How does ageism influence frailty? A preliminary study using a structural equation model

Ye, Bo; Gao, Junling; Fu, Hua; Chen, Hao; Dong, Wenjing; Gu, Ming

doi:10.21203/rs.2.14601/v2

Cited by 1 publication

(1 citation statement)

References 52 publications

(40 reference statements)

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“…By now, there is abundant evidence for the importance of SPA for the way people actually grow older (3,4). For example, people with more positive SPA report better physical and mental health (5) and even live up to 7.5 years longer (1), while people with more negative SPA are at increased risk of physical decline or frailty (6,7). However, most ndings in this context rely on self-report data for physical function obtained by measures like the Short Form Health Survey (8,9) or the Health Scale for the Aged (10).…”

Section: Self-perceptions Of Aging and Physical Functionmentioning

confidence: 99%

Domain-Specific Self-Perceptions of Aging are Associated with Different Gait Patterns in Older Adults: A Cross-Sectional Latent Profile Analysis

Blawert

Krumpoch

Freiberger

et al. 2021

Preprint

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Background: Previous studies have pointed to the impact of self-perceptions of aging (SPA) on self-reported physical function in later life. However, less is known about the role of SPA for objectively measured physical function, especially gait. Research that examined other psychological variables and objectively measured gait has focused on single gait parameters such as gait speed, which seems to fall short for the complexity of this movement. Some approaches have proposed ways to identify gait patterns in specific patient groups (such as patients with hemiplegia), but not in community samples. Our goal was a) to identify gait patterns based on a combination of important gait parameters in a community sample, and b) to investigate differential associations of gain- and loss-related SPA with these gait patterns.Methods: The study used an electronic walkway to assess gait parameters of 150 community dwelling adults aged 71-93 years (61.0% women) at their usual and maximum gait speed. SPA were assessed with a questionnaire. We used latent profile analysis (LPA) to identify groups exhibiting distinct gait patterns and binary logistic regression to investigate associations of SPA with these groups, controlling for personality traits, number of illnesses, age, gender, and education. To compare overall function between groups, a t-test for scores in the Short Physical Performance Battery was used.Results: LPA revealed two distinct groups in both gait speed conditions. The fit group exhibited a stable, well-coordinated and faster gait pattern while the functionally limited group’s gait pattern was less stable, less coordinated and slower. The odds of belonging to the functionally limited group were increased by loss-related SPA at usual gait speed, while the odds of belonging to the fit group were increased by gain-related SPA at individual maximum speed. Conclusions: The findings a) suggest LPA as a useful approach to investigate complex gait patterns considering several gait parameters simultaneously, and b) provide first evidence for the differential role of gain- and loss-related SPA for gait patterns at usual and maximum gait speed. Intervention studies addressing gait in older adults should additionally address gain-related views on aging.Trial registration: NA

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