The physiological determinants of low-level urine cadmium: an assessment in a cross-sectional study among schoolchildren
Wang et al. Environmental Health
The physiological determinants of low-level urine cadmium: an assessment in a cross- sectional study among schoolchildren
Hongyu Wang 0
Xavier Dumont 0
Vincent Haufroid 0
Alfred Bernard 0
0 Louvain Centre for Toxicology and Applied Pharmacology, Institut de Recherche Expérimentale et Clinique (IREC), Université catholique de Louvain , Avenue Emmanuel Mounier 53.02, B-1200 Brussels , Belgium
Background: Recent studies in children have reported associations of urinary cadmium (U-Cd), used as biomarker of Cd body burden, with renal dysfunction, retarded growth and impaired cognitive development in children. Little is known, however, about factors influencing U-Cd in children and likely to act as confounders. Methods: In a cross-sectional study involving 249 schoolchildren (mean age, 5.72 years; 138 boys), we measured the urine concentrations of cadmium, zinc, lead, albumin, alpha1-microglobulin (A1M), retinol-binding protein, β2-microglobulin and club cell protein (CC16). Determinants of U-Cd expressed per creatinine or adjusted to specific gravity were identified by multiple regression analyses. Results: Girls and boys had similar median concentrations of U-Cd (0.22 and 0.24 μg/L, 0.33 and 0.35 μg/g creatinine, respectively). When models were run without including creatinine or specific gravity among independent variables, urinary zinc, urinary A1M and age emerged as the strongest predictors of U-Cd expressed per g creatinine or adjusted to SG. When adding creatinine among predictors, urinary creatinine emerged as an additional strong predictor correlating negatively with U-Cd per g creatinine. This strong residual influence of diuresis, not seen when adding specific gravity among predictors, linked U-Cd to U-A1M or U-CC16 through secondary associations mimicking those induced by Cd nephrotoxity. Conclusions: In young children U-Cd largely varies with diuresis, zinc metabolism and urinary A1M. These physiological determinants, unrelated to Cd body burden, may confound the child renal and developmental outcomes associated with low-level U-Cd.
Cadmium; Biomarker; Club cell protein; alfa1-microglobulin; Protein HC; Retinol-binding protein; β2-microglobulin
Cadmium (Cd) is a highly toxic and cumulative metal
that after long term exposure can cause serious health
effects, including renal dysfunction, bone demineralization
and by inhalation lung cancer. Diet and tobacco smoke
are the main sources of human exposure to Cd [
absorbed by inhalation or ingestion, Cd accumulates over
lifetime in the body, especially in the kidneys, with a
biological half-life of more than 15 years [
]. The kidney,
the main site of Cd storage, is generally considered to be
also the critical target organ i.e. the first organ to be
damaged after prolonged exposure. The earliest nephrotoxic
effect of Cd is a dysfunction of the proximal tubule, resulting
in an increased urinary excretion of low-molecular-weight
(LMW) proteins, such as retinol-binding protein,
alpha1microglobulin or β2-microglobulin [
]. This LMW
proteinuria, also referred to as tubular proteinuria, is due
to the decreased reabsorption capacity of defective
proximal tubular cells .
An important concept in Cd risk assessment is the
assumption that U-Cd is a reliable non-invasive measure
of the amount of metal stored in the body. As explained
], international regulatory bodies recently
endorsed this concept when establishing the tolerable
dietary intakes or occupational exposures to Cd. The
vast majority of epidemiological studies also relied on
this concept when implicating low-level Cd exposure as
a risk factor for bone, cardiovascular and other
degenerative diseases [
]. In these studies, the use of U-Cd as
indicator of Cd body burden is an argument for excluding the
possibility of reverse causation since in most cases the
studied outcomes (e.g. renal or developmental effects) are
unlikely to increase the body burden of the heavy metal.
Of concern, recent research suggests that Cd can exert its
toxicity during the first years of life and this at the
exposure levels prevailing in most industrialized countries.
Several studies among children with low dietary exposure
to Cd have indeed associated an increase of U-Cd with
renal dysfunction (decreased glomerular filtration rate and
increased proteinuria), retarded growth and impaired
cognitive development (learning disability, special education
utilization, cognitive delays) [
However, the significance of U-Cd as an index of
cumulative exposure to the metal is now called into question by
studies revealing that low-level U-Cd of adults or
adolescents is predominantly influenced by factors unrelated to
Cd body burden such as recent exposure, urinary flow or
the co-excretion of Cd with urinary proteins [
Particularly challenging is the finding that children have
UCd values comparable to those of adults despite a Cd body
burden about ten times lower . These findings raise
doubt about the significance of low-level U-Cd in children
and therefore about the significance of associations seen
with this exposure measure. Therefore, the purpose of this
study was to investigate the physiological and
environmental factors that influence U-Cd levels in children with low
background exposure to the heavy metal.
