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Abstract

Background:

There is a rapidly ageing population globally, leading to a rise in subsidised public housing in many countries for older adults. According to the World Health Organisation, depression is the most prevalent mental disorder in older adults. There is a gap in literature on the factors associated with depression in those residing in studio apartments for older adults, characterised by small living spaces and isolated community settings.

Objective:

The aim of this study was to examine the associations between socio-demographic variables, social support, self-perceived health and mental status, life satisfaction, exercise, physical functioning, chronic conditions, and the use of eldercare services, with depressive symptoms.

Methods:

We utilised a cross-sectional study of older adults aged ⩾55 years residing in Singapore’s studio apartments. Multivariable logistic regression was applied.

Results:

Widowhood was associated with depressive symptoms, compared to being married or having a domestic partner (adjusted odds ratio (AOR) = 1.70, 95% confidence interval (CI) = 1.01 to 2.86). Odds of depressive symptoms were associated with difficulty bathing and showering (AOR = 3.74, 95% CI = 1.06 to 13.21). Depressive symptoms were associated with cataract (AOR = 1.67, 95% CI = 1.01 to 2.77) and urinary tract disorder (AOR = 4.70, 95% CI = 1.21 to 18.26). There were dose-response relationships between higher odds of depressive symptoms and poorer social support, self-perceived mental health, life satisfaction, and exercise behaviour (p for trend < 0.001).

Conclusion:

Factors including widowhood, physical functioning difficulty, chronic conditions, low social support, low self-perceived mental health, poor life satisfaction, and lack of exercise behaviour, were associated with depressive symptoms in older adults residing in studio apartments. More attention is needed to care for the psychosocial and physical needs of older adults in studio apartments.

Keywords

Depressive symptoms older adult ageing public housing studio apartments

Introduction

There is a rapidly ageing population from lower fertility rates and higher life expectancies globally.^1,2 By 2030, one in five persons worldwide would be aged 60+ years.¹ By 2050, 44% of the world’s population will live in relatively aged countries, with at least 20% of the population aged 60+ years, and one in four people living in a country where more than 30% are aged above 60 years.^1,2 According to the World Health Organisation (WHO), over 20% of older adults aged 60+ years suffer from a mental disorder, with depression being the most prevalent, affecting 7% of the world’s older population.³ Depression accounts for 5.7% of Years Lived with Disability (YLD) among these older adults.³ Depressive symptoms are frequently unnoticed and untreated, and older adults with depressive symptoms have poorer functioning than those with chronic conditions like hypertension or diabetes.^3,4 The WHO Comprehensive Mental Health Action Plan 2013–2020 highlights the importance of addressing mental health in older adults, especially depressive symptoms.³

Importantly, this ageing phenomenon has led to a rise in subsidised public housing in many countries, particularly studio apartments (SAs), built specifically for older adults, many of whom live alone.^5–7 Literature shows that depressive symptoms associated with older adults living alone due to widowhood, having never married, being childless, or lacking communication with relatives and friends.^8–10 In Japan, older adults living in isolation is reaching epidemic proportions, to the extent of numerous older adults not being assisted in critical conditions and found dead alone a significant time later.¹¹ Furthermore, Japanese older adults living alone significantly associated with depressive symptoms like loss of appetite, suicidal thoughts, and worrying.¹² A study in Korea found that older adults living alone with superficial social support and relationships associated with suicidal ideation.¹³

Currently, most literature focus on factors for depressive symptoms associated with older adults in nursing homes or exclusively living alone.^14–16 A systematic review on living arrangements and elderly depression found that depression associated with older adults residing alone, in old folks’ homes, or being institutionalised, and there was a lack of studies examining public housing for the aged and depression.¹⁷ There is a gap in understanding the unique living arrangements and immediate environments of public housing for older adults, particularly SAs, characterised by small living spaces and relatively isolated community settings.^7,18 We aim to examine psychosocial and physical factors associated with depressive symptoms of older adults residing in public housing for the aged in Singapore, particularly in SAs. Singapore serves as a suitable country for this study due to its ageing multi-ethnic population, and having subsidised SAs for older adults for more than two decades.¹⁹

Methods

Study design and participants

Participants were from a cross-sectional social survey conducted in Singapore from May to December 2012, under the project ‘The Home Safety Issues for Older Adults Living Alone: Enhancing Independence and Dignity in the Face of Environmental Press’, with a sampling frame consisting 100% of older adults residing in SAs in Singapore (n = 1861). SAs were 35 or 45 square metres, with elderly-friendly features including non-slip tiles, lever taps, support hand bars, and emergency pull cords linked to an alert system.²⁰ Older adults were Singapore citizens or permanent residents, at least 55 years old, who must reside with a spouse unless unmarried, divorced, or widowed, and had gross monthly household income not exceeding SGD$10,000.²¹

To minimise non-response, interviewers visited the SAs of non-respondents on different days of the week, and at different times of the day. Continued non-response from additional visits was followed-up by leaving a note on the survey form and slipped into the SA for residents to contact interviewers.

