BACKGROUND: Socioeconomic and healthcare indicators are major determinants of health outcomes. The impact of social and healthcare inequalities on Brazilian morbidity and mortality indicators is of concern but it is not well studied. METHODS: A multilevel ecological study was performed in order to investigate the association between a set of socioeconomic and healthcare indicators and five morbidity and mortality outcomes. Datasets were presented at three hierarchical levels: local (lower level), regional (intermediate level) and state (higher level). A Poisson regression model was estimated for each outcome with random intercept and fixed regression coefficients for independent variables at the three levels. The magnitude of outcome variability at intermediate and higher levels was assessed for all models. RESULTS: All outcomes were associated with both socioeconomic and healthcare variables, with predominance of associations at the local level. General and high-complexity healthcare infrastructures were directly associated with indicators related to later stages of the demographic and epidemiological transition process. A mild effect on morbidity and mortality related to political voting patterns was found at the local level. CONCLUSIONS: Healthcare conditions and socioeconomic indicators are associated with health outcomes in a complex way at the local level in Brazil, but part of the variability of health outcomes is related to factors operating at higher levels. Some possible interaction effects and cross-sectional design limitations of this study must be considered.
BACKGROUND: Socioeconomic and healthcare indicators are major determinants of health outcomes. The impact of social and healthcare inequalities on Brazilian morbidity and mortality indicators is of concern but it is not well studied. METHODS: A multilevel ecological study was performed in order to investigate the association between a set of socioeconomic and healthcare indicators and five morbidity and mortality outcomes. Datasets were presented at three hierarchical levels: local (lower level), regional (intermediate level) and state (higher level). A Poisson regression model was estimated for each outcome with random intercept and fixed regression coefficients for independent variables at the three levels. The magnitude of outcome variability at intermediate and higher levels was assessed for all models. RESULTS: All outcomes were associated with both socioeconomic and healthcare variables, with predominance of associations at the local level. General and high-complexity healthcare infrastructures were directly associated with indicators related to later stages of the demographic and epidemiological transition process. A mild effect on morbidity and mortality related to political voting patterns was found at the local level. CONCLUSIONS: Healthcare conditions and socioeconomic indicators are associated with health outcomes in a complex way at the local level in Brazil, but part of the variability of health outcomes is related to factors operating at higher levels. Some possible interaction effects and cross-sectional design limitations of this study must be considered.
Authors: Felipe J Aidar; Ricardo J de Oliveira; António J Silva; Dihogo G de Matos; André L Carneiro; Nuno Garrido; Robert C Hickner; Victor M Reis Journal: Health Qual Life Outcomes Date: 2011-10-13 Impact factor: 3.186
Authors: Katarina Rosicova; Sijmen A Reijneveld; Andrea Madarasova Geckova; Roy E Stewart; Martin Rosic; Johan W Groothoff; Jitse P van Dijk Journal: Int J Equity Health Date: 2015-11-05