The beneficial association of the Mediterranean diet (MedDiet) with longevity has been consistently demonstrated, but the associations of MedDiet components have not been accordingly evaluated. We performed an updated meta-analysis of prospective cohort studies published up to 31 December 2017, to quantify the association of adherence to MedDiet, expressed as an index/score (MDS) and of its components with all-cause mortality. We estimated summary relative risks (SRR) and 95 % CI using random effects models. On the basis of thirty studies (225 600 deaths), SRR for the study-specific highest/lowest and per 1sd MDS increment were 0·79 (95 % CI 0·77, 0·81, Ι²=42 %, P-heterogeneity 0·02) and 0·92 (95 % CI 0·90, 0·94, Ι² 56 %, P-heterogeneity <0·01), respectively. Inversely, statistically significant associations were evident in stratified analyses by country, MDS range and publication year, with some evidence for heterogeneity across countries overall (P-heterogeneity 0·011), as well as across European countries (P=0·018). Regarding MDS components, relatively stronger and statistically significant inverse associations were highlighted for moderate/none-excessive alcohol consumption (0·86, 95 % CI 0·77, 0·97) and for above/below-the-median consumptions of fruit (0·88, 95 % CI 0·83, 0·94) and vegetables (0·94, 95 % CI 0·89, 0·98), whereas a positive association was apparent for above/below-the-median intake of meat (1·07, 95 % CI 1·01, 1·13). Our meta-analyses confirm the inverse association of MedDiet with mortality and highlight the dietary components that influence mostly this association. Our results are important for better understanding the role of MedDiet in health and proposing dietary changes to effectively increase adherence to this healthy dietary pattern.

Few published breast cancer (BC) risk prediction models consider the heterogeneity of predictor variables between estrogen-receptor positive (ER+) and negative (ER-) tumors. Using data from two large cohorts, we examined whether modeling this heterogeneity could improve prediction. We built two models, for ER+ (ModelER+) and ER- tumors (ModelER-), respectively, in 281,330 women (51% postmenopausal at recruitment) from the European Prospective Investigation into Cancer and Nutrition cohort. Discrimination (C-statistic) and calibration (the agreement between predicted and observed tumor risks) were assessed both internally and externally in 82,319 postmenopausal women from the Women’s Health Initiative study. We performed decision curve analysis to compare ModelER+ and the Gail model (ModelGail) regarding their applicability in risk assessment for chemoprevention. Parity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for ModelER+ and 0.59 for ModelER-. External validation reduced the C-statistic of ModelER+ (0.59) and ModelGail (0.57). In external evaluation of calibration, ModelER+ outperformed the ModelGail: the former led to a 9% overestimation of the risk of ER+ tumors, while the latter yielded a 22% underestimation of the overall BC risk. Compared with the treat-all strategy, ModelER+ produced equal or higher net benefits irrespective of the benefit-to-harm ratio of chemoprevention, while ModelGail did not produce higher net benefits unless the benefit-to-harm ratio was below 50. The clinical applicability, i.e. the area defined by the net benefit curve and the treat-all and treat-none strategies, was 12.7 × 10− 6 for ModelER+ and 3.0 × 10− 6 for ModelGail. Modeling heterogeneous epidemiological risk factors might yield little improvement in BC risk prediction. Nevertheless, a model specifically predictive of ER+ tumor risk could be more applicable than an omnibus model in risk assessment for chemoprevention.

Background: Adherence to a Mediterranean diet (MD) has been quantified through various indexes that rely on full-length questionnaires, but their app