ENVIRONMENTAL

HEALTH 

PERSPECTIVES

ENVIRONMENTAL

HEALTH 

PERSPECTIVES

National Institutes of Health

U.S. Department of Health and Human Services 

Serum Fluoride Level and Children’s 

Intelligence Quotient in Two Villages in China

Quanyong Xiang, Youxin Liang, 

Bingheng Chen, Liansheng Chen, Minghao Zhou, 

Ming Wu, and Mingsheng Zhou

doi: 10.1289/ehp.1003171 (available at http://dx.doi.org/)

Online 17 December 2010

ehponline.org

ehp
1

Serum Fluoride Level and Children’s Intelligence Quotient in Two Villages in 

China 

Quanyong Xiang,1 Youxin Liang,2 Bingheng Chen,2 Liansheng Chen,1 Minghao Zhou,1

Ming Wu1, Mingsheng Zhou3 

1

 Department of Environmental Health, Jiangsu Province Center for Diseases Control 

and Prevention, Nanjing, China; 

2

 Department of Occupational and Environmental Health, School of Public Health, 

Fudan University (formerly Shanghai Medical University), Shanghai, China; 

3

 Sihong County Center for Diseases Control and Prevention, Sihong County, Jiangsu 

Province, China 

For correspondence: 

Quanyong Xiang, Department of Environmental Health, Jiangsu Province Center for 

Diseases Control and Prevention. 172 Jiangsu Road, Nanjing, Jiangsu Province, 

210009, P.R. China. 

Tel: 86-25-83759414 Fax: 86-25-83759411 

E-mail: quanyongxiang@yahoo.com.cn 

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Article running title: Fluoride and Intelligence Quotient 

Keywords: Children; Fluoride; Intelligence quotient 

Acknowledgements: This work was supported by Jiangsu Province Association for 

Endemic Disease Control and Prevention (X200327). We thank Xipen Jin (School of 

Public Health, Fudan Univesity), Zumin Shi (Jiangsu Province Center for Diseases 

Control and Prevention) and Mingfang Zhang (Sihong County Center for Disease 

Control and Prevention) for their valuable suggestions. The authors declare that they 

have no competing financial interests. 

Abbreviation: 

CI Confidence Interval 

CRT-RC Combined Raven’s Test for Rural China 

IQ Intelligence Quotient 

 NCTB Neurobehavioral Core Test Battery 

OR Odds Ratios 

 SD Standard Deviation 

 WPPSI Wechsler Preschool and Primary Scale of Intelligence 

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Abstract 

Background: Animal studies show that brain fluoride levels increase with increasing 

exposure to fluoride. Human studies have indicated an association between high levels 

of drinking-water fluoride and lower intelligence. Data on the association between 

serum fluoride and children’s intelligence quotient (IQ) are limited.

Objective: This study was conducted to assess the relationship between serum fluoride 

and children’s IQ. 

Methods: We collected blood samples from 512 children aged 8-13 years from two

villages (Wamiao and Xinhuai) in China. We also used minitype fluoride ion selective 

electrode and Combined Raven’s Test for Rural China (CRT-RC) to measure serum 

fluoride and children’s IQ. 

Results: In Wamiao, the mean (± SD) serum fluoride concentration was 0.081± 0.019 

mg/L, and average children’s IQ was 92.02 ± 13.00; in Xinhuai, the mean serum 

fluoride concentration was 0.041 ± 0.009 mg/L and average IQ was 100.41 ± 13.21. 

There was a significant inverse association between serum fluoride concentration and 

IQ scores among children in Wamiao (regression coefficient for a 1-unit change in 

serum fluoride = –112.61, p = 0.015), the association was not significant in Xinhuai 

(regression coefficient = 78.85, p = 0.362). Serum fluoride levels were negatively 

associated with IQ after adjustment for age and sex [odds ratios and 95% confidence 

intervals for IQ < 80 of 2.22 (1.42-3.47) and 2.48 (1.85-3.32) for serum fluoride 

concentrations of 0.05–0.08 and > 0.08 mg/L compared with < 0.05 mg/L, respectively, 

p for trend < 0.001]. IQ was not related to family income or parent’s education level. 

There was a significant positive relation between serum fluoride and drinking-water 

fluoride. 

