Skip to main content

Advertising Disclaimer »

Main menu

  • Journals
    • Pediatrics
    • Hospital Pediatrics
    • Pediatrics in Review
    • NeoReviews
    • AAP Grand Rounds
    • AAP News
  • Authors/Reviewers
    • Submit Manuscript
    • Author Guidelines
    • Reviewer Guidelines
    • Open Access
    • Editorial Policies
  • Content
    • Current Issue
    • Online First
    • Archive
    • Blogs
    • Topic/Program Collections
    • AAP Meeting Abstracts
  • Pediatric Collections
    • COVID-19
    • Racism and Its Effects on Pediatric Health
    • More Collections...
  • AAP Policy
  • Supplements
  • Multimedia
    • Video Abstracts
    • Pediatrics On Call Podcast
  • Subscribe
  • Alerts
  • Careers
  • Other Publications
    • American Academy of Pediatrics

User menu

  • Log in
  • Log out
  • My Cart

Search

  • Advanced search
American Academy of Pediatrics

AAP Gateway

Advanced Search

AAP Logo

  • Log in
  • Log out
  • My Cart
  • Journals
    • Pediatrics
    • Hospital Pediatrics
    • Pediatrics in Review
    • NeoReviews
    • AAP Grand Rounds
    • AAP News
  • Authors/Reviewers
    • Submit Manuscript
    • Author Guidelines
    • Reviewer Guidelines
    • Open Access
    • Editorial Policies
  • Content
    • Current Issue
    • Online First
    • Archive
    • Blogs
    • Topic/Program Collections
    • AAP Meeting Abstracts
  • Pediatric Collections
    • COVID-19
    • Racism and Its Effects on Pediatric Health
    • More Collections...
  • AAP Policy
  • Supplements
  • Multimedia
    • Video Abstracts
    • Pediatrics On Call Podcast
  • Subscribe
  • Alerts
  • Careers

Discover Pediatric Collections on COVID-19 and Racism and Its Effects on Pediatric Health

American Academy of Pediatrics
Review Article

Children’s Physical Activity and Depression: A Meta-analysis

Daphne J. Korczak, Sheri Madigan and Marlena Colasanto
Pediatrics April 2017, 139 (4) e20162266; DOI: https://doi.org/10.1542/peds.2016-2266
Daphne J. Korczak
aDepartment of Psychiatry, Hospital for Sick Children, Toronto, Ontario, Canada;
bDepartment of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sheri Madigan
cDepartment of Psychology, Aberta Children's Research Institute, Calgary, Alberta, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Marlena Colasanto
aDepartment of Psychiatry, Hospital for Sick Children, Toronto, Ontario, Canada;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • Comments
Loading
Download PDF

Abstract

CONTEXT: Research regarding the protective effects of early physical activity on depression has yielded conflicting results.

OBJECTIVE: Our objective was to synthesize observational studies examining the association of physical activity in childhood and adolescence with depression.

DATA SOURCES: Studies (from 2005 to 2015) were identified by using a comprehensive search strategy.

STUDY SELECTION: The included studies measured physical activity in childhood or adolescence and examined its association with depression.

DATA EXTRACTION: Data were extracted by 2 independent coders. Estimates were examined by using random-effects meta-analysis.

RESULTS: Fifty independent samples (89 894 participants) were included, and the mean effect size was significant (r = –0.14; 95% confidence interval [CI] = –0.19 to –0.10). Moderator analyses revealed stronger effect sizes in studies with cross-sectional versus longitudinal designs (k = 36, r = –0.17; 95% CI = –0.23 to –0.10 vs k = 14, r = –0.07; 95% CI = –0.10 to –0.04); using depression self-report versus interview (k = 46, r = –0.15; 95% CI = –0.20 to –0.10 vs k = 4, r = –0.05; 95% CI = –0.09 to –0.01); using validated versus nonvalidated physical activity measures (k = 29, r = –0.18; 95% CI = –0.26 to –0.09 vs k = 21, r = –0.08; 95% CI = –0.11 to –0.05); and using measures of frequency and intensity of physical activity versus intensity alone (k = 27, r = –0.17; 95% CI = –0.25 to –0.09 vs k = 7, r = –0.05; 95% CI = –0.09 to –0.01).

LIMITATIONS: Limitations included a lack of standardized measures of physical activity; use of self-report of depression in majority of studies; and a small number of longitudinal studies.

CONCLUSIONS: Physical activity is associated with decreased concurrent depressive symptoms; the association with future depressive symptoms is weak.

  • Abbreviations:
    CI —
    confidence interval
    MDD —
    major depressive disorder
    PA —
    physical activity
  • Research interest in the health and psychological benefits of exercise has grown exponentially over recent years. Evidence suggests that physical activity may ameliorate depressive symptoms, supporting the use of exercise as part of a comprehensive treatment plan for major depressive disorder (MDD).1,2 The reverse association has also been demonstrated: decreased physical activity (PA), as well as increased sedentary behaviors, confers vulnerability for developing depressive symptoms.3–5 To date, studies have investigated whether increased PA may also protect individuals against the development of MDD, and findings from observational studies are promising.3,6–8 However, the age range of participants in these studies has been wide, research has been conducted principally in adult populations, and results have been conflicting.9–11 Thus, using the current state of the literature for the purpose of clinical decision-making is challenging. A meta-analysis is warranted to resolve discrepancies in the literature and to examine the suggestion that the largest magnitude of protective effect may be found at younger ages,12 which would in turn provide support for a potential preventative role of physical activity in the development of depression.

    Two recent systematic reviews13,14 have reported that increased PA is associated with fewer depressive symptoms. However, only 1 review focused on the child and adolescent age group,13 and neither review conducted a meta-analytic synthesis of the data, which can provide a powerful estimate of the mean effect size across studies. Compared with adult participants, in which the investigation of risk factors is confounded by years of the allostatic load of depression (exposure to depressive symptoms and their associated physiologic strain)15 and comorbid cardiometabolic disease,16 studies of children and adolescents enable the examination of the relationship between PA and depressive symptoms at their most nascent. To our knowledge, this is the first study to conduct a meta-analytic review of the protective effect of PA on depression and, as such, is the first to describe the magnitude of this association. Also, previous systematic reviews have not explored the potential moderating role of sex in the association between PA and MDD, although a stronger effect for females has been suggested in several independent studies.4,17,18 Understanding if the association between PA and MDD is sex-specific is relevant for the elucidation of potential underlying mechanisms of association.

