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Health risk in children to fluoride exposure in a typical endemic fluorosis area on Loess Plateau, north China, in the last decade
Chemosphere 243 (2020) 125451
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Health risk in children to fluoride exposure in a typical endemic fluorosis area on Loess Plateau, north China, in the last decade Li Yuan a, c, Wang Fei b, **, Feng Jia a, Lv Jun-ping a, Liu Qi a, Nan Fang-ru a, Liu Xu-dong a, Xie Shu-lian a, * a b c
School of Life Science, Shanxi University, Taiyuan, Shanxi, 030006, China School of Physical Education, Shanxi University, Taiyuan, Shanxi, 030006, China Taiyuan Monitoring Station of National Urban Water Quality Monitoring Network, Taiyuan, Shanxi, 030009, China
h i g h l i g h t s
g r a p h i c a l a b s t r a c t
Fluoride concentrations were 0.55 mg L1 in 3427 water consumption points in Shanxi Province. Health risks were assessed for children consumers regarding fluoride exposure. Approximately 10%, 1.3% and 0.06% children are at risk for dental decay, dental and skeletal fluorosis, respectively. The fluoride concentrations were being decreased significantly from 2008 to 2017. The fluoride endemic areas were marked by GIS mapping system.
a r t i c l e i n f o
a b s t r a c t
Article history: Received 23 September 2019 Received in revised form 5 November 2019 Accepted 22 November 2019 Available online 23 November 2019
Excessive and inadequate intake of fluoride may cause adverse effects in children, such as dental caries and dental fluorosis. This study reports the results of monitoring fluoride concentrations in drinking water from an endemic fluorosis region during the ten-year period (2008 through 2017). The fluoride concentration had a range of 0.03e9.42 mg L1 (mean ¼ 0.55 ± 0.01 mg L1). Approximately 10%, 1.3% and 0.06% children are at risk for dental decay, dental fluorosis and skeletal fluorosis, respectively. Probabilistic risks for children were assessed and the fluoride endemic areas were marked by GIS mapping system. On several water consumption points, the hazard quotient (HQ) values for children were higher than 1, indicating potential non-cancer health risks due to fluoride exposure. The results of this study will help governmental agencies to develop better policies for protecting children from exposure to fluoride. © 2019 Elsevier Ltd. All rights reserved.
Handling Editor: A. Gies Keywords: Fluoride Daily exposure Dental caries Dental fluorosis Hazard quotient GIS
* Corresponding author. School of Life Science, Shanxi University, No. 92 Wucheng Road, Taiyuan, 030006, China. ** Corresponding author. E-mail addresses: [email protected], [email protected] (X. Shu-lian). https://doi.org/10.1016/j.chemosphere.2019.125451 0045-6535/© 2019 Elsevier Ltd. All rights reserved.
1. Introduction Recently, increasing global attention has focused on public
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health issues related to fluoride exposure in children, especially in developing countries (Bretzler, 2017; Chen et al., 2016). Fluoride is abundant in nature and it can be easily dissolved in groundwater (WHO, 2011). Drinking water therefore represents the major source of daily fluoride exposure, with about 90% of fluoride from drinking water being absorbed through the digestive system (Yousefi et al., 2017). Approximately 65% of endemic fluorosis is caused by excessive fluoride exposure in drinking water (Fallahzadeh et al., 2018; Miri et al., 2017). It is known that inadequate or excessive intake of fluoride may cause adverse effects in children (Rasool et al., 2017). In cases of inadequate intake, such as if the fluoride concentration in drinking water is lower than 0.5 mg L1, the risks of dental caries in children may increase (Aslani et al., 2019; Kirkeskov et al., 2010). Fluoride can prevent tooth decay by up to 40% (Guissouma et al., 2017). In cases of an excessive fluoride concentration, e.g. between 1.5 and 5.0 mg L1, the risk of dental fluorosis and skeletal fluorosis may increase. Fluoride levels in drinking water in excess of 10.0 mg L1 can precipitate more diseases, such as hypertension, neurological problems, Alzheimer’s, cancer, etc., constituting a serious threat to human health (Neisi et al., 2018; Zhang et al., 2016). One study has documented that when fluoride concentrations in drinking water were higher than 1.0 mg L1 (1.0e11.6 mg L1), the prevalence of dental fluorosis was 62% among children between 8 and 15 years of age (Yu et al., 2013). Additionally, it has been shown that fluoride in drinking water can have a negative effect on the IQ of developing children (Razdan et al., 2017). These findings provided criteria for health departments to use when revising their screening guidelines of fluoride concentrations in drinking water to safe levels (Ding et al., 2011). For instance, fluoride concentrations between 0.5 and 1.5 mg L1 and 0.5e1.0 mg L1in drinking water are recommended by the World Health Organization (WHO) in order to prevent fluorosis and dental caries, respectively (WHO, 1996). Several new methods have been proposed to help children prevent future caries, such as application of compeer restorations to release fluoride and recommendations for fluoride limits in drinking water based on estimated daily fluoride intake (Trachtenberg et al., 2009). Health risk assessment has been applied extensively to estimate the probability of adverse health effects caused by the chemicals in contaminated environmental media (Peng et al., 2016). Hazard quotient (HQ) is often used to assess health risks associated with potentially hazardous pollutants (Augustsson and Berger, 2014; Miri et al., 2018). In a recent study involving children living in northwest Iran, Mahmood et al. (2019) found that HQ values exceeded 1.0 (indicating a health hazard) for 54.55% of the samples collected and advance proposals to decrease endemic fluorosis. A probabilistic approach, such as Monte Carlo simulation, has shown to be effective in obtaining the distribution of outcomes, by repeated selection from the probability distribution (Smith, 1994). This assessment method can be used to examine the real risk, especially in areas where risk is thought to be relatively low (Fallahzadeh et al., 2018; Craig et al., 2015). A Geographic Information System (GIS) can be useful for future water resource planning, and therefore also for regional decision-making on safe drinking water supply (Aghapour et al., 2018; Gholizadeh et al., 2017; Narsimha and Rajitha 2018; Saini et al., 2013). However, there still lack adequate and long-term evidences of fluoride exposure, it is difficult to map fluorosis areas for policy purposes correctly. Most studies of fluoride-related health problems have focused on the short-term risks, and the possible effects of fluoride trends through time are rarely considered. In order to investigate the harmful effects in children on a long-term scale, this study reports a complete survey of the fluoride exposure in drinking water in a typical endemic fluorosis area on Loess Plateau, Shanxi Province,
north China. This study provides the scientific community an effective method that was developed using a combined approach: assessing probabilistic risks and mapping fluorosis areas. The results of this research can help provide policymakers with appropriate guidance for the management of drinking water safety. 2. Materials and methods 2.1. Study area Shanxi Province (110140 Ne114 330 N, 34 340 E40 440 E), with an area of 156,700 km2, is located on Loess Plateau of North China. There is an estimated population of 37 million people distributed in 11 administrative areas, including Datong (DT), Xinzhou (XZ), Shuozhou (SZ), Taiyuan (TY), Jinzhong (JZ), Yangquan (YQ), Lvliang (LL), Changzhi (CZ), Linfen (LF), Jincheng (JC) and Yuncheng (YC), as shown in Fig. 1. Shanxi experiences four distinct seasons, and the climate is temperate with a mild continental monsoon. The annual average temperatures range from 4.2 to 14.2 C with an annual average precipitation of 358e621 mm. Shanxi is located in the eastern wing of the Loess Plateau and presents diverse topography, including hills, mountains, basins and plateaus. Mountain and hills account for roughly 80 percent of the total land area. The primary economic pillar of Shanxi is industry, especially coal. Coal resources have been over-exploited to support economic development, leading to land subsidence and groundwater pollution. Drinking water, which is a scarce commodity in Shanxi province as a whole, is derived from both surface water and groundwater resources. In addition, Shanxi Province is a typical endemic fluorosis area, in southern Shanxi over 69% of the shallow aquifers and 31% of the deep aquifers had fluoride concentrations above the WHO provisional drinking water guideline of 1.5 mg L1 (Li et al., 2015). 2.2. Sample collection and analysis During the period of 2008e2017, 3427 water samples, including tap water, pine water, well water and spring water, were collected from 11 administrative areas (Fig. 1). All the samples were from drinking water sources. Three samples were collected repeatedly at each point every time. The water samples were collected in 5.0 L polyethylene bottles washed twice with distilled water before, filtered using a vacuum filtration unit (0.45 mm, Advantec MFS, Inc., CA, USA) and then stored at 4 C prior to use analysis (Li et al., 2019). Global Positioning System (GPS, Unistrong G120BD) (Beijing, China) was used to locate the sites. To determine fluoride in drinking water, we followed the Chinese drinking water standard (GBe2006) and used ion chromatography (Thermo Scientific™ Dionex™ICSe1100) (MA, USA) (Prasad, 2018). 2.3. Exposure and health risk assessment Humans are exposed to fluoride in drinking water through oral intake, dermal absorption and inhalation (Zhang et al., 2017). In this research, two exposure pathways, daily intake (fluoride ingested only in drinking water) and dermal absorption were selected to estimate the daily exposure dose of fluoride by using Equations (1) and (2), based on USEPA (1989): 2.3.1. Estimated daily intake and dermal absorption
EDIingest ¼
Cw IRw EF ED BW AT
(1)
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Fig. 1. Distribution of the sampling points and fluoride concentrations (mg L1) of Shanxi Province. Different colors represent different administrative divisions. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
EDIabsorb ¼
Cw SA Kp F ETs EF ED 103 BW AT
safe level set at 1 (Zhang et al., 2017).
