Social contextual factors, social support and accessibility of social services in the health and life satisfaction of family caregivers in Hong Kong

Abstract

Purpose

Health issues and life satisfaction among family caregivers have attracted significant public and scholarly attention, but research on socio-demographic and social contextual factors contributing to family caregivers’ burdens remains limited in scope. This study aims to assess the factors associated with subjective health, mental health and life satisfaction among family caregivers based on a representative community sample of Hong Kong families.

Methods

The analysis was performed using the Family Survey, a territory-wide household survey conducted in Hong Kong. The data for the current study included 1,647 family members in either nuclear families or extended households. A three-phase multivariate regression analysis was carried out to investigate the associations between a variety of social contextual factors and physical health, mental health, as well as life satisfaction.

Results

Results show that female caregivers experience significant psychological health burdens, older caregivers face physical health burdens, unemployment impacts overall life satisfaction, and lower monthly income and smaller living spaces contribute significantly to physical health and life satisfaction. Additionally, primary caregiving roles are associated with lower life satisfaction, while a higher level of perceived social support leads to better health and a higher level of life satisfaction. No significant relationship was found between caregiving duties and constraints on accessing social services for assistance.

Conclusion

The study highlights the importance of enhancing social support and economic assistance for caregivers, particularly for women and the elderly, to alleviate psychological and physical burdens. Future services should focus on improving accessibility to social service resources and developing targeted programs to address these specific needs.

Introduction

In recent years, there has been a growing trend to prioritize comfort and reduce medical expenses, leading more families to opt for home-based care over traditional hospitals [1]. Unlike formal caregivers who provide professional assistance or services for a fee, informal or family caregivers provide non-professional and free basis care to family members, relatives or friends due to aging, long-term disease and disability [2]. A primary caregiver is a caregiver who performs round-the-clock care for their care recipient, while a secondary caregiver is a caregiver who supports a primary caregiver in providing care to their care recipient [3]. Regardless of caregiving duties, extensive research notes that family caregivers experience a significant burden when providing care to family members, relatives or loved ones with specific illnesses [4], chronic diseases [5] and disabilities [6]. The physical, psychological, social, and financial demands of caregiving are termed caregiver burden [7]. Caregiver burden has been studied to understand the multidimensional responses to physical, psychological, emotional, social, and financial stressors associated with the at-home caregiving experience [8–9]. Previous research has indicated that family caregivers show poor physical health [10], poor mental health (e.g., increased depressive and anxiety symptoms) [11], lower levels of life satisfaction [12], and social exclusion [13]. In addition, evidence reveals an association between the effects of caregiving on various socioeconomic outcomes, such as financial difficulties [14] and income reduction [15]. Socioeconomic factors are considered crucial determinants of caregiver’s health, mental health, and life satisfaction. These findings emphasize that caregiver stress is common and is caused by the ongoing social, family, and socioeconomic strains of caregiving. Unpacking the specific individual, family factors and shared social contextual factors among family caregivers in Hong Kong may help reconcile the caregiving burdens and health-related issues and improve general life satisfaction.

Caregiver burden is a broadly recognized concept referring to the extent to which caregivers perceive their physical health, mental health, social life, and financial state because of the caregiving [16]. Much of the existing research has taken a holistic approach to conceptualizing a caregiver burden by investigating physical, psychological, emotional, social, and financial problems experienced by various caregiving duties and roles [17–19]. For example, caregivers’ burdens can be applied to adults caring for chronically ill elderly [20], individuals caring for family members with disability [21], as well as parents caring for their children with chronic diseases or disability [22]. Caregivers’ burdens are associated with declining physical and psychological health [23] and poorer quality of life [24]. Negative caregiving experiences could lead to various physical and mental health symptoms, including physical strain [25], anxiety [26], and depression [27]. Caregivers’ health conditions have a strong influence on the caregiver’s well-being because family caregivers often neglect their health problems that are likely aggravated by caregiving duties [23]. Strong associations were found between stressful caregiving situations and the caregiver’s decreasing general well-being [28]. Particularly, higher caregiver burden and poorer mental health are found among caregivers cohabiting with the care recipient [29]. Stressed caregivers may interact negatively with care recipients and provide poor emotional support daily. Not only that, caregivers’ gender has been suggested to be a major determinant of the caregiving experience and a gender difference was found in caregiving duties, coping styles, and access to formal and informal social services [30–32]. Thus, research on gender differences in health, mental health and life satisfaction in the informal care context is required to ascertain whether female family caregivers may be a particularly vulnerable group in Hong Kong.

Increasing attention has been paid to understanding the economic costs and financial complications associated with caregiver stress. Research has consistently found that the direct and indirect costs of caregiving increase the financial burden for family caregivers, such as increased caregiving time [33], loss of gross income [34], and disruptions in regular employment [35]. Hence, a caregiver’s health correlates and general well-being vary by socio-demographic factors, including gender [36], age [37], and income level [38]. However, it is not well understood to what extent these factors are positively or negatively associated with caregiving experiences and intensity [39]. Limited studies have investigated the association between the socioeconomic impacts of family care and caregivers’ life satisfaction and health, comparing family caregivers with different socioeconomic stressors.

