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Background: Hepato- and nephrotoxicity of fluoride have been demonstrated in animals, but few studies have examined potential effects in humans. This population-based study examines the relationship between chronic low-level fluoride exposure and kidney and liver function among United States (U.S.) adolescents. This study aimed to evaluate whether greater fluoride exposure is associated with altered kidney and liver parameters among U.S. youth. Methods: This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (2013-2016). We analyzed data from 1983 and 1742 adolescents who had plasma and water fluoride measures respectively and did not have kidney disease. Fluoride was measured in plasma and household tap water. Kidney parameters included estimated glomerular filtration rate (calculated by the original Schwartz formula), serum uric acid, and the urinary albumin to creatinine ratio. Liver parameters were assessed in serum and included alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, blood urea nitrogen, gamma-glutamyl transferase, and albumin. Survey-weighted linear regression examined relationships between fluoride exposure and kidney and liver parameters after covariate adjustment. A Holm-Bonferroni correction accounted for multiple comparisons. Results: The average age of adolescents was 15.4 years. Median water and plasma fluoride concentrations were 0.48 mg/L and 0.33 μmol/L respectively. A 1 μmol/L increase in plasma fluoride was associated with a 10.36 mL/min/1.73 m2 lower estimated glomerular filtration rate (95% CI: -17.50, -3.22; p = 0.05), a 0.29 mg/dL higher serum uric acid concentration (95% CI: 0.09, 0.50; p = 0.05), and a 1.29 mg/dL lower blood urea nitrogen concentration (95%CI: -1.87, -0.70; p < 0.001). A 1 mg/L increase in water fluoride was associated with a 0.93 mg/dL lower blood urea nitrogen concentration (95% CI: -1.44, -0.42; p = 0.007). Conclusions: Fluoride exposure may contribute to complex changes in kidney and liver related parameters among U.S. adolescents. As the study is cross-sectional, reverse causality cannot be ruled out; therefore, altered kidney and/or liver function may impact bodily fluoride absorption and metabolic processes.
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Environment International
journal homepage: www.elsevier.com/locate/envint
Fluoride exposure and kidney and liver function among adolescents in the
United States: NHANES, 2013–2016
Ashley J. Malin
a,
, Corina Lesseur
a
, Stefanie A. Busgang
a
, Paul Curtin
a
, Robert O. Wright
a,b
,
Alison P. Sanders
a,b
a
Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
b
Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
ARTICLE INFO
Handling Editor: Lesa Aylward
Keywords:
Fluoride
Kidney
Liver
United States
Adolescents
ABSTRACT
Background: Hepato- and nephrotoxicity of fluoride have been demonstrated in animals, but few studies have
examined potential effects in humans. This population-based study examines the relationship between chronic
low-level fluoride exposure and kidney and liver function among United States (U.S.) adolescents. This study
aimed to evaluate whether greater fluoride exposure is associated with altered kidney and liver parameters
among U.S. youth.
Methods: This cross-sectional study utilized data from the National Health and Nutrition Examination Survey
(2013–2016). We analyzed data from 1983 and 1742 adolescents who had plasma and water fluoride measures
respectively and did not have kidney disease. Fluoride was measured in plasma and household tap water. Kidney
parameters included estimated glomerular filtration rate (calculated by the original Schwartz formula), serum
uric acid, and the urinary albumin to creatinine ratio. Liver parameters were assessed in serum and included
alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, blood urea nitrogen, gamma-glu-
tamyl transferase, and albumin. Survey-weighted linear regression examined relationships between fluoride
exposure and kidney and liver parameters after covariate adjustment. A Holm-Bonferroni correction accounted
for multiple comparisons.
Results: The average age of adolescents was 15.4 years. Median water and plasma fluoride concentrations were
0.48 mg/L and 0.33 μmol/L respectively. A 1 μmol/L increase in plasma fluoride was associated with a
10.36 mL/min/1.73 m
2
lower estimated glomerular filtration rate (95% CI: −17.50, −3.22; p= 0.05), a
0.29 mg/dL higher serum uric acid concentration (95% CI: 0.09, 0.50; p= 0.05), and a 1.29 mg/dL lower blood
urea nitrogen concentration (95%CI: −1.87, −0.70; p< 0.001). A 1 mg/L increase in water fluoride was as-
sociated with a 0.93 mg/dL lower blood urea nitrogen concentration (95% CI: −1.44, −0.42; p= 0.007).
Conclusions: Fluoride exposure may contribute to complex changes in kidney and liver related parameters
among U.S. adolescents. As the study is cross-sectional, reverse causality cannot be ruled out; therefore, altered
kidney and/or liver function may impact bodily fluoride absorption and metabolic processes.
1. Introduction
Approximately 74% of the United States (U.S.) population that re-
lies on public water distribution systems receives chemically fluori-
dated water for the purpose of preventing tooth decay (Centers for
Disease Control and Prevention, 2014). The most commonly used
fluoridating chemical is hydrofluorosilicic acid, although sodium
fluorosilicate and sodium fluoride are used in some water treatment
processes (Centers for Diseaese Control and Prevention, 2018). Until
2015, the recommended U.S. drinking water fluoride concentration
range was 0.7–1.2 mg/L. However, this concentration was lowered in
2015 to 0.7 mg/L in part due to concerns about the rising prevalence of
dental fluorosis – visually detectable changes in tooth enamel due to
excess fluoride exposure during tooth development, among U.S. youth
(U.S. Department of Health and Human Services Federal Panel on
Community Water Fluoridation, 2015;Centers for Disease Control and
https://doi.org/10.1016/j.envint.2019.105012
Received 29 March 2019; Received in revised form 10 July 2019; Accepted 11 July 2019
Abbreviations: eGFR, estimated glomerular filtration rate; ACR, urinary albumin to creatinine ratio; BUN, blood urea nitrogen; ALT, alanine aminotransferase; ALP,
alkaline phosphatase; AST, aspartate amino transferase; GGT, gamma-glutamyl transferase; SUA, serum uric acid
Corresponding author at: Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box
1057, New York, NY 10029, USA.
E-mail address: Ashley.malin@mssm.edu (A.J. Malin).
Environment International xxx (xxxx) xxxx
0160-4120/ © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/BY-NC-ND/4.0/).
Please cite this article as: Ashley J. Malin, et al., Environment International, https://doi.org/10.1016/j.envint.2019.105012
Prevention, 2010).
Among healthy adults, approximately 60% of absorbed fluoride is
excreted in urine by the kidneys, while the corresponding percentage
among children is approximately 45% (Buzalaf and Whitford, 2011;
Villa et al., 2010). The kidneys, followed by the liver, accumulate more
fluoride than any other organ system in the body (National Research
Council, 2006;Whitford et al., 1979). Therefore, these organs and their
intersectional processes may be especially vulnerable to effects of
fluoride, even among healthy individuals. Additionally, fluoride is ab-
sorbed in calcified tissues – such as bones and teeth, as well as calcium-
containing glands such as the pineal gland.
While fluoride exposure in adulthood has been associated with ne-
phro- and hepatotoxicity in animals and humans (Jimenez-Cordova
et al., 2018a;National Research Council, 2006;Sayanthooran et al.,
2018), few studies have examined associations between fluoride ex-
posure and kidney or liver function in youth. Three prior studies con-
ducted in India, Japan and/or China found potential evidence of kidney
and liver function decline in children and/or adolescents exposed to
relatively high fluoride concentrations (Liu and Xia, 2005;Ando et al.,
2001;Khandare et al., 2017;Xiong et al., 2007). Findings of a fourth
study conducted in Mexico were inconsistent (Jimenez-Cordova et al.,
2019). The few studies conducted among young animals also demon-
strated adverse renal and hepatic effects of fluoride, even at low con-
centrations (Shashi and Thapar, 2002;Shashi, 2001;Cardenas-Gonzalez
et al., 2013;Perera et al., 2013). Taken together these findings suggest
that fluoride may be developmentally nephrotoxic and hepatotoxic.
However, whether these findings apply to low-level fluoride exposures
relevant to U.S. youth has not been investigated.
Our study aimed to examine the relationship between fluoride ex-
posure, measured in blood plasma and drinking water, and kidney and
liver parameters among adolescents in the U.S.. We hypothesized that
higher blood plasma and water fluoride concentrations would be as-
sociated with altered kidney and liver parameters in this population.
