Adherence to WCRF/AICR cancer prevention recommendations and metabolic syndrome in breast cancer patients

International Journal of CancerVolume 138, Issue 1 p. 237-244 Cancer Therapy and PreventionFree Access Adherence to WCRF/AICR cancer prevention recommendations and metabolic syndrome in breast cancer patients Eleonora Bruno, Corresponding Author Eleonora Bruno Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalyCorrespondence to: Eleonora Bruno, Epidemiology & Prevention Unit, Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori Via Venezian, 1 20133 Milano, Italy, Tel.: +390223903512, Fax: + 390223903516, E-mail: eleonora.bruno@istitutotumori.mi.itSearch for more papers by this authorGiuliana Gargano, Giuliana Gargano Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalySearch for more papers by this authorAnna Villarini, Anna Villarini Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalySearch for more papers by this authorAdele Traina, Adele Traina Department of Oncology, A.R.N.A.S Ospedali Civico E Benfratelli G. Di Cristina E M. Ascoli, Palermo, ItalySearch for more papers by this authorHarriet Johansson, Harriet Johansson Division of Chemoprevention and Genetics, European Institute Of Oncology, Milan, ItalySearch for more papers by this authorMaria Piera Mano, Maria Piera Mano Dipartimento Scienze Chirurgiche, Study University, Turin, Italy S.C. Epidemiologia Dei Tumori, AOU Città Della Salute E Della Scienza, CPO Piemonte, Turin, ItalySearch for more papers by this authorMaria Santucci De Magistris, Maria Santucci De Magistris Azienda Ospedaliera Unversitaria, Federico II, Naples, ItalySearch for more papers by this authorMilena Simeoni, Milena Simeoni Associazione LUMEN, San Pietro In Cerro (Piacenza), ItalySearch for more papers by this authorElena Consolaro, Elena Consolaro Azienda Sanitaria Locale, Varese, ItalySearch for more papers by this authorAngelica Mercandino, Angelica Mercandino Fondazione Edo Tempia, Biella, ItalySearch for more papers by this authorMaggiorino Barbero, Maggiorino Barbero Obstetrics and Gynecology Unit, Cardinal Massaia Hospital, Asti, ItalySearch for more papers by this authorRocco Galasso, Rocco Galasso Biostatistics and Cancer Registry, Unit Of Clinical Epidemiology, IRCCS Centro Di Riferimento Oncologico Di Basilicata, Rionero In Vulture (Potenza), ItalySearch for more papers by this authorMaria Chiara Bassi, Maria Chiara Bassi Azienda Sanitaria Locale, Mantova, ItalySearch for more papers by this authorMaurizio Zarcone, Maurizio Zarcone Department of Oncology, A.R.N.A.S Ospedali Civico E Benfratelli G. Di Cristina E M. Ascoli, Palermo, ItalySearch for more papers by this authorEmanuela Zagallo, Emanuela Zagallo Division of Chemoprevention and Genetics, European Institute Of Oncology, Milan, ItalySearch for more papers by this authorElisabetta Venturelli, Elisabetta Venturelli Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalySearch for more papers by this authorManuela Bellegotti, Manuela Bellegotti Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalySearch for more papers by this authorFranco Berrino, Franco Berrino Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalySearch for more papers by this authorPatrizia Pasanisi, Patrizia Pasanisi Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalySearch for more papers by this author Eleonora Bruno, Corresponding Author Eleonora Bruno Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalyCorrespondence to: Eleonora Bruno, Epidemiology & Prevention Unit, Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori Via Venezian, 1 20133 Milano, Italy, Tel.: +390223903512, Fax: + 390223903516, E-mail: eleonora.bruno@istitutotumori.mi.itSearch for more papers by this authorGiuliana Gargano, Giuliana Gargano Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalySearch for more papers by this authorAnna Villarini, Anna Villarini Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalySearch for more papers by this authorAdele Traina, Adele Traina Department of Oncology, A.R.N.A.S Ospedali Civico E Benfratelli G. Di Cristina E M. Ascoli, Palermo, ItalySearch for more papers by this authorHarriet Johansson, Harriet Johansson Division of Chemoprevention and Genetics, European Institute Of Oncology, Milan, ItalySearch for more papers by this authorMaria Piera Mano, Maria Piera Mano Dipartimento Scienze Chirurgiche, Study University, Turin, Italy S.C. Epidemiologia Dei Tumori, AOU Città Della Salute E Della Scienza, CPO Piemonte, Turin, ItalySearch for more papers by this authorMaria Santucci De Magistris, Maria Santucci De Magistris Azienda Ospedaliera Unversitaria, Federico II, Naples, ItalySearch for more papers by this