The impact of atmospheric particulate matter on cancer incidence and mortality in the city of Sao Paulo, Brazil

This study aimed to verify the impact of inhalable particulate matter (PM10) on cancer incidence and mortality in the city of Sao Paulo, Brazil. Statistical techniques were used to investigate the relationship between PM10 on cancer incidence and mortality in selected districts. For some types of cancer (skin, lung, thyroid, larynx, and bladder) and some periods, the correlation coefficients ranged from 0.60 to 0.80 for incidence. Lung cancer mortality showed more correlations during the overall period. Spatial analysis showed that districts distant from the city center showed higher than expected relative risk, depending on the type of cancer According to the study, urban PM10 can contribute to increased incidence of some cancers and may also contribute to increased cancer mortality. The results highlight the need to adopt measures to reduce atmospheric PM10 levels and the importance of their continuous monitoring.

The impact of mortality from external causes on human development in the Brazilian borderland

This article estimates the impact of mortality from external causes on the human development index (HDI) along the Brazilian borderland from 2000 to 2005. Data obtained from Brazilian government agencies were combined using the methodology defined by the United Nations Development Program, revealing the HDI according to actual conditions. Subsequently, deaths from external causes were excluded in order to estimate their impact on the index, recalculating life expectancy using the technique of competing causes. HDI showed a gradual increase from North to South, with the most developed regions concentrated in the South, consistent with studies using other sets of economic indicators. By excluding mortality from external causes, the highest gains appeared in regions where the HDI (under actual conditions) were lower, and the magnitude of gains declined towards the South.

Factors Associated with Dengue Mortality in Latin America and the Caribbean, 1995-2009: An Ecological Study

In this study, we aimed to estimate the effect that environmental, demographic, and socioeconomic factors have on dengue mortality in Latin America and the Caribbean. To that end, we conducted an observational ecological study, analyzing data collected between 1995 and 2009. Dengue mortality rates were highest in the Caribbean (Spanish-speaking and non-Spanish-speaking). Multivariate analysis through Poisson regression revealed that the following factors were independently associated with dengue mortality: time since identification of endemicity (adjusted rate ratio [aRR] = 3.2 [for each 10 years]); annual rainfall (aRR = 1.5 [for each 10(3) L/m(2)]); population density (aRR = 2.1 and 3.2 for 20-120 inhabitants/km(2) and > 120 inhabitants/km(2), respectively); Human Development Index > 0.83 (aRR = 0.4); and circulation of the dengue 2 serotype (aRR = 1.7). These results highlight the important role that environmental, demographic, socioeconomic, and biological factors have played in increasing the severity of dengue in recent decades.

Trends in aortic aneurysm- and dissection-related mortality in the state of Sao Paulo, Brazil, 1985-2009: multiple-cause-of-death analysis

Background: Aortic aneurysm and dissection are important causes of death in older people. Ruptured aneurysms show catastrophic fatality rates reaching near 80%. Few population-based mortality studies have been published in the world and none in Brazil. The objective of the present study was to use multiple-cause-of-death methodology in the analysis of mortality trends related to aortic aneurysm and dissection in the state of Sao Paulo, between 1985 and 2009. Methods: We analyzed mortality data from the Sao Paulo State Data Analysis System, selecting all death certificates on which aortic aneurysm and dissection were listed as a cause-of-death. The variables sex, age, season of the year, and underlying, associated or total mentions of causes of death were studied using standardized mortality rates, proportions and historical trends. Statistical analyses were performed by chi-square goodness-of-fit and H Kruskal-Wallis tests, and variance analysis. The joinpoint regression model was used to evaluate changes in age-standardized rates trends. A p value less than 0.05 was regarded as significant. Results: Over a 25-year period, there were 42,615 deaths related to aortic aneurysm and dissection, of which 36,088 (84.7%) were identified as underlying cause and 6,527 (15.3%) as an associated cause-of-death. Dissection and ruptured aneurysms were considered as an underlying cause of death in 93% of the deaths. For the entire period, a significant increased trend of age-standardized death rates was observed in men and women, while certain non-significant decreases occurred from 1996/2004 until 2009. Abdominal aortic aneurysms and aortic dissections prevailed among men and aortic dissections and aortic aneurysms of unspecified site among women. In 1985 and 2009 death rates ratios of men to women were respectively 2.86 and 2.19, corresponding to a difference decrease between rates of 23.4%. For aortic dissection, ruptured and non-ruptured aneurysms, the overall mean ages at death were, respectively, 63.2, 68.4 and 71.6 years; while, as the underlying cause, the main associated causes of death were as follows: hemorrhages (in 43.8%/40.5%/13.9%); hypertensive diseases (in 49.2%/22.43%/24.5%) and atherosclerosis (in 14.8%/25.5%/15.3%); and, as associated causes, their principal overall underlying causes of death were diseases of the circulatory (55.7%), and respiratory (13.8%) systems and neoplasms (7.8%). A significant seasonal variation, with highest frequency in winter, occurred in deaths identified as underlying cause for aortic dissection, ruptured and non-ruptured aneurysms. Conclusions: This study introduces the methodology of multiple-causes-of-death to enhance epidemiologic knowledge of aortic aneurysm and dissection in Sao Paulo, Brazil. The results presented confer light to the importance of mortality statistics and the need for epidemiologic studies to understand unique trends in our own population.

