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Abstract Background Spain has been hit hard by COVID-19 since March 2020, especially in its metropolitan areas. We share experiences from Barcelona in measuring socioeconomic inequalities in the incidence of COVID-19 in the different waves, and in implementing coordinated and equity-oriented public health policy responses. Methods We collected daily data on confirmed COVID-19 cases, geocoded the address of residence to assign each case to one of the 73 neighborhoods and 1068 census tracts, and calculated the cumulative incidence of COVID-19 by neighborhood and five income groups (quintiles of census tracts) by sex across four waves of the pandemic. We adjusted hierarchical Bayesian spatial models to obtain the relative risk (RR) of cumulative incidences in each quintile compared with the richest areas. A variety of public health policies implemented to tackle the pandemic and especially these inequalities in COVID-19 incidence and vaccination are selected and described. Results Area-level income inequalities in the incidence of COVID-19 were present at different degree in all four waves. In the second wave (10/1/2020 to 12/6/2020), RR for the poorest income quintile census tracts compared with the richest was 1.43 (95% credible interval-CI-: 1.22–1.67) for men and 1.58 (95% CI: 1.35–1.83) for women. Later, inequalities in vaccination coverage also arose. Equity-oriented policy responses included: “health hotels” or home delivery of basic products for individuals with COVID-19 and without adequate conditions for isolation; new emergency facilities for homeless people, including those with active drug use; mass screening in high incidence areas; contingency plans for nursing homes and schools; adapting community health programs for their early reactivation; digital self-appointment support points and community vaccination days. Conclusion COVID-19 hit Barcelona neighborhoods unequally, with variations between waves. The rapid availability of geolocalized data and by socioeconomic level helped public authorities to implement targeted policies and collaborative interventions for the most vulnerable populations. Further studies would be needed to evaluate their impact.

Abstract 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.

Abstract Background Mortality registries are an essential data source for public health surveillance and for planning and evaluating public policy. Nevertheless, there are still large inequalities in the completeness and quality of mortality registries between and within countries. In Ecuador, there have been few nationwide evaluations of the mortality registry and no evaluations of inequalities between provinces. This kind of analysis is fundamental for strengthening the vital statistics system. Methods Ecological study assessing the completeness, quality and internal consistency of mortality data in the provinces of Ecuador, using 13 years of mortality data (2001–2013). Completeness was assessed using three types of death distribution methods (DDMs), quality by estimating the percentages of garbage codes and deaths with unspecified age or sex in the registered deaths, and internal consistency by estimating the percentage of deaths with reported causes of deaths considered impossible in some age–sex combinations. Finally, we propose a classification of the mortality registry in the studied areas based on completeness and quality. Results Completeness estimates (mean of the three methods used) in the provinces ranged from 21 to 87% in women and from 35 to 89% in men. The percentage of garbage codes in the provinces ranged from 21 to 56% in women and from 25 to 52% in men. Garbage coding was higher in women and in older age groups. The percentage of deaths with unspecified age or sex, and the percentage of deaths with reported causes of deaths considered impossible in some age–sex combinations was low in all the studied areas. The mortality registry could only be classified as acceptable in one area for men and one area for women. Conclusions We found substantial inequalities by sex, geographical areas and age in the completeness and quality of the mortality registry of Ecuador. The findings of this study will be helpful to direct measures to improve Ecuador’s vital statistics system and to generate strategies to reduce bias when using mortality data to analyse health inequalities in the country.

Abstract Background Prior studies have identified a decrease in ischaemic heart disease mortality during the recent economic recession. The Spanish population was severely affected by the Great Recession, however, there is little evidence on its effects on socioeconomic inequalities in ischaemic heart disease mortality. This study examines trends in socioeconomic inequalities in mortality due to ischaemic heart disease (IHD). Methods We used linked census records with mortality registers available from the Basque Country and Barcelona city for population above 25 years, between 2001 and 04, the accelerated economic growth period of 2005–08, and 2009–12, with the last period coinciding with the Great Recession. Applying Poisson models, we calculated relative and absolute indexes of inequalities by education level for each period, age group, gender, and site. Results We found moderate age-adjusted inequalities in IHD with a gradient of increasing rates through less educational level, but no significant evidence of increasing trends in socioeconomic inequalities in IHD mortality, rather an inverted U-shape time trend in some groups below 75 years in relative inequalities. Absolute inequalities decrease in the last period except for women from 50 to 64 years. Conclusions This study shows that the economic crisis has not increased socioeconomic inequalities in IHD mortality in two geographical settings in Spain.

