Adult total wellness: group differences based on sitting time and physical activity level

Background An increasing body of evidence associates a high level of sitting time with poor health outcomes. The benefits of moderate to vigorous-intensity physical activities to various aspects of health are now well documented; however, individuals may engage in moderate-intensity physical activity for at least 30 minutes on five or more days of the week and still exhibit a high level of sitting time. This purpose of this study was to examine differences in total wellness among adults relative to high/low levels of sitting time combined with insufficient/sufficient physical activity (PA). The construct of total wellness incorporates a holistic approach to the body, mind and spirit components of life, an approach which may be more encompassing than some definitions of health. Methods Data were obtained from 226 adult respondents (27 ± 6 years), including 116 (51%) males and 110 (49%) females. Total PA and total sitting time were assessed with the International Physical Activity Questionnaire (IPAQ) (short-version). The Wellness Evaluation of Lifestyle Inventory was used to assess total wellness. An analysis of covariance (ANCOVA) was utilised to assess the effects of the sitting time/physical activity group on total wellness. A covariate was included to partial out the effects of age, sex and work status (student or employed). Cross-tabulations were used to show associations between the IPAQ derived high/low levels of sitting time with insufficient/sufficient PA and the three total wellness groups (i.e. high level of wellness, moderate wellness and wellness development needed). Results The majority of the participants were located in the high total sitting time and sufficient PA group. There were statistical differences among the IPAQ groups for total wellness [F (2,220) = 32.5 (p <0.001)]. A Chi-square test revealed a significant difference in the distribution of the IPAQ categories within the classification of wellness [χ2 (N = 226) = 54.5, p < .001]. One-hundred percent (100%) of participants who self-rated as high total sitting time/insufficient PA were found in the wellness development needed group. In contrast, 72% of participants who were located in the low total sitting time/sufficient PA group were situated in the moderate wellness group. Conclusion Many participants who meet the physical activity guidelines, in this sample, sit for longer periods of time than the median Australian sitting time. An understanding of the effects of the enhanced PA and reduced sitting time on total wellness can add to the development of public health initiatives. Keywords: IPAQ; The Wellness Evaluation of Lifestyle (WEL); Sedentary lifestyle

An analysis of MONTBLEX data on heat and momentum flux at Jodhpur

Parameterization of sensible heat and momentum fluxes as inferred from an analysis of tower observations archived during MONTBLEX-90 at Jodhpur is proposed, both in terms of standard exchange coefficients C-H and C-D respectively and also according to free convection scaling. Both coefficients increase rapidly at low winds (the latter more strongly) and with increasing instability. All the sensible heat flux data at Jodhpur (wind speed at 10m <(U)over bar (10)>, < 8ms(-1)) also obey free convection scaling, with the flux proportional to the '4/3' power of an appropriate temperature difference such as that between 1 and 30 m. Furthermore, for <(U)over bar (10)> < 4 ms(-1) the momentum flux displays a linear dependence on wind speed.

Growth and study of antiferroelectric lead zirconate thin films by pulsed laser ablation

Antiferroelectric lead zirconate (PZ) thin films were deposited by pulsed laser ablation on platinum-coated silicon substrates. Films showed a polycrystalline pervoskite structure upon annealing at 650 degrees C for 5-10 min. Dielectric properties were investigated as a function of temperature and frequency. The dielectric constant of PZ films was 220 at 100 kHz with a dissipation factor of 0.03. The electric field induced transformation from the antiferroelectric phase to the ferroelectric phase was observed through the polarization change, using a Sawyer-Tower circuit. The maximum polarization value obtained was 40 mu C/cm(2). The average fields to excite the ferroelectric state, and to reverse to the antiferroelectric state were 71 and 140 kV/cm, respectively. The field induced switching was also observed through double maxima in capacitance-voltage characteristics. Leakage current was studied in terms of current versus time and current versus voltage measurements. A leakage current density of 5x10(-7) A/cm(2) at 3 V, for a film of 0.7 mu m thickness, was noted at room temperature. The trap mechanism was investigated in detail in lead zirconate thin films based upon a space charge limited conduction mechanism. The films showed a backward switching time of less than 90 ns at room temperature.