Study participants were 249 children (138 boys, mean
age, 5.75 years) in the third year of kindergarten. These
children were recruited from 30 schools located in Belgium
in the framework of an epidemiological study investigating
the effects of various environmental stressors on child’s
health. The origin of children, the recruitment protocol and
the participation rate are described in detail elsewhere [
Children participated to the study with their assent and
the informed consent of their parents. A parent
selfadministered questionnaire was used to obtain
information about children health and factors likely to impact
on kidney function or to be sources of Cd exposure.
Examinations of children, which took place in schools,
included the measurement of body weight and height
and the collection of an untimed urine sample. Children
were examined between 9:00 A.M. and 3:00 P.M., and in
most cases (n = 219) urine was collected before noon.
Samples of urine were collected in Cd-free containers and
stored at −20 °C until analysis. The study population did
not include seven children who were removed because
their U-Cd (n = 3) or urinary creatinine (n = 4) deviated by
more than three geometric SDs from the geometric mean
in the initial population. There were no reports of diabetes
or renal disease among study participants. The Ethics
Committee of the Faculty of Medicine of the Catholic University
of Louvain approved the study protocol that complied with
applicable requirements of international regulations.
We measured Cd, Pb and Zn in urine by inductively
coupled argon plasma mass spectrometry (ICP-MS) with
an Agilent 7500 instrument (Agilent Technologies. Santa
Clara, CA, USA), as described in a previous study [
Briefly, urine specimens (500 μl) were diluted
quantitatively [1 + 9 (vol/vol)] with a 1% nitric acid/0.5%
hydrochloric acid solution containing scandium, germanium,
rhodium and iridium as internal standards. As described
] our Cd analyses by ICP-MS were
unaffected by the interference from molybdenum. The
detection and quantification limits were respectively 0.02 and
0.05 μg/L for Cd, 0.03 and 0.09 μg/L for Pb and 0.6 and
1.8 μg/L for Zn. The accuracy of our method for Cd
measurement was ascertained by the participation to the
University of Erlangen quality assurance program. For the
periods of 2011–2014 corresponding to the measurements
performed in this study, the results of U-Cd (μg/L) vs. the
reference value were as follow: low U-Cd, 0.21 vs. 0.22,
0.30 vs. 0.30, 0.25 vs. 0.22, 0.29 vs. 0.25, 0.20 vs. 0.19; high
U-Cd, 0.69 vs. 0.65, 0.78 vs. 0.81, 0.50 vs. 0.47, 0.71 vs.
0.65, 0.61 vs. 0.60. The compliance with reference values
averaged 106% (SD, 8.7) for low values and 104% (SD, 5.1)
for high values of U-Cd. A similar compliance with
references values was obtained for the determination of Pb and
Zn (results not shown). The urinary concentrations of
β2microglobulin (U-β2m), alpha1-microglobulin (U-A1M),
club cell protein (U-CC16), retinol-binding protein
(URBP) and albumin (U-Alb) were determined by automated
latex immunoassays using Dakopatts antibodies and
standards based on commercially available proteins or on
proteins purified in our laboratory [
]. Because of
insufficient urine volume, we could not measure U-β2m in
11 samples, U-CC16 in 50 samples and urinary lead
(UPb) in one sample. We also excluded from the analyses of
U-CC16 another 17 samples with undetectable values
even though including them with the immunoassay
detection limit yielded the same pattern of significant
associations. Creatinine in urine (U-Creat) was determined by a
modified Jaffé reaction using a Beckman Synchron LX 20
analyser (Beckman Coulter GmbH, Krefeld, Germany)
. Specific gravity of urine (SG) was determined with
a refractometer and concentrations were transformed
to the mean value of urinary density in the studied group
(1.021 g/mL) by using the formula: CSG = Cm × 0.021/
(SG − 1.000) where CSG is the adjusted value for SG and
Cm is the measured concentration [
]. The laboratory is
ISO15189 certified for the measurement of 20 trace
elements in urine, including Cd, Zn and Pb.
Data analyses were performed using version 12 of the
JMP (SAS Institute Inc., Cary, NC, USA). All
characteristics and biological parameters in urine were described
as median with interquartile range (IQR) and were
log-transformed to approximate normal distribution.
To adjust for variations in urine dilution, urinary
biomarkers were expressed per g of creatinine or adjusted
to U-SG. Student’s t-test was used to assess gender
differences with regard to biomarkers and their potential
predictors. Associations between variables were evaluated
by Pearson’s correlation analysis. Determinants of U-Cd
were assessed by backward stepwise regression analyses
testing as potential predictors age, gender, parental
smoking, body mass index (BMI), time of urine
collection, urinary zinc (U-Zn), U-Alb, a LMW protein in
urine (U-RBP, U-β2−m, U-A1M or U-CC16). We run
these models by testing five methods to account for the
influence of diuresis. In the first method, the urinary
concentrations of heavy metals and proteins were expressed
per g of creatinine. In the second method, metals and
proteins in urine were also expressed per g of creatinine but
we added U-Creat as a separate independent variable to
remove the possible residual influence of diuresis as
evaluated by U-Creat. In the third method, we expressed metals
and proteins in urine per liter and tested U-Creat as a
separate independent variable as recommended by Barr et al.
