Urinary arsenic species concentration in residents living near abandoned metal mines in South Korea
https://doi.org/10.1186/s40557-016-0150-z
© The Author(s). 2016
Received: 16 June 2016
Accepted: 7 November 2016
Published: 22 November 2016
Abstract
Background
Arsenic is a carcinogenic heavy metal that has a species-dependent health effects and abandoned metal mines are a source of significant arsenic exposure. Therefore, the aims of this study were to analyze urinary arsenic species and their concentration in residents living near abandoned metal mines and to monitor the environmental health effects of abandoned metal mines in Korea.
Methods
This study was performed in 2014 to assess urinary arsenic excretion patterns of residents living near abandoned metal mines in South Korea. Demographic data such as gender, age, mine working history, period of residency, dietary patterns, smoking and alcohol use, and type of potable water consumed were obtaining using a questionnaire. Informed consent was also obtained from all study subjects (n = 119). Urinary arsenic species were quantified using high performance liquid chromatography (HPLC) and inductively coupled plasma mass spectrometry (ICP/MS).
Results
The geometric mean of urinary arsenic (sum of dimethylarsinic acid, monomethylarsonic acid, As3+, and As5+) concentration was determined to be 131.98 μg/L (geometric mean; 95% CI, 116.72–149.23) while urinary inorganic arsenic (As3+ and As5+) concentration was 0.81 μg/L (95% CI, 0.53–1.23). 66.3% (n = 79) and 21.8% (n = 26) of these samples exceeded ATSDR reference values for urinary arsenic (>100 μg/L) and inorganic arsenic (>10 μg/L), respectively. Mean urinary arsenic concentrations (geometric mean, GM) were higher in women then in men, and increased with age. Of the five regions evaluated, while four regions had inorganic arsenic concentrations less than 0.40 μg/L, one region showed a significantly higher concentration (GM 15.48 μg/L; 95% CI, 7.51–31.91) which investigates further studies to identify etiological factors.
Conclusion
We propose that the observed elevation in urinary arsenic concentration in residents living near abandoned metal mines may be due to environmental contamination from the abandoned metal mine.
Trial registration
Not Applicable (We do not have health care intervention on human participants).
Keywords
Background
Arsenic is a naturally occurring element that is widely found in ground water and agricultural products and is one of the most abundant elements in the earth’s crust. Chronic arsenic exposure in humans is associated with diseases such as skin, lung, and hepatic cancer [1–3] and the primary sources of human exposure include ingestion of inorganic arsenic from contaminated water [4], industrial waste, pesticides, and inadequate mine waste disposal [5–7]. As most arsenic metabolites are soluble in water, they contaminate river and underground water, and arsenic contamination in ground water is categorized as a serious public health hazard. According to the United States Agency for Toxic Substances and Disease Registry (ATSDR) [8], the oral route is considered to be a predominant means of arsenic exposure in the general population. Several studies have also reported that exposure to or consumption of, even low levels, arsenic can lead to carcinogenesis [9–11]. In the last few decades, many studies have measured urinary arsenic concentration (organic and inorganic arsenic) and many older studies have used urinary arsenic as a biomarker of recent arsenic exposure. This latter approach, however, became obsolete as certain foods also contain organic arsenic which is similarly excreted in urine. As each arsenic species has different physiological and bioactive properties, separation of urinary arsenic metabolites is considered sufficient to both prevent potential overestimation of arsenic concentration and assess health risk [12, 13].
Metal mining was economically important in during the 19th century, however, many mines were abandoned because of the change in industrial and economic conditions during the late 1970s [14]. Such abandoned metal mines have been identified as an important source of environmental heavy metal contamination and elevated levels of these toxic elements are often present in the soil and ground water of various countries [15, 16]. In many areas of Korea, there is evidence that the uncontrolled abandoning of these metal mines has had a large and lasting impact [17] as metals and metalloids dissolved from these mines may have contaminated both surface and ground water through solubilization into the surrounding environment. Further, as preventive measures to avoid environmental pollution after closures were not adequately implemented in some of these mines, debris from them, such as spoil heaps and water, remain potential source of environmental contamination. Therefore, this study was evaluated concentrations of urinary arsenic species in residents living near abandoned metal mines in Korea.
