Environ Monit Assess (2013) 185:3049–3055
DOI 10.1007/s10661-012-2772-0
Blood mercury concentration among residents of a historic
mercury mine and possible effects on renal
function: a cross-sectional study in southwestern China
Yonghua Li & Biao Zhang & Linsheng Yang &
Hairong Li
Received: 9 January 2012 / Accepted: 28 June 2012 / Published online: 12 July 2012
# Springer Science+Business Media B.V. 2012
Abstract This cross-sectional study aimed to investigate blood mercury (B-Hg) concentration of residents
living in the vicinity of Chatian mercury mine (CMM)
in southwestern China and to assess the possible
effects on renal function. It evaluates the effects of
gender and age (children, <18 years; adults, 18–
60 years; elderly, >60 years) on the B-Hg and serum
creatinine (SCR) and serum urea nitrogen (SUN) levels. In the CMM, elevated levels were found for B-Hg,
SCR, and SUN with mean values at 6.09 μg/L,
74.21 μmol/L, and 13.26 mmol/L, which were significantly higher than those in the control area, respectively. Moreover, the coefficients between paired
results for B-Hg and SCR and SUN levels were positive at statistical significance (B-Hg vs. SCR, r00.45,
p<0.01; B-Hg vs. SUN, r00.20, p<0.05). The aforementioned results revealed that mercury exposure can
cause human renal function impairment. B-Hg, SCR,
and SUN can also be useful biomarkers to assess the
extent of mercury exposure among residents in areas
with extensive mining activities. Furthermore, data analysis revealed that there was a tendency for higher B-Hg,
SCR, and SUN levels in females than in males, and the
levels of B-Hg, SCR, and SUN increased among the
older residents. We conclude that females and the elderly
Y. Li (*) : B. Zhang : L. Yang : H. Li
Institute of Geographical Sciences and Natural Resources
Research, Chinese Academy of Sciences,
11A Datun Road, Chaoyang District, Beijing 100101,
China
e-mail: [email protected]
in the mining area were more susceptible to mercury
exposure, and therefore, they deserve further research.
Keywords Mercury . Blood . Serum . Renal function .
Human health
Introduction
Mercury is a major concern due to its potentially adverse
impacts on public health (Agah et al. 2011; Li et al.
2009; Zhang and Wong 2007). Unfortunately, although
mercury has long been recognized as a hazardous environmental pollutant, it is still widely employed in certain
types of electrical switches, batteries, thermometers, and
vaccine buffers and continues to be an essential component of fluorescent light bulbs (Augusti et al. 2008).
Individuals can be exposed to mercury through contaminated air, water, and food. Moreover, a mixed burden of
mercury compounds has been associated with human
poisoning in mercury and/or gold mining areas (CortesMaramba et al. 2006; Drasch et al. 2001; Li et al. 2008;
Steckling et al. 2011; Howard et al. 2011).
In China, especially southwestern (SW) China, primary mercury production is still ongoing while global
production declined substantially in the late 1980s.
SW China is currently one of the most important
mercury mining/refining areas globally (Li et al.
2009; Qiu et al. 2006; Zhang and Wong 2007). Emissions of mercury from this region to the global atmosphere have been estimated to be approximately 12 %
3050
of the world total anthropogenic emissions (Cheng et
al. 2009; Horvat et al. 2003). Their effects on the
mining and refining localities are particularly severe
and have been considered one of the most serious
health problems of SW China in recent decades
(Cheng et al. 2009; Li et al. 2009; Qiu et al. 2006).
Therefore, monitoring mercury emissions and understanding their potential influence on ecosystems, as
well as populations residing in the vicinity of mining/refining area, are crucial in order to raise public
and scientific concern.
Human biomonitoring does not provide comparative
information on health before and after exposure, but it is
much more accurate than environmental monitoring in
providing data on health effects within the continuum
“source emissions–environmental concentrations–
exposure–human biomonitoring–health effects” (Reis
et al. 2007). Biomonitoring is therefore a useful complement to environmental monitoring for estimating the
level of mercury exposure (Langworth et al. 1991;
Misztal-Szkudlińska et al. 2011). In recent studies, body
fluids or tissues (saliva, blood, urine, hair, nails, etc.) have
been widely used in the biomonitoring of mercury in large
cohorts (Bárányet al. 2002; Becker et al. 2002; Caldwell et
al. 2009; Kim and Lee 2010; Laks 2009; Son et al. 2009).
