Background While most Italian Regions have recorded a dramatic decrease in infant mortality rates in the last 10 years, great geographical variations persist. These variations are mostly attributable to neonatal mortality rates (NMR). In 2005 the Italian NMR was 2.7 deaths per 1.000 live births, ranging from 2.2 in the North to 3.3 in the South. Explanations for such inequalities are complex and involve multiple factors. Population-based studies using vital statistics are a useful source of information for perinatal epidemiology and for monitoring health inequalities. Since 2002, following a change in legislation, Births Certificates are entrusted to the Ministry of Health, while the Italian National Institute of Statistics (ISTAT) is in charge of Death Registry. For privacy protection, individual matching of these data sets is not possible at a national level. Due to the lack of this crucial information, we performed an ecological study to examine potential correlates of these inequalities in NMR. Methods Using regional Italian data derived from the ISTAT and Birth Certificates, three socio-economic indicators were examined as potential correlates of NMR. Additional factors included the percentage deliveries in Birth Units with <500 births and number of Neonatal Intensive Care Units (NICU) with >1000 births/year. Results Preliminary results show that the gross domestic product was negatively correlated with NMR, while Gini’s coefficient for income was positively correlated with NMR. The percentage of deliveries in Birth Units with <500 births, the number of NICU with >1000 births/year and the female employment rate were unrelated with NMR. Conclusions Our results suggest that socio-economic factors play an important role in Italian variations in NMR and provide a useful starting point for hypothesis generation that should be verified with analytical studies. Individual data could provide a more complete picture of the role of socio-economic factors as determinants of health services accessibility.

Persisting geographical disparities in neonatal mortality across Italy. An ecological study.

FRANCHINO, GIUSEPPE;RAINERI, CRISTINA;PIERI, GIULIA;ALBERTINI, GIOVANNA;DALLOLIO, LAURA;FANTINI, MARIA PIA
2009

Abstract

Background While most Italian Regions have recorded a dramatic decrease in infant mortality rates in the last 10 years, great geographical variations persist. These variations are mostly attributable to neonatal mortality rates (NMR). In 2005 the Italian NMR was 2.7 deaths per 1.000 live births, ranging from 2.2 in the North to 3.3 in the South. Explanations for such inequalities are complex and involve multiple factors. Population-based studies using vital statistics are a useful source of information for perinatal epidemiology and for monitoring health inequalities. Since 2002, following a change in legislation, Births Certificates are entrusted to the Ministry of Health, while the Italian National Institute of Statistics (ISTAT) is in charge of Death Registry. For privacy protection, individual matching of these data sets is not possible at a national level. Due to the lack of this crucial information, we performed an ecological study to examine potential correlates of these inequalities in NMR. Methods Using regional Italian data derived from the ISTAT and Birth Certificates, three socio-economic indicators were examined as potential correlates of NMR. Additional factors included the percentage deliveries in Birth Units with <500 births and number of Neonatal Intensive Care Units (NICU) with >1000 births/year. Results Preliminary results show that the gross domestic product was negatively correlated with NMR, while Gini’s coefficient for income was positively correlated with NMR. The percentage of deliveries in Birth Units with <500 births, the number of NICU with >1000 births/year and the female employment rate were unrelated with NMR. Conclusions Our results suggest that socio-economic factors play an important role in Italian variations in NMR and provide a useful starting point for hypothesis generation that should be verified with analytical studies. Individual data could provide a more complete picture of the role of socio-economic factors as determinants of health services accessibility.
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G. Franchino; C. Raineri; G. Pieri; G. Albertini; L. Dallolio; M.P. Fantini
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/80042
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