2. Materials and methods
2.1. Participants
We utilized data from the National Health and Nutrition
Examination Survey (NHANES) collected from 2013 to 2016, the years
that publicly available fluoride biomonitoring data were collected and
available at the time of analysis. NHANES is a program of studies
conducted by the Centers for Disease Control and Prevention that is
designed to assess health and nutrition status of a nationally re-
presentative, noninstitutionalized sample of people of all ages living in
the U.S.. It employs questionnaires, in-home interviews and physical
examinations at mobile examination centers where blood and urine are
collected (Centers for Disease Control and Prevention, 2018). This study
was exempted from review by the Icahn School of Medicine at Mount
Sinai's (ISMMS) Institutional Review Board (#1702145).
Plasma fluoride concentrations were measured among 4470 parti-
cipants aged 6–19 years and tap water fluoride concentrations were
measured among 8087 participants aged 0–19 years. Our analysis in-
cluded adolescents aged 12–19 years because the renal and hepatic
parameters examined herein were not measured in children under 12,
except for the urinary albumin to creatinine ratio. Our sample included
participants who had either plasma or water fluoride measurements
and complete data for all covariates and outcomes. Missing data
were < 15% for all outcome measures, and < 10% for covariates
among participants who had all outcome measures. We excluded 2
participants with suggestive kidney disease, as indicated by estimated
glomerular filtration rate < 60 mL/min/1.73m
2
. Additionally, since
protein intake can influence kidney and liver function test results, we
excluded 1 participant with a reported daily protein intake of 0 g, and 3
participants with reported daily protein intakes > 400 g as these were
considered likely to be erroneous values. There were 1985 adolescents
who met inclusion criteria for analyses. Of those, 1983 participants had
plasma fluoride levels and were included in analyses. For analyses of
water fluoride, 1942 participants had water fluoride levels and we ex-
cluded an additional 200 participants who reported that they did not
drink tap water, resulting in a sample size of 1742. Participant selection
is depicted in Fig. S1. Supplemental Table S1 compares demographic
characteristics of the current overall study sample (n = 1985) and all
adolescents ages 12–19 over the same years (NHANES 2013–2016). We
applied sampling weights to account for the complex NHANES survey
design as recommended by the National Center for Health Statistics
(NCHS) (Centers for Disease Control and Prevention, 2013). The
weighted samples for plasma and water fluoride analyses represented
25,930,302 and 23,287,332 adolescents in the U.S. respectively.
2.2. Fluoride measures
Fluoride concentrations were measured in blood plasma and
household tap water samples. Tap water and blood collection times
were not standardized. Plasma fluoride concentrations reflect fluoride
intake as well as individual differences in fluoride metabolism (Buzalaf
and Whitford, 2011). Plasma fluoride was measured via an ion-specific
electrode and hexamethyldisiloxane (HMDS) method, and household
water samples were measured via an ion-specific electrode. Both
plasma and water fluoride concentrations were measured at the College
of Dental Medicine, Georgia Regents University, Augusta, GA. They
were measured in duplicate (using the same sample) and the average of
these values was released. The lower limit of detection (LLOD) for
plasma fluoride was 0.25 nmol, while the LLOD for water fluoride was
0.10 mg/L (National Health and Nutrition Examination Survey, 2017a;
National Health and Nutrition Examination Survey, 2016a). Approxi-
mately 89% and 100% (all) of participants, had values above the LLOD
for water fluoride and plasma fluoride respectively (National Health
and Nutrition Examination Survey, 2016b;National Health and
Nutrition Examination Survey, 2017b).
2.3. Kidney and liver parameters
Serum was analyzed for markers of kidney and liver function at the
Collaborative Laboratory Services, Ottumwa, Iowa as part of a standard
biochemistry profile. From 2013 to 2016 a Beckman Coulter UniCel
DxC 800 Synchron chemistry analyzer was utilized; while from 2015 to
2016 a Beckman Coulter UniCel DxC 660i Synchron Access chemistry
analyzer was utilized as well. Urine samples were analyzed for albumin
and creatinine at the University of Minnesota via a Turner Digital
Fluorometer, Model 450 and Roche Cobas 6000 Analyzer respectively.
Urine sample collection time was not standardized. All analytical re-
sults were at or above the LLOD.
2.3.1. Estimated glomerular filtration rate (eGFR)
Glomerular filtration rate is considered the gold standard index of
kidney function (Levey and Inker, 2016). We calculated eGFR with
serum creatinine concentrations using the original Schwartz formula
(Schwartz et al., 1987):
= ×eGFR k height in cm creatinine in mg dL[( )/ / ].
This formula is appropriate when serum creatinine concentrations
are measured via a Jaffe rate method, as the larger coefficients account
for the potentially higher serum creatinine levels associated with this
method. In the original formula, k= 0.7 for adolescent boys and k=
0.55 for adolescent girls or individuals < 13 years of age; whereas in
the revised formula the coefficient k= 0.413. Among children, ado-
lescents and young adults, eGFR values < 75 mL/min/1.73 m
2
are
considered abnormal, and those < 60 mL/min/1.73 m
2
are reflective of
chronic kidney disease (Pottel et al., 2015).
A.J. Malin, et al. Environment International xxx (xxxx) xxxx
2
2.3.2. Serum uric acid (SUA)
Uric acid is a waste product of purine metabolism that is excreted in
urine. Dysregulation of SUA levels are common in kidney and metabolic
disorders. SUA was measured using a timed endpoint method. The
LLOD was 0.5 mg/dL. The standard reference range for uric acid for
children and adolescents aged 10–18 years is 3.5–7.3 mg/dL. For males
and females over 18 years the reference ranges are 3.6–8.4 mg/dL and
2.9–7.5 mg/dL respectively (Collaborative Laboratory Services LLC,
2017b).
2.3.3. Albumin to creatinine ratio (ACR)
Increased levels of urinary albumin are present with various renal
diseases, including chronic kidney disease and end stage renal disease,
as well as subclinical glomerular dysfunction. Urinary creatinine cor-
relates with urinary volume and excretion rate. The albumin to crea-
tinine ratio is used to detect kidney disease or dysfunction (Fuhrman
et al., 2017). Urinary albumin was measured via a solid-phase fluor-
escent immunoassay (Chavers et al., 1984) and urinary creatinine was
measured via an enzymatic endpoint method (University of Minnesota,
2014a). The LLOD for urinary albumin was 0.3 μg/mL, while the re-
portable lower limit for urinary creatinine was 5 mg/dL (University of
Minnesota, 2014a;University of Minnesota, 2014b). Among children
and young adults, an ACR of < 10 mg/g is considered normal, an ACR
of 20–30 mg/g is considered mildly increased, an ACR of 30 to 300 mg/
g is moderately increased (termed “microalbuminuria”), and an ACR
of > 300 mg/g is severely increased (termed “macroalbuminuria”)
(KDIGO, 2012).
2.3.4. Blood urea nitrogen (BUN)
Urea is a waste product of nitrogen-containing compounds, such as
amino acids, metabolized by the liver and excreted in urine. High BUN
levels may reflect kidney dysfunction (e.g. reduced ability to excrete
urea) whereas low BUN levels may reflect liver dysfunction (e.g. im-
paired protein metabolism) or malnutrition. BUN was measured using
an enzymatic conductivity rate method (Collaborative Laboratory
Services LLC, 2017d;Collaborative Laboratory Services, 2017a). The
analytical measurement range measured via the Beckman UniCel DxC
800 Synchron was 1–150 mg/dL (or up to 300 mg/dL with ORDAC
enabled). When measured with the Beckman Coulter UniCel DxC 660i
Synchron it was 5–100 mg/dL (or up to 300 mg/dL with ORDAC en-
abled). The standard reference range for BUN for people aged
5–15 years is 7–18 mg/dL. For those over 15 years it is 6–23 mg/dL
(Collaborative Laboratory Services LLC, 2017d;Collaborative
Laboratory Services, 2017a).
2.3.5. Aspartate aminotransferase (AST) and alanine aminotransferase
(ALT)
Serum aminotransferases are enzymes present in liver and cardiac
tissue. Elevations can reflect hepatocyte and myocardial cell damage or
disease states. AST and ALT were measured via enzymatic rate and
kinetic rate methods respectively. The LLOD for both was 5.0 IU/L. The
standard reference range for serum or plasma AST for people ages
10–20 years is 13–38 IU/L (Collaborative Laboratory Services LLC,
2017f). The standard reference ranges for serum or plasma ALT are
8–29 IU/L and 8–36 IU/L for 10–20 year-old females and males re-
spectively (Collaborative Laboratory Services, 2017c).
