NELSON DA CRUZ GOUVEIA
Projetos de Pesquisa
Unidades Organizacionais
Departamento de Medicina Preventiva, Faculdade de Medicina - Docente
LIM/39 - Laboratório de Processamento de Dados Biomédicos, Hospital das Clínicas, Faculdade de Medicina - Líder
LIM/39 - Laboratório de Processamento de Dados Biomédicos, Hospital das Clínicas, Faculdade de Medicina - Líder
73 resultados
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- Maternal Exposure to Particulate Air Pollution and Term Birth Weight: A Multi-Country Evaluation of Effect and Heterogeneity(2013) DADVAND, Payam; PARKER, Jennifer; BELL, Michelle L.; BONZINI, Matteo; BRAUER, Michael; DARROW, Lyndsey A.; GEHRING, Ulrike; GLINIANAIA, Svetlana V.; GOUVEIA, Nelson; HA, Eun-hee; LEEM, Jong Han; HOOVEN, Edith H. van den; JALALUDIN, Bin; JESDALE, Bill M.; LEPEULE, Johanna; MORELLO-FROSCH, Rachel; MORGAN, Geoffrey G.; PESATORI, Angela Cecilia; PIERIK, Frank H.; PLESS-MULLOLI, Tanja; RICH, David Q.; SATHYANARAYANA, Sheela; SEO, Juhee; SLAMA, Remy; STRICKLAND, Matthew; TAMBURIC, Lillian; WARTENBERG, Daniel; NIEUWENHUIJSEN, Mark J.; WOODRUFF, Tracey J.BACKGROUND: A growing body of evidence has associated maternal exposure to air pollution with adverse effects on fetal growth; however, the existing literature is inconsistent. OBJECTIVES: We aimed to quantify the association between maternal exposure to particulate air pollution and term birth weight and low birth weight (LBW) across 14 centers from 9 countries, and to explore the influence of site characteristics and exposure assessment methods on between-center heterogeneity in this association. METHODS: Using a common analytical protocol, International Collaboration on Air Pollution and Pregnancy Outcomes (ICAPPO) centers generated effect estimates for term LBW and continuous birth weight associated with PM10 and PM2.5 (particulate matter <= 10 and 2.5 mu m). We used meta-analysis to combine the estimates of effect across centers (similar to 3 million births) and used meta-regression to evaluate the influence of center characteristics and exposure assessment methods on between-center heterogeneity in reported effect estimates. RESULTS: In random-effects meta-analyses, term LBW was positively associated with a 10-mu g/m(3) increase in PM10 [odds ratio (OR) = 1.03; 95% CI: 1.01, 1.05] and PM2.5 (OR = 1.10; 95% CI: 1.03, 1.18) exposure during the entire pregnancy, adjusted for maternal socioeconomic status. A 10-mu g/m(3) increase in PM10 exposure was also negatively associated with term birth weight as a continuous outcome in the fully adjusted random-effects meta-analyses (-8.9 g; 95% CI: -13.2, -4.6 g). Meta-regressions revealed that centers with higher median PM2.5 levels and PM2.5: PM10 ratios, and centers that used a temporal exposure assessment (compared with spatiotemporal), tended to report stronger associations. CONCLUSION: Maternal exposure to particulate pollution was associated with LBW at term across study populations. We detected three site characteristics and aspects of exposure assessment methodology that appeared to contribute to the variation in associations reported by centers.
