Smoking prevalence and economic crisis in Brazil

OBJECTIVE: To estimate the impact of the 2015–2018 economic crisis on tobacco consumption in Brazil. METHODS: This is an interrupted time series analysis conducted with data from 27 cities collected by VIGITEL, using linear regression models to account for first-order autocorrelation. Analyses were conducted based on gender, age group, and education level. RESULTS: Smoking rates decreased between 2006 and 2018, decelerating after the crisis onset. Differently than women, men showed an immediate but transient increase in smoking, followed by a decelerated decrease. Those over 65 also showed increased smoking rates immediately after the economic crisis onset, but decline accelerated later on. In turn, we found a trend reversal among those aged 31–44. Rates also decreased among those with lower education levels, but decelerated among those with more years of schooling. CONCLUSION: An economic crisis have varied impacts on the smoking habits of different population groups. Tobacco control policies should entail a detailed understanding of smoking epidemiology, especially during an economic crisis. DESCRIPTORS: Tobacco Use Disorder, epidemiology. Poverty. Health Impact Assessment. Financial Managemen

Projecting the impact of air pollution on child stunting in India—synergies and trade-offs between climate change mitigation, ambient air quality control, and clean cooking access

Many children in India face the double burden of high exposure to ambient (AAP) and household air pollution, both of which can affect their linear growth. Although climate change mitigation is expected to decrease AAP, climate policies could increase the cost of clean cooking fuels. Here, we develop a static microsimulation model to project the air pollution-related burden of child stunting in India up to 2050 under four scenarios combining climate change mitigation (2 °C target) with national policies for AAP control and subsidised access to clean cooking. We link data from a nationally representative household survey, satellite-based estimates of fine particulate matter (PM2.5), a multi-dimensional demographic projection and PM2.5 and clean cooking access projections from an integrated assessment model. We find that the positive effects on child linear growth from reductions in AAP under the 2 °C Paris Agreement target could be fully offset by the negative effects of climate change mitigation through reduced clean cooking access. Targeted AAP control or subsidised access to clean cooking could shift this trade-off to result in net benefits of 2.8 (95% uncertainty interval [UI]: 1.4, 4.2) or 6.5 (UI: 6.3, 6.9) million cumulative prevented cases of child stunting between 2020–50 compared to business-as-usual. Implementation of integrated climate, air quality, and energy access interventions has a synergistic impact, reducing cumulative number of stunted children by 12.1 (UI: 10.7, 13.7) million compared to business-as-usual, with the largest health benefits experienced by the most disadvantaged children and geographic regions. Findings underscore the importance of complementing climate change mitigation efforts with targeted air quality and energy access policies to concurrently deliver on carbon mitigation, health and air pollution and energy poverty reduction goals in India

Otherness, human biology, and biomedicine

This article analyzes processes of "othering" in human biology and biomedicine. Othering is understood here as the cultural process of production of otherness by means of the delimitation, tagging, and categorization of the possible ways of being "other" within a given socio-historical context. Although othering can be considered as a constitutive aspect of any process of delimitation of identities within a given culture - and in this sense it can present both positive and negative views of the "other" -, in the present article we are specifically interested in processes of othering that lead to the marginalization and social exclusion of different human groups. We will analyze processes of othering, which have operated in the discourses and practices of biomedical sciences throughout their recent history, that have led to the social exclusion of different categories of "others", or to treating them as inferior, and that have supposedly scientific bases or as a consequence of the institutionalization of certain practices within the scientific community. Typical examples of these "others", marginalized by the Western sciences throughout their history, are the non-European "races", women, gay and lesbian people, and the "poor". The main objective of this article is to analyze, in the recent history of the biomedical technosciences, these different processes of othering that have led to the marginalization of such "others" and to treating them as inferior.O presente artigo analisa processos de alterização na biologia humana e na biomedicina. A alterização é entendida aqui como o processo cultural de produção de alteridades por meio da delimitação, rotulação e categorização das formas possíveis de ser outro, desde um determinado marco de referência sócio-histórico. Ainda que a alterização faça parte de qualquer processo de delimitação de categorias de identidade no seio de uma cultura - e, nesse sentido, possa apresentar visões do outro tanto positivas quanto negativas -, aqui nos interessamos especificamente na alterização como fator de marginalização e exclusão social de diferentes grupos humanos. São analisados diversos processos de alterização operantes nos discursos e nas práticas das ciências biomédicas ao longo de sua história recente, os quais têm conduzido à exclusão social de diferentes categorias de outros, ou a tratá-los como inferiores, em pretendidas bases científicas, ou em função de determinadas práticas institucionalizadas dentro da comunidade científica. Exemplos típicos de grupos marginalizados pelas ciências ocidentais ao longo de sua história incluem as raças não europeias, as mulheres, os homossexuais e os "pobres". O principal objetivo do presente artigo é analisar, na história recente das ciências biomédicas, esses processos de alterização que têm conduzido à marginalização de tais grupos e a considerá-los como inferiores

a cross-sectional analysis of 1.2 million low-income individuals in Rio de Janeiro, Brazil 2010–2016

Funding Information: Funding This study was supported by the UK’s Joint Health Systems Research Initiative (DFID/MRC/Wellcome Trust/ESRC) grant number MR/P014593/1 and NIHR (NIHR133252 and NIHR150067) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the authors and not necessarily those of the NIHR or the UK Department of Health and Social Care. The funders had no role in the study design, in the collection, analysis and interpretation of data, in the writing of the report, or in the decision to submit the paper for publication. Funding Information: This study was supported by the UK’s Joint Health Systems Research Initiative (DFID/MRC/Wellcome Trust/ESRC) grant number MR/P014593/1 and NIHR (NIHR133252 and NIHR150067) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the authors and not necessarily those of the NIHR or the UK Department of Health and Social Care. The funders had no role in the study design, in the collection, analysis and interpretation of data, in the writing of the report, or in the decision to submit the paper for publication. Publisher Copyright: © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY.Introduction Mental health inequalities across racial and ethnic groups are large and unjust in many countries, yet these inequalities remain under-researched, particularly in low-income and middle-income countries such as Brazil. This study investigates racial and socioeconomic inequalities in primary healthcare usage, hospitalisation and mortality for mental health disorders in Rio de Janeiro, Brazil. Methods A cohort of 1.2 million low-income adults from Rio de Janeiro, Brazil with linked socioeconomic, demographic, healthcare use and mortality records was cross-sectionally analysed. Poisson regression models were used to investigate associations between self-defined race/colour and primary healthcare (PHC) usage, hospitalisation and mortality due to mental disorders, adjusting for socioeconomic factors. Interactions between race/colour and socioeconomic characteristics (sex, education level, income) explored if black and pardo (mixed race) individuals faced compounded risk of adverse mental health outcomes. Results There were 272 532 PHC consultations, 10 970 hospitalisations and 259 deaths due to mental disorders between 2010 and 2016. After adjusting for a wide range of socioeconomic factors, the lowest PHC usage rates were observed in black (adjusted rate ratio (ARR): 0.64; 95% CI 0.60 to 0.68; compared with white) and pardo individuals (ARR: 0.87; 95% CI 0.83 to 0.92). Black individuals were more likely to die from mental disorders (ARR: 1.68; 95% CI 1.19 to 2.37; compared with white), as were those with lower educational attainment and household income. In interaction models, being black or pardo conferred additional disadvantage across mental health outcomes. The highest educated black (ARR: 0.56; 95% CI 0.47 to 0.66) and pardo (ARR: 0.75; 95% CI 0.66 to 0.87) individuals had lower rates of PHC usage for mental disorders compared with the least educated white individuals. Black individuals were 3.7 times (ARR: 3.67; 95% CI 1.29 to 10.42) more likely to die from mental disorders compared with white individuals with the same education level. Conclusion In low-income individuals in Rio de Janeiro, racial/colour inequalities in mental health outcomes were large and not fully explainable by socioeconomic status. Black and pardo Brazilians were consistently negatively affected, with lower PHC usage and worse mental health outcomes.publishersversionpublishe

A Spark-based workflow for probabilistic record linkage of healthcare data *

ABSTRACT Several areas, such as science, economics, finance, business intelligence, health, and others are exploring big data as a way to produce new information, make better decisions, and move forward their related technologies and systems. Specifically in health, big data represents a challenging problem due to the poor quality of data in some circumstances and the need to retrieve, aggregate, and process a huge amount of data from disparate databases. In this work, we focused on Brazilian Public Health System and on large databases from Ministry of Health and Ministry of Social Development and Hunger Alleviation. We present our Spark-based approach to data processing and probabilistic record linkage of such databases in order to produce very accurate data marts. These data marts are used by statisticians and epidemiologists to assess the effectiveness of conditional cash transfer programs to poor families in respect with the occurrence of some diseases (tuberculosis, leprosy, and AIDS). The case study we made as a proof-of-concept presents a good performance with accurate results. For comparison, we also discuss an OpenMP-based implementation

Impact of the New Mental Health Services on Rates of Suicide and Hospitalisations by Attempted Suicide, Psychiatric Problems, and Alcohol Problems in Brazil.

A sizeable proportion of all suicides have mental health issues in the background. The association between access to mental health care in the community and decreased suicide rates is inconsistent in the literature. Brazil undertook a major psychiatric reform strengthening psychiatric community-based care. To evaluate the impact of the new Brazilian community mental health care units (CAPS-Psychosocial-Community-Centres) on municipal rates of suicide, and hospitalisations by attempted suicide, psychiatric and alcohol problems. We performed robust multivariable negative binomial regression models with fixed effect for panel data from all 5507 Brazilian municipalities. Suicide and hospitalization rates were calculated by sex and standardised by age for each municipality and year from 2008 to 2012. The main variable of interest was municipal CAPS coverage. CAPS municipal coverage was associated with lower suicide rates but this was not statistically significant (RR: 0.981; 95% CI 0.952-1.011). However, increased CAPS coverage was associated with lower hospitalizations for attempted suicide (RR: 0.887; 95% CI 0.841-0.935), psychiatric (RR: 0.841; 95% CI 0.821-0.862), and alcohol problems (RR: 0.882; 95% CI 0.860-0.904). Our results suggest that access to community mental health services seems to reduce hospitalisations due to attempted suicide, psychiatric and alcohol problems but not suicidal rates. Therefore, increased investments in community mental health services in low-middle-income countries might decrease costs associated with potentially avoidable hospitalizations

Developing an integrated microsimulation model for the impact of fiscal policies on child health in Europe: the example of childhood obesity in Italy.

Background We developed an integrated model called Microsimulation for Income and Child Health (MICH) that provides a tool for analysing the prospective effects of fiscal policies on childhood health in European countries. The aim of this first MICH study is to evaluate the impact of alternative fiscal policies on childhood overweight and obesity in Italy. Methods MICH model is composed of three integrated modules. Firstly, module 1 (M1) simulates the effects of fiscal policies on disposable household income using the tax-benefit microsimulation program EUROMOD fed with the Italian EU-SILC 2010 data. Secondly, module 2 (M2) exploits data provided by the Italian birth cohort called Nascita e Infanzia: gli Effetti dell'Ambiente (NINFEA), translated as Birth and Childhood: the Effects of the Environment study, and runs a series of concatenated regressions in order to estimate the prospective effects of income on child body mass index (BMI) at different ages. Finally, module 3 (M3) uses dynamic microsimulation techniques that combine the population structure and incomes obtained by M1, with regression model specifications and estimated effect sizes provided by M2, projecting BMI distributions according to the simulated policy scenarios. Results Both universal benefits, such as universal basic income (BI), and targeted interventions, such as child benefit (CB) for poorer households, have a significant effect on childhood overweight, with a prevalence ratio (PR) in 10-year-old children-in comparison with the baseline fiscal system-of 0.88 (95%CI 0.82-0.93) and 0.89 (95%CI 0.83-0.94), respectively. The impact of the fiscal reforms was even larger for child obesity, reaching a PR of 0.67 (95%CI 0·50-0.83) for the simulated BI and 0.64 (95%CI 0.44-0.84) for CB at the same age. While both types of policies show similar effects, the estimated costs for a 1% prevalence reduction in overweight and obesity with respect to the baseline scenario is much lower with a more focalised benefit policy than with universal ones. Conclusions Our results show that fiscal policies can have a strong impact on childhood health conditions. Focalised interventions that increase family income, especially in the most vulnerable populations, can help to prevent child overweight and obesity. Robust microsimulation models to forecast the effects of fiscal policies on health should be considered as one of the instruments to reach the Health in All Policies (HiAP) goals

The potential impact of austerity on attainment of the Sustainable Development Goals in Brazil

In the recent decades, Brazil has outperformed comparable countries in its progress toward meeting the Millennium Development Goals. Many of these improvements have been driven by investments in health and social policies. In this article, we aim to identify potential impacts of austerity policies in Brazil on the chances of achieving the sustainable development goals (SDGs) and its consequences for population health. Austerity’s anticipated impacts are assessed by analysing the change in federal spending on different budget programmes from 2014 to 2017. We collected budget data made publicly available by the Senate. Among the selected 19 programmes, only 4 had their committed budgets increased, in real terms, between 2014 and 2017. The total amount of extra money committed to these four programmes in 2017, above that committed in 2014, was small (BR$9.7 billion). Of the 15 programmes that had budget cuts in the period from 2014 to 2017, the total decrease amounted to BR$60.2 billion (US$15.3 billion). In addition to the overall large budget reduction, it is noteworthy that the largest proportional reductions were in programmes targeted at more vulnerable populations. In conclusion, it seems clear that the current austerity policies in Brazil will probably damage the population’s health and increase inequities, and that the possibility of meeting SDG targets is lower in 2018 than it was in 2015

Long-term impact of a conditional cash transfer programme on maternal mortality: a nationwide analysis of Brazilian longitudinal data.

BACKGROUND: Reducing poverty and improving access to health care are two of the most effective actions to decrease maternal mortality, and conditional cash transfer (CCT) programmes act on both. The aim of this study was to evaluate the effects of one of the world's largest CCT (the Brazilian Bolsa Familia Programme (BFP)) on maternal mortality during a period of 11 years. METHODS: The study had an ecological longitudinal design and used all 2548 Brazilian municipalities with vital statistics of adequate quality during 2004-2014. BFP municipal coverage was classified into four levels, from low to consolidated, and its duration effects were measured using the average municipal coverage of previous years. We used negative binomial multivariable regression models with fixed-effects specifications, adjusted for all relevant demographic, socioeconomic, and healthcare variables. RESULTS: BFP was significantly associated with reductions of maternal mortality proportionally to its levels of coverage and years of implementation, with a rate ratio (RR) reaching 0.88 (95%CI 0.81-0.95), 0.84 (0.75-0.96) and 0.83 (0.71-0.99) for intermediate, high and consolidated BFP coverage over the previous 11 years. The BFP duration effect was stronger among young mothers (RR 0.77; 95%CI 0.67-0.96). BFP was also associated with reductions in the proportion of pregnant women with no prenatal visits (RR 0.73; 95%CI 0.69-0.77), reductions in hospital case-fatality rate for delivery (RR 0.78; 95%CI 0.66-0.94) and increases in the proportion of deliveries in hospital (RR 1.05; 95%CI 1.04-1.07). CONCLUSION: Our findings show that a consolidated and durable CCT coverage could decrease maternal mortality, and these long-term effects are stronger among poor mothers exposed to CCT during their childhood and adolescence, suggesting a CCT inter-generational effect. Sustained CCT coverage could reduce health inequalities and contribute to the achievement of the Sustainable Development Goal 3.1, and should be preserved during the current global economic crisis due to the COVID-19 pandemic