861 resultados para Linear-regression
Resumo:
Developing a novel technique for the efficient, noninvasive clinical evaluation of bone microarchitecture remains both crucial and challenging. The trabecular bone score (TBS) is a new gray-level texture measurement that is applicable to dual-energy X-ray absorptiometry (DXA) images. Significant correlations between TBS and standard 3-dimensional (3D) parameters of bone microarchitecture have been obtained using a numerical simulation approach. The main objective of this study was to empirically evaluate such correlations in anteroposterior spine DXA images. Thirty dried human cadaver vertebrae were evaluated. Micro-computed tomography acquisitions of the bone pieces were obtained at an isotropic resolution of 93μm. Standard parameters of bone microarchitecture were evaluated in a defined region within the vertebral body, excluding cortical bone. The bone pieces were measured on a Prodigy DXA system (GE Medical-Lunar, Madison, WI), using a custom-made positioning device and experimental setup. Significant correlations were detected between TBS and 3D parameters of bone microarchitecture, mostly independent of any correlation between TBS and bone mineral density (BMD). The greatest correlation was between TBS and connectivity density, with TBS explaining roughly 67.2% of the variance. Based on multivariate linear regression modeling, we have established a model to allow for the interpretation of the relationship between TBS and 3D bone microarchitecture parameters. This model indicates that TBS adds greater value and power of differentiation between samples with similar BMDs but different bone microarchitectures. It has been shown that it is possible to estimate bone microarchitecture status derived from DXA imaging using TBS.
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BACKGROUND: Several studies have reported increased levels of inflammatory biomarkers in chronic kidney disease (CKD), but data from the general population are sparse. In this study, we assessed levels of the inflammatory markers C-reactive protein (hsCRP), tumor necrosis factor α (TNF-α), interleukin (IL)-1β and IL-6 across all ranges of renal function. METHODS: We conducted a cross-sectional study in a random sample of 6,184 Caucasian subjects aged 35-75 years in Lausanne, Switzerland. Serum levels of hsCRP, TNF-α, IL-6, and IL-1β were measured in 6,067 participants (98.1%); serum creatinine-based estimated glomerular filtration rate (eGFR(creat), CKD-EPI formula) was used to assess renal function, and albumin/creatinine ratio on spot morning urine to assess microalbuminuria (MAU). RESULTS: Higher serum levels of IL-6, TNF-α and hsCRP and lower levels of IL-1β were associated with a lower renal function, CKD (eGFR(creat) <60 ml/min/1.73 m(2); n = 283), and MAU (n = 583). In multivariate linear regression analysis adjusted for age, sex, hypertension, smoking, diabetes, body mass index, lipids, antihypertensive and hypolipemic therapy, only log-transformed TNF-α remained independently associated with lower renal function (β -0.54 ±0.19). In multivariate logistic regression analysis, higher TNF-α levels were associated with CKD (OR 1.17; 95% CI 1.01-1.35), whereas higher levels of IL-6 (OR 1.09; 95% CI 1.02-1.16) and hsCRP (OR 1.21; 95% CI 1.10-1.32) were associated with MAU. CONCLUSION: We did not confirm a significant association between renal function and IL-6, IL-1β and hsCRP in the general population. However, our results demonstrate a significant association between TNF-α and renal function, suggesting a potential link between inflammation and the development of CKD. These data also confirm the association between MAU and inflammation.
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The aim of this paper is twofold. First, we study the determinants of economic growth among a wide set of potential variables for the Spanish provinces (NUTS3). Among others, we include various types of private, public and human capital in the group of growth factors. Also,we analyse whether Spanish provinces have converged in economic terms in recent decades. Thesecond objective is to obtain cross-section and panel data parameter estimates that are robustto model speci¯cation. For this purpose, we use a Bayesian Model Averaging (BMA) approach.Bayesian methodology constructs parameter estimates as a weighted average of linear regression estimates for every possible combination of included variables. The weight of each regression estimate is given by the posterior probability of each model.
