PRODUCTION AND OPERATIONS MANAGEMENT, Issue 4 2003
JORIS M. KEIZERS
We present a tool to diagnose the behavior of planners in complex production processes and to establish improvement potential for the delivery performance by changing the planning behavior. Scientific literature on production control offers valuable knowledge, but the complexity of real-life processes makes it impossible to directly apply this knowledge in real-life. The presented tool identifies possible deficiencies in the current way of managing the business processes, by matching the scientific knowledge on order planning with data reflecting the real-life processes via logistic regression. A case study at a maintenance organization illustrates the diagnosis tool. [source]

Using Logistic Regression to Analyze the Sensitivity of PVA Models: a Comparison of Methods Based on African Wild Dog Models

CONSERVATION BIOLOGY, Issue 5 2001
Paul C. Cross
Standardized coefficients from the logistic regression analyses indicated that pup survival explained the most variability in the probability of extinction, regardless of whether or not the model incorporated density dependence. Adult survival and the standard deviation of pup survival were the next most important parameters in density-dependent simulations, whereas the severity and probability of catastrophe were more important during density-independent simulations. The inclusion of density dependence decreased the probability of extinction, but neither the abruptness nor the inclusion of density dependence were important model parameters. Results of both relative sensitivity analyses that altered each parameter by 10% of its range and life-stage-simulation analyses of deterministic matrix models supported the logistic regression results, indicating that pup survival and its variation were more important than other parameters. But both conventional sensitivity analysis of the stochastic model which changed each parameter by 10% of its mean value and elasticity analyses indicated that adult survival was more important than pup survival. We evaluated the advantages and disadvantages of using logistic regression to analyze the sensitivity of stochastic population viability models and conclude that it is a powerful method because it can address interactions among input parameters and can incorporate the range of parameter variability, although the standardized regression coefficients are not comparable between studies. Model structure, method of analysis, and parameter uncertainty affect the conclusions of sensitivity analyses. Therefore, rigorous model exploration and analysis should be conducted to understand model behavior and management implications. Resumen: Utilizamos la regresión logística como un método de análisis de sensibilidad par a un modelo de análisis de viabilidad poblacional de perros silvestres Africanos ( Lycaon pictus) y comparamos estos resultados con análisis de sensibilidad convencionales de modelos estocásticos y determinísticos. Coeficientes estandarizados de los análisis de regresión logística indicaron que la supervivencia de cachorros explicaba la mayor variabilidad en la probabilidad de extinción, independientemente de que el modelo incorporara la denso-dependencia. La supervivencia de adultos y la desviación estándar de la supervivencia de cachorros fueron los parámetros que siguieron en importancia en simulaciones de denso-dependencia, mientras que la severidad y la probabilidad de catástrofes fueron más importantes durante simulaciones denso-independientes. La inclusión de la denso dependencia disminuyó la probabilidad de extinción, pero ni la severidad ni la inclusión de denso-dependencia fueron parámetros importantes. Resultados de los análisis de sensibilidad relativa que alteraron cada parámetro en 10% de su rango y análisis de la simulación de etapas de vida de modelos matriciales determinísticos apoyaron los resultados de la regresión logística, indicando que la supervivencia de cachorros y su variación fueron más importantes que otros parámetros. Sin embargo, el análisis de sensibilidad convencional del modelo estocástico que cambiaron cada parámetro en 10% de su valor medio y el análisis de elasticidad indicaron que la supervivencia de adultos fue más importante que la supervivencia de cachorros. Evaluamos las ventajas y desventajas de utilizar la regresión logística para analizar la sensibilidad de modelos estocásticos de viabilidad poblacional y concluimos que es un método poderoso porque puede atender interacciones entre parámetros ingresados e incorporar el rango de variabilidad de parámetros, aunque los coeficientes de regresión estandarizada no son comparables entre estudios. La estructura del modelo, el método de análisis y la incertidumbre en los parámetros afectan las conclusiones del análisis de sensibilidad. Por lo tanto, se debe realizar una rigurosa exploración y análisis del modelo para entender su comportamiento y sus implicaciones en el manejo. [source]

Hierarchical Logistic Regression: Accounting for Multilevel Data in DIF Detection

JOURNAL OF EDUCATIONAL MEASUREMENT, Issue 3 2010
Brian F. French
The purpose of this study was to examine the performance of differential item functioning (DIF) assessment in the presence of a multilevel structure that often underlies data from large-scale testing programs. Analyses were conducted using logistic regression (LR), a popular, flexible, and effective tool for DIF detection. Data were simulated using a hierarchical framework, such as might be seen when examinees are clustered in schools, for example. Both standard and hierarchical LR (accounting for multilevel data) approaches to DIF detection were employed. Results highlight the differences in DIF detection rates when the analytic strategy matches the data structure. Specifically, when the grouping variable was within clusters, LR and HLR performed similarly in terms of Type I error control and power. However, when the grouping variable was between clusters, LR failed to maintain the nominal Type I error rate of .05. HLR was able to maintain this rate. However, power for HLR tended to be low under many conditions in the between cluster variable case. [source]

Recommendations for the Assessment and Reporting of Multivariable Logistic Regression in Transplantation Literature

