Association of school social status with Covid pandemic related changes and post-pandemic rebounds of children’s physical fitness

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The present report includes new data from 2023 to examine whether there were post-pandemic rebounds in the negatively affected fitness components, and whether pandemic and potential rebound effects differed by school social status. Methods The EMOTIKON project annually tests the fitness of all third-graders in the Federal State of Brandenburg, Germany. Tests assess cardiorespiratory endurance (6-min-run), coordination (star-run), speed (20-m linear sprint), lower (powerLOW, standing long jump), and upper (powerUP, ball-push) limbs muscle power, and static balance (one-legged-stance). A total of 108,308 third-graders aged between 8 and 9.2 years from 444 schools were tested in the falls from 2016–2023. Linear mixed models, specified for a regression discontinuity design with random factors for child and school, tested pandemic effects at the first day of school in the school year 2020/21 (i.e., the critical date) and cohort trends before and after the pandemic onset. Results At the critical date, there were small negative pandemic effects in cardiorespiratory endurance, coordination, speed, and powerUP. Pandemic effects in speed and coordination were larger in schools with higher social status. Coordination and powerUP were characterized by a post-pandemic rebound, with slightly larger coordination rebounds for schools with higher social status. There was no evidence for rebounds of cardiorespiratory endurance and speed. Conclusions Absence of evidence for task-specific rebounds may indicate long-term consequences of pandemic-related movement restrictions. Especially children in schools with higher social burden may be in need of improved access to sports opportunities. Physical fitness primary school children regression discontinuity design linear mixed model socioeconomic background Figures Figure 1 Background Various studies have examined Covid-19-pandemic-related changes in children’s physical fitness [1–9]. In our recent study, we examined the physical fitness of third-graders tested between 2016 and 2022 and reported negative pandemic effects in three running tests. Here, we include new data from cohort 2023 to examine whether there were post-pandemic rebounds in the negatively affected fitness components, and whether pandemic and potential rebound effects differed by school social status. Using the EMOTIKON test battery [10], 98,510 third-graders aged between 8 and 9 years were tested between 2016 and 2022 in the German Federal State of Brandenburg [8]. A regression discontinuity design (RDD) [11,12], specified for a linear mixed model with random factors child and school, tested pandemic effects at the first day of school in school year 2020/21 and found small negative pandemic effects in the 6-min run, star-run coordination test, and 20-m sprint [8]. Similar results were reported in Berlin, Germany, where 68,996 third-graders from ten cohorts completed the German Motor Fitness Test [13] between school years 2011/12 and 2021/22. Children tested after the start of the pandemic exhibited lower performance in the 20-m sprint, side jumps, standing long jump and push-ups, relative to predicted performance taking into account secular trends, but better 6-min run and sit-up performance [7]. In the Federal State of Thuringia, Germany, 24,777 third-graders were tested between 2017 and 2022 using the same physical fitness tests as in Brandenburg [1]. In simple pre-post comparisons, children also exhibited lower performance after the pandemic onset in four out of six fitness tests. However, while there was some evidence for declining trends between 2020 and 2022, pandemic effects at the first school day in school year 2020/21 were not significant when adjusting for school-related differences in pandemic effects and secular trends. Some studies have suggested that the magnitude of Covid pandemic effects differed by socioeconomic background, but findings are mixed. In general, socioeconomic background is associated with children’s health and development [14,15] and can influence their physical activity [16,17] and fitness levels [7,9,18]. For instance, access to organized sports depends on financial resources and regional sports opportunities, and children are less likely to be in sports clubs if their parents have lower socioeconomic status [16,19]. In high-income countries, children of low socioeconomic background have a higher risk of obesity, as people with low socioeconomic status have limited access to healthy, more expensive food options and may be compelled into adverse eating habits [20]. In Berlin, Germany, children from schools with lower socioeconomic background tended to exhibit higher BMIs [21] and poorer performance in tests assessing cardiorespiratory endurance, speed, coordination and muscular power/strength [7] compared to children from schools with higher socioeconomic background. Some researchers reported that pandemic-related increases in BMI were larger in schools of low socioeconomic background [9,21], thus increasing social disparities. However, the opposite pattern of results was found in some studies regarding physical fitness test performance. In Berlin, children from schools with higher socioeconomic background exhibited larger pandemic-related declines in fitness [7]. Similar findings were reported in the German Federal States Brandenburg and Thuringia, were schools with a higher average fitness exhibited more pronounced pandemic effects [1,7,8]. In contrast to these results, Wessely et al. [9] reported larger decreases in 6-min run performance for schools with higher social burden. In the Federal State of Brandenburg, pandemic-related changes in children’s physical fitness have not yet been analyzed with reference to schools’ social structure. Further, while there are many studies on pandemic-related changes in children’s fitness, it is not yet clear how children’s fitness has developed after the pandemic and whether potential rebound effects differ by socioeconomic status. Until 2022, there was not much evidence for post-pandemic rebounds of cardiorespiratory endurance and speed in the Federal State of Brandenburg [8]. A reason for the absence of rebound effects may be that third-graders in cohorts 2020, 2021, and 2022 all experienced pandemic-related lockdowns and school closures in third, second, or first grade, respectively, and were not able to compensate this loss of structured exercise. However, cohort 2023 was the first cohort that did not experience strict pandemic-related lockdowns in their school time (i.e., third-graders of cohort 2023 were enrolled to school in fall of 2021), and this cohort may thus exhibit better physical fitness relative to the previous years. The goal of the present paper was thus to examine whether (1) physical fitness and (2) pandemic effects differed by schools’ social structure, (3) whether negatively affected physical fitness components have recovered after the pandemic, and (4) whether potential rebound effects differed by social structure. Based on previous studies reporting lower physical fitness for children in schools or regions of lower socioeconomic background exhibited lower physical fitness [7,9,22] we expected lower performance in tests of cardiorespiratory endurance, coordination, speed, and lower limbs muscle power in schools with lower social status. As prior studies indicated more pronounced pandemic effects for “fitter” schools [1,7,8], we expected larger negative pandemic effects for schools with a higher social status. After the pandemic, movement restrictions were lifted and access to school sports and sports clubs was restored. If there is evidence for post-pandemic rebound effects, potential rebounds may thus have been larger in schools with higher social status, located in more affluent areas in which children likely have easier access to organized sports clubs. Secondary analyses tested whether previously reported effects of age [23] on children’s physical fitness are moderated by schools’ social status. Previous research has shown that third-graders in “fitter” schools exhibit larger age-related fitness trends within the ninth year of life [23]. Fühner et al. suggested that fitter schools may be located in more affluent areas and be attended by active children with greater access to sports opportunities promoting larger age gains, or that they may conduct more effective physical education classes and extracurricular school sports that drive larger age-related development. If higher school social status is associated with better average physical fitness, higher social status may also be associated with larger age-related development in physical fitness in the ninth year of life. Methods Experimental approach . In the Federal State of Brandenburg, Germany, the EMOTIKON project annually tests the physical fitness of all third graders (www.uni-potsdam.de/en/emotikon/). The project is mandated and approved by the Ministry of Education Youth, and Sport of the Federal State of Brandenburg, Germany and is obligatory for all public primary schools [24]. The physical fitness tests are conducted between August and December by physical education teachers. Before test administration, parents receive written information on the physical fitness tests to be conducted and on data processing regulations; written parental consent is not required due to the obligatory nature of the assessments. Researchers received the data completely anonymized from the Ministry of Education Youth, and Sport of the Federal State of Brandenburg, Germany. No personally identifiable information on the children was available to the researchers at any point. Population . We used data from cohorts 2016 to 2022 that were analyzed and published previously [8,23], and added new data from children who were tested in the fall of 2023. Main analyses focused on third-graders who had been enrolled to school according to the legal key date and were aged between 8.0 and 9.2 years. Analyses for children with delayed school enrollment aged between 9 and 10 years in third grade (older-than-keyage children, OTK) are reported in the OSF repository. The two groups are analyzed separately because cross-sectional physical fitness development in third grade is qualitatively different for keyage and OTK children [23,25]. School-specific social index was provided by the Ministry of Education Youth, and Sport of the Federal State of Brandenburg, Germany, with the goal of distributing school budget according to schools’ social burden and structural disadvantage. School social index was computed based on (1) social welfare rate (German: SGB-II) weighted by student residential commune (for independent cities: district rates), (2) proportion of students with non-German primary language, and (3) proportion of students with special educational needs [26]. We refer to schools as having “high social status” when they fall into the category of low social burden (and vice versa) to maintain the traditional polarity with socioeconomic status and improve clarity of the text. Based on quartiles of the weighted composite score computed from the three indicators, schools were categorized into four groups of “school social status”. Category 1 included schools with the highest social status, category 4 included schools with the lowest social status. Schools’ social index categories are freely available online [26]. For analysis, we used the four-category social index. Physical fitness tests . Details on test administration are reported in previous studies [1,8,23]. Cardiorespiratory endurance was tested by the 6-min run. The dependent variable was distance traveled in meters. Coordination was tested using the star-run test, in which children had to memorize and complete a star-shaped parkour as fast as possible using different movement forms (running forward/backward, sidesteps to the right/left). The dependent variable was duration measured in seconds, which was transformed to meters/second for analysis. Speed was tested using the 20-m linear sprint. Again, the dependent variable was duration measured in seconds, which was transformed to meters/second for analysis. Lower limbs muscle power (powerLOW) was tested by the standing long jump, with the dependent variable distance measured in centimeters. Upper limbs muscle power (powerUP) was assessed by the ball-push test, where children had to push a 1-kg medicine ball from a standing position as far as possible. Pushing distance was measured in meters, to the nearest 10 centimeters. Static balance was tested using the one-legged stance test with eyes closed, with the dependent variable duration measured in seconds (logarithmic transformation for analysis). Statistics. For data preprocessing, we used the tidyverse packages [27] in R version 4.2.3 [28], and the R Studio IDE [29]. We fit Linear Mixed Models (LMMs) using the MixedModels.jl [30] and MixedModelsMakie.jl [31] packages in Julia (version 1.10) [32]. Preprocessing of data was adapted from previous studies [23,33]. According to a Box-Cox distributional analysis [34], transformation of test sores of the star-run and the 20-m sprint to meters/seconds (reciprocal transformation multiplied by running distance) brought model residuals in line with a normal distribution. Test scores of the one-legged stance test were log-transformed. Data selection for data from cohorts 2016 – 2022 is documented in the previous report [8]. For data from 2023, we followed the same procedure. We first computed z-scores separately for each test and for boys and girls and excluded test scores outside of a ± 3 SD range (193 test scores were excluded). For the one-legged stance test assessing static balance, we did not exclude scores outside of the ± 3 SD range, since for this test, the whole range of possible test scores with a maximum of 60 seconds indicated valid performance [8,33]. In a second step, we recomputed z-scores for all data using test means and SDs of keyage children analyzed in the previous report (i.e., cohorts 2016 – 2022) [8]. This was done to obtain the same z-scores for data from cohorts 2016 – 2022 as in the previously published analysis [8]. We only kept data from schools with available social index (31,239 test scores from 5494 children in 75 schools were excluded). We ended up with 628,399 test scores from 108,308 children in 444 schools. Table 1 provides an overview of the sample characteristics. A more detailed sample description including test means and SDs in original metric is provided in the Supplements. Table 1 . Sample description Cohorts N children (% girls) N test scores Age [years] M (SD) N schools 2016 – 2019 51,796 (51%) 300,778 8.61 (0.28) 435 2020 – 2022 41,798 (51%) 242,073 8.56 (0.28) 436 2023 14,714 (52%) 85,548 8.61 (0.28) 432 Total 108,308 (51%) 628,399 8.59 (0.28) 444 Physical fitness tests were treated as six levels of the factor “physical fitness component” (i.e, cardiorespiratory endurance, coordination, speed, powerLOW, powerUP, and static balance). Physical fitness test contrasts were adopted from previous reports [1,35]. Five contrasts compared (1) cardiorespiratory e ndurance vs. c oordination, s peed and power L OW (i.e., cardiorespiratory endurance vs. tests of acceleration, E_CSL), (2) c oordination vs. s peed and power L OW (C_SL), (3) s peed vs. power L OW (S_L), (4) cardiorespiratory e ndurance, c oordination, s peed and power L OW vs. power U P (ECSL_U), and (5) cardiorespiratory e ndurance, c oordination, s peed and power L OW vs. b alance (ECSL_B). These contrasts