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Article |

Factors Associated With Changes in Physical Activity:  A Cohort Study of Inactive Adolescent Girls FREE

Dianne Neumark-Sztainer, PhD; Mary Story, PhD; Peter J. Hannan, MStat; Terri Tharp, MPH; Jeanna Rex, MEd
[+] Author Affiliations

From the Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis.


Arch Pediatr Adolesc Med. 2003;157(8):803-810. doi:10.1001/archpedi.157.8.803.
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Objective  To identify factors associated with changes in physical activity in adolescent girls at risk for sedentary lifestyles and obesity.

Design  A cohort study was performed with 201 high school girls recruited to participate in an evaluation study of a school-based obesity prevention physical education program. Three assessments were performed during an 8-month period.

Main Outcome Measures  Associations between physical activity and a range of personal factors (self-acceptance, self-worth, athletic competence, body image, depressive mood, perceived benefits, enjoyment of physical activity, self-efficacy, and body mass index), behavioral factors (watching television and time constraints), and socioenvironmental factors (social support and costs/resources) were assessed.

Results  The 2 strongest and most consistent factors associated with change in physical activity were time constraints and support for physical activity from peers, parents, and teachers. Measures assessing self-perceptions, global (ie, self-worth) and specific to physical activity (ie, self-efficacy to be physically active), were also associated with change in physical activity. For example, a decrease of 2.0 U for an adolescent's perceived time constraints (possible range, 3.0-12.0 U) would be expected to lead to an increase of 53 minutes of moderate to vigorous physical activity per week (95% confidence interval, 33-72 minutes). An increase of 2.0 U in perceived support for physical activity (possible range, 3.0-12.0 U) would be expected to lead to an increase of 35 minutes of moderate to vigorous physical activity per week (95% confidence interval, 13-56 minutes). An increase of 3.0 U on the self-worth scale (possible range, 5.0-20.0 U) might be expected to lead to an increase of 19 minutes of moderate to vigorous physical activity per week (95% confidence interval, 0-40 minutes).

Conclusion  The effectiveness of interventions aimed at increasing physical activity among adolescent girls might be enhanced by engaging support from friends, family, and caring adults; addressing real and perceived time constraints; and helping adolescent girls feel more confident about themselves and their ability to engage in physical activity.

PHYSICAL ACTIVITY is an important component of a healthy lifestyle, with implications for the prevention of chronic diseases and obesity.1 However, physical activity declines sharply during adolescence, particularly among adolescent girls. Data from the 2001 National Youth Risk Behavior Surveillance2 indicate that high school girls in all racial/ethnic groups are less active than high school boys; 38% of adolescent girls and 24% of adolescent boys did not meet national recommendations for moderate or vigorous physical activity.1,3 Furthermore, adolescent girls were more likely than adolescent boys to report not participating in any vigorous or moderate physical activity in the previous week (adolescent girls, 12%; and adolescent boys, 7%). Physical activity tends to decline as youths progress through high school, with a widening sex gap. For example, among 9th graders, 28% of adolescent girls and 20% of adolescent boys reported low physical activity; this increased to 48% of adolescent girls and 30% of adolescent boys in the 12th grade. Furthermore, the proportion of adolescent girls reporting no vigorous or moderate physical activity in the previous week almost doubled from 9th to 12th grade (increasing from 8% to 15%).2 Overweight adolescent girls may be at even higher risk for low levels of physical activity, which may place them at increased risk for further weight gain.4

To prevent this decline in physical activity among adolescent girls, it is essential to identify factors correlated with physical activity that are amenable to change and can be addressed within interventions. Sallis et al5 conducted a comprehensive review of 108 studies on factors associated with physical activity in children and adolescents, and concluded that there is a need for further studies because there was considerable lack of consistency across studies. They noted that differences in samples across studies may have contributed to this lack of consistency. It is important to identify factors likely to influence the physical activity of adolescent girls at greatest risk for low levels of activity, such as overweight adolescent girls. Most of the studies reviewed by Sallis et al focused primarily on population-based samples of youth rather than on subgroups of the adolescent population at increased risk for inactive lifestyles. Furthermore, most studies have used cross-sectional designs, not allowing for an examination of factors associated with change in physical activity over time.5 To guide the development of interventions for youth at risk for sedentary lifestyles, it is important to identify factors associated with change in physical activity over time, and to determine whether these factors tend to be similar in these high-risk youth compared with the broader adolescent population.