However, from a toxicological viewpoint, blood mercury
(B-Hg) levels are considered to be the most appropriate
indicator of the absorbed dose and the total amount present in the human body (Budtz-Jørgensen et al. 2004).
Mercury exposure can cause serious damage in multiple organs, as is well documented. Moreover, in recent
years, studies have revealed that kidneys (as well as the
central nervous system) are affected severely by exposure to mercury (Augusti et al. 2008; Emanuelli et al.
1996; Ohno et al. 2007). For instance, chronic nephropathy, including epithelial degeneration of proximal
tubules and interstitial fibrosis, was observed in rats
and mice following long-term exposure to methylmercury (Fowler 1972; Mitsumori et al. 1990). Glomerulonephritis with proteinuria and nephritic syndrome has
been shown to result from exposure to elemental mercury, as well as after the use of mercury-containing
ointments or skin-lightening creams (Becker et al.
1962; Karimi et al. 2002; Tubbs et al. 1982; Zalups
1997). To date, little evidence has been gathered
regarding the effects of mercury exposure on renal
function in humans, although some animal studies
have provided evidence on mercury-induced renal
poisoning (ATSDR 1999; NRC 2000).
Environ Monit Assess (2013) 185:3049–3055
Serum creatinine (SCR) and serum urea nitrogen
(SUN) are frequently used as markers of renal function,
especially for nephrotoxic assessment of environmental
exposures to mercury. On this basis, our study had two
main objectives: (1) to investigate mercury concentrations in the blood of all residents living in the vicinity of
one mercury mining area in SW China and (2) to assess
the possible biological effects of this exposure on the
kidneys. Simultaneously, the study evaluated the correlation between B-Hg and SCR and SUN levels and
gender and age (children, <18 years; adults, 18–60 years;
elderly, >60 years).
Materials and methods
Study area
The Chatian mercury mine (CMM) is located in the
town of Chatian, county of Fenghuang, in Hunan province of SW China, with north latitude from 27°46′00″ to
27°48′00″ and east longitude from 109°20′30″ to 109°
21′30″. It has a typical subtropical humid monsoon
climate with annual average temperature and rainfall
of 13–18 °C and 1,100–1,500 mm, respectively. Mining
activity in CMM goes back to the Qin Dynasty (221 BC),
but only in the early 1950s were local mineral resources
rediscovered, and an intensive mining activity was
started. Because of increased health concerns about
mercury and the steep decline of its price, the mines in
CMM were gradually abandoned until the late 1990s.
However, the legacy of the industrial development is
still significant, as swathes of mining and metallurgical
wastes were dumped in CMM valleys after mining and
processing activities decreased. There is no adequate
waste disposal system in the area (including disposal
of human waste). Waste is deposited on farm fields, in
the river, or simply dumped. The local health center is
not equipped to diagnose mercury intoxication, nor can
it treat such a condition.
An agricultural town (Jixin town) situated in the
same county about 40 km north of Chatian was selected as the control area.
Sample collection and preparation
In Spring 2010, a cross-sectional study was conducted
in the CMM and the control area. A total of 101 apparently healthy individuals (54 from the CMM and 47
Environ Monit Assess (2013) 185:3049–3055
3051
from the control area), aged between 2 and 77 years, not
known to be occupationally exposed to mercury, and
living at their current address for over 2 years volunteered to participate in this study after written informed
consent. Approximately 6 ml of venous blood from each
fasting participant were collected by health professionals using two vacuum tubes—3 ml sample for B-Hg
analysis was collected in a 6-ml metal-free plastic vacutainer containing potassium EDTA as the anticoagulant
(BD Medical, NJ, USA), and 3 ml sample for serum
biochemical assay was collected in a 6-ml metal-free
plastic vacutainer without anticoagulant, which was
centrifuged immediately at 3,000 rpm for 10 min to
obtain the serum. Once collected, samples were kept at
4 °C until stored at −20 °C in Fenghuang Center for
Disease Control and Prevention (CDC). The serum biochemical assay was performed at Fenghuang CDC within 48 h of collection; however, B-Hg analysis was
performed at the Institute of Geographical Sciences
and Natural Resource Research, Beijing. During their
transfer from Fenghuang CDC to Beijing laboratory, the
samples were kept frozen in insulated containers
with ice packs. Simultaneously with blood collection,
face-to-face interviews were conducted with participants to collect information on socio-demographic
characteristics and lifestyle habits.