Correlates of the incidence of disability and mortality among older adult Brazilians with and without diabetes mellitus and stroke

Background: The combined effect of diabetes and stroke on disability and mortality remains largely unexplored in Brazil and Latin America. Previous studies have been based primarily on data from developed countries. This study addresses the empirical gap by evaluating the combined impact of diabetes and stroke on disability and mortality in Brazil. Methods: The sample was drawn from two waves of the Survey on Health and Well-being of the Elderly, which followed 2,143 older adults in Sao Paulo, Brazil, from 2000 to 2006. Disability was assessed via measures of activities of daily living (ADL) limitations, severe ADL limitations, and receiving assistance to perform these activities. Logistic and multinomial regression models controlling for sociodemographic and health conditions were used to address the influence of diabetes and stroke on disability and mortality. Results: By itself, the presence of diabetes did not increase the risk of disability or the need for assistance; however, diabetes was related to increased risks when assessed in combination with stroke. After controlling for demographic, social and health conditions, individuals who had experienced stroke but not diabetes were 3.4 times more likely to have ADL limitations than those with neither condition (95% CI 2.26-5.04). This elevated risk more than doubled for those suffering from a combination of diabetes and stroke (OR 7.34, 95% CI 3.73-14.46). Similar effects from the combination of diabetes and stroke were observed for severe ADL limitations (OR 19.75, 95% CI 9.81-39.76) and receiving ADL assistance (OR 16.57, 95% CI 8.39-32.73). Over time, older adults who had experienced a stroke were at higher risk of remaining disabled (RRR 4.28, 95% CI 1.53, 11.95) and of mortality (RRR 3.42, 95% CI 1.65, 7.09). However, risks were even higher for those who had experienced both diabetes and stroke. Diabetes was associated with higher mortality. Conclusions: Findings indicate that a combined history of stroke and diabetes has a great impact on disability prevalence and mortality among older adults in Sao Paulo, Brazil.

Infant mortality in Brazil, 1980-2000: A spatial panel data analysis

Background: Infant mortality is an important measure of human development, related to the level of welfare of a society. In order to inform public policy, various studies have tried to identify the factors that influence, at an aggregated level, infant mortality. The objective of this paper is to analyze the regional pattern of infant mortality in Brazil, evaluating the effect of infrastructure, socio-economic, and demographic variables to understand its distribution across the country. Methods: Regressions including socio-economic and living conditions variables are conducted in a structure of panel data. More specifically, a spatial panel data model with fixed effects and a spatial error autocorrelation structure is used to help to solve spatial dependence problems. The use of a spatial modeling approach takes into account the potential presence of spillovers between neighboring spatial units. The spatial units considered are Minimum Comparable Areas, defined to provide a consistent definition across Census years. Data are drawn from the 1980, 1991 and 2000 Census of Brazil, and from data collected by the Ministry of Health (DATASUS). In order to identify the influence of health care infrastructure, variables related to the number of public and private hospitals are included. Results: The results indicate that the panel model with spatial effects provides the best fit to the data. The analysis confirms that the provision of health care infrastructure and social policy measures (e. g. improving education attainment) are linked to reduced rates of infant mortality. An original finding concerns the role of spatial effects in the analysis of IMR. Spillover effects associated with health infrastructure and water and sanitation facilities imply that there are regional benefits beyond the unit of analysis. Conclusions: A spatial modeling approach is important to produce reliable estimates in the analysis of panel IMR data. Substantively, this paper contributes to our understanding of the physical and social factors that influence IMR in the case of a developing country.

Cause-specific mortality and income inequality in Sao Paulo, Brazil

OBJECTIVE: To analyze cause-specifi c mortality rates according to the relative income hypothesis. METHODS: All 96 administrative areas of the city of Sao Paulo, southeastern Brazil, were divided into two groups based on the Gini coefficient of income inequality: high (>= 0.25) and low (<0.25). The propensity score matching method was applied to control for confounders associated with socioeconomic differences among areas. RESULTS: The difference between high and low income inequality areas was statistically significant for homicide (8.57 per 10,000; 95% CI: 2.60; 14.53); ischemic heart disease (5.47 per 10,000 [95% CI 0.76; 10.17]); HIV/AIDS (3.58 per 10,000 [95% CI 0.58; 6.57]); and respiratory diseases (3.56 per 10,000 [95% CI 0.18; 6.94]). The ten most common causes of death accounted for 72.30% of the mortality difference. Infant mortality also had signifi cantly higher age-adjusted rates in high inequality areas (2.80 per 10,000 [95% CI 0.86; 4.74]), as well as among males (27.37 per 10,000 [95% CI 6.19; 48.55]) and females (15.07 per 10,000 [95% CI 3.65; 26.48]). CONCLUSIONS: The study results support the relative income hypothesis. After propensity score matching cause-specifi c mortality rates was higher in more unequal areas. Studies on income inequality in smaller areas should take proper accounting of heterogeneity of social and demographic characteristics.

Propensity score matching approach to test the association of income inequality and mortality in Sao Paulo, Brazil

Background Support for the adverse effect of high income inequality on population health has come from studies that focus on larger areas, such as the US states, while studies at smaller geographical areas (eg, neighbourhoods) have found mixed results. Methods We used propensity score matching to examine the relationship between income inequality and mortality rates across 96 neighbourhoods (distritos) of the municipality of Sao Paulo, Brazil. Results Prior to matching, higher income inequality distritos (Gini >= 0.25) had slightly lower overall mortality rates (2.23 per 10 000, 95% CI -23.92 to 19.46) compared to lower income inequality areas (Gini <0.25). After propensity score matching, higher inequality was associated with a statistically significant higher mortality rate (41.58 per 10 000, 95% CI 8.85 to 73.3). Conclusion In Sao Paulo, the more egalitarian communities are among some of the poorest, with the worst health profiles. Propensity score matching was used to avoid inappropriate comparisons between the health status of unequal (but wealthy) neighbourhoods versus equal (but poor) neighbourhoods. Our methods suggest that, with proper accounting of heterogeneity between areas, income inequality is associated with worse population health in Sao Paulo.