were motivated by the fact that the first four fitness components are positively correlated, whereas correlations of powerUP and balance with the other four fitness components are lower [8,23]. Moreover, boys tend to outperform girls in five physical fitness components except for static balance, where girls outperform boys [1,8]. For school-specific four-level factor “social index” we specified a Helmert contrast comparing (1) the mean of index categories 1, 2, and 3 against category 4 (lowest social status), (2), the mean of index categories 1 and 2 against category 3, and (4) the index category 1 against index category 2. The Covid factor was dummy coded, with the pre-pandemic cohorts (i.e., 2016 – 2019) as the reference category coded as “0”, and cohorts 2020 – 2023 coded as “1”. For the factor Gender, we specified a sequential difference contrast with positive estimates indicating better performance of boys. A regression discontinuity design [11,12] tested Covid pandemic effects at the first day of school in school year 2020/21 (i.e., August 10 in the Federal State of Brandenburg, Germany) and secular trends (linear, quadratic) before and after this critical date. Test date was centered at the critical date, and age was centered at 8.5 years. The RDD was specified for a LMM with random factors child ( N = 108,308) and school ( N = 444). Details on parsimonious model selection are reported in script keyage_lmm_16_23.qmd in the OSF repository. We started with a complex LMM with fixed effects of Covid, school social index, age (linear), gender, and linear and quadratic test date trends (i.e., cohort trends) that were nested under the Covid factor, with all terms nested under the six levels of ‘physical fitness component’. In this model, social index interacted with Covid, test date, and age. For the random factor child, we included variance components (VCs) and correlation parameters (CPs) of physical fitness component contrasts, and for the random factor school, we included VCs and CPs of physical fitness component contrasts, Covid, test date trends (linear, quadratic), age, and gender effects. To obtain a parsimonious LMM that was supported by the data without overparameterization [36], we reduced the complexity of the fixed and random effect structure (details reported in the OSF repository). The final LMM included the fixed effects reported above, with school social index interacting with Covid, linear cohort trends before and after Covid onset, quadratic cohort trends after the pandemic onset, and with age. For the random factor child, we included VCs and CPs of physical fitness component contrasts. For the random factor school, the LMM included VCs of physical fitness component contrasts, Covid nested under the levels of physical fitness component, and age (linear), and CPs for all VCs except for age. Following earlier practice [1,8,23], |z-values| ≥ 2.0 were interpreted as statistically significant. Results Figure 1 shows mean test performance by physical fitness component and cohort (2016 – 2023) by school social index category. LMM-based inferential fixed effect estimates with standard errors and z-values are reported in Tables 2 and 3; VCs and CPs related to the random effects child and school are presented in Table 4. The LMM estimated cohort trends nested under the Covid factor (i.e., separate linear and quadratic cohort trends before and after the critical date). Main effects of school social status on physical fitness . In line with our hypothesis, and as depicted in figure 1 and reported in table 2, children in schools with higher social status exhibited better performances in the 6-min run (cardiorespiratory endurance, SI123_4: b = 0.166, z = 3.68; SI12_3: b = 0.145, z = 3.03), star-run (coordination, SI123_4: b = 0.114, z = 2.27), 20m-sprint (speed, SI123_4: b = 0.196, z = 4.36; SI1_2: b = 0.115, z = 2.08), and standing long jump (powerLOW, SI123_4: b = 0.142, z = 3.92; SI12_3: b = 0.095, z = 2.47; SI1_2: b = 0.179, z = 4.04) compared to schools with lower social status. An additional result was that schools of social index category 3 exhibited better average one-legged-stance performance (static balance) than schools with index category 1 and 2 (SI12_3: b = -0.132, z = -2.80). Table 2 . Fixed effect estimates, standard errors (SE) and z-values of the linear mixed model for Covid pandemic effects, cohort trends, school social index and interactions of school social index with Covid pandemic and cohort effects Estimate (b) SE z-value (Intercept) 0.032 0.016 1.98 Physical fitness component contrasts E_CSL -0.024 0.025 -0.96 C_SL 0.116 0.027 4.33 S_L 0.058 0.027 2.18 ECSL_U 0.035 0.025 1.42 ECSL_B -0.015 0.030 -0.50 Cardiorespiratory endurance (6-min run) SI123_4 0.166 0.045 3.68 SI12_3 0.145 0.048 3.03 SI1_2 0.056 0.056 1.01 Pre-covid td1 0.023 0.021 1.09 Pre-covid td1 x SI123_4 0.029 0.009 3.30 Pre-covid td1 x SI12_3 0.020 0.009 2.13 Pre-covid td1 x SI1_2 0.032 0.010 3.10 Pre-covid td2 0.005 0.004 1.21 Covid @ critical date -0.054 0.027 -2.04 Covid x SI123_4 -0.061 0.045 -1.35 Covid x SI12_3 -0.088 0.048 -1.84 Covid x SI1_2 -0.058 0.055 -1.05 Post-covid td1 -0.043 0.013 -3.25 Post-covid td1 x SI123_4 0.045 0.031 1.44 Post-covid td1 x SI12_3 0.022 0.033 0.67 Post-covid td1 x SI1_2 0.129 0.037 3.50 Post-covid td2 0.009 0.004 2.46 Post-covid td2 x SI123_4 -0.009 0.009 -1.02 Post-covid td2 x SI12_3 -0.004 0.010 -0.37 Post-covid td2 x SI1_2 -0.042 0.011 -3.99 Coordination (star-run) SI123_4 0.114 0.050 2.27 SI12_3 -0.011 0.053 -0.21 SI1_2 0.063 0.062 1.02 Pre-covid td1 0.106 0.021 5.04 Pre-covid td1 x SI123_4 0.005 0.009 0.55 Pre-covid td1 x SI12_3 -0.007 0.009 -0.74 Pre-covid td1 x SI1_2 0.019 0.011 1.77 Pre-covid td2 0.024 0.005 5.39 Covid @ critical date -0.189 0.030 -6.26 Covid x SI123_4 -0.144 0.056 -2.60 Covid x SI12_3 -0.054 0.059 -0.91 Covid x SI1_2 -0.034 0.068 -0.50 Post-covid td1 -0.062 0.014 -4.62 Post-covid td1 x SI123_4 0.067 0.032 2.12 Post-covid td1 x SI12_3 0.037 0.034 1.10 Post-covid td1 x SI1_2 0.003 0.037 0.09 Post-covid td2 0.024 0.004 6.22 Post-covid td2 x SI123_4 -0.005 0.009 -0.58 Post-covid td2 x SI12_3 0.007 0.010 0.71 Post-covid td2 x SI1_2 0.001 0.011 0.12 Speed (20m sprint) SI123_4 0.196 0.045 4.36 SI12_3 0.094 0.048 1.98 SI1_2 0.115 0.055 2.08 Pre-covid td1 0.043 0.021 2.02 Pre-covid td1 x SI123_4 0.031 0.009 3.54 Pre-covid td1 x SI12_3 0.015 0.009 1.63 Pre-covid td1 x SI1_2 0.042 0.011 3.98 Pre-covid td2 0.005 0.005 1.03 Covid @ critical date -0.087 0.028 -3.07 Covid x SI123_4 -0.080 0.0496 -1.62 Covid x SI12_3 -0.139 0.053 -2.64 Covid x SI1_2 -0.175 0.061 -2.88 Post-covid td1 -0.010 0.013 -0.72 Post-covid td1 x SI123_4 -0.016 0.031 -0.52 Post-covid td1 x SI12_3 0.051 0.033 1.52 Post-covid td1 x SI1_2 0.003 0.037 0.08 Post-covid td2 0.002 0.004 0.59 Post-covid td2 x SI123_4 0.009 0.009 1.03 Post-covid td2 x SI12_3 -0.010 0.010 -1.03 Post-covid td2 x SI1_2 0.005 0.011 0.46 PowerLOW (standing long jump) SI123_4 0.142 0.036 3.92 SI12_3 0.095 0.039 2.47 SI1_2 0.179 0.044 4.04 Pre-covid td1 0.058 0.022 2.71 Pre-covid td1 x SI123_4 -0.001 0.009 -0.05 Pre-covid td1 x SI12_3 -0.006 0.010 -0.66 Pre-covid td1 x SI1_2 0.053 0.011 4.92 Pre-covid td2 0.016 0.005 3.40 Covid @ critical date 0.021 0.026 0.80 Covid x SI123_4 -0.025 0.041 -0.61 Covid x SI12_3 -0.003 0.044 -0.06 Covid x SI1_2 -0.079 0.049 -1.60 Post-covid td1 -0.051 0.014 -3.67 Post-covid td1 x SI123_4 0.018 0.032 0.56 Post-covid td1 x SI12_3 -0.033 0.034 -0.96 Post-covid td1 x SI1_2 -0.020 0.038 -0.53 Post-covid td2 0.016 0.004 3.97 Post-covid td2 x SI123_4 -0.003 0.009 -0.27 Post-covid td2 x SI12_3 0.007 0.010 0.71 Post-covid td2 x SI1_2 -0.007 0.011 -0.65 PowerUP (ball-push test) SI123_4 0.055 0.036 1.51 SI12_3 0.070 0.039 1.82 SI1_2 0.046 0.044 1.03 Pre-covid td1 0.023 0.020 1.12 Pre-covid td1 x SI123_4 -0.006 0.009 -0.67 Pre-covid td1 x SI12_3 0.017 0.009 1.87 Pre-covid td1 x SI1_2 0.032 0.010 3.11 Pre-covid td2 0.010 0.004 2.31 Covid @ critical date -0.066 0.025 -2.59 Covid x SI123_4 -0.032 0.043 -0.75 Covid x SI12_3 -0.044 0.045 -0.97 Covid x SI1_2 -0.031 0.052 -0.60 Post-covid td1 -0.029 0.013 -2.25 Post-covid td1 x SI123_4 -0.023 0.030 -0.75 Post-covid td1 x SI12_3 0.014 0.032 0.42 Post-covid td1 x SI1_2 -0.044 0.036 -1.22 Post-covid td2 0.010 0.004 2.63 Post-covid td2 x SI123_4 0.002 0.009 0.26 Post-covid td2 x SI12_3 0.001 0.009 0.06 Post-covid td2 x SI1_2 0.008 0.010 0.78 Static balance (one-legged-stance) SI123_4 -0.021 0.045 -0.46 SI12_3 -0.133 0.047 -2.80 SI1_2 0.018 0.055 0.32 Pre-covid td1 0.101 0.021 4.76 Pre-covid td1 x SI123_4 -0.035 0.009 -3.94 Pre-covid td1 x SI12_3 -0.040 0.009 -4.20 Pre-covid td1 x SI1_2 0.002 0.011 0.17 Pre-covid td2 0.021 0.005 4.68 Covid @ critical date -0.047 0.030 -1.59 Covid x SI123_4 -0.055 0.053 -1.03 Covid x SI12_3 0.188 0.057 3.31 Covid x SI1_2 0.053 0.065 0.81 Post-covid td1 0.066 0.014 4.83 Post-covid td1 x SI123_4 0.093 0.032 2.93 Post-covid td1 x SI12_3 -0.093 0.034 -2.76 Post-covid td1 x SI1_2 0.089 0.037 2.38 Post-covid td2 -0.025 0.004 -6.38 Post-covid td2 x SI123_4 -0.015 0.009 -1.62 Post-covid td2 x SI12_3 0.021 0.010 2.20 Post-covid td2 x SI1_2 -0.026 0.011 -2.39 Note . E_CSL = cardiorespiratory endurance vs. coordination, speed and powerLOW, C_SL = coordination vs. speed and powerLOW, S_L = speed vs. powerLOW, ECSL_U = cardiorespiratory endurance, coordination, speed and powerLOW vs. powerUP, ECSL_B = cardiorespiratory endurance, coordination, speed and powerLOW vs. balance. School social index contrasts: SI123_4 = Mean of index categories 1, 2, and 3 vs. index category 4; SI12_3 = Mean of index categories 1 and 2 vs. index category 3, SI1_2 = Index category 1 vs. index category 2. Td1 = linear test date trend, td2 = quadratic test date trend. Covid @ critical date = Covid pandemic effect estimated at first school day in school year 2020/21. Bold = |z| > 2. Covid pandemic effects and cohort trends of physical fitness Cardiorespiratory endurance (6-min run). When tested at the first day of school in school year 2020/21 indicated by the vertical line in figure 1, there was a small negative Covid pandemic effect (b = -0.054, z = -2.04). There was no evidence that pandemic effects at the critical date differed between schools of different social index categories (|z| < 2). Although these interactions were not significant, figure 1 suggests that pandemic effects at the critical date were larger for school index categories 1 and 2 (high social status) compared to schools in categories 3 and 4 (lower social status). Does the inclusion of between-school differences in pandemic effects in the LMM’s random effect structure capture the variance also related to social index category? Indeed, when not including pandemic effect-related VCs and CPs in the random effect structure for school, fixed effect interactions between school social index and Covid pandemic effect became significant also for cardiorespiratory endurance (SI123_4: b = -0.080, z = -2.65; SI12_3: b = -0.084, z = -2.60), with schools of higher social status (i.e., categories 1, 2, and 3) exhibiting larger negative pandemic effects compared to schools with lower social status (i.e., category 4). Between 2016 and 2019, main effects of linear and quadratic cohort trends were not significant. After the start of the Covid-19 pandemic, 6-min run performance declined (b = -0.043, z = -3.25), followed by a plateau (b = 0.009, z = 2.46). Cohort trends differed by school social status. Schools with higher social status exhibited slightly more positive pre-pandemic linear secular trends than schools with lower social status (SI123_4: b = 0.029, z = 3.30; SI12_3: b = 0.020, z = 2.13; SI1_2: b = 0.032, z = 3.10). After the pandemic, schools with social index category 1 (highest social status) exhibited a less negative linear cohort trend (SI1_2: b = 0.129, z = 3.50) and a more negative quadratic cohort trend (SI1_2: b = -0.042, z = -3.99), compared to schools of index category 2. Coordination (star-run). As shown in figure 1, there was a small negative pandemic effect at the critical date (b = -0.189, z = -6.26). This pandemic effect was more pronounced in schools with higher social status compared to schools with low social status (SI123_4: b = -0.144, z = -2.60). Before the pandemic onset, coordination was characterized by a positive linear (b = 0.106, z = 5.04) and quadratic (b = 0.024, z = 5.39) cohort trend. After the pandemic onset, star-run test performance declined linearly (b = -0.062, z = -4.62), followed by a positive quadratic trend (b = 0.024, z = 6.22). Schools with high social status exhibited a more positive linear cohort trend after the pandemic onset compared to schools with low social status (SI123_4: b = 0.067, z = 2.12). Speed (20m sprint). At the first day of school in school year 2020/21 indicated by the vertical line in figure 1, 20m sprint performance was characterized by a small negative Covid pandemic effect (b = -0.087, z = -3.07). This pandemic effect was more pronounced for schools of higher social status (SI12_3: b = -0.139, z = -2.64; SI1_2: b = -0.175, z = -2.88). Prior to the pandemic, sprint performance slightly increased (linear cohort trend, b = 0.042, z = 2.02), with schools of higher social status exhibiting more positive linear cohort trends (SI123_4: b = 0.031, z = 3.54; SI1_2: b = 0.042, z = 3.98). After the pandemic onset, there was no evidence for significant linear of quadratic cohort trends (|z| < 2). PowerLOW (standing long jump). At the critical date, there was no evidence for a Covid-19 pandemic effect on standing long jump performance (|z| < 2). Between 2016 and 2019, standing long jump performance was characterized by a positive linear (b = 0.058, z = 2.71) and quadratic (b = 0.016, z = 3.40) cohort trend. The positive linear cohort trend was more pronounced for schools with index category 1 (highest social status) compared to schools of index category 2 (b = 0.053, z = 4.92). After the pandemic onset, standing long jump performance decreased linearly (b = -0.051, z = -3.67), followed by a positive quadratic trend (b = 0.016, z = 3.97). There was no evidence that these cohort trends differed significantly between school social index categories. PowerUP (ball-push test). Ball-push test performance was characterized by a small negative Covid pandemic effect when estimated at the first day of school in school year 2020/21 (b = -0.066, b = -2.59). There was no evidence for significant differences in this Covid pandemic effect between schools of different social index categories. Between 2016 and 2019, Ball-push test performance exhibited a small positive quadratic cohort trend (b = 0.010, z = 2.31). Between 2020 and 2023, ball-push test performance decreased linearly (b = -0.029, z = -2.25), followed by a rebound (i.e., positive quadratic trend, b = 0.010, z = 2.63; depicted in figure 1). Cohort trends largely did not differ between school social index categories. The only significant interaction between social index and cohort trend indicated that schools of social index category 1 exhibited a more positive linear cohort trend than schools of index category 2 (b = 0.031, z = 3.11). Balance (one-legged-stance test). There was no evidence for a significant main effect of the Covid pandemic on one-legged-stance test performance at the critical date (|z| < 2). However, schools with social index categories 1 and 2 exhibited a more positive pandemic effect than schools of index category 3 (b = 0.187, z = 3.31). Prior to the pandemic, one-legged-stance performance was characterized by a positive linear (b = 0.101, z = 4.76) and quadratic (b = 0.021, z = 4.68) cohort trend. Schools with lower social status exhibited more pronounced linear trends (SI123_4: b = -0.035, z = -3.94; S12_3: b = -0.039, z = -4.20). After the pandemic onset, performance initially increased linearly (0.066, z = 4.83), followed by a negative quadratic decline (b = -0.025, z = -6.38). During this period, the positive linear cohort trend was more pronounced in schools of index categories 1, 2, and 3, relative to category 4 (SI123_4: b = 0.093, z = 2.93). Further, schools in index category 1 exhibited a slightly more pronounced secular balance trend between 2020 and 2023 compared to schools in index category 2, indicated by a larger positive linear cohort trend (S1_2: b = 0.088, z = 2.38) and more pronounced (i.e., more negative) quadratic decline (S1_2: b = -0.025, z = -2.39; see figure 1). Similarly, schools in index category 3 exhibited a more pronounced secular trend compared to schools in index categories 1 and 2, indicated by a larger positive linear cohort trend (S12_3: b = -0.093, z = -2.76) and stronger quadratic decline (S12_3: b = 0.021, z = 2.20). Age- and gender-related differences in physical fitness . Previously reported age and gender effects [1,23,33] were replicated and are shown in table 3. As hypothesized, age-related gains in five of six physical fitness tests were larger in schools with higher social status (social index categories 1 – 3) than in schools with low social status (index category 4). This applied to performance in the 6-min run (b = 0.100, z = 4.25), star-run (b = 0.072, z = 3.00), 20m sprint (b = 0.091, z = 3.79), standing long jump (b = 0.096, z = 3.91), and ball-push test (b = 0.067, z = 2.88). Further, schools with social index categories 1 and 2 exhibited larger age effects in the ball-push test than schools with index category 3 (b = 0.064, z = 2.65). Table 3 . Fixed effect estimates, standard errors (SE) and z-values of the linear mixed model for age and gender effects, as well as age by school social index interactions Estimate (b) SE z-value Cardiorespiratory endurance (6-min run) Age 0.081 0.010 7.98 SI123_4 x Age 0.101 0.024 4.25 SI12_3 x Age -0.001 0.025 -0.04 SI1_2 x Age 0.040 0.028 1.42 Gender 0.444 0.006 79.28 Coordination (star-run) Age 0.278 0.010 26.93 SI123_4 x Age 0.072 0.024 3.00 SI12_3 x Age 0.040 0.025 1.58 SI1_2 x Age 0.000 0.028 0.01 Gender 0.232 0.006 40.81 Speed (20m sprint) Age 0.207 0.010 20.08 SI123_4 x Age 0.091 0.024 3.79 SI12_3 x Age 0.045 0.025 1.76 SI1_2 x Age 0.046 0.028 1.64 Gender 0.305 0.006 53.77 PowerLOW (standing-long-jump) Age 0.213 0.011 20.22 SI123_4 x Age 0.096 0.025 3.91 SI12_3 x Age 0.007 0.026 0.27 SI1_2 x Age -0.009 0.029 -0.30 Gender 0.393 0.006 67.59 PowerUP (ball-push test) Age 0.521 0.010 52.42 SI123_4 x Age 0.067 0.023 2.88 SI12_3 x Age 0.065 0.025 2.65 SI1_2 x Age 0.047 0.027 1.72 Gender 0.666 0.006 121.64 Static balance (one-legged-stance) Age 0.148 0.010 14.27 SI123_4 x Age 0.034 0.024 1.42 SI12_3 x Age 0.013 0.026 0.50 SI1_2 x Age 0.017 0.028 0.59 Gender -0.241 0.006 -42.13 Age = linear age trend. School social index contrasts: SI123_4 = Mean of index categories 1, 2, and 3 vs. index category 4; SI12_3 = Mean of index categories 1 and 2 vs. index category 3, SI1_2 = Index category 1 vs. index category 2. Bold = |z| > 2. Table 4 shows variance components (VCs) and correlation parameters (CPs) of the LMM. VCs indicated that schools differed in their physical fitness, Covid pandemic effects, and age effects. Correlation parameters were in line with previously reported results [1,8], indicating that schools with better average physical fitness prior to the pandemic exhibited more pronounced negative Covid pandemic effects in the respective physical fitness components. As depicted in table 4, the Covid pandemic effect on cardiorespiratory endurance was more negative the better cardiorespiratory endurance was relative to coordination, speed, and powerLOW (CP: -0.42), the pandemic effect on coordination was more negative the better coordination was relative to speed and powerLOW (CP: -0.46), the pandemic effect on speed was more negative the better speed was relative to powerLOW (CP: -0.43), the pandemic effect on powerUP was more negative the better powerUP was relative to cardiorespiratory endurance, coordination, speed and powerLOW (ECSL_U, CP: +0.41), and the Covid pandemic effect on balance was more negative the higher balance was relative to cardiorespiratory endurance, coordination, speed and powerLOW (ECSL_B, CP: +0.37). A reparametrized LMM with physical fitness component levels instead of physical fitness component contrasts is provided in the OSF repository. Correlation parameters from this LMM were in line with the above reported findings for all six physical fitness components (CPs between -0.44 and -0.53). Table 4. Child- and school-related variance components and correlation parameters of the linear mixed model VC CP Covid @ crit. date Int E_CSL C_SL S_L ECSL_U ECSL_B E C S pL pU Child Int 0.297 E_CSL 0.325 -0.18 C_SL 0.307 -0.09 -0.01 S_L 0.256 -0.08 +0.07 +0.04 ECSL_U 0.467 +0.25 +0.20 -0.06 +0.10 ECSL_B 0.661 +0.29 -0.06 -0.06 +0.01 +0.21 School Int 0.041 E_CSL 0.117 -0.06 C_SL 0.144 +0.25 -0.12 S_L 0.120 +0.18 -0.16 -0.19 ECSL_U 0.091 +0.32 +0.06 +0.15 +0.07 ECSL_B 0.158 +0.19 +0.17 +0.00 +0.13 +0.31 Covid @ crit. date E 0.088 -0.23 -0.42 -0.04 -0.08 -0.20 -0.23 C 0.174 -0.31 +0.11 -0.46 +0.07 -0.12 -0.10 +0.13 S 0.123 -0.21 +0.03 +0.18 -0.43 -0.11 -0.12 +0.21 +0.16 pL 0.054 -0.29 +0.03 +0.05 +0.17 -0.15 -0.17 +0.07 +0.16 +0.21 pU 0.075 -0.23 +0.01 -0.02 -0.04 +0.41 +0.12 +0.07 +0.18 +0.11 +0.08 B 0.152 -0.18 +0.04 -0.04 -0.04 +0.02 +0.37 -0.11 +0.15 +0.02 +0.04 +0.03 Age <0.001 - - - - - - - - - - - Int = Intercept, E = cardiorespiratory endurance (i.e., 6-min run), C = coordination (i.e., star-run), S = speed (i.e., 20-m linear sprint), pL = lower limbs muscle power (i.e., powerLOW, standing long jump), pU = upper limbs muscle power (i.e., powerUP, ball-push test), B = static balance (i.e., one-legged-stance test). E_CSL = cardiorespiratory endurance vs. coordination, speed and powerLOW, C_SL = coordination vs. speed and powerLOW, S_L = speed vs. powerLOW, ECSL_U = cardiorespiratory endurance, coordination, speed and powerLOW vs. powerUP, ECSL_B = cardiorespiratory endurance, coordination, speed and powerLOW vs. balance. Covid @ crit. date = Covid pandemic effect estimated at first day of school in school year 2020/21. Age = linear age trend. VC = variance component, CP = correlation parameter. Theoretically relevant correlations are set in bold. LMM random factors: schools (444) and children (108,308), observations = 628,399. VC for Residual = 0.293. Exploratory analysis: Regional differences in physical fitness while adjusting for school social status Previous analyses of the EMOTIKON data as well as results from the school entry examination have shown regional physical fitness differences in the Federal State of Brandenburg. In the Federal State of Brandenburg, communes can be categorized either as close to Berlin (“Berliner Umland“) or far from Berlin (“weiterer Metropolenraum”) [37]. The Brandenburg area close to Berlin is strongly integrated with the metropolitan capital city, and exhibits a higher population density [37] and lower average socioeconomic deprivation than the largely rural area far from Berlin [38]. In the school entry examination, regions close to Berlin exhibit a lower percentage of overweight and obese children than regions far from Berlin [39]. Further, third-graders in communes close to Berlin tend to exhibit better 6-min run, 20m sprint, and standing long jump performance in the EMOTKON test compared to children in regions far from Berlin (details provided in the OSF repository). However, it is unclear whether these regional differences in physical fitness are explained by schools’ socio-structural composition (social welfare rate, migration background, special educational needs), or whether there are additional regional effects on physical fitness, for example linked to the proximity, accessibility (e.g., public transportation), and variety of sports clubs and quality of school sports facilities. In fact, children from areas in rural Brandenburg are less often in sports clubs than children in urban areas [40]. To test whether there are regional effects on physical fitness in addition to effects of school social structure, we conducted an LMM with the fixed effects reported above and the additional two-level factor “region” (close to vs. far from Berlin; details reported in the OSF repository) nested under each physical fitness component. Indeed, in this LMM adjusting for school social index, children in schools close to Berlin exhibited slightly better 6-min run (b = 0.074, z = 2.21) and standing long jump (b = 0.098, z = 3.88) performance compared to children far from Berlin. Thus, there is some evidence for region-related physical fitness differences independent of school social structure effects. Discussion We examined whether (1) physical fitness and (2) pandemic effects differed by schools’ social structure, (3) whether negatively affected physical fitness components have recovered after the pandemic, and (4) whether potential rebound effects differed by social structure. We used previously analyzed data from cohorts 2016–2022 [ 8 , 23 ] and added new fitness data from cohort 2023. Positive linear or quadratic secular trends during cohorts 2020–2023 were interpreted as evidence for post-pandemic rebound effects. As predicted, children from schools with lower social status tended to exhibit poorer 6-min run, star-run, 20m sprint, and standing long jump performance relative to children in schools with higher social status. When estimated at the first day of school in school year 2020/2021, there were small negative Covid pandemic effects in cardiorespiratory endurance, coordination, speed, and powerUP. These results were similar to the ones reported in our previous study that included data from cohorts 2016 to 2022 [ 8 ]. In the previous report, we also reported better average performance in tests assessing powerLOW and static balance after, compared to before the pandemic onset. However, this pattern of results was likely explained by secular trends independent of the Covid pandemic. In the present report, we adjusted for secular trends by using a regression discontinuity design to estimate pandemic effects at the first day of school in school year 2020/21. Pandemic effects and cohort trends differed by school social structure. First, schools with lower social status exhibited slightly more negative trends in cardiorespiratory endurance and speed prior to the pandemic. Second, in line with previous research indicating larger pandemic effects in “fitter” schools [ 1 , 8 ] and in schools with higher socioeconomic background [ 7 ], pandemic effects on the star-run and 20m sprint performance were slightly more pronounced in schools with higher social status. In the other negatively affected fitness components cardiorespiratory endurance and powerUP, there was no evidence for differences in pandemic effects across school index categories. As in previous reports [ 1 , 8 ], correlation parameters in the random effect structure indicated that schools with better average performances exhibited larger negative Covid pandemic effects in all six fitness components. In cardiorespiratory endurance, between-school differences in the pandemic effect estimated in the random effect structure accounted for differences in the pandemic effect by school social index. After an initial decline in performance at the start of the pandemic, coordination and powerUP rebounded, with a slightly larger coordination rebound in schools with high social status. Cardiorespiratory endurance and speed in 2023 remained at levels similar to the pandemic years. Other studies assessing children’s physical fitness development until 2022 reported mixed findings, with evidence for some rebounds after the pandemic [ 3 , 6 ]. In a large Slovenian study including over 41,000 children and adolescents tested yearly between 2019 and 2022, cardiorespiratory endurance, muscular fitness, speed, and neuromuscular and gross motor coordination declined from 2019 to 2020 but rebounded in all physical fitness components. These rebounds, however, were incomplete in most gender-BMI groups, with physical fitness remaining lower in 2022 compared to 2019 [ 6 ]. Similarly, Austrian elementary school children still exhibited lower cardiorespiratory endurance, agility and flexibility in 2022 compared to pre-pandemic cohorts [ 3 ]. PowerUP, however, was better in 2022 relative to pre-pandemic cohorts 2016–2019. Pandemic effects and incomplete rebounds may be associated with pandemic-related losses of sports opportunities, but potentially also with long COVID symptoms including respiratory symptoms and fatigue [ 41 , 42 ]. In the present study, larger pandemic effects and subsequent larger rebounds in schools with higher social status illustrate the importance of a cultural environment and infrastructure providing sports opportunities for children’s physical fitness. Further, in addition to effects of school social structure, there were small regional differences in cardiorespiratory endurance and powerLOW, with slightly poorer performances for children in areas far to Berlin. Access to sports and healthy nutrition should be enhanced in socioeconomically disadvantaged schools with low access to sports opportunities and lower physical fitness, especially in Brandenburg regions far from Berlin. As cardiorespiratory endurance and muscular fitness are closely linked to physical health [ 43 , 44 ] and well-being [ 45 ] in youth, children from socioeconomically disadvantaged areas likely are, through no fault of their own, at greater risk of adverse health outcomes. In fact, according to 18,773 voluntary parental reports of children’s body mass and height in EMOTIKON cohorts 2021, 2022 and 2023, around 18 percent of children in social index category 4 were overweight or obese, compared to 10 percent of children from school index category 1. As self-reported height and weight were only available from cohort 2021 onwards, we were not able to estimate Covid pandemic effects on children’s body constitution. However, in Berlin, Germany, although physical fitness losses were more pronounced in schools with higher socioeconomic status [ 7 ], pandemic-related BMI increases were larger in schools of lower socioeconomic background [ 21 ]. An additional result of the present study was that schools with higher social status exhibited slightly larger developmental trends in the ninth year of life in all physical fitness components except for static balance. This was in line with a previous study, that reported larger developmental rates in “fitter” schools, suggesting that these schools may be located in more affluent areas, where children are more active and have easier access to sports opportunities, or that they provide higher-quality physical education lessons and school sports [ 23 ]. Conclusions Negative pandemic effects in coordination and speed were more pronounced in schools with higher social status. There were post-pandemic rebounds in coordination and powerUP, with slightly larger coordination rebounds for schools with higher social status. Differences in Covid pandemic and rebound effects between schools highlight the importance of children’s living environment for their physical fitness development. Enhancing healthy living environments by increasing sports opportunities and access to healthy food in disadvantaged schools and structurally deprived areas may help compensate physical fitness differences. Although pandemic effects were small, absence of evidence for rebounds in cardiorespiratory endurance