Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Physical activity and screen time of children and adolescents before and during the COVID-19 lockdown in Germany: a natural experiment

Abstract

The impact of COVID-19 on social life has been drastic and global. However, the different numbers of cases and different actions in different countries have been leading to various interesting yet unexplored effects on human behavior. In the present study, we compare the physical activity and recreational screen time of a representative sample of 1711 4- to 17-year-olds before and during the strictest time of the first COVID-19 lockdown in Germany. We found that sports activity declined whereas recreational screen time increased. However, a substantial increase in habitual physical activities leads to an overall increase in physical activity among children and adolescents in Germany. The effects differ in size but not in their direction between age groups and are stable for boys and girls. We conclude from this natural experiment that physical activity among children and adolescents is highly context-driven and mutual and does not act as a functional opposite to recreational screen time.

Introduction

Physical activity (PA), described as “any bodily movement produced by skeletal muscles that results in energy expenditure1”, and low levels of sedentary time spent in front of screens and monitors (screen time, ST) have been associated with improved physical, psychosocial, and mental health2,3,4,5, especially among children and adolescents6. For a healthy lifestyle, the World Health Organization (WHO) and other authors recommend 60 min of moderate-to-vigorous daily PA for children and adolescents and low levels of recreational screen time (ST)7,8. Although there is no consensus yet for ST recommendations in children and adolescents, several experts have established guidelines recommending no more than 2 h of recreational ST for youth9,10.

Many countries have successfully worked towards these goals by implementing different organized, i.e., guided and repeated opportunities for being active, such as extracurricular sports classes in schools, and nonorganized opportunities such as public sports facilities or jogging routes in youth’s everyday life9,11. Therefore, the COVID-19 outbreak and concomitant shutdown of organized sports and public sports facilities in most countries resulted in crucial changes in youth’s daily routines and their opportunities for being active.

After the WHO had declared COVID-19 a global pandemic on March 11, 2020, the federal states in Germany closed kindergartens, schools, sports clubs, gyms, and other leisure institutions relevant to children’s and adolescents’ organized PA between March 16 and 18, 2020. The government also imposed physical distancing measures and contact restrictions, allowing no more than two people from different households to meet in public space12. This resulted in a complete shutdown of organized PA in the context of sports (SA). However, nonorganized SA, such as workouts at home, or jogging, and other forms of habitual PA besides sports (HA), like going for a walk or playing outside remained allowed if done alone or with people from the same household13. Although some stores were allowed to reopen on April 20, the lockdown was imposed until May 3, 202014. An overview of the restrictions is presented in Fig. 2.

Previous studies indicate that healthy behaviors have complied more beneficially during structured days (especially school days) as compared to unstructured days (e.g., during vacations or on weekends)15. This is supported by data that shows the importance of structured institutions and organizations (e.g., schools, sports clubs) for children's and adolescents' SA in Germany16. Therefore, some researchers assume that the COVID-19 pandemic reinforces the pandemic of physical inactivity and sedentariness due to missing PA opportunities and physical distancing17,18 with a long return to normality19. Studies that have investigated the impact of COVID-19 on children’s PA and ST are scarce, but most of them support these assumptions. One study carried out in Shanghai compared data of 2426 children and adolescents (6–17 years) before and during the pandemic. The results showed that participants drastically reduced overall PA from an average of 540 to 105 min per week, while they increased ST from an average of 170 to 450 min weekly20. A study using prospective data from 823 adolescents around the age of 16 years in Croatia also showed that PA levels decreased and that there was a stronger decrease in adolescents living in urban areas21. Another study investigated step count changes in 109 children with congenital heart disease in Canada, showing that total steps decreased by 21–24% at the end of March and beginning of April 2020 as compared to the same time in 201922. A study with 41 children between 6 and 18 years of age with obesity in Italy also showed that children reduced PA by almost 2.5 h per week23.

Two studies investigated the compliance with PA guidelines and ST recommendations. A study carried out in Shanghai showed that the compliance with the PA guidelines dropped from 60% before the pandemic to 17.7% during the pandemic20. Another study among 1472 children and adolescents between 5 and 17 years of age from Canada showed that 18% adhered to the PA guidelines and 11.2% adhered to the screen time recommendations24 during COVID-19. In comparison, Canada reported a 35% compliance with the PA guidelines and a 8–64% compliance with the ST guidelines in their PA report card of 201825.

In sum, studies on the impact of COVID-19 on PA and ST lack methodological comparability, and the representativeness of most samples is low. Comparability between the different studies is also limited through the respective countries’ different policy measures that probably impacted PA and ST. Most countries reacted to the pandemic by a shutdown of real-world social life, including institutions that offered preventive health care with organized PA. However, the different reactions to the pandemic also created a patchwork of different natural experiments that may reveal interesting insights into human behavior. One important question derived from the circumstances in Germany is to what extend children and adolescents will transfer organized, guided PA to other forms of self-determined PA, or whether they will transfer it to ST and other sedentary behaviors instead.

In the following, we present the results of a natural experimental study among children and adolescents between 4 and 17 years of age in a nationwide representative sample during the strictest time of the first COVID-19 lockdown in Germany. We investigated how SA, HA, and recreational ST in children and adolescents in Germany changed during the COVID-19 lockdown using the data of two measurement points before (pre) and during (peri) the lockdown from the German Motorik-Modul (MoMo) cohort study.

Results

The MoMo PA questionnaire measures PA and ST in different settings and allows to map PA recommendations8 and recommendations for recreational ST7,8. PA is further differentiated into different forms of organized and nonorganized SA and HA. An overview of differences between the pre and peri measurements of the whole sample of 4- to 17-year-olds can be found in Fig. 1.

Figure 1
figure1

Differences for total amount of sports, habitual physical activity, and recreational screen time among youth in Germany pre and peri the COVID-19 lockdown (MoMo study).

Guideline adherence

Table 1 shows how many days participants reported to be active for more than 60 min during a normal week pre and peri the lockdown and indicates the percentage of participants that adhered to the PA and ST guidelines. The analysis revealed a main effect of the lockdown on reported active days (F1, 1686 = 72.9, p < 0.01, p. η2 = 0.041) with an increase of 0.44 days per week. Additionally, an interaction between the lockdown and age group for active days was found (F3, 1686 = 4.5, p < 0.01, p. η2 = 0.008). 4- to 5-year-olds increased their PA by 0.76 active days whereas 14- to 17-year-olds increased it by 0.26 days. In terms of adherence to the WHO PA guidelines, this translates into a significant 11.1% overall increase during the lockdown with differences being larger for younger participants (4- to 5-year-olds + 14.7%) than for older ones (14- to 17-year-olds + 4.8%). At the same time, ST guideline adherence decreased by 17.5% (cf. Table 1).

