(In)consistency between longitudinal developmental pathways and normative data: the case of cardiorespiratory fitness Conference Paper uri icon

abstract

  • The assessment of cardiorespiratory fitness (CRF) is of paramount importance in the field of human health and sports sciences. The maintenance of satisfactory cardiorespiratory fitness levels is related with the prevention of cardiovascular disease (Ortega et al., 2008), diabetes and obesity (Dwyer et al., 2009), and school-based interventions have proved a positive effect in promoting cardiorespiratory fitness (Minatto et al., 2016). Since the more direct measurement of CRF (VO2max) is complex and expensive, a variety of indirect tests have been used in field-based protocols such as the 20-m endurance shuttle run (PACER). International normative data for the PACER is well established (Tomkinson et al., 2016). Both percentile and average values show that PACER values are expected to increase from 9-to 17 years of age, although more for boys than girls. Furthermore, CRF values in youth are expected to track into adulthood. In this presentation we will show that individual developmental pathways of PACER can be quite distinct from the widely used normative data. Two hundred and twenty nine children (56% boys) were followed longitudinally from age 9 to 15. Multilevel modelling of changes was conducted in HLM 6.0 software. Ordinary least square (OLS) regressions were used to estimate each child’s linear regression equation for the PACER test. Children were clustered into three groups according to their rate of change (slope values), thus representing distinct developmental pathways (Low, Average and High Rate of Change). These three developmental pathways were tested on a hierarchical linear regression (measures within persons), resulting on a very good model fit. Outputs were compared with the normative data setting. Results showed that three groups of children with similar rate of change on their developmental PACER performance can be found, but these pathways do not fully copy with the normative tables’ information. In conclusion, we suggest that developmental pathways, using longitudinal information, should be preferably used for predicting present and future outcomes.
  • The present study examined differences in 5–9-year-old children’s motor competence (MC) across Northern-, Central-, and Southern European countries using the Körperkoordinationstest für Kinder (KTK). A secondary aim was to examine whether the cross-cultural differences in MC accumulate in the interaction with children’s age group and body weight status determined as being normal or overweight. Methods: Data was pooled from four independent studies conducted in Finland (mean age 7.31 +/− 1.38 years, n = 360 + 432), Belgium (mean age 8.19 +/− 1.14 years, n = 1936) and Portugal (mean age 8.31 ± 1.02 years, n = 758) between years 2008 and 2016. Differences between countries in the raw scores of KTK and the interaction effects were tested by using oneand two-way analyses of covariance. Age, sex and BMI percentile were used as covariates. Results: Country explained significantly (9%) the variance in MC, meanwhile age (44%) and BMI percentile (5%) were significant covariates. Age and country had significant interaction effect (6%), as well as country and body weight status (2%). Conclusions: Results strengthen existing literature showing cross-cultural differences in children’s MC. Based on the present results, the differences are accumulating along the childhood. Novel finding of the study suggests polarization in the development of MC between normal and overweight children is differing across countries. Further studies is needed for exploring the reasons explaining the age and body weight status interaction effects in cross-cultural differences in children’s MC
  • To identify classes of different developmental trajectories of body massindex (BMI) andtestingit for differencesinmotor competence (MC) and physical fitness (PF). Methods: This is a mixed longitudinal study lasting five years. Participants were N=147 of both sexes (69 girls) divided in 8 cohorts, at baseline the youngest and the oldest cohorts had 4 and 11 years of age respectively. Height and weight were assessed and BMI was calculated [weight (kg)/height (m2)]. MC was assessed with KTK, TGMD-2 and PF was evaluated with one-mile run/walk. Developmental trajectories of BMI were identified using latent class mixed modeling. Post-hoc analyses were calculated using linear models. Results: Modeling revealed four based on the information criteria minimum. However, two classes show very low numbers (n < 6). Therefore,twomeaningful classes wereidentified based on modelling and content related considerations. Class 1 (36%) show larger initial BMI and a larger slope compared to class 2 (64%). No differences were identified in locomotion and object control. ForClass 2increases faster comparedto class 1 (p < .05) and class 2 shows better physical fitness (p < .05). Conclusion: This study identified two meaningful trajectories for children based on their BMI development across five time points. In line with previous research, children with slower increasing BMI showed better physical performances and performance improvements. This shows the importance and interplay between multiple indicators of physical health.

publication date

  • January 1, 2018