A longitudinal analysis of sex differences in bone mineral accrual in healthy 8-19-year-old boys and girls

Background: Although early in life there is little discernible difference in bone mass between boys and girls, at puberty sex differences are observed. It is uncertain if these differences represent differences in bone mass or just differences in anthropometric dimensions. Aim: The study aimed to identify whether sex independently affects bone mineral content (BMC) accrual in growing boys and girls. Three sites are investigated: total body (TB), femoral neck (FN) and lumbar spine (LS). Subjects and methods: 85 boys and 67 girls were assessed annually for seven consecutive years. BMC was assessed by dual energy X-ray absorptiometry (DXA). Biological age was defined as years from age at peak height velocity (PHV). Data were analysed using a hierarchical (random effects) modelling approach. Results: When biological age, body size and body composition were controlled, boys had statistically significantly higher TB and FN BMC at all maturity levels (p < 0.05). No independent sex differences were found at the LS (p > 0.05). Conclusion: Although a statistical significant sex effect is observed, it is less than the error of the measurement, and thus sex difference are debatable. In general, sex difference are explained by anthropometric difference

Sexual dimorphism of the femoral neck during the adolescent growth spurt: a structural analysis

Before puberty, there are only small sex differences in body shape and composition. During adolescence, sexual dimorphism in bone, lean, and fat mass increases, giving rise to the greater size and strength of the male skeleton. The question remains as to whether there are sex differences in bone strength or simply differences in anthropometric dimensions. To test this, we applied hip structural analysis (HSA) to derive strength and geometric indices of the femoral neck using bone densitometry scans (DXA) from a 6-year longitudinal study in Canadian children. Seventy boys and sixty-eight girls were assessed annually for 6 consecutive years. At the femoral neck, cross-sectional area (CSA, an index of axial strength), subperiosteal width (SPW), and section modulus (Z, an index of bending strength) were determined, and data were analyzed using a hierarchical (random effects) modeling approach. Biological age (BA) was defined as years from age at peak height velocity (PHV). When BA, stature, and total-body lean mass (TB lean) were controlled, boys had significantly higher Z than girls at all maturity levels (P < 0.05). Controlling height and TB lean for CSA demonstrated a significant independent sex by BA interaction effect (P < 0.05). That is, CSA was greater in boys before PHV but higher in girls after PHV The coefficients contributing the greatest proportion to the prediction of CSA, SPW, and Z were height and lean mass. Because the significant sex difference in Z was relatively small and close to the error of measurement, we questioned its biological significance. The sex difference in bending strength was therefore explained by anthropometric differences. In contrast to recent hypotheses, we conclude that the CSA-lean ratio does not imply altered mechanosensitivity in girls because bending dominates loading at the neck, and the Z-lean ratio remained similar between the sexes throughout adolescence. That is, despite the greater CSA in girls, the bone is strategically placed to resist bending; hence, the bones of girls and boys adapt to mechanical challenges in a similar way. (C) 2004 Elsevier Inc. All rights reserved.

Cold periods and coronary events: an analysis of populations worldwide

Study objective: To investigate the association between cold periods and coronary events, and the extent to which climate, sex, age, and previous cardiac history increase risk during cold weather. Design: A hierarchical analyses of populations from the World Health Organisation's MONICA project. Setting: Twenty four populations from the WHO's MONICA project, a 21 country register made between 1980 and 1995. Patients: People aged 35 - 64 years who had a coronary event. Main results: Daily rates of coronary events were correlated with the average temperature over the current and previous three days. In cold periods, coronary event rates increased more in populations living in warm climates than in populations living in cold climates, where the increases were slight. The increase was greater in women than in men, especially in warm climates. On average, the odds for women having an event in the cold periods were 1.07 higher than the odds for men (95% posterior interval: 1.03 to 1.11). The effects of cold periods were similar in those with and without a history of a previous myocardial infarction. Conclusions: Rates of coronary events increased during comparatively cold periods, especially in warm climates. The smaller increases in colder climates suggest that some events in warmer climates are preventable. It is suggested that people living in warm climates, particularly women, should keep warm on cold days.

