Spatial Distribution Of Mortality Research Articles

Geodemographic profiles of COVID-19 mortality inside/outside nursing homes. Spatial analysis from microdata in North Spain

After two years of the COVID-19 pandemic, there is extensive research on the spread of the virus and geo-statistical analysis of spatial patterns. However, from the perspective of health geography, COVID-19 mortality is still under-studied. This research aims to provide a geographic profile of COVID-19 mortality, in terms of the space-time evolution and the relationship with individual and contextual variables. To this end, we geocoded the daily COVID-19 microdata of deceased persons provided by the Government of Cantabria (in northern Spain) from March 1, 2020 to March 31, 2022. The study also took cadastral variables, population records, and connections to geo-enrichment services accessed through ArcGIS Pro License (ESRI) into account. Using spatial statistics methods, such as 3D bins and emerging hot spots, local bivariate relationships, and ordinary least squares, we propose an exportable and scalable methodology to help policymakers cope with the current stage of living with the epidemic virus. Our results suggest that the spatial distribution of mortality is less clustered than that of contagion and shed light on differences in COVID-19 mortality profiles inside/outside nursing homes, such as higher age, and the temporal concentration of deaths in nursing homes. Spatial regimes showed hot spots of COVID-19 mortality in urban and metropolitan areas, with a pattern of repetition over time, such as sporadic hot spots that accounted for 36.28% of deaths in only 11.88% of the area with COVID-19 deaths. Despite immunization, periods of high contagion meant a subsequent increase in mortality, such as during the Omicron wave, where consecutive metropolitan hot spots accounted for 37.50% of the area and 51.45% of deaths were concentrated. Finally, there were interesting nuances in the significant local context variables of COVID-19 mortality compared with the explanatory factors of COVID-19 cases.

Estimation of health risk and economic loss attributable to PM2.5 and O3 pollution in Jilin Province, China

Ambient pollutants, particularly fine particulate matter (PM2.5) and ozone (O3), pose significant risks to both public health and economic development. In recent years, PM2.5 concentration in China has decreased significantly, whereas that of O3 has increased rapidly, leading to considerable health risks. In this study, a generalized additive model was employed to establish the relationship of PM2.5 and O3 exposure with non-accidental mortality across 17 districts and counties in Jilin Province, China, over 2015–2016. The health burden and economic losses attributable to PM2.5 and O3 were assessed using high-resolution satellite and population data. According to the results, per 10 µg/m3 increase in PM2.5 and O3 concentrations related to an overall relative risk (95% confidence interval) of 1.004 (1.001–1.007) and 1.009 (1.005–1.012), respectively. In general, the spatial distribution of mortality and economic losses was uneven. Throughout the study period, a total of 23,051.274 mortalities and 27,825.015 million Chinese Yuan (CNY) in economic losses were attributed to O3 exposure, which considerably surpassing the 5,450.716 mortalities and 6,553,780 million CNY in economic losses attributed to PM2.5 exposure. The O3-related health risks and economic losses increased by 3.75% and 9.3% from 2015 to 2016, while those linked to PM2.5 decreased by 23.33% and 18.7%. Sensitivity analysis results indicated that changes in pollutant concentrations were the major factors affecting mortality rather than baseline mortality and population.

Retrospective Analysis of the Outcome of Hospitalized COVID-19 Patients with Coexisting Metabolic Syndrome and HIV Using Multinomial Logistic Regression.