authorMilena Simeoni, Milena Simeoni Associazione LUMEN, San Pietro In Cerro (Piacenza), ItalySearch for more papers by this authorElena Consolaro, Elena Consolaro Azienda Sanitaria Locale, Varese, ItalySearch for more papers by this authorAngelica Mercandino, Angelica Mercandino Fondazione Edo Tempia, Biella, ItalySearch for more papers by this authorMaggiorino Barbero, Maggiorino Barbero Obstetrics and Gynecology Unit, Cardinal Massaia Hospital, Asti, ItalySearch for more papers by this authorRocco Galasso, Rocco Galasso Biostatistics and Cancer Registry, Unit Of Clinical Epidemiology, IRCCS Centro Di Riferimento Oncologico Di Basilicata, Rionero In Vulture (Potenza), ItalySearch for more papers by this authorMaria Chiara Bassi, Maria Chiara Bassi Azienda Sanitaria Locale, Mantova, ItalySearch for more papers by this authorMaurizio Zarcone, Maurizio Zarcone Department of Oncology, A.R.N.A.S Ospedali Civico E Benfratelli G. Di Cristina E M. Ascoli, Palermo, ItalySearch for more papers by this authorEmanuela Zagallo, Emanuela Zagallo Division of Chemoprevention and Genetics, European Institute Of Oncology, Milan, ItalySearch for more papers by this authorElisabetta Venturelli, Elisabetta Venturelli Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalySearch for more papers by this authorManuela Bellegotti, Manuela Bellegotti Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalySearch for more papers by this authorFranco Berrino, Franco Berrino Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalySearch for more papers by this authorPatrizia Pasanisi, Patrizia Pasanisi Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, ItalySearch for more papers by this author First published: 14 July 2015 https://doi.org/10.1002/ijc.29689Citations: 24 Conflict of Interest: : All Authors declare no conflicts of interest. AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract Metabolic syndrome (MetS), conventionally defined by the presence of at least three out of five dismetabolic traits (abdominal obesity, hypertension, low plasma HDL-cholesterol and high plasma glucose and triglycerides), has been associated with both breast cancer (BC) incidence and prognosis. We investigated the association between the prevalence of MetS and a score of adherence to the World Cancer Research Fund (WCRF) and American Institute for Cancer Research (AICR) recommendations for the prevention of cancer in a cross-sectional study of BC patients. The DIet and ANdrogen-5study (DIANA-5) for the prevention of BC recurrences recruited 2092 early stage BC survivors aged 35–70. At recruitment, all women completed a 24-hour food frequency and physical activity diary on their consumption and activity of the previous day. Using these diaries we created a score of adherence to five relevant WCRF/AICR recommendations. The prevalence ratios (PRs) and 95% confidence intervals (CIs) of MetS associated with the number of recommendations met were estimated using a binomial regression model. The adjusted PRs of MetS decreased with increasing number of recommendations met (p < 0.001). Meeting all the five recommendations versus meeting none or only one was significantly associated with a 57% lower MetS prevalence (95% CI 0.35–0.73). Our results suggest that adherence to WCRF/AICR recommendations is a major determinant of MetS and may have a clinical impact. Abstract What's new? Postmenopausal women with metabolic syndrome (MetS) are at increased risk of breast cancer (BC), as well as poorer prognosis and possibly recurrence. In this study, the authors found that women who adhered to more dietary recommendations for preventing cancer were also less likely to develop MetS. These results warrant further study, as they suggest that following dietary guidelines that reduce MetS might, in turn, reduce the risk of BC and BC recurrence. Postmenopausal women with metabolic syndrome (MetS) are at increased risk of breast cancer (BC)1 and we recently published that in BC patients MetS is also significantly associated with a poorer prognosis.2 The etiology of MetS is considered to reside in a complex interaction between genetic, metabolic and environmental factors such as diet and physical activity.3-5 Prospective studies showed an inverse relationship between adherence to the Mediterranean Diet (MedDiet) and MetS.6, 7 Randomized intervention trials showed that MetS can be reversed by adhering to the MedDiet,8-10 with a reduction of MetS prevalence to one-third after 2 years of diet.8 In 2007 the systematic literature review carried out by the World Cancer Research Fund (WCRF) and the American Institute for Cancer Research (AICR) provided lifestyle recommendations aimed at