Analysis and Interpretation of Findings Using Multiple Regression Techniques

ERIC Educational Resources Information Center

Hoyt, William T.; Leierer, Stephen; Millington, Michael J.

2006-01-01

Multiple regression and correlation (MRC) methods form a flexible family of statistical techniques that can address a wide variety of different types of research questions of interest to rehabilitation professionals. In this article, we review basic concepts and terms, with an emphasis on interpretation of findings relevant to research questions…

Quantitative assessment of cervical vertebral maturation using cone beam computed tomography in Korean girls.

PubMed

Byun, Bo-Ram; Kim, Yong-Il; Yamaguchi, Tetsutaro; Maki, Koutaro; Son, Woo-Sung

2015-01-01

This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6-18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R (2) had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status.

An improved multiple linear regression and data analysis computer program package

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

Ridge: a computer program for calculating ridge regression estimates

Treesearch

Donald E. Hilt; Donald W. Seegrist

1977-01-01

Least-squares coefficients for multiple-regression models may be unstable when the independent variables are highly correlated. Ridge regression is a biased estimation procedure that produces stable estimates of the coefficients. Ridge regression is discussed, and a computer program for calculating the ridge coefficients is presented.

Confidence Intervals for Squared Semipartial Correlation Coefficients: The Effect of Nonnormality

ERIC Educational Resources Information Center

Algina, James; Keselman, H. J.; Penfield, Randall D.

2010-01-01

The increase in the squared multiple correlation coefficient ([delta]R[superscript 2]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. Algina, Keselman, and Penfield found that intervals based on asymptotic principles were typically very inaccurate, even though the sample size…

Statistical experiments using the multiple regression research for prediction of proper hardness in areas of phosphorus cast-iron brake shoes manufacturing

NASA Astrophysics Data System (ADS)

Kiss, I.; Cioată, V. G.; Ratiu, S. A.; Rackov, M.; Penčić, M.

2018-01-01

Multivariate research is important in areas of cast-iron brake shoes manufacturing, because many variables interact with each other simultaneously. This article focuses on expressing the multiple linear regression model related to the hardness assurance by the chemical composition of the phosphorous cast irons destined to the brake shoes, having in view that the regression coefficients will illustrate the unrelated contributions of each independent variable towards predicting the dependent variable. In order to settle the multiple correlations between the hardness of the cast-iron brake shoes, and their chemical compositions several regression equations has been proposed. Is searched a mathematical solution which can determine the optimum chemical composition for the hardness desirable values. Starting from the above-mentioned affirmations two new statistical experiments are effectuated related to the values of Phosphorus [P], Manganese [Mn] and Silicon [Si]. Therefore, the regression equations, which describe the mathematical dependency between the above-mentioned elements and the hardness, are determined. As result, several correlation charts will be revealed.

Interpret with caution: multicollinearity in multiple regression of cognitive data.

PubMed

Morrison, Catriona M

2003-08-01

Shibihara and Kondo in 2002 reported a reanalysis of the 1997 Kanji picture-naming data of Yamazaki, Ellis, Morrison, and Lambon-Ralph in which independent variables were highly correlated. Their addition of the variable visual familiarity altered the previously reported pattern of results, indicating that visual familiarity, but not age of acquisition, was important in predicting Kanji naming speed. The present paper argues that caution should be taken when drawing conclusions from multiple regression analyses in which the independent variables are so highly correlated, as such multicollinearity can lead to unreliable output.

Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.

PubMed

He, Dan; Kuhn, David; Parida, Laxmi

2016-06-15

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.

Physical and Cognitive-Affective Factors Associated with Fatigue in Individuals with Fibromyalgia: A Multiple Regression Analysis

ERIC Educational Resources Information Center

Muller, Veronica; Brooks, Jessica; Tu, Wei-Mo; Moser, Erin; Lo, Chu-Ling; Chan, Fong

2015-01-01

Purpose: The main objective of this study was to determine the extent to which physical and cognitive-affective factors are associated with fibromyalgia (FM) fatigue. Method: A quantitative descriptive design using correlation techniques and multiple regression analysis. The participants consisted of 302 members of the National Fibromyalgia &…

Quantitative Assessment of Cervical Vertebral Maturation Using Cone Beam Computed Tomography in Korean Girls

PubMed Central

Byun, Bo-Ram; Kim, Yong-Il; Maki, Koutaro; Son, Woo-Sung

2015-01-01

This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6–18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R 2 had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status. PMID:25878721

Data Mining Methods Applied to Flight Operations Quality Assurance Data: A Comparison to Standard Statistical Methods

NASA Technical Reports Server (NTRS)

Stolzer, Alan J.; Halford, Carl

2007-01-01

In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.

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.

Fast determination of total ginsenosides content in ginseng powder by near infrared reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Chen, Hua-cai; Chen, Xing-dan; Lu, Yong-jun; Cao, Zhi-qiang

2006-01-01

Near infrared (NIR) reflectance spectroscopy was used to develop a fast determination method for total ginsenosides in Ginseng (Panax Ginseng) powder. The spectra were analyzed with multiplicative signal correction (MSC) correlation method. The best correlative spectra region with the total ginsenosides content was 1660 nm~1880 nm and 2230nm~2380 nm. The NIR calibration models of ginsenosides were built with multiple linear regression (MLR), principle component regression (PCR) and partial least squares (PLS) regression respectively. The results showed that the calibration model built with PLS combined with MSC and the optimal spectrum region was the best one. The correlation coefficient and the root mean square error of correction validation (RMSEC) of the best calibration model were 0.98 and 0.15% respectively. The optimal spectrum region for calibration was 1204nm~2014nm. The result suggested that using NIR to rapidly determinate the total ginsenosides content in ginseng powder were feasible.

Tools to Support Interpreting Multiple Regression in the Face of Multicollinearity

PubMed Central

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K.

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses. PMID:22457655

Tools to support interpreting multiple regression in the face of multicollinearity.

PubMed

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses.

Estimating Optimal Transformations for Multiple Regression and Correlation.

DTIC Science & Technology

1982-07-01

S w.EECTli1Z"", , J OCT 0 11982 u! !for Public its... .. . ESTIMATING OPTIMAL TRANSFORMATIONS FOR MULTIPLE REGRESSION AND CORRELATION by Leo...in the plot lb of *(yk) versus 1 < k < 200. Figure lc is a plot of $*(xk) versus xk. These plots clearly suggest the transformati " s 6(y) = log(y) and...direct .814 .022 ACE .808 .031 -13- Figure la6L ’ ’ I . . . S " ’ ’ . . I ’ 6- - - .4...... Co o • . o ’ 0 0.2 0.4 0.5 0.8 1 Fi gure lb2 2 2 // II / / -/

Partitioning sources of variation in vertebrate species richness

USGS Publications Warehouse

Boone, R.B.; Krohn, W.B.

2000-01-01

Aim: To explore biogeographic patterns of terrestrial vertebrates in Maine, USA using techniques that would describe local and spatial correlations with the environment. Location: Maine, USA. Methods: We delineated the ranges within Maine (86,156 km2) of 275 species using literature and expert review. Ranges were combined into species richness maps, and compared to geomorphology, climate, and woody plant distributions. Methods were adapted that compared richness of all vertebrate classes to each environmental correlate, rather than assessing a single explanatory theory. We partitioned variation in species richness into components using tree and multiple linear regression. Methods were used that allowed for useful comparisons between tree and linear regression results. For both methods we partitioned variation into broad-scale (spatially autocorrelated) and fine-scale (spatially uncorrelated) explained and unexplained components. By partitioning variance, and using both tree and linear regression in analyses, we explored the degree of variation in species richness for each vertebrate group that Could be explained by the relative contribution of each environmental variable. Results: In tree regression, climate variation explained richness better (92% of mean deviance explained for all species) than woody plant variation (87%) and geomorphology (86%). Reptiles were highly correlated with environmental variation (93%), followed by mammals, amphibians, and birds (each with 84-82% deviance explained). In multiple linear regression, climate was most closely associated with total vertebrate richness (78%), followed by woody plants (67%) and geomorphology (56%). Again, reptiles were closely correlated with the environment (95%), followed by mammals (73%), amphibians (63%) and birds (57%). Main conclusions: Comparing variation explained using tree and multiple linear regression quantified the importance of nonlinear relationships and local interactions between species richness and environmental variation, identifying the importance of linear relationships between reptiles and the environment, and nonlinear relationships between birds and woody plants, for example. Conservation planners should capture climatic variation in broad-scale designs; temperatures may shift during climate change, but the underlying correlations between the environment and species richness will presumably remain.

Cancer Patients Enrolled in a Smoking Cessation Clinical Trial: Characteristics and Correlates of Smoking Rate and Nicotine Dependence.

PubMed

Miele, Andrew; Thompson, Morgan; Jao, Nancy C; Kalhan, Ravi; Leone, Frank; Hogarth, Lee; Hitsman, Brian; Schnoll, Robert

2018-01-01

A substantial proportion of cancer patients continue to smoke after their diagnosis but few studies have evaluated correlates of nicotine dependence and smoking rate in this population, which could help guide smoking cessation interventions. This study evaluated correlates of smoking rate and nicotine dependence among 207 cancer patients. A cross-sectional analysis using multiple linear regression evaluated disease, demographic, affective, and tobacco-seeking correlates of smoking rate and nicotine dependence. Smoking rate was assessed using a timeline follow-back method. The Fagerström Test for Nicotine Dependence measured levels of nicotine dependence. A multiple linear regression predicting nicotine dependence showed an association with smoking to alleviate a sense of addiction from the Reasons for Smoking scale and tobacco-seeking behavior from the concurrent choice task ( p < .05), but not with affect measured by the HADS and PANAS ( p > .05). Multiple linear regression predicting prequit showed an association with smoking to alleviate addiction ( p < .05). ANOVA showed that Caucasian participants reported greater rates of smoking compared to other races. The results suggest that behavioral smoking cessation interventions that focus on helping patients to manage tobacco-seeking behavior, rather than mood management interventions, could help cancer patients quit smoking.

Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes

NASA Astrophysics Data System (ADS)

Mekanik, F.; Imteaz, M. A.; Gato-Trinidad, S.; Elmahdi, A.

2013-10-01

In this study, the application of Artificial Neural Networks (ANN) and Multiple regression analysis (MR) to forecast long-term seasonal spring rainfall in Victoria, Australia was investigated using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as potential predictors. The use of dual (combined lagged ENSO-IOD) input sets for calibrating and validating ANN and MR Models is proposed to investigate the simultaneous effect of past values of these two major climate modes on long-term spring rainfall prediction. The MR models that did not violate the limits of statistical significance and multicollinearity were selected for future spring rainfall forecast. The ANN was developed in the form of multilayer perceptron using Levenberg-Marquardt algorithm. Both MR and ANN modelling were assessed statistically using mean square error (MSE), mean absolute error (MAE), Pearson correlation (r) and Willmott index of agreement (d). The developed MR and ANN models were tested on out-of-sample test sets; the MR models showed very poor generalisation ability for east Victoria with correlation coefficients of -0.99 to -0.90 compared to ANN with correlation coefficients of 0.42-0.93; ANN models also showed better generalisation ability for central and west Victoria with correlation coefficients of 0.68-0.85 and 0.58-0.97 respectively. The ability of multiple regression models to forecast out-of-sample sets is compatible with ANN for Daylesford in central Victoria and Kaniva in west Victoria (r = 0.92 and 0.67 respectively). The errors of the testing sets for ANN models are generally lower compared to multiple regression models. The statistical analysis suggest the potential of ANN over MR models for rainfall forecasting using large scale climate modes.

Risk factors for autistic regression: results of an ambispective cohort study.

PubMed

Zhang, Ying; Xu, Qiong; Liu, Jing; Li, She-chang; Xu, Xiu

2012-08-01

A subgroup of children diagnosed with autism experience developmental regression featured by a loss of previously acquired abilities. The pathogeny of autistic regression is unknown, although many risk factors likely exist. To better characterize autistic regression and investigate the association between autistic regression and potential influencing factors in Chinese autistic children, we conducted an ambispective study with a cohort of 170 autistic subjects. Analyses by multiple logistic regression showed significant correlations between autistic regression and febrile seizures (OR = 3.53, 95% CI = 1.17-10.65, P = .025), as well as with a family history of neuropsychiatric disorders (OR = 3.62, 95% CI = 1.35-9.71, P = .011). This study suggests that febrile seizures and family history of neuropsychiatric disorders are correlated with autistic regression.

Novel Index (Hepatic Receptor: IHR) to Evaluate Hepatic Functional Reserve Using (99m)Tc-GSA Scintigraphy.

PubMed

Hasegawa, Daisuke; Onishi, Hideo; Matsutomo, Norikazu

2016-02-01

This study aimed to evaluate the novel index of hepatic receptor (IHR) on the regression analysis derived from time activity curve of the liver for hepatic functional reserve. Sixty patients had undergone (99m)Tc-galactosyl serum albumin ((99m)Tc-GSA) scintigraphy in the retrospective clinical study. Time activity curves for liver were obtained by region of interest (ROI) on the whole liver. A novel hepatic functional predictor was calculated with multiple regression analysis of time activity curves. In the multiple regression function, the objective variables were the indocyanine green (ICG) retention rate at 15 min, and the explanatory variables were the liver counts in 3-min intervals until end from beginning. Then, this result was defined by IHR, and we analyzed the correlation between IHR and ICG, uptake ratio of the heart at 15 minutes to that at 3 minutes (HH15), uptake ratio of the liver to the liver plus heart at 15 minutes (LHL15), and index of convexity (IOC). Regression function of IHR was derived as follows: IHR=0.025×L(6)-0.052×L(12)+0.027×L(27). The multiple regression analysis indicated that liver counts at 6 min, 12 min, and 27 min were significantly related to objective variables. The correlation coefficient between IHR and ICG was 0.774, and the correlation coefficient between ICG and conventional indices (HH15, LHL15, and IOC) were 0.837, 0.773, and 0.793, respectively. IHR had good correlation with HH15, LHL15, and IOC. The finding results suggested that IHR would provide clinical benefit for hepatic functional assessment in the (99m)Tc-GSA scintigraphy.

A Modified Double Multiple Nonlinear Regression Constitutive Equation for Modeling and Prediction of High Temperature Flow Behavior of BFe10-1-2 Alloy

NASA Astrophysics Data System (ADS)

Cai, Jun; Wang, Kuaishe; Shi, Jiamin; Wang, Wen; Liu, Yingying

2018-01-01

Constitutive analysis for hot working of BFe10-1-2 alloy was carried out by using experimental stress-strain data from isothermal hot compression tests, in a wide range of temperature of 1,023 1,273 K, and strain rate range of 0.001 10 s-1. A constitutive equation based on modified double multiple nonlinear regression was proposed considering the independent effects of strain, strain rate, temperature and their interrelation. The predicted flow stress data calculated from the developed equation was compared with the experimental data. Correlation coefficient (R), average absolute relative error (AARE) and relative errors were introduced to verify the validity of the developed constitutive equation. Subsequently, a comparative study was made on the capability of strain-compensated Arrhenius-type constitutive model. The results showed that the developed constitutive equation based on modified double multiple nonlinear regression could predict flow stress of BFe10-1-2 alloy with good correlation and generalization.

Disentangling the Correlates of Drug Use in a Clinic and Community Sample: A Regression Analysis of the Associations between Drug Use, Years-of-School, Impulsivity, IQ, Working Memory, and Psychiatric Symptoms.

PubMed

Heyman, Gene M; Dunn, Brian J; Mignone, Jason

2014-01-01

Years-of-school is negatively correlated with illicit drug use. However, educational attainment is positively correlated with IQ and negatively correlated with impulsivity, two traits that are also correlated with drug use. Thus, the negative correlation between education and drug use may reflect the correlates of schooling, not schooling itself. To help disentangle these relations we obtained measures of working memory, simple memory, IQ, disposition (impulsivity and psychiatric status), years-of-school and frequency of illicit and licit drug use in methadone clinic and community drug users. We found strong zero-order correlations between all measures, including IQ, impulsivity, years-of-school, psychiatric symptoms, and drug use. However, multiple regression analyses revealed a different picture. The significant predictors of illicit drug use were gender, involvement in a methadone clinic, and years-of-school. That is, psychiatric symptoms, impulsivity, cognition, and IQ no longer predicted illicit drug use in the multiple regression analyses. Moreover, high risk subjects (low IQ and/or high impulsivity) who spent 14 or more years in school used stimulants and opiates less than did low risk subjects who had spent <14 years in school. Smoking and drinking had a different correlational structure. IQ and years-of-school predicted whether someone ever became a smoker, whereas impulsivity predicted the frequency of drinking bouts, but years-of-school did not. Many subjects reported no use of one or more drugs, resulting in a large number of "zeroes" in the data sets. Cragg's Double-Hurdle regression method proved the best approach for dealing with this problem. To our knowledge, this is the first report to show that years-of-school predicts lower levels of illicit drug use after controlling for IQ and impulsivity. This paper also highlights the advantages of Double-Hurdle regression methods for analyzing the correlates of drug use in community samples.

Predictive value of grade point average (GPA), Medical College Admission Test (MCAT), internal examinations (Block) and National Board of Medical Examiners (NBME) scores on Medical Council of Canada qualifying examination part I (MCCQE-1) scores.

PubMed

Roy, Banibrata; Ripstein, Ira; Perry, Kyle; Cohen, Barry

2016-01-01

To determine whether the pre-medical Grade Point Average (GPA), Medical College Admission Test (MCAT), Internal examinations (Block) and National Board of Medical Examiners (NBME) scores are correlated with and predict the Medical Council of Canada Qualifying Examination Part I (MCCQE-1) scores. Data from 392 admitted students in the graduating classes of 2010-2013 at University of Manitoba (UofM), College of Medicine was considered. Pearson's correlation to assess the strength of the relationship, multiple linear regression to estimate MCCQE-1 score and stepwise linear regression to investigate the amount of variance were employed. Complete data from 367 (94%) students were studied. The MCCQE-1 had a moderate-to-large positive correlation with NBME scores and Block scores but a low correlation with GPA and MCAT scores. The multiple linear regression model gives a good estimate of the MCCQE-1 (R2 =0.604). Stepwise regression analysis demonstrated that 59.2% of the variation in the MCCQE-1 was accounted for by the NBME, but only 1.9% by the Block exams, and negligible variation came from the GPA and the MCAT. Amongst all the examinations used at UofM, the NBME is most closely correlated with MCCQE-1.

Emission and distribution of phosphine in paddy fields and its relationship with greenhouse gases.

PubMed

Chen, Weiyi; Niu, Xiaojun; An, Shaorong; Sheng, Hong; Tang, Zhenghua; Yang, Zhiquan; Gu, Xiaohong

2017-12-01

Phosphine (PH 3 ), as a gaseous phosphide, plays an important role in the phosphorus cycle in ecosystems. In this study, the emission and distribution of phosphine, carbon dioxide (CO 2 ) and methane (CH 4 ) in paddy fields were investigated to speculate the future potential impacts of enhanced greenhouse effect on phosphorus cycle involved in phosphine by the method of Pearson correlation analysis and multiple linear regression analysis. During the whole period of rice growth, there was a significant positive correlation between CO 2 emission flux and PH 3 emission flux (r=0.592, p=0.026, n=14). Similarly, a significant positive correlation of emission flux was also observed between CH 4 and PH 3 (r=0.563, p=0.036, n=14). The linear regression relationship was determined as [PH 3 ] flux =0.007[CO 2 ] flux +0.063[CH 4 ] flux -4.638. No significant differences were observed for all values of matrix-bound phosphine (MBP), soil carbon dioxide (SCO 2 ), and soil methane (SCH 4 ) in paddy soils. However, there was a significant positive correlation between MBP and SCO 2 at heading, flowering and ripening stage. The correlation coefficients were 0.909, 0.890 and 0.827, respectively. In vertical distribution, MBP had the analogical variation trend with SCO 2 and SCH 4 . Through Pearson correlation analysis and multiple stepwise linear regression analysis, pH, redox potential (Eh), total phosphorus (TP) and acid phosphatase (ACP) were identified as the principal factors affecting MBP levels, with correlative rankings of Eh>pH>TP>ACP. The multiple stepwise regression model ([MBP]=0.456∗[ACP]+0.235∗[TP]-1.458∗[Eh]-36.547∗[pH]+352.298) was obtained. The findings in this study hold great reference values to the global biogeochemical cycling of phosphorus in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Assessment of Communications-related Admissions Criteria in a Three-year Pharmacy Program

PubMed Central

Tejada, Frederick R.; Lang, Lynn A.; Purnell, Miriam; Acedera, Lisa; Ngonga, Ferdinand

2015-01-01

Objective. To determine if there is a correlation between TOEFL and other admissions criteria that assess communications skills (ie, PCAT variables: verbal, reading, essay, and composite), interview, and observational scores and to evaluate TOEFL and these admissions criteria as predictors of academic performance. Methods. Statistical analyses included two sample t tests, multiple regression and Pearson’s correlations for parametric variables, and Mann-Whitney U for nonparametric variables, which were conducted on the retrospective data of 162 students, 57 of whom were foreign-born. Results. The multiple regression model of the other admissions criteria on TOEFL was significant. There was no significant correlation between TOEFL scores and academic performance. However, significant correlations were found between the other admissions criteria and academic performance. Conclusion. Since TOEFL is not a significant predictor of either communication skills or academic success of foreign-born PharmD students in the program, it may be eliminated as an admissions criterion. PMID:26430273

Assessment of Communications-related Admissions Criteria in a Three-year Pharmacy Program.

PubMed

Parmar, Jayesh R; Tejada, Frederick R; Lang, Lynn A; Purnell, Miriam; Acedera, Lisa; Ngonga, Ferdinand

2015-08-25

To determine if there is a correlation between TOEFL and other admissions criteria that assess communications skills (ie, PCAT variables: verbal, reading, essay, and composite), interview, and observational scores and to evaluate TOEFL and these admissions criteria as predictors of academic performance. Statistical analyses included two sample t tests, multiple regression and Pearson's correlations for parametric variables, and Mann-Whitney U for nonparametric variables, which were conducted on the retrospective data of 162 students, 57 of whom were foreign-born. The multiple regression model of the other admissions criteria on TOEFL was significant. There was no significant correlation between TOEFL scores and academic performance. However, significant correlations were found between the other admissions criteria and academic performance. Since TOEFL is not a significant predictor of either communication skills or academic success of foreign-born PharmD students in the program, it may be eliminated as an admissions criterion.

Multiple regression equations modelling of groundwater of Ajmer-Pushkar railway line region, Rajasthan (India).

PubMed

Mathur, Praveen; Sharma, Sarita; Soni, Bhupendra

2010-01-01

In the present work, an attempt is made to formulate multiple regression equations using all possible regressions method for groundwater quality assessment of Ajmer-Pushkar railway line region in pre- and post-monsoon seasons. Correlation studies revealed the existence of linear relationships (r 0.7) for electrical conductivity (EC), total hardness (TH) and total dissolved solids (TDS) with other water quality parameters. The highest correlation was found between EC and TDS (r = 0.973). EC showed highly significant positive correlation with Na, K, Cl, TDS and total solids (TS). TH showed highest correlation with Ca and Mg. TDS showed significant correlation with Na, K, SO4, PO4 and Cl. The study indicated that most of the contamination present was water soluble or ionic in nature. Mg was present as MgCl2; K mainly as KCl and K2SO4, and Na was present as the salts of Cl, SO4 and PO4. On the other hand, F and NO3 showed no significant correlations. The r2 values and F values (at 95% confidence limit, alpha = 0.05) for the modelled equations indicated high degree of linearity among independent and dependent variables. Also the error % between calculated and experimental values was contained within +/- 15% limit.

Overcoming multicollinearity in multiple regression using correlation coefficient

NASA Astrophysics Data System (ADS)

Zainodin, H. J.; Yap, S. J.

2013-09-01

Multicollinearity happens when there are high correlations among independent variables. In this case, it would be difficult to distinguish between the contributions of these independent variables to that of the dependent variable as they may compete to explain much of the similar variance. Besides, the problem of multicollinearity also violates the assumption of multiple regression: that there is no collinearity among the possible independent variables. Thus, an alternative approach is introduced in overcoming the multicollinearity problem in achieving a well represented model eventually. This approach is accomplished by removing the multicollinearity source variables on the basis of the correlation coefficient values based on full correlation matrix. Using the full correlation matrix can facilitate the implementation of Excel function in removing the multicollinearity source variables. It is found that this procedure is easier and time-saving especially when dealing with greater number of independent variables in a model and a large number of all possible models. Hence, in this paper detailed insight of the procedure is shown, compared and implemented.

[Correlation of retinol binding protein 4 with 
metabolic indexes of glucose and 
lipid, bile cholesterol saturation index].

PubMed

Wang, Wen; Li, Nianfeng

2015-06-01

To measure retinol binding protein 4 (RBP4) levels in serum and bile and to analyze their relationship with insulin resistance, dyslipidemia or cholesterol saturation index (CSI).
 A total of 60 patients with gallstone were divided into a diabetes group (n=30) and a control group (n=30). The concentrations of RBP4 in serum and bile were detected by enzyme-linked immunosorbent assay (ELISA). Enzyme colorimetric method was used to measure the concentration of biliary cholesterol, bile acid and phospholipid. Biliary CSI was calculated by Carey table. Partial correlation and multiple linear regression analysis were used to evaluate the correlation between the RBP4 levels in serum or bile and the above indexes.
 The RBP4 concentrations in serum and bile in the diabetes group were significantly elevated compared with those in the control group (both P<0.01). There was no significant difference in the serum total bile acid (TBA), serum triglyceride (TG), serum high-density lipoprotein (HDL), bile TBA, bile total cholesterol (TC) , bile phospholipids and bile CSI between the 2 groups (all P>0.05); but the serum TC, low density lipoprotein (LDL), fasting blood glucose (FBG), fasting insulin (FINS), and homeostasis model assessment for insulin resistance (HOMA-IR) in the diabetes group were significantly increased compared to those in the control group (all P<0.05). The partial correlation analysis, which was adjusted by age, showed that the bile RBP4 was positively correlated with body mass index (BMI), waist circumference (WC), FINS, FBG, TC, LDL and HOMA-IR (r=0.283, 0.405, 0.685, 0.667, 0.553, 0.424 and 0.735, respectively), and the serum RBP4 was also positively correlated with the WC, FINS, FBG, TC, LDL and HOMA-IR (r=0.317, 0.734, 0.609, 0.528, 0.386 and 0.751, respectively). Stepwise multivariate linear regression analysis suggested that the HOMA-IR, BMI and WC were independently correlated with the level of bile RBP4 (multiple regression equation: Ybile RBP4=2.372XHOMA-IR+0.420XBMI+0.178XWC-26.813), and the serum RBP4 level was correlated with the HOMA-IR and WC independently (multiple regression equation: Yserum RBP4=2.832XHOMA-IR +0.235XWC-20.128). Multiple regression equations showed that HOMA-IR was the strongest correlation factor with RBP4.
 RBP4 concentrations in serum and bile in the diabetes group are significantly higher than those in the control group. HOMA-IR, BMI and WC are independently correlated with the level of bile RBP4. HOMA-IR and WC are independently correlated with the serum RBP4 level. HOMA-IR is the strongest correlation factor with RBP4. RBP4 might play an important role in the course of gallstone formation in Type 2 diabetes mellitus.

Visual Acuity Is Correlated with the Area of the Foveal Avascular Zone in Diabetic Retinopathy and Retinal Vein Occlusion.

PubMed

Balaratnasingam, Chandrakumar; Inoue, Maiko; Ahn, Seungjun; McCann, Jesse; Dhrami-Gavazi, Elona; Yannuzzi, Lawrence A; Freund, K Bailey

2016-11-01

To determine if the area of the foveal avascular zone (FAZ) is correlated with visual acuity (VA) in diabetic retinopathy (DR) and retinal vein occlusion (RVO). Cross-sectional study. Ninety-five eyes of 66 subjects with DR (65 eyes), branch retinal vein occlusion (19 eyes), and central retinal vein occlusion (11 eyes). Structural optical coherence tomography (OCT; Spectralis, Heidelberg Engineering) and OCT angiography (OCTA; Avanti, Optovue RTVue XR) data from a single visit were analyzed. FAZ area, point thickness of central fovea, central 1-mm subfield thickness, the occurrence of intraretinal cysts, ellipsoid zone disruption, and disorganization of retinal inner layers (DRIL) length were measured. VA was also recorded. Correlations between FAZ area and VA were explored using regression models. Main outcome measure was VA. Mean age was 62.9±13.2 years. There was no difference in demographic and OCT-derived anatomic measurements between branch retinal vein occlusion and central retinal vein occlusion groups (all P ≥ 0.058); therefore, data from the 2 groups were pooled together to a single RVO group for further statistical comparisons. Univariate and multiple regression analysis showed that the area of the FAZ was significantly correlated with VA in DR and RVO (all P ≤ 0.003). The relationship between FAZ area and VA varied with age (P = 0.026) such that for a constant FAZ area, an increase in patient age was associated with poorer vision (rise in logarithm of the minimum angle of resolution visual acuity). Disruption of the ellipsoid zone was significantly correlated with VA in univariate and multiple regression analysis (both P < 0.001). Occurrence of intraretinal cysts, DRIL length, and lens status were significantly correlated with VA in the univariate regression analysis (P ≤ 0.018) but not the multiple regression analysis (P ≥ 0.210). Remaining variables evaluated in this study were not predictive of VA (all P ≥ 0.225). The area of the FAZ is significantly correlated with VA in DR and RVO and this relationship is modulated by patient age. Further study about FAZ area and VA correlations during the natural course of retinal vascular diseases and following treatment is warranted. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Two SPSS programs for interpreting multiple regression results.

PubMed

Lorenzo-Seva, Urbano; Ferrando, Pere J; Chico, Eliseo

2010-02-01

When multiple regression is used in explanation-oriented designs, it is very important to determine both the usefulness of the predictor variables and their relative importance. Standardized regression coefficients are routinely provided by commercial programs. However, they generally function rather poorly as indicators of relative importance, especially in the presence of substantially correlated predictors. We provide two user-friendly SPSS programs that implement currently recommended techniques and recent developments for assessing the relevance of the predictors. The programs also allow the user to take into account the effects of measurement error. The first program, MIMR-Corr.sps, uses a correlation matrix as input, whereas the second program, MIMR-Raw.sps, uses the raw data and computes bootstrap confidence intervals of different statistics. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from http://brm.psychonomic-journals.org/content/supplemental.

Effect of Ankle Range of Motion (ROM) and Lower-Extremity Muscle Strength on Static Balance Control Ability in Young Adults: A Regression Analysis

PubMed Central

Kim, Seong-Gil

2018-01-01

Background The purpose of this study was to investigate the effect of ankle ROM and lower-extremity muscle strength on static balance control ability in young adults. Material/Methods This study was conducted with 65 young adults, but 10 young adults dropped out during the measurement, so 55 young adults (male: 19, female: 36) completed the study. Postural sway (length and velocity) was measured with eyes open and closed, and ankle ROM (AROM and PROM of dorsiflexion and plantarflexion) and lower-extremity muscle strength (flexor and extensor of hip, knee, and ankle joint) were measured. Pearson correlation coefficient was used to examine the correlation between variables and static balance ability. Simple linear regression analysis and multiple linear regression analysis were used to examine the effect of variables on static balance ability. Results In correlation analysis, plantarflexion ROM (AROM and PROM) and lower-extremity muscle strength (except hip extensor) were significantly correlated with postural sway (p<0.05). In simple correlation analysis, all variables that passed the correlation analysis procedure had significant influence (p<0.05). In multiple linear regression analysis, plantar flexion PROM with eyes open significantly influenced sway length (B=0.681) and sway velocity (B=0.011). Conclusions Lower-extremity muscle strength and ankle plantarflexion ROM influenced static balance control ability, with ankle plantarflexion PROM showing the greatest influence. Therefore, both contractile structures and non-contractile structures should be of interest when considering static balance control ability improvement. PMID:29760375

Effect of Ankle Range of Motion (ROM) and Lower-Extremity Muscle Strength on Static Balance Control Ability in Young Adults: A Regression Analysis.

PubMed

Kim, Seong-Gil; Kim, Wan-Soo

2018-05-15

BACKGROUND The purpose of this study was to investigate the effect of ankle ROM and lower-extremity muscle strength on static balance control ability in young adults. MATERIAL AND METHODS This study was conducted with 65 young adults, but 10 young adults dropped out during the measurement, so 55 young adults (male: 19, female: 36) completed the study. Postural sway (length and velocity) was measured with eyes open and closed, and ankle ROM (AROM and PROM of dorsiflexion and plantarflexion) and lower-extremity muscle strength (flexor and extensor of hip, knee, and ankle joint) were measured. Pearson correlation coefficient was used to examine the correlation between variables and static balance ability. Simple linear regression analysis and multiple linear regression analysis were used to examine the effect of variables on static balance ability. RESULTS In correlation analysis, plantarflexion ROM (AROM and PROM) and lower-extremity muscle strength (except hip extensor) were significantly correlated with postural sway (p<0.05). In simple correlation analysis, all variables that passed the correlation analysis procedure had significant influence (p<0.05). In multiple linear regression analysis, plantar flexion PROM with eyes open significantly influenced sway length (B=0.681) and sway velocity (B=0.011). CONCLUSIONS Lower-extremity muscle strength and ankle plantarflexion ROM influenced static balance control ability, with ankle plantarflexion PROM showing the greatest influence. Therefore, both contractile structures and non-contractile structures should be of interest when considering static balance control ability improvement.

Attachment Style, Social Support, and Coping as Psychosocial Correlates of Happiness in Persons with Spinal Cord Injuries

ERIC Educational Resources Information Center

Wilson, Lisa; Catalano, Denise; Sung, Connie; Phillips, Brian; Chou, Chih-Chin; Chan, Jacob Yui Chung; Chan, Fong

2013-01-01

Objective: To examine the roles of attachment, social support, and coping as psychosocial correlates in predicting happiness in people with spinal cord injuries. Design: Quantitative descriptive research design using multiple regression and correlation techniques. Participants: 274 individuals with spinal cord injuries. Outcome Measures: Happiness…

HRCT findings of collagen vascular disease-related interstitial pneumonia (CVD-IP): a comparative study among individual underlying diseases.

PubMed

Tanaka, N; Kunihiro, Y; Kubo, M; Kawano, R; Oishi, K; Ueda, K; Gondo, T

2018-05-29

To identify characteristic high-resolution computed tomography (CT) findings for individual collagen vascular disease (CVD)-related interstitial pneumonias (IPs). The HRCT findings of 187 patients with CVD, including 55 patients with rheumatoid arthritis (RA), 50 with systemic sclerosis (SSc), 46 with polymyositis/dermatomyositis (PM/DM), 15 with mixed connective tissue disease, 11 with primary Sjögren's syndrome, and 10 with systemic lupus erythematosus, were evaluated. Lung parenchymal abnormalities were compared among CVDs using χ 2 test, Kruskal-Wallis test, and multiple logistic regression analysis. A CT-pathology correlation was performed in 23 patients. In RA-IP, honeycombing was identified as the significant indicator based on multiple logistic regression analyses. Traction bronchiectasis (81.8%) was further identified as the most frequent finding based on χ 2 test. In SSc IP, lymph node enlargement and oesophageal dilatation were identified as the indicators based on multiple logistic regression analyses, and ground-glass opacity (GGO) was the most extensive based on Kruskal-Wallis test, which reflects the higher frequency of the pathological nonspecific interstitial pneumonia (NSIP) pattern present in the CT-pathology correlation. In PM/DM IP, airspace consolidation and the absence of honeycombing were identified as the indicators based on multiple logistic regression analyses, and predominance of consolidation over GGO (32.6%) and predominant subpleural distribution of GGO/consolidation (41.3%) were further identified as the most frequent findings based on χ 2 test, which reflects the higher frequency of the pathological NSIP and/or the organising pneumonia patterns present in the CT-pathology correlation. Several characteristic high-resolution CT findings with utility for estimating underlying CVD were identified. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Construction of multiple linear regression models using blood biomarkers for selecting against abdominal fat traits in broilers.

PubMed

Dong, J Q; Zhang, X Y; Wang, S Z; Jiang, X F; Zhang, K; Ma, G W; Wu, M Q; Li, H; Zhang, H

2018-01-01

Plasma very low-density lipoprotein (VLDL) can be used to select for low body fat or abdominal fat (AF) in broilers, but its correlation with AF is limited. We investigated whether any other biochemical indicator can be used in combination with VLDL for a better selective effect. Nineteen plasma biochemical indicators were measured in male chickens from the Northeast Agricultural University broiler lines divergently selected for AF content (NEAUHLF) in the fed state at 46 and 48 d of age. The average concentration of every parameter for the 2 d was used for statistical analysis. Levels of these 19 plasma biochemical parameters were compared between the lean and fat lines. The phenotypic correlations between these plasma biochemical indicators and AF traits were analyzed. Then, multiple linear regression models were constructed to select the best model used for selecting against AF content. and the heritabilities of plasma indicators contained in the best models were estimated. The results showed that 11 plasma biochemical indicators (triglycerides, total bile acid, total protein, globulin, albumin/globulin, aspartate transaminase, alanine transaminase, gamma-glutamyl transpeptidase, uric acid, creatinine, and VLDL) differed significantly between the lean and fat lines (P < 0.01), and correlated significantly with AF traits (P < 0.05). The best multiple linear regression models based on albumin/globulin, VLDL, triglycerides, globulin, total bile acid, and uric acid, had higher R2 (0.73) than the model based only on VLDL (0.21). The plasma parameters included in the best models had moderate heritability estimates (0.21 ≤ h2 ≤ 0.43). These results indicate that these multiple linear regression models can be used to select for lean broiler chickens. © 2017 Poultry Science Association Inc.

The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method.

PubMed

Peng, Ying; Li, Su-Ning; Pei, Xuexue; Hao, Kun

2018-03-01

Amultivariate regression statisticstrategy was developed to clarify multi-components content-effect correlation ofpanaxginseng saponins extract and predict the pharmacological effect by components content. In example 1, firstly, we compared pharmacological effects between panax ginseng saponins extract and individual saponin combinations. Secondly, we examined the anti-platelet aggregation effect in seven different saponin combinations of ginsenoside Rb1, Rg1, Rh, Rd, Ra3 and notoginsenoside R1. Finally, the correlation between anti-platelet aggregation and the content of multiple components was analyzed by a partial least squares algorithm. In example 2, firstly, 18 common peaks were identified in ten different batches of panax ginseng saponins extracts from different origins. Then, we investigated the anti-myocardial ischemia reperfusion injury effects of the ten different panax ginseng saponins extracts. Finally, the correlation between the fingerprints and the cardioprotective effects was analyzed by a partial least squares algorithm. Both in example 1 and 2, the relationship between the components content and pharmacological effect was modeled well by the partial least squares regression equations. Importantly, the predicted effect curve was close to the observed data of dot marked on the partial least squares regression model. This study has given evidences that themulti-component content is a promising information for predicting the pharmacological effects of traditional Chinese medicine.

STATLIB: NSWC Library of Statistical Programs and Subroutines

DTIC Science & Technology

1989-08-01

Uncorrelated Weighted Polynomial Regression 41 .WEPORC Correlated Weighted Polynomial Regression 45 MROP Multiple Regression Using Orthogonal Polynomials ...could not and should not be con- NSWC TR 89-97 verted to the new general purpose computer (the current CDC 995). Some were designed tu compute...personal computers. They are referred to as SPSSPC+, BMDPC, and SASPC and in general are less comprehensive than their mainframe counterparts. The basic

Time-localized wavelet multiple regression and correlation

NASA Astrophysics Data System (ADS)

Fernández-Macho, Javier

2018-02-01

This paper extends wavelet methodology to handle comovement dynamics of multivariate time series via moving weighted regression on wavelet coefficients. The concept of wavelet local multiple correlation is used to produce one single set of multiscale correlations along time, in contrast with the large number of wavelet correlation maps that need to be compared when using standard pairwise wavelet correlations with rolling windows. Also, the spectral properties of weight functions are investigated and it is argued that some common time windows, such as the usual rectangular rolling window, are not satisfactory on these grounds. The method is illustrated with a multiscale analysis of the comovements of Eurozone stock markets during this century. It is shown how the evolution of the correlation structure in these markets has been far from homogeneous both along time and across timescales featuring an acute divide across timescales at about the quarterly scale. At longer scales, evidence from the long-term correlation structure can be interpreted as stable perfect integration among Euro stock markets. On the other hand, at intramonth and intraweek scales, the short-term correlation structure has been clearly evolving along time, experiencing a sharp increase during financial crises which may be interpreted as evidence of financial 'contagion'.

Importance of Preserving Cross-correlation in developing Statistically Downscaled Climate Forcings and in estimating Land-surface Fluxes and States

NASA Astrophysics Data System (ADS)

Das Bhowmik, R.; Arumugam, S.

2015-12-01

Multivariate downscaling techniques exhibited superiority over univariate regression schemes in terms of preserving cross-correlations between multiple variables- precipitation and temperature - from GCMs. This study focuses on two aspects: (a) develop an analytical solutions on estimating biases in cross-correlations from univariate downscaling approaches and (b) quantify the uncertainty in land-surface states and fluxes due to biases in cross-correlations in downscaled climate forcings. Both these aspects are evaluated using climate forcings available from both historical climate simulations and CMIP5 hindcasts over the entire US. The analytical solution basically relates the univariate regression parameters, co-efficient of determination of regression and the co-variance ratio between GCM and downscaled values. The analytical solutions are compared with the downscaled univariate forcings by choosing the desired p-value (Type-1 error) in preserving the observed cross-correlation. . For quantifying the impacts of biases on cross-correlation on estimating streamflow and groundwater, we corrupt the downscaled climate forcings with different cross-correlation structure.

Wavelet regression model in forecasting crude oil price

NASA Astrophysics Data System (ADS)

Hamid, Mohd Helmie; Shabri, Ani

2017-05-01

This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

Multiple regression for physiological data analysis: the problem of multicollinearity.

PubMed

Slinker, B K; Glantz, S A

1985-07-01

Multiple linear regression, in which several predictor variables are related to a response variable, is a powerful statistical tool for gaining quantitative insight into complex in vivo physiological systems. For these insights to be correct, all predictor variables must be uncorrelated. However, in many physiological experiments the predictor variables cannot be precisely controlled and thus change in parallel (i.e., they are highly correlated). There is a redundancy of information about the response, a situation called multicollinearity, that leads to numerical problems in estimating the parameters in regression equations; the parameters are often of incorrect magnitude or sign or have large standard errors. Although multicollinearity can be avoided with good experimental design, not all interesting physiological questions can be studied without encountering multicollinearity. In these cases various ad hoc procedures have been proposed to mitigate multicollinearity. Although many of these procedures are controversial, they can be helpful in applying multiple linear regression to some physiological problems.

Estimation of premorbid general fluid intelligence using traditional Chinese reading performance in Taiwanese samples.

PubMed

Chen, Ying-Jen; Ho, Meng-Yang; Chen, Kwan-Ju; Hsu, Chia-Fen; Ryu, Shan-Jin

2009-08-01

The aims of the present study were to (i) investigate if traditional Chinese word reading ability can be used for estimating premorbid general intelligence; and (ii) to provide multiple regression equations for estimating premorbid performance on Raven's Standard Progressive Matrices (RSPM), using age, years of education and Chinese Graded Word Reading Test (CGWRT) scores as predictor variables. Four hundred and twenty-six healthy volunteers (201 male, 225 female), aged 16-93 years (mean +/- SD, 41.92 +/- 18.19 years) undertook the tests individually under supervised conditions. Seventy percent of subjects were randomly allocated to the derivation group (n = 296), and the rest to the validation group (n = 130). RSPM score was positively correlated with CGWRT score and years of education. RSPM and CGWRT scores and years of education were also inversely correlated with age, but the declining trend for RSPM performance against age was steeper than that for CGWRT performance. Separate multiple regression equations were derived for estimating RSPM scores using different combinations of age, years of education, and CGWRT score for both groups. The multiple regression coefficient of each equation ranged from 0.71 to 0.80 with the standard error of estimate between 7 and 8 RSPM points. When fitting the data of one group to the equations derived from its counterpart group, the cross-validation multiple regression coefficients ranged from 0.71 to 0.79. There were no significant differences in the 'predicted-obtained' RSPM discrepancies between any equations. The regression equations derived in the present study may provide a basis for estimating premorbid RSPM performance.

Stature estimation from the lengths of the growing foot-a study on North Indian adolescents.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Passi, Neelam; DiMaggio, John A

2012-12-01

Stature estimation is considered as one of the basic parameters of the investigation process in unknown and commingled human remains in medico-legal case work. Race, age and sex are the other parameters which help in this process. Stature estimation is of the utmost importance as it completes the biological profile of a person along with the other three parameters of identification. The present research is intended to formulate standards for stature estimation from foot dimensions in adolescent males from North India and study the pattern of foot growth during the growing years. 154 male adolescents from the Northern part of India were included in the study. Besides stature, five anthropometric measurements that included the length of the foot from each toe (T1, T2, T3, T4, and T5 respectively) to pternion were measured on each foot. The data was analyzed statistically using Student's t-test, Pearson's correlation, linear and multiple regression analysis for estimation of stature and growth of foot during ages 13-18 years. Correlation coefficients between stature and all the foot measurements were found to be highly significant and positively correlated. Linear regression models and multiple regression models (with age as a co-variable) were derived for estimation of stature from the different measurements of the foot. Multiple regression models (with age as a co-variable) estimate stature with greater accuracy than the regression models for 13-18 years age group. The study shows the growth pattern of feet in North Indian adolescents and indicates that anthropometric measurements of the foot and its segments are valuable in estimation of stature in growing individuals of that population. Copyright © 2012 Elsevier Ltd. All rights reserved.

Self-reports of trauma and dissociation: An examination of context effects.

PubMed

Lemons, Peter; Lynn, Steven Jay

2016-08-01

To examine context effects in moderating the link between self-reported trauma and dissociation in undergraduate samples, we administered these measures either in the same or different experimental contexts. Trauma History Screen/THS (Carlson et al., 2011)-Dissociative Experiences Scale/DES-II (Bernstein & Putnam, 1986) correlations revealed a context effect (greater correlations in same test context), although multiple regression analyses did not confirm this finding. A context effect was supported in DES-Taxon scores using multiple regression for the THS but not the Modified Posttraumatic Stress Scale (MPSS-SR; Falsetti, Resnick, Resick, & Kilpatrick, 1993), an effect confirmed with correlation comparisons. Ethnicity influenced the association between measures of trauma and dissociation. Overall, the relation between measures of trauma and dissociation was small to medium, although high correlations were observed between the DES depersonalization/derealization subscale and the Multiscale Dissociation Inventory (Briere, Weathers, & Runtz, 2005) depersonalization and derealization subscales, supporting the construct validity of these measures. Copyright © 2016 Elsevier Inc. All rights reserved.

High-level language ability in healthy individuals and its relationship with verbal working memory.

PubMed

Antonsson, Malin; Longoni, Francesca; Einald, Christina; Hallberg, Lina; Kurt, Gabriella; Larsson, Kajsa; Nilsson, Tina; Hartelius, Lena

2016-01-01

The aims of the study were to investigate healthy subjects' performance on a clinical test of high-level language (HLL) and how it is related to demographic characteristics and verbal working memory (VWM). One hundred healthy subjects (20-79 years old) were assessed with the Swedish BeSS test (Laakso, Brunnegård, Hartelius, & Ahlsén, 2000) and two digit span tasks. Relationships between the demographic variables, VWM and BeSS were investigated both with bivariate correlations and multiple regression analysis. The results present the norms for BeSS. The correlations and multiple regression analysis show that demographic variables had limited influence on test performance. Measures of VWM were moderately related to total BeSS score and weakly to moderately correlated with five of the seven subtests. To conclude, education has an influence on the test as a whole but measures of VWM stood out as the most robust predictor of HLL.

Testing a single regression coefficient in high dimensional linear models

PubMed Central

Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2017-01-01

In linear regression models with high dimensional data, the classical z-test (or t-test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z-test to assess the significance of each covariate. Based on the p-value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively. PMID:28663668

Testing a single regression coefficient in high dimensional linear models.

PubMed

Lan, Wei; Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2016-11-01

In linear regression models with high dimensional data, the classical z -test (or t -test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z -test to assess the significance of each covariate. Based on the p -value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively.

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.

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…

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

Relationship between body composition and postural control in prepubertal overweight/obese children: A cross-sectional study.

PubMed

Villarrasa-Sapiña, Israel; Álvarez-Pitti, Julio; Cabeza-Ruiz, Ruth; Redón, Pau; Lurbe, Empar; García-Massó, Xavier

2018-02-01

Excess body weight during childhood causes reduced motor functionality and problems in postural control, a negative influence which has been reported in the literature. Nevertheless, no information regarding the effect of body composition on the postural control of overweight and obese children is available. The objective of this study was therefore to establish these relationships. A cross-sectional design was used to establish relationships between body composition and postural control variables obtained in bipedal eyes-open and eyes-closed conditions in twenty-two children. Centre of pressure signals were analysed in the temporal and frequency domains. Pearson correlations were applied to establish relationships between variables. Principal component analysis was applied to the body composition variables to avoid potential multicollinearity in the regression models. These principal components were used to perform a multiple linear regression analysis, from which regression models were obtained to predict postural control. Height and leg mass were the body composition variables that showed the highest correlation with postural control. Multiple regression models were also obtained and several of these models showed a higher correlation coefficient in predicting postural control than simple correlations. These models revealed that leg and trunk mass were good predictors of postural control. More equations were found in the eyes-open than eyes-closed condition. Body weight and height are negatively correlated with postural control. However, leg and trunk mass are better postural control predictors than arm or body mass. Finally, body composition variables are more useful in predicting postural control when the eyes are open. Copyright © 2017 Elsevier Ltd. All rights reserved.

A sampling study on rock properties affecting drilling rate index (DRI)

NASA Astrophysics Data System (ADS)

Yenice, Hayati; Özdoğan, Mehmet V.; Özfırat, M. Kemal

2018-05-01

Drilling rate index (DRI) developed in Norway is a very useful index in determining the drillability of rocks and even in performance prediction of hard rock TBMs and it requires special laboratory test equipment. Drillability is one of the most important subjects in rock excavation. However, determining drillability index from physical and mechanical properties of rocks is very important for practicing engineers such as underground excavation, drilling operations in open pit mining, underground mining and natural stone production. That is why many researchers have studied concerned with drillability to find the correlations between drilling rate index (DRI) and penetration rate, influence of geological properties on drillability prediction in tunneling, correlations between rock properties and drillability. In this study, the relationships between drilling rate index (DRI) and some physico-mechanical properties (Density, Shore hardness, uniaxial compressive strength (UCS, σc), Indirect tensile strength (ITS, σt)) of three different rock groups including magmatic, sedimentary and metamorphic were evaluated using both simple and multiple regression analysis. This study reveals the effects of rock properties on DRI according to different types of rocks. In simple regression, quite high correlations were found between DRI and uniaxial compressive strength (UCS) and also between DRI and indirect tensile strength (ITS) values. Multiple regression analyses revealed even higher correlations when compared to simple regression. Especially, UCS, ITS, Shore hardness (SH) and the interactions between them were found to be very effective on DRI values.

Optimization of selective breeding through analysis of morphological traits in Chinese sea bass (Lateolabrax maculatus).

PubMed

Wang, W; Ma, C Y; Chen, W; Ma, H Y; Zhang, H; Meng, Y Y; Ni, Y; Ma, L B

2016-08-19

Determining correlations between certain traits of economic importance constitutes an essential component of selective activities. In this study, our aim was to provide effective indicators for breeding programs of Lateolabrax maculatus, an important aquaculture species in China. We analyzed correlations between 20 morphometric traits and body weight, using correlation and path analyses. The results indicated that the correlations among all 21 traits were highly significant, with the highest correlation coefficient identified between total length and body weight. The path analysis indicated that total length (X 1 ), body width (X 5 ), distance from first dorsal fin origin to anal fin origin (X 10 ), snout length (X 16 ), eye diameter (X 17 ), eye cross (X 18 ), and slanting distance from snout tip to first dorsal fin origin (X 19 ) significantly affected body weight (Y) directly. The following multiple-regression equation was obtained using stepwise multiple-regression analysis: Y = -472.108 + 1.065X 1 + 7.728X 5 + 1.973X 10 - 7.024X 16 - 4.400X 17 - 3.338X 18 + 2.138X 19 , with an adjusted multiple-correlation coefficient of 0.947. Body width had the largest determinant coefficient, as well as the highest positive direct correlation with body weight. At the same time, high indirect effects with six other morphometric traits on L. maculatus body weight, through body width, were identified. Hence, body width could be a key factor that efficiently indicates significant effects on body weight in L. maculatus.

Exploring Race Differences in Correlates of Seniors' Satisfaction with Undergraduate Education

ERIC Educational Resources Information Center

Einarson, Marne K.; Matier, Michael W.

2005-01-01

This study employed multiple linear regression and decision tree analysis to examine the correlates of overall satisfaction with undergraduate education for white, Asian American, Latino and African American seniors enrolled at 17 doctoral/research universities. Satisfaction with the overall quality of instruction and social involvement were the…

Exploring Race Differences in Correlates of Seniors' Satisfaction with Undergraduate Education

ERIC Educational Resources Information Center

Einarson, Marne K.; Matier, Michael W.

2004-01-01

This study employed multiple linear regression and decision tree analysis to examine the correlates of overall satisfaction with undergraduate education for white, Asian American, Hispanic and African American seniors enrolled at 17 research-extensive universities. Satisfaction with the overall quality of instruction and social involvement were…

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

Multiple Regression with Varying Levels of Correlation among Predictors: Monte Carlo Sampling from Normal and Non-Normal Populations.

ERIC Educational Resources Information Center

Vasu, Ellen Storey

1978-01-01

The effects of the violation of the assumption of normality in the conditional distributions of the dependent variable, coupled with the condition of multicollinearity upon the outcome of testing the hypothesis that the regression coefficient equals zero, are investigated via a Monte Carlo study. (Author/JKS)

Inhibitory saccadic dysfunction is associated with cerebellar injury in multiple sclerosis.

PubMed

Kolbe, Scott C; Kilpatrick, Trevor J; Mitchell, Peter J; White, Owen; Egan, Gary F; Fielding, Joanne

2014-05-01

Cognitive dysfunction is common in patients with multiple sclerosis (MS). Saccadic eye movement paradigms such as antisaccades (AS) can sensitively interrogate cognitive function, in particular, the executive and attentional processes of response selection and inhibition. Although we have previously demonstrated significant deficits in the generation of AS in MS patients, the neuropathological changes underlying these deficits were not elucidated. In this study, 24 patients with relapsing-remitting MS underwent testing using an AS paradigm. Rank correlation and multiple regression analyses were subsequently used to determine whether AS errors in these patients were associated with: (i) neurological and radiological abnormalities, as measured by standard clinical techniques, (ii) cognitive dysfunction, and (iii) regionally specific cerebral white and gray-matter damage. Although AS error rates in MS patients did not correlate with clinical disability (using the Expanded Disability Status Score), T2 lesion load or brain parenchymal fraction, AS error rate did correlate with performance on the Paced Auditory Serial Addition Task and the Symbol Digit Modalities Test, neuropsychological tests commonly used in MS. Further, voxel-wise regression analyses revealed associations between AS errors and reduced fractional anisotropy throughout most of the cerebellum, and increased mean diffusivity in the cerebellar vermis. Region-wise regression analyses confirmed that AS errors also correlated with gray-matter atrophy in the cerebellum right VI subregion. These results support the use of the AS paradigm as a marker for cognitive dysfunction in MS and implicate structural and microstructural changes to the cerebellum as a contributing mechanism for AS deficits in these patients. Copyright © 2013 Wiley Periodicals, Inc.

Spatial and visuospatial working memory tests predict performance in classic multiple-object tracking in young adults, but nonspatial measures of the executive do not.

PubMed

Trick, Lana M; Mutreja, Rachna; Hunt, Kelly

2012-02-01

An individual-differences approach was used to investigate the roles of visuospatial working memory and the executive in multiple-object tracking. The Corsi Blocks and Visual Patterns Tests were used to assess visuospatial working memory. Two relatively nonspatial measures of the executive were used: operation span (OSPAN) and reading span (RSPAN). For purposes of comparison, the digit span test was also included (a measure not expected to correlate with tracking). The tests predicted substantial amounts of variance (R (2) = .33), and the visuospatial measures accounted for the majority (R (2) = .30), with each making a significant contribution. Although the executive measures correlated with each other, the RSPAN did not correlate with tracking. The correlation between OSPAN and tracking was similar in magnitude to that between digit span and tracking (p < .05 for both), and when regression was used to partial out shared variance between the two tests, the remaining variance predicted by the OSPAN was minimal (sr ( 2 ) = .029). When measures of spatial memory were included in the regression, the unique variance predicted by the OSPAN became negligible (sr ( 2 ) = .000004). This suggests that the executive, as measured by tests such as the OSPAN, plays little role in explaining individual differences in multiple-object tracking.

Pressures, Stresses, Anxieties, and On-Job Safety of the School Superintendent.

ERIC Educational Resources Information Center

Chand, Krishan

Identification of the causes of job stress for public school superintendents, with a focus on personal-experiential and task variables, is the purpose of this study. Methodology involved a mail survey of 1,531 randomly selected superintendents. Canonical correlation analysis (CCA) and multiple regression correlation (MCR) analysis were used to…

Relationships between World Health Organization "International Classification of Functioning, Disability and Health" Constructs and Participation in Adults with Severe Mental Illness

ERIC Educational Resources Information Center

Sánchez, Jennifer; Rosenthal, David A.; Chan, Fong; Brooks, Jessica; Bezyak, Jill L.

2016-01-01

Purpose: To examine the World Health Organization "International Classification of Functioning, Disability and Health" (ICF) constructs as correlates of community participation of people with severe mental illnesses (SMI). Methods: Quantitative descriptive research design using multiple regression and correlational techniques was used to…

Exact Interval Estimation, Power Calculation, and Sample Size Determination in Normal Correlation Analysis

ERIC Educational Resources Information Center

Shieh, Gwowen

2006-01-01

This paper considers the problem of analysis of correlation coefficients from a multivariate normal population. A unified theorem is derived for the regression model with normally distributed explanatory variables and the general results are employed to provide useful expressions for the distributions of simple, multiple, and partial-multiple…

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

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

Andrews, M; Abazeed, M; Woody, N

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less

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.

Sources of variability in satellite-derived estimates of phytoplankton production in the eastern tropical Pacific

NASA Technical Reports Server (NTRS)

Banse, Karl; Yong, Marina

1990-01-01

As a proxy for satellite CZCS observations and concurrent measurements of primary production rates, data from 138 stations occupied seasonally during 1967-1968 in the offshore eastern tropical Pacific were analyzed in terms of six temporal groups and our current regimes. Multiple linear regressions on column production Pt show that simulated satellite pigment is generally weakly correlated, but sometimes not correlated with Pt, and that incident irradiance, sea surface temperature, nitrate, transparency, and depths of mixed layer or nitracline assume little or no importance. After a proxy for the light-saturated chlorophyll-specific photosynthetic rate P(max) is added, the coefficient of determination ranges from 0.55 to 0.91 (median of 0.85) for the 10 cases. In stepwise multiple linear regressions the P(max) proxy is the best predictor for Pt.

Exercise, Diet, and Stress Management as Mediators between Functional Disability and Health-Related Quality of Life in Multiple Sclerosis

ERIC Educational Resources Information Center

Sung, Connie; Chiu, Chung-Yi; Lee, Eun-Jeong; Bezyak, Jill; Chan, Fong; Muller, Veronica

2013-01-01

The main objective of this study was to examine the mediational and moderational effect of exercise, diet, and stress management on the relationship between functional disability and health-related quality of life. Quantitative descriptive research design using multiple regression and correlation techniques was used. Participants were 215…

[Stature estimation for Sichuan Han nationality female based on X-ray technology with measurement of lumbar vertebrae].

PubMed

Qing, Si-han; Chang, Yun-feng; Dong, Xiao-ai; Li, Yuan; Chen, Xiao-gang; Shu, Yong-kang; Deng, Zhen-hua

2013-10-01

To establish the mathematical models of stature estimation for Sichuan Han female with measurement of lumbar vertebrae by X-ray to provide essential data for forensic anthropology research. The samples, 206 Sichuan Han females, were divided into three groups including group A, B and C according to the ages. Group A (206 samples) consisted of all ages, group B (116 samples) were 20-45 years old and 90 samples over 45 years old were group C. All the samples were examined lumbar vertebrae through CR technology, including the parameters of five centrums (L1-L5) as anterior border, posterior border and central heights (x1-x15), total central height of lumbar spine (x16), and the real height of every sample. The linear regression analysis was produced using the parameters to establish the mathematical models of stature estimation. Sixty-two trained subjects were tested to verify the accuracy of the mathematical models. The established mathematical models by hypothesis test of linear regression equation model were statistically significant (P<0.05). The standard errors of the equation were 2.982-5.004 cm, while correlation coefficients were 0.370-0.779 and multiple correlation coefficients were 0.533-0.834. The return tests of the highest correlation coefficient and multiple correlation coefficient of each group showed that the highest accuracy of the multiple regression equation, y = 100.33 + 1.489 x3 - 0.548 x6 + 0.772 x9 + 0.058 x12 + 0.645 x15, in group A were 80.6% (+/- lSE) and 100% (+/- 2SE). The established mathematical models in this study could be applied for the stature estimation for Sichuan Han females.

An investigation of the effect of seasonal activity levels on avian censusing

Treesearch

C. John Ralph

1981-01-01

Intensive variable distance circular-plot censuses and timed activity budget data were used to compare the effects of conspicuousness upon census results. In six of ten species no correlation was found, suggesting that all birds within the "Effective Detection Distance" (EDD) were seen. In four species there were significant correlations. Multiple regression...

Estimation of PM2.5 and PM10 using ground-based AOD measurements during KORUS-AQ campaign

NASA Astrophysics Data System (ADS)

Koo, J. H.; Kim, J.; Kim, S.; Go, S.; Lee, S.; Lee, H.; Mok, J.; Hong, J.; Lee, J.; Eck, T. F.; Holben, B. N.

2017-12-01

During the KORUS-AQ campaign (2 May - 12 June, 2016), aerosol optical depth (AOD) was obtained at multiple channels using various ground-based instruments at Yonsei University, Seoul: AERONET sunphotometer, SKYNET skyradiometer, Brewer spectrophotometer, and multi-filter rotating shadowband radiometer (MFRSR). At the same location, planetary boundary layer (PBL) height and vertical profile of backscattering coefficients also can be obtained based on the celiometer measurements. Using celiometer products and various AODs, we try to estimate the amount of particular matter (PM2.5 and PM10) and validate with in-situ surface PM2.5 and PM10 measurements from AIRKOREA network. Direct comparison between PM2.5 and AOD reveals that the ultraviolet(UV) channel AOD has better correlations, due to the higher sensitivity of short wavelength to the fine-mode particle. In contrast, PM10 shows the highest correlation with the near-infrared(NIR) AOD. Next, we extract the boundary-layer portion of AOD using either PBL height or vertical profile of backscattering coefficients to compare with PM2.5 and PM10. Both results enhance the correlation, but consideration of weighting factor calculated from backscattering coefficients shows larger contribution to the correlation increase. Finally, we performed the multiple linear regression to estimate PM2.5 and PM10 using AODs. Consideration of meteorology (temperature, wind speed, and relative humidity) can enhance the correlation and also O3 and NO2 consideration highly contributes to the high correlation. This finding implies the importance to consider the ambient condition of secondary aerosol formation related to the PM2.5 variation. Multiple regression model finally finds the correlation 0.7-0.8, and diminishes the wavelength-dependent correlation patterns.

Statistical research using the multiple regression analysis in areas of the cast hipereutectoid steel rolls manufacturing

NASA Astrophysics Data System (ADS)

Kiss, I.; Alexa, V.; Serban, S.; Rackov, M.; Čavić, M.

2018-01-01

The cast hipereutectoid steel (usually named Adamite) is a roll manufacturing destined material, having mechanical, chemical properties and Carbon [C] content of which stands between steelandiron, along-withitsalloyelements such as Nickel [Ni], Chrome [Cr], Molybdenum [Mo] and/or other alloy elements. Adamite Rolls are basically alloy steel rolls (a kind of high carbon steel) having hardness ranging from 40 to 55 degrees Shore C, with Carbon [C] percentage ranging from 1.35% until to 2% (usually between 1.2˜2.3%), the extra Carbon [C] and the special alloying element giving an extra wear resistance and strength. First of all the Adamite roll’s prominent feature is the small variation in hardness of the working surface, and has a good abrasion resistance and bite performance. This paper reviews key aspects of roll material properties and presents an analysis of the influences of chemical composition upon the mechanical properties (hardness) of the cast hipereutectoid steel rolls (Adamite). Using the multiple regression analysis (the double and triple regression equations), some mathematical correlations between the cast hipereutectoid steel rolls’ chemical composition and the obtained hardness are presented. In this work several results and evidence obtained by actual experiments are presented. Thus, several variation boundaries for the chemical composition of cast hipereutectoid steel rolls, in view the obtaining the proper values of the hardness, are revealed. For the multiple regression equations, correlation coefficients and graphical representations the software Matlab was used.

Multi-Target Regression via Robust Low-Rank Learning.

PubMed

Zhen, Xiantong; Yu, Mengyang; He, Xiaofei; Li, Shuo

2018-02-01

Multi-target regression has recently regained great popularity due to its capability of simultaneously learning multiple relevant regression tasks and its wide applications in data mining, computer vision and medical image analysis, while great challenges arise from jointly handling inter-target correlations and input-output relationships. In this paper, we propose Multi-layer Multi-target Regression (MMR) which enables simultaneously modeling intrinsic inter-target correlations and nonlinear input-output relationships in a general framework via robust low-rank learning. Specifically, the MMR can explicitly encode inter-target correlations in a structure matrix by matrix elastic nets (MEN); the MMR can work in conjunction with the kernel trick to effectively disentangle highly complex nonlinear input-output relationships; the MMR can be efficiently solved by a new alternating optimization algorithm with guaranteed convergence. The MMR leverages the strength of kernel methods for nonlinear feature learning and the structural advantage of multi-layer learning architectures for inter-target correlation modeling. More importantly, it offers a new multi-layer learning paradigm for multi-target regression which is endowed with high generality, flexibility and expressive ability. Extensive experimental evaluation on 18 diverse real-world datasets demonstrates that our MMR can achieve consistently high performance and outperforms representative state-of-the-art algorithms, which shows its great effectiveness and generality for multivariate prediction.

Science Teaching Efficacy of Preservice Elementary Teachers: Examination of the Multiple Factors Reported as Influential

NASA Astrophysics Data System (ADS)

Taştan Kırık, Özgecan

2013-12-01

This study explores the science teaching efficacy beliefs of pr-service elementary teachers and the relationship between efficacy beliefs and multiple factors such as antecedent factors (participation in extracurricular activities and number of science and science teaching methods courses taken), conceptual understanding, classroom management beliefs and science teaching attitudes. Science education majors ( n = 71) and elementary education majors ( n = 262) were compared with respect to these variables. Finally, the predictors of two constructs of science teaching efficacy beliefs, personal science teaching efficacy (PSTE) and science teaching outcome expectancy (STOE), were examined by multiple linear regression analysis. According to the results, participation in extracurricular activities has a significant but low correlation with science concept knowledge, science teaching attitudes, PSTE and STOE. In addition, there is a small but significant correlation between science concept knowledge and outcome expectancy, which leads the idea that preservice elementary teachers' conceptual understanding in science contributes to their science teaching self-efficacy. This study reveals a moderate correlation between science teaching attitudes and STOE and a high correlation between science teaching attitudes and PSTE. Additionally, although the correlation coefficient is low, the number of methodology courses was found to be one of the correlates of science teaching attitudes. Furthermore, students of both majors generally had positive self-efficacy beliefs on both the STOE and PSTE. Specifically, science education majors had higher science teaching self-efficacy than elementary education majors. Regression results showed that science teaching attitude is the major factor in predicting both PSTE and STOE for both groups.

Which symptoms contribute the most to patients' perception of health in multiple sclerosis?

PubMed

Green, Rivka; Cutter, Gary; Friendly, Michael; Kister, Ilya

2017-01-01

Multiple sclerosis is a polysymptomatic disease. Little is known about relative contributions of the different multiple sclerosis symptoms to self-perception of health. To investigate the relationship between symptom severity in 11 domains affected by multiple sclerosis and self-rated health. Multiple sclerosis patients in two multiple sclerosis centers assessed self-rated health with a validated instrument and symptom burden with symptoMScreen, a validated battery of Likert scales for 11 domains commonly affected by multiple sclerosis. Pearson correlations and multivariate linear regressions were used to investigate the relationship between symptoMScreen scores and self-rated health. Among 1865 multiple sclerosis outpatients (68% women, 78% with relapsing-remitting multiple sclerosis, mean age 46.38 ± 12.47 years, disease duration 13.43 ± 10.04 years), average self-rated health score was 2.30 ('moderate to good'). Symptom burden (composite symptoMScreen score) highly correlated with self-rated health ( r  = 0.68, P  < 0.0001) as did each of the symptoMScreen domain subscores. In regression analysis, pain ( t  = 7.00), ambulation ( t  = 6.91), and fatigue ( t  = 5.85) contributed the highest amount of variance in self-rated health ( P  < 0.001). Pain contributed the most to multiple sclerosis outpatients' perception of health, followed by gait dysfunction and fatigue. These findings suggest that 'invisible disability' may be more important to patients' sense of wellbeing than physical disability, and challenge the notion that physical disability should be the primary outcome measure in multiple sclerosis.

A Solution to Separation and Multicollinearity in Multiple Logistic Regression

PubMed Central

Shen, Jianzhao; Gao, Sujuan

2010-01-01

In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27–38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth’s penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study. PMID:20376286

A Solution to Separation and Multicollinearity in Multiple Logistic Regression.

PubMed

Shen, Jianzhao; Gao, Sujuan

2008-10-01

In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27-38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth's penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study.

Criteria for the use of regression analysis for remote sensing of sediment and pollutants

NASA Technical Reports Server (NTRS)

Whitlock, C. H.; Kuo, C. Y.; Lecroy, S. R.

1982-01-01

An examination of limitations, requirements, and precision of the linear multiple-regression technique for quantification of marine environmental parameters is conducted. Both environmental and optical physics conditions have been defined for which an exact solution to the signal response equations is of the same form as the multiple regression equation. Various statistical parameters are examined to define a criteria for selection of an unbiased fit when upwelled radiance values contain error and are correlated with each other. Field experimental data are examined to define data smoothing requirements in order to satisfy the criteria of Daniel and Wood (1971). Recommendations are made concerning improved selection of ground-truth locations to maximize variance and to minimize physical errors associated with the remote sensing experiment.

