Jong-Il Park1,2, Tae Won Park1,2, Jong-Chul Yang1,2, Sang-Keun Chung1,2. 1. Department of Psychiatry, Chonbuk National University Medical School. 2. Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk National University Hospital, Jeonju, Republic of Korea.
Abstract
OBJECTIVES: The objective of this cross-sectional study was to investigate the relationship between depression in elderly individuals and chronic illness, subjective health status, and cognitive impairment. METHOD: This study used the dataset of the Survey of Living Conditions and Welfare Needs of Korean Older Persons, which was conducted by the Korea Institute for Health and Social Affairs in 2011. Participants (n = 10,674) were randomly selected from a pool of individuals aged 65 years and older. Elderly depression was evaluated by the short version of the Geriatric Depression Scale. Multivariate logistic regression was used to investigate factors associated with depression in terms of their sociodemographic and health-related characteristics. RESULTS: Our results revealed that chronic illness, subjective health status, and cognitive impairment were significant factors associated with depression. In particular, subjective health status showed the highest odds ratio (OR) (OR for bad subjective health status = 4.290, P < 0.001), followed by chronic illness (OR for three or more chronic illnesses = 1.403, P < 0.01) and cognitive impairment (OR = 1.347, P < 0.001) in the final model. Interestingly, the significant association between chronic illness and depression was attenuated (OR for three or more chronic illnesses = 1.403, P = 0.01) or even disappeared (OR for two chronic illnesses = 1.138, P = 0.274; OR for one chronic illnesses = 0.999, P = 0.996) after adjustment for subjective health status in the final model; this may be attributable to the close relationship among the variables studied: chronic illness, subjective health status, and depression. CONCLUSIONS: Development and implementation of prevention strategies, including management of chronic illness, individual's perception of health status, and cognitive impairment, could possibly reduce the impact of depression.
OBJECTIVES: The objective of this cross-sectional study was to investigate the relationship between depression in elderly individuals and chronic illness, subjective health status, and cognitive impairment. METHOD: This study used the dataset of the Survey of Living Conditions and Welfare Needs of Korean Older Persons, which was conducted by the Korea Institute for Health and Social Affairs in 2011. Participants (n = 10,674) were randomly selected from a pool of individuals aged 65 years and older. Elderly depression was evaluated by the short version of the Geriatric Depression Scale. Multivariate logistic regression was used to investigate factors associated with depression in terms of their sociodemographic and health-related characteristics. RESULTS: Our results revealed that chronic illness, subjective health status, and cognitive impairment were significant factors associated with depression. In particular, subjective health status showed the highest odds ratio (OR) (OR for bad subjective health status = 4.290, P < 0.001), followed by chronic illness (OR for three or more chronic illnesses = 1.403, P < 0.01) and cognitive impairment (OR = 1.347, P < 0.001) in the final model. Interestingly, the significant association between chronic illness and depression was attenuated (OR for three or more chronic illnesses = 1.403, P = 0.01) or even disappeared (OR for two chronic illnesses = 1.138, P = 0.274; OR for one chronic illnesses = 0.999, P = 0.996) after adjustment for subjective health status in the final model; this may be attributable to the close relationship among the variables studied: chronic illness, subjective health status, and depression. CONCLUSIONS: Development and implementation of prevention strategies, including management of chronic illness, individual's perception of health status, and cognitive impairment, could possibly reduce the impact of depression.
Authors: Mark B Snowden; Lesley E Steinman; Lucinda L Bryant; Monique M Cherrier; Kurt J Greenlund; Katherine H Leith; Cari Levy; Rebecca G Logsdon; Catherine Copeland; Mia Vogel; Lynda A Anderson; David C Atkins; Janice F Bell; Annette L Fitzpatrick Journal: Int J Geriatr Psychiatry Date: 2017-02-01 Impact factor: 3.485
Authors: Hye-Mi Noh; Junhee Han; Yeo Jin Kim; Jin-Hyung Jung; Yong Kyun Roh; Hong Ji Song Journal: Medicine (Baltimore) Date: 2019-03 Impact factor: 1.889