1  Review of literature

1.1 Physical fitness

The term physical fitness has served as an umbrella term for a variety of different concepts and perspectives. In this thesis, physical fitness is understood as a multidimensional concept that includes: (1) the ability to perform daily tasks with vigor and alertness, without excessive fatigue, and with sufficient energy to enjoy leisure activities and cope with unforeseen emergencies (Caspersen et al., 1985; Corbin et al., 2000; Howley & Franks, 1986; R. Pate et al., 2012; R. R. Pate, 1983) and (2) is related to current and future health status (Corbin et al., 2000; Howley & Franks, 1986; Malina, 2004; R. Pate et al., 2012). Thus, physical fitness is an umbrella term referring to several components, such as cardiorespiratory fitness, muscular fitness, motor fitness, flexibility, and body composition, each with further subcomponents. Table 1.1 provides an overview, including definitions of different (sub)components.

Table 1.1: Components of physical fitness and definitions

fitness components	definition
cardiorespiratory fitness	ability of circulatory and respiratory systems to supply energy during sustained physical activity and to eliminate fatigue products after energy supply (Corbin et al., 1978)
muscular fitness
muscular endurance	(1) ability of a muscle or muscle group to exert force over many repetitions or successive loads (Corbin et al., 1978) or (2) sustaining voluntary contractions over a prolonged period of time (Ortega et al., 2014)
muscular strength	ability of a muscle or muscle group to exert/generate an external force (Corbin et al., 1978; Ortega et al., 2014)
muscular power	ability of a muscle or muscle group to perform a maximum dynamic contraction in a short time (Ortega et al., 2014)
motor fitness
agility	(1) ability to change position of the whole body in space quickly and precisely (Corbin et al., 1978; Ortega et al., 2014) or (2) a combination of speed, balance, strength, and coordination (Ortega et al., 2008)
balance	ability to maintain balance while stationary or in motion (Corbin et al., 1978)
coordination	ability to use senses, such as vision and hearing, together with body parts to perform motor tasks smoothly and accurately (Corbin et al., 1978)
power	(1) ability, which refers to speed at which a person can perform work (Corbin et al., 1978), or (2) ability to exert force quickly (Howley & Franks, 1986)
reaction time	ability that refers to time elapsed between stimulation and onset of response (Corbin et al., 1978)
speed	ability to perform movements in a short period of time (Corbin et al., 1978)
flexibility	ability of a muscle or group of muscles to move a joint freely through full range of motion (Corbin et al., 1978; Ortega et al., 2014)
body composition	health-related component referring to the relative amount of muscle, fat, bone, and other vital parts of the body (Corbin et al., 1978)

Cardiorespiratory fitness can also be referred to as cardiorespiratory endurance (Corbin et al., 1978), cardiorespiratory function (Howley & Franks, 1986), aerobic fitness (Léger et al., 1988; Tomkinson, 2007), cardiovascular fitness, aerobic capacity, aerobic power, physical work capacity, and maximal oxygen consumption (VO2max) (Ortega et al., 2014). Similarly, musculoskeletal fitness is synonymous with muscular fitness (Smith et al., 2014).

Historically, physical fitness in children and adolescents was first conceptualized in the late 18th century by physical education teachers and focused primarily on muscular strength and flexibility with the goal of improving ‘health fitness’. First assessments of physical fitness were made using performance based tests such as high jump, pull-ups, sprints, standing and running long jump, rope climb, push-ups, and shot put (Dalen et al., 1953). During World War II, these concepts gained traction by incorporating the military’s understanding of physical fitness, which traditionally focused on ‘motor fitness’. ‘Motor fitness’ was understood as adequate abilities in a wide range of movement factors, with an emphasis on athletic performance rather than health outcomes (R. R. Pate, 1983). When publications suggested a decline in fitness among American youth¹ (Kraus & Hirschland, 1954), policies were introduced to promote youth health through physical fitness (Hunsicker & Reiff, 1976). As promotion of physical fitness gained importance over time, the understanding of ‘being fit’ evolved as well. The shift occurred from a broader ‘motor fitness’ (i.e., cardiorespiratory endurance, muscle strength, body composition, flexibility, agility, strength, speed, balance) to a narrower ‘health-related physical fitness’ (i.e., cardiorespiratory endurance, muscle strength, body composition, flexibility). The focus herein was on specific components of ‘motor fitness’ that could be associated with health parameters or disease prevention (R. R. Pate, 1983).

Differentiation between ‘motor fitness’ and ‘health-related physical fitness’ over time translated into the distinction between skill-related and health-related components of physical fitness (Blair et al., 1983; Caspersen et al., 1985; Corbin et al., 1978; R. R. Pate, 1983). Following Caspersen et al. (1985), health-related physical fitness includes cardiorespiratory fitness, muscular fitness excluding the muscle strength component, flexibility, and body composition, while skill-related components of physical fitness include the listed subcomponents of motor fitness (see Table 1.1). Of note, the retirement of flexibility as a component of physical fitness has been suggested since it has comparatively little predictive power for meaningful health and performance outcomes in healthy individuals (Nuzzo, 2020). In addition, it is worth noting that a framework for health-related physical fitness proposed by Howley et al. (1986) focused on relative leanness rather than body composition² and further incorporated an arousal-relaxation balance, referring to the balance between relaxation (i.e., dominance of the parasympathetic nervous system) and arousal (i.e., dominance of the sympathetic nervous system) in relation to personality traits, external stress, and physical activity³.

Another differentiation in context of physical fitness occurred between motor skills (‘motorische Fertigkeiten’) and motor abilities (‘motorische Fähigkeiten’). Motor abilities represent latent constructs here, describing general processes of control and functionality that inform and influence the execution of specific movements and motor skills, with motor skills representing specific patterns of movement to accomplish movement tasks (Roth & Willimczik, 1999). Motor abilities (similar to (sub)components of physical fitness) can be divided into (1) conditional abilities such as cardiorespiratory fitness (‘Ausdauer’), muscular strength/fitness (‘Kraft’), and speed (‘Schnelligkeit’), (2) coordinative abilities such as speed (‘Schnelligkeit’) and coordination (‘Koordination’) as well as (3) flexibility (‘Beweglichkeit’) as a passive system for energy transfer. These motor abilities are further separated into [1] aerobic cardiorespiratory fitness (’Aerobe Ausdauer‘), [2] anaerobic cardiorespiratory fitness (’Anaerobe Ausdauer‘), [3] muscular endurance (’Kraftausdauer‘), [4] muscular maximum strength/force (’Maximalkraft‘), [5] muscular speed (’Schnellkraft‘), [6] action speed (’Aktionsschnelligkeit‘), [7] reaction speed (’Reaktionsschnelligkeit‘), [8] coordination (time pressure) (’Koordination (Zeitdruck)’), and [9] coordination (precision) (’Koordination (Präzision)’)⁴ (Bös, 2000).

The approach of Bös (2000) assumes that only motor abilities, but not motor skills, can be measured directly. Accordingly, assessment of physical fitness constructs (or, in case of Bös et al. (2000), motor abilities) is done via assessment of motor skills, from which physical fitness information is inferred⁵. Assessment of physical fitness in children and adolescents is usually carried out with field-based tests, as these can easily be administered with little equipment and staff and have good validity and reliability (Artero et al., 2011; Castro-Piñero et al., 2010; Oberger et al., 2006; Ruiz et al., 2011; Safrit, 1990). This allows time-efficient testing of large numbers of subjects (Castro-Piñero et al., 2009; Golle, 2015; Golle et al., 2015).

1.1.1 Maturity and gender

In children, physical fitness is substantially affected by growth and maturation processes that can improve physical fitness irrespective of children’s physical activity (Malina, 2004; Malina & Katzmarzyk, 2006). While growth and maturation are intertwined, growth usually refers to directly measurable changes in body size, weight, proportions and composition, whereas maturation refers to processes that lead the body to a mature (adult) state⁶ (Manna, 2014). While all body tissues, organs and organ systems mature at different rates, maturation tends to be independent of chronological age, depending on respective tissues/organs/systems (G. P. Beunen et al., 2006). Skeletal maturity is considered the best single indicator of maturation in children as it is present in all children and is not primarily dependent on maturation of other tissues/organs (Acheson, 1966; G. P. Beunen et al., 2006; G. Beunen & Malina, 1988). Skeletal maturity is usually determined by age at peak height velocity, which refers to the adolescent growth spurt (G. Beunen & Malina, 1988; R. Malina, 1988; Tanner, 1951). The most accurate assessment of skeletal maturity and age at peak height velocity uses radiological examinations of one or more bones (Chumela et al., 1989; Greulich & Pyle, 1959), however, these examinations are expensive, equipment-intensive, require expert interpretation, and carry risks of radiation exposure (Mirwald et al., 2002). Alternatives were proposed by Mirwald et al. (2002), who used longitudinal data from children with predetermined ages at peak height velocity ranging from four years before to three years after peak height velocity. Based on this information, an equation was generated including age, standing height, sitting height and mass, to calculate gender-specific estimates. A similar approach was adopted by Moore et al. (2015), who used a larger data set and created simpler gender-specific equations using only age, standing height, and sitting height to estimate age at maximum height velocity⁷.

With regard to gendered determination of maturity, it is important to clarify uses of gender and ‘sex’ in their relations with each other. It is common practice to classify participants as either male or female under the umbrella term ‘sex’⁸. Feminist scholars, scientists, and activists in particular have expressed concern about (mis)uses of these terms over past decades (even centuries), calling for (1) a more nuanced understanding of an individual’s biological characteristics (i.e., ‘sex’) and socially constructed reality in relation to these characteristics (i.e., ‘gender’), (2) an awareness of their interrelationships and interdependencies, and (3) a move away from a binary understanding of these two terms (Butler, 1990; Fausto-Sterling, 2020; Johnson & Repta, 2012; Jordan-Young & Karkazis, 2019). Classification of ‘sex’ into two distinct categories based on biological properties does not relate unambiguously to individual biological characteristics. In a scientific context, commonly used properties are chromosomes, gonads, external and internal genitalia, secondary ‘sex’ characteristics, and hormones, which do not allow for a ‘natural’ binary definition within and among themselves (Ainsworth, 2015; Blackless et al., 2000; Fausto-Sterling, 2020; Jordan-Young & Karkazis, 2019; Oudshoorn, 2005). For example, classification of maturity based on Tanner stages uses inspection of external genitalia in boys and secondary sexual characteristics in boys and girls⁹ (Tanner & Whitehouse, 1981). Of note, study on birth rates of intersex people (i.e., people who cannot be identified as “ideally male” or “ideally female” based on their chromosomes, gonads, and internal and external genitalia) found that the birth rate of intersex children is ~1.728% (Blackless et al., 2000), but they are usually considered “not intended by nature” and require surgical “correction” (Fausto-Sterling, 2020). Alternative concepts to a binary ‘sex’ classification can be found, for example, in the Dominican Republic or in New Guinea, where children with dihydrotestosterone deficiency¹⁰ are recognised as a third ‘sex’ (G. Herdt, 1990; G. H. Herdt & Davidson, 1988; Rivera-Garza & Herdt, 1996). Additionally, Western scientists such as Fausto-Sterling (Fausto-Sterling & Trajanoski, 2004) have proposed a system of five sexes (i.e., female, female pseudo-hermaphrodite, true hermaphrodite, male pseudo-hermaphrodite and male), still based on external primary genitalia but allowing for more variability and reducing the need for imminent surgical intervention on infants.

