Effects of the economic recession on suicide mortality in Brazil: interrupted time series analysis / Efectos de la recesión económica en la mortalidad por suicidio en Brasil: análisis de series de tiempo interrumpido / Efeitos da recessão econômica na mortalidade por suicídio no Brasil: análise com séries temporais interrompidas

ABSTRACT Objectives: to analyze trends in suicide rates in Brazil in the period before and after the start of the economic recession. Methods: interrupted time series research using national suicide data recorded in the period between 2012 and 2017 with socioeconomic subgroups analyses. Quasi-Poisson regression model was employed to analyze trends in seasonally adjusted data. Results: there was an abrupt increase in the risk of suicide after economic recession in the population with less education (12.5%; RR = 1.125; 95%CI: 1.027; 1.232) and in the South Region (17.7%; 1.044; 1.328). After an abrupt reduction, there was a progressive increase in risk for the black and brown population and for those with higher education. In most other population strata, there was a progressive increase in the risk of suicide. Conclusions: the Brazilian economic recession caused different effects on suicide rates, considering social strata, which requires health strategies and policies that are sensitive to the most vulnerable populations.

RESUMEN Objetivos: analizar tendencias de tasas de suicidio en Brasil, antes y después del inicio de la recesión económica. Métodos: estudio de series de tiempo interrumpido utilizando datos nacionales de suicidio registrados entre 2012 y 2017 con análisis por subgrupos socioeconómicos. Modelo de regresión quasi-Poisson empleado para analizar tendencias de datos ajustados estacionalmente. Resultados: observado aumento abrupto en el riesgo de suicidio pos recesión económica en la población con menor escolaridad (12,5%; RR = 1,125; IC95%:1,027; 1,232) y en la Región Sur (17,7%; 1,044; 1,328). Pos reducción abrupta, ocurrió aumento progresivo en el riesgo para la población de negros y pardos y de mayor escolaridad. En la mayoría de los demás estratos poblacionales, verificado aumento progresivo en el riesgo de suicidio. Conclusiones: la recesión económica brasileña produzco efectos diferentes en las tasas de suicidio, considerando los estratos sociales, lo que demanda estrategias de salud y políticas sensibles a poblaciones más vulnerables.

RESUMO Objetivos: analisar as tendências nas taxas de suicídio no Brasil, no período antes e depois do início da recessão econômica. Métodos: estudo de séries temporais interrompidas utilizando dados nacionais de suicídio registrados no período entre 2012 e 2017 com análises por subgrupos socioeconômicos. Modelo de regressão quasi-Poisson foi empregado para analisar as tendências dos dados ajustados sazonalmente. Resultados: observou-se aumento abrupto no risco de suicídio após recessão econômica na população com menor escolaridade (12,5%; RR = 1,125; IC95%:1,027; 1,232) e na Região Sul (17,7%; 1,044; 1,328). Após redução abrupta, ocorreu aumento progressivo no risco para a população de pretos e pardos e na de maior escolaridade. Na maioria dos demais estratos populacionais, verificou-se aumento progressivo no risco de suicídio. Conclusões: a recessão econômica brasileira produziu efeitos diferentes nas taxas de suicídio, considerando os estratos sociais, o que demanda estratégias de saúde e políticas sensíveis às populações mais vulneráveis.

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.

Trends in socioeconomic inequalities in preventable mortality in urban areas of 33 Spanish cities, 1996-2007 (MEDEA project).

