Applied research in healthy cities is often based on empirical investigations of the association between the built environment and health outcomes using spatial analysis. We investigated the influence of proximity to urban facilities on the occurrence of early deaths from myocardial infarction (age <60 years) in the city of Sa similar to o Paulo, with cause of death determined by autopsy. The study data were extracted from interviews applied to relatives/ caregivers of 458 deceased autopsied at the Death Verification Service, collecting information on demographic characteristics, residential address, life habits and previous health conditions. After geocoding the residential addresses of the deceased, the distances to different urban facilities were calculated. The existence of an association between the odds of death from myocardial infarction aged <60 years versus >= 60 years and distance to urban facilities was assessed by fitting logistic regression models. The results showed a significant association between these distances and the odds of early death from infarction. More specifically, when distances to different facilities were halved, the odds of death at <60 years were reduced by a factor of 0.78 (-22 %) for community clubs; 0.73 (-27 %) for sports centers; and by 0.80 (20 %) for cycle paths). These results indicate the potential of interventions to benefit human health through the formulation of spatially-integrated public policies in cities.

Carbon dioxide from fossil fuels and industrial processes accounted for approximately 78

Background The characterisation of individual exposure to air pollution in urban scenarios is a challenge in environmental epidemiological studies. We investigated if the city's pollution monitoring stations over or underes-timate the exposure of individuals depending on their socioeconomic conditions and daily commuting times. Methods The amount of black carbon accumulated in the lungs of 604 deceased who underwent autopsy in Sao Paulo was considered as a proxy for PM10. The concentrations of PM10 in the residence of the deceased were estimated by interpolating an ordinary kriging model. These two-exposure metrics allowed us to construct an environmental exposure misclassification index ranging from -1 to 1. The association between the index and daily commuting, socioeconomic context index (GeoSES), and street density as predictors was assessed by means of a multilevel linear regression model. Findings With a decrease of 0.1 units in GeoSES, the index increases, on average, by 0.028 units and with an increase of 1 h in daily commuting, the index increases, on average, by 0.022 units indicating that individual exposure to air pollution is underestimated in the lower GeoSES and in people with many hours spent in daily commuting. Interpretation Reduction of health consequences of air pollution demands not only alternative fuel and more efficient mobility strategies, but also should include profound rethink of cities.

Reliable mortality data are essential for the development of public health policies. In Brazil, although there is a well-consolidated universal system for mortality data, the quality of information on causes of death (CoD) is not even among Brazilian regions, with a high proportion of ill-defined CoD. Verbal autopsy (VA) is an alternative to improve mortality data. This study aimed to evaluate the performance of an adapted and reduced version of VA in identifying the underlying causes of non-forensic deaths, in São Paulo, Brazil. This is the first time that a version of the questionnaire has been validated considering the autopsy as the gold standard. The performance of a physician-certified verbal autopsy (PCVA) was evaluated considering conventional autopsy (macroscopy plus microscopy) as gold standard, based on a sample of 2060 decedents that were sent to the Post-Mortem Verification Service (SVOC-USP). All CoD, from the underlying to the immediate, were listed by both parties, and ICD-10 attributed by a senior coder. For each cause, sensitivity and chance corrected concordance (CCC) were computed considering first the underlying causes attributed by the pathologist and PCVA, and then any CoD listed in the death certificate given by PCVA. Cause specific mortality fraction accuracy (CSMF-accuracy) and chance corrected CSMF-accuracy were computed to evaluate the PCVA performance at the populational level. There was substantial variability of the sensitivities and CCC across the causes. Well-known chronic diseases with accurate diagnoses that had been informed by physicians to family members, such as various cancers, had sensitivities above 40% or 50%. However, PCVA was not effective in attributing Pneumonia, Cardiomyopathy and Leukemia/Lymphoma as underlying CoD. At populational level, the PCVA estimated cause specific mortality fractions (CSMF) may be considered close to the fractions pointed by the gold standard. The CSMF-accuracy was 0.81 and the chance corrected CSMF-accuracy was 0.49. The PCVA was efficient in attributing some causes individually and proved effective in estimating the CSMF, which indicates that the method is useful to establish public health priorities.