Globally, the coexistence of metabolic syndrome (MetS) and HIV has become an important public health problem, putting coronavirus disease 19 (COVID-19) hospitalized patients at risk for severe manifestations and higher mortality. A retrospective cross-sectional analysis was conducted to identify factors and determine their relationships with hospitalization outcomes for COVID-19 patients using secondary data from the Department of Health in Limpopo Province, South Africa. The study included 15,151 patient clinical records of laboratory-confirmed COVID-19 cases. Data on MetS was extracted in the form of a cluster of metabolic factors. These included abdominal obesity, high blood pressure, and impaired fasting glucose captured on an information sheet. Spatial distribution of mortality among patients was observed; overall (21-33%), hypertension (32-43%), diabetes (34-47%), and HIV (31-45%). A multinomial logistic regression model was applied to identify factors and determine their relationships with hospitalization outcomes for COVID-19 patients. Mortality among COVID-19 patients was associated with being older (≥50+ years), male, and HIV positive. Having hypertension and diabetes reduced the duration from admission to death. Being transferred from a primary health facility (PHC) to a referral hospital among COVID-19 patients was associated with ventilation and less chance of being transferred to another health facility when having HIV plus MetS. Patients with MetS had a higher mortality rate within seven days of hospitalization, followed by those with obesity as an individual component. MetS and its components such as hypertension, diabetes, and obesity should be considered a composite predictor of COVID-19 fatal outcomes, mostly, increased risk of mortality. The study increases our understanding of the common contributing variables to severe manifestations and a greater mortality risk among COVID-19 hospitalized patients by investigating the influence of MetS, its components, and HIV coexistence. Prevention remains the mainstay for both communicable and non-communicable diseases. The findings underscore the need for improvement of critical care resources across South Africa.

Spatial distribution of mortality from colorectal cancer in the southern region of Brazil.

Colorectal cancer (CRC) is the leading cause of death due to cancer worldwide. In Brazil, it is the second most frequent cancer in men and women, with a mortality reaching 9.4% of those diagnosed. The aim of this study was to analyze the spatial heterogeneity of CRC deaths among municipalities in south Brazil, from 2015 to 2019, in different age groups (50-59 years, 60-69 years, 70-79 years, and 80 years old or more) and identify the associated variables. Global Spatial Autocorrelation (Moran's I) and Local Spatial Autocorrelation (LISA) analyses were used to evaluate the spatial correlation between municipalities and CRC mortality. Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) were applied to evaluate global and local correlations between CRC deaths, sociodemographic, and coverage of health care services. For all age groups, our results found areas with high CRC rates surrounded by areas with similarly high rates mainly in the Rio Grande do Sul state. Even as factors associated with CRC mortality varied according to age group, our results suggested that improved access to specialized health centers, the presence of family health strategy teams, and higher rates of colonoscopies are protective factors against colorectal cancer mortality in southern Brazil.

Spatial analysis of colorectal cancer outcomes and socioeconomic factors in Virginia

BackgroundColorectal cancer (CRC) disparities vary by country and population group, but often have spatial features. This study of the United States state of Virginia assessed CRC outcomes, and identified demographic, socioeconomic and healthcare access contributors to CRC disparities.MethodsCounty- and city-level cross-sectional data for 2011–2015 CRC incidence, mortality, and mortality-incidence ratio (MIR) were analyzed for geographically determined clusters (hotspots and cold spots) and their correlates. Spatial regression examined predictors including proportion of African American (AA) residents, rural-urban status, socioeconomic (SES) index, CRC screening rate, and densities of primary care providers (PCP) and gastroenterologists. Stationarity, which assesses spatial equality, was examined with geographically weighted regression.ResultsFor incidence, one CRC hotspot and two cold spots were identified, including one large hotspot for MIR in southwest Virginia. In the spatial distribution of mortality, no clusters were found. Rurality and AA population were most associated with incidence. SES index, rurality, and PCP density were associated with spatial distribution of mortality. SES index and rurality were associated with MIR. Local coefficients indicated stronger associations of predictor variables in the southwestern region.ConclusionsRurality, low SES, and racial distribution were important predictors of CRC incidence, mortality, and MIR. Regions with concentrations of one or more factors of disparities face additional hurdles to improving CRC outcomes. A large cluster of high MIR in southwest Virginia region requires further investigation to improve early cancer detection and support survivorship. Spatial analysis can identify high-disparity populations and be used to inform targeted cancer control programming.

The spatial footprint and patchiness of large-scale disturbances on coral reefs.

