Imagem corporal, estado nutricional e comportamento com relação ao peso entre adolescentes brasileiros

O objetivo deste artigo é descrever a concordância entre imagem corporal (IC) e estado nutricional (EN) e verificar a associação de IC e de EN com comportamentos relacionados ao peso corporal (CRPC) entre adolescentes brasileiros. Estudou-se, em 2009, amostra representativa de alunos do 9º ano do ensino fundamental de escolas públicas e privadas das 26 capitais brasileiras e do Distrito Federal. Utilizou-se questionário autoaplicável sobre IC, CRPC e dados sociodemográficos e foram aferidos peso e altura. Utilizou-se o teste Kappa ponderado (KP) para exame da concordância entre EN e IC. Análises de regressão logística foram realizadas para exame da associação entre as variáveis. Do total de adolescentes, 24% apresentavam excesso de peso (EP), quase 2/3 deles tinham alguma atitude para controlar o peso e 7% realizavam práticas extremas para redução do peso (PECP). Foi baixa a concordância entre EN e IC (KP=0,33). Quase metade dos alunos com EP considerava-se com peso adequado e 27%, magros. Maior proporção de adolescentes com EP fazia uso de PECP, quando comparados àqueles de peso adequado e baixo peso. O mesmo foi observado em relação à IC. Conclusão: foi baixa a concordância entre EN e IC. Atitudes de controle de peso e PECP foram frequentes mesmo entre indivíduos com EN adequado.

Prevalência e fatores associados ao tabagismo em escolares da Região Sul do Brasil

OBJETIVO: Estimar a prevalência do tabagismo em estudantes e os fatores associados.MÉTODOS: Foram utilizados dados secundários, provenientes do inquérito Vigescola realizado em Curitiba (PR), Florianópolis (SC) e Porto Alegre (RS) em 2002 e 2004. A amostra compreendeu 3.690 escolares de 13 a 15 anos, cursando as sétima e oitava séries do ensino fundamental e primeira do ensino médio, em escolas públicas e privadas. Para a análise dos resultados foram estimadas proporções ponderadas, odds ratio (OR), e utilizada a técnica de regressão logística múltipla.RESULTADOS: As taxas de prevalência de tabagismo corresponderam a 10,7 por cento (IC 95 por cento: 10,2;11,3) em Florianópolis, 12,6 por cento (IC 95 por cento: 12,4;12,9) em Curitiba e 17,7 por cento (IC 95 por cento: 17,4;18,0) em Porto Alegre. Os fatores associados ao tabagismo em escolares em Curitiba foram: sexo feminino (OR=1,49), pai fumante (OR=1,59), amigos fumantes (OR=3,46), exposição à fumaça do tabaco fora de casa (OR=3,26) e possuir algum objeto com logotipo de marca de cigarro (OR=3,29). Em Florianópolis, as variáveis associadas ao tabagismo foram escolares do sexo feminino (OR=1,26), ter amigos fumantes (OR=9,31), exposição à fumaça do tabaco em casa (OR=2,03) e fora de casa (OR=1,45) e ter visto propaganda em cartazes (OR=1,82). Em Porto Alegre, as variáveis que estiveram associadas com o uso de tabaco pelos escolares foram sexo feminino (OR=1,57), idade entre 14 anos (OR=1,77) e 15 anos (OR=2,89), amigos fumantes (OR=9,12), exposição à fumaça do tabaco em casa (OR=1,87) e fora de casa (OR=1,77) e possuir algo com logotipo de marca de cigarro (OR=2,83).CONCLUSÕES: Há elevada prevalência de tabagismo entre escolares de 13 a 15 anos, cujos fatores significativamente associados comuns às três capitais são: ter amigos fumantes e estar exposto à fumaça ambiental fora de casa

Weighted S-Asymptotically omega-Periodic Solutions of a Class of Fractional Differential Equations

We study the existence of weighted S-asymptotically omega-periodic mild solutions for a class of abstract fractional differential equations of the form u' = partial derivative (alpha vertical bar 1)Au + f(t, u), 1 < alpha < 2, where A is a linear sectorial operator of negative type.

Traffic-Related Air Pollution and Perinatal Mortality: A Case-Control Study

BACKGROUND: Ambient levels of air pollution may affect the health of children, as indicated by studies of infant and perinatal mortality. Scientific evidence has also correlated low birth weight and preterm birth, which are important determinants of perinatal death, with air pollution. However, most of these studies used ambient concentrations measured at monitoring sites, which may not consider differential exposure to pollutants found at elevated concentrations near heavy-traffic roadways. OBJECTIVES: Our goal was to examine the association between traffic-related pollution and perinatal mortality. METHODS: We used the information collected for a case-control study conducted in 14 districts in the City of Sao Paulo, Brazil, regarding risk factors for perinatal deaths. We geocoded the residential addresses of cases (fetal and early neonatal deaths) and controls (children who survived the 28th day of life) and calculated a distance-weighted traffic density (DWTD) measure considering all roads contained in a buffer surrounding these homes. RESULTS: Logistic regression revealed a gradient of increasing risk of early neonatal death with higher exposure to traffic-related air pollution. Mothers exposed to the highest quartile of the DWTD compared with those less exposed exhibited approximately 50% increased risk (adjusted odds ratio = 1.47; 95% confidence interval, 0.67-3.19). Associations for fetal mortality were less consistent. CONCLUSIONS: These results suggest that motor vehicle exhaust exposures may be a risk factor for perinatal mortality.

Multi-trait and random regression mature weight heritability and breeding value estimates in Nelore cattle

Mature weight breeding values were estimated using a multi-trait animal model (MM) and a random regression animal model (RRM). Data consisted of 82 064 weight records from 8 145 animals, recorded from birth to eight years of age. Weights at standard ages were considered in the MM. All models included contemporary groups as fixed effects, and age of dam (linear and quadratic effects) and animal age as covariates. In the RRM, mean trends were modelled through a cubic regression on orthogonal polynomials of animal age and genetic maternal and direct and maternal permanent environmental effects were also included as random. Legendre polynomials of orders 4, 3, 6 and 3 were used for animal and maternal genetic and permanent environmental effects, respectively, considering five classes of residual variances. Mature weight (five years) direct heritability estimates were 0.35 (MM) and 0.38 (RRM). Rank correlation between sires' breeding values estimated by MM and RRM was 0.82. However, selecting the top 2% (12) or 10% (62) of the young sires based on the MM predicted breeding values, respectively 71% and 80% of the same sires would be selected if RRM estimates were used instead. The RRM modelled the changes in the (co) variances with age adequately and larger breeding value accuracies can be expected using this model.

Residuals for log-Burr XII regression models in survival analysis

In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the modified martingale-type residual in log-Burr XII regression models with censored data.

A log-extended Weibull regression model

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likelihood to estimate the model parameters and some inferential procedures are presented. We reanalyze a real data set under the new model and the log-modified Weibull regression model. We perform a model check based on martingale-type residuals and generated envelopes and the statistics AIC and BIC to select appropriate models. (C) 2009 Elsevier B.V. All rights reserved.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

Definition of priority areas for forest conservation through the ordered weighted averaging method

The general objective of this study was to evaluate the ordered weighted averaging (OWA) method, integrated to a geographic information systems (GIS), in the definition of priority areas for forest conservation in a Brazilian river basin, aiming at to increase the regional biodiversity. We demonstrated how one could obtain a range of alternatives by applying OWA, including the one obtained by the weighted linear combination method and, also the use of the analytic hierarchy process (AHP) to structure the decision problem and to assign the importance to each criterion. The criteria considered important to this study were: proximity to forest patches; proximity among forest patches with larger core area; proximity to surface water; distance from roads: distance from urban areas; and vulnerability to erosion. OWA requires two sets of criteria weights: the weights of relative criterion importance and the order weights. Thus, Participatory Technique was used to define the criteria set and the criterion importance (based in AHP). In order to obtain the second set of weights we considered the influence of each criterion, as well as the importance of each one, on this decision-making process. The sensitivity analysis indicated coherence among the criterion importance weights, the order weights, and the solution. According to this analysis, only the proximity to surface water criterion is not important to identify priority areas for forest conservation. Finally, we can highlight that the OWA method is flexible, easy to be implemented and, mainly, it facilitates a better understanding of the alternative land-use suitability patterns. (C) 2008 Elsevier B.V. All rights reserved.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

Paclitaxel associated with cholesterol-rich nanoemulsions promotes atherosclerosis regression in the rabbit

A cholesterol-rich nanoemulsion (LDE) that resembles LDL binds to the LDL receptors and after injection into the blood stream may concentrate in cells with LDL receptor overexpression, as occurs in neoplasias and other proliferative processes. Thus, LDE can be used as vehicle to target drugs against those cells. The current study was designed to verify in rabbits whether LDE concentrates in the lesioned rabbit artery and whether a paclitaxel derivative, paclitaxel oleate, associated to LDE could reduce the atherosclerotic lesions. Sixteen male New Zealand rabbits were fed a 1% cholesterol diet for 60 days. Starting from day 30 under cholesterol feeding, eight animals were treated with four weekly intravenous injections of LDE-paclitaxel (4 mg/kg) and eight with four weekly intravenous saline solution injections for additional 30 days. On day 60, the animals were sacrificed for analysis. The uptake of LDE labeled with [C-14]-cholesteryl oleate by the aortic arch of cholesterol-fed rabbits was twice as much that observed in animals fed only regular chow. LDE-paclitaxel reduced the lesion areas of cholesterol-fed animals by 60% and intima-media ratio fourfold and inhibited the macrophage migration and the smooth muscle cell proliferation and invasion of the intima. LDE-paclitaxel treatment had no toxicity. In conclusion, LDE-paclitaxel produced pronounced atherosclerosis regression without toxicity and has shown remarkable potential in cardiovascular therapeutics. (c) 2008 Published by Elsevier Ireland Ltd.