HUANG Jing; WU JiLei; LI TieJun; SONG XinMing; ZHANG BingZi; ZHANG PingWen; ZHENG XiaoYing

doi:10.3967/0895-3988.2011.02.002

Effect of Exposure to Trace Elements in the Soil on the Prevalence of Neural Tube Defects in a High-Risk Area of China

HUANG Jing, WU JiLei, LI TieJun, SONG XinMing, ZHANG BingZi, ZHANG PingWen, ZHENG XiaoYing

文章导航 > Biomedical and Environmental Sciences > 2011 > 24(2): 94-101

HUANG Jing, WU JiLei, LI TieJun, SONG XinMing, ZHANG BingZi, ZHANG PingWen, ZHENG XiaoYing. Effect of Exposure to Trace Elements in the Soil on the Prevalence of Neural Tube Defects in a High-Risk Area of China[J]. Biomedical and Environmental Sciences, 2011, 24(2): 94-101. doi: 10.3967/0895-3988.2011.02.002

Citation:

HUANG Jing, WU JiLei, LI TieJun, SONG XinMing, ZHANG BingZi, ZHANG PingWen, ZHENG XiaoYing. Effect of Exposure to Trace Elements in the Soil on the Prevalence of Neural Tube Defects in a High-Risk Area of China[J]. Biomedical and Environmental Sciences, 2011, 24(2): 94-101. doi: 10.3967/0895-3988.2011.02.002

doi: 10.3967/0895-3988.2011.02.002

基金项目: the National "973" project on Population and Health(2007CB5119001)%the National Yang-Zi Scholar Program,211 and 985 projects of Peking University(20020903)

Effect of Exposure to Trace Elements in the Soil on the Prevalence of Neural Tube Defects in a High-Risk Area of China

School of Mathematical Sciences, Peking University, Beijing 100871, China
Institute of Population Research, Peking University, Beijing 100871, China

Funds: the National "973" project on Population and Health(2007CB5119001)%the National Yang-Zi Scholar Program,211 and 985 projects of Peking University(20020903)

摘要: Objective Our objective is to build a model that explains the association between the exposure to trace elements in the soil and the risk of neural tube defects. Methods We built a function with different parameters to describe the effects of trace elements on neural tube defects. The association between neural tube defects and trace element levels was transformed into an optimization problem using the maximum likelihood method. Results Tin, lead, nickel, iron, copper, and aluminum had typical layered effects (dosage effects) on the prevalence of neural tube defects. Arsenic, selenium, zinc, strontium, and vanadium had no effect, and molybdenum had one threshold value that affected the prevalence of birth defects. Conclusion As an exploratory research work, our model can be used to determine the direction of the effect of the trace element content of cultivated soil on the risk of neural tube defects, which shows the clues by the dosage effect of their toxicological characteristics. Based on our findings, future biogeochemical research should focus on the direct effects of trace elements on human health.
- /
- /
- /
- /
Abstract: Objective Our objective is to build a model that explains the association between the exposure to trace elements in the soil and the risk of neural tube defects. Methods We built a function with different parameters to describe the effects of trace elements on neural tube defects. The association between neural tube defects and trace element levels was transformed into an optimization problem using the maximum likelihood method. Results Tin, lead, nickel, iron, copper, and aluminum had typical layered effects (dosage effects) on the prevalence of neural tube defects. Arsenic, selenium, zinc, strontium, and vanadium had no effect, and molybdenum had one threshold value that affected the prevalence of birth defects. Conclusion As an exploratory research work, our model can be used to determine the direction of the effect of the trace element content of cultivated soil on the risk of neural tube defects, which shows the clues by the dosage effect of their toxicological characteristics. Based on our findings, future biogeochemical research should focus on the direct effects of trace elements on human health.
- Trace element /
- Neural tube defects /
- Risk factors identification /
- Poisson model /
- Maximum likelihood estimation