The present study expands on the existing body of research examining factors associated with physical activity in high school girls, specifically adolescent girls at risk for sedentary lifestyles. A cohort design was used to study factors associated with changes in moderate physical activity, vigorous physical activity, and moderate to vigorous physical activity (MVPA) over time. Variables selected for inclusion as potential predictors were theoretically driven, using Social Cognitive Theory as a guide,6,7 and included a range of personal, behavioral, and socioenvironmental variables. Practical considerations were also considered in choosing variables; we focused on variables that are potentially amenable to change and are suitable for addressing within interventions. Findings may help guide the development of interventions aimed at increasing physical activity among adolescent girls at risk for inactive lifestyles and obesity.

STUDY POPULATION AND DESIGN

The study population included 201 adolescent girls who participated in an evaluation study of New Moves, a school-based obesity prevention physical education program.8 New Moves targeted adolescent girls who were overweight or at risk for becoming overweight because of low levels of physical activity. Adolescent girls were recruited from 6 high schools, in the Minneapolis/St Paul area, that were randomized into 3 intervention and 3 control schools. There were 90 participants in the intervention schools and 111 participants in the control schools. The mean (SD) age of the adolescent girls was 15.4 (1.1) years; 25% were in 9th grade, 41% were in 10th grade, 19% were in 11th grade, and 15% were in 12th grade. The ethnic distribution of participants was as follows: 42% white, 29% African American, 21% Asian American, 4% Hispanic, 1% Native American, and 4% mixed or other. The adolescent girls' mean (SD) body mass index (BMI) (calculated as weight in kilograms divided by the square of height in meters) was 26.7 (6.5); 62% of the adolescent girls had BMI values 75th percentile or higher for age and sex (19% had BMI values between the 85th and 95th percentile, and 31% had BMI values 95th percentile or higher).9

Three assessments were conducted during an 8-month period: at baseline (September 2000), postintervention (January 2001), and follow-up (April 2001). Response rates were 94% at the second assessment and 92% at the third assessment. Reasons for attrition included moving out of the school district or state, suspension from school, drug rehabilitation, severe illness, and no-shows or refusals. The profile of responders and nonresponders (at either postintervention or follow-up) did not differ significantly across mean (SD) age (15.3 [1.0] vs 14.8 [0.9] years; P = .65), mean (SD) BMI (26.6 [6.4] vs 26.6 [6.9]; P = .96), and race/ethnicity (44% white, 28% African American, 20% Asian American, and 8% mixed or other vs 26% white, 35% African American, 26% Asian American, and 13% other; P = .42).

Participants in the intervention schools were enrolled in the New Moves program. Instead of regular coed physical education class, they participated in an adolescent girls–only class for 1 semester (5 days per week for 16 weeks) that included physical activity, nutritional guidance, and social support.8,10,11 Participants in the control schools received a minimal intervention that included written materials on healthy eating and physical activity that were distributed at the baseline assessment. A small percentage of adolescent girls in the control group (12%) participated in a standard physical education class during the study period. Study procedures were approved by the Human Subjects Institutional Review Board at the University of Minnesota and by the participating school districts. Active consent was obtained before study participation, including signed parental consent and student assent.

RECRUITMENT AND SCREENING OF PARTICIPANTS

Recruitment flyers and posters were used to promote the study to high school girls. Recruitment materials were designed to attract adolescent girls who had low levels of physical activity, wanted to become more active, and were interested in healthy weight management. Interested students were directed to contact the school's New Moves liaison to sign up for the study, turn in a signed parental or guardian consent form, and complete a brief screening survey. The highest priority for study inclusion was given to adolescent girls with low physical activity, defined as being in the precontemplation, contemplation, or preparation stage of change for physical activity,1214 with activity levels (any physical activity, regardless of intensity) at or below 30 minutes per day for 3 days per week. To assess stage of change for physical activity, girls were asked 1 question with 5 response categories, ranging from "I am not physically active and do not intend to become active" (precontemplation) to "I am regularly active and have been for longer than six months" (maintenance). Girls were also asked about their current weight and height, and those with self-reported BMI values 75th percentile or higher and low levels of physical activity were given preference for participation. Adolescent girls who reported that a physician had told them that they had an eating disorder and/or reported disordered eating behaviors (ie, self-induced vomiting or use of diet pills, laxatives, or diuretics) during the past month were excluded from study participation.

