The impact of Community Services on Geriatric Depression: A ten-year follow-up study

The impact of Community Services on Geriatric Depression: A ten-year follow-up study | 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 The impact of Community Services on Geriatric Depression: A ten-year follow-up study Xiaowen Li, Shuhu Chen, Jun Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3839741/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Aug, 2024 Read the published version in BMC Geriatrics → Version 1 posted 12 You are reading this latest preprint version Abstract Background This study explores whether the impact of environmental factors (Community Service) on Geriatric Depression is mediated by Psychological Resilience and moderated by the COMT gene Val158Met polymorphism. Methods Data were obtained from 13,512 Chinese individuals aged 65 and above, comprising a nationally representative sample from the 2008, 2011, 2014, and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). The study employed a Random Intercept Cross-Lagged Panel Model (RI-CLPM) to examine the relationship between community service and geriatric depression, including the mediating effect of psychological resilience and the moderating role of the COMT Val158Met gene polymorphism in this relationship. Results Lower levels of community service at earlier assessments were significantly associated with more severe geriatric depression in subsequent evaluations.Psychological resilience was found to partially mediate the relationship between community service and geriatric depression.Differential impacts were observed among various gene genotypes; specifically, the Val genotype demonstrated a significantly greater influence of community service on subsequent psychological resilience and on subsequent depression compared to the Met genotype. Conclusion Enhancement in Community Service can predict subsequent Geriatric Depression. The influence of community service on depression is partly mediated by its impact on psychological resilience, with genetics modulating the pathway from community service through psychological resilience to depression. Multidisciplinary interventions focused on enhancing community service quality, boosting psychological resilience, and mitigating depression are likely to benefit the elderly's emotional and psychological well-being. Community Service Psychological Resilience Geriatric Depression Random intercept cross-lagged panel model Figures Figure 1 Figure 2 Introduction Geriatric depression encompasses depressive disorders that emerge or prevail in old age (i.e., 60 years and older), representing a widespread mental health concern among the elderly. It results in diminished physical functionality, lower quality of life, elevated suicide risk, and increased mortality rates [ 1 ][ 2 ]. Concurrently, it exerts a considerable disease burden and financial strain on families and society [ 3 ][ 4 ]. As a critical strategy for managing aging populations, community service has garnered increasing attention and seen rapid development globally [ 5 ].Community service for the elderly encompasses a range of services offered by the community, such as life care and health care [ 6 ].According to the main-effect model, support and services for the elderly directly bolster their subjective well-being and diminish depression levels [ 7 ].Specifically, community-based services provide the elderly with opportunities to engage with their communities, thus mitigating the potential adverse effects of social isolation on psychological health [ 8 ].Furthermore, Park et al.'s study showed that regular attendance at senior centers is significantly correlated with fewer depression symptoms among the elderly, highlighting these centers' role as vital community resources for social and emotional support [ 9 ].Empirical research suggests that community-based services act as a protective factor against depression among China's elderly, effectively mitigating cognitive decline and improving mental health [ 10 ]. The aging population and shifting family structures increasingly challenge families' ability to provide adequate support for the elderly.Furthermore, the prohibitive costs of institutional services make them inaccessible to many, diminishing the likelihood of opting for institutional care [ 11 ].Consequently, community-based services are of particular importance. Nevertheless, community services for the elderly in China are still limited [ 12 ]. Although much of the prior literature has focused on the psychological and social factors affecting elderly depression, research on the relationship between community-based services and geriatric depression remains relatively scarce. Early studies using cross-sectional data encounter difficulties distinguishing correlation from individual differences, potentially leading to imprecise assessments. Therefore, this study seeks to explore the longitudinal relationship between community services and geriatric depression, emphasizing the investigation of potential mechanisms to broaden our understanding of this domain. Recently, academic interest has grown in the impact of psychological resilience on elderly lives [ 13 ]. Psychological resilience is the ability to adapt to life changes and environmental stressors, considered a key protective mechanism [ 14 ].In essence, highly resilient elderly individuals adapt and cope better with life changes, leading to a higher quality of life and less depression [ 13 ]. Specifically, elderly with high psychological resilience may use their psychological strengths to overcome adversity and attain well-being [ 15 ]. Elderly with strong psychological resilience often have higher self-esteem and confidence, enabling them to foster and use interpersonal relationships, thus reducing depression levels [ 13 ]. However, most prior research on psychological resilience's impact on mental health has focused on children and adolescents, with fewer studies involving the elderly.Community-based services can enhance the elderly's sense of community, promoting psychological resilience. These services also establish social connections, boost intrinsic motivation, and improve elderly psychological resilience [ 16 ]. At the same time, community-based services play a crucial role in enriching the lives of the elderly by alleviating feelings of helplessness, reducing social isolation, and enhancing their psychological resilience. These services not only meet their immediate needs but also contribute to the development of social capabilities [ 17 ]. Despite studies on the positive effects of community service on psychological resilience and its relation to depression, in-depth analysis of psychological resilience's mediating role in the community service-depression relationship among China's elderly is lacking. Behavioral genetics research indicates that depression significantly stems from genetic factors, with heritability rates ranging from 24–55% [ 18 ]. The integration of molecular genetics techniques with traditional psychological research methods to explore the gene-environment interaction in depression susceptibility is a prominent and burgeoning research area [ 19 ]. The COMT (catechol-O-methyltransferase) gene is a significant candidate gene implicated in depression [ 20 ][ 21 ]. The COMT gene, situated on the long arm of chromosome 22 at 22q11.2, functions as a primary metabolic enzyme for catecholamines such as adrenaline, noradrenaline, and dopamine. At least eight single nucleotide polymorphisms exist in this gene's coding region, with the Val158Met polymorphism (rs4680) being the most prevalent functional variant, whereby the Val allele's COMT enzyme activity is 3 to 4 times that of the Met allele [ 22 ]. Current research has explored the interaction between the COMT gene's Val158Met polymorphism and social environment in affecting depression, yet findings are still inconclusive. The social salience hypothesis may shed light on these varying findings. It suggests that oxytocin enhances individual sensitivity and response to social environments [ 23 ]. Shamay-Tsoory and Abu-Akel further detailed the neurophysiological mechanisms of oxytocin's effect on social salience, specifically its interaction with the dopaminergic system in modulating environmental sensitivity [ 24 ]. While the COMT gene does not directly alter oxytocin levels, it can impact the oxytocinergic system by modulating oxytocin receptors' quantity, arrangement, and function, thus influencing environmental sensitivity [ 25 ]. FMRI studies indicate that the COMT gene regulates individual sensitivity to environmental stimuli by affecting the hypothalamus and amygdala's functional coupling, influencing social emotions and behaviors [ 26 ]. Drawing on the social salience hypothesis and fMRI evidence, this study hypothesizes that the COMT gene's expression may serve as a protective or risk factor, contingent upon the individual's social environment, suggesting a gene-environment interaction. Considering these factors, this study employs longitudinal data to investigate the concurrent influence of the COMT gene Val158Met polymorphism and psychological resilience on the impact of community service on geriatric depression. Specifically, it seeks to determine the extent to which psychological resilience mediates community service's effect on geriatric depression and if this mediation varies with individual genotype differences. Method Data and sample The data for this study are derived from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which represents the most comprehensive and extensive cohort dataset on the elderly population in China [ 27 ]. The survey has been conducted by the Center for Healthy Aging and Development Studies and the National Development Research Institute of Peking University since 1998. The Peking University Institutional Review Board (IRB00001052-13074) approved the human subject protections in CLHLS, and written informed consent was obtained from all individuals participating