103 resultados para Negative Binomial Regression Model (NBRM)
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Abstract OBJECTIVE Evaluating the evidence of hypertension prevalence among indigenous populations in Brazil through a systematic review and meta-analysis. METHODS A search was performed by two reviewers, with no restriction of date or language in the databases of PubMed, LILACS, SciELO, Virtual Health Library and Capes Journal Portal. Also, a meta-regression model was designed in which the last collection year of each study was used as a moderating variable. RESULTS 23 articles were included in the review. No hypertension was found in indigenous populations in 10 studies, and its prevalence was increasing and varied, reaching levels of up to 29.7%. Combined hypertension prevalence in Indigenous from the period of 1970 to 2014 was 6.2% (95% CI, 3.1% - 10.3%). In the regression, the value of the odds ratio was 1.12 (95% CI, 1.07 - 1.18; p <0.0001), indicating a 12% increase every year in the probability of an indigenous person presenting hypertension. CONCLUSION There has been a constant increase in prevalence despite the absence of hypertension in about half of the studies, probably due to changes in cultural, economic and lifestyle habits, resulting from indigenous interaction with non-indigenous society.
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The Brazilian East coast was intensely affected by deforestation, which drastically cut back the original biome. The possible impacts of this process on water resources are still unknown. The purpose of this study was an evaluation of the impacts of deforestation on the main water balance components of the Galo creek watershed, in the State of Espírito Santo, on the East coast of Brazil. Considering the real conditions of the watershed, the SWAT model was calibrated with data from 1997 to 2000 and validated for the period between 2001 and 2003. The calibration and validation processes were evaluated by the Nash-Sutcliffe efficiency coefficient and by the statistical parameters (determination coefficient, slope coefficient and F test) of the regression model adjusted for estimated and measured flow data. After calibration and validation of the model, new simulations were carried out for three different land use scenarios: a scenario in compliance with the law (C1), assuming the preservation of PPAs (permanent preservation areas); an optimistic scenario (C2), which considers the watershed to be almost entirely covered by native vegetation; and a pessimistic scenario (C3), in which the watershed would be almost entirely covered by pasture. The scenarios C1, C2 and C3 represent a soil cover of native forest of 76, 97 and 0 %, respectively. The results were compared with the simulation, considering the real scenario (C0) with 54 % forest cover. The Nash-Sutcliffe coefficients were 0.65 and 0.70 for calibration and validation, respectively, indicating satisfactory results in the flow simulation. A mean reduction of 10 % of the native forest cover would cause a mean annual increase of approximately 11.5 mm in total runoff at the watershed outlet. Reforestation would ensure minimum flows in the dry period and regulate the maximum flow of the main watercourse of the watershed.
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ABSTRACT Diffuse reflectance spectroscopy (DRS) is a fast and cheap alternative for soil clay, but needs further investigation to assess the scope of application. The purpose of the study was to develop a linear regression model to predict clay content from DRS data, to classify the soils into three textural classes, similar to those defined by a regulation of the Brazilian Ministry of Agriculture, Livestock and Food Supply. The DRS data of 412 soil samples, from the 0.0-0.5 m layer, from different locations in the state of Rio Grande do Sul, Brazil, were measured at wavelengths of 350 to 2,500 nm in the laboratory. The fitting of the linear regression model developed to predict soil clay content from the DRS data was based on a R2 value of 0.74 and 0.75, with a RMSE of 7.82 and 8.51 % for the calibration and validation sets, respectively. Soil texture classification had an overall accuracy of 79.0 % (calibration) and 80.9 % (validation). The heterogeneity of soil samples affected the performance of the prediction models. Future studies should consider a previous classification of soil samples in different groups by soil type, parent material and/or sampling region.
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Objective The objective of the present study was to evaluate current radiographic parameters designed to investigate adenoid hypertrophy and nasopharyngeal obstruction, and to present an alternative radiographic assessment method. Materials and Methods In order to do so, children (4 to14 years old) who presented with nasal obstruction or oral breathing complaints were submitted to cavum radiographic examination. One hundred and twenty records were evaluated according to quantitative radiographic parameters, and data were correlated with a gold-standard videonasopharyngoscopic study, in relation to the percentage of choanal obstruction. Subsequently, a regression analysis was performed in order to create an original model so the percentage of the choanal obstruction could be predicted. Results The quantitative parameters demonstrated moderate, if not weak correlation with the real percentage of choanal obstruction. The regression model (110.119*A/N) demonstrated a satisfactory ability to “predict” the actual percentage of choanal obstruction. Conclusion Since current adenoid quantitative radiographic parameters present limitations, the model presented by the present study might be considered as an alternative assessment method in cases where videonasopharyngoscopic evaluation is unavailable.
