Wildfire, deforestation and health in tropical rainforest areas: a scoping review protocol.

INTRODUCTION: Wildfires and deforestation potentially have direct effects on multiple health outcomes as well as indirect consequences for climate change. Tropical rainforest areas are characterised by high rainfall, humidity and temperature, and they are predominantly found in low-income and middle-income countries. This study aims to synthesise the methods, data and health outcomes reported in scientific papers on wildfires and deforestation in these locations. METHODS AND ANALYSIS: We will carry out a scoping review according to the Joanna Briggs Institute's (JBI) manual for scoping reviews and the framework proposed by Arksey and O'Malley, and Levac et al. The search for articles was performed on 18 August 2023, in 16 electronic databases using Medical Subject Headings terms and adaptations for each database from database inception. The search for local studies will be complemented by the manual search in the list of references of the studies selected to compose this review. We screened studies written in English, French, Portuguese and Spanish. We included quantitative studies assessing any human disease outcome, hospitalisation and vital statistics in regions of tropical rainforest. We exclude qualitative studies and quantitative studies whose outcomes do not cover those of interest. The text screening was done by two independent reviewers. Subsequently, we will tabulate the data by the origin of the data source used, the methods and the main findings on health impacts of the extracted data. The results will provide descriptive statistics, along with visual representations in diagrams and tables, complemented by narrative summaries as detailed in the JBI guidelines. ETHICS AND DISSEMINATION: The study does not require an ethical review as it is meta-research and uses published, deidentified secondary data sources. The submission of results for publication in a peer-reviewed journal and presentation at scientific and policymakers' conferences is expected. STUDY REGISTRATION: Open Science Framework (https://osf.io/pnqc7/).

Effects of heat waves on cardiovascular and respiratory mortality in Rio de Janeiro, Brazil.

BACKGROUND: Heat waves are becoming more intense and extreme as a consequence of global warming. Epidemiological evidence reveals the health impacts of heat waves in mortality and morbidity outcomes, however, few studies have been conducted in tropical regions, which are characterized by high population density, low income and low health resources, and susceptible to the impacts of extreme heat on health. The aim of this paper is to estimate the effects of heat waves on cardiovascular and respiratory mortality in the city of Rio de Janeiro, Brazil, according to sex, age, and heat wave intensity. METHODS: We carried out a time-stratified case-crossover study stratified by sex, age (0-64 and 65 or above), and by sex for the older group. Our analyses were restricted to the hot season. We included 42,926 participants, 29,442 of whom died from cardiovascular and 13,484 from respiratory disease, between 2012 and 2017. The death data were obtained from Rio de Janeiro's Municipal Health Department. We estimated individual-level exposure using the inverse distance weighted (IDW) method, with temperature and humidity data from 13 and 12 stations, respectively. We used five definitions of heat waves, based on temperature thresholds (90th, 92.5th, 95th, 97.5th, and 99th of individual daily mean temperature in the hot season over the study period) and a duration of two or more days. Conditional logistic regression combined with distributed lag non-linear models (DLNM) were used to estimate the short-term and delayed effects of heat waves on mortality over a lag period (5 days for cardiovascular and 10 for respiratory mortality). The models were controlled for daily mean absolute humidity and public holidays. RESULTS: The odds ratios (OR) increase as heat waves intensify, although some effect estimates are not statistically significant at 95% level when we applied the most stringent heat wave criteria. Although not statistically different, our central estimates suggest that the effects were greater for respiratory than cardiovascular mortality. Results stratified by sex and age were also not statistically different, but suggest that older people and women were more vulnerable to the effects of heat waves, although for some heat wave definitions, the OR for respiratory mortality were higher among the younger group. The results also indicate that older women are the most vulnerable to heat wave-related cardiovascular mortality. CONCLUSION: Our results show an increase in the risk of cardiovascular and respiratory mortality on heat wave days compared to non-heat wave ones. These effects increase with heat wave intensity, and evidence suggests that they were greater for respiratory mortality than cardiovascular mortality. Furthermore, the results also suggest that women and the elderly constitute the groups most vulnerable to heat waves.

