Background Despite a concerted policy effort in Europe, social inequalities in health are a persistent problem. Developing a standardised measure of socioeconomic level across Europe will improve the understanding of the underlying mechanisms and causes of inequalities. This will facilitate developing, implementing and assessing new and more effective policies, and will improve the comparability and reproducibility of health inequality studies among countries. This paper presents the extension of the European Deprivation Index (EDI), a standardised measure first developed in France, to four other European countries—Italy, Portugal, Spain and England, using available 2001 and 1999 national census data. Methods and results The method previously tested and validated to construct the French EDI was used: first, an individual indicator for relative deprivation was constructed, defined by the minimal number of unmet fundamental needs associated with both objective (income) poverty and subjective poverty. Second, variables available at both individual (European survey) and aggregate (census) levels were identified. Third, an ecological deprivation index was constructed by selecting the set of weighted variables from the second step that best correlated with the individual deprivation indicator. Conclusions For each country, the EDI is a weighted combination of aggregated variables from the national census that are most highly correlated with a country-specific individual deprivation indicator. This tool will improve both the historical and international comparability of studies, our understanding of the mechanisms underlying social inequalities in health and implementation of intervention to tackle social inequalities in health.

Background Mortality increases during heat waves have been reported worldwide. The magnitude of these increases can vary within regions according to sociodemographic and urban landscape characteristics. The objectives of this study were to explore this variation and its determinants, and to identify the most heat-vulnerable areas by mapping heat vulnerability. Methods We conducted a time-stratified case-crossover analysis using daily mortality in the Barcelona metropolitan area during the warm seasons of 1999–2006. Temperature data on the date of death were assigned to each individual, which were assigned to their census tract of residence. Eight census tract-level variables on socioeconomic or built environment characteristics were obtained from the census. Residence surrounding greenness was obtained from satellite data. The relative risk (RR) of mortality after three consecutive hot days (defined as those exceeding the 95th percentile of maximum temperature) was calculated via conditional logistic regression. Effect modification was examined by including interaction terms. Results Analyses were based on 52 806 deaths. The effect of three consecutive hot days was a 30% increase in all-cause mortality (RR=1.30, 95% CI 1.24 to 1.38). Heterogeneity of this effect was observed across census tracts. The effect of heat on mortality was higher in the census tracts with a large percentage of old buildings (RR=1.21, 95% CI 1.00 to 1.46), manual workers (RR=1.25, 95% CI 0.96 to 1.64) and residents perceiving little surrounding greenness (RR=1.29, 95% CI 1.01 to 1.65). After three consecutive hot days, mortality doubled in the most heat-vulnerable census tracts. Conclusions Sociodemographic and urban landscape characteristics are associated to mortality risk during heat waves and are useful to build heat vulnerability maps.

Objetivo: Examinar las diferencias entre la Razón de Prevalencia (RP) y la Odds Ratio (OR) en un estudio transversal y proporcionar herramientas para calcular la RP usando dos paquetes estadísticos ampliamente utilizados en la investigación de adicciones (STATA y R). Métodos: Se utilizaron los datos de un estudio transversal de 41.263 participantes de 16 países de Europa que participaron en la Encuesta sobre Salud y Envejecimiento en Europa (SHARE). La variable dependiente, consumo de riesgo de alcohol, se calculó a partir del Alcohol Use Disorders Identification Test – Consumption (AUDIT-C). Como principal variable independiente se utilizó el género. Otras variables fueron la edad, el nivel de estudios y el país de residencia. Las RP de consumo de riesgo de alcohol entre hombres y mujeres se estimaron a partir del método de Mantel Haenzel, de modelos de regresión log-binomial y de modelos de regresión de Poisson con varianza robusta. Estas estimaciones fueron comparadas con las OR obtenidas a partir de modelos de regresión logística. Resultados: La prevalencia de consumidores de riesgo de alcohol varía según país. En general los hombres tienen un mayor consumo de riesgo que las mujeres [RP=1.43 (1.38-1.47)]. La RP estimada no varía, independientemente del método o paquete estadístico utilizado. Sin embargo, dependiendo de la prevalencia del consumo de riesgo del país, la OR entre los consumidores de riesgo y el género sobrestima la RP. Conclusiones: En estudios transversales en los que se comparan distintos países con diferente prevalencia de una determinada enfermedad o condición es recomendable utilizar la RP en lugar de la OR.

Background: The objective of this paper is to analyze social inequalities in COVID-19 incidence, stratified by age, sex, geographical area, and income in Barcelona during the first two waves of the pandemic. Methods: We collected data on COVID-19 cases confirmed by laboratory tests during the first two waves of the pandemic (1 March to 15 July and 16 July to 30 November, 2020) in Barcelona. For each wave and sex, we calculated smooth cumulative incidence by census tract using a hierarchical Bayesian model. We analyzed income inequalities in the incidence of COVID-19, categorizing the census tracts into quintiles based on the income indicator. Results: During the two waves, women showed higher COVID-19 cumulative incidence under 64 years, while the trend was reversed after that threshold. The incidence of the disease was higher in some poor neighborhoods. The risk ratio (RR) increased in the poorest groups compared to the richest ones, mainly in the second wave, with RR being 1.67 (95% Credible Interval-CI-: 1.41–1.96) in the fifth quintile income group for men and 1.71 (95% CI: 1.44–1.99) for women. Conclusion: Our results indicate the existence of inequalities in the incidence of COVID-19 in an urban area of Southern Europe.

A large body of literature shows the link between inadequate housing conditions and poor physical and mental health. The aim of this paper is to summarize the research on the impact of local housing policies on health inequalities, focusing on the issues of access to housing and fuel poverty as studied in the SOPHIE project. Our case studies in Spain showed that people facing housing insecurity, experienced intense levels of mental distress. We found that access to secure and adequate housing can improve the health of these populations, therefore, public policies that address housing instability and their consequences are urgently needed. Housing conditions related to fuel poverty are associated with poorer health and are unevenly distributed across Europe. We found possible positive effects of façade insulation interventions on cold-related mortality in women living in social housing; but not in men. Policies on housing energy efficiency can reduce the health consequences of fuel poverty, but need to be free to users, target the most vulnerable groups and be adaptable to their needs.