The structured interviewer-administered questionnaires were conducted on a one-to-one basis with an average duration of 1.5 hours per participant. The questionnaire included data on: demographics; activity profile; social support; health status; life satisfaction, physical functioning and use of devices; attitude towards assistive devices and home modification; self-care; neighbourhood environment; quality of services; living arrangement; and attitude towards living alone. Interviews were carried out in Singapore’s four national languages: English, Mandarin, Malay, and Tamil. Interviewers were from an independent professional survey company.

Outcome measure

The outcome measure was being symptomatically depressed. Depressive symptoms were measured using the modified version eight-item CES-D (Center for Epidemiologic Studies-Depression).^22–24 Each item was scored on a four-point Likert-type scale consisting of: rarely/none of the time = one point; some or little of the time = two points; occasionally/a moderate amount of time = three points; most/all of the time = four points. The eight items were on whether participants experienced these eight depressive symptoms during the past one week: depressed; everything I did was an effort; sleep was restless; could not get going; felt lonely; enjoyed life; felt sad; was happy. Reverse coding was done for two of the eight items: enjoyed life; was happy.

The scores from the eight items were added to obtain a single summated score, which ranged from eight to 32 points. The higher the summated score, the more symptomatically depressed the participant. We utilised a cut-off point of six points and above for classification as symptomatically depressed. This cut-off was derived using proportional strategy from the 20-items CES-D scale.²⁵ The original 20-item CES-D scale was a widely used, valid, and reliable index for measuring depressive symptom severity among older adults and has been validated in Singapore.²⁶ The eight-item CES-D was validated on European and American older adults under the European Social Survey and the Health and Retirement Study, respectively.^27,28 Cronbach’s Alpha was high at 0.8542 for the eight-item CES-D in this study.

Independent variables

The independent variables consisted of psychosocial and physical factors.

Psychosocial factors consisted of social support, self-perceived health status, life satisfaction, sensory functioning, exercise behaviour, use of eldercare services, and neighbourhood environment. Physical factors referred to physical functioning and the presence of chronic medical conditions.

Physical and sensory functioning were assessed collectively due to the design of the questionnaire.

Social support

We used the Multidimensional Scale of Perceived Social Support (MSPSS), which measured social support via relationships with family, friends, and significant others. MSPSS is a widely used scale in different populations, which included Singapore citizens and older adults, and was shown to be psychometrically sound, with good reliability, factorial validity, and adequate construct validity.^29,30 There were 12 items and each item was rated on a five-point Likert-type scale ranging from strongly disagree (one point), to strongly agree (five points). The summated range was 12 to 60. The higher the MSPSS score, the better the social support. Cronbach’s Alpha was 0.9173 in this study.

Social support by marital status was also examined. Categories of marital status comprised: married/domestic partner; separated/divorced; widowed; never married.

Self-perceived health status

Participants responded to three self-reported questions on their self-perceived overall, mental, and physical health: ‘In general, would you say that your (overall/mental/physical) health is…’, and responses were categorised into five options: very poor = one point; poor = two points; fair = three points; good = four points; excellent = five points. The three questions were analysed separately.

Life satisfaction

Life satisfaction was measured using self-reported responses to: ‘How satisfied are you with your (health; financial/economic situation; relationship with significant other; condition of house; community or neighbourhood; life and leisure; overall)?’ Responses were categorised using a Likert-type scale of 0 to 100 for each question, 0 being ‘absolutely dissatisfied’ and 100 being ‘absolutely satisfied’. Unlike other Likert scales in this study where all question could be answered, a couple of questions in the Life Satisfaction scale may not be applicable for certain participants. The analysis was based on the total number of questions that were applicable to each of the participants. For example, a participant who was single with no significant other, would be unable to answer how satisfied he/she was with the current relationship with his/her significant other, and this was accounted for when calculating the percentage score. The higher the summated score, the higher the satisfaction.³¹

Physical and sensory functioning

Physical functioning was assessed based on activities of daily living, including bathing and showering, getting in and out of bed, and short-distance walking. Sensory function included vision and hearing. Participants self-reported if they had ‘difficulty with’ each item, and responses were categorised into: no; yes; not applicable. Each item was analysed as an individual dependent variable.

Exercise behaviour

Participants responded to the two statements: ‘Do regular exercise that are good for me’; ‘Find safe and comfortable ways to prevent from getting hurt when doing exercises’. The responses were categorised as follows: completely = four points; mostly = three points; somewhat = two points; a little = one point; not at all = 0 points. The summated score of two statements ranged from 0 to 8. The higher the score, the greater the exercise behaviour.

Eldercare services and assistance

Participants were asked about their participation or uptake of eldercare services and assistance, such as counselling and community case management services (CCMS), and the responses were categorised into ‘yes’ and ‘no’.

Neighbourhood environment

We modified the Neighbourhood Environment Scale (NES) to the Singapore context. The NES is a 10-item assessment related to perceived personal safety, physical appearance, convenience of neighbourhood, and appraisals of dangers posed by others in the neighbourhood.³² Each item was rated on a five-point Likert scale ranging from ‘strongly disagree’ (one point) to ‘strongly agree’ (five points). The question, ‘I and my visitors have been lost because of no or unclear signs of directions’, was reverse-coded. The summated range was 10 to 50. The higher the summated NES score, the better the perception of the neighbourhood environment. Although the NES was developed for use in the context of children and families, the majority of the items were relevant to older adults.³² The modified NES scale’s Cronbach’s alpha was 0.8046 in this study.