Short-term association between ambient air pollution and cardio-respiratory mortality in Rio de Janeiro, Brazil.

BACKGROUND: Several epidemiological studies have reported associations between ambient air pollution and mortality. However, relatively few studies have investigated this relationship in Brazil using individual-level data. OBJECTIVES: To estimate the short-term association between exposure to particulate matter <10 µm (PM10) and ozone (O3), and cardiovascular and respiratory mortality in Rio de Janeiro, Brazil, between 2012 and 2017. METHODS: We used a time-stratified case-crossover study design with individual-level mortality data. Our sample included 76,798 deaths from cardiovascular diseases and 36,071 deaths from respiratory diseases. Individual exposure to air pollutants was estimated by the inverse distance weighting method. We used data from seven monitoring stations for PM10 (24-hour mean), eight stations for O3 (8-hour max), 13 stations for air temperature (24-hour mean), and 12 humidity stations (24-hour mean). We estimated the mortality effects of PM10 and O3 over a 3-day lag using conditional logistic regression models combined with distributed lag non-linear models. The models were adjusted for daily mean temperature and daily mean absolute humidity. Effect estimates were presented as odds ratios (OR) with their 95% confidence interval (CI) associated with a 10 µg/m3 increase in each pollutant exposure. RESULTS: No consistent associations were observed for both pollutant and mortality outcome. The cumulative OR of PM10 exposure was 1.01 (95% CI 0.99-1.02) for respiratory mortality and 1.00 (95% CI 0.99-1.01) for cardiovascular mortality. For O3 exposure, we also found no evidence of increased mortality for cardiovascular (OR 1.01, 95% CI 1.00-1.01) or respiratory diseases (OR 0.99, 95% CI 0.98-1.00). Our findings were similar across age and gender subgroups, and different model specifications. CONCLUSION: We found no consistent associations between the PM10 and O3 concentrations observed in our study and cardio-respiratory mortality. Future studies need to explore more refined exposure assessment methods to improve health risk estimates and the planning and evaluation of public health and environmental policies.

Heat waves and mortality in the Brazilian Amazon: Effect modification by heat wave characteristics, population subgroup, and cause of death.

BACKGROUND: The Brazilian Amazon faces overlapping socio-environmental, sanitary, and climate challenges, and is a hotspot of concern due to projected increases in temperature and in the frequency of heat waves. Understanding the effects of extreme events on health is a central issue for developing climate policies focused on the population's health. OBJECTIVES: We investigated the effects of heat waves on mortality in the Brazilian Amazon, examining effect modification according to various heat wave definitions, population subgroups, and causes of death. METHODS: We included all 32 Amazonian municipalities with more than 100,000 inhabitants. The study period was from 2000 to 2018. We obtained mortality data from the Information Technology Department of the Brazilian Public Healthcare System, and meteorological data were derived from the ERA5-Land reanalysis dataset. Heat waves were defined according to their intensity (90th; 92.5th; 95th; 97.5th and 99th temperature percentiles) and duration (≥2, ≥3, and ≥4 days). In each city, we used a time-stratified case-crossover study to estimate the effects of each heat wave definition on mortality, according to population subgroup and cause of death. The lagged effects of heat waves were estimated using conditional Poisson regression combined with distributed lag non-linear models. Models were adjusted for specific humidity and public holidays. Risk ratios were pooled for the Brazilian Amazon using a univariate random-effects meta-analysis. RESULTS: The pooled relative risks (RR) for mortality from total non-external causes varied between 1.03 (95% CI: 1.01-1.06), for the less stringent heat wave definition, and 1.18 (95% CI: 1.04-1.33) for the more stringent definition. The mortality risk rose as the heat wave intensity increased, although the increase from 2 to 3, and 3-4 days was small. Although not statistically different, our results suggest a higher mortality risk for the elderly, this was also higher for women than men, and for cardiovascular causes than for non-external or respiratory ones. CONCLUSIONS: Heat waves were associated with a higher risk of mortality from non-external causes and cardiovascular diseases. Heat wave intensity played a more important role than duration in determining this risk. Suggestive evidence indicated that the elderly and women were more vulnerable to the effects of heat waves on mortality.