[1]	LIU Can, ZHOU Shi Hui, SU Hong, YANG Wen Qin, LU Jiao. An Artificial Neural Network Model Combined with Dietary Retinol Intake from Different Sources to Predict the Risk of Nonalcoholic Fatty Liver Disease . Biomedical and Environmental Sciences, 2023, 36(12): 1123-1135. doi: 10.3967/bes2023.120
[2]	WANG Shan, ZENG Yu Bing, PEI Pei, HE Xue Jia, LIU Fan, WANG Yi, ZHANG Ting. Characterization of CircRNA-Associated CeRNA Networks in Folate Deficiency-Induced Neural Tube Defects . Biomedical and Environmental Sciences, 2023, 36(9): 837-849. doi: 10.3967/bes2023.071
[3]	QIN Jia Bi, LUO Liu, SUN Meng Ting, HUANG Peng, WANG Ting Ting, ZHANG Sen Mao, LI Jin Qi, LI Yi Huan, CHEN Le Tao, DIAO Jing Yi, ZHU Ping. Association between Maternal Drug Use and Cytochrome P450 Genetic Polymorphisms and the Risk of Congenital Heart Defects in Offspring . Biomedical and Environmental Sciences, 2022, 35(1): 45-57. doi: 10.3967/bes2022.006
[4]	S. Karkuzhali. Identification and Prediction of Diabetic Macular Edema on Two-dimensional Fundus Images with Raphe Assessment and Deep Convolution Neural Networks . Biomedical and Environmental Sciences, 2022, 35(12): 1156-1160. doi: 10.3967/bes2022.147
[5]	YE Cheng Yin, LI Jin Mei, WU Jing Hua, LI Zheng, XIAO Juan, YIN Xiao Yu, WANG Da Hui, XU Guo Zhang, YANG Lei. A Risk Prediction Model for Ischemic Stroke in Southern Chinese Population: Impact of Multiple Genetic Variants and Clinical/Lifestyle Factors . Biomedical and Environmental Sciences, 2021, 34(8): 641-645. doi: 10.3967/bes2021.089
[6]	LI Qiang, SHEN Qun Lun, XU Chao Nan, LI Ming Liang, MA Zhi Min, ZHANG Shan, CHEN Shuo, ZHANG Min Ying, ZHANG Jing Bo, LIU Feng, YANG Xing Hua. A Self-test Prediction Model to Determine the Probability Risk of Non-alcoholic Fatty Liver Disease . Biomedical and Environmental Sciences, 2020, 33(11): 857-861. doi: 10.3967/bes2020.116
[7]	SAI Xiao Yong, CHEN Qiao, LUO Ting Gang, SUN Yuan Yuan, SONG Yu Jian, CHEN Juan. Analysis of Factors Influencing Insomnia and Construction of a Prediction Model: A Cross-sectional Survey on Rescuers . Biomedical and Environmental Sciences, 2020, 33(7): 502-509. doi: 10.3967/bes2020.067
[8]	SONG Xiu Ping, ZHANG Hai Bin, LIU Qi Yong, SUN Ji Min, XU Lei, GU Shao Hua, SUN Wan Wan, YUE Yu Juan, REN Dong Sheng, WANG Jun, LI Dong Mei. Seroprevalence of Bartonella henselae and Identification of Risk Factors in China . Biomedical and Environmental Sciences, 2020, 33(1): 72-75. doi: 10.3967/bes2020.011
[9]	Mohammad Rezaei, Bahareh Ghasemidehkordi, Babak Peykarestan, Nabi Shariatifar, Maryam Jafari, Yadolah Fakhri, Maryam Jabbari, Amin Mousavi Khaneghah. Potentially Toxic Element Concentration in Fruits Collected from Markazi Province (Iran): A Probabilistic Health Risk Assessment . Biomedical and Environmental Sciences, 2019, 32(11): 839-853. doi: 10.3967/bes2019.105
