Physical activity is associated with an array of health benefits, including decreased risk of type 2 diabetes, metabolic syndrome, cardiovascular disease, breast and colon cancer, and up to a 30% reduction in all cause mortality (11,22). Mental health benefits of physical activity have also been observed for depression and anxiety among both adults and adolescents (2,37). The mechanisms explaining this link include the development of positive self-worth, self-esteem, social support systems, and self-efficacy as well as physiological mechanisms such as neural plasticity and neurological system changes involving norepinephrine, dopamine, and serotonin (2,9). Self-worth and self-esteem have received considerable attention in child and adolescent research given that these constructs are recognized as important indicators of positive mental health and well-being (2,24,34). Self-worth has been described as the average general satisfaction with oneself across several domains (e.g., physical, social, and intellectual), whereas self-esteem represents the evaluation and affect one holds toward themselves based on a hierarchical and multidimensional framework in which specific domains of the self are nested (18,29). Although traditionally viewed as distinct constructs, self-worth and self-esteem both reflect a broader sense of self-concept, defined as the organized perceptions of the self that are consciously available (41).
The association between physical activity and self-concept in children has been analyzed using a variety of methodologies, yet the direction and existence of this relationship remains controversial. A systematic review of 25 randomized controlled trials found that short-term exercise had a beneficial effect on self-esteem among children and adolescents (3–20 yr of age) (10). However, the studies included in this review were limited to short follow-up periods (2–20 wk), relatively small sample sizes (n = 24–288), and 14 of the 25 trials were assessed to have a high risk of bias (10). Insufficient follow-up is particularly concerning in this context because adolescence represents a period of significant psychological, physiological, and social development. Psychological changes associated with adolescence involve the development of multiple self-identities, each with their own affinity, that vary based on the diverse social and relational roles in this developmental stage (16,21). For instance, self-evaluations vary based on the description of their roles with parents, friends, classmates, or romantic partners (16,21).
With regard to physical activity and self-worth, the relationship is also unclear. Early reports found that global self-worth (GSW) was associated with increased physical activity levels (8,32), whereas more recent studies conclude that physical activity promotes GSW (33,34,40,47,49), and a third group of studies have found associations between physical activity and domain-specific self-worth, but not GSW (15,24,44). Of these studies, the vast majority used observational designs; of the two randomized controlled trials conducted in this area, both found that physical activity improved GSW (15,33,34). However, these trials were restricted to overweight and obese participants engaged in structured physical activity programs, and only two of the observational studies analyzed sample sizes greater than 250 (24,44). Inchley et al. (24) (N = 641) found that the physical self-worth domain increased physical activity levels, whereas the largest study by Stein et al. (44) (N = 5260) found that physical activity improved physical and social subdomains of self-worth but not GSW. The variability in these finding may be, in part, attributed to the different types of physical activities analyzed in each study. For example, group-based cooperative physical activities may produce improvements in the social acceptance domain of self-worth, whereas individual fitness based exercise may not produce these benefits. It is possible that physical activities addressing a combination of self-worth subdomains are needed to produce significant changes in GSW. Nevertheless, the relationship between physical activity and GSW remains uncertain.
Additional determinants of self-concept include physical characteristics such as body composition and physical fitness (12,41). The exercise and self-esteem model (EXSEM) provides a framework for understanding the mechanism of these associations (41). This model predicts that physical changes associated with exercise (e.g., improved fitness and body composition) will result in increased self-efficacy (12,41). These improvements in self-efficacy are then believed to enhance physical self-perceptions in several subdomains (e.g., sport, conditioning, body, and strength), which translate into increased global physical self-worth and global self-concept (12). This model conceptualizes physical changes as mediators of the relationship between exercise and self-concept, and given that children's perceived competence in the physical appearance domain has the greatest effect on GSW, it is expected that physical fitness and body composition may represent important mediators of the association between physical activity and self-concept (20). Evidence from a previous review supported this hypothesis by demonstrating that improvements in physical fitness mediated the association between physical activity and global self-esteem (43). A previous systematic review identified sedentary behavior as another important predictor of self-worth and reported that each additional hour of TV viewing was associated with significant decreases in self-worth and self-concept (45).
Determinants of self-concept can also be understood through the psychological centrality hypothesis, which proposes that the effect of each self-conception of global self-esteem is moderated by the importance the individual attaches to each self-conception (38,39). Given the physical and psychological changes that occur during childhood and adolescence, the value assigned to each of their qualities may fluctuate during this period. In addition, these developmental changes occur at different rates in males and females raising the possibility that sex may moderate these changes in self-concept. Previous studies support this hypothesis by indicating that self-evaluations vary as new relationships are developed, and the importance of self-worth subdomains, such as physical appearance, varies significantly among boys throughout adolescence (16,21,36).
