Age-Based Prediction of Maximal Heart Rate in Children and Adolescents: A Systematic Review and Meta-Analysis

References

• Armstrong, N., & Welsman, J. R. (1994). Assessment and interpretation of aerobic fitness in children and adolescents. Exercise and Sport Sciences Reviews, 22(1), 435–476. doi:10.1249/00003677-199401000-00016
   PubMedGoogle Scholar
• Åstrand, P.-O. (1952). Experimental studies of physical working capacity in relation to sex and age ( Dissertation). Copenhagen, Denmark: Ejnor Munksgaard.
   Google Scholar
• Becker, B. J. (1988). Synthesizing standardized mean-change measures. British Journal of Mathematical and Statistical Psychology, 41(2), 257–278. doi:10.1111/bmsp.1988.41.issue-2
   Web of Science ®Google Scholar
• Begg, C. B., & Mazumdar, M. (1994). Operating characteristics of a rank correlation test for publication bias. Biometrics, 50(4), 1088–1101. doi:10.2307/2533446
   PubMed Web of Science ®Google Scholar
• Bitar, A., Vernet, J., Coudert, J., & Vermorel, M. (2000). Longitudinal changes in body composition, physical capacities and energy expenditure in boys and girls during the onset of puberty. European Journal of Nutrition, 39(4), 157–163. doi:10.1007/s003940070019
   PubMed Web of Science ®Google Scholar
• Boisseau, N., & Delamarche, P. (2000). Metabolic and hormonal responses to exercise in children and adolescents. Sports Medicine, 30(6), 405–422.
   PubMed Web of Science ®Google Scholar
• Bruce, R. A., Fisher, L. D., Cooper, M. N., & Gey, G. O. (1974). Separation of effects of cardiovascular disease and age on ventricular function with maximal exercise. The American Journal of Cardiology, 34(7), 757–763.
   PubMedGoogle Scholar
• Cicone, Z. S., Sinelnikov, O. A., & Esco, M. R. (2018). Age-predicted maximal heart rate equations are inaccurate for use in youth male soccer players. Pediatric Exercise Science, 30(4), 495–499.
   PubMed Web of Science ®Google Scholar
• Cochran, W. G. (1954). The combination of estimates from different experiments. Biometrics, 10(1), 101–129.
   Web of Science ®Google Scholar
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
   Google Scholar
• Colantonio, E., & Kiss, M. (2013). Is the hrmax= 220-age equation valid to prescribe exercise training in children. Journal of Exercise Physiology Online, 16(1), 19–27.
   Google Scholar
• Coleman, L., & Coleman, J. (2002). The measurement of puberty: A review. Journal of Adolescence, 25(5), 535–550.
   PubMed Web of Science ®Google Scholar
• Collins, G. S., Reitsma, J. B., Altman, D. G., & Moons, K. G. (2015). Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (tripod): The tripod statement. Bmj, 350, g7594.
   PubMed Web of Science ®Google Scholar
• Conn, V. S., Valentine, J. C., Cooper, H. M., & Rantz, M. J. (2003). Grey literature in meta-analyses. Nursing Research, 52(4), 256–261.
   PubMed Web of Science ®Google Scholar
• Donnelly, J. E., Hillman, C. H., Castelli, D., Etnier, J. L., Lee, S., Tomporowski, P., & Szabo-Reed, A. N. (2016). Physical activity, fitness, cognitive function, and academic achievement in children: A systematic review. Medicine and Science in Sports and Exercise, 48(6), 1197–1222.
   PubMed Web of Science ®Google Scholar
• Dorn, L. D., & Biro, F. M. (2011). Puberty and its measurement: A decade in review. Journal of Research on Adolescence, 21(1), 180–195.
   Web of Science ®Google Scholar
• Dorn, L. D., Dahl, R. E., Woodward, H. R., & Biro, F. (2006). Defining the boundaries of early adolescence: A user’s guide to assessing pubertal status and pubertal timing in research with adolescents. Applied Developmental Science, 10(1), 30–56.
   Google Scholar
• Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. Bmj, 315(7109), 629–634.
   PubMed Web of Science ®Google Scholar
• Fernhall, B., McCubbin, J. A., Pitetti, K. H., Rintala, P., Rimmer, J. H., Millar, A. L., & De Silva, A. (2001). Prediction of maximal heart rate in individuals with mental retardation. Medicine and Science in Sports and Exercise, 33(10), 1655–1660.
