Higher incidence of childhood-onset type 1 diabetes mellitus in remote areas: a UK regional small-area analysis

Aims/hypothesis: We investigated the association between the incidence of type 1 diabetes mellitus and remoteness (a proxy measure for exposure to infections) using recently developed techniques for statistical analysis of small-area data.

Subjects, materials and methods: New cases in children aged 0 to 14 years in Northern Ireland were prospectively registered from 1989 to 2003. Ecological analysis was conducted using small geographical units (582 electoral wards) and area characteristics including remoteness, deprivation and child population density. Analysis was conducted using Poisson regression models and Bayesian
hierarchical models to allow for spatially correlated risks that were potentially caused by unmeasured explanatory variables.

Results: In Northern Ireland between 1989 and 2003, there were 1,433 new cases of type 1 diabetes, giving a directly standardised incidence rate of 24.7 per 100,000 personyears. Areas in the most remote fifth of all areas had a significantly (p=0.0006) higher incidence of type 1 diabetes mellitus (incidence rate ratio=1.27 [95% CI 1.07, 1.50]) than those in the most accessible fifth of all areas. There was also a higher incidence rate in areas that were less deprived (p<0.0001) and less densely populated (p=0.002). After adjustment for deprivation and additional adjustment for child population density the association between diabetes and remoteness remained significant (p=0.01 and p=0.03, respectively).

Conclusions/interpretation: In Northern Ireland, there is evidence that remote areas experience higher rates of type 1 diabetes mellitus. This could reflect a reduced or delayed exposure to infections, particularly early in life, in these areas.

The analysis of large-scale turbulence characteristics in the Indonesian seas derived from a regional model based on the Princeton Ocean Model

Turbulence characteristics in the Indonesian seas on the horizontal scale of order of 100 km were calculated with a regional model of the Indonesian seas circulation in the area based on the Princeton Ocean Model (POM). As is well known, the POM incorporates the Mellor–Yamada turbulence closure scheme. The calculated characteristics are: twice the turbulence kinetic energy per unit mass, <i>q</i>²; the turbulence master scale, &ell;; mixing coefficients of momentum, <i>K</i>_M; and temperature and salinity, <i>K</i>_H; etc. The analyzed turbulence has been generated essentially by the shear of large-scale ocean currents and by the large-scale wind turbulence. We focused on the analysis of turbulence around important topographic features, such as the Lifamatola Sill, the North Sangihe Ridge, the Dewakang Sill, and the North and South Halmahera Sea Sills. In general, the structure of turbulence characteristics in these regions turned out to be similar. For this reason, we have carried out a detailed analysis of the Lifamatola Sill region because dynamically this region is very important and some estimates of mixing coefficients in this area are available. <br><br> Briefly, the main results are as follows. The distribution of <i>q</i>² is quite adequately reproduced by the model. To the north of the Lifamatola Sill (in the Maluku Sea) and to the south of the Sill (in the Seram Sea), large values of <i>q</i>² occur in the deep layer extending several hundred meters above the bottom. The observed increase of <i>q</i>² near the very bottom is probably due to the increase of velocity shear and the corresponding shear production of <i>q</i>² very close to the bottom. The turbulence master scale, &ell;, was found to be constant in the main depth of the ocean, while &ell; rapidly decreases close to the bottom, as one would expect. However, in deep profiles away from the sill, the effect of topography results in the &ell; structure being unreasonably complicated as one moves towards the bottom. Values of 15 to 20 × 10^&minus;4 m² s^-1 were obtained for <i>K</i>_M and <i>K</i>_H in deep water in the vicinity of the Lifamatola Sill. These estimates agree well with basin-scale averaged values of 13.3 × 10^&minus;4 m² s^-1 found diagnostically for <i>K</i>_H in the deep Banda and Seram Seas (Gordon et al., 2003) and a value of 9.0 × 10^&minus;4 m² s^-1 found diagnostically for <i>K</i>_H for the deep Banda Sea system (van Aken et al., 1988). The somewhat higher simulated values can be explained by the presence of steep topography around the sill.

The use of Ecological and Carbon Footprint Analysis in regional policy making: application and insights using the REAP model

This paper builds on and extends previous research to contribute to ongoing discussion on the use of resource and carbon accounting tools in regional policy making. The Northern Visions project has produced the first evidence-based footpath setting out the actions that need to be taken to achieve the step changes in the Ecological and Carbon Footprint of Northern Ireland. A range of policies and strategies were evaluated using the Resources and Energy Analysis Programme. The analysis provided the first regional evidence base that current sustainable development policy commitments would not lead to the necessary reductions in either the Ecological Footprint or carbon dioxide emissions. Building on previous applications of Ecological Footprint analysis in regional policy making, the research has demonstrated that there is a valuable role for Ecological and Carbon Footprint Analysis in policy appraisal. The use of Ecological and Carbon Footprint Analysis in regional policy making has been evaluated and recommendations made on ongoing methodological development. The authors hope that the research can provide insights for the ongoing use Ecological and Carbon Footprint Analysis in regional policy making and help set out the priorities for research to support this important policy area

The use of material flow analysis and the ecological footprint in regional policy-making: application and insights from Northern Ireland.