In contrast to ‘sex’, gender is held as continuous construction of specific roles in representation of society (i.e., man and woman as representations for Western societies). This construction occurs in a specific cultural system of meaning in which value is assigned according to social values and hierarchies. Thus, it is linked to political and economic factors in every society/culture (Lauretis, 1987). Gender can be based on individuals identification with an existing gender-identity, in social situations especially in presence of systems of governance however, the construction of gender is still mostly tied to assumptions of a “true” and “binary” ‘sex’ (Butler, 1990; Fausto-Sterling, 2020; Lugones, 2010; Westbrook & Schilt, 2014). Gender could therefore be based on the individual’s identification with a gender identity. However, in social situations, especially in presence of governance systems, construction of gender is currently still mostly tied to a ‘true’ and ‘binary’ gender assumption (Butler, 1990; Fausto-Sterling, 2020; Lugones, 2010; Westbrook & Schilt, 2014). In these social situations, the basis of gender assignment¹¹ may occur in forms such as visual cues in face-to-face interactions, presence of genitalia in sexual situations or even legal cases or political decisions¹², or symbolic reassignment of trans people from one side of the gender binary to the other, which may be required by officials to legally confirm their gender (Westbrook & Schilt, 2014). It is important to note that in processes of colonialism, a binary division of gender into ‘men’ and ‘women’ was reserved for colonisers (i.e., bourgeois white Europeans), which also classified them as ‘human’. Colonised (i.e., indigenous peoples) were not classified into ‘men’ and ‘women’ and thus were classified as ‘non-human’¹³ (Lugones, 2010). Accordingly, gendered oppression occurs and intersects with other lines of oppression such as race (Ahmed, 2013; Alcoff, 2006; Collins, 2002; Collins & Bilge, 2016; Fanon, 1986; Gilman, 1994; hooks, 1990; Tate, 2009) or (dis)ability (Clare, 2015; Garland-Thomson, 2011; McRuer & Berube, 2006; Toombs, 2001; Wendell, 1996). Depending on where and how gender is situated¹⁴, lived experiences of gendered individuals as well as access to spaces and resources thus differ depending on social/cultural environments (Lugones, 2010; Westbrook & Schilt, 2014). Some examples of this can be found in income inequality (Mischler, 2021), sports participation (Jordan-Young & Karkazis, 2012; Karkazis et al., 2012), or quality of self-reported health (Gómez-Costilla et al., 2022). In line with Kessler et al. (1978), the word ‘gender’ is used instead of ‘sex’ to emphasise social construction of both ‘sex’ and ‘gender’ and to relate gendered research findings to their sociocultural setting rather than defaulting to biological markers of gender differences.

1.1.2 Development of physical fitness

Physiological and morphological changes associated with growth and maturation shape development of children’s physical fitness in different ways and interact with children’s socioecological environment. Several studies have examined this development either through a singular examination of children of different ages (i.e., cross-sectional study) or through several examinations of children over time (i.e., longitudinal study). Ample evidence of improvement in physical fitness during childhood and adolescence (i.e., up to the age of 16-18 years) exists for (1) cardiorespiratory fitness¹⁵ (Albrecht, 2015; Andersen et al., 1976; Castro-Piñero et al., 2011; Catley & Tomkinson, 2013; Fühner et al., 2021; Golle et al., 2014; Miguel-Etayo et al., 2014; Niessner et al., 2020; Oliveira et al., 2014; Santos et al., 2014; Tambalis et al., 2016), (2) muscular fitness¹⁶ (Castro-Piñero et al., 2009; Catley & Tomkinson, 2013; Fühner et al., 2021; Golle et al., 2014; Lundgren et al., 2011; Miguel-Etayo et al., 2014; Niessner et al., 2020; Oliveira et al., 2014; Ortega et al., 2023; Santos et al., 2014; Tambalis et al., 2016), and (3) speed¹⁷ (Catley & Tomkinson, 2013; Fühner et al., 2021; Golle et al., 2014; Miguel-Etayo et al., 2014; Oliveira et al., 2014; Tambalis et al., 2016). Of note one study remarked that cardiorespiratory fitness plateaued as early as 12 years (Castro-Piñero et al., 2011). (4) Flexibility¹⁸ also shows age-related improvements, however improvements are less pronounced compared to aforementioned physical fitness components (Albrecht, 2015; Catley & Tomkinson, 2013; Golle et al., 2014; Miguel-Etayo et al., 2014; Niessner et al., 2020; Oliveira et al., 2014; Santos et al., 2014; Tambalis et al., 2016). (5) Evidence for continuous improvements in balance¹⁹ until adolescence were found in some studies (Lundgren et al., 2011; Miguel-Etayo et al., 2014), while others found that evidence for a stabilisation for dynamic balance around 9 years and for static balance around 12 years (Niessner et al., 2020).

Improvements in physical fitness and especially cardiorespiratory fitness, muscular fitness, and speed also show different gender-related patterns. (1) Cardiorespiratory fitness tests show overall better performances in boys compared to girls (Castro-Piñero et al., 2011; Catley & Tomkinson, 2013; Fühner et al., 2021; Golle et al., 2014; Miguel-Etayo et al., 2014; Oliveira et al., 2014; Tambalis et al., 2016), with more pronounced improvements in boys at age 13 (Niessner et al., 2020; Ortega et al., 2023; Santos et al., 2014). Furthermore, studies show that cardiorespiratory fitness peaks in boys at 15-16 years of age (Niessner et al., 2020; Ortega et al., 2023; Tambalis et al., 2016), while in girls it varies between 11-13 (Albrecht, 2015; Ortega et al., 2023) and 14-15 years of age (Niessner et al., 2020; Tambalis et al., 2016). (2) In muscular fitness tests, boys overall tend to outperform girls as well (Castro-Piñero et al., 2009; Catley & Tomkinson, 2013; Golle et al., 2014; Miguel-Etayo et al., 2014; Oliveira et al., 2014; Ortega et al., 2023; Santos et al., 2014; Tambalis et al., 2016). However, these differences appear to be comparatively small before puberty, particularly in muscular endurance (Albrecht, 2015; Castro-Piñero et al., 2009; Lundgren et al., 2011; Santos et al., 2014), and evidence for gender differences before puberty ranges from studies finding no difference (Castro-Piñero et al., 2009; Lundgren et al., 2011; Santos et al., 2014) to boys performing better than girls (Fühner et al., 2021; Golle et al., 2014). Furthermore, longitudinal studies indicate steeper age-related improvements in girls within school grades (Golle et al., 2014), while cross-sectional studies indicate no gendered differences in age-related improvements rates during childhood across grades (Castro-Piñero et al., 2009; Fühner et al., 2021). During and after puberty, muscular strength performance in particular increases in boys and plateaus in girls (Albrecht, 2015; Castro-Piñero et al., 2009; Niessner et al., 2020; Tambalis et al., 2016). (3) Performances in sprint speed tests are better in boys compared to girls (Catley & Tomkinson, 2013; Fühner et al., 2021; Miguel-Etayo et al., 2014; Oliveira et al., 2014; Tambalis et al., 2016), but remain stagnant in all children after the age of 16 (Tambalis et al., 2016). (4) For flexibility and (5) balance performance, most studies found better performance in girls compared to boys (Golle et al., 2014; Miguel-Etayo et al., 2014; Oliveira et al., 2014; Santos et al., 2014; Tambalis et al., 2016), while some studies found no evidence of gender differences in terms of balance (Lundgren et al., 2011; Niessner et al., 2020).

In summary, physical fitness improves continuously in childhood up to the age of ~12 years, with subsequent different trajectories in boys and girls, such as a greater increase in cardiorespiratory fitness in boys (Niessner et al., 2020; Santos et al., 2014) compared to a possible plateau in girls (Albrecht, 2015; Castro-Piñero et al., 2011). For a more detailed presentation of development curves of physical fitness components in children, see Albrecht et al. (2015), Niessner et al. (2020), or Ortega et al. (2023). Physical, physiological, and biological changes related to growth and maturation are often cited as the reason for difference in development of physical fitness with age and between genders (Albrecht, 2015; Castro-Piñero et al., 2011; Santos et al., 2014; Tambalis et al., 2016). Due to the complexity of maturation and growth (G. P. Beunen et al., 2006), effects of specific maturation processes on physical fitness performances in their interrelationships are still unclear.

1.1.3 Secular trends of physical fitness

Aside from interactions with growth and maturity, physical fitness in children of same age and location changes over time, as so-called secular changes. Particularly, concerns of declining physical fitness among youth has gained much attention in recent decades and has led to research assessing these trends at an local, national, and international level (Dooley et al., 2020; Fühner et al., 2020; Tomkinson et al., 2003, 2019, 2020; Tomkinson & Olds, 2007).

1.1.3.1 International secular trends

International²⁰ analyses of secular trends in children aged 6 to 19 years were first published from the early 2000s and have since increased in popularity. Cardiorespiratory fitness²¹ showed an overall improvement from 1958 to 1970 (Tomkinson & Olds, 2007), followed by a decline until 2000 ~ 2010 (Fühner et al., 2020; Tomkinson et al., 2003, 2019; Tomkinson & Olds, 2007), where it stabilised and reached a floor (Fühner et al., 2020; Tomkinson et al., 2019). Regarding muscular fitness, international trends are available for the subcomponents muscular strength, muscular power, and muscular endurance. International secular trends for muscular strength²² yielded conflicting results, showing an overall small negative quadratic trend (Fühner et al., 2020) in contrast to overall progressive improvements until 2017 (Dooley et al., 2020). For muscular power²³, international secular trends showed overall improvements followed by subsequent declines with peaks in ~1985 (Tomkinson, 2007) or ~2000 (Tomkinson et al., 2020). For muscular endurance²⁴ large international improvements with a slowdown that stabilised around 2010 and declined thereafter were found (Kaster et al., 2020). Studies assessing international secular trends for speed²⁵ found improvements up to ~1970, followed by steady declines (Tomkinson, 2007), while another study found slight to moderate improvements from 1970 to ~2015 (Fühner et al., 2020). Contradictory results for muscular strength and speed could be at least partly explained by differences in inclusion criteria between studies. For example, Fühner et al. (2020) used a comprehensive approach to muscular strength that allowed different tests to be included in the analysis, while Dooley et al. (2020) focused on handgrip strength only.

Explanations of varying trend directions and developments can be combined into an interrelated model of physiological/psychological, physical, behavioural, and social factors (Tomkinson, 2004). Following this model, several subanalyses have been conducted to further identify and elucidate moderator variables of these trends. Estimating trends for larger geographical regions²⁶, as well as individual countries showed trends in geographic regions to be similar to international trends (Tomkinson, 2007; Tomkinson & Olds, 2007), while greater variability is shown around directions of national trends regarding direction and uniformity (i.e., linear or curvilinear) (Dooley et al., 2020; Kaster et al., 2020; Tomkinson et al., 2003, 2019, 2020). For gender, most studies found similar trends for boys and girls (Dooley et al., 2020; Kaster et al., 2020; Tomkinson et al., 2003, 2019, 2020; Tomkinson, 2007), with the exception of cardiorespiratory fitness, where a steeper decline was found for boys (Fühner et al., 2020; Tomkinson & Olds, 2007). Correlating international secular physical fitness trends with international secular trends of body mass index²⁷ (BMI) found a positive correlation for handgrip strength in children but not adolescents, with higher body mass indices being associated with stronger handgrips (Dooley et al., 2020), but found no associations with shuttle run, standing long jump, and sit up performances (Dooley et al., 2020; Kaster et al., 2020; Tomkinson et al., 2019, 2020). Correlating international physical fitness trends with international trends in moderate to vigorous and vigorous physical activity²⁸ revealed a positive correlation between sit up performances and vigorous physical activity, indicating that being vigorously physically active for one hour four times a week might be beneficial for secular trends in sit up performance or vice versa (Kaster et al., 2020). No significant correlations were found between handgrip strength, standing long jump, and shuttle run performance with physical activity (Dooley et al., 2020; Tomkinson et al., 2019, 2020). Comparing secular trends to developments in socioeconomic variables at country level such as gross national income per capita²⁹ (Tomkinson, 2007; Tomkinson & Olds, 2007), Gini index³⁰ (Dooley et al., 2020; Kaster et al., 2020; Tomkinson et al., 2019, 2020), human development index³¹ (Dooley et al., 2020; Kaster et al., 2020; Tomkinson et al., 2019, 2020), and urbanisation rate³² (Dooley et al., 2020; Kaster et al., 2020; Tomkinson et al., 2019, 2020) found (1) trends in speed and muscle strength to be favourable in low income countries but detrimental in high income countries between 1970 and 2000 (Tomkinson, 2007), (2) smaller declines in shuttle run performance to be associated with a larger increase in gross domestic product (Tomkinson et al., 2003), (3) correlations between Gini index with shuttle run performances, with countries approaching income equality showing more favourable trends (Tomkinson et al., 2019), and (4) no significant associations for the remaining comparisons/correlations.

