94 Bomed Envron Sc, 011; 4(): 94 101 Orgnal Artcle Effect of Exposure to Trace Elements n the Sol on the Prevalence of Neural Tube Defects n a Hgh-Rsk Area of Chna* HUANG Jng 1,, WU JLe,, LI TeJun 1, SONG XnMng, ZHANG BngZ, ZHANG PngWen 1,#, and ZHENG XaoYng,# 1. School of Mathematcal Scences, Pekng Unversty, Bejng 100871, Chna;. Insttute of Populaton Research, Pekng Unversty, Bejng 100871, Chna Abstract Objectve Our objectve s to buld a model that explans the assocaton between the exposure to trace elements n the sol and the rsk of neural tube defects. Methods We bult a functon wth dfferent parameters to descrbe the effects of trace elements on neural tube defects. The assocaton between neural tube defects and trace element levels was transformed nto an optmzaton problem usng the maxmum lkelhood method. Results Tn, lead, nckel, ron, copper, and alumnum had typcal layered effects (dosage effects) on the prevalence of neural tube defects. Arsenc, selenum, znc, strontum, and vanadum had no effect, and molybdenum had one threshold value that affected the prevalence of brth defects. Concluson As an exploratory research work, our model can be used to determne the drecton of the effect of the trace element content of cultvated sol on the rsk of neural tube defects, whch shows the clues by the dosage effect of ther toxcologcal characterstcs. Based on our fndngs, future bogeochemcal research should focus on the drect effects of trace elements on human health. Key words: Trace element; Neural tube defects; Rsk factors dentfcaton; Posson model; Maxmum lkelhood estmaton Bomed Envron Sc, 011; 4():94 101 do:10.3967/0895 3988.011.0.00 ISSN:0895 3988 www.besjournal.com(full text) CN: 11 816/Q Copyrght 011 by Chna CDC INTRODUCTION T he qualty of human lfe and health are affected by the chemcal composton of food and the surroundng envronment. Advances n analytcal chemstry and envronmental nvestgatons have substantally added to the knowledge of the bogeochemstry of trace elements. Most chemcal elements necessary for lfe are suppled by the sol overlyng the surfcal lthosphere. Thus, the sol s not only a part of the ecosystem, but lnked to the health and survval of humans through the producton of foods. Sol functons as a flterng, bufferng, storage, and transformaton system that to prevent envronment al polluton [1]. The nternal bochemstry of the human body s naturally adjusted to the natural contents of the envronment. In some regons, however, geochem cal anomales n the bedrock, sols from agrcultural practces and envronmental polluton affect the trace element content of food crops and other plants, makng them maladjusted to human health. Detary defcency or excess of these elements may result n dsease and mpared metabolsm. The effects of trace elements on human health are complex, and there are few quantfable standards aganst whch they can be measured []. * Ths study was supported by the Natonal 973 project on Populaton and Health (No. 007CB5119001), the Natonal Yang Z Scholar Program, 11 and 985 projects of Pekng Unversty (No. 000903). HUANG Jng and WU JLe are both frst authors, and contrbuted equally to ths work. # Correspondences should be addressed: ZHENG XaoYng, E mal: xyzheng@pku.edu.cn; ZHANG PngWen, E mal: pzhang@pku.edu.cn Receved: May 14, 010; Accepted: January 4, 011
Bomed Envron Sc, 011; 4(): 94 101 A brth defect occurs when a fetus s developng wth an abnormalty n functon, structure, or metabolsm. Causes of brth defects nclude both genetc and envronmental factors. Genetc factors account for 10% and envronmental factors account for 0% of the brth defects. The remander s mostly caused by nteractons between genetc and envronmental factors[3]. Envronmental factors, such as regonal geochemcal characterstcs lke geomagnetsm, terrestral heat, and excessve radoactvty, and ar, sol, and water polluton can ncrease the prevalence of brth defects[4]. The heterogenety of sol at mcroscopc level and