Background:Accurate cause of death data are essential to guide health policy. However, mortality surveillance is limited in many low-income countries. In such settings, verbal autopsy (VA) is increasingly used to provide population-level cause of death data. VAs are now widely interpreted using the automated algorithms SmartVA and InterVA. Here we use conventional autopsy as the gold standard to validate SmartVA methodology.Methods:This study included adult deaths from natural causes in São Paulo and Recife for which conventional autopsy was indicated. VA was conducted with a relative of the deceased using an amended version of the SmartVA instrument to suit the local context. Causes of death from VA were produced using the SmartVA-Analyze program. Physician coded verbal autopsy (PCVA), conducted on the same questionnaires, and Global Burden of Disease Study data were used as additional comparators. Cause of death data were grouped into 10 broad causes for the validation due to the real-world utility of VA lying in identifying broad population cause of death patterns.Findings:The study included 2,060 deaths in São Paulo and 1,079 in Recife. The cause specific mortality fractions (CSMFs) estimated using SmartVA were broadly similar to conventional autopsy for: cardiovascular diseases (46.8% vs 54.0%, respectively), cancers (10.6% vs 11.4%), infections (7.0% vs 10.4%) and chronic respiratory disease (4.1% vs 3.7%), causes accounting for 76.1% of the autopsy dataset. The SmartVA CSMF estimates were lower than autopsy for "Other NCDs" (7.8% vs 14.6%) and higher for diabetes (13.0% vs 6.6%). CSMF accuracy of SmartVA compared to autopsy was 84.5%. CSMF accuracy for PCVA was 93.0%.Interpretation:The results suggest that SmartVA can, with reasonable accuracy, predict the broad cause of death groups important to assess a population's epidemiological transition. VA remains a useful tool for understanding causes of death where medical certification is not possible.

Introdução: Os óbitos por causa mal definida (CDM) prejudicam a formação depolíticas públicas de saúde. A pandemia de COVID-19 levou a interrupção da realizaçãode exames necroscópicos no estado de São Paulo. Objetivo: Demonstrar a implantação daautopsia verbal como instrumento complementar na investigação e apresentar resultadosno período de 2020 e 2021. Metodologia: Descrever o processo de recuperação dasinformações coletadas nas AV e analisar o grau de recuperação. Resultados: Proporçãode CMD reclassificadas ao longo o período foi de 89% do total de 4.369 AV recebidase 3849 ativas para o processo. Discussão: A plausibilidade das proporções de causasespecíficas detectadas entre as CMD indica acurácia dos dados da investigação. Conclusão:Sensibilização dos municípios para a ampliação do uso da AV é um importante ponto paramelhoria futura.

HINTS AND KINKS Int J Public Health, 05 October 2021 https://doi.org/10.3389/ijph.2021.1604249

Although air pollution decreased in some cities that shifted from an industrial to a service-based economy, and vehicular emission regulation became more restrictive, it is still a major risk factor for mortality worldwide. In central São Paulo, Brazil, air quality monitoring stations and tree-ring analyses revealed a decreasing trend in the concentrations of particulate matter and metals. Such trends, however, may not be observed in industrial districts located in the urban periphery, where the usual mobile sources may be combined with local stationary sources. To evaluate environmental pollution in an industrial district in southeastern São Paulo, we assessed its spatial variability, by measuring magnetic properties and concentrations of Al, Ba, Ca, Cl, Cu, Fe, K, Mg, Mn, P, S, Sr, Zn in the bark of 62 trees, and its temporal trends, by measuring Cd, Cu, Ni, Pb, V, Zn in tree rings of three trees. Source apportionment analysis based on tree barks revealed two clusters with high concentrations of metals, one related to vehicular and industrial emissions (Al, Ba, Cu, Fe, Zn) in the east side of the industrial cluster, and the other related to soil resuspension (Cu, Zn, Mn) in its west side. These patterns are also supported by the magnetic properties of bark associated with iron oxides and titanium-iron alloy concentrations. Dendrochemical analyses revealed that only the concentrations of Pb consistently decreased over the last four decades. The concentrations of Cd, Cu, Ni, V, and Zn did not significantly decrease over time, in contrast with their negative trends previously reported in central São Paulo. This combined biomonitoring approach revealed spatial clusters of metal concentration in the vicinity of this industrial cluster and showed that the local population has not benefited from the decreasing polluting metal concentrations in the last decades.