]. In the fourth method, urinary metals and proteins
were adjusted to SG. In the fifth method, we expressed
metals and proteins in urine per liter and we added U-SG
as a separate independent variable. We optimized these
models by minimizing the Akaike information criterion. To
further explore the confounding effect of diuresis, we
compared by ANOVA with the Dunnett’s post-hoc test the
urinary excretion of LMW proteins across quartiles of
increasing U-Cd expressed per g of creatinine, without and
with further adjusting these biomarkers for their residual
association with U-Creat. All P-values were two-sided with
the level of statistical significance at P < 0.05.
Characteristics of children and the concentrations of
metals in urine are summarized in Table 1. The mean
age of the studied group was 5.72 years and 55.4% of
them were boys. Boys had significantly higher U-Creat
and U-SG than girls. Boys also had higher U-Pb but this
difference disappeared after adjustment with creatinine
or SG. There were, by contrast, no gender differences in
aGirls, n = 110; boys, n = 138. Values are median (interquartile range)
U-Cd and U-Zn whatever the method used for urine
dilution adjustment. As displayed in Table 2, the two
sexes had also very similar levels of U-RBP, U-β2m and
U-CC16. Girls, however, had higher U-Alb than boys
while their U-A1M was lower.
Table 3 shows the univariate associations between heavy
metals, renal biomarkers and their potential predictors for
urinary biomarkers expressed per g creatinine (Table 3) or
after adjustment with U-SG (Table 3). Although the values
of U-SG and U-Creat were highly correlated (r = 0.84,
P < 0.001), there were noticeable differences in the
correlation patterns according to the method of adjustment for
urine dilution. When expressed per g of creatinine, U-Cd,
U-A1M, U-CC16 and U-β2m correlated negatively with
U-Creat and in some cases even with U-SG (Table 3). This
suggests, as illustrated in Fig. 1, that dividing by U-Creat
does not completely abolish the associations of these
urinary biomarkers with U-Creat but rather changes its
direction from a positive into a negative one. Of note, there
were virtually no differences in this correlation inversion
between girls and boys at the exception of U-A1M, for
which this phenomenon occurred mainly in girls. Such
residual influence of diuresis after dividing by U-Creat
was not observed with U-RBP and U-Alb, neither with
UPb and U-Zn. Interestingly, the over-adjustment with
creatinine is linked to the β coefficient of the log-log
regression of the biomarker concentration per liter with
U-Creat. For those biomarkers expressed per g creatinine
showing no residual correlation with U-Creat, this β
coefficient was close to one: U-Zn, 0.92; U-Pb, 0.95 and
U-RBP, 0.94 (r = 0.66, 0.59 and 0.66 respectively, all
P < 0.001). By contrast for biomarkers with a strong
inverse correlation with U-Creat, this β coefficient was
much lower: U-Cd, 0.71; U-A1M, 0.73; U-β2m, 0.43;
UCC16, 0.36 (r = 0.67, 0.44, 0.44 and 0.14, respectively, all
P < 0.001 except for U-CC16, P = 0.06). As expected, the
four LMW urinary proteins correlated with each other
but none of them correlated with U-Alb. The only
statistically significant correlations between the concentrations
per g creatinine of the three heavy metals (U-Cd, U-Zn
and U-Pb) and urinary proteins were those linking U-Cd
to U-A1M or U-CC16.
As shown in Table 3, the adjustment on the basis of
U-SG apparently abolished the influence of diuresis on
U-Cd and LMW proteins since the SG-adjusted values
of these biomarkers showed no residual correlation with
U-SG. However, one should not infer from this finding
that the adjustment with U-SG better corrects for
variations in diuresis than the adjustment based on U-Creat.
Actually, in some cases, it might be the opposite as the
SG-adjusted concentrations of U-RBP, U-Cd, U-Zn and
U-Pb showed strong positive correlations with U-Creat
(Table 3). Such residual associations were not seen or
were less strong when correlating biomarkers per g
creatinine with U-SG (Table 3). Of note, U-RBP correlated
positively with both U-Zn and U-Pb after adjustment
with U-SG but not when expressed per g creatinine,
which is the consequence of this under-adjustment with
Determinants of U-Cd were identified by multiple
regression analyses testing as potential predictors gender,
age, BMI, parental smoking, U-Zn, U-Alb and, in
separate models, U-A1M, U-RBP, U-β2m or U-CC16. We run
these four models by testing five methods of adjustment
for urine dilution: 1) U-Cd per g of creatinine, 2) U-Cd
per g of creatinine with U-Creat added as separate
independent variable 3) U-Cd per liter with U-Creat added
as separate independent variable 4) U-Cd adjusted on
the basis of U-SG and 5) U-Cd per liter with U-SG
added as separate independent variable. As shown in
Table 4, in models expressing U-Cd per g of creatinine
without any further adjustment, U-Zn emerged as the
strongest predictor of U-Cd. Among LMW proteins, it is
U-A1M that correlated the most strongly with U-Cd
followed by U-CC16, U-RBP and U-β2m. Age was retained
in all models except in the models run with U-CC16. When
further adjusting U-Cd for the residual negative correlation
with U-Creat, U-Creat and U-Zn consistently emerged
as the main determinants of U-Cd. With this
additional adjustment, associations with age, if anything,
were strengthened while associations with proteins
were weakened, U-A1M and U-RBP being the only
LMW proteins retained in the models. The same
associations were observed when running these models with
UCd and other urinary analytes expressed per liter and with
U-Creat added to independent variables (Table 4). Figure 2
illustrates the influence of these determinants on U-Cd in
the A1M model that best explains the variance of U-Cd.
