31 resultados para LINEAR MODELS
em Scielo Saúde Pública - SP
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OBJECTIVE: Myocardial infarction is an acute and severe cardiovascular disease that generally leads to patient admissions to intensive care units and few cases are initially admitted to infirmaries. The objective of the study was to assess whether estimates of air pollution effects on myocardial infarction morbidity are modified by the source of health information. METHODS: The study was carried out in hospitals of the Brazilian Health System in the city of São Paulo, Southern Brazil. A time series study (1998-1999) was performed using two outcomes: infarction admissions to infirmaries and to intensive care units, both for people older than 64 years of age. Generalized linear models controlling for seasonality (long and short-term trends) and weather were used. The eight-day cumulative effects of air pollutants were assessed using third degree polynomial distributed lag models. RESULTS: Almost 70% of daily hospital admissions due to myocardial infarction were to infirmaries. Despite that, the effects of air pollutants on infarction were higher for intensive care units admissions. All pollutants were positively associated with the study outcomes but SO2 presented the strongest statistically significant association. An interquartile range increase on SO2 concentration was associated with increases of 13% (95% CI: 6-19) and 8% (95% CI: 2-13) of intensive care units and infirmary infarction admissions, respectively. CONCLUSIONS: It may be assumed there is a misclassification of myocardial infarction admissions to infirmaries leading to overestimation. Also, despite the absolute number of events, admissions to intensive care units data provides a more adequate estimate of the magnitude of air pollution effects on infarction admissions.
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OBJECTIVE: To evaluate metabolic changes associated with highly active antiretroviral therapy (HAART) in HIV-positive patients, and to identify risk factors associated. METHODS: Retrospective study that included 110 HIV-positive patients who where on HAART in the city of Porto Alegre (Southern Brazil) between January 2003 and March 2004. Data on demographic variables, cigarette smoking, diabetes mellitus, cholesterol and triglyceride levels, stage of HIV infection, antiretroviral therapy and HCV coinfection were collected. General linear models procedure for repeated measures was used to test the interaction between HAART and HCV coinfection or protease inhibitor treatment. RESULTS: Total cholesterol, triglycerides, and glucose levels significantly increased after receiving HAART (p<0.001 for all variables), but no interaction with protease inhibitors was seen for total cholesterol, glucose and triglyceride levels (interaction treatment*protease inhibitors p=0.741, p=0.784, and p=0.081, respectively). An association between total cholesterol levels and HCV coinfection was found both at baseline and follow-up (effect of HCV coinfection, p=0.011). Glucose levels were increased by HAART (treatment effect, p=0.036), but the effect was associated to HCV coinfection (treatment*HCV effect, p=0.018). Gender, smoking habit, intravenous drug use and age were not significantly associated with cholesterol, triglyceride and glucose changes. CONCLUSIONS: HCV-infected patients at baseline were significantly less likely to develop hypercholesterolemia. The results provide further evidence of the role of HAART for the development of metabolic disturbances.
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OBJECTIVE To analyze vaccination coverage and factors associated with a complete immunization scheme in children < 5 years old. METHODS This cross-sectional household census survey evaluated 1,209 children < 5 years old living in Bom Jesus, Angola, in 2010. Data were obtained from interviews, questionnaires, child immunization histories, and maternal health histories. The statistical analysis used generalized linear models, in which the dependent variable followed a binary distribution (vaccinated, unvaccinated) and the association function was logarithmic and had the children’s individual, familial, and socioeconomic factors as independent variables. RESULTS Vaccination coverage was 37.0%, higher in children < 1 year (55.0%) and heterogeneous across neighborhoods; 52.0% of children of both sexes had no immunization records. The prevalence rate of vaccination significantly varied according to child age, mother’s level of education, family size, ownership of household appliances, and destination of domestic waste. CONCLUSIONS Vulnerable groups with vaccination coverage below recommended levels continue to be present. Some factors indicate inequalities that represent barriers to full immunization, indicating the need to implement more equitable policies. The knowledge of these factors contributes to planning immunization promotion measures that focus on the most vulnerable groups.