- The International Collaboration on Air Pollution and Pregnancy Outcomes: Initial Results(2011) PARKER, Jennifer D.; RICH, David Q.; GLINIANAIA, Svetlana V.; LEEM, Jong Han; WARTENBERG, Daniel; BELL, Michelle L.; BONZINI, Matteo; BRAUER, Michael; DARROW, Lyndsey; GEHRING, Ulrike; GOUVEIA, Nelson; GRILLO, Paolo; HA, Eunhee; HOOVEN, Edith H. van den; JALALUDIN, Bin; JESDALE, Bill M.; LEPEULE, Johanna; MORELLO-FROSCH, Rachel; MORGAN, Geoffrey G.; SLAMA, Remy; PIERIK, Frank H.; PESATORI, Angela Cecilia; SATHYANARAYANA, Sheela; SEO, Juhee; STRICKLAND, Matthew; TAMBURIC, Lillian; WOODRUFF, Tracey J.BACKGROUND: The findings of prior studies of air pollution effects on adverse birth outcomes are difficult to synthesize because of differences in study design. OBJECTIVES: The International Collaboration on Air Pollution and Pregnancy Outcomes was formed to understand how differences in research methods contribute to variations in findings. We initiated a feasibility study to a) assess the ability of geographically diverse research groups to analyze their data sets using a common protocol and b) perform location-specific analyses of air pollution effects on birth weight using a standardized statistical approach. METHODS: Fourteen research groups from nine countries participated. We developed a protocol to estimate odds ratios (ORs) for the association between particulate matter <= 10 mu m in aerodynamic diameter (PM(10)) and low birth weight (LBW) among term births, adjusted first for socioeconomic status (SES) and second for additional location-specific variables. RESULTS: Among locations with data for the PM(10) analysis, ORs estimating the relative risk of term LBW associated with a 10-mu g/m(3) increase in average PM(10) concentration during pregnancy, adjusted for SES, ranged from 0.63 [95% confidence interval (CI), 0.30-1.35] for the Netherlands to 1.15 (95% CI, 0.61-2.18) for Vancouver, with six research groups reporting statistically significant adverse associations. We found evidence of statistically significant heterogeneity in estimated effects among locations. CONCLUSIONS: Variability in PM(10)-LBW relationships among study locations remained despite use of a common statistical approach. A more detailed meta-analysis and use of more complex protocols for future analysis may uncover reasons for heterogeneity across locations. However, our findings confirm the potential for a diverse group of researchers to analyze their data in a standardized way to improve understanding of air pollution effects on birth outcomes.
- Socioeconomic Position and Low Birth Weight among Mothers Exposed to Traffic-Related Air Pollution(2014) HABERMANN, Mateus; GOUVEIA, NelsonBackground: Atmospheric pollution is a major public health concern. It can affect placental function and restricts fetal growth. However, scientific knowledge remains too limited to make inferences regarding causal associations between maternal exposure to air pollution and adverse effects on pregnancy. This study evaluated the association between low birth weight (LBW) and maternal exposure during pregnancy to traffic related air pollutants (TRAP) in Sao Paulo, Brazil. Methods and findings: Analysis included 5,772 cases of term-LBW (<2,500 g) and 5,814 controls matched by sex and month of birth selected from the birth registration system. Mothers' addresses were geocoded to estimate exposure according to 3 indicators: distance from home to heavy traffic roads, distance-weighted traffic density (DWTD) and levels of particulate matter <= 10 mg/m(3) estimated through land use regression (LUR-PM10). Final models were evaluated using multiple logistic regression adjusting for birth, maternal and pregnancy characteristics. We found decreased odds in the risk of LBW associated with DWTD and LUR-PM10 in the highest quartiles of exposure with a significant linear trend of decrease in risk. The analysis with distance from heavy traffic roads was less consistent. It was also observed that mothers with higher education and neighborhood-level income were potentially more exposed to TRAP. Conclusions: This study found an unexpected decreased risk of LBW associated with traffic related air pollution. Mothers with advantaged socioeconomic position (SEP) although residing in areas of higher vehicular traffic might not in fact be more expose to air pollution. It can also be that the protection against LBW arising from a better SEP is stronger than the effect of exposure to air pollution, and this exposure may not be sufficient to increase the risk of LBW for these mothers.
