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Fluoride Exposure and Children’s IQ Scores: A Systematic Review and Meta-Analysis.
Abstract
Key Points
Question Is fluoride exposure associated with children’s IQ scores?
Findings Despite differences in exposure and outcome measures and risk of bias across studies, and when using group-level and individual-level exposure estimates, this systematic review and meta-analysis of 74 cross-sectional and prospective cohort studies found significant inverse associations between fluoride exposure and children’s IQ scores. For fluoride measured in water, associations remained inverse when exposed groups were restricted to less than 4 mg/L or less than 2 mg/L but not when restricted to less than 1.5 mg/L; for fluoride measured in urine, associations remained inverse at less than 4 mg/L, less than 2 mg/L, and less than 1.5 mg/L; and among the subset of low risk-of-bias studies, there were inverse associations when exposed groups were restricted to less than 4 mg/L, less than 2 mg/L, and less than 1.5 mg/L for analyses of fluoride measured both in water and in urine.
Meaning This comprehensive meta-analysis may inform future risk-benefit assessments of the use of fluoride in children’s oral health.
Importance Previous meta-analyses suggest that fluoride exposure is adversely associated with children’s IQ scores. An individual’s total fluoride exposure comes primarily from fluoride in drinking water, food, and beverages.
Objective To perform a systematic review and meta-analysis of epidemiological studies investigating children’s IQ scores and prenatal or postnatal fluoride exposure.
Data Sources BIOSIS, Embase, PsycInfo, PubMed, Scopus, Web of Science, CNKI, and Wanfang, searched through October 2023.
Study Selection Studies reporting children’s IQ scores, fluoride exposure, and effect sizes.
Data Extraction and Synthesis Data were extracted into the Health Assessment Workplace Collaborative system. Study quality was evaluated using the OHAT risk-of-bias tool. Pooled standardized mean differences (SMDs) and regression coefficients were estimated with random-effects models.
Main Outcomes and Measures Children’s IQ scores.
Results Of 74 studies included (64 cross-sectional and 10 cohort studies), most were conducted in China (n=45); other locations included Canada (n=3), Denmark (n=1), India (n=12), Iran (n=4), Mexico (n=4), New Zealand (n=1), Pakistan (n=2), Spain (n=1), and Taiwan (n=1). Fifty-two studies were rated high risk of bias and 22 were rated low risk of bias. Sixty-four studies reported inverse associations between fluoride exposure measures and children’s IQ. Analysis of 59 studies with group-level measures of fluoride in drinking water, dental fluorosis, or other measures of fluoride exposure (47 high risk of bias, 12 low risk of bias; n =20932 children) showed an inverse association between fluoride exposure and IQ (pooled SMD, -0.45; 95% CI, -0.57 to -0.33; P<.001). In 31 studies reporting fluoride measured in drinking water, a dose-response association was found between exposed and reference groups (SMD, -0.15; 95% CI, -0.20 to -0.11; P<.001), and associations remained inverse when exposed groups were restricted to less than 4 mg/L and less than 2 mg/L; however, the association was null at less than 1.5 mg/L. In analyses restricted to low risk-of-bias studies, the association remained inverse when exposure was restricted to less than 4 mg/L, less than 2 mg/L, and less than 1.5 mg/L fluoride in drinking water. In 20 studies reporting fluoride measured in urine, there was an inverse dose-response association (SMD, -0.15; 95% CI, -0.23 to -0.07; P<.001). Associations remained inverse when exposed groups were restricted to less than 4 mg/L, less than 2 mg/L, and less than 1.5 mg/L fluoride in urine; the associations held in analyses restricted to the low risk-of-bias studies. Analysis of 13 studies with individual-level measures found an IQ score decrease of 1.63 points (95% CI, -2.33 to -0.93; P<.001) per 1-mg/L increase in urinary fluoride. Among low risk-of-bias studies, there was an IQ score decrease of 1.14 points (95% CI, –1.68 to –0.61; P<.001). Associations remained inverse when stratified by risk of bias, sex, age, outcome assessment type, country, exposure timing, and exposure matrix.
Conclusions and Relevance This systematic review and meta-analysis found inverse associations and a dose-response association between fluoride measurements in urine and drinking water and children’s IQ across the large multicountry epidemiological literature. There were limited data and uncertainty in the dose-response association between fluoride exposure and children’s IQ when fluoride exposure was estimated by drinking water alone at concentrations less than 1.5 mg/L. These findings may inform future comprehensive public health risk-benefit assessments of fluoride exposures.
… To incorporate newer evidence and increase transparency, objectivity, and rigor in the analysis of fluoride research, we conducted a systematic review and meta-analysis of studies that provided estimates of group-level and individual-level fluoride exposure in relation to children’s IQ scores.
Quality of individual studies, also called risk of bias, was independently evaluated by 2 trained assessors following criteria prespecified in the protocol,13 using the National Toxicology Program’s or Division of Translational Toxicology’s OHAT approach.14 Risk-of-bias questions concerning confounding, exposure characterization, and outcome assessment were considered key. If not addressed appropriately, these questions were thought to have the greatest potential impact on the results.13 The remaining risk-of-bias questions were used to identify other concerns that may indicate serious risk-of-bias issues (eg, selection bias, inappropriate statistical analysis). No study was excluded from the meta-analysis based on concerns for risk of bias; however, subgroup analyses were conducted with and without high risk-of-bias studies (ie, studies rated probably high risk of bias for >2 key risk-of-bias questions or definitely high risk of bias for any single question) to assess their potential impact, in terms of magnitude and direction of bias, on the results. Ratings and justification are available in HAWC (https://hawcproject.org/assessment/405/).
