Ecotoxicology and Environmental Safety 70 (2008) 27–37
Highlighted article
Arsenic cancer risk posed to human health from tilapia
consumption in Taiwan
Chung-Min Liao
a,, Huan-Hsiang Shen
a, Tzu-Ling Lin
a, Szu-Chieh Chen
a,
Chi-Ling Chen
b, Ling-I Hsu
c, Chien-Jen Chen
b,daDepartment of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan, ROC bGenomics Research Center, Academic Sinica, Taipei 11529, Taiwan, ROC
cGraduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan, ROC dGraduate Institute of Epidemiology, College of Public Health, National Taiwan University, Taipei 11018, Taiwan, ROC
Received 8 May 2007; received in revised form 4 October 2007; accepted 20 October 2007 Available online 18 December 2007
Abstract
Ingested inorganic arsenic is strongly associated with a wide spectrum of adverse health outcomes. We propose a bioaccumulation and
the Weibull model-based epidemiological framework to accurately estimate the reference arsenic intake guideline for tilapia consumption
and tilapia-cultured water arsenic concentration based on bioaccumulations of tilapia and gender/age/cancer-specific epidemiological
data from the arseniasis-endemic area in Taiwan. Our results show a positive relationship between arsenic exposure and age/gender- and
cancer-specific cumulative incidence ratio using Weibull dose–response model. Based on male bladder cancer with an excess lifetime
cancer risk of 10
4, we estimate the reference tilapia inorganic arsenic guideline value to be 0.084 mg g
1dry wt based on the suggested
daily consumption rate of 120 g d
1. Our findings show that consumption of tilapia in a blackfoot disease (BFD)-endemic area poses no
significant cancer risk (excess cancer risks ranging from 3.4 10
5to 9.3 10
5), implying that people in BFD-endemic areas are not
readily associated with higher fatalities for bladder cancer exposed from tilapia consumption. We are confident that our model can be
easily adapted for other aquaculture species, and encourage risk managers to use the model to evaluate the potential population-level
long-term low-dose cancer risks. We conclude that, by integrating the bioaccumulation concept and epidemiological investigation of
humans exposed to arsenic, we can provide a scientific basis for risk analysis to enhance risk management strategies.
r
2007 Elsevier Inc. All rights reserved.
Keywords: Arsenic; Human health; Epidemiology; Bioaccumulation; Tilapia; Cancer; Risk; Blackfoot disease
1. Introduction
Previous epidemiological studies have indicated that
ingested inorganic arsenic is strongly associated with a
wide spectrum of adverse health outcomes, primary cancers
(lung, bladder, kidney, skin) and other chronic diseases
such as dermal, cardiovascular, neurological, and diabetic
effects in an arseniasis-endemic area in southwestern and
northeastern Taiwan (
Chen et al., 2001a, b
;
Smith et al.,
2002
;
Chiou et al., 2005, 2001
;
Chen et al., 2005
;
Yang et
al., 2005, 2003a, b
). Chronic and systemic exposure to
arsenic is known to lead to serious disorders, such as
vascular diseases (Blackfoot disease (BFD) and
hyperten-sion) and irritations of the skin and mucous membranes, as
well as dermatitis, keratosis, and melanosis. The clinical
manifestations of chronic arsenic intoxication are referred
to as arsenicosis (hyperpigmentation and keratosis). There
is, however, no effective therapy for arsenicosis. Potential
treatment involves reducing arsenic exposure and
provid-ing specific drugs for recovery and/or preventprovid-ing disease
progression.
Drinking water and food are the two major sources of
arsenic exposure. Toxicity of an exposure is dependent on
the chemical form(s) of arsenic. This has caused an increase
in speciation-based analyses (
Schoof et al., 1999
), especially
in dietary samples containing a mixture of arsenicals.
Chronic toxicity is observed from exposure to drinking
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Corresponding author. Fax: +886 2 2362 6433. E-mail address:cmliao@ntu.edu.tw (C.-M. Liao).
water that contains ppb levels of inorganic arsenic (
NRC,
2001
). Higher doses of arsenic are acutely toxic (LD50,
mice nearly 10 mg sodium arsenite kg
1) (
Hughes, 2002
).
On the basis of this, the World Health Organization
(WHO) has set a tolerable daily intake for arsenic of
0.15 mg d
1for a 70 kg person (
WHO, 1989
). The final
regulation by the US Environmental Protection Agency
(USEPA) on arsenic in drinking water lowered the
standard from 50 to 10 mg L
1(
USEPA, 2002
). There are
still great uncertainties on the health effects of arsenic at
low doses. Research is needed to investigate and assess
human health effects of arsenic at low concentrations using
biologically based mechanistic models.
Tilapia (Oreochromis mossambicus), a traditional food
fish for people in Taiwan, is appreciated for its delicacy and
is the second most important farmed fish in Taiwan.