In summary, secular trends of physical fitness show a complex development with ambiguous directions for different components of physical fitness, as well as interdependencies with the social world. This emphasises the need for an understanding of these interdependencies in order to properly contextualise secular fitness trends and be able to create meaningful and effective interventions.

1.1.3.2 Regional secular trends and interrelations - EMOTIKON study

Due to the regional relevance for this thesis, regional secular trends for the federal state of Brandenburg, Germany, are presented. These trends were assessed in the EMOTIKON study, which also served as foundation for the SMaRTER study (see Section 2.3). Measurements of physical fitness are taken using a fitness battery of six tests consisting of 6 min run, standing long jump, ball push test, 20 m sprint, one leg balance test, and star run (Teich, 2023). A detailed descriptions of these tests can be found in Section 2.4.2.1.

Secular trends in the EMOTIKON study were analysed for five of the six tests mentioned above (one leg balance test was not included in the analysis) from 2011 to 2019 in 108,295 children aged 8 to 8.99 years spread across 515 schools. Of note, in this analysis, contrasts were specified to compare performance trends in (1) star run to 6 min run, (2) 20 m sprint to star run, (3) standing long jump to 20 m sprint, and (4) standing long jump to ball push test. Analyses showed linear increases in test performances with chronological age and better performances of boys compared to girls in all included fitness tests. Tests differed in magnitude of respective gender and age effects. Interestingly, no evidence of an age-gender interaction was found for any of the tests or contrasts, despite an abundance of statistical power. Evidence for secular trends was only found for 6 min run with declines and for 20 m sprint with improvements in test performances. Additional findings were that 6 min run, 20 m sprint, star run and standing long jump tests form a correlated construct representing a potential conception of ‘physical fitness’, and that ‘physically fit schools’ show greater age-related improvement (Fühner et al., 2021).

In another publication, Fühner et al. (2022) analysed physical fitness of children depending on their age at school enrollment (i.e., 30 September). Three different groups were defined as (1) keyage (108,296 children aged 8 to 8.99 years; sample from Fühner et al. (2021)), (2) younger than keyage (2,586 children aged 7 to 7.99 years), and (3) older than keyage (26,540 children aged 9 to 9.99 years). Their analyses showed that keyage children performed better than older than keyage children, especially in the star run test, and that gender differences were present but reversed for older than keyage children. In addition, analyses showed that younger than keyage children performed better than keyage children, especially in the star run test. The authors hypothesise that differences between groups are related to differences in maturation that lead to children being enrolled in school earlier or later (Fühner et al., 2022).

In unpublished analyses on sociocultural, -economic, and -structural interrelations of physical fitness in the federal state of Brandenburg, the EMOTIKON research team investigated effects related to proximity to Berlin³³. They found better performance in 6 min run, 20 m sprint, and standing long jump in children who lived closer to Berlin, although there was no evidence for the effect of proximity to Berlin on the direction of secular trends in the analysed tests (Kliegl & Teich, 2022). A further analysis linking the EMOTIKON data set to results of the 2021 federal election in the state of Brandenburg, Germany found a negative correlation between 6 min run performance and percentage of right-wing members in local councils and a positive correlation between performance in 6 min run performance and percentage of Green and Liberal party members in local councils. These effects were reversed for ball push test performances (Kliegl & Teich, 2022). This means, for example, that areas with a high proportion of right-wing party members and a low proportion of green and liberal party members in local councils have comparably lower 6 min run performances and higher ball push test performances. With regard to the tendency of low-income voters to prefer right-wing parties and of higher-income voters to prefer green and liberal parties (DIW, 2017), these results emphasise the sociocultural, -economic, and -structural conditions of physical fitness and its health-related correlates.

As regional secular trends in 6 min run and 20 m sprint (Fühner et al., 2021) share parallels with international trends in cardiorespiratory fitness (Fühner et al., 2021; Tomkinson et al., 2019; Tomkinson & Olds, 2007) and speed (Fühner et al., 2020), these trends might be caused by a similar component. Particularly striking is the relation to different aspects of income in its specific sociocultural context, such as the Gini-index (Tomkinson et al., 2019) or the association between income and electoral behaviour (DIW, 2017; Kliegl & Teich, 2022).

1.2 Physical fitness and weight status

Over the past few decades, considerable evidence has been found to show low physical fitness to be a risk factor associated with a wide range of health problems in children. For example, low muscular fitness in childhood and adolescence is associated with an increased risk of cardiovascular disease, an increase in metabolic risk factors and an increase in obesity, while high muscular fitness is associated with improved bone health (García-Hermoso et al., 2019; Ramírez-Vélez et al., 2016; Smith et al., 2014). Similarly, low cardiorespiratory fitness is associated with an increase in cardiovascular risk factors such as abnormal blood lipids, hypertension, and increased obesity (Ruiz et al., 2009), as well as symptoms of depression (Esmaeilzadeh, 2014, 2015). While there are a variety of different negative health effects, the following sections primarily focuses on associations between physical fitness and weight status.

Weight status in mostly used in physical fitness research to determine children with overweight/obesity, which can vary depending on its definition. The most commonly used tool for assessing overweight/obesity is the BMI (i.e., mass/height\(^2\)). For adults, BMI cut-off scores for overweight are 25 kg/m\(^2\) and for obesity 30 kg/m\(^2\), which are predominantly used for adults in Western countries (Akram et al., 2000). For children and adolescents, age- and gender-specific BMI cut-off values have been estimated based on adult prevalence to account for maturation and growth-related changes in the body (Cole et al., 2000; Cole & Lobstein, 2012; Kromeyer-Hauschild et al., 2001). BMI is most commonly used in population-based studies as it is easily accessible and provides a reasonable estimate of prevalence of overweight and obesity in a larger population (Akram et al., 2000; Bentham et al., 2017; Ng et al., 2014; Wang & Lobstein, 2006). It is assumed that changes in body mass (which affect the ratio of height to body mass) are mainly due to an increase in body fat (Akram et al., 2000; Cole et al., 2000; Nishida et al., 2004). However, for exercise-based interventions, the general goal is to reduce fat mass and increase muscle mass. The BMI is not suitable for differentiating between fat and muscle mass, thus other measures and methods, such as dual-energy X-ray absorptiometry, skinfold thickness, waist circumference, or bioelectrical impedance analysis, can be used (Lindsay et al., 2001; Lobstein et al., 2004; Steinberger et al., 2005; Tyrrell et al., 2001; Wohlfahrt-Veje et al., 2014).

In recent decades, both scientists and health-oriented institutions have expressed concern about growing numbers of overweight and obese people worldwide. A survey assessing international changes of overweight and obesity prevalences³⁴ in children and adolescence aged 2 to 19 years in 188 countries found an overall increases between 1980 and 2013. In developed countries³⁵ prevalences increased from 16.2% to 22.6% in girls and from 16.9% to 23.8% in boys, and for developing countries from 8.4% to 13.4% in girls and from 8.1% to 12.9% in boys (Ng et al., 2014). Another study examined secular trends in mean BMI among 24.1 million children and adolescents aged 5 to 17 years from 1975 to 2016. Across all age groups, an international increase from ~17.2 kg/m\(^2\) to ~18.6 kg/m\(^2\) was found for girls (i.e., ~0.32 kg/m\(^2\) per decade), and from ~16.8 kg/m\(^2\) to ~18.5 kg/m\(^2\) for boys (i.e., ~0.4 kg/m\(^2\) per decade). Regarding prevalence in age standardised obesity³⁶, found increases from 0.7% to 5.6% in girls and from 0.9% to 7.8% in boys from 1975 to 2016 (Bentham et al., 2017). A study that did not utilise BMI examined secular changes in skinfold thickness and percent body fat in 458 547 children and adolescents aged 0 to 18 years from 1951 to 2003 in 30 industrialised countries³⁷. The analyses showed an increase in skinfold thickness of ~0.49 mm and percentage body fat of ~0.86% per decade with highest rates in children age 10 to 14 years (Olds, 2009).

These changes are of particular concern to public health officials, as overweight and obesity are associated with negative health outcomes. For example, childhood overweight or obesity³⁸ is associated with increased risk factors for cardiovascular disease such as elevated trigylceride, LDL, and HDL cholesterol levels, insulin, and elevated systolic and diastolic blood pressure (Freedman et al., 2009, 2013). Moreover, a meta-analysis examining diagnosis and symptoms of depression in overweight and obese³⁹ children (0 to 12 years) and adolescents (13 to 21 years) showed that obese children have a higher risk of developing depression (OR = 1.34) (Quek et al., 2017). While children who are classified as overweight or obese face immediate risks to their physical and mental health, several studies have examined links between childhood overweight and obesity classifications and health risks later in life. For example, one study found an increased risk of death from coronary heart disease, atherosclerosis, colorectal cancer, and gout in 256 men who were classified as overweight in their youth⁴⁰ (Must et al., 1992). A systematic review examining effects of obesity in childhood (i.e., 2 to 12 years) and adolescence (i.e., 13 to 19 years) on morbidity and mortality in adulthood (i.e., ≥ 19 years) found strong evidence of increased risk of type 2 diabetes, hypertension, coronary heart disease, colorectal cancer, and all-cause mortality⁴¹ (Park et al., 2012). In addition, several studies have shown that childhood and adolescent overweight/obesity continues into adulthood (Singh et al., 2008), and that the number of years living with obesity further increases all-cause mortality, cardiovascular mortality, cancer mortality, and mortality from other causes (Abdullah et al., 2011).

