Gender differences in the association between multimorbidity and depression in older Korean adults: an analysis of data from the National Survey of Older Koreans (2011-2017)

SeoYeon Hwang; Jin Young Nam; Jeong Hyun Ahn; Soojin Park

doi:10.4178/epih.e2022049

Epidemiol Health > Volume 44; 2022 > Article

Hwang, Nam, Ahn, and Park: Gender differences in the association between multimorbidity and depression in older Korean adults: an analysis of data from the National Survey of Older Koreans (2011-2017)

Original Article

Epidemiol Health 2022; 44: e2022049.

Published online: May 24, 2022

DOI: https://doi.org/10.4178/epih.e2022049

Gender differences in the association between multimorbidity and depression in older Korean adults: an analysis of data from the National Survey of Older Koreans (2011-2017)

Department of Healthcare Management, Eulji University, Sungnam, Korea

Correspondence: Jin Young Nam Department of Healthcare Management, Eulji University, 553 Sanseongdae-ro, Sujeong-gu, Seongnam 13135, Korea E-mail: jynam@eulji.ac.kr

Received Nov 19, 2021 Accepted May 24, 2022

This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

OBJECTIVES

Previous studies have shown that people with multimorbidity have a higher risk of depression than those without multimorbidity. However, few studies have examined the association between depression and multimorbidity in men and women separately. Since the rates of depression and multimorbidity are different in men and women, it is necessary to examine whether gender differences affect their association.

METHODS

This study included 30,138 participants (aged ≥ 65 years) from the National Survey of Older Koreans (2011-2017). Depression was defined using the Korean version of the Geriatric Depression Scale (SGDS-K). Multimorbidity was defined as people who had 2 or more chronic diseases, including arthritis, diabetes, heart disease, hypertension, pulmonary disease, cancer, stroke, or osteoporosis. Multiple logistic regression analysis was performed to determine the association between depression and multimorbidity.

RESULTS

In total, 22.2% and 30.7% of men and women, respectively, had depression. Those with multimorbidity had a higher risk of depression than those without chronic conditions; specifically, the difference in risk among men was greater than that among women. Age was considered a moderator for women. While the effects of pulmonary disease, stroke, and cancer were especially substantial in the integrated analysis, gender differences were observed related to various chronic conditions comorbid with heart disease.

CONCLUSIONS

There are gender differences in the association between multimorbidity and depression among older Korean adults. Therefore, gender-specific care should be provided to reduce depression in older adults with multimorbidity.

KEY WORDS: Depression, Multimorbidity, Gender differences, Comorbidity

INTRODUCTION

Depression in older adults is a common psychiatric disorder that diminishes their quality of life [1]. Depression should not be considered a typical side effect of aging, even if it occurs frequently. Depression tends to worsen with age [2] and can cause mortality by suicide or medical illnesses [3]. Factors known to be related to depression in older adults include gender (women in particular), chronic somatic illnesses, disability, poor social support, and bereavement [4-6].

Multimorbidity, which refers to the presence of 2 or more chronic diseases in an individual, is also associated with depression [7]. The presence of multimorbidity increases steadily with age [8,9]; accordingly, the number of patients with multimorbidity is growing rapidly as aging increases worldwide [10]. Moreover, multimorbidity elevates the risk of death, disability, poor quality of life, hospitalization, and instrumentalization [11,12]. For these reasons, the U.S. Department of Health and Human Services has called for researchers to focus on multimorbidity rather than on individual chronic conditions given the powerful effects of multimorbidity on individuals’ lives [13].

The association between depression and multimorbidity has been examined in many studies. A meta-analysis of 40 studies found that people with multimorbidity had a 2 times higher risk of depression than those with 1 chronic disease and approximately a 3 times higher risk of depression than those without any chronic diseases [14]. However, a recent longitudinal study of 2,002 community-dwelling older people from Canada, Brazil, Colombia, and Albania found that multimorbidity was not a risk factor for depression regardless of cultural differences [15]. In response to these conflicting results, this study examined the association between depression and multimorbidity in older Korean adults.

Furthermore, although gender differences related to depression and multimorbidity have been observed separately, few studies have examined gender differences related to the association between depression and multimorbidity together. In an epidemiological study of gender differences in depression among older adults, 69 (81%) out of 85 reports found that women were more likely to be depressed than men [16]. The proportion of women with multimorbidity is also higher than that of men [17]. Moreover, gender differences have been observed in terms of the types of common comorbid chronic conditions affecting men and women (men: hypertension with cancer and/or arrhythmia; women: hypertension with arthritis and/or hyperlipidemia) [18]. Gender differences related to depression and multimorbidity, therefore, are likely to be reflected in their association; this possibility should not be overlooked.

In this study, we examined the association between depression and multimorbidity with stratification by gender. Furthermore, we examined which combinations of chronic conditions had the most substantial effects on depression in men and women.

MATERIALS AND METHODS

Database and study population

The National Survey of Older Koreans (NSOK) is a nationally representative, cross-sectional survey conducted by the Korea Institute for Health and Social Affairs. These data contain information on the living conditions, needs, and characteristics of older Koreans and, per legislative requirements, they have been collected every 3 years since 2008 [19]. We restricted the analysis to the 2011-2017 NSOK dataset since previous data did not include information about exercise habits and insurance type, which were covariates in this study.

Among the 31,744 respondents, we excluded participants diagnosed with depression (n=979) and who answered “preschool children under 10 years of age” to the question about education level (n=1). Additionally, we excluded participants who had missing values for depression score (n = 453), frequency of contact (n=270), exercise time (n=2), and frequency of drinking (n=1). As a result, the total sample included in this study contained 30,138 participants.

Depression

Depression was measured using the Korean version of the shortform Geriatric Depression Scale (SGDS-K). The SGDS-K comprises 15 items to identify depression symptoms experienced during the previous week. Five of these items are scored from 0 (yes) to 1 (no), and the remaining items are reverse-scored. Total possible scores range from 0 to 15. A higher score indicates more depressive symptoms, and according to the tool’s developer [20], a score of 8 or above indicates depression.

