Healthy newborns' neurobehavior: norms and relations to medical and demographic factors

J Pediatr. 2012 Dec;161(6):1073-9. doi: 10.1016/j.jpeds.2012.05.036. Epub 2012 Jun 23.


Objective: To generate neurobehavioral norms for an unselected random sample of clinically healthy newborns by examining the newborns with use of the Neonatal Intensive Care Unit Network Neurobehavioral Scale (NNNS).

Study design: We recruited 344 healthy mothers and newborns from a well-child nursery. The NNNS, a 128-item assessment of infant neurobehavior, was used to examine newborn performance. Associations between 11 NNNS summary scales and the stress/abstinence scale, as well as medical and demographic variables, were evaluated. Mean, SD, and 5th and 95th percentile values for the summary scores of the NNNS are presented.

Results: NNNS scores from the 10th to the 90th percentile represent a range of normative performance. Performance on different neurobehavioral domains was related to marital status, ethnicity, prenatal, intrapartum and neonatal risk factors, complications during labor/delivery, cesarean delivery, gestational age, the age of the newborn at testing, and infant sex.

Conclusion: These data provide clinicians and researchers with normative data for evaluation of newborn neurobehavior. Even in a low-risk sample, medical and demographic factors below clinical cut-offs were related to newborn performance. Infants with scores outside the ranges for the 11 NNNS summary scores and the stress/abstinence scale may need further observation and, if necessary, early intervention.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Analysis of Variance
  • Cesarean Section
  • Demography
  • Female
  • Gestational Age
  • Humans
  • Infant Behavior* / ethnology
  • Infant Behavior* / physiology
  • Infant Behavior* / psychology
  • Infant, Newborn
  • Male
  • Neuropsychological Tests*
  • Pregnancy
  • Pregnancy Complications
  • Reference Values
  • Regression Analysis
  • Sex Factors
  • Socioeconomic Factors