186,875 research outputs found
Income and health differentials in Italian context: differences and relationships
No full textSituations of significant health inequalities in the different socio-economic groups are documented in many countries (Cavelaars, 1988; Costa et al. 2004, WHO 2008). The most convincing empirical results are found in works with an epidemiological basis, which show how different material, social and stress conditions are able to explain differences in morbidity and mortality related to specific diseases found among population groups (Barnett et al., 2004, Kim and Kim 2015). Situations of significant inequality in mortality, morbidity and, in general, in health needs are documented also in Italy (Biggeri et al., 1998; Bar-rella Spandonaro 2002; Cadum et al. 1999; Michelozzi et al. 1999; Rapiti et al. 1999; SLto 1999, 2004; Valerio Vitullo 2000, (Testi et al. 2005, Testi e Ivaldi 2005, 2011, Ivaldi e Testi 2012) although health is a variable that always has a certain measurement complexity.
Since there are multiple variables related to health, individual correlations may change in intensity and direction depending on the context of application and are often affected by problems of interactions between the variables and of non-linearity of the relationships (Fuchs 2004).
It is therefore necessary to measure the state of health through a set of varia-bles or partial indicators, on a geographical basis, in order to take better ac-count of their multidimensional nature, trying to grasp as many gradations and components as possible, thus leading to excellent results in the evaluation of the life standards of a society by policy-makers and by ordinary citizens as well.
The indices are constructed on a geographic basis, one of the few operational tools available to measure in a concise and precise manner the health differ-ences in a given territory. (Ivaldi and Testi, 2011). Moreover, they have the ad-vantage of being inexpensive, because they can be inferred directly from the census data, and transparent, because they are based on objective infor-mation, readily available, and that use the same survey criteria (Carstairs and Morris 1991). The use of health indices on a geographical basis, however, bears the implicit assumption that the characteristics of an individual derive from the area they belong to and that there is a "context effect" (Macintyre S. et al. 2002), namely that the conditions in which a person lives are able to de-termine the risks of morbidity and mortality as well as every other condition.
The analysis of the literature offers several solutions to derive a priori what should be the most appropriate variables to be included in an indicator (Jarman 1983, 1984; Carstairs and Morris 1991, Townsend et al 1988). The choice of var-iables depends on several considerations. However, some common practices can be highlighted; in particular, the availability of data influences the choice of variables to be included and so, ultimately, the composition of the indicator it-self (Grasso 2002; Ivaldi 2006; Ivaldi e Di Gennaro 2011, Soliani et. al 2011, Munda 2012).
The specific purpose of this paper is to propose an indicator that is able to explain the geographical variability of health, linking it with the disposable in-come in order to verify the existing relationships described in the literature.
The source of the data is the 2015 publication by the Italian Institute of Statis-tics (ISTAT): "Fair and Sustainable Well-being (BES)". The database contains a set of indicators, created in 2010, following an initiative by the National Council for Economy and Labour and by the National Institute of Statistics. The BES (Fair and Sustainable Well-being, the name given to the project) is based large-ly on the OECD framework and on findings by the Stiglitz-Sen-Fitoussi Com-mission. (CNEL-ISTAT, 2012, 2013, Stiglitz et al 2009). Among the intentions of the BES there is a measurement of fairness by reference to appropriate statis-tical indicators in 12 different dimensions for a total of 128 indicators. One of the dimensions analysed is, of course, health
Income and health differentials in Italian context: differences and relationships
No full textSituations of significant health inequalities in the different socio-economic groups are documented in many countries (Cavelaars, 1988; Costa et al. 2004, WHO 2008). The most convincing empirical results are found in works with an epidemiological basis, which show how different material, social and stress conditions are able to explain differences in morbidity and mortality related to specific diseases found among population groups (Barnett et al., 2004, Kim and Kim 2015). Situations of significant inequality in mortality, morbidity and, in general, in health needs are documented also in Italy (Biggeri et al., 1998; Bar-rella Spandonaro 2002; Cadum et al. 1999; Michelozzi et al. 1999; Rapiti et al. 1999; SLto 1999, 2004; Valerio Vitullo 2000, (Testi et al. 2005, Testi e Ivaldi 2005, 2011, Ivaldi e Testi 2012) although health is a variable that always has a certain measurement complexity.