Multimorbidity

The NSOK surveys 32 chronic diseases, but only 8 were considered in this study: arthritis, diabetes mellitus, heart disease (angina pectoris, myocardial infarction, other heart problems), hypertension, pulmonary disease (chronic bronchitis, emphysema, asthma), cancer, stroke, and osteoporosis. The criteria for choosing diseases were determined based on a previous study [15]. All diseases were self-reported by participants who had been diagnosed by a doctor at least 3 months prior to the survey. Participants were considered to have multimorbidity if they had more than 2 of the 8 chronic diseases simultaneously.

Covariates

We considered the factors that could potentially confound the association between multimorbidity and depression. The covariates were as follows: gender (men, women), age (65-69, 70-74, 75-79, ≥ 80 years), marital status (married, single/divorced/separated/widowed), living arrangement (living alone, living with someone), education level (≤ primary school, middle school, high school, ≥ college), insurance type (National Health Insurance, Medical Aid), current smoking, lack of exercise, high-risk alcohol drinking, restrictions on activities of daily living (ADL), frequency of contact with people (hardly ever, at least once per year), other chronic conditions, and year.

In the NSOK data, several factors indicated socioeconomic status, including household income and insurance type. When household income was included as a covariate, as in other studies, the 95% confidence interval (CI) corresponding to the frequency of the contact variable was significant but abnormally wide. Based on evidence suggesting that insurance type affects depression among older adults [21], we included insurance type as a covariate instead of household income.

Health behaviors such as smoking, lack of exercise, and high-risk alcohol drinking were assessed based on whether they currently smoked, exercised more than 150 minutes per week, and consumed ≥ 7 (men) or ≥ 5 (women) drinks in a 2-week period [22]. When setting the standard for lack of exercise, since the frequency of exercise in the 2011 NSOK was recorded on a monthly basis, we divided the totals by 4 to measure this parameter in terms of weeks.

A previous study [15] designated the degree of assistance needed as a covariate based on a report [14] that found that older adults living in residential care facilities tended to feel more depressed than community-dwelling older adults. However, we used restrictions on ADL as a covariate instead of the degree of assistance needed since it included those who did not receive formal assistance despite difficulties with ADL. Restrictions on ADL were determined based on whether the respondent answered that he or she needed partial or complete assistance at least once to questions about ADL and instrumental ADL. This study also controlled for social support that negatively affected depression and multimorbidity [23] based on whether the participants had contact with family, friends, or acquaintances at least once in the past year.

In addition to the 8 chronic conditions that were assessed for multimorbidity, any other chronic conditions were assessed by grouping them into a single variable [24]. Since individuals’ living habits changed over time, chronic conditions surveyed on a yearly basis were continually added, and these additional chronic conditions could also affect depression.

Statistical analysis

In the primary analyses, we investigated the association between depression and multimorbidity. First, we examined the frequency of participants’ characteristics related to depression. The p-values, which were calculated using the chi-square test, were considered to indicate statistical significance when below 0.05. Multiple logistic regression was performed to estimate the odds ratios (ORs) and 95% CIs for the effect of multimorbidity on depression. Moreover, we conducted subgroup analysis by characteristics (gender, age, marital status, living arrangement, education, insurance type, current smoking, lack of exercise, high-risk alcohol drinking, restrictions on ADL, frequency of contact, and presence of other chronic conditions) and tested for interaction effects. In the secondary analyses, we examined the association between depression and combinations of chronic conditions. First, we examined the number of chronic conditions (ranging from 0 to 8) and their associations with depression. Then, we tested various combinations of the 8 chronic conditions (arthritis, diabetes, heart disease, hypertension, pulmonary disease, cancer, stroke, and osteoporosis) to determine which combinations were most closely associated with depression.

Ethics statement

All participants in this study were protected according to the tenets of the Declaration of Helsinki. The NSOK was approved by the National Statistical Office (approval No. 11771) before each survey was conducted. In 2013, it became mandatory to establish an institutional review board (IRB) under the Bioethics and Safety Act, and the 2017 NSOK was approved by the IRB of the Korean Institute for Health and Social Affairs (IRB No.17-034-00). All participants provided informed consent before enrollment, and all participants’ records were anonymously provided to researchers who agreed to comply with the management rules.

RESULTS

The participants’ general characteristics are reported in Table 1. The results show that 37.3% of men and 59.2% of women reported multimorbidity. Of them, 31.0% of men and 36.2% of women experienced depression.

Table 2 shows the associations between depression and the participants’ characteristics. In both men and women, those with multimorbidity had a higher risk of depression than those without chronic conditions (men: OR, 2.13; 95% CI, 1.88 to 2.42; women: OR, 1.90; 95% CI, 1.68 to 2.15). The difference in risk among men was greater than the difference in risk among women. Additionally, a greater number of chronic conditions corresponded to a higher risk of depression in men than in women (Supplementary Material 1).

Table 3 presents the stratified analyses according to age and other chronic conditions. Young-old women with multimorbidity had higher levels of depression than old-old women. However, no interaction effect was observed in men. Individuals who reported having any of the 8 chronic conditions had higher levels of depression than their counterparts among both men and women. The results are presented in Supplementary Material 2.

We also examined comorbidities with the 8 chronic conditions and their associations with depression (Table 4). For single chronic conditions, there was a significant association, in descending order, between depression and cancer, stroke, pulmonary disease, arthritis, diabetes, and heart disease. For multimorbidity, combinations that included pulmonary disease, stroke, or cancer were associated with a high level of depression. The results are shown in Supplementary Material 3.

Gender differences related to comorbid chronic conditions were observed (Supplementary Material 4). Among the individual chronic conditions, diabetes (men: OR, 1.16; 95% CI, 0.85 to 1.58; women: OR, 1.67; 95% CI, 1.25 to 2.24) and heart disease (men: OR, 1.14; 95% CI, 0.83 to 1.58; women: OR, 1.74; 95% CI, 1.24 to 2.46) were associated with depression in women only, while pulmonary disease (men: OR, 1.94; 95% CI, 1.41 to 2.68; women: OR, 1.30; 95% CI, 0.78 to 2.18) and osteoporosis (men: OR, 2.53; 95% CI, 1.34 to 4.77; women: OR, 1.02; 95% CI, 0.78 to 1.34) were associated with depression in men only. For multimorbidity, the association between heart disease and depression differed between men and women based on the number of comorbid chronic conditions.

