Accumulating evidence suggests the importance of childhood physical fitness and physical activity as protective health-related phenomena (8). This evidence has prompted public health officials to advocate for improving children’s physical fitness levels and increasing their daily physical activity (8,28). At this time, cross-sectional studies indicate a wide variation in physical fitness and physical activity among children (6,27). If these levels of fitness and activity are maintained in rank order from childhood to adolescence, those children initially observed to be unfit or inactive, relative to their peers, would predictably become unfit or inactive adolescents. The maintenance of relative rank within an age-sex group so that a measurement over time tends to follow a pattern where initial measurements predict later levels in the same individual is termed “tracking”(19). In children, little is known as to how well physical fitness and physical activity track into adolescence and early adulthood (16,19,20). However, a high degree of tracking would suggest early measurement and intervention as a strategy to assure healthy levels of physical fitness and physical activity in later years. This health promotion strategy would have long-term implications because the causal relationship among physical fitness, physical activity, and cardiovascular disease outcomes has been established in adults (3,4). In addition to its value in shaping health promotion strategies, tracking provides a measure of a variable’s stability and, as such, adds to our understanding of the natural development of physical fitness and physical activity as health-related phenomena. For example, observing that physical fitness remains stable from childhood into adolescence would provide evidence that the root determinants of physical fitness occur in childhood.
In this paper, we report the variability and tracking of two physical fitness components (aerobic and muscular fitness) and two physical activity intensities (sedentary and vigorous) over a 5-yr period from late childhood to adolescence. With exception, many of the previous long-term, population-based work examining these variables has centered on adolescent boys. For example, of the eight published long-term data sets examining peak V̇O2 in adolescence, only four (non-United States) studies included girls (19,26). Therefore, a secondary purpose of our study was to add to the body of work addressing the physical fitness and physical activity patterns of girls. This purpose is concordant with current federally sponsored initiatives examining how little we know about female adolescent development and calling for specific health-related prevention strategies targeted at girls, e.g., the Centers for Disease Control and Prevention Girl Power Campaign and the President’s Council on Physical Fitness and Sports Report Physical Activity and Sport in the Lives of Girls (5).
MATERIALS AND METHODS
Subjects.
The Muscatine study is a longitudinal, population-based investigation of cardiovascular disease risk factors in children, young adults, and selected family groups from Muscatine, IA. From a large (N = 925) cross-sectional screening of Muscatine school children, 150 subjects thought to be prepubertal based on age were identified. Initial contact was made through information mailed to the parents of each child and a phone call to the parents by a Muscatine study staff member. Nineteen parents reported that their child had begun puberty, and one parent declined participation for her child. Informed consent was secured from 130 subjects and their parents. Based on a physician’s physical examination, 4 of the 130 subjects were judged to have begun significant pubertal development (greater than stage 2 using the criteria of Tanner). A total of 126 subjects, all in pre- or early puberty, were enrolled in this present study; 61 boys, mean age 10.8 and ranging in age from 8 to 12 yr, and 62 girls, mean age 10.3 and ranging in age from 7 to 11 yr, attempted all baseline research procedures. At year 5, 53 boys and 57 girls attempted all research procedures (87% of the initial cohort). When compared with our previously published normative data and the data of others (22), enrolled children were within expected ranges for weight, height, and resting BP, suggesting that the sample was representative of normal children in this age range. All children were Caucasian. Protocol requirements established by the University of Iowa’s Human Subject Review Committee, including written permission from subjects and their parents, were satisfied before data collection.
Procedures.
Sexual maturation and physical fitness were measured annually. Anthropometry, bioelectrical impedance, and physical activity were measured quarterly (once every 3 months). The same field staff conducted all examinations.
Body composition.
