This is the peer reviewed version of the following article: Association Between Western and Mediterranean Dietary Patterns and Mammographic Density Adela Castelló; Nieves Ascunce; Dolores Salas-Trejo; Carmen Vidal; Carmen Sanchez- Contador; Carmen Santamariña; Carmen Pedraz-Pingarrón; Maria Moreno; Beatriz Pérez-Gómez; Virginia Lope; Nuria Aragonés; Jesús Vioque; Marina Pollán;. Obstet Gynecol. 2016 Sep;128(3):574-81. which has been published in final form at https://doi.org/10.1097/AOG.0000000000001589 1 Title: Association between Western and Mediterranean dietary patterns and 1 mammographic density. 2 Authors: Adela Castelló1,2,3PhD, Nieves Ascunce2,4MD, Dolores Salas-Trejo5PhD, Carmen 3 Vidal6MD, Carmen Sanchez-Contador7MD, Carmen Santamariña8MD, Carmen Pedraz-4 Pingarrón9MD, Maria Pilar Moreno10MD, Beatriz Pérez-Gómez1,2,3PhD, Virginia 5 Lope1,2,3PhD, Nuria Aragonés1,2,3 PhD, Jesús Vioque,2, 11 PhD, Marina Pollán1,2,3 PhD on 6 behalf of DDM-Spain research group† 7 1. Cancer Epidemiology Unit. National Center for Epidemiology. Instituto de Salud Carlos III. 8 Madrid, Spain. 9 2. Consortium for Biomedical Research in Epidemiology & Public Health (CIBERESP). 10 Instituto de Salud Carlos III. Madrid, Spain. 11 3. Cancer Epidemiology Research Group. Oncology and Hematology Area. IIS Puerta de 12 Hierro (IDIPHIM). Madrid, Spain. 13 4. Navarre Breast Cancer Screening Program, Public Health Institute. Pamplona, Spain. 14 5. Valencian Breast Cancer Screening Program, General Directorate of Public Health. Valencia, 15 Spain. 16 6. Cancer Prevention and Control Unit, Catalonian Institute of Oncology (ICO. Barcelona, 17 Spain. 18 7. Balearic Islands Breast Cancer Screening Program, Directorate General of Public Health and 19 Participation. Palma de Mallorca, Illes Balears. 20 2 8. Galician Breast Cancer Screening Program, Galician Regional Health Authority. A Coruña, 21 Spain. 22 9. Castile-León Breast Cancer Screening Program, General Directorate of Public Health. 23 Burgos, Spain 24 10. Aragón Breast Cancer Screening Program. Aragon Health Service. Zaragoza, Spain. 25 11. Universidad Miguel Hernandez. Sant Joan D'Alacant, Spain. 26 Membership of the DDM-Spain research group is provided in the Appendix 1 27 CORRESPONDING AUTHOR: 28 Dr. Adela Castelló 29 Cancer Epidemiology Unit, National Center for Epidemiology. 30 Instituto de Salud Carlos III. 31 Avenida Monforte de Lemos, 5, 28029, Madrid, Spain. 32 Phone: +34 91 822 2667. 33 Fax: +34 91 387 7815. 34 e-mail: acastello@isciii.es 35 SOURCES OF SUPPORT 36 37 This study was supported by Carlos III Institute of Health FIS (Spanish Public Health Research 38 Fund: PI060386 FIS; PS09/00790 and PI15CIII/0029 research grants); the Spanish Ministry of 39 Health (EC11-273); the Spanish Ministry of Economy and Competitiveness (IJCI-2014-40 3 20900); the Spanish Federation of Breast Cancer Patients (FECMA: EPY 1169-10); and the 41 Association of Women with Breast Cancer from Elche (AMACMEC: EPY 1394/15). 42 43 Short title: Dietary patterns and mammographic density 44 ACKNOWLEDGEMENTS 45 Authors which to acknowledge the financial support provided by Carlos III Institute of Health 46 (PI060386 FIS;PS09/0790 and PI15CIII/0029), the Spanish Ministry of Economy and 47 Competitiveness (IJCI-2014-20900), the Spanish Federation of Breast Cancer Patients 48 (FECMA EPY 1169-10) and the Association of Women with Breast Cancer from Elche 49 (AMACMEC EPY 1394/15). 50 51 52 4 Précis 53 High adherence to the Western dietary pattern is associated with higher mammographic density. 54 However, the Mediterranean dietary pattern is not associated with mammographic density. 55 5 Abstract 56 Objective: To examine the association between two dietary patterns (Western and 57 Mediterranean), previously linked to breast cancer risk, and mammographic density. Methods: 58 This cross-sectional study included 3584 women attending population-based breast cancer 59 screening programs and recruited between October 7th, 2007 and July 14th, 2008 (participation 60 rate: 74.5%). Collected data included anthropometric measurements, demographic, obstetric 61 and gynecologic characteristics, family and personal health history, and diet in the preceding 62 year. Mammographic density was blindly assessed by a single radiologist and classified into 63 four categories: <10%, 10–25%, 25–50%, and >50%. The association between adherence to 64 either a Western or a Mediterranean dietary pattern and mammographic density was explored 65 using multivariable ordinal logistic regression models with random center-specific intercepts. 66 Models were adjusted for age, body mass index, parity, menopause, smoking, family history, 67 hormonal treatment and calorie and alcohol intake. Differences according to women’s 68 characteristics were tested including interaction terms. 