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OBJECTIVE To analyze the spatial distribution of risk for tuberculosis and its socioeconomic determinants in the city of Rio de Janeiro, Brazil.METHODS An ecological study on the association between the mean incidence rate of tuberculosis from 2004 to 2006 and socioeconomic indicators of the Censo Demográfico (Demographic Census) of 2000. The unit of analysis was the home district registered in the Sistema de Informação de Agravos de Notificação (Notifiable Diseases Information System) of Rio de Janeiro, Southeastern Brazil. The rates were standardized by sex and age group, and smoothed by the empirical Bayes method. Spatial autocorrelation was evaluated by Moran’s I. Multiple linear regression models were studied and the appropriateness of incorporating the spatial component in modeling was evaluated.RESULTS We observed a higher risk of the disease in some neighborhoods of the port and north regions, as well as a high incidence in the slums of Rocinha and Vidigal, in the south region, and Cidade de Deus, in the west. The final model identified a positive association for the variables: percentage of permanent private households in which the head of the house earns three to five minimum wages; percentage of individual residents in the neighborhood; and percentage of people living in homes with more than two people per bedroom.CONCLUSIONS The spatial analysis identified areas of risk of tuberculosis incidence in the neighborhoods of the city of Rio de Janeiro and also found spatial dependence for the incidence of tuberculosis and some socioeconomic variables. However, the inclusion of the space component in the final model was not required during the modeling process.
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Introduction This study aimed to analyze the relationship between the incidence of severe dengue during the 2008 epidemic in Rio de Janeiro, Brazil, and socioeconomic indicators, as well as indicators of health service availability and previous circulation of the dengue virus serotype-3 (DENV-3). Methods In this ecological study, the units of analysis were the districts of Rio de Janeiro. The data were incorporated into generalized linear models, and the incidence of severe dengue in each district was the outcome variable. Results The districts with more cases of dengue fever in the 2001 epidemic and a higher percentage of residents who declared their skin color or race as black had higher incidence rates of severe dengue in the 2008 epidemic [incidence rate ratio (IRR)= 1.21; 95% confidence interval (95%CI)= 1.05-1.40 and IRR= 1.34; 95%CI= 1.16-1.54, respectively]. In contrast, the districts with Family Health Strategy (FHS) clinics were more likely to have lower incidence rates of severe dengue in the 2008 epidemic (IRR= 0.81; 95%CI= 0.70-0.93). Conclusions At the ecological level, our findings suggest the persistence of health inequalities in this region of Brazil that are possibly due to greater social vulnerability among the self-declared black population. Additionally, the protective effect of FHS clinics may be due to the ease of access to other levels of care in the health system or to a reduced vulnerability to dengue transmission that is afforded by local practices to promote health.
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The objective of this study was to compare the quality of life of women who survived breast cancer and women who have not had the disease, and to identify associated factors. It is cross-sectional study in which the comparison group includes survivors of breast cancer aged between 40 and 69 years. One hundred and fifty-four women were included, 70 with breast cancer and 84 without the disease. The SF-36 was used to evaluate quality of life. The chi-square test and multivariate linear models were used to compare the groups. The estimated mean physical and mental components were significantly better for the group who survived the disease (51.10 and 52.25, respectively) compared to the group without cancer (47.26 and 47.93, respectively). The study indicates that survivors of breast cancer had a better quality of life compared to women without the disease.
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Abstract OBJECTIVE To identify the factors associated with involuntary hospital admissions of technology-dependent children, in the municipality of Ribeirão Preto, São Paulo State, Brazil. METHOD A cross-sectional study, with a quantitative approach. After an active search, 124 children who qualified under the inclusion criteria, that is to say, children from birth to age 12, were identified. Data was collected in home visits to mothers or the people responsible for the children, through the application of a questionnaire. Analysis of the data followed the assumptions of the Generalized Linear Models technique. RESULTS 102 technology-dependent children aged between 6 months and 12 years participated in the study, of whom 57% were male. The average number of involuntary hospital admissions in the previous year among the children studied was 0.71 (±1.29). In the final model the following variables were significantly associated with the outcome: age (OR=0.991; CI95%=0.985-0.997), and the number of devices (OR=0.387; CI95%=0.219-0.684), which were characterized as factors of protection and quantity of medications (OR=1.532; CI95%=1.297-1.810), representing a risk factor for involuntary hospital admissions in technology-dependent children. CONCLUSION The results constitute input data for consideration of the process of care for technology-dependent children by supplying an explanatory model for involuntary hospital admissions for this client group.
