[Skip to Navigation]
Sign In
December 2006

Objectively Measured Physical Activity in Sixth-Grade Girls

Author Affiliations

Author Affiliations: Department of Exercise Science, University of South Carolina, Columbia (Dr Pate); Departments of Nutrition and Epidemiology, The University of North Carolina at Chapel Hill (Dr Stevens); National Heart, Lung, and Blood Institute, Bethesda, Md (Dr Pratt); Department of Psychology, San Diego State University, San Diego, Calif (Dr Sallis); Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia (Dr Schmitz); Department of Biostatistics, Tulane University, New Orleans, La (Dr Webber); Department of Health and Human Performance, Iowa State University, Ames (Dr Welk); and Department of Kinesiology, University of Maryland, College Park (Dr Young).

Arch Pediatr Adolesc Med. 2006;160(12):1262-1268. doi:10.1001/archpedi.160.12.1262

Objectives  To describe the objectively measured physical activity characteristics of a diverse sample of sixth-grade girls, to examine influences on physical activity, and to report compliance with physical activity guidelines.

Design  Cross-sectional study.

Setting  Six locations across the United States.

Participants  A total of 1578 sixth-grade girls. Accelerometers were worn for 7 days, and data for 6 days were included in the analyses.

Main Exposures  Race/ethnicity, free or reduced-price lunch, and geographic region.

Main Outcome Measures  Six operational definitions of adequate activity (60 or 30 minutes of daily moderate to vigorous physical activity at or above 4.6, 3.8, or 3.0 metabolic equivalents) were used to examine whether girls met physical activity guidelines.

Results  Average times spent in sedentary, light, moderate, and vigorous activities were 460, 342, 18, and 6 min/d, respectively. White girls were more active than girls in other race/ethnic groups, and girls who did not receive free or reduced-price lunch were more active than girls who did. Girls in western states were most active. Percentages of girls in compliance with the 6 thresholds for adequate activity varied widely and ranged from 0.6% to 100.0%.

Conclusions  When physical activity is measured objectively and a 4.6–metabolic equivalents cut point for moderate to vigorous physical activity is used, most sixth-grade girls do not meet guidelines for adequate physical activity. One notable finding was the effect of different accelerometer scoring protocols on estimates of compliance. Conceptual and empirical work is needed to define appropriate physical activity for youth using objective physical activity measures.

Numerous government health agencies and private organizations have emphasized the importance of physical activity to public health.1-4 Among children and adolescents, higher levels of physical activity are associated with reduced risk of obesity, more favorable cardiovascular risk profiles, greater lean weight and bone mass, and enhanced psychological well-being.5-9 Because of the immediate and likely long-term benefits of physical activity for young people, several organizations have issued guidelines on participation in physical activity for children and adolescents. The consensus recommendation is that young people should participate in moderate to vigorous physical activity (MVPA) for at least 60 minutes on most days.10-13

The significance of physical activity to the health of children and adolescents has led to increased interest in developing surveillance systems to monitor compliance with physical activity guidelines in young people.14,15 Most large-scale studies of physical activity behavior have relied on self-report measures, but this approach has clear limitations for use with children.16 Because accelerometers have not yet been used in a surveillance capacity to evaluate large samples of youth in the United States, there is uncertainty regarding activity levels of youth and the percentage who meet current physical activity recommendations.17 Although accelerometers are objective measures, there are challenges in using them in studies of children and youth.18 For example, there is no consensus on the methods of converting accelerometer output to minutes of physical activity,19 so it is important to explore the effect of different accelerometer scoring protocols on the interpretation of results.

Results of previous studies in young people consistently have shown that physical activity decreases with increasing age and that girls tend to be less active than boys.14,15,17,20-22 Furthermore, there is some evidence that physical activity is associated with demographic factors such as socioeconomic status,23,24 race/ethnicity,20,25 and geographic location.1 However, accelerometers have not been used in previous studies to examine the associations with these demographic factors in population-based samples of youth.