Height was measured, without shoes, to the nearest 0.1 cm using the IOWA anthropometric plane and square (University of Iowa Department of Medical Engineering, Iowa City, IA). Weight was measured to the nearest 0.1 kg using a Seca 770 digital metric scale (Columbia, MD) calibrated daily with standardized weights. Fat-free body mass (FFM) was predicted using bioelectrical impedance and the Houtkooper et al. equations (12). For Caucasian children ages 10–19 yr, the reported FFM standard error of the estimate is 2.1 kg, and the adjusted R2 is 0.95 when this method is compared with underwater weighting using age-corrected density equations (12).
Sexual maturation.
Pediatricians conducted a general physical examination of each subject including breast and pubic hair development in girls and genital and pubic hair development in boys according to the criteria of Tanner (30). Using this criteria, pre-puberty was defined as stage 1, early puberty as stage 2, mid-puberty stage 3, late puberty stage 4, and post-puberty stage 5. To ensure adequate cell size, subjects in late- and post-puberty were grouped together.
Aerobic physical fitness.
The Medgraphics System CPX metabolic cart (Medical Graphics Corp., St. Paul, MN) was used to determine aerobic fitness. Before testing, the pneumotachograph was calibrated to within ± 4 mL·s−1. Known reference gases were used to calibrate the system analyzers within ± 0.03%. Heart rate (HR) was measured from a Burdick electrocardiograph single channel recorder (Milton, WI). A Siemens Elema electromechanically braked cycle ergometer (Siemens Systems, Coralville, IA) provided incremental workloads. The protocol for the graded exercise test consisted of a 1-min warm-up and three 3-min submaximal stages followed by a series of 30-s stages (“ramps”) until exhaustion. The highest volume of oxygen consumed (V̇O2) was described as peak V̇O2 providing the subject could no longer maintain a pedal cadence of at least 40 rev·min−1 and had a respiratory exchange ratio of > 1.0 or was within 95% of his/her predicted maximal HR. Peak heart rate, peak mechanical power, peak respiratory exchange ratio, and peak oxygen pulse (a noninvasive marker of cardiopulmonary O2 transportation efficiency) were also recorded (9). Using this protocol, we previously reported laboratory reliability correlations ranging from r = 0.83 to 0.97 for peak exercise variables. Our reliability correlation for peak V̇O2 was r = 0.96 (10).
Aerobic fitness results are presented three ways: as an absolute value [peak V̇O2 (mL·min−1)]; relative to body mass using the ratio method [peak V̇O2 (mL·kg−1·min−1)]; and allometrically adjusted for FFM. We have previously published our procedures for scaling our data using this latter method (14). Briefly, allometric equations take the general form y = axb, where the values for a and b are obtained from a least-squares linear regression analysis of logarithmic transformations of the dependent variable (in this study, V̇O2) and the independent variable (in this study FFM), yielding, for example, the simple model ln(V̇O2) = ln a + b ln(FFM).
Muscular fitness.
Maximum voluntary contraction for hand grip strength (peak grip) was measured using a calibrated Lafayette hand dynamometer (Lafayette, IN). The dynamometer, adjusted for subject’s hand size, was held in line with the forearm at the level of the thigh and then squeezed to exert maximum force. Both hands were alternately measured three times with the greatest value for each hand summed for data analysis. In children, test-retest reliability for hand-held dynamometry is r = 0.94 (95% CI = 0.89 to 0.97) (11).
Physical activity.
Every 3 months, television viewing and video game playing (TV/Video Game Recall) were assessed during a brief interview. During the interview, the subjects’ self-reported the number of min in which they watched television and the number of minutes they played video games during the previous day. Previous work by Baranowski and colleagues (2), Sallis and colleagues (29), and our own work (15) suggest 1-d recalls have acceptable reliability and validity in this age group.
