Loneliness among community-dwelling older adults during the early stage of the Covid-19 pandemic in Taiwan: exploring community-level and individual-level predictors

Loneliness among community-dwelling older adults during the early stage of the Covid-19 pandemic in Taiwan: exploring community-level and individual-level predictors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Loneliness among community-dwelling older adults during the early stage of the Covid-19 pandemic in Taiwan: exploring community-level and individual-level predictors Honghui Pan, LiFan Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6401946/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Loneliness has arisen in policy agenda as a major societal challenge in many western countries. However, little empirical evidence has been provided on loneliness of community-dwelling older adults in Taiwan, a fast-ageing society in east Asia. This study aimed to describe the status quo of and explore the risk factors to loneliness among Taiwanese ageing population during the covid-19 pandemic in Taiwan. Methods We used secondary data analysis of University Responsibility dataset from National Cheng Kung University in Tainan city, Taiwan. 530 older adults aged 65 and above were included in this study. Loneliness was measured by the 6-item De Jong Gierveld loneliness scale (2006). We used hierarchical multiple linear regression analysis to examine the community level risk factors (i.e. non-age-friendly environment, lower social capital in the community, lower levels of social support from family/friends) and individual risk factors (i.e. negative perceptions of physical living environment, lower levels of social participation). We also included demographic covariates of age, gender, marital status, ethnicity, educational level, health and income in the analysis. Results Regarding the status quo of loneliness of our sample (N = 530), 59.2% suffer from moderate loneliness while 19.6% severe loneliness. The predictors at the community level include : social capital in the community (β = -0.562, p < 0.01, 95% CI [-0.975, -0.149]), while at the individual level: housing satisfaction (β = -0.702, p < 0.01, 95% CI [-1.218, -0.186]). Three covariates (i.e. self-rated health, marital status, low-income status) are also significant predictors. Conclusions This study highlights the importance of both community level factors and individual factors in delivering effective interventions to alleviate loneliness among older Taiwanese adults. We put forward two practical suggestions. First, community-based initiatives to alleviate loneliness should focus on building community social capital. Second, fostering older adults’ housing satisfaction can be beneficial for effective intervention. Taiwan loneliness risk factors older adults social capital physical living environment social participation 1. Introduction Taiwan is experiencing rapid population aging, with adults aged 65 and above projected to exceed 20% of the population by 2025 [ 1 ]. While Taiwan's collectivist culture traditionally emphasizes filial piety and family support for older adults, urbanization, shrinking household sizes, and shifting caregiving norms have weakened these traditional safeguards [ 2 ]. These demographic and social changes may heighten vulnerability to loneliness— a subjective feeling of distress resulting from a discrepancy between desired and actual social relationships [ 3 ]. Loneliness in later life is linked to poorer mental and physical health [ 4 ], prompting policy attention in Western societies. However, its predictors or risk factors in non-Western contexts like Taiwan remain understudied. The COVID-19 pandemic exacerbated these concerns. While Taiwan's early containment measures (e.g., mask mandate, contact tracing, quarantines) reduced infections [ 5 ], older adults—already at higher risk of severe outcomes [ 6 , 7 ]—faced intensified isolation due to restricted family visits and social activities [ 8 ]. For those living alone, disrupted family interactions deepened loneliness and mental health risks [ 9 ]. This unique context underscores the need to examine loneliness during the pandemic's early stage filled with uncertainties. There is a long-standing research tradition of studying risk factors to loneliness from perspective of individual factors. These include gender [ 10 ], ethnicity [ 11 ], socio-economic status [ 12 ], or individual life events such as retirement [ 13 ], widowerhood [ 14 ], fear of falling [ 15 ]. We argue that this predominant focus has often overlooked the role of community level factors such as community social environment (e.g. the presence of community stores), social capital (e.g. high level of mutual help or social interaction in the community). In this sense, this article helps to fill in the research gap in addressing the role of community level risk factors to loneliness in a less-studied context. Understanding these dynamics is critical for developing culturally appropriate interventions to mitigate loneliness and improve well-being in Taiwan’s rapidly ageing society. In light of the above discussions, the purpose of this article is to 1) understand the incidence of loneliness during the early stage of covid-19 pandemic in Taiwan 2) explore the risk factors (both at the community level and individual level) to loneliness In the next section, we put forward six hypotheses to explore the risk factors to loneliness among older Taiwanese adults. 2. Theoretical framework and hypothesis Social capital, as manifested through mutual help, refers to the collective value of trust, reciprocity and cooperative networks that merge when community members actively support one another within the community [ 16 ]. Everyday small acts of mutual help such as neighbors sharing resources, offering emotional support or collaborating on local projects, can boost older adults’ social network and decrease loneliness [ 17 , 18 ]. Ultimately, social capital fosters meaningful social contact, which in turn helps reduce loneliness among older adults by strengthening their sense of being connection [ 19 ]. Accordingly, we put forward the first hypothesis. H1: Higher social capital in the community is associated with lower loneliness. Social support plays a role in reducing loneliness among older adults by providing emotional comfort, practical assistance, and opportunities for meaningful social engagement [ 20 ]. Research demonstrates that social support, facilitated by structured social interventions, such as community programs and peer support groups, can significantly reduce loneliness among older adults by fostering regular social interaction [ 21 ]. Emotional support from family, friends, and caregivers helps older adults feel valued and connected, while instrumental support, such as assistance with daily activities, reinforces communal interdependence and trust (Hagan et al., 2022) [ 22 ]. Research has also shown that technology-mediated support, including virtual social networks and telecommunication tools, has also proven effective in combating loneliness among older adults, particularly during public health crisis like the coronavirus pandemic pandemic when in-person interactions are reduced [ 23 ]. Accordingly, we put forward the second hypothesis. H2: Lower social support from friends/family acts as risk factor to loneliness. An age-friendly environment, adapted to the (changing) needs of older adults’ physical and social situation, can effectively reduce loneliness among older adults. This aligns with the environmental gerontology theories, such as the ecological model of ageing by Lawton and Nahemow (1973) [ 24 ] and person-environment fitness theory [ 25 ]. Extant research has shown that walkable communities with accessible public spaces increase social interaction by 30–40% among older residents [ 26 ][ 27 ]. Community-based approaches, such as co-housing models and intergenerational shared spaces, have shown evidence in fostering meaningful connections [ 28 , 29 ]. Recent implementations of the WHO's age-friendly cities framework reveal that age-friendly environment- including accessible transportation and community centers - correlates with higher life satisfaction [ 30 ]. Accordingly, we put forward the third hypothesis. H3: age-friendly environment is negatively correlated with later-life loneliness. Social gerontological research identifies social participation as a critical determinant of active and healthy aging, encompassing meaningful engagement beyond superficial social interactions [ 31 ]. The World Health Organization (2020) explicitly incorporates social participation as a core component of its Global Strategy on Aging and Health, recognizing its potential for later-life wellbeing [ 32 ]. Prior research has shown that participation in social activities yield promising mental health benefits and seems to be linked with reduced loneliness [ 34 ]. Accordingly, we put forward the fourth hypothesis. H4: higher levels of social participation is negatively associated with loneliness. Prior research has demonstrated that individual psychological dispositions significantly influence older adults’ mental health outcomes. For example, self-perceived positive attitudes toward aging have been associated with higher subjective well-being[ 35 ]. Expanding on this, environmental gerontology emphasizes the critical role of person-environment fit in promoting well-being in later life [ 25 ]. Within this framework, housing satisfaction—a key dimension of environmental fit—has been shown to buffer against loneliness by providing security, autonomy, and opportunities for social contacts [ 36 ]. Accordingly, we put forward the fifth hypothesis. H5: housing satisfaction is a predictor for loneliness. Cultural context plays a critical role in shaping loneliness experiences among older Taiwanese adults. In Taiwan, grandparenting is not merely a familial obligation but a deeply ingrained practice rooted in Confucian filial norms [ 37 ], which emphasizes intergenerational reciprocity, family interdependence, and respect for the older people [ 38 ]. While many older adults derive purpose and identity from caring for grandchildren [ 39 ], this role can paradoxically heighten loneliness by restricting opportunities for participation in activities outside the home [ 37 ]. Research suggests that loneliness and social isolation can possibly be reduced by fostering social connections outside the family [ 40 ]. It is for this reason, we put forward the following sixth hypothesis. H6: Grandparenting is a risk factor to loneliness among older Taiwanese adults. 