69 Results: Women with a higher adherence to the Western dietary pattern were more likely to 70 have high mammographic density (n(%)=242(27%)) than women with low adherence 71 (n(%)=169 (19%)) with a fully adjusted odds ratio (aOR Q4vsQ1) of 1.25(95%Confidence Interval 72 (CI)=1.03;1.52)). This association was confined to overweight/obese women 73 (aORQ4vsQ1(95%CI)= 1.41(1.13;1.76)). No association between Mediterranean dietary pattern 74 and mammographic density was observed. 75 Conclusion: 76 6 The Western dietary pattern was associated with increased mammographic density among 77 overweight/obese women. Our results might inform specific dietary recommendations for 78 women with high mammographic density. 79 7 Introduction 80 Breast cancer is the most common malignant tumor among women worldwide and one 81 of the main causes of female mortality in medium and high income countries (1). Early 82 detection and therapeutic advances have improved breast cancer prognosis, but the number of 83 new cases keeps increasing (2) emphasizing the need to prioritize prevention as an 84 indispensable tool to reduce the burden of disease. 85 High mammographic density is an important risk factor for breast cancer (3). Some 86 results indicate a possible mediating effect of mammographic density in breast cancer risk (4), 87 and this phenotype is currently being used to improve the discrimination of classical predictive 88 models (5). Therefore, it is reasonable to presume that some of the factors associated to breast 89 cancer onset might exert their effect by modifying mammographic density. 90 We have recently identified two dietary patterns associated with breast cancer risk: a 91 Western dietary pattern associated to increased risk (Odds Ratio (OR)high-vs-low-adherence 92 (95%Confidence Interval (CI))=1.46(1.06;2.01)) and a protective Mediterranean pattern 93 (ORhigh-vs-low-adherence(95%CI)=0.56(0.40;0.79)) (6). The identification of dietary habits 94 associated with mammographic density may inform the design of dietary recommendations for 95 women attending screening who have high mammographic density and, therefore, at higher risk 96 for breast cancer (3). Unfortunately, since a few studies have explored the association between 97 dietary patterns and mammographic density, current evidence remains inconclusive (7, 8). The 98 objective of this study is to explore the association between adherence to the Western and 99 Mediterranean dietary patterns and mammographic density. 100 8 Materials and Methods 101 In this cross-sectional study (“Determinants of Mammographic Density in Spain”) we recruited 102 women aged 45-69 attending breast cancer screening in one of the 7 centers from the 103 population-based public Spanish Breast Cancer Screening network. Women with a previous 104 cancer diagnosis (except non-melanoma skin cancers), attendees unable to respond to the 105 questionnaire or women with a physical limitation preventing the performance of the 106 mammogram were excluded. Among those eligible, women were randomly selected on a daily 107 basis from the list of attendees scheduled for that particular day, taking into account the number 108 of interviews that could be scheduled for the day. These women were invited to participate and, 109 if they accepted, their appointment was re-scheduled to allow enough time for the interview 110 before the mammogram. With an average participation rate of 74.5% (ranged 64.7–84.0% 111 across centers) and a pre-set minimum sample size of 500 women for each of the 7 sites, the 112 recruitment period lasted from October 7th, 2007 through July 14th, 2008, during which, a total 113 of 3,584 women were recruited. 114 The company Demometrica (http://www.demometrica.com/) provided trained 115 interviewers (one per center) to collect anthropometric, demographic, occupational, physical 116 activity, obstetric and gynecologic data, as well as family and personal history (including 117 weight and height at age 18). Data were entered in a data file in Demometrica headquarters. An 118 internal validation was performed using a random sample of 10% of the questionnaires. In 119 addition, all questionnaires were digitalized to make them easily accessible to researchers for 120 checking for possible inconsistences and unusual values. One hundred and fifty women were 121 re-interviewed to verify their answers. This second interview took place between 2 and 9 122 months after the first one and results from both interviews were highly concordant. 123 9 Smoking status was defined as “current smoker” for those women who smoke at the 124 time of mammography or quit less than 6 months before; and as “nonsmoker” otherwise. 125 Dietary intake during the preceding year was collected using a 117-items food frequency 126 questionnaire (Appendix 2) similar to Willett questionnaire (9) and suitably adapted to and 127 validated in Spanish adult populations (10, 11). Post-menopausal status was defined as self-128 reported absence of menstruation in the last 12 months. Weight, height, waist and hip 129 circumferences were measured twice using the same protocol and identical balance scales, 130 stadiometers and measuring tapes. A third measure was taken when the first two were not 131 similar. 