Fluoride Action Network

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BACKGROUND

The intellectual loss induced by fluoride exposure has been extensively studied, but the association between fluoride exposure in different susceptibility windows and children’s intelligence is rarely reported. Hence, we conducted a cross-sectional study to explore the association between fluoride exposure in prenatal and childhood periods and intelligence quotient (IQ).

Methods

We recruited 633 local children aged 7–13 years old randomly from four primary schools in Kaifeng, China in 2017. The children were divided into four groups, of which included: control group (CG, n = 228), only prenatal excessive fluoride exposure group (PFG, n = 107), only childhood excessive fluoride exposure group (CFG, n = 157), both prenatal and childhood excessive fluoride exposure group (BFG, n = 141). The concentrations of urinary fluoride (UF) and urinary creatinine (UCr) were determined by fluoride ion-selective electrode assay and a creatinine assay kit (picric acid method), respectively. The concentration of UCr-adjusted urinary fluoride (CUF) was calculated. IQ score was assessed using the second revision of the Combined Raven’s Test-The Rural in China (CRT-RC2). Threshold and saturation effects analysis, multiple linear regression analysis and logistic regression analysis were conducted to analyze the association between fluoride exposure and IQ.

Results

The mean IQ score in PFG was respectively lower than those in CG, CFG and BFG (P < 0.05). The odds of developing excellent intelligence among children in PFG decreased by 51.1% compared with children in CG (OR .489, 95% CI: 0.279, 0.858). For all the children, CUF concentration of  >1.7 mg/L was negatively associated with IQ scores (B = -4.965, 95% CI: -9.198, -0.732, P = 0.022). In children without prenatal fluoride exposure, every 1.0 mg/L increment in the CUF concentration of  >2.1 mg/L was related to a reduction of 11.4 points in children’s IQ scores (95% CI: -19.2, -3.5, P = 0.005).

Conclusions

Prenatal and childhood excessive fluoride exposures may impair the intelligence development of school children. Furthermore, children with prenatal fluoride exposure had lower IQ scores than children who were not prenatally exposed; therefore the reduction of IQ scores at higher levels of fluoride exposure in childhood does not become that evident.

Background

Fluoride can prevent dental caries [1], and it is beneficial to bone metabolism as an essential trace element in the body [2]. However, the safe dose range of fluoride is limited [3]. Increasing evidences have shown that long-term exposure to excessive fluoride will not only increase the risk of dental fluorosis [4] and skeletal fluorosis [5], but also impair neural development by influencing gene and protein expression, enzyme activity and inducing oxidative stress [6].

The effects of fluoride on the nervous system have been manifested in intellectual development of rats [7]. Chronic high fluoride exposure of maternal mice in drinking water during pregnancy and lactation may have harmful influences on learning and memory of young mice [8]. Studies indicated that fluoride ingested by the mother can cross the placental barrier [9] and the blood-brain barrier [10], to affect the offspring’s cognitive function development [11]. Green et al. (2019) found that prenatal exposure to excessive fluoride was associated with children’s lower IQ scores. Surprisingly, the mean fluoride concentrations of drinking water in the fluoridated and non-fluoridated communities were 0.59 and 0.13 mg/L, respectively [12], which were lower than 1.5 mg/L suggested by the World Health Organization [3]. Elsewhere, a cross-sectional study in India showed that children’s intelligence quotient (IQ) was inversely associated with fluoride exposure via drinking water and maternal diet during pregnancy [13]. And, another Mexican study suggested that maternal exposure to excessive fluoride during pregnancy reduced children’s cognition and IQ scores, and the fluoride exposure range was 0.15–1.38 mg/L [14]. Some contradictory results have been found in the association between childhood fluoride exposure and intellectual development. Among such instances, a Chinese study found that exposure to moderately high fluoride in childhood could cause the loss of excellent intelligence [15]. A cohort study in Canada also reported that water fluoride concentration was associated with intelligence loss of formula-fed children, and the mean fluoride concentrations in the drinking water in the fluoridated and non-fluoridated communities appeared same as the study of Green et al. (2019) [16]. Meanwhile, no association between excessive fluoride and IQ scores were observed in a community water fluoridation program in New Zealand, where the fluoride concentration ranged from 0.7 to 1.0 mg/L [17]. Adding to the above, there was no significant correlation between fluoride exposure and lower IQ in adolescents [18]. Due to the different study populations and areas, the conclusion that excessive fluoride causes loss of children’s IQ still lacks strong evidence. Furthermore, compared with children without tobacco smoke exposure history, the relative risk of behavior problems of children exposed only in prenatal period was 90% higher, while that of children exposed only in postnatal period was 30% according to a prospective birth cohort study [19], indicating that the effects of prenatal and postnatal exposure on children’s neurodevelopment are different.

