Maternal exposure to ambient temperature and birth defects in Brazil: a nationwide case-control study of over 11 million newborns.

Maternal exposure to extreme ambient temperature during pregnancy has been proposed as a potential risk factor for birth defects. Comprehensive investigations on this association remain limited, particularly in low- and middle-income countries. This study aims to examine the association between ambient temperature exposure during pregnancy and the risk of birth defects in Brazil, contributing to the broader understanding of environmental influences on birth outcomes. Using a large dataset of over 11 million live birth records, we analyzed 12 categories of birth defects, encompassing a time frame from 2001 to 2018. Ambient temperature data were assigned at the municipality level. For the exposure assessment, we considered two biologically driven pregnancy stages by dividing the gestational period into two specific windows: the first trimester (from week 1 to week 12) and the second trimester (from week 13 to week 28). We employed a two-stage case-control design. In the first stage, we applied a conditional logistic regression model to estimate the odds ratio (OR) for specific birth defects and each of the five Brazilian regions (North, Northeast, Midwest, Southeast, and South). The model was adjusted for potential confounding variables, including PM2.5, relative humidity, and socioeconomic status. Temporal trends were addressed using time-stratified sampling. In the second stage, we used mixed-effects meta-analysis to pool region-specific estimates. Our analysis revealed a significant association between maternal exposure to higher ambient temperatures during the first trimester and an increased risk of specific birth defect categories, including those affecting the genital organs (OR = 1.08, 95% CI: 1.02; 1.14), digestive system (OR = 1.12, 95% CI: 1.06; 1.19); circulatory system (OR = 1.08, 95% CI: 1.01; 1.17); eyes, ears, face, and neck (OR = 1.08, 95% CI: 1.02; 1.15); benign neoplasms tumors (OR = 1.17, 95% CI: 1.03; 1.32), musculoskeletal system (OR = 1.03, 95% CI: 1.01; 1.05); and other congenital anomalies (OR = 1.22, 95% CI: 1.15; 1.29). The associations with respiratory system, nervous system, and chromosomal anomalies were null. These findings have significant implications for public health policies aimed at mitigating the impact of environmental factors on birth outcomes, both in Brazil and globally.

SARS-CoV-2 transmission in a highly vulnerable population of Brazil: a household cohort study.

Background: Household transmission studies seek to understand the transmission dynamics of a pathogen by estimating the risk of infection from household contacts and community exposures. We estimated within/extra-household SARS-CoV-2 infection risk and associated factors in a household cohort study in one of the most vulnerable neighbourhoods in Rio de Janeiro city. Methods: Individuals ≥1 years-old with suspected or confirmed COVID-19 in the past 30 days (index cases) and household members aged ≥1 year were enrolled and followed at 14 and 28 days (study period November/2020-December/2021). RT-PCR testing, COVID-19 symptoms, and SARS-CoV-2 serologies were ascertained in all visits. Chain binomial household transmission models were fitted using data from 2024 individuals (593 households). Findings: Extra-household infection risk was 74.2% (95% credible interval [CrI] 70.3-77.8), while within-household infection risk was 11.4% (95% CrI 5.7-17.2). Participants reporting having received two doses of a COVID-19 vaccine had lower extra-household (68.9%, 95% CrI 57.3-77.6) and within-household (4.1%, 95% CrI 0.4-16.6) infection risk. Within-household infection risk was higher among participants aged 10-19 years, from overcrowded households, and with low family income. Contrastingly, extra-household infection risk was higher among participants aged 20-29 years, unemployed, and public transportation users. Interpretation: Our study provides important insights into COVID-19 household/community transmission in a vulnerable population that resided in overcrowded households and who struggled to adhere to lockdown policies and social distancing measures. The high extra-household infection risk highlights the extreme social vulnerability of this population. Prioritising vaccination of the most socially vulnerable could protect these individuals and reduce widespread community transmission. Funding: Fundação Oswaldo Cruz, CNPq, FAPERJ, Royal Society, Instituto Serrapilheira, FAPESP.

Greenness and Hospitalization for Cardiorespiratory Diseases in Brazil.