132 Mammographic density was blindly assessed by a single radiologist, unaware of the 133 survey data. He read the craniocaudal mammogram of the left breast using a visual 134 semiquantitative score with six categories proposed by Boyd (12) based on percentage of dense 135 tissue in the breast, i.e., categories A (0%), B (0-10%), C (10–25%), D (25–50%), E (50–75%) 136 and F (>75%). This scale has been associated with subsequent development of sporadic and 137 familial breast cancer (3, 13) . Given the small percentage of women in categories A (4%) and 138 F (5%), the two lowest and two highest categories were grouped together, creating the definitive 139 outcome variable categorized as: <10%, 10–25%, 25–50%, and >50%. 140 141 Here we examined two dietary patterns identified in a previous case-control study (6) as being 142 associated with breast cancer risk: a) Western dietary pattern, characterized by a high intake of 143 high-fat dairy products, processed meat, refined grains, sweets, caloric drinks, convenience 144 food and sauces and by low intakes of low-fat dairy products and whole grain, was associated 145 with increased risk of breast cancer; and b) the Mediterranean dietary pattern characterized by 146 high intake of fish, vegetables, legumes, boiled potatoes, fruits, olives and vegetable oil, and a 147 10 low intake of juices, was associated with a reduced risk of breast cancer . These two dietary 148 patterns were identified applying principal components analysis without rotation of the 149 variance-covariance matrix over 26 inter-correlated food groups (14). This method reports a set 150 of weights (pattern loadings) associated with each food group that represents the correlation 151 between food consumption and the component/pattern scores that can be used to reproduce such 152 patterns in other samples as explained in detail in Castelló et al.(15). Briefly, we grouped 95 of 153 the 117 items of the food frequency questionnaire (excluding non-caloric and alcoholic 154 beverages) into 26 food groups (Table 1), and calculated the level of adherence scores for the 155 Western and Mediterranean dietary patterns as a linear combination of the weights for each 156 food group and pattern published in Castelló et al. (6) and the food group consumption reported 157 the participants in the current study 158 159 Regarding the statistical analysis, first, we calculated basic descriptive statistics of the 160 anthropometric, sociodemographic and lifestyle characteristics for all women, and by 161 categories of mammographic density. Normally distributed continuous variables were 162 described using the mean±standard deviation. Differences across categories of mammographic 163 density were tested with ANOVA tests. Non-normally distributed continuous variables were 164 described using the median (interquartile interval) and differences by mammographic density 165 were tested with non-parametric Kruskal-Wallis tests. Categorical variables were described 166 using the number of cases and corresponding percentages, and differences by mammographic 167 density were tested with chi-square tests. 168 Associations between adherence to either dietary pattern and mammographic density 169 were evaluated using ordinal logistic regression models with random center-specific intercepts 170 including center as a random effect. As fixed-effects terms, age, body mass index (BMI), parity, 171 menopausal and smoking status, family history of breast cancer, use of hormonal replacement 172 11 therapy and calorie and alcohol intake were considered as potential confounders. Three mixed 173 models were adjusted in order to explore the confounding effect of different sets of variables. 174 Model 1 was only adjusted by age and BMI (additionally to the random effects term); Model 2 175 also included parity, menopausal and smoking status, family history of breast cancer, and use 176 of hormonal replacement therapy. Finally, calorie and alcohol intake were added to Model 3. 177 Both, categorical (grouping the scores of adherence into quartiles) and continuous (1-standard 178 deviation increase) associations with the scores were examined with all three models. For 179 Model 3, nonlinear associations between the adherence to each pattern and mammographic 180 density were assessed by fitting fractional polynomials. 181 With regards to the sample size, 22.8% of women had a mammographic density of over 182 50%. Therefore, our data allowed us to detect differences of 8% or more in the percentage of 183 women classified in this category between extreme quartiles of adherence to each dietary 184 pattern with a power of 80%. 