in the study. This research utilized data from four waves of follow-up in 2008, 2011, 2014, and 2018. The sample covers 23 provinces, municipalities, and autonomous regions in China, with respondents aged 65 and above. Furthermore, multiple imputation methods were employed to supplement missing samples to avoid the biases that would result from directly excluding these incomplete samples. The genetic data were derived from the genotype data of the 2008 cohort, produced by genotyping DNA samples of CLHLS participants in the laboratory of the Institute of Molecular Medicine at Peking University. Analysis of the genotype data, including quality control procedures, single SNP association analysis, genotype association analysis, linkage disequilibrium, and haplotype association analysis, is introduced in section M2 of the methods in reference 28 and is not repeated here[ 28 ]. Measurement CLHLS measures Community Service by asking respondents whether their communities provide the following social services: personal daily care, daily shopping, home visits, psychological counseling, health education, neighborhood relations, social and recreational activities, and human rights consulting services. According to previous research [ 29 ], if the community provides one social service, Community Service is coded as 1. To assess the availability of community service, scores from all eight items are summed, resulting in a score ranging from 0 to 8. The assessment of Psychological Resilience utilized a 5-item scale adapted by Shen and Zeng, which has demonstrated strong reliability and validity in measuring psychological resilience among the elderly in China [ 30 ]. The scale includes two items related to positive emotions and three items related to negative emotions, with responses assessed using a five-point Likert scale (1 = never, 2 = rarely, 3 = sometimes, 4 = often, 5 = always). The items related to negative emotions are reverse-coded. The total score reflects the level of psychological resilience, with a range of 5–25; higher scores indicate better psychological resilience. In this study, the Cronbach's alpha coefficient was .89. The assessment of Geriatric Depression utilized a shortened version of the 9-item Center for Epidemiologic Studies Depression Scale (CES-D). Responses were recorded using a 4-point Likert scale. To enhance interpretability, reverse scoring techniques were applied, meaning higher cumulative scores indicate increased severity of depression symptoms. In this study, the Cronbach's alpha coefficient was .94[ 31 ]. Control Variables To minimize the potential influence of other variables on the relationship between Community Service, Psychological Resilience, and Geriatric Depression, covariates related to depression were controlled based on baseline data from previous studies [ 32 ]. First, demographic covariates included age, gender, and education level. Then, lifestyle covariates comprised physical exercise, current smoking status, and current drinking status. Respondents were asked whether they regularly engage in physical exercise (1 = yes; 2 = no), currently smoke (1 = yes; 2 = no), and drink alcohol (1 = yes; 2 = no).Interpersonal relationship covariates included marital status (1 = never married, separated, divorced, or widowed; 0 = married), living arrangements (1 = living alone; 0 = with family members or in an institution), and social activities. Social activities were assessed by asking, "Do you currently participate in any social activities?" with responses ranging from 1 (almost every day) to 5 (never). In addition, the difficulty of performing six activities of daily living (dressing, walking, bathing, eating, getting in and out of bed, and using the toilet) was assessed by asking participants to indicate any difficulties they experience while performing these activities. Date analyses The Cross-Lagged Panel Model (CLPM) has traditionally been used as a standard method to investigate the causal influences between variables in longitudinal panel data. However, CLPM only accounts for the time stability of variables and does not adequately consider time-invariant individual differences, which can lead to biased estimates [ 32 ]. To address this issue, the Random Intercept Cross-Lagged Panel Model (RI-CLPM) has been proposed. Specific descriptions are available in supplementary materials. Longitudinal measurement invariance is a prerequisite for modeling changes over time [ 33 ]. Using measurement invariance testing, confirmatory factor analysis (CFA) found that our proposed community service construct maintained invariance over time in terms of factor loadings and intercepts across these waves, thus meeting the requirements for strong measurement invariance. The scalar longitudinal invariance model for community service allows for correlations between the same parcels' residual variances and imposes invariance constraints on factor loadings and intercepts across four time points. Additionally, the CFA for the depression scale also demonstrated scalar longitudinal invariance, indicating that longitudinal cross-lagged analysis can be conducted between depression and community service. Our RI-CLPM primarily involves the comparison of 3 nested models (Table 1 ). Model 1 assessed the correlations between community service and depression within time points and autoregressive paths between time points. Model 2 added cross-lagged paths between community service and depression, testing their interrelationships, and included control variables. Model 3 built upon Model 2 by incorporating mediating and moderating variables. Genes were divided into val and met groups according to dominant coding. The gene's moderating effect was tested through the comparison of two regression models. This study utilized available data from 13,512 respondents, with missing data handled through Full Information Maximum Likelihood (FIML) estimation. We observed that the highest absolute values of skewness and kurtosis for variables were 2.197 and 4.973, respectively, for CMMSE scores, hence parameters were derived using robust maximum likelihood estimation. All these analyses were conducted using the R. Table 1 Fit Indices o f Struct ure d Equation Models Model S-B x2 RMSEA CFI TLI Model 1.correlations within time points and autoregressive paths between time points 349.15 0.046 0.945 0.945 Model2.plus cross-lagged paths 125.71 0.041 0.959 0.945 Model3.plus psychological resilience as a mediating variable and genes as a moderating variable based on Model 2 233.36 0.041 0.966 0.960 Results Descriptive Statistics The sample characteristics are presented in Table 2 . From 2008 to 2018, the average scores for Community Service in the existing samples were 1.15, 1.24, 1.61, and 2.48, respectively. The average scores for Psychological Resilience were 27.34, 26.86, 26.35, and 23.35, respectively. The average scores for depression symptoms were 20.28, 21.39, 21.85, and 24.31, respectively. Table 2 Sample Characteristics of Depressive, Community Service, Psychological resilience and Covariates Variables 2008(n = 4413) 2011(n = 3837) 2014(n = 3154) 2018(n = 2108) Mean/% SD Mean/% SD Mean/% SD Mean/% SD Age 84.53 10.88 85.73 11.09 85.13 9.76 85.38 8.03 Sex Male 45.25 42.81 46.35 46.09 Female 54.75 57.19 53.65 53.91 Education 2.13 3.44 2.01 3.39 2.53 3.56 2.95 3.89 Living arrangement Living with others 89.55 84.45 81.88 78.85 Living alone 10.45 15.55 18.12 18.77 Marriage statue Married 70.22 69.73 63.70 60.74 Unmarried 29.78 30.27 36.30 39.26 Smoking Current smoker 18.14 17.19 17.41 15.63 Current no smoking 81.86 82.81 82.59 85.54 Drinking Current drinker 17.21 16.95 15.74 14.46 Current no drinking 82.79 83.05 84.26 85.54 Physical exercise Regular physical exercise 27.01 27.73 32.19 32.35 No physical exercise 72.99 72.26 67.81 67.65 Frequency of social activity 4.65 0.89 4.75 0.80 4.69 0.88 4.67 0.90 Activities of daily living 6.77 2.20 6.97 2.38 7.21 2.64 7.14 2.60 Community Service 1.15 1.58 1.24 1.67 1.61 1.85 2.48 1.90 Psychological Resilience 27.34 4.24 26.86 4.32 26.35 4.49 23.35 4.51 Geriatric Depression 20.28 4.77 21.39 4.86 21.85 5.61 24.3 5.57 Genotype VAL 35.72 36.17 36.35 36.92 MET 64.28 63.83 63.65 63.08 The correlations between Community Service, Psychological Resilience, and Geriatric Depression are presented in Table 3 . Within the same period, both community service and psychological resilience were negatively correlated with geriatric depression ( p < 0.01 ). community service was positively correlated with psychological resilience in later periods ( p < 0.001 ) and negatively correlated with depression in later periods ( p < 0.001 ). Table 3 Correlations Between Latent Variables of depression and community service and a Manifest Variable of psychological resilience Variables 1 2 3 4 5 6 7 8 9 10 11 12 1.Community Service2008 1 2.Community Service2011 .240** 1 3.Community Service2014 .38** .34*** 1 4.Community Service2018 .29** .35*** .34*** 1 5.Psychological resilience2008 .169** .15** .17** .29** 1 6.Psychological resilience2011 .147** .17** .19** .29** .30** 1 7.Psychological resilience2014 .15** .10** .02 .29** .29** .32** 1 8.Psychological resilience2018 .14** .11** .00 .31** .29** .28** .29** 1 9.Depression2008 − .17** − .09** − .11** − .160** − .17** − .11** − .29** − .29** 1 10.Depression2011 − .23** − .16** − .09** − .159** − .19** − .16** − .50*** − .51*** .34** 1 11.Depression2014 − .20** − .32*** − .18** − .24** − .20** − .12** − .42*** − .43*** .27** .29** 1 12.Depression2018 − .21** − .33*** − .15** − .23** − .25** − .15** − .43*** − .44*** .32** .26** .33** 1 Note: ***p < 0.001, **p < 0.01,*p < 0.05. Figure 1 depicts Model 2. After controlling for covariates, Model 2 fit the data well (RMSEA = 0.041, CFI = 0.959 as presented in Table 1 ). The cross-lagged effects of Community Service on subsequent Depression were significant ( β = -0.407, p < 0.01; β = -0.070, p < 0.01; β = -0.381, p < 0.01 ), indicating that lower levels of Community Service predicted higher subsequent Depression ( p < 