Funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.3, Theme 10.
Analysis of existing data on food consumption, lifestyle and biochemical/genetic parameters in Italian population groups along the lifecycle: elaboration of available datasets providing information on eating and lifestyle habits, accessibility, drivers and barriers towards a healthy diet of defined groups (children, adolescents, adults, pregnant women, older subjects) in connection with Spoke 1.
Development of an ONFOODS cohort (including relevant target groups along the lifecycle) within the geographical area covered by the participant institutions with the aim to systematically assess nutritional status, eating behaviour, physical activity and lifestyle in target populations through the application of shared procedures and questionnaire able to add information lacking from the available datasets and to provide a setting for the validation of possible biomarker (see WP 5.4.) new intervention (in connection with Spoke 4) or educational strategies (in connection with spoke 7).
Definition of the protocols for the acquisition of data and metadata relating to biomarkers of eating habits (identification of the multi-omic protocols of choice for the measurement of food biomarkers, classification of biomarkers according to specific links with diet-related risk factors, definition of criteria for the use of biomarkers for applications in interventions of diet improvement).
Investigations on selected cohorts for the validation of biomarkers in a real-life and life-long environment (biomarkers of adherence to dietary recommendations for children, biomarkers of adherence to dietary recommendations for the elderly, biomarkers of adherence to diet recommendations for pregnant women).
Report on available data and defined network (M18)
Protocols for the definition of nutritional status, eating behaviour, physical activity, and lifestyle (M12)
Report on nutritional status, eating behaviour, physical activity and lifestyle linked to quality of diet, nutrition and adherence to sustainable food patterns (M36)
Classifications of dietary patterns based on biomarkers discovery, and associations with possible diet-related health disorders (M24)
Disorder-specific dietary intervention criteria based on predictive tools based on biomarkers patterns (M36)
Fact sheets reporting the prevalence of diet-related disorders based on biomarkers among different population groups (M36)
Environmental factors such as unhealthy eating behavior, poor diet and a sedentary lifestyle contribute to weight gain and chronic disease risk. In Italy, 45% of the adult population suffers from overweight and obesity and is, therefore, at higher risk of developing chronic diseases. Diet and lifestyle can contribute to increased risk of chronic disease even in normal weight condition, through excessive increase in total and visceral fat mass, as well as high intake of harmful nutrients and non-nutrients and reduction of protective ones. Therefore, dietary-nutritional characterization is critical to understand the complex relationship between diet, nutritional status, and risk of disease.
A phenotypic trait of the utmost importance that is closely related to nutritional status and to dietary quality, relates to glyco-metabolic control, because it is strongly related to the cardiometabolic risk and the prevalence of dysglycemia is likely underestimated in the general population. We plan to study the relationship between nutritional status, diet, and glycometabolic status in people with overweight and obesity.
The research will involve different activities as reported below.
Insights of the contribution to the glycol-metabolic phenotype of BMI status, body composition and fat distribution, metabolic syndrome, eating behavior and adherence to the Mediterranean diet.
Characterization of insulin secretory and sensitivity parameters through direct measures and modelling, and identification of simple biomarkers that can surrogate the more complex measures.
Insights of the contribution of different dietary patterns and processing level of foods on the glycol-metabolic phenotype.
Developments of prediction tools that may assist the allocation of subjects to specific interventions to optimize their nutritional status and glycol-metabolic phenotype.