Evaluation of the comprehensive palatability of Japanese sake paired with dishes by multiple regression analysis based on subdomains.

PubMed

Nakamura, Ryo; Nakano, Kumiko; Tamura, Hiroyasu; Mizunuma, Masaki; Fushiki, Tohru; Hirata, Dai

2017-08-01

Many factors contribute to palatability. In order to evaluate the palatability of Japanese alcohol sake paired with certain dishes by integrating multiple factors, here we applied an evaluation method previously reported for palatability of cheese by multiple regression analysis based on 3 subdomain factors (rewarding, cultural, and informational). We asked 94 Japanese participants/subjects to evaluate the palatability of sake (1st evaluation/E1 for the first cup, 2nd/E2 and 3rd/E3 for the palatability with aftertaste/afterglow of certain dishes) and to respond to a questionnaire related to 3 subdomains. In E1, 3 factors were extracted by a factor analysis, and the subsequent multiple regression analyses indicated that the palatability of sake was interpreted by mainly the rewarding. Further, the results of attribution-dissections in E1 indicated that 2 factors (rewarding and informational) contributed to the palatability. Finally, our results indicated that the palatability of sake was influenced by the dish eaten just before drinking.

Application of Semiparametric Spline Regression Model in Analyzing Factors that In uence Population Density in Central Java

NASA Astrophysics Data System (ADS)

Sumantari, Y. D.; Slamet, I.; Sugiyanto

2017-06-01

Semiparametric regression is a statistical analysis method that consists of parametric and nonparametric regression. There are various approach techniques in nonparametric regression. One of the approach techniques is spline. Central Java is one of the most densely populated province in Indonesia. Population density in this province can be modeled by semiparametric regression because it consists of parametric and nonparametric component. Therefore, the purpose of this paper is to determine the factors that in uence population density in Central Java using the semiparametric spline regression model. The result shows that the factors which in uence population density in Central Java is Family Planning (FP) active participants and district minimum wage.

Logistic Regression and Path Analysis Method to Analyze Factors influencing Students’ Achievement

NASA Astrophysics Data System (ADS)

Noeryanti, N.; Suryowati, K.; Setyawan, Y.; Aulia, R. R.

2018-04-01

Students' academic achievement cannot be separated from the influence of two factors namely internal and external factors. The first factors of the student (internal factors) consist of intelligence (X1), health (X2), interest (X3), and motivation of students (X4). The external factors consist of family environment (X5), school environment (X6), and society environment (X7). The objects of this research are eighth grade students of the school year 2016/2017 at SMPN 1 Jiwan Madiun sampled by using simple random sampling. Primary data are obtained by distributing questionnaires. The method used in this study is binary logistic regression analysis that aims to identify internal and external factors that affect student’s achievement and how the trends of them. Path Analysis was used to determine the factors that influence directly, indirectly or totally on student’s achievement. Based on the results of binary logistic regression, variables that affect student’s achievement are interest and motivation. And based on the results obtained by path analysis, factors that have a direct impact on student’s achievement are students’ interest (59%) and students’ motivation (27%). While the factors that have indirect influences on students’ achievement, are family environment (97%) and school environment (37).

Using Linear Regression To Determine the Number of Factors To Retain in Factor Analysis and the Number of Issues To Retain in Delphi Studies and Other Surveys.

ERIC Educational Resources Information Center

Jurs, Stephen; And Others

The scree test and its linear regression technique are reviewed, and results of its use in factor analysis and Delphi data sets are described. The scree test was originally a visual approach for making judgments about eigenvalues, which considered the relationships of the eigenvalues to one another as well as their actual values. The graph that is…

INNOVATIVE INSTRUMENTATION AND ANALYSIS OF THE TEMPERATURE MEASUREMENT FOR HIGH TEMPERATURE GASIFICATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seong W. Lee

During this reporting period, the literature survey including the gasifier temperature measurement literature, the ultrasonic application and its background study in cleaning application, and spray coating process are completed. The gasifier simulator (cold model) testing has been successfully conducted. Four factors (blower voltage, ultrasonic application, injection time intervals, particle weight) were considered as significant factors that affect the temperature measurement. The Analysis of Variance (ANOVA) was applied to analyze the test data. The analysis shows that all four factors are significant to the temperature measurements in the gasifier simulator (cold model). The regression analysis for the case with the normalizedmore » room temperature shows that linear model fits the temperature data with 82% accuracy (18% error). The regression analysis for the case without the normalized room temperature shows 72.5% accuracy (27.5% error). The nonlinear regression analysis indicates a better fit than that of the linear regression. The nonlinear regression model's accuracy is 88.7% (11.3% error) for normalized room temperature case, which is better than the linear regression analysis. The hot model thermocouple sleeve design and fabrication are completed. The gasifier simulator (hot model) design and the fabrication are completed. The system tests of the gasifier simulator (hot model) have been conducted and some modifications have been made. Based on the system tests and results analysis, the gasifier simulator (hot model) has met the proposed design requirement and the ready for system test. The ultrasonic cleaning method is under evaluation and will be further studied for the gasifier simulator (hot model) application. The progress of this project has been on schedule.« less

[Logistic regression model of noninvasive prediction for portal hypertensive gastropathy in patients with hepatitis B associated cirrhosis].

PubMed

Wang, Qingliang; Li, Xiaojie; Hu, Kunpeng; Zhao, Kun; Yang, Peisheng; Liu, Bo

2015-05-12

To explore the risk factors of portal hypertensive gastropathy (PHG) in patients with hepatitis B associated cirrhosis and establish a Logistic regression model of noninvasive prediction. The clinical data of 234 hospitalized patients with hepatitis B associated cirrhosis from March 2012 to March 2014 were analyzed retrospectively. The dependent variable was the occurrence of PHG while the independent variables were screened by binary Logistic analysis. Multivariate Logistic regression was used for further analysis of significant noninvasive independent variables. Logistic regression model was established and odds ratio was calculated for each factor. The accuracy, sensitivity and specificity of model were evaluated by the curve of receiver operating characteristic (ROC). According to univariate Logistic regression, the risk factors included hepatic dysfunction, albumin (ALB), bilirubin (TB), prothrombin time (PT), platelet (PLT), white blood cell (WBC), portal vein diameter, spleen index, splenic vein diameter, diameter ratio, PLT to spleen volume ratio, esophageal varices (EV) and gastric varices (GV). Multivariate analysis showed that hepatic dysfunction (X1), TB (X2), PLT (X3) and splenic vein diameter (X4) were the major occurring factors for PHG. The established regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4. The accuracy of model for PHG was 79.1% with a sensitivity of 77.2% and a specificity of 80.8%. Hepatic dysfunction, TB, PLT and splenic vein diameter are risk factors for PHG and the noninvasive predicted Logistic regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4.

Meta-regression analysis of commensal and pathogenic Escherichia coli survival in soil and water.

PubMed

Franz, Eelco; Schijven, Jack; de Roda Husman, Ana Maria; Blaak, Hetty

2014-06-17

The extent to which pathogenic and commensal E. coli (respectively PEC and CEC) can survive, and which factors predominantly determine the rate of decline, are crucial issues from a public health point of view. The goal of this study was to provide a quantitative summary of the variability in E. coli survival in soil and water over a broad range of individual studies and to identify the most important sources of variability. To that end, a meta-regression analysis on available literature data was conducted. The considerable variation in reported decline rates indicated that the persistence of E. coli is not easily predictable. The meta-analysis demonstrated that for soil and water, the type of experiment (laboratory or field), the matrix subtype (type of water and soil), and temperature were the main factors included in the regression analysis. A higher average decline rate in soil of PEC compared with CEC was observed. The regression models explained at best 57% of the variation in decline rate in soil and 41% of the variation in decline rate in water. This indicates that additional factors, not included in the current meta-regression analysis, are of importance but rarely reported. More complete reporting of experimental conditions may allow future inference on the global effects of these variables on the decline rate of E. coli.

Methods for Improving Information from ’Undesigned’ Human Factors Experiments.

DTIC Science & Technology

Human factors engineering, Information processing, Regression analysis , Experimental design, Least squares method, Analysis of variance, Correlation techniques, Matrices(Mathematics), Multiple disciplines, Mathematical prediction

Selecting risk factors: a comparison of discriminant analysis, logistic regression and Cox's regression model using data from the Tromsø Heart Study.

PubMed

Brenn, T; Arnesen, E

1985-01-01

For comparative evaluation, discriminant analysis, logistic regression and Cox's model were used to select risk factors for total and coronary deaths among 6595 men aged 20-49 followed for 9 years. Groups with mortality between 5 and 93 per 1000 were considered. Discriminant analysis selected variable sets only marginally different from the logistic and Cox methods which always selected the same sets. A time-saving option, offered for both the logistic and Cox selection, showed no advantage compared with discriminant analysis. Analysing more than 3800 subjects, the logistic and Cox methods consumed, respectively, 80 and 10 times more computer time than discriminant analysis. When including the same set of variables in non-stepwise analyses, all methods estimated coefficients that in most cases were almost identical. In conclusion, discriminant analysis is advocated for preliminary or stepwise analysis, otherwise Cox's method should be used.

[Development of the lung cancer diagnostic system].

PubMed

Lv, You-Jiang; Yu, Shou-Yi

2009-07-01

To develop a lung cancer diagnosis system. A retrospective analysis was conducted in 1883 patients with primary lung cancer or benign pulmonary diseases (pneumonia, tuberculosis, or pneumonia pseudotumor). SPSS11.5 software was used for data processing. For the relevant factors, a non-factor Logistic regression analysis was used followed by establishment of the regression model. Microsoft Visual Studio 2005 system development platform and VB.Net corresponding language were used to develop the lung cancer diagnosis system. The non-factor multi-factor regression model showed a goodness-of-fit (R2) of the model of 0.806, with a diagnostic accuracy for benign lung diseases of 92.8%, a diagnostic accuracy for lung cancer of 89.0%, and an overall accuracy of 90.8%. The model system for early clinical diagnosis of lung cancer has been established.

Risk Factors of Falls in Community-Dwelling Older Adults: Logistic Regression Tree Analysis

ERIC Educational Resources Information Center

Yamashita, Takashi; Noe, Douglas A.; Bailer, A. John

2012-01-01

Purpose of the Study: A novel logistic regression tree-based method was applied to identify fall risk factors and possible interaction effects of those risk factors. Design and Methods: A nationally representative sample of American older adults aged 65 years and older (N = 9,592) in the Health and Retirement Study 2004 and 2006 modules was used.…

Factor Retention in Exploratory Factor Analysis: A Comparison of Alternative Methods.

ERIC Educational Resources Information Center

Mumford, Karen R.; Ferron, John M.; Hines, Constance V.; Hogarty, Kristine Y.; Kromrey, Jeffery D.

This study compared the effectiveness of 10 methods of determining the number of factors to retain in exploratory common factor analysis. The 10 methods included the Kaiser rule and a modified Kaiser criterion, 3 variations of parallel analysis, 4 regression-based variations of the scree procedure, and the minimum average partial procedure. The…

Using Refined Regression Analysis To Assess The Ecological Services Of Restored Wetlands

EPA Science Inventory

A hierarchical approach to regression analysis of wetland water treatment was conducted to determine which factors are the most appropriate for characterizing wetlands of differing structure and function. We used this approach in an effort to identify the types and characteristi...

Logistic regression for risk factor modelling in stuttering research.

PubMed

Reed, Phil; Wu, Yaqionq

2013-06-01

To outline the uses of logistic regression and other statistical methods for risk factor analysis in the context of research on stuttering. The principles underlying the application of a logistic regression are illustrated, and the types of questions to which such a technique has been applied in the stuttering field are outlined. The assumptions and limitations of the technique are discussed with respect to existing stuttering research, and with respect to formulating appropriate research strategies to accommodate these considerations. Finally, some alternatives to the approach are briefly discussed. The way the statistical procedures are employed are demonstrated with some hypothetical data. Research into several practical issues concerning stuttering could benefit if risk factor modelling were used. Important examples are early diagnosis, prognosis (whether a child will recover or persist) and assessment of treatment outcome. After reading this article you will: (a) Summarize the situations in which logistic regression can be applied to a range of issues about stuttering; (b) Follow the steps in performing a logistic regression analysis; (c) Describe the assumptions of the logistic regression technique and the precautions that need to be checked when it is employed; (d) Be able to summarize its advantages over other techniques like estimation of group differences and simple regression. Copyright © 2012 Elsevier Inc. All rights reserved.

Two-factor logistic regression in pediatric liver transplantation

NASA Astrophysics Data System (ADS)

Uzunova, Yordanka; Prodanova, Krasimira; Spasov, Lyubomir

2017-12-01

Using a two-factor logistic regression analysis an estimate is derived for the probability of absence of infections in the early postoperative period after pediatric liver transplantation. The influence of both the bilirubin level and the international normalized ratio of prothrombin time of blood coagulation at the 5th postoperative day is studied.

Associated factors of radiation pneumonitis induced by precise radiotherapy in 186 elderly patients with esophageal cancer.

PubMed

Cui, Zhen; Tian, Ye; He, Bin; Li, Hongwei; Li, Duojie; Liu, Jingjing; Cai, Hanfei; Lou, Jianjun; Jiang, Hao; Shen, Xueming; Peng, Kaigui

2015-01-01

Radiation pneumonitis is one of the most severe complications of esophageal cancer. To explore the factors correlated to radiation pneumonitis induced by precise radiotherapy for elderly patients with esophageal cancer. The retrospective analysis was used to collect clinical data from 186 elderly patients with esophageal cancer. The incidence of radiation pneumonitis was observed, followed by statistical analysis through ANVON or multiple regression analysis. 27 in 186 cases of esophageal cancer suffered from radiation pneumonitis, with incidence of 14.52%. The single factor analysis showed that, Karnofsky performance status (KPS) score, chronic obstructive pulmonary disease, concurrent chemoradiotherapy, gross tumor volume (GTV) dose, lung V20, mean lung dose (MLD) and planning target volume (PTV) were associated with radiation pneumonitis. The logistic regression analysis indicated that, concurrent chemoradiotherapy, GTV dose, lung V20 and PTV were the independent factors of radiation pneumonitis. The concurrent chemoradiotherapy, GTV dose, lung V20, MLD and PTV are the major risk factors of radiation pneumonitis for elderly patients with esophageal cancer.

[Predicting the probability of development and progression of primary open angle glaucoma by regression modeling].

PubMed

Likhvantseva, V G; Sokolov, V A; Levanova, O N; Kovelenova, I V

2018-01-01

Prediction of the clinical course of primary open-angle glaucoma (POAG) is one of the main directions in solving the problem of vision loss prevention and stabilization of the pathological process. Simple statistical methods of correlation analysis show the extent of each risk factor's impact, but do not indicate the total impact of these factors in personalized combinations. The relationships between the risk factors is subject to correlation and regression analysis. The regression equation represents the dependence of the mathematical expectation of the resulting sign on the combination of factor signs. To develop a technique for predicting the probability of development and progression of primary open-angle glaucoma based on a personalized combination of risk factors by linear multivariate regression analysis. The study included 66 patients (23 female and 43 male; 132 eyes) with newly diagnosed primary open-angle glaucoma. The control group consisted of 14 patients (8 male and 6 female). Standard ophthalmic examination was supplemented with biochemical study of lacrimal fluid. Concentration of matrix metalloproteinase MMP-2 and MMP-9 in tear fluid in both eyes was determined using 'sandwich' enzyme-linked immunosorbent assay (ELISA) method. The study resulted in the development of regression equations and step-by-step multivariate logistic models that can help calculate the risk of development and progression of POAG. Those models are based on expert evaluation of clinical and instrumental indicators of hydrodynamic disturbances (coefficient of outflow ease - C, volume of intraocular fluid secretion - F, fluctuation of intraocular pressure), as well as personalized morphometric parameters of the retina (central retinal thickness in the macular area) and concentration of MMP-2 and MMP-9 in the tear film. The newly developed regression equations are highly informative and can be a reliable tool for studying of the influence vector and assessment of pathogenic potential of the independent risk factors in specific personalized combinations.

Risk factors for pedicled flap necrosis in hand soft tissue reconstruction: a multivariate logistic regression analysis.

PubMed

Gong, Xu; Cui, Jianli; Jiang, Ziping; Lu, Laijin; Li, Xiucun

2018-03-01

Few clinical retrospective studies have reported the risk factors of pedicled flap necrosis in hand soft tissue reconstruction. The aim of this study was to identify non-technical risk factors associated with pedicled flap perioperative necrosis in hand soft tissue reconstruction via a multivariate logistic regression analysis. For patients with hand soft tissue reconstruction, we carefully reviewed hospital records and identified 163 patients who met the inclusion criteria. The characteristics of these patients, flap transfer procedures and postoperative complications were recorded. Eleven predictors were identified. The correlations between pedicled flap necrosis and risk factors were analysed using a logistic regression model. Of 163 skin flaps, 125 flaps survived completely without any complications. The pedicled flap necrosis rate in hands was 11.04%, which included partial flap necrosis (7.36%) and total flap necrosis (3.68%). Soft tissue defects in fingers were noted in 68.10% of all cases. The logistic regression analysis indicated that the soft tissue defect site (P = 0.046, odds ratio (OR) = 0.079, confidence interval (CI) (0.006, 0.959)), flap size (P = 0.020, OR = 1.024, CI (1.004, 1.045)) and postoperative wound infection (P < 0.001, OR = 17.407, CI (3.821, 79.303)) were statistically significant risk factors for pedicled flap necrosis of the hand. Soft tissue defect site, flap size and postoperative wound infection were risk factors associated with pedicled flap necrosis in hand soft tissue defect reconstruction. © 2017 Royal Australasian College of Surgeons.

Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

ERIC Educational Resources Information Center

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…

To Identify the Important Soil Properties Affecting Dinoseb Adsorption with Statistical Analysis

PubMed Central

Guan, Yiqing; Wei, Jianhui; Zhang, Danrong; Zu, Mingjuan; Zhang, Liru

2013-01-01

Investigating the influences of soil characteristic factors on dinoseb adsorption parameter with different statistical methods would be valuable to explicitly figure out the extent of these influences. The correlation coefficients and the direct, indirect effects of soil characteristic factors on dinoseb adsorption parameter were analyzed through bivariate correlation analysis, and path analysis. With stepwise regression analysis the factors which had little influence on the adsorption parameter were excluded. Results indicate that pH and CEC had moderate relationship and lower direct effect on dinoseb adsorption parameter due to the multicollinearity with other soil factors, and organic carbon and clay contents were found to be the most significant soil factors which affect the dinoseb adsorption process. A regression is thereby set up to explore the relationship between the dinoseb adsorption parameter and the two soil factors: the soil organic carbon and clay contents. A 92% of the variation of dinoseb sorption coefficient could be attributed to the variation of the soil organic carbon and clay contents. PMID:23737715

Cement Leakage in Percutaneous Vertebral Augmentation for Osteoporotic Vertebral Compression Fractures: Analysis of Risk Factors.

PubMed

Xie, Weixing; Jin, Daxiang; Ma, Hui; Ding, Jinyong; Xu, Jixi; Zhang, Shuncong; Liang, De

2016-05-01

The risk factors for cement leakage were retrospectively reviewed in 192 patients who underwent percutaneous vertebral augmentation (PVA). To discuss the factors related to the cement leakage in PVA procedure for the treatment of osteoporotic vertebral compression fractures. PVA is widely applied for the treatment of osteoporotic vertebral fractures. Cement leakage is a major complication of this procedure. The risk factors for cement leakage were controversial. A retrospective review of 192 patients who underwent PVA was conducted. The following data were recorded: age, sex, bone density, number of fractured vertebrae before surgery, number of treated vertebrae, severity of the treated vertebrae, operative approach, volume of injected bone cement, preoperative vertebral compression ratio, preoperative local kyphosis angle, intraosseous clefts, preoperative vertebral cortical bone defect, and ratio and type of cement leakage. To study the correlation between each factor and cement leakage ratio, bivariate regression analysis was employed to perform univariate analysis, whereas multivariate linear regression analysis was employed to perform multivariate analysis. The study included 192 patients (282 treated vertebrae), and cement leakage occurred in 100 vertebrae (35.46%). The vertebrae with preoperative cortical bone defects generally exhibited higher cement leakage ratio, and the leakage is typically type C. Vertebrae with intact cortical bones before the procedure tend to experience type S leakage. Univariate analysis showed that patient age, bone density, number of fractured vertebrae before surgery, and vertebral cortical bone were associated with cement leakage ratio (P<0.05). Multivariate analysis showed that the main factors influencing bone cement leakage are bone density and vertebral cortical bone defect, with standardized partial regression coefficients of -0.085 and 0.144, respectively. High bone density and vertebral cortical bone defect are independent risk factors associated with bone cement leakage.

A Factor Analytic and Regression Approach to Functional Age: Potential Effects of Race.

ERIC Educational Resources Information Center

Colquitt, Alan L.; And Others

Factor analysis and multiple regression are two major approaches used to look at functional age, which takes account of the extensive variation in the rate of physiological and psychological maturation throughout life. To examine the role of racial or cultural influences on the measurement of functional age, a battery of 12 tests concentrating on…

In Spite of Indeterminacy Many Common Factor Score Estimates Yield an Identical Reproduced Covariance Matrix

ERIC Educational Resources Information Center

Beauducel, Andre

2007-01-01

It was investigated whether commonly used factor score estimates lead to the same reproduced covariance matrix of observed variables. This was achieved by means of Schonemann and Steiger's (1976) regression component analysis, since it is possible to compute the reproduced covariance matrices of the regression components corresponding to different…

INNOVATIVE INSTRUMENTATION AND ANALYSIS OF THE TEMPERATURE MEASUREMENT FOR HIGH TEMPERATURE GASIFICATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seong W. Lee

2004-10-01

The systematic tests of the gasifier simulator on the clean thermocouple were completed in this reporting period. Within the systematic tests on the clean thermocouple, five (5) factors were considered as the experimental parameters including air flow rate, water flow rate, fine dust particle amount, ammonia addition and high/low frequency device (electric motor). The fractional factorial design method was used in the experiment design with sixteen (16) data sets of readings. Analysis of Variances (ANOVA) was applied to the results from systematic tests. The ANOVA results show that the un-balanced motor vibration frequency did not have the significant impact onmore » the temperature changes in the gasifier simulator. For the fine dust particles testing, the amount of fine dust particles has significant impact to the temperature measurements in the gasifier simulator. The effects of the air and water on the temperature measurements show the same results as reported in the previous report. The ammonia concentration was included as an experimental parameter for the reducing environment in this reporting period. The ammonia concentration does not seem to be a significant factor on the temperature changes. The linear regression analysis was applied to the temperature reading with five (5) factors. The accuracy of the linear regression is relatively low, which is less than 10% accuracy. Nonlinear regression was also conducted to the temperature reading with the same factors. Since the experiments were designed in two (2) levels, the nonlinear regression is not very effective with the dataset (16 readings). An extra central point test was conducted. With the data of the center point testing, the accuracy of the nonlinear regression is much better than the linear regression.« less

Multiple Linear Regression Analysis of Factors Affecting Real Property Price Index From Case Study Research In Istanbul/Turkey

NASA Astrophysics Data System (ADS)

Denli, H. H.; Koc, Z.

2015-12-01

Estimation of real properties depending on standards is difficult to apply in time and location. Regression analysis construct mathematical models which describe or explain relationships that may exist between variables. The problem of identifying price differences of properties to obtain a price index can be converted into a regression problem, and standard techniques of regression analysis can be used to estimate the index. Considering regression analysis for real estate valuation, which are presented in real marketing process with its current characteristics and quantifiers, the method will help us to find the effective factors or variables in the formation of the value. In this study, prices of housing for sale in Zeytinburnu, a district in Istanbul, are associated with its characteristics to find a price index, based on information received from a real estate web page. The associated variables used for the analysis are age, size in m2, number of floors having the house, floor number of the estate and number of rooms. The price of the estate represents the dependent variable, whereas the rest are independent variables. Prices from 60 real estates have been used for the analysis. Same price valued locations have been found and plotted on the map and equivalence curves have been drawn identifying the same valued zones as lines.

Multivariate logistic regression analysis of postoperative complications and risk model establishment of gastrectomy for gastric cancer: A single-center cohort report.

PubMed

Zhou, Jinzhe; Zhou, Yanbing; Cao, Shougen; Li, Shikuan; Wang, Hao; Niu, Zhaojian; Chen, Dong; Wang, Dongsheng; Lv, Liang; Zhang, Jian; Li, Yu; Jiao, Xuelong; Tan, Xiaojie; Zhang, Jianli; Wang, Haibo; Zhang, Bingyuan; Lu, Yun; Sun, Zhenqing

2016-01-01

Reporting of surgical complications is common, but few provide information about the severity and estimate risk factors of complications. If have, but lack of specificity. We retrospectively analyzed data on 2795 gastric cancer patients underwent surgical procedure at the Affiliated Hospital of Qingdao University between June 2007 and June 2012, established multivariate logistic regression model to predictive risk factors related to the postoperative complications according to the Clavien-Dindo classification system. Twenty-four out of 86 variables were identified statistically significant in univariate logistic regression analysis, 11 significant variables entered multivariate analysis were employed to produce the risk model. Liver cirrhosis, diabetes mellitus, Child classification, invasion of neighboring organs, combined resection, introperative transfusion, Billroth II anastomosis of reconstruction, malnutrition, surgical volume of surgeons, operating time and age were independent risk factors for postoperative complications after gastrectomy. Based on logistic regression equation, p=Exp∑BiXi / (1+Exp∑BiXi), multivariate logistic regression predictive model that calculated the risk of postoperative morbidity was developed, p = 1/(1 + e((4.810-1.287X1-0.504X2-0.500X3-0.474X4-0.405X5-0.318X6-0.316X7-0.305X8-0.278X9-0.255X10-0.138X11))). The accuracy, sensitivity and specificity of the model to predict the postoperative complications were 86.7%, 76.2% and 88.6%, respectively. This risk model based on Clavien-Dindo grading severity of complications system and logistic regression analysis can predict severe morbidity specific to an individual patient's risk factors, estimate patients' risks and benefits of gastric surgery as an accurate decision-making tool and may serve as a template for the development of risk models for other surgical groups.

Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

Drivers of wetland conversion: a global meta-analysis.

PubMed

van Asselen, Sanneke; Verburg, Peter H; Vermaat, Jan E; Janse, Jan H

2013-01-01

Meta-analysis of case studies has become an important tool for synthesizing case study findings in land change. Meta-analyses of deforestation, urbanization, desertification and change in shifting cultivation systems have been published. This present study adds to this literature, with an analysis of the proximate causes and underlying forces of wetland conversion at a global scale using two complementary approaches of systematic review. Firstly, a meta-analysis of 105 case-study papers describing wetland conversion was performed, showing that different combinations of multiple-factor proximate causes, and underlying forces, drive wetland conversion. Agricultural development has been the main proximate cause of wetland conversion, and economic growth and population density are the most frequently identified underlying forces. Secondly, to add a more quantitative component to the study, a logistic meta-regression analysis was performed to estimate the likelihood of wetland conversion worldwide, using globally-consistent biophysical and socioeconomic location factor maps. Significant factors explaining wetland conversion, in order of importance, are market influence, total wetland area (lower conversion probability), mean annual temperature and cropland or built-up area. The regression analyses results support the outcomes of the meta-analysis of the processes of conversion mentioned in the individual case studies. In other meta-analyses of land change, similar factors (e.g., agricultural development, population growth, market/economic factors) are also identified as important causes of various types of land change (e.g., deforestation, desertification). Meta-analysis helps to identify commonalities across the various local case studies and identify which variables may lead to individual cases to behave differently. The meta-regression provides maps indicating the likelihood of wetland conversion worldwide based on the location factors that have determined historic conversions.

Drivers of Wetland Conversion: a Global Meta-Analysis

PubMed Central

van Asselen, Sanneke; Verburg, Peter H.; Vermaat, Jan E.; Janse, Jan H.

2013-01-01

Meta-analysis of case studies has become an important tool for synthesizing case study findings in land change. Meta-analyses of deforestation, urbanization, desertification and change in shifting cultivation systems have been published. This present study adds to this literature, with an analysis of the proximate causes and underlying forces of wetland conversion at a global scale using two complementary approaches of systematic review. Firstly, a meta-analysis of 105 case-study papers describing wetland conversion was performed, showing that different combinations of multiple-factor proximate causes, and underlying forces, drive wetland conversion. Agricultural development has been the main proximate cause of wetland conversion, and economic growth and population density are the most frequently identified underlying forces. Secondly, to add a more quantitative component to the study, a logistic meta-regression analysis was performed to estimate the likelihood of wetland conversion worldwide, using globally-consistent biophysical and socioeconomic location factor maps. Significant factors explaining wetland conversion, in order of importance, are market influence, total wetland area (lower conversion probability), mean annual temperature and cropland or built-up area. The regression analyses results support the outcomes of the meta-analysis of the processes of conversion mentioned in the individual case studies. In other meta-analyses of land change, similar factors (e.g., agricultural development, population growth, market/economic factors) are also identified as important causes of various types of land change (e.g., deforestation, desertification). Meta-analysis helps to identify commonalities across the various local case studies and identify which variables may lead to individual cases to behave differently. The meta-regression provides maps indicating the likelihood of wetland conversion worldwide based on the location factors that have determined historic conversions. PMID:24282580

Detecting Outliers in Factor Analysis Using the Forward Search Algorithm

ERIC Educational Resources Information Center

Mavridis, Dimitris; Moustaki, Irini

2008-01-01

In this article we extend and implement the forward search algorithm for identifying atypical subjects/observations in factor analysis models. The forward search has been mainly developed for detecting aberrant observations in regression models (Atkinson, 1994) and in multivariate methods such as cluster and discriminant analysis (Atkinson, Riani,…

Old and New Ideas for Data Screening and Assumption Testing for Exploratory and Confirmatory Factor Analysis

PubMed Central

Flora, David B.; LaBrish, Cathy; Chalmers, R. Philip

2011-01-01

We provide a basic review of the data screening and assumption testing issues relevant to exploratory and confirmatory factor analysis along with practical advice for conducting analyses that are sensitive to these concerns. Historically, factor analysis was developed for explaining the relationships among many continuous test scores, which led to the expression of the common factor model as a multivariate linear regression model with observed, continuous variables serving as dependent variables, and unobserved factors as the independent, explanatory variables. Thus, we begin our paper with a review of the assumptions for the common factor model and data screening issues as they pertain to the factor analysis of continuous observed variables. In particular, we describe how principles from regression diagnostics also apply to factor analysis. Next, because modern applications of factor analysis frequently involve the analysis of the individual items from a single test or questionnaire, an important focus of this paper is the factor analysis of items. Although the traditional linear factor model is well-suited to the analysis of continuously distributed variables, commonly used item types, including Likert-type items, almost always produce dichotomous or ordered categorical variables. We describe how relationships among such items are often not well described by product-moment correlations, which has clear ramifications for the traditional linear factor analysis. An alternative, non-linear factor analysis using polychoric correlations has become more readily available to applied researchers and thus more popular. Consequently, we also review the assumptions and data-screening issues involved in this method. Throughout the paper, we demonstrate these procedures using an historic data set of nine cognitive ability variables. PMID:22403561

Prediction of hearing outcomes by multiple regression analysis in patients with idiopathic sudden sensorineural hearing loss.

PubMed

Suzuki, Hideaki; Tabata, Takahisa; Koizumi, Hiroki; Hohchi, Nobusuke; Takeuchi, Shoko; Kitamura, Takuro; Fujino, Yoshihisa; Ohbuchi, Toyoaki

2014-12-01

This study aimed to create a multiple regression model for predicting hearing outcomes of idiopathic sudden sensorineural hearing loss (ISSNHL). The participants were 205 consecutive patients (205 ears) with ISSNHL (hearing level ≥ 40 dB, interval between onset and treatment ≤ 30 days). They received systemic steroid administration combined with intratympanic steroid injection. Data were examined by simple and multiple regression analyses. Three hearing indices (percentage hearing improvement, hearing gain, and posttreatment hearing level [HLpost]) and 7 prognostic factors (age, days from onset to treatment, initial hearing level, initial hearing level at low frequencies, initial hearing level at high frequencies, presence of vertigo, and contralateral hearing level) were included in the multiple regression analysis as dependent and explanatory variables, respectively. In the simple regression analysis, the percentage hearing improvement, hearing gain, and HLpost showed significant correlation with 2, 5, and 6 of the 7 prognostic factors, respectively. The multiple correlation coefficients were 0.396, 0.503, and 0.714 for the percentage hearing improvement, hearing gain, and HLpost, respectively. Predicted values of HLpost calculated by the multiple regression equation were reliable with 70% probability with a 40-dB-width prediction interval. Prediction of HLpost by the multiple regression model may be useful to estimate the hearing prognosis of ISSNHL. © The Author(s) 2014.

Catching up with Harvard: Results from Regression Analysis of World Universities League Tables

ERIC Educational Resources Information Center

Li, Mei; Shankar, Sriram; Tang, Kam Ki

2011-01-01

This paper uses regression analysis to test if the universities performing less well according to Shanghai Jiao Tong University's world universities league tables are able to catch up with the top performers, and to identify national and institutional factors that could affect this catching up process. We have constructed a dataset of 461…

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis

PubMed Central

Rahman, Md. Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D. W.; Labrique, Alain B.; Rashid, Mahbubur; Christian, Parul; West, Keith P.

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 − -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset. PMID:29261760

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis.

PubMed

Kabir, Alamgir; Rahman, Md Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D W; Labrique, Alain B; Rashid, Mahbubur; Christian, Parul; West, Keith P

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 - -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset.

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

PubMed

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

[Establishment of multiple regression model for virulence factors of Saccharomyces albicans by random amplified polymorphic DNA bands].

PubMed

Liu, Qi; Wu, Youcong; Yuan, Youhua; Bai, Li; Niu, Kun

2011-12-01

To research the relationship between the virulence factors of Saccharomyces albicans (S. albicans) and the random amplified polymorphic DNA (RAPD) bands of them, and establish the regression model by multiple regression analysis. Extracellular phospholipase, secreted proteinase, ability to generate germ tubes and adhere to oral mucosal cells of 92 strains of S. albicans were measured in vitro; RAPD-polymerase chain reaction (RAPD-PCR) was used to get their bands. Multiple regression for virulence factors of S. albicans and RAPD-PCR bands was established. The extracellular phospholipase activity was associated with 4 RAPD bands: 350, 450, 650 and 1 300 bp (P < 0.05); secreted proteinase activity of S. albicans was associated with 2 bands: 350 and 1 200 bp (P < 0.05); the ability of germ tube produce was associated with 2 bands: 400 and 550 bp (P < 0.05). Some RAPD bands will reflect the virulence factors of S. albicans indirectly. These bands would contain some important messages for regulation of S. albicans virulence factors.

The use of cognitive ability measures as explanatory variables in regression analysis.

PubMed

Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J

2012-12-01

Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual's wage, or a decision such as an individual's education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score , constructed via standard psychometric practice from individuals' responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a "mixed effects structural equations" (MESE) model, may be more appropriate in many circumstances.

Regression Levels of Selected Affective Factors on Science Achievement: A Structural Equation Model with TIMSS 2011 Data

ERIC Educational Resources Information Center

Akilli, Mustafa

2015-01-01

The aim of this study is to demonstrate the science success regression levels of chosen emotional features of 8th grade students using Structural Equation Model. The study was conducted by the analysis of students' questionnaires and science success in TIMSS 2011 data using SEM. Initially, the factors that are thought to have an effect on science…

Bias due to two-stage residual-outcome regression analysis in genetic association studies.

PubMed

Demissie, Serkalem; Cupples, L Adrienne

2011-11-01

Association studies of risk factors and complex diseases require careful assessment of potential confounding factors. Two-stage regression analysis, sometimes referred to as residual- or adjusted-outcome analysis, has been increasingly used in association studies of single nucleotide polymorphisms (SNPs) and quantitative traits. In this analysis, first, a residual-outcome is calculated from a regression of the outcome variable on covariates and then the relationship between the adjusted-outcome and the SNP is evaluated by a simple linear regression of the adjusted-outcome on the SNP. In this article, we examine the performance of this two-stage analysis as compared with multiple linear regression (MLR) analysis. Our findings show that when a SNP and a covariate are correlated, the two-stage approach results in biased genotypic effect and loss of power. Bias is always toward the null and increases with the squared-correlation between the SNP and the covariate (). For example, for , 0.1, and 0.5, two-stage analysis results in, respectively, 0, 10, and 50% attenuation in the SNP effect. As expected, MLR was always unbiased. Since individual SNPs often show little or no correlation with covariates, a two-stage analysis is expected to perform as well as MLR in many genetic studies; however, it produces considerably different results from MLR and may lead to incorrect conclusions when independent variables are highly correlated. While a useful alternative to MLR under , the two -stage approach has serious limitations. Its use as a simple substitute for MLR should be avoided. © 2011 Wiley Periodicals, Inc.

Psychosocial risk and protective factors for depression in the dialysis population: a systematic review and meta-regression analysis.

PubMed

Chan, Ramony; Steel, Zachary; Brooks, Robert; Heung, Tracy; Erlich, Jonathan; Chow, Josephine; Suranyi, Michael

2011-11-01

Research into the association between psychosocial factors and depression in End-Stage Renal Disease (ESRD) has expanded considerably in recent years identifying a range of factors that may act as important risk and protective factors of depression for this population. The present study provides the first systematic review and meta-analysis of this body of research. Published studies reporting associations between any psychosocial factor and depression were identified and retrieved from Medline, Embase, and PsycINFO, by applying optimised search strategies. Mean effect sizes were calculated for the associations across five psychosocial constructs (social support, personality attributes, cognitive appraisal, coping process, stress/stressor). Multiple hierarchical meta-regression analysis was applied to examine the moderating effects of methodological and substantive factors on the strength of the observed associations. 57 studies covering 58 independent samples with 5956 participants were identified, resulting in 246 effect sizes of the association between a range of psychosocial factors and depression. The overall mean effect size (Pearsons correlation coefficient) of the association between psychosocial factor and depression was 0.36. The effect sizes between the five psychosocial constructs and depression ranged from medium (0.27) to large levels (0.46) with personality attributes (0.46) and cognitive appraisal (0.46) having the largest effect sizes. In the meta-regression analyses, identified demographic (gender, age, location of study) and treatment (type of dialysis) characteristics moderated the strength of the associations with depression. The current analysis documents a moderate to large association between the presence of psychosocial risk factors and depression in ESRD. 2011. Published by Elsevier Inc. All rights reserved.

A Quantitative Analysis of the Extrinsic and Intrinsic Turnover Factors of Relational Database Support Professionals

ERIC Educational Resources Information Center

Takusi, Gabriel Samuto

2010-01-01

This quantitative analysis explored the intrinsic and extrinsic turnover factors of relational database support specialists. Two hundred and nine relational database support specialists were surveyed for this research. The research was conducted based on Hackman and Oldham's (1980) Job Diagnostic Survey. Regression analysis and a univariate ANOVA…

A Bayesian goodness of fit test and semiparametric generalization of logistic regression with measurement data.

PubMed

Schörgendorfer, Angela; Branscum, Adam J; Hanson, Timothy E

2013-06-01

Logistic regression is a popular tool for risk analysis in medical and population health science. With continuous response data, it is common to create a dichotomous outcome for logistic regression analysis by specifying a threshold for positivity. Fitting a linear regression to the nondichotomized response variable assuming a logistic sampling model for the data has been empirically shown to yield more efficient estimates of odds ratios than ordinary logistic regression of the dichotomized endpoint. We illustrate that risk inference is not robust to departures from the parametric logistic distribution. Moreover, the model assumption of proportional odds is generally not satisfied when the condition of a logistic distribution for the data is violated, leading to biased inference from a parametric logistic analysis. We develop novel Bayesian semiparametric methodology for testing goodness of fit of parametric logistic regression with continuous measurement data. The testing procedures hold for any cutoff threshold and our approach simultaneously provides the ability to perform semiparametric risk estimation. Bayes factors are calculated using the Savage-Dickey ratio for testing the null hypothesis of logistic regression versus a semiparametric generalization. We propose a fully Bayesian and a computationally efficient empirical Bayesian approach to testing, and we present methods for semiparametric estimation of risks, relative risks, and odds ratios when parametric logistic regression fails. Theoretical results establish the consistency of the empirical Bayes test. Results from simulated data show that the proposed approach provides accurate inference irrespective of whether parametric assumptions hold or not. Evaluation of risk factors for obesity shows that different inferences are derived from an analysis of a real data set when deviations from a logistic distribution are permissible in a flexible semiparametric framework. © 2013, The International Biometric Society.

Classification and regression tree analysis vs. multivariable linear and logistic regression methods as statistical tools for studying haemophilia.

PubMed

Henrard, S; Speybroeck, N; Hermans, C

2015-11-01

Haemophilia is a rare genetic haemorrhagic disease characterized by partial or complete deficiency of coagulation factor VIII, for haemophilia A, or IX, for haemophilia B. As in any other medical research domain, the field of haemophilia research is increasingly concerned with finding factors associated with binary or continuous outcomes through multivariable models. Traditional models include multiple logistic regressions, for binary outcomes, and multiple linear regressions for continuous outcomes. Yet these regression models are at times difficult to implement, especially for non-statisticians, and can be difficult to interpret. The present paper sought to didactically explain how, why, and when to use classification and regression tree (CART) analysis for haemophilia research. The CART method is non-parametric and non-linear, based on the repeated partitioning of a sample into subgroups based on a certain criterion. Breiman developed this method in 1984. Classification trees (CTs) are used to analyse categorical outcomes and regression trees (RTs) to analyse continuous ones. The CART methodology has become increasingly popular in the medical field, yet only a few examples of studies using this methodology specifically in haemophilia have to date been published. Two examples using CART analysis and previously published in this field are didactically explained in details. There is increasing interest in using CART analysis in the health domain, primarily due to its ease of implementation, use, and interpretation, thus facilitating medical decision-making. This method should be promoted for analysing continuous or categorical outcomes in haemophilia, when applicable. © 2015 John Wiley & Sons Ltd.

Copula-based regression modeling of bivariate severity of temporary disability and permanent motor injuries.

PubMed

Ayuso, Mercedes; Bermúdez, Lluís; Santolino, Miguel

2016-04-01

The analysis of factors influencing the severity of the personal injuries suffered by victims of motor accidents is an issue of major interest. Yet, most of the extant literature has tended to address this question by focusing on either the severity of temporary disability or the severity of permanent injury. In this paper, a bivariate copula-based regression model for temporary disability and permanent injury severities is introduced for the joint analysis of the relationship with the set of factors that might influence both categories of injury. Using a motor insurance database with 21,361 observations, the copula-based regression model is shown to give a better performance than that of a model based on the assumption of independence. The inclusion of the dependence structure in the analysis has a higher impact on the variance estimates of the injury severities than it does on the point estimates. By taking into account the dependence between temporary and permanent severities a more extensive factor analysis can be conducted. We illustrate that the conditional distribution functions of injury severities may be estimated, thus, providing decision makers with valuable information. Copyright © 2016 Elsevier Ltd. All rights reserved.

A logistic regression analysis of factors related to the treatment compliance of infertile patients with polycystic ovary syndrome.

PubMed

Li, Saijiao; He, Aiyan; Yang, Jing; Yin, TaiLang; Xu, Wangming

2011-01-01

To investigate factors that can affect compliance with treatment of polycystic ovary syndrome (PCOS) in infertile patients and to provide a basis for clinical treatment, specialist consultation and health education. Patient compliance was assessed via a questionnaire based on the Morisky-Green test and the treatment principles of PCOS. Then interviews were conducted with 99 infertile patients diagnosed with PCOS at Renmin Hospital of Wuhan University in China, from March to September 2009. Finally, these data were analyzed using logistic regression analysis. Logistic regression analysis revealed that a total of 23 (25.6%) of the participants showed good compliance. Factors that significantly (p < 0.05) affected compliance with treatment were the patient's body mass index, convenience of medical treatment and concerns about adverse drug reactions. Patients who are obese, experience inconvenient medical treatment or are concerned about adverse drug reactions are more likely to exhibit noncompliance. Treatment education and intervention aimed at these patients should be strengthened in the clinic to improve treatment compliance. Further research is needed to better elucidate the compliance behavior of patients with PCOS.

Specific factors for prenatal lead exposure in the border area of China.

PubMed

Kawata, Kimiko; Li, Yan; Liu, Hao; Zhang, Xiao Qin; Ushijima, Hiroshi

2006-07-01

The objectives of this study are to examine the prevalence of increased blood lead concentrations in mothers and their umbilical cords, and to identify risk factors for prenatal lead exposure in Kunming city, Yunnan province, China. The study was conducted at two obstetrics departments, and 100 peripartum women were enrolled. The mean blood lead concentrations of the mothers and the umbilical cords were 67.3microg/l and 53.1microg/l, respectively. In multiple linear regression analysis, maternal occupational exposure, maternal consumption of homemade dehydrated vegetables and maternal habitation period in Kunming city were significantly associated with an increase of umbilical cord blood lead concentration. In addition, logistic regression analysis was used to assess the association of umbilical cord blood lead concentrations that possibly have adverse effects on brain development of newborns with each potential risk factor. Maternal frequent use of tableware with color patterns inside was significantly associated with higher cord blood lead concentration in addition to the three items in the multiple linear regression analysis. These points should be considered as specific recommendations for maternal and fetal lead exposure in this city.

Factors Influencing Cecal Intubation Time during Retrograde Approach Single-Balloon Enteroscopy

PubMed Central

Chen, Peng-Jen; Shih, Yu-Lueng; Huang, Hsin-Hung; Hsieh, Tsai-Yuan

2014-01-01

Background and Aim. The predisposing factors for prolonged cecal intubation time (CIT) during colonoscopy have been well identified. However, the factors influencing CIT during retrograde SBE have not been addressed. The aim of this study was to determine the factors influencing CIT during retrograde SBE. Methods. We investigated patients who underwent retrograde SBE at a medical center from January 2011 to March 2014. The medical charts and SBE reports were reviewed. The patients' characteristics and procedure-associated data were recorded. These data were analyzed with univariate analysis as well as multivariate logistic regression analysis to identify the possible predisposing factors. Results. We enrolled 66 patients into this study. The median CIT was 17.4 minutes. With univariate analysis, there was no statistical difference in age, sex, BMI, or history of abdominal surgery, except for bowel preparation (P = 0.021). Multivariate logistic regression analysis showed that inadequate bowel preparation (odds ratio 30.2, 95% confidence interval 4.63–196.54; P < 0.001) was the independent predisposing factors for prolonged CIT during retrograde SBE. Conclusions. For experienced endoscopist, inadequate bowel preparation was the independent predisposing factor for prolonged CIT during retrograde SBE. PMID:25505904

[A case-control study on the risk factors of work-related acute pesticide poisoning among farmers from Jiangsu province].

PubMed

Tu, Zhi-bin; Cui, Meng-jing; Yao, Hong-yan; Hu, Guo-qing; Xiang, Hui-yun; Stallones, Lorann; Zhang, Xu-jun

2012-04-01

To explore the risk factors on cases regarding work-related acute pesticide poisoning among farmers of Jiangsu province. A population-based, 1:2 matched case-control study was carried out, with 121 patients as case-group paired by 242 persons with same gender, district and age less then difference of 3 years, as controls. Cases were the ones who had suffered from work-related acute pesticide poisoning. A unified questionnaire was used. Data base was established by EpiData 3.1, and SPSS 16.0 was used for both data single factor and multi-conditional logistics regression analysis. Results from the single factor logistic regression analysis showed that the related risk factors were: lack of safety guidance, lack of readable labels before praying pesticides, no regression during application, using hand to wipe sweat, using leaking knapsack, body contaminated during application and continuing to work when feeling ill after the contact of pesticides. Results from multi-conditional logistic regression analysis indicated that the lack of safety guidance (OR=2.25, 95%CI: 1.35-3.74), no readable labels before praying pesticides (OR=1.95, 95%CI: 1.19-3.18), wiping the sweat by hand during application (OR=1.97, 95%CI: 1.20-3.24) and using leaking knapsack during application (OR=1.82, 95%CI:1.10-3.01) were risk factors for the occurrence of work-related acute pesticide poisoning. The lack of safety guidance, no readable labels before praying pesticides, wiping the sweat by hand or using leaking knapsack during application were correlated to the occurrence of work-related acute pesticide poisoning.

Selection of higher order regression models in the analysis of multi-factorial transcription data.

PubMed

Prazeres da Costa, Olivia; Hoffman, Arthur; Rey, Johannes W; Mansmann, Ulrich; Buch, Thorsten; Tresch, Achim

2014-01-01

Many studies examine gene expression data that has been obtained under the influence of multiple factors, such as genetic background, environmental conditions, or exposure to diseases. The interplay of multiple factors may lead to effect modification and confounding. Higher order linear regression models can account for these effects. We present a new methodology for linear model selection and apply it to microarray data of bone marrow-derived macrophages. This experiment investigates the influence of three variable factors: the genetic background of the mice from which the macrophages were obtained, Yersinia enterocolitica infection (two strains, and a mock control), and treatment/non-treatment with interferon-γ. We set up four different linear regression models in a hierarchical order. We introduce the eruption plot as a new practical tool for model selection complementary to global testing. It visually compares the size and significance of effect estimates between two nested models. Using this methodology we were able to select the most appropriate model by keeping only relevant factors showing additional explanatory power. Application to experimental data allowed us to qualify the interaction of factors as either neutral (no interaction), alleviating (co-occurring effects are weaker than expected from the single effects), or aggravating (stronger than expected). We find a biologically meaningful gene cluster of putative C2TA target genes that appear to be co-regulated with MHC class II genes. We introduced the eruption plot as a tool for visual model comparison to identify relevant higher order interactions in the analysis of expression data obtained under the influence of multiple factors. We conclude that model selection in higher order linear regression models should generally be performed for the analysis of multi-factorial microarray data.

Comparison of Cox's Regression Model and Parametric Models in Evaluating the Prognostic Factors for Survival after Liver Transplantation in Shiraz during 2000-2012.

PubMed

Adelian, R; Jamali, J; Zare, N; Ayatollahi, S M T; Pooladfar, G R; Roustaei, N

2015-01-01

Identification of the prognostic factors for survival in patients with liver transplantation is challengeable. Various methods of survival analysis have provided different, sometimes contradictory, results from the same data. To compare Cox's regression model with parametric models for determining the independent factors for predicting adults' and pediatrics' survival after liver transplantation. This study was conducted on 183 pediatric patients and 346 adults underwent liver transplantation in Namazi Hospital, Shiraz, southern Iran. The study population included all patients undergoing liver transplantation from 2000 to 2012. The prognostic factors sex, age, Child class, initial diagnosis of the liver disease, PELD/MELD score, and pre-operative laboratory markers were selected for survival analysis. Among 529 patients, 346 (64.5%) were adult and 183 (34.6%) were pediatric cases. Overall, the lognormal distribution was the best-fitting model for adult and pediatric patients. Age in adults (HR=1.16, p<0.05) and weight (HR=2.68, p<0.01) and Child class B (HR=2.12, p<0.05) in pediatric patients were the most important factors for prediction of survival after liver transplantation. Adult patients younger than the mean age and pediatric patients weighing above the mean and Child class A (compared to those with classes B or C) had better survival. Parametric regression model is a good alternative for the Cox's regression model.

Using mixed treatment comparisons and meta-regression to perform indirect comparisons to estimate the efficacy of biologic treatments in rheumatoid arthritis.

PubMed

Nixon, R M; Bansback, N; Brennan, A

2007-03-15

Mixed treatment comparison (MTC) is a generalization of meta-analysis. Instead of the same treatment for a disease being tested in a number of studies, a number of different interventions are considered. Meta-regression is also a generalization of meta-analysis where an attempt is made to explain the heterogeneity between the treatment effects in the studies by regressing on study-level covariables. Our focus is where there are several different treatments considered in a number of randomized controlled trials in a specific disease, the same treatment can be applied in several arms within a study, and where differences in efficacy can be explained by differences in the study settings. We develop methods for simultaneously comparing several treatments and adjusting for study-level covariables by combining ideas from MTC and meta-regression. We use a case study from rheumatoid arthritis. We identified relevant trials of biologic verses standard therapy or placebo and extracted the doses, comparators and patient baseline characteristics. Efficacy is measured using the log odds ratio of achieving six-month ACR50 responder status. A random-effects meta-regression model is fitted which adjusts the log odds ratio for study-level prognostic factors. A different random-effect distribution on the log odds ratios is allowed for each different treatment. The odds ratio is found as a function of the prognostic factors for each treatment. The apparent differences in the randomized trials between tumour necrosis factor alpha (TNF- alpha) antagonists are explained by differences in prognostic factors and the analysis suggests that these drugs as a class are not different from each other. Copyright (c) 2006 John Wiley & Sons, Ltd.

Prevalence of vitamin D deficiency and associated factors in women and newborns in the immediate postpartum period

PubMed Central

do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2015-01-01

Abstract Objective: To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. Methods: This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95%, was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α <5%. Results: From 226 women included, 200 (88.5%) were 20-44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. Conclusions: This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. PMID:26100593

Logistic regression applied to natural hazards: rare event logistic regression with replications

NASA Astrophysics Data System (ADS)

Guns, M.; Vanacker, V.

2012-06-01

Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

Regression: The Apple Does Not Fall Far From the Tree.

PubMed

Vetter, Thomas R; Schober, Patrick

2018-05-15

Researchers and clinicians are frequently interested in either: (1) assessing whether there is a relationship or association between 2 or more variables and quantifying this association; or (2) determining whether 1 or more variables can predict another variable. The strength of such an association is mainly described by the correlation. However, regression analysis and regression models can be used not only to identify whether there is a significant relationship or association between variables but also to generate estimations of such a predictive relationship between variables. This basic statistical tutorial discusses the fundamental concepts and techniques related to the most common types of regression analysis and modeling, including simple linear regression, multiple regression, logistic regression, ordinal regression, and Poisson regression, as well as the common yet often underrecognized phenomenon of regression toward the mean. The various types of regression analysis are powerful statistical techniques, which when appropriately applied, can allow for the valid interpretation of complex, multifactorial data. Regression analysis and models can assess whether there is a relationship or association between 2 or more observed variables and estimate the strength of this association, as well as determine whether 1 or more variables can predict another variable. Regression is thus being applied more commonly in anesthesia, perioperative, critical care, and pain research. However, it is crucial to note that regression can identify plausible risk factors; it does not prove causation (a definitive cause and effect relationship). The results of a regression analysis instead identify independent (predictor) variable(s) associated with the dependent (outcome) variable. As with other statistical methods, applying regression requires that certain assumptions be met, which can be tested with specific diagnostics.

The Relationship among Leisure Interests, Personality Traits, Affect, and Mood

ERIC Educational Resources Information Center

Wilkinson, Todd J.; Hansen, Jo-Ida C.

2006-01-01

The present study examined relationships between leisure interests and the Big Five personality traits, positive and negative affect, and moods. Regression analysis identified particular personality but not mood or affect variables as significant predictors of leisure factor scores. Further exploration through factor analysis revealed factor…

Enhancing the estimation of blood pressure using pulse arrival time and two confounding factors.

PubMed

Baek, Hyun Jae; Kim, Ko Keun; Kim, Jung Soo; Lee, Boreom; Park, Kwang Suk

2010-02-01

A new method of blood pressure (BP) estimation using multiple regression with pulse arrival time (PAT) and two confounding factors was evaluated in clinical and unconstrained monitoring situations. For the first analysis with clinical data, electrocardiogram (ECG), photoplethysmogram (PPG) and invasive BP signals were obtained by a conventional patient monitoring device during surgery. In the second analysis, ECG, PPG and non-invasive BP were measured using systems developed to obtain data under conditions in which the subject was not constrained. To enhance the performance of BP estimation methods, heart rate (HR) and arterial stiffness were considered as confounding factors in regression analysis. The PAT and HR were easily extracted from ECG and PPG signals. For arterial stiffness, the duration from the maximum derivative point to the maximum of the dicrotic notch in the PPG signal, a parameter called TDB, was employed. In two experiments that normally cause BP variation, the correlation between measured BP and the estimated BP was investigated. Multiple-regression analysis with the two confounding factors improved correlation coefficients for diastolic blood pressure and systolic blood pressure to acceptable confidence levels, compared to existing methods that consider PAT only. In addition, reproducibility for the proposed method was determined using constructed test sets. Our results demonstrate that non-invasive, non-intrusive BP estimation can be obtained using methods that can be applied in both clinical and daily healthcare situations.

The use of cognitive ability measures as explanatory variables in regression analysis

PubMed Central

Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J

2015-01-01

Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual’s wage, or a decision such as an individual’s education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score, constructed via standard psychometric practice from individuals’ responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a “mixed effects structural equations” (MESE) model, may be more appropriate in many circumstances. PMID:26998417

Factors associated with active commuting to work among women.

PubMed

Bopp, Melissa; Child, Stephanie; Campbell, Matthew

2014-01-01

Active commuting (AC), the act of walking or biking to work, has notable health benefits though rates of AC remain low among women. This study used a social-ecological framework to examine the factors associated with AC among women. A convenience sample of employed, working women (n = 709) completed an online survey about their mode of travel to work. Individual, interpersonal, institutional, community, and environmental influences were assessed. Basic descriptive statistics and frequencies described the sample. Simple logistic regression models examined associations with the independent variables with AC participation and multiple logistic regression analysis determined the relative influence of social ecological factors on AC participation. The sample was primarily middle-aged (44.09±11.38 years) and non-Hispanic White (92%). Univariate analyses revealed several individual, interpersonal, institutional, community and environmental factors significantly associated with AC. The multivariable logistic regression analysis results indicated that significant factors associated with AC included number of children, income, perceived behavioral control, coworker AC, coworker AC normative beliefs, employer and community supports for AC, and traffic. The results of this study contribute to the limited body of knowledge on AC participation for women and may help to inform gender-tailored interventions to enhance AC behavior and improve health.

[The Influence of Subjective Health Status, Post-Traumatic Growth, and Social Support on Successful Aging in Middle-Aged Women].

PubMed

Lee, Seung Hee; Jang, Hyung Suk; Yang, Young Hee

2016-10-01

This study was done to investigate factors influencing successful aging in middle-aged women. A convenience sample of 103 middle-aged women was selected from the community. Data were collected using a structured questionnaire and analyzed using descriptive statistics, two-sample t-test, one-way ANOVA, Kruskal Wallis test, Pearson correlations, Spearman correlations and multiple regression analysis with the SPSS/WIN 22.0 program. Results of regression analysis showed that significant factors influencing successful aging were post-traumatic growth and social support. This regression model explained 48% of the variance in successful aging. Findings show that the concept 'post-traumatic growth' is an important factor influencing successful aging in middle-aged women. In addition, social support from friends/co-workers had greater influence on successful aging than social support from family. Thus, we need to consider the positive impact of post-traumatic growth and increase the chances of social participation in a successful aging program for middle-aged women.

Modeling the number of car theft using Poisson regression

NASA Astrophysics Data System (ADS)

Zulkifli, Malina; Ling, Agnes Beh Yen; Kasim, Maznah Mat; Ismail, Noriszura

2016-10-01

Regression analysis is the most popular statistical methods used to express the relationship between the variables of response with the covariates. The aim of this paper is to evaluate the factors that influence the number of car theft using Poisson regression model. This paper will focus on the number of car thefts that occurred in districts in Peninsular Malaysia. There are two groups of factor that have been considered, namely district descriptive factors and socio and demographic factors. The result of the study showed that Bumiputera composition, Chinese composition, Other ethnic composition, foreign migration, number of residence with the age between 25 to 64, number of employed person and number of unemployed person are the most influence factors that affect the car theft cases. These information are very useful for the law enforcement department, insurance company and car owners in order to reduce and limiting the car theft cases in Peninsular Malaysia.

Bias in logistic regression due to imperfect diagnostic test results and practical correction approaches.

PubMed

Valle, Denis; Lima, Joanna M Tucker; Millar, Justin; Amratia, Punam; Haque, Ubydul

2015-11-04

Logistic regression is a statistical model widely used in cross-sectional and cohort studies to identify and quantify the effects of potential disease risk factors. However, the impact of imperfect tests on adjusted odds ratios (and thus on the identification of risk factors) is under-appreciated. The purpose of this article is to draw attention to the problem associated with modelling imperfect diagnostic tests, and propose simple Bayesian models to adequately address this issue. A systematic literature review was conducted to determine the proportion of malaria studies that appropriately accounted for false-negatives/false-positives in a logistic regression setting. Inference from the standard logistic regression was also compared with that from three proposed Bayesian models using simulations and malaria data from the western Brazilian Amazon. A systematic literature review suggests that malaria epidemiologists are largely unaware of the problem of using logistic regression to model imperfect diagnostic test results. Simulation results reveal that statistical inference can be substantially improved when using the proposed Bayesian models versus the standard logistic regression. Finally, analysis of original malaria data with one of the proposed Bayesian models reveals that microscopy sensitivity is strongly influenced by how long people have lived in the study region, and an important risk factor (i.e., participation in forest extractivism) is identified that would have been missed by standard logistic regression. Given the numerous diagnostic methods employed by malaria researchers and the ubiquitous use of logistic regression to model the results of these diagnostic tests, this paper provides critical guidelines to improve data analysis practice in the presence of misclassification error. Easy-to-use code that can be readily adapted to WinBUGS is provided, enabling straightforward implementation of the proposed Bayesian models.

Hospital charges associated with motorcycle crash factors: a quantile regression analysis.

PubMed

Olsen, Cody S; Thomas, Andrea M; Cook, Lawrence J

2014-08-01

Previous studies of motorcycle crash (MC) related hospital charges use trauma registries and hospital records, and do not adjust for the number of motorcyclists not requiring medical attention. This may lead to conservative estimates of helmet use effectiveness. MC records were probabilistically linked with emergency department and hospital records to obtain total hospital charges. Missing data were imputed. Multivariable quantile regression estimated reductions in hospital charges associated with helmet use and other crash factors. Motorcycle helmets were associated with reduced median hospital charges of $256 (42% reduction) and reduced 98th percentile of $32,390 (33% reduction). After adjusting for other factors, helmets were associated with reductions in charges in all upper percentiles studied. Quantile regression models described homogenous and heterogeneous associations between other crash factors and charges. Quantile regression comprehensively describes associations between crash factors and hospital charges. Helmet use among motorcyclists is associated with decreased hospital charges. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Classification and regression tree analysis of acute-on-chronic hepatitis B liver failure: Seeing the forest for the trees.

PubMed

Shi, K-Q; Zhou, Y-Y; Yan, H-D; Li, H; Wu, F-L; Xie, Y-Y; Braddock, M; Lin, X-Y; Zheng, M-H

2017-02-01

At present, there is no ideal model for predicting the short-term outcome of patients with acute-on-chronic hepatitis B liver failure (ACHBLF). This study aimed to establish and validate a prognostic model by using the classification and regression tree (CART) analysis. A total of 1047 patients from two separate medical centres with suspected ACHBLF were screened in the study, which were recognized as derivation cohort and validation cohort, respectively. CART analysis was applied to predict the 3-month mortality of patients with ACHBLF. The accuracy of the CART model was tested using the area under the receiver operating characteristic curve, which was compared with the model for end-stage liver disease (MELD) score and a new logistic regression model. CART analysis identified four variables as prognostic factors of ACHBLF: total bilirubin, age, serum sodium and INR, and three distinct risk groups: low risk (4.2%), intermediate risk (30.2%-53.2%) and high risk (81.4%-96.9%). The new logistic regression model was constructed with four independent factors, including age, total bilirubin, serum sodium and prothrombin activity by multivariate logistic regression analysis. The performances of the CART model (0.896), similar to the logistic regression model (0.914, P=.382), exceeded that of MELD score (0.667, P<.001). The results were confirmed in the validation cohort. We have developed and validated a novel CART model superior to MELD for predicting three-month mortality of patients with ACHBLF. Thus, the CART model could facilitate medical decision-making and provide clinicians with a validated practical bedside tool for ACHBLF risk stratification. © 2016 John Wiley & Sons Ltd.

An Attempt at Quantifying Factors that Affect Efficiency in the Management of Solid Waste Produced by Commercial Businesses in the City of Tshwane, South Africa

PubMed Central

Worku, Yohannes; Muchie, Mammo

2012-01-01

Objective. The objective was to investigate factors that affect the efficient management of solid waste produced by commercial businesses operating in the city of Pretoria, South Africa. Methods. Data was gathered from 1,034 businesses. Efficiency in solid waste management was assessed by using a structural time-based model designed for evaluating efficiency as a function of the length of time required to manage waste. Data analysis was performed using statistical procedures such as frequency tables, Pearson's chi-square tests of association, and binary logistic regression analysis. Odds ratios estimated from logistic regression analysis were used for identifying key factors that affect efficiency in the proper disposal of waste. Results. The study showed that 857 of the 1,034 businesses selected for the study (83%) were found to be efficient enough with regards to the proper collection and disposal of solid waste. Based on odds ratios estimated from binary logistic regression analysis, efficiency in the proper management of solid waste was significantly influenced by 4 predictor variables. These 4 influential predictor variables are lack of adherence to waste management regulations, wrong perception, failure to provide customers with enough trash cans, and operation of businesses by employed managers, in a decreasing order of importance. PMID:23209483

Predictions of biochar production and torrefaction performance from sugarcane bagasse using interpolation and regression analysis.

PubMed

Chen, Wei-Hsin; Hsu, Hung-Jen; Kumar, Gopalakrishnan; Budzianowski, Wojciech M; Ong, Hwai Chyuan

2017-12-01

This study focuses on the biochar formation and torrefaction performance of sugarcane bagasse, and they are predicted using the bilinear interpolation (BLI), inverse distance weighting (IDW) interpolation, and regression analysis. It is found that the biomass torrefied at 275°C for 60min or at 300°C for 30min or longer is appropriate to produce biochar as alternative fuel to coal with low carbon footprint, but the energy yield from the torrefaction at 300°C is too low. From the biochar yield, enhancement factor of HHV, and energy yield, the results suggest that the three methods are all feasible for predicting the performance, especially for the enhancement factor. The power parameter of unity in the IDW method provides the best predictions and the error is below 5%. The second order in regression analysis gives a more reasonable approach than the first order, and is recommended for the predictions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Factors Associated With Work Ability in Patients Undergoing Surgery for Cervical Radiculopathy.

PubMed

Ng, Eunice; Johnston, Venerina; Wibault, Johanna; Löfgren, Håkan; Dedering, Åsa; Öberg, Birgitta; Zsigmond, Peter; Peolsson, Anneli

2015-08-15

Cross-sectional study. To investigate the factors associated with work ability in patients undergoing surgery for cervical radiculopathy. Surgery is a common treatment of cervical radiculopathy in people of working age. However, few studies have investigated the impact on the work ability of these patients. Patients undergoing surgery for cervical radiculopathy (n = 201) were recruited from spine centers in Sweden to complete a battery of questionnaires and physical measures the day before surgery. The associations between various individual, psychological, and work-related factors and self-reported work ability were investigated by Spearman rank correlation coefficient, multivariate linear regression, and forward stepwise regression analyses. Factors that were significant (P < 0.05) in each statistical analysis were entered into the successive analysis to reveal the factors most related to work ability. Work ability was assessed using the Work Ability Index. The mean Work Ability Index score was 28 (SD, 9.0). The forward stepwise regression analysis revealed 6 factors significantly associated with work ability, which explained 62% of the variance in the Work Ability Index. Factors highly correlated with greater work ability included greater self-efficacy in performing self-cares, lower physical load on the neck at work, greater self-reported chance of being able to work in 6 months' time, greater use of active coping strategies, lower frequency of hand weakness, and higher health-related quality of life. Psychological, work-related and individual factors were significantly associated with work ability in patients undergoing surgery for cervical radiculopathy. High self-efficacy was most associated with greater work ability. Consideration of these factors by surgeons preoperatively may provide optimal return to work outcomes after surgery. 3.

Prevalence of difficult venous access and associated risk factors in highly complex hospitalised patients.

PubMed

Armenteros-Yeguas, Victoria; Gárate-Echenique, Lucía; Tomás-López, Maria Aranzazu; Cristóbal-Domínguez, Estíbaliz; Moreno-de Gusmão, Breno; Miranda-Serrano, Erika; Moraza-Dulanto, Maria Inmaculada

2017-12-01

To estimate the prevalence of difficult venous access in complex patients with multimorbidity and to identify associated risk factors. In highly complex patients, factors like ageing, the need for frequent use of irritant medication and multiple venous catheterisations to complete treatment could contribute to exhaustion of venous access. A cross-sectional study was conducted. 'Highly complex' patients (n = 135) were recruited from March 2013-November 2013. The main study variable was the prevalence of difficult venous access, assessed using one of the following criteria: (1) a history of difficulties obtaining venous access based on more than two attempts to insert an intravenous line and (2) no visible or palpable veins. Other factors potentially associated with the risk of difficult access were also measured (age, gender and chronic illnesses). Univariate analysis was performed for each potential risk factor. Factors with p < 0·2 were then included in multivariable logistic regression analysis. Odds ratios were also calculated. The prevalence of difficult venous access was 59·3%. The univariate logistic regression analysis indicated that gender, a history of vascular access complications and osteoarticular disease were significantly associated with difficult venous access. The multivariable logistic regression showed that only gender was an independent risk factor and the odds ratios was 2·85. The prevalence of difficult venous access is high in this population. Gender (female) is the only independent risk factor associated with this. Previous history of several attempts at catheter insertion is an important criterion in the assessment of difficult venous access. The prevalence of difficult venous access in complex patients is 59·3%. Significant risk factors include being female and a history of complications related to vascular access. © 2017 John Wiley & Sons Ltd.

Comparison of Cox’s Regression Model and Parametric Models in Evaluating the Prognostic Factors for Survival after Liver Transplantation in Shiraz during 2000–2012

PubMed Central

Adelian, R.; Jamali, J.; Zare, N.; Ayatollahi, S. M. T.; Pooladfar, G. R.; Roustaei, N.

2015-01-01

Background: Identification of the prognostic factors for survival in patients with liver transplantation is challengeable. Various methods of survival analysis have provided different, sometimes contradictory, results from the same data. Objective: To compare Cox’s regression model with parametric models for determining the independent factors for predicting adults’ and pediatrics’ survival after liver transplantation. Method: This study was conducted on 183 pediatric patients and 346 adults underwent liver transplantation in Namazi Hospital, Shiraz, southern Iran. The study population included all patients undergoing liver transplantation from 2000 to 2012. The prognostic factors sex, age, Child class, initial diagnosis of the liver disease, PELD/MELD score, and pre-operative laboratory markers were selected for survival analysis. Result: Among 529 patients, 346 (64.5%) were adult and 183 (34.6%) were pediatric cases. Overall, the lognormal distribution was the best-fitting model for adult and pediatric patients. Age in adults (HR=1.16, p<0.05) and weight (HR=2.68, p<0.01) and Child class B (HR=2.12, p<0.05) in pediatric patients were the most important factors for prediction of survival after liver transplantation. Adult patients younger than the mean age and pediatric patients weighing above the mean and Child class A (compared to those with classes B or C) had better survival. Conclusion: Parametric regression model is a good alternative for the Cox’s regression model. PMID:26306158

[Analysis of risk factors for dry eye syndrome in visual display terminal workers].

PubMed

Zhu, Yong; Yu, Wen-lan; Xu, Ming; Han, Lei; Cao, Wen-dong; Zhang, Hong-bing; Zhang, Heng-dong

2013-08-01

To analyze the risk factors for dry eye syndrome in visual display terminal (VDT) workers and to provide a scientific basis for protecting the eye health of VDT workers. Questionnaire survey, Schirmer I test, tear break-up time test, and workshop microenvironment evaluation were performed in 185 VDT workers. Multivariate logistic regression analysis was performed to determine the risk factors for dry eye syndrome in VDT workers after adjustment for confounding factors. In the logistic regression model, the regression coefficients of daily mean time of exposure to screen, daily mean time of watching TV, parallel screen-eye angle, upward screen-eye angle, eye-screen distance of less than 20 cm, irregular breaks during screen-exposed work, age, and female gender on the results of Schirmer I test were 0.153, 0.548, 0.400, 0.796, 0.234, 0.516, 0.559, and -0.685, respectively; the regression coefficients of daily mean time of exposure to screen, parallel screen-eye angle, upward screen-eye angle, age, working years, and female gender on tear break-up time were 0.021, 0.625, 2.652, 0.749, 0.403, and 1.481, respectively. Daily mean time of exposure to screen, daily mean time of watching TV, parallel screen-eye angle, upward screen-eye angle, eye-screen distance of less than 20 cm, irregular breaks during screen-exposed work, age, and working years are risk factors for dry eye syndrome in VDT workers.