reducing the incidence of the most common cancers worldwide.11 The dietary recommendations include avoiding sugared beverages and processed meat, limiting calorie-dense food, alcoholic beverages, salty food and red meat, and the central recommendation is to “Eat mostly food of plant origin, with a variety of nonstarchy vegetables and of fruit every day and with unprocessed cereals and/or pulses within every meal”. This coincides with the basic MedDiet characteristics. Recently, the European Prospective Investigation into Cancer and Nutrition (EPIC) study12 reported a statistically significant 16% reduction of BC in women with the highest concordance with the WCRF/AICR recommendations compared with women with the lowest concordance. The Vitamins and Lifestyle (VITAL) study showed that BC risk was reduced by 60% in women who met at least five WCRF/AICR recommendations compared with those who met none.13 Our DIet and ANdrogen (DIANA) randomized controlled trials showed that an insulin-lowering diet, based on traditional Mediterranean and macrobiotic recipes, significantly decreases the main factors defining MetS in healthy postmenopausal women14, 15 and in women with a previous diagnosis of BC.16 As the preventive effect of respecting the WCRF/AICR recommendations may be largely mediated by the prevention of MetS, we performed a cross-sectional analysis to explore the association between the prevalence of MetS and the adherence to the 2007 WCRF/AICR cancer prevention recommendations. Subjects And Methods The present report concerns the baseline data of 2092 women, aged 35–70 years, diagnosed with invasive BC within the previous 5 years (1.76 years on average), free of recurrence, enrolled in the DIet and ANdrogen-5 study (DIANA-5)2, 17 an ongoing multi-institutional randomized controlled trial aimed at testing the hypothesis that a lifestyle change based on the Mediterranean diet and macrobiotic principles, together with moderate physical activity, can reduce the incidence of additional BC-related events. The design of the trial has been previously described in detail.17 The study was approved by the Institutional Review Board and Ethical Committee of the all collaborating Institutions. At baseline, all the women provided a copy of their clinical notes, donated a fasting early morning blood sample and filled in a questionnaire on BC risk factors, and a questionnaire on food intake and physical exercise in the previous 24 hr. Height and body weight were measured without shoes and heavy clothes, waist circumference was measured with a measuring tape in the mid-point between the lowest rib and the iliac crest during expiration. Blood pressure was taken using the same electronic meter in all centres. Definition of MetS MetS was defined on the basis of the presence of at least three out of five components, according to the thresholds proposed by the International Diabetic Federation—systolic blood pressure ≥ 130 and diastolic blood pressure ≥ 85 mmHg, fasting plasma glucose ≥ 100 mg/100 ml (5.6 mmol/l) or previously diagnosed type II diabetes, triglycerides ≥ 150 mg/100 ml (1.7 mmol/l), high-density lipoprotein < 50 mg/100 ml (1.03 mmol/l)—except for waist circumference, for which we used the threshold of ≥ 85 cm instead of ≥ 80 cm, because the constitution of Italian women is not as lean as the constitution of the other European women.18 As suggested,19 we considered as MetS components also the presence of treatments for dyslipidemia and for hypertension. Dietary and physical activity data collection At baseline all participants completed a 24-hr food frequency and physical activity diary concerning the previous day. The diary contained a list of 65 food items, without information on portion size or weight, nor on recipes. The women only had to indicate whether, on the previous day, they had eaten or had not eaten the specified food at breakfast, lunch, dinner and breaks. The diary contained also five questions about the time spent on physical exercise on the day before the enrollment, enquiring on work and recreational physical activity duration (hours/minutes) and intensity (moderate, vigorous). The score of adherence to the WCRF/AICR recommendations We created a score of adherence to the WCRF/AICR recommendations using the 24-hr food frequency and physical activity diary filled in at recruitment, when the participating women had not yet received any lifestyle recommendations. We classified the women according to the adherence to the following five WCRF/AICR recommendations: Physical activity (be physically active as part of everyday life). We asked if the participants had engaged in walking and/or other moderate or strenuous activity