Individual and environmental variables related to outdoor walking among older adults: Verifying a model to guide the design of interventions targeting outdoor walking

Abstract

Objective: To estimate the relationships between individual and environmental variables and outdoor walking (OW) in older adults with OW limitations through verifying a conceptual model.

Methods: Baseline data from 205 older adults participating in a randomized trial of a park-based OW program were analyzed using structural equation modeling. We evaluated a three latent factor model: OW (accelerometry and self-report); individual factors (balance; leg strength; walking self-confidence, speed and endurance; mental health; education; income; car access); and environmental factors (neighbourhood walkability components).

Results: Mean age was 75 years; 73% were women. Individual factors was significantly associated with OW (β = 0.39, p < .01). Environmental factors was not directly associated with OW but was indirectly linked to OW through its significant covariance with the individual factors (β = 0.22, p < .01). The standardized factor loadings from the individual factors on walking self-confidence and walking capacity measures exceeded 0.65.

Conclusions: Better walking capacity and more confidence in the ability to walk outdoors are associated with higher OW in older adults. Better neighbourhood walkability is indirectly associated with more OW. The conceptual model demonstrates an individual and environment association; if the capacity of the individual is increased (potentially through walking interventions), they may be able to better navigate environmental challenges.

Fig 1. Conceptual framework for the GO-OUT intervention.

Note: This figure is reprinted from the Fig 1 by Salbach NM, Barclay R, Webber SC, et al. A theory-based, task-oriented, outdoor walking programme for older adults with difficulty walking outdoors: protocol for the Getting Older Adults Outdoors (GO-OUT) randomised controlled trial. BMJ Open 2019;9:e029393. doi: 10.1136/bmjopen-2019-029393.

Fig 2. Initial structural equation model proposed based on the conceptual framework.

Fig 3. Modified measurement model for the individual factors.

Note: The format of factor loadings and covariances: standardized estimation (standard error) ^{significance level}. * p < .05; **.01 < p < .05; *** p < .001. The green color indicates a positive relationship while red indicates a negative relationship.

Fig 4. Modified measurement model for the environmental factors.

Note: The format of factor loadings and covariances: standardized estimation (standard error) ^{significance level}. * p < .05; **.01 < p < .05; *** p < .001. The green color indicates a positive relationship while red indicates a negative relationship. A: higher scores indicate higher density; E: higher scores indicate more infrastructure and safer neighborhood; F: higher scores indicate more aesthetically appealing neighborhood; G: higher scores indicate more traffic hazards; H: higher scores indicate higher crime rate and feeling of unsafe to walk in the neighborhood; I: higher scores indicate that parking is more difficult in local shopping areas; K: higher scores indicate that the streets in the neighborhood is more hilly; L: higher scores indicate more physical barriers to walking in the neighborhood; N: higher scores indicate more social interactions while walking in the neighborhood.

Fig 5. The SEM for outdoor walking.

Note: The format of factor loadings and covariances: standardized estimation (standard error) ^{significance level}; the format of path coefficients: unstandardized estimation (standard error) ^{significance level}. * p < .05; ** .01 < p < .05; *** p < .001. The green color indicates a positive relationship while red color indicates a negative relationship.