On the basis of the above analyses, it is an urgent need to distinguish the health effects of fluoride exposure in different susceptibility windows during development. Here, we selected Tongxu County, Kaifeng, Henan Province, a typical drinking-water-born fluorosis area, as the research region (no industrial sources of neurotoxic environmental pollutants such as arsenic, lead, mercury, etc.) to assess the association between excessive fluoride exposure in prenatal or childhood periods and children’s intelligence.

Methods

Study areas and population

Four primary schools were randomly selected in Tongxu County, Henan Province, China from late April to late May in 2017. The study was conducted in the middle of the semester, when students were in school with no psychological fluctuations caused by the beginning or end of the semester and psychological pressure brought by the final exam. The natural conditions, living conditions, population composition, living habits and dietary structure of the four schools were consistent, and no industrial fluoride pollution source was found in all the investigated areas. Exclusion criteria included taking calcium supplements, children who were not resident locally, diagnosed of digestive disease, thyroid disease, calcium and phosphorus metabolism disorders. The potential eligible participants included 642 students (7–13 years old) from the four primary schools in grades 2–6, and were recruited by the cluster sampling method. Then, 9 children were excluded for incomplete information or urinary samples. Finally, a total of 633 participants were included in the study with the participation rate of 98.60%. This study was approved by the Ethics Review Board at Zhengzhou University (ZZUIRB2017–018). All the children and their legal guardians were informed of the study procedures and signed the informed consent before recruitment.

General data collection

The study’s questionnaire was designed in advance, including sociodemographic information, medical history, maternal pregnancy and delivery information, birth characteristics and personal behaviors (such as daily exercise, diet). The student’s status at school was filled by the student or the teacher, and other information was provided by the guardian. The physical measurements of this study were completed by the clinical professional doctors in the survey area based on the standard method recommended by Chinese hygiene department. Physical measurements included weight, height, etc. The height and weight of the participants were measured by standard calibrated ruler and weight measurement device (V. BODY HBF-371; OMRON, Kyoto, Japan) according to the operation guidance, and were measured twice to the nearest 0.1 cm and 0.1 kg, respectively, all done while the participants wore light clothing and stood barefooted. The average value was considered for analysis. Body mass index (BMI) was calculated according to weight (kg)/square of height (m2).

Exposure assessment

Morning urine (at least 50 mL) was collected into cleaned polyethylene tubes and then stored at – 80°C, as described in the previous study [20]. Determination of urinary fluoride (UF) concentrations were conducted by a fluoride ion-selective electrode (Shanghai Exactitude Instruments, Shanghai, China), and the standard curve method was used according to the protocol of health industry standard of China (WS/T 89–2015). The fluoride standard stock solution (National Center for Analysis and Testing for Nonferrous Metals and Electronic Materials, GSB 04–1771-2004) was 1000 mg/L. UF levels in each sample were measured twice, and the mean value was used. The recovery rates reached 93.19–109.93%. The concentrations of urinary creatinine (UCr) were determined using a creatinine assay kit (picric acid method) (Jiancheng Bioengineering Institute, Nanjing, China). All of the samples were measured in duplicate, and two measurements were averaged for analysis. Fifteen percent of urine samples from different plates were randomly selected to repeat the measurement of UCr. The recovery rates were 93.83–105.25%. To correct the influence of urinary dilution on UF concentration, the concentrations of UCr-adjusted urinary fluoride (CUF) were calculated using the following equation: CUF (mg/L) = (UF (mg/L)/UCr (mg/L))× UCrmean (mg/L), where UCrmean is the mean Cr concentration of total samples available [21]. According to whether the mother was exposed to excessive fluoride (the fluoride concentration in drinking water > 1.0mg/L, GB5749–2006) during pregnancy, the children were divided into two groups: prenatal excessive fluoride exposure group (PF), and prenatal control group (PC). Moreover, according to whether the children’s UF concentration exceeded the national standard (UF concentration > 1.4 mg/L, WS/T 256–2005), children were divided into childhood excessive fluoride exposure group and childhood control group. On the basis of the above criteria, eligible children were divided into four groups: only prenatal excessive fluoride exposure group (PFG), only childhood excessive fluoride exposure group (CFG), both prenatal and childhood excessive fluoride exposure group (BFG), control group (CG).

