Stability of Executive Functioning of Moderately-Late Preterm and Full-Term Born Children at Ages 11 and 19: The TRAILS Cohort Study.
Sijmen A ReijneveldJorijn HornmanSarai R BoelemaAndrea F de WinterPublished in: International journal of environmental research and public health (2021)
Moderately-late preterm-born children (MLPs, 32-36 weeks gestational age, GA) have poorer executive functioning (EF) at primary school age than full-term children (FTs). Evidence is lacking on their EF in adolescence, but for early preterm-born children, this has been shown to be much poorer. We, therefore, compared EF of MLPs and FTs at ages 11 and 19 and assessed development between these ages. We obtained data from TRAILS, a community-based prospective cohort study in the northern Netherlands, on 98 MLPs and 1832 FTs. We assessed EF by the Amsterdam Neuropsychological Tasks (ANT) at ages 11 and 19 years and computed gender-specific z-scores on reaction time and accuracy. We compared baseline speed, pattern search, working memory, sustained attention, inhibition, and attentional flexibility of MLPs and FTs crude, and adjusted for small-for-GA status, socioeconomic status, and estimated intelligence. MLPs and FTs performed similarly on all EF components at ages 11 and 19, except for the speed, but not the accuracy measure of attentional flexibility. This was slightly poorer for MLPs than FTs at age 19 (adjusted B 0.25; 95% confidence interval: 0.00 to 0.50; p = 0.047), but not at age 11 (adjusted B -0.02; -0.19 to 0.22; p = 0.87). Differences in EF between MLPs and FTs did not change significantly from age 11 to 19. MLPs had comparable EF on most components as FTs, with only attentional flexibility at age 19 developing slightly poorer for MLPs than for FTs. These findings suggest the effects of MLP birth on long-term EF to be small.
Keyphrases
- gestational age
- working memory
- birth weight
- preterm birth
- young adults
- transcranial direct current stimulation
- low birth weight
- attention deficit hyperactivity disorder
- pet ct
- preterm infants
- magnetic resonance imaging
- body mass index
- pregnant women
- depressive symptoms
- big data
- weight loss
- weight gain
- deep learning
- data analysis