Appleby and Key17) and fatal CVD(Reference Sahyoun, Jacques and Russell6, Reference Gaziano, Manson and Branch15, Reference Buijsse, Feskens and Kwape18). Cruciferous vegetables were inversely related to incident CHD(Reference Joshipura, Hu and Manson4), and broccoli to fatal CHD(Reference Yochum, Kushi and Meyer13). With regard to incident CHD only, inverse relationships were observed for intake of green leafy and vitamin C-rich vegetables(Reference Joshipura, Hu and Manson4).

Randomised trials focusing on antioxidant supplements have failed to demonstrate a beneficial effect on CVD(Reference Vivekananthan, Penn and Sapp19, Reference Sesso, Buring and Christen20). Although this could be explained by methodological issues, such as a relatively brief follow-up period or the use of high doses of antioxidants, this could also indicate that the protective effect of fruit and vegetables may be due to the combined or even synergistic effects of the various components in their natural food matrix and not to one particular antioxidant(Reference Jacobs, Gross and Tapsell21). Fruit and vegetable subgroups, therefore, need to be classified according to similarities in micronutrient and phytochemical content. Pennington & Fisher(Reference Pennington and Fisher3, Reference Pennington and Fisher22) defined ten fruit and vegetable subgroups based on their unique nutritional value and characteristics, e.g. edible part of the plant, colour, botanical family or total antioxidant capacity.

The colour of the edible part of fruit and vegetables reflects the presence of pigmented phytochemicals, e.g. carotenoids and flavonoids, and therefore indicates their nutritional value(Reference Simon23). Drewnowski(Reference Drewnowski24) found that consumers perceive the most colourful vegetables as the most nutritious and suggested that fruit and vegetable colours may be an important factor in food selection. Heber & Bowerman(Reference Heber and Bowerman25) has suggested using fruit and vegetable colours as a tool to translate the science of phytochemical nutrition into dietary guidelines for the public. The 2010 Dietary Guidelines for Americans recommend selecting vegetables from five subgroups, i.e. dark green, red–orange, legumes, starchy and other vegetables to reach the recommendation(26). However, there have been no prospective cohort studies to date that focus on fruit and vegetable colour groups in relation to incident CHD.

Our investigation, therefore, focuses on the associations of fruit and vegetable colour groups and their subgroups with 10-year CHD incidence in a population-based follow-up study in The Netherlands.

Methods

Population

We used data from the Monitoring Project on Risk Factors and Chronic Diseases in The Netherlands (MORGEN Study), a Dutch population-based cohort(Reference Verschuren, Blokstra and Picavet27, Reference Van Loon, Tijhuis and Picavet28). The baseline measurements were carried out between 1993 and 1997. The present study was conducted in accordance with the guidelines laid down in the declaration of Helsinki and all procedures involving human subjects were approved by the Medical Ethics Committee of The Netherlands Organisation for Applied Scientific Research. Written informed consent was obtained from all participants. Of the total 22 654 participants, we excluded respondents without informed consent for vital status follow-up (n 701), with incomplete dietary assessment (n 72), with reported extreme total energy intakes of < 2094 or >18 844 kJ/d for women or < 3350 or >20 938 kJ/d for men (n 97), with a history of myocardial infarction or stroke at baseline (n 442) and with self-reported diabetes or use of lipid-lowering or anti-hypertensive drugs (n 1273). This resulted in a study population of 20 069 participants, including 8988 men and 11 081 women.

Dietary assessment

Information on habitual food consumption of 178 food items, covering the previous year, was collected using a validated, self-administered, semi-quantitative FFQ developed for the Dutch cohorts of the European Prospective Investigation into Cancer Study(Reference Ocké, Bueno-de-Mesquita and Goddijn29). Participants indicated their consumption as absolute frequencies in times per d, per week, per month, per year or as never. For several food items, additional questions were included about consumption frequency of different sub-items or preparation methods using the following categories: always/mostly, often, sometimes and seldom/never. Consumed amounts were calculated using standard household measures, natural units or portion sizes indicated by coloured photographs. Frequencies per d and portion sizes were multiplied to obtain g/d for each food item. The Dutch food composition database of 1996 was used to calculate values for energy and nutrient intakes(30). To calculate the intake of carotenoids and flavonoids from fruit and vegetables, the Dutch food composition database of 2001 was used(31).