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The effect of environment on development and survival of pupae of the necrophagous fly Ophyra albuquerquei Lopes (Diptera, Muscidae). Species of Ophyra Robineau-Desvoidy, 1830 are found in decomposing bodies, usually in fresh, bloated and decay stages. Ophyra albuquerquei Lopes, for example, can be found in animal carcasses. The influence of environmental factors has not been evaluated in puparia of O. albuquerquei. Thus, the focus of this work was motivated by the need for models to predict the development of a necrophagous insect as a function of abiotic factors. Colonies of O. albuquerquei were maintained in the laboratory to obtain pupae. On the tenth day of each month 200 pupae, divided equally into 10 glass jars, were exposed to the environment and checked daily for adult emergence of each sample. We concluded that the high survival rate observed suggested that the diets used for rearing the larvae and maintaining the adults were appropriate. Also, the data adjusted to robust generalized linear models and there were no interruptions of O. albuquerquei pupae development within the limits of temperatures studied in southern Rio Grande do Sul, given the high survival presented.
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Human activities in tropical forests are the main causes of forest fragmentation. According to historical factor in deforestation processes, forest remnants exhibit different sizes and shapes. The aim of the present study was to evaluate the dung beetle assemblage on fragments of different degree of sizes. Sampling was performed during rainy and dry season of 2010 in six fragments of Atlantic forest, using pitfall traps baited with excrement and carrion. Also, we used two larger fragments as control. We used General Linear Models to determine whether the fragments presented distinguished dung beetle abundance and richness. Analysis of Similarities and Non-Metric Multidimensional Scaling were used to determine whether the dung beetle assemblage was grouped according to species composition. A total of 3352 individuals were collected and 19 species were identified in the six fragments sampled. Dung beetle abundance exhibited a shift according to fragment size; however, richness did not change among fragments evaluated. Also, fragments sampled and the two controls exhibited distinct species composition. The distinction on abundance of dung beetles among fragments may be related to different amount of resource available in each one. It is likely that the dung beetle richness did not distinguish among the different fragments due to the even distribution of the mammal communities in these patches, and consequent equal dung diversity. We conclude that larger fragments encompass higher abundance of dung beetle and distinct species. However, for a clearer understanding of effects of fragmentation on dung beetles in Atlantic forest, studies evaluating narrower variations of larger fragments should be conducted.
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ABSTRACT Biomass is a fundamental measure for understanding the structure and functioning (e.g. fluxes of energy and nutrients in the food chain) of aquatic ecosystems. We aim to provide predictive models to estimate the biomass of Triplectides egleri Sattler, 1963, in a stream in Central Amazonia, based on body and case dimensions. We used body length, head-capsule width, interocular distance and case length and width to derive biomass estimations. Linear, exponential and power regression models were used to assess the relationship between biomass and body or case dimensions. All regression models used in the biomass estimation of T. egleri were significant. The best fit between biomass and body or case dimensions was obtained using the power model, followed by the exponential and linear models. Body length provided the best estimate of biomass. However, the dimensions of sclerotized structures (interocular distance and head-capsule width) also provided good biomass predictions, and may be useful in estimating biomass of preserved and/or damaged material. Case width was the dimension of the case that provided the best estimate of biomass. Despite the low relation, case width may be useful in studies that require low stress on individuals.
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The structural modeling of spatial dependence, using a geostatistical approach, is an indispensable tool to determine parameters that define this structure, applied on interpolation of values at unsampled points by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations in sampled data. The purpose of this study was to use diagnostic techniques in Gaussian spatial linear models in geostatistics to evaluate the sensitivity of maximum likelihood and restrict maximum likelihood estimators to small perturbations in these data. For this purpose, studies with simulated and experimental data were conducted. Results with simulated data showed that the diagnostic techniques were efficient to identify the perturbation in data. The results with real data indicated that atypical values among the sampled data may have a strong influence on thematic maps, thus changing the spatial dependence structure. The application of diagnostic techniques should be part of any geostatistical analysis, to ensure a better quality of the information from thematic maps.