DESCRIPTION OF MEASURES

Variables assessing level of physical activity and potentially relevant variables from the personal, behavioral, and socioenvironmental domains are described in Table 1. Physical activity was measured using a modified version of the Leisure Time Exercise Questionnaire.15 This measure has been used in previous studies,2023 and has been shown to be reliable and significantly correlated with other measures of physical activity in children and adolescents.24 Questions on sedentary activity assessed average hours per week spent watching television and videotapes on weekends and weekdays.

Table Graphic Jump LocationTable 1. Description of Variables Assessing PA and Variables of Potential Relevance for PA From Within Personal, Behavioral, and Socioenvironmental Domains

The selection of personal, behavioral, and socioenvironmental variables was guided by a thorough review of the literature to identify factors most likely to be associated with physical activity, Social Cognitive Theory,6,7 and objectives of the New Moves program.8 A broad array of personal variables was assessed, including measures of body image, overall self-image, psychological well-being, and cognitive measures specifically related to physical activity (eg, self-efficacy to be physically active and enjoyment of physical activity).

Before development of the final evaluation tools, measures were assessed for test-retest reliability during a 1-month period in a population of 56 adolescent girls from a local high school that serves a student population similar to the study population. Test-retest reliabilities for variables obtained from this sample are shown in Table 1. Also shown are measures of internal consistency (Cronbach α) for scales that were obtained from the baseline study population (N = 201).

DATA ANALYSIS

The distributions of the activity variables were first examined graphically, and were generally symmetric. This was done to ensure the appropriateness of models to be tested, which assume a gaussian distribution. For longitudinal regression analyses, the averages of baseline, posttest, and follow-up data for each girl were calculated, and deviations from each girl's average were generated by subtracting the average from the measure specific to each time point. The 3 deviations are measures of change for each outcome and each independent variable. Because the deviations add to zero within adolescent girl, they contribute a df = 2 to the estimation of the regression of change in outcome on change in independent variables. If the girl is missing the posttest or the follow-up survey, the contribution is only a df = 1. Within girl, changes in outcome were fit by a linear regression model of changes in independent variables. Backward elimination25,26 with manual choice of the variable next to be removed (based on the P value) was used to simplify each regression model until only statistically significant contributors remained. The 2 adjusting changing variables (age and BMI) were retained in all competing models and not tested. The process was performed separately for vigorous physical activity, moderate physical activity, and MVPA.

No adjustment for the intervention condition was necessary in these models, nor for race. The intervention and race are fixed covariates for each girl and so cannot explain changes within girl. This is equivalent to the assumption that the regression relationships do not differ by intervention status. It is hypothesized that whatever mechanisms for changes operate in girls in the control condition operate similarly in girls in the intervention condition, although the changes may be larger.

To give perspective to the abstract regression coefficient, we calculated the expected change in time in physical activity per week for a change equivalent to about 1 SD in each independent variable, keeping the other regressors unchanged. Finally, goodness of fit was calculated as the percentage of variance explained by the independent variables, adjusted for changing age (trend) and BMI. All analyses were performed using SAS statistical software, release 8.2.26

LEVELS OF PHYSICAL ACTIVITY AND TIME SPENT WATCHING TELEVISION IN THE STUDY POPULATION

At baseline, adolescent girls reported participating in a mean (SD) of 1.5 (1.8) hours of vigorous activity, 1.8 (1.7) hours of moderate activity, and 3.3 (2.9) hours of total MVPA during the past week. In contrast, adolescent girls reported a mean (SD) of 17.3 (12.6) hours of watching television (or videotapes) in the past week.