Due to negative health effects associated with overweight and obesity in childhood and adolescence, the relationship between physical fitness and weight status is considered a possible cause and explanation for negative health effects associated with low physical fitness. However, the relationship between physical fitness and weight status is ambivalent, multidirectional, and varies for different components of fitness and assessments of obesity. For example, in the aforementioned studies assessing international secular trends in physical fitness, no overall significant national-level correlations with secular trends in BMI were found for different components (Dooley et al., 2020; Kaster et al., 2020; Tomkinson et al., 2019, 2020) (see Section 1.1.3.1 for more details). Only subanalyses of secular trends in BMI and handgrip strength for children and adolescents seperately showed a positive correlation for children (r = .55, 95%CI = .03 to .84) but not for adolescents (r = .21, 95%CI = -.36 to .67). This may indicate that positive effects of BMI on handgrip strength may lessen with age. As a reason for the positive direction of the relationship, the authors hypothesised that improvements in handgrip strength are due to an increase in lean muscle mass, which is part of increases in BMI (Dooley et al., 2020). Similarly, in a study examining the relationship between handgrip strength and BMI or percentage body fat in children⁴², found a positive correlation between BMI and handgrip strength, while the correlation between body fat and handgrip strength was negative⁴³ (Sartorio et al., 2002). In other tests of muscular fitness, the relationship of weight status with physical fitness changes direction. For example, in a study examining the relationship between muscular strength and weight status in American children and adolescents, a positive relationship was found between weight status with knee extension and handgrip strength, with higher performance associated with higher weight status. However, while in plank and pull-up tests, there was an inverse relationship, with an increase in weight status associated with a decrease in performance⁴⁴ (Ervin et al., 2014). It has been theorised that muscle strength in tests that require lifting body mass is inversely related to weight status, as performances are more affected by body mass and especially body fat mass, while tests that focus on specific muscles without utilising total body mass show a parallel relationship due to better utilisation of lean body mass (Deforche et al., 2003; Ervin et al., 2014). Similarly, cardiorespiratory fitness, particularly in tests measuring running performance over a given distance or time, is consistently better in normal-weight children compared to overweight and obese children (Abdelkarim et al., 2020; Palomäki et al., 2015). For example, a study examining the relationship between weight status, 20 m shuttle run performance, and physical activity in adolescents aged 15-16 years showed that cardiorespiratory fitness was better in normal-weight adolescents than in overweight adolescents, regardless of physical activity and gender⁴⁵ (Palomäki et al., 2015). Another study assessing effects of weight status on 9 min run performance in 519 Brazilian students could show better performances in normalweight compared to overweight, and overweight compared to obese children⁴⁶. They were also able to show that weight status had a greater impact on 9 min run performance compared to other fitness tests such as sit-and-reach, stationary long jump, 1 min curl-up, modified pull-up, medicine ball throw, 20 m run, and 4 m shuttle run (Dumith et al., 2010).

In relation to aforementioned interrelations between physical fitness and socioeconomic variables, it is important to highlight socioeconomic correlates shaping weight status in youth. For example, a systematic review of 158 papers examining associations between socioeconomic position and weight status among adolescents in the 21 richest countries between 1990 and 2005 found an inverse association in 60.7% of the studies⁴⁷. 18.7% found no association and 20.9% found the association to be confounded by other variables such as age, gender, or ethnic group, and only 1.1% found a parallel association (Barriuso et al., 2015). Similar results were obtained in a study examining effects of physical activity, television viewing, video game play, socioeconomic status, and ethnicity on BMI of American adolescents aged 10 to 16 years⁴⁸. The most striking associations were found for ethnicity, socioeconomic status, and gender, with higher rates of overweight in African American children, low socioeconomic status, or girls compared to White children, high socioeconomic status, or boys (McMurray et al., 2000). These findings suggest that prevalence of overweight and obesity runs along lines of societal marginalisation, which would support an intersectional approach⁴⁹. A study assessing obesity prevalence and its social correlates in Black and White American adolescents aged 15.2 ± 1.6 years attending public school found that Black girls comparatively assigned themselves to the lowest social stratification and had the highest BMI. Analysis of socioeconomic status revealed that lower-income and Black students were more likely to be overweight and that, on average, Black students came from lower-income families compared to White students⁵⁰ (Goodman et al., 2003). Interestingly, a study that examined trends in obesity prevalence among 534 children aged 2 to 4 years over a three-year period in relation to household income⁵¹ found that obesity prevalence increased at a greater annual rate in low-income households compared to higher-income households, highlighting longevity of income-related differences in obesity prevalence (Kunin-Batson et al., 2023).

In summary, the relation on weight status varies between and within different physical fitness components in its magnitude as well as direction depending on different test properties. Further, as weight status is associated with specific socioeconomic markers, interpretations of effects of weight status on physical fitness need to consider its socioeconomic context.

1.3 Physical fitness and executive function

In recent decades, in context of physical fitness, cognitive performance, particularly executive function⁵², has received increasing attention in children and adolescents (Chu et al., 2019; Donnelly et al., 2016; Ruiz-Ariza et al., 2017). Executive functions describe top-down control processes against automatic or instinctive decisions or actions, and is subdivided into the domains inhibition, working memory and cognitive flexibility (Diamond, 2013; Haapala, 2013). Inhibitions is at the core of executive function and is ascribed to the control of attention, actions and reactions, while working memory describes the ability to hold and actively process information (Diamond, 2013; Haapala, 2013). Cognitive flexibility is found at the intersection of inhibition and working memory and is described as changing perspective on a problem or adjusting to new rules (Diamond, 2013) Studies examining the relationship of physical fitness with executive function have found a small but positive association. For example, in studies comparing high-fit with low-fit children on basis of their cardiorespiratory fitness, high-fit children were found to have better allocation of attentional and working memory resources (Hillman et al., 2005) and better response accuracy (Hillman et al., 2009) compared to low-fit children⁵³. A study examining the relationship between shuttle run performance and executive functions in children aged 12 to 15 years found a small but significant positive correlation between shuttle run performance and cognitive flexibility, but not with problem-solving skills⁵⁴ (Niet et al., 2014). Another study that examined the association between a 10-minute interval running performance and a composite of executive functions in 378 children (aged 9 to 10 years) found a small but significant positive association⁵⁵ (Kvalø et al., 2019). Skog et al. (2020) examined the relationship between maximal oxygen uptake and maximal power output with working memory, short-term memory, visual learning and memory, paired associated learning, attention, reaction time, and ‘executive function’ and found that maximal oxygen uptake was positively associated with working memory, visual learning, and associated learning⁵⁶. In contrast, Havercamp et al. (2021) found no relationship between performance in 20 m shuttle run and visuo-spatial working memory, verbal working memory, and interference control in adolescents⁵⁷. Positive direction of the relationship between cardiorespiratory fitness and executive function is attributed to cardiorespiratory fitness-induced structural changes in the brain, such as synaptic plasticity (Chaddock et al., 2011), grey matter development (Cotman et al., 2007), white matter integrity (Chaddock-Heyman et al., 2014), activated growth factors (Cotman et al., 2007; Hillman et al., 2008), and/or improved cerebral blood flow (Chaddock et al., 2012; Tyndall et al., 2018).

Studies examining the relationship between muscular fitness and executive functions in children do not show such a clear pattern. In studies investigating the relationship between physical fitness and executive functions, tests assessing muscular fitness parameters usually calculate a composite score with a test assessing cardiorespiratory fitness to achieve a proxy score for physical fitness (Chu et al., 2019). In these studies, similar correlations are found as in aforementioned studies on cardiorespiratory fitness. For example, using a composite score consisting of 20 m shuttle run and maximum ball throwing performance, Marchetti et al. (2015) found a slight positive relationship between the composite score for physical fitness and working memory updating and inhibition in adolescents⁵⁸. Only a few studies have directly measured muscle strength, and they have not shown a consistent pattern linking muscular fitness and executive function. Van der Niet et al. (2014) found significant small positive associations between performance in sit-up, 10 x 5 m shuttle run, and standing long jump with cognitive flexibility but not with problem-solving skills⁵⁹. Whereas Haverkamp et al. (2021) found no correlation between standing long jump/sit up performance and any included executive function test⁶⁰. Weak but positive associations between muscular fitness and executive function could be due to strength training-induced increases in insulin-like growth factor 1 found in older individuals (Cassilhas et al., 2007). Assuming that this relationship is transferable to children and adolescents, increases in neuronal growth could at least partially explain positive relations between muscular fitness and executive function.

In addition to cardiorespiratory and muscular fitness, fitness tests that include a cognitive component were assessed in relation to executive function. Haverkamp et al. (2021) found a positive association between 10 × 5 m shuttle run and plate tapping performances with visuospatial working memory, information processing and control, and interference control⁶¹, Van der Niet et al. (2014) found significant small positive associations between 10 x 5 m shuttle run performance and cognitive flexibility⁶², and Marchetti et al. (2015) found a positive association between inhibition and performance in pendulum running in high fitness children but not in low fitness children⁶³. These positive relationships are attributed to neural network activations as a common denominator associated with both motor and executive functions (Diamond, 2006; Koziol et al., 2014).

1.4 Physical education interventions

In context of some negative secular trends internationally (see Section 1.1.3.1) and nationally (see Section 1.1.3.2) and the correlation between physical fitness and adverse health outcomes (see Section 1.2), researchers have called for interventions to counter secular trends and promote children’s physical fitness and health (Fühner et al., 2020, 2021; Tomkinson et al., 2020). A common approach is to implement physical fitness interventions in schools, where almost all children can be reached⁶⁴ (Kriemler et al., 2011). In addition, schools provide a convenient environment for implementation of physical fitness interventions, as they have access to trained instructors and training facilities and equipment. A meta-analysis evaluating the impact of qualitative (i.e., incorporating fitness exercises or teaching strategies into existing physical education) and quantitative (i.e., increasing the number of physical education lessons per week) physical education interventions found that both interventions have a positive impact on physical fitness, with quantitative physical education interventions having a greater impact on components of physical fitness compared to qualitative interventions (García-Hermoso et al., 2020). Since quantitative physical education interventions seem to be effective in improving physical fitness, the following sections highlight effects of these interventions on components of physical fitness as well as on parameters of body composition and cognition.

1.4.1 Physical education interventions and physical fitness

Several studies have investigated effects of additional physical education on physical fitness. Ardoy et al. (2011) analysed effects of two hours of standard physical education, four hours of standard physical education, and four hours of intensive physical education in 67 Spanish adolescents (aged 12-14 years; 35.8% girls) over a 16-week period on different components of physical fitness⁶⁵. They found larger increases in 20 m shuttle run and sit and reach performances in both intervention groups compared to a control group, and in 4 x 10 m shuttle run performance in the intensive physical education group compared to the control group. No differences were found between groups regarding standing long jump performances. A study evaluating effects of a comprehensive physical education intervention that involved doubling weekly physical education time (i.e., from 90 min/week to 180 min/week) over a three-year period in 696 preschool children (aged 6-7 years at baseline)⁶⁶ found no differences in VO2 peak between intervention and control groups (Bugge et al., 2012). A similar study involving 503 first and fifth grade children compared three hours of regular physical education with five hours of special physical education over the course of a school year. They found small differences in shuttle run performances between intervention and control groups, favouring the intervention group⁶⁷ (Kriemler et al., 2010). Löfgren et al. (2013) investigated daily physical education lessons (i.e., 5 x 40 min./week) compared to regular physical education lessons (i.e., 2 x 30 min./week) in 232 children aged 7 to 9 years at baseline over a 2-year period⁶⁸. They found better knee extension strength at 180° in boys and girls in the intervention group compared to controls, better intervention-related knee flexion strength at 180° in boys only, and better vertical jump performance in girls in the intervention group compared to girls in the control group. However, in a study with a similar design involving 189 elementary school children, girls in the intervention group with daily physical education (i.e., 5 x 45 minutes/week) were found to have higher push-up and curl-up performances compared to girls in the control group with regular physical education (i.e., 1 x 45 minutes/week). No differences were found for boys overall or for either gender in shuttle run performance⁶⁹ (Reed et al., 2013).