Table 1 Overall physical activity and guideline adherence before and during the COVID-19 lockdown in Germany (MoMo Study).

Sports activity

Organized sports at school and in sports clubs were shut down during the lockdown which leads to no measurable organized sports during the peri measurement. Table 2 shows the average daily minutes spent doing organized and nonorganized sports, and the total amount of sports pre and peri the lockdown. A significant main effect of the lockdown on nonorganized sports was found (F1, 1601 = 626.3, p < 0.01, p. η2 = 0.281). Participants reported an increase in nonorganized sports of 17.7 min per day. Additionally, an interaction between the lockdown and age was found for nonorganized sports (F3, 1601 = 9.8, p < 0.01, p. η2 = 0.018). 14- to 17-year-olds increased their nonorganized sports by 17.0 min per day whereas 4- to 5-year-olds increased it by 11.8 min. For the total amount of sports, we found a main effect of the lockdown (F1, 1644 = 122.3, p < 0.01, p. η2 = 0.069) in a negative direction. Participants reported a decrease in the total amount of sports of 10.8 min per day, and an interaction between the lockdown and age (F3, 1644 = 8.6, p < 0.01, p. η2 = 0.015) was significant: 14- to 17-year-olds reduced their total amount of sports by 15.6 min per day whereas 4- to 5- year-olds reduced it by 2.2 min.

Table 2 Sports activity before and during the COVID-19 lockdown in Germany (MoMo Study).

Habitual physical activity

In the pre-measurement, significant effects of age were detected for playing outside (F3, 1665 = 166.7, p < 0.01, p. η2 = 0.231), walking and cycling (F3, 1554 = 12.1, p < 0.01, p. η2 = 0.023), gardening (F3, 1652 = 7.1, p < 0.01, p. η2 = 0.013), housework (F3, 1658 = 38.3, p < 0.01, p. η2 = 0.065), and the total amount of HA (F3, 1680 = 42.3, p < 0.01, p. η2 = 0.070) (cf. Table 3). Younger children accumulated more minutes of PA playing outside whereas adolescents accumulated more minutes walking and cycling as well as gardening and doing housework. In sum, with 136.5 min per day, 4- to 5-year-olds accumulated more minutes of daily HA than 14- to 17-year-olds with 80.3 min. Furthermore, significant effects of sex were detected for playing outside (F1, 1665 = 12.6, p < 0.01, p. η2 = 0.007), gardening (F1, 1652 = 14.1, p < 0.01, p. η2 = 0.008), housework (F1, 1658 = 10.4, p < 0.01, p. η2 = 0.006), and the total amount of HA (F1, 1680 = 11.9, p < 0.01, p. η2 = 0.007) in the pre-measurement. Boys accumulated more minutes of PA by playing outside, walking and cycling, and gardening, whereas girls accumulated more minutes of PA doing housework.

Table 3 Habitual physical activity before and during the COVID-19 lockdown in Germany (MoMo Study).

The longitudinal analysis revealed a main effect of the lockdown on playing outside (F1, 1665 = 12.6, p < 0.01, p. η2 = 0.007), gardening (F1, 1638 = 80.7, p < 0.01, p. η2 = 0.047), housework (F1, 1645 = 62.2, p < 0.01, p. η2 = 0.036), and the total amount of HA (F1, 1673 = 181.4, p < 0.01, p. η2 = 0.098). No main effect of the lockdown was found for walking and cycling. Playing outside increased by 21.4 min, gardening increased by 6.7 min, housework increased by 4.0 min, and the total amount of HA increased by 36.2 min. An interaction between the lockdown and age was found for playing outside (F3, 1654 = 22.2, p < 0.01, p. η2 = 0.039), gardening (F3, 1638 = 7.3, p < 0.01, p. η2 = 0.013), housework (F3, 1645 = 2.8, p = 0.04, p. η2 = 0.003), and the total amount of HA (F3, 1673 = 14.9, p < 0.01, p. η2 = 0.026) (c.f. Table 3).

Recreational screen time

Significant effects of age were detected for watching TV (F3, 1671 = 7.7, p < 0.01, p. η2 = 0.014), gaming (F3, 1660 = 147.5, p < 0.01, p. η2 = 0.210), recreational internet usage (F3, 1655 = 410.0, p < 0.01, p. η2 = 0.426), and the total amount of recreational ST (F3, 1652 = 257.9, p < 0.01, p. η2 = 0.316) during the pre-study (c.f. Table 4). Significant effects for sex were found for gaming (F1, 1660 = 123.4, p < 0.01, p. η2 = 0.069) and the total amount of recreational ST (F1, 1652 = 21.8, p < 0.01, p. η2 = 0.013). Significant interactions between age and sex for gaming (F3, 1660 = 52.4, p < 0.01, p. η2 = 0.086) and the total amount of recreational ST (F3, 1652 = 12.3, p < 0.01, p. η2 = 0.022) indicate that differences between the sexes increase with age (c.f. Table 4).

Table 4 Recreational screen time usage before and during the COVID-19 lockdown in Germany (MoMo Study).

A main effect of the lockdown is significant for watching television (F1, 1667 = 248.8, p < 0.01, p. η2 = 0.130), gaming (F1, 1654 = 209.5, p < 0.01, p. η2 = 0.112), recreational internet usage (F1, 1646 = 149.9, p < 0.01, p. η2 = 0.083), and the total amount of recreational ST (F1, 1676 = 494.7, p < 0.01, p. η2 = 0.228). TV watching increased by 21.2 min, gaming increased by 21.5 min, recreational internet usage increased by 18.5 min, and the total amount of recreational ST increased by 61.2 min per day. An interaction between the lockdown and the participants’ age was found for internet usage (F3, 1646 = 4.9, p < 0.01, p. η2 = 0.009), gaming (F3, 1654 = 4.9, p < 0.01, p. η2 = 0.009), and the total amount of recreational ST (F3, 1676 = 5.2, p < 0.01, p. η2 = 0.009). Interaction effects between the lockdown and sex were only found for gaming (F3, 1654 = 20.9, p < 0.01, p. η²= 0.012). This translates into a 17.5% overall decrease in adherence to the recreational ST guideline during the lockdown with a substantially larger decrease for participants aged 14–17 years with − 18.4% compared to 4- to 5-year-olds with − 4.1%.