… Results
A total of 74 publications (64 cross-sectional studies and 10 prospective cohort studies) met the inclusion criteria, with 65 included in the primary analyses and an additional 9 included in sensitivity analyses (eFigure 1B in Supplement 1; see eTable 2 in Supplement 1 for excluded publications). Characteristics of the 74 publications and the study-specific effect estimates used in the meta-analyses are shown in eTable 1 in Supplement 1. Most studies were conducted in China (n=45); other locations included Canada (n=3), Denmark (n=1), India (n=12), Iran (n=4), Mexico (n=4), New Zealand (n=1), Pakistan (n=2), Spain (n=1), and Taiwan (n=1). No studies were conducted in the United States. Of these, 59 publications reported mean IQ scores for group-level exposures10,11,32–95 and 19 reported regression slopes for individual-level exposures based on urinary or water fluoride concentrations and fluoride intake.9–11,32–38,96–104 Additional details on study characteristics are provided in the “Results” section of eAppendix 1 in Supplement 1. Sixty-four studies reported inverse associations between fluoride exposure measures and children’s IQ. Fifty-two studies were rated high risk of bias. Twenty-two studies were rated low risk of bias, with 13 rated low risk of bias across all 7 risk-of-bias domains and 9 rated low risk of bias in 6 domains and probably high risk of bias in no more than 1 domain. Results from risk-of-bias evaluations are presented in eFigure 2 in Supplement 1. Interactive versions of the figures and risk-of-bias evaluations are available in HAWC (links provided in the “Results” section of eAppendix 1 in Supplement 1). Further details and justification about low risk-of-bias studies are presented in eAppendix 2 in Supplement 1.
A total of 74 publications (64 cross-sectional studies and 10 prospective cohort studies) met the inclusion criteria, with 65 included in the primary analyses and an additional 9 included in sensitivity analyses (eFigure 1B in Supplement 1; see eTable 2 in Supplement 1 for excluded publications). Characteristics of the 74 publications and the study-specific effect estimates used in the meta-analyses are shown in eTable 1 in Supplement 1. Most studies were conducted in China (n=45); other locations included Canada (n=3), Denmark (n=1), India (n=12), Iran (n=4), Mexico (n=4), New Zealand (n=1), Pakistan (n=2), Spain (n=1), and Taiwan (n=1). No studies were conducted in the United States. Of these, 59 publications reported mean IQ scores for group-level exposures10,11,32–95 and 19 reported regression slopes for individual-level exposures based on urinary or water fluoride concentrations and fluoride intake.9–11,32–38,96–104 Additional details on study characteristics are provided in the “Results” section of eAppendix 1 in Supplement 1. Sixty-four studies reported inverse associations between fluoride exposure measures and children’s IQ. Fifty-two studies were rated high risk of bias. Twenty-two studies were rated low risk of bias, with 13 rated low risk of bias across all 7 risk-of-bias domains and 9 rated low risk of bias in 6 domains and probably high risk of bias in no more than 1 domain. Results from risk-of-bias evaluations are presented in eFigure 2 in Supplement 1. Interactive versions of the figures and risk-of-bias evaluations are available in HAWC (links provided in the “Results” section of eAppendix 1 in Supplement 1). Further details and justification about low risk-of-bias studies are presented in eAppendix 2 in Supplement 1.
This systematic review and meta-analysis found statistically significant inverse associations between measures of fluoride exposure and children’s IQ. These inverse associations were observed in all 3 sets of meta-analyses: the mean-effects meta-analysis (47 high risk-of-bias studies, 12 low risk-of-bias studies) and dose-response mean-effects meta-analysis (27 high risk-of-bias studies, 11 low risk-of-bias studies) of group-level fluoride exposure, and the regression slopes meta-analysis (2 high risk-of-bias studies, 11 low risk-of-bias studies) of individual-level urinary fluoride. Within each of these meta-analyses, we used prespecified criteria to assess study quality and classify studies into low and high risk of bias. Stratified analyses found similar inverse associations in both study quality strata. Further subgroup analyses by sex, age, timing of exposure, study location, outcome assessment type, and exposure assessment matrix also found inverse associations between fluoride exposure and children’s IQ.
Studies in these meta-analyses included cross-sectional and prospective cohort designs, each study having its own strengths and limitations. Although all studies contribute to our understanding of the overall association, well-designed studies that accurately measure exposure and outcome and adequately account for potential confounding variables are particularly informative. In these meta-analyses, we followed the OHAT approach14 to extract data from each of the published studies and to classify studies into high risk of bias and low risk of bias based on carefully predefined criteria.13 To make our process and decisions transparent, we provide full public access to the extracted data, risk-of-bias ratings, and rationale for those ratings for each individual study. These data can be used by other investigators to evaluate or extend our process and analysis (https://hawcproject.org/assessment/405/).
Studies using group-level exposures were assessed in the mean-effects meta-analysis. An advantage of such studies is that they can, for example, examine communities with different CWS fluoride levels. Although in the United States 40% to 70% of a person’s fluoride intake comes from fluoridated drinking water, there are other sources of fluoride exposure.4 Therefore, relying on CWS levels alone may underestimate an individual’s total fluoride exposure, which may vary considerably among members of a group depending on individual behaviors. Most of the studies in the mean-effects meta-analysis were cross-sectional; however, we have higher confidence in cross-sectional studies when there is evidence of temporality.14 Among the low risk-of-bias cross-sectional studies, most provided information to establish that exposure likely preceded the outcome (eg, only including children who had lived in a community since birth or children who had dental fluorosis).
Studies using individual-level exposures were assessed in the regression slopes meta-analysis, which included 13 studies with urinary fluoride measures, a more precise exposure assessment measure than group-level exposures. Unlike drinking water levels, individual-level urinary fluoride concentrations include all ingested fluoride and are considered a valid estimate of total fluoride exposure.106,107 Fluoride in urine is measured from both single or spot samples and multiple collections. When compared with 24-hour urine samples, spot samples are more prone to the influence of timing of exposure and can be affected by differences in dilution. However, correlations between urinary fluoride concentrations from 24-hour samples and spot samples adjusted for urinary dilution have been described.108 There were several recent North American prospective cohort studies conducted in Canada and Mexico32,96,97,101 that reported maternal urinary fluoride levels comparable to those in the United States.109,110 These studies combined multiple urinary measurements over the course of pregnancy to examine prenatal fluoride exposure during a critical period of brain development. Although the estimated decreases in IQ found in the regression slopes meta-analysis may seem small (1.63 IQ points per 1-mg/L increase in urinary fluoride), research on other neurotoxicants has shown that subtle shifts in IQ at the population level can affect people who fall within the high and low ranges of the population’s IQ distribution.111–115 For context, a 5-point decrease in a population’s IQ would nearly double the number of people classified as intellectually disabled.116
Finally, studies with group-level exposure measurements were used in the dose-response mean-effects meta-analysis of water or urinary fluoride levels. Although we examined 2 nonlinear models, a linear model almost always provided the best fit for both water and urinary data. There was a statistically significant dose-response association between group-level fluoride measures and children’s IQ. In stratified analyses of low risk-of-bias studies, the association remained inverse when exposure was restricted to less than 4 mg/L, less than 2 mg/L, and less than 1.5 mg/L fluoride in water or urine; except for fluoride concentrations less than 1.5 mg/L in water, these results were statistically significant. There was some inconsistency in the best-fit model and a lack of statistical significance at lower levels for water fluoride exposures, leading to uncertainty in the shape of the dose-response curve. This uncertainty is not surprising given the lower number of observations for fluoride concentrations in water (n=879 from 3 studies) compared with urinary fluoride concentrations (n=4218 from 5 studies). The ability to detect a true effect is reduced at lower exposure levels when exposure contrasts are diminished.117 Although the same cutoffs were used for the water and urine subgroup analyses, fluoride levels in water likely underestimate total fluoride exposures that are better estimated by levels in urine. Variable fluoride exposures from nonwater sources may also decrease the precision of the effect estimates at lower fluoride concentrations in water. In contrast, the best model fit for urinary fluoride concentrations was consistently linear.
