Social inequalities and COVID-19 mortality between neighborhoods of Bariloche city, Argentina.

BACKGROUND: The COVID-19 pandemic has shown how intraurban inequalities are likely to reinforce health and social inequalities. Studies at small area level help to visualize social inequialities hidden in large areas as cities or regions. AIM: To describe the spatial patterning of COVID-19 death rates in neighborhoods of the medium-sized city of Bariloche, Argentina, and to explore its relationship with the socioeconomic characteristics of neighborhoods. METHODS: We conducted an ecological study in Bariloche, Argentina. The outcome was counts of COVID-19 deaths between June 2020 and May 2022 obtained from the surveillance system and georeferenced to neighborhoods. We estimated crude- and age-adjusted death rates by neighborhood using a Bayesian approach through a Poisson regression that accounts for spatial-autocorrelation via Conditional Autoregressive (CAR) structure. We also analyzed associations of age-adjusted death rates with area-level socioeconomic indicators. RESULTS: Median COVID-19 death rate across neighborhoods was 17.9 (10th/90th percentile of 6.3/35.2) per 10,000 inhabitants. We found lower age-adjusted rates in the city core and western part of the city. The age-adjusted death rate in the most deprived areas was almost double than in the least deprived areas, with an education-related relative index of inequality (RII) of 2.14 (95% CI 1.55 to 2.96). CONCLUSION: We found spatial heterogeneity and intraurban variability in age-adjusted COVID-19 death rates, with a clear social gradient, and a higher burden in already deprived areas. This highlights the importance of studying inequalities in health outcomes across small areas to inform placed-based interventions.

Detecting early signals of COVID-19 outbreaks in 2020 in small areas by monitoring healthcare utilisation databases: first lessons learned from the Italian Alert_CoV project.

BackgroundDuring the COVID-19 pandemic, large-scale diagnostic testing and contact tracing have proven insufficient to promptly monitor the spread of infections.AimTo develop and retrospectively evaluate a system identifying aberrations in the use of selected healthcare services to timely detect COVID-19 outbreaks in small areas.MethodsData were retrieved from the healthcare utilisation (HCU) databases of the Lombardy Region, Italy. We identified eight services suggesting a respiratory infection (syndromic proxies). Count time series reporting the weekly occurrence of each proxy from 2015 to 2020 were generated considering small administrative areas (i.e. census units of Cremona and Mantua provinces). The ability to uncover aberrations during 2020 was tested for two algorithms: the improved Farrington algorithm and the generalised likelihood ratio-based procedure for negative binomial counts. To evaluate these algorithms' performance in detecting outbreaks earlier than the standard surveillance, confirmed outbreaks, defined according to the weekly number of confirmed COVID-19 cases, were used as reference. Performances were assessed separately for the first and second semester of the year. Proxies positively impacting performance were identified.ResultsWe estimated that 70% of outbreaks could be detected early using the proposed approach, with a corresponding false positive rate of ca 20%. Performance did not substantially differ either between algorithms or semesters. The best proxies included emergency calls for respiratory or infectious disease causes and emergency room visits.ConclusionImplementing HCU-based monitoring systems in small areas deserves further investigations as it could facilitate the containment of COVID-19 and other unknown infectious diseases in the future.

The role of socio-demographic determinants in the geo-spatial distribution of newly diagnosed HIV infections in small areas of Catalonia (Spain).

BACKGROUND: Spatial visualization of HIV surveillance data could improve the planning of programs to address the HIV epidemic. The objectives of the study were to describe the characteristics and the spatial distribution of newly diagnosed HIV infection in Catalonia and to identify factors associated with HIV infection rates. METHODS: Surveillance data from the national registry were presented in the form of descriptive and ring maps and used to study the spatial distribution of new HIV diagnoses in Catalonia (2012-2016) and associated risk factors at the small area level (ABS, acronym for "basic health area" in Catalan). Incident cases were modeled using the following as predictors: type of municipality, prevalence of young men and migrant groups, GBMSM activity indicators, and other variables at the aggregated level. RESULTS: New HIV diagnoses are heterogeneously distributed across Catalonia. The predictors that proved to be significantly associated with a higher rate of new HIV diagnoses were ABS located in the city of Barcelona (IRR, 2.520; P < 0.001), a higher proportion of men aged 15-44 years (IRR, 1.193; P = 0.003), a higher proportion of GBMSM (IRR, 1.230; P = 0.030), a higher proportion of men from Western Europe (IRR, 1.281; P = 0.003), a higher proportion of men from Latin America (IRR, 1.260; P = 0.003), and a higher number of gay locations (IRR, 2.665; P < 0.001). No association was observed between the HIV diagnosis rate and economic deprivation. CONCLUSIONS: Ring maps revealed substantial spatial associations for the rate of new HIV diagnoses. New HIV diagnoses are concentrated in ABS located in urban areas. Our results show that, in the case of HIV infection, the socioeconomic deprivation index on which the Catalan government bases its budget allocation policies among the ABS should not be the only criterion used.