From an ecological point of view, caregiving involves multiple settings and contexts in which both caregivers and care recipients are actively linked [40]. The social-ecological model emphasizes how individuals are linked to dynamic social systems at individual, interpersonal, and community levels [41]. Thus, social support resources reflect the ongoing dynamic transactions that include individuals, families, communities, and society [42]. Based on the social support theory, social support provided by peers, families and professionals is needed not only for caregivers to continue caregiving roles but also to reduce distress and burdens for both caregivers and family members [43]. Consistent evidence has shown that the level of social support can explain differences between the stresses experienced by family caregivers in various situations [44–45]. In addition, strong associations between the availability of social support and psychosocial distress and health issues have been reported in previous empirical studies [46–47]. Lower levels of social support are associated with depressive symptoms and lower levels of mental well-being among family caregivers [48]. These challenges contribute to a wide range of adverse physical and mental health outcomes, as well as the increased risk of suicide and homicide [49]. The relevant work revealed that thoughts of suicide were common among caregivers [50], and family caregivers might be at higher risk of suicide ideation, and some of them might develop the following homicide ideation [51]. Suicidal and homicidal thoughts in family caregivers are existing challenges that warrant further consideration in both research and practice.

Regarding the social context of Hong Kong, a body of research has consistently found that collectivistic cultural values such as familism influence caregiver outcomes through social support [52–53]. Specifically, a Chinese study revealed that familial obligations and certain cultural values (e.g., prioritizing the collective well-being of the family) predict poorer subjective health and mental health [54]. The endorsement of traditional collectivistic family values and beliefs on caregiving may lead to experience of extra burdens due to the unwilful caregiving duties with the lack of alternative suitable placements. Given that some individuals and families do not reach out for help due to filial piety and obligations based on respect and obedience to family members’ demands [52], the currently available social support resources may not be sufficient to address the burden among Hong Kong family caregivers. Previous studies have revealed that coping resources involved in caregiving are limited for the aging population of family caregivers in Hong Kong as older spouses have increasingly become the primary caregivers for older adults [55–56]. Increasing attention has been paid to caregiver protection policies in Hong Kong, including the Chief Executive’s 2022 Policy Address [57], which identifies caregiver support as one of the important directions in the annual planning policies. The Hong Kong Legislative Council [58] initiated a special sub-committee on developing caregiver-centered policies in 2023 [59]. Hence, the previous findings and government policies illuminate the importance of considering adequate support provided to family caregivers in Hong Kong, especially focusing on the development of culturally responsive and appropriate social services at the community level.

To add a layer to the study of predictors of family caregivers’ general life satisfaction and health correlates, it is necessary to examine how these predictors differ by caregiving roles. In the family caregiver literature, research has primarily focused on the stressors or risk factors that impact the primary caregivers in terms of quality of life [60], psychological and physical consequences [61], and caregiver burden [62]. Several studies suggest that the nature of the caregiving role, in terms of the timing of entry, responsibilities, and duration, affects the social, physical, and emotional health of the caregiver over time [63–64]. However, little is known about the variations between primary/major and secondary/non-major caregiving roles. Family caregiving ranges from assistance with daily activities to providing direct and intense care to the care recipient, but few studies explicitly distinguish among the roles and duties of family caregivers. Given that family caregivers’ roles are highly variable across the caregiving experience, it is important to explore the differences in caregiving experiences across primary and secondary roles. Such understanding would encourage the development of family-centered interventions to address the health and mental health issues of different types of family caregivers, ultimately benefiting their general health and well-being.

Building on past literature that shows the caregiver burden reflects multifaceted and multileveled stresses and strains, individual and specific socioeconomic factors may not be sufficient to address the health and well-being consequences of caregiving. In addition, previous studies examined the relationships between caregivers’ burdens and physical health, mental health, and life satisfaction separately. By using a non-clinical, heterogeneous community-based sample in Hong Kong, this study aims to (1) explore the individual and family characteristics of family caregivers in Hong Kong; (2) identify the socio-demographic and social contextual factors associated with caregiving and family caregivers’ roles on physical health, mental health, and life satisfaction; (3) investigate the associations among the protective factors including social support and accessibility of social services, physical health, mental health and life satisfaction.

Methods

Study sample and data collection

This territory-wide Family Survey was conducted by our team to investigate the health, mental health, and well-being of family caregivers among families in Hong Kong. The Government of Hong Kong commissioned the Family Survey and provided updated, evidence-based data on changes and developments among Hong Kong families.

The Family Council, an advisory body set up by the Government of the Hong Kong Special Administrative Region, commissioned a research team to conduct a “Consolidation of Findings of Family Surveys Conducted since 2011”. The research team conducted the fieldwork for the Questionnaire Survey from November 2021 to May 2022. A sample list was obtained from the Census & Statistics Department (C&SD) based on the frame of quarters maintained by the C&SD, including the Register of Quarters and the Register of Segments.

A two-stage stratified sample design was adopted for the Survey. In the first stage, a list of quarters was randomly sampled by geographical area and type of quarters, etc. The target respondents of the Survey were persons aged 15 or above residing in Hong Kong (excluding foreign domestic helpers) at the time of enumeration and able to speak Cantonese/Putonghua or read Chinese/English. In the second stage, a household member except domestic helpers aged 15 or above was randomly selected by adopting the last birthday method. Permission by at least one parent or legal guardian is required for a participant who is under 18. If there was more than one household in the sampled quarter, one household was randomly sampled. A total of 3,650 quarters were sampled, and after excluding 568 invalid cases, 3,082 cases completed the questionnaire in any form. Respondents received invitation letters with QR codes before the survey. They could either scan the QR code and self-administer the questionnaire through the online survey platform. The trained interviewers rearranged the interviews for respondents who did not respond by the deadline and conducted telephone or face-to-face interviews with the sampled respondents. Given a response rate of 65.2%, a total of 2,010 individual responses were successfully enumerated. In this study, we only included respondents living in either a nuclear family household or an extended family; ultimately, 1,647 individual responses were used in the analysis.

