Wildfire, deforestation and health in tropical rainforest areas: a scoping review protocol.

INTRODUCTION: Wildfires and deforestation potentially have direct effects on multiple health outcomes as well as indirect consequences for climate change. Tropical rainforest areas are characterised by high rainfall, humidity and temperature, and they are predominantly found in low-income and middle-income countries. This study aims to synthesise the methods, data and health outcomes reported in scientific papers on wildfires and deforestation in these locations. METHODS AND ANALYSIS: We will carry out a scoping review according to the Joanna Briggs Institute's (JBI) manual for scoping reviews and the framework proposed by Arksey and O'Malley, and Levac et al. The search for articles was performed on 18 August 2023, in 16 electronic databases using Medical Subject Headings terms and adaptations for each database from database inception. The search for local studies will be complemented by the manual search in the list of references of the studies selected to compose this review. We screened studies written in English, French, Portuguese and Spanish. We included quantitative studies assessing any human disease outcome, hospitalisation and vital statistics in regions of tropical rainforest. We exclude qualitative studies and quantitative studies whose outcomes do not cover those of interest. The text screening was done by two independent reviewers. Subsequently, we will tabulate the data by the origin of the data source used, the methods and the main findings on health impacts of the extracted data. The results will provide descriptive statistics, along with visual representations in diagrams and tables, complemented by narrative summaries as detailed in the JBI guidelines. ETHICS AND DISSEMINATION: The study does not require an ethical review as it is meta-research and uses published, deidentified secondary data sources. The submission of results for publication in a peer-reviewed journal and presentation at scientific and policymakers' conferences is expected. STUDY REGISTRATION: Open Science Framework (https://osf.io/pnqc7/).

Income Segregation, Conditional Cash Transfers, and Breast Cancer Mortality Among Women in Brazil.

Importance: Women living in income-segregated areas are less likely to receive adequate breast cancer care and access community resources, which may heighten breast cancer mortality risk. Objective: To investigate the association between income segregation and breast cancer mortality and whether this association is attenuated by receipt of the Bolsa Família program (BFP), the world's largest conditional cash-transfer program. Design, Setting, and Participants: This cohort study was conducted using data from the 100 Million Brazilian Cohort, which were linked with nationwide mortality registries (2004-2015). Data were analyzed from December 2021 to June 2023. Study participants were women aged 18 to 100 years. Exposure: Women's income segregation (high, medium, or low) at the municipality level was obtained using income data from the 2010 Brazilian census and assessed using dissimilarity index values in tertiles (low [0.01-0.25], medium [0.26-0.32], and high [0.33-0.73]). Main Outcomes and Measures: The main outcome was breast cancer mortality. Mortality rate ratios (MRRs) for the association of segregation with breast cancer deaths were estimated using Poisson regression adjusted for age, race, education, municipality area size, population density, area of residence (rural or urban), and year of enrollment. Multiplicative interactions of segregation and BFP receipt (yes or no) in the association with mortality (2004-2015) were assessed. Results: Data on 21 680 930 women (mean [SD] age, 36.1 [15.3] years) were analyzed. Breast cancer mortality was greater among women living in municipalities with high (adjusted MRR [aMRR], 1.18; 95% CI, 1.13-1.24) and medium (aMRR, 1.08; 95% CI, 1.03-1.12) compared with low segregation. Women who did not receive BFP had higher breast cancer mortality than BFP recipients (aMRR, 1.17; 95% CI, 1.12-1.22). By BFP strata, women who did not receive BFP and lived in municipalities with high income segregation had a 24% greater risk of death from breast cancer compared with those living in municipalities with low income segregation (aMRR, 1.24: 95% CI, 1.14-1.34); women who received BFP and were living in areas with high income segregation had a 13% higher risk of death from breast cancer compared with those living in municipalities with low income segregation (aMRR, 1.13; 95% CI, 1.07-1.19; P for interaction = .008). Stratified by the amount of time receiving the benefit, segregation (high vs low) was associated with an increase in mortality risk for women receiving BFP for less time but not for those receiving it for more time (<4 years: aMRR, 1.16; 95% CI, 1.07-1.27; 4-11 years: aMRR, 1.09; 95% CI, 1.00-1.17; P for interaction <.001). Conclusions and Relevance: These findings suggest that place-based inequities in breast cancer mortality associated with income segregation may be mitigated with BFP receipt, possibly via improved income and access to preventive cancer care services among women, which may be associated with early detection and treatment and ultimately reduced mortality.