BAYESIAN LARGE-SCALE MULTIPLE REGRESSION WITH SUMMARY STATISTICS FROM GENOME-WIDE ASSOCIATION STUDIES1

PubMed Central

Zhu, Xiang; Stephens, Matthew

2017-01-01

Bayesian methods for large-scale multiple regression provide attractive approaches to the analysis of genome-wide association studies (GWAS). For example, they can estimate heritability of complex traits, allowing for both polygenic and sparse models; and by incorporating external genomic data into the priors, they can increase power and yield new biological insights. However, these methods require access to individual genotypes and phenotypes, which are often not easily available. Here we provide a framework for performing these analyses without individual-level data. Specifically, we introduce a “Regression with Summary Statistics” (RSS) likelihood, which relates the multiple regression coefficients to univariate regression results that are often easily available. The RSS likelihood requires estimates of correlations among covariates (SNPs), which also can be obtained from public databases. We perform Bayesian multiple regression analysis by combining the RSS likelihood with previously proposed prior distributions, sampling posteriors by Markov chain Monte Carlo. In a wide range of simulations RSS performs similarly to analyses using the individual data, both for estimating heritability and detecting associations. We apply RSS to a GWAS of human height that contains 253,288 individuals typed at 1.06 million SNPs, for which analyses of individual-level data are practically impossible. Estimates of heritability (52%) are consistent with, but more precise, than previous results using subsets of these data. We also identify many previously unreported loci that show evidence for association with height in our analyses. Software is available at https://github.com/stephenslab/rss. PMID:29399241

Abdominal girth, vertebral column length, and spread of spinal anesthesia in 30 minutes after plain bupivacaine 5 mg/mL.

PubMed

Zhou, Qing-he; Xiao, Wang-pin; Shen, Ying-yan

2014-07-01

The spread of spinal anesthesia is highly unpredictable. In patients with increased abdominal girth and short stature, a greater cephalad spread after a fixed amount of subarachnoidally administered plain bupivacaine is often observed. We hypothesized that there is a strong correlation between abdominal girth/vertebral column length and cephalad spread. Age, weight, height, body mass index, abdominal girth, and vertebral column length were recorded for 114 patients. The L3-L4 interspace was entered, and 3 mL of 0.5% plain bupivacaine was injected into the subarachnoid space. The cephalad spread (loss of temperature sensation and loss of pinprick discrimination) was assessed 30 minutes after intrathecal injection. Linear regression analysis was performed for age, weight, height, body mass index, abdominal girth, vertebral column length, and the spread of spinal anesthesia, and the combined linear contribution of age up to 55 years, weight, height, abdominal girth, and vertebral column length was tested by multiple regression analysis. Linear regression analysis showed that there was a significant univariate correlation among all 6 patient characteristics evaluated and the spread of spinal anesthesia (all P < 0.039) except for age and loss of temperature sensation (P > 0.068). Multiple regression analysis showed that abdominal girth and the vertebral column length were the key determinants for spinal anesthesia spread (both P < 0.0001), whereas age, weight, and height could be omitted without changing the results (all P > 0.059, all 95% confidence limits < 0.372). Multiple regression analysis revealed that the combination of a patient's 5 general characteristics, especially abdominal girth and vertebral column length, had a high predictive value for the spread of spinal anesthesia after a given dose of plain bupivacaine.

Dysfunctional Metacognitive Beliefs in Body Dysmorphic Disorder

PubMed Central

Zeinodini, Zahra; Sedighi, Sahar; Rahimi, Mandana Baghertork; Noorbakhsh, Simasadat; Esfahani, Sepideh Rajezi

2016-01-01

The present study aims to examine the correlation of body dysmorphic disorder, with metacognitive subscales, metaworry and thought-fusion. The study was conducted in a correlation framework. Sample included 155 high school students in Isfahan, Iran in 2013-2014, gathered through convenience sampling. To gather data about BDD, Yale-Brown Obsessive Compulsive Scale Modified for BDD was applied. Then, Meta Cognitive Questionnaire, Metaworry Questionnaire, and Thought-Fusion Inventory were used to assess metacognitive subscales, metaworry and thought-fusion. Data obtained from this study were analyzed using Pearson correlation and multiple regressions in SPSS 18. Result indicated YBOCS-BDD scores had a significant correlation with scores from MCQ (P<0.05), MWG (P<0.05), and TFI (P<0.05). Also, multiple regressions were run to predict YBOCS from TFI, MWQ, and MCQ-30. These variables significantly predicted YBOCS [F (3,151) =32.393, R2=0.57]. Findings indicated that body dysmorphic disorder was significantly related to metacognitive subscales, metaworry, and thought fusion in high school students in Isfahan, which is in line with previous studies. A deeper understanding of these processes can broaden theory and treatment of BDD, thereby improve the lives of sufferers and potentially protect others from developing this devastating disorder. PMID:26493420

A retrospective study: correlation of histologic inflammation in biopsy specimens of Chinese men undergoing surgery for benign prostatic hyperplasia with serum prostate-specific antigen.

PubMed

Song, Lingmin; Zhu, Yuchun; Han, Ping; Chen, Ni; Lin, Dao; Lai, Jianyu; Wei, Qiang

2011-03-01

To reveal the correlation between benign prostatic hyperplasia (BPH) histologic inflammation and serum prostate-specific antigen (sPSA) concentrations, and the possible mechanism. Patients underwent surgery at the Urology Department of West China Hospital of Sichuan University were retrospectively studied. Preoperative sPSA and transrectal ultrasonography were measured. According to the histopathological classification system for chronic prostatic inflammation proposed by the Chronic Prostatitis Collaborative Research Network (CPCRN) and the International Prostatitis Collaborative Network (IPCN), we classified the histologic sections of prostatic biopsy into glandular, periglandular, and stromal inflammation by the anatomical location of inflammatory infiltration. The glandular inflammation was graded according to the inflammatory aggressiveness. The periglandular and stromal inflammation were graded according to the inflammatory density. The correlation between histologic inflammation and sPSA was studied by a multiple regression model in conjunction with age and total prostatic volume. A total of 454 patients with exclusively BPH were analyzed. The periglandular inflammatory infiltration was the most common pattern (95.6%). Single regression analysis revealed that total prostatic volume, the aggressiveness of glandular inflammation, and the intensity of periglandular and stromal inflammation were correlated with sPSA. However, the multiple regression analysis revealed that only the total prostatic volume and the aggressiveness of glandular inflammation were correlated significantly with sPSA (R = .389, 0.289; P = .000). The aggressiveness of glandular inflammatory infiltration in BPH is a significant contributor to elevated sPSA levels. The theory of leakage may be the most reasonable mechanism to reveal the correlation morphologically. We should take inflammation into consideration when interpreting the abnormal elevating of sPSA levels. Copyright © 2011 Elsevier Inc. All rights reserved.

Predicting MHC-II binding affinity using multiple instance regression

PubMed Central

EL-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2011-01-01

Reliably predicting the ability of antigen peptides to bind to major histocompatibility complex class II (MHC-II) molecules is an essential step in developing new vaccines. Uncovering the amino acid sequence correlates of the binding affinity of MHC-II binding peptides is important for understanding pathogenesis and immune response. The task of predicting MHC-II binding peptides is complicated by the significant variability in their length. Most existing computational methods for predicting MHC-II binding peptides focus on identifying a nine amino acids core region in each binding peptide. We formulate the problems of qualitatively and quantitatively predicting flexible length MHC-II peptides as multiple instance learning and multiple instance regression problems, respectively. Based on this formulation, we introduce MHCMIR, a novel method for predicting MHC-II binding affinity using multiple instance regression. We present results of experiments using several benchmark datasets that show that MHCMIR is competitive with the state-of-the-art methods for predicting MHC-II binding peptides. An online web server that implements the MHCMIR method for MHC-II binding affinity prediction is freely accessible at http://ailab.cs.iastate.edu/mhcmir. PMID:20855923

Changes in aerobic power of men, ages 25-70 yr

NASA Technical Reports Server (NTRS)

Jackson, A. S.; Beard, E. F.; Wier, L. T.; Ross, R. M.; Stuteville, J. E.; Blair, S. N.

1995-01-01

This study quantified and compared the cross-sectional and longitudinal influence of age, self-report physical activity (SR-PA), and body composition (%fat) on the decline of maximal aerobic power (VO2peak). The cross-sectional sample consisted of 1,499 healthy men ages 25-70 yr. The 156 men of the longitudinal sample were from the same population and examined twice, the mean time between tests was 4.1 (+/- 1.2) yr. Peak oxygen uptake was determined by indirect calorimetry during a maximal treadmill exercise test. The zero-order correlations between VO2peak and %fat (r = -0.62) and SR-PA (r = 0.58) were significantly (P < 0.05) higher that the age correlation (r = -0.45). Linear regression defined the cross-sectional age-related decline in VO2peak at 0.46 ml.kg-1.min-1.yr-1. Multiple regression analysis (R = 0.79) showed that nearly 50% of this cross-sectional decline was due to %fat and SR-PA, adding these lifestyle variables to the multiple regression model reduced the age regression weight to -0.26 ml.kg-1.min-1.yr-1. Statistically controlling for time differences between tests, general linear models analysis showed that longitudinal changes in aerobic power were due to independent changes in %fat and SR-PA, confirming the cross-sectional results.

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.

Wheat flour dough Alveograph characteristics predicted by Mixolab regression models.

PubMed

Codină, Georgiana Gabriela; Mironeasa, Silvia; Mironeasa, Costel; Popa, Ciprian N; Tamba-Berehoiu, Radiana

2012-02-01

In Romania, the Alveograph is the most used device to evaluate the rheological properties of wheat flour dough, but lately the Mixolab device has begun to play an important role in the breadmaking industry. These two instruments are based on different principles but there are some correlations that can be found between the parameters determined by the Mixolab and the rheological properties of wheat dough measured with the Alveograph. Statistical analysis on 80 wheat flour samples using the backward stepwise multiple regression method showed that Mixolab values using the ‘Chopin S’ protocol (40 samples) and ‘Chopin + ’ protocol (40 samples) can be used to elaborate predictive models for estimating the value of the rheological properties of wheat dough: baking strength (W), dough tenacity (P) and extensibility (L). The correlation analysis confirmed significant findings (P < 0.05 and P < 0.01) between the parameters of wheat dough studied by the Mixolab and its rheological properties measured with the Alveograph. A number of six predictive linear equations were obtained. Linear regression models gave multiple regression coefficients with R²(adjusted) > 0.70 for P, R²(adjusted) > 0.70 for W and R²(adjusted) > 0.38 for L, at a 95% confidence interval. Copyright © 2011 Society of Chemical Industry.

Adjusting data to body size: a comparison of methods as applied to quantitative trait loci analysis of musculoskeletal phenotypes.

PubMed

Lang, Dean H; Sharkey, Neil A; Lionikas, Arimantas; Mack, Holly A; Larsson, Lars; Vogler, George P; Vandenbergh, David J; Blizard, David A; Stout, Joseph T; Stitt, Joseph P; McClearn, Gerald E

2005-05-01

The aim of this study was to compare three methods of adjusting skeletal data for body size and examine their use in QTL analyses. It was found that dividing skeletal phenotypes by body mass index induced erroneous QTL results. The preferred method of body size adjustment was multiple regression. Many skeletal studies have reported strong correlations between phenotypes for muscle, bone, and body size, and these correlations add to the difficulty in identifying genetic influence on skeletal traits that are not mediated through overall body size. Quantitative trait loci (QTL) identified for skeletal phenotypes often map to the same chromosome regions as QTLs for body size. The actions of a QTL identified as influencing BMD could therefore be mediated through the generalized actions of growth on body size or muscle mass. Three methods of adjusting skeletal phenotypes to body size were performed on morphologic, structural, and compositional measurements of the femur and tibia in 200-day-old C57BL/6J x DBA/2 (BXD) second generation (F(2)) mice (n = 400). A common method of removing the size effect has been through the use of ratios. This technique and two alternative techniques using simple and multiple regression were performed on muscle and skeletal data before QTL analyses, and the differences in QTL results were examined. The use of ratios to remove the size effect was shown to increase the size effect by inducing spurious correlations, thereby leading to inaccurate QTL results. Adjustments for body size using multiple regression eliminated these problems. Multiple regression should be used to remove the variance of co-factors related to skeletal phenotypes to allow for the study of genetic influence independent of correlated phenotypes. However, to better understand the genetic influence, adjusted and unadjusted skeletal QTL results should be compared. Additional insight can be gained by observing the difference in LOD score between the adjusted and nonadjusted phenotypes. Identifying QTLs that exert their effects on skeletal phenotypes through body size-related pathways as well as those having a more direct and independent influence on bone are equally important in deciphering the complex physiologic pathways responsible for the maintenance of bone health.

[Aggression and related factors in elementary school students].

PubMed

Ji, Eun Sun; Jang, Mi Heui

2010-10-01

This study was done to explore the relationship between aggression and internet over-use, depression-anxiety, self-esteem, all of which are known to be behavior and psychological characteristics linked to "at-risk" children for aggression. Korean-Child Behavior Check List (K-CBCL), Korean-Internet Addiction Self-Test Scale, and Self-Esteem Scale by Rosenberg (1965) were used as measurement tools with a sample of 743, 5th-6th grade students from 3 elementary schools in Jecheon city. Chi-square, t-test, ANOVA, Pearson's correlation and stepwise multiple regression with SPSS/Win 13.0 version were used to analyze the collected data. Aggression for the elementary school students was positively correlated with internet over-use and depression-anxiety, whereas self-esteem was negatively correlated with aggression. Stepwise multiple regression analysis showed that 68.4% of the variance for aggression was significantly accounted for by internet over-use, depression-anxiety, and self-esteem. The most significant factor influencing aggression was depression-anxiety. These results suggest that earlier screening and intervention programs for depression-anxiety and internet over-use for elementary student will be helpful in preventing aggression.

The effects of texting on driving performance in a driving simulator: the influence of driver age.

PubMed

Rumschlag, Gordon; Palumbo, Theresa; Martin, Amber; Head, Doreen; George, Rajiv; Commissaris, Randall L

2015-01-01

Distracted driving is a significant contributor to motor vehicle accidents and fatalities, and texting is a particularly significant form of driver distraction that continues to be on the rise. The present study examined the influence of driver age (18-59 years old) and other factors on the disruptive effects of texting on simulated driving behavior. While 'driving' the simulator, subjects were engaged in a series of brief text conversations with a member of the research team. The primary dependent variable was the occurrence of Lane Excursions (defined as any time the center of the vehicle moved outside the directed driving lane, e.g., into the lane for oncoming traffic or onto the shoulder of the road), measured as (1) the percent of subjects that exhibited Lane Excursions, (2) the number of Lane Excursions occurring and (3) the percent of the texting time in Lane Excursions. Multiple Regression analyses were used to assess the influence of several factors on driving performance while texting, including text task duration, texting skill level (subject-reported), texting history (#texts/week), driver gender and driver age. Lane Excursions were not observed in the absence of texting, but 66% of subjects overall exhibited Lane Excursions while texting. Multiple Regression analysis for all subjects (N=50) revealed that text task duration was significantly correlated with the number of Lane Excursions, and texting skill level and driver age were significantly correlated with the percent of subjects exhibiting Lane Excursions. Driver gender was not significantly correlated with Lane Excursions during texting. Multiple Regression analysis of only highly skilled texters (N=27) revealed that driver age was significantly correlated with the number of Lane Excursions, the percent of subjects exhibiting Lane Excursions and the percent of texting time in Lane Excursions. In contrast, Multiple Regression analysis of those drivers who self-identified as not highly skilled texters (N=23) revealed that text task duration was significantly correlated with the number of Lane Excursions. The present studies confirm past reports that texting impairs driving simulator performance. Moreover, the present study demonstrates that for highly skilled texters, the effects of texting on driving are actually worse for older drivers. Given the increasing frequency of texting while driving within virtually all age groups, these data suggest that 'no texting while driving' education and public service messages need to be continued, and they should be expanded to target older drivers as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

Comparisons of Office and 24-Hour Ambulatory Blood Pressure Monitoring in Children with Obstructive Sleep Apnea.

PubMed

Kang, Kun-Tai; Chiu, Shuenn-Nan; Weng, Wen-Chin; Lee, Pei-Lin; Hsu, Wei-Chung

2017-03-01

To compare office blood pressure (BP) and 24-hour ambulatory BP (ABP) monitoring to facilitate the diagnosis and management of hypertension in children with obstructive sleep apnea (OSA). Children aged 4-16 years with OSA-related symptoms were recruited from a tertiary referral medical center. All children underwent overnight polysomnography, office BP, and 24-hour ABP studies. Multiple linear regression analyses were applied to elucidate the association between the apnea-hypopnea index and BP. Correlation and consistency between office BP and 24-hour ABP were measured by Pearson correlation, intraclass correlation, and Bland-Altman analyses. In the 163 children enrolled (mean age, 8.2 ± 3.3 years; 67% male). The prevalence of systolic hypertension at night was significantly higher in children with moderate-to-severe OSA than in those with primary snoring (44.9% vs 16.1%, P = .006). Pearson correlation and intraclass correlation analyses revealed associations between office BP and 24-hour BP, and Bland-Altman analysis indicated an agreement between office and 24-hour BP measurements. However, multiple linear regression analyses demonstrated that 24-hour BP (nighttime systolic BP and mean arterial pressure), unlike office BP, was independently associated with the apnea-hypopnea index, after adjustment for adiposity variables. Twenty-four-hour ABP is more strongly correlated with OSA in children, compared with office BP. Copyright © 2016 Elsevier Inc. All rights reserved.

Forecasting defoliation by the gypsy moth in oak stands

Treesearch

Robert W. Campbell; Joseph P. Standaert

1974-01-01

A multiple-regression model is presented that reflects statistically significant correlations between defoliation by the gypsy moth, the dependent variable, and a series of biotic and physical independent variables. Both possible uses and shortcomings of this model are discussed.

Sequential Processing and the Matching-Stimulus Interval Effect in ERP Components: An Exploration of the Mechanism Using Multiple Regression

PubMed Central

Steiner, Genevieve Z.; Barry, Robert J.; Gonsalvez, Craig J.

2016-01-01

In oddball tasks, increasing the time between stimuli within a particular condition (target-to-target interval, TTI; nontarget-to-nontarget interval, NNI) systematically enhances N1, P2, and P300 event-related potential (ERP) component amplitudes. This study examined the mechanism underpinning these effects in ERP components recorded from 28 adults who completed a conventional three-tone oddball task. Bivariate correlations, partial correlations and multiple regression explored component changes due to preceding ERP component amplitudes and intervals found within the stimulus series, rather than constraining the task with experimentally constructed intervals, which has been adequately explored in prior studies. Multiple regression showed that for targets, N1 and TTI predicted N2, TTI predicted P3a and P3b, and Processing Negativity (PN), P3b, and TTI predicted reaction time. For rare nontargets, P1 predicted N1, NNI predicted N2, and N1 predicted Slow Wave (SW). Findings show that the mechanism is operating on separate stages of stimulus-processing, suggestive of either increased activation within a number of stimulus-specific pathways, or very long component generator recovery cycles. These results demonstrate the extent to which matching-stimulus intervals influence ERP component amplitudes and behavior in a three-tone oddball task, and should be taken into account when designing similar studies. PMID:27445774

Sequential Processing and the Matching-Stimulus Interval Effect in ERP Components: An Exploration of the Mechanism Using Multiple Regression.

PubMed

Steiner, Genevieve Z; Barry, Robert J; Gonsalvez, Craig J

2016-01-01

In oddball tasks, increasing the time between stimuli within a particular condition (target-to-target interval, TTI; nontarget-to-nontarget interval, NNI) systematically enhances N1, P2, and P300 event-related potential (ERP) component amplitudes. This study examined the mechanism underpinning these effects in ERP components recorded from 28 adults who completed a conventional three-tone oddball task. Bivariate correlations, partial correlations and multiple regression explored component changes due to preceding ERP component amplitudes and intervals found within the stimulus series, rather than constraining the task with experimentally constructed intervals, which has been adequately explored in prior studies. Multiple regression showed that for targets, N1 and TTI predicted N2, TTI predicted P3a and P3b, and Processing Negativity (PN), P3b, and TTI predicted reaction time. For rare nontargets, P1 predicted N1, NNI predicted N2, and N1 predicted Slow Wave (SW). Findings show that the mechanism is operating on separate stages of stimulus-processing, suggestive of either increased activation within a number of stimulus-specific pathways, or very long component generator recovery cycles. These results demonstrate the extent to which matching-stimulus intervals influence ERP component amplitudes and behavior in a three-tone oddball task, and should be taken into account when designing similar studies.

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages.

PubMed

Kim, Yoonsang; Choi, Young-Ku; Emery, Sherry

2013-08-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods' performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages-SAS GLIMMIX Laplace and SuperMix Gaussian quadrature-perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes.

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages

PubMed Central

Kim, Yoonsang; Emery, Sherry

2013-01-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods’ performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages—SAS GLIMMIX Laplace and SuperMix Gaussian quadrature—perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes. PMID:24288415

The relationship between hemoglobin level and the type 1 diabetic nephropathy in Anhui Han's patients.

PubMed

Jiang, Jun; Lei, Lan; Zhou, Xiaowan; Li, Peng; Wei, Ren

2018-02-20

Recent studies have shown that low hemoglobin (Hb) level promote the progression of chronic kidney disease. This study assessed the relationship between Hb level and type 1 diabetic nephropathy (DN) in Anhui Han's patients. There were a total of 236 patients diagnosed with type 1 diabetes mellitus and (T1DM) seen between January 2014 and December 2016 in our centre. Hemoglobin levels in patients with DN were compared with those without DN. The relationship between Hb level and the urinary albumin-creatinine ratio (ACR) was examined by Spearman's correlational analysis and multiple stepwise regression analysis. The binary logistic multivariate regression analysis was performed to analyze the correlated factors for type 1 DN, calculate the Odds Ratio (OR) and 95%confidence interval (CI). The predicting value of Hb level for DN was evaluated by area under receiver operation characteristic curve (AUROC) for discrimination and Hosmer-Lemeshow goodness-of-fit test for calibration. The average Hb levels in the DN group (116.1 ± 20.8 g/L) were significantly lower than the non-DN group (131.9 ± 14.4 g/L) , P < 0.001. Hb levels were independently correlated with the urinary ACR in multiple stepwise regression analysis. The logistic multivariate regression analysis showed that the Hb level (OR: 0.936, 95% CI: 0.910 to 0.963, P < 0.001) was inversely correlated with DN in patients with T1DM. In sub-analysis, low Hb level (Hb < 120g/L in female, Hb < 130g/L in male) was still negatively associated with DN in patients with T1DM. The AUROC was 0.721 (95% CI: 0.655 to 0.787) in assessing the discrimination of the Hb level for DN. The value of P was 0.593 in Hosmer-Lemeshow goodness-of-fit test. In Anhui Han's patients with T1DM, the Hb level is inversely correlated with urinary ACR and DN. This article is protected by copyright. All rights reserved.

Rape Myth Acceptance, Hypermasculinity, and SAT Scores as Correlates of Moral Development: Understanding Sexually Aggressive Attitudes in First-Year College Men

ERIC Educational Resources Information Center

Tatum, Jerry L.; Foubert, John D.

2009-01-01

Male perpetrated sexual aggression has long been recognized as a serious problem on college campuses. The purpose of this multiple regression correlation study was to assess the relationship between levels of moral development (measured by the Defining Issues Test) and the degree to which first-year college men (N = 161) ascribed to rape…

Multivariate meta-analysis using individual participant data

PubMed Central

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2016-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

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.

Prediction of random-regression coefficient for daily milk yield after 305 days in milk by using the regression-coefficient estimates from the first 305 days.

PubMed

Yamazaki, Takeshi; Takeda, Hisato; Hagiya, Koichi; Yamaguchi, Satoshi; Sasaki, Osamu

2018-03-13

Because lactation periods in dairy cows lengthen with increasing total milk production, it is important to predict individual productivities after 305 days in milk (DIM) to determine the optimal lactation period. We therefore examined whether the random regression (RR) coefficient from 306 to 450 DIM (M2) can be predicted from those during the first 305 DIM (M1) by using a random regression model. We analyzed test-day milk records from 85690 Holstein cows in their first lactations and 131727 cows in their later (second to fifth) lactations. Data in M1 and M2 were analyzed separately by using different single-trait RR animal models. We then performed a multiple regression analysis of the RR coefficients of M2 on those of M1 during the first and later lactations. The first-order Legendre polynomials were practical covariates of random regression for the milk yields of M2. All RR coefficients for the additive genetic (AG) effect and the intercept for the permanent environmental (PE) effect of M2 had moderate to strong correlations with the intercept for the AG effect of M1. The coefficients of determination for multiple regression of the combined intercepts for the AG and PE effects of M2 on the coefficients for the AG effect of M1 were moderate to high. The daily milk yields of M2 predicted by using the RR coefficients for the AG effect of M1 were highly correlated with those obtained by using the coefficients of M2. Milk production after 305 DIM can be predicted by using the RR coefficient estimates of the AG effect during the first 305 DIM.

Physical Activity and Depressive Symptoms in Four Ethnic Groups of Midlife Women

PubMed Central

Im, Eun-Ok; Ham, Ok Kyung; Chee, Eunice; Chee, Wonshik

2014-01-01

The purpose of this study was to determine the associations between physical activity and depression and the multiple contextual factors influencing these associations in four major ethnic-groups of midlife women in the U.S. This was a secondary analysis of the data from 542 midlife women. The instruments included questions on background characteristics and health and menopausal status; the Depression Index for Midlife Women; and the Kaiser Physical Activity Survey. The data were analyzed using chi-square tests, the ANOVA, twoway ANOVA, correlation analyses, and hierarchical multiple regression analyses. The women's depressive symptoms were negatively correlated with active living and sports/exercise physical activities whereas they were positively correlated with occupational physical activities (p < .01). Family income was the strongest predictor of their depressive symptoms. Increasing physical activity may improve midlife women's depressive symptoms, but the types of physical activity and multiple contextual factors need to be considered in intervention development. PMID:24879749

Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure.

PubMed

Louys, Julien; Meloro, Carlo; Elton, Sarah; Ditchfield, Peter; Bishop, Laura C

2015-01-01

We test the performance of two models that use mammalian communities to reconstruct multivariate palaeoenvironments. While both models exploit the correlation between mammal communities (defined in terms of functional groups) and arboreal heterogeneity, the first uses a multiple multivariate regression of community structure and arboreal heterogeneity, while the second uses a linear regression of the principal components of each ecospace. The success of these methods means the palaeoenvironment of a particular locality can be reconstructed in terms of the proportions of heavy, moderate, light, and absent tree canopy cover. The linear regression is less biased, and more precisely and accurately reconstructs heavy tree canopy cover than the multiple multivariate model. However, the multiple multivariate model performs better than the linear regression for all other canopy cover categories. Both models consistently perform better than randomly generated reconstructions. We apply both models to the palaeocommunity of the Upper Laetolil Beds, Tanzania. Our reconstructions indicate that there was very little heavy tree cover at this site (likely less than 10%), with the palaeo-landscape instead comprising a mixture of light and absent tree cover. These reconstructions help resolve the previous conflicting palaeoecological reconstructions made for this site. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluation of Relationship between Trunk Muscle Endurance and Static Balance in Male Students

PubMed Central

Barati, Amirhossein; SafarCherati, Afsaneh; Aghayari, Azar; Azizi, Faeze; Abbasi, Hamed

2013-01-01

Purpose Fatigue of trunk muscle contributes to spinal instability over strenuous and prolonged physical tasks and therefore may lead to injury, however from a performance perspective, relation between endurance efficient core muscles and optimal balance control has not been well-known. The purpose of this study was to examine the relationship of trunk muscle endurance and static balance. Methods Fifty male students inhabitant of Tehran university dormitory (age 23.9±2.4, height 173.0±4.5 weight 70.7±6.3) took part in the study. Trunk muscle endurance was assessed using Sørensen test of trunk extensor endurance, trunk flexor endurance test, side bridge endurance test and static balance was measured using single-limb stance test. A multiple linear regression analysis was applied to test if the trunk muscle endurance measures significantly predicted the static balance. Results There were positive correlations between static balance level and trunk flexor, extensor and lateral endurance measures (Pearson correlation test, r=0.80 and P<0.001; r=0.71 and P<0.001; r=0.84 and P<0.001, respectively). According to multiple regression analysis for variables predicting static balance, the linear combination of trunk muscle endurance measures was significantly related to the static balance (F (3,46) = 66.60, P<0.001). Endurance of trunk flexor, extensor and lateral muscles were significantly associated with the static balance level. The regression model which included these factors had the sample multiple correlation coefficient of 0.902, indicating that approximately 81% of the variance of the static balance is explained by the model. Conclusion There is a significant relationship between trunk muscle endurance and static balance. PMID:24800004

Predictive ability of a comprehensive incremental test in mountain bike marathon.

PubMed

Ahrend, Marc-Daniel; Schneeweiss, Patrick; Martus, Peter; Niess, Andreas M; Krauss, Inga

2018-01-01

Traditional performance tests in mountain bike marathon (XCM) primarily quantify aerobic metabolism and may not describe the relevant capacities in XCM. We aimed to validate a comprehensive test protocol quantifying its intermittent demands. Forty-nine athletes (38.8±9.1 years; 38 male; 11 female) performed a laboratory performance test, including an incremental test, to determine individual anaerobic threshold (IAT), peak power output (PPO) and three maximal efforts (10 s all-out sprint, 1 min maximal effort and 5 min maximal effort). Within 2 weeks, the athletes participated in one of three XCM races (n=15, n=9 and n=25). Correlations between test variables and race times were calculated separately. In addition, multiple regression models of the predictive value of laboratory outcomes were calculated for race 3 and across all races (z-transformed data). All variables were correlated with race times 1, 2 and 3: 10 s all-out sprint (r=-0.72; r=-0.59; r=-0.61), 1 min maximal effort (r=-0.85; r=-0.84; r=-0.82), 5 min maximal effort (r=-0.57; r=-0.85; r=-0.76), PPO (r=-0.77; r=-0.73; r=-0.76) and IAT (r=-0.71; r=-0.67; r=-0.68). The best-fitting multiple regression models for race 3 (r 2 =0.868) and across all races (r 2 =0.757) comprised 1 min maximal effort, IAT and body weight. Aerobic and intermittent variables correlated least strongly with race times. Their use in a multiple regression model confirmed additional explanatory power to predict XCM performance. These findings underline the usefulness of the comprehensive incremental test to predict performance in that sport more precisely.

Memory complaints in epilepsy: An examination of the role of mood and illness perceptions.

PubMed

Tinson, Deborah; Crockford, Christopher; Gharooni, Sara; Russell, Helen; Zoeller, Sophie; Leavy, Yvonne; Lloyd, Rachel; Duncan, Susan

2018-03-01

The study examined the role of mood and illness perceptions in explaining the variance in the memory complaints of patients with epilepsy. Forty-four patients from an outpatient tertiary care center and 43 volunteer controls completed a formal assessment of memory and a verbal fluency test, as well as validated self-report questionnaires on memory complaints, mood, and illness perceptions. In hierarchical multiple regression analyses, objective memory test performance and verbal fluency did not contribute significantly to the variance in memory complaints for either patients or controls. In patients, illness perceptions and mood were highly correlated. Illness perceptions correlated more highly with memory complaints than mood and were therefore added to the multiple regression analysis. This accounted for an additional 25% of the variance, after controlling for objective memory test performance and verbal fluency, and the model was significant (model B). In order to compare with other studies, mood was added to a second model, instead of illness perceptions. This accounted for an additional 24% of the variance, which was again significant (model C). In controls, low mood accounted for 11% of the variance in memory complaints (model C2). A measure of illness perceptions was more highly correlated with the memory complaints of patients with epilepsy than with a measure of mood. In a hierarchical multiple regression model, illness perceptions accounted for 25% of the variance in memory complaints. Illness perceptions could provide useful information in a clinical investigation into the self-reported memory complaints of patients with epilepsy, alongside the assessment of mood and formal memory testing. Copyright © 2017 Elsevier Inc. All rights reserved.

[Correlations Between Joint Proprioception, Muscle Strength, and Functional Ability in Patients with Knee Osteoarthritis].

PubMed

Chen, Yoa; Yu, Yong; He, Cheng-qi

2015-11-01

To establish correlations between joint proprioception, muscle flexion and extension peak torque, and functional ability in patients with knee osteoarthritis (OA). Fifty-six patients with symptomatic knee OA were recruited in this study. Both proprioceptive acuity and muscle strength were measured using the isomed-2000 isokinetic dynamometer. Proprioceptive acuity was evaluated by establishing the joint motion detection threshold (JMDT). Muscle strength was evaluated by Max torque (Nm) and Max torque/weight (Nm/ kg). Functional ability was assessed by the Western Ontario and McMaster Universities Osteoarthritis Index physical function (WOMAC-PF) questionnaire. Correlational analyses were performed between proprioception, muscle strength, and functional ability. A multiple stepwise regression model was established, with WOMAC-PF as dependent variable and patient age, body mass index (BMI), visual analogue scale (VAS)-score, mean grade for Kellgren-Lawrance of both knees, mean strength for quadriceps and hamstring muscles of both knees, and mean JMDT of both knees as independent variables. Poor proprioception (high JMDT) was negatively correlated with muscle strength (P<0.05). There was no significant correlation between knee proprioception (high JMDT) and joint pain (WOMAC pain score), and between knee proprioception (high JMDT) and joint stiffness (WOMAC stiffness score). Poor proprioception (high JMDT) was correlated with limitation in functional ability (WOMAC physical function score r=0.659, P<0.05). WOMAC score was correlated with poor muscle strength (quadriceps muscle strength r = -0.511, P<0.05, hamstring muscle strength r = -0.408, P<0.05). The multiple stepwise regression model showed that high JMDT C standard partial regression coefficient (B) = 0.385, P<0.50 and high VAS-scale score (B=0.347, P<0.05) were significant predictors of WOMAC-PF score. Patients with poor proprioception is associated with poor muscle strength and limitation in functional ability. Patients with symptomatic OA of knees commonly endure with moderate to considerable dysfunction, which is associated with poor proprioception (high JMDT) and high VAS-scale score.

100-point scale evaluating job satisfaction and the results of the 12-item General Health Questionnaire in occupational workers.

PubMed

Kawada, Tomoyuki; Yamada, Natsuki

2012-01-01

Job satisfaction is an important factor in the occupational lives of workers. In this study, the relationship between one-dimensional scale of job satisfaction and psychological wellbeing was evaluated. A total of 1,742 workers (1,191 men and 551 women) participated. 100-point scale evaluating job satisfaction (0 [extremely dissatisfied] to 100 [extremely satisfied]) and the General Health Questionnaire, 12-item version (GHQ-12) evaluating psychological wellbeing were used. A multiple regression analysis was then used, controlling for gender and age. The change in the GHQ-12 and job satisfaction scores after a two-year interval was also evaluated. The mean age for the subjects was 42.2 years for the men and 36.2 years for the women. The GHQ-12 and job satisfaction scores were significantly correlated in each generation. The partial correlation coefficients between the changes in the two variables, controlling for age, were -0.395 for men and -0.435 for women (p< 0.001). A multiple regression analysis revealed that the 100-point job satisfaction score was associated with the GHQ-12 results (p< 0.001). The adjusted multiple correlation coefficient was 0.275. The 100-point scale, which is a simple and easy tool for evaluating job satisfaction, was significantly associated with psychological wellbeing as judged using the GHQ-12.

Intercellular adhesion molecule, plasma adiponectin and albuminuria in type 2 diabetic patients.

PubMed

Lenghel, Alina Ramona; Kacso, Ina Maria; Bondor, Cosmina Ioana; Rusu, Crina; Rahaian, Rodica; Gherman Caprioara, Mirela

2012-01-01

Our study addressed the influence of early inflammatory stages of diabetic kidney disease: leukocyte adhesion and monocyte activation (as assessed by intercellular leukocyte adhesion molecule-ICAM-1 and monocyte chemoatractant protein-MCP-1) on the degree of albuminuria. Plasma levels of adiponectin, a possible anti-inflammatory counteracting mechanism, were also studied in correlation to the above-mentioned cytokines. 79 consecutive type 2 diabetic outpatients and 46 controls were included. Routine laboratory analysis, urinary albumin to creatinine ratio (uACR), plasma adiponectin, plasma ICAM-1 and urinary MPC-1 were assessed. In multiple regression ICAM-1 (p=0.004) and adiponectin (p=0.04) were the main determinants of uACR. Plasma adiponectin positively correlated to ICAM-1 (p=0.03, r=0.24). In albuminuric patients (uACR ≥30 mg/g) plasma adiponectin was significantly higher compared to normoalbuminuric ones (uACR <30 mg/g). In albuminuric patients the main determinants of uACR were plasma ICAM-1 and adiponectin. In multiple regression ICAM-1 is the only one that retains statistical significance (p=0.02). Urinary MCP-1 did not correlate to uACR. In our type 2 diabetic patients, plasma levels of ICAM-1 and adiponectin are predictive for albuminuria. Urinary MCP-1 does not correlated to uACR. Plasma adiponectin positively correlates to adhesion molecule ICAM-1 in our cohort. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Role of anthropometric data in the prediction of 4-stranded hamstring graft size in anterior cruciate ligament reconstruction.

PubMed

Ho, Sean Wei Loong; Tan, Teong Jin Lester; Lee, Keng Thiam

2016-03-01

To evaluate whether pre-operative anthropometric data can predict the optimal diameter and length of hamstring tendon autograft for anterior cruciate ligament (ACL) reconstruction. This was a cohort study that involved 169 patients who underwent single-bundle ACL reconstruction (single surgeon) with 4-stranded MM Gracilis and MM Semi-Tendinosus autografts. Height, weight, body mass index (BMI), gender, race, age and -smoking status were recorded pre-operatively. Intra-operatively, the diameter and functional length of the 4-stranded autograft was recorded. Multiple regression analysis was used to determine the relationship between the anthropometric measurements and the length and diameter of the implanted autografts. The strongest correlation between 4-stranded hamstring autograft diameter was height and weight. This correlation was stronger in females than males. BMI had a moderate correlation with the diameter of the graft in females. Females had a significantly smaller graft both in diameter and length when compared with males. Linear regression models did not show any significant correlation between hamstring autograft length with height and weight (p>0.05). Simple regression analysis demonstrated that height and weight can be used to predict hamstring graft diameter. The following regression equation was obtained for females: Graft diameter=0.012+0.034*Height+0.026*Weight (R2=0.358, p=0.004) The following regression equation was obtained for males: Graft diameter=5.130+0.012*Height+0.007*Weight (R2=0.086, p=0.002). Pre-operative anthropometric data has a positive correlation with the diameter of 4 stranded hamstring autografts but no significant correlation with the length. This data can be utilised to predict the autograft diameter and may be useful for pre-operative planning and patient counseling for graft selection.

Efficient parameter estimation in longitudinal data analysis using a hybrid GEE method.

PubMed

Leung, Denis H Y; Wang, You-Gan; Zhu, Min

2009-07-01

The method of generalized estimating equations (GEEs) provides consistent estimates of the regression parameters in a marginal regression model for longitudinal data, even when the working correlation model is misspecified (Liang and Zeger, 1986). However, the efficiency of a GEE estimate can be seriously affected by the choice of the working correlation model. This study addresses this problem by proposing a hybrid method that combines multiple GEEs based on different working correlation models, using the empirical likelihood method (Qin and Lawless, 1994). Analyses show that this hybrid method is more efficient than a GEE using a misspecified working correlation model. Furthermore, if one of the working correlation structures correctly models the within-subject correlations, then this hybrid method provides the most efficient parameter estimates. In simulations, the hybrid method's finite-sample performance is superior to a GEE under any of the commonly used working correlation models and is almost fully efficient in all scenarios studied. The hybrid method is illustrated using data from a longitudinal study of the respiratory infection rates in 275 Indonesian children.

Health-related quality of life in multiple sclerosis: role of cognitive appraisals of self, illness and treatment.

PubMed

Wilski, Maciej; Tasiemski, Tomasz

2016-07-01

Health-related quality of life (HRQoL) is considered an important measure of treatment and rehabilitation outcomes in multiple sclerosis (MS) patients. In this study, we used multivariate regression analysis to examine the role of cognitive appraisals, adjusted for clinical, socioeconomic and demographic variables, as correlates of HRQoL in MS. The cross-sectional study included 257 MS patients, who completed Multiple Sclerosis Impact Scale, Generalized Self-Efficacy Scale, Rosenberg Self-Esteem Scale, Brief Illness Perception Questionnaire, Treatment Beliefs Scale, Actually Received Support Scale (a part of Berlin Social Support Scale) and Socioeconomic Resources Scale. Demographic and clinical characteristics of the participants were collected with a self-report survey. Correlation and regression analyses were conducted to determine associations between the variables. Five variables, illness identity (β = 0.29, p ≤ 0.001), self-esteem (β = -0.22, p ≤ 0.001), general self-efficacy (β = -0.21, p ≤ 0.001), disability subgroup "EDSS" (β = 0.14, p = 0.006) and age (β = 0.12, p = 0.012), were significant correlates of HRQoL in MS. These variables explained 46 % of variance in the dependent variable. Moreover, we identified correlates of physical and psychological dimensions of HRQoL. Cognitive appraisals, such as general self-efficacy, self-esteem and illness perception, are more salient correlates of HRQoL than social support, socioeconomic resources and clinical characteristics, such as type and duration of MS. Therefore, interventions aimed at cognitive appraisals may also improve HRQoL of MS patients.

The relationship among self-efficacy, perfectionism and academic burnout in medical school students.

PubMed

Yu, Ji Hye; Chae, Su Jin; Chang, Ki Hong

2016-03-01

The purpose of this study was to examine the relationship among academic self-efficacy, socially-prescribed perfectionism, and academic burnout in medical school students and to determine whether academic self-efficacy had a mediating role in the relationship between perfectionism and academic burnout. A total of 244 first-year and second-year premed medical students and first- to fourth-year medical students were enrolled in this study. As study tools, socially-prescribed perfectionism, academic self-efficacy, and academic burnout scales were utilized. For data analysis, correlation analysis, multiple regression analysis, and hierarchical multiple regression analyses were conducted. Academic burnout had correlation with socially-prescribed perfectionism. It had negative correlation with academic self-efficacy. Socially-prescribed perfectionism and academic self-efficacy had 54% explanatory power for academic burnout. When socially-prescribed perfectionism and academic self-efficacy were simultaneously used as input, academic self-efficacy partially mediated the relationship between socially-prescribed perfectionism and academic burnout. Socially-prescribed perfectionism had a negative effect on academic self-efficacy, ultimately triggering academic burnout. This suggests that it is important to have educational and counseling interventions to improve academic self-efficacy by relieving academic burnout of medical school students.

Drug use, mental health and problems related to crime and violence: cross-sectional study1

PubMed Central

Claro, Heloísa Garcia; de Oliveira, Márcia Aparecida Ferreira; Bourdreaux, Janet Titus; Fernandes, Ivan Filipe de Almeida Lopes; Pinho, Paula Hayasi; Tarifa, Rosana Ribeiro

2015-01-01

Objective: to investigate the correlation between disorders related to the use of alcohol and other drugs and symptoms of mental disorders, problems related to crime and violence and to age and gender. Methods: cross-sectional descriptive study carried out with 128 users of a Psychosocial Care Center for Alcohol and other Drugs, in the city of São Paulo, interviewed by means of the instrument entitled Global Appraisal of Individual Needs - Short Screener. Univariate and multiple linear regression models were used to verify the correlation between the variables. Results: using univariate regression models, internalizing and externalizing symptoms and problems related to crime/violence proved significant and were included in the multiple model, in which only the internalizing symptoms and problems related to crime and violence remained significant. Conclusions: there is a correlation between the severity of problems related to alcohol use and severity of mental health symptoms and crime and violence in the study sample. The results emphasize the need for an interdisciplinary and intersectional character of attention to users of alcohol and other drugs, since they live in a socially vulnerable environment. PMID:26626010

The relationship among self-efficacy, perfectionism and academic burnout in medical school students

PubMed Central

Yu, Ji Hye; Chae, Su Jin; Chang, Ki Hong

2016-01-01

Purpose: The purpose of this study was to examine the relationship among academic self-efficacy, socially-prescribed perfectionism, and academic burnout in medical school students and to determine whether academic self-efficacy had a mediating role in the relationship between perfectionism and academic burnout. Methods: A total of 244 first-year and second-year premed medical students and first- to fourth-year medical students were enrolled in this study. As study tools, socially-prescribed perfectionism, academic self-efficacy, and academic burnout scales were utilized. For data analysis, correlation analysis, multiple regression analysis, and hierarchical multiple regression analyses were conducted. Results: Academic burnout had correlation with socially-prescribed perfectionism. It had negative correlation with academic self-efficacy. Socially-prescribed perfectionism and academic self-efficacy had 54% explanatory power for academic burnout. When socially-prescribed perfectionism and academic self-efficacy were simultaneously used as input, academic self-efficacy partially mediated the relationship between socially-prescribed perfectionism and academic burnout. Conclusion: Socially-prescribed perfectionism had a negative effect on academic self-efficacy, ultimately triggering academic burnout. This suggests that it is important to have educational and counseling interventions to improve academic self-efficacy by relieving academic burnout of medical school students. PMID:26838568

The relationship between vascular endothelial dysfunction and treatment frequency in neovascular age-related macular degeneration.

PubMed

Ueda-Consolvo, Tomoko; Hayashi, Atsushi; Ozaki, Mayumi; Nakamura, Tomoko; Yagou, Takaaki; Abe, Shinya

2017-07-01

To assess the correlation between endothelial dysfunction and frequency of antivascular endothelial growth factor (anti-VEGF) treatment for neovascular age-related macular degeneration (nAMD). We examined 64 consecutive patients with nAMD who were evaluated for endothelial function by use of peripheral arterial tonometry (EndoPAT 2000; Itamar Medical, Caesarea, Israel) at Toyama University Hospital from January 2015. We tallied the number of anti-VEGF treatments between January 2014 and December 2015 and determined the correlation between the number of anti-VEGF injections and endothelial function expressed as the reactive hyperemia index (RHI). Multiple regression analysis was also performed to identify the independent predictors of a larger number of injections. The mean number of anti-VEGF injections was 8.2 ± 3.3. The mean lnRHI was 0.47 ± 0.17. The lnRHI correlated with the number of anti-VEGF injections (r = -0.56; P = 0.030). The multiple regression analysis revealed that endothelial function, neovascular subtypes, and treatment regimens were associated with the number of injections. Endothelial dysfunction may affect the efficacy of anti-VEGF therapy. Neovascular subtypes may also predict a larger number of injections.

Monitoring Changes of Ecosystem Services Supply and Demand Pattern in Central and Southern Liaoning Urban Agglomerations, China Using Landsat Images

NASA Astrophysics Data System (ADS)

Li, B.; Huang, F.; Chang, S.; Qi, H.; Zhai, H.

2018-04-01

Indentifying the spatio-temporal patterns of ecosystem services supply and demand and the driving forces is of great significance to the regional ecological security and sustainable socio-economic development. Due to long term and high-intensity development, the ecological environment in central and southern Liaoning urban agglomerations has been greatly destroyed thereafter has restricted sustainable development in this region. Based on Landsat ETM and OLI images, land use of this urban agglomeration in 2005, 2010 and 2015 was extracted. The integrative index of multiple-ecosystem services (IMES) was used to quantify the supply (IMESs), demand (IMESd) and balance (IMESb) of multiple-ecosystem services, The spatial patterns of ecosystem services and its dynamics for the period of 2005-2015 were revealed. The multiple regression and stepwise regression analysis were used to explore relationships between ecosystem services and socioeconomic factors. The results showed that the IMESs of the region increased by 2.93 %, whereas IMESd dropped 38 %. The undersupplied area was reduced to 2. The IMESs and IMESb were mainly negatively correlated with gross domestic product (GDP), population density, foreign investment and industrial output, while GDP per capita and the number of teachers had significant positive impacts on ecosystem services supply. The positive correlation between IMESd and GDP, population density and foreign investment were found. The ecosystem services models were established. Supply and balance of multiple-ecosystem services were positively correlated with population density, but the demand was the opposite. The results can provide some reference value for the coordinately economic and ecological development in the study area.

Partial Least Square Analyses of Landscape and Surface Water Biota Associations in the Savannah River Basin

EPA Science Inventory

Ecologists are often faced with problem of small sample size, correlated and large number of predictors, and high noise-to-signal relationships. This necessitates excluding important variables from the model when applying standard multiple or multivariate regression analyses. In ...

Isovolumic relaxation period as an index of left ventricular relaxation under different afterload conditions--comparison with the time constant of left ventricular pressure decay in the dog.

PubMed

Ochi, H; Ikuma, I; Toda, H; Shimada, T; Morioka, S; Moriyama, K

1989-12-01

In order to determine whether isovolumic relaxation period (IRP) reflects left ventricular relaxation under different afterload conditions, 17 anesthetized, open chest dogs were studied, and the left ventricular pressure decay time constant (T) was calculated. In 12 dogs, angiotensin II and nitroprusside were administered, with the heart rate constant at 90 beats/min. Multiple linear regression analysis showed that the aortic dicrotic notch pressure (AoDNP) and T were major determinants of IRP, while left ventricular end-diastolic pressure was a minor determinant. Multiple linear regression analysis, correlating T with IRP and AoDNP, did not further improve the correlation coefficient compared with that between T and IRP. We concluded that correction of the IRP by AoDNP is not necessary to predict T from additional multiple linear regression. The effects of ascending aortic constriction or angiotensin II on IRP were examined in five dogs, after pretreatment with propranolol. Aortic constriction caused a significant decrease in IRP and T, while angiotensin II produced a significant increase in IRP and T. IRP was affected by the change of afterload. However, the IRP and T values were always altered in the same direction. These results demonstrate that IRP is substituted for T and it reflects left ventricular relaxation even in different afterload conditions. We conclude that IRP is a simple parameter easily used to evaluate left ventricular relaxation in clinical situations.

Estimation of nutrients and organic matter in Korean swine slurry using multiple regression analysis of physical and chemical properties.

PubMed

Suresh, Arumuganainar; Choi, Hong Lim

2011-10-01

Swine waste land application has increased due to organic fertilization, but excess application in an arable system can cause environmental risk. Therefore, in situ characterizations of such resources are important prior to application. To explore this, 41 swine slurry samples were collected from Korea, and wide differences were observed in the physico-biochemical properties. However, significant (P<0.001) multiple property correlations (R²) were obtained between nutrients with specific gravity (SG), electrical conductivity (EC), total solids (TS) and pH. The different combinations of hydrometer, EC meter, drying oven and pH meter were found useful to estimate Mn, Fe, Ca, K, Al, Na, N and 5-day biochemical oxygen demands (BOD₅) at improved R² values of 0.83, 0.82, 0.77, 0.75, 0.67, 0.47, 0.88 and 0.70, respectively. The results from this study suggest that multiple property regressions can facilitate the prediction of micronutrients and organic matter much better than a single property regression for livestock waste. Copyright © 2011 Elsevier Ltd. All rights reserved.

Chronic atrophic gastritis in association with hair mercury level.

PubMed

Xue, Zeyun; Xue, Huiping; Jiang, Jianlan; Lin, Bing; Zeng, Si; Huang, Xiaoyun; An, Jianfu

2014-11-01

The objective of this study was to explore hair mercury level in association with chronic atrophic gastritis, a precancerous stage of gastric cancer (GC), and thus provide a brand new angle of view on the timely intervention of precancerous stage of GC. We recruited 149 healthy volunteers as controls and 152 patients suffering from chronic gastritis as cases. The controls denied upper gastrointestinal discomforts, and the cases were diagnosed as chronic superficial gastritis (n=68) or chronic atrophic gastritis (n=84). We utilized Mercury Automated Analyzer (NIC MA-3000) to detect hair mercury level of both healthy controls and cases of chronic gastritis. The statistic of measurement data was expressed as mean ± standard deviation, which was analyzed using Levene variance equality test and t test. Pearson correlation analysis was employed to determine associated factors affecting hair mercury levels, and multiple stepwise regression analysis was performed to deduce regression equations. Statistical significance is considered if p value is less than 0.05. The overall hair mercury level was 0.908949 ± 0.8844490 ng/g [mean ± standard deviation (SD)] in gastritis cases and 0.460198 ± 0.2712187 ng/g (mean±SD) in healthy controls; the former level was significantly higher than the latter one (p=0.000<0.01). The hair mercury level in chronic atrophic gastritis subgroup was 1.155220 ± 0.9470246 ng/g (mean ± SD) and that in chronic superficial gastritis subgroup was 0.604732 ± 0.6942509 ng/g (mean ± SD); the former level was significantly higher than the latter level (p<0.01). The hair mercury level in chronic superficial gastritis cases was significantly higher than that in healthy controls (p<0.05). The hair mercury level in chronic atrophic gastritis cases was significantly higher than that in healthy controls (p<0.01). Stratified analysis indicated that the hair mercury level in healthy controls with eating seafood was significantly higher than that in healthy controls without eating seafood (p<0.01) and that the hair mercury level in chronic atrophic gastritis cases was significantly higher than that in chronic superficial gastritis cases (p<0.01). Pearson correlation analysis indicated that eating seafood was most correlated with hair mercury level and positively correlated in the healthy controls and that the severity of gastritis was most correlated with hair mercury level and positively correlated in the gastritis cases. Multiple stepwise regression analysis indicated that the regression equation of hair mercury level in controls could be expressed as 0.262 multiplied the value of eating seafood plus 0.434, the model that was statistically significant (p<0.01). Multiple stepwise regression analysis also indicated that the regression equation of hair mercury level in gastritis cases could be expressed as 0.305 multiplied the severity of gastritis, the model that was also statistically significant (p<0.01). The graphs of regression standardized residual for both controls and cases conformed to normal distribution. The main positively correlated factor affecting the hair mercury level is eating seafood in healthy people whereas the predominant positively correlated factor affecting the hair mercury level is the severity of gastritis in chronic gastritis patients. That is to say, the severity of chronic gastritis is positively correlated with the level of hair mercury. The incessantly increased level of hair mercury possibly reflects the development of gastritis from normal stomach to superficial gastritis and to atrophic gastritis. The detection of hair mercury is potentially a means to predict the severity of chronic gastritis and possibly to insinuate the environmental mercury threat to human health in terms of gastritis or even carcinogenesis.

Weather Impact on Airport Arrival Meter Fix Throughput

NASA Technical Reports Server (NTRS)

Wang, Yao

2017-01-01

Time-based flow management provides arrival aircraft schedules based on arrival airport conditions, airport capacity, required spacing, and weather conditions. In order to meet a scheduled time at which arrival aircraft can cross an airport arrival meter fix prior to entering the airport terminal airspace, air traffic controllers make regulations on air traffic. Severe weather may create an airport arrival bottleneck if one or more of airport arrival meter fixes are partially or completely blocked by the weather and the arrival demand has not been reduced accordingly. Under these conditions, aircraft are frequently being put in holding patterns until they can be rerouted. A model that predicts the weather impacted meter fix throughput may help air traffic controllers direct arrival flows into the airport more efficiently, minimizing arrival meter fix congestion. This paper presents an analysis of air traffic flows across arrival meter fixes at the Newark Liberty International Airport (EWR). Several scenarios of weather impacted EWR arrival fix flows are described. Furthermore, multiple linear regression and regression tree ensemble learning approaches for translating multiple sector Weather Impacted Traffic Indexes (WITI) to EWR arrival meter fix throughputs are examined. These weather translation models are developed and validated using the EWR arrival flight and weather data for the period of April-September in 2014. This study also compares the performance of the regression tree ensemble with traditional multiple linear regression models for estimating the weather impacted throughputs at each of the EWR arrival meter fixes. For all meter fixes investigated, the results from the regression tree ensemble weather translation models show a stronger correlation between model outputs and observed meter fix throughputs than that produced from multiple linear regression method.

Estimating Optimal Transformations for Multiple Regression and Correlation.

DTIC Science & Technology

1982-07-01

algorithm; we minimize (2.4) e2 (,,, ...,) = E[e(Y) - 1I (X 2 j=l j 2holding EO =1, E6 = E0, =.-. =Ecp = 0, through a series of single function minimizations...X, x = INU = lIVe . Then (5.16) THEOREM. If 6*, p* is an optimal transformation for regression, then = ue*o Conversely, if e satisfies Xe = U6, Nll1...Stanford University, Tech. Report ORIONOO6. Gasser, T. and Rosenblatt, M. (eds.) (1979). Smoothing Techniques for Curve Estimation, in Lecture Notes in

Multivariate research in areas of phosphorus cast-iron brake shoes manufacturing using the statistical analysis and the multiple regression equations

NASA Astrophysics Data System (ADS)

Kiss, I.; Cioată, V. G.; Alexa, V.; Raţiu, S. A.

2017-05-01

The braking system is one of the most important and complex subsystems of railway vehicles, especially when it comes for safety. Therefore, installing efficient safe brakes on the modern railway vehicles is essential. Nowadays is devoted attention to solving problems connected with using high performance brake materials and its impact on thermal and mechanical loading of railway wheels. The main factor that influences the selection of a friction material for railway applications is the performance criterion, due to the interaction between the brake block and the wheel produce complex thermos-mechanical phenomena. In this work, the investigated subjects are the cast-iron brake shoes, which are still widely used on freight wagons. Therefore, the cast-iron brake shoes - with lamellar graphite and with a high content of phosphorus (0.8-1.1%) - need a special investigation. In order to establish the optimal condition for the cast-iron brake shoes we proposed a mathematical modelling study by using the statistical analysis and multiple regression equations. Multivariate research is important in areas of cast-iron brake shoes manufacturing, because many variables interact with each other simultaneously. Multivariate visualization comes to the fore when researchers have difficulties in comprehending many dimensions at one time. Technological data (hardness and chemical composition) obtained from cast-iron brake shoes were used for this purpose. In order to settle the multiple correlation between the hardness of the cast-iron brake shoes, and the chemical compositions elements several model of regression equation types has been proposed. Because a three-dimensional surface with variables on three axes is a common way to illustrate multivariate data, in which the maximum and minimum values are easily highlighted, we plotted graphical representation of the regression equations in order to explain interaction of the variables and locate the optimal level of each variable for maximal response. For the calculation of the regression coefficients, dispersion and correlation coefficients, the software Matlab was used.

Inflammation, homocysteine and carotid intima-media thickness.

PubMed

Baptista, Alexandre P; Cacdocar, Sanjiva; Palmeiro, Hugo; Faísca, Marília; Carrasqueira, Herménio; Morgado, Elsa; Sampaio, Sandra; Cabrita, Ana; Silva, Ana Paula; Bernardo, Idalécio; Gome, Veloso; Neves, Pedro L

2008-01-01

Cardiovascular disease is the main cause of morbidity and mortality in chronic renal patients. Carotid intima-media thickness (CIMT) is one of the most accurate markers of atherosclerosis risk. In this study, the authors set out to evaluate a population of chronic renal patients to determine which factors are associated with an increase in intima-media thickness. We included 56 patients (F=22, M=34), with a mean age of 68.6 years, and an estimated glomerular filtration rate of 15.8 ml/min (calculated by the MDRD equation). Various laboratory and inflammatory parameters (hsCRP, IL-6 and TNF-alpha) were evaluated. All subjects underwent measurement of internal carotid artery intima-media thickness by high-resolution real-time B-mode ultrasonography using a 10 MHz linear transducer. Intima-media thickness was used as a dependent variable in a simple linear regression model, with the various laboratory parameters as independent variables. Only parameters showing a significant correlation with CIMT were evaluated in a multiple regression model: age (p=0.001), hemoglobin (p=00.3), logCRP (p=0.042), logIL-6 (p=0.004) and homocysteine (p=0.002). In the multiple regression model we found that age (p=0.001) and homocysteine (p=0.027) were independently correlated with CIMT. LogIL-6 did not reach statistical significance (p=0.057), probably due to the small population size. The authors conclude that age and homocysteine correlate with carotid intima-media thickness, and thus can be considered as markers/risk factors in chronic renal patients.

A study of Solar-Enso correlation with southern Brazil tree ring index (1955- 1991)

NASA Astrophysics Data System (ADS)

Rigozo, N.; Nordemann, D.; Vieira, L.; Echer, E.

The effects of solar activity and El Niño-Southern Oscillation on tree growth in Southern Brazil were studied by correlation analysis. Trees for this study were native Araucaria (Araucaria Angustifolia)from four locations in Rio Grande do Sul State, in Southern Brazil: Canela (29o18`S, 50o51`W, 790 m asl), Nova Petropolis (29o2`S, 51o10`W, 579 m asl), Sao Francisco de Paula (29o25`S, 50o24`W, 930 m asl) and Sao Martinho da Serra (29o30`S, 53o53`W, 484 m asl). From these four sites, an average tree ring Index for this region was derived, for the period 1955-1991. Linear correlations were made on annual and 10 year running averages of this tree ring Index, of sunspot number Rz and SOI. For annual averages, the correlation coefficients were low, and the multiple regression between tree ring and SOI and Rz indicates that 20% of the variance in tree rings was explained by solar activity and ENSO variability. However, when the 10 year running averages correlations were made, the coefficient correlations were much higher. A clear anticorrelation is observed between SOI and Index (r=-0.81) whereas Rz and Index show a positive correlation (r=0.67). The multiple regression of 10 year running averages indicates that 76% of the variance in tree ring INdex was explained by solar activity and ENSO. These results indicate that the effects of solar activity and ENSO on tree rings are better seen on long timescales.

Hyperspectral analysis of soil organic matter in coal mining regions using wavelets, correlations, and partial least squares regression.

PubMed

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Wang, Xuchen

2016-02-01

Hyperspectral estimation of soil organic matter (SOM) in coal mining regions is an important tool for enhancing fertilization in soil restoration programs. The correlation--partial least squares regression (PLSR) method effectively solves the information loss problem of correlation--multiple linear stepwise regression, but results of the correlation analysis must be optimized to improve precision. This study considers the relationship between spectral reflectance and SOM based on spectral reflectance curves of soil samples collected from coal mining regions. Based on the major absorption troughs in the 400-1006 nm spectral range, PLSR analysis was performed using 289 independent bands of the second derivative (SDR) with three levels and measured SOM values. A wavelet-correlation-PLSR (W-C-PLSR) model was then constructed. By amplifying useful information that was previously obscured by noise, the W-C-PLSR model was optimal for estimating SOM content, with smaller prediction errors in both calibration (R(2) = 0.970, root mean square error (RMSEC) = 3.10, and mean relative error (MREC) = 8.75) and validation (RMSEV = 5.85 and MREV = 14.32) analyses, as compared with other models. Results indicate that W-C-PLSR has great potential to estimate SOM in coal mining regions.

Genetic analysis of milk production traits of Tunisian Holsteins using random regression test-day model with Legendre polynomials

PubMed Central

2018-01-01

Objective The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. Methods A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. Results All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from 0.78±0.01 to 0.82±0.03, between the first and second parities, from 0.73±0.03 to 0.8±0.04 between the first and third parities, and from 0.82±0.02 to 0.84±0.04 between the second and third parities. Conclusion These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins. PMID:28823122

Genetic analysis of milk production traits of Tunisian Holsteins using random regression test-day model with Legendre polynomials.

PubMed

Ben Zaabza, Hafedh; Ben Gara, Abderrahmen; Rekik, Boulbaba

2018-05-01

The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from 0.78±0.01 to 0.82±0.03, between the first and second parities, from 0.73±0.03 to 0.8±0.04 between the first and third parities, and from 0.82±0.02 to 0.84±0.04 between the second and third parities. These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins.

The Impact of Prior Programming Knowledge on Lecture Attendance and Final Exam

ERIC Educational Resources Information Center

Veerasamy, Ashok Kumar; D'Souza, Daryl; Lindén, Rolf; Laakso, Mikko-Jussi

2018-01-01

In this article, we report the results of the impact of prior programming knowledge (PPK) on lecture attendance (LA) and on subsequent final programming exam performance in a university level introductory programming course. This study used Spearman's rank correlation coefficient, multiple regression, Kruskal-Wallis, and Bonferroni correction…

Investigating the Relationship of Library Usage to Student Outcomes

ERIC Educational Resources Information Center

Stemmer, John K.; Mahan, David M.

2016-01-01

This study connects library user surveys, a common library assessment technique, to institutional data to demonstrate the value an academic library brings to student learning and student outcomes. Using regression techniques, the study identifies multiple significant correlations, both positive and negative, between student use of the library and…

Predicting Student Engagement in Online High Schools

ERIC Educational Resources Information Center

Vieira, Christopher James

2013-01-01

The purpose of this study was to analyze student engagement in online high schools based on demographic information of high school students using a mixed methods research design. Key findings through a multiple regression analysis and Pearson correlation coefficient suggest that although the majority of participants in the study are highly engaged…

Psychosocial and demographic predictors of fruit, juice and vegetable consumption among 11-14-year-old Boy Scouts

USDA-ARS?s Scientific Manuscript database

Psychosocial and demographic correlates of fruit, juice, and vegetable (FJV) consumption were investigated to guide how to increase FJV intake. Experimental design consisted of hierarchical multiple regression analysis of FJV consumption on demographics and psychosocial variables. Subjects were boys...

Emotional Intelligence, Cognitive Flexibility and Psychological Symptoms in Pre-Service Teachers

ERIC Educational Resources Information Center

Gunduz, Bulent

2013-01-01

The purpose of this study is to examine the relationship between emotional intelligence, cognitive flexibility and psychological symptoms in pre-service teachers. The study included 414 pre-service teachers at the Faculty of Education, Mersin University, Turkey. Pearson product-moment correlation and multiple regression analyses were used to…

An Extension of Dominance Analysis to Canonical Correlation Analysis

ERIC Educational Resources Information Center

Huo, Yan; Budescu, David V.

2009-01-01

Dominance analysis (Budescu, 1993) offers a general framework for determination of relative importance of predictors in univariate and multivariate multiple regression models. This approach relies on pairwise comparisons of the contribution of predictors in all relevant subset models. In this article we extend dominance analysis to canonical…

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...

Silanols, a New Class of Antimicrobial Agent

DTIC Science & Technology

2006-04-01

carbinols against the four bacteria was log (1/MLC) = 0.670 log P + 0.0035 ∆ν -1.836, n = 282, r = 0.96, s = 0.22. This equation and a significantly...activity relationship of antimicrobial agents by means of equations [8] based on a method proposed by Hansch and Fujita in 1964 [1]. This multiple...correlation equations between their antimicrobial activities and structural properties, log P and H-bond acidity, were created by a multiple regression

Multivariate meta-analysis using individual participant data.

PubMed

Riley, R D; Price, M J; Jackson, D; Wardle, M; Gueyffier, F; Wang, J; Staessen, J A; White, I R

2015-06-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment-covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. © 2014 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

Socio-economic factors associated with infant mortality in Italy: an ecological study.

PubMed

Dallolio, Laura; Di Gregori, Valentina; Lenzi, Jacopo; Franchino, Giuseppe; Calugi, Simona; Domenighetti, Gianfranco; Fantini, Maria Pia

2012-08-16

One issue that continues to attract the attention of public health researchers is the possible relationship in high-income countries between income, income inequality and infant mortality (IM). The aim of this study was to assess the associations between IM and major socio-economic determinants in Italy. Associations between infant mortality rates in the 20 Italian regions (2006-2008) and the Gini index of income inequality, mean household income, percentage of women with at least 8 years of education, and percentage of unemployed aged 15-64 years were assessed using Pearson correlation coefficients. Univariate linear regression and multiple stepwise linear regression analyses were performed to determine the magnitude and direction of the effect of the four socio-economic variables on IM. The Gini index and the total unemployment rate showed a positive strong correlation with IM (r = 0.70; p < 0.001 and r = 0.84; p < 0.001 respectively), mean household income showed a strong negative correlation (r = -0.78; p < 0.001), while female educational attainment presented a weak negative correlation (r = -0.45; p < 0.05). Using a multiple stepwise linear regression model, only unemployment rate was independently associated with IM (b = 0.15, p < 0.001). In Italy, a high-income country where health care is universally available, variations in IM were strongly associated with relative and absolute income and unemployment rate. These results suggest that in Italy IM is not only related to income distribution, as demonstrated for other developed countries, but also to economic factors such as absolute income and unemployment. In order to reduce IM and the existing inequalities, the challenge for Italian decision makers is to promote economic growth and enhance employment levels.

Does the utilization of dental services associate with masticatory performance in a Japanese urban population?: the Suita study

PubMed Central

Kikui, Miki; Kida, Momoyo; Kosaka, Takayuki; Yamamoto, Masaaki; Yoshimuta, Yoko; Yasui, Sakae; Nokubi, Takashi; Maeda, Yoshinobu; Kokubo, Yoshihiro; Watanabe, Makoto; Miyamoto, Yoshihiro

2015-01-01

Abstract There are numerous reports on the relationship between regular utilization of dental care services and oral health, but most are based on questionnaires and subjective evaluation. Few have objectively evaluated masticatory performance and its relationship to utilization of dental care services. The purpose of this study was to identify the effect of regular utilization of dental services on masticatory performance. The subjects consisted of 1804 general residents of Suita City, Osaka Prefecture (760 men and 1044 women, mean age 66.5 ± 7.9 years). Regular utilization of dental services and oral hygiene habits (frequency of toothbrushing and use of interdental aids) was surveyed, and periodontal status, occlusal support, and masticatory performance were measured. Masticatory performance was evaluated by a chewing test using gummy jelly. The correlation between age, sex, regular dental utilization, oral hygiene habits, periodontal status or occlusal support, and masticatory performance was analyzed using Spearman's correlation test and t‐test. In addition, multiple linear regression analysis was carried out to investigate the relationship of regular dental utilization with masticatory performance after controlling for other factors. Masticatory performance was significantly correlated to age when using Spearman's correlation test, and to regular dental utilization, periodontal status, or occlusal support with t‐test. Multiple linear regression analysis showed that regular utilization of dental services was significantly related to masticatory performance even after adjusting for age, sex, oral hygiene habits, periodontal status, and occlusal support (standardized partial regression coefficient β = 0.055). These findings suggested that the regular utilization of dental care services is an important factor influencing masticatory performance in a Japanese urban population. PMID:29744141

Does the utilization of dental services associate with masticatory performance in a Japanese urban population?: the Suita study.

