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Change in Children's Physical Activity: Predictors in the Transition From Elementary to Middle School

Open AccessPublished:January 15, 2019DOI:https://doi.org/10.1016/j.amepre.2018.10.012

      Introduction

      Interventions to promote physical activity in children should be informed by knowledge of the factors that influence physical activity behavior during critical developmental transitions. The purpose of this study is to identify, from a comprehensive, multidomain set of factors, those that are associated with change in objectively measured physical activity in children as they transition from elementary to middle school.

      Methods

      The study used a prospective cohort design, with children observed in fifth, sixth, and seventh grades. Growth curve analyses were used to examine associations between exposure variables measured at baseline and children's physical activity across three observations. A total of 828 children, aged 10.6 (SD=0.5) years at baseline provided physical activity data in fifth grade and at one or both follow-ups. Exposure variables assessed child characteristics, parent characteristics, home characteristics, social factors, school environment, and community characteristics. Physical activity was measured via accelerometry. Data were collected in two school districts in South Carolina in 2010–2013 and analyzed in 2017.

      Results

      Variables measured within the child, parent/home, and community domains were positively associated with children's physical activity as they transitioned from fifth to seventh grade. These included parent encouragement of physical activity, parental support for physical activity, child sports participation, parent's report of the child's physical activity level, the child's time spent outdoors, social spaces for physical activity in the community, and the number of physical activity facilities that were proximal to the child's home.

      Conclusions

      Interventions designed to increase children's physical activity should include strategies that target multiple domains of influence.

      INTRODUCTION

      Physical activity provides important health benefits to children and youth,
      • Timmons BW
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      Systematic review of physical activity and health in the early years (aged 0–4 years).
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      Systematic review of the health benefits of physical activity and fitness in school-aged children and youth.
      and the Physical Activity Guidelines for Americans recommend that young people engage in 60 or more minutes of moderate to vigorous intensity physical activity (MVPA) per day.

      HHS. 2008 Physical Activity Guidelines for Americans. www.health.gov/paguidelines/. Published 2008. Accessed April 23, 2017.

      However, most U.S. youth do not meet that guideline, and it is well documented that the percentage of youth meeting the guideline declines with age.
      • Troiano RP
      • Berrigan D
      • Dodd KW
      • Masse LC
      • Tilert T
      • McDowell M
      Physical activity in the United States measured by accelerometer.
      • Kann L
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      • Harris WA
      • et al.
      Youth Risk Behavior Surveillance - United States, 2015.
      The National Health and Nutrition Examination Survey (2003–2004) observed that, on average, children aged 6–11 years engaged in more than 75 minutes of MVPA per day, but youth aged 12–15 years engaged in only 25 (girls) to 45 (boys) minutes per day.
      • Troiano RP
      • Berrigan D
      • Dodd KW
      • Masse LC
      • Tilert T
      • McDowell M
      Physical activity in the United States measured by accelerometer.
      Clearly, one strategy for increasing the prevalence of children and youth meeting the federal physical activity guideline is to reduce the rate at which PA declines during the transition from childhood to adolescence.
      Interventions to reduce the age-related decline in PA in children should be informed by a thorough understanding of the factors that influence change in PA as young people grow and develop. However, those factors are not well understood. Craggs et al.
      • Craggs C
      • Corder K
      • van Sluijs EM
      • Griffin SJ
      Determinants of change in physical activity in children and adolescents: a systematic review.
      performed a systematic review of 46 studies to assess evidence regarding determinants of change in PA. Few of the variables studied were consistently associated with change in PA, due in part to the different measures of PA and the frequent use of self-reported PA (31 of 46 studies).
      Much of the previous research on factors that influence PA in youth has been based on a social ecologic model of health behavior.
      • Sallis JF
      • Owen N
      • Fisher E
      Ecological models of health behavior.
      This model posits that PA behavior is influenced by a complex set of personal, social, institutional, and community factors.
      • Sallis JF
      • Owen N
      • Fisher E
      Ecological models of health behavior.
      Research based on this model has identified numerous individual factors that are associated with PA in young people.
      • Crawford D
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      • Timperio A
      • et al.
      The longitudinal influence of home and neighbourhood environments on children's body mass index and physical activity over 5 years: the CLAN study.
      • Hearst MO
      • Patnode CD
      • Sirard JR
      • Farbakhsh K
      • Lytle LA
      Multilevel predictors of adolescent physical activity: a longitudinal analysis.
      • Graham DJ
      • Wall MM
      • Larson N
      • Neumark-Sztainer D
      Multicontextual correlates of adolescent leisure-time physical activity.
      To date, however, few studies of children have examined factors that represent multiple domains of the social ecologic model while using a longitudinal study design and objective measurement of PA.
      • Hearst MO
      • Patnode CD
      • Sirard JR
      • Farbakhsh K
      • Lytle LA
      Multilevel predictors of adolescent physical activity: a longitudinal analysis.
      • Corder K
      • Sharp SJ
      • Atkin AJ
      • et al.
      Change in objectively measured physical activity during the transition to adolescence.
      Accordingly, the purpose of this study is to identify, from a comprehensive set of child, parent/home, social, school, and community factors, those that are associated with change in objectively measured PA in children as they transition from elementary to middle school.

      METHODS

      This study employed a longitudinal, observational research design in which children were measured on up to three occasions as they transitioned from elementary to middle school (aged 10.6 [SD=0.5]–12.5 [SD=0.5] years). The primary outcome variable was PA measured objectively via accelerometry. Exposure variables were conceptualized using the social ecologic model and were selected from four domains: child, parent/home, school, and community. These variables were measured at baseline when the children were in the fifth grade, and growth curve analysis was used to identify the variables that were associated with PA during 2 years of follow-up.

      Study Sample

      Participants were students drawn from 21 elementary schools, who subsequently enrolled in 12 middle schools in two school districts in South Carolina. Once per year, data were collected in the school setting. During an initial data collection session, students completed a questionnaire and anthropometric measurements and received an accelerometer. During a second session, students returned the accelerometer. A parent/guardian also completed a questionnaire; 87% of responding parents were mothers. Prior to data collection, parent/guardian consent and child assent were obtained. Data were collected in 2010–2013 and analyzed in 2017. The IRB at the University of South Carolina approved the protocols.

      Measures

      PA (minutes/hour) was measured using accelerometers (ActiGraph GT1M and GT3X models). Each child wore an accelerometer for 7 consecutive days, except while bathing, swimming, or sleeping. Accelerometer counts in the vertical plane were collected and stored in 60-second epochs and reduced using methods previously described.
      • Catellier DJ
      • Hannan PJ
      • Murray DM
      • et al.
      Imputation of missing data when measuring physical activity by accelerometry.
      PA was defined as ≥100 counts/minute and included light, moderate, and vigorous intensity PA. To adjust for differences in accelerometer wear-time, PA was expressed as minutes of PA per hour of wear time. Data for Sundays were not used because of poor wear rates (<8 hours) and low reliability. Missing values for children with >2 days of ≥8 hours of wear each day were estimated by multiple imputation using Proc MI in SAS, version 9.3. A total of five data sets were imputed and then averaged for each variable. Prior to imputation, most children in the analysis sample had ≥4 qualifying days (80% at fifth grade, 75% at sixth grade, and 67% at seventh grade). On average, 73% of total possible records from Monday to Saturday were available over the 3 years.
      Children's standing and seated heights were measured to the nearest 0.1 cm using a portable stadiometer. Leg length, used in calculating maturity offset, was estimated by subtracting seated height from standing height. Weight was measured to the nearest 0.1 kg using an electronic scale. The average of two measurements was used for both height and weight, and BMI was calculated (kg/m2). To assess maturational status, maturity offset was calculated using sex-specific equations from Mirwald and colleagues
      • Mirwald RL
      • Baxter-Jones AD
      • Bailey DA
      • Beunen GP
      An assessment of maturity from anthropometric measurements.
      as revised by Malina and Koziel.
      • Malina RM
      • Koziel SM
      Validation of maturity offset in a longitudinal sample of Polish boys.
      The student questionnaire included assessments of personal, social, and home environment variables. Child-reported personal variables included PA self-efficacy,
      • Dishman RK
      • Motl RW
      • Saunders RP
      • et al.
      Factorial invariance and latent mean structure of questionnaires measuring social-cognitive determinants of physical activity among black and white adolescent girls.
      • Motl RW
      • Dishman RK
      • Trost SG
      • et al.
      Factorial validity and invariance of questionnaires measuring social-cognitive determinants of physical activity among adolescent girls.
      • Saunders RP
      • Pate RR
      • Felton GM
      • et al.
      Development of questionnaires to measure psychosocial influences on children's physical activity.
      perceived barriers,
      • Dishman RK
      • Hales DP
      • Sallis JF
      • et al.
      Validity of social-cognitive measures for physical activity in middle-school girls.
      self-schema,
      • Kendzierski D
      Self-schemata and exercise.
      • Dishman RK
      • McIver KL
      • Dowda M
      • Pate RR
      Declining physical activity and motivation from middle school to high school.
      and motives for PA,
      • Dishman RK
      • Saunders RP
      • McIver KL
      • Dowda M
      • Pate RR
      Construct validity of selected measures of physical activity beliefs and motives in fifth and sixth grade boys and girls.
      including enjoyment, competence, appearance, fitness, and social subscales. Social variables included perception of parent support,
