Social isolation from childhood to mid-adulthood: is there an association with older brain age?

Brain age cognitive decline life course social isolation

Journal

Psychological medicine
ISSN: 1469-8978
Titre abrégé: Psychol Med
Pays: England
ID NLM: 1254142

Informations de publication

Date de publication:
24 Jul 2023
Historique:
medline: 24 7 2023
pubmed: 24 7 2023
entrez: 24 7 2023
Statut: aheadofprint

Résumé

Older brain age - as estimated from structural MRI data - is known to be associated with detrimental mental and physical health outcomes in older adults. Social isolation, which has similar detrimental effects on health, may be associated with accelerated brain aging though little is known about how different trajectories of social isolation across the life course moderate this association. We examined the associations between social isolation trajectories from age 5 to age 38 and brain age assessed at age 45. We previously created a typology of social isolation based on onset during the life course and persistence into adulthood, using group-based trajectory analysis of longitudinal data from a New Zealand birth cohort. The typology comprises four groups: 'never-isolated', 'adult-only', 'child-only', and persistent 'child-adult' isolation. A brain age gap estimate (brainAGE) - the difference between predicted age from structural MRI date and chronological age - was derived at age 45. We undertook analyses of brainAGE with trajectory group as the predictor, adjusting for sex, family socio-economic status, and a range of familial and child-behavioral factors. Older brain age in mid-adulthood was associated with trajectories of social isolation after adjustment for family and child confounders, particularly for the 'adult-only' group compared to the 'never-isolated' group. Although our findings are associational, they indicate that preventing social isolation, particularly in mid-adulthood, may help to avert accelerated brain aging associated with negative health outcomes later in life.

Sections du résumé

BACKGROUND BACKGROUND
Older brain age - as estimated from structural MRI data - is known to be associated with detrimental mental and physical health outcomes in older adults. Social isolation, which has similar detrimental effects on health, may be associated with accelerated brain aging though little is known about how different trajectories of social isolation across the life course moderate this association. We examined the associations between social isolation trajectories from age 5 to age 38 and brain age assessed at age 45.
METHODS METHODS
We previously created a typology of social isolation based on onset during the life course and persistence into adulthood, using group-based trajectory analysis of longitudinal data from a New Zealand birth cohort. The typology comprises four groups: 'never-isolated', 'adult-only', 'child-only', and persistent 'child-adult' isolation. A brain age gap estimate (brainAGE) - the difference between predicted age from structural MRI date and chronological age - was derived at age 45. We undertook analyses of brainAGE with trajectory group as the predictor, adjusting for sex, family socio-economic status, and a range of familial and child-behavioral factors.
RESULTS RESULTS
Older brain age in mid-adulthood was associated with trajectories of social isolation after adjustment for family and child confounders, particularly for the 'adult-only' group compared to the 'never-isolated' group.
CONCLUSIONS CONCLUSIONS
Although our findings are associational, they indicate that preventing social isolation, particularly in mid-adulthood, may help to avert accelerated brain aging associated with negative health outcomes later in life.

Identifiants

pubmed: 37485695
doi: 10.1017/S0033291723001964
pii: S0033291723001964
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-9

Subventions

Organisme : Medical Research Council
ID : MR/P005918/1
Pays : United Kingdom
Organisme : NIA NIH HHS
ID : R01AG049789
Pays : United States

Auteurs

Roy Lay-Yee (R)

Centre of Methods and Policy Application in the Social Sciences, and School of Social Sciences, Faculty of Arts, University of Auckland, Auckland, New Zealand.

Ahmad R Hariri (AR)

Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.

Annchen R Knodt (AR)

Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.

Ashleigh Barrett-Young (A)

Department of Psychology, University of Otago, Dunedin, New Zealand.

Timothy Matthews (T)

Department of Social Genetic & Developmental Psychiatry, Institute of Psychiatry, King's College London, London, UK.

Barry J Milne (BJ)

Centre of Methods and Policy Application in the Social Sciences, and School of Social Sciences, Faculty of Arts, University of Auckland, Auckland, New Zealand.
Department of Statistics, Faculty of Science, University of Auckland, Auckland, New Zealand.

Classifications MeSH