PubMed

Kikui, Miki; Ono, Takahiro; Kida, Momoyo; Kosaka, Takayuki; Yamamoto, Masaaki; Yoshimuta, Yoko; Yasui, Sakae; Nokubi, Takashi; Maeda, Yoshinobu; Kokubo, Yoshihiro; Watanabe, Makoto; Miyamoto, Yoshihiro

2015-12-01

There are numerous reports on the relationship between regular utilization of dental care services and oral health, but most are based on questionnaires and subjective evaluation. Few have objectively evaluated masticatory performance and its relationship to utilization of dental care services. The purpose of this study was to identify the effect of regular utilization of dental services on masticatory performance. The subjects consisted of 1804 general residents of Suita City, Osaka Prefecture (760 men and 1044 women, mean age 66.5 ± 7.9 years). Regular utilization of dental services and oral hygiene habits (frequency of toothbrushing and use of interdental aids) was surveyed, and periodontal status, occlusal support, and masticatory performance were measured. Masticatory performance was evaluated by a chewing test using gummy jelly. The correlation between age, sex, regular dental utilization, oral hygiene habits, periodontal status or occlusal support, and masticatory performance was analyzed using Spearman's correlation test and t -test. In addition, multiple linear regression analysis was carried out to investigate the relationship of regular dental utilization with masticatory performance after controlling for other factors. Masticatory performance was significantly correlated to age when using Spearman's correlation test, and to regular dental utilization, periodontal status, or occlusal support with t -test. Multiple linear regression analysis showed that regular utilization of dental services was significantly related to masticatory performance even after adjusting for age, sex, oral hygiene habits, periodontal status, and occlusal support (standardized partial regression coefficient β  = 0.055). These findings suggested that the regular utilization of dental care services is an important factor influencing masticatory performance in a Japanese urban population.

Physical activity and depressive symptoms in four ethnic groups of midlife women.

PubMed

Im, Eun-Ok; Ham, Ok Kyung; Chee, Eunice; Chee, Wonshik

2015-06-01

The purpose of this study was to determine the associations between physical activity and depression and the multiple contextual factors influencing these associations in four major ethnic groups of midlife women in the United States. This was a secondary analysis of the data from 542 midlife women. The instruments included questions on background characteristics and health and menopausal status; the Depression Index for Midlife Women (DIMW); and the Kaiser Physical Activity Survey (KPAS). The data were analyzed using chi-square tests, the ANOVA, two-way ANOVA, correlation analyses, and hierarchical multiple regression analyses. The women's depressive symptoms were negatively correlated with active living and sports/exercise physical activities whereas they were positively correlated with occupational physical activities (p < .01). Family income was the strongest predictor of their depressive symptoms. Increasing physical activity may improve midlife women's depressive symptoms, but the types of physical activity and multiple contextual factors need to be considered in intervention development. © The Author(s) 2014.

Serum levels of the immune activation marker neopterin change with age and gender and are modified by race, BMI, and percentage of body fat.

PubMed

Spencer, Monique E; Jain, Alka; Matteini, Amy; Beamer, Brock A; Wang, Nae-Yuh; Leng, Sean X; Punjabi, Naresh M; Walston, Jeremy D; Fedarko, Neal S

2010-08-01

Neopterin, a GTP metabolite expressed by macrophages, is a marker of immune activation. We hypothesize that levels of this serum marker alter with donor age, reflecting increased chronic immune activation in normal aging. In addition to age, we assessed gender, race, body mass index (BMI), and percentage of body fat (%fat) as potential covariates. Serum was obtained from 426 healthy participants whose age ranged from 18 to 87 years. Anthropometric measures included %fat and BMI. Neopterin concentrations were measured by competitive ELISA. The paired associations between neopterin and age, BMI, or %fat were analyzed by Spearman's correlation or by linear regression of log-transformed neopterin, whereas overall associations were modeled by multiple regression of log-transformed neopterin as a function of age, gender, race, BMI, %fat, and interaction terms. Across all participants, neopterin exhibited a positive association with age, BMI, and %fat. Multiple regression modeling of neopterin in women and men as a function of age, BMI, and race revealed that each covariate contributed significantly to neopterin values and that optimal modeling required an interaction term between race and BMI. The covariate %fat was highly correlated with BMI and could be substituted for BMI to yield similar regression coefficients. The association of age and gender with neopterin levels and their modification by race, BMI, or %fat reflect the biology underlying chronic immune activation and perhaps gender differences in disease incidence, morbidity, and mortality.

White Blood Cells, Neutrophils, and Reactive Oxygen Metabolites among Asymptomatic Subjects.

PubMed

Kotani, Kazuhiko; Sakane, Naoki

2012-06-01

Chronic inflammation and oxidative stress are associated with health and the disease status. The objective of the present study was to investigate the association among white blood cell (WBC) counts, neutrophil counts as a WBC subpopulation, and diacron reactive oxygen metabolites (d-ROMs) levels in an asymptomatic population. The clinical data, including general cardiovascular risk variables and high-sensitivity C-reactive protein (hs-CRP), were collected from 100 female subjects (mean age, 62 years) in outpatient clinics. The correlation of the d-ROMs with hs-CRP, WBC, and neutrophil counts was examined. The mean/median levels were WBC counts 5.9 × 10(9)/L, neutrophil counts 3.6 × 10(9)/L, hs-CRP 0.06 mg/dL, and d-ROMs 359 CURR U. A simple correlation analysis showed a significant positive correlation of the d-ROMs with the WBC counts, neutrophil counts, or hs-CRP levels. The correlation between d-ROMs and neutrophil counts (β = 0.22, P < 0.05), as well as that between d-ROMs and hs-CRP (β = 0.28, P < 0.01), remained significant and independent in a multiple linear regression analysis adjusted for other variables. A multiple linear regression analysis showed that WBC counts had only a positive correlation tendency to the d-ROMs. Neutrophils may be slightly but more involved in the oxidative stress status, as assessed by d-ROMs, in comparison to the overall WBC. Further studies are needed to clarify the biologic mechanism(s) of the observed relationship.

Personal growth, symptoms, and uncertainty in community-residing adults with heart failure.

PubMed

Overbaugh, Kristen J; Parshall, Mark B

Personal growth has not been studied extensively in heart failure (HF). To characterize personal growth in HF and its relationships with symptom burden, uncertainty, and demographic and clinical factors. Associations among personal growth, uncertainty, symptom burden, and clinical and demographic variables were examined in adult outpatients with HF using bivariate correlations and multiple regressions. Participants (N = 103; 76% male, mean age = 74 years, 97% New York Heart Association classes II and III) reported moderate levels of personal growth, uncertainty, and symptom burden. Personal growth was weakly correlated with age and symptom burden but not with other study variables. In a regression model, age, sex, ethnicity, disease severity, time since diagnosis, symptom burden, and uncertainty were not significant independent correlates of personal growth. Community-residing patients with HF report moderate personal growth that is not explained by uncertainty, symptom burden, or demographic and clinical variables. Copyright © 2016 Elsevier Inc. All rights reserved.

Radiographic assessment of third molars development and it's relation to dental and chronological age in an Iranian population.

PubMed

Monirifard, Mohamad; Yaraghi, Navid; Vali, Ava; Vali, Asana; Vali, Amrita

2015-01-01

The aim of the present study was to estimate chronological age based on third molar development and to determine the association between dental age and third molar calcification stages. In this cross-sectional study, 505 digital panoramic radiographs of 223 males (44.2%) and 282 females (55.8%) between the age of 6 and 17 were selected from patients who were treated in Departments of Pediatrics and Orthodontics of Isfahan University of Medical Sciences between the years of 2009 and 2013. Correlation between chronological age and third molar development was analyzed with SPSS 21 using Spearman's Rank correlation coefficient, Chi-square test and multiple regression statistical tests (P < 0.05). All third molars demonstrated a highly significant correlation with dental age (P < 0.001). The teeth showing the highest relationship with dental age were mandibular left third molar in males and mandibular right third molar in females (r s = 0.072). When multiple regression was used to predict dental age based on molar calcification stage, the only significant correlation was between maxillary left third molar in males (P < 0.05). There was no statistically significant correlation for any of third molars in females. Relationship between chronological age and molars development stage was significant in all age subgroups and in both gender (P < 0.001). Strong correlation was observed between left third molars and dental age in males. Results showed that third molar calcification stage can be used as an age predictor and in general mandibular teeth seems to be more reliable for this purpose in both genders and in all ages.

Medication Adherence, Work Performance and Self-Esteem among Psychiatric Patients Attending Psychosocial Rehabilitation Services at Bangalore, India.

PubMed

Gandhi, Sailaxmi; Pavalur, Rajitha; Thanapal, Sivakumar; Parathasarathy, Nirmala B; Desai, Geetha; Bhola, Poornima; Philip, Mariamma; Chaturvedi, Santosh K

2014-10-01

Work benefits mental health in innumerable ways. Vocational rehabilitation can enhance self-esteem. Medication adherence can improve work performance and thereby the individuals' self-esteem. To test the hypothesis that there would be a significant correlation between medication adherence, work performance and self-esteem. A quantitative, descriptive correlational research design was adopted to invite patients attending psychiatric rehabilitation services to participate in the research. Data was collected from a convenience sample of 60 subjects using the 'Medication Adherence Rating scale', 'Griffiths work behaviour scale' and the 'Rosenberg's Self-esteem scale'. Analysis was done using spss18 with descriptive statistics, Pearsons correlation coefficient and multiple regression analysis. There were 36 males and 24 females who participated in this study. The subjects had good mean medication adherence of 8.4 ± 1.5 with median of 9.00, high mean self-esteem of 17.65 ± 2.97 with median of 18.0 and good mean work performance of 88.62 ± 22.56 with median of 93.0. Although weak and not significant, there was a positive correlation (r = 0.22, P = 0.103) between medication adherence and work performance; positive correlation between (r = 0.25, P = 0.067) medication adherence and self-esteem; positive correlation between (r = 0.136, P = 0.299) work performance and self-esteem. Multiple regression analysis showed no significant predictors for medication adherence, work performance and self-esteem among patients with psychiatric illness. Medication monitoring and strengthening of work habit can improve self-esteem thereby, strengthening hope of recovery from illness.

Relationship between parent–infant attachment and parental satisfaction with supportive nursing care

PubMed Central

Ghadery-Sefat, Akram; Abdeyazdan, Zahra; Badiee, Zohreh; Zargham-Boroujeni, Ali

2016-01-01

Background: Parent–infant attachment is an important factor in accepting parenting role, accelerating infant survival, and adjusting to the environment outside the uterus. Since family supportive interventions can strengthen the parent–infant caring relationship, this study sought to investigate the relationship between mother–infant attachment and satisfaction of the mothers with the supportive nursing care received in the neonatal intensive care unit (NICU). Materials and Methods: In this descriptive–correlational study, 210 mothers with premature infants who were hospitalized in the NICUs affiliated to Isfahan Medical University hospitals took part. The data were collected via Maternal Postnatal Attachment Scale and researcher's self-tailored questionnaire based on Nurse Parent Support Tool. Pearson correlation coefficient and multiple linear regressions were used to analyze the collected data. Results: The results showed that the overall score of mother–infant attachment and the overall score of maternal satisfaction correlated with a correlation coefficient of r = 0.195. Also, the overall score of mother–infant attachment and mothers’ satisfaction scores in the emotional, communicative-informative, and self-confidence domains correlated with correlation coefficients of r = 0.182, r = 0.0.189, and r = 0.0.304, respectively. The results of multiple regression analysis revealed that about 15% of changes in the dependent variable (mother–infant attachment) could be explained by different dimensions of mothers’ satisfaction. Conclusions: The results of the study showed that mother–infant attachment improved by increasing mothers’ satisfaction of supportive nursing care. Therefore, it seems necessary to increase maternal satisfaction through given nursing care support, in order to promote mother–infant attachment. PMID:26985225

Relationship between parent-infant attachment and parental satisfaction with supportive nursing care.

PubMed

Ghadery-Sefat, Akram; Abdeyazdan, Zahra; Badiee, Zohreh; Zargham-Boroujeni, Ali

2016-01-01

Parent-infant attachment is an important factor in accepting parenting role, accelerating infant survival, and adjusting to the environment outside the uterus. Since family supportive interventions can strengthen the parent-infant caring relationship, this study sought to investigate the relationship between mother-infant attachment and satisfaction of the mothers with the supportive nursing care received in the neonatal intensive care unit (NICU). In this descriptive-correlational study, 210 mothers with premature infants who were hospitalized in the NICUs affiliated to Isfahan Medical University hospitals took part. The data were collected via Maternal Postnatal Attachment Scale and researcher's self-tailored questionnaire based on Nurse Parent Support Tool. Pearson correlation coefficient and multiple linear regressions were used to analyze the collected data. The results showed that the overall score of mother-infant attachment and the overall score of maternal satisfaction correlated with a correlation coefficient of r = 0.195. Also, the overall score of mother-infant attachment and mothers' satisfaction scores in the emotional, communicative-informative, and self-confidence domains correlated with correlation coefficients of r = 0.182, r = 0.0.189, and r = 0.0.304, respectively. The results of multiple regression analysis revealed that about 15% of changes in the dependent variable (mother-infant attachment) could be explained by different dimensions of mothers' satisfaction. The results of the study showed that mother-infant attachment improved by increasing mothers' satisfaction of supportive nursing care. Therefore, it seems necessary to increase maternal satisfaction through given nursing care support, in order to promote mother-infant attachment.

Inverse Association between Air Pressure and Rheumatoid Arthritis Synovitis

PubMed Central

Furu, Moritoshi; Nakabo, Shuichiro; Ohmura, Koichiro; Nakashima, Ran; Imura, Yoshitaka; Yukawa, Naoichiro; Yoshifuji, Hajime; Matsuda, Fumihiko; Ito, Hiromu; Fujii, Takao; Mimori, Tsuneyo

2014-01-01

Rheumatoid arthritis (RA) is a bone destructive autoimmune disease. Many patients with RA recognize fluctuations of their joint synovitis according to changes of air pressure, but the correlations between them have never been addressed in large-scale association studies. To address this point we recruited large-scale assessments of RA activity in a Japanese population, and performed an association analysis. Here, a total of 23,064 assessments of RA activity from 2,131 patients were obtained from the KURAMA (Kyoto University Rheumatoid Arthritis Management Alliance) database. Detailed correlations between air pressure and joint swelling or tenderness were analyzed separately for each of the 326 patients with more than 20 assessments to regulate intra-patient correlations. Association studies were also performed for seven consecutive days to identify the strongest correlations. Standardized multiple linear regression analysis was performed to evaluate independent influences from other meteorological factors. As a result, components of composite measures for RA disease activity revealed suggestive negative associations with air pressure. The 326 patients displayed significant negative mean correlations between air pressure and swellings or the sum of swellings and tenderness (p = 0.00068 and 0.00011, respectively). Among the seven consecutive days, the most significant mean negative correlations were observed for air pressure three days before evaluations of RA synovitis (p = 1.7×10−7, 0.00027, and 8.3×10−8, for swellings, tenderness and the sum of them, respectively). Standardized multiple linear regression analysis revealed these associations were independent from humidity and temperature. Our findings suggest that air pressure is inversely associated with synovitis in patients with RA. PMID:24454853

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.

Urinary symptoms following external beam radiotherapy of the prostate: Dose-symptom correlates with multiple-event and event-count models.

PubMed

Yahya, Noorazrul; Ebert, Martin A; Bulsara, Max; House, Michael J; Kennedy, Angel; Joseph, David J; Denham, James W

2015-11-01

This study aimed to compare urinary dose-symptom correlates after external beam radiotherapy of the prostate using commonly utilised peak-symptom models to multiple-event and event-count models which account for repeated events. Urinary symptoms (dysuria, haematuria, incontinence and frequency) from 754 participants from TROG 03.04-RADAR trial were analysed. Relative (R1-R75 Gy) and absolute (A60-A75Gy) bladder dose-surface area receiving more than a threshold dose and equivalent uniform dose using exponent a (range: a ∈[1 … 100]) were derived. The dose-symptom correlates were analysed using; peak-symptom (logistic), multiple-event (generalised estimating equation) and event-count (negative binomial regression) models. Stronger dose-symptom correlates were found for incontinence and frequency using multiple-event and/or event-count models. For dysuria and haematuria, similar or better relationships were found using peak-symptom models. Dysuria, haematuria and high grade (⩾ 2) incontinence were associated to high dose (R61-R71 Gy). Frequency and low grade (⩾ 1) incontinence were associated to low and intermediate dose-surface parameters (R13-R41Gy). Frequency showed a parallel behaviour (a=1) while dysuria, haematuria and incontinence showed a more serial behaviour (a=4 to a ⩾ 100). Relative dose-surface showed stronger dose-symptom associations. For certain endpoints, the multiple-event and event-count models provide stronger correlates over peak-symptom models. Accounting for multiple events may be advantageous for a more complete understanding of urinary dose-symptom relationships. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Depression is a predictor for balance in people with multiple sclerosis.

PubMed

Alghwiri, Alia A; Khalil, Hanan; Al-Sharman, Alham; El-Salem, Khalid

2018-05-26

Balance impairments are common and multifactorial among people with multiple sclerosis (MS). Depression is the most common psychological disorder in MS population and is strongly correlated with MS disease. Depression might be one of the factors that contribute to balance deficits in this population. However, the relationship between depression and balance impairments has not been explored in people with MS. To investigate the association between depression and balance impairments in people with MS. Cross sectional design was used in patients with MS. The Activities-specific Balance Confidence scale (ABC) and Berg Balance Scale (BBS) was used to assess balance. Beck Depression Inventory (BDI-II) was used to quantify depression and Kurtizki Expanded Disability Status Scale (EDSS) was utilized for the evaluation of MS disability severity. Pearson correlation coefficient was used to examine the association between depression and balance measurements. Multiple linear stepwise regressions were also conducted to find out if depression is a potential predictor for balance deficits. Seventy-five individuals with MS (Female = 69%) with a mean age (SD) of 38.8 (10) and a mean (SD) EDSS score of 3.0 (1.4) were recruited in this study. Depression was present in 53% of the patients. Depression was significantly correlated with balance measurements and EDSS. However, multiple linear stepwise regressions found that only depression and age significantly predict balance. Depression and balance were found frequent and associated in people with MS. Importantly depression was a significant predictor for balance impairments in individuals with MS. Balance rehabilitation may be hindered by depression. Therefore, depression should be evaluated and treated properly in individuals with MS. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Cineradiographic Examination of Articulatory Movement of Pseudo-Tongue, Hyoid, and Mandible in Congenital Aglossia

ERIC Educational Resources Information Center

McMicken, Betty; Vento-Wilson, Margaret; Von Berg, Shelley; Rogers, Kelly

2014-01-01

This research examined cineradiographic films (CRF) of articulatory movements in a person with congenital aglossia (PWCA) during speech production of four phrases. Pearson correlations and a multiple regression model investigated co-variation of independent variables, positions of mandible and hyoid; and pseudo-tongue-dependent variables,…

Factors Related to Play Therapists' Social Justice Advocacy Attitudes

ERIC Educational Resources Information Center

Parikh, Sejal B.; Ceballos, Peggy; Post, Phyllis

2013-01-01

The authors used a correlational research design to examine how belief in a just world, political ideology, socioeconomic status of family of origin, and percentage of racial minority clients were related to social justice advocacy attitudes among play therapists. A multiple regression was used to analyze the data. Results indicated that belief in…

Some Factors Effected Student's Calculus Learning Outcome

ERIC Educational Resources Information Center

Rajagukguk, Wamington

2016-01-01

The purpose of this study is to determine the factors effected calculus learning outcome of the student. This study was conducted with 176 respondents, which were selected randomly. The data were obtained by questionnaire, and then analyzed by using multiple regressions, and correlation, at level of a = 0.05. The findings showed there is the…

Determination of Habitat Requirements For Birds in Suburban Areas

Treesearch

Jack Ward Thomas; Richard M. DeGraaf; Joseph C. Mawson

1977-01-01

Songbird populations can be related to habitat components by a method that allows the simultaneous determination of habitat requirements for a variety of species . Through correlation and multiple-regression analyses, 10 bird species were studied in a suburban habitat, which was stratified according to human density. Variables used to account for bird distribution...

Organizational Response to Conflict: Future Conflict and Work Outcomes

ERIC Educational Resources Information Center

Meyer, Susan

2004-01-01

The purpose of this study was to examine how on organization's response to conflict affected the amount and intensity of future conflict and negative work outcomes. In this cross-sectional study of 3,374 government service workers, bivariate correlations and multiple regressions revealed associations between managers' conflict-handling style (CHS)…

Student Characteristics and Collegiate Environments That Contribute to the Overall Satisfaction with Academic Advising among College Students

ERIC Educational Resources Information Center

DeLaRosby, Hal R.

2017-01-01

Academic advising satisfaction is highly correlated with retention in higher education. Thriving Quotient survey responses were collected from undergraduate students at a private, liberal arts college in the Pacific Northwest. Using a multiple regression analysis, this study examined what "student characteristics" and "collegiate…

Analyzing Preservice Teachers' Technological Pedagogical Content Knowledge Development in the Context of a Multidimensional Teacher Preparation Program

ERIC Educational Resources Information Center

Shinas, Valerie Harlow; Karchmer-Klein, Rachel; Mouza, Chrystalla; Yilmaz-Ozden, Sule; Glutting, Joseph J.

2015-01-01

In this quantitative study, correlational and multiple regression analyses were conducted to examine the technological pedagogical content knowledge (TPACK) development of 299 preservice teachers in response to the technology preparation they received during their initial teacher licensure program. Survey data were analyzed to determine the…

Pre-Service Teacher Self-Efficacy for Teaching Students with Disabilities: What Knowledge Matters?

ERIC Educational Resources Information Center

Browarnik, Brooke; Bell, Sherry Mee; McCallum, R. Steve; Smyth, Kelly; Martin, Melissa

2017-01-01

The relation between items assessing knowledge about educating students with disabilities and the Tschannen-Moran and Hoy's Teachers' Sense of Efficacy Scale (TSES; 2001) was explored for 140 preservice, general education teachers using biserial correlation coefficients and a multiple regression equation. From the data collected, 8 correlations…

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.

The ties that bind what is known to the recall of what is new.

PubMed

Nelson, D L; Zhang, N

2000-12-01

Cued recall success varies with what people know and with what they do during an episode. This paper focuses on prior knowledge and disentangles the relative effects of 10 features of words and their relationships on cued recall. Results are reported for correlational and multiple regression analyses of data obtained from free association norms and from 29 experiments. The 10 features were only weakly correlated with each other in the norms and, with notable exceptions, in the experiments. The regression analysis indicated that forward cue-to-target strength explained the most variance, followed by backward target-to-cue strength. Target connectivity and set size explained the next most variance, along with mediated cue-to-target strength. Finally, frequency, concreteness, shared associate strength, and cue set size also contributed significantly to recall. Taken together, indices of prior word knowledge explain 49% of the recall variance. Theoretically driven equations that use free association to predict cued recall were also evaluated. Each equation was designed to condense multiple indices of word interconnectivity into a single predictor.

Quantification of the effects of quality investment on the Cost of Poor Quality: A quasi-experimental study

NASA Astrophysics Data System (ADS)

Tamimi, Abdallah Ibrahim

Quality management is a fundamental challenge facing businesses. This research attempted to quantify the effect of quality investment on the Cost of Poor Quality (COPQ) in an aerospace company utilizing 3 years of quality data at United Launch Alliance, a Boeing -- Lockheed Martin Joint Venture Company. Statistical analysis tools, like multiple regressions, were used to quantify the relationship between quality investments and COPQ. Strong correlations were evident by the high correlation coefficient R2 and very small p-values in multiple regression analysis. The models in the study helped produce an Excel macro that based on preset constraints, optimized the level of quality spending to minimize COPQ. The study confirmed that as quality investments were increased, the COPQ decreased steadily until a point of diminishing return was reached. The findings may be used to develop an approach to reduce the COPQ and enhance product performance. Achieving superior quality in rocket launching enhances the accuracy, reliability, and mission success of delivering satellites to their precise orbits in pursuit of knowledge, peace, and freedom while assuring safety for the end user.

Hydrology and trout populations of cold-water rivers of Michigan and Wisconsin

USGS Publications Warehouse

Hendrickson, G.E.; Knutilla, R.L.

1974-01-01

Statistical multiple-regression analyses showed significant relationships between trout populations and hydrologic parameters. Parameters showing the higher levels of significance were temperature, hardness of water, percentage of gravel bottom, percentage of bottom vegetation, variability of streamflow, and discharge per unit drainage area. Trout populations increase with lower levels of annual maximum water temperatures, with increase in water hardness, and with increase in percentage of gravel and bottom vegetation. Trout populations also increase with decrease in variability of streamflow, and with increase in discharge per unit drainage area. Most hydrologic parameters were significant when evaluated collectively, but no parameter, by itself, showed a high degree of correlation with trout populations in regression analyses that included all the streams sampled. Regression analyses of stream segments that were restricted to certain limits of hardness, temperature, or percentage of gravel bottom showed improvements in correlation. Analyses of trout populations, in pounds per acre and pounds per mile and hydrologic parameters resulted in regression equations from which trout populations could be estimated with standard errors of 89 and 84 per cent, respectively.

Spiritual Well-Being and Its Relationship with Mindfulness, Self-Compassion and Satisfaction with Life in Baccalaureate Nursing Students: A Correlation Study.

PubMed

Mathad, Monali D; Rajesh, S K; Pradhan, Balaram

2017-12-06

The present study aimed to explore the correlates and predictors of spiritual well-being among nursing students. One hundred and forty-five BSc nursing students were recruited from three nursing colleges in Bangalore, Karnataka, India. Data were collected using SHALOM, FMI, SCS-SF and SWLS questionnaires and analysed by the Pearson correlation test and multiple regression analysis. The results of our study revealed a significant correlation between variables, and a considerable amount of variance was explained by self-compassion, mindfulness and satisfaction with life on personal, communal, environmental and transcendental domains of spiritual well-being.

SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes.

PubMed

Mägi, Reedik; Suleimanov, Yury V; Clarke, Geraldine M; Kaakinen, Marika; Fischer, Krista; Prokopenko, Inga; Morris, Andrew P

2017-01-11

Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits. We have developed the SCOPA software to enable GWAS analysis of multiple correlated phenotypes. The software implements "reverse regression" methodology, which treats the genotype of an individual at a SNP as the outcome and the phenotypes as predictors in a general linear model. SCOPA can be applied to quantitative traits and categorical phenotypes, and can accommodate imputed genotypes under a dosage model. The accompanying META-SCOPA software enables meta-analysis of association summary statistics from SCOPA across GWAS. Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, triglycerides and body mass index, and subsequent meta-analysis with META-SCOPA, highlighted stronger association signals than univariate phenotype analysis at established lipid and obesity loci. The META-SCOPA meta-analysis also revealed a novel signal of association at genome-wide significance for triglycerides mapping to GPC5 (lead SNP rs71427535, p = 1.1x10 -8 ), which has not been reported in previous large-scale GWAS of lipid traits. The SCOPA and META-SCOPA software enable discovery and dissection of multiple phenotype association signals through implementation of a powerful reverse regression approach.

Correlations of diffusion tensor imaging values and symptom scores in patients with schizophrenia.

PubMed

Michael, Andrew M; Calhoun, Vince D; Pearlson, Godfrey D; Baum, Stefi A; Caprihan, Arvind

2008-01-01

Abnormalities in white matter (WM) brain regions are attributed as a possible biomarker for schizophrenia (SZ). Diffusion tensor imaging (DTI) is used to capture WM tracts. Psychometric tests that evaluate the severity of symptoms of SZ are clinically used in the diagnosis process. In this study we investigate the correlates of scalar DTI measures, such as fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity with behavioral test scores. The correlations were found by different schemes: mean correlation with WM atlas regions and multiple regression of DTI values with test scores. The corpus callosum, superior longitudinal fasciculus right and inferior longitudinal fasciculus left were found to be having high correlations with test scores.

Chromium (VI) induced oxidative damage to DNA: increase of urinary 8-hydroxydeoxyguanosine concentrations (8-OHdG) among electroplating workers

PubMed Central

Kuo, H; Chang, S; Wu, K; Wu, F

2003-01-01

Aims: To investigate the concentration of urinary 8-hydroxydeoxyguanosine (8-OHdG) among electroplating workers in Taiwan. Methods: Fifty workers were selected from five chromium (Cr) electroplating plants in central Taiwan. The 20 control subjects were office workers with no previous exposure to Cr. Urinary 8-OHdG concentrations were determined using high performance liquid chromatography with electrochemical detection. Results: Urinary 8-OHdG concentrations among Cr workers (1149.5 pmol/kg/day) were higher than those in the control group (730.2 pmol/kg/day). There was a positive correlation between urinary 8-OHdG concentrations and urinary Cr concentration (r = 0.447, p < 0.01), and urinary 8-OHdG correlated positively with airborne Cr concentration (r = 0.285). Using multiple regression analysis, the factors that affected urinary 8-OHdG concentrations were alcohol, the common cold, and high urinary Cr concentration. There was a high correlation of urinary 8-OHdG with both smoking and drinking, but multiple regression analysis showed that smoking was not a significant factor. Age and gender were also non-significant factors. Conclusion: 8-OHdG, which is an indicator of oxidative DNA damage, was a sensitive biomarker for Cr exposure. PMID:12883020

Examination of the Relationship Between Autonomy and English Achievement as Mediated by Foreign Language Classroom Anxiety.

PubMed

Ghorbandordinejad, Farhad; Ahmadabad, Roghayyeh Moradian

2016-06-01

This study investigated the relationship between autonomy and English language achievement among third-grade high school students as mediated by foreign language classroom anxiety in a city in the north-west of Iran. A sample of 400 students (187 males, and 213 females) was assessed for their levels of autonomy and foreign language anxiety using the Autonomy Questionnaire and Foreign Language Classroom Anxiety Scale (FLCAS), respectively. Participants' scores on their final English exam were also used as the measurement of their English achievement. The results of Pearson correlation revealed a strong correlation between learners' autonomy and their English achievement (r [Formula: see text] .406, n [Formula: see text] 400, [Formula: see text]). Also, foreign language classroom anxiety was found to be significantly and negatively correlated with English achievement (r [Formula: see text] [Formula: see text].472, n [Formula: see text] 400, [Formula: see text]). Hierarchical multiple regression was used to assess the ability of autonomy to predict language learning achievement, after controlling for the influence of anxiety. In sum, the results of hierarchical multiple regressions revealed that foreign language classroom anxiety significantly mediates the relationship between autonomy and English language achievement. Implications for both teachers and learners, and suggestions for further research are provided.

Relation between trinucleotide GAA repeat length and sensory neuropathy in Friedreich's ataxia.

PubMed

Santoro, L; De Michele, G; Perretti, A; Crisci, C; Cocozza, S; Cavalcanti, F; Ragno, M; Monticelli, A; Filla, A; Caruso, G

1999-01-01

To verify if GAA expansion size in Friedreich's ataxia could account for the severity of sensory neuropathy. Retrospective study of 56 patients with Friedreich's ataxia selected according to homozygosity for GAA expansion and availability of electrophysiological findings. Orthodromic sensory conduction velocity in the median nerve was available in all patients and that of the tibial nerve in 46 of them. Data of sural nerve biopsy and of a morphometric analysis were available in 12 of the selected patients. The sensory action potential amplitude at the wrist (wSAP) and at the medial malleolus (m mal SAP) and the percentage of myelinated fibres with diameter larger than 7, 9, and 11 microm in the sural nerve were correlated with disease duration and GAA expansion size on the shorter (GAA1) and larger (GAA2) expanded allele in each pair. Pearson's correlation test and stepwise multiple regression were used for statistical analysis. A significant inverse correlation between GAA1 size and wSAP, m mal SAP, and percentage of myelinated fibres was found. Stepwise multiple regression showed that GAA1 size significantly affects electrophysiological and morphometric data, whereas duration of disease has no effect. The data suggest that the severity of the sensory neuropathy is probably genetically determined and that it is not progressive.

Assessment of triglyceride and cholesterol in overweight people based on multiple linear regression and artificial intelligence model.

PubMed

Ma, Jing; Yu, Jiong; Hao, Guangshu; Wang, Dan; Sun, Yanni; Lu, Jianxin; Cao, Hongcui; Lin, Feiyan

2017-02-20

The prevalence of high hyperlipemia is increasing around the world. Our aims are to analyze the relationship of triglyceride (TG) and cholesterol (TC) with indexes of liver function and kidney function, and to develop a prediction model of TG, TC in overweight people. A total of 302 adult healthy subjects and 273 overweight subjects were enrolled in this study. The levels of fasting indexes of TG (fs-TG), TC (fs-TC), blood glucose, liver function, and kidney function were measured and analyzed by correlation analysis and multiple linear regression (MRL). The back propagation artificial neural network (BP-ANN) was applied to develop prediction models of fs-TG and fs-TC. The results showed there was significant difference in biochemical indexes between healthy people and overweight people. The correlation analysis showed fs-TG was related to weight, height, blood glucose, and indexes of liver and kidney function; while fs-TC was correlated with age, indexes of liver function (P < 0.01). The MRL analysis indicated regression equations of fs-TG and fs-TC both had statistic significant (P < 0.01) when included independent indexes. The BP-ANN model of fs-TG reached training goal at 59 epoch, while fs-TC model achieved high prediction accuracy after training 1000 epoch. In conclusions, there was high relationship of fs-TG and fs-TC with weight, height, age, blood glucose, indexes of liver function and kidney function. Based on related variables, the indexes of fs-TG and fs-TC can be predicted by BP-ANN models in overweight people.

Empirical predictive models of daily relativistic electron flux at geostationary orbit: Multiple regression analysis

DOE PAGES

Simms, Laura E.; Engebretson, Mark J.; Pilipenko, Viacheslav; ...

2016-04-07

The daily maximum relativistic electron flux at geostationary orbit can be predicted well with a set of daily averaged predictor variables including previous day's flux, seed electron flux, solar wind velocity and number density, AE index, IMF Bz, Dst, and ULF and VLF wave power. As predictor variables are intercorrelated, we used multiple regression analyses to determine which are the most predictive of flux when other variables are controlled. Empirical models produced from regressions of flux on measured predictors from 1 day previous were reasonably effective at predicting novel observations. Adding previous flux to the parameter set improves the predictionmore » of the peak of the increases but delays its anticipation of an event. Previous day's solar wind number density and velocity, AE index, and ULF wave activity are the most significant explanatory variables; however, the AE index, measuring substorm processes, shows a negative correlation with flux when other parameters are controlled. This may be due to the triggering of electromagnetic ion cyclotron waves by substorms that cause electron precipitation. VLF waves show lower, but significant, influence. The combined effect of ULF and VLF waves shows a synergistic interaction, where each increases the influence of the other on flux enhancement. Correlations between observations and predictions for this 1 day lag model ranged from 0.71 to 0.89 (average: 0.78). Furthermore, a path analysis of correlations between predictors suggests that solar wind and IMF parameters affect flux through intermediate processes such as ring current ( Dst), AE, and wave activity.« less

Empirical predictive models of daily relativistic electron flux at geostationary orbit: Multiple regression analysis

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

Simms, Laura E.; Engebretson, Mark J.; Pilipenko, Viacheslav

The daily maximum relativistic electron flux at geostationary orbit can be predicted well with a set of daily averaged predictor variables including previous day's flux, seed electron flux, solar wind velocity and number density, AE index, IMF Bz, Dst, and ULF and VLF wave power. As predictor variables are intercorrelated, we used multiple regression analyses to determine which are the most predictive of flux when other variables are controlled. Empirical models produced from regressions of flux on measured predictors from 1 day previous were reasonably effective at predicting novel observations. Adding previous flux to the parameter set improves the predictionmore » of the peak of the increases but delays its anticipation of an event. Previous day's solar wind number density and velocity, AE index, and ULF wave activity are the most significant explanatory variables; however, the AE index, measuring substorm processes, shows a negative correlation with flux when other parameters are controlled. This may be due to the triggering of electromagnetic ion cyclotron waves by substorms that cause electron precipitation. VLF waves show lower, but significant, influence. The combined effect of ULF and VLF waves shows a synergistic interaction, where each increases the influence of the other on flux enhancement. Correlations between observations and predictions for this 1 day lag model ranged from 0.71 to 0.89 (average: 0.78). Furthermore, a path analysis of correlations between predictors suggests that solar wind and IMF parameters affect flux through intermediate processes such as ring current ( Dst), AE, and wave activity.« less

Color vision impairment in multiple sclerosis points to retinal ganglion cell damage.

PubMed

Lampert, E J; Andorra, M; Torres-Torres, R; Ortiz-Pérez, S; Llufriu, S; Sepúlveda, M; Sola, N; Saiz, A; Sánchez-Dalmau, B; Villoslada, P; Martínez-Lapiscina, Elena H

2015-11-01

Multiple Sclerosis (MS) results in color vision impairment regardless of optic neuritis (ON). The exact location of injury remains undefined. The objective of this study is to identify the region leading to dyschromatopsia in MS patients' NON-eyes. We evaluated Spearman correlations between color vision and measures of different regions in the afferent visual pathway in 106 MS patients. Regions with significant correlations were included in logistic regression models to assess their independent role in dyschromatopsia. We evaluated color vision with Hardy-Rand-Rittler plates and retinal damage using Optical Coherence Tomography. We ran SIENAX to measure Normalized Brain Parenchymal Volume (NBPV), FIRST for thalamus volume and Freesurfer for visual cortex areas. We found moderate, significant correlations between color vision and macular retinal nerve fiber layer (rho = 0.289, p = 0.003), ganglion cell complex (GCC = GCIP) (rho = 0.353, p < 0.001), thalamus (rho = 0.361, p < 0.001), and lesion volume within the optic radiations (rho = -0.230, p = 0.030). Only GCC thickness remained significant (p = 0.023) in the logistic regression model. In the final model including lesion load and NBPV as markers of diffuse neuroaxonal damage, GCC remained associated with dyschromatopsia [OR = 0.88 95 % CI (0.80-0.97) p = 0.016]. This association remained significant when we also added sex, age, and disease duration as covariates in the regression model. Dyschromatopsia in NON-eyes is due to damage of retinal ganglion cells (RGC) in MS. Color vision can serve as a marker of RGC damage in MS.

Learning style and concept acquisition of community college students in introductory biology

NASA Astrophysics Data System (ADS)

Bobick, Sandra Burin

This study investigated the influence of learning style on concept acquisition within a sample of community college students in a general biology course. There are two subproblems within the larger problem: (1) the influence of demographic variables (age, gender, number of college credits, prior exposure to scientific information) on learning style, and (2) the correlations between prior scientific knowledge, learning style and student understanding of the concept of the gene. The sample included all students enrolled in an introductory general biology course during two consecutive semesters at an urban community college. Initial data was gathered during the first week of the semester, at which time students filled in a short questionnaire (age, gender, number of college credits, prior exposure to science information either through reading/visual sources or a prior biology course). Subjects were then given the Inventory of Learning Processes-Revised (ILP-R) which measures general preferences in five learning styles; Deep Learning; Elaborative Learning, Agentic Learning, Methodical Learning and Literal Memorization. Subjects were then given the Gene Conceptual Knowledge pretest: a 15 question objective section and an essay section. Subjects were exposed to specific concepts during lecture and laboratory exercises. At the last lab, students were given the Genetics Conceptual Knowledge Posttest. Pretest/posttest gains were correlated with demographic variables and learning styles were analyzed for significant correlations. Learning styles, as the independent variable in a simultaneous multiple regression, were significant predictors of results on the gene assessment tests, including pretest, posttest and gain. Of the learning styles, Deep Learning accounted for the greatest positive predictive value of pretest essay and pretest objective results. Literal Memorization was a significant negative predictor for posttest essay, essay gain and objective gain. Simultaneous multiple regression indicated that demographic variables were significant positive predictors for Methodical, Deep and Elaborative Learning Styles. Stepwise multiple regression resulted in number of credits, Read Science and gender (female) as significant predictors of learning styles. The findings of this study emphasize the importance of learning styles in conceptual understanding of the gene and the correlation of nonformal exposure to science information with learning style and conceptual understanding.

Modification of the USLE K factor for soil erodibility assessment on calcareous soils in Iran

NASA Astrophysics Data System (ADS)

Ostovari, Yaser; Ghorbani-Dashtaki, Shoja; Bahrami, Hossein-Ali; Naderi, Mehdi; Dematte, Jose Alexandre M.; Kerry, Ruth

2016-11-01

The measurement of soil erodibility (K) in the field is tedious, time-consuming and expensive; therefore, its prediction through pedotransfer functions (PTFs) could be far less costly and time-consuming. The aim of this study was to develop new PTFs to estimate the K factor using multiple linear regression, Mamdani fuzzy inference systems, and artificial neural networks. For this purpose, K was measured in 40 erosion plots with natural rainfall. Various soil properties including the soil particle size distribution, calcium carbonate equivalent, organic matter, permeability, and wet-aggregate stability were measured. The results showed that the mean measured K was 0.014 t h MJ- 1 mm- 1 and 2.08 times less than the estimated mean K (0.030 t h MJ- 1 mm- 1) using the USLE model. Permeability, wet-aggregate stability, very fine sand, and calcium carbonate were selected as independent variables by forward stepwise regression in order to assess the ability of multiple linear regression, Mamdani fuzzy inference systems and artificial neural networks to predict K. The calcium carbonate equivalent, which is not accounted for in the USLE model, had a significant impact on K in multiple linear regression due to its strong influence on the stability of aggregates and soil permeability. Statistical indices in validation and calibration datasets determined that the artificial neural networks method with the highest R2, lowest RMSE, and lowest ME was the best model for estimating the K factor. A strong correlation (R2 = 0.81, n = 40, p < 0.05) between the estimated K from multiple linear regression and measured K indicates that the use of calcium carbonate equivalent as a predictor variable gives a better estimation of K in areas with calcareous soils.

Relationship of aerobic and anaerobic parameters with 400 m front crawl swimming performance

PubMed Central

Kalva-Filho, CA; Campos, EZ; Andrade, VL; Silva, ASR; Zagatto, AM; Lima, MCS

2015-01-01

The aims of the present study were to investigate the relationship of aerobic and anaerobic parameters with 400 m performance, and establish which variable better explains long distance performance in swimming. Twenty-two swimmers (19.1±1.5 years, height 173.9±10.0 cm, body mass 71.2±10.2 kg; 76.6±5.3% of 400 m world record) underwent a lactate minimum test to determine lactate minimum speed (LMS) (i.e., aerobic capacity index). Moreover, the swimmers performed a 400 m maximal effort to determine mean speed (S400m), peak oxygen uptake (V.O2PEAK) and total anaerobic contribution (CANA). The CANA was assumed as the sum of alactic and lactic contributions. Physiological parameters of 400 m were determined using the backward extrapolation technique (V.O2PEAK and alactic contributions of CANA) and blood lactate concentration analysis (lactic anaerobic contributions of CANA). The Pearson correlation test and backward multiple regression analysis were used to verify the possible correlations between the physiological indices (predictor factors) and S400m (independent variable) (p < 0.05). Values are presented as mean ± standard deviation. Significant correlations were observed between S400m (1.4±0.1 m·s-1) and LMS (1.3±0.1 m·s-1; r = 0.80), V.O2PEAK (4.5±3.9 L·min-1; r = 0.72) and CANA (4.7±1.5 L·O2; r= 0.44). The best model constructed using multiple regression analysis demonstrated that LMS and V.O2PEAK explained 85% of the 400 m performance variance. When backward multiple regression analysis was performed, CANA lost significance. Thus, the results demonstrated that both aerobic parameters (capacity and power) can be used to predict 400 m swimming performance. PMID:28479663

Predictive ability of a comprehensive incremental test in mountain bike marathon

PubMed Central

Schneeweiss, Patrick; Martus, Peter; Niess, Andreas M; Krauss, Inga

2018-01-01

Objectives Traditional performance tests in mountain bike marathon (XCM) primarily quantify aerobic metabolism and may not describe the relevant capacities in XCM. We aimed to validate a comprehensive test protocol quantifying its intermittent demands. Methods Forty-nine athletes (38.8±9.1 years; 38 male; 11 female) performed a laboratory performance test, including an incremental test, to determine individual anaerobic threshold (IAT), peak power output (PPO) and three maximal efforts (10 s all-out sprint, 1 min maximal effort and 5 min maximal effort). Within 2 weeks, the athletes participated in one of three XCM races (n=15, n=9 and n=25). Correlations between test variables and race times were calculated separately. In addition, multiple regression models of the predictive value of laboratory outcomes were calculated for race 3 and across all races (z-transformed data). Results All variables were correlated with race times 1, 2 and 3: 10 s all-out sprint (r=−0.72; r=−0.59; r=−0.61), 1 min maximal effort (r=−0.85; r=−0.84; r=−0.82), 5 min maximal effort (r=−0.57; r=−0.85; r=−0.76), PPO (r=−0.77; r=−0.73; r=−0.76) and IAT (r=−0.71; r=−0.67; r=−0.68). The best-fitting multiple regression models for race 3 (r2=0.868) and across all races (r2=0.757) comprised 1 min maximal effort, IAT and body weight. Conclusion Aerobic and intermittent variables correlated least strongly with race times. Their use in a multiple regression model confirmed additional explanatory power to predict XCM performance. These findings underline the usefulness of the comprehensive incremental test to predict performance in that sport more precisely. PMID:29387445

Applied immuno-epidemiological research: an approach for integrating existing knowledge into the statistical analysis of multiple immune markers.

PubMed

Genser, Bernd; Fischer, Joachim E; Figueiredo, Camila A; Alcântara-Neves, Neuza; Barreto, Mauricio L; Cooper, Philip J; Amorim, Leila D; Saemann, Marcus D; Weichhart, Thomas; Rodrigues, Laura C

2016-05-20

Immunologists often measure several correlated immunological markers, such as concentrations of different cytokines produced by different immune cells and/or measured under different conditions, to draw insights from complex immunological mechanisms. Although there have been recent methodological efforts to improve the statistical analysis of immunological data, a framework is still needed for the simultaneous analysis of multiple, often correlated, immune markers. This framework would allow the immunologists' hypotheses about the underlying biological mechanisms to be integrated. We present an analytical approach for statistical analysis of correlated immune markers, such as those commonly collected in modern immuno-epidemiological studies. We demonstrate i) how to deal with interdependencies among multiple measurements of the same immune marker, ii) how to analyse association patterns among different markers, iii) how to aggregate different measures and/or markers to immunological summary scores, iv) how to model the inter-relationships among these scores, and v) how to use these scores in epidemiological association analyses. We illustrate the application of our approach to multiple cytokine measurements from 818 children enrolled in a large immuno-epidemiological study (SCAALA Salvador), which aimed to quantify the major immunological mechanisms underlying atopic diseases or asthma. We demonstrate how to aggregate systematically the information captured in multiple cytokine measurements to immunological summary scores aimed at reflecting the presumed underlying immunological mechanisms (Th1/Th2 balance and immune regulatory network). We show how these aggregated immune scores can be used as predictors in regression models with outcomes of immunological studies (e.g. specific IgE) and compare the results to those obtained by a traditional multivariate regression approach. The proposed analytical approach may be especially useful to quantify complex immune responses in immuno-epidemiological studies, where investigators examine the relationship among epidemiological patterns, immune response, and disease outcomes.

Multiple role adaptation among women who have children and re-enter nursing school in Taiwan.

PubMed

Lin, Li-Ling

2005-03-01

This study assessed multiple role adaptation within maternal and student roles among female RNs who had children and returned to school for baccalaureate degrees in Taiwan. Using Roy's Adaptation Model as the theoretical framework, relationships were explored among demographic (number of children, age of youngest child, employment status), physical (sleep quality, health perception, activity), and psychosocial factors (self-identity, role expectation, role involvement, social support) and multiple role adaptation (role accumulation). The sample included 118 mother-students who had at least one child younger than age 18 and who were studying in nursing programs in Taiwan. The highest correlation was found between activity and role accumulation followed by significant correlations between sleep quality, health perception, maternal role expectation, and age of youngest child and role accumulation. In regression analyses, the complete model explained 46% of the variance in role accumulation. Implications for education and future research are identified.

[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.

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.

Measuring decision weights in recognition experiments with multiple response alternatives: comparing the correlation and multinomial-logistic-regression methods.

PubMed

Dai, Huanping; Micheyl, Christophe

2012-11-01

Psychophysical "reverse-correlation" methods allow researchers to gain insight into the perceptual representations and decision weighting strategies of individual subjects in perceptual tasks. Although these methods have gained momentum, until recently their development was limited to experiments involving only two response categories. Recently, two approaches for estimating decision weights in m-alternative experiments have been put forward. One approach extends the two-category correlation method to m > 2 alternatives; the second uses multinomial logistic regression (MLR). In this article, the relative merits of the two methods are discussed, and the issues of convergence and statistical efficiency of the methods are evaluated quantitatively using Monte Carlo simulations. The results indicate that, for a range of values of the number of trials, the estimated weighting patterns are closer to their asymptotic values for the correlation method than for the MLR method. Moreover, for the MLR method, weight estimates for different stimulus components can exhibit strong correlations, making the analysis and interpretation of measured weighting patterns less straightforward than for the correlation method. These and other advantages of the correlation method, which include computational simplicity and a close relationship to other well-established psychophysical reverse-correlation methods, make it an attractive tool to uncover decision strategies in m-alternative experiments.

Bullying Victimization and Perpetration and Their Correlates in Adolescents Clinically Diagnosed With ADHD.

PubMed

Chou, Wen-Jiun; Liu, Tai-Ling; Yang, Pinchen; Yen, Cheng-Fang; Hu, Huei-Fan

2018-01-01

To examine the prevalence rates of bullying involvement and their correlates in adolescents diagnosed with ADHD in Taiwan. Bullying involvement, family and ADHD characteristics, the levels of behavioral inhibition system (BIS) and behavioral approach system (BAS), and psychiatric comorbidity were assessed in 287 adolescents with ADHD. The multiple regression analysis was used to examine the correlate of bullying victimization and perpetration. The prevalence rates of the pure victims, pure perpetrators, and victim-perpetrators were 14.6%, 8.4%, and 5.6%, respectively. Young age, a high BIS score, autism spectrum disorders, and low satisfaction with family relationships were associated with severe bullying victimization. A high score of fun seeking on the BAS and low satisfaction with family relationships were associated with severe bullying perpetration. A high proportion of adolescents with ADHD are involved in bullying. Multiple factors are associated with bullying involvement in adolescents with ADHD.

Multicollinearity may lead to artificial interaction: an example from a cross sectional study of biomarkers.

PubMed

Sithisarankul, P; Weaver, V M; Diener-West, M; Strickland, P T

1997-06-01

Collinearity is the situation which arises in multiple regression when some or all of the explanatory variables are so highly correlated with one another that it becomes very difficult, if not impossible, to disentangle their influences and obtain a reasonably precise estimate of their effects. Suppressor variable is one of the extreme situations of collinearity that one variable can substantially increase the multiple correlation when combined with a variable that is only modestly correlated with the response variable. In this study, we describe the process by which we disentangled and discovered multicollinearity and its consequences, namely artificial interaction, using the data from cross-sectional quantification of several biomarkers. We showed how the collinearity between one biomarker (blood lead level) and another (urinary trans, trans-muconic acid) and their interaction (blood lead level* urinary trans, trans-muconic acid) can lead to the observed artificial interaction on the third biomarker (urinary 5-aminolevulinic acid).

Relationships between Lifestyle, Living Environments, and Incidence of Hypertension in Japan (in Men): Based on Participant’s Data from the Nationwide Medical Check-Up

PubMed Central

Oka, Mayumi; Yamamoto, Mio; Mure, Kanae; Takeshita, Tatsuya; Arita, Mikio

2016-01-01

This study aims to investigate factors that contribute to the differences in incidence of hypertension between different regions in Japan, by accounting for not only individual lifestyles, but also their living environments. The target participants of this survey were individuals who received medical treatment for hypertension, as well as hypertension patients who have not received any treatment. The objective variable for analysis was the incidence of hypertension as data aggregated per prefecture. We used data (in men) including obesity, salt intake, vegetable intake, habitual alcohol consumption, habitual smoking, and number of steps walked per day. The variables within living environment included number of rail stations, standard/light vehicle usage, and slope of habitable land. In addition, we analyzed data for the variables related to medical environment including, participation rate in medical check-ups and number of hospitals. We performed multiple stepwise regression analyses to elucidate the correlation of these variables by using hypertension incidence as the objective variable. Hypertension incidence showed a significant negative correlation with walking and medical check-ups, and a significant positive correlation with light-vehicle usage and slope. Between the number of steps and variables related to the living environment, number of rail stations showed a significant positive correlation, while, standard- and light-vehicle usage showed significant negative correlation. Moreover, with stepwise multiple regression analysis, walking showed the strongest effect. The differences in daily walking based on living environment were associated with the disparities in the hypertension incidence in Japan. PMID:27788198

Higher HOMA-IR index and correlated factors of insulin resistance in patients with IgA nephropathy.

PubMed

Yang, Yue; Wei, Ri-Bao; Wang, Yuan-da; Zhang, Xue-Guang; Rong, Na; Tang, Li; Chen, Xiang-Mei

2012-11-01

To investigate the index of homeostasis model of insulin resistance (HOMA-IR) in IgA nephropathy (IgAN) patients, and to explore the possible correlated factors contributing to insulin resistance (IR) within these patients. There were 255 IgAN patients and 45 membranous nephropathy (MN) patients in our database. We identified 89 IgAN subjects and 21 MN subjects without diabetes and undergoing glucocorticoid therapy for at least 6 months. Data regarding physical examination, blood chemistry and renal pathology were collected from 89 IgAN subjects and 21 MN subjects. Then 62 IgAN patients and 19 MN patients with chronic kidney disease (CKD) Stage 1 - 2 were selected for the comparison of HOMA-IR index, 89 IgAN patients were selected for multiple regression analysis to test for correlated factors of HOMA-IR index with IgAN patients. Comparison between IgAN and MN show that HOMA-IR index was significantly higher in IgAN patients with CKD Stage 1 - 2. After logarithmic transformation with urine protein (UPr), Ln(UPr) (b = 0.186, p = 0.008), eGFR (b = -0.005, p = 0.014), > 50% of glomeruli with mesangial hypercellularity (b = 0.285, p = 0.027) and body mass index (BMI) (b = 0.039, p = 0.008) were correlated factors of HOMA-IR index in the multiple regression analysis. IgAN patients had higher HOMA-IR index compared with MN in the stages of CKD 1 - 2. For IgAN patients, more UPr, lower eGFR, > 50% of glomeruli with mesangial hypercellularity and higher BMI were correlated with IR.

Pulmonary hypertension and computed tomography measurement of small pulmonary vessels in severe emphysema.

PubMed

Matsuoka, Shin; Washko, George R; Yamashiro, Tsuneo; Estepar, Raul San Jose; Diaz, Alejandro; Silverman, Edwin K; Hoffman, Eric; Fessler, Henry E; Criner, Gerard J; Marchetti, Nathaniel; Scharf, Steven M; Martinez, Fernando J; Reilly, John J; Hatabu, Hiroto

2010-02-01

Vascular alteration of small pulmonary vessels is one of the characteristic features of pulmonary hypertension in chronic obstructive pulmonary disease. The in vivo relationship between pulmonary hypertension and morphological alteration of the small pulmonary vessels has not been assessed in patients with severe emphysema. We evaluated the correlation of total cross-sectional area of small pulmonary vessels (CSA) assessed on computed tomography (CT) scans with the degree of pulmonary hypertension estimated by right heart catheterization. In 79 patients with severe emphysema enrolled in the National Emphysema Treatment Trial (NETT), we measured CSA less than 5 mm(2) (CSA(<5)) and 5 to 10 mm(2) (CSA(5-10)), and calculated the percentage of total CSA for the lung area (%CSA(<5) and %CSA(5-10), respectively). The correlations of %CSA(<5) and %CSA(5-10) with pulmonary arterial mean pressure (Ppa) obtained by right heart catheterization were evaluated. Multiple linear regression analysis using Ppa as the dependent outcome was also performed. The %CSA(<5) had a significant negative correlation with Ppa (r = -0.512, P < 0.0001), whereas the correlation between %CSA(5-10) and Ppa did not reach statistical significance (r = -0.196, P = 0.083). Multiple linear regression analysis showed that %CSA(<5) and diffusing capacity of carbon monoxide (DL(CO)) % predicted were independent predictors of Ppa (r(2) = 0.541): %CSA (<5) (P < 0.0001), and DL(CO) % predicted (P = 0.022). The %CSA(<5) measured on CT images is significantly correlated to Ppa in severe emphysema and can estimate the degree of pulmonary hypertension.

The Effects of Social Capital Elements on Job Satisfaction and Motivation Levels of Teachers

ERIC Educational Resources Information Center

Boydak Özan, Mukadder; Yavuz Özdemir, Tuncay; Yaras, Zübeyde

2017-01-01

The purpose of this study is to examine the effects of social capital elements' on job satisfaction and motivation levels of teachers. The mixed method was used in the study. The quantitative data were analyzed through Correlation and Multiple Regression analyses. An interview form developed by the researchers was used for analyzing the…

The Counseling Opportunity Structure: Examining Correlates of Four-Year College-Going Rates

ERIC Educational Resources Information Center

Engberg, Mark E.; Gilbert, Aliza J.

2014-01-01

This study examines the relationships between the normative and resource dimensions of a high school counseling department and four-year college-going rates. Utilizing data from the High School Longitudinal Study of 2009 (HSLS: 09), we employ multiple regression and latent class analysis to identify salient factors related to the college-going…

High- and Low-Achieving Fraternity Environments at a Selective Institution: Their Influence on Members' Binge Drinking and GPA

ERIC Educational Resources Information Center

Maholchic-Nelson, Suzy

2010-01-01

This correlational study tested the efficacy of the social-ecological theory (Moos, 1979) by employing the University Residential Environmental Scale and multiple regression analysis to examine the influences of personal attributes (SAT, parents' level of education, race/ethnicity, and high school drinking) and environmental factors (high/low…

Correlates of Geriatric Loneliness in Philippine Nursing Homes: A Multiple Regression Model

ERIC Educational Resources Information Center

de Guzman, Allan B.; Maravilla, Katrina N.; Maravilla, Veniza Anne M.; Marfil, Jomille D. V.; Marinas, Janine Angelica R.; Marquez, Jorelle Michael B.

2012-01-01

Numerous studies have been conducted worldwide about loneliness in older adults living in nursing homes and the factors associated with it. However, only a few studies have focused on social factors that may predispose these older adults to experience loneliness. The purpose of this study was to examine the interplay between and among loneliness,…

The Impact of Selected Academic and Demographic Variables on Mathematics College Readiness Predicted by ACT

ERIC Educational Resources Information Center

Smith, Marcia

2013-01-01

The purpose of the study was to determine the degree to which academic and demographic variables affected the ACT results used in determining college readiness. This quantitative research study followed a non-experimental correlational design. A multiple regression was used to analyze archival data to determine the impact the combined Arkansas…

The Rosenberg Self-Esteem Scale and Harter's Self-Perception Profile for Adolescents: A Concurrent Validity Study.

ERIC Educational Resources Information Center

Hagborg, Winston J.

1993-01-01

Administered Rosenberg Self-Esteem Scale (RSE) and Harter's Self-Perception Profile for Adolescents to 150 adolescents in grades 8 through 12. Correlational and cross-validation multiple regression analyses found that RSE total score and both its factor scores were strongly related to Global Self-Worth. Females reported significantly lower RSE…

School-Related Variables in the Dimensions of Anger in High School Students in Turkey

ERIC Educational Resources Information Center

Siyez, Digdem M.

2018-01-01

The study aimed to examine the effects of perceived social support from teachers, expectation of academic achievement, school control, and gender on anger dimensions in high school students in Izmir, Turkey. In total, 446 high school students (234 girls, 212 boys) participated in the study. Pearson's correlation and multiple regression analyses…

Methods for Improving Information from "Undesigned" Human Factors Experiments. Technical Report No. p75-287.

ERIC Educational Resources Information Center

Simon, Charles W.

An "undesigned" experiment is one in which the predictor variables are correlated, either due to a failure to complete a design or because the investigator was unable to select or control relevant experimental conditions. The traditional method of analyzing this class of experiment--multiple regression analysis based on a least squares…

Exploring the Relationship between Cultural Intelligence, Transformational Leadership, and Burnout in Doctorate of Education Students

ERIC Educational Resources Information Center

Stokes, D. Michelle.

2013-01-01

This correlational study used standard multiple regression to determine if there was a relationship between the factors of cultural intelligence (metacognitive CQ, cognitive CQ, motivational CQ, and behavioral CQ) and transformational leadership in doctoral students. This study also sought to determine the best predictor of burnout by using a…

Exploring the Impact of Undergraduate Intramural Sports on Undergraduate Students' Perceived Sense of Community: A Multiple Regression Analysis

ERIC Educational Resources Information Center

Penland, Nathan Paul

2017-01-01

Research has shown benefits to the student experience for college students when they participate in intramural sports on university campuses. These benefits include improved physical and social health as well as academic performance. This non-experimental, predictive correlational study sought to understand if a relationship exists between the…

Teacher Empathy and Its Relationship to the Standardized Test Scores of Diverse Secondary English Students

ERIC Educational Resources Information Center

Bostic, Timothy B.

2014-01-01

The purpose of this research study was to ascertain whether there is a relationship between teachers' cognitive role taking aspect of empathy and the Virginia Standards of Learning (VSOL), English/Reading scores of their students. A correlational research design using hierarchical multiple regression was used to look for this relationship. In…

Prevalence and Correlates of School Bullying Victimization in Xi'an, China.

PubMed

Zhu, Yuhong; Chan, Ko Ling

2015-01-01

This study used the data from a representative sample to estimate the prevalence of child bullying victimization in Xi'an, China. Data on social demographic information and the experiences of different types of bullying victimization were collected from a randomly selected sample with 3,175 middle school students aged 15-17 years by self-administrated questionnaires. t Test, χ2 test, and multiple logistic regression analyses were used to test group differences and examine the correlates of bullying victimization. Results show that 54.9% and 44.6% of Chinese children have been bullied in a lifetime and in the preceding year, respectively. Correlates for direct and relational bullying victimization includes male participants, father's lower education level, father's unemployment, having one or more siblings, smoking, depression, borderline personality trait, posttraumatic stress disorder, and from rural schools. Overall, the prevalence of child bullying victimization in China is substantial. The multiple correlates suggest prevention and intervention of bullying victimization in a holistic and comprehensive way.

Estimating the exceedance probability of rain rate by logistic regression

NASA Technical Reports Server (NTRS)

Chiu, Long S.; Kedem, Benjamin

1990-01-01

Recent studies have shown that the fraction of an area with rain intensity above a fixed threshold is highly correlated with the area-averaged rain rate. To estimate the fractional rainy area, a logistic regression model, which estimates the conditional probability that rain rate over an area exceeds a fixed threshold given the values of related covariates, is developed. The problem of dependency in the data in the estimation procedure is bypassed by the method of partial likelihood. Analyses of simulated scanning multichannel microwave radiometer and observed electrically scanning microwave radiometer data during the Global Atlantic Tropical Experiment period show that the use of logistic regression in pixel classification is superior to multiple regression in predicting whether rain rate at each pixel exceeds a given threshold, even in the presence of noisy data. The potential of the logistic regression technique in satellite rain rate estimation is discussed.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies.

PubMed

Koerner, Tess K; Zhang, Yang

2017-02-27

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers.

Estimation of streamflow, base flow, and nitrate-nitrogen loads in Iowa using multiple linear regression models

USGS Publications Warehouse

Schilling, K.E.; Wolter, C.F.

2005-01-01

Nineteen variables, including precipitation, soils and geology, land use, and basin morphologic characteristics, were evaluated to develop Iowa regression models to predict total streamflow (Q), base flow (Qb), storm flow (Qs) and base flow percentage (%Qb) in gauged and ungauged watersheds in the state. Discharge records from a set of 33 watersheds across the state for the 1980 to 2000 period were separated into Qb and Qs. Multiple linear regression found that 75.5 percent of long term average Q was explained by rainfall, sand content, and row crop percentage variables, whereas 88.5 percent of Qb was explained by these three variables plus permeability and floodplain area variables. Qs was explained by average rainfall and %Qb was a function of row crop percentage, permeability, and basin slope variables. Regional regression models developed for long term average Q and Qb were adapted to annual rainfall and showed good correlation between measured and predicted values. Combining the regression model for Q with an estimate of mean annual nitrate concentration, a map of potential nitrate loads in the state was produced. Results from this study have important implications for understanding geomorphic and land use controls on streamflow and base flow in Iowa watersheds and similar agriculture dominated watersheds in the glaciated Midwest. (JAWRA) (Copyright ?? 2005).

Work related stress and blood glucose levels.

PubMed

Sancini, A; Ricci, S; Tomei, F; Sacco, C; Pacchiarotti, A; Nardone, N; Ricci, P; Suppi, A; De Cesare, D P; Anzelmo, V; Giubilati, R; Pimpinella, B; Rosati, M V; Tomei, G

2017-01-01

The aim of the study is to evaluate work-related subjective stress in a group of workers on a major Italian company in the field of healthcare through the administration of a valid "questionnaire-tool indicator" (HSE Indicator Tool), and to analyze any correlation between stress levels taken from questionnaire scores and blood glucose values. We studied a final sample consisting of 241 subjects with different tasks. The HSE questionnaire - made up of 35 items (divided into 7 organizational dimensions) with 5 possible answers - has been distributed to all the subjects in occasion of the health surveillance examinations provided by law. The questionnaire was then analyzed using its specific software to process the results related to the 7 dimensions. These results were compared using the Pearson correlation and multiple linear regression with the blood glucose values obtained from each subject. From the analysis of the data the following areas resulted critical, in other words linked to an intermediate (yellow area) or high (red area) condition of stress: sustain from managers, sustain from colleagues, quality of relationships and professional changes. A significant positive correlation (p <0.05) between the mean values of all critical areas and the concentrations of glucose values have been highlighted with the correlation index of Pearson. Multiple linear regression confirmed these findings, showing that the critical dimensions resulting from the questionnaire were the significant variables that can increase the levels of blood glucose. The preliminary results indicate that perceived work stress can be statistically associated with increased levels of blood glucose.

Psychological Characteristics and Traits for Finding Benefit From Prostate Cancer: Correlates and Predictors.

PubMed

Pascoe, Elizabeth C; Edvardsson, David

Although beginning evidence suggests that the capacity to derive benefit from cancer-associated experiences may be influenced by some individual psychological characteristics and traits, little is known about predictors for finding benefit from prostate cancer. The aim of this study was to explore the correlates and predictors for finding benefit from prostate cancer among a sample of men undergoing androgen deprivation. Pearson correlation and multiple linear regression modeling were performed on data collected in an acute tertiary hospital outpatient setting (N = 209) between July 2011 and December 2013 to determine correlates and predictors for finding benefit from prostate cancer. Multiple linear regression modeling showed that while the 6 predictors of self-reported coping, depression, anxiety, distress, resilience, and hope explained 38% of the variance in finding benefit, coping provided the strongest and statistically significant predictive contribution. Self-reported coping was strongly predictive of finding benefit from prostate cancer, but questions remain about if subtypes of coping strategies can be more or less predictive of finding benefit. Self-reported levels of depression, anxiety, distress, resilience, and hope had a less predictive and nonsignificant role in finding benefit from prostate cancer and raise questions about their function in this subpopulation. The findings suggest that coping strategies can maximize finding benefit from prostate cancer. Knowledge of influential coping strategies for finding benefit from prostate cancer can be immensely valuable to support men in rebuilding positive meaning amid a changed illness reality. Developing practice initiatives that foster positive meaning-making coping strategies seems valuable.

Clinical determinants of the 6-Minute Walk Test in bronchiectasis.

PubMed

Lee, A L; Button, B M; Ellis, S; Stirling, R; Wilson, J W; Holland, A E; Denehy, L

2009-05-01

The 6-Minute Walk Test (6MWT) is a widely used measurement of functional exercise capacity in chronic lung disease. While exercise intolerance has been identified in patients with bronchiectasis, the clinical determinants of the 6MWT in this population have not been examined. The aim of this study was to 1) establish the relationship between the 6-Minute Walk Distance (6MWD), disease severity and Health-Related Quality of Life (HRQOL) and 2) identify predictors of exercise tolerance in adults with bronchiectasis. The 6MWT was performed in 27 patients with bronchiectasis (mean [SD] FEV(1) 73.9% predicted [23.4]). Disease severity was assessed using spirometry and HRCT scoring while HRQOL was evaluated using the St George's Respiratory Questionnaire (SGRQ) and the Short-Form 36 (SF-36). The relationships were evaluated using correlation and multiple regression. The 6MWD correlated positively with FVC (r=0.52, p<0.01), generations of bronchopulmonary divisions (r(s)=0.38, p<0.05) and SF-36 physical summary (r=0.71, p<0.001) while a negative correlation was observed between all domains of the SGRQ (all correlations r>0.5, p<0.001). Multiple regression analysis indicated that the SGRQ activity, symptom scores and generations of bronchial divisions involved were identified as independent predictors of the 6MWD, explaining 76% of the variance. Measures of HRQOL demonstrated a stronger association with the 6MWD compared to physiological measures of disease severity in patients with predominantly mild to moderate bronchiectasis.

Combining ultrasonography and noncontrast helical computerized tomography to evaluate Holmium laser lithotripsy

PubMed Central

Mi, Jia; Li, Jie; Zhang, Qinglu; Wang, Xing; Liu, Hongyu; Cao, Yanlu; Liu, Xiaoyan; Sun, Xiao; Shang, Mengmeng; Liu, Qing

2016-01-01

Abstract The purpose of the study was to establish a mathematical model for correlating the combination of ultrasonography and noncontrast helical computerized tomography (NCHCT) with the total energy of Holmium laser lithotripsy. In this study, from March 2013 to February 2014, 180 patients with single urinary calculus were examined using ultrasonography and NCHCT before Holmium laser lithotripsy. The calculus location and size, acoustic shadowing (AS) level, twinkling artifact intensity (TAI), and CT value were all documented. The total energy of lithotripsy (TEL) and the calculus composition were also recorded postoperatively. Data were analyzed using Spearman's rank correlation coefficient, with the SPSS 17.0 software package. Multiple linear regression was also used for further statistical analysis. A significant difference in the TEL was observed between renal calculi and ureteral calculi (r = –0.565, P < 0.001), and there was a strong correlation between the calculus size and the TEL (r = 0.675, P < 0.001). The difference in the TEL between the calculi with and without AS was highly significant (r = 0.325, P < 0.001). The CT value of the calculi was significantly correlated with the TEL (r = 0.386, P < 0.001). A correlation between the TAI and TEL was also observed (r = 0.391, P < 0.001). Multiple linear regression analysis revealed that the location, size, and TAI of the calculi were related to the TEL, and the location and size were statistically significant predictors (adjusted r2 = 0.498, P < 0.001). A mathematical model correlating the combination of ultrasonography and NCHCT with TEL was established; this model may provide a foundation to guide the use of energy in Holmium laser lithotripsy. The TEL can be estimated by the location, size, and TAI of the calculus. PMID:27930563

Radiographic assessment of third molars development and it's relation to dental and chronological age in an Iranian population

PubMed Central

Monirifard, Mohamad; Yaraghi, Navid; Vali, Ava; Vali, Asana; Vali, Amrita

2015-01-01

Background: The aim of the present study was to estimate chronological age based on third molar development and to determine the association between dental age and third molar calcification stages. Materials and Methods: In this cross-sectional study, 505 digital panoramic radiographs of 223 males (44.2%) and 282 females (55.8%) between the age of 6 and 17 were selected from patients who were treated in Departments of Pediatrics and Orthodontics of Isfahan University of Medical Sciences between the years of 2009 and 2013. Correlation between chronological age and third molar development was analyzed with SPSS 21 using Spearman's Rank correlation coefficient, Chi-square test and multiple regression statistical tests (P < 0.05). Results: All third molars demonstrated a highly significant correlation with dental age (P < 0.001). The teeth showing the highest relationship with dental age were mandibular left third molar in males and mandibular right third molar in females (rs = 0.072). When multiple regression was used to predict dental age based on molar calcification stage, the only significant correlation was between maxillary left third molar in males (P < 0.05). There was no statistically significant correlation for any of third molars in females. Relationship between chronological age and molars development stage was significant in all age subgroups and in both gender (P < 0.001). Conclusion: Strong correlation was observed between left third molars and dental age in males. Results showed that third molar calcification stage can be used as an age predictor and in general mandibular teeth seems to be more reliable for this purpose in both genders and in all ages. PMID:25709677

Combining multiple regression and principal component analysis for accurate predictions for column ozone in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Rajab, Jasim M.; MatJafri, M. Z.; Lim, H. S.