Improving geocoding matching rates of structured addresses in Rio de Janeiro, Brazil.

Strategies for improving geocoded data often rely on interactive manual processes that can be time-consuming and impractical for large-scale projects. In this study, we evaluated different automated strategies for improving address quality and geocoding matching rates using a large dataset of addresses from death records in Rio de Janeiro, Brazil. Mortality data included 132,863 records with address information in a structured format. We performed regular expressions and dictionary-based methods for address standardization and enrichment. All records were linked by their postal code or street name to the Brazilian National Address Directory (DNE) obtained from Brazil's Postal Service. Residential addresses were geocoded using Google Maps. Records with address data validated down to the street level and location type returned as rooftop, range interpolated, or geometric center were considered a geocoding match. The overall performance was assessed by manually reviewing a sample of addresses. Out of the original 132,863 records, 85.7% (n = 113,876) were geocoded and validated, out of which 83.8% were matched as rooftop (high accuracy). Overall sensitivity and specificity were 87% (95%CI: 86-88) and 98% (95%CI: 96-99), respectively. Our results indicate that address quality and geocoding completeness can be reliably improved with an automated geocoding process. R scripts and instructions to reproduce all the analyses are available at https://github.com/reprotc/geocoding.

Projections of excess cardiovascular mortality related to temperature under different climate change scenarios and regionalized climate model simulations in Brazilian cities.

BACKGROUND: There is an urgent need for more information about the climate change impact on health in order to strengthen the commitment to tackle climate change. However, few studies have quantified the health impact of climate change in Brazil and in the Latin America region. In this paper, we projected the impacts of temperature on cardiovascular (CVD) mortality according to two climate change scenarios and two regionalized climate model simulations in Brazilian cities. METHODS: We estimated the temperature-CVD mortality relationship in 21 Brazilian cities, using distributed lag non-linear models in a two-stage time-series analysis. We combined the observed exposure-response functions with the daily temperature projected under two representative concentration pathways (RCP), RCP8.5 and RCP4.5, and two regionalized climate model simulations, Eta-HadGEM2-ES and Eta-MIROC5. RESULTS: We observed a trend of reduction in mortality related to low temperatures and a trend of increase in mortality related to high temperatures, according to all the investigated models and scenarios. In most places, the increase in mortality related to high temperatures outweighed the reduction in mortality related to low temperatures, causing a net increase in the excess temperature-related mortality. These trends were steeper according to the higher emission scenario, RCP8.5, and to the Eta-HadGEM2-ES model. According to RCP8.5, our projections suggested that the temperature-related mortality fractions in 2090-99 compared to 2010-2019 would increase by 8.6% and 1.7%, under Eta-HadGEM2-ES and Eta-MIROC5, respectively. According to RCP4.5, these values would be 0.7% and -0.6%. CONCLUSIONS: For the same climate model, we observed a greater increase trend in temperature-CVD mortality according to RCP8.5, highlighting a greater health impact associated with the higher emission scenario. Our results may be useful to support public policies and strategies for mitigation of and adaptation to climate change, particularly in the health sector.

Temperature and cardiovascular mortality in Rio de Janeiro, Brazil: effect modification by individual-level and neighbourhood-level factors.