Since there are multiple variables related to health, individual correlations may change in intensity and direction depending on the context of application and are often affected by problems of interactions between the variables and of non-linearity of the relationships (Fuchs 2004).
It is therefore necessary to measure the state of health through a set of varia-bles or partial indicators, on a geographical basis, in order to take better ac-count of their multidimensional nature, trying to grasp as many gradations and components as possible, thus leading to excellent results in the evaluation of the life standards of a society by policy-makers and by ordinary citizens as well.
The indices are constructed on a geographic basis, one of the few operational tools available to measure in a concise and precise manner the health differ-ences in a given territory. (Ivaldi and Testi, 2011). Moreover, they have the ad-vantage of being inexpensive, because they can be inferred directly from the census data, and transparent, because they are based on objective infor-mation, readily available, and that use the same survey criteria (Carstairs and Morris 1991). The use of health indices on a geographical basis, however, bears the implicit assumption that the characteristics of an individual derive from the area they belong to and that there is a "context effect" (Macintyre S. et al. 2002), namely that the conditions in which a person lives are able to de-termine the risks of morbidity and mortality as well as every other condition.
The analysis of the literature offers several solutions to derive a priori what should be the most appropriate variables to be included in an indicator (Jarman 1983, 1984; Carstairs and Morris 1991, Townsend et al 1988). The choice of var-iables depends on several considerations. However, some common practices can be highlighted; in particular, the availability of data influences the choice of variables to be included and so, ultimately, the composition of the indicator it-self (Grasso 2002; Ivaldi 2006; Ivaldi e Di Gennaro 2011, Soliani et. al 2011, Munda 2012).
The specific purpose of this paper is to propose an indicator that is able to explain the geographical variability of health, linking it with the disposable in-come in order to verify the existing relationships described in the literature.
The source of the data is the 2015 publication by the Italian Institute of Statis-tics (ISTAT): "Fair and Sustainable Well-being (BES)". The database contains a set of indicators, created in 2010, following an initiative by the National Council for Economy and Labour and by the National Institute of Statistics. The BES (Fair and Sustainable Well-being, the name given to the project) is based large-ly on the OECD framework and on findings by the Stiglitz-Sen-Fitoussi Com-mission. (CNEL-ISTAT, 2012, 2013, Stiglitz et al 2009). Among the intentions of the BES there is a measurement of fairness by reference to appropriate statis-tical indicators in 12 different dimensions for a total of 128 indicators. One of the dimensions analysed is, of course, health
Asymétries d'information et richesse immatérielle de l'entreprise : Mesure microéconométrique
No full textLes économètres ont estimé des frontières de coût et de production afin d'évaluer l'inefficacité des entreprises. En parallèle, les économistes ont considéré des problèmes d'information asymétrique dans les relations contractuelles entre des principaux et des agents. Cet article propose de faire coïncider ces deux approches. On y construit des frontières structurelles ou le terme d'inefficacité est en partie endogène et dépend des contraintes économiques qui pèsent sur l'activité d'un producteur. Des données sur la régulation du transport urbain en France sont utilisées afin d'illustrer notre méthode.
Maurice Ivaldi (1944-2011)
No full textMaurice Ivaldi (1944-2011). In: Bulletin mensuel de la Société linnéenne de Lyon, 81ᵉ année, n°3-4, Mars-avril 2012. p. 72
Maurice Ivaldi (1944-2011)
No full textMaurice Ivaldi (1944-2011). In: Bulletin mensuel de la Société linnéenne de Lyon, 81ᵉ année, n°3-4, Mars-avril 2012. p. 72
Formante giurisprudenziale e principio di legalità: tensioni ed equilibri
No full textThe role of judicial precedent is dealt with and debated in different fields of national, supranational and international la
Interventi di prima ristrutturazione dell'immobile patrimoniale gia' sede dell'Ambasciata d'Italia a Tripoli (Libia)
No full text- …