2013-06-01

This study encompasses columnar ozone modelling in the peninsular Malaysia. Data of eight atmospheric parameters [air surface temperature (AST), carbon monoxide (CO), methane (CH4), water vapour (H2Ovapour), skin surface temperature (SSKT), atmosphere temperature (AT), relative humidity (RH), and mean surface pressure (MSP)] data set, retrieved from NASA's Atmospheric Infrared Sounder (AIRS), for the entire period (2003-2008) was employed to develop models to predict the value of columnar ozone (O3) in study area. The combined method, which is based on using both multiple regressions combined with principal component analysis (PCA) modelling, was used to predict columnar ozone. This combined approach was utilized to improve the prediction accuracy of columnar ozone. Separate analysis was carried out for north east monsoon (NEM) and south west monsoon (SWM) seasons. The O3 was negatively correlated with CH4, H2Ovapour, RH, and MSP, whereas it was positively correlated with CO, AST, SSKT, and AT during both the NEM and SWM season periods. Multiple regression analysis was used to fit the columnar ozone data using the atmospheric parameter's variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to acquire subsets of the predictor variables to be comprised in the linear regression model of the atmospheric parameter's variables. It was found that the increase in columnar O3 value is associated with an increase in the values of AST, SSKT, AT, and CO and with a drop in the levels of CH4, H2Ovapour, RH, and MSP. The result of fitting the best models for the columnar O3 value using eight of the independent variables gave about the same values of the R (≈0.93) and R2 (≈0.86) for both the NEM and SWM seasons. The common variables that appeared in both regression equations were SSKT, CH4 and RH, and the principal precursor of the columnar O3 value in both the NEM and SWM seasons was SSKT.

Association between response rates and survival outcomes in patients with newly diagnosed multiple myeloma. A systematic review and meta-regression analysis.

PubMed

Mainou, Maria; Madenidou, Anastasia-Vasiliki; Liakos, Aris; Paschos, Paschalis; Karagiannis, Thomas; Bekiari, Eleni; Vlachaki, Efthymia; Wang, Zhen; Murad, Mohammad Hassan; Kumar, Shaji; Tsapas, Apostolos

2017-06-01

We performed a systematic review and meta-regression analysis of randomized control trials to investigate the association between response to initial treatment and survival outcomes in patients with newly diagnosed multiple myeloma (MM). Response outcomes included complete response (CR) and the combined outcome of CR or very good partial response (VGPR), while survival outcomes were overall survival (OS) and progression-free survival (PFS). We used random-effect meta-regression models and conducted sensitivity analyses based on definition of CR and study quality. Seventy-two trials were included in the systematic review, 63 of which contributed data in meta-regression analyses. There was no association between OS and CR in patients without autologous stem cell transplant (ASCT) (regression coefficient: .02, 95% confidence interval [CI] -0.06, 0.10), in patients undergoing ASCT (-.11, 95% CI -0.44, 0.22) and in trials comparing ASCT with non-ASCT patients (.04, 95% CI -0.29, 0.38). Similarly, OS did not correlate with the combined metric of CR or VGPR, and no association was evident between response outcomes and PFS. Sensitivity analyses yielded similar results. This meta-regression analysis suggests that there is no association between conventional response outcomes and survival in patients with newly diagnosed MM. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Refractive Status at Birth: Its Relation to Newborn Physical Parameters at Birth and Gestational Age

PubMed Central

Varghese, Raji Mathew; Sreenivas, Vishnubhatla; Puliyel, Jacob Mammen; Varughese, Sara

2009-01-01

Background Refractive status at birth is related to gestational age. Preterm babies have myopia which decreases as gestational age increases and term babies are known to be hypermetropic. This study looked at the correlation of refractive status with birth weight in term and preterm babies, and with physical indicators of intra-uterine growth such as the head circumference and length of the baby at birth. Methods All babies delivered at St. Stephens Hospital and admitted in the nursery were eligible for the study. Refraction was performed within the first week of life. 0.8% tropicamide with 0.5% phenylephrine was used to achieve cycloplegia and paralysis of accommodation. 599 newborn babies participated in the study. Data pertaining to the right eye is utilized for all the analyses except that for anisometropia where the two eyes were compared. Growth parameters were measured soon after birth. Simple linear regression analysis was performed to see the association of refractive status, (mean spherical equivalent (MSE), astigmatism and anisometropia) with each of the study variables, namely gestation, length, weight and head circumference. Subsequently, multiple linear regression was carried out to identify the independent predictors for each of the outcome parameters. Results Simple linear regression showed a significant relation between all 4 study variables and refractive error but in multiple regression only gestational age and weight were related to refractive error. The partial correlation of weight with MSE adjusted for gestation was 0.28 and that of gestation with MSE adjusted for weight was 0.10. Birth weight had a higher correlation to MSE than gestational age. Conclusion This is the first study to look at refractive error against all these growth parameters, in preterm and term babies at birth. It would appear from this study that birth weight rather than gestation should be used as criteria for screening for refractive error, especially in developing countries where the incidence of intrauterine malnutrition is higher. PMID:19214228

Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA

USGS Publications Warehouse

Ohlmacher, G.C.; Davis, J.C.

2003-01-01

Landslides in the hilly terrain along the Kansas and Missouri rivers in northeastern Kansas have caused millions of dollars in property damage during the last decade. To address this problem, a statistical method called multiple logistic regression has been used to create a landslide-hazard map for Atchison, Kansas, and surrounding areas. Data included digitized geology, slopes, and landslides, manipulated using ArcView GIS. Logistic regression relates predictor variables to the occurrence or nonoccurrence of landslides within geographic cells and uses the relationship to produce a map showing the probability of future landslides, given local slopes and geologic units. Results indicated that slope is the most important variable for estimating landslide hazard in the study area. Geologic units consisting mostly of shale, siltstone, and sandstone were most susceptible to landslides. Soil type and aspect ratio were considered but excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression. Soil types were highly correlated with the geologic units, and no significant relationships existed between landslides and slope aspect. ?? 2003 Elsevier Science B.V. All rights reserved.

Computing mammographic density from a multiple regression model constructed with image-acquisition parameters from a full-field digital mammographic unit

PubMed Central

Lu, Lee-Jane W.; Nishino, Thomas K.; Khamapirad, Tuenchit; Grady, James J; Leonard, Morton H.; Brunder, Donald G.

2009-01-01

Breast density (the percentage of fibroglandular tissue in the breast) has been suggested to be a useful surrogate marker for breast cancer risk. It is conventionally measured using screen-film mammographic images by a labor intensive histogram segmentation method (HSM). We have adapted and modified the HSM for measuring breast density from raw digital mammograms acquired by full-field digital mammography. Multiple regression model analyses showed that many of the instrument parameters for acquiring the screening mammograms (e.g. breast compression thickness, radiological thickness, radiation dose, compression force, etc) and image pixel intensity statistics of the imaged breasts were strong predictors of the observed threshold values (model R2=0.93) and %density (R2=0.84). The intra-class correlation coefficient of the %-density for duplicate images was estimated to be 0.80, using the regression model-derived threshold values, and 0.94 if estimated directly from the parameter estimates of the %-density prediction regression model. Therefore, with additional research, these mathematical models could be used to compute breast density objectively, automatically bypassing the HSM step, and could greatly facilitate breast cancer research studies. PMID:17671343

A Study of the Effect of the Front-End Styling of Sport Utility Vehicles on Pedestrian Head Injuries

PubMed Central

Qin, Qin; Chen, Zheng; Bai, Zhonghao; Cao, Libo

2018-01-01

Background The number of sport utility vehicles (SUVs) on China market is continuously increasing. It is necessary to investigate the relationships between the front-end styling features of SUVs and head injuries at the styling design stage for improving the pedestrian protection performance and product development efficiency. Methods Styling feature parameters were extracted from the SUV side contour line. And simplified finite element models were established based on the 78 SUV side contour lines. Pedestrian headform impact simulations were performed and validated. The head injury criterion of 15 ms (HIC15) at four wrap-around distances was obtained. A multiple linear regression analysis method was employed to describe the relationships between the styling feature parameters and the HIC15 at each impact point. Results The relationship between the selected styling features and the HIC15 showed reasonable correlations, and the regression models and the selected independent variables showed statistical significance. Conclusions The regression equations obtained by multiple linear regression can be used to assess the performance of SUV styling in protecting pedestrians' heads and provide styling designers with technical guidance regarding their artistic creations.

Abdominal girth and vertebral column length can adjust spinal anesthesia for lower limb surgery, a prospective, observational study.

PubMed

Zhou, Qing-he; Zhu, Bo; Wei, Chang-na; Yan, Min

2016-03-24

Studies have shown that abdominal girth and vertebral column length have high predictive value for spinal spread after administering a dose of plain bupivacaine. we designed a study to identify the specific correlations between abdominal girth, vertebral column length and a 0.5% dosage of plain bupivacaine, which should provide a minimum upper block level (T12) and a suitable upper block level (T10) for lower limb surgeries. A suitable dose of 0.5% plain bupivacaine was administered intrathecally between the L3 and L4 vertebrae for lower limb surgeries. If the upper cephalad spread of the patient by loss of pinprick discrimination was T12 or T10, the patient was enrolled in this study. Five patient variables and intrathecal plain bupivacaine dose were recorded. Linear regression and multiple regression analyses were performed. Totals of 111 patients and 121 patients who lost pinprick discrimination at T12 and T10, respectively, were analyzed in this study. Linear regression analysis showed that only abdominal girth and plain bupivacaine dose were strongly correlated (r =-0.827 for T12, r = -0.806 for T10; both p < 0.0001). Multiple linear regression analysis showed that both abdominal girth and vertebral column length were the key determinants of plain bupivacaine dose (both p < 0.0001). R(2) was 0.874 and 0.860 for the loss of pinprick discrimination at T12 and T10, respectively. Our data indicated that vertebral column length and abdominal girth were strongly correlated with the dosage of intrathecal plain bupivacaine for the loss of pinprick discrimination at T12 and T10. The two regression equations were YT12 = 3.547 + 0.045X1-0.044X2 and YT10 = 3.848 + 0.047X1- 0.046X2 (Y, 0.5% plain bupivacaine volume; X1, vertebral column length;and X 2, abdominal girth), which can accurately predict the minimum and suitable intrathecal bupivacaine dose for lower limb surgery to a great extent, separately.

Serum resistin is associated with the severity of microangiopathies in type 2 diabetes

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

Osawa, Haruhiko; Ochi, Masaaki; Kato, Kenichi

2007-04-06

Resistin, secreted from adipocytes, causes insulin resistance and diabetes in rodents. To determine the relation between serum resistin and diabetic microangiopathies in humans, we analyzed 238 Japanese T2DM subjects. Mean serum resistin was higher in subjects with either advanced retinopathy (preproliferative or proliferative) (P = 0.0130), advanced nephropathy (stage III or IV) (P = 0.0151), or neuropathy (P = 0.0013). Simple regression analysis showed that serum resistin was positively correlated with retinopathy stage (P = 0.0212), nephropathy stage (P = 0.0052), and neuropathy (P = 0.0013). Multiple regression analysis adjusted for age, gender, and BMI, revealed that serum resistin wasmore » correlated with retinopathy stage (P = 0.0144), nephropathy stage (P = 0.0111), and neuropathy (P = 0.0053). Serum resistin was positively correlated with the number of advanced microangiopathies, independent of age, gender, BMI, and either the duration of T2DM (P = 0.0318) or serum creatinine (P = 0.0092). Therefore, serum resistin was positively correlated with the severity of microangiopathies in T2DM.« less

Asymptotics of nonparametric L-1 regression models with dependent data

PubMed Central

ZHAO, ZHIBIAO; WEI, YING; LIN, DENNIS K.J.

2013-01-01

We investigate asymptotic properties of least-absolute-deviation or median quantile estimates of the location and scale functions in nonparametric regression models with dependent data from multiple subjects. Under a general dependence structure that allows for longitudinal data and some spatially correlated data, we establish uniform Bahadur representations for the proposed median quantile estimates. The obtained Bahadur representations provide deep insights into the asymptotic behavior of the estimates. Our main theoretical development is based on studying the modulus of continuity of kernel weighted empirical process through a coupling argument. Progesterone data is used for an illustration. PMID:24955016

Anthropometric Survey of US Army Personnel (1988): Correlation Coefficients and Regression Equations. Part 5. Stepwise and Standard Multiple Regression Tables

DTIC Science & Technology

1990-05-01

0.759 0.744 0.768 0.753 106 (THUMBBR) THUMB BREADTH -0.652 -0.673 -0.539 -0.663 217 (LIPLGTHH) LIP LENGTH HEADBOARD 0.017 0.019 0.020 51 (FTBRHOR) FOOT...DEPENDENT VARIABLE: (106) THUMB BREADTH (THUBBR) MODEL INDEPENDENT VARIABLE 1 2 3 4 5 INTERCEPT 6.621 5.016 6.267 5.697 4.528 59 (HANDCIRC) HAND...95 (SLLSPEL) SLEEVE LENGTH: SPINE-ELBOW -0.020 -0.019 -C.018 9 (BLFTCIRC) BALL OF FOOT CIRCUMFERENCE -0.032 -0.039 106 (THUMBBR) THUMB BREADTH 0.228

Correlates and predictors of missed nursing care in hospitals.

PubMed

Bragadóttir, Helga; Kalisch, Beatrice J; Tryggvadóttir, Gudný Bergthora

2017-06-01

To identify the contribution of hospital, unit, staff characteristics, staffing adequacy and teamwork to missed nursing care in Iceland hospitals. A recently identified quality indicator for nursing care and patient safety is missed nursing care defined as any standard, required nursing care omitted or significantly delayed, indicating an error of omission. Former studies point to contributing factors to missed nursing care regarding hospital, unit and staff characteristics, perceptions of staffing adequacy as well as nursing teamwork, displayed in the Missed Nursing Care Model. This was a quantitative cross-sectional survey study. The samples were all registered nurses and practical nurses (n = 864) working on 27 medical, surgical and intensive care inpatient units in eight hospitals throughout Iceland. Response rate was 69·3%. Data were collected in March-April 2012 using the combined MISSCARE Survey-Icelandic and the Nursing Teamwork Survey-Icelandic. Descriptive, correlational and regression statistics were used for data analysis. Missed nursing care was significantly related to hospital and unit type, participants' age and role and their perception of adequate staffing and level of teamwork. The multiple regression testing of Model 1 indicated unit type, role, age and staffing adequacy to predict 16% of the variance in missed nursing care. Controlling for unit type, role, age and perceptions of staffing adequacy, the multiple regression testing of Model 2 showed that nursing teamwork predicted an additional 14% of the variance in missed nursing care. The results shed light on the correlates and predictors of missed nursing care in hospitals. This study gives direction as to the development of strategies for decreasing missed nursing care, including ensuring appropriate staffing levels and enhanced teamwork. By identifying contributing factors to missed nursing care, appropriate interventions can be developed and tested. © 2016 John Wiley & Sons Ltd.

Study relationship between inorganic and organic coal analysis with gross calorific value by multiple regression and ANFIS

USGS Publications Warehouse

Chelgani, S.C.; Hart, B.; Grady, W.C.; Hower, J.C.

2011-01-01

The relationship between maceral content plus mineral matter and gross calorific value (GCV) for a wide range of West Virginia coal samples (from 6518 to 15330 BTU/lb; 15.16 to 35.66MJ/kg) has been investigated by multivariable regression and adaptive neuro-fuzzy inference system (ANFIS). The stepwise least square mathematical method comparison between liptinite, vitrinite, plus mineral matter as input data sets with measured GCV reported a nonlinear correlation coefficient (R2) of 0.83. Using the same data set the correlation between the predicted GCV from the ANFIS model and the actual GCV reported a R2 value of 0.96. It was determined that the GCV-based prediction methods, as used in this article, can provide a reasonable estimation of GCV. Copyright ?? Taylor & Francis Group, LLC.

Generalized regression neural network (GRNN)-based approach for colored dissolved organic matter (CDOM) retrieval: case study of Connecticut River at Middle Haddam Station, USA.

PubMed

Heddam, Salim

2014-11-01

The prediction of colored dissolved organic matter (CDOM) using artificial neural network approaches has received little attention in the past few decades. In this study, colored dissolved organic matter (CDOM) was modeled using generalized regression neural network (GRNN) and multiple linear regression (MLR) models as a function of Water temperature (TE), pH, specific conductance (SC), and turbidity (TU). Evaluation of the prediction accuracy of the models is based on the root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (CC), and Willmott's index of agreement (d). The results indicated that GRNN can be applied successfully for prediction of colored dissolved organic matter (CDOM).

Investigating bias in squared regression structure coefficients

PubMed Central

Nimon, Kim F.; Zientek, Linda R.; Thompson, Bruce

2015-01-01

The importance of structure coefficients and analogs of regression weights for analysis within the general linear model (GLM) has been well-documented. The purpose of this study was to investigate bias in squared structure coefficients in the context of multiple regression and to determine if a formula that had been shown to correct for bias in squared Pearson correlation coefficients and coefficients of determination could be used to correct for bias in squared regression structure coefficients. Using data from a Monte Carlo simulation, this study found that squared regression structure coefficients corrected with Pratt's formula produced less biased estimates and might be more accurate and stable estimates of population squared regression structure coefficients than estimates with no such corrections. While our findings are in line with prior literature that identified multicollinearity as a predictor of bias in squared regression structure coefficients but not coefficients of determination, the findings from this study are unique in that the level of predictive power, number of predictors, and sample size were also observed to contribute bias in squared regression structure coefficients. PMID:26217273

The insulin effect on cerebrocortical theta activity is associated with serum concentrations of saturated nonesterified Fatty acids.

PubMed

Tschritter, Otto; Preissl, Hubert; Hennige, Anita M; Sartorius, Tina; Grichisch, Yuko; Stefan, Norbert; Guthoff, Martina; Düsing, Stephan; Machann, Jürgen; Schleicher, Erwin; Cegan, Alexander; Birbaumer, Niels; Fritsche, Andreas; Häring, Hans-Ulrich

2009-11-01

Insulin action in the brain contributes to adequate regulation of body weight, neuronal survival, and suppression of endogenous glucose production. We previously demonstrated by magnetoencephalography in lean humans that insulin stimulates activity in beta and theta frequency bands, whereas this effect was abolished in obese individuals. The present study aims to define metabolic signals associated with the suppression of the cerebrocortical response in obese humans. We determined insulin-mediated modulation of spontaneous cerebrocortical activity by magnetoencephalography during a hyperinsulinemic euglycemic clamp and related it to measures of ectopic fat deposition and mediators of peripheral insulin resistance. Visceral fat mass and intrahepatic lipid content were quantified by magnetic resonance imaging and spectroscopy. Multiple regression analysis was used to analyze associations of cerebrocortical insulin sensitivity and metabolic markers related to obesity. Forty-nine healthy, nondiabetic humans participated in the study. In a multiple regression, insulin-mediated stimulation of theta activity was negatively correlated to body mass index, visceral fat mass, and intrahepatic lipid content. Although fasting saturated nonesterified fatty acids mediated the correlations of theta activity with abdominal and intrahepatic lipid stores, adipocytokines displayed no independent correlation with insulin-mediated cortical activity in the theta frequency band. Thus, insulin action at the level of cerebrocortical activity in the brain is diminished in the presence of elevated levels of saturated nonesterified fatty acids.

[Life satisfaction and related socio-demographic factors during female midlife].

PubMed

Cuadros, José Luis; Pérez-Roncero, Gonzalo R; López-Baena, María Teresa; Cuadros-Celorrio, Angela M; Fernández-Alonso, Ana María

2014-01-01

To assess life satisfaction and related factors in middle-aged Spanish women. This was a cross-sectional study including 235 women aged 40 to 65, living in Granada (Spain), healthy companions of patients visiting the obstetrics and gynecology clinics. They completed the Diener Satisfaction with Life Scale, the Menopause Rating Scale, the Perceived Stress Scale, the Insomnia Severity Index and a sociodemographic questionnaire containing personal and partner data. Internal consistency of each tool was also calculated. Almost two-thirds (61.3%) of the women were postmenopausal, and 43.8% had abdominal obesity, 36.6% had insomnia, 18.7% had poor menopause-related quality of life, 31.9% performed regular exercise, and 5.1% had severe financial problems. Life satisfaction showed significant positive correlations (Spearman's test) with female and male age, and inverse correlations with menopause-related quality of life, perceived stress and insomnia. In the multiple linear regression analysis, high life satisfaction is positively correlated with having a partner who performed exercise, and inversely with having work problems, perceived stress and the suspicion of partner infidelity. These factors explained 40% of the variance of the multiple regression analysis for life satisfaction in middle-aged women. Life satisfaction is a construct related to perceived stress, work problems, and having a partner, while aspects of menopause and general health had no significant influence. Copyright © 2014 Elsevier España, S.L.U. All rights reserved.

Modeling lactation curves and estimation of genetic parameters in Holstein cows using multiple-trait random regression models.

PubMed

Kheirabadi, Khabat; Rashidi, Amir; Alijani, Sadegh; Imumorin, Ikhide

2014-11-01

We compared the goodness of fit of three mathematical functions (including: Legendre polynomials, Lidauer-Mäntysaari function and Wilmink function) for describing the lactation curve of primiparous Iranian Holstein cows by using multiple-trait random regression models (MT-RRM). Lactational submodels provided the largest daily additive genetic (AG) and permanent environmental (PE) variance estimates at the end and at the onset of lactation, respectively, as well as low genetic correlations between peripheral test-day records. For all models, heritability estimates were highest at the end of lactation (245 to 305 days) and ranged from 0.05 to 0.26, 0.03 to 0.12 and 0.04 to 0.24 for milk, fat and protein yields, respectively. Generally, the genetic correlations between traits depend on how far apart they are or whether they are on the same day in any two traits. On average, genetic correlations between milk and fat were the lowest and those between fat and protein were intermediate, while those between milk and protein were the highest. Results from all criteria (Akaike's and Schwarz's Bayesian information criterion, and -2*logarithm of the likelihood function) suggested that a model with 2 and 5 coefficients of Legendre polynomials for AG and PE effects, respectively, was the most adequate for fitting the data. © 2014 Japanese Society of Animal Science.

Relationship between pelvic incidence and osteoarthritis of the hip

PubMed Central

Weinberg, D. S.; Bohl, M. S.; Liu, R. W.

2016-01-01

Objectives Sagittal alignment of the lumbosacral spine, and specifically pelvic incidence (PI), has been implicated in the development of spine pathology, but generally ignored with regards to diseases of the hip. We aimed to determine if increased PI is correlated with higher rates of hip osteoarthritis (HOA). The effect of PI on the development of knee osteoarthritis (KOA) was used as a negative control. Methods We studied 400 well-preserved cadaveric skeletons ranging from 50 to 79 years of age at death. Each specimen’s OA of the hip and knee were graded using a previously described method. PI was measured from standardised lateral photographs of reconstructed pelvises. Multiple regression analysis was performed to determine the relationship between age and PI with HOA and KOA. Results The mean age was 60.2 years (standard deviation (sd) 8.1), and the mean PI was 46.7° (sd 10.7°). Multiple regression analysis demonstrated a significant correlation between increased PI and HOA (standardised beta = 0.103, p = 0.017). There was no correlation between PI and KOA (standardised beta = 0.003, p = 0.912). Conclusion Higher PI in the younger individual may contribute to the development of HOA in later life. Cite this article: Dr J. J. Gebhart. Relationship between pelvic incidence and osteoarthritis of the hip. Bone Joint Res 2016;5:66–72. DOI: 10.1302/2046-3758.52.2000552. PMID:26912384

Decision making of heavy cannabis users on the Iowa Gambling Task: stronger association with THC of hair analysis than with personality traits of the Tridimensional Personality Questionnaire.

PubMed

Hermann, Derik; Leménager, Tagrid; Gelbke, Jan; Welzel, Helga; Skopp, Gisela; Mann, Karl

2009-01-01

It is unclear whether impairment in decision making, measured by the Iowa Gambling Task (IGT), in addiction is substance-induced or the consequence of personality structure. Analysis of the IGT, the Tridimensional Personality Questionnaire (TPQ) and cannabinoids in hair and urine were performed in 13 cannabis users and matched controls. Hair Delta(9)-tetrahydrocannabinol (THC) correlated negatively with the last subtrial (cards 80-100) of the IGT (R = -0.67). In all participants (n = 26) the TPQ dimension, harm avoidance, correlated negatively with the total IGT score (R = -0.46). The last IGT-subtrial correlated with adventure seeking (R = 0.43), harm avoidance (R = -0.39) and reward dependence (R = -0.44). The last subtrial gives information on whether a participant has learned the IGT strategy. Multiple regression confirmed the impact of THC on the last subtrial, whereas TPQ personality traits did not additionally explain variance. Former indications of the IGT performance depending on the amount of cannabis consumed were replicated with an objective measurement of chronic cannabis consumption (hair THC). Multiple regression analysis argues for a stronger impact of chronic THC consumption than personality traits, but does not provide a causal relationship. Other factors (e.g. genetic) may also play a role. 2009 S. Karger AG, Basel.

Ethnic differences in correlates of suicidal behavior among women seeking help for intimate partner violence.

PubMed

Cavanaugh, Courtenay E; Messing, Jill T; Eyzerovich, Evelina; Campbell, Jacquelyn C

2015-01-01

Women abused by an intimate partner are at risk of engaging in nonfatal suicidal behavior and suicidal communication (NSBSC). No studies have examined ethnic differences in correlates of NSBSC among abused women. This secondary data analytic study examined whether correlates of NSBSC previously reported among a mixed ethnic sample of women seeking help for abuse by a male intimate partner differed for those who self-identified as Latina (N = 340), African American (N = 184), or European American (N = 67). Logistic regression was used to examine correlates of NSBSC separately among Latina, African American, and European American women. More severe violence by a male intimate partner, having a chronic or disabling illness, being younger, and being unemployed were positively associated with NSBSC in bivariate analyses among Latina women, but unemployment did not remain significantly associated with NSBSC in the multiple logistic regression. There were no significant correlates of NSBSC for African American women. Having a chronic illness was significantly associated with NSBSC among European American women. Findings suggest the need for culturally tailored suicide prevention interventions and studies that examine risk and protective factors for NSBSC among a diversity of women abused by male intimate partners.

Correlates and Predictors of Resilience among Baccalaureate Nursing Students.

PubMed

Mathad, Monali Devaraj; Pradhan, Balaram; Rajesh, Sasidharan K

2017-02-01

A growing body of literature recognizes the importance of resilience in the nursing profession. Both mindfulness and resilience aid in handling stress, stress increases the risk of rumination and/or worry especially in females and they are more empathetic than other healthcare students. To identify correlates and predictors of the resilience among nursing students. This is a descriptive correlation study and we have recruited 194 participants (1-4 th year B.Sc Nursing) from Government College of Nursing and NIMHANS College of Nursing in Bangalore, India. The following instruments were used to collect the data, Freiburg Mindfulness Inventory (FMI), Toronto Empathy Questionnaire (TEQ), Perseverative Thinking Questionnaire (PTQ) and Connor-Davidson Resilience Scale (CD-RISC). Data was analysed using Pearson's correlation test and multiple regression analysis. Resilience is significantly correlated with mindfulness, perseverative thinking and empathy in nursing students. Based on regression analysis this model accounted for almost 33% of variance in resilience. This result is of interest as mindfulness alone explained 23% of the variance and unproductive Repeated Negative Thinking (RNT) and RNT consuming mental capacity predicted 8% and 2% respectively. These results support the importance of resilience and mindfulness in nursing students. Hence, resilience and/or mindfulness enhancing interventions should be inculcated in nursing education.

Epidemiology of multiple childhood traumatic events: child abuse, parental psychopathology, and other family-level stressors.

PubMed

Menard, C B; Bandeen-Roche, K J; Chilcoat, H D

2004-11-01

Multiple family-level childhood stressors are common and are correlated. It is unknown if clusters of commonly co-occurring stressors are identifiable. The study was designed to explore family-level stressor clustering in the general population, to estimate the prevalence of exposure classes, and to examine the correlation of sociodemographic characteristics with class prevalence. Data were collected from an epidemiological sample and analyzed using latent class regression. A six-class solution was identified. Classes were characterized by low risk (prevalence=23%), universal high risk (7 %), family conflict (11 %), household substance problems (22 %), non-nuclear family structure (24 %), parent's mental illness (13 %). Class prevalence varied with race and welfare status, not gender. Interventions for childhood stressors are person-focused; the analytic approach may uniquely inform resource allocation.

Temporal Progression of Visual Injury from Blast Exposure

DTIC Science & Technology

2017-09-01

seen throughout the duration of the study. To correlate experimental blast exposures in rodents to human blast exposures, a computational parametric...software (JMP 10.0, Cary,NC). Descriptive and univariate analyses will first be performed to identify the occurrence of delayed visual system...later). The biostatistician evaluating the retrospective data has completed the descriptive analysis and is working on the multiple regression. Table

The Influence of Socioeconomic, Parental, and District Factors on the 2013 MCAS Grade 4 Language Arts and Mathematics Scores

ERIC Educational Resources Information Center

Caldwell, Dale G.

2017-01-01

This correlational, explanatory study utilized multiple linear and hierarchical regression to examine the predictive power of socioeconomic, parental and district factors on the total percentage of students who scored Proficient or Advanced Proficient on the 2013 MCAS Grade 4 language arts and mathematics test. The population for this study…

Tumble Graphs: Avoiding Misleading End Point Extrapolation When Graphing Interactions From a Moderated Multiple Regression Analysis

ERIC Educational Resources Information Center

Bodner, Todd E.

2016-01-01

This article revisits how the end points of plotted line segments should be selected when graphing interactions involving a continuous target predictor variable. Under the standard approach, end points are chosen at ±1 or 2 standard deviations from the target predictor mean. However, when the target predictor and moderator are correlated or the…

The Association between Working Memory and Educational Attainment as Measured in Different Mathematical Subtopics in the Swedish National Assessment: Primary Education

ERIC Educational Resources Information Center

Nyroos, Mikaela; Wiklund-Hornqvist, Carola

2012-01-01

The aim of this study was to examine the relationship between working memory capacity and mathematical performance measured by the national curriculum assessment in third-grade children (n = 40). The national tests concerned six subareas within mathematics. One-way ANOVA, two-tailed Pearson correlation and multiple regression analyses were…

Effects of Motivation, Academic Stress and Age in Predicting Self-Directed Learning Readiness (SDLR): Focused on Online College Students

ERIC Educational Resources Information Center

Heo, JeongChul; Han, Sumi

2018-01-01

The purpose of this study is to determine whether the self-directed learning readiness (SDLR) among online students might be significantly predicted by motivation, academic stress, and age. To complete the purpose of this study, the Pearson correlation and multiple-regression are analyzed. The participants for this study are college students who…

Cognitive and Behavioural Correlates of Non-Adherence to HIV Anti-Retroviral Therapy: Theoretical and Practical Insight for Clinical Psychology and Health Psychology

ERIC Educational Resources Information Center

Begley, Kim; McLaws, Mary-Louise; Ross, Michael W.; Gold, Julian

2008-01-01

This cross-sectional study identified variables associated with protease inhibitor (PI) non-adherence in 179 patients taking anti-retroviral therapy. Univariate analyses identified 11 variables associated with PI non-adherence. Multiple logistic regression modelling identified three predictors of PI non-adherence: low adherence self-efficacy and…

Spirituality/Religiosity, Life Satisfaction, and Life Meaning as Protective Factors for Nonsuicidal Self-Injury in College Students

ERIC Educational Resources Information Center

Kress, Victoria E.; Newgent, Rebecca A.; Whitlock, Janis; Mease, Laura

2015-01-01

The purpose of this study was to identify factors that may protect or insulate people from engaging in nonsuicidal self-injury (NSSI). College students (N = 14,385) from 8 universities participated in a web-based survey. Results of bivariate correlations and multiple regression revealed that spirituality/religiosity, life satisfaction, and life…

Female homicide in Rio Grande do Sul, Brazil.

PubMed

Leites, Gabriela Tomedi; Meneghel, Stela Nazareth; Hirakata, Vania Noemi

2014-01-01

This study aimed to assess the female homicide rate due to aggression in Rio Grande do Sul, Brazil, using this as a "proxy" of femicide. This was an ecological study which correlated the female homicide rate due to aggression in Rio Grande do Sul, according to the 35 microregions defined by the Brazilian Institute of Geography and Statistics (IBGE), with socioeconomic and demographic variables access and health indicators. Pearson's correlation test was performed with the selected variables. After this, multiple linear regressions were performed with variables with p < 0.20. The standardized average of female homicide rate due to aggression in the period from 2003 to 2007 was 3.1 obits per 100 thousand. After multiple regression analysis, the final model included male mortality due to aggression (p = 0.016), the percentage of hospital admissions for alcohol (p = 0.005) and the proportion of ill-defined deaths (p = 0.015). The model have an explanatory power of 39% (adjusted r2 = 0.391). The results are consistent with other studies and indicate a strong relationship between structural violence in society and violence against women, in addition to a higher incidence of female deaths in places with high alcohol hospitalization.

Language and hope in schizophrenia-spectrum disorders.

PubMed

Bonfils, Kelsey A; Luther, Lauren; Firmin, Ruth L; Lysaker, Paul H; Minor, Kyle S; Salyers, Michelle P

2016-11-30

Hope is integral to recovery for those with schizophrenia. Considering recent advancements in the examination of clients' lexical qualities, we were interested in how clients' words reflect hope. Using computerized lexical analysis, we examined social, emotion, and future words' relations to hope and its pathways and agency components. Forty-five clients provided detailed narratives about their life and mental illness. Transcripts were analyzed using the Linguistic Inquiry and Word Count program (LIWC), which assigns words to categories (e.g., "anxiety") based on a pre-existing dictionary. Correlations and linear multiple regression were used to examine relationships between lexical qualities and hope. Hope and its subcomponents had significant or trending bivariate correlations in expected directions with several emotion-related word categories (anger and sadness) but were not associated with expected categories such as social words, positive emotions, optimism, achievement, and future words. In linear multiple regressions, no LIWC variable significantly predicted hope agency, but anger words significantly predicted both total hope and hope pathways. Our findings indicate lexical analysis tools can be used to investigate recovery-oriented concepts such as hope, and results may inform clinical practice. Future research should aim to replicate our findings in larger samples. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

[Culture and quality of life assessment in Chinese populations].

PubMed

Xia, Ping; Li, Ning-Xiu; Liu, Chao-Jie; Lü, Yu-Bo; Zhang, Qiang; Ou, Ai-Hua

2010-07-01

To investigate the impact of cultural factors on quality of life (QOL) and to identify appropriate ways of dividing sub-populations for population norm-based quality of life assessment. The WHOQOL-BREF was used as a QOL instrument. Another questionnaire was developed to assess cultural values. A cross-sectional survey was undertaken in 1090 Guangzhou residents, which included 635 respondents from communities and 455 patients who visited outpatient departments of hospitals. Cronbach's a coefficients and item-domain correlation coefficients were calculated to test the reliability and validity of the WHOQOL-BREF, respectively. Student t test, ANOVA and stepwise multiple linear regression analysis were performed to identify the variables that might have an impact on the QOL. Two regression models with and without including cultural variables were constructed, and the extent of impact exerted by the cultural factors was assessed through a comparison of the change of adjusted R square values. A total of 1052 (96%) valid questionnaire were returned. The Cronbach's alpha coefficients of the WHOQOL-BREF ranged from 0.67 to 0.78. Age, education, occupation and family income were correlated with all of the domains of the WHOQOL-BREF. Chronic condition was correlated with physical, psychological, and social relationship domains of the WHOQOL-BREF. Gender was correlated with physical and psychological domains of the WHOQOL-BREF. The multiple regression analysis showed that social and demographic factors contributed to 6.3%, 13.6%, 10.4% and 8.7% of the predicted variances for the physical, psychological, social relationship, and environment domains, respectively. Social support, horizontal collectivism, vertical individualism, escape acceptance, fear of death, health value, supernatural belief had a significant impact on QOL. However, social support was the only one factor that had an impact on all of the four QOL domains. It is necessary to divide sub-cultural populations for population norm-based QOL assessment. Further research is needed to develop a practical approach to the sub-cultural population division.

Socio-economic factors associated with infant mortality in Italy: an ecological study

PubMed Central

2012-01-01

Introduction One issue that continues to attract the attention of public health researchers is the possible relationship in high-income countries between income, income inequality and infant mortality (IM). The aim of this study was to assess the associations between IM and major socio-economic determinants in Italy. Methods Associations between infant mortality rates in the 20 Italian regions (2006–2008) and the Gini index of income inequality, mean household income, percentage of women with at least 8 years of education, and percentage of unemployed aged 15–64 years were assessed using Pearson correlation coefficients. Univariate linear regression and multiple stepwise linear regression analyses were performed to determine the magnitude and direction of the effect of the four socio-economic variables on IM. Results The Gini index and the total unemployment rate showed a positive strong correlation with IM (r = 0.70; p < 0.001 and r = 0.84; p < 0.001 respectively), mean household income showed a strong negative correlation (r = −0.78; p < 0.001), while female educational attainment presented a weak negative correlation (r = −0.45; p < 0.05). Using a multiple stepwise linear regression model, only unemployment rate was independently associated with IM (b = 0.15, p < 0.001). Conclusions In Italy, a high-income country where health care is universally available, variations in IM were strongly associated with relative and absolute income and unemployment rate. These results suggest that in Italy IM is not only related to income distribution, as demonstrated for other developed countries, but also to economic factors such as absolute income and unemployment. In order to reduce IM and the existing inequalities, the challenge for Italian decision makers is to promote economic growth and enhance employment levels. PMID:22898293

Disability-Specific Atlases of Gray Matter Loss in Relapsing-Remitting Multiple Sclerosis.

PubMed

MacKenzie-Graham, Allan; Kurth, Florian; Itoh, Yuichiro; Wang, He-Jing; Montag, Michael J; Elashoff, Robert; Voskuhl, Rhonda R

2016-08-01

Multiple sclerosis (MS) is characterized by progressive gray matter (GM) atrophy that strongly correlates with clinical disability. However, whether localized GM atrophy correlates with specific disabilities in patients with MS remains unknown. To understand the association between localized GM atrophy and clinical disability in a biology-driven analysis of MS. In this cross-sectional study, magnetic resonance images were acquired from 133 women with relapsing-remitting MS and analyzed using voxel-based morphometry and volumetry. A regression analysis was used to determine whether voxelwise GM atrophy was associated with specific clinical deficits. Data were collected from June 28, 2007, to January 9, 2014. Voxelwise correlation of GM change with clinical outcome measures (Expanded Disability Status Scale and Multiple Sclerosis Functional Composite scores). Among the 133 female patients (mean [SD] age, 37.4 [7.5] years), worse performance on the Multiple Sclerosis Functional Composite correlated with voxelwise GM volume loss in the middle cingulate cortex (P < .001) and a cluster in the precentral gyrus bilaterally (P = .004). In addition, worse performance on the Paced Auditory Serial Addition Test correlated with volume loss in the auditory and premotor cortices (P < .001), whereas worse performance on the 9-Hole Peg Test correlated with GM volume loss in Brodmann area 44 (Broca area; P = .02). Finally, voxelwise GM loss in the right paracentral lobulus correlated with bowel and bladder disability (P = .03). Thus, deficits in specific clinical test results were directly associated with localized GM loss in clinically eloquent locations. These biology-driven data indicate that specific disabilities in MS are associated with voxelwise GM loss in distinct locations. This approach may be used to develop disability-specific biomarkers for use in future clinical trials of neuroprotective treatments in MS.

Low triiodothyronine: A new facet of inflammation in acute ischemic stroke.

PubMed

Ma, Lili; Zhu, Dongliang; Jiang, Ying; Liu, Yingying; Ma, Xiaomeng; Liu, Mei; Chen, Xiaohong

2016-07-01

Patients with acute ischemic stroke (AIS) frequently experience low free triiodothyronine (fT3) concentrations. Inflammation is recognized as a key contributor to the pathophysiology of stroke. Previous studies, however, did not simultaneously evaluate fT3 and inflammation biomarkers in AIS patients. Markers of inflammation, including serum concentrations of C-reactive protein (CRP) and albumin, and fT3 were assessed retrospectively in 117 patients. Stroke severity was measured on the National Institutes of Health Stroke Scale (NIHSS). Regression analyses were performed to adjust for confounders. Serum fT3 concentrations were significantly lower in moderate AIS patients than those in mild AIS patients (P<0.001). fT3 concentration also positively correlated with serum albumin concentration (r=0.358, P<0.001) and negatively correlated with log10CRP concentration (r=-0.341, P<0.001), NIHSS score (r=-0.384, P<0.001). Multiple regression analysis showed that CRP, albumin concentrations and NIHSS score were independently correlated with fT3 concentration. Binary logistic regression analysis showed that fT3 concentration was an independent factor correlated with NIHSS score, the area under the receiver operating characteristic curve was 0.712 (95% CI, 0.618-0.805). Low fT3 concentrations may be involved in the pathogenic pathway linking inflammation to stroke severity in AIS patients. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling the energy content of combustible ship-scrapping waste at Alang-Sosiya, India, using multiple regression analysis.

PubMed

Reddy, M Srinivasa; Basha, Shaik; Joshi, H V; Sravan Kumar, V G; Jha, B; Ghosh, P K

2005-01-01

Alang-Sosiya is the largest ship-scrapping yard in the world, established in 1982. Every year an average of 171 ships having a mean weight of 2.10 x 10(6)(+/-7.82 x 10(5)) of light dead weight tonnage (LDT) being scrapped. Apart from scrapped metals, this yard generates a massive amount of combustible solid waste in the form of waste wood, plastic, insulation material, paper, glass wool, thermocol pieces (polyurethane foam material), sponge, oiled rope, cotton waste, rubber, etc. In this study multiple regression analysis was used to develop predictive models for energy content of combustible ship-scrapping solid wastes. The scope of work comprised qualitative and quantitative estimation of solid waste samples and performing a sequential selection procedure for isolating variables. Three regression models were developed to correlate the energy content (net calorific values (LHV)) with variables derived from material composition, proximate and ultimate analyses. The performance of these models for this particular waste complies well with the equations developed by other researchers (Dulong, Steuer, Scheurer-Kestner and Bento's) for estimating energy content of municipal solid waste.

Anodic microbial community diversity as a predictor of the power output of microbial fuel cells.

PubMed

Stratford, James P; Beecroft, Nelli J; Slade, Robert C T; Grüning, André; Avignone-Rossa, Claudio

2014-03-01

The relationship between the diversity of mixed-species microbial consortia and their electrogenic potential in the anodes of microbial fuel cells was examined using different diversity measures as predictors. Identical microbial fuel cells were sampled at multiple time-points. Biofilm and suspension communities were analysed by denaturing gradient gel electrophoresis to calculate the number and relative abundance of species. Shannon and Simpson indices and richness were examined for association with power using bivariate and multiple linear regression, with biofilm DNA as an additional variable. In simple bivariate regressions, the correlation of Shannon diversity of the biofilm and power is stronger (r=0.65, p=0.001) than between power and richness (r=0.39, p=0.076), or between power and the Simpson index (r=0.5, p=0.018). Using Shannon diversity and biofilm DNA as predictors of power, a regression model can be constructed (r=0.73, p<0.001). Ecological parameters such as the Shannon index are predictive of the electrogenic potential of microbial communities. Copyright © 2014 Elsevier Ltd. All rights reserved.

[Impact of air pollution in paediatric consultations in Primary Health Care: Ecological study].

PubMed

Martín Martín, Raquel; Sánchez Bayle, Marciano

2017-08-09

To study the correlation between the levels of environmental pollutants and the number of paediatric consultations related to respiratory disease in Primary Health Care. An ecological study is performed, in which the dependent variable analysed was the number of paediatric consultations in an urban Primary Health Care centre in Madrid over a 3 year period (2013-2015), and specifically the consultations related to bronchiolitis, recurrent bronchospasm, and upper respiratory diseases. The independent variables analysed were the levels of environmental pollutants. Coefficients of correlation and multiple lineal regressions were calculated. An analysis has been carried out comparing the average of paediatric consultations when the levels of nitrogen dioxide (NO 2 ) were higher and lower than 40μg/m 3. RESULTS: During the period of the study, there were a total of 52,322 paediatric consultations in the health centre, of which 6,473 (12.37%) were related to respiratory diseases. A positive correlation was found between SO 2 , CO, NOx and NO 2 and benzene levels and paediatric consultations related to respiratory diseases, and a negative correlation with temperature. The number of consultations was significantly higher when NO 2 levels exceeded 40μg/m 3 . In the multiple lineal regression (P=.0001), the correlation was only positive between consultations and NO 2 levels (3.630, 95% CI: 0.691-6.570), and negative with temperature (-5,957, 95% CI: -8.665 to -3.248). NO 2 environmental pollution is related to an increase in respiratory diseases in children. Paediatricians should contribute to promote an improvement in urban air quality as a significant preventive measure. Copyright © 2017. Publicado por Elsevier España, S.L.U.

Digit ratio (2D:4D), testosterone, cortisol, aggression, personality and hand-grip strength: Evidence for prenatal effects on strength.

PubMed

Ribeiro, Evaldo; Neave, Nick; Morais, Rosana Nogueiro; Kilduff, Liam; Taylor, Suzan R; Butovskaya, Marina; Fink, Bernhard; Manning, John T

2016-09-01

Digit ratio (2D:4D) is a putative marker for prenatal testosterone and is correlated with performance in many sports. Low 2D:4D has been linked to strength but the evidence is mixed and strength is also influenced by mass, testosterone, and behavioural factors. It has been hypothesised that the 2D:4D-strength correlation may be strongest in challenge conditions when short-term changes occur in steroid hormones. We tested this suggestion in men. We used a cross-over study design with a challenge (an aggressive video of rugby tackles) and control (a blank screen) condition. 89 healthy men. Finger lengths (2nd and 4th for both hands), hand-grip strength (HGS), testosterone (T), cortisol (C), aggression (Buss-Perry Aggression Questionnaire) and personality type (Ten Item Personality Measure). In both conditions participants provided saliva samples (for hormone assays). In the challenge condition there was a highly significant increase in HGS, and modest changes in T, physical aggression and emotional stability. HGS correlated negatively with left hand 2D:4D. In a multiple regression, left hand 2D:4D was negatively related to HGS and emotional stability was positively related to HGS. In the control condition HGS was not correlated with 2D:4D. In a multiple regression, BMI, physical aggression, and emotional stability were significantly related to HGS. 2D:4D is a negative correlate of strength in challenge situations. This finding may in part explain associations between 2D:4D and sports performance. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Pain in patients with transverse myelitis and its relationship to aquaporin 4 antibody status.

PubMed

Kong, Yazhuo; Okoruwa, Helen; Revis, Jon; Tackley, George; Leite, Maria Isabel; Lee, Michael; Tracey, Irene; Palace, Jacqueline

2016-09-15

Pain in transverse myelitis has been poorly studied. The aim of the study was to investigate the relationship between transverse myelitis related pain and disability, quality of life, anxiety and depression, cognitive-affective states in neuromyelitis optica (NMO) patients and aquaporin4 antibody status (AQP4-Ab +ve as positive and AQP4-Ab -ve as negative). Transverse myelitis patients (44 in total; 29 AQP4-Ab +ve and 15 AQP4-Ab -ve) completed questionnaires including Pain Severity Index (PSI), Pain Catastrophising Scale (PCS), Hospital Anxiety and Depression Scale (HADS), Short Form-36 quality of life (SF-36 QOL). Clinical details such as disability, gender, age and spinal cord lesion type (short or long lesion) were noted. Correlation and multiple linear regression tests were performed using these clinical scores. Pain was found to be correlated strongly with quality of life in both groups but only correlated with disability in the AQP4-Ab +ve group. PCS, HADS and EDMUS were found to be highly correlated with pain severity using partial correlation, however, a stronger relationship between pain severity and PCS was found in the AQP4-Ab -ve group. Multiple regression analysis showed that pain severity was the most important factor for quality of life but not disability or anxiety and depression symptoms in the whole patient group. We confirm that pain is an important symptom of transverse myelitis and has more influence on quality of life than disability despite health services being predominantly focused on the latter. There may be different factors associated with pain between AQP4-Ab +ve and -ve patients. Copyright © 2016 Elsevier B.V. All rights reserved.

Serum Albumin and Disease Severity of Non-Cystic Fibrosis Bronchiectasis.

PubMed

Lee, Seung Jun; Kim, Hyo-Jung; Kim, Ju-Young; Ju, Sunmi; Lim, Sujin; Yoo, Jung Wan; Nam, Sung-Jin; Lee, Gi Dong; Cho, Hyun Seop; Kim, Rock Bum; Cho, Yu Ji; Jeong, Yi Yeong; Kim, Ho Cheol; Lee, Jong Deog

2017-08-01

A clinical classification system has been developed to define the severity and predict the prognosis of subjects with non-cystic fibrosis (CF) bronchiectasis. We aimed to identify laboratory parameters that are correlated with the bronchiectasis severity index (BSI) and FACED score. The medical records of 107 subjects with non-CF bronchiectasis for whom BSI and FACED scores could be calculated were retrospectively reviewed. The correlations between the laboratory parameters and BSI or FACED score were assessed, and multiple-linear regression analysis was performed to identify variables independently associated with BSI and FACED score. An additional subgroup analysis was performed according to sex. Among all of the enrolled subjects, 49 (45.8%) were male and 58 (54.2%) were female. The mean BSI and FACED scores were 9.43 ± 3.81 and 1.92 ± 1.59, respectively. The serum albumin level (r = -0.49), bilirubin level (r = -0.31), C-reactive protein level (r = 0.22), hemoglobin level (r = -0.2), and platelet/lymphocyte ratio (r = 0.31) were significantly correlated with BSI. Meanwhile, serum albumin (r = -0.37) and bilirubin level (r = -0.25) showed a significant correlation with the FACED score. Multiple-linear regression analysis showed that the serum bilirubin level was independently associated with BSI, and the serum albumin level was independently associated with both scoring systems. Subgroup analysis revealed that the level of uric acid was also a significant variable independently associated with the BSI in male bronchiectasis subjects. Several laboratory variables were identified as possible prognostic factors for non-CF bronchiectasis. Among them, the serum albumin level exhibited the strongest correlation and was identified as an independent variable associated with the BSI and FACED scores. Copyright © 2017 by Daedalus Enterprises.

Bibliometric Analysis of Manuscript Characteristics That Influence Citations: A Comparison of Six Major Radiology Journals.

PubMed

Shekhani, Haris Naseem; Shariff, Shoaib; Bhulani, Nizar; Khosa, Faisal; Hanna, Tarek Noel

2017-12-01

The objective of our study was to investigate radiology manuscript characteristics that influence citation rate, capturing features of manuscript construction that are discrete from study design. Consecutive articles published from January 2004 to June 2004 were collected from the six major radiology journals with the highest impact factors: Radiology (impact factor, 5.076), Investigative Radiology (2.320), American Journal of Neuroradiology (AJNR) (2.384), RadioGraphics (2.494), European Radiology (2.364), and American Journal of Roentgenology (2.406). The citation count for these articles was retrieved from the Web of Science, and 29 article characteristics were tabulated manually. A point-biserial correlation, Spearman rank-order correlation, and multiple regression model were performed to predict citation number from the collected variables. A total of 703 articles-211 published in Radiology, 48 in Investigative Radiology, 106 in AJNR, 52 in RadioGraphics, 129 in European Radiology, and 157 in AJR-were evaluated. Punctuation was included in the title in 55% of the articles and had the highest statistically significant positive correlation to citation rate (point-biserial correlation coefficient [r pb ] = 0.85, p < 0.05). Open access status provided a low-magnitude, but significant, correlation to citation rate (r pb = 0.140, p < 0.001). The following variables created a significant multiple regression model to predict citation count (p < 0.005, R 2 = 0.186): study findings in the title, abstract word count, abstract character count, total number of words, country of origin, and all authors in the field of radiology. Using bibliometric knowledge, authors can craft a title, abstract, and text that may enhance visibility and citation count over what they would otherwise experience.

Early pregnancy fasting plasma glucose and lipid concentrations in pregnancy and association to offspring size: a retrospective cohort study.

PubMed

Liu, Bin; Geng, Huizhen; Yang, Juan; Zhang, Ying; Deng, Langhui; Chen, Weiqing; Wang, Zilian

2016-03-17

Hyperlipidemia and high fasting plasma glucose levels at the first prenatal visit (First Visit FPG) are both related to gestational diabetes mellitus, maternal obesity/overweight and fetal overgrowth. The purpose of the present study is to investigate the correlation between First Visit FPG and lipid concentrations, and their potential association with offspring size at delivery. Pregnant women that received regular prenatal care and delivered in our center in 2013 were recruited for the study. Fasting plasma glucose levels were tested at the first prenatal visit (First Visit FPG) and prior to delivery (Before Delivery FPG). HbA1c and lipid profiles were examined at the time of OGTT test. Maternal and neonatal clinical data were collected for analysis. Data was analyzed by independent sample t test, Pearson correlation, and Chi-square test, followed by partial correlation and multiple linear regression analyses to confirm association. Statistical significance level was α =0.05. Analyses were based on 1546 mother-baby pairs. First Visit FPG was not correlated with any lipid parameters after adjusting for maternal pregravid BMI, maternal age and gestational age at First Visit FPG. HbA1c was positively correlated with triglyceride and Apolipoprotein B in the whole cohort and in the NGT group after adjusting for maternal age and maternal BMI at OGTT test. Multiple linear regression analyses showed neonatal birth weight, head circumference and shoulder circumference were all associated with First Visit FPG and triglyceride levels. Fasting plasma glucose at first prenatal visit is not associated with lipid concentrations in mid-pregnancy, but may influence fetal growth together with triglyceride concentration.

Meteorological adjustment of yearly mean values for air pollutant concentration comparison

NASA Technical Reports Server (NTRS)

Sidik, S. M.; Neustadter, H. E.

1976-01-01

Using multiple linear regression analysis, models which estimate mean concentrations of Total Suspended Particulate (TSP), sulfur dioxide, and nitrogen dioxide as a function of several meteorologic variables, two rough economic indicators, and a simple trend in time are studied. Meteorologic data were obtained and do not include inversion heights. The goodness of fit of the estimated models is partially reflected by the squared coefficient of multiple correlation which indicates that, at the various sampling stations, the models accounted for about 23 to 47 percent of the total variance of the observed TSP concentrations. If the resulting model equations are used in place of simple overall means of the observed concentrations, there is about a 20 percent improvement in either: (1) predicting mean concentrations for specified meteorological conditions; or (2) adjusting successive yearly averages to allow for comparisons devoid of meteorological effects. An application to source identification is presented using regression coefficients of wind velocity predictor variables.

[Trend in mortality from external causes in pregnant and postpartum women and its relationship to socioeconomic factors in Colombia, 1998-2010].

PubMed

Salazar, Edwin; Buitrago, Carolina; Molina, Federico; Alzate, Catalina Arango

2015-05-01

Determine the trend in mortality from external causes in pregnant and postpartum women and its relationship to socioeconomic factors. Descriptive study, based on the official registries of deaths reported by the National Statistics Agency, 1998-2010. The trend was analyzed using Poisson regressions. Bivariate correlations and multiple linear regression models were constructed to explore the relationship between mortality and socioeconomic factors: human development index, Gini index, gross domestic product, unsatisfied basic needs, unemployment rate, poverty, extreme poverty, quality of life index, illiteracy rate, and percentage of affiliation to the Social Security System. A total of 2 223 female deaths from external causes were recorded, of which 1 429 occurred during pregnancy and 794 in the postpartum period. The gross mortality rate dropped from 30.7 per 100 000 live births plus fetal deaths in 1998 to 16.7 in 2010. A downward curve with no significant inflection points was shown in the risk of dying from this cause. The multiple linear regression model showed a correlation between mortality and extreme poverty and the illiteracy rate, suggesting that these indicators could explain 89.4% of the change in mortality from external causes in pregnant and postpartum women each year in Colombia. Mortality from external causes in pregnant and postpartum women showed a significant downward trend that may be explained by important socioeconomic changes in the country, including a decrease in extreme poverty and in the illiteracy rate.

Maximal bite force, facial morphology and sucking habits in young children with functional posterior crossbite.

PubMed

Castelo, Paula Midori; Gavião, Maria Beatriz Duarte; Pereira, Luciano José; Bonjardim, Leonardo Rigoldi

2010-01-01

The maintenance of normal conditions of the masticatory function is determinant for the correct growth and development of its structures. Thus, the aims of this study were to evaluate the influence of sucking habits on the presence of crossbite and its relationship with maximal bite force, facial morphology and body variables in 67 children of both genders (3.5-7 years) with primary or early mixed dentition. The children were divided in four groups: primary-normocclusion (PN, n=19), primary-crossbite (PC, n=19), mixed-normocclusion (MN, n=13), and mixed-crossbite (MC, n=16). Bite force was measured with a pressurized tube, and facial morphology was determined by standardized frontal photographs: AFH (anterior face height) and BFW (bizygomatic facial width). It was observed that MC group showed lower bite force than MN, and AFH/BFW was significantly smaller in PN than PC (t-test). Weight and height were only significantly correlated with bite force in PC group (Pearson's correlation test). In the primary dentition, AFH/BFW and breast-feeding (at least six months) were positive and negatively associated with crossbite, respectively (multiple logistic regression). In the mixed dentition, breast-feeding and bite force showed negative associations with crossbite (univariate regression), while nonnutritive sucking (up to 3 years) associated significantly with crossbite in all groups (multiple logistic regression). In the studied sample, sucking habits played an important role in the etiology of crossbite, which was associated with lower bite force and long-face tendency.

Increased risk of kidney damage among Chinese adults with simple renal cyst.

PubMed

Kong, Xianglei; Ma, Xiaojing; Zhang, Chengyin; Su, Hong; Gong, Xiaojie; Xu, Dongmei

2018-05-04

The presence of simple renal cyst (SRC) has been related to hypertension, the early and long-term allograft function, and aortic disease, but the relationship with kidney damage was still controversial. Accordingly, we conducted a large sample cross-sectional study to explore the association of SRC with indicators of kidney damage among Chinese adults. A total of 42,369 adults (aged 45.8 ± 13.67 years, 70.6% males) who visited the Health Checkup Clinic were consecutively enrolled. SRC was assessed by ultrasonography according to Bosniak category. Multiple regression models were applied to explore the relationships between SRC and indicators of kidney damage [proteinuria (dipstick urine protein ≥ 1+) and decreased estimated glomerular filtration rate (DeGFR) < 60 ml/min/1.73 m 2 ]. Among all participants in the study, the prevalence of SRC was 10.5%. As a categorical outcome, participants with more 1 cyst and with 1 cyst had higher percentage of proteinuria [53 (5.3%) and 93 (2.7%) vs. 596 (1.6%), p < 0.001] and DeGFR [57 (5.7%) and 85 (2.5%) vs. 278 (0.7%), p < 0.001] compared with participants with no cyst. SRC significantly correlated with proteinuria [OR 1.59 (95% CI 1.30-1.95)] and DeGFR [OR 1.97 (95% CI 1.56-2.47)] after adjusting for potential confounders. Furthermore, the results also demonstrated that maximum diameter (per 1 cm increase), bilateral location, and multiple cysts significantly correlated with DeGFR in the multiple logistic regression analysis. The study revealed that SRC significantly correlated with kidney damage and special attention should be paid among Chinese adults with SRC.

Quality of life among people with multiple sclerosis: Replication of a three-factor prediction model.

PubMed

Bishop, Malachy; Rumrill, Phillip D; Roessler, Richard T

2015-01-01

This article presents a replication of Rumrill, Roessler, and Fitzgerald's 2004 analysis of a three-factor model of the impact of multiple sclerosis (MS) on quality of life (QOL). The three factors in the original model included illness-related, employment-related, and psychosocial adjustment factors. To test hypothesized relationships between QOL and illness-related, employment-related, and psychosocial variables using data from a survey of the employment concerns of Americans with MS (N = 1,839). An ex post facto, multiple correlational design was employed incorporating correlational and multiple regression analyses. QOL was positively related to educational level, employment status, job satisfaction, and job-match, and negatively related to number of symptoms, severity of symptoms, and perceived stress level. The three-factor model explained approximately 37 percent of the variance in QOL scores. The results of this replication confirm the continuing value of the three-factor model for predicting the QOL of adults with MS, and demonstrate the importance of medical, mental health, and vocational rehabilitation interventions and services in promoting QOL.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies

PubMed Central

Koerner, Tess K.; Zhang, Yang

2017-01-01

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers. PMID:28264422

[A Correlational Study of the Recovery Process in Patients With Mental Illness].

PubMed

Huang, Yao-Hui; Lin, Yao-Yu; Lee, Shih-Kai; Lee, Ming-Feng; Lin, Ching-Lan Esther

2018-04-01

The ideology of recovery addresses the autonomy of patients with mental illness and their ability to reconstruct a normal life. Empirical knowledge of this process of recovery and related factors remains unclear. To assess the process of recovery and related factors in patients with mental illness. This cross-sectional, correlational study was conducted on a convenience sample in a psychiatric hospital. Two-hundred and fifty patients with mental illness were recruited and were assessed using 3 instruments: Questionnaire about the Process of Recovery (QPR), Perceived Psychiatric Stigma Scale (PPSS), and Personal and Social Performance Scale (PSP). Data were analyzed using descriptive statistics, χ 2 , analysis of variance, and multiple linear regression analysis. Most of the participants were male, middle-aged, unmarried, educated to the senior high school level, employed, receiving home-care treatment, and diagnosed with schizophrenia. Those who were unemployed, living in a community rehabilitative house, and living in the community, respectively, earned relatively higher recovery scores (p < .05). The total scores of QPR and the 3 subscales were negatively correlated with PPSS (p < .01) and positively correlated with PSPS (p < .01; p < .05). Multiple regression analysis indicated that the factors of education, employment, having received community rehabilitative models, and stigma, respectively, significantly explained the recovery capacity of patients with mental illness. Community psychiatric nurses should provide care to help employed patients adapt to stresses in the workplace, strengthen their stigma-coping strategies, and promote public awareness of mental health issues by increasing public knowledge and acceptance of mental illness in order to minimize patient-perceived stigma and facilitate their recovery.

Relationships Between Meibomian Gland Loss and Age, Sex, and Dry Eye.

PubMed

Pult, Heiko

2018-02-12

This study evaluated relationships between meibomian gland loss (MGL) and age, sex, and dry eye. Dry eye and MGL of the lower eyelid was evaluated from 112 randomly selected subjects (66 women; mean age 62.8; SD ±15.7; and age range: 19-89 years) from Horst Riede GmbH, Weinheim, Germany. In addition, subjects were grouped into dry eye and non-dry eye by the Ocular Surface Disease Index (OSDI) score, lid-parallel conjunctival folds and non-invasive break-up time. Symptoms were evaluated by the OSDI. Meibography of the lower eyelid was performed using a Cobra camera (bon Optic, Lübeck, Germany), and images were analyzed by its digital grading tool. Data were analyzed by backward, multiple regression analyses and Pearson correlation. Analyzing all subjects, multiple regression analyses detected that age and dry eye status (dry eye diagnosis or OSDI) but not sex were significantly related to MGL. In both, non-dry eye (n=66) and dry eye subjects (n=46), dry eye status (OSDI) but not age or sex was significantly related to MGL. Ocular Surface Disease Index scores were significantly correlated with MGL, but this correlation was stronger among all subjects (Pearson correlation; r=0.536, P<0.001) and dry eye group subjects (r=0.520, P<0.001) than in non-dry eye group subjects (r=0.275, P=0.014). Dry eye group subjects showed significantly increased MGL of the lower eyelid. Age and dry eye status were related to MGL of the lower eyelid, but sex was not; dry eye status was the dominant factor.

Climate change but not unemployment explains the changing suicidality in Thessaloniki Greece (2000-2012).

PubMed

Fountoulakis, Konstantinos N; Savopoulos, Christos; Zannis, Prodromos; Apostolopoulou, Martha; Fountoukidis, Ilias; Kakaletsis, Nikolaos; Kanellos, Ilias; Dimellis, Dimos; Hyphantis, Thomas; Tsikerdekis, Athanasios; Pompili, Maurizio; Hatzitolios, Apostolos I

2016-03-15

Recently there was a debate concerning the etiology behind attempts and completed suicides. The aim of the current study was to search for possible correlations between the rates of attempted and completed suicide and climate variables and regional unemployment per year in the county of Thessaloniki, Macedonia, northern Greece, for the years 2000-12. The regional rates of suicide and attempted suicide as well as regional unemployment were available from previous publications of the authors. The climate variables were calculated from the daily E-OBS gridded dataset which is based on observational data Only the male suicide rates correlate significantly with high mean annual temperature but not with unemployment. The multiple linear regression analysis results suggest that temperature is the only variable that determines male suicides and explains 51% of their variance. Unemployment fails to contribute significantly to the model. There seems to be a seasonal distribution for attempts with mean rates being higher for the period from May to October and the rates clearly correlate with temperature. The highest mean rates were observed during May and August and the lowest during December and February. Multiple linear regression analysis suggests that temperature also determines the female attempts rate although the explained variable is significant but very low (3-5%) Climate variables and specifically high temperature correlate both with suicide and attempted suicide rates but with a different way between males and females. The climate effect was stronger than the effect of unemployment. Copyright © 2016 Elsevier B.V. All rights reserved.

Estimation of lung tumor position from multiple anatomical features on 4D-CT using multiple regression analysis.

PubMed

Ono, Tomohiro; Nakamura, Mitsuhiro; Hirose, Yoshinori; Kitsuda, Kenji; Ono, Yuka; Ishigaki, Takashi; Hiraoka, Masahiro

2017-09-01

To estimate the lung tumor position from multiple anatomical features on four-dimensional computed tomography (4D-CT) data sets using single regression analysis (SRA) and multiple regression analysis (MRA) approach and evaluate an impact of the approach on internal target volume (ITV) for stereotactic body radiotherapy (SBRT) of the lung. Eleven consecutive lung cancer patients (12 cases) underwent 4D-CT scanning. The three-dimensional (3D) lung tumor motion exceeded 5 mm. The 3D tumor position and anatomical features, including lung volume, diaphragm, abdominal wall, and chest wall positions, were measured on 4D-CT images. The tumor position was estimated by SRA using each anatomical feature and MRA using all anatomical features. The difference between the actual and estimated tumor positions was defined as the root-mean-square error (RMSE). A standard partial regression coefficient for the MRA was evaluated. The 3D lung tumor position showed a high correlation with the lung volume (R = 0.92 ± 0.10). Additionally, ITVs derived from SRA and MRA approaches were compared with ITV derived from contouring gross tumor volumes on all 10 phases of the 4D-CT (conventional ITV). The RMSE of the SRA was within 3.7 mm in all directions. Also, the RMSE of the MRA was within 1.6 mm in all directions. The standard partial regression coefficient for the lung volume was the largest and had the most influence on the estimated tumor position. Compared with conventional ITV, average percentage decrease of ITV were 31.9% and 38.3% using SRA and MRA approaches, respectively. The estimation accuracy of lung tumor position was improved by the MRA approach, which provided smaller ITV than conventional ITV. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Uterine Fibroids: Correlation of T2 Signal Intensity with Semiquantitative Perfusion MR Parameters in Patients Screened for MR-guided High-Intensity Focused Ultrasound Ablation.

PubMed

Kim, Young-Sun; Lee, Jeong-Won; Choi, Chel Hun; Kim, Byoung-Gie; Bae, Duk-Soo; Rhim, Hyunchul; Lim, Hyo Keun

2016-03-01

To evaluate the relationships between T2 signal intensity and semiquantitative perfusion magnetic resonance (MR) parameters of uterine fibroids in patients who were screened for MR-guided high-intensity focused ultrasound (HIFU) ablation. Institutional review board approval was granted, and informed consents were waived. One hundred seventy most symptom-relevant, nondegenerated uterine fibroids (mean diameter, 7.3 cm; range, 3.0-17.2 cm) in 170 women (mean age, 43.5 years; range, 24-56 years) undergoing screening MR examinations for MR-guided HIFU ablation from October 2009 to April 2014 were retrospectively analyzed. Fibroid signal intensity was assessed as the ratio of the fibroid T2 signal intensity to that of skeletal muscle. Parameters of semiquantitative perfusion MR imaging obtained during screening MR examination (peak enhancement, percentage of relative peak enhancement, time to peak [in seconds], wash-in rate [per seconds], and washout rate [per seconds]) were investigated to assess their relationships with T2 signal ratio by using multiple linear regression analysis. Correlations between T2 signal intensity and independently significant perfusion parameters were then evaluated according to fibroid type by using Spearman correlation test. Multiple linear regression analysis revealed that relative peak enhancement showed an independently significant correlation with T2 signal ratio (Β = 0.004, P < .001). Submucosal intracavitary (n = 20, ρ = 0.275, P = .240) and type III (n = 18, ρ = 0.082, P = .748) fibroids failed to show significant correlations between perfusion and T2 signal intensity, while significant correlations were found for all other fibroid types (ρ = 0.411-0.629, P < .05). In possible candidates for MR-guided HIFU ablation, the T2 signal intensity of nondegenerated uterine fibroids showed an independently significant positive correlation with relative peak enhancement in most cases, except those of submucosal intracavitary or type III fibroids.

Preoperative Biometric Parameters Predict the Vault after ICL Implantation: A Retrospective Clinical Study.

