The Mediating Role of Loneliness in the Association between Social Isolation and Self-Rated Health in Community-Dwelling Chilean Older Adults

Aim: Research indicates that social isolation and loneliness among older adults increase the risk of poor self-rated health (SRH) and vice versa. This study examines how loneliness may mediate the relationship between social isolation and health status among older Chilean adults. Methods:This cross-sectional study included 6755 participants aged 60 and older. The social isolation concept was operationalised using a 6-item measure adapted from Zavaleta et al.’s approach; loneliness was measured using the Three-Item Lonely Scale; and SRH status was measured with a standardised question from the Chilean Quality of Life and Health Survey. An IRT-1PL model and Confirmatory Factor Analysis were used in combination to validate the psychometric properties of social isolation. A mediation analysis using generalised structural equation modelling (GSEM), adjusted for relevant confounding factors, was conducted. Results:30.4% of participants experienced social isolation, and 23.4% reported feelings of loneliness. Among those with poor SRH, 45% faced social isolation, and 37% experienced loneliness. GSEM indicated that the indirect effect of social isolation on poor SRH via loneliness was significant (β = −0.183), suggesting that loneliness was an important mediator, and the direct effect of social isolation on poor SRH was also significant (β = −0.324), indicating partial mediation. Conclusions:The association between social isolation and poor health status was significantly mediated by loneliness among Chilean older adults. The findings underscore the importance of social connectivity for the health status and well-being of older adults, and provide guidance for future interventions that promote social engagement and help older adults cope with loneliness to achieve successful ageing.

• Social Isolation
• Loneliness
• Self-Rated Health
• Mediation Analysis
• Older Adults
• Chile

1. Introduction

Globally, by 2050, the number of people aged 60 or older is projected to reach 2.1 billion, double the 2020 population. Two-thirds of the world’s population aged 60 and over will live in low- and middle-income countries (LMICs), placing these countries at a disadvantage in addressing the challenges of an ageing population, given their limited financial resources and established health and social insurance systems ([59]; [48]).

In response to this demographic shift, the societal lack of understanding about the complex ageing process and the slow adaptation of states to the ageing of the population often postpones their needs for health and social well-being, the United Nations has declared 2021-2030 as the Decade for Healthy Ageing, urging countries to provide adequate health and social care to address physical, mental and community engagement to contribute to a healthy ageing and wellbeing in older adults ([53]; [56]).

Healthy Ageing means more than merely avoiding illness; it involves maintaining physical, psychological, mental, and social abilities and conditions while ensuring a safe environment, thereby contributing to a better quality of life and well-being among older adults. This plan also tries to protect the rights of older people and combat age discrimination, neglect, abuse, and violence, as well as to reduce social isolation and loneliness and socioeconomic marginalisation among older persons, among other crucial issues ([53]; [56]).

However, it is essential to acknowledge that older adults are a highly heterogeneous population, and the health and social challenges they face vary significantly based on factors such as their health status, socioeconomic background, and cultural context ([48]).

An ageing population is associated with a rise in age-related health issues, such as frailty, cardiovascular, metabolic and mental diseases or disability. Overall, the states face, with varying degrees of success, the increasing demand for healthcare and long-term care required by the older population ([11]; [43]). However, age-related social issues, such as retirement, loss of a life partner, family or close friends, declining health or social discrimination, can affect social connections, contributing to the marginalisation of older adults, and consequently worsen their quality of life and well-being ([40]; [44]; [56]; [25]; [48]).

According to the World Health Organisation ([60]), health implies “a state of complete well-being”, highlighting the importance of social connections; its structural, functional and quality dimensions that significantly influence physical and mental well-being. Solid social connections and community engagements significantly contribute to the health and well-being of older adults ([33]; [24]).

Positive social connections lead to improved emotional support, increased information sharing, provide a sense of belonging and enhanced opportunities for social participation ([33]; [24]). Conversely, social disconnection refers to the lack of these connections, manifesting as social isolation, loneliness, inadequate support, low social capital, and negative experiences. Social isolation and loneliness are widespread, with serious but under-recognised impacts on health, well-being, and society. Social disconnection can lead to issues like depression, cognitive decline and premature mortality, posing significant, yet often overlooked, public health threats ([42]; [60]).

Social isolation refers to an objective lack of roles, relationships, or interactions with others. It involves a limited social support network and infrequent social interactions, regardless of personal feelings about social life. Social isolation explicitly reflects a deficit in the structural dimension of social connection, rather than in the other functional and quality dimensions. It is measured by the absence or weakness of a social support network ([23]; [60]). Loneliness is a subjective, negative emotional state that arises when a person’s expectations of social connection differ from their actual experiences of social connection ([46]). It can stem from a lack of friends, support, or poor interactions. Unlike solitude, loneliness is usually involuntary and unwanted ([23]). From an evolutionary perspective, loneliness is considered “double-edged”: while short-term loneliness can be beneficial, chronic loneliness is harmful, resulting in various health issues and significant social and economic challenges ([23]).

Social isolation and loneliness affect health through distinct but overlapping mechanisms: loneliness acts as a subjective, chronic stressor (psychological), while isolation is an objective, behavioural lack of social contact (physiological). Both conditions are linked to adverse mental and physical health outcomes and mortality, particularly in older adults, who often experience reduced social interactions, longer periods of time living alone, and higher prevalence of loneliness ([16]; [45]). Notably, social isolation and loneliness frequently act as sources of chronic stress in adults. Several reports indicate that loneliness and social stress are associated with dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic nervous system. As a result, repeated and chronic social stress can lead to neuroendocrine changes, immune dysfunction, oxidative stress, sleep disturbances, cognitive decline, cognitive and emotional dysregulation, and maladaptive cognitions ([29]; [52]; [49]; [5]; [62]; [7]; [55]). Despite these associations, the causal role of these mechanisms in the development of harmful physiological and psychological outcomes associated with chronic social stress remains unclear ([62]).

Recent meta-analyses across 27 countries indicate that social isolation affects 25.0% to 33.6% of older adults in the community ([51]; [15]; [60]). The estimated prevalence of loneliness ranges from 12.0% to 33.0%, with significant differences observed between genders ([58]; [60]). Higher rates of loneliness are observed in low-income (24.3%) and lower-middle-income countries (19.3%), compared with 10.6% in high-income countries ([1]; [60]). This disparity is linked to income and cultural differences, with lower income levels correlating with greater loneliness. Cultural factors also play a role; in collectivist societies, social support is greater, but it is diminishing in post-modern society due to rising individualism, changing family structures, socioeconomic inequalities, digital exclusion, and public insecurity ([64]; [60]). Marginalised individuals and caregivers also report significant social disconnection, with 21.0% to 52.7% of caregivers for mental health patients experiencing social isolation and loneliness, respectively ([13]; [60]).

Chile is experiencing a rapid demographic shift, with the proportion of adults aged 60 and over increasing from 16.2% of the population in 2017 to 19.8% in the 2024 Census, and projected to reach 32% by 2050 ([21]; [22]). This change is primarily driven by the Baby Boomer generation, which has undergone significant social, political and economic changes. However, many baby boomers encounter challenges such as loss of identity after retirement, age-related prejudice, and a disconnect from family life due to dispersed families. High divorce rates lead many to live alone, heightening the risk of social disconnection ([26]; [27]; [28]). They also face gaps in social protection and leisure services, emphasising the need for targeted public policies to promote healthy ageing.

