Investigation of Age-Associated Cognitive Functional Homophily in Community-Dwelling Older Adults’ Confidant Social Networks Using Exponential Random Graph Model
Abstract
:1. Introduction
2. Materials and Methods
2.1. Participants
2.2. Aging-Related Cognitive Function
2.3. Confidant Social Network
2.4. Demographics
2.5. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Leigh-Hunt, N.; Bagguley, D.; Bash, K.; Turner, V.; Turnbull, S.; Valtorta, N.; Caan, W. An overview of systematic reviews on the public health consequences of social isolation and loneliness. Public Health 2017, 152, 157–171. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mehrabi, F.; Beland, F. Effects of social isolation, loneliness and frailty on health outcomes and their possible mediators and moderators in community-dwelling older adults: A scoping review. Arch. Gerontol. Geriat. 2020, 90, 104119. [Google Scholar] [CrossRef] [PubMed]
- Tsuji, T.; Saito, M.; Ikeda, T.; Aida, J.; Cable, N.; Koyama, S.; Noguchi, T.; Osaka, K.; Kondo, K. Change in the prevalence of social isolation among the older population from 2010 to 2016: A repeated cross-sectional comparative study of Japan and England. Arch. Gerontol. Geriatr. 2020, 91, 104237. [Google Scholar] [CrossRef] [PubMed]
- Surkalim, D.L.; Luo, M.; Eres, R.; Gebel, K.; Van Buskirk, J.; Bauman, A.; Ding, D. The prevalence of loneliness across 113 countries: Systematic review and meta-analysis. BMJ 2022, 376, e067068. [Google Scholar] [CrossRef] [PubMed]
- Wrzus, C.; Hänel, M.; Wagner, J.; Neyer, F.J. Social network changes and life events across the life span: A meta-analysis. Psychol. Bull. 2013, 139, 53–80. [Google Scholar] [CrossRef]
- Courtin, E.; Knapp, M. Social isolation, loneliness and health in old age: A scoping review. Health Soc. Care Community 2017, 25, 799–812. [Google Scholar] [CrossRef]
- Gardiner, C.; Geldenhuys, G.; Gott, M. Interventions to reduce social isolation and loneliness among older people: An integrative review. Health Soc. Care Community 2018, 26, 147–157. [Google Scholar] [CrossRef]
- Freedman, A.; Nicolle, J. Social isolationand lonelines: The new geriatric giants: Approach for primary care. Can. Fam. Physician 2020, 66, 176–182. [Google Scholar]
- McPherson, M.; Smith-Lovin, L.; Cook, J.M. Birds of a Feather: Homophily in Social Networks. Annu. Rev. Sociol. 2001, 27, 415–444. [Google Scholar] [CrossRef] [Green Version]
- Morse, C.K. Does variability increase with age? An archival study of cognitive measures. Psychol. Aging 1993, 8, 156–164. [Google Scholar] [CrossRef]
- Boutwell, B.B.; Meldrum, R.C.; Petkovsek, M.A. General intelligence in friendship selection: A study of preadolescent best friend dyads. Intelligence 2017, 64, 30–35. [Google Scholar] [CrossRef]
- Burgess, S.; Sanderson, E.; Umana-Aponte, M. School ties: An analysis of homophily in an adolescent friendship network. In The Centre for Market and Public Organisation 11/267; University of Bristol: Bristol, UK, 2011. [Google Scholar]
- Meldrum, R.C.; Young, J.; KAvish, N.; Boutwell, B. Could peers influence intelligence during adolescence? An exploratory study. Intelligence 2019, 72, 28–34. [Google Scholar] [CrossRef] [Green Version]
- Sacerdote, B. Peer Effects with Random Assignment: Results for Dartmouth Roommates. Q. J. Econ. 2001, 116, 681–704. [Google Scholar] [CrossRef] [Green Version]
- Mascie-Taylor, C.G.N. Spouse similarity for IQ and personality and convergence. Behav. Genet. 1989, 19, 223–227. [Google Scholar] [CrossRef]
- Vinkhuyzen, A.A.; Van Der Sluis, S.; Maes, H.H.M.; Posthuma, D. Reconsidering the Heritability of Intelligence in Adulthood: Taking Assortative Mating and Cultural Transmission into Account. Behav. Genet. 2011, 42, 187–198. [Google Scholar] [CrossRef] [Green Version]
