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Air pollution and children's mental health in rural areas: compositional spatio-temporal model.
Mota-Bertran, Anna; Coenders, Germà; Plaja, Pere; Saez, Marc; Barceló, Maria Antònia.
Afiliación
  • Mota-Bertran A; Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, Carrer de la Universitat de Girona 10, Campus de Montilivi, 17003, Girona, Spain.
  • Coenders G; Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública, Instituto de Salud Carlos III., Madrid, Spain.
  • Plaja P; Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, Carrer de la Universitat de Girona 10, Campus de Montilivi, 17003, Girona, Spain.
  • Saez M; Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública, Instituto de Salud Carlos III., Madrid, Spain.
  • Barceló MA; Fundació Salut Empordà., Figueres, Spain.
Sci Rep ; 14(1): 19363, 2024 08 21.
Article en En | MEDLINE | ID: mdl-39169039
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Población Rural / Salud Mental / Teorema de Bayes / Contaminantes Atmosféricos / Contaminación del Aire Límite: Adolescent / Child / Child, preschool / Female / Humans / Male Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: España Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Población Rural / Salud Mental / Teorema de Bayes / Contaminantes Atmosféricos / Contaminación del Aire Límite: Adolescent / Child / Child, preschool / Female / Humans / Male Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: España Pais de publicación: Reino Unido