Meta-Analysis: The Effect of Social Capital on Depression in Elderly
DOI:
https://doi.org/10.26911/thejhpb.2025.10.01.10Abstract
Background: According to WHO (2022), 14% of adults >60 years live with depression which accounts for 10.6% of total disability in the elderly. Depression is associated with an increased risk of premature death, with a potential reduction in life expectancy of around 10 years. Studies report that strengthening social capital can be an effective strategy in preventing and managing depression in the elderly. This study aims to analyze the influence of social capital on depression in the elderly.
Subjects and Method: This research is a meta-analysis of the PICO model. Population: elderly. Intervention: high social participation, high social cohesion, high reciprocity, high social trust and high social network. Comparison: low social participation, low social cohesion, low reciprocity, low social trust and low social network. Outcome: depression. The data used involves Google Scholar, PubMed, BMC, Elsevier, ScienceDirect, and Springer Link. Inclusion criteria were full-text articles with a cross-sectional study design using multivariate analysis that included OR values and were published from 2014-2023. Data analysis using the Review Manager 5.3 application.
Results: The meta-analysis included 17 cross-sectional studies from Korea, Spain, Japan, Taiwan, the Netherlands, China, and Myanmar. The results showed that the incidence of depression decreased with high social participation (aOR= 0.78; 95% CI= 0.61–1.00; p= 0.050), high social cohesion (aOR= 0.84; 95% CI= 0.72 – 0.99; p= 0.030), high reciprocity (aOR= 0.75; 95% CI= 0.63 – 0.90; p= 0.020), and high social trust (aOR= 0.52; 95% CI= 0.41 – 0.66; p<0.001). Social networks reduce the risk of depression but were not statistically significant a(OR= 0.71; CI 95%= 0.31 – 1.59; p= 0.400).
Conclusion: Social participation, social cohesion, reciprocity, and social trust have an effect on reducing the risk of depression in the elderly.
Keywords:
Social capital, social participation, social cohesion, reciprocity, social trust, social network, depression, elderlyReferences
A national survey. BMC Public Health. 20(1): 1-14. https://doi.org/10.1186-/s12889-020-09695-1
Bae M, Kim Y, Hong I. (2023). Factors of capital on depression in older adult-hood: a comparison of urban and rural regions in Korea. In Healthcare. 11(21): 2850. https://doi.org/10.33-90/healthcare11212850.
Bai Z, Xu Z, Xu X, Qin X, Hu W, Hu Z. (2020). Association between social capital and depression among older people: evidence from Anhui Province China. BMC Public Health. 20. 1-11. https://doi.org/10.1186/s12889-020-09657-7.
Baranyi G, Sieber S, Cullati S, Pearce JR, Dibben CJL, Courvoisier DS. (2020). The longitudinal associations of perceived neighborhood disorder and lack of social cohesion with depres-sion among adults aged 50 years or older: an individual-participant-data meta-analysis from 16 high-income countries. AmJ Epidemiol. 189(4): 343-353. https://doi.org/10.1093/aj-e/kwz209.
Cavanagh D, Jurcik T, Charkhabi M. (2022). How does trust affect help-seeking for depression in Russia and Australia? Int J Soc Psychiatry. 68(8): 1561-1570. https://doi.org/10.1177/-00207640211039253.
Cheng Y, Sun M, Wang F, Geng X, Wang F. (2021). Identification of hub genes related to Alzheimer’s disease and major depressive disorder. Am J Alzheimers Dis Other Demen. 36. 1-13. https://doi.org/10.1177/153331-75211046123.
Cho SM, Saw YM, Saw TN, Than TM, Khaing M, Khine AT, et al. (2021). Prevalence and risk factors of anxiety and depression among the commu-nity-dwelling elderly in Nay Pyi Taw Union Territory Myanmar. Sci Rep. 11(1): 9763. https://doi.org/10.1038-/s41598-021-88621-w.
Choi E, Han KM, Chang J, Lee YJ, Choi KW, Han C. et al. (2021). Social parti-cipation and depressive symptoms in community-dwelling older adults: Emotional social support as a media-tor. J Psychiatr Res. 137: 589-596. https://doi.org/10.1016/j.jpsy-chires.2020.10.043.
Domènech-Abella J, Lara E, Rubio-Valera M, Olaya B, Moneta MV, Rico-Uribe LA. et al. (2017). Loneliness and depression in the elderly: the role of social network. Soc Psychiatry Psy-chiatr Epidemiol. 52(4): 381-390. https://doi.org/10.1007/s00127-017-1339-3. PMID: 28154893.
Generaal E, Hoogendijk EO, Stam M, Henke CE, Rutters F, Oosterman M. et al. (2019). Neighbourhood charac-teristics and prevalence and severity of depression: pooled analysis of eight Dutch cohort studies. Br J Psychiatry. 215(2): 468-475. https://doi.org/10-.1192/bjp.2019.100.
Gianfredi V, Beran M, Koster A, Eussen SJ, Odone A, Signorelli C. et al. (2021). Association between social network characteristics and prevalent and incident depression: The Maastricht Study. J Affect Disord. 293: 338-346. https://doi.org/10.1016/j.jad.2021.06.046.5. PMID: 34229287.
Hall BJ, Lam AIF, Wu TL, Hou WK, Latkin C, Galea S (2017). The epidemiology of current depression in Macau, China: towards a plan for mental health action. Soc Psychiatry Psychiatr Epidemiol. 52: 1227-1235. https://doi.org/10.1007/s00127-017-1415-8.