Outcome assessment

The second revision of the Combined Raven’s Test-The Rural in China (CRT-RC2) was used to measure children’s IQ scores [22]. The IQ test was conducted in the school classrooms. Each child had an independent desk. Students completed the answer sheets independently under the supervision of trained investigators. The test conditions, test methods, calculation steps, etc. performed were totally consistent with the protocol of the Combined Raven’s Test. The classification criteria for children’s IQ were excellent (IQ scores > 130), superior (IQ scores 120–129), high normal (IQ scores 110–119), normal (IQ scores 90–109), dull normal (IQ scores 80–89), marginal (IQ scores 70–79) and retarded (IQ scores <69) [23]. Due to few children with IQ scores < 90 (n = 11), thus, we included children with IQ scores < 90 (n = 622) in the intelligence analysis.

Statistical analysis

Epidata version 3.0 (Epidata Association Odense, Denmark) was used to establish the database, and all data were independently integrated into the database by two investigators. One-way ANOVA was used to compare the difference of the continuous variables among the four exposure groups and the results were described by the mean ± standard deviation. Chi-square test was used to compare the difference of distribution of categorical variables in different groups, and the results were described in percentage (number). Multiple logistic regression analysis was conducted to explore the differences of intelligence distribution in different fluoride exposure groups. Threshold and saturation effects analysis and multiple linear regression analysis were used to analyze the association between CUF concentration and IQ scores and, the association between prenatal fluoride exposure and IQ scores. The analyses were adjusted for children’s age, gender, gestational weeks, maternal education level, paternal education level and children’s BMI. All data were analyzed by SPSS software, version 25.0 (SPSS Inc., Chicago, USA) and EmpowerStats (R). Plots were drawn by Graphpad prism 6.01. The criterion with statistical difference was P < 0.05.

Results

Distribution of general characteristics

All of the 633 children were divided into CG, PFG, CFG and BFG. As shown in Table 1, children’s age in PFG and BFG were higher than that in CG and CFG (P < 0.05, respectively). Similar results could be observed in the distribution of children’s height, weight and BMI (P <0.05, respectively). The CUF concentrations of children in PFG, CFG and BFG were higher than that in CG, and the CUF concentrations of children in CFG and BFG were higher than that in PFG (P < 0.05, respectively). IQ scores of children in PFG were lower than that in CG, CFG and BFG (P< 0.05, respectively). Moreover, no statistical differences were observed among the four groups under the distribution of children’s gender, birth weight, gestational weeks, maternal and paternal education levels and birth mode (P > 0.05, respectively).

Table 1 Characteristics of children aged 7–13 years
Full size table

Comparisons of intelligence in different fluoride exposure groups

Logistic regression analysis suggested that the odds of developing excellent intelligence for children in PFG decreased by 51.1% compared with children in CG (OR = 0.489, 95% CI: 0.279, 0.858). No significant associations between the odds of developing normal, high normal and superior intelligence and fluoride exposure were found (Table 2). As shown in Fig. 1, the percentages of children with superior intelligence in PFG and BFG were 34 and 35%, respectively. Children with excellent intelligence in CG and CFG had the percentage of 33 and 34%, respectively.

Table 2 Logistic regression analysis between fluoride exposure and children’s intelligence
Fig. 1
figure1

Distribution of all children’s intelligence in different fluoride exposure groups. The percentages of children with superior intelligence in PFG and BFG were 34 and 35%, respectively. Children with excellent intelligence in CG and CFG had the percentage of 33 and 34%, respectively

Association between CUF concentration and children’s IQ scores

The CUF concentrations of the 633 children included in the study ranged from 0.18 mg/L to 3.39 mg/L, and the mean ± standard deviation was 1.44 ± 0.76 mg/L. The range of IQ scores was 60.00–146.00, and the mean ± standard deviation was 122.48 ± 12.91. In Fig. 2, we observed a negative association between children’s IQ scores and concentrations of CUF at 1.7 mg/L (P < 0.05).

