Análise espacial dos transtornos mentais no Estado do Maranhão, Brasil

Abstract

Mental health is a global concern due to its significant impact on quality of life and society. In Brazil, mental disorders are one of the leading causes of disability, affecting not only individual well-being but also productivity and socioeconomic development. The Covid-19 pandemic has intensified the challenges faced by mental health services, increasing the demand for psychological care and exacerbating disparities in access to services. Based on this, this study aimed to analyze the spatial distribution of hospitalizations for mental disorders in the State of Maranhão and in the city of São Luís between 2010 and 2021. The study also investigated the sociodemographic profiles and factors associated with mental disorders, identifying the temporal and spatial patterns of hospitalizations, as well as mapping the dynamics of the health care network in São Luís. Data from DATASUS, IBGE, and PNS were used to collect and analyze 103,357 notifications of hospitalizations for mental disorders in Maranhão and 15,892 cases in São Luís. Geoprocessing techniques such as Buffer, Moran's Index, Kernel Density Interpolator, and Spatial Hierarchical Clustering were employed to analyze the data and develop thematic maps. QGis and GeoDa software were used to process maps on a geographic scale from 1:250,000. The theoretical foundation of the research was guided by the implications of social and economic determinants on mental health, highlighting the importance of the geographical approach in understanding mental disorders. The research results were: A literature review on the construction and trajectory of mental health policies in Brazil, with an emphasis on the Psychiatric Reform, in addition to analyzing the impact of the Covid-19 pandemic on mental disorders. Two articles were developed in the course of this dissertation: 1. "Spatial analysis of hospitalizations for mental disorders in the state of Maranhão, Brazil (2010-2021)" and 2. "Spatial analysis of hospitalizations for mental disorders in the municipality of São Luís". The results of these articles highlighted heterogeneous patterns of spatial autocorrelation, demonstrating the importance of geographical analysis in understanding the patterns of hospitalization for mental disorders. Although the highest rates of hospitalization were observed in urbanized areas, the residential clusters of patients were often distant from mental health services, pointing to inequalities in access to treatment. As final considerations, the need for more effective and targeted public policies was highlighted, incorporating geoprocessing techniques for an accurate analysis of the spatial dynamics of mental disorders, aiming to improve access to treatment and contribute to the development of more inclusive and effective policies.