Childhood obesity: should primary school children be routinely screened? A systematic review and discussion of the evidence

Background: Population monitoring has been introduced in UK primary schools in an effort to track the growing obesity epidemic. It has been argued that parents should be informed of their child's results, but is there evidence that moving from monitoring to screening would be effective? We describe what is known about the effectiveness of monitoring and screening for overweight and obesity in primary school children and highlight areas where evidence is lacking and research should be prioritised. Design: Systematic review with discussion of evidence gaps and future research. Data sources: Published and unpublished studies ( any language) from electronic databases ( inception to July 2005), clinical experts, Primary Care Trusts and Strategic Health Authorities, and reference lists of retrieved studies. Review methods: We included any study that evaluated measures of overweight and obesity as part of a population-level assessment and excluded studies whose primary outcome measure was prevalence. Results: There were no trials assessing the effectiveness of monitoring or screening for overweight and obesity. Studies focussed on the diagnostic accuracy of measurements. Information on the attitudes of children, parents and health professionals to monitoring was extremely sparse. Conclusions: Our review found a lack of data on the potential impact of population monitoring or screening for obesity and more research is indicated. Identification of effective weight reduction strategies for children and clarification of the role of preventative measures are priorities. It is difficult to see how screening to identify individual children can be justified without effective interventions.

Predicting violence in schizophrenia: a prospective study

Background: People with schizophrenia are more violent than the general population, but this increased risk is attributable to the actions of a small subgroup. Identifying those at risk has become an essential part of clinical practice. Aims: To estimate the risk factors for assault in patients with schizophrenia. Methods: Two hundred seventy-one patients with schizophrenia were interviewed using an extensive battery of instruments. Assault was measured from multiple data sources over the next 2 years and criminal records were obtained. Multiple sociodemographic and clinical variables measured at baseline were examined as possible predictors of assault during follow-up. Results: Sixty-nine (25%) patients committed assault during the 2-year followup. The model that best predicted assault included a history of recent assault (OR 2.33, 95% CI 1.17-4.61), a previous violent conviction (OR 2.02, 95% CI 1.04-3.87), having received special education (OR 2.76, 95% CI 1.22-6.26) and alcohol abuse (OR 3.55, 95% CI 1.24-10.2). Conclusions: Previously established risk factors including a history of violence and alcohol abuse are replicated in this study. Although low premorbid IQ did not predict violence, a need for special education did. (C) 2003 Published by Elsevier B.V.

Fast regridding of large, complex geospatial datasets

In the earth sciences, data are commonly cast on complex grids in order to model irregular domains such as coastlines, or to evenly distribute grid points over the globe. It is common for a scientist to wish to re-cast such data onto a grid that is more amenable to manipulation, visualization, or comparison with other data sources. The complexity of the grids presents a significant technical difficulty to the regridding process. In particular, the regridding of complex grids may suffer from severe performance issues, in the worst case scaling with the product of the sizes of the source and destination grids. We present a mechanism for the fast regridding of such datasets, based upon the construction of a spatial index that allows fast searching of the source grid. We discover that the most efficient spatial index under test (in terms of memory usage and query time) is a simple look-up table. A kd-tree implementation was found to be faster to build and to give similar query performance at the expense of a larger memory footprint. Using our approach, we demonstrate that regridding of complex data may proceed at speeds sufficient to permit regridding on-the-fly in an interactive visualization application, or in a Web Map Service implementation. For large datasets with complex grids the new mechanism is shown to significantly outperform algorithms used in many scientific visualization packages.