Fig. 2
figure2

Association between fluoride exposure and children’s IQ scores of all childrena. a Adjusted for age, gender, gestational weeks, maternal education level, paternal education level and children’s BMI. The estimated values and their corresponding 95% CI were respectively represented by the solid line and the dotted lines. A negative association was observed between children’s IQ scores and concentrations of CUF at >1.7m g/L (P < 0.05)

Multiple liner regression analysis presented that a decrease of 4.965 points in children’s IQ scores was associated with each 1.0?mg/L increase in the CUF concentration of >1.7 mg/L (95% CI: -9.198, -0.732, P = 0.022) (Table 3). No statistical significance was observed in the association between CUF concentration and children’s IQ scores in PF and PC, respectively. Furthermore, the interaction between prenatal exposure and CUF concentration on children’s IQ scores in PF and PC was not statistically significant (P > 0.05, respectively) (Table 3).

Table 3 Multiple liner regression analysis between fluoride exposure and children’s IQ scores

Threshold and saturation effects of fluoride exposure on children’s IQ scores in PF and PC

Figure 3a showed that the association between CUF concentrations and changes in IQ scores among children in PF was initially positive, and then saturated gradually. However, in Fig. 3b, children’s IQ scores in PC rose slowly to a peak and then fell evidently. And we observed every 1.0 mg/L increment in the CUF concentration of > 2.1 mg/L was related to a reduction of 11.4 points in children’s IQ scores (B = -11.4, 95% CI: -19.2, -3.5, P = 0.005) (Fig. 3b).

Fig. 3
figure3

Associations between fluoride exposure and children’s IQ scores in PF (a)a and PC (b)a. a Adjusted for age, gender, gestational weeks, maternal education level, paternal education level and children’s BMI. The estimated values and their corresponding 95% CI were represented by the solid line and the dotted lines

Discussion

Our study examined the association between excessive fluoride exposure in prenatal and childhood periods and the intelligence of school-age children. We found that prenatal excessive fluoride exposure could cause lower IQ scores, especially the decreased odds of developing excellent intelligence. Meanwhile, a negative association between fluoride exposure and children’s IQ scores was observed in children without prenatal exposure.

Several epidemiological studies have shown that excessive prenatal fluoride exposure could reduce offspring’s IQ scores [12, 14], which are consistent with our findings. Fluoride ingested by the mother during pregnancy can cross the placental barrier and enter the embryo [24], and affect the brain development of children [25]. In addition, we found that the odds of developing excellent intelligence for children in PFG decreased by 51.1% compared with nonexposed children. Lower intelligence has become a new public health and social problem, which not only endangers children’s physical and mental health, but also increases family burden [26, 27]. Hence, it is necessary to consider limiting the intake of excessive fluoride by pregnant women.

For all participants, we observed that a decrease of 4.965 points in children’s IQ scores was associated with each 1.0 mg/L increase in the CUF concentration of >1.7 mg/L. A cross-sectional study found that moderate fluoride exposure was inversely correlated with children’s IQ scores, and suggested a UF threshold of 1.6 mg/L for intelligence damage [15]. The reason for the difference between the two thresholds may be that we adjusted the UF concentration by UCr. We further found that every 1.0 mg/L increment in the CUF concentration of >2.1 mg/L was related to a reduction of 11.4 points of children’s IQ scores in prenatal control group. These results suggested that excessive fluoride exposure in childhood was negatively associated with children’s IQ scores. Fluoride can penetrate into the brain through the blood-brain barrier [10]. Several researches reported that exposure to fluoride could damage the function of hippocampus and thyroid, thus impairing intellectual development of school children [28, 29]. Contrary, no findings were obtained in a New Zealand study to support that fluoride exposure in community water fluoridation could affect neurologic development or IQ of children aged 7–13 years old [17]. Also, a study in India showed that fluorosis was not significantly associated with adolescent intelligence in a non-endemic fluorosis area with lower level of fluoride [18]. The differences of exposure level, ethnicity and study areas may explain these results which are inconsistent with ours.

