Research Programme

Background

Ageing is generally associated with a decrease in mobility and social interaction (Morris et al. 2004) and this decrease is dependent on various health and social factors (Chen et al. 2004). A recent government report on the scientific aspects of ageing noted that 43% of people over the age of 50 report problems with their mobility and reported a deterioration in walking speed that is more marked in women than in men (Select Committee on Science and Technology 2002). The report cited The Royal College of Physicians of Edinburgh as stating that: "Physical activity is the major modifiable influence on health in old age,” citing the damaging problems of loss of bone density as but one example of the problems associated with restricted activity. Mobility loss is not inevitable – although clearly a function of age, it is also linked to income and educational attainment (Guralnik et al, 1993; Melzer et al, 2001) and simple interventions can help to alleviate the problem: For example, those older adults who keep a dog reported much greater levels of activity than those who did not, with many associated benefits (Serpell, 1991). Adults for whom mobility is a problem suffer in a variety of ways. Not only are their social lives restricted but they are also more limited in terms of their access to good nutrition, leisure and other activities. For example people with restricted mobility have fewer choices in terms of where and when they can shop, and they have been found to experience problems in maintaining a balanced diet (Wylie et al, 1999).

Aims and Objectives

In this study we seek to utilise the dataset from a 20 year longitudinal study of ageing and complement this with a new study utilising an innovative method for mapping the mobility of the surviving oldest old. The project will draw upon activity monitoring methods and combine this with data from state-of-the-art location-aware technologies in order to develop new metrics. These will then be used to describe the relationship between mobility and physical and mental well-being. The project will address elements of the NDA second call in its four objectives, as follows: Firstly, we seek to establish a sophisticated mobility profile of the oldest old – determining where individuals go and how active they are in the process. In order to achieve this, we will combine, for the first time, accelerometry data with new data from location-based technologies in order to create innovative mobility metrics. These can then be used to corroborate self-reports and which can help document older adults’ autonomy and independence in terms of diversity in activity and engagement with public space. Secondly, we will develop a more accurate picture of the current status of our oldest-old cohort in order to map the new mobility data against accurate indices of successful ageing – including assessments of balance, nutrition, health, lifestyle and social engagement. Thirdly, we seek to use these new data in combination with the existing longitudinal data in order to model predictors and consequences of mobility in the oldest old. Finally, we wish to consult with stakeholders in order to make preliminary assessments of the utility and acceptability of the new mobility-tracking technologies as healthcare interventions - supporting the identification of individuals at risk.

Accelerometry

Activity or ambulatory monitors can be used to provide a clearer picture of how much activity an individual achieves and can map the pattern of activity throughout the day. The monitors are small and typically worn around the ankle or thigh where they register the stepping movements of the legs but can also register changes in body position indicative of the transition from lying to sitting or from sitting to standing. This kind of activity monitoring provides an objective method of quantifying activity unobtrusively for extended periods of time in the home and community. Accelerometry has been used for the assessment of activity levels in different subjects and also as an outcome in intervention studies (Rochester et al., 2006; Bussman et al., 1998a&b; Busse et al., 2004). For example, Busse et al., 2004, demonstrated that activity monitoring was a reliable and valid measure of activity in people with neurological conditions who were living independently in the community. They found that neurological patients, including those with PD, had lower levels of walking activity than age matched controls.

Tracking

In recent years a number of new technologies have made it easy for us to be located by others. Services such as OnStar’s Driving Directions, MModes’s Find Things or People Nearby help others to keep track of our movements but remove certain privacy priveleges (Consolvo et al., 2005). These new location-based technologies tend to fall into two camps: Location-tracking services collate information from third parties (such as mobile telephony service providers) in order to track individuals, while position-aware services depend upon devices which have knowledge of their own position (Snekkenes, 2001). Several of these systems have been specifically developed to monitor people for homecare purposes e.g. Telemonitoring (Rialle et al 2003). Maciuszek et al (2005) argue such systems can make a decisive contribution to coping and quality of life particularly for vulnerable adults. Location-aware systems can help the ageing population live independently but we need to understand more about the opportunities and problems associated with such monitoring. 

As we have argued, sustained levels of activity are important for successful ageing. Tracking offers the potential to assess the mobility of older adults and also offers opportunities for monitoring of health and wellbeing – with low levels of activity, for example, signalling that an individual may be at risk. Within the proposed project, new tracking technologies will enable us to gather information, manage and model the data associated with mobility in a group of our oldest old. In this regard, we propose a partnership with a North East based technology firm (Trackaphone) that has set up innovative tracking services via mobile phones and wearable badges.

The Participant panel

The participants included in the NDA project are part of a large, multi-centre longitudinal study. Recruitment of the sample began in 1983 and over the past 27 has been funded by: the UK Social Science Research Council from 1983-88; Medical Research and Economic and Social Council from 1988-1993; Medical Research Council 1993-1998; Economic and Social Research Council, Wellcome Trust, Unilever plc and University of Manchester during 1998-2003.

For the current NDA-funded project 380 of the ‘oldest old’ volunteers from the original sample were invited to participate and 86 individuals completed the study.

The Steering Group

The NDA steering group included representatives from two industrial collaborators (trackaphone and the Centre of Excellence for Life Science; CELS), the grant applicants and Research Assistants. The steering group met 3 times a year to advise on the overall project activity and project outcomes.