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1.	Demnitz, Naiara, et al. (författare) Characterising the covariance pattern between lifestyle factors and structural brain measures : a multivariable replication study of two independent ageing cohorts 2023 Ingår i: Neurobiology of Aging. - : Elsevier. - 0197-4580 .- 1558-1497. ; 131, s. 115-123 Tidskriftsartikel (refereegranskat)abstract Modifiable lifestyle factors have been shown to promote healthy brain ageing. However, studies have typically focused on a single factor at a time. Given that lifestyle factors do not occur in isolation, multivariable analyses provide a more realistic model of the lifestyle-brain relationship. Here, canonical correlation analyses (CCA) examined the relationship between nine lifestyle factors and seven MRI-derived indices of brain structure. The resulting covariance pattern was further explored with Bayesian regressions. CCA analyses were first conducted on a Danish cohort of older adults (n = 251) and then replicated in a British cohort (n = 668). In both cohorts, the latent factors of lifestyle and brain structure were positively correlated (UK: r =.37, p < 0.001; Denmark: r =.27, p < 0.001). In the cross-validation study, the correlation between lifestyle-brain latent factors was r =.10, p = 0.008. However, the pattern of associations differed between datasets. These findings suggest that baseline characterisation and tailoring towards the study sample may be beneficial for achieving targeted lifestyle interventions.

Demnitz, Naiara, et al. (författare)
Characterising the covariance pattern between lifestyle factors and structural brain measures : a multivariable replication study of two independent ageing cohorts
2023
Ingår i: Neurobiology of Aging. - : Elsevier. - 0197-4580 .- 1558-1497. ; 131, s. 115-123
Tidskriftsartikel (refereegranskat)abstract
- Modifiable lifestyle factors have been shown to promote healthy brain ageing. However, studies have typically focused on a single factor at a time. Given that lifestyle factors do not occur in isolation, multivariable analyses provide a more realistic model of the lifestyle-brain relationship. Here, canonical correlation analyses (CCA) examined the relationship between nine lifestyle factors and seven MRI-derived indices of brain structure. The resulting covariance pattern was further explored with Bayesian regressions. CCA analyses were first conducted on a Danish cohort of older adults (n = 251) and then replicated in a British cohort (n = 668). In both cohorts, the latent factors of lifestyle and brain structure were positively correlated (UK: r =.37, p < 0.001; Denmark: r =.27, p < 0.001). In the cross-validation study, the correlation between lifestyle-brain latent factors was r =.10, p = 0.008. However, the pattern of associations differed between datasets. These findings suggest that baseline characterisation and tailoring towards the study sample may be beneficial for achieving targeted lifestyle interventions.

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