3. Methods 3.1Participants We used secondary data analysis from the first wave survey of a university social responsibility (USR) project which aimed at doing research that can create social impact and benefiting local communities. This project, conducted from October 2020 to February 2021, involved two rural and two urban counties in a southern municipality in Taiwan. The study is conducted in full compliance with the Helsinki Declaration. Ethical approved was granted by the University Human Research Ethics Committee (protocol number A-ER-109-361) and no conflicts of interests were declared. Convenient sampling was used to recruit a sample of older community-dwelling adults aged 50 years and above (N = 1232). Project staff members are the interviewers who are responsible for conducting face-to-face interviews with the participants. All staff members have received research interviews training prior from the principal investigators to conducting the formal field work. The interviewers assisted each participant in completing the survey and offered clarifications for any questions that were unclear. All participants provide their informed consent in this research. Due to the ongoing pandemic, all participants were required to wear face masks during the interviews. The exclusion criteria included: (a) individuals with severe cognitive impairments, (b) individuals who were bedridden, (c) individuals who refused to disclose their demographic information, and (d) individuals who did not provide informed consent. In the end, 802 community dwelling older adults participated in this research project and we extracted a sub-sample (N = 530) aged 65 and above for this research purpose. 3.2Mathematical statistics analysis Measurements Dependent Variable Loneliness was measured by the validated Chinese version of the shortened six-item De Jong Gierveld loneliness scale (Leung et al., 2008). Participants were asked to indicate to which degree they agree to six statements and they were given three possible answers (yes, more or less, no). The six statements are, (1) I experience a general sense of emptiness, (2) I miss having people around, (3) I often feel rejected, (4) they are plenty of people I can rely on when I have problems, (5) there are many people I can trust completely, (6) there are enough people I feel close to. The overall De Jong Gierveld scale was reliable (crobach’s alpha 0.78). Independent Variables The community-level predictors to loneliness included four factors: social capital, social support from friends, social support from family, and age-friendly living environment. The individual level factors are the following: grandparenting, satisfaction with housing conditions and social participation. Covariates include age, gender, health, maritial status, income, education and ethnicity. Social capital was measured by gauging the existing mutual help in the community. Respondents were asked if they think people in this community are willing to help their neighbours (responses ranging from one [no, absolutely non-existent] to five [yes, it happens frequently]). Respondents who reported yes or it happens frequently were coded 1, the others were coded 0. Social support from family/friends were measured by asking people, in recent six months, how often they receive support from their family/non-family. There are ten different kinds of support in the survey, ranging from listening to my worries, to providing needed material assistance.There are three possible responses: seldom (1), occasionally (2), frequently (3). Social support was measured by the number of times respondents reported occasionally or frequently to a certain kind of support. Age-friendly environment was measured by asking respondents if they live in an apartment without elevator, or if there exists steps or other barriers to their toilet/bathroom. Respondents who reported yes to at least one of the two questions were coded 1, the others were coded 0. Housing satisfaction was measured by asking respondents if they like their current housing (1 = yes, very much; 2 = yes. 3 = more or less; 4 = no; 5 = no, not at all). Respondents who answered 1 or 2 were coded 1, others were 0. Grandparenting was measured by asking respondents if they helped take care of their grandchildren, (0 = no, 1 = occasionally [once per week or less], 3 = frequent (everyday or several days per week). Respondents who answered occasionally or frequent were coded as 1, others were 0. Social participation was measured by asking respondents their frequency in going out to participate in an activity (including visiting neighbors, grocery shopping, activity participation etc). possible answers were 1 = four times or more per week, 2 = twice or three times per week, 3 = once per week, 4 = once or three times per month, 5 = several times per year, 6 = rarely going out. Those who answered at least once per week were coded 1, others were 0. 4. Results Table 1 presents the descritpive statistics of the dependent variable (loneliness measured by De Jong Gierveld scale) and the key predictors to loneliness. During the pandemic, the overall loneliness score among older Taiwanese adults were 3.09 (SD = 1.61). This means that respondents answered on average about 3 times yes to the six statements of the De Jong Gierveld loneliness. 59.2% participants reported moderate loneliness while 19.6% severe loneliness. For the community-level predictors, 70% respondents reported that there were (frequent) mutual help in their community. Social support from family was 8.06 (SD = 2.98) while social support from friends 5.15 (SD = 3.92). 32% respondents reported that they experience no barrier in their housing. For individual-level predictors, 86% respondents reported satisfaction with their living environment. 25% respondents engaged in grandparenting and 66.8% have social participation activities (including visiting neighbours, grocery shopping, activity participation etc) at least four times per week. Table 1 Descriptive statistics of both dependent variable and independent variables (N = 530) %/M SD Dependent variable Overall Loneliness 3.09 1.61 Not lonely 21.1 Moderate loneliness 59.2 Severe loneliness 19.6 Community-level predictors Community social capital 70 Social support from family 8.06 2.98 Social support from non-family 5.15 3.92 Age-friendly living environment 0.32 Individual-level predictors Housing satisfaction 0.86 Grandparenting 0.25 0.43 Social pariticipation 66.8 Co-variates Age 75.73 8.35 Gender (Female) 62.12 Self-perceived health (not good or very bad) 0.51 Marital status (married) 0.58 Income (low income) 11 0.31 Education 0.28 0.45 Ethnicity (with a migration background) 11 Length of living in the community 27.00 11.83 Linear regression analysis Table 2 Linear Regression of Overall Loneliness among older Taiwanese adults (N = 530) B SE Community-level predictors Community social capital -0.355*** 0.151 Social support from family -0.019 0.023 Social support from non-family -0.002 0.018 Age-friendly living environment 0.009 0.161 Individual-level predictors Housing satisfaction -0.680*** 0.205 Grandparenting -0.121 0.155 Social pariticipation -0.287 0.189 Co-variates Age − .0012 0.009 Gender -0.201 0.146 Health -0.463** 0.122 Marital status 0.328** 0.152 Income (low-income status) 0.514** 0.027 Education 0.096 0.161 Ethnicity -0.027 0.186 Length of living in the community 0.003 0.006 * p < 0.1; ** p < 0.05; *** p < 0.01; adjusted R square = 12.2% Table 2 presents the findings of the linear regression analysis examining the association between social capital, housing satisfaction, and loneliness among older adults. The model accounted for 12.2% of the variance (adjusted R² = 0.122) in loneliness, indicating a modest but statistically significant explanatory power. Multicollinearity diagnostics confirmed the absence of significant collinearity among predictors, as all variance inflation factor (VIF) values were below 2.0, well within the acceptable threshold (VIF < 5). Consistent with Hypothesis 1, social capital demonstrated a significant negative association with loneliness (β = -0.355, p < 0.01, 95% CI [-0.651, -0.058]). The standardized coefficient indicates that for each standard deviation increase in social capital, loneliness scores decrease by 0.355 standard deviations, after controlling for other variables in the model. The narrow confidence interval that does not cross zero suggests the significance of this association. Housing satisfaction emerged as an even stronger individual-level predictor (β = -0.702, p < 0.01, 95% CI [-1.218, -0.186]), with the magnitude of effect approximately twice that of social capital. The negative coefficient suggests a dose-response relationship, where each unit increase in housing satisfaction corresponds to a 0.702-unit decrease in loneliness scores. While the wider confidence interval indicates greater variability in this effect, the entirely negative range confirms robust significance. The regression analysis identified three significant covariates of loneliness (model R ² = 0.122, F = 5.87, p < 0.01). First, self-rated health showed a robust negative association with loneliness (β = -0.463, p < 0.05, 95% CI [-0.702, -0.224]), indicating that each unit increase in health perception was associated with a 0.46-unit decrease in loneliness scores, holding other variables constant. The effect size (Cohen’s f ² = 0.14) suggests a moderate practical significance. Secondly, marital status demonstrated a positive relationship (β = 0.328, p < 0.05, 95% CI [0.030, 0.628]), with married participants scoring 0.33 units higher on loneliness than non-married counterparts. The narrow confidence interval crossing zero marginally (lower bound = 0.030) warrants caution in interpretation, though the effect direction remained consistent across sensitivity analyses.Thirdly, low-income status (under Taiwan’s Social Assistance Act) showed the strongest association (β = 0.514, p < 0.05, 95% CI [0.068, 0.960]), with low-income individuals reporting 0.51-unit higher loneliness scores. The wider CI suggests greater variability in this effect, potentially reflecting heterogeneous socioeconomic experiences. 5. Discussion The objective of this study was to explore the loneliness (including their emotional and social loneliness) prevelance of the Taiwanese older adults during the early stages of the coronavirus pandemic and to explore the possible risk factors both at the community level and individual level to their lonliness. To answer these research questions, survey data of 530 older Taiwanese were analyzed. In this secion, we briefly disuss the findings of the research. We also present suty limitations, directions for future research and some practical implications for Taiwanese policy makers to formulate effective measures to combat loneliness. For the first research question of understanding the loneliness incidence during the pandemic, our results indicated that 59.2% suffer from moderate loneliness while 19.6% severe loneliness. This finding is significant as almost 6 in 10 older people experience moderate loneliness. This prevalence represents a marked increase compared to pre-pandemic levels. Prior longitudinal data from Taiwan's aging surveys reported loneliness rates of approximately 23.6% in this population [ 10 ]. The dramatic rise observed in our study likely reflects the psychosocial consequences of COVID-19 containment measures, including social distancing protocols and reduced community engagement opportunities. The discrepancy between pre-pandemic estimates and our findings may be partially attributable to methodological differences in loneliness assessment. Earlier surveys often employed single-item measures by asking respondents if they are lonely. A recent systematic review on loneliness [ 41 ] has shown that employing sing-item question yield significantly lower prevalence estimates compared to multi-item scales like the De Jong Gierveld Loneliness Scale. Our use of a validated multi-dimensional instrument is more likely to capture a more comprehensive representation of loneliness experiences. The second research question explored the community-level and individual level predictors to loneliness. After testing the six hypotheses, findings reveal that the significant role of community social capital in reducing loneliness among older Taiwanese adults. The finding highlighted the protective role of social capital, defined as existing resources in the community that facilitates mutual help, in reducing loneliness among older adults. This finding aligns with theoretical frameworks positing that structural (e.g., neighborhood cohesion) and cognitive (e.g., trust in community members) dimensions of social capital buffer against loneliness by fostering meaningful social integration [ 42 ]. Notably, the protective association persisted even after adjusting for individual-level covariates (e.g., health status, income), suggesting that community interventions targeting social infrastructure may mitigate loneliness irrespective of personal circumstances. The second hypothesis of social support from friends/family as a possible predictor could not be confirmed. A possible explanation is that the study was conducted during the early stage of the pandemic. Due to the lockdown measures to contain the virus, older adults might have lower expectations of social support from friends/family. This social support could be possibly supplemented by the mutual support in the community [ 43 ]. Our findings reveal a paradoxical situation in Taiwan during the COVID-19 pandemic: despite maintaining frequent contact with family and friends, many older adults continued to experience significant loneliness. This aligns with emerging research showing that pandemic-related restrictions fundamentally altered the quality of social relationship, manifested as fewer meaningful interactions and increased tensions [ 44 ]. While daily communication with family members is maintained (mainly through digital ways), these interactions often lacked emotional depth and were dominated by practical concerns about health risks and caregiving logistics [ 45 ]. Contrary to our initial hypothesis, the analysis did not support age-friendly environments as a predictor for loneliness among older adults during the pandemic period. This finding may be attributed to two methodological and contextual considerations. First, our operationalization of age-friendliness was limited to two structural indicators: elevator availability in apartment buildings and toilet accessibility barriers. This restricted measurement approach fails to capture the multidimensional nature of age-friendly environments as conceptualized in the literature [ 46 ], which should ideally incorporate additional domains such as neighborhood walkability, transportation accessibility, and availability of community services. Second, the unique context of pandemic-related mobility restrictions likely attenuated the importance of physical environmental factors. During lockdown periods, older adults' reduced outdoor activities [ 23 ] may have diminished the impact of neighborhood age-friendliness on their lived experience of loneliness. This temporal effect aligns with emerging evidence suggesting that pandemic containment measures fundamentally altered the environmental determinants of wellbeing in aging populations [ 23 , 47 ]. The findings underscore the need for more comprehensive measures of age-friendliness in future studies, as well as greater attention to how exceptional circumstances like pandemics may temporarily modify established risk factor relationships. Our analysis of individual-level risk factors revealed one significant predictors of loneliness among older adults during the pandemic period. First, reduced social participation was not a significant risk factor. The finding is consistent with prior literature demonstrating that reduced social participation may not lead to higher loneliness level [ 23 ] as older adults might lower their expectation of social participation during a pandemic. Second, we identified lower housing as a predictor of loneliness during the pandemic. This relationship may be particularly salient in the context of lockdown measures that forced older adults to spend extended periods in their homes. When mobility is constrained, the quality of one's immediate living environment likely assumes greater importance for psychological well-being [ 48 ]. Contrary to expectations, grandparenting responsibilities did not significantly predict loneliness in our sample. This finding contrasts with previous research suggesting that caregiving roles might limit older adults' opportunities for broader social participation [ 37 ]. The discrepancy may reflect unique pandemic conditions where traditional social activities were already severely restricted for all older adults, regardless of grandparenting status. Alternatively, the emotional rewards of intergenerational contact during this isolating period may have offset negative effects stemming from reduced social participation [ 49 ]. Although the study provides useful insights, it is not without limitations worth addressing in future research. First, standardized and multi-dimensional assessment of age-friendly environment should be incorporated into future research conducted in Taiwan. Second, future research should explore how specific dimensions of social capital (e.g., bridging vs. bonding ties) differentially influence loneliness across cultural contexts. Third, since our study is limited to the coronavirus pandemic times, it is worthwhile to conduct longitudinal tracking of how these associations could evolve post-pandemic. We put forward two practical policy suggestion to effectively address loneliness. First, policy makers can focus on community social capital development that strength community cohesion and increase social participation opportunities. Second, fostering older adults’ positive perception of their living environment can be beneficial for effective intervention. Declarations Funding Declaration: no funding Clinical trial number: not applicable Human Ethics and Consent to Participate declarations: not applicable Consent to Publish declaration: not applicable Author Contribution Honghui Pan authored the manuscript, and Lifan Liu played a significant role in shaping the research idea and enhancing the manuscript through constructive feedback. Data Availability The data that support the findings of this study are available from National Cheng Kung University but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of National Cheng Kung University. References National Development Council. (2022). Population Projections for Taiwan: 2022–2070. Executive Yuan, Taiwan. Chen YJ, Matsuoka RH, Wang HC. 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Geneva: World Health Organization; 2020. Rashedi, V., Gharib, M., & Yazdani, A. A. (2014). Social participation and mental health among older adults in Iran. Iranian rehabilitation journal, 12(1), 9-13. Goll JC, Charlesworth G, Scior K, Stott J (2015) Barriers to social participation among lonely older adults: the influence of social fears and identity. PLoS ONE 10(2):e0116664 Chen, J.-J., Liu, L.-F., & Shea, J. L. (2023). The impact of positive self-perceptions of aging on subjective well-being through the mediation of psychological resilience among community-dwelling older adults during COVID-19 in Taiwan. Health and Social Care in the Community, 31(4), e123-e134. https://doi.org/10.1111/hsc.13825 Prieto-Flores ME, Fernandez-Mayoralas G, Forjaz MJ, Rojo-Perez F, Martinez-Martin P. Residential satisfaction, sense of belonging and loneliness among older adults living in the community and in care facilities. Health & Place. 2011 Nov;17(6):1183–90. Pan H, Fokkema T, Wang R, Dury S, De Donder L. ‘It’s like a double-edged sword’: understanding Confucianism’s role in activity participation among first-generation older Chinese migrants in the Netherlands and Belgium. J Cross Cult Gerontol. 2021 Sep;36(3):229–52. Lin J, Yi C. Filial norms and intergenerational support to aging parents in China and Taiwan. Int J Soc Welfare [Internet]. 2011 Oct [cited 2025 Apr 6];20(s1). Available from: https://onlinelibrary.wiley.com/doi/10.1111/j.1468-2397.2011.00824.x Xu L, Tang F, Li LW, Dong XQ. Grandparent Caregiving and Psychological Well-Being Among Chinese American Older Adults-The Roles of Caregiving Burden and Pressure. J Gerontol A Biol Sci Med Sci. 2017 Jul 1;72(suppl_1):S56-S62. doi: 10.1093/gerona/glw186. PMID: 28575256. Chen YRR, Schulz PJ. The Effect of Information Communication Technology Interventions on Reducing Social Isolation in the Elderly: A Systematic Review. J Med Internet Res. 2016 Jan 28;18(1):e18. Stegen H, Duppen D, Savieri P, Stas L, Pan H, Aartsen M, et al. Loneliness prevalence of community-dwelling older adults and the impact of the mode of measurement, data collection, and country: A systematic review and meta-analysis. International Psychogeriatrics. 2024 Sep;36(9):747–61. Chen Y, Zhou Y, Li M, Hong Y, Chen H, Zhu S, et al. Social capital and loneliness among older adults in community dwellings and nursing homes in Zhejiang Province of China. Front Public Health. 2023 May 19;11:1150310. Dury S, Brosens D, Pan H, Principi A, Smetcoren AS, Perek-Białas J, et al. Helping Behavior of Older Adults during the Early COVID-19 Lockdown in Belgium. Res Aging. 2023 Jan;45(1):8–20. Luchetti M, Lee JH, Aschwanden D, Sesker A, Strickhouser JE, Terracciano A, Sutin AR. The trajectory of loneliness in response to COVID-19. Am Psychol. 2020 Oct;75(7):897-908. doi: 10.1037/amp0000690. Epub 2020 Jun 22. PMID: 32567879; PMCID: PMC7890217. Wu, B. (2021)."Social isolation and loneliness among older adults in the context of COVID-19: A global challenge." Global Health Research and Policy, 6(1), 1-11. Lehning AJ, Smith RJ, Dunkle RE. Age-Friendly Environments and Self-Rated Health: An Exploration of Detroit Elders. Res Aging. 2014 Jan;36(1):72–94. Buffel, T., Yarker, S., Phillipson, C., Lang, L., Lewis, C., Doran, P., & Goff, M. (2021). Locked down by inequality: Older people and the COVID-19 pandemic. Urban Studies, 60(8), 1465-1482. Kleeman A, Foster S. ‘It feels smaller now’: The impact of the COVID-19 lockdown on apartment residents and their living environment – A longitudinal study. Journal of Environmental Psychology. 2023 Aug;89:102056. Gilligan M, Suitor JJ, Rurka M, Silverstein M. Multigenerational social support in the face of the COVID ‐19 pandemic. J of Family Theo & Revie. 2020 Dec;12(4):431–47. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6401946","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":462890811,"identity":"ed042cd2-afc9-495f-82ab-c1004b3a7034","order_by":0,"name":"Honghui Pan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYJACZhBhwMDY+ICB4QCQQYKWZgNStTCwSRClxZz97AHmgoo7dtslktuqedvuAEUa8Gux7MlLYJ5x5lnyzhmJbbd5254BRQ7g12JwIMeAmbftcLLBjcS2mzPbDjMY3EggoOX8G4SWQrCW+w8IaLkBscUOpIXhI9gW/DoYLGe8MTjMc+ZwgsGZh80SH84947HsIeAwc/4cw8c8FYftDY6nP/yQUHZHzpz9AAGHMYDigoEhsQEqwEPAWQzwiLMnqHIUjIJRMApGLgAAuSBKfSiaq+AAAAAASUVORK5CYII=","orcid":"","institution":"Vrije Universiteit Brussel","correspondingAuthor":true,"prefix":"","firstName":"Honghui","middleName":"","lastName":"Pan","suffix":""},{"id":462890812,"identity":"f5201edf-14ef-4ced-b686-2d2d7ad85dd8","order_by":1,"name":"LiFan Liu","email":"","orcid":"","institution":"National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"LiFan","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-04-08 09:53:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6401946/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6401946/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83605345,"identity":"f4850574-1549-4c9c-8b31-f29ed22313be","added_by":"auto","created_at":"2025-05-29 10:35:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":772975,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6401946/v1/0aefbd82-6c82-4d1b-86d1-a8964e0add4d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Loneliness among community-dwelling older adults during the early stage of the Covid-19 pandemic in Taiwan: exploring community-level and individual-level predictors","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eTaiwan is experiencing rapid population aging, with adults aged 65 and above projected to exceed 20% of the population by 2025 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. While Taiwan's collectivist culture traditionally emphasizes filial piety and family support for older adults, urbanization, shrinking household sizes, and shifting caregiving norms have weakened these traditional safeguards [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These demographic and social changes may heighten vulnerability to loneliness\u0026mdash; a subjective feeling of distress resulting from a discrepancy between desired and actual social relationships [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Loneliness in later life is linked to poorer mental and physical health [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], prompting policy attention in Western societies. However, its predictors or risk factors in non-Western contexts like Taiwan remain understudied.\u003c/p\u003e \u003cp\u003eThe COVID-19 pandemic exacerbated these concerns. While Taiwan's early containment measures (e.g., mask mandate, contact tracing, quarantines) reduced infections [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], older adults\u0026mdash;already at higher risk of severe outcomes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u0026mdash;faced intensified isolation due to restricted family visits and social activities [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. For those living alone, disrupted family interactions deepened loneliness and mental health risks [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This unique context underscores the need to examine loneliness during the pandemic's early stage filled with uncertainties.\u003c/p\u003e \u003cp\u003eThere is a long-standing research tradition of studying risk factors to loneliness from perspective of individual factors. These include gender [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], ethnicity [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], socio-economic status [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], or individual life events such as retirement [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], widowerhood [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], fear of falling [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. We argue that this predominant focus has often overlooked the role of community level factors such as community social environment (e.g. the presence of community stores), social capital (e.g. high level of mutual help or social interaction in the community). In this sense, this article helps to fill in the research gap in addressing the role of community level risk factors to loneliness in a less-studied context. Understanding these dynamics is critical for developing culturally appropriate interventions to mitigate loneliness and improve well-being in Taiwan\u0026rsquo;s rapidly ageing society.