[10]	LIN Hong, LUO Mi Yang, LUO Jia You, ZENG Rong, LI Ya Mei, DU Qi Yun, FANG Jun Qun. Demographic Characteristics and Environmental Risk Factors Exposure of Birth Defects in Pregnant Women: A Population-based Study . Biomedical and Environmental Sciences, 2019, 32(1): 51-57. doi: 10.3967/bes2019.008
[11]	LI Jun Jian, LI Wei, XU Guang Rong, XU Ke Jun, YE Ping, QUAN Yu, NING Rong Bing, GAO Hai Jun, HE Qian Jun, ZHOU Ying, WU Wei Ping. Analysis on Serum Trace Element Levels of Echinococciasis Patients in Garze Tibetan Autonomous Prefecture in Sichuan, China, 2011 . Biomedical and Environmental Sciences, 2015, 28(9): 683-686. doi: 10.3967/bes2015.096
[12]	NIU Pei Hua, ZHANG Chen, WANG Ji, TAN Wen Jie, MA Xue Jun. Detection and Identification of Six Foodborne Bacteria by Two-tube Multiplex Real Time PCR and Melting Curve Analysis . Biomedical and Environmental Sciences, 2014, 27(10): 770-778. doi: 10.3967/bes2014.112
[13]	YU Shan Fa, NAKATA Akinori, GU Gui Zhen, SWANSON Naomi G, ZHOU Wen Hui, HE Li Hua, WANG Sheng. Co-effect of Demand-control-support Model and Effort-reward Imbalance Model on Depression Risk Estimation in Humans:Findings from Henan Province of China . Biomedical and Environmental Sciences, 2013, 26(12): 962-971. doi: 10.3967/bes2013.031
[14]	LIAO Yi Lan, WANG Jin Feng, WU Ji Lei, WANG Jiao Jiao, ZHENG XiaoYing. PSO/ACO Algorithm-based Risk Assessment of Human Neural Tube Defects in Heshun County, China . Biomedical and Environmental Sciences, 2012, 25(5): 569-576. doi: 10.3967/0895-3988.2012.05.011
[15]	JIN-FENG WANG, XIN LIU, YI-LAN LIAO, HONG-YAN CHEN, WAN-XIN LI, XIAO-YING ZHENG. Prediction of Neural Tube Defect Using Support Vector Machine . Biomedical and Environmental Sciences, 2010, 23(3): 167-172.
[16]	GONG CHEN, LI-JUN PEI, JIAN HUANG, XIN-MING SONG, LIANG-MING LIN, XUE GU, JIAN-XINWU, FANG WANG, JI-LEI WU, JIA-PENG CHEN, JU-FEN LIU, RUO-LEI XIN, TING ZHANG, XIAO-YING ZHENG. Unusual Patterns of Neural Tube Defects in a High Risk Region of Northern China . Biomedical and Environmental Sciences, 2009, 22(4): 340-344.
[17]	WEN-ZHEN ZHU, XIANG LI, JIAN-PIN QI, ZHOU-PING TANG, WH WANG, LI WEI, HAO LEI. Experimental Study of Cell Migration and Functional Differentiation of Transplanted Neural Stem Cells Co-labeled with Superparamagnetic Iron Oxide and Brdu in an Ischemic Rat Model . Biomedical and Environmental Sciences, 2008, 21(5): 420-424.
[18]	JIN LI, CHONG-RAN SUN, HAN ZHANG, KAM-SZE TSANG, JUN-HUA LI, SHAO-DONG ZHANG, YI-HUA AN. Induction of Functional Recovery by Co-transplantation of Neural Stem Cells and Schwann Cells in a Rat Spinal Cord Contusion Injury Model . Biomedical and Environmental Sciences, 2007, 20(3): 242-249.
[19]	XIANG GAO, QI YU, LI-MIN CHEN. Health Effects of Airborne Particulate Matter Trace Elements . Biomedical and Environmental Sciences, 2005, 18(5): 349-355.
[20]	XIAN-BING TANG, SHU-YI SI, YUE-QIN ZHANG. Identification of a New Peptide Deformylase Gene From Enterococcus faecium and Establishment of a New Screening Model Targeted on PDF for Novel Antibiotics . Biomedical and Environmental Sciences, 2004, 17(3): 350-358.