Ecosystems have always been shaped by disturbances, but many of these events are becoming larger, more severe and more frequent. The recovery capacity of depleted populations depends on the frequency of disturbances, the spatial distribution of mortality and the scale of dispersal. Here, we show that four mass coral bleaching events on the Great Barrier Reef (in 1998, 2002, 2016 and 2017) each had markedly larger disturbance footprints and were less patchy than a severe category 5 tropical cyclone (Cyclone Yasi, 2011). Severely bleached reefs in 2016 and 2017 were isolated from the nearest lightly affected reefs by up to 146 and 200km, respectively. In contrast, reefs damaged by Cyclone Yasi were on average 20km away from relatively undisturbed reefs, well within the estimated range of larval dispersal for most corals. Based on these results, we present a model of coral reef disturbance and recovery to examine (1) how the spatial clustering of disturbances modifies large-scale recovery rates; and (2) how recovery rates are shaped by species' dispersal abilities. Our findings illustrate that the spatial footprint of the recent mass bleaching events poses an unprecedented threat to the resilience of coral species in human history, a threat that is even larger than the amount of mortality suggests.

Exploring the Influence of Drug Trafficking Gangs on Overdose Deaths in the Largest Narcotics Market in the Eastern United States

Research has found that drug markets tend to cluster in space, potentially because of the profit that can be made when customers are drawn to areas with multiple suppliers. But few studies have examined how these clusters of drug markets—which have been termed “agglomeration economies”—may be related to accidental overdose deaths, and in particular, the spatial distribution of mortality from overdose. Focusing on a large neighborhood in Philadelphia, Pennsylvania, known for its open-air drug markets, this study examines whether deaths from accidental drug overdose are clustered around street corners controlled by drug trafficking gangs. This study incorporates theoretically-informed social and physical environmental characteristics of street corner units into the models predicting overdose deaths. Given a number of environmental changes relevant to drug use locations was taking place in the focal neighborhood during the analysis period, the authors first employ a novel concentration metric—the Rare Event Concentration Coefficient—to assess clustering of overdose deaths annually between 2015 and 2019. The results of these models reveal that overdose deaths became less clustered over time and that the density was considerably lower after 2017. Hence, the predictive models in this study are focused on the two-year period between 2018 and 2019. Results from spatial econometric regression models find strong support for the association between corner drug markets and accidental overdose deaths. In addition, a number of sociostructural factors, such as concentrated disadvantage, and physical environmental factors, particularly blighted housing, are associated with a higher rate of overdose deaths. Implications from this study highlight the need for efforts that strategically coordinate law enforcement, social service provision and reductions in housing blight targeted to particular geographies.

Spatial Distribution of Mortality Caused by the 1995 Kobe Earthquake An Examination on Applicability of Human Damage Data for Reconstruction of Historical Earthquake

Spatial Distribution of Mortality Caused by the 1995 Kobe Earthquake An Examination on Applicability of Human Damage Data for Reconstruction of Historical Earthquake

Geodemographic Area Classification and Association with Mortality: An Ecological Study of Small Areas of Cyprus.

Geographical investigations are a core function of public health monitoring, providing the foundation for resource allocation and policies for reducing health inequalities. The aim of this study was to develop geodemographic area classification based on several area-level indicators and to explore the extent of geographical inequalities in mortality. A series of 19 area-level socioeconomic indicators were used from the 2011 national population census. After normalization and standardization of the geographically smoothed indicators, the k-means cluster algorithm was implemented to classify communities into groups based on similar characteristics. The association between geodemographic area classification and the spatial distribution of mortality was estimated in Poisson log-linear spatial models. The k-means algorithm resulted in four distinct clusters of areas. The most characteristic distinction was between the ageing, socially isolated, and resource-scarce rural communities versus metropolitan areas with younger population, higher educational attainment, and professional occupations. By comparison to metropolitan areas, premature mortality appeared to be 44% (95% Credible Intervals [CrI] of Rate Ratio (RR): 1.06–1.91) higher in traditional rural areas and 36% (95% CrI of RR: 1.13–1.62) higher in young semi-rural areas. These findings warrant future epidemiological studies investigating various causes of the urban-rural differences in premature mortality and implementation policies to reduce the mortality gap between urban and rural areas.