Integrating nitrogen fluxes at the European scale

Executive summary Nature of the problem • Environmental problems related to nitrogen concern all economic sectors and impact all media: atmosphere, pedosphere, hydrosphere and anthroposphere. • Therefore, the integration of fluxes allows an overall coverage of problems related to reactive nitrogen (Nr) in the environment, which is not accessible from sectoral approaches or by focusing on specific media. Approaches • This chapter presents a set of high resolution maps showing key elements of the N flux budget across Europe, including N2 and Nr fluxes. • Comparative nitrogen budgets are also presented for a range of European countries, highlighting the most efficient strategies for mitigating Nr problems at a national scale. A new European Nitrogen Budget (EU-27) is presented on the basis of state-of-the-art Europe-wide models and databases focusing on different segments of Europe’s society. Key findings • From c. 18 Tg Nr yr −1 input to agriculture in the EU-27, only about 7 Tg Nr yr− 1 find their way to the consumer or are further processed by industry. • Some 3.7 Tg Nr yr−1 is released by the burning of fossil fuels in the EU-27, whereby the contribution of the industry and energy sectors is equal to that of the transport sector. More than 8 Tg Nr yr−1 are disposed of to the hydrosphere, while the EU-27 is a net exporter of reactive nitrogen through atmospheric transport of c. 2.3 Tg Nr yr−1. • The largest single sink for Nr appears to be denitrifi cation to N2 in European coastal shelf regions (potentially as large as the input of mineral fertilizer, about 11 Tg N yr–1 for the EU-27); however, this sink is also the most uncertain, because of the uncertainty of Nr import from the open ocean. Major uncertainties • National nitrogen budgets are diffi cult to compile using a large range of data sources and are currently available only for a limited number of countries. • Modelling approaches have been used to fill in the data gaps in some of these budgets, but it became obvious during this study that further research is needed in order to collect necessary data and make national nitrogen budgets inter-comparable across Europe. • In some countries, due to inconsistent or contradictory information coming from different data sources, closure of the nitrogen budget was not possible. Recommendations • The large variety of problems associated with the excess of Nr in the European environment,including adverse impacts, requires an integrated nitrogen management approach that would allow for creation and closure of N budgets within European environments. • Development of nitrogen budgets nationwide, their assessment and management could become an effective tool to prioritize measures and prevent unwanted side effects.

Putting the S-word back into Sustainability: Can we be more social?

In an era dominated by climate change debate and environmentalism there is a real danger that the important ‘social’ pillar of sustainability drops out of our vocabulary. This can happen at a variety of scales from business level through to building and neighbourhood level regeneration and development. Social sustainability should be at the heart of all housing and mixed-use development but for a variety of reasons tends to be frequently underplayed. The recent English city riots have brought this point back sharply into focus. The relationships between people, places and the local economy all matter and this is as true today as it was in the late 19th century when Patrick Geddes, the great pioneering town planner and ecologist, wrote of ‘place-work-folk’. This paper, commissioned from Tim Dixon, explains what is meant by social sustainability (and how it is linked to concepts such as social capital and social cohesion); why the debate matters during a period when ‘localism’ is dominating political debate; and what is inhibiting its growth and its measurement. The paper reviews best practice in post-occupancy social sustainability metric systems, based on recent research undertaken by the author on Dockside Green in Vancouver, and identifi es some of the key operational issues in mainstreaming the concept within major mixed-use projects. The paper concludes by offering a framework for the key challenges faced in setting strategic corporate goals and objectives; prioritising and selecting the most appropriate investments; and measuring social sustainability performance by identifying the required data sources

Entity-based semantic search on conversational transcripts semantic

This paper describes the implementation of a semantic web search engine on conversation styled transcripts. Our choice of data is Hansard, a publicly available conversation style transcript of parliamentary debates. The current search engine implementation on Hansard is limited to running search queries based on keywords or phrases hence lacks the ability to make semantic inferences from user queries. By making use of knowledge such as the relationship between members of parliament, constituencies, terms of office, as well as topics of debates the search results can be improved in terms of both relevance and coverage. Our contribution is not algorithmic instead we describe how we exploit a collection of external data sources, ontologies, semantic web vocabularies and named entity extraction in the analysis of underlying semantics of user queries as well as the semantic enrichment of the search index thereby improving the quality of results.

The prevalence and nature of prescribing and monitoring errors in English general practice – a retrospective case note review