DISCUSSION

Among the 30,138 older Korean adults, multimorbidity was associated with a high-risk of depression. Moreover, the effects of multimorbidity differed by gender. Compared to older Korean adults with no chronic conditions, men with multimorbidity had a 2.1-fold higher risk, and women with multimorbidity had a 1.9-fold higher risk of depression. Surprisingly, multimorbidity, compared to having no chronic conditions, corresponded to a higher risk of depression in men than in women. This is inconsistent with previous studies that found that women were more likely to have more chronic conditions [17,25] and a higher risk of depression than men [16].

Subgroup analysis revealed an interaction effect related to age. In particular, age moderated the association between multimorbidity and depression in women. In particular, older women with multimorbidity had a higher risk of depression than those without chronic conditions. However, young-old women with multimorbidity had a greater risk of depression than old-old women with multimorbidity. This differed from the results of a previous study that found that older people are at a higher risk of depression after examining only the association between depression and age. The reason for this result may be the effect of age on the association between self-rated health (SRH) and depression. According to a previous study [26], the effect of SRH on depressive symptoms was stronger among those aged 65-79 years compared to those aged 80 years or older. One explanation is that old-old people tend to cognitively adapt to changes in their health. They tend to compare their health to that of others their age, and since most older people experience many chronic conditions as they get older, they can more positively accept changes in health status, such as the number of chronic conditions, compared to young-old people [27,28]. A secondary explanation may be that young-old people consider their health to be their functional status, reflecting their ability to participate in different activities [29]. Therefore, young-old people can react sensitively to changes in health, which can lead to depressive symptoms. For these reasons, mental health care among young-old people with multimorbidity must be monitored closely.

In our secondary analyses, we found a positive association between depression and the number of chronic conditions. The frequency of the same number of chronic conditions was higher among women than among men, and depression compared to frequency was higher for men than for women, indicating the presence of gender differences.

Analyses of specific comorbid chronic conditions associated with depression were conducted both overall and after stratifying by gender. The most important finding in this analysis was the independent effect of pulmonary disease on depression. A previous study [30] in which 5 chronic conditions were combined suggested that people with only pulmonary disease were not at risk for depression compared to those with other chronic conditions. Unexpectedly, in our study, individuals diagnosed with only pulmonary disease reported the third-highest depression level (OR, 1.76) among the 8 chronic conditions. Consistent with these findings, combinations that included pulmonary disease (e.g., pulmonary disease-stroke, diabetes-pulmonary disease, hypertension-pulmonary disease-cancer, diabetes-hypertension-pulmonary disease-cancer) were associated with a high risk of depression. Our study showed that people with ADL restrictions had a greater risk of depression. In previous studies, pulmonary diseases such as chronic obstructive pulmonary disease and chronic bronchitis were found to restrict ADL [31]. In addition, asthma is highly associated with depression in individuals [32]. Thus, improving ADL was a mediator for the association between asthma and depression [32].

Our findings on comorbidities involving stroke were also significant. Individuals with a history of stroke had a 2.81 times higher likelihood of depression than those without chronic conditions, which was the second-highest level of depression among the 8 chronic conditions. In addition, combinations of pulmonary disease with stroke, diabetes with stroke, and arthritis with stroke had the highest risks of depression among the other 2-disease combinations. Depression is more common in stroke patients than in people with similar physical disabilities caused by orthopedic diseases such as severe arthritis [33]. A previous study found that people with stroke had to improve their ADL for treatment through initiatives such as “plan, do, check, and action” nursing [34]. According to this study, stroke affected the limits of an individual’s ADL [34]. In addition, many studies have shown that improved ADL has a preventive effect on depression [32,35].

The strong effect of cancer on depression must also be emphasized. The independent effect of cancer on depression showed the highest risk (OR, 3.04) among the 8 chronic conditions. Cancer is a life-threatening disease [36]; thus, a cancer diagnosis can cause a greater sense of distress than non-neoplastic diseases with poorer prognoses in patients [37], and mental distress in cancer patients experienced for sustained periods of time may lead to depression [38]. One study found an increased number of comorbidities to be associated with a higher level of depression among older adults with cancer [39]. However, in this study, some combinations of conditions (such as arthritis and cancer; heart disease and cancer; hypertension and cancer; and arthritis, hypertension, and cancer) had weaker associations with depression than in patients with cancer only. Therefore, cancer patients should be treated based on the expected risk of depression associated with their chronic conditions in addition to cancer rather than simply based on a patient’s total number of comorbidities.

The analysis of gender differences yielded results that contradicted the widespread assumption in the medical field that morbidity related to heart disease is more common among men and morbidity related to osteoporosis is more common among women. Based on this set of assumptions, most past studies of osteoporosis have focused on postmenopausal women. However, according to an innovative study that explored differences according to gender, morbidity and mortality related to major osteoporosis fractures were significantly higher among men than among women [40]. Concerning heart disease, women were found to have a worse prognosis than men [41]. These results could also be associated with mental health.

Another gender difference was observed in the effect of heart disease on depression. Gender differences were observed related to the number of chronic conditions. In women, heart disease was found to have an effect on depression when accompanied by 1 or 2 chronic conditions. Heart disease also had a significant independent effect on depression in women. In addition, the combination of heart disease and pulmonary disease had the strongest association with depression among all other possible comorbidities related to either condition. However, when women had 3 or more chronic conditions, combinations that included cancer, stroke, and osteoporosis (e.g., arthritis, cancer, and osteoporosis, or arthritis, diabetes, stroke, and osteoporosis) were associated with higher levels of depression. In contrast, in men, the effects of heart disease on depression were observed when they had 3 or more chronic conditions. Heart disease did not independently affect depression in men like it did with diabetes and hypertension. However, when men had 3 or more chronic conditions, combinations that included heart disease (e.g., diabetes, heart disease, and pulmonary disease; or heart disease, hypertension, pulmonary disease, and stroke) significantly increased the risk of depression. Older adults with heart disease may become depressed due to a fear of death [42], and women with heart disease actually have a higher mortality rate than men with heart disease [43]. Therefore, unlike in men, depression can be assumed to have a stronger association with heart disease in women even without additional comorbidities.