Elevated naturally occurring fluoride levels in groundwater (>1.5 mg/L) are prevalent globally and include central Australia, eastern Brazil, sub-Saharan Africa, the southern Arabian Peninsula, south and east Asia, and western North America.118 Although to our knowledge no epidemiological studies addressing fluoride exposure and children’s IQ have been conducted in the United States, significant inequalities in CWS fluoride levels exist by county sociodemographic characteristics, including racial and ethnic composition, especially among Hispanic and Latino communities.119 Of note, there are regions of the United States where CWS and private wells contain natural fluoride concentrations greater than 1.5 mg/L,120 serving more than 2.9 million US residents.119 In addition, the US Geological Survey estimates that 172000 US residents are served by domestic wells that exceed EPA’s enforceable standard of 4.0 mg/L fluoride in drinking water, and 522000 are served by domestic wells that exceed EPA’s nonenforceable standard of 2.0 mg/L fluoride in drinking water.1 To reduce risk of moderate-to-severe dental fluorosis, the CDC recommends that parents use an alternative source of water for children aged 8 years or younger and for bottle-fed infants if their primary drinking water contains greater than 2 mg/L of fluoride.121 Currently, there are no recommendations or restrictions on fluoride levels in drinking water based on cognitive neurodevelopmental outcomes.121
To our knowledge, no studies of fluoride exposure and children’s IQ have been performed in the United States, and no nationally representative urinary fluoride levels are available, hindering application of these findings to the US population. Although this meta-analysis was not designed to address the broader public health implications of water fluoridation in the United States, these results may inform future public health risk-benefit assessments of fluoride.
Strengths of this systematic review and meta-analysis include a large body of literature, a predefined systematic search and screening process, risk-of-bias assessment of individual studies, prespecified subgroup analyses, and use of both group-level and individual-level exposure data. The consistency of the inverse associations across the high and low risk-of-bias studies, different intelligence assessment methods, different exposure matrices, different study locations, different analytical approaches, and evidence of a dose-response association strengthen confidence in the conclusion of an overall inverse association between fluoride exposure and children’s IQ. It is notable that there is a diversity of study design factors across studies, which could be described as overall heterogeneity of the body of evidence. In this case, the heterogeneity supports the robustness of the conclusions and is different from heterogeneity in the results, which we did not find in this meta-analysis.
The body of existing literature has limitations in that many of the studies were classified as having high risk of bias. Most of the studies included in the mean-effects and dose-response mean-effects meta-analyses were cross-sectional and had study design and/or methodological limitations. However, the consistency in meta-analytic associations across the high and low risk-of-bias studies and the other subgroup analyses reduced the likelihood that specific biases or potential confounders in individual studies could explain the inverse association between fluoride exposure and children’s IQ.
While several recent studies conclude that fluoride exposures from community water fluoridation are not associated with children’s IQ or other neurodevelopmental outcomes,122–124 the results of the mean-effects meta-analysis were consistent with 6 previous meta-analyses6–8,122,125,126 that reported statistically significant inverse associations between fluoride exposure and children’s IQ scores (see the “Characteristics of Previous Meta-Analyses” section of eAppendix 1 and eTable 6 in Supplement 1).
This meta-analysis found inverse associations and an inverse dose-response association between fluoride exposure and children’s IQ across the multicountry epidemiological literature. There were limited data and uncertainty in the dose-response association between fluoride exposure and children’s IQ when fluoride exposure was estimated by drinking water alone at concentrations less than 1.5 mg/L. Confidence in the associations at lower fluoride levels could be increased by additional prospective cohort studies with individual fluoride exposure measures. These results may inform future comprehensive public health risk-benefit assessments of fluoride.
Accepted for Publication: September 9, 2024.
Published Online: January 6, 2025. doi:10.1001/jamapediatrics.2024.5542
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2025 Taylor KW et al. JAMA Pediatrics.
Corresponding Author: Kyla W. Taylor, PhD, Division of Translational Toxicology, National Institute of Environmental Health Sciences, National Institutes of Health, 530 Davis Dr, Morrisville, NC 27719 (kyla.taylor@nih.gov).
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1Division of Translational Toxicology, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina
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2ICF, Reston, Virginia
Author Contributions: Drs Taylor and Eftim had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Taylor, Eftim, Blain, Hartman, Rooney, Bucher.
Acquisition, analysis, or interpretation of data: Taylor, Eftim, Sibrizzi, Blain, Magnuson, Hartman, Bucher.
Drafting of the manuscript: Taylor, Eftim, Magnuson, Rooney, Bucher.
Critical review of the manuscript for important intellectual content: Taylor, Eftim, Sibrizzi, Blain, Hartman, Rooney, Bucher.
Statistical analysis: Eftim.
Obtained funding: Rooney, Bucher.
Administrative, technical, or material support: Sibrizzi, Blain, Magnuson, Hartman, Rooney, Bucher.
Supervision: Taylor, Rooney, Bucher.
Conflict of Interest Disclosures: None reported.
Funding/Support: This work was supported by the Intramural Research Program (ES103316, ES103317) at the National Institute of Environmental Health Sciences (NIEHS), National Institutes of Health and was performed for NIEHS under contract GS00Q14OADU417 (order HHSN273201600015U).