on the day before the enrollment. The women who exercised for at least 30 minutes were considered compliant with the recommendation. Food and drinks that promote weight gain (limit consumption of energy-dense food and avoid sugary drinks). The recommendation to limit energy-dense foods could not be operationalized because our questionnaire did not include recipes and food portions. However, the women who did not consume any sugary drinks were considered compliant. Plant foods (eat mostly foods of plant origin: at least 5 servings of a variety of nonstarchy vegetables and fruits every day, and relatively unprocessed grains and/or legumes with every meal). The women who consumed at least 5 servings of fruits (excluding fruit juices) and/or nonstarchy (i.e., excluding potatoes) vegetables, and at least one serving of whole grains and/or legumes per day were considered compliant. Animal foods (limit intake of red meat and avoid processed meat). The women who had not eaten any processed meat and had eaten no more than one portion of red meat on the previous day were considered compliant. In a sensitivity analysis we considered compliant only in women who did not eat red and processed meat. Alcoholic drinks (limit alcoholic drinks). The women who had consumed no more than one time alcoholic drink (wine or beer or spirits) on the previous day were considered compliant. Since body fatness is strongly related to waist circumference, which is a component of MetS, we did not include BMI data and the recommendation on body fatness (be as lean as possible within the normal range of body weight) in our adherence score. The DIANA-5 diaries did not give sufficient information to include into the compliance score the recommendations to limit consumption of salt, to avoid mouldy cereals or pulses, and to meet nutritional needs through diet alone (i.e., not thought dietary supplements). We generated the compliance score by giving 1 point if the women met the recommendation and 0 if they did not meet it, so that the score ranges 0–5. Consistently with the method used in several studies13, 20-22 to analyze the disease risk according to the adherence to WCRF recommendations, we classified adherence simply as the number of respected recommendations (0 to 5). Other studies12, 23-26 used a different compliance score, by giving 0, 0.5, 1 point, according to the level of adherence. We performed a sensitivity analysis creating subcategories of adherence for: physical activity, plant foods, animal foods and alcohol (detailed description available on request). Statistical analysis We performed a preliminary description of the baseline characteristics of the DIANA-5 population stratifying by the presence or absence of MetS. The means of the continuous variables in the women with MetS were compared with those of the unaffected women by using Student's t test. χ2d was used to compare frequencies. We generated food group variables by summing up single food items: added sugars (white sugar + brown sugar + malt); refined cereals (white bread + white rice + egg noodles + corn flakes + sweetened muesli + biscuits); whole-grain products (whole bread + whole rice + other whole grain cereals + unsweetened muesli + oat flakes); legumes and soya products (tofu or tempeh). Food and food group consumption was described according to three categories (0 = not consumed; 1 = 1 time/day; >1 = >1 time/day). We performed a trend test across these categories to compare women with and without MetS. The Prevalence Ratios (PRs) and 95% confidence intervals (CI) of MetS associated with the number of recommendations met (vs. meeting none or a single one) were estimated using a binomial regression model which included age at recruitment (in quintiles), education (none or primary school, high school, degree or more) and parity as covariates. We used a binomial regression model instead of a logistic regression because we were interested not to estimate the risk of MetS but the prevalence. Further models were produced controlling for BMI (even if associated with several aspect of MetS), study center, menopausal status and years from BC diagnosis. We also computed the PRs and 95% confidence intervals (CI) of MetS associated with meeting (vs. not meeting) each single recommendation. The covariates included in the models were age, education, parity, study center and the other 4 WCRF/AICR recommendations. A p values of <0.05 was considered to be significant. All statistical tests were two-sided. All analyses were carried out using the STATA 12 statistical package. Results Out of 2092 BC patients enrolled into the DIANA-5 study, 419 women (20%) had MetS, 962 (46%) had only one or two