Médecine sociale en 2013 : quand la précarité précède la pauvreté [Social medicine : does it still make sense in 2013?]

Social medicine is a medicine that seeks to understand the impact of socio-economic conditions on human health and diseases in order to improve the health of a society and its individuals. In this field of medicine, determining the socio-economic status of individuals is generally not sufficient to explain and/or understand the underlying mechanisms leading to social inequalities in health. Other factors must be considered such as environmental, psychosocial, behavioral and biological factors that, together, can lead to more or less permanent damages to the health of the individuals in a society. In a time where considerable progresses have been made in the field of the biomedicine, does the practice of social medicine in a primary care setting still make sense? La médecine sociale est une médecine qui cherche à comprendre l'impact des conditions socio-économiques sur la santé humaine et les maladies, dans la perspective d'améliorer l'état de santé d'une société et de ses individus. Dans ce domaine, la détermination du statut socio-économique des individus ne suffit généralement pas à elle seule pour expliquer et comprendre les mécanismes qui sous-tendent les inégalités sociales de santé. D'autres facteurs doivent être pris en considération, tels que les facteurs environnementaux, psychosociaux, comportementaux et biologiques, facteurs qui peuvent conduire de manière synergique à des atteintes plus ou moins durables de l'état de santé des individus d'une société. A une époque où les connaissances, les compétences et les moyens à disposition en biomédecine ont fait des progrès considérables, la pratique de la médecine sociale en cabinet a-t-elle encore sa place en 2013?

Clustering and hot spot detection in socio-economic spatio-temporal data

Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward's classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.

An Introduction to Health Economics & Economic Evaluations

- Overview of Economic Evaluation - Stages in Economic Evaluation  

Understanding socio-economic inequalities affecting older people

In 2012, CARDI was asked by The Office of the First Minister and Deputy First Minister in Northern Ireland to carry out a series of research projects on ageing in Ireland, North and South. This research project, 'Understanding socio-economic inequalities affecting older people’ , was carried out by Paul McGill, CARDI. The research sought to answer the following questions: Are there inequalities that affect older people as a group compared with younger people, or inequalities that exist within the older population? How are these inequalities changing over time? Do these socio-economic inequalities have a detrimental impact on older people or on a substantial number of them? How can any harmful socio-economic inequalities be reduced or eliminated and what are the implications for policy-making? Key Findings*: In RoI the poorest older people had a rise of €32 per week between 2004 and 2011 in total incomes while those with the highest incomes had a rise of €255 (CSO 2013). Total incomes of the poorest pensioner couples in NI did not change between 2003-06 and 2008-11 but the best off had a rise of �37 per week (DSD 2013). Employees aged 60+ earn €10,000 less per year than earners in their peak years in RoI and �2,400 less in NI (CSO Database and NISRA 2012). The richest older people in RoI earn 14 times more from employment than the poorest. In NI it is 36 times more for single pensioners and 44 times more for pensioner couples (CSO 2013; NISRA 2013). The gap in weekly earnings between top and bottom earners aged 60+ in NI rose from �294 to �430 between 2005 and 2012 (NISRA 2012). In the two years 2009-2011 the incomes of the poorest older people in ROI declined by €24 per week (11.4%) (CSO, 2013).

Ethnic disparities in health and health care: a focused review of the evidence and selected examples of good practice. Full report

This report arises from a project commissioned by the Department of Health's Equality and Human Rights Group to produce an evidence-based review with a national perspective that addresses (i) ethnic differentials in health and healthcare and (ii) evidence of effective NHS and other action, including seective examples of good practice to illustrate each area. Rather than aiming for comprehensive coverage, the Department suggested a document that focuses on selective topics and population health priorities drawn from the NHS plan, existing and developing National Service Frameworks, and other policy documents and which, collectively, are encompassed in the NHS's 10-point Race Equality Action Plan. The authors were not asked to review the evidence on other key areas (such ashypertension, stroke, disability, etc.), ethnic disparities in the wider determinants of health, and on some specific groups such as Gypsy Travellers and refugees and asylum seekers. Some of these topics are covered in other reviews.

