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Prematurity and potential predictors

Tiffany Field1, Miguel Diego, Maria Hernandez-Reif

  • 1Touch Research Institute, University of Miami Miller School of Medicine, Miami, Florida, USA. tfield@med.miami.edu

The International Journal of Neuroscience
|January 22, 2008
PubMed

Insights

Identifying predictors for preterm birth is crucial for reducing neonatal mortality. This review explores psychological, physiological, and biochemical factors, and presents massage therapy as a potential intervention to lower cortisol levels and prevent prematurity.

Area of Science:

  • Neonatal Health
  • Reproductive Medicine
  • Psychoneuroendocrinology

Background:

  • Prematurity remains the primary cause of neonatal mortality and long-term developmental issues.
  • Identifying reliable predictors and effective interventions for prematurity is a critical public health priority.

Purpose of the Study:

  • To review recent research on psychological, physiological, and biochemical predictors of preterm birth.
  • To present a research program linking interventions to identified predictors, specifically massage therapy for cortisol reduction.

Main Methods:

  • Literature review of recent studies on prematurity predictors.
  • Exploration of psychological stressors (depression, anxiety, relationship difficulties, social isolation).
  • Identification of biochemical markers (corticotropin-releasing hormone, cortisol, fetal fibronectin).

Main Results:

  • Psychological factors like depression and anxiety are linked to increased prematurity risk.
  • Biochemical markers such as cortisol and fetal fibronectin show potential as predictors.
  • Massage therapy is proposed as an intervention to reduce cortisol and potentially mitigate prematurity.

Conclusions:

  • Understanding the multifactorial nature of prematurity is essential for developing targeted interventions.
  • Linking interventions like massage therapy to physiological predictors like cortisol offers a promising avenue for prevention.
  • Further research is needed to validate these predictors and interventions in diverse populations.

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