Login / Signup

Nocturnal sleep duration trajectories in early childhood and school performance at age 10 years.

Dominique PetitEvelyne TouchetteMarie-Helene PennestriJean PaquetSylvana M CôtéRichard E TremblayMichel BoivinJacques Y Montplaisir
Published in: Journal of sleep research (2023)
Sleep plays a fundamental role in brain development and resultant functions. The aim was to verify whether nocturnal sleep duration during early childhood has long-term associations with academic achievement at age 10 years. The present study is part of the Quebec Longitudinal Study of Child Development, a representative cohort of infants born in 1997-1998 in the province of Quebec, Canada. Children with known neurological conditions were excluded from this cohort. Four trajectories of parent-reported nocturnal sleep duration at ages 2.5, 3, 4, 5 and 6 years were determined using a SAS procedure named PROC TRAJ. Sleep duration at age 10 years was also reported. Teachers provided data on academic performance when the children were age 10 years. These data were available for 910 children (430 boys, 480 girls; 96.6% Caucasians). Univariate and multivariable logistic regressions were performed using SPSS. Children who slept less than 8 hr per night at 2.5 years but normalized later on (Traj1) had three-five times the odds of having grades below the class average in reading, writing, mathematics and science compared with children who slept sufficiently (Traj3-4: 10-11 hr per night). Children who slept about 9 hr per night throughout childhood (Traj2) had two-three times the odds of being below the class average in mathematics and science. Sleep duration at age 10 years was not correlated with the academic performance. These results point to the presence of a very important early period during which sufficient sleep is needed to fine-tune the functions necessary for academic achievement later on.
Keyphrases
  • young adults
  • sleep quality
  • physical activity
  • blood pressure
  • depressive symptoms
  • public health
  • mental health
  • brain injury
  • machine learning
  • minimally invasive
  • air pollution
  • electronic health record
  • sleep apnea