Cardiovascular disease (CVD) is the leading cause of death worldwide.1 It was estimated to cause 17.8 million deaths in 20172 and one third occurred in people younger than 70 years.1 There is clear evidence that intervention strategies have helped to reduce mortality trends but, despite this progress, CVD remains a public health challenge.3

The incidence of CVD is largely explained by several risk factors, mostly related to lifestyles, which are in turn potentially modifiable and susceptible to prevention. These includes cigarette smoking, low physical activity levels and unhealthy dietary patterns, all of which can contribute to high blood pressure, high body mass index (BMI), high total cholesterol levels, and high fasting plasma glucose levels.4 One of the dietary patterns which has shown benefits in relation to CVD is the Mediterranean diet.5 It is postulated that the beneficial effect of the Mediterranean diet is due to its richness in antioxidant and anti-inflammatory substances, especially polyphenols.5–11

Polyphenols are found in foods including fruits, cereals, vegetables, legumes and cocoa, and beverages such as coffee, tea, and wine.12 These compounds have been observed to show preventive properties against a wide variety of diseases, including CVD.13–15 In addition, many studies have shown that polyphenols may have protective effects in the vascular system and in reducing inflammatory responses.12,16

In epidemiological studies, the relationship between polyphenol intake and cardiovascular risk factors has been analyzed by various approaches.7,8,10,17 In almost all of these, an inverse relationship was observed between them, although results varied with regard to the polyphenol classes or subclasses. Nevertheless, the evidence is still too limited to lead to a recommendation for daily polyphenol intake.

The multifactorial nature of CVD events has led to the development of multivariable risk assessment tools or CVD risk scores,18 including Framingham,19 Framingham-REGICOR,20 and SCORE.21.The Life's Simple 7 (LS7)22 is an alternative to calculate optimal cardiovascular health and provide a new approach to the previous tools. There is wide variability between scores in terms of in the population on which they are based or in the traits they include, so they are not exempt from limitations and agreement problems.23

The aim of this study was to provide a new approach using different cardiovascular risk scores. Since the scores include cardiovascular risk factors (cholesterol, hypertension, smoking, diabetes, overweight/obesity, and other nonmodifiable factors such as age and sex), commonly gathered in the participants included in the PREDIMED-Plus trial, the aim was to assess the possible association between intake of different polyphenol classes and the Framingham, Framingham-REGICOR, SCORE and LS7 instruments.

Table 2 shows the main characteristics of the 6633 participants from the PREDIMED-Plus study according to quintiles of total dietary polyphenol intake. Participants included in the fifth quintile of polyphenol intake were mainly men, with the highest score in the 17-item MedDiet questionnaire and higher physical activity and energy dietary intake than in the other quintiles. In addition, participants in the fifth quintile had less diabetes and lower BMI than those in the other quintiles.

The 4 scores were statistically significantly correlated (P < .001): the coefficient was 0.849 for Framingham and Framingham-REGICOR, 0.731 for Framingham and SCORE, −0.309 Framingham and LS7 was, 0.602 for Framingham-REGICOR and SCORE, −0.333 for Framingham-REGICOR and LS7, and −0.249 for SCORE and LS7.

The associations between the energy-adjusted dietary intake of polyphenols and cardiovascular risk for the different risk equations are shown in table 3 and in the supplementary tables. Total polyphenol and flavonoid intake were only directly and significantly associated with the LS7 scale. Total polyphenol and flavonoid intake were only directly and significantly associated with the LS7 scale. Regarding Q1 of total polyphenol intake, the participants in Q5 showed an improvement in cardiovascular health of 10% (βQ5vs.Q1 = 0.10; 95%CI, 0.04-0.17). For those in Q5 of flavonoid intake, the improvement in cardiovascular health was 17% (βQ5vs.Q1 = 0.17; 95%CI, 0.10-0.24). Similarly, Q5 intake of lignans (in relation to Q1) was associated with an increase in the risk of cardiovascular death of 48% (SCORE: βQ5vs.Q1 = 0.48; 95%CI, 0.25-0.71) and with an increase in cardiovascular health of 23% (LS7: βQ5vs.Q1 = 0.23; 95%CI, 0.16-0.30). The Q5 intake in stilbenes was associated with a 38% increase in the risk of cardiovascular death (SCORE: βQ5vs.Q1 = 0.38; 95%CI, 0.15-0.62), Q5 intake of phenolic acids with a 191% increase in total CVD risk (Framingham: βQ5vs.Q1 = 1.91; 95%CI, 0.76-3.06) and with a 27% increase in coronary risk (Framingham-REGICOR: βQ5vs.Q1 = 0.27; 95%CI, 0.00-0.54). Intake of other polyphenols was significantly associated in Framingham (βQ5vs.Q1 = −1.22; 95%CI, −2.37 to −0.07) and SCORE (βQ5vs.Q1 = −0.32; 95%CI, −0.55 to −0.08), decreasing total CVD risk by 122% and coronary risk by 8%, respectively.

