Spatial Bayesian distributed lag non-linear models (SB-DLNM) for small-area exposure-lag-response epidemiological modelling.

BACKGROUND: Distributed lag non-linear models (DLNMs) are the reference framework for modelling lagged non-linear associations. They are usually used in large-scale multi-location studies. Attempts to study these associations in small areas either did not include the lagged non-linear effects, did not allow for geographically-varying risks or downscaled risks from larger spatial units through socioeconomic and physical meta-predictors when the estimation of the risks was not feasible due to low statistical power. METHODS: Here we proposed spatial Bayesian DLNMs (SB-DLNMs) as a new framework for the estimation of reliable small-area lagged non-linear associations, and demonstrated the methodology for the case study of the temperature-mortality relationship in the 73 neighbourhoods of the city of Barcelona. We generalized location-independent DLNMs to the Bayesian framework (B-DLNMs), and extended them to SB-DLNMs by incorporating spatial models in a single-stage approach that accounts for the spatial dependence between risks. RESULTS: The results of the case study highlighted the benefits of incorporating the spatial component for small-area analysis. Estimates obtained from independent B-DLNMs were unstable and unreliable, particularly in neighbourhoods with very low numbers of deaths. SB-DLNMs addressed these instabilities by incorporating spatial dependencies, resulting in more plausible and coherent estimates and revealing hidden spatial patterns. In addition, the Bayesian framework enriches the range of estimates and tests that can be used in both large- and small-area studies. CONCLUSIONS: SB-DLNMs account for spatial structures in the risk associations across small areas. By modelling spatial differences, SB-DLNMs facilitate the direct estimation of non-linear exposure-response lagged associations at the small-area level, even in areas with as few as 19 deaths. The manuscript includes an illustrative code to reproduce the results, and to facilitate the implementation of other case studies by other researchers.

Adapting Schools to Climate Change with Green, Blue, and Grey Measures in Barcelona: Study Protocol of a Mixed-Method Evaluation.

Under the framework of the Urban Innovative Actions program of the European Commission, in 2020, 11 primary schools in Barcelona were transformed into climate shelters by implementing green, blue, and grey measures. Schoolyards were also opened to the local community to be used during non-school periods. Here we present the study protocol of a mixed-method approach to evaluate the effectiveness of the interventions in terms of improving environmental quality and health for users. We evaluated school level through the following: (1) quantitative pre-post quasi-experimental study, and (2) qualitative evaluation. The quantitative study included measures of (a) environmental variables (collected via low-cost and non-low-cost sensors), (b) students' health and well-being (collected via health questionnaires, attention levels test, and systematic observations), and (c) teachers' health and well-being (collected via thermal comfort measurements and health questionnaires). The qualitative methods evaluated the perceptions about the effects of the interventions among students (using Photovoice) and teachers (through focus groups). The impact of the interventions was assessed at community level during summer non-school periods through a spontaneous ethnographic approach. Data collection started in August 2019 and ended in July 2022. The evaluation provides the opportunity to identify those solutions that worked and those that need to be improved for future experiences, as well as improve the evaluation methodology and replication for these kinds of interventions.

Association of drought conditions and heavy rainfalls with the quality of drinking water in Barcelona (2010-2022).

