Survival analysis is commonly conducted in medical and public health research to assess the association of an exposure or intervention with a hard end outcome such as mortality. The Cox (proportional hazards) regression model is probably the most popular statistical tool used in this context. However, when the exposure includes compositional covariables (that is, variables representing a relative makeup such as a nutritional or physical activity behaviour composition), some basic assumptions of the Cox regression model and associated significance tests are violated. Compositional variables involve an intrinsic interplay between one another which precludes results and conclusions based on considering them in isolation as is ordinarily done. In this work, we introduce a formulation of the Cox regression model in terms of log-ratio coordinates which suitably deals with the constraints of compositional covariates, facilitates the use of common statistical inference methods, and allows for scientifically meaningful interpretations. We illustrate its practical application to a public health problem: the estimation of the mortality hazard associated with the composition of daily activity behaviour (physical activity, sitting time and sleep) using data from the U.S. National Health and Nutrition Examination Survey (NHANES).

• Keywords
• Cox regression, NHANES, Survival analysis, accelerometry, compositional data, physical activity, sedentary behaviour, time use,
• MeSH
• Exercise * MeSH
• Proportional Hazards Models MeSH
• Regression Analysis MeSH
• Nutrition Surveys MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Three algorithms for assessment of respiratory sinus arrhythmia (RSA) have been evaluated: cross-correlation function, histogram analysis and regression plot. The algorithms were tested experimentally in a group of 11 subjects. A cross-correlation function with a high time resolution (1 ms) was used for investigation of the time lag between instantaneous heart rate and respiration (CTL). This time lag was not affected by the breathing rate in a range of 8 to 29 breaths per minute. A mathematical model of CTL compared with experimental results indicates that respiratory sinus arrhythmia is probably modulated directly by the respiratory network in the brainstem rather than by a baroreflex in the range of breathing rate investigated. Histogram analysis reflects the impact of inspiration and expiration on respiratory sinus arrhythmia. For this purpose heart rate changes were separated into two distributions (inspiration-expiration). The result value (U-VAL) of the Mann-Whitney U-test reflects the impact of respiration on heart rate variability. Regression analysis of heart rate versus respiration shows that the heart rate increase is more closely coupled to inspiration than the heart rate decrease to expiration. Both, CTL and U-VAL are thought to be useful parameters for clinical investigation of RSA.

• MeSH
• Algorithms * MeSH
• Models, Biological MeSH
• Adult MeSH
• Respiration physiology   MeSH
• Humans MeSH
• Brain Stem physiology   MeSH
• Nerve Net physiology   MeSH
• Regression Analysis MeSH
• Heart Rate physiology   MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Male MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Comparative Study MeSH

This research proposes an assessment and decision support model to use when a driver should be examined about their propensity for traffic accidents, based on an estimation of the driver's psychological traits. The proposed model was tested on a sample of 305 drivers. Each participant completed four psychological tests: the Barratt Impulsiveness Scale (BIS-11), the Aggressive Driving Behaviour Questionnaire (ADBQ), the Manchester Driver Attitude Questionnaire (DAQ) and the Questionnaire for Self-assessment of Driving Ability. In addition, participants completed an extensive demographic and driving survey. Various fuzzy inference systems were tested and each was defined using the well-known Wang-Mendel method for rule-base definition based on empirical data. For this purpose, a programming code was designed and utilized. Based on the obtained results, it was determined which combination of the considered psychological tests provides the best prediction of a driver's propensity for traffic accidents. The best of the considered fuzzy inference systems might be used as a decision support tool in various situations, such as in recruitment procedures for professional drivers. The validity of the proposed fuzzy approach was confirmed as its implementation provided better results than from statistics, in this case multiple regression analysis.

• Keywords
• Traffic accidents, driving behaviour, fuzzy rules based on data, fuzzy systems, multiple regression, road safety,
• MeSH
• Aggression MeSH
• Safety MeSH
• Accidents, Traffic * MeSH
• Adult MeSH
• Fuzzy Logic MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Attitude MeSH
• Surveys and Questionnaires MeSH
• Models, Psychological * MeSH
• Regression Analysis MeSH
• Automobile Driving psychology   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

BACKGROUND: Economic data pertaining to cystic fibrosis (CF), is limited in Europe generally, and completely lacking in Central and Eastern Europe. We performed an analysis of all direct costs associated with CF relative to key disease features and laboratory examinations. METHODS: A retrospective prevalence-based cost-of-illness (COI) study was performed in a representative cohort of 242 CF patients in the Czech Republic, which represents about 65 % of all Czech CF patients. Medical records and invoices to health insurance companies for reference year 2010 were analyzed. RESULTS: The mean total health care costs were €14,486 per patient, with the majority of the costs going towards medicinal products and devices (€10,321). Medical procedures (€2676) and inpatient care (€1829) represented a much smaller percentage of costs. A generalized linear model showed that the strongest cost drivers, for all cost categories, were associated with patient age and lung disease severity (assessed using the FEV1 spirometric parameter), when compounded by chronic Pseudomonas aeruginosa airway infections. Specifically, maximum total costs are around the age 16 years; a FEV1 increase of 1 % point represented a cost decrease of: 0.9 % (medicinal products), 1.7 % (total costs), 2.8 % (procedures) and 7.0 % (inpatient care). CONCLUSIONS: COI analysis and regression modeling using the most recent data available can provide a better understanding of the overall economic CF burden. A comparison of our results with other methodologically similar studies demonstrates that although overall costs may differ, FEV1 can nonetheless be utilized as a generally transferrable indicator of the relative economic impact of CF.

