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Review

Physical Activity of Children and Adolescents during the COVID-19 Pandemic—A Scoping Review

Institute of Sport Economics and Sport Management, German Sport University Cologne, 50933 Cologne, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Paul B. Tchounwou
Int. J. Environ. Res. Public Health 2021, 18(21), 11440; https://doi.org/10.3390/ijerph182111440
Received: 8 October 2021 / Revised: 21 October 2021 / Accepted: 29 October 2021 / Published: 30 October 2021
(This article belongs to the Special Issue Physical Activity and Sport in the COVID-19 Context)

Abstract

To counteract the COVIC-19 pandemic, many governments have introduced social distancing measures. While these restrictions helped contain the virus, it had adverse effects on individuals’ mental and physical health—especially children. The aim of the present study is to review the evidence on the effects of COVID-19 restrictions on children’s physical activity and their determinants. A scoping review was conducted in the databases PubMed, Web of Science, SportDiscus, and BISp-Surf. Inclusion criteria were empirical and peer-reviewed studies, youth samples, investigation of COVID-19 restrictions, and investigating changes and/or determinants of physical activity before and during the COVID-19 pandemic. Risk of bias was assessed using the checklist by Downs and Black. The search resulted in 1672 studies, of which 84 studies were included in the analysis. The results highlighted a decrease in physical activity during the pandemic, ranging between −10.8 min/day and −91 min/day. If an increase was detected, it related to unstructured and outdoor activities. The main determinants of children’s physical activity during the pandemic were age, gender, socioeconomic background, and the outdoor environment. The results imply that governments need to consider the negative effects that restrictive measures have on children’s physical activity and act to ensure high levels of physical activity.
Keywords: exercise; sports; lockdown; public health exercise; sports; lockdown; public health

1. Introduction

Since December 2019, the SARS-CoV-2 virus, responsible for the COVID-19 disease, has spread across the globe and caused a global pandemic. The World Health Organization (WHO) declared it a public health emergency of international concern on 30 January 2020 [1]. Many national governments have introduced countermeasures to counteract the disease and avoid infections, including social distancing policies, closure of schools, shops and leisure opportunities, contact restrictions, and curfews. While these restrictions effectively slowed down the spread of the virus and contained the disease, they came with negative externalities as individuals were forced to stay home, which increased the risk of social isolation [2]. Restricting leisure opportunities such as sports also created a barrier to physical activity, while at the same time, sedentary time increased during lockdown due to more time spent at home [3]. In contrast, physical activity was widely recommended by national governments during the time to maintain a healthy lifestyle [4].
One population group that has been struck especially hard by the restrictive measures is children and adolescents. While young people are less likely to experience severe symptoms after infection [5], they were still confined through school closures and the close-down of leisure activities. This confinement could have adverse effects on children’s physical and mental health as they did not get to play with their friends, be active in their sports groups, or have regular exercise in school physical education (PE) classes. This is especially dramatic as previous studies have shown that most children and adolescents did not reach the physical activity guidelines of 60 min of PA per day recommended by the WHO even before the pandemic [6]. A further reduction of physical activity during the pandemic could have harmful effects as PA during youth is an essential determinant for future PA [7], is an antecedent for mental health [8], and helps avoid future health challenges such as obesity and cardiovascular diseases [9].
While there have been several reviews on the effects of the COVID-19-pandemic on physical activity behaviors [3,4,10,11], there is a lack of systematic evidence on the effects on children and adolescents specifically. This is especially important as children below the age of 12 are at this point unable to receive a vaccination against the virus and might face further restrictions in later waves of the virus. Thus, this study aims to (1) identify how far the restrictions have impacted the physical activity levels of children and adolescents and (2) identify which factors determine the physical activity levels. The latter enables us to derive practical implications for effective strategies to raise physical activity levels in future pandemic waves, respectively, in potential future pandemics. The research questions guiding our study are thus two-fold:
RQ1. 
How do the restrictions during the COVID-19 pandemic affect the physical activity behavior of children and adolescents?
RQ2. 
Which individual and context-specific factors determine the physical activity behavior of children and adolescents during the COVID-19 pandemic?
To address the research questions, a scoping review of existing studies on physical activity behaviors before and during the COVID-19 pandemic was conducted. In the following, information on the methods and main results are presented. The study concludes with practical implications based on the identified effects.