The prevalence rates of social isolation and loneliness among older adults in Chile vary across studies and samples. Recently, in a nationally representative study, the prevalence of social isolation and loneliness was reported at 30.4% and 23.4%, respectively, with both rates increasing with age and higher among women ([37]). A study by [18] revealed increases in loneliness from 48% to 53% and in social isolation from 39% to 41% during the COVID-19 pandemic ([18]). A post-pandemic study in Santiago found that 42% of self-sufficient older adults faced social isolation, while 26% felt lonely ([12]). The 2023 Social Wellbeing Survey indicated a 32% rate of loneliness ([35]). Loneliness is particularly high among certain ethnic groups in rural areas, with rates above 55%, except for Rapa Nui (9.0%) and Diaguita (14.0%).

Despite extensive research on social isolation and loneliness, these terms are often used interchangeably and as a proxy for one another in social research; however, they are distinct constructs that denote distinct experiences ([60]; [34]; [2]; [3]). Numerous studies have examined each construct separately or combined; however, less effort has been dedicated to exploring the mediating role of loneliness, a subjective experience, in the relationship between social isolation and important adverse health outcomes in older adults ([8]; [4]; [41]; [17]; [63]; [14]).

Social disconnection, both social isolation and loneliness in older adults, is strongly associated with worse self-rated health, and these relationships are likely reciprocal; a worse self-rated health predicts later higher social disconnection, with more potent effects in unmarried women and lesseducated older adults ([39]; [31]). Understanding the relationships among social isolation, self-rated health, and loneliness is crucial for developing strategies to support social engagement and promote health and well-being, particularly mental well-being, among older adults. Mediation analysis helps examine the explanatory role of loneliness by estimating the magnitude of its mediating effect in the relationship between social isolation and self-rated health. Therefore, this study aims to examine whether loneliness mediates the association between social isolation and self-rated health among community-dwelling Chilean older adults.

2. Method

2.1. Data and Sample Population

This observational cross-sectional study utilises data from the National Quality of Life and Health Survey (NQoLHS-2023/2024), conducted by Chile’s Ministry of Health and the Institute of Sociology at the Pontifical Catholic University of Chile. It targets non-institutionalised Chileans and foreign residents aged 15 and older living in private homes for at least six months. The study assesses perceptions of health-related quality of life across all regions of Chile using a stratified sampling method. Personal interviews were conducted between October 2023 and February 2024. The present analysis focuses on a sample of 6755 individuals aged 60 years or older who could answer the questions independently ([32]).

2.2. Measures

2.2.1. Outcome variable

Self-rated health (SRH) reflects an individual’s overall perception of their health, providing a holistic overview of both physical and mental health and offering a valuable perspective on quality of life ([36]). Despite its subjective nature, SRH has proved to be a good predictor of future healthcare needs and mortality ([38]). SRH was assessed by asking participants, “How is your health in general?” Responses ranged from 1 to 7, where one corresponded to “very bad”, 2 to “bad”, 3 to “less than fair”, 4 to “fair”, 5 to “more than fair”, 6 to good and 7 to “very good”. Responses were grouped into an ordinal variable with three categories: “very bad/bad” (scores 1 - 3), “fair” (score 4), and “good/very good” (scores 5 - 7). The good/very good category was the reference group.

2.2.2. Independent Variable

The social isolation(SI) concept was operationalised using a 6-item measure adapted from the approach of [65], which evaluates domains from both external and internal perspectives of social isolation ([65]). External indicators include: a) Current marital or civil status (1 = married, civil partner, or cohabitant; 0 = other statuses), b) Social participation (1 = participates in one or more social organizations, including religious groups; 0 = does not participate), c) Social network support (“If you were in financial trouble, would you have relatives or friends you could count on for help?” 1 = yes; 0 = no), d) Emotional support (“When you have problems, do you have anyone you trust to ask for help or advice?” 1 = yes; 0 = no). Internal indicators include: a) Level of satisfaction with time shared with family (“Are you satisfied with how you and your close family share time together?” 1 = yes; 0 = no), and b) Sense of belonging to the community (“How often do you feel like you belong to your neighbourhood, a social group, or similar?” 1 = always/often; 0 = never/rarely). Because the SI is a negative construct, the indicator values were reversed before calculating the total score. The total score ranges from 0 to 6, with higher scores indicating greater social isolation. Because the distribution of total scores was positively skewed, and to avoid overrepresentation of the variable due to the non-structured questions about social isolation and potential bias from participants’ educational and cognitive characteristics, the cut-off score was set at the 67th percentile. A score of 3 or more indicates social isolation. With these criteria, 2222 individuals were identified as socially isolated. SI was categorised as a binary variable (1 = socially isolated; 0 = not socially isolated).

2.2.3. Mediator Variable

Loneliness was measured using the Three-Item Lonely Scale (TILS) from [20]. It includes questions about lack of companionship, feeling left out, and feeling isolated. Responses are scored on a 1 - 3 scale, where 1 corresponds to “hardly ever”, 2 to “sometimes”, and 3 to “often”. The total scores range from 3 to 9, with higher scores indicating greater loneliness. Because the score distribution was positively skewed, the cutoff score was set at the 75th percentile to better capture loneliness. However, those who scored 5 points were classified as lonely only if they answered “often” (score = 3) to the question “feel a lack of companionship,” underscoring the item’s representation as a social component of loneliness, to improve the accuracy of loneliness measurement and build reliable models. This method identified 1785 individuals experiencing loneliness. Loneliness was categorised as a binary variable (1 = feeling alone; 0 = no feeling alone). Cronbach’s alpha of TILS in this study was 0.8045.

2.2.4. Other Covariates

Socio-demographic and economic factors, as well as health and lifestyle issues, were included to adjust the models. Gender was a binary variable, with men as the reference group. Participants were categorised by age into the following groups: 60 - 64 years (reference group), 65 - 69 years, 70 - 74 years, 75 - 79 years and 80 years and older. Having sons/daughters was treated as a binary variable, and individuals without children served as the reference group.

Education level was categorised into four groups: illiterate/elementary, high school, technical, and graduate, with the latter used as the reference group. Household income was categorised into quintiles, with the fifth quintile as the reference. Working status and retirement status were treated as binary variables, with individuals who were neither employed nor retired as the reference group.

Caregivers were identified with the question: “Apart from your usual activities, are you responsible for caring for children, elderly individuals with moderate to severe dependency, or chronically ill individuals?” Response options were: “Yes, as the sole caregiver,” “Yes, shared with another person,” and “No, I am not in charge of anyone,” with the last option as the reference category. Safety perception in the neighbourhood was assessed with the question: “How safe do you feel walking alone in your neighbourhood after dark?” The response options were: very unsafe, somewhat unsafe, moderately safe, and very safe. For analysis, these were grouped into a dichotomous variable: 0 for “very unsafe/somewhat unsafe” and 1 for “moderately safe/very safe”, as the reference group.

Multimorbidity was assessed by the number of self-reported physician diagnoses of 14 chronic diseases. These conditions include hypertension, diabetes mellitus, acute myocardial infarction, heart failure/arrhythmias, stroke, arthritis/osteoarthritis, depression, anxiety or other mental health disorders, chronic obstructive pulmonary disease (COPD), liver cirrhosis/chronic liver damage, cataracts/glaucoma, chronic pain (lasting more than 3 months), urinary incontinence, chronic kidney failure and other chronic diseases. Multimorbidity was defined as having at least two of the fourteen selected conditions mentioned above, and was categorised as a binary variable (1 = multimorbidity; 0 = none or one chronic disease).

Depression/anxiety or other mental health disorders were included as a binary variable (1 = yes; 0 = no). Sensory deficiency, including blindness and/or deafness, was treated as a binary variable, with individuals without sensory deficits serving as the reference group. The disability level was a binary variable, with those with moderate or severe disability as the group of interest, and those with mild or no disability as the reference group. Discrimination was measured with the question, “Have you felt discriminated against in the last year?” Response options were yes or no. The no option was the reference group.