Bayesian Estimation of Age-Specific Mortality and Life Expectancy for Small Areas With Defective Vital Records.

High sampling variability complicates estimation of demographic rates in small areas. In addition, many countries have imperfect vital registration systems, with coverage quality that varies significantly between regions. We develop a Bayesian regression model for small-area mortality schedules that simultaneously addresses the problems of small local samples and underreporting of deaths. We combine a relational model for mortality schedules with probabilistic prior information on death registration coverage derived from demographic estimation techniques, such as Death Distribution Methods, and from field audits by public health experts. We test the model on small-area data from Brazil. Incorporating external estimates of vital registration coverage though priors improves small-area mortality estimates by accounting for underregistration and automatically producing measures of uncertainty. Bayesian estimates show that when mortality levels in small areas are compared, noise often dominates signal. Differences in local point estimates of life expectancy are often small relative to uncertainty, even for relatively large areas in a populous country like Brazil.

Assessing impact of organised breast screening across small residential areas-development and internal validation of a prediction model.

Monitoring screening mammography effects in small areas is often limited by small numbers of deaths and delayed effects. We developed a risk score for breast cancer death to circumvent these limitations. Screening, if effective, would increase post-diagnostic survivals through lead-time and related effects, as well as mortality reductions. Linked cancer and BreastScreen data at four hospitals (n = 2,039) were used to investigate whether screened cases had higher recorded survivals in 13 small areas, using breast cancer deaths as the outcome (M1), and a risk of death score derived from TNM stage, grade, histology type, hormone receptor status, and related variables (M2). M1 indicated lower risk of death in screened cases in 12 of the 13 areas, achieving statistical significance (p < .05) in 5. M2 indicated lower risk scores in screened cases in all 13 areas, achieving statistical significance in 12. For cases recently screened at diagnosis (<6 months), statistically significant reductions applied in 8 areas (M1) and all 13 areas (M2). Screening effects are more detectable in small areas using these risk scores than death itself as the outcome variable. An added advantage is the application of risk scores for providing a marker of screening effect soon after diagnosis.

Trends in socioeconomic inequalities in mortality in small areas of 33 Spanish cities.

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.

Multivariable flexible modelling for estimating complete, smoothed life tables for sub-national populations.

BACKGROUND: The methods currently available to estimate age- and sex-specific mortality rates for sub-populations are subject to a number of important limitations. We propose two alternative multivariable approaches: a relational model and a Poisson model both using restricted cubic splines. METHODS: We evaluated a flexible Poisson and flexible relational model against the Elandt-Johnson approach in a simulation study using 100 random samples of population and death counts, with different sampling proportions and data arrangements. Estimated rates were compared to the original mortality rates using goodness-of-fit measures and life expectancy. We further investigated an approach for determining optimal knot locations in the Poisson model. RESULTS: The flexible Poisson model outperformed the flexible relational and Elandt-Johnson methods with the smallest sample of data (1%). With the largest sample of data (20%), the flexible Poisson and flexible relational models performed comparably, though the flexible Poisson model displayed a slight advantage. Both approaches tended to underestimate infant mortality and thereby overestimate life expectancy at birth. The flexible Poisson model performed much better at young ages when knots were fixed a priori. For ages 30 and above, results were similar to the model with no fixed knots. CONCLUSIONS: The flexible Poisson model is recommended because it derives robust and unbiased estimates for sub-populations without making strong assumptions about age-specific mortality profiles. Fixing knots a priori in the final model greatly improves fit at the young ages.