Vigorous physical activity was also assessed every 3 months using the 3-Day Sweat Recall. This instrument requires children to report the number of episodes in which they were sweating or breathing hard due to physical activity during the past 3 d and queries the same temporal and physiological criteria of at least 20 min of sweating and hard breathing used to define vigorous physical activity in the national Youth Risk Behavior Survey (6). (In our instrument we defined episodes as sports, games, play, work, or movement that lasted approximately 20–90 min.) We have previously shown this question to be reliable and valid when compared with accelerometry-derived movement counts corresponding to an overload of at least 60% of V̇O2max (13). The means of the responses for each year were used for data analysis for the 3-Day Sweat Recall and TV/Video Game Recall. This approach improved reliability (which increases as the number of measurements increase) and dampened the known affects of seasonal and weekend variations in physical activity that occur in this age group (7). Moderate physical activity was not measured due to our inability to identify a survey instrument that adequately assessed this physical activity intensity and monetary constraints that precluded objective monitoring of movement (e.g., accelerometry).
Statistical analysis.
All analyses were stratified by gender. Yearly means and standard deviations were calculated for age and body composition variables. The modal category of Tanner stage was also noted. Yearly means, standard deviations, and percentiles were calculated for the fitness and physical activity outcomes. The year 1 and year 5 values of these outcomes were then compared using a Wilcoxon signed rank test to assess whether these outcomes changed over time. We also compared the outcomes at adjacent years (year 1 vs 2, 2 vs 3, 3 vs 4, and 4 vs 5) by using Wilcoxon signed rank tests with a Bonferroni adjustment. Tracking of fitness and physical activity outcomes over time was examined in two ways. First, Spearman rank correlation coefficients were calculated to estimate how well the year 5 outcomes were predicted by outcomes at earlier years. We also categorized the data into tertiles, and reported the percentage who remained in the extreme tertiles in year 5, given they began in that tertile in year 1. Under the null hypothesis of no tracking, one would expect to see these percentages to be near 33%. The statistical significance of the tracking within tertiles was assessed using Kendall’s tau-b.
RESULTS
Subject characteristics by study year are presented in Table 1. Mean body mass, height, and FFM increased each year for boys and girls. At the beginning of the study, all study subjects were either prepubertal or in early puberty. At year 5, all study subjects had advanced at least one stage in genital or breast development and over 80% of the study subjects were in late- or post-puberty. The greatest amount of maturational change occurred between years 3 and 4 for boys and year 4 and 5 for girls. By year 4, 42% of the boys (mean age 13.8 yr) were in late- or post-puberty. By year 5, 75% of the girls (mean age 14.2 yr) were in late- or post-puberty. The proportion of boys and girls within specific stages for pubic hair development (data not shown) was similar to the proportion in specific stages for genital and breast development.
;)
Table 1: Description of subjects by gender, years 1 through 5 (mean ± SD).
Table 2, Figure 1, and Figure 2 present peak physical fitness and physical activity responses by study year. Regardless of how the data were described, peak V̇O2 values were greater in boys than girls. Mean peak V̇O2, described in absolute terms (mL·min−1), improved through-out the observational period in boys whereas improving until year 4 in girls and then remaining unchanged in year 5. When described in relative terms using the ratio method (mL·kg−1·min−1) or when allometrically scaled using FFM, mean peak V̇O2 decreased slightly between years 2 and 3, increased slightly between years 3 and 4, and then remained unchanged between years 4 and 5 in boys. In girls, when described in relative terms using the ratio method (mL·kg−1·min−1) or when allometrically scaled using FFM, mean peak V̇O2 decreased slightly between years 2 and 3 then decreased to an even greater extent between years 4 and 5. For both adjustment methods (ratio and allometrically scaled), year 1 peak V̇O2 was significantly greater than year 5 in boys and girls. However, the year 1 to year 5 difference was 2 times greater in girls than boys.
Table 2: Description of physical fitness and physical activity variables by gender, years 1 through 5 (mean ± SD).
Figure 1: Changes in peak V̇O2 by study year for boys (mean).
Figure 2: Changes in peak V̇O2 by study year for girls (mean).
