饮水型氟病区改水后儿童健康风险度评价
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摘要
背景：氟广泛地存在于自然界,是地球表面第13个最丰富的天然元素。虽然科学家们仍不确定氟化物是否对人体健康有至关重要的作用,但许多人认为,在日常饮食中少量的氟有助于防止龋齿,强化骨骼。另一方面,长期摄入高剂量的氟对人体健康可产生的不良影响,包括氟斑牙和氟骨症、增加骨折风险、导致出生率下降、增加尿路结石(肾结石)、导致甲状腺功能减退、降低儿童智力等。地方性氟中毒在世界范围内分布广泛,流行于五大洲50多个国家和地区。中国是世界上地氟病分布最广、危害最严重的国家之一。根据氟的摄入途径不同,我国地方性氟中毒病区可分为饮水型、燃煤污染型、饮茶型和混合型等几种,其中以饮水型氟中毒为最严重,其次为煤烟污染型,均可导致牙齿和骨骼的氟中毒流行。广东省是我国南方饮水型地方性氟中毒分布范围最广泛的省份之一,1980年已查清全省共有396个氟病区村,分布在14个地级市37个县,115个乡镇。病区人口数50.24万。广东省粤东地区的汕头市是广东省病区人口数最多的地级市,查明的病区人口数为21.61万,病区8-15岁儿童氟斑牙患病率为62.01%。广东省各饮水型氟病区自1985年开展饮水降氟措施以来,已取得了显著成效,至2003年,全省各氟病区改水后,改水受益率已达到病区总人口数的93.3%,儿童氟斑牙平均患病率由改水前的61.12%降至41.5%。
然而,虽然改水降氟已取得了明显的效果,但由于氟对人体的健康具有双重效应作用,在地氟病防治过程中,氟在多大的剂量范围内对人体健康是有益的,低于多大剂量或者高于多大剂量是有害的?可接受剂量是多少?引起不同健康效应的基准剂量是多少?高氟区氟暴露人群尤其是儿童群体的健康风险度如何评价?改水后氟病区饮水氟的安全剂量应该是多少为好,如何确定等等,这些问题均需进一步探索研究。本课题就是在这样的背景下,探索高氟病区改水后氟暴露儿童健康的风险度评价方法,通过基准剂量模型的构建,寻找氟暴露安全剂量,为改水地区氟的安全剂量确定提供科学的依据。
目的：通过对不同改水时间儿童氟暴露水平、基本特征和氟暴露各种特定效应的研究,确定氟暴露各特定效应的基准剂量,寻求不同改水时间、儿童不同尿氟含量的各特定效应指标的变化规律及剂量-反应关系,建立氟病区改水后儿童健康风险度综合评价模型,为制定氟暴露限值、提高氟病区儿童健康水平的政策提供科学的决策依据。
方法：从汕头市潮南区63个氟病村中随机抽取4个氟病村以及一个非氟病村进行6-12岁儿童氟斑牙、龋齿的普查；同时从中抽取600名儿童,检测其尿氟含量及血清中骨钙素、降钙素、碱性磷酸酶含量和骨密度。根据上述各项指标的检测结果进行氟病区改水后儿童健康风险度评价,评价方法采用美国环保署2001年修订的风险度评价指南,评价步骤有：危害认定、剂量-反应关系评价、暴露评定、危险度特征分析。各步骤的统计方法采用SPSS软件16.0以及BMDS软件进行(P<0.05表示差别有统计学意义)。其中危害认定通过Logistic回归分析进行氟暴露与各指标的患病情况的相关性分析；剂量-反应关系评价使用BMDS软件绘制尿氟与各指标的剂量-反应曲线并计算基准剂量以及基准剂量下限；暴露评定采用平均水平来描述氟暴露的剂量,用各指标90%的上限来确定异常指标的范围,用Logistic回归分析暴露与异常的关系；危险度特征分析根据基准剂量下限确定的范围来定量认定风险,衡量风险的大小。
结果：A、B、C、D四个氟病区村改水前水氟含量分别是5.51mg/1、2.17mg/1、3.99mg/1和3.31mg/,改水后的水氟含量均降至0.11mg/1,与对照村一致。对照E村儿童尿氟含量平均水平为0.48mg/l,改水后A、B、C、D村儿童尿氟含量分别是：0.62MG/1、0.51mg/1、0.36mg/1和0.27mg/l,各观察村与对照村间差异有统计学意义(χ2=127.915,P<0.001),A村儿童尿氟平均水平高于对照村,而C、D村尿氟平均水平低于对照村。不同改水年限氟病区儿童血清骨钙素水平之间差别有统计学意义(F=14.465,P<0.001),改水年限为14年的B村和对照E村低于其他村。儿童血清降钙素水平之间有差别;F=48.959,P<0.001), B、C村间无差别,低于其他村。血清碱性磷酸酶活性之间差别有统计学意义(F=9.831,P<0.001),C村、D村均低于E村。儿童总骨密度值之间有差别(F=3.781,P=0.005),A村、C村均高于B村。
改水前4个氟病区村氟斑牙患病率为76.99%。改水后除A村氟斑牙患病率高于30%(低于此值可判断为非氟病区)外,其他村均远低于30%。以E村为对照进行Logistic回归分析,A村OR值为7.71(χ2=212.02,P<0.001),其他村OR值没有统计学意义。五个村龋齿患病率均高于30%。E村龋齿患病率为49.7%,以E村为对照,进行单因素Logistic回归分析。A、B、C、D村龋齿患病率分别为31.97%(OR=0.48, χ2=73.62, P<0.001)、65.0%(OR=1.88,χ2=21.38, P<0.001)、56.3%(OR=1.31,χ2=10.81,P<0.001)、45.2%(OR=0.83, χ2=3.40,P=0.045)。各氟病区村骨钙素、碱性磷酸酶、骨密度异常率均不高于对照村。A村降钙素异常率高于对照E村,其OR值为6.39(χ2=27.14,P<0.001)。
随着尿氟含量的增加,氟斑牙患病率逐渐增加,OR值也逐渐增加。尿氟剂量组在0.00～组龋齿患病率最高,为53.9%；0.37～组龋齿患病率最低,为39.8%；呈U型变化趋势。骨钙素、碱性磷酸酶、骨密度异常率在不同尿氟组间无差别,而降钙素异常率则有随着尿氟含量的增加而上升的趋势,相比尿氟含量0.0～组,0.6～组骨钙素异常的OR值为2.35(χ2=4.02,P=0.045),0.9～组的OR值为2.78(χ2=4.90,P=0.027)。
尿氟与氟斑牙的剂量-反应模型选用Logistic模型,计算的基准剂量BMD=0.857mg/1, BMDL=0.720mg/1.儿童尿氟含量与龋齿间的剂量-反应关系选用Multistage模型,下降曲线的BMD和BMDL(基准剂量下限)值分别为1.095mg/l和0.898mg/l,上升曲线的BMD和BMDL值分别为0.275mg/l和0.124mg/l。尿氟与骨钙素剂量-反应关系模型采用Logistic回归模型,计算的BMD=0.975mg/1, BMDL=0.622mg/1。降钙素异常的剂量-反应关系模型为Quantal-线性模型；计算的BMD=0.636mg/1, BMDL=0.383mg/1。碱性磷酸酶异常的剂量-反应关系模型是Logistic回归模型,计算的BMD=2.299mg/1, BMDL=0.837mg/1.尿氟与骨密度异常的剂量-反应关系模型为对数-Logistic回归模型,计算的BMD=0.941mg/1, BMDL=0.811mg/1。
