Beta-binomial/Poisson regression models for repeated bivariate counts

We analyze data obtained from a study designed to evaluate training effects on the performance of certain motor activities of Parkinson`s disease patients. Maximum likelihood methods were used to fit beta-binomial/Poisson regression models tailored to evaluate the effects of training on the numbers of attempted and successful specified manual movements in 1 min periods, controlling for disease stage and use of the preferred hand. We extend models previously considered by other authors in univariate settings to account for the repeated measures nature of the data. The results suggest that the expected number of attempts and successes increase with training, except for patients with advanced stages of the disease using the non-preferred hand. Copyright (c) 2008 John Wiley & Sons, Ltd.

Problems with accessibility to health services by persons with disabilities in Sao Paulo, Brazil

Purpose. To describe the occurrence of self-reported problems of accessibility to health services used by persons with disabilities in terms of social and health services variables. Methods. We performed a cross-sectional household survey designed to assess problems with accessibility to health services faced by persons with disabilities. We interviewed 333 persons in Sao Paulo city, in 2007. Variables related to the presence of accessibility problems, disabilities, gender, age, family head income, ethnicity, use of health services and others were analysed using frequencies, percentages, chi(2)-test, ANOVA and Poisson regression models. Results. 15.92% of the interviewed persons reported problems with accessibility to health services. Persons having multiple (prevalence ratios; PR = 2.91) or mobility disability (PR = 6.46) had more problems with accessibility than persons with hearing disability. Persons younger than 78 years old had more problems with accessibility; those who needed help to go to the health service (PR = 3.01) also. Conclusions. Persons with multiple or mobility disability, younger than 78 years, and those who needed help of others to go to the health service were more likely to have problems with accessibility to health services. This information could be one of the first steps to the management and/or planning of appropriate health services for persons with disabilities.

Impact of socioeconomic and clinical factors on child oral health-related quality of life (COHRQoL)

Child oral health-related quality of life (COHRQoL) has been increasingly assessed; however, few studies appraised the influence of socioeconomic status on COHRQoL in developing countries. This study assessed the relationship of COHRQoL with socioeconomic backgrounds and clinical factors. This study followed a cross-sectional design, with a multistage random sample of 792 schoolchildren aged 12 years, representative of Santa Maria, a southern city in Brazil. Participants completed the Brazilian version of the Child Perceptions Questionnaire (CPQ(11-14)), their parents or guardians answered questions on socioeconomic status, and a dental examination provided information on the prevalence of caries, dental trauma and occlusion. The assessment of association used hierarchically adjusted Poisson regression models. Higher impacts on COHRQoL were observed for children presenting with untreated dental caries (RR 1.20; 95% CI 1.07-1.35) and maxillary overjet (RR 1.19; 95% CI 1.02-1.40). Socioeconomic factors also associated with COHRQoL; poorer scores were reported by children whose mothers have not completed primary education (RR 1.30; 95% CI 1.17-1.44) and those with lower household income (RR 1.13; 95% CI 1.02-1.26). Poor socioeconomic standings and poor dental status have a negative impact on COHRQoL; reducing health inequalities may demand dental programmes and policies targeting deprived population.

Sex and socioeconomic inequalities of lung cancer mortality in Barcelona, Spain and Sao Paulo, Brazil

The objective of this paper was to assess sex and socioeconomic inequalities in lung cancer mortality in two major cities of Europe and South America. Official information on mortality and population allowed the estimation of sex- and age-specific death rates for Barcelona, Spain and Sao Paulo, Brazil (1995-2003). Mortality trends and levels were independently assessed for each city and subsequently compared. Rate ratios assessed by Poisson regression analysis addressed hypotheses of association between the outcome and socioeconomic covariates (human development index, unemployment and schooling) at the inner-city area level. Barcelona had a higher mortality in men (76.9/100000 inhabitants) than Sao Paulo (38.2/100 000 inhabitants); although rates were decreasing for the former (-2%/year) and levelled-off for the [after. Mortality in women ranked similarly (9.1 for Barcelona, 11.5 for Sao Paulo); with an increasing trend for women aged 35-64 years (+ 7.7%/year in Barcelona and + 2.4%/year in Sao Paulo). The socioeconomic gradient of mortality in men was negative for Barcelona and positive for Sao Paulo; for women, the socioeconomic gradient was positive in both cities. Negative gradients indicate that deprived areas suffer a higher burden of disease; positive gradients suggest that prosmoking lifestyles may have been more prevalent in more affluent areas during the last decades. Sex and socioeconomic inequalities of lung cancer mortality reinforce the hypothesis that the epidemiologic profile of cancer can be improved by an expanded access to existing technology of healthcare and prevention. The continuous monitoring of inequalities in health may contribute to the concurrent promotion of well-being and social justice.