Currently, tilapia production is nearly 84,000 ton yr
1(6.3% of total fisheries production) in that 84% tilapia
production was produced from the southwestern coastal
area (
http://www.fagov.tw/chn/statistics_price/year_book/
2005c/94tab8_6.pdf
;
http://www.fagov.tw/chn/statistic-s_price/year_book/2005c/94tab8_3.pdf
). Farming of tilapia
is therefore a promising business. Most tilapia farms are
located at the southwestern coastal area of Taiwan, where
the inhabitants used to suffer from BFD due to long-term
exposure to inorganic arsenic in groundwater (
Chen et al.,
1988, 2001a
). Currently, people living in BFD-endemic
areas do not drink water from groundwater because tap
water has been made available in these areas.
Ground-water, however, is still utilized for aquaculture purposes
(
Liu et al., 2006
). Increasing evidence both from field
observation and experimental studies shows that a
significant correlation exists between tilapia arsenic burden
and cultured water arsenic contents in BFD-endemic areas
(
Huang et al., 2003a, b
;
Liao et al., 2003, 2004,
;
Tsai and
Liao, 2006
;
Jang et al., 2006
). If farmed tilapia is not
contaminated by arsenic, it is a health food with valuable
nutrients such as omega-3 polyunsaturated fatty and
muscle proteins, which are well known to have certain
benefits to human health (
Huang et al., 2004
;
Tokur et al.,
2004
).
The bioconcentration factor (BCF) is generally adopted
to estimate the propensity of an organism accumulating
chemicals. Fish are targets for BCF assessments because of
their importance as a human food source and the
availability of standardized testing protocols. Measured
or predicted BCFs are a requisite component for both
environmental and human risk assessment (
Liao and Ling,
2003
;
Jang et al., 2006
). Great potential benefits could be
gained from appropriately employing arsenic
bioaccumu-lation of tilapia to estimate site-specific equilibrium BCF
values for evaluating the reference cultured water arsenic
guideline.
The analysis in this paper is based on a variety of survey
data and prior analyses. We estimate the incidence ratios of
various types of internal cancers. The epidemiological
survey provided by the Blackfoot Disease Study Group
(BDSG) in Taiwan (cjchen@ha.mc.ntu.edu.tw) enables us
to estimate the dose–response function for arsenic-induced
cancers. This paper is the first to report dose–response for
internal cancers in BFD-endemic areas based on a recent
survey on arsenic epidemiology. The choice of an
appro-priate dose–response model to represent pharmacodynamic
characteristics is an important consideration in risk
assessment. There are three empirical dose–response
models that have received some attentions. The log-logistic
model uses the log-logistic distribution as a tolerance
distribution. The log-probit model uses the lognormal as a
tolerance distribution. The Weibull model uses the Weibull
distribution. At high doses, all three models are quite
similar. At low doses, however, the log-logit and Weibull
models are linear on a log–log scale, whereas the log-probit
model has a substantial curvature and gives a much lower
risk estimate.
Christensen and Nyholm (1984)
,
ten Berge
(1999)
, and
Kodell et al. (2006)
suggested that the Weibull
model was particularly well suited for a long-term low-dose
exposure purpose on dose–response modeling on lifetime
cancer risk estimation.
We argue that, by understanding the linkages between
bioaccumulation of tilapia and arsenic epidemiology of
human–arsenic–tilapia interactions, we can provide a
scientific basis for risk analysis to enhance broad risk
management strategies. The purposes of this study are
twofold: (1) to estimate the reference tilapia-cultured water
arsenic guideline based on the proposed bioaccumulation
and epidemiological framework on the basis of gender- and
age-specific epidemiological data on arsenic exposure,
cancer incidences, and at-risk population obtained from
studies conducted in arseniasis-endemic areas and (2) to
quantify the internal cancer risks of arsenic exposure from
farmed tilapia consumption in BFD-endemic areas.
2. Materials and methods
Our risk assessment approach (Fig. 1) was proposed based on a risk analysis approach for estimating the reference cultured water arsenic guidelines and excess lifetime cancer risk estimates in that the methodol-ogy can be divided into 4 phases: (A) problem formulation, (B) exposure analysis, (C) effect analysis, and (D) risk characterization. The four phases were based on the USEPA ecological risk assessment paradigm (USEPA, 1998) to account for the human–arsenic–tilapia system response to a spectrum of adverse health effects that have been identified across a range of gender/age- and site-specific scales and are described in subsequent sections.
