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Article

Feeling Healthy Matters: Comparing the Moderating Roles of Multimorbidity and Self-Rated Health in the Link Between Loneliness and Quality of Life

by
Hui Foh Foong
1,
Rahimah Ibrahim
1,2,*,
Mohamad Fazdillah Bagat
1,
Siti Farra Zillah Abdullah
1 and
Sook Yee Lim
1
1
Malaysian Research Institute on Ageing (MyAgeing®), Universiti Putra Malaysia, Serdang, Selangor, Malaysia
2
Department of Human Development and Family Studies, Faculty of Human Ecology, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
*
Author to whom correspondence should be addressed.
J. Gerontol. Geriatr. 2025, 73(4), 129-142; https://doi.org/10.36150/2499-6564-N844
Submission received: 9 April 2025 / Accepted: 29 September 2025 / Published: 18 December 2025
Browse Figures
Versions Notes

Background and aims

Loneliness is a significant psychosocial issue among middle-aged and older adults, negatively impacting quality of life (QoL). However, little is known about how different health measures – specifically objective (multimorbidity) and subjective (self-rated health, SRH) – moderate this association. This study investigates the moderating roles of multimorbidity and SRH in the loneliness-QoL relationship among community-dwelling middle-aged and older adults in Malaysia.

Methods

This cross-sectional analysis used baseline data from the AGELESS study, involving 1,697 participants aged 55 and above. QoL was measured using the CASP-12 scale, covering control and autonomy, self-realization, and pleasure. Loneliness was assessed using the 3-item UCLA Loneliness Scale. Multimorbidity was defined as having two or more chronic conditions, while SRH was assessed via a single-item question and categorized as “good” or “poor”. Moderation effects were tested using Model 1 of the PROCESS Macro in SPSS (5,000 bootstraps), adjusting for demographics.

Results

Loneliness was significantly and negatively associated with total QoL and all three domains. Multimorbidity did not moderate this relationship but was independently linked to poorer QoL. In contrast, SRH significantly moderated the association between loneliness and total QoL, as well as the control and autonomy and self-realization domains. The negative effect of loneliness on QoL was stronger among those reporting “good” health. Contrary to our hypothesis, the negative effect of loneliness on QoL was stronger among those reporting “good” health. Sensitivity analyses using the ordinal SRH scale confirmed these results.

Conclusions

Subjective health perception shapes how loneliness affects QoL. Middle-aged and older adults with better SRH may be more vulnerable, underscoring the need for person-centered interventions.

INTRODUCTION

With longer lifespans and declining fertility rates, the global population is aging rapidly. By 2050, the number of people aged 60 and older is projected to double, from 1 billion in 2020 to 2.1 billion 1. In Malaysia, 15% of the population is expected to be aged 60 and above by 2030 2, emphasizing the need for policies to improve older adults’ quality of life (QoL).
Understanding QoL among older adults has become increasingly important amid global population aging. QoL is shaped by a range of interrelated factors, including physical and mental health, social relationships, financial stability, and a supportive living environment 3,4. In the Malaysian context, positive self-rated health (SRH), higher educational attainment, better socioeconomic status, and strong social support have been associated with higher QoL, whereas depression, disability, and limited social connections are significant predictors of poorer QoL 5,6.
Measuring QoL through a multidimensional lens – encompassing physical, psychological, and social domains – offers a more holistic understanding of the aging experience 7,8. This comprehensive approach acknowledges the dynamic interaction between various determinants and enables researchers and policymakers to better address the complexities of aging. Ultimately, such insights are critical for designing targeted interventions and enhancing the overall well-being of older adults 9,10.
Loneliness, defined as the subjective feeling of being socially disconnected or lacking meaningful relationships, is a prevalent and pressing issue among middle-aged and older adults. It has been consistently linked to poorer health outcomes, including increased depressive symptoms, higher morbidity, and elevated mortality risk – highlighting its global significance for promoting well-being in later life 11-13. While commonly associated with older age, middle-aged adults are also vulnerable to loneliness due to factors such as caregiving responsibilities, health-related limitations, and shifting social roles 14,15. In Malaysia, loneliness is a widespread concern among older adults, warranting urgent attention from both researchers and policymakers 16.
Measuring health is a complex process that involves both objective and subjective dimensions. Objective measures, like multimorbidity, quantify health through chronic conditions affecting physical well-being and functionality 17,18. On the other hand, subjective measures, such as SRH, capture personal health perceptions influenced by psychological and social factors 19,20. In Malaysia, while 50.4% of older adults experience multimorbidity 21, only 32.6% report poor SRH 22, highlighting the complex relationship between physical health and individual perceptions.

RATIONALE FOR THE STUDY

Loneliness is a widespread issue linked to poorer QoL outcomes 23. While previous research highlights loneliness’s negative impact on QoL, the role of multimorbidity – defined as the coexistence of two or more chronic conditions – remains unclear. Multimorbidity can exacerbate loneliness through physical and social challenges, further reducing QoL 24. SRH, reflecting individuals’ perceptions of their health, also influences emotional well-being and loneliness 25. Although some evidence suggests positive health perceptions may buffer loneliness’s effects 26, research on this interaction is limited. Therefore, this study aims to address these research gaps by examining how multimorbidity and SRH, as distinct measures of objective and subjective health respectively, influence the relationship between loneliness and QoL in middle-aged and older adults.