氟斑牙在改水年限为6年的归因危险度(ARP)最低,为0.41；而改水年限为14年、15年、17年的归因危险度分别是0.91、0.92、0.96。以各效应指标安全剂量范围下限为对照,计算超过安全剂量范围的OR值：氟斑牙、骨钙素、降钙素OR值分别为2.415、1.945、1.761。龋齿、碱性磷酸酶、骨密度OR值均无统计学意义。以疾病危害程度所占权重乘以异常率作为合计风险,计算各基准剂量组总的风险值,结果显示随尿氟含量的增加,总的风险有上升的趋势。
结论：
1.改水后各观察村居民饮用水均符合国家饮用水卫生标准(1.0mmg/1以下)。
2.改水超过六年,观察村儿童尿氟含量、氟斑牙患病率及健康效应指标已达到非氟病区水平。
3.儿童尿氟与儿童氟斑牙、龋齿患病率及氟性骨损伤四项指标(BPG, CT, ALP和骨密度)均存在剂量-反应关系,其中尿氟含量与龋齿呈U型曲线关系。
4.通过尿氟与儿童氟斑牙、龋齿患病率及氟性骨损伤四项指标(BPG, CT, ALP和骨密度)的剂量-反应关系构建,计算出各效应指标的BMD值分别为：0.857mg/1、1.095mg/1(龋齿上限值)和0.275mg/l(龋齿下限值)、0.975mg/1、0.636mg/1、2.299mg/1和0.941mg/1; BMDL值分别为：0.720mg/1、0.898mg/1(龋齿上限值)和0.124mg/1(龋齿下限值)、0.622mg/1、0.383mg/1、0.837mg/1和0.811mg/l。
5.各效应指标的尿氟基准剂量下限可作为当地尿氟含量的生物限值。
6.在改水后的4个氟病村中,B村和C村儿童患龋齿的风险高于其他村。
Background:Fluorine is widely found in nature and is one of the13most abundant natural elements in the Earth's surface. Although scientists are still not sure the fluoride whether a vital role in human health, but many people believe that a small amount of fluoride in the diet helps to prevent tooth decay and strengthen bones. On the other hand, long-term intake of high doses of fluoride can produce adverse effects on human health, including dental fluorosis and skeletal fluorosis, increased risk of fractures, resulting in declining birth rate, increased urinary calculi (kidney stones), resulting in hypothyroidism and reduce children's intelligence. Endemic fluorosis is widely distributed in the world which includes more than50countries and regions of five continents. China is one of most serious endemic fluorosis in the world. According to the ways of fluoride intake, endemic fluorosis in China can be divided into several types:drinking water type, coal burning pollution type, drinking tea type and mixed type, and the most serious one is drinking water type fluorosis, followed by coal burning type which can lead to dental and skeletal fluorosis epidemic. Most of fluorosis endemic areas in southern China are drinking water type and Guangdong is the most serious one confirmed in the1980s. The province totally has396endemic villages located in115towns of37counties of14cities with an endemic population of502,400. Shantou, a city in eastern Guangdong province, is the most serious city in14endemic cities with an endemic population of216,100. The dental fluorosis prevalence in the children aged8-15in Shantou endemic areas was62.01%. The procedures to treat fluorosis in Guangdong Province is to provide low fluoride public water for the residents in the endemic villages and which has been conducted since the late1980s and the remarkable results have been achieved. Until2003, the province has finished changing the water in all endemic areas and93.3%of the population has got the benefits, and the average prevalence rate of dental fluorosis has fell to41.5%from61.12%.