点击查看大图

计量

文章访问数: 1569
HTML全文浏览量: 375
PDF下载量: 64
被引次数: 0

Effect of Exposure to Trace Elements in the Soil on the Prevalence of Neural Tube Defects in a High-Risk Area of China

doi: 10.3967/0895-3988.2011.02.002

基金项目: the National "973" project on Population and Health(2007CB5119001)%the National Yang-Zi Scholar Program,211 and 985 projects of Peking University(20020903)

刊出日期: 2011-04-20

关键词:

Trace element /

Neural tube defects /

Risk factors identification /

Poisson model /

Maximum likelihood estimation

摘要: Objective Our objective is to build a model that explains the association between the exposure to trace elements in the soil and the risk of neural tube defects. Methods We built a function with different parameters to describe the effects of trace elements on neural tube defects. The association between neural tube defects and trace element levels was transformed into an optimization problem using the maximum likelihood method. Results Tin, lead, nickel, iron, copper, and aluminum had typical layered effects (dosage effects) on the prevalence of neural tube defects. Arsenic, selenium, zinc, strontium, and vanadium had no effect, and molybdenum had one threshold value that affected the prevalence of birth defects. Conclusion As an exploratory research work, our model can be used to determine the direction of the effect of the trace element content of cultivated soil on the risk of neural tube defects, which shows the clues by the dosage effect of their toxicological characteristics. Based on our findings, future biogeochemical research should focus on the direct effects of trace elements on human health.

English Abstract

Effect of Exposure to Trace Elements in the Soil on the Prevalence of Neural Tube Defects in a High-Risk Area of China

School of Mathematical Sciences, Peking University, Beijing 100871, China

Institute of Population Research, Peking University, Beijing 100871, China

Funds: the National "973" project on Population and Health(2007CB5119001)%the National Yang-Zi Scholar Program,211 and 985 projects of Peking University(20020903)

Publish Date: 2011-04-20

Keywords:

Abstract: Objective Our objective is to build a model that explains the association between the exposure to trace elements in the soil and the risk of neural tube defects. Methods We built a function with different parameters to describe the effects of trace elements on neural tube defects. The association between neural tube defects and trace element levels was transformed into an optimization problem using the maximum likelihood method. Results Tin, lead, nickel, iron, copper, and aluminum had typical layered effects (dosage effects) on the prevalence of neural tube defects. Arsenic, selenium, zinc, strontium, and vanadium had no effect, and molybdenum had one threshold value that affected the prevalence of birth defects. Conclusion As an exploratory research work, our model can be used to determine the direction of the effect of the trace element content of cultivated soil on the risk of neural tube defects, which shows the clues by the dosage effect of their toxicological characteristics. Based on our findings, future biogeochemical research should focus on the direct effects of trace elements on human health.

Citation:

HUANG Jing, WU JiLei, LI TieJun, SONG XinMing, ZHANG BingZi, ZHANG PingWen, ZHENG XiaoYing. Effect of Exposure to Trace Elements in the Soil on the Prevalence of Neural Tube Defects in a High-Risk Area of China[J]. Biomedical and Environmental Sciences, 2011, 24(2): 94-101. doi: 10.3967/0895-3988.2011.02.002

全文HTML

下载: 全尺寸图片幻灯片

返回文章

用微信扫码二维码

分享至好友和朋友圈

Biomedical and Environmental Sciences ISSN 0895-3988 CN 11-2816 / Q

Publish Under the Auspices of Chinese Center for Disease Control and Prevention

Distributed by Chinese Center for Disease Control and Prevention

Quick Links

Supported by Beijing Renhe Information Technology Co. Ltd E-mail: info@rhhz.net

doi: 10.3967/0895-3988.2011.02.002

Effect of Exposure to Trace Elements in the Soil on the Prevalence of Neural Tube Defects in a High-Risk Area of China

计量

出版历程

Effect of Exposure to Trace Elements in the Soil on the Prevalence of Neural Tube Defects in a High-Risk Area of China

doi: 10.3967/0895-3988.2011.02.002

English Abstract

Effect of Exposure to Trace Elements in the Soil on the Prevalence of Neural Tube Defects in a High-Risk Area of China

School of Mathematical Sciences, Peking University, Beijing 100871, China Institute of Population Research, Peking University, Beijing 100871, China

全文HTML

目录

School of Mathematical Sciences, Peking University, Beijing 100871, China

Institute of Population Research, Peking University, Beijing 100871, China