THEORETICAL FRAMEWORK, STUDY OBJECTIVES, AND STUDY HYPOTHESES

This study integrates the stress process model (SPM) and resource-based model (RBM) of QoL to examine how health measures moderate the loneliness-QoL relationship. The SPM posits that stressors like loneliness negatively affect well-being, with contextual factors influencing the severity of these effects 27. Here, loneliness serves as the primary stressor, while multimorbidity and SRH represent contextual factors that may amplify or buffer its impact on QoL.
The RBM emphasizes how individual resources shape well-being outcomes 28. Multimorbidity may deplete coping resources, potentially intensifying loneliness’s effects, while positive SRH may function as a psychological resource that helps maintain QoL despite loneliness. However, these models also suggest that resources can create vulnerability – individuals with more resources may experience greater impact when those resources are threatened or when stressors contradict their resource perceptions.
Together, these frameworks predict that both objective (multimorbidity) and subjective (SRH) health measures will moderate the loneliness-QoL relationship, though the direction and magnitude of these effects may vary based on the specific mechanisms involved. This study aims to:
  • Examine the relationship between loneliness and QoL among community-dwelling middle-aged and older adults;
  • Evaluate the moderating effect of multimorbidity on this relationship;
  • Assess the moderating role of SRH on this relationship.
The hypotheses are: H1A: Loneliness negatively impacts QoL, with higher loneliness corresponding to lower QoL. H2A: Multimorbidity moderates the loneliness-QoL relationship, making the association stronger among those with multimorbidity. H3A: SRH moderates the loneliness-QoL relationship, with the negative impact stronger among individuals with poor SRH. Figure 1 depicts the conceptual framework of this study.

MATERIALS AND METHODS

STUDY DESIGN, PARTICIPANTS, AND DATA COLLECTION

This study used a cross-sectional correlational design and baseline data from the Transforming Cognitive Frailty into Later Life Self-Sufficiency (AGELESS) study, a longitudinal investigation of aging involving community-dwelling middle-aged and older adults aged 55 and above in Malaysia. Participants were initially recruited between 2013 and 2016 from three cohort studies: Malaysian Elders Longitudinal Research (MELoR) 29, Towards Useful Aging (TUA) 30, and the Protecting Elderly Against Abuse and Neglect (PEACE) study 31. MELoR participants were recruited through stratified random sampling using electoral rolls in the Klang Valley, while TUA and PEACE used sampling frames from the Department of Statistics Malaysia. TUA covered participants from Johor, Perak, Kelantan, and Selangor, and PEACE focused on Kuala Pilah, Negeri Sembilan 29-31.
Due to COVID-19 restrictions, a virtual survey was conducted with AGELESS participants between September 2020 and January 2022 32. Trained researchers, including postgraduate students and medical graduates, administered the survey following competency evaluations. For participants unable to respond due to cognitive decline or severe conditions, next-of-kin provided responses. Exclusion criteria included clinical diagnoses of dementia, depression, or anxiety, based on self-reported medical histories, as these conditions could affect data validity. Papers using this methodology have been published elsewhere 33-35.
Ethics approval for this study was granted by the Medical Research Ethics Committee of the University of Malaya Medical Centre (MED-ID 20191231-8121). The authors confirm that all participants provided written informed consent to participate, which was obtained during virtual interviews.

KEY VARIABLES AND MEASUREMENTS

QoL (dependent variable)

QoL was measured using the Control, Autonomy, Self-realization, and Pleasure (CASP-12) scale, designed specifically for older adults 36,37. The CASP-12 assesses four dimensions of QoL, focusing on well-being beyond physical health and is widely used in gerontological research 37. Due to the conceptual similarity between the “Control” and “Autonomy” domains – both reflecting independence and decision-making – they were combined into a single factor, as supported by factor analyses 37. This approach simplifies the scale while maintaining its reliability and validity 37. The CASP scale has also been validated among Malaysian older adults 38.
In this study, the scale measured three domains: “Control and Autonomy” (e.g., “I can do the things I want to do”), “Self-realization” (e.g., “I feel that life is full of opportunities”), and “Pleasure” (e.g., “I look forward to each day”) using a 4-point Likert format (1 = Often to 4 = Never). The scale showed good reliability (α = 0.823), with domain-specific reliabilities of 0.701 for Control and Autonomy, 0.804 for Self-realization, and 0.737 for Pleasure. Total and domain scores, treated as continuous variables, were used in moderation analysis.

Loneliness (independent variable)

This study assessed loneliness using the three-item UCLA Loneliness Scale, with items rated on a three-point Likert scale (1 = hardly ever, 2 = some of the time, 3 = often). Respondents indicated how often they felt the absence of companionship, left out, or isolated, with higher scores indicating greater loneliness. The scale, previously validated among local community-dwelling older adults 39, showed good internal consistency (α = 0.839) in this study. The total score, treated as a continuous variable, was included in moderation analysis.

