Objectives: This study used latent growth curve modeling (LGCM) to estimate the independent and joint associations between frailty and depression trajectories and likelihood of nursing home admission and falls resulting in injury.
Methods: Data come from five waves (2004-2012) of the Health and Retirement Study. Community-dwelling individuals aged 51 and older (N = 13,495) were analyzed using LGCM. Frailty was measured using a frailty index consisting of 30 deficits. Depressive symptoms were measured using the eight-item Centers for Epidemiologic Studies - Depression scale. Adverse health outcomes included nursing home admissions and falls resulting in injury.
Results: Prevalence of frailty increased over the study period (24.1%-32.1%), while the prevalence of depression was relatively constant over time (approximately 13%). Parallel process LGCM showed that more rapid increases of frailty and depressive symptoms were associated with higher odds of both nursing home admission and serious falls over time (Frailty: ORNursinghome = 1.33, 95% CI: 1.09-1.66; ORFall = 1.52, 95% CI: 1.12-2.08; Depression: ORNursinghome = 3.63, 95% CI: 1.29-9.97; ORFall = 1.16, 95% CI: 1.01-1.34). Associations between frailty and adverse outcomes were attenuated, and in some cases were no longer statistically significant, after accounting for concurrent depression.
Conclusion: Frailty trajectories may be important indicators of risk for nursing home admissions and falls, independent of baseline frailty status; however, concurrent depression trajectories are associated with adverse outcomes to a similar degree as frailty. Focus should be given to distilling elements of the frailty index which confer most risk for poor health outcomes.
Keywords: depression; frailty; latent growth models.