Identifying the activity and habits of individuals in a large geospatial dataset
Lead Research Organisation:
University of Leeds
Department Name: Sch of Geography
Abstract
The Consumer Data Research Centre has partnered with health and lifestyle app Bounts to assess the activity patterns of individuals. These data provide insight in to the level and type of physical activity, engagement with technology and daily spatial mobility patterns of a large group of individuals over an extended time period. This PhD will provide an opportunity to understand these patterns in detail and develop methods to predict and test how individuals might behave in the future. Practical applications are aligned to core CDRC areas: healthy lifestyles, transport, sustainability and retail.
Understanding patterns. We have an opportunity to use these data to better understand the activity patterns of individuals and how these relate to their basic demographic information. We can examine the effects of geography and time on activity levels and start to see how these vary spatially and temporally.
Predicting behaviours. Using techniques such as microsimulation and Agent Based Modelling, we have an opportunity to predict activity patterns under given scenarios or in different locations. We can test the impact of policy intervention on activity levels and begin to explore strategies for improving health.
Understanding patterns. We have an opportunity to use these data to better understand the activity patterns of individuals and how these relate to their basic demographic information. We can examine the effects of geography and time on activity levels and start to see how these vary spatially and temporally.
Predicting behaviours. Using techniques such as microsimulation and Agent Based Modelling, we have an opportunity to predict activity patterns under given scenarios or in different locations. We can test the impact of policy intervention on activity levels and begin to explore strategies for improving health.
Publications
Clark S
(2021)
Clustering Accelerometer Activity Patterns from the UK Biobank Cohort.
in Sensors (Basel, Switzerland)
Jenneson VL
(2022)
A systematic review of supermarket automated electronic sales data for population dietary surveillance.
in Nutrition reviews
Oldroyd R
(2021)
Correction to: Progress Towards Using Linked Population-Based Data For Geohealth Research: Comparisons Of Aotearoa New Zealand And The United Kingdom
in Applied Spatial Analysis and Policy
Oldroyd RA
(2021)
Progress Towards Using Linked Population-Based Data For Geohealth Research: Comparisons Of Aotearoa New Zealand And The United Kingdom.
in Applied spatial analysis and policy
Pontin F
(2021)
Characterisation of Temporal Patterns in Step Count Behaviour from Smartphone App Data: An Unsupervised Machine Learning Approach.
in International journal of environmental research and public health
Pontin F
(2021)
Socio-demographic determinants of physical activity and app usage from smartphone data.
in Social science & medicine (1982)
Pontin FL
(2022)
Objectively measuring the association between the built environment and physical activity: a systematic review and reporting framework.
in The international journal of behavioral nutrition and physical activity
| Description | This research evaluates the suitability of secondary smartphone data in assessing physical activity of large popualtions. Identifying both the opportunities and considerations that need to be taken while using secondary data for this purpose. Identifying key take away findings in demographic variations in physical activity levels and the influence of environmental exposures in determining activity levels. Whilst focusing on developing reproducible methods in using secondary smartphone data to allow future researchers to build upon the patterns identified in other populations and situations. |
| Exploitation Route | This funded project, in its identification and evaluation of the opportunities and considerations that need to be taken while using secondary data provide a strong body of evidence from which both researchers or commercial stakeholders can begin to develop their own applications for assessing physical activity. As well as, through the use of reproducible methodologies, provide a striating point for future research in this field. Which could allow cheaper and easier assessment of population and individual level physical activity, allowing identification of both beneficial and detrimental health behaviours and environmental influences. Allowing more targeted as well as general public health interventions to increase physical activity levels. |
| Sectors | Digital/Communication/Information Technologies (including Software),Healthcare,Leisure Activities, including Sports, Recreation and Tourism,Transport,Other |
| Description | CSAP cluster fund |
| Amount | £540 (GBP) |
| Organisation | University of Leeds |
| Department | Centre for Spatial Analysis and Policy |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 06/2019 |
| End | 07/2019 |
| Description | Overseas Institutional Visit funding (Economic Social Research Council: Data Analytics & Society CDT) |
| Amount | £2,200 (GBP) |
| Organisation | Economic and Social Research Council |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2020 |
| End | 03/2020 |
| Description | Collaboration with the GeoHealth laboratory, University of Canterbury |
| Organisation | University of Canterbury NZ |
| Country | New Zealand |
| Sector | Academic/University |
| PI Contribution | Working collaborating with the GeoHealth laboratory on a publication, utilising data collected by the GeoHealth lab. |
| Collaborator Contribution | Also working on the publication. |
| Impact | NA |
| Start Year | 2019 |
| Description | Be Curious: University fo Leeds Public engagement event |
| Form Of Engagement Activity | Participation in an open day or visit at my research institution |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Public/other audiences |
| Results and Impact | The purpose of this engagement event was to educate and engage the public in the ways their secondary data is and can be beneficially used. Taking the idea that this data collect forms part of a 'smart city'. For example how data that is routinely collected such as purchasing patterns using supermarket loyalty cards, footfall counters in city centres, wifi logins or smartphone activity tracking. Can be used to assess population diet and activity levels and design interventions to benefit public health or be used in emergency and urban planning. The smart city approach was used and activities designed to engage children from age 4 upwards and adults attending the event. |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://datacdt.org/be-curious-2019/ |