Methods
Study subjects and questionnaire
The five provinces and locations of abandoned metal mines in this study
Urine sample collection
All spot urine samples for organic and inorganic arsenic measurements were collected in disposable urine collection cups, placed in 15 ml polyethylene tubes, maintained at 4 °C, and transported to a laboratory where they were stored at – 70 °C till further analysis.
Urinary arsenic speciation
Urinary arsenic species were analyzed at the Environmental Health Center, Dong-A university. Arsenic species were separated using an inductively coupled plasma mass spectrometry (ICP-MS) instrument (Agilent Technologies, Santa Clara, CA, USA) equipped with a high performance liquid chromatography (HPLC) system (Agilent 1260 Infinity, Agilent Technologies, Santa Clara, CA, USA). This methodology analyses As3+, As5+, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) concentrations and the respective limits of detection are 0.17, 0.13, 0.19, and 0.12 μg/L. Urinary arsenic concentration was defined sum of the As3+, As5+, MMA, and DMA concentrations in this study. All urine samples were filtered through a 0.22 μm membrane before being placed into chromatographic vials, and the auto-sampler tray. Five-point calibration curves for all arsenic species tested (As3+, As5+, MMA and DMA) showed satisfactory linearity and the four major arsenic species could be separated within 16 min. The proportion of each arsenic species was calculated by dividing the concentration of that species by urinary arsenic. Replicate analyses of the standard reference material (SRM 2669, NIST standard, quality control) showed coefficient of variation to be less than 8%. For external quality assurance, we also completed both the occupational-medical and environmental-medical programs of German External Quality Assessment Scheme (G-EQUAS) of the Friedrich Alexander University, Erlangen.
Statistical analysis
All statistical analyses were performed using the SAS statistical software (Version 9.4, SAS Institute, Cary, NC). Chi-square test for independence was performed for gender, age, period of residence, smoking, alcohol, type of drinking water, and history of working in mines. Arsenic species concentration is presented as unadjusted and adjusted geometric means with 95% confidence interval due to its right skewed distribution. The ANOVA and t-test were used to examine the relationship between demographic characteristics and arsenic species concentration. A p-value < 0.05 was considered statistically significant.
Results
Characteristics of the study population
General characteristics, including demographic and lifestyle data, of the study subjects
Characteristics | Total | Province | p-value | |||||
|---|---|---|---|---|---|---|---|---|
Gangwon/Kyounggi/Inchon | Daegu/Gyeongbuk | Busan/Ulsan/Gyeongnam | Jeonnam/Jeonbuk | Chungnam/Chungbuk | ||||
Total | 119 | 25(21.0) | 25(21.0) | 14(11.8) | 36(30.3) | 19(16.0) | ||
Gender | Male | 54(45.4) | 7(28.0) | 13(52.0) | 4(28.6) | 19(52.8) | 11(57.9) | 0.132 |
Female | 65(54.6) | 18(72.0) | 12(48.0) | 10(71.4) | 17(47.2) | 8(42.1) | ||
Age(yr) | mean ± std | 70.76 ± 9.17 | 71.44 ± 9.51 | 71.12 ± 7.10 | 70.57 ± 7.94 | 68.89 ± 11.01 | 73.11 ± 8.31 | 0.578 |
41–59 | 13(10.9) | 2(8.0) | 1(4.0) | 2(14.3) | 7(19.4) | 1(5.3) | 0.541 | |
60–69 | 37(31.1) | 8(32.0) | 7(28.0) | 3(21.4) | 13(36.1) | 6(31.6) | ||
≥70 | 69(58.0) | 15(60.0) | 17(68.0) | 9(64.3) | 16(44.4) | 12(63.2) | ||
Period fo residence(yr) | mean ± std | 50.28 ± 23.77 | 40.04 ± 24.30 | 57.68 ± 21.56 | 52.93 ± 20.53 | 51.92 ± 25.41 | 48.42 ± 22.50 | 0.117 |
≤40 | 35(29.7) | 12(50.0) | 3(12.0) | 4(28.6) | 11(30.6) | 5(26.3) | 0.178 | |
41–60 | 37(31.4) | 7(29.2) | 9(36.0) | 3(21.4) | 10(27.8) | 8(42.1) | ||
≥61 | 46(39.0) | 5(20.8) | 13(52.0) | 7(50.0) | 15(41.7) | 6(31.6) | ||
Smoking | Current smoker | 14(11.8) | 2(8.0) | 5(20.0) | 2(14.3) | 5(13.9) | 0 (0.0) | 0.379 |
Ex-smoker | 22(18.5) | 3(12.0) | 6(24.0) | 2(14.3) | 5(13.9) | 6(31.6) | ||
Non-smoker | 83(69.7) | 20(80.0) | 14(56.0) | 10(71.4) | 26(72.2) | 13(68.4) | ||
Alcohol | Drinking | 64(53.8) | 10(40.0) | 18(72.0) | 5(35.7) | 23(63.9) | 8(42.1) | 0.048 |
Non-drinking | 55(46.2) | 15(60.0) | 7(28.0) | 9(64.3) | 13(36.1) | 11(57.9) | ||
House income(KRW) | Below 500,000 | 63(52.9) | 19(76.0) | 11(44.0) | 7(50.0) | 18(50.0) | 8(42.1) | 0.035 |
500,000–1,000,000 | 20(16.8) | 1(4.0) | 3(12.0) | 3(21.4) | 11(30.6) | 2(10.5) | ||
1,000,000–2,000,000 | 36(30.3) | 5(20.0) | 11(44.0) | 4(28.6) | 7(19.4) | 9(47.4) | ||
Mine working history | Yes | 17(14.4) | 0 (0.0) | 10(40.0) | 1(7.1) | 5(13.9) | 1(5.6) | 0.001 |
No | 101(85.6) | 25(100.0) | 15(60.0) | 13(92.9) | 31(86.1) | 17(94.4) | ||
Dietary water | Tap water | 30(31.9) | 3(12.5) | 3(50.0) | 5(41.7) | 10(27.8) | 9(56.3) | 0.037 |
Underground water | 64(68.1) | 21(87.5) | 3(50.0) | 7(58.3) | 26(72.2) | 7(43.8) | ||
Herbicide | Yes | 73(70.2) | 13(52.0) | 9(90.0) | 10(71.4) | 26(72.2) | 15(78.9) | 0.158 |
No | 31(29.8) | 12(48.0) | 1(10.0) | 4(28.6) | 10(27.8) | 4(21.1) | ||
Concentration of urinary arsenic species
Distribution of urinary arsenic species concentration (μg/L) in the populations living near abandoned metal mines at each province
Province | Number | Arsenic species | GM(95% CI), μg/L | |
|---|---|---|---|---|
Total | 119 | Organic | DMA | 116.11(102.03–132.13) |
MMA | 2.08(1.41–3.08) | |||
Inorganic | As3+ | 0.30(0.20–0.47) | ||
As5+ | 0.37(0.24–0.56) | |||
uAs | 131.98(116.72–149.23) | |||
Gangwon/Kyounggi/Inchon | 25 | Organic | DMA | 138.69(112.83–170.47) |
MMA | 0.73(0.35–1.52) | |||
Inorganic | As3+ | <LOD(0.07–0.29) | ||
As5+ | <LOD(0.07–0.26) | |||
uAs | 144.39(116.80–178.51) | |||
Daegu/Gyeongbuk | 25 | Organic | DMA | 134.92(116.51–156.23) |
MMA | 1.66(0.94–2.92) | |||
Inorganic | As3+ | <LOD | ||
As5+ | <LOD | |||
uAs | 138.18(119.59–159.65) | |||
Busan/Ulsan/Gyeongnam | 14 | Organic | DMA | 117.29(89.51–153.71) |
MMA | 0.73(0.25–2.12) | |||
Inorganic | As3+ | <LOD | ||
As5+ | <LOD | |||
