Maternal and Neonatal Risk Factors Affecting the Occurrence of Neurodevelopmental Disorders: A Population-Based Nationwide Study.
Seong Woo KimTaemi YoukJi Yong KimPublished in: Asia-Pacific journal of public health (2021)
To investigate the maternal and neonatal risk factors related to pregnancy and birth affecting the occurrence of neurodevelopmental disorders to their children using the medical claim data for the whole population. The study was conducted on all the babies born in Korea from 2005 to 2009 based on data from the National Health Information Database. All birth records were tracked from birth to December 31, 2015. To analyze factors related to the mother, data related to the mother of the newborn were collected. Increased maternal age was found to increase the risk of cerebral palsy (adjusted odds ratio [aOR] = 1.46) and autism spectrum disorder (aOR = 1.48), while lowering the risk of intellectual disability (aOR = 1.83) and speech and language impairment (aOR = 1.41) compared with the reference group aged 25 to 29 years old. The incidence affected by socioeconomic factors varied according to the types of disorders. Among various risk factors, prematurity or low birth weight, problems associated with amniotic fluid or amniotic membrane, preeclampsia or eclampsia, and cesarean section affect the incidence of neurodevelopmental disorders. To reduce the incidence or severity of neurodevelopmental disorders, a better understanding of the risk factors of neurodevelopmental disorders is important. The results of this study can be used as basic data to help such understanding.
Keyphrases
- risk factors
- autism spectrum disorder
- low birth weight
- intellectual disability
- pregnancy outcomes
- gestational age
- birth weight
- health information
- preterm infants
- electronic health record
- preterm birth
- big data
- risk assessment
- cerebral palsy
- early onset
- young adults
- mental health
- human milk
- social media
- congenital heart disease
- emergency department
- umbilical cord
- mesenchymal stem cells
- physical activity
- machine learning