      • Sallis JF
      • Taylor WC
      • Dowda M
      • Freedson PS
      • Pate RR
      Correlates of vigorous physical activity for children in grades 1 through 12: comparing parent-reported and objectively measured physical activity.
      • Evenson KR
      • Birnbaum AS
      • Bedimo-Rung AL
      • et al.
      Girls’ perception of physical environmental factors and transportation: reliability and association with physical activity and active transport to school.
      perception of parent encouragement, peer support, and number of active friends. Home environment variables included perceived environment
      • Evenson KR
      • Birnbaum AS
      • Bedimo-Rung AL
      • et al.
      Girls’ perception of physical environmental factors and transportation: reliability and association with physical activity and active transport to school.
      and availability of PA equipment at home.
      • Sallis JF
      • Taylor WC
      • Dowda M
      • Freedson PS
      • Pate RR
      Correlates of vigorous physical activity for children in grades 1 through 12: comparing parent-reported and objectively measured physical activity.
      ,
      • Dennison BA
      • Erb TA
      • Jenkins PL
      Television viewing and television in bedroom associated with overweight risk among low-income preschool children.
      • Davison KK
      Do structural, interpersonal and intrapersonal constraints impede parents’ ability to support their children's physical activity? Examining ethnic differences.
      • Taylor WC
      • Sallis JF
      • Dowda M
      • Freedson PS
      • Eason K
      • Pate RR
      Activity patterns and correlates among youth: differences by weight status.
      Parent-reported personal variables included perception of the child's PA levels and importance of the child's participation in sports/PA. Social variables included parent's perception of his/her support of child's PA,
      • Sallis JF
      • Taylor WC
      • Dowda M
      • Freedson PS
      • Pate RR
      Correlates of vigorous physical activity for children in grades 1 through 12: comparing parent-reported and objectively measured physical activity.
      parent's enjoyment of PA, and parent's participation in leisure-time PA and sports.
      • Baecke JA
      • Burema J
      • Frijters JE
      A short questionnaire for the measurement of habitual physical activity in epidemiological studies.
      Home environment variables included access to PA and sedentary equipment at home, rules about sedentary behavior in the home, and number of adults in the home.
      • Dennison BA
      • Erb TA
      • Jenkins PL
      Television viewing and television in bedroom associated with overweight risk among low-income preschool children.
      • Davison KK
      Do structural, interpersonal and intrapersonal constraints impede parents’ ability to support their children's physical activity? Examining ethnic differences.
      A school administrator and a physical education teacher at each participating school completed surveys. These surveys included items from the School Health Policies and Programs Study,
      • Lee SM
      • Burgeson CR
      • Fulton JE
      • Spain CG
      Physical education and physical activity: results from the School Health Policies and Programs Study 2006.
      including recess minutes per week, physical education minutes per year, and intramural activities.
      A windshield survey
      • Evenson KR
      • Sotres-Alvarez D
      • Herring AH
      • Messer L
      • Laraia BA
      • Rodriguez DA
      Assessing urban and rural neighborhood characteristics using audit and GIS data: derivation and reliability of constructs.
      was completed for the street segment (i.e., cross street to cross street, not to exceed 0.5 miles) for each child's home address. Three scales were created from the windshield data: physical incivilities (e.g., litter, graffiti), territoriality (e.g., fences or barriers), and social spaces (e.g., presence of yards). Also, facilities that provide PA opportunities and resources were identified in each community by searching internet resources and databases for churches, commercial facilities, trails, parks, and schools/colleges. Trained staff confirmed facility offerings and completed a Physical Activity Resource Assessment
      • Lee RE
      • Booth KM
      • Reese-Smith JY
      • Regan G
      • Howard HH
      The Physical Activity Resource Assessment (PARA) instrument: evaluating features, amenities and incivilities of physical activity resources in urban neighborhoods.
      for each facility. The Physical Activity Resource Assessment includes information on facility features (e.g., baseball fields), amenities (e.g., drinking fountains), and incivilities (e.g., graffiti). For each resource the authors created an index and summed this index across all the facilities within a 2-mile buffer around a participant's home.