traits of MetS and 711 (34%) had none. Table 1 shows the baseline characteristics of the population stratifying by the presence or absence of MetS. Table 1. Baseline characteristics of the DIANA-5 population by MetS No metabolic syndrome Metabolic syndrome pc All participants N = 1673 N = 419 N = 2092 Mean SD Mean SD Mean SD Age at enrollment (years)1 50.6 (8.0) 55.2 7.8 <0.001a 51.5 8.2 Age at diagnosis (years) 48.9 7.9 53.2 7.9 <0.001a 49.7 8.1 ER-positive (%) 84.0 88.2 0.03b 84.9 Stage (%) I 47.3 41.4 46.0 II a 28.1 32.8 29.1 II b 10.8 11.3 10.9 ≥III a 13.8 14.5 0.16 14.0 Education (%) Primary school 19.8 32.1 14.6 High school 47.9 48.4 51.0 Universiy degree 32.3 19.5 <0.001b 34.4 Nulliparous (%) 8.8 7.3 0.39 5.4 Current smokers (%) 12.8 16.9 0.09 13.1 Mean SD Mean SD Mean SD Waist circumference (cm) 81.1 10.6 96.7 10.3 84.3 12.3 Glycemia (mg/dl) 89.8 10.8 105.1 25.6 92.8 16.2 Total cholesterol (mg/dl) 206.8 36.6 215.2 39.9 208.5 37.5 HDL (mg/dl) 66.7 15.3 49.7 11.9 63.3 16.2 LDL (mg/dl) 123.7 49.6 134.1 39.2 125.8 47.8 Triglycerides (mg/dl) 87.2 41.3 165.0 99.0 102.9 65.6 Diastolic blood press (mmHg) 79.2 10.8 88.0 11.7 81.0 11.6 Systolic blood press(mmHg) 122.2 17.1 136.5 18.6 125.1 18.3 Insulin (μU/ml) 7.0 6.1 12.8 12.6 8.2 8.2 a p of t Student. b p of chi-square. c boldface values are for p < 0.05. The average age at study entry was 51.5 years. The women without MetS were significantly younger at enrollment and at diagnosis (p < 0.001), and were more educated than the women with MetS (p < 0.001). There weren't any significant differences in smoking habits and parity between the two groups. At the time of diagnosis, the women with MetS had a higher proportion of ER-positive tumors (p = 0.03) and a somewhat more advanced stage distribution (p = 0.16). As expected, the women affected by MetS showed significantly poorer metabolic and anthropometric parameters compared with the women without MetS. Consistently, serum insulin levels were significantly higher in patients with MetS (p < 0.001). Table 2 describes the baseline frequency of consumption of selected foods or food groups (3 categories of consumption) by the presence or absence of MetS. The women without MetS had a significantly higher consumption of whole grains, legumes, nuts and vegetables, and a significantly lower consumption of refined foods, pasta, red and processed meat than the women with MetS. There was no difference in the declared consumption of fruit, added sugars, alcoholic and sugared beverages. However, women with MetS included a slightly higher number of women who consumed sugared beverages twice or more frequently. Table 2. Baseline daily frequency of consumption of selected foods or food groups in women with and without MetS No metabolic syndrome (%) N = 1673 Metabolic syndrome (%) N = 419 pa Food/frequency 0 1 >1 0 1 >1 Added Sugars 41.9 36.0 23.1 44.1 34.9 21.0 0.17 Refined cereals 14.5 22.8 62.7 10.1 21.5 68.4 0.01 Pasta 57.2 40.3 2.5 48.9 46.8 4.3 <0.001 Whole-grain products 50.6 27.2 22.2 64.3 21.5 14.2 <0.001 Legumes and soy products 74.8 21.4 3.76 80.5 16.9 2.6 0.02 Red meat 71.7 26.6 1.7 64.6 31.8 3.6 <0.001 Processed meat 73.5 24.8 1.7 71.1 26.5 2.4 0.21 Red and processed meat 53.7 35.5 10.8 47.7 37.3 14.9 0.01 Vegetables 9.3 20.6 70.1 11.6 24.8 63.6 0.01 Fruit 21.6 30.2 48.2 24.8 27.2 48.0 0.60 Nuts and seeds 71.5 24.8 3.7 81.7 16.4 1.9 <0.001 Alcoholic drinks 68.8 23.0 8.2 68.7 19.8 11.6 0.63 Sugared beverages 81.4 17.1 1.5 84.7 12.5 2.8 0.14 a p of trend test across categories. Boldface values are for p < 0.05. Table 3 gives the percentages of women who met the recommendations and the prevalence rate ratios (PRs) of MetS in the women who complied compared with those who did not. Table 3. Proportions of women who met the WCRF/AICR cancer prevention recommendations in women with and without MetS (A), and prevalence ratios (PRs) of MetS in compliant versus noncompliant women (B) WCRF/AICR recommendations A B % of women who met the recommendation* Metabolic syndrome PRsc No metabolic syndrome N = 1673 Metabolic syndrome N = 419 PRs (95% CIs)a PRs (95% CIs)b Physical activity A brisk walking and/or moderate or strenuous activity 64.8 53.2 0.80 (0.72–0.89) 0.82 (0.73–0.90) Sugary beverages No sugary drinks 81.4 84.7 1.03 (0.98–1.08) 1.04 (0.98–1.12) Plant foods ≥5 servings of fruits and vegetables and ≥1 serving of whole grains and/or legumes 39.4 32.0 0.81 (0.69–0.95) 0.83 (0.71–0.98) Animal foods ≤1 portions of red meat and no portion of processed meat 54.0 47.7 0.90 (0.80–1.01) 0.92 (0.82–1.04) Alcohol consumption ≤1 serving/die 91.8 88.5 0.99 (0.96–1.03) 1.01 (0.97–1.05) a Adjusted for quintile of age, education, parity and center. b Adjusted