Epidemiological, clinical, and genomic landscape of coccidioidomycosis in northeastern Brazil.

Coccidioidomycosis, listed as a priority mycosis by the WHO, is endemic in the United States but often overlooked in Central and South America. Employing a multi-institutional approach, we investigate how disease characteristics, pathogen genetic variation, and environmental factors impact coccidioidomycosis epidemiology and outcomes in South America. We identified 292 cases (1978-2021) and 42 outbreaks in Piauí and Maranhão states, Brazil, the largest series outside the US/Mexico epidemic zone. The male-to-female ratio was 57.4:1 and the most common activity was armadillo hunting (91.1%) 4 to 30 days before symptom onset. Most patients (92.8%) exhibited typical acute pulmonary disease, with cough (93%), fever (90%), and chest pain (77%) as predominant symptoms. The case fatality rate was 8%. Our negative binomial regression model indicates that reduced precipitation levels in the current (p = 0.015) and preceding year (p = 0.001) predict heightened incidence. Unlike other hotspots, acidic soil characterizes this region. Brazilian strains differ genomically from other C. posadasii lineages. Northeastern Brazil presents a distinctive coccidioidomycosis profile, with armadillo hunters facing elevated risks. Low annual rainfall emerges as a key factor in increasing cases. A unique C. posadasii lineage in Brazil suggests potential differences in environmental, virulence, and/or pathogenesis traits compared to other Coccidioides genotypes.

Space-time clusters of cardiovascular mortality and the role of heatwaves and cold spells in the city of São Paulo, Brazil.

The effects extreme air temperature events are related with an increase in cardiovascular mortality among vulnerable groups worldwide. Therefore, we identify spatiotemporal mortality clusters associated with diseases of the cardiovascular system among people ≥ 65 years in São Paulo, from 2006 to 2015, and investigate whether high-risk mortality clusters occurred during or following extreme air temperature events. To detect the clusters, we used daily mortality data and a retrospective space-time scan analysis with a discrete Poisson model. Extreme air temperature events were defined by daily mean temperatures, below the 10th percentile for cold spells and above the 90th percentile for heatwaves, with two or more consecutive days. We found statistically significant high-risk mortality clusters located in the peripheral areas. The spatiotemporal clusters of risk areas for cardiovascular and ischemic heart disease occurred during or following cold spell events, whereas those for stroke and ischemic stroke events were related to heatwaves.

Covid-19 hospital mortality using spatial hierarchical models: cohort design with 74,994 registers.

OBJECTIVE: To investigate the relationship between covid-19 hospital mortality and risk factors, innovating by considering contextual and individual factors and spatial dependency and using data from the city of São Paulo, Brazil. METHODS: The study was performed with a spatial hierarchical retrospective cohort design using secondary data (individuals and contextual data) from hospitalized patients and their geographic unit residences. The study period corresponded to the first year of the pandemic, from February 25, 2020 to February 24, 2021. Mortality was modeled with the Bayesian context, Bernoulli probability distribution, and the integrated nested Laplace approximations. The demographic, distal, medial, and proximal covariates were considered. RESULTS: We found that per capita income, a contextual covariate, was a protective factor (odds ratio: 0.76 [95% credible interval: 0.74-0.78]). After adjusting for income, the other adjustments revealed no differences in spatial dependence. Without income inequality in São Paulo, the spatial risk of death would be close to one in the city. Other factors associated with high covid-19 hospital mortality were male sex, advanced age, comorbidities, ventilation, treatment in public healthcare settings, and experiencing the first covid-19 symptoms between January 24 and February 24, 2021. CONCLUSIONS: Other than sex and age differences, geographic income inequality was the main factor responsible for the spatial differences in the risk of covid-19 hospital mortality. Investing in public policies to reduce socioeconomic inequities, infection prevention, and other intersectoral measures should focus on lower per capita income, to control covid-19 hospital mortality.

Assessing socioeconomic bias of exposure to urban air pollution: an autopsy-based study in São Paulo, Brazil.

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 underestimate 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 São 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. Funding: São Paulo Research Foundation (FAPESP-13/21728-2) and National Council for Scientific and Technological Development (CNPq-304126/2015-2, 401825/2020-5).

Molecular Phylogenetic Analysis of Paracoccidioides Species Complex Present in Paracoccidioidomycosis Patient Tissue Samples.