The FFQ was designed to assess habitual intake during summer and winter of thirty-five commonly used fruit and vegetables in The Netherlands, including juices and sauces. Potatoes and legumes were not included, because their nutritional value differs significantly from that of vegetables(30). The reproducibility of the FFQ after 12 months and relative validity against twelve repeated 24 h recalls for food group and nutrient intake were tested in sixty-three males and fifty-eight females(Reference Ocké, Bueno-de-Mesquita and Goddijn29, Reference Ocké, Bueno-de-Mesquita and Pols32). Reproducibility of the FFQ after 12 months expressed as Spearman's correlation coefficients for vegetables was 0·76 in men and 0·65 in women; for fruit intake, it was 0·61 in men and 0·77 in women. The validity against twelve repeated 24 h recalls over a period of 1 year varied between 0·31 and 0·38 for vegetables, and between 0·56 and 0·68 for fruit.

In 284 men and 287 women of the MORGEN Study, Jansen et al. (Reference Jansen, Van Kappel and Ocké33) validated fruit and vegetable intake using plasma carotenoids and found that intake of several fruit and vegetable subgroups was positively associated with plasma levels of specific carotenoids. Participants in the highest quartile of carrot intake showed a 31 % higher α-carotene level compared with participants in the lowest quartile. For tomatoes, 26 % higher β-carotene and 21 % higher lycopene levels were observed. For cabbages, β-carotene levels were 17 % higher and lutein levels were 13 % higher.

Classification of fruit and vegetables

Fruit and vegetables were classified into colour groups and subgroups (Table 1). First, we categorised fruit and vegetables into four fruit and vegetable colour groups according to the colour of the primarily edible part: green, orange/yellow, red/purple and white. Second, we subdivided fruit and vegetables within these colour groups, resulting in nine fruit and vegetable subgroups and two groups with ‘other’ fruit and vegetables, as recently proposed by Pennington & Fisher(Reference Pennington and Fisher3, Reference Pennington and Fisher22). We made small adjustments in the classification of subgroups to make it more compatible with our FFQ and the Dutch situation. Cabbages were classified according to their colour as green, red/purple and white cabbages. As apples and pears are commonly consumed in The Netherlands and are an important source of flavonoids(Reference Hertog, Hollman and Katan34), we created the specific subgroup of hard fruits. Several green and white fruit and vegetables that could not be classified because of their unique micronutrient composition were allocated to an ‘other’ group.

Table 1 Classification of fruit and vegetables according to type and colour group*

* Fruit and vegetables were classified into subgroups as proposed by Pennington & Fisher(Reference Pennington and Fisher3, Reference Pennington and Fisher22).

Risk factors

The baseline measurements were previously described in detail by Verschuren et al. (Reference Verschuren, Blokstra and Picavet27). Body weight, height and blood pressure of the participants were measured by trained research assistants during a physical examination at a municipal health service site. Non-fasting venous blood samples were collected, and serum total and HDL-cholesterol concentrations were determined using an enzymatic method. Information on cigarette smoking, educational level, physical activity, use of anti-hypertensive and lipid-lowering drugs, past or present use of hormone replacement therapy and the history of acute myocardial infarction (AMI) of the participants' parents were obtained through a self-administered questionnaire. Dietary supplement use (yes/no) and alcohol intake were obtained from the FFQ. Alcohol intake was expressed as the number of glasses of beer, wine, port wines and strong liquor consumed per week. From 1994 onwards, physical activity was assessed using a validated questionnaire that was developed for the European Prospective Investigation into Cancer Study(Reference Pols, Peeters and Ocké35). Physical activity was defined as engaging in cycling and/or sports on at least 5 d/week during ≥ 30 min with an intensity of ≥ 4 metabolic equivalents. In this subsample, both cycling and sports were related to CVD(Reference Hoevenaar-Blom, Wanda Wendel-Vos and Spijkerman36).

