Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUCTION: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. METHODS: We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a Bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. RESULTS: The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. CONCLUSIONS: It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the Bayesian paradigm is a good strategy for modeling malaria counts.

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUÇÃO: A malaria é uma doença endêmica na região da Amazônia Brasileira, e a detecção de possíveis fatores de risco pode ser de grande interesse às autoridades em saúde pública. O objetivo deste artigo é investigar a associação entre variáveis ambientais e os registros anuais de malária na região amazônica usando métodos bayesianos espaço-temporais. MÉTODOS: Utilizaram-se modelos de regressão espaço-temporais de Poisson para analisar os dados anuais de contagem de casos de malária entre os anos de 1999 a 2008, considerando a presença de alguns fatores como a taxa de desflorestamento. em uma abordagem bayesiana, as inferências foram obtidas por métodos Monte Carlo em cadeias de Markov (MCMC) que simularam amostras para a distribuição conjunta a posteriori de interesse. A discriminação de diferentes modelos também foi discutida. RESULTADOS: O modelo aqui proposto sugeriu que a taxa de desflorestamento, o número de habitants por km² e o índice de desenvolvimento humano (IDH) são importantes para a predição de casos de malária. CONCLUSÕES: É possível concluir que o desenvolvimento humano, o crescimento populacional, o desflorestamento e as alterações ecológicas associadas a estes fatores estão associados ao aumento do risco de malária. Pode-se ainda concluir que o uso de modelos de regressão de Poisson que capturam o efeito temporal e espacial em um enfoque bayesiano é uma boa estratégia para modelar dados de contagem de malária.

The Poisson-exponential regression model under different latent activation schemes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The Poisson-exponential regression model under different latent activation schemes

In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activation schemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer.

Finite mixture regression model with random effects: application to neonatal hospital length of stay

A two-component mixture regression model that allows simultaneously for heterogeneity and dependency among observations is proposed. By specifying random effects explicitly in the linear predictor of the mixture probability and the mixture components, parameter estimation is achieved by maximising the corresponding best linear unbiased prediction type log-likelihood. Approximate residual maximum likelihood estimates are obtained via an EM algorithm in the manner of generalised linear mixed model (GLMM). The method can be extended to a g-component mixture regression model with the component density from the exponential family, leading to the development of the class of finite mixture GLMM. For illustration, the method is applied to analyse neonatal length of stay (LOS). It is shown that identification of pertinent factors that influence hospital LOS can provide important information for health care planning and resource allocation. (C) 2002 Elsevier Science B.V. All rights reserved.

Modelling inpatient length of stay by a hierarchical mixture regression via the EM algorithm

The modelling of inpatient length of stay (LOS) has important implications in health care studies. Finite mixture distributions are usually used to model the heterogeneous LOS distribution, due to a certain proportion of patients sustaining-a longer stay. However, the morbidity data are collected from hospitals, observations clustered within the same hospital are often correlated. The generalized linear mixed model approach is adopted to accommodate the inherent correlation via unobservable random effects. An EM algorithm is developed to obtain residual maximum quasi-likelihood estimation. The proposed hierarchical mixture regression approach enables the identification and assessment of factors influencing the long-stay proportion and the LOS for the long-stay patient subgroup. A neonatal LOS data set is used for illustration, (C) 2003 Elsevier Science Ltd. All rights reserved.

Modelling HIV/AIDS length of stay in Portugal

Tese apresentada como requisito parcial para obtenção do grau de Doutor em Estatística e Gestão de Informação pelo Instituto Superior de Estatística e Gestão de Informação da Universidade Nova de Lisboa

Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros

Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.

Extended truncated Tweedie-Poisson model

It has been argued that by truncating the sample space of the negative binomial and of the inverse Gaussian-Poisson mixture models at zero, one is allowed to extend the parameter space of the model. Here that is proved to be the case for the more general three parameter Tweedie-Poisson mixture model. It is also proved that the distributions in the extended part of the parameter space are not the zero truncation of mixed poisson distributions and that, other than for the negative binomial, they are not mixtures of zero truncated Poisson distributions either. By extending the parameter space one can improve the fit when the frequency of one is larger and the right tail is heavier than is allowed by the unextended model. Considering the extended model also allows one to use the basic maximum likelihood based inference tools when parameter estimates fall in the extended part of the parameter space, and hence when the m.l.e. does not exist under the unextended model. This extended truncated Tweedie-Poisson model is proved to be useful in the analysis of words and species frequency count data.

