Lifespace metrics of older adults with mild cognitive impairment and dementia recorded via geolocation data

• Published in: Australasian journal on ageing 2021-12, Vol.40 (4), p.e341-e346
• Main Authors: Liddle, Jacki, Ireland, David, Krysinska, Karolina, Harrison, Fleur, Lamont, Robyn, Karunanithi, Mohan, Kang, Kristan, Reppermund, Simone, Sachdev, Perminder S., Gustafsson, Louise, Brauer, Sandra, Pachana, Nancy A., Brodaty, Henry
• Format: Article
• Language: English
• Subjects: Aged; Aged, 80 and over; Automobile Driving; Benchmarking; Cognitive Dysfunction - diagnosis; Cognitive Dysfunction - epidemiology; community; Dementia - diagnosis; Dementia - epidemiology; gerontology; Humans; Independent Living; Male; mobility restriction; Smartphone
• ISSN: 1440-6381; 1741-6612
• DOI: 10.1111/ajag.13007

Objective Lifespace, the physical area in which someone conducts life activities, indicates lived community mobility. This study explored the feasibility of technology‐based lifespace measurement for older people with dementia and mild cognitive impairment (MCI), including the generation of a range of lifespace metrics, and investigation of relationships with health and mobility status. Methods An exploratory study was conducted within a longitudinal observational study. Eighteen older adults (mean age 86.7 years (SD: 3.2); 8 men; 15 MCI), participated. Lifespace metrics were generated from geolocation data (GPS and Bluetooth beacon) collected through a smartphone application for one week (2015–2016). Cognitive and mobility‐related outcomes were compared from study data sets at baseline (2005–2007) and 6‐year follow‐up (2011–2014). Results Lifespace data could be collected from all participants, and metrics were generated including percentage of time at home, maximum distance from home, episodes of travel in a week, days in a week participants left home, lifespace area (daily, weekly and total), indoor lifespace (regions in the home/hour), and a developed lifespace score that combined time, frequency of travel, distance and area. Results indicated a large range of lifespace areas (0.1 – 97.88 km2; median 6.77 km2) with similar patterns across lifespace metrics. Significant relationships were found between lifespace metrics and concurrent driving status and anteceding scores on the sit‐to‐stand test (at baseline and follow‐up). Conclusions Further longitudinal exploration of lifespace is required to develop an understanding of the nature of lifespace of older community‐dwelling people, and its relationship with health, mobility and well‐being outcomes.