AMERICAN JOURNAL OF TRANSPLANTATION, Issue 7 2010
A. C. Kalil
Multivariable logistic regression is an important method to evaluate risk factors and prognosis in solid organ transplant literature. We aimed to assess the quality of this method in six major transplantation journals. Eleven analytical criteria and four documentation criteria were analyzed for each selected article that used logistic regression. A total of 106 studies (6%) out of 1,701 original articles used logistic regression analyses from January 1, 2005 to January 1, 2006. The analytical criteria and their respective reporting percentage among the six journals were: Linearity (25%); Beta coefficient (48%); Interaction tests (19%); Main estimates (98%); Ovefitting prevention (84%); Goodness-of-fit (3.8%); Multicolinearity (4.7%); Internal validation (3.8%); External validation (8.5%). The documentation criteria were reported as follows: Selection of independent variables (73%); Coding of variables (9%); Fitting procedures (49%); Statistical program (65%). No significant differences were found among different journals or between general versus subspecialty journals with respect to reporting quality. We found that the report of logistic regression is unsatisfactory in transplantation journals. Because our findings may have major consequences for the care of transplant patients and for the design of transplant clinical trials, we recommend a practical solution for the use and reporting of logistic regression in transplantation journals. [source]

Evaluating the Ability of Tree-Based Methods and Logistic Regression for the Detection of SNP-SNP Interaction

ANNALS OF HUMAN GENETICS, Issue 3 2009
M. García-Magariños
Summary Most common human diseases are likely to have complex etiologies. Methods of analysis that allow for the phenomenon of epistasis are of growing interest in the genetic dissection of complex diseases. By allowing for epistatic interactions between potential disease loci, we may succeed in identifying genetic variants that might otherwise have remained undetected. Here we aimed to analyze the ability of logistic regression (LR) and two tree-based supervised learning methods, classification and regression trees (CART) and random forest (RF), to detect epistasis. Multifactor-dimensionality reduction (MDR) was also used for comparison. Our approach involves first the simulation of datasets of autosomal biallelic unphased and unlinked single nucleotide polymorphisms (SNPs), each containing a two-loci interaction (causal SNPs) and 98 ,noise' SNPs. We modelled interactions under different scenarios of sample size, missing data, minor allele frequencies (MAF) and several penetrance models: three involving both (indistinguishable) marginal effects and interaction, and two simulating pure interaction effects. In total, we have simulated 99 different scenarios. Although CART, RF, and LR yield similar results in terms of detection of true association, CART and RF perform better than LR with respect to classification error. MAF, penetrance model, and sample size are greater determining factors than percentage of missing data in the ability of the different techniques to detect true association. In pure interaction models, only RF detects association. In conclusion, tree-based methods and LR are important statistical tools for the detection of unknown interactions among true risk-associated SNPs with marginal effects and in the presence of a significant number of noise SNPs. In pure interaction models, RF performs reasonably well in the presence of large sample sizes and low percentages of missing data. However, when the study design is suboptimal (unfavourable to detect interaction in terms of e.g. sample size and MAF) there is a high chance of detecting false, spurious associations. [source]

Misclassification in Logistic Regression with Discrete Covariates

BIOMETRICAL JOURNAL, Issue 5 2003
Ori Davidov
Abstract We study the effect of misclassification of a binary covariate on the parameters of a logistic regression model. In particular we consider 2 × 2 × 2 tables. We assume that a binary covariate is subject to misclassification that may depend on the observed outcome. This type of misclassification is known as (outcome dependent) differential misclassification. We examine the resulting asymptotic bias on the parameters of the model and derive formulas for the biases and their approximations as a function of the odds and misclassification probabilities. Conditions for unbiased estimation are also discussed. The implications are illustrated numerically using a case control study. For completeness we briefly examine the effect of covariate dependent misclassification of exposures and of outcomes. [source]

Combining Multiple Biomarker Models in Logistic Regression

BIOMETRICS, Issue 2 2008
Zheng Yuan
Summary In medical research, there is great interest in developing methods for combining biomarkers. We argue that selection of markers should also be considered in the process. Traditional model/variable selection procedures ignore the underlying uncertainty after model selection. In this work, we propose a novel model-combining algorithm for classification in biomarker studies. It works by considering weighted combinations of various logistic regression models; five different weighting schemes are considered in the article. The weights and algorithm are justified using decision theory and risk-bound results. Simulation studies are performed to assess the finite-sample properties of the proposed model-combining method. It is illustrated with an application to data from an immunohistochemical study in prostate cancer. [source]

Variable Selection for Logistic Regression Using a Prediction-Focused Information Criterion

BIOMETRICS, Issue 4 2006
Gerda Claeskens
Summary In biostatistical practice, it is common to use information criteria as a guide for model selection. We propose new versions of the focused information criterion (FIC) for variable selection in logistic regression. The FIC gives, depending on the quantity to be estimated, possibly different sets of selected variables. The standard version of the FIC measures the mean squared error of the estimator of the quantity of interest in the selected model. In this article, we propose more general versions of the FIC, allowing other risk measures such as the one based on Lp error. When prediction of an event is important, as is often the case in medical applications, we construct an FIC using the error rate as a natural risk measure. The advantages of using an information criterion which depends on both the quantity of interest and the selected risk measure are illustrated by means of a simulation study and application to a study on diabetic retinopathy. [source]