BACKGROUND: The potential health benefits of exposure to vegetation, or greenness, are well documented, but there are few nationwide studies in Brazil, a country facing challenges related to land-use planning, deforestation, and environmental health risks. OBJECTIVES: In this study, we investigated the association between greenness and hospitalizations for cardiorespiratory diseases in Brazil. METHODS: We accessed hospital admissions data from 967,771 postal codes (a total of 26,724,624 admissions) covering Brazil for the period between 2008 and 2018. We used Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to measure greenness at the postal-code level. First, we applied a quasi-Poisson regression model to estimate the association between greenness and hospitalizations for circulatory and respiratory diseases, adjusted for air pollution, weather variables, and area-level socioeconomic status. We stratified the analyzes by sex, age group, health outcome, and Brazilian regions. In the second stage, we performed a meta-analysis to estimate pooled effects across the Brazilian regions. RESULTS: The national meta-analysis for the whole population, incorporating both urban and nonurban areas, showed that higher levels of greenness were associated with a lower risk of hospitalizations for circulatory diseases. An interquartile range (IQR=0.18) increase in average NDVI was associated with a 17% (95% confidence interval: 8%, 27%) lower risk of cardiovascular admissions. In contrast, there was no association found between greenness and respiratory admissions. When specifically examining urban areas, the results remained consistent with the overall findings. However, the analyses of nonurban areas revealed divergent results, suggesting that higher levels of greenness in rural regions are associated with a lower risk of hospital admissions for both circulatory and respiratory diseases. DISCUSSION: The findings emphasize the importance of prioritizing the preservation and creation of green spaces in urban areas as a means of promoting cardiovascular health in Brazil. https://doi.org/10.1289/EHP13442.

Weather impact on ambient air pollution and its association with land use types/activities over 5,572 municipalities in Brazil.

Quantify the impact of meteorological changes on air pollution levels is the aim of numerous recent studies. However, there is still a lack of investigations assessing the influence of land use/activities on the relationship between climate and air quality. In this study, we used a two-stage design to estimate the influence of land use types and activities on the association between weather changes and air pollution (PM2.5, NO2, SO2, O3) over 5572 municipalities in Brazil. To calculate the influence of recent weather change on air pollution concentration for each municipality, we used the "weather penalty" concept. This approach considers differences in linear trend coefficients between two generalized additive models. Then, using quantile regression, we estimated the effect of land use types and activities (8 variables related to transportation, energy generation, and land use) on weather-related increases in ambient air pollution. We found that an increase in PM2.5 was associated to recent weather changes in most municipalities (average increase of 0.07µg/m3per year) and a decrease in NO2 in most municipalities (average decrease of 0.0003 ppb per year). O3 and SO2 had more intense increases associated with weather changes in the North region. Our findings suggest the most robust positive associations between weather penalties on PM2.5 and areas with non-clean energy and oil refineries (average increase of 0.006µg/m3per year and 0.04µg/m3per year, respectively). We also found positive associations between Pasture areas, urban areas, and transportation and the weather penalties of this pollutant. In contrast, forest areas were negatively associated with PM2.5 penalties. We also found that oil refineries, urban areas, and transportation significantly positively influenced weather penalties for SO2 and O3. Overall, the study highlights the importance of considering the influence of land use types and activities on weather-related changes in ambient air pollution.

Thermal stress and hospital admissions for cardiorespiratory disease in Brazil.

The growing body of scientific literature underscores the intricate relationship between meteorological conditions and human health, particularly in the context of extreme temperatures. However, conventional temperature-centric approaches often fall short in capturing the complexity of thermal stress experienced by individuals. Temperature alone, as a metric, fails to encompass the entirety of the thermal stress individuals face, necessitating a more nuanced understanding. In response to this limitation, climatologists have devised thermal indices-composite measures meticulously crafted to reflect the intricate interplay of meteorological factors influencing human perception of temperature. Recognizing the inadequacy of simplistic temperature-focused methodologies, our study aims to address the multifaceted nature of thermal stress. In this study, we explored the association between thermal indices and hospital admissions for circulatory and respiratory diseases in Brazil. We used an extensive dataset spanning 11 years (2008-2018) from the Brazilian Ministry of Health, encompassing a total of 23,791,093 hospitalizations for circulatory and respiratory diseases. We considered four distinct thermal indices-Discomfort Index (DI), Net Effective Temperature (NET), Humidex (H), and Heat Index (HI). We used an extension of the two-stage design with a case time series to assess this relationship. In the first stage, we applied a distributed lag non-linear modeling framework to create a cross-basis function. We next applied quasi-Poisson regression models adjusted by time-varying confounders. In the second stage, we applied meta-analysis with random effects to estimate the national relative risk (RR). Our findings suggest robust variations among the thermal indices under examination. These variations underscore the intricate nature of associations between temperature and health, with each index capturing distinct aspects of thermal conditions. Our results indicate that extreme thermal conditions, both at the low and high ends, are associated with increased risks of hospital admissions. The diverse impact observed among different indices emphasizes the complex interplay between various meteorological factors and their specific physiological consequences. This underscores the necessity for a comprehensive comprehension of temperature metrics to guide precise public health interventions, recognizing the multifaceted nature of temperature-health relationships.