However, even though the content of fluoride in the water has been reduced, the effects on the human being remain a lot of unknown elements since the fluoride in the water has a dual effect on human health. For instance, below what dose or higher than what dose the fluoride in the water is harmful to health? What is the acceptable dose? What are the benchmark doses to beneficially or harmfully affect human health? How to assess the health risk for the population in the endemic fluorosis areas? High fluoride areas of fluoride exposure groups, especially groups of children and how to assess the health risks? What dosage of fluoride is safety in the Changed water, and how to determine this dose etc.. The aim of this paper is to create an assessing method to evaluate the children's health risk who explored to the high water fluoride environment but have had water changed for different years, as well as to recommend a safety dose for the local government based on the calculation of bench mark doses.
Objective:based on the study on the years of the children's exposure, the duration of water changed and different specific effects responded to fluoride exposures, to determine the benchmark doses of the specific effects of different fluoride exposures, to seek the changing rules and dose-response relationship ofthe specific effective criteria related to different water change years and children's urinary fluoride contents, to establish the children's health risk evaluation model and to provide the scientific basis for decision making to set the fluorine exposure limits and improve the children's health in the endemic fluorosis areas.
Methods:Four endemic fluorosis villages were randomly selected from63endemic fluorosis village of Chaonan county, Shantou city as well as a non-endemic fluorosis village and all of the children aged6-12were chosen for the examination of dental fluorosis, dental caries and600were selected for determines of fluoride contents in urine and serum osteocalcin, calcitonin, alkaline phosphates' content and bone mineral density. According to the test results of the above indicators, children's health risk assessment was conducted based on the Risk Assessment Guide revised in2001by the U.S. Environmental Protection Agency. The evaluation steps included identification of hazards, the dose-response relationship, evaluation of exposure assessment, and risk analysis. Software SPSS16.0and BMDS were used for statistics Including the identification of hazards by using Logistic regression analysis to analyze the correlation of fluoride exposure and the prevalence of various indicators(P<0.05showes statistically significant); using BMDS software to evaluate dose-response relationship and draw the dose-response curve between urine fluoride and indicators and calculate the reference dose, and the benchmark dose lower limit; average exposure was assessed to describe the dose of fluoride exposure, with a ceiling of90%of each indicator to determine the scope of the exception indicators; Logistic regression was used to analyze the relationship between exposure and abnormal; risk determination and risk scope were determined based on the benchmark dose lower limit.
