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Background: Our aims were to evaluate the relationship of habitual legume consumption with blood pressure (BP) control in a large cohort of people with T2D and hypertension, and to investigate whether specific nutritional components of legumes or other foods may contribute to regulate BP levels. Methods: We studied 1897 participants with T2D and hypertension. Dietary habits were assessed through a validated food frequency questionnaire. Sex-specific quartiles of legume consumption were created. Results: Higher legume consumption was associated with a lower intake of energy, carbohydrates, glycaemic load, alcohol, and sodium, and a significantly greater intake of proteins, fat, monounsaturated, polyunsaturated, fibre, potassium, and polyphenols. Significantly lower systolic and diastolic BP values were observed in the highest vs. lowest quartile of legume consumption (132.9 ± 6.7 vs. 137.3 ± 7.0 mmHg, p < 0.001; 78.9 ± 4.1 vs. 81.0 ± 4.2 mmHg, p = 0.002; respectively), as well as the proportion of people meeting the treatment targets (61.3% vs. 37.4% and 71.3% vs. 52.4%, respectively, p < 0.01). This association was independent from other foods whose consumption is associated with the high legume intake. Conclusions: In people with T2D and hypertension, three servings of legumes per week are associated with significantly better BP control. This gives further support to current dietary guidelines in recommending the frequent consumption of legumes, as a “ready-to-use” dietary strategy to achieve optimal BP control.

Background: The recommended protein intake for the elderly is 25–30 g at main meals, with at least 2500–2800 mg of leucine at each meal. There is still little evidence regarding the amount and distribution of protein and leucine intake with meals in the elderly with type 2 diabetes (T2D). In this cross-sectional study, we evaluated protein and leucine intake at each meal in elderly patients with T2D. Methods: A total of 138 patients (91 men and 47 women) with T2D, aged 65 years or older, were included. Participants performed three 24-h dietary recalls for the evaluation of their dietary habits and protein and leucine intake at meals. Results: The average protein intake was 0.9 ± 0.2 g/kg body weight/day, and only 23% of patients complied with the recommendations. The average protein intake was 6.9 g at breakfast, 29 g at lunch, and 21 g at dinner. None of the patients reached the recommended protein intake at breakfast; 59% of patients complied with the recommendations at lunch; and 32% at dinner. The average leucine intake was 579 mg at breakfast, 2195 g at lunch, and 1583 mg at dinner. The recommended leucine intake was not reached by any patient at breakfast, by 29% of patients at lunch, and by 13% at dinner. Conclusions: Our data show that, in elderly patients with T2D, the average protein intake is low, particularly at breakfast and dinner, and that leucine intake is remarkably lower than the recommended levels. These data raise the need to implement nutritional strategies capable of increasing protein and leucine intake in the elderly with T2D.

The study compares the performance of the European Society of Cardiology (ESC) risk criteria and the Steno Type 1 Risk Engine (ST1RE) in the prediction of cardiovascular (CV) events.456 adults with type 1 diabetes (T1D) were retrospectively studied. During 8.5 ± 5.5 years of observation, twenty-four patients (5.2%) experienced a CV event. The predictive performance of the two risk models was evaluated by classical metrics and the event-free survival analysis.The ESC criteria show excellent sensitivity (91.7%) and suboptimal specificity (64.4 %) in predicting CV events in the very high CV risk group, but a poor performance in the high/moderate risk groups. The ST1RE algorithm shows a good predictive performance in all CV risk categories. Using ESC classification, the event-free survival analysis shows a significantly higher event rate in the very high CV risk group compared to the high/moderate risk group (p 0.0019). Using the ST1RE algorithm, a significant difference in the event-free survival curve was found between the three CV risk categories (p 0.0001).In T1D the ESC classification has a good performance in predicting CV events only in those at very high CV risk, whereas the ST1RE algorithm has a good performance in all risk categories.