Objective: Multimorbidity, or the occurrence of two or more chronic conditions, is a global challenge, with implications for mortality, morbidity, disability, and life quality. Psychiatric disorders are common among the chronic diseases that affect patients with multimorbidity. It is still not well understood whether psychiatric symptoms, especially depressive symptoms, moderate the effect of multimorbidity on cognition. Methods: We used a large (n=2,681) dataset to assess whether depressive symptomatology moderates the effect of multimorbidity on cognition using structural equation modelling. Results: It was found that the more depressive symptoms and chronic conditions, the worse the cognitive performance, and the higher the educational level, the better the cognitive performance. We found a significant but weak (0.009; p = 0.04) moderating effect. Conclusion: We have provided the first estimate of the moderating effect of depression on the relation between multimorbidity and cognition, which was small. Although this moderation has been implied by many previous studies, it was never previously estimated.

BackgroundAlmost twenty percent of women worldwide experience mental health disorders following childbirth. Despite their importance and consequences, postpartum psychiatric disorders are still under-investigated. In Brazil, studies are restricted to state capitals and are not representative of the country as a whole. Understanding the factors associated with postpartum psychiatric disorders can provide insights for adequate maternal mental health screening. This study was conducted with the objective of evaluating factors associated with postpartum psychiatric disorders in Brazil. MethodsWe used Authorization of Outpatient Procedure data for women who used community mental health services in Brazil between 2008 and 2012. The dependent variable was the diagnosis of mental disorders and behavioural factors associated with the puerperium (ICD-10 code F53). Age categorized in quartiles and Psychosocial Care Centre (CAPS) coverage were covariates considered for the analysis. To partially neutralize the bias from repeated observations, we used the Proximity Index (PP), created through of geographic information for each visit to the level of the patient’s neighbourhood. We used Generalized Additive Models for Location, Scale, and Shape (GAMLSS) with double Poisson distribution. FindingsWe identified 6,802 records of mental and behavioural disorders associated with the puerperium diagnoses. Among them, 47.6% of the outpatient records were for diagnosis of ICD F53.1, and 32.09% for ICD-10 F53.0, which correspond to severe and mild mental disorders associated with the puerperium, respectively. Diagnosis for ICD-10 F53.0 was higher between the ages of 26 and 30 (10%), while diagnosis for ICD F53.1 was higher between the ages of 31 and 35 (12.7%). For each increment in the maternal age unit and CAPS coverage percentage, there is an increase of 1.01 (p<0.001) in the occurrence of postpartum psychiatric disorders. ConclusionsOur results showed that increases in maternal age and municipal CAPS coverage heightened the risk of postpartum psychiatric disorders. With regards to severity, we found that diagnosis for ICD F53.0 (mild mental and behavioural disorders associated with the puerperium) was higher among women aged between 26 and 30, while diagnosis for ICD F53.1(severe mental and behavioural disorders associated with the puerperium) was higher among women aged between 31 and 35. Our findings support the need to improve knowledge of maternal mental health and to integrate routine screening into postnatal care settings, for the early identification of women who are at risk, and to apply timely preventive and therapeutic approaches. For collaborations please contact: Email: flaviajosy1@gmail.com

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This study analyzed the behavior of daily rainfall in the State of Paraíba using the data from five meteorological stations distributed across the mesoregions of this state. We used the three-state Markov Chain model, in which states are defined as dry, wet and rainy. We calculated transition probabilities among states, probabilities of equilibrium of states, and expected lengths of the defined states for all stations and seasons to investigate spatial/seasonal variability. Results showed that for the entire region and for all seasons, the probability of dry days is greater than the probability of rainy days; expected values of rainy spells are low, indicating that the rainfall regime in Paraíba is characterized by high rainfall intensity distributed over short rainy periods. The dry-dry transition probability presents the highest values for all seasons and stations, as well as the corresponding expected dry spell length, indicating that this region is subjected to prolonged dry periods. The transition probabilities that lead to dry condition are higher in the interior of the State, while probabilities that lead to rainy condition are higher in the coastal region as well as the probability of rainy days, which is greater in fall, during the rainy season.

Atualmente a análise de sobrevivência é uma das áreas que mais crescem no campo da análise estatística, com uma sólida teoria para ajustar modelos de regressão para estudar certos fenômenos, os quais têm, em sua estrutura, a característica de ter observações incompletas na amostra denominada censura. Embora esses modelos possam representar eficientemente o fenômeno em estudo em muitas situações, alguns deles não levam em consideração a existência de uma variável não observável presente na maioria dos estudos, denominada fragilidade. Essa fragilidade denota a suscetibilidade do evento a ocorrer por um indivíduo ou objeto determinado sob investigação. O objetivo deste trabalho foi mostrar que, em situações em que a fragilidade está presente, o uso de modelos que capturam a variabilidade dessa variável é mais viável para a análise desses dados quando comparado aos modelos convencionais em estudos de sobrevivência. Para tanto, foi realizada uma análise comparativa entre esses modelos, ajustada para um conjunto de dados de pacientes diagnosticados com retinopatia diabética, e também foi realizado um estudo de simulação para o modelo de fragilidade gama com diferentes porcentagens de censura e heterogeneidade. Após o ajuste dos modelos, observa-se que os modelos de fragilidade tiveram melhor desempenho quando comparados ao modelo de Cox, com ênfase no modelo de fragilidade gama, que gerou o menor valor para AIC e BIC. O estudo de simulação mostrou que altas taxas de censura prejudicam o grau de previsibilidade do modelo de fragilidade e que altas taxas de heterogeneidade contribuem para estimativas de parâmetros.