Stress at work among electric utility workers

In the last decades there was an increase in stress at work and its effects on workers' health. These issues are still little studied in the electric utility sector. This study aims to evaluate factors associated with stress at work and to verify its associations with health status among workers of an electric company in São Paulo State, Brazil. A cross-sectional study was conducted with 474 subjects (87.5% of the eligible workers). Data were collected using self-reported questionnaires. A descriptive analysis, a multiple linear hierarchical regression analysis and a correlation analysis were performed. The majority of participants were males (91.1%) and the mean age was 37.5 yr. The mean score of stress level was 2.3 points (scale ranging from 1.0 to 5.0). Hierarchical multiple analyses showed that: regular practice of physical activities (p=0.025) and individual monthly income (p=0.002) were inversely associated with stress level; BMI was marginally associated with the stress level (p=0.074). The demographic characteristics were not associated with stress. Stress at work was significantly associated with physical and mental health status (p<0.001). To improve health of electric utility workers, actions are suggested to decrease stress by remuneration and an appropriate practice of physical activity aiming reduction of BMI

Stress at Work among Electric Utility Workers

In the last decades there was an increase in stress at work and its effects on workers' health. These issues are still little studied in the electric utility sector. This study aims to evaluate factors associated with stress at work and to verify its associations with health status among workers of an electric company in Sao Paulo State, Brazil. A cross-sectional study was conducted with 474 subjects (87.5% of the eligible workers). Data were collected using self-reported questionnaires. A descriptive analysis, a multiple linear hierarchical regression analysis and a correlation analysis were performed. The majority of participants were males (91.1%) and the mean age was 37.5 yr. The mean score of stress level was 2.3 points (scale ranging from 1.0 to 5.0). Hierarchical multiple analyses showed that: regular practice of physical activities (p=0.025) and individual monthly income (p=0.002) were inversely associated with stress level; BMI was marginally associated with the stress level (p=0.074). The demographic characteristics were not associated with stress. Stress at work was significantly associated with physical and mental health status (p<0.001). To improve health of electric utility workers, actions are suggested to decrease stress by remuneration and an appropriate practice of physical activity aiming reduction of BMI.

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.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

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.

Likelihood-based estimation of the regression model with scrambled responses

A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.

Epidermal iontophoresis: II. Application of the ionic mobility-pore model to the transport of local anesthetics

Purpose, An in vitro study was carried out to determine the iontophoretic permeability of local anesthetics through human epidermis. The relationship between physicochemical structure and the permeability of these solutes was then examined using an ionic mobility-pore model developed to define quantitative relationships. Methods. The iontophoretic permeability of both ester-type anesthetics (procaine, butacaine, tetracaine) and amide-type anesthetics (prilocaine, mepivacaine, lidocaine, bupivacaine, etidocaine, cinchocaine) were determined through excised human epidermis over 2 hrs using a constant d.c. current and Ag/AgCl electrodes. Individual ion mobilities were determined from conductivity measurements in aqueous solutions. Multiple stepwise regression was applied to interrelate the iontophoretic permeability of the solutes with their physical properties to examine the appropriateness of the ionic mobility-pore model and to determine the best predictor of iontophoretic permeability of the local anesthetics. Results. The logarithm of the iontophoretic permeability coefficient (log PCj,iont) for local anesthetics was directly related to the log ionic mobility and MW for the free volume form of the model when other conditions are held constant. Multiple linear regressions confirmed that log PCj,iont was best defined by ionic mobility (and its determinants: conductivity, pK(a) and MW) and MW. Conclusions. Our results suggest that of the properties studied, the best predictors of iontophoretic transport of local anesthetics are ionic mobility (or pK(a)) and molecular size. These predictions are consistent with the ionic mobility pore model determined by the mobility of ions in the aqueous solution, the total current, epidermal permselectivity and other factors as defined by the model.