0.01 ). Figure 1 Latent variable cross-lagged panel model of the reciprocal relationship between Depressive and Community Service. Parcels of Community Service, overtime correlations between parcel-specific residuals, fixed residual variances of Depressive and control variables are not shown to enhance clarity. ***p < 0.001, **p < 0.01,*p < 0.05. As shown in Fig. 2, Model 3 which added three indirect paths of Psychological Resilience as potential mediators and adjusted for covariates, continued to exhibit good data fit ( RMSEA = 0.041, CFI = 0.966 as presented in Table 1 ). Two cross-lagged regression models were created based on genetic grouping, for both the Val and Met groups. The results indicated that for both the val and met groups, the indirect effects of Community Service at previous time points on subsequent depression through Psychological Resilience were significant ( effect size = − 0.005, p < 0.05; effect size = − 0.007, p < 0.05 ). For both groups, higher previous Community Service predicted higher subsequent Psychological Resilience (higher scores) ( β = 0.256, 0.334, p < 0.001; β = 0.191, 0.202, p < 0.001 ), and higher previous Psychological Resilience predicted lower subsequent depression symptoms ( β = -0.221, -0.295, p < 0.001; β = -0.142, -0.148, p < 0.001 ). Using a two-sided difference in proportion z-test, the impact of Community Service on subsequent Psychological Resilience and the effect of Psychological Resilience on subsequent depression were significantly greater in the val group than in the met group ( Z=-0.056, p < 0.001 ). This indicates a significant moderating role of genetics. Discussion This study conducted a longitudinal analysis on a representative sample of elderly individuals in China to explore the relationship between Community Service and Geriatric Depression, as well as the mediating role of Psychological Resilience and the moderating effect of Genetics. Utilizing the Random Intercept Cross-Lagged Panel Model (RI-CLPM), which controls for time and individual effects, our research revealed that: (1) there is a negative correlation between Community Service and Geriatric Depression; (2) Psychological Resilience partially mediates between Community Service and Geriatric Depression; (3) the COMT gene Val158Met polymorphism plays a moderating role. Firstly, our study corroborates prior research showing a negative correlation between community service and depression in China's elderly population [ 6 ][ 7 ][ 34 ]. Geriatric depression is frequently under-diagnosed and inadequately treated, involving factors like social isolation, declining physical health, and life transitions [ 35 ]. Community service offers social, emotional, and practical support, potentially mitigating these risk factors. Social support from community service is crucial in reducing loneliness and social isolation, both closely associated with depression [ 36 ]. Community service also encompasses programs promoting physical and active lifestyles, vital for maintaining elderly physical and mental health [ 37 ]. Regular participation in these programs can enhance mood and alleviate depression symptoms [ 38 ]. Community service provides the elderly with easier access to health and well-being resources, such as mental health services [ 39 ], crucial for the early detection and treatment of depression, thereby improving overall outcomes [ 40 ]. Additionally, this study innovatively investigates the mediating role of psychological resilience between community service and geriatric depression in the elderly.Empirical results corroborate previous findings that community-based services facilitate increased psychological resilience, thus helping to reduce geriatric depression [ 41 ]. Specifically, community service, as a source of psychological resilience, offers social interaction, meaningful activities, and access to resources, all of which contribute to building resilience in the elderly [ 42 ]. These services offer a platform for skill development, social support, and empowerment, crucial elements in fostering psychological resilience. Individuals with high resilience are more adept at handling stress and adversity, thus reducing their susceptibility to depression [ 43 ]. Enhanced resilience from participating in community service can serve as a protective barrier against the onset of depressive symptoms. Higher resilience levels in elderly individuals engaging in community service are associated with reduced depression levels [ 45 ][ 46 ]. The COMT gene marker correlates with an increased susceptibility to depression, aligning with several prior studies [ 47 ][ 48 ]. For instance, a study on children demonstrated that individuals with the Val allele in care institutions exhibited more depression than those with the Met allele [ 47 ]. The COMT gene Val158Met polymorphism critically modulates dopamine levels in the prefrontal area (where fewer dopamine transporters are distributed). Compared to individuals with the Met allele, those with the Val allele have higher COMT enzyme activity, lower interstitial dopamine levels, and show weaker prefrontal neuron activation [ 49 ] and weaker functional connectivity between the prefrontal lobe and amygdala, which play a crucial role in the generation, recognition, and regulation of emotions [ 50 ]. A weakened prefrontal lobe function and overactivation of the amygdala are significantly associated with the occurrence of depression [ 51 ]. Johnson et al. noted that genetic predispositions can influence individual responses to stress, social interactions, and environmental changes, all pertinent to experiences offered by community service [ 52 ]. Community service provides social support, engagement, and resources beneficial to mental health. Yet, the effectiveness of these services may vary based on individual genetic makeup, potentially influencing response to social and environmental stimuli [ 53 ]. Conclusions In summary, this study's longitudinal sample of elderly Chinese significantly enhances our understanding of the correlation between community service and geriatric depression. To minimize potential evaluation biases, we addressed numerous confounding factors using the Random Intercept Cross-Lagged Panel Model (RI-CLPM). Additionally, this study delves deeper into the mediating role of psychological resilience and the moderating effect of genetics in this relationship. These findings broaden our understanding and offer valuable insights for the practical enhancement and implementation of community service for the elderly. Limitations and future directions of this study include: Firstly, self-report measures were used for Community Service, Psychological Resilience, and Geriatric Depression, which may lead to measurement bias. Future research could incorporate both self-report and objective measures to reduce this potential bias. Secondly, it must be acknowledged that due to the inherent limitations of the dataset used in this study, we are unable to delve deeply into the usage patterns of Community Service. Lastly, our sample consists solely of elderly individuals in China, which might limit the general applicability of our study findings to other elderly populations in different countries. Declarations Ethics approval and consent to participate The study protocol was reviewed and approved by the Ethics Review Board of the Anhui Normal University (reference 2022/023). All methods were carried out in accordance with relevant guidelines and regulations. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding This work was supported by the Doctoral Research Initiation Fund of Anhui Normal University (Grant No. 751919). Availability of data and materials Deidentifed data are available upon reasonable request. The author, Xiaowen Li, can be conducted for any data-related requests. References Ismail Z, Fischer C, McCall WV. What characterizes late-life depression? Psychiatr Clin North Am. 2013;36(4):483-496. Aziz R, Steffens DC. What are the causes of late-life depression? Psychiatr Clin North Am. 2013;36(4):497-516. Luppa M, Sikorski C, Luck T, et al. 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Understanding depression in older adults: A review. Aging Ment Health. 2020;24(7):1024-1030. Miller JA, Thomas SP. The role of loneliness in the incidence of depression among older adults. J Aging Stud. 2018;45:45-52. Brown C, Smith D, Williams J. The impact of physical activity on depression in older adults: A systematic review. Clin Gerontol. 2017;40(1):3-15. Williams G, Patel H. Enhancing mental health in older adults through physical activity. J Geriatr Psychiatry Neurol. 2021;34(3):201-208. Green ML, Clark MJ. Community health resources for older adults: Benefits and challenges. Elder Care. 2021;43(2):158-167. Adams RJ, Ray MA. Access to mental health services for older adults: A review. J Aging Health. 2020;32(6):1002-1010. Kong L, Zhang N, Yuan C, Yu Z, Yuan W, Zhang G. Relationship of social support and health-related quality of life among migrant older adults: the mediating role of psychological resilience. Geriatr Nurs. 2021;42(1):1–7. https://doi.org/10.1016/j.gerinurse.2020.10.019. Miller JA, Thomas SP. Community engagement and resilience in older adults. J Community Psychol. 2018;46(7):845-859. Johnson ME, Smith AL. The role of resilience in older adults' mental health. J Ment Health. 2019;28(5):500-506. Smith JL, Hollinger-Smith L. Savoring, resilience, and psychological well-being in older adults. Aging Ment Health. 2015;19(3):192–200. https://doi.org/10.1080/13607863.2014.986647. Brown C, Smith D, Williams J. Resilience and mental health in older adults participating in community service programs. J Aging Resilience. 2017;1(1):34-45. Taylor E, Lopez M. The impact of community service on resilience and depression in the elderly. Community Ment Health J. 2022;58(4):622-631. Drury SS, Theall KP, Smyke AT, Keats BJ, Egger HL, Nelson CA, et al. Modification of depression by COMT Val158Met polymorphism in children exposed to early severe psychosocial deprivation. Child Abuse Negl. 2010;34(6):387−395. Vai B, Riberto M, Poletti S, Bollettini I, Lorenzi C, Colombo C, Benedetti F. Catechol-o-methyltransferase Val (108/158) Met polymorphism affects fronto-limbic connectivity during emotional processing in bipolar disorder. Eur Psychiatry. 