and speed as of 2023 may indicate long-term consequences of pandemic-related movement restrictions. Regular assessments of children’s physical fitness are needed to examine how physical fitness develops throughout the next years. Abbreviations CP Correlation parameter LMM Linear mixed model RDD Regression discontinuity design VC Variance component Contrasts for six-level factor physical fitness component E vs. CSL Cardiorespiratory endurance vs. coordination, speed, powerLOW C vs. SL Coordination vs. speed and powerLOW S vs. L Speed vs. powerLOW ECSL vs. U Cardiorespiratory endurance, coordination, speed, powerLOW vs. powerUP ECSL vs. B Cardiorespiratory endurance, coordination, speed, powerLOW vs. balance Contrasts for four-level factor school social status SI123_4 Mean of categories 1, 2, and 3 vs. category 4 SI12_3 Mean of categories 1 and 2 vs. category 3 SI1_2 Category 1 vs. category 2 Declarations Ethics approval and consent to participate The EMOTIKON project is mandated and approved by the Ministry of Education, Youth and Sport of the Federal State of Brandenburg, Germany. According to the Brandenburg School Law, participation is mandatory for all public primary schools in the Federal State of Brandenburg, Germany [24]. Written consent to participate is not required. Research was conducted in accordance with the latest Declaration of Helsinki [46] and the Brandenburg School Law [24]. Consent for publication According to the Brandenburg School Law, participation is mandatory for children in all public primary schools in the Federal State of Brandenburg, Germany. Written consent for data processing or publication is not required. The authors of this study received the data completely anonymized from the Ministry of Education, Youth and Sport of the Federal State of Brandenburg, Germany. Details on the legal basis of data processing can be found in § 65 of the Brandenburg School Law [24]. Availability of material, data, and code Data as well as R and Julia scripts are available in the Open Science Framework (OSF) repository: https://osf.io/5273n/ Competing Interests Statement The authors declare that they have no competing interests. Authors’ contributions PT, RK, FA, FB, TW, and KG contributed to conception and design. KG, PT, and FA contributed to data collection. PT and RK analyzed data. PT wrote the first draft of the manuscript. All authors were involved in iterative revisions, provided final approval of the version to be published and agreed to be accountable for all aspects of the work. Funding The study was commissioned and supported by the Ministry of Education, Youth, and Sport of the Federal State Brandenburg, Germany. Paula Teich was supported by the Research Focus Cognitive Sciences at the University of Potsdam. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. 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Available from: https://doi.org/10.5281/zenodo.13174525 Alday P, Bates D. palday/MixedModelsMakie.jl: v0.3.24 [Internet]. Zenodo; 2023 [cited 2023 Jul 12]. Available from: https://zenodo.org/record/8125544 Bezanson J, Edelman A, Karpinski S, Shah VB. Julia: A Fresh Approach to Numerical Computing. SIAM Rev [Internet]. 2017 [cited 2022 May 14];59:65–98. Available from: https://epubs.siam.org/doi/10.1137/141000671 Teich P, Fühner T, Granacher U, Kliegl R. Physical fitness of primary school children differs depending on their timing of school enrollment. Sci Rep [Internet]. 2023 [cited 2023 May 31];13:1–16. Available from: https://www.nature.com/articles/s41598-023-35727-y Box GEP, Cox DR. An Analysis of Transformations. J R Stat Soc Ser B Methodol [Internet]. 1964 [cited 2022 Mar 18];26:211–52. Available from: https://www.jstor.org/stable/2984418 Teich P, Golle K, Kliegl R. Association between time of assessment within a school year and physical fitness of primary school children. 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Available from: https://gesundheitsplattform.brandenburg.de/#/SE/g14 Golle K, Granacher U, Hoffmann M, Wick D, Muehlbauer T. Effect of living area and sports club participation on physical fitness in children: a 4 year longitudinal study. BMC Public Health [Internet]. 2014 [cited 2022 May 24];14:499. Available from: https://doi.org/10.1186/1471-2458-14-499 Gross RS, Thaweethai T, Kleinman LC, Snowden JN, Rosenzweig EB, Milner JD, et al. Characterizing Long COVID in Children and Adolescents. JAMA [Internet]. 2024 [cited 2024 Aug 27]; Available from: https://doi.org/10.1001/jama.2024.12747 Zheng Y-B, Zeng N, Yuan K, Tian S-S, Yang Y-B, Gao N, et al. Prevalence and risk factor for long COVID in children and adolescents: A meta-analysis and systematic review. J Infect Public Health. 2023;16:660–72. García-Hermoso A, Ramírez-Campillo R, Izquierdo M. Is Muscular Fitness Associated with Future Health Benefits in Children and Adolescents? A Systematic Review and Meta-Analysis of Longitudinal Studies. Sports Med Auckl NZ. 2019;49:1079–94. García-Hermoso A, Ramírez-Vélez R, García-Alonso Y, Alonso-Martínez AM, Izquierdo M. Association of Cardiorespiratory Fitness Levels During Youth With Health Risk Later in Life: A Systematic Review and Meta-analysis. JAMA Pediatr. 2020;174:952–60. Bermejo-Cantarero A, Álvarez-Bueno C, Martínez-Vizcaino V, Redondo-Tébar A, Pozuelo-Carrascosa DP, Sánchez-López M. Relationship between both cardiorespiratory and muscular fitness and health-related quality of life in children and adolescents: a systematic review and meta-analysis of observational studies. Health Qual Life Outcomes [Internet]. 2021 [cited 2023 Jan 14];19:127. Available from: https://doi.org/10.1186/s12955-021-01766-0 World Medical Association. World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310:2191–4. Supplementary Files CovidreboundSupp.docx Cite Share Download PDF Status: Published Journal Publication published 23 Apr, 2025 Read the published version in Sports Medicine-Open → Version 1 posted Reviewers agreed at journal 25 Sep, 2024 Reviewers invited by journal 05 Sep, 2024 Editor invited by journal 04 Sep, 2024 Editor assigned by journal 30 Aug, 2024 First submitted to journal 29 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4997009","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":350283053,"identity":"8f367345-cdfa-4287-8062-6cbe944f9478","order_by":0,"name":"Paula Teich","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0001-7825-0761","institution":"University of Potsdam: Universitat Potsdam","correspondingAuthor":true,"prefix":"","firstName":"Paula","middleName":"","lastName":"Teich","suffix":""},{"id":350283054,"identity":"1691a7b8-0bdc-436a-94b9-d984b756a439","order_by":1,"name":"Fabian Arntz","email":"","orcid":"","institution":"University of Potsdam: Universitat Potsdam","correspondingAuthor":false,"prefix":"","firstName":"Fabian","middleName":"","lastName":"Arntz","suffix":""},{"id":350283055,"identity":"0dc67c0a-2f99-4c97-9d08-d8bf54b10d50","order_by":2,"name":"Toni Wöhrl","email":"","orcid":"","institution":"University Erfurt: Universitat Erfurt","correspondingAuthor":false,"prefix":"","firstName":"Toni","middleName":"","lastName":"Wöhrl","suffix":""},{"id":350283056,"identity":"97a2296a-91fb-4e03-9396-6efd9cbf5bbc","order_by":3,"name":"Florian Bähr","email":"","orcid":"","institution":"University Erfurt: Universitat Erfurt","correspondingAuthor":false,"prefix":"","firstName":"Florian","middleName":"","lastName":"Bähr","suffix":""},{"id":350283057,"identity":"3ead1edb-0c94-4281-98be-6784260a164d","order_by":4,"name":"Kathleen Golle","email":"","orcid":"","institution":"University of Potsdam: Universitat Potsdam","correspondingAuthor":false,"prefix":"","firstName":"Kathleen","middleName":"","lastName":"Golle","suffix":""},{"id":350283058,"identity":"ededdc81-6299-45ca-ab2b-38d7a6454188","order_by":5,"name":"Reinhold Kliegl","email":"","orcid":"","institution":"University of Potsdam: Universitat Potsdam","correspondingAuthor":false,"prefix":"","firstName":"Reinhold","middleName":"","lastName":"Kliegl","suffix":""}],"badges":[],"createdAt":"2024-08-29 10:45:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4997009/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4997009/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40798-025-00838-5","type":"published","date":"2025-04-23T15:58:26+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":67182340,"identity":"290ad5e1-dd39-4bfe-a518-5c8d98b5f9d0","added_by":"auto","created_at":"2024-10-22 06:36:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":292484,"visible":true,"origin":"","legend":"\u003cp\u003ePhysical fitness by fitness component, school social status, and cohort (means and 95% CIs). The vertical line marks the critical date (first day of school in school year 2020/21). Endurance = cardiorespiratory endurance (i.e., 6-min run), Coordination = star-run, Speed = 20-m linear sprint, PowerLOW = lower limbs muscle power (i.e., standing long jump), PowerUP = upper limbs muscle power (i.e., ball-push test), Balance = one-legged-stance with eyes closed. SI1_SI2 = school social index categories 1 and 2 (high social status), SI3 = school social index category 3, SI4 = school social index category 4 (lowest social status). For visual clarity, school social index categories 1 and 2 were combined. A figure depicting physical fitness for all four social index categories is provided in the supplements.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4997009/v1/c326c6edac7e409eecfebc8f.png"},{"id":81569912,"identity":"f6762f8a-4f80-4a8a-8c4a-2db7c35d0b5a","added_by":"auto","created_at":"2025-04-28 16:12:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1534497,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4997009/v1/48c42dde-95dd-4ede-8cd6-44b18c80f984.pdf"},{"id":67182341,"identity":"60085007-b0a9-46a4-8d5d-f68485a63144","added_by":"auto","created_at":"2024-10-22 06:36:54","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":646332,"visible":true,"origin":"","legend":"","description":"","filename":"CovidreboundSupp.docx","url":"https://assets-eu.researchsquare.com/files/rs-4997009/v1/f45b05014fe44efcf8f97618.docx"}],"financialInterests":"","formattedTitle":"Association of school social status with Covid pandemic related changes and post-pandemic rebounds of children’s physical fitness","fulltext":[{"header":"Background","content":"\u003cp\u003eVarious studies have examined Covid-19-pandemic-related changes in children\u0026rsquo;s physical fitness [1\u0026ndash;9]. In our recent study, we examined the physical fitness of third-graders tested between 2016 and 2022 and reported negative pandemic effects in three running tests. Here, we include new data from cohort 2023 to examine whether there were post-pandemic rebounds in the negatively affected fitness components, and whether pandemic and potential rebound effects differed by school social status.\u003c/p\u003e\n\u003cp\u003eUsing the EMOTIKON test battery [10], 98,510 third-graders aged between 8 and 9 years were tested between 2016 and 2022 in the German Federal State of Brandenburg [8]. A regression discontinuity design (RDD) [11,12], specified for a linear mixed model with random factors child and school, tested pandemic effects at the first day of school in school year 2020/21 and found small negative pandemic effects in the 6-min run, star-run coordination test, and 20-m sprint [8]. Similar results were reported in Berlin, Germany, where 68,996 third-graders from ten cohorts completed the German Motor Fitness Test [13] between school years 2011/12 and 2021/22. Children tested after the start of the pandemic exhibited lower performance in the 20-m sprint, side jumps, standing long jump and push-ups, relative to predicted performance taking into account secular trends, but better 6-min run and sit-up performance [7]. In the Federal State of Thuringia, Germany, 24,777 third-graders were tested between 2017 and 2022 using the same physical fitness tests as in Brandenburg [1]. In simple pre-post comparisons, children also exhibited lower performance after the pandemic onset in four out of six fitness tests. However, while there was some evidence for declining trends between 2020 and 2022, pandemic effects at the first school day in school year 2020/21 were not significant when adjusting for school-related differences in pandemic effects and secular trends.\u003c/p\u003e\n\n\u003cp\u003eSome studies have suggested that the magnitude of Covid pandemic effects differed by socioeconomic background, but findings are mixed. In general, socioeconomic background is associated with children\u0026rsquo;s health and development [14,15] and can influence their physical activity [16,17] and fitness levels [7,9,18]. For instance, access to organized sports depends on financial resources and regional sports opportunities, and children are less likely to be in sports clubs if their parents have lower socioeconomic status [16,19]. In high-income countries, children of low socioeconomic background have a higher risk of obesity, as people with low socioeconomic status have limited access to healthy, more expensive food options and may be compelled into adverse eating habits [20]. In Berlin, Germany, children from schools with lower socioeconomic background tended to exhibit higher BMIs [21] and poorer performance in tests assessing cardiorespiratory endurance, speed, coordination and muscular power/strength [7] compared to children from schools with higher socioeconomic background. \u003c/p\u003e\n\u003cp\u003eSome researchers reported that pandemic-related increases in BMI were larger in schools of low socioeconomic background [9,21], thus increasing social disparities. However, the opposite pattern of results was found in some studies regarding physical fitness test performance. In Berlin, children from schools with higher socioeconomic background exhibited larger pandemic-related declines in fitness [7]. Similar findings were reported in the German Federal States Brandenburg and Thuringia, were schools with a higher average fitness exhibited more pronounced pandemic effects [1,7,8]. In contrast to these results, Wessely et al. [9] reported larger decreases in 6-min run performance for schools with higher social burden. \u003c/p\u003e\n\n\u003cp\u003eIn the Federal State of Brandenburg, pandemic-related changes in children\u0026rsquo;s physical fitness have not yet been analyzed with reference to schools\u0026rsquo; social structure. Further, while there are many studies on pandemic-related changes in children\u0026rsquo;s fitness, it is not yet clear how children\u0026rsquo;s fitness has developed after the pandemic and whether potential rebound effects differ by socioeconomic status. Until 2022, there was not much evidence for post-pandemic rebounds of cardiorespiratory endurance and speed in the Federal State of Brandenburg [8]. A reason for the absence of rebound effects may be that third-graders in cohorts 2020, 2021, and 2022 all experienced pandemic-related lockdowns and school closures in third, second, or first grade, respectively, and were not able to compensate this loss of structured exercise. However, cohort 2023 was the first cohort that did not experience strict pandemic-related lockdowns in their school time (i.e., third-graders of cohort 2023 were enrolled to school in fall of 2021), and this cohort may thus exhibit better physical fitness relative to the previous years. The goal of the present paper was thus to examine whether (1) physical fitness and (2) pandemic effects differed by schools\u0026rsquo; social structure, (3) whether negatively affected physical fitness components have recovered after the pandemic, and (4) whether potential rebound effects differed by social structure.