Using geo-spatial analysis for assessing the risk of hospital admissions due to community-acquired pneumonia in under-5 children and its association with socially vulnerable areas (Brazil)

Abstract

Abstract Background The concentration of under-5 child morbidity and mortality due to pneumonia in developing countries reflects the social inequities. This study aimed to map and assess the spatial risk for hospitalization due to Community-Acquired Pneumonia in children under 5 years of age and its association with vulnerable areas. Methods Ecological study in the city of Ribeirão Preto, state of São Paulo, Brazil. The study population consisted of hospitalized under-5 children, diagnosed with community-acquired pneumonia, in Ribeirão Preto-São Paulo-Brazil, from 2012 to 2013. Data were collected in different databases, by a trained team, between March 2012 and August 2013 and from the 2010 Demographic Census of the Brazilian Institute of Geography and Statistics. The 956 urban census tracts were considered as the units of analysis. The incidence of cases per 10,000 inhabitants was calculated by census tracts during the study period. For the identification of the spatial risk clusters, the Kernel density estimator and the Getis-Ord Gi* technique were performed. Generalized additive models were used to verify the association between areas with social vulnerability and the occurrence of childhood pneumonia. Results The study included 265 children under the age of five, hospitalized due to community-acquired pneumonia. A concentration of cases was identified in the regions with greater social vulnerability (low income, poor housing conditions and homelessness), as well as a lower occurrence of cases in the most developed and economically privileged area of the city. The majority of the children lived in territories served by traditional primary healthcare units, in which the health surveillance and family and community focus are limited. It is important to highlight that the tracts with the highest degrees of vulnerability, such as those identified as high vulnerability (urban) and very high vulnerability (subnormal urban clusters). Conclusions The results contribute to the comprehension of the social factors involved in child hospitalization due to pneumonia, based on the analysis of the spatial distribution. This approach revealed a strategic tool for diagnosing the disparities as well presenting evidences for the planning in health and strength health care system in achieving equity, welfare and social protection of children.

Keywords

• Pneumonia
• Child health
• Spatial analysis
• Primary health care