Self-rated oral health and associated factors in Brazilian elders

Objective: Self-rating provides a simple direct way of capturing perceptions of health. The objective of this study was to estimate the prevalence and associated factors of poor self-rated oral health among elders. Methods: National data from a cross-sectional population-based study with a multistage random sample of 4786 Brazilian older adults (aged 65-74) in 250 towns were analysed. Data collection included oral examinations (WHO 1997) and struct-ured interviews at elderly households. The outcome was measured by a single five-point-response-scale question dichotomized into `poor` (fair/poor/very poor) and `good` (good/very good) self-rated oral health. Data analyses used Poisson regression models stratified by sex. Results: The prevalence of poor self-rated oral health was 46.6% (95% CI: 45.2-48%) in the whole sample, 50.3% (48-52.5) in men and 44.2% (42.4-46) in women. Higher prevalence ratios (PR) were found in elders reporting unfavourable dental appearance (PR = 2.31; 95% CI: 2.02-2.65), poor chewing ability (PR = 1.64; CI: 1.48-1.8) and dental pain (PR = 1.44; CI: 1.04-1.23) in adjusted analysis. Poor self-perception was also associated with being men, black, unfavourable socioeconomic circumstances, unfavourable clinical oral health and with not using or needing a dental prosthesis. Conclusion: Assessment and understanding of self-rated oral health should take into account social factors, subjective and clinical oral symptoms.

Paleoamerican Morphology in the Context of European and East Asian Late Pleistocene Variation: Implications for Human Dispersion Into the New World

Early American crania show a different morphological pattern from the one shared by late Native Americans. Although the origin of the diachronic morphological diversity seen on the continents is still debated, the distinct morphology of early Americans is well documented and widely dispersed. This morphology has been described extensively for South America, where larger samples are available. Here we test the hypotheses that the morphology of Early Americans results from retention of the morphological pattern of Late Pleistocene modern humans and that the occupation of the New World precedes the morphological differentiation that gave rise to recent Eurasian and American morphology. We compare Early American samples with European Upper Paleolithic skulls, the East Asian Zhoukoudian Upper Cave specimens and a series of 20 modern human reference crania. Canonical Analysis and Minimum Spanning Tree were used to assess the morphological affinities among the series, while Mantel and Dow-Cheverud tests based on Mahalanobis Squared Distances were used to test different evolutionary scenarios. Our results show strong morphological affinities among the early series irrespective of geographical origin, which together with the matrix analyses results favor the scenario of a late morphological differentiation of modern humans. We conclude that the geographic differentiation of modern human morphology is a late phenomenon that occurred after the initial settlement of the Americas. Am J Phys Anthropol 144:442-453, 2011. (c) 2010 Wiley-Liss, Inc.

Power series generalized nonlinear models

We introduce in this paper a new class of discrete generalized nonlinear models to extend the binomial, Poisson and negative binomial models to cope with count data. This class of models includes some important models such as log-nonlinear models, logit, probit and negative binomial nonlinear models, generalized Poisson and generalized negative binomial regression models, among other models, which enables the fitting of a wide range of models to count data. We derive an iterative process for fitting these models by maximum likelihood and discuss inference on the parameters. The usefulness of the new class of models is illustrated with an application to a real data set. (C) 2008 Elsevier B.V. All rights reserved.

Association between particulate matter from biomass burning and respiratory diseases in the southern region of the Brazilian Amazon

Objective. To investigate the short-term effects of exposure to particulate matter from biomass burning in the Amazon on the daily demand for outpatient care due to respiratory diseases in children and the elderly. Methods. Epidemiologic study with ecologic time series design. Daily consultation records were obtained from the 14 primary health care clinics in the municipality of Alta Floresta, state of Mato Grosso, in the southern region of the Brazilian Amazon, between January 2004 and December 2005. Information on the daily levels of fine particulate matter was made available by the Brazilian National Institute for Spatial Research. To control for confounding factors ( situations in which a non-causal association between exposure and disease is observed due to a third variable), variables related to time trends, seasonality, temperature, relative humidity, rainfall, and calendar effects ( such as occurrence of holidays and weekends) were included in the model. Poisson regression with generalized additive models was used. Results. A 10 mu g/m(3) increase in the level of exposure to particulate matter was associated with increases of 2.9% and 2.6% in outpatient consultations due to respiratory diseases in children on the 6th and 7th days following exposure. Significant associations were not observed for elderly individuals. Conclusions. The results suggest that the levels of particulate matter from biomass burning in the Amazon are associated with adverse effects on the respiratory health of children.