   PubMed Web of Science ®Google Scholar
• Fox, S. M., Naughton, J. P., & Haskell, W. L. (1971). Physical activity and the prevention of coronary heart disease. Annals of Clinical Research, 3(6), 404–432.
   PubMedGoogle Scholar
• Gagnon, I., Grilli, L., Friedman, D., & Iverson, G. (2016). A pilot study of active rehabilitation for adolescents who are slow to recover from sport‐related concussion. Scandinavian Journal of Medicine and Science in Sports, 26(3), 299–306.
   PubMed Web of Science ®Google Scholar
• Gelbart, M., Ziv-Baran, T., Williams, C. A., Yarom, Y., & Dubnov-Raz, G. (2017). Prediction of maximal heart rate in children and adolescents. Clinical Journal of Sport Medicine, 27(2), 139–144.
   PubMed Web of Science ®Google Scholar
• Gellish, R. L., Goslin, B. R., Olson, R. E., McDonald, A., Russi, G. D., & Moudgil, V. K. (2007). Longitudinal modeling of the relationship between age and maximal heart rate. Medicine and Science in Sports and Exercise, 39(5), 822–829.
   PubMed Web of Science ®Google Scholar
• Gibbons, R. D., Hedeker, D. R., & Davis, J. M. (1993). Estimation of effect size from a series of experiments involving paired comparisons. Journal of Educational Statistics, 18(3), 271–279.
   Google Scholar
• Halstead, M. E., & Walter, K. D. (2010). Sport-related concussion in children and adolescents. Pediatrics, 126(3), 597–615.
   PubMed Web of Science ®Google Scholar
• Hammond, H. K., Kelly, T. L., & Froelicher, V. (1983). Radionuclide imaging correlatives of heart rate impairment during maximal exercise testing. Journal of the American College of Cardiology, 2(5), 826–833.
   PubMed Web of Science ®Google Scholar
• Higgins, J., Thompson, S., Deeks, J., & Altman, D. (2003). Measuring inconsistency in meta-analyses. Bmj, 327(7414), 557–560.
   PubMed Web of Science ®Google Scholar
• Higgins, J. P., & Green, S. (Eds.). (2011). Cochrane handbook for systematic reviews of interventions, Version 5.1.0. Retrieved from https://handbook-5-1.cochrane.org/
   Google Scholar
• Hopewell, S., McDonald, S., Clarke, M. J., & Egger, M. (2007). Grey literature in meta-analyses of randomized trials of health care interventions. Cochrane Database of Systematic Reviews, 2007(2), MR000010.
   Web of Science ®Google Scholar
• Huedo-Medina, T. B., Sánchez-Meca, J., Marín-Martínez, F., & Botella, J. (2006). Assessing heterogeneity in meta-analysis: Q statistic or I2 index? Psychological Methods, 11(2), 193.
   PubMed Web of Science ®Google Scholar
• Inbar, O., Oren, A., Scheinowitz, M., Rotstein, A., Dlin, R., & Casaburi, R. (1994). Normal cardiopulmonary responses during incremental exercise in 20-to 70-yr-old men. Medicine and Science in Sports and Exercise, 26, 538.
   PubMed Web of Science ®Google Scholar
• Kostis, J. B., Moreyra, A. E., Amendo, M. T., Di Pietro, J., Cosgrove, N., & Kuo, P. T. (1982). The effect of age on heart rate in subjects free of heart disease. Studies by ambulatory electrocardiography and maximal exercise stress test. Circulation, 65(1), 141–145.
   PubMed Web of Science ®Google Scholar
• Lehmann, M., Keul, J., & Korsten-Reck, U. (1980). The influence of graduated treadmill exercise on plasma catecholamines, aerobic and anaerobic capacity in boys and adults. European Journal of Applied Physiology and Occupational Physiology, 47(3), 301–311.
   Web of Science ®Google Scholar
• Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis. Thousand Oaks, CA: Sage.
   Google Scholar
• Londeree, B. R., & Moeschberger, M. L. (1982). Effect of age and other factors on maximal heart rate. Research Quarterly for Exercise and Sport, 53(4), 297–304.