Baseline levels of physical activity and time spent watching television were examined across BMI, age, and race/ethnicity (Table 2). The BMI was not associated with moderate or vigorous physical activity, but was positively associated with time spent watching television. An inverse association was found between age and physical activity; older adolescent girls reported less vigorous activity and total MVPA. Associations between age and time spent watching television were significant but not linear; adolescent girls in the youngest and oldest groups watched less television than adolescent girls in the middle groups. Race/ethnicity was not significantly associated with physical activity, but was significantly associated with watching television; African American girls reported the most television watching. Analyses were also performed mutually adjusting for BMI, age, and race/ethnicity; patterns were similar to those for unadjusted analyses (data not shown).

Table Graphic Jump LocationTable 2. Time Spent on PA and on Watching Television by BMI, Age, and Race/Ethnicity*
FACTORS ASSOCIATED WITH CHANGE IN PHYSICAL ACTIVITY

To examine factors associated with changes in physical activity, initial multivariate models were run for change in vigorous physical activity, moderate physical activity, and MVPA. These models included change in all of the personal, behavioral, and socioenvironmental variables included in Table 1, and were adjusted for change in age and BMI. The estimates of the initial model are shown in Table 3 for MVPA. Models were then simplified to retain only variables that were either significantly associated with physical activity or of marginal statistical significance and showed a consistent pattern across different levels of physical activity (Table 4); age and BMI were always included. The final models indicate that factors associated with change in vigorous physical activity and MVPA during the study period included time constraints and social support for physical activity; associations with self-worth were of marginal statistical significance (Table 4). Time constraints and self-efficacy to be physically active were associated with change in moderate physical activity.

Table Graphic Jump LocationTable 3. Associations Between Personal, Behavioral, and Socioenvironmental Variables and Change in MVPA Over Time*
Table Graphic Jump LocationTable 4. Variables Associated With Change in PA Over Time*

To make the regression results concrete, we calculated the expected impact of a change in each independent variable, keeping the other independent variables constant. The changes were taken to be approximately equal to the SDs of the variables in this population. For example, an increase of 3.0 U on the self-worth scale (possible range, 5.0-20.0 U) might be expected to lead to an increase of 19 minutes of MVPA per week (95% confidence interval, 0-40 minutes). A decrease of 2.0 U for an adolescent's perceived time constraints (possible range, 3.0-12.0 U) would be expected to lead to an increase of 53 minutes of MVPA per week (95% confidence interval, 33-72 minutes). An increase of 2.0 U in perceived support for physical activity from parents, peers, and teachers (possible range, 3.0-12.0 U) would be expected to lead to an increase of 35 minutes of MVPA per week (95% confidence interval, 13-56 minutes).

A regression adjustment for changes in self-worth, perceived time constraints, and support for physical activity reduced the variance for change in time spent in vigorous activity from 0.90 to 0.67 (a 26% reduction), conditional on the adjustment for trend (age) and change in BMI. The corresponding reductions in the models for changes in moderate physical activity and MVPA were from 1.70 to 1.61 (5%) and from 4.99 to 4.45 (11%), respectively.

This study aimed to identify factors associated with change in physical activity over time among adolescent girls at risk for sedentary lifestyles. In multivariate models, the 2 strongest and most consistent factors associated with change in physical activity were as follows: (1) time constraints, which were inversely associated with physical activity; and (2) support for physical activity from parents, peers, and teachers, which was positively associated with physical activity. Measures assessing self-perceptions, global (ie, self-worth) and specific to physical activity (ie, self-efficacy to be physically active), were also positively associated with physical activity, albeit associations with self-worth were of marginal statistical significance. These findings suggest the importance of addressing time constraints within interventions; youths may need help in time management, making physical activity a priority, and finding ways to fit physical activity into their daily activities. Previous research has similarly demonstrated the importance of time constraints as a barrier to physical activity; in a study27 of 236 high school adolescents, "wanting to do other things with one's time" was the most frequently cited barrier to regular exercise. Findings from the present study further suggest that interventions aimed at increasing physical activity among adolescent girls might be enhanced by enlisting support from significant others in the adolescent girls' lives. Other studies have also shown that parental support23,2830 and peer support23,28,30,31 for physical activity are correlated with active lifestyles among adolescents. In addition, our findings suggest the importance of helping adolescent girls develop confidence in themselves and their physical activity skills. Previous research in children and adolescents has similarly suggested the importance of perceived physical/sports competence32 and self-efficacy to be physically active.33,34