for quintile of age, education, parity, center and all the other recommendation. c boldface values are for p < 0.05. The women with MetS were less physically active, consumed less plant food and more meat. The PRs of MetS for the women who met the physical activity and plant food recommendations were significantly lower (−20% and −19%, respectively). The association persisted significant also after further adjustment for the other recommendations. There was no difference in the compliance with the recommendation of limiting alcohol consumption and the difference for red and processed meat consumption was not statistically significant. So, we performed a sensitivity analysis changing the definition of the animal foods and alcohol variables. Modifying the definition of the compliance to the recommendation on red and processed meat consumption to “no red or processed meat consumption” the prevalence ratio of MetS became 0.82 (0.65–1.08), instead of 0.92 (0.82–1.04). For alcohol consumption recommendation, changing the definition of the compliance to “no alcohol consumption” instead of “≤ 1 portion of alcohol”, the PRs of MetS became 1.04 (0.87–1.26), instead of 0.99 (0.96–1.03). Table 4 gives the PRs of MetS and the 95% CIs by the number of WCRF/AICR recommendations met. On average, women with MetS totalized 2.46 ± 0.93 adherence points against 2.70 ± 0.91 among women without MetS (p < 0.001). After adjusting for age, parity and education, the PR decreased with the number of recommendations met (p < 0.001). Meeting all the five recommendations vs. meeting none or only one was significantly associated with a 57% reduction in prevalence. BMI is associated with several aspects of the MetS. However, since there were women with high BMI who did not have MetS, we also produced results adjusted for BMI and PR of women complying with all the 5 recommendations became 0.59 (0.39–0.88, p < 0.01). Further adjustment for study center, menopausal status at recruitment and years from BC diagnosis did not modify the results. Table 4. Prevalence ratios of metabolic syndrome and 95% CIs by number of WCRF/AICR recommendations met Number of WCRF/AICR recommendation met % of women who met recommendation PRs (95% CIs)a No metabolic syndrome N = 1673 Metabolic syndrome N = 419 0/1 4.1 6.8 1 2 18.5 22.9 0.77 (0.55–1.09) 3 33.3 35.2 0.73 (0.53–1.01) 4 30.7 28.2 0.67 (0.48–0.94) 5 13.4 7.0 0.43 (0.27–0.65) p trendb <0.001 a Adjusted for quintile of age, education and parity. b boldface values are for p < 0.05. Using as a reference category the women complying with 0 to 2 recommendations, the PR of those complying with all the 5 recommendations became 0.52 (0.36–0.77, p < 0.001). Comparing women with only 1 or 2 MetS parameters with those without any MetS trait, we found intermediate results PR = 0.80 (0.62–0.91) for those complying with all the 5 recommendations. Since other studies used a different compliance score, by giving 0, 0.5, 1 point, according to the level of adherence, we performed a sensitivity analysis by using also this score. Women in the upper quintile of this summary score (≥ 4 points) showed a prevalence ratio 0.62 (0.46–0.86, p trend <0.001) with respect to women in the lower quintile (≤ 2 points), quite consistent with our main results. Discussion Our results reported a lower prevalence of MetS with increasing adherence to the WCRF/AICR recommendations, apparently largely due to meeting the recommendations on physical activity and on the consumption of plant foods. Women without MetS showed a significantly higher frequency of consumption of whole grain cereals, nuts and seeds, fruits and vegetables compared with the women affected by MetS. This is consistent with the results of prospective studies on the association of body weight and the consumption of foods and beverages, showing that people who eat more whole grains, fruits, nuts and vegetables gain less weight over time.27 Previous observational studies already showed that a moderate physical activity is associated with a lower prevalence of MetS parameters.28 Consistently, randomized controlled trials of both dietary modification and physical exercise showed lower rates of MetS in persons with impaired glucose tolerance or impaired fasting glucose.29-31 The WCRF/AICR recommendation on the consumption of plant foods (“Eat mostly food of plant origin, with a variety of nonstarchy vegetables and of fruit every day and with unprocessed cereals and/or pulses within every meal”) is also the basic characteristic of the MedDiet. Based on the results of a meta-analysis of 50 independent studies, adherence to the Mediterranean dietary pattern was associated with a 50% reduction of Met