Ethics approval

In accordance with the Declaration of Helsinki, the study protocol and ethics approval were reviewed and approved by the Institutional Review Board of the authors’ affiliated university. Informed consent was obtained from all participants in the study.

Measures

Demographics

Several demographic variables, including age, gender, marital status, and education level, were collected. The gender was coded as 0 = “Male” or 1 “Female.” Marital status was coded as 0 = “Married or cohabiting with a partner” or 1 = “Not married or separated or divorced or widowed.” Education level was coded on a 3-point scale (0 = “Primary or lower education;” 2 = “Secondary education;” 3 = “Post-secondary education or above”).

Outcome measures

The participants were asked to rate their physical health on a single five-point Likert scale item, ranging from 1 (excellent) to 5 (very bad). A higher score indicated the participant’s perceptions of bad physical health.

The index regarding the frequency of anxiety and depression symptoms in the past 2 weeks were measured by a 4-item Patient Health Questionnaire-4 (PHQ-4) [65]: (1) “feeling bored doing anything or not wanting to do anything at all,” (2) “feeling down, depressed, or hopeless,” (3) “feeling nervous, uneasy, or irritable,” and (4) “inability to stop or control worry.” Respondents indicated their level of agreement on a four-point Likert scale (ranging from 1 = almost never to 4 = frequently). The advantage of the PHQ-4 over the PHQ-9 is that it is a brief screener of both depression and anxiety, which could facilitate a more targeted and time-efficient assessment [66]. All items were translated into Chinese. The sum-to-scale of the items was computed using an unweighted sum of all PHQ-4 items, with a higher score indicating the participant’s perceptions of poor mental health. The Cronbach reliability statistics for this scale were satisfactory (α = 0.89).

Overall life satisfaction among the respondents was measured by a 5-item Satisfaction with Life Scale (SWLS) [67]: (1) General life satisfaction (generally speaking, my current life is quite close to my ideal life), (2) Satisfaction with the living situation (my living situation is very ideal), (3) Satisfaction with life (I am satisfied with my life), (4) Satisfaction with resource accessibility (so far I have been able to get the things I want in my life), and (5) Satisfaction with my current situation (if I could live my life over again, I wouldn’t make drastic changes). Items were rated separately on Likert scales ranging from 1 (very satisfied) to 5 (very dissatisfied). All items were translated in Chinese. The sum-to-scale of the items was computed using an unweighted sum of all SWLS measures, with a higher score indicating less life satisfaction among the participants. The Cronbach reliability statistics for this scale were satisfactory (α = 0.96).

Socio-economic status (SES) factors

Participants employment status was coded as 0 = “Employed,” or 1 = “Unemployed.” We referred to the classification by the Census and Statistics Department of Hong Kong (calculated by family total monthly income per household members) and categorized the family monthly income into two groups (1 = “below median family monthly income of Hong Kong;” 2 = “above median family monthly income of Hong Kong”). For the ratio of rent or mortgage to family income, respondents were asked to report their price-to-rent ratio or percentage of mortgage covered by their monthly income. The item was coded as 1 = “Under 30%,” 2 = “30%-49%,” 3 = “50% or above.” The average living space per person was calculated by the total household living space divided by household members. The item was coded as 1 = “Below median,” 2 = “above median,” based on the standard of median per capita floor area of accommodation in Hong Kong (Hong Kong 2021 Population Census - Thematic Report: Persons Living in Subdivided Units, n.d.).

Presence of chronic illness and disability

Participants were asked to report their health problems: whether they had chronic illness or disability. The question item was coded as follows: 0 (none), 1 (disabled), 2 (being chronically ill), 3 (children with learning disability or special educational needs (SEN), and 4 (elderly with poor self-care ability). A value of 0 was coded as “not having chronic illness and disability,” and values 1 through 4 were coded as “had chronic illness and disability.”

Caregiving role

Participants were asked to report whether they served as caregivers in their families. The question item was coded as follows: 0 (none), 1 (caregiver of disabled care-dependent), 2 (caregiver of chronically ill care-dependent), 3 (caregiver of children with SEN), and 4 (caregiver of elderly care-dependent with poor self-care ability). A value of 0 was coded as “non-caregiver” and values 1 through 4 were coded as “caregiver.” Participants were then asked whether they served as their family members’ major/primary caregivers. The question was coded as 0 (non-major caregiver) and 1 (major/primary caregiver). A value of 0 from caregiver item combining a value of 0 from major caregiver item was coded as “Individual without caregiving role,” a value of 1 from caregiver item combining a value of 1 from major caregiver item was coded as “Individual with primary caregiving role,” and a value of 1 from caregiver item combining a value of 0 from major caregiver item was coded as “Individual with secondary caregiving role.”

Perceived social support

Respondents’ perceived social support was captured by the Multidimensional Scale of Perceived Social Support (MSPSS) [68]. Respondents rated the perceived social support from their families (four items; e.g., “My family really tries to help me”), friends (four items; e.g., “I can count on my friends when things go wrong”), and significant others (four items; e.g., “There is a special person in my life who cares about my feelings”) on a seven-point Likert scale (ranging from 1 = extremely disagree to 7 = extremely agree). All items were translated into Chinese. A higher score indicated a greater level of social support from family members, important others and friends. The Cronbach reliability statistics for this scale were satisfactory (α = 0.95).