\u003c/p\u003e\n\n\u003cp\u003eBased on previous studies reporting lower physical fitness for children in schools or regions of lower socioeconomic background exhibited lower physical fitness [7,9,22] we expected lower performance in tests of cardiorespiratory endurance, coordination, speed, and lower limbs muscle power in schools with lower social status.\u003c/p\u003e\n\u003cp\u003eAs prior studies indicated more pronounced pandemic effects for \u0026ldquo;fitter\u0026rdquo; schools [1,7,8], we expected larger negative pandemic effects for schools with a higher social status. After the pandemic, movement restrictions were lifted and access to school sports and sports clubs was restored. If there is evidence for post-pandemic rebound effects, potential rebounds may thus have been larger in schools with higher social status, located in more affluent areas in which children likely have easier access to organized sports clubs.\u003c/p\u003e\n\n\u003cp\u003eSecondary analyses tested whether previously reported effects of age [23] on children\u0026rsquo;s physical fitness are moderated by schools\u0026rsquo; social status. Previous research has shown that third-graders in \u0026ldquo;fitter\u0026rdquo; schools exhibit larger age-related fitness trends within the ninth year of life [23]. F\u0026uuml;hner et al. suggested that fitter schools may be located in more affluent areas and be attended by active children with greater access to sports opportunities promoting larger age gains, or that they may conduct more effective physical education classes and extracurricular school sports that drive larger age-related development. If higher school social status is associated with better average physical fitness, higher social status may also be associated with larger age-related development in physical fitness in the ninth year of life.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eExperimental approach\u003c/em\u003e. In the Federal State of Brandenburg, Germany, the EMOTIKON project annually tests the physical fitness of all third graders (www.uni-potsdam.de/en/emotikon/). The project is mandated and approved by the Ministry of Education Youth, and Sport of the Federal State of Brandenburg, Germany and is obligatory for all public primary schools [24]. The physical fitness tests are conducted between August and December by physical education teachers. Before test administration, parents receive written information on the physical fitness tests to be conducted and on data processing regulations; written parental consent is not required due to the obligatory nature of the assessments. Researchers received the data completely anonymized from the Ministry of Education Youth, and Sport of the Federal State of Brandenburg, Germany. No personally identifiable information on the children was available to the researchers at any point.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePopulation\u003c/em\u003e. We used data from cohorts 2016 to 2022 that were analyzed and published previously [8,23], and added new data from children who were tested in the fall of 2023. Main analyses focused on third-graders who had been enrolled to school according to the legal key date and were aged between 8.0 and 9.2 years. Analyses for children with delayed school enrollment aged between 9 and 10 years in third grade (older-than-keyage children, OTK) are reported in the OSF repository. The two groups are analyzed separately because cross-sectional physical fitness development in third grade is qualitatively different for keyage and OTK children [23,25].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSchool-specific social index\u003c/em\u003e was provided by the Ministry of Education Youth, and Sport of the Federal State of Brandenburg, Germany, with the goal of distributing school budget according to schools\u0026rsquo; social burden and structural disadvantage. School social index was computed based on (1) social welfare rate (German: SGB-II) weighted by student residential commune (for independent cities: district rates), (2) proportion of students with non-German primary language, and (3) proportion of students with special educational needs [26]. We refer to schools as having \u0026ldquo;high social status\u0026rdquo; when they fall into the category of low social burden (and vice versa) to maintain the traditional polarity with socioeconomic status and improve clarity of the text. Based on quartiles of the weighted composite score computed from the three indicators, schools were categorized into four groups of \u0026ldquo;school social status\u0026rdquo;. Category 1 included schools with the highest social status, category 4 included schools with the lowest social status. Schools\u0026rsquo; social index categories are freely available online [26]. For analysis, we used the four-category social index.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePhysical fitness tests\u003c/em\u003e. Details on test administration are reported in previous studies [1,8,23]. \u003cem\u003eCardiorespiratory endurance\u003c/em\u003e was tested by the 6-min run. The dependent variable was distance traveled in meters. \u003cem\u003eCoordination\u003c/em\u003e was tested using the star-run test, in which children had to memorize and complete a star-shaped parkour as fast as possible using different movement forms (running forward/backward, sidesteps to the right/left). The dependent variable was duration measured in seconds, which was transformed to meters/second for analysis. \u003cem\u003eSpeed\u003c/em\u003e was tested using the 20-m linear sprint. Again, the dependent variable was duration measured in seconds, which was transformed to meters/second for analysis. \u003cem\u003eLower limbs muscle power\u003c/em\u003e (powerLOW) was tested by the standing long jump, with the dependent variable distance measured in centimeters. \u003cem\u003eUpper limbs muscle power\u003c/em\u003e (powerUP) was assessed by the ball-push test, where children had to push a 1-kg medicine ball from a standing position as far as possible. Pushing distance was measured in meters, to the nearest 10 centimeters. \u003cem\u003eStatic balance\u003c/em\u003e was tested using the one-legged stance test with eyes closed, with the dependent variable duration measured in seconds (logarithmic transformation for analysis).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistics.\u0026nbsp;\u003c/em\u003eFor data preprocessing, we used the tidyverse packages [27] in \u003cem\u003eR version 4.2.3\u0026nbsp;\u003c/em\u003e[28], and the \u003cem\u003eR Studio IDE\u003c/em\u003e [29]. We fit Linear Mixed Models (LMMs) using the \u003cem\u003eMixedModels.jl\u0026nbsp;\u003c/em\u003e[30] and \u003cem\u003eMixedModelsMakie.jl\u003c/em\u003e [31] packages in \u003cem\u003eJulia\u003c/em\u003e (version 1.10) [32].\u003c/p\u003e\n\u003cp\u003ePreprocessing of data was adapted from previous studies [23,33]. According to a Box-Cox distributional analysis [34], transformation of test sores of the star-run and the 20-m sprint to meters/seconds (reciprocal transformation multiplied by running distance) brought model residuals in line with a normal distribution. Test scores of the one-legged stance test were log-transformed.\u003c/p\u003e\n\u003cp\u003eData selection for data from cohorts 2016 \u0026ndash; 2022 is documented in the previous report [8]. For data from 2023, we followed the same procedure. We first computed z-scores separately for each test and for boys and girls and excluded test scores outside of a \u0026plusmn; 3 SD range (193 test scores were excluded). For the one-legged stance test assessing static balance, we did not exclude scores outside of the \u0026plusmn; 3 SD range, since for this test, the whole range of possible test scores with a maximum of 60 seconds indicated valid performance [8,33]. In a second step, we recomputed z-scores for all data using test means and SDs of keyage children analyzed in the previous report (i.e., cohorts 2016 \u0026ndash; 2022) [8]. This was done to obtain the same z-scores for data from cohorts 2016 \u0026ndash; 2022 as in the previously published analysis [8]. We only kept data from schools with available social index (31,239 test scores from 5494 children in 75 schools were excluded). We ended up with 628,399 test scores from 108,308 children in 444 schools. Table 1 provides an overview of the sample characteristics. A more detailed sample description including test means and SDs in original metric is provided in the Supplements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. Sample description\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"517\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.112%;\"\u003e\n \u003cp\u003e\u003cem\u003eCohorts\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5483%;\"\u003e\n \u003cp\u003e\u003cem\u003eN children\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e(% girls)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.4286%;\"\u003e\n \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003etest scores\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.3243%;\"\u003e\n \u003cp\u003e\u003cem\u003eAge [years]\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eM (SD)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.5869%;\"\u003e\n \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eschools\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.112%;\"\u003e\n \u003cp\u003e2016 \u0026ndash; 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5483%;\"\u003e\n \u003cp\u003e51,796 (51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.4286%;\"\u003e\n \u003cp\u003e300,778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.3243%;\"\u003e\n \u003cp\u003e8.61 (0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.5869%;\"\u003e\n \u003cp\u003e435\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.112%;\"\u003e\n \u003cp\u003e2020 \u0026ndash; 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5483%;\"\u003e\n \u003cp\u003e41,798 (51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.4286%;\"\u003e\n \u003cp\u003e242,073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.3243%;\"\u003e\n \u003cp\u003e8.56 (0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.5869%;\"\u003e\n \u003cp\u003e436\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.112%;\"\u003e\n \u003cp\u003e2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5483%;\"\u003e\n \u003cp\u003e14,714 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.4286%;\"\u003e\n \u003cp\u003e85,548\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.3243%;\"\u003e\n \u003cp\u003e8.61 (0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.5869%;\"\u003e\n \u003cp\u003e432\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.112%;\"\u003e\n \u003cp\u003e\u003cem\u003eTotal\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5483%;\"\u003e\n \u003cp\u003e108,308 (51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.4286%;\"\u003e\n \u003cp\u003e628,399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.3243%;\"\u003e\n \u003cp\u003e8.59 (0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.5869%;\"\u003e\n \u003cp\u003e444\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePhysical fitness tests were treated as six levels of the factor \u0026ldquo;physical fitness component\u0026rdquo; (i.e, cardiorespiratory endurance, coordination, speed, powerLOW, powerUP, and static balance). Physical fitness test contrasts were adopted from previous reports [1,35]. Five contrasts compared (1) cardiorespiratory \u003cstrong\u003ee\u003c/strong\u003endurance vs. \u003cstrong\u003ec\u003c/strong\u003eoordination, \u003cstrong\u003es\u003c/strong\u003epeed and power\u003cstrong\u003eL\u003c/strong\u003eOW (i.e., cardiorespiratory endurance vs. tests of acceleration, E_CSL), (2) \u003cstrong\u003ec\u003c/strong\u003eoordination vs. \u003cstrong\u003es\u003c/strong\u003epeed and power\u003cstrong\u003eL\u003c/strong\u003eOW (C_SL), (3) \u003cstrong\u003es\u003c/strong\u003epeed vs. power\u003cstrong\u003eL\u003c/strong\u003eOW (S_L), (4) cardiorespiratory \u003cstrong\u003ee\u003c/strong\u003endurance, \u003cstrong\u003ec\u003c/strong\u003eoordination, \u003cstrong\u003es\u003c/strong\u003epeed and power\u003cstrong\u003eL\u003c/strong\u003eOW vs. power\u003cstrong\u003eU\u003c/strong\u003eP (ECSL_U), and (5) cardiorespiratory \u003cstrong\u003ee\u003c/strong\u003endurance, \u003cstrong\u003ec\u003c/strong\u003eoordination, \u003cstrong\u003es\u003c/strong\u003epeed and power\u003cstrong\u003eL\u003c/strong\u003eOW vs. \u003cstrong\u003eb\u003c/strong\u003ealance (ECSL_B). These contrasts were motivated by the fact that the first four fitness components are positively correlated, whereas correlations of powerUP and balance with the other four fitness components are lower [8,23]. Moreover, boys tend to outperform girls in five physical fitness components except for static balance, where girls outperform boys [1,8].\u003c/p\u003e\n\u003cp\u003eFor school-specific four-level factor \u0026ldquo;social index\u0026rdquo; we specified a Helmert contrast comparing (1) the mean of index categories 1, 2, and 3 against category 4 (lowest social status), (2), the mean of index categories 1 and 2 against category 3, and (4) the index category 1 against index category 2.\u003c/p\u003e\n\u003cp\u003eThe Covid factor was dummy coded, with the pre-pandemic cohorts (i.e., 2016 \u0026ndash; 2019) as the reference category coded as \u0026ldquo;0\u0026rdquo;, and cohorts 2020 \u0026ndash; 2023 coded as \u0026ldquo;1\u0026rdquo;. For the factor Gender, we specified a sequential difference contrast with positive estimates indicating better performance of boys. A regression discontinuity design [11,12] tested Covid pandemic effects at the first day of school in school year 2020/21 (i.e., August 10 in the Federal State of Brandenburg, Germany) and secular trends (linear, quadratic) before and after this critical date. Test date was centered at the critical date, and age was centered at 8.5 years.\u003c/p\u003e\n\u003cp\u003eThe RDD was specified for a LMM with random factors child (\u003cem\u003eN\u003c/em\u003e = 108,308) and school (\u003cem\u003eN\u003c/em\u003e = 444). Details on parsimonious model selection are reported in script \u003cem\u003ekeyage_lmm_16_23.qmd\u003c/em\u003e in the OSF repository. We started with a complex LMM with fixed effects of Covid, school social index, age (linear), gender, and linear and quadratic test date trends (i.e., cohort trends) that were nested under the Covid factor, with all terms nested under the six levels of \u0026lsquo;physical fitness component\u0026rsquo;. In this model, social index interacted with Covid, test date, and age. For the random factor child, we included variance components (VCs) and correlation parameters (CPs) of physical fitness component contrasts, and for the random factor school, we included VCs and CPs of physical fitness component contrasts, Covid, test date trends (linear, quadratic), age, and gender effects. To obtain a parsimonious LMM that was supported by the data without overparameterization [36], we reduced the complexity of the fixed and random effect structure (details reported in the OSF repository). The final LMM included the fixed effects reported above, with school social index interacting with Covid, linear cohort trends before and after Covid onset, quadratic cohort trends after the pandemic onset, and with age. For the random factor child, we included VCs and CPs of physical fitness component contrasts. For the random factor school, the LMM included VCs of physical fitness component contrasts, Covid nested under the levels of physical fitness component, and age (linear), and CPs for all VCs except for age. Following earlier practice [1,8,23], |z-values| \u0026ge; 2.0 were interpreted as statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFigure 1 shows mean test performance by physical fitness component and cohort (2016 \u0026ndash; 2023) by school social index category. LMM-based inferential fixed effect estimates with standard errors and z-values are reported in Tables 2 and 3; VCs and CPs related to the random effects child and school are presented in Table 4. The LMM estimated cohort trends nested under the Covid factor (i.e., separate linear and quadratic cohort trends before and after the critical date).