There were small but significant fluctuations in peak HR throughout the study period. Peak HR in girls was consistently higher than peak HR in boys. For both boys and girls, year 1 peak HR was not significantly different than year 5. Peak power and peak grip, physical fitness variables that are partially weight dependent, increased each year in boys and girls. In boys, the greatest increase in these variables occurred between years 3 and 4, the same time period in which the largest proportion of boys advanced to late- or post-puberty and gained the greatest amount of FFM. The smallest increases in peak power and peak grip occurred between years 4 and 5 in girls. This was the same time period when the largest proportion of girls advanced to late-or post-puberty and gained the least amount of FFM. Peak O2 pulse, a product of peak stroke volume and peak arterial-venous O2 difference, is partially determined by body weight because stroke volume increases with body size, as well as heart strength and contractility (8). Similarly to changes in absolute peak V̇O2 (mL·min−1), peak O2 pulse increased each year with the largest increase occurring between years 3 and 4 in boys. In girls, peak O2 pulse increased each year until year 4 and then remained unchanged. For boys and girls, year 1 peak O2 pulse was less than year 5. Physical activity variables were positively skewed; therefore, medians and percentiles are presented in Table 2. Throughout the study period, boys had greater values than girls for the 3-Day Sweat Recall and TV/Video Game Recall. The year 5, 3-Day Sweat Recall was greater than year 1 in boys, but remained unchanged in girls. For both boys and girls, values for the TV/Video Game Recall decreased between years 1 and 2 then remained unchanged (see Figs. 3 and 4).
Figure 3: Changes in TV viewing and video game recall by study year (median).
Figure 4: Changes in three-day sweat recall by study year (median)
Tracking results.
Table 3 displays the Spearman correlations between the same variable measured at follow-up (year 5) and the 4 preceding years. In general, there was a decline in the magnitude of the association over time; however, with few exceptions, physical fitness and physical activity variables tracked across the 5-yr study period. For boys and girls, the variables with the highest degree of tracking tended to be weight-dependent variables (e.g., peak power, peak grip strength, and unadjusted peak V̇O2), suggesting that the subjects’ body weight relative to peers remained stable through out the study period and contributed to the high degree of tracking. In boys, peak power and peak grip demonstrated the highest degree of tracking with correlations ranging from 0.68 to 0.90. Peak V̇O2, peak HR, peak O2 pulse, 3-Day Sweat Recall, and TV/Video Game Recall tracked moderately well with correlations ranging from 0.24 to 0.86. With several exceptions, tracking correlations for girls were similar to boys though physical fitness correlations were slightly lower. Peak power and peak grip demonstrated a high degree of tracking (r = 0. 52 to 0.80). Absolute peak V̇O2, peak V̇O2 (mL·kg−1·min−1), peak HR, peak O2 pulse, and the 3-Day Sweat Recall demonstrated a moderate degree of tracking (r = 0.32 to 0.79). Year 5 peak V̇O2 allometrically scaled for FFM was moderately associated with years 4, 3, and 2 but not with year 1 (r = 0.04). In girls, year 5 TV/Video Game Recall tracked only with year 4.
