Depressive Symptom Trajectories and Associated Risks among Korean Elderly

IlSung Nam; Hyunsook Yoon

doi:10.15384/kjhp.2014.14.3.112

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Nam and Yoon: Depressive Symptom Trajectories and Associated Risks among Korean Elderly

Original Article

Korean J Health Promot 2014;14(3):112-120.

Published online: 20 January 2014

DOI: https://doi.org/10.15384/kjhp.2014.14.3.112

Depressive Symptom Trajectories and Associated Risks among Korean Elderly

IlSung Nam^1,, Hyunsook Yoon²

¹Hallym University Institute of Aging, Chuncheon, Korea

²Department of Social Welfare, Hallym University, Chuncheon, Korea

Corresponding author：IlSung Nam, PhD Hallym University Institute of Aging, 1 Hallimdaehak-gil, Chuncheon 200-702, Korea Tel: +82-33-248-3091, Fax: +82-33-248-3095 E-mail: ilsungn@gmail.com

Received 2 December 2013 Accepted 10 June 2014

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Recent studies conducting changes in depressive symptoms among the elderly reported mixed results. The present study sought to determine if subgroups of elderly Koreans follow distinctive depressive symptom trajectories and the characteristics associated with the depressive symptom trajectories.

Methods

Subjects were those who had participated in a longitudinal study of quality of life in older adults. A latent class mixture model was examined to identify the trajectories of depressive symptom changes with time.

Results

We found four depressive symptom trajectories. Poorer health status, poor economic status, and less social support were risk factors in the high depression group.

Conclusions

Early intervention to help elderly individuals manage their health, economic concerns, and social relationships may decrease the risk of high level depression.

Keywords: Elderly, Depression, Demographic factor

References

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Figure 1.

Four trajectories of depressive symptoms

Table 1.

Review of previous studies on depression trajectories in older adults

Author (year)	Sample (N)	Study duration, y	Depression measurement	Identified groups (%)	Risks associated with the trajectory groups
Andreescu C (2008)	Older adults aged above 65 (1,260)	12	CESD	Persisting depressive symptoms group (2)	Self-esteem,
				Remitting depressive symptoms group (4.8)	interpersonal
				Emerging depressive symptoms group (4.2)	difficulties,
				Stable low-depressed group (52.6)	health-related
				Stable asymptomatic group 1 (28.1)	worries
Byers AL (2012)	Older women aged above 65 (7,240)	20	GDS	Stable asymptomatic group 2 (8.2) Persistently high depressive symptoms (3.4)	Smoking, diabetes,
				Increasing depressive symptoms (14.8)	obesity,
				Persistently low depressive symptoms (54)	physical activities,
				Minimal depressive symptoms (27.8)	social network
Kuchibtatla MN (2012)	Older adults aged above 65 (4,162)	10	CESD	Depressed group (5.4)	Self-reported health,
				Improver group (10)	social network,
				Decliner group (8)	life stresses
				Not depressed (76.6)
Murphy BM (2008)	Women interviewed following acute	1	HADS	Depressed (16)	Loneliness, having a first
				Not depressed (84)	language other than
	myocardial				English
	infarction (226)
Taylor DH Jr (2008)	Dementia caregivers (1,580)	3	CESD	High depression group (30.22)	Education level,
				Moderate depression group (33.86)	income level,
				Low depression group (21.88)	quality of life
				Very low depression group (14.04)

Abbreviations: CESD, The center for epidemiologic studies depression scale; GDS, Geriatric depression scale; HADS, The hospital anxiety and depression scale.

Table 2.

Comparisons of depressive trajectories using demographic, health-related, social information^a,b