Discussion

Due to consecutive tracking of the PA, fitness, and health of children and adolescents in Germany since 2003, the MoMo study had the opportunity to rely on longitudinal PA data from a representative national cohort directly before and during the COVID-19 pandemic.

Our results show a decline in SA among boys and girls of all age groups paralleled by an increase in HA and recreational ST. In summary, the negative effects of the lockdown were stronger pronounced among adolescence, which showed a larger decline of SA and a lower increase in HA compared to younger children. A decline in SA is in line with other studies that tracked PA during the COVID-19 lockdown by questionnaires in Canada24,26, China20, Spain27, as well as by step counts in Italy23 and Canada22. In contrast to SA, the adherence to the PA guidelines and total PA increased among children and adolescents in Germany, which is in line with a study from Belgium28 but in contrast to studies from other countries20,21,22,23,24,26,27. The different behaviors of children and adolescents among countries may be related to different context factors such as different policy restrictions and the number of COVID-19 infections among countries that directly affected behavior. For example, during the lockdown in China, outdoor exercises were not allowed29, whereas Belgium had only mild restrictions. On the other hand, we assume that differences may be caused by methodological issues of tracking PA. For example, the questionnaire we used to track PA differentiated between a multitude of settings and activities and therefore we were able to analyze and contrast shifts among different types of PA and different settings.

In our sample, the increase in guideline adherence, which stands in contrast to the 28.5 min decline in organized SA, was not only initiated by an increase in nonorganized SA of 17.7 min per day but ultimately achieved by a 36.2 min increase in daily HA. Data from the US confirm that nonorganized PA and outdoor play were highly relevant during the COVID-19 pandemic, especially among younger children30. We found a change in total daily PA from 142.2 min pre to 167.8 min peri the lockdown in our study. In contrast, the study among 6- to 17-year-olds from Shanghai reported a change in total daily PA from 77.1 min pre to 15.0 min peri the lockdown20. PA behavior is a multi-dimensional construct with fluid settings. The different reactions to the pandemic all over the world showed that many children, adolescents, and adults can compensate for the elimination of settings within weeks. Nevertheless, being able to go outdoors safely with rules of social distancing and contact to at least one known person was the most striking difference in the execution of lockdowns between countries and seems crucial in maintaining sufficient levels of PA among children and adolescents.

Interestingly, an increase in nonorganized sports was not limited to those who were already doing sports before the lockdown in our study. 30.2% of those who had reported no SA before the lockdown engaged in nonorganized sports during the lockdown whereas only 60.3% of those who had engaged in SA in sports clubs before the lockdown transferred their organized to nonorganized SA. Within-person analyses pre to peri the lockdown showed that the mean correlation coefficients were substantially lower for nonorganized sports (r = 0.13, p < 0.01) compared to HA (r = 0.43; p < 0.01), days active (r = 0.41; p < 0.01), or recreational ST (r = 0.69; p < 0.01). These results are supported by a cross-sectional study with 13,515 adults from Belgium28. The data from Belgium shows a general increase in exercise frequencies, but exercise response to the lockdown differed between active and nonactive people before the lockdown: Of those who had exercised at least once a week before the lockdown, 23% reported less and 36% reported more exercising during the lockdown. In contrast, 58% of those who had exercised less than once a week before the lockdown reported more exercising during the lockdown28. Most likely, a more pronounced focus on a healthy lifestyle during the pandemic triggered this behavior in countries where policy restrictions allowed exercising. We also analyzed the distribution of PA and ST among a multitude of socioeconomic variables and found a slightly smaller impact of the socioeconomic status on PA and ST peri compared to pre lockdown. This may be explained by the fact that children and adolescents from families with lower socioeconomic status engage less often in organized and more often in nonorganized SA compared to those from households with a higher socioeconomic status11. The Gini coefficient31, which has recently been used to describe inequalities among the PA distribution between countries32, decreased from 0.80 to 0.70 for SA and from 0.47 to 0.39 for recreational ST but increased from 0.35 to 0.40 for HA among children and adolescents during the lockdown in Germany. A decrease in the Gini coefficient for SA and ST can be interpreted as a step towards a more equally distributed amount of SA and ST among children and adolescents as entry barriers to organized SA played no role and the demand for a healthy lifestyle was high during the lockdown. We can derive from this that countries and policies need to enable access to nonorganized PA to all children and adolescents during potential future lockdowns. Especially for adolescents, internet interventions from sports clubs are one potential option but scientists should also focus on upcoming affordable virtual and augmented-reality solutions to enable comprehensive PA opportunities for children and adolescents from all social classes, especially in urban areas. In reaction to the drastic decrease in PA among children and adolescents in China20, authors from the Shanghai University of Sport recommended exercising at home but also mentioned the danger of prolonged stays at home which can increase behaviors that lead to inactivity and contribute to anxiety and depression29. In the context of the studies from other countries mentioned before, results speak for the fact that the current technical possibilities are not adequate to comprehensively maintain sufficient levels of PA at home. Until there are virtual options for PA that satisfy the needs of users to an extent that they are comparably motivational and continual to analog forms of PA, policies should focus on providing safe natural space for nonorganized outdoor activities in addition to organized offers.

The finding that children and adolescents in Germany spent more active time peri than pre lockdown may be explained by the simple fact that they had more recreational time to do so, but also theoretically by self-determination theory33 and a more pronounced focus on health. Studies show that boys get most of their moderate-to-vigorous PA at school during recess and non-structured times34. During non-structured days, children and adolescents can choose PA behaviors that allow them to develop mastery, skills, and competence and can satisfy the need that they are in control of their behavior which leads to more motivation for PA34.

