1.Effect of exposure to trace elements in the soil on the prevalence of neural tube defects in a high-risk area of China.
Jing HUANG ; Jilei WU ; Tiejun LI ; Xinming SONG ; Bingzi ZHANG ; Pingwen ZHANG ; Xiaoying ZHENG
Biomedical and Environmental Sciences 2011;24(2):94-101
OBJECTIVEOur 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.
METHODSWe 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.
RESULTSTin, 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.
CONCLUSIONAs 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.
China ; epidemiology ; Dose-Response Relationship, Drug ; Environmental Exposure ; Female ; Humans ; Metals ; chemistry ; toxicity ; Models, Biological ; Neural Tube Defects ; chemically induced ; epidemiology ; Pregnancy ; Prevalence ; Soil Pollutants ; chemistry ; toxicity ; Trace Elements ; chemistry ; toxicity
2. Epidemiological characteristics of amoebic dysentery in China, 2015-2018
Jilei HUANG ; Zhaorui CHANG ; Canjun ZHENG ; Huihui LIU ; Yingdan CHEN ; Junling SUN
Chinese Journal of Epidemiology 2020;41(1):90-95
Objective:
To understand the characteristics and changes of the incidence of amoebic dysentery in China during 2015-2018, explore the causes of high incidence in some areas and provide a data base for the development of national prevention and control strategies and measures.
Methods:
Data were collected from the infectious disease reporting management information system from Chinese Disease Control and Prevention. To understand the seasonal, population and area distributions of amoebic dysentery, descriptive epidemiological method and software SPSS 16.0 were used to analyze the amoebic dysentery data.
Results:
A total of 4 366 amoebic dysentery cases were reported without death in China during 2015-2018. The reported average annual incidence was 0.08/100 000, and the overall proportion of laboratory confirmed cases was 68.23