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMain effects of school social status on physical fitness\u003c/em\u003e. In line with our hypothesis, and as depicted in figure 1 and reported in table 2, children in schools with higher social status exhibited better performances in the 6-min run (cardiorespiratory endurance, SI123_4: b = 0.166, z = 3.68; SI12_3: b = 0.145, z = 3.03), star-run (coordination, SI123_4: b = 0.114, z = 2.27), 20m-sprint (speed, SI123_4: b = 0.196, z = 4.36; SI1_2: b = 0.115, z = 2.08), and standing long jump (powerLOW, SI123_4: b = 0.142, z = 3.92; SI12_3: b = 0.095, z = 2.47; SI1_2: b = 0.179, z = 4.04) compared to schools with lower social status. An additional result was that schools of social index category 3 exhibited better average one-legged-stance performance (static balance) than schools with index category 1 and 2 (SI12_3: b = -0.132, z = -2.80).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e. Fixed effect estimates, standard errors (SE) and z-values of the linear mixed model for Covid pandemic effects, cohort trends, school social index and interactions of school social index with Covid pandemic and cohort effects\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"78%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 24%;\"\u003e\n \u003cp\u003eEstimate (b)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13%;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13%;\"\u003e\n \u003cp\u003ez-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e(Intercept)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cem\u003ePhysical fitness component contrasts\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eE_CSL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eC_SL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.33\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eS_L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eECSL_U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eECSL_B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 73%;\"\u003e\n \u003cp\u003e\u003cem\u003eCardiorespiratory endurance (6-min run)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.68\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePre-covid td1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePre-covid td2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003eCovid @ critical date\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePost-covid td1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-3.25\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.50\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePost-covid td2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.46\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-3.99\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003eCoordination (star-run)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.27\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePre-covid td1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePre-covid td2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.39\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003eCovid @ critical date\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-6.26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePost-covid td1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-4.62\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePost-covid td2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003eSpeed (20m sprint)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.36\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.08\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePre-covid td1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.54\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.98\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePre-covid td2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003eCovid @ critical date\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-3.07\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.0496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.64\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.88\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePost-covid td1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePost-covid td2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePowerLOW (standing long jump)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.92\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.47\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePre-covid td1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.71\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.92\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePre-covid td2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.40\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003eCovid @ critical date\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePost-covid td1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-3.67\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePost-covid td2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.97\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePowerUP (ball-push test)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePre-covid td1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePre-covid td2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.31\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003eCovid @ critical date\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.59\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePost-covid td1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.25\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePost-covid td2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003eStatic balance (one-legged-stance)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.80\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eSI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePre-covid td1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.76\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-3.94\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-4.20\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePre-covid td1 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePre-covid td2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.68\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003eCovid @ critical date\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.31\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003eCovid x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePost-covid td1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.83\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.93\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.76\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td1 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003e\u003cem\u003ePost-covid td2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-6.38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI123_4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e-1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI12_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.20\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48%;\"\u003e\n \u003cp\u003ePost-covid td2 x SI1_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e-0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.39\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. E_CSL = cardiorespiratory endurance vs. coordination, speed and powerLOW, C_SL = coordination vs. speed and powerLOW, S_L = speed vs. powerLOW, ECSL_U = cardiorespiratory endurance, coordination, speed and powerLOW vs. powerUP, ECSL_B = cardiorespiratory endurance, coordination, speed and powerLOW vs. balance. School social index contrasts: SI123_4 = Mean of index categories 1, 2, and 3 vs. index category 4; SI12_3 = Mean of index categories 1 and 2 vs. index category 3, SI1_2 = Index category 1 vs. index category 2. Td1 = linear test date trend, td2 = quadratic test date trend. Covid @ critical date = Covid pandemic effect estimated at first school day in school year 2020/21. Bold = |z| \u0026gt; 2.\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCovid pandemic effects and cohort trends of physical fitness\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCardiorespiratory endurance\u003c/em\u003e (6-min run). When tested at the first day of school in school year 2020/21 indicated by the vertical line in figure 1, there was a small negative Covid pandemic effect (b = -0.054, z = -2.04). There was no evidence that pandemic effects at the critical date differed between schools of different social index categories (|z| \u0026lt; 2). Although these interactions were not significant, figure 1 suggests that pandemic effects at the critical date were larger for school index categories 1 and 2 (high social status) compared to schools in categories 3 and 4 (lower social status). Does the inclusion of between-school differences in pandemic effects in the LMM\u0026rsquo;s random effect structure capture the variance also related to social index category? Indeed, when not including pandemic effect-related VCs and CPs in the random effect structure for school, fixed effect interactions between school social index and Covid pandemic effect became significant also for cardiorespiratory endurance (SI123_4: b = -0.080, z = -2.65; SI12_3: b = -0.084, z = -2.60), with schools of higher social status (i.e., categories 1, 2, and 3) exhibiting larger negative pandemic effects compared to schools with lower social status (i.e., category 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBetween 2016 and 2019, main effects of linear and quadratic cohort trends were not significant. After the start of the Covid-19 pandemic, 6-min run performance declined (b = -0.043, z = -3.25), followed by a plateau (b = 0.009, z = 2.46). Cohort trends differed by school social status. Schools with higher social status exhibited slightly more positive pre-pandemic linear secular trends than schools with lower social status (SI123_4: b = 0.029, z = 3.30; SI12_3: b = 0.020, z = 2.13; SI1_2: b = 0.032, z = 3.10). After the pandemic, schools with social index category 1 (highest social status) exhibited a less negative linear cohort trend (SI1_2: b = 0.129, z = 3.50) and a more negative quadratic cohort trend (SI1_2: b = -0.042, z = -3.99), compared to schools of index category 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCoordination\u003c/em\u003e (star-run). As shown in figure 1, there was a small negative pandemic effect at the critical date (b = -0.189, z = -6.26). This pandemic effect was more pronounced in schools with higher social status compared to schools with low social status (SI123_4: b = -0.144, z = -2.60). Before the pandemic onset, coordination was characterized by a positive linear (b = 0.106, z = 5.04) and quadratic (b = 0.024, z = 5.39) cohort trend. After the pandemic onset, star-run test performance declined linearly (b = -0.062, z = -4.62), followed by a positive quadratic trend (b = 0.024, z = 6.22). Schools with high social status exhibited a more positive linear cohort trend after the pandemic onset compared to schools with low social status (SI123_4: b = 0.067, z = 2.12). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSpeed\u003c/em\u003e (20m sprint). At the first day of school in school year 2020/21 indicated by the vertical line in figure 1, 20m sprint performance was characterized by a small negative Covid pandemic effect (b = -0.087, z = -3.07). This pandemic effect was more pronounced for schools of higher social status (SI12_3: b = -0.139, z = -2.64; SI1_2: b = -0.175, z = -2.88). Prior to the pandemic, sprint performance slightly increased (linear cohort trend, b = 0.042, z = 2.02), with schools of higher social status exhibiting more positive linear cohort trends (SI123_4: b = 0.031, z = 3.54; SI1_2: b = 0.042, z = 3.98). After the pandemic onset, there was no evidence for significant linear of quadratic cohort trends (|z| \u0026lt; 2).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePowerLOW\u003c/em\u003e (standing long jump). At the critical date, there was no evidence for a Covid-19 pandemic effect on standing long jump performance (|z| \u0026lt; 2). Between 2016 and 2019, standing long jump performance was characterized by a positive linear (b = 0.058, z = 2.71) and quadratic (b = 0.016, z = 3.40) cohort trend. The positive linear cohort trend was more pronounced for schools with index category 1 (highest social status) compared to schools of index category 2 (b = 0.053, z = 4.92). After the pandemic onset, standing long jump performance decreased linearly (b = -0.051, z = -3.67), followed by a positive quadratic trend (b = 0.016, z = 3.97). There was no evidence that these cohort trends differed significantly between school social index categories.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePowerUP\u003c/em\u003e (ball-push test). Ball-push test performance was characterized by a small negative Covid pandemic effect when estimated at the first day of school in school year 2020/21 (b = -0.066, b = -2.59). There was no evidence for significant differences in this Covid pandemic effect between schools of different social index categories. Between 2016 and 2019, Ball-push test performance exhibited a small positive quadratic cohort trend (b = 0.010, z = 2.31). Between 2020 and 2023, ball-push test performance decreased linearly (b = -0.029, z = -2.25), followed by a rebound (i.e., positive quadratic trend, b = 0.010, z = 2.63; depicted in figure 1). Cohort trends largely did not differ between school social index categories. The only significant interaction between social index and cohort trend indicated that schools of social index category 1 exhibited a more positive linear cohort trend than schools of index category 2 (b = 0.031, z = 3.11).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBalance\u003c/em\u003e (one-legged-stance test). There was no evidence for a significant main effect of the Covid pandemic on one-legged-stance test performance at the critical date (|z| \u0026lt; 2). However, schools with social index categories 1 and 2 exhibited a more positive pandemic effect than schools of index category 3 (b = 0.187, z = 3.31). Prior to the pandemic, one-legged-stance performance was characterized by a positive linear (b = 0.101, z = 4.76) and quadratic (b = 0.021, z = 4.68) cohort trend. Schools with lower social status exhibited more pronounced linear trends (SI123_4: b = -0.035, z = -3.94; S12_3: b = -0.039, z = -4.20). After the pandemic onset, performance initially increased linearly (0.066, z = 4.83), followed by a negative quadratic decline (b = -0.025, z = -6.38). During this period, the positive linear cohort trend was more pronounced in schools of index categories 1, 2, and 3, relative to category 4 (SI123_4: b = 0.093, z = 2.93). Further, schools in index category 1 exhibited a slightly more pronounced secular balance trend between 2020 and 2023 compared to schools in index category 2, indicated by a larger positive linear cohort trend (S1_2: b = 0.088, z = 2.38) and more pronounced (i.e., more negative) quadratic decline (S1_2: b = -0.025, z = -2.39; see figure 1). Similarly, schools in index category 3 exhibited a more pronounced secular trend compared to schools in index categories 1 and 2, indicated by a larger positive linear cohort trend (S12_3: b = -0.093, z = -2.76) and stronger quadratic decline (S12_3: b = 0.021, z = 2.20). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAge- and gender-related differences in physical fitness\u003c/em\u003e. Previously reported age and gender effects [1,23,33] were replicated and are shown in table 3. As hypothesized, age-related gains in five of six physical fitness tests were larger in schools with higher social status (social index categories 1 \u0026ndash; 3) than in schools with low social status (index category 4). This applied to performance in the 6-min run (b = 0.100, z = 4.25), star-run (b = 0.072, z = 3.00), 20m sprint (b = 0.091, z = 3.79), standing long jump (b = 0.096, z = 3.91), and ball-push test (b = 0.067, z = 2.88). Further, schools with social index categories 1 and 2 exhibited larger age effects in the ball-push test than schools with index category 3 (b = 0.064, z = 2.65).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e. Fixed effect estimates, standard errors (SE) and z-values of the linear mixed model for age and gender effects, as well as age by school social index interactions\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"84%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eEstimate (b)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ez-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eCardiorespiratory endurance (6-min run)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.98\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI123_4 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.25\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI12_3 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI1_2 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e79.28\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eCoordination (star-run)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e26.93\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI123_4 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.00\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI12_3 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI1_2 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e40.81\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSpeed (20m sprint)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e20.08\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI123_4 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.79\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI12_3 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI1_2 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e53.77\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ePowerLOW (standing-long-jump)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e20.22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI123_4 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.91\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI12_3 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI1_2 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e67.59\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ePowerUP (ball-push test)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e52.42\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI123_4 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.88\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI12_3 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.65\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI1_2 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e121.64\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eStatic balance (one-legged-stance)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e14.27\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI123_4 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI12_3 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSI1_2 x Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e-42.13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAge = linear age trend.\u003cem\u003e\u0026nbsp;\u003c/em\u003eSchool social index contrasts: SI123_4 = Mean of index categories 1, 2, and 3 vs. index category 4; SI12_3 = Mean of index categories 1 and 2 vs. index category 3, SI1_2 = Index category 1 vs. index category 2. Bold = |z| \u0026gt; 2.\u003c/p\u003e\n\u003cp\u003eTable 4 shows variance components (VCs) and correlation parameters (CPs) of the LMM. VCs indicated that schools differed in their physical fitness, Covid pandemic effects, and age effects. Correlation parameters were in line with previously reported results [1,8], indicating that schools with better average physical fitness prior to the pandemic exhibited more pronounced negative Covid pandemic effects in the respective physical fitness components. As depicted in table 4, the Covid pandemic effect on cardiorespiratory endurance was more negative the better cardiorespiratory endurance was relative to coordination, speed, and powerLOW (CP: -0.42), the pandemic effect on coordination was more negative the better coordination was relative to speed and powerLOW (CP: -0.46), the pandemic effect on speed was more negative the better speed was relative to powerLOW (CP: -0.43), the pandemic effect on powerUP was more negative the better powerUP was relative to cardiorespiratory endurance, coordination, speed and powerLOW (ECSL_U, CP: +0.41), and the Covid pandemic effect on balance was more negative the higher balance was relative to cardiorespiratory endurance, coordination, speed and powerLOW (ECSL_B, CP: +0.37). A reparametrized LMM with physical fitness component \u003cem\u003elevels\u003c/em\u003e instead of physical fitness component \u003cem\u003econtrasts\u003c/em\u003e is provided in the OSF repository. Correlation parameters from this LMM were in line with the above reported findings for all six physical fitness components (CPs between -0.44 and -0.53). \u003cem\u003e\u003cbr\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eChild- and school-related variance components and correlation parameters of the linear mixed model\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"756\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.93651%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"11\" style=\"width: 85.7143%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.93651%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.55556%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" style=\"width: 45.2381%;\"\u003e\n \u003cp\u003eCovid @ crit. date\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.93651%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003eInt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003eE_CSL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003eC_SL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.55556%;\"\u003e\n \u003cp\u003eS_L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003eECSL_U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003eECSL_B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003eE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6984%;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003epL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.73016%;\"\u003e\n \u003cp\u003epU\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.93651%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChild\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.55556%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6984%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.73016%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.93651%;\"\u003e\n \u003cp\u003eInt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.55556%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6984%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.73016%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.93651%;\"\u003e\n \u003cp\u003eE_CSL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e-0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.55556%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6984%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n 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style=\"width: 5.55556%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6984%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.73016%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.93651%;\"\u003e\n \u003cp\u003eECSL_U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n 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style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6984%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.73016%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.93651%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSchool\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.55556%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6984%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.73016%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.93651%;\"\u003e\n 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6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.73016%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.93651%;\"\u003e\n \u003cp\u003eE_CSL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.55556%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n 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style=\"width: 12.6984%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.73016%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.93651%;\"\u003e\n \u003cp\u003eECSL_U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e+0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e+0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e+0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.55556%;\"\u003e\n 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7.14286%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6984%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.73016%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.93651%;\"\u003e\n \u003cp\u003eE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e-0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n 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\u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e+0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e+0.37\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6984%;\"\u003e\n \u003cp\u003e+0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e+0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e+0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.73016%;\"\u003e\n \u003cp\u003e+0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.93651%;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.55556%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.14286%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6984%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.34921%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.73016%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eInt = Intercept, E = cardiorespiratory endurance (i.e., 6-min run), C = coordination (i.e., star-run), S = speed (i.e., 20-m linear sprint), pL = lower limbs muscle power (i.e., powerLOW, standing long jump), pU = upper limbs muscle power (i.e., powerUP, ball-push test), B = static balance (i.e., one-legged-stance test). E_CSL = cardiorespiratory endurance vs. coordination, speed and powerLOW, C_SL = coordination vs. speed and powerLOW, S_L = speed vs. powerLOW, ECSL_U = cardiorespiratory endurance, coordination, speed and powerLOW vs. powerUP, ECSL_B = cardiorespiratory endurance, coordination, speed and powerLOW vs. balance. Covid @ crit. date = Covid pandemic effect estimated at first day of school in school year 2020/21. Age = linear age trend. VC = variance component, CP = correlation parameter. Theoretically relevant correlations are set in bold. LMM random factors: schools (444) and children (108,308), observations = 628,399. VC for Residual = 0.293.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eExploratory analysis: Regional differences in physical fitness while adjusting for school social status\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePrevious analyses of the EMOTIKON data as well as results from the school entry examination have shown regional physical fitness differences in the Federal State of Brandenburg. In the Federal State of Brandenburg, communes can be categorized either as close to Berlin (\u0026ldquo;Berliner Umland\u0026ldquo;) or far from Berlin (\u0026ldquo;weiterer Metropolenraum\u0026rdquo;)\u0026nbsp;[37]. The Brandenburg area close to Berlin is strongly integrated with the metropolitan capital city, and exhibits a higher population density\u0026nbsp;[37]\u0026nbsp;and lower average socioeconomic deprivation than the largely rural area far from Berlin\u0026nbsp;[38]. In the school entry examination, regions close to Berlin exhibit a lower percentage of overweight and obese children than regions far from Berlin\u0026nbsp;[39]. Further, third-graders in communes close to Berlin tend to exhibit better 6-min run, 20m sprint, and standing long jump performance in the EMOTKON test compared to children in regions far from Berlin (details provided in the OSF repository). However, it is unclear whether these regional differences in physical fitness are explained by schools\u0026rsquo; socio-structural composition (social welfare rate, migration background, special educational needs), or whether there are additional regional effects on physical fitness, for example linked to the proximity, accessibility (e.g., public transportation), and variety of sports clubs and quality of school sports facilities. In fact, children from areas in rural Brandenburg are less often in sports clubs than children in urban areas\u0026nbsp;[40].\u003c/p\u003e\n\u003cp\u003eTo test whether there are regional effects on physical fitness in addition to effects of school social structure, we conducted an LMM with the fixed effects reported above and the additional two-level factor \u0026ldquo;region\u0026rdquo; (close to vs. far from Berlin; details reported in the OSF repository) nested under each physical fitness component. Indeed, in this LMM adjusting for school social index, children in schools close to Berlin exhibited slightly better 6-min run (b = 0.074, z = 2.21) and standing long jump (b = 0.098, z = 3.88) performance compared to children far from Berlin. Thus, there is some evidence for region-related physical fitness differences independent of school social structure effects.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe examined whether (1) physical fitness and (2) pandemic effects differed by schools\u0026rsquo; social structure, (3) whether negatively affected physical fitness components have recovered after the pandemic, and (4) whether potential rebound effects differed by social structure. We used previously analyzed data from cohorts 2016\u0026ndash;2022 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and added new fitness data from cohort 2023. Positive linear or quadratic secular trends during cohorts 2020\u0026ndash;2023 were interpreted as evidence for post-pandemic rebound effects.