• Keywords
• Cost-of-illness, Cystic fibrosis, Disease severity, FEV1, Generalized linear model, Health care costs,
• MeSH
• Cystic Fibrosis economics   epidemiology   physiopathology   MeSH
• Child MeSH
• Adult MeSH
• Humans MeSH
• Adolescent MeSH
• Health Care Costs statistics & numerical data   MeSH
• Cost of Illness * MeSH
• Child, Preschool MeSH
• Prevalence MeSH
• Pseudomonas Infections economics   epidemiology   MeSH
• Regression Analysis MeSH
• Retrospective Studies MeSH
• Spirometry MeSH
• Check Tag
• Child MeSH
• Adult MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Child, Preschool MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Czech Republic epidemiology   MeSH

When drugs are poorly soluble then, instead of the potentiometric determination of dissociation constants, pH-spectrophotometric titration can be used along with nonlinear regression of the absorbance response surface data. Generally, regression models are extremely useful for extracting the essential features from a multiwavelength set of data. Regression diagnostics represent procedures for examining the regression triplet (data, model, method) in order to check (a) the data quality for a proposed model; (b) the model quality for a given set of data; and (c) that all of the assumptions used for least squares hold. In the interactive, PC-assisted diagnosis of data, models and estimation methods, the examination of data quality involves the detection of influential points, outliers and high leverages, that cause many problems when regression fitting the absorbance response hyperplane. All graphically oriented techniques are suitable for the rapid estimation of influential points. The reliability of the dissociation constants for the acid drug silybin may be proven with goodness-of-fit tests of the multiwavelength spectrophotometric pH-titration data. The uncertainty in the measurement of the pK (a) of a weak acid obtained by the least squares nonlinear regression analysis of absorption spectra is calculated. The procedure takes into account the drift in pH measurement, the drift in spectral measurement, and all of the drifts in analytical operations, as well as the relative importance of each source of uncertainty. The most important source of uncertainty in the experimental set-up for the example is the uncertainty in the pH measurement. The influences of various sources of uncertainty on the accuracy and precision are discussed using the example of the mixed dissociation constants of silybin, obtained using the SQUAD(84) and SPECFIT/32 regression programs.

• MeSH
• Antioxidants analysis   chemistry   MeSH
• Time Factors MeSH
• Models, Chemical MeSH
• Hydrogen-Ion Concentration MeSH
• Pharmaceutical Preparations chemistry   MeSH
• Least-Squares Analysis * MeSH
• Regression Analysis * MeSH
• Sensitivity and Specificity MeSH
• Silybin MeSH
• Silymarin analysis   chemistry   MeSH
• Spectrophotometry methods   MeSH
• Drug Stability MeSH
• Titrimetry methods   MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Antioxidants MeSH
• Pharmaceutical Preparations MeSH
• Silybin MeSH
• Silymarin MeSH

The distribution of time that people spend in physical activity of various intensities has important health implications. Physical activity (commonly categorised by the intensity into light, moderate and vigorous physical activity), sedentary behaviour and sleep, should not be analysed separately, because they are parts of a time-use composition with a natural constraint of 24 h/day. To find out how are relative reallocations of time between physical activity of various intensities associated with health, herewith we describe compositional scalar-on-function regression and a newly developed compositional functional isotemporal substitution analysis. Physical activity intensity data can be considered as probability density functions, which better reflects the continuous character of their measurement using accelerometers. These probability density functions are characterised by specific properties, such as scale invariance and relative scale, and they are geometrically represented using Bayes spaces with the Hilbert space structure. This makes possible to process them using standard methods of functional data analysis in the L2 space, via centred logratio (clr) transformation. The scalar-on-function regression with clr transformation of the explanatory probability density functions and compositional functional isotemporal substitution analysis were applied to a dataset from a cross-sectional study on adiposity conducted among school-aged children in the Czech Republic. Theoretical reallocations of time to physical activity of higher intensities were found to be associated with larger and more progressive expected decreases in adiposity. We obtained a detailed insight into the dose-response relationship between physical activity intensity and adiposity, which was enabled by using the compositional functional approach.

