Kalu ME1,2, Tang A1, Nwankwo H2,3,4, Dal Bello-Haas V1
1McMaster University, School of Rehabilitation Science, Hamilton, Canada, 2Emerging Researchers & Professional in Ageing - African Network, Abuja, Nigeria, 3MacKenzie Physiotherapy Clinic, Nigeria, Nigeria, 4University of Southampton, Center for Research on Ageing, Southampton, United Kingdom
Background: The associations between socioeconomic status (e.g., income, education and occupation) and health parameters have been studied in some populations (obesity, low back pain, metabolic syndrome) and have focused primarily on relationships with physical activity participation, well-being and mortality. Given the aging population, the aim of this study was to examine the association between socioeconomic status and mobility in older adults. Understanding this relationship can inform the development of a framework for using socioeconomic status as a guide for selecting mobility assessment and interventions for older adults.
Purpose: In this presentation, we will:
1) provide a review of the current evidence regarding the association between the socioeconomic status elements (income, education, and occupation) and mobility for older adults, and
2) discuss how this evidence can be used to inform the choice of mobility assessment and interventions for older adults.
Methods: This was a state-of-art review of which multiple databases were systematically searched using the following search terms: education OR occupation OR profession OR income AND mobility interventions OR mobility limitation OR physical mobility OR walking OR older adult* OR elderly OR ag*ing OR geriatrics OR gerontology. Quantitative articles that investigated the association of socioeconomic status (SES) on any mobility outcome for older adults (³60 years of age), published from 2000-2018 were included. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines in conducting this review. Two authors independently conducted title and abstract screening (kappa=0.84), assessed full-text articles for inclusion, and extracted the data, and conducted quality assessment of the included articles using the Downs and Black checklist (a=.87).
Results: Of the thirty-five articles included in this review, most (85%) were population-based studies of community-dwelling older adults. Studies were conducted in eleven countries. Most of the articles (91%) were rated excellent or good quality. In total, there were 69 analyses conducted that examined the associations between income (n=27), education (n=35) and occupation (n=7) on self-reported (n=33, e.g. Life Space Measure, Mobility Help and Tiredness, 15-minute walk around neighbourhood) and performance-based measures of mobility (n=36, e.g. Short Physical Performance Battery (SPPB), Time Up and Go (TUG), Chair Rise) . Of these, 53 analyses (77%) found that mobility in older adults was associated with higher education (n=27 analyses, p=0.001-0.01), higher incomes (n=21 analyses, p≤0.001), and holding skilled jobs (n=5 analyses, p= 0.01- 0.03). Nearly all (95%) analyses that focused on mobility outcomes of walking over longer distances (e.g. 400 or 800m) reported positive associations with SES, whereas only 50% of analyses with walking outcomes measured over a shorter distance (e.g. 2.4m) found similar associations.
Conclusion(s): Income, education and occupation are significantly associated with several mobility outcomes including SPPB, TUG, Chair Rise, 400m and 800m walk, Life Space Measure scores, Mobility Help and Tiredness measures and 15-minute walk around the neighbourhood. Mobility outcomes where walking was measured over short distances (e.g. 2.4m) were not consistently associated with SES.
Implications: Clinicians assessing older adults should consider assessing mobility using outcome measures that consider a longer walking distance e.g., at least 400 or 800m.
Keywords: socio-economic status, mobility, older adults
Funding acknowledgements: Michael Kalu is the first recipient of the Labarge Mobility Scholarship from the McMaster Institute for Research on Aging.
Purpose: In this presentation, we will:
1) provide a review of the current evidence regarding the association between the socioeconomic status elements (income, education, and occupation) and mobility for older adults, and
2) discuss how this evidence can be used to inform the choice of mobility assessment and interventions for older adults.
Methods: This was a state-of-art review of which multiple databases were systematically searched using the following search terms: education OR occupation OR profession OR income AND mobility interventions OR mobility limitation OR physical mobility OR walking OR older adult* OR elderly OR ag*ing OR geriatrics OR gerontology. Quantitative articles that investigated the association of socioeconomic status (SES) on any mobility outcome for older adults (³60 years of age), published from 2000-2018 were included. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines in conducting this review. Two authors independently conducted title and abstract screening (kappa=0.84), assessed full-text articles for inclusion, and extracted the data, and conducted quality assessment of the included articles using the Downs and Black checklist (a=.87).
Results: Of the thirty-five articles included in this review, most (85%) were population-based studies of community-dwelling older adults. Studies were conducted in eleven countries. Most of the articles (91%) were rated excellent or good quality. In total, there were 69 analyses conducted that examined the associations between income (n=27), education (n=35) and occupation (n=7) on self-reported (n=33, e.g. Life Space Measure, Mobility Help and Tiredness, 15-minute walk around neighbourhood) and performance-based measures of mobility (n=36, e.g. Short Physical Performance Battery (SPPB), Time Up and Go (TUG), Chair Rise) . Of these, 53 analyses (77%) found that mobility in older adults was associated with higher education (n=27 analyses, p=0.001-0.01), higher incomes (n=21 analyses, p≤0.001), and holding skilled jobs (n=5 analyses, p= 0.01- 0.03). Nearly all (95%) analyses that focused on mobility outcomes of walking over longer distances (e.g. 400 or 800m) reported positive associations with SES, whereas only 50% of analyses with walking outcomes measured over a shorter distance (e.g. 2.4m) found similar associations.
Conclusion(s): Income, education and occupation are significantly associated with several mobility outcomes including SPPB, TUG, Chair Rise, 400m and 800m walk, Life Space Measure scores, Mobility Help and Tiredness measures and 15-minute walk around the neighbourhood. Mobility outcomes where walking was measured over short distances (e.g. 2.4m) were not consistently associated with SES.
Implications: Clinicians assessing older adults should consider assessing mobility using outcome measures that consider a longer walking distance e.g., at least 400 or 800m.
Keywords: socio-economic status, mobility, older adults
Funding acknowledgements: Michael Kalu is the first recipient of the Labarge Mobility Scholarship from the McMaster Institute for Research on Aging.
Topic: Older people; Older people
Ethics approval required: No
Institution: McMaster University
Ethics committee: Not applicable
Reason not required: This is a systematic review that requires no ethical approval
All authors, affiliations and abstracts have been published as submitted.
