Physical Activity During Youth Sports Practices FREE

National guidelines state that children and adolescents should accumulate 60 minutes of moderate to vigorous physical activity (MVPA) each day.¹ Based on objective physical activity measures, fewer than 50% of children and 10% of adolescents meet these guidelines.² The American Academy of Pediatrics recommends youth sports as a means of obtaining physical activity as well as social benefits.³ In the United States, an estimated 44 million youth participate in organized sports.⁴ Youth sports participants include 66% boy players and 34% girl players, with greater sex equity at younger ages and an average length of time in an organized sport program of 5 years.⁴ Although intensity values in the moderate to vigorous range are obtained while playing common youth sports, it is not clear how much physical activity is provided by youth sports practices, as much of the time may be inactive, such as receiving verbal instruction and waiting for turns.

The limited data show that youth sports contribute 23% to 60% of children's daily MVPA, with the remainder coming from activity during physical education, unstructured play, and recess.^5- 6 One study showed higher MVPA on sports participation days than non–sports-participation days.⁶ However, a study using direct observation found that 43% of youth sports practice was spent being inactive.⁷ Another study that used accelerometers to measure physical activity in after-school programs rather than youth organized sports found that youth were significantly more active during free play than structured activity sessions.⁸ Organized youth sports place more emphasis on competition than physical activity.³ Thus, it should not be assumed that sports practices are highly active.

The objective of this study was to document the physical activity of youth during organized soccer and baseball/softball practices using accelerometers. Soccer and baseball/softball were chosen because they are common youth sports in the United States and were expected to vary in opportunities for physical activity. A 2009 article⁹ showed that baseball was the second (15 million) and soccer the third (14.2 million) most played organized sport by North American youth aged 6 and older (after basketball, with 26.2 million children). It was hypothesized that soccer, with an intensity level of 7.0 metabolic equivalents (METs), would provide more MVPA than softball/baseball, at 5.0 METs.¹⁰ It was also hypothesized that boys would be more physically active than girls across both sports.

After obtaining approval from institutional review boards, permission was granted by the governing boards of youth sports leagues in San Diego County, California, to speak with coaches and recruit participants. Researchers attended practices to introduce the study, and interested parents and athletes completed consent and assent forms. Players who participated were compensated with a small prize worth $2.

The independent community sports leagues served 2 moderate-income cities. The soccer leagues were in Chula Vista, California, where the median household income was $63 095; the population was 26% Hispanic and 59% white; 80.5% had more education than a high school diploma; and 24.8% had more than a bachelor degree.^11- 12 The soccer league cost $500 per person and was 10 to 11 months in duration. The league was organized into 10 girls' teams and 23 boys' teams, with varying levels of skill across teams. Players practiced twice per week and had weekly games.

The baseball (boys) and softball (girls) leagues were in El Cajon, California, where the median household income was $52 175; residents were 47% Hispanic and 53% white; 80.7% had more education than a high school diploma; and 15.6% had more than a bachelor degree.¹² Fees for baseball and softball were $70 to $85 for the season, which ran for 5 months. Leagues had 14 teams with varying skill levels. Players practiced 1 to 2 times per week, with 1 to 2 games per week.

Participants were aged between 7 and 14 years and attended soccer or baseball/softball practices. There were 103 participants who played soccer and 97 who played baseball/softball. Response rates for soccer were 93% and were not collected for baseball/softball. Figure 1 presents distributions of teams by sport, sex, and age group. Participants were recruited from 29 teams. There were 14 soccer teams with 3 to 15 participants from each team (mean [SD], 7.4 [3.8]) and 15 baseball/softball teams with 3 to 12 participants from each team (mean (SD), 6.5 [2.7]). Teams were categorized into age groups of 7 to 10 and 11 to 14 years. Team age category was based on the predominant age group, although 2 teams had participants in both age groups.

Parents completed a survey assessing demographic characteristics, including parents' marital status, education, household size, and income as well as the child's age, racial/ethnic background, height, and weight.

