M. Boonzaaijer1, O. Oudgenoeg-Paz2, I. Suir1, J. Nuysink1, M.J. Volman2, M. Jongmans2
1University of Applied Science, Knowledge Center Healthy and Sustainable Living, Research Group Lifestyle and Health, Utrecht, Netherlands, 2Utrecht University, Faculty of Social and Behavioral Sciences, Department of Pedagogical and Educational Sciences, Utrecht, Netherlands
Background: Interindividual variability in gross motor development of infants is substantial and challenges the interpretation of motor assessments. Longitudinal research designs can provide insight into individual trajectories and factors associated with this variability.
Purpose: To model a gross motor growth curve of healthy term-born infants from 3.5 to 15.5 months with the Alberta Infant Motor Scale (AIMS) and to explore groups of infants with similar patterns of development.
Methods: A prospective longitudinal study was carried out including six assessments of gross motor development of healthy term-born infants from 3.5 months to 15.5 months assessed with the AIMS. A home-video method for parents enabled the data collection. Infant- and parent characteristics were collected by online questionnaires. The individual trajectories were examined. A Linear Mixed Model analysis was applied to model a gross motor growth curve on the total population. The final model was controlled for important covariates. Subsequently, a cluster analysis was conducted to explore groups with different pathways. Group characteristics were described and gross motor growth curves for the subgroups were modeled.
Results: A total of 103 infants, with more than two motor assessments available, were included in the analysis. A Linear Mixed Model analysis showed that the best fit for the overall data was a cubic function (F(1,571) = 89.68, p <.001). Only the factor birth rank remained in the final model with a significant effect on the shape of the curve (β -1.13, SD =.52 ; p = .033). Cluster analysis delineated three clinically relevant groups:
1) Early developers (32%),
2) Gradual developers (45.6%), and
3) Late bloomers (22.4%).
Significant differences between the groups were found for the factors birth rank and maternal education. The generalizability of the outcomes beyond the study sample should be carefully considered due to sample size and overrepresentation of parents with advanced education.
1) Early developers (32%),
2) Gradual developers (45.6%), and
3) Late bloomers (22.4%).
Significant differences between the groups were found for the factors birth rank and maternal education. The generalizability of the outcomes beyond the study sample should be carefully considered due to sample size and overrepresentation of parents with advanced education.
Conclusion(s): Modeling a gross motor curve of AIMS raw scores is possible using Linear Mixed Models. Although it concerned a homogeneous sample, birth rank was found to have a significant effect on the shape of the curve. Using cluster analysis, three groups with different gross motor developmental trajectories were identified in the data: Early developers, Gradual developers, and Late bloomers. The distinction of these groups within a sample of typically developing infants is clinically relevant because this visualizes the variation in gross motor development that is present within the normal range.
Implications: This motor growth curve of typical developing Dutch infants provides a baseline for future research on developmental trajectories of infants at risk such as preterm-born infants or infants with congenital heart diseases. Furthermore, identifying various pathways of typically developing infants increases knowledge that supports clinicians to estimate whether the observed motor behavior lies within the normal range or not. It can also help parents to build adequate expectations of their baby’s development.
Funding, acknowledgements: The Netherlands Organization for Scientific Research (NWO), Teachers Grant (023.006.070).
Keywords: infants, gross motor development, longitudinal design
Topic: Paediatrics
Did this work require ethics approval? Yes
Institution: University Medical Centre Utrecht, The Netherlands
Committee: Medical Ethical Board METC/ UMCU Utrecht, The Netherlands
Ethics number: METC number 16/366C
All authors, affiliations and abstracts have been published as submitted.
