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

Teemu J. Niiranen, Danielle M. Enserro, Martin G. Larson, Ramachandran S. Vasan

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Background: Comprehensive conjoint characterization of long-term trajectories representing several biological systems is lacking. Methods: 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). Results: We observed that correlations among the 14 sex-specific trajectories were modest (r <. 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 (p <. 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 (p <. 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; p <. 001) and a 2.71-fold risk of death (95% CI, 2.30-3.20; p <. 001). Trajectory risk scores were suggestive of a greater increase in model c-statistic compared with single occasion measures (delta-c compared with age- and sex-adjusted models:. 032 vs. 026 for CVD;. 042 vs. 030 for mortality). Conclusions: 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.

Original languageEnglish (US)
Pages (from-to)1778-1785
Number of pages8
JournalJournals of Gerontology - Series A Biological Sciences and Medical Sciences
Volume74
Issue number11
DOIs
StatePublished - Oct 4 2019
Externally publishedYes

Keywords

  • Aging
  • Cardiovascular disease
  • Epidemiology
  • Trajectories

ASJC Scopus subject areas

  • Aging
  • Geriatrics and Gerontology

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