Conglomerados espaciais da mortalidade por suicídio no nordeste do Brasil e sua relação com indicadores socioeconômicos

Resumo Objetivo Avaliar a distribuição espacial da mortalidade por suicídios no Nordeste do Brasil e sua relação com indicadores sociais e econômicos, buscando identificar o padrão dessa distribuição por meio de uma análise geoestatística. Método Trata-se de um estudo ecológico que utilizou dados de óbitos por suicídio ocorridos nos anos de 2000 a 2014 registrados no Sistema de Informação sobre Mortalidade. Foram aplicados os testes Moran Global e Local para análise da autocorrelação espacial, e a análise bivariada LISA para avaliação da correlação espacial entre a taxa de mortalidade por suicídio e as variáveis independentes. Resultados Os resultados mostraram que a Mortalidade por suicídio no Nordeste possui fraca autocorrelação espacial (I=0,2608), embora exista forte autocorrelação espacial para a maioria das variáveis analisadas. Na análise bivariada espacial, as variáveis apresentaram Índice de Moran LISA próximo a zero, como o IDH (I=0,025), Envelhecimento (I=0,146) e Analfabetismo (I=0,06). A análise bivariada espacial evidenciou que não existe autocorrelação espacial entre as variáveis socioeconômicas e a Taxa de Mortalidade Padronizada (TMP) por suicídio. Conclusão Conclui-se que a mortalidade por suicídio no Nordeste do Brasil apresenta distribuição aleatória e não guarda relação espacial com variáveis socioeconômicas.

Compositional analysis of topsoil metals and its associations with cancer mortality using spatial misaligned data

The presence of toxic metals in soil per se, and in soil impacted by mining, industry, agriculture and urbanisation in particular, is a major concern for both human health and ecotoxicology. The dual aim of this study was: to ascertain whether topsoil composition could influence the spatial distribution of mortality due to different types of cancer and to identify possible errors committed by epidemiological studies which analyse soil composition data as a closed number system. We conducted an ecological cancer mortality study, covering 861,440 cancer deaths (27 cancer sites) in 7917 Spanish mainland towns, from 1999 to 2008. Topsoil levels of Al, As, Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn were determined by ICP-MS at 13,317 sampling points. We transformed the topsoil data in two ways, i.e. log transformation and centred logratio transformation. Principal factor analysis was performed to obtain independent latent factors for the transformed variables. To estimate the effect on mortality of topsoil factor loadings, we fitted Besag, York and Mollié models embedded in geostatistical-spatial models. This model included soil sample locations and town centroids (non-aligned data), fitted using the integrated nested Laplace approximation (INLA) as a tool for Bayesian inference and stochastic partial differential equations (SPDE). All results were adjusted for socio-demographic variables. The results indicated that soil composition could have an influence on the spatial distribution and mortality patterns of cancer. The analysis adjusted for socio-demographic variables showed excess male mortality due to digestive system tumours in areas with soils containing higher Cd, Pb, Zn, Mn and Cu concentrations, bladder cancer in areas with soils containing higher Cd concentrations, and brain cancer in areas with soils containing As. In both sexes, cancer of oesophagus was associated with soils containing a higher lead content, while lung cancer was associated with soils containing a higher copper content. Stress should be laid on the importance of taking into account the compositional nature of the data in this type of analysis.

An exploratory spatial analysis to assess the relationship between deprivation, noise and infant mortality: an ecological study