Role of the Funder/Sponsor: NIEHS had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation of the manuscript. NIEHS did have a role in the review approval of the manuscript and the decision to submit the manuscript for publication.
Data Sharing Statement: See Supplement 2.
Additional Contributions: We appreciate the helpful input on the draft manuscript from Suril Mehta, DrPH, MPH, Kelly Ferguson, PhD, MPH, Allen Wilcox, MD, PhD, and Alison Motsinger-Reif, PhD (NIEHS). We thank Jonathan Cohen, PhD (ICF), who performed independent verification of the dose-response meta-analysis; Cynthia Lin, PhD, Nathan Lothrop, PhD, Michelle Mendez, PhD, and Alexandra Goldstone, MPH (ICF), for independent quality control of the data; and Jeremy Frye, MSLS (ICF), for conducting literature searches and reference management. No additional compensation was provided.
1. US Geological Survey. Fluoride in groundwater: too much of too little of a good thing? Water Resources Mission Area, Colorado Water Science Center; 2020. Accessed May 3, 2020. https://www.usgs.gov/news/comprehensive-assessment-fluoride-groundwater
2. US Department of Health and Human Services Federal Panel on Community Water Fluoridation. U.S. Public Health Service recommendation for fluoride concentration in drinking water for the prevention of dental caries. Public Health Rep. 2015;130(4):318-331. doi:10.1177/003335491513000408 PubMedGoogle ScholarCrossref
3. Centers for Disease Control and Prevention. Recommendations for using fluoride to prevent and control dental caries in the United States. MMWR Recomm Rep. 2001;50(RR-14):1-42.PubMedGoogle Scholar
4. US Environmental Protection Agency. Fluoride: exposure and relative source contribution analysis. US Environmental Protection Agency; 2010. Accessed August 19, 2019. https://www.epa.gov/sdwa/fluoride-risk-assessment-and-relative-source-contribution
5. National Research Council. Fluoride in drinking water: a scientific review of EPA’s standards. National Research Council; 2006. Accessed August 19, 2019. https://nap.nationalacademies.org/catalog/11571/fluoride-in-drinking-water-a-scientific-review-of-epas-standards
6. Choi AL, Sun G, Zhang Y, Grandjean P. Developmental fluoride neurotoxicity: a systematic review and meta-analysis. Environ Health Perspect. 2012;120(10):1362-1368. doi:10.1289/ehp.1104912 PubMedGoogle ScholarCrossref
7. Duan Q, Jiao J, Chen X, Wang X. Association between water fluoride and the level of children’s intelligence: a dose-response meta-analysis. Public Health. 2018;154:87-97. doi:10.1016/j.puhe.2017.08.013 PubMedGoogle ScholarCrossref
8. Veneri F, Vinceti M, Generali L, et al. Fluoride exposure and cognitive neurodevelopment: systematic review and dose-response meta-analysis. Environ Res. 2023;221:115239. doi:10.1016/j.envres.2023.115239 PubMedGoogle ScholarCrossref
9. Grandjean P, Meddis A, Nielsen F, et al. Dose dependence of prenatal fluoride exposure associations with cognitive performance at school age in three prospective studies. Eur J Public Health. 2024;34(1):143-149. Published online October 5, 2023. doi:10.1093/eurpub/ckad170 PubMedGoogle ScholarCrossref
10. Lin YY, Hsu WY, Yen CE, Hu SW. Association of dental fluorosis and urinary fluoride with intelligence among schoolchildren. Children (Basel). 2023;10(6):987. doi:10.3390/children10060987 PubMedGoogle ScholarCrossref
11. Xia Y, Xu Y, Shi M, et al. Effects of high-water fluoride exposure on IQ levels in school-age children: a cross-sectional study in Jiangsu, China. Expo Health. 2023;16:885-895. doi:10.1007/s12403-023-00597-2 Google ScholarCrossref
12. National Toxicology Program. NTP monograph on the state of the science concerning fluoride exposure and neurodevelopment and cognition: a systematic review. NTP Monogr. 2024;(8):NTP-MGRAPH-8. PubMedGoogle Scholar
13. National Toxicology Program. Protocol for systematic review of effects of fluoride exposure on neurodevelopment. US Dept of Health & Human Services, Public Health Service, National Institutes of Health; 2020. Accessed May 3, 2020. https://ntp.niehs.nih.gov/sites/default/files/ntp/ohat/fluoride/ntpprotocol_revised20200916_508.pdf
14. National Toxicology Program. OHAT Risk of Bias Rating Tool for Human and Animal Studies. US Dept of Health & Human Services, Public Health Service, National Institutes of Health; 2015.
15. Bonett DG. Confidence intervals for standardized linear contrasts of means. Psychol Methods. 2008;13(2):99-109. doi:10.1037/1082-989X.13.2.99 PubMedGoogle ScholarCrossref
17. Rosenthal R. Parametric measures of effect size. In: Cooper H, Hedges LV, eds. The Handbook of Research Synthesis. Russell Sage Foundation; 1994.
18. Crippa A, Thomas I, Orsini N. A pointwise approach to dose-response meta-analysis of aggregated data. Int J Stat Med Res. 2018;7(2):25-32. doi:10.6000/1929-6029.2018.07.02.1 Google ScholarCrossref
19. Crippa A, Discacciati A, Bottai M, Spiegelman D, Orsini N. One-stage dose-response meta-analysis for aggregated data. Stat Methods Med Res. 2019;28(5):1579-1596. doi:10.1177/0962280218773122 PubMedGoogle ScholarCrossref
20. Orsini N. Weighted mixed-effects dose–response models for tables of correlated contrasts. Stata J. 2021;21(2):320-347. doi:10.1177/1536867X211025798 Google ScholarCrossref
21. Müller S, Scealy JL, Welsh AH. Model selection in linear mixed models. Stat Sci. 2013;28(2):135-167. doi:10.1214/12-STS410 Google ScholarCrossref
22. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7(3):177-188. doi:10.1016/0197-2456(86)90046-2 PubMedGoogle ScholarCrossref
23. Cochran WG. The combination of estimates from different experiments. Biometrics. 1954;10(1):101-129. doi:10.2307/3001666 Google ScholarCrossref
24. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557-560. doi:10.1136/bmj.327.7414.557 PubMedGoogle ScholarCrossref
25. Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994;50(4):1088-1101. doi:10.2307/2533446 PubMedGoogle ScholarCrossref
26. Egger M, Smith G, Schneider M, Minder C, eds. Systematic Reviews in Health Care: Meta-Analysis in Context. BMJ Publishing Group; 2008.
27. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629-634. doi:10.1136/bmj.315.7109.629 PubMedGoogle ScholarCrossref
28. Duval S, Tweedie R. A nonparametric “trim and fill” method of accounting for publication bias in meta-analysis. J Am Stat Assoc. 2000;95(449):89-98. Google Scholar
29. Duval S, Tweedie R. Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics. 2000;56(2):455-463. doi:10.1111/j.0006-341X.2000.00455.x PubMedGoogle ScholarCrossref
31. Palmer TM, Sterne JAC, eds. Meta-Analysis in Stata: An Updated Collection From the Stata Journal. 2nd ed. Stata Press; 2016.
32. Green R, Lanphear B, Hornung R, et al. Association between maternal fluoride exposure during pregnancy and IQ scores in offspring in Canada. JAMA Pediatr. 2019;173(10):940-948. doi:10.1001/jamapediatrics.2019.1729
ArticlePubMedGoogle ScholarCrossref
33. Yu X, Chen J, Li Y, 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;118:116-124. doi:10.1016/j.envint.2018.05.042 PubMedGoogle ScholarCrossref
34. Ding Y, YanhuiGao, Sun H, 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(2-3):1942-1946. doi:10.1016/j.jhazmat.2010.12.097 PubMedGoogle ScholarCrossref
35. Zhang S, Zhang X, Liu H, et al. Modifying effect of COMT gene polymorphism and a predictive role for proteomics analysis in children’s intelligence in endemic fluorosis area in Tianjin, China. Toxicol Sci. 2015;144(2):238-245. doi:10.1093/toxsci/kfu311 PubMedGoogle ScholarCrossref
36. Saeed M, Rehman MYA, Farooqi A, Malik RN. Arsenic and fluoride co-exposure through drinking water and their impacts on intelligence and oxidative stress among rural school-aged children of Lahore and Kasur districts, Pakistan. Environ Geochem Health. 2022;44(11):3929-3951. Published online November 9, 2021. doi:10.1007/s10653-021-01141-4 PubMedGoogle ScholarCrossref
37. Feng Z, An N, Yu F, et al. Do methylenetetrahydrofolate dehydrogenase, cyclohydrolase, and formyltetrahydrofolate synthetase 1 polymorphisms modify changes in intelligence of school-age children in areas of endemic fluorosis? Chin Med J (Engl). 2022;135(15):1846-1854. doi:10.1097/CM9.0000000000002062 PubMedGoogle ScholarCrossref
38. Tian W, Zhao A, Yu Y, et al. The relationship between IQ and urinary fluoride in children in endemic fluorosis endemic areas polluted by coal burning. Chin J Endem Dis. 2022;41(2):117-119. doi:10.3760/cma.j.cn231583-20210125-00025Google Scholar
39. Broadbent JM, Thomson WM, Moffitt TE, Poulton R. Response: community water fluoridation and intelligence response. Am J Public Health. 2015;105(4):e3-e4. doi:10.2105/AJPH.2015.302647 PubMedGoogle ScholarCrossref
40. Ahmad MS, Sarker MNI, Ahmad MN, Ali M, Sadiq AM. Does high fluoride intake cause low IQ? a case of Islamic religious schools (Madrassas) in rural and urban areas of Sindh, Pakistan. Fluoride. 2022;55(1):49-62.Google Scholar
41. Kang J, Cheng Y, Wu K, Lin S, He G, Jin Y. Effect of exposure to fluoride and arsenic in drinking water of Hangjinhouqi on children’s intelligence. Article in Chinese. Chin School Health. 2011:679-681.Google Scholar
42. Dewey D, England-Mason G, Ntanda H, et al; APrON Study Team. Fluoride exposure during pregnancy from a community water supply is associated with executive function in preschool children: a prospective ecological cohort study. Sci Total Environ. 2023;891:164322. doi:10.1016/j.scitotenv.2023.164322 PubMedGoogle ScholarCrossref
43. Khan SA, Singh RK, Navit S, et al. Relationship between dental fluorosis and intelligence quotient of school going children in and around Lucknow District: a cross-sectional study. J Clin Diagn Res. 2015;9(11):ZC10-ZC15. doi:10.7860/JCDR/2015/15518.6726 PubMedGoogle ScholarCrossref
44. Lin F, Ai H, Zhao H, Lin J, Jhiang J, Maimaiti. High fluoride and low iodine environment and subclinical cretinism in Xinjiang. Endemic Dis Bull. 1991;6(2):62-67.Google Scholar
45. Li Y, Li X, Wei S. Effects of high fluoride intake on child mental work capacity: preliminary investigation into the mechanisms involved. Article in Chinese. J West China Univ Med Sci. 1994;25(2):188-191.Google Scholar
46. Li Y, Li X, Wei S. Effects of high fluoride intake on child mental work capacity: preliminary investigation into the mechanisms involved. Fluoride. 2008;41(4):331-335.Google Scholar
47. Xiang Q, Liang Y, Chen L, et al. Effect of fluoride in drinking water on children’s intelligence. Fluoride. 2003;36:84-94.Google Scholar
48. Seraj B, Shahrabi M, Shadfar M, et al. Effect of high water fluoride concentration on the intellectual development of children in Makoo/Iran. J Dent (Tehran). 2012;9(3):221-229.PubMedGoogle Scholar
49. Trivedi M, Sangai N, Patel R, Payak M, Vyas S. Assessment of groundwater quality with special reference to fluoride and its impact on IQ of schoolchildren in six villages of the Mundra Region, Kachchh, Gujurat, India. Fluoride. 2012;45(4):377-383.Google Scholar
50. Cui Y, Yu J, Zhang B, Guo B, Gao T, Liu H. The relationships between thyroid-stimulating hormone and/or dopamine levels in peripheral blood and IQ in children with different urinary iodine concentrations. Neurosci Lett. 2020;729:134981. doi:10.1016/j.neulet.2020.134981 PubMedGoogle ScholarCrossref
51. Zhang J, Yao H, Chen Y. The effect of high levels of arsenic and fluoride on the development of children’s intelligence. Article in Chinese. Chin J Publ Health. 1998;17(2):119.Google Scholar
