Multisystem Trajectories Over the Adult Life Course and Relations to Cardiovascular Disease and Death

Abstract

<div>Background</div><p>Comprehensive conjoint characterization of long-term trajectories representing several biological systems is lacking.</p><div>Methods</div><p>We measured serially indicators representing 14 distinct biological systems in up to 3,453 participants attending four Framingham Study examinations: bone mineral density, body mass index (BMI), C-reactive protein, glomerular filtration rate, forced vital capacity (FVC), 1 second forced expiratory volume/FVC ratio (FEV1/FVC), gait speed, grip strength, glycosylated hemoglobin (HbA1c), heart rate, left ventricular mass, Mini-Mental State Examination (MMSE), pulse pressure, and total/high-density lipoprotein cholesterol ratio (TC/HDL).</p><div>Results</div><p>We observed that correlations among the 14 sex-specific trajectories were modest (<em>r</em> < .30 for 169 of 182 sex-specific correlations). During follow-up (median 8 years), 232 individuals experienced a cardiovascular disease (CVD) event and 393 participants died. In multivariable regression models, CVD incidence was positively related to trajectories of BMI, HbA1c, TC/HDL, gait time, and pulse pressure (<em>p</em> < .06); mortality risk was related directly to trajectories of gait time, C-reactive protein, heart rate, and pulse pressure but inversely to MMSE and FEV1/FVC (<em>p</em> < .006). A unit increase in the trajectory risk score was associated with a 2.80-fold risk of CVD (95% confidence interval [CI], 2.04–3.84; <em>p</em> < .001) and a 2.71-fold risk of death (95% CI, 2.30–3.20; <em>p</em> < .001). Trajectory risk scores were suggestive of a greater increase in model <em>c</em>-statistic compared with single occasion measures (delta-<em>c</em> compared with age- and sex-adjusted models: .032 vs .026 for CVD; .042 vs .030 for mortality).</p><div>Conclusions</div><p>Biological systems age differentially over the life course. Longitudinal data on a parsimonious set of biomarkers reflecting key biological systems may facilitate identification of high-risk individuals.</p>