digested by adding 3 ml of a nitric acid/hydrogen
peroxide solution (2:1 in v/v). Each sample was subsequently evaporated in an electric oven at 120±5 °C
until a colorless and clear digest was obtained. The
digest was cooled to room temperature and then diluted in 5 ml Milli-Q water and 0.5 ml nitric acid, and
then transferred to a 10 ml polyethylene bottle, diluted
to the volume, and sealed for later analysis. The concentrations of mercury were determined by ELAN
9000 inductively coupled plasma mass spectrometry
(PerkinElmer, Waltham, MA, USA).
For quality assurance and quality control, method blanks, blank spikes, certified reference material
(GBW9101b), and blind duplicates were used during
analyses. The analytical results of mercury (1.05±0.08
in μg/g, n06) in the certified reference material were in
good agreement with the certified value (1.06±0.28 in
μg/g). The percentage of recoveries on spiked samples
ranged from 87 % to 110 %, and the relative percentage
difference was less than 11 % for mercury in duplicate
samples. The method detection limit was approximately
0.006 μg mercury per liter of blood.
Analysis of SCR and SUN levels were all performed on a Roche Modular automatic biochemical
analyzer (Roche Reflotron® Plus, Shanghai, China)
according to the manufacturer’s instructions.
Analytical methods
Statistical methods
All the reagents were of analytical-reagent grade or
better. For dilution and wash, high-purity de-ionized
water provided by a Milli-Q Plus filter apparatus
(Millipore, MA, USA) was used throughout. All
implements that came into contact with the samples had
been prewashed using 5 % nitric acid solution.
For B-Hg analysis, 1 ml whole blood from each
sample was placed in a 50-ml beaker and was then
Shapiro–Wilk's W tests were performed to study the
normal distribution of B-Hg, SCR, and SUN in the
samples. Overall, B-Hg, SCR, and SUN data were not
distributed normally (Shapiro–Wilk's W00.82, 0.96,
and 0.86, respectively, p<0.01, n0101). Therefore,
the data were Log-transformed before further analysis.
Statistically significant differences between subgroups
(such as between residents from the CMM and those
Table 1 The B-Hg, SCR, and SUN levels in residents from the CMM and control area
CMM (n054)
Mean±SD
Control area (n047)
Median
Range
Mean±SD
Median
Kruskal–Wallis test
Range
H-value
p level
6.09±3.26
5.35
1.29–15.07
3.67±0.82
3.78
0.97–5.06
37.048
0.000a
SCR (μmol/L)
74.21±17.74
75.08
27.08–140.31
62.02±14.03
61.67
19.69–86.28
15.388
0.000a
SUN (mmol/L)
13.26±4.56
12.34
6.54–31.33
11.65±3.20
10.72
6.42–20.26
4.214
0.040b
B-Hg (μg/L)
a
Statistical difference of the data between the CMM and control area is significant at 1 % level of probability
b
Statistical difference of the data between the CMM and control area is significant at 5 % level of probability
3052
Environ Monit Assess (2013) 185:3049–3055
Table 2 Kruskal–Wallis ANOVA test of the subjects broken down by gender
Regiona
Element
Male
Mean±SD
CMM
Control area
B-Hg (μg/L)
Female
Median
Mean±SD
Kruskal–Wallis test
Median
H-value
p level
0.519
6.02±2.99
6.31
6.13±3.17
5.00
0.607
SCR (μmol/L)
71.26±16.99
77.54
75.94±18.19
73.84
0.093
0.760
SUN (mmol/L)
13.05±4.63
11.88
13.38±4.58
12.71
0.451
0.502
3.96±0.98
3.49
3.31±0.60
3.51
0.066
0.797
SCR (μmol/L)
60.29±14.30
61.67
64.15±13.74
61.54
0.322
0.570
SUN (mmol/L)
10.78±2.83
9.30
12.74±3.46
12.76
4.906
0.027b
B-Hg (μg/L)
a
The sample sizes for male and female groups are 20 and 34 in the CMM and 26 and 21 in the control area, respectively
b
Means that statistical difference of the data between male and female is significant at 5 % level of probability
from the control area; between female and male; children and adult; children and elderly individuals; and
adult and elderly) for B-Hg, SCR, and SUN were
ascertained using the Kruskal–Wallis ANOVA test.