(2)
where EDIingest and EDIabsorb are the estimated daily intake of fluoride through ingestion and dermal absorption, respectively (mg kg1 day1); Cw is the fluoride concentration (ten-year average) in drinking water (mg L1); IRw is the drinking water ingestion rate (L day1); EF is the exposure frequency (days year1); ED is the exposure duration (year); BW is the body weight (kg); AT is the averaging time (days);SA is the skin surface area (cm2); Kp is the dermal permeability constant (cm h1); F is the fraction of surface skin contact with water (unitless); ETs is the exposure time in the shower (h day1); 103 is the number of L per cm3.The exposure parameters are listed in Table S1. 2.3.2. Hazard quotient (HQ) A Hazard quotient (HQ), an expression of non-carcinogenic risk through different exposure routes, was calculated using the estimated daily intake (EDI) and the oral reference dose (RfD) [Equation (3)]. Children, 0e14 years old, were the primary subjects. Children’s health risks were analyzed and evaluated because the risk posed to them is the highest. An upper limit of 95% confidence interval of the non-carcinogenic risks was used, and the HQ used a
HQ ¼
EDI Rf D
(3)
2.4. Statistical analysis To analyze the chronic health risks posed by fluoride, we focused on the long-term trends to fluoride concentrations at any given location. In our analysis, the average value for a decade of samples was used as a single data point. Fluoride concentration data were expressed as average values and standard error (SE). We used linear regression analysis to explore possible statistical relationships within three groups of data: all fluoride concentrations, all fluoride concentrations >1.5 mg L1, and all fluoride concentrations <0.5 mg L1. All of the concentration data in this study were processed in Microsoft Excel 2007. All statistical analyses were conducted using statistics software Sigma Plot 14.0 (CA, USA). The concentrations of fluoride across years and sampling sites were compared by one-way ANOVA analysis of variance; P < 0.05 was considered as statistically significant. ArcGIS Esri 10.2 (CA, USA) was used to spatially interpolate fluoride concentrations and
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fluoride risks across the study area. The inverse distance weighting (IDW) method was used to map fluoride endemic areas. Five categorical risk levels of fluoride concentration were created, namely Super High (4.01e10.00 mg L1), Very High (1.51e4.0 mg L1), High (1.01e1.5 mg L1), Optimal (0.51e1.0 mg L1) and Low (<0.5 mg L1), by considering fluoride concentrations less than 0.5 mg L1 as posing a higher risk for dental caries and concentrations greater than 1.5 mg L1 as posing a higher risk for dental fluorosis. 3. Results and discussion 3.1. Fluoride concentration The fluoride concentrations in Shanxi Province drinking water varied widely, from 0.03 mg L1 to 9.42 mg L1 in Shanxi Province with an average of 0.55 ± 0.01 mg L1, which is lower than the Chinese and WHO standard for drinking water (1.0 mg L1 and 1.5 mg L1, respectively) (Table 1). The highest fluoride concentration was found in JC (9.42 mg L1), followed by LF (9.13 mg L1). The lowest fluoride concentration was detected in LL (0.03 mg L1). The frequency distributions showed that 62.71% of fluoride concentrations in Shanxi Province are<0.5 mg L1, with 3.44% being >1.5 mg L1. In YQ, 90.00% of fluoride concentrations were <0.5 mg L1; while in LF 19.66% of fluoride concentrations are >1.0 mg L1. In the 11 geographical regions, 63.64% of all the areas were within the optimum fluoride range. No average fluoride concentrations >1.0 mg L1 were found. For comparison, a study conducted by Hu et al. (2013) in DT and SZ, northern Shanxi, reported that fluoride concentrations ranged from 0.3 to 5.6 mg L1.
of dental caries in Shanxi Province. Each country should provide appropriate standard fluoride concentrations in drinking water on the basis of their social-economic conditions and residents’ living habits (Khan et al., 2004; Ozsvath 2009). The areas, have high fluoride concentrations (>1.0 mg L1, such as YC, LF and JC), are mostly located in suburbs and remote mountain regions where the use of a centralized water supply is not feasible. Local policy makers have to remove fluoride in drinking water to prevent fluorosis (Yadav et al., 2017).
3.2. Spatial distribution of fluoride
3.3. Temporal distribution of fluoride
Fig. 2 shows fluoride levels in drinking water of Shanxi Province in ten years. The fluoride levels in LF, LL, DT, SZ, YC and TY are higher than that in SX. The fluoride level in LF is highest and the fluoride level in CZ is lowest. It should be noted that all the fluoride levels are lower than 0.5 mg L1. The GIS interpolation analysis of is plotted using the ten-year average fluoride concentrations, classified into five categories, forecasted the spatial distribution pattern of fluoride concentrations in drinking water in Shanxi Province (Fig. 3). The results show that fluoride concentrations in most areas are <0.5 mg L1, which is below the range recommended by WHO (2011) for the prevention of dental caries (0.5e1.0 mg L1). Fluorinated toothpaste and fluorinated food contribute to the suppression of dental caries especially in children, however fluorinated drinking water has not the recommended standard for the control
In addition to the spatial variations in fluoride concentrations in Shanxi Province, we investigated changes on a ten-year scale (Fig. S1). The average level of fluoride in Shanxi Province was the highest in 2009 (0.67 mg L1) and the lowest in 2017 (0.49 mg L1). The average level of fluoride concentrations exceeded 1.0 mg L1 in LL [1.14 mg L1 (in 2009)], in LF [1.04 mg L1 (in 2009); 1.22 mg L1 (in 2016)] and in JC [1.3 mg L1 (in 2015)]. The fluoride annual average levels of 2009 and 2010 were higher than the decadal average level of Shanxi. For decades, the main economic activity in Shanxi has been the coal industry (Cao, 2017). Long term widespread coal mining and coal combustion give rise to serious environmental problems such as emission of fluoride directly into atmosphere and surface water (may then enter groundwater through precipitation and seepage) (Querol et al., 2008; Edmunds
Fig. 2. Box plot of fluoride concentrations (mg L1) in drinking water of Shanxi Province in ten years.
Table 1 Fluoride concentrations (mg L1) and frequency in drinking water in each district of Shanxi Province. Location
Datong Xinzhou Shuozhou Taiyuan* Jinzhong Yangquan Lvliang Changzhi Linfen Jincheng Yuncheng Shanxi Province
Region
DT XZ SZ TY JZ YQ LL CZ LF JC YC SX
N
67 810 132 898 334 60 657 97 173 41 158 3427
N: number of samples; Taiyuan*: capital.
