48,408 research outputs found
Road-traffic pollution and asthma – using modelled exposure assessment for routine public health surveillance
Asthma is a common disease and appears to be increasing in prevalence. There is evidence linking air pollution, including that from road-traffic, with asthma. Road traffic is also on the increase. Routine surveillance of the impact of road-traffic pollution on asthma, and other diseases, would be useful in informing local and national government policy in terms of managing the environmental health risk.
Several methods for exposure assessment have been used in studies examining the association between asthma and road traffic pollution. These include comparing asthma prevalence in areas designated as high and low pollution areas, using distance from main roads as a proxy for exposure to road traffic pollution, using traffic counts to estimate exposure, using vehicular miles travelled and using modelling techniques. Although there are limitations to all these methods, the modelling approach has the advantage of incorporating several variables and may be used for prospective health impact assessment.
The modelling approach is already in routine use in the United Kingdom in support of the government's strategy for air quality management. Combining information from such models with routinely collected health data would form the basis of a routine public health surveillance system. Such a system would facilitate prospective health impact assessment, enabling policy decisions concerned with road-traffic to be made with knowledge of the potential implications. It would also allow systematic monitoring of the health impacts when the policy decisions and plans have been implemented
Travel choices in Scotland - the effect of local accessibility on non-work travel
Accessibility features prominently in the developing transport policies of both the United Kingdom Government and the devolved Scottish Executive which aim to promote social inclusion in particular and the integration of transport and land use planning more generally. It follows that a detailed understanding of the relationship between accessibility, personal mobility and travel behaviour is critical to the successful implementation of these policies. This paper presents the results of a disaggregate, multi-variate analysis of the Scottish Household Survey (SHS) dataset and attempts to unravel the complex relationship between socio-economical circumstance, geographical access to local services and public transport and revealed non-work travel choices. The socio-economical and geographical diversity of Scotland offers an excellent opportunity to undertake an analysis of this nature. The SHS is a continuous, cross-sectional survey funded by the Scottish Executive and undertaken by face-to-face interview based on a sample of the general population in private residences in Scotland. It seeks to provide information on the composition, characteristics and behaviour of Scottish households. The survey collects information in two parts - firstly the highest income householder provides household level data including household composition and income, key attributes of household members, transport resources available to the household including access to public transport; secondly a randomly selected adult from the household provides information on inter alia personal travel (including the completion of a one-day travel diary on the previous day) and personal views on transport, the neighbourhood and local services. The dataset analysed in this paper was collected between 1999 and 2003 and contains over 75,000 surveyed households and over 49,000 completed travel diaries. Two other variables were matched with the residential location of SHS respondents and added to the dataset; namely, an index representing proximity to local services at electoral ward level derived in the Scottish Indices of Deprivation 2003 study and a locational classification for each respondent which captures settlement size and wider regional accessibility. The primary focus of the analysis presented in this paper is an examination of the extent to which the quality of local access to services affects distance travelled for non-work purposes. Within this analysis individual and household socio-economical circumstance, available transport resources (both car ownership and local access to public transport) and the wider regional geographical context are also taken into account. It is hypothesised that good local access is negatively associated with distance travelled and that there also exists the possibility of significant interaction between local access and socio-economical circumstance and available transport resources. Regression models are developed for non-work travel which test the statistical significance of these explanatory variables. The results of the analysis reported here will add to the existing evidence base on the relationship between accessibility and travel choice. Its conclusions are expected to inform the development of strategies to enhance social inclusion and reduce overall travel which are tailored to socio-economical and geographical circumstance
Improving the viability of mental models held by novice programmers
Recent research has found that many novice programmers often hold non-viable mental models of basic programming concepts such as assignment and object reference. This paper proposes a constructivist-based teaching model, integrating a cognitive conflict strategy with program visualization, with the aim of improving novice programmers’ mental models. The results of a preliminary empirical study suggest that, for the relatively straightforward concept of assignment, tight integration of program visualization with a cognitive conflict event that highlights a student’s inappropriate understanding can help improve students’ non-viable mental models. 14 out of 18 participants who held non-viable mental models of the assignment process successfully changed their model to be viable as a result of the proposed teaching model
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