      Statistical Analysis

      Growth curve analysis, performed in SAS Proc Mixed, was used to identify factors that were associated with PA in children as they transitioned from elementary to middle school.
      • Singer JD
      • Willett JB.
      Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence.
      In all analyses, time was included as a random variable and children were nested in schools. Time was coded according to grade level as an ordered categorical variable (0, 1, 2) using procedures described by Singer and Willett.
      • Singer JD
      • Willett JB.
      Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence.
      Exposure variables were examined as main effects and as interactions with time. Data were analyzed in 2017.
      Initially, eight preliminary exploratory growth curve analyses were performed to identify exposure variables for inclusion in comprehensive, multidomain models. Missing values for 21 selected exposure variables were replaced by multiple imputation data augmentation using SAS Proc MI. The longitudinal relationships between PA and the exposure variables identified in exploratory analyses were then examined by constructing two additional growth curve models. The first examined only the influence of time on PA. The second included the 21 variables selected from the preliminary exploratory analyses and variable by time interactions. Maturity offset was included in this model to adjust for children's maturational status. All models included time, sex, race/ethnicity, parent education, and poverty index. Continuous variables were centered by subtracting the grand mean of the variable. Goodness-of-fit for each model was estimated by three statistics: deviance, Akaike Information Criteria, and Bayesian Information Criteria.

      RESULTS

      A total of 1,080 children (501 boys, 579 girls) were recruited into the study as fifth graders, and 992 of these children provided baseline accelerometer data for assessment of PA. The analytic sample included 828 children who provided PA data in the fifth grade and again in the sixth or seventh, or both sixth and seventh grades. This sample was diverse (53.9% girls, 38.3% white, 35.1% African American, 9.5% Hispanic). Table 1 provides descriptive data for the analysis sample. The group included in the analysis was similar to the group excluded; however, the analysis sample included a greater proportion of white children and fewer Hispanics than the excluded group (p=0.001). Parental education was higher in the analytic sample than in the excluded group (p=0.02).
      Table 1Baseline Characteristics of Children in the Analysis Sample
      Analysis sample, N=828
      Characteristicn?>% or mean (SD)
      Sex
       Males38246.1
       Females44653.9
      Race
       White31738.3
       African American29135.1
       Hispanic799.5
       Other14117.0
      Age82810.6 (0.5)
      Maturity offset, 5th grade828–1.62 (1.1)
      Physical activity
       5th grade PA, minutes/hour82828.2 (4.6)
      Parent education
       ≤High school34341.4
       >High school48558.6
      Mother completed questionnaire
       Yes66587.3
       No9712.7
      PA, physical activity.
      As shown in Table 2, exposure variables were selected in eight categories. Within each category a backward elimination analysis was performed to identify variables that were associated with PA (p<0.20). Across the eight categories, 21 variables of a total of 36 were identified as associated with PA at the specified level.
      Table 2Summaries and Psychometric Properties of Variables Hypothesized to Associate with Children's Physical Activity
      VariableNumber of itemsPossible RangeCronbach's αnObserved rangeMean (SD) or ?>%Estimate (95?>% CI), p<0.20
      Child characteristics, child reported
       Self-efficacy81–40.778281–43.3 (0.5)0.56 (–0.12, 1.14)
       Perceived barriers51–40.498281–3.61.7 (0.4)–0.59 (–1.24, 0.07)
       Self schema61–48N/A8152.3–37.325.7 (9.2)0.06 (0.03, 0.09)
       Enjoyment motivation41–40.748281–43.6 (0.5)
       Competence motivation41–40.728281–43.5 (0.6)
       Appearance motivation61–40.868281–43.1 (0.8)0.37 (0.01, 0.73)
       Fitness motivation31–40.658281–43.7 (0.5)–0.78 (–1.44, –0.11)
       Social motivation31–40.648281–43.1 (0.8)
      Child characteristics, parent reported
       Parent rating of child's PA31–50.757741–53.1 (0.8)1.09 (0.70, 1.48)
       Sport/classes participation, Yes/No10–1N/A7361–5Yes, 65.40.79 (0.18, 1.39)
       Weekday outdoor hours1N/A
      No range. Respondents reported an open-ended response.N/A, not applicable; PA, physical activity; PARA, Physical Activity Resource Assessment; PE, physical education.
      N/A7560–42.1 (1.2)
       Weekend day outdoor hours1N/A
      No range. Respondents reported an open-ended response.N/A, not applicable; PA, physical activity; PARA, Physical Activity Resource Assessment; PE, physical education.
      N/A7580–84.3 (2.2)0.19 (0.05, 0.32)
       Walk/bike to school10–1N/A7260–1Yes, 50.7
       How important that child is active11–4N/A7671–43.6 (0.6)0.61 (0.10, 1.12)
      Parent characteristics, parent reported
       Parent-reported support41–50.767711–52.8 (0.8)1.12 (0.76, 1.48)
       Parent leisure time4N/A
      No range. Respondents reported an open-ended response.N/A, not applicable; PA, physical activity; PARA, Physical Activity Resource Assessment; PE, physical education.
      0.427591–4.82.5 (0.7)–0.58 (–1.12, –0.14)
       Parent sports4N/A
      No range. Respondents reported an open-ended response.N/A, not applicable; PA, physical activity; PARA, Physical Activity Resource Assessment; PE, physical education.
      N/A7720.7–6.42.1 (0.8)
       Parent enjoys PA11–5N/A7641–53.2 (0.8)
      Home environment, child reported
       Perceived environment91–40.738281–42.9 (0.6)0.51 (0.08, 0.95)
       Equipment11–4NA8241–43.3 (1.0)0.18 (–0.09, 0.45)
      Home characteristics, parent reported
       Rules on sedentary equipment31–40.847731–41.9 (0.7)–0.30 (–0.69, 0.09)
       Sedentary equipment in child's

