Advertisement

Afterschool Program Participation, Youth Physical Fitness, and Overweight

      Background

      Fighting childhood obesity has become a key policy focus. The role of community-based interventions to promote physical activity is an important part of an overall strategy to increase physical activity for youth.

      Purpose

      This study examines whether community-based afterschool physical activity programs lead to improved youth fitness and lower obesity rates.

      Methods

      Individually linked, longitudinal administrative data were used from local afterschool programs and two school districts in one California community to follow 1105 students from the 2006–2007 to 2008–2009 school years. Models were estimated in 2009–2010 using linear probability regressions and robust SEs, controlling for individual, family, and school characteristics, including fitness and overweight status prior to program participation.

      Results

      One third (36%) of the students participated in fitness-focused afterschool programs. Controlling for baseline fitness status, participating in fitness-focused afterschool programs was associated with a 10% increase in the probability of being physically fit after 2 years. This finding held for nearly all subgroups, including students who were initially unfit. Participation in 2 years of the program was associated with a 14.7% increased likelihood of subsequent fitness compared to 8.8% for 1 year of participation. Participation in other types of afterschool programs was not associated with fitness improvements. There were no effects of participation in either type of program on overweight status.

      Conclusions

      These findings point to the promise of relying on existing community resources in the fight against childhood obesity. Fitness-focused afterschool programs will need to ensure that the highest-risk children—including those who are Latino and low-income—are served.