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Soil penetration resistance is an important property that affects root growth and elongation and water movement in the soil. Since no-till systems tend to increase organic matter in the soil, the purpose of this study was to evaluate the efficiency with which soil penetration resistance is estimated using a proposed model based on moisture content, density and organic matter content in an Oxisol containing 665, 221 and 114 g kg-1 of clay, silt and sand respectively under annual no-till cropping, located in Londrina, Paraná State, Brazil. Penetration resistance was evaluated at random locations continually from May 2008 to February 2011, using an impact penetrometer to obtain a total of 960 replications. For the measurements, soil was sampled at depths of 0 to 20 cm to determine gravimetric moisture (G), bulk density (D) and organic matter content (M). The penetration resistance curve (PR) was adjusted using two non-linear models (PR = a Db Gc and PR' = a Db Gc Md), where a, b, c and d are coefficients of the adjusted model. It was found that the model that included M was the most efficient for estimating PR, explaining 91 % of PR variability, compared to 82 % of the other model.
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The control and regrowth after nicosulfuron reduced rate treatment of Johnsongrass (Sorghum halepense L. Pers.) populations, from seven Argentinean locations, were evaluated in pot experiments to assess if differential performance could limit the design and implementation of integrated weed management programs. Populations from humid regions registered a higher sensibility to reduced rates of nicosulfuron than populations from subhumid regions. This effect was visualised in the values of regression coefficient of the non-linear models (relating fresh weight to nicosulfuron rate), and in the time needed to obtain a 50% reduction of photosynthesis rate and stomatal conductance. The least leaf CO2 exchange of subhumid populations could result in a lower foliar absorption and translocation of nicosulfuron, thus producing less control and increasing their ability to sprout and produce new aerial biomass. The three populations from subhumid regions, with less sensibility to nicosulfuron rates, presented substantial difference in fresh weight, total rhizome length and number of rhizome nodes, when they were evaluated 20 week after treatment. In consequence, a substantial Johnsongrass re-infestation could occur, if rates below one-half of nicosulfuron labeled rate were used to control Johnsongrass in subhumid regions.
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The objective of this work was to assess the genetic diversity and population structure of wheat genotypes, to detect significant and stable genetic associations, as well as to evaluate the efficiency of statistical models to identify chromosome regions responsible for the expression of spike-related traits. Eight important spike characteristics were measured during five growing seasons in Serbia. A set of 30 microsatellite markers positioned near important agronomic loci was used to evaluate genetic diversity, resulting in a total of 349 alleles. The marker-trait associations were analyzed using the general linear and mixed linear models. The results obtained for number of allelic variants per locus (11.5), average polymorphic information content value (0.68), and average gene diversity (0.722) showed that the exceptional level of polymorphism in the genotypes is the main requirement for association studies. The population structure estimated by model-based clustering distributed the genotypes into six subpopulations according to log probability of data. Significant and stable associations were detected on chromosomes 1B, 2A, 2B, 2D, and 6D, which explained from 4.7 to 40.7% of total phenotypic variations. The general linear model identified a significantly larger number of marker-trait associations (192) than the mixed linear model (76). The mixed linear model identified nine markers associated to six traits.
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Response Surface Methodology (RSM) was applied to evaluate the chromatic features and sensory acceptance of emulsions that combine Soy Protein (SP) and red Guava Juice (GJ). The parameters analyzed were: instrumental color based on the coordinates a* (redness), b* (yellowness), L* (lightness), C* (chromaticity), h* (hue angle), visual color, acceptance, and appearance. The analyses of the results showed that GJ was responsible for the high measured values of red color, hue angle, chromaticity, acceptance, and visual color, whereas SP was the variable that increased the yellowness intensity of the assays. The redness (R²adj = 74.86%, p < 0.01) and hue angle (R²adj = 80.96%, p < 0.01) were related to the independent variables by linear models, while the sensory data (color and acceptance) could not be modeled due to a high variability. The models of yellowness, lightness, and chromaticity did not present lack of fit but presented adjusted determination coefficients bellow 70%. Notwithstanding, the linear correlations between sensory and instrumental data were not significant (p > 0.05) and low Pearson coefficients were obtained. The results showed that RSM is a useful tool to develop soy-based emulsions and model some chromatic features of guava-based emulsions through RSM.