To respond to the need to increase physical activity in girls, the National Heart, Lung, and Blood Institute is sponsoring the Trial of Activity for Adolescent Girls (TAAG), a multicenter study designed to promote physical activity in middle-school girls. The primary goal of TAAG is to determine if a physical activity intervention that links schools to community organizations reduces the age-related decrease in MVPA in girls in sixth through eighth grades. The purposes of this article are to describe the baseline physical activity characteristics of a diverse sample of sixth-grade girls by using an objective measure of physical activity and to examine the relation of race/ethnicity, socioeconomic status, and geographic region to physical activity levels in those girls. The percentage of girls meeting physical activity guidelines and the influence of varying accelerometer scoring protocols also are reported.



This is a cross-sectional examination of sixth-grade girls recruited from 6 communities in the United States. University-based field centers were located in and around the cities of Tucson, Arizona; San Diego, California; New Orleans, Louisiana; Washington, DC, and Baltimore, Maryland; Minneapolis, Minnesota; and Columbia, South Carolina. Six middle schools in each community were recruited for the study. To be eligible, schools had to have a minimum of 90 girls in the eighth grade and offer physical education at all grade levels. Schools were selected for convenience but with ethnic diversity as a goal. Within each school, girls were selected by means of random sampling of all eligible sixth-grade girls. Girls were considered eligible unless they had a health problem that contraindicated physical activity or if a school administrator requested that the girl not be included in the study. Study coordination was provided by The University of North Carolina at Chapel Hill and the National Heart, Lung, and Blood Institute Project Office.

The study was approved by the participating universities' institutional review boards. Each participant's parent or guardian provided written informed consent, and all subjects assented to participation. Consent for measurement was obtained for 1721 girls. Differences in measurement rates across racial and ethnic groups were not significant. For the analyses described in this article, girls who were missing data for ethnicity (n = 6), free or reduced-price lunch (n = 27), or physical activity (n = 110) were excluded. Thus, 1578 (91.7%) of 1721 girls with consent were included in the analysis sample.


Girls classified themselves in 1 of 5 race/ethnicity categories: Asian American, African American, Hispanic, white, or other. Girls were categorized as Hispanic if they indicated Hispanic ethnicity on the questionnaire. Otherwise, girls who indicated more than one race group or who selected “Native Hawaiian or other Pacific Islanders” were classified as “other.” Socioeconomic status was assessed by asking each girl if she received free or reduced-price school lunch. The answer set included the options “yes,” “no,” and “don't know.” The investigators found that reported school lunch eligibility associated well with US Census figures for neighborhood income among TAAG subjects. Date of birth was self-reported. Weight and height were measured by using standard protocols.

Physical activity was measured by using accelerometers (MTI model 7164; Actigraph, Ft Walton Beach, Fla). Participating girls wore an accelerometer during most waking hours for 7 consecutive days. Accelerometers were initialized before data collection and were set to begin collecting data at 5:00 AM on the day after they were distributed to participants; thus, data for 6 complete days were available for analysis. Data were collected and stored in 30-second intervals. Trained and certified staff members provided detailed oral and written instruction on how and when to wear the monitors. Girls wore the accelerometer on their right hip, attached to a belt. They were asked to wear it all the time, except at night while sleeping and while bathing or swimming.

Measurement coordinators from each field site were trained and certified at a centralized training event. The TAAG Measurement Committee provided oversight for all measures. On the basis of the recommendations of a TAAG preliminary study, all data were collected during at least 2 separate calendar weeks in each participating school to minimize the school-level intraclass correlation between girls within a school.26

Data reduction

Data from the accelerometers were downloaded to the same laptop computer that was used to initialize them. Accelerometer data were reduced by using methods previously described by Treuth et al.19 Briefly, missing accelerometry data within a girl's 6-day record were replaced via imputation based on the Expectation Maximization algorithm; details on the imputation methods are provided elsewhere.27 On average, approximately 12 hours of data per girl were imputed across the 6 days of data collection. The count thresholds (counts × 30 seconds-1) established by Treuth and colleagues19 in a study of eighth-grade girls were used for the activity intensities of interest: sedentary (≤50), light physical activity (51-1499), moderate physical activity (1500-2600), and vigorous physical activity (>2600).