ActiGraph GT1M accelerometers (Pensacola, Florida) were used to objectively measure physical activity, recording in 10-second epochs. Actigraphs have been validated as physical activity measures in numerous studies.¹³ Trained staff fit an elastic belt with an attached accelerometer snugly around each participant's waist at the beginning of practice and collected it at the end of practice. Practice start and end times were noted so that data collected outside of this time frame could be deleted. Each interval was scored as meeting or not meeting criteria for sedentary, light, moderate, or vigorous physical activity based on age-specific cutoff points.^14- 15 Sedentary time was less than 100 counts per minute. Moderate and vigorous physical activity (≥3 METs) were combined into 1 variable, MVPA. MeterPlus version 4.0 software (Santech Inc, San Diego, California) was used to clean and score the data (www.meterplussoftware.com). Although there is controversy regarding the cutoff points used to define moderate activity, US Department of Health and Human Services physical activity guidelines¹ define the minimum threshold for moderate physical activity as 3 METs for all ages, and numerous large studies have used these cutoff points.^16- 17

Statistical Package for the Social Sciences (SPSS) version 17.0 (SPSS Inc, Chicago, Illinois) was used for analyses. The outcome variable was minutes of physical activity spent in each level of intensity (ie, sedentary, light, moderate, vigorous, and MVPA). Because practice times were highly variable, the percentage of each intensity level during practice (eg, minutes in MVPA divided by total minutes of practice) was used as an additional outcome. For descriptive purposes, participants' average minutes in MVPA and percentage of time spent in MVPA during practice were calculated for each sport and separated by sex and age group. Participants' mean minutes and percentage of practice time for each intensity level were calculated for each sport. Participants were then categorized based on the daily physical activity guideline (60 minutes of MVPA)¹ as meeting at least half of the guideline, 30 minutes of MVPA, or meeting the full 60-minute guideline during practice. The percentage of participants who met the guideline was calculated for each sport and separated by sex and age group.

Because participants within teams can be highly interrelated and thus nonindependent (ie, participants within teams could be more alike than participants across teams), mixed effects regression models were conducted.¹⁸ The intraclass correlation coefficient, assessing the proportion of variance between teams, was examined. The intraclass correlation coefficient was 0.68 for minutes in MVPA and 0.60 for percentage of time spent in MVPA, indicating that a high percentage of the variability in MVPA was between teams. The models used were random intercept models with team entered as a random-effect, level 2 variable. Sport, sex, and age group were entered as fixed level 2 variables. Two models were used to investigate the relationships of sport, sex, and age group with MVPA (minutes and percentage). Sport × sex and sport × age interactions were included in both models. Four additional models were used to examine the relationship between sport and physical activity for each intensity level while controlling for sex and age group. The independent variables were binary and were centered on 0 (ie, −0.5 and 0.5) so the intercept would reflect the grand mean of the outcome and avoid colinearity when testing interactions. Unstandardized coefficients are reported and can be interpreted as differences for minutes in MVPA or percentage of practice in MVPA, while all other variables in the model are held constant. When appropriate, square root or log transformations were used for highly skewed distributions. However, regression coefficients, test statistics, and P values for models using transformed dependent variables were similar to those using nontransformed dependent variables. Therefore, to facilitate interpretation, only data from models with nontransformed variables are reported.

Owing to incomplete survey responses, the sample size for demographic questions ranged from 34 to 49 soccer participants and 36 to 50 baseball/softball participants. Among soccer respondents, 17% were white, 77% were Hispanic, and 6% were multiracial. Among baseball/softball respondents, 17% were white, 67% were Hispanic, and 16% reported their race as other. Seventy-three percent of soccer players and 28% of baseball/softball players had at least 1 parent with a college degree. Sixty-eight percent of soccer players and 77% of baseball/softball players had an annual household income of $50 000 or more. Body mass index (calculated as weight in kilograms divided by height in meters squared) was calculated from the child's parent-reported height and weight. Body mass index percentiles were calculated using Centers for Disease Control and Prevention growth charts, and participants were categorized as being underweight, normal weight, overweight, or obese.¹⁹ For soccer, 12% of participants were underweight, 52% were normal weight, 16% were overweight, and 20% were obese. For baseball/softball, 2% of participants were underweight, 54% were normal weight, 22% were overweight, and 22% were obese.

Practice times ranged from 40 to 130 minutes for soccer and 35 to 217 minutes for baseball/softball. t Tests revealed that practice time did not differ significantly between soccer (mean [SD], 105 [15]) and baseball/softball participants (mean [SD], 102 [41]), boys (mean [SD], 106 [38]), and girls (mean [SD], 100 [21]) or participants aged 7 to 10 (mean [SD], 105 [33]) and those aged 11 to 14 years (mean [SD], 100 [27]).