Fluoride (mg L1)
Frequency
Range
Mean
SE
<0.5 mg L1
0.5e1.0 mg L1
1.0e4.0 mg L1
>4.0 mg L1
0.10e1.49 0.06e8.24 0.10e1.99 0.10e5.70 0.09e3.16 0.10e0.99 0.03e6.49 0.10e2.88 0.10e9.13 0.11e9.42 0.10e2.95 0.03e9.42
0.49 0.52 0.55 0.58 0.47 0.38 0.59 0.39 0.69 0.75 0.62 0.55
0.03 0.02 0.03 0.02 0.02 0.02 0.02 0.03 0.06 0.15 0.03 0.01
0.6567 0.7235 0.5303 0.5846 0.6946 0.9000 0.5175 0.8866 0.5029 0.4478 0.6013 0.6271
0.3134 0.2086 0.4318 0.3263 0.2605 0.1000 0.3957 0.0722 0.3006 0.1045 0.2278 0.2903
0.0299 0.0617 0.0379 0.0857 0.0449 0.0000 0.0807 0.0412 0.1908 0.0448 0.1709 0.0826
0.0000 0.0062 0.0000 0.0033 0.0000 0.0000 0.0061 0.0000 0.0058 0.0149 0.0000 0.0041
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regulations have been actually implemented to prevent adverse effects from the fluoride in the drinking water including improving water projects and drilling deep wells (selection of water source) in Shanxi Province (Cai et al., 2016; Shan et al., 2013). These could be responsible for the decreasing trend of all fluoride concentrations and fluoride concentrations <0.5 mg L1. 3.4. Dental disease risk in children Our results showed that approximately 10%, 1.3% and 0.06% children, based on overall average concentrations for the ten-year period, are at risk for dental decay, dental fluorosis and skeletal fluorosis, respectively (Table 2). There have more of children being suffering the risk of dental decay in YQ (13.95%). Appropriate fluoridation measures such as foods, drinks, tea and fluoride toothpastes need to be proposed by local government. The children in LF (2.96%) and YC (2.65%) have the highest risk of dental fluorosis than other locations; the children in JC (0.23%) have the highest risk of skeletal fluorosis. These three areas are all located in south basin areas of SX. Groundwater moves from the margin to the center of the basin. The poor hydrodynamic conditions in the center and the slow runoff of groundwater result in the poor quality in the lowaltitude area (Li et al., 2011). The higher incidence in LF, YC and JC might be related to topography and groundwater flow conditions. Defluoridation projects (such as improving drinking water project), which effectively reduce the fluoride in drinking water, are necessary for these higher incidence areas (Zhang et al., 2017). 3.5. Health risk assessment of fluoride
Fig. 3. Spatial distribution maps of fluoride concentrations in drinking water in endemic fluorosis areas in Shanxi Province.
and Smedley, 2013). Active environmental policy implemented in 2009 such as recent recombination of coal industry and attempts to introduce clean energy in Shanxi Province might be one of the reasons of water quality improvement. Simple linear regressions were performed for the three groups of data: all fluoride concentrations, all fluoride concentrations >1.5 mg L1, and all fluoride concentrations <0.5 mg L1 (Fig. 4). The results indicate that two of these data sets exhibited significant downward trends from 2008 to 2017: all fluoride concentrations (r ¼ 0.011, p < 0.001) and fluoride concentrations < 0.5 mg L1 (r ¼ 3.433, p < 0.001). In recent years, many policies and
The non-carcinogenic risk HQ was used to evaluate the risk to human health of fluoride in drinking water. In our study, the calculated risk index includes two exposure routes: daily intake and dermal absorption. HQ for children was calculated using the average fluoride concentration for the ten years of data from each region (Fig. 5). Because children have the lowest BW, they have higher health risk values. In some areas HQ of children was >1, such as northern XZ, western LL, southern LF and northern YC, indicating that fluoride might pose non-carcinogenic health risks to the local children. Fig. S2 showed the spatial distribution of HQ of children changed through 2008 to 2017. High HQ of children appeared in the west, middle, southeast and southwest of Shanxi Province in 2009, 2010, 2015 and 2016, respectively. These time points are helpful to find out connections between time and environmental policy. Overall the HQ levels of the ten-year fluoride are lower than 1 in most of Shanxi Province. It is connected with improving water projects and recent positive environment policies. For example,
Fig. 4. Simple linear regression and correlation test of regression coefficients for fluoride concentration variations in Shanxi Province from 2008 to 2017: a, b and c represent all of fluoride concentrations, larger than 1.5 mg L1 and lower than 0.5 mg L1, respectively.
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Table 2 Risks of dental caries, dental fluorosis and skeletal fluorosis in children in Shanxi Province. Region
DT XZ SZ TY JZ YQ LL CZ LF JC YC SX
Population ( 104)
332 307 171 420 325 139 373 333 432 228 513 3573
Children ( 104) (1e14 years old)
51.46 47.585 26.505 65.1 50.375 21.545 57.815 51.615 66.96 35.34 79.515 553.815
Average altitude (m)
1044 790 1087 778 811 742 951 931 450 800 376 e
Risk Dental caries
Safety
Dental fluorosis
Skeletal fluorosis
10.18% 11.21% 8.22% 9.06% 10.77% 13.95% 8.02% 13.74% 7.79% 6.94% 9.32% 9.72%
4.86% 3.23% 6.69% 5.06% 4.04% 1.55% 6.13% 1.12% 4.66% 1.62% 3.53% 4.50%
0.46% 0.96% 0.59% 1.33% 0.70% 0.00% 1.25% 0.64% 2.96% 0.69% 2.65% 1.28%
0.00% 0.10% 0.00% 0.05% 0.00% 0.00% 0.09% 0.00% 0.09% 0.23% 0.00% 0.06%
continuously updated protection policies) to decrease the adverse health impacts. 3.6. Comparison of fluoride concentrations The relationship between fluoride and drinking water has been investigated in many developing countries to better understand the distribution of fluoride and its potential health risks to human beings (Table 3). In this study, the mean fluoride level of SX (0.55 mg L1) is lower than a national average level (0.66 mg L1) and the maximum value of SX (9.42 mg L1) is at a higher level (5.6, 5.7, 6.2 mg L1). There is a need for policymakers to establish appropriate native guidelines to protecting local residents, especially in endemic area like Shanxi Province. For example, fluoride toxicity increases with the amount of drinking water being consumed. Therefore, in the humid tropics, the maximum permissible fluoride concentration in drinking water ought to be proportionally lower (Craig et al., 2015). The criteria regarding fluoride content in drinking water differ across regions in response to specific conditions. Especially in China, there is no the minimum limit for fluoride in drinking water to protect from dental caries. There is a famous saying in China: specific analysis for specific problems. It is necessary to determine local guideline values that are suitable for a respective area based on its economy, politics, climate, population and environment. 4. Conclusions
Fig. 5. Health risk assessment for children in the endemic fluorosis areas in Shanxi Province.
Zhang et al. (2017) reported the fluoride concentration in improved drinking water ranged from 0.7 to 1.0 mg L1 (1.8e6.2 mg L1, before improving) in Shanxi Province. However, the specific areas with high risks of fluoride on children should receive more health concerns, and some effective measures (such as reasonable water source selection, regular monitoring of water quality and
This study investigated the spatial-temporal distribution of fluoride in drinking water and its health risk in a typical endemic fluorosis area of northern China. Probabilistic risks in children were assessed and the fluoride endemic areas were marked by GIS mapping system. Our results suggested that approximately 10%, 1.3% and 0.06% children are at risk for dental decay, dental fluorosis and skeletal fluorosis, respectively, according to the limits of fluoride in drinking water recommended by WHO. This study provided valuable information helping governmental agencies to develop better policies for protecting children from exposure to fluoride. Further research should focus on the relationship between land use change caused by human activity and fluoride level. Declaration of competing interest The authors declare that they have no conflict of interest.