    The objective of this meta-analysis was to investigate the potential preventative effect of child and adolescent PA on depression. Several variables have been linked to differences in effects size; thus, we will examine whether between-study differences were observed for child age, sex, and social risk.19–21 We will also examine if heterogeneity in effect sizes can be explained by variation in study methodology (eg, methods of assessing physical activity and depression), as well as study quality (eg, longitudinal versus cross-sectional). Clarification on the role of these factors for understanding systematic differences in effect sizes are important for the design and implementation of targeted and effective public health prevention programs.

    Methods

    Search Strategy

    Published studies on PA and depression in children and adolescents were identified by searching Social Sciences Abstracts, International Bibliography of the Social Sciences, Scopus, SportDiscus, CBA Abstracts, Physical Education Index, Sociological Abstracts, and PsycINFO electronic databases for potential articles through October 2015. The search was limited to English language articles published between 2005 and 2015 using the keywords (“child*,” or “teen*,” or “adolesc*,” or “youth*,” or “infant,” or “infancy,” or “baby,” or “babies”) AND (“depress*”), AND (“sedentary behavio*” or “recreation” or “physical activity” or “leisure activity” or “exercise” or “fitness” or “sport*”). This search strategy yielded 3147 nonduplicate articles.

    Study Inclusion and Exclusion Criteria

    Titles and abstracts of the articles were reviewed to identify studies that met the inclusion criteria. Articles selected for the current study were based on the following criteria. (1) Cross-sectional study of PA and depression collected during childhood or adolescence (<18 years). (2) Longitudinal study of PA collected during childhood or adolescence (<18 years); (3) The constructs measured were PA (eg, energy expenditure) and depressive symptoms. Studies that measured broader, nonspecific constructs of either PA (eg, participation in extracurricular activities) or of depression (eg, psychological distress) were excluded. Because numerous standardized, validated and accessible measures of depression among youth are widely available, studies that assessed the outcome of depression by using a nonvalidated measure were excluded. Only 1 study22 needed to be excluded because it assessed depression by using a single self-report item with no demonstrated psychometric properties. In contrast to the depression literature, fewer standardized and validated measures exist for assessing physical activity. Thus, no validity criterion was applied to the measure of PA. However, a validated versus nonvalidated PA measure was examined as a moderator to determine if this measurement characteristic explained between study heterogeneity. (4) The study statistic could be transformed into an effect size (eg, correlations, odds ratios, means/SDs, and/or P values). (5) The full-text article was available and written in English. Studies in which PA was used as an intervention were not included in the current study.

    Multiple results often emerge from a single dataset. If the same participants were used across multiple publications, only 1 study was included in the meta-analysis to ensure independence of effect sizes. A protocol was developed so that each sample of participants was only represented once in the meta-analysis. First, if a single dataset presented both cross-sectional and longitudinal analyses, we selected the study with longitudinal data because this study design was underrepresented in our analyses. Second, if multiple publications emerged from a single cross-sectional dataset, we selected the publication with the largest sample size and most comprehensive data extraction information.

    Multiple samples or groups often exist within a particular study. For example, some studies present results separately for boys and girls within a sample. In such cases, effects sizes for both these nonoverlapping samples were calculated and entered into the meta-analysis separately.

    Data Extraction

    All articles that met inclusion criteria were coded by using a standard coding form to collect information on study and sample characteristics. Several moderator variables were collected to explain effect size variability across studies. Moderator variables were divided into categorical moderators (sex, social risk [ie, low income, minority, or involved in child protective services], PA type, PA validated measure, depression measure type, study design, and country) and continuous moderators (age at PA/depression, time between assessments, and publication year). Some studies reported data stratified by level of PA. In such cases, data for the group with the greatest PA were used in the analysis. This was done to remain consistent with our primary objective. Data extraction was performed by 2 independent coders (DK and MC). Discrepancies were resolved through discussion, and consensus scores were entered into the final dataset.

    Data Analysis

    Effect sizes were calculated and analyzed by using Comprehensive Meta-Analysis version 3.0 software.23 Effect sizes were calculated directly from information provided in each study. When provided, adjusted effect sizes were included. All effect sizes were transformed into correlations for the purpose of reporting mean effect sizes. Pooled effect size estimates were based on random effects model. We assessed for overall heterogeneity of the mean effect size using the Q statistic and by calculating the I2 statistic. The Q statistic is a test of the null hypothesis that all studies share a common effect size, and the I2 statistic examines the proportion of the variation across studies that is due to heterogeneity rather than chance, expressed as a percentage. General guidelines for the interpretation of the I2 are as follows: 25%, 50%, and 75% indicate low, moderate, and high heterogeneity, respectively.24 Categorical moderator analyses were conducted by using Q statistics,25,26 whereas the significance of each continuous moderator was assessed by using meta-regressions.27 Finally, we examined publication bias using funnel plots and Egger’s test.

    Study Quality

    To assess the quality of studies, a 7-point quality assessment tool was created based on those implemented in previous meta-analyses of observational studies.28,29 The tool evaluated the articles based on the following 7 criteria: (1) having a defined sample, (2) having a representative sample, (3) rater blinding, (4) report of relevant MDD and PA data, (5) adequate sample size, (6) statistical adjustment for covariates, and (7) a validated PA measure. Articles were given a score of 0 (“No”) or 1 (“Yes”) for each of the abovementioned criteria and summed to give a total score out of 7.

    Results

    Our electronic search of 7 databases yielded 3147 nonduplicate articles. On review of the titles and abstracts, 87 articles met inclusion criteria and full articles were retrieved. A total of 40 studies with 50 independent samples (89 894 participants) met the inclusion criteria and were included in analyses. Figure 1 presents a flowchart of the review process.

    FIGURE 1
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 1

    PRISMA flow diagram of the literature search used to identify studies for analysis of physical activity and depression.

    Study and Sample Characteristics

    Study Characteristics

    As detailed in Table 1, 14 studies were longitudinal and 36 studies were cross-sectional. Sample sizes ranged from 55 to 14 594. Child age at the time of the assessment of PA ranged from 8 to 19 years. With respect to PA measures, 15 studies examined the frequency of activity only, 7 studies examined the intensity of the activity, and 27 examined a combination of frequency and intensity. With respect to the assessment of depression, 4 studies measured depressive symptoms by using interview methodology, whereas 46 studies used self-report questionnaires. The overall burden of depressive symptoms in studies that used a depression self-report measure was low (see Table 1). A clinical diagnosis of MDD was reported at follow-up for the 4 longitudinal samples that measured depressive symptoms by using a standardized interview. An MDD diagnosis was made in 5% to 13% of participants across these studies at follow-up.6,30,31 Although several studies specifically noted the absence of antidepressant medication use among participants, the large majority of studies did not include information regarding the use of medications.