Investigating the effects of climate variations on bacillary dysentery incidence in northeast China using ridge regression and hierarchical cluster analysis

PubMed Central

Huang, Desheng; Guan, Peng; Guo, Junqiao; Wang, Ping; Zhou, Baosen

2008-01-01

Background The effects of climate variations on bacillary dysentery incidence have gained more recent concern. However, the multi-collinearity among meteorological factors affects the accuracy of correlation with bacillary dysentery incidence. Methods As a remedy, a modified method to combine ridge regression and hierarchical cluster analysis was proposed for investigating the effects of climate variations on bacillary dysentery incidence in northeast China. Results All weather indicators, temperatures, precipitation, evaporation and relative humidity have shown positive correlation with the monthly incidence of bacillary dysentery, while air pressure had a negative correlation with the incidence. Ridge regression and hierarchical cluster analysis showed that during 1987–1996, relative humidity, temperatures and air pressure affected the transmission of the bacillary dysentery. During this period, all meteorological factors were divided into three categories. Relative humidity and precipitation belonged to one class, temperature indexes and evaporation belonged to another class, and air pressure was the third class. Conclusion Meteorological factors have affected the transmission of bacillary dysentery in northeast China. Bacillary dysentery prevention and control would benefit from by giving more consideration to local climate variations. PMID:18816415

[Prevalence of vitamin D deficiency and associated factors in women and newborns in the immediate postpartum period].

PubMed

do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado Junior, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2015-01-01

To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95% was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α<5%. From 226 women included, 200 (88.5%) were 20 to 44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. Copyright © 2015 Sociedade de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.

An Analysis of Losses to the Southern Commercial Timberland Base

Treesearch

Ian A. Munn; David Cleaves

1998-01-01

Demographic and physical factors influencing the conversion of commercial timberland iu the south to non-forestry uses between the last two Forest Inventory Analysis (FIA) surveys were investigated. GIS techniques linked Census data and FIA plot level data. Multinomial logit regression identified factors associated with losses to the timberland base. Conversion to...

Aneurysmal subarachnoid hemorrhage prognostic decision-making algorithm using classification and regression tree analysis.

PubMed

Lo, Benjamin W Y; Fukuda, Hitoshi; Angle, Mark; Teitelbaum, Jeanne; Macdonald, R Loch; Farrokhyar, Forough; Thabane, Lehana; Levine, Mitchell A H

2016-01-01

Classification and regression tree analysis involves the creation of a decision tree by recursive partitioning of a dataset into more homogeneous subgroups. Thus far, there is scarce literature on using this technique to create clinical prediction tools for aneurysmal subarachnoid hemorrhage (SAH). The classification and regression tree analysis technique was applied to the multicenter Tirilazad database (3551 patients) in order to create the decision-making algorithm. In order to elucidate prognostic subgroups in aneurysmal SAH, neurologic, systemic, and demographic factors were taken into account. The dependent variable used for analysis was the dichotomized Glasgow Outcome Score at 3 months. Classification and regression tree analysis revealed seven prognostic subgroups. Neurological grade, occurrence of post-admission stroke, occurrence of post-admission fever, and age represented the explanatory nodes of this decision tree. Split sample validation revealed classification accuracy of 79% for the training dataset and 77% for the testing dataset. In addition, the occurrence of fever at 1-week post-aneurysmal SAH is associated with increased odds of post-admission stroke (odds ratio: 1.83, 95% confidence interval: 1.56-2.45, P < 0.01). A clinically useful classification tree was generated, which serves as a prediction tool to guide bedside prognostication and clinical treatment decision making. This prognostic decision-making algorithm also shed light on the complex interactions between a number of risk factors in determining outcome after aneurysmal SAH.

[Associations between dormitory environment/other factors and sleep quality of medical students].

PubMed

Zheng, Bang; Wang, Kailu; Pan, Ziqi; Li, Man; Pan, Yuting; Liu, Ting; Xu, Dan; Lyu, Jun

2016-03-01

To investigate the sleep quality and related factors among medical students in China, understand the association between dormitory environment and sleep quality, and provide evidence and recommendations for sleep hygiene intervention. A total of 555 undergraduate students were selected from a medical school of an university in Beijing through stratified-cluster random-sampling to conduct a questionnaire survey by using Chinese version of Pittsburgh Sleep Quality Index (PSQI) and self-designed questionnaire. Analyses were performed by using multiple logistic regression model as well as multilevel linear regression model. The prevalence of sleep disorder was 29.1%(149/512), and 39.1%(200/512) of the students reported that the sleep quality was influenced by dormitory environment. PSQI score was negatively correlated with self-reported rating of dormitory environment (γs=-0.310, P<0.001). Logistic regression analysis showed the related factors of sleep disorder included grade, sleep regularity, self-rated health status, pressures of school work and employment, as well as dormitory environment. RESULTS of multilevel regression analysis also indicated that perception on dormitory environment (individual level) was associated with sleep quality with the dormitory level random effects under control (b=-0.619, P<0.001). The prevalence of sleep disorder was high in medical students, which was associated with multiple factors. Dormitory environment should be taken into consideration when the interventions are taken to improve the sleep quality of students.

Bayesian Adaptive Lasso for Ordinal Regression with Latent Variables

ERIC Educational Resources Information Center

Feng, Xiang-Nan; Wu, Hao-Tian; Song, Xin-Yuan

2017-01-01

We consider an ordinal regression model with latent variables to investigate the effects of observable and latent explanatory variables on the ordinal responses of interest. Each latent variable is characterized by correlated observed variables through a confirmatory factor analysis model. We develop a Bayesian adaptive lasso procedure to conduct…

Identifying the Factors That Influence Change in SEBD Using Logistic Regression Analysis

ERIC Educational Resources Information Center

Camilleri, Liberato; Cefai, Carmel

2013-01-01

Multiple linear regression and ANOVA models are widely used in applications since they provide effective statistical tools for assessing the relationship between a continuous dependent variable and several predictors. However these models rely heavily on linearity and normality assumptions and they do not accommodate categorical dependent…

A multivariate analysis of clinical and morphological prognostic factors in squamous cell carcinoma of the vulva.

PubMed

Smyczek-Gargya, B; Volz, B; Geppert, M; Dietl, J

1997-01-01

Clinical and histological data of 168 patients with squamous cell carcinoma of the vulva were analyzed with respect to survival. 151 patients underwent surgery, 12 patients were treated with primary radiation and in 5 patients no treatment was performed. Follow-up lasted from at least 2 up to 22 years' posttreatment. In univariate analysis, the following factors were highly significant: presurgery lymph node status, tumor infiltration beyond the vulva, tumor grading, histological inguinal lymph node status, pre- and postsurgery tumor stage, depth of invasion and tumor diameter. In the multivariate analysis (Cox regression), the most powerful factors were shown to be histological inguinal lymph node status, tumor diameter and tumor grading. The multivariate logistic regression analysis worked out as main prognostic factors for metastases of inguinal lymph nodes: presurgery inguinal lymph node status, tumor size, depth of invasion and tumor grading. Based on these results, tumor biology seems to be the decisive factor concerning recurrence and survival. Therefore, we suggest a more conservative treatment of vulvar carcinoma. Patients with confined carcinoma to the vulva, with a tumor diameter up to 3 cm and without clinical suspected lymph nodes, should be treated by wide excision/partial vulvectomy with ipsilateral lymphadenectomy.

Dimensions of Intuition: First-Round Validation Studies

ERIC Educational Resources Information Center

Vrugtman, Rosanne

2009-01-01

This study utilized confirmatory factor analysis (CFA), canonical correlation analysis (CCA), regression analysis (RA), and correlation analysis (CA) for first-round validation of the researcher's Dimensions of Intuition (DOI) instrument. The DOI examined 25 personal characteristics and situations purportedly predictive of intuition. Data was…

Influence factors and forecast of carbon emission in China: structure adjustment for emission peak

NASA Astrophysics Data System (ADS)

Wang, B.; Cui, C. Q.; Li, Z. P.

2018-02-01

This paper introduced Principal Component Analysis and Multivariate Linear Regression Model to verify long-term balance relationships between Carbon Emissions and the impact factors. The integrated model of improved PCA and multivariate regression analysis model is attainable to figure out the pattern of carbon emission sources. Main empirical results indicate that among all selected variables, the role of energy consumption scale was largest. GDP and Population follow and also have significant impacts on carbon emission. Industrialization rate and fossil fuel proportion, which is the indicator of reflecting the economic structure and energy structure, have a higher importance than the factor of urbanization rate and the dweller consumption level of urban areas. In this way, some suggestions are put forward for government to achieve the peak of carbon emissions.

Predictors of exercise capacity following exercise-based rehabilitation in patients with coronary heart disease and heart failure: A meta-regression analysis.

PubMed

Uddin, Jamal; Zwisler, Ann-Dorthe; Lewinter, Christian; Moniruzzaman, Mohammad; Lund, Ken; Tang, Lars H; Taylor, Rod S

2016-05-01

The aim of this study was to undertake a comprehensive assessment of the patient, intervention and trial-level factors that may predict exercise capacity following exercise-based rehabilitation in patients with coronary heart disease and heart failure. Meta-analysis and meta-regression analysis. Randomized controlled trials of exercise-based rehabilitation were identified from three published systematic reviews. Exercise capacity was pooled across trials using random effects meta-analysis, and meta-regression used to examine the association between exercise capacity and a range of patient (e.g. age), intervention (e.g. exercise frequency) and trial (e.g. risk of bias) factors. 55 trials (61 exercise-control comparisons, 7553 patients) were included. Following exercise-based rehabilitation compared to control, overall exercise capacity was on average 0.95 (95% CI: 0.76-1.41) standard deviation units higher, and in trials reporting maximum oxygen uptake (VO2max) was 3.3 ml/kg.min(-1) (95% CI: 2.6-4.0) higher. There was evidence of a high level of statistical heterogeneity across trials (I(2) statistic > 50%). In multivariable meta-regression analysis, only exercise intervention intensity was found to be significantly associated with VO2max (P = 0.04); those trials with the highest average exercise intensity had the largest mean post-rehabilitation VO2max compared to control. We found considerable heterogeneity across randomized controlled trials in the magnitude of improvement in exercise capacity following exercise-based rehabilitation compared to control among patients with coronary heart disease or heart failure. Whilst higher exercise intensities were associated with a greater level of post-rehabilitation exercise capacity, there was no strong evidence to support other intervention, patient or trial factors to be predictive. © The European Society of Cardiology 2015.

Serum dehydroepiandrosterone sulphate, psychosocial factors and musculoskeletal pain in workers.

PubMed

Marinelli, A; Prodi, A; Pesel, G; Ronchese, F; Bovenzi, M; Negro, C; Larese Filon, F

2017-12-30

The serum level of dehydroepiandrosterone sulphate (DHEA-S) has been suggested as a biological marker of stress. To assess the association between serum DHEA-S, psychosocial factors and musculoskeletal (MS) pain in university workers. The study population included voluntary workers at the scientific departments of the University of Trieste (Italy) who underwent periodical health surveillance from January 2011 to June 2012. DHEA-S level was analysed in serum. The assessment tools included the General Health Questionnaire (GHQ) and a modified Nordic musculoskeletal symptoms questionnaire. The relation between DHEA-S, individual characteristics, pain perception and psychological factors was assessed by means of multivariable linear regression analysis. There were 189 study participants. The study population was characterized by high reward and low effort. Pain perception in the neck, shoulder, upper limbs, upper back and lower back was reported by 42, 32, 19, 29 and 43% of people, respectively. In multivariable regression analysis, gender, age and pain perception in the shoulder and upper limbs were significantly related to serum DHEA-S. Effort and overcommitment were related to shoulder and neck pain but not to DHEA-S. The GHQ score was associated with pain perception in different body sites and inversely to DHEA-S but significance was lost in multivariable regression analysis. DHEA-S was associated with age, gender and perception of MS pain, while effort-reward imbalance dimensions and GHQ score failed to reach the statistical significance in multivariable regression analysis. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com

A Logistic Regression Analysis of Turkey's 15-Year-Olds' Scoring above the OECD Average on the PISA'09 Reading Assessment

ERIC Educational Resources Information Center

Kasapoglu, Koray

2014-01-01

This study aims to investigate which factors are associated with Turkey's 15-year-olds' scoring above the OECD average (493) on the PISA'09 reading assessment. Collected from a total of 4,996 15-year-old students from Turkey, data were analyzed by logistic regression analysis in order to model the data of students who were split into two: (1)…

Symptoms of musculoskeletal disorders among ammunition factory workers in Turkey.

PubMed

Pinar, Tevfik; Cakmak, Z Aytul; Saygun, Meral; Akdur, Recep; Ulu, Nuriye; Keles, Isik; Saylam, Hamdi Saim

2013-01-01

The aim of this study was to assess the prevalence of symptoms of work-related musculoskeletal disorders (MSDs) and to determine the risk factors among ammunition factory workers in Turkey. This cross-sectional study was performed on 955 ammunition factory workers. Potential risk factors were investigated with a questionnaire and multivariate logistic regression analysis was performed. During the previous year, 39.3% of ammunition workers experienced symptoms of work-related MSDs. Logistic regression analysis showed smoking (odds ratio [OR] = 1.372), chronic diseases (OR = 1.795), body mass index (BMI; overweight) (OR = 1.631), working year (OR = 1.509), cold temperature (OR = 1.838), and work load (OR = 2.210) were significant independent risk factors for the development of symptoms of MSDs. It was found that both work-related conditions and personal and environmental factors are important for the development of occupational MSDs.

Development and Validation of the Work-Related Well-Being Index: Analysis of the Federal Employee Viewpoint Survey.

PubMed

Eaton, Jennifer L; Mohr, David C; Hodgson, Michael J; McPhaul, Kathleen M

2018-02-01

To describe development and validation of the work-related well-being (WRWB) index. Principal components analysis was performed using Federal Employee Viewpoint Survey (FEVS) data (N = 392,752) to extract variables representing worker well-being constructs. Confirmatory factor analysis was performed to verify factor structure. To validate the WRWB index, we used multiple regression analysis to examine relationships with burnout associated outcomes. Principal Components Analysis identified three positive psychology constructs: "Work Positivity", "Co-worker Relationships", and "Work Mastery". An 11 item index explaining 63.5% of variance was achieved. The structural equation model provided a very good fit to the data. Higher WRWB scores were positively associated with all three employee experience measures examined in regression models. The new WRWB index shows promise as a valid and widely accessible instrument to assess worker well-being.

The Effect of Missing Data Handling Methods on Goodness of Fit Indices in Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Köse, Alper

2014-01-01

The primary objective of this study was to examine the effect of missing data on goodness of fit statistics in confirmatory factor analysis (CFA). For this aim, four missing data handling methods; listwise deletion, full information maximum likelihood, regression imputation and expectation maximization (EM) imputation were examined in terms of…

Psychological factors influence the gastroesophageal reflux disease (GERD) and their effect on quality of life among firefighters in South Korea.

PubMed

Jang, Seung-Ho; Ryu, Han-Seung; Choi, Suck-Chei; Lee, Sang-Yeol

2016-10-01

The purpose of this study was to examine psychosocial factors related to gastroesophageal reflux disease (GERD) and their effects on quality of life (QOL) in firefighters. Data were collected from 1217 firefighters in a Korean province. We measured psychological symptoms using the scale. In order to observe the influence of the high-risk group on occupational stress, we conduct logistic multiple linear regression. The correlation between psychological factors and QOL was also analyzed and performed a hierarchical regression analysis. GERD was observed in 32.2% of subjects. Subjects with GERD showed higher depressive symptom, anxiety and occupational stress scores, and lower self-esteem and QOL scores relative to those observed in GERD - negative subject. GERD risk was higher for the following occupational stress subcategories: job demand, lack of reward, interpersonal conflict, and occupational climate. The stepwise regression analysis showed that depressive symptoms, occupational stress, self-esteem, and anxiety were the best predictors of QOL. The results suggest that psychological and medical approaches should be combined in GERD assessment.

Psychological factors influence the gastroesophageal reflux disease (GERD) and their effect on quality of life among firefighters in South Korea

PubMed Central

Jang, Seung-Ho; Ryu, Han-Seung; Choi, Suck-Chei; Lee, Sang-Yeol

2016-01-01

Objectives The purpose of this study was to examine psychosocial factors related to gastroesophageal reflux disease (GERD) and their effects on quality of life (QOL) in firefighters. Methods Data were collected from 1217 firefighters in a Korean province. We measured psychological symptoms using the scale. In order to observe the influence of the high-risk group on occupational stress, we conduct logistic multiple linear regression. The correlation between psychological factors and QOL was also analyzed and performed a hierarchical regression analysis. Results GERD was observed in 32.2% of subjects. Subjects with GERD showed higher depressive symptom, anxiety and occupational stress scores, and lower self-esteem and QOL scores relative to those observed in GERD – negative subject. GERD risk was higher for the following occupational stress subcategories: job demand, lack of reward, interpersonal conflict, and occupational climate. The stepwise regression analysis showed that depressive symptoms, occupational stress, self-esteem, and anxiety were the best predictors of QOL. Conclusions The results suggest that psychological and medical approaches should be combined in GERD assessment. PMID:27691373

Regression analysis for solving diagnosis problem of children's health

NASA Astrophysics Data System (ADS)

Cherkashina, Yu A.; Gerget, O. M.

2016-04-01

The paper includes results of scientific researches. These researches are devoted to the application of statistical techniques, namely, regression analysis, to assess the health status of children in the neonatal period based on medical data (hemostatic parameters, parameters of blood tests, the gestational age, vascular-endothelial growth factor) measured at 3-5 days of children's life. In this paper a detailed description of the studied medical data is given. A binary logistic regression procedure is discussed in the paper. Basic results of the research are presented. A classification table of predicted values and factual observed values is shown, the overall percentage of correct recognition is determined. Regression equation coefficients are calculated, the general regression equation is written based on them. Based on the results of logistic regression, ROC analysis was performed, sensitivity and specificity of the model are calculated and ROC curves are constructed. These mathematical techniques allow carrying out diagnostics of health of children providing a high quality of recognition. The results make a significant contribution to the development of evidence-based medicine and have a high practical importance in the professional activity of the author.

Linking Professional, School, Demographic, and Motivational Factors to Desire for Principalship

ERIC Educational Resources Information Center

Walker, Allan; Kwan, Paula

2009-01-01

Purpose: This study attempts to link four groups of contextual factors to vice principals' desire for principalship using regression analysis. Relevant items representing context are grouped under professional, school, demographic, and motivational factors. The findings aim to provide greater understanding of the desire, or lack thereof, of vice…

Risk profiles for weight gain among postmenopausal women: A classification and regression tree analysis approach

USDA-ARS?s Scientific Manuscript database

Risk factors for obesity and weight gain are typically evaluated individually while "adjusting for" the influence of other confounding factors, and few studies, if any, have created risk profiles by clustering risk factors. We identified subgroups of postmenopausal women homogeneous in their cluster...

Early Home Activities and Oral Language Skills in Middle Childhood: A Quantile Analysis

ERIC Educational Resources Information Center

Law, James; Rush, Robert; King, Tom; Westrupp, Elizabeth; Reilly, Sheena

2018-01-01

Oral language development is a key outcome of elementary school, and it is important to identify factors that predict it most effectively. Commonly researchers use ordinary least squares regression with conclusions restricted to average performance conditional on relevant covariates. Quantile regression offers a more sophisticated alternative.…

Survival analysis of postoperative nausea and vomiting in patients receiving patient-controlled epidural analgesia.

PubMed

Lee, Shang-Yi; Hung, Chih-Jen; Chen, Chih-Chieh; Wu, Chih-Cheng

2014-11-01

Postoperative nausea and vomiting as well as postoperative pain are two major concerns when patients undergo surgery and receive anesthetics. Various models and predictive methods have been developed to investigate the risk factors of postoperative nausea and vomiting, and different types of preventive managements have subsequently been developed. However, there continues to be a wide variation in the previously reported incidence rates of postoperative nausea and vomiting. This may have occurred because patients were assessed at different time points, coupled with the overall limitation of the statistical methods used. However, using survival analysis with Cox regression, and thus factoring in these time effects, may solve this statistical limitation and reveal risk factors related to the occurrence of postoperative nausea and vomiting in the following period. In this retrospective, observational, uni-institutional study, we analyzed the results of 229 patients who received patient-controlled epidural analgesia following surgery from June 2007 to December 2007. We investigated the risk factors for the occurrence of postoperative nausea and vomiting, and also assessed the effect of evaluating patients at different time points using the Cox proportional hazards model. Furthermore, the results of this inquiry were compared with those results using logistic regression. The overall incidence of postoperative nausea and vomiting in our study was 35.4%. Using logistic regression, we found that only sex, but not the total doses and the average dose of opioids, had significant effects on the occurrence of postoperative nausea and vomiting at some time points. Cox regression showed that, when patients consumed a higher average dose of opioids, this correlated with a higher incidence of postoperative nausea and vomiting with a hazard ratio of 1.286. Survival analysis using Cox regression showed that the average consumption of opioids played an important role in postoperative nausea and vomiting, a result not found by logistic regression. Therefore, the incidence of postoperative nausea and vomiting in patients cannot be reliably determined on the basis of a single visit at one point in time. Copyright © 2014. Published by Elsevier Taiwan.

Use of factor scores for predicting body weight from linear body measurements in three South African indigenous chicken breeds.

PubMed

Malomane, Dorcus Kholofelo; Norris, David; Banga, Cuthbert B; Ngambi, Jones W

2014-02-01

Body weight and weight of body parts are of economic importance. It is difficult to directly predict body weight from highly correlated morphological traits through multiple regression. Factor analysis was carried out to examine the relationship between body weight and five linear body measurements (body length, body girth, wing length, shank thickness, and shank length) in South African Venda (VN), Naked neck (NN), and Potchefstroom koekoek (PK) indigenous chicken breeds, with a view to identify those factors that define body conformation. Multiple regression was subsequently performed to predict body weight, using orthogonal traits derived from the factor analysis. Measurements were obtained from 210 chickens, 22 weeks of age, 70 chickens per breed. High correlations were obtained between body weight and all body measurements except for wing length in PK. Two factors extracted after varimax rotation explained 91, 95, and 83% of total variation in VN, NN, and PK, respectively. Factor 1 explained 73, 90, and 64% in VN, NN, and PK, respectively, and was loaded on all body measurements except for wing length in VN and PK. In a multiple regression, these two factors accounted for 72% variation in body weight in VN, while only factor 1 accounted for 83 and 74% variation in body weight in NN and PK, respectively. The two factors could be used to define body size and conformation of these breeds. Factor 1 could predict body weight in all three breeds. Body measurements can be better selected jointly to improve body weight in these breeds.

An Exploratory Factor Analysis of Coping Styles and Relationship to Depression Among a Sample of Homeless Youth.

PubMed

Brown, Samantha M; Begun, Stephanie; Bender, Kimberly; Ferguson, Kristin M; Thompson, Sanna J

2015-10-01

The extent to which measures of coping adequately capture the ways that homeless youth cope with challenges, and the influence these coping styles have on mental health outcomes, is largely absent from the literature. This study tests the factor structure of the Coping Scale using Exploratory Factor Analysis (EFA) and then investigates the relationship between coping styles and depression using hierarchical logistic regression with data from 201 homeless youth. Results of the EFA indicate a 3-factor structure of coping, which includes active, avoidant, and social coping styles. Results of the hierarchical logistic regression show that homeless youth who engage in greater avoidant coping are at increased risk of meeting criteria for major depressive disorder. Findings provide insight into the utility of a preliminary tool for assessing homeless youths' coping styles. Such assessment may identify malleable risk factors that could be addressed by service providers to help prevent mental health problems.

Logistic regression analysis of risk factors for postoperative recurrence of spinal tumors and analysis of prognostic factors.

PubMed

Zhang, Shanyong; Yang, Lili; Peng, Chuangang; Wu, Minfei

2018-02-01

The aim of the present study was to investigate the risk factors for postoperative recurrence of spinal tumors by logistic regression analysis and analysis of prognostic factors. In total, 77 male and 48 female patients with spinal tumor were selected in our hospital from January, 2010 to December, 2015 and divided into the benign (n=76) and malignant groups (n=49). All the patients underwent microsurgical resection of spinal tumors and were reviewed regularly 3 months after operation. The McCormick grading system was used to evaluate the postoperative spinal cord function. Data were subjected to statistical analysis. Of the 125 cases, 63 cases showed improvement after operation, 50 cases were stable, and deterioration was found in 12 cases. The improvement rate of patients with cervical spine tumor, which reached 56.3%, was the highest. Fifty-two cases of sensory disturbance, 34 cases of pain, 30 cases of inability to exercise, 26 cases of ataxia, and 12 cases of sphincter disorders were found after operation. Seventy-two cases (57.6%) underwent total resection, 18 cases (14.4%) received subtotal resection, 23 cases (18.4%) received partial resection, and 12 cases (9.6%) were only treated with biopsy/decompression. Postoperative recurrence was found in 57 cases (45.6%). The mean recurrence time of patients in the malignant group was 27.49±6.09 months, and the mean recurrence time of patients in the benign group was 40.62±4.34. The results were significantly different (P<0.001). Recurrence was found in 18 cases of the benign group and 39 cases of the malignant group, and results were significantly different (P<0.001). Tumor recurrence was shorter in patients with a higher McCormick grade (P<0.001). Recurrence was found in 13 patients with resection and all the patients with partial resection or biopsy/decompression. The results were significantly different (P<0.001). Logistic regression analysis of total resection-related factors showed that total resection should be the preferred treatment for patients with benign tumors, thoracic and lumbosacral tumors, and lower McCormick grade, as well as patients without syringomyelia and intramedullary tumors. Logistic regression analysis of recurrence-related factors revealed that the recurrence rate was relatively higher in patients with malignant, cervical, thoracic and lumbosacral, intramedullary tumors, and higher McCormick grade and patient received partial resection or biopsy. Tumor property, tumor location, McCormick grade, tumor resection, and intramedullary tumors are risk factors for the recurrence of spinal tumors. Clinical assessment of these risk factors may be helpful in selecting appropriate treatment strategies.

Logistic regression analysis of risk factors for postoperative recurrence of spinal tumors and analysis of prognostic factors

PubMed Central

Zhang, Shanyong; Yang, Lili; Peng, Chuangang; Wu, Minfei

2018-01-01

The aim of the present study was to investigate the risk factors for postoperative recurrence of spinal tumors by logistic regression analysis and analysis of prognostic factors. In total, 77 male and 48 female patients with spinal tumor were selected in our hospital from January, 2010 to December, 2015 and divided into the benign (n=76) and malignant groups (n=49). All the patients underwent microsurgical resection of spinal tumors and were reviewed regularly 3 months after operation. The McCormick grading system was used to evaluate the postoperative spinal cord function. Data were subjected to statistical analysis. Of the 125 cases, 63 cases showed improvement after operation, 50 cases were stable, and deterioration was found in 12 cases. The improvement rate of patients with cervical spine tumor, which reached 56.3%, was the highest. Fifty-two cases of sensory disturbance, 34 cases of pain, 30 cases of inability to exercise, 26 cases of ataxia, and 12 cases of sphincter disorders were found after operation. Seventy-two cases (57.6%) underwent total resection, 18 cases (14.4%) received subtotal resection, 23 cases (18.4%) received partial resection, and 12 cases (9.6%) were only treated with biopsy/decompression. Postoperative recurrence was found in 57 cases (45.6%). The mean recurrence time of patients in the malignant group was 27.49±6.09 months, and the mean recurrence time of patients in the benign group was 40.62±4.34. The results were significantly different (P<0.001). Recurrence was found in 18 cases of the benign group and 39 cases of the malignant group, and results were significantly different (P<0.001). Tumor recurrence was shorter in patients with a higher McCormick grade (P<0.001). Recurrence was found in 13 patients with resection and all the patients with partial resection or biopsy/decompression. The results were significantly different (P<0.001). Logistic regression analysis of total resection-related factors showed that total resection should be the preferred treatment for patients with benign tumors, thoracic and lumbosacral tumors, and lower McCormick grade, as well as patients without syringomyelia and intramedullary tumors. Logistic regression analysis of recurrence-related factors revealed that the recurrence rate was relatively higher in patients with malignant, cervical, thoracic and lumbosacral, intramedullary tumors, and higher McCormick grade and patient received partial resection or biopsy. Tumor property, tumor location, McCormick grade, tumor resection, and intramedullary tumors are risk factors for the recurrence of spinal tumors. Clinical assessment of these risk factors may be helpful in selecting appropriate treatment strategies. PMID:29434866

Modelling typhoid risk in Dhaka Metropolitan Area of Bangladesh: the role of socio-economic and environmental factors

PubMed Central

2013-01-01

Background Developing countries in South Asia, such as Bangladesh, bear a disproportionate burden of diarrhoeal diseases such as Cholera, Typhoid and Paratyphoid. These seem to be aggravated by a number of social and environmental factors such as lack of access to safe drinking water, overcrowdedness and poor hygiene brought about by poverty. Some socioeconomic data can be obtained from census data whilst others are more difficult to elucidate. This study considers a range of both census data and spatial data from other sources, including remote sensing, as potential predictors of typhoid risk. Typhoid data are aggregated from hospital admission records for the period from 2005 to 2009. The spatial and statistical structures of the data are analysed and Principal Axis Factoring is used to reduce the degree of co-linearity in the data. The resulting factors are combined into a Quality of Life index, which in turn is used in a regression model of typhoid occurrence and risk. Results The three Principal Factors used together explain 87% of the variance in the initial candidate predictors, which eminently qualifies them for use as a set of uncorrelated explanatory variables in a linear regression model. Initial regression result using Ordinary Least Squares (OLS) were disappointing, this was explainable by analysis of the spatial autocorrelation inherent in the Principal factors. The use of Geographically Weighted Regression caused a considerable increase in the predictive power of regressions based on these factors. The best prediction, determined by analysis of the Akaike Information Criterion (AIC) was found when the three factors were combined into a quality of life index, using a method previously published by others, and had a coefficient of determination of 73%. Conclusions The typhoid occurrence/risk prediction equation was used to develop the first risk map showing areas of Dhaka Metropolitan Area whose inhabitants are at greater or lesser risk of typhoid infection. This, coupled with seasonal information on typhoid incidence also reported in this paper, has the potential to advise public health professionals on developing prevention strategies such as targeted vaccination. PMID:23497202

Modelling typhoid risk in Dhaka metropolitan area of Bangladesh: the role of socio-economic and environmental factors.

PubMed

Corner, Robert J; Dewan, Ashraf M; Hashizume, Masahiro

2013-03-16

Developing countries in South Asia, such as Bangladesh, bear a disproportionate burden of diarrhoeal diseases such as cholera, typhoid and paratyphoid. These seem to be aggravated by a number of social and environmental factors such as lack of access to safe drinking water, overcrowdedness and poor hygiene brought about by poverty. Some socioeconomic data can be obtained from census data whilst others are more difficult to elucidate. This study considers a range of both census data and spatial data from other sources, including remote sensing, as potential predictors of typhoid risk. Typhoid data are aggregated from hospital admission records for the period from 2005 to 2009. The spatial and statistical structures of the data are analysed and principal axis factoring is used to reduce the degree of co-linearity in the data. The resulting factors are combined into a quality of life index, which in turn is used in a regression model of typhoid occurrence and risk. The three principal factors used together explain 87% of the variance in the initial candidate predictors, which eminently qualifies them for use as a set of uncorrelated explanatory variables in a linear regression model. Initial regression result using ordinary least squares (OLS) were disappointing, this was explainable by analysis of the spatial autocorrelation inherent in the principal factors. The use of geographically weighted regression caused a considerable increase in the predictive power of regressions based on these factors. The best prediction, determined by analysis of the Akaike information criterion (AIC) was found when the three factors were combined into a quality of life index, using a method previously published by others, and had a coefficient of determination of 73%. The typhoid occurrence/risk prediction equation was used to develop the first risk map showing areas of Dhaka metropolitan area whose inhabitants are at greater or lesser risk of typhoid infection. This, coupled with seasonal information on typhoid incidence also reported in this paper, has the potential to advise public health professionals on developing prevention strategies such as targeted vaccination.

Time series regression studies in environmental epidemiology.

PubMed

Bhaskaran, Krishnan; Gasparrini, Antonio; Hajat, Shakoor; Smeeth, Liam; Armstrong, Ben

2013-08-01

Time series regression studies have been widely used in environmental epidemiology, notably in investigating the short-term associations between exposures such as air pollution, weather variables or pollen, and health outcomes such as mortality, myocardial infarction or disease-specific hospital admissions. Typically, for both exposure and outcome, data are available at regular time intervals (e.g. daily pollution levels and daily mortality counts) and the aim is to explore short-term associations between them. In this article, we describe the general features of time series data, and we outline the analysis process, beginning with descriptive analysis, then focusing on issues in time series regression that differ from other regression methods: modelling short-term fluctuations in the presence of seasonal and long-term patterns, dealing with time varying confounding factors and modelling delayed ('lagged') associations between exposure and outcome. We finish with advice on model checking and sensitivity analysis, and some common extensions to the basic model.

Schistosomiasis Breeding Environment Situation Analysis in Dongting Lake Area

NASA Astrophysics Data System (ADS)

Li, Chuanrong; Jia, Yuanyuan; Ma, Lingling; Liu, Zhaoyan; Qian, Yonggang

2013-01-01

Monitoring environmental characteristics, such as vegetation, soil moisture et al., of Oncomelania hupensis (O. hupensis)’ spatial/temporal distribution is of vital importance to the schistosomiasis prevention and control. In this study, the relationship between environmental factors derived from remotely sensed data and the density of O. hupensis was analyzed by a multiple linear regression model. Secondly, spatial analysis of the regression residual was investigated by the semi-variogram method. Thirdly, spatial analysis of the regression residual and the multiple linear regression model were both employed to estimate the spatial variation of O. hupensis density. Finally, the approach was used to monitor and predict the spatial and temporal variations of oncomelania of Dongting Lake region, China. And the areas of potential O. hupensis habitats were predicted and the influence of Three Gorges Dam (TGB)project on the density of O. hupensis was analyzed.

Quality of life in breast cancer patients--a quantile regression analysis.

PubMed

Pourhoseingholi, Mohamad Amin; Safaee, Azadeh; Moghimi-Dehkordi, Bijan; Zeighami, Bahram; Faghihzadeh, Soghrat; Tabatabaee, Hamid Reza; Pourhoseingholi, Asma

2008-01-01

Quality of life study has an important role in health care especially in chronic diseases, in clinical judgment and in medical resources supplying. Statistical tools like linear regression are widely used to assess the predictors of quality of life. But when the response is not normal the results are misleading. The aim of this study is to determine the predictors of quality of life in breast cancer patients, using quantile regression model and compare to linear regression. A cross-sectional study conducted on 119 breast cancer patients that admitted and treated in chemotherapy ward of Namazi hospital in Shiraz. We used QLQ-C30 questionnaire to assessment quality of life in these patients. A quantile regression was employed to assess the assocciated factors and the results were compared to linear regression. All analysis carried out using SAS. The mean score for the global health status for breast cancer patients was 64.92+/-11.42. Linear regression showed that only grade of tumor, occupational status, menopausal status, financial difficulties and dyspnea were statistically significant. In spite of linear regression, financial difficulties were not significant in quantile regression analysis and dyspnea was only significant for first quartile. Also emotion functioning and duration of disease statistically predicted the QOL score in the third quartile. The results have demonstrated that using quantile regression leads to better interpretation and richer inference about predictors of the breast cancer patient quality of life.

Happiness among Adolescent Students in Thailand: Family and Non-Family Factors

ERIC Educational Resources Information Center

Gray, Rossarin Soottipong; Chamratrithirong, Aphichat; Pattaravanich, Umaporn; Prasartkul, Pramote

2013-01-01

This paper explores family and non-family factors contributing to happiness among students aged 15-18 in Thailand. Data come from the Social and Cultural Situation and Mental Health Survey (n = 905). Based on regression analysis, family factors are more important than non- family factors in explaining the variations in adolescents' happiness.…

Internal and external environmental factors affecting the performance of hospital-based home nursing care.

PubMed

Noh, J-W; Kwon, Y-D; Yoon, S-J; Hwang, J-I

2011-06-01

Numerous studies on HNC services have been carried out by signifying their needs, efficiency and effectiveness. However, no study has ever been performed to determine the critical factors associated with HNC's positive results despite the deluge of positive studies on the service. This study included all of the 89 training hospitals that were practising HNC service in Korea as of November 2006. The input factors affecting the performance were classified as either internal or external environmental factors. This analysis was conducted to understand the impact that the corresponding factors had on performance. Data were analysed by using multiple linear regressions. The internal and external environment variables affected the performance of HNC based on univariate analysis. The meaningful variables were internal environmental factors. Specifically, managerial resource (the number of operating beds and the outpatient/inpatient ratio) were meaningful when the multiple linear regression analysis was performed. Indeed, the importance of organizational culture (the passion of HNC nurses) was significant. This study, considering the limited market size of Korea, illustrates that the critical factor for the development of hospital-led HNC lies with internal environmental factors rather than external ones. Among the internal environmental factors, the hospitals' managerial resource-related factors (specifically, the passion of nurses) were the most important contributing element. © 2011 The Authors. International Nursing Review © 2011 International Council of Nurses.

Constitution of traditional chinese medicine and related factors in women of childbearing age.

PubMed

Jiang, Qiao-Yu; Li, Jue; Zheng, Liang; Wang, Guang-Hua; Wang, Jing

2018-04-01

This study investigates the constitution of traditional Chinese medicine (TCM) among women who want to be pregnant in one year and explores factors related to TCM constitution. This study was conducted on women who participated in free preconception check-ups provided by the Zhabei District Maternity and Child Care Center in Shanghai, China. The information regarding the female demographic characteristics, physical condition, history of pregnancy and childbearing, diet and behavior, and social psychological factors was collected, and TCM constitution assessment was performed. The Chi-square test, t-test, logistic regression analysis, and multinomial logistic regression analysis were used to explore the related factors of TCM constitution. The participants in this study were aged 28.3 ± 3.0 years. Approximately fifty-five women in this study had Unbalanced Constitution. Logistic regression analysis showed that Shanghai residence, dysmenorrhea, gum bleeding, aversion to vegetables, preference for raw meat, job stress, and economic stress were significantly and negatively associated with Balanced Constitution. Multinomial logistic analysis showed that Shanghai residence was significantly associated with Yang-deficiency, Yin-deficiency, and Stagnant Qi Constitutions; gum bleeding was significantly associated with Yin-deficiency, Stagnant Blood, Stagnant Qi, and Inherited Special Constitutions; aversion to vegetables was significantly associated with Damp-heat Constitution; job stress was significantly associated with Yang-deficiency, Phlegm-dampness, Damp-heat, Stagnant Blood, and Stagnant Qi Constitutions; and economic stress was significantly associated with Yang-deficiency, and Stagnant Qi Constitutions. The application of TCM constitution to preconception care would be beneficial for early identification of potential TCM constitution risks and be beneficial for early intervention (e.g., health education, and dietary education), especially during the women who do not have a medical condition and those who have related factors found in this study. Copyright © 2018. Published by Elsevier Taiwan LLC.

A population-based study on the association between rheumatoid arthritis and voice problems.

PubMed

Hah, J Hun; An, Soo-Youn; Sim, Songyong; Kim, So Young; Oh, Dong Jun; Park, Bumjung; Kim, Sung-Gyun; Choi, Hyo Geun

2016-07-01

The objective of this study was to investigate whether rheumatoid arthritis increases the frequency of organic laryngeal lesions and the subjective voice complaint rate in those with no organic laryngeal lesion. We performed a cross-sectional study using the data from 19,368 participants (418 rheumatoid arthritis patients and 18,950 controls) of the 2008-2011 Korea National Health and Nutrition Examination Survey. The associations between rheumatoid arthritis and organic laryngeal lesions/subjective voice complaints were analyzed using simple/multiple logistic regression analysis with complex sample adjusting for confounding factors, including age, sex, smoking status, stress level, and body mass index, which could provoke voice problems. Vocal nodules, vocal polyp, and vocal palsy were not associated with rheumatoid arthritis in a multiple regression analysis, and only laryngitis showed a positive association (adjusted odds ratio, 1.59; 95 % confidence interval, 1.01-2.52; P = 0.047). Rheumatoid arthritis was associated with subjective voice discomfort in a simple regression analysis, but not in a multiple regression analysis. Participants with rheumatoid arthritis were older, more often female, and had higher stress levels than those without rheumatoid arthritis. These factors were associated with subjective voice complaints in both simple and multiple regression analyses. Rheumatoid arthritis was not associated with organic laryngeal diseases except laryngitis. Rheumatoid arthritis did not increase the odds ratio for subjective voice complaints. Voice problems in participants with rheumatoid arthritis originated from the characteristics of the rheumatoid arthritis group (higher mean age, female sex, and stress level) rather than rheumatoid arthritis itself.

Ultrasound-enhanced bioscouring of greige cotton: regression analysis of process factors

USDA-ARS?s Scientific Manuscript database

Ultrasound-enhanced bioscouring process factors for greige cotton fabric are examined using custom experimental design utilizing statistical principles. An equation is presented which predicts bioscouring performance based upon percent reflectance values obtained from UV-Vis measurements of rutheniu...

Quasi-likelihood generalized linear regression analysis of fatality risk data

DOT National Transportation Integrated Search

2009-01-01

Transportation-related fatality risks is a function of many interacting human, vehicle, and environmental factors. Statisitcally valid analysis of such data is challenged both by the complexity of plausable structural models relating fatality rates t...

ENVIRONMENTAL APPLICATION OF GAS CHROMATOGRAPHY/ATOMIC EMISSION DETECTION

EPA Science Inventory

A gas chromatography/atomic emission detector (GC/AED) system has been evaluated for its applicability to environmental analysis. Detection limits, elemental response factors, and regression analysis data were determined for 58 semivolatile environmental contaminants. Detection l...

Development and Validation of the Work-Related Well-Being Index: Analysis of the Federal Employee Viewpoint Survey (FEVS).

PubMed

Eaton, Jennifer L; Mohr, David C; Hodgson, Michael J; McPhaul, Kathleen M

2017-10-11

To describe development and validation of the Work-Related Well-Being (WRWB) Index. Principal Components Analysis was performed using Federal Employee Viewpoint Survey (FEVS) data (N = 392,752) to extract variables representing worker well-being constructs. Confirmatory factor analysis was performed to verify factor structure. To validate the WRWB index, we used multiple regression analysis to examine relationships with burnout associated outcomes. PCA identified three positive psychology constructs: "Work Positivity", "Co-worker Relationships", and "Work Mastery". An 11 item index explaining 63.5% of variance was achieved. The structural equation model provided a very good fit to the data. Higher WRWB scores were positively associated with all 3 employee experience measures examined in regression models. The new WRWB index shows promise as a valid and widely accessible instrument to assess worker well-being.

Pattern variation of fish fingerling abundance in the Na Thap Tidal river of Southern Thailand: 2005-2015

NASA Astrophysics Data System (ADS)

Donroman, T.; Chesoh, S.; Lim, A.

2018-04-01

This study aimed to investigate the variation patterns of fish fingerling abundance based on month, year and sampling site. Monthly collecting data set of the Na Thap tidal river of southern Thailand, were obtained from June 2005 to October 2015. The square root transformation was employed for maintaining the fingerling data normality. Factor analysis was applied for clustering number of fingerling species and multiple linear regression was used to examine the association between fingerling density and year, month and site. Results from factor analysis classified fingerling into 3 factors based on saline preference; saline water, freshwater and ubiquitous species. The results showed a statistically high significant relation between fingerling density, month, year and site. Abundance of saline water and ubiquitous fingerling density showed similar pattern. Downstream site presented highest fingerling density whereas almost of freshwater fingerling occurred in upstream. This finding confirmed that factor analysis and the general linear regression method can be used as an effective tool for predicting and monitoring wild fingerling density in order to sustain fish stock management.

Linear regression analysis of emissions factors when firing fossil fuels and biofuels in a commercial water-tube boiler

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharon Falcone Miller; Bruce G. Miller

2007-12-15

This paper compares the emissions factors for a suite of liquid biofuels (three animal fats, waste restaurant grease, pressed soybean oil, and a biodiesel produced from soybean oil) and four fossil fuels (i.e., natural gas, No. 2 fuel oil, No. 6 fuel oil, and pulverized coal) in Penn State's commercial water-tube boiler to assess their viability as fuels for green heat applications. The data were broken into two subsets, i.e., fossil fuels and biofuels. The regression model for the liquid biofuels (as a subset) did not perform well for all of the gases. In addition, the coefficient in the modelsmore » showed the EPA method underestimating CO and NOx emissions. No relation could be studied for SO{sub 2} for the liquid biofuels as they contain no sulfur; however, the model showed a good relationship between the two methods for SO{sub 2} in the fossil fuels. AP-42 emissions factors for the fossil fuels were also compared to the mass balance emissions factors and EPA CFR Title 40 emissions factors. Overall, the AP-42 emissions factors for the fossil fuels did not compare well with the mass balance emissions factors or the EPA CFR Title 40 emissions factors. Regression analysis of the AP-42, EPA, and mass balance emissions factors for the fossil fuels showed a significant relationship only for CO{sub 2} and SO{sub 2}. However, the regression models underestimate the SO{sub 2} emissions by 33%. These tests illustrate the importance in performing material balances around boilers to obtain the most accurate emissions levels, especially when dealing with biofuels. The EPA emissions factors were very good at predicting the mass balance emissions factors for the fossil fuels and to a lesser degree the biofuels. While the AP-42 emissions factors and EPA CFR Title 40 emissions factors are easier to perform, especially in large, full-scale systems, this study illustrated the shortcomings of estimation techniques. 23 refs., 3 figs., 8 tabs.« less

[Relationship between social-psycological factors and quality of life in old women with coronary heart disease].

PubMed

Wu, Lin-Na; Yang, Guo-Yun; Ge, Ning

2013-03-01

To investigate the influence of depression, social supports and quality of sleep and quality of life on old women who were 60 years or older and postmenopause with coronary heart disease. 125 old women with coronary heart disease completed questionnaires of Seattle Angina Questionnaire (SAQ), Social Support Scale (SSRS) and Self-rating Depression Scale (SDS). Logistic regression analysis and Spearman correlation analysis were performed to evaluate the relationship between social-psycological factors and quality of life. 120 of questionnaires wereeffective (representing 96% of all collected questionnaires). Regression analysis showed that marital status (OR = 2.450), education (OR = 0.520), income (OR = 19.541) and course of disease (OR = 0.309) were associated with QOL in CHD (P < 0.05). Spearman analysis demonstrated that there were negative correlations between SQA score and PSQI and depression scores (r = -0.771, P < 0.01; r = -0.703, P < 0.05); and positive correlation between SQA score and Social support score (r = 0.565, P < 0.05). Social-psychological factors might influence the quality of life in old women with coronary heart disease, it is important that physicians pay attention to these factors when they treat old women with coronary heart disease.

A Time Series Analysis: Weather Factors, Human Migration and Malaria Cases in Endemic Area of Purworejo, Indonesia, 2005–2014

PubMed Central

REJEKI, Dwi Sarwani Sri; NURHAYATI, Nunung; AJI, Budi; MURHANDARWATI, E. Elsa Herdiana; KUSNANTO, Hari

2018-01-01

Background: Climatic and weather factors become important determinants of vector-borne diseases transmission like malaria. This study aimed to prove relationships between weather factors with considering human migration and previous case findings and malaria cases in endemic areas in Purworejo during 2005–2014. Methods: This study employed ecological time series analysis by using monthly data. The independent variables were the maximum temperature, minimum temperature, maximum humidity, minimum humidity, precipitation, human migration, and previous malaria cases, while the dependent variable was positive malaria cases. Three models of count data regression analysis i.e. Poisson model, quasi-Poisson model, and negative binomial model were applied to measure the relationship. The least Akaike Information Criteria (AIC) value was also performed to find the best model. Negative binomial regression analysis was considered as the best model. Results: The model showed that humidity (lag 2), precipitation (lag 3), precipitation (lag 12), migration (lag1) and previous malaria cases (lag 12) had a significant relationship with malaria cases. Conclusion: Weather, migration and previous malaria cases factors need to be considered as prominent indicators for the increase of malaria case projection. PMID:29900134

Multinomial Logistic Regression Predicted Probability Map To Visualize The Influence Of Socio-Economic Factors On Breast Cancer Occurrence in Southern Karnataka

NASA Astrophysics Data System (ADS)

Madhu, B.; Ashok, N. C.; Balasubramanian, S.

2014-11-01

Multinomial logistic regression analysis was used to develop statistical model that can predict the probability of breast cancer in Southern Karnataka using the breast cancer occurrence data during 2007-2011. Independent socio-economic variables describing the breast cancer occurrence like age, education, occupation, parity, type of family, health insurance coverage, residential locality and socioeconomic status of each case was obtained. The models were developed as follows: i) Spatial visualization of the Urban- rural distribution of breast cancer cases that were obtained from the Bharat Hospital and Institute of Oncology. ii) Socio-economic risk factors describing the breast cancer occurrences were complied for each case. These data were then analysed using multinomial logistic regression analysis in a SPSS statistical software and relations between the occurrence of breast cancer across the socio-economic status and the influence of other socio-economic variables were evaluated and multinomial logistic regression models were constructed. iii) the model that best predicted the occurrence of breast cancer were identified. This multivariate logistic regression model has been entered into a geographic information system and maps showing the predicted probability of breast cancer occurrence in Southern Karnataka was created. This study demonstrates that Multinomial logistic regression is a valuable tool for developing models that predict the probability of breast cancer Occurrence in Southern Karnataka.

[Risk factors for anorexia in children].

PubMed

Liu, Wei-Xiao; Lang, Jun-Feng; Zhang, Qin-Feng

2016-11-01

To investigate the risk factors for anorexia in children, and to reduce the prevalence of anorexia in children. A questionnaire survey and a case-control study were used to collect the general information of 150 children with anorexia (case group) and 150 normal children (control group). Univariate analysis and multivariate logistic stepwise regression analysis were performed to identify the risk factors for anorexia in children. The results of the univariate analysis showed significant differences between the case and control groups in the age in months when supplementary food were added, feeding pattern, whether they liked meat, vegetables and salty food, whether they often took snacks and beverages, whether they liked to play while eating, and whether their parents asked them to eat food on time (P<0.05). The results of the multivariate logistic regression analysis showed that late addition of supplementary food (OR=5.408), high frequency of taking snacks and/or drinks (OR=11.813), and eating while playing (OR=6.654) were major risk factors for anorexia in children. Liking of meat (OR=0.093) and vegetables (OR=0.272) and eating on time required by parents (OR=0.079) were protective factors against anorexia in children. Timely addition of supplementary food, a proper diet, and development of children's proper eating and living habits can reduce the incidence of anorexia in children.

Gene expression factor analysis to differentiate pathways linked to fibromyalgia, chronic fatigue syndrome, and depression in a diverse patient sample

PubMed Central

Iacob, Eli; Light, Alan R.; Donaldson, Gary W.; Okifuji, Akiko; Hughen, Ronald W.; White, Andrea T.; Light, Kathleen C.

2015-01-01

Objective To determine if independent candidate genes can be grouped into meaningful biological factors and if these factors are associated with the diagnosis of chronic fatigue syndrome (CFS) and fibromyalgia (FMS) while controlling for co-morbid depression, sex, and age. Methods We included leukocyte mRNA gene expression from a total of 261 individuals including healthy controls (n=61), patients with FMS only (n=15), CFS only (n=33), co-morbid CFS and FMS (n=79), and medication-resistant (n=42) or medication-responsive (n=31) depression. We used Exploratory Factor Analysis (EFA) on 34 candidate genes to determine factor scores and regression analysis to examine if these factors were associated with specific diagnoses. Results EFA resulted in four independent factors with minimal overlap of genes between factors explaining 51% of the variance. We labeled these factors by function as: 1) Purinergic and cellular modulators; 2) Neuronal growth and immune function; 3) Nociception and stress mediators; 4) Energy and mitochondrial function. Regression analysis predicting these biological factors using FMS, CFS, depression severity, age, and sex revealed that greater expression in Factors 1 and 3 was positively associated with CFS and negatively associated with depression severity (QIDS score), but not associated with FMS. Conclusion Expression of candidate genes can be grouped into meaningful clusters, and CFS and depression are associated with the same 2 clusters but in opposite directions when controlling for co-morbid FMS. Given high co-morbid disease and interrelationships between biomarkers, EFA may help determine patient subgroups in this population based on gene expression. PMID:26097208

Introduction to the use of regression models in epidemiology.

PubMed

Bender, Ralf

2009-01-01

Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

Regression Analysis and Calibration Recommendations for the Characterization of Balance Temperature Effects

NASA Technical Reports Server (NTRS)

Ulbrich, N.; Volden, T.

2018-01-01

Analysis and use of temperature-dependent wind tunnel strain-gage balance calibration data are discussed in the paper. First, three different methods are presented and compared that may be used to process temperature-dependent strain-gage balance data. The first method uses an extended set of independent variables in order to process the data and predict balance loads. The second method applies an extended load iteration equation during the analysis of balance calibration data. The third method uses temperature-dependent sensitivities for the data analysis. Physical interpretations of the most important temperature-dependent regression model terms are provided that relate temperature compensation imperfections and the temperature-dependent nature of the gage factor to sets of regression model terms. Finally, balance calibration recommendations are listed so that temperature-dependent calibration data can be obtained and successfully processed using the reviewed analysis methods.

[Influencing factors on depression among medical staff in Hunan province under ordinal regression analysis].

PubMed

Liu, Zhi-yu; Zhong, Meng; Hai, Yan; Du, Qi-yun; Wang, Ai-hua; Xie, Dong-hua

2012-11-01

To understand the situation of depression and its related influencing factors among medical staff in Hunan province. Data were collected through random sampling with multi-stage stratified cluster. Wilcoxon rank sum test, Kruskal-Wallis H test and Ordinal regression analysis were used for data analysis by SPSS 17.0 software. This survey was including 16,000 medical personnel with 14, 988 valid questionnaires and the effective rate was 93.68%. from the single factor analysis showed that factors as: level of the hospital grading, gender, education background, age, occupation, title, departments, the number of continue education, income, working overtime every week, the frequency of night work, the number of patients treated in the emergency room etc., had statistical significances (P < 0.05). Data from ordinal regression showed that the probabilities related to depression that clinicians and nurses suffering from were 1.58 times more than the pharmacists (OR = 1.58, 95%CI: 1.30 - 1.92). The probability among those whose income was less than 2000 Yuan/month was 2.19 times of the ones whose earned more than 3000 Yuan/month (OR = 2.19, 95%CI: 2.05 - 2.35). The higher the numbers of days with working overtime every week, the frequencies of night work, and the numbers of patients being treated at the emergency room, with more probabilities of the people with depression seen in our study. Depression seemed to be common among doctors and nurses. We suggested that the government need to increase the monthly income and to reduce the workload and intensity, lessen the overworking time, etc.

A comparison between Bayes discriminant analysis and logistic regression for prediction of debris flow in southwest Sichuan, China

NASA Astrophysics Data System (ADS)

Xu, Wenbo; Jing, Shaocai; Yu, Wenjuan; Wang, Zhaoxian; Zhang, Guoping; Huang, Jianxi

2013-11-01

In this study, the high risk areas of Sichuan Province with debris flow, Panzhihua and Liangshan Yi Autonomous Prefecture, were taken as the studied areas. By using rainfall and environmental factors as the predictors and based on the different prior probability combinations of debris flows, the prediction of debris flows was compared in the areas with statistical methods: logistic regression (LR) and Bayes discriminant analysis (BDA). The results through the comprehensive analysis show that (a) with the mid-range scale prior probability, the overall predicting accuracy of BDA is higher than those of LR; (b) with equal and extreme prior probabilities, the overall predicting accuracy of LR is higher than those of BDA; (c) the regional predicting models of debris flows with rainfall factors only have worse performance than those introduced environmental factors, and the predicting accuracies of occurrence and nonoccurrence of debris flows have been changed in the opposite direction as the supplemented information.

Multicollinearity and Regression Analysis

NASA Astrophysics Data System (ADS)

Daoud, Jamal I.

2017-12-01

In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.

Analysis and compensation for the effect of the catheter position on image intensities in intravascular optical coherence tomography

NASA Astrophysics Data System (ADS)

Liu, Shengnan; Eggermont, Jeroen; Wolterbeek, Ron; Broersen, Alexander; Busk, Carol A. G. R.; Precht, Helle; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke

2016-12-01

Intravascular optical coherence tomography (IVOCT) is an imaging technique that is used to analyze the underlying cause of cardiovascular disease. Because a catheter is used during imaging, the intensities can be affected by the catheter position. This work aims to analyze the effect of the catheter position on IVOCT image intensities and to propose a compensation method to minimize this effect in order to improve the visualization and the automatic analysis of IVOCT images. The effect of catheter position is modeled with respect to the distance between the catheter and the arterial wall (distance-dependent factor) and the incident angle onto the arterial wall (angle-dependent factor). A light transmission model incorporating both factors is introduced. On the basis of this model, the interaction effect of both factors is estimated with a hierarchical multivariant linear regression model. Statistical analysis shows that IVOCT intensities are significantly affected by both factors with p<0.001, as either aspect increases the intensity decreases. This effect differs for different pullbacks. The regression results were used to compensate for this effect. Experiments show that the proposed compensation method can improve the performance of the automatic bioresorbable vascular scaffold strut detection.

Using Recursive Regression to Explore Nonlinear Relationships and Interactions: A Tutorial Applied to a Multicultural Education Study

ERIC Educational Resources Information Center

Strang, Kenneth David

2009-01-01

This paper discusses how a seldom-used statistical procedure, recursive regression (RR), can numerically and graphically illustrate data-driven nonlinear relationships and interaction of variables. This routine falls into the family of exploratory techniques, yet a few interesting features make it a valuable compliment to factor analysis and…

Comparing Linear Discriminant Function with Logistic Regression for the Two-Group Classification Problem.

ERIC Educational Resources Information Center

Fan, Xitao; Wang, Lin

The Monte Carlo study compared the performance of predictive discriminant analysis (PDA) and that of logistic regression (LR) for the two-group classification problem. Prior probabilities were used for classification, but the cost of misclassification was assumed to be equal. The study used a fully crossed three-factor experimental design (with…

Effects of Social Class and School Conditions on Educational Enrollment and Achievement of Boys and Girls in Rural Viet Nam

ERIC Educational Resources Information Center

Nguyen, Phuong L.

2006-01-01

This study examines the effects of parental SES, school quality, and community factors on children's enrollment and achievement in rural areas in Viet Nam, using logistic regression and ordered logistic regression. Multivariate analysis reveals significant differences in educational enrollment and outcomes by level of household expenditures and…

Factors Associated with Participation in Employment for High School Leavers with Autism

ERIC Educational Resources Information Center

Chiang, Hsu-Min; Cheung, Ying Kuen; Li, Huacheng; Tsai, Luke Y.

2013-01-01

This study aimed to identify the factors associated with participation in employment for high school leavers with autism. A secondary data analysis of the National Longitudinal Transition Study 2 (NLTS2) data was performed. Potential factors were assessed using a weighted multivariate logistic regression. This study found that annual household…

Analysis of Academic Administrators' Attitudes: Annual Evaluations and Factors That Improve Teaching

ERIC Educational Resources Information Center

Cherry, Brian D.; Grasse, Nathan; Kapla, Dale; Hamel, Brad

2017-01-01

This article examines academic administrators' attitudes towards the academic evaluation process in the US and those factors that are utilised to improve teaching. We use path regressions to examine satisfaction with evaluation procedures, as well as the direct and indirect effects of these factors on perceptions of whether the evaluation process…

Unpredictability of fighter pilots' g duration tolerance by anthropometric and physiological characteristics.

PubMed

Park, Myunghwan; Yoo, Seunghoon; Seol, Hyeongju; Kim, Cheonyoung; Hong, Youngseok

2015-04-01

While the factors affecting fighter pilots' G level tolerance have been widely accepted, the factors affecting fighter pilots' G duration tolerance have not been well understood. Thirty-eight subjects wearing anti-G suits were exposed to sustained high G forces using a centrifuge. The subjects exerted AGSM and decelerated the centrifuge when they reached the point of loss of peripheral vision. The G profile consisted of a +2.3 G onset rate, +7.3 G single plateau, and -1.6 G offset rate. Each subject's G tolerance time was recorded and the relationship between the tolerance time and the subject's anthropometric and physiological factors were analyzed. The mean tolerance time of the 38 subjects was 31.6 s, and the min and max tolerance times were 20 s and 58 s, respectively. The correlation analysis indicated that none of the factors had statistically significant correlations with the subjects' G duration tolerance. Stepwise multiple regression analysis showed that G duration tolerance was not dependent on any personal factors of the subjects. After the values of personal factors were simplified into 0 or 1, the t-test analysis showed that subjects' heights were inversely correlated with G duration tolerance at a statistically significant level. However, a logistic regression analysis suggested that the effect of the height factor to a pilot's G duration tolerance was too weak to be used as a predictor of a pilot's G tolerance. Fighter pilots' G duration tolerance could not be predicted by pilots' anthropometric and physiological factors.

Evaluating the relationship between wildfire extent and nitrogen dry deposition in a boreal forest in interior Alaska

NASA Astrophysics Data System (ADS)

Nagano, Hirohiko; Iwata, Hiroki

2017-03-01

Alaska wildfires may play an important role in nitrogen (N) dry deposition in Alaskan boreal forests. Here we used annual N dry deposition data measured by CASTNET at Denali National Park (DEN417) during 1999-2013, to evaluate the relationships between wildfire extent and N dry deposition in Alaska. We established six potential factors for multiple regression analysis, including burned area within 100 km of DEN417 (BA100km) and in other distant parts of Alaska (BAAK), the sum of indexes of North Atlantic Oscillation and Arctic Oscillation (OI), number of days with negative OI (OIday), precipitation (PRCP), and number of days with PRCP (PRCPday). Multiple regression analysis was conducted for both time scales, annual (using only annual values of factors) and six-month (using annual values of BAAK and BA100km, and fire and non-fire seasons' values of other four factors) time scales. Together, BAAK, BA100km, and OIday, along with PRCPday in the case of the six-month scale, explained more than 92% of the interannual variation in N dry deposition. The influence of BA100km on N dry deposition was ten-fold greater than from BAAK; the qualitative contribution was almost zero, however, due to the small BA100km. BAAK was the leading explanatory factor, with a 15 ± 14% contribution. We further calculated N dry deposition during 1950-2013 using the obtained regression equation and long-term records for the factors. The N dry deposition calculated for 1950-2013 revealed that an increased occurrence of wildfires during the 2000s led to the maximum N dry deposition exhibited during this decade. As a result, the effect of BAAK on N dry deposition remains sufficiently large, even when large possible uncertainties (>40%) in the measurement of N dry deposition are taken into account for the multiple regression analysis.

[Risk factors for elevated serum total bile acid in preterm infants].

PubMed

Song, Yan-Ting; Wang, Yong-Qin; Zhao, Yue-Hua; Zhu, Hai-Ling; Liu, Qian; Zhang, Xiao; Gao, Yi-Wen; Zhang, Wei-Ye; Sang, Yu-Tong

2018-03-01

To study the risk factors for elevated serum total bile acid (TBA) in preterm infants. A retrospective analysis was performed for the clinical data of 216 preterm infants who were admitted to the neonatal intensive care unit. According to the presence or absence of elevated TBA (TBA >24.8 μmol/L), the preterm infants were divided into elevated TBA group with 53 infants and non-elevated TBA group with 163 infants. A univariate analysis and an unconditional multivariate logistic regression analysis were used to investigate the risk factors for elevated TBA. The univariate analysis showed that there were significant differences between the elevated TBA group and the non-elevated TBA group in gestational age at birth, birth weight, proportion of small-for-gestational-age infants, proportion of infants undergoing ventilator-assisted ventilation, fasting time, parenteral nutrition time, and incidence of neonatal respiratory failure and sepsis (P<0.05). The unconditional multivariate logistic regression analysis showed that low birth weight (OR=3.84, 95%CI: 1.53-9.64) and neonatal sepsis (OR=2.56, 95%CI: 1.01-6.47) were independent risk factors for elevated TBA in preterm infants. Low birth weight and neonatal sepsis may lead to elevated TBA in preterm infants.

Use of linear regression models to determine influence factors on the concentration levels of radon in occupied houses

NASA Astrophysics Data System (ADS)

Buermeyer, Jonas; Gundlach, Matthias; Grund, Anna-Lisa; Grimm, Volker; Spizyn, Alexander; Breckow, Joachim

2016-09-01

This work is part of the analysis of the effects of constructional energy-saving measures to radon concentration levels in dwellings performed on behalf of the German Federal Office for Radiation Protection. In parallel to radon measurements for five buildings, both meteorological data outside the buildings and the indoor climate factors were recorded. In order to access effects of inhabited buildings, the amount of carbon dioxide (CO2) was measured. For a statistical linear regression model, the data of one object was chosen as an example. Three dummy variables were extracted from the process of the CO2 concentration to provide information on the usage and ventilation of the room. The analysis revealed a highly autoregressive model for the radon concentration with additional influence by the natural environmental factors. The autoregression implies a strong dependency on a radon source since it reflects a backward dependency in time. At this point of the investigation, it cannot be determined whether the influence by outside factors affects the source of radon or the habitant’s ventilation behavior resulting in variation of the occurring concentration levels. In any case, the regression analysis might provide further information that would help to distinguish these effects. In the next step, the influence factors will be weighted according to their impact on the concentration levels. This might lead to a model that enables the prediction of radon concentration levels based on the measurement of CO2 in combination with environmental parameters, as well as the development of advices for ventilation.

Job compensable factors and factor weights derived from job analysis data.

PubMed

Chi, Chia-Fen; Chang, Tin-Chang; Hsia, Ping-Ling; Song, Jen-Chieh

2007-06-01

Government data on 1,039 job titles in Taiwan were analyzed to assess possible relationships between job attributes and compensation. For each job title, 79 specific variables in six major classes (required education and experience, aptitude, interest, work temperament, physical demands, task environment) were coded to derive the statistical predictors of wage for managers, professionals, technical, clerical, service, farm, craft, operatives, and other workers. Of the 79 variables, only 23 significantly related to pay rate were subjected to a factor and multiple regression analysis for predicting monthly wages. Given the heterogeneous nature of collected job titles, a 4-factor solution (occupational knowledge and skills, human relations skills, work schedule hardships, physical hardships) explaining 43.8% of the total variance but predicting only 23.7% of the monthly pay rate was derived. On the other hand, multiple regression with 9 job analysis items (required education, professional training, professional certificate, professional experience, coordinating, leadership and directing, demand on hearing, proportion of shift working indoors, outdoors and others, rotating shift) better predicted pay and explained 32.5% of the variance. A direct comparison of factors and subfactors of job evaluation plans indicated mental effort and responsibility (accountability) had not been measured with the current job analysis data. Cross-validation of job evaluation factors and ratings with the wage rates is required to calibrate both.

Risk Factors for Child Malnutrition in Bangladesh: A Multilevel Analysis of a Nationwide Population-Based Survey.

PubMed

Chowdhury, Mohammad Rocky Khan; Rahman, Mohammad Shafiur; Khan, Mohammad Mubarak Hossain; Mondal, Mohammad Nazrul Islam; Rahman, Mohammad Mosiur; Billah, Baki

2016-05-01

To identify the prevalence and risk factors of child malnutrition in Bangladesh. Data was extracted from the Bangladesh Demographic Health Survey (2011). The outcome measures were stunting, wasting, and underweight. χ(2) analysis was performed to find the association of outcome variables with selected factors. Multilevel logistic regression models with a random intercept at each of the household and community levels were used to identify the risk factors of stunting, wasting, and underweight. From the 2011 survey, 7568 children less than 5 years of age were included in the current analysis. The overall prevalence of stunting, wasting, and underweight was 41.3% (95% CI 39.0-42.9). The χ(2) test and multilevel logistic regression analysis showed that the variables age, sex, mother's body mass index, mother's educational status, father's educational status, place of residence, socioeconomic status, community status, religion, region of residence, and food security are significant factors of child malnutrition. Children with poor socioeconomic and community status were at higher risk of malnutrition. Children from food insecure families were more likely to be malnourished. Significant community- and household-level variations were found. The prevalence of child malnutrition is still high in Bangladesh, and the risk was assessed at several multilevel factors. Therefore, prevention of malnutrition should be given top priority as a major public health intervention. Copyright © 2016 Elsevier Inc. All rights reserved.

Intraoperative factors associated with delayed recovery of liver function after hepatectomy: analysis of 1969 living donors.

PubMed

Choi, S-S; Cho, S-S; Ha, T-Y; Hwang, S; Lee, S-G; Kim, Y-K

2016-02-01

The safety of healthy living donors who are undergoing hepatic resection is a primary concern. We aimed to identify intraoperative anaesthetic and surgical factors associated with delayed recovery of liver function after hepatectomy in living donors. We retrospectively analysed 1969 living donors who underwent hepatectomy for living donor liver transplantation. Delayed recovery of hepatic function was defined by increases in international normalised ratio of prothrombin time and concomitant hyperbilirubinaemia on or after post-operative day 5. Univariate and multivariate logistic regression analyses were performed to determine the factors associated with delayed recovery of hepatic function after living donor hepatectomy. Delayed recovery of liver function after donor hepatectomy was observed in 213 (10.8%) donors. Univariate logistic regression analysis showed that sevoflurane anaesthesia, synthetic colloid, donor age, body mass index, fatty change and remnant liver volume were significant factors for prediction of delayed recovery of hepatic function. Multivariate logistic regression analysis showed that independent factors significantly associated with delayed recovery of liver function after donor hepatectomy were sevoflurane anaesthesia (odds ratio = 3.514, P < 0.001), synthetic colloid (odds ratio = 1.045, P = 0.033), donor age (odds ratio = 0.970, P = 0.003), female gender (odds ratio = 1.512, P = 0.014) and remnant liver volume (odds ratio = 0.963, P < 0.001). Anaesthesia with sevoflurane was an independent factor in predicting delayed recovery of hepatic function after donor hepatectomy. Although synthetic colloid may be associated with delayed recovery of hepatic function after donor hepatectomy, further study is required. These results can provide useful information on perioperative management of living liver donors. © 2015 The Acta Anaesthesiologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Vitamin D insufficiency and subclinical atherosclerosis in non-diabetic males living with HIV.

PubMed

Portilla, Joaquín; Moreno-Pérez, Oscar; Serna-Candel, Carmen; Escoín, Corina; Alfayate, Rocio; Reus, Sergio; Merino, Esperanza; Boix, Vicente; Giner, Livia; Sánchez-Payá, José; Picó, Antonio

2014-01-01

Vitamin D insufficiency (VDI) has been associated with increased cardiovascular risk in the non-HIV population. This study evaluates the relationship among serum 25-hydroxyvitamin D [25(OH)D] levels, cardiovascular risk factors, adipokines, antiviral therapy (ART) and subclinical atherosclerosis in HIV-infected males. A cross-sectional study in ambulatory care was made in non-diabetic patients living with HIV. VDI was defined as 25(OH)D serum levels <75 nmol/L. Fasting lipids, glucose, inflammatory markers (tumour necrosis factor-α, interleukin-6, high-sensitivity C-reactive protein) and endothelial markers (plasminogen activator inhibitor-1, or PAI-I) were measured. The common carotid artery intima-media thickness (C-IMT) was determined. A multivariate logistic regression analysis was made to identify factors associated with the presence of VDI, while multivariate linear regression analysis was used to identify factors associated with common C-IMT. Eighty-nine patients were included (age 42 ± 8 years), 18.9% were in CDC (US Centers for Disease Control and Prevention) stage C and 75 were on ART. VDI was associated with ART exposure, sedentary lifestyle, higher triglycerides levels and PAI-I. In univariate analysis, VDI was associated with greater common C-IMT. The multivariate linear regression model, adjusted by confounding factors, revealed an independent association between common C-IMT and patient age, time of exposure to protease inhibitors (PIs) and impaired fasting glucose (IFG). In contrast, there were no independent associations between common C-IMT and VDI or inflammatory and endothelial markers. VDI was not independently associated with subclinical atherosclerosis in non-diabetic males living with HIV. Older age, a longer exposure to PIs, and IFG were independent factors associated with common C-IMT in this population.

