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. Author manuscript; available in PMC: 2017 Jul 11.
Published in final edited form as: J Phys Act Health. 2014 Dec 10;12(9):1238–1244. doi: 10.1123/jpah.2014-0126

Toward a Better Understanding of the Link between Parent and Child Physical Activity Levels: The Moderating Role of Parental Encouragement

Eleanor B Tate 1, Anuja Shah 1, Malia Jones 1, Mary Ann Pentz 1, Yue Liao 1, Genevieve F Dunton 1
PMCID: PMC5504529  NIHMSID: NIHMS872958  PMID: 25494399

Abstract

Background

Research on adolescent physical activity is mixed regarding the role of parent activity. This study tested parent encouragement, direct modeling, and perceived influence as moderators of objectively-measured (accelerometer) parent and child moderate-to-vigorous physical activity (MVPA) associations.

Methods

Parent-child dyads (n = 423; Mchild age = 11.33 yrs.) wore accelerometers for 7 days; parents completed surveys. Hierarchical linear regression models tested moderation using a product of constituent terms interaction.

Results

Parent-reported encouragement moderated the association between parent and child MVPA (B = −.15, p = .01, ΔR2 = .02, p < .01). Among parents with lower MVPA, child MVPA was higher for children receiving high encouragement (M = 3.06, SE = .17) vs. low (M = 3.03, SE = .15, p = .02) and moderate encouragement (M = 3.40, SE = .09) vs. low (p = 0.04).

Conclusions

Physical activity promotion programs may use parent encouragement as a tool to boost child activity, but must consider other child and parent characteristics that could attenuate effects.

Keywords: child obesity, prevention, moderate-to-vigorous physical activity, parent modeling

Introduction

In the United States, approximately 58% of children aged 6 – 11 years and over 90% of adolescents aged 12 – 19 fail to meet the recommended 60 minutes of physical activity per day, based on estimates derived from objectively-measured physical activity (i.e., accelerometer) 1,2 Yet physical activity in children and adolescents reduces risk for cardiovascular disease, overweight/obesity, higher adiposity and possibly adult cancer 4,5, and physical fitness is associated with better skeletal health and may improve psychological outcomes such as depression and anxiety 6. Physical activity is a key component of short- and long-term childhood obesity prevention and reduction in conjunction with dietary modification and behavioral changes 7.

Parents may influence child and adolescent physical activity levels 8–15. According to Bandura’s Social Cognitive Theory, behavior is influenced by social contextual factors, such as behavior modeled by important others 16. Parents, in particular, play an important role in shaping children’s health behaviors and may do so through direct modeling (i.e., engaging in physical activity behaviors observed by children), which increases the likelihood that children will emulate parents’ actions 8,13,16,17. While some evidence indicates that physically active mothers have children who engage in more physical activity 18,19, other reviews have failed to find support for an association between parent and child physical activity 11,20. Possibly, certain circumstances suppress or magnify the association. For example, the effect could occur – or be moderated – by parenting factors such as parental support for physical activity.

A sizeable body of work has examined parental support for physical activity as an important determinant of child physical activity levels. Parents who provide greater encouragement, involvement, support, transportation, and believe in the importance of physical activity have more active children 7,9,13,21–25. However, whether these types of parenting techniques act independently or in conjunction with parent’s own physical activity remains unknown.

To address this gap, the current study tested the moderating effects of parent encouragement, modeling, and perceived influence on the relationship between parent and child physical activity levels. To our knowledge, this study is the first to examine the question using objectively-measured (i.e., accelerometer) physical activity in parent-child pairs. The study aims were to 1) examine the association between parent and child physical activity levels as measured objectively during the same 7-day period and 2) determine whether this relationship was moderated by three parenting techniques— parental encouragement for physical activity, direct modeling of physical activity (i.e., in the presence of children during adult physical activity), and parents’ perceived influence over children’s physical activity. The first hypothesis was that children whose parents had higher levels of objectively-measured physical activity would have higher levels themselves. The second hypothesis was that greater perceived influence, parental encouragement, and direct modeling of physical activity would strengthen the association between parent and child physical activity.

Methods

Recruitment and Procedure

The sample for this cross-sectional study consisted of parent-child dyads enrolled in a larger intervention study, called Healthy PLACES, investigating effects of a smart growth community on obesity risk. 26. Recruitment strategies targeted families who had moved to The Preserve, a smart-growth community in Chino, California, as well as families living within a 30-minute drive (approximately 13 miles) of The Preserve who had similar demographics and income. Recruitment procedures have been reported in detail elsewhere 26–30. Participant families included one parent and one child, aged 8–14 years. If a household had two eligible children wanting to participate, the child was selected with the next closest birthday to the date of the screening phone call. If a household had two parents wanting to participate, the parents selected the one having the greatest availability. Inclusion criteria were (a) having a child enrolled in grades 4 – 8, (b) both the child and the parent living in Chino, CA or surrounding communities, (c) ability to read English, and (d) annual household income < $210,000. For participants who met the eligibility criteria, data were collected either at a local community site or their home. The Institutional Review Board at the University of Southern California approved the study; written informed consent and minor assent were obtained from parents and children. For the current study, only baseline data were used, which were collected between March 2009 and December 2010. During that time, no data collection took place from late July through August and during January due to seasonal conditions that limit outside activity. Within the parent–child pairs, both wore an accelerometer over the same 7-day period.

Participants

From an initial baseline sample of 623 parent-child pairs, 200 pairs (32%) were excluded due to missing or invalid data for one or more demographic variables used as covariates in the model (n = 106, 17%), accelerometer (n = 130, 21%), or parenting questionnaire data (n = 26, 4%) (see Table 1). Some participants were missing data in more than one category. Participants were excluded for missing data on items either related to hypothesis testing (parenting items, accelerometer data) or to statistically adjust for potential confounders (demographic variables).

Table 1.

Demographic, BMI, and MVPA for retained vs. non-retained participants

Characteristic Retained (n= 423)
% or M (SD)		 Non-retained (n= 200)
% or M (SD)		 F or χ2
Child
Age 11.33 (1.49) 11.55 (1.59) 2.01
Gender 1.04
 Female 48.46 43.96
 Male 51.54 56.04
Ethnicity 0.22
 Non-Hispanic 58.63 56.59
 Hispanic 41.37 43.41
BMI 0.59
 Normal/underweight 62.17 59.35
 Overweight 18.20 17.89
 Obese 19.62 22.76
MVPA 47.00 (42.77) 50.92 (43.68) 0.73
Parent
Age 39.30 (5.95) 38.99 (6.11) 0.33
Gender 6.56*
 Female 83.22 74.16
 Male 16.78 25.84
Ethnicity 0.14
 Non-Hispanic 49.41 47.75
 Hispanic 50.59 52.25
BMI 6.04*
 Normal/underweight 29.55 24.21
 Overweight 39.01 34.21
 Obese 31.44 41.58
MVPA 28.73 (32.62) 33.39 (39.59) 1.77
Income 3.28
 < 30,000 23.64 17.01
 30,000–60,000 28.84 28.57
 60,000–100,000 25.53 28.57
 >100,000 21.99 25.85
Parent encouragement of PA 2.60 (0.75) 2.70 (0.82) 1.99
Parent modeling of PA 2.28 (0.68) 2.37 (0.70) 2.18
Parent influence on PA 2.46 (0.53) 2.47 (0.53) 0.01
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*

p < 0.05

Note: Body Mass Index (BMI), Moderate-to-vigorous physical activity (MVPA), Physical activity (PA); Missing data – For children; ethnicity (18), BMI (77), gender (18), age (75), MVPA (89); For parents; ethnicity (22), BMI (10), gender (22), age (22), MVPA (76), income (53), encouragement (24), modeling (22), influence (20)

Measures

Parent and child MVPA

Parent and child daily moderate-to-vigorous physical activity minutes (MVPA) were recorded over 7 days using the ActiGraph, Inc. GT2M model activity monitor accelerometer (firmware v06.02.00). Participants were instructed to wear the accelerometer for 7 days during all waking activities except bathing and swimming. The device recorded physical activity information in 30 second epochs. Non-wear was defined as 60 consecutive minutes of 0 activity counts, and non-wear periods were removed from analysis. Valid days were defined as having at least 10 hours of wear. Participants with fewer than 4 valid days were excluded. Of the original 623, 55 children had fewer than 4 valid days, and an additional 32 had missing data. For parents, 51 had fewer than 4 valid days, and an additional 11 had missing data. As indicated, 130 participants overall were excluded for missing or insufficient accelerometer data, and demographic characteristics for excluded and non-excluded participants were similar except for parent gender and obesity status (Table 1). For participants with 4 or more valid days, average daily minutes of MVPA was calculated as (Total valid minutes)/(Total valid days). The MVPA cut-off for adults was >3 Metabolic Equivalent of Task (MET). Age-adjusted MET cut-offs were used for children consistent with national studies on youth physical activity based on the Freedson et al. prediction equation 31,32.