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Table 3 Comparison of fluoride concentrations (mg L1) in drinking water with guidelines and other studied areas. Criteria China WHO US EPA
Drinking water quality Drinking water quality Drinking water quality 1
Region
Location
Range (mg L
China China China China China Iran India Pakistan
Taiyuan, Shanxi Province Northern Shanxi Province Yuncheng, Shanxi Province Shanxi Province national level Yazd province Alleppey province Sindh Province
0.1e5.7 0.3e5.6 0.31e14.2 1.8e6.2 0.3e15.24 0.02e1.96 0.68e2.88 1.10e7.90
)
Guidelines (mg L1)
Reference
<1.0 0.5e1.5 0.70e1.20
a
1
Average (mg L 0.63 e 2.4 0.89 0.66 0.658 e 3.33
)
b c
N
Reference
485 111 70 802 61,671 269 16 32
Li et al. (2019) Hu et al. (2013) Khair et al. (2014) Zhang et al. (2017) Zhang et al. (2017) Fallahzadeh et al. (2018) Dhanya and Shaji (2017) Rafique et al. (2009)
N: number of samples. a Standards for drinking water quality GB5749-2006, 2007. b Guidelines for drinking water quality, fourth edition, 2011. c Edition of the drinking water standards and health advisories, 2012.
Acknowledgments We are grateful to Dr D.F. Crockett (University of Oklahoma, USA) for the editorial assistance with English. This work was funded by financial support from the National Natural Sciences Foundation of China (No.41401020; No.41601202), the Social Development Foundation of Shanxi, China (No. 201603D321008; 201803D31204-1), the Applied Basic Research Project of Shanxi, China (No.201801D121261) and the Fund for Shanxi “1331 Project”. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.chemosphere.2019.125451. References Aghapour, S., Bina, B., Tarrahi, M.J., Amiri, F., Ebrahimi, A., 2018. Distribution and health risk assessment of natural fluoride of drinking groundwater resources of Isfahan, Iran, using GIS. Environ. Monit. Assess. 190, 137. https://doi.org/10.1007/ s10661-018-6467-z. Aslani, H., Zarei, M., Taghipour, H., Khashabi, E., Ghanbari, H., Ejlali, A., 2019. Monitoring, mapping and health risk assessment of fluoride in drinking water supplies in rural areas of Maku and Poldasht, Iran. Environ Geochem Health 1e14. https://doi.org/10.1007/s10653-019-00282-x. Augustsson, A., Berger, T., 2014. Assessing the risk of an excess fluoride intake among Swedish children in households with private wells d expanding static single-source methods to a probabilistic multi-exposure-pathway approach. Environ. Int. 68, 192e199. https://doi.org/10.1016/j.envint.2014.03.014. Bretzler, A., 2017. Fluoride in drinking water: status, issues and solutions. Gr. Water 55, 155. https://doi.org/10.1111/gwat.12497. Cai, H., Xu, L., Chen, G., Peng, C., Ke, F., Liu, Z., et al., 2016. Removal of fluoride from drinking water using modified ultrafine tea powder processed using a ball-mill. Appl. Surf. Sci. 375, 74e84. https://doi.org/10.1016/j.apsusc.2016.03.005. Cao, X., 2017. Policy and regulatory responses to coalmine closure and coal resources consolidation for sustainability in Shanxi, China. J. Clean. Prod. 145, 199e208. https://doi.org/10.1016/j.jclepro.2017.01.050. Chen, J., Wu, H., Qian, H., Gao, Y., 2016. Assessing nitrate and fluoride contaminants in drinking water and their health risk of rural residents living in a semiarid region of northwest China. Expos Health 1e13. https://doi.org/10.1007/s12403016-0231-9. Craig, L., Lutz, A., Berry, K., Yang, W., 2015. Recommendations for fluoride limits in drinking water based on estimated daily fluoride intake in the upper east region, Ghana. Sci. Total Environ. 532, 127e137. https://doi.org/10.1016/ j.scitotenv.2015.05.126. Dhanya, R., Shaji, E., 2017. Fluoride contamination in groundwater resources of alleppey, southern India. Geosci. Front. 8, 117e124. https://doi.org/10.1016/ j.gsf.2016.01.002. Ding, Y., Gao, Y., Sun, H., Han, H., Wang, W., Ji, X., et al., 2011. The relationships between low levels of urine fluoride on children’s intelligence, dental fluorosis in endemic fluorosis areas in Hulunbuir, Inner Mongolia, China. J. Hazard Mater. 186, 1942e1946. https://doi.org/10.1016/j.jhazmat.2010.12.097. Edmunds, W., Smedley, P., 2013. Fluoride in Natural Waters. Essentials of Medical Geology. Springer, Netherlands. https://doi.org/10.1007/978-94-007-4375-5_13.
Fallahzadeh, R.A., Miri, M., Taghavi, M., Gholizadeh, A., Anbarani, R., HosseiniBandegharaei, A., et al., 2018. Spatial variation and probabilistic risk assessment of exposure to fluoride in drinking water. Food Chem. Toxicol. 113, 314e321. https://doi.org/10.1016/j.fct.2018.02.001. Gholizadeh, A., Mokhtari, M., Naimi, N., Shiravand, B., Ehrampoush, M.H., Miri, M., et al., 2017. Assessment of corrosion and scaling potential in groundwater resources; a case study of Yazd-Ardakan Plain, Iran. Groundw Sustain Dev 5, 59e65. https://doi.org/10.1016/j.gsd.2017.04.002. Guissouma, W., Hakami, O., Al-Rajab, A., Tarhouni, J., 2017. Risk assessment of fluoride exposure in drinking water of Tunisia. Chemosphere 177, 102e108. https://doi.org/10.1016/j.chemosphere.2017.03.011. Hu, S., Luo, T., Jing, C., 2013. Principal component analysis of fluoride geochemistry of groundwater in Shanxi and Inner Mongolia, China. Geochem Explor 135, 124e129. https://doi.org/10.1016/j.gexplo.2012.08.013. Khair, A., Li, C., Hu, Q., Gao, X., Wang, Y., 2014. Fluoride and arsenic hydrogeochemistry of groundwater at Yuncheng basin, northern China. Geochem. Int. 52, 868e881. https://doi.org/10.1134/S0016702914100024. Khan, A., Whelton, H., O’Mullane, D., 2004. Is the fluoride level in drinking water a gold standard for the control of dental caries? Int. Dent. J. 54, 256e260. https:// doi.org/10.1111/j.1875-595X.2004.tb00290.x. Kirkeskov, L., Kristiansen, E., Bøggild, H., von Platen-Hallermund, F., Sckerl, H., Carlsen, A., 2010. The association between fluoridein drinking water and dentalcaries in Danish children: linking data from health registers, environmental registers and administrative registers. Community Dent Oral 38, 206e212. https://doi.org/10.1111/j.1600-0528.2009.00526.x. Li, C., Gao, X., Wang, Y., 2014. Fluoride and arsenic hydrogeochemistry of groundwater at Yuncheng basin, northern China. Sci. Total Environ. 508, 155e165. https://doi.org/10.1134/S0016702914100024. Li, X., Hou, X., Zhou, Z., Liu, L., 2011. Geochemical provenance and spatial distribution of fluoride in groundwater of Taiyuan Basin, China. Environ. Earth Sci. 62, 1635e1642. https://doi.org/10.1007/s12665-010-0648-6. Li, Y., Wang, F., Feng, J., Lv, J., Liu, Q., Nan, F., et al., 2019. Long term spatial-temporal dynamics of fluoride in sources of drinking water and associated health risks in a semiarid region of Northern China. Ecotox. Environ. Saf. 171, 274e280. https:// doi.org/10.1016/j.ecoenv.2018.12.090. Miri, M., Akbari, E., Amrane, A., Jafari, S.J., Eslami, H., Hoseinzadeh, E., et al., 2017. Health risk assessment of heavy metal intake due to fish consumption in the Sistan region, Iran. Environ. Monit. Assess. 189, 583. https://doi.org/10.1007/ s10661-017-6286-7. Miri, M., Bhatnagar, A., Mahdavi, Y., Basiri, L., Nakhaei, A., Khosravi, R., et al., 2018. Probabilistic risk assessment of exposure to fluoride in most consumed brands of tea in the Middle East. Food Chem. Toxicol. 