Advancing tools to promote health equity across European Union regions: the EURO-HEALTHY project

BACKGROUND

Population health measurements are recognised as appropriate tools to support public health monitoring. Yet, there is still a lack of tools that offer a basis for policy appraisal and for foreseeing impacts on health equity. In the context of persistent regional inequalities, it is critical to ascertain which regions are performing best, which factors might shape future health outcomes and where there is room for improvement.

METHODS

Under the EURO-HEALTHY project, tools combining the technical elements of multi-criteria value models and the social elements of participatory processes were developed to measure health in multiple dimensions and to inform policies. The flagship tool is the Population Health Index (PHI), a multidimensional measure that evaluates health from the lens of equity in health determinants and health outcomes, further divided into sub-indices. Foresight tools for policy analysis were also developed, namely: (1) scenarios of future patterns of population health in Europe in 2030, combining group elicitation with the Extreme-World method and (2) a multi-criteria evaluation framework informing policy appraisal (case study of Lisbon). Finally, a WebGIS was built to map and communicate the results to wider audiences.

RESULTS

The Population Health Index was applied to all European Union (EU) regions, indicating which regions are lagging behind and where investments are most needed to close the health gap. Three scenarios for 2030 were produced - (1) the 'Failing Europe' scenario (worst case/increasing inequalities), (2) the 'Sustainable Prosperity' scenario (best case/decreasing inequalities) and (3) the 'Being Stuck' scenario (the EU and Member States maintain the status quo). Finally, the policy appraisal exercise conducted in Lisbon illustrates which policies have higher potential to improve health and how their feasibility can change according to different scenarios.

CONCLUSIONS

The article makes a theoretical and practical contribution to the field of population health. Theoretically, it contributes to the conceptualisation of health in a broader sense by advancing a model able to integrate multiple aspects of health, including health outcomes and multisectoral determinants. Empirically, the model and tools are closely tied to what is measurable when using the EU context but offering opportunities to be upscaled to other settings.

Spatial variability in air pollution exposure in relation to socioeconomic indicators in nine European metropolitan areas: A study on environmental inequality

A limited number of studies have addressed environmental inequality, using various study designs and methodologies and often reaching contradictory results. Following a standardized multi-city data collection process within the European project EURO-HEALTHY, we conducted an ecological study to investigate the spatial association between nitrogen dioxide (NO₂), as a surrogate for traffic related air pollution, and ten socioeconomic indicators at local administrative unit level in nine European Metropolitan Areas. We applied mixed models for the associations under investigation with random intercepts per Metropolitan Area, also accounting for the spatial correlation. The stronger associations were observed between NO₂ levels and population density, population born outside the European Union (EU28), total crimes per 100,000 inhabitants and unemployment rate that displayed a highly statistically significant trend of increasing concentrations with increasing levels of the indicators. Specifically, the highest vs the lowest quartile of each indicator above was associated with 48.7% (95% confidence interval (CI): 42.9%, 54.8%), 30.9% (95%CI: 22.1%, 40.2%), 19.8% (95%CI: 13.4%, 26.6%) and 15.8% (95%CI: 9.9%, 22.1%) increase in NO₂ respectively. The association with population density most probably reflects the higher volume in vehicular traffic, which is the main source of NO₂ in urban areas. Higher pollution levels in areas with higher percentages of people born outside EU28, crime or unemployment rates indicate that worse air quality is typically encountered in deprived European urban areas. Policy makers should consider spatial environmental inequalities to better inform actions aiming to lower urban air pollution levels that will subsequently lead to improved quality of life, public health and health equity across the population.

Spatial variability in air pollution exposure in relation to socioeconomic indicators in nine European metropolitan areas: A study on environmental inequality