\u003c/p\u003e \u003cp\u003eIn light of the above discussions, the purpose of this article is to\u003c/p\u003e\n\u003cp\u003e1) understand the incidence of loneliness during the early stage of covid-19 pandemic in Taiwan\u003c/p\u003e\n\u003cp\u003e2) explore the risk factors (both at the community level and individual level) to loneliness\u003c/p\u003e\n\u003cp\u003eIn the next section, we put forward six hypotheses to explore the risk factors to loneliness among older Taiwanese adults.\u003c/p\u003e"},{"header":"2. Theoretical framework and hypothesis","content":"\u003cp\u003eSocial capital, as manifested through mutual help, refers to the collective value of trust, reciprocity and cooperative networks that merge when community members actively support one another within the community [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Everyday small acts of mutual help such as neighbors sharing resources, offering emotional support or collaborating on local projects, can boost older adults\u0026rsquo; social network and decrease loneliness [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Ultimately, social capital fosters meaningful social contact, which in turn helps reduce loneliness among older adults by strengthening their sense of being connection [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Accordingly, we put forward the first hypothesis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH1: Higher social capital in the community is associated with lower loneliness.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSocial support plays a role in reducing loneliness among older adults by providing emotional comfort, practical assistance, and opportunities for meaningful social engagement [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Research demonstrates that social support, facilitated by structured social interventions, such as community programs and peer support groups, can significantly reduce loneliness among older adults by fostering regular social interaction [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Emotional support from family, friends, and caregivers helps older adults feel valued and connected, while instrumental support, such as assistance with daily activities, reinforces communal interdependence and trust (Hagan et al., 2022) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Research has also shown that technology-mediated support, including virtual social networks and telecommunication tools, has also proven effective in combating loneliness among older adults, particularly during public health crisis like the coronavirus pandemic pandemic when in-person interactions are reduced [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Accordingly, we put forward the second hypothesis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH2: Lower social support from friends/family acts as risk factor to loneliness.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAn age-friendly environment, adapted to the (changing) needs of older adults\u0026rsquo; physical and social situation, can effectively reduce loneliness among older adults. This aligns with the environmental gerontology theories, such as the ecological model of ageing by Lawton and Nahemow (1973) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and person-environment fitness theory [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Extant research has shown that walkable communities with accessible public spaces increase social interaction by 30\u0026ndash;40% among older residents [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e][\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Community-based approaches, such as co-housing models and intergenerational shared spaces, have shown evidence in fostering meaningful connections [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Recent implementations of the WHO's age-friendly cities framework reveal that age-friendly environment- including accessible transportation and community centers - correlates with higher life satisfaction [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Accordingly, we put forward the third hypothesis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH3: age-friendly environment is negatively correlated with later-life loneliness.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSocial gerontological research identifies social participation as a critical determinant of active and healthy aging, encompassing meaningful engagement beyond superficial social interactions [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The World Health Organization (2020) explicitly incorporates social participation as a core component of its Global Strategy on Aging and Health, recognizing its potential for later-life wellbeing [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Prior research has shown that participation in social activities yield promising mental health benefits and seems to be linked with reduced loneliness\u003c/p\u003e \u003cp\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Accordingly, we put forward the fourth hypothesis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH4: higher levels of social participation is negatively associated with loneliness.\u003c/b\u003e \u003c/p\u003e \u003cp\u003ePrior research has demonstrated that individual psychological dispositions significantly influence older adults\u0026rsquo; mental health outcomes. For example, self-perceived positive attitudes toward aging have been associated with higher subjective well-being[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Expanding on this, environmental gerontology emphasizes the critical role of person-environment fit in promoting well-being in later life [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Within this framework, housing satisfaction\u0026mdash;a key dimension of environmental fit\u0026mdash;has been shown to buffer against loneliness by providing security, autonomy, and opportunities for social contacts [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Accordingly, we put forward the fifth hypothesis. \u003cb\u003eH5: housing satisfaction is a predictor for loneliness.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCultural context plays a critical role in shaping loneliness experiences among older Taiwanese adults. In Taiwan, grandparenting is not merely a familial obligation but a deeply ingrained practice rooted in Confucian \u003cem\u003efilial norms\u003c/em\u003e [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], which emphasizes intergenerational reciprocity, family interdependence, and respect for the older people [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. While many older adults derive purpose and identity from caring for grandchildren [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], this role can paradoxically heighten loneliness by restricting opportunities for participation in activities outside the home [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Research suggests that loneliness and social isolation can possibly be reduced by fostering social connections outside the family [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. It is for this reason, we put forward the following sixth hypothesis. \u003cb\u003eH6: Grandparenting is a risk factor to loneliness among older Taiwanese adults.\u003c/b\u003e\u003c/p\u003e"},{"header":"3. Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1Participants\u003c/h2\u003e \u003cp\u003e We used secondary data analysis from the first wave survey of a university social responsibility (USR) project which aimed at doing research that can create social impact and benefiting local communities.\u003c/p\u003e \u003cp\u003eThis project, conducted from October 2020 to February 2021, involved two rural and two urban counties in a southern municipality in Taiwan. The study is conducted in full compliance with the Helsinki Declaration. Ethical approved was granted by the University Human Research Ethics Committee (protocol number A-ER-109-361) and no conflicts of interests were declared.\u003c/p\u003e \u003cp\u003eConvenient sampling was used to recruit a sample of older community-dwelling adults aged 50 years and above (N\u0026thinsp;=\u0026thinsp;1232). Project staff members are the interviewers who are responsible for conducting face-to-face interviews with the participants. All staff members have received research interviews training prior from the principal investigators to conducting the formal field work. The interviewers assisted each participant in completing the survey and offered clarifications for any questions that were unclear. All participants provide their informed consent in this research.