Ascertainment of fatal and non-fatal events

After enrolment, the participants' vital status up to 1 January 2006 was monitored using the municipal population register. For participants who died, information on cause of death was obtained from Statistics Netherlands. The hospital discharge register provided information on clinically diagnosed AMI discharges. CHD incidence was defined as the first non-fatal AMI or fatal CHD event that was not preceded by any other CHD event. Non-fatal AMI comprised code 410 of the 9th revision of the International Classification of Diseases(37). Fatal CHD included ICD-10 codes I20–I25 as the primary cause of death(38). Where the dates of hospital admission and death coincided, the event was considered fatal.

Statistical analysis

For each participant, we calculated person time from date of enrolment until the first event (non-fatal AMI or fatal CHD), date of emigration (n 693), date of death or censoring date (1 January 2006), whichever occurred first. The intake of the total of fruit and vegetable colour groups was calculated by summing the intake of fruit and vegetable colour groups. Quartiles of intake were computed for each fruit and vegetable colour group. Tertiles of intake were calculated for each fruit and vegetable type. Hazard ratios (HR) for each category of fruit and vegetables compared with the lowest category and per 25 g/d increase in intake were estimated using Cox proportional hazards models. The Cox proportional hazards assumption was fulfilled in all models according to the graphical approach and Schoenfeld residuals. To test P for trend across increasing categories of intake, median values of intake were assigned to each category and used as a continuous variable in the Cox model.

Besides an age- (continuous) and sex-adjusted model, we used a multivariable model that included total energy intake (continuous), smoking status (never, former, current smoker of < 10, 10–20, ≥ 20 cigarettes/d), alcohol intake (never, moderate and high consumption of more than one glass/d in women and two glasses/d in men), educational level (four categories), dietary supplement use (yes/no), past or present hormone replacement therapy (yes/no), family history of AMI before 55 years of the father or before 65 years of the mother (yes/no) and BMI (kg/m2). In addition, we extended the model with dietary covariates, including intake of whole-grain foods and processed meat (g/d), fish (quartiles) and mutually for the sum of the intake of the other fruit and vegetable colour groups or subgroups. With regard to the participants enrolled from 1994 onwards, we evaluated whether physical activity was a potential confounder (‘active’ being defined as engagement in cycling or sports of ≥ 4 metabolic equivalents). We calculated the HR with and without physical activity in the multivariable model.

According to stratified analyses and the log-likelihood test using cross-product terms in the multivariable model, no evidence was observed for potential effect modification by age ( < 50 v. ≥ 50 years), sex or smoking status (never v. current). P values < 0·05 (two-tailed) were considered statistically significant. Analyses were performed using the Statistical Analysis System (version 9.1; SAS Institute, Inc., Cary, NC, USA).

Results

Participants were 42 (sd 11) years old at baseline and 45 % were male. Women had a higher fruit and vegetable consumption, had a lower educational level, used alcohol less often and used dietary supplements more often than men (Table 2). Women had a lower intake of energy and dietary fibre, but a higher intake of vitamin C and flavonoids than men.

Table 2 Baseline characteristics of 20 069 Dutch men and women for high and low fruit and vegetable intake

(Mean values and standard deviations or percentages)

AMI, acute myocardial infarction.

* Low educational level is defined as primary school and lower, intermediate general education.

High alcohol consumption is defined as >1 glass/d in women and >2 glasses/d in men.

Physically active is defined as engagement in cycling or sports of ≥ 4 metabolic equivalents. In a subsample of participants enrolled from 1994 onwards (n 15 433).

§ Fish consumption is defined as the highest quartile of fish intake (median 17 g/d, i.e. approximately one portion of fish/week).

Family history of AMI is defined as occurrence of AMI before 55 years of the father or before 65 years of the mother.

Participants had an average daily fruit and vegetable intake of 378 (sd 193) g/d. The largest contributors to total fruit and vegetable consumption were white (36 %) and orange/yellow (29 %) fruit and vegetables (Table 1). The most commonly consumed items in the white fruit and vegetable range were hard fruits (55 %). Orange/yellow fruit and vegetables comprised citrus fruits (78 %) and deep orange fruit and vegetables (22 %). Green fruit and vegetables consisted of several vegetable subgroups, e.g. cabbages (18 %), dark leafy vegetables (15 %) and lettuces (13 %), and other green fruit and vegetables (54 %). Red/purple fruit and vegetables comprised red vegetables (59 %) and berries (41 %). Spearman's correlation coefficients between fruit and vegetable colour groups ranged from 0·38 for green v. orange/yellow fruit and vegetables to 0·60 for orange/yellow v. white fruit and vegetables.

