Low cardiorespiratory (CRF) is associated with health problems in elderly people, especially cardiovascular and metabolic disease. However, physical limitations in this population frequently preclude the application of aerobic tests. We developed a model to estimate CRF without aerobic testing in older men with chronic cardiovascular and metabolic diseases. Subjects aged from 60 to 91 years were randomly assigned into validation ( ？？ = 6 7 ) and cross-validation ( ？？ = 2 9 ) groups. A hierarchical linear regression model included age, self-reported fitness, and handgrip strength normalized to body weight ( ？？ 2 = 0 . 7 9 ; SEE？=？1.1 METs). The PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage in relation to the original model and that predicted by the model and actual CRF correlated well in the cross-validation group ( ？？ = 0 . 8 5 ). The area under curve (AUC) values suggested a good accuracy of the model to detect disability in the validation (0.876, 95% CI: 0.793–0.959) and cross-validation groups (0.826, 95% CI: 0.677–0.975). Our findings suggest that CRF can be reliably estimated without exercise test in unhealthy elderly men. 1. Introduction Cardiorespiratory fitness (CRF) maintenance is important for functional independence and physical capacity throughout aging [1, 2]. Substantial declines in the ability to tolerate physical exertion generally predict mobility problems and cardiovascular morbidity and mortality, particularly in the sedentary elderly [3, 4]. Despite the importance of CRF assessment, very low functional capacity and frailty may hinder the use of exercise tests in this population [5, 6]. In this context, nonexercise prediction models become practical alternatives to estimate CRF [7] and may have important applications both in clinical and epidemiological settings. These models are developed by means of regression-based equations that usually include variables of simple and fast assessment, such as anthropometric measures, demographic characteristics, and daily habits [8]. Recently, Mailey et al. [7] cross-validated an equation developed primarily in middle-aged adults by Jurca et al. [9] and suggested that nonexercise models could be used to estimate the CRF of older adults. The sample studied was mainly composed by healthy old women (~60%). However, the prevalence of chronic diseases such as cardiovascular disease and diabetes increases dramatically with age [10], and is associated to lower physical capacity, inactivity, and limitations in the ability to exercise [2]. It would be therefore important
References
[1]
A. Mroszczyk-McDonald, P. D. Savage, and P. A. Ades, “Handgrip strength in cardiac rehabilitation: normative values, interaction with physical function, and response to training,” Journal of Cardiopulmonary Rehabilitation and Prevention, vol. 27, no. 5, pp. 298–302, 2007.
[2]
G. A. Heckman and R. S. McKelvie, “Cardiovascular aging and exercise in healthy older adults,” Clinical Journal of Sport Medicine, vol. 18, no. 6, pp. 479–485, 2008.
[3]
J. A. Berlin and G. A. Colditz, “A meta-analysis of physical activity in the prevention of coronary heart disease,” American Journal of Epidemiology, vol. 132, no. 4, pp. 612–628, 1990.
[4]
M. E. Cress and M. Meyer, “Maximal voluntary and functional performance levels needed for independence in adults aged 65 to 97 years,” Physical Therapy, vol. 83, no. 1, pp. 37–48, 2003.
[5]
N. B. Alexander, D. R. Dengel, R. J. Olson, and K. M. Krajewski, “Oxygen-uptake (VO2) kinetics and functional mobility performance in impaired older adults,” Journals of Gerontology—Series A, vol. 58, no. 8, pp. 734–739, 2003.
[6]
T. S. Church, T. M. Gill, A. B. Newman, S. N. Blair, C. P. Earnest, and M. Pahor, “Maximal fitness testing in sedentary elderly at substantial risk of disability: LIFE-P study experience,” Journal of Aging and Physical Activity, vol. 16, no. 4, pp. 408–415, 2008.
[7]
E. L. Mailey, S. M. White, T. R. Wójcicki, A. N. Szabo, A. F. Kramer, and E. McAuley, “Construct validation of a non-exercise measure of cardiorespiratory fitness in older adults,” BMC Public Health, vol. 10, article 59, 2010.
[8]
G. de A. Maranh？o Neto, P. M. Louren？o, and P.de T. Farinatti, “Prediction of aerobic fitness without stress testing and applicability to epidemiological studies: a systematic review,” Cadernos de Saude Publica, vol. 20, no. 1, pp. 48–56, 2004.
[9]
R. Jurca, A. S. Jackson, M. J. LaMonte et al., “Assessing cardiorespiratory fitness without performing exercise testing,” American Journal of Preventive Medicine, vol. 29, no. 3, pp. 185–193, 2005.
[10]
C. Hoffman, D. Rice, and H. Y. Sung, “Persons with chronic conditions: their prevalence and costs,” Journal of the American Medical Association, vol. 276, no. 18, pp. 1473–1479, 1996.