    View this table:
    • View inline
    • View popup
    TABLE 1

    Independent Samples Included in the Meta-analysis of Physical Activity and Depression

    Study Quality

    Validated measures of PA were used in 19 out of 36 (53%) cross-sectional studies and in 10 out of 14 (71%) longitudinal studies, as indicated in Table 1. The mean study quality score was 4.9 (SD = 0.9) out of 7. For cross-sectional studies, the mean percentage of participants with complete data were 96.6% (range: 68%–100%). For longitudinal studies, the mean rate of attrition between time points was 13.8% (range: 0.04%–30%). Additional detail regarding individual study- and item-level quality assessment scoring is summarized in Supplemental Table 6.

    Overall Measure of Effect Size

    A significant mean effect size for the association between PA and depression was found: (r = –0.14; 95% confidence interval [CI] = –0.19 to –0.10) (Fig 2), suggesting that children’s PA is negatively associated with depressive symptoms. The funnel plot revealed asymmetry (Fig 3) and Egger’s test suggested that the asymmetry was significant (P < .01). Using the trim and fill analysis, the adjusted pooled effect size estimate was r = 0.06 (95% CI = –0.11 to –0.01). Statistically significant heterogeneity between the studies was found (Q = 1767.95; P < .0001; I2 = 95.23) and potential moderator analyses were explored, including demographic, measurement, and study design factors. The results of all moderator analyses are presented in Tables 2 and 3, and significant moderators are discussed in detail below.

    FIGURE 2
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 2

    Forest plot of the overall mean effect size, as well as the effect size for each study included in the analysis. Observed effect sizes (r) and 95% CIs are indicated for each study included in the meta-analysis. The black diamond, located at the bottom of the forest plot, indicates the overall mean effect size. Inserting an average effect size across all stratified groups for studies that categorized PA into strata had no effect on the overall mean effect size (r = –0.14; 95% CI: 0.18 to 0.10).

    FIGURE 3
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 3

    Funnel plot of the meta-analysis of included studies. The y-axis on the funnel plot represents the SE, and the x-axis is the effect size. Observed studies are indicated by open circles. The white diamond represents the observed mean effect size, and the black diamond represents the adjusted mean effect size.

    View this table:
    • View inline
    • View popup
    TABLE 2

    Examination of Potential Effect Modifiers in the Association of Physical Activity and Depression: Categorical Variables

    View this table:
    • View inline
    • View popup
    TABLE 3

    Examination of Potential Effect Modifiers in the Association of Physical Activity and Depression: Continuous Variables

    Effect sizes were stronger in samples using cross-sectional designs (k = 36, r = –0.17; 95% CI = –0.23 to –0.10) compared with those using longitudinal designs (k = 14, r = –0.07; 95% CI = –0.10 to –0.04), in which a weak inverse relationship between physical activity and future depressive symptoms was found. Similarly, studies that used interview-based MDD measures demonstrated weaker effect sizes compared with those that used questionnaires (k = 4, r = –0.05; 95% CI = –0.09 to –0.01 vs k = 46, r = –0.15; 95% CI = –0.20 to –0.10). Stronger effect sizes were also observed in samples with no known risks (k = 44; r = –0.15; 95% CI = –0.21 to –0.10) compared with samples with social risk (eg, low income) (k = 6; r = –0.05; 95% CI = –0.09 to –0.01). Effect sizes were stronger in samples examining a combination of PA frequency and intensity (k = 27; r = –0.17; 95% CI = –0.25 to –0.09) compared with intensity alone (k = 7; r = –0.05; 95% CI = –0.09 to –0.01). Finally, stronger effect sizes were found in studies that used validated (k = 29, r = –0.18; 95% CI = –0.26 to –0.09) versus nonvalidated PA measures (k = 21, r = –0.08; 95% CI = –0.11 to –0.05).

    Longitudinal Studies

    Because there were significant differences in effect sizes between cross-sectional and longitudinal studies, and because longitudinal associations may provide insight into the directionality of associations, we performed a set of subanalyses with longitudinal studies only to more explicitly examine the magnitude of the association, as well as the between-study variability, for studies assessing a baseline metric of physical activity and its association with later depressive symptoms. There were 14 studies involving 15 926 participants that reported on longitudinal associations between PA and depression. Five studies6,8,30,64,66 reported on depression-related covariates, including baseline depressive symptoms, number of weeks depressed during the preceding year, body dissatisfaction, social support, self-efficacy, history of childhood trauma or stressful life events, and medication status (Table 1).

    The mean effect size for the longitudinal association between PA and depression was r = –0.07 (95% CI = –0.10 to –0.04). Statistically significant heterogeneity between studies was found (Q = 59.25; P < .0001; I2 = 77.52) and potential moderator analyses were explored (Tables 4 and 5). However, because the number of studies for several subgroups was small (eg, there were only 2 studies with social risk), the results of these moderator analyses should be interpreted with caution (Table 5).

    View this table:
    • View inline
    • View popup
    TABLE 4

    Examination of Potential Categorical Effect Modifiers in Studies With Longitudinal Associations Between Physical Activity and Depression

    View this table:
    • View inline
    • View popup
    TABLE 5

    Examination of Continuous Moderators in Studies With Longitudinal Associations Between Physical Activity and Depression

    Discussion

    This systematic review and meta-analysis of 50 samples involving 89 894 participants found that a greater PA level was associated with fewer depressive symptoms, although not with decreased diagnoses of MDD. This association was stronger for cross-sectional studies than for longitudinal studies, in which the mean effect size was significant, but weak. The nature of the PA was also associated with the presence of depressive symptoms, in that PA of increased frequency and intensity was more strongly associated with decreased depressive symptoms compared with PA that was defined by intensity of activity alone.

    Significant effect sizes were observed for studies that examined depressive symptomatology by using questionnaire measures and were considerably stronger than those of studies assessing MDD by using interview measures. Indeed, the majority of studies in this meta-analysis employed self-report inventories to assess depressive symptoms (n = 46) rather than diagnostic interviews (n = 4), which are considered to be the gold-standard measure for MDD. Self-report measures are frequently used in research studies due to their ease of administration, low cost, minimal time requirement, and low patient response burden. These measures are useful screening tools; however, self-report instruments are limited by their inability to confirm the presence or absence of an MDD diagnosis. That increased PA was more highly associated with decreased depressive symptoms in this meta-analysis, as compared with an MDD diagnosis, is a critical finding. This finding suggests that individuals who are at risk for more severe, syndromal-level symptom burden, impairment, and associated poor health outcomes may not respond to the potential preventative effects of PA. Although it is possible that these results may also reflect the relative methodological limitations associated with the examination of a dichotomous versus a continuous variable, our findings are consistent with previous data reporting that MDD severity is distinguished from subsyndromal depressive symptoms by its decreased sensitivity to prevention strategies, greater association with cardiovascular risk factors and health outcomes, and greater treatment resistance.67–70

    Increased PA was more strongly associated with decreased depressive symptoms in cross-sectional studies compared with longitudinal studies, where the effect size was small. Cross-sectional studies are limited in their ability to probe causality, because the temporal relationship between variables cannot be determined. Thus, it is possible that the cross-sectional studies included in this meta-analysis are actually indicative of the reverse association of PA and depression: that children and adolescents with increased depressive symptoms are less likely to participate in PA. Indeed, amotivation, pessimism, and anhedonia associated with the depressed state have been reported to lead to decreased PA among adult populations.71 In contrast, longitudinal studies provide insight into the direction of the association and, in the present meta-analysis, demonstrated a weak inverse relationship between PA and future depressive symptoms measured 2 to 17 years later, suggesting that PA has a weak but positive association with future mood.