Conclusions: The results indicated that fluoride in drinking water was highly 

correlated with serum fluoride, and that higher fluoride exposure may affect 

intelligence among children. 

 

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Introduction 

In 1937, Kaj Roholm published his classic study on 68 cryolite workers chronically 

exposed to fluoride, 84% of whom had skeletal fluorosis. Twenty-two percent of these 

cases had neurologic symptoms such as excessive tiredness, sleepiness, headache, and 

giddiness (Roholm 1937). In 1961, Singh and Jolly reported that 10% of patients who 

had skeletal fluorosis also had nervous system damage (Singh and Jolly 1961). 

Autopsies of patients with skeletal fluorosis indicated nuclear vacuoles; reduction of 

cells in the anterior horn of the spinal cord, the medical posterior funiculus, and the 

lateral horns; as well as reduction and partial clotting of the Nissl bodies which are 

located near the cell membrane. These results suggested that the damage was directly 

caused by the effects of fluoride on the nervous system (Franke 1976; Franke et al. 

1975). 

There have been a number of studies in humans on the relationship between 

cognitive function and fluoride in drinking water (Fan et al. 1991; Guo et al. 1991; He 

et al. 1989; Li et al. 1994; Li et al. 1995; Lu et al. 2000; Qin and Cui 1990; Ren et al. 

1989; Zhao et al. 1996, Xiang et al. 2003 ). Studies by Zhao (Zhao et al. 1996), Lu (Lu 

et al. 2000), and Xiang (Xiang et al. 2003) have indicated an association between higher 

levels of drinking-water fluoride and a lower intelligence quotient (IQ) in children, but 

other studies (WHO 2002) did not find such an association. 

Serum fluoride concentration has been recognized as a reliable indicator of fluoride 

exposure and is also used as one of the biomarkers to assess the effect of endemic 

fluorosis control and prevention (Lund et al. 1997; WHO 1996; National Standard of

P.R. China 2001; Wan et al. 2000). The literature, however, contains a wide range 

(0.4–2.4 μmol/L or 0.018–0.101 mg/L) of measures defining “normal” plasma fluoride 

concentration. The differences in these results may have been attributable to the testing 

of fasting individuals in some studies and nonfasting in others (WHO 2002). Currently, 

there is no cut-off point of serum fluoride which is considered acceptable by WHO or 

other academic organizations. 

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The relationship between serum fluoride and children’s IQ has not been reported. 

The objective of the present study was to describe the association between levels of 

fluoride in serum and in drinking water and children’s IQ. 

Materials and Methods 

Selection of study areas 

Two villages, Wamiao (a severe endemic fluorosis area) and Xinhuai (a non endemic 

fluorosis area) in Jiangsu Province, People’s Republic of China, were selected for this 

study 

Study subjects 

The study was conducted between September 2002 and June 2003 and included 

children 8–13 years of age who attended village primary schools in Wamiao and 

Xinhuai (from grade 2 to grade 6, at an age when dental fluorosis in permanent teeth 

can be diagnosed clearly) (Xiang et al. 2004). A questionnaire, completed with the 

assistance of parents, provided information on personal characteristics, medical history 

including illnesses affecting the nervous system and head trauma, educational level of 

the children and parents, family socioeconomic status, and lifestyle. There were a total 

of 238 and 305 students in grade 2 through 6 in Wamiao and Xinhuai, respectively. 

After excluding children who had been absent from either village for ≥ 2 years or who 

had a history of brain disease or head injury, 222 children (93%) were enrolled from 

Wamiao and 290 (95%) were enrolled from Xinhuai (Table 1). 

Before the investigation, written informed consent was obtained from the children’s 

parents. The study was approved by Jiangsu Provincial Center for Disease Control and 

Prevention, and School of Public Health, Fudan University. 

Higher levels of lead and iodine deficiency are significant causes of mental 

impairment (Burgstahler 2003; National standard of P.R. China 1995; Carpenter 2005; 

Chen et al. 2005). To identify whether the blood lead and urinary iodine had significant 

relationship with children’s IQ or not in these two villages, children were randomly 

selected used random function in Excel 2000 (Microsoft Corporation, Redmond, USA) 

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for urine iodine (46 in Wamiao, 40 in Xinhuai) and blood lead (71 in Wamiao, 67 in

Xinhuai) measurements. 