A limited number of studies have addressed environmental inequality, using various study designs and methodologies and often reaching contradictory results. Following a standardized multi-city data collection process within the European project EURO-HEALTHY, we conducted an ecological study to investigate the spatial association between nitrogen dioxide (NO₂), as a surrogate for traffic related air pollution, and ten socioeconomic indicators at local administrative unit level in nine European Metropolitan Areas. We applied mixed models for the associations under investigation with random intercepts per Metropolitan Area, also accounting for the spatial correlation. The stronger associations were observed between NO₂ levels and population density, population born outside the European Union (EU28), total crimes per 100,000 inhabitants and unemployment rate that displayed a highly statistically significant trend of increasing concentrations with increasing levels of the indicators. Specifically, the highest vs the lowest quartile of each indicator above was associated with 48.7% (95% confidence interval (CI): 42.9%, 54.8%), 30.9% (95%CI: 22.1%, 40.2%), 19.8% (95%CI: 13.4%, 26.6%) and 15.8% (95%CI: 9.9%, 22.1%) increase in NO₂ respectively. The association with population density most probably reflects the higher volume in vehicular traffic, which is the main source of NO₂ in urban areas. Higher pollution levels in areas with higher percentages of people born outside EU28, crime or unemployment rates indicate that worse air quality is typically encountered in deprived European urban areas. Policy makers should consider spatial environmental inequalities to better inform actions aiming to lower urban air pollution levels that will subsequently lead to improved quality of life, public health and health equity across the population.

Environmental public health risks in European metropolitan areas within the EURO-HEALTHY project

Urban areas in Europe are facing a range of environmental public health challenges, such as air pollution, traffic noise and road injuries. The identification and quantification of the public health risks associated with exposure to environmental conditions is important for prioritising policies and interventions that aim to diminish the risks and improve the health of the population. With this purpose in mind, the EURO-HEALTHY project used a consistent approach to assess the impact of key environmental risk factors and urban environmental determinants on public health in European metropolitan areas. A number of environmental public health indicators, which are closely tied to the physical and built environment, were identified through stakeholder consultation; data were collected from six European metropolitan areas (Athens, Barcelona, Lisbon, London, Stockholm and Turin) covering the period 2000-2014, and a health impact assessment framework enabled the quantification of health effects (attributable deaths) associated with these indicators. The key environmental public health indicators were related to air pollution and certain urban environmental conditions (urban green spaces, road safety). The air pollution was generally the highest environmental public health risk; the associated number of deaths in Athens, Barcelona and London ranged between 800 and 2300 attributable deaths per year. The number of victims of road traffic accidents and the associated deaths were lowest in the most recent year compared with previous years. We also examined the positive impacts on health associated with urban green spaces by calculating reduced mortality impacts for populations residing in areas with greater green space coverage; results in Athens showed reductions of all-cause mortality of 26 per 100,000 inhabitants for populations with benefits of local greenspace. Based on our analysis, we discuss recommendations of potential interventions that could be implemented to reduce the environmental public health risks in the European metropolitan areas covered by this study.

Population Health Inequalities Across and Within European Metropolitan Areas through the Lens of the EURO-HEALTHY Population Health Index

The different geographical contexts seen in European metropolitan areas are reflected in the uneven distribution of health risk factors for the population. Accumulating evidence on multiple health determinants point to the importance of individual, social, economic, physical and built environment features, which can be shaped by the local authorities. The complexity of measuring health, which at the same time underscores the level of intra-urban inequalities, calls for integrated and multidimensional approaches. The aim of this study is to analyse inequalities in health determinants and health outcomes across and within nine metropolitan areas: Athens, Barcelona, Berlin-Brandenburg, Brussels, Lisbon, London, Prague, Stockholm and Turin. We use the EURO-HEALTHY Population Health Index (PHI), a tool that measures health in two components: Health Determinants and Health Outcomes. The application of this tool revealed important inequalities between metropolitan areas: Better scores were found in Northern cities when compared with their Southern and Eastern counterparts in both components. The analysis of geographical patterns within metropolitan areas showed that there are intra-urban inequalities, and, in most cities, they appear to form spatial clusters. Identifying which urban areas are measurably worse off, in either Health Determinants or Health Outcomes, or both, provides a basis for redirecting local action and for ongoing comparisons with other metropolitan areas.

The Role of Contextual Socioeconomic Circumstances and Neighborhood Poverty Segregation on Mortality in 4 European Cities

Several studies have recognized the health disadvantage of residents in socioeconomically deprived neighborhoods, independent of the influence of individual socioeconomic conditions. The effect of neighborhood socioeconomic deprivation on general mortality has appeared heterogeneous among the cities analyzed: the underlying mechanisms have been less empirically explored, and explanations for this heterogeneous health effect remain unclear. The present study aimed to: (1) analyze the distribution of socioeconomically disadvantaged persons in neighborhoods of 4 European cities—Turin, Barcelona, Stockholm and Helsinki—trying to measure segregation of residents according to their socioeconomic conditions. Two measuring approaches were used, respectively, through dissimilarity index and clustering estimated from Bayesian models. (2) Analyze the distribution of mortality in the above mentioned cities, trying to disentangle the independent effects of both neighborhood socioeconomic deprivation and neighborhood segregation of residents according to their socioeconomic conditions, using multilevel models. A significantly higher risk of death was observed among residents in more deprived neighborhoods in all 4 cities considered, slightly heterogeneous across them. Poverty segregation appeared to be slightly associated with increasing mortality in Turin and, among females and only according to dissimilarity, in Barcelona. Few studies have explored the health effects of social clustering, and results could inform urban policy design with regard to social mix.