2. Materials and Methods

A scoping literature review was conducted on the changes in physical activity levels of children and adolescents during the COVID-19 pandemic. The approach of a scoping review was chosen as the body of evidence on physical activity and COVID-19 is rapidly growing and is rather heterogenous, which is problematic for a precise systematic review. The databases searched included PubMed, Web of Science, SportDiscus, and BISp-Surf. The last date of search was 1 July 2021. The search strategy was structured with the following search terms: sport and/or physical activity, children and/or adolescents and/or youth, COVID-19 and/or Corona. Searches were conducted both in English and in German to cover a broader range of research contexts.
Studies were included when the sample contained children and adolescents (under 18 years). This included both studies that focused exclusively on children and adolescents and population studies that included children and adolescents as a subgroup in their sample. Further, studies were included when COVID-19 restrictions were investigated. Thus, only studies published after March 2020 (when lockdown measures started in most countries) were considered in the present analysis. Another inclusion criterion was the investigation of changes and/or determinants of physical activity before and during the COVID-19 pandemic. This excluded studies that investigated physical activity as a determinant for mental or physical health outcomes. This inclusion criterion chosen as the focus was specifically on physical activity as an outcome rather than as a treatment for other outcomes. Lastly, studies were included when empirical data were presented and studies were peer-reviewed. Studies were collected by one author, and two authors independently reviewed the studies for inclusion/exclusion. In case of disagreement, a final decision on inclusion/exclusion was discussed until consensus was reached.
Studies included in the qualitative synthesis were summarized by two authors in an Excel spreadsheet and information on study characteristics and main interest results were gathered. Information was summarized on the country of interest (research context), research paradigm, study design, sample size and age of interest (of children), methods used, change of physical activity behavior, and determinants of physical activity behavior. These characteristics were considered when interpreting the results of studies.
The principal summary measure was the change of physical activity behavior, which was coded “decrease” when studies reported a reduction of frequency or duration of physical activity, “increase” when studies reported growth of frequency or duration of physical activity behavior, and “no difference” when no significant differences were detected. Determinants of physical activity during the COVID-19 pandemic were gathered when significant effects were reported. Due to the high heterogeneity in the outcome measures (i.e., how physical activity was assessed), no meta-analysis could be performed and the studies were synthesized in a narrative review. Evidence was assessed to be certain when studies had low levels of risk and the majority of studies reported similar results.
Studies were assessed on their risk of bias using the checklist by Downs and Black [12]. The checklist was slightly adapted in item 27, following previous review studies [13]. Two researchers assessed each study independently, and scores were compared in the aftermath. In case of divergence, the consensus was reached through in-depth assessment by both researchers jointly. Quality levels of studies were classified as excellent (scores 26–28), good (20–25), fair (15–19), and poor (≤14) following previous applications of the Downs and Black checklist [14].

3. Results

3.1. Study Selection

The search and identification process is illustrated in Figure 1.
The database search resulted in 1645 identified studies, enriched by 27 studies identified through additional searches in reference lists. After duplicates were removed, 1063 records remained, which were initially screened on eligibility based on their title and abstract. A total of 882 records were excluded as the study content and the topic of the study were considered irrelevant to the present analysis. The remaining 150 studies were sought for retrieval, of which 31 studies could not be retrieved. The remaining 119 studies were assessed on eligibility based on the full-text article, and 35 studies were excluded as they did not fulfil the inclusion criteria. Finally, 84 studies were included in the final synthesis of findings. An overview of the studies included in the analysis is presented in Appendix A.

