Economic growth and increased urbanization pose a new risk for cancer development: the exposure of high numbers of people to ambient air pollution. Epidemiological evidence that links air pollution to mortality from lung cancer is robust. An ability to produce high-quality scientific research that addresses these risks and the ability of local health authorities to understand and respond to these risks are basic requirements to solve the conflict between economic development and the preservation of human health. However, this is currently far from being achieved. Thus, this Science and Society article addresses the possibilities of expanding scientific networking to increase awareness of the risk of lung cancer that is promoted by air pollution.

Access to public open space is important to increase leisure-time walking (LTW) in high-income countries, but there is little evidence in middle-income countries. We conducted a cross-sectional analysis to examine the relationship between LTW and the presence of different public open spaces (parks, bike paths, and squares) and the mix of these recreational destinations near the homes of adults participating in the Sao Paulo Health Survey (n = 3145). LTW was evaluated by a questionnaire. We delineated buffers (500, 1000, and 1500 m) from the geographic coordinates of the adults’ residential addresses using a geographic information system. We used multilevel logistic regression taking account of clustering by census tracts and households, and with adjustment for social, demographics, and health characteristics. The main results showed that the presence of at least two recreational destinations within a 500-m buffer of participants’ homes were associated with an increased odds of LTW compared with no destinations present (OR = 1.65; 95% CI 1.09–2.55). No associations were found for destinations further away. These results support actions outlined in the new urban plan for Sao Paulo city and could be used to highlight the importance access to a mix of public open spaces to promote physical activity in megacities of middle-income countries.

Abstractobjectives To investigate spatial clusters and possible associations between relative risks of leprosy with socio-economic and environmental factors, taking into account diagnosed cases in children under 15 years old.methods An ecological study was conceived using data aggregated by municipality to identify possible spatial clusters of leprosy from 2005 to 2011. Relative risks were calculated accounting for the respective covariate gender. The second stage of the analysis consisted of verifying possible associations between the relative risks of leprosy as a dependent variable, and socio-economic and environmental variables as independent. This was performed using a multivariate regression analysis according to a previously defined conceptual framework.results Overall rates have decreased from 0.88/10 000 in 2005 to 0.52 in 2011. Spatial scan statistics identified 4 high-risk and 6 low-risk clusters. In the regression model, after allowing for spatial dependence, relative risks were associated with higher percentage of water bodies, higher Gini index, higher percentage of urban population, larger average number of dwellers by permanent residence and smaller percentage of residents born in Bahia.conclusions Although relative risks of leprosy in Bahia have been decreasing, they remain very high. The association between relative risks of leprosy and water bodies in the proposed geographic scale indicates that hypothesis linking M. leprae and humid environments cannot be discarded. Socioeconomic conditions such as inequality, a greater number of dwellers by residence and migration are derived from the urbanisation process carried out in this State. Precarious settlements and poor living conditions in the cities would favour the continuity of leprosy transmission.keywords leprosy, spatial scan statistic, environmental factors, socio-economic factors, spatial regression, Brazil

Background Currently, Brazil is experiencing one of the fastest increasing coronavirus disease (COVID-19) mortality rates worldwide, with a minimum of 158,000 confirmed deaths presently. The city of São Paulo is particularly vulnerable because it is the most populated city in Brazil. Thus, this study aimed to analyse COVID-19 mortality in a spatiotemporal context in São Paulo, with respect to socio-economic levels. Method We modelled the deaths using spatiotemporal architectures and Poisson probability distributions using a latent Gaussian Bayesian model approach. Results Both total deaths and confirmed deaths showed similar spatial patterns. Mortality was higher in men and increased with age. The most critical period regarding mortality occurred between the 20 th and 23 rd epidemiological weeks, followed by an apparent stabilisation of the epidemiological trend. The risk of death was greater in areas with the worst social conditions during the study period. However, this pattern was not uniform over time, since we identified a shift of high risk from the areas with the best socio-economic conditions to those with the worst conditions. Conclusions Our study corroborated the relationship between COVID-19 mortality and socio-economic conditions, revealing the importance of geographic screening in the integration of better actions to face the pandemic.

The individual's socioeconomic conditions are the most relevant to predict the quality of someone's health. However, such information is not usually found in medical records, making studies in the area difficult. Therefore, it is common to use composite indices that characterize a region socioeconomically, such as the Human Development Index (HDI). The main advantage of the HDI is its understanding and adoption on a global scale. However, its applicability is limited for health studies since its longevity dimension presents mathematical redundancy in regression models. Here we introduce the GeoSES, a composite index that summarizes the main dimensions of the Brazilian socioeconomic context for research purposes. We created the index from the 2010 Brazilian Census, whose variables selection was guided by theoretical references for health studies. The proposed index incorporates seven socioeconomic dimensions: