Cohort profile
Cohort profile: health effects monitoring
programme in Ndilǫ, Dettah and
Yellowknife (YKHEMP)
Hing Man Chan
,1 Xue Feng Hu,1 Janet S. Cheung,1 Rajendra Prasad Parajuli,2
1
Renata Rosol, Emmanuel Yumvihoze,1 Linna Williams,3 Asish Mohapatra4
To cite: Chan HM, Hu XF,
Cheung JS, et al. Cohort
profile: health effects
monitoring programme in
Ndilǫ, Dettah and Yellowknife
(YKHEMP). BMJ Open
2020;10:e038507. doi:10.1136/
bmjopen-2020-038507
► Prepublication history for
this paper is available online.
To view these files, please visit
the journal online (http://dx.doi.
org/10.1136/bmjopen-2020038507).
Received 12 March 2020
Revised 25 August 2020
Accepted 03 September 2020
© Author(s) (or their
employer(s)) 2020. Re-use
permitted under CC BY-NC. No
commercial re-use. See rights
and permissions. Published by
BMJ.
1
Biology, University of Ottawa
Faculty of Science, Ottawa,
Ontario, Canada
2
Biology, University of Ottawa,
Ottawa, Ontario, Canada
3
Health and Social Services,
Government of the Northwest
Territories, Yellowknife,
Northwest Territories, Canada
4
Environmental Health Program,
Health Canada, Ottawa, Ontario,
Canada
Correspondence to
Dr Hing Man Chan;
laurie.chan@uottawa.ca
ABSTRACT
Purpose The Yellowknife Health Effects Monitoring
Programme (YKHEMP) was established to examine the
relationship of exposure to arsenic and other chemicals
of potential concern such as antimony, cadmium, lead,
manganese and vanadium and health outcomes.
Participants A total of 2037 individuals were recruited,
including children (age 3–19) and adults (age 20+),
residing in Dettah, Ndilǫ and Yellowknife, in the Northwest
Territories, Canada, in two waves in Fall 2017 and
Spring 2018. In Yellowknife, there were 891 (675 adults,
216 children), randomly selected participants with a
participation rate of 64%. In addition, we also recruited
a total of 875 (669 adults, 206 children) volunteer
participants. A total of 225 (137 adults, 88 children) of
the Yellowknives Dene First Nation (YKDFN), and 46 (33
adults, 13 children) of the North Slave Métis Alliance
participated in the study. Each participant answered a
lifestyle questionnaire as well as provided toenail clippings
and urine for contaminant testing and saliva samples for
testing of genetic polymorphisms associated with arsenic
metabolism. Participants also provided consent to have
their medical records reviewed by the research team for
the past 5 years to allow for the investigation between
exposure and health outcomes.
Findings to date The adult YKHEMP participants had
lower urinary total arsenic but the children had higher
inorganic arsenic than the general Canadian population.
There was no difference in urinary total arsenic
concentrations between adults and children, however,
urinary inorganic arsenic concentrations were generally
higher in children than in adults in all four YKHEMP
sampling groups. The adult YKDFN participants had lower
urinary total arsenic and inorganic arsenic concentrations
compared with the random selected and volunteer
participants.
Future plans YKHEMP is designed as a prospective
cohort study; the children participants will be re-examined
in 2022 and both adult and children participants in 2027.
INTRODUCTION
Giant Mine was a gold mine located within the
boundary of the city of Yellowknife, where it
operated from 1948 to 2004. The site reverted
to the Crown when owner Royal Oaks Mine
went into receivership in 1999. Gold was
extracted from arsenopyrite ores through
Strengths and limitations of this study
► Multiple validations were designed to account for
potential inaccuracy in exposure characterisation
and recalling bias in the questionnaire interview.
► Community meetings were organised with each
population to review study protocols and seek public input.
► Does not address the potential long-term effects
of legacy arsenic exposure of the populations
in Yellowknife when the Giant Mine was still in
operation.
► Urine is a good medium to measure arsenic exposure; however, it may not be the optimal one for the
other chemicals of potential concern, for example,
lead.
a roasting process that generated arsenic
trioxide as a toxic byproduct. As a result,
there are currently 237 000 tonnes of arsenic
trioxide dust present at the site, contained
in 15 underground chambers, and 4 large
tailings ponds. Between 1949 and 1953, an
estimated 16 500 pounds or about 7500 kg
of arsenic trioxide dust was released into the
environment every day without any filtration.1 Following reports of arsenic poisoning
in the 1950s, a baghouse filtration system was
installed in 1958 to filter and store the arsenic
trioxide in underground chambers.1
At present, the mine is considered one
of the most contaminated sites in Canada.2
Although Giant Mine is no longer in operation, there are concerns of chemical contamination originating from the site via surface
runoff and groundwater migration or from
historical aerial deposition.3 The list of
chemicals of potential concern (COPCs)
includes arsenic, antimony, cadmium, lead,
manganese and vanadium. Arsenic exposure is of particular concern and arsenic is
highly toxic in its inorganic form. Long-term
exposure to arsenic from drinking water and
food are associated with cancer, skin lesions,
Chan HM, et al. BMJ Open 2020;10:e038507. doi:10.1136/bmjopen-2020-038507
1
BMJ Open: first published as 10.1136/bmjopen-2020-038507 on 28 September 2020. Downloaded from http://bmjopen.bmj.com/ on February 19, 2022 by guest. Protected by copyright.
Open access
cardiovascular disease and diabetes.4–9 Chronic exposure
to other COPCs were associated with various adverse
health outcomes.10 To address concerns about arsenic
and other COPCs, the Giant Mine Remediation Project
was established and approved by the Mackenzie Valley
Environmental Impact Review Board. The Giant Mine
Remediation Project’s primary goal is to protect human
health and the environment. To do so, the Project is
focused on the long-term containment and management
of the stored underground arsenic trioxide waste, demolition and removal of on-site buildings, water management
and treatment, and the remediation of all surface areas
including the tailings ponds at the Giant Mine site. As
required by the review board, the Project is subject to 26
measures aimed at preventing significant adverse impacts
on the environment and public health and mitigating
public concern.
This research programme titled ‘Health Effects Monitoring Programme in Ndilǫ, Dettah and Yellowknife
(YKHEMP)’ was developed to make sure the remediation
activities that take place at Giant Mine will not have a
negative impact on people’s health. The project objective
will be achieved by investigating the exposure and impact
of the COPCs, particularly arsenic, on the Ndilǫ, Dettah
and Yellowknife population. The YKHEMP will be a longterm programme that will monitor the level of COPCs
within the human population as the remediation at the
Giant Mine progresses.
The overall objective of YKHEMP is to implement a
broad health effects biomonitoring programme for the
population of Yellowknife, Ndilǫ and Dettah, focusing on
arsenic and other COPCs such as antimony, cadmium,
lead, manganese and vanadium. It will provide a comprehensive overview of the levels of contaminants currently
present in the human population. The specific project
objectives are as follows:
A. Compare body-burden of COPCs in YKHEMP participants to those reported in national biomonitoring
study, the Canadian Health Measures Survey (CHMS).
B. Investigate the associations between COPC concentrations, particularly arsenic and the observed/reported
health outcomes in YKHEMP participants.
C. Explore results sharing with other related studies to
understand sources of contaminant exposure and
their relationships with health outcomes in Yellowknife.
D. Establish a detailed protocol, including a set of benchmarks for the future ongoing monitoring programme.
COHORT DESCRIPTION
Study population
YKHEMP is a prospective cohort study, and it comprises
four groups of participants; (1) randomly selected Yellowknife participants, (2) Yellowknives Dene First Nation
(YKDFN), (3) North Slave Métis Alliance (NSMA)
members and (4) volunteer Yellowknife participants.
Yellowknife has a population of roughly 21 183 residents
2
including 1540 Yellowknives Dene, in 10 districts. Participant recruitment and biomonitoring were conducted
from September 2017 to December 2017 (wave 1) and
from April 2018 to June 2018 (wave 2) for the baseline
survey. The two-wave approach was designed to account
for any potential seasonal effect on levels of COPC in
biological samples and risk factors for exposure such
as water recreation activities, fishing, children playing
outdoors with bare foot.
For the Yellowknife general population, a two-stage
stratified systematic sampling approach was used to
yield a representative sample of residents from 3 to 79
years, who have lived in Yellowknife for at least 1 year,
excluding members of the YKDFN and NSMA. The population in Yellowknife was estimated to be approximately
20 000. For a confidence level of 5%, the required sample
size was 1000. The sample size increased to 2000 after
accounting for a non-response rate of 50%, and to 2500
after accounting for out-of-scope rate of 20% (dwellers
have been residing in Yellowknife for less than 1 year),
and to 2800 after accounting for an occupancy rate of
90%. On average, 1.5 persons (assuming 50% of the
households have children) were expected to be selected
using the number of households from the 2011 Census.
Thus, 1900 households were the target sample. A list of
the dwellings that contained 6886 residential addresses
was provided by the City of Yellowknife municipality. A
sample of 1900 addresses were selected in random and
then divided into two waves of collection, September
2017 and April 2018. From each selected household, up
to one adult (18+) and one child (3–17) was randomly
selected based on whose birth date was next. Population
aged 6 and above were invited to participate during wave
1, and the population aged 3 and above were included
in wave 2.
For YKDFN, a mixed sampling approach was adopted,
as suggested by the Yellowknives Dene leadership. All
YKDFN members were invited to participate on a voluntary basis. Additional members were contacted and
invited to participate if a specific demographic or household characteristic was lacking to better represent the
population. For the NSMA, all members were invited to
participate as recommended by the NSMA leadership. In
responding to the request of the Yellowknife residents
during the consultation period, the study also welcomed
any resident who volunteered to participate, thus forming
the fourth group.
A total of 2037 individuals participated in the baseline
survey, which included 891 randomly selected general
population participants with a participation rate of 64%,
875 volunteer participants from the general population,
a total of 225 YKDFN and 46 NSMA members. For the
randomly selected participants, survey weights were
generated to account for the sampling probability and
non-response rate. A set of 500 bootstrap weights was also
generated to account for the sampling error. Details of
the demographic and socioeconomic characteristics for
the four participation groups are shown in table 1.
Chan HM, et al. BMJ Open 2020;10:e038507. doi:10.1136/bmjopen-2020-038507
BMJ Open: first published as 10.1136/bmjopen-2020-038507 on 28 September 2020. Downloaded from http://bmjopen.bmj.com/ on February 19, 2022 by guest. Protected by copyright.
Open access
Table 1 Sociodemographic characteristics by participant group in the Yellowknife Health Effects Monitoring programme
Random sample
Sex*
Male
Female
Volunteers
YKDFN
NSMA
400 (44.8)
400 (45.7)
97 (43.1)
22 (47.8)
491 (55.2)
474 (54.3)
128 (56.9)
24 (52.2)
Age
3–19
216 (24.3)
206 (23.5)
88 (39.1)
13 (28.3)
20 and above
675 (75.7)
669 (76.5)
137 (60.9)
33 (71.7)
Adult current smoker
121 (13.6)
125 (14.3)
63 (28.0)
13 (28.3)
47 (6.9)
72 (10.7)
24 (17.4)
5 (14.3)
Working experience
Giant mine site
Hunting
94 (10.6)
127 (14.5)
68 (30.2)
14 (30.4)
Fishing
462 (51.9)
461 (52.7)
113 (50.2)
36 (78.3)
Water recreation activity
595 (66.9)
613 (70.1)
123 (54.7)
33 (71.7)
Meat
476 (53.5)
536 (61.3)
216 (96.0)
38 (82.6)
Fish
714 (80.2)
744 (85.0)
194 (86.2)
44 (95.7)
Plant
Mushrooms
545 (61.3)
97 (10.9)
574 (65.6)
459 (18.2)
71 (31.6)
10 (4.4)
28 (60.9)
7 (15.2)
Local food consumption
The bracketed numbers are the percentage of all participants within the group.
*One volunteer participant self-identified sex as ‘other’.
NSMA, North Slave Métis Alliance; YKDFN, Yellowknives Dene First Nation.
YKHEMP is designed as a prospective cohort study that
will last for at least 10 years (figure 1).
Phase 2, 2022–2023
The children who participated in the baseline survey
(2017–2018) will be contacted again. A random selection will be conducted to make up for the attrition of
participants over the 5-year period, in case that some of
these children will not live in Yellowknife at the time of
resampling.
Phase 3, 2027–2028
All participants (children and adults) from the baseline survey (2017–2018) and the children from phase
2 (2022–2023) will be contacted. In addition, another
sample of adults and children will be selected in 2027–
2028 to make up for the attrition of participants over this
10-year period. This sample will be designed later with the
updated values for the population size of Yellowknife and
updated requirements for the project.
The retrospective phase of YKHEMP collected the
medical history of all participants for up to 5 years. The
baseline survey of YKHEMP includes three main components: questionnaire interview, physical examination
(YKDFN only), laboratory chemical measurements and
genotyping (table 2).
All participants were invited to complete a Lifestyle
Questionnaire. The lifestyle questionnaire contained
two components: general information and exposure
Figure 1 Study design for the YKHEMP. YKHEMP, Yellowknife Health Effects Monitoring Programme.
Chan HM, et al. BMJ Open 2020;10:e038507. doi:10.1136/bmjopen-2020-038507
3
BMJ Open: first published as 10.1136/bmjopen-2020-038507 on 28 September 2020. Downloaded from http://bmjopen.bmj.com/ on February 19, 2022 by guest. Protected by copyright.
Open access
Table 2 Summary of measurements at baseline in the Yellowknife Health Effects Monitoring programme
Survey
component
Measurements
Lifestyle
Questionnaire
Demographics and socioeconomic information: age,
sex, ethnicity, date of birth, education, occupation,
marital status, household income, years living in
Yellowknife.
Lifestyle: smoking, alcohol drinking, drinking water,
hunting, swimming and fishing.
For all participants
YKDFN only
Occupational exposure: currently or previously worked
in Giant Mine and other occupational exposures.
Environmental exposure: exposure to wood
preservatives, chemical fertilisers, pesticides, rat
poison, and other chemicals.
Food frequency Consumption of locally harvested fish, locally grown
Questionnaire vegetables/herbs and locally collected berries,
mushrooms, wild fungus and other wild plants;
consumption of fish, shellfish, rice and rice product
from store.
Consumption of different types of locally harvested
meat, local lake fish, locally grown vegetables and
herbs and locally collected berries, mushrooms, tea,
birch sap and spruce gum.
Physical
examination
Anthropometric measures: weight, height and blood
pressure.
Medical
Questionnaire
Medication and symptoms: dermatological,
respiratory, cardiovascular, haematological, hepatic,
neurological, cancer, other.
Laboratory
Urinary concentrations of total arsenic, different
chemical
components of inorganic arsenic, vanadium,
measurements manganese, cadmium, antimony, and lead, CC16 and
KIM-1 (for children only).
Toenail concentrations of arsenic, vanadium,
manganese, cadmium, antimony and lead.
Medical
records
Genotyping
Diseases certified by ICD-9 codes and medical
conditions identified from free text in the medical
record: cancer including skin cancer and melanoma,
heart disease, diabetes, various symptoms related to
arsenic exposure.
Single nucleotide polymorphism for genes related to
arsenic exposure, metabolism, regulation and DNA
repair.
ICD-9, International Classification of Diseases, Revision 9; YKDFN, Yellowknives Dene First Nation.
history (eg, lifestyle, diet, water source, occupational
history). Participants were also asked to complete a short
Food Frequency Questionnaire (FFQ) on the types and
amounts of local harvested fish consumed. Information
about serving sizes was collected using food models. The
FFQ also included other fish, shellfish, rice and rice products purchased from the market; locally grown vegetables/herbs and locally collected berries, mushrooms, wild
fungus and other wild plants. The FFQ for the YKDFN
included additional components including the types and
amounts of local traditional foods including wild animals,
wild birds, wild berries, wild plants for tea, other edible
4
plants: greens, onions, rhubarb, spruce gum, birch sap
and mushrooms consumed, as suggested by the YKDFN
leadership. All participants were also asked to complete
a medical questionnaire and invited to undergo a brief
medical exam that included taking a person’s height,
weight and blood pressure. The medical history included
diagnosed diseases, for example, hypertension, diabetes,
cancer and common clinical symptoms associated with
arsenic exposure.6 Parents completed the questionnaires
on their child’s behalf for any children from 3 to 12 years
of age. However, starting from age 13, the youth was able
to answer the questionnaire for themselves. Diseases were
Chan HM, et al. BMJ Open 2020;10:e038507. doi:10.1136/bmjopen-2020-038507
BMJ Open: first published as 10.1136/bmjopen-2020-038507 on 28 September 2020. Downloaded from http://bmjopen.bmj.com/ on February 19, 2022 by guest. Protected by copyright.
Open access
extracted according to International Classification of
Diseases, Revision 9 and clinical symptoms were extracted
through keyword searching in the participants’ medical
records from the Wolf EMR electronic medical record
system, which was launched in 2014. Medical records
start at birth of each child but they are not linked to
the parents’ records. The list of symptoms and medical
conditions included in the medical history questionnaire
are presented in online supplemental material 1 and the
search terms for the medical records are presented in
online supplemental material 2.
For children (ages 6–17), we measured CC16 and KIM-1
in urine as two candidate biomarkers of effect for arsenic
on the lung and the kidney, respectively. CC16, a secretory
protein in the lung and KIM-1, a molecule upregulated in
the kidneys.11–14 Urine samples were analysed for CC16
and KIM-1 using ELISA as described elsewhere.12 13 The
primary antibodies used were Monoclonal Antibodies
AY1E6 and ARD5 for CC16 and KIM-1, respectively.
Urine, toenail and saliva samples were collected, and
COPCs were analysed for participants. Sample kits were
distributed to all participants by trained research assistants to collect urine, toenail clippings and saliva, at their
own time. Toilet hat was provided for the collection of
urine for young children (3–6 years). Participants were
instructed to abstain from eating seafood 3 days before
urine sampling and to provide the first-morning urine
void. Samples were kept at the local research office under
appropriate storage conditions: at room temperature
for saliva and toenails, and in the refrigerator at 4°C
for urine, and until shipped to the University of Ottawa
(urine and toenail) or Génome Quebec (saliva) for analysis within 30 days. All chemical analyses were performed
at the Laboratory for the Analysis of Natural and Synthetic
Environmental Toxicants at the University of Ottawa.
Concentration of arsenic and COPCs in the urine and
digested toenail were analysed using inductively coupled
plasma mass spectrometry (ICP-MS) (7700 x ICP-MS,
Agilent Technologies, Japan). For quality control, certified reference materials, as well as in-house and external
quality controls were used (eg, field blanks and spiked
samples). Details of the sample processing and chemical
analysis procedures can be found elsewhere (http://
www.ykhemp.ca/reports.php). To ensure laboratory analysis quality, 2.5% of the urine samples were randomly
selected and sent to Institut National de Santé Publique
du Québec. There was a strong correlation between the
two sets of results, and there was no statistical difference
in both total and inorganic arsenic results. The detection limit in the urine samples was 0.012 ug/L for total
arsenic, 0.005 ug/L for the arsenic species, 0.007 ug/L
for cadmium and 0.02 ug/L for lead. The detection limit
in the toenail samples was 0.05 ug/kg for total arsenic.
The detection limits of CHMS were 0.5 ug/L for total
arsenic, 0.8 ug/L for the arsenic species and 0.1 ug/L for
cadmium and lead, respectively.15
Genetic polymorphisms may occur as sequences or
single nucleotides. The latter is referred to as single
Chan HM, et al. BMJ Open 2020;10:e038507. doi:10.1136/bmjopen-2020-038507
nucleotide polymorphism (SNP). Several SNPs have been
identified to be associated with arsenic, most notably the
metabolism of arsenic.16–25 Based on previous evidence,
72 SNPs were selected that were hypothesised to underlie
interindividual differences in arsenic metabolism
including SNPs in genes of the following pathways and
classes: sheath interacting, nucleotide excision repair,
organic anion transporter, reduction activity in arsenic
metabolism, DNA repair, efflux carrier, transporter (ZIP
family metal transporter), one-carbon metabolism and
folate metabolism pathway. In this study, buccal swabs
were collected from participants using a DNA Genotek
buccal swab kit (OCR-100) and sent to Genome Quebec
where DNA was isolated from buccal swab with the QIA
symphony instrument along with the DSP Midi kit (cat#
937255, QIAGEN) according to the manufacturer’s
protocol, and genotyped using the Sequenom iPLEX
Gold platform.26
Immediate follow-up of participants with potential high
exposure
Participants with urine sample of at least one of the
COPCs exceeding the reference values (the 95th percentile of the CHMS) will be followed up and have urine
samples retested to confirm the higher exposure as well as
given advice on ways to lower their exposure. Participants
with persistently elevated levels will be followed up every
6 months. As no reference values are available for toenail
arsenic, the Health Effects Monitoring Programme Advisory Committee (HEMPAC) decided to use the 80th
percentile for children and 95th percentile for adults as
screening levels for arsenic in toenails to identify participants with an elevated level of exposure for follow-up.
Participants who had urinary lead concentrations exceed
the reference values were asked to have their blood lead
concentrations measured to confirm the lead exposure.
Patient and public involvement
There is no patient involved in this study. Our study
adopts an integrated knowledge approach to involve
the public. A HEMPAC was created as a mechanism
for member stakeholders to contribute to the development and implementation of the study. HEMPAC meets
once a month and consists of the following representatives: Crown-Indigenous Relations and Northern Affairs
Canada, the Government of the Northwest Territories
Department of Environment and Natural Resources, the
Government of the Northwest Territories Department of
Health and Social Services, Health Canada, City of Yellowknife, YKDFN, NSMA, Giant Mine Oversight Board and
the University of Ottawa.
The HEMPAC will continue the collaboration, consultation and coordination on matters arising from the
YKHEMP, including ongoing data analyses, management
of data files and requests from researchers and students
for access to data, the approval process for publications
and conference presentations, reports, funding opportunities, knowledge translation and intervention strategies.
5
BMJ Open: first published as 10.1136/bmjopen-2020-038507 on 28 September 2020. Downloaded from http://bmjopen.bmj.com/ on February 19, 2022 by guest. Protected by copyright.
Open access
A detailed communication plan has been developed to
facilitate public engagement. Progress of the study and
results are communicated through public meetings, news
channels, social media and web site www.ykhemp.ca.
Statistical analysis
Geometric mean and the corresponding 95% CI for
urinary and toenail COPC concentrations are reported.
Urinary inorganic arsenic concentration was calculated
as the total concentration of arsenite As(III), arsenate
As(V), monomethylarsonic acid and dimethylarsinic acid.
Values below the limit of detection (LOD) were replaced
with half the LOD. Sample weights and 500 bootstrap
weights were used to adjust for sampling design, generate
population-representative statistics, and to produce
appropriate variance estimation for both the YKHMEP
random sample and the CHMS. Combined data on urine
total arsenic, cadmium and lead collected in CHMS cycles
1 (2007–2009) and 2 (2009–2011) and the combined data
for urine inorganic arsenic collected from CHMS cycles
2 (2009–2011), 3 (2012–2013) and 4 (2014–2015) were
used as references.15 27 The data were merged with the
appropriate combined weights file for the specific combination of cycles being combined and taking into account
differences in age. As CHMS did not measure arsenic in
the toenail, there is no comparable data for reference
levels as in the case for metals in urine samples. All analyses were performed using Stata SE (V.14). A two-sample
t-test was performed to compare the urinary COPC
concentrations between YKHEMP populations and the
Canadian general population concentrations, as reported
by the CHMS. Sampling weights were used for comparisons between YKHEMP random sample and the CHMS.
The details of laboratory procedures of CHMS15 and
YKHEMP can be find elsewhere (http://www.ykhemp.
ca/reports.php).
Findings to date
Among the 2037 YKEHMP participants, 1966 participants have urinary COPC measurements, and 1872 have
toenail COPC measurements. Urinary total arsenic, inorganic arsenic, cadmium and lead concentrations are
presented in table 3. In general, the urinary total arsenic
concentration was lower in the YKHEMP participants
(especially in YKDFN and NSMA children), compared
with the CHMS. However, for urinary inorganic arsenic,
children participants from the Yellowknife randomised
sample group, the volunteer group and the YKDFN had
higher urinary concentrations than the adults within the
group, as well as CHMS results for the same age group
(especially age 6–11, table 4). YKHEMP participants
(both children and adults) had lower urinary cadmium
concentrations, compared with the CHMS participants.
Within YKHEMP participants, children had lower urinary
cadmium concentrations compared with adults. The
urinary lead concentration of YKHEMP participants was
comparable to CHMS participants. In general, YKHEMP
children participants had lower urinary concentrations of
total arsenic, cadmium and lead, compared with adults;
however, children were found to have higher toenail
concentrations of such COPC (table 5).
It is important to note that, in addition to contamination from historical gold mining activity, arsenic
also occurs naturally in the Yellowknife area because
of the local geological formations. The YKHEMP study
currently cannot distinguish arsenic exposures from
natural sources, the Giant mine or dietary sources.
Several ongoing analyses are being conducted to gain a
Table 3 Urinary total arsenic, inorganic arsenic, cadmium and lead concentrations (µg/L)—geometric means for Yellowknife
population by participation group from YKHEMP and Canadian population from CHMS
Random sample
Volunteers
YKDFN
NSMA
Canadian*
Sample size
211
198
75
13
4709
Total arsenic
7.5 (6.6 to 8.6)
8.2 (7.1 to 9.5)
6.7† (5.7 to 7.8)
4.1† (2.8 to 6.0)
8.2 (7.5 to 9.1)
Inorganic arsenic
6.6† (6.0 to 7.3)
7.2† (6.4 to 8.1)
6.4† (5.7 to 7.3)
4.7 (3.3 to 6.7)
5.4 (5.1 to 5.7)
Cadmium
0.06† (0.05 to 0.07)
0.06† (0.05 to 0.07)
0.08† (0.06 to 0.09)
0.05† (0.02 to 0.09)
0.26 (0.23 to 0.28)
Lead
0.44 (0.38 to 0.50)
0.44 (0.40 to 0.48)
0.52 (0.44 to 0.62)
0.37 (0.25 to 0.55)
0.42 (0.41 to 0.44)
3–19 years old
20–79 years old
Sample size
659
658
119
33
7094
Total arsenic
8.1† (7.4 to 8.8)
8.1† (7.5 to 8.7)
5.4† (4.6 to 6.4)
5.9† (4.5 to 7.7)
10.7 (9.5 to 12.1)
Inorganic arsenic
5.3 (5.0 to 5.6)
5.7 (5.4 to 6.0)
4.5† (4.1 to 5.0)
4.2† (3.3 to 5.3)
5.4 (5.1 to 5.7)
Cadmium
0.22† (0.20 to 0.23)
0.22† (0.20 to 0.24)
0.24† (0.21 to 0.28)
0.24† (0.16 to 0.35)
0.41 (0.39 to 0.44)
Lead
0.57 (0.53 to 0.61)
0.58 (0.54 to 0.61)
0.66† (0.58 to 0.75)
0.52 (0.40 to 0.67)
0.54 (0.52 to 0.57)
Values presented in the parentheses are the 95% CI.
*Presented numbers are the sample size for total arsenic, cadmium and lead, the sample size for inorganic arsenic differ from these.
†Significantly different from CHMS.
CHMS, Canadian Health Measures Survey; NSMA, North Slave Métis Alliance; YKDFN, Yellowknives Dene First Nation; YKHEMP,
Yellowknife Health Effects Monitoring Program.
6
Chan HM, et al. BMJ Open 2020;10:e038507. doi:10.1136/bmjopen-2020-038507
BMJ Open: first published as 10.1136/bmjopen-2020-038507 on 28 September 2020. Downloaded from http://bmjopen.bmj.com/ on February 19, 2022 by guest. Protected by copyright.
Open access
Table 4 Urinary total arsenic and inorganic arsenic concentrations (µg/L)—geometric means (GM) for randomly selected
samples from YKHEMP and Canadian population aged 3–79 from CHMS cycle 1 and 2
YHKEMP random sample
Age group
n
Weighted N
CHMS
Total arsenic
Inorganic arsenic
GM (95% CI)
GM (95% CI)
Weighted N
Total arsenic
Inorganic arsenic
GM (95% CI)
GM (95% CI)
3–5
6–11
39 686
91 1579
7.3 (5.6 to 9.5)
9.0 (7.0 to 11.6)
6.5 (5.1 to 8.2)
7.3 (6.2 to 8.8)*
1 081 167
2 122 370
6.6 (5.3 to 8.2)
8.1 (7.5 to 8.9)
5.1 (4.8 to 5.4)
5.5 (5.1 to 5.8)
12–19
81 1529
6.4 (5.2 to 7.8)*
6.0 (5.3 to 6.9)
3 287 580
9.1 (8.0 to 10.4)
5.5 (5.0 to 5.9)
20–39
260 6777
8.4 (7.4 to 9.6)*
5.9 (5.3 to 6.5)
8 978 147
10.7 (9.5 to 12.1)
5.7 (5.2 to 6.2)
40–59
60–79
292 5538
107 1841
7.9 (7.0 to 9.0)*
7.4 (5.9 to 9.2)*
4.9 (4.5 to 5.4)
4.4 (3.8 to 5.1)
9 827 356
5 116 239
10.7 (9.2 to 12.3)
11.2 (9.4 to 13.4)
5.1 (4.7 to 5.6)
5.3 (4.9 to 5.8)
Sample size for CHMS suppressed due to Statistics Canada requirement. Values presented in the parentheses are the 95% CI.
*Significantly different from CHMS.
CHMS, Canadian Health Measures Survey; YHKEMP, Yellowknife Health Effects Monitoring Program.
better understanding of the sources of arsenic exposure
in Yellowknife and its potential health impacts. Arsenic
species will be measured in different layers of the toenail.
This will help to understand the proportion of arsenic
exposure from dietary sources and toenail contamination from external contact (surface metal/contaminant
adsorption).
YKHEMP provides a unique opportunity to understand
the potential long-term health impacts as the Giant Mine
Remediation Project progresses, which may also apply to
remediation processes at other mining sites worldwide.
YKHEMP has several strengths. Both urine and toenail
samples were collected. Metal concentrations in urine and
toenail provide an estimate of arsenic and other COPC
exposure in different time periods and forms.28–31 Indigenous people (YKDFN and NSMA) who were more vulnerable to environmental contamination were also included
in the YKHEMP. YKDFN live closer to the Giant Mine area
compared with other YKHEMP participants. The higher
rates of consumption of locally harvested food also make
YKDFN and NSMA more likely to have a higher exposure to arsenic and other COPCs from dietary sources.
The comparison of their arsenic exposure and health
conditions to other YKHEMP participants, as well as to the
Canadian population, may provide additional information on arsenic’s health effect. A separate medical history
questionnaire was designed for YKDFN as well. The information collected by this questionnaire will be compared
with the medical file. Community involvement is another
strength of the YKHEMP. YKHEMP welcomed volunteers
to join the study. The number of volunteers was similar to
the random sample. By comparing the arsenic exposure
levels in the randomly selected sample and the volunteers, we will be able to see if any individual or group with
high exposure might be ignored by systematic sampling.
In addition, it will help in identifying possible participation bias. In this study, buccal swabs were collected from
participants. Analysis of polymorphisms will provide indications on how the genetic makeup of the study participants may affect the metabolism and kinetics of arsenic.
One weakness of the study is that it does not address
the potential long-term effects of legacy arsenic exposure of the populations in Yellowknife when the Giant
Mine was still in operation. The baseline measurement
of urine and toenail only reflect arsenic exposure of the
participants in recent days or months before the sample
Table 5 Toenail total arsenic, cadmium and lead concentrations (µg/g)—geometric means for the Yellowknife population by
participation group from YKHEMP
Random sample
Volunteers
YKDFN
NSMA
3–19 years old
Total arsenic
0.40 (0.33 to 0.47)
0.51 (0.43 to 0.62)
0.29 (0.24 to 0.37)
0.53 (0.25 to 1.14)
Cadmium
0.03 (0.02 to 0.03)
0.04 (0.03 to 0.04)
0.02 (0.01 to 0.02)
0.03 (0.01 to 0.09)
Lead
0.65 (0.55 to 0.75)
0.70 (0.59 to 0.84)
0.39 (0.30 to 0.49)
0.72 (0.44 to 1.17)
Total arsenic
0.11 (0.10 to 0.11)
0.13 (0.12 to 0.14)
0.09 (0.08 to 0.10)
0.13 (0.09 to 0.17)
Cadmium
Lead
0.01 (0.01 to 0.01)
0.25 (0.23 to 0.27)
0.01 (0.01 to 0.01)
0.25 (0.23 to 0.27)
0.01 (0.01 to 0.01)
0.17 (0.14 to 0.20)
0.01 (0.01 to 0.02)
0.19 (0.14 to 0.24)
20–79 years old
Values presented in the parentheses are the 95% CI.
NSMA, North Slave Métis Alliance; YKHEMP, Yellowknife Health Effects Monitoring Program.
Chan HM, et al. BMJ Open 2020;10:e038507. doi:10.1136/bmjopen-2020-038507
7
BMJ Open: first published as 10.1136/bmjopen-2020-038507 on 28 September 2020. Downloaded from http://bmjopen.bmj.com/ on February 19, 2022 by guest. Protected by copyright.
Open access
collection period. Therefore, while the YKHEMP baseline and subsequent data will provide essential information regarding the potential health impact during and
after the Giant Mine remediation process in the future,
it will be limited in examining the association between
legacy arsenic exposure and its long-term health impact.
Urine is a good medium to measure arsenic exposure;
however, it may not be the optimal one for the other
COPCs, for example, lead. Finally, this study only aims to
address health risks associated with chemical exposures
and does not capture other indirect health risks such as
those related to changes in their traditional diet and lifestyle. It also only reports current body burden and has not
accounted for behavioural changes that people may have
taken to protect themselves from arsenic in the environment, for example, not picking berries near the mine site,
travelling further from their community to fish and hunt,
and reduce their local fish and meat consumption.
study has been granted a Scientific Research License from the Aurora Research
Institute in Northwest Territories. Individual participation in the project was voluntary
and based on informed written consent following an oral and written explanation of
each project component.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available on reasonable request.
Investigators interested in learning more about the Project and how to obtain
YKHEMP data can contact ykhemp@uottawa.ca.
Open access This is an open access article distributed in accordance with the
Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which
permits others to distribute, remix, adapt, build upon this work non-commercially,
and license their derivative works on different terms, provided the original work is
properly cited, appropriate credit is given, any changes made indicated, and the use
is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
ORCID iD
Hing Man Chan http://orcid.org/0000-0003-4351-7483
REFERENCES
Ethics approval The study is approved by the Health Sciences and Sciences
Research Ethics Board of the University of Ottawa (http://research.uottawa.ca/
ethics/reb) and the Aurora College Research Ethics Committee. In addition, the
1 Sandlos J, Keeling A. Giant mine: historical summary, 2012.
Available: http://reviewboard.ca/upload/project_document/EA0809001_Giant_Mine__History_Summary.PDF [Accessed 19 Aug 2019].
2 Officer of the Auditor General Canada. Chapter 3 – Federal
contaminated sites and their impacts. In: 2012 spring report of the
commissioner of the environment and sustainable development,
2012. http://www.oag-bvg.gc.ca/internet/English/parl_cesd_201205_
03_e_36775.html
3 Stantec Consulting Company. Analysis of contaminants in tissues of
fish captured in the Yellowknife Bay area, northwest territories final
report. retrieved from public works and government services Canada,
2014.
4 Ratnaike RN. Acute and chronic arsenic toxicity. Postgrad Med J
2003;79:391–6.
5 Hong Y-S, Song K-H, Chung J-Y. Health effects of chronic arsenic
exposure. J Prev Med Public Health 2014;47:245–52.
6 Agency for toxic substances and disease registry (ATSDR).
Toxicological profile for arsenic. Atlanta, GA, 2007. www.atsdr.cdc.
gov/
7 Abernathy CO, Thomas DJ, Calderon RL. Toxicity and risk
assessment of trace elements health effects and risk assessment of
arsenic 1,2. Available: https://academic.oup.com/jn/article-abstract/
133/5/1536S/4558544 [Accessed 19 Aug 2019].
8 Kapaj S, Peterson H, Liber K, et al. Human health effects from
chronic arsenic poisoning-a review. J Environ Sci Health A Tox
Hazard Subst Environ Eng 2006;41:2399–428.
9 Abernathy C, Liu Y-P, Longfellow D, et al. Arsenic: health effects,
mechanisms of actions, and research issues. Available: https://ehp.
niehs.nih.gov/doi/pdf/10.1289/ehp.99107593 [Accessed 19 Aug
2019].
10 Tchounwou PB, Yedjou CG, Patlolla AK, et al. Heavy metal toxicity
and the environment. Exp Suppl 2012;101:133–64.
11 Han WK, Bailly V, Abichandani R, et al. Kidney injury molecule-1
(KIM-1): a novel biomarker for human renal proximal tubule injury.
Kidney Int 2002;62:237–44.
12 Cárdenas-González M, Osorio-Yáñez C, Gaspar-Ramírez O,
et al. Environmental exposure to arsenic and chromium in
children is associated with kidney injury molecule-1. Environ Res
2016;150:653–62.
13 Beamer P, Klimecki W, Loh M, et al. Association of children’s urinary
CC16 levels with arsenic concentrations in multiple environmental
media. Int J Environ Res Public Health 2016;13:521.
14 Ahmed S, Akhtar E, Roy A, et al. Arsenic exposure alters lung
function and airway inflammation in children: a cohort study in rural
Bangladesh. Environ Int 2017;101:108–16.
15 Health Canada. Second report on human biomonitoring of
environmental chemicals in Canada -Results of the Canadian health
measures survey cycle 2 (2009-2011). Ottawa, Ontario, 2013. https://
www.healthcanada.gc.ca
16 Agusa T, Fujihara J, Takeshita H, et al. Individual variations in
inorganic arsenic metabolism associated with AS3MT genetic
polymorphisms. Int J Mol Sci 2011;12:2351–82.
17 Agusa T, Iwata H, Fujihara J, et al. Genetic polymorphisms in
glutathione S-transferase (GST) superfamily and arsenic metabolism
in residents of the red River delta, Vietnam. Toxicol Appl Pharmacol
2010;242:352–62.
8
Chan HM, et al. BMJ Open 2020;10:e038507. doi:10.1136/bmjopen-2020-038507
Collaboration
The HEMPAC has full governance of and access to the
data, however, the University of Ottawa maintains the
database. Investigators interested in learning more about
the Project and how to obtain YKHEMP data can contact
ykhemp@uottawa.ca.
