Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2018 Jan 1.
Published in final edited form as: J Sports Sci. 2016 Mar 4;35(1):29–34. doi: 10.1080/02640414.2016.1154594

Cardiorespiratory fitness in urban adolescent girls: associations with race and pubertal status

Catherine Gammon a, Karin A Pfeiffer a, Anamaria Kazanis b,c, Jiying Ling b, Lorraine B Robbins b
PMCID: PMC5011028  NIHMSID: NIHMS768821  PMID: 26942487

Abstract

Cardiorespiratory fitness affords health benefits to youth. Among females, weight-relative fitness declines during puberty and is lower among African American (AA) than Caucasian girls. Data indicate racial differences in pubertal timing and tempo, yet the interactive influence of puberty and race on fitness, and the role of physical activity (PA) in these associations have not been examined. Thus, independent and interactive associations of race and pubertal development with fitness in adolescent girls, controlling for PA were examined. Girls in grades 5–8 (n = 1011; Caucasian = 25.2%, AA = 52.3%, Other Race group = 22.5%) completed the Pubertal Development Scale (pubertal stage assessment) and Fitnessgram® Progressive Aerobic Cardiovascular Endurance Run (PACER) test (cardiorespiratory fitness assessment). PA was assessed by accelerometry. Bivariate and multivariate analyses were used to examine associations among race, pubertal stage and fitness, controlling for vigorous PA, AA, and pubertally advanced girls demonstrated lower fitness than Caucasian and less mature counterparts. Puberty and race remained significantly associated with fitness after controlling for vigorous PA. The interaction effect of race and puberty on fitness was non-significant. The pubertal influence on fitness is observed among AA adolescents. Associations between fitness and race/puberty appear to be independent of each other and vigorous PA. Pubertally advanced AA girls represent a priority group for fitness interventions.

Keywords: VO2max, physical activity, African American, Caucasian

Introduction

Epidemiologic data indicating that the prevalence of obesity among African American (AA) girls, on average, is higher than among Caucasian girls, which is concurrent with a higher prevalence of Type II diabetes and elevated blood pressure in AA youth (Dabelea et al., 2014; Ogden, Carroll, Kit, & Flegal, 2012; Rosner, Cook, Daniels, & Falkner, 2013). The poor health profile of AA children warrants the investigation of factors which protect against the development of chronic diseases and associated risk factors. Cardiorespiratory fitness (also referred to as VO2max) is associated with a range of positive health outcomes for children and adolescents and may thus be an important health attribute for AA youth to accrue (Ortega et al., 2008; Silva et al., 2013).

Multiple studies report lower weight-relative fitness levels among AA youth when compared to Caucasian youth (Andreacci et al., 2004; Pivarnik, Bray, Hergenroeder, Hill, & Wong, 1995; Shaibi, Ball, & Goran, 2006; Trowbridge et al., 1997; Wong et al., 1999). Suggested explanations for this difference include lower hemoglobin levels (Andreacci et al., 2004; Hunter, Weinsier, McCarthy, Enette Larson-Meyer, & Newcomer, 2001; Pivarnik et al., 1995) and a lower percentage of Type I muscle fibers among AAs than Caucasians (Ama et al., 1986). One factor not considered in many of these studies, which may contribute to racial differences in fitness among youth, is pubertal development.

During adolescence and across the pubertal years, VO2max declines in females by 3–12 ml · kg.min−1 between the ages of 8–18 years (Malina, Bouchard, & Bar-Or, 2004). The decline in weight-relative fitness may reflect a puberty-related increase in body fat percentage, which results in a lower proportion of metabolically active tissue in females (Malina et al., 2004). The timing and tempo of pubertal events varies by racial group. Compared with Caucasian girls, AA girls are reported to start puberty earlier, take longer to progress from pubertal onset (the first appearance of secondary sexual characteristics) to menses, and take longer to progress from stage 2 to stage 3 of sexual maturation, according to Tanner’s criteria (Herman-Giddens et al., 1997). These racial differences may contribute to differences in body composition (Kimm et al., 2001) and size (Sirard, Pfeiffer, Dowda, & Pate, 2008), which can affect performance during a cardiorespiratory fitness test. This information suggests that puberty and racial group may have an interactive influence on weight-relative fitness, yet this contention has not been examined. To our knowledge, the only study reporting fitness levels by pubertal status among AA and Caucasian youth reported higher relative VO2max values for pubertally advanced compared with prepubertal youth in both AA and Caucasian groups (Andreacci et al., 2004). The inclusion of males and females in the calculation of average VO2max values may explain these findings, as weight-relative fitness is known to decline in girls but increase in boys, post-puberty (Malina et al., 2004). Given the racial variation in the pubertal process and potential importance of fitness to the long-term health of AA females, direct examination of the interactive association of puberty and race with fitness is necessary.