A scaling investigation of urban form features in Latin America cities.

This paper examines scaling behaviors of urban landscape and street design metrics with respect to city population in Latin America. We used data from the SALURBAL project, which has compiled and harmonized data on health, social, and built environment for 371 Latin American cities above 100,000 inhabitants. These metrics included total urbanized area, effective mesh size, area in km2 and number of streets. We obtained scaling relations by regressing log(metric) on log (city population). The results show an overall sub-linear scaling behavior of most variables, indicating a relatively lower value of each variable in larger cities. We also explored the potential influence of colonization on the current built environment, by analyzing cities colonized by Portuguese (Brazilian cities) or Spaniards (Other cities in Latin America) separately. We found that the scaling behaviors are similar for both sets of cities.

Racial and economic segregation in Brazil: a nationwide analysis of socioeconomic and socio-spatial inequalities / Segregação racial e econômica no Brasil: uma análise nacional das desigualdades socioeconômicas e socioespaciais / Segregación racial y económica en Brasil: un análisis nacional de las desigualdades socioeconómicas y socioespaciales

Abstract This article aims to analyze residential segregation by race (racial segregation) and income (economic segregation) in Brazil and explore its relationship with socioeconomic and socio-spatial factors. Residential segregation was assessed using the dissimilarity index based on the 2010 demographic census and considering urban census tracts since segregation is sociologically considered an urban problem. The results for racial segregation showed that it is more evident in cities in the South and Southeast of Brazil and mainly affects the self-declared black population. The approach used to calculate economic segregation involved examining the income level of different low-income groups. Therefore, we consider families that earned between 0 and 1 minimum wage as the group with the greatest social vulnerability. We did not find significant correlations between racial and income segregation indices with aspects such as urbanization (urban population size). Finally, we present the racial segregation indices stratifying families by income thresholds for the 27 Brazilian capitals and conclude that per capita household income is a preponderant factor for the segregation of the poorest, especially in families whose residents self-identify as black.

Resumo Este artigo tem como objetivo analisar a segregação residencial por raça (segregação racial) e renda (segregação econômica) no Brasil e explorar sua relação com fatores socioeconômicos e socioespaciais. A segregação residencial foi avaliada pelo índice de dissimilaridade baseado no Censo Demográfico de 2010 e considerando setores censitários urbanos, uma vez que a segregação é entendida sociologicamente como um problema urbano. Os resultados mostram que a segregação racial é mais evidente nas cidades do Sul e Sudeste do Brasil, atingindo principalmente a população autodeclarada preta. A abordagem utilizada para calcular a segregação econômica envolveu examinar o nível de renda de diferentes grupos de baixa renda. Portanto, consideramos as famílias que ganham entre 0 e 1 salário mínimo - o grupo de maior vulnerabilidade social. Não encontramos correlações significativas entre os índices de segregação racial e de renda com fatores como a urbanização (tamanho da população urbana). Por fim, apresentamos os índices de segregação racial estratificando as famílias por faixas de renda para as 27 capitais brasileiras e concluímos que a renda domiciliar per capita é fator preponderante para a segregação dos mais pobres, principalmente nas famílias cujos moradores se autodeclaram pretos.