The primary analyses performed in this study were conducted by using an accelerometry count cut point for moderate-intensity physical activity (1500 counts per 30 seconds) corresponding to 4.6 metabolic equivalents (METs; 1 MET = 3.5 mL O2 × kg-1 × min-1). Thirty-second increments with counts at or above that level were summed across the period between 6:00 AM and midnight to determine minutes of MVPA. Also, for each time increment above the 4.6-MET cut point, METs were estimated by using a regression equation.19 The MET-weighted minutes of MVPA were calculated as the sum of the MET values for all time increments above the 4.6-MET cut point. As previously reported, the 4.6-MET cut point was selected as the intensity that best discriminated between slow and brisk walking in eighth-grade girls.19 Two additional cut points for defining MVPA were used in some analyses. A 3.0-MET cut point (579 counts per 30 seconds) was used because it has been taken as the threshold for moderate-intensity physical activity in some studies of youth17,28,29 and is typically used in studies of adults.1,30 A 3.8-MET cut point (1047 counts per 30 seconds) was used because it is the intensity midway between the means for slow and brisk walking in the accelerometry calibration study.19

Because accelerometry is a recent innovation in public health surveillance of physical activity, there is no broad consensus as to how physical activity guidelines should be defined in terms of accelerometry data. Accordingly, compliance with physical activity guidelines was calculated by using 6 different operational definitions. In the first definition, a girl was considered compliant if she had accumulated 60 or more minutes of physical activity at or above a cut point of 4.6 METs on 4 or more of the 6 days on which the accelerometer recorded physical activity data. The second definition was similar but used the 3.8-MET cut point. A third definition used a cut point of 3.0 METs, a standard often used with adults.1 We also examined compliance by using 30 min/d of physical activity as the standard instead of 60 minutes because 30 minutes of daily activity is the consensus guideline for adults.1

Statistical methods

Data were analyzed by using commercially available software (Statistical Analysis System, version 8.2, PROC MIXED and PROC GLIMMIX; SAS Institute, Inc, Cary, NC). Unadjusted means and frequencies were calculated. Mixed models were used to test for group differences in mean levels of activity, and generalized linear models with a logit link function were used to test for group differences in the percentage of girls who met physical activity guidelines. By treating “school” as a random effect, these models account for the correlation in responses resulting from clustering of girls within schools. Means, adjusted for clustering of girls nested within schools, and percentages were estimated by using least squares means based on the observed marginal (the OM option in SAS) distributions of categorical variables. Three-way and 2-way interactions between location, ethnicity, and lunch subsidy were tested.


Table 1 describes characteristics of the girls according to state, arbitrarily listed from west to east. The mean (SD) age of the girls ranged from 11.7 (0.4) years to 12.3 (0.7) years across the 6 sites. Each of 4 ethnic groups was represented at each of the 6 study sites, although distributions varied considerably. In Arizona, Maryland, Minnesota, and South Carolina, the highest percentage of girls was white; in California, the highest percentage was Hispanic; and in Louisiana, the highest percentage was African American. Fewer than 10 Asian American girls participated at the Arizona and South Carolina sites, and fewer than 10 African American girls participated at the Arizona and Minnesota sites. Overall, 706 white girls, 344 African American girls, 343 Hispanic girls, and 61 Asian American girls participated. The percentage of girls who reported receiving subsidized school lunch ranged from 23.8% in Minnesota to 76.2% in Louisiana. Across the sites, 4.2% to 25.7% of girls did not know if they received a subsidy for school lunch.

Table 1. 
Descriptive Characteristics of Girls According to State
Descriptive Characteristics of Girls According to State

Table 2 shows the adjusted mean minutes and unadjusted overall mean minutes of sedentary, light, moderate, and vigorous physical activity according to location, ethnicity, and school lunch subsidy status. Overall, on a daily basis, girls spent 459.9 minutes in sedentary activity, 341.6 minutes in light activity, 18.1 minutes in moderate activity, and 5.6 minutes in vigorous activity. Girls in Arizona and California had the smallest number of sedentary minutes and the largest number of moderate and vigorous minutes. Examination of adjusted means showed that Asian American girls had the largest number of sedentary minutes and the smallest number of moderate and vigorous minutes compared with the other racial/ethnic groups. White girls were more active than girls in other race/ethnic groups. Girls who reported they did not receive subsidized school lunch had the largest number of moderate and vigorous minutes.