Sensitivity Analysis of Mechanical Parameters of Different Rock Layers to the Stability of Coal Roadway in Soft Rock Strata

PubMed Central

Zhao, Zeng-hui; Wang, Wei-ming; Gao, Xin; Yan, Ji-xing

2013-01-01

According to the geological characteristics of Xinjiang Ili mine in western area of China, a physical model of interstratified strata composed of soft rock and hard coal seam was established. Selecting the tunnel position, deformation modulus, and strength parameters of each layer as influencing factors, the sensitivity coefficient of roadway deformation to each parameter was firstly analyzed based on a Mohr-Columb strain softening model and nonlinear elastic-plastic finite element analysis. Then the effect laws of influencing factors which showed high sensitivity were further discussed. Finally, a regression model for the relationship between roadway displacements and multifactors was obtained by equivalent linear regression under multiple factors. The results show that the roadway deformation is highly sensitive to the depth of coal seam under the floor which should be considered in the layout of coal roadway; deformation modulus and strength of coal seam and floor have a great influence on the global stability of tunnel; on the contrary, roadway deformation is not sensitive to the mechanical parameters of soft roof; roadway deformation under random combinations of multi-factors can be deduced by the regression model. These conclusions provide theoretical significance to the arrangement and stability maintenance of coal roadway. PMID:24459447

Wolf population regulation revisited: again

USGS Publications Warehouse

McRoberts, Ronald E.; Mech, L. David

2014-01-01

The long-accepted conclusion that wolf density is regulated by nutrition was recently challenged, and the conclusion was reached that, at greater levels of prey biomass, social factors such as intraspecific strife and territoriality tend to regulate wolf density. We reanalyzed the data used in that study for 2 reasons: 1) we disputed the use of 2 data points, and 2) because of recognized heteroscedasticity, we used weighted-regression analysis instead of the unweighted regressions used in the original study. We concluded that the data do not support the hypothesis that wolf densities are regulated by social factors.

Logistic regression analysis to predict Medical Licensing Examination of Thailand (MLET) Step1 success or failure.

PubMed

Wanvarie, Samkaew; Sathapatayavongs, Boonmee

2007-09-01

The aim of this paper was to assess factors that predict students' performance in the Medical Licensing Examination of Thailand (MLET) Step1 examination. The hypothesis was that demographic factors and academic records would predict the students' performance in the Step1 Licensing Examination. A logistic regression analysis of demographic factors (age, sex and residence) and academic records [high school grade point average (GPA), National University Entrance Examination Score and GPAs of the pre-clinical years] with the MLET Step1 outcome was accomplished using the data of 117 third-year Ramathibodi medical students. Twenty-three (19.7%) students failed the MLET Step1 examination. Stepwise logistic regression analysis showed that the significant predictors of MLET Step1 success/failure were residence background and GPAs of the second and third preclinical years. For students whose sophomore and third-year GPAs increased by an average of 1 point, the odds of passing the MLET Step1 examination increased by a factor of 16.3 and 12.8 respectively. The minimum GPAs for students from urban and rural backgrounds to pass the examination were estimated from the equation (2.35 vs 2.65 from 4.00 scale). Students from rural backgrounds and/or low-grade point averages in their second and third preclinical years of medical school are at risk of failing the MLET Step1 examination. They should be given intensive tutorials during the second and third pre-clinical years.

Risk factors for amendment in type, duration and setting of prescribed outpatient parenteral antimicrobial therapy (OPAT) for adult patients with cellulitis: a retrospective cohort study and CART analysis.

PubMed

Quirke, Michael; Curran, Emma May; O'Kelly, Patrick; Moran, Ruth; Daly, Eimear; Aylward, Seamus; McElvaney, Gerry; Wakai, Abel

2018-01-01

To measure the percentage rate and risk factors for amendment in the type, duration and setting of outpatient parenteral antimicrobial therapy ( OPAT) for the treatment of cellulitis. A retrospective cohort study of adult patients receiving OPAT for cellulitis was performed. Treatment amendment (TA) was defined as hospital admission or change in antibiotic therapy in order to achieve clinical response. Multivariable logistic regression (MVLR) and classification and regression tree (CART) analysis were performed. There were 307 patients enrolled. TA occurred in 36 patients (11.7%). Significant risk factors for TA on MVLR were increased age, increased Numerical Pain Scale Score (NPSS) and immunocompromise. The median OPAT duration was 7 days. Increased age, heart rate and C reactive protein were associated with treatment prolongation. CART analysis selected age <64.5 years, female gender and NPSS <2.5 in the final model, generating a low-sensitivity (27.8%), high-specificity (97.1%) decision tree. Increased age, NPSS and immunocompromise were associated with OPAT amendment. These identified risk factors can be used to support an evidence-based approach to patient selection for OPAT in cellulitis. The CART algorithm has good specificity but lacks sensitivity and is shown to be inferior in this study to logistic regression modelling. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Comparison of Survival Models for Analyzing Prognostic Factors in Gastric Cancer Patients

PubMed

Habibi, Danial; Rafiei, Mohammad; Chehrei, Ali; Shayan, Zahra; Tafaqodi, Soheil

2018-03-27

Objective: There are a number of models for determining risk factors for survival of patients with gastric cancer. This study was conducted to select the model showing the best fit with available data. Methods: Cox regression and parametric models (Exponential, Weibull, Gompertz, Log normal, Log logistic and Generalized Gamma) were utilized in unadjusted and adjusted forms to detect factors influencing mortality of patients. Comparisons were made with Akaike Information Criterion (AIC) by using STATA 13 and R 3.1.3 softwares. Results: The results of this study indicated that all parametric models outperform the Cox regression model. The Log normal, Log logistic and Generalized Gamma provided the best performance in terms of AIC values (179.2, 179.4 and 181.1, respectively). On unadjusted analysis, the results of the Cox regression and parametric models indicated stage, grade, largest diameter of metastatic nest, largest diameter of LM, number of involved lymph nodes and the largest ratio of metastatic nests to lymph nodes, to be variables influencing the survival of patients with gastric cancer. On adjusted analysis, according to the best model (log normal), grade was found as the significant variable. Conclusion: The results suggested that all parametric models outperform the Cox model. The log normal model provides the best fit and is a good substitute for Cox regression. Creative Commons Attribution License

Three-way analysis of the UPLC-PDA dataset for the multicomponent quantitation of hydrochlorothiazide and olmesartan medoxomil in tablets by parallel factor analysis and three-way partial least squares.

PubMed

Dinç, Erdal; Ertekin, Zehra Ceren

2016-01-01

An application of parallel factor analysis (PARAFAC) and three-way partial least squares (3W-PLS1) regression models to ultra-performance liquid chromatography-photodiode array detection (UPLC-PDA) data with co-eluted peaks in the same wavelength and time regions was described for the multicomponent quantitation of hydrochlorothiazide (HCT) and olmesartan medoxomil (OLM) in tablets. Three-way dataset of HCT and OLM in their binary mixtures containing telmisartan (IS) as an internal standard was recorded with a UPLC-PDA instrument. Firstly, the PARAFAC algorithm was applied for the decomposition of three-way UPLC-PDA data into the chromatographic, spectral and concentration profiles to quantify the concerned compounds. Secondly, 3W-PLS1 approach was subjected to the decomposition of a tensor consisting of three-way UPLC-PDA data into a set of triads to build 3W-PLS1 regression for the analysis of the same compounds in samples. For the proposed three-way analysis methods in the regression and prediction steps, the applicability and validity of PARAFAC and 3W-PLS1 models were checked by analyzing the synthetic mixture samples, inter-day and intra-day samples, and standard addition samples containing HCT and OLM. Two different three-way analysis methods, PARAFAC and 3W-PLS1, were successfully applied to the quantitative estimation of the solid dosage form containing HCT and OLM. Regression and prediction results provided from three-way analysis were compared with those obtained by traditional UPLC method. Copyright © 2015 Elsevier B.V. All rights reserved.

Individual and community risk factors and sexually transmitted diseases among arrested youths: a two level analysis.

PubMed

Dembo, Richard; Belenko, Steven; Childs, Kristina; Wareham, Jennifer; Schmeidler, James

2009-08-01

High rates of infection for chlamydia and gonorrhea have been noted among youths involved in the juvenile justice system. Although both individual and community-level factors have been found to be associated with sexually transmitted disease (STD) risk, their relative importance has not been tested in this population. A two-level logistic regression analysis was completed to assess the influence of individual-level and community-level predictors on STD test results among arrested youths processed at a centralized intake facility. Results from weighted two level logistic regression analyses (n = 1,368) indicated individual-level factors of gender (being female), age, race (being African American), and criminal history predicted the youths' positive STD status. For the community-level predictors, concentrated disadvantage significantly and positively predicted the youths' STD status. Implications of these findings for future research and public health policy are discussed.

Hypomagnesemia predicts postoperative biochemical hypocalcemia after thyroidectomy.

PubMed

Luo, Han; Yang, Hongliu; Zhao, Wanjun; Wei, Tao; Su, Anping; Wang, Bin; Zhu, Jingqiang

2017-05-25

To investigate the role of magnesium in biochemical and symptomatic hypocalcemia, a retrospective study was conducted. Less-than-total thyroidectomy patients were excluded from the final analysis. Identified the risk factors of biochemical and symptomatic hypocalcemia, and investigated the correlation by logistic regression and correlation test respectively. A total of 304 patients were included in the final analysis. General incidence of hypomagnesemia was 23.36%. Logistic regression showed that gender (female) (OR = 2.238, p = 0.015) and postoperative hypomagnesemia (OR = 2.010, p = 0.017) were independent risk factors for biochemical hypocalcemia. Both Pearson and partial correlation tests indicated there was indeed significant relation between calcium and magnesium. However, relative decreasing of iPTH (>70%) (6.691, p < 0.001) and hypocalcemia (2.222, p = 0.046) were identified as risk factors of symptomatic hypocalcemia. The difference remained significant even in normoparathyroidism patients. Postoperative hypomagnesemia was independent risk factor of biochemical hypocalcemia. Relative decline of iPTH was predominating in predicting symptomatic hypocalcemia.

[Risk factors for asthma in children in Hefei, China].

PubMed

Xiong, Mei; Ni, Chen; Pan, Jia-Hua; Wang, Qiang; Zheng, Li-Lin

2013-05-01

To investigate the risk factors for asthma in children in Hefei, China and to provide a strategy for asthma control in this region. A total of 400 children with a confirmed diagnosis of asthma, as well as 400 children of comparable age, sex, living environment, and family background, who had no respiratory diseases, were selected for a case-control study. A survey questionnaire survey was completed for all children. The obtained data were subjected to univariate and multivariate logistic regression analysis to determine the risk factors for asthma. The logistic regression analysis showed that a family history of allergy, allergic rhinitis, infantile eczema, no breastfeeding, air-conditioning and passive smoking were the risk factors for asthma in children, with odds ratios of 9.63, 7.56, 4.58, 2.16, 1.73, and 1.55 respectively. In order to reduce the incidence of asthma, we should advocate breast feeding, promote outdoor activities, keep ventilation natural, prevent passive smoking and cure allergic rhinitis.

Risk Factors for Developing Scoliosis in Cerebral Palsy: A Cross-Sectional Descriptive Study.

PubMed

Bertoncelli, Carlo M; Solla, Federico; Loughenbury, Peter R; Tsirikos, Athanasios I; Bertoncelli, Domenico; Rampal, Virginie

2017-06-01

This study aims to identify the risk factors leading to the development of severe scoliosis among children with cerebral palsy. A cross-sectional descriptive study of 70 children (aged 12-18 years) with severe spastic and/or dystonic cerebral palsy treated in a single specialist unit is described. Statistical analysis included Fisher exact test and logistic regression analysis to identify risk factors. Severe scoliosis is more likely to occur in patients with intractable epilepsy ( P = .008), poor gross motor functional assessment scores ( P = .018), limb spasticity ( P = .045), a history of previous hip surgery ( P = .048), and nonambulatory patients ( P = .013). Logistic regression model confirms the major risk factors are previous hip surgery ( P = .001), moderate to severe epilepsy ( P = .007), and female gender ( P = .03). History of previous hip surgery, intractable epilepsy, and female gender are predictors of developing severe scoliosis in children with cerebral palsy. This knowledge should aid in the early diagnosis of scoliosis and timely referral to specialist services.

Composite marginal quantile regression analysis for longitudinal adolescent body mass index data.

PubMed

Yang, Chi-Chuan; Chen, Yi-Hau; Chang, Hsing-Yi

2017-09-20

Childhood and adolescenthood overweight or obesity, which may be quantified through the body mass index (BMI), is strongly associated with adult obesity and other health problems. Motivated by the child and adolescent behaviors in long-term evolution (CABLE) study, we are interested in individual, family, and school factors associated with marginal quantiles of longitudinal adolescent BMI values. We propose a new method for composite marginal quantile regression analysis for longitudinal outcome data, which performs marginal quantile regressions at multiple quantile levels simultaneously. The proposed method extends the quantile regression coefficient modeling method introduced by Frumento and Bottai (Biometrics 2016; 72:74-84) to longitudinal data accounting suitably for the correlation structure in longitudinal observations. A goodness-of-fit test for the proposed modeling is also developed. Simulation results show that the proposed method can be much more efficient than the analysis without taking correlation into account and the analysis performing separate quantile regressions at different quantile levels. The application to the longitudinal adolescent BMI data from the CABLE study demonstrates the practical utility of our proposal. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Cervical Vertebral Body's Volume as a New Parameter for Predicting the Skeletal Maturation Stages.

PubMed

Choi, Youn-Kyung; Kim, Jinmi; Yamaguchi, Tetsutaro; Maki, Koutaro; Ko, Ching-Chang; Kim, Yong-Il

2016-01-01

This study aimed to determine the correlation between the volumetric parameters derived from the images of the second, third, and fourth cervical vertebrae by using cone beam computed tomography with skeletal maturation stages and to propose a new formula for predicting skeletal maturation by using regression analysis. We obtained the estimation of skeletal maturation levels from hand-wrist radiographs and volume parameters derived from the second, third, and fourth cervical vertebrae bodies from 102 Japanese patients (54 women and 48 men, 5-18 years of age). We performed Pearson's correlation coefficient analysis and simple regression analysis. All volume parameters derived from the second, third, and fourth cervical vertebrae exhibited statistically significant correlations (P < 0.05). The simple regression model with the greatest R-square indicated the fourth-cervical-vertebra volume as an independent variable with a variance inflation factor less than ten. The explanation power was 81.76%. Volumetric parameters of cervical vertebrae using cone beam computed tomography are useful in regression models. The derived regression model has the potential for clinical application as it enables a simple and quantitative analysis to evaluate skeletal maturation level.

Cervical Vertebral Body's Volume as a New Parameter for Predicting the Skeletal Maturation Stages

PubMed Central

Choi, Youn-Kyung; Kim, Jinmi; Maki, Koutaro; Ko, Ching-Chang

2016-01-01

This study aimed to determine the correlation between the volumetric parameters derived from the images of the second, third, and fourth cervical vertebrae by using cone beam computed tomography with skeletal maturation stages and to propose a new formula for predicting skeletal maturation by using regression analysis. We obtained the estimation of skeletal maturation levels from hand-wrist radiographs and volume parameters derived from the second, third, and fourth cervical vertebrae bodies from 102 Japanese patients (54 women and 48 men, 5–18 years of age). We performed Pearson's correlation coefficient analysis and simple regression analysis. All volume parameters derived from the second, third, and fourth cervical vertebrae exhibited statistically significant correlations (P < 0.05). The simple regression model with the greatest R-square indicated the fourth-cervical-vertebra volume as an independent variable with a variance inflation factor less than ten. The explanation power was 81.76%. Volumetric parameters of cervical vertebrae using cone beam computed tomography are useful in regression models. The derived regression model has the potential for clinical application as it enables a simple and quantitative analysis to evaluate skeletal maturation level. PMID:27340668

Risk factors for highly pathogenic avian influenza in commercial layer chicken farms in bangladesh during 2011.

PubMed

Osmani, M G; Thornton, R N; Dhand, N K; Hoque, M A; Milon, Sk M A; Kalam, M A; Hossain, M; Yamage, M

2014-12-01

A case-control study conducted during 2011 involved 90 randomly selected commercial layer farms infected with highly pathogenic avian influenza type A subtype H5N1 (HPAI) and 175 control farms randomly selected from within 5 km of infected farms. A questionnaire was designed to obtain information about potential risk factors for contracting HPAI and was administered to farm owners or managers. Logistic regression analyses were conducted to identify significant risk factors. A total of 20 of 43 risk factors for contracting HPAI were identified after univariable logistic regression analysis. A multivariable logistic regression model was derived by forward stepwise selection. Both unmatched and matched analyses were performed. The key risk factors identified were numbers of staff, frequency of veterinary visits, presence of village chickens roaming on the farm and staff trading birds. Aggregating these findings with those from other studies resulted in a list of 16 key risk factors identified in Bangladesh. Most of these related to biosecurity. It is considered feasible for Bangladesh to achieve a very low incidence of HPAI. Using the cumulative list of risk factors to enhance biosecurity pertaining to commercial farms would facilitate this objective. © 2013 Blackwell Verlag GmbH.

Above-ground biomass of mangrove species. I. Analysis of models

NASA Astrophysics Data System (ADS)

Soares, Mário Luiz Gomes; Schaeffer-Novelli, Yara

2005-10-01

This study analyzes the above-ground biomass of Rhizophora mangle and Laguncularia racemosa located in the mangroves of Bertioga (SP) and Guaratiba (RJ), Southeast Brazil. Its purpose is to determine the best regression model to estimate the total above-ground biomass and compartment (leaves, reproductive parts, twigs, branches, trunk and prop roots) biomass, indirectly. To do this, we used structural measurements such as height, diameter at breast-height (DBH), and crown area. A combination of regression types with several compositions of independent variables generated 2.272 models that were later tested. Subsequent analysis of the models indicated that the biomass of reproductive parts, branches, and prop roots yielded great variability, probably because of environmental factors and seasonality (in the case of reproductive parts). It also indicated the superiority of multiple regression to estimate above-ground biomass as it allows researchers to consider several aspects that affect above-ground biomass, specially the influence of environmental factors. This fact has been attested to the models that estimated the biomass of crown compartments.

The Social Action Perspective: Attachments to Work and Productivity in the Research Function.

ERIC Educational Resources Information Center

Rebne, Douglas

1989-01-01

Examines faculty motivation and quantitative performance in research. Factor analysis discloses three bases of employment motivation: moral, calculative, and alienative. Regression analysis indicates that moral and alienative attachments contribute to explaining research productivity. (Author/TE)

The impact of young drivers' lifestyle on their road traffic accident risk in greater Athens area.

PubMed

Chliaoutakis, J E; Darviri, C; Demakakos, P T

1999-11-01

Young drivers (18-24) both in Greece and elsewhere appear to have high rates of road traffic accidents. Many factors contribute to the creation of these high road traffic accidents rates. It has been suggested that lifestyle is an important one. The main objective of this study is to find out and clarify the (potential) relationship between young drivers' lifestyle and the road traffic accident risk they face. Moreover, to examine if all the youngsters have the same elevated risk on the road or not. The sample consisted of 241 young Greek drivers of both sexes. The statistical analysis included factor analysis and logistic regression analysis. Through the principal component analysis a ten factor scale was created which included the basic lifestyle traits of young Greek drivers. The logistic regression analysis showed that the young drivers whose dominant lifestyle trait is alcohol consumption or drive without destination have high accident risk, while these whose dominant lifestyle trait is culture, face low accident risk. Furthermore, young drivers who are religious in one way or another seem to have low accident risk. Finally, some preliminary observations on how health promotion should be put into practice are discussed.

Healthcare Expenditures Associated with Depression Among Individuals with Osteoarthritis: Post-Regression Linear Decomposition Approach.

PubMed

Agarwal, Parul; Sambamoorthi, Usha

2015-12-01

Depression is common among individuals with osteoarthritis and leads to increased healthcare burden. The objective of this study was to examine excess total healthcare expenditures associated with depression among individuals with osteoarthritis in the US. Adults with self-reported osteoarthritis (n = 1881) were identified using data from the 2010 Medical Expenditure Panel Survey (MEPS). Among those with osteoarthritis, chi-square tests and ordinary least square regressions (OLS) were used to examine differences in healthcare expenditures between those with and without depression. Post-regression linear decomposition technique was used to estimate the relative contribution of different constructs of the Anderson's behavioral model, i.e., predisposing, enabling, need, personal healthcare practices, and external environment factors, to the excess expenditures associated with depression among individuals with osteoarthritis. All analysis accounted for the complex survey design of MEPS. Depression coexisted among 20.6 % of adults with osteoarthritis. The average total healthcare expenditures were $13,684 among adults with depression compared to $9284 among those without depression. Multivariable OLS regression revealed that adults with depression had 38.8 % higher healthcare expenditures (p < 0.001) compared to those without depression. Post-regression linear decomposition analysis indicated that 50 % of differences in expenditures among adults with and without depression can be explained by differences in need factors. Among individuals with coexisting osteoarthritis and depression, excess healthcare expenditures associated with depression were mainly due to comorbid anxiety, chronic conditions and poor health status. These expenditures may potentially be reduced by providing timely intervention for need factors or by providing care under a collaborative care model.

Classification of Effective Soil Depth by Using Multinomial Logistic Regression Analysis

NASA Astrophysics Data System (ADS)

Chang, C. H.; Chan, H. C.; Chen, B. A.

2016-12-01

Classification of effective soil depth is a task of determining the slopeland utilizable limitation in Taiwan. The "Slopeland Conservation and Utilization Act" categorizes the slopeland into agriculture and husbandry land, land suitable for forestry and land for enhanced conservation according to the factors including average slope, effective soil depth, soil erosion and parental rock. However, sit investigation of the effective soil depth requires a cost-effective field work. This research aimed to classify the effective soil depth by using multinomial logistic regression with the environmental factors. The Wen-Shui Watershed located at the central Taiwan was selected as the study areas. The analysis of multinomial logistic regression is performed by the assistance of a Geographic Information Systems (GIS). The effective soil depth was categorized into four levels including deeper, deep, shallow and shallower. The environmental factors of slope, aspect, digital elevation model (DEM), curvature and normalized difference vegetation index (NDVI) were selected for classifying the soil depth. An Error Matrix was then used to assess the model accuracy. The results showed an overall accuracy of 75%. At the end, a map of effective soil depth was produced to help planners and decision makers in determining the slopeland utilizable limitation in the study areas.

The Impact of Letter Grades on Student Effort, Course Selection, and Major Choice: A Regression-Discontinuity Analysis

ERIC Educational Resources Information Center

Main, Joyce B.; Ost, Ben

2014-01-01

The authors apply a regression-discontinuity design to identify the causal impact of letter grades on student effort within a course, subsequent credit hours taken, and the probability of majoring in economics. Their methodology addresses key issues in identifying the causal impact of letter grades: correlation with unobservable factors, such as…

Spirometry results (FEV1 and FVC) in young Bantu men from Tanzania vs environmental and family characteristics.

PubMed

Rębacz-Maron, Ewa; Parafiniuk, Mirosław

2014-01-01

The aim of this paper was to examine the extent to which socioeconomic factors, anthropological data and somatic indices influenced the results of spirometric measurements (FEV1 and FVC) in Tanzanian youth. The population studied were young black Bantu men aged 12.8-24.0 years. Analysis was performed for the whole data set (n = 255), as well as separately for two age groups: under 17.5 years (n = 168) and 17.5 + (n = 87). A backward stepwise multiple regression analysis was performed for FEV1 and FVC as dependent variables on socioeconomic and anthropometric data. Multiple regression analysis for the whole group revealed that the socioeconomic and anthropometric data under analysis accounted for 38% of the variation in FEV1. In addition the analysis demonstrated that 34% of the variation in FVC could be accounted for by the variables used in the regression. A significant impact in explaining the variability of FVC was exhibited by the thorax mobility, financial situation of the participants and Pignet-Verwaecka Index. Analysis of the data indicates the significant role of selected socio-economic factors on the development of the biological specimens investigated. There were no perceptible pathologies, and the results can be treated as a credible interpretation of the influence exerted by the environment in which the teenagers under study grew up.

Categorized or Continuous? Strength of an Association--And Linear Regression

ERIC Educational Resources Information Center

Drummond, Gordon B.; Vowler, Sarah L.

2012-01-01

In this article, the authors consider the possibility that groups could be different, because of the different conditions of a factor. This is as far as the analysis can extend: the consideration is restricted to groups characterized by the different category of the factor being considered. In many biological experiments, the factor considered may…

A study of home deaths in Japan from 1951 to 2002

PubMed Central

Yang, Limin; Sakamoto, Naoko; Marui, Eiji

2006-01-01

Background Several surveys in Japan have indicated that most terminally ill Japanese patients would prefer to die at home or in a homelike setting. However, there is a great disparity between this stated preference and the reality, since most Japanese die in hospital. We report here national changes in home deaths in Japan over the last 5 decades. Using prefecture data, we also examined the factors in the medical service associated with home death in Japan. Methods Published data on place of death was obtained from the vital statistics compiled by the Ministry of Health, Labor and Welfare of Japan. We analyzed trends of home deaths from 1951 to 2002, and describe the changes in the proportion of home deaths by region, sex, age, and cause of death. Joinpoint regression analysis was used for trend analysis. Logistic regression analysis was performed to identify secular trends in home deaths, and the impact of age, sex, year of deaths and cause of deaths on home death. We also examined the association between home death and medical service factors by multiple regression analysis, using home death rate by prefectures in 2002 as a dependent variable. Results A significant decrease in the percentage of patients dying at home was observed in the results of joinpoint regression analysis. Older patients and males were more likely to die at home. Patients who died from cancer were less likely to die at home. The results of multiple regression analysis indicated that home death was related to the number of beds in hospital, ratio of daily occupied beds in general hospital, the number of families in which the elderly were living alone, and dwelling rooms. Conclusion The pattern of the place of death has not only been determined by social and demographic characteristics of the decedent, but also associated with the medical service in the community. PMID:16524485

The impact of intrinsic and extrinsic factors on the job satisfaction of dentists.

PubMed

Goetz, K; Campbell, S M; Broge, B; Dörfer, C E; Brodowski, M; Szecsenyi, J

2012-10-01

The Two-Factor Theory of job satisfaction distinguishes between intrinsic-motivation (i.e. recognition, responsibility) and extrinsic-hygiene (i.e. job security, salary, working conditions) factors. The presence of intrinsic-motivation facilitates higher satisfaction and performance, whereas the absences of extrinsic factors help mitigate against dissatisfaction. The consideration of these factors and their impact on dentists' job satisfaction is essential for the recruitment and retention of dentists. The objective of the study is to assess the level of job satisfaction of German dentists and the factors that are associated with it. This cross-sectional study was based on a job satisfaction survey. Data were collected from 147 dentists working in 106 dental practices. Job satisfaction was measured with the 10-item Warr-Cook-Wall job satisfaction scale. Organizational characteristics were measured with two items. Linear regression analyses were performed in which each of the nine items of the job satisfaction scale (excluding overall satisfaction) were handled as dependent variables. A stepwise linear regression analysis was performed with overall job satisfaction as the dependent outcome variable, the nine items of job satisfaction and the two items of organizational characteristics controlled for age and gender as predictors. The response rate was 95.0%. Dentists were satisfied with 'freedom of working method' and mostly dissatisfied with their 'income'. Both variables are extrinsic factors. The regression analyses identified five items that were significantly associated with each item of the job satisfaction scale: 'age', 'mean weekly working time', 'period in the practice', 'number of dentist's assistant' and 'working atmosphere'. Within the stepwise linear regression analysis the intrinsic factor 'opportunity to use abilities' (β = 0.687) showed the highest score of explained variance (R(2) = 0.468) regarding overall job satisfaction. With respect to the Two-Factor Theory of job satisfaction both components, intrinsic and extrinsic, are essential for dentists but the presence of intrinsic motivating factors like the opportunity to use abilities has most positive impact on job satisfaction. The findings of this study will be helpful for further activities to improve the working conditions of dentists and to ensure quality of care. © 2012 John Wiley & Sons A/S.

Systematic analysis of factors associated with progression and regression of ulcerative colitis in 918 patients.

PubMed

Safroneeva, E; Vavricka, S; Fournier, N; Seibold, F; Mottet, C; Nydegger, A; Ezri, J; Straumann, A; Rogler, G; Schoepfer, A M

2015-09-01

Studies that systematically assess change in ulcerative colitis (UC) extent over time in adult patients are scarce. To assess changes in disease extent over time and to evaluate clinical parameters associated with this change. Data from the Swiss IBD cohort study were analysed. We used logistic regression modelling to identify factors associated with a change in disease extent. A total of 918 UC patients (45.3% females) were included. At diagnosis, UC patients presented with the following disease extent: proctitis [199 patients (21.7%)], left-sided colitis [338 patients (36.8%)] and extensive colitis/pancolitis [381 (41.5%)]. During a median disease duration of 9 [4-16] years, progression and regression was documented in 145 patients (15.8%) and 149 patients (16.2%) respectively. In addition, 624 patients (68.0%) had a stable disease extent. The following factors were identified to be associated with disease progression: treatment with systemic glucocorticoids [odds ratio (OR) 1.704, P = 0.025] and calcineurin inhibitors (OR: 2.716, P = 0.005). No specific factors were found to be associated with disease regression. Over a median disease duration of 9 [4-16] years, about two-thirds of UC patients maintained the initial disease extent; the remaining one-third had experienced either progression or regression of the disease extent. © 2015 John Wiley & Sons Ltd.

Finding the Perfect Match: Factors That Influence Family Medicine Residency Selection.

PubMed

Wright, Katherine M; Ryan, Elizabeth R; Gatta, John L; Anderson, Lauren; Clements, Deborah S

2016-04-01

Residency program selection is a significant experience for emerging physicians, yet there is limited information about how applicants narrow their list of potential programs. This study examines factors that influence residency program selection among medical students interested in family medicine at the time of application. Medical students with an expressed interest in family medicine were invited to participate in a 37-item, online survey. Students were asked to rate factors that may impact residency selection on a 6-point Likert scale in addition to three open-ended qualitative questions. Mean values were calculated for each survey item and were used to determine a rank order for selection criteria. Logistic regression analysis was performed to identify factors that predict a strong interest in urban, suburban, and rural residency programs. Logistic regression was also used to identify factors that predict a strong interest in academic health center-based residencies, community-based residencies, and community-based residencies with an academic affiliation. A total of 705 medical students from 32 states across the country completed the survey. Location, work/life balance, and program structure (curriculum, schedule) were rated the most important factors for residency selection. Logistic regression analysis was used to refine our understanding of how each factor relates to specific types of residencies. These findings have implications for how to best advise students in selecting a residency, as well as marketing residencies to the right candidates. Refining the recruitment process will ensure a better fit between applicants and potential programs. Limited recruitment resources may be better utilized by focusing on targeted dissemination strategies.

A multilateral modelling of Youth Soccer Performance Index (YSPI)

NASA Astrophysics Data System (ADS)

Bisyri Husin Musawi Maliki, Ahmad; Razali Abdullah, Mohamad; Juahir, Hafizan; Abdullah, Farhana; Ain Shahirah Abdullah, Nurul; Muazu Musa, Rabiu; Musliha Mat-Rasid, Siti; Adnan, Aleesha; Azura Kosni, Norlaila; Muhamad, Wan Siti Amalina Wan; Afiqah Mohamad Nasir, Nur

2018-04-01

This study aims to identify the most dominant factors that influencing performance of soccer player and to predict group performance for soccer players. A total of 184 of youth soccer players from Malaysia sport school and six soccer academy encompasses as respondence of the study. Exploratory factor analysis (EFA) and Confirmatory factor analysis (CFA) were computed to identify the most dominant factors whereas reducing the initial 26 parameters with recommended >0.5 of factor loading. Meanwhile, prediction of the soccer performance was predicted by regression model. CFA revealed that sit and reach, vertical jump, VO2max, age, weight, height, sitting height, calf circumference (cc), medial upper arm circumference (muac), maturation, bicep, triceps, subscapular, suprailiac, 5M, 10M, and 20M speed were the most dominant factors. Further index analysis forming Youth Soccer Performance Index (YSPI) resulting by categorizing three groups namely, high, moderate, and low. The regression model for this study was significant set as p < 0.001 and R2 is 0.8222 which explained that the model contributed a total of 82% prediction ability to predict the whole set of the variables. The significant parameters in contributing prediction of YSPI are discussed. As a conclusion, the precision of the prediction models by integrating a multilateral factor reflecting for predicting potential soccer player and hopefully can create a competitive soccer games.

Application of geographically-weighted regression analysis to assess risk factors for malaria hotspots in Keur Soce health and demographic surveillance site.

PubMed

Ndiath, Mansour M; Cisse, Badara; Ndiaye, Jean Louis; Gomis, Jules F; Bathiery, Ousmane; Dia, Anta Tal; Gaye, Oumar; Faye, Babacar

2015-11-18

In Senegal, considerable efforts have been made to reduce malaria morbidity and mortality during the last decade. This resulted in a marked decrease of malaria cases. With the decline of malaria cases, transmission has become sparse in most Senegalese health districts. This study investigated malaria hotspots in Keur Soce sites by using geographically-weighted regression. Because of the occurrence of hotspots, spatial modelling of malaria cases could have a considerable effect in disease surveillance. This study explored and analysed the spatial relationships between malaria occurrence and socio-economic and environmental factors in small communities in Keur Soce, Senegal, using 6 months passive surveillance. Geographically-weighted regression was used to explore the spatial variability of relationships between malaria incidence or persistence and the selected socio-economic, and human predictors. A model comparison of between ordinary least square and geographically-weighted regression was also explored. Vector dataset (spatial) of the study area by village levels and statistical data (non-spatial) on malaria confirmed cases, socio-economic status (bed net use), population data (size of the household) and environmental factors (temperature, rain fall) were used in this exploratory analysis. ArcMap 10.2 and Stata 11 were used to perform malaria hotspots analysis. From Jun to December, a total of 408 confirmed malaria cases were notified. The explanatory variables-household size, housing materials, sleeping rooms, sheep and distance to breeding site returned significant t values of -0.25, 2.3, 4.39, 1.25 and 2.36, respectively. The OLS global model revealed that it explained about 70 % (adjusted R(2) = 0.70) of the variation in malaria occurrence with AIC = 756.23. The geographically-weighted regression of malaria hotspots resulted in coefficient intercept ranging from 1.89 to 6.22 with a median of 3.5. Large positive values are distributed mainly in the southeast of the district where hotspots are more accurate while low values are mainly found in the centre and in the north. Geographically-weighted regression and OLS showed important risks factors of malaria hotspots in Keur Soce. The outputs of such models can be a useful tool to understand occurrence of malaria hotspots in Senegal. An understanding of geographical variation and determination of the core areas of the disease may provide an explanation regarding possible proximal and distal contributors to malaria elimination in Senegal.

An association between dietary habits and traffic accidents in patients with chronic liver disease: A data-mining analysis

PubMed Central

KAWAGUCHI, TAKUMI; SUETSUGU, TAKURO; OGATA, SHYOU; IMANAGA, MINAMI; ISHII, KUMIKO; ESAKI, NAO; SUGIMOTO, MASAKO; OTSUYAMA, JYURI; NAGAMATSU, AYU; TANIGUCHI, EITARO; ITOU, MINORU; ORIISHI, TETSUHARU; IWASAKI, SHOKO; MIURA, HIROKO; TORIMURA, TAKUJI

2016-01-01

The incidence of traffic accidents in patients with chronic liver disease (CLD) is high in the USA. However, the characteristics of patients, including dietary habits, differ between Japan and the USA. The present study investigated the incidence of traffic accidents in CLD patients and the clinical profiles associated with traffic accidents in Japan using a data-mining analysis. A cross-sectional study was performed and 256 subjects [148 CLD patients (CLD group) and 106 patients with other digestive diseases (disease control group)] were enrolled; 2 patients were excluded. The incidence of traffic accidents was compared between the two groups. Independent factors for traffic accidents were analyzed using logistic regression and decision-tree analyses. The incidence of traffic accidents did not differ between the CLD and disease control groups (8.8 vs. 11.3%). The results of the logistic regression analysis showed that yoghurt consumption was the only independent risk factor for traffic accidents (odds ratio, 0.37; 95% confidence interval, 0.16–0.85; P=0.0197). Similarly, the results of the decision-tree analysis showed that yoghurt consumption was the initial divergence variable. In patients who consumed yoghurt habitually, the incidence of traffic accidents was 6.6%, while that in patients who did not consume yoghurt was 16.0%. CLD was not identified as an independent factor in the logistic regression and decision-tree analyses. In conclusion, the difference in the incidence of traffic accidents in Japan between the CLD and disease control groups was insignificant. Furthermore, yoghurt consumption was an independent negative risk factor for traffic accidents in patients with digestive diseases, including CLD. PMID:27123257

An association between dietary habits and traffic accidents in patients with chronic liver disease: A data-mining analysis.

PubMed

Kawaguchi, Takumi; Suetsugu, Takuro; Ogata, Shyou; Imanaga, Minami; Ishii, Kumiko; Esaki, Nao; Sugimoto, Masako; Otsuyama, Jyuri; Nagamatsu, Ayu; Taniguchi, Eitaro; Itou, Minoru; Oriishi, Tetsuharu; Iwasaki, Shoko; Miura, Hiroko; Torimura, Takuji

2016-05-01

The incidence of traffic accidents in patients with chronic liver disease (CLD) is high in the USA. However, the characteristics of patients, including dietary habits, differ between Japan and the USA. The present study investigated the incidence of traffic accidents in CLD patients and the clinical profiles associated with traffic accidents in Japan using a data-mining analysis. A cross-sectional study was performed and 256 subjects [148 CLD patients (CLD group) and 106 patients with other digestive diseases (disease control group)] were enrolled; 2 patients were excluded. The incidence of traffic accidents was compared between the two groups. Independent factors for traffic accidents were analyzed using logistic regression and decision-tree analyses. The incidence of traffic accidents did not differ between the CLD and disease control groups (8.8 vs. 11.3%). The results of the logistic regression analysis showed that yoghurt consumption was the only independent risk factor for traffic accidents (odds ratio, 0.37; 95% confidence interval, 0.16-0.85; P=0.0197). Similarly, the results of the decision-tree analysis showed that yoghurt consumption was the initial divergence variable. In patients who consumed yoghurt habitually, the incidence of traffic accidents was 6.6%, while that in patients who did not consume yoghurt was 16.0%. CLD was not identified as an independent factor in the logistic regression and decision-tree analyses. In conclusion, the difference in the incidence of traffic accidents in Japan between the CLD and disease control groups was insignificant. Furthermore, yoghurt consumption was an independent negative risk factor for traffic accidents in patients with digestive diseases, including CLD.

Hepatitis B virus mutation may play a role in hepatocellular carcinoma recurrence: A systematic review and meta-regression analysis.

PubMed

Zhou, Hua-ying; Luo, Yue; Chen, Wen-dong; Gong, Guo-zhong

2015-06-01

A number of studies have confirmed that antiviral therapy with nucleotide analogs (NAs) can improve the prognosis of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) after curative therapy. However, what factors affected the prognosis of HBV-HCC after removal of the primary tumor and inhibition of HBV replication? A meta-regression analysis was conducted to explore the prognostic factor for this subgroup of patients. MEDLINE, EMBASE, Web of Science, and Cochrane library were searched from January 1995 to February 2014 for clinical trials evaluating the effect of NAs on the prognosis of HBV-HCC after curative therapy. Data were extracted for host, viral, and intervention information. Single-arm meta-analysis was performed to assess overall survival (OS) rates and HCC recurrence. Meta-regression analysis was carried out to explore risk factors for 1-year OS rate and HCC recurrence for HBV-HCC patients after curative therapy and antiviral therapy. Fourteen observational studies with 1284 patients met the inclusion criteria. Influential factors for prognosis of HCC were mainly baseline HBeAg positivity, cirrhotic stage, advanced Tumor-Node-Metastasis (TNM) stage, macrovascular invasion, and antiviral agent type. The 1-year OS rate decreased by more than four times (coefficient -4.45, P<0.001) and the 1-year HCC recurrence increased by more than one time (coefficient 1.20, P=0.003) when lamivudine was chosen for HCC after curative therapy, relative to entecavir for HCC. HBV mutation may play a role in HCC recurrence. Entecavir or tenofovir, a high genetic barrier to resistance, should be recommended for HBV-HCC patients. © 2015 The Authors. Journal of Gastroenterology and Hepatology published by Journal of Gastroenterology and Hepatology Foundation and Wiley Publishing Asia Pty Ltd.

Association between metabolic syndrome and bone fracture risk: A community-based study using a fracture risk assessment tool.

PubMed

Yu, Chia-Ying; Chen, Fang-Ping; Chen, Li-Wei; Kuo, Sheng-Fong; Chien, Rong-Nan

2017-12-01

Osteoporosis and metabolic syndrome (MS) share similar risk factors. Previous studies of association between bone marrow density (BMD) and MS are controversial. Moreover, some studies revealed that MS is associated with BMD but not with bone fracture. In clinical practice, patients pay more attention to bone fracture risk than BMD values. Hence, this study aimed to evaluate the association between MS and the 10-year bone fracture risk probability using a fracture risk assessment tool (FRAX) from community-based data. From March 2014 to August 2015, 2689 participants (897 men and 1792 women) were enrolled in this study. Inflammatory cytokines, such as tumor necrosis factor alpha and C-reactive protein, and adipokines were included for analysis.The mean age was 60.2 ± 10.7 years in men and 58.9 ± 9.6 years in women. The percentage of MS was 27.6% in men and 27.9% in women. Participants were divided into 2 groups, those with or without MS. Compared with women without MS, women with MS had a higher rate of fracture risk (22.8% vs 16.3%, P = .001). In contrast, men with MS had a lower rate of fracture risk then men without MS (5.6% vs 12.3%, P = .004). However, MS loss the association with a high bone fracture risk in men based on multivariate logistical regression analysis, after adjusting for confounding factor of body mass index (BMI). Conclusively, the result of regression analysis between MS and the bone fracture risk may be different in men and women, and BMI was an important confounding factor to interfere with the regression analysis. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

Attitudes Toward Seeking Professional Psychological Help: Factor Structure and Socio-Demographic Predictors

PubMed Central

Picco, Louisa; Abdin, Edimanysah; Chong, Siow Ann; Pang, Shirlene; Shafie, Saleha; Chua, Boon Yiang; Vaingankar, Janhavi A.; Ong, Lue Ping; Tay, Jenny; Subramaniam, Mythily

2016-01-01

Attitudes toward seeking professional psychological help (ATSPPH) are complex. Help seeking preferences are influenced by various attitudinal and socio-demographic factors and can often result in unmet needs, treatment gaps, and delays in help-seeking. The aims of the current study were to explore the factor structure of the ATSPPH short form (-SF) scale and determine whether any significant socio-demographic differences exist in terms of help-seeking attitudes. Data were extracted from a population-based survey conducted among Singapore residents aged 18–65 years. Respondents provided socio-demographic information and were administered the ATSPPH-SF. Weighted mean and standard error of the mean were calculated for continuous variables, and frequencies and percentages for categorical variables. Confirmatory factor analysis and exploratory factor analysis were performed to establish the validity of the factor structure of the ATSPPH-SF scale. Multivariable linear regressions were conducted to examine predictors of each of the ATSPPH-SF factors. The factor analysis revealed that the ATSPPH-SF formed three distinct dimensions: “Openness to seeking professional help,” “Value in seeking professional help,” and “Preference to cope on one's own.” Multiple linear regression analyses showed that age, ethnicity, marital status, education, and income were significantly associated with the ATSPPH-SF factors. Population subgroups that were less open to or saw less value in seeking psychological help should be targeted via culturally appropriate education campaigns and tailored and supportive interventions. PMID:27199794

Lifestyle and Genetic Predictors of Stiffness Index in Community-dwelling Elderly Korean Men and Women.

PubMed

Park, Kyung-Ae; Park, Yeon-Hwan; Suh, Min-Hee; Choi-Kwon, Smi

2015-09-01

Differing lifestyle, nutritional, and genetic factors may lead to a differing stiffness index (SI) determined by quantitative ultrasound in elderly men and women. The purpose of this study was to determine SI and the gender-specific factors associated with low SI in a Korean elderly cohort. This was a cross-sectional descriptive study identifying the gender-specific factors related to SI in 252 men and women aged 65 years and greater from local senior centers in Seoul, Korea between January and February 2009. The mean SI of elderly men was significantly higher than that of the women's. A multiple regression analysis reveals that age, nutritional status, and physical activity were predictive factors of lower SI in men, whereas age, alcohol consumption, educational level, and genetic polymorphism were predictive factors for elderly women. Low SI was common in both elderly men and women. We found gender differences in factors linked to low SI. In multiple regression analysis, nutritional status and physical activity were more important factors in men, whereas alcohol consumption, educational level, and genetic polymorphism were significant factors predicting low SI in women. Gender-specific modifiable risk factors associated with low SI should be considered when developing osteoporosis prevention programs for the elderly. Copyright © 2015. Published by Elsevier B.V.

Bim may be a poor prognostic biomarker in breast cancer patients especially in those with luminal A tumors.

PubMed

Maimaiti, Yusufu; Dong, Lingling; Aili, Aikebaier; Maimaitiaili, Maimaitiaili; Huang, Tao; Abudureyimu, Kelimu

2017-07-04

Bcl-2 interacting mediator of cell death (Bim) appears to have contradictory roles in cancer. It is uncertain whether Bim show prognostic significance in patients with breast cancer. To investigate the correlation between Bim expression and clinicopathological characteristics of breast cancer and to evaluate Bim's effect on overall survival (OS). We used immunohistochemistry (IHC) technique to detect the expression of Bim via tissue microarray in 275 breast cancer samples, Kaplan-Meier analysis to perform survival analysis, and Cox proportional hazards regression model to explore the risk factors of breast cancer. The results revealed that Bim expression was significantly correlated with age, estrogen receptor (ER) and/or progesterone receptor (PR), human epidermal growth factor receptor (HER2) and Ki67 expression (P< 0.05). Bim expression was significantly different in the four molecular subtypes (P= 0.000). Survival analysis showed that Bim positive expression contributed to a shorter OS (P= 0.034), especially in patients with luminal A tumors (P= 0.039). Univariate and multivariate regression analysis showed that Bim was an independent prognostic factor for breast cancer (P< 0.05). Bim may serve as an effective predictive factor for lower OS in breast cancer patients, especially in those with luminal A tumors.

Adolescent religiosity and attitudes to HIV and AIDS in Ghana.

PubMed

Amoako-Agyeman, Kofi Nyame

2012-11-01

This study investigated the relationships between adolescent religiosity and attitudes to HIV/AIDS based on two major techniques of analysis, factor and regression analysis towards informing preventive school education strategies. Using cross-sectional data of 448 adolescents in junior high school, the study incorporated survey in a self-administered questionnaire and sought to identify underlying factors that affect pupils' responses, delineate the pattern of relationships between variables and select models which best explain and predict relationships among variables. A seven-factor solution described the 'attitude' construct including abstinence and protection, and six for 'religiosity'. The results showed relatively high levels of religiosity and a preference for private religiosity as opposed to organisational religiosity. The regression analysis produced significant relationships between factors of attitudes to HIV/AIDS and of religiosity. Adolescent with very high private religiosity are more likely to abstain from sex but less likely to use condoms once they initiate: protection is inversely related to religiosity. The findings suggest that religious-based adolescent interventions should focus on intrinsic religiosity. Additionally, increasing HIV prevention information and incorporating culturally relevant and socially acceptable values might lend support to improved adolescent school-based HIV/AIDS prevention programmes.

Risk factors affecting human traumatic tympanic membrane perforation regeneration therapy using fibroblast growth factor-2.

PubMed

Lou, Zhengcai; Yang, Jian; Tang, Yongmei; Xiao, Jian

2015-01-01

The use of growth factors to achieve closure of human traumatic tympanic membrane perforations (TMPs) has recently been demonstrated. However, pretreatment factors affecting healing outcomes have seldom been discussed. The objective of this study was to evaluate pretreatment factors contributing to the success or failure of healing of TMPs using fibroblast growth factor-2 (FGF-2). A retrospective cohort study of 99 patients (43 males, 56 females) with traumatic TMPs who were observed for at least 6 months after FGF-2 treatment between March 2011 and December 2012. Eleven factors considered likely to affect the outcome of perforation closure were evaluated statistically using univariate and multivariate logistic regression analysis. Each traumatic TMP was treated by direct application of FGF-2. Complete closure versus failure to close. In total, 99 patients were analyzed. The total closure rate was 92/99 (92.9%) at 6 months; the mean closure time was 10.59 ±  6.81 days. The closure rate did not significantly differ between perforations with or without inverted edges (100.0% vs. 91.4%, p = 0.087), among different size groups (p = 0.768), or among different periods of exposure to injury (p = 0.051). However, the closure rate was significantly different between the high- and low-dose FGF-2 groups (85.0% vs. 98.3%, p = 0.010) and between perforations where the umbo or malleus was or was not involved in perforation (85.4% vs. 98.3%, p = 0.012). Additionally, univariate logistic regression analysis tests showed that it was difficult to achieve healing of these perforations with a history of chronic otitis media or residual TM calcification (p = 0.006), the umbo or malleus was involved in perforation (p = 0.038), and with a high dose of FGF-2 (p = 0.035) compared with control groups. Multivariate logistic regression analysis showed that only a history of chronic otitis media and residual TM calcification and perforation close to the umbo or malleus were associated with non-healing of the TM perforation (p = 0.03 and p = 0.017, respectively) with relative risk factors. Direct application of FGF-2 can be used in all traumatic TMPs, the size of the perforation and inverted edges did not affect the closure rate, and the most beneficial dose was sufficient to keep the residual eardrum environment moist, but without adding liquid. Additionally, multivariate logistic regression analysis revealed that a large perforation was not a major risk factor for nonhealing of TM perforations. However, a history of chronic otitis media, residual TM calcification and involvement of the umbo or malleus in perforation were significant risk factors.

A long-recommended but seldom-used method of analysis for fall injuries found a unique pattern of risk factors in the youngest-old.

PubMed

Legrand, Helen; Pihlsgård, Mats; Nordell, Eva; Elmståhl, Sölve

2015-08-01

Few studies on fall risk factors use long-recommended methods for analysis of recurrent events. Previous falls are the biggest risk factor for future falls, but few fall studies focus on the youngest-old. This study's objective was to apply Cox regression for recurrent events to identify factors associated with injurious falls in the youngest-old. Participants were community-dwelling residents of southern Sweden (n = 1,133), aged 59-67 at baseline (median 61.2), from the youngest cohorts of the larger Good Aging in Skåne (GÅS) study. Exposure variable data were collected from baseline study visits and medical records. Injurious falls, defined as emergency, inpatient, or specialist visits associated with ICD-10 fall codes during the follow-up period (2001-2011), were gathered from national and regional registries. Analysis was conducted using time to event Cox Regression for recurrent events. A majority (77.1 %) of injurious falls caused serious injuries such as fractures and open wounds. Exposure to nervous system medications [hazard ratio (HR) 1.40, 95 % confidence interval (CI) 1.03-1.89], central nervous system disease (HR 1.79, CI 1.18-2.70), and previous injurious fall(s) (HR 2.00, CI 1.50-2.68) were associated with increased hazard of injurious fall. Regression for recurrent events is feasible with typical falls' study data. The association of certain exposures with increased hazard of injurious falls begins earlier than previously studied. Different patterns of risk factors by age can provide insight into the progression of frailty. Tailored fall prevention screening and intervention may be of value in populations younger than those traditionally screened.

Predictors of unsuccessful outcome in cemented femoral revisions using bone impaction grafting; Cox regression analysis of 208 cases.

PubMed

Te Stroet, Martijn A J; Rijnen, Wim H C; Gardeniers, Jean W M; Schreurs, B Willem; Hannink, Gerjon

2016-09-29

Despite improvements in the technique of femoral impaction bone grafting, reconstruction failures still can occur. Therefore, the aim of our study was to determine risk factors for the endpoint re-revision for any reason. We used prospectively collected demographic, clinical and surgical data of all 202 patients who underwent 208 femoral revisions using the X-change Femoral Revision System (Stryker-Howmedica), fresh-frozen morcellised allograft and a cemented polished Exeter stem in our department from 1991 to 2007. Univariable and multivariable Cox regression analyses were performed to identify potential factors associated with re-revision. The mean follow-up was 10.6 (5-21) years. The cumulative re-revision rate was 6.3% (13/208). After univariable selection, sex, age, body mass index (BMI), American Association of Anesthesiologists (ASA) classification, type of removed femoral component, and mesh used for reconstruction were included in multivariable regression analysis.In the multivariable analysis, BMI was the only factor that was significantly associated with the risk of re-revision after bone impaction grafting (BMI ≥30 vs. BMI <30, HR = 6.54 [95% CI 1.89-22.65]; p = 0.003). BMI was the only factor associated with the risk of re-revision for any reason. Besides BMI also other factors, such as Endoklinik score and the type of removed femoral component, can provide guidance in the process of preclinical decision making. With the knowledge obtained from this study, preoperative patient selection, informed consent, and treatment protocols can be better adjusted to the individual patient who needs to undergo a femoral revision with impaction bone grafting.

Factors Influencing Willingness to Move: An Examination of Nonmetropolitan Residents.

ERIC Educational Resources Information Center

Swanson, Louis E., Jr.; And Others

1979-01-01

Examining relationships between social restraints and economic incentives on individuals' willingness to move, special attention was given to labor force participation relative to social factors. Regression Analysis found age and community tenure correlated negatively with willingness to move; people who were employed or not yet retired showed…

Factors Associated with Living in Developmental Centers in California

ERIC Educational Resources Information Center

Harrington, Charlene; Kang, Taewoon; Chang, Jamie

2009-01-01

This study examined need, predisposing, market, and regional factors that predicted the likelihood of individuals with developmental disabilities living in state developmental centers (DCs) compared with living at home, in community care, or in intermediate care (ICFs) and other facilities. Secondary data analysis using logistic regression models…

Factors Contributing to the Upward Transfer of Baccalaureate Aspirants Beginning at Community Colleges

ERIC Educational Resources Information Center

Wang, Xueli

2012-01-01

This study examined factors associated with the upward transfer of baccalaureate aspirants beginning at community colleges. Based on data from the National Education Longitudinal Study of 1988 and the Postsecondary Education Transcript Study, a sequential logistic regression analysis was conducted to predict bachelor's degree-seeking community…

Environmental factors affecting understory diversity in second-growth deciduous forests

Treesearch

Cynthia D. Huebner; J.C. Randolph; G.R. Parker

1995-01-01

The purpose of this study was to determine the most important nonanthropogenic factors affecting understory (herbs, shrubs and low-growing vines) diversity in forested landscapes of southern Indiana. Fourteen environmental variables were measured for 46 sites. Multiple regression analysis showed significant positive correlation between understory diversity and tree...

Factors Influencing New York Doctoral Graduate Student Satisfaction: A Quantitative Multiple Regression Analysis

ERIC Educational Resources Information Center

Nwenyi, Sabina E.

2013-01-01

Higher education administrators face challenges in providing a welcoming environment for doctoral students in higher education institutions. Administrators need to identify factors influencing satisfaction of this group of students to provide a supportive environment, reduce attrition rates, and promote persistence. The purpose of this…

Functions of Marijuana Use in College Students

ERIC Educational Resources Information Center

Bates, Julie K.; Accordino, Michael P.; Hewes, Robert L.

2010-01-01

Hierarchical regression analysis was used to test the hypothesis that specific functional factors of marijuana use would predict past 30-day marijuana use in 425 college students more precisely than demographic variables alone. This hypothesis was confirmed. Functional factors of personal/physical enhancement as well as activity enhancement were…

A systematic review of methodology: time series regression analysis for environmental factors and infectious diseases.

PubMed

Imai, Chisato; Hashizume, Masahiro

2015-03-01

Time series analysis is suitable for investigations of relatively direct and short-term effects of exposures on outcomes. In environmental epidemiology studies, this method has been one of the standard approaches to assess impacts of environmental factors on acute non-infectious diseases (e.g. cardiovascular deaths), with conventionally generalized linear or additive models (GLM and GAM). However, the same analysis practices are often observed with infectious diseases despite of the substantial differences from non-infectious diseases that may result in analytical challenges. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, systematic review was conducted to elucidate important issues in assessing the associations between environmental factors and infectious diseases using time series analysis with GLM and GAM. Published studies on the associations between weather factors and malaria, cholera, dengue, and influenza were targeted. Our review raised issues regarding the estimation of susceptible population and exposure lag times, the adequacy of seasonal adjustments, the presence of strong autocorrelations, and the lack of a smaller observation time unit of outcomes (i.e. daily data). These concerns may be attributable to features specific to infectious diseases, such as transmission among individuals and complicated causal mechanisms. The consequence of not taking adequate measures to address these issues is distortion of the appropriate risk quantifications of exposures factors. Future studies should pay careful attention to details and examine alternative models or methods that improve studies using time series regression analysis for environmental determinants of infectious diseases.

Contributions of sociodemographic factors to criminal behavior

PubMed Central

Mundia, Lawrence; Matzin, Rohani; Mahalle, Salwa; Hamid, Malai Hayati; Osman, Ratna Suriani

2016-01-01

We explored the extent to which prisoner sociodemographic variables (age, education, marital status, employment, and whether their parents were married or not) influenced offending in 64 randomly selected Brunei inmates, comprising both sexes. A quantitative field survey design ideal for the type of participants used in a prison context was employed to investigate the problem. Hierarchical multiple regression analysis with backward elimination identified prisoner marital status and age groups as significantly related to offending. Furthermore, hierarchical multinomial logistic regression analysis with backward elimination indicated that prisoners’ age, primary level education, marital status, employment status, and parental marital status as significantly related to stealing offenses with high odds ratios. All 29 nonrecidivists were false negatives and predicted to reoffend upon release. Similarly, all 33 recidivists were projected to reoffend after release. Hierarchical binary logistic regression analysis revealed age groups (24–29 years and 30–35 years), employed prisoner, and primary level education as variables with high likelihood trends for reoffending. The results suggested that prisoner interventions (educational, counseling, and psychotherapy) in Brunei should treat not only antisocial personality, psychopathy, and mental health problems but also sociodemographic factors. The study generated offending patterns, trends, and norms that may inform subsequent investigations on Brunei prisoners. PMID:27382342

Analysis and improvement measures of flight delay in China

NASA Astrophysics Data System (ADS)

Zang, Yuhang

2017-03-01

Firstly, this paper establishes the principal component regression model to analyze the data quantitatively, based on principal component analysis to get the three principal component factors of flight delays. Then the least square method is used to analyze the factors and obtained the regression equation expression by substitution, and then found that the main reason for flight delays is airlines, followed by weather and traffic. Aiming at the above problems, this paper improves the controllable aspects of traffic flow control. For reasons of traffic flow control, an adaptive genetic queuing model is established for the runway terminal area. This paper, establish optimization method that fifteen planes landed simultaneously on the three runway based on Beijing capital international airport, comparing the results with the existing FCFS algorithm, the superiority of the model is proved.

Adolescent Drug Use and Other Behaviors.

ERIC Educational Resources Information Center

Hundleby, John D.; And Others

1982-01-01

Two-hundred-thirty-one adolescents completed questionnaires concerning their use of drugs (alcohol, tobacco, pain-killers, and marijuana). Factor analysis of endorsements of a broad range of behavior, followed by regression analysis, indicated that sexual behavior, general delinquency, school achievement, and social behavior were all related to…

Determinants of Internet use as a preferred source of information on personal health.

PubMed

Lemire, Marc; Paré, Guy; Sicotte, Claude; Harvey, Charmian

2008-11-01

To understand the personal, social and cultural factors likely to explain recourse to the Internet as a preferred source of personal health information. A cross-sectional survey was conducted among a population of 2923 Internet users visiting a firmly established website that offers information on personal health. Multiple regression analysis was performed to identify the determinants of site use. The analysis template comprised four classes of determinants likely to explain Internet use: beliefs, intentions, user satisfaction and socio-demographic characteristics. Seven-point Likert scales were used. An analysis of the psychometric qualities of the variables provided compelling evidence of the construct's validity and reliability. A confirmatory factor analysis confirmed the correspondence with the factors predicted by the theoretical model. The regression analysis explained 35% of the variance in Internet use. Use was directly associated with five factors: perceived usefulness, importance given to written media in searches for health information, concern for personal health, importance given to the opinions of physicians and other health professionals, and the trust placed in the information available on the site itself. This study confirms the importance of the credibility of information on the frequency of Internet use as a preferred source of information on personal health. It also shows the potentially influential role of the Internet in the development of personal knowledge of health issues.

[Factors of psychiatric treatment satisfaction in inpatients with neurotic and depressive disorders].

PubMed

Tsygankov, B D; Malygin, Ya V; Gatin, F F

2015-01-01

Factors of patients' satisfaction with medical care vary depending on the level of care and medical specialty. Patient's satisfaction with psychiatric care is understudied. An aim of the present study is to find out the factors of satisfaction with psychiatric care in inpatients with neurotic and depressive disorders. The sample included 356 inpatients suffering from neurotic or depressive disorders. The patients were questioned using PAPI questionnaire designed for this study. Statistical analysis was performed using multiple regression. Key factors of satisfaction with medical care included quality of work of nurses and psychiatrists, hospital ward comfort, the number and quality of psychotherapeutic sessions, psychiatrists' empathy and aptitude to provide the patient with information about the disease and treatment. Multiple regression equation explained 81% of the variance of patients' satisfaction.

Independent risk factors of morbidity in penetrating colon injuries.

PubMed

Girgin, Sadullah; Gedik, Ercan; Uysal, Ersin; Taçyildiz, Ibrahim Halil

2009-05-01

The present study explored the factors effective on colon-related morbidity in patients with penetrating injury of the colon. The medical records of 196 patients were reviewed for variables including age, gender, factor of trauma, time between injury and operation, shock, duration of operation, Penetrating Abdominal Trauma Index (PATI), Injury Severity Score (ISS), site of colon injury, Colon Injury Score, fecal contamination, number of associated intra- and extraabdominal organ injuries, units of transfused blood within the first 24 hours, and type of surgery. In order to determine the independent risk factors, multivariate logistic regression analysis was performed. Gunshot wounds, interval between injury and operation > or =6 hours, shock, duration of the operation > or =6 hours, PATI > or =25, ISS > or =20, Colon Injury Score > or = grade 3, major fecal contamination, number of associated intraabdominal organ injuries >2, number of associated extraabdominal organ injuries >2, multiple blood transfusions, and diversion were significantly associated with morbidity. Multivariate logistic regression analysis showed diversion and transfusion of > or =4 units in the first 24 hours as independent risk factors affecting colon-related morbidity. Diversion and transfusion of > or =4 units in the first 24 hours were determined to be independent risk factors for colon-related morbidity.

Intraurban Differences in the Use of Ambulatory Health Services in a Large Brazilian City

PubMed Central

Lima-Costa, Maria Fernanda; Proietti, Fernando Augusto; Cesar, Cibele C.; Macinko, James

2010-01-01

A major goal of health systems is to reduce inequities in access to services, that is, to ensure that health care is provided based on health needs rather than social or economic factors. This study aims to identify the determinants of health services utilization among adults in a large Brazilian city and intraurban disparities in health care use. We combine household survey data with census-derived classification of social vulnerability of each household’s census tract. The dependent variable was utilization of physician services in the prior 12 months, and the independent variables included predisposing factors, health needs, enabling factors, and context. Prevalence ratios and 95% confidence intervals were estimated by the Hurdle regression model, which combined Poisson regression analysis of factors associated with any doctor visits (dichotomous variable) and zero-truncated negative binomial regression for the analysis of factors associated with the number of visits among those who had at least one. Results indicate that the use of health services was greater among women and increased with age, and was determined primarily by health needs and whether the individual had a regular doctor, even among those living in areas of the city with the worst socio-environmental indicators. The experience of Belo Horizonte may have implications for other world cities, particularly in the development and use of a comprehensive index to identify populations at risk and in order to guide expansion of primary health care services as a means of enhancing equity in health. PMID:21104332

Analysis of occlusal variables, dental attrition, and age for distinguishing healthy controls from female patients with intracapsular temporomandibular disorders.

PubMed

Seligman, D A; Pullinger, A G

2000-01-01

Confusion about the relationship of occlusion to temporomandibular disorders (TMD) persists. This study attempted to identify occlusal and attrition factors plus age that would characterize asymptomatic normal female subjects. A total of 124 female patients with intracapsular TMD were compared with 47 asymptomatic female controls for associations to 9 occlusal factors, 3 attrition severity measures, and age using classification tree, multiple stepwise logistic regression, and univariate analyses. Models were tested for accuracy (sensitivity and specificity) and total contribution to the variance. The classification tree model had 4 terminal nodes that used only anterior attrition and age. "Normals" were mainly characterized by low attrition levels, whereas patients had higher attrition and tended to be younger. The tree model was only moderately useful (sensitivity 63%, specificity 94%) in predicting normals. The logistic regression model incorporated unilateral posterior crossbite and mediotrusive attrition severity in addition to the 2 factors in the tree, but was slightly less accurate than the tree (sensitivity 51%, specificity 90%). When only occlusal factors were considered in the analysis, normals were additionally characterized by a lack of anterior open bite, smaller overjet, and smaller RCP-ICP slides. The log likelihood accounted for was similar for both the tree (pseudo R(2) = 29.38%; mean deviance = 0.95) and the multiple logistic regression (Cox Snell R(2) = 30.3%, mean deviance = 0.84) models. The occlusal and attrition factors studied were only moderately useful in differentiating normals from TMD patients.

Clinical insomnia and associated factors in failed back surgery syndrome: a retrospective cross-sectional study.

PubMed

Yun, Soon Young; Kim, Do Heon; Do, Hae Yoon; Kim, Shin Hyung

2017-01-01

Background Insomnia frequently occurs to patients with persistent back pain. By worsening pain, mood, and physical functioning, insomnia could lead to the negative clinical consequences of patients with failed back surgery syndrome (FBSS). This retrospective and cross-sectional study aims to identify the risk factors associated with clinical insomnia in FBSS patients. Methods A total of 194 patients with FBSS, who met the study inclusion criteria, were included in this analysis. The Insomnia Severity Index (ISI) was utilized to ascertain the presence of clinical insomnia (ISI score ≥ 15). Logistic regression analysis evaluates patient demographic factors, clinical factors including prior surgical factors, and psychological factors to identify the risk factors of clinical insomnia in FBSS patients. Results After the persistent pain following lumbar spine surgery worsened, 63.4% of patients reported a change from mild to severe insomnia. In addition, 26.2% of patients met the criteria for clinically significant insomnia. In a multivariate logistic regression analysis, high pain intensity (odds ratio (OR) =2.742, 95% confidence interval (CI): 1.022 - 7.353, P =0.045), high pain catastrophizing (OR=4.185, 95% CI: 1.697 - 10.324, P =0.002), greater level of depression (OR =3.330, 95% CI: 1.127 - 9.837, P =0.030) were significantly associated with clinical insomnia. However, patient demographic factors and clinical factors including prior surgical factors were not significantly associated with clinical insomnia. Conclusions Insomnia should be addressed as a critical part of pain management in FBSS patients with these risk factors, especially in patients with high pain catastrophizing.

Statistical model to perform error analysis of curve fits of wind tunnel test data using the techniques of analysis of variance and regression analysis

NASA Technical Reports Server (NTRS)

Alston, D. W.

1981-01-01

The considered research had the objective to design a statistical model that could perform an error analysis of curve fits of wind tunnel test data using analysis of variance and regression analysis techniques. Four related subproblems were defined, and by solving each of these a solution to the general research problem was obtained. The capabilities of the evolved true statistical model are considered. The least squares fit is used to determine the nature of the force, moment, and pressure data. The order of the curve fit is increased in order to delete the quadratic effect in the residuals. The analysis of variance is used to determine the magnitude and effect of the error factor associated with the experimental data.

Recurrent shoulder dystocia: is it predictable?

PubMed

Kleitman, Vered; Feldman, Roi; Walfisch, Asnat; Toledano, Ronen; Sheiner, Eyal

2016-11-01

To examine the course and outcome of deliveries occurring in women who previously experienced shoulder dystocia. In addition, recurrent shoulder dystocia risk factors were assessed. A retrospective cohort analysis comparing all singleton deliveries with and without shoulder dystocia in their preceding delivery was conducted. Independent predictors of recurrent shoulder dystocia were investigated using a multiple logistic regression model. Of the 201,422 deliveries included in the analysis, 307 occurred in women with a previous shoulder dystocia (0.015 %). Women with a history of shoulder dystocia were more likely to be older, experienced higher rates of gestational diabetes mellitus, polyhydramnios, prolonged second stage, operative delivery and macrosomia (>4000 g) in the following delivery. Previous shoulder dystocia was found to be an independent risk factor for recurrent shoulder dystocia (OR = 6.1, 95 % CI 3.2-11.8, p value <0.001) in the multivariable regression analysis. Shoulder dystocia is an independent risk factor for recurrent shoulder dystocia. Deliveries in women with a history of shoulder dystocia are characterized by higher rates of operative delivery, prolonged second stage of labor and macrosomia.

Evaluation of spectral domain optical coherence tomography parameters in ocular hypertension, preperimetric, and early glaucoma.

PubMed

Aydogan, Tuğba; Akçay, BetÜl İlkay Sezgin; Kardeş, Esra; Ergin, Ahmet

2017-11-01

The objective of this study is to evaluate the diagnostic ability of retinal nerve fiber layer (RNFL), macular, optic nerve head (ONH) parameters in healthy subjects, ocular hypertension (OHT), preperimetric glaucoma (PPG), and early glaucoma (EG) patients, to reveal factors affecting the diagnostic ability of spectral domain-optical coherence tomography (SD-OCT) parameters and risk factors for glaucoma. Three hundred and twenty-six eyes (89 healthy, 77 OHT, 94 PPG, and 66 EG eyes) were analyzed. RNFL, macular, and ONH parameters were measured with SD-OCT. The area under the receiver operating characteristic curve (AUC) and sensitivity at 95% specificity was calculated. Logistic regression analysis was used to determine the glaucoma risk factors. Receiver operating characteristic regression analysis was used to evaluate the influence of covariates on the diagnostic ability of parameters. In PPG patients, parameters that had the largest AUC value were average RNFL thickness (0.83) and rim volume (0.83). In EG patients, parameter that had the largest AUC value was average RNFL thickness (0.98). The logistic regression analysis showed average RNFL thickness was a risk factor for both PPG and EG. Diagnostic ability of average RNFL and average ganglion cell complex thickness increased as disease severity increased. Signal strength index did not affect diagnostic abilities. Diagnostic ability of average RNFL and rim area increased as disc area increased. When evaluating patients with glaucoma, patients at risk for glaucoma, and healthy controls RNFL parameters deserve more attention in clinical practice. Further studies are needed to fully understand the influence of covariates on the diagnostic ability of OCT parameters.

The Management Standards Indicator Tool and evaluation of burnout.

PubMed

Ravalier, J M; McVicar, A; Munn-Giddings, C

2013-03-01

Psychosocial hazards in the workplace can impact upon employee health. The UK Health and Safety Executive's (HSE) Management Standards Indicator Tool (MSIT) appears to have utility in relation to health impacts but we were unable to find studies relating it to burnout. To explore the utility of the MSIT in evaluating risk of burnout assessed by the Maslach Burnout Inventory-General Survey (MBI-GS). This was a cross-sectional survey of 128 borough council employees. MSIT data were analysed according to MSIT and MBI-GS threshold scores and by using multivariate linear regression with MBI-GS factors as dependent variables. MSIT factor scores were gradated according to categories of risk of burnout according to published MBI-GS thresholds, and identified priority workplace concerns as demands, relationships, role and change. These factors also featured as significant independent variables, with control, in outcomes of the regression analysis. Exhaustion was associated with demands and control (adjusted R (2) = 0.331); cynicism was associated with change, role and demands (adjusted R (2) =0.429); and professional efficacy was associated with managerial support, role, control and demands (adjusted R (2) = 0.413). MSIT analysis generally has congruence with MBI-GS assessment of burnout. The identification of control within regression models but not as a priority concern in the MSIT analysis could suggest an issue of the setting of the MSIT thresholds for this factor, but verification requires a much larger study. Incorporation of relationship, role and change into the MSIT, missing from other conventional tools, appeared to add to its validity.

Risk of suicide in male prison inmates.