In addition, few studies have examined the role of physical activity (PA) in the association between puberty and fitness, and race and fitness in youth. AA youth are reported to engage in less moderate-to-vigorous intensity physical activity (MVPA), and more sedentary behaviour than Caucasian youth (Bradley, McMurray, Harrell, & Deng, 2000; Sirard et al., 2008). The positive association between PA and fitness (albeit weak to moderate in youth; Baquet, Twisk, Kemper, Van, & Berthoin, 2006; Katzmarzyk, Malina, Song, & Bouchard, 1998; Pfeiffer, Dowda, Dishman, Sirard, & Pate, 2007), suggests that lower PA levels may contribute to lower cardiorespiratory fitness levels among AA youth, yet few studies exploring racial differences in fitness have examined the concomitant influence of PA. Thus, the purpose of this study was to examine the independent and interactive associations of race and pubertal development with cardiorespiratory fitness in adolescent girls, while controlling for PA.

Methods

Study design and participants

Baseline data collected during the fall of the first (2012) and second years (2013) of a group randomised controlled trial (RCT) that included a school-based PA intervention were used. A detailed description of the intervention and its theoretical basis has been reported elsewhere (Robbins et al., 2013). Inclusion criteria for the RCT were: (1) girls in grades 5–8, and (2) able to read, understand, and speak English. Exclusion criteria were: (1) involvement in organised sport or activity requiring MVPA on 3 or more days a week after school, and (2) having a health condition that prevented participation in PA or exercise. Data included herein were collected prior to randomization to intervention versus control condition.

Procedure

The University Biomedical Institutional Review Board and school district administrators approved the study protocol (IRB# 11–247, initial application #: i038097). At the beginning of the 2012–2013 and 2013–2014 academic years, the research team introduced the study to prospective participants at each school. Students were provided with information packets (including consent and assent forms, and an inclusion/exclusion-criteria screening questionnaire) to share with their parents. Students were informed that returning completed forms the following day would earn them $5.00, regardless of whether they decided to participate or not.

Demographics

Age, race, ethnicity, and school grade were reported by the participants’ parent/legal guardian. Socio-economic status (SES) was assessed by asking about the participants’ eligibility for a free or reduced-price school lunch.

Anthropometrics

Height (cm) and weight (kg) were measured according to standardised procedures (Lohman, Roche, & Martorell, 1988). Two measures of height (within 0.5 cm of each other), and two measures of weight (kg) were averaged, and the mean value was used to calculate body mass index (BMI; weight [kg]/height [m2]) and BMI-z score (http://www.cdc.gov).

Fitness

Cardiovascular fitness was assessed using the Progressive Aerobic Cardiovascular Endurance Run (PACER) test, the procedure for which is described in detail elsewhere (The Cooper Institute, 2010). Participants were required to run 15 m or 20 m laps (depending on school space) between two cones, reaching each cone in time with an audio cue. As the test progressed, the time between the audio cues decreased. Participants were considered to have ended the test when they failed to reach the next cone in time with the matching audio cue for two consecutive laps. The number of laps completed by the participant were converted to the mile equivalent and used to estimate VO2max (ml.kg · min−1) according to the following equation: VO2 = (−8.41 ×(mile equivalent)) + (0.34 ×(mile equivalent × mile equivalent)) + (0.21 ×(age × gender)) – (0.84 × BMI) + 108.94 (Cureton, Sloniger, O’Bannon, Black, & McCormack, 1995).

Physical activity

PA was assessed by accelerometry (ActiGraph GT3X-plus). Participants wore the monitor on the right hip for 7 days. They were instructed on how to wear monitor, and told that they should wear the monitor at all times during the monitoring period, with the exception of swimming, bathing, and sleeping. To remind them to wear the monitor, participants received an automated phone call each morning during the data collection period.

The accelerometers were programmed to start collecting data at 5.00 am on the day following the distribution of monitors to participants. Data were collected in raw mode and integrated into 15-s epochs, and cut-points established by Evenson, Catellier, Gill, Ondrak, and McMurray (2008) were used to distinguish activity of sedentary (<26 counts per 15 s), light (26–573), moderate (574–1002), and vigorous intensity (≥1003). Non-wear periods were identified as intervals of at least 60 consecutive minutes of zero activity counts, and these data were excluded from the final analysis. Only participants providing a minimum of 8 hours of valid accelerometer data on 4 days (three weekdays and one weekend day) were included in the analysis (Jago et al., 2013; Matthews, Hagströmer, Pober, & Bowles, 2012; Patnode et al., 2011). To control for differences in wear time, PA variables were expressed as minutes of PA per hour.