185 Finally, when significant associations were found, separate analyses were performed by 186 categories of all potential confounders above mentioned and represented in forest plots . 187 Heterogeneity of effects was tested in model 3 by including an interaction term between the 188 score of adherence and the corresponding variable. 189 Analyses were performed using STATA/MP (version 14.0, 2015, StataCorp LP) and statistical 190 significance was set at 2-sided p <0.05. 191 The protocol study “Determinants of Mammographic Density in Spain” was formally 192 approved by the bioethics and animal welfare committee at the Carlos III Institute of Health 193 and all participants signed an informed consent, including permission to publish the results from 194 the research. 195 12 196 RESULTS 197 Thirty-six participants were excluded from analyses: 10 women who developed breast cancer 198 within 6 months of study entry and mammography, 16 did not have mammographic density 199 assessment, 2 did not have BMI information, and 8 participants reported a daily kcal intake 200 under 750 Kcal or above 4500 Kcal. Therefore, analyses included data from 3548 women for 201 whom we had complete information regarding all the variables of interest. As expected, 202 pre/perimenopausal women showed a higher percentage of dense tissue (higher 203 mammographic density). An elevated mammographic density was also associated with family 204 history of breast cancer, tobacco use, high calorie and alcohol intake, younger age and lower 205 BMI and parity (Table 2). 206 Crude associations summarized in Table 2 showed that, compared to women in the lowest 207 quartile of adherence to the Western dietary pattern, a higher proportion of those in the highest 208 quartile had a mammographic density of over 50% (19% (n=169) vs. 27% (n=242), 209 respectively). This association was not observed for the Mediterranean dietary pattern, 21% 210 (n=187) of women in the lowest quartile of adherence and 24% (n=211) of those in the highest 211 quartile of adherence had mammographic density of over 50%. 212 Multivariable analyses supported these findings confirming that, while breast density did not 213 differ by level of adherence to the Mediterranean dietary pattern (aORQ4vsQ1(95%CI)= 214 0.99(0.81-1.21) and aOR1-standard deviation increase (95%CI)= 1.02(0.95-1.09)), those with a high 215 adherence to the Western dietary pattern had higher mammographic density 216 (aORQ4vsQ1(95%CI)= 1.25(1.03;1.52) and aOR1-standard deviationincrease (95%CI)= 1.09(1.02;1.18)) 217 (Table 3). No statistically significant departure from linearity was observed in this association 218 when the analysis with fractional polynomials was performed (data not shown). 219 13 Stratified analysis by subgroups revealed that, the effect of the Western dietary pattern 220 on mammographic density was confined to women with a BMI over 25 (aORQ4vsQ1(95%CI)= 221 1.41(1.13;1.76), heterogeneity p-value=0.068). Our results also suggested some differences 222 according to parity, calorie intake and tobacco consumption, but none of the interaction terms 223 reached statistical significance (Figure 1). 224 225 DISCUSSION 226 Our results suggest that, whereas the Mediterranean diet was not related to 227 mammographic density, a higher adherence to the Western dietary pattern was associated with 228 higher mammographic density. Subgroup analyses suggest that this effect may be confined to 229 overweight/obese women, and to be stronger among parous, non-smokers, and women with 230 elevated calorie intake. However, our tests for heterogeneity approached significance at best, 231 probably for lack of power. Thus, larger studies are needed to confirm these potential 232 differential effects of diet on mammographic density. 233 Taking into account that high mammographic density is considered one of the key risk 234 factors for breast cancer (3) , we expected to identify associations between dietary patterns and 235 mammographic density similar in direction to those found for dietary patterns and breast cancer 236 by Castelló et al. (6). However, while we found a positive association for the Western dietary 237 pattern, mammographic density was not influenced by adherence to the Mediterranean dietary 238 pattern. 239 Our findings support previous studies exploring the association between 240 mammographic density and specific nutrients or foods included in the Western dietary pattern 241 that reported positive associations with total energy, (16) high density foods (17), total, 242 14 saturated, and cholesterol fats (18, 19), proteins (18) and meat (20). Not surprisingly, a Western-243 type diet contrasts with the recommendations issued by the World Cancer Research Fund and 244 the American Association for Cancer Research to reduce cancer burden. Adherence to these 245 recommendations has been positively associated with a reduction of breast cancer risk (21) and 246 mammographic density (17) in our context. 