Background: Dietary total antioxidant capacity (TAC), glycemic index (GI), and glycemic load (GL) are accepted indicators of diet quality, which have an effect on diet–disease relationships. The aim of this study was to evaluate potential associations of dietary TAC, GI, and GL with variables related to nutritive status and insulin resistance (IR) risk in cardiometabolic subjects. Methods: A total of 112 overweight or obese adults (age: 50.8 ± 9 years old) were included in the trial. Dietary intake was assessed by a validated 137-item food frequency questionnaire (FFQ), which was also used to calculate the dietary TAC, GI, and GL. Anthropometrics, blood pressure, body composition by dual-energy X-ray absorptiometry (DXA), glycemic and lipid profiles, C-reactive protein (CRP), as well as fatty liver quantification by magnetic resonance imaging (MRI) were assessed. Results: Subjects with higher values of TAC had significantly lower circulating insulin concentration and homeostatic model assessment of insulin resistance (HOMA-IR). Participants with higher values of HOMA-IR showed significantly higher GI and GL. Correlation analyses showed relevant inverse associations of GI and GL with TAC. A regression model evidenced a relationship of HOMA-IR with TAC, GI, and GL. Conclusion: This data reinforces the concept that dietary TAC, GI, and GL are potential markers of diet quality, which have an impact on the susceptible population with a cardiometabolic risk profile.

Introduction: Postprandial hyperglycemia is a risk factor for type 2 diabetes. Insulin resistance (IR) might affect metabolic responses in non-fasting states. Dietary intake and food composition influence postprandial glucose homeostasis. The aims of this study were to evaluate the effects of different test foods varying in the macronutrient composition on postprandial glycemic responses and whether these outcomes are conditioned by the basal glycemic status in senior subjects. Methods: In a randomized, controlled crossover design, thirty-four adults consumed a test food, a high protein product (n = 19) or a high carbohydrate (CHO) product (n = 15), using the oral glucose tolerance test (OGTT) as a reference. Blood glucose and insulin were measured at fasting and at 15, 30, 45, 60, 90, and 120 min after starting the food intake. For each type of food, the incremental area under the curve (iAUC) for glucose and insulin was calculated. IR was measured using the Homeostatic Model Assessment of IR (HOMA-IR). Results: Consumption of a high protein product significantly lowered the peak and Δ blood glucose concentrations compared to the high CHO product (p < 0.001). Concerning the insulin response, no significant differences between both foods were observed. Fasting glucose was positively correlated with the glucose iAUC only for the high protein product. Positive associations of both fasting insulin and HOMA-IR with the insulin iAUC for all the cases were observed. Linear regression models showed significant positive associations between the glucose iAUC and fasting glucose after adjusting for age and sex. Regarding the insulin iAUC, positive associations were found with fasting insulin and HOMA-IR. Regression models also evidenced that both food test consumptions were able to decrease the glucose and insulin iAUC values when compared with the OGTT product. Conclusion: Our research found that not only is the nutritional composition of foods important, but also the baseline glycemic state of individuals when assessing glycemic index estimations and addressing precision nutritional strategies to prevent and treat IR-associated disturbances.

The identification of affordable noninvasive biomarkers for the diagnosis and characterization of nonalcoholic fatty liver disease (NAFLD) is a major challenge for the research community. This study aimed to explore the usefulness of ferritin as a proxy biomarker of NAFLD condition, alone or in combination with other routine biochemical parameters. Subjects with overweight/obesity and ultrasound-confirmed liver steatosis (n = 112) from the Fatty Liver in Obesity (FLiO) study were assessed. The hepatic evaluation considered magnetic resonance imaging, ultrasonography, and credited routine blood liver biomarkers. Anthropometry and body composition, dietary intake (by means of a validated 137-item food frequency questionnaire), and specific biochemical markers were also determined. Serum ferritin levels were analyzed using a chemiluminescent microparticle immunoassay kit. Lower serum ferritin concentrations were associated with general better liver health and nutritional status. The evaluation of ferritin as a surrogate of liver damage by means of quantile regression analyses showed a positive association with alanine aminotransferase (ALT) (β = 19.21; p ≤ 0.001), liver fat content (β = 8.70; p = 0.008), and hepatic iron (β = 3.76; p ≤ 0.001), after adjusting for potential confounders. In receiver operating characteristic (ROC) analyses, the panel combination of blood ferritin, glucose, and ALT showed the best prediction for liver fat mass (area under the curve (AUC) 0.82). A combination of ferritin and ALT showed the higher predictive ability for estimating liver iron content (AUC 0.73). This investigation demonstrated the association of serum ferritin with liver health as well as with glucose and lipid metabolism markers in subjects with NAFLD. Current findings led to the identification of ferritin as a potential noninvasive predictive biomarker of NAFLD, whose surrogate value increased when combined with other routine biochemical measurements (glucose/ALT).

Estrategias de guía e ingredientes dietéticos de precisión para enfermedades crónicas en población pre-sénior y sénior