the susceptblty of ndvduals to brth defects are challenges to the quanttatve analyss of the effects of trace elements n sol on human health. The present study was conducted n the Lvlang regon of Shanx provnce, whch s the area wth the hghest prevalence of neural tube defects n Chna[5]. A model was bult to analyze the assocaton between the trace element content of cultvated sol and the prevalence of neural tube defects. The object of ths model was to determne the normal ranges of trace elements n the sol and ther effects on the prevalence of brth defects. Dependng on the results, an exploratory analyss of the exposure to envronmental rsk factors could be carred out. MATERIALS AND METHODS Study Area and Data Collecton The study area was the Lvlang regon, Shanx provnce, Chna (Fgure 1). Brth defect cases ncluded all lve brths and stllbrths from January 1, 00 to December 31, 004. All mothers gave brth ether at the hosptal or at home and were resdents of the study area durng the study perod. All neural tube defects were verfed by doctors n the hosptal, regardless of pregnancy outcome. Data collecton and qualty control were descrbed[6]. At least two patches of the cultvated land n each of the surveyed vllages were selected for collecton of sol samples. The depth of the sol samples was between cm and 0 cm. All sol samples collected n one vllage were mxed thoroughly to represent that vllage[7]. All feld samplng works were carred out durng a week perod n December 004. We used nductvely coupled plasma mass spectroscopy (ICP MS) to measure the content level of 1 trace elements n the sol samples wth standard procedures[8]. Trace elements studed were tn (Sn), arsenc (As), 95 selenum (Se), molybdenum (Mo), znc (Zn), strontum (Sr), lead (Pb), ron (Fe), nckel (N), vanadum (V), copper (Cu), and alumnum (Al). Fgure 1. Study area and vllages. All cases of neural tube defects and all sol samples were matched by geo code of the vllages names and locatons. In total, 11 vllages had both records of brth defects and data on trace element content of sol samples. Hypothess for Model Buldng Trace elements can be classfed as essental, possbly essental, or non essental for human health. Accordng to related studes, most elements studed here are essental, such as nckel, arsenc, copper, ron, molybdenum, selenum, vanadum, and znc. Alumnum, tn, and strontum mght be possbly essental whle the heavy metal element lead s non essental and hghly toxc to humans[1]. However, these elements play an unclear role n human health. We assumed that there are three possble types of assocaton between trace element content and human health. 1), The trace element content has ether a postve or negatve relaton to health. An ncrease or decrease n the sol levels would cause a correspondng effect on the health of the populaton. In terms of the present study ths would mean an ncrease or decrease n the prevalence of brth defects. ), The relatonshp between the trace element content level and populaton health shows a dose effect. That s, hgher or lower amounts of the trace element content level would result n a hgher or lower prevalence of brth defects. 3), There s no
96 Bomed Envron Sc, 011; 4(): 94 101 relatonshp between trace element content and the rsk of brth defects, meanng that ncreasng or decreasng levels of the trace element has no effect on populaton health, and no effect on the prevalence of the brth defects. Exstng studes show that there are dfferent effects of the studed trace elements on populaton health. The assocaton s not lnear; the curve of effects on populaton health usually shows some one or two crtcal ponts (Fgure ). Model Buldng We bult a model that could reflect the assocaton between the trace element levels and the occurrence of neural tube defects. The effect of trace elements depends on certan parameters. Dfferent values of these parameters would reveal the effects of varous elements on populaton health, whch