2.1. Quantitative tilapia arsenic data
We re-analyze quantitatively the valuable data obtained fromHuang et al. (2003b)regarding arsenic species contents in aquaculture pond water and farmed tilapia based on a field survey in 4 major townships of Putai, Yichu, Peimen, and Hsuehchia in BFD-endemic areas to reconstruct our tilapia arsenic data (Table 1). Table 1indicates that the average total arsenic concentration in tilapia-cultured water was 48.93 mg L1 and the percentages of inorganic arsenic in total arsenic ranged from 70% to 89%, whereas the average tilapia total arsenic level was 0.858 mg g1 dry wt. The provision of aquaculture water arsenic standard is recommended as 50 mg L1 by the Taiwan regulatory authority (EPAROC, 1998;
http://w3.epa.gov.tw/epalaw/index.aspx).Han et al. (1998)provided data for farmed fish consumption rates for adults, indicating that the fish consumption rates ranged from 10 to 30 g d1 (% of respondents was 50%) and 35 to 70 g d1(% of respondents was 18%) for 2–6 and 7–14 meals per week, respectively, based on a brief questionnaire for seafood consumption frequency and weeks of consumption for 850 residents in Taiwan Region.
2.2. Quantitative arsenic epidemiological data
A remarkable data set related to arsenic epidemiology of gender-specific and age-adjusted internal cancer incidences including liver, lung, and bladder cancers in arseniasis-endemic areas in Taiwan provided by the BDSG gives us the opportunity to test all theoretical considerations of arsenic exposure effects and quantify its strength. We appraise the data set from the cohort studies in arseniasis-endemic areas in Taiwan to quantitatively reconstruct pooled arsenic epidemiological data of gender-and cancer-specific cumulative incidence ratios (Fig. 2). BDSG used a standardized questionnaire interview to collect information including arsenic exposure, cigarette smoking and alcohol consumption, and other risk factors such as sociodemographic characteristics, residential and occupational history, and history of drinking well water by 2 well-trained public health nurses. A total of 2050 residents in 4 townships of Peimen, Hsuehchia, Putai, and Yichu on the southwestern coast and 8088 in 4 townships of Tungshan, Chuangwei, Chiaohsi, and Wuchieh in the northeastern Lanyang Plain were followed up for an average period of 8 years (Chen et al., 2004). A detailed description of the recruitment
procedure for cohort studies and cancer cases ascertainment has been reported previously (Chen et al., 2004;Chiou et al., 2005).
Residents in the southwestern endemic area had consumed artesian well water (100–300 m in depth) for more than 50 years before the implementation of the tap water supply system in the early 1960s. The estimated amount of ingested arsenic mainly from drinking water was X1 mg d1in this area. Residences in the northeastern endemic area had
consumed water from shallow well (o40 m in depth) since the late 1940s through the early 1990s, when the tap water system was implemented. Arsenic levels in well water in the northeastern Lanyang Plain ranged from o0.15 to 43000 mg L1
(Chen et al., 2004). The larger number of study participants (10,138 residents from southwestern and northeastern Taiwan), longer period of follow-up with more incident cancer cases, and wider range of arsenic exposure levels gives us with a unique opportunity to further investigate the dose–response relationship between ingested arsenic exposure and cancer risks.
2.3. Weibull dose–response function and bioaccumulation of tilapia
Here we use the Weibull probability density function to account for the age-specific incidence ratio for human long-term exposure to low doses of arsenic:
gðt; ðCÞÞ ¼ ðCÞk2tk21expððCÞtk2Þ, (1) with
ðCÞ ¼ k0Ck1þk3, (2)
where g(t,e(C)) represents the cancer-specific incidence ratio for humans exposed to arsenic concentration C (mg L1) at age t (yr), e(C) is the
C-dependent shape parameter, and k0, k1, k2, and k3are the cancer-specific
best-fitted parameters. The cumulative incidence ratio for human exposed to arsenic concentration C at age t can then be obtained by the integral of Eq. (1) as Pðt; CÞ ¼ Z t 0 gðt; ðCÞÞ dt ¼ 1 expððCÞtk2Þ ¼1 expððk0Ck1þk3Þtk2Þ. ð3Þ We employed TableCurve 3D (Version 4, AISN Software Inc., Mapleton, OR, USA) to perform model fitting to pooled arsenic epidemiological data from BDF-endemic areas and Lanyang Plain to reflect the reasonable trend of dose–response relationship (Fig. 2).
We used a bioaccumulation model to describe the arsenic concentration in tilapia exposed to arsenic in an aquaculture pond. For a long-term arsenic exposure for tilapia, the whole body burden (muscle) of arsenic in tilapia can be expressed as
Cf¼ k1 k2
Cw¼BCF Cw, (4)
where Cfis the arsenic concentration in tilapia (mg g1dry wet), Cwis the
dissolved arsenic concentration in water (mg L1), k1is the uptake rate
constant (mL g1g1) and k
2 is the depuration rate (d1) constant of
arsenic, and BCF ¼ k1/k2¼Cf/Cw is the equilibrium bioconcentration
factor (BCF) for tilapia (mL g1) that can be estimated from tilapia
arsenic data inTable 1.