	Total	Low (Group 1)	Emerging	Decline	High	Group 1 vs.
	Total	Low (Group 1)	(Group 2)	(Group 3)	(Group 4)	Group 4
Demographic
Age, y	70.43±9.01	70.31±9.04	71.35±7.96	72.88±8.35	74.05±7.32	0.002
Sex
Male	632 (39.75)	626 (40.6)	37 (33.9)	29 (29)	7 (13.5)	<0.001
Female	958 (60.25)	916 (59.4)	72 (66.1)	71 (71)	45 (86.5)	<0.001
Education, y	5.89±4.96	5.98±4.95	4.18±4.25	3.69±4.82	3.19±4.41	0.002
Resident area
Seoul	621 (39.01)	594 (38.5)	17 (15.6)	38 (38)	31 (59.6)	0.002
Chuncheon	971 (60.99)	950 (61.5)	92 (84.4)	62 (62)	21 (40.4)	0.002
Resident area2
City	922 (57.91)	887 (57.4)	46 (42.2)	54 (54)	39 (75)	0.012
Rural	670 (42.09)	657 (42.6)	63 (57.8)	46 (46)	13 (25)	0.012
Widowed
Yes	621 (39.01)	593 (38.4)	40 (36.7)	53 (53)	31 (59.6)	0.002
No	971 (60.99)	951 (61.6)	69 (63.3)	47 (47)	21 (40.4)	0.002
Religion
Have	978 (61.43)	944 (61.1)	61 (56)	52 (52)	38 (73.1)	0.082
Does not have	614 (38.57)	600 (38.9)	48 (44)	48 (48)	14 (26.9)	0.082
Employed
Yes	1,131 (71.45)	443 (28.9)	33 (31.1)	12 (12.1)	9 (17.3)	0.069
No	452 (28.55)	1,092 (71.1)	73 (68.9)	87 (87.9)	43 (82.7)	0.069
Income, 10,000 Korean Won
0–99	643 (41.86)	610 (40.9)	60 (57.1)	56 (57.1)	36 (73.5)	<0.001
100–199	419 (27.28)	412 (27.6)	23 (21.9)	20 (20.4)	7 (13.3)	<0.001
≤200	474 (30.86)	469 (31.5)	22 (21.0)	22 (22.5)	6 (12.2)	<0.001
Saving, 10,000 Korean Won	29.46±85.22	29.95±86.19	32.83±53.80	24.30±60.16	13.83±41.59	0.016
Economic hardship	2.70±0.97	2.68±0.96	2.94±0.97	3.38±0.97	3.38±0.84	<0.001
Health-related
Self-reported	1.87±1.09	1.89±1.08	1.54±1.06	0.86±0.98	1.08±0.86	<0.001
Fall Experience
Yes	334 (20.98)	316 (20.5)	27 (24.8)	30 (30.0)	19 (36.5)	0.005
No	1,258 (79.02)	1,228 (79.5)	82 (75.2)	70 (70.0)	33 (63.5)	0.005
BMI Number of disease	24.07±3.69 1.99±1.72	24.06±3.70 1.93±1.69	24.85±5.07 2.56±1.98	23.12±4.30 3.01±2.03	24.32±3.38 3.51±2.01	0.603 <0.001
MMSE score	24.69±4.47	24.78±4.45	24.03±4.13	22.48±5.19	22.04±4.38	<0.001
Social-related
Number of social group	1.43±1.20	1.44±1.21	1.40±1.17	0.9±0.95	1.08±0.97	0.037
Social support	23.40±6.72	23.52±6.69	22.13±5.88	20.44±6.64	19.86±6.78	<0.001

Abbreviations: BMI, body mass index; MMSE, mini-mental state examination, SE, standard error.

^a Values are presented as mean±SE or N (%).

^b When comparing group differences chi-square test was used for the nominal variables, and t-test or Kruskal Wallis test was used for the continuous variable according to the normality test result.

Table 3.

Results of predicting the likelihood of falling in group 2, group 3, and group 4 compared to group 1^a

Model	Group 2				Group 3				Group 4
Model	B	SE	OR	P	B	SE	OR	P	B	SE	OR	P
1. Economic hardship	0.347	0.143	1.415	0.016	0.830	0.154	2.293	<0.001	0.590	0.369	1.804	0.004
2. Self-reported health	–0.388	0.126	0.678	0.002	–1.028	0.152	0.358	<0.001	–0.634	0.167	0.530	<0.001
3. Fall experience	–0.256	0.267	0.774	0.337	0.454	0.226	1.575	0.045	0.689	0.308	1.991	0.025
4. Number of diseases	0.161	0.075	1.175	0.032	0.274	0.054	1.315	<0.001	0.299	0.078	1.349	<0.001
5. MMSE score	–0.016	0.025	0.984	0.529	–0.077	0.021	0.926	<0.001	–0.072	0.030	0.930	0.015
6. Number of social groups	–0.078	0.107	0.925	0.461	–0.480	0.136	0.619	<0.001	–0.161	0.164	0.851	0.325
7. Social support	–0.019	0.017	0.981	0.251	–0.073	0.016	0.930	<0.001	–0.065	0.023	0.938	0.006

Abbreviations: SE, standard error; OR, odds ratio; MMSE, mini-mental state examination.

^a A series of logit models were run controlling for age, sex, education, resident areas, marital status, religion, employment, income, and BMI.

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