In response to these mixed findings and methodological limitations, we sought to analyze the relationship between physical activity and GSW in a prospective cohort study of children. To build on the existing literature, we analyzed physical activity and sedentary behaviors as distinct exposures and examined if the effect of physical activity on GSW changed over time or varied by sex. A mediation analysis was also performed to determine whether the association between physical activity and GSW could be partially explained by changes in body composition and/or fitness. These associations were analyzed in a repeated-measures design with eight follow-up contacts over a 4-yr study period.
The data for this investigation were collected from the Physical Health Activity Study Team (PHAST) project. This is a longitudinal cohort study of children (8–10 yr of age), which includes data pertaining to anthropometry, socioeconomic status, physical activity, aerobic fitness, motor coordination, and psychological health. The study began in the spring of 2005 and included children who were enrolled in the public school system in the Niagara region of Ontario, Canada. Children who were not English speaking or who were living with known physical or intellectual disabilities were excluded from the study. Seventy-five of 92 schools granted permission to enroll students, and written informed consent was obtained from the parents of 2278 of 2378 (95.8%) children. A total of eight waves of data collection were conducted from 2005 to 2009: wave 1 = spring 2005, wave 2 = fall 2005, wave 3 = spring 2006, wave 4 = fall 2006, wave 5 = spring 2007, wave 6 = fall 2007, wave 7 = fall 2008, and wave 9 = fall 2009. A total of 2278 children were included in the analysis at baseline, whereas 1581 (69%) were available at follow-up. Both the district school board and Brock University provided ethical approval for the study.
The GSW subscale from the self-perception profile for children (SPPC) was administered to measure participants' self-worth in the PHAST cohort (19). The items are designed to elicit the participants' perception of their overall worth as a person. Each question is written in a “structured alternative format” where the child must select one of two response options (e.g., some kids are often unhappy with themselves, but other kids are pretty pleased with themselves) rather than rating their responses on a scale. Although this approach helps reduce the frequency of socially desirable responses, the complicated structured alternative format has been shown to reduce reliability in some studies (14,18). After selecting one of the two options, the child then rated whether the statement was “sort of true for me” or “really true for me” (19). The GSW subscale includes six items, and each item is given a score from one to four, with higher values indicating greater perception of GSW. The scores are summed to create total score ranging from 6 to 24, and the construct validity of this subscale has been supported by studies demonstrating negative correlations with depression (r = −0.67) and the Trait Anxiety Scale (r = −0.56) in children 8–12 yr of age (30). Reliability analyses have shown internal consistency values ranging from 0.76 to 0.84 (19,35) and a 4-wk test–retest reliability of 0.86 (30).
Measurements of height and weight were performed with participants wearing light clothing (e.g., T-shirt and shorts) and without shoes. Height was measured to the nearest 0.2 cm using a stadiometer, whereas weight was measured to the nearest 0.1 kg using an electronic scale. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared.
Physical activity assessment
Physical activity was assessed using the participation questionnaire, which assesses physical activity over a 1-yr period (23). The scale is a self-report questionnaire that collects information related to intramurals, school and community sports teams, additional organized activities, and free-time play, coded as “activity units” (e.g., play soccer with friends after school; play on a hockey team outside school). Eight items assess free-time play with scores ranging from 0 to 20, and six items measure organized activities with scores ranging from 0 to 29. As a result, total physical activity scores range from 0 to 49 with higher scores reflecting greater physical activity levels. Eight items measured time spent performing sedentary behaviors with scores ranging from 0 to 16. This scale has been shown to have reasonable construct validity by demonstrating significant differences between boys and girls, urban and rural dwellers, and significant correlations with aerobic capacity and body fat (6,23). These scores also correlate with teachers' assessment of children's physical activity (r = 0.62) (6,23), and the test–retest reliability over a 2-wk interval has been estimated to be 0.81 (23).
The Leger 20-m shuttle run test was used as a measure of aerobic fitness for this analysis (26). The demands of the test involve running back and forth between two markers 20 m apart. An audio device emits a signal to indicate when the participants should reach each marker, and the interval between signals gets progressively shorter as the test continues and becomes more difficult (25). Participants in the PHAST cohort were tested in mixed-sex groups of 5–10, and the test for each individual concluded when they were unable to keep pace with two consecutive signals. The final score was recorded as the last stage completed before failure, and this stage was used to estimate peak V˙O2 (25,26). The Leger test has been shown to provide reliable and valid estimates of peak V˙O2 and has been widely used in school-based research (26). This test has also been used internationally by recent studies to measure secular trends in physical fitness (46).