2.3.6. Alkaline phosphatase (ALP)
ALP is an enzyme present in bone and liver cells and can be used to
diagnose liver, bone and parathyroid disease. ALP was measured via a
kinetic rate method. The LLOD was 5.0 IU/L. The standard reference
range for serum or plasma ALP for individuals ages 12–16 is 67–382 IU/
L, while for those > 16 years of age it is 36–113 IU/L (Collaborative
Laboratory Services LLC, 2017e).
2.3.7. Serum albumin
Albumin is synthesized in the liver and is a major component of
plasma where it plays a key role in maintaining oncotic pressure. Serum
concentrations can be used to assess kidney and/or liver disease or
dysfunction. Serum albumin concentrations were measured via a timed
endpoint method. The analytic range was 1.0–7.0 g/dL. The standard
reference range for serum or plasma albumin for healthy children and
adolescents aged 1–18 years is 3.1–4.8 g/dL. For individuals over
18 years it is 3.5–5.0 mg/dL when measured with the Beckman Coulter
UniCel DxC 660i Synchron Access chemistry analyzer and 3.7–4.7 mg/
dL when measured with the Beckman Coulter UniCel DxC 800 Synchron
analyzer (Collaborative Laboratory Services, 2017g;Collaborative
Laboratory Services LLC, 2017h).
2.3.8. Gamma-glutamyl transferase (GGT)
GGT is an enzyme present in hepatocytes, a sensitive indicator of
liver disease and more specific to liver function than AST/ALT. Serum
GGT was measured via an enzymatic rate method. The analytical range
was 5–750 IU/L or up to 3000 IU/L with ORDAC enabled. The reference
ranges for males and females aged 10–15 years are 7–26 IU/L and
8–23 IU/L respectively. The reference ranges for males and females >
15 years are 10–65 IU/L and 8–36 IU/L respectively (Collaborative
Laboratory Services LLC, 2017i).
2.4. Covariates
Covariates were selected a priori based on prior empirical evidence
associated with fluoride exposure and kidney/liver function. They in-
cluded: age, sex, body mass index, race/ethnicity, the ratio of family
income to poverty, and daily protein intake (Villa et al., 2010;
Martinez-Mier and Soto-Rojas, 2010;Jain, 2017;Boyde and Cerklewski,
1987;Moxey-Mims, 2018). Additionally, we adjusted for serum coti-
nine level as a biomarker of tobacco smoke exposure in sensitivity
analyses including only the 2013–2014 NHANES cycle, since cotinine
was only assessed in the 2013–2014 cycle (see analysis Section 2.5).
The ratio of family income to poverty was calculated by dividing annual
family income by the poverty guidelines specific to the survey year.
Daily protein intake was obtained from a 24-hour dietary recall. Al-
though, two 24-hour dietary recalls were conducted (one in person and
one via telephone), we only used protein intake estimates from the in-
person interview because most of the study sample did not complete the
telephone interview. Only participants whose recall estimates were
determined by the NCHS to be reliable were included in this study.
2.5. Statistical analyses
All analyses applied survey weights from the mobile exam center
visit (i.e. MEC weights) to account for the clustered sample design,
survey non-response, over-sampling, post-stratification, and sampling
error, and to permit generalization to the U. S. population (National
Center for Health Statistics, 2013). Given that we utilized dietary
variables as covariates and/or exclusion criteria (i.e. protein intake; tap
water consumption) we applied reweighted MEC weights to our dietary
sample prior to analyses according to NCHS guidance. The MEC weights
were recalculated based on our dietary subsample using an adjustment
factor (see Appendix A). Descriptive statistics and regression analyses
were performed using SAS (V.9.4) software. We used Pearson correla-
tion to examine the relationship between plasma and water fluoride
concentrations (both log
2
-transformed).
Survey-weighted linear regression was used to model kidney and
liver parameters as a function of plasma or water fluoride concentra-
tions while adjusting for covariates. For regression analyses, we in-
cluded laboratory generated values for water fluoride values below the
LLOD; however, we imputed water fluoride values below the LLOD as
LLOD/ √2 in our calculation of descriptive statistics. We note that im-
putation (or lack thereof) did not appreciably change the results of
A.J. Malin, et al. Environment International xxx (xxxx) xxxx
3
regression analyses. We explored potentially influential values using a
Cook's Distance estimate; none were identified. Assumptions pertaining
to normality, homogeneity of variance and linearity were satisfied for
models testing the relationship between plasma fluoride and eGFR,
SUA, BUN, serum albumin or GGT, as well as for models testing the
relationship between water fluoride and BUN, serum albumin or SUA.
For remaining models, linear regression assumptions were not satisfied.
Therefore, a log
2
transformation was applied to skewed fluoride vari-
ables, and skewed outcome variables, including: ACR, ALT, AST, ALP,
and GGT, to satisfy assumptions. The relationship between plasma
fluoride and ALP remained nonlinear after the transformation, and
thus, we tested a quadratic relationship in the regression model. We
also included a fluoride*sex interaction term in our models to test for
sex-specific effects; however, it was not significant in any of the models,
and therefore was removed. We also conducted sensitivity analyses to
examine whether adjusting for cotinine exposure or removing partici-
pants with serum cotinine levels ≥10 ng/mL (Kim, 2016) influenced
the relationship between plasma fluoride concentrations and kidney/
liver parameters for participants in NHANES 2013–2014 (the only years
in which both plasma fluoride and cotinine were measured). A two-
tailed alpha of 0.05 was the criteria for statistical significance for re-
gression analyses. We applied a Holm-Bonferroni correction to account
for multiple comparisons for each fluoride variable.
3. Results
Demographic characteristics are presented in Table 1. Table S1
compares demographics between current study participants and all
adolescents in NHANES 2013–2016. The average age of participants
was 15.4 years.
Descriptive statistics for fluoride and kidney and liver parameters
are presented in Table 2. The mean household water fluoride con-
centration among participants who drank tap water fell below the re-
commended level (mean = 0.48 mg/L); however, values between the
75th and 95th percentiles were above this level ranging from 0.71 to
1.00 mg/L. Participants generally had normal kidney and liver function
(i.e. eGFR ranged between 84 and 212 mL/min/1.73 m
2
). However,
SUA and BUN measurements at the 5th percentile were below their
respective reference ranges. Additionally, ACR values at the 95th
percentile (98 participants) fell in the microalbuminuria range.
Fluoride concentrations in plasma and tap water were moderately po-
sitively correlated (r= 0.42, p< 0.001).
3.1. Plasma fluoride regression results
In linear regression models adjusted for covariates, higher plasma
fluoride concentrations were associated with lower eGFR, higher SUA,
and lower BUN (B: −10.36, 95%CI: −17.50, − 3.22, p= 0.05; B: 0.29,
95%CI: 0.09, 0.50, p= 0.05; and B: −1.29, 95%CI: −1.87, −0.70,
p< 0.001 respectively). Therefore, a 1 μmol/L increase in plasma
fluoride was associated with a 10.36 mL/min/1.73 m
2
lower eGFR, a
0.29 mg/dL higher SUA concentration, and a 1.29 mg/dL lower BUN
concentration. Plasma fluoride concentrations were not associated with
the remaining kidney or liver parameters examined herein (Table 3)
(Fig. 1).
3.2. Water fluoride regression results
In linear regression models adjusted for covariates, higher water
fluoride concentrations were associated with lower BUN (B = −0.93,
95%CI: −1.44, −0.42, p= 0.007). Therefore, a 1 mg/L increase in
household tap water fluoride concentration was associated with a
0.93 mg/dL lower BUN concentration. Water fluoride concentrations
were not significantly associated with the remaining kidney or liver
parameters examined herein (Table 4) (Fig. 2).
3.3. Sensitivity analysis
Associations between plasma fluoride and kidney and liver mea-
sures separated by NHANES cycle are presented in Table S2. Cotinine-
adjusted associations between plasma fluoride and kidney and liver
measures for NHANES 2013–2014 are presented in Table S3 (Note:
2013–2014 was the only cycle in our study with available serum coti-
nine data). Compared to the 2013–2014 results without cotinine ad-
justment (Table S2), our findings did not change appreciably when
cotinine was included as a covariate in the survey-weighted covariate-
adjusted regression model (Table S3). When participants with serum
cotinine levels ≥10 ng/mL were excluded from the regression analysis
Table 1
Demographic characteristics according to sample participating in NHANES 2013–2016.