Objective (multimorbidity) and subjective (SRH) measures of health status (moderator)

Participants’ objective health status was assessed by evaluating multimorbidity, defined as having two or more chronic conditions 40. They were asked whether they had been diagnosed with any of 17 medical conditions, including hypertension, high cholesterol, diabetes, stroke, joint problems, heart disease, cataracts or glaucoma, chronic kidney disease, asthma, chronic lung disease, tuberculosis, gout, hip fracture, thyroid disorders, gastric pain, cancer, or urinary problems 21. For moderation analyses, multimorbidity was treated as a binary variable (yes vs no). This dichotomous approach, widely used in epidemiological research 41,42, reflects a clinically significant threshold that distinguishes individuals at higher risk for adverse outcomes.
Subjective health status was measured using a single-item SRH scale 43, asking participants to rate their health over the past month on a 5-point Likert scale: 1 (ill most of the time) to 5 (well most of the time). For moderation analysis, responses were recoded into a binary format: 4 and 5 as “good” health, indicating positive health perceptions despite occasional unwellness, and 1 to 3 as “poor” health, reflecting more frequent unwellness 44. This binary categorization aligns with standard practice in aging research where SRH is dichotomized to distinguish between positive versus negative health perceptions, which has been shown to predict outcomes like mortality and morbidity more robustly than continuous measures 45,46. Moreover, this recategorization enhances interpretability and clinical relevance in moderation analyses, facilitating the identification of differential effects in applied settings 47,48.

Control and demographic variables

Demographic characteristics, including gender, age, ethnicity, education level, and marital status, were included as control variables in the moderation analysis. Ethnicity was categorized as Bumiputera (indigenous peoples, including Malays and native groups in East Malaysia) and Non-Bumiputera (primarily Chinese and Indians). Education was grouped into formal education and no formal education, while marital status was coded as married and non-married. Age was treated as a continuous variable.

DATA PREPARATION AND ANALYTIC STRATEGY

Descriptive statistics summarized the sample and variable characteristics. Chi-square tests and independent samples t-tests were conducted to assess associations and gender differences among the study variables. Additionally, Pearson’s correlation analysis was performed to examine the preliminary relationships among these variables.
Model 1 of the PROCESS Macro in SPSS was used with 5000 bootstrap samples to assess moderating effects, while controlling for previously mentioned variables. Significant moderation was indicated by significant R2 change (ΔR2) with confidence intervals that did not include zero. To illustrate these effects, slopes were plotted using visualization codes generated during the analysis, depicting how the loneliness-QoL relationship varied by levels of multimorbidity or SRH 49. When moderation was significant, post-hoc tests compared the simple slopes for “good” versus “poor” health, providing a localized view of the effect within subgroups, as described in previous methods 50. Then, the moderation effect size (f2) was determined using the guidelines provided in Liu and Yuan 51.
Next, a sensitivity analysis was conducted to test the robustness of our main findings. Instead of using categorical moderators, as in the primary analysis, continuous measures were employed: the number of chronic conditions for objective health and the original 5-point Likert scale for subjective health.

RESULTS

SAMPLE CHARACTERISTICS AND DESCRIPTIONS OF STUDY VARIABLES

Table I shows the sample characteristics and descriptions of study variables. This study included 1,697 community-dwelling Malaysian older adults, with a majority being female (59%). The participants’ average age was 72.39 ± 6.86 years. Most participants were from non-Bumiputera ethnicities (66.9%) and had attended formal education (93.8%). A substantial proportion were currently married (70.3%). Although majority had multimorbidity (69.8%), 90% still rated their health status as “good” health. Chi-square analysis revealed no significant association between gender and multimorbidity or between gender and SRH.
Females reported significantly higher loneliness (Mean = 3.74 ± 1.36) than males (Mean = 3.52 ± 1.12), t (1695) = -3.66, p < 0.001. Regarding QoL, there was no significant difference in total scores between males and females. However, females scored significantly lower in the domains of self-realization (Mean = 10.21 ± 1.89 vs. Mean = 10.43 ± 1.85; t (1695) = 2.44, p = 0.015) and pleasure (Mean = 11.17 ± 1.49 vs. Mean = 11.36 ± 1.36; t (1695) = 2.67, p = 0.008) compared to males.

BIVARIATE CORRELATIONS AMONG MAIN STUDY VARIABLES

Pearson’s correlation analysis was conducted to determine whether the main variables in the study were meaningfully interrelated. The results showed that loneliness was negatively correlated with overall QoL (r = -0.37, p < 0.001) and its domains: control and autonomy (r = -0.36), self-realization (r = -0.25), and pleasure (r = -0.25), all with p < 0.001. Additionally, multimorbidity was associated with higher loneliness (r = 0.10, p < 0.001) and poorer SRH (r = 0.22, p < 0.001). Both correlations (r < 0.7) indicated no evidence of multicollinearity in the following moderation analysis 52. Furthermore, significant correlations were observed between multimorbidity, SRH, and all aspects of QoL. Multimorbidity was also associated with poorer SRH (r = 0.12, p < 0.001) (Tab. II).

