Cardiovascular disease (CVD) is one of the main causes of death in the developed world1 and, although its aetiololgy is multifactorial, diet plays a major role in its appearanceReference Samman, Sivarajah, Man, Ahmad, Petocz and Caterson2.
High total plasma homocysteine (t-Hcys) levels have been identified as a risk factor for CVDReference Suliman, Stenvinkel, Barany, Heimburger, Anderstam and Lindholm3. There is evidence to suggest that vitamins B2, B6 and B12 might reduce t-HCys since, like folic acid, they act as cofactors for the enzymes that break it downReference Ullegaddi, Powers and Gariballa4, Reference Ortega, Jimenez, Andres, Faci, Lolo and Lozano5. Indeed, t-Hcys levels are negatively correlated with serum and erythrocyte folate levelsReference Vrentzos, Papadakis, Malliaraki, Zacharis, Mazokopakis and Margioris6, Reference Gao, Bermudez and Tucker7.
Diets rich in fruits and vegetables may help reduce the risk of CVD via a number of beneficial effects, for example through the displacement from the diet of foods high in sodium and fats, as well as high-energy foods. These foods are also important sources of fibre and sterols, which reduce serum low-density lipoprotein (LDL)-cholesterol and total cholesterol levelsReference Djousse, Arnett, Coon, Province, Moore and Ellison8, and reduce blood pressure (by being low in sodium)Reference Miura, Greenland, Stamler, Liu, Daviglus and Nakagawa9. In addition, the high antioxidant content of fruit and vegetables helps improve endothelial functionReference Brown and Hu10 and, together with legumes, these foods are the main source of folateReference Rissanen, Voutilainen, Virtanen, Venho, Vanharanta and Mursu11.
Many studies (the majority of which were performed on adult populations) have shown an association between low fruit and vegetable intake and the development of CVD and other degenerative diseasesReference Genkinger, Platz, Hoffman, Comstock and Helzlsouer12. As people become older they eat less food (and therefore consume fewer fruit and vegetables), their lifestyles become more sedentary and their energy expenditure falls. This exposes the ageing population to nutritional deficits and malnutrition (especially with respect to trace elements), increasing their risk of developing CVDReference Fletcher, Breeze and Shetty13.
The aim of the present work was to assess the differences in the nutritional status of elderly people with respect to their consumption of fruit and vegetables, and to study the possible association between the intake of these foods and cardiovascular risk factors, especially t-Hcys levels.
Methods
Study population
The study subjects were 152 people (all ≥ 65 years of age; 64% women, 36% men) from three homes for the elderly in the Madrid region of Spain. These centres were chosen from an original total of 15 randomly selected centres in the area. Six of these centres declined the offer to participate, and another three had insufficient residents. The directors, medical staff and kitchen staff of the remaining six were contacted for information on the residents' medical backgrounds, mental health scores and the medications they took. This allowed three centres to be chosen with sufficient residents of similar characteristics and who were in an acceptable physical and mental condition. The meals of all three centres were prepared by the same catering service.
Subjects who had any of the following were excluded: all those with a disease that might affect digestion, absorption or use of nutrients (neoplasms, cirrhosis, abnormal liver function, poor intestinal absorption, etc.); and those who took medications that might interfere with their appetite or any of the measured variables. After informing the subjects of the characteristics of the study, their written consent to be included was requested in line with the ethical requirements of the Faculty of Pharmacy Research Committee.
Dietetic study
All food and drink consumed over 7 days was recorded using the ‘precise individual weighing’ methodReference Maisey, Loughridge, Southon and Fulcher14. Data were recorded under the same conditions at all three centres, i.e. by the same persons, in the same way, starting on the same day of the week and using the same equipment. A ‘food record’ was also kept by all subjects in order to register all consumptions outside set meal times (e.g. food brought to them by family members, food bought at the centres' cafeterias and food purchased outside the centres). Data were provided by the subjects themselves.
Once the consumption of food was known (g day− 1), the number of servings of each food was calculated. Each food (g) was divided into the average sized servings established for the Spanish populationReference Perea, Navia, Requejo and Ortega15. The average size considered for fruit was 100–150 g, and for vegetables 150–200 g. The population was then divided into tertiles corresponding to the daily consumption of fruits and vegetables: the first tertile (T1) ate < 2.29 servings day− 1, the second (T2) ate 2.29–2.79 servings day− 1 and the third (T3) ate more than this.