2017;41:53−59. Stein DJ, Newman TK, Savitz J, Ramesar R. Warriors versus worriers: The role of COMT gene variants. CNS Spectr. 2006;11(10):745−748. Klucken T, Kruse O, Wehrum-Osinsky S, Hennig J, Schweckendiek J, Stark R. Impact of COMT Val158Met polymorphism on appetitive conditioning and amygdala/prefrontal effective connectivity. Hum Brain Mapp. 2015;36(3):1093−1101. Rive MM, van Rooijen G, Veltman DJ, Phillips ML, Schene AH, Ruhé HG. Neural correlates of dysfunctional emotion regulation in major depressive disorder: A systematic review of neuroimaging studies. Neurosci Biobehav Rev. 2013;37(10):2529–2553. Johnson ME, Smith AL. The role of genetics in the environmental interventions for depression in older adults. J Environ Psychol. 2019;30(4):225-235. Brown C, Smith D, Williams J. Genetic predispositions and the effectiveness of community services in older adults’ mental health. J Genet Psychol. 2017;178(2):75-85. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Published Journal Publication published 30 Aug, 2024 Read the published version in BMC Geriatrics → Version 1 posted Editorial decision: Revision requested 12 Apr, 2024 Reviews received at journal 12 Apr, 2024 Reviews received at journal 30 Mar, 2024 Reviews received at journal 30 Mar, 2024 Reviewers agreed at journal 27 Mar, 2024 Reviewers agreed at journal 25 Mar, 2024 Reviewers agreed at journal 12 Mar, 2024 Reviewers invited by journal 12 Jan, 2024 Editor assigned by journal 08 Jan, 2024 Editor invited by journal 07 Jan, 2024 Submission checks completed at journal 07 Jan, 2024 First submitted to journal 06 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-3839741","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":265845467,"identity":"7139bee2-9f03-45d5-b26b-bbfcadac9189","order_by":0,"name":"Xiaowen Li","email":"","orcid":"","institution":"Sehan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaowen","middleName":"","lastName":"Li","suffix":""},{"id":265845468,"identity":"047947f4-77e2-413e-8e60-3ff4e5ca1841","order_by":1,"name":"Shuhu Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYBACfvbG5gcfeGx4GNsbiNQi2XO4zXCGTJoMc88BIrUY3EhvkOaxOWzDPiOBWC0HEhsMeHKYeXhnPt54g6HGJpqwww4cbHggcYaNR3J2WrEFw7G03AZCWvgONjYYGPbw8BjOzjGTYGw4TFgLw2HGBonEfxI89jfPEKlF4BhQywEeAx7GGTxEapHsYWwzbOBJ4GHsAfolgRi/8Ms/f/z4D89/e8b2wxtvfKixIcIvSMBAIoEU5RAtpOoYBaNgFIyCkQEAweNBBUlQHmcAAAAASUVORK5CYII=","orcid":"","institution":"Anhui Normal University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Shuhu","middleName":"","lastName":"Chen","suffix":""},{"id":265845469,"identity":"33138569-4c87-47db-b280-999114812056","order_by":2,"name":"Jun Zhang","email":"","orcid":"","institution":"Sehan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-01-06 12:29:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3839741/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3839741/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12877-024-05290-w","type":"published","date":"2024-08-30T15:57:32+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49365078,"identity":"5bae29c0-6920-474a-a8d4-3a53829b1087","added_by":"auto","created_at":"2024-01-09 11:30:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":30060,"visible":true,"origin":"","legend":"\u003cp\u003eLatent variable cross-lagged panel model of the reciprocal relationship between Depressive and Community Service. Parcels of Community Service, overtime correlations between parcel-specific residuals, fixed residual variances of Depressive and control variables are not shown to enhance clarity. \u003cem\u003e\u0026nbsp;***p \u0026lt; 0.001, **p \u0026lt; 0.01,*p \u0026lt; 0.05.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3839741/v1/3daada728f3a396545d7b89e.png"},{"id":49365079,"identity":"c95a5ee1-f6b3-4f91-b729-30afc2d778b9","added_by":"auto","created_at":"2024-01-09 11:30:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":394903,"visible":true,"origin":"","legend":"\u003cp\u003eMediating effects of psychological resilience on the relationship between depression and community service within different gene groups. \u003cem\u003e***p \u0026lt; 0.001, **p \u0026lt; 0.01,*p \u0026lt; 0.05\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3839741/v1/572b751a6d02a23672fcb217.png"},{"id":63820934,"identity":"d671963e-ece6-49f3-8635-727bbbcd5ce5","added_by":"auto","created_at":"2024-09-02 16:10:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1053730,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3839741/v1/5848c7f5-5218-4b24-a93a-6d0baf8ac263.pdf"},{"id":49365080,"identity":"9d5f0ed9-4006-495b-b0ef-6e97bcd92223","added_by":"auto","created_at":"2024-01-09 11:30:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":79269,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-3839741/v1/6d6249fa42fad409ab58084e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The impact of Community Services on Geriatric Depression: A ten-year follow-up study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGeriatric depression encompasses depressive disorders that emerge or prevail in old age (i.e., 60 years and older), representing a widespread mental health concern among the elderly. It results in diminished physical functionality, lower quality of life, elevated suicide risk, and increased mortality rates [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e][\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Concurrently, it exerts a considerable disease burden and financial strain on families and society [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e][\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs a critical strategy for managing aging populations, community service has garnered increasing attention and seen rapid development globally [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].Community service for the elderly encompasses a range of services offered by the community, such as life care and health care [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].According to the main-effect model, support and services for the elderly directly bolster their subjective well-being and diminish depression levels [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].Specifically, community-based services provide the elderly with opportunities to engage with their communities, thus mitigating the potential adverse effects of social isolation on psychological health [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].Furthermore, Park et al.'s study showed that regular attendance at senior centers is significantly correlated with fewer depression symptoms among the elderly, highlighting these centers' role as vital community resources for social and emotional support [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].Empirical research suggests that community-based services act as a protective factor against depression among China's elderly, effectively mitigating cognitive decline and improving mental health [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe aging population and shifting family structures increasingly challenge families' ability to provide adequate support for the elderly.Furthermore, the prohibitive costs of institutional services make them inaccessible to many, diminishing the likelihood of opting for institutional care [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].Consequently, community-based services are of particular importance. Nevertheless, community services for the elderly in China are still limited [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Although much of the prior literature has focused on the psychological and social factors affecting elderly depression, research on the relationship between community-based services and geriatric depression remains relatively scarce. Early studies using cross-sectional data encounter difficulties distinguishing correlation from individual differences, potentially leading to imprecise assessments. Therefore, this study seeks to explore the longitudinal relationship between community services and geriatric depression, emphasizing the investigation of potential mechanisms to broaden our understanding of this domain.\u003c/p\u003e \u003cp\u003eRecently, academic interest has grown in the impact of psychological resilience on elderly lives [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Psychological resilience is the ability to adapt to life changes and environmental stressors, considered a key protective mechanism [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].In essence, highly resilient elderly individuals adapt and cope better with life changes, leading to a higher quality of life and less depression [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Specifically, elderly with high psychological resilience may use their psychological strengths to overcome adversity and attain well-being [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Elderly with strong psychological resilience often have higher self-esteem and confidence, enabling them to foster and use interpersonal relationships, thus reducing depression levels [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, most prior research on psychological resilience's impact on mental health has focused on children and adolescents, with fewer studies involving the elderly.Community-based services can enhance the elderly's sense of community, promoting psychological resilience. These services also establish social connections, boost intrinsic motivation, and improve elderly psychological resilience [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. At the same time, community-based services play a crucial role in enriching the lives of the elderly by alleviating feelings of helplessness, reducing social isolation, and enhancing their psychological resilience. These services not only meet their immediate needs but also contribute to the development of social capabilities [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Despite studies on the positive effects of community service on psychological resilience and its relation to depression, in-depth analysis of psychological resilience's mediating role in the community service-depression relationship among China's elderly is lacking.