Objective To determine the prevalence and nature of prescribing and monitoring errors in general practices in England. Design Retrospective case note review of unique medication items prescribed over a 12 month period to a 2% random sample of patients. Mixed effects logistic regression was used to analyse the data. Setting Fifteen general practices across three primary care trusts in England. Data sources Examination of 6048 unique prescription items prescribed over the previous 12 months for 1777 patients. Main outcome measures Prevalence of prescribing and monitoring errors, and severity of errors, using validated definitions. Results Prescribing and/or monitoring errors were detected in 4.9% (296/6048) of all prescription items (95% confidence interval 4.4 - 5.5%). The vast majority of errors were of mild to moderate severity, with 0.2% (11/6048) of items having a severe error. After adjusting for covariates, patient-related factors associated with an increased risk of prescribing and/or monitoring errors were: age less than 15 (Odds Ratio (OR) 1.87, 1.19 to 2.94, p=0.006) or greater than 64 years (OR 1.68, 1.04 to 2.73, p=0.035), and higher numbers of unique medication items prescribed (OR 1.16, 1.12 to 1.19, p<0.001). Conclusion Prescribing and monitoring errors are common in English general practice, although severe errors are unusual. Many factors increase the risk of error. Having identified the most common and important errors, and the factors associated with these, strategies to prevent future errors should be developed based on the study findings.

Reading the world through words: cultural themes in heritage Chinese language textbooks

This paper explores the social and cultural knowledge embedded in the textbooks for language and literacy education in a Chinese heritage language school, the Zhonguo School, in Montreal, Quebec, Canada. It examines how Chinese language arts textbooks introduce the child reader to cultural knowledge considered legitimate and valued in China as well as in Chinese diasporan communities. Furthermore, it looks at the construction of cultural knowledge in Chinese language textbooks in relation to the mainstream ideology to which immigrant children are exposed in and out of mainstream school classrooms. It looks at how the power relationship between legitimate cultural knowledge in majority and minority contexts is established and to what extent it affects language minority students' literacy practices in mainstream school and heritage language school contexts. Data sources are the Chinese textbooks used from kindergarten to Grade 5 in a Chinese heritage language school.

Updated empirical model of genetically-modified maize grain production practices to achieve European Union labeling thresholds

An updated empirical approach is proposed for specifying coexistence requirements for genetically modified (GM) maize (Zea mays L.) production to ensure compliance with the 0.9% labeling threshold for food and feed in the European Union. The model improves on a previously published (Gustafson et al., 2006) empirical model by adding recent data sources to supplement the original database and including the following additional cases: (i) more than one GM maize source field adjacent to the conventional or organic field, (ii) the possibility of so-called “stacked” varieties with more than one GM trait, and (iii) lower pollen shed in the non-GM receptor field. These additional factors lead to the possibility for somewhat wider combinations of isolation distance and border rows than required in the original version of the empirical model. For instance, in the very conservative case of a 1-ha square non-GM maize field surrounded on all four sides by homozygous GM maize with 12 m isolation (the effective isolation distance for a single GM field), non-GM border rows of 12 m are required to be 95% confident of gene flow less than 0.9% in the non-GM field (with adventitious presence of 0.3%). Stacked traits of higher GM mass fraction and receptor fields of lower pollen shed would require a greater number of border rows to comply with the 0.9% threshold, and an updated extension to the model is provided to quantify these effects.

Ubiquitous grid resource monitoring

In any wide-area distributed system there is a need to communicate and interact with a range of networked devices and services ranging from computer-based ones (CPU, memory and disk), to network components (hubs, routers, gateways) and specialised data sources (embedded devices, sensors, data-feeds). In order for the ensemble of underlying technologies to provide an environment suitable for virtual organisations to flourish, the resources that comprise the fabric of the Grid must be monitored in a seamless manner that abstracts away from the underlying complexity. Furthermore, as various competing Grid middleware offerings are released and evolve, an independent overarching monitoring service should act as a corner stone that ties these systems together. GridRM is a standards-based approach that is independent of any given middleware and that can utilise legacy and emerging resource-monitoring technologies. The main objective of the project is to produce a standardised and extensible architecture that provides seamless mechanisms to interact with native monitoring agents across heterogeneous resources.

GridRM: an extensible resource monitoring system

GridRM is an open and extensible resource monitoring system, based on the Global Grid Forum's Grid Monitoring Architecture (GMA). GridRM is not intended to interact with applications; rather it is designed to monitor the resources that an application may use. This paper focuses on the dynamic driver infrastructure used by GridRM to interact with heterogeneous data sources, such as SNMP or Ganglia agents, and how it provides a homogeneous view of the underlying heterogeneous data. This paper discusses the local infrastructure and details work implementing and deploying a number of drivers.