Resumen Este artículo tiene como objetivo analizar la segregación residencial por raza (segregación racial) y renta (segregación económica) en Brasil y explorar su relación con factores socioeconómicos y socioespaciales. La segregación residencial se evaluó utilizando el índice de disimilitud con base en el censo demográfico de 2010 y considerando las secciones censales urbanas ya que la segregación es considerada sociológicamente como un problema urbano. Los resultados para la segregación racial mostraron que esta es más evidente en ciudades del sur y del sudeste de Brasil y que afecta principalmente a la población autodeclarada negra. El enfoque usado para calcular la segregación económica implicó examinar el nivel de ingresos de diferentes grupos de bajos ingresos. Por lo tanto, consideramos que las familias que ganaban entre cero y un salario mínimo son el grupo con mayor vulnerabilidad social. No encontramos correlaciones significativas entre los índices de segregación racial y los de ingresos con factores como la urbanización (tamaño de la población urbana). Finalmente, presentamos los índices de segregación racial estratificando a las familias por umbrales de renta para las 27 capitales brasileñas y concluimos que la renta per cápita de los hogares es un factor preponderante para la segregación de los más pobres, en especial en las familias cuyos habitantes se autodeclaran negros.

Association of urban inequality and income segregation with COVID-19 mortality in Brazil.

Socioeconomic factors have exacerbated the impact of COVID-19 worldwide. Brazil, already marked by significant economic inequalities, is one of the most affected countries, with one of the highest mortality rates. Understanding how inequality and income segregation contribute to excess mortality by COVID-19 in Brazilian cities is essential for designing public health policies to mitigate the impact of the disease. This paper aims to fill in this gap by analyzing the effect of income inequality and income segregation on COVID-19 mortality in large urban centers in Brazil. We compiled weekly COVID-19 mortality rates from March 2020 to February 2021 in a longitudinal ecological design, aggregating data at the city level for 152 Brazilian cities. Mortality rates from COVID-19 were compared across weeks, cities and states using mixed linear models. We estimated the associations between COVID-19 mortality rates with income inequality and income segregation using mixed negative binomial models including city and week-level random intercepts. We measured income inequality using the Gini index and income segregation using the dissimilarity index using data from the 2010 Brazilian demographic census. We found that 88.2% of COVID-19 mortality rates variability was between weeks, 8.5% between cities, and 3.3% between states. Higher-income inequality and higher-income segregation values were associated with higher COVID-19 mortality rates before and after accounting for all adjustment factors. In our main adjusted model, rate ratios (RR) per 1 SD increases in income inequality and income segregation were associated with 17% (95% CI 9% to 26%) and 11% (95% CI 4% to 19%) higher mortality. Income inequality and income segregation are long-standing hallmarks of large Brazilian cities. Risk factors related to the socioeconomic context affected the course of the pandemic in the country and contributed to high mortality rates. Pre-existing social vulnerabilities were critical factors in the aggravation of COVID-19, as supported by the observed associations in this study.

Inequality and income segregation in Brazilian cities: a nationwide analysis.

Residential segregation has brought significant challenges to cities worldwide and has important implications for health. This study aimed to assess income segregation in the 152 largest Brazilian cities in the SALURBAL Project. We identify specific socioeconomic characteristics related to residential segregation by income using the Brazilian demographic census of 2010 and calculated the income dissimilarity index (IDI) at the census tract level for each city, subsequently comparing it with Gini and other local socioeconomic variables. We evaluated our results' robustness using a bootstrap correction to the IDI to examine the consequences of using different income cut-offs in substantial urban and regional inequalities. We identified a two minimum wage cut-off as the most appropriate. We found little evidence of upward bias in the calculation of the IDI regardless of the cut-off used. Among the ten most segregated cities, nine are in the Northeast region, with Brazil's highest income inequality and poverty. Our results indicate that the Gini index and poverty are the main variables associated with residential segregation. Supplementary Information: The online version contains supplementary material available at 10.1007/s43545-022-00491-9.

Racial Inequities in Self-Rated Health Across Brazilian Cities: Does Residential Segregation Play a Role?