The Spearman's rank correlation was used to evaluate
the correlation between B-Hg and the SCR and SUN
levels.
All statistical analyses were performed using STATISTICA 6.0 for Windows (StatSoft, Inc., Tulsa,
USA). The statistical significance was set at p<0.01
and p<0.05, respectively.
Results and discussion
Overall descriptive statistics
Table 1 presents the findings regarding the B-Hg,
SCR, and SUN levels of the study participants together
with the basic statistical descriptions. As it illustrates,
major discrepancies are present in B-Hg levels between
the CMM and the control area. The value of B-Hg
concentration found in the CMM residents (6.09 μg/L
in average) is 1.7 times higher than that found in the
Table 3 Kruskal–Wallis ANOVA test of the subjects broken down by age
Regiona
Basic statistical
description
Children
Mean±SD
CMM
Control area
Region
CMM
B-Hg (μg/L)
a
Median
Mean±SD
Elderly
Median
Mean±SD
Median
4.63±1.17
4.59
6.46±3.73
6.05
6.47±2.83
5.12
SCR (μmol/L)
55.05±18.36
51.69
77.95±11.13
78.77
81.07±18.10
77.54
SUN (mmol/L)
10.61±1.98
10.60
13.65±5.78
12.26
14.42±2.47
14.28
B-Hg (μg/L)
2.38±0.76
2.38
3.92±0.87
3.49
2.47±0.44
2.70
SCR (μmol/L)
41.85±17.40
41.85
62.87±13.54
61.13
63.20±13.74
56.61
SUN (mmol/L)
9.44±1.47
9.44
11.59±3.11
10.72
12.80±4.11
12.36
Kruskal–Wallis test
B-Hg (μg/L)
SCR (μmol/L)
Control area
Adults
Children to adults
Adults to elderly
Elderly to children
H-value
p level
H-value
p level
H-value
p level
5.674
0.017b
0.818
0.366
2.652
0.103
12.169
c
0.001
0.970
10.187
0.001c
11.429
0.001c
0.182
0.001
b
SUN (mmol/L)
3.984
0.046
4.143
0.042
b
B-Hg (μg/L)
0.938
0.333
0.492
0.483
1.778
SCR (μmol/L)
3.415
0.065
0.323
0.570
2.305
0.129
SUN (mmol/L)
2.002
0.157
0.361
0.548
1.000
0.317
The sample size for children, adults, and elderly is 11, 27, and 16 in the CMM and 2, 39, and 6 in the control area, respectively
b
Statistical difference of the data between two age groups is significant at 5 % level of probability
c
Statistical difference of the data between two age groups is significant at 1 % level of probability
Environ Monit Assess (2013) 185:3049–3055
It has been reported that several individual characteristics such as gender, age, lifestyle, and geographic
location might affect trace element levels in human
body (Clark et al. 2007; Kristiansen et al. 1997; Li et
al. 2011). When the subjects in our study were
grouped by gender and tested for differences (Table 2),
we found that no significant difference along gender
lines in the CMM was visible for B-Hg, SCR, and
SUN; however, their concentrations tended to be
higher in females than in males. Therefore, it was
more plausible to assume that females in the mining
area were more susceptible to mercury pollution than
males.
A comparative study based on three different age
groups of residents (children, <18 years; adults, 18–
60 years; elderly, >60 years) was also carried out
(Table 3). The results show that the average concentrations of B-Hg, SCR, and SUN among residents of
the CMM increased in the order of children<adults<
elderly. When compared with children, the B-Hg,
SCR, and SUN levels were 1.40, 1.42, and 1.29 times
higher in adults, and 1.40, 1.47, and 1.36 times higher
in the elderly, respectively. Furthermore, in the CMM,
statistically significant differences for SCR and SUN
between children and the elderly (p<0.01), for B-Hg,
SCR, and SUN between children and adults (p<0.05),
and for SUN between adults and the elderly (p<0.05)
Relationship between B-Hg concentrations and SCR
and SUN levels
With special attention to the effect of B-Hg concentration on renal function, we found that there was an
increase in the SCR and SUN levels in the CMM
group, when compared with the control group. In fact,
there was a positive correlation between paired results
160
(a)
SCR levels (µmol/L)
Effects of gender and age on B-Hg, SCR, and SUN
concentrations
were detected. Consequently, there is a tendency to
show increasing B-Hg, SCR, and SUN levels with
increasing age in the cohort in the mining area. This
echoes findings by Barbosa et al. (1997) and Crompton
et al. (2002) who found that the levels of mercury in
human body increase with age.
