European fitness landscape for children and adolescents: updated reference values, fitness maps and country rankings based on nearly 8 million test results from 34 countries gathered by the FitBack network

1 of 13 OrtegaFB, etal. Br J Sports Med 2023;57:299–310. doi:10.1136/bjsports-2022-106176 European fitness landscape for children and adolescents: updated reference values, fitness maps and country rankings based on nearly 8 million test results from 34 countries gathered by the FitBacknetwork Francisco B Ortega ,1,2,3 Bojan Leskošek,4 Rok Blagus ,4,5,6 José J GilCosano ,1,7 Jarek Mäestu ,8 Grant R Tomkinson ,9 Jonatan R Ruiz ,1,3,10 Evelin Mäestu,8 Gregor Starc ,4 Ivana Milanovic,11 Tuija H Tammelin ,12 Maroje Sorić ,4,13 Claude Scheuer ,14,15 Attilio Carraro ,16 Mónika Kaj,17 Tamás Csányi ,17,18,19 Luis B Sardinha ,20 Matthieu Lenoir ,21 Arunas Emeljanovas,22 Brigita Mieziene,22 Labros S Sidossis,23 Maret Pihu,8 Nicola Lovecchio ,24,25 Kenn Konstabel ,26,27 Konstantinos D Tambalis,28,29 Lovro Štefan ,13,30,31 Clemens Drenowatz,32 Lukáš Rubín ,33,34 Seryozha Gontarev,35 José CastroPiñero ,36,37 Jérémy Vanhelst ,38 Brendan O’Keeffe ,39 Oscar L Veiga,40 Thordis Gisladottir,41 Gavin Sandercock ,42 Marjeta MisigojDurakovic,13 Claudia Niessner,43 EvaMaria Riso,8 Stevo Popovic,44,45 Saima Kuu,46 Mai Chinapaw,47 Iván Clavel,48,49 Idoia Labayen ,50 Janusz Dobosz ,51 Dario Colella,52 Susi Kriemler ,53 Sanja Salaj,13 Maria Jose Noriega,54 Klaus Bös,43 Mairena SánchezLópez ,55,56 Timo A Lakka ,57,58,59 Garden Tabacchi,60 Dario Novak,13 Wolfgang Ahrens,61 Niels Wedderkopp ,62 Gregor Jurak ,4 the FitBack, HELENA and IDEFICS consortia Original research To cite: OrtegaFB, LeskošekB, BlagusR, etal. Br J Sports Med 2023;57:299–310. ►Additional supplemental material is published online only. To view, please visit the journal online (http:// dx. doi. org/ 10. 1136/ bjsports2022106176). For numbered affiliations see end of article. Correspondence to Francisco B Ortega; ortegaf@ ugr. es Gregor Jurak; Gregor. Jurak@ fsp. unilj. si Accepted 18 November 2022 Published Online First 9January2023 © Author(s) (or their employer(s)) 2023. Reuse permitted under CC BYNC. No commercial reuse. See rights and permissions. Published by BMJ. ABSTRACT Objectives (1) To develop reference values for healthrelated fitness in European children and adolescents aged 6–18 years that are the foundation for the webbased, openaccess and multilanguage fitness platform (FitBack); (2) to provide comparisons across European countries. Methods This study builds on a previous large fitness reference study in European youth by (1) widening the age demographic, (2) identifying the most recent and representative countrylevel data and (3) including national data from existing fitness surveillance and monitoring systems. We used the Assessing Levels of PHysical Activity and fitness at population level (ALPHA) test battery as it comprises tests with the highest test–retest reliability, criterion/construct validity and healthrelated predictive validity: the 20 m shuttle run (cardiorespiratory fitness); handgrip strength and standing long jump (muscular strength); and body height, body mass, body mass index and waist circumference (anthropometry). Percentile values were obtained using the generalised additive models for location, scale and shape method. Results A total of 7 966 693 test results from 34 countries (106 datasets) were used to develop sexspecific and agespecific percentile values. In addition, countrylevel rankings based on mean percentiles are provided for each fitness test, as well as an overall fitness ranking. Finally, an interactive fitness platform, including individual and group reporting and European fitness maps, is provided and freely available online ( www.fitbackeurope.eu). WHAT IS ALREADY KNOWN ON THIS TOPIC ⇒Fitness testing in youth is important from health, educational and sport points of view. ⇒The European Unionfunded ALPHA project reviewed the existing evidence and proposed a selection of fieldbased fitness tests that showed the highest test–retest reliability, criterion/construct validity and healthrelated predictive validity among available tests. WHAT THIS STUDY ADDS ⇒The FitBack project provides the most uptodate and geographically diverse reference fitness values for Europeans 6–18 years of age. ⇒This study introduces the first webbased, openaccess and multilingual fitness reporting platform (FitBack) providing interactive information and visual mapping of the European fitness landscape. Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from 2 of 13 OrtegaFB, etal. Br J Sports Med 2023;57:299–310. doi:10.1136/bjsports-2022-106176 Original research Conclusion This study discusses the major implications of fitness assessment in youth from health, educational and sport perspectives, and how the FitBack reference values and interactive webbased platform contribute to it. Fitness testing can be conducted in school and/or sport settings, and the interpreted results be integrated in the healthcare systems across Europe. INTRODUCTION Robust and consistent evidence supports that physical fitness is a powerful marker of health in children and adolescents.1 2 Among the different fitness components, cardiorespiratory fitness (CRF, used in the literature and this article interchangeably with aerobic fitness) and muscular strength (used in the literature and this article interchangeably with muscular fitness) have shown the strongest and most consistent healthrelated associations and are therefore considered to be the main healthrelated fitness components.3 4 Other fitness components include flexibility, motor fitness and body composition/anthropometry (height, body mass, body mass index (BMI) and waist circumference). Recently, data from large registries have added compelling evidence linking both CRF and muscular strength in late adolescence with allcause mortality and cardiovascularspecific and cancerspecific mortality in later life.5–8 In addition, these two fitness components predict severe, chronic and irreversible allcause disease 30 years later as indicated by granted disability pensions,9–12 and also specifically cardiovascular, musculoskeletal, neurological and psychiatric diseases granted by a disability pension.9–12 Particularly, CRF is the most wellstudied and strongest predictor of future health.2 Indeed, a position stand from the American Heart Association has highlighted the clinical value of CRF in youth and recommended that it be regularly assessed.13 In addition to the welldocumented associations between fitness and physical/mental health among youth,1–4 14 emerging evidence supports that better fitness is related to better cognition, academic performance, and healthier structural and functional brain outcomes.15–29 For example, recent observations from the ActiveBrains project have shown that total brain size, as well as total grey and white matter volumes, is larger in fit compared with unfit children with overweight/obesity.30 This is important because total brain size is positively associated with intelligence.31 These findings are in line with those from Chaddock and colleagues, who included children also with normal weight, and found that fitter kids had larger grey matter volumes in subcortical brain regions such as hippocampus17 and dorsal stratium.19 The evidence hereby presented about fitness as a powerful marker of health in youth supports the relevance of fitness assessment at the individual and population levels. However, the availability of different fitness batteries/tests leads to a lack of consistency and comparability across studies. To address this problem, the European Commission funded the ALPHA project. By conducting a set of systematic reviews2 32 33 and methodological papers, the ALPHA consortium aimed to identify the fieldbased fitness tests that demonstrated the highest test– retest reliability, criterion/construct validity and healthrelated predictive validity (see ALPHA summary article34). Anthropometry and body composition are known to be tightly linked to fitness performance and health and were therefore considered as fitness components in the ALPHA project. The final output of the project was the ALPHAfitness test battery for children and adolescents, which in its highpriority version (a shorter, more suitable version for schoolbased use) recommended using: the 20 m shuttle run test for assessing CRF; the handgrip and standing long jump tests for assessing muscular strength and power; and BMI and waist circumference as indicators of total and central obesity, respectively. A year later and after following a similar systematic review process, the US Institute of Medicine (now the National Academy of Medicine) recommended these same tests for the assessment of youth physical fitness,35 36 strengthening the recommendation of using the ALPHA fitness