Results:Fluoride contents in villages A, B, C, D before water changed were5.51mg/1,2.17mg/1,3.99mg/1and3.31mg/1. They all came down to0.11mg/1after water changed, consistent with the control village. The average of the children's urine fluoride in village E (control) was0.480mg/1, and those in A, B, C, D villages were0.62mg/1,0.51mg/1,0.36mg/1and0.27mg/1after water changed. The difference was statistically significant between the observed villages and the control one (χ2=127.915, P<0.001). The averaged children's urine fluoride in village A was higher than control, while the C and D Villages were lower than the control village. The children serum osteocalcin levels were significantly different among the years of water change(F=14.465, P<0.001), village B which was14years of water changed and control Village E were lower than the others. There are statistical differences between the levels of serum calcitonin(F=48.959, P<0.001), village B and C were lower than other villages but no difference between B and C. Differences between children serum alkaline phosphates'activity were statistically significant (F=9.831, P<0.001), Village C and D were lower than Village E. Children's bone mineral densities were also different(F=3.781,P=0.005), A Village and C village were higher than B village.
The dental fluorosis prevalence rate in the observed villages was76.99%before water change. After the water changes, all the observed villages except A have decreased to30%(below this value can be judged as a non-fluorine area). Based on the control Village E, the Logistic regression showes that the OR value of Village A was7.71(χ2=212.02, P<0.001), and no statistically significant OR values of the other villages. The dental caries prevalence rates in five villages were higher than30%. E village's caries prevalence was49.7%. Compared with E village of control, the Logistic regression analysis showed that the caries prevalence of villages A, B, C, D ware31.97%(OR=0.48, χ2=73.62, P<0.001),65.0%(OR=1.88, χ2=21.38, P<0.001),56.3%(OR=1.31, χ2=10.81, P<0.001), and45.2%(OR=0.83, χ2=3.40, P<0.001) respectively. All of the villages'osteocalcin, alkaline phosphates'and bone mineral density abnormal rates were not higher than the control village, but calcitonin anomalies in village A was higher than the control Village E,(OR=6.39,χ2=27.14, P<0.001).
With the increase in urine fluoride, dental fluorosis prevalence as well as OR values gradually increased. The urine fluoride content in the0.00-group had the highest caries prevalence of53.9%; The0.37-group had the lowest prevalence of dental caries of39.8%; The change showed a U-shaped trend. Osteocalcin, alkaline phosphates, bone mineral density anomaly rates were not different among the different urine fluoride groups. The calcitonin abnormal rate showed an upward trend with the increase of urinary fluoride contents. Compared to the urine fluoride content of0.0～group, the0.6～group's abnormal osteocalcin OR was2.35(χ2=4.02, P=0.045), and the0.9～group's OR was2.78(χ2=4.90, P=0.027).
The dose-response model of urinary fluoride and dental fluorosis selected Logistic model, with a benchmark dose BMD=0.857mg/1, BMDL (benchmark dose lower limit)=0.720mg/1. The dose-response relationship between the children's urinary fluoride and dental caries selected the Multistage model, the down trend curve of BMD and BMDL values were1.095and0.898mg/1, and the up trend curve of BMD and BMDL values were0.275and0.124mg/1respectively. Logistic regression model was selected to calculate the dose-response relationship of urinary fluoride and osteocalcin and BMD=0.975mg/1, BMDL=0.622mg/1. The calcitonin abnormal dose-response relationship model calculated Quantal-linear model:the BMD=0.636mg/1, BMDL=0.383mg/1. ALP dose-response relationship model was a Logistic regression model and the BMD=2.299mg/1, BMDL=0.837mg/1. Abnormal urinary fluoride and bone mineral density's dose-response relationship model chosen the log-logistic regression model, the BMD was0.941mg/1, and the BMDL was0.811mg/1.
The attributable risk (ARP) of dental fluorosis in the village with water change for six years was the lowest0.41; and the attributable risks for those with water change for14years,15years and17years were0.91,0.92and0.96. Compared with the lower limits for the safe dose range of each effect indicators and calculated OR value exceeded the safe dose range:OR values for dental fluorosis, osteocalcin, and calcitonin were2.415,1.945and1.761. Dental caries, alkaline phosphates, bone mineral density OR values were not statistically significant. The total value of risk calculated based on the combination of weight of quality of life and abnormal rate of the indicators showed an upward trend:total risk increases with the increasing of urinary fluoride content.
Conclusion:
1. The content of the fluoride in the drinking water in the water-changed villages meets the national health standards for drinking water (1.0mg/1or less).
2. When the water has been changed for more than six years, the observed village children's urinary fluoride, dental fluorosis prevalence and health effect indicators have reached the levels of non-fluorine village.
3. There are dose-response relationship between children's urinary fluoride and dental fluorosis, caries prevalence and four fluoride-induced bone damage indicators (BPG, CT, ALP, and bone mineral density). Urinary fluoride and dental caries shows a U-shaped curve relationship.