The energy and nutrient contents of the food and drink consumed by each subject were calculated using the food composition tables of the Instituto de Nutrición (1994)16, as completed by Moreiras et al. Reference Moreiras, Carbajal and Cabrera17. To assess the adequacy of the diet, the subjects' nutrient intakes were compared with the ‘Recommended Intakes of Energy and Nutrients for the Spanish Population’18. The recommended intake of fibreReference Ortega19 was established as 25 g day− 1.
The energy expenditure was estimated using equations proposed by the World Health Organization (WHO) in 198520 for the calculation of the basal metabolic rate, and then multiplying by an activity coefficient appropriate for each subject. To establish these coefficients, each subject completed a questionnaire (adapted from that of Dallosso et al. Reference Dallosso, Morgan, Bassey, Ebrahim, Fentem and Arie21 for elderly persons) that collected information on the number of hours spent involved in typical daily activities, e.g. walking, eating, standing, reading and sleeping. The discrepancy between the energy intake and estimated energy expenditure was calculated using the equationReference Dallosso, Morgan, Bassey, Ebrahim, Fentem and Arie22: (energy expenditure–energy intake) × 100/energy expenditure. When the final value is negative, this probably indicates that the energy intake is greater than the estimated energy expenditure, and thus the subject probably overestimated his/her intake. When the final value is positive, the energy intake is less than the energy expenditure, and the subject has underestimated his/her intakeReference Johnson, Goran and Poehlman22.
Anthropometric study
Height and weight were measured using a Seca Alpha digital electronic balance (range 0.1–150 kg) and a Harpenden digital stadiometer (range 70–205 cm), respectively. Hip and waist circumferences were measured using a flexible, metallic measuring tape (Holtain) (range 0–150 cm). All measurements were performed by trained personnel with the subjects barefoot and wearing only underwear, following the international norms recommended by WHO23. These data were used to calculate the body mass index (kg m− 2) and the waist-to-hip ratio.
Biochemical study
Blood samples were taken from 146 subjects either in the infirmary of each centre or in their rooms. All extractions, performed first thing in the morning after a minimum 12 h nocturnal fast, were made by venous puncture in the antecubital fossa. The collected blood was distributed into different tubes: one with heparin – to determine the number of erythrocytes and vitamin B2 status; two with no anticoagulant – to obtain serum and to determine vitamin B6, serum folate, cyanocobalamin and lipid levels; and one with ethylenediaminetetraacetic acid – to determine the erythrocyte folate and t-Hcys levels. All tubes were kept at 4–6°C until analysis, which was always preformed within 48 h.
Vitamin B2 status was determined by measuring the activation of erythrocyte glutathione reductase (EGR) by flavine adenine dinucleotide (FAD). The activity of the enzyme was measured by spectrophotometry in baseline conditions and after the addition of excess FAD from haemolysed blood samples. The relationship between enzyme activity before and after saturation is expressed by the saturation coefficient α. High α-coefficients imply an unfavourable biochemical riboflavin status (coefficient of variation (CV) = 4.4%)Reference Vuilleumier, Keller, Rettenmaier and Hunziker24.
Serum vitamin B6 levels were determined by high-pressure liquid chromatography (HPLC), using a semicarbazone pre-column and fluorescence detection (CV = 3.1%)Reference Ubbink, Serfontein and de Villiers25.
Serum folate (CV = 4.5%), erythrocyte folate (CV = 4.9%) and serum vitamin B12 (CV = 3.2%) were determined by radioimmunoassay using the Vitamin B12/Folate Dual Radioassay Kit (Diagnostic Products Corporation). A gamma counter model 1612 (Nuclear Enterprises Ltd) was used to quantify the signals emittedReference Lindenbaum26.