      bedroom
      30–3N/A7630–31.3 (0.9)
       Sedentary items in home40–25N/A7611–259.5 (3.5)
       Access to active equipment140–14N/A7571–136.3 (2.6)0.09 (–0.02, 0.20)
       Number adults in home: single parent

      vs ≥2 adults
      10–1N/A7640–1≥2 =78.9
      Social factors, child reported
       Parent support81–50.887891–53.3 (1.0)0.79 (0.43, 1.16)
       Parent encouragement21–50.657901–53.7 (1.0)–0.49 (–0.86, –0.12)
       Peer support31–50.718281–53.4 (1.0)
       Active friends10–5N/A8250–53.8 (1.3)0.22 (–0.005, 0.43)
      School environment, teacher or administrator reported
       Recess minutes/week, administrator

      reported
      2N/A
      No range. Respondents reported an open-ended response.N/A, not applicable; PA, physical activity; PARA, Physical Activity Resource Assessment; PE, physical education.
      N/A82875–200100.5 (25.6)
       PE yearly minutes, teacher reported2N/A
      No range. Respondents reported an open-ended response.N/A, not applicable; PA, physical activity; PARA, Physical Activity Resource Assessment; PE, physical education.
      N/A7871,440–3,3302,255 (631)
       Intramural activities, teacher reported1N/A
      No range. Respondents reported an open-ended response.N/A, not applicable; PA, physical activity; PARA, Physical Activity Resource Assessment; PE, physical education.
      N/A8280–61.3 (1.7)0.35 (0.14, 0.56)
      Community characteristics, directly observed
       Physical incivilities (windshield survey)70–1N/A7520–10.26 (0.4)
       Social spaces (windshield survey)90–9N/A7520–93.1 (1.0)0.01 (–0.28, 0.30)
       Territorial (windshield survey)60–4N/A7520–41.7 (0.9)
       PARA weighted score (2-mile buffer)1N/A
      No range. Respondents reported an open-ended response.N/A, not applicable; PA, physical activity; PARA, Physical Activity Resource Assessment; PE, physical education.
      N/A8210–14825.2 (29.1)0.01 (–0.001, 0.02)
      a No range. Respondents reported an open-ended response.N/A, not applicable; PA, physical activity; PARA, Physical Activity Resource Assessment; PE, physical education.
      Table 3 presents the findings for the composite growth curve analyses. Model 1 is the unconditional growth model with time. This model shows that there was a significant decline in PA as children progressed from fifth to seventh grade (p<0.05). Model 2, presented in Table 3, examined the influence of the 21 exposure variables identified in the first phase of the analysis on PA as it changed between fifth and seventh grades. This model controlled for parent education, poverty rate, sex, race, and maturational status. The following variables were found to be positively associated with PA as main effects across the three time points: parental support for PA (child reported), rating of child PA (parent reported), child time spent outdoors on weekends (parent reported), child sports participation (parent reported), intramural activities (teacher reported), and number of proximal community PA facilities (Physical Activity Resource Assessment weighted score; p<0.05). The multivariate model accounted for 41% of between-child variance in PA averaged across fifth through seventh grades (variance of the model intercept was 7.23 minutes/hour of PA compared with 12.35 minutes/hour in the unconditional model).
      Table 3Growth Curve Analyses for Identification of Variables Longitudinally Associated With Physical Activity in Children
      Variables were centered, and values reported are coefficients with 95% CI in parentheses estimated using full maximum likelihood.
      Model 2
      Fixed effectsModel 1Estimate (95% CI)Initial PA, estimate (95% CI)Change in PA,
      From 5th to 7th grade.AIC, Akaike's Information Criterion; BIC, Bayesian Information Criterion; PA, physical activity; PARA, Physical Activity Resource Assessment.
      estimate (95% CI)
      Intercept28.03 (27.62, 28.44)27.22 (26.36, 28.07 )
      Time–2.94 (–3.25, –2.63)–2.87 (–3.12, –2.62)
      Sex, male0.19 (–0.63, 1.00)
      Race
       Black1.19 (0.57, 1.80)
       Hispanic0.34 (–0.50, 1.18)
       Other0.42 (–0.25, 1.08)
       Whiteref
      Parent education, >high school–0.99 (0.50, 1.47)
      Percent poverty–0.02 (–0.05, 0.02)
      Maturity offset, 5th grade–1.12 (–1.49, –0.75)
      Self-efficacy0.21 (–0.42, 0.85)0.05 (–0.36, 0.45)
      Perceived barriers0.29 (–0.40, 0.98)–0.17 (–0.59, 0.26)
      Self schema0.01 (–0.03, 0.04)0.003 (–0.02, 0.03)
      Appearance motivation0.23 (–0.16, 0.62)0.22 (–0.02, 0.46)
      Fitness motivation–0.35 (–1.05, 0.36)–0.33 (–0.77, 0.10)
      Parent rating of child's PA0.86 (0.42, 1.31)0.05 (–0.23, 0.32)
      Sport/classes participation0.92 (0.25, 1.60)–0.07 (–0.49, 0.36)
      Weekend day outdoor hours0.19 (0.05, 0.34)–0.03 (–0.12, 0.06)
      How important that child is active0.52 (–0.03, 1.07)–0.21 (–0.55, 0.13)
      Parent-reported support0.16 (–0.27, 0.60)–0.03 (–0.31, 0.24)
      Parent leisure time–0.45 (–0.92, 0.02)0.02 (–0.27, 0.31)
      Perceived environment0.01 (–0.48, 0.51)–0.11 (–0.42, 0.21)
      Child-reported equipment0.00002 (–0.29, 0.29)–0.08 (–0.26, 0.11)
      Rules on sedentary equipment–0.11 (–0.52, 0.30)0.03 (–0.22, 0.29)
      Access to active equipment–0.003 (–0.13, 0.12)0.04 (–0.03, 0.12)
      Child-reported parent support0.51 (0.10, 0.91)–0.05 (–0.31, 0.20)
      Child-reported parent encouragement–0.54 (–0.90, –0.18)0.27 (0.04, 0.49)
      Active friends0.12 (–0.11, 0.35)–0.02 (–0.16, 0.12)
      Intramural activities, teacher reported0.32 (0.15, 0.50)–0.28 (–0.42, –0.14)
      Social spaces (windshield survey)–0.34 (–0.64, –0.04)0.32 (0.14, 0.51)
      PARA weighted score (2-mile buffer)0.01 (0.003, 0.02)–0.003 (–0.01, 0.004)
      Goodness of fit
       Deviance12,741.812,412.1
       AIC12,757.812,526.1
       BIC12,765.812,582.8
      Note: Boldface indicates statistical significance (p<0.05).
      a Variables were centered, and values reported are coefficients with 95% CI in parentheses estimated using full maximum likelihood.
      b From 5th to 7th grade.AIC, Akaike's Information Criterion; BIC, Bayesian Information Criterion; PA, physical activity; PARA, Physical Activity Resource Assessment.
      Three variables were significantly associated with change in PA. Two of these variables were positively associated with change in PA: parent encouragement of PA (child reported) and social spaces for PA in the neighborhood (p<0.05). The number of school-based intramural programs was negatively associated with change in PA (p<0.05). The multivariate model accounted for 54% of between-child variance in the decline in PA from fifth grade through seventh grade (variance of the model slope was 0.52 minutes/hour of PA compared with 1.14 minutes/hour in the unconditional model). To verify that the assumptions underlying linear mixed model regression were met, the authors examined mixed procedure residual diagnostic plots for the model presented in Table 3. These plots indicated constant variance and linearity.

