To effectively tackle obesity, it is necessary to identify all specific socioeconomic factors which contribute to its development. We aimed to highlight the prevalence of adult overweight/obesity in European countries and investigate the association of various socioeconomic factors and their accumulative effect on overweight/obesity status. Cross-sectional data from the Feel4Diabetes study for 24,562 adults residing in low socioeconomic areas were collected, representing Belgium, Finland, Greece, Spain, Bulgaria, and Hungary. Socioeconomic Burden Score (SEBS) was created, accounting for unemployment, financial insecurity, and education ≤ 12 years. Data were analyzed using analysis of variance and logistic regression. In total, 19,063 adults with complete data were included (34.5% overweight and 15.8% obese). The highest overweight/obesity rates occurred in Greece (37.5%/17.8%) and Hungary (35.4%/19.7%). After adjusting for confounders, age of <45 years and female sex were inversely associated with overweight/obesity, while low educational level (≤12 years), unemployment, and financial insecurity were positively associated. The increase in SEBS (clustering of socioeconomic disadvantages) was associated with increased overweight/obesity likelihood. This association of SEBS scores with overweight/obesity was evident for males and females across all examined countries, excluding males in low-income countries (Bulgaria and Hungary), where the highest SEBS score was inversely associated with overweight/obesity. The clustering burden of socioeconomic disadvantages on overweight/obesity was found to be influenced by the countries’ economic state and sex.

Background: Obesity arises from complex interactions among genetic, biological, behavioral, and environmental factors. Traditional “one‐size‐fits‐all” interventions often yield modest, short‐term outcomes, failing to account inter‐individual variability. Advances in artificial intelligence (AI), polygenic risk scores (PRS), and digital health technologies now enable personalized and adaptive lifestyle interventions. Objective: This paper presents the design and evaluation framework of the BETTER4All personalized intervention, a multicentre randomized controlled trial within the EU‐funded BETTER4U project. The trial aims to integrate biological and behavioral data into tailored obesity prevention and management strategies. Methods: The BETTER4All trial will be conducted across seven European countries, targeting 1022 adults with body mass index (BMI) ≥ 25 kg/m ² . Participants will be randomized to an intervention group receiving AI and PRS‐based lifestyle recommendations via a smartphone application, wearable device, and structured counseling, or to a control group receiving standard hypocaloric diet and lifestyle advice. The primary outcome is change in BMI at 6 months. Secondary outcomes include weight‐loss maintenance at 1 year, metabolomic and gut microbiota biomarkers, lifestyle behaviors, and psychosocial parameters. Process evaluation incorporates measures of fidelity, acceptability, feasibility, and appropriateness, alongside adherence metrics from the digital tools. Conclusion: The BETTER4All trial will provide evidence on the effectiveness and scalability of AI‐driven, biologically informed personalization in obesity care, offering a methodological framework for integrating multimodal digital data, from omics and biomarkers to behavior and lifestyle, contributing to the advancement of precision public health strategies. Trial Registration: ClinicalTrials.gov identifier: NCT06997510

Background : The role of partially hydrolyzed formulas (pHF) as a nutritional intervention for the prevention of Allergic Manifestations (AM) remains debatable, and the effectiveness of each specific pHF should be longitudinally examined. Objective : To investigate whether the risk-reduction effect of a specific pHF compared to a standard formula (SF) on Atopic Dermatitis (AD) within the first 6 months of life observed in the Allergy Reduction Trial (A.R.T.) persists at the age of 5 years and, if it applies to other AM. Methods : Parents/legal guardians of the A.R.T. participants who constituted the Intention-to-Treat population set (N=551) were invited to answer an enriched validated questionnaire regarding doctor diagnosis of AM between 1-5 years of age, including AD, Food Allergy (FA), Asthma, and Allergic Rhinitis. Results : Four hundred and fifty-five subjects (83%) completed the 5-year follow-up (pHF: 131/160, SF: 145/171 and EBF: 179/220). Infant feeding with the pHF resulted in 87% risk-reduction of FA [1,5% vs 12.4%, RR 0.13 (0.03-0.58), p=0.007] between the ages of 1-5 years compared to SF. The RR from birth to 5 years was significantly lower in the pHF group, for the development of any AM [32.7% vs 51.7%, RR 0.73 (0.57-0.94), p=0.02], AD [22.1% vs 38.5%, RR 0.58 (0.41-0.83), p=0.003] and, FA [10.5% vs 20.4%, RR 0.53 (0.29-0.95), p=0.03] compared to the SF group. Conclusion : In non-exclusively breastfed infants at high-risk for allergy, mixed-feeding with a specific whey-based pHF may reduce the risk of atopic dermatitis and food allergy from birth up to the age of 5 years.

Dietary and physical activity interventions are considered the cornerstone in obesity management, however their efficacy at community settings has not been

In total, 3274 adults (65.2% females) from six European countries were included in this cross-sectional analysis using data from the baseline assessment of the Feel4Diabetes study. Anthropometric, sociodemographic, dietary and behavioral data were assessed, and the existence of metabolic syndrome (MetS) was recorded. Beverage consumption patterns (BCPs) were derived via principal component analysis. Three BCPs were derived explaining 39.5% of the total variation. BCP1 was labeled as “Alcoholic beverage pattern”, which loaded heavily on high consumption of beer/cider, wine and other spirits; BCP2 was labeled as “High in sugars beverage pattern” that was mainly characterized by high consumption of soft drinks with sugar, juice containing sugar and low consumption of water; and BCP3 was labeled as “Healthy beverage pattern” that was mainly characterized by high consumption of water, tea, fruit juice freshly squeezed or prepacked without sugar and low consumption of soft drinks without sugar. After adjusting for various confounders, BCP2 was positively associated with elevated triglycerides (p = 0.001), elevated blood pressure (p = 0.001) elevated fasting glucose (p = 0.008) and the existence of MetS (p = 0.006), while BCP1 was inversely associated with reduced HDL-C (p = 0.005) and BCP3 was inversely associated with elevated blood pressure (p = 0.047). The establishment of policy actions as well as public health nutritional education can contribute to the promotion of a healthy beverage consumption.