A Goodness-of-Fit Test for Multinomial Logistic Regression

BIOMETRICS, Issue 4 2006
Jelle J. Goeman
Summary This article presents a score test to check the fit of a logistic regression model with two or more outcome categories. The null hypothesis that the model fits well is tested against the alternative that residuals of samples close to each other in covariate space tend to deviate from the model in the same direction. We propose a test statistic that is a sum of squared smoothed residuals, and show that it can be interpreted as a score test in a random effects model. By specifying the distance metric in covariate space, users can choose the alternative against which the test is directed, making it either an omnibus goodness-of-fit test or a test for lack of fit of specific model variables or outcome categories. [source]

Bayesian Multivariate Logistic Regression

BIOMETRICS, Issue 3 2004
Sean M. O'Brien
Summary Bayesian analyses of multivariate binary or categorical outcomes typically rely on probit or mixed effects logistic regression models that do not have a marginal logistic structure for the individual outcomes. In addition, difficulties arise when simple noninformative priors are chosen for the covariance parameters. Motivated by these problems, we propose a new type of multivariate logistic distribution that can be used to construct a likelihood for multivariate logistic regression analysis of binary and categorical data. The model for individual outcomes has a marginal logistic structure, simplifying interpretation. We follow a Bayesian approach to estimation and inference, developing an efficient data augmentation algorithm for posterior computation. The method is illustrated with application to a neurotoxicology study. [source]

Using Conditional Logistic Regression to Fit Proportional Odds Models to Interval Censored Data

BIOMETRICS, Issue 2 2000
Daniel Rabinowitz
Summary. An easily implemented approach to fitting the proportional odds regression model to interval-censored data is presented. The approach is based on using conditional logistic regression routines in standard statistical packages. Using conditional logistic regression allows the practitioner to sidestep complications that attend estimation of the baseline odds ratio function. The approach is applicable both for interval-censored data in settings in which examinations continue regardless of whether the event of interest has occurred and for current status data. The methodology is illustrated through an application to data from an AIDS study of the effect of treatment with ZDV + ddC versus ZDV alone on 50% drop in CD4 cell count from baseline level. Simulations are presented to assess the accuracy of the procedure. [source]

The functional impact of anxiety sensitivity in the chronically physically ill

DEPRESSION AND ANXIETY, Issue 4 2005
Sonya B. Norman Ph.D.
Abstract The symptoms and physical limitations resulting from chronic physical illness often diminish physical functioning. Comorbidity of chronic physical illness and an anxiety disorder is associated with greater impairment in functioning than chronic illness alone. One potential contributor to anxiety in the chronically ill is anxiety sensitivity (AS). The goal of this study was to explore the role of AS on functioning in the chronically ill. Participants were 267 primary care patients. Logistic regression showed that physical AS (but not social or psychological), controlling for age, gender, and negative affect, was associated with hypertension, heart disease, and high cholesterol (P<.01). Higher AS was associated with poorer vitality, mental functioning, and social functioning (P<.05). AS may be a correlate of poorer adjustment to chronic illness. Depression and Anxiety 21:154,160, 2005. © 2005 Wiley-Liss, Inc. [source]

Impulsive aggression in adults with attention-deficit/hyperactivity disorder

ACTA PSYCHIATRICA SCANDINAVICA, Issue 2 2010
J. H. Dowson
Dowson JH, Blackwell AD. Impulsive aggression in adults with attention-deficit/hyperactivity disorder. Objective:, DSM-IV criteria for attention-deficit/hyperactivity disorder (ADHD) include examples of ,impulsivity'. This term can refer to various dysfunctional behaviours, including some examples of aggressive behaviour. However, impulsive aggression is not included in the DSM-IV criteria for ADHD. The associations of impulsive aggression with ADHD were investigated. Method:, Seventy-three male adults with DSM-IV ADHD, and their informants, completed questionnaires. Impulsive aggression was assessed by ratings of two criteria for borderline personality disorder (BPD), involving hot temper and/or self-harm. Results:, Logistic regression indicated that features of DSM-IV ADHD were predictors of comorbid impulsive aggression. However, compared with ADHD features, verbal IQ and comorbid psychopathology were more strongly associated with impulsive aggression. Conclusion:, The findings support the inclusion of features of impulsive aggression, such as hot temper/short fuse, in the ADHD syndrome in adults. These overlap with features of BPD. The findings inform the selection of research samples. [source]

Irritability is associated with anxiety and greater severity, but not bipolar spectrum features, in major depressive disorder

ACTA PSYCHIATRICA SCANDINAVICA, Issue 4 2009
R. H. Perlis
Objective:, Irritability is common during major depressive episodes, but its clinical significance and overlap with symptoms of anxiety or bipolar disorder remains unclear. We examined clinical correlates of irritability in a confirmatory cohort of Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study participants with major depressive disorder (MDD). Method:, Logistic regression was used to identify features associated with presence of irritability on the clinician-rated Inventory of Depressive Symptomatology. Results:, Of 2307 study participants, 1067(46%) reported irritability at least half the time during the preceding week; they were more likely to be female, to be younger, to experience greater depression severity and anxiety, and to report poorer quality of life, prior suicide attempts and suicidal ideation. Bipolar spectrum features were not more common among those with irritability. Conclusion:, Irritable depression is not a distinct subtype of MDD, but irritability is associated with greater overall severity, anxiety comorbidity and suicidality. [source]