Mean minutes in MVPA, the percentage of time in MVPA, and the percentage of participants who met at least half the guideline (30 minutes) or the full 60 minutes of MVPA during practice are presented separately for sport × sex (Figure 2) and sport × age group (Figure 3). Soccer participants, boys, and those aged 7 to 10 years were generally more active than their counterparts. Overall, 24% of participants met the 60-minute physical activity guideline during practice, but fewer than 10% of participants aged 11 to 14 years and 2% of softball players met the full 60-minute physical activity guideline.

Table 1 presents the relationship of minutes in MVPA and the percentage in MVPA by sport, sex, and age group. Sport, sex, age group, sport × sex interaction, and sport × age group interaction explained 37.7% of the variance between teams in the model predicting minutes in MVPA and 45.8% of the variance between teams in the model predicting percentage of time in MVPA. The mean of the unweighted team means was 45.1 minutes in MVPA and 46.1% in MVPA. Participants who played soccer spent an average of 13.7 more minutes in MVPA and 10.6% more time in MVPA during practice than baseball/softball participants. Boys spent an average of 10.7 more minutes in MVPA and 7.8% more time in MVPA than girls. Participants aged 7 to 10 years spent an average of 7.0 more minutes in MVPA and 5.8% more time in MVPA than participants aged 11 to 14 years. The interaction between sport and sex was marginally significant for percentage of time in MVPA (P = .09). The difference between sports for minutes in MVPA and percentage of time in MVPA was much greater for girls (Δ = 22.2 and Δ = 17.4, respectively) than for boys (Δ = 7.6 and Δ = 6.8, respectively). The difference between sexes for minutes in MVPA and percentage of time in MVPA was much greater for baseball/softball participants (Δ = 17.6 and Δ = 13.0, respectively) than for soccer participants (Δ = 3.0 and Δ = 2.4, respectively; Figure 2).

Results from the 4 models investigating differences between sports for sedentary, light, moderate, and vigorous intensity physical activity are presented in Table 2. Minutes in sedentary, light, and MVPA, percentage of time spent sedentary, and percentage of time in MVPA did not differ between sports. There were small but significant differences for percentage in light activity, and large differences in minutes in vigorous activity and percentage of time in vigorous activity between sports. Participants who played baseball/softball spent an average of 6.1% more time in light activity and 5.4% more time in moderate activity than participants who played soccer. Participants who played soccer spent an average of 17.0 more minutes in vigorous activity and 15.9% more time in vigorous activity than baseball/softball participants.

It is expected that one benefit of organized youth sports participation is substantial amounts of physical activity, but fewer than one-fourth of youth in the present study obtained the recommended 60 minutes of MVPA during practice. The findings revealed substantial MVPA differences by sport, sex, and age.

Soccer and baseball/softball were chosen because they are popular with children of both sexes over a wide age range but they vary in activity levels. Thus, differences in activity levels were expected and found. There were particularly large differences between sports in vigorous physical activity (6 METs or more). Soccer players spent about 17 more minutes per practice in vigorous physical activity than baseball/softball players. Consistent with present findings, Katzmarzyk and colleagues’⁷ study using direct observation found that youth soccer players obtained more vigorous physical activity compared with other sports studied such as basketball and hockey. This is an important finding for 2 reasons. First, vigorous physical activity is relatively rare, with an average of 3 to 10 minutes daily for girls aged 6 to 15 years and 6 to 16 minutes for boys in the National Health and Nutrition Examination Study.² Second, vigorous-intensity physical activity is more strongly related to youth body composition than moderate intensity activities.^20- 21 Therefore, it appears playing soccer would be more likely to contribute to health benefits generally, and obesity prevention specifically, than playing baseball/softball.

Girls were less active in sports practices than boys by about 11 minutes overall. This is consistent with a similar finding that boys were more active than girls in after-school activity programs.⁸ Though the sex differences appeared larger for baseball/softball, the sport × sex interaction was only marginally significant. Nevertheless, only 2% of girls obtained 60 or more minutes of MVPA in baseball/softball practice compared with about 32% of boys. A possible explanation for this trend is that coaches included less physical training in girls' softball practices, devoting most of the time to skill building, game play, or other nonactive instruction. Owing to the extensive running inherent in soccer, boys' and girls' MVPA levels were very similar.