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A model based on chemical structure was developed for the accurate prediction of octanol/water partition coefficient (K OW) of polychlorinated biphenyls (PCBs), which are molecules of environmental interest. Partial least squares (PLS) was used to build the regression model. Topological indices were used as molecular descriptors. Variable selection was performed by Hierarchical Cluster Analysis (HCA). In the modeling process, the experimental K OW measured for 30 PCBs by thin-layer chromatography - retention time (TLC-RT) has been used. The developed model (Q² = 0,990 and r² = 0,994) was used to estimate the log K OW values for the 179 PCB congeners whose K OW data have not yet been measured by TLC-RT method. The results showed that topological indices can be very useful to predict the K OW.
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The objective of this paper was to evaluate the potential of neural networks (NN) as an alternative method to the basic epidemiological approach to describe epidemics of coffee rust. The NN was developed from the intensities of coffee (Coffea arabica) rust along with the climatic variables collected in Lavras-MG between 13 February 1998 and 20 April 2001. The NN was built with climatic variables that were either selected in a stepwise regression analysis or by the Braincel® system, software for NN building. Fifty-nine networks and 26 regression models were tested. The best models were selected based on small values of the mean square deviation (MSD) and of the mean prediction error (MPE). For the regression models, the highest coefficients of determination (R²) were used. The best model developed with neural networks had an MSD of 4.36 and an MPE of 2.43%. This model used the variables of minimum temperature, production, relative humidity of the air, and irradiance 30 days before the evaluation of disease. The best regression model was developed from 29 selected climatic variables in the network. The summary statistics for this model were: MPE=6.58%, MSE=4.36, and R²=0.80. The elaborated neural networks from a time series also were evaluated to describe the epidemic. The incidence of coffee rust at four previous fortnights resulted in a model with MPE=4.72% and an MSD=3.95.
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In Cerrado soils under grazing, changes occur in physical attributes, such as increased density, decreasing on the size of water stable aggregates, and macroporosity reduction. Thus, the aim of this study was to study the effect of compaction on the establishment of two forages. It was adopted a completely randomized design with three replications, in 2 x 4 factorial design, and two forages (Xaraés grass and Marandu grass), and four levels of compaction (soil densities of 1.0, 1.2, 1.4, and 1.6 Mg m-3). The following variables were evaluated 48 days after sowing: tiller population, plant height, dry matter production of shoots and components, leaf and stem, as well as the root dry mass. The stem dry mass decreased with soil density in a similar manner for both forages. It was observed that the leaf dry mass and shoots dry mass of Xaraés grass remained constant in the levels of soil compaction, not adjusting to any regression model. The establishment of Xaraés grass has not been negatively affected by compaction, which may be suitable for situations where there may be layers that restrict the growth of different forages.
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This experiment was conducted in Lavras - state of Minas Gerais (MG), Brazil, in a protected environment, and aims to estimate the irrigation depths that maximize productivity and economic returns in the cultivation of asparagus bean and analyze the economic viability of irrigation management. The experimental delineation was randomized blocks with five treatments and four replications. The treatments consisted of five drip irrigation depths: 40, 70, 100, 130 and 160% of water replacement depth up to field capacity. The depths of water that maximize productivity and economic returns were obtained from the regression model adjusted to productivity data, cost of product relations and water cost. The economic viability was achieved on the benefit/cost ratio basis. The depth with the maximum economic return was estimated in 434.4mm, with a productivity of 35,160.6kg ha-1, which is economically viable for the cultivation of asparagus bean, with a expected profitability of R$ 1.70 for every real invested.