Model selection with misspecified spatial covariance structure

Spatial data analysis has become more and more important in the studies of ecology and economics during the last decade. One focus of spatial data analysis is how to select predictors, variance functions and correlation functions. However, in general, the true covariance function is unknown and the working covariance structure is often misspecified. In this paper, our target is to find a good strategy to identify the best model from the candidate set using model selection criteria. This paper is to evaluate the ability of some information criteria (corrected Akaike information criterion, Bayesian information criterion (BIC) and residual information criterion (RIC)) for choosing the optimal model when the working correlation function, the working variance function and the working mean function are correct or misspecified. Simulations are carried out for small to moderate sample sizes. Four candidate covariance functions (exponential, Gaussian, Matern and rational quadratic) are used in simulation studies. With the summary in simulation results, we find that the misspecified working correlation structure can still capture some spatial correlation information in model fitting. When the sample size is large enough, BIC and RIC perform well even if the the working covariance is misspecified. Moreover, the performance of these information criteria is related to the average level of model fitting which can be indicated by the average adjusted R square ( [GRAPHICS] ), and overall RIC performs well.

Rank regression for accelerated failure time model with clustered and censored data

For clustered survival data, the traditional Gehan-type estimator is asymptotically equivalent to using only the between-cluster ranks, and the within-cluster ranks are ignored. The contribution of this paper is two fold: - (i) incorporating within-cluster ranks in censored data analysis, and; - (ii) applying the induced smoothing of Brown and Wang (2005, Biometrika) for computational convenience. Asymptotic properties of the resulting estimating functions are given. We also carry out numerical studies to assess the performance of the proposed approach and conclude that the proposed approach can lead to much improved estimators when strong clustering effects exist. A dataset from a litter-matched tumorigenesis experiment is used for illustration.

Working covariance model selection for generalized estimating equations

We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice.

Modeling strategies in longitudinal data analysis: Covariate, variance function and correlation structure selection

A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis. Appropriate selection of covariates is pertinent to correct variance modeling and selecting the appropriate covariates and variance function is vital to correlation structure selection. This leads to a stepwise model selection procedure that deploys a combination of different model selection criteria. Although these criteria find a common theoretical root based on approximating the Kullback-Leibler distance, they are designed to address different aspects of model selection and have different merits and limitations. For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures. The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported. Two longitudinal studies are used for illustration.

Working correlation structure misspecification, estimation and covariate design: Implications for generalised estimating equations performance

The method of generalised estimating equations for regression modelling of clustered outcomes allows for specification of a working matrix that is intended to approximate the true correlation matrix of the observations. We investigate the asymptotic relative efficiency of the generalised estimating equation for the mean parameters when the correlation parameters are estimated by various methods. The asymptotic relative efficiency depends on three-features of the analysis, namely (i) the discrepancy between the working correlation structure and the unobservable true correlation structure, (ii) the method by which the correlation parameters are estimated and (iii) the 'design', by which we refer to both the structures of the predictor matrices within clusters and distribution of cluster sizes. Analytical and numerical studies of realistic data-analysis scenarios show that choice of working covariance model has a substantial impact on regression estimator efficiency. Protection against avoidable loss of efficiency associated with covariance misspecification is obtained when a 'Gaussian estimation' pseudolikelihood procedure is used with an AR(1) structure.