4.Through the dose-response relationship building between urinary fluoride and dental fluorosis, dental caries and four fluoride-induced bone injury indicators (BPG, CT, ALP, and bone mineral density), the BMD values for the above indicators were:0.857mg/1,1.095mg/1(caries upper limit) and0.275mg/1(caries lower limit value),0.975mg/1,0.636mg/1,2.299mg/1and0.941mg/1; BMDL value were:0.720mg/1,0.898mg/1(caries upper limit) and0.124mg/1(caries limit)0.622mg/1,0.383mg/1,0.837mg/1and0.811mg/1.
5. The urinary fluoride benchmark dose lower limit for each indicator can be used as a biological limit for the local areas.
6. In the observed villages with water change, the risk of dental caries in village B and C was higher than other villages.
然而,虽然改水降氟已取得了明显的效果,但由于氟对人体的健康具有双重效应作用,在地氟病防治过程中,氟在多大的剂量范围内对人体健康是有益的,低于多大剂量或者高于多大剂量是有害的?可接受剂量是多少?引起不同健康效应的基准剂量是多少?高氟区氟暴露人群尤其是儿童群体的健康风险度如何评价?改水后氟病区饮水氟的安全剂量应该是多少为好,如何确定等等,这些问题均需进一步探索研究。本课题就是在这样的背景下,探索高氟病区改水后氟暴露儿童健康的风险度评价方法,通过基准剂量模型的构建,寻找氟暴露安全剂量,为改水地区氟的安全剂量确定提供科学的依据。
目的：通过对不同改水时间儿童氟暴露水平、基本特征和氟暴露各种特定效应的研究,确定氟暴露各特定效应的基准剂量,寻求不同改水时间、儿童不同尿氟含量的各特定效应指标的变化规律及剂量-反应关系,建立氟病区改水后儿童健康风险度综合评价模型,为制定氟暴露限值、提高氟病区儿童健康水平的政策提供科学的决策依据。
方法：从汕头市潮南区63个氟病村中随机抽取4个氟病村以及一个非氟病村进行6-12岁儿童氟斑牙、龋齿的普查；同时从中抽取600名儿童,检测其尿氟含量及血清中骨钙素、降钙素、碱性磷酸酶含量和骨密度。根据上述各项指标的检测结果进行氟病区改水后儿童健康风险度评价,评价方法采用美国环保署2001年修订的风险度评价指南,评价步骤有：危害认定、剂量-反应关系评价、暴露评定、危险度特征分析。各步骤的统计方法采用SPSS软件16.0以及BMDS软件进行(P<0.05表示差别有统计学意义)。其中危害认定通过Logistic回归分析进行氟暴露与各指标的患病情况的相关性分析；剂量-反应关系评价使用BMDS软件绘制尿氟与各指标的剂量-反应曲线并计算基准剂量以及基准剂量下限；暴露评定采用平均水平来描述氟暴露的剂量,用各指标90%的上限来确定异常指标的范围,用Logistic回归分析暴露与异常的关系；危险度特征分析根据基准剂量下限确定的范围来定量认定风险,衡量风险的大小。
结果：A、B、C、D四个氟病区村改水前水氟含量分别是5.51mg/1、2.17mg/1、3.99mg/1和3.31mg/,改水后的水氟含量均降至0.11mg/1,与对照村一致。对照E村儿童尿氟含量平均水平为0.48mg/l,改水后A、B、C、D村儿童尿氟含量分别是：0.62MG/1、0.51mg/1、0.36mg/1和0.27mg/l,各观察村与对照村间差异有统计学意义(χ2=127.915,P<0.001),A村儿童尿氟平均水平高于对照村,而C、D村尿氟平均水平低于对照村。不同改水年限氟病区儿童血清骨钙素水平之间差别有统计学意义(F=14.465,P<0.001),改水年限为14年的B村和对照E村低于其他村。儿童血清降钙素水平之间有差别;F=48.959,P<0.001), B、C村间无差别,低于其他村。血清碱性磷酸酶活性之间差别有统计学意义(F=9.831,P<0.001),C村、D村均低于E村。儿童总骨密度值之间有差别(F=3.781,P=0.005),A村、C村均高于B村。
改水前4个氟病区村氟斑牙患病率为76.99%。改水后除A村氟斑牙患病率高于30%(低于此值可判断为非氟病区)外,其他村均远低于30%。以E村为对照进行Logistic回归分析,A村OR值为7.71(χ2=212.02,P<0.001),其他村OR值没有统计学意义。五个村龋齿患病率均高于30%。E村龋齿患病率为49.7%,以E村为对照,进行单因素Logistic回归分析。A、B、C、D村龋齿患病率分别为31.97%(OR=0.48, χ2=73.62, P<0.001)、65.0%(OR=1.88,χ2=21.38, P<0.001)、56.3%(OR=1.31,χ2=10.81,P<0.001)、45.2%(OR=0.83, χ2=3.40,P=0.045)。各氟病区村骨钙素、碱性磷酸酶、骨密度异常率均不高于对照村。A村降钙素异常率高于对照E村,其OR值为6.39(χ2=27.14,P<0.001)。
随着尿氟含量的增加,氟斑牙患病率逐渐增加,OR值也逐渐增加。尿氟剂量组在0.00～组龋齿患病率最高,为53.9%；0.37～组龋齿患病率最低,为39.8%；呈U型变化趋势。骨钙素、碱性磷酸酶、骨密度异常率在不同尿氟组间无差别,而降钙素异常率则有随着尿氟含量的增加而上升的趋势,相比尿氟含量0.0～组,0.6～组骨钙素异常的OR值为2.35(χ2=4.02,P=0.045),0.9～组的OR值为2.78(χ2=4.90,P=0.027)。
尿氟与氟斑牙的剂量-反应模型选用Logistic模型,计算的基准剂量BMD=0.857mg/1, BMDL=0.720mg/1.儿童尿氟含量与龋齿间的剂量-反应关系选用Multistage模型,下降曲线的BMD和BMDL(基准剂量下限)值分别为1.095mg/l和0.898mg/l,上升曲线的BMD和BMDL值分别为0.275mg/l和0.124mg/l。尿氟与骨钙素剂量-反应关系模型采用Logistic回归模型,计算的BMD=0.975mg/1, BMDL=0.622mg/1。降钙素异常的剂量-反应关系模型为Quantal-线性模型；计算的BMD=0.636mg/1, BMDL=0.383mg/1。碱性磷酸酶异常的剂量-反应关系模型是Logistic回归模型,计算的BMD=2.299mg/1, BMDL=0.837mg/1.尿氟与骨密度异常的剂量-反应关系模型为对数-Logistic回归模型,计算的BMD=0.941mg/1, BMDL=0.811mg/1。