THE MODERATING ROLE OF MULTIMORBIDITY ON THE RELATIONSHIP BETWEEN LONELINESS AND QOL (AND ITS DOMAIN)

Model 1 of the PROCESS Macro moderation test revealed that the objective measure of health status –multimorbidity – did not moderate the association between loneliness and QoL (and its domains). As shown in Table III, the ΔR2 after including the interaction term was not significant for total QoL (ΔR2 < 0.001; LLCI, ULCI = -0.676, 0.308), control and autonomy (ΔR2 < 0.001; LLCI, ULCI = -0.296, 0.308), self-realization (ΔR2 = 0.001; LLCI, ULCI = -0.262, 0.077), or pleasure (ΔR2 = 0.002; LLCI, ULCI = -0.249, 0.012). Multimorbidity was negatively associated with total QoL (B = -1.19, p < 0.001), control and autonomy (B = -0.82, p < 0.001), and self-realization (B = -0.25, p = 0.012), but not pleasure (B = -0.11, p = 0.168) (Tab. III).

THE MODERATING ROLE OF SRH ON THE RELATIONSHIP BETWEEN LONELINESS AND QOL (AND ITS DOMAIN)

Interestingly, in contrast to the results in the previous section, the moderation analysis revealed that SRH moderated the association between loneliness and total QoL (ΔR2 = 0.005; LLCI, ULCI = 0.277, 1.398), the domain of control and autonomy (ΔR2 = 0.005; LLCI, ULCI = 0.184, 0.860), and self-realization (ΔR2 = 0.003; LLCI, ULCI = 0.014, 0.415), but not pleasure (ΔR2 = 0.001; LLCI, ULCI = -0.078, 0.223). The moderation effects were small for total QoL (f2 = 0.007) and control and autonomy (f2 = 0.007), and very small for self-realization (f2 = 0.004). In addition, poor SRH was negatively associated with total QoL (B = -5.73, p < 0.001) and all domains of QoL (control and autonomy: B = -3.16, p < 0.001; self-realization: B = -1.51, p < 0.001; pleasure: B = -0.99, p < 0.001) (see Table IV).
Figure 2 illustrates that peak QoL was observed among older adults with “good” health and lower loneliness, while the lowest QoL was reported among those with “poor” health and higher loneliness, a trend consistent across all QoL domains. Notably, these findings contradict our original hypothesis H3A, which predicted that the negative impact of loneliness on QoL would be stronger among individuals with poor SRH. Instead, our results revealed the opposite pattern—the loneliness-QoL relationship was significantly stronger among those reporting good SRH.

POST-HOC ANALYSIS OF DIFFERENCES IN SIMPLE SLOPES

Since the global moderation test confirmed the moderating effects of SRH on the relationship between loneliness and total QoL, as well as on the domains of control and autonomy and self-realization, a post-hoc analysis was conducted to compare the simple slopes between individuals with “good” and “poor” health. For total QoL, the slope was significantly steeper for those with “good” health (B = -1.52, S.E. = 0.13) compared to those with “poor” health (B = -0.68, S.E. = 0.26) (t = 2.164, p = 0.031). In the domain of control and autonomy, a similar pattern was observed, with participants rating their health as “good” showing a steeper slope (B = -0.97, S.E. = 0.08) than those with “poor” health (B = -0.45, S.E. = 0.16) (t = 2.235, p = 0.026). For self-realization, there was no significant difference between the slopes for “good” (B = -0.31, S.E. = 0.05) and “poor” (B = -0.10, S.E. = 0.09) health (t = 1.548, p = 0.122). These findings suggest a stronger negative association between loneliness and QoL for those with “good” health.

SENSITIVITY ANALYSIS

To verify the robustness of our binary SRH categorization, we conducted sensitivity analyses using the original 5-point ordinal scale (1 = ill most of the time to 5 = well most of the time), which confirmed that our main findings remained consistent regardless of whether SRH was treated as a binary or ordinal variable. As shown in Table V, consistent with the main findings, the number of chronic conditions did not moderate the association between loneliness and total QoL or most of its domains. Although the number of chronic conditions appeared to moderate the loneliness-self-realization link, the effect size was very small and practically negligible (ΔR2 = 0.002; LLCI, ULCI = -0.073, -0.002; f2 = 0.002). Overall, this analysis confirmed our main finding: multimorbidity did not moderate the loneliness-total QoL relationship. In addition, the ordinal measure of SRH was the only significant moderator for the loneliness-control and autonomy link. These results suggested that a binary categorization of SRH captures the moderating effect more effectively, with greater sensitivity and practical meaning. Therefore, our main analysis was validated.