The increase in recreational ST among children and adolescents in Germany is in line with data about leisure screen time in Spain27 and China20. The study from Spain found an increase in ST between 132 (3–5-year-olds) and 198 (13–16-year-olds) minutes per day and a significant increase in overall sleep time among the 13–16-year-olds of 36 minutes per day during strict COVID-19 confinement. The Chinese study shows an increase in daily recreational ST among 6- to 17-year-olds from 24.3 to 64.3 min and an increase in daily total ST from 87.1 to 334.3 min. Adding nonrecreational screen media usage to our data, we find an increase from 146.1 to 237.5 min in total ST pre to peri the lockdown and an increase from 215.1 to 338.7 min in daily total media usage (including reading and listening to music). Home confinement restricted opportunities for children in China more than in Germany, and the fact that, as of reports by free journalists35, homeschooling started much earlier in China (March 2, 2020) than in Germany (May, 4, 2020) explains the pronounced increase in total ST in China. The numerically larger increase in ST with increasing age we found is supported by a German study that interviewed more than 8000 parents of children aged 3–15 years during the lockdown and found an increase of 38% (kindergarten) to 72% (secondary education) among recreational ST36. An increase in ST paralleled by an increase in PA among children and adolescents in Germany during the COVID-19 lockdown adds a piece to the puzzle of the relationship between PA and ST. Although it may be against common understanding at first glance that PA and ST are mutually exclusive in youth’s recreational time, a meta-analysis of 163 studies about the associations between sedentary behavior and physical activity in children and adolescents found a global correlation of only r = 0.11 between PA and ST37. The authors stated that the activities do not behave as functional opposites and substitute each other only marginally. Cluster analyses of the MoMo baseline sample confirmed that there are a multitude of different behavioral patterns concerning PA and recreational ST including children and adolescents with very large amounts of PA and ST and some that do not report any PA but also report low amounts of ST at the same time38,39. Other studies support the idea of ST and physical inactivity being different risk factors for an unhealthy lifestyle40,41,42. In the cluster-randomized, controlled trial “Switch-Off 4 Healthy Minds”, the authors found that a successful reduction of ST did not lead to a meaningful increase in PA among adolescents43.

Despite the comprehensive approach of tracking PA in Germany within the MoMo study, there are some limitations to this study. First, all our results are based on self-reports. Our questionnaire has been tailored to the different PA settings in Germany with a higher focus on recall bias compared to the relatively short and unspecific, yet economical, GPAQ44, which has been used for example in the Chinese study20. We also use device-based measures (Actigraph GT3X) to validate and augment our PA data in MoMo, but decided that it is not ethically justifiable to use them on a large sample during the lockdown. Device-based studies of PA during the lockdown are scarce and the little data that have been published so far rely on nonrepresentative ad-hoc samples, for example, children with congenital heart disease22 or already active people45. The largest sources of published device-based measured PA peri the lockdown are country-stratified data from Garmin wearables45 and a smartphone app46. The Garmin data show that different activities such as walking or outdoor and indoor cycling changed differently among countries, with most of them increasing45. The study which analyzed step counts from a smartphone app confirmed substantial differences between countries but reported decreases in step counts within 30 days of the pandemic from 6.9% in Sweden to 48.7% in Italy with a mean decrease of 27.3%46. Second, as it is a natural experiment, there is no control group and we can only assume that the lockdown was causal for the changes in PA and ST behavior. Since a full representative MoMo study takes 2 years to be completed, the mean age peri exceeded the mean age pre by almost exactly 1 year (Table 5). Since studies show that especially nonorganized PA declines during maturation in humans9,16,47,48 as well as in most nonhuman species49, this may have led to a small underestimation of the observed increase in PA in our study.

Table 5 Sample characteristics.

The weather was untypically warm in April 2020 in Germany. A mean temperature of 10.4 °C (9.6 °C in 2019) and on average 292.4 sunshine hours (227.9 in 2019) were measured across Germany in April, 202050,51. Warmer temperatures are associated with more PA and less ST in mild climates52. We also analyzed our data for seasonal effects. When considering only those MoMo participants who were tested in April 2019, the effects on PA and recreational ST were stable. Nonorganized sports increased by 15.9 min per day, HA by 46.2 min per day, recreational ST by 49.5 min per day, and WHO guideline compliance increased from 17.6 to 33.7%.

Lastly, the representativeness of our longitudinal pre-peri sample is limited because of the unforeseen COVID-19 outbreak during the collection of the representative pre-study sample. However, 120 out of 167 initial sample points across Germany were reached during the pre-study. Since the survey design includes a circle concept which ensures that sample points with different environmental contexts are tested during different months of the year, the reduction in representativeness because of missing sample points can be considered as small. The main effects of the lockdown remained stable after stratifying the sample by potential influencing socioeconomic factors such as housing situation, region within Germany, socioeconomic status, and the number of siblings.

What we can conclude from this natural experiment is that in some individuals the insufficient levels of PA are context-driven (e.g. too much forced sitting during school, homework, and other organized sedentary activities) and will vanish, once they regain autonomy over their everyday life. It is striking that in countries with suitable circumstances like in Belgium28, people found their way to PA during the lockdown. Phases with high alertness and focus on health may be a chance to positively interact with people's preventive behavior.

The fact that some children and adolescents did not engage in PA peri the lockdown and that the decline in SA is more pronounced in older age groups is alarming. Among European countries, there is a weak agreement that total PA among children and adolescents declined during the 1980/1990s, however comparable data with high standards regarding the methodology is missing among studies from that time47. This trend is followed by a slight increase in PA and a substantial increase in ST during the 2000s in Germany16,53,54 and most European countries48,55, leading to the stagnation of total PA with a shift from nonorganized to organized settings during the 2010s11. The fact that the recommended 60 min of daily moderate to vigorous PA nearly doubled among children and adolescents during the COVID-19 lockdown after having been stable for two decades is striking and needs to be analyzed further from a scientific yet political point of view.

The special circumstances during the COVID-19 lockdown also told us that PA and recreational ST behavior do not act as functional opposites and may decrease or increase concurrently43. Although there are cases where youth show very high levels of recreational ST, sometimes even diagnosed as gaming disorder, which can lead to an almost complete denial of PA56,57, the majority of studies among healthy or representative samples report a weak relationship between PA and ST or other forms of media usage among children and adolescents37,38,39,40,41,42 and speak for the fact that issues among both behaviors need to be addressed separately.

Methods

We obtained self-reported data from 1717 participants at two measurement points before (pre) and during (peri) the COVID-19 lockdown in Germany to examine the influence of the lockdown on PA and ST of children and adolescents aged 4–17 years pre. The STROBE statement58 guided the reporting of this study.

Procedures

The data were obtained within the framework of the MoMo study59. The study follows a cohort sequence design, which means that in addition to a longitudinal observation of the MoMo participants, a new representative sample of children and adolescents living in Germany is recruited at each follow-up. The baseline data was collected from 2003 to 2006, Wave 1 was conducted between 2009 and 2012, and Wave 2 between 2015 and 201759. Wave 3 started in August 2018 and was planned to be finished in June 2020, but had to be interrupted in March 2020 because of the COVID-19 lockdown in Germany. During the strictest time of the lockdown (20/04/2020–01/05/2020), we asked every participant of Wave 3 (pre-study) to answer our questionnaire again (peri-study) to track the direct changes in behavior (c.f. Fig. 2).

Figure 2
figure2

Timeline of events and survey context during the COVID-19 lockdown in Germany.

The study was conducted in accordance with the Declaration of Helsinki. For MoMo, ethics approval was obtained by the Charité Universitätsmedizin Berlin ethics committee, by the University of Konstanz, and the ethics committee of the Karlsruhe Institute of Technology. The Federal Commissioner for Data Protection and Freedom of Information was informed about the study and approved it.

For the pre-study, parents and children were invited to examination rooms at central locations in the proximity of their homes in the 167 cities and municipalities in which the study was conducted. Parents gave their written consent for minors and the presence of a legal guardian was mandatory under the age of 15. Questionnaires were filled out on-site by the participants on laptops (pre) or online (peri). Participation in the study was voluntary and every participant received a gift worth 20 €. The participants or their custodians were informed about the contents of the study and about data protection and gave their written consent. During the COVID lockdown in Germany, the participants were contacted via email and were asked to answer the peri-questions online.

Participants

The MoMo participants for Wave 3, respectively the pre-study, were selected based on a nationwide multi-stage sampling approach with two evaluation levels60 to maximize representativeness. First, a systematic sample of 167 primary sampling units was selected from an inventory of German communities stratified according to the classification system that measures the level of urbanization and geographic distribution61. The probability of any community being picked was proportional to the number of inhabitants younger than 18 years of age in that community. Second, based on the official registers of local residents, an age-stratified sample of randomly selected children and adolescents was drawn. 2722 MoMo Wave 3 participants (preliminary response 25.2%) were contacted for the peri-study and data from 1711 participants were gathered. Twenty-three e-mails could not be delivered because of incorrect addresses, and a total longitudinal response of 63.6% was achieved.

Table 5 shows the characteristics of the longitudinal sample and the ages pre and peri the lockdown.

Measures

The pre-lockdown data were derived via questionnaires (PA and ST) and interviews (socioeconomic data) on the pursuant screening site. For children under the age of 11 years, parents filled in the questionnaires together with the child. During the peri-study, the same questions about PA and ST were asked via an online version of the questionnaire except for the questions about organized PA which was shut down and forbidden by governmental law. We also changed each instance of time mentioned in the description of the questions during the peri-study to “during the Corona lockdown”.

Physical activity

The MoMo PA Questionnaire (MoMo-PAQ) was used to assess PA via self-reported SA and HA in different settings (sports clubs, leisure time, and school)62. The MoMo-PAQ consists of 28 items and measures frequency, duration, type, intensity, and setting of SA and HA. The data obtained with the MoMo-PAQ are sufficiently reliable and valid (test–retest reliability: ICC ≥ 0.68)62. SA at school was assessed by two items about the frequency (times per week) of 45-min classes in curricular and extracurricular sports activities which are multiplied by a factor of 8.5/12 to correct for vacations. SA in sports clubs was assessed by three items which could be answered up to four times: type of sports club activity, duration (minutes per week), and time throughout the year (months per year). Minutes were then multiplied by months per year divided by twelve to control for periodic effects of SA. Nonorganized leisure-time SA was assessed in the same way by three items which could be answered for up to four types of sports: type, duration, and time throughout the year. These items were combined in an index that reflects the daily minutes with organized (school and sports clubs) and nonorganized SA. Types of sports that do not lead to an increase in energy expenditure using large skeletal muscles (for example esports) were not defined as SA according to the definition of PA1, and minutes spent were multiplied with zero. Nonorganized playing outside, gardening, and housework were each assessed separately by two 8-scaled items about days per week and minutes a day in which the participants pursued the activity (“On how many days do you normally play outside/garden/work in the household during a week?”, “How long do you on average work/play on one of those days?”). Walking and cycling were assessed by one item each about the daily distance participants travel by walking or cycling62.

We also asked the participants on how many days they are active for more than 60 min with moderate to vigorous intensity to reproduce the WHO PA guideline: “Over a typical or usual week (peri: “during the Corona lockdown”), on how many days are you physically active for a total of at least 60 min per day?”63.

Recreational screen time

ST was measured via self-reported screen-time behaviors which are commonly used to report ST in youth and which have similar directions with health outcomes as direct measures of sedentary behavior3. Participants were asked to report the time spent watching television (TV), playing games on any device (Gaming), and using the internet for recreational use (Internet) separately for weekdays and weekends using an 7-point scale including (almost) never, 15 min per day, 30 min per day, 1 h per day, 2 h per day, 3 h per day, and 4 h per day64. An index reflecting weekdays and weekend days at a 5:2 ratio was then calculated for each activity.

Sociodemographic variables

Sociodemographic variables were assessed within the pre-study, including age, sex, and a multitude of socioenvironmental and socioeconomic variables. A detailed description of the MoMo survey instruments can be found elsewhere65.

Statistics

All statistical tests were conducted using IBM SPSS 25 (IBM Corporation, Armonk, NY). Statistically significant (two-sided) differences pre and peri were determined via ANOVA for repeated measurements where the effect of time represents the lockdown effect and 95% confidence intervals for differences of units and proportions66, as well as effect sizes Cohen's d for pre-to-peri differences in the form of \(d = \frac{{{\text{|Diff|}}}}{{{\upsigma }\left( {{\text{Diff}}} \right)}}\) were reported. Means and standard deviations were reported for PA in different settings. Means of difference and 95% CIs were reported for overall SA, HA, and ST.

Data availability

The datasets generated and analyzed during the current study are not publicly available due to the strict ethical standards required by the Federal Office for the Protection of Data with which study investigators are obliged to comply but are available from the corresponding author on reasonable request.