      Introduction

      The statistics on childhood obesity are alarming: 32% of children in the U.S. aged 2–19 years have BMIs high enough to classify them as overweight, 17% are obese, and 12% are severely obese.
      • Ogden C.L.
      • Carroll M.D.
      • Curtin L.R.
      • Lamb M.M.
      • Flegal K.M.
      Prevalence of high body mass index in U.S. children and adolescents, 2007–2008.
      Obesity among U.S. children has tripled since the 1970s
      • Paxson C.
      • Donahue E.
      • Orleans C.T.
      • Grisso J.A.
      Introducing the issue.
      and is now associated with medical problems that were once thought to be characteristic of only adults, including type 2 diabetes, high cholesterol, and high blood pressure.
      President's Council on Physical Fitness and Sports
      Physical fitness facts.
      Comparable national statistics on children's physical fitness levels are unavailable, but data from physical fitness testing among public school students in California—the location of the present study—indicate that 40% of children in Grades 5, 7, and 9 are physically unfit according to the guidelines established by the California Department of Education.
      California Department of Education
      Dataquest.
      Federal, state, and local leaders recognize that the solution to this public health problem must be multipronged, with changes not only at home and within the family but also at school and within the community at large. This approach, embodied in First Lady Michelle Obama's Let's Move! initiative, relies on local agencies and organizations, community leaders, and others who work with or live with young people to reframe their everyday strategies. The hope is that making incremental changes in young people's lives will lead to a healthier population.
      According to a recent review, the role of community-based interventions to promote physical activity is an important part of an overall strategy to increase physical activity.
      • Kahn E.B.
      • Ramsey L.T.
      • Brownson R.C.
      • et al.
      The effectiveness of interventions to increase physical activity A systematic review.
      Non-experimental research has shown a strong link between physical activity and lower obesity for school-aged youth.
      • Berkey C.S.
      • Rockett H.R.
      • Gillman M.W.
      • Colditz G.A.
      One-year changes in activity and in inactivity among 10- to 15-year-old boys and girls: relationship to change in body mass index.
      • Delva J.
      • O'Malley P.M.
      • Johnston L.D.
      Health-related behaviors and overweight: a study of Latino adolescents in the U.S.A..
      • Dowda M.
      • Ainsworth B.E.
      • Addy C.L.
      • Saunders R.
      • Riner W.
      Environmental influences, physical activity, and weight status in 8- to 16-year-olds.
      • Elkins W.L.
      • Cohen D.A.
      • Koralewicz L.M.
      • Taylor S.N.
      After school activities, overweight, and obesity among inner city youth.
      Physical activity, and especially vigorous physical activity, also can be associated with improved youth mental health
      • Nelson M.C.
      • Gordon-Larsen P.
      Physical activity and sedentary behavior patterns are associated with selected adolescent health risk behaviors.
      • Norris R.
      • Carroll D.
      • Cochrane R.
      The effects of physical activity and exercise training on psychological stress and well-being in an adolescent population.
      and other health outcomes.
      • Beets M.W.
      • Beighle A.
      • Erwin H.E.
      • Huberty J.L.
      After-school program impact on physical activity and fitness: a meta-analysis.
      However, studies tend to be cross-sectional, limiting the conclusions that can be drawn given the inherent selection bias associated with studying program effects at a single point in time.
      Experimental studies also test the effects of afterschool sports, physical activity, and education programs on obesity outcomes. The results are mixed, with some showing that specifically designed programs can modestly reduce youth BMI and other measures of obesity over a relatively short period of time,
      • Ara I.
      • Vicente-Rodriguez G.
      • Perez-Gomez J.
      • et al.
      Influence of extracurricular sport activities on body composition and physical fitness in boys: a 3-year longitudinal study.
      • Robinson T.N.
      • Killen J.D.
      • Kraemer H.C.
      • et al.
      Dance and reducing television viewing to prevent weight gain in African-American girls: the Stanford GEMS pilot study.
      • Story M.
      • Sherwood N.E.
      • Himes J.H.
      • et al.
      An after-school obesity prevention program for African-American girls: the Minnesota GEMS pilot study.
      • Weintraub D.L.
      • Tirumalai E.C.
      • Haydel K.F.
      • Fujimoto M.
      • Fulton J.E.
      • Robinson T.N.
      Team sports for overweight children: the Stanford Sports to Prevent Obesity Randomized Trial (SPORT).
      can have time-limited effects on BMI or obesity,
      • Gutin B.
      • Yin Z.
      • Johnson M.
      • Barbeau P.
      Preliminary findings of the effect of a 3-year after-school physical activity intervention on fitness and body fat: the Medical College of Georgia Fitkid Project.
      or no effect.
      • Vizcaíno1 V.M.
      • Aguilar F.S.
      • Gutiérrez R.F.
      • et al.
      Assessment of an after-school physical activity program to prevent obesity among 9- to 10-year-old children: a cluster randomized trial.
      Because these studies tend to be highly focused and time-limited research trials of programs that are developed and operated by research universities rather than community-designed and led programs, they tend to lack scalability and sustainability at a community level.
      The relationship between participation in afterschool programs of any kind and physical health outcomes remains underexamined in the adolescent development afterschool program literature. According to two recent reviews, the literature has not considered the physical health consequences of afterschool participation.
      • Durlak J.A.
      • Weissberg R.P.
      The impact of after-school programs that promote personal and social skills.
      • Lauer P.A.
      • Akiba M.
      • Wilkerson S.B.
      • Apthorp H.S.
      • Snow D.
      • Martin-Glenn M.L.
      Out-of-school-time programs: a meta-analysis of effects for at-risk students.
      It is therefore unknown whether afterschool programs that are developed and run by community practitioners and educators accrue health benefits for their participants in the same way as targeted antiobesity programs.
      The purpose of the current study was to determine whether community resources that enhance opportunities for youth to engage in physical activity outside of school lead to improved physical fitness and lower obesity rates. The mechanism through which afterschool programming is linked to improved fitness and reduced obesity is hypothesized to be twofold: (1) For youth engaged in physical activities after school, there can be a direct effect of increased activity on improved fitness and decreased overweight status; and (2) for youth engaged in afterschool activities that are not focused on physical activity, there may be improvements in overweight or fitness status because these activities replace sedentary, at-home alternatives, such as watching TV, playing video games, or excessive snacking, which are all associated with increased obesity.
      • Gortmaker S.L.
      • Peterson K.
      • Wiecha J.
      • et al.
      Reducing obesity via a school-based interdisciplinary intervention among youth: Planet Health.
      • Mahoney J.L.
      • Lord H.
      • Carryl E.
      Afterschool program participation and the development of child obesity and peer acceptance.
      • Motl R.W.
      • McAuley E.
      • Birnbaum A.S.
      • Lytle L.A.
      Naturally occurring changes in time spent watching television are inversely related to frequency of physical activity during early adolescence.
      • Robinson T.N.
      Reducing children's television viewing to prevent obesity: a randomized controlled trial.
      The study used longitudinal, individually linked administrative records to study youth participation in community-based afterschool programming and their health outcomes as measured by overweight status and physical fitness. The data came from one San Francisco Bay Area community, which has a large population of low-income and young Latino people—who are at highest risk of obesity.
      • Ogden C.L.
      • Carroll M.D.
      • Curtin L.R.
      • Lamb M.M.
      • Flegal K.M.
      Prevalence of high body mass index in U.S. children and adolescents, 2007–2008.
      Community partners from afterschool programs, school districts, the County Health Department, and others engaged in designing research questions and interpreting findings through a process of university–community collaboration.