Demographic characteristic Overall sample
n = 1985
N = 25,942,026
Plasma fluoride sample
n = 1983
N = 25,930,302
Water fluoride sub-sample
a
n = 1742
N = 23,287,332
Age (yrs.); mean (SE) 15.38 (0.07) 15.37 (0.07) 15.32 (0.07)
Sex; N (%)
Male 13,672,321(52.7) 13,665,854 (52.7) 12,494,779 (53.7)
Female 12,269,705 (47.3) 12,264,448 (47.3) 10,792,553 (46.3)
BMI; mean (SE) 24.34 (0.24) 24.34 (0.24) 24.21 (0.25)
BMI categories
b
; N (%)
Underweight 841,241 (3.3) 834,774 (3.2) 724,010 (3.1)
Normal weight 14,660,261 (56.8) 14,660,261 (56.8) 13,422,456 (57.9)
Overweight 4,698,550 (18.2) 4,698,550 (18.2) 4,144,842 (17.9)
Obese 5,608,569 (21.7) 5,603,312 (21.7) 4,901,026 (21.1)
Race/ethnicity
Mexican American; N (%) 3,806,271 (14.7) 3,801,014 (14.7) 3,160,150 (13.6)
Other Hispanic 1,953,725 (7.5) 1,953,725 (7.5) 1,635,251 (7.0)
Non-Hispanic White 14,544,657 (56.1) 14,544,657 (56.1) 13,382,896 (57.5)
Non-Hispanic Black 3,220,902 (12.4) 3,220,902 (12.4) 2,871,360 (12.3)
Non-Hispanic Asian 1,069,372 (4.1) 1,069,372 (4.1) 967,296 (4.2)
Other race-including multi-racial 1,347,100 (5.2) 1,340,634 (5.2) 1,270,379 (5.5)
Daily protein intake (gm) 75.52 (1.21) 75.53 (1.21) 75.86 (1.30)
Ratio of family income to poverty 2.47 (0.10) 2.47 (0.10) 2.51 (0.10)
Note. Sampling weights were applied for calculation of demographic descriptive statistics and therefore Ns for frequencies represent the weighted sample size. Re-
weighting for the dietary sample was not applied for calculation of descriptive statistics above.
a
Participants who reported that they did not drink the tap water were excluded.
b
n = 1972 for entire sample, n = 1970 for plasma F sample and n = 1732 for water F subsample due to missing data for this variable.
A.J. Malin, et al. Environment International xxx (xxxx) xxxx
4
(n = 949), the association between plasma fluoride and eGFR had a
greater magnitude of effect, but did not reach statistical significance (B:
−5.50, 95%, CI: −13.77, 2.77, uncorrected p= 0.18) (Table S3). In
the association between plasma fluoride and BUN, the magnitude of
association was attenuated and marginally statistically significant
(uncorrected p= 0.06). The association between plasma fluoride and
SUA was relatively unchanged in magnitude or significance level (Table
S3).
4. Discussion
To our knowledge, this study represents the first population-based
study in the U.S. to examine the relationship between chronic low-level
fluoride exposure and kidney and liver related parameters among
adolescents. We included a breadth of kidney and liver measures to
examine these relationships. Furthermore, we adjusted for factors that
can influence fluoride exposure or absorption, kidney and liver func-
tion, or access to healthcare, such as socioeconomic status, as well as
multiple comparisons. We utilized plasma fluoride concentrations as
they account for both fluoride intake and individual differences in
fluoride absorption and metabolism (Buzalaf and Whitford, 2011).
Conversely, household tap water fluoride concentrations are unaffected
by individual differences in fluoride metabolism; yet, water fluoride
constitutes the primary source of U.S. fluoride exposure (Health and
Ecological Criteria Division. Office of Water, 2010).
Higher plasma fluoride concentrations were associated with
changes in kidney and liver related parameters. Most notably, a 1 μmol/
L increase in plasma fluoride was associated with a 10.36 mL/min/
1.73 m
2
lower eGFR. This is consistent with previous studies in which
higher urinary fluoride and dental fluorosis were associated with lower
eGFR among youth in China and India (Ando et al., 2001;Khandare
et al., 2017). However, it is inconsistent with a recent cross-sectional
study in Mexico that found an association between higher urinary
fluoride and increased eGFR among 374 children (Jimenez-Cordova
et al., 2018). Differing results could reflect eGFR measurement, parti-
cipant age, and/or fluoride biomarkers utilized (i.e. urine vs. blood
fluoride assessment). Specifically, in the study conducted in Mexico
eGFR was determined from a single serum measure with the creatinine-
cystatin C-based CKiD equation (Schwartz et al., 2012), children were
5–12 years old, and fluoride was assessed in urine adjusted for specific
gravity. We also found that adolescents with higher plasma fluoride
tended to have higher SUA and lower BUN which can reflect altered
kidney and liver function respectively; although, lower BUN levels can
also reflect nutritional deficiencies (Kumar et al., 1972). Consistently,
among adolescents who consumed tap water, those with higher
household tap water fluoride concentrations tended to have lower BUN,
which may indicate impaired protein metabolism.
Given the cross-sectional nature of this study, there are several
possible interpretations for the findings. First, fluoride exposure may
contribute to complex changes in kidney and liver parameters among
U.S. adolescents. This possibility is supported by the consistency of our
findings with research demonstrating a dose-response relationship be-
tween water fluoride levels above 2 mg/L and enzyme markers of liver
and kidney dysfunction (Xiong et al., 2007). Although in the current
study, tap water fluoride concentrations were generally below 1 mg/L.
There are several mechanisms by which fluoride exposure may con-
tribute to kidney dysfunction. First, studies with adult rats have shown
that chronic low-level fluoride exposure can lead to glomerular hy-
percellularity and mesangial cell proliferation (Varner et al., 1998),
reduced kidney enzyme activity (Sullivan, 1969), interstitial nephritis,
and renal tubule hypertrophy and hyperplasia (McCay et al., 1957).
Increased apoptosis and tubular epithelial damage, including necrosis,
have also been observed among children with high fluoride exposures
(Quadri et al., 2018). Chronic low-level fluoride exposure is also asso-
ciated with decreased thyroid gland activity among children (Lin et al.,
1991;Singh et al., 2014;Khandare et al., 2018) and adults
(Kheradpisheh et al., 2018;Malin et al., 2018). Moreover, reduced
thyroid gland function, within the clinically normal range, is associated
Table 2
Descriptive statistics of fluoride exposure and kidney and liver measures.
Measure Arithmetic mean
(Standard error)
Median 5th percentile 95th percentile
Plasma fluoride (μmol/L)
a
0.40 (0.01) 0.33 0.16 0.81
Tap water fluoride (mg/L)
b
0.48 (0.03) 0.48 0.07 1.00
eGFR (mL/min/1.73 m
2
) 147.98 (1.21) 143.55 106.25 203.66
SUA (mg/dL) 5.07 (0.04) 4.92 3.07 7.21
Albumin/creatinine ratio (mg/g) 24.63 (1.93) 7.49 3.03 67.08
BUN (mg/dL) 11.25 (0.17) 10.41 5.80 16.59
ALT (IU/L) 19.57 (0.38) 15.72 10.15 38.57
ALP (IU/L) 134.26 (2.91) 96.70 48.41 323.58
AST (IU/L) 23.81 (0.37) 21.62 15.25 35.01
Serum albumin (g/dL) 4.51 (0.01) 4.46 3.96 4.96
GGT (IU/L) 14.35 (0.28) 11.88 7.15 27.48
Note. Sampling weights were applied for calculation of all descriptive statistics. N = 25,942,026 (unweighted n = 1985).
a
N = 25,930,302 (unweighted n = 1983).
b
N =23,287,332 (unweighted n=1742); Samples were reweighted to the dietary sample prior to calculating these descriptive statistics as these were the values
utilized in regression analyses. Only standard errors changed following reweighting.
Table 3
Associations between plasma fluoride and kidney and liver measures.
