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Background and ObjectivesMore older adults with multimorbidity are aging in place than ever before. Knowing how the environment affects their mental well-being could enhance the efficacy of age-friendly interventions for multimorbidity resilience. With reference to the Transdisciplinary Neighborhood Health Framework, we construct and examine a priori models of environmental influences on life satisfaction and depressive symptoms.Research Design and MethodsBaseline and follow-up data (after 3 years) were drawn from the Canadian Longitudinal Study on Aging to identify a subsample (n = 14,301) of participants aged at least 65 years with at least 2 chronic diseases. Path analysis examined sociobehavioral attributes (i.e., social support, social participation, walking) and loneliness as primary and secondary mediators, controlling for age, sex, education, and outcomes during baseline.ResultsGood model fit was found (TFI = 1.00; CFI = 1.00; RMSEA < 0.001; SRMR < 0.001). The total effects of housing quality (rtotal = 0.08, −0.07) and neighborhood cohesion (rtotal = 0.03, −0.06) were weak but statistically significant in the expected direction. The mediators explained 21%–31% of the total effects of housing quality and 67%–100% of the total effects of neighborhood cohesion. Loneliness mediated 27%–29% of these environmental influences on mental well-being, whereas walking mediated a mere 0.4%–0.9% of the total effects. Walking did not explain the relationship between housing quality and mental well-being.Discussion and ImplicationsData supported a priori pathways from environment to mental well-being through sociobehavioral attributes and loneliness. If these pathways from neighborhood cohesion to life satisfaction reflect causal effects, community-based age-friendly interventions should focus on enhancing neighborhood cohesion to mitigate loneliness among multimorbid older adults for their mental well-being.
The Gerontologist – Oxford University Press
Published: Jan 16, 2022
Keywords: Age-friendly community; Multimorbidity; Neighborhood effects; Social cohesion; Structural equation modeling
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