BACKGROUND: Although depressive symptoms in older adults are common, their relationship with disability and the influence of disability on the development of depressive symptoms over time is not well understood. This longitudinal study investigates the change trajectories of both depressive symptoms and disability, as well as their associations over time. METHODS: Participants included 442 community-dwelling older adults living in Taiwan, aged 65 years or older, who completed six waves of survey interviews. Depression was scored with the Short Psychiatric Evaluation Schedule and disability with the instrumental and physical activities of daily living measure during each consecutive data collection wave. The autoregressive latent trajectory model and parallel latent growth curve modeling were adopted for analysis of the data. RESULTS: The autoregressive latent trajectory model highlights that previous depressive symptoms (and disability) significantly contributed to the advancement of more severe depressive symptoms (and disability). This model also indicates that disability significantly contributed to the onset of depressive symptoms and vice versa. The parallel latent growth curve modeling highlights that the disability intercept had significant effects on the depressive symptoms intercept, as did the depressive symptoms on disability. Furthermore, the disability slope had significant effects on the slope of the depressive symptoms. CONCLUSIONS: These findings demonstrate that disability is a stronger predictor of depressive symptoms than depressive symptoms are of disability. In addition, the prior existence of a health condition will lead to further deterioration of health conditions and that they often coexist.
BACKGROUND: Although depressive symptoms in older adults are common, their relationship with disability and the influence of disability on the development of depressive symptoms over time is not well understood. This longitudinal study investigates the change trajectories of both depressive symptoms and disability, as well as their associations over time. METHODS:Participants included 442 community-dwelling older adults living in Taiwan, aged 65 years or older, who completed six waves of survey interviews. Depression was scored with the Short Psychiatric Evaluation Schedule and disability with the instrumental and physical activities of daily living measure during each consecutive data collection wave. The autoregressive latent trajectory model and parallel latent growth curve modeling were adopted for analysis of the data. RESULTS: The autoregressive latent trajectory model highlights that previous depressive symptoms (and disability) significantly contributed to the advancement of more severe depressive symptoms (and disability). This model also indicates that disability significantly contributed to the onset of depressive symptoms and vice versa. The parallel latent growth curve modeling highlights that the disability intercept had significant effects on the depressive symptoms intercept, as did the depressive symptoms on disability. Furthermore, the disability slope had significant effects on the slope of the depressive symptoms. CONCLUSIONS: These findings demonstrate that disability is a stronger predictor of depressive symptoms than depressive symptoms are of disability. In addition, the prior existence of a health condition will lead to further deterioration of health conditions and that they often coexist.
Authors: J Fernandes de Souza Barbosa; C Dos Santos Gomes; J Vilton Costa; T Ahmed; M V Zunzunegui; C-L Curcio; F Gomez; R Oliveira Guerra Journal: J Nutr Health Aging Date: 2018 Impact factor: 4.075
Authors: Stephen F Smagula; Charles F Reynolds; Sonia Ancoli-Israel; Elizabeth Barrett-Connor; Thuy-Tien Dam; Jan M Hughes-Austin; Misti Paudel; Susan Redline; Katie L Stone; Jane A Cauley Journal: J Gerontol B Psychol Sci Soc Sci Date: 2013-12-10 Impact factor: 4.077
Authors: Lisa C Barry; Pamela R Soulos; Terrence E Murphy; Stanislav V Kasl; Thomas M Gill Journal: J Gerontol A Biol Sci Med Sci Date: 2012-09-11 Impact factor: 6.053