      Methods

      Data Source

      Data were used from the Youth Data Archive (YDA), a collaboration of public, private, and university partners in the San Francisco Bay Area that share administrative data across agencies. Data came from two school districts that together serve approximately 18,000 students: an elementary school district serving students in Grades K–8 and the high school district into which it feeds, serving students in Grades 9–12. A total of 67% of students in the elementary district were Latino, 47% were English learners, and 58% were free and reduced-price lunch recipients. Data included student demographics, physical fitness outcomes, and academic achievement from the 2006–2007 to 2008–2009 school years.
      Student physical fitness status was measured using the California Physical Fitness Test (PFT), which consists of the following six fitness standards: aerobic capacity, body composition, abdominal strength and endurance, trunk extensor strength and endurance, upper body strength and endurance, and flexibility.
      The body composition standard used height and weight to calculate BMI and classify students as overweight or obese. All students in California take the PFT in Grades 5, 7, and 9 and pass a standard if their score falls within a designated healthy fitness zone.
      Fitnessgram FITNESSGRAM® Healthy Fitness Zones.
      • Plowman S.A.
      • Sterling C.L.
      • Corbin C.B.
      • Meredith M.D.
      • Welk G.J.
      • Morrow J.R.J.
      The history of FITNESSGRAM®.
      Individual schools were responsible for collecting these data and may have varied in their collection methods, but school staff, including credentialed physical education teachers, were responsible for test implementation.
      Student trajectories were created by following a cohort of students who took the PFT in 2006–2007 and again in 2008–2009 (n=1105), focusing on a younger group of students who took the PFT in Grades 5 and 7 (n=566) and an older group who took it in Grades 7 and 9 (n=539). Analysis occurred in the subsequent school year (2009–2010). Schools in the two districts administered the PFT near the end of the school year. Students were defined as physically fit if they passed five of the six PFT components; this standard is used by the California Department of Education to exempt high school students from up to 2 years of physical education.

      Measures

      Student records from the two school districts were individually linked to participation records from eight afterschool providers; this strategy resulted in a data set that combined students' background characteristics, fitness test outcomes, and levels of participation in a variety of afterschool programs for a 2-year period starting in Grade 5 (or 7) and ending in Grade 7 (or 9). The afterschool programs included those offered by city departments, school districts, and four nonprofit organizations, covering opportunities for both physical activity and other kinds of activities both on and off school campuses. The programs included served the largest number of students in the community. The focus was on afterschool programs and not sports leagues, which are not intended to provide regularly scheduled programming for children after school.
      To capture these two effects, programs were divided into those focused on fitness (e.g., dance, yoga, or soccer) and those that did not have an explicit fitness component (e.g., academic enrichment, arts, or leadership). Some of the nonfitness programs also included a fitness component, but unless the program was primarily focused on physical activity it was classified as “other enrichment.”

      Data Analysis

      Initial tables present raw tabulations of students' obesity and physical fitness trajectories. The likelihood of students' afterschool program participation was then modeled, separately examining students' participation in fitness and other enrichment afterschool programs. Regression analyses were used to examine whether participation in afterschool programs was associated with improved fitness and obesity outcomes for all students, and for specific student subgroups.
      All regressions used linear probability models, instead of logistic regressions, because of recent work that highlights the difficulties of interpreting logistic regressions in the presence of omitted variables, especially when comparing the magnitude of coefficients across groups.
      • Mood C.
      Logistic regression: why we cannot do what we think we can do, and what we can do about it.
      All tables report robust SEs that account for potential heteroskedasticity. Logistic regressions (not presented here) with identical specifications produced comparable results.
      A key challenge was that fitness and weight are influenced by a variety of factors, including parents' actions, genetics, food habits at home, classroom differences in physical education, and others that were not measured by the data. Some of these factors may be correlated with afterschool program participation. For example, students who were already physically fit may have been more likely to enroll in programs with fitness benefits and would have remained fit regardless of their afterschool participation.
      Ideally, one would collect data on these unobservable factors, but this was not possible for the students included in the analysis. However, longitudinal data helped account for this selection bias because a strong indicator of whether students will be physically fit or overweight at a point in time is their prior fitness or overweight status. This initial fitness or overweight measure was used to control for student selection into various types of programs. Models also controlled for student and family demographics, student academic achievement, and school fixed effects, which are also potentially correlated with unobservable characteristics.

