Background: Indoor dampness is thought to affect around 16% of European homes. It is generally accepted that increased exposure to indoor dampness and mould contamination (e.g. spores and hyphae) increases the risk of developing and/or exacerbating asthma. Around 30% of people in the Western world have an allergic disease (e.g. allergy, wheeze and asthma). The role of indoor mould contamination in the risk of allergic diseases in older adults is yet to be fully explored. This is of interest because older people spend more time indoors, as well as facing health issues due to the ageing process, and may be at greater risk of developing and/or exacerbating asthma as a result of indoor dampness. Methods: Face-to-face questionnaires were carried out with 302 participants residing in social housing properties located in South West England. Self-reported demographic, mould contamination (i.e. presence of mould growth and mouldy odour) and health information was linked with the asset management records (e.g. building type, age and levels of maintenance). Multivariate logistic regression was used to calculate the odd ratios and confidence intervals of developing and/or exacerbating asthma, wheeze and allergy with exposure to reported indoor mould contamination. We adjusted for a range of factors that may affect asthma outcomes, which include age, sex, current smoking, presence of pets, education, and building type and age. To assess the role of mould contamination in older adults, we compared younger adults to those aged over 50 years. Results: Doctor-diagnosed adult asthma was reported by 26% of respondents, 34% had current wheeze while 18% had allergies. Asthma was common among subjects exposed to reported visible mould (32%) and reported mouldy odour (42%). Exposure to visible mould growth and mouldy odour were risk factors for asthma, but not for wheeze or allergy. Exposure to mouldy odour increased the risk of asthma in adults over the age of 50 years (odds ratio (OR) 2.4, 95% confidence interval (CI) 1.10-5.34) and the risk was higher for females than for males (OR 3.5, 95% CI 1.37-9.08). These associations were modified by a range of built environment characteristics. Conclusions: We found that older adults living in social (public) housing properties, specifically women, may be at higher risk of asthma when exposed to mouldy odour, which has a number of implications for policy makers and practitioners working in the health and housing sector. Additional measures should be put in place to protect older people living in social housing against indoor damp and mould contamination.

Objective
This systematic review aimed to assess the effectiveness, feasibility and acceptability of mobile health (mHealth) technology (including wearable activity monitors and smartphone applications) for promoting physical activity (PA) and reducing sedentary behaviour (SB) in workplace settings.

Methods
Systematic searches were conducted in seven electronic databases (MEDLINE, SPORTDiscus, Scopus, EMBASE, PsycINFO, Web of Science and the Cochrane library). Studies were included if mHealth was a major intervention component, PA/SB was a primary outcome, and participants were recruited and/or the intervention was delivered in the workplace. Study quality was assessed using the Effective Public Health Practice Project (EPHPP) tool. Interventions were coded for behaviour change techniques (BCTs) using the Coventry, Aberdeen and London – Refined (CALO-RE) taxonomy.

Results
Twenty-five experimental and quasi-experimental studies were included. Studies were highly heterogeneous and only one was rated as ‘strong’ methodological quality. Common BCTs included self-monitoring, feedback, goal-setting and social comparison. A total of 14/25 (56%) studies reported a significant increase in PA, and 4/10 (40%) reported a significant reduction in sedentary time; 11/16 (69%) studies reported a significant impact on secondary outcomes including reductions in weight, systolic blood pressure and total cholesterol. While overall acceptability was high, a large decline in technology use and engagement was observed over time.

Conclusions
While methodological quality was generally weak, there is reasonable evidence for mHealth in a workplace context as a feasible, acceptable and effective tool to promote PA. The impact in the longer term and on SB is less clear. Higher quality, mixed methods studies are needed to explore the reasons for decline in engagement with time and the longer-term potential of mHealth in workplace interventions.