s the prevalence of neural tube defects here. Consder the functonf( x, a1, a, b1, b, ε1, ε, c ), where x s the content level of one type of trace element. The parameters a1, a, b1, b, ε1, ε, c descrbe how ths element works on populaton health, n ths case the occurrence of neural tube defects. Assumng that ε1 >0, ε >0, a1, a, b1, b, c R, the functon s expressed as follows: f( x; a1, a, b1, b, ε1, ε, c)= b1tanh x a 1 x + a + btanh + c ε1 ε where, f means the occurrng cases of neural tube defects n vllage x. Fgure 3 shows the dfferent effects of the trace element content on the prevalence of neural tube defects, gven dfferent values for a1, a, b1, b, ε1, ε, c. The trace element content has dfferent crtcal ponts, dependng on these parameters. Here are some examples: 1) Case I. There are two crtcal ponts, x and x. 1 When the element content s less than x 1 or greater than x, the rsk of neural tube defects s hgh. Only when the element content s between the two crtcal thresholds, the rsk of brth defects s low. The correspondng parameters a1, a, b1, b, ε1, ε, c here mght be a11, a1, β11, β1, 0.01, 0.05, and γ 1, respectvely. In the reverse stuaton, the occurrng rsk of the neural tube defects would be hgh when the elements content s between the two crtcal thresholds. Fgure. Relatonshp between trace element content level and human health [9]. ) Cases II and III. There s a crtcal threshold that abruptly changes the rsk of the neural tube defects. When the element content level s hgher or lower than that threshold, the rsk of defects ncreases or decreases. In Case II, f the trace element content s greater than the crtcal threshold x 1, the rsk of neural tube defects clearly ncreases. Case III s the reverse stuaton: When the content s less than x 1, the rsk of the defects s hgh, but t decreases when the content s greater than x 1. 3) Case IV. The trace elem ent content has no effect on the rsk of brth defects. In ths case, the curve of the rsk of neural tube defects s a horzontal lne, expressng that the occurrence of brth defects s ndependent of the trace element content. Wth the object functon bult, we consdered how to quantfy the prevalence of neural tube defects, or occurrng rsk, n a vllage. Because brth defects are a small probablty event, we hypotheszed that the number of brth defects would follow a Posson dstrbuton [10]. The probablty of an nfant beng born wth a knd of neural tube defect s P (0 P 1); the probablty that the nfant s born wthout any neural tube defects s 1 P. The number of nfants who have any type of neural tube defects follows a bnomal
Bomed Envron Sc, 011; 4(): 94 101 97 dstrbuton, whch means that the probablty of k brth defect cases over n brths would be k k n k C np (1 P ). When P s small enough, the lmtaton of a bnomal dstrbuton s the Posson dstrbuton as n tends to be nfnte and n P remans constant [11]. In practce, the occurrng probablty of brth defects must be less than 1. Gven that the vllage s relatvely ndependent of sol samples and neural tube defects, we assume that the occurrence of defects follows a Posson dstrbuton wth parameter λ, whch s the average number of brth cases wth any type of neural tube a 1 =α 11, a = α 1, b 1 =β 11, b = β 1, ε 1 =0.01, ε =0.05, c=γ 1 a 1 =α 1, a = α, b 1 =β 1, b = β, ε 1 =0.01, ε =0.05, c=γ a 1 =α 13, a = α 3, b 1 =β 13, b = β 3, ε 1 =0.01, ε =0.05, c=γ 3 a 1 =α 14, a = α 4, b 1 =β 14, b = β 4, ε 1 =0.01, ε =0.05, c=γ 4 Fgure 3. Dfferent functons obtaned usng dfferent parameters. defect. Wth the Posson model, the probablty of a vllage havng Y brth cases wth neural tube defects s: PY ( ; λ)= λ Y e λ / Y!. Here, the Posson parameter λ s determned by the functon f. To ensure that λ s postve, we use a smple transformaton of f to get λ : λ =( f + f + ε )/, where ε <<1, and λ s: 0for f < 0, or f for f > 0. Assumng that n vllage the content level of one trace element n the sol s x, the number of brths wth a neural tube defect s