BACKGROUND: Many factors related to susceptibility or vulnerability to temperature effects on mortality have been proposed in the literature. However, there is limited evidence of effect modification by some individual-level factors such as occupation, colour/race, education level and community-level factors. We investigated the effect modification of the temperature-cardiovascular mortality relationship by individual-level and neighbourhood-level factors in the city of Rio de Janeiro, Brazil. METHODS: We used a case-crossover study to estimate the total effect of temperature on cardiovascular mortality in Rio de Janeiro between 2001 and 2018, and the effect modification by individual-level and neighbourhood-level factors. Individual-level factors included sex, age, colour/race, education, and place of death. Neighbourhood-level characteristics included social development index (SDI), income, electricity consumption and demographic change. We used conditional Poisson regression models combined with distributed lag non-linear models, adjusted for humidity and public holidays. RESULTS: Our results suggest a higher vulnerability to high temperatures among the elderly, women, non-hospitalised deaths, and people with a lower education level. Vulnerability to low temperatures was higher among the elderly, men, non-white people, and for primary education level. As for neighbourhood-level factors, we identified greater vulnerability to low and high temperatures in places with lower SDI, lower income, lower consumption of electricity, and higher demographic growth. CONCLUSION: The effects of temperature on cardiovascular disease mortality in Rio de Janeiro vary according to individual-level and neighbourhood-level factors. These findings are valuable to inform policymakers about the most vulnerable groups and places, in order to develop more effective and equitable public policies.

Neighborhood physical disorder and common mental disorders in adolescence.

OBJECTIVE: The aim of this study is to estimate the association between observed indicators of neighborhood physical disorder and common mental disorders in adolescents. METHODS: The study population included 2506 adolescents from three Brazilian state capitals (Rio de Janeiro, Porto Alegre, and Fortaleza) who participated in the Cardiovascular Risk Study in Adolescents (ERICA), a cross-sectional school-based study conducted in 2013-2014. Common mental disorders were assessed using the 12-item General Health Questionnaire. Measures of neighborhood physical disorder were based on the 2010 Brazilian census data and were derived using principal component analysis. RESULTS: Although associations were found between some exposure components and CMD, there were no clear or consistent trends across exposure quartiles. CONCLUSION: Overall, there was no evidence of an association between observed indicators of neighborhood physical disorder and common mental disorders. Future studies should explore alternative tools for measuring neighborhood physical disorder to minimize the likelihood of exposure misclassification.

The effect of ambient temperature on cardiovascular mortality in 27 Brazilian cities.

BACKGROUND: There is limited evidence on the relationship between temperature and cardiovascular mortality in middle and low-income countries, particularly in Latin America. In this study, we investigated the total effect of temperature on cardiovascular mortality in 27 Brazilian cities, and the effect modification by geographic, socioeconomic, demographic and infrastructure characteristics within cities. METHODS: In the city-specific analysis, we used time-series analyses to estimate the relationship between mean temperature and daily cardiovascular mortality using quasi-Poisson generalized linear models combined with distributed lag non-linear models. In the second stage, a meta-analysis was used to pool the effects of temperature on cardiovascular mortality for Brazil and its five regions (Central-West, North, Northeast, South, and Southeast). We used a meta-regression to examine the effect modification of city-specific geographic, socioeconomic, demographic and infrastructure-related variables. RESULTS: The risks associated with temperature varied across the locations. Higher cardiovascular mortality was associated with low and high temperatures in most of the cities, Brazil and the Central-West, North, South, and Southeast regions. The overall relative risk (RR) for Brazil was 1.26 (95% confidence interval [CI]: 1.17-1.35) for the 1st percentile of temperature and 1.07 (95% CI: 1.01-1.13) for the 99th percentile of temperature versus the 79th percentile (27.7 °C), where RR was lowest. The temperature range was the variable that best explained the variation in effects among the cities, with greater effects in locations having a broader range. CONCLUSIONS: The results indicate effects of low and high temperatures on the risk of cardiovascular mortality in most of Brazil's capital cities, besides a pooled effect for Brazil and the Central-West, North, South, and Southeast regions. These findings can help inform public policies addressing the health impact of temperature extremes, especially in the context of climate change.

