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◆ Frontiers in Public Health2026-04-10· Environmental health

Multifactorial determinants of health status: insights from the MEDIET4ALL large-scale survey on eco-sociodemographic, psychological, and lifestyle (diet, physical activity, and sleep) factors

Achraf Ammar, Atef Salem, Mohamed Ali Boujelbane, Khaled Trabelsi, Bassem Bouaziz, Mohamed Kerkeni, Liwa Masmoudi, Juliane Heydenreich, Christiana Schallhorn, Gabriel Müller, Ayse Merve Uyar, Hadeel Ghazzawi, Adam Tawfiq Amawi, Bekir Erhan Orhan, Giuseppe Grosso, Osama Abdelkarim, Tarak Driss, Kaïs El Abed, Piotr Żmijewski, Frédéric Debeaufort, Nasreddine Benbettaïeb, Clément Poulain, Laura Reyes, Amparo Gamero, Marta Cuenca-Ortolá, Antonio Cilla, Nicola Francesca, Concetta María Messina, Enrico Viola, Björn Lorenzen, Stefania Filice, Sadjia Lahiani, Taha Khaldi, Nafaa Souissi, Omar Boukhris, Evelyn Frias-Toral, Haitham Jahrami, Waqar Husain, Walid Mahdi, Hamdi Chtourou, Wolfgang I. Schöllhorn

原始摘要(英文原文)· Original abstract
Background Non-communicable diseases are a growing public health challenge, shaped not only by biological predispositions but also by geo-demographic, socioeconomic, psychological, and lifestyle factors. A comprehensive understanding of these determinants is essential for developing targeted public health strategies. This study aimed to examine the multifactorial determinants of individual health status by analyzing geo-demographic, socio-economic, behavioral, psychological, and lifestyle variables. Methods Data were collected from 4,010 participants (age: 37.2 ± 15.4 years; 59.5% female) across 10 Mediterranean and neighboring countries using the multinational MEDIET4ALL e-survey. Health status was categorized as healthy, at-risk, or with diseases. Multinomial logistic regression, Quade’s Rank ANCOVA and series of multiple regression models were conducted. Results Collectively, around 25% of respondents declared to be at-risk of or with known disease. BMI emerged as the strongest negative predictor of health status ( β = −0.145), with both obesity and underweight significantly increasing the odds of being at risk (OR = 1.8 and 5.2, respectively) and having diseases (OR = 2.2 and 11.9, respectively). Other significant negative predictors included psychological distress (notably anxiety, β = −0.091), insomnia ( β = −0.084), alcohol consumption ( β = −0.053), and prolonged sitting time ( β = −0.037). Conversely, life satisfaction was the strongest significant protective factor ( β = 0.066), followed by higher education, better sleep quality, and adherence to the Mediterranean Diet and lifestyle ( β = 0.034 to 0.050). Socio-economic disparities, including employment status ( β = −0.045) and living environment ( β = −0.031), also significantly influenced health outcomes with rural environment and employed individual showing lower odd ratios of being at-risk and/or having diseases ( p < 0.001). Furthermore, individuals residing in Mediterranean regions, females, married or cohabiting individuals, and non-smokers exhibited significantly lower odds of being at-risk or having diseases ( p < 0.05). While gender remained a significant predictor in the final refined comprehensive regression model ( β = −0.049), marital status lost significance, suggesting that its protective effect may be mediated by psychological well-being and health-related behaviors. Conclusion These findings highlight the complex interplay of lifestyle, mental health, and socio-environmental factors in determining health outcomes, while emphasizing the urgent need for multi-level public health interventions, including policies promoting physical activity, healthy eating, mental well-being, and equitable healthcare access. Future research should employ longitudinal designs to establish causal relationships and guides preventive strategies.
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Multifactorial determinants of health status: insights from the MEDIET4ALL large-scale survey on eco-sociodemographic, psychological, and lifestyle (diet, physical activity, and sleep) factors — 科研速览 Science Skim