For the stratified analysis by sex, in women, the intake of all the polyphenol classes, except phenolic acids, showed an indirect association in the results of the Framingham and Framingham-REGICOR scores and a direct association in the LS7 scale. Other polyphenol intake also showed the same result for the SCORE equation. In men, total polyphenol intake was directly associated with the Framingham-REGICOR and LS7 equations. Intake of lignans was directly associated with SCORE and LS7 equations, stilbene intake with SCORE, and intake of other polyphenols with the LS7 scale.

Table 4 shows the main results derived from linear regression models after removal of 1 risk factor at a time from each score. In general, for Framingham, Framingham-REGICOR and SCORE, the inverse associations were maintained even if some risk factors were not taken into account in the equations (for Framingham and Framingham-REGICOR in flavonoids and total polyphenols, and for the 3 equations in other polyphenols). The direct association was reversed in Framingham and Framingham-REGICOR equations when blood pressure was eliminated for lignans and, in Framingham for stilbenes when cholesterol, blood pressure and diabetes were removed. The best cardiovascular health (higher score on LS7 scale) was found when consumption of all polyphenol classes (except for phenolic acids) was highest, regardless of removing traits from the equation, except when a healthy diet was removed.

In this cross-sectional study, we evaluated the relationship between intake of different polyphenol classes and estimated cardiovascular risk measured with different tools in the cohort of the PREDIMED-Plus trial.

Previous evidence, mainly from in vivo or in vitro studies, suggests that polyphenol intake reduces CVD probably due to their anti-inflammatory effect, since they lower blood pressure, protect pancreatic cells, improve insulin resistance, inhibit platelet aggregation, reduce very low-density lipoprotein, reduce plasma triglyceride levels, improve nitric oxide homeostasis, antagonize atherogenesis, and improve atherosclerosis.12,38

A few previous studies have evaluated the association between the Mediterranean diet39 and other dietary patterns40 with cardiovascular risk but none has evaluated the association between polyphenol intake and overall cardiovascular risk measured by risk equations. Previous reports were of associations with individual cardiovascular risk factors, mostly focused on the flavonoid family41 and on components of the metabolic syndrome.42–44

Our results are consistent with those already published from the PREDIMED-Plus trial9,10 in which intake of stilbenes and lignans showed a direct association, while intake of flavonoids and other polyphenols showed an inverse association with systolic and diastolic blood pressure. All polyphenol classes were directly associated with high-density lipoprotein cholesterol. The direct association between phenolic acids with the equations and their inverse association with LS7 could also be seen in the aforementioned study,10 in which this family showed a direct and significant association with fasting plasma glucose and, in another study, with higher levels of low-density lipoprotein cholesterol.45 However, another study reported that phenolic acids showed an inverse association with blood pressure, glucose and lipid metabolism, as well as a stronger independent association with metabolic syndrome.42 The main source of phenolic acids in our participants was coffee,10 and some studies have suggested a J-shape relationship between coffee and cardiovascular risk,45,46 which could partly explain the inconclusive results.

Other polyphenol intakes showed a tendency for a protective effect against CVD risk measured by all scores. One of the main sources of these polyphenols in our participants were olives and olive oil,10 which have shown health benefits, mainly attributable to their polyphenol content, which include improvements in lipid profile, insulin sensitivity and endothelial function, as well as antiatherosclerotic and antithrombotic properties.47,48

Interestingly, in the analyses stratified by sex a stronger protective trend was observed in women (except for the phenolic acid family) and, in most cases, results were statistically significant and in the opposite direction than for men. In general, the effects of the Mediterranean diet appear to be greater in men than in premenopausal women when cardiometabolic changes are considered,49 although in this trial the women were postmenopausal. However, the results of the present study are in line with those previously observed in the trial.10 Another study also reported that consumption of foods rich in flavonoids was inversely associated with cardiovascular risk factors in premenopausal women but not in men.50 As in the aforementioned publication, men's habits may have changed due to diagnosis of high cardiovascular risk. In fact, men showed higher CVD risks, measured with all scales, than women. Therefore, reverse causality may have taken place.

