Predicting risk of low birth weight offspring from maternal features and blood polycyclic aromatic hydrocarbon concentration.

Abstract Prenatal exposure to organic pollutants increases the risk of low birth weight (LBW) offspring. Women involved in the plucking of tea leaves can be exposed to polycyclic aromatic hydrocarbons (PAHs) during pregnancy through inhalation and diet. Therefore, the aim of the study was to investigate the association of maternal socio-demographic features and blood PAHs concentration with LBW; also to develop a model for predicting LBW risk. The study was performed by recruiting 55 women who delivered LBW and 120 women with NBW (normal birth weight) babies from Assam Medical College. The placental tissue, maternal and cord blood samples were collected. A total of sixteen PAHs and cotinine were analysed by HPLC and GC/MS. Association of PAHs concentration with weight was determined using correlation and multiple logistic regression analyses. Predictive model was developed using SVMlight and Weka software. Maternal features such as age, education, food habits, occupation, etc. were found to be associated with LBW deliveries (p-value http://dev.icmr.org.in/plbw/ webserver. With machine learning gaining more importance in medical science; our webserver could be instrumental for researchers and clinicians to predict the state of the fetus.