52. Hong F, Wang Hui Yang Dong Zhang Z. Investigation on the intelligence and metabolism of iodine and fluoride in children with high iodine and fluoride. Chin J Endem Dis Control; 2001:12-14.Google Scholar
53. Wang X, Wang L, Hu P, Guo X, Luo X. Effects of high iodine and high fluorine on children’s intelligence and thyroid function. Article in Chinese. Zhonghua Difangbingxue Zazhi. 2001;20(4):288-290.Google Scholar
54. Zhao Y, Cui Y, Yu J, et al. Study on the relationship between water-borne high iodine and thyroid hormone and children’s intelligence level. J Environ Health. 2018;35(1):6-9.Google Scholar
55. An J, Mei S, Liu A, Fu Y, Wang C. Effect of high level of fluoride on children’s intelligence. Article in Chinese. Chin J Control Endem Dis. 1992;7(2):93-94.Google Scholar
56. Li X, Hou G, Yu B, Yuan C, Liu Y, Hao Z. Investigation and analysis of children’s IQ and dental fluorosis in high fluoride area. Article in Chinese. Chin J Pest Control. 2010;26(3):230-231.Google Scholar
57. Ren D, Li K, Liu D. A study of the intellectual ability of 8-14 year-old children in high fluoride, low iodine areas. Article in Chinese. Chin J Control Endem Dis. 1989;4(4):251.Google Scholar
58. Ren D, Li K, Liu D. A study of the intellectual ability of 8-14 year-old children in high fluoride, low iodine areas. Fluoride. 2008;41:319-320.Google Scholar
59. Wang SX, Wang ZH, Cheng XT, et al. Arsenic and fluoride exposure in drinking water: children’s IQ and growth in Shanyin county, Shanxi province, China. Environ Health Perspect. 2007;115(4):643-647. doi:10.1289/ehp.9270 PubMedGoogle ScholarCrossref
60. Sun M, Li S, Wang Y, Li F. Measurement of intelligence by drawing test among the children in the endemic area of Al-F combined toxicosis. Article in Chinese. J Guiyang Med Coll. 1991;16(3):204-206.Google Scholar
61. Guo XC, Wang RY, Cheng CF, et al. A preliminary investigation of the IQs of 7-13 year-old children from an area with coal burning-related fluoride poisoning. Article in Chinese. Chin J Epidemiol. 1991;10(2):98-100.Google Scholar
62. Guo XC, Wang RY, Cheng CF, et al. A preliminary investigation of the IQs of 7-13 year-old children from an area with coal burning-related fluoride poisoning. Fluoride. 2008;41:125-128.Google Scholar
63. Wang G, Yang D, Jia F, Wang H. A study of the IQ levels of four- to seven-year-old children in high fluoride areas. Article in Chinese. Endemic Dis Bull. 1996;11(1):60-62.Google Scholar
64. Wang G, Yang D, Jia F, Wang H. A study of the IQ levels of four- to seven-year-old children in high fluoride areas. Fluoride. 2008;41:340-343.Google Scholar
65. Li F, Chen X, Huang R, Xie Y. The impact of endemic fluorosis caused by the burning of coal on the development of intelligence in children. J Environ Health. 2009;26(4):838-840.Google Scholar
66. Bai A, Li Y, Fan Z, Li X, Li P. Intelligence and growth development of children in coal-burning-borne arsenism and fluorosis areas: an investigation study. Article in Chinese. Zhonghua Difangbingxue Zazhi. 2014;33(2):160-163.Google Scholar
67. Lou D, Luo Y, Liu J, et al. Refinement impairments of verbal-performance intelligent quotient in children exposed to fluoride produced by coal burning. Biol Trace Elem Res. 2021;199(2):482-489. doi:10.1007/s12011-020-02174-z PubMedGoogle ScholarCrossref
68. Zhang P, Cheng L. Effect of coal-burning endemic fluorosis on children’s physical development and intellectual level. Chin J Endem Dis Control. 2015;30(6):458-459.Google Scholar
69. Wang J, Yu M, Yang L, Yang X, Deng B. The effect of coal-burning fluoride exposure on children’s intelligence and physical development. J Environ Health. 2020;37(11):971-974.Google Scholar
70. Chen YX, Han FL, Zhoua ZL, et al. Research on the intellectual development of children in high fluoride areas. Article in Chinese. Chin J Control Endem Dis. 1991;6(suppl):99-100.Google Scholar
71. Chen YX, Han FL, Zhoua ZL, et al. Research on the intellectual development of children in high fluoride areas. Fluoride. 2008;41:120-124.Google Scholar
72. Xu Y, Lu C, Zhang X. The effect of fluorine on the level of intelligence in children. Endemic Dis Bull. 1994;9(2):83-84.Google Scholar
73. Li XS, Zhi JL, Gao RO. Effect of fluoride exposure on the intelligence of children. Fluoride. 1995;28:189-192.Google Scholar
74. Yao L, Zhou J, Wang S, Cui K, Lin F. Analysis on TSH and intelligence level of children with dental fluorosis in a high fluoride area. Lit Inf Prev Med. 1996;2(1):26-27.Google Scholar
75. Zhao LB, Liang GH, Zhang DN, Wu XR. Effect of a high fluoride water supply on children’s intelligence. Fluoride. 1996;29:190-192.Google Scholar
76. Yao Y. Comparable analysis on the physical and mental development of children in endemic fluorosis area with water improvement and without water improvement. Lit Inf Prev Med. 1997;3(1):42-43.Google Scholar
77. Lu Y, Sun ZR, Wu LN, Wang X, Lu W, Liu SS. Effect of high-fluoride water on intelligence in children. Fluoride. 2000;33:74-78.Google Scholar
78. Hong FG, Cao YX, Yang D, Wang H. Research on the effects of fluoride on child intellectual development under different environmental conditions. Chin Prim Health Care. 2001;15(3):56-57.Google Scholar
79. Hong FG, Cao YX, Yang D, Wang H. Research on the effects of fluoride on child intellectual development under different environmental conditions. Fluoride. 2008;41:156-160.Google Scholar