Pubertal development

Pubertal development was assessed using the Pubertal Development Scale (Petersen, Crockett, Richards, & Boxer, 1988). The Pubertal Development Scale is a self-report measure of pubertal development, which has been validated against physician assessments of pubertal status with correlations of 0.6–0.7 (Brooks-Gunn, Warren, Rosso, & Gargiulo, 1987). Girls self-reported their pubertal development in the following areas: body hair, breast growth, skin changes, and growth spurt, by indicating one of the following four response choices: (a) no, (b) yes, barely, (c) yes, definitely, (d) development complete. The response choices were scored from 1–4 points, respectively. Participants were also asked whether they had experienced menarche (“yes” or “no” response choices, no = 1 point, yes = 4 points). A summary score for pubertal development was created, by calculating the average of the five questions (higher scores indicated more advanced pubertal development). To create pubertal categories, the scores for body hair and breast growth were summed. Participants with a total score of three or less and reporting “no” for menstruation were categorised as being in early puberty. Participants with a total score of four or more and reporting “no” for menstruation were categorised as being in middle puberty. Participants were categorised as being in late puberty if they responded “yes” to menstruation (Carskadon & Acebo, 1993). The Pubertal Development Scale was completed behind a privacy screen. A female member of the research team was present to assist participants with the completion of the survey, if needed.

Statistical analyses

Data were analyzed using Statistical Package for the Social Sciences (SPSS) 22.0 for Windows. Descriptive statistics, including means, standard deviations, frequencies, and percentages, were calculated to describe demographic and PA variables. Previous literature indicates that of the typical PA intensity classifications (sedentary, light, moderate, moderate–vigorous, vigorous), vigorous PA consistently demonstrates the strongest association with fitness (Denton et al., 2013). To verify that vigorous PA was the most appropriate activity variable to use as a covariate in the final analysis, correlations between fitness and time spent sedentary and in light, moderate, moderate-vigorous, and vigorous PA were inspected. Vigorous PA demonstrated the strongest correlation with fitness (r = 0.20, P < .001) and was included as the PA covariate in subsequent analyses. Age and BMI were components of the VO2max prediction equation and therefore were not included as covariates. To control for age differences across pubertal categories, school grade was included as a covariate. One-way analysis of variance (ANOVA) with Scheffé post hoc tests was used to examine fitness by race and pubertal status, controlling for vigorous PA and school grade. Two-way ANOVA was used to examine the interactive effect of race and pubertal status on fitness, controlling for vigorous PA, and school grade.

Results

A total of 1011 5th–8th grade girls from 16 urban schools, with a mean age of 12.20 years (SD = .96) participated. The majority of the sample (n = 803, 85.5%) qualified for a free or reduced price school lunch. The sample included 255 Caucasian girls, 528 AA girls, and 228 girls from other races (combined to represent an “Other Races” group; see Table 1). The Other Race group comprised Asian, Indian, and Hawaiian girls, girls identifying with more than one racial group, and girls indicating “other racial group” on the demographic questionnaire. The majority of the sample (51.4%, n = 519) were classified as being in the late stage of pubertal development, with smaller proportions in the middle (38.3%, n = 387) and early (10.2%, n = 103) stages of pubertal development (see Table 2).

Table 1.

Participant characteristics by racial group; mean (SD).

Total sample (n = 1011) Caucasian (n = 255) African American (n = 528) Other Race (n = 228) Group comparisons (P < 0.05)
Age (years) 12.2 (0.96) 12.0 (0.93) 12.3 (0.92) 12.2 (1.07) AA > C
Height (cm) 155.1 (8.0) 152.9 (7.8) 156.7 (7.5) 153.6 (8.5) AA > C, OR
Weight (kg) 58.0 (18.1) 53.6 (16.6) 60.4 (18.0) 57.3 (19.0) AA > C
BMI z-score 1.06 (1.03) 0.89 (1.02) 1.13 (1.02) 1.07 (1.03) AA > C
Vigorous PA (minh−1) 0.7 (0.6) 0.7 (0.5) 0.8 (0.6) 0.7 (0.5) NS
VO2max (ml.kg · min−1) 37.5 (5.2) 38.5 (4.9) 37.0 (5.2) 37.3 (5.4) AA < C
Accelerometer counts per minute 397.6 (238.2) 387.7 (127.6) 408.0 (282.4) 379.2 (121.6) NS
Accelerometer wear time (minday−1) 832.3 (88.3) 807.8 (68.2) 843.4 (95.4) 835.1 (87.1) C < AA, OR
Time spent sedentary (minh−1) 39.3 (4.3) 39.3 (4.3) 39.2 (4.3) 39.6 (4.2) NS
Light PA (minh−1) 17.8 (3.5) 17.9 (3.5) 17.8 (3.5) 17.7 (3.4) NS
Moderate PA (minh−1) 2.1 (0.8) 2.1 (0.9) 2.2 (0.8) 2.0 (0.8) NS
Open in a new tab

AA = African American, C = Caucasian, OR = Other Race, NS = Non-significant

Table 2.