Access to social services

The participants were asked whether they had access to family-related promotional activities (1 item). Participants reporting “yes” to the question were regarded as having access to informal social services. The participants were then asked whether they had access to formal service programs organized by the Government, NGOs, or religious groups (1 item). Participants reporting “yes” to the question were regarded as having access to formal social services. The questions were recorded based on the answers to these two items: 0 = “No access to any social services” or 1 = “Had some access to informal or formal social services.”

Data analysis

Descriptive analyses were first conducted to summarize and compare the participants’ demographic characteristics, including age, gender, marital status, and education attainment level. Descriptive data were also calculated to analyze the predictors of SES and other predictors, including caregiving role, presence of disability or chronic illness, perceived social support, and participation in social services. Further, outcome variables and all the predictor variables were compared between male and female respondents using chi-square tests and t-tests to examine potential gender differences. We also explored the differences between families with care dependent and families without care dependent. Next, a series of hierarchical regression analyses (i.e., multivariate and ordinal regression models) were performed to estimate the associations among the demographic, SES, family, community factors, and the caregiver’s physical health, mental health and life satisfaction outcomes while controlling for demographic characteristics. We checked the assumptions of multiple regression that were not robust to the violation, including linearity, reliability of measurement, homoscedasticity, and normality. This approach enabled the consideration of the relative contributions of each domain of predictors. In the first phase of regression analyses, demographic characteristics and SES predictors were entered as independent variables. In the second phase of regression analysis, the presence of disability or chronic illness and caregiving role were added as higher-level predictors. The final regression models included variables of perceived social support and participation in social services, followed by all previous variables in an additive and gradual manner. Three outcome variables (i.e., physical health, mental health and life satisfaction) remained the dependent variable in all models. While a series of multiple linear regressions were used on continuous outcomes (e.g., mental health and life satisfaction), a series of multiple ordinal regressions were used on the categorial outcome of physical health. Statistical analyses were completed using R software version 4.2.3 and the significance level was determined by two-tailed tests with a p-value less than 0.05 deemed significant.

Results

Participant characteristics

Table 1 shows the demographic characteristics of the respondents by gender. Among all respondents who completed the survey (N = 1,647), 47.24% (n = 778) were males and 52.76% (n = 869) were females. The respondents’ mean age was 47.68 (SD = 15.86), with a significant gender difference (t = 5.198, p < 0.001). In terms of marital status, a majority of respondents reported married or cohabiting with a partner (90.02%), with a significant gender difference for male participants (97.30%) and female participants (89.18%) who were married or cohabiting with a partner (t = -6.743, p < 0.001). Notably, more female participants were reporting separated/divorced/widowed (10.82%) than male participants (2.70%). A total of 17.73% of the overall sample completed primary education, 42.44% completed secondary education and 39.83% completed secondary education or above. For SES predictors, a small proportion of respondents were unemployed (4.86%). More female respondents reported below-average living space (81.59%) than male respondents (76.35%). Gender differences were also observed in some individual and family parameters. More male respondents reported the presence of disability or chronic illness (20.95%), while more female participants were major caregivers in their families (13.81%). Females perceived less social support (t = -2.671, p = 0.008), reported poorer physical health (t = -2.308, p = 0.021), and poorer mental health (t = -0.310, p = 0.002).

Table 1.

Demographic characteristics of the participants

	Total (N = 1647)	Male Respondents (n = 778)	Female Respondent (n = 869)	Chi-Square or t-Statistic	df	p-value
Household size (Mean, SD)	3.15 (0.98)	3.14 (0.96)	3.16 (0.10)	-0.487	1637	0.626
Gender
Male	47.24%
Female	52.76%
Age (Mean, SD)	47.68 (15.86)	49.82 (16.24)	45.77 (15.27)	5.198	1598	< 0.001
Marital status
Married or cohabiting with a partner	1532 (90.02%)	757 (97.30%)	775 (89.18%)	-6.743	1338	< 0.001
Separated/divorced/widowed	115 (6.98%)	21 (2.70%)	94 (10.82%)
Educational attainment
Primary education or lower	292 (17.73%)	135 (17.35%)	157 (18.06%)	-0.766	1534	0.444
Secondary education	699 (42.44%)	341 (43.83%)	358 (41.20%)
Post-secondary education	656 (39.83%)	302 (38.82%)	354 (40.74%)
Socioeconomic Status (SES)
Unemployment	80 (4.86%)	37 (4.76%)	43 (4.95%)	-0.181	1631	0.856
Family monthly income (in HKD)
Below median family monthly income	883 (53.61%)	422 (54.24%)	461 (53.05%)	-0.484	1626	0.628
Above median family monthly income	764 (46.39%)	356 (45.76%)	408 (46.95%)
Ratio of rent or mortgage/Family income (Mean, SD)	14.96 (16.47)	14.19 (16.83)	15.65 (16.11)	-1.783	1607	0.075
Under 30%	1445 (87.74%)	685 (88.05%)	760 (87.46%)	0.007	1616	0.995
30 − 49%	112 (6.80%)	48 (6.17%)	64 (7.36%)
50% or above	90 (5.46%)	45 (5.78%)	45 (5.18%)
Per capita living space/average living space per person (Mean, SD)	155.59 (70.21)	160.79 (70.57)	150.93 (69.60)	2.847	1620	0.005
Below median	1303 (79.11%)	594 (76.35%)	709 (81.59%)	2.602	1581	0.009
Above median	344 (20.89%)	184 (23.65%)	160 (18.41%)
Presence of Disability or chronic illness Caregiving roles	285 (17.30%)	163 (20.95%)	122 (14.04%)	3.683	1536	< 0.001
Non-caregiver	1326 (80.51%)	639 (82.13%)	687 (79.06%)	2.119	1645	0.034
Primary caregiver	201 (12.20%)	81 (10.41%)	120 (13.81%)	-1.945	1645	0.052
Secondary caregiver	120 (7.29%)	58 (7.46%)	62 (7.13%)
Perceived social support (Mean, SD)	61.63 (11.49)	60.83 (11.24)	62.34 (11.68)	-2.671	1637	0.008
Access to social services	782 (47.48%)	370 (47.56%)	412 (47.41%)	-0.060	1625	0.953
Outcomes
Physical health (Mean, SD)	3.16 (0.93)	3.10 (0.94)	3.21 (0.91)	-2.308	1611	0.021
Mental health (Mean, SD)	2.29 (2.72)	2.07 (2.70)	2.49 (2.72)	-0.310	1627	0.002
Life satisfaction (Mean, SD)	17.55 (6.31)	17.37 (6.47)	17.70 (6.17)	-1.050	1605	0.294