      DISCUSSION

      The major finding of this study was that factors drawn from multiple domains of the social ecologic model were associated with PA in children as they transitioned from elementary school to middle school. The social ecologic model holds that health behaviors, such as PA, are influenced by an interactive constellation of personal, social environmental, physical environmental, community, and societal characteristics.
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      and practitioners.
      HHS
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      • Blas E
      • Kurup AS.
      Equity, Social Determinants and Public Health Programmes.
      The findings of the present study are consistent with this theory in that factors measured in the child, parent/home, and community domains were found to be longitudinally associated with children's objectively measured PA.
      Both child and parent social cognitive variables were related to PA and change in PA. Child-reported parental support of PA was positively associated with the child's PA across the observation period, and parental encouragement of PA was positively associated with change in child PA. These observations advance knowledge of the impact of parenting behavior on children's PA, because few related observational studies have used a longitudinal design
      • Laird Y
      • Fawkner S
      • Kelly P
      • McNamee L
      • Niven A
      The role of social support on physical activity behaviour in adolescent girls: a systematic review and meta-analysis.
      • Yao CA
      Rhodes RE. Parental correlates in child and adolescent physical activity: a meta-analysis.
      and very few have used a device-based measure of PA.
      • Laird Y
      • Fawkner S
      • Kelly P
      • McNamee L
      • Niven A
      The role of social support on physical activity behaviour in adolescent girls: a systematic review and meta-analysis.
      The few previous studies that used methodologies similar to those of the present study have yielded inconsistent findings.
      • Bradley RH
      • McRitchie S
      • Houts RM
      • Nader P
      • O'Brien M
      NICHD Early Child Care Research Network
      Parenting and the decline of physical activity from age 9 to 15.
      • Dewar DL
      • Plotnikoff RC
      • Morgan PJ
      • Okely AD
      • Costigan SA
      • Lubans DR
      Testing social-cognitive theory to explain physical activity change in adolescent girls from low-income communities.
      Findings from the present study indicate that parental support and encouragement, as perceived by the child, are important influences on children's PA during the critical transition from childhood to adolescence. Parents can encourage, co-participate, and provide opportunities for and transportation to PA programs.
      • Sallis JF
      • Prochaska JJ
      • Taylor WC
      A review of correlates of physical activity of children and adolescents.
      • Biddle SJ
      • Whitehead SH
      • O'Donovan TM
      • Nevill ME
      Correlates of participation in physical activity for adolescent girls: a systematic review of recent literature.
      Higher scores on the social spaces scale in this study were associated with less decline in PA over time. Social spaces in neighborhoods have been identified as vital places that support health.
      • Walton E
      Vital places: facilitators of behavioral and social health mechanisms in low-income neighborhoods.
      The social spaces scale from this inventory has also been associated with decreased odds of excessive weight gain in pregnant women.
      • Laraia B
      • Messer L
      • Evenson K
      • Kaufman JS
      Neighborhood factors associated with physical activity and adequacy of weight gain during pregnancy.
      Furthermore, many of the individual characteristics that constitute the social spaces scale, (e.g., people outside, homes with yards, homes with porches, at least one park), have been associated with higher PA levels primarily in adult studies. For example, availability of parks
      • Kaczynski AT
      • Henderson KA
      Parks and recreation settings and active living: a review of associations with physical activity function and intensity.
      • Bauman AE
      • Reis RS
      • Sallis JF
      • et al.
      Correlates of physical activity: why are some people physically active and others not?.
      • Carroll-Scott A
      • Gilstad-Hayden K
      • Rosenthal L
      • et al.
      Disentangling neighborhood contextual associations with child body mass index, diet, and physical activity: the role of built, socioeconomic, and social environments.
      and presence of sidewalks
      • McCormack G
      • Giles-Corti B
      • Lange A
      • Smith T
      • Martin K
      • Pikora TJ
      An update of recent evidence of the relationship between objective and self-report measures of the physical environment and physical activity behaviours.
      • Owen N
      • Humpel N
      • Leslie E
      • Bauman A
      • Sallis JF
      Understanding environmental influences on walking: review and research agenda.