115, S0278691518301728 https:// doi.org/10.1016/j.fct.2018.03.023. Mahmood, Y., Saha, G., Farzaneh, B., Afshin, G., Mohammad, H., Mansour, G., 2019. Distribution of fluoride contamination in drinking water resources and health risk assessment using geographic information system, northwest Iran. Regul. Toxicol. Pharm. 107, 104408. https://doi.org/10.1007/s10661-018-6467-z. Narsimha, A., Rajitha, S., 2018. Spatial distribution and seasonal variation in fluoride enrichment in groundwater and its associated human health risk assessment in Telangana State, South India. Hum. Ecol. Risk Assess 1e14. https://doi.org/ 10.1080/10807039.2018.1438176. Neisi, A., Mirzabeygi, M., Zeyduni, G., Hamzezadeh, A., Jalili, D., Abbasnia, A., et al., 2018. Data on fluoride concentration levels in cold and warm season in City area of Sistan and Baluchistan Province, Iran. Data Brief 18, 713e718. https://doi.org/ 10.1016/j.dib.2018.03.060. Ozsvath, D., 2009. Fluoride and environmental health: a review. Rev. Environ. Sci. Biotechnol. 8, 59e79. https://doi.org/10.1007/s11157-008-9136-9. Peng, Q., Nunes, L., Greenfield, B., Dang, F., Zhong, H., 2016. Are Chinese consumers at risk due to exposure to metals in crayfish? A bioaccessibility-adjusted
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probabilistic risk assessment. Environ. Int. 88, 261e268. https://doi.org/10.1016/ j.envint.2015.12.035. Prasad, N., Pushpaangaeli, B., Ram, A., Maimanuku, L., 2018. Fluoride concentration in drinking water samples in Fiji. AUST Aust. NZ J Publ. Heal. 42, 372e374. https://doi.org/10.1111/1753-6405.12787. Querol, X., Izquierdo, M., Monfort, E., Alvarez, E., Font, O., Moreno, T., et al., 2008. Environmental characterization of burnt coal gangue banks at Yangquan, Shanxi province, China. Int. J. Coal Geol. 75 (2), 93e104. https://doi.org/10.1016/ j.coal.2008.04.003. Rafique, T., Naseem, S., Usmani, T., Bashir, E., Khan, F., Bhanger, M., 2009. Geochemical factors controlling the occurrence of high fluoride groundwater in the Nagar Parkar area, Sindh, Pakistan. J. Hazard Mater. 171, 424e430. https:// doi.org/10.1016/j.jhazmat.2009.06.018. Rasool, A., Farooqi, A., Xiao, T., Ali, W., Noor, S., Abiola, O., et al., 2017. A review of global outlook on fluoride contamination in groundwater with prominence on the Pakistan current situation. Environ. Geochem. Health 40, 1e17. https:// doi.org/10.1007/s10653-017-0054-z. Razdan, P., Patthi, B., Kumar, J., Agnihotri, N., Chaudhari, P., Prasad, M., 2017. Effect of fluoride concentration in drinking water on intelligence quotient of 12-14-yearold children in Mathura district: a cross-sectional study. J. Int. Soc. Prev. Community Dent. 7, 252e258. https://doi.org/10.4103/jispcd.JISPCD_201_17. Saini, P., Khan, S., Baunthiyal, M., Sharma, V., 2013. Mapping of fluoride endemic area and assessment of F-1 accumulation in soil and vegetation. Environ. Monit. Assess. 185, 2001e2008. https://doi.org/10.1007/s10661-012-2683-0. Shan, H., Luo, T., Jing, C., 2013. Principal component analysis of fluoride geochemistry of groundwater in Shanxi and Inner Mongolia, China. J. Geochem. Explor. 135, 124e129. https://doi.org/10.1016/j.gexplo.2012.08.013. Smith, R., 1994. Use of Monte Carlo simulation for human exposure assessment at a superfund site. Risk Anal. 14, 433e439. https://doi.org/10.1111/j.1539-
6924.1994.tb00261.x. Trachtenberg, F., Maserejian, N., Soncini, J., Hayes, C., Tavares, M., 2009. Does fluoride in compomers prevent future caries in children? J. Dent. Res. 88, 276e279. https://doi.org/10.1177/0022034508330884. USEPA, 1989. Risk Assessment Guidance for Superfund, vol. I. Human Health Evaluation Manual (Part A). WHO, 1996. Guidelines for Drinking-Water Quality, second ed., vol. 2. Health criteria and other supporting information. WHO, 2011. Guidelines for Drinking Water Quality. World Health Organization, Geneva. Yadav, K., Gupta, N., Kumar, V., Khan, S., Kumar, A., 2017. A review of emerging adsorbents and current demand for defluoridation of water: bright future in water sustainability. Environ. Int. 111, 80e108. https://doi.org/10.1016/ j.envint.2017.11.014. Yousefi, M., Ghoochani, M., Hossein, M., 2017. Health risk assessment to fluoride in drinking water of rural residents living in the Poldasht city, Northwest of Iran. Ecotoxicol. Environ. Saf. 148, 426. https://doi.org/10.1016/j.ecoenv.2017.10.057. Yu, S., Chen, S., Li, B., Zhao, X., Zhang, M., 2013. Change of urinary fluoride and bone metabolism indicators in the endemic fluorosis areas of southern China after supplying low fluoride public water. BMC Public Health 13. https://doi.org/ 10.1186/1471-2458-13-156, 156-156. Zhang, Le, Huang, D., Yang, J., Wei, X., Qin, J., Ou, S., et al., 2017. Probabilistic risk assessment of Chinese residents’ exposure to fluoride in improved drinking water in endemic fluorosis areas. Environ. Pollut. 222, 118e125. https://doi.org/ 10.1016/j.envpol.2016.12.074. Zhang, S., Niu, Q., Gao, H., Ma, R., Lei, R., Zhang, C., et al., 2016. Excessive apoptosis and defective autophagy contribute to developmental testicular toxicity induced by fluoride. Environ. Pollut. 212, 97e104. https://doi.org/10.1016/ j.envpol.2016.01.059.
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Health risk in children to fluoride exposure in a typical endemic fluorosis area on Loess Plateau, north China, in the last decade Li Yuan a, c, Wang Fei b, **, Feng Jia a, Lv Jun-ping a, Liu Qi a, Nan Fang-ru a, Liu Xu-dong a, Xie Shu-lian a, * a b c
School of Life Science, Shanxi University, Taiyuan, Shanxi, 030006, China School of Physical Education, Shanxi University, Taiyuan, Shanxi, 030006, China Taiyuan Monitoring Station of National Urban Water Quality Monitoring Network, Taiyuan, Shanxi, 030009, China
h i g h l i g h t s
g r a p h i c a l a b s t r a c t
Fluoride concentrations were 0.55 mg L1 in 3427 water consumption points in Shanxi Province. Health risks were assessed for children consumers regarding fluoride exposure. Approximately 10%, 1.3% and 0.06% children are at risk for dental decay, dental and skeletal fluorosis, respectively. The fluoride concentrations were being decreased significantly from 2008 to 2017. The fluoride endemic areas were marked by GIS mapping system.
a r t i c l e i n f o
a b s t r a c t
Article history: Received 23 September 2019 Received in revised form 5 November 2019 Accepted 22 November 2019 Available online 23 November 2019
Excessive and inadequate intake of fluoride may cause adverse effects in children, such as dental caries and dental fluorosis. This study reports the results of monitoring fluoride concentrations in drinking water from an endemic fluorosis region during the ten-year period (2008 through 2017). The fluoride concentration had a range of 0.03e9.42 mg L1 (mean ¼ 0.55 ± 0.01 mg L1). Approximately 10%, 1.3% and 0.06% children are at risk for dental decay, dental fluorosis and skeletal fluorosis, respectively. Probabilistic risks for children were assessed and the fluoride endemic areas were marked by GIS mapping system. On several water consumption points, the hazard quotient (HQ) values for children were higher than 1, indicating potential non-cancer health risks due to fluoride exposure. The results of this study will help governmental agencies to develop better policies for protecting children from exposure to fluoride. © 2019 Elsevier Ltd. All rights reserved.