Parent perceived influence on child physical activity

Parent perceived influence on child physical activity was measured using three survey items adapted from prior research 33: “Parent’s physical activity can have a lot of influence on children.”(reverse-coded), “Parent’s physical activity can help their children learn how to be active.” (reverse-coded), and “My children are either going to exercise or they are not, no matter what I do”. Response options ranged from 0 = Strongly Agree to 3 = Strongly Disagree. A score was created by averaging the responses on these three items, with higher scores indicating higher perceived influence. Internal reliability was moderate (α= 0.60).

Parent-reported modeling of physical activity

Parent modeling of physical activity was assessed using five items adapted from prior research 33, and the Youth Risk Behavior Survey 34. Example items included, “In the past 30 days, how often did your child see you do something physically active?” and “In the past 30 days, how often did your child see you use physical activity for relaxation or stress relief?” Response options ranged from 0 = Never to 4 = Always. A score was created by averaging the responses on these five items; higher scores indicated greater modeling. Reliability was moderate (α = 0.65).

Parent-reported encouragement of child physical activity

Parent encouragement of child physical activity was assessed using seven items adapted from previous research 33. Example items included, “In the past 30 days, how often did you verbally encourage your child to be physically active or play sports?” and “In the past 30 days, how often did you transport your child to a place where he/she can be physically active or play sports?” Response options ranged from 0 = Never to 4 = Always. A scale was created by averaging the responses on these seven items; higher scores indicated greater encouragement. Reliability was high (α = 0.81).

Child BMI

Child height and weight were measured in duplicate using an electronically calibrated digital scale (Tania WB-11A) and a professional stadiometer (PE-AIM-101). Body Mass Index (BMI) was calculated as (weight in kilograms)/(height in meters2). Child BMI z-score was calculated using Centers for Disease Control and Prevention standards and methods 35.

Data analysis

Distributions were examined for outliers and skew. Parent and child MVPA were positively skewed and were normalized through log transformations. A correlation matrix was generated for all variables to examine the bivariate relationships between hypothesized moderators and MVPA. Moderation tests were conducted as outlined by Frazier et al. 200436 using SPSS (IBM Corp. Released 2012. IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp). Predictor and moderator variables (parent MVPA, parent encouragement, parent modeling, parent perceived influence) were grand mean centered, and a product of constituent terms interaction was calculated for each moderator using the centered variables (parent MVPA * moderator)36,37. As recommended by Frazier et al. (2004), unstandardized estimates and standard errors were reported and interpreted. In Step 1 of a hierarchical linear regression, a predictor (parent MVPA) and moderator variable (e.g., parent encouragement) were entered. In Step 2, the product of constituent terms interaction was added to the model. If the significance value of the F-statistic for the R-squared change from the 1st to 2nd Step was less than 0.05, moderation was indicated 38. For each moderator, a second model (Model 2) was conducted that also adjusted for child gender, age, ethnicity, BMI z-score, parent gender, parent BMI, income and group (Preserve vs. control).

Results

Table 1 shows demographic characteristics for parent-child dyads who provided complete data (n = 423) versus those who did not (n = 200). Of the retained dyads, half of parents self-identified as Hispanic (51%), and most were mothers (83%). The mean age was 39.30 years (SD = 5.95). Twenty-four percent (24%) of parents had annual incomes of less than <$30,000 and 22% earned >$100,000. The child sample contained an even gender mix and had a mean age of 11.33 years (SD = 1.49). The retained group had a different distribution of parent BMI than the excluded group, with a lower percentage of obese parents (31% vs. 42%, p < 0.05).