Urban structure types and students' academic performance.

In this study, we propose a novel approach for estimating the relationship between neighborhood characteristics and students' academic performance. We propose the concept of urban morphology by Urban Structure Types (USTs). USTs are spatial indicators that describe the urban system through its physical, environmental, and functional characteristics. Our academic performance data includes 344,175 students from 256 public schools in the Federal District (FD), Brazil. This is student-level academic achievement data from 2017 to 2020. We performed the UST mapping in the FD by using visual interpretation. We classified 21 different types of UST. We fit mixed-effects regression models with a student-specific random intercept and slope. The model was adjusted for temporal factors, SES factors, and variables representing the characteristics and the location of each school. Our findings suggest associations between several types of USTs surrounding schools and academic performance. Overall, areas characterized as low population density, with high green index, and high standard residences were associated with an increase in student performance. In contrast, areas that include old buildings near streets, with significant traffic density, and areas with significant exposed soil (areas devasted) were associated with a decrease in student performance. The results of our study support the creation of effective educational and urban planning policies for local interventions. These interventions are likely to translate into healthier schools and improvements in children's behavioral development and learning performance.

Effects of land cover and air pollution on the risk of preterm births.

OBJECTIVE: To evaluate the association between gestational age and green areas, urban built areas, and the concentration of particulate matter 2.5 (PM2.5) in the city of São Paulo, analyzing the irregular distribution of these areas and pollution levels above the recommended level. METHODS: The study population consisted of a cohort of live births from 2012, and data from the Live Birth Information System (Sinasc) of the city of São Paulo were used. Using satellite images and supervised classification, the distribution and quantity of green areas and built areas in the city of São Paulo was obtained, as well as the concentrations of PM2.5. Logistic regressions were used to obtain possible associations. RESULTS: The results of the study show that a lower percentage of green areas is significantly associated with a higher chance of preterm births. A higher building density was positively associated with the odds ratio for preterm birth. We did not find any significant associations between air pollution (PM2.5) and preterm births. CONCLUSIONS: The results of this study show that greener areas are less associated with preterm births when compared with less green areas.

Effects of land cover and air pollution on the risk of preterm births / Efeitos da cobertura de solo e poluição do ar no risco de nascimentos prematuros

ABSTRACT OBJECTIVE To evaluate the association between gestational age and green areas, urban built areas, and the concentration of particulate matter 2.5 (PM2.5) in the city of São Paulo, analyzing the irregular distribution of these areas and pollution levels above the recommended level. METHODS The study population consisted of a cohort of live births from 2012, and data from the Live Birth Information System (Sinasc) of the city of São Paulo were used. Using satellite images and supervised classification, the distribution and quantity of green areas and built areas in the city of São Paulo was obtained, as well as the concentrations of PM2.5. Logistic regressions were used to obtain possible associations. RESULTS The results of the study show that a lower percentage of green areas is significantly associated with a higher chance of preterm births. A higher building density was positively associated with the odds ratio for preterm birth. We did not find any significant associations between air pollution (PM2.5) and preterm births. CONCLUSIONS The results of this study show that greener areas are less associated with preterm births when compared with less green areas.