Handling Editor: A. Gies Keywords: Fluoride Daily exposure Dental caries Dental fluorosis Hazard quotient GIS
* Corresponding author. School of Life Science, Shanxi University, No. 92 Wucheng Road, Taiyuan, 030006, China. ** Corresponding author. E-mail addresses: [email protected], [email protected] (X. Shu-lian). https://doi.org/10.1016/j.chemosphere.2019.125451 0045-6535/© 2019 Elsevier Ltd. All rights reserved.
1. Introduction Recently, increasing global attention has focused on public
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health issues related to fluoride exposure in children, especially in developing countries (Bretzler, 2017; Chen et al., 2016). Fluoride is abundant in nature and it can be easily dissolved in groundwater (WHO, 2011). Drinking water therefore represents the major source of daily fluoride exposure, with about 90% of fluoride from drinking water being absorbed through the digestive system (Yousefi et al., 2017). Approximately 65% of endemic fluorosis is caused by excessive fluoride exposure in drinking water (Fallahzadeh et al., 2018; Miri et al., 2017). It is known that inadequate or excessive intake of fluoride may cause adverse effects in children (Rasool et al., 2017). In cases of inadequate intake, such as if the fluoride concentration in drinking water is lower than 0.5 mg L1, the risks of dental caries in children may increase (Aslani et al., 2019; Kirkeskov et al., 2010). Fluoride can prevent tooth decay by up to 40% (Guissouma et al., 2017). In cases of an excessive fluoride concentration, e.g. between 1.5 and 5.0 mg L1, the risk of dental fluorosis and skeletal fluorosis may increase. Fluoride levels in drinking water in excess of 10.0 mg L1 can precipitate more diseases, such as hypertension, neurological problems, Alzheimer’s, cancer, etc., constituting a serious threat to human health (Neisi et al., 2018; Zhang et al., 2016). One study has documented that when fluoride concentrations in drinking water were higher than 1.0 mg L1 (1.0e11.6 mg L1), the prevalence of dental fluorosis was 62% among children between 8 and 15 years of age (Yu et al., 2013). Additionally, it has been shown that fluoride in drinking water can have a negative effect on the IQ of developing children (Razdan et al., 2017). These findings provided criteria for health departments to use when revising their screening guidelines of fluoride concentrations in drinking water to safe levels (Ding et al., 2011). For instance, fluoride concentrations between 0.5 and 1.5 mg L1 and 0.5e1.0 mg L1in drinking water are recommended by the World Health Organization (WHO) in order to prevent fluorosis and dental caries, respectively (WHO, 1996). Several new methods have been proposed to help children prevent future caries, such as application of compeer restorations to release fluoride and recommendations for fluoride limits in drinking water based on estimated daily fluoride intake (Trachtenberg et al., 2009). Health risk assessment has been applied extensively to estimate the probability of adverse health effects caused by the chemicals in contaminated environmental media (Peng et al., 2016). Hazard quotient (HQ) is often used to assess health risks associated with potentially hazardous pollutants (Augustsson and Berger, 2014; Miri et al., 2018). In a recent study involving children living in northwest Iran, Mahmood et al. (2019) found that HQ values exceeded 1.0 (indicating a health hazard) for 54.55% of the samples collected and advance proposals to decrease endemic fluorosis. A probabilistic approach, such as Monte Carlo simulation, has shown to be effective in obtaining the distribution of outcomes, by repeated selection from the probability distribution (Smith, 1994). This assessment method can be used to examine the real risk, especially in areas where risk is thought to be relatively low (Fallahzadeh et al., 2018; Craig et al., 2015). A Geographic Information System (GIS) can be useful for future water resource planning, and therefore also for regional decision-making on safe drinking water supply (Aghapour et al., 2018; Gholizadeh et al., 2017; Narsimha and Rajitha 2018; Saini et al., 2013). However, there still lack adequate and long-term evidences of fluoride exposure, it is difficult to map fluorosis areas for policy purposes correctly. Most studies of fluoride-related health problems have focused on the short-term risks, and the possible effects of fluoride trends through time are rarely considered. In order to investigate the harmful effects in children on a long-term scale, this study reports a complete survey of the fluoride exposure in drinking water in a typical endemic fluorosis area on Loess Plateau, Shanxi Province,
north China. This study provides the scientific community an effective method that was developed using a combined approach: assessing probabilistic risks and mapping fluorosis areas. The results of this research can help provide policymakers with appropriate guidance for the management of drinking water safety. 2. Materials and methods 2.1. Study area Shanxi Province (110140 Ne114 330 N, 34 340 E40 440 E), with an area of 156,700 km2, is located on Loess Plateau of North China. There is an estimated population of 37 million people distributed in 11 administrative areas, including Datong (DT), Xinzhou (XZ), Shuozhou (SZ), Taiyuan (TY), Jinzhong (JZ), Yangquan (YQ), Lvliang (LL), Changzhi (CZ), Linfen (LF), Jincheng (JC) and Yuncheng (YC), as shown in Fig. 1. Shanxi experiences four distinct seasons, and the climate is temperate with a mild continental monsoon. The annual average temperatures range from 4.2 to 14.2 C with an annual average precipitation of 358e621 mm. Shanxi is located in the eastern wing of the Loess Plateau and presents diverse topography, including hills, mountains, basins and plateaus. Mountain and hills account for roughly 80 percent of the total land area. The primary economic pillar of Shanxi is industry, especially coal. Coal resources have been over-exploited to support economic development, leading to land subsidence and groundwater pollution. Drinking water, which is a scarce commodity in Shanxi province as a whole, is derived from both surface water and groundwater resources. In addition, Shanxi Province is a typical endemic fluorosis area, in southern Shanxi over 69% of the shallow aquifers and 31% of the deep aquifers had fluoride concentrations above the WHO provisional drinking water guideline of 1.5 mg L1 (Li et al., 2015). 2.2. Sample collection and analysis During the period of 2008e2017, 3427 water samples, including tap water, pine water, well water and spring water, were collected from 11 administrative areas (Fig. 1). All the samples were from drinking water sources. Three samples were collected repeatedly at each point every time. The water samples were collected in 5.0 L polyethylene bottles washed twice with distilled water before, filtered using a vacuum filtration unit (0.45 mm, Advantec MFS, Inc., CA, USA) and then stored at 4 C prior to use analysis (Li et al., 2019). Global Positioning System (GPS, Unistrong G120BD) (Beijing, China) was used to locate the sites. To determine fluoride in drinking water, we followed the Chinese drinking water standard (GBe2006) and used ion chromatography (Thermo Scientific™ Dionex™ICSe1100) (MA, USA) (Prasad, 2018). 2.3. Exposure and health risk assessment Humans are exposed to fluoride in drinking water through oral intake, dermal absorption and inhalation (Zhang et al., 2017). In this research, two exposure pathways, daily intake (fluoride ingested only in drinking water) and dermal absorption were selected to estimate the daily exposure dose of fluoride by using Equations (1) and (2), based on USEPA (1989): 2.3.1. Estimated daily intake and dermal absorption
EDIingest ¼
Cw IRw EF ED BW AT
(1)
L. Yuan et al. / Chemosphere 243 (2020) 125451
3
Fig. 1. Distribution of the sampling points and fluoride concentrations (mg L1) of Shanxi Province. Different colors represent different administrative divisions. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
EDIabsorb ¼
Cw SA Kp F ETs EF ED 103 BW AT
safe level set at 1 (Zhang et al., 2017).