test battery. As the next step to the ALPHA project, the European Commission funded the FitBack consortium (www.fitbackeurope.eu), representing the European Network for the Support of Development of Systems for Monitoring Physical Fitness of Children and Adolescents. The major goal of the network is to take an important step toward the implementation of fitness surveillance and monitoring across Europe as an educational tool for physical literacy.37 The final output of the FitBack project has been the development of a webbased, openaccess and multilanguage fitness platform which allows the results of fitness testing to be automatically and interactively interpreted based on sexspecific and agespecific reference values and is supported by userfriendly visual feedback and tips for improvement. For this purpose, we gathered available fitness data on European children and adolescents. Previous fitness reference values published were mostly from individual countries (see references in online supplemental table 1) or multicentre EU projects (eg, IDEFICS - Identification and prevention of Dietaryand lifestyleinduced health EFfects in Children and infantS - and HELENA - Healthy Lifestyle in Europe by Nutrition in Adolescence - projects38 39) collecting data in one to two cities per country. The study by Tomkinson and colleagues provided the first European reference values that included numerous countries and covered a wide age demographic (subjects 9–17 years old).40 However, until now, European reference values have not covered all schoolage children (primary, secondary and high school) from age 6 years to 18 years. Also, the writing group was aware of nationally representative fitness monitoring systems and large datasets not included in Tomkinson’s study, indicating the need to update existing reference values. There was also a pressing need to develop an automated, freely accessible web platform containing these normative values to facilitate the interpretation of sexspecific and agespecific fitness test results. The aim of this article is to develop healthrelated fitness reference values for European children and adolescents aged 6–18 years. Additionally, we provide European fitness maps and HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY ⇒From a health perspective, very low fitness levels are a noninvasive indicator of poor health at both individual and group levels (eg, school and region), which have utility for health screening and may guide public health policy. There are already examples of regional and national fitness testing systems that are integrated into healthcare systems. ⇒From an educational perspective, fitness testing is part of the school curriculum in many countries, and the FitBack platform offers physical education teachers an easytouse tool for interpreting fitness test results by sex and age. ⇒From a sport perspective, these reference values can help identify young individuals who are talented in specific fitness components. Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from 3 of 13 OrtegaFB, etal. Br J Sports Med 2023;57:299–310. doi:10.1136/bjsports-2022-106176 Original research country ranking for the main healthrelated fitness components, all together as part the new, freeaccess, FitBack web platform ( www.fitbackeurope.eu). Since paediatric obesity is being comprehensively monitored by other organisations (eg, World Obesity Federation, www.worldobesity.org/; WHOEurope www.euro. who.int/en/health-topics/disease-prevention/nutrition/activities/ who-european-childhood-obesity-surveillance-initiative-cosi), the focus of this article is mainly on CRF and muscular strength. Nonetheless, we also provide reference values and European maps for anthropometric measures (body height, body mass, BMI and waist circumference) as online supplemental material. METHODS Data search and pooling A systematic review of existing datasets including fitness tests in children and adolescents was previously performed by Tomkinson et al and details of the search have been published.40 These data were included in the FitBack dataset, with Monte Carlo simulation used to produce pseudo data (from reported means and SDs) when raw data were unavailable. In addition to this, the authors of the FitBack network conducted a centralised narrative search based on fitness terms to identify new datasets not included in the Tomkinson et al review.40 For inclusion, valid data on sex, age and at least one of the ALPHA fitness tests (highpriority version) was required. In the previous study by Tomkinson et al, the age range was 9–17 year old, whereas in this study, we widened the age demographic to include subjects aged 6–18 years old. It is important to note that our search strategy was focused on fitness, and specific searches on adiposity, BMI or waist circumference were not conducted for pragmatic reasons (eg, the very large number of studies including these key words). Therefore, it is possible that we missed relevant anthropometryspecific datasets. This, together with the fact that other organisations are comprehensively monitoring paediatric obesity, is the reason why we primarily focused on CRF and muscular strength, and reported results for anthropometric measures (body height, body mass, BMI and waist circumference) as online supplemental material. The FitBack network involved numerous experienced researchers working in paediatric fitness across Europe, which helped to identify unpublished fitness datasets that were pooled with gathered data. Moreover, large datasets from existing surveillance systems in Europe such as SLOfit,41 NETFIT42 and Fitescola43 were also included. Further, we excluded older datasets if a more recent and more representative dataset was available for certain countries. The ambition was to use the most recent available data for each country, which in some cases was a single large dataset, while in others was the accumulation of several studies or datasets covering different geographical regions within a country. Sources used for generating the reference values are available on the FitBack website (www. fitbackeurope.eu/en-us/fitness-map/sources) as well as in online supplemental table 1. Physical fitness measures The FitBack dataset was compiled for studies that used the ALPHA fitness test battery2 32–34 since these tests have shown to be feasible, reliable, valid, and scalable for children and adolescents. Moreover, some of them are used in wellestablished European national fitness surveillance and monitoring systems like SLOfit,41 NETFIT42 and Fitescola.43 Specifically, CRF was assessed using the 20 m shuttle run test.44 The number of completed stages was used as an indicator of CRF. However, different studies had expressed the result of the 20 m shuttle run test in other units, such as completed laps (shuttles) or speed at the last completed stage, and there are at least three known protocols/versions of this test.45 All data were converted and harmonised into completed stages according to the original Léger protocol,44 as described elsewhere.45 Muscular strength was assessed by the handgrip strength (ie, upperlimb muscular strength) and standing long jump tests (ie, lowerlimb muscular strength). Total and abdominal adiposities were assessed by BMI and waist circumference, respectively, following standardised procedures. For handgrip, most studies collected data from both hands, with the average of the best performance from both hands used in our analyses. Two studies had handgrip strength data only for the dominant hand, which is known to be systematically higher compared with the nondominant hand. Exploratory analyses on Spanish data in children46 showed a 0.6 kg mean difference between hands, and thus, we applied a –0.3 kg correction factor to these two studies to estimate the average score. Statistical analysis We applied different cleansing procedures to the data. First, data were trimmed to remove values outside the probable lower and upper limits. The limits were defined based on authors’ experiences working with previous large datasets. The limits used were 20 m shuttle run (0–21 stages), handgrip strength (0–80 kg), standing long jump (15–330 cm), body height (80–220 cm), body mass (0–200 kg), BMI (7–60 kg/m2) and waist circumference (40–130 cm). Second, outliers were identified and removed as follows. For each fitness measure, herein referred to as the test, a multivariate regression model including the test as the dependent variable and age (modelled as a cubic spline with 5 degrees of freedom (df)), sex and their interaction as independent variables was fitted. Studentised residuals were obtained, and then 0.01% of the subjects with the smallest and largest studentised residuals were removed from further analysis. Weights were computed via iterative poststratification (aka iterative proportional fitting)47 to match the