Predicting risk of low birth weight offspring from maternal features and blood polycyclic aromatic hydrocarbon concentration
Predicting risk of low birth weight offspring from maternal features and blood polycyclic aromatic hydrocarbon concentration
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DOI：
10.1016/j.reprotox.2020.03.009
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发表时间：
2020-06-01
影响因子：
3.3
通讯作者：
Jain, Arun Kumar
中科院分区：
文献类型：
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作者：
Kumar, Shashi Nandar;Saxena, Pallavi;Jain, Arun Kumar
产前暴露于有机污染物会增加低出生体重（LBW）后代的风险。参与采摘茶叶的妇女在怀孕期间可能通过吸入和饮食接触到多环芳烃（PAHs）。因此，本研究的目的是调查母亲的社会人口统计学特征和血液PAH浓度与LBW的关系，并建立预测LBW风险的模型。该研究招募了55名分娩LBW的妇女和120名来自阿萨姆医学院的NBW（正常出生体重）婴儿的妇女。收集胎盘组织、母体和脐带血样本。采用HPLC和GC-MS分析了16种多环芳烃和可替宁。采用相关分析和多元Logistic回归分析确定了多环芳烃浓度与体重的关系。使用SVMlight和Weka软件开发预测模型。发现母亲特征如年龄、教育、饮食习惯、职业等与LBW分娩相关（p值
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 PAH 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 PAH 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