   Web of Science ®Google Scholar
• Machado, F. A., & Denadai, B. S. (2011). Validity of maximum heart rate prediction equations for children and adolescents. Arquivos Brasileiros De Cardiologia, 97(2), 136–140.
   PubMed Web of Science ®Google Scholar
• Mahon, A. D., Lee, J. D., & Hanna, L. E. (2010). Evaluating the prediction of maximal heart rate in children and adolescents. Research Quarterly for Exercise and Sport, 81(4), 466–471.
   PubMed Web of Science ®Google Scholar
• Miller, W. C., Wallace, J., & Eggert, K. (1993). Predicting max HR and the HR-VO2 relationship for exercise prescription in obesity. Medicine and Science in Sports and Exercise, 25(9), 1077–1081.
   PubMed Web of Science ®Google Scholar
• Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & Group, P. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Journal of Clinical Epidemiology, 62, 1006–1012.
   PubMed Web of Science ®Google Scholar
• Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., & Stewart, L. A. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-p) 2015 statement. Systematic Reviews, 4(1), 1.
   PubMed Web of Science ®Google Scholar
• Moons, K. G. M., Altman, D. G., Reitsma, J. B., & Collins, G. S.; Transparent Reporting of a Multivariate Prediction Model for Individual Prognosis or Development, I. (2015). New guideline for the reporting of studies developing, validating, or updating a multivariable clinical prediction model: The TRIPOD statement. Advances in Anatomic Pathology, 22(5), 303–305.
   PubMed Web of Science ®Google Scholar
• Nes, B., Janszky, I., Wisløff, U., Støylen, A., & Karlsen, T. (2013). Age-predicted maximal heart rate in healthy subjects: The HUNT fitness study. Scandinavian Journal of Medicine and Science in Sports, 23(6), 697–704.
   PubMed Web of Science ®Google Scholar
• Nikolaidis, P. T. (2014). Age-predicted vs. measured maximal heart rate in young team sport athletes. Nigerian Medical Journal: Journal of the Nigeria Medical Association, 55(4), 314–320.
   PubMedGoogle Scholar
• Nikolaidis, P. T. (2015). Maximal heart rate in soccer players: Measured versus age-predicted. Biomedical Journal, 38(1), 84–89.
   PubMed Web of Science ®Google Scholar
• Nikolaidis, P. T., Padulo, J., Chtourou, H., Torres-Luque, G., Afonso, J., & Heller, J. (2014). Estimating maximal heart rate with the ‘220-age’ formula in adolescent female volleyball players: A preliminary study. Human Movement, 15(3), 166–170.
   Google Scholar
• Paridon, S. M., Alpert, B. S., Boas, S. R., Cabrera, M. E., Caldarera, L. L., Daniels, S. R., & Rhodes, J. (2006). Clinical stress testing in the pediatric age group: A statement from the american heart association council on cardiovascular disease in the young, committee on atherosclerosis, hypertension, and obesity in youth. Circulation, 113(15), 1905–1920.
   PubMed Web of Science ®Google Scholar
• Petersen, A. C., Crockett, L., Richards, M., & Boxer, A. (1988). A self-report measure of pubertal status: Reliability, validity, and initial norms. Journal of Youth and Adolescence, 17(2), 117–133.
   PubMed Web of Science ®Google Scholar
• Rasmussen, A. R., Wohlfahrt-Veje, C., de Renzy-Martin, K. T., Hagen, C. P., Tinggaard, J., Mouritsen, A., & Main, K. M. (2015). Validity of self-assessment of pubertal maturation. Pediatrics, 135(1), 86–93.
   PubMed Web of Science ®Google Scholar
• Riley, R. D., Lambert, P. C., & Abo-Zaid, G. (2010). Meta-analysis of individual participant data: Rationale, conduct, and reporting. Bmj, 340, 521–525.
   Google Scholar
• Robergs, R. A., & Landwehr, R. (2002). The surprising history of the” hrmax= 220-age” equation. Journal of Exercise Physiology Online, 5(2), 1–10.
   Google Scholar
• Robinson, S. (1938). Experimental studies of physical fitness in relation to age. European Journal of Applied Physiology and Occupational Physiology, 10(3), 251–323.
   Google Scholar
• Rosenberg, M. S. (2005). The file‐drawer problem revisited: A general weighted method for calculating fail‐safe numbers in meta‐analysis. Evolution, 59(2), 464–468.