This study had several limitations. The sample was too small to yield significant results on the association between depression and different comorbid chronic conditions. Although all individuals with particular combinations of conditions (such as arthritis–heart disease–cancer–osteoporosis, diabetes–stroke–osteoporosis) had symptoms of depression, the results were insignificant due to the small sample size. Thus, other comorbid chronic conditions that might have a great impact on depression could not be considered. Second, depression may have been underestimated since people who had been diagnosed with depression were excluded from the study. Third, we determined the presence of chronic conditions using self-reports. This method can underrepresent the number of people affected by chronic conditions that they inadvertently overlooked or had not been diagnosed with by a doctor, such as hypertension and diabetes [44]. Fourth, we could not evaluate the effect of other chronic conditions (such as chronic obstructive pulmonary disease) known to be associated with depression [45] since the types of chronic conditions investigated were restricted. Fifth, in previous studies, in addition to the number of chronic conditions, the severity of chronic conditions also affected depression [46-48]. The severity of chronic conditions such as asthma, stroke, and diabetes increases the risk of depression [46-48]. However, the severity of chronic conditions was not analyzed in this study. Thus, this should be included in future studies for accurate analyses. Finally, the cross-sectional data only measured the prevalence of depression and did not determine the onset of depression. Therefore, a causal association cannot be determined. However, we excluded those who had previously been diagnosed with depression. Therefore, the results indicated that multimorbidity might increase depression. In other words, although we found that chronic disease diagnoses were associated with elevated levels of depression, the diagnoses could not be determined to have caused elevated depression [24].

Despite the aforementioned limitations, this study has several strengths. First, to the best of our knowledge, this is the first study to analyze comorbid chronic conditions using the multimorbidity index from previous studies [30,49] and complements the extant body of literature that included only a small number of chronic conditions. Although a previous study [15] examined the association between multimorbidity and depression in terms of the same 8 chronic conditions included in this study, it did not evaluate different combinations of these conditions. Second, the effects of gender were not overlooked since men and women were classified and analyzed separately. Numerous studies have examined the impact of gender on multimorbidity and depression, but few have investigated how the association between multimorbidity and depression differs by gender.

In conclusion, we found that multimorbidity, and specifically the number of chronic conditions, were strongly associated with depression in older Korean adults. In addition, men with multimorbidity reported higher levels of depression than women with multimorbidity. Gender differences were also observed in terms of comorbid chronic conditions. Using the present study as a stepping stone, future studies can accurately interpret patients’ depression levels based on combinations of chronic conditions. Based on our findings, gender-specific prevention methods should be used to provide treatment to individuals with multimorbidity who experience depressive symptoms.

SUPPLEMENTARY MATERIALS

Supplementary materials are available at https://www.e-epih.org/.

Supplementary Material 1.

Depression based on the number of chronic conditions by gender

epih-44-e2022049-suppl1.docx

Supplementary Material 2.

A subgroup analysis of the association between depression and multimorbidity

epih-44-e2022049-suppl2.docx

Supplementary Material 3.

The association between chronic conditions combinations and depression

epih-44-e2022049-suppl3.docx

Supplementary Material 4.

The association between chronic conditions combinations and depression by gender

epih-44-e2022049-suppl4.docx

NOTES

CONFLICT OF INTEREST

The authors have no conflicts of interest to declare for this study.

FUNDING

None.

AUTHOR CONTRIBUTIONS

Conceptualization: Hwang SY, Nam JY, Park S. Data curation: Hwang SY. Formal analysis: Hwang SY. Funding acquisition: None. Methodology: Hwang SY, Nam JY, Park S. Project administration: Nam JY. Visualization: Hwang SY. Writing – original draft: Hwang SY. Writing – review & editing: Hwang SY, Nam JY, Ahn JH, Park S.

ACKNOWLEDGEMENTS

None.

Table 1.