Descriptive statistics and results of the chi-square and t-tests comparing outcome variables and all predictor variables between caregivers and non-caregivers are presented in Table 2. The t-test indicates a significant difference in age (t = 5.424, p < 0.001), educational attainment (t = -2.716, p = 0.007), employment status (t = 2.884, p = 0.004), and family monthly income level (t = -4.764, p < 0.001). With respect to disability and chronic illness, a significant difference was found between caregivers and non-caregivers (t = -4.951, p < 0.001). Among these families, more females served caregiving roles than males (t = 46.045, p < 0.001). Caregivers perceived less social support (t = -4.776, p < 0.001), reported poorer physical health (t = -7.955, p < 0.001), poorer mental health (t = 6.575, p < 0.001), and a lower-level life satisfaction (t = 4.413, p < 0.001).

Table 2.

Descriptive statistics by family characteristics

	Total (N = 1647)	Family with care-dependent (n = 321)	Family without care-dependent (n = 1326)	Chi-Square or t-Statistic	df	p-value
Household size (Mean, SD)	3.15 (0.98)	3.14 (1.12)	3.15 (0.94)	-0.203	437	0.840
Gender
Male	778 (47.24%)	139 (43.30%)	639 (48.19%)	1.580	490	0.115
Female	869 (52.76%)	182 (56.70%)	687 (51.81%)
Age (Mean, SD)	47.68 (15.86)	51.85 (15.20)	46.68 (15.86)	5.424	503	< 0.001
Marital status
Married or cohabiting with a partner	1532 (90.02%)	296 (92.21%)	1236 (93.21%)	0.607	466	0.544
Separated/divorced/widowed	115 (6.98%)	25 (7.79%)	90 (6.79%)
Educational attainment
Primary education or lower	292 (17.73%)	69 (21.50%)	233 (16.82%)	-2.716	481	0.007
Secondary education	699 (42.44%)	144 (44.86%)	555 (41.85%)
Post-secondary education or above	656 (39.83%)	108 (33.64%)	548 (41.33%)
Socioeconomic Status (SES)
Unemployed	80 (4.86%)	28 (8.72%)	52 (3.92%)	2.884	396	0.004
Family monthly income (in HKD)
Below median family monthly income	883 (53.61%)	209 (65.11%)	674 (50.83%)	-4.764	504	< 0.001
Above median family monthly income	764 (46.39%)	112 (34.89%)	652 (49.17%)
Ratio of rent or mortgage/Family income (Mean, SD)	14.96 (16.47)	15.05 (18.26)	14.94 (16.01)	0.097	446	0.923
Under 30%	1445 (87.74%)	277 (86.30%)	1168 (88.08%)	1.050	454	0.295
30 − 49%	112 (6.80%)	22 (6.85%)	90 (6.79%)
50% or above	90 (5.46%)	22 (6.85%)	68 (5.13%)
Per capita living space/average living space per person (Mean, SD)	155.59 (70.21)	149.94 (70.71)	156.96 (70.04)	-1.599	483	0.111
Below median	1303 (79.11%)	252 (78.51%)	1051 (79.26%)	0.296	481	0.767
Above median	344 (20.89%)	69 (21.49%)	275 (20.74%)
Disability or chronic illness	285 (17.30%)	90 (28.04%)	195 (14.71%)	-4.951	421	< 0.001
Major Caregiver		60 (66.67%)		26.683	89	< 0.001
Non-major caregiver		30 (33.33%)
Caregiving roles
Non-caregiver	1326 (80.51%)	0 (0.00%)	1326 (100%)	-23.152	320	< 0.001
Primary caregiver	201 (12.20%)	201 (62.62%)	0 (0.00%)	46.045	200	< 0.001
Male primary caregiver		81 (40.30%)
Female primary caregiver		120 (59.70%)
Secondary caregiver	120 (7.29%)	120 (37.38%)	0 (0%)	60.125	320	< 0.001
Perceived social support	61.63 (11.49)	58.69 (12.53)	62.34 (11.12)	-4.776	450	< 0.001
Access to social services (Mean, SD)	782 (47.48%)	160 (49.84%)	622 (46.91%)	-0.943	486	0.346
Outcomes
Physical health (Mean, SD)	3.16 (0.93)	3.51 (0.86)	3.07 (0.92)	-7.955	516	< 0.001
Mental health (Mean, SD)	2.29 (2.72)	3.25 (3.01)	2.06 (2.59)	6.575	442	< 0.001
Life satisfaction (Mean, SD)	17.55 (6.31)	19.00 (6.69)	17.19 (6.17)	4.413	461	< 0.001