Triglycerides were determined by GPO/PAP enzymatic hydrolysis (Merck 19706, CV = 3.2%)Reference Bucolo and David27, and total cholesterol (CV = 3.2%) and high-density lipoprotein (HDL)-cholesterol (CV = 3.2%) by an enzymatic–colorimetric technique after precipitation in serum with phosphowolframic acid and magnesium ionsReference Allain, Poon, Chan, Richmond and Fu28. LDL-cholesterol was estimated using the Friedewald equationsReference Friedewald, Levy and Fredrickson29. VLDL-cholesterol = triglycerides/5 and LDL-cholesterol = total cholesterol – (VLDL-cholesterol + HDL-cholesterol), where VLDL = very-low-density lipoprotein.
Plasma homocysteine levels were determined by HPLCReference Turnell and Cooper30 (CV = 6.5%). Separation was achieved with an RP-18 column (Symta) using an intelligent pump (Merck-Hitachi L-6200 A; Hitachi). Detection was performed by fluorescence spectrophotometry. All reagents were supplied by Merck.
Health study
All diseases suffered by the subjects and the medications they took were recorded. Blood pressure was measured following the recommendations of Frohlich et al. Reference Frohlich, Grim and Labarthe31.
Statistical analysis
All data were processed using RSIGMA BABEL 2000 software (Horus Hardward). Means and standard deviations were calculated for all variables. One-way analysis of variance was used to determine the differences between groups. Differences between proportions were determined using the χ2 test. A number of correlation coefficients were also recorded. The Newman–Keuls test was used for detailed comparisons of the three tertile groups. Analysis of covariance (ANCOVA) was used to determine the interaction between variables. Significance was set at P < 0.05.
Results
The mean age of the subjects was 82 years; no significant differences in age were seen with respect to sex. The mean daily consumption of fruit and vegetables was 2.95 ± 0.92 servings day− 1, again with no significant differences between the sexes. No significant differences were seen in the general characteristics of the three tertile groups (Table 1).
Table 1 General and anthropometric characteristics of the study population divided into tertiles with respect to the consumption of fruits and vegetables (mean±SD)
SD – standard deviation; T1 – population with consumption of fruit and vegetable servings ≥ 1.26 and < 2.29 per day; T2 – population with consumption of fruit and vegetable servings ≥ 2.29 and < 2.79 per day; T3 – population with consumption of fruit and vegetable servings ≥ 2.79 and < 3.45 per day; ANOVA – analysis of variance; BMI – body mass index; SBP – systolic blood pressure; DBP – diastolic blood pressure; NS – non-significant.
The mean discrepancy between the energy intake and theoretical energy expenditure was − 0.21 ± 17.78, but this fell as the consumption of fruit and vegetables increased (r = − 0.2789, P < 0.001). The dietary data were therefore corrected by ANCOVA.
Table 2 shows that the T3 subjects had a smaller difference between their true and recommended intakes of servings of cereals, legumes, meat, fish and eggs than did T1 subjects (P < 0.05). In addition, a positive correlation was seen between fruit and vegetable consumption and the number of servings of legumes (r = 0.2701, P < 0.001), meat, fish and eggs (r = 0.5214, P < 0.001) and nuts (r = 0.1884, P < 0.05) consumed; a negative correlation was found with the consumption of sweet foods (g day− 1) (r = − 0.1749, P < 0.05). These correlations were maintained when the discrepancy between energy intake and theoretical energy expenditure was taken into account.
Table 2 Daily servings consumed by each tertile group (mean±SD)
SD – standard deviation; T1 – population with consumption of fruit and vegetable servings ≥ 1.26 and < 2.29 per day; T2 – population with consumption of fruit and vegetable servings ≥ 2.29 and < 2.79 per day; T3 – population with consumption of fruit and vegetable servings ≥ 2.79 and < 3.45 per day; ANCOVA – analysis of covariance; DMRI – difference from the minimum recommended intake.
Different letters indicate significant differences between groups (Newman–Keuls test): P < 0.05.
The intake of energy (P < 0.001), carbohydrates (P < 0.01) and proteins (P < 0.001) increased with the consumption of fruit and vegetables. However, ANCOVA showed that this increase in protein consumption was not due to the extra intake of fruit and vegetables, but rather to the associated increased intake of fish and meats because the significance disappeared after correcting for the underestimation of food intake, plus the differences in the consumption of meat and fish between the three groups.