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Some models have been developed using agrometeorological and remote sensing data to estimate agriculture production. However, it is expected that the use of SAR images can improve their performance. The main objective of this study was to estimate the sugarcane production using a multiple linear regression model which considers agronomic data and ALOS/PALSAR images obtained from 2007/08, 2008/09 and 2009/10 cropping seasons. The performance of models was evaluated by coefficient of determination, t-test, Willmott agreement index (d), random error and standard error. The model was able to explain 79%, 12% and 74% of the variation in the observed productions of the 2007/08, 2008/09 and 2009/10 cropping seasons, respectively. Performance of the model for the 2008/09 cropping season was poor because of the occurrence of a long period of drought in that season. When the three seasons were considered all together, the model explained 66% of the variation. Results showed that SAR-based yield prediction models can contribute and assist sugar mill technicians to improve such estimates.
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Objective: to assess predictors of intra-abdominal injuries in blunt trauma patients admitted without abdominal pain or abnormalities on the abdomen physical examination. Methods: We conducted a retrospective analysis of trauma registry data, including adult blunt trauma patients admitted from 2008 to 2010 who sustained no abdominal pain or abnormalities on physical examination of the abdomen at admission and were submitted to computed tomography of the abdomen and/or exploratory laparotomy. Patients were assigned into: Group 1 (with intra-abdominal injuries) or Group 2 (without intra-abdominal injuries). Variables were compared between groups to identify those significantly associated with the presence of intra-abdominal injuries, adopting p<0.05 as significant. Subsequently, the variables with p<0.20 on bivariate analysis were selected to create a logistic regression model using the forward stepwise method. Results: A total of 268 cases met the inclusion criteria. Patients in Group I were characterized as having significantly (p<0.05) lower mean AIS score for the head segment (1.0±1.4 vs. 1.8±1.9), as well as higher mean AIS thorax score (1.6±1.7 vs. 0.9±1.5) and ISS (25.7±14.5 vs. 17,1±13,1). The rate of abdominal injuries was significantly higher in run-over pedestrians (37.3%) and in motorcyclists (36.0%) (p<0.001). The resultant logistic regression model provided 73.5% accuracy for identifying abdominal injuries. The variables included were: motorcyclist accident as trauma mechanism (p<0.001 - OR 5.51; 95%CI 2.40-12.64), presence of rib fractures (p<0.003 - OR 3.00; 95%CI 1.47-6.14), run-over pedestrian as trauma mechanism (p=0.008 - OR 2.85; 95%CI 1.13-6.22) and abnormal neurological physical exam at admission (p=0.015 - OR 0.44; 95%CI 0.22-0.85). Conclusion Intra-abdominal injuries were predominantly associated with trauma mechanism and presence of chest injuries.
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The aim of this study was evaluate the risk factors for Mycobacterium avium subsp. paratuberculosis (Map) seroprevalence in sheep in the North of Portugal. The effects on seroprevalence of several variables such as individual characteristics, management practices, farm characteristics, animal health, and available veterinary services were evaluated. This information was then used in a multivariable logistic regression model in order to identify risk factors for Map seropositivity. Univariable analysis was used to screen the variables used in the logistic regression model. Variables that showed p values of <0.15 were retained for the multivariable analysis. Fifteen variables were associated with paratuberculosis in univariable analysis. The multivariable logistic regression model identified a number of variables as risk factors for seropositivity like sheep pure local and/or a cross of a local breed (OR=2.02), herd size with 31-60 head (OR=2.14), culling during the Spring-Summer season (OR=1.69) and the use of an anti-parasitic treatment such as Ivermectin as the only anti-parasitic medication (OR=5.60). Potential risk factors identified in this study support current recommendations for the control of paratuberculosis.
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Few data are available on the prevalence and risk factors of Chlamydophila abortus infection in goats in Brazil. A cross-sectional study was carried out to determine the flock-level prevalence of C. abortus infection in goats from the semiarid region of the Paraíba State, Northeast region of Brazil, as well as to identify risk factors associated with the infection. Flocks were randomly selected and a pre-established number of female goats > 12 mo old were sampled in each of these flocks. A total of 975 serum samples from 110 flocks were collected, and structured questionnaire focusing on risk factors for C. abortus infection was given to each farmer at the time of blood collection. For the serological diagnosis the complement fixation test (CFT) using C. abortus S26/3 strain as antigen was performed. The flock-level factors for C. abortus prevalence were tested using multivariate logistic regression model. Fifty-five flocks out of 110 presented at least one seropositive animal with an overall prevalence of 50.0% (95%; CI: 40.3%, 59.7%). Ninety-one out of 975 dairy goats examined were seropositive with titers >32, resulting in a frequency of 9.3%. Lend buck for breeding (odds ratio = 2.35; 95% CI: 1.04-5.33) and history of abortions (odds ratio = 3.06; 95% CI: 1.37-6.80) were associated with increased flock prevalence.
