Prediction of absenteeism in public schools teachers with machine learning

OBJECTIVE To predict the risk of absence from work due to morbidities of teachers working in early childhood education in the municipal public schools, using machine learning algorithms. METHODS This is a cross-sectional study using secondary, public and anonymous data from the Relação Anual de Informações Sociais, selecting early childhood education teachers who worked in the municipal public schools of the state of São Paulo between 2014 and 2018 (n = 174,294). Data on the average number of students per class and number of inhabitants in the municipality were also linked. The data were separated into training and testing, using records from 2014 to 2016 (n = 103,357) to train five predictive models, and data from 2017 to 2018 (n = 70,937) to test their performance in new data. The predictive performance of the algorithms was evaluated using the value of the area under the ROC curve (AUROC). RESULTS All five algorithms tested showed an area under the curve above 0.76. The algorithm with the best predictive performance (artificial neural networks) achieved 0.79 of area under the curve, with accuracy of 71.52%, sensitivity of 72.86%, specificity of 70.52%, and kappa of 0.427 in the test data. CONCLUSION It is possible to predict cases of sickness absence in teachers of public schools with machine learning using public data. The best algorithm showed a better result of the area under the curve when compared with the reference model (logistic regression). The algorithms can contribute to more assertive predictions in the public health and worker health areas, allowing to monitor and help prevent the absence of these workers due to morbidity.OBJETIVO Predizer o risco de ausência laboral decorrente de morbidades dos docentes que atuam na educação infantil na rede pública municipal, com o uso de algoritmos de machine learning. MÉTODOS Trata-se de um estudo transversal utilizando dados secundários, públicos e anônimos da Relação Anual de Informações Sociais, selecionando professores da educação infantil que atuaram na rede pública municipal do estado de São Paulo entre 2014 e 2018 (n = 174.294). Foram também vinculados dados da média de alunos por turma e número de habitantes no município. Os dados foram separados em treinamento e teste, utilizando os registros de 2014 a 2016 (n = 103.357) para treinar cinco modelos preditivos e os dados de 2017 a 2018 (n = 70.937) para testar seus desempenhos em dados novos. A performance preditiva dos algoritmos foi avaliada por meio do valor da área abaixo da curva ROC (AUROC). RESULTADOS Todos os cinco algoritmos testados apresentaram área abaixo da curva acima de 0,76. O algoritmo com melhor performance preditiva (redes neurais artificiais) obteve 0,79 de área abaixo da curva, com acurácia de 71,52%, sensibilidade de 72,86%, especificidade de 70,52% e kappa de 0,427 nos dados de teste. CONCLUSÃO É possível predizer casos de afastamentos por morbidade em docentes da rede pública com machine learning usando dados públicos. O melhor algoritmo apresentou melhor resultado da área abaixo da curva quando comparado ao modelo de referência (regressão logística). Os algoritmos podem contribuir para predições mais assertivas na área da saúde pública e da saúde do trabalhador, permitindo acompanhar e ajudar a prevenir afastamentos por morbidade desses trabalhadores

Disparidades étnico-raciais em saúde autoavaliada: análise multinível de 2.697 indivíduos residentes em 145 municípios brasileiros

Revisões recentes da literatura indicam que o número de estudos sobre disparidades étnicoraciais no Brasil é escasso. A análise multinível torna-se necessária já que o conceito de raça/cor é socialmente construído e pode variar segundo local de residência. Foram analisados 2.697 indivíduos residentes em 145 municípios brasileiros, segundo raça (branca, preta e parda). Foram ajustados modelos multinível utilizando inferência bayesiana pelo método Monte Carlo via Cadeias de Markov. Após a inclusão de variáveis demográficas, socioeconômicas e de acesso a serviços de saúde, indivíduos de raça preta e parda tiveram maior razão de chances de avaliarem sua saúde como negativa (RC = 1,71; IC95%: 1,24; 2,37 e RC = 1,37; IC95%: 1,10; 1,71, respectivamente). Características do local de residência não alteraram significativamente a relação entre raça/cor e saúde autoavaliada. Após a recategorização da variável dependente, as características étnico-raciais perderam significância estatística. O presente estudo indica que as disparidades raciais em saúde podem ser mais complexas do que o esperado

Income inequality is associated with adolescent fertility in Brazil: a longitudinal multilevel analysis of 5,565 municipalities