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In the areas where irrigated rice is grown in the south of Brazil, few studies have been carried out to investigate the spatial variability structure of soil properties and to establish new forms of soil management as well as determine soil corrective and fertilizer applications. In this sense, this study had the objective of evaluating the spatial variability of chemical, physical and biological soil properties in a lowland area under irrigated rice cultivation in the conventional till system. For this purpose, a 10 x 10 m grid of 100 points was established, in an experimental field of the Embrapa Clima Temperado, in the County of Capão do Leão, State of Rio Grande do Sul. The spatial variability structure was evaluated by geostatistical tools and the number of subsamples required to represent each soil property in future studies was calculated using classical statistics. Results showed that the spatial variability structure of sand, silt, SMP index, cation exchange capacity (pH 7.0), Al3+ and total N properties could be detected by geostatistical analysis. A pure nugget effect was observed for the nutrients K, S and B, as well as macroporosity, mean weighted diameter of aggregates, and soil water storage. The cross validation procedure, based on linear regression and the determination coefficient, was more efficient to evaluate the quality of the adjusted mathematical model than the degree of spatial dependence. It was also concluded that the combination of classical with geostatistics can in many cases simplify the soil sampling process without losing information quality.
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In this study, we assessed whether the white-coat effect (difference between office and daytime blood pressure (BP)) is associated with nondipping (absence of BP decrease at night). Data were available in 371 individuals of African descent from 74 families selected from a population-based hypertension register in the Seychelles Islands and in 295 Caucasian individuals randomly selected from a population-based study in Switzerland. We used standard multiple linear regression in the Swiss data and generalized estimating equations to account for familial correlations in the Seychelles data. The prevalence of systolic and diastolic nondipping (<10% nocturnal BP decrease) and white-coat hypertension (WCH) was respectively 51, 46, and 4% in blacks and 33, 37, and 7% in whites. When white coat effect and nocturnal dipping were taken as continuous variables (mm Hg), systolic (SBP) and diastolic BP (DBP) dipping were associated inversely and independently with white-coat effect (P < 0.05) in both populations. Analogously, the difference between office and daytime heart rate was inversely associated with the difference between daytime and night-time heart rate in the two populations. These results did not change after adjustment for potential confounders. The white-coat effect is associated with BP nondipping. The similar associations between office-daytime values and daytime-night-time values for both BP and heart rate suggest that the sympathetic nervous system might play a role. Our findings also further stress the interest, for clinicians, of assessing the presence of a white-coat effect as a means to further identify patients at increased cardiovascular risk and guide treatment accordingly.
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There is evidence that obesity-related disorders are increased among people with depression. Variation in the FTO (fat mass and obesity associated) gene has been shown to contribute to common forms of human obesity. This study aimed to investigate the genetic influence of polymorphisms in FTO in relation to body mass index (BMI) in two independent samples of major depressive disorder (MDD) cases and controls. We analysed 88 polymorphisms in the FTO gene in a clinically ascertained sample of 2442 MDD cases and 809 controls (Radiant Study). In all, 8 of the top 10 single-nucleotide polymorphisms (SNPs) showing the strongest associations with BMI were followed-up in a population-based cohort (PsyCoLaus Study) consisting of 1292 depression cases and 1690 controls. Linear regression analyses of the FTO variants and BMI yielded 10 SNPs significantly associated with increased BMI in the depressive group but not the control group in the Radiant sample. The same pattern was found in the PsyCoLaus sample. We found a significant interaction between genotype and affected status in relation to BMI for seven SNPs in Radiant (P<0.0057), with PsyCoLaus giving supportive evidence for five SNPs (P-values between 0.03 and 0.06), which increased in significance when the data were combined in a meta-analysis. This is the first study investigating FTO and BMI within the context of MDD, and the results indicate that having a history of depression moderates the effect of FTO on BMI. This finding suggests that FTO is involved in the mechanism underlying the association between mood disorders and obesity.
Resumo:
The aim of this paper is twofold. First, we study the determinants of economic growth among a wide set of potential variables for the Spanish provinces (NUTS3). Among others, we include various types of private, public and human capital in the group of growth factors. Also,we analyse whether Spanish provinces have converged in economic terms in recent decades. Thesecond objective is to obtain cross-section and panel data parameter estimates that are robustto model speci¯cation. For this purpose, we use a Bayesian Model Averaging (BMA) approach.Bayesian methodology constructs parameter estimates as a weighted average of linear regression estimates for every possible combination of included variables. The weight of each regression estimate is given by the posterior probability of each model.