      Results

      Table 1 presents characteristics of the cohort of students studied from 2006–2007 to 2008–2009. Variables were selected based on their previously established association with either fitness status or SES (Table 1). Sixty-three percent (n=701) of students were Latino, and about half (n=371) of these were English learners, meaning they had not yet met the California standards for English proficiency. Sixty-one percent (n=683) of students received free or reduced-price lunches and 29% (n=318) had parents who did not complete high school. There were few significant differences between the Grade-5 and Grade-7 cohort, except that the Grade-7 cohort had more English learner students (39.9% vs 28.9%) and fewer students from families with college-educated parents (22.6% vs 30.6%).
      Table 1Students' descriptive characteristics
      Characteristic% (n)
      Female48.6 (537)
      Male51.4 (568)
      Grade-5 cohort51.2 (566)
      Grade-7 cohort48.8 (539)
      Ethnicity and English-language status
       White26.7 (295)
       Latino—English learner33.6 (371)
       Latino—not English learner29.8 (329)
       Other—English learner0.8 (9)
       Other—not English learner9.1 (101)
      Parents' education
       Did not complete high school28.8 (318)
       Completed high school41.8 (462)
       Attended or completed college26.5 (293)
       Missing2.9 (32)
      Free or reduced-price lunch61.8 (683)
      Special education11.4 (126)
      School attendance rate
       Low6.7 (74)
       Medium17.6 (195)
       High75.7 (836)
      English language arts proficiency
       Not proficient50.4 (557)
       Proficient or above49.6 (548)
      Math proficiency
       Not proficient49.0 (542)
       Proficient or above51.0 (563)
      N1105
      Note: Lunch status and special education status are dummy variables that equal 1 if the student was ever enrolled in either program. Low, medium, and high attendance represent cumulative attendance of below 90%, between 90% and 95%, and above 95%, respectively. Parents' education is the highest level attained by either parent. English learners are students who are not considered fluent English proficient. All other variables reflect students' initial status in the 2006–2007 school year.
      Table 2 examines changes in students' physical fitness and overweight status over time, disaggregated by gender and ethnicity. Consistent with national trends, Latino students exhibited lower fitness and had persistently higher overweight rates than non-Latinos. In the younger cohort, Latino boys (n=233) were less likely to be persistently fit (33.3%) than non-Latino boys (n=267, 65.9%) and more likely to be persistently unfit (39.0% vs 16.5%). Findings held when comparing Latino and non-Latino girls or students in the older cohort.
      Table 2Pathways over time for physical fitness and overweight (% and n), by gender and ethnicity
      Fit→fitFit→unfitUnfit→fitUnfit→unfit
      Grades 5–7
       Non-Latino girls78.2 (79)8.9 (9)6.9 (7)5.9 (6)
       Latino girls41.3 (74)14.0 (25)18.4 (33)26.3 (47)
       Non-Latino boys65.9 (60)9.9 (9)7.7 (7)16.5 (15)
       Latino boys33.3 (65)10.8 (21)16.9 (33)39.0 (76)
      Grades 7–9
       Non-Latino girls62.4 (58)7.5 (7)11.8 (11)18.3 (17)
       Latino girls44.5 (73)14.0 (23)17.1 (28)24.4 (40)
       Non-Latino boys67.5 (81)4.2 (5)12.5 (15)15.8 (19)
       Latino boys53.7 (87)6.2 (10)21.6 (35)18.5 (30)
      Not overweight →not overweightNot overweight →overweightOverweight →not overweightOverweight →overweight
      Grades 5–7
       Non-Latino girls85.1 (86)4.0 (4)1.0 (1)9.9 (10)
       Latino girls70.9 (127)10.6 (19)3.4 (6)15.1 (27)
       Non-Latino boys70.3 (64)0.0 (0)9.9 (9)19.8 (18)
       Latino boys49.2 (96)9.7 (19)8.2 (16)32.8 (64)
      Grades 7–9
       Non-Latino girls76.3 (71)4.3 (4)1.1 (1)18.3 (17)
       Latino girls68.9 (113)6.7 (11)4.9 (8)19.5 (32)
       Non-Latino boys72.5 (87)0.8 (1)8.3 (10)18.3 (22)
       Latino boys54.3 (88)5.6 (9)11.1 (15)29.0 (47)
      Note: Overweight includes students who are overweight and obese.
      Boys' overweight status improved relative to girls' in both the younger and older cohorts. For example, Latino and non-Latino boys in the Grades 5–7 cohort moved from overweight to non-overweight 8.2% and 9.9% of the time, respectively, compared to 3.4% and 1.0% of Latino and non-Latino girls. This difference is likely related to the maturation process, as girls exhibit larger increases in BMI than boys during adolescence.
      • Mihalopoulos N.L.
      • Holubkov R.
      • Young P.
      • Dai S.
      • Labarthe D.R.
      Expected changes in clinical measures of adiposity during puberty.