- Ambient fine particulate matter in Latin American cities: Levels, population exposure, and associated urban factors(2021) GOUVEIA, Nelson; KEPHART, Josiah L.; DRONOVA, Iryna; MCCLURE, Leslie; GRANADOS, Jose Tapia; BETANCOURT, Ricardo Morales; O'RYAN, Andrea Cortinez; TEXCALAC-SANGRADOR, Jose Luis; MARTINEZ-FOLGAR, Kevin; RODRIGUEZ, Daniel; V, Ana Diez-RouxBackground: Exposure to particulate matter (PM2.5) is a major risk factor for morbidity and mortality. Yet few studies have examined patterns of population exposure and investigated the predictors of PM2.5 across the rap-idly growing cities in lower- and middle-income countries. Objectives: Characterize PM2.5 levels, describe patterns of population exposure, and investigate urban factors as predictors of PM2.5 levels. Methods: We used data from the Salud Urbana en America Latina/Urban Health in Latin America (SALURBAL) study, a multi-country assessment of the determinants of urban health in Latin America, to characterize PM2.5 levels in 366 cities comprising over 100,000 residents using satellite-derived estimates. Factors related to urban form and transportation were explored. Results: We found that about 172 million or 58% of the population studied lived in areas with air pollution levels above the defined WHO-AQG of 10 mu g/m(3) annual average. We also found that larger cities, cities with higher GDP, higher motorization rate and higher congestion tended to have higher PM2.5. In contrast cities with higher population density had lower levels of PM2.5. In addition, at the sub-city level, higher intersection density was associated with higher PM2.5 and more green space was associated with lower PM2.5. When all exposures were examined adjusted for each other, higher city per capita GDP and higher sub-city intersection density remained associated with higher PM2.5 levels, while higher city population density remained associated with lower levels. The presence of mass transit was also associated with lower PM2.5 after adjustment. The motorization rate also remained associated with PM2.5 and its inclusion attenuated the effect of population density. Discussion: These results show that PM2.5 exposures remain a major health risk in Latin American cities and suggest that urban planning and transportation policies could have a major impact on ambient levels. (C) 2021 The Author(s).
- Vehicular traffic density and cognitive performance in the ELSA-Brasil study(2020) ROCHA, Douglas; SUEMOTO, Claudia K.; SANTOS, Itamar Souza; LOTUFO, Paulo A.; BENSENOR, Isabela; GOUVEIA, NelsonBackground: Despite the knowledge about the deleterious effects of air pollutants and their influence on mortality and morbidity due to respiratory and cardiovascular diseases, little is known about the relationship between atmospheric pollutants and neurological diseases. Recently, studies from high-income countries have suggested an association between exposures to air pollutants with cognitive impairment. Thus, we investigated the association of air pollution with cognitive performance in the participants of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Methods: Cognitive function was evaluated using the word list, the verbal fluency, and the trail making tests (TMT). Pollutant exposure was evaluated indirectly using the distance-weighted traffic density (DWTD) of participants' residence and workplace. We investigated the cross-sectional association between DWTD and cognitive test scores using adjusted linear regression models for sociodemographic and clinical variables. Results: 3050 were included (mean age = 52.1 +/- 9.2 years old, 56.5% women, and 63.6% white). In the simple linear regression models, participants in the higher tertile of combined DWTD (residence and workplace) presented better cognitive performance in all tests when compared to participants in the lower tertile. The DWTD was not associated with cognitive performance in adjusted linear models especially when adjusted for socioeconomic variables (age, sex, education, and race). We found similar results when we investigated the association of cognitive performance with DTWD near participants' workplace and residence separately. Conclusion: Air pollutants were not associated with worse cognitive performance in a large sample of middle-aged and older adults.
- Health impact modelling of different travel patterns on physical activity, air pollution and road injuries for Sao Paulo, Brazil(2017) SA, Thiago Herick de; TAINIO, Marko; GOODMAN, Anna; EDWARDS, Phil; HAINES, Andy; GOUVEIA, Nelson; MONTEIRO, Carlos; WOODCOCK, JamesBackground: Sao Paulo city, Brazil, faces challenges caused by rapid urbanization. We illustrate how future travel patterns could lead to different health consequences in the city. Methods: We evaluated the health impacts of different travel pattern scenarios for the Sao Paulo adult population by comparing the travel patterns of Sao Paulo in 2012 with counterfactual scenarios in which the city adopted travel patterns of i) those living in the city's expanded centre; ii) London (2012); iii) a highly motorized Sao Paulo (SP California); and iv) a visionary Sao Paulo (SP 2040), with high levels of walking and cycling and low levels of car and motorcycle use. For each scenario we estimated changes in exposure to air pollution, road injury risk, and physical activity. Health outcomes were estimated using disability adjusted life years (DALYs) and premature deaths averted. Sensitivity analyses were performed to identify the main sources of uncertainty. Results: We found considerable health gains in the SP 2040 scenario (total 63.6 k DALYs avoided), with 4.7% of premature deaths from ischemic heart disease avoided from increases in physical activity alone. Conversely, we found substantial health losses in the scenario favouring private transport (SP California, total increase of 54.9 k DALYs), with an increase in road traffic deaths and injuries among pedestrians and motorized vehicles. Parameters related to air pollution had the largest impact on uncertainty. Conclusions: Shifting travel patterns towards more sustainable transport can provide major health benefits in Sao Paulo. Reducing the uncertainties in the findings should be a priority for empirical and modelling research on the health impacts of such shifts.