Falls Among The Elderly: Risk Factors In A Population-based Study.

The aim of the present study was to identify factors associated with the occurrence of falls among elderly adults in a population-based study (ISACamp 2008). A population-based cross-sectional study was carried out with two-stage cluster sampling. The sample was composed of 1,520 elderly adults living in the urban area of the city of Campinas, São Paulo, Brazil. The occurrence of falls was analyzed based on reports of the main accident occurred in the previous 12 months. Data on socioeconomic/demographic factors and adverse health conditions were tested for possible associations with the outcome. Prevalence ratios (PR) were estimated and adjusted for gender and age using the Poisson multiple regression analysis. Falls were more frequent, after adjustment for gender and age, among female elderly participants (PR = 2.39; 95% confidence interval (95% CI) 1.47 - 3.87), elderly adults (80 years old and older) (PR = 2.50; 95% CI 1.61 - 3.88), widowed (PR = 1.74; 95% CI 1.04 - 2.89) and among elderly adults who had rheumatism/arthritis/arthrosis (PR = 1.58; 95% CI 1.00 - 2.48), osteoporosis (PR = 1.71; 95% CI 1.18 - 2.49), asthma/bronchitis/emphysema (PR = 1,73; 95% CI 1.09 - 2.74), headache (PR = 1.59; 95% CI 1.07 - 2.38), mental common disorder (PR = 1.72; 95% CI 1.12 - 2.64), dizziness (PR = 2.82; 95% CI 1.98 - 4.02), insomnia (PR = 1.75; 95% CI 1.16 - 2.65), use of multiple medications (five or more) (PR = 2.50; 95% CI 1.12 - 5.56) and use of cane/walker (PR = 2.16; 95% CI 1.19 - 3,93). The present study shows segments of the elderly population who are more prone to falls through the identification of factors associated with this outcome. The findings can contribute to the planning of public health policies and programs addressed to the prevention of falls.

Dyspareunia In Hiv-positive And Hiv-negative Middle-aged Women: A Cross-sectional Study.

To evaluate whether dyspareunia is associated with HIV status in menopausal women and also to assess which factors are associated with dyspareunia in a group of HIV-positive menopausal women. A cross-sectional study was conducted with 178 HIV-negative and 128 HIV-positive women aged 40-60 years. The Short Personal Experiences Questionnaire (SPEQ) was used to collect data. Sociodemographic, clinical, behavioural and reproductive factors were evaluated, as well as factors related to the HIV infection. Dyspareunia was defined as pain during intercourse. A bivariate analysis and Poisson multiple regression analysis were performed. Overall, 41.4% of the HIV-positive women reported dyspareunia compared with 34.8% of the HIV-negative women (p=0.242). In the HIV-positive women, bivariate analysis revealed an association between dyspareunia and having a steady partner (p=0.047); the woman's partner having undergone HIV testing (p=0.020); vaginal dryness (p<0.001); muscle/joint pain (p=0.021); physical/emotional violence (p=0.049); urinary incontinence (p=0.004); and the use of lamivudine/zidovudine (p=0.048). The Poisson multiple regression analysis found an association between dyspareunia and vaginal dryness (prevalence ratio (PR)=1.96, 95% CI 1.10 to 3.50, p=0.023) and urinary incontinence (PR=1.86, 95% CI 1.06 to 3.27, p=0.031). Dyspareunia was common in this group of HIV-positive women and was associated principally with vaginal dryness and urinary incontinence. The importance of treating dyspareunia within the context of sexual health in this group of women should be emphasised and appropriate management of this issue may reduce the likelihood of lesions on the vaginal wall, which may act as a portal of entry for other infections.