PubMed

Zheng, Qian-Yin; Xu, Wen; Liang, Guan-Lu; Wu, Jing; Shi, Jun-Ting

2016-01-01

To investigate the correlation between the preoperative biometric parameters of the anterior segment and the vault after implantable Collamer lens (ICL) implantation via this retrospective study. Retrospective clinical study. A total of 78 eyes from 41 patients who underwent ICL implantation surgery were included in this study. Preoperative biometric parameters, including white-to-white (WTW) diameter, central corneal thickness, keratometer, pupil diameter, anterior chamber depth, sulcus-to-sulcus diameter, anterior chamber area (ACA) and central curvature radius of the anterior surface of the lens (Lenscur), were measured. Lenscur and ACA were measured with Rhinoceros 5.0 software on the image scanned with ultrasound biomicroscopy (UBM). The vault was assessed by UBM 3 months after surgery. Multiple stepwise regression analysis was employed to identify the variables that were correlated with the vault. The results showed that the vault was correlated with 3 variables: ACA (22.4 ± 4.25 mm2), WTW (11.36 ± 0.29 mm) and Lenscur (9.15 ± 1.21 mm). The regressive equation was: vault (mm) = 1.785 + 0.017 × ACA + 0.051 × Lenscur - 0.203 × WTW. Biometric parameters of the anterior segment (ACA, WTW and Lenscur) can predict the vault after ICL implantation using a new regression equation. © 2016 The Author(s) Published by S. Karger AG, Basel.

Causal correlation of foliar biochemical concentrations with AVIRIS spectra using forced entry linear regression

NASA Technical Reports Server (NTRS)

Dawson, Terence P.; Curran, Paul J.; Kupiec, John A.

1995-01-01

A major goal of airborne imaging spectrometry is to estimate the biochemical composition of vegetation canopies from reflectance spectra. Remotely-sensed estimates of foliar biochemical concentrations of forests would provide valuable indicators of ecosystem function at regional and eventually global scales. Empirical research has shown a relationship exists between the amount of radiation reflected from absorption features and the concentration of given biochemicals in leaves and canopies (Matson et al., 1994, Johnson et al., 1994). A technique commonly used to determine which wavelengths have the strongest correlation with the biochemical of interest is unguided (stepwise) multiple regression. Wavelengths are entered into a multivariate regression equation, in their order of importance, each contributing to the reduction of the variance in the measured biochemical concentration. A significant problem with the use of stepwise regression for determining the correlation between biochemical concentration and spectra is that of 'overfitting' as there are significantly more wavebands than biochemical measurements. This could result in the selection of wavebands which may be more accurately attributable to noise or canopy effects. In addition, there is a real problem of collinearity in that the individual biochemical concentrations may covary. A strong correlation between the reflectance at a given wavelength and the concentration of a biochemical of interest, therefore, may be due to the effect of another biochemical which is closely related. Furthermore, it is not always possible to account for potentially suitable waveband omissions in the stepwise selection procedure. This concern about the suitability of stepwise regression has been identified and acknowledged in a number of recent studies (Wessman et al., 1988, Curran, 1989, Curran et al., 1992, Peterson and Hubbard, 1992, Martine and Aber, 1994, Kupiec, 1994). These studies have pointed to the lack of a physical link between wavelengths chosen by stepwise regression and the biochemical of interest, and this in turn has cast doubts on the use of imaging spectrometry for the estimation of foliar biochemical concentrations at sites distant from the training sites. To investigate this problem, an analysis was conducted on the variation in canopy biochemical concentrations and reflectance spectra using forced entry linear regression.

Modified Regression Correlation Coefficient for Poisson Regression Model

NASA Astrophysics Data System (ADS)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

Analysis on the Correlation of Traffic Flow in Hainan Province Based on Baidu Search

NASA Astrophysics Data System (ADS)

Chen, Caixia; Shi, Chun

2018-03-01

Internet search data records user’s search attention and consumer demand, providing necessary database for the Hainan traffic flow model. Based on Baidu Index, with Hainan traffic flow as example, this paper conduct both qualitative and quantitative analysis on the relationship between search keyword from Baidu Index and actual Hainan tourist traffic flow, and build multiple regression model by SPSS.

Factors Influencing the Completion of the GED in a Federal Correctional Setting a Multiple Regression Correlation-Predictive Study

ERIC Educational Resources Information Center

Akers, Kimberly

2013-01-01

Correctional education's primary goal is to reduce recidivism and increase employment among ex-offenders. The Bureau of Prison's practical goal in its mandatory GED program is to maximize the number of inmates obtaining the GED in a given time period. The purpose of this research is to model the number of instructional hours an inmate requires to…

Prediction of kinase-inhibitor binding affinity using energetic parameters

PubMed Central

Usha, Singaravelu; Selvaraj, Samuel

2016-01-01

The combination of physicochemical properties and energetic parameters derived from protein-ligand complexes play a vital role in determining the biological activity of a molecule. In the present work, protein-ligand interaction energy along with logP values was used to predict the experimental log (IC50) values of 25 different kinase-inhibitors using multiple regressions which gave a correlation coefficient of 0.93. The regression equation obtained was tested on 93 kinase-inhibitor complexes and an average deviation of 0.92 from the experimental log IC50 values was shown. The same set of descriptors was used to predict binding affinities for a test set of five individual kinase families, with correlation values > 0.9. We show that the protein-ligand interaction energies and partition coefficient values form the major deterministic factors for binding affinity of the ligand for its receptor. PMID:28149052

Three-parameter modeling of the soil sorption of acetanilide and triazine herbicide derivatives.

PubMed

Freitas, Mirlaine R; Matias, Stella V B G; Macedo, Renato L G; Freitas, Matheus P; Venturin, Nelson

2014-02-01

Herbicides have widely variable toxicity and many of them are persistent soil contaminants. Acetanilide and triazine family of herbicides have widespread use, but increasing interest for the development of new herbicides has been rising to increase their effectiveness and to diminish environmental hazard. The environmental risk of new herbicides can be accessed by estimating their soil sorption (logKoc), which is usually correlated to the octanol/water partition coefficient (logKow). However, earlier findings have shown that this correlation is not valid for some acetanilide and triazine herbicides. Thus, easily accessible quantitative structure-property relationship models are required to predict logKoc of analogues of the these compounds. Octanol/water partition coefficient, molecular weight and volume were calculated and then regressed against logKoc for two series of acetanilide and triazine herbicides using multiple linear regression, resulting in predictive and validated models.

Self-Regulatory Strategies as Correlates of Physical Activity Behavior in Persons With Multiple Sclerosis.

PubMed

Cederberg, Katie L; Balto, Julia M; Motl, Robert W

2018-05-01

To examine self-regulation strategies as correlates of physical activity in persons with multiple sclerosis (MS). Cross-sectional, or survey, study. University-based research laboratory. Convenience sample of persons with MS (N=68). Not applicable. Exercise Self-Efficacy Scale (EXSE), 12-item Physical Activity Self-Regulation Scale (PASR-12), and Godin Leisure-Time Exercise Questionnaire (GLTEQ). Correlation analyses indicated that GLTEQ scores were positively and significantly associated with overall self-regulation (r=.43), self-monitoring (r=.45), goal-setting (r=.27), reinforcement (r=.30), time management (r=.41), and relapse prevention (r=.53) PASR-12 scores. Regression analyses indicated that relapse prevention (B=5.01; SE B=1.74; β=.51) and self-monitoring (B=3.65; SE B=1.71; β=.33) were unique predictors of physical activity behavior, and relapse prevention demonstrated a significant association with physical activity behavior that was accounted for by EXSE. Our results indicate that self-regulatory strategies, particularly relapse prevention, may be important correlates of physical activity behavior that can inform the design of future behavioral interventions in MS. Published by Elsevier Inc.

An integrated, ethically driven environmental model of clinical decision making in emergency settings.

PubMed

Wolf, Lisa

2013-02-01

To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.

Evaluation of regression-based 3-D shoulder rhythms.

PubMed

Xu, Xu; Dickerson, Clark R; Lin, Jia-Hua; McGorry, Raymond W

2016-08-01

The movements of the humerus, the clavicle, and the scapula are not completely independent. The coupled pattern of movement of these bones is called the shoulder rhythm. To date, multiple studies have focused on providing regression-based 3-D shoulder rhythms, in which the orientations of the clavicle and the scapula are estimated by the orientation of the humerus. In this study, six existing regression-based shoulder rhythms were evaluated by an independent dataset in terms of their predictability. The datasets include the measured orientations of the humerus, the clavicle, and the scapula of 14 participants over 118 different upper arm postures. The predicted orientations of the clavicle and the scapula were derived from applying those regression-based shoulder rhythms to the humerus orientation. The results indicated that none of those regression-based shoulder rhythms provides consistently more accurate results than the others. For all the joint angles and all the shoulder rhythms, the RMSE are all greater than 5°. Among those shoulder rhythms, the scapula lateral/medial rotation has the strongest correlation between the predicted and the measured angles, while the other thoracoclavicular and thoracoscapular bone orientation angles only showed a weak to moderate correlation. Since the regression-based shoulder rhythm has been adopted for shoulder biomechanical models to estimate shoulder muscle activities and structure loads, there needs to be further investigation on how the predicted error from the shoulder rhythm affects the output of the biomechanical model. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Spirituality and Resilience Among Mexican American IPV Survivors.

PubMed

de la Rosa, Iván A; Barnett-Queen, Timothy; Messick, Madeline; Gurrola, Maria

2016-12-01

Women with abusive partners use a variety of coping strategies. This study examined the correlation between spirituality, resilience, and intimate partner violence using a cross-sectional survey of 54 Mexican American women living along the U.S.-Mexico border. The meaning-making coping model provides the conceptual framework to explore how spirituality is used as a copying strategy. Multiple ordinary least squares (OLS) regression results indicate women who score higher on spirituality also report greater resilient characteristics. Poisson regression analyses revealed that an increase in level of spirituality is associated with lower number of types of abuse experienced. Clinical, programmatic, and research implications are discussed. © The Author(s) 2015.

High school science enrollment of black students

NASA Astrophysics Data System (ADS)

Goggins, Ellen O.; Lindbeck, Joy S.

How can the high school science enrollment of black students be increased? School and home counseling and classroom procedures could benefit from variables identified as predictors of science enrollment. The problem in this study was to identify a set of variables which characterize science course enrollment by black secondary students. The population consisted of a subsample of 3963 black high school seniors from The High School and Beyond 1980 Base-Year Survey. Using multiple linear regression, backward regression, and correlation analyses, the US Census regions and grades mostly As and Bs in English were found to be significant predictors of the number of science courses scheduled by black seniors.

Ergonomics study on mobile phones for thumb physiology discomfort

NASA Astrophysics Data System (ADS)

Bendero, J. M. S.; Doon, M. E. R.; Quiogue, K. C. A.; Soneja, L. C.; Ong, N. R.; Sauli, Z.; Vairavan, R.

2017-09-01

The study was conducted on Filipino undergraduate college students and aimed to find out about the significant factors associated with mobile phone usage and its effect on thumb pain.A correlation-prediction analysisand Multiple Linear Regression was adopted and used as the main tool in determining the significant factors and coming up with predictive models on thumb related pain. With the use of the software Statistical Package for the Social Sciences or SPSS in conducting linear regression, 2 significant factors on thumb-related pain (percentage of time using portrait as screen orientation when text messaging, amount of time playing games using one hand in a day) were found.

Direct evidence on the immune-mediated spontaneous regression of human cancer: an incentive for pharmaceutical companies to develop a novel anti-cancer vaccine.

PubMed

Saleh, F; Renno, W; Klepacek, I; Ibrahim, G; Dashti, H; Asfar, S; Behbehani, A; Al-Sayer, H; Dashti, A; Kerry, Crotty

2005-01-01

To develop an effective pharmaceutical treatment for a disease, we need to fully understand the biological behavior of that disease, especially when dealing with cancer. The current available treatment for cancer may help in lessening the burden of the disease or, on certain occasions, in increasing the survival of the patient. However, a total eradication of cancer remains the researchers' hope. Some of the discoveries in the field of medicine relied on observations of natural events. Among these events is the spontaneous regression of cancer. It has been argued that such regression could be immunologically-mediated, but no direct evidence has been shown to support such an argument. We, hereby, provide compelling evidence that spontaneous cancer regression in humans is immunologically-mediated, hoping that the results from this study would stimulate the pharmaceutical industry to focus more on cancer vaccine immunotherapy. Our results showed that patients with >3 primary melanomas (very rare group among cancer patients) develop significant histopathological spontaneous regression of further melanomas that they could acquire during their life (P=0.0080) as compared to patients with single primary melanoma where the phenomenon of spontaneous regression is absent or minimal. It seems that such regression resulted from the repeated exposure to the tumor which mimics a self-immunization process. Analysis of the regressing tumors revealed heavy infiltration by T lymphocytes as compared to non-regressing tumors (P<0.0001), the predominant of which were T cytotoxic rather than T helper. Mature dendritic cells were also found in significant number (P<0.0001) in the regressing tumors as compared to the non regressing ones, which demonstrate an active involvement of the different arms of the immune system in the multiple primary melanoma patients in the process of tumor regression. Also, MHC expression was significantly higher in the regressing versus the non-regressing tumors (P <0.0001), which reflects a proper tumor antigen expression. Associated with tumor regression was also loss of the melanoma common tumor antigen Melan A/ MART-1 in the multiple primary melanoma patients as compared to the single primary ones (P=0.0041). Furthermore, loss of Melan A/ MART-1 in the regressing tumors significantly correlated with the presence of Melan A/ MART-1-specific CTLs in the peripheral blood of these patients (P=0.03), which adds to the evidence that the phenomenon of regression seen in these patients was immunologically-mediated and tumor-specific. Such correlation was also seen in another rare group of melanoma patients, namely those with occult primary melanoma. The lesson that we could learn from nature in this study is that inducing cancer regression using the different arms of the immune system is possible. Also, developing a novel cancer vaccine is not out of reach.

Quasi-Likelihood Techniques in a Logistic Regression Equation for Identifying Simulium damnosum s.l. Larval Habitats Intra-cluster Covariates in Togo.

PubMed

Jacob, Benjamin G; Novak, Robert J; Toe, Laurent; Sanfo, Moussa S; Afriyie, Abena N; Ibrahim, Mohammed A; Griffith, Daniel A; Unnasch, Thomas R

2012-01-01

The standard methods for regression analyses of clustered riverine larval habitat data of Simulium damnosum s.l. a major black-fly vector of Onchoceriasis, postulate models relating observational ecological-sampled parameter estimators to prolific habitats without accounting for residual intra-cluster error correlation effects. Generally, this correlation comes from two sources: (1) the design of the random effects and their assumed covariance from the multiple levels within the regression model; and, (2) the correlation structure of the residuals. Unfortunately, inconspicuous errors in residual intra-cluster correlation estimates can overstate precision in forecasted S.damnosum s.l. riverine larval habitat explanatory attributes regardless how they are treated (e.g., independent, autoregressive, Toeplitz, etc). In this research, the geographical locations for multiple riverine-based S. damnosum s.l. larval ecosystem habitats sampled from 2 pre-established epidemiological sites in Togo were identified and recorded from July 2009 to June 2010. Initially the data was aggregated into proc genmod. An agglomerative hierarchical residual cluster-based analysis was then performed. The sampled clustered study site data was then analyzed for statistical correlations using Monthly Biting Rates (MBR). Euclidean distance measurements and terrain-related geomorphological statistics were then generated in ArcGIS. A digital overlay was then performed also in ArcGIS using the georeferenced ground coordinates of high and low density clusters stratified by Annual Biting Rates (ABR). This data was overlain onto multitemporal sub-meter pixel resolution satellite data (i.e., QuickBird 0.61m wavbands ). Orthogonal spatial filter eigenvectors were then generated in SAS/GIS. Univariate and non-linear regression-based models (i.e., Logistic, Poisson and Negative Binomial) were also employed to determine probability distributions and to identify statistically significant parameter estimators from the sampled data. Thereafter, Durbin-Watson test statistics were used to test the null hypothesis that the regression residuals were not autocorrelated against the alternative that the residuals followed an autoregressive process in AUTOREG. Bayesian uncertainty matrices were also constructed employing normal priors for each of the sampled estimators in PROC MCMC. The residuals revealed both spatially structured and unstructured error effects in the high and low ABR-stratified clusters. The analyses also revealed that the estimators, levels of turbidity and presence of rocks were statistically significant for the high-ABR-stratified clusters, while the estimators distance between habitats and floating vegetation were important for the low-ABR-stratified cluster. Varying and constant coefficient regression models, ABR- stratified GIS-generated clusters, sub-meter resolution satellite imagery, a robust residual intra-cluster diagnostic test, MBR-based histograms, eigendecomposition spatial filter algorithms and Bayesian matrices can enable accurate autoregressive estimation of latent uncertainity affects and other residual error probabilities (i.e., heteroskedasticity) for testing correlations between georeferenced S. damnosum s.l. riverine larval habitat estimators. The asymptotic distribution of the resulting residual adjusted intra-cluster predictor error autocovariate coefficients can thereafter be established while estimates of the asymptotic variance can lead to the construction of approximate confidence intervals for accurately targeting productive S. damnosum s.l habitats based on spatiotemporal field-sampled count data.

Gene set analysis using variance component tests.

PubMed

Huang, Yen-Tsung; Lin, Xihong

2013-06-28

Gene set analyses have become increasingly important in genomic research, as many complex diseases are contributed jointly by alterations of numerous genes. Genes often coordinate together as a functional repertoire, e.g., a biological pathway/network and are highly correlated. However, most of the existing gene set analysis methods do not fully account for the correlation among the genes. Here we propose to tackle this important feature of a gene set to improve statistical power in gene set analyses. We propose to model the effects of an independent variable, e.g., exposure/biological status (yes/no), on multiple gene expression values in a gene set using a multivariate linear regression model, where the correlation among the genes is explicitly modeled using a working covariance matrix. We develop TEGS (Test for the Effect of a Gene Set), a variance component test for the gene set effects by assuming a common distribution for regression coefficients in multivariate linear regression models, and calculate the p-values using permutation and a scaled chi-square approximation. We show using simulations that type I error is protected under different choices of working covariance matrices and power is improved as the working covariance approaches the true covariance. The global test is a special case of TEGS when correlation among genes in a gene set is ignored. Using both simulation data and a published diabetes dataset, we show that our test outperforms the commonly used approaches, the global test and gene set enrichment analysis (GSEA). We develop a gene set analyses method (TEGS) under the multivariate regression framework, which directly models the interdependence of the expression values in a gene set using a working covariance. TEGS outperforms two widely used methods, GSEA and global test in both simulation and a diabetes microarray data.

An ecological study on suicide and homicide in Brazil.

PubMed

Bando, Daniel Hideki; Lester, David

2014-04-01

The objective was to evaluate correlations between suicide, homicide and socio-demographic variables by an ecological study. Mortality and socio-demographic data were collected from official records of the Ministry of Health and IBGE (2010), aggregated by state (27). The data were analyzed using correlation techniques, factor analysis, principal component analysis with a varimax rotation and multiple linear regression. Suicide age-adjusted rates for the total population, men and women were 5.0, 8.0, and 2.2 per 100,000 inhabitants respectively. The suicide rates ranged from 2.7 in Pará to 9.1 in Rio Grande do Sul. Homicide for the total population, men and women were 27.2, 50.8, and 4.5 per 100,000, respectively. The homicide rates ranged from 13.0 in Santa Catarina to 68.9 in Alagoas. Suicide and homicide were negatively associated, the significance persisted among men. Unemployment was negatively correlated with suicide and positively with homicide. Different socio-demographic variables were found to correlate with suicide and homicide in the regressions. Suicide showed a pattern suggesting that, in Brazil, it is related to high socioeconomic status. Homicide seemed to follow the pattern found in other countries, associated with lower social and economic status.

Optimizing methods for linking cinematic features to fMRI data.

PubMed

Kauttonen, Janne; Hlushchuk, Yevhen; Tikka, Pia

2015-04-15

One of the challenges of naturalistic neurosciences using movie-viewing experiments is how to interpret observed brain activations in relation to the multiplicity of time-locked stimulus features. As previous studies have shown less inter-subject synchronization across viewers of random video footage than story-driven films, new methods need to be developed for analysis of less story-driven contents. To optimize the linkage between our fMRI data collected during viewing of a deliberately non-narrative silent film 'At Land' by Maya Deren (1944) and its annotated content, we combined the method of elastic-net regularization with the model-driven linear regression and the well-established data-driven independent component analysis (ICA) and inter-subject correlation (ISC) methods. In the linear regression analysis, both IC and region-of-interest (ROI) time-series were fitted with time-series of a total of 36 binary-valued and one real-valued tactile annotation of film features. The elastic-net regularization and cross-validation were applied in the ordinary least-squares linear regression in order to avoid over-fitting due to the multicollinearity of regressors, the results were compared against both the partial least-squares (PLS) regression and the un-regularized full-model regression. Non-parametric permutation testing scheme was applied to evaluate the statistical significance of regression. We found statistically significant correlation between the annotation model and 9 ICs out of 40 ICs. Regression analysis was also repeated for a large set of cubic ROIs covering the grey matter. Both IC- and ROI-based regression analyses revealed activations in parietal and occipital regions, with additional smaller clusters in the frontal lobe. Furthermore, we found elastic-net based regression more sensitive than PLS and un-regularized regression since it detected a larger number of significant ICs and ROIs. Along with the ISC ranking methods, our regression analysis proved a feasible method for ordering the ICs based on their functional relevance to the annotated cinematic features. The novelty of our method is - in comparison to the hypothesis-driven manual pre-selection and observation of some individual regressors biased by choice - in applying data-driven approach to all content features simultaneously. We found especially the combination of regularized regression and ICA useful when analyzing fMRI data obtained using non-narrative movie stimulus with a large set of complex and correlated features. Copyright © 2015. Published by Elsevier Inc.

Application of remote sensing for fishery resources assessment and monitoring. [Gulf of Mexico

NASA Technical Reports Server (NTRS)

Savastano, K. J. (Principal Investigator)

1975-01-01

The author has identified the following significant results. The distribution and abundance of white marlin correlated with the chlorophyll, water temperature, and Secchi depth sea truth measurements. Results of correlation analyses for dolphin were inconclusive. Predicition models for white marlin were developed using stepwise multiple regression and discriminant function analysis techniques which demonstrated a potential for increasing the probability of game fishing success. The S190A and B imagery was density sliced/color enhanced with white marlin location superimposed on the image, but no density/white marlin relationship could be established.

Estimation of instantaneous heat transfer coefficients for a direct-injection stratified-charge rotary engine

NASA Technical Reports Server (NTRS)

Lee, C. M.; Addy, H. E.; Bond, T. H.; Chun, K. S.; Lu, C. Y.

1987-01-01

The main objective of this report was to derive equations to estimate heat transfer coefficients in both the combustion chamber and coolant pasage of a rotary engine. This was accomplished by making detailed temperature and pressure measurements in a direct-injection stratified-charge rotary engine under a range of conditions. For each sppecific measurement point, the local physical properties of the fluids were calculated. Then an empirical correlation of the coefficients was derived by using a multiple regression program. This correlation expresses the Nusselt number as a function of the Prandtl number and Reynolds number.

Relationships between locus of control and paranormal beliefs.

PubMed

Newby, Robert W; Davis, Jessica Boyette

2004-06-01

The present study investigated the associations between scores on paranormal beliefs, locus of control, and certain psychological processes such as affect and cognitions as measured by the Linguistic Inquiry and Word Count. Analysis yielded significant correlations between scores on Locus of Control and two subscales of Tobacyk's (1988) Revised Paranormal Beliefs Scale, New Age Philosophy and Traditional Paranormal Beliefs. A step-wise multiple regression analysis indicated that Locus of Control was significantly related to New Age Philosophy. Other correlations were found between Tobacyk's subscales, Locus of Control, and three processes measured by the Linguistic Inquiry and Word Count.

Social cognitive correlates of physical activity among persons with multiple sclerosis: Influence of depressive symptoms.

PubMed

Ensari, Ipek; Kinnett-Hopkins, Dominique; Motl, Robert W

2017-10-01

Physical inactivity and elevated depressive symptoms are both highly prevalent and correlated among persons with multiple sclerosis (MS). Variables from Social Cognitive Theory (SCT) might be differentially correlated with physical activity in persons with MS who have elevated depressive symptoms. This study investigated the influence of elevated depressive symptoms on correlates of physical activity based on SCT in persons with MS. Participants (mean age = 50.3 years, 87% female, 69% Caucasian) completed questionnaires on physical activity, depressive symptoms, self-efficacy, social support, outcome expectations, functional limitations, and goal setting. The questionnaires were delivered and returned through the U.S. Postal Service. The sample (N = 551) was divided into 2 subgroups (i.e., elevated vs non-elevated levels of depressive symptoms) for statistical analyses. Bivariate correlations and stepwise multiple regressions were conducted using SPSS. Self-efficacy (r = 0.16), functional limitations (r = 0.22) and goal-setting (r = 0.42) were significantly (p < 0.05) associated with physical activity among the elevated depressive sample. The regression analysis indicated that self-efficacy predicted physical activity in Step 1 (β = 0.16, p < 0.05), but was no longer significant when goal-setting (β = 0.06, p > 0.05) entered the model. All social cognitive variables were significantly associated with physical activity levels (r = 0.16-0.40, p < 0.001) among the non-elevated depressive sample. Self-efficacy predicted physical activity in Step 1 (β = 0.24, p < 0.001), but it was no longer significant once goal-setting, functional limitations, and self-evaluative outcome expectations entered the model. Based on SCT, self-efficacy and goal-setting represent possible targets of behavior interventions for increasing physical activity among persons with MS who have elevated depressive symptoms. There is a larger set of targets among those with MS who do not have elevated symptoms. Copyright © 2017 Elsevier Inc. All rights reserved.

Community characteristics that attract physicians in Japan: a cross-sectional analysis of community demographic and economic factors.

PubMed

Matsumoto, Masatoshi; Inoue, Kazuo; Noguchi, Satomi; Toyokawa, Satoshi; Kajii, Eiji

2009-02-18

In many countries, there is a surplus of physicians in some communities and a shortage in others. Population size is known to be correlated with the number of physicians in a community, and is conventionally considered to represent the power of communities to attract physicians. However, associations between other demographic/economic variables and the number of physicians in a community have not been fully evaluated. This study seeks other parameters that correlate with the physician population and show which characteristics of a community determine its "attractiveness" to physicians. Associations between the number of physicians and selected demographic/economic/life-related variables of all of Japan's 3132 municipalities were examined. In order to exclude the confounding effect of community size, correlations between the physician-to-population ratio and other variable-to-population ratios or variable-to-area ratios were evaluated with simple correlation and multiple regression analyses. The equity of physician distribution against each variable was evaluated by the orenz curve and Gini index. Among the 21 variables selected, the service industry workers-to-population ratio (0.543), commercial land price (0.527), sales of goods per person (0.472), and daytime population density (0.451) were better correlated with the physician-to-population ratio than was population density (0.409). Multiple regression analysis showed that the service industry worker-to-population ratio, the daytime population density, and the elderly rate were each independently correlated with the physician-to-population ratio (standardized regression coefficient 0.393, 0.355, 0.089 respectively; each p<0.001). Equity of physician distribution was higher against service industry population (Gini index=0.26) and daytime population (0.28) than against population (0.33). Daytime population and service industry population in a municipality are better parameters of community attractiveness to physicians than population. Because attractiveness is supposed to consist of medical demand and the amenities of urban life, the two parameters may represent the amount of medical demand and/or the extent of urban amenities of the community more precisely than population does. The conventional demand-supply analysis based solely on population as the demand parameter may overestimate the inequity of the physician distribution among communities.

The Relationship of Hypochondriasis to Anxiety, Depressive, and Somatoform Disorders

PubMed Central

Scarella, Timothy M.; Laferton, Johannes A. C.; Ahern, David K.; Fallon, Brian A.; Barsky, Arthur

2015-01-01

Background Though the phenotype of anxiety about medical illness has long been recognized, there continues to be debate as to whether it is a distinct psychiatric disorder and, if so, to which diagnostic category it belongs. Our objective was to investigate the pattern of psychiatric co-morbidity in hypochondriasis and to assess the relationship of health anxiety to anxiety, depressive, and somatoform disorders. Methods Data were collected as part of a clinical trial on treatment methods for hypochondriasis. 194 participants meeting criteria for DSM-IV hypochondriasis were assessed by sociodemographic variables, results of structured diagnostic interviews, and validated instruments for assessing various symptom dimensions of psychopathology. Results The majority of individuals with hypochondriasis had co-morbid psychiatric illness; the mean number of co-morbid diagnoses was 1.4, and 35.1% had hypochondriasis as their only diagnosis. Participants were more likely to have only co-morbid anxiety disorders than only co-morbid depressive or somatoform disorders. Multiple regression analysis of continuous measures of symptoms revealed the strongest correlation of health anxiety with anxiety symptoms, and a weaker correlation with somatoform symptoms; in multiple regression analysis, there was no correlation between health anxiety and depressive symptoms. Conclusion Our findings suggest that the entity of health anxiety (Hypochondriasis in DSM-IV, Illness Anxiety Disorder in DSM-5) is a clinical syndrome distinct from other psychiatric disorders. Analysis of co-morbidity patterns and continuous measures of symptoms suggest its appropriate classification is with anxiety rather than somatoform or mood disorders. PMID:26785798

Matsuda-DeFronzo insulin sensitivity index is a better predictor than HOMA-IR of hypertension in Japanese: the Tanno-Sobetsu study.

PubMed

Furugen, M; Saitoh, S; Ohnishi, H; Akasaka, H; Mitsumata, K; Chiba, M; Furukawa, T; Miyazaki, Y; Shimamoto, K; Miura, T

2012-05-01

Here we examined whether the Matsuda-DeFronzo insulin sensitivity index (ISI-M) is more efficient than the homeostasis model assessment of insulin resistance (HOMA-IR) for assessing risk of hypertension. Cross-sectional and longitudinal analyses were conducted using normotensive subjects who were selected among 1399 subjects in the Tanno-Sobetsu cohort. In the cross-sectional analysis (n=740), blood pressure (BP) level was correlated with HOMA-IR and with ISI-M, but correlation coefficients indicate a tighter correlation with ISI-M. Multiple linear regression analysis adjusted by age, sex, body mass index (BMI) and serum triglyceride level (TG) showed contribution of ISI-M and fasting plasma glucose, but not of HOMA-IR. In the longitudinal analysis (n=607), 241 subjects (39.7%) developed hypertension during a 10-year follow-up period, and multiple logistic regression indicated that age, TG, systolic BP and ISI-M, but not HOMA-IR, were associated with development of hypertension. In subjects <60 years old, odds ratio of new-onset hypertension was higher in the low ISI-M group (ISI-M, less than the median) than in the high ISI-M group for any tertile of BMI. In conclusion, ISI-M is a better predictor of hypertension than is HOMA-IR. Non-hepatic IR may be a determinant, which is independent of TG, BP level and BMI, of the development of hypertension.

Relationship Between Column-Density and Surface Mixing Ratio: Statistical Analysis of O3 and NO2 Data from the July 2011 Maryland DISCOVER-AQ Mission

NASA Technical Reports Server (NTRS)

Flynn, Clare; Pickering, Kenneth E.; Crawford, James H.; Lamsol, Lok; Krotkov, Nickolay; Herman, Jay; Weinheimer, Andrew; Chen, Gao; Liu, Xiong; Szykman, James;

Integrated Central-Autonomic Multifractal Complexity in the Heart Rate Variability of Healthy Humans

PubMed Central

Lin, D. C.; Sharif, A.

2012-01-01

Purpose of Study: The aim of this study was to characterize the central-autonomic interaction underlying the multifractality in heart rate variability (HRV) of healthy humans. Materials and Methods: Eleven young healthy subjects participated in two separate ~40 min experimental sessions, one in supine (SUP) and one in, head-up-tilt (HUT), upright (UPR) body positions. Surface scalp electroencephalography (EEG) and electrocardiogram (ECG) were collected and fractal correlation of brain and heart rate data was analyzed based on the idea of relative multifractality. The fractal correlation was further examined with the EEG, HRV spectral measures using linear regression of two variables and principal component analysis (PCA) to find clues for the physiological processing underlying the central influence in fractal HRV. Results: We report evidence of a central-autonomic fractal correlation (CAFC) where the HRV multifractal complexity varies significantly with the fractal correlation between the heart rate and brain data (P = 0.003). The linear regression shows significant correlation between CAFC measure and EEG Beta band spectral component (P = 0.01 for SUP and P = 0.002 for UPR positions). There is significant correlation between CAFC measure and HRV LF component in the SUP position (P = 0.04), whereas the correlation with the HRV HF component approaches significance (P = 0.07). The correlation between CAFC measure and HRV spectral measures in the UPR position is weak. The PCA results confirm these findings and further imply multiple physiological processes underlying CAFC, highlighting the importance of the EEG Alpha, Beta band, and the HRV LF, HF spectral measures in the supine position. Discussion and Conclusion: The findings of this work can be summarized into three points: (i) Similar fractal characteristics exist in the brain and heart rate fluctuation and the change toward stronger fractal correlation implies the change toward more complex HRV multifractality. (ii) CAFC is likely contributed by multiple physiological mechanisms, with its central elements mainly derived from the EEG Alpha, Beta band dynamics. (iii) The CAFC in SUP and UPR positions is qualitatively different, with a more predominant central influence in the fractal HRV of the UPR position. PMID:22403548

Cognitive ability correlates positively with son birth and predicts cross-cultural variation of the offspring sex ratio

NASA Astrophysics Data System (ADS)

Dama, Madhukar Shivajirao

2013-06-01

Human populations show remarkable variation in the sex ratio at birth which is believed to be related to the parental condition. In the present study, the global variation of sex ratio at birth (SRB, proportion of male offspring born) was analyzed with respect to indirect measure of condition, the intelligence quotient (IQ). IQ correlates strongly with lifespan across nations, which makes it a good indicator of health of the large populations. Relation between three standard measures of average national IQ and SRB was studied using multiple linear regression models. Average national IQ was positively correlated with SRB ( r = 0.54 to 0.57, p < 0.001). Further, IQ emerged as a powerful predictor of SRB after controlling for the effects of all the known covariates like fertility, maternal age, polygyny prevalence, wealth, son preference, latitude, low birth weight, and neonatal mortality in the regression models. These results suggest that the striking variation of offspring sex ratio across nations could be caused in part by the difference in general condition of populations.

Influence of ozone and meteorological parameters on levels of polycyclic aromatic hydrocarbons in the air

NASA Astrophysics Data System (ADS)

Pehnec, Gordana; Jakovljević, Ivana; Šišović, Anica; Bešlić, Ivan; Vađić, Vladimira

2016-04-01

Concentrations of ten polycyclic aromatic hydrocarbons (PAHs) in the PM10 particle fraction were measured together with ozone and meteorological parameters at an urban site (Zagreb, Croatia) over a one-year period. Data were subjected to regression analysis in order to determine the relationship between the measured pollutants and selected meteorological variables. All of the PAHs showed seasonal variations with high concentrations in winter and autumn and very low concentrations during summer and spring. All of the ten PAHs concentrations also correlated well with each other. A statistically significant negative correlation was found between the concentrations of PAHs and ozone concentrations and concentrations of PAHs and temperature, as well as a positive correlation between concentrations of PAHs and PM10 mass concentration and relative humidity. Multiple regression analysis showed that concentrations of PM10 and ozone, temperature, relative humidity and pressure accounted for 43-70% of PAHs variability. Concentrations of PM10 and temperature were significant variables for all of the measured PAH's concentrations in all seasons. Ozone concentrations were significant for only some of the PAHs, particularly 6-ring PAHs.

A quantitative study of factors influencing quality of life in rural Mexican women diagnosed with HIV.

PubMed

Holtz, Carol; Sowell, Richard; VanBrackle, Lewis; Velasquez, Gabriela; Hernandez-Alonso, Virginia

2014-01-01

This quantitative study explored the level of Quality of Life (QoL) in indigenous Mexican women and identified psychosocial factors that significantly influenced their QoL, using face-to-face interviews with 101 women accessing care in an HIV clinic in Oaxaca, Mexico. Variables included demographic characteristics, levels of depression, coping style, family functioning, HIV-related beliefs, and QoL. Descriptive statistics were used to analyze participant characteristics, and women's scores on data collection instruments. Pearson's R correlational statistics were used to determine the level of significance between study variables. Multiple regression analysis examined all variables that were significantly related to QoL. Pearson's correlational analysis of relationships between Spirituality, Educating Self about HIV, Family Functioning, Emotional Support, Physical Care, and Staying Positive demonstrated positive correlation to QoL. Stigma, depression, and avoidance coping were significantly and negatively associated with QoL. The final regression model indicated that depression and avoidance coping were the best predictor variables for QoL. Copyright © 2014 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

The relationship between central corneal thickness and optic disc size in patients with primary open-angle glaucoma in a hospital-based population.

PubMed

Terai, Naim; Spoerl, Eberhard; Pillunat, Lutz E; Kuhlisch, Eberhard; Schmidt, Eckart; Boehm, Andreas G

2011-09-01

To investigate the relationship between central corneal thickness (CCT) and optic disc size in patients with primary open-angle glaucoma (POAG) in a hospital-based population. Data for the right eyes of 1435 White patients with POAG were included in a retrospective hospital-based study. All eyes underwent optic nerve head imaging using Heidelberg Retina Tomograph II (HRT II; Heidelberg Engineering, Heidelberg, Germany) and CCT measurement by ultrasound corneal pachymetry. Eyes with prior intraocular or corneal surgery were excluded. Low-quality HRT II images were also excluded. The impact of age, gender, CCT, intraocular pressure, cylindrical and spherical refractive error as independent factors on optic disc size was investigated in a multiple linear regression analysis. The data for 1104 right eyes qualified for participation in the study. The median age of these patients was 65 years. The median CCT was 547 μm (25th-75th percentile 522-575 μm). The median optic disc size was 2.21 mm(2) (25th-75th percentile 1.89-2.60 mm(2)). Multiple linear regression analysis revealed that age (p = 0.001), CCT (p = 0.001) and spherical equivalent (p = 0.049) were correlated to disc size according to the following formula: disc area = -0.004 × age - 0.001 × CCT - 0.014 × spherical equivalent +3.290. R(2) of the whole model was 0.021. Univariate regression analysis between age and disc area provided R(2) = 0.008 with p = 0.002. Univariate regression analysis between disc area and CCT provided R(2) = 0.005 with p = 0.02. In this retrospective hospital-based study we could not detect a clinically relevant correlation between optic disc size and CCT. The correlation between CCT and disc size and between age and disc size were statistically significant, but the R(2) values were very low. The results of the study are biased because of its hospital-based design, so the results of the study need to be confirmed in a large population-based study. © 2009 The Authors. Journal compilation © 2009 Acta Ophthalmol.

Impact of angiogenesis-related gene expression on the tracer kinetics of 18F-FDG in colorectal tumors.

PubMed

Strauss, Ludwig G; Koczan, Dirk; Klippel, Sven; Pan, Leyun; Cheng, Caixia; Willis, Stefan; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2008-08-01

18F-FDG kinetics are primarily dependent on the expression of genes associated with glucose transporters and hexokinases but may be modulated by other genes. The dependency of 18F-FDG kinetics on angiogenesis-related gene expression was evaluated in this study. Patients with primary colorectal tumors (n = 25) were examined with PET and 18F-FDG within 2 days before surgery. Tissue specimens were obtained from the tumor and the normal colon during surgery, and gene expression was assessed using gene arrays. Overall, 23 angiogenesis-related genes were identified with a tumor-to-normal ratio exceeding 1.50. Analysis revealed a significant correlation between k1 and vascular endothelial growth factor (VEGF-A, r = 0.51) and between fractal dimension and angiopoietin-2 (r = 0.48). k3 was negatively correlated with VEGF-B (r = -0.46), and a positive correlation was noted for angiopoietin-like 4 gene (r = 0.42). A multiple linear regression analysis was used for the PET parameters to predict the gene expression, and a correlation coefficient of r = 0.75 was obtained for VEGF-A and of r = 0.76 for the angiopoietin-2 expression. Thus, on the basis of these multiple correlation coefficients, angiogenesis-related gene expression contributes to about 50% of the variance of the 18F-FDG kinetic data. The global 18F-FDG uptake, as measured by the standardized uptake value and influx, was not significantly correlated with angiogenesis-associated genes. 18F-FDG kinetics are modulated by angiogenesis-related genes. The transport rate for 18F-FDG (k1) is higher in tumors with a higher expression of VEGF-A and angiopoietin-2. The regression functions for the PET parameters provide the possibility to predict the gene expression of VEGF-A and angiopoietin-2.

Zinc, lead, and cadmium levels in serum and milk of lactating women in Ibadan, Nigeria.

PubMed

Edem, Victory Fabian; Akintunde, Kikelomo; Adelaja, Yewande Adeola; Nwozo, Sarah O; Charles-Davies, Mabel

2017-01-01

Zinc (Zn) is known to interact with lead (Pb) and cadmium (Cd) reversing their toxicity and reducing their concentrations. However, lactating women are at high risk of developing Zn deficiency, which may result in Pb and Cd intoxication or increased exposure of breast-fed infants to Pb and Cd from breast milk. The aim of this study was to determine Zn, Pb, and Cd concentrations and examine their relationship in serum and breast milk of lactating women in Ibadan, Nigeria. Ninety-two lactating women were recruited into this study. Anthropometric measurements were assessed by standard methods while serum and breast milk concentrations of Zn, Pb, and Cd were assessed by atomic absorption spectrophotometry. Data analyzed statistically by Student's t test, Pearson's correlation coefficient, and a multiple regression model were significant at p < 0.05. Zn deficiency was observed in 12 (17.1%) of lactating women. Breast milk levels of Zn, Pb, and Cd were significantly higher than their levels in serum, whereas the ratios Zn:Pb and Zn:Cd in milk were significantly less than serum ratios. Significant negative correlation was observed between milk Pb and serum Zn:Pb while milk Cd correlated positively with milk Zn. Significant positive correlations were observed between serum Zn and serum Zn:Pb, serum Zn and serum Zn:Cd, as well as serum Zn:Cd and serum Zn:Pb. Serum Cd and serum Zn were significantly negatively related. Significant negative correlations between serum Pb and serum Zn:Pb as well as milk Zn:Pb. Serum Cd and serum Zn:Pb as well as serum Zn:Cd correlated negatively. Milk Cd and Zn/Cd positively related with milk Pb while milk Zn was a negatively related with milk Pb in a multiple regression model ( R 2 = 0.333; p = 0.023). Breast milk may be contaminated by toxic metals. However, Zn supplementation in deficient mothers may protect maternal and infant health.

Association of academic performance of premedical students to satisfaction and engagement in a short training program: a cross sectional study presenting gender differences

PubMed Central

2014-01-01

Background It is important that students have a high academic engagement and satisfaction in order to have good academic achievement. No study measures association of these elements in a short training program. This study aimed to measure the correlation between academic achievement, satisfaction and engagement dimensions in a short training program among premedical students. Methods We carried out a cross sectional study, in August 2013, at Cercle d’Etudiants, Ingénieurs, Médecins et Professeurs de Lycée pour le Triomphe de l’Excellence (CEMPLEX) training center, a center which prepares students for the national common entrance examination into medical schools in Cameroon. We included all students attending this training center during last examination period. They were asked to fill out a questionnaire on paper. Academic engagement was measured using three dimensions: vigor, dedication and absorption. Satisfaction to lessons, for each learning subject was collected. Academic achievement was calculated using mean of the score of all learning subjects affected with their coefficient. Pearson coefficient (r) and multiple regression models were used to measure association. A p value < 0.05 was statistically significant. Results In total, 180 students were analyzed. In univariate linear analysis, we found correlation with academic achievement for vigor (r = 0.338, p = 0.006) and dedication (r = 0.287, p = 0.021) only in male students. In multiple regression linear analysis, academic engagement and satisfaction were correlated to academic achievement only in male students (R2 = 0.159, p = 0.035). No correlation was found in female students and in all students. The independent variables (vigor, dedication, absorption and satisfaction) explained 6.8-24.3% of the variance of academic achievement. Conclusion It is only in male students that academic engagement and satisfaction to lessons are correlated to academic achievement in this short training program for premedical students and this correlation is weak. PMID:24564911

Relationship of lifestyle and body stature growth with the development of myopia and axial length elongation in Taiwanese elementary school children.

PubMed

Huang, Chung-Ying; Hou, Chiun-Ho; Lin, Ken-Kuo; Lee, Jiahn-Shing; Yang, Meng-Ling

2014-08-01

The development of myopia and growth of the eye, occur at a time when body stature is increasing. To investigate the relationship of lifestyle and body growth with axial elongation and myopia development among schoolchildren aged 7 to 9 years. Prospective study. Children in elementary schools without serious eye disorders were invited to participate. We measured cycloplegic refraction, corneal curvature, intraocular pressure, axial length, body height, and weight. Questionnaires about the children's daily lifestyles, family members' myopia and parents' socio-demographic status were completed. The children were followed up every 6 months in a 3-year period. Bivariate correlations, simple and multiple regression. Eighty-eight children participated in this study. Forty-eight were myopic at the beginning of the study, and their myopia correlated with longer axial length and parental myopia (P = 0.015, 0.012). Sixty-five children (74%) completed the study, and the rates of change per year were -0.43 ± 0.58 (mean + standard deviation) diopters in spherical equivalence, 0.32 ± 0.25 mm in axial length (AL), 5.73 ± 2.71 cm in body height, and 3.84 ± 2.23 kg in weight. The axial length change was positively correlated with the height change (P < 0.001). The myopia shift was correlated to axial length change (P = 0.000) but not correlated to height change. Using multiple regression test, near work was the only significant risk factor for myopia progression (P = 0.022). Our study showed that body height increment was correlated to axial length elongation but not to myopia shift in children aged 7-9 years. Genetic factors such as parental myopia and body height had a possible influence on myopia development, and the environment factor as near work intensity was related to myopia progression.

Association of academic performance of premedical students to satisfaction and engagement in a short training program: a cross sectional study presenting gender differences.

PubMed

Bigna, Jean Joel R; Fonkoue, Loic; Tchatcho, Manuela Francette F; Dongmo, Christelle N; Soh, Dorothée M; Um, Joseph Lin Lewis N; Sime, Paule Sandra D; Affana, Landry A; Woum, Albert Ruben N; Noumegni, Steve Raoul N; Tabekou, Alphonce; Wanke, Arlette M; Taffe, Herman Rhais K; Tchoukouan, Miriette Linda N; Anyope, Kevin O; Ella, Stephane Brice E; Mouaha, Berny Vanessa T; Kenne, Edgar Y; Mbessoh, Ulrich Igor K; Tchapmi, Adrienne Y; Tene, Donald F; Voufouo, Steve S; Zogo, Stephanie M; Nouebissi, Linda P; Satcho, Kevine F; Tchoumo, Wati Joel T; Basso, Moise Fabrice; Tcheutchoua, Bertrand Daryl N; Agbor, Ako A

2014-02-24

It is important that students have a high academic engagement and satisfaction in order to have good academic achievement. No study measures association of these elements in a short training program. This study aimed to measure the correlation between academic achievement, satisfaction and engagement dimensions in a short training program among premedical students. We carried out a cross sectional study, in August 2013, at Cercle d'Etudiants, Ingénieurs, Médecins et Professeurs de Lycée pour le Triomphe de l'Excellence (CEMPLEX) training center, a center which prepares students for the national common entrance examination into medical schools in Cameroon. We included all students attending this training center during last examination period. They were asked to fill out a questionnaire on paper. Academic engagement was measured using three dimensions: vigor, dedication and absorption. Satisfaction to lessons, for each learning subject was collected. Academic achievement was calculated using mean of the score of all learning subjects affected with their coefficient. Pearson coefficient (r) and multiple regression models were used to measure association. A p value < 0.05 was statistically significant. In total, 180 students were analyzed. In univariate linear analysis, we found correlation with academic achievement for vigor (r = 0.338, p = 0.006) and dedication (r = 0.287, p = 0.021) only in male students. In multiple regression linear analysis, academic engagement and satisfaction were correlated to academic achievement only in male students (R2 = 0.159, p = 0.035). No correlation was found in female students and in all students. The independent variables (vigor, dedication, absorption and satisfaction) explained 6.8-24.3% of the variance of academic achievement. It is only in male students that academic engagement and satisfaction to lessons are correlated to academic achievement in this short training program for premedical students and this correlation is weak.

Correlation between Volume of Apical Periodontitis Determined by Cone-beam Computed Tomography Analysis and Endotoxin Levels Found in Primary Root Canal Infection.

PubMed

Cardoso, Flávia G R; Ferreira, Nádia S; Martinho, Frederico C; Nascimento, Gustavo G; Manhães, Luiz R C; Rocco, Marco A; Carvalho, Cláudio A T; Valera, Marcia C

2015-07-01

This clinical study was conducted to correlate the levels of endotoxins and bacterial counts found in primary endodontic infection with the volume of periapical bone destruction determined by cone-beam computed tomography (CBCT) analysis. Moreover, the levels of bacteria and endotoxins were correlated with the development of clinical features. Twenty-four root canals with primary endodontic disease and apical periodontitis were selected. Clinical features such as pain on palpation, pain on percussion, and previous episode of pain were recorded. The volume (cubic millimeters) of periapical bone destruction was determined by CBCT analysis. Endotoxins and bacterial samplings were collected by using sterile/apyrogenic paper points. Endotoxins were quantified by using limulus amebocyte lysate assay (KQCL test), and bacterial count (colony-forming units [CFU]/mL) was determined by using anaerobic culture techniques. Data were analyzed by Pearson correlation and multiple logistic regression (P < .05). Endotoxins and bacteria were detected in 100% of the root canal samples (24 of 24), with median values of 10.92 endotoxin units (EU)/mL (1.75-128 EU/mL) and 7.5 × 10(5) CFU/mL (3.20 × 10(5)-8.16 × 10(6) CFU/mL), respectively. The median volume of bone destruction determined by CBCT analysis was 100 mm(3) (10-450 mm(3)). The multiple regression analysis revealed a positive correlation between higher levels of endotoxins present in root canal infection and larger volume of bone destruction (P < .05). Moreover, higher levels of endotoxins were also correlated with the presence of previous pain (P < .05). Our findings revealed that the levels of endotoxins found in root canal infection are related to the volume of periapical bone destruction determined by CBCT analysis. Moreover, the levels of endotoxin are related to the presence of previous pain. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

[Burnout syndrome and suicide risk among primary care nurses].

PubMed

Tomás-Sábado, Joaquín; Maynegre-Santaulària, Montserrat; Pérez-Bartolomé, Meritxell; Alsina-Rodríguez, Marta; Quinta-Barbero, Roser; Granell-Navas, Sergi

2010-01-01

To observe the prevalence of the burnout syndrome and the relationship with suicide risk, self-esteem, anxiety and depression, in a sample of primary care nurses. Observational, cross-sectional and correlational study. The sample consisted of 146 nursing professionals, 131 women and 15 men, with an average age of 44.02 years (SD=10.89). Participants responded to a questionnaire which included the Spanish forms of the Maslach burnout inventory (MBI), the Plutchik Suicide Risk Scale (SR), the Kuwait University Anxiety Scale (KUAS), the Self-Rating Depression Scale (SDS) and the Rosenberg Self-esteem Scale (RSES). In the inferential statistical analysis, Pearson's r coefficients and multiple linear regression were calculated. Significant correlations between suicidal risk and anxiety, depression, self-esteem, emotional exhaustion and personal performance, were obtained. In the multiple regression analysis, depression was the main predictor of suicidal risk, followed by anxiety and emotional exhaustion. The scores obtained in burnout and suicidal risk were, in general, lower than those observed in other studies, emphasising the high level observed in personal performance, which reflects reasonable professional satisfaction. The results show the important role of working atmosphere and early recognition of mental disorders in burnout and suicidal risk prevention. Copyright (c) 2009 Elsevier España, S.L. All rights reserved.

The effect of working in an infection isolation room on hospital nurses' job satisfaction.

PubMed

Kagan, Ilya; Fridman, Shoshana; Shalom, Esther; Melnikov, Semyon

2018-03-01

To examine how the nature of working in a carbapenemase-producing Klebsiella pneumoniae infection isolation room affects nurses' job performance and job satisfaction. Job satisfaction is under intensive research as a factor in the retention of nursing staff. In a cross-sectional design study, a convenience sample of 87 registered nurses who had worked in carbapenemase-producing Klebsiella pneumoniae isolation rooms in a tertiary medical centre in Israel answered a self-administered questionnaire. Data were analysed by descriptive statistics, Pearson correlation coefficients, t tests, one-way ANOVA and multiple regression analysis. Job satisfaction was significantly correlated with perceived knowledge of carbapenemase-producing Klebsiella pneumoniae, with personal experience of working in an isolation room and the perceived level of professional functioning. Multiple regression analysis found that the quality of the nurses' personal experience of isolation room work and their perceived level of professional functioning there explained 33% of the variance in job satisfaction. Managers need to take into account that prolonged work in isolation can negatively impinge upon both performance and job satisfaction. Managers can consider refraining from lengthy nurse assignment to the isolation room. This would also apply to other areas of nursing practice where work is performed in isolation. © 2017 John Wiley & Sons Ltd.

Measurement of pyridoxal 5'-phosphate, pyridoxal, and 4-pyridoxic acid in the cerebrospinal fluid of children.

PubMed

Akiyama, Tomoyuki; Akiyama, Mari; Hayashi, Yumiko; Shibata, Takashi; Hanaoka, Yoshiyuki; Toda, Soichiro; Imai, Katsumi; Hamano, Shin-Ichiro; Okanishi, Tohru; Yoshinaga, Harumi; Kobayashi, Katsuhiro

2017-03-01

We quantified pyridoxal 5'-phosphate (PLP), pyridoxal (PL), and 4-pyridoxic acid (PA) in the cerebrospinal fluid (CSF) of children and to investigate the effect of age, sex, epilepsy, and anti-epileptic drug (AED) therapy on these vitamers. CSF samples prospectively collected from 116 pediatric patients were analyzed. PLP, PL, and PA were measured using high-performance liquid chromatography with fluorescence detection, using pre-column derivatization by semicarbazide. Effects of age, sex, epilepsy, and AEDs on these vitamers and the PLP/PL ratio were evaluated using multiple linear regression models. The PLP, PL, and PA concentrations were correlated negatively with age and the PLP/PL ratio was correlated positively with age. Multiple regression analysis revealed that the presence of epilepsy was associated with lower PLP concentrations and PLP/PL ratios but sex and AED therapy had no influence on these values. The observed ranges of these vitamers in epileptic and non-epileptic patients were demonstrated. We showed the age dependence of PLP and PL in CSF from pediatric patients. Epileptic patients had lower PLP concentrations and PLP/PL ratios than non-epileptic patients, but it is unknown whether this is the cause, or a result, of epilepsy. Copyright © 2016 Elsevier B.V. All rights reserved.

Relationship of cariogenic bacteria levels with periodontal status and root surface caries in elderly Japanese.

PubMed

Saotome, Yasuhiko; Tada, Akio; Hanada, Nobuhiro; Yoshihara, Akihiro; Uematsu, Hiroshi; Miyazaki, Hideo; Senpuku, Hidenobu

2006-12-01

The relationship of the levels of cariogenic bacterial species with periodontal status and decayed root surfaces was investigated in elderly Japanese subjects. Three hundred and sixty-eight individuals (each 75 years old) were examined for periodontal status (pocket depth, attachment loss), root surface caries and salivary levels of mutans streptococci (MS) and lactobacilli (LB). Values >4 mm of attachment loss (rAL4) and for average attachment loss (aAL) of sites measured were significantly higher in subjects with LB than those without. Multiple regression analysis also showed a correlation between aAL and rAL4 values with the presence of LB (aAL p = 0.003; rAL4 p = 0.002). Further, multiple regression analysis of interacting factors regarding decayed root surfaces showed that LB carriers had a greater incidence of decayed root surface caries (p = 0.003), while MS and LB levels were correlated to the number of decayed root surfaces (LB p = 0.010; MS p = 0.026). Our results indicate that considerable attachment loss elevates the possibility of having LB, thus increasing the risk of root surface caries. It was also found that LB and MS measurements may be useful indicators of decayed root surfaces in elderly individuals with attachment loss.

Prediction of Maximal Aerobic Capacity in Severely Burned Children

PubMed Central

Porro, Laura; Rivero, Haidy G.; Gonzalez, Dante; Tan, Alai; Herndon, David N.; Suman, Oscar E.

2011-01-01

Introduction Maximal oxygen uptake (VO2 peak) is an indicator of cardiorespiratory fitness, but requires expensive equipment and a relatively high technical skill level. Purpose The aim of this study is to provide a formula for estimating VO2 peak in burned children, using information obtained without expensive equipment. Methods Children, with ≥40% total surface area burned (TBSA), underwent a modified Bruce treadmill test to asses VO2 peak at 6 months after injury. We recorded gender, age, %TBSA, %3rd degree burn, height, weight, treadmill time, maximal speed, maximal grade, and peak heart rate, and applied McHenry’s select algorithm to extract important independent variables and Robust multiple regression to establish prediction equations. Results 42 children; 7 to 17 years old were tested. Robust multiple regression model provided the equation: VO2=10.33 – 0.62 *Age (years) + 1.88 * Treadmill Time (min) + 2.3 (gender; Females = 0, Males = 1). The correlation between measured and estimated VO2 peak was R=0.80. We then validated the equation with a group of 33 burned children, which yielded a correlation between measured and estimated VO2 peak of R=0.79. Conclusions Using only a treadmill and easily gathered information, VO2 peak can be estimated in children with burns. PMID:21316155

The effect of multiple stressors on salt marsh end-of-season biomass

USGS Publications Warehouse

Visser, J.M.; Sasser, C.E.; Cade, B.S.

2006-01-01

It is becoming more apparent that commonly used statistical methods (e.g., analysis of variance and regression) are not the best methods for estimating limiting relationships or stressor effects. A major challenge of estimating the effects associated with a measured subset of limiting factors is to account for the effects of unmeasured factors in an ecologically realistic matter. We used quantile regression to elucidate multiple stressor effects on end-of-season biomass data from two salt marsh sites in coastal Louisiana collected for 18 yr. Stressor effects evaluated based on available data were flooding, salinity, air temperature, cloud cover, precipitation deficit, grazing by muskrat, and surface water nitrogen and phosphorus. Precipitation deficit combined with surface water nitrogen provided the best two-parameter model to explain variation in the peak biomass with different slopes and intercepts for the two study sites. Precipitation deficit, cloud cover, and temperature were significantly correlated with each other. Surface water nitrogen was significantly correlated with surface water phosphorus and muskrat density. The site with the larger duration of flooding showed reduced peak biomass, when cloud cover and surface water nitrogen were optimal. Variation in the relatively low salinity occurring in our study area did not explain any of the variation in Spartina alterniflora biomass. ?? 2006 Estuarine Research Federation.

The effect of multiple stressors on salt marsh end-of-season biomass

USGS Publications Warehouse

Visser, J.M.; Sasser, C.E.; Cade, B.S.

2006-01-01

It is becoming more apparent that commonly used statistical methods (e.g. analysis of variance and regression) are not the best methods for estimating limiting relationships or stressor effects. A major challenge of estimating the effects associated with a measured subset of limiting factors is to account for the effects of unmeasured factors in an ecologically realistic matter. We used quantile regression to elucidate multiple stressor effects on end-of-season biomass data from two salt marsh sites in coastal Louisiana collected for 18 yr. Stressor effects evaluated based on available data were flooding, salinity air temperature, cloud cover, precipitation deficit, grazing by muskrat, and surface water nitrogen and phosphorus. Precipitation deficit combined with surface water nitrogen provided the best two-parameter model to explain variation in the peak biomass with different slopes and intercepts for the two study sites. Precipitation deficit, cloud cover, and temperature were significantly correlated with each other. Surface water nitrogen was significantly correlated with surface water phosphorus and muskrat density. The site with the larger duration of flooding showed reduced peak biomass, when cloud cover and surface water nitrogen were optimal. Variation in the relatively low salinity occurring in our study area did not explain any of the variation in Spartina alterniflora biomass.

Cultural Competence of Obstetric and Neonatal Nurses.

PubMed

Heitzler, Ella T

To measure the cultural competence level of obstetric and neonatal nurses, explore relationships among cultural competence and selected sociodemographic variables, and identify factors related to cultural competence. Descriptive correlational study. Online survey. A convenience sample of 132 obstetric and neonatal registered nurses practicing in the United States. Nurse participants completed the Cultural Competence Assessment (CCA) instrument, which included Cultural Awareness and Sensitivity (CAS) and Cultural Competence Behaviors (CCB) subscales, and a sociodemographic questionnaire. Correlation and regression analyses were conducted. The average CCA score was 5.38 (possible range = 1.00-7.00). CCA scores were negatively correlated with age and positively correlated with self-ranked cultural competence, years of nursing experience, years of experience within the specialty area, and number of types of previous cultural diversity training. CCB subscale scores were correlated positively with age, years of nursing experience, years of experience within the specialty area, and number of types of previous diversity training. CAS subscale scores were positively correlated with number of types of previous diversity training. Standard multiple linear regression explained approximately 10%, 12%, and 11% of the variance in CCA, CAS, and CCB scores, respectively. Obstetric and neonatal registered nurses should continue to work toward greater cultural competence. Exposing nurses to more types of cultural diversity training may help achieve greater cultural competence. Copyright © 2017 AWHONN, the Association of Women’s Health, Obstetric and Neonatal Nurses. Published by Elsevier Inc. All rights reserved.

Correlates of circulating 25-hydroxyvitamin D: Cohort Consortium Vitamin D Pooling Project of Rarer Cancers.

PubMed

McCullough, Marjorie L; Weinstein, Stephanie J; Freedman, D Michal; Helzlsouer, Kathy; Flanders, W Dana; Koenig, Karen; Kolonel, Laurence; Laden, Francine; Le Marchand, Loic; Purdue, Mark; Snyder, Kirk; Stevens, Victoria L; Stolzenberg-Solomon, Rachael; Virtamo, Jarmo; Yang, Gong; Yu, Kai; Zheng, Wei; Albanes, Demetrius; Ashby, Jason; Bertrand, Kimberly; Cai, Hui; Chen, Yu; Gallicchio, Lisa; Giovannucci, Edward; Jacobs, Eric J; Hankinson, Susan E; Hartge, Patricia; Hartmuller, Virginia; Harvey, Chinonye; Hayes, Richard B; Horst, Ronald L; Shu, Xiao-Ou

2010-07-01

Low vitamin D status is common globally and is associated with multiple disease outcomes. Understanding the correlates of vitamin D status will help guide clinical practice, research, and interpretation of studies. Correlates of circulating 25-hydroxyvitamin D (25(OH)D) concentrations measured in a single laboratory were examined in 4,723 cancer-free men and women from 10 cohorts participating in the Cohort Consortium Vitamin D Pooling Project of Rarer Cancers, which covers a worldwide geographic area. Demographic and lifestyle characteristics were examined in relation to 25(OH)D using stepwise linear regression and polytomous logistic regression. The prevalence of 25(OH)D concentrations less than 25 nmol/L ranged from 3% to 36% across cohorts, and the prevalence of 25(OH)D concentrations less than 50 nmol/L ranged from 29% to 82%. Seasonal differences in circulating 25(OH)D were most marked among whites from northern latitudes. Statistically significant positive correlates of 25(OH)D included male sex, summer blood draw, vigorous physical activity, vitamin D intake, fish intake, multivitamin use, and calcium supplement use. Significant inverse correlates were body mass index, winter and spring blood draw, history of diabetes, sedentary behavior, smoking, and black race/ethnicity. Correlates varied somewhat within season, race/ethnicity, and sex. These findings help identify persons at risk for low vitamin D status for both clinical and research purposes.

Correlates of Circulating 25-Hydroxyvitamin D

PubMed Central

McCullough, Marjorie L.; Weinstein, Stephanie J.; Freedman, D. Michal; Helzlsouer, Kathy; Flanders, W. Dana; Koenig, Karen; Kolonel, Laurence; Laden, Francine; Le Marchand, Loic; Purdue, Mark; Snyder, Kirk; Stevens, Victoria L.; Stolzenberg-Solomon, Rachael; Virtamo, Jarmo; Yang, Gong; Yu, Kai; Zheng, Wei; Albanes, Demetrius; Ashby, Jason; Bertrand, Kimberly; Cai, Hui; Chen, Yu; Gallicchio, Lisa; Giovannucci, Edward; Jacobs, Eric J.; Hankinson, Susan E.; Hartge, Patricia; Hartmuller, Virginia; Harvey, Chinonye; Hayes, Richard B.; Horst, Ronald L.; Shu, Xiao-Ou

2010-01-01

Low vitamin D status is common globally and is associated with multiple disease outcomes. Understanding the correlates of vitamin D status will help guide clinical practice, research, and interpretation of studies. Correlates of circulating 25-hydroxyvitamin D (25(OH)D) concentrations measured in a single laboratory were examined in 4,723 cancer-free men and women from 10 cohorts participating in the Cohort Consortium Vitamin D Pooling Project of Rarer Cancers, which covers a worldwide geographic area. Demographic and lifestyle characteristics were examined in relation to 25(OH)D using stepwise linear regression and polytomous logistic regression. The prevalence of 25(OH)D concentrations less than 25 nmol/L ranged from 3% to 36% across cohorts, and the prevalence of 25(OH)D concentrations less than 50 nmol/L ranged from 29% to 82%. Seasonal differences in circulating 25(OH)D were most marked among whites from northern latitudes. Statistically significant positive correlates of 25(OH)D included male sex, summer blood draw, vigorous physical activity, vitamin D intake, fish intake, multivitamin use, and calcium supplement use. Significant inverse correlates were body mass index, winter and spring blood draw, history of diabetes, sedentary behavior, smoking, and black race/ethnicity. Correlates varied somewhat within season, race/ethnicity, and sex. These findings help identify persons at risk for low vitamin D status for both clinical and research purposes. PMID:20562191

Restoring method for missing data of spatial structural stress monitoring based on correlation

NASA Astrophysics Data System (ADS)

Zhang, Zeyu; Luo, Yaozhi

2017-07-01

Long-term monitoring of spatial structures is of great importance for the full understanding of their performance and safety. The missing part of the monitoring data link will affect the data analysis and safety assessment of the structure. Based on the long-term monitoring data of the steel structure of the Hangzhou Olympic Center Stadium, the correlation between the stress change of the measuring points is studied, and an interpolation method of the missing stress data is proposed. Stress data of correlated measuring points are selected in the 3 months of the season when missing data is required for fitting correlation. Data of daytime and nighttime are fitted separately for interpolation. For a simple linear regression when single point's correlation coefficient is 0.9 or more, the average error of interpolation is about 5%. For multiple linear regression, the interpolation accuracy is not significantly increased after the number of correlated points is more than 6. Stress baseline value of construction step should be calculated before interpolating missing data in the construction stage, and the average error is within 10%. The interpolation error of continuous missing data is slightly larger than that of the discrete missing data. The data missing rate of this method should better not exceed 30%. Finally, a measuring point's missing monitoring data is restored to verify the validity of the method.

Spatial interpolation schemes of daily precipitation for hydrologic modeling

USGS Publications Warehouse

Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.

2012-01-01

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

Maximal bite force, facial morphology and sucking habits in young children with functional posterior crossbite

PubMed Central

CASTELO, Paula Midori; GAVIÃO, Maria Beatriz Duarte; PEREIRA, Luciano José; BONJARDIM, Leonardo Rigoldi

2010-01-01

Objective The maintenance of normal conditions of the masticatory function is determinant for the correct growth and development of its structures. Thus, the aims of this study were to evaluate the influence of sucking habits on the presence of crossbite and its relationship with maximal bite force, facial morphology and body variables in 67 children of both genders (3.5-7 years) with primary or early mixed dentition. Material and methods The children were divided in four groups: primary-normocclusion (PN, n=19), primary-crossbite (PC, n=19), mixed-normocclusion (MN, n=13), and mixed-crossbite (MC, n=16). Bite force was measured with a pressurized tube, and facial morphology was determined by standardized frontal photographs: AFH (anterior face height) and BFW (bizygomatic facial width). Results It was observed that MC group showed lower bite force than MN, and AFH/ BFW was significantly smaller in PN than PC (t-test). Weight and height were only significantly correlated with bite force in PC group (Pearson’s correlation test). In the primary dentition, AFH/BFW and breast-feeding (at least six months) were positive and negatively associated with crossbite, respectively (multiple logistic regression). In the mixed dentition, breastfeeding and bite force showed negative associations with crossbite (univariate regression), while nonnutritive sucking (up to 3 years) associated significantly with crossbite in all groups (multiple logistic regression). Conclusions In the studied sample, sucking habits played an important role in the etiology of crossbite, which was associated with lower bite force and long-face tendency. PMID:20485925

A Systematic Comparison of Linear Regression-Based Statistical Methods to Assess Exposome-Health Associations.

PubMed

Agier, Lydiane; Portengen, Lützen; Chadeau-Hyam, Marc; Basagaña, Xavier; Giorgis-Allemand, Lise; Siroux, Valérie; Robinson, Oliver; Vlaanderen, Jelle; González, Juan R; Nieuwenhuijsen, Mark J; Vineis, Paolo; Vrijheid, Martine; Slama, Rémy; Vermeulen, Roel

2016-12-01

The exposome constitutes a promising framework to improve understanding of the effects of environmental exposures on health by explicitly considering multiple testing and avoiding selective reporting. However, exposome studies are challenged by the simultaneous consideration of many correlated exposures. We compared the performances of linear regression-based statistical methods in assessing exposome-health associations. In a simulation study, we generated 237 exposure covariates with a realistic correlation structure and with a health outcome linearly related to 0 to 25 of these covariates. Statistical methods were compared primarily in terms of false discovery proportion (FDP) and sensitivity. On average over all simulation settings, the elastic net and sparse partial least-squares regression showed a sensitivity of 76% and an FDP of 44%; Graphical Unit Evolutionary Stochastic Search (GUESS) and the deletion/substitution/addition (DSA) algorithm revealed a sensitivity of 81% and an FDP of 34%. The environment-wide association study (EWAS) underperformed these methods in terms of FDP (average FDP, 86%) despite a higher sensitivity. Performances decreased considerably when assuming an exposome exposure matrix with high levels of correlation between covariates. Correlation between exposures is a challenge for exposome research, and the statistical methods investigated in this study were limited in their ability to efficiently differentiate true predictors from correlated covariates in a realistic exposome context. Although GUESS and DSA provided a marginally better balance between sensitivity and FDP, they did not outperform the other multivariate methods across all scenarios and properties examined, and computational complexity and flexibility should also be considered when choosing between these methods. Citation: Agier L, Portengen L, Chadeau-Hyam M, Basagaña X, Giorgis-Allemand L, Siroux V, Robinson O, Vlaanderen J, González JR, Nieuwenhuijsen MJ, Vineis P, Vrijheid M, Slama R, Vermeulen R. 2016. A systematic comparison of linear regression-based statistical methods to assess exposome-health associations. Environ Health Perspect 124:1848-1856; http://dx.doi.org/10.1289/EHP172.