2.4. Quantitative arsenic intake and risk estimates
We incorporated fish consumption rate distribution based onHan et al. (1998) into a Weibull dose–response function to evaluate the excess lifetime cancer risks (Fig. 1C). We evaluate the reference tilapia-cultured water guideline based on the human health effects. We link drinking water inorganic arsenic estimates with the average tilapia inorganic arsenic body burden (the average BCF value) associated with a conservative daily fish consumption rate of 120 g d1 recommended by the Department of Health, ROC to estimate the reference tilapia-cultured water arsenic guideline value (Fig. 1D).Table 1indicates that the average percentage of inorganic arsenic in total arsenic is 81%.Chen et al. (1995)also indicated Risk characterization
Exposure analysis
Effect analysis Problem Formulation
Evaluate regional health effects due to arsenic exposure from tilapia consumption
Evaluate the reference cultured water arsenic concentration
Tilapia arsenic data
Bioaccumulation of tilapia: Cf =BCF×Cw
Arsenic epidemiological data
Weibull dose-response function: P(t,C ) = 1 − exp(−(k0Ck1+ k3)tk2)
Reference cultured water arsenic guidelines: ΔED0.01
Regional cancer risk estimates Excess lifetime cancer risk estimate
Fig. 1. Schematic diagram showing the proposed risk analysis approach for estimating the reference cultured water arsenic guidelines and excess lifetime cancer risk estimates. Modified fromUSEPA (1998).
that the ratios of inorganic arsenic to total arsenic in well water in southwestern coasts and Lanyang Plain were larger than 90%. Here we use 90% of inorganic arsenic in total arsenic as the evaluation basis.
We assume that daily water uptake rate and tilapia consumption rate undergo a variability analysis. To explicitly quantify the uncertainty/ variability of data, a Monte Carlo simulation is performed with 10,000 iterations (stability condition) to obtain the 95% confidence interval (CI). The Monte Carlo simulation is implemented by using the Crystal Ball software (Version 2000.2, Decisioneering Inc., Denver, CO, USA). The w2
and Kolmogorov–Smirnov (K–S) statistics were used to optimize the goodness-of-fit of the distribution. Results show that the selected lognormal distribution had the optimal K–S and w2 goodness-of-fit for
both drinking water uptake and tilapia consumption rates.
Morales et al. (2000)suggested that the use of 1% and 5% excess risks (DED01 and DED05, respectively) for the point-of-departure analysis for
cancer risk assessment suggested byUSEPA (1996)is better than that of 10% excess risk (DED10) because an excess risk of 10% is relatively large and
happens only at relative high doses in epidemiological studies. The USEPA-suggested point-of-departure analysis for cancer risk assessment is to estimate a point on the exposure response curve within the observed range of the data and then extrapolate it linearly to a lower dose (Morales et al., 2000).Morales et al. (2000) also pointed out that the traditionally employed unit excess lifetime risk of 106 is probably unreliable for epidemiological data where
exposure is not typically measured accurately enough to extrapolate to such low risk levels. In the present study, we use 0.01% excess risk (DED0.01) and
DED01point-of-departure to quantify the risk estimates. We perform excess
cancer risk assessment by the Monte Carlo simulation technique.
3. Results
3.1. Fitting Weibull model to arsenic epidemiological data
Table 2
shows the best-fitted parameters k
0, k
1, k
2, and k
3in Eq. (3) for lung, liver, and bladder cancers for each gender
by fitting a Weibull dose–response function (Eq. (3)) to
gender- and cancer-specific cumulative incidence ratios
(
Fig. 2
). Here we estimate the Weibull dose–response
function for the background incidence of internal cancers
and for the total incidence at a given arsenic concentration.
We obtain Eq. (3) by incorporating a background dose–
response function into the original dose–response function.
We use a comparison population defining unexposed internal
mortality rates as our background dose–response function,
where the internal cancer mortality data were collected from
death certificates of residents of 42 villages during 1973–1986
in Taiwan (
Morales et al., 2000
). Here we define DPP
(t, C)P(t, 0) to be the background-adjusted cumulative
incidence rate of internal cancers.
Our results indicate that bladder cancer has the highest r
2values (40.85) for all genders than those of lung (nearly 0.6)
and liver (
o0.5) cancers, respectively (
Table 2
). For bladder
cancer, r
2values are all larger than 0.85 (male r
2¼
0.86 and
female r
2¼
0.87), indicating that arsenic exposure and age
are the most influential factors for bladder cancer incidence.
Specifically, arsenic exposure has notable influence than that
of age (k
1¼
1.36 and k
2¼
0.6) for females, whereas for
males arsenic exposure and age have significant
contribu-tions to the incidence (k
1¼
k
2¼
1.13) (
Table 2
). Generally,
our result indicates that arsenic exposure is the major
attribute to bladder cancer incidence ratio for the study
participants of residents in arseniasis-endemic areas.