      have been consistently associated with higher PA levels. The presence of homes with porches has been theorized to provide for “eyes on the streets” and promote social capital, both of which can facilitate PA.
      • Satariano WA
      • McAuley E
      Promoting physical activity among older adults: from ecology to the individual.
      • Day K
      • Boarnet M
      • Alfonzo M
      • Forsyth A
      The Irvine-Minnesota inventory to measure built environments: development.
      The presence of porches as well as the number of people in the area (both factors in the social spaces scale) have been associated with walking to work in previous research.
      • Craig CL
      • Brownson RC
      • Cragg SE
      • Dunn AL
      Exploring the effect of the environment on physical activity: a study examining walking to work.
      Finally, the availability of yards has been shown to support PA levels in children.
      • Kaushal N
      Rhodes RE. The home physical environment and its relationship with physical activity and sedentary behavior: a systematic review.
      Children in the U.S. are spending less time outdoors compared with previous generations,
      • Bassett DR
      • John D
      • Conger SA
      • Fitzhugh EC
      • Coe DP
      Trends in physical activity and sedentary behaviors of United States youth.
      and this appears to be negatively affecting their PA. A recent systematic review found that children tend to have more PA when they are outdoors than indoors.
      • Gray C
      • Gibbons R
      • Larouche R
      • et al.
      What is the relationship between outdoor time and physical activity, sedentary behaviour, and physical fitness in children? A systematic review.
      Results of the present study support the importance of outdoor time as an influence on children's PA. Parent-reported time that children spent outdoors was positively associated with PA. Another longitudinal study found that weekend outdoor time was significantly associated with higher levels of MVPA.
      • Cleland V
      • Crawford D
      • Baur LA
      • Hume C
      • Timperio A
      • Salmon J
      A prospective examination of children's time spent outdoors, objectively measured physical activity and overweight.
      These findings suggest that actions to increase children's outdoor time may be effective in increasing their PA.
      The findings of this study provide important guidance to professionals who seek to increase the PA levels of children and adolescents. To address the increased prevalence of obesity in U.S. youth, healthcare providers, educators, and public health specialists have been called upon to adopt policies and practices to promote PA in young people.
      Institute of Medicine
      Preventing Childhood Obesity: Health in the Balance.
      In response to these recommendations, some health systems have implemented protocols for assessing PA behavior and for counseling children and their parents regarding strategies for increasing PA.
      • Pate RR
      • Joy E
      • Lobelo F
      Physical activity promotion in the adolescent patient.
      Comprehensive, multicomponent school-based PA interventions have been shown to be effective,
      Physical Activity Guidelines for Americans Midcourse Report Subcommittee, President's Council on Fitness Sports and Nutrition
      Physical Activity Guidelines for Americans Midcourse Report: Strategies to Increase Physical Activity Among Youth.
      and some community-level interventions have increased children's PA.
      • Folta SC
      • Kuder JF
      • Goldberg JP
      • et al.
      Changes in diet and physical activity resulting from the Shape Up Somerville community intervention.
      The findings of the present study are consistent with a multidomain approach to promoting increased PA in young people. This approach would include elements aimed at helping children experience forms of PA that they enjoy and will be motivated to continue, assisting the parent in adopting behaviors that support the child's PA, and linking the child to community-based resources to support his/her PA.
      Strengths of the study include the use of an objective measure of PA, repeated observations of a large cohort of boys and girls followed for 3 years, and application of growth modeling, which uses each student's trajectory of change to estimate the typical change across students in PA and the variance of those changes, while also adjusting for initial fifth grade values. This approach permits a fuller test of correlated changes across time than prior longitudinal approaches, which may have failed to detect significant associations among similar variables when analysis was limited to less precise estimates of change across just 2 years.
      • Hearst MO
      • Patnode CD
      • Sirard JR
      • Farbakhsh K
      • Lytle LA
      Multilevel predictors of adolescent physical activity: a longitudinal analysis.
      • Dishman RK
      • Dunn AL
      • Sallis JF
      • Vandenberg RJ
      • Pratt CA
      Social-cognitive correlates of physical activity in a multi-ethnic cohort of middle-school girls: two-year prospective study.

