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.

Climate Penalty on Air Pollution Abated by Anthropogenic Emission Reductions in the United States.

Climate change poses direct and indirect threats to public health, including exacerbating air pollution. However, how a warmer temperature deteriorates air quality, known as the "climate penalty" effect, remains highly uncertain in the United States, particularly under rapid reduction in anthropogenic emissions. Here we examined the sensitivity of surface-level fine particulate matter (PM2.5) and ozone (O3) to summer temperature anomalies in the contiguous US and their decadal changes using high-resolution datasets generated by machine learning models. Our findings demonstrate that, in the eastern US, efficient emission control strategies have significantly reduced the climate penalty effects on PM2.5 and O3, lowering the associated population exposure. In contrast, summer and annual PM2.5 in the western US became more sensitive to temperature, highlighting the urgent need for the management and mitigation of worsening wildfires. Our results have important implications for air quality management and risk assessments of future climate change.

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.

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.

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.

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.

Intermediate and long-term exposure to air pollution and temperature and the extracellular microRNA profile of participants in the normative aging study (NAS).

BACKGROUND: The molecular effects of intermediate and long-term exposure to air pollution and temperature, such as those on extracellular microRNA (ex-miRNA) are not well understood but may have clinical consequences. OBJECTIVES: To assess the association between exposure to ambient air pollution and temperature and ex-miRNA profiles. METHODS: Our study population consisted of 734 participants in the Normative Aging Study (NAS) between 1999 and 2015. We used high-resolution models to estimate four-week, eight-week, twelve-week, six-month, and one-year moving averages of PM2.5, O3, NO2, and ambient temperature based on geo-coded residential addresses. The outcome of interest was the extracellular microRNA (ex-miRNA) profile of each participant over time. We used a longitudinal quantile regression approach to estimate the association between the exposures and each ex-miRNA. Results were corrected for multiple comparisons and ex-miRNAs that were still significantly associated with the exposures were further analyzed using KEGG pathway analysis and Ingenuity Pathway Analysis. RESULTS: We found 151 significant associations between levels of PM2.5, O3, NO2, and ambient temperature and 82 unique ex-miRNAs across multiple quantiles. Most of the significant results were associations with intermediate-term exposure to O3, long-term exposure to PM2.5, and both intermediate and long-term exposure to ambient temperature. The exposures were most often associated with the 75th and 90th percentile of the outcomes. Pathway analyses of significant ex-miRNAs revealed their involvement in biological pathways involving cell function and communication as well as clinical diseases such as cardiovascular disease, respiratory disease, and neurological disease. CONCLUSION: Our results show that intermediate and long-term exposure to all our exposures of interest were associated with changes in the ex-miRNA profile of study participants. Further studies on environmental risk factors and ex-miRNAs are warranted.

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 and temperature exposure and changes in the extracellular microRNA profile of Normative Aging Study (NAS) participants.

BACKGROUND: While the health effects of air pollution and temperature are widely studied, the molecular effects are poorly understood. Extracellular microRNAs (ex-miRNAs) have the potential to serve as diagnostic or prognostic biomarkers and/or to act as intercellular signaling molecules that mediate the effects of environmental exposures on health outcomes. METHODS: We examined the relationship between short-term exposure to air pollution and ambient temperature and the ex-miRNA profiles of participants in the Normative Aging Study (NAS) from 1999 to 2015. Our exposures were defined as same-day, two-day, three-day, one-week, two-week, and three-week moving averages of PM2.5, NO2, O3, and temperature which were derived from high-resolution spatio-temporal models. The ex-miRNA profiles of the subjects were obtained during follow-up visits. We analyzed the data using a longitudinal quantile regression model adjusted for individual covariates, batch effects, and time trends. We adjusted for multiple comparisons using a false discovery rate (FDR) correction. Ex-miRNAs that were significantly associated with exposures were further investigated using pathway analyses. RESULTS: We found that all the examined exposures were associated with changes in ex-miRNA profiles in our study, particularly PM2.5 which was responsible for most of the statistically significant results. We found 110 statistically significant exposure-outcome relationships that revealed associations with the levels of 52 unique ex-miRNAs. Pathway analyses showed these ex-miRNAs have been linked to target mRNAs, genes, and biological mechanisms that could affect virtually every organ system, and as such may be linked to multiple clinical disease presentations such as cardiovascular disease, respiratory disease, and neurological disease. CONCLUSIONS: Air pollution and temperature exposures were significantly associated with alterations in the ex-miRNA profiles of NAS subjects with possible biological consequences.