Collaboration model for SSMEnetUK: a service science perspective

This paper aims to design a collaboration model for a Knowledge Community - SSMEnetUK. The research identifies SSMEnetUK as a socio-technical system and uses the core concepts of Service Science to explore the subject domain. The paper is positioned within the concept of Knowledge Management (KM) and utilising Web 2.0 tools for collaboration. A qualitative case study method was adopted and multiple data sources were used. In achieving that, the degree of co-relation between knowledge management activities and Web 2.0 tools for collaboration in the scenario are pitted against the concept of value propositions offered by both customer/user and service provider. The proposed model provides a better understanding of how Knowledge Management and Web 2.0 tools can enable effective collaboration within SSMEnetUK. This research is relevant to the wider service design and innovation community because it provides a basis for building a service-centric collaboration platform for the benefit of both customer/user and service provider.

The neuropsychology of male adults with High-Functioning Autism or Asperger Syndrome

Autism Spectrum Disorder (ASD) is diagnosed on the basis of behavioral symptoms, but cognitive abilities may also be useful in characterizing individuals with ASD. One hundred seventy-eight high-functioning male adults, half with ASD and half without, completed tasks assessing IQ, a broad range of cognitive skills, and autistic and comorbid symptomatology. The aims of the study were, first, to determine whether significant differences existed between cases and controls on cognitive tasks, and whether cognitive profiles, derived using a multivariate classification method with data from multiple cognitive tasks, could distinguish between the two groups. Second, to establish whether cognitive skill level was correlated with degree of autistic symptom severity, and third, whether cognitive skill level was correlated with degree of comorbid psychopathology. Fourth, cognitive characteristics of individuals with Asperger Syndrome (AS) and high-functioning autism (HFA) were compared. After controlling for IQ, ASD and control groups scored significantly differently on tasks of social cognition, motor performance, and executive function (P's < 0.05). To investigate cognitive profiles, 12 variables were entered into a support vector machine (SVM), which achieved good classification accuracy (81%) at a level significantly better than chance (P < 0.0001). After correcting for multiple correlations, there were no significant associations between cognitive performance and severity of either autistic or comorbid symptomatology. There were no significant differences between AS and HFA groups on the cognitive tasks. Cognitive classification models could be a useful aid to the diagnostic process when used in conjunction with other data sources-including clinical history.

Network optimization for enhanced resilience of urban heat island measurements

The urban heat island is a well-known phenomenon that impacts a wide variety of city operations. With greater availability of cheap meteorological sensors, it is possible to measure the spatial patterns of urban atmospheric characteristics with greater resolution. To develop robust and resilient networks, recognizing sensors may malfunction, it is important to know when measurement points are providing additional information and also the minimum number of sensors needed to provide spatial information for particular applications. Here we consider the example of temperature data, and the urban heat island, through analysis of a network of sensors in the Tokyo metropolitan area (Extended METROS). The effect of reducing observation points from an existing meteorological measurement network is considered, using random sampling and sampling with clustering. The results indicated the sampling with hierarchical clustering can yield similar temperature patterns with up to a 30% reduction in measurement sites in Tokyo. The methods presented have broader utility in evaluating the robustness and resilience of existing urban temperature networks and in how networks can be enhanced by new mobile and open data sources.

A variational approach to retrieve rain rate by combining information from rain gauges, radars, and microwave links

Accurate and reliable rain rate estimates are important for various hydrometeorological applications. Consequently, rain sensors of different types have been deployed in many regions. In this work, measurements from different instruments, namely, rain gauge, weather radar, and microwave link, are combined for the first time to estimate with greater accuracy the spatial distribution and intensity of rainfall. The objective is to retrieve the rain rate that is consistent with all these measurements while incorporating the uncertainty associated with the different sources of information. Assuming the problem is not strongly nonlinear, a variational approach is implemented and the Gauss–Newton method is used to minimize the cost function containing proper error estimates from all sensors. Furthermore, the method can be flexibly adapted to additional data sources. The proposed approach is tested using data from 14 rain gauges and 14 operational microwave links located in the Zürich area (Switzerland) to correct the prior rain rate provided by the operational radar rain product from the Swiss meteorological service (MeteoSwiss). A cross-validation approach demonstrates the improvement of rain rate estimates when assimilating rain gauge and microwave link information.