This study explores longitudinal relationships between material, psycho-social and behavioural social determinants of health and multimorbidity of people aged 50 years or older in England. We used data from the English Longitudinal Study of Ageing collected biannually between 2002 and 2015. Apart from the basic measure of multimorbidity (two or more diseases within a person) we constructed two distinct measures of health in order to take into account the biology of ageing (complex multimorbidity and multiple functional limitations). We found that the likelihood of multimorbidity and multiple functional limitations was consistently associated with the levels of household wealth, sense of control over one's life, physical activity and loneliness. Larger health inequalities were observed when health was measured as complex multimorbidity and multiple functional limitations than basic multimorbidity. Compared to the population group with the highest wealth, those with the lowest wealth had 47% higher odds of basic multimorbidity (95% C.I. 1.34-1.61), 73% higher odds of complex multimorbidity (95% C.I. 1.52-1.96) and 90% higher odds of having 10 or more functional limitations (95% C.I. 1.59-2.26). We did not find a dose-response relationship between alcohol consumption, smoking and multimorbidity but rather evidence of people in ill health actively moderating their health behaviour. We suggest that materialist models of multimorbidity and functional limitation at older age can not, on their own, explain the health inequalities as the behavioural and psycho-social factors play an important role. Policies aiming to reduce the risk of multimorbidity and functional limitation should address the issue at these three levels simultaneously, using the existing national infrastructure of General Practices.

This study aimed to estimate the prevalence of three measures of multimorbidity among people aged 50 years or older in England. Beside the basic measure of two or more diseases within a person, we added a measure of three or more affected body systems (complex multimorbidity) and a measure of 10 or more functional limitations. We found that the three health outcomes became more prevalent between 2002 and 2015. They were more common among females than males and were becoming more common among younger age groups. While in 2002, the prevalence of basic multimorbidity overcame 50% from the 70–74 age group upwards, in 2015 it crossed the same threshold in the 65–69 age group. The distribution of multimorbidity and multiple functional limitations were stratified by the amount of household wealth. Multiple functional limitations reflected the largest differences between the most and the least affluent groups (5.9-fold in 2014/2015), followed by the measure of complex multimorbidity (2.8-fold in 2014/2015) and basic multimorbidity (1.9-fold) in 2014/2015.While age acted as a levelling factor for the wealth differences in basic multimorbidity, it had no such effect on the two other outcomes. Our study observed social polarization among multimorbid ageing population in England where complex multimorbidity and multiple functional limitations increase faster and reflect stronger inequality than basic multimorbidity.

© 2018 There is a good understanding of past and present coastal processes as a result of coastal monitoring programmes within the UK. However, one of the key challenges for coastal managers in the face of climate change is future coastal change and vulnerability of infrastructure and communities to flooding. Drawing on a vulnerability-led and decision-centric framework (VL-DC) a Decision Support Tool (DST) is developed which, combines new observations and modelling to explore the future vulnerability to sea-level rise and storms for nuclear energy sites in Britain. The combination of these numerical projections within the DST and a Real Options Analysis (ROA) delivers essential support for: (i) improved response to extreme events and (ii) a strategy that builds climate change resilience.

Winder and Le Heron (2017) advocate for geographers to engage directly and critically with the Blue Economy and to remove the ‘disciplinary framings’ from which the notion of the Blue Economy has emerged. While endorsing Winder and Le Heron’s call for human geography to engage with debates about the Blue Economy, I argue that the lack of critical engagement within the geographical community with respect to the Blue Economy has not been imposed by disciplinary framings. Instead I ask Winder and Le Heron to clarify how a social and cultural critique of the Blue Economy will expand the current knowledge base of our oceans and seas. I also ask whether a critique of extensive literature within economics, planning and governance on the ocean resource have been the building blocks for the critical analysis of the Blue Economy provided by Winder and Le Heron.

The Lancet Countdown: tracking progress on health and climate change is an international, multidisciplinary research collaboration between academic institutions and practitioners across the world. It follows on from the work of the 2015 Lancet Commission, which concluded that the response to climate change could be "the greatest global health opportunity of the 21st century". The Lancet Countdown aims to track the health impacts of climate hazards; health resilience and adaptation; health co-benefits of climate change mitigation; economics and finance; and political and broader engagement. These focus areas form the five thematic working groups of the Lancet Countdown and represent different aspects of the complex association between health and climate change. These thematic groups will provide indicators for a global overview of health and climate change; national case studies highlighting countries leading the way or going against the trend; and engagement with a range of stakeholders. The Lancet Countdown ultimately aims to report annually on a series of indicators across these five working groups. This paper outlines the potential indicators and indicator domains to be tracked by the collaboration, with suggestions on the methodologies and datasets available to achieve this end. The proposed indicator domains require further refinement, and mark the beginning of an ongoing consultation process-from November, 2016 to early 2017-to develop these domains, identify key areas not currently covered, and change indicators where necessary. This collaboration will actively seek to engage with existing monitoring processes, such as the UN Sustainable Development Goals and WHO's climate and health country profiles. The indicators will also evolve over time through ongoing collaboration with experts and a range of stakeholders, and be dependent on the emergence of new evidence and knowledge. During the course of its work, the Lancet Countdown will adopt a collaborative and iterative process, which aims to complement existing initiatives, welcome engagement with new partners, and be open to developing new research projects on health and climate change.