DISCUSSION

The findings of this study reveal a significant negative correlation between loneliness and QoL, supporting Hypothesis H1A and consistent with prior research on loneliness’s detrimental effects on well-being. Ahadi and Hassani showed that loneliness negatively impacts QoL directly and indirectly 53, with depression as a key mediating factor. Additionally, the lack of meaningful social connections plays a crucial role, as these connections provide emotional support and a sense of belonging 54. Loneliness manifests as emotional loneliness (lack of close relationships) and social loneliness (deficiency in broader social networks) 55, both of which significantly impair well-being 16.
This study also provides insights into the moderating roles of multimorbidity and SRH in the loneliness-QoL relationship. While multimorbidity, an objective health measure, did not significantly moderate the relationship (rejecting Hypothesis H2A), SRH, a subjective health measure, demonstrated a clear moderating effect (failing to reject Hypothesis H3A).
The absence of a moderating role for multimorbidity may reflect how older adults perceive and manage chronic conditions. While multimorbidity, defined as multiple chronic illnesses, negatively affects QoL and increases vulnerability to mental health issues 42,56, effective management through treatment can reduce its impact 57. When chronic conditions are well-managed, their influence on QoL may diminish, allowing factors like loneliness to become more significant. Thus, subjective health perceptions, captured by SRH, may play a greater role in the loneliness-QoL relationship.
Supporting the earlier argument, this study found that SRH significantly moderated the relationship between loneliness and QoL, emphasizing the role of subjective health in shaping psychosocial well-being. Interestingly, the moderating pattern differed from the original hypothesis. While it was expected that the negative impact of loneliness on QoL would be stronger among those with “poor” SRH, the findings revealed that this relationship was actually more pronounced among individuals with “good” SRH. This unexpected finding represents an important empirical contribution that challenges conventional assumptions about the protective role of positive health perceptions against psychosocial stressors. This paradoxical pattern aligns with international literature that documents counterintuitive relationships between positive health perceptions and psychosocial vulnerability. For example, Cornwell and Waite found that social isolation intensifies psychological distress particularly in older adults who otherwise report strong self-perceived health 58, implying that subjective health may amplify rather than mitigate vulnerability to social risks. Similarly, research shows that older adults with better SRH but lacking social ties exhibit sharper declines in well-being over time than those with poorer health 59, underscoring the “hidden vulnerability” of socially isolated but otherwise healthy elders, indicating that positive SRH does not buffer against the impacts of social stress.
Several theoretical mechanisms may explain this phenomenon. The “ceiling effect” hypothesis 60 suggests that individuals with good SRH operate from a higher baseline, making them more susceptible to relative declines when faced with psychosocial stressors like loneliness. Their elevated starting point creates greater potential for perceived loss when social connections deteriorate. Additionally, the “multiple discrepancies” theory 61 posits that those with positive health perceptions maintain higher expectations for overall well-being, including social fulfilment. When loneliness occurs, the discrepancy between expected and experienced QoL becomes more pronounced, amplifying negative impacts. These findings collectively suggest that positive health perceptions may create psychological frameworks that paradoxically increase vulnerability to specific stressors, highlighting the complex interplay between subjective health assessments and psychosocial resilience in aging populations.
Unlike objective measures, SRH integrates physical, emotional, and social dimensions, offering a comprehensive view of health 62. Older adults with better SRH often feel more independent 63, socially connected 64, and better equipped to cope with loneliness 65, which enhances their QoL. This supports the stress-buffering hypothesis, where positive health perceptions mitigate stressors like loneliness 66. Conversely, those with poorer SRH may struggle more with the psychological and social challenges of loneliness, amplifying its negative effects on QoL.
The study found that SRH moderated the relationship between loneliness and QoL in a domain-specific manner. SRH significantly influenced the effects of loneliness on overall QoL, as well as the control and autonomy and self-realization domains, but not the pleasure domain. Control and autonomy and self-realization are linked to an individual’s sense of independence and personal fulfillment, which are crucial for older adults to navigate aging and health challenges 67. Loneliness can undermine a sense of control, increasing helplessness and negatively affecting self-realization 68. In contrast, the pleasure domain may be less impacted by SRH because it relies more on external social interactions and activities that foster joy, which are less dependent on internal health perceptions 69. This suggests that pleasure may remain resilient to health-related challenges, relying more on social and environmental factors.
Older adults with “good” SRH experienced a significantly stronger negative association between loneliness and QoL compared to those with poorer SRH, suggesting they may be more sensitive to loneliness’s impact. One explanation is that individuals with “good” SRH likely have higher expectations for their social lives and well-being 70. Their positive health perceptions may enable active, socially engaging lifestyles, making loneliness particularly disruptive. Conversely, those with poorer SRH may have adapted to reduced social interaction or adjusted expectations due to physical or functional limitations 71, buffering the impact of loneliness. Additionally, resilience differences could play a role. Healthier older adults may have faced fewer difficulties, potentially limiting their coping mechanisms, while those with poorer health often develop stronger resilience to handle stressors 72,73, leaving the former more vulnerable to loneliness’s effects on QoL.
While our findings provide valuable insights into the relationship between loneliness, health perceptions, and QoL, it is important to acknowledge the cultural context of Malaysia and its potential impact on generalizability. Several cultural factors may influence how our results translate to other settings. First, Malaysian society emphasizes strong family ties and intergenerational support systems, which are deeply rooted in Confucian, Islamic, and traditional values across the country’s diverse ethnic groups 74. In this context, loneliness may be particularly distressing because it contradicts cultural expectations of family-centered social support. Individuals with good SRH may feel greater pressure to maintain active family and community roles, making loneliness especially disruptive to their sense of purpose and well-being. This cultural dynamic may explain why the loneliness-QoL relationship was stronger among those with good SRH in our sample. Second, the meaning and interpretation of SRH may differ across cultural contexts. In Malaysian culture, health is often viewed holistically, encompassing physical, spiritual, and social well-being 75. Positive SRH may therefore reflect not just physical wellness but also social integration and spiritual harmony. When loneliness occurs, it may represent a more comprehensive threat to this holistic health concept, potentially explaining the stronger negative associations we observed. Finally, cultural expectations regarding aging in Malaysia emphasize active community participation and continued family contributions 76. Older adults with good health may be expected to maintain these roles, making social isolation particularly challenging to their cultural identity and self-worth. These expectations may differ significantly from more individualistic cultures where aging is viewed differently.

