Depressive symptoms of house-poor persons: Korean panel data evidence

Abstract

Background:

There are no studies researching the relationship between house-poor persons and mental health. Therefore, this study aimed to investigate the relationship between house-poor status and depressive symptoms.

Aim:

To examine the relationship between the house-poor and depressive symptoms according to household income.

Methods:

Data from the Korean Welfare Panel Study were used. House-poor were defined as people having possession with over 10% house-related interest in disposable income. About 7,565 participants over the age of 19 years were followed up from 2011 to 2013. The generalized estimating equations were used for analysis.

Results:

Individuals with more house-related debt showed increasingly higher depression scores (possession with under 5% related debt to disposable income β = 0.2024, p = .1544; under 10% β = 0.7030, p = .0008; over 10% β = 1.3207, p < .0001). Individuals possessing houses with over 10% ratio of house-related debts to disposable income had higher depression scores than individuals without house ownership (no possession β = 0.8927, p < .0001).

Conclusion:

Individuals without houses and individuals owning houses with higher percentages of house-related interests showed higher levels of depressive symptoms. Therefore, this study affirmed that the importance of considering the most vulnerable groups in addressing the mental health of individual.

Keywords

Depressive symptom house tenure housing affordability house-poor

Introduction

In South Korea, depression has become a major public issue. There has been a rapid increase in suicide rates (Oh et al., 2013), and the lifetime prevalence of major depressive disorders has increased by 0.2% annually for the last decade (Jeon, 2012) to 6.7%. Depression has become recognized as a major burden in terms of disability-adjusted life years. In 2010, it constituted the top cause along with cancer (Lee & Park, 2013).

Studies on the effect of economic conditions on individuals’ mental health (Statistics Korea, 2014) have reported that lower economic status are generally related to depression (Martikainen, Adda, Ferrie, Davey Smith, & Marmot, 2003; Riumallo-Herl, Basu, Stuckler, Courtin, & Avendano, 2014). Of economic stability indicators, housing tenure has been of particular interest to population health researchers (McConnell, 2012; Nettleton & Burrows, 1998; Ritchey, La Gory, Fitzpatrick, & Mullis, 1990). Previous studies have reported that homeowners have better health compared to those who rent (Dunn, 2000; Dunn & Hayes, 2000; Filakti & Fox, 1994; Gibson et al., 2011). However, there is no definite agreement on the term ‘housing tenure’ (Cairney & Boyle, 2004), but a previous study defined house-poor as individuals who have their own houses but without the ability to afford them (McConnell, 2012). Specifically, there are two criteria defining house-poor. One is whether the ratio of income to shelter costs is over 30%, and another is whether residual income (income remaining after housing expenditures) is below the federally defined income thresholds after housing expenditures (Combs, Combs, & Ziebarth, 1995; Jewkes & Delgadillo, 2010; Kutty, 2005). Hence, this article aimed to clarify the effect of an aspect of economic deprivation on the prevalence of depression.

Regarding the use of house-poor in South Korea, a report by a private institute for Chief Executive Officers (CEOs) suggested the following objective criteria. First, individuals are to be defined as house-poor, if they possess only one house for the purpose of living. Second, individuals must be in the process of repaying loans after purchase. Last, of total disposable income, the proportion of house-related principle and debt must exceed 10%, leading to a decrease in household expenditure (Hyundai Research Institute, 2011). Although the 10% criteria may be comparatively low compared to other countries, this criteria have been suggested because South Korea’s house prices against average income and loan-to-value ratio are lower than other countries (respectively, 60.8, 50%) (Crowe, Dell’Ariccia, Igan, & Rabanal, 2013; The Economist, 2016; Hyundai Research Institute, 2011). In fact, based on this criteria, 10.1% of South Korean individuals with house possession were defined as house-poor (Hyundai Research Institute, 2011). Thus, 10% principle and interests can affect depression levels through relative deprivation.

Individuals with debts are known to often feel anxious and fearful of losing their home while in the process of keeping up with mortgage payments and interests (Davis, Dhooge, & Coles, 1993; Ford, Kempson, & Wilson, 1995; Reading & Reynolds, 2001). This is particularly because, whereas loans and mortgages are based on the assumption of stable employment (Burrows & Ford, 1997; Ford & Wilcox, 1999), home ownership has become increasingly problematic and unsustainable in South Korea due to recent economic trends toward increased work flexibility resulting from insecure and short-term employment in Korea (Jang & Park, 2015). Therefore, studies of the relationships between house affordability and mental health are needed

Furthermore, equalized household income is also a known risk factor for depression in individuals, and individuals with lower household income are known to experience higher depression (Lorant et al., 2007). Hence, house affordability can be differently associated with depressive symptoms based on equalized household income. Therefore, this study aimed to (a) investigate the frequency of house-poor status and its associated depressive symptoms, (b) determines trends of depressive symptoms by house-poor status and (c) evaluates the relationship between house-poor status and depressive symptoms by equalized household income.