According to WHO guidelines, older adults should engage in 150 to 300 minutes of moderate-intensity or 75 to 150 minutes of vigorous-intensity aerobic activity, or an equivalent combination of both, throughout the week ([57]). Physical activity was included as a binary variable: individuals who met the WHO recommendations were classified as physically active, whereas those with no activity or lower levels of activity were classified as the reference group.

2.3. Statistical Analysis

Descriptive statistics were used to analyse participants’ baseline characteristics by Self-Rated Health status. The chi-square test was conducted to assess the significance of the associations between covariates and the dependent variable. The sample design was incorporated into the analysis, enabling valid inferences for the population. The analysis employed the svyset and svy commands to incorporate the primary sampling unit, individual weights, and strata. Multicollinearity was examined using correlation matrices and variance inflation factors (VIFs).

Additionally, the One-Parameter Logistic Item Response Theory (IRT) Model (1PL) and Confirmatory Factor Analysis (CFA) were used in combination to validate the psychometric properties of the latent variable representing social isolation. Given the binary nature of the data, the CFA was estimated using the gsem command and average marginal effects (AMEs) were calculated. To ensure identification of the CFA model, the variance of the latent variable was constrained to 1. Note that the absolute metric (e.g., root mean square error of approximation (RMSEA), comparative fit index (CFI), and Tucker-Lewis index (TLI) SEM model goodness-of-fit statistics are not supported by the gsem command for binary indicators in Stata 14.0.

A pathway diagram was created to illustrate the mediation analysis, specifically the potential mediating effect of loneliness on the relationship between social isolation and self-rated health (see Figure 1).

Figure 1

Figure 1. Pathway diagram of the mediating effect of Loneliness on the association between Social Isolation and Self-Rated Health.

The mediation analysis was conducted with structural equation modelling (SEM) according to the following equations:

(Ep. 1) Y = i 1 + c X + ε 1 (Ep. 2) M = i 2 + a X + ε 2 (Ep. 3) Y = i 3 + c ′ X + b M + ε 3

Because SRH is ordinal and categorical, Equation (1) was estimated using an ordered logistic regression (ologit). The linktest checked model specification errors, and gologit2 with autofit tested the proportional odds assumption. In this model, the null hypothesis (H0: c ≠ 0) is rejected. Therefore, it is important to assess partial mediation through direct, indirect, and total effects. Using a generalised structural equation modelling (gsem), models for Equations (2) and (3) were combined into a single model, and their inference parameters were estimated concurrently using the boot1r class user-written program. This approach estimated direct, indirect, and total effects. The bootstrap command with 1000 replications produced robust standard errors (SE) and 95% confidence intervals (CI). Finally, global macro variables (the nlcomcommand) were used to compute the ratio of indirect to direct effects and the proportion of the total effect mediated by loneliness. All three models were adjusted by demographic, economic, health and social variables. Statistical significance was assessed using t-tests and z-tests at a 5% significance level. Analyses were conducted in Stata 14.0.

3. Results

Table 1 summarises the sample characteristics and the relationships among the outcome, dependent, and mediator variables. A sample of 6,755 individuals aged 60 and over corresponds to 3,718,439 individuals after accounting for the analysis’s sample design. Among this population, 16.2%, 32.1%, and 51.7% reported SRH as bad/very bad, fair, and good/very good, respectively. The average participant age was 70.6 years (SD = 7.65), with 60% being women and 50% aged 70 or older.

The 30.4% and 23.4% of participants were socially isolated and felt alone, respectively. Social isolation was more frequent among men (34.1%), whereas feeling alone was more frequent among women (27.4%). Among participants with bad/very bad SRH,45% and 37% reported social isolation and loneliness, respectively. On the other hand, participants with good/very good SRH shows 25% and 17% of social isolation and loneliness, respectively.

Table 1. Sample characteristics according to self-rated health in older adults. NQoLHS-2023/2024.

Table 1

Characteristics	Self-rated Health
	bad/very bad (n: 1162)	fair (n: 2217)	good/very good (n: 3369)
Social isolation***	44.8%	31.5%	25.4%
Loneliness***	36.5%	27.3%	16.9%
Women n s	56.0%	55.9%	54.8%
Having children n s	91.5%	92.9%	91.4%
Education levels***
Illiterate/elementary school	59.6%	53.6%	36.9%
high school	27.4%	26.5%	30.7%
technical school	10.0%	15.6%	19.4%
graduated (ref.)	3.0%	4.3%	13.0%
Household income quintiles***
1st quintile	31.4%	25.6%	15.6%
2nd quintile	43.5%	36.0%	29.0%
3rd quintile	7.6%	12.8%	11.3%
4th quintile	14.4%	19.2%	30.1%
5th quintile (ref.)	3.0%	6.4%	14.1%
Working***	10.5%	16.3%	25.3%
Retiree n s	57.4%	56.6%	54.4%
Caregiver activity n s
sole caregiver	13.6%	15.1%	12.7%
shared care	10.2%	11.0%	12.0%
does not care (ref.)	76.2%	73.9%	75.3%
Multimorbidity***	89.9%	78.7%	53.9%
Depression/anxiety***	40.1%	21.6%	12.7%
Disability(moderate/severe)***	90.4%	79.6%	58.4%
Sensory deficiency ***	44.1%	32.9%	23.0%
Discrimination***	11.8%	7.3%	3.6%
Physically active***	10.6%	16.7%	23.0%
Live in an unsafe neighborhood**	58.6%	52.1%	48.6%

**: p < 0.05; ***: p <0.0001; ns: no significant.

Lifestyle factors, alcohol consumption, and sleep duration were examined but excluded from the models due to high rates of missing data; smoking was not significantly associated and thus did not affect the robustness or simplicity of the models.

The multicollinearity diagnostic showed that most variables had low correlations (rho < 0.30), except for a few pairs with moderate correlations, including retirement status and working status, retirement status and age groups, and multimorbidity with self-rated health, disability and depression. The mean variance inflation factor (VIF) was 1.22, indicating no multicollinearity.

Psychometric validation of the social isolation variable using the IRT-1PL model indicates that factors such as a lack of emotional support, dissatisfaction with family time, and a lack of social network support are associated with greater difficulty with social isolation (β > 1). In contrast, not having a partner, limited social activities, and not belonging to a community are associated with lower difficulty (β < 1). Higher difficulty indicates a greater degree of social isolation required for correct responses, whereas lower difficulty suggests that average or below-average individuals are more likely to respond correctly. CFA assesses the extent to which observed indicators reflect social isolation, with older adults without a partner, limited social participation, and a lack of a sense of belonging to a community experiencing higher probabilities of social isolation. However, excluding the lack-of-emotional-support indicator, the CFA model’s robustness improved.

The goodness-of-fit for the ordered logistic regression model for equation (1) indicates adequate specification and does not violate the proportional odds assumption (hatsq: p > 0.05). The model indicates a significant association between social isolation and SRH status. Socially isolated individuals (21.0%) have a significant 5.8% higher probability of experiencing bad/very bad SRH than non-isolated individuals (15.2%), whereas non-isolated individuals (52.1%) have a 6.1% higher likelihood of reporting good/very good SRH than isolated individuals (46.0%).

Table 2 summarises the results of the generalised structural equation modelling, assessing the partial mediation through the estimated direct, indirect, and total effects. The estimated effect of social isolation on loneliness (a-path) is 0.82973 (95% CI: 0.70740 to 0.95206), indicating a positive and significant association. Loneliness also significantly predicts SRH status (b-path), with an estimated adverse effect of −0.23083 (95% C.I.: −0.35228 to −0.10937). This suggests that the indirect effect of social isolation on SRH status through loneliness is significant. This implies that the influence of social isolation on feeling loneliness partially explains the adverse effect of social isolation on SRH status.