THEORETICAL IMPLICATIONS

The findings provide enhanced insights into the interplay between loneliness, health status, and QoL that reinforce both SPM and the RBM of QoL. Consistent with the SPM, the study confirmed that loneliness serves as a significant stressor that detrimentally impacts QoL across multiple domains. In addition, the differential moderating roles of subjective and objective health measures further enrich these theoretical perspectives. Specifically, the finding that SRH significantly moderated the loneliness – QoL association – particularly for overall QoL, control and autonomy, and self-realization – supports the RBM’s assertion that personal resources, such as positive self-perceptions of health, can buffer against the negative impacts of stressors. Conversely, the absence of a moderating effect for multimorbidity indicates that objective health measures may not capture the subjective subtleties that determine an individual’s ability to manage the adverse effects of loneliness. This distinction emphasizes the value of incorporating both subjective and objective assessments of health within these theoretical frameworks, thereby enhancing our understanding of the complex mechanisms through which loneliness influences well-being.

PRACTICAL IMPLICATIONS

The findings have significant practical implications for improving the QoL among older adults. Given the significant moderating effect of SRH on the loneliness–QoL relationship, interventions that enhance individuals’ subjective health perceptions – through tailored health education, counseling, and community support – may help buffer the adverse effects of loneliness. Such initiatives could be particularly effective in boosting QoL in specific domains, including control, autonomy, and self-realization. Moreover, the domain-specific effects observed in this study highlight the importance of measuring QoL at a granular level, as domain-specific assessments can provide more precise insights into which areas of well-being are most affected by loneliness and guide the development of targeted, health-related interventions. Although multimorbidity did not significantly moderate the loneliness – QoL link in our study, its role in overall health management should not be underestimated. This finding suggests that, while the current level of multimorbidity may not yet be exerting a substantial impact on QoL, it is crucial to interpret these results with caution and continue to monitor and manage chronic conditions in older populations.

LIMITATIONS OF THE STUDY

While this study provides insights into the moderating roles of multimorbidity and SRH on the relationship between loneliness and QoL among community-dwelling older adults, some limitations should be noted. First, the cross-sectional design restricts the ability to infer causation, as the observed relationships are associative. Future research should employ longitudinal designs to validate these findings and explore causal pathways. Second, multimorbidity was assessed through self-reported diagnoses, which may not fully reflect objective health measures and could introduce recall bias. Future studies should consider using medical records from healthcare settings to obtain more accurate assessments of multimorbidity and validate the results.
Third, our study was conducted within the specific cultural context of Malaysia, which may limit the generalizability of our findings to other cultural settings. The relationships between loneliness, health perceptions, and QoL may be influenced by cultural norms regarding social support, family obligations, health beliefs, and aging expectations that are specific to Malaysian society. Future research should examine these relationships across diverse cultural contexts to determine whether our findings are universal or culturally specific. Fourth, several potential residual confounders may also influence our findings. Subclinical depression, cognitive function, and personality factors were not measured but could affect health perceptions, experiences of loneliness, and QoL ratings. Fifth, our subjective loneliness measure did not capture objective social isolation indicators (e.g., network size, contact frequency), which may have different relationships with health outcomes. Finally, unmeasured health and lifestyle factors such as physical activity levels, sleep quality, pain levels, and socioeconomic status could also confound the observed associations.

CONCLUDING REMARKS

This study examined the interplay between loneliness, health status, and QoL among community-dwelling middle-aged and older adults. It revealed that while loneliness adversely affects QoL overall, its impact is differentially moderated by health measures. Specifically, multimorbidity – a measure of objective health – did not moderate the loneliness – QoL relationship, whereas SRH significantly influenced this link, particularly for total QoL and the domains of control and autonomy and self-realization. Notably, participants with “good” SRH exhibited a stronger negative association between loneliness and QoL, suggesting that those with positive health perceptions may be more sensitive to the detrimental effects of loneliness. While our hypothesis regarding SRH was not supported as originally formulated, the contradictory findings provide valuable empirical insights that advance our understanding of how health perceptions interact with psychosocial stressors. These unexpected results demonstrate that contradictory findings can be as valuable as confirmatory results in advancing our understanding of aging processes. Overall, these findings highlight the importance of focusing on subjective health perceptions in interventions aimed at alleviating loneliness and improving the well-being of older adults, advocating for domain-specific, person-centered strategies to effectively enhance QoL.

Conflict of interest statement

The authors declare no conflict of interest.

Funding

The Transforming Cognitive Frailty to Later-Life Self-sufficiency (AGELESS) study is funded by the Ministry of Higher Education Malaysia Long Term Research Grant Scheme (LRGS/1/2019/UM/1/1).

Author contributions

HFF, SYL: conducted data cleaning and analysis; HFF, SFZA, SYL, MFB: completed the first draft; RI: reviewed and corrected the first draft. All authors read and approved the final manuscript.