Confirmatory factor analysis and psychometric properties of the Anxiety Sensitivity Index-Revised in clinical and normative populations

The present investigation aimed to critically examine the factor structure and psychometric properties of the Anxiety Sensitivity Index - Revised (ASI-R). Confirmatory factor analysis using a clinical sample of adults (N = 248) revealed that the ASI-R could be improved substantially through the removal of 15 problematic items in order to account for the most robust dimensions of anxiety sensitivity. This modified scale was renamed the 21-item Anxiety Sensitivity Index (21-item ASI) and reanalyzed with a large sample of normative adults (N = 435), revealing configural and metric invariance across groups. Further comparisons with other alternative models, using multi-sample analysis, indicated the 21-item ASI to be the best fitting model for both groups. There was also evidence of internal consistency, test-retest reliability, and construct validity for both samples suggesting that the 21-item ASI is a useful assessment device for investigating the construct of anxiety sensitivity in both clinical and normative populations.

On the statistical analysis of the GS-NS0 cell proteome: Imputation, clustering and variability testing

We have undertaken two-dimensional gel electrophoresis proteomic profiling on a series of cell lines with different recombinant antibody production rates. Due to the nature of gel-based experiments not all protein spots are detected across all samples in an experiment, and hence datasets are invariably incomplete. New approaches are therefore required for the analysis of such graduated datasets. We approached this problem in two ways. Firstly, we applied a missing value imputation technique to calculate missing data points. Secondly, we combined a singular value decomposition based hierarchical clustering with the expression variability test to identify protein spots whose expression correlates with increased antibody production. The results have shown that while imputation of missing data was a useful method to improve the statistical analysis of such data sets, this was of limited use in differentiating between the samples investigated, and highlighted a small number of candidate proteins for further investigation. (c) 2006 Elsevier B.V. All rights reserved.

Physical activity and strength of the femoral neck during the adolescent growth spurt: A longitudinal analysis

Loading of the femoral neck (FN) is dominated by bending and compressive stresses. We hypothesize that adaptation of the FN to physical activity would be manifested in the cross-sectional area (CSA) and section modulus (Z) of bone, indices of axial and bending strength, respectively. We investigated the influence of physical activity on bone strength during adolescence using 7 years of longitudinal data from 109 boys and 121 girls from the Saskatchewan Paediatric Bone and Mineral Accrual Study (PBMAS). Physical activity data (PAC-Q physical activity inventory) and anthropometric measurements were taken every 6 months and DXA bone scans were measured annually (Hologic QDR2000, array mode). We applied hip structural analysis to derive strength and geometric indices of the femoral neck using DXA scans. To control for maturation, we determined a biological maturity age defined as years from age at peak height velocity (APHV). To account for the repeated measures within individual nature of longitudinal data, multilevel random effects regression analyses were used to analyze the data. When biological maturity age and body size (height and weight) were controlled, in both boys and girls, physical activity was a significant positive independent predictor of CSA and Z of the narrow region of the femoral neck (P < 0.05). There was no independent effect of physical activity on the subperiosteal width of the femoral neck. When leg length and leg lean mass were introduced into the random effects models to control for size and muscle mass of the leg (instead of height and weight), all significant effects of physical activity disappeared. Even among adolescents engaged in normal levels of physical activity, the statistically significant relationship between physical activity and indices of bone strength demonstrate that modifiable lifestyle factors like exercise play an important role in optimizing bone strength during the growing years. Physical activity differences were explained by the interdependence between activity and lean mass considerations. Physical activity is important for optimal development of bone strength. (c) 2005 Elsevier Inc. All rights reserved.

A Bayesian hierarchical model for categorical longitudinal data from a social survey of immigrants

The paper investigates a Bayesian hierarchical model for the analysis of categorical longitudinal data from a large social survey of immigrants to Australia. Data for each subject are observed on three separate occasions, or waves, of the survey. One of the features of the data set is that observations for some variables are missing for at least one wave. A model for the employment status of immigrants is developed by introducing, at the first stage of a hierarchical model, a multinomial model for the response and then subsequent terms are introduced to explain wave and subject effects. To estimate the model, we use the Gibbs sampler, which allows missing data for both the response and the explanatory variables to be imputed at each iteration of the algorithm, given some appropriate prior distributions. After accounting for significant covariate effects in the model, results show that the relative probability of remaining unemployed diminished with time following arrival in Australia.