\u003c/p\u003e \u003cp\u003eDue to the ongoing pandemic, all participants were required to wear face masks during the interviews. The exclusion criteria included: (a) individuals with severe cognitive impairments, (b) individuals who were bedridden, (c) individuals who refused to disclose their demographic information, and (d) individuals who did not provide informed consent. In the end, 802 community dwelling older adults participated in this research project and we extracted a sub-sample (N\u0026thinsp;=\u0026thinsp;530) aged 65 and above for this research purpose.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2Mathematical statistics analysis\u003c/h2\u003e \u003cp\u003e \u003cb\u003eMeasurements\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eDependent Variable\u003c/b\u003e \u003c/p\u003e \u003cp\u003eLoneliness was measured by the validated Chinese version of the shortened six-item De Jong Gierveld loneliness scale (Leung et al., 2008). Participants were asked to indicate to which degree they agree to six statements and they were given three possible answers (yes, more or less, no). The six statements are, (1) I experience a general sense of emptiness, (2) I miss having people around, (3) I often feel rejected, (4) they are plenty of people I can rely on when I have problems, (5) there are many people I can trust completely, (6) there are enough people I feel close to. The overall De Jong Gierveld scale was reliable (crobach\u0026rsquo;s alpha 0.78).\u003c/p\u003e \u003cp\u003e \u003cb\u003eIndependent Variables\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe community-level predictors to loneliness included four factors: social capital, social support from friends, social support from family, and age-friendly living environment. The individual level factors are the following: grandparenting, satisfaction with housing conditions and social participation. Covariates include age, gender, health, maritial status, income, education and ethnicity.\u003c/p\u003e \u003cp\u003eSocial capital was measured by gauging the existing mutual help in the community. Respondents were asked if they think people in this community are willing to help their neighbours (responses ranging from one [no, absolutely non-existent] to five [yes, it happens frequently]). Respondents who reported yes or it happens frequently were coded 1, the others were coded 0.\u003c/p\u003e \u003cp\u003eSocial support from family/friends were measured by asking people, in recent six months, how often they receive support from their family/non-family. There are ten different kinds of support in the survey, ranging from listening to my worries, to providing needed material assistance.There are three possible responses: seldom (1), occasionally (2), frequently (3). Social support was measured by the number of times respondents reported occasionally or frequently to a certain kind of support.\u003c/p\u003e \u003cp\u003eAge-friendly environment was measured by asking respondents if they live in an apartment without elevator, or if there exists steps or other barriers to their toilet/bathroom. Respondents who reported yes to at least one of the two questions were coded 1, the others were coded 0.\u003c/p\u003e \u003cp\u003eHousing satisfaction was measured by asking respondents if they like their current housing (1\u0026thinsp;=\u0026thinsp;yes, very much; 2\u0026thinsp;=\u0026thinsp;yes. 3\u0026thinsp;=\u0026thinsp;more or less; 4\u0026thinsp;=\u0026thinsp;no; 5\u0026thinsp;=\u0026thinsp;no, not at all). Respondents who answered 1 or 2 were coded 1, others were 0. Grandparenting was measured by asking respondents if they helped take care of their grandchildren, (0\u0026thinsp;=\u0026thinsp;no, 1\u0026thinsp;=\u0026thinsp;occasionally [once per week or less], 3\u0026thinsp;=\u0026thinsp;frequent (everyday or several days per week). Respondents who answered occasionally or frequent were coded as 1, others were 0. Social participation was measured by asking respondents their frequency in going out to participate in an activity (including visiting neighbors, grocery shopping, activity participation etc). possible answers were 1\u0026thinsp;=\u0026thinsp;four times or more per week, 2\u0026thinsp;=\u0026thinsp;twice or three times per week, 3\u0026thinsp;=\u0026thinsp;once per week, 4\u0026thinsp;=\u0026thinsp;once or three times per month, 5\u0026thinsp;=\u0026thinsp;several times per year, 6\u0026thinsp;=\u0026thinsp;rarely going out. Those who answered at least once per week were coded 1, others were 0.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the descritpive statistics of the dependent variable (loneliness measured by De Jong Gierveld scale) and the key predictors to loneliness. During the pandemic, the overall loneliness score among older Taiwanese adults were 3.09 (SD\u0026thinsp;=\u0026thinsp;1.61). This means that respondents answered on average about 3 times yes to the six statements of the De Jong Gierveld loneliness. 59.2% participants reported moderate loneliness while 19.6% severe loneliness. For the community-level predictors, 70% respondents reported that there were (frequent) mutual help in their community. Social support from family was 8.06 (SD\u0026thinsp;=\u0026thinsp;2.98) while social support from friends 5.15 (SD\u0026thinsp;=\u0026thinsp;3.92). 32% respondents reported that they experience no barrier in their housing. For individual-level predictors, 86% respondents reported satisfaction with their living environment. 25% respondents engaged in grandparenting and 66.8% have social participation activities (including visiting neighbours, grocery shopping, activity participation etc) at least four times per week.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of both dependent variable and independent variables (N\u0026thinsp;=\u0026thinsp;530)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%/M\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDependent variable\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall Loneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot lonely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate loneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere loneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCommunity-level predictors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity social capital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial support from family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial support from non-family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge-friendly living environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndividual-level predictors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousing satisfaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrandparenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial pariticipation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCo-variates\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-perceived health (not good or very bad)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status (married)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome (low income)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity (with a migration background)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of living in the community\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eLinear regression analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLinear Regression of Overall Loneliness among older Taiwanese adults (N\u0026thinsp;=\u0026thinsp;530)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCommunity-level predictors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity social capital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.355***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial support from family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial support from non-family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge-friendly living environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndividual-level predictors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousing satisfaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.680***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrandparenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial pariticipation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.189\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-variates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.0012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.463**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.328**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome (low-income status)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.514**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of living in the community\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e* \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1; **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; adjusted R square\u0026thinsp;=\u0026thinsp;12.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the findings of the linear regression analysis examining the association between social capital, housing satisfaction, and loneliness among older adults. The model accounted for 12.2% of the variance (adjusted R\u0026sup2; = 0.122) in loneliness, indicating a modest but statistically significant explanatory power. Multicollinearity diagnostics confirmed the absence of significant collinearity among predictors, as all variance inflation factor (VIF) values were below 2.0, well within the acceptable threshold (VIF\u0026thinsp;\u0026lt;\u0026thinsp;5).