RESUMO OBJETIVO Avaliar a associação entre a idade gestacional e as áreas verdes, áreas construídas urbanas e a concentração de material particulado 2,5 (MP2,5) em São Paulo, analisando a distribuição irregular dessas áreas e os níveis de poluição acima do recomendado. MÉTODOS A população utilizada no estudo foi a dos nascidos vivos no ano de 2012, com os dados do Sistema de Informações sobre Nascidos Vivo (Sinasc) na cidade de São Paulo. Por meio de imagens de satélites e realizando a classificação supervisionada, obtivemos a distribuição e quantidade de áreas verdes e de áreas construídas, na cidade de São Paulo, assim como as concentrações de MP2,5. Regressões logísticas foram utilizadas para obter possíveis associações. RESULTADOS Os resultados do estudo mostram que menor percentual de áreas verdes está associado significativamente com maior chance de prematuridade. Maior densidade de construção foi associada positivamente com a razão de chance de nascimento prematuro. Não encontramos resultados significativos entre a poluição do ar (MP2,5) e prematuridade. CONCLUSÕES Os resultados deste estudo demostraram que áreas mais verdes em relação às áreas menos verdes são menos associadas a nascimentos prematuros.

Wildfire exposure and academic performance in Brazil: A causal inference approach for spatiotemporal data.

As the frequency and intensity of wildfires are projected to globally amplify due to climate change, there is a growing need to quantify the impact of exposure to wildfires in vulnerable populations such as adolescents. In our study, we applied rigorous causal inference methods to estimate the effect of wildfire exposure on the academic performance of high school students in Brazil between 2009 and 2015. Using longitudinal data from 8,183 high schools across 1,571 municipalities in Brazil, we estimated that the average performance in most academic subjects decreases under interventions that increase wildfire exposure, e.g., a decrease of 1.8 % (p = 0.01) in the natural sciences when increasing the wildfire density from 0.0035 wildfires/km2 (first quantile in the sample) to 0.0222 wildfires/km2 (third quartile). Furthermore, these effects considerably worsened over time. Our findings highlight the adverse impact of wildfires on educational outcomes.

Short-term exposure to sulfur dioxide and daily mortality in Brazil: A nationwide time-series study between 2003-2017.

Sulfur dioxide (SO2), despite its ubiquitousness, there is relatively less epidemiological evidence regarding the health risks associated with SO2 compared to other pollutants, especially in low-income countries where there are high levels of SO2 emissions. In this study, we estimated the association between ambient SO2 exposure and daily mortality in Brazil over a period of 15 years (2003-2017). We used an extension of the two-stage time-series design in a time-series analytic approach with a distributed lag model. The study population consisted of 2,872,084 death records, with a higher proportion of male deaths observed across all-cause mortality (58%). The majority of the individuals were aged above 65 years. The mean SO2 concentration across the study period was 1.5 µg/m³ (range: 0.0 to 71.0). The national meta-analysis for the whole dataset (without stratification by sex and age) showed an uncertain association, in which a 10 µg/m3 increase in daily SO2 was associated with an RR of mortality of 1.015 (95%CI: 0.992; 1.037). Robust associations were observed only for the subgroup analysis of people 46-65 years old [RR = 1.050 (95%CI: 1.004; 1.096)] and men 46-65 years old [RR = 1.064 (95%CI: 1.005; 1.122)]. We found moderate heterogeneity in the national analysis, with an I2 of 21% for the subgroup of people 46-65 years old. Excess mortality fraction for people between 46 and 65 years old attributable to per 10 µg/m3 increase in SO2 was 2.93% (95% eCI: 0.29%-6.78%). These results highlight the need for targeted air pollution control policies to reduce the health burden of SO2 exposure in Brazil. Further research is needed to fully understand the mechanisms behind the age-specific and regional effects of SO2 on mortality.

Association of low and high ambient temperature with mortality for cardiorespiratory diseases in Brazil.