Table 3: Spearman correlations coefficients tracking physical fitness and physical activity between follow-up (year 5) and preceding years (4–1)
Table 4 displays the percent of subjects who were in upper or lower tertiles at baseline and were also there at follow-up (33% would be expected to remain in an extreme tertile by chance alone). Movement out of extreme tertiles was almost always to the middle tertile, i.e., during the study period, very few subjects moved from a lower to an upper tertile (or vice versa). For physical fitness variables, boys in the upper (more physically fit) tertiles appeared to track better than boys in the lower (less physically fit) tertiles. For example, 53% of boys in the upper tertile for peak V̇O2 (mL·kg−1·min−1) and 50% of boys in the upper tertile for peak V̇O2 allometrically scaled for FFM remained in this tertile at follow-up, whereas 43% and 36%, respectively, were in the lower peak V̇O2 tertile at follow-up. This trend was not evident in girls. Conversely, for the physical activity variables, inactive boys were more likely than active boys to remain in their respective tertiles at follow-up. For example, 73% of boys who were in the upper tertile for TV/Video Game Recall remained there at follow-up. (The upper tertile represents boys, who relative to their peers, were watching more TV and playing more video games.) This percentage is 2.2 times greater than expected by chance alone. Forty-seven percent of boys in the lower tertile for the 3-Day Sweat Recall also remained in this tertile at follow-up (1.4 times greater than expected due to chance). When compared with less active girls, there was a trend for the more physically active girls (upper tertile for the 3-Day Sweat Recall and lower tertile for TV/Video Game Recall) to remain in their respective tertile at follow-up. The difference, however, was not statistically significant.
Table 4: Percent of subjects remaining in lower and upper tertiles for physical fitness and physical activity at follow-up who were in these same tertiles at baseline.
DISCUSSION
Aerobic fitness, muscular fitness, sedentary activity, vigorous activity, and selected indices of growth and sexual maturation were measured in a representative sample of children, all of whom were Tanner 1 or 2 at baseline. This recruitment strategy allowed us to prospectively view changes in these variables as we followed the children for 5-yr measuring their physical fitness and sexual maturation yearly, for a total of five examinations, and their physical activity and body composition quarterly, 20 examinations. With few exceptions, physical fitness and physical activity tracked from baseline to follow-up with more children remaining in extreme tertiles than expected by random distribution.
Changes and tracking of physical fitness.
The yearly mean values in unadjusted and adjusted peak V̇O2 that we report are consistent with other North American papers examining aerobic fitness using a representative sample and bicycle ergometry; however, our adjusted values are consistently lower than reports examining aerobic fitness levels in Northern European children and adolescents using similar methods (17,26). Because it is unlikely that substantial genetic differences exist between our cohort and European children, it is probable that lifestyle differences (e.g., physical activity and diet) explain the lower aerobic fitness values that we observed.
Generally, adjusting peak V̇O2 for the confounding variable of body size produces different results and interpretations depending on the type of adjustment (1). However, that did not seem to be the case with our tracking data; the direction, magnitude, and interpretation of changes of peak V̇O2 were surprisingly similar between the two adjustment methods used (ratio and allometrically scaled for FFM). Observed changes in peak V̇O2 were also consistent with reviews examining changes in aerobic fitness during late childhood and early adolescence and with the small number of longitudinal reports directly examining peak V̇O2 during adolescence, e.g., the Amsterdam Growth and Health Study (17,23,26,31). Our results, coupled with the work of others, suggest peak V̇O2 normalized for body size remains relatively stable throughout this period in boys, whereas decreasing in girls (17,18,21,23). Our longitudinal data are also consistent with reports from cross-sectional studies that suggest that boys decrease their 1-mile run times through childhood and then times plateau at approximately 14 yr, whereas girls decrease run times until approximately 14 yr and then their times increase (26). (At the completion of our study, the mean age for boys was 14.6 yr and the mean age for girls was 14.2 yr.)
The greatest improvement in adjusted peak V̇O2 and peak O2 pulse for boys in our study occurred between years 3 and 4, which was when the largest proportion of boys advanced to late- or post-puberty. For girls, the greatest decline in adjusted peak V̇O2 and the only decrease in peak O2 pulse occurred between years 4 and 5, when the largest proportion of girls advanced to late- or post-puberty. Concurrently, boys gained proportionately more FFM than fat tissue between years 3 and 4, whereas girls gained proportionately more fat tissue than FFM between years 4 and 5. The shift in body composition during this period in our study subjects would directly impact on their ability to transport oxygen to working tissue and on the relative amount of lean tissue available to do work (26). In addition, because FFM did not increase proportionately with body weight between years 4 and 5 in girls, year 5 FFM was a smaller proportion of body mass than previous years, making our sample of girls more homogenous with respect to FFM. The restricted variability of FFM may have contributed to the low correlation between year 5 and year 1 for peak V̇O2 allometrically scaled for FFM. Whether viewed from a physiological or mathematical perspective, these results indicate the importance of maturity-related body composition changes to aerobic fitness. They also suggest a critical period for working with girls to reverse aerobic fitness declines.