PubMed

Saavedra, Javier; López, Marcelino

2015-01-01

Many studies have demonstrated that the risk of suicide in prison is higher than in the general population. This study has two aims. First, to explore the risk of suicide in men sentenced in Andalusian prisons. And second, to study the sociodemographic, criminal and, especially, psychopathological factors associated with this risk. An assessment was made of 472 sentenced inmates in two Andalusian prisons, and included a sociodemographic interview, the IPDE personality disorders questionnaire, the SCID-I diagnostic interview (DSMIV), and the Plutchick suicide risk questionnaire. The interviewers were experienced clinical psychologists with training in prison environments. Adjusted ORs were calculated using a logistic regression. A risk of committing suicide was detected in 33.5% of the sample. The diagnoses (lifetime prevalence) of affective disorder (adjusted OR 3329), substance dependence disorders (adjusted OR 2733), personality disorders (adjusted OR 3115) and anxiety disorder (adjusted OR 1650), as well as a family psychiatric history (adjusted OR 1650), were the predictors that remained as risk factors after the regression analysis. No socio-demographic risk factor was significant in the regression analysis. The psychopathological variables are essential and the most powerful factors to explain suicide risk in prisons. A correct and systematic diagnosis, and an appropriate treatment by mental health professionals during the imprisonment are essential to prevent the risk of suicide. Copyright © 2013 SEP y SEPB. Published by Elsevier España. All rights reserved.

Exploring visuospatial abilities and their contribution to constructional abilities and nonverbal intelligence.

PubMed

Trojano, Luigi; Siciliano, Mattia; Cristinzio, Chiara; Grossi, Dario

2018-01-01

The present study aimed at exploring relationships among the visuospatial tasks included in the Battery for Visuospatial Abilities (BVA), and at assessing the relative contribution of different facets of visuospatial processing on tests tapping constructional abilities and nonverbal abstract reasoning. One hundred forty-four healthy subjects with a normal score on Mini Mental State Examination completed the BVA plus Raven's Coloured Progressive Matrices and Constructional Apraxia test. We used Principal Axis Factoring and Parallel Analysis to investigate relationships among the BVA visuospatial tasks, and performed regression analyses to assess the visuospatial contribution to constructional abilities and nonverbal abstract reasoning. Principal Axis Factoring and Parallel Analysis revealed two eigenvalues exceeding 1, accounting for about 60% of the variance. A 2-factor model provided the best fit. Factor 1 included sub-tests exploring "complex" visuospatial skills, whereas Factor 2 included two subtests tapping "simple" visuospatial skills. Regression analyses revealed that both Factor 1 and Factor 2 significantly affected performance on Raven's Coloured Progressive Matrices, whereas only the Factor 1 affected performance on Constructional Apraxia test. Our results supported functional segregation proposed by De Renzi, suggesting clinical caution to utilize a single test to assess visuospatial domain, and qualified the visuospatial contribution in drawing and non-verbal intelligence test.

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China

PubMed Central

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-01-01

Background: In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. Methods: As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6–12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. Results: The prevalence of anemia was 12.60% with a range of 3.47%–40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. Conclusions: The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities. PMID:27174328

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China.

PubMed

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-05-20

In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6-12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. The prevalence of anemia was 12.60% with a range of 3.47%-40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities.

Cerebrovascular risk factors for patients with cerebral watershed infarction: A case-control study based on computed tomography angiography in a population from Southwest China.

PubMed

Dong, Mei-Xue; Hu, Ling; Huang, Yuan-Jun; Xu, Xiao-Min; Liu, Yang; Wei, You-Dong

2017-07-01

To determine cerebrovascular risk factors for patients with cerebral watershed infarction (CWI) from Southwest China.Patients suffering from acute ischemic stroke were categorized into internal CWI (I-CWI), external CWI (E-CWI), or non-CWI (patients without CWI) groups. Clinical data were collected and degrees of steno-occlusion of all cerebral arteries were scored. Arteries associated with the circle of Willis were also assessed. Data were compared using Pearson chi-squared tests for categorical data and 1-way analysis of variance with Bonferroni post hoc tests for continuous data, as appropriate. Multivariate binary logistic regression analysis was performed to determine independent cerebrovascular risk factors for CWI.Compared with non-CWI, I-CWI had higher degrees of steno-occlusion of the ipsilateral middle cerebral artery, ipsilateral carotid artery, and contralateral middle cerebral artery. E-CWI showed no significant differences. All the 3 arteries were independent cerebrovascular risk factors for I-CWI confirmed by multivariate binary logistic regression analysis. I-CWI had higher degrees of steno-occlusion of the ipsilateral middle cerebral artery compared with E-CWI. No significant differences were found among arteries associated with the circle of Willis.The ipsilateral middle cerebral artery, carotid artery, and contralateral middle cerebral artery were independent cerebrovascular risk factors for I-CWI. No cerebrovascular risk factor was identified for E-CWI.

Determinant of securitization asset pricing in Malaysia

NASA Astrophysics Data System (ADS)

Bakri, M. H.; Ali, R.; Ismail, S.; Sufian, F.; Baharom, A. H.

2014-12-01

Malaysian firms have been reported involve in Asset Back Securities since 1986s where Cagamas is a pioneer. This research aims to examine the factor influencing primary market spread. Least square method and regression analysis are applied for the study period 2004-2012. The result shows one determinants in internal regression model and three determinants in external regression influence or contribute to the primary market spread and are statistically significant in developing the securitization in Malaysia. It can be concluded that transaction size significantly contribute to the determinant primary market spread in internal regression model while liquidity, transaction size and crisis is significant in both regression model. From five hypotheses, three hypotheses support that the determinants have a relationship with primary market spread.

[The related factors of head and neck mocosal melanoma with lymph node metastasis].

PubMed

Yin, G F; Guo, W; Chen, X H; Huang, Z G

2017-12-05

Objective: To investigate the related factors of mucosal melanoma of head and neck with lymph node metastasis for early diagnosis and further treatments. Method: A retrospective analysis of 117 cases of head and neck mucosal malignant melanoma patients which received surgical treatment was performed. Eleven cases of patients with pathologically confirmed lymph node metastasis and 33 cases without lymph node metastasis (1∶3) were randomly selected to analyze. The related factors of lymph node metastasis of head and neck mucosal melanoma patients including age, gender, whether the existence of recurrence, bone invasion, lesion location were analyzed. The single factor and logistic regression analysis were performed, P <0.05 difference was statistically significant. Result: The lymph node metastasis rate of head and neck mucosal melanoma was 9.40%(11/117), the single factor analysis showed that there were 3 factors to be associated with lymph node metastasis, which was recurrence ( P =0.0000), bone invasion ( P =0.001), primary position ( P =0.007). Recurrence ( P =0.021) was a risk factor for lymph node metastasis according to the Logistic regression analysis, and the impact of bone invasion ( P =0.487) and primary location ( P =0.367) remained to be further explored. Conclusion: The patients of head and neck mucosal melanoma with the presence of recurrent usually accompanied by a further progression of the disease, such as lymph node metastasis, so for recurrent patients should pay special attention to the situation of lymph node and choose the reasonable treatment. Copyright© by the Editorial Department of Journal of Clinical Otorhinolaryngology Head and Neck Surgery.

A tandem regression-outlier analysis of a ligand cellular system for key structural modifications around ligand binding.

PubMed

Lin, Ying-Ting

2013-04-30

A tandem technique of hard equipment is often used for the chemical analysis of a single cell to first isolate and then detect the wanted identities. The first part is the separation of wanted chemicals from the bulk of a cell; the second part is the actual detection of the important identities. To identify the key structural modifications around ligand binding, the present study aims to develop a counterpart of tandem technique for cheminformatics. A statistical regression and its outliers act as a computational technique for separation. A PPARγ (peroxisome proliferator-activated receptor gamma) agonist cellular system was subjected to such an investigation. Results show that this tandem regression-outlier analysis, or the prioritization of the context equations tagged with features of the outliers, is an effective regression technique of cheminformatics to detect key structural modifications, as well as their tendency of impact to ligand binding. The key structural modifications around ligand binding are effectively extracted or characterized out of cellular reactions. This is because molecular binding is the paramount factor in such ligand cellular system and key structural modifications around ligand binding are expected to create outliers. Therefore, such outliers can be captured by this tandem regression-outlier analysis.

Individual-Level Influences on Perceptions of Neighborhood Disorder: A Multilevel Analysis

ERIC Educational Resources Information Center

Latkin, Carl A.; German, Danielle; Hua, Wei; Curry, Aaron D.

2009-01-01

Health outcomes are associated with aggregate neighborhood measures and individual neighborhood perceptions. In this study, the authors sought to delineate individual, social network, and spatial factors that may influence perceptions of neighborhood disorder. Multilevel regression analysis showed that neighborhood perceptions were more negative…

Correlates of Successful Aging: Are They Universal?

ERIC Educational Resources Information Center

Litwin, Howard

2005-01-01

The analysis compared differing correlates of life satisfaction among three diverse population groups in Israel, examining background and health status variables, social environment factors, and activity indicators. Multiple regression analysis revealed that veteran Jewish-Israelis (n = 2,043) had the largest set of predictors, the strongest of…

Examination of Parameters Affecting the House Prices by Multiple Regression Analysis and its Contributions to Earthquake-Based Urban Transformation

NASA Astrophysics Data System (ADS)

Denli, H. H.; Durmus, B.

2016-12-01

The purpose of this study is to examine the factors which may affect the apartment prices with multiple linear regression analysis models and visualize the results by value maps. The study is focused on a county of Istanbul - Turkey. Totally 390 apartments around the county Umraniye are evaluated due to their physical and locational conditions. The identification of factors affecting the price of apartments in the county with a population of approximately 600k is expected to provide a significant contribution to the apartment market.Physical factors are selected as the age, number of rooms, size, floor numbers of the building and the floor that the apartment is positioned in. Positional factors are selected as the distances to the nearest hospital, school, park and police station. Totally ten physical and locational parameters are examined by regression analysis.After the regression analysis has been performed, value maps are composed from the parameters age, price and price per square meters. The most significant of the composed maps is the price per square meters map. Results show that the location of the apartment has the most influence to the square meter price information of the apartment. A different practice is developed from the composed maps by searching the ability of using price per square meters map in urban transformation practices. By marking the buildings older than 15 years in the price per square meters map, a different and new interpretation has been made to determine the buildings, to which should be given priority during an urban transformation in the county.This county is very close to the North Anatolian Fault zone and is under the threat of earthquakes. By marking the apartments older than 15 years on the price per square meters map, both older and expensive square meters apartments list can be gathered. By the help of this list, the priority could be given to the selected higher valued old apartments to support the economy of the country during an earthquake loss. We may call this urban transformation as earthquake-based urban transformation.

Vascular Disease, ESRD, and Death: Interpreting Competing Risk Analyses

PubMed Central

Coresh, Josef; Segev, Dorry L.; Kucirka, Lauren M.; Tighiouart, Hocine; Sarnak, Mark J.

2012-01-01

Summary Background and objectives Vascular disease, a common condition in CKD, is a risk factor for mortality and ESRD. Optimal patient care requires accurate estimation and ordering of these competing risks. Design, setting, participants, & measurements This is a prospective cohort study of screened (n=885) and randomized participants (n=837) in the Modification of Diet in Renal Disease study (original study enrollment, 1989–1992), evaluating the association of vascular disease with ESRD and pre-ESRD mortality using standard survival analysis and competing risk regression. Results The method of analysis resulted in markedly different estimates. Cumulative incidence by standard analysis (censoring at the competing event) implied that, with vascular disease, the 15-year incidence was 66% and 51% for ESRD and pre-ESRD death, respectively. A more accurate representation of absolute risk was estimated with competing risk regression: 15-year incidence was 54% and 29% for ESRD and pre-ESRD death, respectively. For the association of vascular disease with pre-ESRD death, estimates of relative risk by the two methods were similar (standard survival analysis adjusted hazard ratio, 1.63; 95% confidence interval, 1.20–2.20; competing risk regression adjusted subhazard ratio, 1.57; 95% confidence interval, 1.15–2.14). In contrast, the hazard and subhazard ratios differed substantially for other associations, such as GFR and pre-ESRD mortality. Conclusions When competing events exist, absolute risk is better estimated using competing risk regression, but etiologic associations by this method must be carefully interpreted. The presence of vascular disease in CKD decreases the likelihood of survival to ESRD, independent of age and other risk factors. PMID:22859747

Vascular disease, ESRD, and death: interpreting competing risk analyses.

PubMed

Grams, Morgan E; Coresh, Josef; Segev, Dorry L; Kucirka, Lauren M; Tighiouart, Hocine; Sarnak, Mark J

2012-10-01

Vascular disease, a common condition in CKD, is a risk factor for mortality and ESRD. Optimal patient care requires accurate estimation and ordering of these competing risks. This is a prospective cohort study of screened (n=885) and randomized participants (n=837) in the Modification of Diet in Renal Disease study (original study enrollment, 1989-1992), evaluating the association of vascular disease with ESRD and pre-ESRD mortality using standard survival analysis and competing risk regression. The method of analysis resulted in markedly different estimates. Cumulative incidence by standard analysis (censoring at the competing event) implied that, with vascular disease, the 15-year incidence was 66% and 51% for ESRD and pre-ESRD death, respectively. A more accurate representation of absolute risk was estimated with competing risk regression: 15-year incidence was 54% and 29% for ESRD and pre-ESRD death, respectively. For the association of vascular disease with pre-ESRD death, estimates of relative risk by the two methods were similar (standard survival analysis adjusted hazard ratio, 1.63; 95% confidence interval, 1.20-2.20; competing risk regression adjusted subhazard ratio, 1.57; 95% confidence interval, 1.15-2.14). In contrast, the hazard and subhazard ratios differed substantially for other associations, such as GFR and pre-ESRD mortality. When competing events exist, absolute risk is better estimated using competing risk regression, but etiologic associations by this method must be carefully interpreted. The presence of vascular disease in CKD decreases the likelihood of survival to ESRD, independent of age and other risk factors.

Using regression analysis to predict emergency patient volume at the Indianapolis 500 mile race.

PubMed

Bowdish, G E; Cordell, W H; Bock, H C; Vukov, L F

1992-10-01

Emergency physicians often plan and provide on-site medical care for mass gatherings. Most of the mass gathering literature is descriptive. Only a few studies have looked at factors such as crowd size, event characteristics, or weather in predicting numbers and types of patients at mass gatherings. We used regression analysis to relate patient volume on Race Day at the Indianapolis Motor Speedway to weather conditions and race characteristics. Race Day weather data for the years 1983 to 1989 were obtained from the National Oceanic and Atmospheric Administration. Data regarding patients treated on 1983 to 1989 Race Days were obtained from the facility hospital (Hannah Emergency Medical Center) data base. Regression analysis was performed using weather factors and race characteristics as independent variables and number of patients seen as the dependent variable. Data from 1990 were used to test the validity of the model. There was a significant relationship between dew point (which is calculated from temperature and humidity) and patient load (P less than .01). Dew point, however, failed to predict patient load during the 1990 race. No relationships could be established between humidity, sunshine, wind, or race characteristics and number of patients. Although higher dew point was associated with higher patient load during the 1983 to 1989 races, dew point was a poor predictor of patient load during the 1990 race. Regression analysis may be useful in identifying relationships between event characteristics and patient load but is probably inadequate to explain the complexities of crowd behavior and too simplified to use as a prediction tool.

Factors associated with secondhand smoke exposure in different settings: Results from the German Health Update (GEDA) 2012.

PubMed

Fischer, Florian; Kraemer, Alexander

2016-04-14

The ubiquity of secondhand smoke (SHS) exposure at home or in private establishments, workplaces and public areas poses several challenges for the reduction of SHS exposure. This study aimed to describe the prevalence of SHS exposure in Germany and key factors associated with exposure. Results were also differentiated by place of exposure. A secondary data analysis based on the public use file of the German Health Update 2012 was conducted (n = 13,933). Only non-smokers were included in the analysis. In a multivariable logistic regression model the factors associated with SHS exposure were calculated. In addition, a further set of multivariable logistic regressions were calculated for factors associated with the place of SHS exposure (workplace, at home, bars/discotheques, restaurants, at the house of a friend). More than a quarter of non-smoking study participants were exposed to SHS. The main area of exposure was the workplace (40.9 %). The multivariable logistic regression indicated young age as the most important factor associated with SHS exposure. The odds for SHS exposure was higher in men than in women. The likelihood of SHS exposure decreased with higher education. SHS exposure and the associated factors varied between different places of exposure. Despite several actions to protect non-smokers which were implemented in Germany during the past years, SHS exposure still remains a relevant risk factor at a population level. According to the results of this study, particularly the workplace and other public places such as bars and discotheques have to be taken into account for the development of strategies to reduce SHS exposure.

A regression-kriging model for estimation of rainfall in the Laohahe basin

NASA Astrophysics Data System (ADS)

Wang, Hong; Ren, Li L.; Liu, Gao H.

2009-10-01

This paper presents a multivariate geostatistical algorithm called regression-kriging (RK) for predicting the spatial distribution of rainfall by incorporating five topographic/geographic factors of latitude, longitude, altitude, slope and aspect. The technique is illustrated using rainfall data collected at 52 rain gauges from the Laohahe basis in northeast China during 1986-2005 . Rainfall data from 44 stations were selected for modeling and the remaining 8 stations were used for model validation. To eliminate multicollinearity, the five explanatory factors were first transformed using factor analysis with three Principal Components (PCs) extracted. The rainfall data were then fitted using step-wise regression and residuals interpolated using SK. The regression coefficients were estimated by generalized least squares (GLS), which takes the spatial heteroskedasticity between rainfall and PCs into account. Finally, the rainfall prediction based on RK was compared with that predicted from ordinary kriging (OK) and ordinary least squares (OLS) multiple regression (MR). For correlated topographic factors are taken into account, RK improves the efficiency of predictions. RK achieved a lower relative root mean square error (RMSE) (44.67%) than MR (49.23%) and OK (73.60%) and a lower bias than MR and OK (23.82 versus 30.89 and 32.15 mm) for annual rainfall. It is much more effective for the wet season than for the dry season. RK is suitable for estimation of rainfall in areas where there are no stations nearby and where topography has a major influence on rainfall.

Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet

2010-05-01

This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross application model yields reasonable results which can be used for preliminary landslide hazard mapping.

T56. AN EXPLORATORY ANALYSIS CONVERTING SCORES BETWEEN THE PANSS AND BNSS

PubMed Central

Kott, Alan; Daniel, David

2018-01-01

Abstract Background The Brief Negative Symptom Scale is a relatively new instrument designed specifically to measure the negative symptoms in schizophrenia. Recently more clinical trials include the BNSS scale as a secondary or exploratory outcome, typically along with the PANSS. In the current analysis we aimed at establishing the equations that would allow conversion between the BNSS scale total score and the PANSS negative subscale and PANSS negative factors score as well as conversion equations between the expressive deficits and avolition/apathy factors of the scales. (Kirkpatrick, 2011; Strauss, 2012) Methods Data from 518 schizophrenia clinical trials subjects with both PANSS and BNSS data available were used. Regression analyses predicting the BNSS total score with the PANSS negative subscale score, and the BNSS total score with the PANSS Negative factor (NFS) score were performed on data from all subjects. Regression analyses predicting the BNSS avolition/apathy factor (items 1, 2, 3, 5, 6, 7, and 8) with the PANSS avolition/apathy factor (items N2, N4 and G16) and the BNSS expressive deficits factor (items 4, 9, 10, 11, 12, and 13)with the expressive deficits factor (items N1, N3, N6, G5, G7, and G13)of the PANSS were performed on a sample of 318 subjects with individual BNSS item scores available. In addition to estimating the equations we as well calculated the Pearson’s correlations between the scales. Results The PANSS and BNSS avolition/apathy factors were highly correlated (r=0.70) as were the expressive deficit factors r=0.83). The following equations predicting the BNSS total score were obtained from regression analyses performed on 2,560 data points: BNSS_total = -11.64 + 2.10*PANSS_negative_subscale BNSS_total = -9.26 + 2.11*PANSS_NFS The following equations predicting the BNSS factor scores from the PANSS factor scores were obtained from regression analyses performed on 1,634 data points: BNSS_avolition/apathy = -2.40 + 2.38 * PANSS_avolition/apathy BNSS_expressive_deficit_factor = -4.21 + 1.27 * PANSS_expressive_deficit_factor Discussion The BNSS differs from the PANSS negative factor because it addresses all five currently recognized domains of negative symptoms including anhedonia and attempts to differentiate anticipatory from consummatory states. In our analysis we have replicated the strong correlation between the BNSS total score and PANSS negative subscale and newly identified strong correlations between the BNSS total score and NFS as well as strong correlations between the avolotion/apathy and expressive deficit factors of the BNSS and the PANSS scales. (Kirkpatrick, 2011)The provided equations offer a useful tool allowing researchers and clinicians to easily convert the data between the instruments for reasons such as pooling data from multiple trials using one of the instruments, to allow interpretation of results within the context of previously conducted research, etc. but as well offer a framework for risk based monitoring to identify data deviating from the expected relationship and allow for a targeted exploration of the causes for such a disagreement. The data used for analysis included not only subjects with predominantly negative symptoms but as well acutely psychotic subjects as well as subjects in stable conditions allowing therefore to generalize the results across the majority of schizophrenic subjects. This post-hoc analysis is exploratory. We plan to further explore the potential utility of equations addressing the relationships among schizophrenia measures of symptom severity in an iterative manner with larger datasets.

Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

PubMed Central

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

Reliability and Validity of the Chinese Version of the Solution-Focused Inventory in College Students

ERIC Educational Resources Information Center

Yang, Hongfei; Hai, Tang

2015-01-01

The psychometrics of the Chinese Solution-Focused Inventory (CSFI) was studied in Chinese college students. Confirmatory factor analysis confirmed the 3-factor structure. All subscales showed good reliability and convergent and incremental validity. Results of hierarchical regression analyses indicated that the 3 subscales accounted for additional…

Factors Affecting University Entrants' Performance in High-Stakes Tests: A Multiple Regression Analysis

ERIC Educational Resources Information Center

Uy, Chin; Manalo, Ronaldo A.; Cabauatan, Ronaldo R.

2015-01-01

In the Philippines, students seeking admission to a university are usually required to meet certain entrance requirements, including passing the entrance examinations with questions on IQ and English, mathematics, and science. This paper aims to determine the factors that affect the performance of entrants into business programmes in high-stakes…

The Trait Emotional Intelligence Questionnaire: Internal Structure, Convergent, Criterion, and Incremental Validity in an Italian Sample

ERIC Educational Resources Information Center

Andrei, Federica; Smith, Martin M.; Surcinelli, Paola; Baldaro, Bruno; Saklofske, Donald H.

2016-01-01

This study investigated the structure and validity of the Italian translation of the Trait Emotional Intelligence Questionnaire. Data were self-reported from 227 participants. Confirmatory factor analysis supported the four-factor structure of the scale. Hierarchical regressions also demonstrated its incremental validity beyond demographics, the…

School Principals' Job Satisfaction: The Effects of Work Intensification

ERIC Educational Resources Information Center

Wang, Fei; Pollock, Katina; Hauseman, Cameron

2018-01-01

This study examines principals' job satisfaction in relation to their work intensification. Frederick Herzberg's two-factor theory was used to shed light on how motivating and maintenance factors affect principals' job satisfaction. Logistic multiple regressions were used in the analysis of survey data that were collected from 2,701 elementary and…

The parenting attitudes and the stress of mothers predict the asthmatic severity of their children: a prospective study.

PubMed

Nagano, Jun; Kakuta, Chikage; Motomura, Chikako; Odajima, Hiroshi; Sudo, Nobuyuki; Nishima, Sankei; Kubo, Chiharu

2010-10-07

To examine relationships between a mother's stress-related conditions and parenting attitudes and their children's asthmatic status. 274 mothers of an asthmatic child 2 to 12 years old completed a questionnaire including questions about their chronic stress/coping behaviors (the "Stress Inventory"), parenting attitudes (the "Ta-ken Diagnostic Test for Parent-Child Relationship, Parent Form"), and their children's disease status. One year later, a follow-up questionnaire was mailed to the mothers that included questions on the child's disease status. 223 mothers (81%) responded to the follow-up survey. After controlling for non-psychosocial factors including disease severity at baseline, multiple linear regression analysis followed by multiple logistic regression analysis found chronic irritation/anger and emotional suppression to be aggravating factors for children aged < 7 years; for children aged 7 and over, the mothers' egocentric behavior was a mitigating factor while interference was an aggravating factor. Different types of parental stress/coping behaviors and parenting styles may differently predict their children's asthmatic status, and such associations may change as children grow.

Seroprevalence and Risk Factors of Chlamydia abortus Infection in Tibetan Sheep in Gansu Province, Northwest China

PubMed Central

Qin, Si-Yuan; Yin, Ming-Yang; Cong, Wei; Zhou, Dong-Hui; Zhang, Xiao-Xuan; Zhao, Quan; Zhu, Xing-Quan; Zhou, Ji-Zhang; Qian, Ai-Dong

2014-01-01

Chlamydia abortus, an important pathogen in a variety of animals, is associated with abortion in sheep. In the present study, 1732 blood samples, collected from Tibetan sheep between June 2013 and April 2014, were examined by the indirect hemagglutination (IHA) test, aiming to evaluate the seroprevalence and risk factors of C. abortus infection in Tibetan sheep. 323 of 1732 (18.65%) samples were seropositive for C. abortus antibodies at the cut-off of 1 : 16. A multivariate logistic regression analysis was used to evaluate the risk factors associated with seroprevalence, which could provide foundation to prevent and control C. abortus infection in Tibetan sheep. Gender of Tibetan sheep was left out of the final model because it is not significant in the logistic regression analysis (P > 0.05). Region, season, and age were considered as major risk factors associated with C. abortus infection in Tibetan sheep. Our study revealed a widespread and high prevalence of C. abortus infection in Tibetan sheep in Gansu province, northwest China, with higher exposure risk in different seasons and ages and distinct geographical distribution. PMID:25401129

Massive Open Online Course Completion Rates Revisited: Assessment, Length and Attrition

ERIC Educational Resources Information Center

Jordan, Katy

2015-01-01

This analysis is based upon enrolment and completion data collected for a total of 221 Massive Open Online Courses (MOOCs). It extends previously reported work (Jordan, 2014) with an expanded dataset; the original work is extended to include a multiple regression analysis of factors that affect completion rates and analysis of attrition rates…

The Impact of Managerial Coaching on Learning Outcomes within the Team Context: An Analysis

ERIC Educational Resources Information Center

Hagen, Marcia; Aguilar, Mariya Gavrilova

2012-01-01

This study investigates the relationship between coaching expertise, project difficulty, and team empowerment on team learning outcomes within the context of a high-performance work team. Variables were tested using multiple regression analysis. The data were analyzed for two groups--team leaders and team members--using t-tests, factor analysis,…

Methods of estimating or accounting for neighborhood associations with health using complex survey data.

PubMed

Brumback, Babette A; Cai, Zhuangyu; Dailey, Amy B

2014-05-15

Reasons for health disparities may include neighborhood-level factors, such as availability of health services, social norms, and environmental determinants, as well as individual-level factors. Investigating health inequalities using nationally or locally representative data often requires an approach that can accommodate a complex sampling design, in which individuals have unequal probabilities of selection into the study. The goal of the present article is to review and compare methods of estimating or accounting for neighborhood influences with complex survey data. We considered 3 types of methods, each generalized for use with complex survey data: ordinary regression, conditional likelihood regression, and generalized linear mixed-model regression. The relative strengths and weaknesses of each method differ from one study to another; we provide an overview of the advantages and disadvantages of each method theoretically, in terms of the nature of the estimable associations and the plausibility of the assumptions required for validity, and also practically, via a simulation study and 2 epidemiologic data analyses. The first analysis addresses determinants of repeat mammography screening use using data from the 2005 National Health Interview Survey. The second analysis addresses disparities in preventive oral health care using data from the 2008 Florida Behavioral Risk Factor Surveillance System Survey.

Age Estimation of Infants Through Metric Analysis of Developing Anterior Deciduous Teeth.

PubMed

Viciano, Joan; De Luca, Stefano; Irurita, Javier; Alemán, Inmaculada

2018-01-01

This study provides regression equations for estimation of age of infants from the dimensions of their developing deciduous teeth. The sample comprises 97 individuals of known sex and age (62 boys, 35 girls), aged between 2 days and 1,081 days. The age-estimation equations were obtained for the sexes combined, as well as for each sex separately, thus including "sex" as an independent variable. The values of the correlations and determination coefficients obtained for each regression equation indicate good fits for most of the equations obtained. The "sex" factor was statistically significant when included as an independent variable in seven of the regression equations. However, the "sex" factor provided an advantage for age estimation in only three of the equations, compared to those that did not include "sex" as a factor. These data suggest that the ages of infants can be accurately estimated from measurements of their developing deciduous teeth. © 2017 American Academy of Forensic Sciences.

Forecasting municipal solid waste generation using prognostic tools and regression analysis.

PubMed

Ghinea, Cristina; Drăgoi, Elena Niculina; Comăniţă, Elena-Diana; Gavrilescu, Marius; Câmpean, Teofil; Curteanu, Silvia; Gavrilescu, Maria

2016-11-01

For an adequate planning of waste management systems the accurate forecast of waste generation is an essential step, since various factors can affect waste trends. The application of predictive and prognosis models are useful tools, as reliable support for decision making processes. In this paper some indicators such as: number of residents, population age, urban life expectancy, total municipal solid waste were used as input variables in prognostic models in order to predict the amount of solid waste fractions. We applied Waste Prognostic Tool, regression analysis and time series analysis to forecast municipal solid waste generation and composition by considering the Iasi Romania case study. Regression equations were determined for six solid waste fractions (paper, plastic, metal, glass, biodegradable and other waste). Accuracy Measures were calculated and the results showed that S-curve trend model is the most suitable for municipal solid waste (MSW) prediction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Which sociodemographic factors are important on smoking behaviour of high school students? The contribution of classification and regression tree methodology in a broad epidemiological survey.

PubMed

Ozge, C; Toros, F; Bayramkaya, E; Camdeviren, H; Sasmaz, T

2006-08-01

The purpose of this study is to evaluate the most important sociodemographic factors on smoking status of high school students using a broad randomised epidemiological survey. Using in-class, self administered questionnaire about their sociodemographic variables and smoking behaviour, a representative sample of total 3304 students of preparatory, 9th, 10th, and 11th grades, from 22 randomly selected schools of Mersin, were evaluated and discriminative factors have been determined using appropriate statistics. In addition to binary logistic regression analysis, the study evaluated combined effects of these factors using classification and regression tree methodology, as a new statistical method. The data showed that 38% of the students reported lifetime smoking and 16.9% of them reported current smoking with a male predominancy and increasing prevalence by age. Second hand smoking was reported at a 74.3% frequency with father predominance (56.6%). The significantly important factors that affect current smoking in these age groups were increased by household size, late birth rank, certain school types, low academic performance, increased second hand smoking, and stress (especially reported as separation from a close friend or because of violence at home). Classification and regression tree methodology showed the importance of some neglected sociodemographic factors with a good classification capacity. It was concluded that, as closely related with sociocultural factors, smoking was a common problem in this young population, generating important academic and social burden in youth life and with increasing data about this behaviour and using new statistical methods, effective coping strategies could be composed.

A dynamic factor model of the evaluation of the financial crisis in Turkey.

PubMed

Sezgin, F; Kinay, B

2010-01-01

Factor analysis has been widely used in economics and finance in situations where a relatively large number of variables are believed to be driven by few common causes of variation. Dynamic factor analysis (DFA) which is a combination of factor and time series analysis, involves autocorrelation matrices calculated from multivariate time series. Dynamic factor models were traditionally used to construct economic indicators, macroeconomic analysis, business cycles and forecasting. In recent years, dynamic factor models have become more popular in empirical macroeconomics. They have more advantages than other methods in various respects. Factor models can for instance cope with many variables without running into scarce degrees of freedom problems often faced in regression-based analysis. In this study, a model which determines the effect of the global crisis on Turkey is proposed. The main aim of the paper is to analyze how several macroeconomic quantities show an alteration before the evolution of the crisis and to decide if a crisis can be forecasted or not.

[Correlation research on contents of podophyllotoxin and total lignans in Sinopodophyllum hexandrum and ecological factors].

PubMed

Li, Min; Zhong, Guo-yue; Wu, Ao-lin; Zhang, Shou-wen; Jiang, Wei; Liang, Jian

2015-05-01

To explore the correlation between the ecological factors and the contents of podophyllotoxin and total lignans in root and rhizome of Sinopodophyllum hexandrum, podophyllotoxin in 87 samples (from 5 provinces) was determined by HPLC and total lignans by UV. A correlation and regression analysis was made by software SPSS 16.0 in combination with ecological factors (terrain, soil and climate). The content determination results showed a great difference between podophyllotoxin and total lignans, attaining 1.001%-6.230% and 5.350%-16.34%, respective. The correlation and regression analysis by SPSS showed a positive linear correlation between their contents, strong positive correlation between their contents, latitude and annual average rainfall within the sampling area, weak negative correlation with pH value and organic material in soil, weaker and stronger positive correlations with soil potassium, weak negative correlation with slope and annual average temperature and weaker positive correlation between the podophyllotoxin content and soil potassium.

Comparing statistical and machine learning classifiers: alternatives for predictive modeling in human factors research.

PubMed

Carnahan, Brian; Meyer, Gérard; Kuntz, Lois-Ann

2003-01-01

Multivariate classification models play an increasingly important role in human factors research. In the past, these models have been based primarily on discriminant analysis and logistic regression. Models developed from machine learning research offer the human factors professional a viable alternative to these traditional statistical classification methods. To illustrate this point, two machine learning approaches--genetic programming and decision tree induction--were used to construct classification models designed to predict whether or not a student truck driver would pass his or her commercial driver license (CDL) examination. The models were developed and validated using the curriculum scores and CDL exam performances of 37 student truck drivers who had completed a 320-hr driver training course. Results indicated that the machine learning classification models were superior to discriminant analysis and logistic regression in terms of predictive accuracy. Actual or potential applications of this research include the creation of models that more accurately predict human performance outcomes.

Analysis of the effectiveness of fertilizer subsidy policy and its effect on rice production in Karanganyar Regency

NASA Astrophysics Data System (ADS)

Mulyadiana, A. T.; Marwanti, S.; Rahayu, W.

2018-03-01

The research aims to know the factors which affecting rice production, and to know the effectiveness of fertilizer subsidy policy on rice production in Karanganyar Regency. The fertilizer subsidy policy was based on four indicators of fertilizer subsidy namely exact price, exact place, exact time, and exact quantity. Data was analyzed using descriptive quantitative and qualitative and multiple linear regression. The result of research showed that fertilizer subsidy policy in Karanganyar Regency evaluated from four indicators was not effective because the distribution of fertilizer subsidy to farmers still experience some mistakes. The result of regression analysis showed that production factors such as land area, use of urea fertilizer, use of NPK fertilizer, and effectiveness of fertilizer subsidy policy had positive correlation and significant influence on rice production, while labor utilization and use of seeds factors had no significant effect on rice production in Karanganyar Regency. This means that if the fertilizer subsidy policy is more effective, rice production is also increased.

Clinical features and risk factor analysis for lower extremity deep venous thrombosis in Chinese neurosurgical patients

PubMed Central

Guo, Fuyou; Shashikiran, Tagilapalli; Chen, Xi; Yang, Lei; Liu, Xianzhi; Song, Laijun

2015-01-01

Background: Deep venous thrombosis (DVT) contributes significantly to the morbidity and mortality of neurosurgical patients; however, no data regarding lower extremity DVT in postoperative Chinese neurosurgical patients have been reported. Materials and Methods: From January 2012 to December 2013, 196 patients without preoperative DVT who underwent neurosurgical operations were evaluated by color Doppler ultrasonography and D-dimer level measurements on the 3rd, 7th, and 14th days after surgery. Follow-up clinical data were recorded to determine the incidence of lower extremity DVT in postoperative neurosurgical patients and to analyze related clinical features. First, a single factor analysis, Chi-square test, was used to select statistically significant factors. Then, a multivariate analysis, binary logistic regression analysis, was used to determine risk factors for lower extremity DVT in postoperative neurosurgical patients. Results: Lower extremity DVT occurred in 61 patients, and the incidence of DVT was 31.1% in the enrolled Chinese neurosurgical patients. The common symptoms of DVT were limb swelling and lower extremity pain as well as increased soft tissue tension. The common sites of venous involvement were the calf muscle and peroneal and posterior tibial veins. The single factor analysis showed statistically significant differences in DVT risk factors, including age, hypertension, smoking status, operation time, a bedridden or paralyzed state, the presence of a tumor, postoperative dehydration, and glucocorticoid treatment, between the two groups (P < 0.05). The binary logistic regression analysis showed that an age greater than 50 years, hypertension, a bedridden or paralyzed state, the presence of a tumor, and postoperative dehydration were risk factors for lower extremity DVT in postoperative neurosurgical patients. Conclusions: Lower extremity DVT was a common complication following craniotomy in the enrolled Chinese neurosurgical patients. Multiple factors were identified as predictive of DVT in neurosurgical patients, including the presence of a tumor, an age greater than 50 years, hypertension, and immobility. PMID:26752303

Influencing factors of alexithymia in Chinese medical students: a cross-sectional study.

PubMed

Zhu, Yaxin; Luo, Ting; Liu, Jie; Qu, Bo

2017-04-04

A much higher prevalence of alexithymia has been reported in medical students compared with the general population, and alexithymia is a risk factor that increases vulnerability to mental disorders. Our aim was to evaluate the level of alexithymia in Chinese medical students and to explore its influencing factors. A cross-sectional study of 1,950 medical students at Shenyang Medical College was conducted in May 2014 to evaluate alexithymia in medical students using the Chinese version of the 20-item Toronto Alexithymia Scale (TAS-20). The reliability of the questionnaire was assessed by Cronbach's α coefficient and mean inter-item correlations. Confirmatory factor analysis (CFA) was used to evaluate construct validity. The relationships between alexithymia and influencing factors were examined using Student's t-test, analysis of variance, and multiple linear regression analysis. Statistical analysis was performed using SPSS 21.0. Of the 1,950 medical students, 1,886 (96.7%) completed questionnaires. Overall, Cronbach's α coefficient of the TAS-20 questionnaire was 0.868. The results of CFA showed that the original three-factor structure produced an acceptable fit to the data. By univariate analysis, gender, grade (academic year of study), smoking behavior, alcohol use, physical activity, history of living with parents during childhood, and childhood trauma were influencing factors of TAS-20 scores (p < 0.05). Multiple linear regression analysis showed that gender, physical activity, grade, living with parents, and childhood trauma also had statistically significant association with total TAS-20 score (p < 0.05). Gender, physical activity, grade, history of living with parents during childhood, and childhood trauma were all factors determining the level of alexithymia. To prevent alexithymia, it will be advisable to promote adequate physical activity and pay greater attention to male medical students and those who are in the final year of training.

Multiple regression analysis of factors influencing dominant hand grip strength in an adult Malaysian population.

PubMed

Hossain, M G; Zyroul, R; Pereira, B P; Kamarul, T

2012-01-01

Grip strength is an important measure used to monitor the progression of a condition, and to evaluate outcomes of treatment. We assessed how various physical and social factors predict normal grip strength in an adult Malaysian population of mixed Asian ethnicity (254 men, 246 women). Grip strength was recorded using the Jamar dynamometer. The mean grip strength for the dominant hand was 29.8 kg for men and 17.6 kg for women. Multiple regression analysis demonstrated that the dominant hand grip strength was positively associated with height and body mass index, and negatively associated with age for both sexes. Dominant hand grip strength was related to work status for men (p < 0.05) but not for women. However, there was no difference in grip strength among ethnic groups.

Risk Factors for Venous Thromboembolism After Spine Surgery

PubMed Central

Tominaga, Hiroyuki; Setoguchi, Takao; Tanabe, Fumito; Kawamura, Ichiro; Tsuneyoshi, Yasuhiro; Kawabata, Naoya; Nagano, Satoshi; Abematsu, Masahiko; Yamamoto, Takuya; Yone, Kazunori; Komiya, Setsuro

2015-01-01

Abstract The efficacy and safety of chemical prophylaxis to prevent the development of deep venous thrombosis (DVT) or pulmonary embolism (PE) following spine surgery are controversial because of the possibility of epidural hematoma formation. Postoperative venous thromboembolism (VTE) after spine surgery occurs at a frequency similar to that seen after joint operations, so it is important to identify the risk factors for VTE formation following spine surgery. We therefore retrospectively studied data from patients who had undergone spinal surgery and developed postoperative VTE to identify those risk factors. We conducted a retrospective clinical study with logistic regression analysis of a group of 80 patients who had undergone spine surgery at our institution from June 2012 to August 2013. All patients had been screened by ultrasonography for DVT in the lower extremities. Parameters of the patients with VTE were compared with those without VTE using the Mann–Whitney U-test and Fisher exact probability test. Logistic regression analysis was used to analyze the risk factors associated with VTE. A value of P < 0.05 was used to denote statistical significance. The prevalence of VTE was 25.0% (20/80 patients). One patient had sensed some incongruity in the chest area, but the vital signs of all patients were stable. VTEs had developed in the pulmonary artery in one patient, in the superficial femoral vein in one patient, in the popliteal vein in two patients, and in the soleal vein in 18 patients. The Mann–Whitney U-test and Fisher exact probability test showed that, except for preoperative walking disability, none of the parameters showed a significant difference between patients with and without VTE. Risk factors identified in the multivariate logistic regression analysis were preoperative walking disability and age. The prevalence of VTE after spine surgery was relatively high. The most important risk factor for developing postoperative VTE was preoperative walking disability. Gait training during the early postoperative period is required to prevent VTE. PMID:25654385

Can we "predict" long-term outcome for ambulatory transcutaneous electrical nerve stimulation in patients with chronic pain?

PubMed

Köke, Albère J; Smeets, Rob J E M; Perez, Roberto S; Kessels, Alphons; Winkens, Bjorn; van Kleef, Maarten; Patijn, Jacob

2015-03-01

Evidence for effectiveness of transcutaneous electrical nerve stimulation (TENS) is still inconclusive. As heterogeneity of chronic pain patients might be an important factor for this lack of efficacy, identifying factors for a successful long-term outcome is of great importance. A prospective study was performed to identify variables with potential predictive value for 2 outcome measures on long term (6 months); (1) continuation of TENS, and (2) a minimally clinical important pain reduction of ≥ 33%. At baseline, a set of risk factors including pain-related variables, psychological factors, and disability was measured. In a multiple logistic regression analysis, higher patient's expectations, neuropathic pain, no severe pain (< 80 mm visual analogue scale [VAS]) were independently related to long-term continuation of TENS. For the outcome "minimally clinical important pain reduction," the multiple logistic regression analysis indicated that no multisited pain (> 2 pain locations) and intermittent pain were positively and independently associated with a minimally clinical important pain reduction of ≥ 33%. The results showed that factors associated with a successful outcome in the long term are dependent on definition of successful outcome. © 2014 World Institute of Pain.

Statistical analysis of the factors that influenced the mechanical properties improvement of cassava starch films

NASA Astrophysics Data System (ADS)

Monteiro, Mayra; Oliveira, Victor; Santos, Francisco; Barros Neto, Eduardo; Silva, Karyn; Silva, Rayane; Henrique, João; Chibério, Abimaelle

2017-08-01

In order to obtain cassava starch films with improved mechanical properties in relation to the synthetic polymer in the packaging production, a complete factorial design 23 was carried out in order to investigate which factor significantly influences the tensile strength of the biofilm. The factors to be investigated were cassava starch, glycerol and modified clay contents. Modified bentonite clay was used as a filling material of the biofilm. Glycerol was the plasticizer used to thermoplastify cassava starch. The factorial analysis suggested a regression model capable of predicting the optimal mechanical property of the cassava starch film from the maximization of the tensile strength. The reliability of the regression model was tested by the correlation established with the experimental data through the following statistical analyse: Pareto graph. The modified clay was the factor of greater statistical significance on the observed response variable, being the factor that contributed most to the improvement of the mechanical property of the starch film. The factorial experiments showed that the interaction of glycerol with both modified clay and cassava starch was significant for the reduction of biofilm ductility. Modified clay and cassava starch contributed to the maximization of biofilm ductility, while glycerol contributed to the minimization.

Understanding Child Stunting in India: A Comprehensive Analysis of Socio-Economic, Nutritional and Environmental Determinants Using Additive Quantile Regression

PubMed Central

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A.

2013-01-01

Background Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. Objective We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Design Using cross-sectional data for children aged 0–24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. Results At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Conclusions Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role. PMID:24223839

Understanding child stunting in India: a comprehensive analysis of socio-economic, nutritional and environmental determinants using additive quantile regression.

PubMed

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A

2013-01-01

Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Using cross-sectional data for children aged 0-24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role.

Gender effects in gaming research: a case for regression residuals?

PubMed

Pfister, Roland

2011-10-01

Numerous recent studies have examined the impact of video gaming on various dependent variables, including the players' affective reactions, positive as well as detrimental cognitive effects, and real-world aggression. These target variables are typically analyzed as a function of game characteristics and player attributes-especially gender. However, findings on the uneven distribution of gaming experience between males and females, on the one hand, and the effect of gaming experience on several target variables, on the other hand, point at a possible confound when gaming experiments are analyzed with a standard analysis of variance. This study uses simulated data to exemplify analysis of regression residuals as a potentially beneficial data analysis strategy for such datasets. As the actual impact of gaming experience on each of the various dependent variables differs, the ultimate benefits of analysis of regression residuals entirely depend on the research question, but it offers a powerful statistical approach to video game research whenever gaming experience is a confounding factor.

Analysis of Young Men: Chapter Two. Determinants of Adult Socioeconomic Attainment in Young Men: An Analysis of the Role of Risk and Social Capital Factors, and the Pathways through Which They Have Their Impacts.

ERIC Educational Resources Information Center

Brown, Brett V.

In this chapter, a series of nested regression models are estimated to analyze three measures of adult socioeconomic attainment measured at age 29: (1) educational attainment; (2) occupational attainment; and (3) earnings. The models seek to relate risk, social capital, social-psychological factors, and life course events in early adulthood, both…

A Systematic Review of Methodology: Time Series Regression Analysis for Environmental Factors and Infectious Diseases

PubMed Central

Imai, Chisato; Hashizume, Masahiro

2015-01-01

Background: Time series analysis is suitable for investigations of relatively direct and short-term effects of exposures on outcomes. In environmental epidemiology studies, this method has been one of the standard approaches to assess impacts of environmental factors on acute non-infectious diseases (e.g. cardiovascular deaths), with conventionally generalized linear or additive models (GLM and GAM). However, the same analysis practices are often observed with infectious diseases despite of the substantial differences from non-infectious diseases that may result in analytical challenges. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, systematic review was conducted to elucidate important issues in assessing the associations between environmental factors and infectious diseases using time series analysis with GLM and GAM. Published studies on the associations between weather factors and malaria, cholera, dengue, and influenza were targeted. Findings: Our review raised issues regarding the estimation of susceptible population and exposure lag times, the adequacy of seasonal adjustments, the presence of strong autocorrelations, and the lack of a smaller observation time unit of outcomes (i.e. daily data). These concerns may be attributable to features specific to infectious diseases, such as transmission among individuals and complicated causal mechanisms. Conclusion: The consequence of not taking adequate measures to address these issues is distortion of the appropriate risk quantifications of exposures factors. Future studies should pay careful attention to details and examine alternative models or methods that improve studies using time series regression analysis for environmental determinants of infectious diseases. PMID:25859149

Risk mapping of bovine hypodermosis using geographical information system (GIS) in cattle of subtropical region, Pakistan.

PubMed

Khan, Mobushir Riaz; Ahmed, Haroon; Panadero-Fontan, Rosario; Lopez-Sandez, Ceferino; Khan, Muhammad Aamir; Asif, Saira; Mustafa, Irfan; Ali, Muhammad Isthiaq; Raza, Hamid; Qayyum, Mazhar

2015-08-29

Hypodermosis is an ectoparasitic disease of cattle caused by Hypoderma lineatum and Hypoderma bovis. It is an important health problem of cattle, leading to considerable economic losses. There are various factors that are involved in the spread of this disease such as herd size, location, temperature, humidity, and precipitation. Blood samples from 112 herds were collected to determine the presence of Hypoderma spp. infestation. For these herds, size and location were determined; temperature, humidity, and precipitation data were obtained from meteorological stations; and topographic features were obtained from existing maps and through field work. A regression analysis was then used to generate a risk factor analysis profile for hypodermosis and geographic information system (GIS) was used to map the risks. The GIS map developed showed the degree of infestation in different geographical locations at district and village levels. Cluster analysis demonstrated that hypodermosis prevalence varied within zones and across zones. The regression analysis showed that the temperature in the months of January, February, March, August, and November, and the precipitation in September and October had significant results (p < 0.05) when all the risks factors were analyzed. It is concluded that different ecological factors have an important impact on the intensity and infestation rate of hypodermosis across the globe. The present study might be used to control and eradicate the hypodermosis across the globe.

Using Structured Additive Regression Models to Estimate Risk Factors of Malaria: Analysis of 2010 Malawi Malaria Indicator Survey Data

PubMed Central

Chirombo, James; Lowe, Rachel; Kazembe, Lawrence

2014-01-01

Background After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. Methods We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Results Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. Conclusions The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities. PMID:24991915

Using structured additive regression models to estimate risk factors of malaria: analysis of 2010 Malawi malaria indicator survey data.

PubMed

Chirombo, James; Lowe, Rachel; Kazembe, Lawrence

2014-01-01

After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities.

Length bias correction in gene ontology enrichment analysis using logistic regression.

PubMed

Mi, Gu; Di, Yanming; Emerson, Sarah; Cumbie, Jason S; Chang, Jeff H

2012-01-01

When assessing differential gene expression from RNA sequencing data, commonly used statistical tests tend to have greater power to detect differential expression of genes encoding longer transcripts. This phenomenon, called "length bias", will influence subsequent analyses such as Gene Ontology enrichment analysis. In the presence of length bias, Gene Ontology categories that include longer genes are more likely to be identified as enriched. These categories, however, are not necessarily biologically more relevant. We show that one can effectively adjust for length bias in Gene Ontology analysis by including transcript length as a covariate in a logistic regression model. The logistic regression model makes the statistical issue underlying length bias more transparent: transcript length becomes a confounding factor when it correlates with both the Gene Ontology membership and the significance of the differential expression test. The inclusion of the transcript length as a covariate allows one to investigate the direct correlation between the Gene Ontology membership and the significance of testing differential expression, conditional on the transcript length. We present both real and simulated data examples to show that the logistic regression approach is simple, effective, and flexible.

Quantitative analysis of organizational culture in occupational health research: a theory-based validation in 30 workplaces of the organizational culture profile instrument.

PubMed

Marchand, Alain; Haines, Victor Y; Dextras-Gauthier, Julie

2013-05-04

This study advances a measurement approach for the study of organizational culture in population-based occupational health research, and tests how different organizational culture types are associated with psychological distress, depression, emotional exhaustion, and well-being. Data were collected over a sample of 1,164 employees nested in 30 workplaces. Employees completed the 26-item OCP instrument. Psychological distress was measured with the General Health Questionnaire (12-item); depression with the Beck Depression Inventory (21-item); and emotional exhaustion with five items from the Maslach Burnout Inventory general survey. Exploratory factor analysis evaluated the dimensionality of the OCP scale. Multilevel regression models estimated workplace-level variations, and the contribution of organizational culture factors to mental health and well-being after controlling for gender, age, and living with a partner. Exploratory factor analysis of OCP items revealed four factors explaining about 75% of the variance, and supported the structure of the Competing Values Framework. Factors were labeled Group, Hierarchical, Rational and Developmental. Cronbach's alphas were high (0.82-0.89). Multilevel regression analysis suggested that the four culture types varied significantly between workplaces, and correlated with mental health and well-being outcomes. The Group culture type best distinguished between workplaces and had the strongest associations with the outcomes. This study provides strong support for the use of the OCP scale for measuring organizational culture in population-based occupational health research in a way that is consistent with the Competing Values Framework. The Group organizational culture needs to be considered as a relevant factor in occupational health studies.

Reexamining the Validity and Dimensionality of the Moorong Self-Efficacy Scale: Improving Its Clinical Utility.

PubMed

Middleton, James W; Tran, Yvonne; Lo, Charles; Craig, Ashley

2016-12-01

To improve the clinical utility of the Moorong Self-Efficacy Scale (MSES) by reexamining its factor structure and comparing its performance against a measure of general self-efficacy in persons with spinal cord injury (SCI). Cross-sectional survey design. Community. Adults with SCI (N=161; 118 men and 43 women) recruited from Australia (n=82) and the United States (n=79), including 86 with paraplegia and 75 with tetraplegia. None. Confirmatory factor analysis deriving fit indices on reported 1-, 2-, and 3-factor structures for the MSES. Exploratory factor analysis of MSES using principal component analysis with promax oblique rotation and structure validation, with correlations and multiple regression using cross-sectional data from the Sherer General Self-Efficacy Scale and Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). The MSES was confirmed to have a 3-factor structure, explaining 61% of variance. Two of the factors, labeled social function self-efficacy and personal function self-efficacy, were SCI condition-specific, whereas the other factor (accounting for 9.7% of variance) represented general self-efficacy, correlating most strongly with the Sherer General Self-Efficacy Scale. Correlations and multiple regression analyses between MSES factors, Sherer General Self-Efficacy Scale total score, SF-36 Physical and Mental Component Summary scores, and SF-36 domain scores support validity of this MSES factor structure. No significant cross-cultural differences existed between Australia and the United States in total MSES or factor scores. The findings support a 3-factor structure encompassing general and SCI domain-specific self-efficacy beliefs and better position the MSES to assist SCI rehabilitation assessment, planning, and research. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

[A competency model of rural general practitioners: theory construction and empirical study].

PubMed

Yang, Xiu-Mu; Qi, Yu-Long; Shne, Zheng-Fu; Han, Bu-Xin; Meng, Bei

2015-04-01

To perform theory construction and empirical study of the competency model of rural general practitioners. Through literature study, job analysis, interviews, and expert team discussion, the questionnaire of rural general practitioners competency was constructed. A total of 1458 rural general practitioners were surveyed by the questionnaire in 6 central provinces. The common factors were constructed using the principal component method of exploratory factor analysis and confirmatory factor analysis. The influence of the competency characteristics on the working performance was analyzed using regression equation analysis. The Cronbach 's alpha coefficient of the questionnaire was 0.974. The model consisted of 9 dimensions and 59 items. The 9 competency dimensions included basic public health service ability, basic clinical skills, system analysis capability, information management capability, communication and cooperation ability, occupational moral ability, non-medical professional knowledge, personal traits and psychological adaptability. The rate of explained cumulative total variance was 76.855%. The model fitting index were Χ(2)/df 1.88, GFI=0.94, NFI=0.96, NNFI=0.98, PNFI=0.91, RMSEA=0.068, CFI=0.97, IFI=0.97, RFI=0.96, suggesting good model fitting. Regression analysis showed that the competency characteristics had a significant effect on job performance. The rural general practitioners competency model provides reference for rural doctor training, rural order directional cultivation of medical students, and competency performance management of the rural general practitioners.

Sexual possibility situations and sexual behaviors among young adolescents: the moderating role of protective factors.

PubMed

DiLorio, Colleen; Dudley, William N; Soet, Johanna E; McCarty, Frances

2004-12-01

To examine sexual possibility situations (SPS) and protective practices associated with involvement in intimate sexual behaviors and the initiation of sexual intercourse among young adolescents and to determine if protective factors moderate the relationship between SPS and sexual behaviors. Data for these analyses were obtained from the baseline assessment for adolescents conducted as part of an HIV prevention study called "Keepin' it R.E.A.L.!" The study was conducted with a community-based organization (CBO) in an urban area serving a predominantly African-American population. In addition to items assessing SPS, intimate sexual behaviors, and initiation of sexual intercourse, adolescents provided information on the following protective factors: educational goals, self-concept, future time perspective, orientation to health, self-efficacy, outcome expectations, parenting, communication, values, and prosocial activities. Background personal information, including age and gender, was also collected. The analyses were conducted on data from 491 predominantly African-American adolescents, 61% of whom were boys. Variables were combined to form SPS and protective indices that were used in the first set of regression analyses. In a second set of analyses, the indices were unbundled and individual variables were entered into regression analyses. Both SPS and protective indices explained significant portions of variance in intimate sexual behaviors, and the SPS index explained a significant portion of variance in the initiation of sexual intercourse. The regression analysis using the unbundled SPS and protective factors revealed the following statistically significant predictors for intimate sexual behaviors: age, gender, time alone with groups of peers, time alone with a member of the opposite sex, behavior self-concept, popularity self-concept, self-efficacy for abstinence, outcome expectations for abstinence, parental control, personal values, and parental values. A similar regression analysis revealed that age, time alone with a member of the opposite sex, and personal values were significant predictors of initiation of sexual intercourse. These results provide evidence for the important role of protective factors in explaining early involvement in sexual behaviors and show that protective factors extend beyond personal characteristics to include both familial and peer factors.

The association between meteorological factors and road traffic injuries: a case analysis from Shantou city, China

PubMed Central

Gao, Jinghong; Chen, Xiaojun; Woodward, Alistair; Liu, Xiaobo; Wu, Haixia; Lu, Yaogui; Li, Liping; Liu, Qiyong

2016-01-01

Few studies examined the associations of meteorological factors with road traffic injuries (RTIs). The purpose of the present study was to quantify the contributions of meteorological factors to RTI cases treated at a tertiary level hospital in Shantou city, China. A time-series diagram was employed to illustrate the time trends and seasonal variation of RTIs, and correlation analysis and multiple linear regression analysis were conducted to investigate the relationships between meteorological parameters and RTIs. RTIs followed a seasonal pattern as more cases occurred during summer and winter months. RTIs are positively correlated with temperature and sunshine duration, while negatively associated with wind speed. Temperature, sunshine hour and wind speed were included in the final linear model with regression coefficients of 0.65 (t = 2.36, P = 0.019), 2.23 (t = 2.72, P = 0.007) and −27.66 (t = −5.67, P < 0.001), respectively, accounting for 19.93% of the total variation of RTI cases. The findings can help us better understand the associations between meteorological factors and RTIs, and with potential contributions to the development and implementation of regional level evidence-based weather-responsive traffic management system in the future. PMID:27853316

Factors affecting the HIV/AIDS epidemic: an ecological analysis of global data.

PubMed

Mondal, M N I; Shitan, M

2013-06-01

All over the world the prevalence of Human Immunodeficiency Virus (HIV)/Acquired Immune Deficiency Syndrome (AIDS) has became a stumbling stone in progress of human civilization and is a huge concern for people worldwide. To determine the social and health factors which contribute to increase the size of HIV epidemic globally. The country level indicators of HIV prevalence rates, are contraceptive prevalence rate, physicians density, proportion of Muslim populations, adolescent fertility rate, and mean year of schooling were compiled of 187 countries from the United Nations (UN) agencies. To extract the major factors from those indicators of the later five categories, backward multiple regression analysis was used as the statistical tool. The national HIV prevalence rate was significantly correlated with almost all the predictors. Backward multiple linear regression analysis identified the proportion of Muslims, physicians density, and adolescent fertility rate are as the three most prominent factors linked with the national HIV epidemic. The findings support the hypotheses that a higher adolescent fertility rate in the population is the adverse effect of premarital and extramarital sex that leads to longer period of sexual activity which increases the risk of HIV infection. On the hand, and cultural restrictions of Muslims and sufficient physicians will decelerate the spread of HIV infections in the society.

Quantitative analysis of titanium-induced artifacts and correlated factors during micro-CT scanning.

PubMed

Li, Jun Yuan; Pow, Edmond Ho Nang; Zheng, Li Wu; Ma, Li; Kwong, Dora Lai Wan; Cheung, Lim Kwong

2014-04-01

To investigate the impact of cover screw, resin embedment, and implant angulation on artifact of microcomputed tomography (micro-CT) scanning for implant. A total of twelve implants were randomly divided into 4 groups: (i) implant only; (ii) implant with cover screw; (iii) implant with resin embedment; and (iv) implants with cover screw and resin embedment. Implants angulation at 0°, 45°, and 90° were scanned by micro-CT. Images were assessed, and the ratio of artifact volume to total volume (AV/TV) was calculated. A multiple regression analysis in stepwise model was used to determine the significance of different factors. One-way ANOVA was performed to identify which combination of factors could minimize the artifact. In the regression analysis, implant angulation was identified as the best predictor for artifact among the factors (P < 0.001). Resin embedment also had significant effect on artifact volume (P = 0.028), while cover screw had not (P > 0.05). Non-embedded implants with the axis parallel to X-ray source of micro-CT produced minimal artifact. Implant angulation and resin embedment affected the artifact volume of micro-CT scanning for implant, while cover screw did not. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

High Prevalence of Leptotrichia amnionii, Atopobium vaginae, Sneathia sanguinegens, and Factor 1 Microbes and Association of Spontaneous Abortion among Korean Women.

PubMed

Seo, Sang Soo; Arokiyaraj, Selvaraj; Kim, Mi Kyung; Oh, Hea Young; Kwon, Minji; Kong, Ji Sook; Shin, Moon Kyung; Yu, Ye Lee; Lee, Jae Kwan

2017-01-01

Objective. The purpose of this study was to (i) determine the cervical microbial composition in different abortion samples and to (ii) investigate the correlation between spontaneous abortion and cervical microbes in Korean women. Methods. We collected cervical swabs from women who had never undergone abortion ( N = 36), had spontaneous abortion ( N = 23), and had undergone induced abortion ( N = 88) and subjected those samples to 16S rRNA pyrosequencing. Further, factor analysis and correlation between cervical microbiota and spontaneous abortion were evaluated by logistic regression analysis. Results. In spontaneous abortion women, 16 S rRNA gene sequences showed significant increases in Atopobium vaginae , Megasphaera spp., Gardnerella vaginalis , Leptotrichia amnionii , and Sneathia sanguinegens compared to women in nonabortion group. In multivariate logistic regression analysis, A. vaginae (OD = 11.27; 95% = 1.57-81) , L. amnionii (OD = 11.47; 95% = 1.22-107.94), S. sanguinegens (OD = 6.89; 95% = 1.07-44.33), and factor 1 microbes (OD = 16.4; 95% = 1.88-42.5) were strongly associated with spontaneous abortion. Conclusions. This study showed a high prevalence of L. amnionii, A. vaginae, S. sanguinegens , and factor 1 microbes in spontaneous abortion and association with spontaneous abortion in Korean women.

High Prevalence of Leptotrichia amnionii, Atopobium vaginae, Sneathia sanguinegens, and Factor 1 Microbes and Association of Spontaneous Abortion among Korean Women

PubMed Central

Seo, Sang Soo; Arokiyaraj, Selvaraj; Oh, Hea Young; Kwon, Minji; Kong, Ji Sook; Shin, Moon Kyung; Yu, Ye Lee; Lee, Jae Kwan

2017-01-01

Objective. The purpose of this study was to (i) determine the cervical microbial composition in different abortion samples and to (ii) investigate the correlation between spontaneous abortion and cervical microbes in Korean women. Methods. We collected cervical swabs from women who had never undergone abortion (N = 36), had spontaneous abortion (N = 23), and had undergone induced abortion (N = 88) and subjected those samples to 16S rRNA pyrosequencing. Further, factor analysis and correlation between cervical microbiota and spontaneous abortion were evaluated by logistic regression analysis. Results. In spontaneous abortion women, 16 S rRNA gene sequences showed significant increases in Atopobium vaginae, Megasphaera spp., Gardnerella vaginalis, Leptotrichia amnionii, and Sneathia sanguinegens compared to women in nonabortion group. In multivariate logistic regression analysis, A. vaginae (OD = 11.27; 95% = 1.57–81), L. amnionii (OD = 11.47; 95% = 1.22–107.94), S. sanguinegens (OD = 6.89; 95% = 1.07–44.33), and factor 1 microbes (OD = 16.4; 95% = 1.88–42.5) were strongly associated with spontaneous abortion. Conclusions. This study showed a high prevalence of L. amnionii, A. vaginae, S. sanguinegens, and factor 1 microbes in spontaneous abortion and association with spontaneous abortion in Korean women. PMID:29479540

Development of brief versions of the Wechsler Intelligence Scale for schizophrenia: considerations of the structure and predictability of intelligence.

PubMed

Sumiyoshi, Chika; Uetsuki, Miki; Suga, Motomu; Kasai, Kiyoto; Sumiyoshi, Tomiki

2013-12-30

Short forms (SF) of the Wechsler Intelligence Scale have been developed to enhance its practicality. However, only a few studies have addressed the Wechsler Intelligence Scale Revised (WAIS-R) SFs based on data from patients with schizophrenia. The current study was conducted to develop the WAIS-R SFs for these patients based on the intelligence structure and predictability of the Full IQ (FIQ). Relations to demographic and clinical variables were also examined on selecting plausible subtests. The WAIS-R was administered to 90 Japanese patients with schizophrenia. Exploratory factor analysis (EFA) and multiple regression analysis were conducted to find potential subtests. EFA extracted two dominant factors corresponding to Verbal IQ and Performance IQ measures. Subtests with higher factor loadings on those factors were initially nominated. Regression analysis was carried out to reach the model containing all the nominated subtests. The optimality of the potential subtests included in that model was evaluated from the perspectives of the representativeness of intelligence structure, FIQ predictability, and the relation with demographic and clinical variables. Taken together, the dyad of Vocabulary and Block Design was considered to be the most optimal WAIS-R SF for patients with schizophrenia, reflecting both intelligence structure and FIQ predictability. © 2013 Elsevier Ireland Ltd. All rights reserved.

Job demands and job strain as risk factors for employee wellbeing in elderly care: an instrumental-variables analysis.

PubMed

Elovainio, Marko; Heponiemi, Tarja; Kuusio, Hannamaria; Jokela, Markus; Aalto, Anna-Mari; Pekkarinen, Laura; Noro, Anja; Finne-Soveri, Harriet; Kivimäki, Mika; Sinervo, Timo

2015-02-01

The association between psychosocial work environment and employee wellbeing has repeatedly been shown. However, as environmental evaluations have typically been self-reported, the observed associations may be attributable to reporting bias. Applying instrumental-variable regression, we used staffing level (the ratio of staff to residents) as an unconfounded instrument for self-reported job demands and job strain to predict various indicators of wellbeing (perceived stress, psychological distress and sleeping problems) among 1525 registered nurses, practical nurses and nursing assistants working in elderly care wards. In ordinary regression, higher self-reported job demands and job strain were associated with increased risk of perceived stress, psychological distress and sleeping problems. The effect estimates for the associations of these psychosocial factors with perceived stress and psychological distress were greater, but less precisely estimated, in an instrumental-variables analysis which took into account only the variation in self-reported job demands and job strain that was explained by staffing level. No association between psychosocial factors and sleeping problems was observed with the instrumental-variable analysis. These results support a causal interpretation of high self-reported job demands and job strain being risk factors for employee wellbeing. © The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Trust, confidence, procedural fairness, outcome fairness, moral conviction, and the acceptance of GM field experiments.

PubMed

Siegrist, Michael; Connor, Melanie; Keller, Carmen

2012-08-01

In 2005, Swiss citizens endorsed a moratorium on gene technology, resulting in the prohibition of the commercial cultivation of genetically modified crops and the growth of genetically modified animals until 2013. However, scientific research was not affected by this moratorium, and in 2008, GMO field experiments were conducted that allowed us to examine the factors that influence their acceptance by the public. In this study, trust and confidence items were analyzed using principal component analysis. The analysis revealed the following three factors: "economy/health and environment" (value similarity based trust), "trust and honesty of industry and scientists" (value similarity based trust), and "competence" (confidence). The results of a regression analysis showed that all the three factors significantly influenced the acceptance of GM field experiments. Furthermore, risk communication scholars have suggested that fairness also plays an important role in the acceptance of environmental hazards. We, therefore, included measures for outcome fairness and procedural fairness in our model. However, the impact of fairness may be moderated by moral conviction. That is, fairness may be significant for people for whom GMO is not an important issue, but not for people for whom GMO is an important issue. The regression analysis showed that, in addition to the trust and confidence factors, moral conviction, outcome fairness, and procedural fairness were significant predictors. The results suggest that the influence of procedural fairness is even stronger for persons having high moral convictions compared with persons having low moral convictions. © 2012 Society for Risk Analysis.

Association of nitrogen compounds in drinking water with incidence of esophageal squamous cell carcinoma in Shexian, China.

PubMed

Zhang, Nan; Yu, Cao; Wen, Denggui; Chen, Jun; Ling, Yiwei; Terajima, Kenshi; Akazawa, Kohei; Shan, Baoen; Wang, Shijie

2012-01-01

The incidence of esophageal squamous cell carcinoma (ESCC), which is the eighth most common malignancy worldwide, is highest in China. The purpose of this study was to investigate the association between nitrogen compounds in drinking water with the incidence of ESCC by geographical spatial analysis. The incidence of ESCC is high in Shexian county, China, and environmental factors, particularly nitrogen-contaminated drinking water, are the main suspected risk factors. This study focuses on three nitrogen compounds in drinking water, namely, nitrates, nitrites, and ammonia, all of which are derived mainly from domestic garbage and agricultural fertilizer. The study surveyed 48 villages in the Shexian area with a total population of 54,716 (661 adults with ESCC and 54,055 non-cancer subjects). Hot-spot analysis was used to identify spatial clusters with a high incidence of ESCC and a high concentration of nitrogen compounds. Logistic regression analysis was used to detect risk factors for ESCC incidence. Most areas with high concentrations of nitrate nitrogen in drinking water had a high incidence of ESCC. Correlation analysis revealed a significant positive relationship between nitrate concentration and ESCC (P = 0.01). Logistic regression analysis also confirmed that nitrate nitrogen has a significantly higher odds ratio. The results indicate that nitrate nitrogen is associated with ESCC incidence in Shexian county. In conclusion, high concentrations of nitrate nitrogen in drinking water may be a significant risk factor for the incidence of ESCC.

Prevalence of abortion and stillbirth in a beef cattle system in Southeastern Mexico.

PubMed

Segura-Correa, José C; Segura-Correa, Victor M

2009-12-01

Prenatal mortality is an important cause of production losses in the livestock industry. This study estimates the prevalences of abortion and stillbirth in a beef cattle system and determines the significance of some risk factors, in the tropics of Mexico. Data were obtained from a Zebu cattle herd and their crosses with Bos taurus breeds, in Yucatan, Mexico. The logit of the probability of an abortion or stillbirth was modeled using binary logistic regression. The risk factors tested were: year of abortion (or calving), season of abortion (or calving), parity number and dam breed group. The effect of twins on stillbirth was tested using Fisher exact test. Of the 4175 calvings studied 49 were abortions (1.17%). Significant factors in the logistic regression analysis for abortions were season of abortion and parity number. The risk of abortion was lower in the dry seasons compared to the rainy and windy seasons (P = 0.009). The risk of abortion was higher in second parity cows followed by the third and first parity cows, as compared to older cows (P = 0.015). Of the 4126 births, 87 were stillbirths (2.11%). Significant factors in the logistic regression analysis for stillbirth were year of calving (P = 0.0001) and parity number (P < 0.001). The risk of stillbirth in first parity cows was 2.6 times that of old cows. Of the total births, 15 were twins (0.36%) of which 7 were born dead calves. Herd owners must focus on the significant risk factors under their control to reduce the prevalence of prenatal mortality.

Logistic regression analysis of the risk factors of anastomotic fistula after radical resection of esophageal‐cardiac cancer

PubMed Central

Huang, Jinxi; Wang, Chenghu; Yuan, Weiwei; Zhang, Zhandong; Chen, Beibei; Zhang, Xiefu

2017-01-01

Background This study was conducted to investigate the risk factors of anastomotic fistula after the radical resection of esophageal‐cardiac cancer. Methods Five hundred and forty‐four esophageal‐cardiac cancer patients who underwent surgery and had complete clinical data were included in the study. Fifty patients diagnosed with postoperative anastomotic fistula were considered the case group and the remaining 494 subjects who did not develop postoperative anastomotic fistula were considered the control. The potential risk factors for anastomotic fistula, such as age, gender, diabetes history, smoking history, were collected and compared between the groups. Statistically significant variables were substituted into logistic regression to further evaluate the independent risk factors for postoperative anastomotic fistulas in esophageal‐cardiac cancer. Results The incidence of anastomotic fistulas was 9.2% (50/544). Logistic regression analysis revealed that female gender (P < 0.05), laparoscopic surgery (P < 0.05), decreased postoperative albumin (P < 0.05), and postoperative renal dysfunction (P < 0.05) were independent risk factors for anastomotic fistulas in patients who received surgery for esophageal‐cardiac cancer. Of the 50 anastomotic fistulas, 16 cases were small fistulas, which were only discovered by conventional imaging examination and not presenting clinical symptoms. All of the anastomotic fistulas occurred within seven days after surgery. Five of the patients with anastomotic fistulas underwent a second surgery and three died. Conclusion Female patients with esophageal‐cardiac cancer treated with endoscopic surgery and suffering from postoperative hypoproteinemia and renal dysfunction were susceptible to postoperative anastomotic fistula. PMID:28940985

Factors influencing the postoperative use of analgesics in dogs and cats by Canadian veterinarians.