BACKGROUND: Preventable mortality is a good indicator of possible problems to be investigated in the primary prevention chain, making it also a useful tool with which to evaluate health policies particularly public health policies. This study describes inequalities in preventable avoidable mortality in relation to socioeconomic status in small urban areas of thirty three Spanish cities, and analyses their evolution over the course of the periods 1996-2001 and 2002-2007. METHODS: We analysed census tracts and all deaths occurring in the population residing in these cities from 1996 to 2007 were taken into account. The causes included in the study were lung cancer, cirrhosis, AIDS/HIV, motor vehicle traffic accidents injuries, suicide and homicide. The census tracts were classified into three groups, according their socioeconomic level. To analyse inequalities in mortality risks between the highest and lowest socioeconomic levels and over different periods, for each city and separating by sex, Poisson regression were used. RESULTS: Preventable avoidable mortality made a significant contribution to general mortality (around 7.5%, higher among men), having decreased over time in men (12.7 in 1996-2001 and 10.9 in 2002-2007), though not so clearly among women (3.3% in 1996-2001 and 2.9% in 2002-2007). It has been observed in men that the risks of death are higher in areas of greater deprivation, and that these excesses have not modified over time. The result in women is different and differences in mortality risks by socioeconomic level could not be established in many cities. CONCLUSIONS: Preventable mortality decreased between the 1996-2001 and 2002-2007 periods, more markedly in men than in women. There were socioeconomic inequalities in mortality in most cities analysed, associating a higher risk of death with higher levels of deprivation. Inequalities have remained over the two periods analysed. This study makes it possible to identify those areas where excess preventable mortality was associated with more deprived zones. It is in these deprived zones where actions to reduce and monitor health inequalities should be put into place. Primary healthcare may play an important role in this process.

Do socioeconomic inequalities in mortality vary between different Spanish cities? a pooled cross-sectional analysis.

BACKGROUND: The relationship between deprivation and mortality in urban settings is well established. This relationship has been found for several causes of death in Spanish cities in independent analyses (the MEDEA project). However, no joint analysis which pools the strength of this relationship across several cities has ever been undertaken. Such an analysis would determine, if appropriate, a joint relationship by linking the associations found. METHODS: A pooled cross-sectional analysis of the data from the MEDEA project has been carried out for each of the causes of death studied. Specifically, a meta-analysis has been carried out to pool the relative risks in eleven Spanish cities. Different deprivation-mortality relationships across the cities are considered in the analysis (fixed and random effects models). The size of the cities is also considered as a possible factor explaining differences between cities. RESULTS: Twenty studies have been carried out for different combinations of sex and causes of death. For nine of them (men: prostate cancer, diabetes, mental illnesses, Alzheimer's disease, cerebrovascular disease; women: diabetes, mental illnesses, respiratory diseases, cirrhosis) no differences were found between cities in the effect of deprivation on mortality; in four cases (men: respiratory diseases, all causes of mortality; women: breast cancer, Alzheimer's disease) differences not associated with the size of the city have been determined; in two cases (men: cirrhosis; women: lung cancer) differences strictly linked to the size of the city have been determined, and in five cases (men: lung cancer, ischaemic heart disease; women: ischaemic heart disease, cerebrovascular diseases, all causes of mortality) both kinds of differences have been found. Except for lung cancer in women, every significant relationship between deprivation and mortality goes in the same direction: deprivation increases mortality. Variability in the relative risks across cities was found for general mortality for both sexes. CONCLUSIONS: This study provides a general overview of the relationship between deprivation and mortality for a sample of large Spanish cities combined. This joint study allows the exploration of and, if appropriate, the quantification of the variability in that relationship for the set of cities considered.

Predictors of the community pharmacy white-coat effect in treated hypertensive patients. The MEPAFAR study.

OBJECTIVE: To determine whether age, gender, body mass index (BMI), community pharmacy blood pressure (CPBP), daytime ambulatory BP (ABP) variability, treatment compliance, number of anti-hypertensive drugs and smoking status are factors associated with the community pharmacy white-coat effect (CPWCE) in treated hypertensive patients. SETTING: Eight community pharmacies in Gran Canaria, Spain. METHOD: A cross-sectional study was carried out from June 2008 to June 2009. The study included treated hypertensive patients older than 18 years. Patients were excluded if: systolic BP (SBP)/diastolic BP (DBP) ≥ 200/110 mmHg, not-recommended or unable to perform home BP measurements, changes in anti-hypertensive treatment <4 weeks, history of cardiovascular disease <6 months or pregnancy. Blood pressure (BP) was measured by a community pharmacist at 4 visits to the community pharmacy and using ABP monitoring (24 h). MAIN OUTCOME MEASURE: The CPWCE was calculated as the difference between the mean BP in the community pharmacy and daytime ABP. Independent predictors of the CPWCE were identified using multivariate linear regression analysis. RESULTS: Two hundred thirteen patients agreed to participate in the study. After exclusion and withdrawal, 169 patients were included in the analysis. Multiple linear regression analysis for systolic CPWCE revealed only community pharmacy SBP as an independent factor (ß = 0.35; P < 0.001). The regression analysis for diastolic CPWCE revealed female gender (ß = 4.88; P < 0.001), BMI (ß = 0.48; P < 0.001) and community pharmacy DBP (ß = 0.24; P < 0.001) as independent determinants. CONCLUSION: In this sample of treated hypertensive patients, factors such as gender, community pharmacy DBP and BMI were positively associated and may exert an important influence on the magnitude of the diastolic CPWCE. On the other hand, the CPWCE on SBP increased as the community pharmacy SBP increased.

