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Jennifer A Schrack; Vadim Zipunnikov; Jeff Goldsmith; Karen Bandeen-Roche; Ciprian M Crainiceanu; Luigi Ferrucci
Publisher: Public Library of Science (PLoS)
Journal: PLoS ONE
Languages: English
Types: Article
Subjects: Research Article, Anatomy, Mathematics, Cardiovascular Anatomy, Epidemiology of Aging, Epidemiology, Physical Sciences, Public and Occupational Health, Energy Metabolism, Statistics (Mathematics), Biology and Life Sciences, Developmental Biology, Physiology, Medicine, Organism Development, Cardiology, Geriatrics, Q, Nutrition, R, Population Biology, Sports and Exercise Medicine, Biochemistry, Science, Metabolism, Aging, Physiological Processes, Medicine and Health Sciences, Geriatric Cardiology
Background Accurate measurement of free-living energy expenditure is vital to understanding changes in energy metabolism with aging. The efficacy of heart rate as a surrogate for energy expenditure is rooted in the assumption of a linear function between heart rate and energy expenditure, but its validity and reliability in older adults remains unclear. Objective To assess the validity and reliability of the linear function between heart rate and energy expenditure in older adults using different levels of calibration. Design Heart rate and energy expenditure were assessed across five levels of exertion in 290 adults participating in the Baltimore Longitudinal Study of Aging. Correlation and random effects regression analyses assessed the linearity of the relationship between heart rate and energy expenditure and cross-validation models assessed predictive performance. Results Heart rate and energy expenditure were highly correlated (r = 0.98) and linear regardless of age or sex. Intra-person variability was low but inter-person variability was high, with substantial heterogeneity of the random intercept (s.d. = 0.372) despite similar slopes. Cross-validation models indicated individual calibration data substantially improves accuracy predictions of energy expenditure from heart rate, reducing the potential for considerable measurement bias. Although using five calibration measures provided the greatest reduction in the standard deviation of prediction errors (1.08 kcals/min), substantial improvement was also noted with two (0.75 kcals/min). Conclusion These findings indicate standard regression equations may be used to make population-level inferences when estimating energy expenditure from heart rate in older adults but caution should be exercised when making inferences at the individual level without proper calibration.

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