Background: Hypertension and air pollution are two important risk factors for cardiovascular morbidity and mortality. Although several studies suggest that air pollution has a significant impact on blood pressure, studies on long-term effects are sparse and still controversial. Objective: To evaluate the effects of exposure of outdoor workers to different levels of traffic-generated PM2.5 on blood pressure. Design: This is an observational panel study. Participants: 88 non-smoking workers exposed to different concentrations of air pollution were evaluated weekly along four successive weeks. Measurements: In each week, personal monitoring of 24-h PM2.5 concentration and 24-h ambulatory blood pressure were measured. The association between blood pressure variables and PM2.5, adjusted for age, body mass index, time in job, daily work hours, diabetes, hypertension and cholesterol was assessed by means of multiple linear regression models fitted by least squares. Results: Exposure to PM2.5 (ranging from 8.5 to 89.7 mu g/m(3)) is significantly and consistently associated with an increase in average blood pressure. An elevation of 10 mu g/m(3) in the concentration of PM2.5 is associated with increments of 3.9 mm Hg (CI 95% = [1.5; 6.3]) in average systolic 24-h blood pressure for hypertensive and/or diabetic workers. Conclusion: Exposure to fine particles, predominantly from vehicular traffic, is associated with elevated blood pressure in hypertensive and/or diabetic workers.

Many studies have been conducted to evaluate the association between air pollution and adverse health effects using a wide variety of methods to assess exposure. However, the assessment of individual long-term exposure to ambient air pollution is a challenging task and has not been evaluated in a large autopsy study. Our goal was to investigate whether exposure to urban air pollution is associated to the degree of lung anthracosis, considering modifying factors such as personal habits, mobility patterns and occupational activities. We conducted a study in Sao Paulo, Brazil from February 2017 to June 2018, combining epidemiological, spatial analysis and autopsy-based approaches. Information about residential address, socio-demographic details, occupation, smoking status, time of residence in the city and time spent commuting was collected via questionnaires applied to the next-of-kin. Images of the pleura surface from upper and lower lobes were used to quantify anthracosis in the lungs. We used multiple regression models to assess the association between the amount of carbon deposits in human lungs, measured by the fraction of pleural anthracosis (FA), and potential explanatory variables. We analyzed 413 cases and our data showed that for each additional hour spent in daily commuting, the ratio FA/(1-FA) is multiplied by 1.05 (95% confidence interval: [1.02; 1.08]). The estimated coefficient for daily hours spent in traffic was not considerably affected by the inclusion of socio-demographic variables and smoking habits. We estimate a tobacco equivalent dose of 5 cigarettes per day in a city where annual PM2.5 concentration oscillates around 25 μg/m3. Pleural anthracosis is a potential index of lifetime exposure to traffic-derived air pollution.

Limited studies have reported on in-vitro analysis of PM2.5 but as far as the authors are aware, bioaccessibility of PM2.5 in artificial lysosomal fluid (ALF) has not been linked to urban development models before. The Brazilian cities Manaus (Amazon) and Curitiba (South region) have different geographical locations, climates, and urban development strategies. Manaus drives its industrialization using the free trade zone policy and Curitiba adopted a services centered economy driven by sustainability. Therefore, these two cities were used to illustrate the influence that these different models have on PM2.5 in vitro profile. We compared PM2.5 mass concentrations and the average total elemental and bioaccessible profiles for Cu, Cr, Mn, and Pb. The total average elemental concentrations followed Mn > Pb > Cu > Cr in Manaus and Pb > Mn > Cu > Cr in Curitiba. Mn had the lowest solubility while Cu showed the highest bioaccessibility (100%) and was significantly higher in Curitiba than Manaus. Cr and Pb had higher bioaccessibility in Manaus than Curitiba. Despite similar mass concentrations, the public health risk in Manaus was higher than in Curitiba indicating that the free trade zone had a profound effect on the emission levels and sources of airborne PM. These findings illustrate the importance of adopting sustainable air quality strategies in urban planning.

The urban environment features poor air quality and harsher climate conditions that affect the life in the cities. Citizens are especially vulnerable to climate change, because heat island and impervious exacerbates extreme climate events. Urban trees are important tools for mitigation and adaptation of cities to climate change because they provide ecosystem services that increase while trees grow. Nonetheless, the growth of trees may be affected by the harsher conditions found in the urban environment. We assessed the impact of air pollution and climate on the spatial/temporal variability of tree growth in São Paulo, Brazil, one of the largest urban conglomerates in the world. For this purpose, we sampled 41 trees of the Tipuana tipu species in a region that includes industrial areas. We built a tree-ring chronology using standard dendrochronological methods. Spatial analyses show that trees grow faster in the warmer parts of the city and under higher concentrations of airborne P, whereas growth is reduced under higher concentrations of Al, Ba, Zn. Particulate matter (PM10) from the industrial cluster also reduce average growth rate of trees, up to 37% in all diameter classes. Similar results were obtained via temporal analyses, suggesting that the annual growth rate is positively associated with temperature, which explain 16% of interannual growth variability. Precipitation, on the other hand, has no association with tree growth. The average concentration of PM10 explains 41% of interannual growth variability, and higher concentrations during the driest months reduce growth rate. Despite heat island effect and water limitation in the soil of the city, this species takes advantage of warmer conditions and it is not limited by water availability as measured by precipitation. On the other hand, air pollution directly impacts the growth of these trees being a major limiting growth factor.

