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.
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.
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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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
Record linkage is the process of identifying and combining records about the same individual from two or more different datasets. While there are many open source and commercial data linkage tools, ...the volume and complexity of currently available datasets for linkage pose a huge challenge; hence, designing an efficient linkage tool with reasonable accuracy and scalability is required.
We developed CIDACS-RL (Centre for Data and Knowledge Integration for Health - Record Linkage), a novel iterative deterministic record linkage algorithm based on a combination of indexing search and scoring algorithms (provided by Apache Lucene). We described how the algorithm works and compared its performance with four open source linkage tools (AtyImo, Febrl, FRIL and RecLink) in terms of sensitivity and positive predictive value using gold standard dataset. We also evaluated its accuracy and scalability using a case-study and its scalability and execution time using a simulated cohort in serial (single core) and multi-core (eight core) computation settings.
Overall, CIDACS-RL algorithm had a superior performance: positive predictive value (99.93% versus AtyImo 99.30%, RecLink 99.5%, Febrl 98.86%, and FRIL 96.17%) and sensitivity (99.87% versus AtyImo 98.91%, RecLink 73.75%, Febrl 90.58%, and FRIL 74.66%). In the case study, using a ROC curve to choose the most appropriate cut-off value (0.896), the obtained metrics were: sensitivity = 92.5% (95% CI 92.07-92.99), specificity = 93.5% (95% CI 93.08-93.8) and area under the curve (AUC) = 97% (95% CI 96.97-97.35). The multi-core computation was about four times faster (150 seconds) than the serial setting (550 seconds) when using a dataset of 20 million records.
CIDACS-RL algorithm is an innovative linkage tool for huge datasets, with higher accuracy, improved scalability, and substantially shorter execution time compared to other existing linkage tools. In addition, CIDACS-RL can be deployed on standard computers without the need for high-speed processors and distributed infrastructures.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
To assess the sociodemographic factors associated with the double burden of malnutrition (DBM) among Brazilian adolescents.
This was a descriptive study based on data from 59,637 and 10,770 students ...who participated in the National Adolescent School-Based Health Survey (PeNSE), 2009 and 2015 editions, respectively. Weight and height measurements were obtained to evaluate nutritional status. DBM was classified as follows: adolescents with high BMI-for-age and low height-for-age (BMI/A: Z-score > +1 and H/A: Z-score < -2). Sociodemographic data on the participants were also collected. A multinomial logistic regression analysis was used to detect associations of interest.
The prevalence of DBM in the 2009 and 2015 editions of the PeNSE was 0.4% and 0.3%, respectively. In the 2009 edition, the chance of DBM was lower among boys (OR = 0.60; 95% CI = 0.45-0.81) and higher among those over 14 years old (OR = 2.40; 95% CI = 1.80-3.20), living in the country's north and northeast regions (OR = 2.01; 95% CI = 1.49-2.84), and from families with a low maternal education level (OR = 1.48; 95% CI = 1.07-2.04). In the 2015 edition, no significant associations were found regarding the DBM outcome.
The results indicate the presence of socioeconomic inequalities in the occurrence of DBM in the 2009 edition of the PeNSE. Simultaneous interventions in the area of equity are necessary to prevent the advancement of nutrition-related problems.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Poisson distribution is a popular discrete model used to describe counting information, from which traditional control charts involving count data, such as the c and u charts, have been established ...in the literature. However, several studies recognize the need for alternative control charts that allow for data overdispersion, which can be encountered in many fields, including ecology, healthcare, industry, and others. The Bell distribution, recently proposed by Castellares et al. (2018), is a particular solution of a multiple Poisson process able to accommodate overdispersed data. It can be used as an alternative to the usual Poisson (which, although not nested in the Bell family, is approached for small values of the Bell distribution) Poisson, negative binomial, and COM-Poisson distributions for modeling count data in several areas. In this paper, we consider the Bell distribution to introduce two new exciting, and useful statistical control charts for counting processes, which are capable of monitoring count data with overdispersion. The performance of the so-called Bell charts, namely Bell-c and Bell-u charts, is evaluated by the average run length in numerical simulation. Some artificial and real data sets are used to illustrate the applicability of the proposed control charts.
Indirect financial costs and barriers to health-care access might contribute to leprosy treatment non-adherence. We estimated the association of the Brazilian conditional cash transfer programme, the ...Programa Bolsa Família (PBF), on leprosy treatment adherence and cure in patients in Brazil.
In this quasi-experimental study, we linked baseline demographic and socioeconomic information for individuals who entered the 100 Million Brazilian Cohort between Jan 1, 2007, and Dec 31, 2014, with the PBF payroll database and the Information System for Notifiable Diseases, which includes nationwide leprosy registries. Individuals were eligible for inclusion if they had a household member older than 15 years and had not received PBF aid or been diagnosed with leprosy before entering the 100 Million Brazilian Cohort; they were excluded if they were partial receivers of PBF benefits, had missing data, or had a monthly per-capita income greater than BRL200 (US$50). Individuals who were PBF beneficiaries before leprosy diagnosis were matched to those who were not beneficiaries through propensity-score matching (1:1) with replacement on the basis of baseline covariates, including sex, age, race or ethnicity, education, work, income, place of residence, and household characteristics. We used logistic regression to assess the average treatment effect on the treated of receipt of PBF benefits on leprosy treatment adherence (six or more multidrug therapy doses for paucibacillary cases or 12 or more doses for multibacillary cases) and cure in individuals of all ages. We stratified our analysis according to operational disease classification (paucibacillary or multibacillary). We also did a subgroup analysis of paediatric leprosy restricted to children aged up to 15 years.
