Open-Source web-based geographical information system for health exposure assessment

This paper presents the design and development of an open source web-based Geographical Information System allowing users to visualise, customise and interact with spatial data within their web browser. The developed application shows that by using solely Open Source software it was possible to develop a customisable web based GIS application that provides functions necessary to convey health and environmental data to experts and non-experts alike without the requirement of proprietary software

On the move:Exploring the impact of residential mobility on cannabis use

AbstractA large literature exists suggesting that residential mobility leads to increased participation in risky health behaviours such as cannabis use amongst youth. However, much of this work fails to account for the impact that underlying differences between mobile and non-mobile youth have on this relationship. In this study we utilise multilevel models with longitudinal data to simultaneously estimate between-child and within-child effects in the relationship between residential mobility and cannabis use, allowing us to determine the extent to which cannabis use in adolescence is driven by residential mobility and unobserved confounding. Data come from a UK cohort, The Avon Longitudinal Study of Parents and Children. Consistent with previous research we find a positive association between cumulative residential mobility and cannabis use when using multilevel extensions of conventional logistic regression models (log odds: 0.94, standard error: 0.42), indicating that children who move houses are more likely to use cannabis than those who remain residentially stable. However, decomposing this relationship into within- and between-child components reveals that the conventional model is underspecified and misleading; we find that differences in cannabis use between mobile and non-mobile children are due to underlying differences between these groups (between-child log odds: 3.56, standard error: 1.22), not by a change in status of residential mobility (within-child log odds: 1.33, standard error: 1.02). Our findings suggest that residential mobility in the teenage years does not place children at an increased risk of cannabis use throughout these years

Spatial and Temporal Geovisualisation and Data Mining of Road Traffic Accidents in Christchurch, New Zealand

Abstract This paper outlines the development of a method for using Kernel Estimation cluster analysis techniques to automatically identify road traffic accident 'black spots' and 'black areas'. A Novel data-mining approach has been developed -adding to the generic exploratory spatial analysis toolkit. Christchurch, New Zealand, was selected as the study area and data from the LTNZ crash database was used to trial the technique. A GIS and Python scripting was used to implement the solution, combining spatial data for average traffic flows with the recorded accident locations. Kernel Estimation was able to identify the accident clusters, and when used in conjunction with Monte Carlo simulation techniques, was able to identify statistically significant clusters

Extended impacts of climate change on health and wellbeing

Anthropogenic climate change is progressively transforming the environment despite political and technological attempts to reduce greenhouse gas emissions to tackle global warming. Here we propose that greater insight and understanding of the health-related impacts of climate change can be gained by integrating the positivist approaches used in public health and epidemiology, with holistic social science perspectives on health in which the concept of ‘wellbeing’ is more explicitly recognised. Such an approach enables us to acknowledge and explore a wide range of more subtle, yet important health-related outcomes of climate change. At the same time, incorporating notions of wellbeing enables recognition of both the health co-benefits and dis-benefits of climate change adaptation and mitigation strategies across different population groups and geographical contexts. The paper recommends that future adaptation and mitigation policies seek to ensure that benefits are available for all since current evidence suggests that they are spatially and socially differentiated, and their accessibility is dependent on a range of contextually specific socio-cultural factors.<br/

Modelling the spatial risk pattern of dementia in Denmark using residential location data: A registry-based national cohort

Dementia is a major global public health concern that is increasingly leading to morbidity and mortality among older adults. While studies have focused on the risk factors and care provision, there is currently limited knowledge about the spatial risk pattern of the disease. In this study, we employ Bayesian spatial modelling with a stochastic partial differential equation (SPDE) approach to model the spatial risk using complete residential history data from the Danish population and health registers. The study cohort consisted of 1.6 million people aged 65 years and above from 2005 to 2018. The results of the spatial risk map indicate high-risk areas in Copenhagen, southern Jutland and Funen. Individual socioeconomic factors and population density reduce the intensity of high-risk patterns across Denmark. The findings of this study call for the critical examination of the contribution of place of residence in the susceptibility of the global ageing population to dementia

Wellbeing impacts of city policies for reducing greenhouse gas emissions

To mitigate climate change, city authorities are developing policies in areas such as transportation, housing and energy use, to reduce greenhouse gas emissions. In addition to their effects on greenhouse gas emissions, these policies are likely to have consequences for the wellbeing of their populations for example through changes in opportunities to take physical exercise. In order to explore the potential consequences for wellbeing, we first explore what ‘wellbeing’ is and how it can be operationalised for urban planners. In this paper, we illustrate how wellbeing can be divided into objective and subjective aspects which can be measured quantitatively; our review of measures informs the development of a theoretical model linking wellbeing to policies which cities use to reduce greenhouse gas emissions. Finally, we discuss the extent to which the links proposed in the conceptual model are supported by the literature and how cities can assess wellbeing implications of policies.</p