Table 2. Result of the generalized structural equation model of loneliness on the relationship between social isolation and self-rated health status.

Table 2

	Coef.	Std. Err.	[95% C. I.]	p -value
Direct effects (c’ path)
SI > SRH (adj. by L)	−0.32377	0.057044	(−0.43558 - −0.21197)	<0.0001
a path
SI > L	0.82973	0.062413	(0.70740 - 0.95206)	<0.0001
b path
L > SRH	−0.23083	0.061969	(−0.35228 - −0.10937)	<0.0001
Indirect effects (a*b path)
SI > L > SRH	−0.18344	0.049394	(−0.28025 - −0.08663)	<0.0001
Total effects ( c path)
SI > SRH	−0.50721	0.069887	(−0.64419 - −0.37023)	<0.0001

SI: Social Isolation;SRH: Self-rated Health;L: Loneliness; adj.: Adjusted; Coef.: coefficient; Std. Err.: Standard error; C. I.: Confidence Interval.

The estimated indirect effect (a*b-path) of social isolation on SRH status via loneliness is −0.18344 (95% CI: −0.28025 to −0.8663), indicating that social isolation significantly and indirectly influences SRH status by increasing loneliness. Finally, the estimated total effect of social isolation on SRH status (c-path) via loneliness is −0.50721 (95% C.I.: −0.64419 to −0.37023). This represents the overall direct (c’-path) and indirect effects(a*b-path) combined. Overall, these results highlight the significant mediating role of loneliness in the relationship between social isolation and SRH status in older adults. The ratio of indirect to total effect indicates that approximately 36.0% of the effect of social isolation on SRH status in older adults is mediated by loneliness, and the ratio of indirect to direct effect indicates that the mediated effect of loneliness is 57.0% of the direct effect of social isolation on SRH status in older adults.

Conceptually and empirically, isolation and loneliness are moderately correlated but largely non-overlapping experiences in older adults ([25]; [50]; [41]). These constructs show a low correlation (rho= 0.222) and an overlap of 11.3% in the survey sample analysed. Moreover, social isolation and loneliness are often confused and used interchangeably in social research ([60]; [34]; [2]; [19]; [33]; [60]; [15]), then, the mediating role of social isolation in the relationship between loneliness and SRH status in older people was also examined (data not shown). In summary, the estimated direct effect of loneliness (−0.2308; 95%CI: −0.34627 to −0.11538) and the indirect effect of loneliness (−0.2577; 95%CI: −0,35727 to −0.15826) on SRH status via social isolation is greater than that of social isolation. In contrast, the total effect of loneliness (−0.48859; 95% CI: −0.62972 to −0.34746) on SRH status via social isolation is slightly lower than that of social isolation alone. The ratio of indirect to total effect indicates that approximately 53.0% of the effect of loneliness on SRH status in older adults is mediated by social isolation, and the ratio of indirect to direct effect indicates that the mediated effect of social isolation is 112.0% of the direct effect of loneliness on SRH status in older adults. This result indicates that social isolation explains most of the relationship between loneliness and SRH status, suggesting full mediation.

4. Discussion

Due to changes in life circumstances, many older adults are socially isolated and experience loneliness, posing significant challenges to community engagement. These social disconnections are considered serious public health issues given their association with adverse health outcomes and declines in quality of life and well-being ([8]). In consequence, this situation creates a pressing need to develop strategies to ensure that older people can live socially integrated lives within effective families and social networks.

This study indicates that 52%, 32%, and 16% of older adults reported SRH as good/very good, fair, and bad/very bad, respectively. Additionally, the prevalence of social isolation and loneliness in this population was 30.4% and 23.4%, respectively. Social isolation was more frequent among men, whereas feeling alone was more frequent among women. The risk of both social disconnections increases with age, lower levels of education, and lower economic positions. These findings align with global research, indicating that social isolation among community-dwelling older adults ranges from 25% to 34%, while loneliness ranges from 12% to 33%. Both also tend to increase with age and show significant gender differences ([15]; [51]; [58], 2025). However, these results are lower than those reported in previous Chilean studies, possibly due to differences in sample characteristics and methodological approaches ([12]; [35]; [6]; [18]).

The results also show a consistent and reciprocal relationship between social disconnection and worse SRH status among older adults. As social isolation score increases, they experience a worse SRH, and vice versa; a worse health status reported, they are more likely to feel socially isolated. A similar situation was observed with loneliness. This finding aligns with previous studies demonstrating a reciprocal link between social disconnections and poorer self-rated health among older adults. A recent Chinese longitudinal study shows that higher baseline social isolation predicted subsequent declines in SRH, and poorer SRH predicted increased later isolation among women and less-educated older adults. SI and SRH are reciprocally linked in older adults, with meaningful variation across demographic strata ([39]). Another study using structured questionnaires conducted in Hong Kong reported a significant, reciprocal association between social isolation and poorer overall health status among community-dwelling Chinese older adults receiving home care services ([61]). Another Chinese longitudinal study shows that both social isolation and loneliness among people aged 65 and older predict poor SRH and functional decline ([66]). Moreover, some studies reported that loneliness is strongly associated with poorer self-rated health, particularly among women ([9]; [10]).

To my knowledge, no other studies have directly examined the mediating role of loneliness in the relationship between social isolation and SRH among Chilean older adults. The mediation analysis confirmed the hypothesis that the effect of social isolation directly affects SRH status in older adults and indirectly influences SRH status mediated by loneliness experiences. From structural equation modelling, about 36% of the effect of social isolation on SRH status is indirect via loneliness, and the mediated effect of loneliness accounts for about 57% of the direct effect of social isolation on SRH status in older adults. This finding aligns with previous studies demonstrating that among community-dwelling older adults, loneliness consistently emerges as a key pathway linking social isolation to poorer self-rated health and other adverse related outcomes such as cognitive functioning, depression or overall life satisfaction ([8]; [41]; [17]; [63]; [14]).

Given that isolation and loneliness are often used interchangeably in social research, the mediating role of social isolation in the relationship between loneliness and SRH status in older people was sketchily investigated. The mediation analysis indicates that 53.0% of the effect of loneliness on SRH status is indirectly mediated by social isolation. Furthermore, the mediated effect of social isolation accounts for approximately 112.0% of the direct effect of loneliness on SRH status in older adults. There is strong evidence that loneliness and social isolation both predict poorer self-rated health, but reviews note a lack of studies directly testing social isolation as a mediator between loneliness and self-rated health ([30]; [8]; [47]). Future research, particularly longitudinal studies that account for cultural and socioeconomic contexts, is needed to test whether social isolation mediates the relationship between loneliness and SRH among community-dwelling older adults. Also, it seems necessary to account for a short, user-friendly scale with adequate psychometric properties and validated for use in population surveys in Chile to confirm or refute these results.

This study had several limitations. First, self-reported measures may introduce recall bias, particularly among older adults and individuals with lower educational attainment. Secondly, although the operational definition of social isolation is theoretically well-founded, goodness-of-fit statistics for the CFA model in the psychometric validation, such as RMSEA, CFI, and TLI, could not be estimated using the gsem command in Stata 14.0. It seems necessary to confirm the model’s reliability through a more specific and comprehensive study. Thirdly, reverse causality between health status and social disconnection—where poor health reduces the ability to maintain social connections rather than the other way around—is a critical, bidirectional issue that could involve endogeneity, overestimate the mediation effect, or reduce the model’s predictive power. To address this bidirectional link, longitudinal studies and advanced analytical methods are required. Finally, as an observational study, the findings may be influenced by unmeasured confounding variables; therefore, caution is advised when interpreting them in light of these limitations.