Paracoccidioidomycosis (PCM) is the main and most prevalent systemic mycosis in Latin America, that until recently, it was believed to be caused only by Paracoccidioides brasiliensis (P. brasiliensis). In 2006, researchers described three cryptic species: S1, PS2, PS3, and later, another one, PS4. In 2009, Paracoccidioides lutzii (Pb01-like) was described, and in 2017, a new nomenclature was proposed for the different agents: P. brasiliensis (S1), P. americana (PS2), P. restrepiensis (PS3), and P. venezuelensis (PS4). These species are not uniformly distributed throughout Latin America and, knowing that more than one cryptic species could coexist in some regions, we aimed to identify those species in patients' biopsy samples for a better understanding of the distribution and occurrence of these recently described species in Botucatu region. The Hospital of Medical School of Botucatu-UNESP, which is a PCM study pole, is located in São Paulo State mid-west region and is classified as a PCM endemic area. Genotyping analyses of clinical specimens from these patients that have been diagnosed and treated in our Hospital could favor a possible correlation between genetic groups and mycological and clinical characteristics. For this, molecular techniques to differentiate Paracoccidioides species in these biopsies, such as DNA extraction, PCR, and sequencing of three target genes (ITS, CHS2, and ARF) were conducted. All the sequences were analyzed at BLAST to testify the presence of P. brasiliensis. The phylogenetic trees were constructed using Mega 7.0 software and showed that 100% of our positive samples were from S1 cryptic species, therefore P. brasiliensis. This is important data, demonstrating the predominance of this species in the São Paulo State region.

Covid-19 hospital mortality using spatial hierarchical models: cohort design with 74, 994 registers

ABSTRACT OBJECTIVE To investigate the relationship between covid-19 hospital mortality and risk factors, innovating by considering contextual and individual factors and spatial dependency and using data from the city of São Paulo, Brazil. METHODS The study was performed with a spatial hierarchical retrospective cohort design using secondary data (individuals and contextual data) from hospitalized patients and their geographic unit residences. The study period corresponded to the first year of the pandemic, from February 25, 2020 to February 24, 2021. Mortality was modeled with the Bayesian context, Bernoulli probability distribution, and the integrated nested Laplace approximations. The demographic, distal, medial, and proximal covariates were considered. RESULTS We found that per capita income, a contextual covariate, was a protective factor (odds ratio: 0.76 [95% credible interval: 0.74-0.78]). After adjusting for income, the other adjustments revealed no differences in spatial dependence. Without income inequality in São Paulo, the spatial risk of death would be close to one in the city. Other factors associated with high covid-19 hospital mortality were male sex, advanced age, comorbidities, ventilation, treatment in public healthcare settings, and experiencing the first covid-19 symptoms between January 24 and February 24, 2021. CONCLUSIONS Other than sex and age differences, geographic income inequality was the main factor responsible for the spatial differences in the risk of covid-19 hospital mortality. Investing in public policies to reduce socioeconomic inequities, infection prevention, and other intersectoral measures should focus on lower per capita income, to control covid-19 hospital mortality.

Use of an Elevated Avenue for Leisure-Time Physical Activity by Adults from Downtown São Paulo, Brazil.

Leisure-time physical activity (LTPA) is associated with access and use of public open spaces. The President João Goulart Elevated Avenue, currently denominated Minhocão, is a facility for leisure activities that is open for people during the night and weekends. The aim of this study was to examine if the prevalence of LTPA among individuals living in the surroundings of Minhocão is different according to proximity to, and use of, the facility. We conducted a cross-sectional study with cluster sampling with people aged ≥18 years who lived in households up to 500 m, and between 501 m and 1500 m of Minhocão. The survey was conducted between December 2017 and March 2019 using an electronic questionnaire. We conducted a bivariate analysis and Poisson regression to examine possible differences in LTPA according to the proximity of residences and use of Minhocão. The analysis used post-stratification weights. A total of 12,030 telephone numbers of people were drawn (≤500 m = 6942; and >500 m to ≤1500 m = 5088). The final sample included 235 residents who returned the questionnaires. There was a higher prevalence of individuals engaging in at least 150 min per week of LTPA among users than non-users (Prevalence Ratio = 2.19, IC95% 1.66 to 2.90), independently of sex, age, education, the distance of houses to nearest accesses and number of barriers. The main five barriers related to the usage of the Minhocão were safety issues in and around the Minhocão, rainy weather, lack of vegetation, and lack of facilities. People who used the park had higher prevalence of all types of LTPA than non-users. The results can serve to inform government decision-making on the future of Minhocão.

Impact of heat waves and cold spells on cause-specific mortality in the city of São Paulo, Brazil.