    Studies that included a measure of both increased PA frequency and intensity demonstrated stronger associations with depressive symptoms than those that used measures of intensity alone. This finding is consistent with other systematic reviews examining the role of PA as an intervention for depressed adults.1 Currently, some clinical guidelines recommend the inclusion of 45 minutes of moderately intense exercise at least 3 days per week in the treatment of MDD among adults.72 In contrast, guidelines for general health promotion by the Canadian Pediatric Society73 and American Academy of Pediatrics74 recommend that children and adolescents get at least 60 minutes of moderate to vigorous PA daily to maintain general health. As such, the findings from the current study support the inclusion of both the PA frequency and intensity components in the Canadian Pediatric Society and American Academy of Pediatrics recommendations with respect to the benefit to depressed mood. Many hypotheses regarding the mechanism by which PA may lead to improved mood have been theorized, including via antiinflammatory effects, increased growth factors leading to neural plasticity, neuroendocrine effects on the hypothalamic-pituitary-adrenal axis and insulin sensitivity, and improvements in self-efficacy.75–77 However, neither the pathophysiological pathways themselves nor whether they are specific to mood state are known. These factors are important for determining rational prevention versus treatment strategies, gaining insight into the etiology of depression, and for research into novel treatments for depression for medically ill populations and those unable to participate in PA.

    Studies that examined the association of PA with depression in samples of higher social risk (eg, low income, minority, or involved in child protective services) reported weaker effect sizes than those of lower-risk groups. Socioeconomic status and its associated risk factors (eg, disadvantaged neighborhoods) explain a significant proportion of the variance in childhood psychopathology, including depression.78 Because children in high–social risk environments may be exposed to many more risk factors for depression, including lower socioeconomic status,79 increased PA may have relatively less influence with respect to the proportion of the variance in depression it explains when compared with children of lower social risk.80 Also, because measures of depression and PA have traditionally been developed in samples of low social risk, they may be less well calibrated to capture the variation in depression or PA seen in high–social risk children.81,82 These results should be interpreted with caution, however, because few studies have examined the association of PA with depression in high–social risk samples. Given the increased prevalence of both depression and obesity in populations of high social risk, however, additional research examining potential targets for prevention among this vulnerable group of children is needed.

    As the first study to conduct a meta-analytic review of the potential protective association of childhood PA with depression, this study has many strengths, including the analysis of a large number of studies to increase the precision of effect size estimates, subanalysis of cross-sectional versus longitudinal associations, and examination of PA frequency and intensity as potentially contributing effect modifiers. However, our findings must be interpreted within the context of the limitations of this study. The measurement of PA in the majority of studies relied on self-report measures of frequency, intensity, and type of activity, which were not correlated with objective measures of activity (eg, accelerometry). This also reflects a limitation of the PA literature more broadly, in that the use of standardized instruments that have demonstrated reliability and validity was not consistent across studies. The current meta-analysis demonstrated that studies with validated measures of PA had stronger effect sizes than those that used nonvalidated measures. Thus, future PA research should focus on the methodology for PA measurement in children and adolescents to increase confidence in the study results. In addition, the majority of the literature relies on the self-report of depressive symptoms, with few studies able to confirm a diagnosis of depression, leading to wide precision estimates of the magnitude of the effect of PA on clinical depression. Finally, we only included studies that were published in English, and this inclusion criterion may limit the generalizability of our findings to predominantly English-speaking countries.

    Conclusions

    This systematic review and meta-analysis finds that increased PA in childhood and adolescence is associated with decreased depressive symptoms. Substantive moderators of this association include (1) study design, with the strongest association found in cross-sectional studies; (2) type of PA, with a combination of PA frequency and intensity resulting in the greatest effect on depressive symptoms; and (3) depression measure, with a stronger protective effect of increased PA for depressive symptoms than for a clinical diagnosis of MDD. Taken together, this study suggests that PA in childhood and adolescence is associated with improved concurrent symptoms of depression, particularly when undertaken regularly and with vigor, and has weak but significant effects on future depressive symptoms. Future research is needed to advance the knowledge of PA measurement, elucidate the mechanism of association between PA and depression, and examine the longitudinal relationships between PA, depression, and health outcomes to determine the critical periods in which preventative efforts may be most effective.

    Acknowledgment

    We thank Ms Qi Fang (University of Toronto) for assistance in the literature search.

    Footnotes

      • Accepted January 6, 2017.
    • Address correspondence to Daphne J. Korczak, MD, MSc, Department of Psychiatry, The Hospital for Sick Children, 555 University Ave, Toronto, ON M5G1X8, Canada. E-mail: daphne.korczak{at}sickkids.ca
    • FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

    • FUNDING: Research support was provided to Dr Madigan by the Alberta Children’s Hospital Foundation and the Canada Research Chairs program.

    • POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

    References

    1. ↵
      1. Cooney GM,
      2. Dwan K,
      3. Greig CA, et al
      . Exercise for depression. Cochrane Database Syst Rev. 2013;(9):CD004366pmid:24026850
      OpenUrlCrossRefPubMed
    2. ↵
      1. Nyström MB,
      2. Neely G,
      3. Hassmén P,
      4. Carlbring P
      . Treating major depression with physical activity: a systematic overview with recommendations. Cogn Behav Ther. 2015;44(4):341–352pmid:25794191
      OpenUrlCrossRefPubMed
    3. ↵
      1. Åberg MA,
      2. Waern M,
      3. Nyberg J, et al
      . Cardiovascular fitness in males at age 18 and risk of serious depression in adulthood: Swedish prospective population-based study. Br J Psychiatry. 2012;201(5):352–359pmid:22700083
      OpenUrlAbstract/FREE Full Text
    4. ↵
      1. Carroll DD,
      2. Blanck HM,
      3. Serdula MK,
      4. Brown DR
      . Obesity, physical activity, and depressive symptoms in a cohort of adults aged 51 to 61. J Aging Health. 2010;22(3):384–398pmid:20164412
      OpenUrlAbstract/FREE Full Text
    5. ↵
      1. Hamer M,
      2. Molloy GJ,
      3. de Oliveira C,
      4. Demakakos P
      . Leisure time physical activity, risk of depressive symptoms, and inflammatory mediators: the English Longitudinal Study of Ageing. Psychoneuroendocrinology. 2009;34(7):1050–1055pmid:19272716
      OpenUrlCrossRefPubMed
    6. ↵
      1. Jerstad SJ,
      2. Boutelle KN,
      3. Ness KK,
      4. Stice E
      . Prospective reciprocal relations between physical activity and depression in female adolescents. J Consult Clin Psychol. 2010;78(2):268–272pmid:20350037
      OpenUrlCrossRefPubMed
      1. Strawbridge WJ,
      2. Deleger S,
      3. Roberts RE,
      4. Kaplan GA
      . Physical activity reduces the risk of subsequent depression for older adults. Am J Epidemiol. 2002;156(4):328–334pmid:12181102
      OpenUrlAbstract/FREE Full Text
    7. ↵
      1. Sund AM,
      2. Larsson B,
      3. Wichstrøm L
      . Role of physical and sedentary activities in the development of depressive symptoms in early adolescence. Soc Psychiatry Psychiatr Epidemiol. 2011;46(5):431–441pmid:20358175
      OpenUrlCrossRefPubMed
    8. ↵
      1. Cooper-Patrick L,
      2. Ford DE,
      3. Mead LA,
      4. Chang PP,
      5. Klag MJ
      . Exercise and depression in midlife: a prospective study. Am J Public Health. 1997;87(4):670–673pmid:9146452
      OpenUrlCrossRefPubMed
      1. Kritz-Silverstein D,
      2. Barrett-Connor E,
      3. Corbeau C
      . Cross-sectional and prospective study of exercise and depressed mood in the elderly: the Rancho Bernardo study. Am J Epidemiol. 2001;153(6):596–603pmid:11257068
      OpenUrlAbstract/FREE Full Text
    9. ↵
      1. Rothon C,
      2. Edwards P,
      3. Bhui K,
      4. Viner RM,
      5. Taylor S,
      6. Stansfeld SA
      . Physical activity and depressive symptoms in adolescents: a prospective study. BMC Med. 2010;8:32pmid:20509868
      OpenUrlCrossRefPubMed
    10. ↵
      1. Pinto Pereira SM,
      2. Geoffroy MC,
      3. Power C
      . Depressive symptoms and physical activity during 3 decades in adult life: bidirectional associations in a prospective cohort study. JAMA Psychiatry. 2014;71(12):1373–1380pmid:25321867
      OpenUrlCrossRefPubMed
    11. ↵
      1. Bursnall P
      . The relationship between physical activity and depressive symptoms in adolescents: a systematic review. Worldviews Evid Based Nurs. 2014;11(6):376–382pmid:25213686
      OpenUrlPubMed
    12. ↵
      1. Mammen G,
      2. Faulkner G
      . Physical activity and the prevention of depression: a systematic review of prospective studies. Am J Prev Med. 2013;45(5):649–657pmid:24139780
      OpenUrlCrossRefPubMed
    13. ↵
      1. Kobrosly RW,
      2. van Wijngaarden E,
      3. Seplaki CL,
      4. Cory-Slechta DA,
      5. Moynihan J
      . Depressive symptoms are associated with allostatic load among community-dwelling older adults. Physiol Behav. 2014;123:223–230pmid:24432360
      OpenUrlPubMed
    14. ↵
      1. Vaccarino V,
      2. McClure C,
      3. Johnson BD, et al
      . Depression, the metabolic syndrome and cardiovascular risk. Psychosom Med. 2008;70(1):40–48pmid:18158378
      OpenUrlAbstract/FREE Full Text
    15. ↵
      1. Mikkelsen SS,
      2. Tolstrup JS,
      3. Flachs EM,
      4. Mortensen EL,
      5. Schnohr P,
      6. Flensborg-Madsen T
      . A cohort study of leisure time physical activity and depression. Prev Med. 2010;51(6):471–475pmid:20858516
      OpenUrlCrossRefPubMed
    16. ↵
      1. Wang F,
      2. DesMeules M,
      3. Luo W,
      4. Dai S,
      5. Lagace C,
      6. Morrison H
      . Leisure-time physical activity and marital status in relation to depression between men and women: A prospective study. Health Psychol. 2011;30(2):204–211pmid:21401254
      OpenUrlCrossRefPubMed
    17. ↵
      1. Matsudo VK,
      2. Ferrari GL,
      3. Araújo TL, et al
      . Socioeconomic status indicators, physical activity, and overweight/obesity in Brazilian children [in Portuguese]. Rev Paul Pediatr. 2016;34(2):162–170
      OpenUrl
      1. Ritterman Weintraub ML,
      2. Fernald LC,
      3. Goodman E,
      4. Guendelman S,
      5. Adler NE
      . Obesity-related behaviors among poor adolescents and young adults: is social position associated with risk behaviors? Front Public Health. 2015;3:224pmid:26528461
      OpenUrlPubMed
    18. ↵
      1. Villagran Perez S,
      2. Novalbos-Ruiz JP,
      3. Rodriguez-Martin A,
      4. Martinez-Nieto M,
      5. Lechuga-Sancho AM
      . Implications of family socioeconomic level on risk behaviors in child-youth obesity. Nutr Hosp. 2013;28(6):1951–1960
      OpenUrl
    19. ↵
      1. Eassa S,
      2. Hagag SA,
      3. Seliem HAEW,
      4. Amar HA
      . Assessment of sport practice among adolescent school students and its effect on perceived health in Sharkia Governorate–Egypt. J Am Sci. 2011;7(3):544–551
      OpenUrl
    20. ↵
      1. Borenstein M,
      2. Hedges LV,
      3. Higgins JP,
      4. Rothstein HR
      . Comprehensive Meta-analysis [computer program]. Version 3. Englewood, NJ: Biostat; 2014
    21. ↵
      1. Higgins JP,
      2. Thompson SG,
      3. Deeks JJ,
      4. Altman DG
      . Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–560pmid:12958120
      OpenUrlFREE Full Text
    22. ↵
      1. Borenstein M,
      2. Hedges LV,
      3. Higgins JPT,
      4. Rothstein HR
      . Introduction to Meta-Analysis. West Sussex, United Kingdom: John Wiley & Sons; 2009
    23. ↵
      1. Rosenthal R
      . Writing meta-analytic reviews. Psychol Bull. 1995;118(2):183–192
      OpenUrlCrossRef
    24. ↵
      1. Thompson SG,
      2. Higgins JPT
      . How should meta-regression analyses be undertaken and interpreted? Stat Med. 2002;21(11):1559–1573pmid:12111920
      OpenUrlCrossRefPubMed
    25. ↵
      1. Sanderson S,
      2. Tatt ID,
      3. Higgins JP