PubMed

Dohoo, S E; Dohoo, I R

1996-09-01

Four hundred and seventeen Canadian veterinarians were surveyed to determine their postoperative use of analgesics in dogs and cats following 6 categories of surgeries, and their opinion toward pain perception and perceived complications associated with the postoperative use of potent opioid analgesics. Three hundred and seventeen (76%) returned the questionnaire. An analgesic user was defined as a veterinarian who administers analgesics to at least 50% of dogs or 50% of cats following abdominal surgery, excluding ovariohysterectomy. The veterinarians responding exhibited a bimodal distribution of analgesic use, with 49.5% being defined as analgesic users. These veterinarians tended to use analgesics in 100% of animals following abdominal surgery. Veterinarians defined as analgesic nonusers rarely used postoperative analgesics following any abdominal surgery. Pain perception was defined as the average of pain rankings (on a scale of 1 to 10) following abdominal surgery, or the value for dogs or cats if the veterinarian worked with only 1 of the 2 species. Maximum concern about the risks associated with the postoperative use of potent opioid agonists was defined as the highest ranking assigned to any of the 7 risks evaluated in either dogs or cats. Logistic regression analysis identified the pain perception score and the maximum concern regarding the use of potent opioid agonists in the postoperative period as the 2 factors that distinguished analgesic users from analgesic nonusers. This model correctly classified 68% of veterinarians as analgesic users or nonusers. Linear regression analysis identified gender and the presence of an animal health technologist in the practice as the 2 factors that influenced pain perception by veterinarians. Linear regression analysis identified working with an animal health technologist, graduation within the past 10 years, and attendance at continuing education as factors that influenced maximum concern about the postoperative use of opioid agonists.

Evaluation of spectral domain optical coherence tomography parameters in ocular hypertension, preperimetric, and early glaucoma

PubMed Central

Aydoğan, Tuğba; Akçay, Betül İlkay Sezgin; Kardeş, Esra; Ergin, Ahmet

2017-01-01

Purpose: The objective of this study is to evaluate the diagnostic ability of retinal nerve fiber layer (RNFL), macular, optic nerve head (ONH) parameters in healthy subjects, ocular hypertension (OHT), preperimetric glaucoma (PPG), and early glaucoma (EG) patients, to reveal factors affecting the diagnostic ability of spectral domain-optical coherence tomography (SD-OCT) parameters and risk factors for glaucoma. Methods: Three hundred and twenty-six eyes (89 healthy, 77 OHT, 94 PPG, and 66 EG eyes) were analyzed. RNFL, macular, and ONH parameters were measured with SD-OCT. The area under the receiver operating characteristic curve (AUC) and sensitivity at 95% specificity was calculated. Logistic regression analysis was used to determine the glaucoma risk factors. Receiver operating characteristic regression analysis was used to evaluate the influence of covariates on the diagnostic ability of parameters. Results: In PPG patients, parameters that had the largest AUC value were average RNFL thickness (0.83) and rim volume (0.83). In EG patients, parameter that had the largest AUC value was average RNFL thickness (0.98). The logistic regression analysis showed average RNFL thickness was a risk factor for both PPG and EG. Diagnostic ability of average RNFL and average ganglion cell complex thickness increased as disease severity increased. Signal strength index did not affect diagnostic abilities. Diagnostic ability of average RNFL and rim area increased as disc area increased. Conclusion: When evaluating patients with glaucoma, patients at risk for glaucoma, and healthy controls RNFL parameters deserve more attention in clinical practice. Further studies are needed to fully understand the influence of covariates on the diagnostic ability of OCT parameters. PMID:29133640

Urinary Incontinence of Women in a Nationwide Study in Sri Lanka: Prevalence and Risk Factors.

PubMed

Pathiraja, Ramya; Prathapan, Shamini; Goonawardena, Sampatha

2017-05-23

Urinary incontinence, be stress incontinence or urge incontinence or a mixed type incontinence affects women of all ages. The aim of this study was to describe the prevalence and risk factors of urinary incontinence in Sri Lanka. A community based cross-sectional study was performed in Sri Lanka. The age group of the women in Sri Lanka was categorized into 3 age groups: Less than or equal to 35 years, 36 to 50 years of age and more than or equal to 51 years of age. A sample size of 675 women was obtained from each age category obtaining a total sample of 2025 from Sri Lanka. An interviewer-administered questionnaire consisting of two parts; Socio demographic factors, Medical and Obstetric History, and the King's Health Questionnaire (KHQ), was used for data collection. Stepwise logistic regression analysis was performed. The Prevalence of women with only stress incontinence was 10%, with urge incontinence was 15.6% and with stress and urge incontinence was 29.9%. Stepwise logistic regression analysis showed that the age groups of 36 - 50 years (OR = 2.03; 95% CI = 1.56 - 2.63) and 51 years and above (OR = 2.61; 95% CI= 1.95 - 3.48), Living in one of the districts in Sri Lanka (OR = 4.58; 95% CI = 3.35 - 6.27) and having given birth to multiple children (OR = 1.1; 95% CI = 1.02 - 1.21), diabetes mellitus (OR = 1.97; 95% CI = 1.19 - 3.23), and respiratory diseases (OR = 2.17; 95% CI = 1.48 - 3.19 ) showed a significant risk in the regression analysis. The risk factor, mostly modifiable, if prevented early, could help to reduce the symptoms of urinary incontinence.

Low thrombospondin 2 expression is predictive of low tumor regression after neoadjuvant chemoradiotherapy in rectal cancer.

PubMed

Lin, Cheng-Yi; Lin, Ching-Yih; Chang, I-Wei; Sheu, Ming-Jen; Li, Chien-Feng; Lee, Sung-Wei; Lin, Li-Ching; Lee, Ying-En; He, Hong-Lin

2015-01-01

Neoadjuvant concurrent chemoradiotherapy (CCRT) followed by surgery is the mainstay of treatment for locally advanced rectal cancer. Several heparin-binding associated proteins have been reported to play a critical role in cancer progression. However, the clinical relevancies of such proteins and their associations with CCRT response in rectal cancer have not yet to be fully elucidated. The analysis of a public transcriptome of rectal cancer indicated that thrombospondin 2 (THBS2) is a predictive factor for CCRT response. Immunohistochemical analyses were conducted to evaluate the expression of THBS2 in pretreatment biopsy specimens from rectal cancer patients without distant metastasis. Furthermore, the relationships between THBS2 expression and various clinicopathological factors or survival were analyzed. Low expression of THBS2 was significantly associated with advanced pretreatment tumor (P<0.001) and nodal status (P=0.004), post-treatment tumor (P<0.001) and nodal status (P<0.001), increased vascular invasion (P=0.003), increased perineural invasion (P=0.023) and inferior tumor regression grade (P=0.015). In univariate analysis, low THBS2 expression predicted worse outcomes for disease-free survival, local recurrence-free survival and metastasis-free survival (all P<0.001). In multivariate analysis, low expression of THBS2 still served as a negative prognostic factor for disease-free survival (Hazard ratio=3.057, P=0.002) and metastasis-free survival (Hazard ratio=3.362, P=0.012). Low THBS2 expression was correlated with advanced disease status and low tumor regression after preoperative CCRT and that it acted as an independent negative prognostic factor in rectal cancer. THBS2 may represent a predictive biomarker for CCRT response in rectal cancer.

Using decision tree analysis to identify risk factors for relapse to smoking

PubMed Central

Piper, Megan E.; Loh, Wei-Yin; Smith, Stevens S.; Japuntich, Sandra J.; Baker, Timothy B.

2010-01-01

This research used classification tree analysis and logistic regression models to identify risk factors related to short- and long-term abstinence. Baseline and cessation outcome data from two smoking cessation trials, conducted from 2001 to 2002, in two Midwestern urban areas, were analyzed. There were 928 participants (53.1% women, 81.8% white) with complete data. Both analyses suggest that relapse risk is produced by interactions of risk factors and that early and late cessation outcomes reflect different vulnerability factors. The results illustrate the dynamic nature of relapse risk and suggest the importance of efficient modeling of interactions in relapse prediction. PMID:20397871

Railroad Classification Yard Technology Manual. Volume III. Freight Car Rollability

DOT National Transportation Integrated Search

1981-07-01

The report presents a survey of rolling resistance research, histograms of rolling resistance from five yards, a statistical regression analysis of causal factors affecting rolling resistance, procedures for constructing a rolling resistance histogra...

Suspicion of respiratory tract infection with multidrug-resistant Enterobacteriaceae: epidemiology and risk factors from a Paediatric Intensive Care Unit.

PubMed

Renk, Hanna; Stoll, Lenja; Neunhoeffer, Felix; Hölzl, Florian; Kumpf, Matthias; Hofbeck, Michael; Hartl, Dominik

2017-02-21

Multidrug-resistant (MDR) infections are a serious concern for children admitted to the Paediatric Intensive Care Unit (PICU). Tracheal colonization with MDR Enterobacteriaceae predisposes to respiratory infection, but underlying risk factors are poorly understood. This study aims to determine the incidence of children with suspected infection during mechanical ventilation and analyses risk factors for the finding of MDR Enterobacteriaceae in tracheal aspirates. A retrospective single-centre analysis of Enterobacteriaceae isolates from the lower respiratory tract of ventilated PICU patients from 2005 to 2014 was performed. Resistance status was determined and clinical records were reviewed for potential risk factors. A classification and regression tree (CRT) to predict risk factors for infection with MDR Enterobacteriaceae was employed. The model was validated by simple and multivariable logistic regression. One hundred sixty-seven Enterobacteriaceae isolates in 123 children were identified. The most frequent isolates were Enterobacter spp., Klebsiella spp. and E.coli. Among these, 116 (69%) isolates were susceptible and 51 (31%) were MDR. In the CRT analysis, antibiotic exposure for ≥ 7 days and presence of gastrointestinal comorbidity were the most relevant predictors for an MDR isolate. Antibiotic exposure for ≥ 7 days was confirmed as a significant risk factor for infection with MDR Enterobacteriaceae by a multivariable logistic regression model. This study shows that critically-ill children with tracheal Enterobacteriaceae infection are at risk of carrying MDR isolates. Prior use of antibiotics for ≥ 7 days significantly increased the risk of finding MDR organisms in ventilated PICU patients with suspected infection. Our results imply that early identification of patients at risk, rapid microbiological diagnostics and tailored antibiotic therapy are essential to improve management of critically ill children infected with Enterobacteriaceae.

Strengths use as a secret of happiness: Another dimension of visually impaired individuals' psychological state.

PubMed

Matsuguma, Shinichiro; Kawashima, Motoko; Negishi, Kazuno; Sano, Fumiya; Mimura, Masaru; Tsubota, Kazuo

2018-01-01

It is well recognized that visual impairments (VI) worsen individuals' mental condition. However, little is known about the positive aspects including subjective happiness, positive emotions, and strengths. Therefore, the purpose of this study was to investigate the positive aspects of persons with VI including their subjective happiness, positive emotions, and strengths use. Positive aspects of persons with VI were measured using the Subjective Happiness Scale (SHS), the Scale of Positive and Negative Experience-Balance (SPANE-B), and the Strengths Use Scale (SUS). A cross-sectional analysis was utilized to examine personal information in a Tokyo sample (N = 44). We used a simple regression analysis and found significant relationships between the SHS or SPANE-B and SUS; on the contrary, VI-related variables were not correlated with them. A multiple regression analysis confirmed that SUS was a significant factor associated with both the SHS and SPANE-B. Strengths use might be a possible protective factor from the negative effects of VI.

Binding affinity toward human prion protein of some anti-prion compounds - Assessment based on QSAR modeling, molecular docking and non-parametric ranking.

PubMed

Kovačević, Strahinja; Karadžić, Milica; Podunavac-Kuzmanović, Sanja; Jevrić, Lidija

2018-01-01

The present study is based on the quantitative structure-activity relationship (QSAR) analysis of binding affinity toward human prion protein (huPrP C ) of quinacrine, pyridine dicarbonitrile, diphenylthiazole and diphenyloxazole analogs applying different linear and non-linear chemometric regression techniques, including univariate linear regression, multiple linear regression, partial least squares regression and artificial neural networks. The QSAR analysis distinguished molecular lipophilicity as an important factor that contributes to the binding affinity. Principal component analysis was used in order to reveal similarities or dissimilarities among the studied compounds. The analysis of in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) parameters was conducted. The ranking of the studied analogs on the basis of their ADMET parameters was done applying the sum of ranking differences, as a relatively new chemometric method. The main aim of the study was to reveal the most important molecular features whose changes lead to the changes in the binding affinities of the studied compounds. Another point of view on the binding affinity of the most promising analogs was established by application of molecular docking analysis. The results of the molecular docking were proven to be in agreement with the experimental outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

Clinical multifactorial analysis of early postoperative seizures in elderly patients following meningioma resection

PubMed Central

ZHANG, BO; WANG, DAN; GUO, YUNBAO; YU, JINLU

2015-01-01

The aim of the present study was to identify the major factors correlated with early postoperative seizures in elderly patients who had undergone a meningioma resection, and subsequently, to develop a logistic regression equation for assessing the seizures risk. Fourteen factors possibly correlated with early postoperative seizures in a cohort of 209 elderly patients who had undergone meningioma resection, as analyzed by multifactorial stepwise logistic regression. Phenobarbital sodium (0.1 g, intramuscularly) was administered to all 209 patients 30 min prior to undergoing surgery. All the patients had no previous history of seizures. The correlation of the 14 clinical factors (gender, tumor site, dyskinesia, peritumoral brain edema (PTBE), tumor diameter, pre- and postoperative prophylaxes, surgery time, tumor adhesion, circumscription, blood supply, intraoperative transfusion, original site of the tumor and dysphasia) was assessed in association with the risk for post-operative seizures. Tumor diameter, postoperative prophylactic antiepileptic drug (PPAD) administration, PTBE and tumor site were entered as risk factors into a mathematical regression model. The odds ratio (OR) of the tumor diameter was >1, and PPAD administration showed an OR >1, relative to a non-prophylactic group. A logistic regression equation was obtained and the sensitivity, specificity and misdiagnosis rates were 91.4, 74.3 and 25.7%, respectively. Tumor diameter, PPAD administration, PTBE and tumor site were closely correlated with early postoperative seizures; PTBE and PPAD administration were risk and protective factors, respectively. PMID:26137257

Malaria treatment-seeking behaviour and related factors of Wa ethnic minority in Myanmar: a cross-sectional study

PubMed Central

2012-01-01

Background In Southeast Asia, data on malaria treatment-seeking behaviours and related affecting factors are rare. The population of the Wa ethnic in Myanmar has difficulty in accessing formal health care. To understand malaria treatment-seeking behaviour and household-affecting factors of the Wa people, a cross-sectional study carried out in Shan Special Region II, Myanmar. Methods The two methods, questionnaire-based household surveys to household heads and in-depth interviews to key informants, were carried out independently. The proportion of treatment-seeking patterns was calculated. Logistic regression was used to determine affecting factors of treatment-seeking. Qualitative data were analysed by using Text Analysis Markup System. Results Overall, 87.5% of the febrile population sought treatment, but only 32.0% did so within 24 hours. The proportion accessing the retail sector (79.6%) was statistically significant higher (P<0.0001) than accessing the public sector (10.6%). Multivariable logistic regression analysis identified family income, distances from a health facility, family decision and patient characteristics being independently associated with delayed malaria treatment. Conclusion Malaria treatment-seeking behaviour is not appropriate, and affecting factors include health service systems, social and cultural factors in Wa State of Myanmar. PMID:23237576

A case-control study evaluating relative risk factors for decompression sickness: a research report.

PubMed

Suzuki, Naoko; Yagishita, Kazuyosi; Togawa, Seiichiro; Okazaki, Fumihiro; Shibayama, Masaharu; Yamamoto, Kazuo; Mano, Yoshihiro

2014-01-01

Factors contributing to the pathogenesis of decompression sickness (DCS) in divers have been described in many studies. However, relative importance of these factors has not been reported. In this case-control study, we compared the diving profiles of divers experiencing DCS with those of a control group. The DCS group comprised 35 recreational scuba divers who were diagnosed by physicians as having DCS. The control group consisted of 324 apparently healthy recreational divers. All divers conducted their dives from 2009 to 2011. The questionnaire consisted of 33 items about an individual's diving profile, physical condition and activities before, during and just after the dive. To simplify dive parameters, the dive site was limited to Izu Osezaki. Odds ratios and multiple logistic regression were used for the analysis. Odds ratios revealed several items as dive and health factors associated with DCS. The major items were as follows: shortness of breath after heavy exercise during the dive (OR = 12.12), dehydration (OR = 10.63), and maximum dive depth > 30 msw (OR = 7.18). Results of logistic regression were similar to those by odds ratio analysis. We assessed the relative weights of the surveyed dive and health factors associated with DCS. Because results of several factors conflict with previous studies, future studies are needed.

Development of risk assessment tool for foundry workers.

PubMed

Mohan, G Madhan; Prasad, P S S; Mokkapati, Anil Kumar; Venkataraman, G

2008-01-01

Occupational ill-health and work-related disorders are predominant in manufacturing industries due to the inevitable presence of manual work even after several waves of industrial automation and technological advancements. Ergonomic risk factors and musculoskeletal disorders like low-back symptoms have been noted amongst foundry workers. The purpose of this study was to formulate and develop a Physical Effort Index to assess risk factor. The questionnaire tool applicable to foundry environment has been designed and validated. The data recorded through survey across the foundries has been subjected to regression analysis to correlate between proposed physical effort index and the standard Borg's Ratings of Perceived Exertion (RPE) scale. The physical efforts of sixty seven workers in various foundry shop floors were assessed subjectively. The 'Job factors' and 'Work environment' were the two major parameters considered in assessing the worker discomfort level at workplace. A relation between Borg's RPE scale and the above two parameters were arrived at, through regression analysis. The study demonstrates the prevalence of risk factors amongst foundry workers and the effectiveness of the proposed index in estimating the risk factor levels. RELEVANCE TO THE INDUSTRY: The proposed tool will assist foundry supervisors and managers to assess the risk factors and helps in better understanding of the workplace to avoid work-related disorders, ensuring better output.

Evaluation of Factors Determining the Results of Vocational Rehabilitation. Norwegian Monographs on Medical Science.

ERIC Educational Resources Information Center

Gogstad, Anders C.

Physical disability from disease or injury often results in a permanent state of social insufficiency, especially when the disability is reinforced by individual or environmental factors. In a study of almost 700 persons treated at a Norwegian rehabilitation center, regression analysis was used to compare those who benefited from the program with…

Predicting Job Decisions in Tomorrow's Workforce

ERIC Educational Resources Information Center

Martin, Cody; Anderson, Lance; Cronin, Brian; Heinen, Beth; Swetharanyan, Sukanya

2010-01-01

The Job Decision Factors Survey used policy capturing to measure the influence of 7 factors on job decisions. Data from 400 undergraduate students at a large university, 88% 18-25 years of age, 12% 25-65 years of age, 82% female, 54% White, 21% Asian, 10% Black, 10% Hispanic, 1% American Indian, were included in a regression analysis. Hypothesis…

Determining the Factors of Social Phobia Levels of University Students: A Logistic Regression Analysis

ERIC Educational Resources Information Center

Ozen, Hamit

2016-01-01

Experiencing social phobia is an important factor which can hinder academic success during university years. In this study, research of social phobia with several variables is conducted among university students. The research group of the study consists of total 736 students studying at various departments at universities in Turkey. Students are…

Accounting for Slipping and Other False Negatives in Logistic Models of Student Learning

ERIC Educational Resources Information Center

MacLellan, Christopher J.; Liu, Ran; Koedinger, Kenneth R.

2015-01-01

Additive Factors Model (AFM) and Performance Factors Analysis (PFA) are two popular models of student learning that employ logistic regression to estimate parameters and predict performance. This is in contrast to Bayesian Knowledge Tracing (BKT) which uses a Hidden Markov Model formalism. While all three models tend to make similar predictions,…

Income, Language, and Citizenship Status: Factors Affecting the Health Care Access and Utilization of Chinese Americans.

ERIC Educational Resources Information Center

Jang, Michael; Lee, Evelyn; Woo, Kent

1998-01-01

The effects of income, language, and citizenship on the use of health-care services by Chinese Americans is examined (N=1808). Focus groups, a telephone survey, and key informant interviews were conducted. Data analysis included an acculturation index, demographic profile, and logistical regression. Health insurance and social factors are…

Evaluation of the association of polymorphisms in EYA1, environmental factors, and non-syndromic orofacial clefts in Western Han Chinese.

PubMed

Zeng, Ni; Wu, Jun; Zhu, Wen-Chao; Shi, Bing; Jia, Zhong-Lin

2015-11-01

Non-syndromic orofacial clefts (NSOCs) are complex disease involving genetic triggers, environmental factors, and their interplay. Recent studies demonstrated that EYA1, a member of eye absent gene family, might contribute to NSOCs. We investigated three single nucleotide polymorphisms (SNPs) and eight environmental factors (multivitamin, folic acid and calcium supplementation history, maternal alcohol consumption, common cold history, maternal smoking and environmental tobacco smoke in the first trimester, and paternal smoking in the 3 months before pregnancy) among 294 case-parent trios and 183 individual controls in western Han Chinese to evaluate the relationship between EYA1, environmental factors, and NSOCs. To be better known the gene's role in the etiology of NSOCs, we performed statistical analysis in different aspects including the linkage disequilibrium test, transmission disequilibrium test, haplotype analysis, multiple logistic regression analysis, and conditional logistic regression analysis. Allele C at rs3779748 showed an over-transmission in NSCL/P trios (P = 0.03), and genotype A/A at rs10094908 was under-transmitted among NSCL/P trios (P = 0.03), whereas over-transmitted among NSCPO trios (P = 0.02). The haplotype GC of rs10094908-rs3779748 was over-transmitted among NSCL/P trios (P = 0.05) and NSCPO trios (P = 0.05), respectively. Maternal common cold history, environmental tobacco smoke, and maternal alcohol consumption during the first trimester of pregnancy were risk factors for NSOCs, while calcium supplementation during the first trimester showed a protective effect. No evidence of interactions between EYA1 and environmental factors was found. These results revealed an association between EYA1, some environmental factors, and NSOCs in western Han Chinese. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Ileus in children presenting with diarrhea and severe acute malnutrition: A chart review

PubMed Central

Shahid, Abu SMSB; Shahunja, K. M.; Bardhan, Pradip Kumar; Faruque, Abu Syeed Golam; Shahrin, Lubaba; Das, Sumon Kumar; Barua, Dipesh Kumar; Hossain, Md Iqbal; Ahmed, Tahmeed

2017-01-01

Background Severely malnourished children aged under five years requiring hospital admission for diarrheal illness frequently develop ileus during hospitalization with often fatal outcomes. However, there is no data on risk factors and outcome of ileus in such children. We intended to evaluate predictive factors for ileus during hospitalization and their outcomes. Methodology/Principal findings This was a retrospective chart review that enrolled severely malnourished children under five years old with diarrhea, admitted to the Dhaka Hospital of the International Centre for Diarrhoeal Disease Research, Bangladesh between April 2011 and August 2012. We used electronic database to have our chart abstraction from previously admitted children in the hospital. The clinical and laboratory characteristics of children with (cases = 45), and without ileus (controls = 261) were compared. Cases were first identified by observation of abnormal bowel sounds on physical examination and confirmed with abdominal radiographs. For this comparison, Chi-square test was used to measure the difference in proportion, Student’s t-test to calculate the difference in mean for normally distributed data and Mann-Whitney test for data that were not normally distributed. Finally, in identifying independent risk factors for ileus, logistical regression analysis was performed. Ileus was defined if a child developed abdominal distension and had hyperactive or sluggish or absent bowel sound and a radiologic evidence of abdominal gas-fluid level during hospitalization. Logistic regression analysis adjusting for potential confounders revealed that the independent risk factors for admission for ileus were reluctance to feed (odds ratio [OR] = 3.22, 95% confidence interval [CI] = 1.24–8.39, p = 0.02), septic shock (OR = 3.62, 95% CI = 1.247–8.95, p<0.01), and hypokalemia (OR = 1.99, 95% CI = 1.03–3.86, p = 0.04). Mortality was significantly higher in cases compared to controls (22% vs. 8%, p<0.01) in univariate analysis; however, in multivariable regression analysis, after adjusting for potential confounders such as septic shock, no association was found between ileus and death (OR = 2.05, 95% CI = 0.68–6.14, p = 0.20). In a separate regression analysis model, after adjusting for potential confounders such as ileus, reluctance to feed, hypokalemia, hypocalcemia, and blood transfusion, septic shock (OR = 168.84, 95% CI = 19.27–1479.17, p<0.01) emerged as the only independent predictor of death in severely malnourished diarrheal children. Conclusions/Significance This study suggests that the identification of simple independent admission risk factors for ileus and risk factors for death in hospitalized severely malnourished diarrheal children may prompt clinicians to be more vigilant in managing these conditions, especially in resource-limited settings in order to decrease ileus and ileus-related fatal outcomes in such children. PMID:28493871

Ileus in children presenting with diarrhea and severe acute malnutrition: A chart review.

PubMed

Chisti, Mohammod Jobayer; Shahid, Abu Smsb; Shahunja, K M; Bardhan, Pradip Kumar; Faruque, Abu Syeed Golam; Shahrin, Lubaba; Das, Sumon Kumar; Barua, Dipesh Kumar; Hossain, Md Iqbal; Ahmed, Tahmeed

2017-05-01

Severely malnourished children aged under five years requiring hospital admission for diarrheal illness frequently develop ileus during hospitalization with often fatal outcomes. However, there is no data on risk factors and outcome of ileus in such children. We intended to evaluate predictive factors for ileus during hospitalization and their outcomes. This was a retrospective chart review that enrolled severely malnourished children under five years old with diarrhea, admitted to the Dhaka Hospital of the International Centre for Diarrhoeal Disease Research, Bangladesh between April 2011 and August 2012. We used electronic database to have our chart abstraction from previously admitted children in the hospital. The clinical and laboratory characteristics of children with (cases = 45), and without ileus (controls = 261) were compared. Cases were first identified by observation of abnormal bowel sounds on physical examination and confirmed with abdominal radiographs. For this comparison, Chi-square test was used to measure the difference in proportion, Student's t-test to calculate the difference in mean for normally distributed data and Mann-Whitney test for data that were not normally distributed. Finally, in identifying independent risk factors for ileus, logistical regression analysis was performed. Ileus was defined if a child developed abdominal distension and had hyperactive or sluggish or absent bowel sound and a radiologic evidence of abdominal gas-fluid level during hospitalization. Logistic regression analysis adjusting for potential confounders revealed that the independent risk factors for admission for ileus were reluctance to feed (odds ratio [OR] = 3.22, 95% confidence interval [CI] = 1.24-8.39, p = 0.02), septic shock (OR = 3.62, 95% CI = 1.247-8.95, p<0.01), and hypokalemia (OR = 1.99, 95% CI = 1.03-3.86, p = 0.04). Mortality was significantly higher in cases compared to controls (22% vs. 8%, p<0.01) in univariate analysis; however, in multivariable regression analysis, after adjusting for potential confounders such as septic shock, no association was found between ileus and death (OR = 2.05, 95% CI = 0.68-6.14, p = 0.20). In a separate regression analysis model, after adjusting for potential confounders such as ileus, reluctance to feed, hypokalemia, hypocalcemia, and blood transfusion, septic shock (OR = 168.84, 95% CI = 19.27-1479.17, p<0.01) emerged as the only independent predictor of death in severely malnourished diarrheal children. This study suggests that the identification of simple independent admission risk factors for ileus and risk factors for death in hospitalized severely malnourished diarrheal children may prompt clinicians to be more vigilant in managing these conditions, especially in resource-limited settings in order to decrease ileus and ileus-related fatal outcomes in such children.

Patient characteristics of smokers undergoing lumbar spine surgery: an analysis from the Quality Outcomes Database.

PubMed

Asher, Anthony L; Devin, Clinton J; McCutcheon, Brandon; Chotai, Silky; Archer, Kristin R; Nian, Hui; Harrell, Frank E; McGirt, Matthew; Mummaneni, Praveen V; Shaffrey, Christopher I; Foley, Kevin; Glassman, Steven D; Bydon, Mohamad

2017-12-01

OBJECTIVE In this analysis the authors compare the characteristics of smokers to nonsmokers using demographic, socioeconomic, and comorbidity variables. They also investigate which of these characteristics are most strongly associated with smoking status. Finally, the authors investigate whether the association between known patient risk factors and disability outcome is differentially modified by patient smoking status for those who have undergone surgery for lumbar degeneration. METHODS A total of 7547 patients undergoing degenerative lumbar surgery were entered into a prospective multicenter registry (Quality Outcomes Database [QOD]). A retrospective analysis of the prospectively collected data was conducted. Patients were dichotomized as smokers (current smokers) and nonsmokers. Multivariable logistic regression analysis fitted for patient smoking status and subsequent measurement of variable importance was performed to identify the strongest patient characteristics associated with smoking status. Multivariable linear regression models fitted for 12-month Oswestry Disability Index (ODI) scores in subsets of smokers and nonsmokers was performed to investigate whether differential effects of risk factors by smoking status might be present. RESULTS In total, 18% (n = 1365) of patients were smokers and 82% (n = 6182) were nonsmokers. In a multivariable logistic regression analysis, the factors significantly associated with patients' smoking status were sex (p < 0.0001), age (p < 0.0001), body mass index (p < 0.0001), educational status (p < 0.0001), insurance status (p < 0.001), and employment/occupation (p = 0.0024). Patients with diabetes had lowers odds of being a smoker (p = 0.0008), while patients with coronary artery disease had greater odds of being a smoker (p = 0.044). Patients' propensity for smoking was also significantly associated with higher American Society of Anesthesiologists (ASA) class (p < 0.0001), anterior-alone surgical approach (p = 0.018), greater number of levels (p = 0.0246), decompression only (p = 0.0001), and higher baseline ODI score (p < 0.0001). In a multivariable proportional odds logistic regression model, the adjusted odds ratio of risk factors and direction of improvement in 12-month ODI scores remained similar between the subsets of smokers and nonsmokers. CONCLUSIONS Using a large, national, multiinstitutional registry, the authors described the profile of patients who undergo lumbar spine surgery and its association with their smoking status. Compared with nonsmokers, smokers were younger, male, nondiabetic, nonobese patients presenting with leg pain more so than back pain, with higher ASA classes, higher disability, less education, more likely to be unemployed, and with Medicaid/uninsured insurance status. Smoking status did not affect the association between these risk factors and 12-month ODI outcome, suggesting that interventions for modifiable risk factors are equally efficacious between smokers and nonsmokers.

Rapid increase in Japanese life expectancy after World War II.

PubMed

Sugiura, Yasuo; Ju, Young-Su; Yasuoka, Junko; Jimba, Masamine

2010-02-01

Japanese life expectancy increased by about 13.7 years during the first decade after World War II, despite the country's post-war poverty. Although it is known that medical progress explains part of this increase, roles of non-medical factors have not been systematically studied. This study hypothesizes that non-medical factors, in addition to medical factors, are associated with the rapid increase in life expectancy in Japan. We analyzed the time trends of potential explanatory factors and used regression analysis with historical data from the Ministry of Internal Affairs and Communications' Historical Statistics of Japan during the period between 1946 and 1983. Time trends analysis revealed that the rapid increase in life expectancy preceded the dramatic growth of per capita Gross Domestic Product (GDP) by 10 years. In education, the nearly universal enrollment in elementary schools and increased advancement to upper secondary schools for both sexes were associated with better health. Regarding legislation, 32 health laws were passed in the first decade after the war and these laws were associated with improved health. Using regression analysis, we found that the enrollment rate in elementary schools, the number of health laws, and expansion of community-based activity staff were significantly associated with the increased life expectancy during the first decade after World War II. To conclude, in addition to medical factors, non-medical factors applied across the country, particularly education, community-based activities and legislation were associated with the rapid increase in Japanese life expectancy after World War II.

No rationale for 1 variable per 10 events criterion for binary logistic regression analysis.

PubMed

van Smeden, Maarten; de Groot, Joris A H; Moons, Karel G M; Collins, Gary S; Altman, Douglas G; Eijkemans, Marinus J C; Reitsma, Johannes B

2016-11-24

Ten events per variable (EPV) is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth's correction, are compared. The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect ('separation'). We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth's correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

Multiple regression analysis of anthropometric measurements influencing the cephalic index of male Japanese university students.

PubMed

Hossain, Md Golam; Saw, Aik; Alam, Rashidul; Ohtsuki, Fumio; Kamarul, Tunku

2013-09-01

Cephalic index (CI), the ratio of head breadth to head length, is widely used to categorise human populations. The aim of this study was to access the impact of anthropometric measurements on the CI of male Japanese university students. This study included 1,215 male university students from Tokyo and Kyoto, selected using convenient sampling. Multiple regression analysis was used to determine the effect of anthropometric measurements on CI. The variance inflation factor (VIF) showed no evidence of a multicollinearity problem among independent variables. The coefficients of the regression line demonstrated a significant positive relationship between CI and minimum frontal breadth (p < 0.01), bizygomatic breadth (p < 0.01) and head height (p < 0.05), and a negative relationship between CI and morphological facial height (p < 0.01) and head circumference (p < 0.01). Moreover, the coefficient and odds ratio of logistic regression analysis showed a greater likelihood for minimum frontal breadth (p < 0.01) and bizygomatic breadth (p < 0.01) to predict round-headedness, and morphological facial height (p < 0.05) and head circumference (p < 0.01) to predict long-headedness. Stepwise regression analysis revealed bizygomatic breadth, head circumference, minimum frontal breadth, head height and morphological facial height to be the best predictor craniofacial measurements with respect to CI. The results suggest that most of the variables considered in this study appear to influence the CI of adult male Japanese students.

Size, Stability and Incremental Budgeting Outcomes in Public Universities.

ERIC Educational Resources Information Center

Schick, Allen G.; Hills, Frederick S.

1982-01-01

Examined the influence of relative size in the analysis of total dollar and workforce budgets, and changes in total dollar and workforce budgets when correlational/regression methods are used. Data suggested that size dominates the analysis of total budgets, and is not a factor when discretionary dollar increments are analyzed. (JAC)

Job Satisfaction in Mexican Faculty: An Analysis of its Predictor Variables. ASHE Annual Meeting Paper.

ERIC Educational Resources Information Center

Galaz-Fontes, Jesus Francisco; Gil-Anton, Manuel

This study examined overall job satisfaction among college faculty in Mexico. The study used data from a 1992-93 Carnegie International Faculty Survey. Secondary multiple regression analysis identified predictor variables for several faculty subgroups. Results were interpreted by differentiating between work-related and intrinsic factors, as well…

A Growth Model for Academic Program Life Cycle (APLC): A Theoretical and Empirical Analysis

ERIC Educational Resources Information Center

Acquah, Edward H. K.

2010-01-01

Academic program life cycle concept states each program's life flows through several stages: introduction, growth, maturity, and decline. A mixed-influence diffusion growth model is fitted to enrolment data on academic programs to analyze the factors determining progress of academic programs through their life cycles. The regression analysis yield…

Youth tobacco sales in a metropolitan county: factors associated with compliance.

PubMed

Pearson, Dave C; Song, Lin; Valdez, Roger B; Angulo, Antoinette S

2007-08-01

To describe and identify factors associated with tobacco sales in a metropolitan county. King County, Washington is the largest county in Washington State with an estimated population of 1.8 million or about 30% of the state's population. The data analysis is based on compliance checks in King County between January 2001 and March 2005. The 8879 checks were conducted by 91 youth operatives aged 14-17. Analysis of data was completed in 2006. The outcome variable for this analysis was whether "a sale was made" to a youth operative during a compliance check. Associations between independent variables and the outcome variable were examined using 2 x 2 tables, univariate (unadjusted) logistic regression, and multivariate (adjusted) logistic regression analysis. Overall tobacco sales during the 4-year and 3-month period was 7.7%. Convenience stores selling gas were significantly more likely to sell tobacco products to minors, whereas restaurants, bars, and tobacco discount stores were less likely to sell to minors. Other factors that were significantly associated with sales are described. In a county that has adopted many of the required youth access laws, opportunities still exist to reduce sales of tobacco products to minors. Asking for age and photo identification still appears to be an effective strategy in reducing sales of tobacco products to minors.

Motivation and Self-Management Behavior of the Individuals With Chronic Low Back Pain.

PubMed

Jung, Mi Jung; Jeong, Younhee

2016-01-01

Self-management behavior is an important component for successful pain management in individuals with chronic low back pain. Motivation has been considered as an effective way to change behavior. Because there are other physical, social, and psychological factors affecting individuals with pain, it is necessary to identify the main effect of motivation on self-management behavior without the influence of those factors. The purpose of this study was to investigate the effect of motivation on self-management in controlling pain, depression, and social support. We used a nonexperimental, cross-sectional, descriptive design with mediation analysis and included 120 participants' data in the final analysis. We also used hierarchical multiple regression to test the effect of motivation, and multiple regression analysis and Sobel test were used to examine the mediating effect. Motivation itself accounted for 23.4% of the variance in self-management, F(1, 118) = 35.003, p < .001. After controlling covariates, motivation was also a significant factor for self-management. In the mediation analysis, motivation completely mediated the relationship between education and self-management, z = 2.292, p = .021. Motivation is an important part of self-management, and self-management education is not effective without motivation. The results of our study suggest that nurses incorporate motivation in nursing intervention, rather than only giving information.

Response of dissolved trace metals to land use/land cover and their source apportionment using a receptor model in a subtropic river, China.

PubMed

Li, Siyue; Zhang, Quanfa

2011-06-15

Water samples were collected for determination of dissolved trace metals in 56 sampling sites throughout the upper Han River, China. Multivariate statistical analyses including correlation analysis, stepwise multiple linear regression models, and principal component and factor analysis (PCA/FA) were employed to examine the land use influences on trace metals, and a receptor model of factor analysis-multiple linear regression (FA-MLR) was used for source identification/apportionment of anthropogenic heavy metals in the surface water of the River. Our results revealed that land use was an important factor in water metals in the snow melt flow period and land use in the riparian zone was not a better predictor of metals than land use away from the river. Urbanization in a watershed and vegetation along river networks could better explain metals, and agriculture, regardless of its relative location, however slightly explained metal variables in the upper Han River. FA-MLR analysis identified five source types of metals, and mining, fossil fuel combustion, and vehicle exhaust were the dominant pollutions in the surface waters. The results demonstrated great impacts of human activities on metal concentrations in the subtropical river of China. Copyright © 2011 Elsevier B.V. All rights reserved.

Global Prevalence of Elder Abuse: A Meta-analysis and Meta-regression.

PubMed

Ho, C Sh; Wong, S Y; Chiu, M M; Ho, R Cm

2017-06-01

Elder abuse is increasingly recognised as a global public health and social problem. There has been limited inter-study comparison of the prevalence and risk factors for elder abuse. This study aimed to estimate the pooled and subtype prevalence of elder abuse worldwide and identify significant associated risk factors. We conducted a meta-analysis and meta-regression of 34 population-based and 17 non-population-based studies. The pooled prevalences of elder abuse were 10.0% (95% confidence interval, 5.2%-18.6%) and 34.3% (95% confidence interval, 22.9%-47.8%) in population-based studies and third party- or caregiver-reported studies, respectively. Being in a marital relationship was found to be a significant moderator using random-effects model. This meta-analysis revealed that third parties or caregivers were more likely to report abuse than older abused adults. Subgroup analyses showed that females and those resident in non-western countries were more likely to be abused. Emotional abuse was the most prevalent elder abuse subtype and financial abuse was less commonly reported by third parties or caregivers. Heterogeneity in the prevalence was due to the high proportion of married older adults in the sample. Subgroup analysis showed that cultural factors, subtypes of abuse, and gender also contributed to heterogeneity in the pooled prevalence of elder abuse.

Factors predicting early postpartum glucose intolerance in Japanese women with gestational diabetes mellitus: decision-curve analysis.

PubMed

Kondo, M; Nagao, Y; Mahbub, M H; Tanabe, T; Tanizawa, Y

2018-04-29

To identify factors predicting early postpartum glucose intolerance in Japanese women with gestational diabetes mellitus, using decision-curve analysis. A retrospective cohort study was performed. The participants were 123 Japanese women with gestational diabetes who underwent 75-g oral glucose tolerance tests at 8-12 weeks after delivery. They were divided into a glucose intolerance and a normal glucose tolerance group based on postpartum oral glucose tolerance test results. Analysis of the pregnancy oral glucose tolerance test results showed predictive factors for postpartum glucose intolerance. We also evaluated the clinical usefulness of the prediction model based on decision-curve analysis. Of 123 women, 78 (63.4%) had normoglycaemia and 45 (36.6%) had glucose intolerance. Multivariable logistic regression analysis showed insulinogenic index/fasting immunoreactive insulin and summation of glucose levels, assessed during pregnancy oral glucose tolerance tests (total glucose), to be independent risk factors for postpartum glucose intolerance. Evaluating the regression models, the best discrimination (area under the curve 0.725) was obtained using the basic model (i.e. age, family history of diabetes, BMI ≥25 kg/m 2 and use of insulin during pregnancy) plus insulinogenic index/fasting immunoreactive insulin <1.1. Decision-curve analysis showed that combining insulinogenic index/fasting immunoreactive insulin <1.1 with basic clinical information resulted in superior net benefits for prediction of postpartum glucose intolerance. Insulinogenic index/fasting immunoreactive insulin calculated using oral glucose tolerance test results during pregnancy is potentially useful for predicting early postpartum glucose intolerance in Japanese women with gestational diabetes. © 2018 Diabetes UK.

Factors associated with discontinuation of aripiprazole treatment after switching from other antipsychotics in patients with chronic schizophrenia: A prospective observational study.

PubMed

Takaesu, Yoshikazu; Kishimoto, Taishiro; Murakoshi, Akiko; Takahashi, Nobutada; Inoue, Yuichi

2016-02-28

The purpose of the study was to identify factors associated with discontinuation of aripiprazole after switching from other antipsychotics in patients with schizophrenia in real world clinical settings. From January 2011 to December 2012, a prospective, 48-week open-label study was undertaken. Thirty-eight subjects on antipsychotic monotherapy were switched to aripiprazole. Patients who discontinued aripiprazole were compared to those who continued with regards to demographic characteristics as well as treatment factors. Multiple regression analysis was conducted to identify predictors for aripiprazole discontinuation. Thirteen out of 38 patients (34.2%) discontinued aripiprazole during the follow up period. Nine patients (23.7%) discontinued aripiprazole due to worsening of psychotic symptoms. Multiple logistic regression analysis revealed that only the duration of previous antipsychotic treatment was associated with aripiprazole discontinuation after switching to aripiprazole. The receiver operating curve (ROC) analysis identified that the cut-off length for duration of illness to predict aripiprazole discontinuation was 10.5 years. Longer duration of illness was associated with aripiprazole discontinuation. Greater caution may be required when treating such patients with aripiprazole. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Supply and demand analysis for flood insurance by using logistic regression model: case study at Citarum watershed in South Bandung, West Java, Indonesia

NASA Astrophysics Data System (ADS)

Sidi, P.; Mamat, M.; Sukono; Supian, S.

2017-01-01

Floods have always occurred in the Citarum river basin. The adverse effects caused by floods can cover all their property, including the destruction of houses. The impact due to damage to residential buildings is usually not small. Indeed, each of flooding, the government and several social organizations providing funds to repair the building. But the donations are given very limited, so it cannot cover the entire cost of repair was necessary. The presence of insurance products for property damage caused by the floods is considered very important. However, if its presence is also considered necessary by the public or not? In this paper, the factors that affect the supply and demand of insurance product for damaged building due to floods are analyzed. The method used in this analysis is the ordinal logistic regression. Based on the analysis that the factors that affect the supply and demand of insurance product for damaged building due to floods, it is included: age, economic circumstances, family situations, insurance motivations, and lifestyle. Simultaneously that the factors affecting supply and demand of insurance product for damaged building due to floods mounted to 65.7%.

Prognostic value of inflammation-based scores in patients with osteosarcoma

PubMed Central

Liu, Bangjian; Huang, Yujing; Sun, Yuanjue; Zhang, Jianjun; Yao, Yang; Shen, Zan; Xiang, Dongxi; He, Aina

2016-01-01

Systemic inflammation responses have been associated with cancer development and progression. C-reactive protein (CRP), Glasgow prognostic score (GPS), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), and neutrophil-platelet score (NPS) have been shown to be independent risk factors in various types of malignant tumors. This retrospective analysis of 162 osteosarcoma cases was performed to estimate their predictive value of survival in osteosarcoma. All statistical analyses were performed by SPSS statistical software. Receiver operating characteristic (ROC) analysis was generated to set optimal thresholds; area under the curve (AUC) was used to show the discriminatory abilities of inflammation-based scores; Kaplan-Meier analysis was performed to plot the survival curve; cox regression models were employed to determine the independent prognostic factors. The optimal cut-off points of NLR, PLR, and LMR were 2.57, 123.5 and 4.73, respectively. GPS and NLR had a markedly larger AUC than CRP, PLR and LMR. High levels of CRP, GPS, NLR, PLR, and low level of LMR were significantly associated with adverse prognosis (P < 0.05). Multivariate Cox regression analyses revealed that GPS, NLR, and occurrence of metastasis were top risk factors associated with death of osteosarcoma patients. PMID:28008988

Building and verifying a severity prediction model of acute pancreatitis (AP) based on BISAP, MEWS and routine test indexes.

PubMed

Ye, Jiang-Feng; Zhao, Yu-Xin; Ju, Jian; Wang, Wei

2017-10-01

To discuss the value of the Bedside Index for Severity in Acute Pancreatitis (BISAP), Modified Early Warning Score (MEWS), serum Ca2+, similarly hereinafter, and red cell distribution width (RDW) for predicting the severity grade of acute pancreatitis and to develop and verify a more accurate scoring system to predict the severity of AP. In 302 patients with AP, we calculated BISAP and MEWS scores and conducted regression analyses on the relationships of BISAP scoring, RDW, MEWS, and serum Ca2+ with the severity of AP using single-factor logistics. The variables with statistical significance in the single-factor logistic regression were used in a multi-factor logistic regression model; forward stepwise regression was used to screen variables and build a multi-factor prediction model. A receiver operating characteristic curve (ROC curve) was constructed, and the significance of multi- and single-factor prediction models in predicting the severity of AP using the area under the ROC curve (AUC) was evaluated. The internal validity of the model was verified through bootstrapping. Among 302 patients with AP, 209 had mild acute pancreatitis (MAP) and 93 had severe acute pancreatitis (SAP). According to single-factor logistic regression analysis, we found that BISAP, MEWS and serum Ca2+ are prediction indexes of the severity of AP (P-value<0.001), whereas RDW is not a prediction index of AP severity (P-value>0.05). The multi-factor logistic regression analysis showed that BISAP and serum Ca2+ are independent prediction indexes of AP severity (P-value<0.001), and MEWS is not an independent prediction index of AP severity (P-value>0.05); BISAP is negatively related to serum Ca2+ (r=-0.330, P-value<0.001). The constructed model is as follows: ln()=7.306+1.151*BISAP-4.516*serum Ca2+. The predictive ability of each model for SAP follows the order of the combined BISAP and serum Ca2+ prediction model>Ca2+>BISAP. There is no statistical significance for the predictive ability of BISAP and serum Ca2+ (P-value>0.05); however, there is remarkable statistical significance for the predictive ability using the newly built prediction model as well as BISAP and serum Ca2+ individually (P-value<0.01). Verification of the internal validity of the models by bootstrapping is favorable. BISAP and serum Ca2+ have high predictive value for the severity of AP. However, the model built by combining BISAP and serum Ca2+ is remarkably superior to those of BISAP and serum Ca2+ individually. Furthermore, this model is simple, practical and appropriate for clinical use. Copyright © 2016. Published by Elsevier Masson SAS.

Analysis of quality of life and influencing factors in 197 Chinese patients with port-wine stains

PubMed Central

Wang, Juan; Zhu, Yu-you; Wang, Zhong-ying; Yao, Xiu-hua; Zhang, Lan-fang; Lv, Hong; Zhang, Si-ping; Hu, Bai

2017-01-01

Abstract Port-wine stains (PWS) are congenital capillary malformations, usually occurring on the face, neck, and other exposed parts of the skin, that have serious psychological and social impact on the patient. Most researchers focus on the treatment of PWS, but the quality of life (QoL) of PWS patients is seldom researched. The objective of this study is to evaluate the QoL of patients with PWS on exposed parts and explore the factors influencing the QoL of PWS patients. The QoL of 197 cases with PWS on exposed parts were prospectively studied using the Dermatology Life Quality Index questionnaire (DLQI), and the factors influencing the patients’ QoL were analyzed by single-factor analysis and multiple-factor logistic regression analysis. The reliability and validity of the QoL of PWS patients were then assessed by DLQI. A total of 197 valid questionnaires were collected. The DLQI scores in PWS cases ranged from 2 to 16, with 2 to 5 in 52.29% (103/197), 6 to 10 in 42.13% (83/197), and 11 to 20 in 5.58% (11/197). The main score elements of the DLQI focused on symptoms and feelings, daily activities, and social entertainment. Single-factor analysis and multiple-factor logistic regression analysis showed that the main influencing factors were female sex, skin hypertrophy, and lesion area >30 cm2. The inter-item correlation averaged 47.46% and the Cronbach α was 0.740, indicating high internal consistency. Correlation of the 6 dimensions of the DLQI questionnaires with the total scores showed that the Spearman correlation coefficient r ranged from 0.550 to 0.782 (P < .001), with symptoms and feelings having a correlation coefficient of 0.782 and a high correlation with total scores. This study shows that PWS has mild to moderate influence on the QoL of most patients, mainly on daily activities, social entertainment, and feelings. PMID:29390578

Prognostic Impact of Neutrophil/Lymphocyte Ratio, Platelet Count, CRP, and Albumin Levels in Metastatic Colorectal Cancer Patients Treated with FOLFIRI-Bevacizumab.

PubMed

Artaç, Mehmet; Uysal, Mükremin; Karaağaç, Mustafa; Korkmaz, Levent; Er, Zehra; Güler, Tunç; Börüban, Melih Cem; Bozcuk, Hakan

2017-06-01

Metastatic colorectal cancer (mCRC) is a lethal disease and fluorouracil-leucovorin-irinotecan (FOLFIRI) plus bevacizumab (bev) is a standard approach. Hence, there is a strong need for identifying new prognostic factors to show the efficacy of FOLFIRI-bev. This is a retrospective study including patients (n = 90) with mCRC from two centers in Turkey. Neutrophil/lymphocyte (N/L) ratio, platelet count, albumin, and C-reactive protein (CRP) were recorded before FOLFIRI-bev therapy. The efficacy of these factors on progression-free survival (PFS) was analyzed with Kaplan Meier and Cox regression analysis. And the cutoff value of N/L ratio was analyzed with ROC analysis. The median age was 56 years (range 21-80). Forty-seven percent of patients with N/L ratio >2.5 showed progressive disease versus 43 % in patients with N/L ratio <2.5 (p = 0.025). The median PFS was 8.1 months for the patients with N/L ratio >2.5 versus 13.5 months for the patients with N/L ratio <2.5 (p = 0.025). At univariate Cox regression analysis, high baseline neutrophil count, LDH, N/L ratio, and CRP were all significantly associated with poor prognosis. At multivariate Cox regression analysis, CRP was confirmed to be a better independent prognostic factor. CRP variable was divided into above the upper limit of normal (ULN) and normal value. The median PFSs of the patients with normal and above ULN were 11.3 versus 5.8 months, respectively (p = 0.022). CRP and N/L ratio are potential predictors for advanced mCRC treated with FOLFIRI-bev.

Examination of Factors that Influence the Operation Income and Expenditure Balance Difference Rate of 20 Educational Foundation Universities.

PubMed

Nakajima, Hisato; Yano, Kouya; Nagasawa, Kaoko; Katou, Satoka; Yokota, Kuninobu

2017-01-01

The objective of this study is to examine the factors that influence the operation income and expenditure balance ratio of school corporations running university hospitals by multiple regression analysis. 1. We conducted cluster analysis of the financial ratio and classified the school corporations into those running colleges and universities.2. We conducted multiple regression analysis using the operation income and expenditure balance ratio of the colleges as the variables and the Diagnosis Procedure Combination data as the explaining variables.3. The predictive expression was used for multiple regression analysis. 1. The school corporations were divided into those running universities (7), colleges (20) and others. The medical income ratio and the debt ratio were high and the student payment ratio was low in the colleges.2. The numbers of emergency care hospitalizations, operations, radiation therapies, and ambulance conveyances, and the complexity index had a positive influence on the operation income and expenditure balance ratio. On the other hand, the number of general anesthesia procedures, the cover rate index, and the emergency care index had a negative influence.3. The predictive expression was as follows.Operation income and expenditure balance ratio = 0.027 × number of emergency care hospitalizations + 0.005 × number of operations + 0.019 × number of radiation therapies + 0.007 × number of ambulance conveyances - 0.003 × number of general anesthesia procedures + 648.344 × complexity index - 5877.210 × cover rate index - 2746.415 × emergency care index - 38.647Conclusion: In colleges, the number of emergency care hospitalizations, the number of operations, the number of radiation therapies, and the number of ambulance conveyances and the complexity index were factors for gaining ordinary profit.

Collaborative Chronic Care Models for Mental Health Conditions: Cumulative Meta-Analysis and Meta-Regression to Guide Future Research and Implementation

PubMed Central

Grogan-Kaylor, Andrew; Perron, Brian E.; Kilbourne, Amy M.; Woltmann, Emily; Bauer, Mark S.

2013-01-01

Objective Prior meta-analysis indicates that collaborative chronic care models (CCMs) improve mental and physical health outcomes for individuals with mental disorders. This study aimed to investigate the stability of evidence over time and identify patient and intervention factors associated with CCM effects in order to facilitate implementation and sustainability of CCMs in clinical practice. Method We reviewed 53 CCM trials that analyzed depression, mental quality of life (QOL), or physical QOL outcomes. Cumulative meta-analysis and meta-regression were supplemented by descriptive investigations across and within trials. Results Most trials targeted depression in the primary care setting, and cumulative meta-analysis indicated that effect sizes favoring CCM quickly achieved significance for depression outcomes, and more recently achieved significance for mental and physical QOL. Four of six CCM elements (patient self-management support, clinical information systems, system redesign, and provider decision support) were common among reviewed trials, while two elements (healthcare organization support and linkages to community resources) were rare. No single CCM element was statistically associated with the success of the model. Similarly, meta-regression did not identify specific factors associated with CCM effectiveness. Nonetheless, results within individual trials suggest that increased illness severity predicts CCM outcomes. Conclusions Significant CCM trials have been derived primarily from four original CCM elements. Nonetheless, implementing and sustaining this established model will require healthcare organization support. While CCMs have typically been tested as population-based interventions, evidence supports stepped care application to more severely ill individuals. Future priorities include developing implementation strategies to support adoption and sustainability of the model in clinical settings while maximizing fit of this multi-component framework to local contextual factors. PMID:23938600

Reconstruction of the Foot and Ankle Using Pedicled or Free Flaps: Perioperative Flap Survival Analysis

PubMed Central

Li, Xiucun; Cui, Jianli; Maharjan, Suraj; Lu, Laijin; Gong, Xu

2016-01-01

Objective The purpose of this study is to determine the correlation between non-technical risk factors and the perioperative flap survival rate and to evaluate the choice of skin flap for the reconstruction of foot and ankle. Methods This was a clinical retrospective study. Nine variables were identified. The Kaplan-Meier method coupled with a log-rank test and a Cox regression model was used to predict the risk factors that influence the perioperative flap survival rate. The relationship between postoperative wound infection and risk factors was also analyzed using a logistic regression model. Results The overall flap survival rate was 85.42%. The necrosis rates of free flaps and pedicled flaps were 5.26% and 20.69%, respectively. According to the Cox regression model, flap type (hazard ratio [HR] = 2.592; 95% confidence interval [CI] (1.606, 4.184); P < 0.001) and postoperative wound infection (HR = 0.266; 95% CI (0.134, 0.529); P < 0.001) were found to be statistically significant risk factors associated with flap necrosis. Based on the logistic regression model, preoperative wound bed inflammation (odds ratio [OR] = 11.371,95% CI (3.117, 41.478), P < 0.001) was a statistically significant risk factor for postoperative wound infection. Conclusion Flap type and postoperative wound infection were both independent risk factors influencing the flap survival rate in the foot and ankle. However, postoperative wound infection was a risk factor for the pedicled flap but not for the free flap. Microvascular anastomosis is a major cause of free flap necrosis. To reconstruct complex or wide soft tissue defects of the foot or ankle, free flaps are safer and more reliable than pedicled flaps and should thus be the primary choice. PMID:27930679

Which sociodemographic factors are important on smoking behaviour of high school students? The contribution of classification and regression tree methodology in a broad epidemiological survey

PubMed Central

Özge, C; Toros, F; Bayramkaya, E; Çamdeviren, H; Şaşmaz, T

2006-01-01

Background The purpose of this study is to evaluate the most important sociodemographic factors on smoking status of high school students using a broad randomised epidemiological survey. Methods Using in‐class, self administered questionnaire about their sociodemographic variables and smoking behaviour, a representative sample of total 3304 students of preparatory, 9th, 10th, and 11th grades, from 22 randomly selected schools of Mersin, were evaluated and discriminative factors have been determined using appropriate statistics. In addition to binary logistic regression analysis, the study evaluated combined effects of these factors using classification and regression tree methodology, as a new statistical method. Results The data showed that 38% of the students reported lifetime smoking and 16.9% of them reported current smoking with a male predominancy and increasing prevalence by age. Second hand smoking was reported at a 74.3% frequency with father predominance (56.6%). The significantly important factors that affect current smoking in these age groups were increased by household size, late birth rank, certain school types, low academic performance, increased second hand smoking, and stress (especially reported as separation from a close friend or because of violence at home). Classification and regression tree methodology showed the importance of some neglected sociodemographic factors with a good classification capacity. Conclusions It was concluded that, as closely related with sociocultural factors, smoking was a common problem in this young population, generating important academic and social burden in youth life and with increasing data about this behaviour and using new statistical methods, effective coping strategies could be composed. PMID:16891446

[Suicide risk and suicide attempt in North Pas de Calais Region. Lessons from the survey Mental Health in General Population].

PubMed

Danel, T; Vilain, J; Roelandt, J L; Salleron, J; Vaiva, G; Amariei, A; Amarie, A; Plancke, L; Plance, L; Duhamel, A

2010-01-01

The Santé Mentale en Population Générale Survey (Mental Health in General Population Survey (MHGP)) is a multicentre international research and action project initiated by the World Health Organisation Collaboration Centre for research and training in mental health. Its aims are to assess the prevalence of the major mental health disorders in the general adult population and from this to record perceptions associated with "mental illness", "madness" and "depression" together with different means of assistance and specialist or lay care. In this work we present the analysis of data on risks of suicide and past history of suicide attempts in the Nord pas de Calais region. We present the qualitative features of these phenomena and correlations with socio-economic, cultural and psychopathological factors, which are discussed in terms of both protective and vulnerability factors. Risk of suicide is present in 15% of the Nord pas de Calais population and is divided into 10.44% slight risk, 2.37% moderate risk and 2.2% high risk. A comparison with data from the MHGP survey in other regions reveals the high risk of suicide in the NPDC region. A risk of suicide is present is 13% of the population in other SMPG survey regions, broken down into 9.1% low risk, 2.1% medium risk and 1.7% high risk. Compared to the 2.2% high risk figure for NPDC, the population in this category is 21% larger. In terms of risk and protective factors, a bivariate analysis of socio-economic and cultural factors confirms the classical risk factors of sex, marital, occupational and educational status and income. The odds-ratio for these socio-economic and cultural factors can be calculated from logistic regression and the protective factors ranked in decreasing order from religion (Muslim versus other religions), martial status (marked versus separated), age (over 58 years old), occupational status (working or retired versus unemployed), income (more than 1300 euros versus less than 840 euros), sex (men versus women) and immigration. For mental illness, the bivariate analysis confirms that the risk of suicide is significantly higher regardless of the mental disorder in question. Logistic regression categorises the mental illnesses as risk factors in the following order: depression, psychotic disorders, anxiety, alcohol abuse disorders, other drugs and insomnia. Suicide attempts have been made by 9.7% of the study population. This figure should be compared with the 8% of the study population in other regions in the survey and represents 29% more attempts. For the risk and protective factors the results of the bivariate analysis of socio-economic on cultural and psychopathological factors are superimposeable on those found for risk of suicide. The ranking of protective factors obtained from logistic regression places age in first position followed in decreasing order by religion, martial status, income, employment status and finally sex and immigration. The same ranking of mental illnesses by logistic regression places depression as the greatest risk factor followed by anxiety, psychotic disorders, alcohol abuse disorders, drugs and insomnia. Copyright 2010 L’Encéphale. Published by Elsevier Masson SAS.. All rights reserved.

Psychosocial factors associated with young elementary school children's intentions to consume legumes: a test of the theory of reasoned action.

PubMed

Folta, Sara C; Bell, Rick; Economos, Christina; Landers, Stewart; Goldberg, Jeanne P

2006-01-01

The purpose of this study was to test the utility of the Theory of Reasoned Action (TRA) in explaining young elementary school children's intention to consume legumes. A survey was conducted with children in an urban, multicultural community in Massachusetts. A total of 336 children participated. Logistic regression analysis was used to assess the strength of the relationship between attitude and subjective norm and intention. Although attitude was significantly associated with intention, the pseudo-R2 for the regression model that included only the TRA constructs was extremely low (.01). Adding demographic factors and preference improved the model's predictive ability, but attitude was no longer significant. The results of this study do not provide support for the predictive utility of the TRA with young elementary school children for this behavior, when demographic factors are accounted for. Hedonic factors, rather than reasoned judgments, may help drive children's intentions.

Father and adolescent son variables related to son's HIV prevention.

PubMed

Glenn, Betty L; Demi, Alice; Kimble, Laura P

2008-02-01

The purpose of this study was to examine the relationship between fathers' influences and African American male adolescents' perceptions of self-efficacy to reduce high-risk sexual behavior. A convenience sample of 70 fathers was recruited from churches in a large metropolitan area in the South. Hierarchical multiple linear regression analysis indicated father-related factors and son-related factors were associated with 26.1% of the variance in son's self-efficacy to be abstinent. In the regression model greater son's perception of the communication of sexual standards and greater father's perception of his son's self-efficacy were significantly related to greater son's self-efficacy for abstinence. The second regression model with son's self-efficacy for safer sex as the criterion was not statistically significant. Data support the need for fathers to express confidence in their sons' ability to be abstinent or practice safer sex and to communicate with their sons regarding sexual issues and standards.

The time frame of Epstein-Barr virus latent membrane protein-1 gene to disappear in nasopharyngeal swabs after initiation of primary radiotherapy is an independently significant prognostic factor predicting local control for patients with nasopharyngeal carcinoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, S.-Y.; Chang, K.-P.; Graduate Institute of Clinical Medical Sciences, Chang Gung University, Linkou, Taiwan

Purpose: The presence of Epstein-Barr virus latent membrane protein-1 (LMP-1) gene in nasopharyngeal swabs indicates the presence of nasopharyngeal carcinoma (NPC) mucosal tumor cells. This study was undertaken to investigate whether the time taken for LMP-1 to disappear after initiation of primary radiotherapy (RT) was inversely associated with NPC local control. Methods and Materials: During July 1999 and October 2002, there were 127 nondisseminated NPC patients receiving serial examinations of nasopharyngeal swabbing with detection of LMP-1 during the RT course. The time for LMP-1 regression was defined as the number of days after initiation of RT for LMP-1 results tomore » turn negative. The primary outcome was local control, which was represented by freedom from local recurrence. Results: The time for LMP-1 regression showed a statistically significant influence on NPC local control both univariately (p < 0.0001) and multivariately (p = 0.004). In multivariate analysis, the administration of chemotherapy conferred a significantly more favorable local control (p = 0.03). Advanced T status ({>=} T2b), overall treatment time of external photon radiotherapy longer than 55 days, and older age showed trends toward being poor prognosticators. The time for LMP-1 regression was very heterogeneous. According to the quartiles of the time for LMP-1 regression, we defined the pattern of LMP-1 regression as late regression if it required 40 days or more. Kaplan-Meier plots indicated that the patients with late regression had a significantly worse local control than those with intermediate or early regression (p 0.0129). Conclusion: Among the potential prognostic factors examined in this study, the time for LMP-1 regression was the most independently significant factor that was inversely associated with NPC local control.« less

Cancer prevalence and education by cancer site: logistic regression analysis.

PubMed

Johnson, Stephanie; Corsten, Martin J; McDonald, James T; Gupta, Michael

2010-10-01

Previously, using the American National Health Interview Survey (NHIS) and a logistic regression analysis, we found that upper aerodigestive tract (UADT) cancer is correlated with low socioeconomic status (SES). The objective of this study was to determine if this correlation between low SES and cancer prevalence exists for other cancers. We again used the NHIS and employed education level as our main measure of SES. We controlled for potentially confounding factors, including smoking status and alcohol consumption. We found that only two cancer subsites shared the pattern of increased prevalence with low education level and decreased prevalence with high education level: UADT cancer and cervical cancer. UADT cancer and cervical cancer were the only two cancers identified that had a link between prevalence and lower education level. This raises the possibility that an associated risk factor for the two cancers is causing the relationship between lower education level and prevalence.

Isolated and synergistic effects of PM10 and average temperature on cardiovascular and respiratory mortality.

PubMed

Pinheiro, Samya de Lara Lins de Araujo; Saldiva, Paulo Hilário Nascimento; Schwartz, Joel; Zanobetti, Antonella

2014-12-01

OBJECTIVE To analyze the effect of air pollution and temperature on mortality due to cardiovascular and respiratory diseases. METHODS We evaluated the isolated and synergistic effects of temperature and particulate matter with aerodynamic diameter < 10 µm (PM10) on the mortality of individuals > 40 years old due to cardiovascular disease and that of individuals > 60 years old due to respiratory diseases in Sao Paulo, SP, Southeastern Brazil, between 1998 and 2008. Three methodologies were used to evaluate the isolated association: time-series analysis using Poisson regression model, bidirectional case-crossover analysis matched by period, and case-crossover analysis matched by the confounding factor, i.e., average temperature or pollutant concentration. The graphical representation of the response surface, generated by the interaction term between these factors added to the Poisson regression model, was interpreted to evaluate the synergistic effect of the risk factors. RESULTS No differences were observed between the results of the case-crossover and time-series analyses. The percentage change in the relative risk of cardiovascular and respiratory mortality was 0.85% (0.45;1.25) and 1.60% (0.74;2.46), respectively, due to an increase of 10 μg/m3 in the PM10 concentration. The pattern of correlation of the temperature with cardiovascular mortality was U-shaped and that with respiratory mortality was J-shaped, indicating an increased relative risk at high temperatures. The values for the interaction term indicated a higher relative risk for cardiovascular and respiratory mortalities at low temperatures and high temperatures, respectively, when the pollution levels reached approximately 60 μg/m3. CONCLUSIONS The positive association standardized in the Poisson regression model for pollutant concentration is not confounded by temperature, and the effect of temperature is not confounded by the pollutant levels in the time-series analysis. The simultaneous exposure to different levels of environmental factors can create synergistic effects that are as disturbing as those caused by extreme concentrations.

Predictive capacity of sperm quality parameters and sperm subpopulations on field fertility after artificial insemination in sheep.

PubMed

Santolaria, P; Vicente-Fiel, S; Palacín, I; Fantova, E; Blasco, M E; Silvestre, M A; Yániz, J L

2015-12-01

This study was designed to evaluate the relevance of several sperm quality parameters and sperm population structure on the reproductive performance after cervical artificial insemination (AI) in sheep. One hundred and thirty-nine ejaculates from 56 adult rams were collected using an artificial vagina, processed for sperm quality assessment and used to perform 1319 AI. Analyses of sperm motility by computer-assisted sperm analysis (CASA), sperm nuclear morphometry by computer-assisted sperm morphometry analysis (CASMA), membrane integrity by acridine orange-propidium iodide combination and sperm DNA fragmentation using the sperm chromatin dispersion test (SCD) were performed. Clustering procedures using the sperm kinematic and morphometric data resulted in the classification of spermatozoa into three kinematic and three morphometric sperm subpopulations. Logistic regression procedures were used, including fertility at AI as the dependent variable (measured by lambing, 0 or 1) and farm, year, month of AI, female parity, female lambing-treatment interval, ram, AI technician and sperm quality parameters (including sperm subpopulations) as independent factors. Sperm quality variables remaining in the logistic regression model were viability and VCL. Fertility increased for each one-unit increase in viability (by a factor of 1.01) and in VCL (by a factor of 1.02). Multiple linear regression analyses were also performed to analyze the factors possibly influencing ejaculate fertility (N=139). The analysis yielded a significant (P<0.05) relationship between sperm viability and ejaculate fertility. The discriminant ability of the different semen variables to predict field fertility was analyzed using receiver operating characteristic (ROC) curve analysis. Sperm viability and VCL showed significant, albeit limited, predictive capacity on field fertility (0.57 and 0.54 Area Under Curve, respectively). The distribution of spermatozoa in the different subpopulations was not related to fertility. Copyright © 2015 Elsevier B.V. All rights reserved.

Promoting motivation through mode of instruction: The relationship between use of affective teaching techniques and motivation to learn science

NASA Astrophysics Data System (ADS)

Sanchez Rivera, Yamil

The purpose of this study is to add to what we know about the affective domain and to create a valid instrument for future studies. The Motivation to Learn Science (MLS) Inventory is based on Krathwohl's Taxonomy of Affective Behaviors (Krathwohl et al., 1964). The results of the Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) demonstrated that the MLS Inventory is a valid and reliable instrument. Therefore, the MLS Inventory is a uni-dimensional instrument composed of 9 items with convergent validity (no divergence). The instrument had a high Chronbach Alpha value of .898 during the EFA analysis and .919 with the CFA analysis. Factor loadings on the 9 items ranged from .617 to .800. Standardized regression weights ranged from .639 to .835 in the CFA analysis. Various indices (RMSEA = .033; NFI = .987; GFI = .985; CFI = 1.000) demonstrated a good fitness of the proposed model. Hierarchical linear modeling was used to statistical analyze data where students' motivation to learn science scores (level-1) were nested within teachers (level-2). The analysis was geared toward identifying if teachers' use of affective behavior (a level-2 classroom variable) was significantly related with students' MLS scores (level-1 criterion variable). Model testing proceeded in three phases: intercept-only model, means-as-outcome model, and a random-regression coefficient model. The intercept-only model revealed an intra-class correlation coefficient of .224 with an estimated reliability of .726. Therefore, data suggested that only 22.4% of the variance in MLS scores is between-classes and the remaining 77.6% is at the student-level. Due to the significant variance in MLS scores, X2(62.756, p<.0001), teachers' TAB scores were added as a level-2 predictor. The regression coefficient was non-significant (p>.05). Therefore, the teachers' self-reported use of affective behaviors was not a significant predictor of students' motivation to learn science.

Positioning patient-perceived medical services to develop a marketing strategy.

PubMed

Jung, Minsoo; Hong, Myung-Sun

2012-01-01

In today's medical market, marketing philosophy is being rapidly transformed from customer searching to patient satisfaction and service improvement. The principal objective of this study was to contribute to the establishment of a desirable medical marketing strategy, through the factors of customer satisfaction and the positioning of patients' perceptions by marketing institutions. The data were collected from 282 students of the College of Public Health and Medicine in Seoul. The survey tools were developed using the SERVQUAL scale. Analysis in this study involved both statistical and network analysis. The former was used to verify the determinants of service satisfaction as perceived by respondents, via factor analysis and multiple regression analysis. The latter was obtained using a positioning map and 2-mode network analysis with the matrix data converted from raw data. The determining factors for patient satisfaction were identified as facilities, accessibility, process, physicians, and medical staff. The regression equation was significant (R = 0.606), and the most influential variable was the service quality of physicians (β = .569). According to multidimensional scaling, the positioning of medical institutions indicated that patients' perceptions were affected by hospital size and specialization. By recognizing and managing patient satisfaction, medical institutions are able to foster customer loyalty and, in turn, to enhance service quality. It is necessary to develop an adequate marketing mix to provide better medical services and to overcome medical competition among institutions.

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data.

PubMed

Ying, Gui-Shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-04-01

To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field in the elderly. When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI -0.03 to 0.32D, p = 0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, p = 0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller p-values, while analysis of the worse eye provided larger p-values than mixed effects models and marginal models. In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision.

