Distinct components of cardiovascular health are linked with age-related differences in cognitive abilities

Abstract

Cardiovascular ageing contributes to cognitive impairment. However, the unique and synergistic contributions of multiple cardiovascular factors to cognitive function remain unclear because they are often condensed into a single composite score or examined in isolation. We hypothesized that vascular risk factors, electrocardiographic features and blood pressure indices reveal multiple latent vascular factors, with independent contributions to cognition. In a population-based deep-phenotyping study (n = 708, age 18-88), path analysis revealed three latent vascular factors dissociating the autonomic nervous system response from two components of blood pressure. These three factors made unique and additive contributions to the variability in crystallized and fluid intelligence. The discrepancy in fluid relative to crystallized intelligence, indicative of cognitive decline, was associated with a latent vascular factor predominantly expressing pulse pressure. This suggests that higher pulse pressure is associated with cognitive decline from expected performance. The effect was stronger in older adults. Controlling pulse pressure may help to preserve cognition, particularly in older adults. Our findings highlight the need to better understand the multifactorial nature of vascular aging.

Figure 1

Schematic representation of the data processing and analysis pipeline to investigate shared and unique relationships between vascular and cognitive factors in the Cam-CAN dataset (n = 708). BMI body mass index, BP total blood pressure (systolic + diastolic), dia diastolic, Cattell 1–4 sub-scores across the four Cattell tasks, CFA confirmatory factor analysis, Discrepancy, the ability discrepancy, defined as LCF2 (crystallized) minus LCF1 (fluid), ECG electrocardiogram, EFA exploratory factor analysis, HR heart rate, HRV HF heart rate variability at high frequency, HRV LF heart rate variability at low frequency, LCF latent cognitive factor, LVF latent vascular factor, PP pulse pressure (systolic − diastolic), sys systolic, STW spot the word.

Figure 2

A The three-factor Exploratory Factor Analysis model of vascular health. The numeric values of cross-loadings < 0.30 (dashed grey arrows) are omitted here for visual clarity and reported fully in Supplementary Table 5. B The two-factor Confirmatory Factor Analysis model of cognition. BMI body mass index, BP total blood pressure, HR heart rate, HRV HF heart rate variability at high frequency, HRV LF heart rate variability at low frequency, LCF latent cognitive factor, LVF latent vascular factor, PP pulse pressure, STW spot the word.

Figure 3

Scatter plots (lower left), distributions (leading diagonal) and Pearson correlations (upper right) for latent vascular factors, ability discrepancy and age. Scatter plots show linear associations (blue) and data intensity (greyscale). Stars indicate increasing significance on the correlations: ***, p < 0.001; **, p < 0.01; *, p < 0.05. Corr correlation coefficient, Discrepancy ability discrepancy, LVF1-3 latent vascular factors 1–3.

Figure 4

A visualisation of the effect of latent vascular factor 2, expressing predominantly pulse pressure, on the ability discrepancy for complete case data (n = 655). Note that age was a continuous variable for the interaction tested, but here participants are plotted as discrete groups of young (18–37 years, n = 154), middle (38–67 years, n = 307) and old (68–88 years, n = 194) for visualisation purposes only. LVF2 latent vascular factor 2.