Socioeconomic inequalities in cause-specific mortality in 15 European cities

BACKGROUND

Socioeconomic inequalities are increasingly recognised as an important public health issue, although their role in the leading causes of mortality in urban areas in Europe has not been fully evaluated. In this study, we used data from the INEQ-CITIES study to analyse inequalities in cause-specific mortality in 15 European cities at the beginning of the 21st century.

METHODS

A cross-sectional ecological study was carried out to analyse 9 of the leading specific causes of death in small areas from 15 European cities. Using a hierarchical Bayesian spatial model, we estimated smoothed Standardized Mortality Ratios, relative risks and 95% credible intervals for cause-specific mortality in relation to a socioeconomic deprivation index, separately for men and women.

RESULTS

We detected spatial socioeconomic inequalities for most causes of mortality studied, although these inequalities differed markedly between cities, being more pronounced in Northern and Central-Eastern Europe. In the majority of cities, most of these causes of death were positively associated with deprivation among men, with the exception of prostatic cancer. Among women, diabetes, ischaemic heart disease, chronic liver diseases and respiratory diseases were also positively associated with deprivation in most cities. Lung cancer mortality was positively associated with deprivation in Northern European cities and in Kosice, but this association was non-existent or even negative in Southern European cities. Finally, breast cancer risk was inversely associated with deprivation in three Southern European cities.

CONCLUSIONS

The results confirm the existence of socioeconomic inequalities in many of the main causes of mortality, and reveal variations in their magnitude between different European cities.

Municipal interventions against inequalities in health: The view of their managers

BACKGROUND

European city councils are increasingly developing interventions against health inequalities. There is little knowledge about how they are perceived. This study describes and analyses good practices and challenges for local interventions on inequalities in health through the narratives of European city managers.

METHODS

A qualitative study was conducted. Each participating city (Amsterdam, Barcelona, Cluj-Napoca, Helsinki, Lisbon, London, Madrid, Rotterdam) selected interventions following these criteria: at least 6 months of implementation; an evaluation performed or foreseen; the reduction of health inequalities among their objectives, and only one of the interventions selected could be based on health care. Managers of these local interventions were interviewed following an outline. Eleven individual in-depth interviews describing nine local interventions were obtained. A thematic content analysis was performed.

RESULTS

One or more local interventions against health inequalities were identified in each city. Most relied on quantitative data and were linked to national strategies. Few interventions addressed socio-economic determinants. Health care, employment and education were the main determinants addressed. With variable depth, evidence-base, participation and intersectorality were regular components of the interventions. Half of them targeted the city and half some deprived neighbourhoods. Few interventions had been evaluated. Scarcity of funding and sustainability of the projects were the main perceived barriers by the managers.

CONCLUSIONS

City intervention managers were familiar with health inequalities and concepts as intersectorality, participation and evidence-based action, but others such as socioeconomic aims, gradient approach, evaluation and sustainability were not so widely applied. Managers' capacities and political leadership in governance for health should be reinforced.

Social differences in avoidable mortality between small areas of 15 European cities: an ecological study

Background

Health and inequalities in health among inhabitants of European cities are of major importance for European public health and there is great interest in how different health care systems in Europe perform in the reduction of health inequalities. However, evidence on the spatial distribution of cause-specific mortality across neighbourhoods of European cities is scarce. This study presents maps of avoidable mortality in European cities and analyses differences in avoidable mortality between neighbourhoods with different levels of deprivation.

Methods

We determined the level of mortality from 14 avoidable causes of death for each neighbourhood of 15 large cities in different European regions. To address the problems associated with Standardised Mortality Ratios for small areas we smooth them using the Bayesian model proposed by Besag, York and Mollié. Ecological regression analysis was used to assess the association between social deprivation and mortality.