In the present study, the 3 factors most strongly associated with physical activity (time constraints, support for physical activity, and self-perceptions) came from the 3 different domains identified in Social Cognitive Theory (behavioral, socioenvironmental, and personal domains, respectively). Similarly, in a review of the literature examining correlates of physical activity in children and adolescents, Sallis et al5 found significant modifiable variables from within each of the behavioral, social/cultural, and psychological/cognitive domains, indicating that physical activity in youth is a complex behavior determined by multiple factors. Findings from our study and this comprehensive review suggest the importance of addressing variables from different domains within interventions aimed at increasing physical activity within the general population of youth and within subsamples of youth at risk for sedentary lifestyles.

The large difference in time spent in physical activity compared with time spent watching television/videotapes is striking, and demonstrates the sedentary nature of the adolescent girls in this study and the potential for increasing physical activity through the substitution of sedentary activities with physical activities. However, the lack of association between television watching and physical activity in the present study suggests that substitution of time spent watching television with time spent in leisure physical activities may not be occurring among youth. Similarly, in a study of 4746 adolescents in Minnesota, there was no relationship between watching television and physical activity, and different factors were correlated with television viewing than with physical activity.23 In a longitudinal study of 971 middle school adolescents in California, Robinson et al35 found weak associations between baseline television viewing and physical activity in cross-sectional analyses, but no associations with change in level of physical activity over time. Experimental studies with younger children have provided inconsistent findings with regard to whether changes in sedentary behaviors lead to changes in level of physical activity. In a laboratory study with overweight children, Epstein et al36 found that reinforcing a decrease in sedentary behaviors was associated with an increase in physical activity. In nonoverweight children, Epstein et al37 found that increases in sedentary activity were associated with significant increases in calorie (energy) intake and decreases in calorie expenditure; however, decreases in sedentary behaviors were not significantly associated with changes in calorie balance (intake and expenditure). In a school-based intervention aimed at decreasing sedentary behaviors (television/videotape viewing and video games) in third and fourth graders, Robinson38 did not find an effect on reported levels of moderate and vigorous activity or on cardiorespiratory fitness, but did find an effect on BMI. These findings suggest that the relationship between television watching and physical activity is more complex than a simple substitution of one with the other.

Overall, the socioenvironmental, personal, and behavioral variables assessed in this study did not explain large percentages of the variance in physical activity levels. In part, this may be because of difficulties in measuring the independent and dependent variables. However, this also suggests that other factors, not assessed in this study, may be influencing physical activity levels. For example, although we assessed perceived socioenvironmental factors, we did not assess actual social and physical aspects of the adolescent girls' environment that might impact their physical activity (eg, opportunities for overweight adolescent girls to be physically active, sidewalks and lights in neighborhoods, bus transportation from after-school activities, and time availability of parents). We also did not assess to what degree adolescent girls perceive that physical activity negatively impacts their appearance (eg, leads to sweating, ruins hairstyle, and causes bulkiness and large muscles) and how much that discourages them from engaging in physical activity. In a study39 that used focus groups to explore factors influencing physical activity among 34 African American and Latina adolescent girls, both of these factors (lack of opportunities for physical activity and concerns about appearance after physical activity) emerged as perceived barriers to physical activity. Other factors not assessed in the present study but identified as perceived barriers to physical activity in a sample of 2298 adults include having an injury or disability, health concerns, lack of motivation or difficulty getting started, feeling "too fat," and not seeing oneself as the "sporty type."40 This last point (not being the sporty type) raises the issue of self-identity. Garcia et al41 discussed the importance of an exercise self-schema, particularly for adolescent girls. Exercise self-schemas are attributed to people who consider exercise-related attributes to be highly self-descriptive and key to their self-image. Although we assessed factors such as athletic competence in the present study, we did not assess the degree to which youth incorporate their level of physical activity or a particular type of physical activity into their self-identity.