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.

Associations between long-term air pollution exposure and the incidence of cardiovascular diseases among American older adults.

BACKGROUND & AIM: Numerous studies have linked air pollution with cardiovascular diseases. Fewer studies examined the associations at low concentration levels or assessed potential modifiers. Some investigations only examined hospitalizations, which can miss incident cases. This study aims to address these gaps through a nationwide cohort study of Medicare enrollees. METHODS: Our study cohort comprise all Medicare enrollees (≥65 years old) continuously enrolled in the fee-for-service program and both Medicare part A and B across the contiguous U.S. from 2000 to 2016. We examined the associations of population-weighted ZIP code-level annual average PM2.5, NO2, and warm-season O3 (May-October), with the first diagnoses of atrial fibrillation (AF), congestive heart failure (CHF), and stroke. We fit multi-pollutant Cox proportional hazards models adjusted for individual demographic characteristics and area-level covariates. We further examined these associations at low pollutant concentration levels and the potential effect modifications by race/ethnicity and comorbidities (diabetes, hypertension, hyperlipidemia). RESULTS: Elevated PM2.5 and NO2 levels were associated with increased incidence of AF, CHF, and stroke. For each 1 µg/m3 increase in annual PM2.5, hazard ratios (HRs) were 1.0059 (95%CI: 1.0054-1.0064), 1.0260 (95%CI: 1.0256-1.0264), and 1.0279 (95%CI: 1.0274-1.0284), respectively. For each1 ppb increase in annual NO2, HRs are 1.0057 (95%CI: 1.0056-1.0059), 1.0112 (95%CI: 1.0110-1.0113), and 1.0095 (95%CI: 1.0093-1.0096), respectively. For warm-season O3, each 1 ppb increase was associated with increased incidence of CHF (HR=1.0035, 95%CI: 1.0033-1.0037) and stroke (HR=1.0026, 95%CI: 1.0023-1.0028). Larger magnitudes of HRs were observed when restricted to pollutants levels lower than NAAQS standards. Generally higher risks were observed for Black people and diabetics. CONCLUSIONS: Long-term exposure to PM2.5, NO2, and warm-season O3 were associated with increased incidence of cardiovascular diseases, even at low pollutant concentration levels. Black people and people with diabetes were found to be vulnerable populations.

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.

The effect of long-term exposure to air pollution and seasonal temperature on hospital admissions with cardiovascular and respiratory disease in the United States: A difference-in-differences analysis.

BACKGROUND: Few studies have simultaneously examined the effect of long-term exposure to air pollution and ambient temperature on the rate of hospital admissions with cardiovascular and respiratory disease using causal inference methods. METHODS: We used a variation of a difference-in-difference (DID) approach to assess the effects of long-term exposure to warm-season temperature, cold-season temperature, NO2, O3, and PM2.5 on the rate of hospital admissions for cardiovascular disease (CVD), myocardial infarction (MI), ischemic stroke, and respiratory diseases from 2001 to 2016 among Medicare beneficiaries who use fee-for-service programs. We computed the rate of admissions by zip code and year. Covariates included demographic and socioeconomic variables which were obtained from the decennial Census, the American Community Survey, the Behavioral Risk Factor Surveillance System, and the Dartmouth Health Atlas. As a secondary analysis, we restricted the analysis to zip code-years that had exposure to low concentrations of our pollutants. RESULTS: PM2.5 was associated with a significant increase in the absolute rate of annual admissions with cardiovascular disease by 47.71 admissions (95 % CI: 41.25-56.05) per 100,000 person-years, myocardial infarction by 7.44 admissions (95 % CI: 5.53-9.63) per 100,000 person-years, and 18.58 respiratory admissions (95 % CI: 12.42-23.72) for each one µg/m3 increase in two-year average levels. O3 significantly increased the rates of all the studied outcomes. NO2 was associated with a decreased rate of admissions with MI by 0.83 admissions (95 % CI: 0.10-1.55) per 100,000 person-years but increased rate of admissions for respiratory disease by 3.16 admissions (95 % CI: 1.34-5.24) per 100,000 person-years. Warmer cold-season temperature was associated with a decreased admissions rate for all outcomes. CONCLUSION: Air pollutants, particularly PM2.5 and O3, increased the rate of hospital admissions with cardiovascular and respiratory disease among the elderly, while higher cold-season temperatures decreased the rate of admissions with these conditions.

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.