References

  1. 1.

    Caspersen, C. J., Powell, K. E. & Christenson, G. M. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep. 100, 126–131 (1985).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Janssen, I. & LeBlanc, A. G. Systematic review of the health benefits of physical activity and fitness in school-aged children and youth. Int. J. Behav. Nutr. Phys. Act. 7, 40 (2010).

    Article  Google Scholar 

  3. 3.

    Tremblay, M. S. et al. Systematic review of sedentary behaviour and health indicators in school-aged children and youth. Int. J. Behav. Nutr. Phys. Act. 8, 98 (2011).

    Article  Google Scholar 

  4. 4.

    Ekelund, U. et al. Does physical activity attenuate, or even eliminate, the detrimental association of sitting time with mortality? A harmonised meta-analysis of data from more than 1 million men and women. Lancet 388, 1302–1310. https://doi.org/10.1016/S0140-6736(16)30370-1 (2016).

    Article  PubMed  Google Scholar 

  5. 5.

    Warburton, D. E. R. & Bredin, S. S. D. Health benefits of physical activity: a systematic review of current systematic reviews. Curr. Opin. Cardiol. 32, 541–556. https://doi.org/10.1097/HCO.0000000000000437 (2017).

    Article  PubMed  Google Scholar 

  6. 6.

    Poitras, V. J. et al. Systematic review of the relationships between objectively measured physical activity and health indicators in school-aged children and youth. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Metab. 41, S197-239. https://doi.org/10.1139/apnm-2015-0663 (2016).

    Article  Google Scholar 

  7. 7.

    Piercy, K. L. et al. The physical activity guidelines for Americans. JAMA 320, 2020–2028. https://doi.org/10.1001/jama.2018.14854 (2018).

    Article  PubMed  Google Scholar 

  8. 8.

    World Health Organization. WHO guidelines on physical activity and sedentary behaviour. https://apps.who.int/iris/handle/10665/336656 (2020).

  9. 9.

    Tremblay, M. S. et al. Canadian 24-hour movement guidelines for children and youth: an integration of physical activity, sedentary behaviour, and sleep. Appl. Physiol. Nutr. Metab. Physiol. Appl. Nutr. Metab. 41, S311–S327. https://doi.org/10.1139/apnm-2016-0151 (2016).

    Article  Google Scholar 

  10. 10.

    Barlow, S. E. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics 120(Suppl 4), S164–S192. https://doi.org/10.1542/peds.2007-2329C (2007).

    Article  PubMed  Google Scholar 

  11. 11.

    Schmidt, S. C. E. et al. The physical activity of children and adolescents in Germany 2003–2017: The MoMo-study. PLoS ONE 15, e0236117. https://doi.org/10.1371/journal.pone.0236117 (2020).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Press and Information Office of the Federal Government. Agreement: Guidelines to Slow the Spread of the Coronavirus (Press and Information Office of the Federal Government, Berlin, 2020).

    Google Scholar 

  13. 13.

    Press and Information Office of the Federal Government. Meeting of the Chancellor Angela Merkel with the Heads of Government of the German Federal States on 22 March 2020 (Press and Information Office of the Federal Government, Berlin, 2020).

    Google Scholar 

  14. 14.

    Press and Information Office of the Federal Government. Telephone Conference Between the Federal Chancellor and the Heads of Government of the Länder on 15 April 2020. Restrictions to Public Life in Order to Curb the Spread of the Covid-19 Epidemic (Press and Information Office of the Federal Government, Berlin, 2020).

    Google Scholar 

  15. 15.

    Brazendale, K. et al. Understanding differences between summer vs. school obesogenic behaviors of children: the structured days hypothesis. Int. J. Behav. Nutr. Phys. Act. 14, 100. https://doi.org/10.1186/s12966-017-0555-2 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Schmidt, S. C. E., Henn, A., Albrecht, C. & Woll, A. Physical activity of german children and adolescents 2003–2012: the MoMo-study. Int. J. Environ. Res. Public Health 14, 1375. https://doi.org/10.3390/ijerph14111375 (2017).

    Article  PubMed Central  Google Scholar 

  17. 17.

    Rundle, A. G., Park, Y., Herbstman, J. B., Kinsey, E. W. & Wang, Y. C. COVID-19-related school closings and risk of weight gain among children. Obesity 28, 1008–1009. https://doi.org/10.1002/oby.22813 (2020).

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Hall, G., Laddu, D. R., Phillips, S. A., Lavie, C. J. & Arena, R. A tale of two pandemics: How will COVID-19 and global trends in physical inactivity and sedentary behavior affect one another?. Prog. Cardiovasc. Dis. https://doi.org/10.1016/j.pcad.2020.04.005 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Fegert, J. M., Vitiello, B., Plener, P. L. & Clemens, V. Challenges and burden of the Coronavirus 2019 (COVID-19) pandemic for child and adolescent mental health: a narrative review to highlight clinical and research needs in the acute phase and the long return to normality. Child Adolesc. Psychiatry Ment. Health 14, 20. https://doi.org/10.1186/s13034-020-00329-3 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Xiang, M., Zhang, Z. & Kuwahara, K. Impact of COVID-19 pandemic on children and adolescents’ lifestyle behavior larger than expected. Prog. Cardiovasc. Dis. https://doi.org/10.1016/j.pcad.2020.04.013 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Zenic, N. et al. Levels and changes of physical activity in adolescents during the COVID-19 pandemic: contextualizing urban vs. rural living environment. Appl. Sci. 10, 3997. https://doi.org/10.3390/app10113997 (2020).

    CAS  Article  Google Scholar 

  22. 22.

    Hemphill, N. M., Kuan, M. T. & Harris, K. C. Reduced physical activity during COVID-19 pandemic in children with congenital heart disease. Can. J. Cardiol. https://doi.org/10.1016/j.cjca.2020.04.038 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Pietrobelli, A. et al. Effects of COVID-19 lockdown on lifestyle behaviors in children with obesity living in Verona, Italy: a longitudinal study. Obesity https://doi.org/10.1002/oby.22861 (2020).

    Article  PubMed  Google Scholar 

  24. 24.