Table 2. 
Minutes of Physical Activity and MET-Weighted Minutes of Physical Activity According to Geographic Location, Ethnicity, and Receipt of Subsidy for School Lunch*
Minutes of Physical Activity and MET-Weighted Minutes of Physical Activity According to Geographic Location, Ethnicity, and Receipt of Subsidy for School Lunch*

As a first step in the examination of the independent effects of location, race/ethnicity, and subsidized school lunch, we tested the 3-way interaction and found that it was not statistically significant for any of the physical activity variables. We then tested 2-way interactions. Two-way interactions with school lunch subsidy were not significant, but the interaction between location and race/ethnicity was significant (P<.05) for sedentary and vigorous activity, moderate and vigorous activity, and MET-weighted MVPA with the 4.6-MET cut point. Visual examination of plots of residuals indicated that African American girls in Arizona were likely responsible for the interaction between location and race/ethnicity. African American girls living in Arizona were more active than African American girls in other locations.

Table 3 shows the percentage of girls meeting a physical activity guideline, which differed markedly depending on the operational definition used. Using the guideline of 60 min/d at or above the 4.6-MET cut point, we found that less than 1% of girls met the guideline. However, when the lower cut points of 3.8 and 3.0 METs were used with the same requirement of 60 minutes, the percentage increased to 11.8% and 87.7%, respectively. Reducing the amount of time of MVPA from 60 to 30 minutes resulted in 16.1% of girls meeting the standard when the 4.6-MET cut point was used. When the 3.8- and 3.0-MET cut points were used, 73.3% and 100.0% of girls met the standard. The differences were highly significant for all pairwise comparisons.

Table 3. 
Adjusted Percentage of Girls Meeting Guidelines for MVPA According to Geographic Location, Ethnicity, and Receipt of Subsidy for School Lunch*
Adjusted Percentage of Girls Meeting Guidelines for MVPA According to Geographic Location, Ethnicity, and Receipt of Subsidy for School Lunch*


This study is the first to use an objective measure of physical activity to describe the physical activity levels of a large and diverse sample of American youth. Accelerometers were worn by more than 1500 sixth-grade girls in 6 widely separated geographic locations. Intensity-weighted time spent in MVPA was higher in girls residing in western states compared with those living in other regions. Activity was higher in white girls than in ethnic minority groups. Also, when we used school lunch subsidy as an indicator of socioeconomic status, girls in the higher socioeconomic stratum were more active than girls in the lower socioeconomic status group.

The overall sample of sixth-grade girls engaged in an average of 24 minutes of MVPA per day. Of this total, less than 6 min/d were of vigorous intensity. Several expert panels have recommended that youth participate in at least 60 minutes of MVPA per day, and this recommendation was recently reaffirmed by a panel convened by the US Centers for Disease Control and Prevention.13 The findings of this study suggest that most sixth-grade girls are well below the prevailing public health guideline for physical activity. However, it should be noted that, in the present study as in previous studies, physical activity showed high interindividual variability. With a standard deviation for daily minutes of MVPA of 11.8 minutes, we could expect 95% of girls to accumulate approximately 0 to 50 minutes of MVPA (±2 SD of the mean). The observation that physical activity levels differed across geographic areas is consistent with previous surveys based on self-report measures. In the 2003 Youth Risk Behavior Survey, high school girls in the western states reported participating in more vigorous physical activity than did girls in other regions.15 Girls in the southern states reported the lowest level of vigorous physical activity, and those in the eastern and midwestern states reported activity levels between those of girls in the western and southern regions. A similar pattern was observed in the present study. Activity levels were lowest in South Carolina and Louisiana, slightly higher in Maryland and Minnesota, and highest in Arizona and California. The geographic pattern for time spent being sedentary was, in general, inversely related to the time spent in MVPA, with girls in Arizona and California spending less time being sedentary than girls at the other sites.