Extreme temperatures are a major public health concern, as they have been linked to an increased risk of mortality from circulatory and respiratory diseases. Brazil, a country with vast geographic and climatic variations, is particularly vulnerable to the health impacts of extreme temperatures. In this study, we examined the nationwide (considering 5572 municipalities) association of low and high ambient temperature (1st and 99th percentiles) with daily mortality for circulatory and respiratory diseases in Brazil between 2003 and 2017. We used an extension of the two-stage time-series design. First, we applied a case time series design in combination with distributed lag non-linear modeling (DLMN) framework to assess the association by Brazilian region. Here, the analyses were stratified by sex, age group (15-45, 46-65, and >65 years), and cause of death (respiratory and circulatory mortality). In the second stage, we performed a meta-analysis to estimate pooled effects across the Brazilian regions. Our study population included 1,071,090 death records due to cardiorespiratory diseases in Brazil over the study period. We found increased risk of respiratory and circulatory mortality associated with low and high ambient temperatures. The pooled national results for the whole population (all ages and sex) suggest a relative risk (RR) of 1.27 (95% CI: 1.16; 1.37) and 1.11 (95% CI: 1.01; 1.21) associated with circulatory mortality during cold and heat exposure, respectively. For respiratory mortality, we estimated a RR of 1.16 (95% CI: 1.08; 1.25) during cold exposure and a RR of 1.14 (95% CI: 0.99; 1.28) during heat exposure. The national meta-analysis indicated robust positive associations for circulatory mortality on cold days across several subgroups by sex and age, while only a few subgroups presented robust positive associations for circulatory mortality on warm days and respiratory mortality on both cold and warm days. These findings have important public health implications for Brazil and suggest the need for targeted interventions to mitigate the adverse effects of extreme temperatures on human health.

Association of high ambient temperature with daily hospitalization for cardiorespiratory diseases in Brazil: A national time-series study between 2008 and 2018.

Further research is needed to examine the nationwide impact of temperature on health in Brazil, a region with particular challenges related to climate conditions, environmental characteristics, and health equity. To address this gap, in this study, we looked at the relationship between high ambient temperature and hospital admissions for circulatory and respiratory diseases in 5572 Brazilian municipalities between 2008 and 2018. We used an extension of the two-stage design with a case time series to assess this relationship. In the first stage, we applied a distributed lag non-linear modeling framework to create a cross-basis function. We next applied quasi-Poisson regression models adjusted by PM2.5, O3, relative humidity, and time-varying confounders. We estimated relative risks (RRs) of the association of heat (percentile 99th) with hospitalization for circulatory and respiratory diseases by sex, age group, and Brazilian regions. In the second stage, we applied meta-analysis with random effects to estimate the national RR. Our study population includes 23,791,093 hospital admissions for cardiorespiratory diseases in Brazil between 2008 and 2018. Among those, 53.1% are respiratory diseases, and 46.9% are circulatory diseases. The robustness of the RR and the effect size varied significantly by region, sex, age group, and health outcome. Overall, our findings suggest that i) respiratory admissions had the highest RR, while circulatory admissions had inconsistent or null RR in several subgroup analyses; ii) there was a large difference in the cumulative risk ratio across regions; and iii) overall, women and the elderly population experienced the greatest impact from heat exposure. The pooled national results for the whole population (all ages and sex) suggest a relative risk of 1.29 (95% CI: 1.26; 1.32) associated with respiratory admissions. In contrast, national meta-analysis for circulatory admissions suggested robust positive associations only for people aged 15-45, 46-65, >65 years old; for men aged 15-45 years old; and women aged 15-45 and 46-65 years old. Our findings are essential for the body of scientific evidence that has assisted policymakers to promote health equity and to create adaptive measures and mitigations.

Low ambient temperature and hospitalization for cardiorespiratory diseases in Brazil.

Studies have shown that larger temperature-related health impacts may be associated with cold rather than with hot temperatures. Although it remains unclear the cold-related health burden in warmer regions, in particular at the national level in Brazil. We address this gap by examining the association between low ambient temperature and daily hospital admissions for cardiovascular and respiratory diseases in Brazil between 2008 and 2018. We first applied a case time series design in combination with distributed lag non-linear modeling (DLNM) framework to assess the association of low ambient temperature with daily hospital admissions by Brazilian region. Here, we also stratified the analyses by sex, age group (15-45, 46-65, and >65 years), and cause (respiratory and cardiovascular hospital admissions). In the second stage, we performed a meta-analysis to estimate pooled effects across the Brazilian regions. Our sample included more than 23 million hospitalizations for cardiovascular and respiratory diseases nationwide between 2008 and 2018, of which 53% were admissions for respiratory diseases and 47% for cardiovascular diseases. Our findings suggest that low temperatures are associated with a relative risk of 1.17 (95% CI: 1.07; 1.27) and 1.07 (95% CI: 1.01; 1.14) for cardiovascular and respiratory admissions in Brazil, respectively. The pooled national results indicate robust positive associations for cardiovascular and respiratory hospital admissions in most of the subgroup analyses. In particular, for cardiovascular hospital admissions, men and older adults (>65 years old) were slightly more impacted by cold exposure. For respiratory admissions, the results did not indicate differences among the population groups by sex and age. This study can help decision-makers to create adaptive measures to protect public health from the effects of cold temperature.

