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http://dx.doi.org/10.14367/kjhep.2017.34.1.25

The trajectory of depressive symptoms among the oldest-old: Focusing on gender difference  

Jeon, Hae-Sook (Kyungpook National University, Department of Social Welfare)
Publication Information
Korean Journal of Health Education and Promotion / v.34, no.1, 2017 , pp. 25-34 More about this Journal
Abstract
Objectives: Although the number of the oldest-old is rapidly increasing due to longevity, very little is known about the trajectory of depressive symptoms(DS) and its related factors among the oldest-old. Much less is known about whether the trajectory of DS differs by gender among the oldest-old. The current study aims (1) to estimate the trajectory of DS and (2) to examine whether the trajectory differs by gender among the oldest-old. Methods: Sample consists of 296 persons aged 85 and over who participated in the Korean Welfare Panel Study data. Data were processed using the latent growth curve modeling to estimate the trajectory and multi-group SEM to examine gender difference. Results: This study showed that (1) the trajectory of DS was increasing over time and (2) the DS trajectory of males was much more rapidly increasing than that of females, indicating male oldest old are more vulnerable to depression than female oldest old in later life. Conclusions: Given the fact that females are known to be more vulnerable to depression, the findings are counterintuitive to the previous knowledge on depression and gender difference. Based on the findings, implications for intervention and education related to DS among the oldest-old.
Keywords
oldest-old; trajectory of depressive synptoms; gender difference; latent grouth curve modeling;
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1 Blazer, D., Burchett, B., & George, L. K. (1991). The association of age and depression among the elderly: an epidemiologic exploration. Journal of gerontology, 46(6), M210-M215.   DOI
2 Dunkle & Jeon(2015). The oldest old. In D. Kaplan & B. Berkman (Eds.), The Oxford Handbook of Social Work in Health and Aging(431-442). Oxford University Press.
3 Enders, C. K., & Bandalos, D. L. (2001). The relative performance of full information maximum likelihood estimation for missing data in structural equation models, Structural Equation Modeling: A Multidisciplinary Journal, 8(3), pp.430-457.   DOI
4 Frederick, J. T., Steinman, L. E., Prohaska, T., Satariano, W. A., Bruce, M., Bryant, L., & Sharkey, J. (2007). Community-based treatment of late life depression. American Journal of Preventive Medicine, 33(3), 222-249.   DOI
5 Fung, H. H., Carstensen, L. L., & Lang, F. R. (2001). Age-related patterns in social networks among European Americans and African Americans. The International Journal of Aging and Human Development, 52(3), 185-206.   DOI
6 Hu, L. T., & Bentler, P. M. (1999) Cutoff criteria for fit indexes in covariance structure analysis. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), pp.1-55   DOI
7 Kahng, S. (2010). Does depression predict suicide? Korean Journal of Social Welfare Studies, 41(2), 67-99.   DOI
8 Karlin, B. E. & Norris, M. P. (2006). Public mental health care utilization by older adults. Administration and Policy in Mental Health and Mental Health Services Research, 33(6), 730-736.   DOI
9 Kahng, S., & Jeon, H. (2012). A Study on the predictors of depression improvement. Mental Health & Social Work, 40(3), 145-174.
10 Kang, E., & Choi, J. (2014). Multiple trajectories of depressive symptoms among older adults. Journal of Korean Gerontology Society, 34, 387-407.
11 Jeon, H. S., & Dunkle, R. E. (2009). Stress and depression among the oldest-old: A longitudinal analysis. Research on aging, 31, 661-687.   DOI
12 Jeon, H., & Kahng, S. (2009). Predictors of depression trajectory among the elderly. Korean Journal of Social Welfare Studies, 29, 1611-1628.
13 Jeon, H., & Kahng, S. (2013). An Exploratory study on the predictors of depression trajectory among individuals with disabilities. Journal of Rehabilitation Research, 17, 41-67.
14 Leach, L. S., Christensen, H., Mackinnon, A. J., Windsor, T. D., & Butterworth, P. (2008). Gender differences in depression and anxiety across the adult lifespan. Social psychiatry and psychiatric epidemiology, 43(12), 983-998.   DOI
15 Lee, H. (2013). Longitudinal changes in depression in older adults. Journal of Welfare for the Aged, 61, 291-318.
16 Lee, H., Kahng, S., & Lee, J. (2008). The effects of socioeconomic position and health behavior on geriatric depressive symptom. Korean Journal of Social Welfare Studies, 28, 1129-1145.