Participant characteristics by pubertal group; mean (SD).

Early puberty (n = 103) Middle puberty (n = 387) Late puberty (n = 519) Group comparisons (P < 0.05)
Age (years) 11.6 (0.77) 11.8 (0.77) 12.7 (0.92) L > E, M
Height (cm) 148.6 (7.4) 152.2 (7.4) 158.5 (6.9) L > E, M
M > E
Weight (kg) 47.1 (12.3) 52.1 (15.7) 64.5 (18.2) L > E, M
M > E
BMI z-score 0.66 (1.14) 0.82 (1.09) 1.31 (0.88) L > E, M
Vigorous PA (minh−1) 0.96 (0.59) 0.80 (0.58) 0.62 (0.49) L < E, M
M < E
VO2max (ml.kg · min−1) 39.7 (4.0) 38.8 (4.9) 36.0 (5.3) L < E, M
Accelerometer counts per minute 449.6 (142.3) 420.4 (123.9) 366.7 (279.5) L < E, M
Accelerometer wear time (minday−1) 824.4 (92.7) 827.1 (83.3) 837.9 (91.1) NS
Time spent sedentary (minh−1) 37.8 (4.1) 38.2 (4.0) 40.6 (4.23) L > E, M
Light PA (minh−1) 18.9 (3.1) 18.7 (3.3) 16.9 (3.5) L < E, M
Moderate PA (minh−1) 2.4 (0.9) 2.3 (0.8) 1.9 (0.8) L < E, M
Open in a new tab

E = Early Puberty, M = Middle Puberty, L = Late Puberty, NS = Non-Significant

Mean age and BMI z-score were significantly higher among AA girls when compared with Caucasian girls, and among girls in late puberty when compared with girls in early and middle puberty (see Tables 1 and 2). Time spent sedentary, and in light, moderate and vigorous PA did not differ by racial group. Activity levels were significantly different across pubertal categories, with girls in the early stages of pubertal development engaging in the highest levels of light, moderate, and vigorous PA and girls in late pubertal stages engaging in the lowest. Time spent sedentary was significantly higher among girls in late pubertal stages. Caucasian girls had significantly higher cardiorespiratory fitness than AA girls (38.5 ml.kg · min−1 vs. 37.0 ml.kg · min−1, respectively, P < 0.05), and girls in late puberty had significantly lower cardiorespiratory fitness (36.0 ml.kg · min−1) than girls in early (39.7 ml.kg ·min−1) and middle (38.8 ml.kg · min−1) stages of puberty. After controlling for vigorous PA and grade, the independent associations between fitness and race, [F(2923) = 4.956, P = .007] and fitness and puberty [F(2921) = 21.690, P < 0.001] remained significant. There was a non-significant interaction effect of race and puberty on fitness, before and after controlling for vigorous PA and grade.

Discussion

This study examined independent and interactive associations between pubertal development and race with cardiorespiratory fitness in adolescent girls, adjusting for vigorous PA. AA race and late pubertal stage were associated with significantly lower cardiorespiratory fitness, and the associations were not explained by variation in vigorous PA. The non-significant interaction effect of race and puberty on fitness suggests that race and pubertal development influence fitness independently.

The greater cardiorespiratory fitness among Caucasian girls when compared with AA girls is consistent with previous findings (e.g., Pivarnik et al., 1995; Shaibi et al., 2006). Research has indicated that lower hemoglobin levels, a lower proportion of Type I muscle fibers, and racial differences in muscle physiology are likely to play a role in explaining the lower fitness of AAs (Ama et al., 1986; Pivarnik et al., 1995; Roy et al., 2006). Previous research has also suggested that lower PA among AA youth may contribute to lower cardiorespiratory fitness among this racial group (Lohman et al., 2008), although few studies have examined this contention. The current results do not indicate that differences in vigorous PA, explain the lower cardiorespiratory fitness among AA youth. Consistent with this finding, Sirard et al. (2008) compared AA and Caucasian youth, and reported lower PA among the AA children, but no racial differences in weight-relative cardiorespiratory fitness, indicating that differences in PA were not reflected in racial differences in fitness. In addition, Ceaser, Fitzhugh, Thompson, and Basset Jr (2013) examined National Health and Nutrition Examination Survey (NHANES) data on fitness, race, and PA among adults, and reported that race remained a significant predictor of VO2max after controlling for PA. Collectively, the findings suggest that racial differences in cardiorespiratory fitness are not reflective of variation in vigorous PA, and the extant literature supports the role of physiological differences in explaining the lower cardiorespiratory fitness of AAs.