Han KM, Han C, Shin C, Jee HJ, An H, Yoon HK. et al. (2018). Social capital, socioeconomic status, and depression in community-living elderly. J Psy-chiatr Res. 98: 133-140. https://doi.-org/10.1016/j.jpsychires.2018.01.002
Li JB, Yang A, Dou K, Wang LX, Zhang MC, Lin XQ (2020). Chinese public’s knowledge, perceived severity, and perceived controllability of COVID-19 and their associations with emotional and behavioural reactions, social participation, and precautionary behaviour: A national survey. BMC Public Health. 20(1):1589. https://-doi.org/10.1186/s12889-020-09695-1.
Li Q, Zhou X, Ma S, Jiang M, Li L. (2017). The effect of migration on social capital and depression among older adults in China. Soc Psychiatry Psy-chiatr Epidemiol. 52: 1513-1522. https://doi.org/10.1007%2Fs00127-017-1439-0.
Lin YH, Han DS, Lee YH, Chan DC, Chang CH, Yang KC. et al. (2023). Social network associated with depressed mood and sarcopenia among older adults in Taiwan. J Formos Med Assoc. https://doi.org/10.1016/j.jfm-a.2023.11.004
Liu C, Zhou S, Bai X (2022). Intergenera-tional relationship quality, sense of loneliness, and attitude toward later life among aging Chinese adults in Hong Kong. Front Psychol. 13: 930-857. https://doi.org/10.3389%2Ffps-yg.2022.930857
Lu Y, Luo S, Liu X. (2021). Development of social support networks by patients with depression through online health communities: social network analysis. JMIR Medical Informatics. 9(1): 24618. https://doi.org/10.2196%2F2-4618.
Murayama H, Nofuji Y, Matsuo E, Nishi M, Taniguchi Y, Fujiwara Y. et al. (2015). Are neighborhood bonding and brid-ging social capital protective against depressive mood in old age? A multi-level analysis in Japan. Soc Sci Med. 124: 171-179. https://doi.org/10.10-16/j.socscimed.2014.11.042
Qu X, Qi X, Wu B, Yu J, Zhang H (2023). Perceived social cohesion and depressive symptoms among internal migrants in China: The mediating role of social adaptation. Front Public Health. 11: 1-11. https://doi.org/10.3-389%2Ffpubh.2023.1096318
Saito M, Kondo N, Aida J (2017). Develop-ment of an instrument for commu-nity-level health related social capital among Japanese older people: the JAGES Project. J Epidemiol. 27(5): 221–227. https://doi.org/10.1016/j.-je.2016.06.005
Santini Z, Koyanagi, A, Tyrovolas, S, Haro JM (2015). The association of rela-tionship quality and social networks with depression, anxiety, and suicidal ideation among older married adults: Findings from a cross-sectional analy-sis of the irish longitudinal study on ageing. J Affect Disord. 179: 134-141. https://doi.org/10.1016/j.jad.2015.03.015
Sun J, Xiao T, Lyu S, Zhao R (2020). The relationship between social capital and depressive symptoms among the elderly in China: the mediating role of life satisfaction. Risk Manag Health Policy. 13: 205-213. https://doi.org/-10.2147%2FRMHP.S247355
Van Zutphen EM, Kok AA, Rijnhart JJ, Rhebergen D, Huisman, M, Beekman A (2021). An examination of reciprocal effects between cardiovascular morbidity, depressive symptoms and loneliness over time in a longitudinal cohort of dutch older adults. J Affect Disord. 288: 122-128. https://doi.org/-10.1016/j.jad.2021.03.081
Wang G, Duan Kan Q, Zhou Y, Cheng Z, Tang S (2023). The correlation analy-sis of WeChat usage and depression among the middle-aged and elderly in China: the mediating role of social participation. BMC Public Health. 23(1): 462. https://doi.org/10.1186%-2Fs12889-023-15349-9.
Wang J, Luo N, Sun Y, Bai R, Li X, Liu L. et al. (2023). Exploring the reciprocal relationship between activities of daily living disability and depressive symp-toms among middle-aged and older Chinese people: a four-wave, cross-lagged model. BMC Public Health. 23(1): 1-9. http://dx.doi.org/10.1186-/s12889-023-16100-0.
Wang R, Liu Y, Xue D, Yao Y, Liu P, Helbich M (2019). Cross-sectional associations between long-term exposure to particulate matter and depression in China: the mediating effects of sunlight, physical activity, and neigh-borly reciprocity. J Affect Disord. 249: 8-14. https://doi.org/10.1016/j.jad.2-019.02.007
WHO (2022). World Health Organization Depression Elderly. Available at: https://www.who.int/news-room/-fact-sheets/detail/mental-health-of-older-adults
Xin Y, Ren X (2020). Social capital as a mediator through the effect of edu-cation on depression and obesity among the elderly in China. Int J Environ Res Public Health. 17(11): 3977. https://doi.org/10.3390/ijerph-17113977
Zhao H, Wang X, Shi, Y. (2023). The effect of hearing impairment and social participation on depressive symptoms in older adults: a cross-lagged analy-sis. Front Syst Neurosci. 17: 1240587. https://doi.org/10.3389%2Ffncom.2023.1240587.
Zhou S, Li K, Ogihara A, Wang X. (2022). Association between social capital and depression among older adults of different genders: Evidence from Hangzhou China. Front Public Health. 10: 863574. https://doi.org/-10.3389%2Ffpubh.2022.863574.