The present study had several strengths that contribute to the utility of the findings. Factors selected to be included as potential predictors of physical activity were based on a sound theoretical framework and a thorough review of the literature for suitable instruments. Only when suitable preexisting tools could not be identified were questions/scales developed and tested to assess test-retest reliability and internal consistency. The unique composition of the study population is another strength of the study because it is essential to understand the factors correlated with physical activity among adolescent girls at risk for sedentary lifestyles. Adolescent girls in the present study reported considerably lower levels of weekly MVPA (mean [SD], 3.2 [2.9] hours) than were found among the general population of female students in the Minneapolis/St Paul area (mean [SD], 5.6 [4.5] hours) in another study23 in which similar measures were used to assess physical activity. Finally, the longitudinal experimental design used in this study allows for assessing whether a change in one variable (eg, increase in enjoyment of physical activity) is associated with a change in another variable (eg, increase in physical activity); if so, this provides increased support for a predictive relationship between 2 variables. However, this study also had limitations that need to be considered in interpreting the findings. The measure used to assess level of physical activity was brief and based on self-report. In addition, although the experimental and longitudinal nature of the study design provided more information than would be possible from a cross-sectional analysis, the time intervals between assessments were small.

While the findings provide insight into the types of factors influencing physical activity among adolescent girls, they also suggest that a broader range of personal, behavioral, and socioenvironmental factors needs to be explored in future research studies. Furthermore, variables associated with physical activity in the present study, such as social support, should be examined in more depth. Studies using more objective measures of physical activity are needed to better understand predictive factors. Finally, longitudinal studies that capture periods of transition in levels of physical activity (ie, from early to later stages of adolescence) should be conducted.

Findings from the present study can inform the development of more effective programs to increase physical activity among adolescent girls. One socioenvironmental factor that should probably be addressed is that of social support for physical activity. Parents and teachers need to hear how much their support matters to their children, even when they are in high school. Because of the importance of peer relationships during adolescence, programs can build in opportunities for peer support and participation. A behavioral factor that needs to be addressed is time constraints; interventions may aim to provide more time for physical activity (eg, within the school day) or help adolescents learn strategies for fitting physical activity into their daily routines. For example, it may be useful to discuss tips for engaging in 5 minutes of physical activity at several times throughout the day, and provide and review activity logs with adolescents to look for time for physical activity. The objective time constraints that many teenagers experience (eg, schoolwork, part-time jobs, household chores, and other leisure pursuits) should not be minimized. These potentially serious sources of stress may make decisions to engage in physical activity during discretionary time unlikely or difficult. Although increased television watching was only moderately associated with decreased levels of physical activity, the large amount of time spent watching television suggests that the potential exists to address time constraints through a reduction in sedentary activities. A personal factor of potential importance is self-perception, because adolescent girls who felt better about themselves and their athletic competence were more likely to be active. Likewise, learning and improving physical activity skills and competence may positively impact physical activity levels. In summary, findings from the present study suggest that interventions leading to meaningful but reasonable changes in social support, perceived time constraints, self-perceptions, and physical activity skills may lead to increases in physical activity.

Corresponding author: Dianne Neumark-Sztainer, PhD, Division of Epidemiology, School of Public Health, University of Minnesota, 1300 S Second St, Suite 300, Minneapolis, MN 55454 (e-mail: Neumark@epi.umn.edu).

Accepted for publication April 17, 2003.

This study was supported by grant AHA NATL/9970064N from the American Heart Association (Dr Neumark-Sztainer).

What This Study Adds

This study explored predictors of physical activity in adolescent girls at risk for sedentary lifestyles and obesity. It expands on the existing literature examining correlates of physical activity in that it focuses on a high-risk subgroup of youths who are in need of appropriate interventions. The strongest and most consistent predictors of change in physical activity were as follows: time constraints, which was inversely associated with physical activity; and support for physical activity from parents, peers, and teachers, which was positively associated with change in physical activity. Measures assessing different aspects of self-image also predicted change in physical activity. The findings suggest that in interventions aimed at increasing physical activity among adolescent girls at risk for sedentary lifestyles and obesity, efforts should be made to provide support from significant others, address real and perceived time constraints, and help adolescent girls feel better about themselves in general and more specifically about their physical activity skills.