Sampling and testing 

The drinking-water samples collected from the shallow wells of each child’s 

household were kept in clean plastic bottles and analyzed within 1 week. A fasting 

venous blood sample (2–2.5 mL) was obtained from each child and preserved in a clean 

plastic centrifuge tube, which was immediately centrifuged by 3,000 r/min for 10 min. 

The serum was removed to another clean plastic tube and kept in a refrigerator (–40ê), 

and was subsequently analyzed within 1 week. Fluoride in drinking water and serum 

was measured with a fluoride ion selective electrode (National Standard of P.R. China 

1999; National Standard of P.R. China 2001). Urine samples were collected in the early 

morning before breakfast during 6:00-8:00 AM and kept in clean plastic bottles. Iodine 

in urine was measured with a commercially available Rapid Test Kit, manufactured by 

Hubei Province Center for Diseases Control and Prevention (Wuhan, China). The blood 

samples (80 μl) were collected via index finger prick and preserved in clean plastic 

centrifuge tubes which included 0.64 mL Triton X-100, manufactured by Amresco Inc. 

Solon, Ohio, USA. The blood lead was measured by atomic absorption 

spectrophotometer (National Standard of China 1996). 

IQ measures 

We used the Combined Raven’s Test for Rural China (CRT-RC) which was published 

by East China Normal University (1989) to measure the IQ of each child (Li and Chen 

1989). CRT-RC was based on the Combined Raven’s Test (CRT), and revised by East 

China Normal University from 1986 to 1987. In the CRT-RC validation study by East 

China Normal University, 4,212 children 5-14 years of age from 12 provinces in China 

were selected from villages using stratified random sampling (Li and Chen 1989; Wang 

et al. 1989). The test included items with different difficulty index to evaluate sample 

standardization, reliability, and validity. The results of reliability indicated that the 

correlation coefficient was 0.92 (Li and Chen 1989; Wang et al. 1989). 

In the present study, we tested the children’s IQ in the school classroom. The children 

finished the test independently within 40 min under the supervision of an examiner and 

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two assistants according to the guidelines of the CRT-RC manual for the test 

administration conditions, instructions, and the test environment (Li and Chen 1989). 

The examiner (trained by East China Normal University) and assistants were blinded to 

the levels of fluoride in each child’s serum and the household shallow well when they 

conducted the IQ test. A normal model in the instruction manual of CRT-RC divides the 

IQ into seven categories according to the IQ scores: mental retardation (IQ < 70), 

borderline (IQ 70–79), dull normal (IQ 80–89), normal (IQ 90–109), bright normal (IQ 

110–119), superior (IQ 120–129), and very superior (IQ > 129). The IQ was a scaled 

score that was adjusted by age in the normal model. 

Statistical analysis 

The 512 subjects were classified into quartiles according to level of serum fluoride. 

We used the chi-square test to compare differences in categorical variables, and 

analysis of variance to compare differences in continuous variables among groups. We 

analyzed the association between serum fluoride levels and the risk of low IQ using 

logistic regression models, adjusting for age and sex. In the logistic regression, first and 

second quartiles of serum fluoride were combined and used as reference group. Tests of 

linear trend across levels of serum fluoride were computed using ordinal scoring. 

Values were considered significant when p < 0.05 (two sided). The analyses were 

performed using STATA software (version 9; StataCorp, College Station, TX, USA) 

and SAS software (version 8.2; SAS Institute Inc., Cary, NC, USA).

Results 

Wamiao and Xinhuai are located 64 km apart in Sihong County. Wamiao village, in 

northeast Sihong County, about 32 km northeast of Sihong, is a severe endemic 

fluorosis area. The mean fluoride level in Wamaio drinking water was 2.47 ± 0.79 mg/L 

(range 0.57–4.50 mg/L), and the prevalence of dental fluorosis and defected dental 

fluorosis was 88.56% and 38.98%, respectively. Xinhuai village, in the southwest part 

of Sihong county, about 32 km southwest of Sihong, is a non endemic fluorosis area. 

The mean level of fluoride in Xinhuai drinking water was 0.36±0.15 mg/L (range 

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0.18-0.76 mg/L), and the prevalence of dental fluorosis was 4.48%, with no cases of 

defected dental fluorosis identified (Xiang et al. 2004, National Standard of P.R. China 

1997). Neither village has fluoride pollution from burning coal or other industrial 

sources, and the residents do not drink brick tea, which has been known to cause 

fluorosis (Sun and Liu 2005; Wang et al. 1997; Zhao et al. 2000). 