General characteristics of study participants according to depression by gender

Characteristics		Total (n=30,138)			p-value	Men (n=12,298)			p-value	Women (n=17,840)			p-value
Characteristics		No	Yes	Total, %	p-value	No	Yes	Total, %	p-value	No	Yes	Total, %	p-value
No. of chronic conditions
	0	4,663 (84.4)	860 (15.6)	18.3	<0.001	2,805 (86.1)	454 (13.9)	26.5	<0.001	1,858 (82.1)	406 (17.9)	12.7	<0.001
	1	7,375 (77.9)	2,089 (22.1)	31.4		3,600 (81.0)	847 (19.1)	36.2		3,775 (75.2)	1,242 (24.8)	28.1
	≥2	9,902 (65.4)	5,249 (34.6)	50.3		3,167 (69.0)	1,425 (31.0)	37.3		6,735 (63.8)	3,824 (36.2)	59.2
Gender
	Men	9,572 (77.8)	2,726 (22.2)	40.8	<0.001	-	-	-	-	-	-	-	-
	Women	12,368 (69.3)	5,472 (30.7)	59.2		-	-	-		-	-	-
Age (yr)
	65-69	6,298 (81.4)	1,443 (18.6)	25.7	<0.001	2,729 (84.0)	521 (16.0)	26.4	<0.001	3,569 (79.5)	922 (20.5)	25.2	<0.001
	70-74	6,637 (75.3)	2,173 (24.7)	29.2		2,991 (80.0)	748 (20.0)	30.4		3,646 (71.9)	1,425 (28.1)	28.4
	75-79	5,270 (69.0)	2,367 (31.0)	25.3		2,342 (75.1)	777 (24.9)	28.4		2,928 (64.8)	1,590 (35.2)	25.3
	≥80	3,735 (62.8)	2,215 (37.2)	19.7		1,510 (69.0)	680 (31.1)	17.8		2,225 (59.2)	1,535 (40.8)	21.1
Marital status
	Single, divorced, separated, or widowed	7,340 (64.6)	4,028 (35.4)	37.7	<0.001	1,053 (67.4)	509 (32.6)	12.7	<0.001	6,287 (64.1)	3,519 (35.9)	55.0	<0.001
	Married	14,600 (77.8)	4,170 (22.2)	62.3		8,519 (79.4)	2,217 (20.7)	87.3		6,081 (75.7)	1,953 (24.3)	45.0
Living arrangement
	Living alone	4,745 (64.2)	2,648 (35.8)	24.5	<0.001	778 (66.4)	393 (33.6)	9.5	<0.001	3,967 (63.8)	2,255 (36.2)	34.9	<0.001
	Living with someone	17,195 (75.6)	5,550 (24.4)	75.5		8,794 (79.0)	2,333 (21.0)	90.5		8,401 (72.3)	3,217 (27.7)	65.1
Education level
	≤Primary school	13,600 (67.5)	6,535 (32.5)	66.8	<0.001	4,143 (71.6)	1,643 (28.4)	47.1	<0.001	9,457 (65.9)	4,892 (34.1)	80.4	<0.001
	Middle school	3,285 (80.9)	778 (19.2)	13.5		1,856 (80.4)	454 (19.7)	18.8		1,429 (81.5)	324 (18.5)	9.8
	High school	3,435 (83.3)	688 (16.7)	13.7		2,300 (83.1)	468 (16.9)	22.5		1,135 (83.8)	220 (16.2)	7.6
	≥College	1,620 (89.2)	197 (10.8)	6.0		1,273 (88.8)	161 (11.2)	11.7		347 (90.6)	36 (9.4)	2.2
Insurance type
	National Health Insurance	20,872 (74.6)	7,091 (25.4)	92.8	<0.001	9,226 (79.4)	2,396 (20.6)	94.5	<0.001	11,646 (71.3)	4,695 (28.7)	91.6	<0.001
	Medical Aid	1,068 (49.1)	1,107 (50.9)	7.2		346 (51.2)	330 (48.8)	5.5		722 (48.2)	777 (51.8)	8.4
Current smoking
	No	19,539 (73.0)	7,221 (27.0)	88.8	0.017	7,501 (78.8)	2,018 (21.2)	77.4	<0.001	12,038 (69.8)	5,203 (30.2)	96.6	<0.001
	Yes	2,401 (71.1)	977 (28.9)	11.2		2,071 (74.5)	708 (25.5)	22.6		330 (55.1)	269 (44.9)	3.4
Lack of exercise
	No	10,405 (82.1)	2,276 (18.0)	42.1	<0.001	5,281 (85.0)	932 (15.0)	50.5	<0.001	5,124 (79.2)	1,344 (20.8)	36.3	<0.001
	Yes	11,535 (66.1)	5,922 (33.9)	57.9		4,291 (70.5)	1,794 (29.5)	49.5		7,244 (63.7)	4,128 (36.3)	63.7
High-risk alcohol drinking
	No	20,635 (72.3)	7,899 (27.7)	94.7	<0.001	8,314 (77.2)	2,450 (22.8)	87.5	<0.001	12,321 (69.3)	5,449 (30.7)	99.6	0.691
	Yes	1,305 (81.4)	299 (18.6)	5.3		1,258 (82.0)	276 (18.0)	12.5		47 (67.1)	23 (32.9)	0.4
Restriction on activities of daily living
	No	19,032 (77.9)	5,395 (22.1)	81.1	<0.001	8,868 (81.9)	1,962 (18.1)	88.1	<0.001	10,164 (74.8)	3,433 (25.3)	76.2	<0.001
	Yes	2,908 (50.9)	2,803 (49.1)	19.0		704 (48.0)	764 (52.0)	11.9		2,204 (51.9)	2,039 (48.1)	23.8
Frequency of contact with people
	Hardly ever	13 (33.3)	26 (66.7)	0.1	<0.001	8 (40.0)	12 (60.0)	0.2	<0.001	5 (26.3)	14 (73.7)	0.1	<0.001
	At least once	21,927 (72.9)	8,172 (27.2)	99.9		9,564 (77.9)	2,714 (22.1)	99.8		12,363 (69.4)	5,458 (30.6)	99.9
Other chronic conditions¹
	No	9,100 (79.7)	2,317 (20.3)	37.9	<0.001	4,441 (83.7)	865 (16.3)	43.2	<0.001	4,659 (76.2)	1,452 (23.8)	34.3	<0.001
	Yes	12,840 (68.6)	5,881 (31.4)	62.1		5,131 (73.4)	1,861 (26.6)	56.9		7,709 (65.7)	4,020 (34.3)	65.8
Year
	2011	7,331 (70.1)	3,127 (29.9)	34.7	<0.001	3,186 (75.6)	1,030 (24.4)	34.3	<0.001	4,145 (66.4)	2,097 (33.6)	35.0	<0.001
	2014	6,826 (68.9)	3,089 (31.2)	32.9		3,089 (75.0)	1,029 (25.0)	33.5		3,737 (64.5)	2,060 (35.5)	32.5
	2017	7,783 (79.7)	1,982 (20.3)	32.4		3,297 (83.2)	667 (16.8)	32.2		4,486 (77.3)	1,315 (22.7)	32.5

Values are presented as number (%).

¹ Other chronic conditions: hyperlipidemia, thyroid disease, low back pain, sciatica, pulmonary tuberculosis, tuberculosis, cataract, glaucoma, chronic otitis media, stomach ulcer, duodenal ulcer, hepatitis, liver cirrhosis, chronic kidney disease, prostatic hypertrophy, urinary incontinence, venereal disease, anemia, skin disease, dementia, fracture, dislocation, sequela, insomnia, Parkinson’s disease, and others.

Table 2.