BackgroundFew studies have explored how noise might contribute to social health inequalities, and even fewer have considered infant mortality or its risk factors as the health event of interest.In this paper, we investigate the impact of neighbourhood characteristics - both socio-economic status and ambient noise levels - on the spatial distribution of infant mortality in the Lyon metropolitan area, in France.MethodsAll infant deaths (n = 715) occurring between 2000 and 2009 were geocoded at census block level. Each census block was assigned multi-component socio-economic characteristics and Lden levels, which measure exposure to noise. Using a spatial–scan statistic, we examined whether there were significant clusters of high risk of infant mortality according to neighbourhood characteristics.ResultsOur results highlight the fact that infant mortality is non-randomly distributed spatially, with clusters of high risk in the south-east of the Lyon metropolitan area (RR = 1.44; p = 0.09). After adjustments for socio-economic characteristics and noise levels, this cluster disappears or shifts according to in line with different scenarios, suggesting that noise and socio-economic characteristics can partially explain the spatial distribution of infant mortality.ConclusionOur findings show that noise does have an impact on the spatial distribution of mortality after adjustments for socio-economic characteristics. A link between noise and infant mortality seems plausible in view of the three hypothetical, non-exclusive, pathways we propose in our conceptual framework: (i) a psychological pathway, (ii) a physiological disruption process and (iii) an unhealthy behaviours pathway. The lack of studies makes it is difficult to compare our findings with others. They require further research for confirmation and interpretation.

Hierarchical spatio-temporal mapping of premature mortality due to alcoholic liver disease in Hungary, 2005–2010

Excess alcohol consumption is a major public health issue in Hungary, with high mortality rates from alcohol disease. In addition, excess alcohol consumption has been found to differ by socioeconomic and environmental factors. The spatial pattern of mortality from alcoholic liver disease across Hungary for the period 2005 and 2010, at municipality level, was investigated by sex using Bayesian modelling. The changes in mortality over this 6-year period were analysed using hierarchical spatio-temporal disease mapping. The association between the spatial distribution of mortality from alcoholic liver disease and cirrhosis and deprivation (by sex) was also assessed using a Hungarian-specific deprivation index. A statistically significant association was found between mortality and deprivation status in males. Areas of significantly highest age-adjusted relative risks were found, for males, in the south-western part, and at the eastern border of the country. A number of areas showed area-specific trends that were significantly steeper than the national average mortality trend. Using our findings, population groups with increasing mortality trends were identified, which may help decision makers fund effective health promotion programmes to reduce mortality rates in the working-age population.

Spatial analysis of cerebrovascular mortality in Rio de Janeiro municipality from 2002 to 2007, demographic and socioeconomic correlations

Purpose: Despite moderate decline of Cerebrovascular Disease (CBVD) in the last several decades, it is still the leading cause of death in the municipality of Rio de Janeiro (RJ). The spatial distribution of mortality across regions is unknown. The aim of this study was to understand the geographical distribution of deaths from CBVD in Rio de Janeiro and the correlations with socioeconomic and demographic data methods. Methods: This ecological study examined all death certificates from 2002 to 2007 of RJ residents 20 years or older, with CBVD as the underlying cause of death. The geographical distribution of CBVD deaths were observed by geocoding addresses. The proportions of death from each Administrative Region (AR) were analyzed by gender, age, education and marital status and standardized by 2000-2010 population averages. The socioeconomic indicator used in this study was the Human Development Index (HDI) of each AR for the year of 2000. The magnitude of effect of individual variables and HDI were obtained by modeling hierarchical pattern of dots through log-Gaussian Cox model with Bayesian inference credibility intervals (CI) of 95% for each variable (Markov Chain Monte Carlo simulations method -MCMC). The Relative Risk (RR) for death for each AR was calculated and compared with AR 6 (highest HDI-RJ) for variable settings. Results were presented as maps. Results: The spatial distribution of deaths from CBVD in Rio de Janeiro was heterogeneous and showed a strong inverse linear correlation with HDI of the AR (CI: -10,2; -9,7). For each reduction of 0.05 HDI there was a 65% increase in the number of deaths (CI: 1,64; 1,66). Male gender, older age and poor education were risk factors for death from CBVD in almost every AR. For poorly educated people, living together represented a protective factor for death by CBVD in the majority of Administrative Regions (AR's). In all AR's the RR of death was high and occurred earlier compared with AR's of higher socioeconomic status, with regional difference correlating with the HDI of each region. No significant effect was observed for some of the study variables in some slums and Guaratiba AR. Conclusion: Increased risk of death from CBVD in the municipality of Rio de Janeiro was found in areas of lower socioeconomic development where death usually occurs earlier. It is recommended that the government address health issues in a more active manner not only to control individual risk factors, but, most of all, to use multidisciplinary interventions according to the geographical distribution of mortality.