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.

An Evaluation of Projection Methods for Detailed Small Area Projections: An Application and Validation to King County, Washington.

Population projections are used by a number of local agencies to better prepare for the future resource needs of counties, ensuring that educational, health, housing, and economic demands of individuals are met. Meeting the specific needs of a county's population, such as what resources to provide, where to target resources, and ensure an equitable distribution of those resources, requires population projections which are both demographically detailed, such as by age, race, and ethnicity, and geographically precise, such as at the census tract level. Despite this need, an evaluation of which methods are best suited to produce population projections at this level are lacking. In this study, we evaluate the accuracy of several cohort-based methods for small area population projections by race and ethnicity. We apply these methods to population projections of King County, Washington and assess the validity of projections using past population estimates. We find a clear pattern that demonstrates while simplified methods perform well in near term forecasts, methods which employ smoothing strategies perform better in long-term forecasting scenarios. Furthermore, we demonstrate that model's incorporating multiple stages of smoothing can provide detailed insights into the projected population size of King county and the places and groups which will most contribute to this growth. Detailed projections, such as those provided by multi-stage smoothing methods, enable city planners and policy makers a detailed view of the future structure of their county's population and provide for them a resource to better meet the needs of future populations.

[Association between neighborhood walkability and mortality due to different causes in Andalusia (Spain)]. / Asociación entre la caminabilidad del barrio de residencia y la mortalidad por distintas causas en Andalucía.

OBJECTIVE: To describe the association between the Neighborhood Walkability and mortality. METHOD: Ecological study of small areas. The standardized mortality ratios (SMR) and the Walk Score© were calculated in each census tract. These values were compared with parametric and nonparametric tests. RESULTS: For men, in the case of ischemic diseases, the means of the SMR for the categories with the highest walkability and the least were 1.03 and 0.85 (p <0.01), and in chronic obstructive pulmonary disease (COPD) were 1,009 and 1.20 (p <0.01). In women, the means of the SMR for diabetes were 0.97 and 1.2 (p <0.01), for ischemic diseases were 1.01 and 1.12 (p <0.01), for cerebrovascular diseases were 1.007 and 1.18 (p <0.01), for COPD were 1.01 and 1.49 (p <0.01) and for all causes were 1.006 and 1.08 (p <0.01) CONCLUSIONS: Behavior about walking in the activities of daily life is different between sexes. Living in walkable neighborhoods is a protective factor for women.

Dealing with risk discontinuities to estimate cancer mortality risks when the number of small areas is large.

Many statistical models have been developed during the last years to smooth risks in disease mapping. However, most of these modeling approaches do not take possible local discontinuities into consideration or if they do, they are computationally prohibitive or simply do not work when the number of small areas is large. In this paper, we propose a two-step method to deal with discontinuities and to smooth noisy risks in small areas. In a first stage, a novel density-based clustering algorithm is used. In contrast to previous proposals, this algorithm is able to automatically detect the number of spatial clusters, thus providing a single cluster structure. In the second stage, a Bayesian hierarchical spatial model that takes the cluster configuration into account is fitted, which accounts for the discontinuities in disease risk. To evaluate the performance of this new procedure in comparison to previous proposals, a simulation study has been conducted. Results show competitive risk estimates at a much better computational cost. The new methodology is used to analyze stomach cancer mortality data in Spanish municipalities.

Regional Distribution of Causes of Death for Small Areas in Brazil, 1998-2017.