Fig. 3A
gives a model fitting for male bladder cancer ranging from
30 to 80 years, showing that the response surfaces of
dose–response function associated with an age-specific
relationship between cumulative incidence ratio and arsenic
exposure can be fit reasonably well by the Weibull model.
Table 1
Arsenic species contents in tilapia-cultured water and farmed tilapia (Oreochromis mossambicus) in the BFD-endemic areaa
Arsenic species Putai (n ¼ 5)b Yichu (n ¼ 7) Peimen (n ¼ 2) Hsuehchia (n ¼ 7) Average (n ¼ 21) Arsenic species in cultured water (mg L1)
As(III) 0.2c(0.1) 0.5 (0.4) NDd 0.01 (0.01) 0.2 (0.1) As(V) 66.9 (32.6) 10.2 (2.4) 172.6 (118.5) 11.1 (3.5) 39.5 (15.5) MMAe 0.06 (0.05) 0.3 (0.2) 0.2 (0.2) 0.04 (0.04) 0.15 (0.06) DMAf 0.3 (0.2) 0.7 (0.3) 5.4 (3.5) ND 0.8 (0.4) Total As 75.8 (38.8) 15.1 (2.9) 221.0 (138.8) 14.4 (4.1) 48.93 (18.4) InAs/total As (%) 88.5 70.1 78.1 77.2 81.1
Arsenic species in tilapia (mg g1dry wt 102)
(n ¼ 16) (n ¼ 21) (n ¼ 6) (n ¼ 25) (n ¼ 68) As(III) 4.72 (2.06) 1.71 (0.71) 3.9 (3.8) 1.86 (0.71) 2.67 (1.30) As(V) 2.97 (0.92) 1.47 (0.7) 2.8 (1.15) 2.46 (1.2) 2.20 (0.91) MMA 2.34 (2.04) 0.71 (0.44) 0.1 (0.1) 0.75 (0.70) 1.06 (0.88) DMA 16.46 (7.67) 12.23 (5.19) 6.05 (0.85) 11.91 (3.43) 12.56 (4.74) Total As 168.19 (33.52) 51.23 (9.6) 52.15 (7.3) 70.10 (9.01) 85.77 (14.81)
aReanalyzed from Huang et al. (2003). bSample number.
cMean (standard error). dND: non detectable.
eMMA ¼ monoethylarsonic acid. fDMA ¼ dimethylarsonic acid.
Therefore, based on male bladder cancer as our index
cancer, we estimate the drinking water arsenic
concentra-tion based on
Fig. 3A
with excess risk of 10
4suggested by
USEPA and a median daily drinking water uptake rate of
3.29 L d
1(
Fig. 3B
) for a lifetime exposure duration of 75
years and an average male body weight of 60 kg. Our result
shows that the water inorganic arsenic concentration is
estimated to be 3.4 mg L
1based on a 0.01% excess risk
(DED
0.01). We further use 1% excess dose (DED
01) to
linearly extrapolate to the DED
0.01point at low
concentra-tion ranges, resulting in a water inorganic arsenic
con-centration of 2 mg L
1. This result indicates that Weibull
dose–response function for male bladder cancer
demon-strates a nearly linear with slightly concave characteristic at
<49 50–59 Age (years) >60 <50 As concentration ( μg L −1) 50–99 100–299 300–599 >600 0 0.01 0.02 0.03 0.04 Male <40 40–49 50–59 60–69 >70 <10 10–99 100–299 >300 0 0.002 0.004 0.006 0.008 Female <40 40–49 50–59 60–69 >70 <10 10–149 >150 0 0.002 0.004 0.006 0.008 0.01
Cumulative incidence ratio
<40 40–49 50–59 60–69 >70 <10 50–99 300–599 0 0.005 0.01 0.015 0.02 <40 40–4950–59 60–69 >70 <1010–49 50–149150–299 300–599>600 0 0.01 0.02 0.03 0.04 0.05 <40 40–49 50–59 60–69 >70 <1010–49 50–149 150–599 >600 0 0.005 0.01 0.015 0.02 0.025 0.03
Fig. 2. Arsenic epidemiological data of gender- and cancer-specific cumulative incidence ratios in arseniasis-endemic areas in Taiwan (Chen et al., 2004; Chiou et al., 2005), showing the male/female liver cancer (A, B), lung cancer (C, D), and bladder cancer (E, F), respectively.
low arsenic concentration ranges. Therefore, based on male
bladder cancer as the index, internal cancer with an excess
lifetime risk of 10
4to obtain the drinking water arsenic
concentration of 3.4 mg L
1(r
240.8) can be reasonably
adopted as a reference guideline value for drinking water in
the present study.