Results of previous studies showed that white adolescents were more physically active than adolescents from other race/ethnic groups,20,25 and results of a national survey showed white youth reported more vigorous physical activity than African American or Hispanic youth.15 In TAAG, white girls had slightly higher minutes of moderate and vigorous physical activity than girls in the other race/ethnic groups and had the highest MET-weighted MVPA. White girls had a higher prevalence than African American or Hispanic girls of meeting the 60-minute MVPA guidelines. However, the differences among white, African American, and Hispanic girls were small for minutes of moderate and vigorous physical activity considered separately. Few investigators have evaluated the physical activity behavior of Asian American girls. Although the present sample was relatively small, Asian American girls consistently had the lowest levels of physical activity and highest levels of sedentary behavior. These findings of race/ethnic differences in large samples of adolescents by using an objective measure of physical activity confirm the disparities reported in studies that used self-report measures.31-33 These disparities appear to increase as minority youth move from adolescence to adulthood,31 so interventions to promote physical activity in minority adolescents should be designated a public health priority. Research to improve understanding of the reasons for these disparities in physical activity also is needed.

Findings on the relationship between socioeconomic status and physical activity in adolescents have been inconsistent,20 possibly because a wide range of indicators of socioeconomic status have been used. Results of a large national survey, however, showed that vigorous physical activity was directly related to family income and educational level, after adjusting for other variables.31 In TAAG, reported free or reduced-price lunch was used as an indicator of family income, although approximately 12% of girls did not know their free or reduced-price lunch status. We found no variation in physical activity according to lunch subsidy status for sedentary, light, and moderate physical activity. However, girls who received no lunch subsidy engaged in significantly (P = .01) more vigorous physical activity than those who received a subsidy, similar to the findings in a national survey.31 This finding suggests that lower income adolescent girls may be less physically active, but the mean difference in the present study was small. A prudent interpretation is that adolescent-reported lunch subsidy status did not permit an adequate test of the relationship of socioeconomic status to physical activity.

One of the most notable findings of the present study was the effect of different accelerometer scoring protocols on estimates of physical activity. Although there is reasonable consensus that 3.0 METs is an appropriate cut point for moderate-intensity physical activity in adults,1 there is no such consensus in youth. Resting energy expenditure in children is higher than the assumed value of 3.5 mL/kg per minute for adults, so a value of 3.0 METs represents a lower relative activity level for youth. Differences in metabolic and biomechanical efficiency because of growth and maturation34 also alter the relationship between accelerometer counts and energy expenditure. A detailed calibration study conducted by the TAAG investigators determined that a value of 4.6 METs provides an appropriate cut point for moderate-intensity physical activity in adolescent girls.19 Operationally, this cut point was established by using accelerometer values that distinguished between a slow and a brisk walk. The activity levels reported with this cut point are considerably lower than those reported in other studies,17,35 but this result is because of the differences in cut points used in the different studies.

By definition, cut points impart a somewhat artificial categorization to continuous data. To provide an indication of how the cut point can influence the results, the data were analyzed by using 3.0- and 3.8-MET cut points, the former being a value commonly used in other studies.17 The percentage of girls meeting the current physical activity standard for youth (ie, 60 minutes of MVPA per day) varied dramatically, depending on the accelerometry cut point for moderate-intensity physical activity. With the 4.6-MET cut point, almost no girls met the standard. However, if a 3.0-MET cut point was used, 87.7% of girls met the standard. If the adult guideline (30 min/d) was used, all the girls met the standard with a 3.0-MET cut point, but only 16.1% met the 30-minute goal with the 4.6-MET cut point. Using the 3.8-MET cut point yielded compliance rates that were intermediate to those obtained with 4.6 and 3.0 METs but with a different pattern for the 60- and 30-minute standards. Only 11.8% of girls met the 60-minute 3.8-MET standard, but most of them met the 30-minute 3.8-MET standard (73.3%). The difference in compliance estimates because of choice of cut points makes it difficult to draw definitive conclusions about the activity patterns in these youth. The cut point of 3.0 provides a liberal estimate of activity patterns and favors sensitivity over specificity, whereas the 3.8 and 4.6 cut points provide more conservative estimates and favor specificity over sensitivity. Misclassification is always a concern when attempting to determine compliance with public health recommendations, and the dramatic differences demonstrate the need to develop consensus guidelines for reducing and reporting accelerometer data. In addition, conceptual and empirical work are likely to be needed to define health-related physical activity for youth. At present, physical activity guidelines for youth are based on a body of knowledge that experts agree is too limited.13 Hence, there is a need to strengthen the basis for physical activity guidelines and adopt improved methods for monitoring compliance with those guidelines.