Despite its limitations, the study has several strengths. The use of nationally representative data enables generalisation of findings, and a larger sample size enhances the accuracy of the results. The broad, well-validated nature of the SRH outcome variable as a health-status indicator across socioeconomic and cultural strata enables reliable examination of the mediating effect of loneliness in the relationship between social isolation and health status. By employing parsimonious models that account for relevant confounding variables, the study provides reliable estimates. Furthermore, the use of structural equation modelling provides an appropriate framework for inference in mediation analysis, thereby enabling a better understanding of the causal relationships among variables. These findings support the implementation of effective social strategies to address social disconnections. It is important to identify community-dwelling older adults at risk of loneliness and/or social isolation, and to implement strategies that emphasise peer support, group activities, and low-cost technologies.

5. Conclusion

Both loneliness and social isolation are associated with poorer perceived health; however, it is a complex issue, as the relationship between social disconnections and SRH is consistently bidirectional among older adults. Mediation analyzes show that loneliness significantly mediates the impact of social isolation on health status. When the mediating variable is reverted to social isolation, the model results suggest full mediation. More refined research is needed to confirm or rule out whether social isolation mediates the relationship between loneliness and self-rated health among community-dwelling older adults. The findings underscore the importance of social connectivity to health status and well-being of older adults, and provide guidance for future interventions that promote social engagement to achieve successful ageing.

Acknowledgements

The author utilised AI Grammarly to enhance the manuscript’s grammar and clarity.

Funding

No external funding supported this work.

Data Availability

Data supporting this research is available at https://datos.gob.cl/dataset/encavi-2023-24.

References

1.. Akhter-Khan, S. C., van Es, W., Prina, M., Lawrence, V., Piri, I., Rokach, A. et al. (2024). Experiences of Loneliness in Lower-and Middle-Income Countries: A Systematic Review of Qualitative Studies. Social Science & Medicine, 340, Article 116438. https://doi.org/10.1016/j.socscimed.2023.116438 10.1016/j.socscimed.2023.11643838016310https://doi.org/10.1016/j.socscimed.2023.116438 Akhter-Khan, S. Es, W. Prina, M. Lawrence, V. Piri, I. Rokach, A. 2024 116438 10.1016/j.socscimed.2023.116438 38016310

2.. Asante, S., & Tuffour, G. (2022). Social Isolation and Loneliness in Older Adults: Why Proper Conceptualization Matters. Journal of Ageing and Longevity, 2, 206-213. https://doi.org/10.3390/jal2030017 10.3390/jal2030017https://doi.org/10.3390/jal2030017 Asante, S. Tuffour, G. 2022 10.3390/jal2030017

3.. Barnes, T. L., MacLeod, S., Tkatch, R., Ahuja, M., Albright, L., Schaeffer, J. A. et al. (2021). Cumulative Effect of Loneliness and Social Isolation on Health Outcomes among Older Adults. Aging & Mental Health, 26, 1327-1334. https://doi.org/10.1080/13607863.2021.1940096 10.1080/13607863.2021.194009634215167https://doi.org/10.1080/13607863.2021.1940096 Barnes, T. MacLeod, S. Tkatch, R. Ahuja, M. Albright, L. Schaeffer, J. 2021 10.1080/13607863.2021.1940096 34215167

4.. Belau, M. H., Becher, H., & Kraemer, A. (2021). Loneliness as a Mediator of Social Relationships and Health-Related Quality of Life among Refugees Living in North Rhine-Westphalia, Germany. BMC Public Health, 21, Article No. 2233. https://doi.org/10.1186/s12889-021-12303-5 10.1186/s12889-021-12303-534879832https://doi.org/10.1186/s12889-021-12303-5 Belau, M. Becher, H. Kraemer, A. Rhine-Westphalia, G 2021 No 10.1186/s12889-021-12303-5 34879832

5.. Cacioppo, J. T., Cacioppo, S., Capitanio, J. P., & Cole, S. W. (2015). The Neuroendocrinology of Social Isolation. Annual Review of Psychology, 66, 733-767. https://doi.org/10.1146/annurev-psych-010814-015240 10.1146/annurev-psych-010814-01524025148851https://doi.org/10.1146/annurev-psych-010814-015240 Cacioppo, J. Cacioppo, S. Capitanio, J. Cole, S. 2015 10.1146/annurev-psych-010814-015240 25148851

6.. Carrasco, M., Fernández, M., Alexander, E., & Herrera, M. (2021). Loneliness in Older Chilean People: Importance of Family Dysfunction and Depression. International Journal of Mental Health Promotion, 23, 99-109. https://doi.org/10.32604/ijmhp.2021.011568 10.32604/ijmhp.2021.011568https://doi.org/10.32604/ijmhp.2021.011568 Carrasco, M. Alexander, E. Herrera, M. 2021 10.32604/ijmhp.2021.011568

7.. Cudjoe, T. K. M., Selvakumar, S., Chung, S., Latkin, C. A., Roth, D. L., Thorpe, R. J. et al. (2022). Getting under the Skin: Social Isolation and Biological Markers in the National Health and Aging Trends Study. Journal of the American Geriatrics Society, 70, 408-414. https://doi.org/10.1111/jgs.17518 10.1111/jgs.1751834698366https://doi.org/10.1111/jgs.17518 Cudjoe, T. Selvakumar, S. Chung, S. Latkin, C. Roth, D. Thorpe, R. 2022 10.1111/jgs.17518 34698366

8.. Czaja, S. J., Moxley, J. H., & Rogers, W. A. (2021). Social Support, Isolation, Loneliness, and Health among Older Adults in the PRISM Randomized Controlled Trial. Frontiers in Psychology, 12, Article ID: 728658. https://doi.org/10.3389/fpsyg.2021.728658 10.3389/fpsyg.2021.72865834675843https://doi.org/10.3389/fpsyg.2021.728658 Czaja, S. Moxley, J. Rogers, W. Support, I 2021 728658 ID 10.3389/fpsyg.2021.728658 34675843

9.. Deshmukh, M., & Martin, P. (2024). Relationship Between Loneliness and Self-Reported Health and Life Satisfaction among Older Adults. Innovation in Aging, 8, 255-255. https://doi.org/10.1093/geroni/igae098.0823 10.1093/geroni/igae098.0823https://doi.org/10.1093/geroni/igae098.0823 Deshmukh, M. Martin, P. 2024 10.1093/geroni/igae098.0823

10.. Freak-Poli, R., Ryan, J., Tran, T., Owen, A., McHugh Power, J., Berk, M. et al. (2021). Social Isolation, Social Support and Loneliness as Independent Concepts, and Their Relationship with Health-Related Quality of Life among Older Women. Aging & Mental Health, 26, 1335-1344. https://doi.org/10.1080/13607863.2021.1940097 10.1080/13607863.2021.194009734219569https://doi.org/10.1080/13607863.2021.1940097 Freak-Poli, R. Ryan, J. Tran, T. Owen, A. Power, J. Berk, M. Isolation, S 2021 10.1080/13607863.2021.1940097 34219569

11.. Fried, L. P., Tangen, C. M., Walston, J., Newman, A. B., Hirsch, C., Gottdiener, J. et al. (2001). Frailty in Older Adults: Evidence for a Phenotype. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 56, M146-M157. https://doi.org/10.1093/gerona/56.3.m146 10.1093/gerona/56.3.m14611253156https://doi.org/10.1093/gerona/56.3.m146 Fried, L. Tangen, C. Walston, J. Newman, A. Hirsch, C. Gottdiener, J. 2001 10.1093/gerona/56.3.m146 11253156