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En este documento se ilustra de un modo práctico, el empleo de tres instrumentos que permiten al actuario definir grupos arancelarios y estimar premios de riesgo en el proceso que tasa la clase para el seguro de no vida. El primero es el análisis de segmentación (CHAID y XAID) usado en primer lugar en 1997 por UNESPA en su cartera común de coches. El segundo es un proceso de selección gradual con el modelo de regresión a base de distancia. Y el tercero es un proceso con el modelo conocido y generalizado de regresión linear, que representa la técnica más moderna en la bibliografía actuarial. De estos últimos, si combinamos funciones de eslabón diferentes y distribuciones de error, podemos obtener el aditivo clásico y modelos multiplicativos
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Knowledge on the factors influencing water erosion is fundamental for the choice of the best land use practices. Rainfall, expressed by rainfall erosivity, is one of the most important factors of water erosion. The objective of this study was to determine rainfall erosivity and the return period of rainfall in the Coastal Plains region, near Aracruz, a town in the state of Espírito Santo, Brazil, based on available data. Rainfall erosivity was calculated based on historic rainfall data, collected from January 1998 to July 2004 at 5 min intervals, by automatic weather stations of the Aracruz Cellulose S.A company. A linear regression with individual rainfall and erosivity data was fit to obtain an equation that allowed data extrapolation to calculate individual erosivity for a 30-year period. Based on this data the annual average rainfall erosivity in Aracruz was 8,536 MJ mm ha-1 h-1 yr-1. Of the total annual rainfall erosivity 85 % was observed in the most critical period October to March. Annual erosive rains accounted for 38 % of the events causing erosion, although the runoff volume represented 88 % of the total. The annual average rainfall erosivity return period was estimated to be 3.4 years.
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Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.
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In a recent paper A. S. Johal and D. J. Dunstan [Phys. Rev. B 73, 024106 (2006)] have applied multivariate linear regression analysis to the published data of the change in ultrasonic velocity with applied stress. The aim is to obtain the best estimates for the third-order elastic constants in cubic materials. From such an analysis they conclude that uniaxial stress data on metals turns out to be nearly useless by itself. The purpose of this comment is to point out that by a proper analysis of uniaxial stress data it is possible to obtain reliable values of third-order elastic constants in cubic metals and alloys. Cu-based shape memory alloys are used as an illustrative example.
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Endotoxin causes an inflammation at the bronchial and alveolar level. The inflammation-induced increase in permeability of the bronchoalveolar epithelial barrier is supposed to cause a leakage of pneumoproteins. Therefore, their concentrations are expected to increase in the bloodstream.This study aimed at examining the association between occupational exposure to endotoxin and a serum pneumoprotein, surfactant protein A, to look for nonoccupational factors capable of confounding this association, and examine the relation between surfactant protein A and spirometry. There were 369 control subjects, 325 wastewater workers, and 84 garbage collectors in the study. Exposure to endotoxin was assessed through personal sampling and the Limulus amebocytes lysate assay. Surfactant protein A was determined by an in house sandwich enzyme-linked immunosorbent assay (ELISA) in 697 subjects. Clinical and smoking history were ascertained and spirometry carried out according to American Thoracic Society criteria. Multiple linear regression was used for statistical analysis. Exposure was fairly high during some tasks in wastewater workers but did not influence surfactant protein A. Surfactant protein A was lower in asthmatics. Interindividual variability was large. No correlation with spirometry was found. Endotoxin has no effect on surfactant protein A at these endotoxin levels and serum surfactant protein A does not correlate with spirometry. The decreased surfactant protein A secretion in asthmatics requires further study.