This paper aims to contribute to the ongoing debate on the use of resource accounting tools in regional policy making. The Northern Limits project applied Material Flow Analysis and Ecological Footprinting to regional policy making in Northern Ireland over a number of years. The early phase of the research informed the regions first sustainable development strategy which was published in 2006 with key targets relating to the Ecological Footprint and improving the resource efficiency of the economy. Phase II identified the next steps required to address data availability and quality and the use of MFA and EF in providing a measurement and monitoring framework for the strategy and in the development of the strategy implementation plan. The use of MFA and Ecological Footprinting in sustainable regional policy making and the monitoring of its implementation is an ongoing process which has raised a number of research issues which can inform the ongoing application and development of these and other resource accounting tools to within Northern Ireland, provide insights for their use in other regions and help set out the priorities for research to support this important policy area.

Multivariate analysis of regional-scale geochemical data for environmental monitoring

A compositional multivariate approach is used to analyse regional scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey Northern Ireland (GSNI). The multi-element total concentration data presented comprise XRF analyses of 6862 rural soil samples collected at 20cm depths on a non-aligned grid at one site per 2 km2. Censored data were imputed using published detection limits. Using these imputed values for 46 elements (including LOI), each soil sample site was assigned to the regional geology map provided by GSNI initially using the dominant lithology for the map polygon. Northern Ireland includes a diversity of geology representing a stratigraphic record from the Mesoproterozoic, up to and including the Palaeogene. However, the advance of ice sheets and their meltwaters over the last 100,000 years has left at least 80% of the bedrock covered by superficial deposits, including glacial till and post-glacial alluvium and peat. The question is to what extent the soil geochemistry reflects the underlying geology or superficial deposits. To address this, the geochemical data were transformed using centered log ratios (clr) to observe the requirements of compositional data analysis and avoid closure issues. Following this, compositional multivariate techniques including compositional Principal Component Analysis (PCA) and minimum/maximum autocorrelation factor (MAF) analysis method were used to determine the influence of underlying geology on the soil geochemistry signature. PCA showed that 72% of the variation was determined by the first four principal components (PC’s) implying “significant” structure in the data. Analysis of variance showed that only 10 PC’s were necessary to classify the soil geochemical data. To consider an improvement over PCA that uses the spatial relationships of the data, a classification based on MAF analysis was undertaken using the first 6 dominant factors. Understanding the relationship between soil geochemistry and superficial deposits is important for environmental monitoring of fragile ecosystems such as peat. To explore whether peat cover could be predicted from the classification, the lithology designation was adapted to include the presence of peat, based on GSNI superficial deposit polygons and linear discriminant analysis (LDA) undertaken. Prediction accuracy for LDA classification improved from 60.98% based on PCA using 10 principal components to 64.73% using MAF based on the 6 most dominant factors. The misclassification of peat may reflect degradation of peat covered areas since the creation of superficial deposit classification. Further work will examine the influence of underlying lithologies on elemental concentrations in peat composition and the effect of this in classification analysis.

A Longitudinal and Contextual Analysis of Media Representation of Business Ethics

Purpose – The purpose of this paper is to present an analysis of media representation of business ethics within 62 international newspapers to explore the longitudinal and contextual evolution of business ethics and associated terminology. Levels of coverage and contextual analysis of the content of the articles are used as surrogate measures of the penetration of business ethics concepts into society. Design/methodology/approach – This paper uses a text mining application based on two samples of data: analysis of 62 national newspapers in 21 countries from 1990 to 2008; analysis of the content of two samples of articles containing the term business ethics (comprised of 100 newspaper articles spread over an 18-year period from a sample of US and UK newspapers). Findings – The paper demonstrates increased coverage of sustainability topics within the media over the last 18 years associated with events such as the Rio Summit. Whilst some peaks are associated with business ethics scandals, the overall coverage remains steady. There is little apparent use in the media of concepts such as corporate citizenship. The academic community and company ethical codes appear to adopt a wider definition of business ethics more akin to that associated with sustainability, in comparison with the focus taken by the media, especially in the USA. Coverage demonstrates clear regional bias and contextual analysis of the articles in the UK and USA also shows interesting parallels and divergences in the media representation of business ethics. Originality/value – A promising avenue to explore how the evolution of sustainability issues including business ethics can be tracked within a societal context.

Intelligent Assembly Time Analysis Using a Digital Knowledge-Based Approach

The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for intelligent time analysis of aircraft assembly processes within a digital manufacturing framework. A knowledge system is developed so that the design knowledge can be intelligently retrieved for implementing assembly time analysis automatically. A time estimation method based on MOST, is reviewed and employed. Knowledge capture, transfer and storage within the digital manufacturing environment are extensively discussed. Configured plantypes, GUIs and functional modules are designed and developed for the automated time analysis. An exemplar study using an aircraft panel assembly from a regional jet is also presented. Although the method currently focuses on aircraft assembly, it can also be well utilized in other industry sectors, such as transportation, automobile and shipbuilding. The main contribution of the work is to present a methodology that facilitates the integration of time analysis with design and manufacturing using a digital manufacturing platform solution.