      . Tools for assessing quality and susceptibility to bias in observational studies in epidemiology: a systematic review and annotated bibliography. Int J Epidemiol. 2007;36(3):666–676pmid:17470488
      OpenUrlAbstract/FREE Full Text
    26. ↵
      1. Tsang TW,
      2. Lucas BR,
      3. Carmichael Olson H,
      4. Pinto RZ,
      5. Elliott EJ
      . Prenatal alcohol exposure, FASD, and child behavior: a meta-analysis. Pediatrics. 2016;137(3):e20152542pmid:26908693
      OpenUrlAbstract/FREE Full Text
    27. ↵
      1. Colman I,
      2. Zeng Y,
      3. McMartin SE, et al
      . Protective factors against depression during the transition from adolescence to adulthood: findings from a national Canadian cohort. Prev Med. 2014;65:28–32pmid:24732721
      OpenUrlCrossRefPubMed
    28. ↵
      1. McKercher C,
      2. Sanderson K,
      3. Schmidt MD, et al
      . Physical activity patterns and risk of depression in young adulthood: a 20-year cohort study since childhood. Soc Psychiatry Psychiatr Epidemiol. 2014;49(11):1823–1834pmid:24626994
      OpenUrlPubMed
      1. Adeniyi AF,
      2. Okafor NC,
      3. Adeniyi CY
      . Depression and physical activity in a sample of Nigerian adolescents: levels, relationships and predictors. Child Adolesc Psychiatry Ment Health. 2011;5:16pmid:21569581
      OpenUrlPubMed
      1. Ammouri AA,
      2. Kaur H,
      3. Neuberger GB,
      4. Gajewski B,
      5. Choi WS
      . Correlates of exercise participation in adolescents. Public Health Nurs. 2007;24(2):111–120pmid:17319883
      OpenUrlCrossRefPubMed
      1. Asare M,
      2. Danquah SA
      . The relationship between physical activity, sedentary behaviour and mental health in Ghanaian adolescents. Child Adolesc Psychiatry Ment Health. 2015;9:11pmid:25945123
      OpenUrlPubMed
      1. Babiss LA,
      2. Gangwisch JE
      . Sports participation as a protective factor against depression and suicidal ideation in adolescents as mediated by self-esteem and social support. J Dev Behav Pediatr. 2009;30(5):376–384pmid:19692930
      OpenUrlCrossRefPubMed
      1. Cao H,
      2. Qian Q,
      3. Weng T, et al
      . Screen time, physical activity and mental health among urban adolescents in China. Prev Med. 2011;53(4–5):316–320pmid:21933680
      OpenUrlCrossRefPubMed
      1. Castillo F,
      2. Francis L,
      3. Wylie-Rosett J,
      4. Isasi CR
      . Depressive symptoms are associated with excess weight and unhealthier lifestyle behaviors in urban adolescents. Child Obes. 2014;10(5):400–407pmid:25181530
      OpenUrlPubMed
      1. Desha LN,
      2. Ziviani JM,
      3. Nicholson JM,
      4. Martin G,
      5. Darnell RE
      . Physical activity and depressive symptoms in American adolescents. J Sport Exerc Psychol. 2007;29(4):534–543pmid:17968052
      OpenUrlPubMed
      1. Dockray S,
      2. Susman EJ,
      3. Dorn LD
      . Depression, cortisol reactivity, and obesity in childhood and adolescence. J Adolesc Health. 2009;45(4):344–350pmid:19766938
      OpenUrlCrossRefPubMed
      1. Esmaeilzadeh S
      . Relationship between depressive symptoms with physical activity and physical fitness among children. Mental Health & Prevention. 2014;2(1–2):11–17
      OpenUrl
      1. Fatiregun AA,
      2. Kumapayi TE
      . Prevalence and correlates of depressive symptoms among in-school adolescents in a rural district in southwest Nigeria. J Adolesc. 2014;37(2):197–203pmid:24439625
      OpenUrlPubMed
      1. Gray WN,
      2. Janicke DM,
      3. Ingerski LM,
      4. Silverstein JH
      . The impact of peer victimization, parent distress and child depression on barrier formation and physical activity in overweight youth. J Dev Behav Pediatr. 2008;29(1):26–33pmid:18300722
      OpenUrlPubMed
      1. Hoare E,
      2. Millar L,
      3. Fuller-Tyszkiewicz M, et al
      . Associations between obesogenic risk and depressive symptomatology in Australian adolescents: a cross-sectional study. J Epidemiol Community Health. 2014;68(8):767–772pmid:24711573
      OpenUrlAbstract/FREE Full Text
      1. Hong X,
      2. Li J,
      3. Xu F, et al
      . Physical activity inversely associated with the presence of depression among urban adolescents in regional China. BMC Public Health. 2009;9:148pmid:19457241
      OpenUrlCrossRefPubMed
      1. Jin S,
      2. Muhajarine N,
      3. Cushon J,
      4. Lim HJ
      . Factors associated with childhood depression in Saskatoon students: a multilevel analysis. Can J Commun Ment Health. 2013;32(1):29–42
      OpenUrl
      1. Johnson CC,
      2. Murray DM,
      3. Elder JP, et al
      . Depressive symptoms and physical activity in adolescent girls. Med Sci Sports Exerc. 2008;40(5):818–826pmid:18408618
      OpenUrlCrossRefPubMed
      1. Kremer P,
      2. Elshaug C,
      3. Leslie E,
      4. Toumbourou JW,
      5. Patton GC,
      6. Williams J
      . Physical activity, leisure-time screen use and depression among children and young adolescents. J Sci Med Sport. 2014;17(2):183–187pmid:23648221
      OpenUrlCrossRefPubMed
      1. Maras D,
      2. Flament MF,
      3. Murray M, et al
      . Screen time is associated with depression and anxiety in Canadian youth. Prev Med. 2015;73:133–138pmid:25657166
      OpenUrlCrossRefPubMed
      1. Mata J,
      2. Thompson RJ,
      3. Gotlib IH
      . BDNF genotype moderates the relation between physical activity and depressive symptoms. Health Psychol. 2010;29(2):130–133pmid:20230085
      OpenUrlCrossRefPubMed
      1. Moljord IEO,
      2. Moksnes UK,
      3. Espnes GA,
      4. Hjemdal O,
      5. Eriksen L
      . Physical activity, resilience, and depressive symptoms in adolescence. Ment Health Phys Act. 2014;7(2):79–85
      OpenUrl
      1. Piko BF,
      2. Keresztes N
      . Physical activity, psychosocial health, and life goals among youth. J Community Health. 2006;31(2):136–145pmid:16737174
      OpenUrlCrossRefPubMed
      1. Prasad A,
      2. St-Hilaire S,
      3. Wong MM,
      4. Peterson T,
      5. Loftin J
      . Physical activity and depressive symptoms in rural adolescents. N Am J Psychol. 2009;11(1):173–188
      OpenUrl
      1. Salah EM,
      2. Yamamah GA,
      3. Megahed HS,
      4. Salem SE,
      5. El-din S,
      6. Khalifa AG
      . Screening for depressive symptoms and their associated risk factors in adolescent students in South Sinai, Egypt. Life Sci J. 2013;10(3):433–443
      OpenUrl
      1. Shepherd D,
      2. Krägeloh C,
      3. Ryan C,
      4. Schofield G
      . Psychological well-being, self-reported physical activity levels, and attitudes to physical activity in a sample of New Zealand adolescent females. Psychology (Irvine). 2012;3(6):447–453
      OpenUrl
      1. Sigfusdottir ID,
      2. Asgeirsdottir BB,
      3. Sigurdsson JF,
      4. Gudjonsson GH
      . Physical activity buffers the effects of family conflict on depressed mood: a study on adolescent girls and boys. J Adolesc. 2011;34(5):895–902pmid:21334058
      OpenUrlCrossRefPubMed
      1. Soltanian AR,
      2. Nabipour I,
      3. Akhondzadeh S, et al
      . Association between physical activity and mental health among high-school adolescents in Boushehr province: A population based study. Iran J Psychiatry. 2011;6(3):112–116pmid:22952533
      OpenUrlPubMed
      1. Sun Y,
      2. An J,
      3. Wang X,
      4. Zu P,
      5. Tao FB
      . Gender- and puberty-dependent association between physical activity and depressive symptoms: national survey among Chinese adolescents. J Phys Act Health. 2014;11(7):1430–1437pmid:24184797
      OpenUrlPubMed
      1. Tao FB,
      2. Xu ML,
      3. Kim SD,
      4. Sun Y,
      5. Su PY,
      6. Huang K
      . Physical activity might not be the protective factor for health risk behaviours and psychopathological symptoms in adolescents. J Paediatr Child Health. 2007;43(11):762–767pmid:17924938
      OpenUrlCrossRefPubMed
      1. Wiles NJ,
      2. Haase AM,
      3. Lawlor DA,
      4. Ness A,
      5. Lewis G
      . Physical activity and depression in adolescents: cross-sectional findings from the ALSPAC cohort. Soc Psychiatry Psychiatr Epidemiol. 2012;47(7):1023–1033pmid:21826444
      OpenUrlCrossRefPubMed
      1. Birkeland MS,
      2. Torsheim TR,
      3. Wold B
      . A longitudinal study of the relationship between leisure-time physical activity and depressed mood among adolescents. Psychol Sport Exerc. 2009;10(1):25–34
      OpenUrlCrossRef
      1. Brunet J,
      2. Sabiston CM,
      3. Chaiton M, et al
      . The association between past and current physical activity and depressive symptoms in young adults: a 10-year prospective study. Ann Epidemiol. 2013;23(1):25–30pmid:23176784
      OpenUrlCrossRefPubMed
      1. Hume C,
      2. Timperio A,
      3. Veitch J,
      4. Salmon J,
      5. Crawford D,
      6. Ball K
      . Physical activity, sedentary behavior, and depressive symptoms among adolescents. J Phys Act Health. 2011;8(2):152–156pmid:21415441
      OpenUrlPubMed
      1. McPhie ML,
      2. Rawana JS
      . The effect of physical activity on depression in adolescence and emerging adulthood: a growth-curve analysis. J Adolesc. 2015;40:83–92doi: pmid:25721258
      OpenUrlCrossRefPubMed
    29. ↵
      1. Neissaar I,
      2. Raudsepp L
      . Changes in physical activity, self-efficacy and depressive symptoms in adolescent girls. Pediatr Exerc Sci. 2011;23(3):331–343pmid:21881154
      OpenUrlPubMed
      1. Stavrakakis N,
      2. de Jonge P,
      3. Ormel J,
      4. Oldehinkel AJ
      . Bidirectional prospective associations between physical activity and depressive symptoms. The TRAILS Study. J Adolesc Health. 2012;50(5):503–508pmid:22525115
      OpenUrlCrossRefPubMed
    30. ↵
      1. Toseeb U,
      2. Brage S,
      3. Corder K, et al
      . Exercise and depressive symptoms in adolescents: a longitudinal cohort study. JAMA Pediatr. 2014;168(12):1093–1100pmid:25317674
      OpenUrlPubMed
    31. ↵
      1. Almas A,
      2. Forsell Y,
      3. Iqbal R,
      4. Janszky I,
      5. Moller J
      . Severity of depression, anxious distress and the risk of cardiovascular disease in a Swedish population-based cohort. PLoS One. 2015;10(10):e0140742pmid:26469703
      OpenUrlPubMed
      1. Balestri M,
      2. Calati R,
      3. Souery D, et al
      . Socio-demographic and clinical predictors of treatment resistant depression: a prospective European multicenter study. J Affect Disord. 2016;189:224–232pmid:26451508
      OpenUrlPubMed
      1. Lasserre AM,
      2. Marti-Soler H,
      3. Strippoli MP, et al
      . Clinical and course characteristics of depression and all-cause mortality: a prospective population-based study. J Affect Disord. 2016;189:17–24pmid:26402343
      OpenUrlPubMed
    32. ↵
      1. Trivedi MH,
      2. Morris DW,
      3. Wisniewski SR, et al
      . Increase in work productivity of depressed individuals with improvement in depressive symptom severity. Am J Psychiatry. 2013;170(6):633–641pmid:23558394
      OpenUrlCrossRefPubMed
    33. ↵
      1. Roshanaei-Moghaddam B,
      2. Katon WJ,
      3. Russo J
      . The longitudinal effects of depression on physical activity. Gen Hosp Psychiatry. 2009;31(4):306–315pmid:19555789
      OpenUrlCrossRefPubMed
    34. ↵
      1. National Collaborating Centre for Mental Health
      . The Treatment and Management of Depression in Adults (Updated Edition): National Clinical Practice Guideline 90. London, United Kingdom: National Institute for Health & Clinical Excellence; 2010
    35. ↵
      1. Canadian Paediatric Society & Healthy Active Living Committee
      . Healthy active living for children and youth. Paediatr Child Health. 2002;7(5):339–358pmid:20046315
      OpenUrlPubMed
    36. ↵
      1. Council on Sports Medicine and Fitness
      2. Council on School Health
      . Active healthy living: prevention of childhood obesity through increased physical activity. Pediatrics. 2006;117(5):1834–1842pmid:16651347
      OpenUrlAbstract/FREE Full Text
    37. ↵
      1. Cotman CW,
      2. Berchtold NC,
      3. Christie LA
      . Exercise builds brain health: key roles of growth factor cascades and inflammation. Trends Neurosci. 2007;30(9):464–472pmid:17765329
      OpenUrlCrossRefPubMed
      1. Silverman MN,
      2. Deuster PA
      . Biological mechanisms underlying the role of physical fitness in health and resilience. Interface Focus. 2014;4(5):20140040pmid:25285199
      OpenUrlAbstract/FREE Full Text
    38. ↵
      1. Tsatsoulis A,
      2. Fountoulakis S
      . The protective role of exercise on stress system dysregulation and comorbidities. Ann N Y Acad Sci. 2006;1083:196–213pmid:17148741
      OpenUrlCrossRefPubMed
    39. ↵
      1. Zahn-Waxler C,
      2. Shirtcliff EA,
      3. Marceau K
      . Disorders of childhood and adolescence: gender and psychopathology. Annu Rev Clin Psychol. 2008;4:275–303pmid:18370618
      OpenUrlCrossRefPubMed
    40. ↵
      1. Colman I,
      2. Jones PB,
      3. Kuh D, et al
      . Early development, stress and depression across the life course: pathways to depression in a national British birth cohort. Psychol Med. 2014;44(13):2845–2854pmid:25066933
      OpenUrlCrossRefPubMed
    41. ↵
      1. Madigan S,
      2. Brumariu LE,
      3. Villani V,
      4. Atkinson L,
      5. Lyons-Ruth K
      . Representational and questionnaire measures of attachment: A meta-analysis of relations to child internalizing and externalizing problems. Psychol Bull. 2016;142(4):367–399pmid:26619212
      OpenUrlPubMed
    42. ↵
      1. Brooks SJ,
      2. Kutcher S
      . Diagnosis and measurement of adolescent depression: a review of commonly utilized instruments. J Child Adolesc Psychopharmacol. 2001;11(4):341–376pmid:11838819
      OpenUrlCrossRefPubMed
    43. ↵
      1. Ekelund U,
      2. Tomkinson G,
      3. Armstrong N
      . What proportion of youth are physically active? Measurement issues, levels and recent time trends. Br J Sports Med. 2011;45(11):859–865pmid:21836170
      OpenUrlAbstract/FREE Full Text
    • Copyright © 2017 by the American Academy of Pediatrics
    PreviousNext
    Back to top