(2)
where EDIingest and EDIabsorb are the estimated daily intake of fluoride through ingestion and dermal absorption, respectively (mg kg1 day1); Cw is the fluoride concentration (ten-year average) in drinking water (mg L1); IRw is the drinking water ingestion rate (L day1); EF is the exposure frequency (days year1); ED is the exposure duration (year); BW is the body weight (kg); AT is the averaging time (days);SA is the skin surface area (cm2); Kp is the dermal permeability constant (cm h1); F is the fraction of surface skin contact with water (unitless); ETs is the exposure time in the shower (h day1); 103 is the number of L per cm3.The exposure parameters are listed in Table S1. 2.3.2. Hazard quotient (HQ) A Hazard quotient (HQ), an expression of non-carcinogenic risk through different exposure routes, was calculated using the estimated daily intake (EDI) and the oral reference dose (RfD) [Equation (3)]. Children, 0e14 years old, were the primary subjects. Children’s health risks were analyzed and evaluated because the risk posed to them is the highest. An upper limit of 95% confidence interval of the non-carcinogenic risks was used, and the HQ used a
HQ ¼
EDI Rf D
(3)
2.4. Statistical analysis To analyze the chronic health risks posed by fluoride, we focused on the long-term trends to fluoride concentrations at any given location. In our analysis, the average value for a decade of samples was used as a single data point. Fluoride concentration data were expressed as average values and standard error (SE). We used linear regression analysis to explore possible statistical relationships within three groups of data: all fluoride concentrations, all fluoride concentrations >1.5 mg L1, and all fluoride concentrations <0.5 mg L1. All of the concentration data in this study were processed in Microsoft Excel 2007. All statistical analyses were conducted using statistics software Sigma Plot 14.0 (CA, USA). The concentrations of fluoride across years and sampling sites were compared by one-way ANOVA analysis of variance; P < 0.05 was considered as statistically significant. ArcGIS Esri 10.2 (CA, USA) was used to spatially interpolate fluoride concentrations and
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fluoride risks across the study area. The inverse distance weighting (IDW) method was used to map fluoride endemic areas. Five categorical risk levels of fluoride concentration were created, namely Super High (4.01e10.00 mg L1), Very High (1.51e4.0 mg L1), High (1.01e1.5 mg L1), Optimal (0.51e1.0 mg L1) and Low (<0.5 mg L1), by considering fluoride concentrations less than 0.5 mg L1 as posing a higher risk for dental caries and concentrations greater than 1.5 mg L1 as posing a higher risk for dental fluorosis. 3. Results and discussion 3.1. Fluoride concentration The fluoride concentrations in Shanxi Province drinking water varied widely, from 0.03 mg L1 to 9.42 mg L1 in Shanxi Province with an average of 0.55 ± 0.01 mg L1, which is lower than the Chinese and WHO standard for drinking water (1.0 mg L1 and 1.5 mg L1, respectively) (Table 1). The highest fluoride concentration was found in JC (9.42 mg L1), followed by LF (9.13 mg L1). The lowest fluoride concentration was detected in LL (0.03 mg L1). The frequency distributions showed that 62.71% of fluoride concentrations in Shanxi Province are<0.5 mg L1, with 3.44% being >1.5 mg L1. In YQ, 90.00% of fluoride concentrations were <0.5 mg L1; while in LF 19.66% of fluoride concentrations are >1.0 mg L1. In the 11 geographical regions, 63.64% of all the areas were within the optimum fluoride range. No average fluoride concentrations >1.0 mg L1 were found. For comparison, a study conducted by Hu et al. (2013) in DT and SZ, northern Shanxi, reported that fluoride concentrations ranged from 0.3 to 5.6 mg L1.
of dental caries in Shanxi Province. Each country should provide appropriate standard fluoride concentrations in drinking water on the basis of their social-economic conditions and residents’ living habits (Khan et al., 2004; Ozsvath 2009). The areas, have high fluoride concentrations (>1.0 mg L1, such as YC, LF and JC), are mostly located in suburbs and remote mountain regions where the use of a centralized water supply is not feasible. Local policy makers have to remove fluoride in drinking water to prevent fluorosis (Yadav et al., 2017).
3.2. Spatial distribution of fluoride
3.3. Temporal distribution of fluoride
Fig. 2 shows fluoride levels in drinking water of Shanxi Province in ten years. The fluoride levels in LF, LL, DT, SZ, YC and TY are higher than that in SX. The fluoride level in LF is highest and the fluoride level in CZ is lowest. It should be noted that all the fluoride levels are lower than 0.5 mg L1. The GIS interpolation analysis of is plotted using the ten-year average fluoride concentrations, classified into five categories, forecasted the spatial distribution pattern of fluoride concentrations in drinking water in Shanxi Province (Fig. 3). The results show that fluoride concentrations in most areas are <0.5 mg L1, which is below the range recommended by WHO (2011) for the prevention of dental caries (0.5e1.0 mg L1). Fluorinated toothpaste and fluorinated food contribute to the suppression of dental caries especially in children, however fluorinated drinking water has not the recommended standard for the control
In addition to the spatial variations in fluoride concentrations in Shanxi Province, we investigated changes on a ten-year scale (Fig. S1). The average level of fluoride in Shanxi Province was the highest in 2009 (0.67 mg L1) and the lowest in 2017 (0.49 mg L1). The average level of fluoride concentrations exceeded 1.0 mg L1 in LL [1.14 mg L1 (in 2009)], in LF [1.04 mg L1 (in 2009); 1.22 mg L1 (in 2016)] and in JC [1.3 mg L1 (in 2015)]. The fluoride annual average levels of 2009 and 2010 were higher than the decadal average level of Shanxi. For decades, the main economic activity in Shanxi has been the coal industry (Cao, 2017). Long term widespread coal mining and coal combustion give rise to serious environmental problems such as emission of fluoride directly into atmosphere and surface water (may then enter groundwater through precipitation and seepage) (Querol et al., 2008; Edmunds
Fig. 2. Box plot of fluoride concentrations (mg L1) in drinking water of Shanxi Province in ten years.
Table 1 Fluoride concentrations (mg L1) and frequency in drinking water in each district of Shanxi Province. Location
Datong Xinzhou Shuozhou Taiyuan* Jinzhong Yangquan Lvliang Changzhi Linfen Jincheng Yuncheng Shanxi Province
Region
DT XZ SZ TY JZ YQ LL CZ LF JC YC SX
N
67 810 132 898 334 60 657 97 173 41 158 3427
N: number of samples; Taiyuan*: capital.