氟斑牙在改水年限为6年的归因危险度(ARP)最低,为0.41；而改水年限为14年、15年、17年的归因危险度分别是0.91、0.92、0.96。以各效应指标安全剂量范围下限为对照,计算超过安全剂量范围的OR值：氟斑牙、骨钙素、降钙素OR值分别为2.415、1.945、1.761。龋齿、碱性磷酸酶、骨密度OR值均无统计学意义。以疾病危害程度所占权重乘以异常率作为合计风险,计算各基准剂量组总的风险值,结果显示随尿氟含量的增加,总的风险有上升的趋势。
结论：
1.改水后各观察村居民饮用水均符合国家饮用水卫生标准(1.0mmg/1以下)。
2.改水超过六年,观察村儿童尿氟含量、氟斑牙患病率及健康效应指标已达到非氟病区水平。
3.儿童尿氟与儿童氟斑牙、龋齿患病率及氟性骨损伤四项指标(BPG, CT, ALP和骨密度)均存在剂量-反应关系,其中尿氟含量与龋齿呈U型曲线关系。
4.通过尿氟与儿童氟斑牙、龋齿患病率及氟性骨损伤四项指标(BPG, CT, ALP和骨密度)的剂量-反应关系构建,计算出各效应指标的BMD值分别为：0.857mg/1、1.095mg/1(龋齿上限值)和0.275mg/l(龋齿下限值)、0.975mg/1、0.636mg/1、2.299mg/1和0.941mg/1; BMDL值分别为：0.720mg/1、0.898mg/1(龋齿上限值)和0.124mg/1(龋齿下限值)、0.622mg/1、0.383mg/1、0.837mg/1和0.811mg/l。
5.各效应指标的尿氟基准剂量下限可作为当地尿氟含量的生物限值。
6.在改水后的4个氟病村中,B村和C村儿童患龋齿的风险高于其他村。
Background:Fluorine is widely found in nature and is one of the13most abundant natural elements in the Earth's surface. Although scientists are still not sure the fluoride whether a vital role in human health, but many people believe that a small amount of fluoride in the diet helps to prevent tooth decay and strengthen bones. On the other hand, long-term intake of high doses of fluoride can produce adverse effects on human health, including dental fluorosis and skeletal fluorosis, increased risk of fractures, resulting in declining birth rate, increased urinary calculi (kidney stones), resulting in hypothyroidism and reduce children's intelligence. Endemic fluorosis is widely distributed in the world which includes more than50countries and regions of five continents. China is one of most serious endemic fluorosis in the world. According to the ways of fluoride intake, endemic fluorosis in China can be divided into several types:drinking water type, coal burning pollution type, drinking tea type and mixed type, and the most serious one is drinking water type fluorosis, followed by coal burning type which can lead to dental and skeletal fluorosis epidemic. Most of fluorosis endemic areas in southern China are drinking water type and Guangdong is the most serious one confirmed in the1980s. The province totally has396endemic villages located in115towns of37counties of14cities with an endemic population of502,400. Shantou, a city in eastern Guangdong province, is the most serious city in14endemic cities with an endemic population of216,100. The dental fluorosis prevalence in the children aged8-15in Shantou endemic areas was62.01%. The procedures to treat fluorosis in Guangdong Province is to provide low fluoride public water for the residents in the endemic villages and which has been conducted since the late1980s and the remarkable results have been achieved. Until2003, the province has finished changing the water in all endemic areas and93.3%of the population has got the benefits, and the average prevalence rate of dental fluorosis has fell to41.5%from61.12%.