1.4.2 Physical education interventions and weight status

Several of the aforementioned interventions also included health-related anthropometric parameters such as total skinfolds (Ardoy et al., 2011; Bugge et al., 2012; Kriemler et al., 2010), percent body fat (Ardoy et al., 2011; Löfgren et al., 2013), other body fat distribution proxies⁷⁰ (Ardoy et al., 2011; Bugge et al., 2012; Kriemler et al., 2010; Löfgren et al., 2013; Reed et al., 2013), and specific cardiovascular disease risk factors⁷¹ (Bugge et al., 2012; Kriemler et al., 2010) as secondary outcomes. While Kriemler et al. (2010) and Reed et al. (2013) found evidence of a reduction in body fat distribution in favor of children participating in the interventions (i.e., skinfold thickness, BMI), Löfgren et al. (2013) found evidence of an intervention-related increase in body fat, with more favorable trends in the control condition⁷². Ardoy et al. (2011) and Bugge et al. (2012) found no evidence of intervention effects with respect to body fat distribution. However, with respect to cardiovascular disease risk factors, there was evidence of more favorable trends associated with intervention participation (Bugge et al., 2012; Kriemler et al., 2010). Another study examined effects of four additional hours of physical education on overweight and obesity parameters as primary outcomes in 632 children aged 8 to 13 years⁷³. No differences were found in percent body fat and BMI between six lessons of physical education and two lessons of physical education. However, a significant effect was found on prevalence of overweight and obesity, with children who participated in the intervention being at lower risk for overweight and obesity (Klakk et al., 2013).

1.4.3 Physical education interventions and executive function

Few studies have examined effects of additional physical education on executive function or similar cognitive domains in children and adolescents. Of the aforementioned studies, only Reed et al. (2013) included cognitive measures such as puzzle-solving ability and perceptual speed⁷⁴. While no clear intervention-related effects were found for puzzle-solving ability, greater improvements in perceptual speed were found for girls in the intervention group compared to girls in the control group. Another study examining effects of two weekly additional cognitively enhanced tennis lessons compared to one weekly lesson of normal physical education on inhibition and working memory in 9 to 10 year old children found intervention-related improvements in inhibition, but not memory, and only in overweight children⁷⁵ (Crova et al., 2014). However, several studies examined effects of quality/intensity of physical education on executive function in children and adolescents and found ambiguous evidence of the relationship between intensity of physical education and cognition. For example, a study examining effects of high-intensity interval training on memory, selective attention, and concentration in adolescents aged 13.7 ± 1.3 years found that selective attention and concentration, but not memory, increased more in the intervention group compared with the control groups that received regular physical education⁷⁶. Conducting additional subanalyses, the authors found that these effects were more pronounced in more inactive children (Martínez-Lopez et al., 2018). In contrast, a study examining effects of physical education combined with either aerobic high-intensity interval training or resistance and aerobic high-intensity interval training in adolescents aged 14 to 16 years found no effect of intensive physical education on trail making test performance⁷⁷ (Costigan et al., 2016). A meta-analysis examining effects of physical activity on executive functions in children and adolescents found an overall improvement with physical activity, regardless of age. Regarding study design, they found that curricular exercises and extracurricular programs were effective, while physical activity integrated into school curriculums did not significantly improve executive functions. They were also able to show that fewer than 5 sessions per week seem to be most effective with a session duration of less than 90 minutes (Xue et al., 2019).

1.4.4 Overall effectiveness of physical education interventions

In summary, additional physical education can have a positive impact on physical fitness, executive functions, and weight status of children and adolescents. However, these advantages seem to be mitigated by gender and physical condition of participating children and young people, as well as by duration, intensity, and objective of additional physical education. While some studies have examined effects of additional physical education in overweight children (Crova et al., 2014; Klakk et al., 2013), there are no studies to date that examine effects of additional physical education in children with low levels/deficits in physical fitness. Improving physical fitness in children with physical fitness deficits is important because these children are at higher risk of adverse health effects and might also progress more in physical fitness due to their lower baseline levels. Accordingly, further research is needed to investigate effects of additional physical education on physical fitness, weight status, and executive functions in children with physical fitness deficits.

1.5 Physical fitness, health, and cognition during the Covid 19 pandemic

As this thesis was written in late 2022, it is important to consider the impact of the global Covid 19 pandemic and its implications for children and adolescents. To prevent spread of Sars-CoV-2, governments have enacted regulations restricting access to areas of direct human interaction such as workplaces, schools and public spaces. Due to geographical location as well as thematic setting of the intervention, on which this thesis is focused, measures to contain spread of Sars-CoV-2 in schools and organised sports are described for the federal state of Brandenburg, Germany. From March 18th, 2020 to April 20th, 2020, schools were completely closed (MBJS, 2020c, 2020a) and slowly reopened, using models where children could attend school two to three times per week, following hygiene protocols (e.g., regular testing, social distancing, wearing masks) (MBJS, 2020b). From August 9th, 2021 onwards, schools were fully open (MBJS, 2021a) and kept open until winter 2021/22, with compulsory school attendance removed to allow schools to respond to local infection prevalences (MBJS, 2022a, 2022b). Compulsory school attendance was reintroduced from March 7th, 2022 (MBJS, 2022b). During reopening of schools from 2020 to 2021, physical education classes were conducted only outdoors following social distancing and other hygiene measures (MBJS, 2020a) and from August 9th, 2021, physical education classes were conducted without any restrictions (MBJS, 2021b). A more detailed chronological list of regulations for school operations can be found elsewhere⁷⁸. Organised sports were suspended from March 18th, 2020 to May 15th, 2020 (MBJS, 2020c, 2020a) and were subsequently only allowed outdoors, in small groups following social distancing protocols (MBJS, 2020a). From May 28th, 2020, organised indoor activities were allowed following social distancing procedures and a facility-specific hygiene concept (MBJS, 2020b). Operation under 2G regulations (i.e., being vaccinated/cured or tested) was reintroduced on November 24th, 2021 (MBJS, 2021c).

Considering that severity of lockdown measures directly affects children’s physical activity (Kharel et al., 2022; Paterson et al., 2021; Schmidt et al., 2020, 2022), the question arose how these lockdown measures affected children’s physical fitness. Teich et al. (2023) analysed effects of policies described above on secular development of physical fitness in 107,558 third grade children in the federal state of Brandenburg, Germany, using data from the EMOTIKON study (see Section 1.1.3.2). In 87,395 key-age children⁷⁹ they found a significant negative impact of covid pandemic on a composite physical fitness score and on 6 min run, 20 m sprint, and star run performance. There was a significant positive trend in standing long jump performance but no significant effect in ball push test and single leg balance performance. In particular, negative impact in running tests resulted in annual development costs/delays of 3.5 months for 6 min run and star run performance and 2.1 months for 20 m sprint performance. The negative trend in composite physical fitness score resulted in an annual development cost/delay of 1.4 months, while annual developmental gain in standing long jump performance was 1.6 months. Secondary analyses for 22,761 children older than keyage showed negative covid pandemic effects on 6 min run, star run, ball push test, and one-leg balance test performance, whereas 1,321 children younger than keyage showed no significant covid pandemic effects. Similar trends were found in a study assessing the impact of the Covid pandemic in Slovenian 6th and 8th grade children⁸⁰, who showed declines in all tests except hand tapping test and found greatest declines in physical fitness index, 600 m run, polygon course backwards, bent-arm hang, and 60 m sprint performance. They were also able to show that declines were greater for children in rural areas compared to urban children (Pajek, 2022).

While there are negative trends in physical fitness associated with lockdown measures, these measures were put in place to mitigate health risks associated with SARS-CoV-2 infections. Because of the novelty of the virus, knowledge of effects of SARS-CoV-2 infection in general and in children in particular is still sparse and requires further investigation, especially with regard to long-term effects. Acute effects of SARS-CoV-2 infection appear to be less severe in children and adolescents aged 0-18 years than in adults (Liguoro et al., 2020; Mehta et al., 2020), with ~42.5% of children with SARS-CoV-2 infection experiencing mild symptoms and 39.6% experiencing moderate symptoms. ~2% of children with SARS-CoV-2 infections required treatment in a pediatric intensive care unit, and estimated overall mortality rate was <.1%⁸¹ (Liguoro et al., 2020). However, apart from acute SARS-CoV-2 infections, several long-term effects have been observed in children, such as multisystem inflammatory syndrome (Brodin, 2022; Molloy et al., 2022; Nygaard et al., 2022) or post-COVID-19 disease. Multisystem inflammatory syndrome in children causes fever, hypotension/shock, myocardial dysfunction/coronary abnormalities, and elevated inflammatory markers, amongst other symptoms, and can occur 1 to 2 months after asymptomatic or paucisymptomatic SARS-CoV-2 infection (Brodin, 2022; Molloy et al., 2022). Although prevalences of multisystemic inflammatory syndrome in children after SARS-CoV-2 infection is comparatively low (i.e., 51 of 175 458 unvaccinated individuals aged 0 to 18 years), prevalences vary by SARS-CoV-2 variant and underlying mechanisms are not fully understood (Nygaard et al., 2022). The term post-COVID-19 condition refers to symptoms lasting several months after an acute infection, such as fatigue, shortness of breath, insomnia, difficulty breathing, nasal congestion, difficulty concentrating, muscle pain, exercise intolerance, weakness, and walking intolerance (Izquierdo-Pujol et al., 2022; Soriano et al., 2022; Zimmermann et al., 2021). Overall prevalences in children and adolescents are unclear, and early estimates ranged from 4% to 66% (Zimmermann et al., 2021) to 1% to 30% (Izquierdo-Pujol et al., 2022), depending on included symptoms. These findings gain importance as a recent study found that severity and persistence of acute and long-term symptoms increase with the number of SARS-CoV-2 infections (Bowe et al., 2022).

Accordingly, SARS-CoV-2 infections in children pose a significant health risk with as yet unknown long-term consequences. Whether these risks outweigh negative effects of lockdowns and social distancing measures on for example physical activity and physical fitness (Kharel et al., 2022; Pajek, 2022; Paterson et al., 2021; Teich et al., 2023) cannot be conclusively assessed. Full opening of schools (MBJS, 2021a), reinstatement of compulsory school attendance (MBJS, 2022b), and lack of comprehensive testing in schools from April 30th, 2022 (MBJS, 2022c) combined with a high prevalence of asymptomatic acute infections (Liguoro et al., 2020; Mehta et al., 2020) but potentially serious long-term consequences in children (Bowe et al., 2022; Izquierdo-Pujol et al., 2022; Nygaard et al., 2022; Zimmermann et al., 2021), however, seem quite concerning.

1.6 Main hypothesis

Based on the outlined need for further research to assess effects of physical education on physical fitness, weight status, and executive function in children with deficits in their physical fitness (see Section 1.4.4), a study (i.e., SMaRTER study) was conducted guided by the following primary working hypothesis:

Children with physical fitness deficits show greater improvements in physical fitness and cognitive performance following participation in a remedial physical education program compared to a control condition.

The SMaRTER study and its sample are described in detail in Chapter 2, and effects of additional remedial physical education are analyzed in Chapter 3. Chapter 4 through Chapter 6 further explore longitudinal data to elucidate interrelation between physical fitness and anthropometrict measures (see Chapter 4), growth (see Chapter 5), and executive function (see Chapter 6). Specific details for exploratory analyses are described in Section 2.8.

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1. Kraus et al. (1954) was criticized for alleged weaknesses in their research design and too few fitness components (i.e., flexibility and strength) (R. R. Pate, 1983).

2. Relative leanness refers to the relation of lean body mass (i.e., weight of all body tissue except fat) to total body fat (Bubb, 1986).

3. Including external stress as a determining factor allows to consider individual physical fitness and health in their socioeconomic conditions. Given associations of systematic social conditions with physical fitness (see e.g., Section 1.1.3.1 and Section 1.1.3.2) and weight status (see Section 1.2), this approach would allow these conditions to be taken into account when conceptualising research interests and developing policy guidelines.

4. For a more detailed description and discussion of the approach of Bös et al. (2017) see Albrecht (Albrecht, 2015).

5. Due to this assumption, summaries of studies include information about implemented tests, either in text or in footnotes, to clarify respective framings of physical fitness.