- Aplicação de regressão baseada no uso do solo para predizer a concentração de material particulado inalável no município de São Paulo, Brasil(2013) HABERMANN, Mateus; GOUVEIA, NelsonThe study intended to develop a land use regression model to predict inhalable particulate matter (PM10) concentrations in Sao Paulo, Brazil. The model was based on the 2007 average of PM10 available from 9 monitoring stations and demographic, roads and land use data in buffers of 250 to 1,000 m. Simple linear regression were used to select the more robust independent variables and those without collinearity. Four variables were selected for the multiple regression analysis. Only light traffic in buffers <= 250 m remained in the final model which explained 63.8% of the PM(10)variance. The land use regression approach is a quick and easy method to predict air pollution levels. However, our model was based on measurements of only a few sites.
- Trace element levels in blood and associated factors in adults living in the metropolitan area of Sao Paulo, Brazil(2017) TAKEDA, Simone Harue Kimura; KUNO, Rubia; BARBOSA, Fernando; GOUVEIA, NelsonThis study evaluated blood arsenic (As), cadmium (Cd), lead (Pb), mercury (Hg), copper (Cu) and manganese (Mn) levels in a group of residents (n = 374) in the metropolitan area of Sao Paulo (MASP) and investigated the association between trace element levels in blood and sociodemographic and lifestyle factors. Trace elements were measured in specimens by inductively coupled plasma mass spectrometry (ICP-MS). Geometric means were 3.6 mu/L, 0.13 mu/L, 23.9 mu/L, 1.4 mu/L, 999 mu/L, and 12.5 mu/L for As, Cd, Pb, Hg, Cu, and Mn, respectively. As, Pb and Hg levels were associated with education level. Men presented higher blood lead levels (PbB) and lower blood copper levels (CuB) than women. Fish consumption was primarily related to increased blood Hg levels (HgB). Smokers exhibited 1.8 times more blood cadmium levels (CdB) than non-smokers. Only 4% of the study samples exceeded the Pb reference values for the MASP population, and 12% had Hg levels higher than the German HBM-I value (5 mu/L for adults).The study group showed slightly higher exposure to As, Hg and Mn and lower Cd than those of European and North American studies.
- Building a Data Platform for Cross-Country Urban Health Studies: the SALURBAL Study(2019) QUISTBERG, D. Alex; ROUX, Ana V. Diez; BILAL, Usama; MOORE, Kari; ORTIGOZA, Ana; RODRIGUEZ, Daniel A.; SARMIENTO, Olga L.; FRENZ, Patricia; FRICHE, Amelia Augusta; CAIAFFA, Waleska Teixeira; VIVES, Alejandra; MIRANDA, J. Jaime; ALAZRAQUI, Marcio; SPINELLI, Hugo; GUEVEL, Carlos; CECCO, Vanessa Di; TISNES, Adela; LEVEAU, Carlos; SANTORO, Adrian; HERKOVITS, Damian; GOUVEIA, Nelson; BARRETO, Mauricio; SANTOS, Gervasio; CARDOSO, Leticia; MENEZES, Mariana Carvalho de; PINA, Maria de Fatima de; CAIAFFA, Waleska Teixeira; FRICHE, Amelia Augusta de Lima; ANDRADE, Amanda Cristina de Souza; FRENZ, Patricia; ALFARO, Tania; CORDOVA, Cynthia; RUIZ, Pablo; FUENTES, Mauricio; VERGARA, Alejandra Vives; SALAZAR, Alejandro; CORTINEZ-O'RYAN, Andrea; SCHMITT, Cristian; GONZALEZ, Francisca; BAEZA, Fernando; ANGELINI, Flavia; DUENAS, Olga Lucia Sarmiento; HIGUERA, Diana; GONZALEZ, Catalina; MONTES, Felipe; USECHE, Andres F.; GUAJE, Oscar; JARAMILLO, Ana Maria; GUZMAN, Luis Angel; HESSEL, Philipp; LUCUMI, Diego; MEISEL, Jose David; MARTINEZ, Eliana; KROKER-LOBOS, Maria F.; RAMIREZ-ZEA, Manuel; FOLGER, Kevin Martinez; BARRIENTOS-GUTIERREZ, Tonatiuh; PEREZ-FERRER, Carolina; PRADO-GALBARRO, Javier; CASTRO, Filipa de; ROJAS-MARTINEZ, Rosalba; MIRANDA, J. Jaime; VASQUEZ, Akram Hernandez; DIEZ-CANSECO, Francisco; HAMMOND, Ross; RODRIGUEZ, Daniel; DRONOVA, Iryna; SANCHEZ, Brisa N.; HOVMAND, Peter; FUCHS, Ricardo Jordan; BRASLOW, Juliet; SIRI, Jose; ROUX, Ana