Machine learning methods to assess risk for prenatal and neonatal iron deficiency anemia from maternal stress exposure

NIH RePORTER · NIH · R00 · $248,957 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY This K99 application aims to determine biological and behavioral pathways by which maternal psychosocial stress in pregnancy impacts risk for maternal and infant iron deficiency anemia (IDA). IDA is one of the most common causes of anemia worldwide, and around 20% of women in the US experience a stressful life event throughout their pregnancy. Due to the increased iron demands of pregnancy, pregnancy itself poses a significant risk of IDA, especially for low-income and racially- and ethnically-minoritized women. IDA increases the risk of adverse pregnancy outcomes and can negatively impact the iron status of the neonate that may cause irreversible harm to neurodevelopment. There is growing concern that oral vitamin supplementation might not be enough to counteract the risks of IDA in the context of systemic inflammation, including inflammation produced by chronic psychosocial stress and subsequent neuroendocrine dysregulation. Maternal psychosocial stress has been associated with infant iron status previously, but the potential biological mechanisms are not yet characterized despite the

Key facts

NIH application ID
11136629
Project number
4R00HD109373-03
Recipient
NORTHEASTERN UNIVERSITY
Principal Investigator
Brie M Reid
Activity code
R00
Funding institute
NIH
Fiscal year
2024
Award amount
$248,957
Award type
4N
Project period
2022-09-01 → 2027-08-31