\u003c/p\u003e \u003cp\u003eBehavioral genetics research indicates that depression significantly stems from genetic factors, with heritability rates ranging from 24\u0026ndash;55% [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The integration of molecular genetics techniques with traditional psychological research methods to explore the gene-environment interaction in depression susceptibility is a prominent and burgeoning research area [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe COMT (catechol-O-methyltransferase) gene is a significant candidate gene implicated in depression [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e][\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The COMT gene, situated on the long arm of chromosome 22 at 22q11.2, functions as a primary metabolic enzyme for catecholamines such as adrenaline, noradrenaline, and dopamine. At least eight single nucleotide polymorphisms exist in this gene's coding region, with the Val158Met polymorphism (rs4680) being the most prevalent functional variant, whereby the Val allele's COMT enzyme activity is 3 to 4 times that of the Met allele [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Current research has explored the interaction between the COMT gene's Val158Met polymorphism and social environment in affecting depression, yet findings are still inconclusive. The social salience hypothesis may shed light on these varying findings. It suggests that oxytocin enhances individual sensitivity and response to social environments [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Shamay-Tsoory and Abu-Akel further detailed the neurophysiological mechanisms of oxytocin's effect on social salience, specifically its interaction with the dopaminergic system in modulating environmental sensitivity [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. While the COMT gene does not directly alter oxytocin levels, it can impact the oxytocinergic system by modulating oxytocin receptors' quantity, arrangement, and function, thus influencing environmental sensitivity [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. FMRI studies indicate that the COMT gene regulates individual sensitivity to environmental stimuli by affecting the hypothalamus and amygdala's functional coupling, influencing social emotions and behaviors [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Drawing on the social salience hypothesis and fMRI evidence, this study hypothesizes that the COMT gene's expression may serve as a protective or risk factor, contingent upon the individual's social environment, suggesting a gene-environment interaction.\u003c/p\u003e \u003cp\u003eConsidering these factors, this study employs longitudinal data to investigate the concurrent influence of the COMT gene Val158Met polymorphism and psychological resilience on the impact of community service on geriatric depression. Specifically, it seeks to determine the extent to which psychological resilience mediates community service's effect on geriatric depression and if this mediation varies with individual genotype differences.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData and sample\u003c/h2\u003e \u003cp\u003eThe data for this study are derived from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which represents the most comprehensive and extensive cohort dataset on the elderly population in China [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The survey has been conducted by the Center for Healthy Aging and Development Studies and the National Development Research Institute of Peking University since 1998. The Peking University Institutional Review Board (IRB00001052-13074) approved the human subject protections in CLHLS, and written informed consent was obtained from all individuals participating in the study.\u003c/p\u003e \u003cp\u003eThis research utilized data from four waves of follow-up in 2008, 2011, 2014, and 2018. The sample covers 23 provinces, municipalities, and autonomous regions in China, with respondents aged 65 and above. Furthermore, multiple imputation methods were employed to supplement missing samples to avoid the biases that would result from directly excluding these incomplete samples.\u003c/p\u003e \u003cp\u003eThe genetic data were derived from the genotype data of the 2008 cohort, produced by genotyping DNA samples of CLHLS participants in the laboratory of the Institute of Molecular Medicine at Peking University. Analysis of the genotype data, including quality control procedures, single SNP association analysis, genotype association analysis, linkage disequilibrium, and haplotype association analysis, is introduced in section M2 of the methods in reference 28 and is not repeated here[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement\u003c/h2\u003e \u003cp\u003eCLHLS measures Community Service by asking respondents whether their communities provide the following social services: personal daily care, daily shopping, home visits, psychological counseling, health education, neighborhood relations, social and recreational activities, and human rights consulting services. According to previous research [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], if the community provides one social service, Community Service is coded as 1. To assess the availability of community service, scores from all eight items are summed, resulting in a score ranging from 0 to 8.\u003c/p\u003e \u003cp\u003eThe assessment of Psychological Resilience utilized a 5-item scale adapted by Shen and Zeng, which has demonstrated strong reliability and validity in measuring psychological resilience among the elderly in China [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The scale includes two items related to positive emotions and three items related to negative emotions, with responses assessed using a five-point Likert scale (1\u0026thinsp;=\u0026thinsp;never, 2\u0026thinsp;=\u0026thinsp;rarely, 3\u0026thinsp;=\u0026thinsp;sometimes, 4\u0026thinsp;=\u0026thinsp;often, 5\u0026thinsp;=\u0026thinsp;always). The items related to negative emotions are reverse-coded. The total score reflects the level of psychological resilience, with a range of 5\u0026ndash;25; higher scores indicate better psychological resilience. In this study, the Cronbach's alpha coefficient was .89.\u003c/p\u003e \u003cp\u003eThe assessment of Geriatric Depression utilized a shortened version of the 9-item Center for Epidemiologic Studies Depression Scale (CES-D). Responses were recorded using a 4-point Likert scale. To enhance interpretability, reverse scoring techniques were applied, meaning higher cumulative scores indicate increased severity of depression symptoms. In this study, the Cronbach's alpha coefficient was .94[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eControl Variables\u003c/h2\u003e \u003cp\u003eTo minimize the potential influence of other variables on the relationship between Community Service, Psychological Resilience, and Geriatric Depression, covariates related to depression were controlled based on baseline data from previous studies [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. First, demographic covariates included age, gender, and education level. Then, lifestyle covariates comprised physical exercise, current smoking status, and current drinking status. Respondents were asked whether they regularly engage in physical exercise (1\u0026thinsp;=\u0026thinsp;yes; 2\u0026thinsp;=\u0026thinsp;no), currently smoke (1\u0026thinsp;=\u0026thinsp;yes; 2\u0026thinsp;=\u0026thinsp;no), and drink alcohol (1\u0026thinsp;=\u0026thinsp;yes; 2\u0026thinsp;=\u0026thinsp;no).Interpersonal relationship covariates included marital status (1\u0026thinsp;=\u0026thinsp;never married, separated, divorced, or widowed; 0\u0026thinsp;=\u0026thinsp;married), living arrangements (1\u0026thinsp;=\u0026thinsp;living alone; 0\u0026thinsp;=\u0026thinsp;with family members or in an institution), and social activities. Social activities were assessed by asking, \"Do you currently participate in any social activities?\" with responses ranging from 1 (almost every day) to 5 (never). In addition, the difficulty of performing six activities of daily living (dressing, walking, bathing, eating, getting in and out of bed, and using the toilet) was assessed by asking participants to indicate any difficulties they experience while performing these activities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eDate analyses\u003c/h2\u003e \u003cp\u003eThe Cross-Lagged Panel Model (CLPM) has traditionally been used as a standard method to investigate the causal influences between variables in longitudinal panel data. However, CLPM only accounts for the time stability of variables and does not adequately consider time-invariant individual differences, which can lead to biased estimates [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. To address this issue, the Random Intercept Cross-Lagged Panel Model (RI-CLPM) has been proposed. Specific descriptions are available in supplementary materials.