We observed similar patterns of associations in the
SGbased models, whether adjusting all urinary
concentrations with U-SG or adding U-SG to independent variables
and expressing urinary concentrations per liter (Table 5).
Virtually the same associations were also observed with
U-Cd adjusted with U-SG or with U-Creat and in both
cases by adding U-SG or U-Cd to independent urinary
variables expressed per liter (results not shown).
We completed our analyses by examining to what extent
the creatinine over-adjustment of U-Cd and U-LMW
proteins can be a source of confounding when using these
biomarkers to assess renal effects of Cd. As shown in Fig. 3,
expressed per g creatinine, U-A1M and U-CC16 increase
dose-dependently across quartiles of U-Cd, reaching the
level of statistical significance from a median U-Cd of 0.53
and 0.39 μg/g creatinine, respectively (ANOVA, P = 0.04
and 0.02). After further adjusting these biomarkers for
their residual univariate correlation with U-Creat, these
dose-response relationships lose their statistical
significance (ANOVA, P = 0.17 and 0.06, respectively). These
relationships were similarly abolished when further
adjusting U-Cd for U-Zn and its other covariates (Table 4)
(ANOVA, P = 0.14 and 0.31, respectively).
Researchers on environmental health increasingly utilize
urinary biomarkers to characterize exposures.
Associations between chronic diseases and biomarker levels can
be interpreted as possibly causal on the condition that
the amount of chemical found in urine accurately
reflects the long term exposure to the toxic substance
under study. It is also important to ensure that the level
of biomarker is not influenced by studied outcomes, in
which case this would be a source of spurious
associations. All these issues are especially critical for U-Cd, a
biomarker that most epidemiologists and regulatory
bodies rely on to assess lifetime exposure to the metal.
In addition, as Cd primarily targets the kidney, there is
the challenge of distinguishing associations of U-Cd with
renal biomarkers that are caused by Cd nephrotoxicity
from associations that reflect the influence of renal
function on the excretion of the metal [
11, 27, 28
Regarding the physiological confounders of U-Cd, our
study confirms that the concentrations of U-Cd are
substantially altered by the method used for urine
concentration adjustment [
]. Expressed per liter, U-Cd
shows a strong positive correlation with U-Creat, which
makes indispensable an adjustment for the hydration
status. However, as previously reported [
12, 17, 28
positive correlation turns into a negative one when
UCd is expressed per g creatinine. This means that
dividing the concentration of U-Cd by that of creatinine, as
systematically done in most studies, does not completely
abolish the influence of diuresis but simply reverses its
direction. The important new finding made in our study
is that such a correlation inversion also occurs with
LMW proteins at the exception of U-RBP. Associations
of U-A1M, U-CC16 and U-β2m with U-Creat, initially
positive, also turned negative when expressing the
concentrations per g creatinine. This phenomenon is a
source of confounding as it links U-Cd to LMW urinary
proteins, in particular A1M and U-CC16, through
secondary associations due to physiological variations
unrelated to Cd nephrotoxicity. The risk of confounding is
especially high, as these associations resemble those
induced by high Cd exposure, presenting a U-Cd threshold
above which LMW proteins increase in a dose-dependent
manner. As almost all studies on the renal effects of Cd
were based on Cd and LMW proteins in urine expressed
per g of creatinine, this raises the question to what extent
associations reported in these studies were distorted if not
generated by physiological variations in diuresis. Of course
this is especially relevant for associations with low U-Cd
but the possibility of a dose-response relationship distortion
at high doses of Cd cannot be excluded. Adjusting for
USG does not appear to be the ideal alternative since in that
case U-Cd remained positively associated with U-Creat,
testifying to an insufficient adjustment for urine dilution.
Different methods can be used to avoid confounding by
diuresis. When U-Cd is expressed per g of creatinine, the
residual association with U-Creat can be eliminated by
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further adjusting U-Cd to creatinine on the basis the
regression coefficient between the two variables. Currently,
the most recommended method is that of Barr et al. [
which U-Cd is expressed per liter and adjusted with
creatinine on the basis of the regression coefficient between
the two analytes. For multiple regression analysis of
population groups, this can also be done by including U-Cd and
U-Creat, expressed per liter, among independent variables,
which allows to build a model in which associations are
independent of the effects of urine concentration.