12.. Gierke, C., Navarro, C. F., Martinez, M., Delgado, C., Delano, P. H., Medel, V. et al. (2024). Characterization of Social Isolation and Perception of Loneliness in a Group of Chilean Older People Post‐Pandemic. Alzheimer’s & Dementia, 20, e089300. https://doi.org/10.1002/alz.089300 10.1002/alz.089300https://doi.org/10.1002/alz.089300 Gierke, C. Navarro, C. Martinez, M. Delgado, C. Delano, P. Medel, V. 2024 10.1002/alz.089300

13.. Guan, Z., Poon, A. W. C., & Zwi, A. (2023). Social Isolation and Loneliness in Family Caregivers of People with Severe Mental Illness: A Scoping Review. American Journal of CommunityPsychology, 72, 443-463. https://doi.org/10.1002/ajcp.12698 10.1002/ajcp.1269837565657https://doi.org/10.1002/ajcp.12698 Guan, Z. Poon, A. Zwi, A. 2023 10.1002/ajcp.12698 37565657

14.. Güler, A., & Yıldırım, M. (2025). Social Isolation, Loneliness, Death Stress and Life Satisfaction in Older Adults: A Serial Mediation Study. Geriatric Nursing, 62, 78-85. https://doi.org/10.1016/j.gerinurse.2025.01.037 10.1016/j.gerinurse.2025.01.03739919698https://doi.org/10.1016/j.gerinurse.2025.01.037 Isolation, L 2025 10.1016/j.gerinurse.2025.01.037 39919698

15.. Hajek, A., Volkmar, A., & König, H. H. (2023). Prevalence and Correlates of Loneliness and Social Isolation in the Oldest Old: A Systematic Review, Meta-Analysis and Meta-Regression. Social Psychiatry and Psychiatric Epidemiology,60,993-1015. Hajek, A. Volkmar, A. Review, M 2023

16.. Hansen, T., & Slagsvold, B. (2016). Late-Life Loneliness in 11 European Countries: Results from the Generations and Gender Survey. Social Indicators Research, 129, 445-464. https://doi.org/10.1007/s11205-015-1111-6 10.1007/s11205-015-1111-6https://doi.org/10.1007/s11205-015-1111-6 Hansen, T. Slagsvold, B. 2016 10.1007/s11205-015-1111-6

17.. Hao, H., Du, M., & Yue, J. (2024). Social Isolation, Loneliness, and Subjective Wellbeing among Chinese Older Adults during the COVID-19 Pandemic. Frontiers in Public Health, 12, Article ID: 1425575. https://doi.org/10.3389/fpubh.2024.1425575 10.3389/fpubh.2024.142557539440171https://doi.org/10.3389/fpubh.2024.1425575 Hao, H. Du, M. Yue, J. Isolation, L 2024 142557 ID 10.3389/fpubh.2024.1425575 39440171

18.. Herrera, M. S., Elgueta, R., Fernández, M. B., Giacoman, C., Leal, D., Rubio, M., Marshall, P., & Bustamante, F. (2021). Calidad de vida de las personas mayores chilenas durante la pandemia COVID-19. https://sociologia.uc.cl/wp-content/uploads/2021/07/libro_calidad-de-vida-pm-y-covid-19-.pdf Herrera, M. Elgueta, R. Giacoman, C. Leal, D. Rubio, M. Marshall, P. Bustamante, F. 2021

19.. Holt-Lunstad, J., Robles, T. F., & Sbarra, D. A. (2017). Advancing Social Connection as a Public Health Priority in the United States. American Psychologist, 72, 517-530. https://doi.org/10.1037/amp0000103 10.1037/amp000010328880099https://doi.org/10.1037/amp0000103 Holt-Lunstad, J. Robles, T. Sbarra, D. 2017 10.1037/amp0000103 28880099

20.. Hughes, M. E., Waite, L. J., Hawkley, L. C., & Cacioppo, J. T. (2004). A Short Scale for Measuring Loneliness in Large Surveys: Results from Two Population-Based Studies. Research on Aging, 26, 655-672. https://doi.org/10.1177/0164027504268574 10.1177/016402750426857418504506https://doi.org/10.1177/0164027504268574 Hughes, M. Waite, L. Hawkley, L. Cacioppo, J. 2004 10.1177/0164027504268574 18504506

21.. INE (2023). Proyecciones de población por sexo y edad: Chile 2023-2050. Gobierno de Chile. https://www.ine.gob.cl/estadisticas/sociales/demografia-y-vitales/proyecciones-de-poblacion 2023

22.. INE (2024). Censo de población y vivienda de chile, 2024.Estadísticas. https://censo2024.ine.gob.cl/resultados/ 2024

23.. Institute of Medicine (US), Division of Health Promotion and Disease Prevention (1992). Social Isolation Among Older Individuals: The Relationship to Mortality and Morbidity. In R. L. Berg, & Cassells, J. S. (Eds.), The Second Fifty Years: Promoting Health and PreventingDisability (pp. 243-262). National Academies Press. https://www.ncbi.nlm.nih.gov/books/NBK235604/ Cassells, J. 1992

24.. Kim, A., & Park, K. (2025). Development of Social Isolation and Social Network Assessment Tool for Older Adults: A Delphi Survey. PLOS ONE, 20, e0323198. https://doi.org/10.1371/journal.pone.0323198 10.1371/journal.pone.032319840344144https://doi.org/10.1371/journal.pone.0323198 Kim, A. Park, K. 2025 10.1371/journal.pone.0323198 40344144

25.. Kotwal, A. A., Cenzer, I. S., Waite, L. J., Covinsky, K. E., Perissinotto, C. M., Boscardin, W. J. et al. (2021). The Epidemiology of Social Isolation and Loneliness among Older Adults during the Last Years of Life. Journal of the American Geriatrics Society, 69, 3081-3091. https://doi.org/10.1111/jgs.17366 10.1111/jgs.1736634247388https://doi.org/10.1111/jgs.17366 Kotwal, A. Cenzer, I. Waite, L. Covinsky, K. Perissinotto, C. Boscardin, W. 2021 10.1111/jgs.17366 34247388

26.. Leach, R., Phillipson, C., Biggs, S., & Money, A. (2008). Sociological Perspectives on the Baby Boomers: An Exploration of Social Change. Quality of Ageing, 9, 19-26. https://doi.org/10.1108/14717794200800024 10.1108/14717794200800024https://doi.org/10.1108/14717794200800024 Leach, R. Phillipson, C. Biggs, S. Money, A. 2008 10.1108/14717794200800024

27.. Lin, I., & Brown, S. L. (2012). Unmarried Boomers Confront Old Age: A National Portrait. The Gerontologist, 52, 153-165. https://doi.org/10.1093/geront/gnr141 10.1093/geront/gnr14122298744https://doi.org/10.1093/geront/gnr141 Lin, I. Brown, S. 2012 10.1093/geront/gnr141 22298744

28.. Lissitsa, S., Zychlinski, E., & Kagan, M. (2021). The Silent Generation vs Baby Boomers: Socio-Demographic and Psychological Predictors of the “Gray” Digital Inequalities. Computers in Human Behavior, 128, Article 107098. https://doi.org/10.1016/j.chb.2021.107098 10.1016/j.chb.2021.107098https://doi.org/10.1016/j.chb.2021.107098 Lissitsa, S. Zychlinski, E. Kagan, M. 2021 107098 10.1016/j.chb.2021.107098

29.. McPherson, M., Smith-Lovin, L., & Brashears, M. E. (2006). Social Isolation in America: Changes in Core Discussion Networks over Two Decades. American Sociological Review, 71, 353-375. https://doi.org/10.1177/000312240607100301 10.1177/000312240607100301https://doi.org/10.1177/000312240607100301 McPherson, M. Smith-Lovin, L. Brashears, M. 2006 10.1177/000312240607100301