Utilização de diagramas causais e a comunicação de fontes de incerteza em estudos observacionais / Use of causal DAG and reporting of uncertainty in observational studies

Os diagramas causais (gráficos acíclicos direcionados ­ DAG) têm sido apontados como uma das principais ferramentas que podem contribuir para a qualidade metodológica e do relato de estudos observacionais. No entanto, pouco se sabe sobre como essas ferramentas têm sido utilizadas nas investigações empíricas. Neste trabalho, foi realizada uma revisão da literatura com o objetivo de descrever o quanto, como e onde os diagramas causais têm sido utilizados em estudos observacionais analíticos nos últimos 18 anos. Foram realizadas buscas por citações e pesquisas por palavras-chaves nas bases de dados do PubMed e Web of Science. Em uma amostra de 100 artigos que apresentaram a estrutura causal, foram avaliadas as características dos modelos gráficos e o relato de confundimento. Além disso, foi realizada uma análise comparativa do relato das limitações do estudo e da frequência de marcadores linguísticos de incerteza (hedges) nos artigos com e sem a utilização de DAG causais. Foram identificadas 1034 publicações, totalizando 5021 autores e 85 países de afiliação. Apenas 430 artigos (42%) forneceram a estrutura gráfica. A maioria das publicações contém apenas um DAG causal (87%) e poucos modelos gráficos contêm confundidores não observados (23%), ou a representação de erros de mensuração (6%) e mecanismos de seleção (3%). O relato de modificações no conjunto de ajuste foi observado em 19% das publicações. Além disso, 20% foram classificadas como possível ocorrência da falácia da tabela 2. O número de limitações do estudo reconhecidas pelos autores e a frequência de marcadores de incerteza foram semelhantes nas amostras de artigos com e sem diagramas causais. No entanto, o relato de avaliações quantitativas das limitações do estudo foi mais frequente entre os artigos com DAG (52% vs. 21%). Há necessidade de mais discussões e estudos sobre a construção e análise de modelos causais e o desenvolvimento de recomendações gerais para apresentação de DAG causais nos artigos científicos

[Use of causal diagrams in Epidemiology: application to a situation with confounding]. / Utilização de diagramas causais em epidemiologia: um exemplo de aplicação em situação de confusão.

Epidemiological research still rarely uses causal diagrams, despite growing recognition of their explanatory potential. One possible reason is that many research programs involve themes in which there is a certain degree of uncertainty as to mechanisms in the processes that generate the data. In this study, the relationship between occupational stress and obesity is used as an example of the application of causal diagrams to questions related to confounding. The article presents the selection stages for variables in statistical adjustment and the derivation of a causal diagram's statistical implications. The main advantage of causal diagrams is that they explicitly reveal the respective model's underlying hypotheses, allowing critical analysis of the implications and thereby facilitating identification of sources of bias and uncertainty in the epidemiological study's results.

Utilização de diagramas causais em epidemiologia: um exemplo de aplicação em situação de confusão / Use of causal diagrams in Epidemiology: application to a situation with confounding / Utilización de diagramas causales en epidemiología: un ejemplo de su aplicación en situación de confusión

Resumo: Apesar do crescente reconhecimento de seu potencial, os diagramas causais ainda são pouco utilizados na investigação epidemiológica. Uma das possíveis razões é que muitos programas de investigação envolvem temas sobre o qual há certo grau de incerteza sobre os mecanismos dos processos que geram os dados. Neste trabalho, a relação entre estresse ocupacional e obesidade é utilizada como um exemplo de aplicação de diagramas causais em questões relacionadas ao confundimento. São apresentadas etapas da seleção de variáveis para ajuste estatístico e da derivação das implicações estatísticas de um diagrama causal. A principal vantagem dos diagramas causais é tornar explícitas as hipóteses adjacentes ao modelo considerado, permitindo que suas implicações possam ser analisadas criticamente, facilitando, dessa forma, a identificação de possíveis fontes de viés e incerteza nos resultados de um estudo epidemiológico.