\u003c/p\u003e \u003cp\u003eConsistent with Hypothesis 1, social capital demonstrated a significant negative association with loneliness (β = -0.355, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, 95% CI [-0.651, -0.058]). The standardized coefficient indicates that for each standard deviation increase in social capital, loneliness scores decrease by 0.355 standard deviations, after controlling for other variables in the model. The narrow confidence interval that does not cross zero suggests the significance of this association.\u003c/p\u003e \u003cp\u003eHousing satisfaction emerged as an even stronger individual-level predictor (β = -0.702, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, 95% CI [-1.218, -0.186]), with the magnitude of effect approximately twice that of social capital. The negative coefficient suggests a dose-response relationship, where each unit increase in housing satisfaction corresponds to a 0.702-unit decrease in loneliness scores. While the wider confidence interval indicates greater variability in this effect, the entirely negative range confirms robust significance.\u003c/p\u003e \u003cp\u003eThe regression analysis identified three significant covariates of loneliness (model \u003cem\u003eR\u003c/em\u003e\u0026sup2; = 0.122, \u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.87, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). First, self-rated health showed a robust negative association with loneliness (β = -0.463, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, 95% CI [-0.702, -0.224]), indicating that each unit increase in health perception was associated with a 0.46-unit decrease in loneliness scores, holding other variables constant. The effect size (Cohen\u0026rsquo;s \u003cem\u003ef\u003c/em\u003e\u0026sup2; = 0.14) suggests a moderate practical significance. Secondly, marital status demonstrated a positive relationship (β\u0026thinsp;=\u0026thinsp;0.328, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, 95% CI [0.030, 0.628]), with married participants scoring 0.33 units higher on loneliness than non-married counterparts. The narrow confidence interval crossing zero marginally (lower bound\u0026thinsp;=\u0026thinsp;0.030) warrants caution in interpretation, though the effect direction remained consistent across sensitivity analyses.Thirdly, low-income status (under Taiwan\u0026rsquo;s Social Assistance Act) showed the strongest association (β\u0026thinsp;=\u0026thinsp;0.514, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, 95% CI [0.068, 0.960]), with low-income individuals reporting 0.51-unit higher loneliness scores. The wider CI suggests greater variability in this effect, potentially reflecting heterogeneous socioeconomic experiences.\u003c/p\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe objective of this study was to explore the loneliness (including their emotional and social loneliness) prevelance of the Taiwanese older adults during the early stages of the coronavirus pandemic and to explore the possible risk factors both at the community level and individual level to their lonliness. To answer these research questions, survey data of 530 older Taiwanese were analyzed. In this secion, we briefly disuss the findings of the research. We also present suty limitations, directions for future research and some practical implications for Taiwanese policy makers to formulate effective measures to combat loneliness.\u003c/p\u003e \u003cp\u003eFor the first research question of understanding the loneliness incidence during the pandemic, our results indicated that 59.2% suffer from moderate loneliness while 19.6% severe loneliness. This finding is significant as almost 6 in 10 older people experience moderate loneliness. This prevalence represents a marked increase compared to pre-pandemic levels. Prior longitudinal data from Taiwan's aging surveys reported loneliness rates of approximately 23.6% in this population [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The dramatic rise observed in our study likely reflects the psychosocial consequences of COVID-19 containment measures, including social distancing protocols and reduced community engagement opportunities. The discrepancy between pre-pandemic estimates and our findings may be partially attributable to methodological differences in loneliness assessment. Earlier surveys often employed single-item measures by asking respondents if they are lonely. A recent systematic review on loneliness [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] has shown that employing sing-item question yield significantly lower prevalence estimates compared to multi-item scales like the De Jong Gierveld Loneliness Scale. Our use of a validated multi-dimensional instrument is more likely to capture a more comprehensive representation of loneliness experiences.\u003c/p\u003e \u003cp\u003eThe second research question explored the community-level and individual level predictors to loneliness. After testing the six hypotheses, findings reveal that the significant role of community social capital in reducing loneliness among older Taiwanese adults. The finding highlighted the protective role of social capital, defined as existing resources in the community that facilitates mutual help, in reducing loneliness among older adults. This finding aligns with theoretical frameworks positing that structural (e.g., neighborhood cohesion) and cognitive (e.g., trust in community members) dimensions of social capital buffer against loneliness by fostering meaningful social integration [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Notably, the protective association persisted even after adjusting for individual-level covariates (e.g., health status, income), suggesting that community interventions targeting social infrastructure may mitigate loneliness irrespective of personal circumstances.\u003c/p\u003e \u003cp\u003eThe second hypothesis of social support from friends/family as a possible predictor could not be confirmed. A possible explanation is that the study was conducted during the early stage of the pandemic. Due to the lockdown measures to contain the virus, older adults might have lower expectations of social support from friends/family. This social support could be possibly supplemented by the mutual support in the community [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Our findings reveal a paradoxical situation in Taiwan during the COVID-19 pandemic: despite maintaining frequent contact with family and friends, many older adults continued to experience significant loneliness. This aligns with emerging research showing that pandemic-related restrictions fundamentally altered the quality of social relationship, manifested as fewer meaningful interactions and increased tensions [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. While daily communication with family members is maintained (mainly through digital ways), these interactions often lacked emotional depth and were dominated by practical concerns about health risks and caregiving logistics [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eContrary to our initial hypothesis, the analysis did not support age-friendly environments as a predictor for loneliness among older adults during the pandemic period. This finding may be attributed to two methodological and contextual considerations. First, our operationalization of age-friendliness was limited to two structural indicators: elevator availability in apartment buildings and toilet accessibility barriers. This restricted measurement approach fails to capture the multidimensional nature of age-friendly environments as conceptualized in the literature [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], which should ideally incorporate additional domains such as neighborhood walkability, transportation accessibility, and availability of community services.\u003c/p\u003e \u003cp\u003eSecond, the unique context of pandemic-related mobility restrictions likely attenuated the importance of physical environmental factors. During lockdown periods, older adults' reduced outdoor activities [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] may have diminished the impact of neighborhood age-friendliness on their lived experience of loneliness. This temporal effect aligns with emerging evidence suggesting that pandemic containment measures fundamentally altered the environmental determinants of wellbeing in aging populations [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The findings underscore the need for more comprehensive measures of age-friendliness in future studies, as well as greater attention to how exceptional circumstances like pandemics may temporarily modify established risk factor relationships.