247 On the other hand, a weak inverse association with the Mediterranean dietary pattern 248 (8) or with some of its main components such as olive oil (16),vegetables and fiber (22)has 249 been previously reported. Others have found an absence or even a positive association of some 250 of these items with mammographic density (19, 23, 24). . These inconclusive findings suggest 251 that a reduction in mammographic density may not be one of the key mechanisms through 252 which the Mediterranean diet lowers breast cancer risk. A possible explanation for the 253 contradictory effect of a Mediterranean diet on mammographic density and breast cancer, is 254 that this diet could be influencing the fat deposit of the breast without altering the percentage 255 of dense tissue. Obesity, a condition inversely associated with mammographic density, 256 increases breast cancer risk via several mechanisms, including the inflammatory effect of 257 adipokines (25), while the Mediterranean diet seems to counteract an inflammatory state (26). 258 It is worth mentioning that the effect of the Western dietary pattern on mammographic 259 density was only observed among overweight/obese women. Adipocytes are potent endocrine 260 cells that produce hormones and growth factors; obesity strongly influences this endocrine 261 millieu (27). Our results may reflect a synergic effect of this dietary pattern and the local adipose 262 tissue on the fibro glandular component of the breast. 263 For its kind, this is a fairly large and carefully-conducted study on risk factors and 264 mammographic density; however, it presents some limitations. First, the sample size was 265 insufficient to detect significant interactions even when some differences by subgroups are 266 15 observed. Second, the representativeness of the selected sample might be slightly biased since 267 healthy screening participants might be more concerned about their health than non-268 participants. However, participation rates in Spanish breast cancer screening programs are high 269 (28) and women in our study are very similar to the women in the Spanish National Health 270 Survey in terms of age range, socioeconomic level, prevalence of smoking and physical activity 271 (29). Third, the visual assessment of breast density by a single radiologist, may imply a degree 272 of subjectivity. However, the radiologist had very high intra-observer concordance (30), and 273 we have confirmed that the visual scale used here is a predictor of subsequent breast cancer 274 development risk (3). Additionally, the collection of data with different mammographic devices 275 and interviewers in different centers might introduce some heterogeneity. 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BMC cancer. 2010;10:485. 380 381 382 18 TABLES 383 Table 1: Composition of food groups based on the food frequency questionnaire of the 384 “Determinants of Mammographic Density in Spain” study 385 FOOD GROUP FOODa HIGH-FAT DAIRY Whole-fat milk, w1b·A+D enriched milk, w1b·Folate enriched milk, double cream, condensed milk, whole-fat yogurt, semi-cured, cured or creamy cheese, custard, flan, pudding, ice-cream LOW FAT DAIRY Semi-skimmed and skimmed milk, Omega3 enriched milkc, w2b·A+D enriched milk, w2b·Folate enriched milk, soy milk, soy yogurt, skimmed yogurt, cottage or fresh white cheese EGGS Eggs WHITE MEAT Chicken with skin, skinless chicken, game (turkey, rabbit, etc.) RED MEAT Pork, beef, lamb, liver (beef, pork or chicken), entrails, hamburger PROCESSED MEAT Serrano ham and other cold meat, sausages, bacon, pâte, foie-gras WHITE FISH 1/3·all kind of fried fish, Fresh white fish (hake, sea bass, sea bream) OILY FISH 1/3·all kind of fried fish, Fresh blue fish (Tuna, swordfish, sardines, anchovies, salmon), canned tuna, canned sardines or mackerel, salted and smoked fish SEAFOOD/SHELLFISH 1/3·all kind of fried fish, Clams, mussels, oysters, squid, cuttlefish, octopus, prawn, crab, shrimp, lobster LEAFY VEGETABLES Spinach, chard, lettuce, endive, escarole FRUITING VEGETABLES Tomato, eggplant, zucchini, cucumber, pepper, artichoke ROOT VEGETABLES Carrot, pumpkin OTHER VEGETABLES Cooked cabbage, cauliflower or broccoli, onion, green beans, asparagus, mushrooms, corn, garlic, vegetable soup LEGUMES Legumes, soy sprouts POTATOES Roasted or boiled potatoes FRUITS Orange, mandarin, banana, apple, pear, peach, nectarine, apricot, watermelon, melon, grapes, plums or prunes (dried or fresh), strawberries, kiwi NUTS Almonds, peanuts, pine nuts, hazelnut REFINED GRAINS White-flour bread, rice, pasta WHOLE GRAINS Whole-grain bread and partial whole-grain bread, breakfast cereals, wheat germs OLIVES AND VEGETABLE OIL Olives, added olive oil to salads, bread and dishes, other vegetable oils (sunflower, corn, soybean) OTHER EDIBLE FATS Margarine, butter SWEETS Chocolate and other sweets, cocoa powder, plain cookies, chocolate cookies, pastries (croissant, donut, cake, pie or similar) SUGARY Jam, Honey, Sugar JUICES Tomato Juice, freshly squeezed orange juice, juice (other than freshly squeezed) CALORIC DRINKS Sugar-sweetened soft drinks CONVENIENCE FOOD Fried potatoes, crisps, pizza, chicken and Serrano ham croquette, mayonnaise, tomato sauce, ketchup, fish sticks AND SAUCES aLog-transformed centered intake in grams. 