Mobility and ageing
Introduction
New methods are needed to examine how much activity an individual achieves throughout a day. Monitoring activity levels by accelerometry and tracking devices offers the potential to assess the mobility of older adults, and along with monitoring of health and wellbeing can help identify individuals who may be at risk.
Investigators
Lynn McInnes, Northumbria University
Pamela Briggs, Northumbria University
Linda Little, Northumbria University
Lynn Rochester, Glasgow Caledonian University
Team
CELS (Centre of Excellence for Life Sciences), Trackaphone
Aims and objectives
The aim of this project was to utilise an innovative method for mapping the mobility of the oldest-old members of an existing 20 year longitudinal study of ageing.
The project drew upon activity monitoring methods and combined this with data from state-of-art location-aware technologies in order to develop new metrics.
These were then used to describe the relationship between mobility and physical and mental wellbeing.
Specifically, the project aimed to establish a sophisticated mobility profile of the oldest-old by determining where individuals go and how active they are in the process. In order to active this accelerometry data was combined with location based technologies in order to create innovative mobility metrics.
Secondly the project developed a more accurate picture of the current status of the oldest-old cohort in order to map the new mobility data against indices of successful ageing such as nutrition, balance, health, lifestyle and social engagement.
Thirdly, this new data was examined in conjunction with data from an existing longitudinal dataset in order to model predictors and consequences of mobility in the oldest old.
Finally preliminary assessments of the utility and acceptability of the new mobility-tracking methodologies as healthcare interventions were investigated as a means of supporting the identification of individuals at risk.
Design
Phase one
Interviews, tests and questionnaires and data collection using accelerometry and location-based tracking was conducted on a sample of the oldest-old volunteers from a 20 year longitudinal study of ageing to
establish a reliable profile of mobility of the oldest-old
establish a current health and lifestyle profile of the oldest-old
Phase two
Data from a 20 year longitudinal study of ageing which includes information of demographics, health, pathology, exercise, physical and intellectual activities, social involvements, nutrition and alcohol and tobacco consumption was used in conjunction with the new metrics gathered in phase one to model the predictors and consequences of mobility in the oldest-old.
Phase three
Post test interviews were conducted to assess the utility and acceptability of the new mobility-awareness metrics in the health monitoring of older adults and in identifying individuals at risk. These interviews assessed the trade-off between privacy concerns and health benefits of using accelerometry and location-based tracking technologies.
Policy implications
Policy and practice implications of this research focussed mainly on understanding activity and mobility patterns of older people living in the community. It investigated how physical and mental wellbeing relate to this mobility, and also determined the consequences of good or poor mobility among the oldest-old members of the population.
In terms of product development, the research developed and utilised activity monitoring and location awareness technologies with Trackaphone (a non-academic partner). Such systems have the potential to help older people live independently but ease of use, acceptability and privacy issues surrounding such devices needed to be examined.
The research therefore made recommendations of products that were suitable for the health monitoring of older people and factors that needed to be considered to ensure ease of utility and acceptability. It also examined the viability of commercial development of mobility tracking technology as a means of identifying those ‘at risk’.
Findings
New metrics for exploring the relationship between mobility and successful ageing (PDF, 1.3MB)