Are we there yet? Advancing women in Canada and Australia: Similar goals, different policies

Differences in opportunities and outcomes in the workplace are inherent in a free and competitive market. However when differences between individuals and groups are identified as resulting from particular policies, behaviours or attitudes, any resulting inequality may be identified as unfair. Increasingly, unfair disparities in societies and their workplaces are regularly challenged. Many of the unfair disparities are recognised as caused through unfair discrimination (Anker 1997). When defining discrimination, the International Labour Organization Convention (ILO) No. 111 defines it as “any distinction, exclusion or preference made on the basis of race, colour, sex, religion, political opinion, national extraction, or social origin, which has the effect of nullifying or impairing equality of opportunity or treatment in employment or occupation” (ILO, 1958). Yet, the argument for addressing this ideal of ‘equality of opportunity’ is complex. Ekmekci (2013) identifies the difficulties as the determination of whether any process should be based on equality of opportunity or equality of outcome. In addition, there is the difficulty of determining what exactly constitutes a process for addressing unfair disparity due to the haziness of what constitutes discrimination and controversy in the meaning as well as policy implications of equality (Tomei, 2003).

Unsteady Incompressible Two-Dimensional and Axisymmetric Turbulent Boundary Layer Flows

The unsteady turbulent incompressible boundary-layer flow over two-dimensional and axisymmetric bodies with pressure gradient has been studied. An eddy-viscosity model has been used to model the Reynolds shear stress. The unsteadiness is due to variations in the free stream velocity with time. The nonlinear partial differential equation with three independent variables governing the flow has been solved using Keller's Box method. The results indicate that the free stram velocity distribution exerts strong influence on the boundary-layer characteristics. The point of zero skin friction is found to move upstream as time increases.

Methodological and Empirical Advances in the Quantitative Analysis of Spontaneous Responses in Psychophysiological Time Series

The aim of the present study was to advance the methodology and use of time series analysis to quantify dynamic structures in psychophysiological processes and thereby to produce information on spontaneously coupled physiological responses and their behavioral and experiential correlates. Series of analyses using both simulated and empirical cardiac (IBI), electrodermal (EDA), and facial electromyographic (EMG) data indicated that, despite potential autocorrelated structures, smoothing increased the reliability of detecting response coupling from an interindividual distribution of intraindividual measures and that especially the measures of covariance produced accurate information on the extent of coupled responses. This methodology was applied to analyze spontaneously coupled IBI, EDA, and facial EMG responses and vagal activity in their relation to emotional experience and personality characteristics in a group of middle-aged men (n = 37) during the administration of the Rorschach testing protocol. The results revealed new characteristics in the relationship between phasic end-organ synchronization and vagal activity, on the one hand, and individual differences in emotional adjustment to novel situations on the other. Specifically, it appeared that the vagal system is intimately related to emotional and social responsivity. It was also found that the lack of spontaneously synchronized responses is related to decreased energetic arousal (e.g., depression, mood). These findings indicate that the present process analysis approach has many advantages for use in both experimental and applied research, and that it is a useful new paradigm in psychophysiological research. Keywords: Autonomic Nervous System; Emotion; Facial Electromyography; Individual Differences; Spontaneous Responses; Time Series Analysis; Vagal System

Genetic analysis for a shared biological basis between migraine and coronary artery disease

Objective: To apply genetic analysis of genome-wide association data to study the extent and nature of a shared biological basis between migraine and coronary artery disease (CAD). Methods: Four separate methods for cross-phenotype genetic analysis were applied on data from 2 large-scale genome-wide association studies of migraine (19,981 cases, 56,667 controls) and CAD (21,076 cases, 63,014 controls). The first 2 methods quantified the extent of overlapping risk variants and assessed the load of CAD risk loci in migraineurs. Genomic regions of shared risk were then identified by analysis of covariance patterns between the 2 phenotypes and by querying known genome-wide significant loci. Results: We found a significant overlap of genetic risk loci for migraine and CAD. When stratified by migraine subtype, this was limited to migraine without aura, and the overlap was protective in that patients with migraine had a lower load of CAD risk alleles than controls. Genes indicated by 16 shared risk loci point to mechanisms with potential roles in migraine pathogenesis and CAD, including endothelial dysfunction (PHACTR1) and insulin homeostasis (GIP). Conclusions: The results suggest that shared biological processes contribute to risk of migraine and CAD, but surprisingly this commonality is restricted to migraine without aura and the impact is in opposite directions. Understanding the mechanisms underlying these processes and their opposite relationship to migraine and CAD may improve our understanding of both disorders.