Although absolute determinations of activity levels must be made with caution, this study demonstrates the potential for large-scale surveillance of activity patterns with accelerometers. Data from large and ethnically diverse samples were collected in a standardized way from 6 different regions throughout the United States. Obtaining objective physical activity information for 6 days is a major strength because this time frame is sufficient to capture reliable patterns.36 Sophisticated data reduction procedures and imputation methods were used to improve the accuracy and stability of the reported values. Using cut points for MVPA that were empirically determined specifically for adolescent girls is another strength. As the data suggest, the proportion of girls meeting national recommendations varies substantially on the basis of the MET cut point used. Given the increasing epidemic of obesity in adolescents,37,38 it is likely that the percentage of girls achieving sufficient physical activity is reflective of the data reported by using the 4.6-MET cut point. Without having conducted this prior work and being able to use this cut point, the data would suggest almost 90% of sixth-grade girls met recommendations.

Some limitations in the design should be noted. First, the data cannot be considered representative of youth in these regions. The participating TAAG sites were from predominantly urban settings, so the participating schools tended to be from the densely populated metropolitan areas. Second, subtle differences in population profiles, community characteristics, and seasonality could explain the interaction observed between location and ethnicity, but additional research will be needed to understand these influences and to capture possible differences between rural and urban youth. Designs that permit linkages with geographic information system and census data may be particularly helpful in examining the influence of social, environmental, and policy variables on physical activity. The results are limited in that not all geographic regions of the country were represented. Nevertheless, an ethnic/racially diverse sample was obtained. Although the schools were not randomly selected, the girls within the schools were randomly selected. Because girls were sampled from middle schools that met eligibility criteria for participation in the TAAG trial, there is a loss of generalizability. The TAAG schools offered physical education at all grade levels, and girls who participate in physical education may be more active than girls who do not.

The present study demonstrated the feasibility of using accelerometers to collect objective physical activity data in a large number of adolescents. Race/ethnic disparities in physical activity levels were documented, with white girls having slightly higher activity levels than girls of ethnic minority groups. On average, girls living in the West were more physically active than those in other parts of the United States. The difficulty of estimating the prevalence of meeting physical activity guidelines was demonstrated by the dramatic effect of different accelerometer protocols on prevalence rates. Because there is no consensus on the most suitable protocols, a high priority should be given to research to guide the development of accelerometer scoring protocols that can be applied across all ages.

Back to top
Article Information

Correspondence: Russell R. Pate, PhD, Department of Exercise Science, University of South Carolina, 921 Assembly St, Columbia, SC 29208 (rpate@gwm.sc.edu).

Accepted for Publication: August 3, 2006.

Author Contributions: Dr Pate had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Pate, Pratt, Sallis, Schmitz, Webber, and Young. Acquisition of data: Stevens, Schmitz, and Webber. Analysis and interpretation of data: Welk. Drafting of the manuscript: Pate, Stevens, Pratt, Sallis, Schmitz, and Welk. Critical revision of the manuscript for important intellectual content: Pratt, Schmitz, Webber, Welk, and Young. Statistical analysis: Stevens and Webber. Obtained funding: Pate, Stevens, Sallis, Webber, and Young. Administrative, technical, and material support: Pate, Pratt, Sallis, Webber, and Welk. Study supervision: Pate.

Financial Disclosure: None reported.

Funding/Support: The study was supported by grant 5U01HL066852 from the National Institutes of Health.

Acknowledgment: We thank Leslie Lytle, PhD, University of Minnesota, Minneapolis, and Timothy Lohman, PhD, University of Arizona, Tucson, for their leadership of the TAAG field centers in Minnesota and Arizona and Gaye Groover Christmus, MPH, University of South Carolina, Columbia, for assistance in developing and editing the manuscript.