Spatial distribution of mortality in Pacific oysters Crassostrea gigas: reflection on mechanisms of OsHV-1 transmission

The ostreid herpesvirus OsHV-1 has the potential to devastate Pacific oyster Crassostrea gigas culture in Australia as it has done in many other countries, highlighting the need for a better understanding of disease expression and transmission. The aim of this study was to assess the spatial distribution of OsHV-1-associated mortalities in one of only two infected areas in Australia, Woolooware Bay (Botany Bay, New South Wales). In October 2011, healthy sentinel Pacific oysters were placed in 3 different locations at 3 different tidal levels, and OsHV-1 associated mortalities were closely monitored over 7 mo. The outbreak started in November 2011, and the disease remained active until April 2012. Three major mortality events were detected. Rather than being a propagating epizootic, it appeared that most oysters were infected from a common environmental source. The distribution of OsHV-1-associated mortalities was spatially clustered, highly variable and clearly dependent on the age of oysters and their position in the water column. Non-random distribution of mortalities at macro scale (sites several km apart) and micro scale (within rearing trays), and vertical clustering patterns in the water column are discussed in regard to factors known to influence mechanism of disease transmission in aquatic environments (hydrodynamics, physical disturbances, host density/distribution, and variations of environmental parameters). A new hypothesis proposing that OsHV-1 may be carried through water by particles, possibly plankton, is also suggested to explain the patchy distribution of mortalities in Woolooware Bay.

Mesothelioma mortality surveillance and asbestos exposure tracking in Italy

Spatial distribution of mortality from pleural mesothelioma (which in the ICD-10 Revision has a specific code: C45.0) in Italy for the period 2003-2009 is described. Previous mortality studies at national level employed the topographic code "Malignant neoplasms of pleura", because of unavailability of a specific code in ICD-9 Revision for pleural mesothelioma. Standardized mortality ratios were computed for all municipalities, using each regional population as reference; for municipalities in Regions with rate higher than the national rate, the latter has been used as reference. SMRs were computed specifically also for each Italian Polluted Sites "of national concern for environmental remediation" (IPS) with asbestos exposure sources, composed by one or more municipalities, using regional rate as reference. Spatial Scan Statistics procedure, using SatScan software, was applied in cluster analysis: the country was divided into geographic macro-areas and the relative risks (RR) express the ratio of risk within the cluster to the risk of the macro-area outside the cluster. Clusters with p-value < 0.10 were selected. The national standardized annual mortality rate was 1.7 cases per 100 000. Several areas with evident burden of asbestos-related disease were detected. Significant clusters were found in correspondence to asbestos-cement industries (e.g. Casale Monferrato, women: RR = 28.7), shipyards (e.g. Trieste, men: RR = 4.8), petrochemical industries (e.g. Priolo, men: RR = 6.9) and a stone quarry contaminated by fluoro-edenite fibres (Biancavilla, women: RR = 25.9). Some of the increased clusters correspond to IPS. The results may contribute to detect asbestos exposure and to set priorites for environmental remediation.

Griffon vulture mortality at wind farms in southern Spain: Distribution of fatalities and active mitigation measures

Wind is increasingly being used as a renewable energy source around the world. Avian mortality is one of the negative impacts of wind energy and a new technique that reduces avian collision rates is necessary. Using the most frequently-killed species, the griffon vulture (Gyps fulvus), we studied its mortality at 13 wind farms in Tarifa, Cadiz, Spain, before (2006–2007) and after (2008–2009) when selective turbine stopping programs were implemented as a mitigation measure. Ten wind farms (total of 244 turbines) were selectively stopped and three wind farms (total of 52 turbines) were not. We found 221 dead griffon vultures during the entire study and the mortality rate was statistically different per turbine and year among wind farms. During 2006–2007, 135 griffon vultures were found dead and the spatial distribution of mortality was not uniformly distributed among turbines, with very few turbines showing the highest mortality rates. The 10 most dangerous turbines were distributed among six different wind farms. Most of the mortalities were concentrated in October and November matching the migratory period. During 2008–2009, we used a selective stopping program to stop turbines when vultures were observed near them and the griffon vulture mortality rate was reduced by 50% with a consequent reduction in total energy production of by the wind farms by only 0.07% per year. Our results indicate that the use of selective stopping techniques at turbines with the highest mortality rates can help to mitigate the impacts of wind farms on birds with a minimal affect on energy production.