Diez; AUCHINCLOSS, Amy; LANGELLIER, Brent; LOVASI, Gina; MCCLURE, Leslie; MICHAEL, Yvonne; QUICK, Harrison; QUISTBERG, D. Alex; GRANADOS, Jose Tapia; MOORE, Kari; GARCIA-ESPANA, Felipe; BILAL, Usama; STANKOV, IvanaStudies examining urban health and the environment must ensure comparability of measures across cities and countries. We describe a data platform and process that integrates health outcomes together with physical and social environment data to examine multilevel aspects of health across cities in 11 Latin American countries. We used two complementary sources to identify cities with 100,000 inhabitants as of 2010 in Argentina, Brazil, Chile, Colombia, Costa Rica, El Salvador, Guatemala, Mexico, Nicaragua, Panama, and Peru. We defined cities in three ways: administratively, quantitatively from satellite imagery, and based on country-defined metropolitan areas. In addition to cities, we identified sub-city units and smaller neighborhoods within them using census hierarchies. Selected physical environment (e.g., urban form, air pollution and transport) and social environment (e.g., income, education, safety) data were compiled for cities, sub-city units, and neighborhoods whenever possible using a range of sources. Harmonized mortality and health survey data were linked to city and sub-city units. Finer georeferencing is underway. We identified 371 cities and 1436 sub-city units in the 11 countries. The median city population was 234,553 inhabitants (IQR 141,942; 500,398). The systematic organization of cities, the initial task of this platform, was accomplished and further ongoing developments include the harmonization of mortality and survey measures using available sources for between country comparisons. A range of physical and social environment indicators can be created using available data. The flexible multilevel data structure accommodates heterogeneity in the data available and allows for varied multilevel research questions related to the associations of physical and social environment variables with variability in health outcomes within and across cities. The creation of such data platforms holds great promise to support researching with greater granularity the field of urban health in Latin America as well as serving as a resource for the evaluation of policies oriented to improve the health and environmental sustainability of cities.
- Using satellite imagery to estimate heavy vehicle volume for ecological injury analysis in India(2020) GOEL, Rahul; MIRANDA, J. Jaime; GOUVEIA, Nelson; WOODCOCK, JamesA major limitation of road injury research in low- and-middle income countries is the lack of consistent data across the settings, such as traffic counts, to measure traffic risk. This study presents a novel method in which traffic volume of heavy vehicles - trucks and buses - is estimated by identifying these vehicles from satellite imagery of Google Earth. For Rajasthan state in India, a total of similar to 44,000 such vehicles were manually identified and geo-located on national highways (NHs), with no distinction made between trucks and buses. To estimate population living in proximity to NHs, defined as those living within 1 km buffer of NH, we geocoded similar to 45,000 villages and similar to 300 cities using Google Maps Geocoding Application Programming Interface (API). We fitted a spatio-temporal Bayesian regression model with the number of road deaths at the district level as the outcome variable. We found a strong Pearson correlation of 0.84 (p < 0.001) between Google Earth estimates of heavy vehicles and freight vehicle counts reported by a national-level study for different road sections. The regression results show that the volume of heavy vehicles and rural population in proximity to highways are positively associated with fatality risk in the districts. These effects have been estimated after controlling for other modes of travel.