An animal experiment found that fluoride may elevate fluoride tolerance by down-regulating ribosomes, pancreatic secretion, steroid biosynthesis, glutathione metabolism, steroid biosynthesis, and glycerolipid metabolism gene expression [30]. Furthermore, another animal experiment suggested that the decrease of the susceptibility to fluoride was related to the changes in expression level of glutathione S-transferase gene after fluoride stimulation [31]. In the current population study, we found some similar results. Children with prenatal fluoride exposure have lower IQ scores, and therefore the reduction of IQ scores at higher CUF levels in some range during childhood did not become that evident. In addition, the IQ scores of children without prenatal exposure decreased evidently with the increase of CUF concentrations of >2.1 mg/L (Fig. 3). However, the mechanism still needs to be further studies at the population level.

Our study has several limitations. Firstly, urine samples were collected in the morning, not 24 h. However, a study has reported that for population studies, morning urine is a good representation of 24-h urine samples and the results are reliable [32]. Secondly, considering the influence of urine dilution on UF, UCr was used to adjust the UF. However, due to the instability of UCr in growing children or experiencing puberty, this may also be one of the limitations. Since the subjects in our study are all boarding students, their same diet and sleep schedule could alleviate the limitation to some extent. Thirdly, it was very difficult to obtain UF concentrations data from a pregnant mother, thus, we used the fluoride level in local drinking water during mother’s pregnancy. This is because fluoride level in drinking water is highly correlated with UF level [33]. On point, all the mothers in the study were local residents, and local drinking water fluoride level in the village could well represent maternal fluoride exposure level. Fourthly, the project was a cross-sectional study which lasted 1 month, and only one-time sampling was conducted, and so the inferential causality was weak. Long term large-scale epidemiological studies should be conducted to provide more abundant evidences. Finally, we tried to reduce the influence on the results through adjusting for children’s age, gender, gestational weeks, parental education levels and children’s BMI, though some unknown confounding factors may still.

Conclusions

In summary, prenatal and childhood exposure to excessive fluoride may impair the intelligence development of school children. Furthermore, children with prenatal fluoride exposure had lower IQ scores than children who were not prenatally exposed; therefore the reduction of IQ scores at higher levels of fluoride exposure in childhood does not become that evident. Our results support the necessary restriction of fluoride intake for pregnant women and school-age children to protect children’s intellectual development.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

IQ:
Intelligence quotient
BMI:
Body mass index
UF:
Urinary fluoride
UCr:
Urinary creatinine
CUF:
UCr-adjusted urinary fluoride
PF:
Prenatal excessive fluoride exposure group
PC:
Prenatal control group
PFG:
Only prenatal excessive fluoride exposure group
CFG:
Only childhood excessive fluoride exposure group
BFG:
Both prenatal and childhood excessive fluoride exposure group
CG:
Control group
CRT-RC2:
The second revision of the Combined Raven’s Test-The Rural in China
CI:
Confidence interval

References

  1. Featherstone JD. Prevention and reversal of dental caries: role of low level fluoride. Community Dent Oral Epidemiol. 1999;27(1):31–40.

    CAS  Article  Google Scholar

  2. Yamaguchi M. Fluoride and bone metabolism. Clinical Calcium. 2007;17(2):217–23.

    CAS  Google Scholar

  3. WHO. Fluorides, Environmental Health Criteria no. 227, United Nations Environmental Programme, International Labour Organization. Geneva: World Health Organization; 2002.

    Google Scholar

  4. Kumar S, Chauhan A, Kumar A, Kumar S, Gupta A, Roy S, et al. Dental fluorosis and associated risk factors in early adolescents in India. Int J Adolesc Med Health. 2018;32(4):20170200.

  5. Daiwile AP, Tarale P, Sivanesan S, Naoghare PK, Bafana A, Parmar D, et al. Role of fluoride induced epigenetic alterations in the development of skeletal fluorosis. Ecotoxicol Environ Saf. 2019;169:410–7.

