Within-individual variability of repeatedly-measured exposures may predict later outcomes: e.g. blood pressure (BP) variability (BPV) is an independent cardiovascular risk factor above and beyond mean BP. Since two-stage methods, known to introduce bias, are typically used to investigate such associations, we introduce a joint modelling approach, examining associations of mean BP and BPV across childhood to left ventricular mass (indexed to height; LVMI) in early adulthood with data from the UK’s Avon Longitudinal Study of Parents and Children cohort. Using multilevel models, we allow BPV to vary between individuals (a “random effect”) as well as to depend on covariates (allowing for heteroscedasticity). We further distinguish within-clinic variability (“measurement error”) from visit-to-visit BPV. BPV was predicted to be greater at older ages, at higher bodyweights, and in females, and was positively correlated with mean BP. BPV had a weak positive association with LVMI (10% increase in within-individual BP variance was predicted to increase LVMI by 0.21% (95% credible interval: -0.23%, 0.69%)), but this association became negative (-0.78%, 95% credible interval: -2.54%, 0.22%)) once the effect of mean BP on LVMI was adjusted for. This joint modelling approach offers a flexible method of relating repeatedly-measured exposures to later outcomes.
|Journal||American Journal of Epidemiology|
|Publication status||Accepted/In press - 27 Apr 2020|
- SoE Centre for Multilevel Modelling
- Bayesian analysis
- blood pressure
- joint model
- left ventricular hypertrophy
- longitudinal studies
- young adult
Parker, R. M. A., Leckie, G., Goldstein, H., Howe, L. D., Heron, J., Hughes, A. D., Phillippo, D. M., & Tilling, K. (Accepted/In press). Joint modelling of individual trajectories, within-individual variability and a later outcome: systolic blood pressure through childhood and left ventricular mass in early adulthood. American Journal of Epidemiology.