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Metabolic Clusters and Outcomes in Older Adults: The Cardiovascular Health Study
Author(s) -
Mukamal Kenneth J.,
Siscovick David S.,
de Boer Ian H.,
Ix Joachim H.,
Kizer Jorge R.,
Djoussé Luc,
Fitzpatrick Annette L.,
Tracy Russell P.,
Boyko Edward J.,
Kahn Steven E.,
Arnold Alice M.
Publication year - 2018
Publication title -
journal of the american geriatrics society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.992
H-Index - 232
eISSN - 1532-5415
pISSN - 0002-8614
DOI - 10.1111/jgs.15205
Subject(s) - medicine , diabetes mellitus , albuminuria , population , endocrinology , insulin , type 2 diabetes , subclinical infection , cluster (spacecraft) , cohort , computer science , programming language , environmental health
Background/Objectives Few studies have the requisite phenotypic information to define metabolic patterns that may inform our understanding of the pathophysiology and consequences of diabetes in older adults. We sought to characterize clusters of older adults on the basis of shared metabolic features. Design Population‐based prospective cohort study. Setting Four U.S. Cardiovascular Health Study field centers. Participants Individuals aged 65 and older taking no glucose‐lowering agents (N = 2,231). Measurements K‐means cluster analysis of 11 metabolic parameters (fasting and postload serum glucose and plasma insulin, fasting C‐peptide, body mass index, C‐reactive protein ( CRP ), estimated glomerular filtration rate ( eGFR ), albuminuria, carboxymethyl lysine (an advanced glycation end‐product), procollagen III N‐terminal propeptide (a fibrotic marker)) and their associations with incident cardiovascular disease, diabetes, disability, and mortality over 8 to 14.5 years of follow‐up and with measures of subclinical cardiovascular disease. Results A 6‐cluster solution provided robust differentiation into distinct, identifiable clusters. Cluster A (n = 739) had the lowest glucose and insulin and highest eGFR and the lowest rates of all outcomes. Cluster B (n = 419) had high glucose and insulin and intermediate rates of most outcomes. Cluster C (n = 118) had the highest insulin. Cluster D (n = 129) had the highest glucose with much lower insulin. Cluster E (n = 314) had the lowest eGFR and highest albuminuria. Cluster F (n = 512) had the highest CRP . Rates of CVD , mortality, and subclinical atherosclerosis were highest in clusters C, D, and E and were similar to rates in participants with treated diabetes. Incidence of disability was highest in Cluster C. Conclusion Clustering according to metabolic parameters identifies distinct phenotypes that are strongly associated with clinical and functional outcomes, even at advanced age.