\u003c/p\u003e \u003cp\u003eAs predicted, children from schools with lower social status tended to exhibit poorer 6-min run, star-run, 20m sprint, and standing long jump performance relative to children in schools with higher social status.\u003c/p\u003e \u003cp\u003eWhen estimated at the first day of school in school year 2020/2021, there were small negative Covid pandemic effects in cardiorespiratory endurance, coordination, speed, and powerUP. These results were similar to the ones reported in our previous study that included data from cohorts 2016 to 2022 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In the previous report, we also reported better average performance in tests assessing powerLOW and static balance after, compared to before the pandemic onset. However, this pattern of results was likely explained by secular trends independent of the Covid pandemic. In the present report, we adjusted for secular trends by using a regression discontinuity design to estimate pandemic effects at the first day of school in school year 2020/21.\u003c/p\u003e \u003cp\u003ePandemic effects and cohort trends differed by school social structure. First, schools with lower social status exhibited slightly more negative trends in cardiorespiratory endurance and speed prior to the pandemic. Second, in line with previous research indicating larger pandemic effects in \u0026ldquo;fitter\u0026rdquo; schools [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and in schools with higher socioeconomic background [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], pandemic effects on the star-run and 20m sprint performance were slightly more pronounced in schools with higher social status. In the other negatively affected fitness components cardiorespiratory endurance and powerUP, there was no evidence for differences in pandemic effects across school index categories. As in previous reports [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], correlation parameters in the random effect structure indicated that schools with better average performances exhibited larger negative Covid pandemic effects in all six fitness components. In cardiorespiratory endurance, between-school differences in the pandemic effect estimated in the random effect structure accounted for differences in the pandemic effect by school social index.\u003c/p\u003e \u003cp\u003eAfter an initial decline in performance at the start of the pandemic, coordination and powerUP rebounded, with a slightly larger coordination rebound in schools with high social status. Cardiorespiratory endurance and speed in 2023 remained at levels similar to the pandemic years. Other studies assessing children\u0026rsquo;s physical fitness development until 2022 reported mixed findings, with evidence for some rebounds after the pandemic [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In a large Slovenian study including over 41,000 children and adolescents tested yearly between 2019 and 2022, cardiorespiratory endurance, muscular fitness, speed, and neuromuscular and gross motor coordination declined from 2019 to 2020 but rebounded in all physical fitness components. These rebounds, however, were incomplete in most gender-BMI groups, with physical fitness remaining lower in 2022 compared to 2019 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Similarly, Austrian elementary school children still exhibited lower cardiorespiratory endurance, agility and flexibility in 2022 compared to pre-pandemic cohorts [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. PowerUP, however, was better in 2022 relative to pre-pandemic cohorts 2016\u0026ndash;2019. Pandemic effects and incomplete rebounds may be associated with pandemic-related losses of sports opportunities, but potentially also with long COVID symptoms including respiratory symptoms and fatigue [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present study, larger pandemic effects and subsequent larger rebounds in schools with higher social status illustrate the importance of a cultural environment and infrastructure providing sports opportunities for children\u0026rsquo;s physical fitness. Further, in addition to effects of school social structure, there were small regional differences in cardiorespiratory endurance and powerLOW, with slightly poorer performances for children in areas far to Berlin. Access to sports and healthy nutrition should be enhanced in socioeconomically disadvantaged schools with low access to sports opportunities and lower physical fitness, especially in Brandenburg regions far from Berlin.\u003c/p\u003e \u003cp\u003eAs cardiorespiratory endurance and muscular fitness are closely linked to physical health [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] and well-being [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] in youth, children from socioeconomically disadvantaged areas likely are, through no fault of their own, at greater risk of adverse health outcomes. In fact, according to 18,773 voluntary parental reports of children\u0026rsquo;s body mass and height in EMOTIKON cohorts 2021, 2022 and 2023, around 18 percent of children in social index category 4 were overweight or obese, compared to 10 percent of children from school index category 1. As self-reported height and weight were only available from cohort 2021 onwards, we were not able to estimate Covid pandemic effects on children\u0026rsquo;s body constitution. However, in Berlin, Germany, although physical fitness losses were more pronounced in schools with higher socioeconomic status [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], pandemic-related BMI increases were larger in schools of lower socioeconomic background [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAn additional result of the present study was that schools with higher social status exhibited slightly larger developmental trends in the ninth year of life in all physical fitness components except for static balance. This was in line with a previous study, that reported larger developmental rates in \u0026ldquo;fitter\u0026rdquo; schools, suggesting that these schools may be located in more affluent areas, where children are more active and have easier access to sports opportunities, or that they provide higher-quality physical education lessons and school sports [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eNegative pandemic effects in coordination and speed were more pronounced in schools with higher social status. There were post-pandemic rebounds in coordination and powerUP, with slightly larger coordination rebounds for schools with higher social status. Differences in Covid pandemic and rebound effects between schools highlight the importance of children\u0026rsquo;s living environment for their physical fitness development. Enhancing healthy living environments by increasing sports opportunities and access to healthy food in disadvantaged schools and structurally deprived areas may help compensate physical fitness differences. Although pandemic effects were small, absence of evidence for rebounds in cardiorespiratory endurance and speed as of 2023 may indicate long-term consequences of pandemic-related movement restrictions. Regular assessments of children\u0026rsquo;s physical fitness are needed to examine how physical fitness develops throughout the next years.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCP Correlation parameter\u003c/p\u003e\n\u003cp\u003eLMM Linear mixed model\u003c/p\u003e\n\u003cp\u003eRDD Regression discontinuity design\u003c/p\u003e\n\u003cp\u003eVC Variance component\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eContrasts for six-level factor physical fitness component\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eE vs. CSL Cardiorespiratory endurance vs. coordination, speed, powerLOW \u003c/p\u003e\n\u003cp\u003eC vs. SL Coordination vs. speed and powerLOW\u003c/p\u003e\n\u003cp\u003eS vs. L Speed vs. powerLOW\u003c/p\u003e\n\u003cp\u003eECSL vs. U Cardiorespiratory endurance, coordination, speed, powerLOW vs. powerUP\u003c/p\u003e\n\u003cp\u003eECSL vs. B Cardiorespiratory endurance, coordination, speed, powerLOW vs. balance\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eContrasts for four-level factor school social status\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSI123_4 Mean of categories 1, 2, and 3 vs. category 4\u003c/p\u003e\n\u003cp\u003eSI12_3 Mean of categories 1 and 2 vs. category 3\u003c/p\u003e\n\u003cp\u003eSI1_2 Category 1 vs. category 2\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe EMOTIKON project is mandated and approved by the Ministry of Education, Youth and Sport of the Federal State of Brandenburg, Germany.\u0026nbsp;According to the Brandenburg School Law, participation is mandatory for all public primary schools in the Federal State of Brandenburg, Germany\u0026nbsp;[24]. Written consent to participate is not required.\u0026nbsp;Research was conducted in accordance with the latest Declaration of Helsinki [46] and the Brandenburg School Law [24].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the Brandenburg School Law, participation is mandatory for children in all public primary schools in the Federal State of Brandenburg, Germany. Written consent for data processing or publication is not required.\u0026nbsp;The authors of this study received the data completely anonymized from the Ministry of Education, Youth and Sport of the Federal State of Brandenburg, Germany. Details on the legal basis of data processing can be found in \u0026sect; 65 of the Brandenburg School\u0026nbsp;Law\u0026nbsp;[24].\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAvailability of material, data, and code\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData as well as R and Julia scripts are available in the Open Science Framework (OSF) repository: https://osf.io/5273n/\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePT, RK, FA, FB, TW, and KG contributed to conception and design. KG, PT, and FA contributed to data collection. PT and RK analyzed data. PT wrote the first draft of the manuscript. All authors were involved in iterative revisions, provided final approval of the version to be published and agreed to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was commissioned and supported by the Ministry of Education, Youth, and Sport of the Federal State Brandenburg, Germany. Paula Teich was supported by the Research Focus Cognitive Sciences at the University of Potsdam. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all children who participated in EMOTIKON and all physical education teachers who conducted the assessments.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eB\u0026auml;hr F, W\u0026ouml;hrl T, Teich P, Puta C, Kliegl R. Impact of Height-to-Mass Ratio on Physical Fitness of German Third-Grade Children. Unpubl Prepr. 2024;\u003c/li\u003e\n\u003cli\u003eBasterfield L, Galna B, Burn NL, Batten H, Weston M, Goffe L, et al. Back to \u0026lsquo;normal\u0026rsquo;? BMI, physical fitness and health-related quality of life of children from North East England before, during and after the COVID-19 lockdowns. J Sports Sci [Internet]. 2024 [cited 2024 Jun 20];1\u0026ndash;13. 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JAMA. 2013;310:2191\u0026ndash;4.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"sports-medicine-open","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"smoa","sideBox":"Learn more about [Sports Medicine-Open](http://sportsmedicine-open.springeropen.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/smoa/default.aspx","title":"Sports Medicine-Open","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Physical fitness, primary school children, regression discontinuity design, linear mixed model, socioeconomic background","lastPublishedDoi":"10.21203/rs.3.rs-4997009/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4997009/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIn a recent study, we examined Covid-19 pandemic effects on the physical fitness of German third-graders tested between 2016 and 2022. The present report includes new data from 2023 to examine whether there were post-pandemic rebounds in the negatively affected fitness components, and whether pandemic and potential rebound effects differed by school social status.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe EMOTIKON project annually tests the fitness of all third-graders in the Federal State of Brandenburg, Germany. Tests assess cardiorespiratory endurance (6-min-run), coordination (star-run), speed (20-m linear sprint), lower (powerLOW, standing long jump), and upper (powerUP, ball-push) limbs muscle power, and static balance (one-legged-stance). A total of 108,308 third-graders aged between 8 and 9.2 years from 444 schools were tested in the falls from 2016\u0026ndash;2023. Linear mixed models, specified for a regression discontinuity design with random factors for child and school, tested pandemic effects at the first day of school in the school year 2020/21 (i.e., the critical date) and cohort trends before and after the pandemic onset.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAt the critical date, there were small negative pandemic effects in cardiorespiratory endurance, coordination, speed, and powerUP. Pandemic effects in speed and coordination were larger in schools with higher social status. Coordination and powerUP were characterized by a post-pandemic rebound, with slightly larger coordination rebounds for schools with higher social status. There was no evidence for rebounds of cardiorespiratory endurance and speed.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eAbsence of evidence for task-specific rebounds may indicate long-term consequences of pandemic-related movement restrictions. Especially children in schools with higher social burden may be in need of improved access to sports opportunities.\u003c/p\u003e","manuscriptTitle":"Association of school social status with Covid pandemic related changes and post-pandemic rebounds of children’s physical fitness","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-22 06:36:49","doi":"10.21203/rs.3.rs-4997009/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-09-25T08:00:44+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-06T03:23:16+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Sports Medicine-Open","date":"2024-09-04T21:11:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-30T05:53:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Sports Medicine-Open","date":"2024-08-29T06:40:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"sports-medicine-open","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"smoa","sideBox":"Learn more about [Sports Medicine-Open](http://sportsmedicine-open.springeropen.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/smoa/default.aspx","title":"Sports Medicine-Open","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ef0265bd-afcd-4c42-a84f-52756de10276","owner":[],"postedDate":"October 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-04-28T16:07:29+00:00","versionOfRecord":{"articleIdentity":"rs-4997009","link":"https://doi.org/10.1186/s40798-025-00838-5","journal":{"identity":"sports-medicine-open","isVorOnly":false,"title":"Sports Medicine-Open"},"publishedOn":"2025-04-23 15:58:26","publishedOnDateReadable":"April 23rd, 2025"},"versionCreatedAt":"2024-10-22 06:36:49","video":"","vorDoi":"10.1186/s40798-025-00838-5","vorDoiUrl":"https://doi.org/10.1186/s40798-025-00838-5","workflowStages":[]},"version":"v1","identity":"rs-4997009","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4997009","identity":"rs-4997009","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}