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Objectives: to investigate differences in amenable mortality among Italian Regions using the lists of causes of death conceived by Nolte and McKee, and Tobias and Yeh, and assess whether these differences are in part attributable to the list used. We also estimated the contribution of amenable mortality to the gaps in all-cause mortality among North, Centre and South of Italy., Design: cross-sectional study. SETTING AND PARTICIPANTS: Italian National Institute of Statistics (ISTAT) mortality data for the period 2006-2009., Main Outcome Measures: age- and gender-standardised amenable mortality rates., Results: for the period 2006-2009, in Italy the Nolte and McKee mortality rate was 62.38 per 100,000 inhabitants, ranging from 54.92 in the Autonomous Province of Bolzano (Northern Italy) to 62.38 in Campania Region (Southern Italy). For the same period, the Tobias and Yeh mortality rate was 69.59 per 100,000, ranging from 60.06 in Marche Region (Central Italy) to 88.12 in Campania Region. Using Nolte and McKee's list, amenable mortality accounted for 40.65% of the differences in all-cause mortality between Northern and Southern Italy, and for 33.66% of the differences between Southern and Central Italy. Using Tobias and Yeh's list, amenable mortality accounted for 53.99% of the differences in all-cause mortality between Northern and Southern Italy, and for 42.62% of the differences between Southern and Central Italy., Conclusion: the findings here presented show that amenable mortality rates calculated using Tobias and Yeh's list were higher than rates calculated using Nolte and McKee's list. Geographical pattern of amenable mortality derived by the two lists were almost coincident. Moreover, amenable mortality makes a substantial contribution to inequalities in health among North, Centre and South of Italy.

Background: Mortality amenable to health-care services ('amenable mortality') has been defined as "premature deaths that should not occur in the presence of timely and effective health care" and as "conditions for which effective clinical interventions exist." We analyzed the regional variability in health-care services using amenable mortality as a performance indicator. Convergent validity was examined against other indicators, such as health expenditure, GDP per capita, life expectancy at birth, disability-free life expectancy at age 15, number of diagnostic and laboratory tests per 1,000 inhabitants, and the prevalence of cancer and cardiovascular diseases., Methods: Amenable mortality rate was calculated as the average annual number of deaths in the population aged 0-74 years per 100,000 inhabitants, and it was then stratified by gender and region. Data were drawn from national mortality statistics for the period 2006-08., Results: During the study period (2006-08), the age-standardized death rate (SDR) amenable to health-care services in Italy was 62.6 per 100,000 inhabitants: 66.0 per 100,000 for males and 59.1 per 100,000 for females. Significant regional variations ranged from 54.1 per 100,000 inhabitants in Alto Adige to 76.3 per 100,000 in Campania. Regional variability in SDR was examined separately for male and females. The variability proved to be statistically significant for both males and females (males: Q-test = 638.5, p < 0.001; females: Q-test = 700.1, p < 0.001). However, among men, we found a clear-cut divide in SDR values between Central and Southern Italy; among women, this divide was less pronounced. Amenable mortality was negatively correlated with life expectancy at birth for both genders (male: r = -0.64, p = 0.002; female: r = -0.88, p <0.001) and with disability-free life expectancy at age 15 (male: r = -0.70, p <0.001; female: r = -0.67, p <0.001). Amenable mortality displayed a statistically significant negative relationship with GDP per capita, the quantity of diagnostic and laboratory tests per 1,000 inhabitants, and the prevalence of cancer., Conclusions: Amenable mortality shows a wide variation across Italian regions and an inverse relationship with life expectancy and GDP per capita, as expected.

Introduction: One issue that continues to attract the attention of public health researchers is the possible relationship in high-income countries between income, income inequality and infant mortality (IM). The aim of this study was to assess the associations between IM and major socio-economic determinants in Italy., Methods: Associations between infant mortality rates in the 20 Italian regions (2006-2008) and the Gini index of income inequality, mean household income, percentage of women with at least 8 years of education, and percentage of unemployed aged 15-64 years were assessed using Pearson correlation coefficients. Univariate linear regression and multiple stepwise linear regression analyses were performed to determine the magnitude and direction of the effect of the four socio-economic variables on IM., Results: The Gini index and the total unemployment rate showed a positive strong correlation with IM (r = 0.70; p < 0.001 and r = 0.84; p < 0.001 respectively), mean household income showed a strong negative correlation (r = -0.78; p < 0.001), while female educational attainment presented a weak negative correlation (r = -0.45; p < 0.05). Using a multiple stepwise linear regression model, only unemployment rate was independently associated with IM (b = 0.15, p < 0.001)., Conclusions: In Italy, a high-income country where health care is universally available, variations in IM were strongly associated with relative and absolute income and unemployment rate. These results suggest that in Italy IM is not only related to income distribution, as demonstrated for other developed countries, but also to economic factors such as absolute income and unemployment. In order to reduce IM and the existing inequalities, the challenge for Italian decision makers is to promote economic growth and enhance employment levels.