Clinical trials

This study aims to improve how we understand and manage blood sugar responses in adults without diabetes. Even in people who appear healthy, blood sugar levels after meals can behave in different ways. These patterns may help predict future risk of diseases such as type 2 diabetes or other cardiometabolic problems. To study this, researchers at IMDEA Nutrition have developed a computer algorithm called GLIA, which uses artificial intelligence (AI) to analyze continuous glucose monitoring (CGM) data. The goal is to classify people into different "glucotypes", meaning typical patterns of how their blood sugar behaves throughout the day. These glucotypes could help tailor dietary recommendations in the future. Goals of the study 1. Train and validate the GLIA algorithm\*\* in a large and diverse sample of adults. 2. Study how glucotypes relate to health indicators\*\*, such as blood pressure, body composition, cholesterol, or lifestyle. 3. Predict how each person responds to different foods\*\*, to support personalized nutrition advice. Who can participate? Adults 18-70 years old who: * Do not\*have diagnosed diabetes or serious metabolic disease. * Agree to wear a glucose sensor for 14 days. * Can keep stable eating habits and record diet and physical activity. What participation involves The study lasts 3 weeks and includes 3 visits: Visit 1 - Screening (20 min): * Review of eligibility criteria. * Explanation of the study. * Signing informed consent. * Visit 2 - Initial assessment (45 min) * Collection of personal and health information. * Measurements: weight, height, waist, body composition, blood pressure. * Placement of a FreeStyle Libre 3 CGM sensor. * Instructions for: * Completing two 3-day food records (one each week). * Taking photos of all meals. * Reporting physical activity. Continuous monitoring (14 days) Visit 3 - Final evaluation (45 min) * Review of diet records. * Repeat measurements. * Blood and urine samples are collected for metabolic and molecular analyses. Meal photos are analyzed using an AI-based food recognition model. The system identifies foods and estimates nutrients (macronutrients, vitamins, minerals, glycemic index, etc.). This helps researchers understand how meals relate to blood sugar patterns. Potential benefits: Although participants may not receive direct health benefits, the study will: * Improve understanding of how healthy people process glucose. * Help identify early risk markers for metabolic diseases. * Contribute to developing \*\*personalized nutrition tools\*\* based on individual glucose responses. Risks: are minimal and mainly include: * Mild skin irritation from the CGM sensor. * Temporary discomfort from blood draw.

The goal of this clinical trial is to evaluate the effect of a multifactorial lifestyle intervention combining Mediterranean diet, energy reduction and physical activity on weight loss in middle-aged adults (men and women 30-50 years old) with metabolic syndrome. The main questions it aims to answer are: Is a multifactorial intervention based on Mediterranean diet, energy reduction and physical activity able to promote weight loss maintenance in middle-aged men and women with metabolic syndrome? syndrome? Which are the sociodemographic barriers to adhere to a multifactorial lifestyle intervention to promote cardiometabolic health? How is the lifestyle pattern of middle-aged Spanish adults with metabolic Researchers will compare a multifactorial lifestyle intervention combining Mediterranean diet, energy reduction and physical activity to a control intervention based on usual primary healthcare to see if the intervention improve cardiometabolic traits and promote weight loss maintenance after 1 year. Participants in the intervention arm will be asked to follow an energy-reduced Mediterranean diet plus a physical activity program with the aim of reducing 5-10% of the initial weight in 6 months and of maintaining the weight lost after 1 year o follow-up.