Neighborhood income was estimated by combining postal code information with 2006 Canadian census data. Geographical coding of postal codes was performed in Arcmap using the North American Geocide service from Esri. Median household income was linked to the dissemination area of the participant. Each dissemination area is assigned a median household income based on the 400–700 people who are included in the boundaries. Although this is an indirect measure, previous findings indicate that these neighborhood values are valid proxies for household income, and they correspond to distributions of health-related outcomes (31).
Although BMI is often dichotomized to correspond with obesity guidelines, we analyzed BMI as a quantitative measure to preserve the variability in the data and maximize statistical power. The power of this study was calculated using QUANTO (version 1.2.4; University of Southern California, Los Angeles, CA).
Mixed-effects models were used to analyze the relationship between physical activity and GSW. This method accounts for the nesting of individuals within schools and the nesting of observations within children. Child age was included as a random effect, and random intercepts were designated for school classification to account for children moving between schools. Sex, income, BMI, time, aerobic fitness, physical activity, and sedentary behavior were included as fixed effects. The initial model included sex, neighborhood income, time, physical activity, physical activity–sex, and physical activity–time coefficients. A second model was constructed, including all variables in the initial model with the addition of BMI, and a third model included all variables in the second model with the addition of V˙O2. If the parameter estimate for physical activity changed with the addition of BMI and/or V˙O2, it would indicate that the effect of physical activity on GSW was mediated by changes in body composition (BMI) or aerobic fitness (V˙O2). If the parameter estimate for physical activity remained unchanged after the addition of BMI and V˙O2 to the model, this would suggest that each variable represents an independent predictor of GSW. This procedure was performed in a stepwise manner to analyze the effect of each potential mediator (BMI and V˙O2) independently. This procedure was repeated a second time to include sedentary behavior and to determine whether the effect of sedentary behavior on GSW was mediated by BMI and V˙O2. To formally analyze the mediation effects of BMI and V˙O2, we applied the product-of-coefficients test, which has been shown to have greater power than alternative approaches and can be generalized to models with multiple mediators (13). Class-level effects were not included because models of this complexity can create unstable correlation structures. The Akaike information criterion was used to assess model fit. All P values presented are two-tailed, with P < 0.05 considered as statistically significant. All statistical analyses were performed using SPSS (version 20; IBM Corporation, New York, NY).
The descriptive characteristics of the study participants at each wave are presented in Table 1. The mean ± SD age of the 2278 participants at baseline (spring 2005) was 9.9 ± 0.4 yr and 14.6 ± 0.4 yr for the 1581 individuals who completed the final follow-up in 2009. The average GSW scores were consistent over all follow-up visits and remained between 20.0 ± 3.0 and 20.4 ± 3.7. From baseline to final contact, BMI increased marginally from 18.6 ± 3.5 to 21.6 ± 4.2 kg·m−2, whereas physical activity levels decreased slightly from average PQ scores of 15.3 ± 6.7 at baseline to 13.8 ± 6.0 at final contact. Figure 1 shows the mean PQ scores and mean GSW scores at each wave of data collection. The average household income of the participants at baseline was $71,498 ± $21,396. With 2278 participants, this study was adequately powered (80%) to detect effect sizes with a β of 0.05 at a P < 0.05. With 1581 participants at the final wave of data collection, this study was adequately powered to detect effect sizes with a β of 0.06 at a P < 0.05.
The results from the mixed-effects model predicting GSW from sex, income, BMI, V˙O2, sedentary behavior, and physical activity are presented in Tables 2 and 3. Increased physical activity was associated with greater GSW (β = 0.06, 95% confidence interval [CI] = 0.05–0.08, P < 0.001), independent of other physical health measures, including V˙O2 and BMI. V˙O2 was also positively associated with GSW and displayed a comparable effect size with physical activity (β = 0.07, 95% CI = 0.05–0.09, P < 0.001). BMI was the only factor that demonstrated a significant negative association with GSW (β = −0.11, 95% CI = −0.13 to −0.09, P < 0.001): each nine-unit increase in BMI was associated with a one-unit decrease in GSW, on average. The mediation analysis revealed that adjusting for BMI and V˙O2 attenuated the effect of physical activity on GSW. The magnitude of the association between physical activity and GSW decreased from β = 0.10 (95% CI = 0.06–0.13, P < 0.001) to β = 0.06 (95% CI = 0.05–0.08, P < 0.001), a reduction of 40%. Similar results were observed performing the same analysis while also adjusting for sedentary behavior (Table 3). Sedentary behavior was not significantly associated with GSW regardless of whether BMI and V˙O2 were included in the model. This analysis also indicated that BMI and V˙O2 mediated the association between physical activity and GSW: inclusion of these terms in this model attenuated the effect of physical activity on GSW by 33%. The product-of-coefficients tests for both BMI and V˙O2 provided statistical evidence of these mediation effects (BMI, Z = −6.01, P < 0.001; V˙O2, Z = 7.24, P < 0.001). The indirect effects of physical activity on GSW, through the mediators BMI and V˙O2, were β = 0.015 (SE = 0.002) and β = −0.005 (SE = 0.005), respectively. When combined with the direct effect of PA on GSW (β = 0.06, SE = 0.006), the total effect increased to a β = 0.07 (SE = 0.004).