[Impulsivity - aggression - depression: study of adolescents' problem behavior in light of their personality traits].

PubMed

Pikó, Bettina; Pinczés, Tamás

2014-01-01

Impulsivity is a personality trait that may determine our everyday living, quality of life, decisions. Impulsivity in particular has a great significance during adolescence as a part of the adolescent neuroanatomical and neuropsychiatric developmental processes. The main goal of the present study was to examine correlations among depressive symptomatology, types of aggressive behaviors (verbal, physical, psychic), impulsivity and other personality traits (risk-taking, empathy and self-efficacy) in adolescents. Data collection was going on in Debrecen during the first semester of the year 2012 using classes from three high schools (N = 413), 237 (57,4%) boys and 176 (42,6%) girls. The self-administered questionnaire contained items on mental health and personality traits beyond sociodemographics. After descriptive statistics, correlation and multiple linear regression analyses were applied to detect correlations. Girls reported more depressive symptoms and their level of empathy was also higher. In terms of aggression, significant gender difference was detected only in case of physical aggression with a surplus of boys. Based on multiple regression analyses, we may conclude that impulsivity acted as a risk factor both for mean levels of depressive symptomatology and aggression scales. Besides, lack of empathy proved to be related to physical aggression. In both sexes, self-efficacy was positively associated with verbal and physical aggression. Among girls, self-efficacy was a negative predictor of psychic aggression, that is, it seems to act as a protective factor. In summary, we may conclude that there are strong correlations among depressive symptomatology, aggressive behaviors and impulsivity, and this association may be colored by further personality traits, such as risk-taking, empathy, and self-efficacy. There is a need for learning some basic effective techniques for aggression management and self control as early as adolescence.

The influence of daily stress and resilience on successful ageing.

PubMed

Byun, J; Jung, D

2016-09-01

The aim of this study was to identify the effects of daily stress and resilience on successful ageing among community-dwelling older adults. Ageing can be a positive experience if there is good adaptation to ageing processes. Positive ageing needs to be a basis of nursing care, health promotion and education within community settings. Data were collected in March and April of 2014 from 262 older adults living in Seoul and Jeju, South Korea. We used a four-part survey consisting of demographic data, daily stress, resilience and successful ageing scales, in total 91 items. Data were analysed using descriptive statistics, t-test, one-way ANOVA, Tukey HSD test, Pearson's correlation coefficient and hierarchical multiple regression analysis to identify the influence of variables on successful ageing. Successful ageing had a significant negative correlation with daily stress and a positive correlation with resilience. Daily stress had a negative correlation with resilience. Findings of hierarchical multiple regression analysis indicated that resilience and subjective economic status had an effect on successful ageing. Furthermore, these variables accounted for 41.6% of the variance in successful ageing. Data were collected in only two cities of Korea based on convenience sampling. The findings of the study suggest that daily stress and resilience have a statistically significant relationship with successful ageing. Furthermore, resilience is an important influential factor and a much-needed personal characteristic for one's successful ageing. Nurses can advocate joining with health and social policy makers to implement policies on healthy ageing, including evaluation of stress, education programmes and implementation of self-help groups to enhance resilience in older people. © 2016 International Council of Nurses.

High prevalence of refractive errors in a rural population: 'Nooravaran Salamat' Mobile Eye Clinic experience.

PubMed

Hashemi, Hassan; Rezvan, Farhad; Ostadimoghaddam, Hadi; Abdollahi, Majid; Hashemi, Maryam; Khabazkhoob, Mehdi

2013-01-01

The prevalence of myopia and hyperopia and determinants were determined in a rural population of Iran. Population-based cross-sectional study. Using random cluster sampling, 13 of the 83 villages of Khaf County in the north east of Iran were selected. Data from 2001 people over the age of 15 years were analysed. Visual acuity measurement, non-cycloplegic refraction and eye examinations were done at the Mobile Eye Clinic. The prevalence of myopia and hyperopia based on spherical equivalent worse than -0.5 dioptre and +0.5 dioptre, respectively. The prevalence of myopia, hyperopia and anisometropia in the total study sample was 28% (95% confidence interval: 25.9-30.2), 19.2% (95% confidence interval: 17.3-21.1), and 11.5% (95% confidence interval: 10.0-13.1), respectively. In the over 40 population, the prevalence of myopia and hyperopia was 32.5% (95% confidence interval: 28.9-36.1) and 27.9% (95% confidence interval: 24.5-31.3), respectively. In the multiple regression model for this group, myopia strongly correlated with cataract (odds ratio = 1.98 and 95% confidence interval: 1.33-2.93), and hyperopia only correlated with age (P < 0.001). The prevalence of high myopia and high hyperopia was 1.5% and 4.6%. In the multiple regression model, anisometropia significantly correlated with age (odds ratio = 1.04) and cataract (odds ratio = 5.2) (P < 0.001). The prevalence of myopia and anisometropia was higher than that in previous studies in urban population of Iran, especially in the elderly. Cataract was the only variable that correlated with myopia and anisometropia. © 2013 The Authors. Clinical and Experimental Ophthalmology © 2013 Royal Australian and New Zealand College of Ophthalmologists.

Short communication: Genetic correlation and heritability of milk coagulation traits within and across lactations in Holstein cows using multiple-lactation random regression animal models.

PubMed

Pretto, D; Vallas, M; Pärna, E; Tänavots, A; Kiiman, H; Kaart, T

2014-12-01

Genetic parameters of milk rennet coagulation time (RCT) and curd firmness (a30) among the first 3 lactations in Holstein cows were estimated. The data set included 39,960 test-day records from 5,216 Estonian Holstein cows (the progeny of 306 sires), which were recorded from April 2005 to May 2010 in 98 herds across the country. A multiple-lactation random regression animal model was used. Individual milk samples from each cow were collected during routine milk recording. These samples were analyzed for milk composition and coagulation traits with intervals of 2 to 3 mo in each lactation (7 to 305 DIM) and from first to third lactation. Mean heritabilities were 0.36, 0.32, and 0.28 for log-transformed RCT [ln(RCT)] and 0.47, 0.40, and 0.62 for a30 for parities 1, 2, and 3, respectively. Mean repeatabilities for ln(RCT) were 0.53, 0.55, and 0.56, but 0.59, 0.61, and 0.68 for a30 for parities 1, 2 and 3, respectively. Mean genetic correlations between ln(RCT) and a30 were -0.19, -0.14, and 0.02 for parities 1, 2, and 3, respectively. Mean genetic correlations were 0.91, 0.79, and 0.99 for ln(RCT), and 0.95, 0.94, and 0.94 for a30 between parities 1 and 2, 1 and 3, and 2 and 3, respectively. Due to these high genetic correlations, we concluded that for a proper genetic evaluation of milk coagulation properties it is sufficient to record RCT and a30 only in the first lactation. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Effect of knee osteoarthritis on the perception of quality of life in Venezuelan patients.

PubMed

Chacón, José G; González, Nancy E; Véliz, Aleida; Losada, Benito R; Paul, Hernando; Santiago, Luís G; Antúnez, Ana; Finol, Yelitza; González, María E; Granados, Isabel; Maldonado, Irama; Maldonado, Teolinda; Marín, Francisco; Zambrano, Gisela; Rodríguez, Martín A

2004-06-15

To measure the perception of quality of life in Venezuelan patients with knee osteoarthritis and to identify those variables that may influence it. A multicenter, cross-sectional study of 126 mestizo patients with knee osteoarthritis recruited from 8 rheumatology centers in Venezuela. We used a Spanish-translated version of the Arthritis Impact Measurement Scales (AIMS), as adapted in Venezuela. One-way analysis of variance was used to compare the AIMS mean total score among subgroups of knee pain, anatomic stage, and socioeconomic status (SES); a post-hoc test was performed to identify significant intragroup differences. Pearson's correlation coefficient was used to examine correlations between age, body mass index (BMI), disease duration, knee pain, and AIMS score. Associations between radiologic stage, SES, and AIMS scores were examined using Spearman's rank correlation. Multiple regression analysis was used to estimate predictor factors of AIMS scores. A significant correlation was found between total AIMS scores and knee pain, age, and socioeconomic status, but not with BMI, disease duration, or anatomic stage. Patients with severe knee pain differed from those with mild and moderate pain, and the highest AIMS mean total score was seen in patients within the severe knee pain subset. Patients in the highest socioeconomic levels differed from those within lowest categories. Patients classified as being at the levels of relative and critical poverty showed the highest AIMS scores. Multiple regression analysis showed that knee pain was the only variable that exerted an independent effect on the quality of life in our patients. The perception of quality of life is negatively affected by increasing levels of joint pain, old age, and low socioeconomic status in Venezuelan patients with knee osteoarthritis. Our study supports the need for an early and vigorous approach to treat pain in this group of patients.

Prediction of Maximal Oxygen Uptake by Six-Minute Walk Test and Body Mass Index in Healthy Boys.

PubMed

Jalili, Majid; Nazem, Farzad; Sazvar, Akbar; Ranjbar, Kamal

2018-05-14

To develop an equation to predict maximal oxygen uptake (VO2max) based on the 6-minute walk test (6MWT) and body composition in healthy boys. Direct VO2max, 6-minute walk distance, and anthropometric characteristics were measured in 349 healthy boys (12.49 ± 2.72 years). Multiple regression analysis was used to generate VO2max prediction equations. Cross-validation of the VO2max prediction equations was assessed with predicted residual sum of squares statistics. Pearson correlation was used to assess the correlation between measured and predicted VO2max. Objectively measured VO2max had a significant correlation with demographic and 6MWT characteristics (R = 0.11-0.723, P < .01). Multiple regression analysis revealed the following VO2max prediction equation: VO2max (mL/kg/min) = 12.701 + (0.06 × 6-minute walk distance m ) - (0.732 × body mass index kg/m2 ) (R 2 = 0.79, standard error of the estimate [SEE] = 2.91 mL/kg/min, %SEE = 6.9%). There was strong correlation between measured and predicted VO2max (r = 0.875, P < .001). Cross-validation revealed minimal shrinkage (R 2 p = 0.78 and predicted residual sum of squares SEE = 2.99 mL/kg/min). This study provides a relatively accurate and convenient VO2max prediction equation based on the 6MWT and body mass index in healthy boys. This model can be used for evaluation of cardiorespiratory fitness of boys in different settings. Copyright © 2018 Elsevier Inc. All rights reserved.

Multiscale characterization and prediction of monsoon rainfall in India using Hilbert-Huang transform and time-dependent intrinsic correlation analysis

NASA Astrophysics Data System (ADS)

Adarsh, S.; Reddy, M. Janga

2017-07-01

In this paper, the Hilbert-Huang transform (HHT) approach is used for the multiscale characterization of All India Summer Monsoon Rainfall (AISMR) time series and monsoon rainfall time series from five homogeneous regions in India. The study employs the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for multiscale decomposition of monsoon rainfall in India and uses the Normalized Hilbert Transform and Direct Quadrature (NHT-DQ) scheme for the time-frequency characterization. The cross-correlation analysis between orthogonal modes of All India monthly monsoon rainfall time series and that of five climate indices such as Quasi Biennial Oscillation (QBO), El Niño Southern Oscillation (ENSO), Sunspot Number (SN), Atlantic Multi Decadal Oscillation (AMO), and Equatorial Indian Ocean Oscillation (EQUINOO) in the time domain showed that the links of different climate indices with monsoon rainfall are expressed well only for few low-frequency modes and for the trend component. Furthermore, this paper investigated the hydro-climatic teleconnection of ISMR in multiple time scales using the HHT-based running correlation analysis technique called time-dependent intrinsic correlation (TDIC). The results showed that both the strength and nature of association between different climate indices and ISMR vary with time scale. Stemming from this finding, a methodology employing Multivariate extension of EMD and Stepwise Linear Regression (MEMD-SLR) is proposed for prediction of monsoon rainfall in India. The proposed MEMD-SLR method clearly exhibited superior performance over the IMD operational forecast, M5 Model Tree (MT), and multiple linear regression methods in ISMR predictions and displayed excellent predictive skill during 1989-2012 including the four extreme events that have occurred during this period.

Application of factor analysis of infrared spectra for quantitative determination of beta-tricalcium phosphate in calcium hydroxylapatite.

PubMed

Arsenyev, P A; Trezvov, V V; Saratovskaya, N V

1997-01-01

This work represents a method, which allows to determine phase composition of calcium hydroxylapatite basing on its infrared spectrum. The method uses factor analysis of the spectral data of calibration set of samples to determine minimal number of factors required to reproduce the spectra within experimental error. Multiple linear regression is applied to establish correlation between factor scores of calibration standards and their properties. The regression equations can be used to predict the property value of unknown sample. The regression model was built for determination of beta-tricalcium phosphate content in hydroxylapatite. Statistical estimation of quality of the model was carried out. Application of the factor analysis on spectral data allows to increase accuracy of beta-tricalcium phosphate determination and expand the range of determination towards its less concentration. Reproducibility of results is retained.

White light emitting diode as potential replacement of tungsten-halogen lamp for visible spectroscopy system: a case study in the measurement of mango qualities

NASA Astrophysics Data System (ADS)

Chiong, W. L.; Omar, A. F.

2017-07-01

Non-destructive technique based on visible (VIS) spectroscopy using light emitting diode (LED) as lighting was used for evaluation of the internal quality of mango fruit. The objective of this study was to investigate feasibility of white LED as lighting in spectroscopic instrumentation to predict the acidity and soluble solids content of intact Sala Mango. The reflectance spectra of the mango samples were obtained and measured in the visible range (400-700 nm) using VIS spectroscopy illuminated under different white LEDs and tungsten-halogen lamp (pro lamp). Regression models were developed by multiple linear regression to establish the relationship between spectra and internal quality. Direct calibration transfer procedure was then applied between master and slave lighting to check on the acidity prediction results after transfer. Determination of mango acidity under white LED lighting was successfully performed through VIS spectroscopy using multiple linear regression but otherwise for soluble solids content. Satisfactory results were obtained for calibration transfer between LEDs with different correlated colour temperature indicated this technique was successfully used in spectroscopy measurement between two similar light sources in prediction of internal quality of mango.

Test anxiety and academic performance in chiropractic students.

PubMed

Zhang, Niu; Henderson, Charles N R

2014-01-01

Objective : We assessed the level of students' test anxiety, and the relationship between test anxiety and academic performance. Methods : We recruited 166 third-quarter students. The Test Anxiety Inventory (TAI) was administered to all participants. Total scores from written examinations and objective structured clinical examinations (OSCEs) were used as response variables. Results : Multiple regression analysis shows that there was a modest, but statistically significant negative correlation between TAI scores and written exam scores, but not OSCE scores. Worry and emotionality were the best predictive models for written exam scores. Mean total anxiety and emotionality scores for females were significantly higher than those for males, but not worry scores. Conclusion : Moderate-to-high test anxiety was observed in 85% of the chiropractic students examined. However, total test anxiety, as measured by the TAI score, was a very weak predictive model for written exam performance. Multiple regression analysis demonstrated that replacing total anxiety (TAI) with worry and emotionality (TAI subscales) produces a much more effective predictive model of written exam performance. Sex, age, highest current academic degree, and ethnicity contributed little additional predictive power in either regression model. Moreover, TAI scores were not found to be statistically significant predictors of physical exam skill performance, as measured by OSCEs.

Use of a pretest strategy for physical therapist assistant programs to predict success rate on the national physical therapy exam.

PubMed

Sloas, Stacey B; Keith, Becky; Whitehead, Malcolm T

2013-01-01

This study investigated a pretest strategy that identified physical therapist assistant (PTA) students who were at risk of failure on the National Physical Therapy Examination (NPTE). Program assessment data from five cohorts of PTA students (2005-2009) were used to develop a stepwise multiple regression formula that predicted first-time NPTE licensure scores. Data used included the Nelson-Denny Reading Test, grades from eight core courses, grade point average upon admission to the program, and scores from three mock NPTE exams given during the program. Pearson correlation coefficients were calculated between each of the 15 variables and NPTE scores. Stepwise multiple regression analysis was performed using data collected at the ends of the first, second, and third (final) semesters of the program. Data from the class of 2010 were then used to validate the formula. The end-of-program formula accounted for the greatest variance (57%) in predicted scores. Those students scoring below a predicted scaled score of 620 were identified to be at risk of failure of the licensure exam. These students were counseled, and a remedial plan was developed based on regression predictions prior to them sitting for the licensure exam.

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

NASA Astrophysics Data System (ADS)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

Younger age, female sex, and high number of awakenings and arousals predict fatigue in patients with sleep disorders: a retrospective polysomnographic observational study

PubMed Central

Veauthier, Christian

2013-01-01

Background The Fatigue Severity Scale (FSS) is widely used to assess fatigue, not only in the context of multiple sclerosis-related fatigue, but also in many other medical conditions. Some polysomnographic studies have shown high FSS values in sleep-disordered patients without multiple sclerosis. The Modified Fatigue Impact Scale (MFIS) has increasingly been used in order to assess fatigue, but polysomnographic data investigating sleep-disordered patients are thus far unavailable. Moreover, the pathophysiological link between sleep architecture and fatigue measured with the MFIS and the FSS has not been previously investigated. Methods This was a retrospective observational study (n = 410) with subgroups classified according to sleep diagnosis. The statistical analysis included nonparametric correlation between questionnaire results and polysomnographic data, age and sex, and univariate and multiple logistic regression. Results The multiple logistic regression showed a significant relationship between FSS/MFIS values and younger age and female sex. Moreover, there was a significant relationship between FSS values and number of arousals and between MFIS values and number of awakenings. Conclusion Younger age, female sex, and high number of awakenings and arousals are predictive of fatigue in sleep-disordered patients. Further investigations are needed to find the pathophysiological explanation for these relationships. PMID:24109185

Illness perception, treatment beliefs, self-esteem, and self-efficacy as correlates of self-management in multiple sclerosis.

PubMed

Wilski, M; Tasiemski, T

2016-05-01

Self-management of a disease is considered one of the most important factors affecting the treatment outcome. The research on the correlates of self-management in multiple sclerosis (MS) is limited. The aim of this study was to determine if personal factors, such as illness perception, treatment beliefs, self-esteem and self-efficacy, are correlates of self-management in MS. This cross-sectional study included 210 patients with MS who completed Multiple Sclerosis Self-Management Scale - Revised, Brief Illness Perception Questionnaire, Treatment Beliefs Scale, Rosenberg Self-Esteem Scale, and Generalized Self-Efficacy Scale. The patients were recruited from a MS rehabilitation clinic. Demographic data and illness-related problems of the study participants were collected with a self-report survey. Correlation and regression analyses were performed to determine associations between variables. Four factors: age at the time of the study (β = 0.14, P = 0.032), timeline (β = 0.16, P = 0.018), treatment control (β = 0.17, P = 0.022), and general self-efficacy (β = 0.19, P = 0.014) turned out to be the significant correlates of self-management in MS. The model including these variables explained 25% of variance in self-management in MS. Personal factors, such as general self-efficacy, perception of treatment control and realistic MS timeline perspective, are more salient correlates of self-management in MS than the objective clinical variables, such as the severity, type, and duration of MS. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Bone mineral density and correlation factor analysis in normal Taiwanese children.

PubMed

Shu, San-Ging

2007-01-01

Our aim was to establish reference data and linear regression equations for lumbar bone mineral density (BMD) in normal Taiwanese children. Several influencing factors of lumbar BMD were investigated. Two hundred fifty-seven healthy children were recruited from schools, 136 boys and 121 girls, aged 4-18 years were enrolled on a voluntary basis with written consent. Their height, weight, blood pressure, puberty stage, bone age and lumbar BMD (L2-4) by dual energy x-ray absorptiometry (DEXA) were measured. Data were analyzed using Pearson correlation and stepwise regression tests. All measurements increased with age. Prior to age 8, there was no gender difference. Parameters such as height, weight, and bone age (BA) in girls surpassed boys between ages 8-13 without statistical significance (p> or =0.05). This was reversed subsequently after age 14 in height (p<0.05). BMD difference had the same trend but was not statistically significant either. The influencing power of puberty stage and bone age over BMD was almost equal to or higher than that of height and weight. All the other factors correlated with BMD to variable powers. Multiple linear regression equations for boys and girls were formulated. BMD reference data is provided and can be used to monitor childhood pathological conditions. However, BMD in those with abnormal bone age or pubertal development could need modifications to ensure accuracy.

Peripheral arterial stiffness is associated with higher baseline plasma uric acid: A prospective cohort study.

PubMed

Ding, Xiaohan; Ye, Ping; Wang, Xiaona; Cao, Ruihua; Yang, Xu; Xiao, Wenkai; Zhang, Yun; Bai, Yongyi; Wu, Hongmei

2017-03-01

This prospective cohort study aimed at identifying association between uric acid (UA) and peripheral arterial stiffness. A prospective cohort longitudinal study was performed according to an average of 4.8 years' follow-up. The demographic data, anthropometric parameters, peripheral arterial stiffness (carotid-radial pulse-wave velocity, cr-PWV) and biomarker variables including UA were examined at both baseline and follow-up. Pearson's correlations were used to identify the associations between UA and peripheral arterial stiffness. Further logistic regressions were employed to determine the associations between UA and arterial stiffness. At the end of follow-up, 1447 subjects were included in the analyses. At baseline, cr-PWV ( r  = 0.200, p  < 0.001) was closely associated with UA. Furthermore, the follow-up cr-PWV ( r  = 0.145, p  < 0.001) was also strongly correlated to baseline UA in Pearson's correlation analysis. Multiple regressions also indicated the association between follow-up cr-PWV ( β  = 0.493, p  = 0.013) and baseline UA level. Logistic regressions revealed that higher baseline UA level was an independent predictor of arterial stiffness severity assessed by cr-PWV at follow-up cross-section. Peripheral arterial stiffness is closely associated with higher baseline UA level. Furthermore, a higher baseline UA level is an independent risk factor and predictor for peripheral arterial stiffness.

A simple measure of cognitive reserve is relevant for cognitive performance in MS patients.

PubMed

Della Corte, Marida; Santangelo, Gabriella; Bisecco, Alvino; Sacco, Rosaria; Siciliano, Mattia; d'Ambrosio, Alessandro; Docimo, Renato; Cuomo, Teresa; Lavorgna, Luigi; Bonavita, Simona; Tedeschi, Gioacchino; Gallo, Antonio

2018-05-04

Cognitive reserve (CR) contributes to preserve cognition despite brain damage. This theory has been applied to multiple sclerosis (MS) to explain the partial relationship between cognition and MRI markers of brain pathology. Our aim was to determine the relationship between two measures of CR and cognition in MS. One hundred and forty-seven MS patients were enrolled. Cognition was assessed using the Rao's Brief Repeatable Battery and the Stroop Test. CR was measured as the vocabulary subtest of the WAIS-R score (VOC) and the number of years of formal education (EDU). Regression analysis included raw score data on each neuropsychological (NP) test as dependent variables and demographic/clinical parameters, VOC, and EDU as independent predictors. A binary logistic regression analysis including clinical/CR parameters as covariates and absence/presence of cognitive deficits as dependent variables was performed too. VOC, but not EDU, was strongly correlated with performances at all ten NP tests. EDU was correlated with executive performances. The binary logistic regression showed that only the Expanded Disability Status Scale (EDSS) and VOC were independently correlated with the presence/absence of CD. The lower the VOC and/or the higher the EDSS, the higher the frequency of CD. In conclusion, our study supports the relevance of CR in subtending cognitive performances and the presence of CD in MS patients.

Predicting in ungauged basins using a parsimonious rainfall-runoff model

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Olav Peerebom, Ivar; Nilsson, Anna

2015-04-01

Prediction in ungauged basins is a demanding, but necessary test for hydrological model structures. Ideally, the relationship between model parameters and catchment characteristics (CC) should be hydrologically justifiable. Many studies, however, report on failure to obtain significant correlations between model parameters and CCs. Under the hypothesis that the lack of correlations stems from non-identifiability of model parameters caused by overparameterization, the relatively new parameter parsimonious DDD (Distance Distribution Dynamics) model was tested for predictions in ungauged basins in Norway. In DDD, the capacity of the subsurface water reservoir M is the only parameter to be calibrated whereas the runoff dynamics is completely parameterised from observed characteristics derived from GIS and runoff recession analysis. Water is conveyed through the soils to the river network by waves with celerities determined by the level of saturation in the catchment. The distributions of distances between points in the catchment to the nearest river reach and of the river network give, together with the celerities, distributions of travel times, and, consequently unit hydrographs. DDD has 6 parameters less to calibrate in the runoff module than, for example, the well-known Swedish HBV model. In this study, multiple regression equations relating CCs and model parameters were trained from 84 calibrated catchments located all over Norway and all model parameters showed significant correlations with catchment characteristics. The significant correlation coefficients (with p- value < 0.05) ranged from 0.22-0.55. The suitability of DDD for predictions in ungauged basins was tested for 17 catchments not used to estimate the multiple regression equations. For 10 of the 17 catchments, deviations in Nash-Suthcliffe Efficiency (NSE) criteria between the calibrated and regionalised model were less than 0.1. The median NSE for the regionalised DDD for the 17 catchments, for two different time series was 0.66 and 0.72. Deviations in NSE between calibrated and regionalised models are well explained by the deviations between calibrated and regressed parameters describing spatial snow distribution and snowmelt, respectively. This latter result indicates the topic for further improvements in the model structure of DDD.

Digital literacy of youth and young adults with intellectual disability predicted by support needs and social maturity.

PubMed

Seok, Soonhwa; DaCosta, Boaventura

2017-01-01

This study investigated relationships between digital propensity and support needs as well as predictors of digital propensity in the context of support intensity, age, gender, and social maturity. A total of 118 special education teachers rated the support intensity, digital propensity, and social maturity of 352 students with intellectual disability. Leveraging the Digital Propensity Index, Supports Intensity Scale, and the Social Maturity Scale, descriptive statistics, correlations, multiple regressions, and regression analyses were employed. The findings revealed significant relationships between digital propensity and support needs. In addition, significant predictors of digital propensity were found with regard to support intensity, age, gender, and social maturity.

Modeling The Skeleton Weight of an Adult Caucasian Man.

PubMed

Avtandilashvili, Maia; Tolmachev, Sergei Y

2018-05-17

The reference value for the skeleton weight of an adult male (10.5 kg) recommended by the International Commission on Radiological Protection in Publication 70 is based on weights of dissected skeletons from 44 individuals, including two U.S. Transuranium and Uranium Registries whole-body donors. The International Commission on Radiological Protection analysis of anatomical data from 31 individuals with known values of body height demonstrated significant correlation between skeleton weight and body height. The corresponding regression equation, Wskel (kg) = -10.7 + 0.119 × H (cm), published in International Commission on Radiological Protection Publication 70 is typically used to estimate the skeleton weight from body height. Currently, the U.S. Transuranium and Uranium Registries holds data on individual bone weights from a total of 40 male whole-body donors, which has provided a unique opportunity to update the International Commission on Radiological Protection skeleton weight vs. body height equation. The original International Commission on Radiological Protection Publication 70 and the new U.S. Transuranium and Uranium Registries data were combined in a set of 69 data points representing a group of 33- to 95-y-old individuals with body heights and skeleton weights ranging from 155 to 188 cm and 6.5 to 13.4 kg, respectively. Data were fitted with a linear least-squares regression. A significant correlation between the two parameters was observed (r = 0.28), and an updated skeleton weight vs. body height equation was derived: Wskel (kg) = -6.5 + 0.093 × H (cm). In addition, a correlation of skeleton weight with multiple variables including body height, body weight, and age was evaluated using multiple regression analysis, and a corresponding fit equation was derived: Wskel (kg) = -0.25 + 0.046 × H (cm) + 0.036 × Wbody (kg) - 0.012 × A (y). These equations will be used to estimate skeleton weights and, ultimately, total skeletal actinide activities for biokinetic modeling of U.S. Transuranium and Uranium Registries partial-body donation cases.

Matrix diffusion coefficients in volcanic rocks at the Nevada test site: influence of matrix porosity, matrix permeability, and fracture coating minerals.

PubMed

Reimus, Paul W; Callahan, Timothy J; Ware, S Doug; Haga, Marc J; Counce, Dale A

2007-08-15

Diffusion cell experiments were conducted to measure nonsorbing solute matrix diffusion coefficients in forty-seven different volcanic rock matrix samples from eight different locations (with multiple depth intervals represented at several locations) at the Nevada Test Site. The solutes used in the experiments included bromide, iodide, pentafluorobenzoate (PFBA), and tritiated water ((3)HHO). The porosity and saturated permeability of most of the diffusion cell samples were measured to evaluate the correlation of these two variables with tracer matrix diffusion coefficients divided by the free-water diffusion coefficient (D(m)/D*). To investigate the influence of fracture coating minerals on matrix diffusion, ten of the diffusion cells represented paired samples from the same depth interval in which one sample contained a fracture surface with mineral coatings and the other sample consisted of only pure matrix. The log of (D(m)/D*) was found to be positively correlated with both the matrix porosity and the log of matrix permeability. A multiple linear regression analysis indicated that both parameters contributed significantly to the regression at the 95% confidence level. However, the log of the matrix diffusion coefficient was more highly-correlated with the log of matrix permeability than with matrix porosity, which suggests that matrix diffusion coefficients, like matrix permeabilities, have a greater dependence on the interconnectedness of matrix porosity than on the matrix porosity itself. The regression equation for the volcanic rocks was found to provide satisfactory predictions of log(D(m)/D*) for other types of rocks with similar ranges of matrix porosity and permeability as the volcanic rocks, but it did a poorer job predicting log(D(m)/D*) for rocks with lower porosities and/or permeabilities. The presence of mineral coatings on fracture walls did not appear to have a significant effect on matrix diffusion in the ten paired diffusion cell experiments.

Economic Expansion Is a Major Determinant of Physician Supply and Utilization

PubMed Central

Cooper, Richard A; Getzen, Thomas E; Laud, Prakash

2003-01-01

Objective To assess the relationship between levels of economic development and the supply and utilization of physicians. Data Sources Data were obtained from the American Medical Association, American Osteopathic Association, Organization for Economic Cooperation and Development (OECD), Bureau of Health Professions, Bureau of Labor Statistics, Bureau of Economic Analysis, Census Bureau, Health Care Financing Administration, and historical sources. Study Design Economic development, expressed as real per capita gross domestic product (GDP) or personal income, was correlated with per capita health care labor and physician supply within countries and states over periods of time spanning 25–70 years and across countries, states, and metropolitan statistical areas (MSAs) at multiple points in time over periods of up to 30 years. Longitudinal data were analyzed in four complementary ways: (1) simple univariate regressions; (2) regressions in which temporal trends were partialled out; (3) time series comparing percentage differences across segments of time; and (4) a bivariate Granger causality test. Cross-sectional data were assessed at multiple time points by means of univariate regression analyses. Principal Findings Under each analytic scenario, physician supply correlated with differences in GDP or personal income. Longitudinal correlations were associated with temporal lags of approximately 5 years for health employment and 10 years for changes in physician supply. The magnitude of changes in per capita physician supply in the United States was equivalent to differences of approximately 0.75 percent for each 1.0 percent difference in GDP. The greatest effects of economic expansion were on the medical specialties, whereas the surgical and hospital-based specialties were affected to a lesser degree, and levels of economic expansion had little influence on family/general practice. Conclusions Economic expansion has a strong, lagged relationship with changes in physician supply. This suggests that economic projections could serve as a gauge for projecting the future utilization of physician services. PMID:12785567

Matrix diffusion coefficients in volcanic rocks at the Nevada test site: Influence of matrix porosity, matrix permeability, and fracture coating minerals

NASA Astrophysics Data System (ADS)

Reimus, Paul W.; Callahan, Timothy J.; Ware, S. Doug; Haga, Marc J.; Counce, Dale A.

2007-08-01

Diffusion cell experiments were conducted to measure nonsorbing solute matrix diffusion coefficients in forty-seven different volcanic rock matrix samples from eight different locations (with multiple depth intervals represented at several locations) at the Nevada Test Site. The solutes used in the experiments included bromide, iodide, pentafluorobenzoate (PFBA), and tritiated water ( 3HHO). The porosity and saturated permeability of most of the diffusion cell samples were measured to evaluate the correlation of these two variables with tracer matrix diffusion coefficients divided by the free-water diffusion coefficient ( Dm/ D*). To investigate the influence of fracture coating minerals on matrix diffusion, ten of the diffusion cells represented paired samples from the same depth interval in which one sample contained a fracture surface with mineral coatings and the other sample consisted of only pure matrix. The log of ( Dm/ D*) was found to be positively correlated with both the matrix porosity and the log of matrix permeability. A multiple linear regression analysis indicated that both parameters contributed significantly to the regression at the 95% confidence level. However, the log of the matrix diffusion coefficient was more highly-correlated with the log of matrix permeability than with matrix porosity, which suggests that matrix diffusion coefficients, like matrix permeabilities, have a greater dependence on the interconnectedness of matrix porosity than on the matrix porosity itself. The regression equation for the volcanic rocks was found to provide satisfactory predictions of log( Dm/ D*) for other types of rocks with similar ranges of matrix porosity and permeability as the volcanic rocks, but it did a poorer job predicting log( Dm/ D*) for rocks with lower porosities and/or permeabilities. The presence of mineral coatings on fracture walls did not appear to have a significant effect on matrix diffusion in the ten paired diffusion cell experiments.

A dimensional approach to understanding severity estimates and risk correlates of marijuana abuse and dependence in adults

PubMed Central

WU, LI-TZY; WOODY, GEORGE E.; YANG, CHONGMING; PAN, JENG-JONG; REEVE, BRYCE B.; BLAZER, DAN G.

2012-01-01

While item response theory (IRT) research shows a latent severity trait underlying response patterns of substance abuse and dependence symptoms, little is known about IRT-based severity estimates in relation to clinically relevant measures. In response to increased prevalences of marijuana-related treatment admissions, an elevated level of marijuana potency, and the debate on medical marijuana use, we applied dimensional approaches to understand IRT-based severity estimates for marijuana use disorders (MUDs) and their correlates while simultaneously considering gender- and race/ethnicity-related differential item functioning (DIF). Using adult data from the 2008 National Survey on Drug Use and Health (N=37,897), DSM-IV criteria for MUDs among past-year marijuana users were examined by IRT, logistic regression, and multiple indicators–multiple causes (MIMIC) approaches. Among 6,917 marijuana users, 15% met criteria for a MUD; another 24% exhibited subthreshold dependence. Abuse criteria were highly correlated with dependence criteria (correlation=0.90), indicating unidimensionality; item information curves revealed redundancy in multiple criteria. MIMIC analyses showed that MUD criteria were positively associated with weekly marijuana use, early marijuana use, other substance use disorders, substance abuse treatment, and serious psychological distress. African Americans and Hispanics showed higher levels of MUDs than whites, even after adjusting for race/ethnicity-related DIF. The redundancy in multiple criteria suggests an opportunity to improve efficiency in measuring symptom-level manifestations by removing low-informative criteria. Elevated rates of MUDs among African Americans and Hispanics require research to elucidate risk factors and improve assessments of MUDs for different racial/ethnic groups. PMID:22351489

Possible antecedents and consequences of self-esteem in persons with multiple sclerosis: preliminary evidence from a cross-sectional analysis.

PubMed

Dlugonski, Deirdre; Motl, Robert W

2012-02-01

Persons with multiple sclerosis (MS) have consistently reported lower levels of self-esteem compared with the general population. Despite this, very little is known about the antecedents and consequences of self-esteem in persons with MS. To examine (1) physical activity and social support as potentially modifiable correlates (i.e., antecedents) of self-esteem and (2) physical and psychological health-related quality of life as possible consequences of self-esteem in persons with MS. Participants (N = 46) wore an Actigraph accelerometer for 7 days and then completed a battery of questionnaires, including the Rosenberg Self-Esteem Scale (RSES), Multiple Sclerosis Impact Scale (MSIS-29), and Social Provisions Scale (SPS). The data were analyzed using PASW Statistics 18. Bivariate correlation analysis indicated that average daily step counts (r = .298, p = .026) and social support (r = .366, p = .007) were significantly correlated with self-esteem. Multiple linear regression analysis indicated that only social support was a significant predictor of self-esteem scores (β = .411, p = .004); pedometer steps approached significance as a predictor of self-esteem (β = .178, p = .112). Bivariate correlation analysis further indicated significant negative associations between self-esteem and physical (r = -.391, p = .004) and psychological (r = -.540, p = .0001) domains of health-related quality of life (HRQOL), indicating that higher self-esteem was associated with more positive HRQOL. Social support is a potentially modifiable variable that may be important to target when designing interventions to improve self-esteem and this might have implications for improving physical and psychological HRQOL in persons with MS.

Effects of imputation on correlation: implications for analysis of mass spectrometry data from multiple biological matrices.

PubMed

Taylor, Sandra L; Ruhaak, L Renee; Kelly, Karen; Weiss, Robert H; Kim, Kyoungmi

2017-03-01

With expanded access to, and decreased costs of, mass spectrometry, investigators are collecting and analyzing multiple biological matrices from the same subject such as serum, plasma, tissue and urine to enhance biomarker discoveries, understanding of disease processes and identification of therapeutic targets. Commonly, each biological matrix is analyzed separately, but multivariate methods such as MANOVAs that combine information from multiple biological matrices are potentially more powerful. However, mass spectrometric data typically contain large amounts of missing values, and imputation is often used to create complete data sets for analysis. The effects of imputation on multiple biological matrix analyses have not been studied. We investigated the effects of seven imputation methods (half minimum substitution, mean substitution, k-nearest neighbors, local least squares regression, Bayesian principal components analysis, singular value decomposition and random forest), on the within-subject correlation of compounds between biological matrices and its consequences on MANOVA results. Through analysis of three real omics data sets and simulation studies, we found the amount of missing data and imputation method to substantially change the between-matrix correlation structure. The magnitude of the correlations was generally reduced in imputed data sets, and this effect increased with the amount of missing data. Significant results from MANOVA testing also were substantially affected. In particular, the number of false positives increased with the level of missing data for all imputation methods. No one imputation method was universally the best, but the simple substitution methods (Half Minimum and Mean) consistently performed poorly. © The Author 2016. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Modeling Pan Evaporation for Kuwait by Multiple Linear Regression

PubMed Central

Almedeij, Jaber

2012-01-01

Evaporation is an important parameter for many projects related to hydrology and water resources systems. This paper constitutes the first study conducted in Kuwait to obtain empirical relations for the estimation of daily and monthly pan evaporation as functions of available meteorological data of temperature, relative humidity, and wind speed. The data used here for the modeling are daily measurements of substantial continuity coverage, within a period of 17 years between January 1993 and December 2009, which can be considered representative of the desert climate of the urban zone of the country. Multiple linear regression technique is used with a procedure of variable selection for fitting the best model forms. The correlations of evaporation with temperature and relative humidity are also transformed in order to linearize the existing curvilinear patterns of the data by using power and exponential functions, respectively. The evaporation models suggested with the best variable combinations were shown to produce results that are in a reasonable agreement with observation values. PMID:23226984

A Landsat study of water quality in Lake Okeechobee

NASA Technical Reports Server (NTRS)

Gervin, J. C.; Marshall, M. L.

1976-01-01

This paper uses multiple regression techniques to investigate the relationship between Landsat radiance values and water quality measurements. For a period of over one year, the Central and Southern Florida Flood Control District sampled the water of Lake Okeechobee for chlorophyll, carotenoids, turbidity, and various nutrients at the time of Landsat overpasses. Using an overlay map of the sampling stations, Landsat radiance values were measured from computer compatible tapes using a GE image 100 and averaging over a 22-acre area at each station. These radiance values in four bands were used to form a number of functions (powers, logarithms, exponentials, and ratios), which were then compared with the ground measurements using multiple linear regression techniques. Several dates were used to provide generality and to study possible seasonal variations. Individual correlations were presented for the various water quality parameters and best fit equations were examined for chlorophyll and turbidity. The results and their relationship to past hydrological research were discussed.

Correlates and Predictors of Psychological Distress Among Older Asian Immigrants in California.

PubMed

Chang, Miya; Moon, Ailee

2016-01-01

Psychological distress occurs frequently in older minority immigrants because many have limited social resources and undergo a difficult process related to immigration and acculturation. Despite a rapid increase in the number of Asian immigrants, relatively little research has focused on subgroup mental health comparisons. This study examines the prevalence of psychological distress, and relationship with socio-demographic factors, and health care utilization among older Asian immigrants. Weighted data from Asian immigrants 65 and older from 5 countries (n = 1,028) who participated in the California Health Interview Survey (CHIS) were analyzed descriptively and in multiple linear regressions. The prevalence of psychological distress varied significantly across the 5 ethnic groups, from Filipinos (4.83%) to Chinese (1.64%). General health status, cognitive and physical impairment, and health care utilization are all associated (p < .05) with psychological distress in multiple linear regressions. These findings are similar to those from previous studies. The findings reinforce the need to develop more culturally effective mental health services and outreach programs.

Lower back pain in nurses working in home care: linked to work-family conflict, emotional dissonance, and appreciation?

PubMed

Elfering, Achim; Häfliger, Evelyne; Celik, Zehra; Grebner, Simone

2018-07-01

In industrial countries home care services for elderly people living in the community are growing rapidly. Home care nursing is intensive and the nurses often suffer from musculoskeletal pain. Time pressure and job control are job-related factors linked to the risk of experiencing lower back pain (LBP) and LBP-related work impairment. This survey investigated whether work-family conflict (WFC), emotional dissonance and being appreciated at work have incremental predictive value. Responses were obtained from 125 home care nurses (63% response rate). Multiple linear regression showed that emotional dissonance and being appreciated at work predicted LBP intensity and LBP-related disability independently of time pressure and job control. WFC was not a predictor of LBP-related disability in multiple regression analyses despite a zero-order correlation with it. Redesigning the working pattern of home care nurses to reduce the emotional demands and improve appreciation of their work might reduce the incidence of LBP in this group.

Multivariate meta-analysis for non-linear and other multi-parameter associations

PubMed Central

Gasparrini, A; Armstrong, B; Kenward, M G

2012-01-01

In this paper, we formalize the application of multivariate meta-analysis and meta-regression to synthesize estimates of multi-parameter associations obtained from different studies. This modelling approach extends the standard two-stage analysis used to combine results across different sub-groups or populations. The most straightforward application is for the meta-analysis of non-linear relationships, described for example by regression coefficients of splines or other functions, but the methodology easily generalizes to any setting where complex associations are described by multiple correlated parameters. The modelling framework of multivariate meta-analysis is implemented in the package mvmeta within the statistical environment R. As an illustrative example, we propose a two-stage analysis for investigating the non-linear exposure–response relationship between temperature and non-accidental mortality using time-series data from multiple cities. Multivariate meta-analysis represents a useful analytical tool for studying complex associations through a two-stage procedure. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22807043

Sleep, Internalizing Problems, and Social Withdrawal: Unique Associations in Clinic-Referred Youth With Elevated Sluggish Cognitive Tempo Symptoms.

PubMed

Rondon, Ana T; Hilton, Dane C; Jarrett, Matthew A; Ollendick, Thomas H

2018-02-01

We compared clinic-referred youth with ADHD + sluggish cognitive tempo (SCT; n = 34), ADHD Only ( n = 108), and SCT Only ( n = 22) on demographics, co-occurring symptomatology, comorbid diagnoses, and social functioning. In total, 164 youth (age = 6-17 years, M = 9.97) and their parent(s) presented to an outpatient clinic for a psychoeducational assessment. Between-group analyses and regressions were used to examine study variables. SCT groups were older and exhibited more parent-reported internalizing problems, externalizing problems, sleep problems, and social withdrawal on the Child Behavior Checklist. No significant differences emerged between groups on the Teacher Report Form. Regression analyses involving multiple covariates revealed that SCT symptoms were uniquely related to social withdrawal but not general social problems. Based on parent report, SCT symptoms have a unique relationship with internalizing problems, sleep problems, and social withdrawal. Future research should explore correlates of SCT in youth using multiple informants.

Causes of coal-miner absenteeism. Information Circular/1987

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

Peters, R.H.; Randolph, R.F.

The Bureau of Mines report describes several significant problems associated with absenteeism among underground coal miners. The vast empirical literature on employee absenteeism is reviewed, and a conceptual model of the factors that cause absenteeism among miners is presented. Portions of the model were empirically tested by performing correlational and multiple regression analyses on data collected from a group of 64 underground coal miners. The results of these tests are presented and discussed.

Modeling daily soil temperature over diverse climate conditions in Iran—a comparison of multiple linear regression and support vector regression techniques

NASA Astrophysics Data System (ADS)

Delbari, Masoomeh; Sharifazari, Salman; Mohammadi, Ehsan

2018-02-01

The knowledge of soil temperature at different depths is important for agricultural industry and for understanding climate change. The aim of this study is to evaluate the performance of a support vector regression (SVR)-based model in estimating daily soil temperature at 10, 30 and 100 cm depth at different climate conditions over Iran. The obtained results were compared to those obtained from a more classical multiple linear regression (MLR) model. The correlation sensitivity for the input combinations and periodicity effect were also investigated. Climatic data used as inputs to the models were minimum and maximum air temperature, solar radiation, relative humidity, dew point, and the atmospheric pressure (reduced to see level), collected from five synoptic stations Kerman, Ahvaz, Tabriz, Saghez, and Rasht located respectively in the hyper-arid, arid, semi-arid, Mediterranean, and hyper-humid climate conditions. According to the results, the performance of both MLR and SVR models was quite well at surface layer, i.e., 10-cm depth. However, SVR performed better than MLR in estimating soil temperature at deeper layers especially 100 cm depth. Moreover, both models performed better in humid climate condition than arid and hyper-arid areas. Further, adding a periodicity component into the modeling process considerably improved the models' performance especially in the case of SVR.

Association between Personality Traits and Sleep Quality in Young Korean Women

PubMed Central

Kim, Han-Na; Cho, Juhee; Chang, Yoosoo; Ryu, Seungho

2015-01-01

Personality is a trait that affects behavior and lifestyle, and sleep quality is an important component of a healthy life. We analyzed the association between personality traits and sleep quality in a cross-section of 1,406 young women (from 18 to 40 years of age) who were not reporting clinically meaningful depression symptoms. Surveys were carried out from December 2011 to February 2012, using the Revised NEO Personality Inventory and the Pittsburgh Sleep Quality Index (PSQI). All analyses were adjusted for demographic and behavioral variables. We considered beta weights, structure coefficients, unique effects, and common effects when evaluating the importance of sleep quality predictors in multiple linear regression models. Neuroticism was the most important contributor to PSQI global scores in the multiple regression models. By contrast, despite being strongly correlated with sleep quality, conscientiousness had a near-zero beta weight in linear regression models, because most variance was shared with other personality traits. However, conscientiousness was the most noteworthy predictor of poor sleep quality status (PSQI≥6) in logistic regression models and individuals high in conscientiousness were least likely to have poor sleep quality, which is consistent with an OR of 0.813, with conscientiousness being protective against poor sleep quality. Personality may be a factor in poor sleep quality and should be considered in sleep interventions targeting young women. PMID:26030141

[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.

Prevalence and correlates of positive mental health in Chinese adolescents.

PubMed

Guo, Cheng; Tomson, Göran; Keller, Christina; Söderqvist, Fredrik

2018-02-17

Studies investigating the prevalence of positive mental health and its correlates are still scarce compared to the studies on mental disorders, although there is growing interest of assessing positive mental health in adolescents. So far, no other study examining the prevalence and determinants of positive mental health in Chinese adolescents has been found. The purpose of this study was to assess the prevalence and correlates of positive mental health in Chinese adolescents. This cross-sectional study used a questionnaire including Mental Health Continuum-Short Form (MHC-SF) and items regarding multiple aspects of adolescent life. The sample involved a total of 5399 students from grade 8 and 10 in Weifang, China. Multivariate Logistic regression analyses were performed to evaluate the associations between potential indicators regarding socio-economic situations, life style, social support and school life and positive mental health and calculate odds ratios and 95% confidence intervals. More than half (57.4%) of the participants were diagnosed as flourishing. The correlated factors of positive mental health in regression models included gender, perceived family economy, the occurrence of sibling(s), satisfaction of self-appearance, physical activity, sleep quality, stress, social trust, desire to learn, support from teachers and parents as well as whether being bullied at school (OR ranging from 1.23 to 2.75). The Hosmer-Lemeshow p-value for the final regression model (0.45) indicated adequate model fit. This study gives the first overview on prevalence and correlates of positive mental health in Chinese adolescents. The prevalence of positive mental health in Chinese adolescents is higher than reported in most of the previous studies also using MHC-SF. Our findings suggest that adolescents with advantageous socio-economic situations, life style, social support and school life are experiencing better positive mental health than others.

Deterioration of abstract reasoning ability in mild cognitive impairment and Alzheimer's disease: correlation with regional grey matter volume loss revealed by diffeomorphic anatomical registration through exponentiated lie algebra analysis.

PubMed

Yoshiura, Takashi; Hiwatashi, Akio; Yamashita, Koji; Ohyagi, Yasumasa; Monji, Akira; Takayama, Yukihisa; Kamano, Norihiro; Kawashima, Toshiro; Kira, Jun-Ichi; Honda, Hiroshi

2011-02-01

To determine which brain regions are relevant to deterioration in abstract reasoning as measured by Raven's Colored Progressive Matrices (CPM) in the context of dementia. MR images of 37 consecutive patients including 19 with Alzheimer's disease (AD) and 18 with amnestic mild cognitive impairment (aMCI) were retrospectively analyzed. All patients were administered the CPM. Regional grey matter (GM) volume was evaluated according to the regimens of voxel-based morphometry, during which a non-linear registration algorithm called Diffeomorphic Anatomical Registration Through Exponentiated Lie algebra was employed. Multiple regression analyses were used to map the regions where GM volumes were correlated with CPM scores. The strongest correlation with CPM scores was seen in the left middle frontal gyrus while a region with the largest volume was identified in the left superior temporal gyrus. Significant correlations were seen in 14 additional regions in the bilateral cerebral hemispheres and right cerebellum. Deterioration of abstract reasoning ability in AD and aMCI measured by CPM is related to GM loss in multiple regions, which is in close agreement with the results of previous activation studies.

Mapping of fluoride endemic areas and correlation studies of fluoride with other quality parameters of drinking water of Veppanapalli block of Dharmapuri district in Tamil Nadu.

PubMed

Karthikeyan, G; Sundarraj, A Shunmuga; Elango, K P

2003-10-01

193 drinking water samples from water sources of 27 panchayats of Veppanapalli block of Dharmapuri district of Tamil Nadu were analysed for chemical quality parameters. Based on the fluoride content of the water sources, fluoride maps differentiating regions with high / low fluoride levels were prepared using Isopleth mapping technique. The interdependence among the important chemical quality parameters were assessed using correlation studies. The experimental results of the application of linear and multiple regression equations on the influence of hardness, alkalinity, total dissolved solids and pH on fluoride are discussed.

Determination of organic compounds in water using ultraviolet LED

NASA Astrophysics Data System (ADS)

Kim, Chihoon; Ji, Taeksoo; Eom, Joo Beom

2018-04-01

This paper describes a method of detecting organic compounds in water using an ultraviolet LED (280 nm) spectroscopy system and a photodetector. The LED spectroscopy system showed a high correlation between the concentration of the prepared potassium hydrogen phthalate and that calculated by multiple linear regression, indicating an adjusted coefficient of determination ranging from 0.953-0.993. In addition, a comparison between the performance of the spectroscopy system and the total organic carbon analyzer indicated that the difference in concentration was small. Based on the close correlation between the spectroscopy and photodetector absorbance values, organic measurement with a photodetector could be configured for monitoring.

Population dynamics of pond zooplankton, I. Diaptomus pallidus Herrick

USGS Publications Warehouse

Armitage, K.B.; Saxena, B.; Angino, E.E.

1973-01-01

The simultaneous and lag relationships between 27 environmental variables and seven population components of a perennial calanoid copepod were examined by simple and partial correlations and stepwise regression. The analyses consistently explained more than 70% of the variation of a population component. The multiple correlation coefficient (R) usually was highest in no lag or in 3-week or 4-week lag except for clutch size in which R was highest in 1-week lag. Population control, egg-bearing, and clutch size were affected primarily by environmental components categorized as weather; food apparently was relatively minor in affecting population control or reproduction. ?? 1973 Dr. W. Junk B.V. Publishers.

A spatial analysis of health-related resources in three diverse metropolitan areas

PubMed Central

Smiley, Melissa J.; Diez Roux, Ana V.; Brines, Shannon J.; Brown, Daniel G.; Evenson, Kelly R.; Rodriguez, Daniel A.

2010-01-01

Few studies have investigated the spatial clustering of multiple health-related resources. We constructed 0.5-mile kernel densities of resources for census areas in New York City, NY (n=819 block groups), Baltimore, MD (n=737), and Winston-Salem, NC (n=169). Three of the four resource densities (supermarkets/produce stores, retail areas, and recreational facilities) tended to be correlated with each other, whereas park density was less consistently and sometimes negatively correlated with the others. Blacks were more likely to live in block groups with multiple low resource densities. Spatial regression models showed that block groups with higher proportions of black residents tended to have lower supermarket/produce, retail, and recreational facility densities, although these associations did not always achieve statistical significance. A measure that combined local and neighboring block group racial composition was often a stronger predictor of resources than the local measure alone. Overall, our results from three diverse U.S. cities show that health-related resources are not randomly distributed across space and that disadvantage in multiple domains often clusters with residential racial patterning. PMID:20478737

Patient activation, knowledge, and health literacy association with self-management behaviors in persons with heart failure.

PubMed

Jacobson, Ann F; Sumodi, Veronica; Albert, Nancy M; Butler, Robert S; DeJohn, Lori; Walker, Donna; Dion, Kelly; Tai, Hua-Li Lin; Ross, Donna M

2018-06-14

More evidence is needed about factors that influence self-management behaviors in persons with heart failure. To test a correlational mediation model of the independent variables of health literacy, patient activation, and heart failure knowledge with heart failure self-management behaviors. The study used a prospective, cross-sectional, correlational design. Correlation and multiple regression were used to analyze associations among variables. Of 151 participants, 57% were male, and mean age was 68 years. Heart failure self-management behaviors was positively correlated with patient activation level (p = .0008), but not with health literacy or heart failure knowledge. Persons with heart failure may better manage their condition if sufficiently activated, regardless of their level of health literacy or knowledge of heart failure disease and management processes. Copyright © 2018 Elsevier Inc. All rights reserved.

Some environmental and attitudinal characteristics as predictors of mathematical creativity

NASA Astrophysics Data System (ADS)

Kanhai, Abhishek; Singh, Bhoodev

2017-04-01

There are many things which can be made more useful and interesting through the application of creativity. Self-concept in mathematics and some school environmental factors such as resource adequacy, teachers' support to the students, teachers' classroom control, creative stimulation by the teachers, etc. were selected in the study. The sample of the study comprised 770 seventh grade students. Pearson correlation, multiple correlation, regression equation and multiple discriminant function analyses of variance were used to analyse the data. The result of the study showed that the relationship between mathematical creativity and each attitudinal and environmental characteristic was found to be positive and significant. Index of forecasting efficiency reveals that mathematical creativity may be best predicted by self-concept in mathematics. Environmental factors, resource adequacy and creative stimulation by the teachers' are found to be the most important factors for predicting mathematical creativity, while social-intellectual involvement among students and educational administration of the schools are to be suppressive factors. The multiple correlation between mathematical creativity and attitudinal and school environmental characteristic suggests that the combined contribution of these variables plays a significant role in the development of mathematical creativity. Mahalanobis analysis indicates that self-concept in mathematics and total school environment were found to be contributing significantly to the development of mathematical creativity.

Parent-reported suicidal behavior and correlates among adolescents in China.

PubMed

Liu, Xianchen; Sun, Zhenxiao; Yang, Yanyun

2008-01-01

Suicidal risk begins to increase during adolescence and is associated with multiple biological, psychological, social, and cultural factors. This study examined the prevalence and psychosocial factors of parent-reported suicidal behavior in Chinese adolescents. A community sample of 1920 adolescents in China participated in an epidemiological study. Parents completed a structured questionnaire including child suicidal behavior, illness history, mental health problems, family history, parenting, and family environment. Multiple logistic regression was used for data analysis. Overall, 2.4% of the sample talked about suicide in the previous 6 months, 3.2% had deliberately hurt themselves or attempted suicide, and 5.1% had either suicidal talk or self-harm. The rate of suicidal behavior increased as adolescents aged. Multivariate logistic regression indicated that the following factors were significantly associated with elevated risk for suicidal behavior: depressive/anxious symptoms, poor maternal health, family conflict, and physical punishment of parental discipline style. Suicidal behavior was reported by parents. No causal relationships could be made based on cross-sectional data. The prevalence rate of parent-reported suicidal behavior is markedly lower than self-reported rate in previous research. Depressive/anxious symptoms and multiple family environmental factors are associated with suicidal behavior in Chinese adolescents.

QSRR modeling for diverse drugs using different feature selection methods coupled with linear and nonlinear regressions.

PubMed

Goodarzi, Mohammad; Jensen, Richard; Vander Heyden, Yvan

2012-12-01

A Quantitative Structure-Retention Relationship (QSRR) is proposed to estimate the chromatographic retention of 83 diverse drugs on a Unisphere poly butadiene (PBD) column, using isocratic elutions at pH 11.7. Previous work has generated QSRR models for them using Classification And Regression Trees (CART). In this work, Ant Colony Optimization is used as a feature selection method to find the best molecular descriptors from a large pool. In addition, several other selection methods have been applied, such as Genetic Algorithms, Stepwise Regression and the Relief method, not only to evaluate Ant Colony Optimization as a feature selection method but also to investigate its ability to find the important descriptors in QSRR. Multiple Linear Regression (MLR) and Support Vector Machines (SVMs) were applied as linear and nonlinear regression methods, respectively, giving excellent correlation between the experimental, i.e. extrapolated to a mobile phase consisting of pure water, and predicted logarithms of the retention factors of the drugs (logk(w)). The overall best model was the SVM one built using descriptors selected by ACO. Copyright © 2012 Elsevier B.V. All rights reserved.

Multiple regression analysis in modelling of carbon dioxide emissions by energy consumption use in Malaysia

NASA Astrophysics Data System (ADS)

Keat, Sim Chong; Chun, Beh Boon; San, Lim Hwee; Jafri, Mohd Zubir Mat

2015-04-01

Climate change due to carbon dioxide (CO2) emissions is one of the most complex challenges threatening our planet. This issue considered as a great and international concern that primary attributed from different fossil fuels. In this paper, regression model is used for analyzing the causal relationship among CO2 emissions based on the energy consumption in Malaysia using time series data for the period of 1980-2010. The equations were developed using regression model based on the eight major sources that contribute to the CO2 emissions such as non energy, Liquefied Petroleum Gas (LPG), diesel, kerosene, refinery gas, Aviation Turbine Fuel (ATF) and Aviation Gasoline (AV Gas), fuel oil and motor petrol. The related data partly used for predict the regression model (1980-2000) and partly used for validate the regression model (2001-2010). The results of the prediction model with the measured data showed a high correlation coefficient (R2=0.9544), indicating the model's accuracy and efficiency. These results are accurate and can be used in early warning of the population to comply with air quality standards.

A Comprehensive Analysis of the Correlations between Resting-State Oscillations in Multiple-Frequency Bands and Big Five Traits

PubMed Central

Ikeda, Shigeyuki; Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Yokoyama, Ryoichi; Kotozaki, Yuka; Nakagawa, Seishu; Sekiguchi, Atsushi; Iizuka, Kunio; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Miyauchi, Carlos Makoto; Sakaki, Kohei; Nozawa, Takayuki; Yokota, Susumu; Magistro, Daniele; Kawashima, Ryuta

2017-01-01

Recently, the association between human personality traits and resting-state brain activity has gained interest in neuroimaging studies. However, it remains unclear if Big Five personality traits are represented in frequency bands (~0.25 Hz) of resting-state functional magnetic resonance imaging (fMRI) activity. Based on earlier neurophysiological studies, we investigated the correlation between the five personality traits assessed by the NEO Five-Factor Inventory (NEO-FFI), and the fractional amplitude of low-frequency fluctuation (fALFF) at four distinct frequency bands (slow-5 (0.01–0.027 Hz), slow-4 (0.027–0.073 Hz), slow-3 (0.073–0.198 Hz) and slow-2 (0.198–0.25 Hz)). We enrolled 835 young subjects and calculated the correlations of resting-state fMRI signals using a multiple regression analysis. We found a significant and consistent correlation between fALFF and the personality trait of extraversion at all frequency bands. Furthermore, significant correlations were detected in distinct brain regions for each frequency band. This finding supports the frequency-specific spatial representations of personality traits as previously suggested. In conclusion, our data highlight an association between human personality traits and fALFF at four distinct frequency bands. PMID:28680397

A Comprehensive Analysis of the Correlations between Resting-State Oscillations in Multiple-Frequency Bands and Big Five Traits.

PubMed

Ikeda, Shigeyuki; Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Yokoyama, Ryoichi; Kotozaki, Yuka; Nakagawa, Seishu; Sekiguchi, Atsushi; Iizuka, Kunio; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Miyauchi, Carlos Makoto; Sakaki, Kohei; Nozawa, Takayuki; Yokota, Susumu; Magistro, Daniele; Kawashima, Ryuta

2017-01-01

Recently, the association between human personality traits and resting-state brain activity has gained interest in neuroimaging studies. However, it remains unclear if Big Five personality traits are represented in frequency bands (~0.25 Hz) of resting-state functional magnetic resonance imaging (fMRI) activity. Based on earlier neurophysiological studies, we investigated the correlation between the five personality traits assessed by the NEO Five-Factor Inventory (NEO-FFI), and the fractional amplitude of low-frequency fluctuation (fALFF) at four distinct frequency bands (slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz) and slow-2 (0.198-0.25 Hz)). We enrolled 835 young subjects and calculated the correlations of resting-state fMRI signals using a multiple regression analysis. We found a significant and consistent correlation between fALFF and the personality trait of extraversion at all frequency bands. Furthermore, significant correlations were detected in distinct brain regions for each frequency band. This finding supports the frequency-specific spatial representations of personality traits as previously suggested. In conclusion, our data highlight an association between human personality traits and fALFF at four distinct frequency bands.

Locomotive syndrome is associated not only with physical capacity but also degree of depression.

PubMed

Ikemoto, Tatsunori; Inoue, Masayuki; Nakata, Masatoshi; Miyagawa, Hirofumi; Shimo, Kazuhiro; Wakabayashi, Toshiko; Arai, Young-Chang P; Ushida, Takahiro

2016-05-01

Reports of locomotive syndrome (LS) have recently been increasing. Although physical performance measures for LS have been well investigated to date, studies including psychiatric assessment are still scarce. Hence, the aim of this study was to investigate both physical and mental parameters in relation to presence and severity of LS using a 25-question geriatric locomotive function scale (GLFS-25) questionnaire. 150 elderly people aged over 60 years who were members of our physical-fitness center and displayed well-being were enrolled in this study. Firstly, using the previously determined GLFS-25 cutoff value (=16 points), subjects were divided into two groups accordingly: an LS and non-LS group in order to compare each parameter (age, grip strength, timed-up-and-go test (TUG), one-leg standing with eye open, back muscle and leg muscle strength, degree of depression and cognitive impairment) between the groups using the Mann-Whitney U-test followed by multiple logistic regression analysis. Secondly, a multiple linear regression was conducted to determine which variables showed the strongest correlation with severity of LS. We confirmed 110 people for non-LS (73%) and 40 people for LS using the GLFS-25 cutoff value. Comparative analysis between LS and non-LS revealed significant differences in parameters in age, grip strength, TUG, one-leg standing, back muscle strength and degree of depression (p < 0.006, after Bonferroni correction). Multiple logistic regression revealed that functional decline in grip strength, TUG and one-leg standing and degree of depression were significantly associated with LS. On the other hand, we observed that the significant contributors towards the GLFS-25 score were TUG and degree of depression in multiple linear regression analysis. The results indicate that LS is associated with not only the capacity of physical performance but also the degree of depression although most participants fell under the criteria of LS. Copyright © 2016 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Correlation of Vitamin D status and orthodontic-induced external apical root resorption.

PubMed

Tehranchi, Azita; Sadighnia, Azin; Younessian, Farnaz; Abdi, Amir H; Shirvani, Armin

2017-01-01

Adequate Vitamin D is essential for dental and skeletal health in children and adult. The purpose of this study was to assess the correlation of serum Vitamin D level with external-induced apical root resorption (EARR) following fixed orthodontic treatment. In this cross-sectional study, the prevalence of Vitamin D deficiency (defined by25-hydroxyvitamin-D) was determined in 34 patients (23.5% male; age range 12-23 years; mean age 16.63 ± 2.84) treated with fixed orthodontic treatment. Root resorption of four maxillary incisors was measured using before and after periapical radiographs (136 measured teeth) by means of a design-to-purpose software to optimize data collection. Teeth with a maximum percentage of root resorption (%EARR) were indicated as representative root resorption for each patient. A multiple linear regression model and Pearson correlation coefficient were used to assess the association of Vitamin D status and observed EARR. P < 0.05 was considered statistically significant. The Pearson coefficient between these two variables was determined about 0.15 ( P = 0.38). Regression analysis revealed that Vitamin D status of the patients demonstrated no significant statistical correlation with EARR, after adjustment of confounding variables using linear regression model ( P > 0.05). This study suggests that Vitamin D level is not among the clinical variables that are potential contributors for EARR. The prevalence of Vitamin D deficiency does not differ in patients with higher EARR. These data suggest the possibility that Vitamin D insufficiency may not contribute to the development of more apical root resorption although this remains to be confirmed by further longitudinal cohort studies.

The Relationship of Hypochondriasis to Anxiety, Depressive, and Somatoform Disorders.

PubMed

Scarella, Timothy M; Laferton, Johannes A C; Ahern, David K; Fallon, Brian A; Barsky, Arthur

2016-01-01

Though the phenotype of anxiety about medical illness has long been recognized, there continues to be debate as to whether it is a distinct psychiatric disorder and, if so, to which diagnostic category it belongs. Our objective was to investigate the pattern of psychiatric comorbidity in hypochondriasis (HC) and to assess the relationship of health anxiety to anxiety, depressive, and somatoform disorders. Data were collected as part of a clinical trial on treatment methods for HC. In all, 194 participants meeting criteria for Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) HC were assessed by sociodemographic variables, results of structured diagnostic interviews, and validated instruments for assessing various symptom dimensions of psychopathology. Most of the individuals with HC had comorbid psychiatric illness; the mean number of comorbid diagnoses was 1.4, and 35.1% had HC as their only diagnosis. Participants were more likely to have only comorbid anxiety disorders than only comorbid depressive or somatoform disorders. Multiple regression analysis of continuous measures of symptoms revealed the strongest correlation of health anxiety with anxiety symptoms, and a weaker correlation with somatoform symptoms; in multiple regression analysis, there was no correlation between health anxiety and depressive symptoms. Our findings suggest that the entity of health anxiety (HC in DSM-IV and illness anxiety disorder in DSM-5) is a clinical syndrome distinct from other psychiatric disorders. Analysis of comorbidity patterns and continuous measures of symptoms suggest that its appropriate classification is with anxiety rather than somatoform or mood disorders. Copyright © 2016 The Academy of Psychosomatic Medicine. Published by Elsevier Inc. All rights reserved.

Predictors of caregiver burden in Iranian family caregivers of cancer patients.

PubMed

Mirsoleymani, Seyed Reza; Rohani, Camelia; Matbouei, Mahsa; Nasiri, Malihe; Vasli, Parvaneh

2017-01-01

Caregiver burden threatens the psychological, emotional, functional and even physical health of caregivers. The aims of this study were to determine caregiver burden and family distress and the relationship between them, also to explore predictors of caregiver burden in a sample of Iranian family caregivers of cancer patients. This is a cross-sectional study with correlational design. A total of 104 family caregivers of cancer patients were asked to respond to the Caregiver Burden Inventory (CBI) and the Family Distress Index (FDI) together with a sociodemographic questionnaire. For evaluating the relationship between CBI and FDI scores, the Pearson's product-moment correlation was used. In addition, multiple linear regression analysis was applied to explore the predictive factors of caregiver burden. A high burden was experienced by almost half of the caregivers (48.1%). The FDI mean score was 9.76 ± 5.40 ranged from 0 to 24. A strong positive correlation was found between the caregiver burden and family distress ( r = 0.76). Multiple linear regression results showed the predictive role of FDI score (β = 0.71, P = 0.001), patient's gender (β = -0.25, P = 0.001), and early cancer diagnosis (β =0.13, P = 0.027) in caregiver burden. They could explain 65% of variance in the level of burden in family caregivers. Family nurses should consider the caregivers burden and vulnerability of families with cancer patient, especially if the patient is a male or has a new diagnosis. They should also design special programs for the whole family as a system that family can adapt to the new situation.

Clinical predictors of effective continuous positive airway pressure in patients with obstructive sleep apnea/hypopnea syndrome.

PubMed

Lai, Chi-Chih; Friedman, Michael; Lin, Hsin-Ching; Wang, Pa-Chun; Hwang, Michelle S; Hsu, Cheng-Ming; Lin, Meng-Chih; Chin, Chien-Hung

2015-08-01

To identify standard clinical parameters that may predict the optimal level of continuous positive airway pressure (CPAP) in adult patients with obstructive sleep apnea/hypopnea syndrome (OSAHS). This is a retrospective study in a tertiary academic medical center that included 129 adult patients (117 males and 12 females) with OSAHS confirmed by diagnostic polysomnography (PSG). All OSAHS patients underwent successful full-night manual titration to determine the optimal CPAP pressure level for OSAHS treatment. The PSG parameters and completed physical examination, including body mass index, tonsil size grading, modified Mallampati grade (also known as updated Friedman's tongue position [uFTP]), uvular length, neck circumference, waist circumference, hip circumference, thyroid-mental distance, and hyoid-mental distance (HMD) were recorded. When the physical examination variables and OSAHS disease were correlated singly with the optimal CPAP pressure, we found that uFTP, HMD, and apnea/hypopnea index (AHI) were reliable predictors of CPAP pressures (P = .013, P = .002, and P < .001, respectively, by multiple regression). When all important factors were considered in a stepwise multiple linear regression analysis, a significant correlation with optimal CPAP pressure was formulated by factoring the uFTP, HMD, and AHI (optimal CPAP pressure = 1.01 uFTP + 0.74 HMD + 0.059 AHI - 1.603). This study distinguished the correlation between uFTP, HMD, and AHI with the optimal CPAP pressure. The structure of the upper airway (especially tongue base obstruction) and disease severity may predict the effective level of CPAP pressure. 4. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

Normal reference values for bladder wall thickness on CT in a healthy population.