However, even though the content of fluoride in the water has been reduced, the effects on the human being remain a lot of unknown elements since the fluoride in the water has a dual effect on human health. For instance, below what dose or higher than what dose the fluoride in the water is harmful to health? What is the acceptable dose? What are the benchmark doses to beneficially or harmfully affect human health? How to assess the health risk for the population in the endemic fluorosis areas? High fluoride areas of fluoride exposure groups, especially groups of children and how to assess the health risks? What dosage of fluoride is safety in the Changed water, and how to determine this dose etc.. The aim of this paper is to create an assessing method to evaluate the children's health risk who explored to the high water fluoride environment but have had water changed for different years, as well as to recommend a safety dose for the local government based on the calculation of bench mark doses.
Objective:based on the study on the years of the children's exposure, the duration of water changed and different specific effects responded to fluoride exposures, to determine the benchmark doses of the specific effects of different fluoride exposures, to seek the changing rules and dose-response relationship ofthe specific effective criteria related to different water change years and children's urinary fluoride contents, to establish the children's health risk evaluation model and to provide the scientific basis for decision making to set the fluorine exposure limits and improve the children's health in the endemic fluorosis areas.
Methods:Four endemic fluorosis villages were randomly selected from63endemic fluorosis village of Chaonan county, Shantou city as well as a non-endemic fluorosis village and all of the children aged6-12were chosen for the examination of dental fluorosis, dental caries and600were selected for determines of fluoride contents in urine and serum osteocalcin, calcitonin, alkaline phosphates' content and bone mineral density. According to the test results of the above indicators, children's health risk assessment was conducted based on the Risk Assessment Guide revised in2001by the U.S. Environmental Protection Agency. The evaluation steps included identification of hazards, the dose-response relationship, evaluation of exposure assessment, and risk analysis. Software SPSS16.0and BMDS were used for statistics Including the identification of hazards by using Logistic regression analysis to analyze the correlation of fluoride exposure and the prevalence of various indicators(P<0.05showes statistically significant); using BMDS software to evaluate dose-response relationship and draw the dose-response curve between urine fluoride and indicators and calculate the reference dose, and the benchmark dose lower limit; average exposure was assessed to describe the dose of fluoride exposure, with a ceiling of90%of each indicator to determine the scope of the exception indicators; Logistic regression was used to analyze the relationship between exposure and abnormal; risk determination and risk scope were determined based on the benchmark dose lower limit.
Results:Fluoride contents in villages A, B, C, D before water changed were5.51mg/1,2.17mg/1,3.99mg/1and3.31mg/1. They all came down to0.11mg/1after water changed, consistent with the control village. The average of the children's urine fluoride in village E (control) was0.480mg/1, and those in A, B, C, D villages were0.62mg/1,0.51mg/1,0.36mg/1and0.27mg/1after water changed. The difference was statistically significant between the observed villages and the control one (χ2=127.915, P<0.001). The averaged children's urine fluoride in village A was higher than control, while the C and D Villages were lower than the control village. The children serum osteocalcin levels were significantly different among the years of water change(F=14.465, P<0.001), village B which was14years of water changed and control Village E were lower than the others. There are statistical differences between the levels of serum calcitonin(F=48.959, P<0.001), village B and C were lower than other villages but no difference between B and C. Differences between children serum alkaline phosphates'activity were statistically significant (F=9.831, P<0.001), Village C and D were lower than Village E. Children's bone mineral densities were also different(F=3.781,P=0.005), A Village and C village were higher than B village.