Low Bone Mass In Human Immunodeficiency Virus-infected Climacteric Women Receiving Antiretroviral Therapy: Prevalence And Associated Factors.

Low bone mineral density (BMD) has been found in human immunodeficiency virus (HIV)-infected patients; however, data on associated factors remain unclear, specifically in middle-aged women. This study aims to evaluate factors associated with low BMD in HIV-positive women. In this cross-sectional study, a questionnaire was administered to 206 HIV-positive women aged 40 to 60 years who were receiving outpatient care. Clinical features, laboratory test results, and BMD were assessed. Yates and Pearson χ(2) tests and Poisson multiple regression analysis were performed. The median age of women was 47.7 years; 75% had nadir CD4 T-cell counts higher than 200, and 77.8% had viral loads below the detection limit. There was no association between low BMD at the proximal femur and lumbar spine (L1-L4) and risk factors associated with HIV infection and highly active antiretroviral therapy. Poisson multiple regression analysis showed that the only factor associated with low BMD at the proximal femur and lumbar spine was postmenopause status. Low BMD is present in more than one third of this population sample, in which most women are using highly active antiretroviral therapy and have a well-controlled disease. The main associated factor is related to estrogen deprivation. The present data support periodic BMD assessments in HIV-infected patients and highlight the need to implement comprehensive menopausal care for these women to prevent bone loss.

Factors associated with the prevalence of hypertension and control practices among elderly residents of São Paulo city, Brazil

The aim of this study was to analyze the prevalence of hypertension and control practices among the elderly. The survey analyzed data from 872 elderly people in São Paulo, Brazil, through a cluster sampling, stratified according to education and income. A Poisson multiple regression model checked for the existence of factors associated with hypertension. The prevalence of self-reported hypertension among the elderly was 46.9%. Variables associated with hypertension were self-rated health, alcohol consumption, gender, and hospitalization in the last year, regardless of age. The three most common measures taken to control hypertension, but only rarely, are oral medication, routine salt-free diet and physical activity. Lifestyle and socioeconomic status did not affect the practice of control, but knowledge about the importance of physical activity was higher among those older people with higher education and greater income. The research suggests that health policies that focus on primary care to encourage lifestyle changes among the elderly are necessary.

Atividade fisica e aptidão fisica de adolescentes : similaridades e contrastes em uma decada

Universidade Estadual de Campinas . Faculdade de Educação Física

O risco de incidência e persistência da obesidade entre adultos Brasileiros segundo seu estado nutricional ao final da adolescência

INTRODUÇÃO: A prevalência da obesidade vem aumentando entre adultos nos países desenvolvidos e em desenvolvimento. No Brasil, a obesidade entre adultos atingiu entre 2008 a 2009 pelo menos 10% da população. OBJETIVOS: Com base nos dados do VIGITEL, neste trabalho, serão estimadas a incidência e a persistência da obesidade entre brasileiros adultos no período de 2006 a 2009. MÉTODOS: Nas amostras de 2006 a 2009, foram utilizados casos com registros demográficos, socioeconômicos e antropométricos completos. As estimativas foram expandidas para a população brasileira em 2007. A estimativa do risco relativo (RR) para incidência e persistência da obesidade ou excesso de peso entre homens e mulheres foi feita com regressão múltipla de Poisson, e ajustada para hábito de fumar, idade e atividade física. RESULTADOS: A incidência do excesso de peso entre indivíduos com peso baixo ou normal, aos 20 anos, é estimada em 40%, no sexo masculino, e em 30%, no feminino. A persistência da obesidade, por sua vez, é estimada em 65%, no sexo masculino, e em 47%, no feminino. O gradiente da obesidade como função da escolarização é virtualmente nulo no sexo masculino. Entre mulheres, o gradiente é negativo, com associações lineares e estatisticamente significantes. CONCLUSÃO: Essas características, associadas à forte expansão da obesidade entre adultos jovens detectada em outros estudos, apontam a urgência da utilização de políticas públicas mais incisivas e efetivas, que reduzam a exposição da população à alimentação com má qualidade nutricional e desenvolvam ações voltadas à promoção da atividade física.