    Advertising Disclaimer »

    In this issue

    Pediatrics
    Vol. 139, Issue 4
    1 Apr 2017
    • Table of Contents
    • Index by author
    View this article with LENS
    PreviousNext
    Email Article

    Thank you for your interest in spreading the word on American Academy of Pediatrics.

    NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

    Enter multiple addresses on separate lines or separate them with commas.
    Children’s Physical Activity and Depression: A Meta-analysis
    (Your Name) has sent you a message from American Academy of Pediatrics
    (Your Name) thought you would like to see the American Academy of Pediatrics web site.
    CAPTCHA
    This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
    Request Permissions
    Article Alerts
    Log in
    You will be redirected to aap.org to login or to create your account.
    Or Sign In to Email Alerts with your Email Address
    Citation Tools
    Children’s Physical Activity and Depression: A Meta-analysis
    Daphne J. Korczak, Sheri Madigan, Marlena Colasanto
    Pediatrics Apr 2017, 139 (4) e20162266; DOI: 10.1542/peds.2016-2266

    Citation Manager Formats

    • BibTeX
    • Bookends
    • EasyBib
    • EndNote (tagged)
    • EndNote 8 (xml)
    • Medlars
    • Mendeley
    • Papers
    • RefWorks Tagged
    • Ref Manager
    • RIS
    • Zotero
    Share
    Children’s Physical Activity and Depression: A Meta-analysis
    Daphne J. Korczak, Sheri Madigan, Marlena Colasanto
    Pediatrics Apr 2017, 139 (4) e20162266; DOI: 10.1542/peds.2016-2266
    del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
    Print
    Download PDF
    Insight Alerts
    • Table of Contents

    Jump to section

    • Article
      • Abstract
      • Methods
      • Results
      • Discussion
      • Conclusions
      • Acknowledgment
      • Footnotes
      • References
    • Figures & Data
    • Supplemental
    • Info & Metrics
    • Comments

    Related Articles

    • PubMed
    • Google Scholar

    Cited By...

    • Effects of Extra-curricular Physical Activity Programs on High-school Girls: A Systematic Review
    • Physical Activity Assessment and Counseling in Pediatric Clinical Settings
    • Physical Activity Assessment and Counseling in Pediatric Clinical Settings
    • Physical activity and sport participation among adolescents: associations with mental health in different age groups. Results from the Young-HUNT study: a cross-sectional survey
    • Lifestyle Behavior and Mental Health in Early Adolescence
    • Relationship between leisure time physical activity, sedentary behaviour and symptoms of depression and anxiety: evidence from a population-based sample of Canadian adolescents
    • The Power of Play: A Pediatric Role in Enhancing Development in Young Children
    • Google Scholar

    More in this TOC Section

    • Umbilical Cord Management at Term and Late Preterm Birth: A Meta-analysis
    • Umbilical Cord Management for Newborns <34 Weeks' Gestation: A Meta-analysis
    • Efficacy and Safety of Metformin for Obesity: A Systematic Review
    Show more Review Article

    Similar Articles

    Subjects

    • Public Health
      • Public Health
    • Psychiatry/Psychology
      • Psychiatry/Psychology
    • Journal Info
    • Editorial Board
    • Editorial Policies
    • Overview
    • Licensing Information
    • Authors/Reviewers
    • Author Guidelines
    • Submit My Manuscript
    • Open Access
    • Reviewer Guidelines
    • Librarians
    • Institutional Subscriptions
    • Usage Stats
    • Support
    • Contact Us
    • Subscribe
    • Resources
    • Media Kit
    • About
    • International Access
    • Terms of Use
    • Privacy Statement
    • FAQ
    • AAP.org
    • shopAAP
    • Follow American Academy of Pediatrics on Instagram
    • Visit American Academy of Pediatrics on Facebook
    • Follow American Academy of Pediatrics on Twitter
    • Follow American Academy of Pediatrics on Youtube
    • RSS
    American Academy of Pediatrics

    © 2021 American Academy of Pediatrics