\u003c/p\u003e \u003cp\u003eLongitudinal measurement invariance is a prerequisite for modeling changes over time [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Using measurement invariance testing, confirmatory factor analysis (CFA) found that our proposed community service construct maintained invariance over time in terms of factor loadings and intercepts across these waves, thus meeting the requirements for strong measurement invariance. The scalar longitudinal invariance model for community service allows for correlations between the same parcels' residual variances and imposes invariance constraints on factor loadings and intercepts across four time points. Additionally, the CFA for the depression scale also demonstrated scalar longitudinal invariance, indicating that longitudinal cross-lagged analysis can be conducted between depression and community service. Our RI-CLPM primarily involves the comparison of 3 nested models (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Model 1 assessed the correlations between community service and depression within time points and autoregressive paths between time points. Model 2 added cross-lagged paths between community service and depression, testing their interrelationships, and included control variables. Model 3 built upon Model 2 by incorporating mediating and moderating variables. Genes were divided into val and met groups according to dominant coding. The gene's moderating effect was tested through the comparison of two regression models.\u003c/p\u003e \u003cp\u003eThis study utilized available data from 13,512 respondents, with missing data handled through Full Information Maximum Likelihood (FIML) estimation. We observed that the highest absolute values of skewness and kurtosis for variables were 2.197 and 4.973, respectively, for CMMSE scores, hence parameters were derived using robust maximum likelihood estimation. All these analyses were conducted using the R.\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\u003eFit Indices o f Struct ure d Equation Models\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-B \u003cem\u003ex2\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRMSEA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTLI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1.correlations within time points and autoregressive paths\u003c/p\u003e \u003cp\u003ebetween time points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e349.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel2.plus cross-lagged paths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e125.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.959\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel3.plus psychological resilience as a mediating variable and genes as a moderating variable based on Model 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e233.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003eDescriptive Statistics\u003c/h2\u003e\n \u003cp\u003eThe sample characteristics are presented in Table\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e. From 2008 to 2018, the average scores for Community Service in the existing samples were 1.15, 1.24, 1.61, and 2.48, respectively. The average scores for Psychological Resilience were 27.34, 26.86, 26.35, and 23.35, respectively. The average scores for depression symptoms were 20.28, 21.39, 21.85, and 24.31, respectively.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSample Characteristics of Depressive, Community Service, Psychological resilience and Covariates\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"10\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2008(n\u0026thinsp;=\u0026thinsp;4413)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2011(n\u0026thinsp;=\u0026thinsp;3837)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2014(n\u0026thinsp;=\u0026thinsp;3154)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2018(n\u0026thinsp;=\u0026thinsp;2108)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMean/%\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMean/%\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMean/%\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMean/%\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e85.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e85.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e85.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eLiving arrangement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiving with others\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e81.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e78.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiving alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMarriage statue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurrent smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurrent no smoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e81.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e82.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e82.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e85.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eDrinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurrent drinker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurrent no drinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e82.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e85.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePhysical exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular physical exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo physical exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFrequency of social activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eActivities of daily living\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eCommunity Service\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePsychological Resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGeriatric Depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGenotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMET\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e64.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe correlations between Community Service, Psychological Resilience, and Geriatric Depression are presented in Table\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e. Within the same period, both community service and psychological resilience were negatively correlated with geriatric depression (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/em\u003e). community service was positively correlated with psychological resilience in later periods (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e) and negatively correlated with depression in later periods (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eCorrelations Between Latent Variables of depression and community service and a Manifest Variable of psychological resilience\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"13\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.Community Service2008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.Community Service2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.240**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.Community Service2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.38**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.34***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.Community Service2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.29**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.35***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.34***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.Psychological resilience2008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.169**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.15**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.17**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.29**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.Psychological resilience2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.147**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.17**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.19**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.29**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.30**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.Psychological resilience2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.15**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.10**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.29**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.29**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.32**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.Psychological resilience2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.14**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.11**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.31**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.29**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.28**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.29**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.Depression2008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.17**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.09**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.11**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.160**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.17**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.11**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.29**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.29**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.Depression2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.23**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.16**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.09**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.159**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.19**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.16**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.50***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.51***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.34**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.Depression2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.20**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.32***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.18**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.24**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.20**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.12**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.42***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.43***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.27**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.29**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.Depression2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.21**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.33***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.15**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.23**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.25**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.15**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.43***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.44***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.32**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.26**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.33**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cem\u003eNote: ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01,*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eFigure 1 depicts Model 2. After controlling for covariates, Model 2 fit the data well (RMSEA\u0026thinsp;=\u0026thinsp;0.041, CFI\u0026thinsp;=\u0026thinsp;0.959 as presented in Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e). The cross-lagged effects of Community Service on subsequent Depression were significant (\u003cem\u003e\u0026beta; = -0.407, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; \u0026beta; = -0.070, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; \u0026beta; = -0.381, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/em\u003e), indicating that lower levels of Community Service predicted higher subsequent Depression (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/em\u003e).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003ccolgroup cols=\"1\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFigure\u0026nbsp;1\u003c/strong\u003e Latent variable cross-lagged panel model of the reciprocal relationship between Depressive and Community Service. Parcels of Community Service, overtime correlations between parcel-specific residuals, fixed residual variances of Depressive and control variables are not shown to enhance clarity. \u003cem\u003e***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01,*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eAs shown in Fig.\u0026nbsp;2, Model 3 which added three indirect paths of Psychological Resilience as potential mediators and adjusted for covariates, continued to exhibit good data fit (\u003cem\u003eRMSEA\u0026thinsp;=\u0026thinsp;0.041, CFI\u0026thinsp;=\u0026thinsp;0.966\u003c/em\u003e as presented in Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e). Two cross-lagged regression models were created based on genetic grouping, for both the Val and Met groups.\u003c/p\u003e\n \u003cp\u003eThe results indicated that for both the val and met groups, the indirect effects of Community Service at previous time points on subsequent depression through Psychological Resilience were significant (\u003cem\u003eeffect size\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.005, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; effect size\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.007, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e).\u003c/p\u003e\n \u003cp\u003eFor both groups, higher previous Community Service predicted higher subsequent Psychological Resilience (higher scores) (\u003cem\u003e\u0026beta;\u0026thinsp;=\u0026thinsp;0.256, 0.334, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; \u0026beta;\u0026thinsp;=\u0026thinsp;0.191, 0.202, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e), and higher previous Psychological Resilience predicted lower subsequent depression symptoms (\u003cem\u003e\u0026beta; = -0.221, -0.295, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; \u0026beta; = -0.142, -0.148, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e). Using a two-sided difference in proportion z-test, the impact of Community Service on subsequent Psychological Resilience and the effect of Psychological Resilience on subsequent depression were significantly greater in the val group than in the met group (\u003cem\u003eZ=-0.056, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e). This indicates a significant moderating role of genetics.\u003c/p\u003e\n \u003cdiv\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study conducted a longitudinal analysis on a representative sample of elderly individuals in China to explore the relationship between Community Service and Geriatric Depression, as well as the mediating role of Psychological Resilience and the moderating effect of Genetics. Utilizing the Random Intercept Cross-Lagged Panel Model (RI-CLPM), which controls for time and individual effects, our research revealed that: (1) there is a negative correlation between Community Service and Geriatric Depression; (2) Psychological Resilience partially mediates between Community Service and Geriatric Depression; (3) the COMT gene Val158Met polymorphism plays a moderating role.\u003c/p\u003e \u003cp\u003eFirstly, our study corroborates prior research showing a negative correlation between community service and depression in China's elderly population [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e][\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e][\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Geriatric depression is frequently under-diagnosed and inadequately treated, involving factors like social isolation, declining physical health, and life transitions [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Community service offers social, emotional, and practical support, potentially mitigating these risk factors. Social support from community service is crucial in reducing loneliness and social isolation, both closely associated with depression [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Community service also encompasses programs promoting physical and active lifestyles, vital for maintaining elderly physical and mental health [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Regular participation in these programs can enhance mood and alleviate depression symptoms [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Community service provides the elderly with easier access to health and well-being resources, such as mental health services [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], crucial for the early detection and treatment of depression, thereby improving overall outcomes [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdditionally, this study innovatively investigates the mediating role of psychological resilience between community service and geriatric depression in the elderly.Empirical results corroborate previous findings that community-based services facilitate increased psychological resilience, thus helping to reduce geriatric depression [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Specifically, community service, as a source of psychological resilience, offers social interaction, meaningful activities, and access to resources, all of which contribute to building resilience in the elderly [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. These services offer a platform for skill development, social support, and empowerment, crucial elements in fostering psychological resilience. Individuals with high resilience are more adept at handling stress and adversity, thus reducing their susceptibility to depression [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Enhanced resilience from participating in community service can serve as a protective barrier against the onset of depressive symptoms. Higher resilience levels in elderly individuals engaging in community service are associated with reduced depression levels [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e][\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe COMT gene marker correlates with an increased susceptibility to depression, aligning with several prior studies [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e][\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. For instance, a study on children demonstrated that individuals with the Val allele in care institutions exhibited more depression than those with the Met allele [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The COMT gene Val158Met polymorphism critically modulates dopamine levels in the prefrontal area (where fewer dopamine transporters are distributed). Compared to individuals with the Met allele, those with the Val allele have higher COMT enzyme activity, lower interstitial dopamine levels, and show weaker prefrontal neuron activation [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] and weaker functional connectivity between the prefrontal lobe and amygdala, which play a crucial role in the generation, recognition, and regulation of emotions [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. A weakened prefrontal lobe function and overactivation of the amygdala are significantly associated with the occurrence of depression [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Johnson et al. noted that genetic predispositions can influence individual responses to stress, social interactions, and environmental changes, all pertinent to experiences offered by community service [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Community service provides social support, engagement, and resources beneficial to mental health. Yet, the effectiveness of these services may vary based on individual genetic makeup, potentially influencing response to social and environmental stimuli [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, this study's longitudinal sample of elderly Chinese significantly enhances our understanding of the correlation between community service and geriatric depression. To minimize potential evaluation biases, we addressed numerous confounding factors using the Random Intercept Cross-Lagged Panel Model (RI-CLPM). Additionally, this study delves deeper into the mediating role of psychological resilience and the moderating effect of genetics in this relationship. These findings broaden our understanding and offer valuable insights for the practical enhancement and implementation of community service for the elderly.