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Cattle weight development is highly correlated with some body measurements. Based on the relationship between morphometric measurements and body mass, our aim was to develop regression equations to estimate the body weight of Curraleiro Pé-Duro (CPD) cattle to be used in farms that lack access to weighting scales. Data from 1023 animals from four farms on withers height (WH), body length (BL), body score (BS), heart girth (HG), permanent teeth (PT), scrotal perimeter (SP), and live weight were used. The animals were classified into five categories depending on age and/or sex: newborns (NB), calves, weaned animals, cows, and bulls. The best models are GLM with Gamma, Gamma, inverse Gaussian, Gaussian, and Gamma distributions for NB, calves, weaned animals, cows, and bulls, respectively. Predictive modeling for bulls was the best performing overall, with a correlation of 0.97 between the estimated by the model and the obtained with a weighting scale. For NB, calves, weaned animals, and cows, the correlation (r) was 0.85, 0.90, 0.95, and 0.87, respectively. The evaluated models are adequate to be used as a technical solution to estimate weight in a cattle production system.

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Introducción: La enfermedad por coronavirus (COVID-19) se ha extendido entre la población de todo el país y ha tenido un gran impacto a nivel mundial. Sin embargo, existen diferencias geográficas importantes en la mortalidad de COVID-19 entre las diferentes regiones del mundo y en Costa Rica. Objetivo: Explorar el efecto de algunos de los factores sociodemográficos en la mortalidad de COVID-19 en pequeñas divisiones geográficas o cantones de Costa Rica. Métodos: Usamos registros oficiales y aplicamos un modelo de regresión clásica de Poisson y un modelo de regresión ponderada geográficamente. Resultados: Obtuvimos un criterio de información de Akaike (AIC) más bajo con la regresión ponderada (927.1 en la regresión de Poison versus 358.4 en la regresión ponderada). Los cantones con un mayor riesgo de mortalidad por COVID-19 tuvo una población más densa; bienestar material más alto; menor proporción de cobertura de salud y están ubicadas en el área del Pacífico de Costa Rica. Conclusiones: Una estrategia de intervención de COVID-19 específica debería concentrarse en áreas de la costa pacífica con poblaciones más densas, mayor bienestar material y menor población por unidad de salud.

Introduction: The coronavirus disease (COVID-19) has spread among the population of Costa Rica and has had a great global impact. However, there are important geographic differences in mortality from COVID-19 among world regions and within Costa Rica. Objective: To explore the effect of some sociodemographic factors on COVID-19 mortality in the small geographic divisions or cantons of Costa Rica. Methods: We used official records and applied a classical epidemiological Poisson regression model and a geographically weighted regression model. Results: We obtained a lower Akaike Information Criterion with the weighted regression (927.1 in Poisson regression versus 358.4 in weighted regression). The cantons with higher risk of mortality from COVID-19 had a denser population; higher material well-being; less population by health service units and are located near the Pacific coast. Conclusions: A specific COVID-19 intervention strategy should concentrate on Pacific coast areas with denser population, higher material well-being and less population by health service units.

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PURPOSE: This study evaluated the association between coffee consumption and serum lipid profile in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). METHODS: This is a cross-sectional study on baseline data from participants of the cohort ELSA-Brasil. Only participants of São Paulo Research Center who underwent a nuclear magnetic resonance (NMR) spectroscopy examination of lipid profile were included (N = 4736). Coffee intake was categorized into four categories (cups/day, in reference cup size of 50 mL, which is the household measure adopted in Brazil): never/almost never, ≤ 1, 1-3, and > 3. Serum lipid profile [i.e., Total Cholesterol (TC), Total Triglycerides (TG), Very Low-Density Lipoprotein-cholesterol (VLDL-c), Low-Density Lipoprotein-cholesterol (LDL-c), High-Density Lipoprotein-cholesterol (HDL-c), Triglyceride-rich Lipoprotein Particles (TRLP) and subfractions particles] was analyzed. To estimate the effect of coffee consumption on serum lipid profile, multivariate Generalized Linear Models were performed. RESULTS: Compared to participants who never or almost never drink coffee, individuals who consumed more than 3 cups/day showed an increase in concentrations of TC (ß: 4.13; 95% CI 0.81, 7.45), TG (ß: 9.53; 95% CI 1.65, 17.42), VLDL-c (ß: 1.90; 95% CI 0.38, 3.42), TRLP (ß: 8.42; 95% CI 1.24, 15.60), and Very Small-TRLP and Medium-TRLP subfractions (ß: 7.36; 95% CI 0.21, 14.51; ß: 2.53; 95% CI 0.89, 4.16, respectively), but not with HDL-c and LDL-c. Among individuals with low (≤ 1 cup/day) and moderate (1-3 cups/day) coffee consumption, no significant associations with lipids was observed. CONCLUSION: High coffee consumption (more than 3 cups per day) was associated with an increase in serum lipids, namely TC, TG, VLDL-c, and TRL particles, highlighting the importance of a moderate consumption of this beverage.

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Parasitism is a dynamic ecological phenomenon that is constantly influenced by the environment and intrinsic factors of the host. We aimed to evaluate the influence of vegetation, environmental temperature, reproductive conditions, sex, and body condition (BC) on the detection of Trypanosoma spp. in the blood of Thrichomys fosteri in the Pantanal region, an enzootic area for trypanosomiasis. Whole blood was collected from the tip of the tail, and nPCR was performed for Trypanosoma spp. detection from the DNA extracted from the resultant blood clot. Statistical analyses were performed using generalized linear models. Our results showed that there is a greater probability of detection of Trypanosoma spp. in the bloodstream of animals with the highest BC values in periods with mild temperatures. Since T. fosteri is an abundant and common prey for carnivores, even in periods with low temperatures and consequent decrease in the reproduction and activities of the blood-sucking arthropod vectors, the maintenance of Trypanosoma spp. in the studied area would be guaranteed via predation (trophic network) of T. fosteri individuals with good BC and patent parasitemia. Furthermore, T. fosteri, which displays Trypanosoma spp. in the bloodstream, would be reproducing adequately because we found no influence between the reproductive condition and the detection of Trypanosoma spp. in T. fosteri. The caviomorph rodent T. fostei is an important species for the maintenance of Trypanosoma spp. in the Pantanal biome.

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Multivariate twin and family studies are one of the most important tools to assess diseases inheritance as well as to study their genetic and environment interrelationship. The multivariate analysis of twin and family data is in general based on structural equation modelling or linear mixed models that essentially decomposes sources of covariation as originally suggested by  Fisher. In this paper, we propose a flexible and unified statistical modelling framework for analysing multivariate Gaussian and non-Gaussian twin and family data. The non-normality is taken into account by actually modelling the mean and variance relationship, while the covariance structure is modelled by means of a linear covariance model including the option to model the dispersion components as functions of known covariates in a regression model fashion. The marginal specification of our models allows us to extend classic models and biometric indices such as the bivariate heritability, genetic, environmental and phenotypic correlations to non-Gaussian data. We illustrate the proposed models through simulation studies and six data analyses and provide computational implementation in R through the package mglm4twin.

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Resumo As Doenças Crônicas Não Transmissíveis (DCNT) são as principais causas de morte no mundo, impactando fortemente sobre populações mais vulneráveis. O objetivo deste estudo foi analisar as mudanças nas prevalências dessas doenças, nas condições de saúde, acesso e utilização de serviços de saúde no Brasil, entre 2008 e 2019. Como ferramenta analítica, foram utilizados testes de diferenças de proporções e modelos lineares generalizados, considerando amostragem complexa dos inquéritos da Pesquisa Nacional por Amostra de Domicílios (PNAD) de 2008, e da Pesquisa Nacional de Saúde (PNS), nos anos de 2013 e 2019, para testar mudanças no tempo das prevalências e estimar razões de prevalência, ajustadas por variáveis sociodemográficas. Houve aumento das prevalências de depressão, câncer, diabetes, distúrbios neuropsiquiátricos, problemas pulmonares crônicos e problemas osteomusculares. Houve redução de artrite reumatoide, insuficiência renal crônica e doenças do aparelho circulatório. Entre os brasileiros com pelo menos uma DCNT verificou-se aumento da cobertura da Estratégia de Saúde da Família ao longo do tempo, no entanto verificou-se redução do atendimento médico em tempo oportuno e obtenção de medicamentos prescritos gratuitamente.

Abstract Chronic non-communicable diseases (NCDs) are the leading causes of death globally, impacting heavily on the most vulnerable populations. This study aimed to analyze changes in the prevalence of these diseases, health conditions, access, and health services in Brazil between 2008 and 2019. Tests of differences and generalized linear models were used as analytical tools, considering complex sampling from the PNAD 2008, PNS 2013, and PNS 2019 surveys, to test temporal changes in the prevalence and the prevalence ratio estimates, adjusted by sociodemographic variables. An increase in the prevalence of Depression, Diabetes, Cancers, Neuropsychiatric Disorders, Chronic Pulmonary problems, and Musculoskeletal problems was observed. A decline in rheumatoid arthritis, chronic renal failure, and diseases of the circulatory system was identified. Among Brazilians with at least one NCD, an increase in coverage by the family health strategy over time was observed. However, there was a reduction in timely medical care and obtaining of free prescription drugs.

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In this work, we propose a new model called generalized symmetrical partial linear model, based on the theory of generalized linear models and symmetrical distributions. In our model the response variable follows a symmetrical distribution such a normal, Student-t, power exponential, among others. Following the context of generalized linear models we consider replacing the traditional linear predictors by the more general predictors in whose case one covariate is related with the response variable in a non-parametric fashion, that we do not specified the parametric function. As an example, we could imagine a regression model in which the intercept term is believed to vary in time or geographical location. The backfitting algorithm is used for estimating the parameters of the proposed model. We perform a simulation study for assessing the behavior of the penalized maximum likelihood estimators. We use the quantile residuals for checking the assumption of the model. Finally, we analyzed real data set related with pH rivers in Ireland.

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Animal health surveillance programmes should be reliable and informative to ensure their effective implementation. As such, the regular assessment of those aiming to demonstrate the absence of disease, as well as the ability to detect outbreaks on time, is of vital importance. Several criteria make it possible to assess the performance of surveillance systems, including timeliness, which represents the speed between steps in a surveillance system. Therefore, the objective of this study was to evaluate the variability in the timeliness, within and between states, of the surveillance programme of the Brazilian Veterinary Services (BVS) for foot-and-mouth disease (FMD), for the notification of vesicular disease. A total of 14 years (2004-2017) of data relating to vesicular syndromes from the Brazilian Continental Information and Surveillance System (SivCont) were included. A categorical variable was created with four classes to group the notified vesicular processes in the SivCont, according to two criteria, the similarity of the symptoms of the diseases reported with FMD and aetiology (viral, bacterial, fungal and non-infectious). The three timeliness values (TL-1, TL-2 and TL-3) related to different portions of the FMD surveillance system were analysed as a response in a generalized linear model in which the states of Brazil were the explanatory variables. The analyses were performed separately for each notification class (FMD, vesicular stomatitis, similar symptoms and similar non-infectious symptoms) and included comparisons within and between states. The study results provide an understanding and evaluation of the timeliness of the Brazilian FMD surveillance system, thereby providing a base of knowledge from which involved agents and decision-makers can evaluate BVS and reinforce surveillance measures in the states with poorer timeliness than permitted.

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Response variables in medical sciences are often bounded, e.g. proportions, rates or fractions of incidence of some disease. In this work, we are interested to study if some characteristics of the population, e.g. sex and race which can explain the incidence rate of colorectal cancer cases. To accommodate such responses, we propose a new class of regression models for bounded response by considering a new distribution in the open unit interval which includes a new parameter to make a more flexible distribution. The proposal is to obtain compound power normal distribution as a base distribution with a quantile transformation of another family of distributions with the same support and then is to study some properties of the new family. In addition, the new family is extended to regression models as an alternative to the regression model with a unit interval response. We also present inferential procedures based on the Bayesian methodology, specifically a Metropolis-Hastings algorithm is used to obtain the Bayesian estimates of parameters. An application to real data to illustrate the use of the new family is considered.

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Harmful cyanobacterial blooms in reservoirs have become a serious global issue for environmental health. However, dominance among different toxic cyanobacteria genera remains poorly understood, especially in tropical areas. We evaluated the influence of environmental factors, including total phosphorus, dissolved aluminum, water level, and precipitation on the change of the dominant genus from Microcystis to Aphanocapsa, in a hypereutrophic tropical reservoir, using 443 water samples over six years of field monitoring by applying generalized linear models (GLM). The results pointed out the prevalence of longer hydrologic retention time leading to enhanced water stability, and nutrients' accumulation into the hypolimnetic zones of the reservoir may have favored the ecophysiological advantages for the picocyanobacteria Aphanocapsa, which reached densities greater than 1 million/ml. In addition, this article also suggests that physical-chemical remediation methods applied for immobilizing phosphorus in the sediments of the reservoir may be low effective in limiting cyanobacterial growth. These findings are not only meaningful to the understanding of the dynamics of cyanobacterial genera but also to improve the management of eutrophic reservoirs in tropical regions. PRACTITIONER POINTS: We assessed cyanobacterial dominance changes based on 6-year field monitoring. First article addressing the dominance of Aphanocapsa spp. in a tropical reservoir. Species of Aphanocapsa responded better to hydrological changes in the reservoir. The use of remediators was accompanied by an increase in cyanobacteria biomass.

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