80. Li YP, Jing XY, Chen D, Lin L, Wang ZJ. Effects of endemic fluoride poisoning on the intellectual development of children in Baotou. Article in Chinese. Zhongguo Gonggong Weisheng Guanli. 2003;19(4):337-338.Google Scholar
81. Li YP, Jing XY, Chen D, Lin L, Wang ZJ. Effects of endemic fluoride poisoning on the intellectual development of children in Baotou. Fluoride. 2008;41:161-164.Google Scholar
82. Wang SX, Wang ZH, Cheng XT, et al. Investigation and evaluation on intelligence and growth of children in endemic fluorosis and arsenism areas. Article in Chinese. Zhonghua Difangbingxue Zazhi. 2005;24:179-182.Google Scholar
83. Seraj B, Shahrabi M, Falahzade M, Falahzade F, Akhondi N. Effect of high fluoride concentration in drinking water on children’s intelligence. J Dent Med. 2006;19(2):80-86.Google Scholar
84. Wang Z, Wang S, Zhang X, Li J, Zheng X, Hu C. Investigation of children’s growth and development under long-term fluoride exposure. Chin J Control Endem Dis. 2006;21(4):239-241.Google Scholar
85. Fan Z, Dai H, Bai A, Li P, Li T, Li G. The effect of high fluoride exposure in children’s intelligence. J Environ Health. 2007;24(10):802-803.Google Scholar
86. Trivedi MH, Verma RJ, Chinoy NJ, Patel RS, Sathawara NG. Effect of high fluoride water on intelligence of school children in India. Fluoride. 2007;40:178-183.Google Scholar
87. Eswar P, Nagesh L, Devaraj CG. Intelligent quotients of 12-14 year old school children in a high and low fluoride village in India. Fluoride. 2011;44:168-172.Google Scholar
88. Poureslami HR, Horri A, Garrusi B. A comparative study of the IQ of children age 7-9 in a high and a low fluoride water city in Iran. Fluoride. 2011;44:163-167.Google Scholar
89. Shivaprakash PK, Ohri K, Noorani H. Relation between dental fluorosis and intelligence quotient in school children of Bagalkot district. J Indian Soc Pedod Prev Dent. 2011;29(2):117-120. doi:10.4103/0970-4388.84683 PubMedGoogle ScholarCrossref
90. Wang S, Zhu X. Investigation and analysis of intelligence level of children in high fluoride area. Chin J Endem Dis Control. 2012;27(1):67-68.Google Scholar
91. Karimzade S, Aghaei M, Mahvi AH. Investigation of intelligence quotient in 9-12 year-old children exposed to high- and low-drinking water fluoride in West Azerbaijan Province, Iran. Fluoride. 2014;47:9-14.Google Scholar
92. Sebastian ST, Sunitha S. A cross-sectional study to assess the intelligence quotient (IQ) of school going children aged 10-12 years in villages of Mysore district, India with different fluoride levels. J Indian Soc Pedod Prev Dent. 2015;33(4):307-311. doi:10.4103/0970-4388.165682 PubMedGoogle ScholarCrossref
93. Das K, Mondal NK. Dental fluorosis and urinary fluoride concentration as a reflection of fluoride exposure and its impact on IQ level and BMI of children of Laxmisagar, Simlapal Block of Bankura District, W.B., India. Environ Monit Assess. 2016;188(4):218. doi:10.1007/s10661-016-5219-1 PubMedGoogle ScholarCrossref
94. Mondal D, Dutta G, Gupta S. Inferring the fluoride hydrogeochemistry and effect of consuming fluoride-contaminated drinking water on human health in some endemic areas of Birbhum district, West Bengal. Environ Geochem Health. 2016;38(2):557-576. doi:10.1007/s10653-015-9743-7 PubMedGoogle ScholarCrossref
95. Wang R, He N, Wang Y, Hou G, Zhang PJ. Investigation and analysis of children’s dental fluorosis and IQ level in high fluoride district of Hengshui City. Med Anim Control. 2021;37(8):796-800.Google Scholar
96. Bashash M, Thomas D, Hu H, 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. doi:10.1289/EHP655 PubMedGoogle ScholarCrossref
97. Till C, Green R, Flora D, et al. Fluoride exposure from infant formula and child IQ in a Canadian birth cohort. Environ Int. 2020;134:105315. doi:10.1016/j.envint.2019.105315 PubMedGoogle ScholarCrossref
98. Wang M, Liu L, Li H, et al. Thyroid function, intelligence, and low-moderate fluoride exposure among Chinese school-age children. Environ Int. 2020;134:105229. doi:10.1016/j.envint.2019.105229 PubMedGoogle ScholarCrossref
99. Cui Y, Zhang B, Ma J, et al. Dopamine receptor D2 gene polymorphism, urine fluoride, and intelligence impairment of children in China: a school-based cross-sectional study. Ecotoxicol Environ Saf. 2018;165:270-277. doi:10.1016/j.ecoenv.2018.09.018 PubMedGoogle ScholarCrossref
100. Zhao L, Yu C, Lv J, et al. Fluoride exposure, dopamine relative gene polymorphism and intelligence: a cross-sectional study in China. Ecotoxicol Environ Saf. 2021;209:111826. doi:10.1016/j.ecoenv.2020.111826 PubMedGoogle ScholarCrossref
101. Goodman CV, Bashash M, Green R, et al. Domain-specific effects of prenatal fluoride exposure on child IQ at 4, 5, and 6-12 years in the ELEMENT cohort. Environ Res. 2022;211:112993. doi:10.1016/j.envres.2022.112993 PubMedGoogle ScholarCrossref
102. Cantoral A, Téllez-Rojo MM, Malin AJ, et al. Dietary fluoride intake during pregnancy and neurodevelopment in toddlers: a prospective study in the progress cohort. Neurotoxicology. 2021;87:86-93. doi:10.1016/j.neuro.2021.08.015 PubMedGoogle ScholarCrossref
103. Ibarluzea J, Gallastegi M, Santa-Marina L, et al. Prenatal exposure to fluoride and neuropsychological development in early childhood: 1-to 4 years old children. Environ Res. 2022;207:112181. doi:10.1016/j.envres.2021.112181 PubMedGoogle ScholarCrossref