Wamiao and Xinhuai village are of comparable size (total populations of 3,097 and 

3,208, respectively in 2002) and are both characterized by low economic development 

(the average family income was 1500–2000 Yuan/year/person), limited education 

(average education level of elementary school) and lack of communication with the 

outside world. 

The mean age of the 222 children in Wamiao was significantly higher than the mean 

age of the 290 children in Xinhuai (11.56 ± 1.68 and 10.75 ± 1.76 years, respectively, 

p<0.01) (Table 1). IQ scores, urine iodine concentrations, and blood lead levels were 

normally distributed, but drinking-water fluoride (Kolmogorov-Smirnov Z=6.095, p

<0.01) and serum fluoride (Kolmogorov-Smirnov Z = 3.965, p<0.01) concentrations 

were not. 

 Drinking-water fluoride (2.47±0.79 versus 0.36±0.11 mg/L) and serum fluoride 

(0.081±0.019 versus 0.041±0.009 mg/L) were significantly higher in Wamiao than 

Xinhuai, but urine iodine and blood lead levels were comparable between children from 

the two villages (Table 2). 

There were significant differences between the two villages in IQ scores among 

males (p<0.002), and females (p<0.001) (Figure 1). There was also significant 

difference within Wamiao between male and female children’s IQ scores (p<0.001) 

(Figure 1), but not in Xinhuai (p=0.664). Most children’s IQs were distributed within 

the normal range of 90-109 (47.30% in Wamiao, 51.72% in Xinhuai). In Xinhuai, 

27.59% of the children had a CRT-RC IQ score indicating bright normal or higher 

intelligence (≥ 110), whereas only 8.11% of Wamiao children had IQ within this range. 

In fact, in Wamiao, 15.31% of children had a CRT-RC IQ score indicating mental 

retardation (<70) and borderline (70-79), whereas only 6.20% in Xinhuai village had IQ 

in this range. The k-density distribution of IQ scores shows a shift in the distribution 

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indicating higher IQ scores among children in Xinhuai compared with Wamiao (Figure 

2). 

Linear regression models indicated a significant inverse association between serum 

fluoride concentration and IQ scores among children in Wamiao (regression coefficient 

for a 1-unit change in serum fluoride = –112.61[95% confidence interval (CI) from 

-203.15 to -22.06, r

2

=0.0266, p=0.015] (Figure 3). In contrast, the association was not 

significant among children in Xinhuai (regression coefficient = 79.85, 95% CI from 

-92.15 to 251.84, r

2

=0.0029, p=0.362). Further adjustment for age and sex increased the 

r

2 to 0.088 and 0.034 in Wamiao and Xinhuai, respectively. The regression coefficient 

were: -104.70 (95% CI from -192.41 to -16.98) in Wamiao; 59.82 (95% CI from 

-110.68 to 230.32) in Xinhuai. 

When the data from 512 children from the two villages were combined, serum 

fluoride levels were negatively associated with IQ. The proportion of children with IQ 

scores <80 increased with increasing quartiles of serum fluoride. Adjusted odds ratios 

(OR) for IQ score <80 versus ≥ 80 were 2.22 (95% CI, 1.42–3.47) and 2.48 (95% CI, 

1.85–3.32) for serum fluoride levels of 0.05-0.08 and >0.08 mg/L compared with <0.05 

mg/L, respectively (p for trend < 0.001) (Table 3). Using likelihood ratio test, we found 

no significant interaction between village and serum fluoride level (p= 0.092). 

There was a significant positive relation between fluoride in drinking water and 

fluoride in serum of children 8–13 years of age (Spearman correlation coefficient = 

0.811, p < 0.001, r

2

 = 0.741) (Figure 4). 

Linear regression showed no significant associations between urinary iodine and IQ 

(β=0.011, p=0.942 in Wamiao; β=-0.006, p=0.971 in Xinhuai,) or between blood lead 

levels and IQ (β=-0.160, p=0.181 and β=-0.092, p=0.460, respectively). Similar results 

were obtained when data for both villages were combined (β=0.036, p=0.785 for 

urinary iodine and β=-0.142, p=0.096 for blood lead). 

Discussion 

As previously noted (Xiang et al. 2003), the average IQ of the children in Xinhuai 

was higher than that in Wamiao. The absence of significant associations between IQ 

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and family income or father’s education level in either village (Xiang et al. 2003) May 

be explained by the parents’ low educational level and family income in both villages. 

However, these results are not consistent with those of another study conducted in 

China (Zhao et al. 1996), which reported significant associations between children’s IQ 

scores and their parents’ educational level (the total children were 320 from 7 to 14 

years old in the study of Zhao et al.). 

The results of this cross-sectional study when the data of two villages were combined 

indicated that serum fluoride level was associated with IQ scores. As the fluoride level 

in children’s serum increased, the children’s IQs fell and the rates of borderline or lower 

intelligence increased. 

In this study we found a significant dose–response relation between fluoride level in 

serum and children’s IQ. Fluoride is able to cross the blood–brain barrier, producing 

biochemical and functional impairment of the nervous system during developmental 

periods of infancy and childhood (Guan et al. 1998; He et al. 1989; Mullenix et al. 1995; 

Zhang et al. 2000). The findings of Guan et al. and those of other studies suggest that 

higher fluoride intake during the prenatal period can cause nervous system damage in 

the fetus (Cui and Wang 2001; Guan et al. 1986; He et al. 1989; WHO 1996). The 

results of a study of 4- to 7-year old children by Wang et al. (1996) indicated that the 

higher fluoride intake was mainly associated with Performance IQ rather than Verbal 

IQ scores from the WPPSI (Wechsler Preschool and Primary Scale of Intelligence). 

Guo et al. (2001) suggested that occupational exposure to fluoride affected not only 

cognitive function but also motor function; NCTB (Neurobehavioral Core Test Battery) 

scores were significantly lower in the exposed group compared with the control group, 

except for scores on the Benton Visual Retention Test. The CRT-RC is a test of 

observational ability and logical thinking rather than verbal IQ (Li and Chen 1989; 

Zhang et al. 2007). Therefore our findings suggest an effect of serum fluoride on 

performance IQ, consistent with Wang et al. and Guo et al. (Wang et al. 1996; Guo et al. 

2001), but do not provide information regarding effects on verbal IQ. 

 We found no significant difference between the two villages in urine iodine levels, 

and did not find associations between urine iodine and IQ. In addition, neither village 

Page 10 of 22
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has been identified as being in an area of endemic iodine deficiency (National standard 

of P.R. China 1995). Thus, differences in urinary iodine levels do not appear to explain 

the differences in IQ between the two villages in this study. 

Prenatal and postnatal exposure to lead is now well recognized as an important cause 

of mental impairment (Burgstahler 2003; Carpenter 2005; Chen et al. 2005). We 

measured 138 blood samples for blood lead and found no significant difference 

between the two villages in blood lead levels, and no association between blood lead 

and IQ in study participants. This result could be explained by the low level of blood 

lead in our study population compared with other studies (Ai et al. 2006; Jusko et al. 

2008). 

In our previous study (Xiang et al. 2003), we found a significant dose–response 

relation between fluoride in drinking water and children’s IQ in both Wamiao and 

Xinhuai. In the present study we found a positive dose–response relation between the 

level of fluoride in drinking water and the level of fluoride in serum of children 

(r

2

=0.741), which suggests that fluoride in drinking water is the main source of fluoride 

intake in Wamiao and Xinhuai village. 

In conclusion, we found an inverse association between serum fluoride level and IQ 

among children in an area containing a high level of fluoride in the water. Further 

research should be done in more varied (e.g., urban and village) population to 

determine if the relationship between IQ and fluoride is independent of family income 

and parent’s level of education. In addition, the results of our cross-sectional study 

should be confirmed in a larger study population with a longitudinal study design. 

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Table 1 Sample characteristics in Wamiao and Xinhuai Village*

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Characteristics Wamiao Xinhuai p 

Age (years) (mean, SD) 11.56± 1.68(222) 10.75 ± 1.76(290) <0.010‡

Boys (%) 55.41(123/222) 54.83(159/290) 0.896†

Age (years) (mean, SD) 11.50±1.51 10.81±1.61 <0.010‡

Girls (%) 44.59(99/222) 45.17(131/290) 0.896†

Age (years) (mean, SD) 11.63±1.47 10.68±1.78 <0.010‡

Family income (RMB/year/ person) (%) 

 Very Low (<1000) 18.92(42/222) 13.79(40/290) 0.117†

Low (1001-2000) 57.65(128/222) 56.66(173/290) 0.649†

 Medium (2001-3000) 17.57(39/222) 20.34(59/290) 0.429†

 High (>3000) 5.86(13/222) 6.21(18/290) 0.869†

Education of father (%) 

 Primary and below 33.33(74/222) 41.73(121/290) 0.053†

 Junior 53.16(118/222) 45.17(131/290) 0.073†

 High school and above 13.51(30/222) 13.10(38/290) 0.892†

Having medical history (%)** 1.26(3/238) 0.98(3/305) 0.759†

Absent from village for ≥ 2 years(%) 5.46(13/238) 4.14(12/305) 0.399†

* Data collected in Oct. 2002. 

** History of head trauma or illnesses affecting the nervous system 

† Chi square Test 

‡ Independent–samples T Test 

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Table 2 Fluoride in drinking water and serum, iodine in urine, and lead in serum in two villages’ 

children (Mean±SD)* 

 Drinking water Fluoride Serum Fluoride Urine iodine Blood lead 

Village —————————— —————————— ————————— —————————

 Samples mg/L Samples mg/L Samples μg/L Samples μg/L 

Wamiao 222 2.47±0.79 222 0.081±0.019 46 280.70±87.16 71 21.95±13.65 

Xinhuai 290 0.36±0.11 290 0.041±0.009 40 300.96±92.88 67 23.61±14.17 

p <0.001† <0.001† 0.447‡ 0.487‡

*

 Compared with Wamiao village.

† Mann-Whitney Test

‡ Independent–samples T Test

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Table 3 Association between serum fluoride and children’s IQ a

 N Mean IQ SD IQ p b IQ<80 (%) p

 c

 

OR(95%CI) for 

IQ<80 

Serum fluoride levels 

(quartiles) 

Q1/Q2(<0.05 mg/L) 259 100.1 13.4 7.0 1 

Q3(0.05-0.08 mg/L) 126 95.9 13.7 <0.001 15.1 0.004 2.22(1.42-3.47)

Q4(>0.08 mg/L) 127 92.1 13.4 17.3 2.48(1.85-3.32)

 P trend<0.001 d

a

 Adjusted for age and gender using Logistic regression analysis. The data from two villages were 

combined. 

b

 ANOVA 

c

 Chi square Test 

d

 Tests of linear trend were computed using ordinal scoring. 

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18

Figure Legends 

Figure 1 Boxplot of children’s IQ in Wamiao and Xinhuai village by genders. p values

were for comparing IQs between villages within the same gender using T-test. The dots 

in the female parts of the graph indicated that there are two females’ IQ lower than 

mean-3SD in Xinhuai, and one in Wamiao.

Figure 2 Kdensity distribution of children’s IQ in Wamiao and Xinhuai village. 

Figure 3 Association between serum fluoride and children’s IQ in Wamiao and 

Xinhuai.

Figure 4 Association between the drinking water fluoride and serum fluoride.

Page 18 of 22
p=0.002 p<0.001

60 80 100 120 140

IQ

Male Female

Xinhuai Wamiao Xinhuai Wamiao

Figure 1 Boxplot of children’s IQ in Wamiao and Xinhuai village by genders. p values were for 

comparing IQs between villages within the same gender using T-test. The dots in the female parts of the 

graph indicated that there are two females’ IQ lower than mean-3SD in Xinhuai, and one in Wamiao. 

Page 19 of 22
0 .01 .02 .03

Kdensity

60 80 100 120 140

IQ

Xinhuai W amiao

Figure 2 Kdensity distribution of children’s IQ in Wamiao and Xinhuai village 

Page 20 of 22
r=0.054 p=0.362 r=-0.163 p=0.015

60 80 100 120 140

0 .05 .1 .15 0 .05 .1 .15

Xinhuai Wamiao

IQ Fitted values

Serum Fluoride

Figure 3 Association between serum fluoride and children’s IQ in Wamiao and Xinhuai 

Page 21 of 22
Figure 4 Association between the drinking water fluoride and serum fluoride 

Page 22 of 22