There was no evidence of associations between income or time and GSW. In addition, the interaction tests between physical activity and time and between physical activity and sex were also not significant. This indicates that the effect of physical activity on GSW was consistent over follow-up and did not differ significantly between males and females. In both analyses, sex became a significant predictor of GSW after adjustment for both BMI and V˙O2, with females displaying GSW scores that were 0.22 units greater than males, on average (Tables 2 and 3).
The objectives of the present analysis were to analyze the relationship between physical activity and GSW and to determine how sex, time, fitness, or body composition influenced this association. The results from this study demonstrate that physical activity was associated with greater GSW among a cohort of children followed prospectively for 4 yr. This effect did not change significantly over follow-up and did not differ between males and females. In addition to physical activity, aerobic fitness was also positively associated with GSW, whereas increased BMI was associated with lower GSW scores. Our results also suggest that aerobic fitness and BMI may mediate the association between physical activity and GSW: accounting for these variables attenuated the effect of physical activity on GSW by 33%–40%. We did not observe any significant evidence of association between sedentary behavior and GSW.
Although the existing evidence examining physical activity and GSW has been mixed, many studies support the positive association between exercise and GSW (33,34,40,47,49). Mechanisms proposed to explain this association include improvements in mastery, body image, fitness, social acceptance, and emotional control and the formation of positive relationships with peer groups and coaches in physical activity settings (4,15,17,22). However, other studies have not reported this association and only observed associations between domain-specific self-worth and exercise (24,44). The variability in these findings may be due to differences in the type and context of physical activity performed. Compared with individual sports, team sport participation has been linked to reduced social anxiety, improved social concept, and increased self-esteem (5,17,28). Previous research has also found that exercise-induced changes in psychological outcomes were mediated by social connections with others (47). These findings suggest that physical activity settings that encourage cooperation, autonomy, and personal development may elicit more positive psychological results than activities based on skill acquisition and competition (7). This evidence is congruent with self-determination theory, which suggests that it is critical to satisfy individuals' innate need for autonomy, competence, and relatedness for children to achieve psychological growth, well-being, and optimal motivation. Support for this theory includes a randomized controlled trial, which demonstrated that participation in a physical activity program focused on enjoyment and cooperation, rather than competition, was associated with dose–response benefits in GSW and depressive symptoms (34).
Youth interactions with adults also influence the psychological benefits derived from physical activity. Changes in support from leaders in physical activity programs, including teachers in the context of physical education, have been linked to improvements in GSW as well as additional developmental outcomes (47). Therefore, contextual factors, including peer and adult relationships, represent important determinants of GSW in physical activity settings, and variability in these interactions may account for the heterogeneity in studies analyzing physical activity and GSW. Future research integrating contextual determinants and types of activity that produce optimal psychological benefits in childhood are required.
Other explanations for these conflicting results may include the variability in measurement of physical activity and GSW. Physical activity assessments used in current studies have included objective measures such as accelerometers and heart rate monitors, as well as a variety of self-report scales (15,24,34,40). GSW was frequently measured using the Harter Self-Perception Profile, although other instruments were also used (40,47,49). Because these scales included different subdomains of self-worth, some instruments may have failed to capture important self-conceptions related to both physical activity and GSW. For example, scales that do not measure social acceptance may fail to capture some benefits of physical activity and lead to an underestimation of the effect of physical activity on GSW. Lastly, a physical activity–race interaction was identified in an RCT analyzing GSW, which suggests that ethnic-specific effects may also account for some of the variability in these studies (34).