Twitter Rajendra Prasad Parajuli @parajulirp
Acknowledgements We would like to thank those who have been involved in the
Health Effects Monitoring Program. The Health Effects Monitoring Program Advisory
Committee, the research assistants and research nurses involved in data collection,
and technicians involved in laboratory analyses. We would also like to acknowledge
those involved in questionnaire programming, website design, translation of survey
materials, and staff from Statistics Canada in facilitating survey sampling. The
analysis presented in this report (CHMS part) was conducted at the COOL RDC,
which is part of the Canadian Research Data Centre Network (CRDCN). The services
and activities provided by the COOL RDC were made possible by the financial
or in-kind support of the SSHRC, the CIHR, the CFI, Statistics Canada, Carleton
University, University of Ottawa, and the Université du Québec en Outaouais. We
would also like to thank the members of the Advisory Committee and Subramanian
Karthikeyan from Health Canada for providing constructive comments to the
manuscript.
Contributors HMC was responsible for the funding acquisition, conception and
design of the study; data acquisition and interpretation; and drafting and revising
the manuscript. XFH, JC and RPP were responsible for data acquisition, analysis
and interpretation; and drafting and revising the manuscript. RR and EY were
responsible for data acquisition and interpretation; and revising the manuscript. LW
and AM were responsible for conception and design of the study, data acquisition
and interpretation; and revising the manuscript. All contributors agreed to be
accountable for all aspects of the work in ensuring that questions related to the
accuracy or integrity of any part of the work are appropriately investigated and
resolved.
Funding Funding was provided by the Crown-Indigenous Relations and Northern
Affairs Canada. Hing Man Chan is a holder of a Canada Research Chair funded the
Canada Research Chair Program. Award/Grant number is not applicable for both
funding sources.
Competing interests None declared.
Patient and public involvement Patients and/or the public were involved in the
design, or conduct, or reporting, or dissemination plans of this research. Refer to
the Methods section for further details.
Patient consent for publication Not required.
BMJ Open: first published as 10.1136/bmjopen-2020-038507 on 28 September 2020. Downloaded from http://bmjopen.bmj.com/ on February 19, 2022 by guest. Protected by copyright.
Open access
18 Applebaum KM, Karagas MR, Hunter DJ, et al. Polymorphisms
in nucleotide excision repair genes, arsenic exposure, and nonmelanoma skin cancer in New Hampshire. Environ Health Perspect
2007;115:1231–6.
19 Banerjee M, Marensi V, Conseil G, et al. Polymorphic variants of
MRP4/ABCC4 differentially modulate the transport of methylated
arsenic metabolites and physiological organic anions. Biochem
Pharmacol 2016;120:72–82.
20 De Chaudhuri S, Ghosh P, Sarma N, et al. Genetic variants
associated with arsenic susceptibility: study of purine nucleoside
phosphorylase, arsenic (+3) methyltransferase, and glutathione Stransferase omega genes. Environ Health Perspect 2008;116:501–5.
21 Schläwicke Engström K, Broberg K, Concha G, et al. Genetic
polymorphisms influencing arsenic metabolism: evidence from
Argentina. Environ Health Perspect 2007;115:599–605.
22 Fujihara J, Soejima M, Yasuda T, et al. Global analysis of genetic
variation in human arsenic (+3 oxidation state) methyltransferase
(AS3MT). Toxicol Appl Pharmacol 2010;243:292–9.
23 Gomez-Rubio P, Meza-Montenegro MM, Cantu-Soto E, et al.
Genetic association between intronic variants in AS3MT and arsenic
methylation efficiency is focused on a large linkage disequilibrium
cluster in chromosome 10. J Appl Toxicol 2010;30:260–70.
24 Hsu L-I, Wu M-M, Wang Y-H, et al. Association of environmental
arsenic exposure, genetic polymorphisms of susceptible genes, and
skin cancers in Taiwan. Biomed Res Int 2015;2015:1–10.
25 Lesseur C, Gilbert-Diamond D, Andrew AS, et al. A case-control
study of polymorphisms in xenobiotic and arsenic metabolism genes
and arsenic-related bladder cancer in New Hampshire. Toxicol Lett
2012;210:100–6.
26 Gabriel S, Ziaugra L, Tabbaa D. SNP genotyping using the
sequenom massARRAY iPLEX platform. In: Current protocols
in human genetics. Hoboken, NJ: John Wiley & Sons, Inc,
2009.
27 Health Canada. Forth report on human biomonitoring of
environmenta chemicals in Canada - results of the Canadian health
mesures survey. Ottawa, Ontario, 2017.
28 Button M, Jenkin GRT, Harrington CF, et al. Human toenails as a
biomarker of exposure to elevated environmental arsenic. J Environ
Monit 2009;11:610.
29 Mandal BK, Ogra Y, Suzuki KT. Speciation of arsenic in human
nail and hair from arsenic- affected area by HPLC- inductively
coupled argon plasma mass spectrometry. Toxicol Appl
Pharmacol 2003;189:73–83.
30 Normandin L, Ayotte P, Levallois P, et al. Biomarkers of arsenic
exposure and effects in a Canadian rural population exposed
through groundwater consumption. J Expo Sci Environ Epidemiol
2014;24:127–34.
31 Pearce DC, Dowling K, Gerson AR, et al. Arsenic microdistribution
and speciation in toenail clippings of children living in a historic gold
mining area. Sci Total Environ 2010;408:2590–9.
Chan HM, et al. BMJ Open 2020;10:e038507. doi:10.1136/bmjopen-2020-038507
9
BMJ Open: first published as 10.1136/bmjopen-2020-038507 on 28 September 2020. Downloaded from http://bmjopen.bmj.com/ on February 19, 2022 by guest. Protected by copyright.
Open access