Shared genetic basis for migraine and ischemic stroke: A genome-wide analysis of common variants

OBJECTIVE To quantify genetic overlap between migraine and ischemic stroke (IS) with respect to common genetic variation. METHODS We applied 4 different approaches to large-scale meta-analyses of genome-wide data on migraine (23,285 cases and 95,425 controls) and IS (12,389 cases and 62,004 controls). First, we queried known genome-wide significant loci for both disorders, looking for potential overlap of signals. We then analyzed the overall shared genetic load using polygenic scores and estimated the genetic correlation between disease subtypes using data derived from these models. We further interrogated genomic regions of shared risk using analysis of covariance patterns between the 2 phenotypes using cross-phenotype spatial mapping. RESULTS We found substantial genetic overlap between migraine and IS using all 4 approaches. Migraine without aura (MO) showed much stronger overlap with IS and its subtypes than migraine with aura (MA). The strongest overlap existed between MO and large artery stroke (LAS; p = 6.4 x 10(-28) for the LAS polygenic score in MO) and between MO and cardioembolic stroke (CE; p = 2.7 x 10(-20) for the CE score in MO). CONCLUSIONS Our findings indicate shared genetic susceptibility to migraine and IS, with a particularly strong overlap between MO and both LAS and CE pointing towards shared mechanisms. Our observations on MA are consistent with a limited role of common genetic variants in this subtype.

The shared genetics of migraine and anxious depression

OBJECTIVES To investigate: - (1) whether shared genetic factors influence migraine and anxious depression; - (2) whether the genetic architecture of migraine depends on anxious depression; - (3) whether the association between migraine and anxious depression is causal. BACKGROUND Migraine and anxious depression frequently occur together, but little is known about the mechanisms causing this association. METHODS A twin study was conducted to model the genetic architecture of migraine and anxious depression and the covariance between them. Anxious depression was also added to the model as a moderator variable to examine whether anxious depression affects the genetic architecture of migraine. Causal models were explored with the co-twin control method. RESULTS Modest but significant phenotypic (rP=0.28), genetic (rG=0.30), and nonshared environmental (rE=0.26) correlations were found between the 2 traits. Interestingly, the heritability of migraine depended on the level of anxious depression: the higher the anxious depression score, the lower the relative contribution of genetic factors to the individual differences in migraine susceptibility. The observed risk patterns in discordant twins are most consistent with a bidirectional causal relationship. CONCLUSIONS These findings confirm the genetic association between migraine and anxious depression and are consistent with a syndromic association between the 2 traits. This highlights the importance of taking comorbidity into account in genetic studies of migraine, especially in the context of selection for large-scale genotyping efforts. Genetic studies may be most effective when migraine with and without comorbid anxious depression are treated as separate phenotypes.

Environmental and fishing effects on the dynamics of brown tiger prawn (Penaeus esculentus) in Moreton Bay (Australia)

This analysis of the variations of brown tiger prawn (Penaeus esculentus) catch in Moreton Bay multispecies trawl fishery estimated catchability using a delay difference model. It integrated several factors responsible for variations in catchability: targeting of fishing effort, increasing fishing power and changing availability. An analysis of covariance was used to define fishing events targeted at brown tiger prawns. A general linear model estimated inter-annual variations of fishing power. Temperature-induced changes in prawn behaviour played an important role on the dynamics of this fishery. Maximum likelihood estimates of targeted catchability (4.09 ± 0.42 × 10−4 boat-day−1) were twice as large as non-targeted catchability (1.86 ± 0.25 × 10−4 boat-day−1). The causes of recent declines in fishing effort in this fishery were discussed.