The intake of fibre increased with consumption of fruit and vegetables (r = 0.6839, P < 0.001) (Table 3). No significant differences were seen between the tertile groups with respect to energy and lipid profiles when the data were corrected for the underestimation of food intake, and for fish and meat intake (Table 3).
Table 3 Intake of energy and macronutrients, energy and lipid profiles in the different tertile groups (mean±SD)
SD – standard deviation; T1 – population with consumption of fruit and vegetable servings ≥ 1.26 and < 2.29 per day; T2 – population with consumption of fruit and vegetable servings ≥ 2.29 and < 2.79 per day; T3 – population with consumption of fruit and vegetable servings ≥ 2.79 and < 3.45. per day; ANOVA – analysis of variance; SFA – saturated fatty acids; MUFA – monounsaturated fatty acids; PUFA – polyunsaturated fatty acids; EI – energy intake (kJ day− 1); EE – estimated energy expenditure (kJ day− 1); NS – non siginificant.
Different letters indicate significant differences between groups (Newman–Keuls test): P < 0.05.
The recommended intakes of vitamins and minerals were better covered by the diets of T2 and T3 subjects (Table 4). Table 5 shows that T3 subjects had significantly higher serum and erythrocyte folate levels than T1 and T2 subjects (P < 0.05). A positive correlation was found between the consumption of fruit and vegetables and serum folate (r = 0.2665, P < 0.01) and erythrocyte folate levels (r = 0.2034, P < 0.05), and a negative correlation with t-Hcys (r = − 0.2493, P < 0.01). An inverse correlation was found between t-Hcys and serum cyanocobalamin (r = − 0.2066, P < 0.05) and serum folate levels (r = − 0.2971, P < 0.001).
Table 4 Contribution of the diet towards the coverage of recommended intakes for micronutrients in the different tertile groups (mean±SD)
SD – standard deviation; T1 – population with consumption of fruit and vegetable servings ≥ 1.26 and < 2.29 per day; T2 – population with consumption of fruit and vegetable servings ≥ 2.29 and < 2.79 per day; T3 – population with consumption of fruit and vegetable servings ≥ 2.79 and < 3.45 per day; ANCOVA – analysis of covariance; CRI – coverage of recommended intake; NS–non siginificant.
Different letters indicate significant differences between groups (Newman–Keuls test): P < 0.05.
Table 5 Biochemical data for the different tertile groups (mean±SD)
SD – standard deviation; T1 – population with consumption of fruit and vegetable servings ≥ 1.26 and < 2.29 per day; T2 – population with consumption of fruit and vegetable servings ≥ 2.29 and < 2.79 per day; T3 – population with consumption of fruit and vegetable servings ≥ 2.79 and < 3.45 per day; ANOVA – analysis of variance; SCT – Spearman correlation test (**P < 0.01, *P < 0.05); α-EGR – coefficient of activation of erythrocyte glutathione reductase; HDL – high-density lipoprotein; LDL – low-density lipoprotein; NS–non siginificant.
Different letters indicate significant differences between groups (Newman – Keuls test): P < 0.05.
Discussion
The mean consumption of fruit and vegetables was 2.95 ± 0.92 servings day− 1, similar to that seen in other groups of elderly peopleReference Requejo, Ortega, Robles, Navia, Faci and Aparicio32, but lower than that recommended (a minimum of five servings daily)Reference Perea, Navia, Requejo and Ortega15. Although this recommendation was not met, this study shows that a greater intake of fruit and vegetables is associated with more healthy food habits in general via a positive correlation with a greater intake of cereals, legumes, nuts and fish (typical foods of the Mediterranean diet) (Table 2) and with the reduced consumption of sweet foodsReference Kok and Kromhout33, Reference Trichopoulou34. Independently of its nutritional components, the Mediterranean diet has frequently been reported to help prevent CVDReference Schroder, Marrugat, Vila, Covas and Elosua35, Reference Lasheras, Huerta, Gonzalez, Prada, Braga and Fernandez36, as well as other degenerative diseases such as cancerReference La Vecchia37 and mental deteriorationReference Solfrizzi, Panza and Capurso38, and to increase longevityReference Trichopoulou34.