Trait Mindfulness as a Limiting Factor for Residual Depressive Symptoms: An Explorative Study Using Quantile Regression

PubMed Central

Radford, Sholto; Eames, Catrin; Brennan, Kate; Lambert, Gwladys; Crane, Catherine; Williams, J. Mark G.; Duggan, Danielle S.; Barnhofer, Thorsten

2014-01-01

Mindfulness has been suggested to be an important protective factor for emotional health. However, this effect might vary with regard to context. This study applied a novel statistical approach, quantile regression, in order to investigate the relation between trait mindfulness and residual depressive symptoms in individuals with a history of recurrent depression, while taking into account symptom severity and number of episodes as contextual factors. Rather than fitting to a single indicator of central tendency, quantile regression allows exploration of relations across the entire range of the response variable. Analysis of self-report data from 274 participants with a history of three or more previous episodes of depression showed that relatively higher levels of mindfulness were associated with relatively lower levels of residual depressive symptoms. This relationship was most pronounced near the upper end of the response distribution and moderated by the number of previous episodes of depression at the higher quantiles. The findings suggest that with lower levels of mindfulness, residual symptoms are less constrained and more likely to be influenced by other factors. Further, the limiting effect of mindfulness on residual symptoms is most salient in those with higher numbers of episodes. PMID:24988072

[Gender difference in risk factors for depression in community-dwelling elders].

PubMed

Kim, Chul-Gyu; Park, Seungmi

2012-02-01

This study was conducted to compare the degree of depression between men and women and to identify factors influencing their depression. Participants in this cross-sectional descriptive study were 263 persons over 65 years old (men: 103, women: 160). Data were collected through face to face interviews using questionnaires and were done in two urban areas in 2010. Research instruments utilized in this study were SGDS, MMSE-K, SRH, FILE, sleep pattern scale, family and friend support scale, and social support scale. Multivariate regression analysis was performed to identify factors influencing depression in elders. The proportions of participants with depression were significantly different between men and women (52.4% vs. 67.5%). Regression model for depression in elderly men significantly accounted for 54%; disease stress (32%), economic stress (10%), perceived health status (4%), and family support, educational level, age, and hypertension. Regression model for depression in elderly women significantly accounted for 47%; disease stress (25%), perceived social loneliness (8%), friend support (5%), family stress (4%), and sleep satisfaction, and family support. Results demonstrate that depression is an important health problem for elders, and show gender differences for factors influencing depression. These results could be used in the developing depression prevention programs.

Factors Associated with Recurrent Suicidal Ideation among Racially and Ethnically Diverse College Students with a History of Suicide Attempt: The Role of Mindfulness.

PubMed

Chesin, Megan S; Jeglic, Elizabeth L

2016-01-01

Although one-third of enrolled U.S. undergraduate college students are non-White, little is known about risk factors for suicidal behavior among racial and ethnic minority students. Thus, we set out to determine psychosocial factors associated with recurrent suicidal ideation among racially and ethnically diverse college students with a history of suicide attempt. From 2012-2013, 1,734 racially and ethnically diverse college students completed an on-line survey of suicidal behavior and associated factors. Depression, hopelessness, rejection sensitivity, and mindfulness, as well as past-year discrimination, ethnic identification, and acculturative stress were measured using well-validated self-report instruments. The Beck Scale for Suicide Ideation was used to assess current suicidal ideation. A subsample of 118 college students who self-reported a past suicide attempt were selected for the current analysis. Logistic regression analysis was used to test associations between risk factors and the presence of suicidal ideation, and linear regression analysis was used to test factors associated with suicidal ideation severity among those who reported current suicidal ideation. Depression was significantly related to both the presence and severity of current suicidal ideation. Mindfulness, and in particular awareness of present moment experience, was also inversely associated with ideation severity. We found depression and mindlessness were associated with suicidal ideation severity among a sample of diverse college students at high risk for suicidal behavior due to a past suicide attempt. Factors unique to the minority experience, such as acculturative stress, were not associated with current suicidal ideation. Implications for suicide prevention are discussed.

Adherence to preferable behavior for lipid control by high-risk dyslipidemic Japanese patients under pravastatin treatment: the APPROACH-J study.

PubMed

Kitagawa, Yasuhisa; Teramoto, Tamio; Daida, Hiroyuki

2012-01-01

We evaluated the impact of adherence to preferable behavior on serum lipid control assessed by a self-reported questionnaire in high-risk patients taking pravastatin for primary prevention of coronary artery disease. High-risk patients taking pravastatin were followed for 2 years. Questionnaire surveys comprising 21 questions, including 18 questions concerning awareness of health, and current status of diet, exercise, and drug therapy, were conducted at baseline and after 1 year. Potential domains were established by factor analysis from the results of questionnaires, and adherence scores were calculated in each domain. The relationship between adherence scores and lipid values during the 1-year treatment period was analyzed by each domain using multiple regression analysis. A total of 5,792 patients taking pravastatin were included in the analysis. Multiple regression analysis showed a significant correlation in terms of "Intake of high fat/cholesterol/sugar foods" (regression coefficient -0.58, p=0.0105) and "Adherence to instructions for drug therapy" (regression coefficient -6.61, p<0.0001). Low-density lipoprotein cholesterol (LDL-C) values were significantly lower in patients who had an increase in the adherence score in the "Awareness of health" domain compared with those with a decreased score. There was a significant correlation between high-density lipoprotein (HDL-C) values and "Awareness of health" (regression coefficient 0.26; p= 0.0037), "Preferable dietary behaviors" (regression coefficient 0.75; p<0.0001), and "Exercise" (regression coefficient 0.73; p= 0.0002). Similar relations were seen with triglycerides. In patients who have a high awareness of their health, a positive attitude toward lipid-lowering treatment including diet, exercise, and high adherence to drug therapy, is related with favorable overall lipid control even in patients under treatment with pravastatin.

Predictors of pain relief following spinal cord stimulation in chronic back and leg pain and failed back surgery syndrome: a systematic review and meta-regression analysis.

PubMed

Taylor, Rod S; Desai, Mehul J; Rigoard, Philippe; Taylor, Rebecca J

2014-07-01

We sought to assess the extent to which pain relief in chronic back and leg pain (CBLP) following spinal cord stimulation (SCS) is influenced by patient-related factors, including pain location, and technology factors. A number of electronic databases were searched with citation searching of included papers and recent systematic reviews. All study designs were included. The primary outcome was pain relief following SCS, we also sought pain score (pre- and post-SCS). Multiple predictive factors were examined: location of pain, history of back surgery, initial level of pain, litigation/worker's compensation, age, gender, duration of pain, duration of follow-up, publication year, continent of data collection, study design, quality score, method of SCS lead implant, and type of SCS lead. Between-study association in predictive factors and pain relief were assessed by meta-regression. Seventy-four studies (N = 3,025 patients with CBLP) met the inclusion criteria; 63 reported data to allow inclusion in a quantitative analysis. Evidence of substantial statistical heterogeneity (P < 0.0001) in level of pain relief following SCS was noted. The mean level of pain relief across studies was 58% (95% CI: 53% to 64%, random effects) at an average follow-up of 24 months. Multivariable meta-regression analysis showed no predictive patient or technology factors. SCS was effective in reducing pain irrespective of the location of CBLP. This review supports SCS as an effective pain relieving treatment for CBLP with predominant leg pain with or without a prior history of back surgery. Randomized controlled trials need to confirm the effectiveness and cost-effectiveness of SCS in the CLBP population with predominant low back pain. © 2013 The Authors Pain Practice Published by Wiley Periodicals, Inc. on behalf of World Institute of Pain.

Animal models of maternal high fat diet exposure and effects on metabolism in offspring: a meta-regression analysis.

PubMed

Ribaroff, G A; Wastnedge, E; Drake, A J; Sharpe, R M; Chambers, T J G

2017-06-01

Animal models of maternal high fat diet (HFD) demonstrate perturbed offspring metabolism although the effects differ markedly between models. We assessed studies investigating metabolic parameters in the offspring of HFD fed mothers to identify factors explaining these inter-study differences. A total of 171 papers were identified, which provided data from 6047 offspring. Data were extracted regarding body weight, adiposity, glucose homeostasis and lipidaemia. Information regarding the macronutrient content of diet, species, time point of exposure and gestational weight gain were collected and utilized in meta-regression models to explore predictive factors. Publication bias was assessed using Egger's regression test. Maternal HFD exposure did not affect offspring birthweight but increased weaning weight, final bodyweight, adiposity, triglyceridaemia, cholesterolaemia and insulinaemia in both female and male offspring. Hyperglycaemia was found in female offspring only. Meta-regression analysis identified lactational HFD exposure as a key moderator. The fat content of the diet did not correlate with any outcomes. There was evidence of significant publication bias for all outcomes except birthweight. Maternal HFD exposure was associated with perturbed metabolism in offspring but between studies was not accounted for by dietary constituents, species, strain or maternal gestational weight gain. Specific weaknesses in experimental design predispose many of the results to bias. © 2017 The Authors. Obesity Reviews published by John Wiley & Sons Ltd on behalf of World Obesity Federation.

Influence of Health Behaviors and Occupational Stress on Prediabetic State among Male Office Workers.

PubMed

Ryu, Hosihn; Moon, Jihyeon; Jung, Jiyeon

2018-06-14

This study examined the influence of health behaviors and occupational stress on the prediabetic state of male office workers, and identified related risks and influencing factors. The study used a cross-sectional design and performed an integrative analysis on data from regular health checkups, health questionnaires, and a health behavior-related survey of employees of a company, using Spearman’s correlation coefficients and multiple logistic regression analysis. The results showed significant relationships of prediabetic state with health behaviors and occupational stress. Among health behaviors, a diet without vegetables and fruits (Odds Ratio (OR) = 3.74, 95% Confidence Interval (CI) = 1.93⁻7.66) was associated with a high risk of prediabetic state. In the subscales on occupational stress, organizational system in the 4th quartile (OR = 4.83, 95% CI = 2.40⁻9.70) was significantly associated with an increased likelihood of prediabetic state. To identify influencing factors of prediabetic state, the multiple logistic regression was performed using regression models. The results showed that dietary habits (β = 1.20, p = 0.002), total occupational stress score (β = 1.33, p = 0.024), and organizational system (β = 1.13, p = 0.009) were significant influencing factors. The present findings indicate that active interventions are needed at workplace for the systematic and comprehensive management of health behaviors and occupational stress that influence prediabetic state of office workers.

Is investigator background related to outcome in head to head trials of psychotherapy and pharmacotherapy for adult depression? A systematic review and meta-analysis

PubMed Central

Gentili, Claudio; Pietrini, Pietro; Cuijpers, Pim

2017-01-01

Background The influence of factors related to the background of investigators conducting trials comparing psychotherapy and pharmacotherapy has remained largely unstudied. Specializations emphasizing biological determinants of mental disorders, like psychiatry, might favor pharmacotherapy, while others stressing psychosocial factors, like psychology, could promote psychotherapy. Yet financial conflict of interest (COI) could be a confounding factor as authors with a medical specialization might receive more sponsoring from the pharmaceutical industry. Method We conducted a meta-analysis with subgroup and meta-regression analysis examining whether the specialization and affiliation of trial authors were associated to outcomes in the direct comparison of psychotherapy and pharmacotherapy for the acute treatment of depression. Meta-regression analysis also included trial risk of bias and author conflict of interest in relationship to the pharmaceutical industry. Results We included 45 trials. In half, the first author was psychologist. The last author was psychiatrist/MD in half of the trials, and a psychologist or statistician/other technical in the rest. Most lead authors had medical affiliations. Subgroup analysis indicated that studies with last authors statisticians favored pharmacotherapy. Univariate analysis showed a negative relationship between the presence of statisticians and outcomes favoring psychotherapy. Multivariate analysis showed that trials including authors with financial COI reported findings more favorable to pharmacotherapy. Discussion We report the first detailed overview of the background of authors conducting head to head trials for depression. Trials co-authored by statisticians appear to subtly favor pharmacotherapy. Receiving funding from the industry is more closely related to finding better outcomes for the industry’s elective treatment than are factors related to authors’ background. Limitations For a minority of authors we could not retrieve background information. The number of trials was insufficient to evidence subtler effects. PMID:28158281

Evaluation of the Risk Factors for a Rotator Cuff Retear After Repair Surgery.

PubMed

Lee, Yeong Seok; Jeong, Jeung Yeol; Park, Chan-Deok; Kang, Seung Gyoon; Yoo, Jae Chul

2017-07-01

A retear is a significant clinical problem after rotator cuff repair. However, no study has evaluated the retear rate with regard to the extent of footprint coverage. To evaluate the preoperative and intraoperative factors for a retear after rotator cuff repair, and to confirm the relationship with the extent of footprint coverage. Cohort study; Level of evidence, 3. Data were retrospectively collected from 693 patients who underwent arthroscopic rotator cuff repair between January 2006 and December 2014. All repairs were classified into 4 types of completeness of repair according to the amount of footprint coverage at the end of surgery. All patients underwent magnetic resonance imaging (MRI) after a mean postoperative duration of 5.4 months. Preoperative demographic data, functional scores, range of motion, and global fatty degeneration on preoperative MRI and intraoperative variables including the tear size, completeness of rotator cuff repair, concomitant subscapularis repair, number of suture anchors used, repair technique (single-row or transosseous-equivalent double-row repair), and surgical duration were evaluated. Furthermore, the factors associated with failure using the single-row technique and transosseous-equivalent double-row technique were analyzed separately. The retear rate was 7.22%. Univariate analysis revealed that rotator cuff retears were affected by age; the presence of inflammatory arthritis; the completeness of rotator cuff repair; the initial tear size; the number of suture anchors; mean operative time; functional visual analog scale scores; Simple Shoulder Test findings; American Shoulder and Elbow Surgeons scores; and fatty degeneration of the supraspinatus, infraspinatus, and subscapularis. Multivariate logistic regression analysis revealed patient age, initial tear size, and fatty degeneration of the supraspinatus as independent risk factors for a rotator cuff retear. Multivariate logistic regression analysis of the single-row group revealed patient age and fatty degeneration of the supraspinatus as independent risk factors for a rotator cuff retear. Multivariate logistic regression analysis of the transosseous-equivalent double-row group revealed a frozen shoulder as an independent risk factor for a rotator cuff retear. Our results suggest that patient age, initial tear size, and fatty degeneration of the supraspinatus are independent risk factors for a rotator cuff retear, whereas the completeness of rotator cuff repair based on the extent of footprint coverage and repair technique are not.

A regional classification scheme for estimating reference water quality in streams using land-use-adjusted spatial regression-tree analysis

USGS Publications Warehouse

Robertson, Dale M.; Saad, D.A.; Heisey, D.M.

2006-01-01

Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States. ?? 2006 Springer Science+Business Media, Inc.

Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

PubMed

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

2018-03-01

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

[A study of factors influenced by self-efficacy for exercise among community-dwelling elderly men in urban areas].

PubMed

Takai, Itsushi

2012-01-01

It is important to promote self-efficacy for exercise for developing exercise habit. The purpose of this study was to investigate factors influenced by self-efficacy for exercise among community-dwelling elderly men in urban areas. The subjects were 69 elderly men (mean age of 74.2±2.0 SD) who had given approval for participation in the study. We examined the following factors: family situation, history of falls, frequency of going out, stage model of a change, self-efficacy for exercise, fall efficacy scale (FES), geriatric depression scale (GDS), subjective health, functional ability and motor function (5 m walking time, chair stand test-5times). Analysis of variance was used to assess a stage model of a change differences in self-efficacy for exercise and other measures. Correlation analysis and multiple regression analysis were performed to determine the relationships between self-efficacy for exercise and other measures. We found that self-efficacy of exercise, FES, GDS (p<0.01) and CST (p<0.05) vary depending on the stage model of change. Self-efficacy for exercise was found to correlate with psychological factors and functional ability (|r|=0.47-0.67). Multiple regression analysis revealed that the independent factors related to self-efficacy for exercise were FES and GDS. FES and GDS were found to be significant and independent predictors of self-efficacy for exercise in community-dwelling elderly men in urban areas. We should consider not only the approach based on behavioral science but also mental support for depression and fear of falling to promote exercise self-efficacy.

Estimating the causes of traffic accidents using logistic regression and discriminant analysis.

PubMed

Karacasu, Murat; Ergül, Barış; Altin Yavuz, Arzu

2014-01-01

Factors that affect traffic accidents have been analysed in various ways. In this study, we use the methods of logistic regression and discriminant analysis to determine the damages due to injury and non-injury accidents in the Eskisehir Province. Data were obtained from the accident reports of the General Directorate of Security in Eskisehir; 2552 traffic accidents between January and December 2009 were investigated regarding whether they resulted in injury. According to the results, the effects of traffic accidents were reflected in the variables. These results provide a wealth of information that may aid future measures toward the prevention of undesired results.

Occupational factors contributing to low self-esteem in registered nurses and licensed practical nurses: a multivariate analysis.

PubMed

Imai, K

2001-03-01

The present study examines job-related factors leading to low self-esteem in nurses. The lowering of self-esteem suggests that such nurses had difficulty in fully accepting themselves and their circumstances. Subjects were registered nurses (RN) and licensed practical nurses (LPN) at hospitals, and unemployed registered nurses (UEN) seeking employment. Questionnaires were provided at 53 hospitals and a Nurse Bank in Kanagawa Prefecture. The responses of 552 RN, 146 LPN and 433 UEN were analyzed. Questions were asked about personal life, past or present nursing experience, working conditions, nursing skills, satisfaction with work performance and self-esteem. Factors giving rise to low self-esteem were determined using logistic regression analysis and logistic discriminant analysis. Employment status and qualifications were determined to be the most important factors determining the self-esteem of nurses. The next most important factors were 'a limited number of years of experience (less than five years)' and 'dissatisfaction with discretion and responsibility as a nurse' (P < 0.01). Adjusted odds ratio for a reduction in self-esteem for LPN was 4.07 times higher than for UEN, and 2.2 times higher than for RN by logistic regression analysis. LPN are treated as unskilled workers, and thus significant differences were apparent in their performance of certain job tasks. These differences were analyzed using discriminant analysis, and were referred to as follows, 1: Advanced assessment skills, 2: Advanced technical skills, 3: Advanced communication skills, and 4: Nursing plan and documentation (positive discrimination rate was 70.8%). Job dissatisfaction is closely associated with the level of professional training. Continuous education and a feedback system for various levels of nurses are needed.

Factors influencing storm-generated suspended-sediment concentrations and loads in four basins of contrasting land use, humid-tropical Puerto Rico

Treesearch

A. C. Gellis; NO-VALUE

2013-01-01

The significant characteristics controlling the variability in storm-generated suspended-sediment loads and concentrations were analyzed for four basins of differing land use (forest, pasture, cropland, and urbanizing) in humid-tropical Puerto Rico. Statistical analysis involved stepwise regression on factor scores. The explanatory variables were attributes of flow,...

Factors Affecting Conservation Practice Behavior of CRP Participants in Alabama

Treesearch

Okwudili Onianwa; Gerald Wheelock; Shannon Hendrix

1999-01-01

This study examines the factors that affect conservation practice choices of CRP farmers in Alabama. From over 9,000 contracts enrolled in the state between 1986 and 1995, 594 were randomly selected for the study. A multiple-regression analysis was employed to analyze the data. Results indicate that education, ratio ofcropland in CRP, farm size, gender, prior crop...

What Do School Report Cards Really Tell Us? (An Analysis of the Relationships among Factors Commonly Reported in School District Report Cards).

ERIC Educational Resources Information Center

Bobbett, Gordon C.; And Others

The relationships among factors reported on school district (SD) report cards were studied for 121 Tennessee SDs. The report cards provided data on student outcomes (achievement test scores) and SD characteristics. Relationships were studied through linear regression, Pearson product moment correlation, and Guttman's partial correlation. Six…

Factors Associated with Level of Living in Washington County, Mississippi. Technical Bulletin No. 1501.

ERIC Educational Resources Information Center

McCoy, John L.

Step-wise multiple regression and typological analysis were used to analyze the extent to which selected factors influence vertical mobility and achieved level of living. A sample of 418 male household heads who were 18 to 45 years old in Washington County, Mississippi were interviewed during 1971. A prescreening using census and local housing…

Factors Affecting Business Students' Performance: The Case of Students in United Arab Emirates

ERIC Educational Resources Information Center

Harb, Nasri; El-Shaarawi, Ahmed

2007-01-01

In this study, the authors found that the most important factor that affected student performance was their competence in speaking English. The sample was a group of 864 business and economics students in United Arab Emirates. The authors used regression analysis for the study. The results of the study showed that students who participated in…

Multicenter retrospective analysis of cardiovascular risk factors affecting long-term outcome of de novo cardiac transplant recipients.

PubMed

Kobashigawa, Jon A; Starling, Randall C; Mehra, Mandeep R; Kormos, Robert L; Bhat, Geetha; Barr, Mark L; Sigouin, Chris S; Kolesar, June; Fitzsimmons, William

2006-09-01

Previous risk factor studies in cardiac transplant patients have analyzed pre-transplant risk factors as they relate to outcomes. This study is the first in-depth multicenter assessment of ongoing post-transplant risk factors in heart transplant patients and their impact on 5-year outcomes. We reviewed 280 heart transplant patients who survived > 1 year for the impact of post-transplant risk factors (hyperlipidemia, hypertension, diabetes, body mass index [BMI] and renal dysfunction: 8 to 18 possible measurements over 5 years) on outcomes, including death, cardiac allograft vasculopathy (CAV) and non-fatal major adverse cardiac events (NF-MACE). Upon multivariate Cox regression analysis, significant findings were high total-cholesterol for NF-MACE (relative risk [RR] = 4.34, confidence interval [CI] 1.35 to 13.98, p = 0.01), presence of diabetes for NF-MACE (RR = 3.96, CI 1.24 to 12.65, p = 0.02) and high serum creatinine for graft death (RR = 1.59, CI 1.35 to 1.87, p < 0.001). No covariates were found to be significant for CAV. Other significant risk factors by univariate Cox regression models with time-dependent covariates included BMI > or = 33 for graft death. Post-transplant risk factors of hypercholesterolemia and diabetes are associated with NF-MACE, whereas high serum creatinine and BMI > or = 33 are associated with graft death. Risk factor modification, including direct therapy to minimize risk factors, should be considered.

Sufficient Forecasting Using Factor Models

PubMed Central

Fan, Jianqing; Xue, Lingzhou; Yao, Jiawei

2017-01-01

We consider forecasting a single time series when there is a large number of predictors and a possible nonlinear effect. The dimensionality was first reduced via a high-dimensional (approximate) factor model implemented by the principal component analysis. Using the extracted factors, we develop a novel forecasting method called the sufficient forecasting, which provides a set of sufficient predictive indices, inferred from high-dimensional predictors, to deliver additional predictive power. The projected principal component analysis will be employed to enhance the accuracy of inferred factors when a semi-parametric (approximate) factor model is assumed. Our method is also applicable to cross-sectional sufficient regression using extracted factors. The connection between the sufficient forecasting and the deep learning architecture is explicitly stated. The sufficient forecasting correctly estimates projection indices of the underlying factors even in the presence of a nonparametric forecasting function. The proposed method extends the sufficient dimension reduction to high-dimensional regimes by condensing the cross-sectional information through factor models. We derive asymptotic properties for the estimate of the central subspace spanned by these projection directions as well as the estimates of the sufficient predictive indices. We further show that the natural method of running multiple regression of target on estimated factors yields a linear estimate that actually falls into this central subspace. Our method and theory allow the number of predictors to be larger than the number of observations. We finally demonstrate that the sufficient forecasting improves upon the linear forecasting in both simulation studies and an empirical study of forecasting macroeconomic variables. PMID:29731537

Alcohol consumption and its related harms in The Netherlands since 1960: relationships with planned and unplanned factors.

PubMed

Knibbe, Ronald A; Derickx, Mieke; Allamani, Allaman; Massini, Giulia

2014-10-01

to establish which unplanned (social developments) and planned (alcohol policy measures) factors are related to per capita consumption and alcohol-related harms in the Netherlands. linear regression was used to establish which of the planned and unplanned factors were most strongly connected with alcohol consumption and harms. Artificial Neural Analysis (ANN) was used to inspect the interconnections between all variables. mothers age at birth was most strongly associated with increase in consumption. The ban on selling alcoholic beverages at petrol station was associated with a decrease in consumption. The linear regression of harms did not show any relation between alcohol policy measures and harms. The ANN-analyses indicate a very high interconnectedness between all variables allowing no causal inferences. Exceptions are the relation between price of beer and wine and the consumption of these beverages and the relation between a decrease in transport mortality and the increased use of breathalyzers tests and a restriction of paracommercial selling. unplanned factors are most strongly associated with per capita consumption and harms. ANN-analysis indicates that price of alcoholic beverages, breath testing, and restriction of sales may have had some influence. The study's limitations are noted.

Patient satisfaction with outpatient health care services: evaluation of the components of this service using regression analysis.

PubMed

Vural, Fisun; Ciftci, Seval; Cakiroglu, Yigit; Vural, Birol

2014-01-01

In health care services, patient's expectations, and satisfaction levels are important markers of the services provided. The aim of this study is to determine patient satisfaction level, and its influential factors in patients receiving treatment on an ambulatory basis who applied to a state hospital. In this cross-sectional study a total of 210 patients were face-to-face interviewed, and patient satisfaction questionnaire survey was performed. Socioeconomic characteristics, physical conditions of the hospital, pecularities of the health care providers, and satisfaction from health care services received were questioned independently. Regression analysis was performed to investigate factors effective on patient satisfaction. A significant correlation was not found between sociodemographic factors, and patient satisfaction (p<0.05). Favourable patient acceptance of the health care services received is effected by the duration of the waiting period. Communication skills of the health care professionals have been found to be the fundamental factors effective on the preference or recommendation of a certain health care institute once more (p<0.005). Empowering the communication skills of health care professionals, and decreasing the waiting period were found to be necessary in order to increase the satisfaction levels of ambulatory patients.

Factors associated with happiness in the elderly persons living in the community.

PubMed

Luchesi, Bruna Moretti; de Oliveira, Nathalia Alves; de Morais, Daiene; de Paula Pessoa, Rebeca Mendes; Pavarini, Sofia Cristina I; Chagas, Marcos Hortes N

2018-01-01

The aim of the present study was to evaluate factors associated with happiness in a sample of Brazilian older adults. A study was conducted with 263 elderly people in the area of coverage of a family health unit located in the state of São Paulo, Brazil. The Subjective Happiness Scale was used to measure happiness, the final score of which determined one of three outcomes: not happy, intermediate, and happy. Disability, sociodemographic characteristics, and psychological, cognitive, and physical factors were considered for the multinomial logistic regression analysis. Statistically significant differences were found among the three groups regarding satisfaction with life, disability, social phobia, anxiety, depression, and frailty (p≤0.05). In the multinomial regression analysis, being "not happy" was significantly associated with satisfaction with life (RRR: 0.53), depression (RRR: 1.46), social phobia (RRR: 1.24), and age (RRR: 1.06). The present findings indicate that psychological factors and age influence the levels of happiness in older adults living in the community. Furthermore, better screening, diagnosis, and treatment of mental health disorders could increase the feeling of happiness among older adults. Copyright © 2017 Elsevier B.V. All rights reserved.

Physical activity and selected cardiovascular risk factors in middle-aged male personnel of self-defense forces.

PubMed

Sakuta, Hidenari; Suzuki, Takashi

2006-01-01

We cross-sectionally analyzed the association between duration of physical activity and the presence of selected cardiovascular risk factors in the middle-aged male personnel of the Self-Defense Forces who underwent retirement check-up (n = 974). In a univariate regression analysis, duration of high intensity physical activity but not that of moderate or low intensity physical activity inversely correlated with body mass index (BMI), triglyceride, fasting plasma glucose, white blood cell (WBC) count and systolic blood pressure. No intensity categories of physical activity correlated with total cholesterol. In a multivariate logistic regression analysis adjusted for lifestyle factors and the rank, the odds ratio per 1 h/wk increase in high intensity physical activity was .88 (95% confidence interval (CI) .80-.97; P=.007) for the presence of obesity (BMI 25.0 kg/m2), .88 (95% CI .81-.95; P = .002) for hypertrigly ceridemia, .87 (95% CI .76-.99; P=.034) for type 2 diabetes, and .90 (95% CI .82-.99; P=.037) for hypertension. Neither hypercholesterolemia nor high WBC count (> or = 6,900/microl) was associated with high intensity physical activity. High intensity physical activity inversely correlated with traditional cardiovascular risk factors in the middle-aged men.

Seroprevalence and risk factors of Chlamydia abortus infection in free-ranging white yaks in China.

PubMed

Qin, Si-Yuan; Huang, Si-Yang; Yin, Ming-Yang; Tan, Qi-Dong; Liu, Guang-Xue; Zhou, Dong-Hui; Zhu, Xing-Quan; Zhou, Ji-Zhang; Qian, Ai-Dong

2015-01-20

Chlamydia is gram-negative obligate bacteria which causes a wide variety of diseases in humans and animals. To date, there are a few reports about the seroprevalence of Chlamydia and the risk factors associated with Chlamydia infection in yaks in the world. In this study, 974 blood samples were collected from white yaks (Bos grunniens) in Tianzhu Tibetan Autonomous County, Gansu province, northwest China from June 2013 to April 2014. Antibodies against Chlamydia abortus were examined by the indirect hemagglutination (IHA) test, and 158 of 974 (16.22%) white yaks were seropositive for C. abortus antibodies at the cut-off of 1:16. The risk factors associated with seroprevalence were evaluated by a multivariate logistic regression analysis. Region, gender and age of white yak were left out of the final model, due to its insignificance in the logistic regression analysis (P > 0.05). However, season was considered as a major risk factor associated with C. abortus infection in white yaks. To our knowledge, this is the first survey of C. abortus seroprevalence in white yaks in China, which extends the host range for C. abortus and has important implications for public health and the local Tibetan economy.

Nurse-physician collaboration in an academic medical centre: The influence of organisational and individual factors.

PubMed

Bowles, Darci; McIntosh, Georgia; Hemrajani, Reena; Yen, Miao-Shan; Phillips, Allison; Schwartz, Nathan; Tu, Shin-Ping; Dow, Alan W

2016-09-01

Ineffective physician-nurse collaboration has been recognised to adversely impact patient and organisational outcomes, and some studies suggest an underlying factor may be that nurses and physicians have different perceptions of interprofessional collaboration (IPC). The objectives of this study were to evaluate for a difference in the perception of IPC between physicians and nurses and to explore potential contributing factors at the individual and organisational levels to any observed difference. Data including measures of perceptions of IPC were collected from a convenience sample of resident physicians (n = 47), attending physicians (n = 18), and nurses (n = 54) providing care for internal medicine patients in a large tertiary care academic medical centre. Regression analysis revealed significantly lower perceptions of IPC scores for nurses in comparison to the scores of both the resident and attending physician groups (p = .0001 for both). Although demographic and workload factors also differed by profession, only profession and workload remained significant in regression analysis. Given the known relationships between effective physician-nurse collaboration and superior patient and organisational outcomes, better defining the individual and organisational predictors of IPC scores may support development of more effective interventions targeting improvements in IPC.

[Associated factors in newborns with intrauterine growth retardation].

PubMed

Thompson-Chagoyán, Oscar C; Vega-Franco, Leopoldo

2008-01-01

To identify the risk factors implicated in the intrauterine growth retardation (IUGR) of neonates born in a social security institution. Case controls design study in 376 neonates: 188 with IUGR (weight < 10 percentile) and 188 without IUGR. When they born, information about 30 variables of risk for IUGR were obtained from mothers. Risk analysis and logistical regression (stepwise) were used. Odds ratios were significant for 12 of the variables. The model obtains by stepwise regression included: weight gain at pregnancy, prenatal care attendance, toxemia, chocolate ingestion, father's weight, and the environmental house. Must of the variables included in the model are related to socioeconomic disadvantages related to the risk of RCIU in the population.

Comparison of Linear and Non-linear Regression Analysis to Determine Pulmonary Pressure in Hyperthyroidism.

PubMed

Scarneciu, Camelia C; Sangeorzan, Livia; Rus, Horatiu; Scarneciu, Vlad D; Varciu, Mihai S; Andreescu, Oana; Scarneciu, Ioan

2017-01-01

This study aimed at assessing the incidence of pulmonary hypertension (PH) at newly diagnosed hyperthyroid patients and at finding a simple model showing the complex functional relation between pulmonary hypertension in hyperthyroidism and the factors causing it. The 53 hyperthyroid patients (H-group) were evaluated mainly by using an echocardiographical method and compared with 35 euthyroid (E-group) and 25 healthy people (C-group). In order to identify the factors causing pulmonary hypertension the statistical method of comparing the values of arithmetical means is used. The functional relation between the two random variables (PAPs and each of the factors determining it within our research study) can be expressed by linear or non-linear function. By applying the linear regression method described by a first-degree equation the line of regression (linear model) has been determined; by applying the non-linear regression method described by a second degree equation, a parabola-type curve of regression (non-linear or polynomial model) has been determined. We made the comparison and the validation of these two models by calculating the determination coefficient (criterion 1), the comparison of residuals (criterion 2), application of AIC criterion (criterion 3) and use of F-test (criterion 4). From the H-group, 47% have pulmonary hypertension completely reversible when obtaining euthyroidism. The factors causing pulmonary hypertension were identified: previously known- level of free thyroxin, pulmonary vascular resistance, cardiac output; new factors identified in this study- pretreatment period, age, systolic blood pressure. According to the four criteria and to the clinical judgment, we consider that the polynomial model (graphically parabola- type) is better than the linear one. The better model showing the functional relation between the pulmonary hypertension in hyperthyroidism and the factors identified in this study is given by a polynomial equation of second degree where the parabola is its graphical representation.

[Sources analysis and contribution identification of polycyclic aromatic hydrocarbons in indoor and outdoor air of Hangzhou].

PubMed

Liu, Y; Zhu, L; Wang, J; Shen, X; Chen, X

2001-11-01

Twelve polycyclic aromatic hydrocarbons (PAHs) were measured in eight homes in Hangzhou during the summer and autumn in 1999. The sources of PAHs and the contributions of the sources to the total concentration of PAHs in the indoor air were identified by the combination of correlation analysis, factor analysis and multiple regression, and the equations between the concentrations of PAHs in indoor and outdoor air and factors were got. It was indicated that the factors of PAHs in the indoor air were domestic cuisine, the volatility of the mothball, cigarette smoke and heating, the waste gas from vehicles. In the smokers' home, cigarette smoke was the most important factor, and it contributed 25.8% of BaP to the indoor air of smokers' home.

Factors determining disease duration in Alzheimer's disease: a postmortem study of 103 cases using the Kaplan-Meier estimator and Cox regression.

PubMed

Armstrong, R A

2014-01-01

Factors associated with duration of dementia in a consecutive series of 103 Alzheimer's disease (AD) cases were studied using the Kaplan-Meier estimator and Cox regression analysis (proportional hazard model). Mean disease duration was 7.1 years (range: 6 weeks-30 years, standard deviation = 5.18); 25% of cases died within four years, 50% within 6.9 years, and 75% within 10 years. Familial AD cases (FAD) had a longer duration than sporadic cases (SAD), especially cases linked to presenilin (PSEN) genes. No significant differences in duration were associated with age, sex, or apolipoprotein E (Apo E) genotype. Duration was reduced in cases with arterial hypertension. Cox regression analysis suggested longer duration was associated with an earlier disease onset and increased senile plaque (SP) and neurofibrillary tangle (NFT) pathology in the orbital gyrus (OrG), CA1 sector of the hippocampus, and nucleus basalis of Meynert (NBM). The data suggest shorter disease duration in SAD and in cases with hypertensive comorbidity. In addition, degree of neuropathology did not influence survival, but spread of SP/NFT pathology into the frontal lobe, hippocampus, and basal forebrain was associated with longer disease duration.

High Expression of EphA4 Predicted Lesser Degree of Tumor Regression after Neoadjuvant Chemoradiotherapy in Rectal Cancer.

PubMed

Lin, Ching-Yih; Lee, Ying-En; Tian, Yu-Feng; Sun, Ding-Ping; Sheu, Ming-Jen; Lin, Chen-Yi; Li, Chien-Feng; Lee, Sung-Wei; Lin, Li-Ching; Chang, I-Wei; Wang, Chieh-Tien; He, Hong-Lin

2017-01-01

Background: Numerous transmembrane receptor tyrosine kinase pathways have been found to play an important role in tumor progression in some cancers. This study was aimed to evaluate the clinical impact of Eph receptor A4 (EphA4) in patients with rectal cancer treated with neoadjuvant concurrent chemoradiotherapy (CCRT) combined with mesorectal excision, with special emphasis on tumor regression. Methods: Analysis of the publicly available expression profiling dataset of rectal cancer disclosed that EphA4 was the top-ranking, significantly upregulated, transmembrane receptor tyrosine kinase pathway-associated gene in the non-responders to CCRT, compared with the responders. Immunohistochemical study was conducted to assess the EphA4 expression in pre-treatment biopsy specimens from 172 rectal cancer patients without distant metastasis. The relationships between EphA4 expression and various clinicopathological factors or survival were statistically analyzed. Results: EphA4 expression was significantly associated with vascular invasion ( P =0.015), post-treatment depth of tumor invasion ( P =0.006), pre-treatment and post-treatment lymph node metastasis ( P =0.004 and P =0.011, respectively). More importantly, high EphA4 expression was significantly predictive for lesser degree of tumor regression after CCRT ( P =0.031). At univariate analysis, high EphA4 expression was a negative prognosticator for disease-specific survival ( P =0.0009) and metastasis-free survival ( P =0.0001). At multivariate analysis, high expression of EphA4 still served as an independent adverse prognostic factor for disease-specific survival (HR, 2.528; 95% CI, 1.131-5.651; P =0.024) and metastasis-free survival (HR, 3.908; 95% CI, 1.590-9.601; P =0.003). Conclusion: High expression of EphA4 predicted lesser degree of tumor regression after CCRT and served as an independent negative prognostic factor in patients with rectal cancer.

Association between Daily Hospital Outpatient Visits for Accidents and Daily Ambient Air Temperatures in an Industrial City.

PubMed

Chau, Tang-Tat; Wang, Kuo-Ying

2016-01-01

An accident is an unwanted hazard to a person. However, accidents occur. In this work, we search for correlations between daily accident rates and environmental factors. To study daily hospital outpatients who were admitted for accidents during a 5-year period, 2007-2011, we analyzed data regarding 168,366 outpatients using univariate regression models; we also used multivariable regression models to account for confounding factors. Our analysis indicates that the number of male outpatients admitted for accidents was approximately 1.31 to 1.47 times the number of female outpatients (P < 0.0001). Of the 12 parameters (regarding air pollution and meteorology) considered, only daily temperature exhibited consistent and significant correlations with the daily number of hospital outpatient visits for accidents throughout the 5-year analysis period. The univariate regression models indicate that older people (greater than 66 years old) had the fewest accidents per 1-degree increase in temperature, followed by young people (0-15 years old). Middle-aged people (16-65 years old) were the group of outpatients that were more prone to accidents, with an increase in accident rates of 0.8-1.2 accidents per degree increase in temperature. The multivariable regression models also reveal that the temperature variation was the dominant factor in determining the daily number of outpatient visits for accidents. Our further multivariable model analysis of temperature with respect to air pollution variables show that, through the increases in emissions and concentrations of CO, photochemical O3 production and NO2 loss in the ambient air, increases in vehicular emissions are associated with increases in temperatures. As such, increases in hospital visits for accidents are related to vehicular emissions and usage. This finding is consistent with clinical experience which shows about 60% to 80% of accidents are related to traffic, followed by accidents occurred in work place.

Association between Daily Hospital Outpatient Visits for Accidents and Daily Ambient Air Temperatures in an Industrial City

PubMed Central

Chau, Tang-Tat; Wang, Kuo-Ying

2016-01-01

An accident is an unwanted hazard to a person. However, accidents occur. In this work, we search for correlations between daily accident rates and environmental factors. To study daily hospital outpatients who were admitted for accidents during a 5-year period, 2007–2011, we analyzed data regarding 168,366 outpatients using univariate regression models; we also used multivariable regression models to account for confounding factors. Our analysis indicates that the number of male outpatients admitted for accidents was approximately 1.31 to 1.47 times the number of female outpatients (P < 0.0001). Of the 12 parameters (regarding air pollution and meteorology) considered, only daily temperature exhibited consistent and significant correlations with the daily number of hospital outpatient visits for accidents throughout the 5-year analysis period. The univariate regression models indicate that older people (greater than 66 years old) had the fewest accidents per 1-degree increase in temperature, followed by young people (0–15 years old). Middle-aged people (16–65 years old) were the group of outpatients that were more prone to accidents, with an increase in accident rates of 0.8–1.2 accidents per degree increase in temperature. The multivariable regression models also reveal that the temperature variation was the dominant factor in determining the daily number of outpatient visits for accidents. Our further multivariable model analysis of temperature with respect to air pollution variables show that, through the increases in emissions and concentrations of CO, photochemical O3 production and NO2 loss in the ambient air, increases in vehicular emissions are associated with increases in temperatures. As such, increases in hospital visits for accidents are related to vehicular emissions and usage. This finding is consistent with clinical experience which shows about 60% to 80% of accidents are related to traffic, followed by accidents occurred in work place. PMID:26815039

Association between metabolic syndrome and intravesical prostatic protrusion in patients with benign prostatic enlargement and lower urinary tract symptoms (MIPS Study).

PubMed

Russo, Giorgio I; Regis, Federica; Spatafora, Pietro; Frizzi, Jacopo; Urzì, Daniele; Cimino, Sebastiano; Serni, Sergio; Carini, Marco; Gacci, Mauro; Morgia, Giuseppe

2018-05-01

To investigate the association between metabolic syndrome (MetS) and morphological features of benign prostatic enlargement (BPE), including total prostate volume (TPV), transitional zone volume (TZV) and intravesical prostatic protrusion (IPP). Between January 2015 and January 2017, 224 consecutive men aged >50 years presenting with lower urinary tract symptoms (LUTS) suggestive of BPE were recruited to this multicentre cross-sectional study. MetS was defined according to International Diabetes Federation criteria. Multivariate linear and logistic regression models were performed to verify factors associated with IPP, TZV and TPV. Patients with MetS were observed to have a significant increase in IPP (P < 0.01), TPV (P < 0.01) and TZV (P = 0.02). On linear regression analysis, adjusted for age and metabolic factors of MetS, we found that high-density lipoprotein (HDL) cholesterol was negatively associated with IPP (r = -0.17), TPV (r = -0.19) and TZV (r = -0.17), while hypertension was positively associated with IPP (r = 0.16), TPV (r = 0.19) and TZV (r = 0.16). On multivariate logistic regression analysis adjusted for age and factors of MetS, hypertension (categorical; odds ratio [OR] 2.95), HDL cholesterol (OR 0.94) and triglycerides (OR 1.01) were independent predictors of TPV ≥ 40 mL. We also found that HDL cholesterol (OR 0.86), hypertension (OR 2.0) and waist circumference (OR 1.09) were significantly associated with TZV ≥ 20 mL. On age-adjusted logistic regression analysis, MetS was significantly associated with IPP ≥ 10 mm (OR 34.0; P < 0.01), TZV ≥ 20 mL (OR 4.40; P < 0.01) and TPV ≥ 40 mL (OR 5.89; P = 0.03). We found an association between MetS and BPE, demonstrating a relationship with IPP. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

SEPARABLE FACTOR ANALYSIS WITH APPLICATIONS TO MORTALITY DATA

PubMed Central

Fosdick, Bailey K.; Hoff, Peter D.

2014-01-01

Human mortality data sets can be expressed as multiway data arrays, the dimensions of which correspond to categories by which mortality rates are reported, such as age, sex, country and year. Regression models for such data typically assume an independent error distribution or an error model that allows for dependence along at most one or two dimensions of the data array. However, failing to account for other dependencies can lead to inefficient estimates of regression parameters, inaccurate standard errors and poor predictions. An alternative to assuming independent errors is to allow for dependence along each dimension of the array using a separable covariance model. However, the number of parameters in this model increases rapidly with the dimensions of the array and, for many arrays, maximum likelihood estimates of the covariance parameters do not exist. In this paper, we propose a submodel of the separable covariance model that estimates the covariance matrix for each dimension as having factor analytic structure. This model can be viewed as an extension of factor analysis to array-valued data, as it uses a factor model to estimate the covariance along each dimension of the array. We discuss properties of this model as they relate to ordinary factor analysis, describe maximum likelihood and Bayesian estimation methods, and provide a likelihood ratio testing procedure for selecting the factor model ranks. We apply this methodology to the analysis of data from the Human Mortality Database, and show in a cross-validation experiment how it outperforms simpler methods. Additionally, we use this model to impute mortality rates for countries that have no mortality data for several years. Unlike other approaches, our methodology is able to estimate similarities between the mortality rates of countries, time periods and sexes, and use this information to assist with the imputations. PMID:25489353

Quantitative analysis of organizational culture in occupational health research: a theory-based validation in 30 workplaces of the organizational culture profile instrument

PubMed Central

2013-01-01

Background This study advances a measurement approach for the study of organizational culture in population-based occupational health research, and tests how different organizational culture types are associated with psychological distress, depression, emotional exhaustion, and well-being. Methods Data were collected over a sample of 1,164 employees nested in 30 workplaces. Employees completed the 26-item OCP instrument. Psychological distress was measured with the General Health Questionnaire (12-item); depression with the Beck Depression Inventory (21-item); and emotional exhaustion with five items from the Maslach Burnout Inventory general survey. Exploratory factor analysis evaluated the dimensionality of the OCP scale. Multilevel regression models estimated workplace-level variations, and the contribution of organizational culture factors to mental health and well-being after controlling for gender, age, and living with a partner. Results Exploratory factor analysis of OCP items revealed four factors explaining about 75% of the variance, and supported the structure of the Competing Values Framework. Factors were labeled Group, Hierarchical, Rational and Developmental. Cronbach’s alphas were high (0.82-0.89). Multilevel regression analysis suggested that the four culture types varied significantly between workplaces, and correlated with mental health and well-being outcomes. The Group culture type best distinguished between workplaces and had the strongest associations with the outcomes. Conclusions This study provides strong support for the use of the OCP scale for measuring organizational culture in population-based occupational health research in a way that is consistent with the Competing Values Framework. The Group organizational culture needs to be considered as a relevant factor in occupational health studies. PMID:23642223

[Analysis of use of personal protective equipment among rural-to-urban migrant workers in small and medium enterprises in Zhongshan and Shenzhen, China].

PubMed

Zeng, Zhi; Lu, Liming; Rao, Zhanhong; Han, Lu; Shi, Jingrong; Ling, Li

2014-04-01

To investigate the current supply and use of personal protective equipment (PPE) among rural-to-urban migrant workers in small and medium enterprises (SMEs) in Zhongshan and Shenzhen, China and the influential factors for the use of PPE, and to provide a basis for better occupational health services and ensuring the health of migrant workers. Multi-stage sampling was used to select 856 migrant workers from 27 SMEs in Zhongshan and Shenzhen, and face-to-face questionnaire survey was conducted in these subjects. Statistical analysis was performed by one-way analysis of variance, chi-square test, and logistic regression. Of all migrant workers, 38.67%were supplied with free PPE by the factory, and this rate varied across industries (furniture industry: 45.81%; electronic industry: 31.46%) and SMEs (medium enterprises: 42.13%; small enterprises: 39.20%; micro enterprises: 22.16%); 22.43% insisted on the use of PPE. The logistic regression analysis showed that factors associated with the use of PPE included sex, age, awareness of occupational health knowledge, and the size of enterprise. The rates of supply and use of PPE among migrant workers are low. The larger the enterprise, the better the supply of PPE. Male gender, being elder, and high occupational health knowledge score were favorable factors for the use of PPE, while small enterprise size was the unfavorable factor for the use of PPE.

[Analysis of the prevalence and risk factors of preoperative angiography confirmed coronary artery stenosis in patients with degenerative valvular heart disease].

PubMed

Xu, Z J; Pan, J; Zhou, Q; Wang, D J

2017-10-24

Objective: To estimate the prevalence and the risk factors of preoperative coronary angiography (CAG) confirmed coronary stenosis in patients with degenerative valvular heart disease. Methods: A total of 491 patients who underwent screening CAG before valvular surgery due to degenerative valvular heart disease were enrolled from January 2011 to September 2014 in our hospital, and clinical data were analyzed. According to CAG results, patients were divided into positive CAG result (PCAG) group or negative CAG (NCAG) group. Positive CAG result was defined as stenosis ≥50% of the diameter of the left main coronary artery or stenosis ≥70% of the diameter of left anterior descending, left circumflex artery, and right coronary artery.Risk factors of positive CAG result were analyzed by multivariable logistic regression analysis, and Bootstrap method was used to verify the results. Results: There were 47(9.57%)degenerative valvular heart disease patients with PCAG. Patients were older ((68.0±7.6)years vs.(62.6±7.1)years, P <0.001) and the prevalence of typical angina was significantly higher (14.89%(7/47)vs. 2.03%(9/444), P <0.001)in PCAG group than in NCAG group. Multivariable logistic regression analysis showed that age ( OR =1.118, 95% CI 1.067-1.172, P <0.001), typical angina ( OR =8.970, 95% CI 2.963-27.154, P <0.001), and serum concentration of apolipoprotein B ( OR =20.311, 95% CI 4.774-86.416, P <0.001) were the independent risk factors of PCAG in degenerative valvular heart disease patients. Bootstrap method revealed satisfactory repeatability of multivariable logistic regression analysis results (age: OR =1.118, 95% CI 1.068-1.178, P =0.001; typical angina: OR =8.970, 95% CI 2.338-35.891, P =0.001; serum concentration of apolipoprotein B: OR =20.311, 95% CI 4.639-91.977, P =0.001). Conclusions: A low prevalence of PCAG before valvular surgery is observed in degenerative valvular heart disease patients in this patient cohort. Age, typical angina, and serum concentration of apolipoprotein B are independent risk factors of PCAG in this patient cohort.

Spectral regression and correlation coefficients of some benzaldimines and salicylaldimines in different solvents

NASA Astrophysics Data System (ADS)

Hammud, Hassan H.; Ghannoum, Amer; Masoud, Mamdouh S.

2006-02-01

Sixteen Schiff bases obtained from the condensation of benzaldehyde or salicylaldehyde with various amines (aniline, 4-carboxyaniline, phenylhydrazine, 2,4-dinitrophenylhydrazine, ethylenediamine, hydrazine, o-phenylenediamine and 2,6-pyridinediamine) are studied with UV-vis spectroscopy to observe the effect of solvents, substituents and other structural factors on the spectra. The bands involving different electronic transitions are interpreted. Computerized analysis and multiple regression techniques were applied to calculate the regression and correlation coefficients based on the equation that relates peak position λmax to the solvent parameters that depend on the H-bonding ability, refractive index and dielectric constant of solvents.

Is isomerism a risk factor for intestinal volvulus?

PubMed

Landisch, Rachel M; Loomba, Rohit S; Salazar, Jose H; Buelow, Matthew W; Frommelt, Michele; Anderson, Robert H; Wagner, Amy J

2018-03-06

Isomerism, or heterotaxy syndrome, affects many organ systems anatomically and functionally. Intestinal malrotation is common in patients with isomerism. Despite a low reported risk of volvulus, some physicians perform routine screening and prophylactic Ladd procedures on asymptomatic patients with isomerism who are found to have intestinal malrotation. The primary aim of this study was to determine if isomerism is an independent risk factor for volvulus. Kid's Inpatient Database data from 1997 to 2012 was utilized for this study. Characteristics of admissions with and without isomerism were compared with a particular focus on intestinal malrotation, volvulus, and Ladd procedure. A logistic regression was conducted to determine independent risk factors for volvulus with respect to isomerism. 15,962,403 inpatient admissions were included in the analysis, of which 7970 (0.05%) patients had isomerism, and 6 patients (0.1%) developed volvulus. Isomerism was associated with a 52-fold increase in the odds of intestinal malrotation by univariate analysis. Of 251 with isomerism and intestinal malrotation, only 2.4% experienced volvulus. Logistic regression demonstrated that isomerism was not an independent risk factor for volvulus. Isomerism is associated with an increased risk of intestinal malrotation but is not an independent risk factor for volvulus. Prognosis study. Level III. Copyright © 2018 Elsevier Inc. All rights reserved.

Factors predicting weight-bearing asymmetry 1month after unilateral total knee arthroplasty: a cross-sectional study.

PubMed

Christiansen, Cory L; Bade, Michael J; Weitzenkamp, David A; Stevens-Lapsley, Jennifer E

2013-03-01

Factors predicting weight-bearing asymmetry (WBA) after unilateral total knee arthroplasty (TKA) are not known. However, identifying modifiable and non-modifiable predictors of WBA is needed to optimize rehabilitation, especially since WBA is negatively correlated to poor functional performance. The purpose of this study was to identify factors predictive of WBA during sit-stand transitions for people 1month following unilateral TKA. Fifty-nine people were tested preoperatively and 1month following unilateral TKA for WBA using average vertical ground reaction force under each foot during the Five Times Sit-to-Stand Test. Candidate variables tested in the regression analysis represented physical impairments (strength, muscle activation, pain, and motion), demographics, anthropometrics, and movement compensations. WBA, measured as the ratio of surgical/non-surgical limb vertical ground reaction force, was 0.69 (0.18) (mean (SD)) 1month after TKA. Regression analysis identified preoperative WBA (β=0.40), quadriceps strength ratio (β=0.31), and hamstrings strength ratio (β=0.19) as factors predictive of WBA 1month after TKA (R(2)=0.30). Greater amounts of WBA 1month after TKA are predicted by modifiable factors including habitual movement pattern and asymmetry in quadriceps and hamstrings strength. Copyright © 2012 Elsevier B.V. All rights reserved.

High Serum Adiponectin Level Is a Risk Factor for Anemia in Japanese Men: A Prospective Observational Study of 1,029 Japanese Subjects

PubMed Central

Kohno, Kei; Narimatsu, Hiroto; Shiono, Yosuke; Suzuki, Ikuko; Kato, Yuichi; Sho, Ri; Otani, Katsumi; Ishizawa, Kenichi; Yamashita, Hidetoshi; Kubota, Isao; Ueno, Yoshiyuki; Kato, Takeo; Fukao, Akira; Kayama, Takamasa

2016-01-01

Erythroid abnormalities including anemia and polycythemia are often observed in the general clinical setting. Because recent studies reported that adiponectin negatively affects hematopoiesis, we performed a prospective observational study to assess the relationship between anemia and adiponectin, as well as other parameters, in 1029 Japanese subjects (477 men and 552 women) 40 years of age and older. Body measurements, blood tests, and nutrition intake studies were performed at baseline, and 5 to 7 years later (follow-up). Hemoglobin (Hb) and hematocrit (Hct) levels in men with high serum adiponectin levels were lower at follow-up than at baseline. Multiple regression analysis showed that age, body mass index, adiponectin, and glutamic-pyruvic transaminase were significantly associated with erythroid-related variables (red blood cells, Hb, and Hct) in both men and women (P <0.05). In a logistic regression analysis, adiponectin, fasting blood glucose, and β-natriuretic peptide were significant risk factors for anemia in men, and blood urea nitrogen and amylase were significant risk factors in women. Physical features and nutrient intake were not risk factors for anemia. Our study demonstrates, both clinically and epidemiologically, that a high serum adiponectin level decreases the amounts of erythroid-related variables and is a risk factor for anemia in Japanese men. PMID:27918575

Vietnamese validation of the short version of Internet Addiction Test.

PubMed

Tran, Bach Xuan; Mai, Hue Thi; Nguyen, Long Hoang; Nguyen, Cuong Tat; Latkin, Carl A; Zhang, Melvyn W B; Ho, Roger C M

2017-12-01

The main goal of the present study was to examine the psychometric properties of a Vietnamese version of the short-version of Internet Addiction Test (s-IAT) and to assess the relationship between s-IAT scores and demographics, health related qualify of life and perceived stress scores in young Vietnamese. The Vietnamese version of s-IAT was administered to a sample of 589 participants. Exploratory factor and reliability analyses were performed. Regression analysis was used to identify the associated factors. The two-factor model of Vietnamese version of s-IAT demonstrated good psychometric properties. The internal consistency of Factor 1 (loss of control/time management) was high (Cronbach's alpha = 0.82) and Factor 2 (craving/social problems) was satisfactory (Cronbach's alpha = 0.75). Findings indicated that 20.9% youths were addicted to the Internet. Regression analysis revealed significant associations between Internet addiction and having problems in self-care, lower quality of life and high perceived stress scores. The Vietnamese version of s-IAT is a valid and reliable instrument to assess IA in Vietnamese population. Due to the high prevalence of IA among Vietnamese youths, IA should be paid attention in future intervention programs. s-IAT can be a useful screening tool for IA to promptly inform and treat the IA among Vietnamese youths.

[Comparison of arterial stiffness in non-hypertensive and hypertensive population of various age groups].

PubMed

Zhang, Y J; Wu, S L; Li, H Y; Zhao, Q H; Ning, C H; Zhang, R Y; Yu, J X; Li, W; Chen, S H; Gao, J S

2018-01-24

Objective: To investigate the impact of blood pressure and age on arterial stiffness in general population. Methods: Participants who took part in 2010, 2012 and 2014 Kailuan health examination were included. Data of brachial ankle pulse wave velocity (baPWV) examination were analyzed. According to the WHO criteria of age, participants were divided into 3 age groups: 18-44 years group ( n= 11 608), 45-59 years group ( n= 12 757), above 60 years group ( n= 5 002). Participants were further divided into hypertension group and non-hypertension group according to the diagnostic criteria for hypertension (2010 Chinese guidelines for the managemengt of hypertension). Multiple linear regression analysis was used to analyze the association between systolic blood pressure (SBP) with baPWV in the total participants and then stratified by age groups. Multivariate logistic regression model was used to analyze the influence of blood pressure on arterial stiffness (baPWV≥1 400 cm/s) of various groups. Results: (1)The baseline characteristics of all participants: 35 350 participants completed 2010, 2012 and 2014 Kailuan examinations and took part in baPWV examination. 2 237 participants without blood pressure measurement values were excluded, 1 569 participants with history of peripheral artery disease were excluded, we also excluded 1 016 participants with history of cardiac-cerebral vascular disease. Data from 29 367 participants were analyzed. The age was (48.0±12.4) years old, 21 305 were males (72.5%). (2) Distribution of baPWV in various age groups: baPWV increased with aging. In non-hypertension population, baPWV in 18-44 years group, 45-59 years group, above 60 years group were as follows: 1 299.3, 1 428.7 and 1 704.6 cm/s, respectively. For hypertension participants, the respective values of baPWV were: 1 498.4, 1 640.7 and 1 921.4 cm/s. BaPWV was significantly higher in hypertension group than non-hypertension group of respective age groups ( P< 0.05). (3) Multiple linear regression analysis defined risk factors of baPWV: Multivariate linear regression analysis showed that baPWV was positively correlated with SBP( t= 39.30, P< 0.001), and same results were found in the sub-age groups ( t -value was 37.72, 27.30, 9.15, all P< 0.001, respectively) after adjustment for other confounding factors, including age, sex, pulse pressure(PP), body mass index (BMI), fasting blood glucose (FBG), total cholesterol (TC), smoking, drinking, physical exercise, antihypertensive medications, lipid-lowering medication. (4) Multivariate logistic regression analysis of baPWV-related factors: After adjustment for other confounding factors, including age, sex, PP, BMI, FBG, TC, smoking, drinking, physical exercise, antihypertensive medication, lipid-lowering medication, multivariate logistic regression analysis showed that risks for increased arterial stiffness in hypertension group were higher than those in non-hypertension group, the OR in participants with hypertension was 2.54 (2.35-2.74) in the total participants, and same results were also found in sub-age groups, the OR s were 3.22(2.86-3.63), 2.48(2.23-2.76), and 1.91(1.42-2.56), respectively, in each sub-age group. Conclusion: SBP is positively related to arterial stiffness in different age groups, and hypertension is a risk factor for increased arterial stiffness in different age groups. Clinical Trial Registry Chinese Clinical Trial Registry, ChiCTR-TNC-11001489.

Motivations and self-presentation strategies on Korean-based "Cyworld" weblog format personal homepages.

PubMed

Jung, Taejin; Youn, Hyunsook; McClung, Steven

2007-02-01

The main purposes of this study are to find out individuals' motives and interpersonal self-presentation strategies on constructing Korean weblog format personal homepage (e.g., "Cyworld mini-homepage"). The study also attempts to find predictor motives that lead to the activities of posting and maintaining a homepage and compare the self-presentation strategies used on the Web with those commonly used in interpersonal situations. By using a principal component factor analysis, four salient self-presentation strategy factors and five interpretable mini-homepage hosting motive factors were identified. Accompanying multiple regression analysis shows that entertainment and personal income factors are major predictors in explaining homepage maintenance expenditures and frequencies of updating.

Information and Communication Technology (ICT) Usage and Achievement of Turkish Students in Pisa 2006

ERIC Educational Resources Information Center

Aypay, Ahmet

2010-01-01

The purpose of this study is to examine the ICT usage and academic achievement of Turkish students in PISA 2006 data. The sample of the study included 4942 students from 160 schools. Frequencies, independent samples t-tests, ANOVAs, pearson correlation coefficients, exploratory factor analysis, and regression analysis were used. A high percentage…

Assessing the Quality of Academic Libraries on the Web: The Development and Testing of Criteria.

ERIC Educational Resources Information Center

Chao, Hungyune

2002-01-01

This study develops and tests an instrument useful for evaluating the quality of academic library Web sites. Discusses criteria for print materials and human-computer interfaces; user-based perspectives; the use of factor analysis; a survey of library experts; testing reliability through analysis of variance; and regression models. (Contains 53…

The Relationship of Core Self-Evaluations and Life Satisfaction in College Students with Disabilities: Evaluation of a Mediator Model

ERIC Educational Resources Information Center

Smedema, Susan Miller; Chan, Fong; Yaghmaian, Rana A.; Cardoso, Elizabeth DaSilva; Muller, Veronica; Keegan, John; Dutta, Alo; Ebener, Deborah J.

2015-01-01

This study examined the factorial structure of the construct core self-evaluations (CSE) and tested a mediational model of the relationship between CSE and life satisfaction in college students with disabilities. We conducted a quantitative descriptive design using exploratory and confirmatory factor analysis and multiple regression analysis.…

Logistic regression analysis of the risk factors of anastomotic fistula after radical resection of esophageal-cardiac cancer.

PubMed

Huang, Jinxi; Zhou, Yi; Wang, Chenghu; Yuan, Weiwei; Zhang, Zhandong; Chen, Beibei; Zhang, Xiefu

2017-11-01

This study was conducted to investigate the risk factors of anastomotic fistula after the radical resection of esophageal-cardiac cancer. Five hundred and forty-four esophageal-cardiac cancer patients who underwent surgery and had complete clinical data were included in the study. Fifty patients diagnosed with postoperative anastomotic fistula were considered the case group and the remaining 494 subjects who did not develop postoperative anastomotic fistula were considered the control. The potential risk factors for anastomotic fistula, such as age, gender, diabetes history, smoking history, were collected and compared between the groups. Statistically significant variables were substituted into logistic regression to further evaluate the independent risk factors for postoperative anastomotic fistulas in esophageal-cardiac cancer. The incidence of anastomotic fistulas was 9.2% (50/544). Logistic regression analysis revealed that female gender (P < 0.05), laparoscopic surgery (P < 0.05), decreased postoperative albumin (P < 0.05), and postoperative renal dysfunction (P < 0.05) were independent risk factors for anastomotic fistulas in patients who received surgery for esophageal-cardiac cancer. Of the 50 anastomotic fistulas, 16 cases were small fistulas, which were only discovered by conventional imaging examination and not presenting clinical symptoms. All of the anastomotic fistulas occurred within seven days after surgery. Five of the patients with anastomotic fistulas underwent a second surgery and three died. Female patients with esophageal-cardiac cancer treated with endoscopic surgery and suffering from postoperative hypoproteinemia and renal dysfunction were susceptible to postoperative anastomotic fistula. © 2017 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

Satellite remote sensing of fine particulate air pollutants over Indian mega cities

NASA Astrophysics Data System (ADS)

Sreekanth, V.; Mahesh, B.; Niranjan, K.

2017-11-01

In the backdrop of the need for high spatio-temporal resolution data on PM2.5 mass concentrations for health and epidemiological studies over India, empirical relations between Aerosol Optical Depth (AOD) and PM2.5 mass concentrations are established over five Indian mega cities. These relations are sought to predict the surface PM2.5 mass concentrations from high resolution columnar AOD datasets. Current study utilizes multi-city public domain PM2.5 data (from US Consulate and Embassy's air monitoring program) and MODIS AOD, spanning for almost four years. PM2.5 is found to be positively correlated with AOD. Station-wise linear regression analysis has shown spatially varying regression coefficients. Similar analysis has been repeated by eliminating data from the elevated aerosol prone seasons, which has improved the correlation coefficient. The impact of the day to day variability in the local meteorological conditions on the AOD-PM2.5 relationship has been explored by performing a multiple regression analysis. A cross-validation approach for the multiple regression analysis considering three years of data as training dataset and one-year data as validation dataset yielded an R value of ∼0.63. The study was concluded by discussing the factors which can improve the relationship.

Factors associated with postoperative C5 palsy after expansive open-door laminoplasty: retrospective cohort study using multivariable analysis.

PubMed

Tsuji, Takashi; Matsumoto, Morio; Nakamura, Masaya; Ishii, Ken; Fujita, Nobuyuki; Chiba, Kazuhiro; Watanabe, Kota

2017-09-01

The aim of the present study was to investigate the factors associated with C5 palsy by focusing on radiological parameters using multivariable analysis. The authors retrospectively assessed 190 patients with cervical spondylotic myelopathy treated by open-door laminoplasty. Four radiographic parameters-the number of expanded lamina, C3-C7 angle, lamina open angle and space anterior to the spinal cord-were evaluated to clarify the factors associated with C5 palsy. Of the 190 patients, 11 developed C5 palsy, giving an overall incidence of 5.8%. Although the number of expanded lamina, lamina open angle and space anterior to the spinal cord were significantly larger in C5 palsy group than those in non-palsy group, a multiple logistic regression analysis revealed that only the space anterior to the spinal cord (odds ratio 2.60) was a significant independent factor associated with C5 palsy. A multiple linear regression analysis indicated that the lamina open angle was associated with the space anterior to the spinal cord and the analysis identified the following equation: space anterior to the spinal cord (mm) = 1.54 + 0.09 × lamina open angle (degree). A cut-off value of 53.5° for the lamina open angle predicted the development of C5 palsy with a sensitivity of 72.7% and a specificity of 83.2%. The larger postoperative space anterior to the spinal cord, which was associated with the lamina open angle, was positively correlated with the higher incidence of C5 palsy.

Factors influencing consumer satisfaction with health care.

PubMed

Deshpande, Satish P; Deshpande, Samir S

2014-01-01

The purpose of this study was to examine factors that impact consumer satisfaction with health care. This is a secondary analysis of the Center for Studying Health System Change's 2010 Health Tracking Household Survey. Regression analysis was used to examine the impact of treatment issues, financial issues, family-related issues, sources of health care information, location, and demographics-related factors on satisfaction with health care. The study involved 12280 subjects, 56% of whom were very satisfied with their health care, whereas 66% were very satisfied with their primary care physician. Fourteen percent of the subjects had no health insurance; 34% of the subjects got their health care information from the Web. Satisfaction with primary care physician, general health status, promptness of visit to doctor, insurance type, medical cost per family, annual income, persons in family, health care information from friends, and age significantly impacted satisfaction with health care. The regression models accounted for 23% of the variance in health care satisfaction. Satisfaction with primary care physicians, health insurance, and general health status are the 3 most significant indicators of an individual's satisfaction with health care.

Prevalence of and risk factors for depressive symptoms among people living with HIV/AIDS receiving antiretroviral treatment in Wuhan, China: a short report.

PubMed

Rong, Hu; Nianhua, Xie; Jun, Xu; Lianguo, Ruan; Si, Wu; Sheng, Wei; Heng, Guo; Xia, Wang

2017-12-01

We aimed to explore the prevalence of and risk factors for depressive symptoms (DS) among people living with HIV/AIDS (PLWHA) receiving antiretroviral treatment (ART) in Wuhan, Hubei, China. A cross-sectional study evaluating adult PLWHA receiving ART in nine designated clinical hospitals was conducted from October to December 2015. The validated Beck Depression Inventory (BDI) was used to assess DS in eligible participants. Socio-demographical, epidemiological and clinical data were directly extracted from the case reporting database of the China HIV/AIDS Information Network. Multinomial regression analysis was used to explore the risk factors for DS. 394 participants were finally included in all analyses. 40.3% were found to have DS with 13.7% having mild DS and 26.6% having moderate to severe DS. The results of multinomial regression analysis suggested that being married or living with a partner, recent experience of ART-related side effects, and/or history of HCV infection were positively associated with mild DS, while increasing age was positively associated with moderate to severe DS.

Cross-cultural relationships between self-concept and body image in high school-age boys.

PubMed

Austin, J K; Champion, V L; Tzeng, O C

1989-08-01

The relationship between self-concept and body image was investigated through a secondary analysis of data from a sample of 1,200 high school male students from 30 language/culture communities (Osgood, May, & Myron, 1975). Subjects rated adjectives pertaining to self-concept and body image using 7-step semantic differential bipolar scales. Adjectives were related to the dimensions of Evaluation, Potency, and Activity. Correlation, factor analysis, and multiple regression were utilized to examine multivariate relationships among self-concept dimensions and body-image dimensions. Significant positive correlations were found between self-concept and body image. In addition, significant positive relationships were found when self-concept factors were regressed on the body-image factor (R2 = .49 to .57, p less than or equal to .001) for Activity and Potency. Results support the existence of a strong positive relationship between self-concept and body image across the 30 cultures involved. Findings have important implications for nursing in assessment and interventions with clients who have deficits in either self-concept or body image.

Environmental Risk Factors in Han and Uyghur Children with Dyslexia: A Comparative Study.

PubMed

Zhao, Hua; Zhang, Baoping; Chen, Yun; Zhou, Xiang; Zuo, Pengxiang

2016-01-01

Several studies have been conducted to explore risk factors for dyslexia. However, most studies examining dyslexia have been skewed toward Western countries, and few have considered two nationalities simultaneously. This study focused on differences in dyslexia prevalence and potential environmental risk factors between Han and Uyghur children. A cross-sectional study was conducted in Kashgar and Aksu, cities in Xinjiang province, China. A two-stage sampling strategy was used to recruit 2,854 students in grades 3-6 from 5 primary schools in 5 districts; 2,348 valid student questionnaires were included in the analysis. Dyslexia checklists for Chinese and Uyghur children and pupil rating scales were used to identify children with dyslexia. Questions related to the home literacy environment and reading ability were used to evaluate potential environmental risk factors. Single factor analysis and multivariate logistic regression were used to examine prevalence and risk factors for dyslexia. Dyslexia prevalence differed significantly between Han (3.9%) and Uyghur (7.0%) children (P < 0.05), and the boy-to-girl diagnosis ratio was almost 2:1. Multiple logistic regression analysis showed that ethnic differences in dyslexia prevalence between Han and Uyghur children could have occurred because of factors such as mother's occupation (P = 0.02, OR = 0.04, 95% CI = 0.01-0.68) and the frequency with which parents told stories (P = 0.00, OR = 4.50, 95% CI = 1.67-12.11). The prevalence of dyslexia was high in all children, particularly those in the Uyghur group. Environmental factors could have been responsible for some of the differences observed. The results contribute to the early identification and management of dyslexia in children from these two groups and research examining developmental dyslexia and differences in racial genetics.

The Role of Family Environment in Depressive Symptoms among University Students: A Large Sample Survey in China.

PubMed

Yu, Yunmiao; Yang, Xiuxian; Yang, Yanjie; Chen, Lu; Qiu, Xiaohui; Qiao, Zhengxue; Zhou, Jiawei; Pan, Hui; Ban, Bo; Zhu, Xiongzhao; He, Jincai; Ding, Yongqing; Bai, Bing

2015-01-01

To explore the relationship between family environment and depressive symptoms and to evaluate the influence of hard and soft family environmental factors on depression levels in a large sample of university students in China. A multi-stage stratified sampling procedure was used to select 6,000 participants. The response rate was 88.8%, with 5,329 students completing the Beck Depression Inventory (BDI) and the Family Environment Scale Chinese Version (FES-CV), which was adapted for the Chinese population. Differences between the groups were tested for significance by the Student's t-test; ANOVA was used to test continuous variables. The relationship between soft family environmental factors and BDI were tested by Pearson correlation analysis. Hierarchical linear regression analysis was conducted to model the effects of hard environmental factors and soft environmental factors on depression in university students. A total of 11.8% of students scored above the threshold of moderate depression (BDI≧14). Hard family environmental factors such as parent relationship, family economic status, level of parental literacy and non-intact family structure were associated with depressive symptoms. The soft family environmental factors--conflict and control--were positively associated with depression, while cohesion was negatively related to depressive symptom after controlling for other important associates of depression. Hierarchical regression analysis indicated that the soft family environment correlates more strongly with depression than the hard family environment. Soft family environmental factors--especially cohesion, conflict and control--appeared to play an important role in the occurrence of depressive symptoms. These findings underline the significance of the family environment as a source of risk factors for depression among university students in China and suggest that family-based interventions and improvement are very important to reduce depression among university students.