Abstract: Epidemiological research still rarely uses causal diagrams, despite growing recognition of their explanatory potential. One possible reason is that many research programs involve themes in which there is a certain degree of uncertainty as to mechanisms in the processes that generate the data. In this study, the relationship between occupational stress and obesity is used as an example of the application of causal diagrams to questions related to confounding. The article presents the selection stages for variables in statistical adjustment and the derivation of a causal diagram's statistical implications. The main advantage of causal diagrams is that they explicitly reveal the respective model's underlying hypotheses, allowing critical analysis of the implications and thereby facilitating identification of sources of bias and uncertainty in the epidemiological study's results.

Resumen: A pesar del creciente reconocimiento de su potencial, los diagramas causales todavía se utilizan poco en la investigación epidemiológica. Una de las posibles razones es que muchos programas de investigación están involucrados en temas sobre los cuales existe un cierto grado de incertidumbre acerca de los mecanismos de los procesos que generan los datos. En este trabajo, la relación entre estrés ocupacional y obesidad se utiliza como un ejemplo de aplicación de diagramas causales en cuestiones relacionadas con la confusión. Se presentan etapas de la selección de variables para el ajuste estadístico y de la derivación de las implicaciones estadísticas de un diagrama causal. La principal ventaja de los diagramas causales es hacer explícitas las hipótesis adyacentes al modelo considerado, permitiendo que sus implicaciones puedan ser analizadas críticamente, facilitando, de esta forma, la identificación de posibles fuentes de sesgo e incertidumbre en los resultados de un estudio epidemiológico.

Television viewing and abdominal obesity in women according to smoking status: results from a large cross-sectional population-based study in Brazil.

OBJECTIVE: To investigate the associations between television viewing and abdominal obesity (AO) in Brazilian women, according to smoking status. METHODS: Data of 13,262 adult women (18-49 years) from the 2006's Demographic Health Survey, a cross-sectional household study with complex probabilistic sample and national representativeness, were analyzed. AO, defined as waist circumference ≥ 80.0 cm, was the outcome. Television viewing frequency (≥ 5 times/week, 1-4 times/week, < 1 time/week) was the main exposure variable, and smoking status (yes or no) the main co-variable. Prevalence ratios were estimated using Poisson regression models separately for smokers and non-smokers. RESULTS: A statistically significant interaction term was observed between smoking status and television viewing (p < 0.05). Prevalence of AO among smokers who reported television viewing ≥ 5 times/week amounted to 59.0%, higher than the 35.0% for those with < 1 time/week television viewing (p-value = 0.020). The values for non-smokers were 55.2% and 55.7%, respectively. Smokers with television viewing ≥ 5 times/week were 1.7 times (95% CI: 1.1 - 2.5) more likely to pre-sent AO, compared to those who reported a frequency < 1 time/week. There was no significant association among non-smokers. CONCLUSIONS: Television viewing ≥ 5 times/week may increase the prevalence of AO among women who smoke. More detailed information on media use, as hours per day, may offer better estimates.

Television viewing and abdominal obesity in women according to smoking status: results from a large cross-sectional population-based study in Brazil / Hábito de assistir televisão e obesidade abdominal entre mulheres fumantes: resultados de um estudo transversal de base populacional no Brasil

OBJECTIVE: To investigate the associations between television viewing and abdominal obesity (AO) in Brazilian women, according to smoking status. METHODS: Data of 13,262 adult women (18-49 years) from the 2006's Demographic Health Survey, a cross-sectional household study with complex probabilistic sample and national representativeness, were analyzed. AO, defined as waist circumference ≥ 80.0 cm, was the outcome. Television viewing frequency (≥ 5 times/week, 1-4 times/week, < 1 time/week) was the main exposure variable, and smoking status (yes or no) the main co-variable. Prevalence ratios were estimated using Poisson regression models separately for smokers and non-smokers. RESULTS: A statistically significant interaction term was observed between smoking status and television viewing (p < 0.05). Prevalence of AO among smokers who reported television viewing ≥ 5 times/week amounted to 59.0%, higher than the 35.0% for those with < 1 time/week television viewing (p-value = 0.020). The values for non-smokers were 55.2% and 55.7%, respectively. Smokers with television viewing ≥ 5 times/week were 1.7 times (95% CI: 1.1 - 2.5) more likely to pre-sent AO, compared to those who reported a frequency < 1 time/week. There was no significant association among non-smokers. CONCLUSIONS: Television viewing ≥ 5 times/week may increase the prevalence of AO among women who smoke. More detailed information on media use, as hours per day, may offer better estimates. .