386 bWeighted within the high and low fat dairy categories according to the consumption of whole, semi-skimmed and skimmed 387 milk. 388 w1 = whole /(whole + semi- skimmed + skimmed) 389 w2 = (semi-skimmed + skimmed) /(whole + semi skimmed + skimmed) 390 w1 and w2 where 0.5 if consumption was 0 grams for whole, semi-skimmed and skimmed milk. 391 cAll the Omega3 enriched milk brands that have been examined are skimmed or semi-skimmed 392 19 Table 2: Description of anthropometric, sociodemographic and lifestyle characteristics for all women and by mammographic density classification (Boyd 393 scale)(12). 394 MAMMOGRAPHIC DENSITY CHARACTERISTICS ALL WOMEN <10% 10-25% 25-50% >50% pa n=3548 n=870 n=733 n=1136 n=809 Age (years) Mean±standard deviation 56.20±5.46 58.28±4.89 57.04±5.03 55.87±5.45 53.66±5.34 <0.001 BMI (Kg/m2) Mean±standard deviation 28.03±4.99 30.77±5.47 28.79±4.80 27.37±4.25 25.33±3.81 <0.001 Parity n(%) <0.001 Nulliparous 318 (9%)b 48 (15%)c 47 (15%)c 110 (35%)c 113 (35%)c 1 541 (15%)b 95 (18%)c 90 (17%)c 181 (33%)c 175 (32%)c 2 1703 (48%)b 408 (24%)c 350 (21%)c 567 (33%)c 378 (22%)c ≥3 986 (28%)b 319 (32%)c 246 (25%)c 278 (28%)c 143 (15%)c Menopausal Status n(%) <0.001 Pre/Perimenopausal 816 (23%)b 107 (13%)c 108 (13%)c 268 (33%)c 333 (41%)c Postmenopausal 2732 (77%)b 763 (28%)c 625 (23%)c 868 (32%)c 476 (17%)c Smoking n(%) <0.001 Never or former ≥6 months 2179 (61%)b 599 (28%)c 460 (21%)c 701 (32%)c 419 (19%)c Smoker or former <6 months 1369 (39%)b 271 (20%)c 273 (20%)c 435 (32%)c 390 (28%)c Family History of Breast Cancer n(%) 0.005 No 3289 (93%)b 815 (25%)c 696 (21%)c 1045 (32%)c 733 (22%)c Yes 259 (7%)b 55 (21%)c 37 (14%)c 91 (35%)c 76 (30%)c Use of Hormonal Replacement Therapy n(%) 0.117 No 3200 (90%)b 768 (24%)c 664 (21%)c 1026 (32%)c 742 (23%)c Yes 348 (10%)b 102 (29%)c 69 (20%)c 110 (32%)c 67 (19%)c 20 Calorie Intake (kcal) Mean±standard deviation 2054±481 1989±471 2023±476 2076±472 2122±498 <0.001 Alcohol Intake (Ethanol in grs) Median(IQR) 0.85 (0.00- 5.68) 0.04 (0.00- 3.19) 0.89 (0.00- 5.68) 0.85 (0.00- 5.83) 1.20 (0.00- 7.05) <0.001 Quartiles(Q) of adherence to the Western dietary Pattern n(%) <0.001 Q1 888(25%)b 285(32%)c 183(21%)c 251(28%)c 169(19%)c Q2 886(25%)b 218(25%)c 181(20%)c 302(34%)c 185(21%)c Q3 887(25%)b 205(23%)c 193(22%)c 276(31%)c 213(24%)c Q4 887(25%)b 162(18%)c 176(20%)c 307(35%)c 242(27%)c Quartiles(Q) of adherence to the Mediterranean dietary Pattern n(%) 0.725 Q1 887(25%)b 223(25%)c 200(23%)c 277(31%)c 187(21%)c Q2 887(25%)b 221(25%)c 180(20%)c 289(33%)c 197(22%)c Q3 886(25%)b 221(25%)c 173(20%)c 278(31%)c 214(24%)c Q4 888(25%)b 205(23%)c 180(20%)c 292(33%)c 211(24%)c a p-value for differences among mammographic density categories resulting from ANOVA test when comparing means, from Kruskal-Wallis test when comparing Medians and from 395 Chi-Square tests when comparing percentages. 396 b Column percentages 397 c Row percentages398 21 Table 3: Adjusted Logistic regression analyses of adherence to Western or Mediterranean dietary 399 patterns on mammographic density--All women. 400 DIETARY PATTERNS MODEL 1a OR (95%CI) b MODEL 2a aOR (95%CI) c MODEL 3a aOR (95%CI) d WESTERN QUARTILES (Q)e Q1 1 1 1 Q2 1.11 (0.93-1.32) 1.09 (0.92-1.3) 1.06 (0.89-1.27) Q3 1.13 (0.95-1.35) 1.11 (0.93-1.32) 1.05 (0.87-1.26) Q4 1.34 (1.12-1.59) 1.35 (1.13-1.61) 1.25 (1.03-1.52) p-trendf 0.002 0.001 0.039 Per 1-standard deviation increaseg 1.11 (1.05-1.19) 1.12 (1.05-1.20) 1.09 (1.02-1.18) MEDITERRANEAN QUARTILES (Q)e Q1 1 1 1 Q2 1.07 (0.90-1.27) 1.06 (0.89-1.26) 1.01 (0.85-1.20) Q3 1.06 (0.89-1.27) 1.05 (0.88-1.25) 0.97 (0.80-1.16) Q4 1.12 (0.94-1.34) 1.12 (0.94-1.34) 0.99 (0.81-1.21) p-trendf 0.234 0.228 0.811 Per 1-standard deviation increaseg 1.06 (0.99-1.13) 1.06 (1.00-1.13) 1.02 (0.95-1.09) a All models included center as a random effect. 401 b Odds Ratio and 95% confidence interval adjusted by age and BMI. 402 c Odds Ratio and 95% confidence interval adjusted by age, BMI, parity, menopausal and smoking status, family history 403 of BC and use of HRT. 404 d Odds Ratio and 95% confidence interval adjusted by age, BMI, parity, menopausal and smoking status, family history 405 of BC, use of HRT, and calorie and alcohol intake. 406 e Odds Ratio and 95% confidence interval for quartiles of adherence. 407 f p value for trend resulting from the Wald test associated to the categorical variable include as continuous in the regression 408 models. 409 g Odds Ratio and 95% confidence intervals per 1-standard deviation increase in the score of adherence to the specified 410 dietary pattern. 