sample joint distributions by age, sex and country to population data. Countryspecific population values were obtained from EUROSTAT. The sample weights were trimmed to avoid excessively large sampling variances.47 Percentile curves and reference values were developed using generalised additive models for location, scale and shape (GAMLSS).48 Several continuous (BoxCox Cole and Green (BCCG), BoxCox power exponential (BCPE), BoxCoxt (BCT), generalised inverse Gaussian) distributions were fitted to the data, optimising the df for Psplines fit for all parameters of the respective distributions using Schwarz Bayesian criterion (SBC); appropriate link functions were used for the parameters. BCCG is routinely used in the lambda mu sigma (LMS) method.49 BCPE and BCT are extensions of LMS adding an extra parameter, ν , to allow modelling (positive or negative) kurtosis (with ν= 2 BCPE and BCCG (LMS) coincide). In all the models, λ= 1/3 and λ= 1/2 were used for the power transformation of age. Separate analyses were performed for boys and girls. The final model for each test and sex was determined by using SBC. The analysis was performed using R language for statistical computing (R V.3.6.3)50; GAMLSS were fitted using R package GAMLSS51; poststratification weights were obtained using R package survey.51 The best fitting model for each test is presented in online supplemental table 2. Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from 4 of 13 OrtegaFB, etal. Br J Sports Med 2023;57:299–310. doi:10.1136/bjsports-2022-106176 Original research RESULTS After cleaning and removing outliers, 7 966 693 test results were available, including 1 026 077 for the 20 m shuttle run; 787 966 for handgrip strength, 1 345 159 for standing long jump, 1 466 821 for body height, 1 466 295 for body mass, 1 464 795 for BMI, and 409 580 for waist circumference. These data came from 106 datasets belonging to 34 European countries, on children and adolescents aged 6 to 18 years. We originally aimed to collect data as recent as possible to obtain uptodate reference values, preferably since 2000. Most (69%) datasets (representing 95% of all test results) were collected post2000; however, pre2000 data were included when post2000 were unavailable at the country level. Using these data, we developed CRF and muscular strength reference values (tables 1–3) and corresponding percentile curves (figure 1). Reference values for body height, body mass, BMI and waist circumference are presented in online supplemental tables 36 and online supplemental figures 1 and 2. Percentile curves for CRF and muscular strength are higher for boys compared with girls across all ages, with differences increasing with age. The agerelated increase in fitness performance tends to stabilise from age 14 years to 15 years onwards. Variation between the fittest (eg, percentiles 90–99) and least fit (eg, percentiles 1–10) is larger for boys compared with girls, particularly for the 20 m shuttle run and handgrip strength tests. Mean countrylevel percentiles and rankings are shown in table 4. Countrylevel rankings based on mean percentiles are provided for each fitness test, as well as an average estimate for each fitness component (CRF, muscular strength) and the overall European fitness ranking. The top 5 most aerobically fit countries were Iceland, Norway, Slovenia, Denmark and Finland, and the top 5 physically strong countries were Denmark, Czech Republic, The Netherlands (only one muscular strength test available), Slovenia and Finland. Online supplemental tables 7 and 8 show the corresponding countrylevel mean percentile and ranking positions for body height, body mass, BMI and waist circumference. Country comparisons according to mean percentiles are also graphically represented in figure 2, with European fitness maps for each test shown separately. The traffic light colour code was used to represent countryspecific percentile ranks, with red indicating lower fitness levels, yellow indicating intermediate fitness levels and green indicating higher fitness levels. The corresponding European maps for BMI and waist circumference are presented as online supplemental figure 3. These maps are available in an interactive mode at the FitBack web platform (www.fitbackeurope. eu/en-us/fitness-map) for boys and girls, together and separately. Visual inspection of the fitness maps shows that Southern European countries and the UK generally performed the worst. The correlation between countrylevel CRF and muscular strength Table 1 Reference values (percentiles) for cardiorespiratory fitness as assessed by the 20 m shuttle run test (expressed in completed stages as a decimal) in European children and adolescents (N=1 026 077) P1 P5 P10 P20 P30 P40 P50 P60 P70 P80 P90 P95 P99 Girls’ ages (years) 6.0–6.9 0.6 0.8 0.9 1.1 1.4 1.6 1.8 2.1 2.4 2.8 3.4 4.1 5.5 7.0–7.9 0.6 0.8 1.0 1.3 1.5 1.8 2.1 2.4 2.7 3.2 3.9 4.6 6.1 8.0–8.9 0.5 0.9 1.1 1.5 1.8 2.1 2.4 2.8 3.2 3.7 4.5 5.3 6.9 9.0–9.9 0.5 1.0 1.3 1.7 2.1 2.5 2.9 3.3 3.7 4.4 5.3 6.1 7.9 10.0–10.9 0.5 1.1 1.4 2.0 2.4 2.8 3.3 3.7 4.3 4.9 5.9 6.9 8.7 11.0–11.9 0.6 1.2 1.6 2.2 2.7 3.1 3.6 4.1 4.6 5.3 6.4 7.3 9.2 12.0–12.9 0.7 1.4 1.8 2.4 2.9 3.4 3.8 4.3 4.9 5.6 6.6 7.5 9.3 13.0–13.9 0.8 1.4 1.9 2.5 3.0 3.4 3.9 4.4 4.9 5.6 6.6 7.5 9.3 14.0–14.9 0.8 1.5 1.9 2.5 3.0 3.5 3.9 4.4 5.0 5.6 6.6 7.5 9.3 15.0–15.9 0.8 1.5 1.9 2.5 3.0 3.5 3.9 4.4 5.0 5.6 6.6 7.5 9.3 16.0–16.9 0.7 1.4 1.9 2.5 3.0 3.5 3.9 4.4 4.9 5.6 6.6 7.4 9.2 17.0–17.9 0.7 1.4 1.9 2.5 3.0 3.4 3.8 4.3 4.8 5.5 6.4 7.3 9.0 18.0–18.9 0.7 1.4 1.8 2.4 2.9 3.3 3.8 4.2 4.7 5.4 6.3 7.1 8.8 Boys’ ages (years) 6.0–6.9 0.6 0.8 0.9 1.2 1.4 1.7 2.0 2.4 2.9 3.4 4.2 5.0 6.4 7.0–7.9 0.6 0.9 1.1 1.4 1.7 2.1 2.5 2.9 3.4 4.0 4.9 5.7 7.2 8.0–8.9 0.6 1.0 1.2 1.7 2.1 2.5 3.0 3.5 4.1 4.8 5.8 6.7 8.2 9.0–9.9 0.6 1.1 1.5 2.0 2.6 3.1 3.6 4.2 4.9 5.7 6.8 7.7 9.4 10.0–10.9 0.6 1.3 1.7 2.4 3.0 3.6 4.2 4.8 5.5 6.4 7.5 8.5 10.2 11.0–11.9 0.7 1.4 2.0 2.7 3.4 4.0 4.6 5.3 6.0 6.8 8.0 9.0 10.7 12.0–12.9 0.8 1.6 2.2 3.1 3.8 4.4 5.0 5.7 6.4 7.3 8.5 9.4 11.1 13.0–13.9 0.9 1.9 2.6 3.5 4.2 4.9 5.5 6.2 7.0 7.8 9.0 9.9 11.7 14.0–14.9 1.0 2.2 2.9 3.9 4.7 5.4 6.1 6.8 7.5 8.4 9.6 10.5 12.3 15.0–15.9 1.1 2.4 3.2 4.3 5.1 5.8 6.5 7.2 7.9 8.8 10.0 11.0 12.8 16.0–16.9 1.1 2.5 3.4 4.4 5.2 6.0 6.7 7.3 8.1 8.9 10.1 11.1 12.8 17.0–17.9 1.1 2.5 3.4 4.5 5.3 6.0 6.6 7.3 8.0 8.8 10.0 10.9 12.6 18.0–18.9 1.0 2.5 3.3 4.4 5.2 5.9 6.5 7.2 7.8 8.6 9.7 10.6 12.2 Smoothed percentiles were calculated using the generalised additive model for location, scale and shape method, and weights were applied according to country population. Age at the midpoint of each interval was selected to provide percentiles. For instance, for the interval 6.0–6.9, data presented were those corresponding to an exact age of a 6.5yearold child. P10 indicates 10th percentile; other percentiles are abbreviated accordingly. Data sources are available online (www.fitbackeurope.eu/en-us/fitness-map/ source) and in online supplemental table 1. Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from 5 of 13 OrtegaFB, etal. Br J Sports Med 2023;57:299–310. doi:10.1136/bjsports-2022-106176 Original research rankings was moderate (r=0.59) and is graphically represented in figure 3. Shaded areas represent those countries ranked in the top 10 for CRF, muscular strength or both. DISCUSSION Main findings in the context of previous literature This article provides the most uptodate and comprehensive reference values for the healthrelated fitness of European children and adolescents aged 6–18 years. We also provided countrylevel mean percentiles for each fitness component. Our overall countrylevel fitness rankings suggest that Northern (Denmark, Finland, Iceland and Norway) and Central Eastern European countries (Slovenia, Czech Republic and Slovakia) have the fittest children and adolescents, while Southern European countries (Spain, Italy and Greece) and the UK are comparatively less fit. Interestingly, we observed a moderate positive correlation between countrylevel CRF and muscular strength, indicating that despite being different fitness components, countries having higher CRF levels generally also had higher muscular strength levels. A major contribution of the present study is that it comes together with the FitBack interactive web platform (www. fitbackeurope.eu), which is free, multilingual (English, Spanish, French, German and Italian) and ready to be used by researchers and practitioners in physical education, sport and health, as well as by policy makers across Europe. FitBack can be useful and informative even for other continents temporally until they develop their own normative values and similar web platforms. The FitBack platform provides individual and groupbased fitness reports supported by educational materials for implementation of fitness monitoring to support fitness education (ie, to help understand why fitness and fitness