Regarding risk equations, the results were concordant for Framingham, Framingham-REGICOR, and LS7. The SCORE equation has shown direct associations with the intake of all the polyphenol classes (except for other polyphenols in all participants and flavonoids and total polyphenols in women).

Differences between polyphenol classes were assessed by a sensitivity analysis. The healthy diet (adherence to the Mediterranean diet) was eliminated from the LS7 scale to check whether the direct association was due to the correlation between diet and polyphenols. In many cases, the direct association was maintained, although in others (stilbenes, other polyphenols, total polyphenols) the association became inverse. The latter suggests that this scale was in harmony with the results shown in the rest of the scores.

In the present study, the 4 scales showed a significant correlation, in addition to showing similar results when they were related to polyphenol intake. Although no studies have been found that compared the equations in this way, those that compared them with each other have shown variation between these scores. The main differences or limitations of these equations are the variables included and the ages for which they were designed. In addition, the risks measured are different, since Framingham addresses total CVD risk, REGICOR addresses coronary risk, SCORE addresses cardiovascular mortality and LS7 measures cardiovascular health. Discrepancies in the detection of high risk have also been shown, specifically, SCORE and Framingham classify different patients as high risk51 and REGICOR classifies fewer individuals as high risk than SCORE.52 In general, most equations work similarly in terms of discrimination, but calibration can vary widely, depending mostly on the population to which it is applied.53

This study shows the association between polyphenol classes and global cardiovascular risk, showing an inverse association between the class of other polyphenols and especially among women. The results were similar for Framingham, Framingham-REGICOR and LS7 (after eliminating diet). SCORE showed different results, but the predictors considered in this equation are limited and do not include some important ones such as diabetes or high-density lipoprotein cholesterol, while it includes other traits with which polyphenols may have no associations.

The PREDIMED-Plus trial was supported by the official funding agency for biomedical research of the Spanish government, ISCIII, through the Fondo de Investigación para la Salud (FIS), which is cofunded by the European Regional Development Fund (5 coordinated FIS projects led by J. Salas-Salvadó and J. Vidal, including the following projects: PI13/00673, PI13/00492, PI13/00272, PI13/01123, PI13/00462, PI13/00233, PI13/02184, PI13/00728, PI13/01090, PI13/01056, PI14/01722, PI14/00636, PI14/00618, PI14/00696, PI14/01206, PI14/01919, PI14/00853, PI14/01374, PI14/00972, PI14/00728, PI14/01471, PI16/00473, PI16/00662, PI16/01873, PI16/01094, PI16/00501, PI16/00533, PI16/00381, PI16/00366, PI16/01522, PI16/01120, PI17/00764, PI17/01183, PI17/00855, PI17/01347, PI17/00525, PI17/01827, PI17/00532, PI17/00215, PI17/01441, PI17/00508, PI17/01732, PI17/00926, PI19/00957, PI19/00386, PI19/00309, PI19/01032, PI19/00576, PI19/00017, PI19/01226, PI19/00781, PI19/01560, and PI19/01332), the Especial Action Project entitled: Implementación y evaluación de una intervención intensiva sobre la actividad física Cohorte PREDIMED-Plus grant to J. Salas-Salvadó, the European Research Council (Advanced Research Grant 2013–2018, 340918) to M.Á. Martínez-González, the Recercaixa Grant to J. Salas-Salvadó (2013ACUP00194), CICYT [AGL2016- 75329-R], a grant from the Generalitat Valenciana (APOSTD/2019/136 to RB) and Generalitat de Catalunya (SGR-2019 to RE), grants from the Consejería de Salud de la Junta de Andalucía (PI0458/2013, PS0358/2016, and PI0137/2018), grants from the Generalitat Valenciana (PROMETEO/2017/017), a SEMERGEN Grant, EU-COST Action CA16112, a grant of support to research groups no. 35/2011 from the Balearic Islands Government, Grants from Balearic Islands Health Research Institute (IDISBA), funds from the European Regional Development Fund (CIBEROBN CB06/03 and CB12/03) and from the European Commission (EAT2BENI-CE_H2020_SFS2016). The Spanish Ministry of Science, Innovation and Universities for the Formación de Profesorado Universitario (FPU17/06488 and FPU17/00785) contract. The funding sponsors had no role in the design of the study, in the collection, analyses, or interpretation of the data, in the writing of the manuscript, or in the decision to publish the results.