US Department of Health and Human Services, Physical Activity and Health: A Report of the Surgeon General.  Atlanta, Ga US Dept of Health and Human Services/Centers for Disease Control1996;
 Physical activity and cardiovascular health: NIH Consensus Development Panel on Physical Activity and Cardiovascular Health  JAMA 1996;276241- 246PubMedGoogle ScholarCrossref
Williams  CLHayman  LLDaniels  SR  et al.  Cardiovascular health in childhood: a statement for health professionals from the Committee on Atherosclerosis, Hypertension, and Obesity in the Young (AHOY) of the Council on Cardiovascular Disease in the Young, American Heart Association  Circulation 2002;106143- 160[published correction appears in Circulation2002;106 (1178) PubMedGoogle ScholarCrossref
US Department of Health and Human Services, Healthy People 2010. 2nd ed Washington, DC US Dept of Health and Human Services2000;
Rowland  TW The role of physical activity and fitness in children in the prevention of adult cardiovascular disease  Prog Pediatr Cardiol 2001;12199- 203PubMedGoogle ScholarCrossref
Hager  RLTucker  LASeljaas  GT Aerobic fitness, blood lipids, and body fat in children  Am J Public Health 1995;851702- 1706PubMedGoogle ScholarCrossref
Hagberg  JMGoldring  DEhsani  AA  et al.  Effect of exercise training on the blood pressure and hemodynamic features of hypertensive adolescents  Am J Cardiol 1983;52763- 768PubMedGoogle Scholar
Armstrong  NSimons-Morton  B Physical activity and blood lipids in adolescents  Pediatric Exerc Sci 1994;6381- 405Google Scholar
Calfas  KJTaylor  WC Effects of physical activity on psychological variables in adolescents  Pediatric Exerc Sci 1994;6406- 423Google Scholar
Corbin  CBPangrazzi  RP Physical Activity for Children: A Statement of Guidelines.  Reston, Va National Association for Sport and Physical Education1998;
Sallis  JFPatrick  KBiddle  SedSallis  JFedCavill  NAed Physical activity guidelines for adolescents: consensus statement  Pediatric Exerc Sci 1994;6302- 314Google Scholar
Health Education Authority, Policy framework for young people and health-enhancing physical activity  Young and Active? Young People and Health-Enhancing Physical Activity—Evidence and Implications. London, England Health Education Authority1998;3Google Scholar
Strong  WBMalina  RMBlimkie  CJ  et al.  Evidence based physical activity for school-age youth  J Pediatr 2005;146732- 737PubMedGoogle ScholarCrossref
Grunbaum  JAKann  LKinchen  SA  et al.  Youth risk behavior surveillance—United States, 2001  MMWR Surveill Summ 2002;511- 62Google Scholar
Grunbaum  JAKann  LKinchen  SA  et al.  Youth risk behavior surveillance—United States, 2003  MMWR Surveill Summ 2004;531- 96[published corrections appear in MMWR Surveill Summ2004;53 (536) 2005;54 (608) Google Scholar
Sallis  JFSaelens  BE Assessment of physical activity by self-report: status, limitations, and future directions  Res Q Exerc Sport 2000;71(2 suppl)S1- S14[published correction appears in Res Q Exerc Sport2000;71 (409) PubMedGoogle ScholarCrossref
Pate  RRFreedson  PSSallis  JF  et al.  Compliance with physical activity guidelines: prevalence in a population of children and youth  Ann Epidemiol 2002;12303- 308PubMedGoogle ScholarCrossref
Welk  GJWelk  GJed Use of accelerometry-based activity monitors to assess physical activity  Physical Activity Assessments for Health-related Research. Champaign, Ill Human Kinetics2002;Google Scholar
Treuth  MSSchmitz  KCatellier  DJ  et al.  Defining accelerometer thresholds for activity intensities in adolescent girls  Med Sci Sports Exerc 2004;361259- 1266PubMedGoogle ScholarCrossref