104. Valdez Jiménez L, López Guzmán OD, Cervantes Flores M, et al. In utero exposure to fluoride and cognitive development delay in infants. Neurotoxicology. 2017;59:65-70. doi:10.1016/j.neuro.2016.12.011 PubMedGoogle ScholarCrossref
105. Guo B, Yu J, Cui Y, et al. DBH gene polymorphism, iodine and fluoride and their interactions and their interaction with children’s intelligence. J Environ Hygiene. 2021;11(2):134-140.Google Scholar
106. Villa A, Anabalon M, Zohouri V, Maguire A, Franco AM, Rugg-Gunn A. Relationships between fluoride intake, urinary fluoride excretion and fluoride retention in children and adults: an analysis of available data. Caries Res. 2010;44(1):60-68. doi:10.1159/000279325 PubMedGoogle ScholarCrossref
107. Watanabe M, Kono K, Orita Y, Usuda K, Takahashi Y, Yoshida Y. Influence of dietary fluoride intake on urinary fluoride concentration and evaluation of corrected levels in spot urine. Fluoride. 1995;28(2):61-70.Google Scholar
108. Zohouri FV, Swinbank CM, Maguire A, Moynihan PJ. Is the fluoride/creatinine ratio of a spot urine sample indicative of 24-h urinary fluoride? Community Dent Oral Epidemiol. 2006;34(2):130-138. doi:10.1111/j.1600-0528.2006.00269.x PubMedGoogle ScholarCrossref
109. Abduweli Uyghurturk D, Goin DE, Martinez-Mier EA, Woodruff TJ, DenBesten PK. Maternal and fetal exposures to fluoride during mid-gestation among pregnant women in northern California. Environ Health. 2020;19(1):38. doi:10.1186/s12940-020-00581-2 PubMedGoogle ScholarCrossref
110. Malin AJ, Hu H, Martínez-Mier EA, et al. Urinary fluoride levels and metal co-exposures among pregnant women in Los Angeles, California. Environ Health. 2023;22(1):74. doi:10.1186/s12940-023-01026-2 PubMedGoogle ScholarCrossref
111. Bellinger DC. Interpretation of small effect sizes in occupational and environmental neurotoxicology: individual versus population risk. Neurotoxicology. 2007;28(2):245-251. doi:10.1016/j.neuro.2006.05.009 PubMedGoogle ScholarCrossref
112. Needleman HL. What can the study of lead teach us about other toxicants? Environ Health Perspect. 1990;86:183-189. doi:10.1289/ehp.9086183 PubMedGoogle ScholarCrossref
113. Rose G. Sick individuals and sick populations. Int J Epidemiol. 1985;14(1):32-38. doi:10.1093/ije/14.1.32 PubMedGoogle ScholarCrossref
114. Rose G. Sick individuals and sick populations. Int J Epidemiol. 2001;30(3):427-432. doi:10.1093/ije/30.3.427 PubMedGoogle ScholarCrossref
115. Weiss B. Vulnerability of children and the developing brain to neurotoxic hazards. Environ Health Perspect. 2000;108(suppl 3):375-381. PubMedGoogle Scholar
116. Braun JM. Early-life exposure to EDCs: role in childhood obesity and neurodevelopment. Nat Rev Endocrinol. 2017;13(3):161-173. doi:10.1038/nrendo.2016.186 PubMedGoogle ScholarCrossref
117. Cooper GS, Lunn RM, Ågerstrand M, et al. Study sensitivity: evaluating the ability to detect effects in systematic reviews of chemical exposures. Environ Int. 2016;92-93:605-610. doi:10.1016/j.envint.2016.03.017 PubMedGoogle ScholarCrossref
118. Podgorski J, Berg M. Global analysis and prediction of fluoride in groundwater. Nat Commun. 2022;13(1):4232. doi:10.1038/s41467-022-31940-x PubMedGoogle ScholarCrossref
119. Hefferon R, Goin DE, Sarnat JA, Nigra AE. Regional and racial/ethnic inequalities in public drinking water fluoride concentrations across the US. J Expo Sci Environ Epidemiol. 2024;34(1):68-76. doi:10.1038/s41370-023-00570-w PubMedGoogle ScholarCrossref
120. McMahon PB, Brown CJ, Johnson TD, Belitz K, Lindsey BD. Fluoride occurrence in United States groundwater. Sci Total Environ. 2020;732:139217. doi:10.1016/j.scitotenv.2020.139217 PubMedGoogle ScholarCrossref
121. Centers for Disease Control and Prevention. Community water fluoridation FAQs: infant formula. Centers for Disease Control & Prevention; 2015. Accessed February 10, 2022. https://www.cdc.gov/fluoridation/faq/?CDC_AAref_Val=https://www.cdc.gov/fluoridation/faqs/infant-formula.html#cdc_faqs_cat5-infant-formula
122. Kumar JV, Moss ME, Liu H, Fisher-Owens S. Association between low fluoride exposure and children’s intelligence: a meta-analysis relevant to community water fluoridation. Public Health. 2023;219:73-84. doi:10.1016/j.puhe.2023.03.011 PubMedGoogle ScholarCrossref
123. Guth S, Hüser S, Roth A, et al. Toxicity of fluoride: critical evaluation of evidence for human developmental neurotoxicity in epidemiological studies, animal experiments and in vitro analyses. Arch Toxicol. 2020;94(5):1375-1415. doi:10.1007/s00204-020-02725-2 PubMedGoogle ScholarCrossref
124. Do LG, Spencer AJ, Sawyer A, et al. Early childhood exposures to fluorides and child behavioral development and executive function: a population-based longitudinal study. J Dent Res. 2023;102(1):28-36. doi:10.1177/00220345221119431 PubMedGoogle ScholarCrossref
125. Tang QQ, Du J, Ma HH, Jiang SJ, Zhou XJ. Fluoride and children’s intelligence: a meta-analysis. Biol Trace Elem Res. 2008;126(1-3):115-120. doi:10.1007/s12011-008-8204-x PubMedGoogle ScholarCrossref
126. Miranda GHN, Alvarenga MOP, Ferreira MKM, et al. A systematic review and meta-analysis of the association between fluoride exposure and neurological disorders. Sci Rep. 2021;11(1):22659. doi:10.1038/s41598-021-99688-w PubMedGoogle ScholarCrossref
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