      Combining both age cohorts, 36.5% (n=403) of students participated in afterschool fitness-focused programs (Table 3). Student participation in other enrichment programs varied by cohort, with 36.1% (n=204) of students in Grades 5–7 participating compared to 17.4% (n=94) of students in the Grades 7–9 cohort. Students were far more likely to participate in any program for 1 year than for 2, for both fitness and other types of enrichment programs.
      Table 3Student participation in afterschool program, % (n)
      Grades 5–7 cohortGrades 7–9 cohort
      Participated in fitness programs36.6 (207)36.4 (196)
       1 year26.0 (147)31.0 (167)
       2 years10.6 (60)5.4 (29)
      Participated in other enrichment programs36.1 (204)17.4 (94)
       1 year29.0 (164)15.4 (83)
       2 years7.1 (40)2.0 (11)
      No program participation42.4 (240)52.7 (284)
      n566539
      Note: Percentages do not sum to 100 because students can participate in both physical activity and other types of programs.
      Table 4 reports the results of cross-sectional linear probability models that examine student characteristics, including fitness and overweight status, associated with increased probability of afterschool program participation. Being physically fit was associated with a significant 8.4% increase in the probability of enrollment in fitness programs. Latinos, particularly those who were English learners, were less likely to enroll in fitness programs than whites. Students with lower SES also had a lower probability of participating, as did girls and students who had higher levels of school absences.
      Table 4Determinants of afterschool program participation (cross-sectional), coefficient (SE)
      Fitness programsOther enrichment programs
      Physically fit in base year0.084
      p<0.01
       (0.011)
      0.002 (0.010)
      Female−0.065
      p<0.01
       (0.021)
      −0.001 (0.023)
      Grade 5 (ref)
      Grade 7−0.127
      p<0.01
       (0.025)
      −0.004 (0.027)
      Grade 9−0.094
      p<0.01
       (0.035)
      −0.233
      p<0.01
       (0.035)
      Female X Grade 70.089
      p<0.01
       (0.030)
      −0.059
      p<0.05,
       (0.032)
      Female X Grade 9−0.014 (0.025)−0.019 (0.024)
      Parent education HS diploma (ref)
      Parent education less than HS−0.047
      p<0.01
       (0.012)
      0.001 (0.013)
      Parent education college0.124
      p<0.01
       (0.015)
      0.018
      p<0.05,
       (0.010)
      Free or reduced-price lunch−0.061
      p<0.01
       (0.017)
      −0.012 (0.015)
      Special education−0.040
      p<0.01
       (0.015)
      0.014 (0.014)
      White and not English learner (ref)
      Latino and not English learner−0.035
      p<0.05,
       (0.021)
      −0.012 (0.018)
      Latino and English learner−0.066
      p<0.01
       (0.023)
      0.005 (0.023)
      Other ethnicity and not English learner0.048
      p<0.01
       (0.021)
      −0.049
      p<0.01
       (0.015)
      Other ethnicity and English learner−0.137
      p<0.01
       (0.025)
      −0.063
      p<0.01
       (0.019)
      Highest school attendance (ref)
      Low school attendance−0.141
      p<0.01
       (0.024)
      −0.025 (0.022)
      Medium school attendance−0.095
      p<0.01
       (0.012)
      −0.030
      p<0.01
       (0.010)
      Overweight in base year (separate regression)−0.024
      p<0.05,
       (0.011)
      −0.004 (0.010)
      N4403
      Note: Boldface indicates significance. Regressions are cross-sectional over all students in Grades 5, 7, and 9, and include school dummy variables, controls for scores on standardized tests in math and English language arts, and dummy variables for missing parental education and attendance.
      HS, high school
      low asterisk p<0.05,
      low asterisklow asterisk p<0.01
      Many of these same characteristics were not associated with differences in enrollment in other types of enrichment programs. This is most likely because of academic enrichment programs that serve educationally at-risk students in eight of the elementary district schools. These programs included physical activity or outside play time as one component, but were classified as other enrichment programs because they were not primarily focused on fitness.
      The last line on Table 4 shows just the coefficient for being overweight, substituted for fitness, from a separate regression model that used the same control variables. Being overweight was associated with a significant 2.4% decreased probability of enrolling in a fitness-focused afterschool program, but was not associated with differences in participation in other types of enrichment programs.
