Health Statistics 2005

The four key principles guiding the development of the Health Strategy (2001): Quality and Fairness: A Health System for You are equity, people-centredness, quality and accountability. Statistical information is fundamental to the delivery of each of these principles. This compendium of health statistics brings together data from a wide variety of sources on demography, health status and the delivery of health services. It provides a broad overview of health in Ireland as well as serving as a resource and reference for those interested in particular aspects of health and thehealth services. Read the Statistics report (PDF, 4.1mb)

Multiple imputations applied to the DREAM3 phosphoproteomics challenge: a winning strategy.

DREAM is an initiative that allows researchers to assess how well their methods or approaches can describe and predict networks of interacting molecules [1]. Each year, recently acquired datasets are released to predictors ahead of publication. Researchers typically have about three months to predict the masked data or network of interactions, using any predictive method. Predictions are assessed prior to an annual conference where the best predictions are unveiled and discussed. Here we present the strategy we used to make a winning prediction for the DREAM3 phosphoproteomics challenge. We used Amelia II, a multiple imputation software method developed by Gary King, James Honaker and Matthew Blackwell[2] in the context of social sciences to predict the 476 out of 4624 measurements that had been masked for the challenge. To chose the best possible multiple imputation parameters to apply for the challenge, we evaluated how transforming the data and varying the imputation parameters affected the ability to predict additionally masked data. We discuss the accuracy of our findings and show that multiple imputations applied to this dataset is a powerful method to accurately estimate the missing data. We postulate that multiple imputations methods might become an integral part of experimental design as a mean to achieve cost savings in experimental design or to increase the quantity of samples that could be handled for a given cost.

An empirical hierarchical Bayesian unification of occupational exposure assessment methods.

In occupational exposure assessment of airborne contaminants, exposure levels can either be estimated through repeated measurements of the pollutant concentration in air, expert judgment or through exposure models that use information on the conditions of exposure as input. In this report, we propose an empirical hierarchical Bayesian model to unify these approaches. Prior to any measurement, the hygienist conducts an assessment to generate prior distributions of exposure determinants. Monte-Carlo samples from these distributions feed two level-2 models: a physical, two-compartment model, and a non-parametric, neural network model trained with existing exposure data. The outputs of these two models are weighted according to the expert's assessment of their relevance to yield predictive distributions of the long-term geometric mean and geometric standard deviation of the worker's exposure profile (level-1 model). Bayesian inferences are then drawn iteratively from subsequent measurements of worker exposure. Any traditional decision strategy based on a comparison with occupational exposure limits (e.g. mean exposure, exceedance strategies) can then be applied. Data on 82 workers exposed to 18 contaminants in 14 companies were used to validate the model with cross-validation techniques. A user-friendly program running the model is available upon request.

Geometry and physics of catenanes applied to the study of DNA replication.

The concept of ideal geometric configurations was recently applied to the classification and characterization of various knots. Different knots in their ideal form (i.e., the one requiring the shortest length of a constant-diameter tube to form a given knot) were shown to have an overall compactness proportional to the time-averaged compactness of thermally agitated knotted polymers forming corresponding knots. This was useful for predicting the relative speed of electrophoretic migration of different DNA knots. Here we characterize the ideal geometric configurations of catenanes (called links by mathematicians), i.e., closed curves in space that are topologically linked to each other. We demonstrate that the ideal configurations of different catenanes show interrelations very similar to those observed in the ideal configurations of knots. By analyzing literature data on electrophoretic separations of the torus-type of DNA catenanes with increasing complexity, we observed that their electrophoretic migration is roughly proportional to the overall compactness of ideal representations of the corresponding catenanes. This correlation does not apply, however, to electrophoretic migration of certain replication intermediates, believed up to now to represent the simplest torus-type catenanes. We propose, therefore, that freshly replicated circular DNA molecules, in addition to forming regular catenanes, may also form hemicatenanes.