      Limitations

      Limitations include data collection in only two school districts in one state, only two follow-up data points, surveys of only one parent (primarily mothers), and only self-reported parent PA.

      CONCLUSIONS

      This study employed a comprehensive, multidomain approach in identifying factors that are associated with children's PA levels as they transitioned from elementary to middle school. A comprehensive set of child, parent/home, social, school, and community factors were measured when children were fifth graders. The findings were consistent with the social ecologic model of health behavior in that variables in the child, parent/home, social, and community domains were found to be associated with children's PA when it was measured in the fifth, sixth, and seventh grades. The results of this study demonstrate that characteristics of children and their environment, observed when the children were in fifth grade, were associated with their PA levels over the next 2 years. These findings suggest that interventions aimed at increasing children's PA should begin early in childhood and should include strategies targeting multiple domains of the social ecologic model.

      ACKNOWLEDGMENTS

      The authors thank the children and parents who participated in the study, the staff of the Children's Physical Activity Research Group who collected the data, and Gaye Groover Christmus, MPH, University of South Carolina, who edited the manuscript. The funding agency was not involved in the design; collection, analysis, and interpretation of data; writing of the manuscript; or decision to submit the manuscript for publication. The study was supported by NIH (R01HL091002 to RP).
      Author contributions are as follows: study conceptualization and design were by RP, MD, RD, NC, RS, and KM; methodology was by RP, MD, RD, NC, and KM; investigation was by RP and KM; management was by RP; funding was from RP; data management was by MD and KM; analysis was by MD; writing was by RP, MD, and NC; review and editing of the manuscript were by RD, RS, and KM.
      No financial disclosures were reported by the authors of this manuscript. No conflicts of interest were reported by the authors of this manuscript.

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