      Table 5 provides the results of the main question examining the role of participation in different types of afterschool programs on student physical fitness and obesity status. For all students, participation in at least one fitness program after school was associated with a significant 10.0% increased probability of passing the physical fitness test at the end of 2 years. Students who participated in fıtness programs for 2 years in a row (n=630) exhibited a higher likelihood of being physically fıt at the end of that time than those who participated in just 1 year (n=177) (after controlling for initial fıtness level), 14.7% vs 8.8%, respectively. Regressions controlled for initial fitness level and other individual-level and school characteristics (coefficient results not reported).
      Table 5Effects of duration of time in afterschool program participation on physical fitness and overweight (longitudinal), coefficient (SE)
      Physically fitOverweight or obese
      Afterschool fitness program (ever)0.100
      p<0.01
       (0.027)
      −0.026 (0.022)
      Afterschool other enrichment program (ever)−0.019 (0.027)−0.001 (0.022)
      Afterschool fitness program, 1 year0.088
      p<0.01
       (0.029)
      −0.029 (0.023)
      Afterschool fitness program, 2 years0.147
      p<0.01
       (0.039)
      −0.015 (0.034)
      Afterschool other enrichment program, 1 year−0.024 (0.030)−0.007 (0.027)
      Afterschool other enrichment program, 2 years−0.013 (0.042)0.011 (0.031)
      N1105
      Note: Boldface indicates significance. Regressions include all variables included in Table 4 models.
      low asterisk p<0.01
      Participation in other types of afterschool enrichment programs did not predict physical fitness outcomes. Neither participation in fitness programs nor other enrichment programs were predictors of being overweight or obese. Although not shown, initial fitness level was the strongest determinant of students' long-term fitness, with a coefficient nearly four times the size of the effect of participation in a fitness program.
      Given the heterogeneous nature of the students studied, these same regressions were estimated separately for each subgroup. Each row in Table 6 represents a separate regression model and shows the coefficient for program participation on fitness or overweight status.
      Table 6Effects of participation in physical activity programs on physical fitness and overweight by subgroup (longitudinal), coefficient (SE)
      Physically fitOverweight or obese
      Effects of participation in fitness programs
      Initially fit0.091
      p<0.01
       (0.030)
      Initially unfit0.125
      p<0.05,
       (0.059)
      Initially overweight−0.095 (0.058)
      Initially not overweight−0.022 (0.022)
      Latino0.077 (0.039)−0.028 (0.032)
      Not Latino0.127
      p<0.01
       (0.039)
      −0.041 (0.028)
      Free or reduced-price lunch0.090
      p<0.05,
       (0.039)
      −0.007 (0.030)
      Not free or reduced-price lunch0.121
      p<0.01
       (0.038)
      −0.053
      p<0.05,
       (0.032)
      Male0.129
      p<0.01
       (0.036)
      −0.047 (0.030)
      Female0.077
      p<0.05,
       (0.045)
      −0.008 (0.033)
      Grade-5 cohort0.105
      p<0.01
       (0.040)
      −0.048 (0.031)
      Grade-7 cohort0.101
      p<0.01
       (0.038)
      −0.009 (0.033)
      Effects of participation in other enrichment programs
      Initially fit−0.022 (0.029)
      Initially unfit−0.018 (0.055)
      Initially overweight0.008 (0.058)
      Initially not overweight−0.008 (0.021)
      Latino−0.019 (0.038)−0.002 (0.032)
      Not Latino0.004 (0.037)0.008 (0.027)
      Free or reduced-price lunch−0.011 (0.039)−0.036 (0.033)
      Not free or reduced-price lunch−0.033 (0.036)0.050
      p<0.05,
       (0.029)
      Male−0.050 (0.035)−0.006 (0.031)
      Female0.061 (0.044)−0.021 (0.034)
      Grade-5 cohort−0.061 (0.038)0.021 (0.029)
      Grade-7 cohort0.059 (0.038)−0.042 (0.033)
      N1105
      Notes: Boldface indicates significance. Regressions include all variables included in Table 4 models.
      low asterisk p<0.05,
      low asterisklow asterisk p<0.01
      The effects of fitness program participation held for nearly all subgroups, with the exception of Latino students (but the coefficient was very close to significance with a p-value=0.053). The effect was larger for those who were initially unfit and also for boys. There was a consistently negative but statistically insignificant relationship between fitness program participation and overweight status for each subgroup. There were no subgroups for which participation in other enrichment programs influenced fitness outcomes, and also no consistent pattern to report on the effects of participation in other enrichment programs on overweight status.