Economic and racial disparities of the weather impact on air quality in Brazil.

Several studies have quantified the air pollution exposure disparities across racial and income groups. However, there is still a lack of investigations assessing disparities related to the impacts of weather on air pollution, which could indicate target air pollution reduction strategies under different climate scenarios. Our study aims to address this gap by estimating the economic and racial disparities of the weather impact on air quality in Brazil between 2003 and 2018. First, we used a generalized additive approach to estimate the weather-related changes in PM2.5. This framework derived "weather penalty", which a positive penalty suggests that an increase in PM2.5 was associated with long-term weather changes in the study period. Then, we estimated the population-weighted weather penalty for racial and income groups. Average penalty for the White population (the most-exposed group) was 31% higher than that of the Pardo population (the least-exposed group, mainly people of light brown skin color) in Brazil. In the stratification analysis by region, the Midwest and South were the regions where the black population was the most-exposed group. For the income group, our results indicate that the high-income population group was the most-exposed group in all analyses, including the national and the regional analyses. These findings are somewhat surprising, as previous studies have shown that minority and low-income populations tend to be more exposed to air pollution, than white and higher-income populations. However, our study suggests that disparities in exposure to air pollution may be more complex and nuanced than previously thought. Further research is needed to better understand the underlying drivers of these environmental disparities, and to develop targeted interventions to reduce exposures.

Air quality and individual-level academic performance in Brazil: A nationwide study of more than 15 million students between 2000 and 2020.

Studies have shown that living and studying in places with poor air quality is associated with cognitive deficits. However, there is still a limitation in the literature in terms of study design and geographic location. Also, only a few studies have looked at the effects of more than one air pollutant. To address this research gap, in this study we estimated the association between air pollution (considering three criteria air pollutants - PM2.5, NO2, and O3) and academic performance (a proxy of cognitive performance) at the student level in Brazil between 2000 and 2020. We assessed academic performance data from a nationwide high school exam. The data included 15,443,772 students who took this national test between 2000 and 2020 in Brazil. Air pollution data was derived from satellite remote sensing observations. We fit mixed-effects regression models with a state-specific random intercept and adjusted for school characteristics, spatio-temporal factors, and socioeconomic status. We performed sub-group analyses by stratifying the analysis by type of school management (private or public), location of the school (urban or rural), sex, and periods. Our findings suggest air pollution exposure was associated with drops in the students' marks varying from 0.13% to 5.39%. To our knowledge, this is the first study that estimates the association between air pollution and individual-level academic performance in Brazil. This study is of substantial environmental and educational importance by supporting policymakers to improve the air quality surrounding schools.

The impact of wildfires on air pollution and health across land use categories in Brazil over a 16-year period.