Our result of moderate tracking of physical fitness during adolescence is similar to previous population-based European reports (16,19,24,31). This magnitude of tracking indicates that the overall chance that physically unfit children will become unfit teenagers is significant. However, approximately 50% of the children in the low physical fitness tertiles at baseline were not there at follow-up. These data demonstrate that some children initially labeled as unfit on the basis of an early exercise test would be expected to have normal fitness values when they reach adolescence. Therefore, fitness promotion efforts during childhood should emphasize maintaining and increasing physical fitness for all children (population approach) rather than singling out unfit children for special programs (high-risk approach). Because relatively high levels of physical fitness tended to track better than low levels of fitness in boys, the data also suggest that it is more likely that unfit boys will improve their physical fitness levels than fit boys will decrease their levels.
Changes and tracking of physical activity.
The mean 25th percentile for the 3-Day Sweat Recall, our index of vigorous physical activity, was 2.5 events per 3-d recall for boys and 1.7 events per 3-d recall for girls. These data indicate that through out the observational period most of our study subjects were meeting the guideline of three or more sessions per week of moderate to vigorous activities set forth by the International Consensus Conference on Physical Activity for Adolescents and that children and adolescents (even relatively sedentary ones) are more active than adults (28). However, though the boys in our study increased their vigorous activity levels as they moved from childhood to adolescence, the amount of reported vigorous activity in girls remained unchanged. These results are consistent with the national Youth Risk Behavior Survey, which indicates that boys increase their self-reported level of vigorous activity from late childhood to age 14, whereas vigorous activity in girls during this time period remains unchanged or slightly decreases (6). Our findings, in tandem with findings from the national Youth Risk Behavior Survey (6), are discouraging since we observed a period of time, movement from elementary to junior high school, in which opportunities to participate in a wide range of youth sport and physical fitness activities are most available to U.S. boys and girls, regardless of skill level (18). By not increasing their levels of vigorous activity during this period, girls are missing out on sporting opportunities and health-related benefits associated with vigorous movement (5,7). Though, our inability to measure moderate activity (which we view as a study limitation) and the decrease in sedentary behavior that we did observe suggest the possibility that our cohort was substituting moderate physical activity, perhaps leisure or work-related, for sedentary behavior and subsequently receiving the health benefits associated with moderate-intensity movement (8).
Vigorous physical activity (3-Day Sweat Recall) tracked as well as aerobic fitness (peak V̇O2). This was surprising, because physical activity, a behavior, is assumed to be associated with more dynamic and volatile factors (e.g., peer support) and less likely to be associated with more stable factors (e.g., genotype) than physical fitness, a biological attribute. The moderate tracking of vigorous physical activity that we observed, particularly in boys, suggests the possibility of a genetic predisposition for activity (25) as well as unidentified stable environmental factors and personality traits (27). The latter, personality traits, would reflect actual preferences for leisure activity including physical activity and self-report response styles (so that a subject consistently over or underreports activity). Self-report response style would inflate the tracking correlations in our survey data and should be considered a study limitation.