BACKGROUND: Climate change influences the incidence and scope of climate extreme events that affect communities and the environment around the world. In an urban context such as Barcelona, these climate extremes can have a negative impact on drinking water quality. The worsening of drinking water quality can have important repercussions on human health, leading to the appearance of different diseases. OBJECTIVE: Investigate the association between climate extremes, in particular heavy rainfall events and drought conditions, and the drinking water quality in the city of Barcelona from 2010 to 2022. METHODS: We conducted a daily retrospective time-series study using data covering 13 years of daily monitoring of conductivity, nickel, turbidity and trihalomethanes parameters of raw water in the Llobregat River catchment area and treated water in the Drinking Water Treatment Plant (DWTP) Sant Joan Despí. We used river flow as a proxy for drought conditions and heavy rainfall events. We analyzed short-term associations between river flow rate and quality parameters in raw and treated water using generalized linear regression with distributed lag-non-linear models (DLNM). RESULTS: A low flow, as an indicator of drought condition or low rainfall, was significantly associated with an increase in conductivity in raw water and nickel in both raw and treated water. A high flow, as an indicator of heavy rainfall events, was significantly associated with an increase of turbidity in raw water, and a decrease in all other quality parameters. IMPACT STATEMENT: This study provides novel evidence that climate extremes have an impact on the quality of drinking water in urban areas with a Mediterranean climate. The findings of this study are significant because they suggest that as the frequency and intensity of climate extremes increase due to climate change, there will be further challenges in managing and treating drinking water, which could have a detrimental effect on public health. This study serves as an important reminder of the need to strengthen and accelerate adaptation actions in water management to ensure an adequate supply of drinking water that protects the people's health.

Socioeconomic inequalities in COVID-19 incidence during the first six waves in Barcelona.

BACKGROUND: The emergence of SARS-CoV-2 affected urban areas. In Barcelona, six waves of COVID-19 hit the city between March 2020 and March 2022. Inequalities in the incidence of COVID-19 have been described. However, no studies have examined the daily trends of socioeconomic inequalities and how they changed during the different phases of the pandemic. The aim of this study is to analyse the dynamic socioeconomic inequalities in the incidence of COVID-19 during the six waves in Barcelona. METHODS: We examined the proportion of daily cases observed in the census tracts in the lower income tercile compared with the proportion of daily cases observed in the sum of the lower and higher income terciles. Daily differences in these proportions were assessed as a function of the epidemic waves, sex, age group, daily incidence and daily change in the incidence. A logistic regression model with an autoregressive term was used for statistical analysis. RESULTS: A time-dynamic effect was found for socioeconomic inequalities in the incidence of COVID-19. In fact, belonging to a lower-income area changed from being a risk factor (Waves 1, 2, 4 and 5) to being a protective factor in the sixth wave of the pandemic. Age also had a significant effect on incidence, which also changed over the different waves of the pandemic. Finally, the lower-income areas showed a comparatively lower incidence during the ascending phase of the epidemic waves. CONCLUSION: Socioeconomic inequalities in COVID-19 changed by wave, age group and wave phase.

A City Surveillance System for Social Health Inequalities: The Case of Barcelona.

INTRODUCTION: In the past, health inequalities were not prioritised in the political agenda of Barcelona. The change of city government (2015) was an opportunity to develop a Surveillance System for Social Health Inequalities in the city, which is described in this article. METHODS: The design of the Surveillance System formed part of the Joint Action for Health Equity in Europe (JAHEE), funded by the European Union. Various steps were considered by the experts to set up the System: define its objectives, target population, domains and indicators, and sources of information; perform data analysis; implement and disseminate the system; define the evaluation; and perform regular data updates. RESULTS: The System considers the following domains: social determinants of health, health-related with behaviours, use of healthcare, and health outcomes, and includes eight indicators. As axes of inequality, the experts chose sex, age, social class, country of origin, and geographical area. The Surveillance System for Social Health Inequalities is presented on a website including different types of figures. CONCLUSION: The methodology used to implement the Surveillance System can be used to implement similar systems in other urban areas around the world.

Air Pollution and Birth Outcomes: Health Impact and Economic Value Assessment in Spain.

Air pollution is considered an ongoing major public health and environmental issue around the globe, affecting the most vulnerable, such as pregnant women and fetuses. The aim of this study is to estimate the health impact and economic value on birth outcomes, such as low birthweight (LBW), preterm birth (PTB), small for gestational age (SGA), attributable to a reduction of PM10 levels in Spain. Reduction based on four scenarios was implemented: fulfillment of WHO guidelines and EU limits, and an attributable reduction of 15% and 50% in annual PM10 levels. Retrospective study on 288,229 live-born singleton children born between 2009-2010, using data from Spain Birth Registry Statistics database, as well as mean PM10 mass concentrations. Our finding showed that a decrease in annual exposure to PM10 appears to be associated with a decrease in the annual cases of LBW, SGA and PTB, as well as a reduction in hospital cost attributed to been born with LBW. Improving pregnancy outcomes by reducing the number of LBW up to 5% per year, will result in an estimate associated monetary saving of 50,000 to 7,000,000 euros annually. This study agrees with previous literature and highlights the need to implement, and ensure compliance with, stricter policies that regulate the maximum exposure to outdoor PM permitted in Spain, contributing to decreased environmental health risk, especially negative birth outcomes.