Forest fires cause many environmental impacts, including air pollution. Brazil is a very fire-prone region where few studies have investigated the impact of wildfires on air quality and health. We proposed to test two hypotheses in this study: i) the wildfires in Brazil have increased the levels of air pollution and posed a health hazard in 2003-2018, and ii) the magnitude of this phenomenon depends on the type of land use and land cover (e.g., forest area, agricultural area, etc.). Satellite and ensemble models derived data were used as input in our analyses. Wildfire events were retrieved from Fire Information for Resource Management System (FIRMS), provided by NASA; air pollution data from the Copernicus Atmosphere Monitoring Service (CAMS); meteorological variables from the ERA-Interim model; and land use/cover data were derived from pixel-based classification of Landsat satellite images by MapBiomas. We used a framework that infers the "wildfire penalty" by accounting for differences in linear pollutant annual trends (ß) between two models to test these hypotheses. The first model was adjusted for Wildfire-related Land Use activities (WLU), considered as an adjusted model. In the second model, defined as an unadjusted model, we removed the wildfire variable (WLU). Both models were controlled by meteorological variables. We used a generalized additive approach to fit these two models. To estimate mortality associated with wildfire penalties, we applied health impact function. Our findings suggest that wildfire events between 2003 and 2018 have increased the levels of air pollution and posed a significant health hazard in Brazil, supporting our first hypothesis. For example, in the Pampa biome, we estimated an annual wildfire penalty of 0.005 µg/m3 (95%CI: 0.001; 0.009) on PM2.5. Our results also confirm the second hypothesis. We observed that the greatest impact of wildfires on PM2.5 concentrations occurred in soybean areas in the Amazon biome. During the 16 years of the study period, wildfires originating from soybean areas in the Amazon biome were associated with a total penalty of 0.64 µg/m3 (95%CI: 0.32; 0.96) on PM2.5, causing an estimated 3872 (95%CI: 2560; 5168) excess deaths. Sugarcane crops were also a driver of deforestation-related wildfires in Brazil, mainly in Cerrado and Atlantic Forest biomes. Our findings suggest that between 2003 and 2018, fires originating from sugarcane crops were associated with a total penalty of 0.134 µg/m3 (95%CI: 0.037; 0.232) on PM2.5 in Atlantic Forest biome, resulting in an estimated 7600 (95%CI: 4400; 10,800) excess deaths during the study period, and 0.096 µg/m3 (95%CI: 0.048; 0.144) on PM2.5 in Cerrado biome, resulting in an estimated 1632 (95%CI: 1152; 2112) excess deaths during the study period. Considering that the wildfire penalties observed during our study period may continue to be a challenge in the future, this study should be of interest to policymakers to prepare future strategies related to forest protection, land use management, agricultural activities, environmental health, climate change, and sources of air pollution.

Short-term air pollution exposure and hospital admissions for cardiorespiratory diseases in Brazil: A nationwide time-series study between 2008 and 2018.

The established evidence associating air pollution with health is limited to populations from specific regions. Further large-scale studies in several regions worldwide are needed to support the literature to date and encourage national governments to act. Brazil is an example of these regions where little research has been performed on a large scale. To address this gap, we conducted a study looking at the relationship between daily PM2.5, NO2, and O3, and hospital admissions for circulatory and respiratory diseases across Brazil between 2008 and 2018. A time-series analytic approach was applied with a distributed lag modeling framework. We used a generalized conditional quasi-Poisson regression model to estimate relative risks (RRs) of the association of each air pollutant with the hospitalization for circulatory and respiratory diseases by sex, age group, and Brazilian regions. Our study population includes 23, 791, 093 hospital admissions for cardiorespiratory diseases in Brazil between 2008 and 2018. Among those, 53.1% are respiratory diseases, and 46.9% are circulatory diseases. Our findings suggest significant associations of ambient air pollution (PM2.5, NO2, and O3) with respiratory and circulatory hospital admissions in Brazil. The national meta-analysis for the whole population showed that for every increase of PM2.5 by 10 µg/m3, there is a 3.28% (95%CI: 2.61; 3.94) increase in the risk of hospital admission for respiratory diseases. For O3, we found positive associations only for some sub-group analyses by age and sex. For NO2, our findings suggest that a 10 ppb increase in this pollutant, there was a 35.26% (95%CI: 24.07; 46.44) increase in the risk of hospital admission for respiratory diseases. This study may better support policymakers to improve the air quality and public health in Brazil.

The association of maternal exposure to ambient temperature with low birth weight in term pregnancies varies by location: In Brazil, positive associations may occur only in the Amazon region.