      Discussion

      This study examined community-based afterschool programs, both those focused on fitness and on other types of enrichment, and their effects on fitness and overweight status in one Bay Area community. Lower-income and Latino students, who were more likely to be overweight and physically unfit, were less likely to participate in fitness-focused afterschool programs. Participation in these programs was associated with a significant 10.0% increased probability of passing the physical fitness test at the end of 2 years. This effect held for all subgroups examined and was stronger for students with more persistent afterschool participation.
      There were no effects on student fitness or overweight status from participating in other types of enrichment programs after school. These findings fit within the existing literature that shows mixed effects of afterschool programs on obesity
      • Ara I.
      • Vicente-Rodriguez G.
      • Perez-Gomez J.
      • et al.
      Influence of extracurricular sport activities on body composition and physical fitness in boys: a 3-year longitudinal study.
      • Robinson T.N.
      • Killen J.D.
      • Kraemer H.C.
      • et al.
      Dance and reducing television viewing to prevent weight gain in African-American girls: the Stanford GEMS pilot study.
      • Story M.
      • Sherwood N.E.
      • Himes J.H.
      • et al.
      An after-school obesity prevention program for African-American girls: the Minnesota GEMS pilot study.
      • Weintraub D.L.
      • Tirumalai E.C.
      • Haydel K.F.
      • Fujimoto M.
      • Fulton J.E.
      • Robinson T.N.
      Team sports for overweight children: the Stanford Sports to Prevent Obesity Randomized Trial (SPORT).
      • Gutin B.
      • Yin Z.
      • Johnson M.
      • Barbeau P.
      Preliminary findings of the effect of a 3-year after-school physical activity intervention on fitness and body fat: the Medical College of Georgia Fitkid Project.
      • Vizcaíno1 V.M.
      • Aguilar F.S.
      • Gutiérrez R.F.
      • et al.
      Assessment of an after-school physical activity program to prevent obesity among 9- to 10-year-old children: a cluster randomized trial.
      but extend this work by showing that even programs that are designed and run by community organizations can generate positive health outcomes. The findings also add to the literature on community-based afterschool programs by focusing on health outcomes, which are generally neglected but an important component of positive development.
      The limitations of relying on data collected by the community include the unknown quality and potential variation in how accurately the physical fitness test data were measured and collected at participating schools. It is also not possible with these data to account for variability in the quality of the afterschool programs studied in terms of availability, duration, and vigor of physical activity offered. Omitted from the analysis were data on participation in local sports leagues. In this low-income community, participation in sports leagues signals the financial capacity to enroll, which could bias the results. In contrast, afterschool programs were low-cost or no-cost. Finally, any observational study is subject to potential bias from omitted variables, but the present study's use of baseline fitness measurements, school fixed effects, and student and family characteristics, controls for key potentially confounding variables.
      The key implication of these findings is that sustained programs designed and run by communities can play an important role in promoting physical fitness. These programs, which exist in similar form in many communities nationwide, appear to have the potential to help students maintain or improve their fitness outcomes, even if they are not leading to a large reduction in obesity. Lower levels of participation and smaller effect sizes were found for the two highest-risk groups—lower-income and Latino students—indicating the confounding effects of disadvantage. A reason for lower participation was that low-income and Latino students, who are more often struggling in school, are often referred to afterschool academic programs aimed to boost achievement, which may limit outdoor play and physical activity time.
      This work suggests that communities consider ways to assist academically focused afterschool programs to include fitness components or offer fitness programs at various times of day, including before school, as an alternative. This may have dual benefits as participation in moderate-to-vigorous physical activity is associated with improvements in cognition and learning among children and youth.
      • Sibley B.A.
      • Etnier J.L.
      The relationship between physical activity and cognition in children: a meta-analysis.
      • Strong W.B.
      • Malina R.M.
      • Blimkie C.J.
      • et al.
      Evidence based physical activity for school-age youth.
      An additional challenge is attracting students who are not capable of participating, whether due to transportation barriers or other factors, or who are not inclined to engage in fitness programs. This may require creativity in designing new programs or altering existing programs to incorporate various types of physical activity and remove local barriers to participation.
      Future research should examine the types of activities, duration of physical activity, and extent of participation among students in afterschool fitness programs in an effort to better understand the link between community-run afterschool programs and youth physical fitness. Research also could examine the mechanisms for student selection into the variety of programs offered and the predictors of intermittent and persistent participation.
      Publication of this article was supported by the Robert Wood Johnson Foundation.
      This study was funded by the Robert Wood Johnson Foundation through its national program, Salud America! The RWJF Research Network to Prevent Obesity Among Latino Children (www.salud-america.org). Salud America!, led by the Institute for Health Promotion Research at The University of Texas Health Science Center at San Antonio, Texas, unites Latino researchers and advocates seeking environmental and policy solutions to the epidemic.
      The research team thanks its partners in the school districts and the afterschool programs for contributing data to this project and working to help interpret the findings. The authors thank Kara Dukakis and Maria Fernandez for leading the community collaboration portion of the work. The authors appreciate the comments and suggestions provided by participants at the University of Chicago Program on Education Seminar, 2010 Society for Research on Adolescence Bi-Annual Conference in Philadelphia and the 2009 and 2010 Salud America! Scientific Summits in San Antonio TX.
      No financial disclosures were reported by the authors of this paper.