testing are important, how to interpret fitness test results, how to set exercise goals, how to improve fitness levels, etc) and improve physical literacy, as well as interactive European fitness maps based on our reference values. To date, the largest and best available fitness reference values for European children and adolescents were those published by Tomkinson et al in 2018.40 Our study updates such work by adding new data and expanding the age range from 9 years to 17 years to 6–18 years.40 It is challenging to directly compare the previous and current reference values, given betweenstudy differences in included studies, countries, ages and sexes. Nevertheless, as an example, the 50th percentile values for the 20 m shuttle run ranged from 3.4 to 4.1 stages in girls aged 9–17 years and from 4.4 to 7.7 stages in boys aged 9–17 years in Tomkinson’s study, with the corresponding FitBack values ranging from 2.9 to 3.8 in girls and from 3.6 to 6.6 in boys. For handgrip, the corresponding values were 13.6–28.4 kg in girls and 15.3– 45.0 kg in boys in Tomkinson’s study and 14.1–28.6 kg in girls Table 2 Reference values (percentiles) for muscular strength as assessed by the handgrip strength test (expressed in kg, average of the maxima for both hands) in European children and adolescents (N=787 966) P1 P5 P10 P20 P30 P40 P50 P60 P70 P80 P90 P95 P99 Girls’ ages (years) 6.0–6.9 4.2 5.6 6.3 7.2 7.8 8.3 8.8 9.3 9.9 10.7 11.8 12.9 15.5 7.0–7.9 4.7 6.4 7.3 8.4 9.1 9.7 10.4 11.0 11.7 12.6 13.9 15.3 18.4 8.0–8.9 5.2 7.4 8.5 9.8 10.7 11.4 12.2 13.0 13.8 14.9 16.6 18.1 21.9 9.0–9.9 5.8 8.4 9.7 11.3 12.3 13.3 14.1 15.1 16.1 17.3 19.3 21.1 25.6 10.0–10.9 6.7 9.7 11.3 13.0 14.3 15.3 16.3 17.4 18.5 20.0 22.2 24.3 29.3 11.0–11.9 8.0 11.6 13.3 15.3 16.8 18.0 19.1 20.3 21.6 23.2 25.7 28.1 33.7 12.0–12.9 9.5 13.6 15.5 17.8 19.3 20.7 21.9 23.2 24.6 26.4 29.1 31.6 37.8 13.0–13.9 11.1 15.5 17.7 20.0 21.7 23.1 24.5 25.8 27.3 29.2 32.0 34.7 41.1 14.0–14.9 12.4 17.1 19.3 21.8 23.5 25.0 26.4 27.8 29.3 31.2 34.1 36.9 43.4 15.0–15.9 13.1 18.0 20.2 22.8 24.6 26.0 27.4 28.8 30.4 32.3 35.2 38.0 44.6 16.0–16.9 13.4 18.4 20.8 23.4 25.1 26.6 28.0 29.4 31.0 32.9 35.8 38.6 45.2 17.0–17.9 13.7 18.9 21.3 23.9 25.7 27.2 28.6 30.0 31.5 33.4 36.3 39.1 45.7 18.0–18.9 14.3 19.6 22.0 24.6 26.4 27.9 29.2 30.6 32.2 34.1 37.0 39.7 46.3 Boys' Ages (years) 6.0–6.9 4.8 6.4 7.1 8.0 8.7 9.2 9.8 10.3 11.0 11.7 13.0 14.1 17.1 7.0–7.9 5.5 7.3 8.3 9.4 10.2 10.9 11.5 12.2 13.0 13.9 15.4 16.8 20.3 8.0–8.9 6.2 8.5 9.6 10.9 11.9 12.7 13.5 14.3 15.3 16.4 18.2 19.9 24.0 9.0–9.9 7.0 9.5 10.8 12.4 13.5 14.5 15.4 16.4 17.5 18.8 20.9 22.8 27.4 10.0–10.9 7.8 10.7 12.1 13.9 15.2 16.3 17.4 18.5 19.7 21.3 23.6 25.8 30.9 11.0–11.9 8.9 12.2 13.9 15.9 17.4 18.7 20.0 21.2 22.7 24.4 27.1 29.6 35.3 12.0–12.9 10.2 14.1 16.1 18.5 20.3 21.8 23.3 24.8 26.5 28.5 31.7 34.6 41.1 13.0–13.9 12.2 16.9 19.3 22.2 24.4 26.2 28.0 29.8 31.8 34.3 38.0 41.4 49.0 14.0–14.9 14.9 20.3 23.2 26.7 29.2 31.4 33.5 35.6 37.9 40.8 45.1 49.0 57.4 15.0–15.9 17.7 23.8 27.0 30.9 33.6 36.0 38.3 40.6 43.2 46.3 50.9 55.0 63.7 16.0–16.9 20.2 26.7 30.1 34.1 37.0 39.5 41.9 44.3 46.9 50.1 54.8 58.9 67.6 17.0–17.9 22.4 29.1 32.6 36.7 39.7 42.2 44.6 47.0 49.7 52.9 57.5 61.6 70.0 18.0–18.9 24.4 31.2 34.8 39.0 42.0 44.5 46.9 49.4 52.0 55.2 59.7 63.7 71.9 Smoothed percentiles were calculated using the generalised additive model for location, scale and shape method, and weights were applied according to country population. Age at the midpoint of each interval was selected to provide percentiles. For instance, for the interval 6.0–6.9, data presented were those corresponding to an exact age of a 6.5yearold child. P10 indicates 10th percentile; other percentiles are abbreviated accordingly. Data sources are available online (www.fitbackeurope.eu/en-us/fitness-map/ sources) and in online supplemental table 1. Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from 6 of 13 OrtegaFB, etal. Br J Sports Med 2023;57:299–310. doi:10.1136/bjsports-2022-106176 Original research and 15.4–44.6 kg in boys in FitBack. Further, the corresponding values for the standing long jump test were 123.9–156.4 cm in girls and 133.8–205.8 cm in boys Tomkinson’s study, and 122.7–156.8 cm in girls and 133.4–207.8 cm in boys in FitBack. Thus, the median fitness levels in the FitBack study are slightly lower than those in Tomkinson’s study for the 20 m shuttle run, and nearly identical for handgrip strength and the standing long jump. These betweenstudy differences are likely because the included datasets differ in sample size, collection time frames, country representation and sample representativeness. Tomkinson’s reference values for the 20 m shuttle run were based on 445 092 data points from 24 countries (see table 9 of Tomkinson et al study40), whereas the FitBack reference values were based on 1 026 077 data points from 30 European countries. The corresponding sample sizes for handgrip strength and standing long jump are n=203 295 vs 787 966 and n=464 900 vs 1 345 159 for Tomkinson et al’s study versus FitBack, respectively. Usefulness and practical implications of fitness testing and monitoring Our reference values, when integrated into the interactive FitBack web platform, have practical utility and implications. First, fitness testing and monitoring is extremely important from a public health and clinical point of view, as recently acknowledged by the American Heart Association13 and others.52 Measuring cardiometabolic risk factors from blood samples is invasive and ethically questionable for youth at the population level. Likewise, mental and cognitive health assessments are often complex, sensitive and time consuming. Since physical fitness has repeatedly and consistently been shown to be a powerful marker of physical, mental and cognitive health in youth, fitness testing and monitoring will provide valuable insights into the health status of youth at individual and group levels. However, clinicians may not have the time, resources, facilities or expertise to conduct fitness testing (eg, the 20 m shuttle run test) in clinical settings. Therefore, we believe that the most feasible alternative and future goal is that populationlevel fitness testing be conducted in schools, with test results and interpretation incorporated into the healthcare system databases and forming part of an individual’s medical records that can be viewed by paediatricians and school doctors/nurses. This might be even more relevant in lowtomiddleincome countries. Such practice has been implemented at the regional level in Galicia, Spain,53 and at the national level in Slovenia40 and Finland.54 In addition, our article and the interactive FitBack website provide a valuable and costeffective solution for establishing fitness monitoring at the school, community, regional and national levels. For instance, policy makers at education, sport and health institutions can obtain valuable information about regional differences or temporal trends by monitoring Table 3 Reference values (percentiles) for muscular strength as assessed by the standing long jump test (expressed in cm) in European children and adolescents (N=1 345 159) P1 P5 P10 P20 P30 P40 P50 P60 P70 P80 P90 P95 P99 Girls’ ages (years) 6.0–6.9 47.4 63.3 71.1 80.2 86.5 91.9 96.8 101.6 106.9 113.0 121.5 128.8 143.0 7.0–7.9 55.1 71.1 79.0 88.3 94.8 100.3 105.5 110.6 116.0 122.5 131.6 139.3 154.6 8.0–8.9 63.1 79.1 87.2 96.7 103.4 109.0 114.3 119.5 125.2 131.9 141.4 149.6 165.8 9.0–9.9 70.8 87.0 95.1 104.8 111.6 117.3 122.7 128.1 134.0 140.9 150.8 159.2 176.3 10.0–10.9 77.2 93.8 102.3 112.2 119.2 125.2 130.8 136.4 142.5 149.7 160.0 168.9 186.8 11.0–11.9 82.9 100.6 109.6 120.1 127.6 133.9 139.9 145.8 152.3 159.9 170.9 180.4 199.6 12.0–12.9 87.3 106.2 115.7 126.9 134.8 141.6 147.8 154.1 161.0 169.1 180.7 190.7 211.1 13.0–13.9 90.2 110.1 120.1 131.9 140.2 147.2 153.7 160.3 167.4 175.8 187.9 198.3 219.4 14.0–14.9 91.1 112.0 122.3 134.4 142.9 150.1 156.8 163.5 170.8 179.4 191.6 202.2 223.5 15.0–15.9 90.7 112.0 122.5 134.8 143.3 150.5 157.2 163.9 171.2 179.7 191.8 202.3 223.4 16.0–16.9 89.7 111.4 121.9 134.2 142.7 149.8 156.5 163.1 170.2 178.6 190.5 200.7 221.3 17.0–17.9 89.9 111.8 122.4 134.7 143.1 150.3 156.8 163.3 170.3 178.6 190.3 200.3 220.3 18.0–18.9 91.1 113.3 124.0 136.2 144.6 151.6 158.1 164.6 171.5 179.6 191.0 200.8 220.3 Boys’ ages (years) 6.0–6.9 51.6 69.3 77.8 87.4 94.1 99.6 104.6 109.6 114.9 121.1 129.7 137.0 151.2 7.0–7.9 60.0 78.2 87.0 96.9 103.8 109.5 114.7 119.9 125.5 131.9 141.1 148.8 164.0 8.0–8.9 68.2 86.9 95.9 106.1 113.2 119.1 124.6 130.0 135.7 142.5 152.1 160.2 176.5 9.0–9.9 75.5 94.7 103.9 114.4 121.7 127.8 133.4 139.0 145.0 152.0 162.0 170.5 187.6 10.0–10.9 81.2 101.1 110.7 121.5 129.1 135.3 141.1 146.9 153.1 160.4 170.7 179.6 197.5 11.0–11.9 86.4 107.5 117.6 129.0 136.9 143.5 149.5 155.6 162.0 169.7 180.5 189.8 208.8 12.0–12.9 92.2 115.1 125.9 138.1 146.4 153.4 159.8 166.2 173.0 181.1 192.5 202.4 222.5 13.0–13.9 99.8 125.0 136.8 150.0 159.0 166.5 173.3 180.1 187.4 196.0 208.2 218.7 240.1 14.0–14.9 107.8 135.4 148.0 162.1 171.7 179.6 186.9 194.0 201.7 210.7 223.4 234.4 256.8 15.0–15.9 114.3 143.6 156.9 171.5 181.4 189.6 197.0 204.4 212.2 221.4 234.4 245.5 268.3 16.0–16.9 118.6 149.1 162.8 177.7 187.7 195.9 203.4 210.8 218.6 227.8 240.7 251.8 274.4 17.0–17.9 122.1 153.4 167.2 182.2 192.2 200.4 207.8 215.1 222.8 231.8 244.5 255.4 277.6 18.0–18.9 125.4 157.1 170.9 185.8 195.6 203.7 210.9 218.0 225.6 234.4 246.8 257.4 279.0 Smoothed percentiles were calculated using the generalised additive model for location, scale and shape method and weights were applied according to country population. Age at the midpoint of each interval was selected to provide percentiles. For instance, for the interval 6.0–6.9, data presented were those corresponding to an exact age of a 6.5yearold child. P10 indicates 10th percentile; other percentiles are abbreviated accordingly. Data sources are available online (www.fitbackeurope.eu/en-us/fitness-map/sources) and in online supplemental table 1. Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from 7 of 13 OrtegaFB, etal. Br J Sports Med 2023;57:299–310. doi:10.1136/bjsports-2022-106176 Original research Figure 1 Percentile curves for cardiorespiratory and muscular strength tests among European children and adolescents. Smoothed percentiles were calculated using the generalised additive model for location, scale and shape method, and weights were applied according to country population. Data sources are available online (https://www.fitbackeurope.eu/en-us/fitness-map/sources) and in online supplemental table 1. Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from 8 of 13 OrtegaFB, etal. Br J Sports Med 2023;57:299–310. doi:10.1136/bjsports-2022-106176 Original research Table 4 Mean percentile and ranking position of each country according to the pooled EU reference values N 20 m shuttle run test N Handgrip strength N Standing long jump Average rank MS Avg.rank CRF Avg.rank MS&CRF Overall fitness ranking Both Girls Boys Both Girls Boys Both Girls Boys Centile Rank Centile Rank Centile Rank Centile Rank Centile Rank Centile Rank Centile Rank Centile Rank Centile Rank ISL 6127 81.3 1 85.2 1 77.7 1 SLO 4648 75.4 1 74.8 1 75.8 1 ISL 6589 72.4 1 74.7 1 70.2 1 DEN 2 4 3 1 NOR 2302 75.3 2 76.5 2 74.2 2 DEN 5938 64.7 2 64.2 3 65.2 2 CZE 439 69.1 2 72 2 66.2 3 NET 3 – 3 1 SVN 4752 73 3 75.9 3 70.2 4 NET 1713 64.6 3 68.3 2 60.8 6 BUL 497 68 3 67.1 5 68.9 2 FIN 5 5 5 2 DEN 9178 68.9 4 67.7 5 70.8 3 BEL 18 012 61.2 4 60.6 4 61.9 4 SVN 211 629 66.5 4 68.4 4 64.7 5 SVN 7 3 5 2 FIN 2077 66.5 5 68.8 4 63.8 5 LIT 3188 60.1 5 56.4 6 64.4 3 FIN 1393 66 5 67.1 6 64.9 4 CZE 2 9 5.5 3 FRA 11 627 61.4 6 61 8 61.9 7 KOS 742 57.6 6 52.9 10 61.7 5 CRO 22 135 65.9 6 70.1 3 60.7 8 ISL 10 1 5.5 3 CYP 1058 61 7 63.7 6 58.6 10 GER 1399 55.9 7 59.9 5 52 11 SLO 5163 65.2 7 66.3 7 64.4 6 SLO 4 8 6 4 SLO 4709 60.8 8 59.1 11 62.1 6 POL 47 061 55.8 8 53.2 9 58.2 7 SWI 2982 64.4 8 64.6 8 64.2 7 NOR 11 2 6.5 5 CZE 1561 60.7 9 63.2 7 58.4 11 HUN 614 569 54.4 9 55.2 7 53.7 9 EST 4997 61.5 9 62.8 9 60.2 9 BUL 7 – 7 6 GER 1968 59.3 10 60.5 9 58.2 13 SVN 4828 54.1 10 54.3 8 54 8 LIT 12 158 58.6 10 58.5 11 58.7 10 BEL 8.5 12 10.3 7 IRE 1055 59 11 59.8 10 58.2 12 BUL 497 51.5 11 49.3 13 53.6 10 NOR 2490 58.5 11 61.2 10 55.9 11 SWI 8 13 10.5 8 BEL 19 623 57.8 12 54.8 14 60.5 8 EST 1681 51.4 12 52.5 11 50.3 14 AUS 595 56.2 12 57.5 12 54.8 12 GER 11.5 10 10.8 9 SWI 3699 56.7 13 54.7 15 58.7 9 AUS 389 50.6 13 49.6 12 51.6 12 BEL 19 161 55.5 13 56.7 13 54.3 14 LIT 7.5 14 10.8 9 LIT 8397 56.3 14 57.6 12 55 16 MCD 7177 48.8 14 46 18 51.4 13 LAT 7743 54.6 14 54.5 15 54.7 13 CRO 6 16 11 10 UK 40 841 55.7 15 53.5 17 57.7 15 CYP 1204 47.8 15 47.6 15 48 15 SWE 1076 53.4 15 53.4 16 53.4 15 CYP 18.5 7 12.8 11 CRO 595 55.5 16 52.5 18 58.1 14 SWE 2719 46.1 16 45 19 47.2 16 GER 5999 53.4 16 54.6 14 52.2 18 FRA 22 6 14 12 SWE 950 52.3 17 54.8 13 49.4 19 POR 7199 45.8 17 47.8 14 43.7 18 POL 47 326 52.3 17 51.2 20 53.3 16 EST 10.5 18 14.3 13 EST 4647 51.1 18 53.7 16 48.6 20 GRE 688 45.4 18 46.7 16 43.9 17 LUX 1128 51.5 18 52.9 18 50.4 21 SWE 15.5 17 16.3 14 SPA 25 877 48.3 19 46.4 22 50.2 17 ISL 387 44.1 19 46.4 17 42.2 19 HUN 604 114 51.4 19 53.1 17 49.8 22 POL 12.5 21 16.8 15 POR 30 265 47.1 20 44.3 23 50 18 LAT 7743 42.3 20 42.5 21 42.1 20 ITA 21 448 51.4 20 51.8 19 50.9 19 AUS 12.5 22 17.3 16 POL 45 925 46.9 21 48.1 20 45.8 22 UK 23 373 42.3 21 42.9 20 41.6 21 FRA 32 943 51.3 21 50.3 21 52.3 17 IRE 25 11 18 17 AUS 270 46.4 22 49.1 19 43.7 24 IRE 1149 40.3 22 40.6 22 40 24 CYP 1193 49.5 22 48.1 23 50.8 20 LUX 18 – 18 17 ITA 4084 44.6 23 43.1 24 45.9 21 FRA 813 40.1 23 38.8 25 41.5 22 ALB 2114 47.4 23 49.4 22 45.7 25 HUN 14 24 19 18 HUN 5,93,803 44.6 24 47.6 21 41.7 25 ITA 5768 39.9 24 39.3 24 40.4 23 GRE 256 826 44.7 24 42.9 26 46.5 23 UK 25 15 20 19 GRE 1,76,056 44.1 25 42.7 25 45.4 23 SPA 23 097 39.3 25 39.6 23 39 25 SRB 20 341 44.4 25 43 25 45.9 24 POR 22 20 21 20 KOS 741 39.1 26 41.3 26 37.2 27 ALB 1984 17.7 26 16.4 26 18.8 26 SPA 27 218 42.9 26 42.3 28 43.4 27 KOS 18 26 22 21 MCD 1011 38 27 36.2 28 39.7 26 BIH – – – – – – – POR 7715 42.5 27 40.2 30 44.9 26 SPA 25.5 19 22.3 22 SRB 18 772 36.4 28 36.5 27 36.4 28 CRO – – – – – – – IRE 1158 41.8 28 43.5 24 40.1 30 ITA 22 23 22.5 23 LAT 3264 30.1 29 28.6 29 31.4 29 CZE – – – – – – – UK 13 981 41.3 29 40.8 29 41.9 28 GRE 21 25 23 24 BIH 843 26.3 30 24.2 30 28.3 30 FIN – – – – – – – KOS 742 40.8 30 42.9 27 39 31 LAT 17 29 23 24 ALB – – – – – – – LUX – – – – – – – BIH 843 39.2 31 36.5 31 41.6 29 ALB 24.5 – 24.5 25 BUL – – – – – – – NOR – – – – – – – MCD 1023 34.6 32 32.8 32 36.3 32 MCD 23 27 25 26 LUX – – – – – – – SRB – – – – – – – DEN – – – – – – – SRB 25 28 26.5 27 NET – – – – – – – SWI – – – – – – – NET – – – – – – – BIH 31 30 30.5 28 N1 026 077 N787 966 N1 345 159 The threedigit country codes were used to abbreviate the full country names (https://en.wikipedia.org/wiki/List_of_UNDP_country_codes). For each fitness test, the countries were sorted according to their rank position in the Both (girls and boys) column. The ranking for muscular strength was computed as the average of the country ranking position in handgrip and standing long jump tests, while ranking for cardiorespiratory fitness directly reflects the country ranking position in the 20 m shuttle run test. Sexspecific and agespecific percentile values were calculated using available countrylevel data and were averaged across sexes and ages to obtain the mean percentile for each country compared to the European Union reference values. Smoothed percentiles were calculated using the generalised additive model for location, scale and shape method and weights were applied according to country population. Not all countries have representative data, and therefore caution should be paid when interpreting country comparisons presented this study and in the platform. Data sources are available online (www.fitbackeurope.eu/en-us/fitness-map/sources) and in online supplemental table 1. ALB, Albania; AUS, Austria; BEL, Belgium; BIH, Bosnia and Herzegovina; BUL, Bulgaria; CRF, cardiorespiratory fitness; CRO, Croatia; CYP, Cyprus; CZE, Czech Republic; DEN, Denmark; EST, Estonia; FIN, Finland; FRA, France; GER, Germany; GRE, Greece; HUN, Hungary; IRE, Ireland; ISL, Iceland; ITA, Italy; KOS, Kosovo; LAT, Latvia; LIT, Lithuania; LUX, Luxembourg; MCD, North Macedonia; MS, muscular strength; N, sample size and total sample size at the bottom of the table; NET, Netherlands; NOR, Norway; POL, Poland; POR, Portugal; SLO, Slovakia; SPA, Spain; SRB, Serbia; SVN, Slovenia; SWE, Sweden; SWI, Switzerland. Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from 9 of 13 OrtegaFB, etal. Br J Sports Med 2023;57:299–310. doi:10.1136/bjsports-2022-106176 Original research fitness levels over time and use these reference values and the FitBack tool for proper sexspecific and agespecific interpretation. Indeed, the use of fitness surveillance to inform decision making is one of the topranked priorities in paediatric fitness according to international experts.55 As a timely example, fitness monitoring can flag a sudden decline in fitness, and therefore health, due to unique/unexpected situations, such as COVID19 pandemicrelated lockdowns and the substantial, rapid declines in youth fitness levels reported in countries with fitness surveillance systems.56 57 Thus, interventions for specific target groups can be implemented to prevent worse deterioration of fitness levels. Second, fitness monitoring is part of physical education curricula in many European countries, but most European teachers do not currently have access to an easytouse and automatic tool for interpreting sexspecific and agespecific fitness test results. With our article and the FitBack platform, we aimed to contribute to an extensive implementation of fitness monitoring across European schools. In this context, the FitBack platform also provides information to avoid undesirable practices, such as grading students based on their fitness levels and fitness competitions among students, by using fitness testing as an educational tool to facilitate learning and understanding about fitness and its importance to health and sport and setting individual goals for improvement. Such an approach to fitness testing should help improve physical literacy among European youth. Physical literacy can be defined as ‘the motivation, confidence, physical competence, knowledge and understanding to value, and take responsibility for, maintaining purposeful physical pursuits/activities throughout the life course”.58 Despite some debate how fitness and its monitoring correspond to the physical literacy paradigm,59 the FitBack consortium supports the interpretation that fitness and motor skills collectively represent physical competence, which is a key component of physical literacy. In line with this, some physical literacy assessment tools (eg, Canadian Assessment for Physical Literacy and Passport For Life) assess motor skills and physical fitness for physical competence.59 In this context, fitness testing should be much more than just ‘one more school assessment’. Schools are in a unique position to positively affect the lifelong physical activity and physical fitness levels of their students by instilling values and developing skills that will help children throughout their lives. Moreover, the FitBack network has recently been granted by Erasmus+Sport programme with a new project called ‘FitBack4Literacy’, which aims to design and test a physical literacy toolkit including the FitBack reporting system. In the next 3 years (2023–2025), this toolkit will be developed and provided in 15 European languages and made freely available on the FitBack platform. Thus, the FitBack platform will have greater potential to be transformed in pedagogical practice by physical education teachers as well as generalist teachers who also conduct physical education classes in the early schooling years. Thus, enhancing physical fitness through goal setting and an appropriate physical activity programme and tracking individual changes through fitness monitoring may improve students’ physical literacy journey. Those with better fitness education may be more attuned to their body and what is required for good function, and may be able to foster lifelong physical activity habits. Third, our reference values can be used for sport/athletic profiling and monitoring, as well as talent identification and development.43 60 Youth who have fitness levels above the 90th percentiles may be considered talented in certain fitness components, and sports participation could be promoted to them and their family. Likewise, changes in fitness levels in response to a lifestyle intervention could be tracked against our sexspecific and agespecific percentile bands to identify expected, better than expected or worse than expected developmental changes. Figure 2 European fitness maps for cardiorespiratory and muscular strength in children and adolescents. Sexspecific and agespecific percentile values were calculated using available countrylevel data and were averaged across sexes and ages to obtain the mean percentile for each country compared with the EU reference values. Smoothed percentiles were calculated using the generalised additive model for location, scale and shape method, and weights were applied according to country population. Separate European fitness maps for girls and boys for these tests (as well as those for the obesity markers of body mass index and waist circumference) are available online (www.fitbackeurope.eu/en-us/fitness-map). The website map is interactive so that detailed information for each country is shown with the mouseover function. Not all countries have representative data, and therefore, caution should be paid when interpreting country comparisons presented in this study and in the platform. Data sources are available online (www.fitbackeurope.eu/en-us/fitness-map/sources) and in online supplemental table 1. EU, European Union. Protected by copyright. on March 23, 2023 at Granada/Medicina/CC Salud PO Box 750.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2022-106176 on 9 January 2023. Downloaded from 3 Denmark 1996-97 39.6% 16–18 9,342 Nielsen & Andersen, 2003 * Estonia 2017 47.0% 13–14 142 155 158 Sepp et al. 2017 Estonia 201849.9% 8–11 212 215 10.23736/S0022-4707.20.10550-4 Estonia 201651.7% 7–9 256 256 222 226 226 Riso et al. 2019 Estonia 2016 50.9% 8–9 145 146 136 137 137 Reisberg et al. 2020 Estonia 201856.4% 13–17 413 413 413 413 413 Galan-Lopez et al. 2019 Estonia 2017 51.5% 12–18 3,052 3,056 3,103 https://www.sportest.eu/ Estonia 2007-08 47.5% 6–9 725 745 745 De Miguel-Etayo et al. 2014 Finland 2013 47.6% 9–15 970 970 Joensuu et al. 2020 Finland 2007-09 51.3% 9–11 374 374 374 Lintu et al. 2015 Finland 1995 46.6% 13–16 1,109 1,109 1,019 Telama et al. 2002 * France 2006-08 42.2% 12–17 307 308 258 304 306 Ortega et al. 2011 France 2009-13 49.8% 9–16 9,669 10,862 Vanhelst et al. 2016 France 2010-18 51.0% 6–18 31,748 31,748 Vanhelst et al. 2020 France 1997 50.7% 12–15 507 507 507 507 Baquet et al. 2001 * Germany 2006-08 58.9% 12–18 495 473 392 433 445 Ortega et al. 2011 Germany 2009-12 50.0% 6–18 3,039 3,023 3,043 Niessner et al. 2020 Germany 2007-08 48.3% 6–10 638 944 952 De Miguel-Etayo et al. 2014 Germany 1994-95 51.0% 13–16 977 977 863 Telama et al. 2002 * Greece 2014 51.5% 6–18 306,217 304,619 176,844 256,026 Tambalis et al. 2015 Greece 2006-08 48.6% 12–18 369 366 346 359 361 Ortega et al. 2011 Hungary 2006-08 49.5% 13–17 397 393 393 394 395 Ortega et al. 2011 Hungary 2013,2019 51.1% 10–18 580,056 574,375 581,464 591,669 Csányi et al. 2014 ** Hungary 2007-08 49.6% 6–10 548 1,230 1,228 De Miguel-Etayo et al. 2014 Hungary 1994-95 48.7% 13–16 439 439 434 Telama et al. 2002 * Iceland 2017 54.0% 12–16 387 387 387 387 387 Galan-Lopez et al. 2018 Iceland 1998 51.8% 10–16 6,130 6,202 Gunnarsson & Sigríksson 1999 * Ireland 2018-19 49.9% 12–16 1,147 1,002 1,158 1,149 O’Keeffe et al. 2020 Italy 2006-08 38.8% 13–18 321 320 263 266 268 Ortega et al. 2011 Italy 2001-02 55.2% 6–18 4,456 Lovecchio & Zago, 2019 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Br J Sports Med doi: 10.1136/bjsports-2022-106176–13.:10 2023;Br J Sports Med, et al. Ortega FB 4 2004-05 2007-08 2009-10 2010-11 2011-12 Italy 2001-02 2004-05 2007-08 2009-10 2010-11 2011-12 48.7% 12–14 6,197 5,898 Lovecchio & Zago, 2019 Italy 2001-02 2004-05 2007-08 2009-10 2010-11 2011-12 50.9% 12–14 558 Lovecchio & Zago, 2019 Italy 2004-13 53.0% 12–16 3,331 3,331 Lovecchio et al. 2019 Italy 2004-13 51.5% 6–18 4,376 3,705 Lovecchio et al. 2019 Italy 2004-13 48.4% 6–18 629 510 Lovecchio et al. 2020 Italy 2013 62.5% 13–18 789 722 634 738 770 Jemni et al. 2017 Italy 2013-14 49.5% 8–10 99 99 99 Colella et al. 2019 Italy 2007-08 50.2% 6–9 1,160 1,147 De Miguel-Etayo et al. 2014 Italy 1997 52.9% 13–18 3,638 3,203 3,740 3,415 Cilia et al. 1997 * Kosovo 2016-17 52.8% 12–18 742 742 742 742 Berisha & Çilli, 2018 * Latvia 2004-09 53.6% 10–18 7,743 3,400 7,743 7,743 Sauka et al. 2010 * Lithuania 2002, 2012 53.6% 11–18 5,339 5,228 5,600 Venckunas et al. 2018 Lithuania 2016 49.8% 7–11 3,214 3,368 Emeljanovas et al. 2020 Lithuania 1992 46.4% 12–18 3,188 3,188 3,188 3,188 Jürimäe & Volbekiene, 2006 * Luxembourg 2003-06 55.1% 9–18 1,128 Woll et al. 2011 Montenegro 2018-19 51.5% 6–18 5,877 3,601 NCD-RisC, 2020 Netherlands 2017-19 48.9% 8–14 1,713 Anselma et al., 2021 North Macedonia 2012 51.4% 6–11 1,156 1,153 1,159 1,159 1,157 Gontarev et al. 2018 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Br J Sports Med doi: 10.1136/bjsports-2022-106176–13.:10 2023;Br J Sports Med, et al. Ortega FB 5 North Macedonia 2012 51.1% 10–15 6,156 Gontarev & Ruzdija, 2014 * Norway 2004 51.9% 14–16 2,604 2,305 2,490 Haugen et al. 2013 * Poland 2009-10 51.7% 6–18 47,404 45,925 47,326 47,061 Dobosz et al. 2015 Portugal 2008 48.4% 10–18 22,004 21,982 22,004 Santos et al. 2014 Portugal 2018 48.6% 10–18 8,700 8,635 8,289 7,714 7,198 Unpublished data Serbia 2012-13 48.1% 9–18 20,677 18,778 20,341 Milanovic et al. 2019 Slovakia 1993 49.9% 15–15 689 689 689 689 Belej et al.1995 * Slovakia 1996 52.0% 12–15 368 287 323 329 Kasa & Majherová, 1997 * Slovakia 1993-95 0.0% 16–16 95 111 95 Kyselovicová O. 2000 * Slovakia 1993 59.7% 10–18 3,630 3,630 3,630 3,630 Moravec et al. 1996 * Slovakia 2014-15 51.9% 10–12 426 426 Krska et al. 2015 * Slovenia 2013-14 50.6% 6–18 4,745 4,688 4,598 4,670 4,673 Morrison et al. 2021 Slovenia 2018 50.9% 6–18 210,037 206,804 Sorić et al. 2020 Spain 2006-08 48.2% 12–17 413 414 308 397 398 Ortega et al. 2011 Spain 2012-20 49.5% 6–18 14,645 13,952 13,450 