Cancer mortality inequalities in urban areas: a Bayesian small area analysis in Spanish cities.

BACKGROUND: Intra-urban inequalities in mortality have been infrequently analysed in European contexts. The aim of the present study was to analyse patterns of cancer mortality and their relationship with socioeconomic deprivation in small areas in 11 Spanish cities. METHODS: It is a cross-sectional ecological design using mortality data (years 1996-2003). Units of analysis were the census tracts. A deprivation index was calculated for each census tract. In order to control the variability in estimating the risk of dying we used Bayesian models. We present the RR of the census tract with the highest deprivation vs. the census tract with the lowest deprivation. RESULTS: In the case of men, socioeconomic inequalities are observed in total cancer mortality in all cities, except in Castellon, Cordoba and Vigo, while Barcelona (RR = 1.53 95%CI 1.42-1.67), Madrid (RR = 1.57 95%CI 1.49-1.65) and Seville (RR = 1.53 95%CI 1.36-1.74) present the greatest inequalities. In general Barcelona and Madrid, present inequalities for most types of cancer. Among women for total cancer mortality, inequalities have only been found in Barcelona and Zaragoza. The excess number of cancer deaths due to socioeconomic deprivation was 16,413 for men and 1,142 for women. CONCLUSION: This study has analysed inequalities in cancer mortality in small areas of cities in Spain, not only relating this mortality with socioeconomic deprivation, but also calculating the excess mortality which may be attributed to such deprivation. This knowledge is particularly useful to determine which geographical areas in each city need intersectorial policies in order to promote a healthy environment.

[Methods to smooth mortality indicators: application to analysis of inequalities in mortality in Spanish cities [the MEDEA Project]]. / Métodos para la suavización de indicadores de mortalidad: aplicación al análisis de desigualdades en mortalidad en ciudades del Estado español (Proyecto MEDEA).

Although there is some experience in the study of mortality inequalities in Spanish cities, there are large urban centers that have not yet been investigated using the census tract as the unit of territorial analysis. The coordinated project <> was designed to fill this gap, with the participation of 10 groups of researchers in Andalusia, Aragon, Catalonia, Galicia, Madrid, Valencia, and the Basque Country. The MEDEA project has four distinguishing features: a) the census tract is used as the basic geographical area; b) statistical methods that include the geographical structure of the region under study are employed for risk estimation; c) data are drawn from three complementary data sources (information on air pollution, information on industrial pollution, and the records of mortality registrars), and d) a coordinated, large-scale analysis, favored by the implantation of coordinated research networks, is carried out. The main objective of the present study was to explain the methods for smoothing mortality indicators in the context of the MEDEA project. This study focusses on the methodology and the results of the Besag, York and Mollié model (BYM) in disease mapping. In the MEDEA project, standardized mortality ratios (SMR), corresponding to 17 large groups of causes of death and 28 specific causes, were smoothed by means of the BYM model; however, in the present study this methodology was applied to mortality due to cancer of the trachea, bronchi and lung in men and women in the city of Barcelona from 1996 to 2003. As a result of smoothing, a different geographical pattern for SMR in both genders was observed. In men, a SMR higher than unity was found in highly deprived areas. In contrast, in women, this pattern was observed in more affluent areas.