Estimating ambient air pollution mortality and disease burden and its economic cost in Barcelona.

BACKGROUND: The new WHO air quality guidelines indicate that the air pollution disease burden is greater than previously reported. We aimed to estimate the air pollution disease burden and its economic cost in Barcelona to inform local action. METHODS: We used a quantitative health impact assessment to estimate the non-accidental mortality and incidence of childhood asthma and lung cancer attributable to long-term air pollution exposure in the city of Barcelona (Spain) in 2018-2019. We used the population weighted mean of PM2.5 and NO2 assigned at the geocoded address during the study period and the 2021 WHO air quality guidelines as counterfactual scenario to estimate new annual cases attributable to each pollutant separately and combined. We estimated the social cost of attributable deaths and the health care cost of childhood asthma and lung cancer attributable cases. We also estimated attributable mortality by city district and the mortality avoidable by achieving the WHO air quality interim targets. RESULTS: Mean exposure was 17 µg/m3 for PM2.5 and 39 µg/m3 for NO2. Total combined air pollution attributable mortality was 13% (95%CI = 9%-17%), corresponding to 1,886 deaths (95%CI = 1,296-2,571) and a social cost of €1,292 million (95%CI = 888-1,762) annually. Fifty-one percent (95%CI = 21%-71%) and 17% (95%CI = 7%-29%) of new cases of childhood asthma and lung cancer were attributable to air pollution with a health care cost of €4.3 and €2.7 million, respectively. Achieving the first unmet WHO air quality interim targets for PM2.5 and for NO2 would avoid 410 deaths and €281 million annually. CONCLUSION: Air pollution in Barcelona represents a huge disease and economic burden, which is greater than previous estimates. Much stronger measures to reduce PM2.5 and NO2 levels are urgently needed. Until the WHO air quality guidelines are met in the city, achieving each WHO air quality interim targets would avoid hundreds of deaths each year.

Neighbourhood income inequalities in mental health in Barcelona 2001-2016: a Bayesian smoothed estimate / Desigualdades de renta por barrios en salud mental en Barcelona 2001-2016: una estimación de alisado bayesiano

Objective: Obtaining reliable health estimates at the small area level (such as neighbourhoods) using survey data usually poses the problem of small sample sizes. To overcome this limitation, we explored smoothing techniques in order to estimate poor mental health prevalence at the neighbourhood level and analyse its profile by income in Barcelona city (Spain). Method: A Bayesian smoothing model with a logit-normal transformation was applied to four repeated cross-sectional waves of the Barcelona health survey for 2001, 2006, 2011 and 2016. Mental health status was identified from the 12-item General Health Questionnaire. Income inequalities were analysed with neighbourhood income in quantiles for each year and trends in the pooled analysis. Results: The prevalence of poor mental health ranged from 14.6% in 2001 to 18.9% in 2016. The yearly difference between neighbourhoods was 12.4% in 2001, 16.7% in 2006, 14.2% in 2011, and 20.0% in 2016. The odds ratio and 95% credible interval (95%CI) of experiencing poor mental health was 1.40 times higher (95%CI: 1.02-1.91) in less advantaged neighbourhoods than in more advantaged neighbourhoods in 2001, 1.61 times higher (95%CI: 1.01-2.59) in 2006 and 2.31 times higher (95%CI: 1.57-3.40) in 2016. Conclusions: This study shows that the Bayesian smoothed techniques allows detection of inequalities in health in neighbourhoods and monitoring of interventions against them. In Barcelona, mental health problems are more prevalent in low-income neighbourhoods and raised in 2016. (AU)