3.2. Reference tilapia-cultured water arsenic guideline
We evaluate the reference tilapia-cultured water
inor-ganic arsenic guideline value based on the average
inorganic
arsenic
(As(III)+As(V))
concentration
of
39.7 mg L
1in tilapia-cultured water with an average
0.0497 mg g
1dry wt of inorganic arsenic in tilapia in
BFD-endemic areas (
Table 3
). Here we adopt the water
arsenic concentration of 3.4 mg L
1with a median daily
drinking water uptake rate of 3.29 L d
1to derive the
reference tilapia-cultured water arsenic guideline value
(
Table 3
): (1) Daily maximum arsenic ingestion rate:
D ¼ 3.29 L d
13.4 mg L
10.9 ¼ 10.1 mg d
1based on
90% of inorganic arsenic content in total organic. (2)
Inorganic arsenic level in tilapia: C
f, s¼
10.1 mg d
1
/120 g d
1¼
0.084 mg g
1dry wt based on the suggested daily fish
consumption of 120 g d
1by the Department of Health,
ROC. (3) Cultured water arsenic concentration: C
w, s¼
C
f, s/BCF
avg¼
(0.084 mg g
1dry wt)/(1.25 10
3L g
1) ¼
67.09 mg L
1based
on
an
average
BCF
avg¼
1.25
10
3L g
1(
Table 3
). Furthermore, the site-specific
refer-ence cultured water arsenic guidelines are also estimated to
be 73, 28, 216, and 21 mg L
1, respectively, for Putai,
Yichu, Peimen, and Hsuehchia, based on the site-specific
BCF values.
3.3. Regional cancer risk estimates
We evaluate the excess cancer risk estimates based on the
Weibull dose–response function for male bladder cancer as
Table 2
Gender- and cancer-specific best fitted parameters in Weibull dose–response function
Cancer k0 k1 k2 k3 r 2 Male Lunga 1.07 107b(0–1.17 106)b 0.7 (0–2.11) 1.46 (0.37–2.55) 6.25 106(0–3.49 105) 0.67 Liverc 5.24 107(0–5.00 106) 0.823 (0–2.01) 1.21 (0.33–2.09) 6.01 105(0–2.82 104) 0.45 Bladderc 1.92 107(0–8.29 107) 1.13 (0.73–1.54) 1.13 (0.66–1.61) 4.38 109(0–2.67 105) 0.86 Female Lunga 8.72 108(0–9.73 107) 0.83 (0–2.26) 1.45 (0.65–2.26) 1.45 105(0–6.40 105) 0.58 Liverc 1.50 105(0–8.90 105) 0.14 (0–0.43) 1.09 (0–2.2) 1.13 105(0–6.74 105) 0.41 Bladderc 2.02 107(0–1.28 106) 1.36 (0.63–2.08) 0.6 (0.04–1.16) 1.03 104(0–1.76 103) 0.87 a
Excluding smoking population.
b
Best fitting value with 95% CI shown in parenthesis.
c
A comparison population is used to define unexposed cancer mortality rates (i.e., cumulative cancer incidence ratio at C ¼ 0: P(t, 0)) in that cancer mortality data were collected from death certificates of residents of 42 villages during 1973–1986 in Taiwan (Morales et al., 2000).
0 100 200300 400500 600700 As concentration ( μg L−1) 30 35 40 45 50 55 60 65 70 75 Age (yr) 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0.05
Cumulative incidence rate
Median 25% – 75% 2.5% – 97.5% 6.52 4.17 3.29 2.59 1.08 1 2 3 4 5 6 7 0
Drinking water uptake rate (L d
−
1)
Fig. 3. (A) Best fitted Weibull model-based dose–response surfaces reflecting an age-specific relationship between cumulative incidence ratio and arsenic exposure for male bladder cancer. (B) A box and whisker plot showing the daily drinking water uptake rate distribution.
our index internal cancer (r
240.85 and k
1¼
k
2(
Table 2
)).
We incorporate farmed fish consumption rate frequencies
(
Han et al., 1998
) and tilapia inorganic arsenic burden data
(
Table 1
) into the Weibull dose–response function for male
bladder cancer to assess the excess lifetime cancer risks in
BFD-endemic area (
Fig. 4
).
Fig. 4
shows that the excess
cancer
risk
estimates
(ranging
from
3.4 10
5to
9.3 10
5) are all within the acceptable value of 10
4in
that Putai and Hsuehcuia have the highest bladder cancer
risk (99%) of 9.3 10
5and 6.7 10
5, respectively
(
Figs. 4B and E
). The 90% risks are 4.2 10
5, 3.6 10
5,
1.7 10
5, and 2.0 10
5for Putai, Peiman, Yichu, and
Hsuehcuia, respectively (
Figs. 4B–E
). Our result indicates
that human exposure to the consumption of tilapia in
BFD-endemic areas may pose no significant cancer risks. The
result also implicates that people in BFD-endemic area are
not readily associated with higher fatalities for bladder
cancer exposed from tilapia consumption.