After a median follow-up of 10·5 (interquartile range 9·2–11·8) years, we documented 245 incident CHD events, which comprised 211 non-fatal cases of AMI and thirty-four fatal cases of CHD. After adjustment for lifestyle and dietary factors, we observed for each 25 g/d increase in the intake of the sum of green, orange/yellow, red/purple and white fruit and vegetables a borderline significant association with incident CHD (HR 0·98; 95 % CI 0·97, 1·01; Table 3). No clear associations were found between intake of the four fruit and vegetable colour groups separately and incident CHD.

Table 3 Associations between quartiles (Q) and per 25 g/d increase in fruit and vegetable colour group intake and incident CHD of 20 069 Dutch participants*

(Hazard ratios (HR), 95 % confidence intervals and medians)

* HR (95 % CI) obtained from Cox proportional hazards models. Model 1 was adjusted for age and sex (n 20 069). Model 2 was the same as model 1 with additional adjustments for energy intake, alcohol intake, smoking status, educational level, dietary supplement use, use of hormone replacement therapy, family history of acute myocardial infarction and BMI (n 19 819). Model 3 was the same as model 2 with additional adjustment for intake of whole-grain foods, processed meat, fish and mutually for the sum of the other fruit and vegetable colour groups.

Reference group.

In addition, we analysed the subgroups of fruit and vegetables as proposed by Pennington & Fisher(Reference Pennington and Fisher22). After adjustment for lifestyle and dietary factors, continuous analysis per 25 g/d increase in the intake of deep orange fruit and vegetables was inversely associated with CHD (HR 0·74; 95 % CI 0·55, 1·00; Table 4). Carrots were the largest contributor to deep orange fruit and vegetables (60 %). Each 25 g/d increase in the intake of carrots was associated with a 32 % lower risk of CHD (HR 0·68; 95 % CI 0·48, 0·98), whereas each 25 g/d increase in the intake of the sum of the other fruit and vegetable subgroups was weakly associated (HR 0·99; 95 % CI 0·97, 1·01). The consumption of the other fruit and vegetable subgroups was not associated with CHD (Table 4).

Table 4 Associations between tertiles (T) and per 25 g/d increase in fruit and vegetable subgroup intake and incident CHD of 20 069 Dutch participants*

(Hazard ratios (HR), 95 % confidence intervals and medians)

* Fruit and vegetables were classified into subgroups as proposed by Pennington & Fisher(Reference Pennington and Fisher3, Reference Pennington and Fisher22).

HR (95 % CI) obtained from Cox proportional hazards models. Model 1 was adjusted for age and sex (n 20 069). Model 2 was the same as model 1 with additional adjustments for energy intake, alcohol intake, smoking status, educational level, dietary supplement use, use of hormone replacement therapy, family history of acute myocardial infarction and BMI (n 19 819). Model 3 was the same as model 2 with additional adjustment for intake of whole-grain foods, processed meat, fish and mutually for the sum of the other fruit and vegetable subgroups.

Reference group.

We evaluated whether physical activity was a potential confounder for the sum of green, orange/yellow, red/purple and white fruit and vegetables with incident CHD for participants enrolled from 1994 onwards (n 15 433). HR for each 25 g increase of all fruit and vegetable colour groups was 0·97 (95 % CI 0·95, 0·99) and remained similar when physical activity was added to the model (HR 0·97; 95 % CI 0·95, 1·00).

Discussion

In the present study, we observed that consumption of the four fruit and vegetable colour groups together was weakly related to a lower risk of CHD. A more detailed analysis of fruit and vegetable subgroups, as defined by Pennington & Fisher(Reference Pennington and Fisher3, Reference Pennington and Fisher22), showed that deep orange fruit and vegetables and their largest contributor, carrots, were strongly associated with a lower risk of incident CHD. The inverse relationship of consumption of fruit and vegetable colour groups with incident CHD was attenuated after adjustment for potential confounders.