The associations between depression and the characteristics of study participants by gender¹

Variable		Men	Women
No. of chronic conditions
	0	1.00 (reference)	1.00 (reference)
	1	1.32 (1.15, 1.50)	1.30 (1.14, 1.48)
	≥2	2.13 (1.88, 2.42)	1.90 (1.68, 2.15)
	p for trend	<0.001	<0.001
Age (yr)
	65-69	1.00 (reference)	1.00 (reference)
	70-74	1.13 (0.99, 1.29)	1.18 (1.07, 1.31)
	75-79	1.39 (1.22, 1.59)	1.37 (1.23, 1.52)
	≥80	1.42 (1.23, 1.65)	1.39 (1.24, 1.55)
	p for trend	<0.001	<0.001
Marital status
	Single, divorced, separated, or widowed	1.27 (1.01, 1.60)	1.17 (1.07, 1.29)
	Married	1.00 (reference)	1.00 (reference)
Living arrangement
	Living alone	1.36 (1.05, 1.76)	1.09 (0.99, 1.19)
	Living with someone	1.00 (reference)	1.00 (reference)
Education level
	≤Primary school	2.30 (1.91, 2.77)	3.20 (2.23, 4.60)
	Middle school	1.77 (1.44, 2.18)	2.16 (1.48, 3.17)
	High school	1.56 (1.28, 1.92)	1.92 (1.30, 2.84)
	≥College	1.00 (reference)	1.00 (reference)
Insurance type
	National Health Insurance	1.00 (reference)	1.00 (reference)
	Medical Aid	2.50 (2.10, 2.99)	2.11 (1.88, 2.37)
Current smoking
	No	1.00 (reference)	1.00 (reference)
	Yes	1.26 (1.13, 1.41)	1.59 (1.33, 1.90)
Lack of exercise
	No	1.00 (reference)	1.00 (reference)
	Yes	1.83 (1.66, 2.02)	1.70 (1.57, 1.83)
High-risk alcohol drinking
	No	1.00 (reference)	1.00 (reference)
	Yes	0.84 (0.72, 0.97)	1.14 (0.67, 1.93)
Restriction on activities of daily living
	No	1.00 (reference)	1.00 (reference)
	Yes	3.54 (3.12, 4.02)	2.30 (2.12, 2.50)
Frequency of contact with people
	Hardly ever	2.99 (1.11, 8.06)	2.79 (0.94, 8.26)
	At least once	1.00 (reference)	1.00 (reference)
Other chronic conditions
	No	1.00 (reference)	1.00 (reference)
	Yes	1.53 (1.39, 1.69)	1.48 (1.37, 1.60)
Year
	2011	1.90 (1.69, 2.15)	2.02 (1.85, 2.21)
	2014	2.00 (1.77, 2.26)	2.28 (2.08, 2.49)
	2017	1.00 (reference)	1.00 (reference)

Values are presented as odds ratio (95% confidence interval).

¹ Adjusted for age, marital status, living arrangement, education level, insurance type, current smoking, lack of exercise, high-risk alcohol drinking, restriction on activities of daily living, frequency of contact with people, other chronic conditions, and year.

Table 3.

Subgroup analysis of the association between depression and multimorbidity¹

Variables	Men			p-value²	Women			p-value²
	No. of chronic conditions				No. of chronic conditions
	0	1	≥2		0	1	≥2
Age (yr)				0.098				0.009
65-69	1.00 (reference)	1.58 (1.20, 2.10)	2.56 (1.95, 3.36)		1.00 (reference)	1.43 (1.09, 1.87)	2.31 (1.79, 2.98)
70-74	1.00 (reference)	1.34 (1.05, 1.72)	2.14 (1.69, 2.71)		1.00 (reference)	1.54 (1.19, 2.01)	2.13 (1.67, 2.71)
75-79	1.00 (reference)	1.18 (0.91, 1.53)	2.20 (1.72, 2.82)		1.00 (reference)	0.94 (0.71, 1.24)	1.56 (1.22, 2.01)
≥80	1.00 (reference)	1.16 (0.88, 1.53)	1.61 (1.22, 2.11)		1.00 (reference)	1.27 (0.97, 1.65)	1.58 (1.24, 2.02)
Other chronic conditions				0.006				0.001
No	1.00 (reference)	1.63 (1.32, 2.02)	2.66 (2.16, 3.28)		1.00 (reference)	1.44 (1.16, 1.79)	2.41 (1.97, 2.94)
Yes	1.00 (reference)	1.12 (0.94, 1.33)	1.82 (1.55, 2.14)		1.00 (reference)	1.17 (0.99, 1.39)	1.61 (1.38, 1.89)

Values are presented as odds ratio (95% confidence interval).

² Defined as the p-value of interactions.

Table 4.

Associations between various combinations of chronic conditions and depression (0-2)¹

Combinations of chronic conditions		Depression
Combinations of chronic conditions		Yes, n (%)	Total, n	OR (95% CI)
Zero		860 (15.6)	5,523	1.00 (reference)
One
	Arthritis	650 (29.1)	2,236	1.55 (1.37, 1.76)
	Diabetes	143 (20.0)	716	1.41 (1.14, 1.73)
	Heart disease	116 (22.7)	511	1.39 (1.10, 1.76)
	Hypertension	793 (17.0)	4,678	1.04 (0.93, 1.17)
	Pulmonary disease	92 (29.9)	308	1.76 (1.35, 2.31)
	Cancer	105 (34.9)	301	3.04 (2.33, 3.96)
	Stroke	79 (38.4)	206	2.81 (2.07, 3.83)
	Osteoporosis	111 (21.9)	508	1.18 (0.93, 1.50)
Two
	Arthritis+diabetes	103 (31.7)	325	2.01 (1.55, 2.60)
	Arthritis+heart disease	97 (37.2)	261	2.14 (1.62, 2.82)
	Arthritis+hypertension	799 (30.4)	2,628	1.61 (1.42, 1.81)
	Arthritis+pulmonary disease	49 (38.6)	127	2.26 (1.54, 3.31)
	Arthritis+cancer	24 (30.8)	78	1.61 (0.95, 2.70)
	Arthritis+stroke	46 (54.8)	84	4.15 (2.59, 6.63)
	Arthritis+osteoporosis	252 (33.3)	757	1.66 (1.38, 1.99)
	Diabetes+heart disease	35 (27.1)	129	1.89 (1.24, 2.88)
	Diabetes+hypertension	437 (23.9)	1,828	1.57 (1.37, 1.81)
	Diabetes+pulmonary disease	12 (50.0)	24	4.29 (1.80, 10.21)
	Diabetes+cancer	24 (40.7)	59	4.11 (2.33, 7.16)
	Diabetes+stroke	30 (52.6)	57	4.92 (2.78, 8.81)
	Diabetes+osteoporosis	17 (25.8)	66	1.46 (0.81, 2.65)
	Heart disease+hypertension	160 (22.4)	713	1.43 (1.17, 1.75)
	Heart disease+pulmonary disease	20 (47.6)	42	3.38 (1.78, 6.50)
	Heart disease+cancer	7 (28.0)	25	2.15 (0.83, 5.60)
	Heart disease+stroke	11 (36.7)	30	1.81 (0.82, 4.03)
	Heart disease+osteoporosis	19 (34.6)	55	1.83 (1.02, 3.30)
	Hypertension+pulmonary disease	62 (32.3)	192	2.00 (1.43, 2.78)
	Hypertension+cancer	48 (29.5)	163	2.25 (1.57, 3.25)
	Hypertension+stroke	195 (38.0)	513	2.53 (2.06, 3.12)
	Hypertension+osteoporosis	171 (29.3)	583	1.50 (1.22, 1.85)
	Pulmonary disease+cancer	6 (42.9)	14	3.90 (1.28, 11.98)
	Pulmonary disease+stroke	10 (66.7)	15	6.88 (2.19, 20.99)
	Pulmonary disease+ osteoporosis	10 (34.5)	29	2.26 (1.01, 5.12)
	Cancer+stroke	5 (55.6)	9	4.19 (0.97, 18.17)
	Cancer+osteoporosis	8 (36.4)	22	2.84 (1.10, 7.35)
	Stroke+osteoporosis	4 (26.7)	15	1.13 (0.33, 3.90)