    CAS  Article  Google Scholar

  6. Dec K, Lukomska A, Skonieczna-Zydecka K, Jakubczyk K, Tarnowski M, Lubkowska A, et al. Chronic exposure to fluoride affects GSH level and NOX4 expression in rat model of this element of neurotoxicity. Biomolecules. 2020;10(3):422.

    CAS  Article  Google Scholar

  7. Jiang C, Zhang S, Liu H, Guan Z, Zeng Q, Zhang C, et al. Low glucose utilization and neurodegenerative changes caused by sodium fluoride exposure in rat’s developmental brain. Neuromolecular Med. 2014;16(1):94–105.

  8. Sun Z, Zhang Y, Xue X, Niu R, Wang J. Maternal fluoride exposure during gestation and lactation decreased learning and memory ability, and glutamate receptor mRNA expressions of mouse pups. Hum Exp Toxicol. 2018;37(1):87–93.

    CAS  Article  Google Scholar

  9. Shen YW, Taves DR. Fluoride concentrations in the human placenta and maternal and cord blood. Am J Obstet Gynecol. 1974;119(2):205–7.

    CAS  Article  Google Scholar

  10. Lubkowska A, Chlubek D, Machoy-Mokrzynska A, Nowacki P. Distribution of fluoride in selected structures of the central nervous system in rats exposed to NaF and AlCl3 in drinking water. Trace Elem and Electroly. 2012;29(3):162–71.

    CAS  Google Scholar

  11. Grandjean P, Landrigan PJ. Neurobehavioural effects of developmental toxicity. Lancet Neurol. 2014;13(3):330–8.

    CAS  Article  Google Scholar

  12. Green R, Lanphear B, Hornung R, Flora D, Martinez-Mier EA, Neufeld R, et al. Association between maternal fluoride exposure during pregnancy and IQ scores in offspring in Canada. JAMA Pediatr. 2019;173(10):940–8.

    Article  Google Scholar

  13. Kundu H, Basavaraj P, Singla A, Gupta R, Singh K, Jain S. Effect of fluoride in drinking water on children’s intelligence in high and low fluoride areas of Delhi. J Indian Assoc Public Health Dent. 2015;13(2):116–21.

    Article  Google Scholar

  14. Bashash M, Thomas D, Hu H, Martinez-Mier EA, Sanchez BN, Basu N, et al. Prenatal fluoride exposure and cognitive outcomes in children at 4 and 6-12 years of age in Mexico. Environ Health Perspect. 2017;125(9):097017.

    Article  Google Scholar

  15. Yu X, Chen J, Li Y, Liu H, Hou C, Zeng Q, et al. Threshold effects of moderately excessive fluoride exposure on children’s health: a potential association between dental fluorosis and loss of excellent intelligence. Environ Int. 2018;118:116–24.

    CAS  Article  Google Scholar

  16. Till C, Green R, Flora D, Hornung R, Martinez-Mier EA, Blazer M, et al. Fluoride exposure from infant formula and child IQ in a Canadian birth cohort. Environ Int. 2020;134:105315.

    CAS  Article  Google Scholar

  17. Broadbent JM, Thomson WM, Ramrakha S, Moffitt TE, Zeng J, Foster Page LA, et al. Community water fluoridation and intelligence: prospective study in New Zealand. Am J Public Health. 2015;105(1):72–6.

    Article  Google Scholar

  18. Sharma P, Bhardwaj AK, Singh M, Kumar D, Sharma A. A. G. Does fluorosis affect the intelligence profile of children? A cross sectional analysis of school children of district una, Himachal Pradesh, India. Int J Community Med Public Health. 2018;5(3):1047–53.

  19. Rückinger S, Rzehak P, Chen CM, Sausenthaler S, Koletzko S, Bauer CP, et al. Prenatal and postnatal tobacco exposure and behavioral problems in 10-year-old children: results from the GINI-plus prospective birth cohort study. Environ Health Perspect. 2010;118(1):150–4.

    Article  Google Scholar

  20. Wang A, Duan L, Huang H, Ma J, Zhang Y, Ma Q, et al. Association between fluoride exposure and behavioural outcomes of school-age children: a pilot study in China. Int J Environ Health Res. 2020. https://doi.org/10.1080/09603123.2020.1747601.

  21. Thomas DB, Basu N, Martinez-Mier EA, Sanchez BN, Zhang Z, Liu Y, et al. Urinary and plasma fluoride levels in pregnant women from Mexico City. Environ Res. 2016;150:489–95.

    CAS  Article  Google Scholar

  22. Liu H, Lam LT, Zeng Q, Han S, Fu G, Hou C. Effects of drinking water with high iodine concentration on the intelligence of children in Tianjin, China. J Public Health (Oxf). 2009;31(1):32–8.

  23. Ding Y, Gao Y, Sun H, Han H, Wang W, Ji X, et al. 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. 2011;186(2):1942–6.

  24. Malhotra A, Tewari A, Chawla HS, Gauba K, Dhall K. Placental transfer of fluoride in pregnant women consuming optimum fluoride in drinking water. J Indian Soc Pedod Prev Dent. 1993;11(1):1–3.

    CAS  Google Scholar

  25. Grandjean P. Developmental fluoride neurotoxicity: an updated review. Environ Health. 2019;18(1):110.

    Article  Google Scholar

  26. Karayagiz Muslu G, Coskun CS. The family burdens and hopelessness of Turkish parents of adolescents with intellectual disabilities. Rehabil Nurs. 2018;43(6):351–62.

    Google Scholar

  27. Irazabal M, Marsa F, Garcia M, Gutierrez-Recacha P, Martorell A, Salvador-Carulla L, et al. Family burden related to clinical and functional variables of people with intellectual disability with and without a mental disorder. Res Dev Disabil. 2012;33(3):796–803.

    CAS  Article  Google Scholar

  28. Wang M, Liu L, Li H, Li Y, Liu H, Hou C, et al. Thyroid function, intelligence, and low-moderate fluoride exposure among Chinese school-age children. Environ Int. 2020;134:105229.

    CAS  Article  Google Scholar

  29. Zhao Q, Tian Z, Zhou G, Niu Q, Chen J, Li P, et al. SIRT1-dependent mitochondrial biogenesis supports therapeutic effects of resveratrol against neurodevelopment damage by fluoride. Theranostics. 2020;10(11):4822–38.

    CAS  Article  Google Scholar

  30. Qian H, Li G, He Q, Zhang H, Xu A. Analysis of differentially expressed genes between fluoride-sensitive and fluoride-endurable individuals in midgut of silkworm, Bombyx mori. Gene. 2016;588(1):47–53.

    CAS  Article  Google Scholar

  31. Li G, Wang X, Weng X, Qian H. Glutathione S-transferase participates in the formation of fluoride tolerance in silkworm. Sci Sericult. 2018;44(01):85–93.

    Google Scholar

  32. Vandeputte M, Cock JD, Dryon L, Vercruysse A, Alexander F, Massart DL. A contribution to the study of fluoride excretion. Clin Chim Acta. 1977;75(2):205–12.

    CAS  Article  Google Scholar

  33. Rango T, Vengosh A, Jeuland M, Whitford GM, Tekle-Haimanot R. Biomarkers of chronic fluoride exposure in groundwater in a highly exposed population. Sci Total Environ. 2017;596–597:1–11.

    Article  Google Scholar

Download references

Acknowledgments

We are deeply grateful to members of Tongxu Center for Disease Prevention and Control for their support and the participants recruited in the study. We sincerely thank Dr. Francis Kojo Afrim for his great help in writing this manuscript.

Funding

This study was supported by the Natural Science Foundation of China (81972981, 81673116), Henan Department of Science and Technology, China (162300410272) and Zhengzhou University (2020ZZUKCSZ008). The sponsors were not involved in research design, information collection, data analysis, or paper writing.

Author information

Affiliations

Contributions

GZ and YB designed the research. HH, LD, JD, TH, JM, JZ, ZL and XC collected the data. KX and NA analyzed the data and drafted the manuscript. GZ and YB reviewed and edited the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Guoyu Zhou or Yue Ba.

Ethics declarations

Ethics approval and consent to participate

All procedures performed in this study involving human participants were approved by the Ethics Review Board at Zhengzhou University (ZZUIRB2017–018) in China. All the children and their legal guardians knew very well about the study procedures and signed the informed consent before recruitment.


*Original study online at https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-020-09765-4