PubMed

Fananapazir, Ghaneh; Kitich, Aleksandar; Lamba, Ramit; Stewart, Susan L; Corwin, Michael T

2018-02-01

To determine normal bladder wall thickness on CT in patients without bladder disease. Four hundred and nineteen patients presenting for trauma with normal CTs of the abdomen and pelvis were included in our retrospective study. Bladder wall thickness was assessed, and bladder volume was measured using both the ellipsoid formula and an automated technique. Patient age, gender, and body mass index were recorded. Linear regression models were created to account for bladder volume, age, gender, and body mass index, and the multiple correlation coefficient with bladder wall thickness was computed. Bladder volume and bladder wall thickness were log-transformed to achieve approximate normality and homogeneity of variance. Variables that did not contribute substantively to the model were excluded, and a parsimonious model was created and the multiple correlation coefficient was calculated. Expected bladder wall thickness was estimated for different bladder volumes, and 1.96 standard deviation above expected provided the upper limit of normal on the log scale. Age, gender, and bladder volume were associated with bladder wall thickness (p = 0.049, 0.024, and < 0.001, respectively). The linear regression model had an R 2 of 0.52. Age and gender were negligible in contribution to the model, and a parsimonious model using only volume was created for both the ellipsoid and automated volumes (R 2  = 0.52 and 0.51, respectively). Bladder wall thickness correlates with bladder wall volume. The study provides reference bladder wall thicknesses on CT utilizing both the ellipsoid formula and automated bladder volumes.

Sources of variability in satellite-derived estimates of Phytoplankton production in the eastern tropical Pacific

NASA Astrophysics Data System (ADS)

Banse, Karl; Yong, Marina

1990-05-01

As a proxy for satellite (coastal zone color scanner) observations and concurrent measurements of primary production rates, data from 138 stations occupied seasonally during 1967-1968 in the offshore, eastern tropical Pacific were analyzed in terms of six temporal groups and four current regimes. In multiple linear regressions on column production Pt, we found that simulated satellite pigment is generally weakly correlated, but sometimes not correlated with Pt, and that incident irradiance, sea surface temperature, nitrate, transparency, and depths of mixed layer or nitracline assume little or no importance. After a proxy for the light-saturated chlorophyll-specific photosynthetic rate pmax is added, the coefficient of determination (r2) ranges from 0.55 to 0.91 (median of 0.85) for the 10 cases. In stepwise multiple linear regressions the pmax proxy is the best predictor for Pt. Pt can be calculated fairly accurately (on the average, within 10-20%) from satellite pigment, the 10% light depth, and station values (but not from regional or seasonal means) of the pmax proxy; for individual stations the precision is 35-84% (median of 57% for the 10 groupings; p = 0.05) of the means of observed values. At present, pmax cannot be estimated from space; in the data set it is not even highly correlated with irradiance, temperature, and nitrate at depth of occurrence. Therefore extant models for calculating Pt in this tropical ocean have inherent limits of accuracy as well as of precision owing to ignorance about a physiological parameter.

A novel approach to identify genes that determine grain protein deviation in cereals.

PubMed

Mosleth, Ellen F; Wan, Yongfang; Lysenko, Artem; Chope, Gemma A; Penson, Simon P; Shewry, Peter R; Hawkesford, Malcolm J

2015-06-01

Grain yield and protein content were determined for six wheat cultivars grown over 3 years at multiple sites and at multiple nitrogen (N) fertilizer inputs. Although grain protein content was negatively correlated with yield, some grain samples had higher protein contents than expected based on their yields, a trait referred to as grain protein deviation (GPD). We used novel statistical approaches to identify gene transcripts significantly related to GPD across environments. The yield and protein content were initially adjusted for nitrogen fertilizer inputs and then adjusted for yield (to remove the negative correlation with protein content), resulting in a parameter termed corrected GPD. Significant genetic variation in corrected GPD was observed for six cultivars grown over a range of environmental conditions (a total of 584 samples). Gene transcript profiles were determined in a subset of 161 samples of developing grain to identify transcripts contributing to GPD. Principal component analysis (PCA), analysis of variance (ANOVA) and means of scores regression (MSR) were used to identify individual principal components (PCs) correlating with GPD alone. Scores of the selected PCs, which were significantly related to GPD and protein content but not to the yield and significantly affected by cultivar, were identified as reflecting a multivariate pattern of gene expression related to genetic variation in GPD. Transcripts with consistent variation along the selected PCs were identified by an approach hereby called one-block means of scores regression (one-block MSR). © 2014 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Characteristics of Venture Capital Network and Its Correlation with Regional Economy: Evidence from China.

PubMed

Jin, Yonghong; Zhang, Qi; Shan, Lifei; Li, Sai-Ping

2015-01-01

Financial networks have been extensively studied as examples of real world complex networks. In this paper, we establish and study the network of venture capital (VC) firms in China. We compute and analyze the statistical properties of the network, including parameters such as degrees, mean lengths of the shortest paths, clustering coefficient and robustness. We further study the topology of the network and find that it has small-world behavior. A multiple linear regression model is introduced to study the relation between network parameters and major regional economic indices in China. From the result of regression, we find that, economic aggregate (including the total GDP, investment, consumption and net export), upgrade of industrial structure, employment and remuneration of a region are all positively correlated with the degree and the clustering coefficient of the VC sub-network of the region, which suggests that the development of the VC industry has substantial effects on regional economy in China.

Characteristics of Venture Capital Network and Its Correlation with Regional Economy: Evidence from China

PubMed Central

Jin, Yonghong; Zhang, Qi; Shan, Lifei; Li, Sai-Ping

2015-01-01

Financial networks have been extensively studied as examples of real world complex networks. In this paper, we establish and study the network of venture capital (VC) firms in China. We compute and analyze the statistical properties of the network, including parameters such as degrees, mean lengths of the shortest paths, clustering coefficient and robustness. We further study the topology of the network and find that it has small-world behavior. A multiple linear regression model is introduced to study the relation between network parameters and major regional economic indices in China. From the result of regression, we find that, economic aggregate (including the total GDP, investment, consumption and net export), upgrade of industrial structure, employment and remuneration of a region are all positively correlated with the degree and the clustering coefficient of the VC sub-network of the region, which suggests that the development of the VC industry has substantial effects on regional economy in China. PMID:26340555

Identifying Nanoscale Structure-Function Relationships Using Multimodal Atomic Force Microscopy, Dimensionality Reduction, and Regression Techniques.

PubMed

Kong, Jessica; Giridharagopal, Rajiv; Harrison, Jeffrey S; Ginger, David S

2018-05-31

Correlating nanoscale chemical specificity with operational physics is a long-standing goal of functional scanning probe microscopy (SPM). We employ a data analytic approach combining multiple microscopy modes, using compositional information in infrared vibrational excitation maps acquired via photoinduced force microscopy (PiFM) with electrical information from conductive atomic force microscopy. We study a model polymer blend comprising insulating poly(methyl methacrylate) (PMMA) and semiconducting poly(3-hexylthiophene) (P3HT). We show that PiFM spectra are different from FTIR spectra, but can still be used to identify local composition. We use principal component analysis to extract statistically significant principal components and principal component regression to predict local current and identify local polymer composition. In doing so, we observe evidence of semiconducting P3HT within PMMA aggregates. These methods are generalizable to correlated SPM data and provide a meaningful technique for extracting complex compositional information that are impossible to measure from any one technique.

QSAR and docking based semi-synthesis and in vitro evaluation of 18 β-glycyrrhetinic acid derivatives against human lung cancer cell line A-549.

PubMed

Yadav, Dharmendra Kumar; Kalani, Komal; Khan, Feroz; Srivastava, Santosh Kumar

2013-12-01

For the prediction of anticancer activity of glycyrrhetinic acid (GA-1) analogs against the human lung cancer cell line (A-549), a QSAR model was developed by forward stepwise multiple linear regression methodology. The regression coefficient (r(2)) and prediction accuracy (rCV(2)) of the QSAR model were taken 0.94 and 0.82, respectively in terms of correlation. The QSAR study indicates that the dipole moments, size of smallest ring, amine counts, hydroxyl and nitro functional groups are correlated well with cytotoxic activity. The docking studies showed high binding affinity of the predicted active compounds against the lung cancer target EGFR. These active glycyrrhetinic acid derivatives were then semi-synthesized, characterized and in-vitro tested for anticancer activity. The experimental results were in agreement with the predicted values and the ethyl oxalyl derivative of GA-1 (GA-3) showed equal cytotoxic activity to that of standard anticancer drug paclitaxel.

Genotype-phenotype association study via new multi-task learning model

PubMed Central

Huo, Zhouyuan; Shen, Dinggang

2018-01-01

Research on the associations between genetic variations and imaging phenotypes is developing with the advance in high-throughput genotype and brain image techniques. Regression analysis of single nucleotide polymorphisms (SNPs) and imaging measures as quantitative traits (QTs) has been proposed to identify the quantitative trait loci (QTL) via multi-task learning models. Recent studies consider the interlinked structures within SNPs and imaging QTs through group lasso, e.g. ℓ2,1-norm, leading to better predictive results and insights of SNPs. However, group sparsity is not enough for representing the correlation between multiple tasks and ℓ2,1-norm regularization is not robust either. In this paper, we propose a new multi-task learning model to analyze the associations between SNPs and QTs. We suppose that low-rank structure is also beneficial to uncover the correlation between genetic variations and imaging phenotypes. Finally, we conduct regression analysis of SNPs and QTs. Experimental results show that our model is more accurate in prediction than compared methods and presents new insights of SNPs. PMID:29218896

[Association of mineral and bone disorder with increasing PWV in CKD 1-5 patients].

PubMed

Shiota, Jun; Watanabe, Mitsuhiro

2007-01-01

The association between pulse wave velocity(PWV) and chronic kidney disease mineral and bone disorder(CKD-MBD) was investigated in CKD 1-5 patients without dialysis. Pulse pressure(PP), PWV, serum Cr, non-HDL-cholesterol, Alb, Ca, Pi, calcitriol, intact-PTH and BAP were measured in sixty patients not receiving a phosphate binder or vitamin D. Using the relationship between age and baPWV in healthy subjects, we determined delta baPWV(measured baPWV-calculated baPWV) as an index for the effect of CKD-related factors. delta baPWV was significantly higher in diabetic patients (p < 0.00001). Simple regression analysis revealed that delta baPWV was positively correlated with PP (p < 0.05) and Log(intact-PTH) (p < 0.01), but negatively correlated with Log(estimated GFR) and Log(calcitriol) (p < 0.01). Multiple regression analysis revealed that delta baPWV was significantly associated with PP and calcitriol, or PP and intact-PTH. These results suggest a relationship between PWV and CKD-MBD.

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

Preferential reduction of bone mineral density at the femur reflects impairment of physical activity in patients with low-activity rheumatoid arthritis.

PubMed

Sugiguchi, Shigeru; Goto, Hitoshi; Inaba, Masaaki; Nishizawa, Yoshiki

2010-02-01

Bone mineral density (BMD) and factors influencing BMD in rheumatoid arthritis (RA) under good or moderate control were examined to assess management of osteoporosis in RA. BMD of the lumbar spine, femur, and distal radius was measured in 105 female patients with well-controlled RA. Laboratory and clinical variables associated with disease activity were measured in the same subjects, and correlations between these variables and BMD were evaluated. The RA patients showed a greater decrease in BMD of the femoral neck than of the lumbar spine. Age, Health Assessment Questionnaire (HAQ) score, and Larsen damage score had negative correlations with BMD of the femoral neck. In multiple regression analysis of the parameters associated with BMD of the femoral neck in simple regression analysis, an increase in HAQ score showed a negative correlation with BMD of the femoral neck. After initiation of treatment with alendronate (ALN), BMD of the femoral neck increased and correlated with improvement in HAQ score. A decrease in BMD of the femoral neck is a characteristic of RA. This suggests that muscle tonus has more effect than weight-bearing activity on BMD in patients with RA. BMD of the femoral neck is a useful index for general evaluation of RA patients.

Assessment of sleep quality and correlates in a large cohort of Colombian women around menopause.

PubMed

Monterrosa-Castro, Alvaro; Marrugo-Flórez, Martha; Romero-Pérez, Ivette; Fernández-Alonso, Ana M; Chedraui, Peter; Pérez-López, Faustino R

2013-04-01

The aim of this study was to determine the relationship between self-reported sleep quality, menopausal symptom intensity, and correlates (including ethnicity) among middle-aged women. The present cross-sectional study involved 1,078 Colombian women aged 40 to 59 years who completed the Pittsburgh Sleep Quality Index (PSQI), the Menopause Rating Scale (MRS), and a general questionnaire exploring sociodemographic data. The median [interquartile range] age of the whole sample was 49.0 [9.0] years. Among the participants, 45.4% were postmenopausal, 57.2% had increased body mass index values, 13.9% were black, 20.7% had hypertension, 74.1% had a stable partner, and 3.8% used hormone therapy. The prevalence of poor sleep quality was 57.1% (PSQI global score ≥5). Significant correlations between PSQI global scores and MRS total and subscale scores were found. Multiple linear regression analysis found that higher PSQI scores (poorer quality of sleep) correlated with higher MRS psychological and somatic subscale scores (more severe symptoms), smoking habit, and hypertension. Menopause status and black ethnicity were excluded from the final regression model. Despite study limitations, poor sleep quality is highly prevalent in this large middle-aged Colombian female sample and is related to menopausal symptom severity, tobacco use, and presence of hypertension.

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.

Genetic analysis of fat-to-protein ratio, milk yield and somatic cell score of Holstein cows in Japan in the first three lactations by using a random regression model.

PubMed

Nishiura, Akiko; Sasaki, Osamu; Aihara, Mitsuo; Takeda, Hisato; Satoh, Masahiro

2015-12-01

We estimated the genetic parameters of fat-to-protein ratio (FPR) and the genetic correlations between FPR and milk yield or somatic cell score in the first three lactations in dairy cows. Data included 3,079,517 test-day records of 201,138 Holstein cows in Japan from 2006 to 2011. Genetic parameters were estimated with a multiple-trait random regression model in which the records within and between parities were treated as separate traits. The phenotypic values of FPR increased soon after parturition and peaked at 10 to 20 days in milk, then decreased slowly in mid- and late lactation. Heritability estimates for FPR yielded moderate values. Genetic correlations of FPR among parities were low in early lactation. Genetic correlations between FPR and milk yield were positive and low in early lactation, but only in the first lactation. Genetic correlations between FPR and somatic cell score were positive in early lactation and decreased to become negative in mid- to late lactation. By using these results for genetic evaluation it should be possible to improve energy balance in dairy cows. © 2015 Japanese Society of Animal Science.

The correlation between calcaneal valgus angle and asymmetrical thoracic-lumbar rotation angles in patients with adolescent scoliosis.

PubMed

Park, Jaeyong; Lee, Sang Gil; Bae, Jongjin; Lee, Jung Chul

2015-12-01

[Purpose] This study aimed to provide a predictable evaluation method for the progression of scoliosis in adolescents based on quick and reliable measurements using the naked eye, such as the calcaneal valgus angle of the foot, which can be performed at public facilities such as schools. [Subjects and Methods] Idiopathic scoliosis patients with a Cobb's angle of 10° or more (96 females, 22 males) were included in this study. To identify relationships between factors, Pearson's product-moment correlation coefficient was computed. The degree of scoliosis was set as a dependent variable to predict thoracic and lumbar scoliosis using ankle angle and physique factors. Height, weight, and left and right calcaneal valgus angles were set as independent variables; thereafter, multiple regression analysis was performed. This study extracted variables at a significance level (α) of 0.05 by applying a stepwise method, and calculated a regression equation. [Results] Negative correlation (R=-0.266) was shown between lumbar lordosis and asymmetrical lumbar rotation angles. A correlation (R=0.281) was also demonstrated between left calcaneal valgus angles and asymmetrical thoracic rotation angles. [Conclusion] Prediction of scoliosis progress was revealed to be possible through ocular inspection of the calcaneus and Adams forward bending test and the use of a scoliometer.

Correlates of self-injurious, aggressive and destructive behaviour in children under five who are at risk of developmental delay.

PubMed

Petty, J L; Bacarese-Hamilton, M; Davies, L E; Oliver, C

2014-01-01

Several behavioural correlates of self-injury, aggression and destructive behaviour have been identified in children and young adults with intellectual disabilities. This cross-sectional study aimed to further explore these correlates in very young children with developmental delay. Parents of 56 children (40 male) under the age of five years (mean age 2 years 10 months) completed a questionnaire about their child's behaviour and the presence of behavioural correlates, including repetitive, over-active or impulsive behaviour and more severe developmental delay. Parents reported very high prevalence of self-injurious, aggressive and destructive behaviour: 51%, 64% and 51%, respectively. A binary logistic regression revealed that a higher score on a measure of overactive and impulsive behaviour significantly predicted the presence of destructive behaviour. A multiple linear regression revealed that both repetitive behaviour and number of health problems approached significance as independent predictors of severe self-injurious behaviour. Despite the very small sample, several factors emerged as potential predictors of self-injurious, aggressive and destructive behaviour. These findings support the need for further investigation in a larger sample. Confirmation in this age group could help guide the development of targeted early intervention for these behaviours by identifying behavioural risk markers. Copyright © 2013 Elsevier Ltd. All rights reserved.

Relationship between serum bilirubin concentrations and diabetic nephropathy in Shanghai Han's patients with type 1 diabetes mellitus.

PubMed

Li, Xu; Zhang, Lei; Chen, Haibing; Guo, Kaifeng; Yu, Haoyong; Zhou, Jian; Li, Ming; Li, Qing; Li, Lianxi; Yin, Jun; Liu, Fang; Bao, Yuqian; Han, Junfeng; Jia, Weiping

2017-03-31

Recent studies highlight a negative association between total bilirubin concentrations and albuminuria in patients with type 2 diabetes mellitus. Our study evaluated the relationship between bilirubin concentrations and the prevalence of diabetic nephropathy (DN) in Chinese patients with type 1 diabetes mellitus (T1DM). A total of 258 patients with T1DM were recruited and bilirubin concentrations were compared between patients with or without diabetic nephropathy. Multiple stepwise regression analysis was used to examine the relationship between bilirubin concentrations and 24 h urinary microalbumin. Binary logistic regression analysis was performed to assess independent risk factors for diabetic nephropathy. Participants were divided into four groups according to the quartile of total bilirubin concentrations (Q1, 0.20-0.60; Q2, 0.60-0.80; Q3, 0.80-1.00; Q4, 1.00-1.90 mg/dL) and the chi-square test was used to compare the prevalence of DN in patients with T1DM. The median bilirubin level was 0.56 (interquartile: 0.43-0.68 mg/dL) in the DN group, significantly lower than in the non-DN group (0.70 [interquartile: 0.58-0.89 mg/dL], P < 0.001). Spearman's correlational analysis showed bilirubin concentrations were inversely correlated with 24 h urinary microalbumin (r = -0.13, P < 0.05) and multiple stepwise regression analysis showed bilirubin concentrations were independently associated with 24 h urinary microalbumin. In logistic regression analysis, bilirubin concentrations were significantly inversely associated with nephropathy. In addition, in stratified analysis, from the first to the fourth quartile group, increased bilirubin concentrations were associated with decreased prevalence of DN from 21.90% to 2.00%. High bilirubin concentrations are independently and negatively associated with albuminuria and the prevalence of DN in patients with T1DM.

Validation of a food frequency questionnaire measurement of dietary acrylamide intake using hemoglobin adducts of acrylamide and glycidamide

PubMed Central

Wilson, Kathryn M.; Vesper, Hubert W.; Tocco, Paula; Sampson, Laura; Rosén, Johan; Hellenäs, Karl-Erik; Törnqvist, Margareta; Willett, Walter C.

2011-01-01

Objective Acrylamide, a probable human carcinogen, is formed during high-heat cooking of many common foods. The validity of food frequency questionnaire (FFQ) measures of acrylamide intake has not been established. We assessed the validity of acrylamide intake calculated from an FFQ using a biomarker of acrylamide exposure. Methods We calculated acrylamide intake from an FFQ in the Nurses' Health Study II. We measured hemoglobin adducts of acrylamide and its metabolite, glycidamide, in a random sample of 296 women. Correlation and regression analyses were used to assess the relationship between acrylamide intake and adducts. Results The correlation between acrylamide intake and the sum of acrylamide and glycidamide adducts was 0.31 (95% CI: 0.20 – 0.41), adjusted for laboratory batch, energy intake, and age. Further adjustment for BMI, alcohol intake, and correction for random within-person measurement error in adducts gave a correlation of 0.34 (CI: 0.23 – 0.45). The intraclass correlation coefficient for the sum of adducts was 0.77 in blood samples collected 1 to 3 years apart in a subset of 45 women. Intake of several foods significantly predicted adducts in multiple regression. Conclusions Acrylamide intake and hemoglobin adducts of acrylamide and glycidamide were moderately correlated. Within-person consistency in adducts was high over time. PMID:18855107

Musculotendinous Stiffness of Triceps Surae, Maximal Rate of Force Development, and Vertical Jump Performance

PubMed Central

Driss, Tarak; Rouis, Majdi; Jaafar, Hamdi; Vandewalle, Henry

2015-01-01

The relationships between ankle plantar flexor musculotendinous stiffness (MTS) and performance in a countermovement vertical jump (CMJ) and maximal rate of torque development (MRTD) were studied in 27 active men. MTS was studied by means of quick releases at 20 (S 0.2), 40 (S 0.4), 60 (S 0.6), and 80% (S 0.8) of maximal voluntary torque (T MVC). CMJ was not correlated with strength indices but was positively correlated with MRTD/BM, S 0.4/BM. The slope α 2 and intercept β 2 of the torque-stiffness relationships from 40 to 80% T MVC were correlated negatively (α 2) and positively (β 2) with CMJ. The different stiffness indices were not correlated with MRTD. The prediction of CMJ was improved by the introduction of MRTD in multiple regressions between CMJ and stiffness. CMJ was also negatively correlated with indices of curvature of the torque-stiffness relationship. The subjects were subdivided in 3 groups in function of CMJ (groups H, M, and L for high, medium, and low performers, resp.). There was a downward curvature of the torque-stiffness relationship at high torques in group H or M and the torque-stiffness regression was linear in group L only. These results suggested that torque-stiffness relationships with a plateau at high torques are more frequent in the best jumpers. PMID:25710026

Limited common origins of multiple adult health-related behaviors: Evidence from U.S. twins.

PubMed

Sudharsanan, Nikkil; Behrman, Jere R; Kohler, Hans-Peter

2016-12-01

Health-related behaviors are significant contributors to morbidity and mortality in the United States, yet evidence on the underlying causes of the vast within-population variation in behaviors is mixed. While many potential causes of health-related behaviors have been identified-such as schooling, genetics, and environments-little is known on how much of the variation across multiple behaviors is due to a common set of causes. We use three separate datasets on U.S. twins to investigate the degree to which multiple health-related behaviors correlate and can be explained by a common set of factors. We find that aside from smoking and drinking, most behaviors are not strongly correlated among individuals. Based on the results of both within-identical-twins regressions and multivariate behavioral genetics models, we find some evidence that schooling may be related to smoking but not to the covariation between multiple behaviors. Similarly, we find that a large fraction of the variance in each of the behaviors is consistent with genetic factors; however, we do not find strong evidence that a single common set of genes explains variation in multiple behaviors. We find, however, that a large portion of the correlation between smoking and heavy drinking is consistent with common, mostly childhood, environments. This suggests that the initiation and patterns of these two behaviors might arise from a common childhood origin. Research and policy to identify and modify this source may provide a strong way to reduce the population health burden of smoking and heavy drinking. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Association of Insight and Change in Insight with Clinical Symptoms in Depressed Inpatients.

PubMed

He, Hongbo; Chang, Qing; Ma, Yarong

2018-04-25

Lack of insight has been extensively studied and was found to be adversely correlated with impaired treatment compliance and worse long term clinical outcomes among patients with schizophrenia, while not much is known about this phenonmenon in patients with severe depression. To explore the correlates of insight and its relation to symptom changes among the most seriously ill patients with affective disorders, those who require hospitalization. Patients hospitalized in a large psychiatric hospital in south China with either major depressive disorder (MDD)(N=55) or bipolar depression (BD) (N=85) based on ICD-10 diagnostic criteria were assessed with the Insight and Treatment Attitudes Questionnaire (ITAQ) one week after admission and at the time of discharge. Clinical symptoms were measured at the same time with the Hamilton Rating Scale for Depression (HAMD-17) and the Depression subscale of the Symptom Check list-90 (SCL-90). Length of stay (LOS), duration of illness, duration of untreated mood disorder, number of previous episodes of depression and previous admissions for depression were documented during interviews with patients and their families and from a review of medical records. Bivariate correlations and multiple regression analysis were used to examine the relationship of sociodemographic characteristics, clinical symptomatology and clinical history, to insight at the time of admission. The relationships between change in clinical symptoms and change in insight from admission to discharge were also examined. Stepwise multiple regression models suggested that any previous admissions for depression and higher anxiety factor scores on the HAMD-17 are significant independent predictors of insight accounting for 22.9% of the variance. Multiple regression analysis residual change scores (change scores adjusted for baseline values) on the ITAQ showed that improved insight over average stays of 51 days were inversely related to the residual psychomotor retardation factor on the HAMD-17 accounting for 9.1% of the variance. More severe anxiety symptoms and previous hospitalization for depression were associated with greater insight into illness at admission. Reduction of motor retardation symptoms during treatment was associated with greater improvement in insight to the time of discharge. The patients who are sicker at admission and who show more improvement in psychomotor retardation show the greatest insight.

The Association of Insight and Change in Insight with Clinical Symptoms in Depressed Inpatients

PubMed Central

HE, Hongbo; CHANG, Qing; MA, Yarong

2018-01-01

Background Lack of insight has been extensively studied and was found to be adversely correlated with impaired treatment compliance and worse long term clinical outcomes among patients with schizophrenia, while not much is known about this phenonmenon in patients with severe depression. Aim To explore the correlates of insight and its relation to symptom changes among the most seriously ill patients with affective disorders, those who require hospitalization. Methods Patients hospitalized in a large psychiatric hospital in south China with either major depressive disorder (MDD)(N=55) or bipolar depression (BD) (N=85) based on ICD-10 diagnostic criteria were assessed with the Insight and Treatment Attitudes Questionnaire (ITAQ) one week after admission and at the time of discharge. Clinical symptoms were measured at the same time with the Hamilton Rating Scale for Depression (HAMD-17) and the Depression subscale of the Symptom Check list-90 (SCL-90). Length of stay (LOS), duration of illness, duration of untreated mood disorder, number of previous episodes of depression and previous admissions for depression were documented during interviews with patients and their families and from a review of medical records. Bivariate correlations and multiple regression analysis were used to examine the relationship of sociodemographic characteristics, clinical symptomatology and clinical history, to insight at the time of admission. The relationships between change in clinical symptoms and change in insight from admission to discharge were also examined. Results Stepwise multiple regression models suggested that any previous admissions for depression and higher anxiety factor scores on the HAMD-17 are significant independent predictors of insight accounting for 22.9% of the variance. Multiple regression analysis residual change scores (change scores adjusted for baseline values) on the ITAQ showed that improved insight over average stays of 51 days were inversely related to the residual psychomotor retardation factor on the HAMD-17 accounting for 9.1% of the variance. Conclusions More severe anxiety symptoms and previous hospitalization for depression were associated with greater insight into illness at admission. Reduction of motor retardation symptoms during treatment was associated with greater improvement in insight to the time of discharge. The patients who are sicker at admission and who show more improvement in psychomotor retardation show the greatest insight. PMID:29736131

Alternative methods for CYP2D6 phenotyping: comparison of dextromethorphan metabolic ratios from AUC, single point plasma, and urine.

PubMed

Chen, Rui; Wang, Haotian; Shi, Jun; Hu, Pei

2016-05-01

CYP2D6 is a high polymorphic enzyme. Determining its phenotype before CYP2D6 substrate treatment can avoid dose-dependent adverse events or therapeutic failures. Alternative phenotyping methods of CYP2D6 were compared to aluate the appropriate and precise time points for phenotyping after single-dose and ultiple-dose of 30-mg controlled-release (CR) dextromethorphan (DM) and to explore the antimodes for potential sampling methods. This was an open-label, single and multiple-dose study. 21 subjects were assigned to receive a single dose of CR DM 30 mg orally, followed by a 3-day washout period prior to oral administration of CR DM 30 mg every 12 hours for 6 days. Metabolic ratios (MRs) from AUC∞ after single dosing and from AUC0-12h at steady state were taken as the gold standard. The correlations of metabolic ratios of DM to dextrorphan (MRDM/DX) values based on different phenotyping methods were assessed. Linear regression formulas were derived to calculate the antimodes for potential sample methods. In the single-dose part of the study statistically significant correlations were found between MRDM/DX from AUC∞ and from serial plasma points from 1 to 30 hours or from urine (all p-values < 0.001). In the multiple-dose part, statistically significant correlations were found between MRDM/DX from AUC0-12h on day 6 and MRDM/DX from serial plasma points from 0 to 36 hours after the last dosing (all p-values < 0.001). Based on reported urinary antimode and linear regression analysis, the antimodes of AUC and plasma points were derived to profile the trend of antimodes as the drug concentrations changed. MRDM/DX from plasma points had good correlations with MRDM/DX from AUC. Plasma points from 1 to 30 hours after single dose of 30-mg CR DM and any plasma point at steady state after multiple doses of CR DM could potentially be used for phenotyping of CYP2D6.

Evaluating the Relationships Between NTNU/SINTEF Drillability Indices with Index Properties and Petrographic Data of Hard Igneous Rocks

NASA Astrophysics Data System (ADS)

Aligholi, Saeed; Lashkaripour, Gholam Reza; Ghafoori, Mohammad; Azali, Sadegh Tarigh

2017-11-01

Thorough and realistic performance predictions are among the main requisites for estimating excavation costs and time of the tunneling projects. Also, NTNU/SINTEF rock drillability indices, including the Drilling Rate Index™ (DRI), Bit Wear Index™ (BWI), and Cutter Life Index™ (CLI), are among the most effective indices for determining rock drillability. In this study, brittleness value (S20), Sievers' J-Value (SJ), abrasion value (AV), and Abrasion Value Cutter Steel (AVS) tests are conducted to determine these indices for a wide range of Iranian hard igneous rocks. In addition, relationships between such drillability parameters with petrographic features and index properties of the tested rocks are investigated. The results from multiple regression analysis revealed that the multiple regression models prepared using petrographic features provide a better estimation of drillability compared to those prepared using index properties. Also, it was found that the semiautomatic petrography and multiple regression analyses provide a suitable complement to determine drillability properties of igneous rocks. Based on the results of this study, AV has higher correlations with studied mineralogical indices than AVS. The results imply that, in general, rock surface hardness of hard igneous rocks is very high, and the acidic igneous rocks have a lower strength and density and higher S20 than those of basic rocks. Moreover, DRI is higher, while BWI is lower in acidic igneous rocks, suggesting that drill and blast tunneling is more convenient in these rocks than basic rocks.

Total energy expenditure in adults with cerebral palsy as assessed by doubly labeled water.

PubMed

Johnson, R K; Hildreth, H G; Contompasis, S H; Goran, M I

1997-09-01

To characterize total energy expenditure (TEE) in free-living adults with cerebral palsy (CP) using the doubly labeled water technique, and to determine those physiologic variables and characteristics of CP that were markers of TEE in adults with CP. TEE was measured using the doubly labeled water technique in 30 free-living adults with CP (12 women, 18 men). To determine the best markers of TEE, the following factors were examined: CP status, resting metabolic rate (RMR), anthropometric characteristics and body composition by means of dual-energy x-ray absorptiometry (DXA) and skinfold thickness measurements, energy cost of leisure-time activities, and oral-motor impairment. Means +/- standard deviations, t tests, Pearson product-moment correlation coefficients, Spearman rank correlation coefficients, chi 2, stepwise multiple-correlation regression analysis, and analysis of covariance were used to examine the relationships among variables of interest. TEE was highly variable in the sample (mean = 2,455 +/- 622 kcal/day for men and 1,986 +/- 363 kcal/day for women). Stepwise regression analysis showed that TEE was best predicted in the sample by RMR, percentage body fat determined by DXA, ambulation status, and sex (multiple R = .68, P = .003). When practical, easily measured variables were used, TEE was best predicted by height, ambulation status, percentage body fat by skinfold thickness measurements, and sex (multiple R = .61, P. = 018). The contribution of energy expended in physical activity to TEE was significantly higher in the ambulatory subjects than the nonambulatory subjects (25% vs 16%, respectively; P = .009). The high degree of variability in TEE, largely attributable to high interindividual variation in energy expended in physical activity, makes it difficult to provide general guidelines for energy requirements for adults with CP. Because ambulation status was an important predictor of TEE, it must be accounted for in estimating energy requirements in this population.

Skeletal height estimation from regression analysis of sternal lengths in a Northwest Indian population of Chandigarh region: a postmortem study.

PubMed

Singh, Jagmahender; Pathak, R K; Chavali, Krishnadutt H

2011-03-20

Skeletal height estimation from regression analysis of eight sternal lengths in the subjects of Chandigarh zone of Northwest India is the topic of discussion in this study. Analysis of eight sternal lengths (length of manubrium, length of mesosternum, combined length of manubrium and mesosternum, total sternal length and first four intercostals lengths of mesosternum) measured from 252 male and 91 female sternums obtained at postmortems revealed that mean cadaver stature and sternal lengths were more in North Indians and males than the South Indians and females. Except intercostal lengths, all the sternal lengths were positively correlated with stature of the deceased in both sexes (P < 0.001). The multiple regression analysis of sternal lengths was found more useful than the linear regression for stature estimation. Using multivariate regression analysis, the combined length of manubrium and mesosternum in both sexes and the length of manubrium along with 2nd and 3rd intercostal lengths of mesosternum in males were selected as best estimators of stature. Nonetheless, the stature of males can be predicted with SEE of 6.66 (R(2) = 0.16, r = 0.318) from combination of MBL+BL_3+LM+BL_2, and in females from MBL only, it can be estimated with SEE of 6.65 (R(2) = 0.10, r = 0.318), whereas from the multiple regression analysis of pooled data, stature can be known with SEE of 6.97 (R(2) = 0.387, r = 575) from the combination of MBL+LM+BL_2+TSL+BL_3. The R(2) and F-ratio were found to be statistically significant for almost all the variables in both the sexes, except 4th intercostal length in males and 2nd to 4th intercostal lengths in females. The 'major' sternal lengths were more useful than the 'minor' ones for stature estimation The universal regression analysis used by Kanchan et al. [39] when applied to sternal lengths, gave satisfactory estimates of stature for males only but female stature was comparatively better estimated from simple linear regressions. But they are not proposed for the subjects of known sex, as they underestimate the male and overestimate female stature. However, intercostal lengths were found to be the poor estimators of stature (P < 0.05). And also sternal lengths exhibit weaker correlation coefficients and higher standard errors of estimate. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

The Detection and Interpretation of Interaction Effects between Continuous Variables in Multiple Regression.

ERIC Educational Resources Information Center

Jaccard, James; And Others

1990-01-01

Issues in the detection and interpretation of interaction effects between quantitative variables in multiple regression analysis are discussed. Recent discussions associated with problems of multicollinearity are reviewed in the context of the conditional nature of multiple regression with product terms. (TJH)

Individual risk factors for deep infection and compromised fracture healing after intramedullary nailing of tibial shaft fractures: a single centre experience of 480 patients.

PubMed

Metsemakers, W-J; Handojo, K; Reynders, P; Sermon, A; Vanderschot, P; Nijs, S

2015-04-01

Despite modern advances in the treatment of tibial shaft fractures, complications including nonunion, malunion, and infection remain relatively frequent. A better understanding of these injuries and its complications could lead to prevention rather than treatment strategies. A retrospective study was performed to identify risk factors for deep infection and compromised fracture healing after intramedullary nailing (IMN) of tibial shaft fractures. Between January 2000 and January 2012, 480 consecutive patients with 486 tibial shaft fractures were enrolled in the study. Statistical analysis was performed to determine predictors of deep infection and compromised fracture healing. Compromised fracture healing was subdivided in delayed union and nonunion. The following independent variables were selected for analysis: age, sex, smoking, obesity, diabetes, American Society of Anaesthesiologists (ASA) classification, polytrauma, fracture type, open fractures, Gustilo type, primary external fixation (EF), time to nailing (TTN) and reaming. As primary statistical evaluation we performed a univariate analysis, followed by a multiple logistic regression model. Univariate regression analysis revealed similar risk factors for delayed union and nonunion, including fracture type, open fractures and Gustilo type. Factors affecting the occurrence of deep infection in this model were primary EF, a prolonged TTN, open fractures and Gustilo type. Multiple logistic regression analysis revealed polytrauma as the single risk factor for nonunion. With respect to delayed union, no risk factors could be identified. In the same statistical model, deep infection was correlated with primary EF. The purpose of this study was to evaluate risk factors of poor outcome after IMN of tibial shaft fractures. The univariate regression analysis showed that the nature of complications after tibial shaft nailing could be multifactorial. This was not confirmed in a multiple logistic regression model, which only revealed polytrauma and primary EF as risk factors for nonunion and deep infection, respectively. Future strategies should focus on prevention in high-risk populations such as polytrauma patients treated with EF. Copyright © 2014 Elsevier Ltd. All rights reserved.

Association between overuse of mobile phones on quality of sleep and general health among occupational health and safety students.

PubMed

Eyvazlou, Meysam; Zarei, Esmaeil; Rahimi, Azin; Abazari, Malek

2016-01-01

Concerns about health problems due to the increasing use of mobile phones are growing. Excessive use of mobile phones can affect the quality of sleep as one of the important issues in the health literature and general health of people. Therefore, this study investigated the relationship between the excessive use of mobile phones and general health and quality of sleep on 450 Occupational Health and Safety (OH&S) students in five universities of medical sciences in the North East of Iran in 2014. To achieve this objective, special questionnaires that included Cell Phone Overuse Scale, Pittsburgh's Sleep Quality Index (PSQI) and General Health Questionnaire (GHQ) were used, respectively. In addition to descriptive statistical methods, independent t-test, Pearson correlation, analysis of variance (ANOVA) and multiple regression tests were performed. The results revealed that half of the students had a poor level of sleep quality and most of them were considered unhealthy. The Pearson correlation co-efficient indicated a significant association between the excessive use of mobile phones and the total score of general health and the quality of sleep. In addition, the results of the multiple regression showed that the excessive use of mobile phones has a significant relationship between each of the four subscales of general health and the quality of sleep. Furthermore, the results of the multivariate regression indicated that the quality of sleep has a simultaneous effect on each of the four scales of the general health. Overall, a simultaneous study of the effects of the mobile phones on the quality of sleep and the general health could be considered as a trigger to employ some intervention programs to improve their general health status, quality of sleep and consequently educational performance.

Caries risk assessment in schoolchildren - a form based on Cariogram® software

PubMed Central

CABRAL, Renata Nunes; HILGERT, Leandro Augusto; FABER, Jorge; LEAL, Soraya Coelho

2014-01-01

Identifying caries risk factors is an important measure which contributes to best understanding of the cariogenic profile of the patient. The Cariogram® software provides this analysis, and protocols simplifying the method were suggested. Objectives The aim of this study was to determine whether a newly developed Caries Risk Assessment (CRA) form based on the Cariogram® software could classify schoolchildren according to their caries risk and to evaluate relationships between caries risk and the variables in the form. Material and Methods 150 schoolchildren aged 5 to 7 years old were included in this survey. Caries prevalence was obtained according to International Caries Detection and Assessment System (ICDAS) II. Information for filling in the form based on Cariogram® was collected clinically and from questionnaires sent to parents. Linear regression and a forward stepwise multiple regression model were applied to correlate the variables included in the form with the caries risk. Results Caries prevalence, in primary dentition, including enamel and dentine carious lesions was 98.6%, and 77.3% when only dentine lesions were considered. Eighty-six percent of the children were classified as at moderate caries risk. The forward stepwise multiple regression model result was significant (R2=0.904; p<0.00001), showing that the most significant factors influencing caries risk were caries experience, oral hygiene, frequency of food consumption, sugar consumption and fluoride sources. Conclusion The use of the form based on the Cariogram® software enabled classification of the schoolchildren at low, moderate and high caries risk. Caries experience, oral hygiene, frequency of food consumption, sugar consumption and fluoride sources are the variables that were shown to be highly correlated with caries risk. PMID:25466473

The impact of depression on fatigue in patients with haemodialysis: a correlational study.

PubMed

Bai, Yu-Ling; Lai, Liu-Yuan; Lee, Bih-O; Chang, Yong-Yuan; Chiou, Chou-Ping

2015-07-01

To investigate the fatigue levels and important fatigue predictors for patients undergoing haemodialysis. Fatigue is a common symptom for haemodialysis patients. With its debilitating and distressing effects, it impacts patients in terms of their quality of life while also increasing their mortality rate. A descriptive correlational study. Convenience sampling was conducted at six chosen haemodialysis centres in Southern Taiwan. Data were collected via a structured questionnaire from 193 haemodialysis patients. The scales involved in this study were socio-demographic details, the Center for Epidemiologic Studies Depression Scale, and the Fatigue Scale for haemodialysis patients. Data analysis included percentages, means, standard deviations and hierarchical multiple regression analysis. The fatigue level for haemodialysis patients was in the moderate range. Results from the hierarchical multiple regression analysis indicated that age, employment status, types of medications, physical activity and depression were significant. Of those variables, depression had the greatest impact on the patients' fatigue level, accounting for up to 30·6% of the explanatory power. The total explanatory power of the regression model was 64·2%. This study determined that for haemodialysis patients, unemployment, increased age, taking more medications or lower exercise frequencies resulted in more severe depression, which translated in turn to higher levels of fatigue. Among all these factors, depression had the greatest impact on the patients' fatigue levels. Not only is this finding beneficial to future studies on fatigue as a source of reference, it is also helpful in our understanding of important predictors relating to fatigue in the everyday lives of haemodialysis patients. It is recommended that when caring for fatigued patients, more care should be dedicated to their psychological states, and assistance should be provided in a timely way so as to reduce the amount of fatigue suffered. © 2015 John Wiley & Sons Ltd.

Multivariate random regression analysis for body weight and main morphological traits in genetically improved farmed tilapia (Oreochromis niloticus).

PubMed

He, Jie; Zhao, Yunfeng; Zhao, Jingli; Gao, Jin; Han, Dandan; Xu, Pao; Yang, Runqing

2017-11-02

Because of their high economic importance, growth traits in fish are under continuous improvement. For growth traits that are recorded at multiple time-points in life, the use of univariate and multivariate animal models is limited because of the variable and irregular timing of these measures. Thus, the univariate random regression model (RRM) was introduced for the genetic analysis of dynamic growth traits in fish breeding. We used a multivariate random regression model (MRRM) to analyze genetic changes in growth traits recorded at multiple time-point of genetically-improved farmed tilapia. Legendre polynomials of different orders were applied to characterize the influences of fixed and random effects on growth trajectories. The final MRRM was determined by optimizing the univariate RRM for the analyzed traits separately via penalizing adaptively the likelihood statistical criterion, which is superior to both the Akaike information criterion and the Bayesian information criterion. In the selected MRRM, the additive genetic effects were modeled by Legendre polynomials of three orders for body weight (BWE) and body length (BL) and of two orders for body depth (BD). By using the covariance functions of the MRRM, estimated heritabilities were between 0.086 and 0.628 for BWE, 0.155 and 0.556 for BL, and 0.056 and 0.607 for BD. Only heritabilities for BD measured from 60 to 140 days of age were consistently higher than those estimated by the univariate RRM. All genetic correlations between growth time-points exceeded 0.5 for either single or pairwise time-points. Moreover, correlations between early and late growth time-points were lower. Thus, for phenotypes that are measured repeatedly in aquaculture, an MRRM can enhance the efficiency of the comprehensive selection for BWE and the main morphological traits.

Deriving the Intrahepatic Arteriovenous Shunt Rate from CT Images and Biochemical Data Instead of from Arterial Perfusion Scintigraphy in Hepatic Arterial Infusion Chemotherapy

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

Ozaki, Toshiro, E-mail: ganronbun@amail.plala.or.jp; Seki, Hiroshi; Shiina, Makoto

2009-09-15

The purpose of the present study was to elucidate a method for predicting the intrahepatic arteriovenous shunt rate from computed tomography (CT) images and biochemical data, instead of from arterial perfusion scintigraphy, because adverse exacerbated systemic effects may be induced in cases where a high shunt rate exists. CT and arterial perfusion scintigraphy were performed in patients with liver metastases from gastric or colorectal cancer. Biochemical data and tumor marker levels of 33 enrolled patients were measured. The results were statistically verified by multiple regression analysis. The total metastatic hepatic tumor volume (V{sub metastasized}), residual hepatic parenchyma volume (V{sub residual};more » calculated from CT images), and biochemical data were treated as independent variables; the intrahepatic arteriovenous (IHAV) shunt rate (calculated from scintigraphy) was treated as a dependent variable. The IHAV shunt rate was 15.1 {+-} 11.9%. Based on the correlation matrixes, the best correlation coefficient of 0.84 was established between the IHAV shunt rate and V{sub metastasized} (p < 0.01). In the multiple regression analysis with the IHAV shunt rate as the dependent variable, the coefficient of determination (R{sup 2}) was 0.75, which was significant at the 0.1% level with two significant independent variables (V{sub metastasized} and V{sub residual}). The standardized regression coefficients ({beta}) of V{sub metastasized} and V{sub residual} were significant at the 0.1 and 5% levels, respectively. Based on this result, we can obtain a predicted value of IHAV shunt rate (p < 0.001) using CT images. When a high shunt rate was predicted, beneficial and consistent clinical monitoring can be initiated in, for example, hepatic arterial infusion chemotherapy.« less

Non-destructive evaluation of chlorophyll content in quinoa and amaranth leaves by simple and multiple regression analysis of RGB image components.

PubMed

Riccardi, M; Mele, G; Pulvento, C; Lavini, A; d'Andria, R; Jacobsen, S-E

2014-06-01

Leaf chlorophyll content provides valuable information about physiological status of plants; it is directly linked to photosynthetic potential and primary production. In vitro assessment by wet chemical extraction is the standard method for leaf chlorophyll determination. This measurement is expensive, laborious, and time consuming. Over the years alternative methods, rapid and non-destructive, have been explored. The aim of this work was to evaluate the applicability of a fast and non-invasive field method for estimation of chlorophyll content in quinoa and amaranth leaves based on RGB components analysis of digital images acquired with a standard SLR camera. Digital images of leaves from different genotypes of quinoa and amaranth were acquired directly in the field. Mean values of each RGB component were evaluated via image analysis software and correlated to leaf chlorophyll provided by standard laboratory procedure. Single and multiple regression models using RGB color components as independent variables have been tested and validated. The performance of the proposed method was compared to that of the widely used non-destructive SPAD method. Sensitivity of the best regression models for different genotypes of quinoa and amaranth was also checked. Color data acquisition of the leaves in the field with a digital camera was quick, more effective, and lower cost than SPAD. The proposed RGB models provided better correlation (highest R (2)) and prediction (lowest RMSEP) of the true value of foliar chlorophyll content and had a lower amount of noise in the whole range of chlorophyll studied compared with SPAD and other leaf image processing based models when applied to quinoa and amaranth.

Air Pollutants, Climate, and the Prevalence of Pediatric Asthma in Urban Areas of China

PubMed Central

Zhang, Juanjuan; Yan, Li; Fu, Wenlong; Yi, Jing; Chen, Yuzhi; Liu, Chuanhe; Xu, Dongqun; Wang, Qiang

2016-01-01

Background. Prevalence of childhood asthma varies significantly among regions, while its reasons are not clear yet with only a few studies reporting relevant causes for this variation. Objective. To investigate the potential role of city-average levels of air pollutants and climatic factors in order to distinguish differences in asthma prevalence in China and explain their reasons. Methods. Data pertaining to 10,777 asthmatic patients were obtained from the third nationwide survey of childhood asthma in China's urban areas. Annual mean concentrations of air pollutants and other climatic factors were obtained for the same period from several government departments. Data analysis was implemented with descriptive statistics, Pearson correlation coefficient, and multiple regression analysis. Results. Pearson correlation analysis showed that the situation of childhood asthma was strongly linked with SO2, relative humidity, and hours of sunshine (p < 0.05). Multiple regression analysis indicated that, among the predictor variables in the final step, SO2 was found to be the most powerful predictor variable amongst all (β = −19.572, p < 0.05). Furthermore, results had shown that hours of sunshine (β = −0.014, p < 0.05) was a significant component summary predictor variable. Conclusion. The findings of this study do not suggest that air pollutants or climate, at least in terms of children, plays a major role in explaining regional differences in asthma prevalence in China. PMID:27556031

Relationship between postoperative refractive outcomes and cataract density: multiple regression analysis.

PubMed

Ueda, Tetsuo; Ikeda, Hitoe; Ota, Takeo; Matsuura, Toyoaki; Hara, Yoshiaki

2010-05-01

To evaluate the relationship between cataract density and the deviation from the predicted refraction. Department of Ophthalmology, Nara Medical University, Kashihara, Japan. Axial length (AL) was measured in eyes with mainly nuclear cataract using partial coherence interferometry (IOLMaster). The postoperative AL was measured in pseudophakic mode. The AL difference was calculated by subtracting the postoperative AL from the preoperative AL. Cataract density was measured with the pupil dilated using anterior segment Scheimpflug imaging (EAS-1000). The predicted postoperative refraction was calculated using the SRK/T formula. The subjective refraction 3 months postoperatively was also measured. The mean absolute prediction error (MAE) (mean of absolute difference between predicted postoperative refraction and spherical equivalent of postoperative subjective refraction) was calculated. The relationship between the MAE and cataract density, age, preoperative visual acuity, anterior chamber depth, corneal radius of curvature, and AL difference was evaluated using multiple regression analysis. In the 96 eyes evaluated, the MAE was correlated with cataract density (r = 0.37, P = .001) and the AL difference (r = 0.34, P = .003) but not with the other parameters. The AL difference was correlated with cataract density (r = 0.53, P<.0001). The postoperative refractive outcome was affected by cataract density. This should be taken into consideration in eyes with a higher density cataract. (c) 2010 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

The relationship between turbidity of mouth-rinsed water and oral health status.

PubMed

Takeuchi, Susumu; Ueno, Masayuki; Takehara, Sachiko; Pham, Thuy Anh Vu; Hakuta, Chiyoko; Morishima, Seiji; Shinada, Kayoko; Kawaguchi, Yoko

2013-01-01

The purpose of this study was to examine the relationship between turbidity of mouth rinsed water and oral health status such as dental and periodontal conditions, oral hygiene status, flow rate of saliva and oral bacteria. Subjects were 165 patients who visited the Dental Hospital, Tokyo Medical and Dental University. Oral health status, including dental and periodontal conditions, oral hygiene status and flow rate of saliva, was clinically examined. The turbidity was measured with a turbidimeter. Quantification of Fusobacterium spp, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola and total bacteria levels was performed using real-time PCR. The Pearson correlation and multiple regression analysis were used to explore the associations between the turbidity and oral health parameters. The turbidity showed significant correlations with the number of decayed teeth and deep pockets, the plaque index, extent of tongue coating and Fusobacterium spp, P. gingivalis, T. forsythia, T. denticola and total bacteria levels. In a multiple regression model, the turbidity was negatively associated with the flow rate of saliva and positively associated with the total number of bacteria (p < 0.001). Current findings suggested that turbidity of mouth rinsed water could be used as an indicator to evaluate oral health condition and the amount of bacteria in the oral cavity. In addition, the turbiditimeter appeared as a simple and objective device for screening abnormality of oral health condition at chair side as well as community-based research.

Associations of sleep bruxism with age, sleep apnea, and daytime problematic behaviors in children.

PubMed

Tachibana, M; Kato, T; Kato-Nishimura, K; Matsuzawa, S; Mohri, I; Taniike, M

2016-09-01

The aims of this study were to investigate the prevalence of sleep bruxism in children in Japan, and its relationships with sleep-related factors and daytime problematic behavior. Guardians of 6023 children aged 2-12 years completed the Japanese Sleep Questionnaire. Multiple regression analysis and structural equation modeling were performed. Sleep bruxism was reported in 21.0% children (n = 1263): the prevalence was highest in the age group of 5-7 years (27.4%). Multiple regression analysis showed that sleep bruxism had significant correlations with age 5-7 years (OR: 1.72; P < 0.0001), 'Moves a lot during sleep' (OR: 1.47; P < 0.0001), 'sleeps with mouth open' (OR: 1.56; P < 0.0001), and 'snores loudly' (OR: 1.80; P < 0.0001). In structural equation modeling, sleep bruxism had a significant but weak direct effect on daytime problematic behavior, while sleep bruxism significantly correlated with obstructive sleep apnea, which had a higher direct effect on daytime problematic behavior. Sleep bruxism was reported in 21.0% of Japanese children and had independent relationships with age, movements during sleep, and snoring. A comorbidity of sleep-disordered breathing might be related to daytime problematic behavior in children with sleep bruxism. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Biomechanical, anthropometric, and psychological determinants of barbell back squat strength.

PubMed

Vigotsky, Andrew D; Bryanton, Megan A; Nuckols, Greg; Beardsley, Chris; Contreras, Bret; Evans, Jessica; Schoenfeld, Brad J

2018-02-27

Previous investigations of strength have only focused on biomechanical or psychological determinants, while ignoring the potential interplay and relative contributions of these variables. The purpose of this study was to investigate the relative contributions of biomechanical, anthropometric, and psychological variables to the prediction of maximum parallel barbell back squat strength. Twenty-one college-aged participants (male = 14; female = 7; age = 23 ± 3 years) reported to the laboratory for two visits. The first visit consisted of anthropometric, psychometric, and parallel barbell back squat one-repetition maximum (1RM) testing. On the second visit, participants performed isometric dynamometry testing for the knee, hip, and spinal extensors in a sticking point position-specific manner. Multiple linear regression and correlations were used to investigate the combined and individual relationships between biomechanical, anthropometric, and psychological variables and squat 1RM. Multiple regression revealed only one statistically predictive determinant: fat free mass normalized to height (standardized estimate ± SE = 0.6 ± 0.3; t(16) = 2.28; p = 0.037). Correlation coefficients for individual variables and squat 1RM ranged from r = -0.79-0.83, with biomechanical, anthropometric, experiential, and sex predictors showing the strongest relationships, and psychological variables displaying the weakest relationships. These data suggest that back squat strength in a heterogeneous population is multifactorial and more related to physical rather than psychological variables.

Role of Alexithymia, Anxiety, and Depression in Predicting Self-Efficacy in Academic Students

PubMed Central

2017-01-01

Objective. Little research is available on the predictive factors of self-efficacy in college students. The aim of the present study is to examine the role of alexithymia, anxiety, and depression in predicting self-efficacy in academic students. Design. In a cross-sectional study, a total of 133 students at Babol University of Medical Sciences (Medicine, Dentistry, and Paramedicine) participated in the study between 2014 and 2015. All participants completed the Toronto Alexithymia Scale (TAS-20), College Academic Self-Efficacy Scale (CASES), and 14 items on anxiety and depression derived from the 28 items of the General Health Questionnaire (28-GHQ). Results. Pearson correlation coefficients revealed negative significant relationships between alexithymia and the three subscales with student self-efficacy. There was no significant correlation between anxiety/depression symptoms and student self-efficacy. A backward multiple regression analysis revealed that alexithymia was a negative significant predictor of self-efficacy in academic students (B = −0.512, P < 0.001). The prevalence of alexithymia was 21.8% in students. Multiple backward logistic analysis regression revealed that number of passed semesters, gender, mother's education, father's education, and doctoral level did not accurately predict alexithymia in college students. Conclusion. As alexithymia is prevalent in college students and affects self-efficacy and academic functioning, we suggest it should be routinely evaluated by mental physicians at universities. PMID:28154839

Patient decision-making related to antirheumatic drugs in rheumatoid arthritis: the importance of patient trust of physician.

PubMed

Martin, Richard W; Head, Andrew J; René, Jonathan; Swartz, Timothy J; Fiechtner, Justus J; McIntosh, Barbara A; Holmes-Rovner, Margaret

2008-04-01

To explore how rheumatoid arthritis (RA) antirheumatic drug-specific knowledge and numeric literacy, patient trust in physician, and demographic and disease-related factors relate to the confidence of patient decision-making related to disease modifying antirheumatic drugs (DMARD). Data were analyzed from 628 randomly selected patients with RA receiving care in community rheumatology practices, who responded to a multicenter, cross-sectional mail survey. We used multiple regression models to predict patient confidence in DMARD decision-making related to their most recently initiated DMARD. Significant positive correlation was found between confidence in DMARD decision and trust in physician, DMARD-specific knowledge, and disease duration, but not risk-related numeric literacy, sex, or education. Negative correlations were found with disease severity and current bother with DMARD side effects. A multiple linear regression model of confidence in DMARD decision had an overall R = 0.788, R2 = 0.620 (p < 0.001). The 4 dependent variables contributing significantly to the model were female sex, Medicaid insurance status, satisfaction with RA disease control, and trust in physician, with standardized beta = 0.077, -0.089, 0.147, and 0.687, respectively. In this sample of community patients with RA, the patient trust in physician had substantially greater effect on confidence in DMARD decision than DMARD-specific knowledge, disease-related factors, or demographic characteristics.

The role of family expressed emotion and perceived social support in predicting addiction relapse.

PubMed

Atadokht, Akbar; Hajloo, Nader; Karimi, Masoud; Narimani, Mohammad

2015-03-01

Emotional conditions governing the family and patients' perceived social support play important roles in the treatment or relapse process of the chronic disease. The current study aimed to investigate the role of family expressed emotion and perceived social support in prediction of addiction relapse. The descriptive-correlation method was used in the current study. The study population consisted of the individuals referred to the addiction treatment centers in Ardabil from October 2013 to January 2014. The subjects (n = 80) were randomly selected using cluster sampling method. To collect data, expressed emotion test by Cole and Kazaryan, and Multidimensional Scale of Perceived Social Support (MSPSS) were used, and the obtained data was analyzed using the Pearson's correlation coefficient and multiple regression analyses. Results showed a positive relationship between family expressed emotions and the frequency of relapse (r = 0.26, P = 0.011) and a significant negative relationship between perceived social support and the frequency of relapse (r = -0.34, P = 0.001). Multiple regression analysis also showed that perceived social support from family and the family expressed emotions significantly explained 12% of the total variance of relapse frequency. These results have implications for addicted people, their families and professionals working in addiction centers to use the emotional potential of families especially their expressed emotions and the perceived social support of addicts to increase the success rate of addiction treatment.

Correlates of willingness to engage in residential gardening: implications for health optimization in ibadan, Nigeria.

PubMed

Motunrayo Ibrahim, Fausat

2013-01-01

Gardening is a worthwhile adventure which engenders health op-timization. Yet, a dearth of evidences that highlights motivations to engage in gardening exists. This study examined willingness to engage in gardening and its correlates, including some socio-psychological, health related and socio-demographic variables. In this cross-sectional survey, 508 copies of a structured questionnaire were randomly self administered among a group of civil servants of Oyo State, Nigeria. Multi-item measures were used to assess variables. Step wise multiple regression analysis was used to identify predictors of willingness to engage in gar-dening Results: Simple percentile analysis shows that 71.1% of respondents do not own a garden. Results of step wise multiple regression analysis indicate that descriptive norm of gardening is a good predictor, social support for gardening is better while gardening self efficacy is the best predictor of willingness to engage in gardening (P< 0.001). Health consciousness, gardening response efficacy, education and age are not predictors of this willingness (P> 0.05). Results of t-test and ANOVA respectively shows that gender is not associated with this willingness (P> 0.05), but marital status is (P< 0.05).  Socio-psychological characteristics and being married are very rele-vant in motivations to engage in gardening. The nexus between gardening and health optimization appears to be highly obscured in this population.

Correlates of Willingness to Engage in Residential Gardening: Implications for Health Optimization in Ibadan, Nigeria

PubMed Central

Motunrayo Ibrahim, Fausat

2013-01-01

Background: Gardening is a worthwhile adventure which engenders health op­timization. Yet, a dearth of evidences that highlights motivations to engage in gardening exists. This study examined willingness to engage in gardening and its correlates, including some socio-psychological, health related and socio-demographic variables. Methods: In this cross-sectional survey, 508 copies of a structured questionnaire were randomly self administered among a group of civil servants of Oyo State, Nigeria. Multi-item measures were used to assess variables. Step wise multiple regression analysis was used to identify predictors of willingness to engage in gar­dening Results: Simple percentile analysis shows that 71.1% of respondents do not own a garden. Results of step wise multiple regression analysis indicate that descriptive norm of gardening is a good predictor, social support for gardening is better while gardening self efficacy is the best predictor of willingness to engage in gardening (P< 0.001). Health consciousness, gardening response efficacy, education and age are not predictors of this willingness (P> 0.05). Results of t-test and ANOVA respectively shows that gender is not associated with this willingness (P> 0.05), but marital status is (P< 0.05).  Conclusion: Socio-psychological characteristics and being married are very rele­vant in motivations to engage in gardening. The nexus between gardening and health optimization appears to be highly obscured in this population. PMID:24688974

Role of Alexithymia, Anxiety, and Depression in Predicting Self-Efficacy in Academic Students.

PubMed

Faramarzi, Mahbobeh; Khafri, Soraya

2017-01-01

Objective . Little research is available on the predictive factors of self-efficacy in college students. The aim of the present study is to examine the role of alexithymia, anxiety, and depression in predicting self-efficacy in academic students. Design . In a cross-sectional study, a total of 133 students at Babol University of Medical Sciences (Medicine, Dentistry, and Paramedicine) participated in the study between 2014 and 2015. All participants completed the Toronto Alexithymia Scale (TAS-20), College Academic Self-Efficacy Scale (CASES), and 14 items on anxiety and depression derived from the 28 items of the General Health Questionnaire (28-GHQ). Results . Pearson correlation coefficients revealed negative significant relationships between alexithymia and the three subscales with student self-efficacy. There was no significant correlation between anxiety/depression symptoms and student self-efficacy. A backward multiple regression analysis revealed that alexithymia was a negative significant predictor of self-efficacy in academic students ( B = -0.512, P < 0.001). The prevalence of alexithymia was 21.8% in students. Multiple backward logistic analysis regression revealed that number of passed semesters, gender, mother's education, father's education, and doctoral level did not accurately predict alexithymia in college students. Conclusion . As alexithymia is prevalent in college students and affects self-efficacy and academic functioning, we suggest it should be routinely evaluated by mental physicians at universities.

QSPR study of polychlorinated diphenyl ethers by molecular electronegativity distance vector (MEDV-4).

PubMed

Sun, Lili; Zhou, Liping; Yu, Yu; Lan, Yukun; Li, Zhiliang

2007-01-01

Polychlorinated diphenyl ethers (PCDEs) have received more and more concerns as a group of ubiquitous potential persistent organic pollutants (POPs). By using molecular electronegativity distance vector (MEDV-4), multiple linear regression (MLR) models are developed for sub-cooled liquid vapor pressures (P(L)), n-octanol/water partition coefficients (K(OW)) and sub-cooled liquid water solubilities (S(W,L)) of 209 PCDEs and diphenyl ether. The correlation coefficients (R) and the leave-one-out cross-validation (LOO) correlation coefficients (R(CV)) of all the 6-descriptor models for logP(L), logK(OW) and logS(W,L) are more than 0.98. By using stepwise multiple regression (SMR), the descriptors are selected and the resulting models are 5-descriptor model for logP(L), 4-descriptor model for logK(OW), and 6-descriptor model for logS(W,L), respectively. All these models exhibit excellent estimate capabilities for internal sample set and good predictive capabilities for external samples set. The consistency between observed and estimated/predicted values for logP(L) is the best (R=0.996, R(CV)=0.996), followed by logK(OW) (R=0.992, R(CV)=0.992) and logS(W,L) (R=0.983, R(CV)=0.980). By using MEDV-4 descriptors, the QSPR models can be used for prediction and the model predictions can hence extend the current database of experimental values.

Relationships among symptom severity, coping styles, and quality of life in community-dwelling women with urinary incontinence: a multiple mediator model.

PubMed

Xu, Dongjuan; Liu, Nana; Qu, Haili; Chen, Liqin; Wang, Kefang

2016-01-01

To investigate the relationships among symptom severity, coping styles, and quality of life (QOL) in community-dwelling women with urinary incontinence (UI). A total of 592 women with UI participated in this cross-sectional study. Bivariate Pearson's correlation was used to examine the correlations between symptom severity, coping styles, and QOL. Multivariate regression models and Sobel tests were used to test the mediating effect of coping styles. Additionally, a multiple mediator model was used to examine the mediating role of coping styles collectively. All regression models were adjusted for age, education, marital status, income, duration of UI, and type of UI. Participants tended to use avoidant and palliative coping styles and not use instrumental coping style. Avoidant and palliative coping styles were associated with poor QOL, and partially mediated the association between symptom severity and QOL. Nearly 73% of the adverse effect of symptom severity on QOL was mediated by avoidant and palliative coping styles. The use of avoidant and palliative coping styles was higher with more severe urine leakage, and QOL tended to be poorer. Coping styles should be addressed in UI management. It may be of particular value to look closely at negative coping styles and implement education and training of patients in improving their coping skills related to managing UI, which will in turn improve their QOL.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits.

PubMed

Fu, Liya; Wang, You-Gan

2011-02-15

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which clearly demonstrates the advantages of the rank regression models.

Principals' instructional management skills and middle school science teacher job satisfaction

NASA Astrophysics Data System (ADS)

Gibbs-Harper, Nzinga A.

The purpose of this research study was to determine if a relationship exists between teachers' perceptions of principals' instructional leadership behaviors and middle school teacher job satisfaction. Additionally, this study sought to assess whether principal's instructional leadership skills were predictors of middle school teachers' satisfaction with work itself. This study drew from 13 middle schools in an urban Mississippi school district. Participants included teachers who taught science. Each teacher was given the Principal Instructional Management Rating Scale (PIMRS; Hallinger, 2011) and the Teacher Job Satisfaction Questionnaire (TJSQ; Lester, 1987) to answer the research questions. The study was guided by two research questions: (a) Is there a relationship between the independent variables Defining the School's Mission, Managing the Instructional Program, and Developing the School Learning Climate Program and the dependent variable Work Itself?; (b) Are Defining the School's Mission, Managing the Instructional Program, and Developing the School Learning Climate Program predictors of Work Itself? The Pearson's correlation and multiple regression analysis were utilized to examine the relationship between the three dimensions of principals' instructional leadership and teacher satisfaction with work itself. The data revealed that there was a strong, positive correlation between all three dimensions of principals' instructional leadership and teacher satisfaction with work itself. However, the multiple regression analysis determined that teachers' perceptions of principals' instructional management skills is a slight predictor of Defining the School's Mission only.

Beyond Multiple Regression: Using Commonality Analysis to Better Understand R[superscript 2] Results

ERIC Educational Resources Information Center

Warne, Russell T.

2011-01-01

Multiple regression is one of the most common statistical methods used in quantitative educational research. Despite the versatility and easy interpretability of multiple regression, it has some shortcomings in the detection of suppressor variables and for somewhat arbitrarily assigning values to the structure coefficients of correlated…

Temperament, Beliefs About Pain Control, and Pain Intensity in Endometriosis Patients.

PubMed

Bylinka, Joanna; Oniszczenko, Włodzimierz

2016-12-01

This correlational study investigated the relationships between temperament, beliefs about pain control, and pain intensity ratings in a group of 103 women diagnosed with endometriosis. Temperament traits were assessed using the Formal Characteristics of Behaviour-Temperament Inventory. Beliefs about pain control were measured using the Polish version of the Beliefs about Pain Control Questionnaire. The Numerical Rating Scale (NRS-11) was used to measure pain intensity. There was a high negative correlation between the temperament trait of endurance and pain intensity ratings. Moderate negative correlations with pain intensity were found for internal beliefs about pain control. Hierarchical multiple regression analysis indicated that the endurance trait and internal beliefs about pain control accounted for 33 % of the variance in pain intensity ratings in women with endometriosis.

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

A clinical study of electrophysiological correlates of behavioural comfort levels in cochlear implantees.

PubMed

Raghunandhan, S; Ravikumar, A; Kameswaran, Mohan; Mandke, Kalyani; Ranjith, R

2014-05-01

Indications for cochlear implantation have expanded today to include very young children and those with syndromes/multiple handicaps. Programming the implant based on behavioural responses may be tedious for audiologists in such cases, wherein matching an effective Measurable Auditory Percept (MAP) and appropriate MAP becomes the key issue in the habilitation program. In 'Difficult to MAP' scenarios, objective measures become paramount to predict optimal current levels to be set in the MAP. We aimed to (a) study the trends in multi-modal electrophysiological tests and behavioural responses sequentially over the first year of implant use; (b) generate normative data from the above; (c) correlate the multi-modal electrophysiological thresholds levels with behavioural comfort levels; and (d) create predictive formulae for deriving optimal comfort levels (if unknown), using linear and multiple regression analysis. This prospective study included 10 profoundly hearing impaired children aged between 2 and 7 years with normal inner ear anatomy and no additional handicaps. They received the Advanced Bionics HiRes 90 K Implant with Harmony Speech processor and used HiRes-P with Fidelity 120 strategy. They underwent, impedance telemetry, neural response imaging, electrically evoked stapedial response telemetry (ESRT), and electrically evoked auditory brainstem response (EABR) tests at 1, 4, 8, and 12 months of implant use, in conjunction with behavioural mapping. Trends in electrophysiological and behavioural responses were analyzed using paired t-test. By Karl Pearson's correlation method, electrode-wise correlations were derived for neural response imaging (NRI) thresholds versus most comfortable level (M-levels) and offset based (apical, mid-array, and basal array) correlations for EABR and ESRT thresholds versus M-levels were calculated over time. These were used to derive predictive formulae by linear and multiple regression analysis. Such statistically predicted M-levels were compared with the behaviourally recorded M-levels among the cohort, using Cronbach's alpha reliability test method for confirming the efficacy of this method. NRI, ESRT, and EABR thresholds showed statistically significant positive correlations with behavioural M-levels, which improved with implant use over time. These correlations were used to derive predicted M-levels using regression analysis. On an average, predicted M-levels were found to be statistically reliable and they were a fair match to the actual behavioural M-levels. When applied in clinical practice, the predicted values were found to be useful for programming members of the study group. However, individuals showed considerable deviations in behavioural M-levels, above and below the electrophysiologically predicted values, due to various factors. While the current method appears helpful as a reference to predict initial maps in 'difficult to Map' subjects, it is recommended that behavioural measures are mandatory to further optimize the maps for these individuals. The study explores the trends, correlations and individual variabilities that occur between electrophysiological tests and behavioural responses, recorded over time among a cohort of cochlear implantees. The statistical method shown may be used as a guideline to predict optimal behavioural levels in difficult situations among future implantees, bearing in mind that optimal M-levels for individuals can vary from predicted values. In 'Difficult to MAP' scenarios, following a protocol of sequential behavioural programming, in conjunction with electrophysiological correlates will provide the best outcomes.

