Finding correlates of Physical Activity of children and adolescents in Germany [in press]

The purpose of this study is to investigate factors that influence physical activity (PA) measured by accelerometers in a representative sample of children and adolescents in Germany and determine whether these factors are correlates of PA. To our knowledge it is the first time that objectively measured PA data is available for a representative sample in Germany.
Methods:
2,278 children and adolescents between the age of 6 and 17 (47.1% male, mean age: 12.52 years) wore either ActiGraph GT3x+ or ActiGraph wGT3X-BT as part of the examination throughout the nationwide MoMo survey “Wave 2” (2014-2017) [Woll, A. et al. (2017). Journal of Health, 2(S3), 66–73.]. The participants wore the device during all waking hours on 8 consecutive days. Accelerometer data was downloaded via ActiLife software and further processed using MATLAB. Influencing factors were measured during the MoMo examination (age, BMI) or as part of the MoMo physical activity questionnaire (MoMo-PAQ): socio-economic status (SES), migration background, media use). Statistical analysis for the cross-sectional data was performed using SPSS. The investigated dependant variable was moderate to vigorous PA (MVPA) per day. ... mehrTwo-way ANOVA was performed, always including age, gender and one of the other mentioned influencing factors.
Results:
Two-way ANOVA using only age and gender reports significant effects of both factors: Fage(2,2272) = 325.008, p<.001 Fsex(1,2272) = 165.679, p<.001. Two-way ANOVA shows significant effects for SES and BMI: FSES(2,2250) = 4.742, p=.009, FBMI(4,2199) = 4.284, p=.002. Looking closer at SES, the effect is only significant for the female population: FSES,male(2,1059) = 1.763, p=.172, FSES,female(2,1191) = 4.087, p=.017. No siginificant effects were found for migration background and media usage: FMigration(1,1631) = 0.134, p=.715, FMedia(3,2168) = 1.127, p=.337.
Conclusions:
As expected, a large part of the variance in PA is explained by age and gender. Other identified correlates in this study are SES and BMI. Compared to the effects of age and gender these correlates explain only a small proportion of variance. Future research with longitudinal data is needed to investigate if the found correlates are determinants.
Support/Funding Source: This work has been developed within the Motorik-Modul Longitudinal Study (MoMo) (2009 – 2021): Physical fitness and physical activity as determinants of health development in children and adolescents. MoMo is funded by the Federal Ministry of Education and Research (funding reference number: 01ER1503) within the research program ´long-term studies` in public health research.