3.2. Study Characteristics

The majority of studies included in the analysis stemmed from Western countries, including 25 studies from the Americas (North and South America), 33 studies from Europe, and 7 studies from Oceania. In contrast, 11 studies were conducted in Asia and only 2 studies stemmed from African countries. Five studies were classified as cross-continental as they included data from countries from different continents (see Table A1).
The research paradigm of the studies included in the analysis was predominantly quantitative, with 74 studies following a quantitative approach. Nine studies followed a qualitative paradigm and two studies used mixed-methods research. The majority of studies used a cross-sectional study design (59 studies), while 25 studies used a longitudinal design. One study employed a retrospective case-control design. The sample size of the studies included in the analyses ranged between n = 9 and n = 16,177. The total sample size cannot be stated as some studies used the same sample for their analysis. Many studies focused exclusively on children and adolescents, meaning that children and adolescents were questioned directly, or parents/caregivers were asked about children’s behavior. A total of 22 studies focused on children up to 12 years, 21 studies focused on adolescents (12–19 years), and 30 studies investigated a sample including children and adolescents (1–19 years). In the final analysis, nine studies were general population studies that included children and adolescents as subgroups. The methods used by the studies in the final analysis mainly were surveys, particularly online surveys (66 studies). Three studies conducted phone interviews, five studies used semi-structured interviews, four studies used fitness or motor competence assessments, and two studies each used accelerometery, that is, step counts. Single studies made use of a cardiopulmonary stress test, a focus group, a case study (including observations and participant journals), community mobility data via Google, and an expert panel.
The assessment of risk of bias resulted in 50 studies rated as ‘fair’, 31 studies rated as ‘poor’, and three studies rated as ‘good’. The rather low scores overall could be traced back to a lack of randomization and blinding in all studies as none of the studies were randomized-controlled trials due to the ad hoc nature of the research and the overall effect that the pandemic had on all study participants. Moreover, common concerns which occurred were the lack of a representative sample, neglection of confounders, and lack of an a priori power analysis.

3.3. Change of Physical Activity Behavior

On the primary variable of interest, most studies (57 studies) reported a decrease in physical activity, both in duration and frequency of physical activity (see Table 1). Four studies identified an increase in physical activity [15,16,17,18], whereas six studies could detect no significant difference in physical activity behaviors before and during the pandemic [19,20,21,22,23,24]. Eight studies reported differentiated results with indoor and organized sports and physical activity decreasing, while non-organized and outdoor sports and physical activity increased [25,26,27,28,29,30,31,32].
The decrease in time spent on physical activity ranged between −45 min/day in Chile [33] to −91 min/day in Spain [34]. However, the measurement of physical activity differed substantially across the studies, which made the reporting of exact effects difficult. Thus, this range covers only those studies reporting concrete figures. The increase in physical activity was reported to be +53 min/day in Sweden [17].

3.4. Determinants of Physical Activity Behavior

Thirty-four studies identified one or more determinants of the physical activity behavior of children and adolescents during the COVID-19 pandemic. Facilitating factors, meaning factors that enabled children and adolescents to be more physically active, were found on an individual level but also on a context level. Individual factors increasing physical activity of children were being male [35,36,37], following a daily routine [27,38], spending time on outdoor physical activity [35,38], taking part in online PE classes [27,38,39], more time available [40], no school [40], use of digital platforms [41], prior fitness status [28,42,43,44], and health-related quality of life [44]. Context-specific factors, i.e., factors relating to the family context, were having more than one child at home [29,33,45], higher parental education [36], perceived parental capability [35], living in a house [46], low dwelling density [46], access to parks [46], parental encouragement and support [27,47,48], parental engagement in physical activity [47], family dog ownership [47], household income [47,48], family coexistence [49], and access and size of outdoor space available [45,48,50,51] (see Table 2).
In contrast, studies also identified constraining factors, meaning factors that hindered children and adolescents from being physically active. These constraining factors were also individual or context-specific. Individual constraining factors included the child’s age [20,37,45,50,52,53], feelings of stress [54,55], feeling comfortable at home [55], having a migration background [34], lower socioeconomic status (SES) [29], change to routines [27], pre-COVID sedentary time [44], pre-COVID activity levels [51], and mood states [56]. Context-related constraints included the caregiver’s level of education [32,33,34], living in an apartment [33], parent’s age [47], parent’s marital status [20], lack of playmates [57], family conflict [36,58], no outdoor space available [55], level of parents’ stress [49], lack of supervision [57], proximity to major roads [46], restrictions from COVID-19 [40,48], club training cancellation [40], enrolment in an early education center [33], and urban environment [51,59] (see Table 3).