Ethnic disparities in health and health care: a focused review of the evidence and selected examples of good practice. Executive summary

This report arises from a project commissioned by the Department of Health's Equality and Human Rights Group to produce an evidence-based review with a national perspective that addresses (i) ethnic differentials in health and healthcare and (ii) evidence of effective NHS and other action, including seective examples of good practice to illustrate each area. Rather than aiming for comprehensive coverage, the Department suggested a document that focuses on selective topics and population health priorities drawn from the NHS plan, existing and developing National Service Frameworks, and other policy documents and which, collectively, are encompassed in the NHS's 10-point Race Equality Action Plan. The authors were not asked to review the evidence on other key areas (such ashypertension, stroke, disability, etc.), ethnic disparities in the wider determinants of health, and on some specific groups such as Gypsy Travellers and refugees and asylum seekers. Some of these topics are covered in other reviews.

Towards economic and monetary union: changing trends in payment systems for new european members

The objective of this paper is preciselyto study the evolution of payment systems within the accession countries between 1996 and 2003 and compare them with those of the E.U. and the Eurozone countries

The allometry of non-employment. What can compositional data analysis tell us about labour market performance across the UK's regions?

The low levels of unemployment recorded in the UK in recent years are widely cited asevidence of the country’s improved economic performance, and the apparent convergence of unemployment rates across the country’s regions used to suggest that the longstanding divide in living standards between the relatively prosperous ‘south’ and the more depressed ‘north’ has been substantially narrowed. Dissenters from theseconclusions have drawn attention to the greatly increased extent of non-employment(around a quarter of the UK’s working age population are not in employment) and themarked regional dimension in its distribution across the country. Amongst these dissenters it is generally agreed that non-employment is concentrated amongst oldermales previously employed in the now very much smaller ‘heavy’ industries (e.g. coal,steel, shipbuilding).This paper uses the tools of compositiona l data analysis to provide a much richer picture of non-employment and one which challenges the conventional analysis wisdom about UK labour market performance as well as the dissenters view of the nature of theproblem. It is shown that, associated with the striking ‘north/south’ divide in nonemployment rates, there is a statistically significant relationship between the size of the non-employment rate and the composition of non-employment. Specifically, it is shown that the share of unemployment in non-employment is negatively correlated with the overall non-employment rate: in regions where the non-employment rate is high the share of unemployment is relatively low. So the unemployment rate is not a very reliable indicator of regional disparities in labour market performance. Even more importantly from a policy viewpoint, a significant positive relationship is found between the size ofthe non-employment rate and the share of those not employed through reason of sicknessor disability and it seems (contrary to the dissenters) that this connection is just as strong for women as it is for men

Social inequalities and mortality in Europe-results from a large multi-national cohort

BACKGROUND Socio-economic inequalities in mortality are observed at the country level in both North America and Europe. The purpose of this work is to investigate the contribution of specific risk factors to social inequalities in cause-specific mortality using a large multi-country cohort of Europeans. METHODS A total of 3,456,689 person/years follow-up of the European Prospective Investigation into Cancer and Nutrition (EPIC) was analysed. Educational level of subjects coming from 9 European countries was recorded as proxy for socio-economic status (SES). Cox proportional hazard model's with a step-wise inclusion of explanatory variables were used to explore the association between SES and mortality; a Relative Index of Inequality (RII) was calculated as measure of relative inequality. RESULTS Total mortality among men with the highest education level is reduced by 43% compared to men with the lowest (HR 0.57, 95% C.I. 0.52-0.61); among women by 29% (HR 0.71, 95% C.I. 0.64-0.78). The risk reduction was attenuated by 7% in men and 3% in women by the introduction of smoking and to a lesser extent (2% in men and 3% in women) by introducing body mass index and additional explanatory variables (alcohol consumption, leisure physical activity, fruit and vegetable intake) (3% in men and 5% in women). Social inequalities were highly statistically significant for all causes of death examined in men. In women, social inequalities were less strong, but statistically significant for all causes of death except for cancer-related mortality and injuries. DISCUSSION In this European study, substantial social inequalities in mortality among European men and women which cannot be fully explained away by accounting for known common risk factors for chronic diseases are reported.