UCLA

Frailty, a public health challenge may be a significant issue among homeless and disenfranchised populations in urban and rural cities across the United States (U.S.). The purpose of this dissertation is to characterize frailty among a sample of 150 homeless men and women. The first manuscript developed a theoretical framework, the Frailty Framework among Homeless and Vulnerable Populations (FFHVP), based on previous models and empirical literature in order to guide two data based papers, namely correlates of frailty and to test a modified FFHVP in order to determine predictors using structural equation modeling (SEM). The second manuscript utilized descriptive, univariate, and multiple regressions to understand predictors. A Pearson (r) bivariate correlation revealed a weak relationship between frailty and being female (r =.230, p<.01). Significant moderate negative correlations were found between frailty and resilience (r = -.395, p<.01), social support (r = -.377, p<.01), and nutrition (r = -.652, p<.01). Further, Spearman rho (r) bivariate correlations revealed a moderate positive relationship between frailty and health care utilization (r =.444, p<.01). A stepwise backward linear regression analysis was conducted and in the final model, age, female gender, health care utilization, nutrition and resilience were significantly related to frailty. The multiple correlation squared was .542, indicating that 54.2% of the variance in frailty could be explained by the variables in the model. The third manuscript examined situational, behavioral, health-related and resource indicators in terms of their direct impact on frailty, hypothesized as a latent variable construct. Using SEM, a model was tested with 150 homeless men and women, ages 40 to 73. Except for age and drugs, all of the independent variables were significantly associated with frailty in the confirmatory factor analysis (CFA); these included months homeless (p<.01), female gender (p<.05), education (p<.05), comorbid conditions (p<.001), nutrition (p<.001), resilience (p<.001), health care utilization (p<.01), and falls (p<.001). In the final path model, significant predictors of frailty included educational attainment (p<.01), comorbid conditions (p<.001), nutrition (p<.001), resilience (p<.001), and falls (p<.01). However, age, gender, length of time homeless, health care utilization and drug use did not emerge as significant in the path model. These findings reframe concepts; specifically, physical, psychological and social frailty domains which investigators have been independently and collaboratively researching for decades with the ultimate goal of developing future nurse-led intervention initiatives.