Our result of moderate tracking for vigorous physical activity during late childhood and adolescence is consistent with data published by European researchers (16,24,31). Malina (19) has recently reviewed European and North American studies examining tracking and also concluded moderate tracking of activity in this age group. His review included the observation that inactivity appears to track better than activity. In our study, sedentary activity (as measured using the TV/Video Game Recall) tracked through the study period in boys, but not in girls. The lack of tracking in TV viewing and video game playing in girls suggests instability in the behavior that might be viewed as a good situation, i.e., antecedents are not firmly rooted and the behavior is modifiable. In contrast, the most stable tertile for TV viewing and video game playing in boys was the upper tertile, i.e., boys who relative to their peers, watched the most television and played the most video games. These results indicate that sedentary behavior patterns are established early in boys, persist through sexual maturation, and may be resistant to change.
In summary, during a period of rapid psychosocial and biological development, late childhood through middle adolescence, physical fitness, vigorous activity, and sedentary activity are moderately stable variables that track from childhood to adolescence. Boys appear to settle into activity and fitness patterns sooner than girls. The stability of sedentary behavior that we observed in boys suggests early intervention may be warranted in this population.
The authors express appreciation to Dr. Ronald M. Lauer and the Muscatine Field team (especially Kathleen Schrieber, Betsy Fletcher, and Catherine Rost) for their organizational efforts; and Mr. John D. Witt for help with data management. We also thank the children of Muscatine, their parents, and their teachers without whom this study would not have been possible.
This work was supported by a grant from the National Institutes of Health Specialized Center of Research in Hypertension HL44546.
REFERENCES
1. Armstrong, N., and J. R. Welsman. Assessment and interpretation of aerobic fitness in children and adolescents. Exerc. Sport Sci. Rev. 22:435–476, 1994.
2. Baranowski, T., R. J. Dworkin, C. J. Cieslik, et al. Reliability and validity of self report of aerobic activity: Family Health Project. Res. Q. Exerc. Sport. 55:309–317, 1984.
3. Blair, S. N., H. W. Kohl, C. E. Barlow, R. S. Paffenbarger, L. W. Gibbons, and C. A. Macera. Changes in physical fitness and all-cause mortality. JAMA 273:1093–1098, 1995.
4. Blair, S. N., H. W. Kohl, R. S. Paffenbarger, D. G. Clark, K. H. Cooper, and L. W. Gibbons. Physical fitness and all-cause mortality: a prospective study of healthy men and women. JAMA 262:2395–2401, 1989.
5. Bunker, L. K. Psycho-physiological contributions of physical activity and sports for girls. President’s Council on Physical Fitness and Sports Research Digest 3:1–8, 1998.
6. Centers for Disease Control and Prevention. Youth risk behavior surveillance: United States. MMWR 47:1–89, 1997.
7. Crocker, P. R., D. A. Bailey, R. A. Faulkner, K. C. Kowalski, and R. McGrath. Measuring general levels of physical activity: preliminary evidence for the Physical Activity Questionnaire for Older Children. Med. Sci. Sports Exerc. 29:1344–1349, 1997.
8. Department of Health and Human Services. Physical activity and health: a report of the Surgeon General. Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service, CDC, National Center for Chronic Disease Prevention and Health Promotion, 1996, pp. 81–208.
9. Froelicher, V. G. Exercise and the Heart: Clinical Concepts. Chicago: Year Book Medical, 1987, pp. 70.
10. Golden, J. C., K. F. Janz, W. R. Clarke, and L. T. Mahoney. New protocol for submaximal and peak exercise values for children and adolescents: the Muscatine study. Pediatr. Exerc. Sci. 2:129–140, 1991.
11. Heeboll-Nielsen, K. Muscle strength of boys and girls, 1981 compared to 1956. Scand. J. Sports Sci. 4:37–43, 1982.
12. Houtkooper, L. B., S. B. Going, T. G. Lohman, A. F. Roche, and M. Van Loan. Bioelectrical impedance estimation of fat-free body mass in children and youth: a cross-validation study. J. Appl. Physiol. 72:366–373, 1992.
13. Janz, K. F., J. D. Witt, and L. T. Mahoney. The stability of children’s physical activity as measured by accelerometry and self-report. Med. Sci. Sports Exerc. 27:1326–332, 1995.