Participants had between 4 and 7 valid days, except for two dyads that wore the accelerometer for one extra day due to delays returning it to researchers. The average number of valid days was around 6 (children M = 6.10 days, SD = 0.92; parents M = 6.30, SD = 0.86). Average wear time on valid days was approximately 13 hours per day (children M = 12.68, SD = 1.49, range: 7.99 – 22.78; parents M = 13.43; SD = 1.48, range: 8.82 – 17.74). For children, the median MVPA was 38.07 minutes per day (range: 2.17 to 135.86), and 22% met the guideline for an average of 60 minutes per day. For parents, the median MVPA was 22.08 minutes per day (range: 1.25 to 406.25), and 51% met the guideline for 150 minutes per week or 21.43 minutes per day. Two parents had very high average daily physical activity greater than 7 standard deviations above the mean. MVPA scores for parents and children were first log-transformed, which normalized the distribution and mitigated the effect of positive outliers. A sensitivity analysis was also conducted by re-running models without the two outliers; however, the pattern of results did not change. The average parent perceived influence score was 2.46 (SD = 0.53) on a 4-point scale (0 – 3), indicating that parents agreed “somewhat” to “strongly” that parent habits can influence child physical activity. On average, parents indicated that they modeled physical activity for their children “rarely” to “sometimes” (parent modeling score M = 2.28; SD = 0.68). The average parent encouragement score (M = 2.60; SD = 0. 75) indicated that parents encouraged children’s physical activity between “rarely” and “sometimes” in the past 30 days. As shown in Table 2, child MVPA was significantly and positively correlated with parent MVPA (r = 0.27), encouragement (r = 163), and modeling (r = .142) (ps < .01).

Table 2.

Correlations between Parent and Child MVPA, Parent PA Behaviors and Demographics

1 2 3 4 5 6 7 8 9 10 11 12 13
1. Child MVPA (log) 1.00
2. Parent MVPA (log) .268** 1.00
3. Encouragement for PA .163** .066 1.00
4. Modeling of PA .142** .266** .486** 1.00
5. Perceived infl. for PA −.006 .052 .120* .158** 1.00
6. Child age −.468** −.058 −.161** −.046 −.023 1.00
7. Child gender −.221** −.013 .038 .055 .019 −.068 1.00
8. Child ethnicity −.017 .011 .116* .131** −.068 .184** −.046 1.00
9. Child BMI (z-score) −.039 .002 .108* .019 −.051 .061 −.124* .119* 1.00
10. Parent BMI −.037 −.057 .036 −.082 −.084 .008 −.064 .164** .318** 1.00
11. Parent income .032 .022 .009 .006 .222** −.124* .022 −.300** −.163** −.169** 1.00
12. Parent gender .040 .124* −.002 .060 −.023 −.088 −.043 −.069 .051 .000 .161** 1.00
13. Group .051 −.042 .053 .022 .055 −.100* .039 −.196** −.007 −.073 .192** .167** 1.00
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Note: moderate-to-vigorous physical activity (MVPA); physical activity (PA); Body Mass Index (BMI); (n = 423)

Gender coded: 1 = Male, 2 = Female; Ethnicity coded: 1 = Hispanic, 0 = Non-Hispanic; Group: 1 = Preserve, Control = 0

***

p < 0.001,

**

p < 0.01,

*

p < 0.05

For parent encouragement, Model 1 results indicated that parent MVPA (B = .23, SE = .04, p < .001) and parent encouragement (B = .13, SE = (.04), p < .01) were significantly and positively associated with child MVPA, (R2 = .09, p < .001) (Step 1; see Table 3) and that their effects were interactive (B = −.15, ΔR2 = .02, p = .01; Step 2). The interaction term remained significant in Model 2, which adjusted for covariates (ΔR2 = .01, p = .02; Step 2), and the main effects of child gender and age were significant. Older children were less active than younger children (B = −.21, SE = .02, p <.001), and girls were less active than boys (B = −.34, SE = .05, p < .001).

Table 3.

Regression models predicting child MVPA from parent MVPA, moderated by parent encouragement and modeling of physical activity

Model 1
B 		(SE) t p-value Model2
B 		(SE) t p-value
Encouragement
 Step 1 (R2 = .093, p < .001) (R2 = .356, p < .001)
  Encouragement .129 (.041) 3.144 .002 .071 (.036) 1.961 .051
  Parent MVPA .225 (.041) 5.553 .000 .206 (.035) 5.900 .000
  Child age −.204 (.018) −11.178 .000
  Child gender −.338 (.052) −6.444 .000
  Child ethnicity .056 (.058) .971 .332
  Child BMI z-score −.032 (.025) −1.292 .197
  Parent gender −.053 (.072) −.733 .464
  Parent BMI −.004 (.004) −.826 .409
  Income −.023 (.026) −.886 .376
  Group (preserve) .043 (.064) .662 .508
 Step 2 (ΔR2 = .019, p = .003) (ΔR2 = .009, p = .017)
  Enc. × Parent MVPA −.150 (.051) −2.959 .003 −.107 (.044) −2.402 .017
Modeling
 Step 1 (R2 = .077, p < .001) (R2 = .354, p < .001)
  Modeling .073 (.047) 1.551 .122 .065 (.041) 1.602 .110
  Parent MVPA .216 (.042) 5.101 .000 .195 (.036) 5.406 .000
  Child age −.212 (.018) −11.765 .000
  Child gender −.345 (.053) −6.515 .000
  Child ethnicity .075 (.058) 1.287 .199
  Child BMI z-score −.025 (.025) −1.001 .318
  Parent gender −.076 (.072) −1.043 .298
  Parent BMI −.003 (.004) −.649 .517
  Income −.014 (.026) −.537 .592
  Group (preserve) .064 (.064) .999 .318
 Step 2 (ΔR2 = .011, p = .028) (ΔR2 = .003, p = .149)
  Modeling × Parent MVPA −.125 (.057) −2.199 .028 −.070 (.048) −1.444 .149
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Moderate-to-vigorous Physical Activity (MVPA); Body Mass Index (BMI); Gender: 1 = boy, 2 = girl