• Keywords
• Compositional scalar-on-function regression, isotemporal substitution, physical activity, probability density functions, sedentary behaviour, sleep,
• MeSH
• Adiposity * MeSH
• Bayes Theorem MeSH
• Time Factors MeSH
• Exercise * physiology   MeSH
• Child MeSH
• Humans MeSH
• Obesity * MeSH
• Cross-Sectional Studies MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Publication type
• Journal Article MeSH

• MeSH
• Accidents, Traffic * MeSH
• Humans MeSH
• Wounds and Injuries MeSH
• Regression Analysis * MeSH
• Statistics as Topic * MeSH
• Check Tag
• Humans MeSH
• Publication type
• English Abstract MeSH
• Journal Article MeSH

Field crops represent one of the highest contributions to dietary metal exposure. The aim of this study was to develop specific regression models for the uptake of metals into various field crops and to compare the usability of other available models. We analysed samples of potato, hop, maize, barley, wheat, rape seed, and grass from 66 agricultural sites. The influence of measured soil concentrations and soil factors (pH, organic carbon, content of silt and clay) on the plant concentrations of Cd, Cr, Cu, Mo, Ni, Pb and Zn was evaluated. Bioconcentration factors (BCF) and plant-specific metal models (PSMM) developed from multivariate regressions were calculated. The explained variability of the models was from 19 to 64% and correlations between measured and predicted concentrations were between 0.43 and 0.90. The developed hop and rapeseed models are new in this field. Available models from literature showed inaccurate results, except for Cd; the modelling efficiency was mostly around zero. The use of interaction terms between parameters can significantly improve plant-specific models.

• Keywords
• Field crops, Heavy metals, Linear regression, Plant uptake, Prediction models,
• MeSH
• Brassica rapa chemistry   MeSH
• Food Contamination MeSH
• Zea mays chemistry   MeSH
• Soil Pollutants analysis   MeSH
• Environmental Monitoring methods   statistics & numerical data   MeSH
• Multivariate Analysis MeSH
• Triticum chemistry   MeSH
• Soil chemistry   MeSH
• Regression Analysis MeSH
• Models, Theoretical * MeSH
• Metals, Heavy analysis   MeSH
• Crops, Agricultural chemistry   MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Czech Republic MeSH
• Names of Substances
• Soil Pollutants MeSH
• Soil MeSH
• Metals, Heavy MeSH

Experiments were carried out in the genetically hypertensive obese rats of Koletsky type (SHR/N-cp) and in their lean siblings. Regression analysis was performed when plasma triglycerides was used as a dependent variable and plasma insulin, insulin binding to erythrocytes, basal plasma glucose tolerance data were used as independent variables. Coefficient determination (R2) as well as the tests of hypotheses of regression coefficients being zero were used to indicate which independent variables contributed the least in the explanation of dependent variable. This way we reduced the list of variables to give a simpler regression equation. In the control animals insulinemia was found to be dominant independent variable in all groups except SHR/N-cp obese females where the dominant independent variable was represented by the basal plasma glycaemia. Under the terguride treatment only in SHR/N-cp female rats the dominant independent variable remained the same as in controls. In the other groups the dominant independent variable was different in relation to the control animals. Long lasting terguride treatment normalized hypertriglyceridemia only in SHR/N-cp obese females. Thus the data obtained by multiple regression analysis of parameters of lipide and glycide metabolism show the close relationship to alleviating effect of terguride in hypertriglyceridemia.

• MeSH
• Dopamine Agonists pharmacology   MeSH
• Glucose metabolism   MeSH
• Glucose Tolerance Test MeSH
• Hypertension complications   metabolism   MeSH
• Insulin blood   MeSH
• Rats MeSH
• Lisuride analogs & derivatives   pharmacology   MeSH
• Obesity complications   metabolism   MeSH
• Rats, Inbred SHR MeSH
• Regression Analysis MeSH
• Triglycerides blood   MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Male MeSH
• Female MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Dopamine Agonists MeSH
• dironyl MeSH Browser
• Glucose MeSH
• Insulin MeSH
• Lisuride MeSH
• Triglycerides MeSH

The aim of our study was to examine in vivo and in vitro cytokines produced by Lewis ratderived R5-28 sarcoma cells. These cells produce rapidly growing tumours in approximately two weeks after subcutaneous inoculation. However, spontaneous tumour regression was noted in about 40% of animals. For an explanation of this phenomenon, we evaluated the profile of 19 cytokines during tumour growth and spontaneous regression by the use of "antibody array". To detect cytokines directly originated by the sarcoma, the R5-28 cells were cultivated in vitro and then both the supernatants and the cell lysates were analysed. Our experiments showed three cytokines (MCP-1, TIMP-1 and VEGF) to be produced by R5-28 cells in vitro. Moreover, in vivo, another three cytokines (TNF-alpha, beta-NGF and LIX) were detected both in blood sera and tumour lysates, probably produced by immune and stromal cells during tumour growth. Changes in their expression after spontaneous regression are discussed.

• MeSH
• Protein Array Analysis methods   MeSH
• Cytokines blood   MeSH
• Rats MeSH
• Disease Models, Animal MeSH
• Neoplasms blood   MeSH
• Rats, Inbred Lew MeSH
• Remission, Spontaneous MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Male MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Cytokines MeSH