Background: What is the spatial pattern of mortality by cause and sex in Brazil? Even considering the main causes of death, such as neoplasms, cardiovascular diseases, external causes, respiratory diseases, and infectious diseases, there are still important debate regarding the spatial pattern of mortality by causes in Brazil. Evidence shows that there is an overlap in transitional health states, due to the persistence of infectious diseases (e.g., dengue, cholera, malaria, etc.,) in parallel with the increase in chronic degenerative diseases. The main objective of this paper is to analyze the spatio-temporal evolution of three groups of causes of death in Brazil across small areas from 1998 to 2017, by sex. Methods: We use publicly available data from the System Data Mortality Information (SIM-DATASUS) from 1998 to 2017. We focus on this period due to the better quality of information, in addition to all deaths are registered following the Tenth Revision of the International Classification of Diseases (ICD-10). We estimate standardized mortality rates by sex and cause aggregated into three main groups. We use a ternary color scheme to maximize all the information in a three-dimensional array of compositional data. Results: We find improvements in mortality from chronic degenerative diseases; faster declines are observed in the Southern regions of the country; but the persistence of high levels of mortality due to infectious diseases remained in the northern parts of the country. We also find impressive differences in external causes of deaths between males and females and an increase in mortality from these causes in the interior part of the country. Conclusions: This study provides useful information for policy makers in establishing effective measures for the prevention of deaths and public health planning for deaths from external and non-communicable causes. We observed how the distribution of causes of death varies across regions and how the patterns of mortality also vary by gender.

Effect of the Financial Crisis on Socioeconomic Inequalities in Mortality in Small Areas in Seven Spanish Cities.

BACKGROUND: The aim of this study was to analyze the trend in socioeconomic inequalities in mortality in small areas due to several specific causes before (2001-2004, 2005-2008) and during (2009-2012) the economic crisis in seven Spanish cities. METHODS: This ecological study of trends, with census tracts as the areas of analysis, was based on three periods. Several causes of death were studied. A socioeconomic deprivation index was calculated for each census tract. For each small area, we estimated standardized mortality ratios, and controlled for their variability using Bayesian models (sSMR). We also estimated the relative risk of mortality according to deprivation in the different cities, periods, and sexes. RESULTS: In general, a similar geographical pattern was found for the socioeconomic deprivation index and sSMR. For men, there was an association in all cities between the deprivation index and all-cause mortality that remained stable over the three periods. For women, there was an association in Barcelona, Granada, and Sevilla between the deprivation index and all-cause mortality in the third period. Patterns by causes of death were more heterogeneous. CONCLUSIONS: After the start of the financial crisis, socioeconomic inequalities in total mortality in small areas of Spanish cities remained stable in most cities, although several causes of death showed a different pattern.

Effect of the recent economic crisis on socioeconomic inequalities in mortality in nine urban areas in Europe.

OBJECTIVE: To analyse socioeconomic inequalities in all-cause mortality among men and women in nine European urban areas during the recent economic crisis, and to compare the results to those from two periods before the crisis. METHOD: This is an ecological study of trends based on three time periods (2000-2003, 2004-2008 and 2009-2014). The units of analysis were the small areas of nine European urban areas. We used a composite deprivation index as a socioeconomic indicator, along with other single indicators. As a mortality indicator, we used the smoothed standardized mortality ratio, calculated using the hierarchical Bayesian model proposed by Besag, York and Mollié. To analyse the evolution of socioeconomic inequalities, we fitted an ecological regression model that included the socioeconomic indicator, the period of time, and the interaction between these terms. RESULTS: We observed significant inequalities in mortality among men for almost all the socioeconomic indicators, periods, and urban areas studied. However, no significant changes occurred during the period of the economic crisis. While inequalities among women were less common, there was a statistically significant increase in inequality during the crisis period in terms of unemployment and the deprivation index in Prague and Stockholm, respectively. CONCLUSIONS: Future analyses should also consider time-lag in the effect of crises on mortality and specific causes of death, and differential effects between genders.

Geographical Patterns in Drug-Related Mortality and Suicide: Investigating Commonalities in English Small Areas.

There are increasing concerns regarding upward trends in drug-related deaths in a number of developed societies. In some countries, these have been paralleled by upward trends in suicide. Of frequent concern to public health policy are local variations in these outcomes, and the factors underlying them. In this paper, we consider the geographic pattern of drug-related deaths and suicide for 2012-2016 across 6791 small areas in England. The aim is to establish the extent of commonalities in area risk factors between the two outcomes, with a particular focus on impacts of deprivation, fragmentation and rurality.

Bayesian smoothed small-areas analysis of urban inequalities in fertility across 1999-2013.