Exposure to ambient temperature has been linked to adverse birth outcomes in several regions, including the USA, Australia, China, countries in the Middle East, and European countries. To date, no studies were performed in South America, a region with serious challenges related to climate change. Our investigation addresses this literature lack by examining the association between Low Birth Weight (LBW) and ambient temperature exposure in the largest county in South America, Brazil. We applied a nationwide case-control study design using a logistic regression model to estimate the odds ratio (OR) for LBW associated with ambient temperature during a specific trimester of pregnancy (1-3 trimester). Our sample size includes 5,790,713 birth records nationwide over 18 years (2001-2018), of which 264,967 infants were included in the model as cases of LBW, representing 4.6% of our total sample. We adjusted our model for several confounding variables, including weather factors, air pollution, seasonality, and SES variables at the individual level. Our findings indicate that North was the only region with positive and statistically significant associations in the primary analysis and most of the sensitivity analysis, which is the region where the Amazon is located. In this region, we estimated an increase of 5.16% (95%CI: 3.60; 6.74) in the odds of LBW per 1 °C increase in apparent temperature when the exposure occurred in the second trimester. Our results may be explained by the climate conditions in the Amazon region in the past years. A large body of literature indicates that the Amazon region has been facing serious climate challenges including issues related to policy, governance, and deforestation. Specifically, regarding deforestation, it is suggested that land use change and deforestation is projected to increase heat stress in the Amazon region, because of Amazon savannization, increasing the risk of heat stress exposure in Northern Brazil. Our study can assist public sectors and clinicians in mitigating the risk and vulnerability of the Amazonian population.

Green areas and students' academic performance in the Federal District, Brazil: An assessment of three greenness metrics.

Most of the epidemiological investigations looking at the health benefits of green spaces have measured the level of green areas by using only one approach, mainly the Normalized Difference Index - NDVI (a satellite-derived indicator). We hypothesized a difference in the association between health and green space depending on the metric used to measure green exposure. This study considers students' academic performance as a proxy of cognitive abilities (a health indicator). We estimated the relationship between green areas and students' academic performance in the Federal District (FD), Brazil, with three different greenness metrics: NDVI, distance to green spaces (m) - obtained from land use data, and quantity of green spaces (m2) - also from land use data. We assessed student-level academic performance data provided by the Department of the Education in the FD. The data includes students from the public schools in the FD for 256 schools (all the public schools in the FD) and 344,175 students (all the students enrolled in the public schools in the FD in 2017-2020).). For the first metric represented by the distance to green spaces, we estimated the straight-line distance between each school and the nearest green area. For NDVI and quantity of green spaces, we estimated the area of all green spaces within buffers of 500 m, 750 m, and 1 km around the schools. We applied a cross-sectional study design using mixed-effects regression models to analyze the association exposure to green areas around schools and student-level academic performance. Our results confirmed our hypothesis showing that the impact of green areas on students' performance varied significantly depending on the type of green metric. After adjustments for the covariates, we estimated that NDVI is positively associated with school-level academic performance, with an estimated coefficient of 0.91 (95%CI: 0.83; 0.99) for NDVI values at a school's centroid. Distance to green areas was negatively associated with academic performance [-2.09 × 10-5 (95CI: 3.91 × 10-5; -2.84 × 10-6]. The quantity of green areas was estimated with mixed results (direction of the association), depending on the buffer size. Results from this paper suggest that epidemiological investigations must consider the different effects of greenness measures when looking at the association between green space and academic performance. More studies on residual confounding from this association with a different study design are needed to promote public health by making schools healthier.

Birth weight following pregnancy wildfire smoke exposure in more than 1.5 million newborns in Brazil: A nationwide case-control study.

Background: Air pollution exposure has been associated with critical neonatal morbidities, including low birth weight (LBW). However, little is known on short-term exposure to wildfire smoke and LBW. In this study, we estimated the association between birth weight following pregnancy and wildfire smoke exposure in more than 1.5 million newborns in Brazil (considered as a very fire-prone region worldwide). Methods: We applied a logistic regression model to estimate the percent variation in newborns with low birth weight when exposed to wildfire in different trimesters of the pregnancy. Findings: After adjusting the model with relevant covariates, we found that an increase of 100 wildfire records in Brazil was associated with an increase in low birth weight in the Midwest region [0.98% (95%CI:0.34; 1.63)] and in the South region [18.55% (95%CI:13.66; 23.65)] when the exposure occurred in the first trimester of pregnancy. Interpretation: Wildfires were associated with LBW and this should be of public health concern for policymakers. Funding: Brazilian Agencies National Council for Scientific and Technological Development (CNPq); Ministry of Science, Technology and Innovation in Brazil (MCTI); and Novo Nordisk Foundation Challenge Programme.