In addition to physical activity, BMI and aerobic fitness (V˙O2) were also independent predictors of GSW. Greater BMI values were associated with decreased GSW, whereas greater aerobic fitness was predictive of increased GSW. In a previous study by Davison et al. (8), a direct measure of body composition indicated that percentage body fat was greater among adolescent females with lower GSW scores. This result is not surprising given that high rates of obesity have been reported among individuals with psychological disorders such as depression (27). The positive association between aerobic fitness and GSW is interesting given that closely related variables, including physical activity, sedentary behavior, and BMI were also included in the same model. Given that the PQ questionnaire used in the present study measures a variety of play-based activity, it is possible that the social aspects of these environments produce psychological benefits that are distinct from the physiological changes (serotonergic and dopaminergic responses) associated with fitness-based activity. This finding indicates that a variety of interrelated physical health measures produce independent effects on GSW among children. Each of the physical health measures analyzed (physical activity, aerobic fitness, and BMI) may exert their influence in a manner consistent with independent subdomains of the expanded EXSEM (42). The association between fitness and GSW has been recognized in previous studies and represents an original antecedent of GSW in the EXSEM, and our results support this framework by demonstrating that aerobic fitness may mediate the effect of physical activity on GSW (41,43). The concept of fitness mediating this relationship has been propagated in mental health literature and supported by existing studies (43). The mediating role of BMI has received less attention, yet the EXSEM provides a theoretical framework to explain this association in our study.
The lack of association between sedentary behavior in our analysis contrasts findings from a secondary analysis of an RCT. Goldfield et al. (15) reported that reduced sitting time (measured by TV viewing) was associated with increased physical and GSW among overweight/obese 8–12 yr olds. These effects were observed independent of changes in adiposity (15). Further study of the independent effect of physical activity and sedentary behavior on psychological outcomes is needed to clarify this relationship among children.
Strengths of this study include the longitudinal repeated-measures design, which facilitated the analysis of multiple independent predictors of GSW across a 4-yr period of childhood. This approach also permitted the examination of physical activity interaction effects to determine whether the effect of exercise was moderated by sex and/or time. The large cohort was advantageous because the population-based sample recruitment mitigates the concern of clinical-referral bias, and the sample size provided sufficient power to identify predictors with modest effect sizes. Analyzing children 9–14 yr of age also provides insight into the relationship between physical behaviors and GSW during a dynamic period of physical and psychological development. Lastly, the availability of information related to physical activity, sedentary behavior, BMI, and aerobic fitness provided a comprehensive analysis of physical health measures that influence GSW.
This study also has limitations: the self-report method for assessing for physical activity may have introduced socially desirable reporting and/or recall bias; BMI and the Leger 20-m shuttle run test were used as indirect measures of adiposity and V˙O2, respectively; and household income was estimated using geographical census data. The statistical power also decreased across follow-up because of the reductions in sample size, and this may have decreased the ability to detect physical activity–time interaction effects. Although we did not assess time invariance estimates of the SPPC, the factorial validity has been reported with children in mid to late elementary school (3), and there is evidence for invariant factor loadings across age from mid to late elementary school (1,48). This indicates that the SPPC items are perceived in a similar way across this age range. Finally, if the loss to follow-up was related to one of the predictor variables and the outcome, some of the effect estimates may have been biased. For instance, if participants with low self-worth were more likely to drop out but were also more physically active, the benefit of physical activity on GSW may have been overestimated. However, this is unlikely to have had a large effect of the results because the GSW scores remained consistent over all waves of data collection.
In summary, the current study demonstrated that increased physical activity was associated with improved GSW among 9- to 14-yr-old children. The effect of exercise on GSW did not change over time and did not differ between males and females. Aerobic fitness was also positively associated with GSW, whereas BMI was inversely associated with GSW. Both aerobic fitness and BMI appeared to mediate the effect of physical activity on GSW. This suggests that several closely related physical health measures influence psychological outcomes in this age-group. Further insight into the determinants of GSW among children may be garnered through future studies that accurately characterize the contextual factors of physical activity environments and use direct measures of physical activity, fitness, and anthropometry.
This study was supported by the Canadian Institutes of Health Research (grant no. 66959). Dr. Cairney was supported by an endowed professorship in the Department of Family Medicine. The PHAST appreciates the commitment by children, parents, and teachers from the District School Board of Niagara. The authors also thank Scott Veldhuizen for his statistical support.
The authors declare no competing financial interests. The results of the present study do not constitute endorsement by the American College of Sports Medicine, and the results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.
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Keywords:© 2017 American College of Sports Medicine
SELF-ESTEEM; PROSPECTIVE COHORT; BODY COMPOSITION; AEROBIC FITNESS; SEDENTARY BEHAVIOUR