- Plomin, R.; Deary, I.J. Genetics and intelligence differences: Five special findings. Mol. Psychiatry 2015, 20, 98–108. [Google Scholar] [CrossRef] [Green Version]
- Siciliano, M.D. Advice Networks in Public Organizations: The Role of Structure, Internal Competition, and Individual Attributes. Public Adm. Rev. 2015, 75, 548–559. [Google Scholar] [CrossRef]
- Van der Pol, J. Introduction to Network Modeling Using Exponential Random Graph Models (ERGM): Theory and an Application Using R-Project. Comput. Econ. 2019, 54, 845–875. [Google Scholar] [CrossRef]
- Japanese Cabinet Office. Annual Report on the Ageing Society [Summary] FY2021; Cabinet Office: Tokyo, Japan, 2021; pp. 1–14. [Google Scholar]
- Asada, T. Prevalence of dementia in Japan: Past, present and future. Rinsho Shinkeigaku 2012, 52, 962–964. [Google Scholar] [CrossRef] [Green Version]
- Wakuya City. Wakuya-Cho Koureisya Fukushi Keikaku Dainanaki Kaigohoken Zigyou Keikaku; Gyousei: Wakuya, Japan, 2018; pp. 1–83. (In Japanese) [Google Scholar]
- Morita, A.; O’Caoimh, R.; Murayama, H.; Molloy, D.W.; Inoue, S.; Shobugawa, Y.; Fujiwara, T. Validity of the Japanese Version of the Quick Mild Cognitive Impairment Screen. Int. J. Environ. Res. Public Health 2019, 16, 917. [Google Scholar] [CrossRef] [Green Version]
- O’Caoimh, R.; Gao, Y.; Gallagher, P.F.; Eustace, J.; McGlade, C.; Molloy, D.W. Which part of the Quick mild cognitive impairment screen (Qmci) discriminates between normal cognition, mild cognitive impairment and dementia? Age Ageing 2013, 42, 324–330. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fujiwara, Y.; Shinkai, S.; Kumagai, S.; Amano, H.; Yoshida, Y.; Yoshida, H.; Kim, H.; Suzuki, T.; Ishizaki, T.; Watanabe, S.; et al. Changes in TMIG-Index of Competence by subscale in Japanese urban and rural community older populations: Six years prospective study. Geriatr. Gerontol. Int. 2003, 3, S63–S68. [Google Scholar] [CrossRef]
- Fit, Simulate and Diagnose Exponential-Family Models for Networks. Available online: www.cran.r-project.org/web/packages/ergm/ergm.pdf (accessed on 10 March 2022).
- Suzuki, T. 7.5 Exponential Random Graph Model. In Network Analysis; Kyoritsu Publisher: Tokyo, Japan, 2018; pp. 175–203. (In Japanese) [Google Scholar]
- Flatt, J.D.; Agimi, Y.; Albert, S.M. Homophily and Health Behavior in Social Networks of Older Adults. Fam. Community Health 2012, 35, 312–321. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ossher, L.; Flegal, K.E.; Lustig, C. Everyday memory errors in older adults. Aging Neuropsychol. Cogn. 2013, 20, 220–242. [Google Scholar] [CrossRef] [Green Version]
- Gow, A.J.; Corley, J.; Starr, J.M.; Deary, I.J. Reverse causation in activity-cognitive ability associations: The Lothian Birth Cohort 1936. Psychol. Aging 2012, 27, 250–255. [Google Scholar] [CrossRef]
- Stoykova, R.; Matharan, F.; Dartigues, J.-F.; Amieva, H. Impact of social network on cognitive performances and age-related cognitive decline across a 20-year follow-up. Int. Psychogeriatr. 2011, 23, 1405–1412. [Google Scholar] [CrossRef]
- Christakis, N.A.; Fowler, J.H. The Spread of Obesity in a Large Social Network over 32 Years. N. Engl. J. Med. 2007, 357, 370–379. [Google Scholar] [CrossRef] [Green Version]
- Rosenquist, J.N.; Fowler, J.H.; Christakis, N.A. Social network determinants of depression. Mol. Psychiatry 2010, 16, 273–281. [Google Scholar] [CrossRef] [Green Version]
- Christakis, N.A.; Fowler, J. The Collective Dynamics of Smoking in a Large Social Network. N. Engl. J. Med. 2008, 358, 2249–2258. [Google Scholar] [CrossRef] [Green Version]
- Number of Senior Clubs and Members According to Prefectures and Cities in Japan. Available online: http://zenrouren.com/siryou/memberr03.html (accessed on 10 March 2022).