Our study provides further insight into the mechanisms
underlying the co-excretion of U-Cd with urinary proteins
as described in recent studies [
14, 15, 17
]. In essence, this
mechanism relies on the fact that Cd is excreted in urine as
a complex with metallothionein (Mt), a LMW protein that
follows the same glomerular filtration-tubular reabsorption
pathway as other proteins, including the LMW proteins
used for screening Cd nephrotoxicity [
]. We previously
hypothesized that the associations of low-level U-Cd with
LMW proteins were the reflection of the physiological
variations in the protein reabsorption capacity of
proximal tubules [
]. The present study demonstrates that,
as suggested by Akerstrom et al. [
], for some
proteins, this co-excretion is to a large extent driven by
variations in urinary flow as estimated by U-Creat. In
multiple regression analyses, introducing U-Creat among
independent variables noticeably weakened the associations
of U-Cd with U-A1M while that with U-CC16 lost its
statistical significance. In univariate analyses, also, further
adjusting U-Cd for the residual association with U-Creat
abolished the dose-dependent increase of U-A1M and
UCC16 with increasing U-Cd. Another mechanism that we
postulated is a competitive inhibition of the tubular
reabsorption of Cd-metallothionein (Cd-Mt) by filtered
plasma proteins. Such a mechanism might explain why
associations of U-Cd are much stronger with U-A1M and
U-CC16 than with U-RBP and U-β2m. The reabsorption of
proteins by the proximal tubule is indeed a high capacity,
low affinity and saturable process in which proteins
compete with each other according to their affinity for the
tubular binding sites (mainly determined by their net positive
charge) and their relative concentration in tubular fluid
. The concentration of A1M in tubular fluid is
approximately three orders of magnitude higher than that of CC16
or Cd-Mt. against about only one order of magnitude
higher than that of RBP or β2m. Because of these huge
differences in concentrations, CC16 and Cd-Mt. are
conceivably much more easily displaced from tubular binding
sites by A1M than are RBP and β2m. In other words, the
correlation of U-Cd with U-A1M and U-CC16 would be
the consequence of the competitive inhibition of CC16 and
Cd-Mt. reabsorption by high filtered load of A1M.
Among determinants of U-Cd unrelated to the renal
function, we identified U-Zn as the most significant
All parameters except age were log transformed. Independent variables measured in urine were expressed in the same units as U-Cd. For models built with variables
adjusted to U-SG, the highest variance inflation factors (VIF) were 1.001 (U-A1M) in the model with U-A1M, 1.053 (U-Zn) in the model with U-RBP, 1.001 (U-Zn and age)
in the model with U-β2-m and 1.005 (U-Zn and U-CC16) in the model with U-CC16. For the models built with U-Cd in μg/l with U-SG among predictors, the highest VIF
values were 1.98 (U-SG) in the model with U-A1M, 2.05 (U-SG) in the model with U-RBP, 1.86 (U-SG) in the model with U-β2-m and 1.85 (U-SG) in the
model with U-CC16. Contrarily to what is observed with U-Creat, there is no residual correlation between SG-adjusted U-Cd and U-SG, which explains that
adding U-SG among independent variables does not change the models based on variables adjusted U-SG
predictor. This association, reported in the adult general
population in Japan [
], is not really surprising as
the two metals are frequently associated in foodstuffs
and also share the same intestinal transporters [
Unlike the co-excretion of Cd with proteins, that between
U-Cd with U-Zn does not seem to be driven by common
renal excretion mechanisms. Although Cd-Mt. transports
some Zn, the proportion of U-Zn bound to this protein in
urine is much too low to explain this co-excretion. In
addition, we found no correlation between U-Zn and
urinary proteins, including albumin, which is the main
Zn-transporting protein in plasma. The explanation for
the co-excretion of the Zn and Cd might thus lie in the
homeostatic regulation of Zn intestinal transporters
that are opportunistically used by Cd. Previous studies,
indeed, have shown that Zn intake or serum Zn
correlates negatively with the concentrations of Cd in blood
or urine, presumably because of a down-regulation of
the intestinal Zn transporters at high Zn intake [
The positive correlation between U-Cd and U-Zn seen in
our study might be explained by the opposite effect i.e. an
up-regulation of the intestinal Zn transporters to meet the
important Zn needs of growing children. This explanation
might also hold for the positive correlation between U-Cd
and U-Zn observed in Japanese populations whose Zn
requirements are not completely satisfied by rice, a staple
food poor in Zn. Because Zn is an essential nutrient for
child growth and development, associations between U-Cd
and outcomes such as retarded growth or developmental
outcomes should be interpreted with caution [
associations might well be secondary to the up-regulation
of Zn transporters to meet Zn requirements of the growing
child, especially when they are found in poorly nourished
children subsisting mainly on rice [
Despite the narrow age range of our children, U-Cd was
weakly but consistently associated with age. Traditionally,
this increase of U-Cd with age is interpreted as the
evidence that U-Cd reflects the accumulation of the metal in
the body. Assuming that this is the case, it is clear that the
contribution of Cd body burden to the U-Cd of children is
completely blunted by the influence of other covariates.
The U-Cd of our children was indeed similar and when
adjusted for U-creatinine even higher than values we
recently found in middle age adults in Belgium, despite a Cd
body burden at least a five times lower [
]. Of interest, in
very young children, U-Cd was not influenced by gender,
body mass index or passive exposure to tobacco smoke.