Following the publication of this article [1], the authors reported a typesetting error in Table 1 that caused the columns of the table to be ordered incorrectly, and a typographical error in a sentence in the Conclusions section.

Abstract Background An increase in suicide mortality is often observed in economic recessions. The objective of this study was to analyse trends in socioeconomic inequalities in suicide mortality before and during the economic recession in two geographical settings in Spain. Methods This study analyses inequalities in mortality according to educational level during 3 different time periods based on individual data from the Basque Country and Barcelona city. We analysed suicide mortality data for all residents over 25 years of age from 2001 to 2012. Two periods before the crisis (2001–2004 and 2005–2008) and another during the crisis (2009–2012) were studied. We performed independent analyses for sex, age group, and for the two geographical settings. We fit Poisson regression models to study the relationship between educational level and mortality, and calculated the relative index of inequality (RII) and the slope index of inequality (SII) as comparative measures. Results For men in the Basque Country, all RII values for the three time periods were similar and almost all were greater than 2; in Barcelona the RII values were generally lower. The SII values for Barcelona tended to decrease over time, whereas in the Basque Country they showed a U-shaped pattern. Among women aged 25–44 years we found an association between educational level and suicide mortality during the first time period; however, we found no clear association for other age groups or time periods. Conclusion This study within two geographical settings in Spain shows that trends in inequalities in suicide mortality according to educational level remained stable among men before and during the economic recession.

Abstract Background In Spain, several ecological studies have analyzed trends in socioeconomic inequalities in mortality from all causes in urban areas over time. However, the results of these studies are quite heterogeneous finding, in general, that inequalities decreased, or remained stable. Therefore, the objectives of this study are: (1) to identify trends in geographical inequalities in all-cause mortality in the census tracts of 33 Spanish cities between the two periods 1996–1998 and 2005–2007; (2) to analyse trends in the relationship between these geographical inequalities and socioeconomic deprivation; and (3) to obtain an overall measure which summarises the relationship found in each one of the cities and to analyse its variation over time. Methods Ecological study of trends with 2 cross-sectional cuts, corresponding to two periods of analysis: 1996–1998 and 2005–2007. Units of analysis were census tracts of the 33 Spanish cities. A deprivation index calculated for each census tracts in all cities was included as a covariate. A Bayesian hierarchical model was used to estimate smoothed Standardized Mortality Ratios (sSMR) by each census tract and period. The geographical distribution of these sSMR was represented using maps of septiles. In addition, two different Bayesian hierarchical models were used to measure the association between all-cause mortality and the deprivation index in each city and period, and by sex: (1) including the association as a fixed effect for each city; (2) including the association as random effects. In both models the data spatial structure can be controlled within each city. The association in each city was measured using relative risks (RR) and their 95 % credible intervals (95 % CI). Results For most cities and in both sexes, mortality rates decline over time. For women, the mortality and deprivation patterns are similar in the first period, while in the second they are different for most cities. For men, RRs remain stable over time in 29 cities, in 3 diminish and in 1 increase. For women, in 30 cities, a non-significant change over time in RR is observed. However, in 4 cities RR diminishes. In overall terms, inequalities decrease (with a probability of 0.9) in both men (RR = 1.13, 95 % CI = 1.12–1.15 in the 1st period; RR = 1.11, 95 % CI = 1.09–1.13 in the 2nd period) and women (RR = 1.07, 95 % CI = 1.05–1.08 in the 1st period; RR = 1.04, 95 % CI = 1.02–1.06 in the 2nd period). Conclusions In the future, it is important to conduct further trend studies, allowing to monitoring trends in socioeconomic inequalities in mortality and to identify (among other things) temporal factors that may influence these inequalities.

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