14,129 14,155 Iglesias-Soler et al. 2021 Spain 2018 49.4% 9–11 173 173 171 171 173 Cadenas-Sánchez et al. 2021 Spain 2017 48.1% 9–12 558 557 551 554 555 Martínez-Vizcaíno et al. 2022 Spain 2013-14 46.5% 6–7 518 519 522 519 Martínez-Vizcaíno et al. 2020 Spain 2010 50.5% 8–12 1,122 1,061 1,116 1,118 Torrijos-Niño et al. 2014 Spain 2019 52.0% 8–16 284 284 284 289 289 Medrano et al. 2020 Spain 2010-11 51.5% 10–18 905 774 889 879 Unpublished data Spain 2011-12 51.9% 6–18 2,179 2,178 2,128 2,172 2,173 Castro-Piñero et al., 2014 Spain 2000-02 48.4% 12–18 2,474 2,468 2,087 2,431 2,427 Ortega et al. 2005 Spain 2007-08 47.9% 6–10 38 689 712 De Miguel-Etayo et al. 2014 Sweden 2006-08 39.8% 12–18 361 356 255 306 310 Ortega et al. 2011 Sweden 2007-08 48.8% 6–10 677 750 659 De Miguel-Etayo et al. 2014 Sweden 2001 51.6% 11–17 1,726 1,739 Örjan et al. 2005 * Switzerland 2004 48.3% 6–13 496 491 501 Meyer et al. 2014 Switzerland 1996-97 49.5% 10–18 2,959 2,982 Cauderay et al. 2000 * Switzerland 2005 47.9% 12–12 265 265 Shmid et al. 2007 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Br J Sports Med doi: 10.1136/bjsports-2022-106176–13.:10 2023;Br J Sports Med, et al. Ortega FB 6 United Kingdom 2006-10 53.4% 9–18 9,642 9,619 9,162 9,397 Sandercock et al. 2012 United Kingdom 1999-10 51.0% 10–11 27,954 Boddy et al. 2012 * United Kingdom 2000-03 46.5% 10–13 13,152 3,466 13,152 13,152 Ridgers et al. 2006 * United Kingdom 2009-10 51.3% 10–12 821 829 824 Ranson et al. 2015 * 20mSRT indicates the 20-m shuttle run test; HGS, handgrip strength; SLJ, standing long jump; BMI, body mass index; WC, waist circumference *Pseudodata generated from Tomkinson et al. [40]. ** Database included the NETFIT national dataset from 2019. BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Br J Sports Med doi: 10.1136/bjsports-2022-106176–13.:10 2023;Br J Sports Med, et al. Ortega FB 7 Online Supplementary Table 2. Generalized Additive Model for Location, Scale and Shape (GAMLSS) models used to calculate the physical fitness smoothed percentiles. Test Sex Distribution n λ µ σ ν τ SBC 20mSRT Girls BCPE 516,811 1/3 6.16 5.30 3.94 3.39 99,786,154 20mSRT Boys BCPE 546,274 1/2 6.67 5.68 4.13 3.43 123,204,436 HGS Girls BCT 404,897 1/2 8.26 5.01 2.94 2.66 158,351,826 HGS Boys BCT 422,230 1/2 8.32 5.22 3.05 2.41 181,302,718 SLJ Girls BCT 677,639 1/2 9.60 5.42 2.84 2.19 269,865,621 SLJ Boys BCT 706,134 1/2 9.97 5.42 2.77 2.30 286,593,503 BH Girls BCT 717,911 1/2 15.37 5.54 2.10 2.17 211,746,507 BH Boys BCT 741,823 1/2 15.28 5.61 2.12 2.12 229,117,658 BM Girls BCT 717,526 1/2 9.66 5.52 2.88 2.13 225,657,454 BM Boys BCPE 741,678 1/2 9.61 5.61 2.95 3.73 245,281,509 BMI Girls BCT 716,750 1/2 10.54 5.57 2.69 2.08 160,587,571 BMI Boys BCT 740,973 1/2 10.69 5.63 2.71 2.06 170,674,420 WC Girls BCPE 197,832 1/2 10.62 5.20 2.38 3.37 150,768,194 WC Boys BCPE 205,870 1/2 10.75 5.15 2.37 3.43 159,088,298 20mSRT indicates 20-m shuttle run test; HGS, handgrip strength; SLJ, standing long jump; BH, body height; BM, body mass; BMI, body mass index; WC, waist circumference; BCT, Box-Cox t distribution; BCPE, Box-Cox power exponential; SBC, Schwarz Bayesian criterion. Parameters of the fitted distribution are lambda (λ), mu (µ), sigma (σ), nu (ν) and tau (τ) BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Br J Sports Med doi: 10.1136/bjsports-2022-106176–13.:10 2023;Br J Sports Med, et al. Ortega FB 8 Online Supplementary Table 3. Reference values (centiles) for body height (cm) in European children and adolescents (N=1,466,821) Girls Age (yr.) P1 P5 P10 P20 P30 P40 P50 P60 P70 P80 P90 P95 P99 6.0-6.9 yrs 107.6 111.5 113.4 115.7 117.3 118.7 120.0 121.3 122.7 124.4 127.0 129.2 133.9 7.0-7.9 yrs 112.7 116.9 119.0 121.4 123.2 124.7 126.1 127.5 129.0 130.9 133.5 135.9 140.8 8.0-8.9 yrs 117.5 122.0 124.3 127.0 128.9 130.5 132.1 133.6 135.3 137.3 140.2 142.7 147.9 9.0-9.9 yrs 121.7 126.6 129.1 132.0 134.1 135.9 137.6 139.3 141.1 143.3 146.4 149.1 154.6 10.0-10.9 yrs 125.9 131.2 133.9 137.0 139.3 141.2 143.0 144.8 146.7 149.0 152.4 155.2 161.0 11.0-11.9 yrs 132.4 137.9 140.7 144.0 146.3 148.3 150.2 152.1 154.1 156.5 159.9 162.8 168.7 12.0-12.9 yrs 137.9 143.4 146.1 149.4 151.7 153.7 155.5 157.4 159.4 161.7 165.0 167.9 173.5 13.0-13.9 yrs 143.0 148.2 150.9 154.1 156.3 158.2 159.9 161.7 163.6 165.9 169.0 171.8 177.1 14.0-14.9 yrs 146.1 151.2 153.8 156.8 158.9 160.8 162.5 164.2 166.0 168.1 171.2 173.8 178.8 15.0-15.9 yrs 148.0 152.9 155.4 158.4 160.5 162.3 163.9 165.6 167.4 169.5 172.4 174.9 179.8 16.0-16.9 yrs 148.7 153.5 156.0 158.9 161.0 162.8 164.4 166.0 167.8 169.9 172.8 175.2 179.9 17.0-17.9 yrs 149.2 154.0 156.5 159.4 161.5 163.2 164.8 166.5 168.2 170.2 173.1 175.5 180.1 18.0-18.9 yrs 150.0 154.8 157.2 160.1 162.2 163.9 165.5 167.1 168.8 170.8 173.6 176.0 180.6 Boys Age (yr.) P1 P5 P10 P20 P30 P40 P50 P60 P70 P80 P90 P95 P99 6.0-6.9 yrs 108.5 112.4 114.4 116.7 118.3 119.7 121.0 122.4 123.8 125.6 128.1 130.4 135.3 7.0-7.9 yrs 113.8 117.9 120.0 122.4 124.2 125.7 127.1 128.5 130.0 131.9 134.6 137.0 141.9 8.0-8.9 yrs 118.7 123.1 125.4 128.0 129.9 131.5 133.1 134.6 136.2 138.2 141.1 143.6 148.7 9.0-9.9 yrs 122.8 127.5 129.9 132.8 134.9 136.6 138.3 139.9 141.7 143.8 146.9 149.5 154.8 10.0-10.9 yrs 125.8 131.0 133.6 136.7 138.9 140.8 142.6 144.4 146.3 148.6 151.8 154.6 160.1 11.0-11.9 yrs 130.5 136.2 139.0 142.5 144.9 147.0 148.9 150.9 153.0 155.5 159.0 161.9 167.8 12.0-12.9 yrs 135.0 141.1 144.3 148.0 150.6 152.9 154.9 157.0 159.3 161.9 165.6 168.7 174.9 13.0-13.9 yrs 141.4 147.8 151.1 155.0 157.7 160.0 162.2 164.4 166.7 169.4 173.2 176.4 182.5 14.0-14.9 yrs 148.3 154.7 157.9 161.7 164.4 166.7 168.8 170.9 173.2 175.8 179.5 182.6 188.6 15.0-15.9 yrs 154.0 160.1 163.2 166.8 169.4 171.5 173.6 175.6 177.7 180.2 183.7 186.6 192.1 16.0-16.9 yrs 157.6 163.3 166.3 169.7 172.2 174.2 176.1 178.0 180.0 182.4 185.6 188.3 193.5 17.0-17.9 yrs 159.6 165.2 168.0 171.3 173.7 175.6 177.5 179.3 181.2 183.4 186.6 189.1 194.0 18.0-18.9 yrs 161.0 166.5 169.3 172.5 174.8 176.7 178.5 180.3 182.1 184.3 187.3 189.8 194.5 Smoothed percentiles were calculated using the Generalized Additive Model for Location, Scale and Shape (GAMLSS) method and weights were applied according to country population. Age at the midpoint of each interval was selected to provide percentiles. For instance, for the interval 6.0–6.9, data presented were those corresponding to an exact age of a 6.5-year-old child. P10 indicates 10th percentile; other percentiles are abbreviated accordingly. Data sources are available at: www.fitbackeurope.eu/en-us/fitness-map/sources. BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Br J Sports Med doi: 10.1136/bjsports-2022-106176–13.:10 2023;Br J Sports Med, et al. Ortega FB 9 Online Supplementary Table 4. Reference values (centiles) for body mass (kg) in European children and adolescents (N=1,466,295) Girls Age (yr.) P1 P5 P10 P20 P30 P40 P50 P60 P70 P80 P90 P95 P99 6.0-6.9 yrs 16.3 17.8 18.7 19.9 20.9 21.9 22.8 23.8 25.0 26.6 29.2 31.7 38.0 7.0-7.9 yrs 17.8 19.7 20.8 22.3 23.5 24.6 25.8 27.1 28.6 30.5 33.7 36.8 44.6 8.0-8.9 yrs 19.6 21.9 23.3 25.1 26.6 28.0 29.4 30.9 32.7 35.1 39.0 42.8 52.3 9.0-9.9 yrs 21.5 24.2 25.8 28.0 29.8 31.4 33.1 34.9 37.1 39.9 44.4 49.0 60.2 10.0-10.9 yrs 23.5 26.7 28.6 31.2 33.2 35.1 37.0 39.1 41.6 44.8 50.1 55.3 68.3 11.0-11.9 yrs 26.2 29.9 32.1 35.1 37.4 39.5 41.7 44.1 46.9 50.5 56.4 62.3 77.0 12.0-12.9 yrs 29.6 33.8 36.2 39.4 42.0 44.3 46.6 49.2 52.1 56.0 62.2 68.4 84.0 13.0-13.9 yrs 33.5 38.0 40.5 43.9 46.5 48.9 51.2 53.8 56.8 60.7 66.9 73.2 88.8 14.0-14.9 yrs 36.7 41.4 44.0 47.4 49.9 52.3 54.6 57.1 60.0 63.8 69.9 75.9 91.2 15.0-15.9 yrs 38.9 43.6 46.2 49.5 52.0 54.3 56.5 59.0 61.7 65.4 71.2 77.1 92.4 16.0-16.9 yrs 40.0 44.9 47.5 50.7 53.2 55.4 57.6 59.9 62.6 66.2 72.0 77.9 93.7 17.0-17.9 yrs 40.6 45.5 48.1 51.4 53.8 56.0 58.1 60.4 63.1 66.6 72.5 78.5 95.5 18.0-18.9 yrs 40.8 45.9 48.5 51.8 54.2 56.3 58.4 60.7 63.4 66.9 72.8 79.2 97.9 Boys Age (yr.) P1 P5 P10 P20 P30 P40 P50 P60 P70 P80 P90 P95 P99 6.0-6.9 yrs 16.7 18.3 19.2 20.5 21.5 22.4 23.3 24.2 25.4 27.0 29.6 32.3 39.5 7.0-7.9 yrs 18.4 20.3 21.4 22.9 24.1 25.2 26.3 27.5 29.0 30.9 34.1 37.4 45.8 8.0-8.9 yrs 20.3 22.5 23.8 25.6 27.1 28.5 29.8 31.3 33.1 35.5 39.4 43.3 53.1 9.0-9.9 yrs 22.1 24.6 26.2 28.3 30.1 31.7 33.4 35.2 37.3 40.1 44.7 49.3 60.4 10.0-10.9 yrs 23.7 26.7 28.5 31.0 33.0 34.9 36.8 39.0 41.5 44.8 50.1 55.3 68.0 11.0-11.9 yrs 25.8 29.3 31.4 34.3 36.7 38.9 41.1 43.6 46.5 50.3 56.5 62.5 77.0 12.0-12.9 yrs 28.6 32.6 35.0 38.4 41.1 43.6 46.1 48.9 52.1 56.4 63.3 70.1 86.4 13.0-13.9 yrs 32.4 37.0 39.8 43.6 46.6 49.3 52.0 55.0 58.5 63.1 70.6 78.0 95.7 14.0-14.9 yrs 36.9 42.1 45.3 49.4 52.5 55.4 58.2 61.3 64.9 69.7 77.5 85.1 103.5 15.0-15.9 yrs 41.4 47.0 50.3 54.6 57.8 60.8 63.6 66.6 70.2 75.0 82.8 90.5 109.0 16.0-16.9 yrs 44.8 50.6 54.0 58.4 61.7 64.6 67.3 70.3 73.8 78.5 86.2 93.9 112.3 17.0-17.9 yrs 47.1 53.0 56.5 60.8 64.1 67.0 69.7 72.6 76.1 80.7 88.4 