Outcomes Unstandardized beta
(95% CI)
Uncorrected pHolm-Bonferroni
corrected p
eGFR −10.36 (−17.50, −
3.22)
0.01 0.05
SUA 0.29 (0.09, 0.50) 0.01 0.05
ACR
a
0.08 (−0.04, 0.19) 0.20 > 0.99
BUN −1.29 (−1.87, −0.70) < 0.001 < 0.001
ALT
a
0.03 (−0.02, 0.08) 0.27 > 0.99
ALP
a,b
0.00 (−0.01, 0.01) 0.95 > 0.99
AST
a
0.00 (−0.04, 0.04) > 0.99 > 0.99
Serum albumin −0.03 (−0.09, 0.03) 0.29 > 0.99
GGT −0.71 (−1.92, 0.50) 0.24 > 0.99
Note. Regression analyses were adjusted for age, sex, race/ethnicity, body mass
index, ratio of family income to poverty and daily protein intake. Sampling
weights were applied to these regression analyses; N = 25,930,302; un-
weighted n = 1983; MEC weights were re-weighted to our dietary sample for
regression analyses.
a
Plasma fluoride exposure and outcome variables were log
2
transformed.
b
Model included a quadratic term.
Significant at p≤ 0.05 after Holm-Bonferroni correction; Regression results
remained consistent regardless of whether MEC weights or re-weighted MEC
weights were applied.
A.J. Malin, et al. Environment International xxx (xxxx) xxxx
5
with decreased eGFR (Anderson et al., 2018;Asvold et al., 2011). Thus,
fluoride exposure could potentially compromise kidney function via
glomerular damage, or indirectly via suppression of the thyroid gland.
However, this study did not aim to determine whether fluoride ex-
posure is associated with clinical decrements in kidney function among
U.S. adolescents. Rather, this study aimed to examine subclinical
changes in kidney or liver parameters associated with fluoride exposure
among a generally healthy population. For example, the lowest GFR
estimated in this study was 84 mL/min/1.73 m
2
, and therefore none
were below the < 75 mL/min/1.73 m
2
value considered reflective of
abnormal kidney function. Future prospective studies including parti-
cipants with and without kidney disease are needed to assess clinical
changes in kidney or liver function. Additionally, if fluoride exposure
does contribute to changes in kidney or liver parameters, future pro-
spective studies are needed to examine critical windows of vulnerability
for these effects; in particular, it is unknown whether these changes
may result from early life exposures during vital stages of kidney and
liver development, from cumulative exposure, or both.
An alternative interpretation for our findings is that poorer kidney
function may contribute to increased plasma fluoride levels rather than
resulting from them. This possibility is supported by our finding that
water fluoride concentrations were not associated with kidney para-
meters. Furthermore, animals and humans with impaired renal function
tend to have higher levels of bone and plasma/serum fluoride because
0
A B C
D E
G H I
F
Fig. 1. Associations between plasma fluoride and kidney and liver measures.
Each figure depicts a regression line with 95% confidence intervals; circles represent individual data points. Sample weighted regressions were adjusted for age, sex,
race/ethnicity, body mass index, ratio of family income to poverty and daily protein intake (N =25,930,302; unweighted n=1983). Plasma fluoride and outcome
variables were log2 transformed for analyses with albumin/creatinine ratio, alanine aminotransferase, alkaline phosphatase (ALP) and aspartate amino transferase.
The model with ALP included a quadratic term. Cook's distance estimates were used to test for influential data points; none were identified.
Table 4
Associations between water fluoride and kidney and liver measures
a
.
Outcomes Unstandardized beta
(95% CI)
Uncorrected pHolm-Bonferroni
corrected p
eGFR
b
−1.03 (−2.93, 0.87) 0.28 > 0.99
SUA 0.05 (−0.07, 0.18) 0.47 > 0.99
ACR
c
−0.01 (−0.07, 0.06) 0.79 > 0.99
BUN −0.93 (−1.44, −0.42) < 0.001 0.007
*
ALT
c
0.01 (−0.02, 0.03) 0.62 > 0.99
ALP
c
−0.02 (−0.04, 0.00) 0.02 0.16
AST
c
−0.00 (−0.02, 0.01) 0.68 > 0.99
Serum albumin −0.06 (−0.12, 0.00) 0.07 0.47
GGT
c
−0.01 (−0.04, 0.02) 0.60 > 0.99
Note. Regression analyses were adjusted for age, sex, race/ethnicity, body mass
index, ratio of family income to poverty and daily protein intake. Sampling
weights were applied to these regression analyses; N = 23,287,332; un-
weighted n = 1742; MEC weights were re-weighted to our dietary sample for
regression analyses.
a
Participants who reported not drinking tap water were excluded from these
analyses.
b
Water fluoride was log2 transformed in this model.
c
Water fluoride and outcome variables were log2 transformed.
* Significant at p 0.05 after Holm-Bonferroni correction; Regression re-
sults remained consistent regardless of whether MEC weights or re-weighted
MEC weights were applied.
A.J. Malin, et al. Environment International xxx (xxxx) xxxx
6
they do not excrete fluoride as readily (Turner et al., 1996;Waterhouse
et al., 1980;Rao and Friedman, 1975). However, plasma fluoride, ra-
ther than water fluoride, may have been associated with kidney func-
tion parameters in this study because it may better reflect individual
fluoride exposure.
A third possibility is that the relationship between fluoride exposure
and kidney function is bidirectional or cyclical in nature; whereby
fluoride hinders kidney function which contributes to decreased
fluoride excretion, increased bodily fluoride absorption and further
decrements in kidney function. Indeed, soluble fluoride that is not ex-
creted in urine is ultimately absorbed in hard and soft tissues, such as
bones or organ systems (including the kidneys) respectively (Buzalaf
and Whitford, 2011). Moreover, fluoride urinary excretion rates tend to
be lower among children (Buzalaf and Whitford, 2011;Villa et al.,
2010) because more fluoride is absorbed in bone in the growing skeletal
system (National Research Council, 2006b). Therefore, increases in
plasma fluoride could render children more vulnerable to other health
effects of fluoride exposure. Indeed, adults and children with kidney
disease have been shown to be at an increased risk of bone disease and
severe dental fluorosis respectively, due to increased skeletal fluoride
absorption (Ibarra-Santana et al., 2007;Lucas and Roberts, 2005;
Johnson and Jowsey, 1979).
Fluoride's effects on the liver are less well-characterized; however,
animal studies have shown that low-level fluoride exposure can
increase fatty deposits in the liver (de Camargo and Merzel, 1980),
affect liver protein expression (Pereira et al., 2013) and cause necrosis
(Perera et al., 2018). High fluoride exposures can cause vacuolization of
hepatocytes, dilated and hypertrophic liver tissue (Shashi, 2001), in-
creased oxidative stress and oxidative damage (Atmaca et al., 2014;
Xiao-ying and Sun, 2003), necrosis and altered liver enzyme activity
(Perera et al., 2018). In this study, fluoride exposure was not associated
with liver enzyme levels; however, higher concentrations of both water
and plasma fluoride were associated with lower BUN. Taken together,
these findings suggest that fluoride exposure may contribute to sub-
clinical decrements in liver function. We speculate that this could po-
tentially occur via interference by fluoride with liver amino acid me-
tabolism or protein synthesis (Chattopadhyay et al., 2011).
Additionally, since lower BUN levels may indicate protein malnutrition
(Kumar et al., 1972), we also speculate that our findings may reflect
subclinical interference of gastrointestinal processes by fluoride, al-
though protein intake in our sample was within ‘normal’ ranges for
adolescents on average. While high fluoride exposures have been shown
to damage gastric mucosa (Spak et al., 1990), to our knowledge, no
human studies have examined gastrointestinal effects of low fluoride
exposures. Mechanistic studies are needed to understand underlying
mechanisms of potential hepatotoxic and/or gastrointestinal effects of
fluoride.
This study had several limitations. First, since this study is cross-
A C
B
D E F
G H I
Fig. 2. Associations between water fluoride and kidney and liver measures.
Each figure depicts a regression line with 95% confidence intervals; circles represent individual data points. Sample weighted regression analyses were adjusted for
age, sex, race/ethnicity, body mass index, ratio of family income to poverty and daily protein intake (Participants who reported not drinking tap water were
excluded; N =23,287,332; unweighted n=1742). Water fluoride and outcome variables were log2 transformed for analyses with albumin/creatinine ratio, alanine
aminotransferase, alkaline phosphatase, aspartate amino transferase and gamma-glutamyl transferase. Water fluoride was log2 transformed for the analysis with
eGFR. Cook's distance estimates were used to test for influential data points; none were identified.