4. Discussion

When it comes to physical activity, behaviors of children and adolescents during the COVID-19 pandemic, the level of evidence is relatively strong, with a surprisingly high number of longitudinal studies. However, the review revealed a lack of methodological variety as most studies used online surveys. Moreover, there is a clear focus on Western countries (Australia, Canada, USA, Europe) with a lack of research into Asian and African countries. More research is needed in these regions (with the exception of China) to see how children and adolescents were affected by lockdown measures there.
There is clear evidence for decreased physical activity during the lockdown in the studies identified in this review, especially in organized sports, as structured sports programs and facilities were closed. This shows that public recommendations for maintaining physical activity have so far been ineffective. If an increase has been detected, it occurred in outdoor play and unstructured activities [15,26,29,30,31] or related to lower levels of national restrictions [17]. The increase in outdoor activities depends strongly on the housing environment. Thus, the pandemic and the resulting restrictions have further increased social differences between families with safe and spacious outdoor spaces and families living in dense environments.
This is also reflected in the determinants of children’s physical activity behavior. The determinants identified by the studies mainly related to the parental and family background, the outdoor environment, participation in structured programs, including having a routine, and previous physical activity experiences. The role of parental education differed depending on the context. In European studies, higher education of parents increased physical activity, whereas in studies in Latin America, higher parental, especially maternal education harmed children’s physical activity. This difference could hint at cultural differences or issues in time availability and strengthens our call for more research in different national contexts (especially Africa and Asia).
One predictor of children’s physical activity identified in the review was the socioeconomic background. This complements general physical activity findings that children and adolescents with a higher SES are generally more physically active [60]. Once again, this difference relates to the built environment that children and adolescents are situated in as they provide little to no opportunities for physical activity—especially in times of a pandemic where indoor activities and crowded areas were restricted.
Last but not least, the problem of inactivity is especially prominent in females and older children and adolescents. This is especially concerning as the teenagers’ age group had already shown decreasing activity levels before the pandemic [60]. Thus, the restrictions and lockdowns have intensified the problem even further. One reason for the steeper decline during the pandemic could be the more substantial reliance on routines and the lack of replacement programs for organized activities. A higher priority needs to be put on adolescents’ routines to maintain a healthy and active lifestyle also during a pandemic.
The findings of the review lead to clear implications for policymakers. First, policymakers and educators need to educate and engage parents and caregivers in physical activity to increase physical activity levels overall ensuring consistent movement at baseline. One approach would be to include physical literacy into pre-school and school education agendas and make physical activity as one component of a healthy lifestyle a top priority in children’s education.
Second, to create physical activity routines and thus maintain physical activity levels during phases of lockdowns, policymakers need to make online PE classes mandatory if schools need to close down again. Programs on digital platforms have been found to have a positive effect as well but to sustain participation and ensure that routines are kept, making these programs mandatory is critical.
Third, policymakers and city planners need to ensure a safe and movement-friendly outdoor environment with access to parks and playgrounds and low-density architecture. This is needed, especially in socially deprived areas, to decrease the divide between families with higher and lower SES. This divide has been illustrated once more during the pandemic—both in infection rates and physical activity behaviors.
Some limitations might constrain the explanatory power of this review. First, it is hard to compare all studies identified in the database search as studies were conducted during different stages of the COVID-19 pandemic. The search period included studies conducted between March 2020 and April 2021. As infection rates and restrictions differed between countries and stages of the pandemic, these findings cannot be related to specific lockdown measures. However, we tried to take these differences into account by considering the national context in interpreting studies. Moreover, the variability in measurement of physical activity across the studies limits the comparability further and makes general statements on the impact of the pandemic difficult.
Future research is needed to establish ongoing monitoring of the physical activity of children and adolescents. Potential long-term effects of the COVID-19 restrictions need to be identified, and effective countermeasures need to be developed. This review has given the first insight into the effects on children’s physical activity and what can be done to counteract the decreasing activity. However, more research is needed to assess this in the long term. Moreover, generalized tools to measure the physical activity of children and adolescents need to be established to ensure comparability of results across studies and national contexts, which again enables researchers to track global long-term changes in physical activity. Lastly, while this review has focused on the changes and determinants of physical activity, governmental restrictions and the resulting decrease in physical activity have potential further effects on children and adolescents, i.e., decreasing scholastic performance or mental health. Future reviews should focus on these outcomes of decreasing physical activity to create a more holistic picture of the effects of the COVID-19 pandemic on children and adolescents.