Echocardiographic predictors of functional capacity in endomyocardial fibrosis patients

Endomyocardial fibrosis (EMF) is a restrictive cardiomyopathy manifested mainly by diastolic heart failure. It is recognized that diastole is an important determinant of exercise capacity. The purpose of this study was to determine whether resting echocardiographic parameters might predict oxygen consumption (VO(2p)) by ergoespirometry and the prognostic role of functional capacity in EMF patients. A total of 32 patients with biventricular EMF (29 women, 55.3 +/- 11.4 years) were studied by echocardiography and ergoespirometry. The relationship between the echocardiographic indexes and the percentage of predicted VO(2p) (%VO(2p)) was investigated by the `stepwise` linear regression analysis. The median VO(2p) was 11 +/- 3 mL/kg/min and the %VO(2p) was 53 +/- 9%. There was a correlation of %VO(2p) with an average of A` at four sites of the mitral annulus (A` peak, r = 0.471, P = 0.023), E`/A` of the inferior mitral annulus (r = -0.433, P = 0.044), and myocardial performance index (r = -0.352, P = 0.048). On multiple regression analysis, only A` peak was an independent predictor of %VO(2p) (%VO(2p)= 26.34 + 332.44 x A` peak). EMF patients with %VO(2p)< 53% had an increased mortality rate with a relative risk of 8.47. In EMF patients, diastolic function plays an important role in determining the limitations to exercise and %VO(2p) has a prognostic value.

Relationship Between Blood Pressure and Anthropometry in a Cohort of Brazilian Men: A Cross-Sectional Study

BACKGROUND Hypertension, a risk factor for cardiovascular diseases, and obesity are becoming a health problem in many developed and developing countries, as Brazil. Although hypertension and obesity are both closely associated, there is no universal anthropometric marker of this association. This is probably due to distinct population characteristics, and in the case of Brazil, the highly heterogeneous population. We evaluated which anthropometric measurement closely relates to high blood pressure in a sample of Brazilian factory workers. METHODS A cross-sectional study was designed. In this study, multiple logistic regression and receiver operating characteristics analysis were performed in order to obtain the precise relevance of each anthropometric measurement as a blood pressure marker. Nine hundred and thirteen men, 36 +/- 8 years-old, were submitted to a standardized questionnaire of demographic and risk factors knowledge, anthropometric and conventional blood pressure measurements were taken, and blood sample evaluations of glucose, total cholesterol, LDL-Cholesterol, and triglycerides were performed. RESULTS Overweightness or obesity was identified in 64, 11.1% were smokers and hypertension was detected in 29.2% of the participants. A linear correlation was significant (P < 0.001) between both the systolic and diastolic blood pressure and all anthropometric measurements, except for the systolic blood pressure and waist-to-hip ratio. Waist circumference (WC) was the only independent anthropometric measurement related to hypertension. Hypertensive patients presented all anthropometric measurements larger than normotensives. CONCLUSIONS Age and WC were the only independent predictors of hypertension, indicating that this simple measurement may be useful as a marker of hypertension in the Brazilian male, younger adult population. Am J Hypertens 2009; 22:980-984 (C) 2009 American Journal of Hypertension, Ltd.

Bridging the gap between different statistical approaches: An integrated framework for modelling

This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.

Association between tooth loss and obesity in Brazilian adults: a population-based study

OBJECTIVE: To examine the association between tooth loss and general and central obesity among adults. METHODS: Population-based cross-sectional study with 1,720 adults aged 20 to 59 years from Florianópolis, Southern Brazil. Home interviews were performed and anthropometric measures were taken. Information on sociodemographic data, self-reported diabetes, self-reported number of teeth, central obesity (waist circumference [WC] > 88 cm in women and > 102 cm in men) and general obesity (body mass index [BMI] ≥ 30 kg/m²) was collected. We used multivariable Poisson regression models to assess the association between general and central obesity and tooth loss after controlling for confounders. We also performed simple and multiple linear regressions by using BMI and WC as continuous variables. Interaction between age and tooth loss was also assessed. RESULTS: The mean BMI was 25.9 kg/m² (95%CI 25.6;26.2) in men and 25.4 kg/m2 (95%CI 25.0;25.7) in women. The mean WC was 79.3 cm (95%CI 78.4;80.1) in men and 88.4 cm (95%CI 87.6;89.2) in women. A positive association was found between the presence of less than 10 teeth in at least one arch and increased mean BMI and WC after adjusting for education level, self-reported diabetes, gender and monthly per capita income. However, this association was lost when the variable age was included in the model. The prevalence of general obesity was 50% higher in those with less than 10 teeth in at least one arch when compared with those with 10 or more teeth in both arches after adjusting for education level, self-reported diabetes and monthly per capita family income. However, the statistical significance was lost after controlling for age. CONCLUSIONS: Obesity was associated with number of teeth, though it depended on the participants' age groups.

Evolution of methodology for the study of adaptability and stability in cultivated species.

The GxE interaction only became widely discussed from evolutionary studies and evaluations of the causes of behavioral changes of species cultivated in environments. In the last 60 years, several methodologies for the study of adaptability and stability of genotypes in multiple environments trials were developed in order to assist the breeder's choice regarding which genotypes are more stable and which are the most suitable for the crops in the most diverse environments. The methods that use linear regression analysis were the first to be used in a general way by breeders, followed by multivariate analysis methods and mixed models. The need to identify the genetic and environmental causes that are behind the GxE interaction led to the development of new models that include the use of covariates and which can also include both multivariate methods and mixed modeling. However, further studies are needed to identify the causes of GxE interaction as well as for the more accurate measurement of its effects on phenotypic expression of varieties in competition trials carried out in genetic breeding programs.

Development of a satellite based PM10 concentration product for urban areas

Dissertação para obtenção do Grau de Doutor em Engenharia do Ambiente

Determinants of Functional and Structural Properties of Large Arteries in Healthy Individuals

Background: Changes in the properties of large arteries correlate with higher cardiovascular risk. Recent guidelines have included the assessment of those properties to detect subclinical disease. Establishing reference values for the assessment methods as well as determinants of the arterial parameters and their correlations in healthy individuals is important to stratify patients. Objective: To assess, in healthy adults, the distribution of the values of pulse wave velocity, diameter, intima-media thickness and relative distensibility of the carotid artery, in addition to assessing the demographic and clinical determinants of those parameters and their correlations. Methods: This study evaluated 210 individuals (54% women; mean age, 44 ± 13 years) with no evidence of cardiovascular disease. The carotid-femoral pulse wave velocity was measured with a Complior® device. The functional and structural properties of the carotid artery were assessed by using radiofrequency ultrasound. Results: The means of the following parameters were: pulse wave velocity, 8.7 ± 1.5 m/s; diameter, 6,707.9 ± 861.6 μm; intima-media thickness, 601 ± 131 μm; relative distensibility, 5.3 ± 2.1%. No significant difference related to sex or ethnicity was observed. On multiple linear logistic regression, the factors independently related to the vascular parameters were: pulse wave velocity, to age (p < 0.01) and triglycerides (p = 0.02); intima-media thickness, to age (p < 0.01); diameter, to creatinine (p = 0.03) and age (p = 0.02); relative distensibility, to age (p < 0.01) and systolic and diastolic blood pressures (p = 0.02 and p = 0.01, respectively). Pulse wave velocity showed a positive correlation with intima media thickness (p < 0.01) and with relative distensibility (p < 0.01), while diameter showed a positive correlation with distensibility (p = 0.03). Conclusion: In healthy individuals, age was the major factor related to aortic stiffness, while age and diastolic blood pressure related to the carotid functional measure. The carotid artery structure was directly related to aortic stiffness, which was inversely related to the carotid artery functional property.

Association between LDL-C, Non HDL-C, and Apolipoprotein B Levels with Coronary Plaque Regression

Background:Previous reports have inferred a linear relationship between LDL-C and changes in coronary plaque volume (CPV) measured by intravascular ultrasound. However, these publications included a small number of studies and did not explore other lipid markers.Objective:To assess the association between changes in lipid markers and regression of CPV using published data.Methods:We collected data from the control, placebo and intervention arms in studies that compared the effect of lipidlowering treatments on CPV, and from the placebo and control arms in studies that tested drugs that did not affect lipids. Baseline and final measurements of plaque volume, expressed in mm3, were extracted and the percentage changes after the interventions were calculated. Performing three linear regression analyses, we assessed the relationship between percentage and absolute changes in lipid markers and percentage variations in CPV.Results:Twenty-seven studies were selected. Correlations between percentage changes in LDL-C, non-HDL-C, and apolipoprotein B (ApoB) and percentage changes in CPV were moderate (r = 0.48, r = 0.47, and r = 0.44, respectively). Correlations between absolute differences in LDL-C, non‑HDL-C, and ApoB with percentage differences in CPV were stronger (r = 0.57, r = 0.52, and r = 0.79). The linear regression model showed a statistically significant association between a reduction in lipid markers and regression of plaque volume.Conclusion:A significant association between changes in different atherogenic particles and regression of CPV was observed. The absolute reduction in ApoB showed the strongest correlation with coronary plaque regression.