A.J. Malin, et al. Environment International xxx (xxxx) xxxx
7
sectional, the directionality of relationships cannot be determined,
particularly for associations of plasma fluoride and kidney/liver para-
meters. Therefore, additional longitudinal studies are needed to better
understand the developmental nephro- and hepatotoxicological impacts
of fluoride, and to parse directionality of these associations. Regardless,
this study contributes important information regarding how plasma
fluoride levels change in association with subclinical changes in kidney
and liver parameters (or vice versa) in the U.S. population which was
previously unreported. Second, blood sample collection time was not
standardized; however, exposure misclassification based on collection
time is more likely to bias estimates toward the null. Therefore, we
consider it unlikely that lack of standardization for blood collection led
to ‘false positive’ findings. Third, we did not have data on smoke ex-
posure for participants in NHANES cycle 2015–2016 and therefore
could not adjust for this in our main analyses. Still, we conducted
sensitivity analyses adjusting for serum cotinine, a biomarker of nico-
tine exposure, and this did not change the findings. Therefore, even
though smoking status may influence plasma fluoride levels (Jain,
2017) and kidney/liver function, it was likely not a confounder in this
study. Still, we had a limited dataset with which to examine this pos-
sibility so we cannot rule it out completely. Fourth, we did not control
for physical activity level or alcohol consumption in our analyses as
data for these variables were not available for the majority of our
sample. Lastly, we could not examine whether associations between
fluoride exposure and kidney and liver parameters differed geo-
graphically as geographic locations of participants are not publicly
available.
While the dental benefits of fluoride are widely established
(O'Mullane et al., 2016), recent concerns have been raised (U.S.
Department of Health and Human Services Federal Panel on Community
Water Fluoridation, 2015;Centers for Disease Control and Prevention,
2010;Aguilar-Diaz et al., 2017) regarding the appropriateness of its
widespread addition to drinking water or salt in North America. The
current study suggests that there may be potential nephro- and hepa-
tological health concerns to consider when evaluating fluoride use and
appropriate levels in public health interventions. However, we em-
phasize that future studies are required to overcome the limitations of a
single cross-sectional study.
4.1. Conclusion
Fluoride exposure may contribute to complex changes in kidney and
liver related parameters among adolescents in the United States.
However, as the study is cross-sectional, reverse causality is possible
and altered kidney and liver function may impact bodily fluoride ab-
sorption and metabolic processes. Further studies are needed to ex-
amine the mechanisms by which chronic low-level fluoride exposure
may impact kidney and liver related parameters during development
and adolescent life stages, as well as the ways in which kidney and liver
function influence bodily fluoride absorption.
Declaration of Competing Interest
The authors have no conflicts of interest to disclose.
Acknowledgments
We would like to thank the Centers for Disease Control and
Prevention (CDC) for conducting NHANES as well as the NCHS em-
ployees who provided us with consultation regarding the application of
survey weights. We would also like to thank the participants of the
2013–2014 and 2015–2016 NHANES cycles, without whom this re-
search would not have been possible.
Sources of funding
This work was supported in part by funding from the Mount Sinai
Children's Center Foundation and NIH/NIEHS: R00ES027508,
R01ES014930, R01ES013744, R24ES028522, P30ES023515.
Appendix A
To better account for the reduced sample size of the dietary recall
dataset used in analyses herein, mobile exam center (MEC) weights
were re-weighted using an adjustment factor, as detailed below, ac-
cording to NCHS guidance:
1. Sum the MEC weights of the domain = Σdomain, where ‘domain’ refers
to the gender, race and/or age group of participants who meet inclusion
criteria prior to reducing to the dietary sample.
2. Sum the MEC weights for study participants (SPs) in dietary sample = Σ
SP
3. Calculated adjustment factor = ΣDomain/ΣSPs
4. For SPs in the dietary sample, the new derived weights are equal to the
MEC weight multiplied by the adjustment factor of the domain. For SPs
not in the dietary sample, the new derived weight was set to missing.
Appendix B. Supplementary data
Supplementary data to this article can be found online at https://
doi.org/10.1016/j.envint.2019.105012.
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... Covariates were selected according to previous studies (10,11). Some covariates were collected from demographics data of NHANES 2013-2016, including age (6-19 years), gender (male, female), race/ethnicity (Non-hispanic White, Non-hispanic black, Mexican American, other race), six-month time period when the examination was performed (November 1 through April 30, May 1 through October 31) and ratio of family income to poverty (value not greater than 1 was categorized as under poverty level, the other side was above poverty level). ...
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Copper, zinc, and selenium are essential trace elements for human and have important effects on sex hormones. There are few studies on the relationships between the three trace elements and sex hormones. Therefore, our study aimed to investigate the relationships between serum copper, zinc, selenium and testosterone, estradiol, SHBG using data from the National Health and Nutrition Examination Survey (NHANES) 2013-2016 in participants 6-19 years. 1097 participants were enrolled and stratified into male/female children and adolescents. Weighted linear regression models combined regression diagnosis were used to estimate the relationships between trace elements and sex hormones according to the different stratifications. Our results showed that copper was inversely associated with testosterone and estradiol but positively correlated with SHBG. Zinc had positive relationships with testosterone in male adolescents and female children but an inverse relationship with testosterone in female adolescents. Furthermore, a negative association was observed between zinc and SHBG. With the rise of selenium level, testosterone and estradiol were increased but SHBG was decreased. In general, this study used more standardized statistical methods to investigate the relationships between copper, zinc, selenium and testosterone, estradiol, SHBG. Further study should pay attention to some details in statistical methods.
... In addition, a correlation between the stage of patients with alcoholic cirrhosis and serum fluoride levels was confirmed, with elevated plasma fluoride accompanied by raised alanine aminotransferase and total bilirubin (42). In a recent population-based cross-sectional study, by monitoring fluoride concentrations in plasma and household tap water, as well as evaluating the hepatic parameters in serum, it was found that every 1 mg/mL increase in water fluoride strongly correlated with 0.93 mg/dL decreased blood urea nitrogen concentration (43). Besides, CES1 is a vital drug metabolic enzyme in the liver that encodes about 1% of the total liver genomes (44). ...
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Background T-2 toxin is recognized as one of the high-risk environmental factors for etiology and pathogenesis of Kashin-Beck disease (KBD). Previous evidence indicates decreased serum fluorine level in KBD patients. However, whether fluoride could regulate carboxylesterase 1 (CES1)-mediated T-2 toxin hydrolysis and alter its chondrocyte toxicity remains largely unknown. Methods In this study, in vitro hydrolytic kinetics were explored using recombinant human CES1. HPLC-MS/MS was used to quantitative determination of hydrolytic metabolites of T-2 toxin. HepG2 cells were treated with different concentration of sodium fluoride (NaF). qRT-PCR and western blot analysis were used to compare the mRNA and protein expression levels of CES1. C28/I2 cells were treated with T-2 toxin, HT-2 toxin, and neosolaniol (NEO), and then cell viability was determined by MTT assay, cell apoptosis was determined by Annexin V-FITC/PI, Hoechst 33258 staining, and cleaved caspase-3, and cell cycle was monitored by flow cytometry assay, CKD4 and CDK6. Results We identified that recombinant human CES1 was involved in T-2 toxin hydrolysis to generate HT-2 toxin, but not NEO, and NaF repressed the formation of HT-2 toxin. Both mRNA and protein expression of CES1 were significantly down-regulated in a dose-dependent manner after NaF treatment in HepG2 cells. Moreover, we evaluated the chondrocyte toxicity of T-2 toxin and its hydrolytic metabolites. Results showed that T-2 toxin induced strongest cell apoptosis, followed by HT-2 toxin and NEO. The decreased the proportion of cells in G0/G1 phase was observed with the descending order of T-2 toxin, HT-2 toxin, and NEO. Conclusions This study reveals that CES1 is responsible for the hydrolysis of T-2 toxin, and that fluoride impairs CES1-mediated T-2 toxin detoxification to increase its chondrocyte toxicity. This study provides novel insight into understanding the relationship between fluoride and T-2 toxin in the etiology of KBD.
... Chronic exposure to F − has been associated with kidney damage [20][21][22], cardiometabolic risk [23], neurological alteration [24], and dental and skeletal fluorosis [25]. F − mainly affects children because at this life stage, it can accumulate more in calcified tissues [26]. ...