   PubMed Web of Science ®Google Scholar
• Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological Bulletin, 86(3), 638.
   Web of Science ®Google Scholar
• Rowland, T., Maresh, C., Charkoudian, N., Vanderburgh, P., Castellani, J., & Armstrong, L. (1996). Plasma norepinephrine responses to cycle exercise in boys and men. International Journal of Sports Medicine, 17(01), 22–26.
   PubMed Web of Science ®Google Scholar
• Shargal, E., Kislev-Cohen, R., Zigel, L., Epstein, S., Pilz-Burstein, R., & Tenenbaum, G. (2015). Age-related maximal heart rate: Examination and reinement of prediction equations. Journal of Sports Medicine and Physical Fitness, 55(10), 1207–1218.
   PubMed Web of Science ®Google Scholar
• Shea, B. J., Grimshaw, J. M., Wells, G. A., Boers, M., Andersson, N., Hamel, C., & Bouter, L. M. (2007). Development of amstar: A measurement tool to assess the methodological quality of systematic reviews. BMC Medical Research Methodology, 7(1), 10.
   PubMed Web of Science ®Google Scholar
• Shea, B. J., Hamel, C., Wells, G. A., Bouter, L. M., Kristjansson, E., Grimshaw, J., & Boers, M. (2009). Amstar is a reliable and valid measurement tool to assess the methodological quality of systematic reviews. Journal of Clinical Epidemiology, 62(10), 1013–1020.
   PubMed Web of Science ®Google Scholar
• Solorzano, C. M. B., & McCartney, C. R. (2010). Obesity and the pubertal transition in girls and boys. Reproduction, 140(3), 399–410.
   PubMed Web of Science ®Google Scholar
• Sterne, J., Egger, M., & Moher, D. (2011). Addressing reporting biases. In J. P. T. Higgins & S. Green (Eds.), Cochrane handbook for systematic reviews of interventions (Chapter 10). Retrieved from https://handbook-5-1.cochrane.org/chapter_10/10_addressing_reporting_biases.htm
   Google Scholar
• Sterne, J. A., Gavaghan, D., & Egger, M. (2000). Publication and related bias in meta-analysis: Power of statistical tests and prevalence in the literature. Journal of Clinical Epidemiology, 53(11), 1119–1129.
   PubMed Web of Science ®Google Scholar
• Stewart, L. A., & Parmar, M. K. B. (1993). Meta-analysis of the literature or of individual patient data: Is there a difference? The Lancet, 341(8842), 418–422.
   PubMed Web of Science ®Google Scholar
• Tanaka, H., Monahan, K. D., & Seals, D. R. (2001). Age-predicted maximal heart rate revisited. Journal of the American College of Cardiology, 37(1), 153–156.
   PubMed Web of Science ®Google Scholar
• Taylor, S., Whincup, P., Hindmarsh, P., Lampe, F., Odoki, K., & Cook, D. (2001). Performance of a new pubertal self-assessment questionnaire: A preliminary study. Paediatric and Perinatal Epidemiology, 15(1), 88–94.
   PubMed Web of Science ®Google Scholar
• Tipton, E., & Shuster, J. (2017). A framework for the meta‐analysis of bland–Altman studies based on a limits of agreement approach. Statistics in Medicine, 36(23), 3621–3635.
   PubMed Web of Science ®Google Scholar
• Turley, K. R., & Wilmore, J. H. (1997). Cardiovascular responses to treadmill and cycle ergometer exercise in children and adults. Journal of Applied Physiology, 83(3), 948–957.
   PubMed Web of Science ®Google Scholar
• Washington, R., Bricker, J., Alpert, B., Daniels, S., Deckelbaum, R., Fisher, E., & Marx, G. (1994). Guidelines for exercise testing in the pediatric age group. From the committee on atherosclerosis and hypertension in children, council on cardiovascular disease in the young, the american heart association. Circulation, 90(4), 2166–2179.
   PubMed Web of Science ®Google Scholar
• Williford, H. N., Scharff-Olson, M., Duey, W. J., Pugh, S., & Barksdale, J. M. (1999). Physiological status and prediction of cardiovascular fitness in highly trained youth soccer athletes. The Journal of Strength and Conditioning Research, 13(1), 10–15.
   Web of Science ®Google Scholar