BACKGROUND: Since the 2008 economic crisis in Spain, overall fertility has continued to decrease, while urban inequalities have increased. There is a general lack of studies of fertility patterns in small-areas of Spanish cities. We explored the effects of the economic crisis on fertility during three time periods in urban settings in Spain. METHODS: We studied the distribution of fertility rates among women (15-49 years) from Spain and low-middle income countries (LIC) who were living in 13 Spanish cities. We mapped fertility and the MEDEA socioeconomic deprivation index in small-areas, and analyzed age-related trends in fertility rates. We performed an ecological regression analysis of fertility and the deprivation index in two pre-crisis periods (1999-2003 and 2004-2008) and one crisis period (2009-2013). Fertility rates were calculated and smoothed using the hierarchical Bayesian model (BYM). RESULTS: Higher fertility was generally associated with socioeconomic deprivation, with adjustment for the mothers' age and nationality. While Spanish citizens tended to delay childbearing throughout the three study periods, fertility increased among Spanish adolescents from deprived urban areas during the economic crisis. There was a general decline in fertility among immigrants after the crisis, especially in southern cities. Overall, fertility appeared to be stable, with higher fertility in more deprived areas. CONCLUSION: Increased unemployment and changes to government family policies may have contributed to delayed childbearing in Spain. For immigrants, more restrictive immigration policies may have played a crucial role in decreasing fertility rates. Reforming such policies will be key for better reproductive rights and improved fertility rates across all population cohorts in Spain.

Online relative risks/rates estimation in spatial and spatio-temporal disease mapping.

BACKGROUND AND OBJECTIVE: Spatial and spatio-temporal analyses of count data are crucial in epidemiology and other fields to unveil spatial and spatio-temporal patterns of incidence and/or mortality risks. However, fitting spatial and spatio-temporal models is not easy for non-expert users. The objective of this paper is to present an interactive and user-friendly web application (named SSTCDapp) for the analysis of spatial and spatio-temporal mortality or incidence data. Although SSTCDapp is simple to use, the underlying statistical theory is well founded and all key issues such as model identifiability, model selection, and several spatial priors and hyperpriors for sensitivity analyses are properly addressed. METHODS: The web application is designed to fit an extensive range of fairly complex spatio-temporal models to smooth the very often extremely variable standardized incidence/mortality risks or crude rates. The application is built with the R package shiny and relies on the well founded integrated nested Laplace approximation technique for model fitting and inference. RESULTS: The use of the web application is shown through the analysis of Spanish spatio-temporal breast cancer data. Different possibilities for the analysis regarding the type of model, model selection criteria, and a range of graphical as well as numerical outputs are provided. CONCLUSIONS: Unlike other software used in disease mapping, SSTCDapp facilitates the fit of complex statistical models to non-experts users without the need of installing any software in their own computers, since all the analyses and computations are made in a powerful remote server. In addition, a desktop version is also available to run the application locally in those cases in which data confidentiality is a serious issue.

A spatio-temporal analysis of cause-specific mortality in São Paulo State, Brazil / Uma análise espaço-temporal da mortalidade por causas específicas no estado de São Paulo, Brasil

Abstract Using five cause-specific mortality data sourced by the Brazilian Ministry of Health, and over 17 years period, we applied Bayesian spatio-temporal models on 644 municipalities of the state of São Paulo, using logistic model to the binary outcome that specifies whether or not the death was from a specific cause. We modeled the temporal mortality effects using B-splines, while the spatial components were considered through Gaussian and Markov random field, and inference was based on Markov chain Monte Carlo simulation. The results demonstrate consistent downward trend in mortality from infectious and parasitic diseases and external causes, while those from neoplasms and respiratory are rising. Cardiovascular is the only cause-specific death that is kept constant in time. All the causes of death considered show heterogeneous spatial and temporal variations among the municipalities, which sometimes change considerably within successive years. Mortality from infectious diseases clustered around the Northwestern municipalities in 2000, but changes to the Southeastern part in 2016, a similar development as external death causes. The study identifies areas with increased and decreased odds mortality and could be useful in disease monitoring, especially if we consider small spatial units.