4. Discussion
4.1. Implications of the reference arsenic guideline
To date, the total arsenic standard for aquaculture water
is recommended to be 50 mg L
1by Taiwan regulatory
authorities.
Huang et al. (2003b)
indicated that the average
ratio of inorganic arsenic to total arsenic of cultured water
is 81.1%, with a min–max from 70.1% to 88.5% in
southwestern coastal areas, resulting in the reference
inorganic arsenic guideline for cultured water to be
calculated as 50 mg L
181.1% ¼ 41 mg L
1, with a
min–-max from 35 to 44 mg L
1. Hence, the reference guideline of
67.09 mg L
1is acceptable.
According to the recommended reference inorganic
arsenic guideline in
Table 3
, the inorganic arsenic in
cultured water in Putai is the second high concentration
(67.1 mg L
1less than 172.6 mg L
1in Peimen); however,
the highest excess risk of framed tilapia consumption also
occurred in Putai (maximum 9.3 10
5with 90% less than
4.2 10
5) in
Fig. 4
. The reason may be that the inorganic
arsenic level in tilapia is highest than those of others
(C
f¼
7.69 mg g
1dry wt in
Table 3
). Cultured water arsenic
concentration is not the only determinant to affect the
excess risk values. Other environmental factors such as
characteristics of water chemistry and bioavailability may
also affect the estimation of excess risk values. Therefore,
the inorganic arsenic level in tilapia is the most direct
uptake exposure concentration to human health and that
may be the critical point to estimate the excess risk values.
Our study suggests that the reference cultured water
arsenic guidelines are estimated to be 67.09 mg L
1based on
the average BCF
avg. Furthermore, the site-specific
refer-ence cultured water arsenic guidelines are estimated to be
73, 28, 216, and 21 mg L
1based on the site-specific BCF
values for Putai, Yichu, Peimen, and Hsuehchia,
respec-tively. Large differences are observed on estimation of the
reference cultured water arsenic guidelines based on
BCF
avgor site-specific BCF values. On the aspect of
human health, we suggest that the site-specific BCF values
will be more appropriate to regulate hazard risk. From the
aspect of regulatory authorities, however, a universal
reference guideline may provide an effective management.
Thus, our estimated reference tilapia inorganic arsenic
guideline of 0.084 mg g
1dry wt is more appropriate than
the reference cultured inorganic arsenic guideline.
Our results suggest that both BCF values of
commer-cially important farmed species and human consumption
frequencies have to be taken into account to further select
appropriately the suitable farmed species with average
arsenic BCF values to detail more accurately and robustly
while assessing the reference cultured water arsenic
guide-line value on the whole. To precisely determine the risk/
benefit ratios from consumption of farmed fish is
complicated; cautious interpretation of present data may
substantially prompt risk management strategy. We argue
that the present reference water arsenic guideline value is
Table 3
Recommended reference inorganic arsenic guideline in tilapia-cultured water in BFD-endemic area
As species Putai (n ¼ 5)a Yichu (n ¼ 7) Peimen (n ¼ 2) Hsuehchia (n ¼ 7) Average (n ¼ 21)
Mean arsenic species in cultured water (Cw, mg L1)
As(III) 0.2 0.5 ND 0.01 0.2
As(V) 66.9 10.2 172.6 11.1 39.5
As(III)+As(V) 67.1 10.7 172.6 11.11 39.7
Mean arsenic species in tilapia (Cf, mg g1dw 102)
As(III) 4.72 1.71 3.9 1.86 2.67
As(V) 2.97 1.47 2.8 2.46 2.30
As(III)+As(V) 7.69 3.19 6.7 4.32 4.97
BCF ¼ Cf/Cw(mL g1)
1.14 2.98 0.39 3.89 1.25
Reference cultured water inorganic arsenic concentration (mg L1)
73.32 28.21 216.39 21.60 67.09
Fig. 4. Excess lifetime risk estimates of tilapia culture water and farmed tilapia based onHuang et al. (2003b)in (A) the overall BFD-endemic area, (B) Putai, (C) Yichu, (D) Peimen, and (E) Hsuehcuia. Ratios of inorganic arsenic/total arsenic in 4 major townships in the BFD-endemic area are shown in (F). Error bar indicates the standard deviation from mean.
estimated based on arsenic epidemiology data from
long-term low-dose exposures and not based on animal models
considering uncertainty factors used to account for
potential interspecies variation in response sensitivity and
potential intraspecies variation in human sensitivity.
There are a number of areas in which further research
could strengthen the water arsenic reference guideline
establishment (
Hrudey et al., 2006
). First, there is a need to
conduct a more extensive characterization of the
distribu-tion of exposures within given aquaculture species
popula-tion. It would be useful to characterize better the detailed
information on aquaculture species arsenic data, arsenic
levels in fish target organs, and site- and species-specific
BCF value. Second, there is a need for sensitivity analysis
using the Monte Carlo simulation model with the more
detailed data sets as inputs. Relationships between the
input ranges and model output should then be assessed
with stepwise regression in order to identify the
relation-ship between output variability and input uncertainties and
variabilities. Finally, on the basis of the results of the
sensitivity analysis, research should be directed to those
parameters that, if better characterized, could most
effectively reduce variability in the results.