The finding of a negative association between pubertal development and weight-relative fitness among females has been well-documented (Malina et al., 2004; Mota et al., 2002; Ortega et al., 2008), and the current investigation extends this finding to a large cohort of AA adolescents. Only one other study was found that provided cardiorespiratory fitness values by pubertal status for different racial groups. Conflicting with findings of the current study, results indicated pubertally advanced Black youth had higher weight-relative VO2max values compared with prepubertal Black youth, and pubertally advanced White youth had higher weight-relative VO2max values than prepubertal White youth (Andreacci et al., 2004). The inclusion of males and females in the calculation of average VO2max values in the study by Andreacci et al. (2004) may account for the unexpected findings, as weight-relative fitness is known to decline in girls but increase in boys, postpuberty (Malina et al., 2004; Mota et al., 2002). The current study thus adds to a limited evidence reporting the association between fitness and puberty among AA youth.

Variation in vigorous PA did not explain the lower cardiorespiratory fitness of girls in late puberty, and this finding is consistent with a small body of previous literature (Nes, Østhus, Welde, Aspenes, & Wisløff, 2013; Ortega et al., 2008). According to Mota et al. (2002), a puberty-driven increase in body fat in females may explain the decline in weight-relative fitness during the adolescent years. Previous literature has reported that body fat is a stronger predictor of fitness in youth when compared with variables such as height and PA (Janz & Mahoney, 1997; Mota et al., 2002). Neither body fat nor BMI were treated as covariates in this study due to the inclusion of BMI in the prediction equation for VO2max (Cureton et al., 1995). Controlling for BMI-z score or body fat in the statistical analyses would not have been appropriate because body mass was accounted for.

The influence of puberty on cardiorespiratory fitness may be partially mediated by PA, as the current findings and previous literature indicate a negative association between pubertal development and PA (Cumming, Sherar, Esliger, Riddoch, & Malina, 2014; Smart et al., 2012) and positive association between PA and fitness (Baquet et al., 2006; Katzmarzyk et al., 1998). However, the relationship between PA and fitness is typically weak among youth (Pfeiffer et al., 2007), particularly when compared to the association between body fat and fitness (Janz & Mahoney, 1997). Thus, the inclusion of an indicator of body mass in the calculation of VO2max may be overshadowing any vigorous PA-related variation in cardiorespiratory fitness in the current study. The relationships among fitness, fatness, PA, and puberty are complex and future research using longitudinal study designs would help to clarify the causal pathways between these variables, and independent versus interactive influences of these variables on fitness.

The interaction effect of puberty and race on VO2max was non-significant, suggesting that puberty and race are independently associated with cardiorespiratory fitness among this cohort of low SES, urban, adolescent girls. Supporting the non-significant interaction effect, the previous discussion highlights that these variables influence fitness via different mechanisms. Additionally, lower fitness and lower hemoglobin levels among AAs have been reported among prepubertal samples (Andreacci et al., 2004; Trowbridge et al., 1997), suggesting that racial differences in fitness and physiological determinants of VO2max are present prior to puberty. The mean age of the current sample was 12.2 years and the majority of participants were in the late stages of pubertal development, particularly among the AA subgroup. Thus, to substantiate the current finding of no interactive effect of puberty and race on cardiorespiratory fitness, replication of this study with a younger cohort, among which variation in pubertal development would be greater, is necessary.

Strengths of this study include the large sample size and representation of AA adolescent girls. The findings make a valuable contribution to a limited body of literature examining the influence of puberty on fitness in AA females and the role of vigorous PA in explaining racial and pubertal differences in fitness. The recruitment of a low SES sample provides valuable information about a population demographic at increased risk for chronic disease. Limitations of this study include controlling for school grade, rather than decimal age, in the statistical analyses, the estimation of VO2max using a field test rather than a laboratory-based test with expired gases collected, and a self-reported method of assessing pubertal status. The large sample size and school-based data collection sessions made the use of indirect calorimetry and objective assessment of pubertal status not feasible. Time spent sedentary and screen time are related to fitness in youth (Fröberg & Raustorp, 2014; Hardy, Dobbins, Denney-Wilson, Okely, & Booth, 2009; Mitchell, Pate, & Blair, 2012); the role of screen time in the relationships among race, puberty, and fitness has not been explored and represents an area for future research.

The current study indicates that among this sample of low SES, urban adolescent girls, race and pubertal development were independent predictors of fitness. While vigorous PA was significantly associated with pubertal development and VO2max, differences in vigorous PA did not explain pubertal or racial differences in cardiorespiratory fitness. AA girls in later stages of puberty should be considered a priority group for fitness interventions. While physiological predictors of racial differences in fitness have been identified, few modifiable factors are known; in the endeavour to improve the long-term health prospects of AA youth, future research should endeavour to identify predictors of fitness among this racial group, which are amenable to change and can be targeted in public health interventions.