Ethical consideration

Ethics approval for this study was granted by the Medical Research Ethics Committee of the University of Malaya Medical Centre (MED-ID 20191231-8121). The authors confirm that all participants provided written informed consent to participate, which was obtained during virtual interviews.

History

Received: April 9, 2025
Accepted: September 29, 2025
Published online: Dec 18, 2025

Figures and tables

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Figure 1. Conceptual framework. Blue variable indicates independent variable, green variable indicates dependent variable, red variable indicates moderator, black arrow indicates direct effect, and red arrow indicates moderating pathway. The analysis also included control variables (gender, age, ethnicity, marital status, and educational level) but these are not shown in the figure.
Figure 1. Conceptual framework. Blue variable indicates independent variable, green variable indicates dependent variable, red variable indicates moderator, black arrow indicates direct effect, and red arrow indicates moderating pathway. The analysis also included control variables (gender, age, ethnicity, marital status, and educational level) but these are not shown in the figure.
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Figure 2. The interaction between loneliness and self-rated health on quality of life (and its domains)
Figure 2. The interaction between loneliness and self-rated health on quality of life (and its domains)
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Table I. Sample characteristics and descriptions of study variables (n = 1697).
Table I. Sample characteristics and descriptions of study variables (n = 1697).
Mean ± SD or percentageGenderChi square statistics or t-valuep value
Male (41%)Female (59%)
Mean ± SD or percentageMean ± SD or percentage
Age (min, max = 56, 97)72.39 ± 6.8672.9372.032.670.008a
6.676.97
EthnicityBumiputera33.1034.4032.200.920.339b
Non-bumiputera66.9065.6067.80
Education levelNo formal education6.200.909.8055.19< 0.001b
Formal education93.8099.1090.20
Marital statusMarried70.3089.3057.20199.98< 0.001b
Non-married29.7010.7042.80
Multimorbidity statusYes69.8070.9069.100.620.432b
No30.2029.1030.90
SRH“Good”90.0090.6089.600.360.548b
“Poor”10.009.4010.40
Loneliness (min, max = 3, 9)3.65 ± 1.273.52 ± 1.123.74 ± 1.36-3.66< 0.001a
Total QoL (min, max = 12, 48)41.08 ± 5.6441.33 ± 5.5140.90 ± 5.731.560.120a
Control and autonomy (min, max = 6, 24)19.53 ± 3.4319.54 ± 3.5019.52 ± 3.390.130.900a
Self-realization (min, max = 3, 12)10.30 ± 1.8810.43 ± 1.8510.21 ± 1.892.440.015a
Pleasure (min, max = 3, 12)11.25 ± 1.4411.36 ± 1.3611.17 ± 1.492.670.008a
a independent sample t-test; b chi-square test; QoL: quality of life; SRH: self-rated health.
Table II. Bivariate correlations among study variables.
Table II. Bivariate correlations among study variables.
1234567
r (p value)r (p value)r (p value)r (p value)r (p value)r (p value)r (p value)
Loneliness1
Multimorbidity (0 = no, 1 = yes)0.10 (< 0.001)1
SRH (0 = “good”, 1 = “poor”)0.22 (< 0.001)0.12 (< 0.001)1
Total QoL-0.37 (< 0.001)-0.14 (< 0.001)-0.36 (< 0.001)1
Control and autonomy-0.36 (< 0.001)-0.15 (< 0.001)-0.33 (< 0.001)0.89 (< 0.001)1
Self-realization-0.25 (< 0.001)-0.10 (< 0.001)-0.27 (< 0.001)0.81 (< 0.001)0.50 (< 0.001)1
Pleasure-0.25 (< 0.001)-0.06 (0.024)-0.26 (< 0.001)0.75 (< 0.001)0.45 (< 0.001)0.68 (< 0.001)1
*** p < 0.001; QoL: quality of life; SRH: self-rated health.
Table III. The moderating role of multimorbidity on the relationship between loneliness and QoL (and its domain).
Table III. The moderating role of multimorbidity on the relationship between loneliness and QoL (and its domain).
Dependent variable = QoL and its domainsTotal QoLDomain 1: control and autonomyDomain 2: self-realizationDomain 3: pleasure
B (SE)p valueB (SE)p valueB (SE)p valueB (SE)p value
Gender (0= male, 1= female)-0.09 (0.29)0.7470.16 (0.18)0.381-0.15 (0.10)0.130-0.09 (0.08)0.271
Age-0.09 (0.02)< 0.001-0.03 (0.01)0.016-0.04 (0.01)< 0.001-0.02 (0.01)< 0.001
Ethnicity (0= non Bumiputera, 1= Malay and other Bumiputera)-0.19 (0.28)0.498-0.09 (0.17)0.617-0.11 (0.10)0.277-0.01 (0.07)0.933
Marital status (0= married, 1= non-married)0.07 (0.31)0.8370.04 (0.19)0.8310.02 (0.11)0.825-0.03 (0.08)0.752
Education level (0= formal education, 1= no formal education)-3.0 (0.57)< 0.001-1.10 (0.35)0.002-0.99 (0.20)< 0.001-0.92 (0.15)< 0.001
Loneliness-1.36 (0.22)< 0.001-0.93 (0.14)< 0.001-0.27 (0.08)0.001-0.17 (0.06)0.005
Multimorbidity (0= no, 1= yes)-1.19 (0.29)< 0.001-0.82 (0.18)< 0.001-0.25 (0.10)0.012-0.11 (0.08)0.168
Interaction (multimorbidity * loneliness)-0.18 (0.25)0.4630.01 (0.15)0.968-0.09 (0.09)0.283-0.12 (0.07)0.076
ΔR2 after including interaction term (p ΔR2)< 0.001 (0.463)< 0.001 (0.968)0.001 (0.283)0.002 (0.076)
95% CI of interaction term (LLCI, ULCI)(-0.676, 0.308)(-0.296, 0.308)(-0.262, 0.077)(-0.249, 0.012)
ΔR2 = R2 change; B: unstandardized coefficient; SE: standard error; QoL: quality of life; 0: reference group; 1: non-reference group; CI: confidence interval; LLCI: lower-level confidence interval; ULCI: upper-level confidence interval.
Table IV. The moderating role of SRH on the relationship between loneliness and QoL (and its domain).
Table IV. The moderating role of SRH on the relationship between loneliness and QoL (and its domain).
Dependent variable = QoL and its domainsTotal QoLDomain 1: Control and autonomyDomain 2: Self-realizationDomain 3: Pleasure
B (SE)p valueB (SE)p valueB (SE)p valueB (SE)p value
Gender (0=male, 1=female)< 0.01 (0.31)0.9990.22 (0.19)0.240-0.09 (0.11)0.410-0.12 (0.08)0.168
Age-0.08 (0.02)< 0.001-0.03 (0.01)0.058-0.03 (0.01)< 0.001-0.02 (0.01)0.001
Ethnicity (0= non bumiputera, 1= Malay and other bumiputera)-0.23 (0.29)0.421-0.26 (0.17)0.1360.02 (0.10)0.8380.01 (0.08)0.999
Marital status (0= married, 1= non-married)0.38 (0.33)0.2440.24 (0.20)0.2230.07 (0.12)0.5790.03 (0.09)0.749
Education level (0= formal education, 1= no formal education)-2.50 (0.56)< 0.001-0.87 (0.34)0.010-0.87 (0.20)< 0.001-0.82 (0.15)< 0.001
Loneliness-1.52 (0.13)< 0.001-0.97 (0.08)< 0.001-0.31 (0.05)< 0.001-0.24 (0.03)< 0.001
SRH (0=good, 1=poor)-5.73 (0.51)< 0.001-3.16 (0.31)< 0.001-1.51 (0.18)< 0.001-0.99 (0.14)< 0.001
Interaction (SRH * loneliness)0.84 (0.29)0.0030.52 (0.17)0.0020.21 (0.10)0.0360.07 (0.08)0.347
ΔR2 after including interaction term (p ΔR2)0.005 (0.003)0.005 (0.002)0.003 (0.036)0.001 (0.347)
95% CI of interaction term (LLCI, ULCI)(0.277, 1.398)(0.184, 0.860)(0.014, 0.415)(-0.078, 0.223)
f2 effect size (Liu and Yuan (2020)’s 51 benchmark)0.007 (small)0.007 (small)0.004 (very small)Not applicable as interaction term is not significant
ΔR2 = R2 change; B: unstandardized coefficient; SE: standard error; QoL: quality of life; SRH: self-rated health; 0: reference group; 1: non-reference group; CI: confidence interval; LLCI: lower-level confidence interval; ULCI: upper-level confidence interval.