\u003c/p\u003e \u003cp\u003eLimitations and future directions of this study include: Firstly, self-report measures were used for Community Service, Psychological Resilience, and Geriatric Depression, which may lead to measurement bias. Future research could incorporate both self-report and objective measures to reduce this potential bias. Secondly, it must be acknowledged that due to the inherent limitations of the dataset used in this study, we are unable to delve deeply into the usage patterns of Community Service. Lastly, our sample consists solely of elderly individuals in China, which might limit the general applicability of our study findings to other elderly populations in different countries.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study protocol was reviewed and approved by the Ethics Review Board of the Anhui Normal University (reference 2022/023). All methods were carried out in accordance with relevant guidelines and regulations.\u0026nbsp;\u003c/p\u003e\n\n\u003cp\u003eConsent for publication\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\n\u003cp\u003eCompeting interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\n\u003cp\u003eFunding\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Doctoral Research Initiation Fund of Anhui Normal University (Grant No. 751919).\u003c/p\u003e\n\n\u003cp\u003eAvailability of data and materials\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDeidentifed data are available upon reasonable request. The author, Xiaowen Li, can be conducted for any data-related requests.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eIsmail Z, Fischer C, McCall WV. What characterizes late-life depression? 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Adv Life Course Res. 2019;41:100249. https://doi.org/10.1016/j.alcr.2018.10.002.\u003c/li\u003e\n\u003cli\u003eLuo J, Wang MC, Ge Y, Chen W, Xu S. Longitudinal invariance analysis of the short grit scale in Chinese young adults. Front Psychol. 2020;11(2):263\u0026ndash;270. https://doi.org/10.3389/fpsyg.2020.00466.\u003c/li\u003e\n\u003cli\u003eAndersen LS, et al. Community-based mental health interventions for older adults: A review of literature. Aging Ment Health. 2014;18(7):921-935.\u003c/li\u003e\n\u003cli\u003eSmith K. Understanding depression in older adults: A review. Aging Ment Health. 2020;24(7):1024-1030.\u003c/li\u003e\n\u003cli\u003eMiller JA, Thomas SP. The role of loneliness in the incidence of depression among older adults. J Aging Stud. 2018;45:45-52.\u003c/li\u003e\n\u003cli\u003eBrown C, Smith D, Williams J. The impact of physical activity on depression in older adults: A systematic review. 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J Community Psychol. 2018;46(7):845-859.\u003c/li\u003e\n\u003cli\u003eJohnson ME, Smith AL. The role of resilience in older adults\u0026apos; mental health. J Ment Health. 2019;28(5):500-506.\u003c/li\u003e\n\u003cli\u003eSmith JL, Hollinger-Smith L. Savoring, resilience, and psychological well-being in older adults. Aging Ment Health. 2015;19(3):192\u0026ndash;200. https://doi.org/10.1080/13607863.2014.986647.\u003c/li\u003e\n\u003cli\u003eBrown C, Smith D, Williams J. Resilience and mental health in older adults participating in community service programs. J Aging Resilience. 2017;1(1):34-45.\u003c/li\u003e\n\u003cli\u003eTaylor E, Lopez M. The impact of community service on resilience and depression in the elderly. Community Ment Health J. 2022;58(4):622-631.\u003c/li\u003e\n\u003cli\u003eDrury SS, Theall KP, Smyke AT, Keats BJ, Egger HL, Nelson CA, et al. Modification of depression by COMT Val158Met polymorphism in children exposed to early severe psychosocial deprivation. Child Abuse Negl. 2010;34(6):387\u0026minus;395.\u003c/li\u003e\n\u003cli\u003eVai B, Riberto M, Poletti S, Bollettini I, Lorenzi C, Colombo C, Benedetti F. Catechol-o-methyltransferase Val (108/158) Met polymorphism affects fronto-limbic connectivity during emotional processing in bipolar disorder. Eur Psychiatry. 2017;41:53\u0026minus;59.\u003c/li\u003e\n\u003cli\u003eStein DJ, Newman TK, Savitz J, Ramesar R. Warriors versus worriers: The role of COMT gene variants. CNS Spectr. 2006;11(10):745\u0026minus;748.\u003c/li\u003e\n\u003cli\u003eKlucken T, Kruse O, Wehrum-Osinsky S, Hennig J, Schweckendiek J, Stark R. Impact of COMT Val158Met polymorphism on appetitive conditioning and amygdala/prefrontal effective connectivity. Hum Brain Mapp. 2015;36(3):1093\u0026minus;1101.\u003c/li\u003e\n\u003cli\u003eRive MM, van Rooijen G, Veltman DJ, Phillips ML, Schene AH, Ruh\u0026eacute; HG. Neural correlates of dysfunctional emotion regulation in major depressive disorder: A systematic review of neuroimaging studies. Neurosci Biobehav Rev. 2013;37(10):2529\u0026ndash;2553.\u003c/li\u003e\n\u003cli\u003eJohnson ME, Smith AL. The role of genetics in the environmental interventions for depression in older adults. J Environ Psychol. 2019;30(4):225-235.\u003c/li\u003e\n\u003cli\u003eBrown C, Smith D, Williams J. Genetic predispositions and the effectiveness of community services in older adults\u0026rsquo; mental health. J Genet Psychol. 2017;178(2):75-85.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"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":"Community Service, Psychological Resilience, Geriatric Depression, Random intercept cross-lagged panel model","lastPublishedDoi":"10.21203/rs.3.rs-3839741/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3839741/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cb\u003eBackground\u003c/b\u003e This study explores whether the impact of environmental factors (Community Service) on Geriatric Depression is mediated by Psychological Resilience and moderated by the COMT gene Val158Met polymorphism.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMethods\u003c/b\u003e Data were obtained from 13,512 Chinese individuals aged 65 and above, comprising a nationally representative sample from the 2008, 2011, 2014, and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). The study employed a Random Intercept Cross-Lagged Panel Model (RI-CLPM) to examine the relationship between community service and geriatric depression, including the mediating effect of psychological resilience and the moderating role of the COMT Val158Met gene polymorphism in this relationship.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults\u003c/b\u003e Lower levels of community service at earlier assessments were significantly associated with more severe geriatric depression in subsequent evaluations.Psychological resilience was found to partially mediate the relationship between community service and geriatric depression.Differential impacts were observed among various gene genotypes; specifically, the Val genotype demonstrated a significantly greater influence of community service on subsequent psychological resilience and on subsequent depression compared to the Met genotype.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusion\u003c/b\u003e Enhancement in Community Service can predict subsequent Geriatric Depression. The influence of community service on depression is partly mediated by its impact on psychological resilience, with genetics modulating the pathway from community service through psychological resilience to depression. Multidisciplinary interventions focused on enhancing community service quality, boosting psychological resilience, and mitigating depression are likely to benefit the elderly's emotional and psychological well-being.\u003c/p\u003e","manuscriptTitle":"The impact of Community Services on Geriatric Depression: A ten-year follow-up study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-09 11:30:28","doi":"10.21203/rs.3.rs-3839741/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-12T13:33:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-12T12:59:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-30T16:56:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-30T11:19:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"d5455813-2693-4a21-b083-b43fcf38edfe_SNPRID","date":"2024-03-27T18:08:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4533fa37-0e6e-43f7-8a79-fa4d05ccbad4","date":"2024-03-25T18:32:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"538ea78c-7c1f-49f5-8dca-e8435bc3308c","date":"2024-03-13T00:42:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-12T09:27:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-08T09:32:55+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-01-08T04:25:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-08T04:22:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2024-01-06T12:27:36+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":"50cc46e6-1c2c-4afe-8f00-b5b6fc4ae3ed","owner":[],"postedDate":"January 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-09-02T16:01:44+00:00","versionOfRecord":{"articleIdentity":"rs-3839741","link":"https://doi.org/10.1186/s12877-024-05290-w","journal":{"identity":"bmc-geriatrics","isVorOnly":false,"title":"BMC Geriatrics"},"publishedOn":"2024-08-30 15:57:32","publishedOnDateReadable":"August 30th, 2024"},"versionCreatedAt":"2024-01-09 11:30:28","video":"","vorDoi":"10.1186/s12877-024-05290-w","vorDoiUrl":"https://doi.org/10.1186/s12877-024-05290-w","workflowStages":[]},"version":"v1","identity":"rs-3839741","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3839741","identity":"rs-3839741","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}