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Author Affiliations: Department of Exercise Science, Arnold School of Public Health (Drs Dowda and Pate and Messrs Mitchell and Byun), and Department of Educational Studies (Dr Brown), University of South Carolina, Columbia; and Department of Kinesiology, Michigan State University, Lansing (Dr Pfeiffer).
Objective To determine, using a social-cognitive framework and structural equation modeling, if parent-reported family physical activity (PA) variables are related to PA of young children.
Design Cross-sectional study.
Setting Children attending 23 preschools in and around Columbia, South Carolina.
Participants Three hundred sixty-nine children (48.0% male and 50.4% black) and their parents.
Main Exposures Family variables were reported by parents and included parent PA, parent enjoyment of PA, importance to adults of child playing sports and being active, and family support.
Main Outcome Measures Moderate to vigorous physical activity (MVPA) of children was modeled as a latent variable using PA from direct observation, accelerometers, and parent's perception of the child's athletic coordination.
Results A model of direct and indirect relations of family variables, preschool quality, home PA equipment, and child's enjoyment of PA had acceptable fit (root mean square error of approximation, 0.053; comparative fit index, 0.90). Parent PA, parent enjoyment of PA, and importance of child's PA were significantly related to family support. Family support, quality of preschool attended, home PA equipment, and child's enjoyment of PA were positively related to child's PA. However, there was no direct relationship between parent PA and the child's PA.
Conclusion Although parent PA was not directly related to children's MVPA, results showed that parent PA indirectly affects preschool children's MVPA via its influence on family support for children's PA.
In preschool children (age, 2-5 years), the prevalence of overweight and obesity has doubled in recent decades.1,2 The causes of the increase have not been fully identified. However, it seems probable that reduced physical activity (PA) and increased sedentary activity are important contributing factors.3-5 According to the PA guidelines for preschool children developed by the National Association for Sport and Physical Education,6 preschool children (age, 3-5 years) should accumulate at least 120 minutes of PA (60 minutes of structured PA and 60 minutes of free-play activity) during a typical day. However, there is evidence that children attending preschool are not accumulating this level of PA.7,8
Parents play a significant role in the health of their children and contribute to the physical and social environments in which their children develop.9 Of particular interest, given the rise in overweight and obesity, is the extent to which parents influence television viewing, dietary intake, and PA patterns of young children.10 The home environment may be an appropriate setting in which to conduct health behavior interventions, particularly school- or community-linked home interventions.9,11 However, a better understanding of how families contribute to the PA of young children is needed to design effective family-based PA interventions for preschool children.
Several models have been used to study correlates of PA, including social cognitive theory and the Youth Physical Activity Promotion Model.12,13 These models incorporate factors at different levels and propose that PA is affected by social and physical environmental influences (eg, social support, preschool a child attends, equipment for PA in the home) and personal factors (eg, sex of the child, enjoyment of PA).12,13 Parental PA and parental support have been accepted as correlates of PA in children and youth.14 Recently, Loprinzi and Trost15 used path analysis to assess parental influences on PA behavior of young children both at home and while in preschool. The purpose of the present study was to use parental variables from the Loprinzi and Trost model15 and variables from other models12,13 to test a model of parental influence and physical environment variables in preschool children's PA over the entire day. Child's PA was measured by 3 methods, and the analysis was performed using structural equation modeling.
Study design and participants
Participants in this study were enrolled in the Children's Activity and Movement in Preschool Study (CHAMPS).16,17 All 3- to 5-year-old children from 23 preschools enrolled in the study (2003-2005) were asked to participate. Accelerometer data and parent questionnaires were collected from 411 children (47.5% male, 51.6% black, and 40.4% white). Complete data (accelerometers, direct observation, and parent questionnaires) were available for 369 children. Data were collected over a 2-week period. Children from whom data were available and were not available did not differ by age, body mass index (BMI), moderate to vigorous PA (MVPA) from accelerometer, or race. Written informed consent was obtained from children's parents or guardians prior to collection of data. The study was approved by the University of South Carolina institutional review board.
Children wore ActiGraph accelerometers (Model 7164; ActiGraph LLC, Pensacola, Florida) over a 2-week period including 1 weekend, both while in preschool and at home. The monitors were initialized to save data in 15-second intervals to detect the short bursts of activity that are characteristic of 3- to 5-year-old children. Participants wore the accelerometers on an elastic belt on the right hip. Parents were instructed to remove the accelerometer only during water activities (bathing or swimming) and when the child went to bed at night.