y, and the Posson parameter s λ, the probablty of y brth cases wth a neural tube defect s: Y -λ P(Y = y ; λ ) = λ e / Y!. As the rsks of neural tube defects n dfferent vllages are ndependent random varables, the probablty of y cases wth a neural tube defects n vllage (1 n, where n s the number of total brths n the vllage) s: PY ( = y, Y = y,..., Y = y ; λ, λ,..., λ ) = PY ( = y ; λ ) = 1 1 n n 1 n =1 n Y λ λ e =1 Y! n Wth a three year nvestgaton, we can assume that the surveyed data n ths area accurately reflects the rsk of neural tube defects n those vllages [6]. The assocaton between the trace element content of the sol and the occurrng rsk of neural tube defects of those vllages s relatve stable. Thus, we can convert the probablty of content levels of trace elements n the sol and the occurrng rsk n each vllage nto a maxmum lkelhood problem as below [1] :
98 Bomed Envron Sc, 011; 4(): 94 101 Where λ n Y -λ max e a1,a,b1,b, ε1ε,,c =1 Y! λ f x f x ε, =( ( )+ ( ) + )/ x a 1 x + a f( x )= b1tanh + btanh + c ε1 ε We used the optmzaton toolbox n MATLAB to solve ths problem [13]. RESULTS There are many dfferences n the levels of trace elements n the sol between our study data and background values n Shanx provnce. Ths may partly explan why our study area has the hghest prevalence of neural tube defects n Chna. Wth the optmzaton model solved wth the optmzaton toolbox software package of MATLAB, we examned 1 trace elements. The results show that tn, lead, nckel, ron, copper, and alumnum had typcal layered level effects on the occurrng rsk of brth defects. The assocaton between the levels of trace elements and the occurrng rsk of brth defects followed varous patterns. Ths s smlar to the dosage effects of toxcologcal characterstcs of trace elements. Arsenc, selenum, znc, strontum, and vanadum had no drect effect on the occurrng rsk of neural tube defects. Ths mght be because these elements really have no effects on human health, or there may be antagonstc nteractons wth other elements, as these elements are typcally more easly combned wth others. Furthermore, there are no sgnfcant dfferences n content levels of those elements among the vllages as s shown by the varance of content levels. Detaled results are shown n Table 1. To evaluate our Posson statstcal model, we defned the ftness value as Pλ ( m = Y) V = max P ( m, ) m when the parameter λ and the expermental data y are known. As the event wth the hghest probablty appears most lkely, we have the hghest ftness value V =1 when the observable y exactly corresponds to the event wth the hghest probablty n the Posson model wth parameter λ ; otherwse t wll be less than 1, and we take t as a quanttatve assessment of the model. The results obtaned for the current data set are shown n the 4th column n Table 1, whch gves reasonable ftness values around 0.80 wth the estmated parameters. The element of molybdenum had a threshold value for the effect on neural tube defects. When the molybdenum content level s below the threshold (8.51 ug/mg), and when content level of t s more than that threshold, the assocaton would become postvely related, reducng and ncreasng content level of t would both ncrease the rsk of neural tube defects. λ Element (µg/g) Table 1. Effects of trace elements on prevalence levels of neural tube defects Average Level # Mean V Std. (var.) Layer Level Prevalence Low Medum Hgh Sn 0.9 3.71 0.7839 1.09 (1.18) 3 <.5 or >3..5 3. \ Pb 14.7 56.14 0.7980 11.43 (130.58) <45 >55 \ N 9.9 41.38 0.8110 6.39 (40.77) 3 30 34 >34 <30 Fe *.95 3.8 0.7858 0.58 3 <3.1 >3.35 3.1 3.35 Cu.9 3.4 0.7906 3.65 (13.34) 3 <0 > 0 Al * 6.35 3.47 0.8150 0.95 <3.8 >3.8 \ As 9.1 0.48 0.8098 14.38 (0.7) 0 \ \ \ Se 0.16 \ \ \ \ \ \ \ Zn 63.5 110.88 0.8075 45.73 (0.41) 0 \ \ \ Sr 07 58.88 0.8098 75.47 (0.9) 0 \ \ \ V 63.4 86.41 0.8 10.44 (0.1) 0 \ \ \ Mo 0.50 1.5 0.818 3.09 (9.53) 1 8.51 Note. * Fe and Al are n mg/g. # average content levels n sol from Sh [14].