Do evoked potentials contribute to the functional follow-up and clinical prognosis of multiple sclerosis?

PubMed

Giffroy, Xavier; Maes, Nathalie; Albert, Adelin; Maquet, Pierre; Crielaard, Jean-Michel; Dive, Dominique

2017-03-01

The clinical variability and complexity of multiple sclerosis (MS) challenges the individual clinical course prognostication. This study aimed to find out whether multimodal evoked potentials (EP) correlate with the motor components of multiple sclerosis functional composite (MSFCm) and predict clinically relevant motor functional deterioration. One hundred MS patients were assessed at baseline (T 0 ) and about 7.5 years later (T 1 ), with visual, somatosensory and motor EP and rated on the Expanded Disability Status Scale (EDSS) and the MSFCm, including the 9 Hole Peg Test and the Timed 25 Foot Walk (T25FW). The Spearman correlation coefficient (r S ) was used to evaluate the cross-sectional and longitudinal relationship between EP Z scores and clinical findings. The predictive value of baseline electrophysiological data for clinical worsening (EDSS, 9-HPT, T25FW, MSFCm) during follow-up was assessed by logistic regression analysis. Unlike longitudinal correlations, cross-sectional correlations between EP Z scores and clinical outcomes were all significant and ranged between 0.22 and 0.67 (p < 0.05). The global EP Z score was systematically predictive of EDSS and MSFCm worsening over time (all p < 0.05). EP latency was a better predictor than amplitude, although weaker than latency and amplitude aggregation in the global EP Z score. The study demonstrates that EP numerical scores can be used for motor function monitoring and outcome prediction in patients with MS.

Short-term electric power demand forecasting based on economic-electricity transmission model

NASA Astrophysics Data System (ADS)

Li, Wenfeng; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Wang, Yubin Mao; Wang, Jiangbo; He, Dandan

2018-04-01

Short-term electricity demand forecasting is the basic work to ensure safe operation of the power system. In this paper, a practical economic electricity transmission model (EETM) is built. With the intelligent adaptive modeling capabilities of Prognoz Platform 7.2, the econometric model consists of three industrial added value and income levels is firstly built, the electricity demand transmission model is also built. By multiple regression, moving averages and seasonal decomposition, the problem of multiple correlations between variables is effectively overcome in EETM. The validity of EETM is proved by comparison with the actual value of Henan Province. Finally, EETM model is used to forecast the electricity consumption of the 1-4 quarter of 2018.

Deaf college students' mathematical skills relative to morphological knowledge, reading level, and language proficiency.

PubMed

Kelly, Ronald R; Gaustad, Martha G

2007-01-01

This study of deaf college students examined specific relationships between their mathematics performance and their assessed skills in reading, language, and English morphology. Simple regression analyses showed that deaf college students' language proficiency scores, reading grade level, and morphological knowledge regarding word segmentation and meaning were all significantly correlated with both the ACT Mathematics Subtest and National Technical Institute for the Deaf (NTID) Mathematics Placement Test scores. Multiple regression analyses identified the best combination from among these potential independent predictors of students' performance on both the ACT and NTID mathematics tests. Additionally, the participating deaf students' grades in their college mathematics courses were significantly and positively associated with their reading grade level and their knowledge of morphological components of words.

Estimation of crown closure from AVIRIS data using regression analysis

NASA Technical Reports Server (NTRS)

Staenz, K.; Williams, D. J.; Truchon, M.; Fritz, R.

1993-01-01

Crown closure is one of the input parameters used for forest growth and yield modelling. Preliminary work by Staenz et al. indicates that imaging spectrometer data acquired with sensors such as the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) have some potential for estimating crown closure on a stand level. The objectives of this paper are: (1) to establish a relationship between AVIRIS data and the crown closure derived from aerial photography of a forested test site within the Interior Douglas Fir biogeoclimatic zone in British Columbia, Canada; (2) to investigate the impact of atmospheric effects and the forest background on the correlation between AVIRIS data and crown closure estimates; and (3) to improve this relationship using multiple regression analysis.

The relationship between severity of violence in the home and dating violence.

PubMed

Sims, Eva Nowakowski; Dodd, Virginia J Noland; Tejeda, Manuel J

2008-01-01

This study used propositions from the social learning theory to explore the effects of the combined influences of child maltreatment, childhood witness to parental violence, sibling violence, and gender on dating violence perpetration using a modified version of the Conflict Tactics Scale 2 (CTS2). A weighted scoring method was utilized to determine how severity of violence in the home impacts dating violence perpetration. Bivariate correlations and linear regression models indicate significant associations between child maltreatment, sibling violence perpetration, childhood witness to parental violence, gender, and subsequent dating violence perpetration. Multiple regression analyses indicate that for men, history of severe violence victimization (i.e., child maltreatment and childhood witness to parental violence) and severe perpetration (sibling violence) significantly predict dating violence perpetration.

Predicting hearing thresholds and occupational hearing loss with multiple-frequency auditory steady-state responses.

PubMed

Hsu, Ruey-Fen; Ho, Chi-Kung; Lu, Sheng-Nan; Chen, Shun-Sheng

2010-10-01

An objective investigation is needed to verify the existence and severity of hearing impairments resulting from work-related, noise-induced hearing loss in arbitration of medicolegal aspects. We investigated the accuracy of multiple-frequency auditory steady-state responses (Mf-ASSRs) between subjects with sensorineural hearing loss (SNHL) with and without occupational noise exposure. Cross-sectional study. Tertiary referral medical centre. Pure-tone audiometry and Mf-ASSRs were recorded in 88 subjects (34 patients had occupational noise-induced hearing loss [NIHL], 36 patients had SNHL without noise exposure, and 18 volunteers were normal controls). Inter- and intragroup comparisons were made. A predicting equation was derived using multiple linear regression analysis. ASSRs and pure-tone thresholds (PTTs) showed a strong correlation for all subjects (r = .77 ≈ .94). The relationship is demonstrated by the equationThe differences between the ASSR and PTT were significantly higher for the NIHL group than for the subjects with non-noise-induced SNHL (p < .001). Mf-ASSR is a promising tool for objectively evaluating hearing thresholds. Predictive value may be lower in subjects with occupational hearing loss. Regardless of carrier frequencies, the severity of hearing loss affects the steady-state response. Moreover, the ASSR may assist in detecting noise-induced injury of the auditory pathway. A multiple linear regression equation to accurately predict thresholds was shown that takes into consideration all effect factors.

Family and school environmental predictors of sleep bruxism in children.

PubMed

Rossi, Debora; Manfredini, Daniele

2013-01-01

To identify potential predictors of self-reported sleep bruxism (SB) within children's family and school environments. A total of 65 primary school children (55.4% males, mean age 9.3 ± 1.9 years) were administered a 10-item questionnaire investigating the prevalence of self-reported SB as well as nine family and school-related potential bruxism predictors. Regression analyses were performed to assess the correlation between the potential predictors and SB. A positive answer to the self-reported SB item was endorsed by 18.8% of subjects, with no sex differences. Multiple variable regression analysis identified a final model showing that having divorced parents and not falling asleep easily were the only two weak predictors of self-reported SB. The percentage of explained variance for SB by the final multiple regression model was 13.3% (Nagelkerke's R² = 0.133). While having a high specificity and a good negative predictive value, the model showed unacceptable sensitivity and positive predictive values. The resulting accuracy to predict the presence of self-reported SB was 73.8%. The present investigation suggested that, among family and school-related matters, having divorced parents and not falling asleep easily were two predictors, even if weak, of a child's self-report of SB.

Investigation of marital satisfaction and its relationship with job stress and general health of nurses in Qazvin, Iran.

PubMed

Azimian, Jalil; Piran, Pegah; Jahanihashemi, Hassan; Dehghankar, Leila

2017-04-01

Pressures in nursing can affect family life and marital problems, disrupt common social problems, increase work-family conflicts and endanger people's general health. To determine marital satisfaction and its relationship with job stress and general health of nurses. This descriptive and cross-sectional study was done in 2015 in medical educational centers of Qazvin by using an ENRICH marital satisfaction scale and General Health and Job Stress questionnaires completed by 123 nurses. Analysis was done by SPSS version 19 using descriptive and analytical statistics (Pearson correlation, t-test, ANOVA, Chi-square, regression line, multiple regression analysis). The findings showed that 64.4% of nurses had marital satisfaction. There was significant relationship between age (p=0.03), job experience (p=0.01), age of spouse (p=0.01) and marital satisfaction. The results showed that there was a significant relationship between marital satisfaction and general health (p<0.0001). Multiple regression analysis showed that there was a significant relationship between depression (p=0.012) and anxiety (p=0.001) with marital satisfaction. Due to high levels of job stress and disorder in general health of nurses and low marital satisfaction by running health promotion programs and paying attention to its dimensions can help work and family health of nurses.

Fish consumption in a sample of people in Bandar Abbas, Iran: application of the theory of planned behavior.

PubMed

Aghamolaei, Teamur; Sadat Tavafian, Sedigheh; Madani, Abdoulhossain

2012-09-01

This study aimed to apply the conceptual framework of the theory of planned behavior (TPB) to explain fish consumption in a sample of people who lived in Bandar Abbass, Iran. We investigated the role of three traditional constructs of TPB that included attitude, social norms, and perceived behavioral control in an effort to characterize the intention to consume fish as well as the behavioral trends that characterize fish consumption. Data were derived from a cross-sectional sample of 321 subjects. Alpha coefficient correlation and linear regression analysis were applied to test the relationships between constructs. The predictors of fish consumption frequency were also evaluated. Multiple regression analysis revealed that attitude, subjective norms, and perceived behavioral control significantly predicted intention to eat fish (R2 = 0.54, F = 128.4, P < 0.001). Multiple regression analysis for the intention to eat fish and perceived behavioral control revealed that both factors significantly predicted fish consumption frequency (R2 = 0.58, F = 223.1, P < 0.001). The results indicated that the models fit well with the data. Attitude, subjective norms, and perceived behavioral control all had significant positive impacts on behavioral intention. Moreover, both intention and perceived behavioral control could be used to predict the frequency of fish consumption.

The Hispanic Americans Baseline Alcohol Survey (HABLAS):Predictive invariance of Demographic Characteristics on Attitudes towards Alcohol across Hispanic National Groups#

PubMed Central

Mills, Britain A.; Caetano, Raul; Bernstein, Ira H.

2011-01-01

This study compares the demographic predictors of items assessing attitudes towards drinking across Hispanic national groups. Data were from the 2006 Hispanic Americans Baseline Alcohol Survey (HABLAS), which used a multistage cluster sample design to interview 5,224 individuals randomly selected from the household population in Miami, New York, Philadelphia, Houston, and Los Angeles. Predictive invariance of demographic predictors of alcohol attitudes over four Hispanic national groups (Puerto Rican, Cuban, Mexican, and South/Central Americans) was examined using multiple-group seemingly unrelated probit regression. The analyses examined whether the influence of various demographic predictors varied across the Hispanic national groups in their regression coefficients, item intercepts, and error correlations. The hypothesis of predictive invariance was supported. Hispanic groups did not differ in how demographic predictors related to individual attitudinal items (regression slopes were invariant). In addition, the groups did not differ in attitudinal endorsement rates once demographic covariates were taken into account (item intercepts were invariant). Although Hispanic groups have different attitudes about alcohol, the influence of multiple demographic characteristics on alcohol attitudes operates similarly across Hispanic groups. Future models of drinking behavior in adult Hispanics need not posit moderating effects of group on the relation between these background characteristics and attitudes. PMID:25379120

Urban air quality forecasting based on multi-dimensional collaborative Support Vector Regression (SVR): A case study of Beijing-Tianjin-Shijiazhuang

PubMed Central

Liu, Bing-Chun; Binaykia, Arihant; Chang, Pei-Chann; Tiwari, Manoj Kumar; Tsao, Cheng-Chin

2017-01-01

Today, China is facing a very serious issue of Air Pollution due to its dreadful impact on the human health as well as the environment. The urban cities in China are the most affected due to their rapid industrial and economic growth. Therefore, it is of extreme importance to come up with new, better and more reliable forecasting models to accurately predict the air quality. This paper selected Beijing, Tianjin and Shijiazhuang as three cities from the Jingjinji Region for the study to come up with a new model of collaborative forecasting using Support Vector Regression (SVR) for Urban Air Quality Index (AQI) prediction in China. The present study is aimed to improve the forecasting results by minimizing the prediction error of present machine learning algorithms by taking into account multiple city multi-dimensional air quality information and weather conditions as input. The results show that there is a decrease in MAPE in case of multiple city multi-dimensional regression when there is a strong interaction and correlation of the air quality characteristic attributes with AQI. Also, the geographical location is found to play a significant role in Beijing, Tianjin and Shijiazhuang AQI prediction. PMID:28708836

Mental Health Correlates of Cigarette Use in LGBT Individuals in the Southeastern United States.

PubMed

Drescher, Christopher F; Lopez, Eliot J; Griffin, James A; Toomey, Thomas M; Eldridge, Elizabeth D; Stepleman, Lara M

2018-05-12

Smoking prevalence for lesbian, gay, bisexual, and transgender (LGBT) individuals is higher than for heterosexual, cisgender individuals. Elevated smoking rates have been linked to psychiatric comorbidities, substance use, poverty, low education levels, and stress. This study examined mental health (MH) correlates of cigarette use in LGBT individuals residing in a metropolitan area in the southeastern United States. Participants were 335 individuals from an LGBT health needs assessment (mean age 34.7; SD = 13.5; 63% gay/lesbian; 66% Caucasian; 81% cisgender). Demographics, current/past psychiatric diagnoses, number of poor MH days in the last 30, the Patient Health Questionnaire (PHQ) 2 depression screener, the Three-Item Loneliness Scale, and frequency of cigarette use were included. Analyses included bivariate correlations, analysis of variance (ANOVA), and regression. Multiple demographic and MH factors were associated with smoker status and frequency of smoking. A logistic regression indicated that lower education and bipolar disorder were most strongly associated with being a smoker. For smokers, a hierarchical regression model including demographic and MH variables accounted for 17.6% of the variance in frequency of cigarette use. Only education, bipolar disorder, and the number of poor MH days were significant contributors in the overall model. Conclusions/Importance: Less education, bipolar disorder, and recurrent poor MH increase LGBT vulnerability to cigarette use. Access to LGBT-competent MH providers who can address culturally specific factors in tobacco cessation is crucial to reducing this health disparities.

Moral distress and burnout syndrome: are there relationships between these phenomena in nursing workers?

PubMed

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; Silveira, Rosemary Silva da

2014-01-01

to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied.

Moral distress and Burnout syndrome: are there relationships between these phenomena in nursing workers?1

PubMed Central

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; da Silveira, Rosemary Silva

2014-01-01

Objective to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. Methods this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. Results the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. Conclusion the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied. PMID:24553701

Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets

NASA Astrophysics Data System (ADS)

Yang, Liansheng; Zhu, Yingming; Wang, Yudong; Wang, Yiqi

2016-11-01

Based on the daily price data of spot prices of West Texas Intermediate (WTI) crude oil and ten CSI300 sector indices in China, we apply multifractal detrended cross-correlation analysis (MF-DCCA) method to investigate the cross-correlations between crude oil and Chinese sector stock markets. We find that the strength of multifractality between WTI crude oil and energy sector stock market is the highest, followed by the strength of multifractality between WTI crude oil and financial sector market, which reflects a close connection between energy and financial market. Then we do vector autoregression (VAR) analysis to capture the interdependencies among the multiple time series. By comparing the strength of multifractality for original data and residual errors of VAR model, we get a conclusion that vector auto-regression (VAR) model could not be used to describe the dynamics of the cross-correlations between WTI crude oil and the ten sector stock markets.

Are peer specialists happy on the job?

PubMed

Jenkins, Sarah; Chenneville, Tiffany; Salnaitis, Christina

2018-03-01

This study was designed to examine the impact of role clarity and job training on job satisfaction among peer specialists. A 3-part survey assessing job training, job satisfaction, and role clarity was administered online to 195 peer specialists who are members of the International Association of Peer Specialists. Data was analyzed using descriptive statistics, correlational analyses to include multiple linear regressions and analysis of variance. Self-study and online training methods were negatively correlated with job satisfaction while job shadowing was positively correlated with job satisfaction. Role clarity was positively correlated with job satisfaction and job training satisfaction as well as job shadowing and one-on-one training. The use of self-study and online training for peer specialists is contraindicated by current findings, which suggest the need to utilize job shadowing or training methods that allow for personal interaction between peer specialists and their colleagues. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Does the perception that God controls health outcomes matter for health behaviors?

PubMed

Karvinen, Kristina H; Carr, Lucas J

2014-04-01

The purpose of this study was to examine the associations between God Locus of Health Control, health behaviors, and beliefs utilizing a cross-sectional online survey (N = 549). Results indicated that God Locus of Health Control was correlated with alcohol use, physical activity, perceived risk of chronic disease, and beliefs that poor health behaviors contribute to chronic disease (all p values < .05). Multiple regression analyses including covariates and other locus of control variables revealed that God Locus of Health Control was only an independent correlate of the belief that physical inactivity contributed to chronic disease. Insights from this study may be important for future faith-based health behavior change interventions.

Characterization of good teleoperators - What aptitudes, interests, and experience correlate with measures of teleoperator performance

NASA Technical Reports Server (NTRS)

Yorchak, J. P.; Hartley, C. S.; Hinman, E.

1985-01-01

The use of aptitude tests and questionnaries to evaluate an individuals aptitude for teleoperation is studied. The Raven Progressive Matrices Test and Differential Aptitude Tests, and a 16-item questionnaire for assessing the subject's interests, academic background, and previous experience are described. The Proto-Flight Manipulator Arm, cameras, console, hand controller, and task board utilized by the 17 engineers are examined. The correlation between aptitude scores and questionnaire responses, and operator performance is investigated. Multiple regression data reveal that the eight predictor variables are not individually significant for evaluating operator performance; however, the complete test battery is applicable for predicting 49 percent of subject variance on the criterion task.

The impact of carbohydrate intake and its sources on hemoglobin A1c levels in Japanese patients with type 2 diabetes not taking anti-diabetic medication

PubMed Central

Haimoto, Hajime; Watanabe, Shiho; Komeda, Masashi; Wakai, Kenji

2018-01-01

Background Although postprandial glucose levels largely depend on carbohydrate intake, the impact of carbohydrate and its sources on hemoglobin A1c (HbA1c) levels has not been demonstrated in patients with type 2 diabetes (T2DM) probably because, in previous studies, more than 50% of patients were taking anti-diabetic medication, and the researchers used energy percent of carbohydrate as an indicator of carbohydrate intake. Patients and methods We recruited 125 Japanese men (mean age 58±12 years) and 104 women (mean age 62±10 years) with T2DM who were not taking anti-diabetic medication and dietary therapy. We used 3-day dietary records to assess total carbohydrate intake and its sources, computed Spearman’s correlation coefficients, and conducted multiple regression analyses for associations of carbohydrate sources with HbA1c by sex. Results Mean HbA1c and total carbohydrate intake were 8.2%±1.9% and 272.0±84.6 g/day in men and 7.6%±1.3% and 226.7±61.5 g/day in women, respectively. We observed positive correlation of total carbohydrate intake (g/day) with HbA1c in men (rs=0.384) and women (rs=0.251), but no correlation for % carbohydrate in either sex. Regarding carbohydrate sources, we found positive correlations of carbohydrate from noodles (rs=0.231) and drinks (rs=0.325), but not from rice, with HbA1c in men. In women, carbohydrate from rice had a positive correlation (rs=0.317), but there were no correlations for carbohydrate from noodles and drinks. The association of total carbohydrate intake (g/day) and carbohydrate from soft drinks with HbA1c in men remained significant even after adjustment for total energy by multiple regression analyses. Conclusion Our findings warrant interventional studies for moderate low-carbohydrate diets that focus on carbohydrate sources and sex differences in order to efficiently decrease HbA1c in patients with T2DM. PMID:29563823

The left hand second to fourth digit ratio (2D:4D) is not related to any physical fitness component in adolescent girls.

PubMed

Peeters, Maarten W; Van Aken, Katrijn; Claessens, Albrecht L

2013-01-01

The second to fourth-digit-ratio (2D:4D), a putative marker of prenatal androgen action and a sexually dimorphic trait, has been suggested to be related with fitness and sports performance, although results are not univocal. Most studies however focus on a single aspect of physical fitness or one sports discipline. In this study the 2D:4D ratio of 178 adolescent girls (age 13.5-18 y) was measured on X-rays of the left hand. The relation between 2D:4D digit ratio and multiple aspects of physical fitness (balance, speed of limb movement, flexibility, explosive strength, static strength, trunk strength, functional strength, running speed/agility, and endurance) was studied by correlation analyses and stepwise multiple regression. For comparison the relation between these physical fitness components and a selected number of objectively measured anthropometric traits (stature, mass, BMI, somatotype components and the Bayer & Bailey androgyny index) are presented alongside the results of 2D:4D digit ratio. Left hand 2D:4D digit ratio (0.925±0.019) was not significantly correlated with any of the physical fitness components nor any of the anthropometric variables included in the present study. 2D:4D did not enter the multiple stepwise regression for any of the physical fitness components in which other anthropometric traits explained between 9.2% (flexibility) and 33.9% (static strength) of variance. Unlike other anthropometric traits the 2D:4D digit ratio does not seem to be related to any physical fitness component in adolescent girls and therefore most likely should not be considered in talent detection programs for sporting ability in girls.

Urinary excretion of uric acid is negatively associated with albuminuria in patients with chronic kidney disease: a cross-sectional study.

PubMed

Li, Fengqin; Guo, Hui; Zou, Jianan; Chen, Weijun; Lu, Yijun; Zhang, Xiaoli; Fu, Chensheng; Xiao, Jing; Ye, Zhibin

2018-04-24

Increasing evidence has shown that albuminuria is related to serum uric acid. Little is known about whether this association may be interrelated via renal handling of uric acid. Therefore, we aim to study urinary uric acid excretion and its association with albuminuria in patients with chronic kidney disease (CKD). A cross-sectional study of 200 Chinese CKD patients recruited from department of nephrology of Huadong hospital was conducted. Levels of 24 h urinary excretion of uric acid (24-h Uur), fractional excretion of uric acid (FEur) and uric acid clearance rate (Cur) according to gender, CKD stages, hypertension and albuminuria status were compared by a multivariate analysis. Pearson and Spearman correlation and multiple regression analyses were used to study the correlation of 24-h Uur, FEur and Cur with urinary albumin to creatinine ratio (UACR). The multivariate analysis showed that 24-h Uur and Cur were lower and FEur was higher in the hypertension group, stage 3-5 CKD and macro-albuminuria group (UACR> 30 mg/mmol) than those in the normotensive group, stage 1 CKD group and the normo-albuminuria group (UACR< 3 mg/mmol) (all P < 0.05). Moreover, males had higher 24-h Uur and lower FEur than females (both P < 0.05). Multiple linear regression analysis showed that UACR was negatively associated with 24-h Uur and Cur (P = 0.021, P = 0.007, respectively), but not with FEur (P = 0.759), after adjusting for multiple confounding factors. Our findings suggested that urinary excretion of uric acid is negatively associated with albuminuria in patients with CKD. This phenomenon may help to explain the association between albuminuria and serum uric acid.

Predicting Patient Advocacy Engagement: A Multiple Regression Analysis Using Data From Health Professionals in Acute-Care Hospitals.

PubMed

Jansson, Bruce S; Nyamathi, Adeline; Heidemann, Gretchen; Duan, Lei; Kaplan, Charles

2015-01-01

Although literature documents the need for hospital social workers, nurses, and medical residents to engage in patient advocacy, little information exists about what predicts the extent they do so. This study aims to identify predictors of health professionals' patient advocacy engagement with respect to a broad range of patients' problems. A cross-sectional research design was employed with a sample of 94 social workers, 97 nurses, and 104 medical residents recruited from eight hospitals in Los Angeles. Bivariate correlations explored whether seven scales (Patient Advocacy Eagerness, Ethical Commitment, Skills, Tangible Support, Organizational Receptivity, Belief Other Professionals Engage, and Belief the Hospital Empowers Patients) were associated with patient advocacy engagement, measured by the validated Patient Advocacy Engagement Scale. Regression analysis examined whether these scales, when controlling for sociodemographic and setting variables, predicted patient advocacy engagement. While all seven predictor scales were significantly associated with patient advocacy engagement in correlational analyses, only Eagerness, Skills, and Belief the Hospital Empowers Patients predicted patient advocacy engagement in regression analyses. Additionally, younger professionals engaged in higher levels of patient advocacy than older professionals, and social workers engaged in greater patient advocacy than nurses. Limitations and the utility of these findings for acute-care hospitals are discussed.

Internalized stigma among psychiatric outpatients: Associations with quality of life, functioning, hope and self-esteem.

PubMed

Picco, Louisa; Pang, Shirlene; Lau, Ying Wen; Jeyagurunathan, Anitha; Satghare, Pratika; Abdin, Edimansyah; Vaingankar, Janhavi Ajit; Lim, Susan; Poh, Chee Lien; Chong, Siow Ann; Subramaniam, Mythily

2016-12-30

This study aimed to: (i) determine the prevalence, socio-demographic and clinical correlates of internalized stigma and (ii) explore the association between internalized stigma and quality of life, general functioning, hope and self-esteem, among a multi-ethnic Asian population of patients with mental disorders. This cross-sectional, survey recruited adult patients (n=280) who were seeking treatment at outpatient and affiliated clinics of the only tertiary psychiatric hospital in Singapore. Internalized stigma was measured using the Internalized Stigma of Mental Illness scale. 43.6% experienced moderate to high internalized stigma. After making adjustments in multiple logistic regression analysis, results revealed there were no significant socio-demographic or clinical correlates relating to internalized stigma. Individual logistic regression models found a negative relationship between quality of life, self-esteem, general functioning and internalized stigma whereby lower scores were associated with higher internalized stigma. In the final regression model, which included all psychosocial variables together, self-esteem was the only variable significantly and negatively associated with internalized stigma. The results of this study contribute to our understanding of the role internalized stigma plays in patients with mental illness, and the impact it can have on psychosocial aspects of their lives. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Drainage basin characteristics from ERTS data

NASA Technical Reports Server (NTRS)

Hollyday, E. F. (Principal Investigator)

1975-01-01

The author has identified the following significant results. ERTS-derived measurements of forests, riparian vegetation, open water, and combined agricultural and urban land use were added to an available matrix of map-derived basin characteristics. The matrix of basin characteristics was correlated with 40 stream flow characteristics by multiple regression techniques. Fifteen out of the 40 equations were improved. If the technique can be transferred to other physiographic regions in the nation, the opportunity exists for a potential annual savings in operations of about $250,000.

Parenting styles and alcohol consumption among Brazilian adolescents.

PubMed

Paiva, Fernando Santana; Bastos, Ronaldo Rocha; Ronzani, Telmo Mota

2012-10-01

This study evaluates the correlation between alcohol consumption in adolescence and parenting styles of socialization among Brazilian adolescents. The sample was composed of 273 adolescents, 58% whom were males. Instruments were: 1) Sociodemographic Questionnaire; 2) Demand and Responsiveness Scales; 3) Drug Use Screening Inventory (DUSI). Study analyses employed multiple correspondence analysis and logistic regression. Maternal, but not paternal, authoritative and authoritarian parenting styles were directly related to adolescent alcohol intake. The style that mothers use to interact with their children may influence uptake of high-risk behaviors.

False Positives in Multiple Regression: Unanticipated Consequences of Measurement Error in the Predictor Variables

ERIC Educational Resources Information Center

Shear, Benjamin R.; Zumbo, Bruno D.

2013-01-01

Type I error rates in multiple regression, and hence the chance for false positive research findings, can be drastically inflated when multiple regression models are used to analyze data that contain random measurement error. This article shows the potential for inflated Type I error rates in commonly encountered scenarios and provides new…

Using Robust Standard Errors to Combine Multiple Regression Estimates with Meta-Analysis

ERIC Educational Resources Information Center

Williams, Ryan T.

2012-01-01

Combining multiple regression estimates with meta-analysis has continued to be a difficult task. A variety of methods have been proposed and used to combine multiple regression slope estimates with meta-analysis, however, most of these methods have serious methodological and practical limitations. The purpose of this study was to explore the use…

Use of Multiple Regression and Use-Availability Analyses in Determining Habitat Selection by Gray Squirrels (Sciurus Carolinensis)

Treesearch

John W. Edwards; Susan C. Loeb; David C. Guynn

1994-01-01

Multiple regression and use-availability analyses are two methods for examining habitat selection. Use-availability analysis is commonly used to evaluate macrohabitat selection whereas multiple regression analysis can be used to determine microhabitat selection. We compared these techniques using behavioral observations (n = 5534) and telemetry locations (n = 2089) of...

Correlation of Vitamin D status and orthodontic-induced external apical root resorption

PubMed Central

Tehranchi, Azita; Sadighnia, Azin; Younessian, Farnaz; Abdi, Amir H.; Shirvani, Armin

2017-01-01

Background: Adequate Vitamin D is essential for dental and skeletal health in children and adult. The purpose of this study was to assess the correlation of serum Vitamin D level with external-induced apical root resorption (EARR) following fixed orthodontic treatment. Materials and Methods: In this cross-sectional study, the prevalence of Vitamin D deficiency (defined by25-hydroxyvitamin-D) was determined in 34 patients (23.5% male; age range 12–23 years; mean age 16.63 ± 2.84) treated with fixed orthodontic treatment. Root resorption of four maxillary incisors was measured using before and after periapical radiographs (136 measured teeth) by means of a design-to-purpose software to optimize data collection. Teeth with a maximum percentage of root resorption (%EARR) were indicated as representative root resorption for each patient. A multiple linear regression model and Pearson correlation coefficient were used to assess the association of Vitamin D status and observed EARR. P < 0.05 was considered statistically significant. Results: The Pearson coefficient between these two variables was determined about 0.15 (P = 0.38). Regression analysis revealed that Vitamin D status of the patients demonstrated no significant statistical correlation with EARR, after adjustment of confounding variables using linear regression model (P > 0.05). Conclusion: This study suggests that Vitamin D level is not among the clinical variables that are potential contributors for EARR. The prevalence of Vitamin D deficiency does not differ in patients with higher EARR. These data suggest the possibility that Vitamin D insufficiency may not contribute to the development of more apical root resorption although this remains to be confirmed by further longitudinal cohort studies. PMID:29238379

Improvement of the air quality in student health centers with chlorine dioxide.

PubMed

Hsu, Ching-Shan; Huang, Da-Ji; Lu, Ming-Chun

2010-04-01

This study aims to monitor bioaerosol levels of a local campus of a student health center in Taiwan and then to perform disinfection by applying chlorine dioxide. First, air samples were taken and evaluated in the six areas of the center. The average background bioaerosol levels were 714 +/- 1706 CFU/m(3) for bacterium and 802 +/- 633 CFU/m(3) for fungi. Then, chlorine dioxide was applied through three different procedures: single, multiple and regular disinfections. The results indicated that both multiple and regular disinfections can achieve efficiency levels higher than 59.0%. The regression analysis on bioaerosol levels showed that the number of people present correlating to the number of persons entering the room per door-opening, had a correlation of p < 0.05. Utilizing this analysis result, an empirical model was developed to predict indoor bioaerosol concentrations. It can be inferred that for indoor human activity of health centers, regular disinfection is a very effective process.

Building Regression Models: The Importance of Graphics.

ERIC Educational Resources Information Center

Dunn, Richard

1989-01-01

Points out reasons for using graphical methods to teach simple and multiple regression analysis. Argues that a graphically oriented approach has considerable pedagogic advantages in the exposition of simple and multiple regression. Shows that graphical methods may play a central role in the process of building regression models. (Author/LS)

Testing Different Model Building Procedures Using Multiple Regression.

ERIC Educational Resources Information Center

Thayer, Jerome D.

The stepwise regression method of selecting predictors for computer assisted multiple regression analysis was compared with forward, backward, and best subsets regression, using 16 data sets. The results indicated the stepwise method was preferred because of its practical nature, when the models chosen by different selection methods were similar…

Oscillatory neural representations in the sensory thalamus predict neuropathic pain relief by deep brain stimulation.

PubMed

Huang, Yongzhi; Green, Alexander L; Hyam, Jonathan; Fitzgerald, James; Aziz, Tipu Z; Wang, Shouyan

2018-01-01

Understanding the function of sensory thalamic neural activity is essential for developing and improving interventions for neuropathic pain. However, there is a lack of investigation of the relationship between sensory thalamic oscillations and pain relief in patients with neuropathic pain. This study aims to identify the oscillatory neural characteristics correlated with pain relief induced by deep brain stimulation (DBS), and develop a quantitative model to predict pain relief by integrating characteristic measures of the neural oscillations. Measures of sensory thalamic local field potentials (LFPs) in thirteen patients with neuropathic pain were screened in three dimensional feature space according to the rhythm, balancing, and coupling neural behaviours, and correlated with pain relief. An integrated approach based on principal component analysis (PCA) and multiple regression analysis is proposed to integrate the multiple measures and provide a predictive model. This study reveals distinct thalamic rhythms of theta, alpha, high beta and high gamma oscillations correlating with pain relief. The balancing and coupling measures between these neural oscillations were also significantly correlated with pain relief. The study enriches the series research on the function of thalamic neural oscillations in neuropathic pain and relief, and provides a quantitative approach for predicting pain relief by DBS using thalamic neural oscillations. Copyright © 2017 Elsevier Inc. All rights reserved.

Decreasing Multicollinearity: A Method for Models with Multiplicative Functions.

ERIC Educational Resources Information Center

Smith, Kent W.; Sasaki, M. S.

1979-01-01

A method is proposed for overcoming the problem of multicollinearity in multiple regression equations where multiplicative independent terms are entered. The method is not a ridge regression solution. (JKS)

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.

Community Air Sensor Network (CAIRSENSE) project ...

EPA Pesticide Factsheets

Advances in air pollution sensor technology have enabled the development of small and low cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low cost, continuous and commercially-available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ~2 km area in Southeastern U.S. Co-location of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as whether multiple identical sensors reproduced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, -0.25 to 0.76, -0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in sampling days could be used in a correction algorihm to im

Physical inactivity, neurological disability, and cardiorespiratory fitness in multiple sclerosis.

PubMed

Motl, R W; Goldman, M

2011-02-01

We examined the associations among physical activity, neurological disability, and cardiorespiratory fitness in two studies of individuals with multiple sclerosis (MS). Study 1 included 25 women with relapsing-remitting MS (RRMS) who undertook an incremental exercise test for measuring peak oxygen (VO₂(peak) ) consumption, wore an accelerometer during a 7-day period, and completed the Godin Leisure-Time Exercise Questionnaire (GLTEQ). Study 2 was a follow-up of Study 1 and included 24 women with RRMS who completed the self-reported Expanded Disability Status Scale (EDSS), undertook an incremental exercise test, wore an accelerometer during a 7-day period, and completed the GLTEQ. Study 1 indicated that VO₂(peak) was significantly correlated with accelerometer counts (pr = 0.69) and GLTEQ scores (pr = 0.63) even after controlling for age and MS duration. Study 2 indicated that VO₂(peak) was significantly correlated with accelerometer counts (pr = 0.50), GLTEQ scores (pr = 0.59), and EDSS scores (pr = -0.43) even after controlling for age and MS duration; there was a moderate partial correlation between accelerometer counts and EDSS scores (pr = -0.43). Multiple linear regression analysis indicated that both accelerometer counts (β = 0.32) and EDSS scores (β = -0.40) had statistically significant associations with VO₂(peak). The findings indicate that physical inactivity and neurological disability might represent independent risk factors for reduced levels of cardiorespiratory fitness in this population. © 2010 John Wiley & Sons A/S.

Multitask TSK fuzzy system modeling by mining intertask common hidden structure.

PubMed

Jiang, Yizhang; Chung, Fu-Lai; Ishibuchi, Hisao; Deng, Zhaohong; Wang, Shitong

2015-03-01

The classical fuzzy system modeling methods implicitly assume data generated from a single task, which is essentially not in accordance with many practical scenarios where data can be acquired from the perspective of multiple tasks. Although one can build an individual fuzzy system model for each task, the result indeed tells us that the individual modeling approach will get poor generalization ability due to ignoring the intertask hidden correlation. In order to circumvent this shortcoming, we consider a general framework for preserving the independent information among different tasks and mining hidden correlation information among all tasks in multitask fuzzy modeling. In this framework, a low-dimensional subspace (structure) is assumed to be shared among all tasks and hence be the hidden correlation information among all tasks. Under this framework, a multitask Takagi-Sugeno-Kang (TSK) fuzzy system model called MTCS-TSK-FS (TSK-FS for multiple tasks with common hidden structure), based on the classical L2-norm TSK fuzzy system, is proposed in this paper. The proposed model can not only take advantage of independent sample information from the original space for each task, but also effectively use the intertask common hidden structure among multiple tasks to enhance the generalization performance of the built fuzzy systems. Experiments on synthetic and real-world datasets demonstrate the applicability and distinctive performance of the proposed multitask fuzzy system model in multitask regression learning scenarios.

Restoration of acidic mine spoils with sewage sludge: II measurement of solids applied

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

Stucky, D.J.; Zoeller, A.L.

1980-01-01

Sewage sludge was incorporated in acidic strip mine spoils at rates equivalent to 0, 224, 336, and 448 dry metric tons (dmt)/ha and placed in pots in a greenhouse. Spoil parameters were determined 48 hours after sludge incorporation, Time Planting (P), and five months after orchardgrass (Dactylis glomerata L.) was planted, Time Harvest (H), in the pots. Parameters measured were: pH, organic matter content (OM), cation exchange capacity (CEC), electrical conductivity (EC) and yield. Values for each parameter were significantly different at the two sampling times. Correlation coefficient values were calculated for all parameters versus rates of applied sewage sludgemore » and all parameters versus each other. Multiple regressions were performed, stepwise, for all parameters versus rates of applied sewage sludge. Equations to predict amounts of sewage sludge incorporated in spoils were derived for individual and multiple parameters. Generally, measurements made at Time P achieved the highest correlation coefficient and multiple correlation coefficient values; therefore, the authors concluded data from Time P had the greatest predictability value. The most important value measured to predict rate of applied sewage sludge was pH and some additional accuracy was obtained by including CEC in equation. This experiment indicated that soil properties can be used to estimate amounts of sewage sludge solids required to reclaim acidic mine spoils and to estimate quantities incorporated.« less

Relation of Environmental characteristics to the composition of aquatic assemblages along a gradient of urban land use in New Jersey, 1996-98

USGS Publications Warehouse

Kennen, Jonathan G.; Ayers, Mark A.

2002-01-01

Community data from 36 watersheds were used to evaluate the response of fish, invertebrate, and algal assemblages in New Jersey streams to environmental characteristics along a gradient of urban land use that ranged from 3 to 96 percent. Aquatic assemblages were sampled at 36 sites during 1996-98, and more than 400 environmental attributes at multiple spatial scales were summarized. Data matrices were reduced to 43, 170, and 103 species of fish, invertebrates, and algae, respectively, by means of a predetermined joint frequency and relative abundance approach. White sucker (Catostomus commersoni) and Tessellated darter (Etheostoma olmstedi) were the most abundant fishes, accounting for more than 20 and 17 percent, respectively, of the mean abundance. Net-spinning caddisflies (Hydropsychidae) were the most commonly occurring benthic invertebrates and were found at all but one of the 36 sampling sites. Blue-green (for example, Calothrix sp. and Oscillatoria sp.) and green (for example, Protoderma viride) algae were the most widely distrib-uted algae; however, more than 81 percent of the algal taxa collected were diatoms. Principal-component and correlation analyses were used to reduce the dimensionality of the environmental data. Multiple linear regression analysis of extracted ordination axes then was used to develop models that expressed effects of increasing urban land use on the structure of aquatic assemblages. Significant environmental variables identified by using multiple linear regression analysis then were included in a direct gradient analysis. Partial canonical correspondence analysis of relativized abundance data was used to restrict further the effects of residual natural variability, and to identify relations among the environmental variables and the structure of fish, invertebrate, and algal assemblages along an urban land-use gradient. Results of this approach, combined with the results of the multiple linear regression analyses, were used to identify human population density (311-37,594 persons/km2), amount and type of impervious surface cover (0.12-1,350 km2), nutrient concentrations (for example, 0.01-0.29 mg/L of phosphorus), hydrologic instability (for example, 100-8,955 ft3/s for 2-year peak flow), the amount of forest and wetlands in a basin (0.01-6.25 km2), and substrate quality (0-87 percent cobble substrate) as variables that are highly correlated with aquatic-assemblage structure. Species distributions in ordination space clearly indicate that tolerant species are more abundant in the streams impaired by urbanization and sensitive taxa are more closely associated with the least impaired basins. The distinct differences in aquatic assemblages along the urban land-use gradient demonstrate the deleterious effects of urbanization on assemblage structure and indicate that conserving landscape attributes that mitigate anthropogenic influences (for example, stormwater-management practices emphasizing infiltration and preservation of existing forests, wetlands, and riparian corridors) will help to maintain the relative abundance of sensitive taxa. Complementary multiple linear regression models indicate that aquatic community indices were correlated with many of the anthropogenic factors that were found to be significant along the urban land-use gradient. These indices appear to be effective in differentiating the moderately and severely impaired streams from the minimally impaired streams. Evaluation of disturbance thresholds for aquatic assemblages indicates that moderate to severe impairment is detectable in New Jersey streams when impervious surface cover in the drainage basin reaches approximately 18 percent.

A Quantitative Study of the Relationship between the Distribution of Different Types of Collagen and the Mechanical Behavior of Rabbit Medial Collateral Ligaments

PubMed Central

Wan, Chao; Hao, Zhixiu; Wen, Shizhu; Leng, Huijie

2014-01-01

The mechanical properties of ligaments are key contributors to the stability and function of musculoskeletal joints. Ligaments are generally composed of ground substance, collagen (mainly type I and III collagen), and minimal elastin fibers. However, no consensus has been reached about whether the distribution of different types of collagen correlates with the mechanical behaviors of ligaments. The main objective of this study was to determine whether the collagen type distribution is correlated with the mechanical properties of ligaments. Using axial tensile tests and picrosirius red staining-polarization observations, the mechanical behaviors and the ratios of the various types of collagen were investigated for twenty-four rabbit medial collateral ligaments from twenty-four rabbits of different ages, respectively. One-way analysis of variance was used in the comparison of the Young's modulus in the linear region of the stress-strain curves and the ratios of type I and III collagen for the specimens (the mid-substance specimens of the ligaments) with different ages. A multiple linear regression was performed using the collagen contents (the ratios of type I and III collagen) and the Young's modulus of the specimens. During the maturation of the ligaments, the type I collagen content increased, and the type III collagen content decreased. A significant and strong correlation () was identified by multiple linear regression between the collagen contents (i.e., the ratios of type I and type III collagen) and the mechanical properties of the specimens. The collagen content of ligaments might provide a new perspective for evaluating the linear modulus of global stress-strain curves for ligaments and open a new door for studying the mechanical behaviors and functions of connective tissues. PMID:25062068

Clinical relevance of valgus deformity of proximal femur in cerebral palsy.

PubMed

Lee, Kyoung Min; Kang, Jong Yeol; Chung, Chin Youb; Kwon, Dae Gyu; Lee, Sang Hyeong; Choi, In Ho; Cho, Tae-Joon; Yoo, Won Joon; Park, Moon Seok

2010-01-01

Proximal femoral deformity related to physis has not been studied in patients with cerebral palsy (CP). This study was performed to investigate the clinical relevance of neck shaft angle (NSA), head shaft angle (HSA), and proximal femoral epiphyseal shape in patients with CP, which represent the deformities of metaphysis, physis, and epiphysis, respectively. Three hundred eighty-four patients with CP (mean age 9.1 y, 249 males and 135 females) were included. Extent of involvement and functional states [Gross Motor Function Classification System (GMFCS) level] were obtained. Radiographic measurements including NSA, HSA, and qualitative shape of the proximal femoral epiphysis were evaluated and analyzed according to extent of involvement and GMFCS level. Reliability and correlation with each measurement were assessed. Multiple regression test was performed to examine the significant contributing factors to migration percentage (MP) that represents hip instability. NSA showed excellent interobserver reliability with intraclass correlation coefficients of 0.976. Correlation with the MP was higher in the NSA (r=0.419, P<0.001) than in the HSA (r=0.256, P<0.001). NSA, HSA, and MP tended to increase with increasing GMFCS level, and proportion of valgus deformed proximal femoral epiphysis also increased with increasing GMFCS level, which means valgus deformity and unstable hips in the less favorable functional states. Multiple regression analysis revealed NSA, GMFCS level, and shape of the proximal femoral epiphysis to be significant factors affecting MP. NSA appeared to be more clinically relevant than HSA in evaluating proximal femoral deformity in patients with CP. Shape of proximal femoral epiphysis is believed to have clinical implications in terms of hip instability. Diagnostic level II.

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.

Multiple linear regression approach for the analysis of the relationships between joints mobility and regional pressure-based parameters in the normal-arched foot.

PubMed

Caravaggi, Paolo; Leardini, Alberto; Giacomozzi, Claudia

2016-10-03

Plantar load can be considered as a measure of the foot ability to transmit forces at the foot/ground, or foot/footwear interface during ambulatory activities via the lower limb kinematic chain. While morphological and functional measures have been shown to be correlated with plantar load, no exhaustive data are currently available on the possible relationships between range of motion of foot joints and plantar load regional parameters. Joints' kinematics from a validated multi-segmental foot model were recorded together with plantar pressure parameters in 21 normal-arched healthy subjects during three barefoot walking trials. Plantar pressure maps were divided into six anatomically-based regions of interest associated to corresponding foot segments. A stepwise multiple regression analysis was performed to determine the relationships between pressure-based parameters, joints range of motion and normalized walking speed (speed/subject height). Sagittal- and frontal-plane joint motion were those most correlated to plantar load. Foot joints' range of motion and normalized walking speed explained between 6% and 43% of the model variance (adjusted R 2 ) for pressure-based parameters. In general, those joints' presenting lower mobility during stance were associated to lower vertical force at forefoot and to larger mean and peak pressure at hindfoot and forefoot. Normalized walking speed was always positively correlated to mean and peak pressure at hindfoot and forefoot. While a large variance in plantar pressure data is still not accounted for by the present models, this study provides statistical corroboration of the close relationship between joint mobility and plantar pressure during stance in the normal healthy foot. Copyright © 2016 Elsevier Ltd. All rights reserved.

Serum Bilirubin Concentrations in Patients With Takayasu Arteritis.

PubMed

Peng, You-Fan; Deng, Yi-Bin

2017-06-01

- Bilirubin has strong anti-inflammatory and antioxidative stress action. Progression of inflammation involving arteries is a crucial activator in pathogenesis of Takayasu arteritis (TA). - To investigate the relationship between serum bilirubin and TA. - Our study involved 115 consecutive TA patients. Patients with active-phase disease were followed and received prednisone therapy. - Lower concentrations of serum bilirubin were detected in TA patients compared with healthy subjects (0.6 ± 0.31 versus 0.7 ± 0.22 mg/dL, P = .02). Serum bilirubin concentrations in active TA patients were lower than those in inactive patients (0.5 ± 0.20 versus 0.8 ± 0.32 mg/dL, P < .001). In all patients with TA, serum bilirubin correlated positively with total protein (r = 0.193, P = .04) and negatively with C-reactive protein and erythrocyte sedimentation rate (r = -0.213, P = .03, and r = -0.532, P < .001, respectively). Multiple logistic regression analysis showed that each decrease of 1 mg/dL in serum bilirubin was associated with a 1.10 times increase in the odds for TA compared with the controls (odds ratio = 0.913, 95% CI, 0.856-0.974; P = .006). Serum bilirubin was correlated with erythrocyte sedimentation rate (β = -0.170, P < .001) in multiple linear regression analysis. The area under the curve for serum bilirubin in predicting active TA patients was 0.802. Serum bilirubin levels were found to be significantly increased after prednisone treatment (0.5 ± 0.20 versus 0.7 ± 0.15 mg/dL, P = .002). - Lower serum bilirubin levels are associated with TA, and serum bilirubin may be influenced by prednisone therapy in active TA patients. Serum bilirubin levels in TA patients correlate negatively with erythrocyte sedimentation rate.

Are lapsed donors willing to resume blood donation, and what determines their motivation to do so?

PubMed

van Dongen, Anne; Abraham, Charles; Ruiter, Robert A C; Schaalma, Herman P; de Kort, Wim L A M; Dijkstra, J Anneke; Veldhuizen, Ingrid J T

2012-06-01

This study investigated the possibility of rerecruiting lapsed blood donors. Reasons for donation cessation, motivation to restart donation, and modifiable components of donation motivation were examined. We distinguished between lapsed donors who had passively withdrawn by merely not responding to donation invitations and donors who had contacted the blood bank to actively withdraw. A cross-sectional survey was sent to 400 actively lapsed donors and to 400 passively lapsed donors, measuring intention to restart donation and psychological correlates of restart intention. The data were analyzed using multiple regression analyses. The response rate among actively lapsed donors was higher than among passively lapsed donors (37% vs. 25%). Actively lapsed donors typically ceased donating because of physical reactions, while passively lapsed donors quit because of a busy lifestyle. Nonetheless, 51% of actively lapsed responders and 80% of passively lapsed responders were willing to restart donations. Multiple regression analysis showed that, for passively lapsed donors, cognitive attitude was the strongest correlate of intention to donate in the future (β=0.605, p<0.001), with affective attitude (β=0.239, p<0.05) and self-efficacy (β=0.266, p<0.001) explaining useful proportions of the variance as well. For actively lapsed donors, cognitive attitude was also the strongest correlate of intention (β=0.601, p<0.001), with affective attitude (β=0.345, p<0.001) and moral norm (β=-0.118, p<0.05) explaining smaller proportions of the variance. The majority of lapsed donors indicated a moderate to high intention to restart donations. Interventions focusing on boosting cognitive and affective attitudes and self-efficacy could further raise such intentions. © 2011 American Association of Blood Banks.

A quantitative study of the relationship between the distribution of different types of collagen and the mechanical behavior of rabbit medial collateral ligaments.

PubMed

Wan, Chao; Hao, Zhixiu; Wen, Shizhu; Leng, Huijie

2014-01-01

The mechanical properties of ligaments are key contributors to the stability and function of musculoskeletal joints. Ligaments are generally composed of ground substance, collagen (mainly type I and III collagen), and minimal elastin fibers. However, no consensus has been reached about whether the distribution of different types of collagen correlates with the mechanical behaviors of ligaments. The main objective of this study was to determine whether the collagen type distribution is correlated with the mechanical properties of ligaments. Using axial tensile tests and picrosirius red staining-polarization observations, the mechanical behaviors and the ratios of the various types of collagen were investigated for twenty-four rabbit medial collateral ligaments from twenty-four rabbits of different ages, respectively. One-way analysis of variance was used in the comparison of the Young's modulus in the linear region of the stress-strain curves and the ratios of type I and III collagen for the specimens (the mid-substance specimens of the ligaments) with different ages. A multiple linear regression was performed using the collagen contents (the ratios of type I and III collagen) and the Young's modulus of the specimens. During the maturation of the ligaments, the type I collagen content increased, and the type III collagen content decreased. A significant and strong correlation (R2 = 0.839, P < 0.05) was identified by multiple linear regression between the collagen contents (i.e., the ratios of type I and type III collagen) and the mechanical properties of the specimens. The collagen content of ligaments might provide a new perspective for evaluating the linear modulus of global stress-strain curves for ligaments and open a new door for studying the mechanical behaviors and functions of connective tissues.

Ghrelin, leptin and insulin in cirrhotic children and adolescents: relationship with cirrhosis severity and nutritional status.

PubMed

Dornelles, Cristina T L; Goldani, Helena A S; Wilasco, Maria Inês A; Maurer, Rafael L; Kieling, Carlos O; Porowski, Marilene; Ferreira, Cristina T; Santos, Jorge L; Vieira, Sandra M G; Silveira, Themis R

2013-01-10

Ghrelin, leptin, and insulin concentrations are involved in the control of food intake and they seem to be associated with anorexia-cachexia in cirrhotic patients. The present study aimed to investigate the relationship between the nutritional status and fasting ghrelin, leptin and insulin concentrations in pediatric cirrhotic patients. Thirty-nine patients with cirrhosis and 39 healthy controls aged 0-15 years matched by sex and age were enrolled. Severity of liver disease was assessed by Child-Pugh classification, and Pediatric for End Stage Liver Disease (PELD) or Model for End-stage Liver Disease (MELD) scores. Blood samples were collected from patients and controls to assay total ghrelin, acyl ghrelin, leptin and insulin by using a commercial ELISA kit. Anthropometry parameters used were standard deviation score of height-for-age and triceps skinfold thickness-for-age ratio. A multiple linear regression analysis was used to determine the correlation between dependent and independent variables. Acyl ghrelin was significantly lower in cirrhotic patients than in controls [142 (93-278) pg/mL vs 275 (208-481) pg/mL, P=0.001]. After multiple linear regression analysis, total ghrelin and acyl ghrelin showed an inverse correlation with age; acyl ghrelin was associated with the severity of cirrhosis and des-acyl ghrelin with PELD or MELD scores ≥15. Leptin was positively correlated with gender and anthropometric parameters. Insulin was not associated with any variable. Low acyl ghrelin and high des-acyl ghrelin concentrations were associated with cirrhosis severity, whereas low leptin concentration was associated with undernourishment in children and adolescents with cirrhosis. Copyright © 2012 Elsevier B.V. All rights reserved.

Skin autofluorescence is associated with renal function and cardiovascular diseases in pre-dialysis chronic kidney disease patients.

PubMed

Tanaka, Kenichi; Tani, Yoshihiro; Asai, Jun; Nemoto, Fumihiko; Kusano, Yuki; Suzuki, Hodaka; Hayashi, Yoshimitsu; Asahi, Koichi; Katoh, Tetsuo; Miyata, Toshio; Watanabe, Tsuyoshi

2011-01-01

Tissue accumulation of advanced glycation end-products (AGE) is thought to be a contributing factor to the progression of cardiovascular disease (CVD). Skin autofluorescence, a non-invasive measure of AGE accumulation using autofluorescence of the skin under ultraviolet light, has shown associations with CVD in haemodialysis patients. The present study aimed to evaluate relationships of skin autofluorescence to renal function as well as CVD in pre-dialysis patients with chronic kidney disease (CKD). Subjects in this cross-sectional analysis comprised 304 pre-dialysis CKD patients [median age, 62.0 years; median estimated glomerular filtration rate (eGFR), 54.3 mL/min/1.73 m(2); diabetes, n = 81 (26.6%)]. AGE accumulation in skin was assessed by skin autofluorescence using an autofluorescence reader. Relationships between skin autofluorescence, eGFR, CVD history and other parameters were evaluated. Skin autofluorescence correlated negatively with eGFR (r = -0.42, P < 0.01) and increased as CKD stage advanced. Multiple regression analysis revealed significant correlations of skin autofluorescence with age, presence of diabetes, eGFR and CVD history in CKD patients (R(2) = 30%). Age, male gender, smoking history, skin autofluorescence and eGFR were significantly correlated with CVD history, and multiple logistic regression analysis identified age [odds ratio (OR), 1.09; 95% confidence interval (CI), 1.03-1.15; P < 0.01], history of smoking (OR, 6.50; 95%CI, 1.94-21.83; P < 0.01) and skin autofluorescence (OR, 3.74; 95%CI, 1.54-9.24; P < 0.01) as independent factors. Tissue AGE accumulation measured as skin autofluorescence increased as GFR decreased and was related to CVD history in CKD patients. Non-invasive autofluorescence readers may provide potential markers for clinical risk assessment in pre-dialysis CKD patients.

Glutamate and GABA contributions to medial prefrontal cortical activity to emotion: implications for mood disorders.

PubMed

Stan, Ana D; Schirda, Claudiu V; Bertocci, Michele A; Bebko, Genna M; Kronhaus, Dina M; Aslam, Haris A; LaBarbara, Eduard J; Tanase, Costin; Lockovich, Jeanette C; Pollock, Myrna H; Stiffler, Richelle S; Phillips, Mary L

2014-09-30

The dorsomedial prefrontal cortex (MdPFC) and anterior cingulate cortices (ACC) play a critical role in implicit emotion regulation; however the understanding of the specific neurotransmitters that mediate such role is lacking. In this study, we examined relationships between MdPFC concentrations of two neurotransmitters, glutamate and γ-amino butyric acid (GABA), and BOLD activity in ACC during performance of an implicit facial emotion-processing task. Twenty healthy volunteers, aged 20-35 years, were scanned while performing an implicit facial emotion-processing task, whereby presented facial expressions changed from neutral to one of the four emotions: happy, anger, fear, or sad. Glutamate concentrations were measured before and after the emotion-processing task in right MdPFC using magnetic resonance spectroscopy (MRS). GABA concentrations were measured in bilateral MdPFC after the emotion-processing task. Multiple regression models were run to determine the relative contribution of glutamate and GABA concentration, age, and gender to BOLD signal in ACC to each of the four emotions. Multiple regression analyses revealed a significant negative correlation between MdPFC GABA concentration and BOLD signal in subgenual ACC (p<0.05, corrected) to sad versus shape contrast. For the anger versus shape contrast, there was a significant negative correlation between age and BOLD signal in pregenual ACC (p<0.05, corrected) and a positive correlation between MdPFC glutamate concentration (pre-task) and BOLD signal in pregenual ACC (p<0.05, corrected). Our findings are the first to provide insight into relationships between MdPFC neurotransmitter concentrations and ACC BOLD signal, and could further understanding of molecular mechanisms underlying emotion processing in healthy and mood-disordered individuals. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Development and validation of the neck dissection impairment index: a quality of life measure.

PubMed

Taylor, Rodney J; Chepeha, Judith C; Teknos, Theodoros N; Bradford, Carol R; Sharma, Pramod K; Terrell, Jeffrey E; Hogikyan, Norman D; Wolf, Gregory T; Chepeha, Douglas B

2002-01-01

To validate a health-related quality-of-life (QOL) instrument for patients following neck dissection and to identify the factors that affect QOL following neck dissection. Cross-sectional validation study. The outpatient clinic of a tertiary care cancer center. Convenience sample of 54 patients previously treated for head and neck cancer who underwent a selective neck dissection or modified radical neck dissection (64 total neck dissections). Patients had a minimum postoperative convalescence of 11 months. Thirty-two underwent accessory nerve-sparing modified radical neck dissection, and 32 underwent selective neck dissection. A 10-item, self-report instrument, the Neck Dissection Impairment Index (NDII), was developed and validated. Reliability was evaluated with test-retest correlation and internal consistency using the Cronbach alpha coefficient. Convergent validity was assessed using the 36-Item Short-Form Health Survey (SF-36) and the Constant Shoulder Scale, a shoulder function test. Multiple variable regression was used to determine variables that most affected QOL following neck dissection The 10-item NDII test-retest correlation was 0.91 (P<.001) with an internal consistency Cronbach alpha coefficient of.95. The NDII correlated with the Constant Shoulder Scale (r = 0.85, P<.001) and with the SF-36 physical functioning (r = 0.50, P<.001) and role-physical functioning (r = 0.60, P<.001) domains. Using multiple variable regression, the variables that contributed most to QOL score were patient's age and weight, radiation treatment, and neck dissection type. The NDII is a valid, reliable instrument for assessing neck dissection impairment. Patient's age, weight, radiation treatment, and neck dissection type were important factors that affect QOL following neck dissection.

Serum Vitamin D Status in Iranian Fibromyalgia Patients: according to the Symptom Severity and Illness Invalidation

PubMed Central

Maafi, Alireza Amir; Haghdoost, Afrooz; Aarabi, Yasaman; Hajiabbasi, Asghar; Shenavar Masooleh, Irandokht; Zayeni, Habib; Ghalebaghi, Babak; Hassankhani, Amir; Bidari, Ali

2016-01-01

Background This study was designed to assess serum vitamin D status (25-OHD) in the fibromyalgia (FM) patients and to compare it with a healthy control group. It also aimed to investigate the correlation of serum vitamin D level with FM symptom severity and invalidation experiences. Methods A total of 74 consecutive patients with FM and 68 healthy control participants were enrolled. The eligible FM patients completed the Illness Invalidation Inventory (3*I), the Revised Fibromyalgia Impact Questionnaire (FIQR) and a short-form health survey (SF-12). Venous blood samples were drawn from all participants to evaluate serum 25-OHD levels. Mann-Whitney tests and multiple logistic regression analyses were performed and Spearman's correlations were calculated. Results 88.4% of FM patients had low levels of serum 25-OHD. FM patients had significantly higher level of serum 25-OHD than the control group (17.24 ± 13.50 and 9.91 ± 6.47 respectively, P = 0.0001). There were no significant correlations between serum 25-OHD levels and the clinical measures of disease impact, invalidation dimensions, and health status. Multiple logistic regression analyses revealed that an increased discounting of the disease by the patient's spouse was associated with a 4-fold increased risk for vitamin D deficiency (OR = 4.36; 95% CI, 0.95–19.87, P = 0.05). Conclusions This study showed that although high rates of vitamin D insufficiency or deficiency were seen among FM patients and healthy non-FM participants, but it seems there was no intrinsic association between FM and vitamin D deficiency. Addressing of invalidation experience especially by the patient's spouse is important in management of FM. PMID:27413482

Measuring Medical Students' Empathy: Exploring the Underlying Constructs of and Associations Between Two Widely Used Self-Report Instruments in Five Countries.

PubMed

Costa, Patrício; de Carvalho-Filho, Marco Antonio; Schweller, Marcelo; Thiemann, Pia; Salgueira, Ana; Benson, John; Costa, Manuel João; Quince, Thelma

2017-06-01

Understanding medical student empathy is important to future patient care; however, the definition and development of clinical empathy remain unclear. The authors sought to examine the underlying constructs of two of the most widely used self-report instruments-Davis's Interpersonal Reactivity Index (IRI) and the Jefferson Scale of Empathy version for medical students (JSE-S)-plus, the distinctions and associations between these instruments. Between 2007 and 2014, the authors administered the IRI and JSE-S in three separate studies in five countries, (Brazil, Ireland, New Zealand, Portugal, and the United Kingdom). They collected data from 3,069 undergraduate medical students and performed exploratory factor analyses, correlation analyses, and multiple linear regression analyses. Exploratory factor analysis yielded identical results in each country, confirming the subscale structures of each instrument. Results of correlation analyses indicated significant but weak correlations (r = 0.313) between the total IRI and JSE-S scores. All intercorrelations of IRI and JSE-S subscale scores were statistically significant but weak (range r = -0.040 to 0.306). Multiple linear regression models revealed that the IRI subscales were weak predictors of all JSE-S subscale and total scores. The IRI subscales explained between 9.0% and 15.3% of variance for JSE-S subscales and 19.5% for JSE-S total score. The IRI and JSE-S are only weakly related, suggesting that they may measure different constructs. To better understand this distinction, more studies using both instruments and involving students at different stages in their medical education, as well as more longitudinal and qualitative studies, are needed.

[Association between distribution of bacillary dysentery and meteorological factors in Beijing, 2004-2015].

PubMed

Du, Z; Zhang, J; Lu, J X; Lu, L P

2018-05-10

Objective: To analyze the distribution characteristics of bacillary dysentery in Beijing during 2004-2015 and evaluate the influence of meteorological factors on the temporal and spatial distribution of bacillary dysentery. Methods: The incidence data of bacterial dysentery and meteorological data in Beijing from 2004 to 2015 were collected. Descriptive epidemiological analysis was conducted to study the distribution characteristics of bacterial dysentery. Linear correlation analysis and multiple linear regression analysis were carried out to investigate the relationship between the incidence of bacillary dysentery and average precipitation, average air temperature, sunshine hours, average wind speed, average air pressure, gale and rain days. Results: A total of 280 704 cases of bacterial dysentery, including 36 deaths, were reported from 2004 to 2015 in Beijing, the average annual incidence was 130.15/100 000. The annual incidence peak was mainly between May and October, the cases occurred during this period accounted for 80.75 % of the total, and the incidence was highest in age group 0 year. The population distribution showed that most cases were children outside child care settings and students, and the sex ratio of the cases was 1.22∶1. The reported incidence of bacillary dysentery was positively associated with average precipitation, average air temperature and rain days with the correlation coefficients of 0.931, 0.878 and 0.888, but it was negatively associated with the average pressure, the correlation coefficient was -0.820. Multiple linear regression equation for fitting analysis of bacillary dysentery and meteorological factors was Y =3.792+0.162 X (1). Conclusion: The reported incidence of bacillary dysentery in Beijing was much higher than national level. The annual incidence peak was during July to August, and the average precipitation was an important meteorological factor influencing the incidence of bacillary dysentery.

The extent of using mobility assistive devices can partly explain fatigue among persons with late effects of polio - a retrospective registry study in Sweden.

PubMed

Santos Tavares Silva, I; Sunnerhagen, K S; Willén, C; Ottenvall Hammar, I

2016-11-18

Fatigue is reported as one of the most disabling symptoms and is common among persons living with late effects of polio. Although fatigue has been studied in the context of people living with late effects of polio, there is a lack of knowledge concerning the association of fatigue and variables of importance for participation in daily life. Therefore, the aim of this study was to explore possible factors associated with fatigue among persons with late effects of polio in Sweden. This retrospective registry study consisted of 89 persons with late effects of polio living in Sweden. Fatigue was measured with the Multidimensional Fatigue Inventory (MFI-20) scale, Swedish version. Pearson's correlation coefficient was used to analyse the correlation between the factors and fatigue, and a multiple linear regression was carried out to explore factors for fatigue. Fatigue statistically significantly correlated with age (r = 0.234, p < 0.05) and the use of mobility assistive devices (r = 0.255, p < 0.05). The multiple linear regression model showed that the factors age (β = 0.304, p < 0.019) and mobility assistive devices (β = 0.262, p < 0.017) were associated with fatigue among persons living with late effects of polio, and the model partly explained 14% of the variation of fatigue. Fatigue could partly be explained by the extent of using mobility assistive devices and age. Healthcare professionals should provide and demonstrate the importance of assistive devices to ensure management of fatigue in persons living with late effects of polio.

Measuring the impact of multiple sclerosis on psychosocial functioning: the development of a new self-efficacy scale.

PubMed

Airlie, J; Baker, G A; Smith, S J; Young, C A

2001-06-01

To develop a scale to measure self-efficacy in neurologically impaired patients with multiple sclerosis and to assess the scale's psychometric properties. Cross-sectional questionnaire study in a clinical setting, the retest questionnaire returned by mail after completion at home. Regional multiple sclerosis (MS) outpatient clinic or the Clinical Trials Unit (CTU) at a large neuroscience centre in the UK. One hundred persons with MS attending the Walton Centre for Neurology and Neurosurgery and Clatterbridge Hospital, Wirral, as outpatients. Cognitively impaired patients were excluded at an initial clinic assessment. Patients were asked to provide demographic data and complete the self-efficacy scale along with the following validated scales: Hospital Anxiety and Depression Scale, Rosenberg Self-Esteem Scale, Impact, Stigma and Mastery and Rankin Scales. The Rankin Scale and Barthel Index were also assessed by the physician. A new 11-item self-efficacy scale was constructed consisting of two domains of control and personal agency. The validity of the scale was confirmed using Cronbach's alpha analysis of internal consistency (alpha = 0.81). The test-retest reliability of the scale over two weeks was acceptable with an intraclass correlation coefficient of 0.79. Construct validity was investigated using Pearson's product moment correlation coefficient resulting in significant correlations with depression (r= -0.52) anxiety (r =-0.50) and mastery (r= 0.73). Multiple regression analysis demonstrated that these factors accounted for 70% of the variance of scores on the self-efficacy scale, with scores on mastery, anxiety and perceived disability being independently significant. Assessment of the psychometric properties of this new self-efficacy scale suggest that it possesses good validity and reliability in patients with multiple sclerosis.

Drug treatment rates with beta-blockers and ACE-inhibitors/angiotensin receptor blockers and recurrences in takotsubo cardiomyopathy: A meta-regression analysis.

PubMed

Brunetti, Natale Daniele; Santoro, Francesco; De Gennaro, Luisa; Correale, Michele; Gaglione, Antonio; Di Biase, Matteo

2016-07-01

In a recent paper Singh et al. analyzed the effect of drug treatment on recurrence of takotsubo cardiomyopathy (TTC) in a comprehensive meta-analysis. The study found that recurrence rates were independent of clinic utilization of BB prescription, but inversely correlated with ACEi/ARB prescription: authors therefore conclude that ACEi/ARB rather than BB may reduce risk of recurrence. We aimed to re-analyze data reported in the study, now weighted for populations' size, in a meta-regression analysis. After multiple meta-regression analysis, we found a significant regression between rates of prescription of ACEi and rates of recurrence of TTC; regression was not statistically significant for BBs. On the bases of our re-analysis, we confirm that rates of recurrence of TTC are lower in populations of patients with higher rates of treatment with ACEi/ARB. That could not necessarily imply that ACEi may prevent recurrence of TTC, but barely that, for example, rates of recurrence are lower in cohorts more compliant with therapy or more prescribed with ACEi because more carefully followed. Randomized prospective studies are surely warranted. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Improving Lidar-based Aboveground Biomass Estimation with Site Productivity for Central Hardwood Forests, USA

NASA Astrophysics Data System (ADS)

Shao, G.; Gallion, J.; Fei, S.

2016-12-01

Sound forest aboveground biomass estimation is required to monitor diverse forest ecosystems and their impacts on the changing climate. Lidar-based regression models provided promised biomass estimations in most forest ecosystems. However, considerable uncertainties of biomass estimations have been reported in the temperate hardwood and hardwood-dominated mixed forests. Varied site productivities in temperate hardwood forests largely diversified height and diameter growth rates, which significantly reduced the correlation between tree height and diameter at breast height (DBH) in mature and complex forests. It is, therefore, difficult to utilize height-based lidar metrics to predict DBH-based field-measured biomass through a simple regression model regardless the variation of site productivity. In this study, we established a multi-dimension nonlinear regression model incorporating lidar metrics and site productivity classes derived from soil features. In the regression model, lidar metrics provided horizontal and vertical structural information and productivity classes differentiated good and poor forest sites. The selection and combination of lidar metrics were discussed. Multiple regression models were employed and compared. Uncertainty analysis was applied to the best fit model. The effects of site productivity on the lidar-based biomass model were addressed.