The Clinicopathological Factors Associated with Disease Progression in Luminal A Breast Cancer and Characteristics of Metastasis: A Retrospective Study from A Single Center in China.

PubMed

Ye, Jingming; Wang, Wenjun; Xin, Ling; Owen, Sioned; Xu, Ling; Duan, Xuening; Cheng, Yuanjia; Zhang, Hong; Zhang, Shuang; Li, Ting; Liu, Yinhua

2017-08-01

This study investigated the clinicopathological factors associated with outcomes in patients with Luminal A breast cancer. Retrospective analysis of the association of clinicopathological factors and breast cancer outcome in 421 patients with newly-diagnosed Luminal-A breast cancer that were enrolled from January 2008 to December 2014. Clinicopathological data were analyzed to validate the relationship with disease-free survival (DFS) and overall survival (OS). Kaplan-Meier curves and log-rank tests were used to analyze the value of clinicopathological factors (tumor size, node status and lymphovascular invasion), and subsequent Cox regression analysis revealed significant prognostic factors. With a median of 61 months follow-up, the 5-year DFS and 5-year OS rate were 98.3% and 99.3%. Cox multivariate regression analysis showed that clinical anatomic stage, tumor size, status of lymph nodes, lymphovascular invasion and systemic treatment are strong prognostic factors for clinical outcome in patients with Luminal-A breast cancer. Of all 413 patients with stage I-III breast cancer, 14 presented with metastasis (3.4%) during the follow up. Bone (6/14, 42.9%) was the most common site of metastasis followed by liver (5/14, 35.7%) and lung (4/14, 28.6%). The median survival time after metastasis was 20.4 months. Of all the sites of distant metastasis, liver metastasis was the only factor that affected survival time after metastasis (χ 2 =6.263, p=0.012). Patients with Luminal A breast cancer have excellent outcomes. Liver metastasis is an important factor compressing the survival time after distant metastasis presents. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays and impacts of using incorrect weighting factors on curve stability, data quality, and assay performance.

PubMed

Gu, Huidong; Liu, Guowen; Wang, Jian; Aubry, Anne-Françoise; Arnold, Mark E

2014-09-16

A simple procedure for selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays is reported. The correct weighting factor is determined by the relationship between the standard deviation of instrument responses (σ) and the concentrations (x). The weighting factor of 1, 1/x, or 1/x(2) should be selected if, over the entire concentration range, σ is a constant, σ(2) is proportional to x, or σ is proportional to x, respectively. For the first time, we demonstrated with detailed scientific reasoning, solid historical data, and convincing justification that 1/x(2) should always be used as the weighting factor for all bioanalytical LC-MS/MS assays. The impacts of using incorrect weighting factors on curve stability, data quality, and assay performance were thoroughly investigated. It was found that the most stable curve could be obtained when the correct weighting factor was used, whereas other curves using incorrect weighting factors were unstable. It was also found that there was a very insignificant impact on the concentrations reported with calibration curves using incorrect weighting factors as the concentrations were always reported with the passing curves which actually overlapped with or were very close to the curves using the correct weighting factor. However, the use of incorrect weighting factors did impact the assay performance significantly. Finally, the difference between the weighting factors of 1/x(2) and 1/y(2) was discussed. All of the findings can be generalized and applied into other quantitative analysis techniques using calibration curves with weighted least-squares regression algorithm.

Reported gum disease as a cardiovascular risk factor in adults with intellectual disabilities.

PubMed

Hsieh, K; Murthy, S; Heller, T; Rimmer, J H; Yen, G

2018-03-01

Several risk factors for cardiovascular disease (CVD) have been identified among adults with intellectual disabilities (ID). Periodontitis has been reported to increase the risk of developing a CVD in the general population. Given that individuals with ID have been reported to have a higher prevalence of poor oral health than the general population, the purpose of this study was to determine whether adults with ID with informant reported gum disease present greater reported CVD than those who do not have reported gum disease and whether gum disease can be considered a risk factor for CVD. Using baseline data from the Longitudinal Health and Intellectual Disability Study from which informant survey data were collected, 128 participants with reported gum disease and 1252 subjects without reported gum disease were identified. A series of univariate logistic regressions was conducted to identify potential confounding factors for a multiple logistic regression. The series of univariate logistic regressions identified age, Down syndrome, hypercholesterolemia, hypertension, reported gum disease, daily consumption of fruits and vegetables and the addition of table salt as significant risk factors for reported CVD. When the significant factors from the univariate logistic regression were included in the multiple logistic analysis, reported gum disease remained as an independent risk factor for reported CVD after adjusting for the remaining risk factors. Compared with the adults with ID without reported gum disease, adults in the gum disease group demonstrated a significantly higher prevalence of reported CVD (19.5% vs. 9.7%; P = .001). After controlling for other risk factors, reported gum disease among adults with ID may be associated with a higher risk of CVD. However, further research that also includes clinical indices of periodontal disease and CVD for this population is needed to determine if there is a causal relationship between gum disease and CVD. © 2017 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Correlation analysis between work-related musculoskeletal disorders and the nursing practice environment, quality of life, and social support in the nursing professionals

PubMed Central

Yan, Ping; Yang, Yi; Zhang, Li; Li, Fuye; Huang, Amei; Wang, Yanan; Dai, Yali; Yao, Hua

2018-01-01

Abstract We aim to analyze the correlated influential factors between work-related musculoskeletal disorders (WMSDs) and nursing practice environment and quality of life and social support. From January 2015 to October 2015, cluster sampling was performed on the nurses from 12 hospitals in the 6 areas in Xinjiang. The questionnaires including the modified Nordic Musculoskeletal Questionnaire, Practice Environment Scale (PES), the Mos 36-item Short Form Health Survey, and Social Support Rating Scale were used to investigate. Multivariate logistic regression analysis was used to explore the influential factors of WMSDs. The total prevalence of WMSDs was 79.52% in the nurses ever since the working occupation, which was mainly involved waist (64.83%), neck (61.83%), and shoulder (52.36%). Multivariate logistic regression analysis indicated age (≥26 years), working in the Department of Surgery, Department of Critical Care, Outpatient Department, and Department of Anesthesia, working duration of >40 hours per week were the risk factors of WMSDs in the nurses. The physiological function (PF), body pain, total healthy condition, adequate working force and financial support, and social support were the protective factors of WMSDs. The prevalence of WMSDs in the nurses in Xinjiang Autonomous Region was high. PF, bodily pain, total healthy condition, having adequate staff and support resources to provide quality patient care, and social support were the protective factors of WMSDs in the nurses. PMID:29489648

Correlation analysis between work-related musculoskeletal disorders and the nursing practice environment, quality of life, and social support in the nursing professionals.

PubMed

Yan, Ping; Yang, Yi; Zhang, Li; Li, Fuye; Huang, Amei; Wang, Yanan; Dai, Yali; Yao, Hua

2018-03-01

We aim to analyze the correlated influential factors between work-related musculoskeletal disorders (WMSDs) and nursing practice environment and quality of life and social support.From January 2015 to October 2015, cluster sampling was performed on the nurses from 12 hospitals in the 6 areas in Xinjiang. The questionnaires including the modified Nordic Musculoskeletal Questionnaire, Practice Environment Scale (PES), the Mos 36-item Short Form Health Survey, and Social Support Rating Scale were used to investigate. Multivariate logistic regression analysis was used to explore the influential factors of WMSDs.The total prevalence of WMSDs was 79.52% in the nurses ever since the working occupation, which was mainly involved waist (64.83%), neck (61.83%), and shoulder (52.36%). Multivariate logistic regression analysis indicated age (≥26 years), working in the Department of Surgery, Department of Critical Care, Outpatient Department, and Department of Anesthesia, working duration of >40 hours per week were the risk factors of WMSDs in the nurses. The physiological function (PF), body pain, total healthy condition, adequate working force and financial support, and social support were the protective factors of WMSDs.The prevalence of WMSDs in the nurses in Xinjiang Autonomous Region was high. PF, bodily pain, total healthy condition, having adequate staff and support resources to provide quality patient care, and social support were the protective factors of WMSDs in the nurses.

Factors associated with trait anger level of juvenile offenders in Hubei province: A binary logistic regression analysis.

PubMed

Tang, Li-Na; Ye, Xiao-Zhou; Yan, Qiu-Ge; Chang, Hong-Juan; Ma, Yu-Qiao; Liu, De-Bin; Li, Zhi-Gen; Yu, Yi-Zhen

2017-02-01

The risk factors of high trait anger of juvenile offenders were explored through questionnaire study in a youth correctional facility of Hubei province, China. A total of 1090 juvenile offenders in Hubei province were investigated by self-compiled social-demographic questionnaire, Childhood Trauma Questionnaire (CTQ), and State-Trait Anger Expression Inventory-II (STAXI-II). The risk factors were analyzed by chi-square tests, correlation analysis, and binary logistic regression analysis with SPSS 19.0. A total of 1082 copies of valid questionnaires were collected. High trait anger group (n=316) was defined as those who scored in the upper 27th percentile of STAXI-II trait anger scale (TAS), and the rest were defined as low trait anger group (n=766). The risk factors associated with high level of trait anger included: childhood emotional abuse, childhood sexual abuse, step family, frequent drug abuse, and frequent internet using (P<0.05 or P<0.01). Birth sequence, number of sibling, ranking in the family, identity of the main care-taker, the education level of care-taker, educational style of care-taker, family income, relationship between parents, social atmosphere of local area, frequent drinking, and frequent smoking did not predict to high level of trait anger (P>0.05). It was suggested that traumatic experience in childhood and unhealthy life style may significantly increase the level of trait anger in adulthood. The risk factors of high trait anger and their effects should be taken into consideration seriously.

Is Emotional Congruence With Children Associated With Sexual Offending in Pedophiles and Hebephiles From the Community?

PubMed

Konrad, Anna; Kuhle, Laura F; Amelung, Till; Beier, Klaus M

2018-02-01

Although emotional congruence with children (ECWC) is a risk factor for sexual offending against children, its conceptual validity has hardly been researched. This study aims to explore the construct of ECWC by evaluating the factor structure of the Child Identification Scale (CIS-R) and its relation to facets of sexual preference and child sexual abuse behaviors. It was hypothesized that the measure comprises consistent subscales that are differently associated with aspects of sexual preference and sexual offending against children. CIS-R data of a sample of 217 adult male pedophiles from the community were used for an exploratory principal component analysis (PCA). Group comparisons and a multinomial logistic regression analysis were conducted after including a non-pedophilic control group of 22 adult men. PCA revealed a three-factor solution for the CIS-R accounting for 30% of variance. Group comparisons found differences in overall scores and the factor labeled "Attachment to Children" between subgroups of sexual age and gender preference, but not between contact, online, and non-offenders. The regression analysis showed a pedophile sexual preference and the interaction between a hebephile sexual age preference and the factor "Attachment to Children" being associated with past offending behavior. The results indicate a wish to attach to children as core feature of the CIS-R measure assessing ECWC. It is discussed whether this is an inherent feature of pedophilia or rather an independent aspect being differently distinct in pedophiles.

Satisfaction of active duty soldiers with family dental care.

PubMed

Chisick, M C

1997-02-01

In the fall of 1992, a random, worldwide sample of 6,442 married and single parent soldiers completed a self-administered survey on satisfaction with 22 attributes of family dental care. Simple descriptive statistics for each attribute were derived, as was a composite overall satisfaction score using factor analysis. Composite scores were regressed on demographics, annual dental utilization, and access barriers to identify those factors having an impact on a soldier's overall satisfaction with family dental care. Separate regression models were constructed for single parents, childless couples, and couples with children. Results show below-average satisfaction with nearly all attributes of family dental care, with access attributes having the lowest average satisfaction scores. Factors influencing satisfaction with family dental care varied by family type with one exception: dependent dental utilization within the past year contributed positively to satisfaction across all family types.

Study of relationship between clinical factors and velopharyngeal closure in cleft palate patients

PubMed Central

Chen, Qi; Zheng, Qian; Shi, Bing; Yin, Heng; Meng, Tian; Zheng, Guang-ning

2011-01-01

BACKGROUND: This study was carried out to analyze the relationship between clinical factors and velopharyngeal closure (VPC) in cleft palate patients. METHODS: Chi-square test was used to compare the postoperative velopharyngeal closure rate. Logistic regression model was used to analyze independent variables associated with velopharyngeal closure. RESULTS: Difference of postoperative VPC rate in different cleft types, operative ages and surgical techniques was significant (P=0.000). Results of logistic regression analysis suggested that when operative age was beyond deciduous dentition stage, or cleft palate type was complete, or just had undergone a simple palatoplasty without levator veli palatini retropositioning, patients would suffer a higher velopharyngeal insufficiency rate after primary palatal repair. CONCLUSIONS: Cleft type, operative age and surgical technique were the contributing factors influencing VPC rate after primary palatal repair of cleft palate patients. PMID:22279464

Key factors contributing to accident severity rate in construction industry in Iran: a regression modelling approach.

PubMed

Soltanzadeh, Ahmad; Mohammadfam, Iraj; Moghimbeigi, Abbas; Ghiasvand, Reza

2016-03-01

Construction industry involves the highest risk of occupational accidents and bodily injuries, which range from mild to very severe. The aim of this cross-sectional study was to identify the factors associated with accident severity rate (ASR) in the largest Iranian construction companies based on data about 500 occupational accidents recorded from 2009 to 2013. We also gathered data on safety and health risk management and training systems. Data were analysed using Pearson's chi-squared coefficient and multiple regression analysis. Median ASR (and the interquartile range) was 107.50 (57.24- 381.25). Fourteen of the 24 studied factors stood out as most affecting construction accident severity (p<0.05). These findings can be applied in the design and implementation of a comprehensive safety and health risk management system to reduce ASR.

[Analysis of rational clinical uses of traditional Chinese medicine injections and factors influencing adverse drug reactions].

PubMed

Sun, Shi-Guang; Li, Zi-Feng; Xie, Yan-Ming; Liu, Jian; Lu, Yan; Song, Yi-Fei; Han, Ying-Hua; Liu, Li-Da; Peng, Ting-Ting

2013-09-01

To rationalize the clinical use and safety are some of the key issues in the surveillance of traditional Chinese medicine injections (TCMIs). In this 2011 study, 240 medical records of patients who had been discharged following treatment with TCMIs between 1 and 12 month previously were randomly selected from hospital records. Consistency between clinical use and the description of TCMIs was evaluated. Research on drug use and adverse drug reactions/events using logistic regression analysis was carried out. There was poor consistency between clinical use and best practice advised in manuals on TCMIs. Over-dosage and overly concentrated administration of TCMIs occurred, with the outcome of modifying properties of the blood. Logistic regression analysis showed that, drug concentration was a valid predictor for both adverse drug reactions/events and benefits associated with TCMIs. Surveillance of rational clinical use and safety of TCMIs finds that clinical use should be consistent with technical drug manual specifications, and drug use should draw on multi-layered logistic regression analysis research to help avoid adverse drug reactions/events.

[New method of mixed gas infrared spectrum analysis based on SVM].

PubMed

Bai, Peng; Xie, Wen-Jun; Liu, Jun-Hua

2007-07-01

A new method of infrared spectrum analysis based on support vector machine (SVM) for mixture gas was proposed. The kernel function in SVM was used to map the seriously overlapping absorption spectrum into high-dimensional space, and after transformation, the high-dimensional data could be processed in the original space, so the regression calibration model was established, then the regression calibration model with was applied to analyze the concentration of component gas. Meanwhile it was proved that the regression calibration model with SVM also could be used for component recognition of mixture gas. The method was applied to the analysis of different data samples. Some factors such as scan interval, range of the wavelength, kernel function and penalty coefficient C that affect the model were discussed. Experimental results show that the component concentration maximal Mean AE is 0.132%, and the component recognition accuracy is higher than 94%. The problems of overlapping absorption spectrum, using the same method for qualitative and quantitative analysis, and limit number of training sample, were solved. The method could be used in other mixture gas infrared spectrum analyses, promising theoretic and application values.

Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

NASA Astrophysics Data System (ADS)

Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.

2008-04-01

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

Factors Associated with Uncontrolled Hypertension among Renal Transplant Recipients Attending Nephrology Clinics in Nairobi, Kenya

PubMed Central

Kubo, Mary N.; Kayima, Joshua K.; Were, Anthony J.; McLigeyo, Seth O.; Ogola, Elijah N.

2015-01-01

Objective. To determine the factors associated with poor blood pressure control among renal transplant recipients in a resource-limited setting. Methods. A cross-sectional study was carried out on renal transplant recipients at the Kenyatta National Hospital. Sociodemographic details, blood pressure, urine albumin : creatinine ratio, and adherence using the MMAS-8 questionnaire were noted. Independent factors associated with uncontrolled hypertension were determined using logistic regression analysis. Results. 85 subjects were evaluated. Mean age was 42.4 (SD ± 12.2) years, with a male : female ratio of 1.9 : 1. Fifty-five patients (64.7%) had uncontrolled hypertension (BP ≥ 130/80 mmHg). On univariate analysis, male sex (OR 3.7, 95% CI 1.4–9.5, p = 0.006), higher levels of proteinuria (p = 0.042), and nonadherence to antihypertensives (OR 18, 95% CI 5.2–65.7, p < 0.001) were associated with uncontrolled hypertension. On logistic regression analysis, male sex (adjusted OR 4.6, 95% CI 1.1–19.0, p = 0.034) and nonadherence (adjusted OR 33.8, 95% CI 8.6–73.0, p < 0.001) were independently associated with uncontrolled hypertension. Conclusion. Factors associated with poor blood pressure control in this cohort were male sex and nonadherence to antihypertensives. Emphasis on adherence to antihypertensive therapy must be pursued within this population. PMID:26257920

Psychological impact of sports activity in spinal cord injury patients.

PubMed

Gioia, M C; Cerasa, A; Di Lucente, L; Brunelli, S; Castellano, V; Traballesi, M

2006-12-01

To investigate whether sports activity is associated with better psychological profiles in patients with spinal cord injury (SCI) and to evaluate the effect of demographic factors on psychological benefits. The State-Trait Anxiety Inventory, Form X2 (STAI-X2), the Eysenck Personality Questionnaire for extraversion (EPQ-R (E)) and the questionnaire for depression (QD) were administered in a cross-sectional study of 137 males with spinal cord injury including 52 tetraplegics and 85 paraplegics. The subjects were divided into two groups according to sports activity participation (high frequency vs no sports participation). Moreover, multiple regression analysis was adopted to investigate the influence of demographic variables, such as age, educational level, occupational status and marital status, on psychological variables. Analysis of variance revealed significant differences among the groups for anxiety (STAI-X2), extraversion (EPQ-R (E)) and depression (QD). In particular, SCI patients who did not practice sports showed higher anxiety and depression scores and lower extraversion scores than sports participants. In addition, with respect to the paraplegics, the tetraplegic group showed the lowest depression scores. Following multiple regression analysis, only the sports activity factor remained as an independent factor of anxiety scores. These findings demonstrate that sports activity is associated with better psychological status in SCI patients, irrespective of tetraplegia and paraplegia, and that psychological benefits are not emphasized by demographic factors.

[Co-author and keyword networks and their clustering appearance in preventive medicine fields in Korea: analysis of papers in the Journal of Preventive Medicine and Public Health, 1991~2006].

PubMed

Jung, Minsoo; Chung, Dongjun

2008-01-01

This study evaluated knowledge structure and its effect factor by analysis of co-author and keyword networks in Korea's preventive medicine sector. The data was extracted from 873 papers listed in the Journal of Preventive Medicine and Public Health, and was transformed into a co-author and keyword matrix where the existence of a 'link' was judged by impact factors calculated by the weight value of the role and rate of author participation. Research achievement was dependent upon the author's status and networking index, as analyzed by neighborhood degree, multidimensional scaling, correspondence analysis, and multiple regression. Co-author networks developed as randomness network in the center of a few high-productivity researchers. In particular, closeness centrality was more developed than degree centrality. Also, power law distribution was discovered in impact factor and research productivity by college affiliation. In multiple regression, the effect of the author's role was significant in both the impact factor calculated by the participatory rate and the number of listed articles. However, the number of listed articles varied by sex. This study shows that the small world phenomenon exists in co-author and keyword networks in a journal, as in citation networks. However, the differentiation of knowledge structure in the field of preventive medicine was relatively restricted by specialization.

Factors associated with abnormal eating attitudes among Greek adolescents.

PubMed

Bilali, Aggeliki; Galanis, Petros; Velonakis, Emmanuel; Katostaras, Theofanis

2010-01-01

To estimate the prevalence of abnormal eating attitudes among Greek adolescents and identify possible risk factors associated with these attitudes. Cross-sectional, school-based study. Six randomly selected schools in Patras, southern Greece. The study population consisted of 540 Greek students aged 13-18 years, and the response rate was 97%. The dependent variable was scores on the Eating Attitudes Test-26, with scores > or = 20 indicating abnormal eating attitudes. Bivariate analysis included independent Student t test, chi-square test, and Fisher's exact test. Multivariate logistic regression analysis was applied for the identification of the predictive factors, which were associated independently with abnormal eating attitudes. A 2-sided P value of less than .05 was considered statistically significant. The prevalence of abnormal eating attitudes was 16.7%. Multivariate logistic regression analysis demonstrated that females, urban residents, and those with a body mass index outside normal range, a perception of being overweight, body dissatisfaction, and a family member on a diet were independently related to abnormal eating attitudes. The results indicate that a proportion of Greek adolescents report abnormal eating attitudes and suggest that multiple factors contribute to the development of these attitudes. These findings are useful for further research into this topic and would be valuable in designing preventive interventions. Copyright 2010 Society for Nutrition Education. Published by Elsevier Inc. All rights reserved.

[Risk factors for patent ductus arteriosus in early preterm infants: a case-control study].

PubMed

Du, Jin-Feng; Liu, Tian-Tian; Wu, Hui

2016-01-01

To investigate the risk factors for the occurrence of patent ductus arteriosus (PDA) and to provide a clinical basis for reducing the occurrence of PDA in early preterm infants. A total of 136 early preterm infants (gestational age≤32 weeks) who were hospitalized between January 2013 and December 2014 and diagnosed with hemodynamicalhy significant PDA (hs-PDA) were enrolled as the case group. Based on the matched case-control principle, 136 early preterm infants without hs-PDA were selected among those who were hospitalized within the same period at a ratio of 1:1 and enrolled as the control group. The two groups were matched for sex and gestational age. The basic information of neonates and maternal conditions during the pregnancy and perinatal periods were collected. Logistic regression analysis was performed to identify the risk factors for the development of PDA. Univariate analysis showed that neonatal infectious diseases, neonatal respiratory distress syndrome, decreased platelet count within 24 hours after birth, and low birth weight were associated with the development of hs-PDA (P<0.05). Multivariate conditional logistic regression analysis revealed that neonatal infectious diseases (OR=2.368) and decreased platelet count within 24 hours after birth (OR=0.996) were independent risk factors for hs-PDA. Neonatal infectious diseases and decreased platelet count within 24 hours after birth increase the risk of hs-PDA in early preterm infants.

Impact of hyperglycemia on outcomes of patients with Pseudomonas aeruginosa bacteremia.

PubMed

Patel, Twisha S; Cottreau, Jessica M; Hirsch, Elizabeth B; Tam, Vincent H

2016-02-01

Bacteremia caused by Pseudomonas aeruginosa is associated with significant morbidity and mortality. In other bacterial infections, hyperglycemia has been identified as a risk factor for mortality in nondiabetic patients. The objective of this study was to determine the impact of early hyperglycemia on outcomes in diabetic and nondiabetic patients with P. aeruginosa bacteremia. A retrospective cohort study was performed in adult patients (≥18 years old) with P. aeruginosa bacteremia. Patients received at least 1 drug empirically to which the isolate was susceptible in vitro. Classification and regression tree analysis was used to determine the threshold breakpoint for average blood glucose concentration within 48 hours of positive blood culture (BG48). Logistic regression was used to explore independent risk factors for 30-day mortality. A total of 176 bacteremia episodes were identified; patients in 66 episodes were diabetic. Diabetic patients had higher BG48 (165.2±64.8 mg/dL versus 123.7±31.5 mg/dL, P<0.001) and lower 30-day mortality (10.7% versus 22.7%, P=0.046) than nondiabetic patients. Multivariate regression revealed 30-day mortality in nondiabetic patients was associated with Acute Physiology and Chronic Health Evaluation II score (odds ratio [OR] 1.1; 95% confidence interval [CI] 1.0-1.2) and BG48 >168 mg/dL (OR 6.3; 95% CI 1.7-23.3). However, blood glucose concentration was not identified as an independent risk factor for mortality in diabetic patients by multivariate regression analysis. Hyperglycemia did not appear to affect outcomes in diabetic patients, whereas nondiabetic patients had a higher risk of mortality from P. aeruginosa bacteremia. Prospective studies evaluating the impact of glycemic control in these patients are needed. Copyright © 2016 Elsevier Inc. All rights reserved.

MetaComp: comprehensive analysis software for comparative meta-omics including comparative metagenomics.

PubMed

Zhai, Peng; Yang, Longshu; Guo, Xiao; Wang, Zhe; Guo, Jiangtao; Wang, Xiaoqi; Zhu, Huaiqiu

2017-10-02

During the past decade, the development of high throughput nucleic sequencing and mass spectrometry analysis techniques have enabled the characterization of microbial communities through metagenomics, metatranscriptomics, metaproteomics and metabolomics data. To reveal the diversity of microbial communities and interactions between living conditions and microbes, it is necessary to introduce comparative analysis based upon integration of all four types of data mentioned above. Comparative meta-omics, especially comparative metageomics, has been established as a routine process to highlight the significant differences in taxon composition and functional gene abundance among microbiota samples. Meanwhile, biologists are increasingly concerning about the correlations between meta-omics features and environmental factors, which may further decipher the adaptation strategy of a microbial community. We developed a graphical comprehensive analysis software named MetaComp comprising a series of statistical analysis approaches with visualized results for metagenomics and other meta-omics data comparison. This software is capable to read files generated by a variety of upstream programs. After data loading, analyses such as multivariate statistics, hypothesis testing of two-sample, multi-sample as well as two-group sample and a novel function-regression analysis of environmental factors are offered. Here, regression analysis regards meta-omic features as independent variable and environmental factors as dependent variables. Moreover, MetaComp is capable to automatically choose an appropriate two-group sample test based upon the traits of input abundance profiles. We further evaluate the performance of its choice, and exhibit applications for metagenomics, metaproteomics and metabolomics samples. MetaComp, an integrative software capable for applying to all meta-omics data, originally distills the influence of living environment on microbial community by regression analysis. Moreover, since the automatically chosen two-group sample test is verified to be outperformed, MetaComp is friendly to users without adequate statistical training. These improvements are aiming to overcome the new challenges under big data era for all meta-omics data. MetaComp is available at: http://cqb.pku.edu.cn/ZhuLab/MetaComp/ and https://github.com/pzhaipku/MetaComp/ .

Independent Risk Factors Contributing to Acute Kidney Injury According to Updated Valve Academic Research Consortium-2 Criteria After Transcatheter Aortic Valve Implantation: A Meta-analysis and Meta-regression of 13 Studies.

PubMed

Wang, Jiayang; Yu, Wenyuan; Zhou, Ye; Yang, Yong; Li, Chenglong; Liu, Nan; Hou, Xiaotong; Wang, Longfei

2017-06-01

This study aimed to examine the risk factors for transcatheter aortic valve implantation (TAVI)-associated acute kidney injury (AKI) according to the AKI definition from the Valve Academic Research Consortium-2 (VARC-2). A meta-analysis. A total of 661 patients with post-TAVI AKI according to the VARC-2 definition and 2,012 controls were included in the meta-analysis. Patients undergoing TAVI were included in this meta-analysis. Multiple electronic databases were searched using predefined criteria. The diagnosis of AKI was based on the VARC-2 classification. The authors found that preoperative New York Heart Association class IV (odds ratio [OR], 7.77; 95% confidence interval [CI], 3.81-15.85), previous chronic renal disease (CKD) (OR, 2.81; 95% CI, 1.96-4.03), and requirement for transfusion (OR, 2.03; 95% CI, 1.59-2.59) were associated significantly with an increased risk for post-TAVI AKI. Furthermore, previous peripheral vascular disease (PVD), hypertension, atrial fibrillation, congestive heart failure, diabetes mellitus, and stroke were also risk factors for TAVI-associated AKI. Additionally, transfemoral access significantly correlated with a reduced risk for post-TAVI AKI (OR, 0.43; 95% CI, 0.33-0.57). The potential confounders, including Society of Thoracic Surgeons Score, the logistic European System for Cardiac Operative Risk Evaluation, aortic valve area, mean pressure gradient, left ventricular ejection fraction, age, body mass index, contrast volume, and valve type, had no impact on the association between the risk factors and post-TAVI AKI. Subgroup analysis of the eligible studies presenting multivariate logistic regression analysis on the independent risk factors for post-TAVI AKI revealed that previous CKD, previous PVD, and transapical access were independent risk factors for TAVI-associated AKI. The current meta-analysis suggested that previous CKD, previous PVD, and transapical access may be independent risk factors for TAVI-associated AKI. Copyright © 2017. Published by Elsevier Inc.

Physical fitness of 9 year olds in England: related factors.

PubMed

Kikuchi, S; Rona, R J; Chinn, S

1995-04-01

To examine the influence of social factors, passive smoking, and other parental health related factors, as well as anthropometric and other measurements on children's cardiorespiratory fitness. This was a cross sectional study. The analysis was based on 22 health areas in England. The subjects were 299 boys and 282 girls aged 8 to 9 years. Parents did not give positive consent for 15% of the eligible sample. A further 25% of the eligible sample did not participate because the cycle-ergometer broke down, study time was insufficient, or they were excluded from the analysis because they were from ethnic minority groups or had missing data on one continuous variable. Cardiorespiratory fitness was determined using the cycle-ergometer test. It was measured in terms of PWC85%-that is, power output per body weight (watt/kg) assessed at 85% of maximum heart rate. The association between children's fitness and biological and social factors was analysed in two stages. Firstly, multiple logistic analysis was used to examine the factors associated with the children's ability to complete the test for at least four minutes. Secondly, multiple linear regression analysis was used to examine the independent association of the factors with PWC85%. In the logistic analysis, shorter children, children with higher blood pressure, and boys with a larger sibship size had poorer fitness. In the multiple regression analysis, only height (p < 0.001) was positively associated, and the sum of skinfold thicknesses at four sites (p = 0.001) was negatively associated with fitness in both sexes. In girls, a positive association was found with pre-exercise peak expiratory flow rate (p < 0.05), and there were negative associations with systolic blood pressure (p < 0.05) and family history of heart attack (p < 0.05). In boys an association was found with skinfold distribution and fitness (p < 0.05), so that children with relatively less body fat were fitter. Social and health behaviour factors such as father's social class, father's employment status, or parents' smoking habits were unrelated to child's fitness. Height and obesity are strongly associated, and systolic blood pressure to a small extent, with children's fitness, but social factors are unrelated.

Use of streamflow data to estimate base flowground-water recharge for Wisconsin

USGS Publications Warehouse

Gebert, W.A.; Radloff, M.J.; Considine, E.J.; Kennedy, J.L.

2007-01-01

The average annual base flow/recharge was determined for streamflow-gaging stations throughout Wisconsin by base-flow separation. A map of the State was prepared that shows the average annual base flow for the period 1970-99 for watersheds at 118 gaging stations. Trend analysis was performed on 22 of the 118 streamflow-gaging stations that had long-term records, unregulated flow, and provided aerial coverage of the State. The analysis found that a statistically significant increasing trend was occurring for watersheds where the primary land use was agriculture. Most gaging stations where the land cover was forest had no significant trend. A method to estimate the average annual base flow at ungaged sites was developed by multiple-regression analysis using basin characteristics. The equation with the lowest standard error of estimate, 9.5%, has drainage area, soil infiltration and base flow factor as independent variables. To determine the average annual base flow for smaller watersheds, estimates were made at low-flow partial-record stations in 3 of the 12 major river basins in Wisconsin. Regression equations were developed for each of the three major river basins using basin characteristics. Drainage area, soil infiltration, basin storage and base-flow factor were the independent variables in the regression equations with the lowest standard error of estimate. The standard error of estimate ranged from 17% to 52% for the three river basins. ?? 2007 American Water Resources Association.

Using multilevel modeling to assess case-mix adjusters in consumer experience surveys in health care.

PubMed

Damman, Olga C; Stubbe, Janine H; Hendriks, Michelle; Arah, Onyebuchi A; Spreeuwenberg, Peter; Delnoij, Diana M J; Groenewegen, Peter P

2009-04-01

Ratings on the quality of healthcare from the consumer's perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for analyzing healthcare performance data, it has rarely been used to assess case-mix adjustment of such data. The purpose of this article is to investigate whether multilevel regression analysis is a useful tool to detect case-mix adjusters in consumer assessment of healthcare. We used data on 11,539 consumers from 27 Dutch health plans, which were collected using the Dutch Consumer Quality Index health plan instrument. We conducted multilevel regression analyses of consumers' responses nested within health plans to assess the effects of consumer characteristics on consumer experience. We compared our findings to the results of another methodology: the impact factor approach, which combines the predictive effect of each case-mix variable with its heterogeneity across health plans. Both multilevel regression and impact factor analyses showed that age and education were the most important case-mix adjusters for consumer experience and ratings of health plans. With the exception of age, case-mix adjustment had little impact on the ranking of health plans. On both theoretical and practical grounds, multilevel modeling is useful for adequate case-mix adjustment and analysis of performance ratings.

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression.

PubMed

Chen, Qiang; Mei, Kun; Dahlgren, Randy A; Wang, Ting; Gong, Jian; Zhang, Minghua

2016-12-01

As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R 2 values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R 2 ~59.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use conditions within each watershed to optimize mitigation strategies for contrasting land-use characteristics and seasonal variations. Copyright © 2016 Elsevier B.V. All rights reserved.

Changes of visual-field global indices after cataract surgery in primary open-angle glaucoma patients.

PubMed

Seol, Bo Ram; Jeoung, Jin Wook; Park, Ki Ho

2016-11-01

To determine changes of visual-field (VF) global indices after cataract surgery and the factors associated with the effect of cataracts on those indices in primary open-angle glaucoma (POAG) patients. A retrospective chart review of 60 POAG patients who had undergone phacoemulsification and intraocular lens insertion was conducted. All of the patients were evaluated with standard automated perimetry (SAP; 30-2 Swedish interactive threshold algorithm; Carl Zeiss Meditec Inc.) before and after surgery. VF global indices before surgery were compared with those after surgery. The best-corrected visual acuity, intraocular pressure (IOP), number of glaucoma medications before surgery, mean total deviation (TD) values, mean pattern deviation (PD) value, and mean TD-PD value were also compared with the corresponding postoperative values. Additionally, postoperative peak IOP and mean IOP were evaluated. Univariate and multivariate logistic regression analyses were performed to identify the factors associated with the effect of cataract on global indices. Mean deviation (MD) after cataract surgery was significantly improved compared with the preoperative MD. Pattern standard deviation (PSD) and visual-field index (VFI) after surgery were similar to those before surgery. Also, mean TD and mean TD-PD were significantly improved after surgery. The posterior subcapsular cataract (PSC) type showed greater MD changes than did the non-PSC type in both the univariate and multivariate logistic regression analyses. In the univariate logistic regression analysis, the preoperative TD-PD value and type of cataract were associated with MD change. However, in the multivariate logistic regression analysis, type of cataract was the only associated factor. None of the other factors was associated with MD change. MD was significantly affected by cataracts, whereas PSD and VFI were not. Most notably, the PSC type showed better MD improvement compared with the non-PSC type after cataract surgery. Clinicians therefore should carefully analyze VF examination results for POAG patients with the PSC type.

Factors associated with variation in financial condition among voluntary hospitals.

PubMed Central

Brecher, C; Nesbitt, S

1985-01-01

This article uses multiple regression analysis to identify factors which affect variations in the financial condition of voluntary hospitals in New York State. Six separate ratios are used to measure financial condition and 18 independent variables are considered. The factors affecting financial conditions were found to vary among dimensions of financial health, and different causal relationships were evident among hospitals in New York City than among those in the rest of the state. PMID:4019212

Obstetrical correlates and perinatal consequences of neonatal hypoglycemia in term infants.

PubMed

Ogunyemi, D; Friedman, P; Betcher, K; Whitten, A; Sugiyama, N; Qu, L; Kohn, Amitai; Paul, Holtrop

2017-06-01

To determine independent perinatal and intrapartum factors associated with neonatal hypoglycemia. Of singleton pregnancies delivered at term in 2013; 318 (3.8%) neonates diagnosed with hypoglycemia were compared to 7955 (96.2%) neonate controls with regression analysis. Regression analysis showed that independent prenatal factors were multiparity (odds-ratio [OR] = 1.61), gestational age (OR = 0.68), gestational diabetes (OR = 0.22), macrosomia (OR = 4.87), small for gestational age neonate [SGA] (OR = 6.83) and admission cervical dilation (OR = 0.79). For intrapartum factors, only cesarean section (OR = 1.57) and last cervical dilation (OR = 0.92) were independently significantly associated with neonatal hypoglycemia. For biologically plausible risk factors, independent factors were cesarean section (OR = 4.18), gentamycin/clindamycin in labor (OR = 5.35), gestational age (OR = 0.59) and macrosomia (OR = 5.62). Mothers of babies with neonatal hypoglycemia had more blood loss and longer hospital stays, while neonates with hypoglycemia had worse umbilical cord gases, more neonatal hypoxic conditions, neonatal morbidities and NICU admissions. Diabetes was protective of neonatal hypoglycemia, which may be explained by optimum maternal glucose management; nevertheless macrosomia was independently predictive of neonatal hypoglycemia. Cesarean section and decreasing gestational age were the most consistent independent risk factors followed by treatment for chorioamnionitis and SGA. Further studies to evaluate these observations and develop preventive strategies are warranted.

Negative mood states and related factors in a sample of adolescent secondary-school students in Barcelona (Spain).

PubMed

Ahonen, Emily Q; Nebot, Manel; Giménez, Emmanuel

2007-01-01

Poor mental health is a common problem in adolescence. Little information is available, however, about the factors influencing negative mood states in otherwise healthy adolescents. We aimed to describe the mood states and related factors in a sample of adolescents in the city of Barcelona (Spain). We administered a health survey to a sample of 2,727 students from public, subsidized, and private schools in Barcelona, aged approximately 14, 16, and 18 years old. To analyze the associations among moods and related factors, we used bivariate logistic regression, and fitted multivariate logistic regressions using the statistically significant variables from the bivariate analysis. To examine the possible group effects of the school on individual students, we employed multilevel analysis. The frequencies of negative mood states increased with age, with girls consistently reporting more frequent negative mood states than boys. The factors associated with negative mood states were problematic alcohol use, perceived mistreatment or abuse, antisocial behavior, intention to use or current use of illegal drugs (not including cannabis), lower perceived academic performance, and feeling isolated. Mood states are influenced by lifestyle and social factors, about which there is little local information. To plan and implement appropriate public health interventions, more complete information about the possible areas of influence is required. To complement the information obtained from studies such as the present study, longitudinal and qualitative studies would be desirable.

Application of classification tree and logistic regression for the management and health intervention plans in a community-based study.

PubMed

Teng, Ju-Hsi; Lin, Kuan-Chia; Ho, Bin-Shenq

2007-10-01

A community-based aboriginal study was conducted and analysed to explore the application of classification tree and logistic regression. A total of 1066 aboriginal residents in Yilan County were screened during 2003-2004. The independent variables include demographic characteristics, physical examinations, geographic location, health behaviours, dietary habits and family hereditary diseases history. Risk factors of cardiovascular diseases were selected as the dependent variables in further analysis. The completion rate for heath interview is 88.9%. The classification tree results find that if body mass index is higher than 25.72 kg m(-2) and the age is above 51 years, the predicted probability for number of cardiovascular risk factors > or =3 is 73.6% and the population is 322. If body mass index is higher than 26.35 kg m(-2) and geographical latitude of the village is lower than 24 degrees 22.8', the predicted probability for number of cardiovascular risk factors > or =4 is 60.8% and the population is 74. As the logistic regression results indicate that body mass index, drinking habit and menopause are the top three significant independent variables. The classification tree model specifically shows the discrimination paths and interactions between the risk groups. The logistic regression model presents and analyses the statistical independent factors of cardiovascular risks. Applying both models to specific situations will provide a different angle for the design and management of future health intervention plans after community-based study.

Influential factors of red-light running at signalized intersection and prediction using a rare events logistic regression model.

PubMed

Ren, Yilong; Wang, Yunpeng; Wu, Xinkai; Yu, Guizhen; Ding, Chuan

2016-10-01

Red light running (RLR) has become a major safety concern at signalized intersection. To prevent RLR related crashes, it is critical to identify the factors that significantly impact the drivers' behaviors of RLR, and to predict potential RLR in real time. In this research, 9-month's RLR events extracted from high-resolution traffic data collected by loop detectors from three signalized intersections were applied to identify the factors that significantly affect RLR behaviors. The data analysis indicated that occupancy time, time gap, used yellow time, time left to yellow start, whether the preceding vehicle runs through the intersection during yellow, and whether there is a vehicle passing through the intersection on the adjacent lane were significantly factors for RLR behaviors. Furthermore, due to the rare events nature of RLR, a modified rare events logistic regression model was developed for RLR prediction. The rare events logistic regression method has been applied in many fields for rare events studies and shows impressive performance, but so far none of previous research has applied this method to study RLR. The results showed that the rare events logistic regression model performed significantly better than the standard logistic regression model. More importantly, the proposed RLR prediction method is purely based on loop detector data collected from a single advance loop detector located 400 feet away from stop-bar. This brings great potential for future field applications of the proposed method since loops have been widely implemented in many intersections and can collect data in real time. This research is expected to contribute to the improvement of intersection safety significantly. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis of the Environmental Management System based on ISO 14001 on the American continent.

PubMed

Neves, Fábio de Oliveira; Salgado, Eduardo G; Beijo, Luiz A

2017-09-01

The American continent is in broad economic and industrial development. Consequently, a more detailed discussion of the impacts generated by such development is needed. Moreover, there is an increase in the number of ISO 14001 certificates issued to this continent. Given the above, no studies were found that bridge the gap to identify the influence of different factors on ISO 14001 in the Americas. Thus, this article has as its main aim to check which economic, environmental and cultural factors have influence on ISO 14001 Certification in the American Continent. The data were collected in the ISO Survey, World Bank, United Nations Development Programme and International Energy Agency. Among the countries of that continent, thirteen were analyzed and only two did not show the economic factors as the influence factor in the multiple regression models fitted with Brazil and the United State. In these models, all presented environmental factors as influencing factors. Only in Brazil the index HDI presented as cultural factor in multiple regression model fitted. The economic factors: Gross Domestic Product and exports of goods and services and environmental: Carbon Dioxide (CO 2 ) and fossil fuel consumption were the most influential in ISO 14001 certification. Venezuela, Uruguay, Colombia and the United States were countries that had factors dependent on each other, featuring the environmental marketing. Briefly, this study brings up several implications: to the academy, with the proposal of new concepts and guidance on the factors that assist in ISO 14001 certification in the American Continent. Additionally, taking into account the industry, the factors serve as efficiency parameters for the implementation of ISO 14001 standard, and for the Government to improve through factors that do not fit in multiple regression models. Copyright © 2017 Elsevier Ltd. All rights reserved.

A spatial analysis of the determinants of pneumonia and influenza hospitalizations in Ontario (1992-2001).

PubMed

Crighton, Eric J; Elliott, Susan J; Moineddin, Rahim; Kanaroglou, Pavlos; Upshur, Ross

2007-04-01

Previous research on the determinants of pneumonia and influenza has focused primarily on the role of individual level biological and behavioural risk factors resulting in partial explanations and largely curative approaches to reducing the disease burden. This study examines the geographic patterns of pneumonia and influenza hospitalizations and the role that broad ecologic-level factors may have in determining them. We conducted a county level, retrospective, ecologic study of pneumonia and influenza hospitalizations in the province of Ontario, Canada, between 1992 and 2001 (N=241,803), controlling for spatial dependence in the data. Non-spatial and spatial regression models were estimated using a range of environmental, social, economic, behavioural, and health care predictors. Results revealed low education to be positively associated with hospitalization rates over all age groups and both genders. The Aboriginal population variable was also positively associated in most models except for the 65+-year age group. Behavioural factors (daily smoking and heavy drinking), environmental factors (passive smoking, poor housing, temperature), and health care factors (influenza vaccination) were all significantly associated in different age and gender-specific models. The use of spatial error regression models allowed for unbiased estimation of regression parameters and their significance levels. These findings demonstrate the importance of broad age and gender-specific population-level factors in determining pneumonia and influenza hospitalizations, and illustrate the need for place and population-specific policies that take these factors into consideration.

An Empirical Analysis of the Default Rate of Informal Lending—Evidence from Yiwu, China

NASA Astrophysics Data System (ADS)

Lu, Wei; Yu, Xiaobo; Du, Juan; Ji, Feng

This study empirically analyzes the underlying factors contributing to the default rate of informal lending. This paper adopts snowball sampling interview to collect data and uses the logistic regression model to explore the specific factors. The results of these analyses validate the explanation of how the informal lending differs from the commercial loan. Factors that contribute to the default rate have particular attributes, while sharing some similarities with commercial bank or FICO credit scoring Index. Finally, our concluding remarks draw some inferences from empirical analysis and speculate as to what this may imply for the role of formal and informal financial sectors.

Modelling lecturer performance index of private university in Tulungagung by using survival analysis with multivariate adaptive regression spline

NASA Astrophysics Data System (ADS)

Hasyim, M.; Prastyo, D. D.

2018-03-01

Survival analysis performs relationship between independent variables and survival time as dependent variable. In fact, not all survival data can be recorded completely by any reasons. In such situation, the data is called censored data. Moreover, several model for survival analysis requires assumptions. One of the approaches in survival analysis is nonparametric that gives more relax assumption. In this research, the nonparametric approach that is employed is Multivariate Regression Adaptive Spline (MARS). This study is aimed to measure the performance of private university’s lecturer. The survival time in this study is duration needed by lecturer to obtain their professional certificate. The results show that research activities is a significant factor along with developing courses material, good publication in international or national journal, and activities in research collaboration.

[Analysis on influencing factors of prognosis of patients with acute organophosphorus pesticide poisoning].

PubMed

Guo, C F; Wang, Y; Liu, J H; Shen, P; Wang, H; Wei, Y J; Shi, X F; Zhou, X J; Wang, W W

2016-05-20

To analyze the relationship between risk factors and prognosis of acute organophosphorus pesticide poisoning (AOPP). The clinical data including APACHEⅡ, D-dimer, C-reactive protein, procalcitonin, lactic acid of the 67 cases of acute organophosphorus pesticide poisoning which respectively divided into survival group and death group by the outcome were collected. The independent influcing factors were got by logistic regression analysis. The analysis showed that APACHEⅡ, D-dimer、C-reactive protein and Procalcitonin were influencing factors to evaluate prognosis of AOPP (P<0.05) .Meanwhile, APACHEⅡ and CRP were the independent influencing factors to evaluate prognosis of AOPP (P<0.05). APACHEⅡ26was the optimum thresholds to acess the prognosis of AOPP and its Youden index was largest. APACHEⅡ and CRP played an important role in the assessment of prognosis on AOPP. When APACHEⅡwas more than 26, it suggested the patient of AOPP will have a bad prognosis.

Identifying the readiness of patients in implementing telemedicine in northern Louisiana for an oncology practice.

PubMed

Gurupur, Varadraj; Shettian, Kruparaj; Xu, Peixin; Hines, Scott; Desselles, Mitzi; Dhawan, Manish; Wan, Thomas Th; Raffenaud, Amanda; Anderson, Lindsey

2017-09-01

This study identified the readiness factors that may create challenges in the use of telemedicine among patients in northern Louisiana with cancer. To identify these readiness factors, the team of investigators developed 19 survey questions that were provided to the patients or to their caregivers. The team collected responses from 147 respondents from rural and urban residential backgrounds. These responses were used to identify the individuals' readiness for utilising telemedicine through factor analysis, Cronbach's alpha reliability test, analysis of variance and ordinary least squares regression. The analysis results indicated that the favourable factor (positive readiness item) had a mean value of 3.47, whereas the unfavourable factor (negative readiness item) had a mean value of 2.76. Cronbach's alpha reliability test provided an alpha value of 0.79. Overall, our study indicated a positive attitude towards the use of telemedicine in northern Louisiana.

Public and Private School Distinction, Regional Development Differences, and Other Factors Influencing the Success of Primary School Students in Turkey

ERIC Educational Resources Information Center

Sulku, Seher Nur; Abdioglu, Zehra

2015-01-01

This study investigates the factors influencing the success of students in primary schools in Turkey. TIMSS 2011 data for Turkey, measuring the success of eighth-grade students in the field of mathematics, were used in an econometric analysis, performed using classical linear regression models. Two hundred thirty-nine schools participated in the…

Exploring the Factors Related to Acceptance of Evolutionary Theory among Turkish Preservice Biology Teachers: Toward a More Informative Conceptual Ecology for Biological Evolution

ERIC Educational Resources Information Center

Deniz, Hasan; Donnelly, Lisa A.; Yilmaz, Irfan

2008-01-01

In this study, using multiple regression analysis, we aimed to explore the factors related to acceptance of evolutionary theory among preservice Turkish biology teachers using conceptual ecology for biological evolution as a theoretical lens. We aimed to determine the extent to which we can account for the variance in acceptance of evolutionary…

A Comparative Analysis of the Effects of Instructional Design Factors on Student Success in E-Learning: Multiple-Regression versus Neural Networks

ERIC Educational Resources Information Center

Cebeci, Halil Ibrahim; Yazgan, Harun Resit; Geyik, Abdulkadir

2009-01-01

This study explores the relationship between the student performance and instructional design. The research was conducted at the E-Learning School at a university in Turkey. A list of design factors that had potential influence on student success was created through a review of the literature and interviews with relevant experts. From this, the…

Risk Factors for Drug Abuse among Nepalese Samples Selected from a Town of Eastern Nepal

ERIC Educational Resources Information Center

Niraula, Surya Raj; Chhetry, Devendra Bahadur; Singh, Girish Kumar; Nagesh, S.; Shyangwa, Pramod Mohan

2009-01-01

The study focuses on the serious issue related to the adolescents' and adults' behavior and health. It aims to identify the risk factors for drug abuse from samples taken from a town of Eastern Nepal. This is a matched case-control study. The conditional logistic regression method was adopted for data analysis. The diagnosis cut off was determined…

A refined method for multivariate meta-analysis and meta-regression.

PubMed

Jackson, Daniel; Riley, Richard D

2014-02-20

Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects' standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. Copyright © 2013 John Wiley & Sons, Ltd.

An evaluation of treatment strategies for head and neck cancer in an African American population.

PubMed

Ignacio, D N; Griffin, J J; Daniel, M G; Serlemitsos-Day, M T; Lombardo, F A; Alleyne, T A

2013-07-01

This study evaluated treatment strategies for head and neck cancers in a predominantly African American population. Data were collected utilizing medical records and the tumour registry at the Howard University Hospital. Kaplan-Meier method was used for survival analysis and Cox proportional hazards regression analysis predicted the hazard of death. Analysis revealed that the main treatment strategy was radiation combined with platinum for all stages except stage I. Cetuximab was employed in only 1% of cases. Kaplan-Meier analysis revealed stage II patients had poorer outcome than stage IV while Cox proportional hazard regression analysis (p = 0.4662) showed that stage I had a significantly lower hazard of death than stage IV (HR = 0.314; p = 0.0272). Contributory factors included tobacco and alcohol but body mass index (BMI) was inversely related to hazard of death. There was no difference in survival using any treatment modality for African Americans.

[On the effectiveness of the homeopathic remedy Arnica montana].

PubMed

Lüdtke, Rainer; Hacke, Daniela

2005-11-01

Arnica montana is a homeopathic remedy often prescribed after traumata and injuries. To assess whether Arnica is effective beyond placebo and to identify factors which support or contradict this effectiveness. All prospective, controlled trials on the effectiveness of homeopathic Arnica were included. Overall effectiveness was assessed by meta-analysis and meta-regression techniques. 68 comparisons from 49 clinical trials show a significant effectiveness of Arnica in traumatic injuries in random effects meta-analysis (odds ratio [OR], 0.36; 95% confidence interval [CI], 0.24-0.55), but not in meta-regression models (OR, 0.37; CI, 0.11-1.24). We found no evidence for publication bias. Studies from Medline-listed journals and high-quality studies are less likely to report positive results (p = 0.0006 and p = 0.0167). The hypothesis that homeopathic Arnica is effective could neither be proved nor rejected. All trials were highly heterogeneous, meta-regression does not help to explain this heterogeneity substantially.

[Factors Influencing Quality of Life of Alcoholics Anonymous Members in Korea].

PubMed

Yoo, Jae Soon; Lee, Jongeun; Park, Woo Young

2016-04-01

The purpose of this study was to determine quality of life (QOL) related factors in Alcoholics Anonymous (AA) members based on PRECEDE Model. A cross sectional survey was conducted with participants (N =203) from AA meeting in 11 alcohol counsel centers all over South Korea. Data were collected using a specially designed questionnaire based on the PRECEDE model and including QOL, epidemiological factors (including depression and perceived health status), behavioral factors (continuous abstinence and physical health status and practice), predisposing factors (abstinence self-efficacy and self-esteem), reinforcing factors (social capital and family functioning), and enabling factors. Data were analyzed using t-test, one way ANOVA, Tukey HSD test and hierarchical multiple regression analysis with SPSS (ver. 21.0). Of the educational diagnostic variables, self-esteem (β=.23), family functioning (β=.12), abstinence self-efficacy (β=.12) and social capital (β=.11) were strong influential factors in AA members' QOL. In addition, epidemiological diagnostic variables such as depression (β=-.44) and perceived health status (β=.35) were the main factors in QOL. Also, physical health status and practice (β=.106), one of behavioral diagnostic variables was a beneficial factor in QOL. Hierarchical multiple regression analysis showed the determinant variables accounted for 44.0% of the variation in QOL (F=25.76, p<.001). The finding of the study can be used as a framework for planning interventions in order to promote the quality of life of AA members. It is necessary to develop nursing intervention strategies for strengthening educational and epidemiological diagnostic variables in order to improve AA members' QOL.

Monitoring heavy metal Cr in soil based on hyperspectral data using regression analysis

NASA Astrophysics Data System (ADS)

Zhang, Ningyu; Xu, Fuyun; Zhuang, Shidong; He, Changwei

2016-10-01

Heavy metal pollution in soils is one of the most critical problems in the global ecology and environment safety nowadays. Hyperspectral remote sensing and its application is capable of high speed, low cost, less risk and less damage, and provides a good method for detecting heavy metals in soil. This paper proposed a new idea of applying regression analysis of stepwise multiple regression between the spectral data and monitoring the amount of heavy metal Cr by sample points in soil for environmental protection. In the measurement, a FieldSpec HandHeld spectroradiometer is used to collect reflectance spectra of sample points over the wavelength range of 325-1075 nm. Then the spectral data measured by the spectroradiometer is preprocessed to reduced the influence of the external factors, and the preprocessed methods include first-order differential equation, second-order differential equation and continuum removal method. The algorithms of stepwise multiple regression are established accordingly, and the accuracy of each equation is tested. The results showed that the accuracy of first-order differential equation works best, which makes it feasible to predict the content of heavy metal Cr by using stepwise multiple regression.

Social motivation in Qatari schools and their relation to school achievement.

PubMed

Nasser, Ramzi

2014-10-01

This study assessed the relation between school-social motivation and student academic achievement. A factor analysis was performed on a set of school-social items selected a priori from three measures of school motivation: the Inventory of School Motivation, the General Achievement Goals Orientation Scale, and the Facilitating Conditions Scale. Three factors with fewer items represented Global Motivation, Peer Help, and Social Power. Hierarchical regression analysis showed social motivation measures were weak predictors of achievement scores in the various content areas. Findings are discussed in the context of Qatari education and culture.

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data

PubMed Central

Ying, Gui-shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-01-01

Purpose To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. Methods We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field data in the elderly. Results When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI −0.03 to 0.32D, P=0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, P=0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller P-values, while analysis of the worse eye provided larger P-values than mixed effects models and marginal models. Conclusion In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision. PMID:28102741

Factors Associated with Salmonella Prevalence in U.S. Swine Grower-Finisher Operations, 2012.

PubMed

Bjork, Kathe E; Fields, Victoria; Garber, Lindsey P; Kopral, Christine A

2018-05-15

Nontyphoidal Salmonella is an important foodborne pathogen with diverse serotypes occurring in animal and human populations. The prevalence of the organism on swine farms has been associated with numerous risk factors, and although there are strong veterinary public health controls for preventing Salmonella from entering food, there remains interest in eradicating or controlling the organism in the preharvest environment. In this study, using data collected via the U.S. Department of Agriculture (USDA) National Animal Health Monitoring System Swine 2012 study, we describe nontyphoidal Salmonella and specific serotype prevalence on U.S. grower-finisher swine operations and investigate associations between Salmonella detection and numerous factors via multiple correspondence analysis (MCA) and regression analysis. MCA plots, complementary to univariate analyses, display relationships between covariates and Salmonella detection at the farm level. In the univariate analysis, Salmonella detection varied with feed characteristics and farm management practices, reports of diseases on farms and vaccinations administered, and administration of certain antimicrobials. Results from the univariate analysis reinforce the importance of biosecurity in managing diseases and pathogens such as Salmonella on farms. All multivariable regression models for the likelihood of Salmonella detection were strongly affected by multicollinearity among variables, and only one variable, pelleted feed preparation, remained in the final model. The study was limited by its cross-sectional nature, timelines of data collection, and reliance on operator-reported data via a convenience sample.

Product competitiveness analysis for e-commerce platform of special agricultural products

NASA Astrophysics Data System (ADS)

Wan, Fucheng; Ma, Ning; Yang, Dongwei; Xiong, Zhangyuan

2017-09-01

On the basis of analyzing the influence factors of the product competitiveness of the e-commerce platform of the special agricultural products and the characteristics of the analytical methods for the competitiveness of the special agricultural products, the price, the sales volume, the postage included service, the store reputation, the popularity, etc. were selected in this paper as the dimensionality for analyzing the competitiveness of the agricultural products, and the principal component factor analysis was taken as the competitiveness analysis method. Specifically, the web crawler was adopted to capture the information of various special agricultural products in the e-commerce platform ---- chi.taobao.com. Then, the original data captured thereby were preprocessed and MYSQL database was adopted to establish the information library for the special agricultural products. Then, the principal component factor analysis method was adopted to establish the analysis model for the competitiveness of the special agricultural products, and SPSS was adopted in the principal component factor analysis process to obtain the competitiveness evaluation factor system (support degree factor, price factor, service factor and evaluation factor) of the special agricultural products. Then, the linear regression method was adopted to establish the competitiveness index equation of the special agricultural products for estimating the competitiveness of the special agricultural products.

Psychosocial correlates of HIV protection motivation among black adolescents in Venda, South Africa.

PubMed

Boer, Henk; Mashamba, M Tshilidzi

2005-12-01

We assessed the usefulness of the theory of planned behavior (TPB) and protection motivation theory (PMT) to predict intended condom use among 201 adolescents from Venda, South Africa. Results indicated that both the TPB and the PMT could significantly predict intended condom use, although the level of explained variance was limited. Hierarchical regression analysis indicated that there was considerable overlap between the TPB and the PMT in predicting condom use intention. In the regression analysis that used both the TPB and the PMT variables subjective norms and response efficacy were positively related to intended condom use. The results indicated that both the TPB and the PMT were valuable in explaining intended condom use among African adolescents. The TPB made clear that the social environment is an important contextual factor, whereas the PMT made clear that response efficacy is positively related to condom use intention. The results of this study indicated that social cognition models have some value in the analysis of condom use intention of African adolescents, but the role of other factors like myths about condoms should be further examined.

The perception of the relationship between environment and health according to data from Italian Behavioural Risk Factor Surveillance System (PASSI).

PubMed

Sampaolo, Letizia; Tommaso, Giulia; Gherardi, Bianca; Carrozzi, Giuliano; Freni Sterrantino, Anna; Ottone, Marta; Goldoni, Carlo Alberto; Bertozzi, Nicoletta; Scaringi, Meri; Bolognesi, Lara; Masocco, Maria; Salmaso, Stefania; Lauriola, Paolo

2017-01-01

"OBJECTIVES: to identify groups of people in relation to the perception of environmental risk and to assess the main characteristics using data collected in the environmental module of the surveillance network Italian Behavioral Risk Factor Surveillance System (PASSI). perceptive profiles were identified using a latent class analysis; later they were included as outcome in multinomial logistic regression models to assess the association between environmental risk perception and demographic, health, socio-economic and behavioural variables. the latent class analysis allowed to split the sample in "worried", "indifferent", and "positive" people. The multinomial logistic regression model showed that the "worried" profile typically includes people of Italian nationality, living in highly urbanized areas, with a high level of education, and with economic difficulties; they pay special attention to their own health and fitness, but they have a negative perception of their own psychophysical state. the application of advanced statistical analysis enable to appraise PASSI data in order to characterize the perception of environmental risk, making the planning of interventions related to risk communication possible. ".

Regional danger assessment of Debris flow and its engineering mitigation practice in Sichuan-Tibet highway

NASA Astrophysics Data System (ADS)

Su, Pengcheng; Sun, Zhengchao; li, Yong

2017-04-01

Luding-Kangding highway cross the eastern edge of Qinghai-Tibet Plateau where belong to the most deep canyon area of plateau and mountains in western Sichuan with high mountain and steep slope. This area belongs to the intersection among Xianshuihe, Longmenshan and Anninghe fault zones which are best known in Sichuan province. In the region, seismic intensity is with high frequency and strength, new tectonic movement is strong, rock is cracked, there are much loose solid materials. Debris flow disaster is well developed under the multiple effects of the earthquake, strong rainfall and human activity which poses a great threat to the local people's life and property security. So this paper chooses Kangding and LuDing as the study area to do the debris flow hazard assessment through the in-depth analysis of development characteristics and formation mechanism of debris flow. Which can provide important evidence for local disaster assessment and early warning forecast. It also has the important scientific significance and practical value to safeguard the people's life and property safety and the security implementation of the national major project. In this article, occurrence mechanism of debris flow disasters in the study area is explored, factor of evaluation with high impact to debris flow hazards is identified, the database of initial evaluation factors is made by the evaluation unit of basin. The factors with high impact to hazards occurrence are selected by using the stepwise regression method of logistic regression model, at the same time the factors with low impact are eliminated, then the hazard evaluation factor system of debris flow is determined in the study area. Then every factors of evaluation factor system are quantified, and the weights of all evaluation factors are determined by using the analysis of stepwise regression. The debris flows hazard assessment and regionalization of all the whole study area are achieved eventually after establishing the hazard assessment model. In this paper, regional debris flows hazard assessment method with strong universality and reliable evaluation result is presented. The whole study area is divided into 1674 units by automatically extracting and artificial identification, and then 11 factors are selected as the initial assessment factors of debris flow hazard assessment in the study area. The factors of the evaluation index system are quantified using the method of standardized watershed unit amount ratio. The relationship between debris flow occurrence and each evaluation factor is simulated using logistic regression model. The weights of evaluation factors are determined, and the model of debris flows hazard assessment is established in the study area. Danger assessment result of debris flow was applied in line optimization and engineering disaster reduction of Sichuan-Tibet highway (section of Luding-Kangding).

The effect of first chromosome long arm duplication on survival of endometrial carcinoma.

PubMed

Sever, Erman; Doğer, Emek; Çakıroğlu, Yiğit; Sünnetçi, Deniz; Çine, Naci; Savlı, Hakan; Yücesoy, İzzet

2014-12-01

The aim of this study is to investigate the effect of first chromosome long arm duplication (dup(1q)) in cases with endometrial carcinoma detected with array based comperative genomic hybridization (aCGH) on survival from the cancer. A total of 53 patients with the diagnosis of endometrial carcinom due to endometrial biopsy and who have been operated for this reason have been allocated in the study. Frozen section biopsy and staging surgery have been performed for all the cases. Samples obtained from the tumoral mass have been investigated for chromosomal aberrations with aCGH method. Kaplan-Meier and Cox-regression analysis have been performed for survival analysis. Among 53 cases with endometrial carcinomas, dup(1q) was diagnosed in 14 (26.4%) of the cases. For the patient group that has been followed-up for 24 months (3-33 months), dup(1q) (p=.01), optimal cytoreduction (p<.001), lymph node positivity (p=.006), tumor stage >1 (p=.006) and presence of high risk tumor were the factors that were associated with survival. Cox-regression analysis has revealed that optimal cytoreduction was the most important prognostic factor (p=.02). Presence of 1q duplication can be used as a prognostic factor in the preoperative period.

The effect of first chromosome long arm duplication on survival of endometrial carcinoma

PubMed Central

Sever, Erman; Doğer, Emek; Çakıroğlu, Yiğit; Sünnetçi, Deniz; Çine, Naci; Savlı, Hakan; Yücesoy, İzzet

2014-01-01

Objective: The aim of this study is to investigate the effect of first chromosome long arm duplication (dup(1q)) in cases with endometrial carcinoma detected with array based comperative genomic hybridization (aCGH) on survival from the cancer. Materials and Methods: A total of 53 patients with the diagnosis of endometrial carcinom due to endometrial biopsy and who have been operated for this reason have been allocated in the study. Frozen section biopsy and staging surgery have been performed for all the cases. Samples obtained from the tumoral mass have been investigated for chromosomal aberrations with aCGH method. Kaplan-Meier and Cox-regression analysis have been performed for survival analysis. Results: Among 53 cases with endometrial carcinomas, dup(1q) was diagnosed in 14 (26.4%) of the cases. For the patient group that has been followed-up for 24 months (3-33 months), dup(1q) (p=.01), optimal cytoreduction (p<.001), lymph node positivity (p=.006), tumor stage >1 (p=.006) and presence of high risk tumor were the factors that were associated with survival. Cox-regression analysis has revealed that optimal cytoreduction was the most important prognostic factor (p=.02). Conclusion: Presence of 1q duplication can be used as a prognostic factor in the preoperative period. PMID:28913021

Nursing home cost and ownership type: evidence of interaction effects.

PubMed

Arling, G; Nordquist, R H; Capitman, J A

1987-06-01

Due to steadily increasing public expenditures for nursing home care, much research has focused on factors that influence nursing home costs, especially for Medicaid patients. Nursing home cost function studies have typically used a number of predictor variables in a multiple regression analysis to determine the effect of these variables on operating cost. Although several authors have suggested that nursing home ownership types have different goal orientations, not necessarily based on economic factors, little attention has been paid to this issue in empirical research. In this study, data from 150 Virginia nursing homes were used in multiple regression analysis to examine factors accounting for nursing home operating costs. The context of the study was the Virginia Medicaid reimbursement system, which has intermediate care and skilled nursing facility (ICF and SNF) facility-specific per diem rates, set according to facility cost histories. The analysis revealed interaction effects between ownership and other predictor variables (e.g., percentage Medicaid residents, case mix, and region), with predictor variables having different effects on cost depending on ownership type. Conclusions are drawn about the goal orientations and behavior of chain-operated, individual for-profit, and public and nonprofit facilities. The implications of these findings for long-term care reimbursement policies are discussed.

Nursing home cost and ownership type: evidence of interaction effects.

PubMed Central

Arling, G; Nordquist, R H; Capitman, J A

1987-01-01

Due to steadily increasing public expenditures for nursing home care, much research has focused on factors that influence nursing home costs, especially for Medicaid patients. Nursing home cost function studies have typically used a number of predictor variables in a multiple regression analysis to determine the effect of these variables on operating cost. Although several authors have suggested that nursing home ownership types have different goal orientations, not necessarily based on economic factors, little attention has been paid to this issue in empirical research. In this study, data from 150 Virginia nursing homes were used in multiple regression analysis to examine factors accounting for nursing home operating costs. The context of the study was the Virginia Medicaid reimbursement system, which has intermediate care and skilled nursing facility (ICF and SNF) facility-specific per diem rates, set according to facility cost histories. The analysis revealed interaction effects between ownership and other predictor variables (e.g., percentage Medicaid residents, case mix, and region), with predictor variables having different effects on cost depending on ownership type. Conclusions are drawn about the goal orientations and behavior of chain-operated, individual for-profit, and public and nonprofit facilities. The implications of these findings for long-term care reimbursement policies are discussed. PMID:3301746

Factors Affecting Seedling Survivorship of Blue Oak (Quercus douglasii H. & A.) in Central California

Treesearch

Frank W. Davis; Mark Borchert; L. E. Harvey; Joel C. Michaelsen

1991-01-01

Blue oak seedling mortality was studied in relation to vertebrate predators, initial acorn planting position, slope and aspect, and oak canopy cover at two sites in the Central Coast Ranges of California. Seedling survival rates (Psd) were related to treatment variables using logistic regression analysis. Analysis of 2842 seedlings for 3 years following establishment...

Spatial analysis of alcohol-related motor vehicle crash injuries in southeastern Michigan.

PubMed

Meliker, Jaymie R; Maio, Ronald F; Zimmerman, Marc A; Kim, Hyungjin Myra; Smith, Sarah C; Wilson, Mark L

2004-11-01

Temporal, behavioral and social risk factors that affect injuries resulting from alcohol-related motor vehicle crashes have been characterized in previous research. Much less is known about spatial patterns and environmental associations of alcohol-related motor vehicle crashes. The aim of this study was to evaluate geographic patterns of alcohol-related motor vehicle crashes and to determine if locations of alcohol outlets are associated with those crashes. In addition, we sought to demonstrate the value of integrating spatial and traditional statistical techniques in the analysis of this preventable public health risk. The study design was a cross-sectional analysis of individual-level blood alcohol content, traffic report information, census block group data, and alcohol distribution outlets. Besag and Newell's spatial analysis and traditional logistic regression both indicated that areas of low population density had more alcohol-related motor vehicle crashes than expected (P < 0.05). There was no significant association between alcohol outlets and alcohol-related motor vehicle crashes using distance analyses, logistic regression, and Chi-square. Differences in environmental or behavioral factors characteristic of areas of low population density may be responsible for the higher proportion of alcohol-related crashes occurring in these areas.

Deletion Diagnostics for Alternating Logistic Regressions

PubMed Central

Preisser, John S.; By, Kunthel; Perin, Jamie; Qaqish, Bahjat F.

2013-01-01

Deletion diagnostics are introduced for the regression analysis of clustered binary outcomes estimated with alternating logistic regressions, an implementation of generalized estimating equations (GEE) that estimates regression coefficients in a marginal mean model and in a model for the intracluster association given by the log odds ratio. The diagnostics are developed within an estimating equations framework that recasts the estimating functions for association parameters based upon conditional residuals into equivalent functions based upon marginal residuals. Extensions of earlier work on GEE diagnostics follow directly, including computational formulae for one-step deletion diagnostics that measure the influence of a cluster of observations on the estimated regression parameters and on the overall marginal mean or association model fit. The diagnostic formulae are evaluated with simulations studies and with an application concerning an assessment of factors associated with health maintenance visits in primary care medical practices. The application and the simulations demonstrate that the proposed cluster-deletion diagnostics for alternating logistic regressions are good approximations of their exact fully iterated counterparts. PMID:22777960

The effect of postoperative medical treatment on left ventricular mass regression after aortic valve replacement.

