Projects

COVID-19

There are several projects I am working on in response to the COVID-19 pandemic. The first involves modeling the risk of infection in workplaces. The second involves modeling the environmental determinants of risk of transmission and death.

DISPLAY: Determining the impact of smoking point of sale legislation among youth (Display) study

The DISPLAY study has a multimodal before-and-after design using mixed methods to collect data in four purposively selected communities. This data was used to explore the location and density of tobacco retail outlets around the home, school and route to school in relation to smoking attitudes and behaviour.

Alcohol and Tobacco Environments in Scotland

This Rshiny web application allows you to map alcohol and tobacco outlet density and related harm for small neighbourhoods across Scotland.

Analysing the Association between Ultraviolet Radiation, Vitamin D and Allergic Disease

Using a number of secondary data sources, I investigated the spatio-temporal relationship between UVR and 25(OH)D levels, in order to determine the association with asthma and allergic health outcomes.

Environmental determinants of IVF treatment

This study proposes to make novel and unique linkages between the HFEA register and temperature, air pollution and UVR exposure data to examine the association of air pollution and UVR with IVF treatment outcomes.

Medical & Environmental Data Mash-up Infrastructure project (MEDMI)

Using data from Public Health England and the Met office we were exploring the relationship between pathogen counts, seasonality and weather for England and Wales. The results were presented in an Rshiny application.

Mobility, Mood and Place Project (MMP)

We are exploring how physical, built and social environments evolve over time and how they impact on inequalities in health-related mobility as people move into older age. We used data from 1,091 people in their 70s, together with temporal, area-level measures of their current, recent and past environment.

Selected Publications

Greater neighbourhood provision of public parks from childhood through to adulthood may help to slow down the rate of cognitive decline in later life, recognising that such environmental associations are always sensitive to individual characteristics.
In SSM
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Recent Publications

  • Association between activity space exposure to parks in childhood and adolescence and cognitive ageing in later life

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  • Pathogen seasonality and links with weather in England and Wales: a big data time series analysis

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  • Changing labour market conditions during the ‘great recession’ and mental health in Scotland 2007–2011: an example using the Scottish Longitudinal Study and data for local areas in Scotland

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  • Association between Serum 25-Hydroxy Vitamin D Levels and the Prevalence of Adult-Onset Asthma

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  • Life course of place: a longitudinal study of mental health and place

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  • A randomised control crossover trial of a theory based intervention to improve sun-safe and healthy behaviours in construction workers: study protocol

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  • Green space and cognitive ageing: A retrospective life course analysis in the Lothian Birth Cohort 1936

    Details PDF Project

  • Land cover and air pollution are associated with asthma hospitalisations: A cross-sectional study.

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  • Coastal climate is associated with elevated solar irradiance and higher serum vitamin D levels

    Details PDF Project

Recent & Upcoming Presentations

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Recent Posts

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Data Processing R, Built environment, Place Monitoring, Tobacco, Retail
Introduction The built environment is constantly changing. Whether it be short-term changes - e.g. roadworks, or long-term, e.g. a new road. These changes can impact exposures (air pollutants from road traffic), behaviours (decision to drive to work) or health (risk of being in a traffic accident). It’s therefore important to monitor the changes to the built environment so that interventions can be developed to reduce risk to health either directly or indirectly (exposure/behaviour).

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Data Collection Lifegrid, Lifecourse, Place, Lifeplace, Edinburgh
Background There are two parts required to conduct a study on health and place across the lifecourse: Longitudinal information on the environment Information on residential location This blog post focusses on the latter. This information might be collected prospectively via routine administrative records (e.g. GP location), which could be linked to health records. However, for a number of research questions we might want to also use non-routinely collected information (e.

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Research Tips Social Media, Twitter, Facebook, Blogging, Public Engagement
Photo by NordWood Themes on Unsplash Background Social media is becoming the dominant platform for getting information, for the general population by superseding television and newspapers and increasingly for academics, displacing peer-reviewed journal articles. Time is limited and short communications are easier to digest, especially when on a mobile. To summarise findings from a research project or engage in an academic/policy debate in very short social media snippets is an impressive skill and one that I am keen to learn.

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Data Visualisation R, QGIS, Politics, Brexit, Geography
Introduction The ‘Revoke article 50 and remain in the EU petition’ is the most popular petition ever, which aims to stop the brexit process. The rules are that after 10,000 signatures, petitions get a response from the government, after 100,000 signatures, petitions are considered for debate in Parliament and after 17.4 million, we stop Brexit (Andrea Leadsom, 2019). As of writing this (25/03/19 17:00 GMT), the petition has amassed over 5 million signatures.

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Data Analysis Statistics, Modelling, SEM, Causality, Lavaan, Moderation, Mediation, R
Background I went on a course in Cambridge over the summer of 2018. This was to get me up to speed on structural equation modelling (SEM), which has a lot of potential applications in scenarios where the pathways between measured and unmeasured variables are the central focus of the research question. What is SEM? SEM is a mixture of confirmatory factor analysis (CFA) and path analysis. Another way to describe that, is that you have a measurement part and a structural part.

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