    Guerrero, M. D. et al. Canadian children’s and youth’s adherence to the 24-h movement guidelines during the COVID-19 pandemic: a decision tree analysis. J. Sport Health Sci. https://doi.org/10.1016/j.jshs.2020.06.005 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Barnes, J. D. et al. Results from Canada’s 2018 report card on physical activity for children and youth. J. Phys. Act. Health 15, 328–330. https://doi.org/10.1123/jpah.2018-0454 (2018).

    Article  Google Scholar 

  26. 26.

    Moore, S. A. et al. Impact of the COVID-19 virus outbreak on movement and play behaviours of Canadian children and youth: a national survey. Int. J. Behav. Nutr. Phys. Act. 17, 85. https://doi.org/10.1186/s12966-020-00987-8 (2020).

    ADS  Article  PubMed  PubMed Central  Google Scholar 

  27. 27.

    López-Bueno, R. et al. Health-related behaviors among school-aged children and adolescents during the Spanish Covid-19 confinement. Front. Pediatr. 8, 573 (2020).

    Article  Google Scholar 

  28. 28.

    Constandt, B. et al. Exercising in times of lockdown: an analysis of the impact of COVID-19 on levels and patterns of exercise among adults in Belgium. Int. J. Environ. Res. Public Health https://doi.org/10.3390/ijerph17114144 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Chen, P. et al. Wuhan coronavirus (2019-nCoV): the need to maintain regular physical activity while taking precautions. J. Sport Health Sci. 9(103–104), 2020. https://doi.org/10.1016/j.jshs.2020.02.001 (2020).

    Article  Google Scholar 

  30. 30.

    Dunton, G., Do, B. & Wang, S. D. Early effects of the COVID-19 pandemic on physical activity and sedentary behavior in U.S. children. Camb. Open Engage https://doi.org/10.33774/coe-2020-q6pz0 (2020).

    Article  Google Scholar 

  31. 31.

    Atkinson, A. B. On the measurement of inequality. J. Econ. Theory 2, 244–263 (1970).

    MathSciNet  Article  Google Scholar 

  32. 32.

    Althoff, T. et al. Large-scale physical activity data reveal worldwide activity inequality. Nature 547, 336–339. https://doi.org/10.1038/nature23018 (2017).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Deci, E. L. & Ryan, R. M. Self-determination theory. In Theories of Social Psychology (ed. van Lange, P. A.) 416–437 (Sage, Los Angeles, 2012).

    Google Scholar 

  34. 34.

    Bailey, D. P. et al. Accelerometry-assessed sedentary behaviour and physical activity levels during the segmented school day in 10–14-year-old children: the HAPPY study. Eur J. Pediatr. 171, 1805–1813. https://doi.org/10.1007/s00431-012-1827-0 (2012).

    Article  PubMed  Google Scholar 

  35. 35.

    Justl, S. Homeschooling in China: Between Silence and Boycott. https://www.wuv.de/agenturen/homeschooling_in_china_zwischen_stille_und_boykott (2020).

  36. 36.

    Langmeyer, A., Guglhör-Rudan, A., Naab, T., Urlen, M. & Winklhofer, U. Childhood in Times of Corona. First Results on the Changed Everyday Life and the Well-Being of Children. https://www.dji.de/themen/familie/kindsein-in-zeiten-von-corona-studienergebnisse.html (2020).

  37. 37.

    Pearson, N., Braithwaite, R. E., Biddle, S. J. H., van Sluijs, E. M. F. & Atkin, A. J. Associations between sedentary behaviour and physical activity in children and adolescents: a meta-analysis. RObes. Rev. Off. J. Int. Assoc. Study Obes. 15, 666–675. https://doi.org/10.1111/obr.12188 (2014).

    CAS  Article  Google Scholar 

  38. 38.

    Spengler, S., Mess, F., Mewes, N., Mensink, G. B. M. & Woll, A. A cluster-analytic approach towards multidimensional health-related behaviors in adolescents: the MoMo-study. BMC Public Health 12, 1128. https://doi.org/10.1186/1471-2458-12-1128 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Spengler, S., Mess, F. & Woll, A. Do media use and physical activity compete in adolescents? Results of the MoMo study. PLoS ONE 10, e0142544. https://doi.org/10.1371/journal.pone.0142544 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Feldman, D. E., Barnett, T., Shrier, I., Rossignol, M. & Abenhaim, L. Is physical activity differentially associated with different types of sedentary pursuits?. Arch. Pediatr. Adolesc. Med. 157, 797–802. https://doi.org/10.1001/archpedi.157.8.797 (2003).

    Article  PubMed  Google Scholar 

  41. 41.

    Gebremariam, M. K. et al. Are screen-based sedentary behaviors longitudinally associated with dietary behaviors and leisure-time physical activity in the transition into adolescence?. Int. J. Behav. Nutr. Phys. Act. 10, 9. https://doi.org/10.1186/1479-5868-10-9 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Melkevik, O., Torsheim, T., Iannotti, R. J. & Wold, B. Is spending time in screen-based sedentary behaviors associated with less physical activity: a cross national investigation. Int. J. Behav. Nutr. Phys. Act. 7, 46. https://doi.org/10.1186/1479-5868-7-46 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Babic, M. J. et al. Intervention to reduce recreational screen-time in adolescents: Outcomes and mediators from the ‘Switch-Off 4 Healthy Minds’ (S4HM) cluster randomized controlled trial. Prev. Med. 91, 50–57. https://doi.org/10.1016/j.ypmed.2016.07.014 (2016).

    Article  PubMed  Google Scholar 

  44. 44.

    Armstrong, T. & Bull, F. Development of the World Health Organization global physical activity questionnaire (GPAQ). J. Public Health 14, 66–70. https://doi.org/10.1007/s10389-006-0024-x (2006).

    Article  Google Scholar 

  45. 45.

    Garmin. Can Fitness Find a Way? The Impact of the Global Pandemic on Human Activity: Part II. https://bit.ly/2XmxwFF (2020).

  46. 46.

    Tison, G. H. et al. Worldwide effect of COVID-19 on physical activity: a descriptive study. Ann. Intern. Med. https://doi.org/10.7326/M20-2665 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Armstrong, N. & Welsman, J. R. The physical activity patterns of European youth with reference to methods of assessment. Sports Med. (Auckland N.Z.) 36, 1067–1086. https://doi.org/10.2165/00007256-200636120-00005 (2006).

    Article  Google Scholar 

  48. 48.