Model 1 contained only predictor and moderator variables, grand mean centered; Model 2 adjusted for covariates

For parent modeling, Model 1 results were that parent MVPA (B = .22, SE =.04 p < .001) was again significantly associated with child MVPA, but the main effect of parent modeling was not significant (B = .07, SE = .05, p = .12) (Step 1) suggesting that modeling does not increase child MVPA at average levels of parent MVPA. Although adding the interaction term did significantly improve the model (B = −.13, ΔR2 = .01, p = .03; Step 2), suggesting moderation, the interaction term became non-significant in Model 2 after adjusting for child age and gender, (ΔR2 = .00, p = .15; Step 2). Again, older children were less active than younger children (B = −.21, SE =.02, p < .001) and girls were less active than boys (B = −.34, SE = .05, p < .001).

Parent perceived influence was not significantly associated with child MVPA (B = −.02, SE =.06, p = .68; Step 1), and adding the interaction term did not significantly improve the model (ΔR2 = .00, p = .60; Step 2).

Significant interactions were further probed by examining child MVPA at different levels of parent MVPA and moderators. Parent variables were collapsed into categories based on high, average, and low levels according to scores that fell one standard deviation above the mean (“high”), 1 SD below (“low”), or between these values (“average”). Estimated means for child MVPA were graphed at levels of parenting variables, and pairwise comparisons were conducted, controlling for covariates. Fourteen percent (14%) of the sample fell into the “low active” group. Although this categorization was artificial, groups may help convey the clinical relevance of the findings. According to accelerometer data collected in 30 second epochs, these groups correspond to parents who engaged in average daily MVPA of 78 minutes, 24 min., and 7 min.

As shown in Figure 1, among parents who engaged in moderate and high levels of MVPA, child MVPA did not differ between levels of parental encouragement (ps > .05) for physical activity. Children of high MVPA parents had relatively high levels of MVPA across levels of encouragement. However, among parents who engaged in low levels of MVPA, child MVPA was significantly greater for those children receiving high (M = 3.06, SE = .17) vs. low (M = 3.03, SE = .15) parental encouragement (p = 0.02) and moderate (M = 3.40, SE = .09) vs. low parental encouragement (p = 0.04).

Figure 1. Estimated child MVPA (log) at levels of low, average, and high parent MVPA (log) and parent encouragement.

Figure 1

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Note: moderate-to-vigorous physical activity (MVPA). Control variables include child age, child gender, child ethnicity, child BMI z-score, parent gender, parent income, adult BMI and group (Preserve).

Discussion

The current study examined the relationship between parent and child physical activity levels and the moderating effects of parent encouragement, modeling, and perceived influence. Results indicated that parent and child MVPA were positively associated with each other. This study extended previous research by investigating the effects of parent modeling, parent encouragement, and parent perceived influence on the association. For less active parents, more encouragement for physical activity was associated with higher children’s MVPA. For more active parents, these parenting factors did not increase children’s activity higher than their already relatively high levels.

This study provides evidence that parent physical activity is positively associated with child physical activity, in contrast to findings from studies using self-report methods.17,21,39 In addition, the current findings indicate how parenting behaviors may moderate the parent-child physical activity relationship. Parental encouragement of physical activity appears to strengthen the relationship between parent and child MVPA, especially for less active parents. To put these results in the context of prior research, they differ from at least one similar study. Spink et al. (2008) found that parent physical activity did not moderate the effect of parental encouragement on children’s physical activity (Spink et al., 2008). In that study, less encouragement (“telling children to be physically active”) was associated with more active children in highly active parents. The moderation analysis from that study was similar but interpreted in terms of parent MVPA moderating an encouragement-child MVPA link rather than encouragement moderating a parent MVPA-child MVPA link. Although that study’s findings seem to contrast with the current results, the studies used different measures of encouragement/social control. Both measures seem to capture related communicative activity but had a different tone, possibly accounting for the discrepancy. In addition, Spink et al. used parent-reported child physical activity, which could have introduced an issue of same-source bias.