14. Janz, K. F., T. L. Burns, J. D. Witt, and L. T. Mahoney. Longitudinal analysis of scaling V̇O
2 for differences in body size during puberty: the Muscatine Study. Med. Sci. Sports Exerc. 30:1436–1444, 1998.
15. Janz, K. F., D. A. Phillips, and L. T. Mahoney. Self-selected physical activity profiles in children and adolescents. Phys. Educator 49:81–87, 1992.
16. Kemper, H. C., J. Snel, R. Verschuur, and L. Storm-van Essen. Tracking of health and risk indicators of cardiovascular disease from teenager to adult: Amsterdam growth and health study. Prev. Med. 19:624–655, 1990.
17. Krahenbuhl, G. S., J. S. Skinner, and W. M. Kohrt. Developmental aspects of maximal aerobic power in children. Exerc. Sport Sci. Rev. 13:503–538, 1985.
18. Malina, R. M. Physical growth and biological maturation of young athletes. Exerc. Sport Sci. Rev. 22:389–433, 1994.
19. Malina, R. M. Tracking of physical activity and physical fitness across the lifespan. Res. Q. Exerc. Sport 67:48–57, 1996.
20. Pate, R. R., T. Baranowski, M. Dowda, and S. G. Trost. Tracking of physical activity in young children. Med. Sci. Sports Exerc. 28:92–96, 1996.
21. Pate, R. R, and R. J. Shephard. Characteristics of physical fitness in youth. In:
Perspectives in Exercise Science and Sports Medicine: Youth, Exercise, and Sport, C. V. Gisolfi and D. R. Lamb (Eds.). Indianapolis: Benchmark Press, 1989, pp. 1–43.
22. Roser, B., R. J. Prineas, J. M. H. Loggie, and S. R. Daniels. Blood pressure nomograms for children and adolescents, by height, sex, and age, in the United States. J. Pediatr. 123:871–86, 1993.
23. Pivarnik, J. M., W. C. Taylor, and S. S. Cummings. Longitudinal Assessment of Aerobic Fitness in Middle School African-American Girls. Pediatr. Exerc. Sci. 10:21–27, 1998.
24. Raitakari, O. T., K. V. K. Porkka, S. Taimela, R. Telama, L. Rasane, and J. S. A. Vikari. Effects of persistent physical activity and inactivity on coronary risk factors in children and young adults. Am. J. Epidemiol. 140:195–205, 1994.
25. Rowland, T. W. The biological basis of physical activity. Med. Sci. Sports Exerc. 30:392–399, 1998.
26. Rowland, T. W. Developmental Exercise Physiology. Champaign, IL: Human Kinetics, 1996, pp. 73–98.
27. Sallis, J. F., C. C. Berry, S. L. Broyles, T. L. McKenzie, and P. R. Nader. Variability and tracking of physical activity over 2 yr. in young children. Med. Sci. Sports Exerc. 27:1042–1049, 1995.
28. Sallis, J. F., and K. Patrick. Physical activity guidelines for adolescents: consensus statement. Pediatr. Exerc. Sci. 6:302–314, 1994.
29. Sallis, J. F., P. K. Strikmiller, D. W. Harsha, et al. Validation of interviewer- and self-administered physical activity checklists for fifth grade students. Med. Sci. Sports Exerc. 28:840–851, 1996.
30. Tanner, J. M. Growth and endocrinology of the adolescent. In: Endocrinology and Diseases of Childhood, 2nd Ed., L. J. Gardner (Ed.). Philadelphia: Saunders, 1975,
31. Van Mechelen, W., and H. C. G. Kemper. Habitual physical activity in longitudinal perspective. In: The Amsterdam Growth Study: A Longitudinal Analysis of Health, Fitness, and Lifestyle, H. C. G. Kemper (Ed.). Champaign, IL: Human Kinetics, 1995, pp. 135–158.