Consistent age differences were found, with 11- to 14-year-old players obtaining about 7 fewer minutes of MVPA per practice than 7- to 10-year-olds, with no difference by sport. This finding is unfortunate because the decline in total physical activity is steepest in the teenage years,²² and decreases in activity during sports practice may contribute to this decline. The age differences could be due to the general age decline in physical activity, greater efficiency of motion with age, or more emphasis on skill development during sports practice as competition intensifies. Data collectors in the present study observed the younger children engaging in more extraneous physical activity such as following the ball in soccer and playing side games during softball/baseball practices.

Strengths of the present study included the objective assessment of physical activity during practices of common youth sports; the design allowing for comparisons across sports, sex, and age of players; multiple teams being sampled; and analyses being adjusted for clustering within teams. The teams drew players from moderate-income communities, and the sample was diverse in race/ethnicity and reported body mass index. Weaknesses included the nonrandomized, cross-sectional design, recruitment of teams and players from a single geographic region, limited response to the demographic survey, and assessment of only community leagues that required payment instead of free leagues. Though accelerometers are well-validated measures of youth physical activity,¹³ they are not sensitive to some activities. For example, intensities of upper-body activities common to baseball/softball such as throwing, catching, and batting would likely be underestimated. Three METs was the lower limit of moderate-intensity physical activity, and other studies have used 4 METs² or higher,²³ reflecting a lack of consensus on definitions. Present definitions resulted in higher estimates of MVPA than if more stringent definitions had been used. Age-specific cutoff points are currently being re-evaluated, and observed age differences in MVPA could be partially explained by the higher accelerometer thresholds for older children.

Millions of youth in the United States and abroad participate in organized sports teams. Youth sports have the potential for large public health effect given the length of the seasons and years of participation. Parents spend substantial amounts of money and time supporting their children's sports participation, youth devote many hours to practices and games, and coaches often volunteer their time for youth development. Though participation in youth sports contributes to overall physical activity,^5- 6 the present study documented that fewer than one-fourth of youth athletes obtained the recommended 60 minutes of MVPA during sports practices. Thus, organized sports participation is not sufficient to ensure youth meet recommendations on practice days. Baseball/softball players, girls, and older youth (11-14 years) accumulated significantly fewer MVPA minutes and were much less likely to meet guidelines than soccer players, boys, and younger players (7-10 years). Surprisingly, youth sports players were inactive about 30 minutes during the average practice, which is similar to previous findings that youth were inactive 43% of sports practice time.⁷ Thus, there clearly are opportunities to increase physical activity in youth sports. Based on current findings, it appears that youth sports practices are making a less-than-optimal contribution to the public health goals of increasing physical activity and preventing childhood obesity.^1,24- 25

The health effects of youth sports could be improved by adopting policies and practices that ensure youth obtain sufficient physical activity during practices: emphasizing participation over competition, sponsoring teams for all skill levels across all ages, ensuring access by lower-income youth with sliding scales for fees, increasing practice frequency, extending short seasons, using pedometers or accelerometers to monitor physical activity periodically during practices, providing coaches strategies to increase physical activity, and supporting youth and parents in obtaining adequate physical activity on nonpractice days. These and other strategies for increasing MVPA during youth sports practice should be evaluated.

Correspondence: James F. Sallis, PhD, Department of Psychology, San Diego State University, 3900 Fifth Avenue, Ste 310, San Diego, CA 92103 (sallis@mail.sdsu.edu).

Accepted for Publication: September 8, 2010.

Published Online: December 6, 2010. doi:10.1001/archpediatrics.2010.252

Author Contributions:Study concept and design: Leek, Carlson, Cain, Henrichon, Rosenberg, Patrick, and Sallis. Acquisition of data: Leek, Cain, and Henrichon. Analysis and interpretation of data: Leek, Carlson, Henrichon, Rosenberg, and Sallis. Drafting of the manuscript: Leek, Carlson, Henrichon, and Sallis. Critical revision of the manuscript for important intellectual content: Leek, Carlson, Cain, Henrichon, Rosenberg, Patrick, and Sallis. Statistical analysis: Carlson, and Rosenberg. Obtained funding: Leek, Henrichon, Patrick, and Sallis. Administrative, technical, and material support: Carlson, Cain, Henrichon, Patrick, and Sallis. Study supervision: Leek, Cain, Rosenberg, Patrick, and Sallis.

Financial Disclosure: None reported.

Funding/Support: This study was supported by a National Institutes of Health Summer Research Grant through the University of California, San Diego, School of Medicine.

Previous Presentations: This study was presented as 2 posters at the Annual Meeting and Scientific Sessions of the Society of Behavioral Medicine; April 9, 2010; Seattle, Washington.