30.. Mehrabi, F., & Béland, F. (2020). Effects of Social Isolation, Loneliness and Frailty on Health Outcomes and Their Possible Mediators and Moderators in Community-Dwelling Older Adults: A Scoping Review. Archives of Gerontology and Geriatrics, 90, Article 104119. https://doi.org/10.1016/j.archger.2020.104119 10.1016/j.archger.2020.10411932562956https://doi.org/10.1016/j.archger.2020.104119 Mehrabi, F. Isolation, L 2020 104119 10.1016/j.archger.2020.104119 32562956

31.. Miao, M., Fang, F., Lyu, J., Liu, Z., Wan, Z., Qin, L. et al. (2025). Relationships of Social Isolation and Loneliness with Healthy Aging among Older Adults. BMC Geriatrics, 25, Article No. 267. https://doi.org/10.1186/s12877-025-05941-6 10.1186/s12877-025-05941-640269703https://doi.org/10.1186/s12877-025-05941-6 Miao, M. Fang, F. Lyu, J. Liu, Z. Wan, Z. Qin, L. 2025 No 10.1186/s12877-025-05941-6 40269703

32.. Ministry of Health (2025). Database User Manual and Code Book. National Quality Survey Life and Health 2023-2024. Santiago de Chile. https://epi.minsal.cl/bases-de-datos 2025

33.. National Academies of Sciences, Engineering, and Medicine (2020). Social Isolation and Loneliness in Older Adults: Opportunities for the Health Care System. The National Academies Press. Sciences, E 2020

34.. Nicholson, N. R. (2012). A Review of Social Isolation: An Important but Underassessed Condition in Older Adults. The Journal of Primary Prevention, 33, 137-152. https://doi.org/10.1007/s10935-012-0271-2 10.1007/s10935-012-0271-222766606https://doi.org/10.1007/s10935-012-0271-2 Nicholson, N. 2012 10.1007/s10935-012-0271-2 22766606

35.. Observatorio del Envejecimiento (2025). Soledad no deseada y aislamiento social en la vejez: Prevalencia, factores de riesgo y estrategias de acción. año 6, v37.Centro de Estudios de Vejez y Envejecimiento de la Pontificia Universidad catóLica de Chile y, Compañía de Seguros con Futuro. https://observatorioenvejecimiento.uc.cl/wp-%20content/uploads/2025/05/Reporte-ODE-37-Soledad-no-Deseada-y-Aislamiento-Social-en-la-Vejez-Prevalencia-Factores-de-Riesgo-y-Estrategias-de-Accion.pdf 2025

36.. OECD (2023). Health at a Glance 2023: OECD Indicators. OECD Publishing. 2023

37.. Olivares-Tirado, P. (2026). Social Isolation and Loneliness among Community-Dwelling Older Chilean Adults: A Gender Perspective. Open Journal of Social Sciences, 14, 222-254. https://doi.org/10.4236/jss.2026.141016 10.4236/jss.2026.141016https://doi.org/10.4236/jss.2026.141016 Olivares-Tirado, P. 2026 10.4236/jss.2026.141016

38.. Palladino, R., Tayu Lee, J., Ashworth, M., Triassi, M., & Millett, C. (2016). Associations between Multimorbidity, Healthcare Utilisation and Health Status: Evidence from 16 European Countries. Age and Ageing, 45, 431-435. https://doi.org/10.1093/ageing/afw044 10.1093/ageing/afw04427013499https://doi.org/10.1093/ageing/afw044 Palladino, R. Lee, J. Ashworth, M. Triassi, M. Millett, C. Multimorbidity, H 2016 10.1093/ageing/afw044 27013499

39.. Pan, C., Ye, J., Yu, L., & Cao, N. (2025). Reciprocal Associations between Social Isolation and Self-Rated Health among Older Adults in China: Findings from the China Longitudinal Aging Social Survey (2018-2020). Archives of Public Health, 83, Article No. 282. https://doi.org/10.1186/s13690-025-01764-4 10.1186/s13690-025-01764-4https://doi.org/10.1186/s13690-025-01764-4 Pan, C. Ye, J. Yu, L. Cao, N. 2025 No 10.1186/s13690-025-01764-4

40.. Pilehvari, A., You, W., & Lin, X. (2023). Retirement’s Impact on Health: What Role Does Social Network Play? European Journal of Ageing, 20, Article No. 14. https://doi.org/10.1007/s10433-023-00759-w 10.1007/s10433-023-00759-w37162581https://doi.org/10.1007/s10433-023-00759-w Pilehvari, A. You, W. Lin, X. 2023 No 10.1007/s10433-023-00759-w 37162581

41.. Pollak, C., Pham, Y., Ehrlich, A., Verghese, J., & Blumen, H. M. (2025). Loneliness and Social Isolation Risk Factors in Community-Dwelling Older Adults Receiving Home Health Services. BMC Geriatrics, 25, Article No. 290. https://doi.org/10.1186/s12877-025-05947-0 10.1186/s12877-025-05947-040296019https://doi.org/10.1186/s12877-025-05947-0 Pollak, C. Pham, Y. Ehrlich, A. Verghese, J. Blumen, H. 2025 No 10.1186/s12877-025-05947-0 40296019

42.. Pomeroy, M. L., Umoh, M., Qian, Y., Gimm, G., Ornstein, K. A., & Cudjoe, T. K. M. (2024). Social Isolation and Hospitalization in Community-Dwelling Older Adults by Dementia Status. The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences, 79, glae224. https://doi.org/10.1093/gerona/glae224 10.1093/gerona/glae22439275949https://doi.org/10.1093/gerona/glae224 Pomeroy, M. Umoh, M. Qian, Y. Gimm, G. Ornstein, K. Cudjoe, T. Gerontology, S 2024 10.1093/gerona/glae224 39275949

43.. Prince, M., Comas-Herrera, A., Knapp, M., Guerchet, M., & Karagiannidou, C. (2015). The Global Impact of Dementia: An Analysis of Prevalence, Incidence, Cost and Trends.World Alzheimer Report 2015, Alzheimer’s Disease International. https://www.alzint.org/u/WorldAlzheimerReport2015.pdf Prince, M. Comas-Herrera, A. Knapp, M. Guerchet, M. Karagiannidou, C. Prevalence, I 2015

44.. Puyané, M., Chabrera, C., Camón, E., & Cabrera, E. (2025). Uncovering the Impact of Loneliness in Ageing Populations: A Comprehensive Scoping Review. BMC Geriatrics, 25, Article No. 244. https://doi.org/10.1186/s12877-025-05846-4 10.1186/s12877-025-05846-440211165https://doi.org/10.1186/s12877-025-05846-4 Chabrera, C. Cabrera, E. 2025 No 10.1186/s12877-025-05846-4 40211165

45.. Rico-Uribe, L. A., Caballero, F. F., Olaya, B., Tobiasz-Adamczyk, B., Koskinen, S., Leonardi, M. et al. (2016). Loneliness, Social Networks, and Health: A Cross-Sectional Study in Three Countries. PLOS ONE, 11, e0145264. https://doi.org/10.1371/journal.pone.0145264 10.1371/journal.pone.014526426761205https://doi.org/10.1371/journal.pone.0145264 Rico-Uribe, L. Caballero, F. Olaya, B. Tobiasz-Adamczyk, B. Koskinen, S. Leonardi, M. Loneliness, S 2016 10.1371/journal.pone.0145264 26761205

46.. Russell, D., Peplau, L. A., & Cutrona, C. E. (1980). The Revised UCLA Loneliness Scale: Concurrent and Discriminant Validity Evidence. J Pers Soc Psychol., 39, 472-480. Russell, D. Peplau, L. Cutrona, C. 1980