Depressive symptoms in the first year from diagnosis of Type 2 diabetes: results from the DESMOND trial

DIABETIC MEDICINE, Issue 8 2010
T. C. Skinner
Diabet. Med. 27, 965,967 (2010) Abstract Aims, To describe the course of depressive symptoms during the first year after diagnosis of Type 2 diabetes. Methods,Post hoc analysis of data from a randomized controlled trial of self-management education for 824 individuals newly diagnosed with Type 2 diabetes. Participants completed the Depression scale of the Hospital Anxiety and Depression Scale after diagnosis and at 4, 8 and 12 months follow-up. Participants also completed the Problem Areas in Diabetes scale at 8 and 12 months follow-up. We present descriptive statistics on prevalence and persistence of depressive symptoms. Logistic regression is used to predict possible depression cases, and multiple regression to predict depressive symptomatology. Results, The prevalence of depressive symptoms in individuals recently diagnosed with diabetes (18,22% over the year) was not significantly different from normative data for the general population (12%) in the UK. Over 20% of participants indicated some degrees of depressive symptoms over the first year of living with Type 2 diabetes; these were mostly transient episodes, with 5% (1% severe) reporting having depressive symptoms throughout the year. At 12 months post diagnosis, after controlling for baseline depressive symptoms, diabetes-specific emotional distress was predictive of depressive symptomatology. Conclusions, The increased prevalence of depressive symptoms in diabetes is not manifest until at least 1 year post diagnosis in this cohort. However, there are a significant number of people with persistent depressive symptoms in the early stages of diabetes, and diabetes-specific distress may be contributing to subsequent development of depressive symptoms in people with Type 2 diabetes. [source]

Affective and anxiety disorders in a German sample of diabetic patients: prevalence, comorbidity and risk factors

DIABETIC MEDICINE, Issue 3 2005
N. Hermanns
Abstract Aims The aims of this study were to examine (1) the prevalence of clinical and subclinical anxiety and affective disorders in a sample of diabetic patients attending a secondary care clinic in Germany and (2) risk factors associated with the occurrence of these disorders. Methods Four hundred and twenty diabetic patients (36.9% Type 1; 24.7% Type 2; 38.4% Type 2 with insulin) participated in a questionnaire-based screening survey. Those who screened positive received a diagnostic interview. Results Prevalence of clinical affective disorders was 12.6%, with an additional 18.8% of patients reporting depressive symptoms without fulfilling all criteria for a clinical affective disorder. The prevalence of anxiety disorders was 5.9%, with an additional 19.3% of patients reporting some anxiety symptoms. The comorbidity rate of affective and anxiety disorders was 1.8%, whereas 21.4% of the diabetic patients reported elevated affective as well as anxiety symptomatology. Logistic regression established demographic variables such as age, female gender and living alone as well as diabetes-specific parameters such as insulin treatment in Type 2 diabetes, hypoglycaemia problems and poor glycaemic control as risk factors for affective disorders. For anxiety symptoms female gender, younger age and Type 2 diabetes were significant independent variables. Conclusion The prevalence of affective disorders in diabetic patients was twofold higher than in the non-diabetic population, whereas prevalence for anxiety disorders was not increased. Analysis of risk factors can facilitate the identification of patients who are at a greater risk for these disorders. [source]

In-hospital breast feeding rates among women with gestational diabetes and pregestational Type 2 diabetes in South Auckland

DIABETIC MEDICINE, Issue 2 2005
D. Simmons
Abstract Aim To describe the uptake of breast feeding in mothers with either Type 2 diabetes or gestational diabetes (GDM) in a hospital serving a multiethnic community in South Auckland, New Zealand. Research design and methods A retrospective study of all women attending the Diabetes in Pregnancy clinic over a 4-year period was undertaken: 30 women had Type 2 diabetes and 373 GDM. Results Compared with mothers with GDM, mothers with Type 2 diabetes were less likely to breast feed in any way as the first feed (41.4% vs. 68.0%, P = 0.011) or at discharge (69.0% vs. 84.0%, P = 0.039). In the combined group, there were no differences in uptake of breast feeding by ethnicity, age, parity, body mass index, smoking or antenatal glycaemia, use of insulin or presence of hypertension. Breast feeding on discharge was associated with a higher APGAR score, breast feeding as the first feed (78.2% vs. 19.4%, P < 0.001) and lower rates of delivery by Caesarean section (17.0% vs. 31.8%, P = 0.006). Logistic regression showed breast feeding as the first feed, the major determinant for breast feeding on discharge. Conclusions Factors delaying breast feeding as the first feed are the major determinant of breast feeding on discharge. Strategies to increase breast feeding as the first feed among women with Type 2 diabetes, and those having a Caesarean section, may be useful in increasing the uptake of breast feeding in the longer term. [source]

Heterogeneity in young adult onset diabetes: aetiology alters clinical characteristics