Bomed Envron Sc, 011; 4(): 94 101 99 DISCUSSION Trace Elements That Have Dose Effects on the Occurrng Rsk of Neural Tube Defects The results show that the lower the content level of lead and alumnum n the sol, the lower occurrng rsk of neural tube defects, and vce versa. Ths s n accordance wth exstng studes, as lead s a non essental and hghly posonous element for humans []. The element of alumnum also has bo posonous effects, especally on the neural system [15]. Lead can enter the human body through the respratory system and almentary tract along wth food or dust partcles. After beng absorbed by the body, t s dstrbuted to the lver, kdney, bran, and major arteres [16]. Generally, lead posons the central neural system and blood, harmng the dgestve system and compromsng kdney functon. It also has strong effects on chld development [17]. Some studes show that lead n herbal medcne mght cause the rsk of neutral tube defects [18]. Alumnum s another non essental element that mght affect bran functon. People wth hgh alumnum content n the bran show reduced memory, low ntellgence, and decreased physcal functonng [19]. In addton, alumnum drectly affects bone cell actvty by preventng the composton of bone bass and calcum absorpton. Increased alumnum content n the body can ultmately lead to anema and kdney dsease [0]. Because of ths, the World Health Organzaton and the Food and Agrculture Organzaton of the Unted Natons declared n 1989 that alumnum content n food must be controlled, recommendng standard daly ntakes of less than 7 mg/kg body weght [1]. These results show that there are assocatons between lead and alumnum levels n the sol and the occurrng rsk of neural tube defects. Ths means that women should avod lead and alumnum exposure when pregnant or tryng to become pregnant. Copper s a major component of enzymes, and s also an essental element for the lver, bran, kdney, heart, lung, spleen, muscles, and bones n humans. However, both defcences and excessve amounts of copper cause pathologcal changes n the bran. Defcences can cause bran shrnkage, decreased neural unts, stagnancy of sprt, tredness, and lmted physcal functonng. Excessve amounts of copper lead to bran and neural system cell dsorders. Excessve copper stores n the lver can be released nto the blood and cause hemolyss and jaundce []. Moreover, hepatocrrhoss and ble slt n chldren are related to excessve copper levels. Copper enters the human body through the food chan. In the envronment, copper s less threatenng to populaton health because humans do requre a certan amount. Excessve amounts of copper usually have a negatve effect on human health [3]. However, some studes show that copper defcency may not be related to the rsk of neural tube defects [4]. Our results show that hgher levels of ron cause an ncrease n the prevalence of neural tube defects. Iron s a key element n blood and s often used as an ndex of the nutrtonal level of humans. It s also known to affect pregnancy outcomes [5]. However, excessve ron levels (.e., several tmes the normal values) ncrease the rsk of cancer [6]. Therefore, excessve exposure to ron should also be avoded. Nckel has dfferent compounds and physcal shapes. These have dfferent levels of toxcty to humans. Our results also show dfferent assocatons between exposure to nckel compounds and human health. The genetc toxcty of nckel s a controversal ssue [7]. Our results show that both defcences n and excessve amounts of nckel cause an ncreased rsk of neural tube defects. Some studes show that low levels of nckel cause changes n metabolsm, and excessve amounts can be posonous (as ndcated by the whtenng of har). In envronments hgh n nckel there s a hgher prevalence of tumors of the respratory system and skn dsease. Nckel usually enters the human body through the respratory system [8]. Our study shows that when the cultvated sol content of tn s about.5 3. ug/mg, the prevalence of neural tube defects ncreases. Tn naturally exsts n plants and sol, but ts relatonshp wth human health s not clear. The levels of tn change wth the envronment [9]. Accordng some studes [30], tn mght be a key envronmental factor n the assocaton between trace elements exposure and the rsk of brth defects n the Lvlang regon, gven the sol content of tn n ths regon, Trace Elements That Have no Clear Effects on the Prevalence of Brth Defects Our results show that arsenc, selenum, znc, strontum, and vanadum have no clear effect on the prevalence of brth defects. We frst checked the levels of these elements and ther dfferences by vllage [31]. For example, selenum s a key element for human health. Selenum defcency can cause Keshan