The dental fluorosis prevalence rate in the observed villages was76.99%before water change. After the water changes, all the observed villages except A have decreased to30%(below this value can be judged as a non-fluorine area). Based on the control Village E, the Logistic regression showes that the OR value of Village A was7.71(χ2=212.02, P<0.001), and no statistically significant OR values of the other villages. The dental caries prevalence rates in five villages were higher than30%. E village's caries prevalence was49.7%. Compared with E village of control, the Logistic regression analysis showed that the caries prevalence of villages A, B, C, D ware31.97%(OR=0.48, χ2=73.62, P<0.001),65.0%(OR=1.88, χ2=21.38, P<0.001),56.3%(OR=1.31, χ2=10.81, P<0.001), and45.2%(OR=0.83, χ2=3.40, P<0.001) respectively. All of the villages'osteocalcin, alkaline phosphates'and bone mineral density abnormal rates were not higher than the control village, but calcitonin anomalies in village A was higher than the control Village E,(OR=6.39,χ2=27.14, P<0.001).
With the increase in urine fluoride, dental fluorosis prevalence as well as OR values gradually increased. The urine fluoride content in the0.00-group had the highest caries prevalence of53.9%; The0.37-group had the lowest prevalence of dental caries of39.8%; The change showed a U-shaped trend. Osteocalcin, alkaline phosphates, bone mineral density anomaly rates were not different among the different urine fluoride groups. The calcitonin abnormal rate showed an upward trend with the increase of urinary fluoride contents. Compared to the urine fluoride content of0.0～group, the0.6～group's abnormal osteocalcin OR was2.35(χ2=4.02, P=0.045), and the0.9～group's OR was2.78(χ2=4.90, P=0.027).
The dose-response model of urinary fluoride and dental fluorosis selected Logistic model, with a benchmark dose BMD=0.857mg/1, BMDL (benchmark dose lower limit)=0.720mg/1. The dose-response relationship between the children's urinary fluoride and dental caries selected the Multistage model, the down trend curve of BMD and BMDL values were1.095and0.898mg/1, and the up trend curve of BMD and BMDL values were0.275and0.124mg/1respectively. Logistic regression model was selected to calculate the dose-response relationship of urinary fluoride and osteocalcin and BMD=0.975mg/1, BMDL=0.622mg/1. The calcitonin abnormal dose-response relationship model calculated Quantal-linear model:the BMD=0.636mg/1, BMDL=0.383mg/1. ALP dose-response relationship model was a Logistic regression model and the BMD=2.299mg/1, BMDL=0.837mg/1. Abnormal urinary fluoride and bone mineral density's dose-response relationship model chosen the log-logistic regression model, the BMD was0.941mg/1, and the BMDL was0.811mg/1.
The attributable risk (ARP) of dental fluorosis in the village with water change for six years was the lowest0.41; and the attributable risks for those with water change for14years,15years and17years were0.91,0.92and0.96. Compared with the lower limits for the safe dose range of each effect indicators and calculated OR value exceeded the safe dose range:OR values for dental fluorosis, osteocalcin, and calcitonin were2.415,1.945and1.761. Dental caries, alkaline phosphates, bone mineral density OR values were not statistically significant. The total value of risk calculated based on the combination of weight of quality of life and abnormal rate of the indicators showed an upward trend:total risk increases with the increasing of urinary fluoride content.
Conclusion:
1. The content of the fluoride in the drinking water in the water-changed villages meets the national health standards for drinking water (1.0mg/1or less).
2. When the water has been changed for more than six years, the observed village children's urinary fluoride, dental fluorosis prevalence and health effect indicators have reached the levels of non-fluorine village.
3. There are dose-response relationship between children's urinary fluoride and dental fluorosis, caries prevalence and four fluoride-induced bone damage indicators (BPG, CT, ALP, and bone mineral density). Urinary fluoride and dental caries shows a U-shaped curve relationship.
4.Through the dose-response relationship building between urinary fluoride and dental fluorosis, dental caries and four fluoride-induced bone injury indicators (BPG, CT, ALP, and bone mineral density), the BMD values for the above indicators were:0.857mg/1,1.095mg/1(caries upper limit) and0.275mg/1(caries lower limit value),0.975mg/1,0.636mg/1,2.299mg/1and0.941mg/1; BMDL value were:0.720mg/1,0.898mg/1(caries upper limit) and0.124mg/1(caries limit)0.622mg/1,0.383mg/1,0.837mg/1and0.811mg/1.
5. The urinary fluoride benchmark dose lower limit for each indicator can be used as a biological limit for the local areas.
6. In the observed villages with water change, the risk of dental caries in village B and C was higher than other villages.
引文
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