DIABETIC MEDICINE, Issue 9 2002
K. R. Owen
Abstract Aims To describe the characteristics of hepatocyte nuclear factor (HNF) 1, mutation carriers diagnosed with diabetes after 25 years and compare them with young-onset Type 2 diabetic patients (YT2D) diagnosed at the same age. Subjects and methods We studied 44 (21 male, 23 female) patients with HNF-1, mutations diagnosed with diabetes at ages 25,45 years and 44 YT2D subjects matched for sex and age of diagnosis. Results Median age of onset of diabetes was 35 years in both groups. The HNF-1, group demonstrated: lower body mass index (25.1 vs. 30.7 kg/m2; P < 0.001) and lower fasting triglycerides (1.37 vs. 2.96 mmol/l; P = 0.001) with similar fasting cholesterol level. They had lower glycated haemoglobin A1c (7.3 vs. 8.5%; P = 0.015) despite greater duration of diabetes (24 vs. 16 years; P = 0.02) and less frequent treatment with insulin (21% vs. 55%; P = 0.002). They were less likely to be treated for hypertension (13.3% vs. 56.3%; P = 0.009). Importantly, no difference was observed in reported parental history of diabetes between the two groups (65.9% vs. 63.6%; P = 0.92). Logistic regression showed that triglyceride levels and presence of anti-hypertensive treatment were the most important independent variables. Conclusions Patients with HNF-1, mutations may present with diabetes as young adults between the ages of 25,45 years. In this age range a wide differential diagnosis of diabetes is observed. Conventional criteria of age of onset and family history will not differentiate HNF-1, mutation carriers from YT2D subjects in this age range, but features of the metabolic syndrome, in particular fasting triglycerides and hypertension, are helpful. In patients diagnosed before 45 years without features of insulin resistance the diagnosis of HNF-1, should be considered. [source]

Rheological determinants of red blood cell aggregation in diabetic patients in relation to their metabolic control

DIABETIC MEDICINE, Issue 2 2002
K. Elishkevitz
Abstract Aims To determine whether increased red blood cell adhesiveness/aggregation in diabetic patients is related to the extent of their metabolic control. Methods We measured erythrocyte adhesiveness/aggregation in a group of 85 adult patients with diabetes mellitus by using citrated venous whole blood and a simple slide test. The erythrocyte adhesiveness/aggregation was determined by measuring the size of the spaces that are formed between the aggregated erythrocytes. We divided the patients into those with either low or high erythrocyte adhesiveness/aggregation values. Results The erythrocyte adhesiveness/aggregation values of the two groups differed significantly in terms of their fibrinogen concentration, erythrocyte sedimentation rate, high sensitive C-reactive protein (CRP), total cholesterol and triglyceride concentrations. There was no difference between the two groups regarding the concentrations of HbA1c. Logistic regression was applied to construct a model to predict the belonging of a patient in the low or high erythrocyte adhesiveness/aggregation group. A linear regression was applied to construct a model to predict the erythrocyte adhesiveness/aggregation values. Both models turned out to include gender, age, fibrinogen, triglyceride, retinopathy, coronary artery disease and age and gender interaction. Neither HbA1c nor CRP entered the models. Conclusions The degree of erythrocyte adhesiveness/aggregation and several variables of the acute-phase response in patients with diabetes mellitus are not directly related to the degree of metabolic control as evaluated by means of HbA1c concentration. Diabetic patients might benefit from rheological or anti-inflammatory interventions regardless of their metabolic control. [source]

Range-wide patterns of greater sage-grouse persistence

DIVERSITY AND DISTRIBUTIONS, Issue 6 2008
Cameron L. Aldridge
ABSTRACT Aim, Greater sage-grouse (Centrocercus urophasianus), a shrub-steppe obligate species of western North America, currently occupies only half its historical range. Here we examine how broad-scale, long-term trends in landscape condition have affected range contraction. Location, Sagebrush biome of the western USA. Methods, Logistic regression was used to assess persistence and extirpation of greater sage-grouse range based on landscape conditions measured by human population (density and population change), vegetation (percentage of sagebrush habitat), roads (density of and distance to roads), agriculture (cropland, farmland and cattle density), climate (number of severe and extreme droughts) and range periphery. Model predictions were used to identify areas where future extirpations can be expected, while also explaining possible causes of past extirpations. Results, Greater sage-grouse persistence and extirpation were significantly related to sagebrush habitat, cultivated cropland, human population density in 1950, prevalence of severe droughts and historical range periphery. Extirpation of sage-grouse was most likely in areas having at least four persons per square kilometre in 1950, 25% cultivated cropland in 2002 or the presence of three or more severe droughts per decade. In contrast, persistence of sage-grouse was expected when at least 30 km from historical range edge and in habitats containing at least 25% sagebrush cover within 30 km. Extirpation was most often explained (35%) by the combined effects of peripherality (within 30 km of range edge) and lack of sagebrush cover (less than 25% within 30 km). Based on patterns of prior extirpation and model predictions, we predict that 29% of remaining range may be at risk. Main Conclusions, Spatial patterns in greater sage-grouse range contraction can be explained by widely available landscape variables that describe patterns of remaining sagebrush habitat and loss due to cultivation, climatic trends, human population growth and peripherality of populations. However, future range loss may relate less to historical mechanisms and more to recent changes in land use and habitat condition, including energy developments and invasions by non-native species such as cheatgrass (Bromus tectorum) and West Nile virus. In conjunction with local measures of population performance, landscape-scale predictions of future range loss may be useful for prioritizing management and protection. Our results suggest that initial conservation efforts should focus on maintaining large expanses of sagebrush habitat, enhancing quality of existing habitats, and increasing habitat connectivity. [source]