Objetivo: Obtener estimadores de salud en áreas pequeñas (como los barrios) utilizando datos de encuestas supone hacer frente al problema de insuficiente tamaño muestral. Para superar esta limitación exploramos técnicas de alisado con el fin de estimar la prevalencia de mala salud mental a nivel de barrio y analizar su patrón por renta en la ciudad de Barcelona (España). Método: Se aplicó un modelo de alisado bayesiano con transformación logística-normal a cuatro muestras transversales repetidas de la Encuesta de Salud de Barcelona para los años 2001, 2006, 2011 y 2016. La salud mental fue identificada con el Cuestionario General de Salud de 12-items. Las desigualdades de ingreso se analizaron por cuantiles de la renta por barrio para cada año y las tendencias en el análisis conjunto. Resultados: La prevalencia de mala salud mental oscila entre el 14,6% en 2001 y el 18,9% en 2016. La diferencia entre barrios fue del 12,4% en 2001, del 16,7% en 2006, del 14,2% en 2011 y del 20,0% en 2016. La odds ratio y el intervalo creíble al 95% (IC95%) de experimentar mala salud mental fue 1,4 veces superior (IC95%: 1,02-1,91) en los barrios menos aventajados respecto de los más aventajados en 2001, de 1,61 (IC95%: 1,01-2,59) en 2006 y de 2,31 (IC95%: 1,57-3,40) en 2016. Conclusiones: Este estudio muestra que las técnicas de alisado bayesiano permiten la detección de desigualdades en salud a nivel de barrios para su monitorización e intervención con el fin de reducirlas. En Barcelona, los problemas de salud mental son más prevalentes en los barrios de menor renta y se incrementaron en 2016. (AU)

Climate Change and Health in Urban Areas with a Mediterranean Climate: A Conceptual Framework with a Social and Climate Justice Approach.

The consequences of climate change are becoming increasingly evident and highlight the important interdependence between the well-being of people and ecosystems. Although climate change is a global phenomenon, its causes and consequences vary dramatically across territories and population groups. Among settings particularly susceptible to health impacts from climate change are cities with a Mediterranean climate. Here, impacts will put additional pressure on already-stressed ecosystems and vulnerable economies and societies, increasing health inequalities. Therefore, this article presents and discusses a conceptual framework for understanding the complex relationship between climate change and health in the context of cities with Mediterranean climate from a social and climate justice approach. The different elements that integrate the conceptual framework are: (1) the determinants of climate change; (2) its environmental and social consequences; (3) its direct and indirect impacts on health; and (4) the role of mitigation and adaptation policies. The model places special emphasis on the associated social and health inequalities through (1) the recognition of the role of systems of privilege and oppression; (2) the distinction between structural and intermediate determinants of climate change at the root of health inequalities; (3) the role of individual and collective vulnerability in mediating the effects of climate change on health; and (4) the need to act from a climate justice perspective to reverse health inequities.

Neighbourhood income inequalities in mental health in Barcelona 2001-2016: a Bayesian smoothed estimate.

OBJECTIVE: Obtaining reliable health estimates at the small area level (such as neighbourhoods) using survey data usually poses the problem of small sample sizes. To overcome this limitation, we explored smoothing techniques in order to estimate poor mental health prevalence at the neighbourhood level and analyse its profile by income in Barcelona city (Spain). METHOD: A Bayesian smoothing model with a logit-normal transformation was applied to four repeated cross-sectional waves of the Barcelona health survey for 2001, 2006, 2011 and 2016. Mental health status was identified from the 12-item General Health Questionnaire. Income inequalities were analysed with neighbourhood income in quantiles for each year and trends in the pooled analysis. RESULTS: The prevalence of poor mental health ranged from 14.6% in 2001 to 18.9% in 2016. The yearly difference between neighbourhoods was 12.4% in 2001, 16.7% in 2006, 14.2% in 2011, and 20.0% in 2016. The odds ratio and 95% credible interval (95%CI) of experiencing poor mental health was 1.40 times higher (95%CI: 1.02-1.91) in less advantaged neighbourhoods than in more advantaged neighbourhoods in 2001, 1.61 times higher (95%CI: 1.01-2.59) in 2006 and 2.31 times higher (95%CI: 1.57-3.40) in 2016. CONCLUSIONS: This study shows that the Bayesian smoothed techniques allows detection of inequalities in health in neighbourhoods and monitoring of interventions against them. In Barcelona, mental health problems are more prevalent in low-income neighbourhoods and raised in 2016.