5. Conclusions

This scoping review has shown strong evidence for a negative effect of COVID-19 restrictions on children’s physical activity behavior. Physical activity has decreased especially with higher age of children and with a lower socioeconomic background. Thus, the COVID-19 pandemic has worsened the trend of inactivity which was alarming even before the pandemic.
While the review has uncovered a strong growth of research on the topic of physical activity of children and adolescents and COVID-19 since the start of the pandemic, it has also highlighted a lack of consistent measurement of physical activity levels which hinders the comparison of results between studies. Developing consistent measurement standards of physical activity should be part of a future research agenda to ensure that long-term developments of physical activity behaviors can be tracked and compared across national and international studies.

Author Contributions

Conceptualization, L.R. and C.B.; methodology, L.R., N.B. and C.B.; validation, L.R. and N.B.; formal analysis, L.R.; data curation, N.B.; writing—original draft preparation, L.R.; writing—review and editing, L.R., N.B. and C.B.; visualization, L.R.; supervision, C.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. Overview of studies included in the systematic review by continent (in alphabetic order).
Table A1. Overview of studies included in the systematic review by continent (in alphabetic order).
No.Author, Year (Ref)CountryResearch ParadigmStudy DesignSample
(Age Incl.)
MethodChange of PARisk of Bias
Americas
1Aguilar-Farias et al., 2020 [33]ChileQUANCross-sectionaln = 3157
(1–5 years)
Online surveyDecreaseFair
2Bazett-Jones et al., 2020 [61]USAQUANCross-sectionaln = 287
(9–19 years)
Online surveyDecreaseFair
3Beck et al., 2021 [62] USAQUANCross-sectionaln = 145
(4–12 years)
SurveyDecreaseFair
4Dayton et al., 2020 [63]USAQUANRetrospective case-controln = 20 (mean: 15.2 years)Cardiopulmonary stress testingDecreaseFair
5Gama de Matos et al., 2020 [64]BrazilQUANCross-sectionaln = 426
(children, adolescents, adults, elders)
Online surveyDecreaseFair
6Dos Santos Cardoso de Sá, 2020 [65]BrazilQUANCross-sectionaln = 816
(<12 years)
Online surveyDecreasePoor
7Dunton et al., 2020 [66]USAQUANCross-sectionaln = 211
(5–13 years)
Online surveyDecreaseFair
8Eyler et al., 2021 [67]USAQUANCross-sectionaln = 245
(5–12 years)
Online surveyDecreaseFair
9Garcia et al., 2020 [68]USAQUANLongitudinaln = 9
(14–19 years)
Online surveyDecreaseFair
10Guerrero et al., 2020 [35]CanadaQUANCross-sectionaln = 1472
(5–17 years)
Online survey, decision tree-Fair
11Hemphill et al., 2020 [69]CanadaQUANLongitudinaln = 109
(9–16 years)
Step count via Fitbit-TrackerDecreaseFair
12Kracht et al., 2021 [58]USAQUANCross-sectionaln = 1836
(3–6 years)
Online surveyDecreaseFair
13Lafave et al., 2021 [15]CanadaQUALCross-sectionaln = 17
(2–5 years)
Semi-structured interviewsIncreasePoor
14Malta et al., 2021 [70]BrazilQUANCross-sectionaln = 6470
(12–17 years)
Online surveyDecreasePoor
15McCormack et al., 2020 [25]CanadaQUANCross-sectionaln = 328
(school-aged)
Online surveyPA at home: increase
PA outdoors: decrease
Fair
16Mitra et al., 2020 [46]CanadaQUANCross-sectionaln = 1472
(5–17 years)
Online surveyDecreaseFair
17Moore et al., 2020 [47]CanadaQUANCross-sectionaln = 1472
(5–17 years)
Online surveyDecreaseFair
18Pavlovic et al., 2021 [71]USAQUANCross-sectionaln = 2440
(PE teachers, school and district administrators, nurses, others)
Online surveyDecreasePoor
19Pelletier et al., 2021 [26]CanadaQUALCross-sectionaln = 21
(7–12 years)
Semi-structured interviewIncrease in unstructured activity; decrease in structured activityPoor