Multivariate regression analysis

To assess whether the demographic, socioeconomics, family, and community factors would explain significant variance in physical health, mental health and life satisfaction, we conducted a series of regression analyses (see Table 3). In the multivariate regression analyses, each variable was computed with controls for other variables. Particularly, we conducted the ordinal regression analysis on physical health, while using multivariate regression analyses on mental health and life satisfaction. Model 1 showed that participants who were female (OR = 0.238, CI [0.055, 0.422], p = 0.011), elder (OR = 0.013, CI [0.006, 0.422], p < 0.001), completed primary education (OR = 0.508, CI [0.175, 0.843], p = 0.003) or secondary education (OR = 0.279, CI [0.060, 0.499], p = 0.013) were significantly associated with poorer physical health. Interestingly, younger participants were significantly associated with poor mental health (β = -0.207, p < 0.05) and a lower level of life satisfaction (β = -0.213, p < 0.001). Participants who were not in a marital or cohabiting relationship (i.e., divorce/separation/widowed) reported poor mental health (β = 0.997, p < 0.001) and a lower level of life satisfaction (β = -0.213, p < 0.001). For SES predictors, unemployment predicted poor physical health (OR = 0.561, CI [0.134, 0.992], p = 0.010), poor mental health (β = 0.997, p = 0.003), and a lower level of life satisfaction (β = 2.155, p < 0.001). Lower family income predicted a lower level of life satisfaction (β = 1.535, p < 0.001). Lower average living space predicted poor physical health (OR = 0.336, CI [0.107, 0.566], p = 0.004) and a lower level of life satisfaction (β = 1.299, p < 0.001).

Table 3.

Multivariate regression results

	Physical health		Mental health		Life satisfaction
	OR (95% CI)	p	Standardized Beta (95% CI)	p	Standardized Beta (95% CI)	p
Phase 1
Intercept	-	-	3.753*** (3.144, 4.362)	< 0.001	19.418*** (18.025, 20.811)	< 0.001
Gender
Male	-	-	-		-
Female	0.238** (0.055, 0.422)	0.011	0.188 (-0.077, 0.452)	0.279	-0.343 (-0.947, 0.261)	0.265
Age	0.013*** (0.006, 0.422)	< 0.001	-0.207*** (-0.271, -0.144)	< 0.001	-0.213*** (-0.276, -0.151)	< 0.001
Marital status
Married or cohabiting with a partner	-	-	-	-	-	-
Separated/divorced/ widowed	0.167 (-0.192, 0.529)	0.363	0.997*** (0.476, 1.517)	< 0.001	3.467*** (2.276, 4.658)	< 0.001
Education attainment
Primary education or lower	0.508** (0.175, 0.843)	0.003	-0.083 (-0.561, 0.395)	0.734	0.154 (-0.939, 1.247)	0.782
Secondary education	0.279** (0.060, 0.499)	0.013	-0.183 (-0.501, 0.134)	0.258	0.367 (-0.361, 1.093)	0.323
Post-secondary education or above	-	-	-	-	-	-
Employment status
Employed	-	-	-	-	-	-
Unemployed	0.561** (0.134, 0.992)	0.010	0.915** (0.311, 1.519)	0.003	2.155** (0.773, 3.537)	0.002
Family monthly income
Below median family monthly income of Hong Kong	0.166 (-0.023, 0.355)	0.086	0.215 (-0.057, 0.488)	0.122	1.535*** (0.911, 2.158)	< 0.001
Above median family monthly income of Hong Kong	-	-	-	-	-	-
Ratio of rent or mortgage/Family income
Under 30%	-	-	-	-	-	-
30–49%	0.039 (-0.309, 0.389)	0.825	-0.495 (-1.008, 0.018)	0.058	-0.106 (-1.278, 1.067)	0.860
50% or above	-0.233 (-0.643, 0.180)	0.268	-0.295 (-0.863, 0.272)	0.308	-0.294 (-1.592, 1.004)	0.657
Per capita living space/average living space per person
Below median	0.336* (0.107, 0.566)	0.004	0.059 (-0.272, 0.391)	0.726	1.299*** (0.541, 2.057)	< 0.001
Above median	-	-	-	-	-	-
R Square	-		0.062		0.088
Cox and Snell R Square Nagelkerke R Square N F	0.053 0.021 1647 -		- - 1647 10.830		- - 1647 15.780
df	-		1636		1636
p-value	-		< 0.001		< 0.001
Phase 2
Intercept	-	-	3.926*** (3.314, 4.538)	-	19.555*** (18.135, 20.976)	-
Presence of Disability or chronic illness	0.201 (-0.085, 0.488)	0.169	0.055* (0.001 0.109)	0.046	0.010 (-0.044, 0.064)	0.713
Caregiving role
Without care-dependent, no caregiving role	-	-	-	-	-	-
With care-dependent, major caregiving role	0.763*** (0.414, 1.118)	< 0.001	1.701*** (1.214, 2.188)	< 0.001	2.337*** (1.207, 3.467)	< 0.001
With care-dependent, secondary caregiving role	0.759*** (0.471, 1.049)	< 0.001	1.098*** (0.704, 1.491)	< 0.001	1.740*** (0.823, 2.651)	< 0.001
R Square	-		0.104		0.103
Cox and Snell R Square Nagelkerke R Square N F	0.077 0.031 1647 -		- - - 14.600		- - - 14.470
df	-		1633		1633
p-value	-		< 0.001		< 0.001
Phase 3
Intercept	-	-	9.105*** (8.197, 10.013)	-	37.096*** (35.174, 39.018)	-
Perceived social support	0.554*** (-0.660, -0.449)	< 0.001	-0.347*** (-0.389, -0.304)	< 0.001	-0.512*** (-0.547, -0.475)	< 0.001
Access to social services	0.173 (-0.009, 0.355)	0.063	0.002 (-0.041, 0.045)	0.929	0.024 (-0.015, 0.064)	0.251
R Square Cox and Snell R Square Nagelkerke R Square N	- 0.140 0.058 1647		0.215 - - 1647		0.346 - - 1647
F	-		29.760		57.640
df	-		1631		1631
p-value	-		< 0.001		< 0.001

