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. 2024 Aug 21;14(1):19363.
doi: 10.1038/s41598-024-70024-2.

Air pollution and children's mental health in rural areas: compositional spatio-temporal model

Anna Mota-Bertran  1   2 , Germà Coenders  1   2 , Pere Plaja  3 , Marc Saez  4   5 , Maria Antònia Barceló  1   2
Affiliations

Air pollution and children's mental health in rural areas: compositional spatio-temporal model

Anna Mota-Bertran et al. Sci Rep. .

Abstract

Air pollution stands as an environmental risk to child mental health, with proven relationships hitherto observed only in urban areas. Understanding the impact of pollution in rural settings is equally crucial. The novelty of this article lies in the study of the relationship between air pollution and behavioural and developmental disorders, attention deficit hyperactivity disorder (ADHD), anxiety, and eating disorders in children below 15 living in a rural area. The methodology combines spatio-temporal models, Bayesian inference and Compositional Data (CoDa), that make it possible to study areas with few pollution monitoring stations. Exposure to nitrogen dioxide (NO2), ozone (O3), and sulphur dioxide (SO2) is related to behavioural and development disorders, anxiety is related to particulate matter (PM10), O3 and SO2, and overall pollution is associated to ADHD and eating disorders. To sum up, like their urban counterparts, rural children are also subject to mental health risks related to air pollution, and the combination of spatio-temporal models, Bayesian inference and CoDa make it possible to relate mental health problems to pollutant concentrations in rural settings with few monitoring stations. Certain limitations persist related to misclassification of exposure to air pollutants and to the covariables available in the data sources used.

Keywords: Air pollution; Bayesian Inference; Children; Compositional data; Mental health; Rural areas; Spatio-temporal models.

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Conflict of interest statement

The manuscript is an original contribution that has not been published before, in whole or in part, in any format, including electronic. All authors declare that they have no actual or potential conflicts of interest, including any financial and non-financial, personal or other relationships with other persons or organizations that may inappropriately influence or be perceived to influence their work.

References

    1. Statistics National Institute of UK. Report on child and adolescent mental health. [Available at: http://www.infocop.es/view_article.asp?id=7807, last accessed on September 14, 2023]
    1. WHO-World Health Organization. Adolescent mental health. [Available at: https://www.who.int/es/news-room/fact-sheets/detail/adolescent-mental-he..., last accessed on July 28, 2023]
    1. Hankin, B. L. et al. Development of depression from preadolescence to young adulthood: emerging gender differences in a 10-year longitudinal study. J. Abnorm. Psychol.107(1), 128–140. 10.1037/0021-843x.107.1.128 (1998). - PubMed
    1. Mota Bertran, A. Air pollutants and mental health of children in a rural region using compositional spatio-temporal models. Phd thesis, University of Girona, Girona, ES (2024).
    1. Volk, H. et al. Prenatal air pollution exposure and neurodevelopment: a review and blueprint for a harmonized approach within ECHO. Environ. Res.196, e110320. 10.1016/J.ENVRES.2020.110320 (2021). - PMC - PubMed

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