Acknowledgments

The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. The authors appreciate the support received from school administrators, teachers, and other staff regarding the study. The authors would like to acknowledge Stacey M. Wesolek, former project manager, and Patrice Patrick-Banks and Ann Kostin-McGill, former intervention coordinators, for their tireless efforts to manage their respective areas. They are also grateful to Michigan State University undergraduate and graduate nursing and kinesiology students who have assisted us in various ways to conduct the study. Lastly, they thank the young female participants and their parents/guardians for their interest.

Funding

The study is funded by a 5-year grant (2011–2016), R01HL109101, $3,657,706, from the National Heart, Lung, and Blood Institute (NHLBI) at the National Institutes of Health (NIH); PI: L. B. Robbins, Michigan State University College of Nursing.

Footnotes

Conflict of interest

All authors declare that they will not benefit (financially or otherwise) from the applications of this research.

Disclosure statement

No potential conflict of interest was reported by the authors.

References

  1. Ama PF, Simoneau JA, Boulay MR, Serresse O, Theriault G, Bouchard C. Skeletal muscle characteristics in sedentary black and Caucasian males. Journal of Applied Physiology. 1986;61:1758–1761. doi: 10.1152/jappl.1986.61.5.1758. [DOI] [PubMed] [Google Scholar]
  2. Andreacci JL, Robertson RJ, Dubé JJ, Aaron DJ, Balaskeran G, Arslanian SA. Comparison of maximal oxygen consumption between black and white prepubertal and pubertal children. Pediatric Research. 2004;56:706–713. doi: 10.1203/01.PDR.0000141521.77229.8D. [DOI] [PubMed] [Google Scholar]
  3. Baquet G, Twisk JW, Kemper HC, Van PE, Berthoin S. Longitudinal follow-up of fitness during childhood: Interaction with physical activity. American Journal of Human Biology. 2006;18:51–58. doi: 10.1002/(ISSN)1520-6300. [DOI] [PubMed] [Google Scholar]
  4. Bradley CB, McMurray RG, Harrell JS, Deng S. Changes in common activities of 3rd through 10th graders: The CHIC study. Medicine and Science in Sports and Exercise. 2000;32:2071–2078. doi: 10.1097/00005768-200012000-00017. [DOI] [PubMed] [Google Scholar]
  5. Brooks-Gunn J, Warren MP, Rosso J, Gargiulo J. Validity of self-report measures of girls’ pubertal status. Child Development. 1987;58:829–841. doi: 10.2307/1130220. [DOI] [PubMed] [Google Scholar]
  6. Carskadon MA, Acebo C. A self-administered rating scale for pubertal development. Journal of Adolescent Health. 1993;14:190–195. doi: 10.1016/1054-139X(93)90004-9. [DOI] [PubMed] [Google Scholar]
  7. Ceaser TG, Fitzhugh EC, Thompson DL, Basset DR., Jr Association of physical activity, fitness, and race: NHANES 1999–2004. Medicine and Science in Sports and Exercise. 2013;45:286–293. doi: 10.1249/MSS.0b013e318271689e. [DOI] [PubMed] [Google Scholar]
  8. Cumming SP, Sherar LB, Esliger DW, Riddoch CJ, Malina RM. Concurrent and prospective associations among biological maturation, and physical activity at 11 and 13 years of age. Scandinavian Journal of Medicine & Science in Sports. 2014;24:e20–28. doi: 10.1111/sms.2014.24.issue-1. [DOI] [PubMed] [Google Scholar]
  9. Cureton KJ, Sloniger MA, O’Bannon JP, Black DN, McCormack WP. A generalized equation for prediction of VO2 peak from one-mile run/walk performance in youth. Medicine and Science in Sports and Exercise. 1995;27:445–451. doi: 10.1249/00005768-199503000-00023. [DOI] [PubMed] [Google Scholar]
  10. Dabelea D, Mayer-Davis EJ, Saydah S, Imperatore G, Linder B, Divers J … SEARCH for Diabetes in Youth Study. Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. Journal of the American Medical Association. 2014;311:1778–1786. doi: 10.1001/jama.2014.3201. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Denton SJ, Trenell MI, Plötz T, Savory LA, Bailey DP, Kerr CJ. Cardiorespiratory fitness is associated with hard and light intensity physical activity but not time spent sedentary in 10–14 year old school children: The HAPPY study. PLoS One. 2013;8:e61073. doi: 10.1371/journal.pone.0061073. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG. Calibration of two objective measures of physical activity for children. Journal of Sports Sciences. 2008;26:1557–1565. doi: 10.1080/02640410802334196. [DOI] [PubMed] [Google Scholar]