P1-401 Temporal trend in and spatial distribution of lung cancer mortality in Brazil between 1979 and 2004: magnitude, regional patterns, and gender-related differences

IntroductionLung cancer is a major public health problem in Brazil. The aim of this study was to describe the temporal trend and the spatial distribution of mortality from tracheal, bronchial,...

Inequalities in mortality of men by oral and pharyngeal cancer in Barcelona, Spain and São Paulo, Brazil, 1995–2003

BackgroundLarge inequalities of mortality by most cancers in general, by mouth and pharynx cancer in particular, have been associated to behaviour and geopolitical factors. The assessment of socioeconomic covariates of cancer mortality may be relevant to a full comprehension of distal determinants of the disease, and to appraise opportune interventions. The objective of this study was to compare socioeconomic inequalities in male mortality by oral and pharyngeal cancer in two major cities of Europe and South America.MethodsThe official system of information on mortality provided data on deaths in each city; general censuses informed population data. Age-adjusted death rates by oral and pharyngeal cancer for men were independently assessed for neighbourhoods of Barcelona, Spain, and São Paulo, Brazil, from 1995 to 2003. Uniform methodological criteria instructed the comparative assessment of magnitude, trends and spatial distribution of mortality. General linear models assessed ecologic correlations between death rates and socioeconomic indices (unemployment, schooling levels and the human development index) at the inner-city area level. Results obtained for each city were subsequently compared.ResultsMortality of men by oral and pharyngeal cancer ranked higher in Barcelona (9.45 yearly deaths per 100,000 male inhabitants) than in Spain and Europe as a whole; rates were on decrease. São Paulo presented a poorer profile, with higher magnitude (11.86) and stationary trend. The appraisal of ecologic correlations indicated an unequal and inequitably distributed burden of disease in both cities, with poorer areas tending to present higher mortality. Barcelona had a larger gradient of mortality than São Paulo, indicating a higher inequality of cancer deaths across its neighbourhoods.ConclusionThe quantitative monitoring of inequalities in health may contribute to the formulation of redistributive policies aimed at the concurrent promotion of wellbeing and social justice. The assessment of groups experiencing a higher burden of disease can instruct health services to provide additional resources for expanding preventive actions and facilities aimed at early diagnosis, standardized treatments and rehabilitation.

Tendência temporal e distribuição espacial da mortalidade por câncer de pulmão no Brasil entre 1979 e 2004: magnitude, padrões regionais e diferenças entre sexos

To describe the temporal trend in and spatial distribution of mortality from tracheal, bronchial, and lung cancer in Brazil from 1979 to 2004. Mortality data by gender and geographic region were obtained from the Mortality Database created by the Ministry of Health in 1975. Demographic data were collected from the national censuses, from population counts, and from population estimates made in non-census years. Mortality rates were standardized according to the direct method, and the trends were analyzed by gender and geographic region using the Prais-Winsten method for generalized linear regression. Lung cancer mortality accounted for approximately 12% of the overall neoplasia-related mortality during the period. There was a trend toward an increase for both genders and in all regions, except for the male population in the southeast region, whose rates remained steady between 1979 and 2004. The highest rates were observed in the south and southeast regions. However, the northeast region was the one that presented the greatest increase, followed by the central-west and north regions. In all regions, the increase in mortality rates was higher in women. The increase in lung cancer mortality in Brazil between 1979 and 2004 requires public measures that can minimize exposition to risk factors, mainly tobacco, and allow greater access to health care facilities for diagnosis and treatment.