Sallis  JFProchaska  JJTaylor  WC A review of correlates of physical activity of children and adolescents  Med Sci Sports Exerc 2000;32963- 975PubMedGoogle ScholarCrossref
Sallis  JFZakarian  JMHovell  MFHofstetter  CR Ethnic, socioeconomic, and sex differences in physical activity among adolescents  J Clin Epidemiol 1996;49125- 134Google ScholarCrossref
Aaron  DJKriska  AMDearwater  SR  et al.  The epidemiology of leisure physical activity in an adolescent population  Med Sci Sports Exerc 1993;25847- 853PubMedGoogle ScholarCrossref
Pate  RRHeath  GWDowda  MTrost  SG Associations between physical activity and other health behaviors in a representative sample of US adolescents  Am J Public Health 1996;861577- 1581PubMedGoogle ScholarCrossref
Gordon-Larsen  PMcMurray  RGPopkin  BM Determinants of adolescent physical activity and inactivity patterns  Pediatrics 2000;105e83http://pediatrics.aappublications.org/cgi/content/full/105/6/e83Accessed September 8, 2006PubMedGoogle ScholarCrossref
Kimm  SYGlynn  NWKriska  AM  et al.  Decline in physical activity in black girls and white girls during adolescence  N Engl J Med 2002;347709- 715PubMedGoogle ScholarCrossref
Murray  DMCatellier  DJHannan  PJ  et al.  School-level intraclass correlation for physical activity in adolescent girls  Med Sci Sports Exerc 2004;36876- 882PubMedGoogle ScholarCrossref
Catellier  DJHannan  PJMurray  DM  et al.  Imputation of missing data when measuring physical activity by accelerometry  Med Sci Sports Exerc 2005;37(suppl 11)S555- S562PubMedGoogle ScholarCrossref
Trost  SGKerr  LMWard  DSPate  RR Physical activity and determinants of physical activity in obese and non-obese children  Int J Obes Relat Metab Disord 2001;25822- 829PubMedGoogle ScholarCrossref
Thompson  AMCampagna  PDRehman  LAMurphy  RJRasmussen  RLNess  GW Physical activity and body mass index in grade 3, 7, and 11 Nova Scotia students  Med Sci Sports Exerc 2005;371902- 1908PubMedGoogle ScholarCrossref
Pate  RRPratt  MBlair  SN  et al.  Physical activity and public health: a recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine  JAMA 1995;273402- 407PubMedGoogle ScholarCrossref
Pratt  MMacera  CABlanton  C Levels of physical activity and inactivity in children and adults in the United States: current evidence and research issues  Med Sci Sports Exerc 1999;31(suppl 11)S526- S533PubMedGoogle ScholarCrossref
Dowda  MPate  RRFelton  GM  et al.  Physical activities and sedentary pursuits in African American and Caucasian girls  Res Q Exerc Sport 2004;75352- 360PubMedGoogle ScholarCrossref
Felton  GMDowda  MWard  DS  et al.  Differences in physical activity between black and white girls living in rural and urban areas  J Sch Health 2002;72250- 255PubMedGoogle ScholarCrossref
Sallis  JFBuono  MJFreedson  PS Bias in estimating caloric expenditure from physical activity in children: implications for epidemiological studies  Sports Med 1991;11203- 209PubMedGoogle ScholarCrossref
Riddoch  CJBo Andersen  LWedderkopp  N  et al.  Physical activity levels and patterns of 9- and 15-yr-old European children  Med Sci Sports Exerc 2004;3686- 92PubMedGoogle ScholarCrossref
Trost  SGPate  RRFreedson  PSSallis  JFTaylor  WC Using objective physical activity measures with youth: how many days of monitoring are needed?  Med Sci Sports Exerc 2000;32426- 431PubMedGoogle ScholarCrossref
Hedley  AAOgden  CLJohnson  CLCarroll  MDCurtin  LRFlegal  KM Prevalence of overweight and obesity among US children, adolescents, and adults, 1999-2002  JAMA 2004;2912847- 2850PubMedGoogle ScholarCrossref
Ogden  CLFlegal  KMCarroll  MDJohnson  CL Prevalence and trends in overweight among US children and adolescents, 1999-2000  JAMA 2002;2881728- 1732PubMedGoogle ScholarCrossref