Note. *P < 0.05, **P < 0.01, ***P < 0.001

In model 2, when we added the individuals’ health and family factors into the analysis, we found that compared with those with no family caring duties, the participants who served as primary caregivers reported poor physical health (OR = 0.763, CI [0.414, 1.118], p < 0.001), poor mental health (β = 1.701, p < 0.001), and a lower level of life satisfaction (β = 2.337, p < 0.001). Similar patterns were observed for family secondary caregivers but with relatively smaller effects (OR = 0.759, CI [0.471, 1.049], p < 0.001 on physical health, β = 1.098, p < 0.001 on mental health, and β = 1.740, p < 0.001 on life satisfaction). Individuals who reported the presence of disability or chronic illness suffered from poorer mental health (β = 0.055, p = 0.046).

In Model 3, respondents’ perceived social support and access to social services were added to the regression analysis. The results showed that perceived social support was negatively associated with poor physical health (OR = -0.554, CI [-0.660, -0.449], p < 0.001), poor mental health (β = -0.347, p < 0.001), and a lower level of life satisfaction (β = -0.512, p < 0.001). However, the regression results revealed insignificant association between social service accessibility and all three outcome variables.

Discussion

The current study expands the literature on caregiver burden by identifying the shared and unique social contextual factors on health, mental health and life satisfaction by using a community-based sample of Hong Kong families with care dependents. As the caregiver burden is a complex and multidimensional construct, our findings provide insight into how family caregivers’ health correlates and life satisfaction are affected by their demographics, SES, family caregiving roles, and the availability of social support. These socio-demographic characteristics of family and social contextual factors could guide tailored policies for family caregivers in Hong Kong.

Consistent with previous literature [39, 69], the findings of this study suggest that caregiver demographics substantially change the nature of the association between caregiving stress and caregiver’s health, mental health status, and life satisfaction. Regarding gender-specific factors, our results provide evidence confirming that female family caregivers show poorer physical health. In line with existing studies, family caregivers also show a considerable gender difference with respect to physiological features [70]. In our sample, more female family caregivers were the primary providers of informal care for their family members, indicating more burdens on their physical health because of the caregiving duties. One possible explanation for this finding is that caregivers’ physical conditions are directly related to the intensity and types of physical interaction between caregivers and recipients (e.g., transfer, bathing, and feeding). Thus, gender differences may exist in physical strength and endurance regarding caregiving duties [69]. However, no gender differences were found in mental health and life satisfaction among family caregivers in Hong Kong. In line with the existing studies, gender differences in caregivers’ mental health, quality of life and subjective burden depend on various factors, including care tasks and time [71] and cultural factors [72]. Additionally, our results indicate that elder family caregivers are more likely to experience negative physical consequences of caregiving than their younger counterparts, but not with mental health and life satisfaction. Likely, the elderly who receive more family support and social support tend to show higher levels of life satisfaction and less emotional burnout. Considering the context of Hong Kong, emotional support from family members is beneficial to the life satisfaction of the elderly [73]. Similar to previous findings, more social support may result in a lower caregiving burden, thus an experience of a higher quality of life [74]. Future social service programs should closely examine help-seeking barriers and the perceived usefulness of services targeted at younger family caregivers.

Regarding SES factors, our results suggest that unemployment is uniquely associated with all three outcome variables (mental health, physical health, and life satisfaction). The unemployment rate was higher among family caregivers (8.72%) than non-caregivers (3.92%), indicating that the caregiving burden may relate to employment status. Given that informal caregiving duties may compete with paid work time and performance, it increases the risk of psychological stressors [75]. Income differences may influence life satisfaction among family caregivers, as we found that more family caregivers reported below a median family monthly income in Hong Kong (65.11%) than non-caregivers (50.83%). This finding is in line with previous research stating that caregiver burden is associated with a lower income level [76]. Interestingly, our findings suggest that smaller living spaces can lead to caregiver stress. Previous studies have rarely included the average living space in the analysis of caregiver burden. Considering the Hong Kong context, especially the local high-density living and unequal housing space [77], the relatively smaller average living space is a unique socioeconomic stressor among Hong Kong family caregivers. Policies should prioritize resource allocation to family caregivers with low SES by expanding access to social services that promote general health and well-being.

Regarding family caregiving roles, we found stronger associations between primary caregiving duties and lower levels of health and life satisfaction compared to secondary caregivers. This coincides with prior studies that the amount of care and level of burden experienced by family caregivers vary [36], and the nature of caregiving may have various adverse effects on primary caregivers [78]. When care duties increase, primary caregivers may face significant mental health symptoms, including depressive symptoms, anxiety, irritability, or anger in the care recipient [44], and they may suffer from physical strains [79]. While much is known about the caregiving burden and its effects [9], there has been little exploration of differences between caregiving roles. Further research is needed to compare burdens between primary and secondary caregivers and to differentiate how stressors from their caregiving roles affect their physical and mental states and life satisfaction.

