|| Checking for direct PDF access through Ovid
WHALEY, M. H., L. A. KAMINSKY, G. B. DWYER, L. H. GETCHELL, and J. A. NORTON. Predictors of over- and underachievement of age-predicted maximal heart rate. Med. Sci. Sports Exerc., Vol. 24, No. 10, pp. 1173–1179, 1992. The age-predicted maximal heart rate (PMHR) formula, 220 - age, is frequently used for identifying exercise training intensity, as well as determining endpoints for submaximal exercise testing. This study was designed to identify variables discriminating those with actual maximal heart rates considerably above or below that predicted from the 220 - age equation. Subjects included 2010 men and women ranging in age from 14 to 77 yr. Stepwise discriminant analysis was performed using maximal heart rate error groups as the dependent variable, and selected preexercise test characteristics as predictors. The HR error groups were based on the difference between the measured and PMHR as follows: below (≥15 beats-min-1 below PMHR), within (± 14 beats-min-1 of PMHR), and above (≥15 beats·min-1 above PMHR). A contrast of the below and above groups identified age, resting HR, body weight, and smoking status as predictors of group membership (P < 0.01) for both men and women. The overall canonical correlation was 0.282 and 0.294 for the men and women, respectively. Older age, higher resting HR, lower weight, and nonsmoking were related to the above group, while the inverse was related to the below group. Standardized coefficients suggest that age and resting heart rate for the men, and age and smoking status for the women were the most potent variables for discriminating extreme deviations between measured and PMHR. The classification procedure using all four significant independent variables revealed 54% (35/65) and 47% (24/51) accuracy in classifying the below group, and 68% (113/166) and 69% (48/70) accuracy in classifying the above group, for the men and women, respectively (P < 0.001). Data from the present study would support the findings from previous studies that older individuals commonly exceed the age-predicted maximal heart rate based on the 220 - age equation. In addition, combining knowledge about age and smoking habits with extreme scores for body weight and resting heart rate will help identify those who differ significantly from the typical age-predicted maximal heart rate.