Chronic medical conditions

Participants self-reported on whether they were diagnosed by medical doctors or health professionals with chronic conditions such as asthma, cataract, circulation trouble in arms or legs, urinary tract disorder, depression, general weakness, and high blood cholesterol. Responses were categorised into ‘yes’, ‘no’, ‘don’t know’, and ‘refused to answer’.

Socio-demographics

Additionally, we examined the potential confounders or covariates, including age, gender, ethnicity, living arrangement, SA type, and highest education level.

Statistical analysis

Scores for depressive symptoms were not studied as a continuous variable as scores were skewed even after transformation. We studied depressive symptoms as a binary outcome, as having depressive symptoms (CES-D ⩾ 6) or not (CES-D < 6).

We calculated the proportions for categorical variables by the status of being symptomatically depressed (i.e. CES-D score ⩾ 6). Pearson’s Chi-Square test or Fisher’s Exact test was used to compare proportions between groups, and we presented categorical variables as frequencies and percentages. For continuous variables that were normally distributed, we summarised them with means and standard deviations, and Student’s t-test was used to compare difference between groups. For those not normally distributed, we calculated medians and inter-quartile ranges, and the Wilcoxon rank-sum test was used to assess difference between groups.

Bivariate analysis was conducted to examine the association between the outcome of interest (i.e. CES-D yes/no) and individual variables, to identify potential confounders or covariates for inclusion in the multivariable model. Unconditional multivariable logistic regression was used to compute adjusted odds ratios (AORs) and 95% confidence intervals (CIs) of the dependent variables associated with depressive symptoms. The forward stepwise method was used to determine the confounders or covariates for inclusion in our multivariable logistic regression model. We reported unadjusted and adjusted ORs, 95% CIs and p-values, and p for trend. ORs and 95% CIs were reported to two decimal places, while p-values were reported to three decimal places.

Statistical analyses were conducted with STATA 12 (StataCorp LP, College Station, TX), assuming two-sided tests with 5% level of significance.

Results

Participant characteristics by depressive symptom status

The total number of respondents was 925. Our final sample size was 899 participants, as 899 out of our total 925 respondents (97.2%) had valid results for CES-D scores to assess depressive symptoms. Singapore is a multi-ethnic country and respondents were 76.1% Chinese, 13.2% Malay, 7.8% Indian, 1.8% Eurasian, and 1.1% others. Table 1 presents the demographic characteristics of participants by depressive status (433 (48.2%) had depressive symptoms, 466 (51.8%) had no depressive symptoms), as well as the variables significantly associated with the outcome of having depressive symptoms. Supplementary Appendix Table 1 shows the descriptive data for all 925 respondents.

Table 1.

Participant characteristics by depressive status.

Depressive symptoms
Variable	Yes (CES-D ⩾ 6)n = 433	No (CES-D < 6)n = 466	p-value
Age group, n (%)			0.001
55–59 years	25 (5.78)	41 (8.80)
60–69 years	145 (33.49)	191 (40.99)
70–79 years	195 (45.03)	194 (41.63)
80 years and above	68 (15.70)	40 (8.58)
Gender, n (%)			0.733
Male	168 (38.80)	187 (40.13)
Female	265 (61.20)	279 (59.87)
Ethnicity, n (%)			0.027
Chinese	317 (73.21)	363 (77.90)
Malay	65 (15.01)	56 (12.02)
Indian	43 (9.93)	29 (6.22)
Others	8 (1.85)	18 (3.86)
Marital status, n (%)			<0.001
Married/domestic partner	177 (40.88)	255 (54.72)
Separated/divorced	32 (7.39)	34 (7.30)
Widowed	142 (32.79)	96 (20.60)
Never married	82 (18.94)	81 (17.38)
Living arrangement, n (%)			0.003
Living alone	203 (46.88)	172 (36.91)
Not living alone	230 (53.12)	294 (63.09)
Studio apartment type, n (%)			0.138
Independent	298 (68.82)	298 (63.95)
Integrated	135 (31.18)	168 (36.05)
Highest education level, n (%)			<0.001
No education	84 (19.40)	77 (16.52)
Low level (primary, secondary, ITE/vocational)	317 (73.21)	315 (67.60)
High level (polytechnic, junior college, university, postgrad, others)	31 (7.16)	73 (15.67)
No data	1 (0.23)	1 (0.21)
Neighbourhood environment (NES score), n (%)			<0.001
Q1 (lowest score quartile; worst environment)	146 (33.72)	79 (16.95)
Q2	103 (23.79)	115 (24.68)
Q3	115 (26.56)	129 (27.68)
Q4 (highest score quartile)	50 (11.55)	120 (25.75)
No data	19 (4.39)	23 (4.94)

CES-D: Center for Epidemiologic Studies-Depression; NES: Neighbourhood Environmental Scale; ITE: Institute of Technical Education.