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This report summarizes research conducted at Iowa State University on behalf of the Iowa Department of Transportation, focusing on the volumetric state of hot-mix asphalt (HMA) mixtures as they transition from stable to unstable configurations. This has raditionally been addressed during mix design by meeting a minimum voids in the mineral aggregate (VMA) requirement, based solely upon the nominal maximum aggregate size without regard to other significant aggregate-related properties. The goal was to expand the current specification to include additional aggregate properties, e.g., fineness modulus, percent crushed fine and coarse aggregate, and their interactions. The work was accomplished in three phases: a literature review, extensive laboratory testing, and statistical analysis of test results. The literature review focused on the history and development of the current specification, laboratory methods of identifying critical mixtures, and the effects of other aggregate-related factors on critical mixtures. The laboratory testing involved three maximum aggregate sizes (19.0, 12.5, and 9.5 millimeters), three gradations (coarse, fine, and dense), and combinations of natural and manufactured coarse and fine aggregates. Specimens were compacted using the Superpave Gyratory Compactor (SGC), conventionally tested for bulk and maximum theoretical specific gravities and physically tested using the Nottingham Asphalt Tester (NAT) under a repeated load confined configuration to identify the transition state from sound to unsound. The statistical analysis involved using ANOVA and linear regression to examine the effects of identified aggregate factors on critical state transitions in asphalt paving mixtures and to develop predictive equations. The results clearly demonstrate that the volumetric conditions of an HMA mixture at the stable unstable threshold are influenced by a composite measure of the maximum aggregate size and gradation and by aggregate shape and texture. The currently defined VMA criterion, while significant, is seen to be insufficient by itself to correctly differentiate sound from unsound mixtures. Under current specifications, many otherwise sound mixtures are subject to rejection solely on the basis of failing to meet the VMA requirement. Based on the laboratory data and statistical analysis, a new paradigm to volumetric mix design is proposed that explicitly accounts for aggregate factors (gradation, shape, and texture).
Resumo:
PURPOSE: Awareness of being monitored can influence participants' habitual physical activity (PA) behavior. This reactivity effect may threaten the validity of PA assessment. Reports on reactivity when measuring the PA of children and adolescents have been inconsistent. The aim of this study was to investigate whether PA outcomes measured by accelerometer devices differ from measurement day to measurement day and whether the day of the week and the day on which measurement started influence these differences. METHODS: Accelerometer data (counts per minute [cpm]) of children and adolescents (n = 2081) pooled from eight studies in Switzerland with at least 10 h of daily valid recording were investigated for effects of measurement day, day of the week, and start day using mixed linear regression. RESULTS: The first measurement day was the most active day. Counts per minute were significantly higher than on the second to the sixth day, but not on the seventh day. Differences in the age-adjusted means between the first and consecutive days ranged from 23 to 45 cpm (3.6%-7.1%). In preschoolchildren, the differences almost reached 10%. The start day significantly influenced PA outcome measures. CONCLUSIONS: Reactivity to accelerometer measurement of PA is likely to be present to an extent of approximately 5% on the first day and may introduce a relevant bias to accelerometer-based studies. In preschoolchildren, the effects are larger than those in elementary and secondary schoolchildren. As the day of the week and the start day significantly influence PA estimates, researchers should plan for at least one familiarization day in school-age children and randomly assign start days.
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BACKGROUND & AIMS: Standardized instruments are needed to assess the activity of eosinophilic esophagitis (EoE) and to provide end points for clinical trials and observational studies. We aimed to develop and validate a patient-reported outcome (PRO) instrument and score, based on items that could account for variations in patient assessments of disease severity. We also evaluated relationships between patient assessment of disease severity and EoE-associated endoscopic, histologic, and laboratory findings. METHODS: We collected information from 186 patients with EoE in Switzerland and the United States (69.4% male; median age, 43 y) via surveys (n = 135), focus groups (n = 27), and semistructured interviews (n = 24). Items were generated for the instruments to assess biologic activity based on physician input. Linear regression was used to quantify the extent to which variations in patient-reported disease characteristics could account for variations in patient assessment of EoE severity. The PRO instrument was used prospectively in 153 adult patients with EoE (72.5% male; median age, 38 y), and validated in an independent group of 120 patients with EoE (60.8% male; median age, 40.5 y). RESULTS: Seven PRO factors that are used to assess characteristics of dysphagia, behavioral adaptations to living with dysphagia, and pain while swallowing accounted for 67% of the variation in patient assessment of disease severity. Based on statistical consideration and patient input, a 7-day recall period was selected. Highly active EoE, based on endoscopic and histologic findings, was associated with an increase in patient-assessed disease severity. In the validation study, the mean difference between patient assessment of EoE severity (range, 0-10) and PRO score (range, 0-8.52) was 0.15. CONCLUSIONS: We developed and validated an EoE scoring system based on 7 PRO items that assess symptoms over a 7-day recall period. Clinicaltrials.gov number: NCT00939263.