4.2. Implications on risk management
An analysis of the implications of arsenic-induced cancer
risks in arseniasis-endemic areas would be more complex
and would include consideration of impacts on farmed fish
production, and regionally specific information on social,
demographic, and economic trends. Moreover, the
arsenic-induced cancer risks may occur concurrent with
human-induced changes. These human-driven transitions in
arseniasis-endemic areas (e.g., cigarette smoking) are likely
to have a larger impact on risk profiling than
arsenic-only-induced transitions (
Chen et al., 2004
). Although our
information may not be able to provide an unambiguous
definition of cultured water arsenic and risk estimates of
tilapia consumption, it may help to inform public and
regulatory authorities on discussions of risk management
and communication by drawing attention to the worldwide
arsenic issues.
Scientific progress in human and environmental risk
management for assuring safe arsenic intake clearly
depends on interdisciplinary collaboration. This task
requires defining environmental risk assessment protocols
appropriate for the specific social and environmental
conditions encountered in arseniasis-endemic areas (e.g.,
demographic and epidemiological history and
biogeochem-ical and geographic information) (
Nieuwenhuijsen et al.,
2006
). There is also a need on the part of regulatory
authorities to enforce more strictly. Epidemiologists must
provide the valuable yet realistic cohort studies to directly
and indirectly identify certain epidemiology data to further
construct the dose–response relationships as the framework
for environmental management (
Chappell et al., 2003
). It is
in this way that the epidemiologists use an understanding
of the biology of diseases and the principles of
epidemiol-ogy to design and conduct studies that will ultimately aid in
the risk management (
Chen et al., 2005
). Chemists and
biologists must work together to harness the potential of
new screening techniques for assessing the environmental
impact of arsenic, whereas environmental chemists and
engineers must strive to develop more powerful strategies
to mitigate arsenic-contaminated drinking water because
meeting the WHO guideline of 10 mg L
1of arsenic is a
major drinking water challenge worldwide for both
geochemists and process engineers (
Berg et al., 2001
;
Hug
et al., 2001
;
Su and Puls, 2001
).
Fig. 5
summarizes our
conceptual bioaccumulation and epidemiological
frame-work, providing an accurate risk analysis for reference
arsenic intake guideline estimations and implicating the
interplay among system approach, regulatory
require-ments, and risk management. This can be grouped into
three major components: (i) human health-based reference
water arsenic guideline estimate based on Weibull
dose–r-esponse model-based epidemiological data (
Fig. 5A
), (ii)
reference cultured water arsenic guideline estimated by
site-specific BCF values and the farmed fish consumption
frequency survey (
Fig. 5B
), and (iii) risk management
analyses and strategies to meet the human health-based
arsenic intake regulations (
Fig. 5C
).
We recognize limitations in each of our data sources,
particularly the inherent problem of uncertainty and
vari-ability of the data. The strength of these results rests on the
consistent agreement of mathematical models and public
and regulatory authorities’ reference guideline values. Our
analysis may provide a wider context for the interpretation
of regional arsenic-induced cancer risk profiling that
pro-duced diverging and controversial outcomes, which have
economic and policy implications. Although more complex
models may be necessary to answer specific questions
regarding risk or particular management strategies, our
simple model captures the essential risk analysis
methodol-ogy, and it is flexible enough to integrate the effects
occurring at varying subpopulation scales. Our results
suggest that even simple models can provide useful insights
into complex bioaccumulation and epidemiological
interac-tions in human and ecological risk management.
In conclusion, our proposed bioaccumulation and
Weibull model-based epidemiological framework provide
a template for integrating the tilapia arsenic data,
bioaccumulation of tilapia, epidemiological data, and risk
profiling techniques to accurately estimate the reference
cultured water arsenic guideline associated with human
arsenic intake. Our data highlight that the tilapia-cultured
water inorganic arsenic concentration is estimated to be
67.09 mg L
1based on male bladder cancer with an excess
lifetime cancer risk of 10
4. Our findings further point out
that consumption of tilapia in BFD-endemic areas is
unlikely to pose substantial cancer risk (excess cancer risks
ranging from 3.4 10
5to 9.3 10
5o10
4) to public
health given the most prevalent exposure routes. We are
confident that our model can be easily adapted for other
aquaculture species, and encourage risk managers to use
the model to evaluate the potential population-level
long-term low-dose cancer risk exposed to environmental
micropollutants in order to recommend the appropriate
reference cultured water guidelines or to quantify rigorous
health risk estimates for food consumption.
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