Antecedents: There is a growing evidence in the recent literature of the relationship between exposure to environmental pollutants and the risk of suffering mental health issues. In particular, pollutants such as O3, NO2, PM1, PM2.5 and PM10 are associated with children’s and adolescents’ mental health and neurodevelopment issues. In addition, for children and adolescents, five specific groups of mental health issues have been identified: behavioral and developmental disorders, attention deficit hyperactivity disorder (ADHD), anxiety, eating disorders and other mental health problems. More recently, some studies analyzed the impact of exposure to environmental pollutants on adults’ mental health, but more evidence is needed in this direction, especially accounting for the potential lack of accuracy of national registers of lifetime mental health disorders.
Hipòtesis: The main hypothesis underlying this project is that exposure to environmental pollutants is significantly associated with an increased risk of mental health disorders in children, adolescents, and
adults, with variations in these associations influenced by factors such as age, gender, socioeconomic status, and spatio-temporal dynamics. Environmental pollutants, such as air pollution and toxic substances, are known to have systemic effects on the body, including neuroinflammatory and neurotoxic impacts that may disrupt mental health. These effects are likely to differ across demographic groups due to biological and social factors, such as hormonal differences, varying developmental stages, and unequal exposure levels tied to socioeconomic disparities. By leveraging Bayesian statistical methods, this project seeks to test this hypothesis and explore whether these associations vary across population subgroups and over time, providing a nuanced understanding of the complex interplay between environmental and psychosocial factors in mental health.
Objectius: The main objectives of this project are 1) to develop new statistical methodology to study the association between the exposure to pollutants and mental health and neurodevelopment issues, 2) to account for the potential underregistering of mental health issues in these statistical methods and 3) to use the introduced statistical techniques to analyze the potential association between the exposure to pollutants and mental health and neurodevelopment issues in Catalunya.
Metodologia: The study population will be all Catalan individuals between 3 and 90 years old with a diagnosis within the health mental diseaes using ICD-10 codes and ATC codes from IDIAP and CMDB-SM in the period 2012-2024, with an estimated size around 2,4 million individuals. This project will employ a comprehensive methodological approach combining statistical modeling, mathematical techniques, and epidemiological analysis. A Bayesian-based model will be developed to investigate the association between environmental pollutants and mental health disorders, incorporating key demographic variables such as gender, age, and socioeconomic status, along with spatio-temporal factors. Given the massive size and complexity of the dataset, the project will adapt and extend mathematical techniques, such as the Divide and Recombine framework, within the Bayesian inference paradigm to ensure computational feasibility and scalability. To enhance data reliability, the model will include components to estimate and correct for misreporting of mental health disorders, which will account for potential biases in the dataset. The statistical analysis will explore both direct and interaction effects of pollutants, demographic factors, and temporal trends. This robust methodological framework will generate detailed insights into the relationships between environmental exposures and mental health outcomes while addressing challenges posed by data volume, complexity, and quality.
Aplicabilitat i Rellevància: The findings could provide a scientific basis for policy changes aimed at mitigating environmental pollutants, improving mental health outcomes, and addressing health inequities. The regional focus on Catalunya also allows for localized recommendations, which can be scaled or adapted for broader applications. By combining methodological innovation with practical relevance, this project addresses an urgent need in public health and environmental science. Its outputs could significantly advance our understanding of how environmental factors influence mental health and guide both scientific inquiry and public health policy.