Methods

Study sample

This study used data from the Korean Welfare Panel Study (KOWEPS) performed by the Korean Institute of Social and Health Affairs in conjunction with the Social Welfare Research Institute of Seoul National University. Briefly, KOWEPS is a comprehensive dataset that provides information on families and individuals aged 15 years and over on social service needs, health-care utilization patterns, economic and demographic backgrounds, income sources and subjective emotional and behavioral health status. Households were selected through a stratified, multistage, probability design and face-to-face interviews, which are conducted accordingly. The analytic sample for this analysis was 7,565 respondents aged over 19 years, followed up from 2011 to 2013.

Study variables

Depressive symptom

The Center for Epidemiologic Studies Depression Scale (CESD-11) was used to measure depression level. The CESD-11 scale was originally designed to measure depressive symptoms in the general population (Radloff, 1977) and has been widely used in community and clinical samples (Shafer, 2006). For each year of the study period, the respondents reported symptoms in the past week using a 4-point scale (0 = ≤1 day/week; 1 = 2–3 days/week; 2 = 4–5 days/week; 3 = ≥ 6 days/week) on 11 respective questions. These were then combined into total scores and multiplied by 20/11. Scores range from 0 to 60, where higher scores indicate increased depressive symptoms.

House-poor

House-poor status was determined by combining three questions. The first question, house ownership, is categorized into own, rent yearly, rent monthly and others (without house ownership but living for free or company housing) in KOWEPS. The second question inquires about the amount of interest paid in house-related debts at the end of last year. The third question asks about disposable income. Based on the three questions, people who rented monthly or yearly and others were categorized into no possession. People who owned houses without house-related debt interest were categorized into possession without related interest. People who owned houses with house-related debt interest were categorized into possession with under 5%-, under 10%- or over 10%-related ratio of interest to disposable income. In this study, the house possession status comprised people affected by 10% house-related debt interest ratio to disposable income.

Equalized household incomes

Equalized household income can act as an indicator of the economic resources available to each individual within a household. Equalized household income was calculated by dividing the yearly household income by the square root of the number of persons in the household (Jin & Kang, 2006). This allows people in large households to have the same contribution to the mean household income as people living alone (Australian Bureau of Statistics, 2006). Thus, equalized household income is the total household income adjusted by an equivalence scale to facilitate comparisons between households of differing size and composition. This reflects the requirement of a larger household to have a higher level of income than a smaller household to achieve the same standard of living. Household incomes were then ranked into four quartiles (high, middle high, middle low and low) using the Statistical Analysis System (SAS) univariate function.

Covariates

Education level was classified as less than high school, high school graduate and college graduate (including graduate school). Job status was divided into two categories: a yes or a no. Participants’ marital status was categorized into no, yes, separation, death or divorce. If participants had children, the status was yes and if not, no. Health and income satisfaction were categorized as high, middle or low. Alcohol intake was divided into two categories: a yes (includes under once a month at least) or a no. House prices were ranked into quartiles (high, middle high, middle low and low). Region was categorized into four categories: capital, city, urban or rural.

Statistical analysis

T-tests and one-way analyses of variance (ANOVAs) were used to analyze statistical differences on CESD-11. Longitudinal data analysis was used to investigate impact of house possession status on depressive symptoms. In order to analyze the associations between house possession status and CESD-11, generalized estimating equations (GEEs) were used, accounting for the longitudinal nature of the data that required the incorporation of correlated structures among observations. All statistical analyses were carried out using SAS 9.3 (SAS institute, Inc., Cary, NC. USA).

Results

Table 1 presents the study participants’ sociodemographic characteristics, which consists of 7,565 individuals at the baseline (2011). In addition, it shows the distribution of participants and average depression scores by respective variable category. There were significant differences in depression scores by house possession status.

Table 1.

General characteristics and average of CESD-11(2011).