The impact of heat waves and cold spells on mortality has become a major public health problem worldwide, especially among older adults living in low-to middle-income countries. This study aimed to investigate the effects of heat waves and cold spells under different definitions on cause-specific mortality among people aged ≥65 years in São Paulo from 2006 to 2015. A quasi-Poisson generalized linear model with a distributed lag model was used to investigate the association between cause-specific mortality and extreme air temperature events. To evaluate the effects of the intensity under different durations, we considered twelve heat wave and nine cold spell definitions. Our results showed an increase in cause-specific deaths related to heat waves and cold spells under several definitions. The highest risk of death related to heat waves was identified mostly at higher temperature thresholds with longer events. We verified that men were more vulnerable to die from cerebrovascular diseases and ischemic stroke on cold spells and heat waves days than women, while women presented a higher risk of dying from ischemic heart diseases during cold spells and tended to have a higher risk of chronic obstructive pulmonary disease than men during heat waves. Identification of heat wave- and cold spell-related mortality is important for the development and promotion of public health measures.

Examining socio-economic factors to understand the hospital case fatality rates of COVID-19 in the city of São Paulo, Brazil.

BACKGROUND: Understanding differences in hospital case fatality rates (HCFRs) of coronavirus disease 2019 (COVID-19) may help evaluate its severity and the capacity of the healthcare system to reduce mortality. METHODS: We examined the variability in HCFRs of COVID-19 in relation to spatial inequalities in socio-economic factors, hospital health sector and patient medical condition across the city of São Paulo, Brazil. We obtained the standardized hospital case fatality ratio adjusted indirectly by age and sex, which is the ratio between the HCFR of a specific spatial unit and the HCFR for the entire study area. We modelled it using a generalized linear mixed model with spatial random effects in a Bayesian context. RESULTS: We found that HCFRs were higher for men and for individuals ≥60 y of age. Our models identified per capita income as a significant factor that is negatively associated with the HCFRs of COVID-19, even after adjusting for age, sex and presence of risk factors. CONCLUSIONS: Spatial analyses of the implementation of these methods and of disparities in COVID-19 outcomes may help in the development of policies for at-risk populations in geographically defined areas.

Study protocol: health survey of Sao Paulo: ISA-Physical Activity and Environment.

BACKGROUND: Many studies have investigated the association between the built environment and physical activity behavior in urban settings. However, most of the studies conducted in low- and middle-income countries were cross-sectional, which are limited to identify behavioral determinants. We propose a prospective cohort study to verify the relationship between built environment features and leisure-time and transport-related physical activity in adults from Sao Paulo city, Brazil. METHODS: Prospective multilevel cohort, denominated "ISA-Physical Activity and Environment". It will build on the Health Survey of Sao Paulo in 2015 ("Inquérito de Saúde de São Paulo (ISA)" in Portuguese). The Health Survey of Sao Paulo, originally designed as a cross-sectional survey, had a multi-stage sample, covering 150 census tracts distributed in five health administrative areas. Data collection was performed by face-to-face interviews until December 2015 and the sample comprised 4043 individuals aged 12 years or more. The ISA-Physical Activity and Environment study will reassess people who are aged 18 years or more in 2020, including telephone and household interviews. The primary outcome will be leisure-time and transport-related physical activity, assessed through the International Physical Activity Questionnaire long version. Exposure variables will be built environment features in the areas participants live and work in the follow-up. Data analysis will include multivariate multilevel linear and logistic models. We will also conduct cost-effectiveness analysis and develop agent-based models to help inform decision-makers. The study will be conducted by an interdisciplinary research team specialized in physical activity epidemiology, nutritional epidemiology, georeferencing applied to health, statistics, agent-based modeling, public health policy, and health economics. DISCUSSION: There are few longitudinal studies on the relationship between the built environment and physical activity behavior in low- and middle-income countries. We believe that the ISA-Physical Activity and Environment study will contribute with important results for the progress of the knowledge in this field and for the implementation of policies that promote leisure-time physical activity and active travel in Sao Paulo and similar cities across the world.

Paracoccidioimycosis and white individuals: Susceptibility and biogeographic aspects in an important endemic area in Brazil.