47.. Santini, Z. I., Jose, P. E., York Cornwell, E., Koyanagi, A., Nielsen, L., Hinrichsen, C. et al. (2020). Social Disconnectedness, Perceived Isolation, and Symptoms of Depression and Anxiety among Older Americans (NSHAP): A Longitudinal Mediation Analysis. The Lancet Public Health, 5, e62-e70. https://doi.org/10.1016/s2468-2667(19)30230-0 10.1016/s2468-2667(19)30230-031910981https://doi.org/10.1016/s2468-2667(19)30230-0 Santini, Z. Jose, P. Cornwell, E. Koyanagi, A. Nielsen, L. Hinrichsen, C. Disconnectedness, P 2020 2667 19 10.1016/s2468-2667(19)30230-0 31910981

48.. Sorinmade, O., Elugbadebo, O., & Peisah, C. (2025). Ensuring Dignity in an Ageing World: Improving Care through a Human Rights Approach. Academia Mental Health and Well-Being, 2, 1-7. https://doi.org/10.20935/mhealthwellb8053 10.20935/mhealthwellb8053https://doi.org/10.20935/mhealthwellb8053 Sorinmade, O. Elugbadebo, O. Peisah, C. 2025 10.20935/mhealthwellb8053

49.. Steptoe, A., & Kivimäki, M. (2013). Stress and Cardiovascular Disease: An Update on Current Knowledge. Annual Review of Public Health, 34, 337-354. https://doi.org/10.1146/annurev-publhealth-031912-114452 10.1146/annurev-publhealth-031912-11445223297662https://doi.org/10.1146/annurev-publhealth-031912-114452 Steptoe, A. 2013 10.1146/annurev-publhealth-031912-114452 23297662

50.. Svensson, M., Rosso, A., Elmståhl, S., & Ekström, H. (2022). Loneliness, Social Isolation, and Health Complaints among Older People: A Population-Based Study from the “Good Aging in Skåne (GÅS)” Project. SSM-Population Health, 20, Article 101287. https://doi.org/10.1016/j.ssmph.2022.101287 10.1016/j.ssmph.2022.10128736387019https://doi.org/10.1016/j.ssmph.2022.101287 Svensson, M. Rosso, A. Loneliness, S 2022 101287 10.1016/j.ssmph.2022.101287 36387019

51.. Teo, R. H., Cheng, W. H., Cheng, L. J., Lau, Y., & Lau, S. T. (2023). Global Prevalence of Social Isolation among Community-Dwelling Older Adults: A Systematic Review and Meta-Analysis. Archives of Gerontology and Geriatrics, 107, Article 104904. https://doi.org/10.1016/j.archger.2022.104904 10.1016/j.archger.2022.10490436563614https://doi.org/10.1016/j.archger.2022.104904 Teo, R. Cheng, W. Cheng, L. Lau, Y. Lau, S. 2023 104904 10.1016/j.archger.2022.104904 36563614

52.. Uchino, B. N. (2006). Social Support and Health: A Review of Physiological Processes Potentially Underlying Links to Disease Outcomes. Journal of Behavioral Medicine, 29, 377-387. https://doi.org/10.1007/s10865-006-9056-5 10.1007/s10865-006-9056-516758315https://doi.org/10.1007/s10865-006-9056-5 Uchino, B. 2006 10.1007/s10865-006-9056-5 16758315

53.. UN (2020). Resolution 75/131: United Nations Decade for Healthy Ageing. https://docs.un.org/en/A/RES/75/131 2020

54.. UN (2022). United Nations Decade for Healthy Ageing:2021-2030. The Platform. https://www.decadeofhealthyageing.org/ 2022 2021 2030

55.. Warren, A. (2025). Loneliness as a Driver of Allostatic Load: Mechanisms Linking Social Disconnection to Physiological Dysregulation and Health Disparities. Stress, 28, Article 2594067. https://doi.org/10.1080/10253890.2025.2594067 10.1080/10253890.2025.2594067https://doi.org/10.1080/10253890.2025.2594067 Warren, A. 2025 2594067 10.1080/10253890.2025.2594067

56.. WHO (2020a). Decade of Healthy Ageing: Plan of Action. https://www.who.int/publications/m/item/decade-of-healthy-ageing-plan-of-action

57.. WHO (2020b). Guidelines on Physical Activity and Sedentary Behaviour. World Health Organization. https://www.who.int/publications/i/item/9789240015128

58.. WHO (2021). Social Isolation and Loneliness among Older Adults [Advocacy Brief].United Nations Department of Economic and Social Affairs. https://www.who.int/publications/i/item/9789240030749 2021

59.. WHO (2024). Ageing and Health. https://www.who.int/news-room/fact-sheets/detail/ageing-and-health 2024

60.. WHO (2025). From Loneliness to Social Connection:Charting a Path to Healthier Societies.Report of the WHO Commission on Social Connection. https://www.who.int/publications/i/item/978240112360 2025

61.. Wong, E. L., Qiu, H., Cheung, A. W., Leung, H. H., Chen, F. Y., & Yeoh, E. (2023). Association of Social Isolation with Health Status among Community-Dwelling Chinese Older Adults Living with Homecare Services: A Cross-Sectional Survey in Hong Kong. Frontiers in Public Health, 11, Article ID: 1099734. https://doi.org/10.3389/fpubh.2023.1099734 10.3389/fpubh.2023.109973437333567https://doi.org/10.3389/fpubh.2023.1099734 Wong, E. Qiu, H. Cheung, A. Leung, H. Chen, F. Yeoh, E. 2023 109973 ID 10.3389/fpubh.2023.1099734 37333567

62.. Xia, N., & Li, H. (2018). Loneliness, Social Isolation, and Cardiovascular Health. Antioxidants & Redox Signaling, 28, 837-851. https://doi.org/10.1089/ars.2017.7312 10.1089/ars.2017.731228903579https://doi.org/10.1089/ars.2017.7312 Xia, N. Li, H. Loneliness, S 2018 10.1089/ars.2017.7312 28903579

63.. Yang, R., Wang, H., Edelman, L. S., Tracy, E. L., Demiris, G., Sward, K. A. et al. (2020). Loneliness as a Mediator of the Impact of Social Isolation on Cognitive Functioning of Chinese Older Adults. Age and Ageing, 49, 599-604. https://doi.org/10.1093/ageing/afaa020 10.1093/ageing/afaa02032147683https://doi.org/10.1093/ageing/afaa020 Yang, R. Wang, H. Edelman, L. Tracy, E. Demiris, G. Sward, K. 2020 10.1093/ageing/afaa020 32147683

64.. Yildirimer, K. S. (2025). On the Threshold of Social Erosion: The Dynamic of Sociological and Psychological Collapse. IRASS Journal of Arts, Humanities and Social Sciences, 2,155-160. https://irasspublisher.com/assets/articles/1753113061.pdf Yildirimer, K. Arts, H 2025

65.. Zavaleta, D., Samuel, K., & Mills, C. T. (2017). Measures of Social Isolation. Social Indicators Research, 131, 367-391. https://doi.org/10.1007/s11205-016-1252-2 10.1007/s11205-016-1252-2https://doi.org/10.1007/s11205-016-1252-2 Zavaleta, D. Samuel, K. Mills, C. 2017 10.1007/s11205-016-1252-2

66.. Zhang, Y., Hu, W., & Feng, Z. (2021). Social Isolation and Health Outcomes among Older People in China. BMC Geriatrics, 21, Article No. 721. https://doi.org/10.1186/s12877-021-02681-1 10.1186/s12877-021-02681-134922481https://doi.org/10.1186/s12877-021-02681-1 Zhang, Y. Hu, W. Feng, Z. 2021 No 10.1186/s12877-021-02681-1 34922481