Constructing and identifying predictors of frailty among homeless adults—a latent variable structural equations model approach.

Homeless urbanites are a heterogeneous population with unique health and social service needs. The study examined situational, behavioral, health-related and resource indicators in terms of their direct impact on frailty, hypothesized as a latent variable. Using structural equation modeling (SEM), a model was tested with 150 homeless men and women, ages 40–73, from three homeless day center drop-in sites on Skid Row and one residential drug treatment (RDT) facility that works with homeless parolees and probationers. In bivariate analyses with the latent construct frailty, months homeless (p < 0.01), female gender (p < 0.05), education (p < 0.05), comorbid conditions (p < 0.001), nutrition (p < 0.001), resilience (p < 0.001), health care utilization (p < 0.01), and falls (p < 0.001) were significantly associated with frailty. In the final path model, significant predictors of frailty included educational attainment (p < 0.01), comorbid conditions (p < 0.001), nutrition (p < 0.001), resilience (p < 0.001), and falls (p < 0.01). These findings will serve as a foundation for future nurse-led, community-based initiatives that focus on key predictors of frailty among the homeless and the development of interventions.