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<p>Climate change and air pollution are two of the most pressing global challenges, increasingly recognized for their implications on health. Thus, we aimed to explore the associations between climate, air pollution and monthly hospitalization to Affective Mood Disorders (AMD). Clinical data were collected from the Hospital Morbidity System of the Unified Health System (SUS) for the city of Porto Alegre, Brazil, from 2013 to 2023. Climate and air pollution data were obtained from the ERA5 and the CAMS Global Reanalysis. We use machine learning algorithms, conduct Structural Equation Modeling (SEM), and use Generalized Additive Models to detect the most important variable and to test direct and indirect effects. Insolation (in hours), visibility, and temperature from 15<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(^\circ\)</EquationSource> </InlineEquation>C to 25<InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(^\circ\)</EquationSource> </InlineEquation>C, proxies for good weather conditions, decrease the values in monthly hospitalization rates for AMD. Also, when the values of the total column of methane (above 0.00955), ozone (above 0.0008) and PM<InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(_{2.5}\)</EquationSource> </InlineEquation> increase (proxies for air pollution), the AMD rate also increases. Our findings highlight that climate, together with air pollution as a potential predictor of psychiatric admissions, particularly in populations exposed to reduced air quality or extreme weather conditions.</p>

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Effects of climate and air pollution on rates of hospitalization for affective mood disorders in southern Brazil

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月18日

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  • Leonardo D. Araújo,
  • Vanessa A. Azevedo,
  • Jonathan V. S. Ferreira,
  • Karina B. Lima,
  • Mellanie Fontes-Dutra,
  • Juliana N. Scherer

摘要

Climate change and air pollution are two of the most pressing global challenges, increasingly recognized for their implications on health. Thus, we aimed to explore the associations between climate, air pollution and monthly hospitalization to Affective Mood Disorders (AMD). Clinical data were collected from the Hospital Morbidity System of the Unified Health System (SUS) for the city of Porto Alegre, Brazil, from 2013 to 2023. Climate and air pollution data were obtained from the ERA5 and the CAMS Global Reanalysis. We use machine learning algorithms, conduct Structural Equation Modeling (SEM), and use Generalized Additive Models to detect the most important variable and to test direct and indirect effects. Insolation (in hours), visibility, and temperature from 15 \(^\circ\) C to 25 \(^\circ\) C, proxies for good weather conditions, decrease the values in monthly hospitalization rates for AMD. Also, when the values of the total column of methane (above 0.00955), ozone (above 0.0008) and PM \(_{2.5}\) increase (proxies for air pollution), the AMD rate also increases. Our findings highlight that climate, together with air pollution as a potential predictor of psychiatric admissions, particularly in populations exposed to reduced air quality or extreme weather conditions.