17 Lee, I. (2014). The effects of stressors and coping on depression of the oldest old. Health and Social Welfare Review, 34(4), 264-294.   DOI
18 Luppa, M., Heinrich, S., Angermeyer, M. C., Konig, H. H., & Riedel-Heller, S. G. (2007). Cost-of-illness studies of depression: a systematic review. Journal of Affective Disorders, 98(1), 29-43.   DOI
19 Ministry of Health and Welfare(2014). Research on the actual condition among older adults. http://kosis.kr/statHtml/statHtml.do?orgId=117&tblId=DT_11771_2011N043&vw_cd=MT_ZTITLE&list_id=117_11771_002_F&seqNo=&lang_mode=ko&language=kor&obj_var_id=&itm_id=&conn_path=E1
20 Menec, V. H., & Chipperfield, J. G. (1997). The interactive effect of perceived control and functional status on health and mortality among young-old and old-old adults. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 52(3), P118-P126.
21 Murray, C. J., & Lopez, A. D. (1996). The global burden of disease and injury series, volume 1. Cambridge. MA.
22 Nelson, E. A., & Dannefer, D. (1992). Aged heterogeneity: Fact or fiction? The fate of diversity in gerontological research. The Gerontologist, 32(1), 17-23.   DOI
23 Parker, G., & Brotchie, H. (2010). Gender differences in depression. International Review of Psychiatry, 22(5), 429-436.   DOI
24 Piccinelli, M., & Wilkinson, G. (2000). Gender differences in depression. The British Journal of Psychiatry, 177(6), 486-492.   DOI
25 Radloff, L. S. (1977). The CES-D scale a self-report depression scale for research in the general population. Applied psychological measurement, 1(3), pp.385-401.   DOI
26 Ross, C. E., & Mirowsky, J. (2006). Sex differences in the effect of education on depression. Social Science & Medicine, 63(5), 1400-1413.   DOI
27 Rybarczyk, B., Garroway, A. M., Auerbach, S. M., Rodriguez, V. M., Lord, B., & Sadock, E. (2013). Primary Care Psychology: An Opportunity for Closing the Gap in Mental Health Services for Older Adults. Clinical Gerontologist, 36(3), 195-215.   DOI
28 Sartorius, N. (2001). The economic and social burden of depression. Journal of Clinical Psychiatry, 62, 8-11.   DOI
29 Statistics Korea. (2016). Estimation of population. http://kosis.kr/
30 Shaw, B. A., & Krause, N. (2001). Exploring race variations in aging and personal control. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 56(2), S119-S124.   DOI
31 Statistics Korea. (2015). Statistics on cause of death. http://kosis.kr/statHtml/statHtml.do?orgId=101&tblId=DT_1B34E01&vw_cd=MT_ZTITLE&list_id=D11&seqNo=&lang_mode=ko&language=kor&obj_var_id=&itm_id=&conn_path=E1
32 Statistics Korea. (2012). Estimation of future population: 2010-2060. http://kosis.kr/statHtml/statHtml.do?orgId=101&tblId=DT_1B01001&vw_cd=MT_ZTITLE&list_id=A41_10_10&seqNo=&lang_mode=ko&language=kor&obj_var_id=&itm_id=&conn_path=E1
33 Stein, J., Pabst, A., Weyerer, S., Werle, J., Maier, W., Heilmann, K., & Mamone, S. (2016). The assessment of met and unmet care needs in the oldest old with and without depression using the Camberwell Assessment of Need for the Elderly (CANE). Journal of affective disorders, 193, 309-317.   DOI
34 Weissman, M. M., Bruce, M. L., Leaf, P. J., Florio, L. P., & Holzer, C. (1991). Affective disorders. Psychiatric Disorders in America, 53-80.
35 WHO(2013). Mental Health Action Plan 2013-2020.
36 WHO(2008). The Global Burden of Disease: 2004 Update. Geneva: WHO Press
37 Zunzunegui, M. V., Beland, F., Llacer, A., & Leon, V. (1998). Gender differences in depressive symptoms among Spanish elderly. Social Psychiatry and Psychiatric Epidemiology, 33(5), 195-205.   DOI