Representative Percentile Curves of Physical Fitness From Early Childhood to Early Adulthood: The MoMo Study

Abstract

Introduction: Monitoring of physical fitness in youth is important because physical fitness is a summative indicator of health. From a developmental and preventive perspective, physical fitness levels are relatively stable from childhood to early adulthood. Thus, it is important to monitor physical fitness on a population based level being able to intervene at early stages (1). In order to reliably assess and evaluate the physical fitness of youth, a reliable system of standard values based on representative data is required. The aim of this analysis is to report sex-and age-specific physical fitness percentile curves from childhood to early adulthood in a nationwide sample in Germany. Methods: We use data from the nationwide representative Motorik Modul (MoMo) Study in Germany (data collection wave 1: 2009-2012; age: 4-23 years; n = 3,742; 50.1% female). Physical fitness was assessed by means of the MoMo test profile covering four dimensions of physical fitness (strength, endurance, coordination, and flexibility) and including eight physical fitness items. Percentile curves were fitted using the LMS transformation method of Cole and Green. Results: Standardized age-and sex-specific physical fitness percentiles were calculated for eight items: ergometric endurance testing, standing long jump, push-ups, sit-ups, jumping sideways , balancing backwards, static stand, and stand and reach test. The physical fitness curves differ according to gender and the fitness dimension. Physical fitness improvements with age are linear (e.g., max. strength) or curvilinear (e.g., coordination) and have their stagnation points at different times over the course of adolescence. Discussion: Our results provide for the first time sex-and age-specific physical fitness percentile curves for Germany from 4 to 17 years. Differences in curve-shapes indicating a timed and capacity-specific physical fitness development. Nationwide German physical fitness percentiles can be useful in comparing different populations (e.g., crosscountry), reporting secular trends, comparing special groups, and to evaluate physical fitness interventions.

Physical fitness in third grade of primary school: A mixed model analysis of 108,295 children and 515 schools

“…The aim of this study was to examine short-term ontogenetic cross-sectional developmental differences in physical fitness for five tests tapping healthand skill-related components of physical fitness in a large sample of 108,295 German eight-year old children. Even in a single prepubertal year of life (1) performance increases linearly with chronological age in all physical fitness tests, (2) boys outperform girls in all physical fitness tests with sex differences being larger for tests requiring muscle mass and being smaller for tests requiring motor coordination, (3) the tests differ, mostly as expected, in the size of age and sex effects, (4) four of the five tests represent a common construct (i.e., correlate strongly positively with each other) -the exception is the ball push test that requires powerUP, (5) there was no evidence for an interaction of age and sex -with each other or with the test contrasts despite an abundance of statistical power, (6) "physically fit schools" apparently promote more developmental gains within a year (but this is only correlational evidence) and (7) diverging secular trends for cardiorespiratory endurance (negative) and speed (positive) are in agreement with other research and meta-analyses.…”

“…Children's development of physical fitness as well as the effects of moderating variables such as age and sex are well documented [1][2][3][4][5][6][7] , especially boys' and girls' divergence during puberty starting late in the twelfth and tenth year of life, respectively 8 . The situation might be different during prepuberty.…”

Predictive value of physical fitness on self‐rated health: A longitudinal study

“…“Cardiorespiratory endurance” was measured by an ergometric test assessing the physical working capacity 170 (PWC170, attained watts at 170 beats/min) with the test protocol of the WHO 23 . For each of these seven physical fitness tests, age‐ and gender‐specific percentile curves were calculated using the LMS transformation method 24 . Therefore, a comparison, independent of age and gender, was possible within the longitudinal study over the period of 2003‐2017.…”

“…A percentile value refers to the percentage of persons in the age‐ and gender‐specific reference population with the same or lower performance. Thus, a percentile value of 1 represents the lowest performance, whereas a percentile value of 99 reflects the best performance 24 …”

“…23 For each of these seven physical fitness tests, age-and gender-specific percentile curves were calculated using the LMS transformation method. 24 Therefore, a comparison, independent of age and gender, was possible within the longitudinal study over the period of 2003-2017. A percentile value refers to the percentage of persons in the age-and gender-specific reference population with the same or lower performance.…”