Effectiveness of an Energy-Counseling Intervention in Reducing Energy Poverty: Evidence from a Quasi-Experimental Study in a Southern European City.

Energy poverty is a serious social problem with well-known adverse health consequences. This problem has been addressed mainly through improvements in the energy efficiency of housing. Still, little is known about the effects of information-based measures on energy poverty and their impacts on health. A quasi-experimental study was implemented to assess the effectiveness of an energy-counseling home visit intervention targeting the vulnerable population in a southern European city, Barcelona, in alleviating energy poverty and improving health. The intervention had beneficial impacts on keeping homes at an adequate indoor temperature and reducing primary care visits. No effects were found on self-perceived health or self-reported anxiety and depression. After the intervention, participants reported a decrease in arrears on utility bills, but less pronounced than in the comparison group. In conclusion, the study showed that information-based measures lead to psychosocial gains and reduced healthcare use. Nevertheless, the impact of these measures could be enhanced by combining them with policies and programmes that address the structural determinants of energy poverty.

Multi-level policy responses to tackle socioeconomic inequalities in the incidence of COVID-19 in a European urban area.

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.

Sociodemographic determinants of intraurban variations in COVID-19 incidence: the case of Barcelona.

BACKGROUND: Intraurban sociodemographic risk factors for COVID-19 have yet to be fully understood. We investigated the relationship between COVID-19 incidence and sociodemographic factors in Barcelona at a fine-grained geography. METHODS: This cross-sectional ecological study is based on 10 550 confirmed cases of COVID-19 registered during the first wave in the municipality of Barcelona (population 1.64 million). We considered 16 variables on the demographic structure, urban density, household conditions, socioeconomic status, mobility and health characteristics for 76 geographical units of analysis (neighbourhoods), using a lasso analysis to identify the most relevant variables. We then fitted a multivariate Quasi-Poisson model that explained the COVID-19 incidence by neighbourhood in relation to these variables. RESULTS: Neighbourhoods with: (1) greater population density, (2) an aged population structure, (3) a high presence of nursing homes, (4) high proportions of individuals who left their residential area during lockdown and/or (5) working in health-related occupations were more likely to register a higher number of cases of COVID-19. Conversely, COVID-19 incidence was negatively associated with (6) percentage of residents with post-secondary education and (7) population born in countries with a high Human Development Index. CONCLUSION: Like other historical pandemics, the incidence of COVID-19 is associated with neighbourhood sociodemographic factors with a greater burden faced by already deprived areas. Because urban social and health injustices already existed in those geographical units with higher COVID-19 incidence in Barcelona, the current pandemic is likely to reinforce both health and social inequalities, and urban environmental injustice all together.

Socioeconomic Inequalities in Chronic Liver Diseases and Cirrhosis Mortality in European Urban Areas before and after the Onset of the 2008 Economic Recession.