The proportion of participants with depressive symptoms who were single (59.12%) was higher than that of participants with no depressive symptoms (45.28%). The proportion of participants with depressive symptoms who lived alone (46.88%) was greater than that of participants with no depressive symptoms (36.91%). The age profiles between the two groups were significantly different, with 15.70% of participants with depressive symptoms age 80+ years, and only 8.58% of participants with no depressive symptoms age 80+ years. Ethnicity, education level, and neighbourhood environment were also significantly different between those with and without depressive symptoms.

Factors associated with depressive symptoms

Table 2 displays unadjusted and adjusted ORs, with corresponding 95% CIs and p-values, for our independent factors for depressive symptoms.

Table 2.

Independent factors associated with depressive symptoms.

	Depressive symptomsYes: CES-D ⩾ 6; No: CES-D < 6
	Unadjusted OR (95% CI)	p-value	AOR (95% CI)^{^}	p-value^{^}	Declaration of conflicting interestsp for trend^{^}
Marital status (reference: married/domestic partner)					NA
Separated/divorced	0.74 (0.36, 1.54)	0.42	0.73 (0.34, 1.57)	0.423
Widowed	2.00 (1.25, 3.13)	0.003	1.70 (1.01, 2.86)	0.047
Never married	1.28 (0.76, 2.17)	0.35	1.32 (0.74, 2.34)	0.345
Social support (reference: Q1 (least social support))					<0.001
Q2	0.57 (0.34, 0.96)	0.03	0.58 (0.34, 0.99)	0.047
Q3	0.42 (0.25, 0.72)	0.002	0.38 (0.21, 0.66)	0.001
Q4	0.23 (0.11, 0.45)	<0.001	0.21 (0.10, 0.42)	<0.001
Self-perceived overall health (reference: very poor/poor)					0.053
Fair	0.76 (0.31, 1.81)	0.53	0.89 (0.36, 2.19)	0.800
Excellent	1.30 (0.51, 3.33)	0.59	1.58 (0.60, 4.18)	0.358
Self-perceived mental health (reference: very poor/poor)					0.001
Fair	0.48 (1.20, 13.61)	0.51	0.49 (0.05, 4.37)	0.519
Excellent	0.22 (0.03, 1.92)	0.17	0.20 (0.02, 1.78)	0.148
Life satisfaction (reference: Q1 (lowest life satisfaction))					<0.001
Q2	0.59 (0.34, 1.01)	0.056	0.57 (0.33, 0.99)	0.046
Q3	0.15 (0.09, 0.27)	<0.001	0.15 (0.08, 0.27)	<0.001
Q4	0.07 (0.04, 0.15)	<0.001	0.07 (0.03, 0.14)	<0.001
Physical functioning (reference: no difficulty)					NA
BADL difficulty
Bathing and showering	4.05 (1.20, 13.61)	0.02	3.74 (1.06, 13.21)	0.040
Getting in and out of bed	0.20 (0.06, 0.60)	0.004	0.24 (0.07, 0.77)	0.017
Short-distance walking	2.64 (1.25, 5.59)	0.01	2.54 (1.17, 5.54)	0.019
Sensory difficulty
Vision	1.67 (1.09, 2.55)	0.02	1.65 (1.06, 2.57)	0.026
Hearing	1.89 (0.89, 4.02)	0.10	1.74 (0.79, 3.86)	0.171
Exercise behaviour (reference: Q1 (lowest exercise behaviour))					<0.001
Q2	1.60 (0.80, 3.19)	0.186	1.51 (0.73, 3.11)	0.271
Q3	0.75 (0.48, 1.17)	0.201	0.70 (0.44, 1.11)	0.126
Q4	0.40 (0.26, 0.68)	0.001	0.37 (0.21, 0.64)	<0.001
Medical condition (reference: no medical condition)					NA
Asthma	2.39 (1.01, 5.65)	0.047	2.14 (0.87, 5.22)	0.096
Cataract	1.68 (1.04, 2.70)	0.035	1.67 (1.01, 2.77)	0.047
Circulation trouble in arms or legs	0.60 (0.28, 1.25)	0.169	0.57 (0.26, 1.25)	0.161
Urinary tract disorder	4.24 (1.16, 15.54)	0.029	4.70 (1.21, 18.26)	0.025
General weakness	2.20 (1.01, 4.76)	0.046	2.12 (0.96, 4.67)	0.064
High blood cholesterol	1.48 (1.02, 2.16)	0.039	1.45 (0.98, 2.13)	0.065
Eldercare services and assistance (reference: no engagement with service)					NA
Counselling and CCMS	6.125 (0.97, 38.51)	0.053	5.45 (0.85, 34.86)	0.073

Multivariable model adjusted for age, gender, ethnicity, studio apartment type, neighbourhood environment.

AOR: adjusted odds ratio; CI: confidence interval; BADL: basic activities of daily living; CCMS: community case management services.