  13. Fröberg A, Raustorp A. Objectively measured sedentary behaviour and cardio-metabolic risk in youth: A review of evidence. European Journal of Pediatrics. 2014;173:845–860. doi: 10.1007/s00431-014-2333-3. [DOI] [PubMed] [Google Scholar]
  14. Hardy LL, Dobbins TA, Denney-Wilson EA, Okely AD, Booth ML. Sedentariness, small-screen recreation, and fitness in youth. American Journal of Preventive Medicine. 2009;36:120–125. doi: 10.1016/j.amepre.2008.09.034. [DOI] [PubMed] [Google Scholar]
  15. Herman-Giddens ME, Slora EJ, Wasserman RC, Bourdony CJ, Bhapkar MV, Koch GG, Hasemeier CM. Secondary sexual characteristics and menses in young girls seen in office practice: A study from the pediatric research in office settings network. Pediatrics. 1997;99:505–512. doi: 10.1542/peds.99.4.505. [DOI] [PubMed] [Google Scholar]
  16. Hunter GR, Weinsier RL, McCarthy JP, Enette Larson-Meyer D, Newcomer BR. Hemoglobin, muscle oxidative capacity, and VO2max in African-American and Caucasian women. Medicine and Science in Sports and Exercise. 2001;33:1739–1743. doi: 10.1097/00005768-200110000-00019. [DOI] [PubMed] [Google Scholar]
  17. Jago R, Edwards M, Sebire S, Cooper AR, Powell JE, Bird EL, Blair PS. Bristol girls dance project (BGDP): Protocol for a cluster randomised controlled trial of an after-school dance programme to increase physical activity among 11–12year old girls. BMC Public Health. 2013;13:1003. doi: 10.1186/1471-2458-13-1003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Janz KF, Mahoney LT. Three-year follow-up of changes in aerobic fitness during puberty: The muscatine study. Research Quarterly for Exercise and Sport. 1997;68:1–9. doi: 10.1080/02701367.1997.10608861. [DOI] [PubMed] [Google Scholar]
  19. Katzmarzyk PT, Malina RM, Song TM, Bouchard C. Physical activity and health-related fitness in youth: A multivariate analysis. Medicine and Science in Sports and Exercise. 1998;30:709–714. doi: 10.1097/00005768-199805000-00011. [DOI] [PubMed] [Google Scholar]
  20. Kimm SYS, Barton BA, Obarzanek E, McMahon RP, Sabry ZI, Waclawiw MA, Daniels SR. Racial divergence in adiposity during adolescence: The NHLBI growth and health study. Pediatrics. 2001;107(3):e34–e34. doi: 10.1542/peds.107.3.e34. [DOI] [PubMed] [Google Scholar]
  21. Lohman TG, Ring K, Pfeiffer K, Camhi S, Arredondo E, Pratt C, Webber LS. Relationships among fitness, body composition, and physical activity. Medicine and Science in Sports and Exercise. 2008;40:1163–1170. doi: 10.1249/MSS.0b013e318165c86b. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. Champaign, IL: Human Kinetics; 1988. [Google Scholar]
  23. Malina RM, Bouchard C, Bar-Or O. Growth, maturation, and physical activity. 2. Champaign, IL: Human Kinetics; 2004. [Google Scholar]
  24. Matthews CE, Hagströmer M, Pober DM, Bowles HR. Best practices for using physical activity monitors in population-based research. Medicine & Science in Sports & Exercise. 2012;44:S68–S76. doi: 10.1249/MSS.0b013e3182399e5b. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Mitchell JA, Pate RR, Blair SN. Screen-based sedentary behavior and cardiorespiratory fitness from age 11 to 13. Medicine & Science in Sports & Exercise. 2012;44:1302–1309. doi: 10.1249/MSS.0b013e318247cd73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Mota J, Guerra S, Leandro C, Pinto A, Ribeiro JC, Duarte JA. Association of maturation, sex, and body fat in cardiorespiratory fitness. American Journal of Human Biology. 2002;14:707–712. doi: 10.1002/(ISSN)1520-6300. [DOI] [PubMed] [Google Scholar]
  27. Nes BM, Østhus IB, Welde B, Aspenes ST, Wisløff U. Peak oxygen uptake and physical activity in 13- to 18-year-olds: The young HUNT study. Medicine and Science in Sports and Exercise. 2013;45:304–313. doi: 10.1249/MSS.0b013e318271ae4d. [DOI] [PubMed] [Google Scholar]