      References

        • Ogden C.L.
        • Carroll M.D.
        • Curtin L.R.
        • Lamb M.M.
        • Flegal K.M.
        Prevalence of high body mass index in U.S. children and adolescents, 2007–2008.
        JAMA. 2010; 303: 242-249
        • Paxson C.
        • Donahue E.
        • Orleans C.T.
        • Grisso J.A.
        Introducing the issue.
        Future Child. 2006; 16: 3-17
        • President's Council on Physical Fitness and Sports
        Physical fitness facts.
        DHHS, Washington DC2010
        • California Department of Education
        Dataquest.
        (2010)
        • Kahn E.B.
        • Ramsey L.T.
        • Brownson R.C.
        • et al.
        The effectiveness of interventions to increase physical activity.
        Am J Prev Med. 2002; 22: 73-107
        • Berkey C.S.
        • Rockett H.R.
        • Gillman M.W.
        • Colditz G.A.
        One-year changes in activity and in inactivity among 10- to 15-year-old boys and girls: relationship to change in body mass index.
        Pediatrics. 2003; 111: 836-843
        • Delva J.
        • O'Malley P.M.
        • Johnston L.D.
        Health-related behaviors and overweight: a study of Latino adolescents in the U.S.A..
        Rev Panam Salud Publica. 2007; 21: 11-20
        • Dowda M.
        • Ainsworth B.E.
        • Addy C.L.
        • Saunders R.
        • Riner W.
        Environmental influences, physical activity, and weight status in 8- to 16-year-olds.
        Arch Pediatr Adolesc Med. 2001; 155: 711-717
        • Elkins W.L.
        • Cohen D.A.
        • Koralewicz L.M.
        • Taylor S.N.
        After school activities, overweight, and obesity among inner city youth.
        J Adolesc. 2004; 27: 181-189
        • Nelson M.C.
        • Gordon-Larsen P.
        Physical activity and sedentary behavior patterns are associated with selected adolescent health risk behaviors.
        Pediatrics. 2006; 117: 1281-1290
        • Norris R.
        • Carroll D.
        • Cochrane R.
        The effects of physical activity and exercise training on psychological stress and well-being in an adolescent population.
        J Psychosom Res. 1992; 36: 55-65
        • Beets M.W.
        • Beighle A.
        • Erwin H.E.
        • Huberty J.L.
        After-school program impact on physical activity and fitness: a meta-analysis.
        Am J Prev Med. 2009; 36: 527-537
        • Ara I.
        • Vicente-Rodriguez G.
        • Perez-Gomez J.
        • et al.
        Influence of extracurricular sport activities on body composition and physical fitness in boys: a 3-year longitudinal study.
        Int J Obes. 2006; 30: 1062-1071
        • Robinson T.N.
        • Killen J.D.
        • Kraemer H.C.
        • et al.
        Dance and reducing television viewing to prevent weight gain in African-American girls: the Stanford GEMS pilot study.
        Ethn Dis. 2003; 13: S65-S77
        • Story M.
        • Sherwood N.E.
        • Himes J.H.
        • et al.
        An after-school obesity prevention program for African-American girls: the Minnesota GEMS pilot study.
        Ethn Dis. 2003; 13: S54-S64
        • Weintraub D.L.
        • Tirumalai E.C.
        • Haydel K.F.
        • Fujimoto M.
        • Fulton J.E.
        • Robinson T.N.
        Team sports for overweight children: the Stanford Sports to Prevent Obesity Randomized Trial (SPORT).
        Arch Pediatr Adolesc Med. 2008; 162: 232-237
        • Gutin B.
        • Yin Z.
        • Johnson M.
        • Barbeau P.
        Preliminary findings of the effect of a 3-year after-school physical activity intervention on fitness and body fat: the Medical College of Georgia Fitkid Project.
        Int J Pediatr Obes. 2008; 3: 3-9
        • Vizcaíno1 V.M.
        • Aguilar F.S.
        • Gutiérrez R.F.
        • et al.
        Assessment of an after-school physical activity program to prevent obesity among 9- to 10-year-old children: a cluster randomized trial.
        Int J Obes. 2008; 32: 12-22
        • Durlak J.A.
        • Weissberg R.P.
        The impact of after-school programs that promote personal and social skills.
        Collaborative for Academic, Social, and Emotional Learning, Chicago IL2007
        • Lauer P.A.
        • Akiba M.
        • Wilkerson S.B.
        • Apthorp H.S.
        • Snow D.
        • Martin-Glenn M.L.
        Out-of-school-time programs: a meta-analysis of effects for at-risk students.
        Rev Educ Res. 2006; 76: 275-313
        • Gortmaker S.L.
        • Peterson K.
        • Wiecha J.
        • et al.
        Reducing obesity via a school-based interdisciplinary intervention among youth: Planet Health.
        Arch Pediatr Adolesc Med. 1999; 153: 409-418
        • Mahoney J.L.
        • Lord H.
        • Carryl E.
        Afterschool program participation and the development of child obesity and peer acceptance.
        Appl Dev Sci. 2005; 9: 202-215
        • Motl R.W.
        • McAuley E.
        • Birnbaum A.S.
        • Lytle L.A.
        Naturally occurring changes in time spent watching television are inversely related to frequency of physical activity during early adolescence.
        J Adolesc. 2006; 29: 19-32
        • Robinson T.N.
        Reducing children's television viewing to prevent obesity: a randomized controlled trial.
        JAMA. 1999; 282: 1561-1567
      1. Welk G.J. Meredith M.D. Fitnessgram/activitygram reference guide. The Cooper Institute, Dallas TX2008
      2. Fitnessgram.
        2007
        • Plowman S.A.
        • Sterling C.L.
        • Corbin C.B.
        • Meredith M.D.
        • Welk G.J.
        • Morrow J.R.J.
        The history of FITNESSGRAM®.
        J Phys Act Health. 2006; 3: S5-S20
        • Mood C.
        Logistic regression: why we cannot do what we think we can do, and what we can do about it.
        Eur Soc Rev. 2010; 26: 67-82
        • Mihalopoulos N.L.
        • Holubkov R.
        • Young P.
        • Dai S.
        • Labarthe D.R.
        Expected changes in clinical measures of adiposity during puberty.
        J Adolesc Health. 2010; 47: 360-366
        • Sibley B.A.
        • Etnier J.L.
        The relationship between physical activity and cognition in children: a meta-analysis.
        Pediatr Exerc Sci. 2003; 15: 243-256
        • Strong W.B.
        • Malina R.M.
        • Blimkie C.J.
        • et al.
        Evidence based physical activity for school-age youth.
        J Pediatr. 2005; 146: 732-737