6. Processes towards a mature state can be defined as growing of breasts, pubic hair, and age of menarche in girls (Marshall & Tanner, 1969), and growing of genitalia and pubic hair in boys (Marshall & Tanner, 1970).

7. Another common approach is to determine sexual maturity using five stages of maturity (so-called Tanner stages) by screening and classifying growth of breasts and pubic hair in girls and genitalia and pubic hair in boys (Marshall & Tanner, 1969, 1970; Tanner & Whitehouse, 1981). These have been heavily criticised for their invasive/intrusive nature and gender bias (G. P. Beunen et al., 2006; Cameron, 2012; Mirwald et al., 2002). For an account of ethical concerns with data collection (e.g., consent) and historical context of Tanner’s work on classifying maturity stages in children, see Roberts et al. (2016).

8. The number of publications in which the terms ‘sex’ and ‘gender’ are implemented is increasing. However, there is a lack of clear definitions and concepts for these terms. For example, Tomkinson et al. (2019) examined international secular trends in cardiorespiratory fitness and reported on ‘sex’ specific trends and interactions. Their discussion then explored these differences in context of “gender equality policies and programmes”. However, in their publication they do not address differences in these concepts and their implications.

9. In their book “Atlas of Children’s Growth - Normal Variation and Growth Disorders”, Tanner and Whitehouse (Tanner & Whitehouse, 1981) classify children maturity according to their criteria, whereby children who can be easily classified according to their criteria are called “normal”. Deviations from criteria are classified as “disorders” (as the title suggests). Some of their “disorder” classifications are, for example, variations in chromosome composition XO (Turner syndrome), XXY (Klinefelter syndrome) or XXY (XYY syndrome). For an account of stigmatisation of ‘disorders’ and processes of sex determination, see Meyer-Bahlburg et al. (2016) and Lee et al. (2016).

10. Dihydrotestosterone induces formation of external sex organs and is crucial for the development of the infantile penis (Sobel et al., 2004).

11. Attribution in this context occurs within frameworks of a binary understanding and in absence of first-hand information about gender identity of the other.

12. Additional information may be required, for example, from athletes, such as assessment of hormone levels or determination of chromosomal structures. Here, identification can be alongside or in opposition to the others identity, and in most legal systems a binary understanding of gender and sex is still upheld and enforced (Jordan-Young & Karkazis, 2019).

13. For an intersectional and postcolonial analysis of recent discussions on hyperandrogenism among professional female athletes, see (Karkazis & Jordan-Young, 2018).

14. In line with Lugones (Lugones, 2010), this placement can be within and outside the binary ‘sex/gender/sexuality system’ (Seidman, 2009; Westbrook & Schilt, 2014).

15. Cardiorespiratory fitness was assessed in cross-sectional studies using 20-m shuttle run in 1,026,077 children from 30 European countries (Austria, Belgium, Bosnia and Herzegovina, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Iceland, Italy, Kosovo, Latvia, Lithuania, North Macedonia, Norway, Poland, Portugal, Slovakia, Spain, Serbia, Slovenia, Sweden, Switzerland) aged 6 - 18.9 years from ~2000 to 2023 (Ortega et al., 2023), 20-m shuttle run in 22,048 Portuguese children and adolescents (11,373 girls; 10-18 years) in 2008 (Santos et al., 2014), 20-m shuttle run among 424,328 Greek children and adolescents (49% girls; 6-18 years) in 2014 (Tambalis et al., 2016), 20-m shuttle run, 1 mile, 1/2 mile and 1/4 mile run/walk in 2,752 Spanish children and adolescents (1,261 girls; 6-17.9 years) (Castro-Piñero et al., 2011), physical work capacity 170 static bicycle ergometer test in 3,742 German children and adolescents (50.1% girls; 4-23 years) from 2009 to 2013 (Niessner et al., 2020), 20-m shuttle run in 6,398 children from Sweden, Germany, Hungary, Italy, Cyprus, Spain, Belgium and Estonia (3,288 girls; 6-10.9 years) from 2007 to 2008 (Miguel-Etayo et al., 2014), 1-mile run/walk in 3,804 Portuguese children (1,819 girls; 6-10 years) (Oliveira et al., 2014), 6-minute run in 108,295 German children (8-9 years) (Fühner et al., 2021), and a meta-analytic approach involving 15 studies of a 1.6-km run or a 20-m shuttle run in Australian children (5-18 years) from 1985 to 2009 (Catley & Tomkinson, 2013). Longitudinal studies assessed cardiorespiratory fitness using 9-minute run in 240 German children (88 girls) aged 9-12 years in four consecutive annual assessments (Golle et al., 2014), assessment of maximal aerobic power in 65 children (34 girls) aged 8.4 to 12.4 years in five consecutive annual studies from 1969 to 1973 (Andersen et al., 1976), and also analysed in a review of longitudinal studies from Australia (3), Belgium (4), Canada (3), China (1), Denmark (4), Germany (10), England (3), Estonia (2), France (1), Greece (1), Japan (1), Luxembourg (1), Netherlands (1), New Zealand (2), Northern Ireland (1), Norway (1), Occupied Palestine (1), Portugal (1), Sweden (3), Switzerland (1), South Africa (1), and USA (1) (Albrecht, 2015).

16. Muscular fitness was assessed in cross-sectional studies using hand grip strength in 747,966 children and standing long jump in 1,345,159 children from 34 European countries (Albania, Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Iceland, Italy, Kosovo, Latvia, Lithuania, Luxembourg, North Macedonia, Netherlands, Norway, Poland, Portugal, Slovakia, Spain, Serbia, Slovenia, Sweden, Switzerland) aged 6 - 18.9 years from ~2000 to 2023 (Ortega et al., 2023), ball throw, standing long jump, vertical jump, push-up, hanging with bent arm, pull-up, sit-up, curl ups in 30 seconds and curl up tests in 2,778 Spanish children and adolescents (1,265 girls; 6-17.9 years) (Castro-Piñero et al., 2009), push-up and curl-up tests in 22,048 Portuguese children and adolescents (11,373 girls; 10-18 years) in 2008 (Santos et al., 2014), isokinetic peak concentric torque at 60 and 180⁄sec of knee extensors and flexors and vertical jump height in 436 Swedish children (190 girls; 6-12 years) from 1999 to 2001 (Lundgren et al., 2011), standing long jump and sit-up test in 424,328 Greek children and adolescents (49% girls; 6-18 years) in 2014 (Tambalis et al., 2016), handgrip strength and standing long jump in 3,804 Portuguese children (1,819 girls; 6-10 years) (Oliveira et al., 2014), sit-up and push-up tests and standing long jump in 3,742 German children and adolescents (50.1 % girls; 4-23 years) from 2009 to 2013 (Niessner et al., 2020), handgrip strength and standing long jump in 8,418 and 8,494 children from Sweden, Germany, Hungary, Italy, Cyprus, Spain, Belgium and Estonia (4,304 and 4,339 girls, respectively; 6-10.9 years) from 2007 to 2008 (Miguel-Etayo et al., 2014), ball push test and standing long jump in 108,295 German children (8-9 years) (Fühner et al., 2021), and another meta-analytic approach with 15 studies examining basketball throw, push-up test, standing long jump, sit-up test and handgrip strength in Australian children (5-18 years) from 1985 to 2009 (Catley & Tomkinson, 2013). Longitudinal studies assessed cardiorespiratory fitness using 1-kg ball throw test and triple hop test in 240 German children (88 girls) aged 9-12 years in four consecutive annual assessments (Golle et al., 2014), and also analysed in a review of longitudinal studies from Australia (3), Belgium (4), Canada (3), China (1), Denmark (4), Germany (10), England (3), Estonia (2), France (1), Greece (1), Japan (1), Luxembourg (1), Netherlands (1), New Zealand (2), Northern Ireland (1), Norway (1), Occupied Palestine (1), Portugal (1), Sweden (3), Switzerland (1), South Africa (1), and USA (1) (Albrecht, 2015).

17. Sprint speed was measured in cross-sectional studies using 10 × 5 m pendulum running test in 424,328 Greek children and adolescents (49% girls; 6-18 years) in 2014 (Tambalis et al., 2016), 40 m sprint test among 6,398 children from Sweden, Germany, Hungary, Italy, Cyprus, Spain, Belgium and Estonia (3,288 girls; 6-10.9 years) from 2007 to 2008 (Miguel-Etayo et al., 2014), 50-m sprint and 4 x 10-m shuttle run in 3,804 Portuguese children (1,819 girls; 6-10 years) (Oliveira et al., 2014), 20 m sprint in 108,295 German children (8-9 years) (Fühner et al., 2021), and a meta-analytic approach with 15 studies using 50-m sprint in Australian children (5-18 years) from 1985 to 2009 (Catley & Tomkinson, 2013). Longitudinal studies assessed cardiorespiratory fitness in 240 German children (88 girls) aged 9-12 years at four consecutive annual assessments using 50-m sprint (Golle et al., 2014), and furthermore, analysed in a review of longitudinal studies from Australia (3), Belgium (4), Canada (3), China (1), Denmark (4), Germany (10), England (3), Estonia (2), France (1), Greece (1), Japan (1), Luxembourg (1), Netherlands (1), New Zealand (2), Northern Ireland (1), Norway (1), Occupied Palestine (1), Portugal (1), Sweden (3), Switzerland (1), South Africa (1), and USA (1) (Albrecht, 2015).

18. Flexibility was assessed in cross-sectional studies using modified Back Saver Sit and Reach Test in 22,048 Portuguese children and adolescents (11,373 girls; 10-18 years) in 2008 (Santos et al., 2014), Sit and Reach Test in 424,328 Greek children and adolescents (49% girls; 6-18 years) in 2014 (Tambalis et al., 2016), sit and reach test in 3,804 Portuguese children (1,819 girls; 6-10 years) (Oliveira et al., 2014), Sit and Reach test in 3,742 German children and adolescents (50.1% girls; 4-23 years) from 2009 to 2013 (Niessner et al., 2020), Back Saver Sit and Reach Test on 6,398 children from Sweden, Germany, Hungary, Italy, Cyprus, Spain, Belgium and Estonia (3,288 girls; 6-10.9 years) from 2007 to 2008 (Miguel-Etayo et al., 2014), and another meta-analytic approach with 15 studies using sit and reach test in Australian children (5-18 years) from 1985 to 2009 (Catley & Tomkinson, 2013). Longitudinal studies assessed cardiorespiratory fitness in 240 German children (88 girls) aged 9-12 years in four consecutive annual assessments using Stand and Reach Test (Golle et al., 2014), and also in a review of longitudinal studies from Australia (3), Belgium (4), Canada (3), China (1), Denmark (4), Germany (10), England (3), Estonia (2), France (1), Greece (1), Japan (1), Luxembourg (1), Netherlands (1), New Zealand (2), Northern Ireland (1), Norway (1), Occupied Palestine (1), Portugal (1), Sweden (3), Switzerland (1), South Africa (1), and USA (1) (Albrecht, 2015).

19. Balance was assessed in cross-sectional studies using postural control with a one leg balance test and a blindfolded one leg balance test in 436 Swedish children (190 girls; 6-12 years) from 1999 to 2001 (Lundgren et al., 2011), static stance and backward balancing in 3,742 German children and adolescents (50.1% girls; 4-23 years) from 2009 to 2013 (Niessner et al., 2020), and a one-leg balance test in 6,398 children from Sweden, Germany, Hungary, Italy, Cyprus, Spain, Belgium and Estonia (3,288 girls; 6-10.9 years) from 2007 to 2008 (Miguel-Etayo et al., 2014).