\u003c/p\u003e \u003cp\u003eOur analysis of individual-level risk factors revealed one significant predictors of loneliness among older adults during the pandemic period. First, reduced social participation was not a significant risk factor. The finding is consistent with prior literature demonstrating that reduced social participation may not lead to higher loneliness level [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] as older adults might lower their expectation of social participation during a pandemic. Second, we identified lower housing as a predictor of loneliness during the pandemic. This relationship may be particularly salient in the context of lockdown measures that forced older adults to spend extended periods in their homes. When mobility is constrained, the quality of one's immediate living environment likely assumes greater importance for psychological well-being [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eContrary to expectations, grandparenting responsibilities did not significantly predict loneliness in our sample. This finding contrasts with previous research suggesting that caregiving roles might limit older adults' opportunities for broader social participation [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The discrepancy may reflect unique pandemic conditions where traditional social activities were already severely restricted for all older adults, regardless of grandparenting status. Alternatively, the emotional rewards of intergenerational contact during this isolating period may have offset negative effects stemming from reduced social participation [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough the study provides useful insights, it is not without limitations worth addressing in future research. First, standardized and multi-dimensional assessment of age-friendly environment should be incorporated into future research conducted in Taiwan. Second, future research should explore how specific dimensions of social capital (e.g., bridging vs. bonding ties) differentially influence loneliness across cultural contexts. Third, since our study is limited to the coronavirus pandemic times, it is worthwhile to conduct longitudinal tracking of how these associations could evolve post-pandemic.\u003c/p\u003e \u003cp\u003eWe put forward two practical policy suggestion to effectively address loneliness. First, policy makers can focus on community social capital development that strength community cohesion and increase social participation opportunities. Second, fostering older adults\u0026rsquo; positive perception of their living environment can be beneficial for effective intervention.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eFunding Declaration: no funding\u003c/p\u003e \u003cp\u003eClinical trial number: not applicable\u003c/p\u003e \u003cp\u003eHuman Ethics and Consent to Participate declarations: not applicable\u003c/p\u003e \u003cp\u003eConsent to Publish declaration: not applicable\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eHonghui Pan authored the manuscript, and Lifan Liu played a significant role in shaping the research idea and enhancing the manuscript through constructive feedback.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from National Cheng Kung University but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. 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PMID: 28575256.\u003c/li\u003e\n\u003cli\u003eChen YRR, Schulz PJ. The Effect of Information Communication Technology Interventions on Reducing Social Isolation in the Elderly: A Systematic Review. J Med Internet Res. 2016 Jan 28;18(1):e18.\u003c/li\u003e\n\u003cli\u003eStegen H, Duppen D, Savieri P, Stas L, Pan H, Aartsen M, et al. Loneliness prevalence of community-dwelling older adults and the impact of the mode of measurement, data collection, and country: A systematic review and meta-analysis. International Psychogeriatrics. 2024 Sep;36(9):747\u0026ndash;61.\u003c/li\u003e\n\u003cli\u003eChen Y, Zhou Y, Li M, Hong Y, Chen H, Zhu S, et al. Social capital and loneliness among older adults in community dwellings and nursing homes in Zhejiang Province of China. Front Public Health. 2023 May 19;11:1150310.\u003c/li\u003e\n\u003cli\u003eDury S, Brosens D, Pan H, Principi A, Smetcoren AS, Perek-Białas J, et al. Helping Behavior of Older Adults during the Early COVID-19 Lockdown in Belgium. Res Aging. 2023 Jan;45(1):8\u0026ndash;20.\u003c/li\u003e\n\u003cli\u003eLuchetti M, Lee JH, Aschwanden D, Sesker A, Strickhouser JE, Terracciano A, Sutin AR. The trajectory of loneliness in response to COVID-19. Am Psychol. 2020 Oct;75(7):897-908. doi: 10.1037/amp0000690. Epub 2020 Jun 22. PMID: 32567879; PMCID: PMC7890217.\u003c/li\u003e\n\u003cli\u003eWu, B. (2021).\u0026quot;Social isolation and loneliness among older adults in the context of COVID-19: A global challenge.\u0026quot; Global Health Research and Policy, 6(1), 1-11.\u003c/li\u003e\n\u003cli\u003eLehning AJ, Smith RJ, Dunkle RE. Age-Friendly Environments and Self-Rated Health: An Exploration of Detroit Elders. Res Aging. 2014 Jan;36(1):72\u0026ndash;94.\u003c/li\u003e\n\u003cli\u003eBuffel, T., Yarker, S., Phillipson, C., Lang, L., Lewis, C., Doran, P., \u0026amp; Goff, M. (2021). Locked down by inequality: Older people and the COVID-19 pandemic. Urban Studies, 60(8), 1465-1482. \u003c/li\u003e\n\u003cli\u003eKleeman A, Foster S. \u0026lsquo;It feels smaller now\u0026rsquo;: The impact of the COVID-19 lockdown on apartment residents and their living environment \u0026ndash; A longitudinal study. Journal of Environmental Psychology. 2023 Aug;89:102056.\u003c/li\u003e\n\u003cli\u003eGilligan M, Suitor JJ, Rurka M, Silverstein M. Multigenerational social support in the face of the COVID ‐19 pandemic. J of Family Theo \u0026amp;amp; Revie. 2020 Dec;12(4):431\u0026ndash;47.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Taiwan, loneliness, risk factors, older adults, social capital, physical living environment, social participation","lastPublishedDoi":"10.21203/rs.3.rs-6401946/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6401946/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eLoneliness has arisen in policy agenda as a major societal challenge in many western countries. However, little empirical evidence has been provided on loneliness of community-dwelling older adults in Taiwan, a fast-ageing society in east Asia. This study aimed to describe the status quo of and explore the risk factors to loneliness among Taiwanese ageing population during the covid-19 pandemic in Taiwan.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe used secondary data analysis of University Responsibility dataset from National Cheng Kung University in Tainan city, Taiwan. 530 older adults aged 65 and above were included in this study. Loneliness was measured by the 6-item De Jong Gierveld loneliness scale (2006). We used hierarchical multiple linear regression analysis to examine the community level risk factors (i.e. non-age-friendly environment, lower social capital in the community, lower levels of social support from family/friends) and individual risk factors (i.e. negative perceptions of physical living environment, lower levels of social participation). We also included demographic covariates of age, gender, marital status, ethnicity, educational level, health and income in the analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eRegarding the status quo of loneliness of our sample (N\u0026thinsp;=\u0026thinsp;530), 59.2% suffer from moderate loneliness while 19.6% severe loneliness. The predictors at the community level include : social capital in the community (β = -0.562, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, 95% CI [-0.975, -0.149]), while at the individual level: housing satisfaction (β = -0.702, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, 95% CI [-1.218, -0.186]). Three covariates (i.e. self-rated health, marital status, low-income status) are also significant predictors.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study highlights the importance of both community level factors and individual factors in delivering effective interventions to alleviate loneliness among older Taiwanese adults. We put forward two practical suggestions. First, community-based initiatives to alleviate loneliness should focus on building community social capital. Second, fostering older adults\u0026rsquo; housing satisfaction can be beneficial for effective intervention.\u003c/p\u003e","manuscriptTitle":"Loneliness among community-dwelling older adults during the early stage of the Covid-19 pandemic in Taiwan: exploring community-level and individual-level predictors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-29 10:27:14","doi":"10.21203/rs.3.rs-6401946/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-05T14:39:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-24T19:37:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"59140299203087311405363646555533797743","date":"2026-03-12T17:25:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-11T08:49:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"93833325857119182151913907568651162594","date":"2025-06-11T06:56:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-28T04:47:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-20T09:01:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-05T09:23:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-05T06:38:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2025-05-05T06:37:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0054725b-3c5b-428b-a71e-169ac570ff35","owner":[],"postedDate":"May 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-23T17:53:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-29 10:27:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6401946","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6401946","identity":"rs-6401946","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}