Spread and current potential distribution of an alien grass, Eragrostis lehmanniana Nees, in the southwestern USA: comparing historical data and ecological niche models

DIVERSITY AND DISTRIBUTIONS, Issue 5 2006
Heather Schussman
ABSTRACT The potential distribution of alien species in a novel habitat often is difficult to predict because factors limiting species distributions may be unique to the new locale. Eragrostis lehmanniana is a perennial grass purposely introduced from South Africa to Arizona, USA in the 1930s; by the 1980s, it had doubled its extent. Based on environmental characteristics associated with its introduced and native range, researchers believed that E. lehmanniana had reached the limits of its distribution by the early 1990s. We collected data on E. lehmanniana locations from various land management agencies throughout Arizona and western New Mexico and found new records that indicate that E. lehmanniana has continued to spread. Also, we employed two modelling techniques to determine the current potential distribution and to re-investigate several environmental variables related to distribution. Precipitation and temperature regimes similar to those indicated by past research were the most important variables influencing model output. The potential distribution of E. lehmanniana mapped by both models was 71,843 km2 and covers a large portion of southeastern and central Arizona. Logistic regression (LR) predicted a potential distribution of E. lehmanniana more similar to this species current distribution than GARP based on average temperature, precipitation, and grassland species composition and recorded occurrences. Results of a cross-validation assessment and extrinsic testing showed that the LR model performed as well or better than GARP based on sensitivity, specificity, and kappa indices. [source]

Influence of the Unbelted Rear-seat Passenger on Driver Mortality: "The Backseat Bullet"

ACADEMIC EMERGENCY MEDICINE, Issue 2 2005
James Mayrose PhD
Abstract Objectives: This study examined whether unrestrained left rear-seat passengers increase the risk of death of belted drivers involved in serious crashes with at least one fatality. Methods: The information from every fatal crash in the United States between 1995 and 2001 was analyzed. Variables such as point of impact, restraint use, seat position, vehicle type, occupant age, gender, and injury severity were extracted from the Fatality Analysis Reporting System. Results: The odds of death for a belted driver seated directly in front of an unrestrained passenger in a serious head-on crash was 2.27 times higher (95% confidence interval [CI] = 1.94 to 2.66) than if seated in front of a restrained passenger. In contrast, a belted driver seated in front of an unrestrained passenger in a driver-side lateral-impact crash had no increase in mortality over a driver with a restrained rear-seat passenger (odds ratio, 0.8; 95% CI = 0.6 to 1.06). Logistic regression showed that passenger restraint, point of impact, vehicle type, passenger age, and driver age had a statistically significant influence on the outcome (death) of belted drivers. Adjusting for confounders (other than point of impact), the odds of fatality for a belted driver in a head-on crash was 2.28 times greater (95% CI = 1.93 to 2.7) with an unbelted rear-seat passenger. The unbelted rear-seat passenger also had an increased risk of death (odds ratio, 2.71; 95% CI = 2.44 to 3.01) when compared with restrained rear-seat passengers. Conclusions: Unrestrained rear-seat passengers place themselves and their driver at great risk of fatal injury when involved in a crash. [source]

Using sensation seeking to target adolescents for substance use interventions

ADDICTION, Issue 3 2010
James D. Sargent
ABSTRACT Aims This study examines the predictive validity of sensation seeking as a predictor of adolescent substance use, in order to optimize targeting for substance use prevention programs. Design Longitudinal study. Setting Random-digit dial telephone survey. Participants A total of 6522 US adolescents aged 10,14 years at baseline, resurveyed at 8-month intervals for three subsequent waves. Measurements Two outcomes were assessed,onset of binge drinking (more than five drinks in a short time) and established smoking (>100 cigarettes life-time). Sensation seeking level was assessed at baseline. Logistic regression was used to predict onset of substance use at any follow-up wave as a function of sensation seeking. The receiver operating characteristics curve was used to illustrate how well sensation seeking predicted substance use as a function of different cut-off points for defining high sensation seeking, and area under the receiver operating characteristics curve (AROC) was the metric of predictive validity. Findings Of 5834 participants with one or more follow-up assessments, 5634 reported no binge drinking and 5802 were not established smokers at baseline, of whom 717 (12.7% of 5634) reported binge drinking and 144 (2.5% of 5802) reported established smoking at one or more follow-up interviews. Sensation seeking predicted binge drinking moderately well [AROC = 0.71 (95% confidence interval 0.69, 0.73)] and was a significantly better predictor of established smoking onset [AROC = 0.80 (0.76, 0.83)]. For binge drinking, predictive validity was significantly lower in blacks; for established smoking it was significantly higher for Hispanics. Implications for two targeting interventions are discussed. Conclusions Sensation seeking works moderately well at identifying adolescents at risk for onset of binge drinking and established smoking. This study offers a guide for determining the appropriate targeting cut-off value, based on intervention efficacy, costs and risks. [source]