Spatial analysis of the distribution of leprosy in the State of Ceará, Northeast Brazil

The aim of this study was to describe spatial patterns of the distribution of leprosy and to investigate spatial clustering of incidence rates in the state of Ceará, Northeast Brazil. The average incidence rate of leprosy for the period of 1991 to 1999 was calculated for each municipality of Ceará. Maps were used to describe the spatial distribution of the disease, and spatial statistics were applied to explore large- and small-scale variations of incidence rates. Three regions were identified in which the incidence of leprosy was particularly high. A spatial gradient in the incidence rates was identified, with a tendency of high rates to be concentrated on the North-South axis in the middle region of the state. Moran's I statistic indicated that a significant spatial autocorrelation also existed. The spatial distribution of leprosy in Ceará is heterogeneous. The reasons for spatial clustering of disease rates are not known, but might be related to an heterogeneous distribution of other factors such as crowding, social inequality, and environmental characteristics which by themselves determine the transmission of Mycobacterium leprae.

Clustering and hot spot detection in socio-economic spatio-temporal data

Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward's classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.

Putting children first: The role of health psychology in applied child/youth research

Overview Part One • Background/context  – defining and thinking about health • The role of the health psychologist • Promoting the psychosocial well being of children and young people • Early intervention and prevention in Ireland • Intervening in the lives of children with emotional and behavioural difficulties   Part Two • Case-study  – The Incredible Years Ireland Study: theory, practice and research   Part Three • Some key considerations in intervention science for research, policy and practice with children and young people   Sinead McGilloway: Putting children first. The role of health psychology

Introduction to Basic Health Care Statistics

A video summary by Catherine Comiskey

A morphological grading of spinal stenosis: a radiological study on LSS and LBP patients : P173

Introduction: Clinical symptoms and degree of spinal stenosis based on cross sectional dural sac area correlate only weakly in lumbar spinal stenosis (LSS) patients. We conceived a four grade classification system (A, B, C & D) based on the morphology of the dural sac and its contents as seen on T2 axial MRI images. The categories take into account the rootlet/CSF ratio. We applied this grading to three patient groups: LSS scheduled for surgery; LSS following conservative treatment and patients with low back pain (LBP) without leg pain. Materials/Methods: A total of 346 T2 axial MRI images taken from LSS and LBP patients were included in this retroperspective study. 37 patients had decompressive surgery (132 MRI images), 31 conservative treatment (116 MRI images) and 27 patients had unspecific LBP (98 MRI images). Dural sac cross-sectional surface area and morphological grading of the canal were measured digitally both at disc and pedicle level. Intra- and inter-observer reliability were assessed (weighted Cohen's kappa statistics) from 50 MRI images taken from the surgery group. Results: At the most severe disc level, grade A (mild stenosis) was found in 3% of MRI images of the surgical group as opposed to 51% in the conservatively treated group and 85% in the LBP group. Grade B occurred in 8% of the surgical, 20% of the conservative and was negligible in LBP group (below 1%). Grade C and D (severe stenosis) was found in 89% of the surgical group, as opposed to 30% in conservative group and 11% in LBP group. The grades of all groups were comparable at the pedicle levels, exhibiting in 94% a grade A with a maximum at the A1 grade. Pedicle and disc level cross-sectional area were smallest in the surgery group and smaller in the conservative group as compared to the LBP group at the levels L2, L3 and L4. According to cross-sectional area measurements patients from the surgery group seems to have smaller vertebral canal although this was not related to smaller stature. Validation of grading: Average intra-and inter observer kappas were 0.76 and 0.69 respectively, for physicians working in the study originating institution. Combining all observers the kappa values were 0.57 +/- 0.19. and 0.44 +/- 0.19 respectively. Dural sac cross-sectional area measurements showed no statistically significant differences between observers. Conclusion: Since no specific measurement tools are needed the grading suits everyday clinical practice and favours communication of degree of stenosis between practising physicians. In our institution Grade A stenosis was less likely to require surgical treatment. This grading can therefore be an aid in surgical patient selection in teaching units.

New imaging techniques applied to Paleogene radiolaria

A simple and time efficient technique to illustrate specimens is described and demonstrated with Paleogene radiolarians. This method produces Scanning Electron Microscope (SEM) and composite focal depth Transmitted Light Microscope (TLM) images for single radiolarian specimens. We propose the use of this technique to clarify radiolarian taxonomy. This technique has distinct advantages over previously published time consuming techniques that can also require toxic materials.