INTRODUCTION:High particulate matter (PM10) concentrations are associated with increased incidence of respiratory symptoms and decreased lung function. This study evaluates the air pollution effects in children's and adolescents' lung function using peak expiratory flow (PEF) measurements over a given period, in an area exposed to industrial emissions. METHODOLOGY:This was a panel study. The effects of air pollution on respiratory symptoms and PEF were investigated in 117 children and adolescents from three public schools in areas of exposure to air pollution from a mining company in a Brazilian medium-sized city, from 2008 to 2009. The average daily PM10, temperature and humidity were recorded by the monitoring network in the region. Association between daily records of PEF and PM10 was assessed in mixed-effect regression models, controlling for temperature, humidity, and body mass index. RESULTS:About 60,000 PEF measurements were performed. Increases of 14µg/m3 in PM10 were associated with decreased PEF in the morning (-1.04%, 95%CI -1.32; -0.77) and evening (-1.2%, 95%CI -1.49, -0.92). DISCUSSION:We found a significant negative association between particulate matter and peak expiratory flow rate in this population, and these remained significant even after adjusted for temperature, humidity, body mass index, coughing, wheezing and coryza. CONCLUSION:Adverse effects were found and it suggests an association between increase in PM10 and reduced lung function.

Chemical element analysis in tree barks is being used to access the variability of urban air pollutant concentrations with high spatial resolution. We conducted an observational study in São Paulo, Brazil, where vehicle emissions are the main source of air pollution. Aim: Verify which trace elements in tree barks may be used as proxies for PM10 concentration in this urban scenario. Methods: Samples of barks from 498 trees (193 Tipuana tipu, 228 Poincianella pluviosa and 77 Ligustrum sp.) were collected near streets with different traffic intensities. Al, Ba, Ca, Cl, Cu, Fe, K, Mg, Mn, P, S, Sr and Zn concentrations were evaluated by energy dispersive X-ray fluorescence (EDXRF) spectrometry. Principal component analyses, considering robust correlation coefficients, were performed with the objective of identifying the sources of the chemical elements, with and without separation by species. Considering 14 trees located around air quality monitoring stations, the association between element concentrations in the tree barks and the annual PM10 (evaluated by Beta Attenuation method) mean concentration in the year preceding the bark sampling was evaluated via regression models. A forward stepwise procedure was adopted in the process of model fitting. Results: Regardless of species, the first principal component was related to vehicular emissions and explained 45% of the total variance. Fe was the element with the largest correlation with this component, both when a correlation matrix containing robust correlation coefficients was considered or not. In the fitting of the regression model, no other element related with vehicular sources had additional contribution to explain the PM10 variability (R2=80%). Conclusion: Fe in tree barks may be used to access the spatial variability of long term PM10 concentrations. The results of this preliminary study are in line with recent research that proposes magnetic analysis of tree barks for air pollution biomonitoring purposes.

The analysis of chemical elements in the barks of trees is an alternative procedure to access spatial heterogeneity of traffic related air pollution. However, the role of tree species in the characterization of the variability of airborne pollution is poorly known. We present an observational study conducted in Sao Paulo, Brazil, based on the analysis of 498 trees from three common species: Tipuana tipu, Poincianella pluviosa, and Ligustrum sp.. We considered ANCOVA models to compare the concentrations of Al, Fe, Zn, Cu, Mn, Ba, and Sin the bark (periderm) of trees located close to streets with different levels of traffic intensity controlling for the extension of nearby green areas. The expected trend of increasing elemental concentration in the bark of trees located near streets with greater traffic intensity or close to smaller green areas was only fully evidenced by T. tipu. For instance, the concentrations of Zn, Fe, Al, and Ba increase by 200, 350, 230, and 280% respectively, for trees of this species located near arterial streets when compared to those observed near local streets. On the other hand, the concentrations of Zn, Fe, Al, and Ba are reduced by 41, 45, 50, and 30%, respectively, for trees located near green areas. For P. pluviosa, the capacity to suggest an association between the tree bark concentration of chemical elements with increasing levels of air pollution and presence of green areas was only fully observed for Zn and Cu. For Ligustrum sp., weaker and sometimes non-expected associations between bark concentrations of the chemical elements and either street classification or green area extension were observed. Our results indicate that the choice of species is a key element in the use of tree barks as a biomonitoring tool in urban landscapes. Species like T. tipu, with rough and highly porous bark, are the most appropriate for such purpose.