Family members of people with alcohol or drug dependence: health problems and medical cost compared to family members of people with diabetes and asthma

ADDICTION, Issue 2 2009
G. Thomas Ray
ABSTRACT Aims To compare the medical costs and prevalence of health conditions of family members of people with an alcohol or drug dependence (AODD) diagnosis to family members of people with diabetes and asthma. Setting Kaiser Permanente of Northern California (KPNC). Participants Family members of people diagnosed with AODD between 2002 and 2005, and matched samples of family members of people diagnosed with diabetes and asthma. Measurements Logistic regression was used to determine whether the family members of people with AODD were more likely to be diagnosed with medical conditions than family members of people with diabetes or asthma. Multivariate models were used to compare health services cost and utilization of AODD family members and diabetes and asthma family members. Analyses were for the year before, and 2 years following, initial diagnosis of the index person. Findings In the year before initial diagnosis of the index person, AODD family members were more likely to be diagnosed with substance use disorders, depression and trauma than diabetes or asthma family members. AODD family members had higher total health-care costs than diabetes family members in the year following, and the second year following, the index date ($217 and $293, respectively). AODD family members had higher total health-care costs than asthma family members in the year before, and second year following, the index date ($104 and $269, respectively). Conclusions AODD family members have unique patterns of health conditions compared to the diabetes and asthma family members and have similar, or higher, health-care cost and utilization. [source]

Estimating the probability of bird mortality from pesticide sprays on the basis of the field study record

ENVIRONMENTAL TOXICOLOGY & CHEMISTRY, Issue 7 2002
Pierre Mineau
Abstract The outcome of avian field studies was examined to model the likelihood of mortality. The data were divided into clusters reflecting the type of pesticide application and bird guilds present on site. Logistic regression was used to model the probability of a bird kill. Four independent variables were tested for their explanatory power: a variable reflecting acute oral toxicity and application rate; a variable reflecting the relative oral to dermal toxicity of the pesticides; Henry's law constant; and a variable reflecting possible avoidance of contaminated food items, the hazard factor (HF). All variables except for HF significantly improved model prediction. The relative dermal to oral toxicity, especially, was shown to have a major influence on field outcome and clearly must be incorporated into future avian risk assessments. The probability of avian mortality could be calculated from a number of current pesticide applications and the conclusion was made that avian mortality occurs regularly and frequently in agricultural fields. [source]

The teratogenic risk of antiepileptic drug polytherapy

EPILEPSIA, Issue 5 2010
Frank J. E. Vajda
Summary Purpose:, To compare the risks of fetal malformation during pregnancy associated with antiepileptic drug (AED) polytherapy and monotherapy. Methods:, Statistical analysis of malformation rate and antiepileptic drug exposure data from the Australian Register of Antiepileptic Drugs in Pregnancy, and from the literature. Results:, The calculated relative risk (RR) value for AED polytherapy compared with monotherapy was below 1.0 in only 3 of 14 literature publications. In the register, at 1 year postnatally there were fetal malformations in 5.32% of 282 AED polytherapy pregnancies, and in 7.84% of 791 AED monotherapy pregnancies, an RR of 0.68 [95% confidence interval (CI) 0.39,1.17). For pregnancies exposed to valproate, the RR of fetal malformation (0.39, 95% CI 0.20,0.89) was lower in polytherapy (7.26%) than in monotherapy (17.9%); the difference did not depend on valproate dosage. The RR values for fetal malformation were not significantly different for AED polytherapy and monotherapy when valproate was not involved. Logistic regression suggested that coadministration of lamotrigine may have reduced the malformation risk from valproate. Discussion:, The fetal hazard of AED polytherapy relative to monotherapy may depend more on the degree of exposure to valproate than on the fact of polytherapy per se. Coadministration with lamotrigine may lower the fetal risk of valproate therapy. [source]

Understanding herb and dietary supplement use in patients with epilepsy

EPILEPSIA, Issue 8 2009
Kitti Kaiboriboon
Summary Objective:, To determine the prevalence of herb and dietary supplement use and to provide a comprehensive analysis of factors influencing the use of these products in patients with epilepsy. Methods:, We performed a cross-sectional study using self-administered questionnaires in a selected group of patients who were receiving care at a tertiary epilepsy center. Logistic regression was used to measure the association between the demographic variables and herb and dietary supplement use. In addition, we performed a MEDLINE search for each of the herb and dietary products used by our patients to determine the effect of these products on seizures and on their potential for interactions with other drugs metabolized by the liver. Results:, One hundred eighty-seven patients completed the survey. Fifty-six percent of this group of patients with epilepsy used herbs and dietary supplements at the time of the survey. A considerable portion (71%) of these patients reported the use of these products to their physician, and most of them relied on their physicians as the primary source of information. Most of the patients used dietary supplement for health promotion rather than to specifically benefit their epilepsy condition. Approximately one-third of patients used herb or dietary supplements that had the potential to increase seizures (16%) or to interact with hepatically metabolized drugs (19%). The most powerful independent predictors of herb and dietary supplement use were partial epilepsy [odds ratio (OR) 3.36; 95% confidence interval (CI) 1.27,8.88] and Caucasian race (OR 3.55; 95% CI 1.11,11.34). Conclusion:, Patients with epilepsy commonly used dietary supplements along with their antiepileptic medications. The majority of these patients used herb and dietary supplements for health promotion rather than because of dissatisfaction with conventional treatment. It is important that physicians involved in the care of patients with epilepsy routinely inquire about the use of dietary supplements and that they make use of reliable resources to assess the safety of these products with regard to modification of seizure risk and the potential for interactions with antiepileptic drugs. [source]