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Emex australis and E. spinosa are significant weed species in wheat and other crops. Information on the extent of competition of the Emex species will be helpful to access yield losses in wheat. Field experiments were conducted to quantify the interference of tested weed densities each as single or mixture of both at 1:1 on their growth and yield, wheat yield components and wheat grain yield losses in two consecutive years. Dry weight of both weed species increased from 3-6 g m-2 with every additional plant of weed, whereas seed number and weight per plant decreased with increasing density of either weed. Both weed species caused considerable decrease in yield components like spike bearing tillers, number of grains per spike, 1000-grain weight of wheat with increasing density population of the weeds. Based on non-linear hyperbolic regression model equation, maximum yield loss at asymptotic weed density was estimated to be 44 and 62% with E. australis, 56 and 70% with E. spinosa and 63 and 72% with mixture of both species at 1:1 during both year of study, respectively. It was concluded that E. spinosa has more competition effects on wheat crop as compared to E. australis.
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We studied the ability of patients not experienced in the use of peak expiratory flow meters to assess the severity of their asthma exacerbations and compared it to the assessment of experienced clinicians. We also evaluated which data of physical examination and medical history are used by physicians to subjectively evaluate the severity of asthma attacks. Fifty-seven adult patients (15 men and 42 women, with a mean (± SD) age of 37.3 ± 14.5 years and 24.0 ± 17.9 years of asthma symptoms) with asthma exacerbations were evaluated in a University Hospital Emergency Department. Patients and physicians independently evaluated the severity of the asthma attack using a linear scale. Patient score, physician score and forced expiratory volume at the first second (FEV1) were correlated with history and physical examination variables, and were also considered as dependent variables in multiple linear regression models. FEV1 correlated significantly with the physician score (rho = 0.42, P = 0.001), but not with patient score (rho = 0.03; P = 0.77). Use of neck accessory muscles, expiratory time and wheezing intensity were the explanatory variables in the FEV1 regression model and were also present in the physician score model. We conclude that physicians evaluate asthma exacerbation severity better than patients and that physician's scoring of asthma severity correlated significantly with objective measures of airway obstruction (FEV1). Some variables (the use of neck accessory muscles, expiratory time and wheezing intensity) persisted as explanatory variables in physician score and FEV1 regression models, and should be emphasized in medical schools and emergency settings.
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The objective of the present study was to investigate clinical, echocardiographic and electrocardiographic (12-lead resting ECG, 24-h ambulatory ECG monitoring and signal-averaged ECG (SAECG)) parameters in subjects with chronic Chagas' disease in a long-term follow-up as prognostic markers for adverse outcomes. Fifty adult outpatients (34 to 74 years old, 31 females) staged according to Los Andes class I, II or III and complaining of palpitation were enrolled in a longitudinal study. SAECG was analyzed in time and frequency domains and the endpoint was a composite of cardiac death and ventricular tachycardia. During a follow-up of 84.2 ± 39.0 months, 34.0% of the patients developed adverse outcomes (9 cardiac deaths and 11 episodes of ventricular tachycardia). After optimal dichotomization, in a stepwise multivariate Cox-hazard regression model, apical aneurysm (HR = 3.7; 95% CI = 1.2-1.3; P = 0.02), left ventricular ejection fraction <62% (HR = 4.60; 95% CI = 1.39-15.24; P = 0.01) and incidence of ventricular premature contractions >614 per 24 h (hazard ratio = 6.1; 95% CI = 1.7-22.6; P = 0.006) were independent predictors of the composite endpoint. Although a high frequency content in SAECG demonstrated association with the presence of left ventricular dysfunction and myocardial fibrosis, its predictive value for the composite endpoint was not significant. Apical aneurysms, reduced left ventricular function and a high incidence of ventricular ectopic beats over a 24-h period have a strong predictive value for a composite endpoint of cardiac death and ventricular tachycardia in subjects with chronic Chagas' disease.