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Introduction Type 2 diabetes has been linked to greater cognitive decline, but other glycemic parameters such as prediabetes, diabetes control and treatment, and HOMA-IR and HbA(1c) diabetes-related biomarkers have shown inconsistent results. Furthermore, there is limited research assessing these relationships in short-term studies. Thus, we aimed to examine 2-year associations between baseline diabetes/glycemic status and changes in cognitive function in older participants at high risk of cardiovascular disease. Methods We conducted a 2-year prospective cohort study (n=6,874) within the framework of the PREDIMED-Plus study. The participants (with overweight/obesity and metabolic syndrome; mean age 64.9 years; 48.5% women) completed a battery of 8 cognitive tests, and a global cognitive function Z-score (GCF) was estimated. At baseline, participants were categorized by diabetes status (no-diabetes, prediabetes, and = 5-year diabetes duration), and also by diabetes control. Furthermore, insulin resistance (HOMA-IR) and glycated hemoglobin (HbA(1c)) levels were measured, and antidiabetic medications were recorded. Linear and logistic regression models, adjusted by potential confounders, were fitted to assess associations between glycemic status and changes in cognitive function. Results Prediabetes status was unrelated to cognitive decline. However, compared to participants without diabetes, those with >= 5-year diabetes duration had greater reductions in GCF (beta=-0.11 (95%CI -0.16;-0.06)], as well as in processing speed and executive function measurements. Inverse associations were observed between baseline HOMA-IR and changes in GCF [beta=-0.0094 (95%CI -0.0164;-0.0023)], but also between HbA(1c) levels and changes in GCF [beta=-0.0085 (95%CI -0.0115, -0.0055)], the Mini-Mental State Examination, and other executive function tests. Poor diabetes control was inversely associated with phonologic fluency. The use of insulin treatment was inversely related to cognitive function as measured by the GCF [beta=-0.31 (95%CI -0.44, -0.18)], and other cognitive tests. Conclusions Insulin resistance, diabetes status, longer diabetes duration, poor glycemic control, and insulin treatment were associated with worsening cognitive function changes in the short term in a population at high cardiovascular risk.

Purpose To assess the association between the consumption of non-soy legumes and different subtypes of non-soy legumes and serum uric acid (SUA) or hyperuricemia in elderly individuals with overweight or obesity and metabolic syndrome. Methods A cross-sectional analysis was conducted in the framework of the PREDIMED-Plus study. We included 6329 participants with information on non-soy legume consumption and SUA levels. Non-soy legume consumption was estimated using a semi-quantitative food frequency questionnaire. Linear regression models and Cox regression models were used to assess the associations between tertiles of non-soy legume consumption, different subtypes of non-soy legume consumption and SUA levels or hyperuricemia prevalence, respectively. Results Individuals in the highest tertile (T3) of total non-soy legume, lentil and pea consumption, had 0.14 mg/dL, 0.19 mg/dL and 0.12 mg/dL lower SUA levels, respectively, compared to those in the lowest tertile (T1), which was considered the reference one. Chickpea and dry bean consumption showed no association. In multivariable models, participants located in the top tertile of total non-soy legumes [prevalence ratio (PR): 0.89; 95% CI 0.82-0.97;ptrend = 0.01, lentils (PR: 0.89; 95% CI 0.82-0.97;ptrend = 0.01), dry beans (PR: 0.91; 95% C: 0.84-0.99;ptrend = 0.03) and peas (PR: 0.89; 95% CI 0.82-0.97;ptrend = 0.01)] presented a lower prevalence of hyperuricemia (vs. the bottom tertile). Chickpea consumption was not associated with hyperuricemia prevalence. Conclusions In this study of elderly subjects with metabolic syndrome, we observed that despite being a purine-rich food, non-soy legumes were inversely associated with SUA levels and hyperuricemia prevalence.