411 412 413 Adela Castelló 22 Figure 1: Adjusted Odds Ratios (aOR) and 95% Confidence Intervals (95%CI) for the risk of high 414 mammographic density in women in the fourth quartile of adherence to the Western dietary pattern 415 according to women characteristics. 416 417 a All interaction models were adjusted by all the variables included in the figure and included center as a random effect. 418 419 Supplemental digital content I: Appendix 1: Researchers involved in the study 420 “Determinants of Mammographic Density in Spain” (Determinantes de la Densidad 421 Mamográfica en España). 422 Marina Pollán (IP), Adela Castelló, Nieves Ascunce, Dolores Salas-Trejo, Carmen Vidal, Carmen 423 Sanchez-Contador, Carmen Santamariña, Carmen Pedraz-Pingarrón, Maria Pilar Moreno, Beatriz 424 Pérez-Gómez, Virginia Lope, Nuria Aragonés, Jesús Vioque, Pilar Moreo, Mª Soledad Abad, 425 Francisca Collado, Francisco Casanova, Jose Antonio Vázquez, Milagros García, Manuela 426 Alcaraz, Mª Soledad Laso, Josefa Miranda, Francisco Ruiz Perales and Maria Ederra. 427 428 Supplemental digital content II: English translation of the food frequency questionnaire used to collect dietary information from the study “Determinants of Mammographic Density in Spain” (Determinantes de la Densidad Mamográfica en España). FOOD FRECUENCY QUESTIONNAIRE OF DDM-SPAIN Dear Madame, the aim of this part of the questionnaire is to assess your diet in the past year. Your answers will be very useful and that is why we demand you all your attention and collaboration. When a type of food does not match complete your consumption pattern you can try to answer approximately with the indicated quantities. We will help you with examples and instructions. For each type of food, please average your use of these foods in the past year. You must take into account when food is to consume alone or when it is to add to other foods. For example, if you prepare eggs consider when you eat them alone (E.g. fried or boiled) and when you add them to another food. If you have eaten a 2-eggs omelet every two days you will answer "1 daily". Do not take into account the eggs used to prepare baked goods or sweets. Do not forget to fill up every line I. DAIRY PRODUCTS Never ó <1 month 1-3 per mo 1 per week 2-4 per week 5-6 per week 1 per day 2-3 per day 4-5 per day 6+ per day Milk (One glass, 200 cc) Whole 1 2 3 4 5 6 7 8 9 Semi-skimmed 1 2 3 4 5 6 7 8 9 Skimmed or low fat 1 2 3 4 5 6 7 8 9 Other milk: with Soy 1 2 3 4 5 6 7 8 9 with Omega-3 1 2 3 4 5 6 7 8 9 with Calcium and vitamins A+D 1 2 3 4 5 6 7 8 9 with Folate 1 2 3 4 5 6 7 8 9 Condensed milk (1 table spoon) 1 2 3 4 5 6 7 8 9 Full cream, e.g. added coffee, whipped (1 table spoon) 1 2 3 4 5 6 7 8 9 Full fat or Greek yogurt (125 g carton) 1 2 3 4 5 6 7 8 9 Low fat yogurt (125 g carton) 1 2 3 4 5 6 7 8 9 Soy yogurt (125 g carton) 1 2 3 4 5 6 7 8 9 Cottage cheese, low fat soft cheese (medium serving, 100 g) 1 2 3 4 5 6 7 8 9 Cheese e.g. Cheddar, Brie, Edam (medium serving, 50 g) 1 2 3 4 5 6 7 8 9 Custard, cream caramel, pudding (one) 1 2 3 4 5 6 7 8 9 Ice cream (1 cup or cornet) 1 2 3 4 5 6 7 8 9 II. EGGS, MEAT, FISH Never ó <1 month 1-3 per mo 1 per week 2-4 per week 5-6 per week 1 per day 2-3 per day 4-5 per day 6+ per day Poultry eggs (one) 1 2 3 4 5 6 7 8 9 Chicken WITH skin (one medium size serving, 90 g) 1 2 3 4 5 6 7 8 9 Chicken WITHOUT skin (one medium size serving, 90 g) 1 2 3 4 5 6 7 8 9 Meat as main dish: roast, steak, mince, stew or casserole (one medium size serving, 125g) Beef 1 2 3 4 5 6 7 8 9 Pork 1 2 3 4 5 6 7 8 9 Lamb 1 2 3 4 5 6 7 8 9 Game: rabbit, quail, duck (one medium size serving, 100g) 1 2 3 4 5 6 7 8 9 Hamburger (one medium, 100 g) 1 2 3 4 5 6 7 8 9 Liver beef, pork, chicken (one medium serving, 100g) 1 2 3 4 5 6 7 8 9 Trips, brains, sweetbreads (one serving, 100 g) 1 2 3 4 5 6 7 8 9 Serrano or cocked ham (one serving, 50 g) 1 2 3 4 5 6 7 8 9 Other Cold meat: salami type sausage, salami, bologna (one serving, 50 g) 1 2 3 4 5 6 7 8 9 Sausages and similar (one, 50 g) 1 2 3 4 5 6 7 8 9 Pâté, liver pâté (medium serving, 50 g) 1 2 3 4 5 6 7 8 9 Pork fat (lard), bacon (2 slides, 50 g) 1 2 3 4 5 6 7 8 9 Fish fried and mixed (1 medium serving, 100 g) 1 2 3 4 5 6 7 8 9 White fish fried or grilled fish: haddock, sole, gilthead (1 serving, 100 g) 1 2 3 4 5 6 7 8 9 Blue fish boiled or grilled: tuna fish, swordfish, bonito (1 serving, 100 g) 1 2 3 4 5 6 7 8 9 Other dark meat fish: mackerel, sardines, anchovy, salmon (1 serving, 100 g) 1 2 3 4 5 6 7 8 9 Canned tuna fish in oil (small can) 1 2 3 4 5 6 7 8 9 Canned sardines or mackerel in oil (small can) 1 2 3 4 5 6 7 8 9 Salted fish and/or smoked fish: anchovy, cod, salmon (small serving, 50g) 1 2 3 4 5 6 7 8 9 Clams, mussels, oysters (one serving, 100 g) 1 2 3 4 5 6 7 8 9 Squid, sepia, octopus (one serving, 100 g) 1 2 3 4 5 6 7 8 9 Shellfish: prawns, crabs, lobster (one serving 100 g) 1 2 3 4 5 6 7 8 9 III. VEGETABLES AND LEGUMES Never