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Randomized clinical trials (RCT) are accepted as the gold-standard approaches to measure effects of intervention or treatment on outcomes. They are also the designs of choice for health technology assessment (HTA). Randomization ensures comparability, in both measured and unmeasured pretreatment characteristics, of individuals assigned to treatment and control or comparator. However, even adequately powered RCTs are not always feasible for several reasons such as cost, time, practical and ethical constraints, and limited generalizability. RCTs rely on data collected on selected, homogeneous population under highly controlled conditions; hence, they provide evidence on efficacy of interventions rather than on effectiveness. Alternatively, observational studies can provide evidence on the relative effectiveness or safety of a health technology compared to one or more alternatives when provided under the setting of routine health care practice. In observational studies, however, treatment assignment is a non-random process based on an individual’s baseline characteristics; hence, treatment groups may not be comparable in their pretreatment characteristics. As a result, direct comparison of outcomes between treatment groups might lead to biased estimate of the treatment effect. Propensity score approaches have been used to achieve balance or comparability of treatment groups in terms of their measured pretreatment covariates thereby controlling for confounding bias in estimating treatment effects. Despite the popularity of propensity scores methods and recent important methodological advances, misunderstandings on their applications and limitations are all too common. In this article, we present a review of the propensity scores methods, extended applications, recent advances, and their strengths and limitations.

Resumo O racismo é um sistema estruturante, gerador de comportamentos, práticas, crenças e preconceitos que fundamentam desigualdades evitáveis e injustas, baseadas na raça ou etnia. Na saúde o racismo pode se manifestar de diversas formas, como o institucional, que frequentemente ocorre de forma implícita. A pandemia do coronavírus tem sido um desafio para países que apresentam profundas desigualdades. No Brasil, em que pese a ausência das informações desagregadas por raça ou etnia ou que quando coletadas apresentam um preenchimento precário, sabe-se que negras e negros irão sofrer mais severamente os impactos da pandemia e seus vários desfechos negativos. No texto recuperamos aspectos históricos e sua relação com as condições de vulnerabilidade da população negra e apresentamos uma agenda de ações específicas para o combate ao racismo e suas devastadoras consequências no contexto da Covid-19.

Health technology assessment (HTA) is the systematic evaluation of the properties and impacts of health technologies and interventions. In this article, we presented a discussion of HTA and its evolution in Brazil, as well as a description of secondary data sources available in Brazil with potential applications to generate evidence for HTA and policy decisions. Furthermore, we highlighted record linkage, ongoing record linkage initiatives in Brazil, and the main linkage tools developed and/or used in Brazilian data. Finally, we discussed the challenges and opportunities of using secondary data for research in the Brazilian context. In conclusion, we emphasized the availability of high quality data and an open, modern attitude toward the use of data for research and policy. This is supported by a rigorous but enabling legal framework that will allow the conduct of large-scale observational studies to evaluate clinical, economical, and social impacts of health technologies and social policies.

We compared Future Discounting (FD, preference for smaller, sooner rewards over larger, later ones) by 160 Brazilian youth (16–30 years old; 71 women and 89 men). University students and slum‐dwelling (favela) youth were compared. Participants completed a monetary FD task, a scale of youngsters′ view of their neighborhood, and self‐reported exposure to violence (EV). Favela youth discounted the future more than students; favela men more than women. However, university women discounted more than men, an unexpected result. Predicted differences in the participants′ view of their neighborhood between the two groups were observed. The interaction context × EV scores was a significant predictor of FD. These youth have apparently adjusted trade‐offs between the short and long term in a context‐sensitive, adaptive manner.