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MDPI and ACS Style

Foong, H.F.; Ibrahim, R.; Bagat, M.F.; Abdullah, S.F.Z.; Lim, S.Y. Feeling Healthy Matters: Comparing the Moderating Roles of Multimorbidity and Self-Rated Health in the Link Between Loneliness and Quality of Life. J. Gerontol. Geriatr. 2025, 73, 129-142. https://doi.org/10.36150/2499-6564-N844

AMA Style

Foong HF, Ibrahim R, Bagat MF, Abdullah SFZ, Lim SY. Feeling Healthy Matters: Comparing the Moderating Roles of Multimorbidity and Self-Rated Health in the Link Between Loneliness and Quality of Life. Journal of Gerontology and Geriatrics. 2025; 73(4):129-142. https://doi.org/10.36150/2499-6564-N844

Chicago/Turabian Style

Foong, Hui Foh, Rahimah Ibrahim, Mohamad Fazdillah Bagat, Siti Farra Zillah Abdullah, and Sook Yee Lim. 2025. "Feeling Healthy Matters: Comparing the Moderating Roles of Multimorbidity and Self-Rated Health in the Link Between Loneliness and Quality of Life" Journal of Gerontology and Geriatrics 73, no. 4: 129-142. https://doi.org/10.36150/2499-6564-N844

APA Style

Foong, H. F., Ibrahim, R., Bagat, M. F., Abdullah, S. F. Z., & Lim, S. Y. (2025). Feeling Healthy Matters: Comparing the Moderating Roles of Multimorbidity and Self-Rated Health in the Link Between Loneliness and Quality of Life. Journal of Gerontology and Geriatrics, 73(4), 129-142. https://doi.org/10.36150/2499-6564-N844

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