Our study highlights the importance of social support theory in reducing caregiver burden, as we found that higher perceived social support reported by caregivers predicted better physical and mental health, as well as higher life satisfaction. Family caregivers may benefit specifically from emotional support, which could positively influence mental health [45, 80]. Additionally, other studies indicated that higher levels of social support are associated with greater well-being and general health [48]. Our results support the implications of the social-ecological model that promoting integrated support across multiple systems, such as microsystem (family and friends), mesosystem (agency policies and institutional practices) and exosystem (government policies and regulations), is more effective in satisfying caregiver’s needs [41]. Our findings suggest future methods for preventing physical and psychological burnout from caregiving duties, ensuring that family caregivers are supported and connected to social services. This could be achieved by including more family-based services embedded in social relations that promote the well-being of caregivers instead of providing services to care recipients in isolation.

Our study yielded different results from existing studies regarding social service participation related to caregivers’ physical and psychological stress. There is evidence that the utilization of social services is positively associated with better health status and less strain [81], as well as improved mental health [46]. However, we found no relationship between participation in social services and caregiver’s physical and mental health or life satisfaction outcomes. A possible explanation for this finding is that the shame or stigma of caregiver burden may inhibit family caregivers from accessing social services. In Asian cultures, it is considered normal and proper to care for family members without complaining. This is consistent with previous studies that family caregivers have poorer access to health and social services in Hong Kong and other Asian countries [82–83]. Previous studies have noted that caregiving duties and responsibilities impact a caregiver’s ability to engage in social activities, leading to social strain and other psychological consequences [84]. Without participation in social services, family caregivers must deal with psychological distress, hopelessness, burnout, fatigue, anxiety, and depression alone. In addition, exposure to physical problems, financial hardships, social isolation, stigma, and decreased quality of life increases the risk of suicide [85] and homicide [86]. Service or intervention programs should screen for the involvement of family caregivers and consider reducing the bias and stigma associated with seeking help to support families with care dependents in need.

The limitations of this study should be considered. First, due to its cross-sectional nature, we are unable to identify causal relations between previous social and family experiences and later caregiver burden. Longitudinal designs are recommended to provide a more comprehensive understanding of caregiver burden. Second, the self-report nature has the potential for unreliability, especially in measuring multidimensional caregiver burden, and variability in the caregiver experience may have been lost. Future research should consider using the household as a unit of analysis and collect all family members’ perceptions of received support to understand the caregiver burden further. Third, alternative correlates, such as the care recipient’s health condition and severity, the duration of caregiving, and coping strategies, could also be explored in future studies to further explain the association between caregiving and health correlates and life satisfaction. Psychological and physical health issues have been found among caregivers in previous studies, particularly for those caregivers who reported the same pathological condition as the care recipient [87]. Drawing attention to the health conditions of both caregivers and recipients has implications for future research, policy, and practice. Finally, despite using a probability population study with a large sample size, the generalizability of the findings is limited to Hong Kong families. Future studies may replicate this research with other samples, including family members from different cultural and socioeconomic backgrounds.

Our findings indicate that social support for family caregivers significantly impacts reducing caregiver burden. Previous studies have found that support from family, society, and government can relieve caregivers from stress and reduce burden [88]. Social care and community care services should aim to improve the caregivers’ health and well-being and help them respond to stress. Meanwhile, our results show that family caregivers cannot fully benefit from social services due to heavy caregiving duties and cultural values in Hong Kong. In line with previous research, Chinese health belief regards mental illness as a punishment for the misconduct of family members and/or their ancestors, which may cause the neglect of their own needs and health for those caregivers adhering to this belief [89]. The negative aspects of caregivers’ responsibilities create a vicious cycle of receiving support and assistance in problem-solving. The findings inform family policy by highlighting the need for proactive and accessible social services across multiple systems and organizations. Proactive screening of families burdened with care dependents and outreach services could be made available. Intervention should not be just focused on formal institutes like hospitals and community-based psychiatric facilities but also on the force of informal social service programs and family-based workshops in neighborhoods, which is also effective in developing an indigenous service for local family caregivers. Additionally, health and mental health professionals can organize education and training programs for family caregivers to enhance their coping skills and knowledge arising from caregiving experiences. Family caregivers should also be provided with options to reduce the stress of frequent caregiving duties, such as at-home health service visits or individual contact with health professionals. Even if some family caregivers are unwilling or unable to seek help, it is recommended that family members, health professionals, and communities work together to facilitate the availability and accessibility of social services.

The findings of this study contribute to understanding the role of social support and the accessibility of social services in reducing family caregiver burden. In general, family caregivers’ social and economic burdens negatively impact their health and well-being. Regarding protective factors, the study showed that higher SES and increased accessibility to social support are beneficial. In addition, socio-demographic variations may disproportionately impact various types of caregiver burden. Future social support programs should focus on helping family caregivers get more convenient access to social services, which may alleviate various caregiver burden and burnout.

Author contributions

K.C. and Q.C. designed and directed the project. S.G. developed the theory and performed the data analysis. S.G., Q.C. and K.C. verified the analytical methods. K.C. supervised the findings of this work. All authors discussed the results and contributed to the final manuscript.

Funding

The work described in this paper was supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. PolyU 15601022) and APSS Research Fund (P0046000).

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

In accordance with the Declaration of Helsinki, the ethics approval was granted by the Institutional Review Board of the Hong Kong Polytechnic University (Reference number: HSEARS20230513001). Informed consent was obtained from all participants in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.