120
80
40
0
0
5
10
15
20
B-Hg concentrations (µg/L)
40
(b)
SUN levels (mmol/L)
control area. Indeed, 15 % percent (in 8 of 54 cases) of
the CMM participants had B-Hg levels that exceeded
the WHO guideline (≤10 μg/L) for individuals who are
not occupationally exposed. The levels in SCR and
SUN, two major bio-markers of renal function, were
also significantly higher in the CMM, demonstrating
that the residents from the CMM were seriously polluted
by mercury, given that the CMM is a poor area of Hunan
province and very far from any lake and ocean. To those
people who live in the inland, consumption of fish or
shellfish was not expected; thereby other pathways,
such as freshwater consumption, grain and vegetable
intake, inhalational input, etc., might have greatly contributed to the residents’ mercury burden. Actually,
recent studies have demonstrated that, in inland
China, rice, rather than fish, is the major pathway
of human exposure to methylmercury (Feng et al.
2008; Zhang et al. 2010).
3053
30
20
10
0
0
5
10
15
B-Hg concentrations (µg/L)
20
Fig. 1 Concentration of mercury in blood (CB-Hg; μg/L) related
to a concentration of creatinine in serum (CSCR; μmol/L) and b
concentration of urea nitrogen in serum (CSUN; μmol/L). The
equations for the regression lines were a CSCR; μmol/L 02.65×
CB-Hg; μg/L +55.36 (r00.45; p<0.01) and b CBUN; mmol/L 00.28×
CB-Hg; μg/L +11.13 (r00.20; p<0.05)
3054
for B-Hg concentrations (micrograms per liter) and
SCR (micromoles per liter), SUN (millimoles per
liter) obtained from the prospective study (Fig. 1),
respectively. This suggests the likelihood that mercury impairs renal function due to biochemical
alterations, since the increase in SCR and SUN are two
of the most sensitive markers of renal disease (Augusti
et al. 2008; Rumbeiha et al. 2000).
There is evidence that some of the negative outcomes
of mercury exposure are partially or wholly reversible,
either through specific therapy or through natural elimination of the metal after exposure has been discontinued. However, heavy or prolonged exposure can do
irreversible damage. Therefore, early diagnosis and
proper treatment are crucial in reducing the burden of
mercury poisoning. At present, the main tool for diagnosis is measurement of the B-Hg concentration. Unfortunately, procedures determining B-Hg using large-scale
instruments and equipment such as atomic absorption
spectrophotometer and inductively coupled plasma
mass spectrometry are considered too expensive and
time-consuming for routine clinical use. In contrast,
measuring SCR and SUN are simple tests for clinicians.
However, whether SCR and SUN are causally linked to
other risk factors for renal disease remains unclear. The
present study reveals that SCR and SUN can be used as
alternative biomarkers for B-Hg in biomonitoring environmental mercury exposure, since the close correlations between B-Hg concentrations and SCR and SUN
levels were detected.
Conclusions
This article has presented a cross-sectional study on
health effects of environmental mercury exposure
from mining activities. Subjects from the CMM displayed increased B-Hg, SUN, and SCR levels, which
suggested mercury exposure may impair human renal
function. Given the importance of kidney diseases
worldwide, these findings, although yet to be confirmed, suggest that mercury exposures need close
attention.
In addition, our study suggested that SCR and SUN
can be used as potential alternative biomarkers for BHg in order to biomonitor environmental mercury exposure, since the coefficients between paired results for
B-Hg and SCR and SUN levels were positive at statistical significance. Nonetheless, our study will provide
Environ Monit Assess (2013) 185:3049–3055
valuable information for developing more effective
approaches for early diagnosis and/or early warning of
mercury exposure.
Acknowledgments This work was supported by the Key Project of the Knowledge Innovation Program of IGSNRR
(2012ZD002) and the National Science Foundation of China
(41040014; 40571008), and the SSRC Collaborative Grants
Program supported by the Rockefeller Brothers Fund. The
authors are also thankful to Dr. Anna Lora-Wainwright from
University of Oxford for reviewing the final draft.
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