Hypertension and air pollution are two important risk factors for cardiovascular morbidity and mortality. Although several studies suggest that air pollution has a significant impact on blood pressure, studies on long-term effects are sparse and controversial. Aims: To evaluate the effects of exposure to different levels of traffic-generated PM2.5 on blood pressure in outdoor workers. Methods: 88 non-smoking workers, exposed to different concentrations of vehicular pollution, were evaluated weekly in four successive weeks. At each evaluation, they underwent personal monitoring of 24-hour PM2.5 concentration and 24-hour ambulatory blood pressure. The association between the blood pressure variables and PM2.5, adjusted for age, body mass index, time in job, daily work hours, diabetes or hypertension and cholesterol was assessed by means of multiple linear regression fitted by least squares. Results: Exposure to PM2.5 (ranging from 8.5 to 89.7µg/m3) was significant and consistently associated with an increase of blood pressure. An elevation of 10 µg/m3 in the PM2.5 concentration was associated with increments of 4.2 (CI 95%= [2.8; 5.6]) and 2.8 mmHg (CI 95%= [1.6, 4.0]) in average systolic and diastolic 24-hour blood pressure, respectively. Conclusion: Exposure to fine particles, predominantly from vehicular traffic, was associated with elevated blood pressure in hypertensive workers. Less relevant effects were observed in non-hypertensive workers.

The concern about environmental pollution has risen in the last decades because of its effects on human's health. However, evaluation of the exposure to certain pollutants is currently hampered by the availability of past environmental data. Tree rings are an alternative to reconstruct environmental variability of pre-instrumental periods. Nevertheless, this approach has some reported limitations including migration of chemical elements in the tree rings. The aim of this study was to evaluate the distribution of Cd, Cu, Hg, Na, Ni, Pb, Zn in the tree rings of Tipuana tipu (Fabaceae) to aid the reconstruction of past environmental pollution. We sampled trees in the central region of the city of São Paulo, Brazil, and scanned their tree rings using LA-ICP-MS. We used these data to evaluate the temporal trends of chemical elements under investigation. Results show a non-random distribution of these chemical elements within the tree rings, with higher content in the cell-walls of vessels and lower content in the fibers. Sodium was the only element intimately related to the axial parenchyma cells. Due to differences in elemental composition of xylem cells, temporal trends where evaluated using distinct quartiles of data distribution in each tree ring. The first quartile represents the lower content found in fibers and parenchyma, while the third quartile corresponds to the higher content found in vessels. Data from vessels better represent the decreasing trend of Cd, Cu, Pb, and Ni in the last three decades. This reduction is less significant for Na and Zn. Our results highlight the potential to improve the records of environmental pollution using data from different cells. Pronounced reduction in Pb may be attributed to the lead phase-out in gasoline, while the decreasing trend of Cd, Cu, Ni pollution is probably related to increasing efficiency of vehicles and the deindustrialization of São Paulo. Chemical elements are non-randomly distributed in tree rings. Chemical content of vessels cell-walls is a reliable record of metal pollution, which is decreasing in São Paulo.

