Population Health Inequalities Across and Within European Metropolitan Areas through the Lens of the EURO-HEALTHY Population Health Index (original) (raw)
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European Journal of Public Health, 2017
Background: In Europe, over 70% of the population live in urban areas (UAs). Most international comparative health research is done using national level data, as reliable and comparable urban data are often unavailable or difficult to access. This study aims to investigate whether population health is different in UAs compared with their corresponding countries. Methods: Routinely available health-related data were collected by the EURO-URHIS 2 project, for 10 European countries and for 24 UAs within those countries. National and UA level data for 11 health indicators were compared through the calculation of relative difference, and geographical patterns within Europe were investigated using the Mann Whitney U test. Linear regression modelling was used to adjust for population density, gross domestic product and urbanicity. Results: In general, the urban population in Eastern Europe is less healthy than the Western European urban population. However, people in Eastern Europe have significantly better broad health outcomes in UAs as compared with the corresponding country as a whole, whereas people in Western Europe have generally worse broader health outcomes in UAs. Discussion: For most European countries and UAs that were investigated, the national level health status data does not correspond with the health status at UA level. In order to identify health problems in UAs and to provide information for local health policy, health monitoring and international benchmarking should also be conducted at the local level.
Health Promotion International, 2015
The WHO European Healthy Cities Network has from its inception aimed at tackling inequalities in health. In carrying out an evaluation of Phase V of the project (2009-13), an attempt was made to examine how far the concept of equity in health is understood and accepted; whether cities had moved further from a disease/medical model to looking at the social determinants of inequalities in health; how far the HC project contributed to cities determining the extent and causes of inequalities in health; what efforts were made to tackle such inequalities and how far inequalities in health may have increased or decreased during Phase V. A broader range of resources was utilized for this evaluation than in previous phases of the project. These indicated that most cities were definitely looking at the broader determinants. Equality in health was better understood and had been included as a value in a range of city policies. This was facilitated by stronger involvement of the HC project in city planning processes. Although almost half the cities participating had prepared a City Health Profile, only few cities had the necessary local level data to monitor changes in inequalities in health.
SPATIAL AND REGIONAL HEALTH INEQUALITIES IN EUROPE
Purpose – We have studied the spatial interrelations of the regional health inequalities in Europe in view of the social selection hypothesis. The primary objective of our paper is to demonstrate the effect of health status on various socioeconomic development indicators. Design/methodology/approach – According to the social selection hypothesis, an individual's health status influences both his own socioeconomic status and the economy as a whole. Accordingly, we have operationalised the regional health status and socioeconomic development and analysed their correlations. For such purpose we have used correlation analysis and explanatory spatial data analysis (ESDA): spatial autocorrelation and regional regression models. Findings – According to our results, there are synergistic effects between the two phenomena, both in view of global and local statistics. Regions with better health status are characterised with better socioeconomic conditions. The spatial regression models have also justified and confirmed the use of the social selection hypothesis for the explanation of regional differences in economic development. Research limitations/implications – It is advisable to use panel databases for the future analysis of this topic. To give correct answer on social selection hypothesis on regional level, other examinations (Markov chain model) must be done. Practical implications – Furthermore, it is advisable to extend the range of health status indicators with variables such as noncommunicable chronic diseases or other causes of death associated with socioeconomic phenomena (e.g. TBC incidence indicates poverty). Originality/Value – As far as the social selection hypothesis is concerned, our paper presents new and innovative results whose approach (method for the exploration of regional data) has not been discussed so far in the international literature.
Equity and the Social Determinants of Health in European Cities
Journal of Urban Health, 2012
Equity in health has been the underlying value of the World Health Organization's (WHO) Health for All policy for 30 years. This article examines how cities have translated this principle into action. Using information designed to help evaluate phase IV (2003IV ( -2008 of the WHO European Healthy Cities Network (WHO-EHCN) plus documentation from city programs and websites, an attempt is made to assess how far the concept of equity in health is understood, the political will to tackle the issue, and types of action taken. Results show that although cities continue to focus considerable support on vulnerable groups, rather than the full social gradient, most are now making the necessary shift towards more upstream policies to tackle determinants of health such as poverty, unemployment, education, housing, and the environment, without neglecting access to care. Although local level data reflecting inequalities in health is improving, there is still a long way to go in some cities. The Healthy Cities Project is becoming an integral part of structures for long-term planning and intersectoral action for health in cities, and Health Impact Assessment is gradually being developed. Participation in the WHO-EHCN appears to allow new members to leap-frog ahead established cities. However, this evaluation also exposes barriers to effective local policies and processes to reduce health inequalities. Armed with locally generated evidence of critical success factors, the WHO-EHCN has embarked on a more rigorous and determined effort to achieve the prerequisites for equity in health. More attention will be given to evaluating the effectiveness of action taken and to dealing not only with the most vulnerable but a greater part of the gradient in socioeconomic health inequalities.
Practical lessons in using indicators of determinants of health across 47 European cities
Health Promotion International, 1999
SUMMARY A survey was conducted of 47 European cities applying to join the third phase of the World Health Organization Healthy Cities Project. The survey tested the feasibility of recording baseline information on health-promoting pro- cesses and activities in the cities. A broad multi-sectoral focus for health in the questionnaire presented formidable chal- lenges to respondents. Despite goodwill and local
Determinants of Health Inequalities in European Countries
2019
The object of this article is to assess the health status of the population of selected European countries and to identify and quantify the determinants causing health inequalities in monitored countries. Health status and its supposed determinants are multidimensional categories, specified by a number of selected indicators from the OECD Health Statistics 2018 database, therefore the monitored countries are those countries of Europe that are also OECD member countries. To reach the objective of the article have been used multivariate statistical methods, namely correlation, factor analysis, cluster analysis and linear ordering of countries using synthetic variable. The results of the analysis are presented in the form of tables and graphical outputs from the SAS and Statgraphics statistical packages and using the Excel spreadsheet. Key-Words: Health status, health determinants, health inequalities, factor analysis, cluster analysis, synthetic variable.
Developing a European urban health indicator system: results of EURO-URHIS 1
European journal of public health, 2015
More than half of the world's population now live in cities, including over 70% in Europe. Cities bring opportunities but can be unhealthy places to live. The poorest urban dwellers live in the worst environments and are at the greatest risk of poor health outcomes. EURO-URHIS 1 set out to compile a cross-EU inventory of member states use of measures of urban health in order to support policymakers and improve public health policy. Following a literature review to define terms and find an appropriate model to guide urban health research, EURO-URHIS Urban Areas in all EU member states except Luxembourg, as well as Croatia, Turkey, Macedonia, Iceland and Norway, were defined and selected in collaboration with project partners. Following piloting of the survey tool, a the EURO-URHIS 45 data collection tool was sent out to contacts in all countries with identified EUA's, asking for data on 45 Urban Health Indicators (UHI) and 10 other indicators. 60 questionnaires were received ...