Abstract\ud \ud Background\ud Brazil has one of the highest adolescent fertility rates in the world. Income inequality has been frequently linked to overall adolescent health, but studies that analyzed its association with adolescent fertility have been performed only in developed countries. Brazil, in the past decade, has presented a rare combination of increasing per capita income and decreasing income inequality, which could influence future desirable pathways for other countries.\ud \ud \ud Methods\ud We analyzed every live birth from 2000 and from 2010 in each of the 5,565 municipalities of Brazil, a total of 6,049,864 births, which included 1,247,145 (20.6%) births from women aged 15 to 19. Income inequality was assessed by the Gini Coefficient and adolescent fertility by the ratio between the number of live births from women aged 15 to 19 and the number of women aged 15 to 19, calculated for each municipality. We first applied multilevel models separately for 2000 and 2010 to test the cross-sectional association between income inequality and adolescent fertility. We then fitted longitudinal first-differences multilevel models to control for time-invariant effects. We also performed a sensitivity analysis to include only municipality with satisfactory birth record coverage.\ud \ud \ud Results\ud Our results indicate a consistent and positive association between income inequality and adolescent fertility. After controlling for per capita income, college access, youth homicide rate and adult fertility, higher income inequality was significantly associated with higher adolescent fertility for both 2000 and 2010. The longitudinal multilevel models found similar results. The sensitivity analysis indicated that the results for the association between income inequality and adolescent fertility were robust. Adult fertility was also significantly associated with adolescent fertility in the cross-sectional and longitudinal models.\ud \ud \ud Conclusion\ud Income inequality is expected to be a leading concern for most countries in the near future. Our results suggest that changes in income inequality are positively and consistently associated with changes in adolescent fertility.Fundação de Amparo à Pesquisa do Estado de São\ud Paulo (FAPESP), grant number 12/09717-

Brazilian mortality of elderly persons: the question about ill-defined underlying causes of death

O envelhecimento populacional é um fato marcante da transição demográfica. O estudo das causas básicas em idosos permite visualizar seu perfil epidemiológico, embora possa ser prejudicado pela alta proporção de causas mal definidas. O objetivo deste trabalho é descrever a mortalidade dos idosos por essas causas no Brasil. A fonte dos dados foi o Sistema de Informações sobre Mortalidade do Ministério da Saúde.Entre as variáveis, a principal modalidade foi a causa básica mal definida [ Capítulo XVIII da Classificação Estatística Internacional de Doenças e Problemas Relacionados à Saúde-Décima Revisão (CID-10)]. O decréscimo desses óbitos em idosos foi de 35 por cento entre 1996 e 2005.Considerando os óbitos de 60 a 69 anos e os de 80 e mais anos, as proporções de mal definidos aumentaram em 9,9 por cento e 14,8 por cento, respectivamente, no ano de 2005. Métodos visando a sua diminuição são sugeridos, salientando-se que o fato mais importante é o de os médicos preencherem adequadamente as declarações de óbito- com as reais causas básicas, conseqüênciais e terminais-, objetivo maior dos estudiososThe study of mortality of elderly persons according to underlying causes permits the understanding of their epidemiological profile; but there is a large proportion of ill-defined causes. The objective of this work is to describe the Brazilian elderly mortality according to ill-defined underlying causes. Data source was the System of Information on Mortality of the Ministry of Health. Among variables, the ill-defined underlying cause of death was the main one [Chapter XVIII, International Statistical Classification of Diseases and Related Health Problems – 10th Revision (ICD-10)]. There was a 35% decrease in the occurrence of them observing the elderly deaths, from 1996 to 2005. An increase on the ratios (ill-defined/all deaths) was detected in 2005 from the deaths of 60 to 69 years to the deaths of 80 and more years: 9.9% and 14.8%, respectively. Methodologies to diminish these proportions are suggested; however, the most relevant factor is an adequate report by the physicians of the actual causes of death – underlying, associated and complications – in the death certificate

Spatial Clusters of Cancer Mortality in Brazil: A Machine Learning Modeling Approach

Objectives: Our aim was to test if machine learning algorithms can predict cancer mortality (CM) at an ecological level and use these results to identify statistically significant spatial clusters of excess cancer mortality (eCM).Methods: Age-standardized CM was extracted from the official databases of Brazil. Predictive features included sociodemographic and health coverage variables. Machine learning algorithms were selected and trained with 70% of the data, and the performance was tested with the remaining 30%. Clusters of eCM were identified using SatScan. Additionally, separate analyses were performed for the 10 most frequent cancer types.Results: The gradient boosting trees algorithm presented the highest coefficient of determination (R2 = 0.66). For total cancer, all algorithms overlapped in the region of Bagé (27% eCM). For esophageal cancer, all algorithms overlapped in west Rio Grande do Sul (48%–96% eCM). The most significant cluster for stomach cancer was in Macapá (82% eCM). The most important variables were the percentage of the white population and residents with computers.Conclusion: We found consistent and well-defined geographic regions in Brazil with significantly higher than expected cancer mortality

