How does unemployement leads to high infant mortality rate?
Answers
The infant mortality rate (IMR) is an indicator of child health [1] as well as of population health. Socio-economic factors affecting the health of the population (such as economic development, general living conditions and social wellbeing) have an impact on the IMR [2,3]. According to the analytical framework proposed by Mosley and Chen, infant or child deaths are seen as attributable to a range of hierarchical determinants that may be proximal (e.g., maternal factors, nutrition deficiency, infections, injuries, health services utilization), intermediate (e.g., access to food, safe water, health services, vaccinations), or distal (e.g., education, unemployment, national income, income distribution, public health spending) [4].
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) [5,6]. According to the income inequality hypothesis, referred to as the “big idea”, once a society progresses beyond the point of absolute deprivation, then it is the distribution of income within the society that affects health outcomes [7]. A significant association in wealthy nations between IM and income distribution, but not with absolute income were found in two recent ecological cross-sectional studies of OECD (Organisation for Economic Co-operation and Development) countries [8,9] and in a systematic review [10]. Conversely, Schell conducted a study of 152 high, middle and low income countries, and did not find a significant association between income inequality and IMR in high income countries [11]. Recently, Olson found that both income and income inequality affect IM in the USA [6]. Moreover, Regidor showed that in 21 high-income countries, the relationship between IM and income inequality, demonstrated in 1995, disappeared in 2005 [5].
In summary the relationship between income, income inequality and IMR in high-income countries seems to vary according to specific characteristics of the countries, socio-economic indicators chosen for the analyses and across years. Therefore, it could be beneficial to investigate the association between IM and socio-economic factors in Italy in order to tackle existing health inequalities. To our knowledge, no such research has been undertaken in Italy, a country characterized by one of the lowest IMR in Europe (3.3/1,000 live births in 2008), but with large inter-regional disparities [12], and levels of inequality and poverty that are among the highest measured in wealthy nations [13].
The aim of our study was to assess the associations between IM and major socio-economic determinants in Italy, in an ecological analysis using recent data (2006–2008).
Methods
The units of observation for the present study were the 20 Italian Regions in the years 2006–2008. We selected, from the existing literature, four potentially important distal socio-economic determinants of IM: income inequality, mean household income, educational attainment and unemployment rate. The Gini coefficient was chosen as a measure of income inequality, and ranged from 0 (total equality) to 1 (total inequality). Data on the Gini coefficient were extracted from the Italian National Institute of Statistics (ISTAT) [14].