Sociodemographic disparities in epilepsy care: Results from the Houston/New York City health care use and outcomes study

EPILEPSIA, Issue 5 2009
Charles E. Begley
Summary Purpose:, The purpose of this study was to identify sociodemographic disparities in health care use among epilepsy patients receiving care at different sites and the extent to which the disparities persisted after adjusting for patient characteristics and site of care. Methods:, Three months of health care use data were obtained from baseline interviews of approximately 560 patients at four sites. One-half of the patients were from a Houston site and two NYC sites that serve predominantly low-income, minority, publicly insured, or uninsured patients. The other half were at the remaining site in Houston that serves a more balanced racial/ethnic and higher sociodemographic population. Differences in general and specialist visits, hospital emergency room (ER) care, and hospitalizations were associated with race/ethnicity, income, and coverage. Logistic regression was used to assess the extent to which the differences persisted when adjusting for individual patient characteristics and site of care. Results:, Compared to whites, blacks and Hispanics had higher rates of generalist visits [odds ratio (OR) = 5.3 and 4.9, p < 0.05), ER care (OR = 3.1 and 2.9, p < 0.05) and hospitalizations (OR = 5.4 and 6.2, p < 0.05), and lower rates of specialist visits (OR = 0.3 and 0.4, p < 0.05). A similar pattern was found related to patient income and coverage. The magnitude and significance of the disparities persisted when adjusting for individual characteristics but decreased substantially or were eliminated when site of care was added to the model. Discussion:, There are sociodemographic disparities in health care for people with epilepsy that are largely explained by differences in where patients receive care. [source]

Improved Prediction of Nonepileptic Seizures with Combined MMPI and EEG Measures

EPILEPSIA, Issue 3 2000
D. Storzbach
Summary: Purpose: Nonepileptic seizures (NESs) are frequently mistaken for epileptic seizures (ESs). Improved detection of patients with NESs could lead to more appropriate treatment and medical cost savings. Previous studies have shown the MMPI/MMPI-2 to be a useful predictor of NES. We hypothesized that combining the MMPI-2 with a physiologic predictor of epilepsy (routine EEG; rEEG) would result in enhanced prediction of NES. Methods: Consecutive patients undergoing CCTV-EEG monitoring underwent rEEG evaluation and completed an MMPI-2. Patients were subsequently classified as having epilepsy (n = 91) or NESs (n = 76) by using standardized criteria. Logistic regression was used to predict seizure type classification. Results: Overall classification accuracy was 74% for rEEG, 71% for MMPI-2 Hs scale, and 77% for MMPI-2 Hy scale. The model that best predicted diagnosis included rEEG, MMPI-2, and number of years since the first spell, resulting in an overall classification accuracy of 86%. Conclusions: The high accuracy achieved by the model suggests that it may be useful for screening candidates for diagnostic telemetry. [source]

Association of type of sport and performance level with anatomical site of orthopaedic injury diagnosis

EQUINE VETERINARY JOURNAL, Issue S36 2006
R. C. MURRAY
Summary Reason for performing study: Although anecdotal reports of increased orthopaedic injury risk in equine sports exist, there is little scientific evidence to support this. Objectives: To test whether horses undertaking a single competitive sport have increased risk of specific injuries compared to those used for general purpose riding (GP); and whether injury type varies with sport category and performance level. Methods: Data from 1069 records of horses undergoing orthopaedic evaluation (1998,2003) and meeting inclusion criteria were reviewed. Sport category (GP, showjumping, dressage, eventing, racing), level (nonelite or elite) and diagnosis were recorded. Effects of sport category and level on probability of a specific diagnosis were assessed using chisquared tests. Logistic regression was used to determine which competitive sports and levels increased risk of injury compared with GP. Results: Overall there was a significant effect of sport category and level on diagnosis (P<0.0001). There was significant difference between anatomical site injured and sport category (P<0.0001); a high risk of forelimb superficial digital flexor tendon injury in elite eventing (P<0.0001) and elite showjumping (P=0.02); distal deep digital flexor tendon (DDFT) injury in elite showjumping (P=0.002); and hindlimb suspensory ligament injury in elite (P<0.0001) and nonelite (P=0.001) dressage. There was a low risk of tarsal injury in elite eventing (P=0.01) and proximal DDFT injury in dressage (P = 0.01). Conclusions: Horses competing in different sports are predisposed to specific injuries; particular sports may increase the risk of injury at certain anatomical sites; and the type and site of injury may reflect the type and level of performance. Potential relevance: These findings could guide clinicians in the diagnosis of sport related injuries. [source]