	CESD-11^a
	N (%)		Mean ± SD	p value
House possession status
No possession	2,332	(30.8)	7.99 ± 9.44	<.0001
Possession without related interest	3,744	(49.5)	6.66 ± 7.75
Possession with under 5% related interest in disposable income	866	(11.4)	4.59 ± 5.88
Possession with under 10% related interest in disposable income	365	(4.8)	5.69 ± 7.53
Possession with over 10% related interest in disposable income	258	(3.4)	7.77 ± 9.29
Equalized household income
Low	1,824	(24.1)	11.61 ± 10.42	<.0001
Middle low	1,836	(24.3)	7.03 ± 7.75
Middle high	1,937	(25.6)	4.96 ± 6.32
High	1,968	(26.0)	4.03 ± 5.69
Sex
Men	3,310	(43.8)	5.53 ± 7.21	<.0001
Women	4,255	(56.2)	7.83 ± 8.83
Age (years)
20–30	579	(7.7)	4.27 ± 6.03	<.0001
30–40	1,273	(16.8)	4.21 ± 6.00
40–50	1,488	(19.7)	5.11 ± 6.79
50–60	1,337	(17.7)	6.60 ± 8.07
60–80	1,329	(17.6)	8.19 ± 9.15
>80	1,559	(20.6)	10.58 ± 9.43
Education
Less than high school	3,128	(41.3)	9.48 ± 9.37	<.0001
High school graduate	2,333	(30.8)	5.62 ± 7.30
College graduate	2,104	(27.8)	4.21 ± 5.96
Job status
No	2,752	(36.4)	9.12 ± 9.74	<.0001
Yes	4,813	(63.6)	5.51 ± 6.91
Marriage status
No	883	(11.7)	5.35 ± 6.94	<.0001
Yes	5,439	(71.9)	5.91 ± 7.33
Separation or by death or divorce	1,243	(16.4)	11.86 ± 10.64
Sons and daughter
Not have	1,096	(14.5)	5.88 ± 7.74	<.0001
Have	6,469	(85.5)	6.99 ± 8.31
Satisfaction of health status
Low	1,781	(23.5)	12.55 ± 10.47	<.0001
Middle	1,857	(24.5)	7.17 ± 7.45
High	3,927	(51.9)	4.07 ± 5.69
Satisfaction of income
Low	3,254	(43.0)	9.10 ± 9.39	<.0001
Middle	2,521	(33.3)	5.93 ± 7.13
High	1,790	(23.7)	3.95 ± 6.01
Drinking of alcohol
No	3,471	(45.9)	8.31 ± 9.15	<.0001
Yes	4,094	(54.1)	5.57 ± 7.15
Price of house
Low	1,903	(25.2)	9.65 ± 9.81	<.0001
Middle low	1,911	(25.3)	6.80 ± 8.01
Middle high	1,983	(26.2)	5.40 ± 6.96
High	1,768	(23.4)	5.40 ± 7.10
Region
Capital	1,346	(17.8)	7.13 ± 8.51	<.0001
City	1,970	(26.0)	6.95 ± 8.88
Urban	2,556	(33.8)	6.24 ± 7.92
Rural	1,693	(22.4)	7.32 ± 7.65
Total	7,565	(100.0)	6.83 ± 8.24

CESD: Center for Epidemiologic Studies Depression Scale; SD: standard deviation.

CESD-11 score is expressed as mean ± SD.

Table 2 presents the results of the GEEs, which assessed the associations between house possession status and depression scores. After adjusting for covariates, the higher the house-related interest to disposable income ratio people with houses had, the higher the depression scores (possession with under 5%-related interest to disposable income ratio β = 0.2024, p = .1544; under 10% β = 0.7030, p = .0008; over 10% β = 1.3207, p < .0001). If individuals had houses with 10% house-related debt interest to disposable income ratios, they had higher depression scores than people without house ownership (no possession β = 0.8927, p < .0001).

Table 2.

Association between house possession status and CESD-11 score.

