Longitudinal algorithms to estimate cardiorespiratory fitness: associations with nonfatal cardiovascular disease and disease-specific mortality

Artero, Enrique G., Jackson, Andrew S., Sui, Xuemei, Lee, Duck-chul, O'Connor, Daniel P., Lavie, Carl J., Church, Timothy S. and Blair, Steven N. (2014) Longitudinal algorithms to estimate cardiorespiratory fitness: associations with nonfatal cardiovascular disease and disease-specific mortality. Journal of the American College of Cardiology, 63 21: 2289-2296. doi:10.1016/j.jacc.2014.03.008

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Author Artero, Enrique G.
Jackson, Andrew S.
Sui, Xuemei
Lee, Duck-chul
O'Connor, Daniel P.
Lavie, Carl J.
Church, Timothy S.
Blair, Steven N.
Title Longitudinal algorithms to estimate cardiorespiratory fitness: associations with nonfatal cardiovascular disease and disease-specific mortality
Journal name Journal of the American College of Cardiology   Check publisher's open access policy
ISSN 1558-3597
0735-1097
Publication date 2014-06-03
Year available 2014
Sub-type Article (original research)
DOI 10.1016/j.jacc.2014.03.008
Open Access Status File (Author Post-print)
Volume 63
Issue 21
Start page 2289
End page 2296
Total pages 8
Place of publication San Diego, CA, United States
Publisher Elsevier
Language eng
Formatted abstract
Objectives
This study sought to determine the capacity of cardiorespiratory fitness (CRF) algorithms without exercise testing to predict the risk for nonfatal cardiovascular disease (CVD) events and disease-specific mortality.

Background
Cardiorespiratory fitness (CRF) is not routinely measured, as it requires trained personnel and specialized equipment.

Methods
Participants were 43,356 adults (21% women) from the Aerobics Center Longitudinal Study, followed up between 1974 and 2003. Estimated CRF was determined on the basis of sex, age, body mass index, waist circumference, resting heart rate, physical activity level, and smoking status. Actual CRF was measured by a maximal treadmill test. Risk reduction per 1–metabolic equivalent increase, discriminative ability (c statistic), and net reclassification improvement were determined.

Results
During a median follow-up of 14.5 years, 1,934 deaths occurred, 627 due to CVD. In a subsample of 18,095 participants, 1,049 cases of nonfatal CVD events were ascertained. After adjustment for potential confounders, both measured and estimated CRF were inversely associated with risks for all-cause mortality, CVD-related mortality and nonfatal CVD events in men, and all-cause mortality and nonfatal CVD events in women. The risk reduction per 1–metabolic equivalent increase ranged from approximately 10% to 20%. Measured CRF had a slightly better discriminative ability (c statistic) than did estimated CRF, and the net reclassification improvement values in measured CRF versus estimated CRF were 12.3% in men (p < 0.05) and 19.8% in women (p < 0.001).

Conclusions
These CRF algorithms utilized information routinely collected to obtain an estimate of CRF, which provides a valid indication of health status. In addition to identifying people at risk, this method can provide more appropriate exercise recommendations that reflect initial CRF levels.
Keyword Algorithms
Cardiorespiratory fitness
Cardiovascular disease
Mortality
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID AG06945
EX-2010-1008
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Medicine Publications
 
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