A pressing problem facing coastal decision makers is the conversion of "high level" but plausible climate change assessments into an effective basis for climate change adaptation at the local scale. Here, we describe a web-based, geospatial decision-support tool (DST) that provides an assessment of the potential flood risk for populated coastal lowlands arising from future sea-level rise, coastal storms and high river flows. This DST has been developed to support operational and strategic decision making by enabling the user to explore the flood hazard from extreme events, changes in the extent of the flood-prone areas with sea-level rise, and thresholds of sea-level rise where current policy and resource options are no longer viable. The DST is built in an open source GIS that uses freely available geospatial data. Flood risk assessments from a combination of LISFLOOD-FP and SWAB models are embedded within the tool; the user interface enables interrogation of different combinations of coastal and river events under rising sea-level scenarios. Users can readily vary the input parameters (sea level, storms, wave height and river flow) relative to the present-day topography and infrastructure to identify combinations where significant regime shifts or "tipping points" occur. Two case studies are used to demonstrate the attributes of the DST with respect to the wider coastal community and the UK energy sector. Examples report on the assets at risk and illustrate the extent of flooding in relation to infrastructure access. This informs an economic assessment of potential losses due to climate change and thus provides local authorities and energy operators with essential information on the feasibility of investment for building resilience into vulnerable components of their area of responsibility.

© Author(s) 2015. A pressing problem facing coastal decision makers is the conversion of "high-level" but plausible climate change assessments into an effective basis for climate change adaptation at the local scale. Here, we describe a web-based, geospatial decision support tool (DST) that provides an assessment of the potential flood risk for populated coastal lowlands arising from future sea-level rise, coastal storms, and high river flows. This DST has been developed to support operational and strategic decision making by enabling the user to explore the flood hazard from extreme events, changes in the extent of the flood-prone areas with sea-level rise, and thresholds of sea-level rise where current policy and resource options are no longer viable. The DST is built in an open-source GIS that uses freely available geospatial data. Flood risk assessments from a combination of LISFLOOD-FP and SWAB (Shallow Water and Boussinesq) models are embedded within the tool; the user interface enables interrogation of different combinations of coastal and river events under rising-sea-level scenarios. Users can readily vary the input parameters (sea level, storms, wave height and river flow) relative to the present-day topography and infrastructure to identify combinations where significant regime shifts or "tipping points" occur. Two case studies demonstrate the attributes of the DST with respect to the wider coastal community and the UK energy sector. Examples report on the assets at risk and illustrate the extent of flooding in relation to infrastructure access. This informs an economic assessment of potential losses due to climate change and thus provides local authorities and energy operators with essential information on the feasibility of investment for building resilience into vulnerable components of their area of responsibility.

Using micro-simulation modelling techniques this paper examines methane emissions across Irish farms. The effects of a carbon equivalent tax on average family farm income are analysed at both the farm and regional level. The spatial micro-simulation model developed uses a technique called simulated annealing to match the Irish Census of Agriculture data to a National Farm Survey. The main advantage of the spatial micro-simulation approach is the fact that it allows one to account for the heterogeneity in the farm population across space. The results of the modelling process are presented using GIS mapping techniques and highlight the fact that there would be significant regional variation in the burden of an agricultural tax that was based on a rate per unit of methane emissions. The results also demonstrate that if the methane tax revenue raised was redistributed in the form of an environmental subsidy to farmers participating in an agri-environmental scheme (the Rural Environment Protection Scheme (REPS)) it would encourage farmers to participate in the scheme and could also have the effect of moving low income farms up the earnings distribution ladder. © 2008 Elsevier B.V. All rights reserved.

Using statistical matching techniques, economists can now create attribute rich datasets by matching across the common variables in two or more datasets. The farm level spatial microsimulation model developed in this paper uses one of many combinational optimatisation techniques-simulated annealing-to match the Irish Census of Agriculture to the 2005 Irish National Farm Survey (NFS). Using the new spatially disaggregated farm population microdata this paper then briefly analyses the impact of future common agricultural policy (CAP) reform on the distribution of family farm income in rural Ireland.