	CESD-11
	β	SE	p value
House-poor status
No possession	0.8927	0.1601	<.0001
Possession without related interest	Ref.	–
Possession with under 5% related interest in disposable income	0.2024	0.1422	.1544
Possession with under 10% related interest in disposable income	0.7030	0.2094	.0008
Possession with over 10% related interest in disposable income	1.3207	0.3070	<.0001
Equalized household income
Low	1.8552	0.2008	<.0001
Middle low	0.4853	0.1511	.0013
Middle high	0.1006	0.1185	.3956
High	Ref.	–
Sex
Men	−0.9546	0.1317	<.0001
Women	Ref.	–
Age (years)
20–30	−2.2329	0.3838	<.0001
30–40	−1.4471	0.2767	<.0001
40–50	−0.9828	0.2502	<.0001
50–60	−0.7020	0.2315	.0024
60–80	−0.6732	0.2085	.0012
>80	Ref.	–
Education
Less than high school	Ref.	–
High school graduate	−0.4465	0.1825	.0144
College graduate	−0.6285	0.2115	.0030
Job status
No	1.0398	0.1357	<.0001
Yes	Ref.	–
Marriage status
No	0.9184	0.4058	.0236
Yes	Ref.	–
Separation or by death or divorce	2.3266	0.2147	<.0001
Sons and daughter
Not have	0.8503	0.3872	.0281
Have	Ref.	–
Satisfaction of health status
Low	4.6171	0.1584	<.0001
Middle	1.6142	0.1147	<.0001
High	Ref.	–
Satisfaction of income
Low	1.7695	0.1235	<.0001
Middle	0.5129	0.1080	<.0001
High	Ref.	–
Drinking of alcohol
No	0.1585	0.1165	.1736
Yes	Ref.	–
Price of house
Low	1.3056	0.1979	<.0001
Middle low	0.6444	0.1601	<.0001
Middle high	0.2909	0.1376	.0346
High	Ref.	–
Region
Capital	Ref.	–
City	−0.5178	0.1885	.0060
Urban	−0.1742	0.1770	.3249
Rural	−0.4000	0.2106	.0575
Year
2011	0.6712	0.1024	<.0001
2012	−0.3853	0.0939	<.0001
2013	Ref.	–

CESD: Center for Epidemiologic Studies Depression Scale; SE: standard error.

Table 3 shows associations between house possession status and depression scores by equalized household income. In the high-income group, there were no significant relationships between house possession status and depressive symptoms. In the middle-high-income group, only people with over 10% house-related interest to disposable income ratios had significantly higher depression scores (β = 1.8556, p = .0025). In the middle-low equalized income group, people with over 10% house-related interest to disposable income ratios had significantly higher depression scores than people without houses when setting people with houses and no debts as the reference (no possession β = 0.7887, p = .0123; over 10% β = 1.1304, p = .0042). In the low-income group, regardless of house possession or related interest status, people had noticeably higher depressive symptoms than individuals in other income groups except for people in the under 5% house-related interest group (no possession β = 2.6265, p < .0001; under 10% β = 2.2860, p = .0118; over 10% β = 2.2723, p = .0016).

Table 3.

Association between house possession status and CESD-11 score according to equalized household income^a.

	CESD-11
	β	SE	p-value
Low
No possession	2.6265	0.4337	<.0001
Possession without related interest	Ref.	–
Possession with under 5% related interest in disposable income	−0.1368	0.6834	8414
Possession with under 10% related interest in disposable income	2.2860	0.9077	.0118
Possession with over 10% related interest in disposable income	2.2723	0.7192	.0016
Middle low
No possession	0.7887	0.3152	.0123
Possession without related interest	Ref.	–
Possession with under 5% related interest in disposable income	0.4521	0.3978	.2557
Possession with under 10% related interest in disposable income	0.6554	0.4313	.1287
Possession with over 10% related interest in disposable income	1.1304	0.5617	.0442
Middle high
No possession	0.1963	0.2510	.4342
Possession without related interest	Ref.	–
Possession with under 5% related interest in disposable income	0.2066	0.2364	.3821
Possession with under 10% related interest in disposable income	0.3117	0.3181	.3271
Possession with over 10% related interest in disposable income	1.8556	0.6134	.0025
High
No possession	0.0425	0.2264	.8510
Possession without related interest	Ref.	–
Possession with under 5% related interest in disposable income	−0.0814	0.1865	.6624
Possession with under 10% related interest in disposable income	0.6115	0.3620	.0912
Possession with over 10% related interest in disposable income	0.4692	0.4676	.3156

CESD: Center for Epidemiologic Studies Depression Scale; SE: standard error.

Covariates are adjusted by sex, age, education, job status, marriage status, sons and daughters, satisfaction of health status and income, drinking of alcohol, price of house, region and year.

Discussion

This study showed that a noticeable proportion of individuals possess houses with related interest as 19.7% of the total participants have house-related debts. In the South Korean society, these trends result mainly because real estate is viewed as an investment measure. This is apparent by the fact that real estate constitutes around 80% of household wealth and this naturally escalates the risk of financial difficulties, if real estate prices decline or transactions decrease (Moon-sung Jung, 2014). When looking at the mean depression scores by house possession status, no possession and possession with over 10%-related interest to disposable income ratio groups had similar scores. This emphasizes that having no house possession is related to higher depression scores, possibly due to the fact that people are not being able to fulfill their basic needs for shelter and security (Maslow, Frager, & Fadiman, 1970). Nevertheless, people with over 10% house-related interest to disposable income ratios also showed similar depression scores, which implies that although house possession is a basic need, possessing money available for living is also essential to individuals.