Paracoccidioidomycosis (PCM) is a neglected mycosis most commonly occurring in Latin America. The etiologic agents are thermo dimorphic fungi of the genus Paracoccidioides, and cause an important granulomatous response in affected tissues. The Botucatu Medical School, from São Paulo State University (UNESP), is a PCM study pole, located in São Paulo State Midwest region, which is classified as a hyperendemic area in the Southeast region in Brazil. This study aimed to perform a retrospective epidemiological, geographical, and clinical analysis by the information available in medical records. It was listed as socio-demographic data along with clinical characteristics from patients diagnosed and treated during a 10-year period in Botucatu, totaling 177 patients with Paracoccidioidomycosis confirmed by the histopathological test. It was observed that the main clinical presentation was the chronic type (76,3%), most commonly identified in white male individuals over the age of 29 years old, smokers, and alcoholics, providing evidences for the first time that white individuals were more affected by the disease, in comparison to non-white individuals that may be more resistant to infection. This data opens new avenues for study within ancestry, resistance and susceptibility in paracoccidioidomycosis.

Mix of destinations and sedentary behavior among Brazilian adults: a cross-sectional study.

BACKGROUND: Sedentary behavior is influenced by contextual, social, and individual factors, including the built environment. However, associations between the built environment and sitting time have not been extensively investigated in countries with economies in transition such as Brazil. The objective of this study is to examine the relationship between sitting-time and access to a mix of destinations for adults from Sao Paulo city, Brazil. METHODS: This study uses data from the Health Survey of Sao Paulo. Sedentary behavior was assessed by a questionnaire using two questions: total sitting time in minutes on a usual weekday; and on a usual weekend day. The mix of destinations was measured by summing the number of facilities (comprising bus stops, train/subway stations, parks, squares, public recreation centres, bike paths, primary health care units, supermarkets, food stores, bakeries, and coffee-shops) within 500 m of each participant's residence. Minutes of sitting time in a typical weekday and weekend day were the outcomes and the mix of destinations score in 500 m buffers was the exposure variable. Associations between the mix of destinations and sitting time were examined using multilevel linear regression: these models accounted for clustering within census tracts and households and adjusted for environmental, sociodemographic, and health-related factors. RESULTS: After adjustment for covariates, the mix of destinations was inversely associated with minutes of sitting time on a weekday (ß=- 8.8, p=0.001) and weekend day (ß=- 6.1, p=0.022). People who lived in areas with a greater mix of destinations had shorter average sitting times. CONCLUSION: Greater mix of destinations within 500 m of peoples' residences was inversely associated with sitting time on a typical weekday and weekend day. In Latin American cities like Sao Paulo built environments more favorable for walking may contribute to reducing sedentary behavior and prevent associated chronic disease.

Spatiotemporal ecological study of COVID-19 mortality in the city of São Paulo, Brazil: Shifting of the high mortality risk from areas with the best to those with the worst socio-economic conditions.

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

Geographical clusters and social risk factors for suicide in the city of São Paulo, 2006-2015: An ecologic study.

BACKGROUND: To identify geographical clusters of suicide in São Paulo, Brazil (2006-2015) and to verify the associations of suicide with sociocultural characteristics of its 96 districts. METHODS: Spatial scan test was used to detect the geographical clusters. Correlation and multiple regression techniques were used to estimate the association of socioeconomic and cultural variables with suicide. RESULTS: The mean suicide rate was 4.8/100,000. Three clusters were identified which are as follows: one of increased risk in downtown and two of decreased risk in the South and in the Southeast. The mean suicide rate of the high-risk clustered districts (7.99/100,000) presented significantly higher average incomes per household, higher proportion of formally educated, of no religious affiliation, of recent migrants, of all-times migrants and lower proportion of married. The multiple model selected two independent risk factors - people with no religious affiliation (ß = 0.182) and of recent migrants (ß = 0.278) - and two protective factors - the proportion of married (ß = -0.185) and of total migrants (ß = -0.075), which jointly explained 58.4% of the variance. CONCLUSION: Durkheimian social and cultural risk factors for suicide were confirmed. Compared to a previous study period (1996-2005), suicide rates and geographical clusters remained relatively stable in the subsequent decade (2006-2015).

GeoSES: A socioeconomic index for health and social research in Brazil.