There were also no gender-differences in the residual
associations of U-Creat with creatinine-adjusted values of
urinary Cd and LMW proteins. The only exception concerned
U-A1M for which the residual association with U-Creat
was much stronger in girls than in boys. The reason for
such difference is unknown but it would be interesting to
determine if this potential source of confounding is relevant
for adults as according some studies U-A1M might be a
more sensitive indicator of Cd nephrotoxicity than U-RBP
or U-β2m [
In addition to the risk of confounding by physiological
determinants of U-Cd, there is also a risk a
misinterpretation or misclassification due to analytical biases. The
accuracy of our U-Cd measurements was ascertained
by the results of our participation to external quality
assurance programs that showed a very good compliance
with reference values. Our values of U-Cd (median, girls,
0.22 μg/L; boys, 0.24 μg/L) were almost identical to values
in Belgian adolescents reported by us (mean age, 15.4 years;
median, girls, 0.27 μg/L and boys, 0.24 μg/L) or by
Vryens et al. [
] (mean age, 14.8 years; geometric
mean, 0.24 μg/L). Similar values were observed in children
living in industrial areas in southwestern Spain (geometric
mean, 0.22 μg/L) [
]. By contrast, these values in Belgium
and Spain were about 4 times higher than those found in
children of the COPHES/DEMOPHES European project
(5–11 years, geometric mean of U-Cd adjusted for age,
gender and U-Creat, 0.071 μg/L) [
]. Quite surprisingly,
in the European project, values of U-Cd for Belgian
children were approximately 4 times lower than our
values when expressed per liter (0.05 vs. 0.23) and almost
7 times lower when expressed per g of creatinine (0.05 vs.
0.34). By contrast, the mothers of these children had
U-Cd values (median, 0.22 μg/L) comparable to values
we reported for Belgian adults (median, 0.28 μg/L) if
one takes into account that the proportion of current
smokers was higher in our study than in the Belgian
cohort of the European project (24.1% vs. 9.3%). It should
be noted that in the COPHES/DEMOCOPHES project the
median U-Cd values of children in Western Europe varied
widely by a factor up to seven when comparing Denmark
(0.024 μg/L) with United Kingdom (0.167 μg/L) [
between two small border countries like Belgium and
Luxembourg, median U-Cd levels of children differed by a
factor of three (0.046 and 0.154 μg/L, respectively) despite
very similar U-Cd values for their mothers (0.224 μg/L and
0.249 μg/L, respectively). Furthermore, according to the
COPHES/DEMOCOPHES project, Belgian children would
be among the less exposed to Cd in Europe, which is
astonishing given the important historical pollution of
Belgium by non-ferrous smelters. As Cd analyses in the
European project were performed by 15 different
laboratories, we think that these inconsistencies in the U-Cd
values of European children are more likely to be
explained by an insufficient analytical harmonization than
by true differences in Cd exposure related to the
environment or nutritional status.
The strongest determinants of U-Cd expressed per g
creatinine or adjusted to SG, are U-Zn, age and LMW
proteins in urine, especially A1M and CC16. The adjustment
for urine dilution with creatinine, but not with SG, linked
U-Cd to U-A1M or U-CC16 through secondary
associations that may be confused with those induced by Cd
nephrotoxicity. These physiological influences on U-Cd of
young children might confound the renal and
developmental effects seen at low-level U Cd.
BMI: body mass index; Cd-Mt.: cadmium-metallothionein; IQR: interquartile
range; LMW: low molecular weight; U-A1M: alpha1-microglobulin in urine;
U-Alb: albumin in urine; U-CC16: club cell protein in urine; U-Cd: cadmium
in urine; U-Creat: creatinine in urine; U-RBP: retinol-binding protein; U-SG: specific
gravity of urine; U-Zn: zinc in urine; U-β2m: β2-microglobulin in urine
Alfred BERNARD is Research Director of the National Fund for Scientific
Research, Belgium. Hongyu WANG was Research Fellow of the Erasmus
Mundus Panacea Programme (Action 2 Project with Asia). We thank Mrs.
Gladys DEUMER for her technical assistance in metals determination.
This study was supported by the Belgian Science Policy (ANIMO project).
Availability of data and materials
Please contact author for data requests.
HW and AB wrote the manuscript. AB provided the scientific guidance of the
project, participating to the study design, analysis of the data and interpretation
of the results. XD and VH were responsible for the analyses of biomarkers.
All authors read and approved the final manuscript.
Ethics approval and consent to participate
The Ethics Committee of the Faculty of Medicine of the Catholic University
of Louvain approved the study protocol that complied with applicable
requirements of international regulations. Children participated to the study
with their assent and the informed consent of their parents.
Consent for publication
The authors declare that they have no competing interests.
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1. EFSA. European Food Safety Authority . Cadmium dietary exposure in the European population . The EFSA Journal . 2012 ; 10 : 2551 .