Resumo Usando dados do Ministério da Saúde do Brasil para cinco causa de mortes, e num período de 17 anos, aplicamos modelos espaço-temporais Bayesianos em 644 municípios do estado de São Paulo, utilizando um modelo logístico binário que especifica se o óbito foi (ou não) de uma determinada causa. Modelamos os efeitos temporais da mortalidade com B-splines, e os componentes espaciais foram estimados através de campos aleatórios de Gaussiano e Markov. Simulamos a inferência estatística com Monte Carlo via cadeias de Markov. Os resultados demonstraram tendência consistente de queda nas mortes por doenças infecciosas e causas externas, enquanto mortes por neoplasias e doenças respiratórias aumentaram no tempo. Cardiovascular foi a única causa de morte constante no tempo. As causas de morte apresentaram variações espaciais e temporais entre os municípios, com consideráveis mudanças em anos sucessivos. A mortalidade por doenças infecciosas se concentrou nos municípios do noroeste do estado em 2000, mas mudou para a parte sudeste em 2016, um desenvolvimento semelhante as causas externas de morte. Este estudo identificou áreas com maior e menor chances de morte entre diferentes causas, e pode ser útil no monitoramento de doenças, especialmente se considerarmos pequenas unidades espaciais.

Maps of systematic variation in renal replacement therapy in Catalonia (2002-2012). / Atlas de variaciones sistemáticas en el tratamiento sustitutivo renal en Cataluña (2002­2012).

INTRODUCTION: Variations in the use of healthcare services can be defined as systematic variations of adjusted rates for certain aggregation levels of the population. The study analyses how renal replacement therapy (RRT) is used, identifying RRT variability in Catalonia from 2002 to 2012. MATERIAL AND METHODS: Ecological study by health area using data from the Catalan renal registry. We present incident rates, standardised incidence ratios and prevalence, while variability was calculated through direct and indirect standardisation methods. RESULTS: From 2002 until 31/12/2012, 10,784 patients initiated RRT in Catalonia: 9,238 on haemodialysis (HD) (50 treatments per 100,000 people 2010/2012), 1,076 on peritoneal dialysis (PD) (8.2 treatments per 100,000 people 2010/2012) and 470 received an early kidney transplant (KT) (4.4 treatments per 100,000 people 2010/2012). Over the 10 years, the HD cumulative incidence rate fell (7%), while the PD and KT incidence rates increased (63% and 177%, respectively); both are higher in young patients (<45 years). 4,750 patients received a kidney transplant in this period, 49% of which were aged between 45 and 65 years. There were no significant differences in variability in HD (RV5-95=1.3; Empirical Bayes [EB]∼ 0), or in the prevalence of KT (RV5-95=1.4; EB ∼ 0). Nevertheless, we found significant geographical variability in PD; notably in the districts of the province of Lérida, where the number of cases observed was greater than expected (RV5-95=4.01; EB=0.08). CONCLUSION: Although there was a notable rise in PD and early KT incidence rates, PD is still underused when compared to international recommendations. No territorial variability was found for HD or KT, but the use of PD was found to be higher in Lérida than in other areas. To reduce PD territorial variability and increase the uptake of this technique in the other regions, we propose 3initiatives: The development of RRT support tools for shared decision-making, the encouragement of specific PD professional training and the promotion of PD through complementary reimbursement systems.

Geographical and Temporal Variations in Female Breast Cancer Mortality in the Municipalities of Andalusia (Southern Spain).

The last published figures have shown geographical variations in mortality with respect to female breast cancer in European countries. However, national health policies need a dynamic image of the geographical variations within the country. The aim of this paper was to describe the spatial distribution of age-specific mortality rates from female breast cancer in the municipalities of Andalusia (southern Spain) and to analyze its evolution over time from 1981 to 2012. An ecological study was devised. Two spatio-temporal hierarchical Bayesian models were estimated. One of these was used to estimate the age-specific mortality rate for each municipality, together with its time trends, and the other was used to estimate the age-specific rate ratio compared with Spain as a whole. The results showed that 98% of the municipalities exhibited a decreasing or a flat mortality trend for all the age groups. In 2012, the geographical variability of the age-specific mortality rates was small, especially for population groups below 65. In addition, more than 96.6% of the municipalities showed an age-specific mortality rate similar to the corresponding rate for Spain, and there were no identified significant clusters. This information will contribute towards a reflection on the past, present and future of breast cancer outcomes in Andalusia.