20. Several studies have used global as a description for trends (Tomkinson, 2007; Tomkinson et al., 2020; Tomkinson & Olds, 2007). However, as analysed data sets in these studies are heavily skewed towards European, North American, and Australasian countries, international was chosen to account for few/missing trends in South American, African, and Asian countries, as well as countries and areas outside these classifications (e.g., Peninsular, Arctic, and Antarctic).

21. countries	fitness tests	number of children	age range [years]	time period	citation
    Australia, Belgium, Canada, France, Greece, Italy, the Netherlands, Northern Ireland, Spain, USA, and Poland	20 m shuttle run	129,882 (63,079 girls)	6 to 19	1980 to 2000	(Tomkinson et al., 2003)
    Australia, Belgium, Bulgaria, Canada, China, Czech Republic, Estonia, Finland, France, Germany, Japan, Hong Kong, Hungary, occupied Palestine, Italy, Korean Republic, Lithuania, Mozambique, Netherlands, New Zealand, Northern Ireland, Poland, Russia, Singapore, Spain, Sweden, and USA, representing the geographical regions Africa/Middle-East (n = 2,542), Asia (n = 23,741,524), Australasia (n = 144,110), Europe (n = 995,950), and North America (n = 304,068)	20 m shuttle run, 5 to 12 min runs, and 300 TO 2,414 m runs	25,455,527	6 to 19	1958 to 2003	(Tomkinson & Olds, 2007)
    Australia, Belgium, Brazil, Canada, Estonia, France, Greece, Hungary, Italy, Japan, Lithuania, the Netherlands, Poland, Portugal, Seychelles, South Africa, Spain, UK, and USA	20 m shuttle run	965,264	9 to 17	1981 to 2014	(Tomkinson et al., 2019)
    Australia, Brazil, Canada, Czech Republic, Denmark, England, Finland, Belgium, Germany, Hungary, Lithuania, Netherlands, New Zealand, Norway, Portugal, Sweden, and USA	20 m shuttle run, 6 to 12 min runs, 1200 to 1600 m run, maximal cycle ergometer, PWC 170 cycle ergometer, and a submaximal cycle ergometer test	96,522	6 to 18	1972 to 2015	(Fühner et al., 2020)

22. countries	fitness tests	number of children	age range [years]	time period	citation
    Australia, Brazil, Canada, Czech Republic, Denmark, England, Finland, Belgium, Germany, Hungary, Lithuania, Netherlands, New Zealand, Norway, Portugal, Sweden, and USA	leg lift, sit-up, push-up, bent arm hang, pull-up, arm-pull, bench-press, or a two-hand lift test	96,522	6 to 18	1972 to 2015	(Fühner et al., 2020)
    Australia, Belgium, Bulgaria, Canada, China, Estonia, France, Greece, Hong Kong, Italy, Japan, Mexico, Mozambique, Poland, Spain, Thailand, Turkey, UK, and USA	hand grip strength	2,230,658	9 to 17	1967 to 2017	(Dooley et al., 2020)

23. countries	fitness tests	number of children	age range [years]	time period	citation
    Australia, Belgium, Bulgaria, Canada, China, Czech Republic, Czechoslovaki, Estonia, Finland, France, Germany, Hungary, Iceland, occupied Palestine, Italy, Japan, Korea, Lithuania, Mozambique, New Zealand, Poland, Singapore, Spain, Sweden, Thailand, Turkey, and USA in five geographical regions Africa/Middle East (n = 2192), Asia (n = 18,080,023), Australasia (n = 115,528), Europe (n = 1,861,841), and North America (n = 39,937)	single jump tests such as standing broad jump, vertical jump, running broad jump, or running vertical jump	49,123,233	6 to 19	1958 to 2003	(Tomkinson, 2007)
    Australia, Belgium, Bulgaria, Canada, China, Czech Republic, Estonia, Finland, France, Germany, Greece, Iceland, occupied Palestine, Italy, Japan, Lithuania, Mozambique, New Zealand, Poland, Republic of Korea, Singapore, Slovakia, Slovenia, Spain, Taiwan, Thailand, Turkey, UK, and USA	standing long jump	10,940,801	9 to 17	1960 to 2013	(Tomkinson et al., 2020).

24. countries	fitness tests	number of children	age range [years]	time period	citation
    Australia, Belgium, Brazil, Bulgaria, Canada, China, Estonia , Finland, France, Greece, Hong Kong, Iceland, occupied Palestine, Italy, Japan, Lithuania, Mozambique, New Zealand, Norway, Poland, Republic of Korea, Singapore, Slovakia, Slovenia, Spain, Sweden, Switzerland, Taiwan, Thailand, Turkey, and UK	sit up test	9,939,289	9 to 17	1964 to 2017	(Kaster et al., 2020)

25. countries	fitness tests	number of children	age range [years]	time period	citation
    Australia, Belgium, Bulgaria, Canada, China, Czech Republic, Czechoslovaki, Estonia, Finland, France, Germany, Hungary, Iceland, occupied Palestine, Italy, Japan, Korea, Lithuania, Mozambique, New Zealand, Poland, Singapore, Spain, Sweden, Thailand, Turkey, and USA in five geographical regions Africa/Middle East (n = 8,855), Asia (n = 25,427,141), Australasia (n = 100,796), Europe (n = 2,164,526), North America (n = 216,925)	20 to 100 m sprint, 4 x 9 to 13.7 m, shuttle run 6 x 13.7 m shuttle run, or 10 x 5 m shuttle run	49,123,233	6 to 19	1958 to 2003	(Tomkinson, 2007)
    Australia, Brazil, Canada, Czech Republic, Denmark, England, Finland, Belgium, Germany, Hungary, Lithuania, Netherlands, New Zealand, Norway, Portugal, Sweden, and USA	20 to 50 m sprints, and 4 × 9 m shuttle run, or 10 × 5 m shuttle run	96,522	6 to 18	1972 to 2015	(Fühner et al., 2020)

26. Secular trends were calculated for geographical regions Africa/Middle East, Asia, Australasia, Europe, and North America (Tomkinson, 2007; Tomkinson & Olds, 2007).

27. Shuttle run performance trends (Tomkinson et al., 2019) were correlated with data from the Global Burden of Disease Study 2013, which provided trends for prevalences of overweight/obese children and adolescents (according to published cut off values (Cole et al., 2000; Cole & Lobstein, 2012)) from 183 countries from 1980 to 2013 (Ng et al., 2014). Trends for handgrip strength (Dooley et al., 2020), standing long jump (Tomkinson et al., 2020), and sit up performance (Kaster et al., 2020) were correlated with data from the NCD Risk Factor Collaboration which provided trends for mean BMI change (per decade) for 31.5 million boys and girls aged 5–19 years in 200 countries from 1975 to 2016 (Bentham et al., 2017).

28. Physical activity trends from the Health Behaviour in School-aged Children survey were included in the studies. Physical activity was operationalised as change in prevalence of daily moderate to vigorous physical activity for at least 60 minutes and vigorous physical activity for at least 60 minutes four times a week for boys and girls aged 11, 13 and 15 years in European countries between 2002 and 2014 (Inchley et al., 2017).

29. Gross national income per capita in this analysis represents annually added value created by production of goods and services in a country (OECD, 2023) and was taken from the World Bank data set (Bank, 2023b). Classifications into low, middle, or high income economies were done using the World Bank atlas method (Bank, 2023b)

30. The Gini index provides information on distributions of income within the population of a country. It is calculated by comparing the cumulative welfare share of households with the cumulative population share, where values of 0 represent perfect income equality and values of 100 represent perfect income inequality (Bank, 2023a). Data was retrieved from the World Bank data set (Bank, 2023b).

31. Urbanisation provides information on percentage growth of urban populations and is calculated using population estimates of the World Bank and urban quotients from the World Urbanization Prospects of the United Nations (Bank, 2023a). Data was retrieved from the World Bank data set (Bank, 2023b).

32. The human development index is composed of (1) life expectancy at birth (to measure ability to live a long and healthy life), (2) average number of years of schooling and expected number of years of schooling (to measure ability to acquire knowledge), and (3) gross national income per capita (to measure ability to achieve an adequate standard of living) (UNDP, 2018). Data was retrieved from the World Bank data set (Bank, 2023b).

33. The federal state of Brandenburg, Germany surrounds Berlin and has a higher population density in close proximity to Berlin. The reasoning behind the analyses was that a higher population density is associated with an environment that offers more opportunities to improve physical fitness. Furthermore, average cost of living is higher in areas closer to Berlin. Accordingly, it is likely that more families with higher incomes live in this area.

34. Overweight and obesity in children and adolescents have been defined using gender- and age-specific BMI values (Cole et al., 2000; Cole & Lobstein, 2012).

35. Development status was defined in accordance with the Global Burden of Diseases, Injuries, and Risk Factors enterprise, based on gross national product per capita (Murray et al., 2012). Which countries were classified as “developed” or “developed” in which time period was not specified in the study or supplementary materials (Ng et al., 2014).

36. Using age-specific growth references (i.e., medians and standard deviations) for children and adolescents, obesity was defined at the 2 standard deviation threshold (Onis et al., 2007).

37. Body fat percent was calculated from skinfold thickness (assessed at triceps and subscapula) using Slaughter equations (Slaughter et al., 1988). Industrialised countries were Argentina, Australia, Bahrain, Belgium, Canada, the Czech Republic, Estonia, Finland, France, Germany, Greece, Hong Kong, Ireland, Italy, Japan, the Netherlands, New Zealand, Poland, Portugal, Russia, South Africa, Spain, Slovakia, South Africa, Sweden, Switzerland, Taiwan, Turkey, the United Arab Emirates, UK, and USA (Olds, 2009)

38. Overweight and obese was assessed as (1) BMI (adjusted and age-specific), (2) skinfold thickness (triceps, subscapula, and sum of both), and (3) percentage body fat (estimated using skinfold thickness and Slaughter equations) in 6725 and 6866 children aged 5 to 17 years in the Bogalusa Heart Study from 1981 to 1994 (Freedman et al., 2009, 2013).

39. Depressive symptoms were evaluated using depression rating scales such as the Child Depression Inventory, the Strength and Difficulties Questionnaire, and the Montgomery-Asberg Depression Rating Scale. Multiple definitions for overweight and obesity, such as BMI at 85th to 95th percentile for overweight and above the 95th percentile for obese, or age- & gender-specific curves, were included and pooled in the meta analysis (Quek et al., 2017).

40. Obesity was defined as a BMI above the 75th percentile of the First National Health an Nutrition Examination Survey from 1971 to 1974 (USDA, 1990) for two consecutive years during their enrollment at Harvard School of Education (Must et al., 1992).

41. Obesity was defined using BMI, which was included as a continuous variable in the analysis, or compared with age- and sex-specific BMI cut-off scores (Cole et al., 2000; Cole & Lobstein, 2012) to determine prevalences. Included studies examined subjects from Western Europe (Denmark, Finland, Norway, Sweden, UK, Netherlands), the USA (including Hawaii), Australia, and occupied Palestine (Park et al., 2012).

42. Specific information on age clustering of secular BMI trends was not provided in this publication (Dooley et al., 2020).

43. The study included 278 normal-weight children aged 5 to 15 years, where normal weight was defined as 2 SD above age-specific thresholds for mean BMI. The source for mean BMI was not reported. Percent body fat was estimated using a tetrapolar foot-to-foot impedance device.

44. The study included 1224 boys and girls (i.e., ~768 normalweight, ~223 overweight, & ~233 obese) aged 6 to 15 and assessed weight status using the Centers for Disease Control and Prevention gender- and age-specific BMI reference values (Ogden & Flegal, 2010).