OR, odds ratio; CI, confidence interval.

¹ Adjusted for gender, age, marital status, living arrangement, education, type of insurance, current smoking, lack of exercise, high-risk alcohol drinking, restriction on activities of daily living, frequency of contact with people, other chronic conditions, and year.

REFERENCES

1. Noël PH, Williams JW, Unützer J, Worchel J, Lee S, Cornell J, et al. Depression and comorbid illness in elderly primary care patients: impact on multiple domains of health status and well-being. Ann Fam Med 2004;2:555-562. PMID: 15576541

2. Schaakxs R, Comijs HC, Lamers F, Kok RM, Beekman AT, Penninx BW. Associations between age and the course of major depressive disorder: a 2-year longitudinal cohort study. Lancet Psychiatry 2018;5:581-590. PMID: 29887519

3. Blazer DG. Depression in late life: review and commentary. Focus 2009;7:118-136.

4. Vink D, Aartsen MJ, Schoevers RA. Risk factors for anxiety and depression in the elderly: a review. J Affect Disord 2008;106:29-44. PMID: 17707515

5. Djernes JK. Prevalence and predictors of depression in populations of elderly: a review. Acta Psychiatr Scand 2006;113:372-387. PMID: 16603029

6. Cole MG, Dendukuri N. Risk factors for depression among elderly community subjects: a systematic review and meta-analysis. Am J Psychiatry 2003;160:1147-1156. PMID: 12777274

7. Uijen AA, van de Lisdonk EH. Multimorbidity in primary care: prevalence and trend over the last 20 years. Eur J Gen Pract 2008;14 Suppl 1:28-32. PMID: 18949641

8. Held FP, Blyth F, Gnjidic D, Hirani V, Naganathan V, Waite LM, et al. Association rules analysis of comorbidity and multimorbidity: the concord health and aging in men project. J Gerontol A Biol Sci Med Sci 2016;71:625-631. PMID: 26508296

9. Rocca WA, Boyd CM, Grossardt BR, Bobo WV, Finney Rutten LJ, Roger VL, et al. Prevalence of multimorbidity in a geographically defined American population: patterns by age, sex, and race/ethnicity. Mayo Clin Proc 2014;89:1336-1349. PMID: 25220409

10. World Health Organization. World health statistics 2016: monitoring health for the SDGs sustainable development goals. [cited 2021 Nov 1]. Available from: https://apps.who.int/iris/handle/10665/206498.

11. Tinetti ME, Fried TR, Boyd CM. Designing health care for the most common chronic condition--multimorbidity. JAMA 2012;307:2493-2494. PMID: 22797447

12. Salive ME. Multimorbidity in older adults. Epidemiol Rev 2013;35:75-83. PMID: 23372025

13. U.S. Department of Health and Human Services. Multiple chronic conditions—a strategic framework: optimum health and quality of life for individuals with multiple chronic conditions; 2010 [cited 2021 Nov 1]. Available from: https://www.hhs.gov/sites/default/files/ash/initiatives/mcc/mcc_framework.pdf.

14. Read JR, Sharpe L, Modini M, Dear BF. Multimorbidity and depression: a systematic review and meta-analysis. J Affect Disord 2017;221:36-46. PMID: 28628766

15. Turuba R, Pirkle C, Bélanger E, Ylli A, Gomez Montes F, Vafaei A. Assessing the relationship between multimorbidity and depression in older men and women: the International Mobility in Aging Study (IMIAS). Aging Ment Health 2020;24:747-757. PMID: 30724575

16. Girgus JS, Yang K, Ferri CV. The gender difference in depression: are elderly women at greater risk for depression than elderly men? Geriatrics (Basel) 2017;2:35.

17. Agur K, McLean G, Hunt K, Guthrie B, Mercer SW. How does sex influence multimorbidity? Secondary analysis of a large nationally representative dataset. Int J Environ Res Public Health 2016;13:391. PMID: 27043599

18. St Sauver JL, Boyd CM, Grossardt BR, Bobo WV, Finney Rutten LJ, Roger VL, et al. Risk of developing multimorbidity across all ages in an historical cohort study: differences by sex and ethnicity. BMJ Open 2015;5:e006413. PMID: 25649210

19. Jung K, Oh Y, Lee Y, Oh M, Kang E, Kim K, et al. National survey of older Koreans. Sejong: Korea Institute for Health and Social Affairs; 2017. p 29 (Korean).