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... For decades fluoride has been extensively used to prevent and delay the progression of dental caries; however, a growing body of literature highlights its association with adverse health effects even at low-level of fluoride exposure (Whelton et al., 2019;Liu et al., 2020;Malin et al., 2019;Malin et al., 2018;Wang et al., 2020). Fluoride crosses the placental barrier (Shen and Taves, 1974) and pregnancy is a window of susceptibility to the toxic effects for the offspring. ...
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Fluoride is widely present in the environment. Excessive fluoride exposure leads to fluorosis, which has become a global public health problem and will cause damage to various organs and tissues. Only a few studies focus on serum metabolomics, and there is still a lack of systematic metabolomics associated with fluorosis within the main organs. Therefore, in the current study, a non-targeted metabolomics method using gas chromatography-mass spectrometry (GC-MS) was used to research the effects of fluoride exposure on metabolites in different organs, to uncover potential biomarkers and study whether the affected metabolic pathways are related to the mechanism of fluorosis. Male Sprague-Dawley rats were randomly divided into two groups: a control group and a fluoride exposure group. GC-MS technology was used to identify metabolites. Multivariate statistical analysis identified 16, 24, 20, 20, 24, 13, 7, and 13 differential metabolites in the serum, liver, kidney, heart, hippocampus, cortex, kidney fat, and brown fat, respectively, in the two groups of rats. Fifteen metabolic pathways were affected, involving toxic mechanisms such as oxidative stress, mitochondrial damage, inflammation, and fatty acid, amino acid and energy metabolism disorders. This study provides a new perspective on the understanding of the mechanism of toxicity associated with sodium fluoride, contributing to the prevention and treatment of fluorosis.
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Water is linked to every aspect of our life, and the nexus between water and health is well-documented. Lack of access to clean water and waterborne diseases is a significant cause of human misery. Pesticides are a group of chemicals widely detected in water bodies, mainly due to their indiscriminate use in the agricultural sector. Due to possible entry into human and animal food chains, health hazards posed by pesticides have become a considerable area of concern worldwide. Nevertheless, the production and use of pesticides are increasing, and the global pesticide market is expected to reach 24.6 billion USD by 2020–2024. Given the widespread occurrence and potential toxicity, many treatment technologies are in place to treat pesticide-contaminated water. However, the diverse chemical nature of the pesticides and the stringent regulations in drinking water standards, 0.1 μg/L for a single pesticide and 0.5 μg/L for the sum of all pesticides, limit the use of many existing treatment systems. The advancement in nanoscience and nanotechnology suggests that nanoscale materials, especially nanocarbon and its derivatives, are promising candidates for scavenging pesticides in water. This chapter reviews the literature on various nanoscale carbons with exciting properties and their applications for treating pesticide-laden drinking water. The mechanism of removal, challenges, prospects, and future development in the area is discussed. This chapter also covers the origin, occurrence of pesticides in water bodies, and their human and ecological health impacts.
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This review covers nearly 100 years of studies on the toxicity of fluoride on human and animal kidneys. These studies reveal that there are direct adverse effects on the kidneys by excess fluoride, leading to kidney damage and dysfunction. With the exception of the pineal gland, the kidney is exposed to higher concentrations of fluoride than all other soft tissues. Therefore, exposure to higher concentrations of fluoride could contribute to kidney damage, ultimately leading to chronic kidney disease (CKD). Among major adverse effects on the kidneys from excessive consumption of fluoride are immediate effects on the tubular area of the kidneys, inhibiting the tubular reabsorption; changes in urinary ion excretion by the kidneys disruption of collagen biosynthesis in the body, causing damages to the kidneys and other organs; and inhibition of kidney enzymes, affecting the functioning of enzyme pathways. This review proposes that there is a direct correlation between CKD and the consumption of excess amounts of fluoride. Studies particularly show immediate adverse effects on the tubular area of human and animal kidneys leading to CKD due to the consumption of excess fluoride. Therefore, it is very important to conduct more investigations on toxicity studies of excess fluoride on the human kidney, including experiments using human kidney enzymes, to study more in depth the impact of excess fluoride on the human kidney. Further, the interference of excess fluoride on collagen synthesis in human body and its effect on human kidney should also be further investigated.
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Background: Fluoride exposure has the potential to disrupt thyroid functioning, though adequate iodine intake may mitigate this effect. This is the first population-based study to examine the impact of chronic low-level fluoride exposure on thyroid function, while considering iodine status. The objective of this study was to determine whether urinary iodine status modifies the effect of fluoride exposure on thyroid stimulating hormone (TSH) levels. Methods: This cross-sectional study utilized weighted population-based data from Cycle 3 (2012−2013) of the Canadian Health Measures Survey (CHMS). Information was collected via a home interview and a visit to a mobile examination centre. The weighted sample represented 6,914,124 adults in Canada aged 18-79 who were not taking any thyroid-related medication. Urinary fluoride concentrations were measured in spot samples using an ion selective electrode and adjusted for specific gravity (UF SG). Serum TSH levels provided a measure of thyroid function. Multivariable regression analyses examined the relationship between UF SG and TSH, controlling for covariates. Results: Approximately 17.8% of participants fell in the moderately-to-severely iodine deficient range. The mean (SD) age of the sample was 46.5 (15.6) years and the median UF SG concentration was 0.74 mg/L. Among iodine deficient adults, a 1 mg/L increase in UF SG was associated with a 0.35 mIU/L increase in TSH [95% CI: 0.06, 0.64; p = 0.01, one-tailed]. Conclusions: Adults living in Canada who have moderate-to-severe iodine deficiencies and higher levels of ur-inary fluoride may be at an increased risk for underactive thyroid gland activity.
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PurposeChronic kidney disease of unknown etiology (CKDu), having epidemic characteristics, is being diagnosed increasingly in certain tropical regions of the world, mainly Latin America and Sri Lanka. They have been observed primarily in farming communities and current hypotheses point toward many environmental and occupational triggers. CKDu does not have common etiologies of chronic kidney disease (CKD) such as hypertension, diabetes, or autoimmune disease. We aimed to understand the molecular processes underlying CKDu in Sri Lanka using transcriptome analysis. MethodsRNA extracted from whole blood was reverse transcribed and used for microarray analysis using the Human HT-12 v.4 array (Illumina). Pathway analysis was carried out using ingenuity pathway analysis (IPA—Qiagen). Microarray results were validated using real-time PCR of five selected genes. ResultsPathways related to innate immune response, including interferon signaling, inflammasome signaling and TREM1 signaling had the most significant positive activation z scores, where as EIF2 signaling and mTOR signaling had the most significant negative activation z scores. Pathways previously linked to fluoride toxicity; G-protein activation, Cdc42 signaling, Rac signaling and RhoA signaling were activated in CKDu patients. The most significantly activated biological functions were cell death, cell movement and antimicrobial response. Significant toxicological functions were mitochondrial dysfunction, oxidative stress and apoptosis. Conclusions Based on the molecular pathway analysis in CKDu patients and review of literature, viral infections and fluoride toxicity appear to be contributing to the molecular mechanisms underlying CKDu.
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Background: High fluoride levels in drinking water in relation to the prevalence of chronic kidney disease of unknown etiology (CKDu) in Sri Lanka were investigated using rats as an experimental model. Method: The effects of fluoride after oral administration of Sodium fluoride (NaF) at levels of 0, 0.5, 5 and 20 ppm F- were evaluated in adult male Wistar rats. Thirty-six rats were randomly divided into 4 groups (n = 9), namely, control, test I, II, and III. Control group was given daily 1 ml/rat of distilled water and test groups I, II, and III were treated 1 ml/rat of NaF doses of 0.5, 5, and 20 ppm, respectively, by using a stomach tube. Three rats from the control group and each experimental group were sacrificed after 15, 30, and 60 days following treatment. Serological and histopathological investigations were carried out using blood, kidney, and liver. Results: No significant differences were observed in body weight gain and relative organ weights of the liver and kidney in fluoride-treated groups compared to control group. After 60 days of fluoride administration, group I showed a mild portal inflammation with lytic necrosis while multiple areas of focal necrosis and various degrees of portal inflammation were observed in groups II and III. This was further confirmed by increased serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), and alkaline phosphatase (ALP) activities. As compared with control and other treated groups, group III showed a significantly higher serum AST activity (p < 0.05) and ALT activity (p < 0.05) after 60 days and ALP activity with a significant difference (p < 0.05) after 15, 30, and 60 days. The renal histological analysis showed normal histological features in all groups with the elevated serum creatinine levels in group III compared to those in the groups I and II (p < 0.05) after 60 days. Significantly elevated serum fluoride levels were observed in group II of 30 and 60 days and group III after 15, 30, and 60 days with respective to control groups (p < 0.05). Conclusion: Taken together, these findings indicate that there can be some alterations in liver enzyme activities at early stages of fluoride intoxication followed by renal damage.