Current findings offer potential alternatives for obesity prevention and treatment programs. Low-active parents may be able to increase their children’s moderate-to-vigorous physical activity through the strategic use of encouragement. Parents who find it difficult to increase their own activity levels due to physical, financial, or time restrictions may find this strategy particularly useful. Intervention programs using this strategy may have the added benefit of higher parent participation rates if parents find it easier to implement parenting practices than to increase their own physical activity. However, prevention programs that promote encouragement in combination with increasing parent physical activity would likely have the greatest impact.

Despite its methodological strengths, including an objective physical activity assessment deployed in parent-child dyads, the study had limitations. First, the data are cross-sectional. Temporal order of the effects between parenting and child MVPA is unknown. Possibly, children who are more active engage parents in physical activity in ways that boost parental encouragement. For example, active children may solicit parent encouragement during sports participation. Second, the study sample was mostly comprised of mothers (84%) and had lower obesity rates than those with missing data, raising questions of representativeness. Fathers are often under-represented in family studies, and some evidence indicates that those who do participate have more education, a more stable presence in the child’s life, less traditional beliefs, and more positive parenting practices40. However, the effect of parent gender was not a significant in our model, indicating that, at least in this sample, the pattern for mothers and fathers was the same. Third, although both parent and child physical activity were measured objectively using accelerometers, parenting behaviors were assessed with self-reports. Potentially, parents’ perceptions of their own encouragement did not reflect actual behavior, or a third unmeasured variable was responsible for both. For example, parents who had high expectations for their children’s activity levels may have communicated these expectations, leading children to be more active. However, those same parents may have also felt pressure to provide socially desirable answers regarding their own encouragement, inflating their scores on these items. Longitudinal studies that include objective measures of parenting behavior, such as direct observation or video, would help address these unanswered questions.

Conclusions

Physical activity is important for children’s health and lowers risk for subsequent obesity, heart disease, and diabetes. This study suggests that parents who are less active may potentially mitigate negative effects of their relative inactivity by strategically encouraging children’s own physical activity.

References

  • 1.Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Medicine and Science in Sports and Exercise. 2008 Jan;40(1):181–188. doi: 10.1249/mss.0b013e31815a51b3. [DOI] [PubMed] [Google Scholar]
  • 2.USDHHS. 2008 physical activity guidelines for Americans. Washington, D.C: 2008. [Google Scholar]
  • 3.Alliance NPAP. [Accessed August 1, 2014];The 2014 United States Report Card on Physical Activity for Children & Youth. 2014 http://www.physicalactivityplan.org/reportcard/NationalReportCard_longform_final%20for%20web.pdf.
  • 4.Andersen LB, Harro M, Sardinha LB, et al. Physical activity and clustered cardiovascular risk in children: a cross-sectional study (The European Youth Heart Study) Lancet. 2006 Jul;368(9532):299–304. doi: 10.1016/S0140-6736(06)69075-2. [DOI] [PubMed] [Google Scholar]
  • 5.Biddle SJH, Gorely T, Stensel DJ. Health-enhancing physical activity and sedentary behaviour in children and adolescents. Journal of Sports Sciences. 2004 Aug;22(8):679–701. doi: 10.1080/02640410410001712412. [DOI] [PubMed] [Google Scholar]
  • 6.Ortega FB, Ruiz JR, Castillo MJ, Sjostrom M. Physical fitness in childhood and adolescence: a powerful marker of health. International Journal of Obesity. 2008 Jan;32(1):1–11. doi: 10.1038/sj.ijo.0803774. [DOI] [PubMed] [Google Scholar]
  • 7.Nemet D, Barkan S, Epstein Y, Friedland O, Kowen G, Eliakim A. Short- and long-term beneficial effects of a combined dietary-behavioral-physical activity intervention for the treatment of childhood obesity. Pediatrics. 2005 Apr;115(4) doi: 10.1542/peds.2004-2172. [DOI] [PubMed] [Google Scholar]
  • 8.Cusatis DC, Shannon BM. Influences on adolescent eating behavior. Journal of Adolescent Health. 1996 Jan;18(1):27–34. doi: 10.1016/1054-139X(95)00125-C. [DOI] [PubMed] [Google Scholar]
  • 9.Dunton GF, Liao Y, Almanza E, Jerrett M, Spruijt-Metz D, Pentz MA. Locations of Joint Physical Activity in Parent-Child Pairs Based on Accelerometer and GPS Monitoring. Annals of Behavioral Medicine. 2013 Feb;45:S162–S172. doi: 10.1007/s12160-012-9417-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Eriksson M, Nordqvist T, Rasmussen F. Associations Between Parents’ and 12-Year-Old Children’s Sport and Vigorous Activity: The Role of Self-Esteem and Athletic Competence. Journal of Physical Activity & Health. 2008 May;5(3):359–373. doi: 10.1123/jpah.5.3.359. [DOI] [PubMed] [Google Scholar]
  • 11.Sallis JF, Prochaska JJ, Taylor WC. A review of correlates of physical activity of children and adolescents. Medicine and Science in Sports and Exercise. 2000 May;32(5):963–975. doi: 10.1097/00005768-200005000-00014. [DOI] [PubMed] [Google Scholar]
  • 12.Wagner A, Klein-Platat C, Arveiler D, Haan MC, Schlienger J, Simon C. Parent-child physical activity relationships in 12-year old French students do not depend on family socioeconomic status. Diabetes & Metabolism. 2004 Sep;30(4):359–366. doi: 10.1016/s1262-3636(07)70129-5. [DOI] [PubMed] [Google Scholar]
  • 13.Welk GJ, Wood K, Morss G. Parental influences on physical activity in children: An exploration of potential mechanisms. Pediatric Exercise Science. 2003 Feb;15(1):19–33. [Google Scholar]
  • 14.Wyszynski CM, Bricker JB, Comstock BA. Parental Smoking Cessation and Child Daily Smoking: A 9-Year Longitudinal Study of Mediation by Child Cognitions About Smoking. Health Psychology. 2011 Mar;30(2):171–176. doi: 10.1037/a0022024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Fredricks JA, Eccles JS. Family socialization, gender, and sport motivation and involvement. Journal of Sport & Exercise Psychology. 2005 Mar;27(1):3–31. [Google Scholar]
  • 16.Bandura A. Health promotion by social cognitive means. Health Education & Behavior. 2004 Apr;31(2):143–164. doi: 10.1177/1090198104263660. [DOI] [PubMed] [Google Scholar]
  • 17.Davison KK, Cutting TM, Birch LL. Parents’ activity-related parenting practices predict girls’ physical activity. Medicine and Science in Sports and Exercise. 2003 Sep;35(9):1589–1595. doi: 10.1249/01.MSS.0000084524.19408.0C. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Karppanen AK, Ahonen SM, Tammelin T, Vanhala M, Korpelainen R. Physical activity and fitness in 8-year-old overweight and normal weight children and their parents. International Journal of Circumpolar Health. 2012:71. doi: 10.3402/ijch.v71i0.17621. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Griffith JR, Clasey JL, King JT, Gantz S, Kryscio RJ, Bada HS. Role of parents in determining children’s physical activity. World Journal of Pediatrics. 2007 Nov;3(4):265–270. [Google Scholar]
  • 20.Trost SG, Loprinzi PD. Parental influences on physical activity behavior in children and adolescents: A brief review. American Journal of Lifestyle Medicine. 2011;5(2):171–181. [Google Scholar]
  • 21.Trost SG, Sallis JF, Pate RR, Freedson PS, Taylor WC, Dowda M. Evaluating a model of parental influence on youth physical activity. American Journal of Preventive Medicine. 2003 Nov;25(4):277–282. doi: 10.1016/s0749-3797(03)00217-4. [DOI] [PubMed] [Google Scholar]
  • 22.Brustad RJ. Attraction to physical activity in urban schoolchildren: Parental socialization and gender influences. Research quarterly for exercise and sport. 1996;67(3):316–323. doi: 10.1080/02701367.1996.10607959. [DOI] [PubMed] [Google Scholar]
  • 23.Dempsey A, Dyehouse J, Schafer J. The Relationship Between Executive Function, AD/HD, Overeating, and Obesity. Western Journal of Nursing Research. 2011 Aug;33(5):609–629. doi: 10.1177/0193945910382533. [DOI] [PubMed] [Google Scholar]
  • 24.Heitzler CD, Martin SL, Duke J, Huhman M. Correlates of physical activity in a national sample of children aged 9–13 years. Preventive Medicine. 2006 Apr;42(4):254–260. doi: 10.1016/j.ypmed.2006.01.010. [DOI] [PubMed] [Google Scholar]
  • 25.Heitzler CD, Lytle LA, Erickson DJ, Barr-Anderson D, Sirard JR, Story M. Evaluating a Model of Youth Physical Activity. American Journal of Health Behavior. 2010;34(5):593–606. doi: 10.5993/ajhb.34.5.9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Pentz MA, Dunton G, Wolch J, et al. DESIGN AND METHODS OF THE HEALTHY PLACES TRIAL: A STUDY OF THE EFFECTS OF SMART GROWTH PLANNING PRINCIPLES ON FAMILY OBESITY PREVENTION. Annals of Behavioral Medicine. 2010 Apr;39:42–42. [Google Scholar]
  • 27.Pentz MA, Dunton G, Huh J, Thomas V. Effects of Living in a Smart Growth Community on Social and Environmental Connectivity, and Physical Activity: The Healthy Places Trial. Obesity. 2010 Oct;18:S58–S58. [Google Scholar]
  • 28.Dunton GF, Intille SS, Wolch J, Pentz MA. Investigating the impact of a smart growth community on the contexts of children’s physical activity using Ecological Momentary Assessment. Health & Place. 2012 Jan;18(1):76–84. doi: 10.1016/j.healthplace.2011.07.007. [DOI] [PubMed] [Google Scholar]
  • 29.Dunton GF, Liao Y, Almanza E, et al. Joint Physical Activity and Sedentary Behavior in Parent-Child Pairs. Medicine and Science in Sports and Exercise. 2012 Aug;44(8):1473–1480. doi: 10.1249/MSS.0b013e31825148e9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Almanza E, Jerrett M, Dunton G, Seto E, Pentz MA. A study of community design, greenness, and physical activity in children using satellite, GPS and accelerometer data. Health & Place. 2012 Jan;18(1):46–54. doi: 10.1016/j.healthplace.2011.09.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Freedson PS, Melanson E, Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Medicine and Science in Sports and Exercise. 1998 May;30(5):777–781. doi: 10.1097/00005768-199805000-00021. [DOI] [PubMed] [Google Scholar]
  • 32.Freedson P, Pober D, Janz KF. Calibration of accelerometer output for children. Medicine and Science in Sports and Exercise. 2005 Nov;37(11):S523–S530. doi: 10.1249/01.mss.0000185658.28284.ba. [DOI] [PubMed] [Google Scholar]
  • 33.Pentz MA, Johnson CA, Dwyer JH, MacKinnon DP, Hansen WB, Flay BR. A comprehensive community approach to adolescent drug abuse prevention: Effects on cardiovascular disease risk behaviors. Annals of Medicine. 1989;21:219–222. doi: 10.3109/07853898909149937. [DOI] [PubMed] [Google Scholar]
  • 34.CDC. Youth Risk Behavior Surveillance—United States, 2011. MMWR. 2012;61(SS-4) [PubMed] [Google Scholar]
  • 35.CDC. [Accessed June 19, 2013];A SAS Program for the CDC Growth Charts. 2011 http://www.cdc.gov/nccdphp/dnpao/growthcharts/resources/sas.htm.
  • 36.Frazier PA, Tix AP, Barron KE. Testing moderator and mediator effects in counseling psychology research. Journal of Counseling Psychology. 2004 Jan;51(1):115–134. [Google Scholar]
  • 37.Aiken LS, West SG, Reno RR. Multiple regression : testing and interpreting interactions. Newbury Park, Calif: Sage Publications; 1991. [Google Scholar]
  • 38.Hayes AF. Introduction to Mediation, Moderation, and Conditional Process Analysis:A Regression-Based Approach. New York, NY: Guilford Press; 2013. [Google Scholar]
  • 39.Kimiecik JC, Horn TS. Parental beliefs and children’s moderate-to-vigorous physical activity. Research Quarterly for Exercise and Sport. 1998 Jun;69(2):163–175. doi: 10.1080/02701367.1998.10607681. [DOI] [PubMed] [Google Scholar]
  • 40.Costigan CL, Cox MJ. Fathers’ participation in family research: Is there a self-selection bias? Journal of Family Psychology. 2001;15(4):706. doi: 10.1037//0893-3200.15.4.706. [DOI] [PubMed] [Google Scholar]

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