Social support

Higher odds of depressive symptoms were significantly associated with being widowed, as compared to being married or having a domestic partner, in both unadjusted and adjusted models (AOR = 1.70, 95% CI = 1.01 to 2.86). Participants who were separated/divorced or never married did not show a significant association with depressive symptoms in both unadjusted and adjusted models. Participants in higher quartiles of social support (Q2 to Q4) compared to the lowest quartile (Q1) showed significantly lower odds of depressive symptoms in both unadjusted and adjusted models (for Q4, AOR = 0.21, 95% CI = 0.10 to 0.42). There was a significant inverse dose–response relationship between increasing support and lower odds of depressive symptoms (p for trend < 0.001).

Self-perceived health status

There was no significant association between self-perceived overall health and depressive symptoms. For self-perceived mental health, odds of depressive symptoms for participants who responded with ‘good/excellent’ and ‘fair’, compared to ‘very poor/poor’, were not statistically significant in both unadjusted and adjusted models. However, there was a significant dose–response relationship between greater odds of depressive symptoms and poor self-perceived health status (p for trend = 0.001).

Life satisfaction

Participants in higher quartiles of life satisfaction (Q2 to Q4) compared to the lowest quartile (Q1) showed significantly lower odds of depressive symptoms in the adjusted model (for Q4, AOR = 0.07, 95% CI = 0.03 to 0.14). There was a significant dose–response relationship between greater odds of depressive symptoms and poorer life satisfaction (p for trend < 0.001).

Physical and sensory functioning

For both unadjusted and adjusted models, difficulty with bathing and showering, short-distance walking, and vision, compared to the reference of ‘no difficulty’, were significantly associated with higher odds of depressive symptoms. The odds of suffering depressive symptoms were highest for those with difficulty bathing and showering (AOR = 3.74, 95% CI = 1.06 to 13.21). Difficulty getting in and out of bed was significantly associated with lower odds of depressive symptoms (AOR = 0.24, 95% CI = 0.07 to 0.77).

Exercise behaviour

Only participants in the highest quartile (Q4) of exercise behaviour, compared to the lowest quartile (Q1), showed significantly lower odds of depressive symptoms in both unadjusted and adjusted models (for Q4, AOR = 0.37, 95% CI = 0.21 to 0.64). There was a significant inverse dose–response relationship (p for trend < 0.001).

Eldercare services and assistance

Although not statistically significant, participants who engaged in counselling and CCMS, compared to those who did not, had much higher odds of depressive symptoms (AOR = 5.45, 95% CI = 0.85 to 34.86).

Medical conditions

Depressive symptoms were significantly associated with the self-reported diagnosis of cataract (AOR = 1.67, 95% CI = 1.01 to 2.77) and urinary tract disorder (AOR = 4.70, 95% CI = 1.21 to 18.26).

Discussion

Summary and interpretation of findings

Depressive symptoms in older adults residing in SAs were associated with widowhood, lower social support, poorer self-perceived mental health, poorer self-perceived life satisfaction, less exercise behaviour, difficulty with physical functioning, and the presence of certain chronic conditions.

The prevalence of depressive symptoms in older adults in SAs was 48%. This was higher than two studies that used CES-D to assess depressive symptoms in older adults staying in public housing in Delaware (31%) and Indianapolis (23%).^33,34 This may be due to these two studies being on older adults in public housing in general, and not only on those who live exclusively in SAs characterised by smaller living spaces and staying alone. Another study on older adults in Care Homes in Pakistan found a higher prevalence of depressive symptoms using CES-D (69%).³⁵ Older adults in care homes may generally be less independent and be in worse physical health, and older adults in Singapore may have more social support than Pakistan. A Singapore study on elderly depression in nursing homes had a lower prevalence of 21% using a Structural Clinical Interview that diagnosed clinical depression, instead of CES-D that assessed depressive symptoms.¹⁶

The association between widowhood and depression was consistent with other studies.^36–38 Depressive symptoms were attributed to bereavement, whereby older adults were more likely than young adults to develop depression following bereavement.^39–41 Our findings revealed a dose–response relationship between lower social support and depressive symptoms. This could be due to social networks of older adults shrinking due to deaths of relatives and friends, and relocation, which resulted in over-reliance on resources only available and accessible in their immediate community as sources for integration and social support.⁴² Residential communities were the most salient environments for older adults, where social support and residential satisfaction are derived from relationships with neighbours, access to close-proximity services, and the immediate home environment.⁴³ Residence could facilitate well-being or conversely act as an obstacle that undermined social integration.^41,44

Exercise behaviour showed an inverse dose–response relationship with depressive symptoms. This was supported by other studies that exercise prevented or reduced depression in older adults by improving physical function via aerobic fitness, and providing social interaction when they exercised with others.^45–47 A bi-directional relationship was possible, whereby depressive symptoms reduced the amount of physical activities older adults engaged in, including exercise.⁴⁸

Difficulty with bathing, showering, and short-distance walking, as well as poor vision, impair the ability to self-care and socialise, predisposing older adults to depression.^49–51 Depressive symptoms may result from loss of privacy and independence from requiring assistance with bathing or showering. Difficulty with short-distance walking and vision may reduce adults’ ability to leave their homes to socialise or explore beyond their immediate residential environments, exacerbating isolation and loneliness, which are risk factors for depression.^52,53 We found that chronic conditions that were associated with depressive symptoms were cataract and urinary tract disorder. The former impaired vision, while the latter had substantial literature supporting its association with poor mental health, psychological distress, and low quality of life from embarrassment and anxiety of urinary leakage in public situations, and self-restriction on usual daily activities.^54,55 Reverse causation could also explain these associations. Depression may have reduced their motivation for proper self-care and to socialise, and depression may have affected their ability to follow their treatment regime for chronic illnesses leading to worse health outcomes.