ó <1 month 1-3 per mo 1 per week 2-4 per week 5-6 per week 1 per day 2-3 per day 4-5 per day 6+ per day Spinach or beet, cooked (1 medium serving, 100 g) 1 2 3 4 5 6 7 8 9 Cabbage, cauliflower, broccoli, cooked (1 medium serving, 100 g) 1 2 3 4 5 6 7 8 9 Lettuce, green salad (1 medium serving, 60 g) 1 2 3 4 5 6 7 8 9 Onions (1 medium size, 50 g) 1 2 3 4 5 6 7 8 9 Tomatoes (1 medium size, 100 g) 1 2 3 4 5 6 7 8 9 Tomato juice (one glass, 200cc) 1 2 3 4 5 6 7 8 9 Tomato sauce (half a cup, 100 cc) 1 2 3 4 5 6 7 8 9 Carrot, pumpkin (1 or small dish, 50 g) 1 2 3 4 5 6 7 8 9 French been, cooked (1 serving, 100 g) 1 2 3 4 5 6 7 8 9 Aubergine, marrow, cucumber (one, 100 g) 1 2 3 4 5 6 7 8 9 Peppers (one, 75 g) 1 2 3 4 5 6 7 8 9 Artichokes (1 serving, 100 g) 1 2 3 4 5 6 7 8 9 Asparagus (1 serving, 75 g) 1 2 3 4 5 6 7 8 9 Mushrooms (1 serving, 100 g) 1 2 3 4 5 6 7 8 9 Sweet corn (1 serving or small can, 82 g) 1 2 3 4 5 6 7 8 9 Soya sprouts (a handful, 30g) 1 2 3 4 5 6 7 8 9 Wheat germ (a handful, 10g) 1 2 3 4 5 6 7 8 9 Legumes: lentils, chickpeas, dark or white beans (1 medium dish, 140 g) 1 2 3 4 5 6 7 8 9 IV. FRUITS Never ó <1 month 1-3 per mo 1 per week 2-4 per week 5-6 per week 1 per day 2-3 per day 4-5 per day 6+ per day Oranges, mandarins (one) 1 2 3 4 5 6 7 8 9 Orange juice, fresh fruit (small glass, 125 cc) 1 2 3 4 5 6 7 8 9 Bananas (one) 1 2 3 4 5 6 7 8 9 Apple, pears (one medium size) 1 2 3 4 5 6 7 8 9 Peaches, apricots (one medium size) 1 2 3 4 5 6 7 8 9 Watermelon, melon (1 slice medium) 1 2 3 4 5 6 7 8 9 Grapes (medium bunch of grapes or dessert dish) 1 2 3 4 5 6 7 8 9 Prunes, plum, dried or fresh (one) 1 2 3 4 5 6 7 8 9 Strawberries (7-8 units) 1 2 3 4 5 6 7 8 9 Kiwi (one) 1 2 3 4 5 6 7 8 9 Olives (15 small olives) 1 2 3 4 5 6 7 8 9 Dried fruit: almonds, peanuts, pinions, hazelnut (1 small dish or small packet, 30g) 1 2 3 4 5 6 7 8 9 V. BREAD, CEREALS AND SIMILAR Never ó <1 month 1-3 per mo 1 per week 2-4 per week 5-6 per week 1 per day 2-3 per day 4-5 per day 6+ per day White bread (small piece or 3 slides, 60 g) 1 2 3 4 5 6 7 8 9 Brown or whole bread (small piece or 3 slides, 60 g) 1 2 3 4 5 6 7 8 9 Breakfast cereals (30 g dried, 1 cup) 1 2 3 4 5 6 7 8 9 Chips (fried potatoes in oil) (1 serving, 100 g) 1 2 3 4 5 6 7 8 9 Potatoes: boiled, grilled (1 medium) 1 2 3 4 5 6 7 8 9 Chips (1 small bag, 25-30 g) 1 2 3 4 5 6 7 8 9 Rice cooked (1 medium dish) 1 2 3 4 5 6 7 8 9 Pasta: spaghetti, noodles, macaroni and similar (1 dish) 1 2 3 4 5 6 7 8 9 Pizza (1 portion, 200 g) 1 2 3 4 5 6 7 8 9 VI. OILS, FAT AND SWEETS Never ó <1 month 1-3 per mo 1 per week 2-4 per week 5-6 per week 1 per day 2-3 per day 4-5 per day 6+ per day Olive oil added to salads, bread or food (1 table spoon) 1 2 3 4 5 6 7 8 9 Other vegetables oils (idem): girasol, corn, soy (1 1 table spoon) 1 2 3 4 5 6 7 8 9 Margarine added to bread or food (1 1 table spoon or spread on bread) 1 2 3 4 5 6 7 8 9 Butter added to bread or meals (spread butter on bread) 1 2 3 4 5 6 7 8 9 Biscuits (one) 1 2 3 4 5 6 7 8 9 Chocolate cookies (1 double cookie) 1 2 3 4 5 6 7 8 9 Baked goods: croissant, donut, small sponge cake, brownies, cake or similar (one) 1 2 3 4 5 6 7 8 9 Chocolate and similar (1 piece or candy bar or 2 chocolates) 1 2 3 4 5 6 7 8 9 Drinking chocolate, cocoa and similar (1 tbs of powder) 1 2 3 4 5 6 7 8 9 VII. DRINKS AND OTHERS Never ó <1 month 1-3 per mo 1 per week 2-4 per week 5-6 per week 1 per day 2-3 per day 4-5 per day 6+ per day Red wine (1 glass, 125 cc) 1 2 3 4 5 6 7 8 9 White, rose or sparkling wine and champagne (1 glass, 125 cc) 1 2 3 4 5 6 7 8 9 Sherry, dry wine, vermouth (small glass, 50 cc) 1 2 3 4 5 6 7 8 9 Cider (1 glass, 125 cc) 1 2 3 4 5 6 7 8 9 Beer (1 glass or small bottle, 200 cc) 1 2 3 4 5 6 7 8 9 No-alcohol beer (1 glass or small bottle, 200 cc) 1 2 3 4 5 6 7 8 9 Fruit and cream spirits (20-25º) (small glass, 50 cc) 1 2 3 4 5 6 7 8 9 Brandy, gin, rum, whiskey, vodka 40º (small glass, 50 cc) 1 2 3 4 5 6 7 8 9 Sugar-sweetened soft drinks (one, 250 cc) 1 2 3 4 5 6 7 8 9 Diet soft drinks (one, 250 cc) 1 2 3 4 5 6 7 8 9 Tap water (one glass, 250cc) 1 2 3 4 5 6 7 8 9 Still bottled water (one glass, 250cc) 1 2 3 4 5 6 7 8 9 Sparkly bottled water (one glass, 250cc) 1 2 3 4 5 6 7 8 9 Bottled fruit juice (one glass, 200cc) 1 2 3 4 5 6 7 8 9 Coffee (1 cup) 1 2 3 4 5 6 7 8 9 Decaffeinated coffee (1 cup) 1 2 3 4 5 6 7 8 9 Red, green, blank of green tea (1 cup) 1 2 3 4 5 6 7 8 9 Other teas like chamomile or mint (1 cup) 1 2 3 4 5 6 7 8 9 Vegetable soup and puree (1 serving, 250 g) 1 2 3 4 5 6 7 8 9 Serrano ham or chicken croquettes (one) 1 2 3 4 5 6 7 8 9 Fish fingers (one) 1 2 3 4 5 6 7 8 9 Mayonnaise (1 1 table spoon) 1 2 3 4 5 6 7 8 9 Ketchup (1 1 table spoon) 1 2 3 4 5 6 7 8 9 Added salt (1 pinch) 1 2 3 4 5 6 7 8 9 Garlic (1 clove) 1 2 3 4 5 6 7 8 9 Jam, honey (1 1 table spoon) 1 2 3 4 5 6 7 8 9 Added sugar (1 tea spoon) 1 2 3 4 5 6 7 8 9 Added spices (1 tea spoon) 1 2 3 4 5 6 7 8 9