25 resultados para generalized linear-models

em Scielo Saúde Pública - SP


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OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study. Daily figures for hospital admissions of children aged < 6, and daily concentrations of air pollutants (PM10, SO2, NO2, O3 and CO) were analyzed in the Região da Grande Vitória, ES, Southeastern Brazil, from January 2005 to December 2010. For statistical analysis, two techniques were combined: Poisson regression with generalized additive models and principal model component analysis. Those analysis techniques complemented each other and provided more significant estimates in the estimation of relative risk. The models were adjusted for temporal trend, seasonality, day of the week, meteorological factors and autocorrelation. In the final adjustment of the model, it was necessary to include models of the Autoregressive Moving Average Models (p, q) type in the residuals in order to eliminate the autocorrelation structures present in the components. RESULTS For every 10:49 μg/m3 increase (interquartile range) in levels of the pollutant PM10 there was a 3.0% increase in the relative risk estimated using the generalized additive model analysis of main components-seasonal autoregressive – while in the usual generalized additive model, the estimate was 2.0%. CONCLUSIONS Compared to the usual generalized additive model, in general, the proposed aspect of generalized additive model − principal component analysis, showed better results in estimating relative risk and quality of fit.

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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 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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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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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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Type 2 diabetes increases the risk of cardiovascular mortality and these patients, even without previous myocardial infarction, run the risk of fatal coronary heart disease similar to non-diabetic patients surviving myocardial infarction. There is evidence showing that particulate matter air pollution is associated with increases in cardiopulmonary morbidity and mortality. The present study was carried out to evaluate the effect of diabetes mellitus on the association of air pollution with cardiovascular emergency room visits in a tertiary referral hospital in the city of São Paulo. Using a time-series approach, and adopting generalized linear Poisson regression models, we assessed the effect of daily variations in PM10, CO, NO2, SO2, and O3 on the daily number of emergency room visits for cardiovascular diseases in diabetic and non-diabetic patients from 2001 to 2003. A semi-parametric smoother (natural spline) was adopted to control long-term trends, linear term seasonal usage and weather variables. In this period, 45,000 cardiovascular emergency room visits were registered. The observed increase in interquartile range within the 2-day moving average of 8.0 µg/m³ SO2 was associated with 7.0% (95%CI: 4.0-11.0) and 20.0% (95%CI: 5.0-44.0) increases in cardiovascular disease emergency room visits by non-diabetic and diabetic groups, respectively. These data indicate that air pollution causes an increase of cardiovascular emergency room visits, and that diabetic patients are extremely susceptible to the adverse effects of air pollution on their health conditions.

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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 the coverage of a cervical cancer screening program in a city with a high incidence of the disease in addition to the factors associated with non-adherence to the current preventive program.METHODS A cross-sectional study based on household surveys was conducted. The sample was composed of women between 25 and 59 years of age of the city of Boa Vista, RR, Northern Brazil who were covered by the cervical cancer screening program. The cluster sampling method was used. The dependent variable was participation in a women’s health program, defined as undergoing at least one Pap smear in the 36 months prior to the interview; the explanatory variables were extracted from individual data. A generalized linear model was used.RESULTS 603 women were analyzed, with an mean age of 38.2 years (SD = 10.2). Five hundred and seventeen women underwent the screening test, and the prevalence of adherence in the last three years was up to 85.7% (95%CI 82.5;88.5). A high per capita household income and recent medical consultation were associated with the lower rate of not being tested in multivariate analysis. Disease ignorance, causes, and prevention methods were correlated with chances of non-adherence to the screening system; 20.0% of the women were reported to have undergone opportunistic and non-routine screening.CONCLUSIONS The informed level of coverage is high, exceeding the level recommended for the control of cervical cancer. The preventive program appears to be opportunistic in nature, particularly for the most vulnerable women (with low income and little information on the disease). Studies on the diagnostic quality of cervicovaginal cytology and therapeutic schedules for positive cases are necessary for understanding the barriers to the control of cervical cancer.

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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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Observational and experimental studies have shown that increased concealment of bird nests reduces nest predation rates. The objective of the present study was to evaluate differences in predation rates between two experimental manipulations of artificial ground nests (i.e., clearing an area around the artificial nest or leaving it as natural as possible), and test whether environmental variables also affected nest predation in an undisturbed area of Amazonian forest in eastern Brazil. A generalized linear model was used to examine the influence of five variables (manipulation type, perpendicular distance from the main trail, total basal area of trees surrounding the nest site, understorey density, and liana quantity) on nest predation rates. Model results, showed that manipulation type was the only variable that significantly affected nest predation rates. Thus, to avoid systematic biases, the influence of nest site manipulation must be taken into consideration when conducting experiments with artificial nests.

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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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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.