Better self-perceived mental health and life satisfaction had dose–response relationships with less depressive symptoms. Literature corroborated that perceiving to have social support, concern from others, a sense of belonging, and access to neighbours were associated with less psychological distress.⁵⁶ General physical and psychological health status have shown to have a strong impact on life satisfaction.⁵⁷ For our study, life satisfaction encompassed a broad range of indicators like health status, financial status, relationship with family (spouse, children, siblings) and others (friends, neighbours), community environment, and leisure. This suggested complexity in assessing the well-being of older adults, which required a more integrative approach to prevent depression.

Our study revealed key public health implications for developing interventions to mediate factors associated with depressive symptoms among older adults residing in SAs or residences of comparable environments, especially to prevent the onset of clinical depression. There is a necessity for social support in immediate environments of older adults, particularly those who are widowed. Resources should be allocated to providing social-care services in community-based settings around SAs, such as senior activity centres, befriending services, and socio-recreational facilities, to enable older adults with physical function difficulties to engage in some social activity to minimise isolation and loneliness. Exercise facilities and programs should be accessible to increase exercise behaviour, which may result in a slower progression of loss of physical function and increased social interaction.

Strengths and limitations

Our study was the first to examine the factors associated with depressive symptoms in older adults in Singapore living in SAs, with results potentially applicable to other ageing countries with older adults in similar living arrangements who risk suffering from depression. Our study examined intra/inter-personal, physical, clinical, and psychosocial factors. However, independent variables were self-reported, with potential recall errors and biases. Chronic conditions may be under-reported due to under-diagnosis by persons of lower socioeconomic backgrounds and reporting error by older adults due to memory issues or reluctance to share medical history. Despite substantial efforts to minimise non-response rates described earlier in the paper, we recognise that a response rate of 49.7% may be suboptimal. However, we need to consider that our target population was older adults who may have medical conditions, physical disabilities, lower cognitive function, and from an older generation that is largely conservative towards sensitive topics like mental health. Regarding the likely directionality of non-response bias, persons who declined contact were likely more incapacitated from medical conditions and physical disabilities, had lower cognitive function, were of a lower socioeconomic status, and were of the ‘oldest old’, and, hence, likely to suffer more depressive symptoms. Our findings on the associations between independent variables and depressive symptoms are likely underestimated. The CES-D eight-item scale could not diagnose depression, but is a good tool for assessing depressive symptoms and is validated in Europe and America^27,28 (high Cronbach’s alpha of 0.85 in this study). The study population was older adults residing in SAs; hence, our findings cannot be extrapolated to other older adult populations. The cross-sectional design limited causal interpretations, but future studies could utilise prospective designs.

Conclusion

Factors including widowhood, physical functioning difficulty, chronic conditions, low social support, low self-perceived mental health, poor life satisfaction, and lack of exercise behaviour, were associated with depressive symptoms in older adults residing in SAs. More attention is needed to care for the psychosocial and physical needs of older adults in SAs.

Supplemental Material

Supplementary_Appendix_revised_12_May2019 – Supplemental material for Psychosocial and physical factors associated with depression in older adults living in studio apartments: A cross-sectional study of a multi-ethnic Asian population

Supplemental material, Supplementary_Appendix_revised_12_May2019 for Psychosocial and physical factors associated with depression in older adults living in studio apartments: A cross-sectional study of a multi-ethnic Asian population by Grace Sum, Yun Ru Tan, Song-Iee Hong and Gerald Choon-Huat Koh in Proceedings of Singapore Healthcare

Footnotes

Acknowledgements

None.

Author’s contributions

G Koh and SI Hong contributed to the conception and design of this research and collected the primary data from older adults living in the SAs. G Sum contributed by writing the first and subsequent drafts of the manuscript and interpreted the findings. YR Tan conducted data analysis and interpreted findings. All authors revised the manuscript for important intellectual content.

Availability of data and materials

There is no additional unpublished data from this study.

Declaration of conflicting interests

None declared.

Ethical approval

Ethics approval was obtained from the Institutional Review Board of the National University of Singapore (NUS-IRB Reference Code 12-021).

Funding

G Sum was funded by the President’s Graduate Fellowship, National University of Singapore. G Koh was supported by the Singapore Ministry of Health’s National Medical Research Council under the Centre Grant Programme, Singapore Population Health Improvement Centre (NMRC/CG/C026/2017_NUHS).

Informed consent

Written informed consent was obtained from the subjects for their anonymised information to be published in this article.