A greater intake of fruits and vegetables was also associated with better coverage of the recommended intakes of many nutrients, some of which are thought to exercise a cardioprotective effect (fibre, antioxidant vitamins (C and A), vitamins B1, B2, B6, B12 and folic acid), and of phosphorus and zinc (Table 4). Numerous epidemiological studies have shown an association between the consumption of fibre and a lower risk of CVDReference Pereira, O'Reilly, Augustsson, Fraser, Goldbourt and Heitmann39. The main cardioprotective effect of fibre is owed to its characteristic cholesterol-lowering agentsReference Mia, Siddiqui, Haque, Islam, Rukunzzaman and Deb40. Others suggest that diets rich in fibre may lower blood pressureReference He, Streiffer, Muntner, Krousel-Wood and Whelton41. However, in the present study, no relationship was seen between the intake of fruit and vegetables and plasma lipid levels or blood pressure.
Many authors have reported that antioxidant vitamins provide protection against CVDReference Samman, Sivarajah, Man, Ahmad, Petocz and Caterson2, Reference Kiefer, Prock, Lawrence, Wise, Bieger and Bayer42. The antioxidants and polyphenols in fruit and vegetables (vitamin C, carotenoids and flavonoids) prevent the oxidation of plasma lipidsReference Rissanen, Voutilainen, Virtanen, Venho, Vanharanta and Mursu11, Reference Kiefer, Prock, Lawrence, Wise, Bieger and Bayer42, exert an anti-inflammatory effect on the endothelium and improve endothelial functionReference Rissanen, Voutilainen, Virtanen, Venho, Vanharanta and Mursu11, Reference Kiefer, Prock, Lawrence, Wise, Bieger and Bayer42. This appears to be especially true of vitamin CReference Sanchez-Moreno, Dashe, Scott, Thaler, Folstein and Martin43.
Other studies have shown the important role played by minerals such as phosphorus, magnesium and zinc in the regulation of blood pressure and in reducing the risk of myocardial infarctionReference Zhao, Stamler, Yan, Zhou, Wu and Liu44. There are even studies that suggest that these minerals might modulate the extent of atherogenesisReference Alissa, Bahijri, Lamb and Ferns45. These nutrients may therefore be very important in the prevention of CVD – and in the present study their intake was higher in subjects who consumed more fruit and vegetables.
No significant differences were found between T1, T2 and T3 subjects with respect to serum lipid levels. However, some authors report a beneficial effect of diets rich in fruits and vegetables with respect to plasma lipid metabolism, with reductions in triglyceride, total cholesterol and LDL-cholesterol levelsReference Djousse, Arnett, Coon, Province, Moore and Ellison8, and an increase in HDL-cholesterolReference Djousse, Arnett, Coon, Province, Moore and Ellison46. However, the majority of these studies took their subjects from the adult or general population rather than from the elderly sub-population. In the elderly, the conclusions to be drawn might be different since some studies on this age group suggest that high total and LDL-cholesterol levels may no longer be a risk for CVD, and may even be beneficialReference Karlamangla, Singer, Reuben and Seeman47.
A high t-Hcys level is an independent risk factor for CVD; this compound promotes the oxidation of the endothelium and inhibits the production of nitric oxide, thus favouring the development and progress of atherosclerosisReference Das48. The present results show that t-Hcys levels are reduced as fruit and vegetable consumption increases. At the same time, serum and erythrocyte folate levels are increased. An inverse relationship was also seen between t-Hcys and serum cyanocobalamin and serum folate levels. Other studiesReference Samman, Sivarajah, Man, Ahmad, Petocz and Caterson2, Reference Ortega, Jimenez, Andres, Faci, Lolo and Lozano5 have reported similar results and suggest that diets rich in foods containing group B vitamins (fruits, vegetables, legumes, etc.) are associated with lower t-Hcys levels.
In conclusion, the present study shows that higher intakes of fruit and vegetables are associated with better food habits and favour the intake of vitamins and minerals with probable cardioprotective effects – in particular the reduction of t-Hcys levels. Encouraging members of the elderly population to consume more of these foods could have a beneficial influence on their health and nutritional status.
Acknowledgements
This work was financed by Unilever Netherlands via the Universidad-Empresa project 138/2000.