Results

Mortality from avoidable causes of death is higher in deprived neighbourhoods and mortality rate ratios between areas with different levels of deprivation differ between gender and cities. In most cases rate ratios are lower among women. While Eastern and Southern European cities show higher levels of avoidable mortality, the association of mortality with social deprivation tends to be higher in Northern and lower in Southern Europe.

Conclusions

There are marked differences in the level of avoidable mortality between neighbourhoods of European cities and the level of avoidable mortality is associated with social deprivation. There is no systematic difference in the magnitude of this association between European cities or regions. Spatial patterns of avoidable mortality across small city areas can point to possible local problems and specific strategies to reduce health inequality which is important for the development of urban areas and the well-being of their inhabitants.

Socioeconomic inequalities in mortality in 16 European cities

AIMS

To explore inequalities in total mortality between small areas of 16 European cities for men and women, as well as to analyse the relationship between these geographical inequalities and their socioeconomic indicators.

METHODS

A cross-sectional ecological design was used to analyse small areas in 16 European cities (26,229,104 inhabitants). Most cities had mortality data for a period between 2000 and 2008 and population size data for the same period. Socioeconomic indicators included an index of socioeconomic deprivation, unemployment, and educational level. We estimated standardised mortality ratios and controlled for their variability using Bayesian models. We estimated relative risk of mortality and excess number of deaths according to socioeconomic indicators.

RESULTS

We observed a consistent pattern of inequality in mortality in almost all cities, with mortality increasing in parallel with socioeconomic deprivation. Socioeconomic inequalities in mortality were more pronounced for men than women, and relative inequalities were greater in Eastern and Northern European cities, and lower in some Western (men) and Southern (women) European cities. The pattern of excess number of deaths was slightly different, with greater inequality in some Western and Northern European cities and also in Budapest, and lower among women in Madrid and Barcelona.

CONCLUSIONS

In this study, we report a consistent pattern of socioeconomic inequalities in mortality in 16 European cities. Future studies should further explore specific causes of death, in order to determine whether the general pattern observed is consistent for each cause of death.

Characterization of the immune response to trivalent influenza vaccine in elderly men

This study characterizes the time course of the immune response to influenza vaccine in elderly men. Sixty-two men aged 58 to 91 years (mean, 74.3 years) were vaccinated with trivalent inactivated influenza vaccine in the fall of 1983. Serum hemagglutinin-inhibiting (HAI) antibody titers were measured at various times up to 24 weeks postvaccination. Seroconversion frequencies determined at single times after vaccination were 28 to 46% of subjects, whereas cumulative seroconversion frequencies were greater than or equal to 70%. Eighteen to 28% of seroconversions occurred later than four weeks, and greater than or equal to 68% of those who seroconverted experienced greater than four-fold declines in peak HAI antibody titers by 24 weeks after vaccination. Consequently, 31 to 73% of subjects had HAI antibody titers greater than 40 throughout the study period. Measurement of HAI antibody titers at only one time after vaccination may not adequately reflect the immune response of this population or the degree of protection maintained through the influenza season.

Phenytoin therapy and immune response to influenza vaccine

The effect of long-term phenytoin therapy on the immune response to inactivated influenza vaccine was evaluated. The patients were 31 white men who were receiving long-term phenytoin therapy for seizure disorders and 31 age-matched controls. Prevaccination blood samples were collected, and the patients were vaccinated subcutaneously with 0.5-mL inactivated whole-virion trivalent influenza vaccine. Venous blood samples were collected at 2, 4, 6, 9, 12, and 24 weeks after vaccination and stored at -20 degrees C until analysis. Total serum phenytoin concentrations were measured by fluorescence polarization immunoassay. Immune response was measured by assaying the sera for hemagglutinin-inhibiting antibody to each of the three antigenic strains. Seroconversion was defined as a fourfold or greater increase in serum antibody titer following vaccination. In the phenytoin-treated patients, the mean (+/- S.D.) serum phenytoin concentration before vaccination was 9.9 +/- 6.1 micrograms/mL. Prevaccination geometric mean titers were high enough in both groups to indicate that these patients had been exposed to these or related antigens, and medical records confirmed that some of the patients had been vaccinated the year before. The percent of patients demonstrating seroconversion to each antigen at week 4 was low in both groups, and there were no significant differences between the two groups. The cumulative seroconversion responses observed up to week 24 were also not significantly different. Long-term phenytoin therapy should not affect the efficacy of influenza vaccine in patients who have been previously exposed to infection or vaccination with identical or related strains.