Supplementary material

Supplemental material for this article is available online at

ORCID iD

Grace Chi-En Sum

References

United Nations, Department of Economic and Social Affairs, Population Division. World population ageing 2015 (ST/ESA/SER.A/390). New York: United Nations, 2015.

World Health Organisation. Ageing and life-course, http://www.who.int/ageing/en/ (2019, accessed 20 December 2018).

World Health Organisation. Mental health of older adults, http://www.who.int/news-room/fact-sheets/detail/mental-health-of-older-adults (2017, accessed 20 December 2018).

Ormel

Kempen

Deeg

, et al. Functioning, well-being, and health perception in late middle-aged and older people: comparing the effects of depressive symptoms and chronic medical conditions. J Am Geriatr Soc 1998; 46: 39–48.

Pynoos

The future of housing for the elderly: four strategies that can make a difference. Public Policy Aging Rep 2018; 28: 35–38.

Chi

Chow

Housing and family care for the elderly in Hong Kong. Ageing Int 1997; 23: 65–77.

Addae-Dapaah

Age segregation and the quality of life of the elderly people in studio apartments. J Housing Elderly 2008; 22: 127–161.

Lee

Kim

Prevalence and risk factors for self-neglect among older adults living alone in South Korea. Int J Aging Human Dev 2014; 78: 115–131.

Wan Mohd Azam

Din

Ahmad

, et al. Loneliness and depression among the elderly in an agricultural settlement: mediating effects of social support. Asia Pac Psychiatry 2013; 5(Suppl 1): 134–139.

10.

Kramarow

EA.

The elderly who live alone in the United States: historical perspectives on household change. Demography 1995; 32: 335–352.

11.

Nomura

McLean

Miyamori

, et al. Isolation and unnatural death of elderly people in the aging Japanese society. Sci Justice 2016; 56: 80–83.

12.

Ryuta

Yasuhisa

Youichi

, et al. Living alone is associated with depression among the elderly in a rural community in Japan. Psychogeriatrics 2012; 12: 179–185.

13.

Kwon

Jeong

Choi

Social relationships and suicidal ideation among the elderly who live alone in Republic of Korea: a logistic model. Inquiry 2018; 55: 46958018774177.

14.

Chou

K-L

Chi

Boey

KW.

Determinants of depressive symptoms among elderly Chinese living alone. Clin Gerontol 2000; 20: 15–27.

15.

Tong

Lai

Zeng

, et al. Effects of social exclusion on depressive symptoms: elderly Chinese living alone in Shanghai, China. J Cross Cult Gerontol 2011; 26: 349–364.

16.

Tiong

Yap

Koh

GCH

, et al. Prevalence and risk factors of depression in the elderly nursing home residents in Singapore. Aging Ment Health 2013; 17: 724–731.

17.

X-Y

Cheng

Peng

X-D

, et al. Living arrangements and risk for late life depression: a meta-analysis of published literature. Int J Psychiatry Med 2012; 43: 19–34.

18.

Wee

Yong

Chng

MWX

, et al. Individual and area-level socioeconomic status and their association with depression amongst community-dwelling elderly in Singapore. Aging Ment Health 2014; 18: 628–641.

19.

Teo

Space to grow old in: the availability of public spaces for elderly persons in Singapore. Urban Stud 1997; 34: 419–439.

20.

Housing Development Board, Singapore. Types of flats, http://www.hdb.gov.sg/cs/infoweb/residential/buying-a-flat/new/types-of-flats (2019, accessed 2 March 2019).

21.

Housing Development Board, Singapore. HDB flat, http://www.hdb.gov.sg/cs/infoweb/residential/buying-a-flat/new/hdb-flat&rendermode=preview (2019, accessed 2 March 2019).

22.

Carleton

Thibodeau

Teale

, et al. The center for epidemiologic studies depression scale: a review with a theoretical and empirical examination of item content and factor structure. PLOS ONE 2013; 8: e58067.

23.

Kohout

Berkman

Evans

, et al. Two shorter forms of the CES-D (Center for Epidemiological Studies Depression) depression symptoms index. J Aging Health 1993; 5: 179–193.

24.

Boey

KW.

Cross-validation of a short form of the CES-D in Chinese elderly. Int J Geriatr Psychiatry 1999; 14: 608–617.

25.

American Psychological Association. Center for Epidemiological Studies-Depression, http://www.apa.org/pi/about/publications/caregivers/practice-settings/assessment/tools/depression-scale.aspx (2019, accessed 2 March 2019).

26.

Stahl

Sum

Lum

, et al. Screening for depressive symptoms. Validation of the Center for Epidemiologic Studies Depression Scale (CES-D) in a multiethnic group of patients with diabetes in Singapore. Diabetes Care 2008; 31: 1118–1119.

27.

Karim

Weisz

Bibi

, et al. Validation of the eight-item Center for Epidemiologic Studies Depression Scale (CES-D) among older adults. Curr Psychol 2015; 34: 681–692.

28.

Steffick

DE.

Documentation of affective functioning measures in the health retirement study. Report, Survey Research Center, University of Michigan, USA, 2000.