OBJECTIVE: To analyse the trends in chronic liver diseases and cirrhosis mortality, and the associated socioeconomic inequalities, in nine European cities and urban areas before and after the onset of the 2008 financial crisis. METHODS: This is an ecological study of trends in three periods of time: two before (2000-2003 and 2004-2008), and one after (2009-2014) the onset of the economic crisis. The units of analysis were the geographical areas of nine cities or urban areas in Europe. We analysed chronic liver diseases and cirrhosis standardised mortality ratios, smoothing them with a hierarchical Bayesian model by each city, area, and sex. An ecological regression model was fitted to analyse the trends in socioeconomic inequalities, and included the socioeconomic deprivation index, the period, and their interaction. RESULTS: In general, chronic liver diseases and cirrhosis mortality rates were higher in men than in women. These rates decreased in all cities during the financial crisis, except among men in Athens (rates increased from 8.50 per 100,000 inhabitants during the second period to 9.42 during the third). Socioeconomic inequalities in chronic liver diseases and cirrhosis mortality were found in six cities/metropolitan areas among men, and in four among women. Finally, in the periods studied, such inequalities did not significantly change. However, among men they increased in Turin and Barcelona and among women, several cities had lower inequalities in the third period. CONCLUSIONS: There are geographical socioeconomic inequalities in chronic liver diseases and cirrhosis mortality, mainly among men, that did not change during the 2008 financial crisis. These results should be monitored in the long term.

The Association of Energy Poverty with Health and Wellbeing in Children in a Mediterranean City.

Children have been identified as being particularly vulnerable to energy poverty (EP), but little empirical research has addressed the effect of EP on children's health and wellbeing, especially in southern Europe. In this work we aimed to provide an in-depth description of the distribution of EP by sociodemographic, socioeconomic and housing characteristics, as well as to analyse the association between EP and health and wellbeing in children in Barcelona. We performed a cross-sectional study using data from the Barcelona Health Survey for 2016 (n = 481 children under 15 years). We analysed the association between EP and health outcomes through prevalence differences and prevalence ratios (PR) and their 95% confidence interval (CI), using Poisson regression models with robust variance. In Barcelona, 10.6% of children were living in EP and large inequalities were found by sociodemographic, socioeconomic and housing characteristics. EP was strongly associated with poor health in children (PR (95% CI): 7.70 (2.86, 20.72)). Living in EP was also associated with poor mental health (PR (95% CI): 2.46 (1.21, 4.99)) and with more cases of asthma (PR (95% CI): 4.19 (1.47, 11.90)) and overweight (PR (95% CI): 1.50 (1.05, 2.15)) in children. It is urgent to develop specific measures to avoid such serious and unfair health effects on children.

Geographical Variability in Mortality in Urban Areas: A Joint Analysis of 16 Causes of Death.

The geographical distribution of mortality has frequently been studied. Nevertheless, those studies often consider isolated causes of death. In this work, we aim to study the geographical distribution of mortality in urban areas, in particular, in 26 Spanish cities. We perform an overall study of 16 causes of death, considering that their geographical patterns could be dependent and estimating the dependence between the causes of death. We study the deaths in these 26 cities during the period 1996-2015 at the census tract level. A multivariate disease mapping model is used in order to solve the potential small area estimation problems that these data could show. We find that most of the geographical patterns found show positive correlations. This suggests the existence of a transversal geographical pattern, common to most causes of deaths, which determines those patterns to a higher/lower extent depending on each disease. The causes of death that exhibit that underlying pattern in a more prominent manner are chronic obstructive pulmonary disease (COPD), lung cancer, and cirrhosis for men and cardiovascular diseases and dementias for women. Such findings are quite consistent for most of the cities in the study. The high positive correlation found between geographical patterns reflects the existence of both high and low-risk areas in urban settings, in general terms for nearly all the causes of death. Moreover, the high-risk areas found often coincide with neighborhoods known for their high deprivation. Our results suggest that dependence among causes of death is a key aspect to be taken into account when mapping mortality, at least in urban contexts.

Índice de privación en España por sección censal en 2011 / Deprivation index by enumeration district in Spain, 2011