100 Bomed Envron Sc, 011; 4(): 94 101 dsease, bg bone dsease etc. However, the sol n our study regon shows low selenum content and our model dd not show an effect on the rsk of brth defects. Arsenc, znc, strontum, and vanadum also have no clear assocaton wth the rsk of brth defects. Ths may be contrbuted to the fact that the levels of these elements n the sol were smlar among the vllages. Further study s necessary to develop more accurate models on the effects of these elements on the rsk of brth defects. Molybdenum The element of molybdenum s a key element for oxygenaton [3]. Excessve amounts of molybdenum can cause decreased sexualty, reducton of cartlage, anema, and darrhea [33]. Our model shows that ts effect on the prevalence of brth defects has a threshold value. CONCLUSION In summary, ths s an exploratory study, whch focused on the assocaton between trace element contents of cultvated sol and the regonal rsk of neural tube defects. Based on the samples and survey data, the model we have bult could determne the drecton of the effects of the trace elements on the rsk of neural tube defects, as well as ther thresholds levels. Our results show that qualtatve conclusons about the assocaton between the trace element content n the sol and the rsk of neural tube defects were proven. Further study s requred to focus on the mechansms behnd these assocatons. For example, bogeochemcal research should be carred out consderng the drect effects of trace elements on human health [34]. Also, longtudnal collecton of brth defect data s necessary to ensure more stable data. We chose to study neural tube defects because they are easly dentfed n clnc, and have complex causes. The regon we studed has the hghest prevalence of neural tube defects n the world. Cases examned here through a 3 year survey could represent the maxmum lkelhood of the real prevalence of neural tube defects wth more than 6000 brth counts [6]. Furthermore, the routes by whch trace elements enter the human body (.e., through respraton, drnkng water, or the food chan) mght affect human health dfferently. Among these, the food chan s the man route for the transfer of trace elements to the human body. The dfferent routes should be a key pont n the analyss of the mechansms of toxcology of trace elements [1]. The model developed n our study must be explaned and quantfed by judgng the meanng of data derved from envronmental analyss on bologcal samples. As bo ndcaton and boaccumulaton of trace elements s a common chemcal phenomenon, the toxcty of these elements mght be dstorted wth dfferent stuatons n the sol [35 36]. Lmted by the measurement of the trace element content, we could not classfy the detals of physcal chemstry among the sol samples. The present results are n accordance wth the qualtatve knowledge of the toxcty of those trace elements to human health. The model descrbed could be used for the analyss of the toxcologcal characterstcs of trace elements, and for preventon of the rsk of exposure to pregnant women. ACKNOWLEDGEMENT The authors are grateful for Prof. WANG JnFeng at the Insttute of Geography and Natural Resource Research, CAS, and Prof. ZHANG KeL s research group at the Bejng Normal Unversty, who worked hard on the sol samples testng. Thanks also go to the anonymous revewers of our manuscrpt. REFERENCES 1. Kabata Pendas A, and Mukherjee AB. Trace Elements from Sol to Human. New York, Sprnger Berln Hedelberg, 007.. Yang K. Trace Elements and Health. Bejng, Scence Press, 003. 3. L Zhu. Genetc and envronment are the two major causes of brth defects, 010; http://acwf.people.com.cn/gb/99060/ 1306114.html 4. L XH, Wang JF, Zheng XY, et al. The ndcaton effect of sol n envronmental rsk assessment of brth defects. Research of Envronmental Scences, 007; 0(6), 1 6. 5. L ZW, Ren AG, Zhang L, et al. Prevalence of major external brth defects n hgh and low rsk areas n Chna, 003. Chnese Journal of Epdemology, 005; 6(4), 5 7. (In Chnese) 6. Gu X, Ln LM, Zheng XY, et al. Hgh Prevalence of NTDs n Shanx Provnce: A Combned Epdemologcal Approach. Brth Defects Res (A Cln Mol Teratol), 007; 79, 70 7. 7. Ma Y. Envronment Inspecton. 1998, Wuhan, Wuhan Industral Unversty Press. 8. Joachm N. ICP Emsson Spectrometry: A Practcal Gude. 003, Wenhem, Germany, Wley VCH. 9. Tan JA. Geo Envronment and Health. 004; Bejng, Chemcal Industry Press. 10. L Z and Y Qan. Inspecton on Brth Defects. 1993, Bejng, People, s Medcne Publshng House. 11. Wang R. The Introducton of Probablty Theory. 1994, Bejng, Pekng Unversty Press. 1. Chen JD, Sun SZ, L DF. The lectures on mathematc statstcs. 1993, Bejng, Hgh Educaton Press. 13. MATLAB. The MathWorks, Inc. 007.
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