Background/Aim: Citizens of megacities are exposed to heterogeneous environments where pollution varies in time and space. Accessing such variability is a complex task since environmental pollution measurements are sparce in most cities, not covering most of the urban spatial variability. Data availability for earlier periods is rarer, most of them covering the last two decades at best. Tree-ring data has the potential to reconstruct past variability of environmental pollution in different parts of the city. The aim of this work is to use the elemental composition of different cell types of wood to create a reliable time series of environmental pollution in São Paulo city, in order to understand the effects of long-term exposures on human health. Methods: We measured the elemental composition in tree rings of Tipuana tipu, an abundant species in São Paulo. Elemental analysis was performed using the Laser Ablation coupled to an ICP-MS. This high-resolution approach allows the semi-quantitative analysis of elemental composition of fibers, cells with a fast-programed cell death, and axial parenchyma that are long-lived storage cells in the wood. Since fibers are short-lived, they are likely the ones that will hold the most reliable information about the environmental pollution in the year of tree-ring formation. Results: The preliminary results show that Hg, Pd, Rh are not found in the analysed samples, whereas Cu, Zn, Pb, Cd are abundant. Out of these elements, Pb and Cd do not seem to be constitutive elements of the wood, probably representing the environmental variability of these elements. This analysis confirms that the concentration of these elements is cell type dependent, and the highest concentrations are found in the storage cells of wood. Conclusions: We expect that the elemental analysis of fibers will produce a reliable reconstruction of the environmental pollution in São Paulo over the last four decades.

Biodiesel is a renewable energy source that reduces particle emission, but few studies have assessed its effects. To assess the effects of acute inhalation of two doses (600 and 1200 mu g/m(3)) of diesel (DE) and biodiesel (BD) fuels on the inflammatory pulmonary and systemic profile of mice. Animals were exposed for 2 h in an inhalation chamber inside the Container Laboratory for Fuels. Heart rate, heart rate variability (HRV) and blood pressure were determined 30 min after exposure. After 24 h. we analyzed the lung inflammation using bronchoalveolar lavage fluid (BALF); neutrophil and macrophage quantification in the lung parenchyma was performed, and blood and bone marrow biomarkers as well as receptor of endothelin-A (ET-Ar), receptor of endothelin-B (ET-Br), vascular cell adhesion molecule 1 (VCAM-1), inducible nitric oxide synthase (iNOs) and isoprostane (ISO) levels in the pulmonary vessels and bronchial epithelium were evaluated. HRV increased for BD600, D600 and D1200 compared to filtered air (FA). Both fuels (DE and BD) produced alterations in red blood cells independent of the dose. BALI from the BD600 and BD1200 groups showed an increase in neutrophils compared to those of the FA group. Numeric density of the polyrnorphonuclear and mononudear cells was elevated with BD600 compared to FA. In the peribronchiolar vessels, there was an increase in ET-Ar and ET-Br expression following BD600 compared to IA; and there was a reduction in the iNOs expression for BD1200 and the VCAM-1 for D1200 compared to FA. In the bronchial epithelium, there was an increase in ETAr at BD600, ET-Br at two doses (600 and 1200 mu g/m(3)) of DE and BD, iNOs at D600 and VCAM-1 at BD1200 and D600; all groups were compared to the FA group. Acute exposure to DE and BD derived from sewage methyl esters triggered pulmonary and cardiovascular inflammatory alterations in mice. (C) 2018 Elsevier B.V. All rights reserved.

Understanding the impact on human health during peak episodes in air pollution is invaluable for policymakers. Particles less than PM2.5 can penetrate the respiratory system, causing cardiopulmonary and other systemic diseases. Statistical regression models are usually used to assess air pollution impacts on human health. However, when there are databases missing, linear statistical regression may not process well and alternative data processing should be considered. Nonlinear Artificial Neural Networks (ANN) are not employed to research environmental health pollution even though another advantage in using ANN is that the output data can be expressed as the number of hospital admissions. This research applied ANN to assess the impact of air pollution on human health. Three well-known ANN were tested: Multilayer Perceptron (MLP), Extreme Learning Machines (ELM) and Echo State Networks (ESN), to assess the influence of PM2.5, temperature, and relative humidity on hospital admissions due to respiratory diseases. Daily PM2.5 levels were monitored, and hospital admissions for respiratory illness were obtained, from the Brazilian hospital information system for all ages during two sampling campaigns (2008-2011 and 2014-2015) in Curitiba, Brazil. During these periods, the daily number of hospital admissions ranged from 2 to 55, PM2.5 concentrations varied from 0.98 to 54.2 μg m-3, temperature ranged from 8 to 26 °C, and relative humidity ranged from 45 to 100%. Of the ANN used in this study, MLP gave the best results showing a significant influence of PM2.5, temperature and humidity on hospital attendance after one day of exposure. The Anova Friedman's test showed statistical difference between the appliance of each ANN model (p < .001) for 1 lag day between PM2.5 exposure and hospital admission. ANN could be a more sensitive method than statistical regression models for assessing the effects of air pollution on respiratory health, and especially useful when there is limited data available.