PubMed

Helder, Meghana R K; Ugur, Murat; Bavaria, Joseph E; Kshettry, Vibhu R; Groh, Mark A; Petracek, Michael R; Jones, Kent W; Suri, Rakesh M; Schaff, Hartzell V

2015-03-01

The study objective was to analyze factors associated with left ventricular mass regression in patients undergoing aortic valve replacement with a newer bioprosthesis, the Trifecta valve pericardial bioprosthesis (St Jude Medical Inc, St Paul, Minn). A total of 444 patients underwent aortic valve replacement with the Trifecta bioprosthesis from 2007 to 2009 at 6 US institutions. The clinical and echocardiographic data of 200 of these patients who had left ventricular hypertrophy and follow-up studies 1 year postoperatively were reviewed and compared to analyze factors affecting left ventricular mass regression. Mean (standard deviation) age of the 200 study patients was 73 (9) years, 66% were men, and 92% had pure or predominant aortic valve stenosis. Complete left ventricular mass regression was observed in 102 patients (51%) by 1 year postoperatively. In univariate analysis, male sex, implantation of larger valves, larger left ventricular end-diastolic volume, and beta-blocker or calcium-channel blocker treatment at dismissal were significantly associated with complete mass regression. In the multivariate model, odds ratios (95% confidence intervals) indicated that male sex (3.38 [1.39-8.26]) and beta-blocker or calcium-channel blocker treatment at dismissal (3.41 [1.40-8.34]) were associated with increased probability of complete left ventricular mass regression. Patients with higher preoperative systolic blood pressure were less likely to have complete left ventricular mass regression (0.98 [0.97-0.99]). Among patients with left ventricular hypertrophy, postoperative treatment with beta-blockers or calcium-channel blockers may enhance mass regression. This highlights the need for close medical follow-up after operation. Labeled valve size was not predictive of left ventricular mass regression. Copyright © 2015 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

STATISTICAL METHOD FOR DETECTION OF A TREND IN ATMOSPHERIC SULFATE

EPA Science Inventory

Daily atmospheric concentrations of sulfate collected in northeastern Pennsylvania are regressed against meteorological factors, ozone, and time in order to determine if a significant trend in sulfate can be detected. he data used in this analysis were collected during the Sulfat...

A comparison between univariate probabilistic and multivariate (logistic regression) methods for landslide susceptibility analysis: the example of the Febbraro valley (Northern Alps, Italy)

NASA Astrophysics Data System (ADS)

Rossi, M.; Apuani, T.; Felletti, F.

2009-04-01

The aim of this paper is to compare the results of two statistical methods for landslide susceptibility analysis: 1) univariate probabilistic method based on landslide susceptibility index, 2) multivariate method (logistic regression). The study area is the Febbraro valley, located in the central Italian Alps, where different types of metamorphic rocks croup out. On the eastern part of the studied basin a quaternary cover represented by colluvial and secondarily, by glacial deposits, is dominant. In this study 110 earth flows, mainly located toward NE portion of the catchment, were analyzed. They involve only the colluvial deposits and their extension mainly ranges from 36 to 3173 m2. Both statistical methods require to establish a spatial database, in which each landslide is described by several parameters that can be assigned using a main scarp central point of landslide. The spatial database is constructed using a Geographical Information System (GIS). Each landslide is described by several parameters corresponding to the value of main scarp central point of the landslide. Based on bibliographic review a total of 15 predisposing factors were utilized. The width of the intervals, in which the maps of the predisposing factors have to be reclassified, has been defined assuming constant intervals to: elevation (100 m), slope (5 °), solar radiation (0.1 MJ/cm2/year), profile curvature (1.2 1/m), tangential curvature (2.2 1/m), drainage density (0.5), lineament density (0.00126). For the other parameters have been used the results of the probability-probability plots analysis and the statistical indexes of landslides site. In particular slope length (0 ÷ 2, 2 ÷ 5, 5 ÷ 10, 10 ÷ 20, 20 ÷ 35, 35 ÷ 260), accumulation flow (0 ÷ 1, 1 ÷ 2, 2 ÷ 5, 5 ÷ 12, 12 ÷ 60, 60 ÷27265), Topographic Wetness Index 0 ÷ 0.74, 0.74 ÷ 1.94, 1.94 ÷ 2.62, 2.62 ÷ 3.48, 3.48 ÷ 6,00, 6.00 ÷ 9.44), Stream Power Index (0 ÷ 0.64, 0.64 ÷ 1.28, 1.28 ÷ 1.81, 1.81 ÷ 4.20, 4.20 ÷ 9.40). Geological map and land use map were also used, considering geological and land use properties as categorical variables. Appling the univariate probabilistic method the Landslide Susceptibility Index (LSI) is defined as the sum of the ratio Ra/Rb calculated for each predisposing factor, where Ra is the ratio between number of pixel of class and the total number of pixel of the study area, and Rb is the ratio between number of landslides respect to the pixel number of the interval area. From the analysis of the Ra/Rb ratio the relationship between landslide occurrence and predisposing factors were defined. Then the equation of LSI was used in GIS to trace the landslide susceptibility maps. The multivariate method for landslide susceptibility analysis, based on logistic regression, was performed starting from the density maps of the predisposing factors, calculated with the intervals defined above using the equation Rb/Rbtot, where Rbtot is a sum of all Rb values. Using stepwise forward algorithms the logistic regression was performed in two successive steps: first a univariate logistic regression is used to choose the most significant predisposing factors, then the multivariate logistic regression can be performed. The univariate regression highlighted the importance of the following factors: elevation, accumulation flow, drainage density, lineament density, geology and land use. When the multivariate regression was applied the number of controlling factors was reduced neglecting the geological properties. The resulting final susceptibility equation is: P = 1 / (1 + exp-(6.46-22.34*elevation-5.33*accumulation flow-7.99* drainage density-4.47*lineament density-17.31*land use)) and using this equation the susceptibility maps were obtained. To easy compare the results of the two methodologies, the susceptibility maps were reclassified in five susceptibility intervals (very high, high, moderate, low and very low) using natural breaks. Then the maps were validated using two cumulative distribution curves, one related to the landslides (number of landslides in each susceptibility class) and one to the basin (number of pixel covering each class). Comparing the curves for each method, it results that the two approaches (univariate and multivariate) are appropriate, providing acceptable results. In both maps the distribution of high susceptibility condition is mainly localized on the left slope of the catchment in agreement with the field evidences. The comparison between the methods was obtained by subtraction of the two maps. This operation shows that about 40% of the basin is classified by the same class of susceptibility. In general the univariate probabilistic method tends to overestimate the areal extension of the high susceptibility class with respect to the maps obtained by the logistic regression method.

Threshold altitude resulting in decompression sickness

NASA Technical Reports Server (NTRS)

Kumar, K. V.; Waligora, James M.; Calkins, Dick S.

1990-01-01

A review of case reports, hypobaric chamber training data, and experimental evidence indicated that the threshold for incidence of altitude decompression sickness (DCS) was influenced by various factors such as prior denitrogenation, exercise or rest, and period of exposure, in addition to individual susceptibility. Fitting these data with appropriate statistical models makes it possible to examine the influence of various factors on the threshold for DCS. This approach was illustrated by logistic regression analysis on the incidence of DCS below 9144 m. Estimations using these regressions showed that, under a noprebreathe, 6-h exposure, simulated EVA profile, the threshold for symptoms occurred at approximately 3353 m; while under a noprebreathe, 2-h exposure profile with knee-bends exercise, the threshold occurred at 7925 m.

Risk and protective factors for psychological distress among adolescents: a family study in the Nord-Trøndelag Health Study.

PubMed

Myklestad, Ingri; Røysamb, Espen; Tambs, Kristian

2012-05-01

The study aimed to investigate potential adolescent and parental psychosocial risk and protective factors for psychological distress among adolescents and, in addition, to examine potential gender and age differences in the effects of risk factors on adolescent psychological distress. Data were collected among 8,984 Norwegian adolescents (13-19 years) and their parents in the Nord-Trøndelag Health Study (HUNT). The outcome measure was psychological distress (SCL-5). Bivariate regression analysis with generalized estimating equation (GEE) model showed that all parental self-reported variables (mental distress, substance use, social network, economic problems, unemployment and family structure) and adolescents' self-reported variables (leisure activities, social support from friends, school-related problems and substance use) were significantly associated with psychological distress among adolescents. Results revealed that in a multiple regression analysis with a GEE model, adolescent psychosocial variables, specifically academic-related problems and being bullied at school, emerged as the strongest predictors of psychological distress among adolescents after controlling for age, gender, and all parental and adolescent variables. The following psychosocial risk factors were significantly more important for girl's psychological distress compared to boys: problems with academic achievement, conduct problems in school, frequency of being drunk, smoking, dissatisfaction in school, living alone and seen parents being drunk. Academic achievement and being bullied at school were the psychosocial factors most strongly associated with psychological distress among adolescents. Parental factors had an indirect effect on adolescent psychological distress, through adolescents' psychosocial factors.

Analysis of a Split-Plot Experimental Design Applied to a Low-Speed Wind Tunnel Investigation

NASA Technical Reports Server (NTRS)

Erickson, Gary E.

2013-01-01

A procedure to analyze a split-plot experimental design featuring two input factors, two levels of randomization, and two error structures in a low-speed wind tunnel investigation of a small-scale model of a fighter airplane configuration is described in this report. Standard commercially-available statistical software was used to analyze the test results obtained in a randomization-restricted environment often encountered in wind tunnel testing. The input factors were differential horizontal stabilizer incidence and the angle of attack. The response variables were the aerodynamic coefficients of lift, drag, and pitching moment. Using split-plot terminology, the whole plot, or difficult-to-change, factor was the differential horizontal stabilizer incidence, and the subplot, or easy-to-change, factor was the angle of attack. The whole plot and subplot factors were both tested at three levels. Degrees of freedom for the whole plot error were provided by replication in the form of three blocks, or replicates, which were intended to simulate three consecutive days of wind tunnel facility operation. The analysis was conducted in three stages, which yielded the estimated mean squares, multiple regression function coefficients, and corresponding tests of significance for all individual terms at the whole plot and subplot levels for the three aerodynamic response variables. The estimated regression functions included main effects and two-factor interaction for the lift coefficient, main effects, two-factor interaction, and quadratic effects for the drag coefficient, and only main effects for the pitching moment coefficient.

Should the poor have no medicines to cure? A study on the association between social class and social security among the rural migrant workers in urban China.

PubMed

Guan, Ming

2017-11-07

The rampant urbanization and medical marketization in China have resulted in increased vulnerabilities to health and socioeconomic disparities among the rural migrant workers in urban China. In the Chinese context, the socioeconomic characteristics of rural migrant workers have attracted considerable research attention in the recent past years. However, to date, no previous studies have explored the association between the socioeconomic factors and social security among the rural migrant workers in urban China. This study aims to explore the association between socioeconomic inequity and social security inequity and the subsequent associations with medical inequity and reimbursement rejection. Data from a regionally representative sample of 2009 Survey of Migrant Workers in Pearl River Delta in China were used for analyses. Multiple logistic regressions were used to analyze the impacts of socioeconomic factors on the eight dimensions of social security (sick pay, paid leave, maternity pay, medical insurance, pension insurance, occupational injury insurance, unemployment insurance, and maternity insurance) and the impacts of social security on medical reimbursement rejection. The zero-inflated negative binomial regression model (ZINB regression) was adopted to explore the relationship between socioeconomic factors and hospital visits among the rural migrant workers with social security. The study population consisted of 848 rural migrant workers with high income who were young and middle-aged, low-educated, and covered by social security. Reimbursement rejection and abusive supervision for the rural migrant workers were observed. Logistic regression analysis showed that there were significant associations between socioeconomic factors and social security. ZINB regression showed that there were significant associations between socioeconomic factors and hospital visits among the rural migrant workers. Also, several dimensions of social security had significant associations with reimbursement rejections. This study showed that social security inequity, medical inequity, and reimbursement inequity happened to the rural migrant workers simultaneously. Future policy should strengthen health justice and enterprises' medical responsibilities to the employed rural migrant workers.

Multivariate analysis on unilateral cleft lip and palate treatment outcome by EUROCRAN index: A retrospective study.

PubMed

Yew, Ching Ching; Alam, Mohammad Khursheed; Rahman, Shaifulizan Abdul

2016-10-01

This study is to evaluate the dental arch relationship and palatal morphology of unilateral cleft lip and palate patients by using EUROCRAN index, and to assess the factors that affect them using multivariate statistical analysis. A total of one hundred and seven patients from age five to twelve years old with non-syndromic unilateral cleft lip and palate were included in the study. These patients have received cheiloplasty and one stage palatoplasty surgery but yet to receive alveolar bone grafting procedure. Five assessors trained in the use of the EUROCRAN index underwent calibration exercise and ranked the dental arch relationships and palatal morphology of the patients' study models. For intra-rater agreement, the examiners scored the models twice, with two weeks interval in between sessions. Variable factors of the patients were collected and they included gender, site, type and, family history of unilateral cleft lip and palate; absence of lateral incisor on cleft side, cheiloplasty and palatoplasty technique used. Associations between various factors and dental arch relationships were assessed using logistic regression analysis. Dental arch relationship among unilateral cleft lip and palate in local population had relatively worse scoring than other parts of the world. Crude logistics regression analysis did not demonstrate any significant associations among the various socio-demographic factors, cheiloplasty and palatoplasty techniques used with the dental arch relationship outcome. This study has limitations that might have affected the results, example: having multiple operators performing the surgeries and the inability to access the influence of underlying genetic predisposed cranio-facial variability. These may have substantial influence on the treatment outcome. The factors that can affect unilateral cleft lip and palate treatment outcome is multifactorial in nature and remained controversial in general. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Disorganized Symptoms Predicted Worse Functioning Outcome in Schizophrenia Patients with Established Illness.

PubMed

Ortiz, Bruno Bertolucci; Gadelha, Ary; Higuchi, Cinthia Hiroko; Noto, Cristiano; Medeiros, Daiane; Pitta, José Cássio do Nascimento; de Araújo Filho, Gerardo Maria; Hallak, Jaime Eduardo Cecílio; Bressan, Rodrigo Affonseca

Most patients with schizophrenia will have subsequent relapses of the disorder, with continuous impairments in functioning. However, evidence is lacking on how symptoms influence functioning at different phases of the disease. This study aims to investigate the relationship between symptom dimensions and functioning at different phases: acute exacerbation, nonremission and remission. Patients with schizophrenia were grouped into acutely ill (n=89), not remitted (n=89), and remitted (n=69). Three exploratory stepwise linear regression analyses were performed for each phase of schizophrenia, in which the five PANSS factors and demographic variables were entered as the independent variables and the total Global Assessment of Functioning Scale (GAF) score was entered as the dependent variable. An additional exploratory stepwise logistic regression analysis was performed to predict subsequent remission at discharge in the inpatient population. The Disorganized factor was the most significant predictor for acutely ill patients (p<0.001), while the Hostility factor was the most significant for not-remitted patients and the Negative factor was the most significant for remitted patients (p=0.001 and p<0.001, respectively). In the logistic regression, the Disorganized factor score presented a significant negative association with remission (p=0.007). Higher disorganization symptoms showed the greatest impact in functioning at acute phase, and prevented patients from achieving remission, suggesting it may be a marker of symptom severity and worse outcome in schizophrenia.

Modified physiologically equivalent temperature—basics and applications for western European climate

NASA Astrophysics Data System (ADS)

Chen, Yung-Chang; Matzarakis, Andreas

2018-05-01

A new thermal index, the modified physiologically equivalent temperature (mPET) has been developed for universal application in different climate zones. The mPET has been improved against the weaknesses of the original physiologically equivalent temperature (PET) by enhancing evaluation of the humidity and clothing variability. The principles of mPET and differences between original PET and mPET are introduced and discussed in this study. Furthermore, this study has also evidenced the usability of mPET with climatic data in Freiburg, which is located in Western Europe. Comparisons of PET, mPET, and Universal Thermal Climate Index (UTCI) have shown that mPET gives a more realistic estimation of human thermal sensation than the other two thermal indices (PET, UTCI) for the thermal conditions in Freiburg. Additionally, a comparison of physiological parameters between mPET model and PET model (Munich Energy Balance Model for Individual, namely MEMI) is proposed. The core temperatures and skin temperatures of PET model vary more violently to a low temperature during cold stress than the mPET model. It can be regarded as that the mPET model gives a more realistic core temperature and mean skin temperature than the PET model. Statistical regression analysis of mPET based on the air temperature, mean radiant temperature, vapor pressure, and wind speed has been carried out. The R square (0.995) has shown a well co-relationship between human biometeorological factors and mPET. The regression coefficient of each factor represents the influence of the each factor on changing mPET (i.e., ±1 °C of T a = ± 0.54 °C of mPET). The first-order regression has been considered predicting a more realistic estimation of mPET at Freiburg during 2003 than the other higher order regression model, because the predicted mPET from the first-order regression has less difference from mPET calculated from measurement data. Statistic tests recognize that mPET can effectively evaluate the influences of all human biometeorological factors on thermal environments. Moreover, a first-order regression function can also predict the thermal evaluations of the mPET by using human biometeorological factors in Freiburg.

Comparison of the Chiron Quantiplex branched DNA (bDNA) assay and the Abbott Genostics solution hybridization assay for quantification of hepatitis B viral DNA.

PubMed

Kapke, G E; Watson, G; Sheffler, S; Hunt, D; Frederick, C

1997-01-01

Several assays for quantification of DNA have been developed and are currently used in research and clinical laboratories. However, comparison of assay results has been difficult owing to the use of different standards and units of measurements as well as differences between assays in dynamic range and quantification limits. Although a few studies have compared results generated by different assays, there has been no consensus on conversion factors and thorough analysis has been precluded by small sample size and limited dynamic range studied. In this study, we have compared the Chiron branched DNA (bDNA) and Abbott liquid hybridization assays for quantification of hepatitis B virus (HBV) DNA in clinical specimens and have derived conversion factors to facilitate comparison of assay results. Additivity and variance stabilizing (AVAS) regression, a form of non-linear regression analysis, was performed on assay results for specimens from HBV clinical trials. Our results show that there is a strong linear relationship (R2 = 0.96) between log Chiron and log Abbott assay results. Conversion factors derived from regression analyses were found to be non-constant and ranged from 6-40. Analysis of paired assay results below and above each assay's limit of quantification (LOQ) indicated that a significantly (P < 0.01) larger proportion of observations were below the Abbott assay LOQ but above the Chiron assay LOQ, indicating that the Chiron assay is significantly more sensitive than the Abbott assay. Testing of replicate specimens showed that the Chiron assay consistently yielded lower per cent coefficients of variance (% CVs) than the Abbott assay, indicating that the Chiron assay provides superior precision.

Predictors of pharmacological treatment outcomes with atomoxetine or methylphenidate in patients with attention-deficit/hyperactivity disorder from China, Egypt, Lebanon, Russian Federation, Taiwan, and United Arab Emirates.

PubMed

Treuer, T; Feng, Q; Desaiah, D; Altin, M; Wu, S; El-Shafei, A; Serebryakova, E; Gado, M; Faries, D

2014-09-01

The reduced availability of data from non-Western countries limits our ability to understand attention-deficit/hyperactivity disorder (ADHD) treatment outcomes, specifically, adherence and persistence of ADHD in children and adolescents. This analysis assessed predictors of treatment outcomes in a non-Western cohort of patients with ADHD treated with atomoxetine or methylphenidate. Data from a 12-month, prospective, observational study in outpatients aged 6-17 years treated with atomoxetine (N = 234) or methylphenidate (N = 221) were analysed post hoc to determine potential predictors of treatment outcomes. Participating countries included the Russian Federation, China, Taiwan, Egypt, United Arab Emirates and Lebanon. Factors associated with remission were analysed with stepwise multiple logistic regression and classification and regression trees (CART). Cox proportional hazards models with propensity score adjustment assessed differences in atomoxetine persistence among initial-dose cohorts. In patients treated with atomoxetine who had available dosing information (N = 134), Cox proportional hazards revealed lower (< 0.5 mg/kg) initial dose was significantly associated with shorter medication persistence (p < 0.01). multiple logistic regression analysis revealed greater rates of remission for atomoxetine-treated patients were associated with age (older), country (United Arab Emirates) and gender (female) (all p < 0.05). CART analysis confirmed older age and lack of specific phobias were associated with greater remission rates. For methylphenidate, greater baseline weight (highly correlated with the age factor found for atomoxetine) and prior atomoxetine use were associated with greater remission rates. These findings may help clinicians assess factors upon initiation of ADHD treatment to improve course prediction, proper dosing and treatment adherence and persistence. Observational study, therefore no registration. © 2014 John Wiley & Sons Ltd.

Logistic regression analysis of psychosocial correlates associated with recovery from schizophrenia in a Chinese community.

PubMed

Tse, Samson; Davidson, Larry; Chung, Ka-Fai; Yu, Chong Ho; Ng, King Lam; Tsoi, Emily

2015-02-01

More mental health services are adopting the recovery paradigm. This study adds to prior research by (a) using measures of stages of recovery and elements of recovery that were designed and validated in a non-Western, Chinese culture and (b) testing which demographic factors predict advanced recovery and whether placing importance on certain elements predicts advanced recovery. We examined recovery and factors associated with recovery among 75 Hong Kong adults who were diagnosed with schizophrenia and assessed to be in clinical remission. Data were collected on socio-demographic factors, recovery stages and elements associated with recovery. Logistic regression analysis was used to identify variables that could best predict stages of recovery. Receiver operating characteristic curves were used to detect the classification accuracy of the model (i.e. rates of correct classification of stages of recovery). Logistic regression results indicated that stages of recovery could be distinguished with reasonable accuracy for Stage 3 ('living with disability', classification accuracy = 75.45%) and Stage 4 ('living beyond disability', classification accuracy = 75.50%). However, there was no sufficient information to predict Combined Stages 1 and 2 ('overwhelmed by disability' and 'struggling with disability'). It was found that having a meaningful role and age were the most important differentiators of recovery stage. Preliminary findings suggest that adopting salient life roles personally is important to recovery and that this component should be incorporated into mental health services. © The Author(s) 2014.

On self-propagating methodological flaws in performance normalization for strength and power sports.

PubMed

Arandjelović, Ognjen

2013-06-01

Performance in strength and power sports is greatly affected by a variety of anthropometric factors. The goal of performance normalization is to factor out the effects of confounding factors and compute a canonical (normalized) performance measure from the observed absolute performance. Performance normalization is applied in the ranking of elite athletes, as well as in the early stages of youth talent selection. Consequently, it is crucial that the process is principled and fair. The corpus of previous work on this topic, which is significant, is uniform in the methodology adopted. Performance normalization is universally reduced to a regression task: the collected performance data are used to fit a regression function that is then used to scale future performances. The present article demonstrates that this approach is fundamentally flawed. It inherently creates a bias that unfairly penalizes athletes with certain allometric characteristics, and, by virtue of its adoption in the ranking and selection of elite athletes, propagates and strengthens this bias over time. The main flaws are shown to originate in the criteria for selecting the data used for regression, as well as in the manner in which the regression model is applied in normalization. This analysis brings into light the aforesaid methodological flaws and motivates further work on the development of principled methods, the foundations of which are also laid out in this work.

Associations of body mass index with cancer incidence among populations, genders, and menopausal status: A systematic review and meta-analysis.

PubMed

Wang, Jun; Yang, Dong-Lin; Chen, Zhong-Zhu; Gou, Ben-Fu

2016-06-01

In order to further reveal the differences of association between body mass index (BMI) and cancer incidence across populations, genders, and menopausal status, we performed comprehensive meta-analysis with eligible citations. The risk ratio (RR) of incidence at 10 different cancer sites (per 5kg/m(2) increase in BMI) were quantified separately by employing generalized least-squares to estimate trends, and combined by meta-analyses. We observed significantly stronger association between increased BMI and breast cancer incidence in the Asia-Pacific group (RR 1.18:1.11-1.26) than in European-Australian (1.05:1.00-1.09) and North-American group (1.06:1.03-1.08) (meta-regression p<0.05). No association between increased BMI and pancreatic cancer incidence (0.94:0.71-1.24) was shown in the Asia-Pacific group (meta-regression p<0.05), whereas positive associations were found in other two groups. A significantly higher RR in men was found for colorectal cancer in comparison with women (meta-regression p<0.05). Compared with postmenopausal women, premenopausal women displayed significantly higher RR for ovarian cancer (pre- vs. post-=1.10 vs. 1.01, meta-regression p<0.05), but lower RR for breast cancer (pre- vs. post-=0.99 vs. 1.11, meta-regression p<0.0001). Our results indicate that overweight or obesity is a strong risk factor of cancer incidence at several cancer sites. Genders, populations, and menopausal status are important factors effecting the association between obesity and cancer incidence for certain cancer types. Copyright © 2016 Elsevier Ltd. All rights reserved.

Are math readiness and personality predictive of first-year retention in engineering?

PubMed

Moses, Laurie; Hall, Cathy; Wuensch, Karl; De Urquidi, Karen; Kauffmann, Paul; Swart, William; Duncan, Steve; Dixon, Gene

2011-01-01

On the basis of J. G. Borkowski, L. K. Chan, and N. Muthukrishna's model of academic success (2000), the present authors hypothesized that freshman retention in an engineering program would be related to not only basic aptitude but also affective factors. Participants were 129 college freshmen with engineering as their stated major. Aptitude was measured by SAT verbal and math scores, high school grade-point average (GPA), and an assessment of calculus readiness. Affective factors were assessed by the NEO-Five Factor Inventory (FFI; P. I. Costa & R. R. McCrae, 2007), and the Nowicki-Duke Locus of Control (LOC) scale (S. Nowicki & M. Duke, 1974). A binary logistic regression analysis found that calculus readiness and high school GPA were predictive of retention. Scores on the Neuroticism and Openness subscales from the NEO-FFI and LOC were correlated with retention status, but Openness was the only affective factor with a significant unique effect in the binary logistic regression. Results of the study lend modest support to Borkowski's model.

The influence of intrinsic and extrinsic job values on turnover intention among continuing care assistants in Nova Scotia.

PubMed

Dill, Donna M; Keefe, Janice M; McGrath, Daniel S

2012-01-01

This article examines the influence that intrinsic and extrinsic job values have on the turnover intention of continuing care assistants (CCAs) who work either in home care or facility-based care in Nova Scotia (n = 188). Factor analysis of job values identified three latent job values structures: "compensation and commitment," "flexibility and opportunity," and "positive work relationships." Using binary logistic regression, we examined the predictive utility of these factors on two indices of turnover intention. Regression results indicate that, in general, job values constructs did not significantly predict turnover intention when controlling for demographics and job characteristics. However, a trend was found for the "positive work relationships" factor in predicting consideration of changing employers. In addition, CCAs who work in facility-based care were significantly more likely to have considered leaving their current employer. With projected increases in the demand for these workers in both home and continuing care, more attention is needed to identify and address factors to reduce turnover intention.

[Spatial differentiation and impact factors of Yutian Oasis's soil surface salt based on GWR model].

PubMed

Yuan, Yu Yun; Wahap, Halik; Guan, Jing Yun; Lu, Long Hui; Zhang, Qin Qin

2016-10-01

In this paper, topsoil salinity data gathered from 24 sampling sites in the Yutian Oasis were used, nine different kinds of environmental variables closely related to soil salinity were selec-ted as influencing factors, then, the spatial distribution characteristics of topsoil salinity and spatial heterogeneity of influencing factors were analyzed by combining the spatial autocorrelation with traditional regression analysis and geographically weighted regression model. Results showed that the topsoil salinity in Yutian Oasis was not of random distribution but had strong spatial dependence, and the spatial autocorrelation index for topsoil salinity was 0.479. Groundwater salinity, groundwater depth, elevation and temperature were the main factors influencing topsoil salt accumulation in arid land oases and they were spatially heterogeneous. The nine selected environmental variables except soil pH had significant influences on topsoil salinity with spatial disparity. GWR model was superior to the OLS model on interpretation and estimation of spatial non-stationary data, also had a remarkable advantage in visualization of modeling parameters.

Hip fractures are risky business: an analysis of the NSQIP data.

PubMed

Sathiyakumar, Vasanth; Greenberg, Sarah E; Molina, Cesar S; Thakore, Rachel V; Obremskey, William T; Sethi, Manish K

2015-04-01

Hip fractures are one of the most common types of orthopaedic injury with high rates of morbidity. Currently, no study has compared risk factors and adverse events following the different types of hip fracture surgeries. The purpose of this paper is to investigate the major and minor adverse events and risk factors for complication development associated with five common surgeries for the treatment of hip fractures using the NSQIP database. Using the ACS-NSQIP database, complications for five forms of hip surgeries were selected and categorized into major and minor adverse events. Demographics and clinical variables were collected and an unadjusted bivariate logistic regression analyses was performed to determine significant risk factors for adverse events. Five multivariate regressions were run for each surgery as well as a combined regression analysis. A total of 9640 patients undergoing surgery for hip fracture were identified with an adverse events rate of 25.2% (n=2433). Open reduction and internal fixation of a femoral neck fracture had the greatest percentage of all major events (16.6%) and total adverse events (27.4%), whereas partial hip hemiarthroplasty had the greatest percentage of all minor events (11.6%). Mortality was the most common major adverse event (44.9-50.6%). For minor complications, urinary tract infections were the most common minor adverse event (52.7-62.6%). Significant risk factors for development of any adverse event included age, BMI, gender, race, active smoking status, history of COPD, history of CHF, ASA score, dyspnoea, and functional status, with various combinations of these factors significantly affecting complication development for the individual surgeries. Hip fractures are associated with significantly high numbers of adverse events. The type of surgery affects the type of complications developed and also has an effect on what risk factors significantly predict the development of a complication. Concerted efforts from orthopaedists should be made to identify higher risk patients and prevent the most common adverse events that occur postoperatively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Ordinal logistic regression analysis on the nutritional status of children in KarangKitri village

NASA Astrophysics Data System (ADS)

Ohyver, Margaretha; Yongharto, Kimmy Octavian

2015-09-01

Ordinal logistic regression is a statistical technique that can be used to describe the relationship between ordinal response variable with one or more independent variables. This method has been used in various fields including in the health field. In this research, ordinal logistic regression is used to describe the relationship between nutritional status of children with age, gender, height, and family status. Nutritional status of children in this research is divided into over nutrition, well nutrition, less nutrition, and malnutrition. The purpose for this research is to describe the characteristics of children in the KarangKitri Village and to determine the factors that influence the nutritional status of children in the KarangKitri village. There are three things that obtained from this research. First, there are still children who are not categorized as well nutritional status. Second, there are children who come from sufficient economic level which include in not normal status. Third, the factors that affect the nutritional level of children are age, family status, and height.

A new multiple regression model to identify multi-family houses with a high prevalence of sick building symptoms "SBS", within the healthy sustainable house study in Stockholm (3H).

PubMed

Engvall, Karin; Hult, M; Corner, R; Lampa, E; Norbäck, D; Emenius, G

2010-01-01

The aim was to develop a new model to identify residential buildings with higher frequencies of "SBS" than expected, "risk buildings". In 2005, 481 multi-family buildings with 10,506 dwellings in Stockholm were studied by a new stratified random sampling. A standardised self-administered questionnaire was used to assess "SBS", atopy and personal factors. The response rate was 73%. Statistical analysis was performed by multiple logistic regressions. Dwellers owning their building reported less "SBS" than those renting. There was a strong relationship between socio-economic factors and ownership. The regression model, ended up with high explanatory values for age, gender, atopy and ownership. Applying our model, 9% of all residential buildings in Stockholm were classified as "risk buildings" with the highest proportion in houses built 1961-1975 (26%) and lowest in houses built 1985-1990 (4%). To identify "risk buildings", it is necessary to adjust for ownership and population characteristics.

Factors influencing attendance at structured education for Type 1 diabetes in south London.

PubMed

Harris, S M; Shah, P; Mulnier, H; Healey, A; Thomas, S M; Amiel, S A; Hopkins, D

2017-06-01

To investigate the factors influencing uptake of structured education for people with Type 1 diabetes in our local population in order to understand why such uptake is low. We conducted a cross-sectional database study of adults with Type 1 diabetes in two south London boroughs, analysed according to Dose Adjustment For Normal Eating (DAFNE) attendance or non-attendance. Demographics, glycaemic control and service use, with subset analysis by ethnicity, were compared using univariate analysis. An exploratory regression model was used to identify influencing factors. The analysis showed that 73% of adults had not attended the DAFNE programme. For non-attenders vs attenders, male gender (59 vs 48%; P = 0.002), older age (39 vs 35 years; P < 0.001), non-white ethnicity (30 vs 20%; P = 0.001) and coming from an area of social deprivation (index of multiple deprivation score 31 vs 28; P < 0.001) were associated with non-attendance. The difference in gender (88% men vs 70% women; P < 0.001) and age (43 vs 34 years) persisted in the non-white group. Regression analysis showed that higher baseline HbA 1c level (odds ratio 1.96; P = 0.004), younger age (odds ratio 0.98; P = 0.001) and lower social deprivation (odds ratio 0.52; P = 0.001) was associated with attendance. Socio-economic status and factors perceived as indicating greater severity of disease (HbA 1c ) influence attendance at DAFNE. More work is necessary to understand the demography of non-attenders to aid future service design and alternative engagement strategies for these groups. © 2017 Diabetes UK.

Analysis of Factors Related to Hypopituitarism in Patients with Nonsellar Intracranial Tumor.

PubMed

Lu, Song-Song; Gu, Jian-Jun; Luo, Xiao-Hong; Zhang, Jian-He; Wang, Shou-Sen

2017-09-01

Previous studies have suggested that postoperative hypopituitarism in patients with nonsellar intracranial tumors is caused by traumatic surgery. However, with development of minimally invasive and precise neurosurgical techniques, the degree of injury to brain tissue has been reduced significantly, especially for parenchymal tumors. Therefore, understanding preexisting hypopituitarism and related risk factors can improve perioperative management for patients with nonsellar intracranial tumors. Chart data were collected retrospectively from 83 patients with nonsellar intracranial tumors admitted to our hospital from May 2014 to April 2015. Pituitary function of each subject was determined based on results of preoperative serum pituitary hormone analysis. Univariate and multivariate logistic regression methods were used to analyze relationships between preoperative hypopituitarism and factors including age, sex, history of hypertension and secondary epilepsy, course of disease, tumor mass effect, site of tumor, intracranial pressure (ICP), cerebrospinal fluid content, and pituitary morphology. A total of 30 patients (36.14%) presented with preoperative hypopituitarism in either 1 axis or multiple axes; 23 (27.71%) were affected in 1 axis, and 7 (8.43%) were affected in multiple axes. Univariate analysis showed that risk factors for preoperative hypopituitarism in patients with a nonsellar intracranial tumor include an acute or subacute course (≤3 months), intracranial hypertension (ICP >200 mm H 2 O), and mass effect (P < 0.05). Multivariate logistic regression analysis showed that mass effect is an independent risk factor for preoperative hypopituitarism in patients with nonsellar intracranial tumors (P < 0.05; odds ratio, 3.197). Prevalence of hypopituitarism is high in patients with nonsellar intracranial tumors. The occurrence of hypopituitarism is correlated with factors including an acute or subacute course (≤3 months), intracranial hypertension (ICP >200 mm H 2 O), and mass effect (P < 0.05). Mass effect is an independent risk factor for hypopituitarism. Copyright © 2017 Elsevier Inc. All rights reserved.

Methods for estimating annual exceedance probability discharges for streams in Arkansas, based on data through water year 2013

USGS Publications Warehouse

Wagner, Daniel M.; Krieger, Joshua D.; Veilleux, Andrea G.

2016-08-04

In 2013, the U.S. Geological Survey initiated a study to update regional skew, annual exceedance probability discharges, and regional regression equations used to estimate annual exceedance probability discharges for ungaged locations on streams in the study area with the use of recent geospatial data, new analytical methods, and available annual peak-discharge data through the 2013 water year. An analysis of regional skew using Bayesian weighted least-squares/Bayesian generalized-least squares regression was performed for Arkansas, Louisiana, and parts of Missouri and Oklahoma. The newly developed constant regional skew of -0.17 was used in the computation of annual exceedance probability discharges for 281 streamgages used in the regional regression analysis. Based on analysis of covariance, four flood regions were identified for use in the generation of regional regression models. Thirty-nine basin characteristics were considered as potential explanatory variables, and ordinary least-squares regression techniques were used to determine the optimum combinations of basin characteristics for each of the four regions. Basin characteristics in candidate models were evaluated based on multicollinearity with other basin characteristics (variance inflation factor < 2.5) and statistical significance at the 95-percent confidence level (p ≤ 0.05). Generalized least-squares regression was used to develop the final regression models for each flood region. Average standard errors of prediction of the generalized least-squares models ranged from 32.76 to 59.53 percent, with the largest range in flood region D. Pseudo coefficients of determination of the generalized least-squares models ranged from 90.29 to 97.28 percent, with the largest range also in flood region D. The regional regression equations apply only to locations on streams in Arkansas where annual peak discharges are not substantially affected by regulation, diversion, channelization, backwater, or urbanization. The applicability and accuracy of the regional regression equations depend on the basin characteristics measured for an ungaged location on a stream being within range of those used to develop the equations.

Impact of Colic Pain as a Significant Factor for Predicting the Stone Free Rate of One-Session Shock Wave Lithotripsy for Treating Ureter Stones: A Bayesian Logistic Regression Model Analysis

PubMed Central

Chung, Doo Yong; Cho, Kang Su; Lee, Dae Hun; Han, Jang Hee; Kang, Dong Hyuk; Jung, Hae Do; Kown, Jong Kyou; Ham, Won Sik; Choi, Young Deuk; Lee, Joo Yong

2015-01-01

Purpose This study was conducted to evaluate colic pain as a prognostic pretreatment factor that can influence ureter stone clearance and to estimate the probability of stone-free status in shock wave lithotripsy (SWL) patients with a ureter stone. Materials and Methods We retrospectively reviewed the medical records of 1,418 patients who underwent their first SWL between 2005 and 2013. Among these patients, 551 had a ureter stone measuring 4–20 mm and were thus eligible for our analyses. The colic pain as the chief complaint was defined as either subjective flank pain during history taking and physical examination. Propensity-scores for established for colic pain was calculated for each patient using multivariate logistic regression based upon the following covariates: age, maximal stone length (MSL), and mean stone density (MSD). Each factor was evaluated as predictor for stone-free status by Bayesian and non-Bayesian logistic regression model. Results After propensity-score matching, 217 patients were extracted in each group from the total patient cohort. There were no statistical differences in variables used in propensity- score matching. One-session success and stone-free rate were also higher in the painful group (73.7% and 71.0%, respectively) than in the painless group (63.6% and 60.4%, respectively). In multivariate non-Bayesian and Bayesian logistic regression models, a painful stone, shorter MSL, and lower MSD were significant factors for one-session stone-free status in patients who underwent SWL. Conclusions Colic pain in patients with ureter calculi was one of the significant predicting factors including MSL and MSD for one-session stone-free status of SWL. PMID:25902059

Severity of mental illness as a result of multiple childhood adversities: US National Epidemiologic Survey.

PubMed

Curran, Emma; Adamson, Gary; Stringer, Maurice; Rosato, Michael; Leavey, Gerard

2016-05-01

To examine patterns of childhood adversity, their long-term consequences and the combined effect of different childhood adversity patterns as predictors of subsequent psychopathology. Secondary analysis of data from the US National Epidemiologic Survey on alcohol and related conditions. Using latent class analysis to identify childhood adversity profiles; and using multinomial logistic regression to validate and further explore these profiles with a range of associated demographic and household characteristics. Finally, confirmatory factor analysis substantiated initial latent class analysis findings by investigating a range of mental health diagnoses. Latent class analysis generated a three-class model of childhood adversity in which 60 % of participants were allocated to a low adversity class; 14 % to a global adversities class (reporting exposures for all the derived latent classes); and 26 % to a domestic emotional and physical abuse class (exposed to a range of childhood adversities). Confirmatory Factor analysis defined an internalising-externalising spectrum to represent lifetime reporting patterns of mental health disorders. Using logistic regression, both adversity groups showed specific gender and race/ethnicity differences, related family discord and increased psychopathology. We identified underlying patterns in the exposure to childhood adversity and associated mental health. These findings are informative in their description of the configuration of adversities, rather than focusing solely on the cumulative aspect of experience. Amelioration of longer-term negative consequences requires early identification of psychopathology risk factors that can inform protective and preventive interventions. This study highlights the utility of screening for childhood adversities when individuals present with symptoms of psychiatric disorders.

Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases.

PubMed

Hirata, Makoto; Kamatani, Yoichiro; Nagai, Akiko; Kiyohara, Yutaka; Ninomiya, Toshiharu; Tamakoshi, Akiko; Yamagata, Zentaro; Kubo, Michiaki; Muto, Kaori; Mushiroda, Taisei; Murakami, Yoshinori; Yuji, Koichiro; Furukawa, Yoichi; Zembutsu, Hitoshi; Tanaka, Toshihiro; Ohnishi, Yozo; Nakamura, Yusuke; Matsuda, Koichi

2017-03-01

To implement personalized medicine, we established a large-scale patient cohort, BioBank Japan, in 2003. BioBank Japan contains DNA, serum, and clinical information derived from approximately 200,000 patients with 47 diseases. Serum and clinical information were collected annually until 2012. We analyzed clinical information of participants at enrollment, including age, sex, body mass index, hypertension, and smoking and drinking status, across 47 diseases, and compared the results with the Japanese database on Patient Survey and National Health and Nutrition Survey. We conducted multivariate logistic regression analysis, adjusting for sex and age, to assess the association between family history and disease development. Distribution of age at enrollment reflected the typical age of disease onset. Analysis of the clinical information revealed strong associations between smoking and chronic obstructive pulmonary disease, drinking and esophageal cancer, high body mass index and metabolic disease, and hypertension and cardiovascular disease. Logistic regression analysis showed that individuals with a family history of keloid exhibited a higher odds ratio than those without a family history, highlighting the strong impact of host genetic factor(s) on disease onset. Cross-sectional analysis of the clinical information of participants at enrollment revealed characteristics of the present cohort. Analysis of family history revealed the impact of host genetic factors on each disease. BioBank Japan, by publicly distributing DNA, serum, and clinical information, could be a fundamental infrastructure for the implementation of personalized medicine. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Desire thinking: A risk factor for binge eating?

PubMed

Spada, Marcantonio M; Caselli, Gabriele; Fernie, Bruce A; Manfredi, Chiara; Boccaletti, Fabio; Dallari, Giulia; Gandini, Federica; Pinna, Eleonora; Ruggiero, Giovanni M; Sassaroli, Sandra

2015-08-01

In the current study we explored the role of desire thinking in predicting binge eating independently of Body Mass Index, negative affect and irrational food beliefs. A sample of binge eaters (n=77) and a sample of non-binge eaters (n=185) completed the following self-report instruments: Hospital Anxiety and Depression Scale, Irrational Food Beliefs Scale, Desire Thinking Questionnaire, and Binge Eating Scale. Mann-Whitney U tests revealed that all variable scores were significantly higher for binge eaters than non-binge eaters. A logistic regression analysis indicated that verbal perseveration was a predictor of classification as a binge eater over and above Body Mass Index, negative affect and irrational food beliefs. A hierarchical regression analysis, on the combined sample, indicated that verbal perseveration predicted levels of binge eating independently of Body Mass Index, negative affect and irrational food beliefs. These results highlight the possible role of desire thinking as a risk factor for binge eating. Copyright © 2015 Elsevier Ltd. All rights reserved.

Trail impacts in Sagarmatha (Mt. Everest) National Park, Nepal: a logistic regression analysis.

PubMed

Nepal, S K

2003-09-01

A trail study was conducted in the Sagarmatha (Mt. Everest) National Park, Nepal, during 1997-1998. Based on that study, this paper examines the spatial variability of trail conditions and analyzes factors that influence trail conditions. Logistic regression (multinomial logit model) is applied to examine the influence of use and environmental factors on trail conditions. The assessment of trail conditions is based on a four-class rating system: (class I, very little damaged; class II, moderately damaged, class III, heavily damaged; and class IV, severely damaged). Wald statistics and a model classification table have been used for data interpretation. Results indicate that altitude, trail gradient, hazard potential, and vegetation type are positively associated with trail condition. Trails are more degraded at higher altitude, on steep gradients, in areas with natural hazard potential, and within shrub/grassland zones. Strong correlations between high levels of trail degradation and higher frequencies of visitors and lodges were found. A detailed analysis of environmental and use factors could provide valuable information to park managers in their decisions about trail design, layout and maintenance, and efficient and effective visitor management strategies. Comparable studies on high alpine environments are needed to predict precisely the effects of topographic and climatic extremes. More refined approaches and experimental methods are necessary to control the effects of environmental factors.

Gender-specific risk factors for low bone mineral density in patients taking antipsychotics for psychosis.

PubMed

Jhon, Min; Yoo, Taeyoung; Lee, Ju-Yeon; Kim, Seon-Young; Kim, Jae-Min; Shin, Il-Seon; Williams, Lana; Berk, Michael; Yoon, Jin-Sang; Kim, Sung-Wan

2018-01-01

This study examined clinical and gender-specific risk factors for low bone mineral density (BMD) in adult patients with psychotic disorders. The study included 285 community-dwelling patients with psychotic disorders. Dual-energy X-ray absorptiometry was used to measure BMD. Clinical characteristics associated with low BMD were identified with logistic regression analysis in total population and each gender. Fifty-eight (20.4%) subjects had low BMD. Low BMD was more common in men and in patients with low body mass indices (BMIs), as well as in those with shorter treatment durations, those on Medicaid, and patients using serotonergic antidepressants. Logistic regression analysis revealed that low BMD was negatively associated with BMI and treatment duration and positively with gender (male) and serotonergic antidepressants use in the overall population. In men, low BMD was associated with treatment duration and BMI; in women, low BMD was associated with BMI, prolactin level, vitamin D, and serotonergic antidepressant use. Managing the risk factors associated with low BMD among patients with psychotic disorder should be done gender-specifically. Psychotropic agents should be prescribed mindful of their effects on bone, as use of these medications is a modifiable risk factor for osteoporosis in women with psychotic disorders. Copyright © 2018 John Wiley & Sons, Ltd.

Risk factors for the breakdown of perineal laceration repair after vaginal delivery.

PubMed

Williams, Meredith K; Chames, Mark C

2006-09-01

The purpose of this study was to identify risk factors that are associated with the breakdown of perineal laceration repair in the postpartum period. We conducted a retrospective, case-control study to review perineal laceration repair breakdown in patients who were delivered between September 1995 and February 2005 at the University of Michigan. Bivariate analysis with chi-square test and t-test and stepwise logistic regression analysis were performed. Fifty-nine cases and 118 control deliveries were identified from a total of 14,124 vaginal deliveries. Risk factors were longer second stage of labor (142 vs 87 minutes; P = .001), operative vaginal delivery (odds ratio, 3.6; 95% CI, 1.8-7.3), mediolateral episiotomy (odds ratio, 6.9; 95% CI, 2.6-18.7), third- or fourth-degree laceration (odds ratio, 3.1; 95% CI, 1.5-6.4), and meconium-stained amniotic fluid (odds ratio, 3.0; 95% CI, 1.1-7.9). Previous vaginal delivery was protective (odds ratio, 0.38; 95% CI, 0.18-0.84). Logistic regression showed the most significant factor to be an interaction between operative vaginal delivery and mediolateral episiotomy (odd ratio, 6.36; 95% CI, 2.18-18.57). The most significant events were mediolateral episiotomy, especially in conjunction with operative vaginal delivery, third- and fourth-degree lacerations, and meconium.

[Prevalence and risk factors of postpartum depression in Tianhe District of Guangzhou].

PubMed

Deng, Aiwen; Jiang, Tingting; Luo, Yingping; Xiong, Ribo

2014-01-01

To investigate the prevalence and risk factors of postpartum depression (PPD) in Tianhe district of Guangzhou. A total of 1428 postpartum women in 3 hospitals in Tianhe District of Guangzhou were screened with Edinburg Postnatal Depression Scale (EPDS), Social Support Rating Scale (SSRS) and a self-designed questionnaire of PPD-related factors during the period from May to September, 2013. The prevalence of PPD was 20.03% in these women. Unconditional logistic regression analysis showed a significant correlation of PPD with education, delivery mode, only daughter, relationship between mother-in-law and daughter-in-law, newborn gender satisfaction and housing condition (P<0.05). Multivariate logistic regression analysis identified education, delivery mode, only daughter, relationship between mother-in-law and daughter-in-law, and newborn gender satisfaction as the risk factors for PPD, and housing condition was negatively correlated with the incidence of PPD with an OR value of 0.900. Compared with healthy postpartum women, the patients with PPD exhibited significantly reduced total score of social support rating scale, score of objective support, score of subjective support, and social utilization degree. The prevalence of PPD is high in Tianhe District of Guangzhou, and health education and psychosocial intervention should be offered to prevent PPD.

Prediction of cadmium enrichment in reclaimed coastal soils by classification and regression tree

NASA Astrophysics Data System (ADS)

Ru, Feng; Yin, Aijing; Jin, Jiaxin; Zhang, Xiuying; Yang, Xiaohui; Zhang, Ming; Gao, Chao

2016-08-01

Reclamation of coastal land is one of the most common ways to obtain land resources in China. However, it has long been acknowledged that the artificial interference with coastal land has disadvantageous effects, such as heavy metal contamination. This study aimed to develop a prediction model for cadmium enrichment levels and assess the importance of affecting factors in typical reclaimed land in Eastern China (DFCL: Dafeng Coastal Land). Two hundred and twenty seven surficial soil/sediment samples were collected and analyzed to identify the enrichment levels of cadmium and the possible affecting factors in soils and sediments. The classification and regression tree (CART) model was applied in this study to predict cadmium enrichment levels. The prediction results showed that cadmium enrichment levels assessed by the CART model had an accuracy of 78.0%. The CART model could extract more information on factors affecting the environmental behavior of cadmium than correlation analysis. The integration of correlation analysis and the CART model showed that fertilizer application and organic carbon accumulation were the most important factors affecting soil/sediment cadmium enrichment levels, followed by particle size effects (Al2O3, TFe2O3 and SiO2), contents of Cl and S, surrounding construction areas and reclamation history.

Replacing zoledronic acid with denosumab is a risk factor for developing osteonecrosis of the jaw.

PubMed

Higuchi, Tomoko; Soga, Yoshihiko; Muro, Misato; Kajizono, Makoto; Kitamura, Yoshihisa; Sendo, Toshiaki; Sasaki, Akira

2018-06-01

Intravenous zoledronic acid (ZA) is often replaced with subcutaneous denosumab in patients with bone metastatic cancer. Despite their different pharmacologic mechanisms of action, both denosumab and ZA are effective in bone metastasis but cause osteonecrosis of the jaw (ONJ) as a side effect. ZA persists in the body almost indefinitely, whereas denosumab does not persist for long periods. This study evaluated the risks of developing ONJ when replacing ZA with denosumab. In total, 161 Japanese patients administered ZA for bone metastatic cancer were enrolled in this single-center, retrospective, observational study. The risk of developing ONJ was evaluated by logistic regression analysis using the following factors: age, gender, cancer type, angiogenesis inhibitors, steroids, and replacement of ZA with denosumab. Seventeen patients (10.6%) developed ONJ. Multiple regression analysis indicated a significant difference in rate of ONJ associated with replacement of ZA with denosumab (odds ratio = 3.81; 95% confidence interval 1.04-13.97; P = .043). Replacing ZA with denosumab is a risk factor for the development of ONJ. Both binding of bisphosphonate to bone and receptor activator of nuclear factor-κ B ligand inhibition could additively increase the risk of ONJ. We bring the replacement of ZA with denosumab to the attention of clinical oncologists. Copyright © 2018 Elsevier Inc. All rights reserved.

Suicidality and its relationships with individual, family, peer, and psychopathology factors among adolescents with attention-deficit/hyperactivity disorder.

PubMed

Chou, Wen-Jiun; Liu, Tai-Ling; Hu, Huei-Fan; Yen, Cheng-Fang

2016-01-01

The aim of this study was to examine the prevalence rates of suicidal intent and its correlates among adolescents diagnosed with ADHD in Taiwan. A total of 287 adolescents aged 11-18 years and diagnosed with ADHD participated in this study. Their suicidal ideation and suicide attempts were assessed. Logistic regression analysis was used to examine the associations of suicide with individual, family, peer, ADHD, and psychopathology factors. A total of 12.2% of the participants reported suicidal ideation or a suicide attempt. A logistic regression analysis model showed that adolescents who were older, were bullying perpetrators, and reported high depression level were more likely to have suicidal intent. These three factors were also significantly correlated with suicidal ideation; however, only having high depression level was significantly correlated with suicidal attempts. The results of this study showed that a high proportion of adolescents with ADHD reported suicidal ideation or a suicide attempt. Multiple factors were significantly associated with suicidal intent among adolescents with ADHD. Clinicians, educational professionals, and parents of adolescents with ADHD should monitor the possibility of suicide in adolescents with ADHD who exhibit the correlates of suicidal intent identified in this study. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predictive Factors of Atelectasis Following Endoscopic Resection.

PubMed

Choe, Jung Wan; Jung, Sung Woo; Song, Jong Kyu; Shim, Euddeum; Choo, Ji Yung; Kim, Seung Young; Hyun, Jong Jin; Koo, Ja Seol; Yim, Hyung Joon; Lee, Sang Woo

2016-01-01

Atelectasis is one of the pulmonary complications associated with anesthesia. Little is known about atelectasis following endoscopic procedures under deep sedation. This study evaluated the frequency, risk factors, and clinical course of atelectasis after endoscopic resection. A total of 349 patients who underwent endoscopic resection of the upper gastrointestinal tract at a single academic tertiary referral center from March 2010 to October 2013 were enrolled. Baseline characteristics and clinical data were retrospectively reviewed from medical records. To identify atelectasis, we compared the chest radiography taken before and after the endoscopic procedure. Among the 349 patients, 68 (19.5 %) had newly developed atelectasis following endoscopic resection. In univariate logistic regression analysis, atelectasis correlated significantly with high body mass index, smoking, diabetes mellitus, procedure duration, size of lesion, and total amount of propofol. In multiple logistic regression analysis, body mass index, procedure duration, and total propofol amount were risk factors for atelectasis following endoscopic procedures. Of the 68 patients with atelectasis, nine patients developed fever, and six patients displayed pneumonic infiltration. The others had no symptoms related to atelectasis. The incidence of radiographic atelectasis following endoscopic resection was nearly 20 %. Obesity, procedural time, and amount of propofol were the significant risk factors for atelectasis following endoscopic procedure. Most cases of the atelectasis resolved spontaneously with no sequelae.

[Mother-child relationship and associated factors: Hierarchical analysis of the population base in a Brazilian state capital - BRISA Study].

PubMed

Cavalcante, Milady Cutrim Vieira; Lamy, Fernando; França, Ana Karina Teixeira da Cunha; Lamy, Zeni Carvalho

2017-05-01

Several factors can interfere in the mother-child relationship. Studies about different maternal characteristics and this relationship are scarce; they mainly evaluate women with psychopathology and use simultaneous regression models with adjustment for multiple confounders. This study aimed to assess factors associated with losses in the mother-child relationship through a cohort of 3,215 mothers of children between 15 and 36 months of age. Losses in the mother-child relationship, assessed by the Postpartum Bonding Questionnaire, was the outcome variable and the explanatory variables were demographic, socioeconomic, reproductive health and mental health of mothers as well as the conditions of the birth of children. It used multivariate regression analysis with a hierarchical approach in which the hierarchical blocks were structured according to the influence on the mother-child relationship. The prevalence of losses in the mother-child relationship was high (12.6%) and associated risk factors to lower maternal education (RR = 1.64), having unplanned pregnancy (RR = 1.42), consumption of alcoholic beverages during pregnancy (RR = 1.42) and maternal stress symptoms (RR = 1.88) and depression (RR = 2.00). Education and elements related to mental health were risks for damage in the mother-child relationship.

Serum S100B Is Related to Illness Duration and Clinical Symptoms in Schizophrenia—A Meta-Regression Analysis

PubMed Central

Schümberg, Katharina; Polyakova, Maryna; Steiner, Johann; Schroeter, Matthias L.

2016-01-01

S100B has been linked to glial pathology in several psychiatric disorders. Previous studies found higher S100B serum levels in patients with schizophrenia compared to healthy controls, and a number of covariates influencing the size of this effect have been proposed in the literature. Here, we conducted a meta-analysis and meta-regression analysis on alterations of serum S100B in schizophrenia in comparison with healthy control subjects. The meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement to guarantee a high quality and reproducibility. With strict inclusion criteria 19 original studies could be included in the quantitative meta-analysis, comprising a total of 766 patients and 607 healthy control subjects. The meta-analysis confirmed higher values of the glial serum marker S100B in schizophrenia if compared with control subjects. Meta-regression analyses revealed significant effects of illness duration and clinical symptomatology, in particular the total score of the Positive and Negative Syndrome Scale (PANSS), on serum S100B levels in schizophrenia. In sum, results confirm glial pathology in schizophrenia that is modulated by illness duration and related to clinical symptomatology. Further studies are needed to investigate mechanisms and mediating factors related to these findings. PMID:26941608

Analysis of a Rocket Based Combined Cycle Engine during Rocket Only Operation

NASA Technical Reports Server (NTRS)

Smith, T. D.; Steffen, C. J., Jr.; Yungster, S.; Keller, D. J.

1998-01-01

The all rocket mode of operation is a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. However, outside of performing experiments or a full three dimensional analysis, there are no first order parametric models to estimate performance. As a result, an axisymmetric RBCC engine was used to analytically determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and statistical regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, percent of injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inject diameter ratio. A perfect gas computational fluid dynamics analysis was performed to obtain values of vacuum specific impulse. Statistical regression analysis was performed based on both full flow and gas generator engine cycles. Results were also found to be dependent upon the entire cycle assumptions. The statistical regression analysis determined that there were five significant linear effects, six interactions, and one second-order effect. Two parametric models were created to provide performance assessments of an RBCC engine in the all rocket mode of operation.

Performance of an Axisymmetric Rocket Based Combined Cycle Engine During Rocket Only Operation Using Linear Regression Analysis

NASA Technical Reports Server (NTRS)

Smith, Timothy D.; Steffen, Christopher J., Jr.; Yungster, Shaye; Keller, Dennis J.

1998-01-01

The all rocket mode of operation is shown to be a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. An axisymmetric RBCC engine was used to determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and multiple linear regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inlet diameter ratio. A perfect gas computational fluid dynamics analysis, using both the Spalart-Allmaras and k-omega turbulence models, was performed with the NPARC code to obtain values of vacuum specific impulse. Results from the multiple linear regression analysis showed that for both the full flow and gas generator configurations increasing mixer-ejector area ratio and rocket area ratio increase performance, while increasing mixer-ejector inlet area ratio and mixer-ejector length-to-diameter ratio decrease performance. Increasing injected secondary flow increased performance for the gas generator analysis, but was not statistically significant for the full flow analysis. Chamber pressure was found to be not statistically significant.

Novel risk score of contrast-induced nephropathy after percutaneous coronary intervention.

PubMed

Ji, Ling; Su, XiaoFeng; Qin, Wei; Mi, XuHua; Liu, Fei; Tang, XiaoHong; Li, Zi; Yang, LiChuan

2015-08-01

Contrast-induced nephropathy (CIN) post-percutaneous coronary intervention (PCI) is a major cause of acute kidney injury. In this study, we established a comprehensive risk score model to assess risk of CIN after PCI procedure, which could be easily used in a clinical environment. A total of 805 PCI patients, divided into analysis cohort (70%) and validation cohort (30%), were enrolled retrospectively in this study. Risk factors for CIN were identified using univariate analysis and multivariate logistic regression in the analysis cohort. Risk score model was developed based on multiple regression coefficients. Sensitivity and specificity of the new risk score system was validated in the validation cohort. Comparisons between the new risk score model and previous reported models were applied. The incidence of post-PCI CIN in the analysis cohort (n = 565) was 12%. Considerably high CIN incidence (50%) was observed in patients with chronic kidney disease (CKD). Age >75, body mass index (BMI) >25, myoglobin level, cardiac function level, hypoalbuminaemia, history of chronic kidney disease (CKD), Intra-aortic balloon pump (IABP) and peripheral vascular disease (PVD) were identified as independent risk factors of post-PCI CIN. A novel risk score model was established using multivariate regression coefficients, which showed highest sensitivity and specificity (0.917, 95%CI 0.877-0.957) compared with previous models. A new post-PCI CIN risk score model was developed based on a retrospective study of 805 patients. Application of this model might be helpful to predict CIN in patients undergoing PCI procedure. © 2015 Asian Pacific Society of Nephrology.

Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression.

PubMed

Beckstead, Jason W

2012-03-30

The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic strategy to isolate, examine, and remove suppression effects has been offered. In this article such an approach, rooted in confirmatory factor analysis theory and employing matrix algebra, is developed. Suppression is viewed as the result of criterion-irrelevant variance operating among predictors. Decomposition of predictor variables into criterion-relevant and criterion-irrelevant components using structural equation modeling permits derivation of regression weights with the effects of criterion-irrelevant variance omitted. Three examples with data from applied research are used to illustrate the approach: the first assesses child and parent characteristics to explain why some parents of children with obsessive-compulsive disorder accommodate their child's compulsions more so than do others, the second examines various dimensions of personal health to explain individual differences in global quality of life among patients following heart surgery, and the third deals with quantifying the relative importance of various aptitudes for explaining academic performance in a sample of nursing students. The approach is offered as an analytic tool for investigators interested in understanding predictor-criterion relationships when complex patterns of intercorrelation among predictors are present and is shown to augment dominance analysis.

MULTIVARIATE ANALYSIS OF DRINKING BEHAVIOUR IN A RURAL POPULATION

PubMed Central

Mathrubootham, N.; Bashyam, V.S.P.; Shahjahan

1997-01-01

This study was carried out to find out the drinking pattern in a rural population, using multivariate techniques. 386 current users identified in a community were assessed with regard to their drinking behaviours using a structured interview. For purposes of the study the questions were condensed into 46 meaningful variables. In bivariate analysis, 14 variables including dependent variables such as dependence, MAST & CAGE (measuring alcoholic status), Q.F. Index and troubled drinking were found to be significant. Taking these variables and other multivariate techniques too such as ANOVA, correlation, regression analysis and factor analysis were done using both SPSS PC + and HCL magnum mainframe computer with FOCUS package and UNIX systems. Results revealed that number of factors such as drinking style, duration of drinking, pattern of abuse, Q.F. Index and various problems influenced drinking and some of them set up a vicious circle. Factor analysis revealed mainly 3 factors, abuse, dependence and social drinking factors. Dependence could be divided into low/moderate dependence. The implications and practical applications of these tests are also discussed. PMID:21584077

[Developing Perceived Competence Scale (PCS) for Adolescents].

PubMed

Özer, Arif; Gençtanirim Kurt, Dilek; Kizildağ, Seval; Demırtaş Zorbaz, Selen; Arici Şahın, Fatma; Acar, Tülin; Ergene, Tuncay

2016-01-01

In this study, Perceived Competence Scale was developed to measure high school students' perceived competence. Scale development process was verified on three different samples. Participants of the research are some high school students in 2011-2012 academic terms from Ankara. Participants' numbers are incorporated in exploratory factor analysis, confirmatory factor analysis and test-retest reliability respectively, as follows: 372, 668 and 75. Internal consistency coefficients (Cronbach's and stratified α) are calculated separately for each group. For data analysis Factor 8.02 and LISREL 8.70 package programs were used. According to results of the analyses, internal consistency coefficients (α) are .90 - .93 for academic competence, .82 - .86 for social competence in the samples that exploratory and confirmatory factor analysis performed. For the whole scale internal consistency coefficient (stratified α) is calculated as .91. As a result of test-retest reliability, adjusted correlation coefficients (r) are .94 for social competence and .90 for academic competence. In addition, to fit indexes and regression weights obtained from factor analysis, findings related convergent and discriminant validity, indicating that competence can be addressed in two dimensions which are academic (16 items) and social (14 items).

[Spatial epidemiological study on malaria epidemics in Hainan province].

PubMed

Wen, Liang; Shi, Run-He; Fang, Li-Qun; Xu, De-Zhong; Li, Cheng-Yi; Wang, Yong; Yuan, Zheng-Quan; Zhang, Hui

2008-06-01

To better understand the characteristics of spatial distribution of malaria epidemics in Hainan province and to explore the relationship between malaria epidemics and environmental factors, as well to develop prediction model on malaria epidemics. Data on Malaria and meteorological factors were collected in all 19 counties in Hainan province from May to Oct., 2000, and the proportion of land use types of these counties in this period were extracted from digital map of land use in Hainan province. Land surface temperatures (LST) were extracted from MODIS images and elevations of these counties were extracted from DEM of Hainan province. The coefficients of correlation of malaria incidences and these environmental factors were then calculated with SPSS 13.0, and negative binomial regression analysis were done using SAS 9.0. The incidence of malaria showed (1) positive correlations to elevation, proportion of forest land area and grassland area; (2) negative correlations to the proportion of cultivated area, urban and rural residents and to industrial enterprise area, LST; (3) no correlations to meteorological factors, proportion of water area, and unemployed land area. The prediction model of malaria which came from negative binomial regression analysis was: I (monthly, unit: 1/1,000,000) = exp (-1.672-0.399xLST). Spatial distribution of malaria epidemics was associated with some environmental factors, and prediction model of malaria epidemic could be developed with indexes which extracted from satellite remote sensing images.

Multidimensional Predictors of Fatigue among Octogenarians and Centenarians

PubMed Central

Cho, Jinmyoung; Martin, Peter; Margrett, Jennifer; MacDonald, Maurice; Johnson, Mary Ann; Poon, Leonard W.

2012-01-01

Background Fatigue is a common and frequently observed complaint among older adults. However, knowledge about the nature and correlates of fatigue in old age is very limited. Objective: This study examined the relationship of functional indicators, psychological and situational factors and fatigue for 210 octogenarians and centenarians from the Georgia Centenarian Study. Methods Three indicators of functional capacity (self-rated health, instrumental activities of daily living, physical activities of daily living), two indicators of psychological well-being (positive and negative affect), two indicators of situational factors (social network and social support), and a multidimensional fatigue scale were used. Blocked multiple regression analyses were computed to examine significant factors related to fatigue. In addition, multi-group analysis in structural equation modeling was used to investigate residential differences (i.e., long-term care facilities vs. private homes) in the relationship between significant factors and fatigue. Results Blocked multiple regression analyses indicated that two indicators of functional capacity, self-rated health and instrumental activities of daily living, both positive and negative affect, and social support were significant predictors of fatigue among oldest-old adults. The multiple group analysis in structural equation modeling revealed a significant difference among oldest-old adults based on residential status. Conclusion The results suggest that we should not consider fatigue as merely an unpleasant physical symptom, but rather adopt a perspective that different factors such as psychosocial aspects can influence fatigue in advanced later life. PMID:22094445

Incidence and risk factors of acute kidney injury after esophageal cancer surgery: A nested case-control study.

PubMed

Wang, Wen; Wang, Tong; Feng, Xiaoshuang; Sun, Li

2017-03-01

Acute kidney injury (AKI) has been increasingly recognized as a common and serious postoperative complication. Although many studies have been conducted to investigate postoperative AKI after thoracic surgery, little is known about AKI after esophageal surgery. Thus, we conducted this study to determine the incidence and identify risk factors of postoperative AKI after esophageal cancer surgery. A retrospective nested case-control study of patients undergoing elective esophageal cancer surgery between July 2013 and July 2016 in a single tertiary specialized cancer hospital was performed. The primary outcome was development of AKI. Conditional logistic regression analysis was performed to identify independent risk factors for AKI. Of 2094 patients, 51 (2.4%) developed postoperative AKI after esophageal cancer surgery. In multivariate conditional logistic regression analysis, four risk factors for AKI after esophageal surgery for cancer were identified: preoperative serum creatinine level (OR 1.040; 95% CI 1.012-1.069), duration of surgery (OR 1.009; 95% CI 1.005-1.014), smoking history (OR 3.029; 95% CI 1.092-8.399) and hypertension (OR 6.422; 95% CI 2.736-15.070). Postoperative AKI occurred in 2.4% of patients after esophageal surgery for cancer. Preoperative serum creatinine level, duration of surgery, smoking history and hypertension were independent risk factors for postoperative AKI. Copyright © 2017 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Multidimensional predictors of fatigue among octogenarians and centenarians.

PubMed

Cho, Jinmyoung; Martin, Peter; Margrett, Jennifer; MacDonald, Maurice; Johnson, Mary Ann; Poon, Leonard W; Jazwinski, S M; Green, R C; Gearing, M; Woodard, J L; Tenover, J S; Siegler, I C; Rott, C; Rodgers, W L; Hausman, D; Arnold, J; Davey, A

2012-01-01

Fatigue is a common and frequently observed complaint among older adults. However, knowledge about the nature and correlates of fatigue in old age is very limited. This study examined the relationship of functional indicators, psychological and situational factors and fatigue for 210 octogenarians and centenarians from the Georgia Centenarian Study. Three indicators of functional capacity (self-rated health, instrumental activities of daily living, physical activities of daily living), two indicators of psychological well-being (positive and negative affect), two indicators of situational factors (social network and social support), and a multidimensional fatigue scale were used. Blocked multiple regression analyses were computed to examine significant factors related to fatigue. In addition, multi-group analysis in structural equation modeling was used to investigate residential differences (i.e., long-term care facilities vs. private homes) in the relationship between significant factors and fatigue. Blocked multiple regression analyses indicated that two indicators of functional capacity, self-rated health and instrumental activities of daily living, both positive and negative affect, and social support were significant predictors of fatigue among oldest-old adults. The multiple group analysis in structural equation modeling revealed a significant difference among oldest-old adults based on residential status. The results suggest that we should not consider fatigue as merely an unpleasant physical symptom, but rather adopt a perspective that different factors such as psychosocial aspects can influence fatigue in advanced later life. Copyright © 2011 S. Karger AG, Basel.

Risk Factors Related with Retroperitoneal Laparoscopic Converted to Open Nephrectomy for Nonfunctioning Renal Tuberculosis.

PubMed

Xu, Bo; Hu, Jinghai; Chen, Anxiang; Hao, Yuanyuan; Liu, GuoHui; Wang, Chunxi; Wang, Xiaoqing

2017-06-01

The present study was designed to investigate the risk factors affecting the conversion to open surgery in retroperitoneal laparoscopic nephrectomy of nonfunctioning renal tuberculosis (TB). The records of 144 patients who underwent a retroperitoneal laparoscopic nephrectomy procedure by a single surgeon were retrospectively reviewed. The following factors, including age, sex, body mass index (BMI), diabetes status, hypertension status, side of kidney, size of kidney, degree of calcification, mild perirenal extravasation, contralateral hydronephrosis, the time of anti-TB, and surgeon experience were analyzed. Univariate and multivariate logistic regression analyses were used for statistical assessment. Twenty-three patients were converted to open surgery and the conversion rate was 15.97%. In univariate analysis, BMI ≥35 kg/m 2 (p = 0.023), hypertension (p = 0.011), diabetes (p = 0.003), and kidney size (p = 0.032) were the main factors of conversion to open surgery. Sex, age, side, anti-TB time, calcification, mild extravasation, and surgeon experience were not significantly related. In multivariate regression analysis, BMI ≥35 kg/m 2 , hypertension, diabetes, and enlargement of kidney were the most important factors for conversion to open surgery. Depending on the results achieved by a single surgeon, BMI ≥30 kg/m 2 , diabetes, hypertension, and enlargement of kidney significantly increased the conversion risk in retroperitoneal laparoscopic nephrectomy for nonfunctioning renal TB.

Combined preoperative measurement of three inferior alveolar canal factors using computed tomography predicts the risk of inferior alveolar nerve injury during lower third molar extraction.

PubMed

Tachinami, H; Tomihara, K; Fujiwara, K; Nakamori, K; Noguchi, M

2017-11-01

A retrospective cohort study was performed to assess the clinical usefulness of combination assessment using computed tomography (CT) images in patients undergoing third molar extraction. This study included 85 patients (124 extraction sites). The relationship between cortication status, buccolingual position, and shape of the inferior alveolar canal (IAC) on CT images and the incidence of inferior alveolar nerve (IAN) injury after third molar extraction was evaluated. IAN injury was observed at eight of the 124 sites (6.5%), and in five of 19 sites (26.3%) in which cortication was absent+the IAC had a lingual position+the IAC had a dumbbell shape. Significant relationships were found between IAN injury and the three IAC factors (cortication status, IAC position, and IAC shape; P=0.0001). In patients with the three IAC factors, logistic regression analysis indicated a strong association between these factors and IAN injury (P=0.007). An absence of cortication, a lingually positioned IAC, and a dumbbell-shaped IAC are considered to indicate a high risk of IAN injury according to the logistic regression analysis (P=0.007). These results suggest that a combined assessment of these three IAC factors could be useful for the improved prediction of IAN injury. Copyright © 2017 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.