A proportion of breast cancer cases are attributable to combined modifiable risk factors. The World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) has recently updated the recommendations for cancer prevention and a standard scoring system has been published. The aim of this study was to evaluate the association between compliance with the 2018 WCRF/AICR cancer prevention recommendations (Third Expert Report) and the risk of breast cancer in the SUN (“Seguimiento Universidad de Navarra”) prospective cohort. Spanish female university graduates, initially free of breast cancer, were included (n = 10,930). An 8-item score to measure compliance to the recommendations was built: body fat, physical activity, consumption of wholegrains/vegetables/fruit/beans, “fast foods”, red/processed meat consumption, sugar-sweetened drinks consumption, alcohol intake, and breastfeeding. A stratified analysis was conducted according to menopausal status. A non-significant inverse association was observed for overall breast cancer. The inverse association became statistically significant for post-menopausal breast cancer after multivariable adjustment (hazard ratio for > 5 vs. ≤ 3 points = 0.27; 95% CI: 0.08-0.93). The results suggested that the possible inverse association with breast cancer was attributable to the combined effects of the different nutritional and lifestyle components.

There is growing interest in natural antioxidants and their potential effects on breast cancer (BC). Epidemiological evidence, however, is inconsistent. We prospectively evaluated the association between dietary intake of vitamins A, C, and E, selenium, and zinc and BC among 9983 female participants from the SUN Project, a Mediterranean cohort of university graduates. Participants completed a food frequency questionnaire at baseline, and biennial follow-up information about incident BC diagnosis was collected. Cases were ascertained through revision of medical charts and consultation of the National Death Index. Cox proportional hazards models were used to estimate multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CI). During an average follow-up of 11.3 years, 107 incident BC cases were confirmed. The multivariable HRs (95% CI) for BC comparing extreme tertiles of energy-adjusted dietary intakes were 1.07 (0.64–1.77; P_trend = 0.673) for vitamin A, 1.00 (0.58–1.71; P_trend = 0.846) for vitamin C, 0.92 (0.55–1.54; P_trend = 0.728) for vitamin E, 1.37 (0.85–2.20; P_trend = 0.135) for selenium, and 1.01 (0.61–1.69; P_trend = 0.939) for zinc. Stratified analyses showed an inverse association between vitamin E intake and postmenopausal BC (HR_{T3 vs. T1} = 0.35; 95% CI, 0.14–0.86; P_trend = 0.027). Our results did not suggest significant protective associations between dietary vitamins A, C, and E, selenium, or zinc and BC risk.

Dairy products might influence breast cancer (BC) risk. However, evidence is inconsistent. We sought to examine the association between dairy product consumption—and their subtypes—and incident BC in a Mediterranean cohort. The SUN (“Seguimiento Universidad de Navarra”) Project is a Spanish dynamic ongoing cohort of university graduates. Dairy product consumption was estimated through a previously validated 136-item food frequency questionnaire (FFQ). Incident BC was reported in biennial follow-up questionnaires and confirmed with revision of medical records and consultation of the National Death Index. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated with Cox regression models. Among 123,297 women-years of follow-up (10,930 women, median follow-up 12.1 years), we confirmed 119 incident BC cases. We found a nonlinear association between total dairy product consumption and BC incidence (p_nonlinear = 0.048) and a significant inverse association for women with moderate total dairy product consumption (HR_Q2vs.Q1 = 0.49 (95% CI 0.28–0.84); HR_Q3vs.Q1 = 0.49 (95% CI 0.29–0.84) p_trend = 0.623) and with moderate low-fat dairy product consumption (HR_Q2vs.Q1 = 0.58 (95% CI 0.35–0.97); HR_Q3vs.Q1 = 0.55 (95% CI 0.32–0.92), p_trend = 0.136). In stratified analyses, we found a significant inverse association between intermediate low-fat dairy product consumption and premenopausal BC and between medium total dairy product consumption and postmenopausal BC. Thus, dairy products, especially low-fat dairy products, may be considered within overall prudent dietary patterns.

Background and Aims: People with type 1 diabetes mellitus (T1D) are at increased risk of disordered eating behaviours (DEBs), partly due to aspects of diabetes management. The aim of this study was to estimate the prevalence of DEBs in a group of adults with T1D in Spain and to examine their association with sociodemographic, clinical, and lifestyle‐related factors. Methods: A nationwide cross‐sectional study was conducted as part of the D1ANAS project, involving 451 people aged ≥ 16 years with T1D living in Spain. DEBs were assessed using the validated Spanish version of the Diabetes Eating Problems Survey‐Revised (DEPS‐R), with scores ≥ 20 indicating a positive screening. Sociodemographic, clinical, and lifestyle variables were collected using a self‐administered online questionnaire. Multivariate linear regression analyses were performed to identify factors independently associated with the total DEPS‐R score. Results: The mean DEPS‐R score was 16.8 (SD 12.1), and 31.7% of participants screened positive for DEBs, with higher prevalence in women than men (35.4% vs. 14.8%, p < 0.001) 36.6% of participants reported insulin restriction behaviours, with no significant differences between sexes. In the adjusted models, female sex ( β = 3.23, 95% CI = 0.65−5.82), higher HbA1c percentage ( β = 2.12, 95% CI = 1.32−2.93), and higher zBMI ( β = 3.44, 95% CI = 2.44−4.44) were independently associated with higher DEPS‐R scores, as were poorer perceived health ( β = 5.11, 95% CI = 2.25−7.96), poorer diet quality ( β = 13.42, 95% CI = 7.23−19.61) and poor sleep perception ( β = 3.43, 95% CI = 1.46−5.39). The model explained 29.6% of the variance in DEPS‐R scores. Conclusion: DEBs affect about one‐third of the participants with T1D and are associated with poorer metabolic control, higher BMI, and adverse lifestyle and psychosocial factors, highlighting the need for diabetes‐specific screening and multidisciplinary management.