The individual's socioeconomic conditions are the most relevant to predict the quality of someone's health. However, such information is not usually found in medical records, making studies in the area difficult. Therefore, it is common to use composite indices that characterize a region socioeconomically, such as the Human Development Index (HDI). The main advantage of the HDI is its understanding and adoption on a global scale. However, its applicability is limited for health studies since its longevity dimension presents mathematical redundancy in regression models. Here we introduce the GeoSES, a composite index that summarizes the main dimensions of the Brazilian socioeconomic context for research purposes. We created the index from the 2010 Brazilian Census, whose variables selection was guided by theoretical references for health studies. The proposed index incorporates seven socioeconomic dimensions: education, mobility, poverty, wealth, income, segregation, and deprivation of resources and services. We developed the GeoSES using Principal Component Analysis and evaluated its construct, content, and applicability. GeoSES is defined at three scales: national (GeoSES-BR), Federative Unit (GeoSES-FU), and intra-municipal (GeoSES-IM). GeoSES-BR dimensions showed a good association with HDI-M (correlation above 0.85). The model with the poverty dimension best explained the relative risk of avoidable cause mortality in Brazil. In the intra-municipal scale, the model with GeoSES-IM was the one that best explained the relative risk of mortality from circulatory system diseases. By applying spatial regressions, we demonstrated that GeoSES shows significant explanatory potential in the studied scales, being a compelling complement for future researches in public health.

Pleural anthracosis as an indicator of lifetime exposure to urban air pollution: An autopsy-based study in Sao Paulo.

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.

Small-Scale Variations in Urban Air Pollution Levels Are Significantly Associated with Premature Births: A Case Study in São Paulo, Brazil.

Premature birth is the result of a complex interaction among genetic, epigenetic, behavioral, socioeconomic, and environmental factors. We evaluated the possible associations between air pollution and the incidence of prematurity in spatial clusters of high and low prevalence in the municipality of São Paulo. It is a spatial case-control study. The residential addresses of mothers with live births that occurred in 2012 and 2013 were geo-coded. A spatial scan statistical test performed to identify possible low-prevalence and high-prevalence clusters of premature births. After identifying, the spatial clusters were drawn samples of cases and controls in each cluster. Mothers were interviewed face-to-face using questionnaires. Air pollution exposure was assessed by passive tubes (NO2 and O3) as well as by the determination of trace elements' concentration in tree bark. Binary logistic regression models were applied to determine the significance of the risk of premature birth. Later prenatal care, urinary infection, and hypertension were individual risk factors for prematurity. Particles produced by traffic emissions (estimated by tree bark accumulation) and photochemical pollutants involved in the photochemical cycle (estimated by O3 and NO2 passive tubes) also exhibited significant and robust risks for premature births. The results indicate that air pollution is an independent risk factor for prematurity.

Epidemiological and geographical characterization of leprosy in a Brazilian hyperendemic municipality.

This study aimed to identify the distribution pattern of leprosy in a hyperendemic municipality in Brazil and determine its relationship with the clinico-epidemiological situation over 11 years. The geographic information system, MapInfo, spatial scan statistics and the Moran I index were used to analyze new cases. The digital cartographic base was used to map clusters of new paucibacillary and multibacillary cases and cases in minors under 15 years old. Socioeconomic indicators are shown using the choropleth mapping technique. A reduction in the detection coefficient, increases in high-risk spatial clusters, marked changes in the distribution of high-risk and low-risk clusters, and high-risk clusters of minors under 15 years old were observed from 2006 to 2010, showing recent illness, the presence of active foci, and overlapping of high-risk clusters of multibacillary infection in minors under 15 years old. Leprosy remains a public health problem in Rondonópolis, Mato Grosso State; the high-risk areas require an intensification of control measures and active search strategies to detect new cases.

Cycling for Transportation in Sao Paulo City: Associations with Bike Paths, Train and Subway Stations.

Cities that support cycling for transportation reap many public health benefits. However, the prevalence of this mode of transportation is low in Latin American countries and the association with facilities such as bike paths and train/subway stations have not been clarified. We conducted a cross-sectional analysis of the relationship between bike paths, train/subway stations and cycling for transportation in adults from the city of Sao Paulo. We used data from the Sao Paulo Health Survey (n = 3145). Cycling for transportation was evaluated by a questionnaire and bike paths and train/subway stations were geocoded using the geographic coordinates of the adults' residential addresses in 1500-m buffers. We used multilevel logistic regression, taking account of clustering by census tract and households. The prevalence of cycling for transportation was low (5.1%), and was more prevalent in males, singles, those active in leisure time, and in people with bicycle ownership in their family. Cycling for transportation was associated with bike paths up to a distance of 500 m from residences (OR (Odds Ratio) = 2.54, 95% CI (Confidence interval) 1.16-5.54) and with the presence of train/subway stations for distances >500 m from residences (OR = 2.07, 95% CI 1.10-3.86). These results are important to support policies to improve cycling for transportation in megacities such as Sao Paulo.