Multilevel phenomena and the implications for method: An example of knowledge transfer in sports

Multilevel theories integrate individual-level processes with those occurring at the level of the firm and above to generate richer and more complete explanations of IB phenomena than the traditional specification of IB relationships as single-level and parsimonious allows. Case study methods permit the timely collection of multiple sources of data, in context, from multiple individuals and multiple organizational units. Further, because the definitions for each level emerge from case data rather than being imposed a priori, case analysis promotes an understanding of deeper structures and cross-level processes. This paper considers the example of sport as an internationalized service to illustrate how the case method might be used to illuminate the multilevel phenomena of knowledge.

Multilevel modelling for inference of genetic regulatory networks

Time-course experiments with microarrays are often used to study dynamic biological systems and genetic regulatory networks (GRNs) that model how genes influence each other in cell-level development of organisms. The inference for GRNs provides important insights into the fundamental biological processes such as growth and is useful in disease diagnosis and genomic drug design. Due to the experimental design, multilevel data hierarchies are often present in time-course gene expression data. Most existing methods, however, ignore the dependency of the expression measurements over time and the correlation among gene expression profiles. Such independence assumptions violate regulatory interactions and can result in overlooking certain important subject effects and lead to spurious inference for regulatory networks or mechanisms. In this paper, a multilevel mixed-effects model is adopted to incorporate data hierarchies in the analysis of time-course data, where temporal and subject effects are both assumed to be random. The method starts with the clustering of genes by fitting the mixture model within the multilevel random-effects model framework using the expectation-maximization (EM) algorithm. The network of regulatory interactions is then determined by searching for regulatory control elements (activators and inhibitors) shared by the clusters of co-expressed genes, based on a time-lagged correlation coefficients measurement. The method is applied to two real time-course datasets from the budding yeast (Saccharomyces cerevisiae) genome. It is shown that the proposed method provides clusters of cell-cycle regulated genes that are supported by existing gene function annotations, and hence enables inference on regulatory interactions for the genetic network.

The Hierarchical Structure of the Firm: A Geometric Perspective

This paper incorporates hierarchical structure into the neoclassical theory of the firm. Firms are hierarchical in two respects: the organization of workers in production and the wage structure. The firm’s hierarchy is represented as the sector of a circle, where the radius represents the hierarchy’s height, the width of the sector represents the breadth of the hierarchy at a given height, and the angle of the sector represents span of control for any given supervisor. A perfectly competitive firm then chooses height and width, as well as capital inputs, in order to maximize profit. We analyze the short run and long run impact of changes in scale economies, input substitutability and input and output prices on the firm’s hierarchical structure. We find that the firm unambiguously becomes more hierarchical as the specialization of its workers increases or as its output price increases relative to input prices. The effect of changes in scale economies is contingent on the output price. The model also brings forth an analysis of wage inequality within the firm, which is found to be independent of technological considerations, and only depends on the firm’s wage schedule.

Goal orientation, ability and task performance: A moderated analysis

Achievement goal orientation represents an individual's general approach to an achievement situation, and has important implications for how individuals react to novel, challenging tasks. However, theorists such as Yeo and Neal (2004) have suggested that the effects of goal orientation may emerge over time. Bell and Kozlowski (2002) have further argued that these effects may be moderated by individual ability. The current study tested the dynamic effects of a new 2x2 model of goal orientation (mastery/performance x approach/avoidance) on performance on a simulated air traffic control (ATC) task, as moderated by dynamic spatial ability. One hundred and one first-year participants completed a self-report goal orientation measure and computerbased dynamic spatial ability test and performed 30 trials of an ATC task. Hypotheses were tested using a two-level hierarchical linear model. Mastery-approach orientation was positively related to task performance, although no interaction with ability was observed. Performance-avoidance orientation was negatively related to task performance; this association was weaker at high levels of ability. Theoretical and practical implications will be discussed.