01 May 2019
DR ANNE-NICOLE CASEY
How people interact with and perceive one another, and each person’s thoughts and feelings about the quality of those interactions and relationships, can affect physical and mental health and well-being. Social cognitive function, which broadly refers to the way our brain processes social information, is recognised as an important marker of how efficiently our brain processes information in general1. Interestingly, the number of individuals with whom a person interacts frequently is associated with their short-term memory capacity2. Some studies report that having larger social networks protects against cognitive decline in older adults3 while others suggest, conversely, that declining cognition and function cause a person’s social network to decrease in size4. Neuroimaging studies indicate that larger social networks are associated with greater volume in specific areas of the brain 5,6. People with Alzheimer’s disease pathology who have larger social networks are better able to briefly hold and process thoughts (working memory) and to remember more ‘common knowledge’ (semantic memory) than are people with similar Alzheimer’s disease pathology who have smaller social networks7. However, the relationships between social lifestyle factors and Alzheimer’s disease pathology, and the precise role of social networks in promoting brain resilience, are not fully understood8.
My role as a postdoctoral research associate with the Centre for Healthy Brain Ageing (CHeBA) is to conduct and collaborate on studies that address questions about the role that social engagement plays in dementia risk, and what individuals and the community can do to promote healthy brain ageing. Our team at CHeBA are addressing these questions through systematic review and analysis of the literature on social engagement and dementia; and by analysing data from the Sydney Memory and Ageing (MAS) study to examine associations between cognition and social network size, social engagement and health-related quality of life.
In recent research led by 5th Year UNSW Doctor of Medicine candidate Ross Penninkilampi, we updated a systematic review of research studies that examined the association between social engagement or loneliness and dementia risk9. We selected 33 studies that met specific criteria and conducted meta-analyses to examine what associations might exist when all of the data from these 33 studies – representing 2,370, 452 participants – were pooled together. Results indicated that markers of poor social engagement, including living alone, having a limited social network, infrequent social contact and inadequate social support, all increased dementia risk. Results also indicated that the risk of dementia increased when poor social engagement was coupled with depression. While loneliness did not appear to increase dementia risk, that analysis included only four studies and renders this finding as inconclusive. When we looked specifically at studies that had followed their participants for 10 or more years, good social engagement was modestly protective against dementia.
Results indicated that markers of poor social engagement, including living alone, having a limited social network, infrequent social contact and inadequate social support, all increased dementia risk.
Previous research has reported that the strength of the association between poor social interaction (low social participation, less contact, more loneliness) and dementia is comparable to that of other well-known risk factors including depression, low physical activity, and low level of education10. Our findings indicate that poor social engagement – or social disengagement – is a risk factor for dementia, that people who are both depressed and socially isolated may be more vulnerable, and that dementia prevention strategies should include interventions that target social isolation and provide support for people lacking social engagement. (And the great thing about psychosocial interventions is that they can take place just about anywhere, and they don’t involve invasive procedures or medication!)
In a recent collaboration with Dr Nicole Kochan, Professor Perminder Sachdev and Professor Henry Brodaty, we presented results of research examining associations between demographic characteristics, depression and social network characteristics from MAS baseline (wave 1) data. Results indicated that a person’s age, how many years of education they had, their scores on a measure of depression and the number of face-to-face contacts that they had with friends and family per month predicted differences in their cognitive function. When compared with the people who reported what might be considered an average or above average number of face-to-face contacts (approximately 11 or more per month), the people who reported fewer than five regular face-to-face contacts per month scored lower in tests of Attention / Processing Speed, and Language and Global Cognition. Very few people said that they didn’t have any face-to-face contacts. However, those that did showed lower ability to coordinate goal-oriented behaviour and thought processes (Executive function). These findings suggest that the type, frequency and number of social relationships should be considered in predictive models of cognitive function for older adults. Thus, we are now using longitudinal MAS data from waves 1 through 4 and collaborating with Dr Zhixin Liu from UNSW Stats Central to investigate predictive models of cognitive function that include measures of social network size/engagement and other modifiable lifestyle variables including mental and physical activity. Clarifying the contribution that social networks and other modifiable lifestyle variables make toward maintaining cognitive function will help to inform clinical guidelines and interventions that promote healthy brain ageing.
Dr Anne-Nicole Casey is a Postdoctoral Research Associate at the Centre for Healthy Brain Ageing (CHeBA), UNSW Sydney. Her research is wholly supported by the Thomas Foundation.
- Henry JD, von Hippel W, Molenberghs P, Lee T, Sachdev PS. Clinical assessment of social cognitive function in neurological disorders. Nat Rev Neurol. 2016;12(1):28-39.
- Stiller J, Dunbar RIM. Perspective-taking and memory capacity predict social network size. Social Networks. 2007;29(1):93-104.
- Zunzunegui M-V, Alvarado BE, Del Ser T, Otero A. Social networks, social integration, and social engagement determine cognitive decline in community-dwelling Spanish older adults. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences. 2003;58(2):S93-S100.
- Green AF, Rebok G, Lyketsos CG. Influence of social network characteristics on cognition and functional status with aging. International journal of geriatric psychiatry. 2008;23(9):972-978.
- Kanai R, Bahrami B, Roylance R, Rees G. Online social network size is reflected in human brain structure. Proceedings of the Royal Society B: Biological Sciences. 2012;279(1732):1327-1334.
- Molesworth T, Sheu LK, Cohen S, Gianaros PJ, Verstynen TD. Social network diversity and white matter microstructural integrity in humans. Social Cognitive and Affective Neuroscience. 2015;10(9):1169-1176.
- Bennett DA, Schneider JA, Tang Y, Arnold SE, Wilson RS. The effect of social networks on the relation between Alzheimer's disease pathology and level of cognitive function in old people: A longitudinal cohort study. The Lancet Neurology. 2006;5(5):406-412.
- Bennett DA, Arnold SE, Valenzuela MJ, Brayne C, Schneider JA. Cognitive and social lifestyle: Links with neuropathology and cognition in late life. Acta neuropathologica. 2014;127(1):137-150.
- Penninkilampi R, Casey A, Singh M, Brodaty H. The association between social engagement, loneliness, and risk of dementia: a systematic review and meta-analysis. Journal of Alzheimer's Disease. 2018;66(4):1619-1633.
- Kuiper JS, Zuidersma M, Oude Voshaar RC, et al. Social relationships and risk of dementia: A systematic review and meta-analysis of longitudinal cohort studies. Ageing Research Reviews. 2015;22:39-57.