20. Bae JN, Cho MJ. Development of the Korean version of the Geriatric Depression Scale and its short form among elderly psychiatric patients. J Psychosom Res 2004;57:297-305 5507257. PMID: 15507257

21. Seo SO, So AY. Depression and cognitive function of the community-dwelling elderly. J Korean Acad Community Health Nurs 2016;27:1-8 (Korean).

22. Lee DH, Nam JY, Kwon S, Keum N, Lee JT, Shin MJ, et al. Lifestyle risk score and mortality in Korean adults: a population-based cohort study. Sci Rep 2020;10:10260. PMID: 32581249

23. Olaya B, Domènech-Abella J, Moneta MV, Lara E, Caballero FF, Rico-Uribe LA, et al. All-cause mortality and multimorbidity in older adults: the role of social support and loneliness. Exp Gerontol 2017;99:120-126. PMID: 28982608

24. Birk JL, Kronish IM, Moise N, Falzon L, Yoon S, Davidson KW. Depression and multimorbidity: Considering temporal characteristics of the associations between depression and multiple chronic diseases. Health Psychol 2019;38:802-811. PMID: 31008648

25. Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, et al. Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev 2011;10:430-439. PMID: 21402176

26. Peleg S, Nudelman G. Associations between self-rated health and depressive symptoms among older adults: does age matter? Soc Sci Med 2021;280:114024. PMID: 34049050

27. Liang J, Shaw BA, Krause N, Bennett JM, Kobayashi E, Fukaya T, et al. How does self-assessed health change with age? A study of older adults in Japan. J Gerontol B Psychol Sci Soc Sci 2005;60:zS224-S232.

28. van Doorslaer E, Gerdtham UG. Does inequality in self-assessed health predict inequality in survival by income? Evidence from Swedish data. Soc Sci Med 2003;57:1621-1629. PMID: 12948571

29. Ebner NC, Freund AM, Baltes PB. Developmental changes in personal goal orientation from young to late adulthood: from striving for gains to maintenance and prevention of losses. Psychol Aging 2006;21:664-678. PMID: 17201488

30. Pruchno RA, Wilson-Genderson M, Heid AR. Multiple chronic condition combinations and depression in community-dwelling older adults. J Gerontol A Biol Sci Med Sci 2016;71:910-915. PMID: 26933159

31. Kanervisto M, Saarelainen S, Vasankari T, Jousilahti P, Heistaro S, Heliövaara M, et al. COPD, chronic bronchitis and capacity for day-to-day activities: negative impact of illness on the health-related quality of life. Chron Respir Dis 2010;7:207-215. PMID: 21084545

32. Jiang CH, Zhu F, Qin TT. Relationships between chronic diseases and depression among middle-aged and elderly people in China: a prospective study from CHARLS. Curr Med Sci 2020;40:858-870. PMID: 33123901

33. Robinson RG, Jorge RE. Post-stroke depression: a review. Am J Psychiatry 2016;173:221-231. PMID: 26684921

34. Si Y, Yuan H, Ji P, Chen X. The combinative effects of orem self-care theory and PDCA nursing on cognitive function, neurological function and daily living ability in acute stroke. Am J Transl Res 2021;13:10493-10500. PMID: 34650719

35. Haghgoo HA, Pazuki ES, Hosseini AS, Rassafiani M. Depression, activities of daily living and quality of life in patients with stroke. J Neurol Sci 2013;328:87-91. PMID: 23522526

36. Smith HR. Depression in cancer patients: pathogenesis, implications and treatment (review). Oncol Lett 2015;9:1509-1514. PMID: 25788991

37. Mishel MH, Hostetter T, King B, Graham V. Predictors of psychosocial adjustment in patients newly diagnosed with gynecological cancer. Cancer Nurs 1984;7:291-299. PMID: 6564913

38. Linden W, Vodermaier A, Mackenzie R, Greig D. Anxiety and depression after cancer diagnosis: prevalence rates by cancer type, gender, and age. J Affect Disord 2012;141:343-351. PMID: 22727334

39. Weiss Wiesel TR, Nelson CJ, Tew WP, Hardt M, Mohile SG, Owusu C, et al. The relationship between age, anxiety, and depression in older adults with cancer. Psychooncology 2015;24:712-717. PMID: 25099337

40. Misiorowski W. Osteoporosis in men. Prz Menopauzalny 2017;16:70-73. PMID: 28721134

41. Canto JG, Rogers WJ, Goldberg RJ, Peterson ED, Wenger NK, Vaccarino V, et al. Association of age and sex with myocardial infarction symptom presentation and in-hospital mortality. JAMA 2012;307:813-822. PMID: 22357832

42. Bogner HR, Dahlberg B, de Vries HF, Cahill E, Barg FK. Older patients’ views on the relationship between depression and heart disease. Fam Med 2008;40:652-657. PMID: 18830841

43. Regitz-Zagrosek V, Kararigas G. Mechanistic pathways of sex differences in cardiovascular disease. Physiol Rev 2017;97:1-37. PMID: 27807199

44. Dong X, Chen R, Simon MA. The prevalence of medical conditions among U.S. Chinese community-dwelling older adults. J Gerontol A Biol Sci Med Sci 2014;69(Suppl 2):S15-S22. PMID: 25378445

45. Connolly MJ, Yohannes AM. The impact of depression in older patients with chronic obstructive pulmonary disease and asthma. Maturitas 2016;92:9-14. PMID: 27621232

46. Eisner MD, Katz PP, Lactao G, Iribarren C. Impact of depressive symptoms on adult asthma outcomes. Ann Allergy Asthma Immunol 2005;94:566-574. PMID: 15948301

47. Shi Y, Yang D, Zeng Y, Wu W. Risk factors for post-stroke depression: a meta-analysis. Front Aging Neurosci 2017;9:218. PMID: 28744213

48. Yu R, Y-Hua L, Hong L. Depression in newly diagnosed type 2 diabetes. Int J Diabetes Dev Ctries 2010;30:102-104. PMID: 20535315

49. Wilson-Genderson M, Heid AR, Pruchno R. Onset of multiple chronic conditions and depressive symptoms: a life events perspective. Innov Aging 2017;1:igx022. PMID: 30480117