20Perez et al., 2021 [48]USAQUALCross-sectionaln = 321 (mean: 7.8 years)Open-ended surveyDecreasePoor
21Riazi et al., 2021 [16]CanadaQUALCross-sectionaln = 29
(5–11 years)
Semi-structured interviewsDecreasePoor
22Shepherd et al., 2021 [27]CanadaQUALCross-sectionaln = 20
(high-school student-athletes)
Semi-structured interviewsVariationsPoor
23Siegle et al., 2020 [50]BrazilQUANCross-sectionaln = 816
(<13 years)
Online surveyDecreaseFair
24Tulchin-Francis et al., 2021 [52]USAQUANCross-sectionaln = 1310
(3–18 years)
Online surveyDecreaseFair
25Wahl-Alexander and Camic, 2021 [72]USAQUANLongitudinaln = 264 (mean: 9.6 years)In-person testing (BMI, fitness assessment)DecreasePoor
Europe
26Androutsos et al., 2021 [73]GreeceQUANCross-sectionaln = 397
(2–18 years)
Online surveyDecreaseFair
27Bronikowska et al., 2021 [28]PolandQUANLongitudinaln = 127 (mean: 15.4 years)Online surveyIncrease in previously inactive, decrease in previously activeFair
28Chambonniere et al., 2021 [51]FranceQUANCross-sectionaln = 6491
(6–17 years)
Online surveyDecreasePoor
29Chen et al., 2021 [74]SwedenQUANLongitudinaln = 1316 (mean: 13.6 years at baseline)Online surveyDecreasePoor
30Dauty et al., 2020 [75]FranceQUANLongitudinaln = 19
(13–15 years)
Pre- and post-confinement Yo-Yo TestDecreaseFair
31Delisle Nyström et al., 2020 [17]SwedenQUANLongitudinaln = 100
(3–5 years)
Phone interview, accelerometerIncreaseGood
32Di Renzo et al., 2020 [19]ItalyQUANCross-sectionaln = 3533
(≥12 years)
Online surveyNo differenceFair
33Dragun et al., 2020 [20]CroatiaQUANLongitudinaln = 1326 (adolescents, medical students)Pre-COVID: in-person survey
During COVID: online survey
No differenceFair
34Fillon et al., 2021 [76]FranceQUANLongitudinaln/aExpert panelDecreasePoor
35Francisco et al., 2020 [77]Italy, Spain, PortugalQUANCross-sectionaln = 1480
(3–18 years)
Online surveyDecreasePoor
36Gallucio et al., 2021 [21]ItalyQUANCross-sectionaln = 91
(15–17 years)
Online surveyNo differenceFair
37Gilic et al., 2020 [36]Bosnia and HerzegovinaQUANLongitudinaln = 688
(15–18 years)
Online surveyDecreaseFair
38Jurak et al., 2021 [78] SloveniaQUANLongitudinaln = 20,000
(6–14 years)
SLOfit barometer, fitness measurementsDecreasePoor
39Kolota and Glabska, 2021 [22]PolandQUANCross-sectionaln = 1334
(10–16 years)
Online surveyNo differenceFair
40Kovacs et al., 2021 [38]10 Euro-pean countriesQUANCross-sectionaln = 8395
(6–18 years)
Online surveyDecreasePoor
41López-Bueno et al., 2020 [79]SpainQUANCross-sectionaln = 860
(3–16 years)
Online surveyDecreaseFair
42Medrano et al., 2020 [34]SpainQUANLongitudinaln = 290
(8–16 years)
Online surveyDecreaseGood
43Ng et al., 2020 [40]IrelandQUANCross-sectionaln = 1214
(12–18 years)
Online surveyDecreaseFair
44O’Kane et al., 2021 [23]IrelandMIXEDLongitudinaln = 281
(12–14 years)
Survey, semi-structured interviewsNo differenceFair
45Orgilés et al., 2020 [49]Italy, SpainQUANCross-sectionaln = 1143
(3–18 years)
Online surveyDecreasePoor
46Pietrobelli et al., 2020 [80]ItalyQUANLongitudinaln = 41
(6–18 years)
Pre-COVID: in-person interview
During COVID: phone interview
DecreaseFair
47Pombo et al., 2020 [45]PortugalQUANCross-sectionaln = 2159
(<13 years)
Online survey-Fair
48Pombo et al., 2021 [81]PortugalQUANLongitudinaln = 114
(6–9 years)
Motor competence assessmentDecreaseGood
49Pombo et al., 2021 [82]PortugalQUANCross-sectionaln = 2159
(<13 years)
Online surveyDecreaseFair
50Poulain et al., 2021 [29]GermanyQUANLongitudinaln = 285
(1–10 years)
Online surveyPlaying outdoors: increase
Indoor sports: decrease
Fair
51Schmidt et al., 2020 [30]GermanyQUANLongitudinaln = 1711
(4–17 years)
Pre-COVID: in-person survey
During COVID: online survey
Nonorganized PA: increase
Organized sports: decrease
