Is the Concentration of Cadmium, Lead, Mercury, and Selenium Related to Preterm Birth?
Engin YıldırımMehmet Kürşat DericiEmre DemirHakan ApaydınÖzgür KoçakÖzgür KanÜmit GörkemPublished in: Biological trace element research (2019)
Environmental pollution and exposure of people to heavy metals cause many bad obstetric outcomes. Our aim is to demonstrate the role of cadmium (Cd), lead (Pb), mercury (Hg), and selenium (Se) in preterm labor etiology with a case-control study. In this study, between November 2017 and April 2018, preterm delivery mothers and term delivery mothers were compared in Çorum, Turkey. All deliveries were performed with cesarean sections and there were 30 mothers in the control group and 20 in the study group. The maternal blood, maternal urine, umbilical cord blood, and heavy metal levels in the amnion fluid in both groups were studied. Graphite furnace atomic absorption spectrometry was used to determine the blood concentration of Cd, Pb, Hg, and Se. We found lower levels of selenium in blood and urine of preterm delivery mothers and umbilical cord and amnion fluids of preterm infants (p < 0.01). We found a statistically significant positive correlation at selenium levels between mother's blood and umbilical cord blood (r (50) = 0.896, p < 0.001) and between maternal urine and amniotic fluid (r (50) = 0.841, p < 0.001). We have not found a similar correlation between mother and fetus of other metals (p > 0.05). We found that selenium levels were lower in mothers who were preterm birth in the light of the data in our study. We could not determine the positive or negative correlation of Cd, Pb, and Hg levels in blood, urine, and amniotic fluid samples with preterm birth.
Keyphrases
- preterm birth
- heavy metals
- umbilical cord
- low birth weight
- mesenchymal stem cells
- gestational age
- preterm infants
- birth weight
- health risk assessment
- risk assessment
- health risk
- pregnant women
- human health
- type diabetes
- mass spectrometry
- sewage sludge
- pregnancy outcomes
- artificial intelligence
- air pollution
- adipose tissue
- climate change
- weight gain
- nk cells
- electronic health record
- aqueous solution
- machine learning
- liquid chromatography