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The elevated fluoride from drinking water impacts on T3, T4 and TSH hormones. The aim was study impacts of drinking water fluoride on T3, T4 and TSH hormones inYGA (Yazd Greater Area). In this case- control study 198 cases and 213 controls were selected. Fluoride was determined by the SPADNS Colorimetric Method. T3, T4 and TSH hormones tested in the Yazd central laboratory by RIA (Radio Immuno Assay) method. The average amount of TSH and T3 hormones based on the levels of fluoride in two concentration levels 0-0.29 and 0.3-0.5 (mg/L) was statistically significant (P = 0.001 for controls and P = 0.001 for cases). In multivariate regression logistic analysis, independent variable associated with Hypothyroidism were: gender (odds ratio: 2.5, CI 95%: 1.6-3.9), family history of thyroid disease (odds ratio: 2.7, CI 95%: 1.6-4.6), exercise (odds ratio: 5.34, CI 95%: 3.2-9), Diabetes (odds ratio: 3.7, CI 95%: 1.7-8), Hypertension (odds ratio: 3.2, CI 95%: 1.3-8.2), water consumption (odds ratio: 4, CI 95%: 1.2-14). It was found that fluoride has impacts on TSH, T3 hormones even in the standard concentration of less than 0.5 mg/L. Application of standard household water purification devices was recommended for hypothyroidism.
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Fluorosis is a public health problem in India; to know its prevalence and severity along with its mitigation measures is very important. The present study has been undertaken with the aim to assess the F dose-dependent clinical and subclinical symptoms of fluorosis and reversal of the disease by providing safe drinking water. For this purpose, a cross-sectional study was undertaken in 1934 schoolgoing children, Nalgonda district. Study villages were categorized into control (category I, F = 0.87 mg/L), affected (category II, F = 2.53 mg/L, and category III, F = 3.77 mg/L), and intervention categories (category IV, F = < 1.0 mg/L). School children were enrolled for dental grading by modified Dean Index criteria. Anthropometric measurements (height and weight) were used to assess nutritional status of the children. The biochemical parameters like serum T3, T4, TSH, PTH, ALP, 25-OH vitamin D, and 1,25-(OH)2 vitamin D were analyzed. The results showed a positive correlation between the drinking water and urinary fluoride (UF) in different categories. However, there was a significant decrease in the UF levels in the intervention category IV compared to affected group (category III). Fluoride altered the clinical (dental fluorosis and stunting) and subclinical indices (urine and blood) of fluorosis in a dose-dependent manner. In conclusion, the biochemical indices were altered in a dose-dependent manner and intervention with safe drinking water for 5 years in intervention group-mitigated clinical and subclinical symptoms of fluorosis.
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Fluoride (F) is a toxicant widely distributed in the environment. Experimental studies have shown kidney toxicity from F exposure. However, co-exposure to arsenic (As) has not been considered, and epidemiological information remains limited. We evaluated the association between F exposure and urinary kidney injury biomarkers and assessed As co-exposure interactions. A cross-sectional study was conducted in 239 adults (18-77 years old) from three communities in Chihuahua, Mexico. Exposure to F was assessed in urine and drinking water, and As in urine samples. We evaluated the urinary concentrations of albumin (ALB), cystatin-C (Cys-C), kidney injury molecule 1 (KIM-1), clusterin (CLU), osteopontin (OPN), and trefoil factor 3 (TFF-3). The estimated glomerular filtration rate (eGFR) was calculated using serum creatinine (Creat) levels. We observed a positive correlation between water and urine F concentrations (ρ = 0.7419, p < 0.0001), with median values of 1.5 mg/L and 2 μg/mL, respectively, suggesting that drinking water was the main source of F exposure. The geometric mean of urinary As was 18.55 ng/mL, approximately 39% of the urine samples had As concentrations above the human biomonitoring value (15 ng/mL). Multiple linear regression models demonstrated a positive association between urinary F and ALB (β = 0.56, p < 0.001), Cys-C (β = 0.022, p = 0.001), KIM-1 (β = 0.048, p = 0.008), OPN (β = 0.38, p = 0.041), and eGFR (β = 0.49, p = 0.03); however, CLU (β = 0.07, p = 0.100) and TFF-3 (β = 1.14, p = 0.115) did not show significant associations. No interaction with As exposure was observed. In conclusion, F exposure was related to the urinary excretion of early kidney injury biomarkers, supporting the hypothesis of the nephrotoxic role of F exposure.
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The susceptibility of the kidneys to fluoride toxicity can largely be attributed to its anatomy and function. As the filtrate moves along the complex tubular structure of each nephron, it is concentrated in the proximal and distal tubules and collecting duct. It has been frequently observed that the children suffering from renal impairments also have some symptoms of dental and skeletal fluorosis. The findings suggest that fluoride somehow interferes with renal anatomy and physiology, which may lead to renal pathogenesis. The aim of this study was to evaluate the fluoride-associated nephrotoxicity. A total of 156 patients with childhood nephrotic syndrome were screened and it was observed that 32 of them had significantly high levels (p ≤ 0.05) of fluoride in urine (4.01 ± 1.83 ppm) and serum (0.1 ± 0.013 ppm). On the basis of urinary fluoride concentration, patients were divided into two groups, namely group 1 (G-1) (n = 32) containing normal urine fluoride (0.61 ± 0.17 ppm) and group 2 (G-2) (n = 32) having high urine fluoride concentration (4.01 ± 1.83 ppm). Age-matched healthy subjects (n = 33) having normal levels of urinary fluoride (0.56 ± 0.15 ppm) were included in the study as control (group 0 (G-0)). Kidney biopsies were taken from G-1 and G-2 only, who were subjected to ultrastructural (transmission electron microscopy) and apoptotic (terminal deoxynucleotidyl transferase deoxyuridine triphosphate nick end labeling) analysis. Various subcellular ultrastructural changes including nuclear disintegration, chromosome condensation, cytoplasmic ground substance lysis, and endoplasmic reticulum blebbing were observed. Increased levels of apoptosis were observed in high fluoride group (G-2) compared to normal fluoride group (G-1). Various degrees of fluoride-associated damages to the architecture of tubular epithelia, such as cell swelling and lysis, cytoplasmic vacuolation, nuclear condensation, apoptosis, and necrosis, were observed.
Article
Background: Effects of variations in thyroid function within the euthyroid range on renal function are unclear. Cystatin C-based equations to estimate glomerular filtration rate (GFR) are currently advocated for mortality and renal risk prediction. However, the applicability of cystatin C-based equations is discouraged in patients with overt thyroid dysfunction, since serum cystatin C and creatinine levels are oppositely affected by thyroid dysfunction. Here, we compared relationships of thyroid stimulating hormone (TSH), free thyroxine (FT4) and free triiodothyronine (FT3) with various measures of kidney function in euthyroid subjects. Methods: Relationships of eGFR, based on creatinine (eGFRcrea), cystatin C (eGFRcysC), creatinine+cystatin C combined (eGFRcrea-cysC) and creatinine clearance (CrCl) with TSH, FT4 and FT3 were determined in 2180 euthyroid subjects (TSH, FT4 and FT3 all within the reference range; anti-thyroid peroxidase autoantibodies negative) who did not use thyroid hormones, anti-thyroid drugs, amiodarone or lithium carbonate. Results: In multivariable models including TSH, FT3 and FT4 together, eGFRcrea, eGFRcysC and eGFRcrea-cysC and CrCl were all positively related to FT3 (P≤0.001), translating into a 2.61 to 2.83mL/min/1.73m(2) increase in eGFR measures and a 3.92mL/min increase in CrCl per 1pmol/L increment in FT3. These relationships with FT3 remained taking account of relevant covariates. Conclusions: In euthyroid subjects renal function is associated with thyroid function status, especially by serum FT3, irrespective of the eGFR equation applied. In the euthyroid state, cystatin C-based eGFR equations are appropriate to assess the relationship of renal function with variation in thyroid function status.