45. The study included 1186 boys (992 normal weight, 194 overweight) and 1142 girls (1105 normal weight, 137 overweight) in 2003, and 661 boys (524 normal weight, 137 overweight) and 640 girls (563 normal weight, 77 overweight) in 2010. Weight status was defined using age- and gender-specific BMI cut-off points (Cole et al., 2000), and physical activity was assessed using a questionnaire, with adolescents grouped into inactive, mildly active, moderately active, active, and very active (Nupponen et al., 2010).

46. The study analysed 270 boys and 249 girls at ages 7 to 15 years and defined weight status (i.e., thin, normalweight, overweight, & obese) using the World Health Organization’s BMI references for children and adolescents (Onis et al., 2007).

47. Inclusion criteria for socioeconomic position were parental education, income and/or occupation, and weight status was defined as (1) reference to presence of overweight (obesity and/or overweight) or (2) some anthropometric parameter. The richest countries were identified based on (1) membership of the Organisation for Economic Co-operation and Development and (2) a gross national income per capita of more than $25,000 according to the International Monetary Fund for 2010. These included Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Holland, Iceland, Ireland, Occupied Palestine, Italy, Japan, Korea, Luxembourg, New Zealand, Norway, Portugal, Slovenia, Spain, Sweden, Switzerland, United Kingdom, and the USA.

48. The study included 2389 adolescents aged 10 to 16 years, 52% girls and 48% boys, or 77% White and 23% African American. Prevalence of overweight was determined using age- and sex-specific BMI reference values (Najjar & Rowland, 1987).

49. Intersectionality describes intertwining of social systems of oppression such as race, or gender with bodies that are placed at intersections of one or more margins are subject to greater oppression, or left out of social counter-movements (Crenshaw, 1989).

50. 1491 adolescents (49.6% boys and 49.4% Black) were enrolled in the study. Weight status was defined as normal weight (i.e., BMI < 85%), at risk for overweight (i.e., BMI between 85% and 95%) and overweight (i.e., BMI ≥ 95%) using age- and sex-specific reference values (Kuczmarski et al., 2002). Socioeconomic status was defined using parental education and combined pre-tax total household income for the last 12 months, and perceptions of social stratification were assessed using the MacArthur Subjective Social Status Scale (Goodman et al., 2001).

51. Prevalence of overweight was determined by percentage BMI at the 95th percentile using fitted linear growth curve modelling, and low-income households were defined as < $25,000/year.

52. Executive function describes cognitive processes underlying selection, planning, coordination, and monitoring of complex, goal-directed processes in areas of perception, memory, and action (Donnelly et al., 2016).

53. Hillman et al. (2005) studied progressive shuttle run performance (Welk et al., 2002) in 600 children and recruited 24 children (9.6 years) from the top and bottom 10%. Attention and working memory resources were assessed using the visual odd-ball paradigm, which required children to quickly identify an infrequent stimulus while not responding to a frequent stimulus (Hillman et al., 2005). Hillmann et al. (2009) determined progressive shuttle run performances (Welk et al., 2002) in 38 children (aged 8 to 11 years) and divided them into equally sized groups (19 high-fit, 19 low-fit). Reaction accuracy was determined with the Eriksen-Flanker task (Eriksen & Eriksen, 1974), in which children had to react as quickly as possible to different series of letters (Hillman et al., 2009).

54. The study included 263 children (145 boys, 118 girls). Cognitive flexibility was assessed with the trail making test (Reitan, 1971) and problem solving ability with the Tower of London (Shallice, 1982).

55. Executive function was measured by calculating a composite score from the Stroop-Gold colour-word test [selective attention, response inhibition, self-control and mental speed], the trail making test [measures attention, speed of psychomotor execution and mental flexibility], verbal semantic fluency [initiation, efficient organisation of verbal recall and memory and self-monitoring], and the backward digit span [working memory function].

56. Skog et al. (2020) used the term ‘executive function’ differently in that publication than in this thesis. They refer to performance in a memory task, whereas in this paragraph executive function is specified above, which includes all cognitive tests used by Skog et al. (2020). They included 54 adolescents (aged 17 ± 2 years; 35 girls; 19 boys), and executive functions were assessed using the Two-Back Task [working memory task], the One-Back Task [speed in short-term memory], the One-Card Learning Test [accuracy in visual memory], the Continuous Paired-Associate Learning Task [visual learning and memory], the Identification Task [speed in an attentional task], the Detection Test [psychomotor function and reaction time], and the Groton Maze Learning Test [‘executive function’].

57. The study involved 423 Dutch adolescents (aged 13.45 ± 0.43 years; 46.8% boys). Visual-spatial working memory was examined with forward and backward conditions of the computerised grid task (Nutley et al., 2009), verbal working memory with forward and backward conditions of the digit span task (Wechsler, 1991), and interference control with an adapted version of the attention network test (Fan et al., 2002).

58. The study included 527 students aged 12 to 15 years (13.5 ± 1.0 years; 340 males; 187 females), including 29 borderline students or students with intellectual-relational disabilities. Working memory updating and inhibition were assessed with the random number generation test.

59. The study included 263 children (145 boys, 118 girls). Cognitive flexibility was assessed with the trail making test (Reitan, 1971) and problem solving ability with the Tower of London (Shallice, 1982).

60. The study involved 423 Dutch adolescents (aged 13.45 ± 0.43 years; 46.8% boys). Visual-spatial working memory was examined with forward and backward conditions of the computerised grid task (Nutley et al., 2009), verbal working memory with forward and backward conditions of the digit span task (Wechsler, 1991), and interference control with an adapted version of the attention network test (Fan et al., 2002).

61. The study involved 423 Dutch adolescents (aged 13.45 ± 0.43 years; 46.8% boys). Visual-spatial working memory was examined with forward and backward conditions of the computerised grid task (Nutley et al., 2009), verbal working memory with forward and backward conditions of the digit span task (Wechsler, 1991), and interference control with an adapted version of the attention network test (Fan et al., 2002).

62. The study included 263 children (145 boys, 118 girls). Cognitive flexibility was assessed with the trail making test (Reitan, 1971) and problem solving ability with the Tower of London (Shallice, 1982).

63. The study included 527 students aged 12 to 15 years (13.5 ± 1.0 years; 340 males; 187 females), including 29 borderline students or students with intellectual-relational disabilities. Working memory updating and inhibition were assessed with the random number generation test.

64. As most countries in the Global South have some form of compulsory school attendance, most children living in these areas can be reached. However, as school attendance is linked to legal status, children without occupational status as well as children without a permanent residence or with attested ‘educational and school inability’ are systematically excluded from this approach (see Gomolla (2015) for a detailed analysis of institutional discrimination in the German education system).

65. Intervention details were published elsewhere in Spanish (Ardoy et al., 2010).

66. Physical education lessons were taught by regular physical education teachers and content was not controlled to reflect ‘real-life’ conditions. Other features of the intervention were additional health education focusing on physical activity and healthy eating, 3-4 days of teacher training, and improvement of indoor facilities for physical education and outdoor playgrounds. Sixty-nine children were recruited from 18 public preschools (10 intervention children [222 boys and 186 girls] and 8 control children [142 boys and 144 girls]).

67. Three physical education lessons for intervention and control groups were taught by class teachers, while two additional physical education lessons in the intervention group were taught by physical education teachers. Details of additional specific physical education lessons were not reported. In addition to two extra physical education lessons per week, the intervention group introduced short daily physical activity breaks and physical activity homework. Mean age of the first grade children was 6.9 ± 0.3 years and that of fifth grade children was 11.1 ± 0.5 years. The intervention group consisted of 297 children (131 first graders and 166 fifth graders) and the control group consisted of 205 children (91 first graders and 114 fifth graders). The study was conducted with Swiss children.

68. Additional physical education was provided by classroom teachers and included general activities within the regular curriculum such as ball games, running, jumping, and climbing. The intervention group consisted of 49 girls and 80 boys, and the control group consisted of 50 girls and 53 boys. Knee extensor strength was determined using peak isokinetic torque at 60° and 180° for knee flexors and extensors.

69. Daily physical education classes at experimental schools and regular physical education classes at two control schools were taught by certified physical education teachers, focusing on fundamental skills.

70. Ardoy et al. (2011) assessed BMI, fat mass index, waist circumference, waist circumference to height ratio, fat-free mass, and fat-free mass index. Bugge et al. (2012) measured waist circumference. Kriemler et al. (2010) recorded BMI and waist circumference. Löfgren et al. (2013) included BMI, fat-free mass (total, legs, and arms), and fat mass (total, legs, and arms) in their analysis. Reed et al. (2013) included mean BMI percentile in their analysis.

71. Bugge et al. (2012) assessed systolic blood pressure, insulin resistance, total cholesterol to high-density lipoprotein ratio, triglycerides, and a composite score for cardiovascular disease, and Kriemler et al. (2010) included systolic blood pressure, diastolic blood pressure, triglycerides, total cholesterol to high-density lipoprotein ratio, glucose, and a cardiovascular risk score in their analyses.

72. Kriemer et al. (2010) found trends favorable to the intervention for skinfold thickness and BMI, and Reed et al. (2013) found similar trends for BMI percentiles in girls only. Löfgren et al. (2013) found inverse trends (i.e., in favor of controls) for fat mass (total, legs, and arms) in boys and girls and for body fat percentage and BMI in girls only. Of note, they also found an increase in lean body mass (total, legs, and arms) and body mass in girls, which could indicate a difference in maturation and thus greater growth and maturation development in girls in the intervention condition.

73. Supplemental physical education was conducted according to the CHAMPS study protocol (Wedderkopp et al., 2012). Overweight and obesity were classified using sex-specific body fat percentage standards (Williams et al., 1992).

74. Puzzle-solving abilities were assessed using the standardized progressive matrices test (Raven et al., 1998), and perceptual speed for recognizing different or identical line patterns was measured using the perceptual speed test (Salthouse, 1996).

75. The intervention lasted 6 months and included 70 children (37 intervention, 33 control). Overweight/lean children were classified using age-specific cutoffs for BMI (Cole et al., 2000). Inhibition and updating of working memory were assessed using various indices of the random number generation task (Towse & McLachlan, 1999).

76. The intervention lasted 12 weeks, and high-intensity interval training was performed on a twice-per-week schedule. Memory was assessed with the RIAS test, which required participants to memorize and recall 15 playing cards (Santamaría-Fernández & Fernández-Pinto, 2013), and selective attention and concentration were assessed with the d2 test, which required participants to identify as many specific letters as possible in a given amount of time (Seisdedos, 2012).

77. Both high-intensity interval trainings were performed in the first 8 to 10 minutes of three weekly physical education sessions over 8 weeks. The aerobic high-intensity interval training focused on gross motor, cardiorespiratory exercises, while the resistance and aerobic high-intensity interval training further included bodyweight training exercises.

78. See https://mbjs.brandenburg.de/corona-aktuell/chronologie.html

79. Keyage children (age 8.6 ± .3 years; 51.1% girls) were classified at age 6 to 6.99 at enrollment on September 30. September, younger and older children (age 7.9 ± .2 years, 57.8% girls & age 9.3 ± .3 years, 41.6% girls; respectively) were classified as one year younger and older than keyage children, respectively.

80. The study included 765 6th and 765 8th grade pre-pandemic children aged 11.3 ± .5 and 13.3 ± .5 years, and 853 6th and 853 8th grade pandemic children aged 11.4 ± .5 and 13.4 ± .5 years. Physical fitness was assessed using SLOfit measures consisting of a hand tapping test, standing long jump, polygon course backward, sit-ups, stand and reach, bent-arm hang, 60 m sprint, and 600 m run, in addition to providing an overall index of physical fitness (Jurak et al., 2020).

81. The review evaluated papers published between January 1st, 2020 and May 1st, 2020. Accordingly, potential long-term effects and newer variants of the SARS-CoV-2 virus were not considered.