A major strength of the present study is the almost complete follow-up for CHD mortality. With respect to non-fatal events, it was shown on the national level that data from the Dutch hospital discharge register can be uniquely matched to an individual for at least 88 % of the hospital admissions(Reference De Bruin, De Bruin and Gast39). In a validation study, 84 % of the AMI cases in the cardiology information system of the University Hospital Maastricht corresponded with AMI cases identified in the hospital discharge register(Reference Merry, Boer and Schouten40). Mild AMI cases where hospitalisation was not necessary may have been missed, but we expect this to be random and not to be related to fruit and vegetable intake. It is unlikely, therefore, that this has influenced the relationship of fruit and vegetable colour groups with CHD incidence.

A potential limitation of the present study was that some vegetables, such as onions and cabbages, are commonly used in mixed dishes which complicates the estimation of intake using an FFQ. Furthermore, fruit and vegetable intake is part of a healthy lifestyle and diet. Although we adjusted for potential risk factors as well as important food groups in relation to CHD, we cannot rule out residual confounding. In addition, comparing studies on subgroups of fruit and vegetables is challenging, since the availability and range of intake of commonly consumed fruit and vegetables differ between countries(Reference Agudo, Slimani and Ocké41).

In the present study, we found that consumption of the four fruit and vegetable colour groups combined was weakly inversely related to incident CHD. Mixed fruit juices that could not be classified into colour groups were not included in the present analysis. However, we reported previously that the intake of total fruit and vegetables, including mixed fruit juices, was associated with a 6 % lower risk of incident CHD in the same population(Reference Oude Griep, Geleijnse and Kromhout42). This finding confirms the results of previous meta-analyses that showed a 4–11 % lower risk of CHD for each approximately 100 g/d increase in fruit and vegetable intake(Reference Dauchet, Amouyel and Hercberg1, Reference He, Nowson and Lucas2).

After adjustment for lifestyle and dietary factors, we did not observe significant associations of the sum of fruit and vegetable colour groups as well as with the four colour groups separately, with incident CHD. In this respect, the present study may have had insufficient power to detect statistically significant associations. Results of further prospective cohort studies with larger numbers of cases are therefore needed to investigate these associations.

A more detailed analysis of fruit and vegetable colour groups defined by Pennington & Fisher(Reference Pennington and Fisher3, Reference Pennington and Fisher22) showed that intake of deep orange fruit and vegetables was associated with a lower risk of incident CHD. Carrots, the primary source of deep orange fruit and vegetables (60 %), were inversely associated with incident CHD, while the intake of the remaining fruit and vegetables was not related. This suggests that the lower CHD risk of total fruit and vegetable intake could be driven by the strong inverse association of carrots, which, is consistent with findings of previous studies with fatal CHD(Reference Mann, Appleby and Key17) and fatal CVD(Reference Sahyoun, Jacques and Russell6, Reference Gaziano, Manson and Branch15, Reference Buijsse, Feskens and Kwape18) as endpoints. Carrots are a rich source of carotenoids(Reference Pennington and Fisher3, 30). Recently, it has been found that serum α-carotene concentrations were inversely associated with IHD mortality among US adults(Reference Li, Ford and Zhao43). Circulating carotenoids were also inversely associated with markers of inflammation, oxidative stress and endothelial dysfunction(Reference Hozawa, Jacobs and Steffes44) and may protect against early atherosclerosis(Reference Dwyer, Navab and Dwyer45, Reference Dwyer, Paul-Labrador and Fan46). This suggests that carotenoids may lower CHD risk through different pathways.

In conclusion, we found that consumption of the sum of all four fruit and vegetable colour groups was weakly inversely related to CHD. A more detailed analysis of different colour groups showed that a higher intake of deep orange fruit and vegetables, especially carrots, may protect against incident CHD. Prospective cohort studies with a larger number of cases are needed to replicate these findings.

Acknowledgements

An unrestricted grant (13281) was obtained by J. M. G. from the Product Board for HorticuIture, Zoetermeer, The Netherlands, to cover the costs of data analysis for the present study. The other authors did not report financial disclosures. The Monitoring Project on Risk Factors and Chronic Diseases in the Netherlands (MORGEN) Study was supported by the Ministry of Health, Welfare and Sport of the Netherlands, the National Institute for Public Health and the Environment, Bilthoven, The Netherlands and the Europe Against Cancer Program of the European Union. The authors declare that there is no conflict of interest related to any part of the study. The sponsors did not participate in the design or conduct of the study; in the collection, analysis or interpretation of the data; or in the preparation, review or approval of the manuscript. The authors' contributions are as follows: L. M. O. G., D. K. and J. M. G. were involved in the study concept and design; W. M. M. V. and M. C. O. were involved in the acquisition of the data; L. M. O. G., D. K. and J. M. G. were involved in the analysis and interpretation of the data; L. M. O. G. was involved in the drafting of the manuscript; W. M. M. V., D. K., M. C. O. and J. M. G. were involved in the critical revision of the manuscript for important intellectual content; L. M. O. G. was involved in the statistical analysis; W. M. M. V. and J. M. G. obtained funding; W. M. M. V. and J. M. G. provided administrative, technical or material support; W. M. M. V., D. K. and J. M. G. were responsible for study supervision.

References

1 Dauchet, L, Amouyel, P, Hercberg, S, et al. (2006) Fruit and vegetable consumption and risk of coronary heart disease: a meta-analysis of cohort studies. J Nutr 136, 25882593.CrossRefGoogle ScholarPubMed
2 He, FJ, Nowson, CA, Lucas, M, et al. (2007) Increased consumption of fruit and vegetables is related to a reduced risk of coronary heart disease: meta-analysis of cohort studies. J Hum Hypertens 21, 717728.CrossRefGoogle ScholarPubMed
3 Pennington, JAT & Fisher, RA (2010) Food component profiles for fruit and vegetable subgroups. J Food Compost Anal 23, 411418.CrossRefGoogle Scholar
4 Joshipura, KJ, Hu, FB, Manson, JE, et al. (2001) The effect of fruit and vegetable intake on risk for coronary heart disease. Ann Intern Med 134, 11061114.CrossRefGoogle ScholarPubMed
5 Dauchet, L, Ferrieres, J, Arveiler, D, et al. (2004) Frequency of fruit and vegetable consumption and coronary heart disease in France and Northern Ireland: the PRIME study. Br J Nutr 92, 963972.CrossRefGoogle ScholarPubMed
6 Sahyoun, NR, Jacques, PF & Russell, RM (1996) Carotenoids, vitamins C and E, and mortality in an elderly population. Am J Epidemiol 144, 501511.CrossRefGoogle Scholar
7 Mink, PJ, Scrafford, CG, Barraj, LM, et al. (2007) Flavonoid intake and cardiovascular disease mortality: a prospective study in postmenopausal women. Am J Clin Nutr 85, 895909.CrossRefGoogle ScholarPubMed
8 Rissanen, TH, Voutilainen, S, Virtanen, JK, et al. (2003) 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 133, 199204.CrossRefGoogle ScholarPubMed
9 Sesso, HD, Gaziano, JM, Jenkins, DJA, et al. (2007) Strawberry intake, lipids, C-reactive protein, and the risk of cardiovascular disease in women. J Am Coll Nutr 26, 303310.CrossRefGoogle ScholarPubMed
10 Hirvonen, T, Pietinen, P, Virtanen, M, et al. (2001) Intake of flavonols and flavones and risk of coronary heart disease in male smokers. Epidemiology 12, 6267.CrossRefGoogle ScholarPubMed
11 Hertog, MG, Feskens, EJ, Hollman, PC, et al. (1993) Dietary antioxidant flavonoids and risk of coronary heart disease: the Zutphen Elderly Study. Lancet 342, 10071011.CrossRefGoogle ScholarPubMed
12 Knekt, P, Järvinen, R, Reunanen, A, et al. (1996) Flavonoid intake and coronary mortality in Finland: a cohort study. BMJ 312, 478481.CrossRefGoogle ScholarPubMed
13 Yochum, L, Kushi, LH, Meyer, K, et al. (1999) Dietary flavonoid intake and risk of cardiovascular disease in postmenopausal women. Am J Epidemiol 149, 943949.CrossRefGoogle ScholarPubMed
14 Liu, S, Lee, IM, Ajani, U, et al. (2001) Intake of vegetables rich in carotenoids and risk of coronary heart disease in men: The Physicians' Health Study. Int J Epidemiol 30, 130135.CrossRefGoogle Scholar
15 Gaziano, JM, Manson, JE, Branch, LG, et al. (1995) A prospective study of consumption of carotenoids in fruits and vegetables and decreased cardiovascular mortality in the elderly. Ann Epidemiol 5, 255260.CrossRefGoogle ScholarPubMed
16 Sesso, HD, Liu, S, Gaziano, JM, et al. (2003) Dietary lycopene, tomato-based food products and cardiovascular disease in women. J Nutr 133, 23362341.CrossRefGoogle ScholarPubMed
17 Mann, JI, Appleby, PN, Key, TJ, et al. (1997) Dietary determinants of ischaemic heart disease in health conscious individuals. Heart 78, 450455.CrossRefGoogle ScholarPubMed
18 Buijsse, B, Feskens, EJ, Kwape, L, et al. (2008) Both alpha- and beta-carotene, but not tocopherols and vitamin C, are inversely related to 15-year cardiovascular mortality in Dutch elderly men. J Nutr 138, 344350.CrossRefGoogle Scholar
19 Vivekananthan, DP, Penn, MS, Sapp, SK, et al. (2003) Use of antioxidant vitamins for the prevention of cardiovascular disease: meta-analysis of randomised trials. Lancet 361, 20172023.CrossRefGoogle ScholarPubMed
20 Sesso, HD, Buring, JE, Christen, WG, et al. (2008) Vitamins E and C in the prevention of cardiovascular disease in men: the Physicians' Health Study II randomized controlled trial. JAMA 300, 21232133.CrossRefGoogle Scholar
21 Jacobs, DR Jr, Gross, MD & Tapsell, LC (2009) Food synergy: an operational concept for understanding nutrition. Am J Clin Nutr 89, 1543S1548S.CrossRefGoogle ScholarPubMed
22 Pennington, JAT & Fisher, RA (2009) Classification of fruits and vegetables. J Food Compost Anal 22, S23S31.CrossRefGoogle Scholar
23 Simon, PW (1997) Plant pigments for color and nutrition. HortScience 32, 1213.CrossRefGoogle Scholar
24 Drewnowski, A (1996) From asparagus to zucchini: mapping cognitive space for vegetable names. J Am Coll Nutr 15, 147153.CrossRefGoogle ScholarPubMed
25 Heber, D & Bowerman, S (2001) Applying science to changing dietary patterns. J Nutr 131, 3078S3081S.CrossRefGoogle ScholarPubMed
26 U.S. Department of Health and Human Services & U.S. Department of Agriculture (2010) Dietary Guidelines for Americans, 7th ed. Washington, DC: U.S. Government Printing Office.Google Scholar
27 Verschuren, WMM, Blokstra, A, Picavet, HS, et al. (2008) Cohort profile: the Doetinchem Cohort Study. Int J Epidemiol 37, 12361241.CrossRefGoogle ScholarPubMed
28 Van Loon, AJ, Tijhuis, M, Picavet, HS, et al. (2003) Survey non-response in the Netherlands: effects on prevalence estimates and associations. Ann Epidemiol 13, 105110.CrossRefGoogle ScholarPubMed
29 Ocké, MC, Bueno-de-Mesquita, HB, Goddijn, HE, et al. (1997) The Dutch EPIC food frequency questionnaire. I. Description of the questionnaire, and relative validity and reproducibility for food groups. Int J Epidemiol 26, Suppl. 1, S37S48.CrossRefGoogle ScholarPubMed
30 Dutch food composition database (1996) The Hague. The Netherlands: Netherlands Nutrition Centre (in Dutch).Google Scholar
31 Dutch food composition database (2001) The Hague. The Netherlands: Netherlands Nutrition Centre (in Dutch).Google Scholar
32 Ocké, MC, Bueno-de-Mesquita, HB, Pols, MA, et al. (1997) The Dutch EPIC food frequency questionnaire. II. Relative validity and reproducibility for nutrients. Int J Epidemiol 26, Suppl. 1, S49S58.CrossRefGoogle ScholarPubMed
33 Jansen, MC, Van Kappel, AL, Ocké, MC, et al. (2004) Plasma carotenoid levels in Dutch men and women, and the relation with vegetable and fruit consumption. Eur J Clin Nutr 58, 13861395.CrossRefGoogle ScholarPubMed
34 Hertog, MGL, Hollman, PC & Katan, MB (1992) Content of potentially anticarcinogenic flavonoids of 28 vegetables and 9 fruits commonly consumed in the Netherlands. J Agric Food Chem 40, 23792383.CrossRefGoogle Scholar
35 Pols, MA, Peeters, PH, Ocké, MC, et al. (1997) Estimation of reproducibility and relative validity of the questions included in the EPIC Physical Activity Questionnaire. Int J Epidemiol 26, Suppl. 1, S181S189.CrossRefGoogle ScholarPubMed
36 Hoevenaar-Blom, MP, Wanda Wendel-Vos, GC, Spijkerman, AM, et al. (2011) Cycling and sports, but not walking, are associated with 10-year cardiovascular disease incidence: the MORGEN Study. Eur J Cardiovasc Prev Rehabil 18, 4147.CrossRefGoogle Scholar
37 World Health Organization (WHO) (1977) International Classification of Diseases, 9th revision. Geneva: WHO.Google Scholar
38 World Health Organization (WHO) (1992) International Classification of Diseases, 10th revision. Geneva: WHO.Google Scholar
39 De Bruin, A, De Bruin, EL, Gast, A, et al. (2003) Linking data of national ambulant register and GBA data: methods, results and quality research (in Dutch). Voorburg: Statistics Netherlands.Google Scholar
40 Merry, AH, Boer, JM, Schouten, LJ, et al. (2009) Validity of coronary heart diseases and heart failure based on hospital discharge and mortality data in the Netherlands using the cardiovascular registry Maastricht cohort study. Eur J Epidemiol 24, 237247.CrossRefGoogle ScholarPubMed
41 Agudo, A, Slimani, N, Ocké, MC, et al. (2002) 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 5, 11791196.CrossRefGoogle ScholarPubMed
42 Oude Griep, LM, Geleijnse, JM, Kromhout, D, et al. (2010) Raw and processed fruit and vegetable consumption and 10-year coronary heart disease incidence in a population-based cohort study in the Netherlands. PLoS One 5, e13609.CrossRefGoogle Scholar
43 Li, C, Ford, ES, Zhao, G, et al. (2011) Serum α-carotene concentrations and risk of death among US adults: The Third National Health and Nutrition Examination Survey Follow-up Study. Arch Intern Med 171, 507515.CrossRefGoogle ScholarPubMed
44 Hozawa, A, Jacobs, DR Jr, Steffes, MW, et al. (2007) Relationships of circulating carotenoid concentrations with several markers of inflammation, oxidative stress, and endothelial dysfunction: The Coronary Artery Risk Development in Young Adults (CARDIA)/Young Adult Longitudinal Trends in Antioxidants (YALTA) study. Clin Chem 53, 447455.CrossRefGoogle Scholar
45 Dwyer, JH, Navab, M, Dwyer, KM, et al. (2001) Oxygenated carotenoid lutein and progression of early atherosclerosis: the Los Angeles atherosclerosis study. Circulation 103, 29222927.CrossRefGoogle ScholarPubMed
46 Dwyer, JH, Paul-Labrador, MJ, Fan, J, et al. (2004) Progression of carotid intima-media thickness and plasma antioxidants: the Los Angeles Atherosclerosis Study. Arterioscler Thromb Vasc Biol 24, 313319.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Classification of fruit and vegetables according to type and colour group*

Figure 1

Table 2 Baseline characteristics of 20 069 Dutch men and women for high and low fruit and vegetable intake(Mean values and standard deviations or percentages)

Figure 2

Table 3 Associations between quartiles (Q) and per 25 g/d increase in fruit and vegetable colour group intake and incident CHD of 20 069 Dutch participants*(Hazard ratios (HR), 95 % confidence intervals and medians)

Figure 3

Table 4 Associations between tertiles (T) and per 25 g/d increase in fruit and vegetable subgroup intake and incident CHD of 20 069 Dutch participants*(Hazard ratios (HR), 95 % confidence intervals and medians)†