Fair
52Sekulic et al., 2020 [42]CroatiaQUANLongitudinaln = 401
(15–18 years)
Online surveyDecreaseFair
53Siachpazidou et al., 2021 [83]GreeceQUANCross-sectionaln = 482
(4–12 years)
Online surveyDecreasePoor
54Szabó et al., 2020 [84]HungaryQUANCross-sectionaln = 840
(<85 years)
Online surveyDecreaseFair
55Ten Velde et al., 2021 [85]NetherlandsQUANLongitudinalCohort A: n = 102
Cohort B: n=131
(A: 4–18 years
B: 7–12 years)
Cohort A: online survey
Cohort B: online survey, accelerometry
DecreaseFair
56Versloot et al., 2020 [86]NetherlandsQUANLongitudinaln = 82
(6–49 years)
Phone interviewDecreasePoor
57Vukovic et al., 2021 [43]SerbiaQUANCross-sectionaln = 450Online surveyDecreaseFair
58Wunsch et al., 2021 [44]GermanyQUANLongitudinaln = 1711
(4–17 years)
Pre-COVID: in-person survey
During COVID: online survey
IncreaseFair
59Zorcec et al., 2020 [87]MacedoniaQUANCross-sectionaln = 72
(mean: 7.3 years)
Online surveyDecreasePoor
Asia
60Constantini et al., 2021 [39] IsraelQUANCross-sectionaln = 473
(16–18 years)
Online survey-Fair
61Elnaggar et al., 2020 [57]Saudi ArabiaQUANLongitudinaln = 63
(14–18 years)
Online surveyDecreasePoor
62Guo et al., 2021 [88]ChinaQUANCross-sectionaln = 10,416
(10–16 years)
Online surveyDecreasePoor
63Jia et al., 2020 [89]ChinaQUANCross-sectionaln = 10,082
(high school, college, graduate school students)
Online surveyDecreasePoor
64Xiang et al., 2020 [90]ChinaQUANLongitudinaln = 2426
(6–17 years)
Online surveyDecreasePoor
65Xiao et al., 2021 [37]ChinaQUANCross-sectionaln = 1680 Online survey-Poor
66Yang et al., 2020 [91]ChinaQUANCross-sectionaln = 10,082 (mean: 19.8 years)Online surveyDecreasePoor
67Zenic et al., 2020 [59]CroatiaQUANLongitudinaln = 823 (mean: 16.5 years)Online surveyDecreaseFair
68Zhang et al., 2020 [56]ChinaQUANCross-sectionaln = 9979
(9–14 years)
Online surveyDecreaseFair
69Zhou et al., 2021 [92]ChinaQUANCross-sectionaln = 8115
(15–33 years)
Online surveyDecreaseFair
70Zhu et al., 2021 [18]Hong KongQUANCross-sectionaln = 2863
(9–17 years)
In-person surveyIncreaseFair
Africa
71Abid et al., 2021 [93]TunisiaQUANCross-sectionaln = 100
(5–12 years)
Online surveyDecreaseFair
72Dixon et al., 2020 [53]KenyaQUALCross-sectionaln = 16
(14–18 years)
Case study (observations, participant journals)DecreasePoor
Oceania
73Elliott et al., 2021 [94]AustraliaQUALCross-sectionaln = 18
(15–17 years)
Online interviews, focus groupsDecreasePoor
74Masi et al., 2020 [95]AustraliaQUANCross-sectionaln = 302
(2–17 years)
Online surveyDecreasePoor
75Munasinghe et al., 2020 [96]AustraliaQUANLongitudinaln = 582
(13–19 years)
App survey, EMA, smartphone sensorsDecreaseFair
76Nathan et al., 2021 [31]AustraliaQUANLongitudinaln = 157
(5–9 years)
Online surveyUnorganized PA: increase
Organized PA: decrease
Fair
77Parker et al., 2021 [41]AustraliaQUANCross-sectionaln = 963
(13–17 years)
Online survey-Fair
78Reece et al., 2020 [97]AustraliaQUANCross-sectionaln = 16,177
(4–18 years)
Online surveyDecreasePoor
79Sciberras et al., 2020 [54]AustraliaQUANLongitudinaln = 213
(5–17 years)
Online surveyDecreaseFair
Cross-continental
80Guan et al., 2020 [98]15 countriesQUANCross-sectionaln/aCommunity mobility data (Google)DecreasePoor
81López-Aymes et al., 2021 [55]Spain, Latin AmericaMIXEDCross-sectionaln = 234
(≥18 years)
Online survey, discourse analysis-Poor
82López-Gil et al., 2021 [99]Brazil, SpainQUANCross-sectionaln = 1099
(3–17 years)
Online surveyDecreaseFair
83Okely et al., 2021 [24]14 countriesQUANLongitudinaln = 948
(3–5 years)
SurveyNo differenceFair
84Ruíz-Roso et al., 2020 [32]Brazil, Chile, Colombia, Spain, ItalyQUANCross-sectionaln = 726
(10–19 years)
Online surveyDecrease overall (increase in Italy, Spain, Colombia)Fair