[11]
T. G. Lohman, A. F. Roche, and R. Martorell, Anthropometric Standardization Reference Manual, Human Kinetics, Champaign, Ill, USA, 1998.
[12]
G.de A. Maranh？o Neto, A. C. M. P. de Leon, and P.de T. Farinatti, “Cross-cultural equivalence of three scales used to estimate cardiorespiratory fitness in the elderly,” Cadernos de Saude Publica, vol. 24, no. 11, pp. 2499–2510, 2008.
[13]
A. G. M. Wisén, R. G. Farazdaghi, and B. Wohlfart, “A novel rating scale to predict maximal exercise capacity,” European Journal of Applied Physiology, vol. 87, no. 4-5, pp. 350–357, 2002.
[14]
K. Wasserman, J. E. Hansen, D. Y. Sue, W. W. Stringer, and B. J. Whipp, Principles of Exercise Testing and Interpretation, Lippincott Williams & Wilkins, Philadelphia, Pa, USA, 4th edition, 2004.
[15]
G. Borg, Borg's Perceived Exertion and Pain Scales, Human Kinetics, Champaign, Ill, USA, 1998.
[16]
American College of Sports Medicine, ACSM's Guidelines for Exercise Testing and Prescription, Lippincott Williams & Wilkins, Philadelphia, Pa, USA, 8th edition, 2010.
[17]
D. B. Holiday, J. E. Ballard, and B. C. McKeown, “PRESS-related statistics: regression tools for cross-validation and case diagnostics,” Medicine and Science in Sports and Exercise, vol. 27, no. 4, pp. 612–620, 1995.
[18]
J. M. Bland and D. G. Altman, “Statistical methods for assessing agreement between two methods of clinical measurement,” The Lancet, vol. 327, no. 8476, pp. 307–310, 1986.
[19]
P. S. Visich and J. K. Ehrman, “Graded exercise testing and exercise prescription,” in Clinical Exercise Physiology, J. K. Ehrman , P. M. Gordon, P. S. Visich, and S. J. Keteyian, Eds., Human Kinetics, Champaign, Ill, USA, 2nd edition, 2009.
[20]
G. de A. Maranh？o Neto and P. de T. Farinatti, “Non-exercise models for prediction of aerobic fitness and applicability on epidemiological studies: descriptive review and analysis of the studies,” Revista Brasileira de Medicina do Esporte, vol. 9, no. 5, pp. 304–324, 2003.
[21]
H. Syddall, C. Cooper, F. Martin, R. Briggs, and A. A. Sayer, “Is grip strength a useful single marker of frailty?” Age and Ageing, vol. 32, no. 6, pp. 650–656, 2003.
[22]
H. Sasaki, F. Kasagi, M. Yamada, and S. Fujita, “Grip strength predicts cause-specific mortality in middle-aged and elderly persons,” American Journal of Medicine, vol. 120, no. 4, pp. 337–342, 2007.
[23]
G. A. McKay and E. W. Banister, “A comparison of maximum oxygen uptake determination by bicycle ergometry at various pedaling frequencies and by treadmill running at various speeds,” European Journal of Applied Physiology and Occupational Physiology, vol. 35, no. 3, pp. 191–200, 1976.
[24]
D. L. Huggett, D. M. Connelly, and T. J. Overend, “Maximal aerobic capacity testing of older adults: a critical review,” Journals of Gerontology—Series A, vol. 60, no. 1, pp. 57–66, 2005.
[25]
P. de T. Farinatti and W. D. Monteiro, “Walk-run transition in young and older adults: with special reference to the cardio-respiratory responses,” European Journal of Applied Physiology, vol. 109, no. 3, pp. 379–388, 2010.
[26]
P. de T. Farinatti and P. P. S. Soares, “Cardiac output and oxygen uptake relationship during physical effort in men and women over 60 years old,” European Journal of Applied Physiology, vol. 107, no. 6, pp. 625–631, 2009.
[27]
S. W. Arnett, J. H. Laity, S. K. Agrawal, and M. E. Cress, “Aerobic reserve and physical functional performance in older adults,” Age and Ageing, vol. 37, no. 4, pp. 384–389, 2008.
[28]
M. J. Peterson, C. F. Pieper, and M. C. Morey, “Accuracy of VO2(max) prediction equations in older adults,” Medicine and Science in Sports and Exercise, vol. 35, no. 1, pp. 145–149, 2003.
[29]
L. J. Brandon, D. A. Ross, J. A. Sanford, and A. Lloyd, “Predicting oxygen uptake in older adults using lower-limb accelerometer measures,” Journal of Rehabilitation Research and Development, vol. 41, no. 6, pp. 861–869, 2004.