2. Nordberg GF , Nogawa K , Nordberg M. Cadmium . In: Handbook on the Toxicology of Metals , vol. Vol. II. Specific Metals. 4th ed. Amsterdam, the Netherlands: Academic Press; 2015 . p. 667 - 716 .
3. Bernard A . Renal dysfunction induced by cadmium: biomarkers of critical effects . Biometals . 2004 ; 17 : 519 - 23 .
4. Penders J , Delanghe JR . Alpha1-Microglobulin: clinical laboratory aspects and applications . Clin Chim Acta . 2004 ; 346 : 107 - 18 .
5. De Burbure C , Buchet JP , Leroyer A , Nisse C , Haguenoer JM , Mutti A , et al. Renal and neurologic effects of cadmium, lead, mercury, and arsenic in children: evidence of early effects and multiple interactions at environmental exposure levels . Environ Health Perspect . 2006 ; 114 : 584 - 90 .
6. Ciesielski T , Weuve J , Bellinger DC , Schwartz J , Lanphear B , Wright RO . Cadmium exposure and neurodevelopmental outcomes in U.S. children . Environ Health Perspect . 2012 ; 120 : 758 - 63 .
7. Rodríguez-Barranco M , Lacasaña M , Gil F , Lorca A , Alguacil J , Rohlman DS , et al. Cadmium exposure and neuropsychological development in school children in southwestern Spain . Environ Res . 2014 ; 134 : 66 - 73 .
8. Kippler M , Tofail F , Hamadani JD , Gardner RM , Grantham-McGregor SM , Bottai M , et al. Early-life cadmium exposure and child development in 5- year-old girls and boys: a cohort study in rural Bangladesh . Environ Health Perspect . 2012 ; 120 : 1462 - 8 .
9. Gardner RM , Kippler M , Tofail F , Bottai M , Hamadani J , Grandér M , et al. Environmental exposure to metals and children's growth to age 5 years: a prospective cohort study . Am J Epidemiol . 2013 ; 177 : 1356 - 67 .
10. Skröder H , Hawkesworth S , Kippler M , El Arifeen S , Wagatsuma Y , Moore SE , et al. Kidney function and blood pressure in preschool-aged children exposed to cadmium and arsenic-potential alleviation by selenium . Environ Res . 2015 ; 140 : 205 - 13 .
11. Bernard A . Confusion about cadmium risks: the unrecognized limitations of an extrapolated paradigm . Environ Health Perspect . 2016 ; 124 : 1 - 5 .
12. Haddam N , Samira S , Dumont X , Taleb A , Lison D , Haufroid V , et al. Confounders in the assessment of the renal effects associated with low-level urinary cadmium: an analysis in industrial workers . Environ Health . 2011 ; 10 : 37 .
13. Weaver VM , Kim NS , Lee BK , Parsons PJ , Spector J , Fadrowski J , et al. Differences in urine cadmium associations with kidney outcomes based on serum creatinine and cystatin C . Environ Res . 2011 ; 111 : 1236 - 42 .
14. Chaumont A , Nickmilder M , Dumont X , Lundth T , Skerfving S , Bernard A . Associations between proteins and heavy metals in urine at low environmental exposures: evidence of reverse causality . Toxicol Lett . 2012 ; 210 : 345 - 52 .
15. Akerstrom M , Sallsten G , Lundh T , Barregard L . Associations between urinary excretion of cadmium and proteins in a nonsmoking population: renal toxicity or normal physiology? Environ Health Perspect . 2013 ; 121 : 187 - 91 .
16. Akerstrom M , Barregard L , Lundh T , Sallsten G . Variability of urinary cadmium excretion in spot urine samples, first morning voids, and 24 h urine in a healthy non-smoking population: implications for study design . J Expo Sci Environ Epidemiol . 2014 ; 24 : 171 - 9 .
17. Chaumont A , Voisin C , Deumer G , Haufroid V , Annesi-Maesano I , Roels H , et al. Associations of urinary cadmium with age and urinary proteins: further evidence of physiological variations unrelated to metal accumulation and toxicity . Environ Health Perspect . 2013 ; 121 : 1047 - 53 .
18. Chaumont A , Voisin C , Sardella A , Bernard A . Interactions between domestic water hardness, infant swimming and atopy in the development of childhood eczema . Environ Res . 2012 ; 116 : 52 - 7 .
19. Chaumont A , De Winter F , Dumont X , Haufroid V , Bernard A . The threshold level of urinary cadmium associated with increased urinary excretion of retinolbinding protein and β2-microglobulin: a re-assessment in a large cohort of nickel-cadmium battery workers . Occup Environ Med . 2011 ; 68 : 257 - 64 .
20. Bernard AM , Vyskocil A , Lauwerys RR . Determination of beta 2- microglobulin in human urine and serum by latex immunoassay . Clin Chem . 1981 ; 27 : 832 - 7 .
21. Bernard AM , Moreau D , Lauwerys RR . Latex immunoassay of retinol-binding protein . Clin Chem . 1982 ; 28 : 1167 - 71 .