How to include the characteristics of the distritos of the Municipality of São Paulo in epidemiologic studies?: an income inequality analysis using the propensity score matching approach

OBJETIVO: o padrão espacial de distribuição de renda do município de São Paulo, frequentemente generalizado como sendo "radial", tem sido muito questionado pela literatura recente. São Paulo tem uma complexa distribuição de características sociais e demográficas entre seus distritos, o que dificulta a análise por meio de modelos estatísticos que permitam a inclusão somente de algumas variáveis de cada vez, como as regressões lineares. O presente estudo objetiva identificar os distritos do município que possam ser considerados como "comparáveis" pelo uso da metodologia estatística conhecida como propensity score matching. METODOLOGIA: os 96 distritos do município de São Paulo foram analisados separadamente; foram incluídas 16 variáveis no modelo, sendo o índice de Gini a variável que permitiu a separação de distritos entre expostos (alta desigualdade) ou não expostos (baixa desigualdade). Do total de distritos, 27 foram considerados comparáveis com algum outro, isto é, possuíram valores de propensity score com uma distância menor de 0,1 de outro com tipo de exposição diferente. RESULTADOS: das 16 variáveis incluídas, 9 apresentaram diferenças estatisticamente significativas entre os distritos incluídos e excluídos, o que é esperado pela metodologia. Dos 17 pares de distritos formados, apenas 3 foram compostos por distritos de uma mesma região administrativa e apenas 1 por distritos que faziam fronteira entre si. CONCLUSÃO: a análise da diferença no padrão de distribuição das variáveis, permitida pelo uso do propensity score matching, indica a dificuldade de dividir a cidade segundo regiões. Para entender São Paulo é preciso considerar suas particularidades e suas complexas distribuições espaciais.OBJECTIVES: The spatial pattern of income distribution in the Municipality of São Paulo, considered to be of a "radial" type, has been challenged by recent studies due to the complex distribution of social and demographic characteristics between its distritos. This demands an in-depth analysis that takes into consideration a multitude of variables in order to control for local heterogeneity. This study aims to identify the distritos of São Paulo that can be defined as "comparable" to another one, by using a statistical methodology known as propensity score matching. METHODOLOGY: The 96 distritos of the Municipality of São Paulo were analyzed separately. 16 variables were included in the model, and the Gini coefficient was used to define "exposure" (high inequality) and "non-exposure" (low inequality). Of the distritos, 27 were considered "comparable". RESULTS: Of the 16 variables inserted in the model, nine presented a statistically significant difference between included and excluded distritos, which is expected by this methodology. Of the 17 pairs of distritos considered to be comparable, only three were composed of distritos situated in the same administrative region, and only one was composed of bordering distritos. CONCLUSION: The complex spatial distribution of the propensity score in the Municipality of São Paulo indicates that it is very difficult to divide the city according to its geographical regions. In order to understand how the distritos of São Paulo affect the health of its residents, it is important to take into consideration its many particularities and how they are spatially distributed

Incremental health expenditure and lost days of normal activity for individuals with mental disorders: results from the São Paulo Megacity Study

Abstract Background With the recent increase in the prevalence of mental disorders in developing countries, there is a growing interest in the study of its consequences. We examined the association of depression, anxiety and any mental disorders with incremental health expenditure, i.e. the linear increase in health expenditure associated with mental disorders, and lost days of normal activity. Methods We analyzed the results from a representative sample survey of residents of the Metropolitan Region of São Paulo (n = 2,920; São Paulo Megacity Mental Health Survey), part of the World Mental Health (WMH) Survey Initiative, coordinated by the World Health Organization and performed in 28 countries. The instrument used for obtaining the individual results, including the assessment of mental disorders, was the WMH version of the Composite International Diagnostic Interview 3.0 (WMH-CIDI 3.0) that generates psychiatric diagnoses according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria. Statistical analyses were performed by multilevel generalized least squares (GLS) regression models. Sociodemographic determinants such as income, age, education and marital status were included as controls. Results Depression, anxiety and any mental disorders were consistently associated with both incremental health expenditure and missing days of normal activity. Depression was associated with an incremental annual expenditure of R$308.28 (95$194.05-R$422.50), or US$252.48 in terms of purchasing power parity (PPP). Anxiety and any mental disorders were associated with a lower, but also statistically significant, incremental annual expenditure (R$177.82, 95$180.52, 95 % CI: 91.13–269.92, or US$145.64 and US$147.85 in terms of PPP, respectively). Most of the incremental health costs associated with mental disorders came from medications. Depression was independently associated with higher incremental health expenditure than the two most prevalent chronic diseases found by the study (hypertension and diabetes). Conclusions The fact that individuals with mental disorders had a consistent higher health expenditure is notable given the fact that Brazil has a universal free-of-charge healthcare and medication system. The results highlight the growing importance of mental disorders as a public health issue for developing countries