OBJETIVO: Investigar a associação entre a frequência assistindo televisão e obesidade abdominal (OA) entre mulheres brasileiras, segundo o hábito de fumar. MÉTODOS: Foram analisados os dados de 13.262 mulheres adultas (18-49 anos) estudadas na Pesquisa Nacional de Demografia e Saúde (PNDS-2006), um estudo transversal, com amostragem probabilística complexa, de representatividade nacional. OA, definida como circunferência da cintura ≥ 80.0 cm, foi considerada como desfecho. A frequência assistindo televisão (≥ 5 vezes/semana, 1-4 vezes/semana, < 1 vez/semana) foi a principal variável de exposição e o hábito de fumar (sim ou não) a principal covariável. Foram estimadas razões de prevalência por meio de modelos de regressão de Poisson, para fumantes e não fumantes separadamente. RESULTADOS: Observou-se interação estatisticamente significante entre frequência assistindo televisão e hábito de fumar (p < 0,05). A prevalência de OA entre mulheres fumantes que assistiam televisão ≥ 5 vezes/semana foi de 59,0%, e maior do que 35,0% entre aquelas que assistiam televisão < 1 vez/semana (p-valor = 0,02). Os valores de OA para não fumantes foram 55,2% e 55,7%, respectivamente. Fumantes que assistiam televisão ≥ 5 vezes/semana apresentaram chance 1,7 (1,1 - 2,5) vezes maior de ter OA, comparadas aquelas que relataram assistir televisão < 1 vez/semana. Não se observou associação significante para não fumantes. CONCLUSÃO: Assistir televisão ≥ 5 vezes/semana pode aumentar a prevalência de OA entre as mulheres fumantes. Informações mais detalhadas sobre a frequência de assistir televisão, como o número de horas por dia, ...

High cesarean prevalence in a national population-based study in Brazil: the role of private practice.

BACKGROUND: Excessive use of cesarean sections (CSs) is a serious problem worldwide. OBJECTIVE: To estimate the frequency and identify factors associated with cesarean deliveries in Brazil. DESIGN: Cross-sectional study conducted in 2006-2007 as part of the third edition of the Children's and Women's National Demographic and Health Survey. SETTING: Brazil. SAMPLE: Brazilian women in reproductive age. METHODS: Socioeconomic and demographic data were utilized, including maternal age, education level, per capita income, skin color, smoking habit, marital status, age at first delivery, parity, and type of prenatal services. MAIN OUTCOME MEASURES: Adjusted estimate of the prevalence ratios of the type of delivery performed (cesarean or vaginal). RESULTS: Cesarean prevalence was 43.9% (95% CI: 40.9-46.9), 68.7% for women who had per capita income greater than US$ 125 per month, and 77.2% for those who had attended private or privately insured prenatal services. In the adjusted analysis, the variables that presented significant prevalence ratios (95% confidence interval) were macro-region [southeast = 1.45 (1.21-1.73); south = 1.48 (1.24-1.77), and midwest = 1.43 (1.21-1.71)], maternal age above 25 years [26-30 years = 1.57 (1.25-1.97); > or = 31 years = 1.77 (1.39-2.27)], education levels > or = 9 years (PR = 1.86, 95% CI: 1.55-2.23), and having attended private or privately insured prenatal services (PR = 1.87, 95% CI: 1.65-2.12) and parity [primipara = 1.87 (1.47-2.36)]. CONCLUSIONS: CS rates are generally very high in Brazil. They are significantly higher than the average among women attending private/insured antenatal care, among the highly educated, and in provinces with higher socioeconomic levels.