22. Bernard A , Lauwerys R . Continuous-flow system for the automation of latex immunoassay by particle counting . Clin Chem . 1983 ; 29 : 1007 - 11 .
23. Bernard AM , Thielemans NO , Lauwerys RR . Urinary protein 1 or Clara cell protein: a new sensitive marker of proximal tubular dysfunction . Kidney Int Suppl . 1994 ; 47 : S34 - 7 .
24. Hare RS . Endogenous creatinine in serum and urine . Proc Soc Exp Biol Med . 1950 ; 74 : 148 - 51 .
25. Suwazono Y , Akesson A , Alfven T , Jarup L , Vahter M. Creatinine versus specific gravity-adjusted urinary cadmium concentrations . Biomarkers . 2005 ; 10 : 117 - 26 .
26. Barr DB , Wilder LC , Caudill SP , Gonzalez AJ , Needham LL , Pirkle JL . Urinary creatinine concentrations in the U.S. population: implications for urinary biologic monitoring measurements . Environ Health Perspect . 2005 ; 113 : 192 - 200 .
27. Bernard A. Biomarkers of metal toxicity in population studies: research potential and interpretation issues . J Toxicol Environ Health A. 2008 ; 71 : 1259 - 65 .
28. Weaver VM , Kotchmar DJ , Fadrowski JJ , Silbergeld EK . Challenges for environmental epidemiology research: are biomarker concentrations altered by kidney function or urine concentration adjustment ? J Expo Sci Environ Epidemiol . 2016 ; 26 : 1 - 8 .
29. Hoet P , Deumer G , Bernard A , Lison D , Haufroid V . Urinary trace element concentrations in environmental settings: is there a value for systematic creatinine adjustment or do we introduce a bias? J Expo Sci Environ Epidemiol . 2016 ; 26 : 296 - 302 .
30. Bernard AM , Ouled Amor A , Lauwerys RR . The effects of low doses of cadmium-metallothionein on the renal uptake of beta 2-microglobulin in rats . Toxicol Appl Pharmacol . 1987 ; 87 : 440 - 5 .
31. Watanabe T , Nakatsuka H , Tang N , Ikeda M. Zinc levels in urine of female farmers in nonpolluted regions of Japan . Sci Total Environ . 1990 ; 94 : 169 - 78 .
32. Watanabe T , Iwami O , Nakatsuka H , Iguchi H , Ikeda M. Correlation of cadmium, copper, manganese, and zinc levels in the urine of people in nonpolluted areas . J Toxicol Environ Health . 1991 ; 33 : 263 - 72 .
33. Vesey DA . Transport pathways for cadmium in the intestine and kidney proximal tubule: focus on the interaction with essential elements . Toxicol Lett . 2010 ; 198 : 13 - 9 .
34. Rentschler G , Kippler M , Axmon A , Raqib R , Skerfving S , Vahter M , et al. Cadmium concentrations in human blood and urine are associated with polymorphisms in zinc transporter genes . Metallomics . 2014 ; 6 : 885 - 91 .
35. Thijs L , Staessen J , Amery A , Bruaux P , Buchet JP , Claeys F , et al. Determinants of serum zinc in a random population sample of four Belgian towns with different degrees of environmental exposure to cadmium . Environ Health Perspect . 1992 ; 98 : 251 - 8 .
36. Vance TM , Chun OK . Zinc intake is associated with lower cadmium burden in U.S. adults . J Nutr . 2015 ; 145 : 2741 - 8 .
37. Hoet P , Jacquerye C , Deumer G , Lison D , Haufroid V . Reference values and upper reference limits for 26 trace elements in the urine of adults living in Belgium . Clin Chem Lab Med . 2013 ; 51 : 839 - 49 .
38. Suwazono Y , Sand S , Vahter M , Filipsson AF , Skerfving S , Lidfeldt J , Akesson A . Benchmark dose for cadmium-induced renal effects in humans . Environ Health Perspect . 2006 ; 114 : 1072 - 6 .
39. Wallin M , Sallsten G , Lundh T , Barregard L. Low-level cadmium exposure and effects on kidney function . Occup Environ Med . 2014 ; 71 : 848 - 54 .
40. Vrijens J , Leermakers M , Stalpaert M , Schoeters G , Den Hond E , Bruckers L , et al. Trace metal concentrations measured in blood and urine of adolescents in Flanders, Belgium: reference population and case studies Genk-Zuid and Menen . Int J Hyg Environ Health . 2014 ; 217 : 515 - 27 .
41. Pirard C , Koppen G , De Cremer K , Van Overmeire I , Govarts E , Dewolf MC , et al. Hair mercury and urinary cadmium levels in Belgian children and their mothers within the framework of the COPHES/DEMOCOPHES projects . Sci Total Environ . 2014 ; 472 : 730 - 40 .
42. Den Hond E , Govarts E , Willems H , Smolders R , Casteleyn L , Kolossa-Gehring M , et al. First steps toward harmonized human biomonitoring in Europe: demonstration project to perform human biomonitoring on a European scale . Environ Health Perspect . 2015 ; 123 : 255 - 63 .