95.9 114.3 18.0-18.9 yrs 48.8 54.8 58.2 62.6 65.8 68.7 71.4 74.3 77.7 82.3 89.9 97.5 116.0 Smoothed percentiles were calculated using the Generalized Additive Model for Location, Scale and Shape (GAMLSS) method and weights were applied according to country population. Age at the midpoint of each interval was selected to provide percentiles. For instance, for the interval 6.0–6.9, data presented were those corresponding to an exact age of a 6.5-year-old child. P10 indicates 10th percentile; other percentiles are abbreviated accordingly. Data sources are available at: www.fitbackeurope.eu/en-us/fitness-map/sources. BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Br J Sports Med doi: 10.1136/bjsports-2022-106176–13.:10 2023;Br J Sports Med, et al. Ortega FB 10 Online Supplementary Table 5. Reference values (centiles) for body mass index (kg/m2) in European children and adolescents (N=1,464,795) Girls Age (yr.) P1 P5 P10 P20 P30 P40 P50 P60 P70 P80 P90 P95 P99 6.0-6.9 yrs 12.3 13.2 13.7 14.3 14.9 15.4 15.8 16.4 17.0 17.8 19.1 20.4 23.4 7.0-7.9 yrs 12.4 13.3 13.8 14.6 15.2 15.7 16.3 16.8 17.5 18.5 19.9 21.4 25.1 8.0-8.9 yrs 12.6 13.6 14.2 15.0 15.7 16.3 16.9 17.5 18.3 19.4 21.0 22.7 27.0 9.0-9.9 yrs 12.9 14.0 14.6 15.5 16.2 16.8 17.5 18.2 19.1 20.2 22.0 23.9 28.7 10.0-10.9 yrs 13.1 14.2 14.9 15.9 16.6 17.3 18.0 18.8 19.7 20.9 22.8 24.8 30.0 11.0-11.9 yrs 13.4 14.6 15.4 16.3 17.1 17.8 18.5 19.3 20.3 21.5 23.6 25.7 31.3 12.0-12.9 yrs 13.9 15.2 15.9 16.9 17.7 18.5 19.2 20.0 21.0 22.3 24.4 26.6 32.3 13.0-13.9 yrs 14.6 15.9 16.7 17.7 18.5 19.2 20.0 20.8 21.8 23.1 25.2 27.4 33.2 14.0-14.9 yrs 15.2 16.5 17.3 18.3 19.1 19.8 20.6 21.4 22.4 23.6 25.7 27.9 33.8 15.0-15.9 yrs 15.5 16.9 17.7 18.7 19.5 20.2 21.0 21.8 22.7 24.0 26.0 28.2 34.1 16.0-16.9 yrs 15.8 17.2 18.0 19.0 19.8 20.5 21.2 22.0 22.9 24.2 26.2 28.4 34.5 17.0-17.9 yrs 15.9 17.3 18.1 19.1 19.9 20.6 21.3 22.1 23.0 24.3 26.3 28.5 35.0 18.0-18.9 yrs 15.9 17.4 18.1 19.1 19.9 20.6 21.3 22.1 23.0 24.2 26.3 28.6 35.4 Boys Age (yr.) P1 P5 P10 P20 P30 P40 P50 P60 P70 P80 P90 P95 P99 6.0-6.9 yrs 12.7 13.5 13.9 14.5 15.0 15.5 15.9 16.4 17.0 17.8 19.1 20.4 23.7 7.0-7.9 yrs 12.7 13.6 14.1 14.7 15.3 15.8 16.3 16.8 17.5 18.4 19.9 21.4 25.4 8.0-8.9 yrs 12.9 13.8 14.4 15.1 15.7 16.3 16.9 17.5 18.2 19.2 20.9 22.7 27.4 9.0-9.9 yrs 13.2 14.2 14.8 15.6 16.2 16.8 17.5 18.2 19.0 20.1 22.0 23.9 29.3 10.0-10.9 yrs 13.4 14.4 15.1 15.9 16.6 17.3 18.0 18.7 19.6 20.8 22.9 25.0 31.1 11.0-11.9 yrs 13.6 14.7 15.4 16.3 17.1 17.8 18.5 19.3 20.3 21.6 23.8 26.1 32.7 12.0-12.9 yrs 14.0 15.1 15.9 16.8 17.6 18.3 19.1 19.9 20.9 22.3 24.5 26.9 33.8 13.0-13.9 yrs 14.4 15.7 16.4 17.4 18.2 19.0 19.7 20.6 21.6 23.0 25.3 27.7 34.5 14.0-14.9 yrs 15.0 16.3 17.0 18.1 18.9 19.6 20.4 21.3 22.3 23.6 25.9 28.3 35.1 15.0-15.9 yrs 15.5 16.9 17.7 18.7 19.5 20.3 21.1 21.9 23.0 24.3 26.6 29.0 35.7 16.0-16.9 yrs 16.0 17.4 18.2 19.3 20.1 20.9 21.7 22.5 23.5 24.9 27.2 29.5 36.2 17.0-17.9 yrs 16.3 17.7 18.6 19.6 20.5 21.3 22.1 22.9 23.9 25.3 27.5 29.9 36.6 18.0-18.9 yrs 16.5 18.0 18.9 20.0 20.8 21.6 22.4 23.2 24.2 25.6 27.8 30.2 37.0 Smoothed percentiles were calculated using the Generalized Additive Model for Location, Scale and Shape (GAMLSS) method and weights were applied according to country population. Age at the midpoint of each interval was selected to provide percentiles. For instance, for the interval 6.0–6.9, data presented were those corresponding to an exact age of a 6.5-year-old child. P10 indicates 10th percentile; other percentiles are abbreviated accordingly. Data sources are available at: www.fitbackeurope.eu/en-us/fitness-map/sources. BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Br J Sports Med doi: 10.1136/bjsports-2022-106176–13.:10 2023;Br J Sports Med, et al. Ortega FB 11 Online Supplementary Table 6. Reference values (centiles) for waist circumference (cm) in European children and adolescents (N=409,580) Girls Age (yr.) P1 P5 P10 P20 P30 P40 P50 P60 P70 P80 P90 P95 P99 6.0-6.9 yrs 45.2 47.9 49.5 51.6 53.2 54.7 56.1 57.7 59.4 61.7 65.2 68.5 76.0 7.0-7.9 yrs 46.5 49.4 51.1 53.4 55.2 56.9 58.6 60.5 62.5 65.2 69.3 73.1 81.5 8.0-8.9 yrs 48.0 51.0 52.8 55.3 57.4 59.3 61.3 63.4 65.8 68.8 73.5 77.8 87.2 9.0-9.9 yrs 49.0 52.2 54.1 56.8 59.0 61.0 63.2 65.5 68.2 71.5 76.6 81.3 91.6 10.0-10.9 yrs 50.2 53.4 55.4 58.2 60.5 62.7 64.9 67.4 70.2 73.7 79.1 84.1 95.3 11.0-11.9 yrs 51.6 55.0 57.1 59.9 62.3 64.5 66.8 69.2 72.1 75.7 81.2 86.5 98.3 12.0-12.9 yrs 53.0 56.4 58.5 61.4 63.7 65.8 68.1 70.5 73.2 76.7 82.2 87.5 99.4 13.0-13.9 yrs 54.3 57.7 59.8 62.6 64.8 66.9 69.0 71.3 73.9 77.2 82.5 87.6 99.4 14.0-14.9 yrs 55.5 58.9 61.0 63.7 65.9 67.9 69.8 72.0 74.4 77.6 82.7 87.6 99.2 15.0-15.9 yrs 56.5 59.9 62.0 64.6 66.7 68.6 70.5 72.5 74.9 77.9 82.8 87.6 99.1 16.0-16.9 yrs 57.3 60.8 62.8 65.4 67.5 69.3 71.1 73.1 75.3 78.3 83.2 87.9 99.5 17.0-17.9 yrs 57.8 61.2 63.2 65.8 67.8 69.6 71.4 73.3 75.5 78.5 83.3 88.1 100.0 18.0-18.9 yrs 57.8 61.3 63.3 65.9 67.9 69.6 71.4 73.2 75.4 78.3 83.1 88.0 100.3 Boys Age (yr.) P1 P5 P10 P20 P30 P40 P50 P60 P70 P80 P90 P95 P99 6.0-6.9 yrs 45.9 48.8 50.5 52.6 54.2 55.6 56.9 58.3 59.9 62.1 65.7 69.3 78.3 7.0-7.9 yrs 47.3 50.3 52.1 54.4 56.1 57.7 59.3 61.0 63.0 65.5 69.7 73.7 83.4 8.0-8.9 yrs 49.0 52.1 53.9 56.4 58.4 60.2 62.1 64.1 66.4 69.4 74.2 78.7 89.3 9.0-9.9 yrs 50.4 53.5 55.4 58.0 60.2 62.2 64.3 66.6 69.2 72.6 77.9 82.8 94.3 10.0-10.9 yrs 51.6 54.8 56.8 59.6 61.9 64.0 66.3 68.8 71.7 75.3 81.0 86.4 98.8 11.0-11.9 yrs 53.0 56.3 58.4 61.3 63.6 65.9 68.3 70.9 73.9 77.7 83.7 89.4 102.6 12.0-12.9 yrs 54.4 57.8 60.0 62.9 65.3 67.6 69.9 72.5 75.5 79.3 85.3 91.1 104.8 13.0-13.9 yrs 56.2 59.7 61.9 64.8 67.2 69.4 71.7 74.1 77.0 80.7 86.6 92.4 106.1 14.0-14.9 yrs 58.0 61.7 63.9 66.9 69.2 71.3 73.4 75.8 78.5 82.0 87.7 93.3 107.1 15.0-15.9 yrs 59.7 63.5 65.8 68.7 71.0 73.1 75.1 77.2 79.8 83.2 88.7 94.3 108.2 16.0-16.9 yrs 61.2 65.2 67.5 70.5 72.7 74.7 76.6 78.7 81.1 84.4 90.0 95.6 110.1 17.0-17.9 yrs 62.1 66.4 68.8 71.8 74.0 75.9 77.7 79.7 82.1 85.3 90.8 96.6 112.0 18.0-18.9 yrs 62.5 66.9 69.3 72.3 74.5 76.4 78.1 80.0 82.3 85.4 90.9 96.8 113.2 Smoothed percentiles were calculated using the Generalized Additive Model for Location, Scale and Shape (GAMLSS) method and weights were applied according to country population. Age at the midpoint of each interval was selected to provide percentiles. For instance, for the interval 6.0–6.9, data presented were those corresponding to an exact age of a 6.5-year-old child. P10 indicates 10th percentile; other percentiles are abbreviated accordingly. Data sources are available at: www.fitbackeurope.eu/en-us/fitness-map/sources. BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Br J Sports Med doi: 10.1136/bjsports-2022-106176–13.:10 2023;Br J Sports Med, et al. Ortega FB 12 Online Supplementary Table 7. Mean percentile and ranking position of each country according to the pooled EU reference values for body height and weight. Body height Body weight Both Girls Boys Both Girls Boys N Centile Rank Centile Rank Centile Rank N Centile Rank Centile Rank Centile Rank MNE 6,551 67.4 1 67.2 1 67.6 1 CRO 23,646 58.2 1 58.9 1 57.3 3 EST 4,113 62.9 2 62.3 3 63.4 2 MNE 6,460 57.6 2 55.4 3 59.7 1 CRO 23,651 60.3 3 62.8 2 57.4 6 MCD 1,022 56.2 3 53.6 8 58.7 2 CZE 1,637 58.9 4 59.6 5 58.3 3 GRE 325,357 55.7 4 54.9 4 56.5 4 SVN 215,493 58.2 5 58.2 6 58.3 4 ISL 387 55.3 5 55.8 2 54.9 6 NOR 2,659 57.1 6 59.7 4 54.7 10 EST 4,091 54.9 6 54.2 6 55.6 5 SRB 20,683 57.0 7 56.5 7 57.6 5 SVN 215,211 53.9 7 53.7 7 54.2 8 DEN 1,041 55.6 8 54.2 14 57.2 7 SRB 20,695 53.4 8 52.5 11 54.3 7 ISL 387 54.7 9 54.4 11 54.9 9 HUN 601,487 53.3 9 53.3 9 53.3 10 GRE 325,078 54.6 10 54.3 13 55.0 8 SPA 26,129 53.2 10 53.1 10 53.3 9 POL 49,550 54.0 11 53.4 15 54.6 11 CZE 1,636 52.0 11 52.3 12 51.7 12 GER 5,229 53.6 12 54.3 12 53.0 13 NOR 2,608 51.8 12 54.3 5 49.6 17 HUN 601,537 53.5 13 53.0 16 54.0 12 AUS 630 51.3 13 50.2 15 52.5 11 LIT 11,854 52.9 14 54.9 10 51.0 18 IRE 1,149 50.2 14 50.1 16 50.3 14 LAT 7,743 52.6 15 54.9 9 50.5 19 GER 5,224 50.0 15 50.3 14 49.7 15 SLO 5,209 52.5 16 55.2 8 50.4 20 POL 49,525 49.4 16 47.8 21 50.9 13 FIN 2,453 51.8 17 52.1 17 51.5 16 ITA 26,467 49.2 17 48.7 18 49.7 16 AUS 630 51.5 18 50.4 18 52.6 15 BEL 23,019 48.1 18 50.7 13 45.5 19 BUL 497 51.4 19 49.8 21 52.8 14 POR 30,731 47.9 19 49.0 17 46.6 18 MCD 1,022 50.6 20 50.0 19 51.3 17 SWE 2,098 46.7 20 48.2 19 45.0 22 IRE 1,161 49.5 21 49.3 23 49.7 21 UK 22,810 46.1 21 47.0 24 45.2 20 ITA 26,568 49.0 22 49.8 20 48.2 22 DEN 1,042 46.0 22 46.7 25 45.2 21 BEL 22,973 48.8 23 49.6 22 48.0 23 FIN 2,453 46.0 23 47.4 23 44.4 25 BIH 843 47.2 24 49.1 24 45.5 25 LAT 7,743 45.8 24 47.5 22 44.4 26 SPA 26,144 45.8 25 45.0 28 46.6 24 BIH 843 45.6 25 48.1 20 43.3 28 FRA 42,700 45.4 26 46.0 26 44.8 26 LIT 11,885 44.7 26 44.9 26 44.4 24 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Br J Sports Med doi: 10.1136/bjsports-2022-106176–13.:10 2023;Br J Sports Med, et al. Ortega FB