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Allison  KRDwyer  JJMMakin  S Self-efficacy and participation in vigorous physical activity by high school students. Health Educ Behav. 1999;2612- 24
PubMed Link to Article
Pate  RRTrost  SGFelton  GMWard  DSDowda  WMSaunders  R Correlates of physical activity behavior in rural youth. Res Q Exerc Sport. 1997;68241- 248
PubMed Link to Article
Robinson  TNHammer  LDKillen  JD  et al.  Does television viewing increase obesity and reduce physical activity? cross-sectional and longitudinal analyses among adolescent girls. Pediatrics. 1993;91273- 280
PubMed
Epstein  LHSaelens  BEMyers  MDVito  D Effects of decreasing sedentary behaviors on activity choice in obese children. Health Psychol. 1997;16107- 113
PubMed Link to Article
Epstein  LHPaluch  RAConsalvi  AKristy  RScholl  T Effects of manipulating sedentary behavior on physical activity and food intake. J Pediatr. 2002;140334- 339
PubMed Link to Article
Robinson  TN Reducing children's television viewing to prevent obesity: a randomized controlled trial. JAMA. 1999;2821561- 1567
PubMed Link to Article
Taylor  WCYancey  AKLeslie  J  et al.  Physical activity among African American and Latino middle school girls: consistent beliefs, expectations, and experiences across two sites. Women Health. 1999;3067- 82
PubMed Link to Article
Ball  KCrawford  DOwen  N Too fat to exercise? obesity as a barrier to physical activity. Aust N Z J Public Health. 2000;24331- 333
PubMed Link to Article
Garcia  AWBroda  MAFrenn  MCoviak  CPender  NJRonis  DL Gender and developmental differences in exercise beliefs among youth and prediction of their exercise behavior. J Sch Health. 1995;65213- 219
PubMed Link to Article

Figures

Tables

Table Graphic Jump LocationTable 1. Description of Variables Assessing PA and Variables of Potential Relevance for PA From Within Personal, Behavioral, and Socioenvironmental Domains
Table Graphic Jump LocationTable 2. Time Spent on PA and on Watching Television by BMI, Age, and Race/Ethnicity*
Table Graphic Jump LocationTable 3. Associations Between Personal, Behavioral, and Socioenvironmental Variables and Change in MVPA Over Time*
Table Graphic Jump LocationTable 4. Variables Associated With Change in PA Over Time*

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PubMed Link to Article
Allison  KRDwyer  JJMMakin  S Self-efficacy and participation in vigorous physical activity by high school students. Health Educ Behav. 1999;2612- 24
PubMed Link to Article
Pate  RRTrost  SGFelton  GMWard  DSDowda  WMSaunders  R Correlates of physical activity behavior in rural youth. Res Q Exerc Sport. 1997;68241- 248
PubMed Link to Article
Robinson  TNHammer  LDKillen  JD  et al.  Does television viewing increase obesity and reduce physical activity? cross-sectional and longitudinal analyses among adolescent girls. Pediatrics. 1993;91273- 280
PubMed
Epstein  LHSaelens  BEMyers  MDVito  D Effects of decreasing sedentary behaviors on activity choice in obese children. Health Psychol. 1997;16107- 113
PubMed Link to Article
Epstein  LHPaluch  RAConsalvi  AKristy  RScholl  T Effects of manipulating sedentary behavior on physical activity and food intake. J Pediatr. 2002;140334- 339
PubMed Link to Article
Robinson  TN Reducing children's television viewing to prevent obesity: a randomized controlled trial. JAMA. 1999;2821561- 1567
PubMed Link to Article
Taylor  WCYancey  AKLeslie  J  et al.  Physical activity among African American and Latino middle school girls: consistent beliefs, expectations, and experiences across two sites. Women Health. 1999;3067- 82
PubMed Link to Article
Ball  KCrawford  DOwen  N Too fat to exercise? obesity as a barrier to physical activity. Aust N Z J Public Health. 2000;24331- 333
PubMed Link to Article
Garcia  AWBroda  MAFrenn  MCoviak  CPender  NJRonis  DL Gender and developmental differences in exercise beliefs among youth and prediction of their exercise behavior. J Sch Health. 1995;65213- 219
PubMed Link to Article

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