- Japanese Ministry of Health, Labor and Welfare. Overview of 2020 Survey on Long-Term Care Service Facilities and Providers; Japanese Ministry of Health, Labor and Welfare: Tokyo, Japan, 2021. (In Japanese) [Google Scholar]
- Heller, K.; Thompson, M.G.; Trueba, P.E.; Hogg, J.R.; Vlachos-Weber, I. Peer support telephone dyads for elderly women: Was this the wrong intervention? Am. J. Community Psychol. 1991, 19, 53–74. [Google Scholar] [CrossRef]
Variables | n | % | Mean (SD) |
---|---|---|---|
Age | 252 | 73.4 (6.1) | |
Sex | |||
Male | 113 | 44.8 | |
Female | 139 | 55.2 | |
Living arrangement (alone) | |||
Alone | 41 | 16.3 | |
With other | 211 | 83.7 | |
Educational attainment | |||
Junior high school or less | 60 | 23.8 | |
High school | 148 | 58.7 | |
College and above | 44 | 17.5 | |
Higher-level functional capacity | |||
No impairment | 139 | 55.2 | |
Disability present | 99 | 39.3 | |
Missing | 14 | 5.6 | |
Cognitive impairment | |||
Likely normal | 136 | 54.0 | |
Suspected mild cognitive impairment | 73 | 29.0 | |
Suspected dementia | 43 | 17.1 |
Variables | Adjusted OR | 95% CI | p-Value |
---|---|---|---|
Difference in educational attainment | |||
Same level | 1.00 | ||
One level of difference | 0.68 | (0.35, 1.29) | 0.24 |
Two levels of difference | 0.39 | (0.10, 1.47) | 0.17 |
Difference in age-associated cognitive function | |||
One score difference on orientation | 1.14 | (0.85, 1.53) | 0.37 |
One score difference on registration | 0.90 | (0.68, 1.18) | 0.41 |
One score difference on clock drawing | 1.01 | (0.94, 1.08) | 0.83 |
One score difference on delayed recall for words | 1.05 | (1.00, 1.11) | 0.075 |
One score difference on verbal fluency | 1.02 | (0.90, 1.15) | 0.76 |
One score difference on logical memory | 0.94 | (0.90, 0.99) | 0.029 |
Akaike Information Criterion = 847 | |||
Bayesian Information Criterion = 1019 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Morita, A.; Takahashi, Y.; Fujiwara, T. Investigation of Age-Associated Cognitive Functional Homophily in Community-Dwelling Older Adults’ Confidant Social Networks Using Exponential Random Graph Model. Int. J. Environ. Res. Public Health 2022, 19, 4574. https://doi.org/10.3390/ijerph19084574
Morita A, Takahashi Y, Fujiwara T. Investigation of Age-Associated Cognitive Functional Homophily in Community-Dwelling Older Adults’ Confidant Social Networks Using Exponential Random Graph Model. International Journal of Environmental Research and Public Health. 2022; 19(8):4574. https://doi.org/10.3390/ijerph19084574
Chicago/Turabian StyleMorita, Ayako, Yoshimitsu Takahashi, and Takeo Fujiwara. 2022. "Investigation of Age-Associated Cognitive Functional Homophily in Community-Dwelling Older Adults’ Confidant Social Networks Using Exponential Random Graph Model" International Journal of Environmental Research and Public Health 19, no. 8: 4574. https://doi.org/10.3390/ijerph19084574