ABSTRACT OBJECTIVE To evaluate the quality of information on gestational syphilis (GS) and congenital syphilis (CS) on the Sistema de Informação de Agravos de Notificação (SINAN-Syphilis Brazil – Notifiable Diseases Information System) by compiling and validating completeness indicators between 2007 and 2018. METHODS Overall, care, and socioeconomic completeness scores were compiled based on selected variables, by using ad hoc weights assigned by experts. The completeness scores were analysed, considering the region and area of residence, the pregnant woman’s race/colour, and the year of case notification. Pearson’s correlation coefficients were used to validate the scores obtained by the weighted average method, compared with the values obtained by principal component analysis (PCA). RESULTS Most selected variables presented a good or excellent degree of completeness for GS and CS, except for clinical classification, pregnant woman’s level of education, partner’s treatment, and child’s race/colour, which were classified as poor or very poor. The overall (89.93% versus 89.69%) and socioeconomic (88.71% versus 88.24%) completeness scores for GS and CS, respectively, were classified as regular, whereas the care score (GS-90.88%, and CS-90.72%) was good, despite improvements over time. Differences in the overall, care and socioeconomic completeness scores according to region, area of residence, and ethnic-racial groups were reported for syphilis notifications. The completeness scores estimated by the weighted average method and PCA showed a strong linear correlation (> 0.90). CONCLUSION The completeness of GS and CS notifications has been improving in recent years, highlighting the variables that form the care score, compared with the socioeconomic scores, despite differences between regions, area of residence, and ethnic-racial groups. The weighted average was a viable methodological alternative easily operationalised to estimate data completeness scores, allowing routine monitoring of the completeness of gestational and congenital syphilis records.

Abstract 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.

ABSTRACT OBJECTIVE To evaluate the quality of information on gestational syphilis (GS) and congenital syphilis (CS) on the Sistema de Informação de Agravos de Notificação (SINAN-Syphilis Brazil – Notifiable Diseases Information System) by compiling and validating completeness indicators between 2007 and 2018. METHODS Overall, care, and socioeconomic completeness scores were compiled based on selected variables, by using ad hoc weights assigned by experts. The completeness scores were analysed, considering the region and area of residence, the pregnant woman’s race/colour, and the year of case notification. Pearson’s correlation coefficients were used to validate the scores obtained by the weighted average method, compared with the values obtained by principal component analysis (PCA). RESULTS Most selected variables presented a good or excellent degree of completeness for GS and CS, except for clinical classification, pregnant woman’s level of education, partner’s treatment, and child’s race/colour, which were classified as poor or very poor. The overall (89.93% versus 89.69%) and socioeconomic (88.71% versus 88.24%) completeness scores for GS and CS, respectively, were classified as regular, whereas the care score (GS-90.88%, and CS-90.72%) was good, despite improvements over time. Differences in the overall, care and socioeconomic completeness scores according to region, area of residence, and ethnic-racial groups were reported for syphilis notifications. The completeness scores estimated by the weighted average method and PCA showed a strong linear correlation (> 0.90). CONCLUSION The completeness of GS and CS notifications has been improving in recent years, highlighting the variables that form the care score, compared with the socioeconomic scores, despite differences between regions, area of residence, and ethnic-racial groups. The weighted average was a viable methodological alternative easily operationalised to estimate data completeness scores, allowing routine monitoring of the completeness of gestational and congenital syphilis records.

Objective: To analyze the prevalence of common mental disorders (CMD) assessed with the Self Reporting Questionnaire (SRQ-20), using the established cutoff point, and comparing it with the results of a joint correspondence factor analysis (CFA) and cluster analysis and of a latent class analysis (LCA). Methods: A cross-sectional study was carried out in an urban sample of 1,095 women aged 19 to 55 years. Joint CFA-cluster analysis and LCA were used. Results: We found a high prevalence of CMD, regardless of classification method (37.6% when using the cutoff point; 44.4% and 52% for LCA and joint CFA-cluster, respectively). The alternative analysis strategies describe the cases more efficiently when compared to the traditional cutoff method, especially regarding more severe symptoms. Both alternative strategies also provide a description of the SRQ-20 dimensions in their particularities, which may be useful for the planning and implementation of specific actions in a given population. Conclusion: The SRQ-20 cutoff point seems to underestimate the magnitude of CMD among women. The alternative methods of analysis presented herein highlight the different possibilities of using this important instrument of screening for mental health.

A modelagem de equações estruturais (MEE) é uma ferramenta estatística importante para avaliar relações complexas em várias áreas do conhecimento. Em Epidemiologia sua divulgação e uso são limitados. Este artigo apresenta princípios e conceitos básicos da MEE, com exemplo de aplicação na análise de dados epidemiológicos. A análise de dados é realizada em estudo que investiga determinantes do desenvolvimento cognitivo infantil, sendo definidos construtos relacionados à organização do ambiente da criança, ao seu status de saúde, e às práticas e estilo de vida dos pais. O impacto positivo da qualidade de estimulação psicossocial do ambiente doméstico sobre o índice de desempenho cognitivo (IDC) esclarece que parte do efeito da estimulação sobre o IDC deve-se ao estilo parental de interação com a criança e às características físico-ambientais do contexto familiar. As potencialidades do uso da MEE em Epidemiologia são apresentadas, enfatizando-se a definição do modelo teórico e seu uso para aprofundamento de questões epidemiológicas sob nova perspectiva.

Structural equation modeling (SEM) is an important statistical tool for evaluating complex relations in several research areas. In epidemiology, the use and discussion of SEM have been limited thus far. This article presents basic principles and concepts in SEM, including an application using epidemiological data analysis from a study on the determinants of cognitive development in young children, considering constructs related to organization of the child's home environment, parenting style, and the child's health status. The relations between the constructs and cognitive development were measured. The results showed a positive association between psychosocial stimulus at home and cognitive development in young children. The article presents the contributions by SEM to epidemiology, highlighting the need for an a priori theoretical model for improving the study of epidemiological questions from a new perspective.

A modelagem de equações estruturais (MEE) é uma ferramenta estatística importante para avaliar relações complexas em várias áreas do conhecimento. Em Epidemiologia sua divulgação e uso são limitados. Este artigo apresenta princípios e conceitos básicos da MEE, com exemplo de aplicação na análise de dados epidemiológicos. A análise de dados é realizada em estudo que investiga determinantes do desenvolvimento cognitivo infantil, sendo definidos construtos relacionados à organização do ambiente da criança, ao seu status de saúde, e às práticas e estilo de vida dos pais. O impacto positivo da qualidade de estimulação psicossocial do ambiente doméstico sobre o índice de desempenho cognitivo (IDC) esclarece que parte do efeito da estimulação sobre o IDC deve-se ao estilo parental de interação com a criança e às características físico-ambientais do contexto familiar. As potencialidades do uso da MEE em Epidemiologia são apresentadas, enfatizando-se a definição do modelo teórico e seu uso para aprofundamento de questões epidemiológicas sob nova perspectiva.

Structural equation modeling (SEM) is an important statistical tool for evaluating complex relations in several research areas. In epidemiology, the use and discussion of SEM have been limited thus far. This article presents basic principles and concepts in SEM, including an application using epidemiological data analysis from a study on the determinants of cognitive development in young children, considering constructs related to organization of the child's home environment, parenting style, and the child's health status. The relations between the constructs and cognitive development were measured. The results showed a positive association between psychosocial stimulus at home and cognitive development in young children. The article presents the contributions by SEM to epidemiology, highlighting the need for an a priori theoretical model for improving the study of epidemiological questions from a new perspective.