This study aimed to determine how modifiable risk factors, such as physical exercise and social support, and non-modifiable risk factors, such as genetic risk may affect cognitive function over time in older adults. As well, the study explored how changes in modifiable risk factors (i.e., increase in exercise) may affect cognitive function over time. This research question was shaped with the help of a patient partner team.

The study used UK Biobank data, and patient partners were involved in shaping research questions/goals. The UK Biobank study had participants complete comprehensive baseline assessments (2006-2010), with subgroups also completing repeat assessments (2012-2013), imaging assessments (2014-ongoing) and/or repeat imaging assessments (2019-ongoing; i.e., 2-4 data points per participant). Age, sex, education, ethnicity, and apolipoprotein E (APOE) e4 status (at least one e4 allele present) data were collected at baseline. Employment, physical activity, social support, and recent depressive symptom data were collected across timepoints. A Fluid intelligence score was obtained at each timepoint via a series of thirteen 1-pt. reasoning tasks (range: 0-13). Participants who did not complete cognitive testing at baseline and at least one other time point, and those with neurological conditions or events (e.g., stroke, epilepsy, dementia) were excluded (final N=17,409).

Multi-Level Modeling (with Maximum Likelihood) was utilized, with fluid intelligence as the primary outcome measure. We ran Model 1: fully unconditioned, Model 2: with time predictor in years (baseline= 0), and Model 3: with baseline physical activity, social support and APOE e-4 predictors and covariates (mean-centered as appropriate), time-varying physical activity and social support predictors, and interaction terms. Nonsignificant interaction terms were trimmed from Model 3 to facilitate interpretation.

Model 1 was significant (p<.001) with an intraclass correlation (ICC) of 0.64, suggesting that 64% of the total variance in fluid intelligence in this sample is due to interindividual differences. Model 2 revealed that the average fluid intelligence score at baseline mean age (55.85) was 6.79 and significantly decreased with each year increase since baseline. Results from Model 3 (trimmed) revealed that being male, white, and having at least a university degree were associated with higher score at baseline, while being older and having more recent depressive symptoms were associated with lower scores. Higher social support quality was associated with higher scores while higher social support quantity was associated with lower scores at baseline; however, higher social support quantity at baseline was associated with less decline in scores over time. Surprisingly, having at least one e4 allele was associated with higher scores. Engaging in more moderate physical activity was associated with lower scores at baseline, however, individuals who increased the length of their moderate physical activity sessions over time showed higher timepoint-specific fluid intelligence scores. Additional significant interactions will be elaborated.

Results suggest that increases in the length of moderate physical activity exercise sessions were associated with better cognitive function over time. Having better social support quality was also associated with better cognitive function, while higher social support quantity was associated with less cognitive decline over time. These findings suggest that positive lifestyle changes in older adulthood may slow cognitive decline.