Racial health inequities may be partially explained by area-level factors such as residential segregation. In this cross-sectional study, using a large, multiracial, representative sample of Brazilian adults (n = 37,009 individuals in the 27 state capitals; National Health Survey (Pesquisa Nacional de Saúde), 2013), we investigated 1) whether individual-level self-rated health (SRH) (fair or poor vs. good or better) varies by race (self-declared White, Brown, or Black) and 2) whether city-level economic or racial residential segregation (using dissimilarity index values in tertiles: low, medium, and high) interacts with race, increasing racial inequities in SRH. Prevalence of fair or poor SRH was 31.5% (Black, Brown, and White people: 36.4%, 34.0%, and 27.3%, respectively). Marginal standardization based on multilevel logistic regression models, adjusted for age, gender, and education, showed that Black and Brown people had, respectively, 20% and 10% higher prevalence of fair or poor SRH than did White people. Furthermore, residential segregation interacted with race such that the more segregated a city, the greater the racial gap among Black, Brown, and White people in fair or poor SRH for both income and race segregation. Policies to reduce racial inequities may need to address residential segregation and its consequences for health.

Scaling of mortality in 742 metropolitan areas of the Americas.

We explored how mortality scales with city population size using vital registration and population data from 742 cities in 10 Latin American countries and the United States. We found that more populated cities had lower mortality (sublinear scaling), driven by a sublinear pattern in U.S. cities, while Latin American cities had similar mortality across city sizes. Sexually transmitted infections and homicides showed higher rates in larger cities (superlinear scaling). Tuberculosis mortality behaved sublinearly in U.S. and Mexican cities and superlinearly in other Latin American cities. Other communicable, maternal, neonatal, and nutritional deaths, and deaths due to noncommunicable diseases were generally sublinear in the United States and linear or superlinear in Latin America. Our findings reveal distinct patterns across the Americas, suggesting no universal relation between city size and mortality, pointing to the importance of understanding the processes that explain heterogeneity in scaling behavior or mortality to further advance urban health policies.

Urban income segregation and homicides: An analysis using Brazilian cities selected by the Salurbal project.

This paper investigates the associations of income segregation with homicide mortality across 152 cities in Brazil. Despite GDP increases, an important proportion of the Brazilian population experiences poverty and extreme poverty. Segregation refers to the way that different groups are located in space based on their socioeconomic status, with groups defined based on education, unemployment, race, age, or income levels. As a measure of segregation, the dissimilarity index showed that overall, it would be necessary to relocate 29.7% of urban low-income families to make the spatial distribution of income homogeneous. For the ten most segregated cities, relocation of more than 37% of families would be necessary. Using negative binomial models, we found a positive association between segregation and homicides for Brazilian cities: one standard deviation higher segregation index was associated with a 50% higher homicide rate when we analyze all the socioeconomic context. Income segregation is potentially an important determinant of homicides, and should be considered in setting public policies.

Socio-economic urban scaling properties: Influence of regional geographic heterogeneities in Brazil.

The recent efforts dedicated to understanding important features and consequences of city growth have profited from the scaling approach to urban indicators. This kind of analysis can be conveniently used to investigate the impact of geo-economic transformations, like fast urbanization and industrial development, which occurred in continental size countries (e.g., India, China, and Brazil) during the past half-century. Profiting from high quality data, this work explores how scaling relationships among urban indicators are influenced by strong regional heterogeneities in Brazil. It is based on economic, infrastructure and violence related data sets for the time interval 2002-2016. Results indicate that regional specificities related to infrastructure, economic development, and geography have a larger influence on the absolute value of the urban indexes. Regional scaling similarities and differences among Brazilian regions were also uncovered. Interesting enough, the results indicate that the richest and poorest Brazilian regions share similar scaling behavior, despite all huge different local influences. By contrast, the results for the two richest regions, with similar average values of urban indexes and the same kind of local influences have rather different scaling properties. Thus, scaling analysis suggests that distinct political solutions might be necessary to improve life's quality, even for two regions with similar average values of urban indicators.