Objetivo: Presentar la metodología seguida en el diseño y la implementación de un índice de privación por sección censal, y describir la situación socioeconómica en España en 2011. Método: La unidad de análisis fue la sección censal (N=35.960). Los datos proceden del Censo de Población y Viviendas de 2011. Teniendo en cuenta el carácter muestral del censo y las limitaciones normativas de confidencialidad de datos, las variables se calcularon indirectamente usando los complementarios de las variables disponibles. Se efectuaron comprobaciones para asegurar su fiabilidad. En la selección de indicadores se consideró la comparabilidad con el índice MEDEA y se exploró la incorporación de nueva información. Se elaboró un índice de privación mediante análisis de componentes principales. Se realizó un análisis de sensibilidad del índice en ámbitos urbanos y en el resto de los territorios. Resultados: Con la información censal se elaboraron 22 indicadores para 35.917 secciones censales. El índice de privación se basó en seis indicadores: población trabajadora manual, población asalariada eventual, desempleo, personas de 16 y más años y de 16 a 29 años con instrucción insuficiente, y viviendas principales sin acceso a Internet. El mapa de España muestra un eje decreciente de privación de suroeste a nordeste. Conclusiones: Se ha aprovechado sistemáticamente la información socioeconómica del censo de 2011 por sección censal. El índice elaborado, similar al MEDEA, facilitará el estudio actualizado de las desigualdades en salud para toda España después de la crisis económica iniciada en 2008. (AU)

Objective: To present the methodology used in the design and implementation of a deprivation index by enumeration district, and to describe the socioeconomic situation of Spain in 2011.Method: The unit of analysis was the enumeration district (N=35,960). Data came from the 2011 Population and Housing Census of Spain. Given both the sampling nature of the Census and the regulatory limitations of data confidentiality, variables were calculated indirectly by using the complement of the available variables. Checks were made to ensure reliability. The selection of the indicators took into account comparability with the MEDEA index. The inclusion of additional information was explored. A deprivation index was built using Principal Component Analysis. Sensitivity analysis of the index was performed for urban areas and the rest of the regions. Results: Using the census information, 22 indicators were calculated for 35,917 enumeration districts. The deprivation index was based on six indicators: manual and temporary workers, unemployment, insufficient education overall and in young people (aged 16 to 29 years), and dwellings without access to the internet. The map of Spain shows a gradient of decreasing deprivation from south-west to north-east. Conclusions: The socioeconomic information of the 2011 census by enumeration district was used systematically. The drafted index, similar to the MEDEA, will facilitate the updated study of health inequalities for Spain overall following the economic recession that began in 2008. (AU)

Energy poverty and health: Trends in the European Union before and during the economic crisis, 2007-2016.

The aim of this study is to analyse the time trends in the European Union (EU) before and during the economic crisis in 1) the energy poverty (EP) prevalence; 2) the association between EP and health and 3) the impact of EP on health. We analyse trends among women and men in two EU macro regions, defined by a novel index of structural vulnerability to EP. The study shows how EP and its impact on health worsened during the economic crisis and identifies groups at higher risk such as women and people living in Mediterranean and Eastern European countries, which have been found to be countries with higher structural vulnerability to EP.

Socioeconomic Inequalities in COVID-19 in a European Urban Area: Two Waves, Two Patterns.

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.

[Deprivation index by enumeration district in Spain, 2011]. / Índice de privación en España por sección censal en 2011.

OBJECTIVE: To present the methodology used in the design and implementation of a deprivation index by enumeration district, and to describe the socioeconomic situation of Spain in 2011. METHOD: The unit of analysis was the enumeration district (N=35,960). Data came from the 2011 Population and Housing Census of Spain. Given both the sampling nature of the Census and the regulatory limitations of data confidentiality, variables were calculated indirectly by using the complement of the available variables. Checks were made to ensure reliability. The selection of the indicators took into account comparability with the MEDEA index. The inclusion of additional information was explored. A deprivation index was built using Principal Component Analysis. Sensitivity analysis of the index was performed for urban areas and the rest of the regions. RESULTS: Using the census information, 22 indicators were calculated for 35,917 enumeration districts. The deprivation index was based on six indicators: manual and temporary workers, unemployment, insufficient education overall and in young people (aged 16 to 29 years), and dwellings without access to the internet. The map of Spain shows a gradient of decreasing deprivation from south-west to north-east. CONCLUSIONS: The socioeconomic information of the 2011 census by enumeration district was used systematically. The drafted index, similar to the MEDEA, will facilitate the updated study of health inequalities for Spain overall following the economic recession that began in 2008.