This study investigated how the percentage of house-related interest to disposable income ratios affects depressive symptoms. Similar to previous studies showing that individuals without mortgages have the lowest levels of distress compared to those with mortgages or without house possession, increased possession-related interest to disposable income ratios and no house possession were related to higher depression scores (Cairney & Boyle, 2004). To many households, allocating a higher proportion of income to housing costs constrains other necessary expenditures, which can affect individuals’ quality of life (Brennan & Lipman, 2008; Lipman, 2005). In fact, stress, defined as a process in which an individual experiences threats to well-being, can likely result in individuals with a higher percentage of possession-related interest of disposable income as fewer resources can be freely used, exhausting resources and leading to negative outcomes (Belle, 1983). In addition, as shelter is one of the most basic necessities of life, owning a home can satisfy the basic security requirements and can also provide a sizeable capital resource; this links housing tenure and mental health (Maslow et al., 1970). However, when housing ownership is present with mortgage, the positive effects of possessing a shelter can be lowered due to various insecurities, such as the fear of not being able to pay mortgage payments on schedule and the stress of the mortgage itself, which may be particularly important in lower income families (Ford et al., 1995). One area of focus is that those with over 10% house-related interest have more depression than those without houses. This implies that interests can cause stress, which leads to individuals with their own houses feeling an increased level of burden and depressive symptoms than those without. Symptoms of extreme distress that result, including agitation, slower activity levels and distractibility, can be characterized as psychological depression. Thus, this study reveals that higher percentages of house-related interest ratios to disposable income can strongly be associated with increased depression scores and confirms that housing status is closely related to individuals’ psychological well-being (Ritchey et al., 1990), which addresses the need to monitor individuals at higher risks.

Regarding the factors related to depression, previous studies have shown that individuals with lower household income have higher depression levels regardless of sex (Lorant et al., 2007; Zimmerman & Katon, 2005). Hence, subgroup analysis was performed to determine how the percentage of possession-related interest to disposable income interplays with household equalized income on the depression levels of individuals. Analysis revealed that in the high equalized income group, depression was not significantly related to the amount of possession-related interest to disposable income. Yet this was not the case in the middle-high-, middle-low- and low-income groups. In the middle-high and low groups, people with over 10% house-related interest had higher scores than people without possession. Also, in the low-income group, no possession had the highest depression scores and under and over 10% interests had higher scores compared to other income groups. This eludes that no possession leads to more devastating mental health outcomes than possession in the low-income group. In the middle-low and high group, although no possession was related with increased depressive symptoms, the effect of over 10% of house-related interest ratio to disposable income was more noticeable. Therefore, people with over 10% of house-related interest to disposable income are likely to experience depressive symptoms regardless of household income except in the high-income group, and thus further emphasis on the house-poor is necessary.

To the best of our knowledge, this is the first study scientifically conducted to investigate the relationship between housing affordability and health outcomes. However, this study is not without limitations. First, because house-related interest was measured based on self-reports, this factor may have been underestimated or overestimated. Still, this study has its advantages in that the wealth-related variables used to create house possession status were not imputed and well followed up. Second, a previous report proposed a Korean house-poor definition of a 10% ratio of principal and interest to disposable income but in this study, the focus was only on interest. Hence, the ratio of interest to disposable income used was used in a more conservative manner because principal repayment depends on loan goods policies. Finally, the house-poor definition could be less conservative in other countries. Therefore, the results must be carefully interpreted according to different cultures. Thus, the study results cannot be generalized without caution.

Conclusion

This study showed that higher levels of depressive symptoms are found among individuals without house possessions and individuals owning house possessions with higher percentages of house-related interests. It can hence be inferred that owning house with excessive house-related expenditure or having no house possession can result in higher levels of depressive symptoms. Therefore, it is important to consider the most vulnerable groups while accounting for the cultural situations in different countries in addressing the mental health of individuals (Moon-sung Jung, 2014; Statistics Korea, 2014).

Footnotes

Acknowledgements

All authors have seen and contributed to approve the study and have met all requirements for authorship. W.K. and J.K. were responsible for the study design and data collection. J.S. and E.C.P. supported the statistical analyses. T.H.L. and T.H.K. were responsible for study design and statistical analyses and interpretation of result. All authors read, approved and also revised it critically.

Declaration of Conflicting of interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Ethical approval

As the KOWEPS data are secondary data that do not contain private information and are available in the public domain, ethical approval was not required.

Funding

The author(s) received no financial support for the research, authorship and/or publication of this article.

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