Method validation using weighted linear regression models for quantification of UV filters in water samples

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

GIS-based analytical tools for transport planning: spatial regression models for transportation demand forecast

Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.

Health-related behavior and quality of life among the elderly: a population-based study

OBJETIVO: Analisar a associação de comportamentos saudáveis com a qualidade de vida relacionada à saúde em idosos. MÉTODOS: Estudo transversal de base populacional que envolveu 1.958 idosos residentes em quatro áreas do estado de São Paulo, em 2001/2002. A qualidade de vida foi aferida com o uso do instrumento Medical Outcomes Study SF-36-Item Short Form Health Survey. As oito escalas e os dois componentes do instrumento constituíram as variáveis dependentes e as independentes foram atividade física, freqüência semanal de ingestão de bebida alcoólica e hábito de fumar. Modelos de regressão linear múltipla foram usados para controlar o efeito de sexo, idade, escolaridade, trabalho, área de residência e número de doenças crônicas. RESULTADOS: Atividade física foi positivamente associada com as oito escalas do SF-36. As maiores associações foram encontradas em aspectos físicos (β = 11,9), capacidade funcional (β = 11,3) e no componente físico. Idosos que ingeriam bebida alcoólica pelo menos uma vez por semana apresentaram melhor qualidade de vida do que os que não ingeriam. Comparados com os que nunca fumaram, os fumantes tiveram pior qualidade de vida no componente mental (β = -2,4). CONCLUSÕES: Os resultados apresentam que praticar atividade física, consumir bebida alcoólica moderadamente e não fumar são fatores positivamente associados a uma melhor qualidade de vida em idosos.

Desenvolvimento de um Questionário Quantitativo de Freqüência Alimentar (QQFA) para gestantes usuárias de Unidades Básicas de Saúde de Ribeirão Preto, São Paulo, Brasil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Weight Training, Aerobic Physical Activities, and Long-Term Waist Circumference Change in Men

ObjectiveFindings on weight training and waist circumference (WC) change are controversial. This study examined prospectively whether weight training, moderate to vigorous aerobic activity (MVAA), and replacement of one activity for another were associated with favorable changes in WC and body weight (BW).MethodsPhysical activity, WC, and BW were reported in 1996 and 2008 in a cohort of 10,500 healthy U.S. men in the Health Professionals Follow-up Study. Multiple linear regression models (partition/substitution) to assess these associations were used.ResultsAfter adjusting for potential confounders, a significant inverse dose-response relationship between weight training and WC change (P-trend<0.001) was observed. Less age-associated WC increase was seen with a 20-min/day activity increase; this benefit was significantly stronger for weight training (-0.67 cm, 95% CI -0.93, -0.41) than for MVAA (-0.33 cm, 95% CI -0.40, -0.27), other activities (-0.16 cm, 95% CI -0.28, -0.03), or TV watching (0.08 cm, 95% CI 0.05, 0.12). Substituting 20 min/day of weight training for any other discretionary activity had the strongest inverse association with WC change. MVAA had the strongest inverse association with BW change (-0.23 kg, 95% CI -0.29, -0.17).ConclusionsAmong various activities, weight training had the strongest association with less WC increase. Studies on frequency/volume of weight training and WC change are warranted.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.

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

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimates of genetic parameters for scrotal circumference using random regression models in Nelore cattle

A total of 15,901 scrotal circumference (SC) records from 5300 Nelore bulls, ranging from 229 to 560 days of age, were used with the objective of estimating (co)variance functions for SC, using random regression models. Models included the fixed effects of contemporary group and age of dam at calving as covariable (linear and quadratic effects). To model the population mean trend, a third order Legendre polynomial on animal age was utilized. The direct additive genetic and animal permanent environmental random effects were modeled by Legendre polynomials on animal age, with orders of fit ranging from 1 to 5. Residual variances were modeled considering 1 (homogeneity of variance) or 4 age classes. Results obtained with the random regression models were compared to multi-trait analysis. (Co)variance estimates using multi-trait and random regression models were similar. The model considering a third- and fifth-order Legendre polynomials for additive genetic and animal permanent environmental effects, respectively, was the most adequate to model changes in variance of SC with age. Heritability estimates for SC ranged from 0.24 (229 days of age) to 0.47 (300 days of age), remained almost constant until 500 days of age (0.52), decreasing thereafter (0.44). In general, the genetic correlations between measures of scrotal circumference obtained from 229 to 560 days of age decreased with increasing distance between ages. For genetic evaluation scrotal circumference could be measured between 400 and 500 days of age. (C) 2010 Elsevier B.V. All rights reserved.

Random regression models to estimate genetic parameters for test-day milk yield in Brazilian Murrah buffaloes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modeling of average growth curve in Santa Ines sheep using random regression models

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Random regression models using different functions to model test-day milk yield of Brazilian Holstein cows

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic parameters for test-day yield of milk, fat and protein in buffaloes estimated by random regression models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)