Fluoride (mg L1)
Frequency
Range
Mean
SE
<0.5 mg L1
0.5e1.0 mg L1
1.0e4.0 mg L1
>4.0 mg L1
0.10e1.49 0.06e8.24 0.10e1.99 0.10e5.70 0.09e3.16 0.10e0.99 0.03e6.49 0.10e2.88 0.10e9.13 0.11e9.42 0.10e2.95 0.03e9.42
0.49 0.52 0.55 0.58 0.47 0.38 0.59 0.39 0.69 0.75 0.62 0.55
0.03 0.02 0.03 0.02 0.02 0.02 0.02 0.03 0.06 0.15 0.03 0.01
0.6567 0.7235 0.5303 0.5846 0.6946 0.9000 0.5175 0.8866 0.5029 0.4478 0.6013 0.6271
0.3134 0.2086 0.4318 0.3263 0.2605 0.1000 0.3957 0.0722 0.3006 0.1045 0.2278 0.2903
0.0299 0.0617 0.0379 0.0857 0.0449 0.0000 0.0807 0.0412 0.1908 0.0448 0.1709 0.0826
0.0000 0.0062 0.0000 0.0033 0.0000 0.0000 0.0061 0.0000 0.0058 0.0149 0.0000 0.0041
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regulations have been actually implemented to prevent adverse effects from the fluoride in the drinking water including improving water projects and drilling deep wells (selection of water source) in Shanxi Province (Cai et al., 2016; Shan et al., 2013). These could be responsible for the decreasing trend of all fluoride concentrations and fluoride concentrations <0.5 mg L1. 3.4. Dental disease risk in children Our results showed that approximately 10%, 1.3% and 0.06% children, based on overall average concentrations for the ten-year period, are at risk for dental decay, dental fluorosis and skeletal fluorosis, respectively (Table 2). There have more of children being suffering the risk of dental decay in YQ (13.95%). Appropriate fluoridation measures such as foods, drinks, tea and fluoride toothpastes need to be proposed by local government. The children in LF (2.96%) and YC (2.65%) have the highest risk of dental fluorosis than other locations; the children in JC (0.23%) have the highest risk of skeletal fluorosis. These three areas are all located in south basin areas of SX. Groundwater moves from the margin to the center of the basin. The poor hydrodynamic conditions in the center and the slow runoff of groundwater result in the poor quality in the lowaltitude area (Li et al., 2011). The higher incidence in LF, YC and JC might be related to topography and groundwater flow conditions. Defluoridation projects (such as improving drinking water project), which effectively reduce the fluoride in drinking water, are necessary for these higher incidence areas (Zhang et al., 2017). 3.5. Health risk assessment of fluoride
Fig. 3. Spatial distribution maps of fluoride concentrations in drinking water in endemic fluorosis areas in Shanxi Province.
and Smedley, 2013). Active environmental policy implemented in 2009 such as recent recombination of coal industry and attempts to introduce clean energy in Shanxi Province might be one of the reasons of water quality improvement. Simple linear regressions were performed for the three groups of data: all fluoride concentrations, all fluoride concentrations >1.5 mg L1, and all fluoride concentrations <0.5 mg L1 (Fig. 4). The results indicate that two of these data sets exhibited significant downward trends from 2008 to 2017: all fluoride concentrations (r ¼ 0.011, p < 0.001) and fluoride concentrations < 0.5 mg L1 (r ¼ 3.433, p < 0.001). In recent years, many policies and
The non-carcinogenic risk HQ was used to evaluate the risk to human health of fluoride in drinking water. In our study, the calculated risk index includes two exposure routes: daily intake and dermal absorption. HQ for children was calculated using the average fluoride concentration for the ten years of data from each region (Fig. 5). Because children have the lowest BW, they have higher health risk values. In some areas HQ of children was >1, such as northern XZ, western LL, southern LF and northern YC, indicating that fluoride might pose non-carcinogenic health risks to the local children. Fig. S2 showed the spatial distribution of HQ of children changed through 2008 to 2017. High HQ of children appeared in the west, middle, southeast and southwest of Shanxi Province in 2009, 2010, 2015 and 2016, respectively. These time points are helpful to find out connections between time and environmental policy. Overall the HQ levels of the ten-year fluoride are lower than 1 in most of Shanxi Province. It is connected with improving water projects and recent positive environment policies. For example,
Fig. 4. Simple linear regression and correlation test of regression coefficients for fluoride concentration variations in Shanxi Province from 2008 to 2017: a, b and c represent all of fluoride concentrations, larger than 1.5 mg L1 and lower than 0.5 mg L1, respectively.
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Table 2 Risks of dental caries, dental fluorosis and skeletal fluorosis in children in Shanxi Province. Region
DT XZ SZ TY JZ YQ LL CZ LF JC YC SX
Population ( 104)
332 307 171 420 325 139 373 333 432 228 513 3573
Children ( 104) (1e14 years old)
51.46 47.585 26.505 65.1 50.375 21.545 57.815 51.615 66.96 35.34 79.515 553.815
Average altitude (m)
1044 790 1087 778 811 742 951 931 450 800 376 e
Risk Dental caries
Safety
Dental fluorosis
Skeletal fluorosis
10.18% 11.21% 8.22% 9.06% 10.77% 13.95% 8.02% 13.74% 7.79% 6.94% 9.32% 9.72%
4.86% 3.23% 6.69% 5.06% 4.04% 1.55% 6.13% 1.12% 4.66% 1.62% 3.53% 4.50%
0.46% 0.96% 0.59% 1.33% 0.70% 0.00% 1.25% 0.64% 2.96% 0.69% 2.65% 1.28%
0.00% 0.10% 0.00% 0.05% 0.00% 0.00% 0.09% 0.00% 0.09% 0.23% 0.00% 0.06%
continuously updated protection policies) to decrease the adverse health impacts. 3.6. Comparison of fluoride concentrations The relationship between fluoride and drinking water has been investigated in many developing countries to better understand the distribution of fluoride and its potential health risks to human beings (Table 3). In this study, the mean fluoride level of SX (0.55 mg L1) is lower than a national average level (0.66 mg L1) and the maximum value of SX (9.42 mg L1) is at a higher level (5.6, 5.7, 6.2 mg L1). There is a need for policymakers to establish appropriate native guidelines to protecting local residents, especially in endemic area like Shanxi Province. For example, fluoride toxicity increases with the amount of drinking water being consumed. Therefore, in the humid tropics, the maximum permissible fluoride concentration in drinking water ought to be proportionally lower (Craig et al., 2015). The criteria regarding fluoride content in drinking water differ across regions in response to specific conditions. Especially in China, there is no the minimum limit for fluoride in drinking water to protect from dental caries. There is a famous saying in China: specific analysis for specific problems. It is necessary to determine local guideline values that are suitable for a respective area based on its economy, politics, climate, population and environment. 4. Conclusions
Fig. 5. Health risk assessment for children in the endemic fluorosis areas in Shanxi Province.
Zhang et al. (2017) reported the fluoride concentration in improved drinking water ranged from 0.7 to 1.0 mg L1 (1.8e6.2 mg L1, before improving) in Shanxi Province. However, the specific areas with high risks of fluoride on children should receive more health concerns, and some effective measures (such as reasonable water source selection, regular monitoring of water quality and
This study investigated the spatial-temporal distribution of fluoride in drinking water and its health risk in a typical endemic fluorosis area of northern China. Probabilistic risks in children were assessed and the fluoride endemic areas were marked by GIS mapping system. Our results suggested that approximately 10%, 1.3% and 0.06% children are at risk for dental decay, dental fluorosis and skeletal fluorosis, respectively, according to the limits of fluoride in drinking water recommended by WHO. This study provided valuable information helping governmental agencies to develop better policies for protecting children from exposure to fluoride. Further research should focus on the relationship between land use change caused by human activity and fluoride level. Declaration of competing interest The authors declare that they have no conflict of interest.
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Table 3 Comparison of fluoride concentrations (mg L1) in drinking water with guidelines and other studied areas. Criteria China WHO US EPA
Drinking water quality Drinking water quality Drinking water quality 1
Region
Location
Range (mg L
China China China China China Iran India Pakistan
Taiyuan, Shanxi Province Northern Shanxi Province Yuncheng, Shanxi Province Shanxi Province national level Yazd province Alleppey province Sindh Province
0.1e5.7 0.3e5.6 0.31e14.2 1.8e6.2 0.3e15.24 0.02e1.96 0.68e2.88 1.10e7.90
)
Guidelines (mg L1)
Reference
<1.0 0.5e1.5 0.70e1.20
a
1
Average (mg L 0.63 e 2.4 0.89 0.66 0.658 e 3.33
)
b c
N
Reference
485 111 70 802 61,671 269 16 32
Li et al. (2019) Hu et al. (2013) Khair et al. (2014) Zhang et al. (2017) Zhang et al. (2017) Fallahzadeh et al. (2018) Dhanya and Shaji (2017) Rafique et al. (2009)
N: number of samples. a Standards for drinking water quality GB5749-2006, 2007. b Guidelines for drinking water quality, fourth edition, 2011. c Edition of the drinking water standards and health advisories, 2012.
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