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

影响健康状况的多因素因素:来自 MEDIET4ALL 大规模调查的生态社会人口学、心理学和生活方式(饮食、身体活动和睡眠)因素的启示

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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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