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Spatial analysis of the tuberculosis treatment dropout, Buenos Aires, Argentina [Separata] / María Belén Herrero ...[y otros] [Recurso electrónico]

Por: Tipo de material: ArtículoArtículoIdioma: Inglés Descripción: pp. 1-9 diagrsTipo de contenido:
  • Texto
Tipo de medio:
  • computadora
Tipo de soporte:
  • Recurso el línea
Tema(s): En: Revista de saúde pública 1518-8787Resumen: OBJECTIVE: Identify spatial distribution patterns of the proportion of nonadherence to tuberculosis treatment and its associated factors. METHODS: We conducted an ecological study based on secondary and primary data from municipalities of the metropolitan area of Buenos Aires, Argentina. An exploratory analysis of the characteristics of the area and the distributions of the cases included in the sample (proportion of nonadherence) was also carried out along with a multifactor analysis by linear regression. The variables related to the characteristics of the population, residences and families were analyzed. RESULTS: Areas with higher proportion of the population without social security benefits (p = 0.007) and of households with unsatisfied basic needs had a higher risk of nonadherence (p = 0.032). In addition, the proportion of nonadherence was higher in areas with the highest proportion of households with no public transportation within 300 meters (p = 0.070). CONCLUSIONS: We found a risk area for the nonadherence to treatment characterized by a population living in poverty, with precarious jobs and difficult access to public transportation.
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OBJECTIVE: Identify spatial distribution patterns of the proportion of nonadherence to tuberculosis treatment and its associated factors. METHODS: We conducted an ecological study based on secondary and primary data from municipalities of the metropolitan area of Buenos Aires, Argentina. An exploratory analysis of the characteristics of the area and the distributions of the cases included in the sample (proportion of nonadherence) was also carried out along with a multifactor analysis by linear regression. The variables related to the characteristics of the population, residences and families were analyzed. RESULTS: Areas with higher proportion of the population without social security benefits (p = 0.007) and of households with unsatisfied basic needs had a higher risk of nonadherence (p = 0.032). In addition, the proportion of nonadherence was higher in areas with the highest proportion of households with no public transportation within 300 meters (p = 0.070).
CONCLUSIONS: We found a risk area for the nonadherence to treatment characterized by a population living in poverty, with precarious jobs and difficult access to public transportation.

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