    Aubert, S. et al. Global Matrix 3.0 physical activity report card grades for children and youth: results and analysis from 49 countries. J. Phys. Act. Health 15, 251–273. https://doi.org/10.1123/jpah.2018-0472 (2018).

    Article  Google Scholar 

  49. 49.

    Ingram, D. K. Age-related decline in physical activity: generalization to nonhumans. Med. Sci. Sports Exercise 32, 1623–1629. https://doi.org/10.1097/00005768-200009000-00016 (2000).

    CAS  Article  Google Scholar 

  50. 50.

    German Weather Service. Monthly Climate Status for Germany. April 2019. https://www.dwd.de/DE/leistungen/pbfb_verlag_monat_klimastatus/monat_klimastatus.html (2019).

  51. 51.

    German Weather Service. Monthly Climate Status for Germany. April 2020. https://www.dwd.de/DE/leistungen/pbfb_verlag_monat_klimastatus/monat_klimastatus.html (2020).

  52. 52.

    Lewis, L. K. et al. At the mercy of the gods: associations between weather, physical activity, and sedentary time in children. Pediatr. Exercise Sci. 28, 152–163. https://doi.org/10.1123/pes.2015-0076 (2016).

    Article  Google Scholar 

  53. 53.

    Bucksch, J., Inchley, J., Hamrik, Z., Finne, E. & Kolip, P. Trends in television time, non-gaming PC use and moderate-to-vigorous physical activity among German adolescents 2002–2010. BMC Public Health 14, 351. https://doi.org/10.1186/1471-2458-14-351 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  54. 54.

    Demetriou, Y. et al. Results from Germany’s 2018 report card on physical activity for children and youth. J. Phys. Act. Health 15, 363–365. https://doi.org/10.1123/jpah.2018-0538 (2018).

    Article  Google Scholar 

  55. 55.

    Bucksch, J. et al. International trends in adolescent screen-time behaviors from 2002 to 2010. J. Adolesc. Health Off. Publ. Soc. Adolesc. Med. 58, 417–425. https://doi.org/10.1016/j.jadohealth.2015.11.014 (2016).

    Article  Google Scholar 

  56. 56.

    Wichstrøm, L., Stenseng, F., Belsky, J., von Soest, T. & Hygen, B. W. Symptoms of internet gaming disorder in youth: predictors and comorbidity. J. Abnorm. Child Psychol. 47, 71–83. https://doi.org/10.1007/s10802-018-0422-x (2019).

    Article  PubMed  Google Scholar 

  57. 57.

    Saunders, J. B. et al. Gaming disorder: its delineation as an important condition for diagnosis, management, and prevention. J. Behav. Addict. 6, 271–279. https://doi.org/10.1556/2006.6.2017.039 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  58. 58.

    Vandenbroucke, J. P. et al. Strengthening the reporting of observational studies in epidemiology (STROBE): explanation and elaboration. PLoS Med. 4, e297. https://doi.org/10.1371/journal.pmed.0040297 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  59. 59.

    Woll, A., Albrecht, C. & Worth, A. Motorik-Module (MoMo)—the KiGGS wave 2 module to survey motor performance and physical activity. J. Health Monit. 2, 63–70. https://doi.org/10.17886/RKI-GBE-2017-110 (2017).

    Article  Google Scholar 

  60. 60.

    Kamtsiuris, P., Lange, M. & Schaffrath Rosario, A. German health interview and exhamination survey for children and adolescents (KiGGS): sample design, response and nonresponse analysis. Bundesgesundheitsblatt Gesundh. Gesundh. 50, 547–556. https://doi.org/10.1007/s00103-007-0215-9 (2007).

    CAS  Article  Google Scholar 

  61. 61.

    Kurth, B.-M. et al. The challenge of comprehensively mapping children’s health in a nation-wide health survey: design of the German KiGGS-Study. BMC Public Health 8, 196. https://doi.org/10.1186/1471-2458-8-196 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  62. 62.

    Jekauc, D., Wagner, M., Kahlert, D. & Woll, A. Reliability and validity of the MoMo-physical-activity-questionnaire for adolescents (MoMo-PAQ). Diagnostica 59, 100–111 (2013).

    Article  Google Scholar 

  63. 63.

    Prochaska, J. J., Sallis, J. F. & Long, B. A physical activity screening measure for use with adolescents in primary care. Arch. Pediatr. Adolesc. Med. 155, 554–559. https://doi.org/10.1001/archpedi.155.5.554 (2001).

    CAS  Article  PubMed  Google Scholar 

  64. 64.

    Mathers, M. et al. Electronic media use and adolescent health and well-being: cross-sectional community study. Acad. Pediatr. 9, 307–314. https://doi.org/10.1016/j.acap.2009.04.003 (2009).

    Article  PubMed  Google Scholar 

  65. 65.

    Lampert, T., Müters, S., Stolzenberg, H. & Kroll, L. E. Assessment of the Socio-Economic Status in the KiGGS-Study. Bundesgesundheitsblatt Gesundh. Gesundh. 57, 762–770 (2014).

    Article  Google Scholar 

  66. 66.

    Cumming, G. & Fidler, F. Confidence Intervals. J. Psychol. 217, 15–26. https://doi.org/10.1027/0044-3409.217.1.15 (2009).

    Article  Google Scholar 

Download references

Acknowledgements

MoMo is funded by the Federal Ministry of Education and Research (Funding Reference Number: 01ER1503) within the research program ´Long-term Studies` in public health research. We acknowledge support by Deutsche Forschungsgemeinschaft and the Open Access Publishing Fund of Karlsruhe Institute of Technology.

Funding

Open Access funding enabled and organized by Projekt DEAL.

Author information

Affiliations

Authors

Contributions

S.C.E.S. wrote the main manuscript text. S.C.E.S. and B.A. conducted the statistcal analyses and prepared the figures and tables. A.B., S.K., A.E. and C.M. collected the data and performed the study. C.N., D.O., A.Worth & A.Woll planed and supervised the study. All authors reviewed the manuscript.

Corresponding author

Correspondence to Steffen C. E. Schmidt.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Schmidt, S.C.E., Anedda, B., Burchartz, A. et al. Physical activity and screen time of children and adolescents before and during the COVID-19 lockdown in Germany: a natural experiment. Sci Rep 10, 21780 (2020). https://doi.org/10.1038/s41598-020-78438-4

Download citation

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing