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Predictors of real-life mobility in community-dwelling older adults: an exploration based on a comprehensive framework for analyzing mobility


Giannouli, Eleftheria; Fillekes, Michelle Pasquale; Mellone, Sabato; Weibel, Robert; Bock, Otmar; Zijlstra, Wiebren (2019). Predictors of real-life mobility in community-dwelling older adults: an exploration based on a comprehensive framework for analyzing mobility. European Review of Aging and Physical Activity, 16(1):19.

Abstract

Background:
Reduced mobility is associated with a plethora of adverse outcomes. To support older adults inmaintaining their independence, it first is important to have deeper knowledge of factors that impact on theirmobility. Based on a framework that encompasses demographical, environmental, physical, cognitive, psychologicaland social domains, this study explores predictors of different aspects of real-life mobility in community-dwellingolder adults.

Methods:
Data were obtained in two study waves with a total sample ofn= 154. Real-life mobility (physicalactivity-based mobility and life-space mobility) was assessed over one week using smartphones. Active and gaittime and number of steps were calculated from inertial sensor data, and life-space area, total distance, and actionrange were calculated from GPS data. Demographic measures included age, gender and education. Physicalfunctioning was assessed based on measures of cardiovascular fitness, leg and handgrip strength, balance and gaitfunction; cognitive functioning was assessed based on measures of attention and executive function. Psychologicaland social assessments included measures of self-efficacy, depression, rigidity, arousal, and loneliness, sociableness,perceived help availability, perceived ageism and social networks. Maximum temperature was used to assessweather conditions on monitoring days.

Results:
Multiple regression analyses indicated just physical and psychological measures accounted for significantbut rather low proportions of variance (5–30%) in real-life mobility. Strength measures were retained in most of theregression models. Cognitive and social measures did not remain as significant predictors in any of the models.

Conclusions:
In older adults without mobility limitations, real-life mobility was associated primarily with measuresof physical functioning. Psychological functioning also seemed to play a role for real-life mobility, though theassociations were more pronounced for physical activity-based mobility than life-space mobility. Further factorsshould be assessed in order to achieve more conclusive results about predictors of real-life mobility in community-dwelling older adults.

Abstract

Background:
Reduced mobility is associated with a plethora of adverse outcomes. To support older adults inmaintaining their independence, it first is important to have deeper knowledge of factors that impact on theirmobility. Based on a framework that encompasses demographical, environmental, physical, cognitive, psychologicaland social domains, this study explores predictors of different aspects of real-life mobility in community-dwellingolder adults.

Methods:
Data were obtained in two study waves with a total sample ofn= 154. Real-life mobility (physicalactivity-based mobility and life-space mobility) was assessed over one week using smartphones. Active and gaittime and number of steps were calculated from inertial sensor data, and life-space area, total distance, and actionrange were calculated from GPS data. Demographic measures included age, gender and education. Physicalfunctioning was assessed based on measures of cardiovascular fitness, leg and handgrip strength, balance and gaitfunction; cognitive functioning was assessed based on measures of attention and executive function. Psychologicaland social assessments included measures of self-efficacy, depression, rigidity, arousal, and loneliness, sociableness,perceived help availability, perceived ageism and social networks. Maximum temperature was used to assessweather conditions on monitoring days.

Results:
Multiple regression analyses indicated just physical and psychological measures accounted for significantbut rather low proportions of variance (5–30%) in real-life mobility. Strength measures were retained in most of theregression models. Cognitive and social measures did not remain as significant predictors in any of the models.

Conclusions:
In older adults without mobility limitations, real-life mobility was associated primarily with measuresof physical functioning. Psychological functioning also seemed to play a role for real-life mobility, though theassociations were more pronounced for physical activity-based mobility than life-space mobility. Further factorsshould be assessed in order to achieve more conclusive results about predictors of real-life mobility in community-dwelling older adults.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
08 Research Priority Programs > Dynamics of Healthy Aging
Dewey Decimal Classification:910 Geography & travel
Scopus Subject Areas:Health Sciences > Geriatrics and Gerontology
Uncontrolled Keywords:Geriatrics and Gerontology
Language:English
Date:1 December 2019
Deposited On:03 Jan 2020 08:49
Last Modified:12 Mar 2023 08:11
Publisher:BioMed Central
ISSN:1813-7253
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1186/s11556-019-0225-2
Project Information:
  • : FunderFP7
  • : Grant ID288940
  • : Project TitleFARSEEING - FAll Repository for the design of Smart and sElf-adaptive Environments prolonging INdependent livinG
  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)