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Linking environmental, socioeconomic and health datasets provides new insights into the potential associations between climate change and human health and wellbeing, and underpins the development of decision support tools that will promote resilience to climate change, and thus enable more effective adaptation. This paper outlines the challenges and opportunities presented by advances in data collection, storage, analysis, and access, particularly focusing on "data mashups". These data mashups are integrations of different types and sources of data, frequently using open application programming interfaces and data sources, to produce enriched results that were not necessarily the original reason for assembling the raw source data. As an illustration of this potential, this paper describes a recently funded initiative to create such a facility in the UK for use in decision support around climate change and health, and provides examples of suitable sources of data and the purposes to which they can be directed, particularly for policy makers and public health decision makers.

There has been considerable discussion in health geography and related areas of neighbourhood effects on health: the idea that people's health in one geographical area may be influenced not only by the composition of that area's population, but also by the area's geographical context. Hence, the healthiness or otherwise of the neighbourhood may have an important effect on local people's health. Although neighbourhoods and their boundaries are sometimes obvious to local residents, it is more common to find considerable disagreement on the size and contents of a neighbourhood. In this paper, we use British census Enumeration Districts as building blocks to construct alternative zonal systems, and experiment to see if neighbourhoods defined in different ways have similar implications for health. The well known modifiable areal unit problem shows that analytical conclusions may differ substantially according to how data are aggregated. Boundaries can be drawn to maximize equality of size, compactness of shape, homogeneity in social composition, accordance with 'natural' boundaries, and probably many other factors; which of these criteria are more effective in defining zones relevant to health? One conclusion is that the effect of neighbourhood conditions should be looked at using several different ways to define neighbourhoods, and that the size and composition of these neighbourhoods may be different in different parts of a study area. Keywords: UK; Modifiable areal unit problem; Zone design; Neighbourhood; Context and composition

This paper addresses the issues surrounding an individual's exposure to potential environmental risk factors, which can be implicated in the aetiology of a disease. We hope to further elucidate the 'lag' or latency period between the initial exposure to potential pathogens and the physical emergence of the disease, with specific reference to the rare neurological condition, motor neurone disease (MND), using a dataset obtained from the Finnish Death Certificate registry, for MND deaths between the period 1985-1995. A space-time approach is adopted, whereby patterns in both time and space are considered. No prior assumptions about the aetiology of MND are adopted. By using methods for the analysis of point processes, which preserve the continuous nature of the data, we resolve some of the problems of analysis that are often based on arbitrary areal units, such as postcode boundaries, or political boundaries. We use kernel estimation to model space-time patterns. Raised relative risk is assessed by adopting appropriate adjustments for the underlying population at risk, with the use of controls. Significance of the results is assessed using Monte Carlo simulation, and comparisons are made with results obtained from Openshaw's geographical analysis machine (GAM). Our results demonstrate the utility of kernel estimation as a visualisation tool. Small areas of elevated risk are identified, which need to be more closely examined before any firm conclusions can be drawn. We highlight a number of issues concerning the inadequacies of the data, and possibly of the techniques themselves.

Background: Climate change is a global threat to health and wellbeing. Here we provide findings of an international research project investigating the health and wellbeing impacts of policies to reduce greenhouse gas emissions in urban environments.Methods: Five European and two Chinese city authorities and partner academic organisations formed the project consortium. The methodology involved modelling the impact of adopted urban climate-change mitigation transport, buildings and energy policy scenarios, usually for the year 2020 and comparing them with business as usual (BAU) scenarios (where policies had not been adopted). Carbon dioxide emissions, health impacting exposures (air pollution, noise and physical activity), health (cardiovascular, respiratory, cancer and leukaemia) and wellbeing (including noise related wellbeing, overall wellbeing, economic wellbeing and inequalities) were modelled. The scenarios were developed from corresponding known levels in 2010 and pre-existing exposure response functions. Additionally there were literature reviews, three longitudinal observational studies and two cross sectional surveys.Results: There are four key findings. Firstly introduction of electric cars may confer some small health benefits but it would be unwise for a city to invest in electric vehicles unless their power generation fuel mix generates fewer emissions than petrol and diesel. Second, adopting policies to reduce private car use may have benefits for carbon dioxide reduction and positive health impacts through reduced noise and increased physical activity. Third, the benefits of carbon dioxide reduction from increasing housing efficiency are likely to be minor and co-benefits for health and wellbeing are dependent on good air exchange. Fourthly, although heating dwellings by in-home biomass burning may reduce carbon dioxide emissions, consequences for health and wellbeing were negative with the technology in use in the cities studied.Conclusions: The climate-change reduction policies reduced CO2 emissions (the most common greenhouse gas) from cities but impact on global emissions of CO2 would be more limited due to some displacement of emissions. The health and wellbeing impacts varied and were often limited reflecting existing relatively high quality of life and environmental standards in most of the participating cities; the greatest potential for future health benefit occurs in less developed or developing countries. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Serious air pollution has caused about one million premature deaths per year in China recently. Besides cross-border atmospheric transport of air pollution, trade also relocates pollution and related health impacts across China as a result of the spatial separation between consumption and production. This study proposes an approach for calculating the health impacts of emissions due to a region's consumption based on a multidisciplinary methodology coupling economic, atmospheric, and epidemiological models. These analyses were performed for China's Beijing and Hebei provinces. It was found that these provinces' consumption-based premature deaths attributable to ambient PM 2.5 were respectively 22,500 and 49,700, which were 23% higher and 37% lower than the numbers solely within their boundaries in 2007. The difference between the effects of trade and trade-related emissions on premature deaths attributable to air pollution in a region has also been clarified. The results illustrate the large and broad impact of domestic trade on regional air quality and the need for comprehensive consideration of supply chains in designing policy to mitigate the negative health impacts of air pollution across China. [ABSTRACT FROM AUTHOR]