29.

Lim

Lee

Hatim

, et al. Clinical and sociodemographic correlates of suicidality in patients with major depressive disorder from six Asian countries. BMC Psychiatry 2014; 14: 37.

30.

Park

Han

Kim

, et al. Predictors of suicidal ideation in older individuals receiving home-care services. Int J Geriatr Psychiatry 2014; 29: 367–376.

31.

Hong

S-I

Han

C-K.

Asset impacts on life satisfaction in an asset-rich country: focusing on older adults in Singapore. Social Ind Res 2014; 118: 125–140.

32.

Lysack

CL.

Household and neighborhood safety, mobility. In: Lichtenberg

(ed) Handbook of assessment in clinical gerontology. 2nd ed. San Diego, CA: Academic Press, 2010, pp.619–646.

33.

Shin

Sims

Bradley

, et al. Prevalence of depressive symptoms and associated factors in older adult public housing residents. Res Gerontol Nurs 2014; 7: 249–255.

34.

Bojrab

Sipes

Weinberger

, et al. A model for predicting depression in elderly tenants of public housing. Hosp Community Psychiatry 1988; 39: 304–309.

35.

Qadir

Haqqani

Khalid

, et al. A pilot study of depression among older people in Rawalpindi, Pakistan. BMC Res Notes 2014; 7: 409.

36.

Mendes

Leon

Kasl

Jacobs

A prospective study of widowhood and changes in symptoms of depression in a community sample of the elderly. Psychol Med 1994; 24: 613–624.

37.

Williams

Zhang

Packard

KC.

Factors affecting the physical and mental health of older adults in China: the importance of marital status, child proximity, and gender. SSM Popul Health 2017; 3: 20–36.

38.

Heuberger

Wong

The association between depression and widowhood and nutritional status in older adults. Geriatr Nurs 2014; 35: 428–433.

39.

Alexopoulos

GS.

Depression in the elderly. Lancet 2005; 365: 1961–1970.

40.

Jozwiak

Preville

Vasiliadis

HM.

Bereavement-related depression in the older adult population: a distinct disorder?

J Affect Disord 2013; 151: 1083–1089.

41.

Kennedy

GJ.

The geriatric syndrome of late-life depression. Psychiatr Serv 1995; 46: 43–48.

42.

Rioux

The well-being of aging people living in their own homes. J Environ Psychol 2005; 25: 231–243.

43.

Rioux

Werner

Residential satisfaction among aging people living in place. J Environ Psychol 2011; 31: 158–169.

44.

Kendig

Dykstra

van Gaalen

, et al. Health of aging parents and childless individuals. J Fam Issues 2007; 28: 1457–1486.

45.

Belvederi Murri

Amore

Menchetti

, et al. Physical exercise for late-life major depression. Br J Psychiatry 2015; 207: 235–242.

46.

Mammen

Faulkner

Physical activity and the prevention of depression: a systematic review of prospective studies. Am J Prev Med 2013; 45: 649–657.

47.

Teixeira

Wender

Goncalves

, et al. Dizziness, physical exercise, falls, and depression in adults and the elderly. Int Arch Otorhinolaryngol 2016; 20: 124–131.

48.

Moraes

Deslandes

Ferreira

, et al. Physical exercise in the treatment of depression in elderly: a systematic review. Rev Psiquiatr Rio Gd Sul 2007; 29: 70–79.

49.

Wen

Hebscher

Lee

SH.

Instrumental activities of daily living in remitted late-life depression: a preliminary study. Int J Geriatr Psychiatry 2014; 29: 109–110.

50.

Kivela

SL.

Depression and physical and social functioning in old age. Acta Psychiatr Scand Suppl 1994; 377: 73–76.

51.

McKnight

Kashdan

TB.

The importance of functional impairment to mental health outcomes: a case for reassessing our goals in depression treatment research. Clin Psychol Rev 2009; 29: 243–259.

52.

Gan

Xie

Duan

, et al. Rumination and loneliness independently predict six-month later depression symptoms among Chinese elderly in nursing homes. PLOS ONE 2015; 10: e0137176.

53.

Tsai

YF.

Changes in depressive symptoms, social support, and loneliness over 1 year after a minimum 3-month videoconference program for older nursing home residents. J Med Internet Res 2011; 13: e93.

54.

Chin

Choi

EPH

Wan

EYF

, et al. The mediating factors in the relationship between lower urinary tract symptoms and health-related quality of life. BMC Res Notes 2017; 10: 611.

55.

Wong

Hong

Leung

, et al. Lower urinary tract symptoms and depressive symptoms in elderly men. J Affect Disord 2006; 96: 83–88.

56.

Forsman

Nyqvist

Wahlbeck

Cognitive components of social capital and mental health status among older adults: a population-based cross-sectional study. Scand J Public Health 2011; 39: 757–765.

57.

Helvik

Engedal

Krokstad

, et al. A comparison of life satisfaction in elderly medical inpatients and the elderly in a population-based study: Nord-Trondelag Health Study 3. Scand J Public Health 2011; 39: 337–344.

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