We included 11 456 new leprosy cases, of whom 8750 (76·3%) had received PBF before diagnosis and 2706 (23·6%) had not. Overall, 9508 (83·0%) patients adhered to treatment and 10 077 (88·0%) were cured. After propensity score matching, receiving PBF before diagnosis was associated with adherence to treatment (OR 1·22, 95% CI 1·01–1·48) and cure (1·26, 1·01–1·58). PBF receipt did not significantly improve treatment adherence (1·37, 0·98–1·91) or cure (1·12, 0·75–1·67) in patients with paucibacillary leprosy. For patients with multibacillary disease, PBF beneficiaries had better treatment adherence (1·37, 1·08–1·74) and cure (1·43, 1·09–1·90) than non-beneficiaries. In the propensity score-matched analysis in 2654 children younger than 15 years with leprosy, PBF exposure was not associated with leprosy treatment adherence (1·55, 0·89–2·68) or cure (1·57, 0·83–2·97).
Our results suggest that being a beneficiary of the PBF, which facilitates cash transfers and improved access to health care, is associated with greater leprosy multidrug therapy adherence and cure in multibacillary cases. These results are especially relevant for patients with multibacillary disease, who are treated for a longer period and have lower cure rates than those with paucibacillary disease.
CONFAP/ESRC/MRC/BBSRC/CNPq/FAPDF–Doenças Negligenciadas, the UK Medical Research Council, the Wellcome Trust, and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior–Brazil (CAPES).
Preterm, low-birth weight (LBW) and small-for-gestational age (SGA) newborns have a higher frequency of adverse health outcomes, including linear and ponderal growth impairment.
To describe the ...growth trajectories and to estimate catch-up growth during the first 5 y of life of small newborns according to 3 vulnerability phenotypes (preterm, LBW, SGA).
Longitudinal study using linked data from the 100 Million Brazilian Cohort baseline, the Brazilian National Live Birth System (SINASC), and the Food and Nutrition Surveillance System (SISVAN) from 2011 to 2017. We estimated the length/height-for-age (L/HAZ) and weight-for-age z-score (WAZ) trajectories from children of 6-59 mo using the linear mixed model for each vulnerable newborn phenotype. Growth velocity for both L/HAZ and WAZ was calculated considering the change (Δ) in the mean z-score between 2 time points. Catch-up growth was defined as a change in z-score > 0.67 at any time during follow-up.
We analyzed 2,021,998 live born children and 8,726,599 observations. The prevalence of at least one of the vulnerable phenotypes was 16.7% and 0.6% were simultaneously preterm, LBW, and SGA. For those born at term, all phenotypes had a period of growth recovery from 12 mo. For preterm infants, the onset of L/HAZ growth recovery started later at 24 mo and the growth trajectories appear to be lower than those born at term, a condition aggravated among children with the 3 phenotypes. Preterm and female infants seem to experience slower growth recovery than those born at term and males. The catch-up growth occurs at 24-59 mo for males preterm: preterm + AGA + NBW (Δ = 0.80), preterm + AGA + LBW (Δ = 0.88), and preterm + SGA + LBW (Δ = 1.08); and among females: term + SGA + NBW (Δ = 0.69), term + AGA + LBW (Δ = 0.72), term + SGA + LBW (Δ = 0.77), preterm + AGA + LBW (Δ = 0.68), and preterm + SGA + LBW (Δ = 0.83).
Children born preterm seem to reach L/HAZ and WAZ growth trajectories lower than those attained by children born at term, a condition aggravated among the most vulnerable.
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.
Evidence points to diverse risk factors associated with small- (SGA) and large-for-gestational-age (LGA) births. A more comprehensive understanding of these factors is imperative, especially in ...vulnerable populations.
To estimate the occurrence of and sociodemographic factors associated with SGA and LGA births in poor and extremely poor populations of Brazil.
The study population consisted of women of reproductive age (14–49 y), whose last child was born between 2012 and 2015. INTERGROWTH 21st consortium criteria were used to classify weight for gestational age according to sex. Multinomial logistic regression modeling was performed to investigate associations of interest.
Of 5,521,517 live births analyzed, SGA and LGA corresponded to 7.8% and 17.1%, respectively. Multivariate analysis revealed greater odds of SGA in children born to women who self-reported as black (OR: 1.21; 95% CI: 1.19, 1.22), mixed-race (parda) (OR: 1.08; 95% CI: 1.07, 1.09), or indigenous (OR: 1.11; 95% CI: 1.06, 1.15), were unmarried (OR: 1.08; 95% CI: 1.07, 1.08), illiterate (OR: 1.47; 95% CI: 1.42, 1.52), did not receive prenatal care (OR: 1.57; 95% CI: 1.53, 1.60), or were aged 14–20 y (OR: 1.21; 95% CI: 1.20, 1.22) or 35–49 y (OR: 1.12; 95% CI: 1.10, 1.13). Considering LGA children, higher odds were found in infants born to women living in households with ≥3 inadequate housing conditions (OR: 1.11; 95% CI: 1.10, 1.12), in indigenous women (OR: 1.22; 95% CI: 1.19, 1.25), those who had 1–3 y of schooling (OR: 1.18; 95% CI: 1.17, 1.19), 1–3 prenatal visits (OR: 1.16; CI 95%: 1.14, 1.17), or were older (OR: 1.26; 95% CI: 1.25, 1.27).
In poorer Brazilian populations, socioeconomic, racial, and maternal characteristics are consistently associated with the occurrence of SGA births, but remain less clearly linked to the occurrence of LGA births.
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