  28. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in body mass index among US children and adolescents, 1999–2010. Journal of the American Medical Association. 2012;307:483–490. doi: 10.1001/jama.2012.40. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Ortega FB, Ruiz JR, Labayen I, Redondo C, Bredenassel C, Gómez S … f Avena Study Group. High fitness is associated with healthier programming of body composition at adolescence. American Journal of Human Biology. 2008;20:732–734. doi: 10.1002/ajhb.20813. [DOI] [PubMed] [Google Scholar]
  30. Patnode CD, Lytle LA, Erickson DJ, Sirard JR, Barr-Anderson DJ, Story M. Physical activity and sedentary activity patterns among children and adolescents: A latent class analysis approach. Journal of Physical Activity and Health. 2011;8:457–467. doi: 10.1123/jpah.8.4.457. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Petersen A, Crockett L, Richards M, Boxer A. A self-report measure of pubertal status: Reliability, validity, and initial norms. Journal of Youth and Adolescence. 1988;17:117–133. doi: 10.1007/BF01537962. [DOI] [PubMed] [Google Scholar]
  32. Pfeiffer KA, Dowda M, Dishman RK, Sirard JR, Pate RR. Cardiorespiratory fitness in girls – change from middle to high school. Medicine & Science in Sports & Exercise. 2007;39:2234–2241. doi: 10.1249/mss.0b013e318156aa60. [DOI] [PubMed] [Google Scholar]
  33. Pivarnik JM, Bray MS, Hergenroeder AC, Hill RB, Wong WW. Ethnicity affects aerobic fitness in U.S. adolescent girls. Medicine & Science in Sports & Exercise. 1995;27:1635–1638. doi: 10.1249/00005768-199512000-00009. [DOI] [PubMed] [Google Scholar]
  34. Robbins LB, Pfeiffer KA, Vermeesch A, Resnicow K, You Z, An L, Wesolek SM. “Girls on the Move” intervention protocol for increasing physical activity among low-active underserved urban girls: A group randomized trial. BMC Public Health. 2013;13:474–485. doi: 10.1186/1471-2458-13-474. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Rosner B, Cook NR, Daniels S, Falkner B. Childhood blood pressure trends and risk factors for high blood pressure: The NHANES experience 1988–2008. Hypertension. 2013;62:247–254. doi: 10.1161/HYPERTENSIONAHA.111.00831. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Roy JLP, Hunter GR, Fernandez JR, McCarthy JP, Larson-Meyer DE, Blaudeau TE, Newcomer BR. Cardiovascular factors explain genetic background differences in VO2max. American Journal of Human Biology. 2006;18:454–460. doi: 10.1002/(ISSN)1520-6300. [DOI] [PubMed] [Google Scholar]
  37. Shaibi GQ, Ball GDC, Goran MI. Aerobic fitness among Caucasian, African American, and Latino youth. Ethnicity and Disease. 2006;16:120–125. [PubMed] [Google Scholar]
  38. Silva G, Aires L, Martins C, Mota J, Oliveira J, Ribeiro JC. Cardiorespiratory fitness associates with metabolic risk independent of central adiposity. International Journal of Sports Medicine. 2013;34:912–916. doi: 10.1055/s-00000028. [DOI] [PubMed] [Google Scholar]
  39. Sirard JR, Pfeiffer KA, Dowda M, Pate RR. Race differences in activity, fitness, and BMI in female eighth graders categorized by sports participation status. Pediatric Exercise Science. 2008;20:198–210. doi: 10.1123/pes.20.2.198. [DOI] [PubMed] [Google Scholar]
  40. Smart JE, Cumming SP, Sherar LB, Standage M, Neville H, Malina RM. Maturity associated variance in physical activity and health-related quality of life in adolescent females: A mediated effects model. Journal of Physical Activity and Health. 2012;9:86–95. doi: 10.1123/jpah.9.1.86. [DOI] [PubMed] [Google Scholar]
  41. The Cooper Institute. Fitnessgram and activitygram test administration manual. Champaign, IL: Human Kinetics; 2010. [Google Scholar]
  42. Trowbridge CA, Gower BA, Nagy TR, Hunter GR, Treuth MS, Goran MI. Maximal aerobic capacity in African American and Caucasian prepubertal children. American Journal of Physiology. 1997;273:E809–E814. doi: 10.1152/ajpendo.1997.273.4.E809. [DOI] [PubMed] [Google Scholar]
  43. Wong WW, Butte NF, Ellis KJ, Hergenroeder AC, Hill RB, Stuff JE, Smith E. Pubertal African American girls expend less energy at rest and during physical activity than Caucasian girls. Journal of Clinical Endocrinology and Metabolism. 1999;84:906–911. doi: 10.1210/jcem.84.3.5517. [DOI] [PubMed] [Google Scholar]

RESOURCES