Factors associated with increased prevalence of human papillomavirus infection in a cohort of HIV-Infected Brazilian women

Objectives: Human papillomavirus (HPV) infection is a major risk factor for cervical disease. Using baseline data from the HIV-infected cohort of Evandro Chagas Clinical Research Institute at Fiocruz, Rio de Janeiro, Brazil, factors associated with an increased prevalence of HPV were assessed. Methods: Samples from 634 HIV-infected women were tested for the presence of HPV infection using hybrid capture 11 and polymerase chain reaction. Prevalence ratios (PR) were estimated using Poisson regression analysis with robust variance. Results: The overall prevalence of HPV infection was 48%, of which 94% were infected with a high-risk HPV. In multivariate analysis, factors independently associated with infection with high-risk HPV type were: younger age (<30 years of age; PR 1.5, 95% confidence interval (CI) 1.1-2.1), current or prior drug use (PR 1.3, 95% CI 1.0-1.6), self-reported history of HPV infection (PR 1.2, 95% CI 0.96-1.6), condom use in the last sexual intercourse (PR 1.3, 95% CI 1.1-1.7), and nadir CD4+ T-cell count <100 cells/mm(3) (PR 1.6, 95% CI 1.2-2.1). Conclusions: The estimated prevalence of high-risk HPV-infection among HIV-infected women from Rio de Janeiro, Brazil, was high. Close monitoring of HPV-related effects is warranted in all HIV-infected women, in particular those of younger age and advanced immunosuppression. (C) 2008 International Society for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Regression Models with Heteroscedasticity using Bayesian Approach

In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.

A gender approach to work ability and its relationship to professional and domestic work hours among nursing personnel

The association between working hours and work ability was examined in a cross-sectional study of male (N = 156) and female (N = 1092) nurses in three public hospitals. Working hours were considered in terms of their professional and domestic hours per week and their combined impact; total work load. Logistic regression analysis showed a significant association between total work load and inadequate work ability index (WAI) for females only. Females reported a higher proportion of inadequate WAI, fewer professional work hours but longer domestic work hours. There were no significant differences in total work load by gender. The combination of professional and domestic work hours in females seemed to best explain their lower work ability. The findings suggest that investigations into female well-being need to consider their total work load. Our male sample may have lacked sufficient power to detect a relationship between working hours and work ability. (c) 2008 Elsevier Ltd. All rights reserved.

Using non-homogeneous Poisson models with multiple change-points to estimate the number of ozone exceedances in Mexico City

In this paper, we consider some non-homogeneous Poisson models to estimate the probability that an air quality standard is exceeded a given number of times in a time interval of interest. We assume that the number of exceedances occurs according to a non-homogeneous Poisson process (NHPP). This Poisson process has rate function lambda(t), t >= 0, which depends on some parameters that must be estimated. We take into account two cases of rate functions: the Weibull and the Goel-Okumoto. We consider models with and without change-points. When the presence of change-points is assumed, we may have the presence of either one, two or three change-points, depending of the data set. The parameters of the rate functions are estimated using a Gibbs sampling algorithm. Results are applied to ozone data provided by the Mexico City monitoring network. In a first instance, we assume that there are no change-points present. Depending on the adjustment of the model, we assume the presence of either one, two or three change-points. Copyright (C) 2009 John Wiley & Sons, Ltd.

A nonlinear regression model with skew-normal errors

In this paper we have discussed inference aspects of the skew-normal nonlinear regression models following both, a classical and Bayesian approach, extending the usual normal nonlinear regression models. The univariate skew-normal distribution that will be used in this work was introduced by Sahu et al. (Can J Stat 29:129-150, 2003), which is attractive because estimation of the skewness parameter does not present the same degree of difficulty as in the case with Azzalini (Scand J Stat 12:171-178, 1985) one and, moreover, it allows easy implementation of the EM-algorithm. As illustration of the proposed methodology, we consider a data set previously analyzed in the literature under normality.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.

Framework for Skew-Probit Links in Binary Regression

We review several asymmetrical links for binary regression models and present a unified approach for two skew-probit links proposed in the literature. Moreover, under skew-probit link, conditions for the existence of the ML estimators and the posterior distribution under improper priors are established. The framework proposed here considers two sets of latent variables which are helpful to implement the Bayesian MCMC approach. A simulation study to criteria for models comparison is conducted and two applications are made. Using different Bayesian criteria we show that, for these data sets, the skew-probit links are better than alternative links proposed in the literature.