Conceptualization: M. Rubín-García, F. Vitelli-Storelli, E. Toledo and V. Martín. Methodology: M. Rubín-García, F. Vitelli-Storelli, E. Toledo, S. Castro-Barquero, A. Tresserra-Rimbau and V. Martín-Sánchez. Formal analysis: M. Rubín-García, E. Toledo and V. Martín-Sánchez. Drafting and preparation of the draft: M. Rubín-García. Review and edition; M. Rubín-García, F. Vitelli-Storelli, E. Toledo, S. Castro-Barquero, A. Tresserra-Rimbau, M.A. Martínez-González, J. Salas-Salvadó, D. Corella, A. Hernáez, J.A. Martínez, A.M. Alonso-Gómez, J. Wärnberg, J. Vioque, D. Romaguera, J. López-Miranda, R. Estruch, M.R. Bernal-López, J. Lapetra, L. Serra-Majem, A. Bueno-Cavanillas, J.A. Tur, L. Álvarez-Álvarez, X. Pintó, J.J. Gaforio, P. Matía-Martín, J. Vidal, C. Vázquez, L. Daimiel, E. Ros, A. Gea, J.J. Manzanares, J.V. Sorlí, H. Schröder, I. Abete, L. Tojal-Sierra, E. Crespo-Oliva, A. González-Botella, E. Rayó, A. García-Rios, A.M. Gómez-Pérez, J.M. Santos-Lozano, R. Bartolomé-Resano, M.M. Murphy, C. Ortega-Azorin, C. Medrano, M.A. Zulet, C. Sorto-Sanchez, N. Babio, M. Fitó, R.M. Lamuela-Raventós and V. Martín-Sánchez; Project management: E. Toledo, M.A. Martínez-González, J. Salas-Salvadó, D. Corella, J.A. Martínez, A.M. Alonso-Gómez, J. Wärnberg, J.Vioque, D. Romaguera, J. López-Miranda, R. Estruch, M.R. Bernal-López, J. Lapetra, J.L. Serra-Majem, A. Bueno-Cavanillas, J.A. Tur, X. Pintó, J.J. Gaforio, P. Matía-Martín, J. Vidal, C. Vázquez, L. Daimiel, E. Ros, H. Schröder, N. Babio, M. Fitó, R.M. Lamuela-Raventós, and V. Martín-Sánchez. Supervision: F. Vitelli-Storelli, E. Toledo, and V. Martín-Sánchez. Funding acquisition: E. Toledo, M.A. Martínez-González, J. Salas-Salvadó, D. Corella, J.A. Martínez, A.M. Alonso-Gómez, J. Wärnberg, J. Vioque, D. Romaguera, J. López-Miranda, R. Estruch, M.R. Bernal-López, J. Lapetra, J.L. Serra-Majem, A. Bueno-Cavanillas, J.A. Tur, X. Pintó, J.J. Gaforio., P. Matía-Martín, J. Josep Vidal, C. Vázquez, L. Daimiel, E. Ros, H. Schröder, N. Babio, M. Fitó, R.M. Lamuela-Raventós, and V. Martín-Sánchez. All authors have read and accepted the final version of the manuscript.

R. Estruch reports grants from Cerveza y Salud, Spain, and Fundación Dieta Mediterránea, Spain, as well as personal fees for lectures from Brewers of Europe, Belgium, Fundación Cerveza y Salud, Spain, Pernaud-Ricard, Mexico, Instituto Cervantes, Alburquerque, USA; Instituto Cervantes, Milan, Italy, Instituto Cervantes, Tokyo, Japan, Lilly Laboratories, Spain, and Wine and Culinary International Forum, Spain, nonfinancial support to organize a National Congress on Nutrition and feeding trials with products from Grand Fountain and Uriach Laboratories, Spain.

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