Factors associated with the use of antihypertensives among seniors

OBJECTIVE Analyze the use of antihypertensives among seniors and the association with socioeconomic and behavioral characteristics. METHODS In this seriate cross-sectional study, we used data from the Saúde, Bem Estar e Envelhecimento study (SABE – Health, Well-being, and Aging), conducted in 2000, 2006, and 2010 in the city of São Paulo. Association between the use of antihypertensives and the demographic, behavioral, and socioeconomic characteristics and risk factors was analyzed by using multilevel logistic regression models. RESULTS We observed increased proportion of use of antihypertensive, from 48.7% in 2000 to 61.3% in 2006, reaching 65.7% in 2010. Among the seniors who made use of this type of medicine, we also observed increased adoption of combined therapy in the period, from 69.9% to 82.6% from 2000 to 2006 and reaching 91.6% in 2010. Multilevel analysis indicated statistically significant increase in use of antihypertensives, even after control by socioeconomic and behavioral characteristics, both in 2006 and in 2010 (OR = 1.90; 95%CI 1.60–2.24 and OR = 1.94; 95%CI 1.62–2.33, respectively). Use of antihypertensives showed positive association with females, higher age group, black skin color, overweight, and smoking history. CONCLUSIONS High use of antihypertensives and its association with sociodemographic and behavioral characteristics can help guide the discussion of strategies to improve the epidemiological situation, the quality of life, and the distribution of medicines to the elderly population.OBJETIVO Analisar o uso de medicamentos anti-hipertensivos em idosos e a associação com características socioeconômicas e comportamentais. MÉTODOS Neste estudo transversal seriado, foram utilizados dados do estudo SABE (Saúde, Bem Estar e Envelhecimento), realizado em 2000, 2006 e 2010 no município de São Paulo. A associação entre o uso de medicamentos anti-hipertensivos e as características demográficas, socioeconômicas comportamentais e fatores de risco foi analisada por meio de modelos de regressão logísticos multinível. RESULTADOS Foi observado aumento da proporção do uso de anti-hipertensivo, de 48,7% em 2000 para 61,3% em 2006, chegando à 65,7% em 2010. Entre os idosos que faziam uso desse tipo de medicamento, também foi observado aumento da adoção da terapia combinada no período, passando de 69,9% para 82,6% de 2000 a 2006 e alcançando 91,6% em 2010. A análise multinível indicou aumento estatisticamente significativo do uso de anti-hipertensivos, mesmo após controle pelas características socioeconômicas e comportamentais, tanto em 2006 como em 2010 (OR = 1,90; IC95% 1,60–2,24 e OR = 1,94; IC95% 1,62–2,33, respectivamente). O uso de anti-hipertensivos apresentou associação positiva com sexo feminino, maior faixa etária, cor da pele preta, sobrepeso e histórico de tabagismo. CONCLUSÕES O uso elevado de anti-hipertensivos e sua associação com as características sociodemográficas e comportamentais podem ajudar a orientar a discussão de estratégias para a melhoria do quadro epidemiológico, da qualidade de vida, e da distribuição de medicamentos para a população idosa

The descriptive epidemiology of DSM-IV Adult ADHD in the World Health Organization World Mental Health Surveys

We previously reported on the cross-national epidemiology of ADHD from the first 10 countries in the WHO World Mental Health (WMH) Surveys. The current report expands those previous findings to the 20 nationally or regionally representative WMH surveys that have now collected data on adult ADHD. The Composite International Diagnostic Interview (CIDI) was administered to 26,744 respondents in these surveys in high-, upper-middle-, and low-/lower-middle-income countries (68.5% mean response rate). Current DSM-IV/CIDI adult ADHD prevalence averaged 2.8% across surveys and was higher in high (3.6%)- and upper-middle (3.0%)- than low-/lower-middle (1.4%)-income countries. Conditional prevalence of current ADHD averaged 57.0% among childhood cases and 41.1% among childhood subthreshold cases. Adult ADHD was significantly related to being male, previously married, and low education. Adult ADHD was highly comorbid with DSM-IV/CIDI anxiety, mood, behavior, and substance disorders and significantly associated with role impairments (days out of role, impaired cognition, and social interactions) when controlling for comorbidities. Treatment seeking was low in all countries and targeted largely to comorbid conditions rather than to ADHD. These results show that adult ADHD is prevalent, seriously impairing, and highly comorbid but vastly under-recognized and undertreated across countries and cultures