Background Brazil has made great progress in reducing child mortality over the past decades, and a parcel of this achievement has been credited to the Bolsa Família program (BFP). We examined the association between being a BFP beneficiary and child mortality (1–4 years of age), also examining how this association differs by maternal race/skin color, gestational age at birth (term versus preterm), municipality income level, and index of quality of BFP management. Methods and findings This is a cross-sectional analysis nested within the 100 Million Brazilian Cohort, a population-based cohort primarily built from Brazil’s Unified Registry for Social Programs (Cadastro Único). We analyzed data from 6,309,366 children under 5 years of age whose families enrolled between 2006 and 2015. Through deterministic linkage with the BFP payroll datasets, and similarity linkage with the Brazilian Mortality Information System, 4,858,253 children were identified as beneficiaries (77%) and 1,451,113 (23%) were not. Our analysis consisted of a combination of kernel matching and weighted logistic regressions. After kernel matching, 5,308,989 (84.1%) children were included in the final weighted logistic analysis, with 4,107,920 (77.4%) of those being beneficiaries and 1,201,069 (22.6%) not, with a total of 14,897 linked deaths. Overall, BFP participation was associated with a reduction in child mortality (weighted odds ratio [OR] = 0.83; 95% CI: 0.79 to 0.88; p < 0.001). This association was stronger for preterm children (weighted OR = 0.78; 95% CI: 0.68 to 0.90; p < 0.001), children of Black mothers (weighted OR = 0.74; 95% CI: 0.57 to 0.97; p < 0.001), children living in municipalities in the lowest income quintile (first quintile of municipal income: weighted OR = 0.72; 95% CI: 0.62 to 0.82; p < 0.001), and municipalities with better index of BFP management (5th quintile of the Decentralized Management Index: weighted OR = 0.76; 95% CI: 0.66 to 0.88; p < 0.001). The main limitation of our methodology is that our propensity score approach does not account for possible unmeasured confounders. Furthermore, sensitivity analysis showed that loss of nameless death records before linkage may have resulted in overestimation of the associations between BFP participation and mortality, with loss of statistical significance in municipalities with greater losses of data and change in the direction of the association in municipalities with no losses. Conclusions In this study, we observed a significant association between BFP participation and child mortality in children aged 1–4 years and found that this association was stronger for children living in municipalities in the lowest quintile of wealth, in municipalities with better index of program management, and also in preterm children and children of Black mothers. These findings reinforce the evidence that programs like BFP, already proven effective in poverty reduction, have a great potential to improve child health and survival. Subgroup analysis revealed heterogeneous results, useful for policy improvement and better targeting of BFP.

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This report describes the development of the BrazDep small-area deprivation measure for the whole of Brazil. The measure uses the 2010 Brazilian Population Census data and is calculated for the smallest possible geographical area level, the census sectors. It combines three variables – (1) percent of households with per capita income ≤ 1/2 minimum wage; (2) percent of people not literate, aged 7+; and (3) average of percent of people with inadequate access to sewage, water, garbage collection and no toilet and bath/shower – into a single measure. Similar measures have previously been developed at the census sector level for some states or municipalities, but the deprivation measure described in this report is the first one to be provided for census sectors for the whole of Brazil. BrazDep is a measure of relative deprivation, placing the census sectors on a scale of material well-being from the least to the most deprived. It is useful in comparing areas within Brazil in 2010, but cannot be used to make comparisons across countries or time. Categorical versions of the measure are also provided, placing census sectors into groups of similar levels of deprivation. Deprivation measures, such as the one developed here, have been developed for many countries and are popular tools in public health research for describing the social patterning of health outcomes and supporting the targeting and delivery of services to areas of higher need. The deprivation measure is exponentially distributed, with a large proportion of areas having a low deprivation score and a smaller number of areas experiencing very high deprivation. There is significant regional variation in deprivation; areas in the North and Northeast of Brazil have on average much higher deprivation compared to the South and Southeast. Deprivation levels in the Central-West region fall between those for the North and South. Differences are also great between urban and rural areas, with the former having lower levels of deprivation compared to the latter. The measure was validated by comparing it to other similar indices measuring health and social vulnerability at the census sector level in states and municipalities where it was possible, and at the municipal level for across the whole of Brazil. At the municipal level the deprivation measure was also compared to health outcomes. The different validation exercises showed that the developed measure produced expected results and could be considered validated. As the measure is an estimate of the “true” deprivation in Brazil, uncertainty exists about the exact level of deprivation for all of the areas. For the majority of census sectors the uncertainty is small enough that we can reliably place the area into a deprivation category. However, for some areas uncertainty is very high and the provided estimate is unreliable. These considerations should always be kept in mind when using the BrazDep measure in research or policy. The measure should be used as part of a toolkit, rather than a single basis for decision-making. The data together with documentation is available from the University of Glasgow http: //dx.doi.org/10.5525/gla.researchdata.980. The data and this report are distributed under Creative Commons Share-Alike license (CC BY-SA 4.0) and can be freely used by researchers, policy makers or members of public.