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Figure 1. PRISMA flow chart of the study selection process.
Figure 1. PRISMA flow chart of the study selection process.
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Table 1. Changes in physical activity (PA) of children and adolescents during the COVID-19 pandemic.
Table 1. Changes in physical activity (PA) of children and adolescents during the COVID-19 pandemic.
Change of PA IdentifiedMinMaxNo. of Studies
Decrease−45 min/day [33]−91 min/day [34]57
Increase-+53 min/day [17]4
No change--6
Mixed results--8
Table 2. Facilitating factors in children’s physical activity (PA) during the COVID-19 pandemic.
Table 2. Facilitating factors in children’s physical activity (PA) during the COVID-19 pandemic.
LevelFacilitating FactorNo. of Studies
Individual levelPrior fitness status4
Male gender3
Taking part in online PE classes3
Following a daily routine2
Spending time on outdoor PA2
More time available1
No school1
Use of digital platforms1
Health-related quality of life1
Context levelSize of outdoor space available4
More than one child3
Parental encouragement and support3
Household income2
Higher parental education1
Perceived parental capability1
Living in a house1
Low dwelling density1
Access to parks1
Parental engagement in PA1
Family dog ownership1
Family coexistence1
Table 3. Constraining factors in children’s physical activity (PA) during the COVID-19 pandemic.
Table 3. Constraining factors in children’s physical activity (PA) during the COVID-19 pandemic.
LevelConstraining FactorNo. of Studies
Individual levelChild’s age6
Feelings of stress2
Feeling comfortable at home1
Having a migration background1
Lower socioeconomic status1
Change to routines1
Pre-COVID sedentary time1
Pre-COVID activity levels1
Mood states1
Context levelCaregiver’s level of education3
Family conflict2
Restrictions from COVID-192
Urban environment2
Living in an apartment1
Parent’s age1
Parent’s marital status1
Lack of playmates1
No outdoor space available1
Level of parent’s stress1
Lack of supervision1
Proximity to major roads1
Club training cancellation1
Enrolment in an early education center1
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