Detalhes bibliográficos
| Ano de defesa: |
2019 |
| Autor(a) principal: |
Duque, Andrezza Marques |
| Orientador(a): |
Nunes, Marco Antônio Prado |
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Tese
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Não Informado pela instituição
|
| Programa de Pós-Graduação: |
Pós-Graduação em Ciências da Saúde
|
| Departamento: |
Não Informado pela instituição
|
| País: |
Não Informado pela instituição
|
| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://ri.ufs.br/jspui/handle/riufs/13078
|
Resumo: |
Introduction: Aging is a worldwide reality and the next global public health challenge. In Brazil, it happens accelerated in unfavorable contexts. This fact demands actions in the economic, political, social and health areas to guarantee the elderly an autonomous and independent life, especially in view of the various inequalities in which they are inserted. Objective: To analyze the patterns and temporal and spatial dynamics of social determinants of health and aging in Brazil and Sergipe. Method: Ecological study with spatial and temporal analysis techniques, carried out in two stages: one in the Brazilian territory and another in the state of Sergipe, with the municipalities as units of analysis, 5,565 and 75, respectively. For the first one, data from the last two Demographic Census and from the National Household Sample Survey (PNAD) were used from 1995 to 2012, from the Brazilian municipalities and states. For the second, secondary data on social, demographic and health indicators collected from Brazilian surveys of the municipalities of the state of Sergipe. The spatial distribution of the social determinants of health and aging was analyzed. Spatial autocorrelation and correlation between variables were tested using the Moran Global Index (I) and the Local Spatial Association Index (LISA). For spatial analysis, the software GeoDa, TerraView 4.2.2 and QGIS 2.18.3 were used and for the models of trend and multiple linear regression, the program R. Results: Significant spatial autocorrelation was observed regarding income inequality, life expectancy and aging rate in Brazil. There are predominant clusters in the North, Northeast and South regions of the country. North and Northeast clusters were associated with higher inequalities and worse indicators. There was an inverse spatial correlation between income inequality with life expectancy and with the aging rate. The characteristics of aging in Brazil showed non-random distribution revealing spatial correlation with income inequality. In the state of Sergipe, the southeastern region had better results clusters in all indicators and the municipalities of the northwest and far east were characterized by lower values, showing them as places of poor living conditions. The high dependency ratio, the illiteracy rate in the elderly and the unemployment rate had a negative impact on life expectancy. Conclusion: There was autocorrelation between social determinants and aging indicating that the worse the social, economic and health indicators the lower life expectancy and aging rates. Aging in Brazil was associated with social determinants in health, with income being one of the most relevant determinants. Given the social and economic disparities in the vast Brazilian territory, spatial analysis proved to be a significant contribution to the formulation of public policies that respect locoregional peculiarities. This recognition points to the need for redirection of public policies and formulation of strategies aimed at reducing social and health inequalities. |