Accelerometer data were reduced using cut points developed specifically for 3- to 5-year-old children to identify intervals of MVPA (>420 counts/15 s).18 Sixty minutes of consecutive zeros were considered as nonwear time. Minutes per hour of MVPA were then calculated, using each child's wear time as the divisor. Days on which total wear time was less than 5 hours or the child was absent from preschool were deleted from the analyses.
Direct observation of pa
The Observational System for Recording Physical Activity in Children-Preschool Version (OSRAC-P)19 was used to measure PA while the children were in the preschool. The OSRAC-P is a focal child, momentary time sampling observation system with a 5-second observe interval, followed by a 25-second record interval for each 30-second observation interval. Physical activity codes used in the OSRAC-P were modified from the Children's Activity Rating Scale.20 Activity intensities were scored on a scale of 1 to 5, with 1 indicating stationary or motionless and 5 indicating fast movement. Percentage of time in intervals coded as levels 4 or 5 was reported as MVPA. Data were collected in 30-minute sessions, and each child was observed for 10 to 12 randomly chosen sessions during the 2-week data collection period. Interobserver agreement was 91% for all reliability observation sessions.
A parent or guardian completed a survey that included questions about the child's date of birth, sex and race, and the level of education of adults in the household. In addition, the parent or guardian also reported his or her child's athletic coordination and enjoyment of PA and completed a checklist of PA equipment at home used by the child (Table 1). The parent's perception of the child's athletic coordination was used in the present study as a parent-reported proxy of PA because of its previously established relationship as a predictor of PA.24
The survey also asked about parent enjoyment of PA, family support for PA (5 items), and importance of the child participating in sports and PA (1 item), which are presented in Table 1. Family support items inquired about support from all family members. Three items assessed parent PA (Table 1), including moderate PA (MPA) during the previous 7 days, vigorous PA (VPA) during the previous 7 days, and a self-rating (0 to 10) of parent's PA level.
Body mass index
Children's height was measured to the nearest 0.1 cm using a portable stadiometer (Shorr Productions, Olney, Maryland). Weight was measured to the nearest 0.1 kg using an electronic scale (Model 770; Seca, Hamburg, Germany). The average of 2 measurements was used for both height and weight, and body mass index (BMI) was calculated from the averages (calculated as weight in kilograms divided by height in meters squared).
The Early Childhood Environment Rating Scale–Revised Edition (ECERS-R)25 was administered in a randomly selected classroom at each preschool by a trained researcher. The ECERS-R provides an estimate of the level of preschool quality based on current understanding of best practices in early childhood education. The ECERS-R evaluates 7 dimensions, and the scale includes 43 items. The items are rated from 1 to 7 on a Likert-type scale, with a score of 1 for inadequate and 7 for excellent. In this study, scores from each subscale were added and divided by the number of items. The psychometric properties of the ECERS-R have been reported elsewhere.25 The mean (range) score for the 23 preschools was 4.9 (3.5-5.9).
Structural equation modeling (SEM) using full-information maximum likelihood estimation was performed using Mplus 5.126 to test the hypothesized relationships (Figure). Approximately 6% of the participants had 1 or more missing values. The model tested is presented in the Figure. The measurement model included latent variables for parent PA (3 indicators), parent enjoyment of PA (1 indicator), importance of child participating in sports/PA (1 indicator), family support of PA (5 indicators), and child's PA (3 indicators: accelerometer, direct observation, and parent report). The model also included preschool quality, sex, PA equipment in the home, and child's enjoyment of PA. Correlations were estimated among all exogenous variables. The structural model included the following: (1) direct paths from parent PA, family support, preschool quality, sex, home equipment, and child's enjoyment of PA to child's PA; (2) direct paths from importance of child participating in PA, parent enjoyment of PA, and parent PA to family support; and (3) direct effects from family support to home equipment and child's enjoyment of PA. The strength of the relationships was determined by the standardized regression coefficients (β) of the model. The β coefficients are correlations but are adjusted for other correlations (paths) in the model. A higher β value indicates a stronger relationship.
Figure. Model illustrating the relationship among child's MVPA and family influences, adjusting for sex, preschool quality, and home equipment using structural equation modeling with standardized regression coefficients (β). D1 through D4 represent disturbance terms for the latent variables. Solid lines represent significant relationships and dashed lines represent nonsignificant relationships. V1 through V5 are single indicators for latent variables. The root mean square error of approximation of the model was 0.053 (95% confidence interval, 0.043-0.063); comparative fit index = 0.90; χ2104 = 211.9; P < .001. ActiGraph refers to ActiGraph accelerometers (Model 7164; ActiGraph LLC, Pensacola, Florida). ECERS-R indicates Early Childhood Environment Rating Scale–Revised Edition; MPA, moderate physical activity; MVPA, moderate to vigorous physical activity; PA, physical activity; VPA, vigorous physical activity.
Indirect effects and 95% confidence intervals (CIs) were estimated with PRODCLIN.27 This program produces unstandardized beta (b) coefficients for the indirect effect and is significant if the 95% CI does not contain 0.
Model fit was assessed according to multiple fit indexes using decision rules described by Hoyle28 and others. A χ2 value that is nonsignificant is an indicator of optimal fit, but it is too sensitive in a large sample, so other fit indexes also were used to test model fit. The root mean square error of approximation is a standardized estimation that is used to represent closeness of fit. Values of 0.06 or lower represent a close fit, while 0 represents an exact fit.29 The comparative fit index (CFI) tests the proportionate improvement in fit of the target model with the null model; CFI values approximating 0.90 indicate minimally acceptable fit.30P < .05 was considered statistically significant.
The mean (SD) age of the children was 4.2 (0.7) years, 48.0% were male, and 92% of the questionnaires were completed by the child's mother (Table 2). On average, children wore the accelerometer for a mean (SD) of 12.7 (1.5) hours per day for 6.9 (2.5) days. The only significant sex difference (P < .05) for the study variables was for MVPA as measured by accelerometry (Table 3).
The SEM model (Figure) provided an acceptable fit. Family support, preschool quality, access to home equipment, and child's enjoyment of PA were positively related to child's MVPA. Significant direct relationships (standardized regression weight [β]) with child's MVPA were observed for family support (β = 0.28), preschool quality (β = 0.20), sex (β = −0.20), home equipment (β = 0.17), and child's enjoyment of PA (β = 0.26). Parent PA, parent enjoyment of PA, and importance of child's participation in sports and PA were positively related to family support. Family support was positively related to child's access to home equipment and child's enjoyment of PA. The model accounted for 20.7% of the variance in family support, 12.0% of the variance in home equipment, 1.5% of the variance in child's enjoyment of PA, and 31.5% of variance in child's MVPA.
Five indirect effects were tested using the PRODCLIN program.27 The indirect effect (unstandardized beta [b ] and 95% CI) between parent PA and child's MVPA (mediated by family support) was significant (b = 0.015; 95% CI, 0.001 to 0.036). Other significant indirect effects were found between parent enjoyment of PA and child's MVPA, mediated by family support (b = 0.031; 95% CI, 0.005 to 0.065); between importance of child participation in PA and child's MVPA, mediated by family support (b = 0.014; 95% CI, 0.001 to 0.034); and between family support and child's MVPA, mediated by child's enjoyment of PA (b = 0.021; 95% CI, 0.0003 to 0.054). However, the indirect effect between family support and child's MVPA, mediated by home equipment, was not significant (b = 0.040; 95% CI, −0.0001 to 0.0826).
Correlations among the exogenous variables in the SEM are displayed in Table 4. Significant correlations were observed between importance of child's participation in PA and parent enjoyment of PA, and between parent PA and parent enjoyment of PA.
This study is the first, to our knowledge, to use SEM in identifying factors that directly and indirectly associate with MVPA in preschool children. Three types of factors were related to child MVPA, including parent/family factors (eg, family support), school/environment factors (eg, preschool quality), and individual factors (eg, enjoyment of PA). The findings that MVPA behavior in young children is influenced by a complex set of social environmental and personal factors are consistent with social cognitive theory, the Youth PA Promotion Model, and social ecological framework.12,13,31
The β coefficients presented for the SEM were standardized and therefore have a common metric that is uniform across all the measures in the model. This makes it possible to assess the relative importance of the predictors. For the direct effects in the Figure (arrows pointing directly to child's MVPA), the strongest predictor of child's MVPA was family support (β = 0.28), and the second was child's enjoyment of PA (β = 0.26). Parent PA was the weakest predictor of child's MVPA (β = 0.002).
The influence of parents' PA levels on their children's PA is not clear, with studies reporting conflicting results. In this study, the SEM analyses revealed that parent PA was related to child MVPA indirectly, through its influence on family support. A recent meta analysis found that parental modeling has a weak influence on child and adolescent PA.32 However, the influence of parent PA may be more important for preschool children. For example, Moore et al33 reported that preschool children of active mothers were more likely to be active than children of inactive mothers. In another study, however, mothers' PA was not related to PA of young children.22 In a longitudinal study of preschool children, father's activity was a significant predictor of child's PA after adjustments for potential confounders.34 Similar to the present study, Loprinzi and Trost15 found no direct effect of parent PA on child PA, but did find an indirect effect that was mediated by parental support. Similar findings have been reported in older children using path analysis over the total day.23 Although it seems clear that parent PA behavior influences children's PA, longitudinal studies are needed to clarify the mechanisms of this influence.
Two additional parent/family factors—parent enjoyment of PA and the importance parents placed on their child participating in sports and PA—were significantly related to family support of PA, which in turn was significantly related to child MVPA. Similar findings in preschool children and older children have been reported by others.15,23,35 For example, in a study of fourth- to sixth-grade children,35 those who reported greater parent enjoyment of PA and parental encouragement of PA participated in PA at higher levels. As in the present study, parental role modeling of PA was not directly related to child's MVPA. Although parental modeling may not affect child PA directly, parents who are active may be more likely to participate in PA with their child and to support his or her PA. Interventions to increase PA levels of children should consider focusing some resources on increasing parent enjoyment of PA and support for their child's sports and PA.
This study used a novel approach to creating the MVPA variable that functioned as the dependent variable in the SEM. The variable was created from 2 objective measures of PA (accelerometry and direct observation) and 1 subjective measure (parent-reported child's athletic coordination). This approach is based on the assumption that MVPA is a latent variable for which there is no single ideal measure. Taken together, multiple data sources can provide a better overall picture of children's PA than any of the sources alone.36
Strengths of the present study include triangulating child's MVPA from 3 measures of PA. Although parent's perception of athletic coordination is not a direct measure of PA, it has been shown to be correlated with PA in preschool children and older youth.11,24,33 Limitations include the cross-sectional nature of the data, self-reported parent PA, and the use of parent report of child's enjoyment of PA. However, there is some evidence that parents can reliably report psychosocial variables of their children.37
In conclusion, similar to other studies in preschool and older children, family influences were strongly associated with preschool children's PA.15,23,35 Because a majority of children aged up to 5 years are enrolled in some form of preschool,38 preschools are a logical setting for intervening to increase PA in young children. The findings of the present study suggest that a family component to interventions may help young children accumulate the recommended 60 minutes or more of structured MVPA each day.6,39,40 Preschools can help families learn about places to be active, promote community PA programs, and sponsor activities that help parents and children be active together.41 Preschools should provide teacher training, focus resources and modify policies and practices in ways that promote structured activity, active free play, and active learning.17,42
Correspondence: Marsha Dowda, DrPH, Department of Exercise Science, Arnold School of Public Health, University of South Carolina, 921 Assembly St, Columbia, SC 29208 (email@example.com).
Accepted for Publication: March 21, 2011.
Published Online: June 6, 2011. doi:10.1001/archpediatrics.2011.84
Author Contributions: Dr Dowda had full access to all of the data in the study and takes responsibility for the integrity of the data and accuracy of the data analysis. Study concept and design: Dowda, Pfeiffer, Brown, and Pate. Analysis and interpretation of data: Dowda, Pfeiffer, Mitchell, and Byun. Drafting of the manuscript: Dowda, Brown, Byun, and Pate. Critical revision of the manuscript for important intellectual content: Pfeiffer, Brown, and Mitchell. Statistical analysis: Dowda. Obtained funding: Pfeiffer, Brown, and Pate. Administrative, technical, and material support: Brown and Pate. Study supervision: Pfeiffer and Pate.
Financial Disclosure: None reported.
Funding/Support: This study was funded by National Institute of Child Health and Human Development grant R01HD043125.
Additional Contributions: Gaye G. Christmus, MPH, edited the manuscript, and Kristen Swaney, MPH, managed the project.
Dowda M, Pfeiffer KA, Brown WH, Mitchell JA, Byun W, Pate RR. Parental and Environmental Correlates of Physical Activity of Children Attending Preschool. Arch Pediatr Adolesc Med. 2011;165(10):939–944. doi:10.1001/archpediatrics.2011.84
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