uAs | 119.88(91.22–157.53) | |||
Jeonnam/Jeonbuk | 36 | Organic | DMA | 108.36(76.45–153.59) |
MMA | 22.61(17.47–29.26) | |||
Inorganic | As3+ | 4.96(2.31–10.61) | ||
As5+ | 7.10(4.26–11.82) | |||
uAs | 156.06(114.28–213.12) | |||
Chungnam/Chungbuk | 19 | Organic | DMA | 85.33(62.65–116.22) |
MMA | 0.26(0.14–0.50) | |||
Inorganic | As3+ | <LOD | ||
As5+ | <LOD | |||
uAs | 86.25(63.42–117.30) | |||
Unadjusted geometric means of the arsenic species concentration in residents living near abandoned metal mines
Characteristics | Number | Organic As (μg/L) | Inorganic As (μg/L) | Urinary Arsenic (μg/L) | |||
|---|---|---|---|---|---|---|---|
DMA | MMA | As3+ | As5+ | ||||
Total | 119 | 116.11(102.03–132.13) | 2.08(1.41–3.08) | 0.30(0.20–0.47) | 0.37(0.24–0.56) | 131.98(116.72–149.23) | |
Gender | Male | 54 | 100.55(83.55–121.02) | 2.37(1.32–4.25) | 0.36(0.19–0.69) | 0.45(0.24–0.84) | 118.42(100.40–139.68) |
Female | 65 | 130.85(109.42-156.47) | 1.87(1.09–3.20) | 0.27(0.15–0.47) | 0.31(0.18–0.55) | 144.42(120.72–172.76) | |
p-value | 0.044 | 0.550 | 0.486 | 0.396 | 0.112 | ||
Age(yr) | 41-59 | 13 | 95.17(61.56–147.12) | 3.23(0.74–14.03) | 0.54(0.11–2.73) | 0.89(0.21–3.78) | 116.28(76.34–177.12) |
60-69 | 37 | 102.00(80.18–129.78) | 2.19(1.01–4.75) | 0.46(0.19–1.08) | 0.54(0.24–1.20) | 121.18(98.10–149.67) | |
≥70 | 69 | 129.21(109.33–152.70) | 1.86(1.14–3.04) | 0.22(0.13–0.37) | 0.25(0.15–0.43) | 141.50(119.71–167.26) | |
p-value | 0.150 | 0.694 | 0.202 | 0.088 | 0.415 | ||
Period of residence | ≤40 | 35 | 104.43(83.68–130.32) | 0.93(0.41–2.11) | 0.26(0.12–0.56) | 0.34(0.16–0.70) | 117.03(94.82–144.43) |
41-60 | 37 | 139.65(111.45–174.99) | 2.39(1.16–4.95) | 0.25(0.11–0.56) | 0.46(0.19–1.11) | 156.52(123.50–198.37) | |
≥61 | 46 | 107.73(85.53–135.70) | 3.40(1.97–5.87) | 0.41(0.20–0.85) | 0.34(0.18–0.64) | 125.50(102.29–153.98) | |
p-value | 0.154 | 0.025 | 0.581 | 0.781 | 0.159 | ||
Smoking | Current-smoker | 14 | 79.08(44.38–140.91) | 1.68(0.52–5.41) | 0.20(0.06–0.65) | 0.33(0.11–1.04) | 97.16(64.31–146.79) |
Ex-smoker | 22 | 118.72(94.31–149.46) | 2.08(0.79–5.47) | 0.33(0.11–0.99) | 0.32(0.11–0.89) | 133.37(103.50–171.87) | |
Non-smoker | 83 | 123.15(105.98–143.10) | 2.16(1.34–3.48) | 0.32(0.19–0.54) | 0.39(0.23–0.65) | 138.59(119.22–161.12) | |
p-value | 0.096 | 0.923 | 0.787 | 0.928 | 0.192 | ||
Alcohol | Drinking | 64 | 102.89(85.73-123.48) | 2.37(1.38-4.07) | 0.34(0.19-0.60) | 0.50(0.28-0.91) | 121.14(103.12-142.31) |
Non-drinking | 55 | 133.65(111.54-160.14) | 1.79(1.00-3.20) | 0.27(0.14-0.52) | 0.26(0.14-0.45) | 145.82(120.53-176.42) | |
p-value | 0.045 | 0.478 | 0.602 | 0.108 | 0.137 | ||
Income(KRW) | Below 500,000 | 63 | 116.52(96.59–140.55) | 2.07(1.21–3.53) | 0.28(0.16–0.50) | 0.38(0.21–0.69) | 131.29(109.08–158.02) |
500,000-1,000,000 | 20 | 106.50(71.20–159.29) | 4.28(1.52–12.06) | 0.58(0.17–2.00) | 0.81(0.26–2.48) | 131.59(95.09–182.10) | |
1,000,000-2,000,000 | 36 | 121.07(100.01–146.55) | 1.40(0.68–2.90) | 0.25(0.11–0.54) | 0.23(0.12–0.44) | 133.42(110.09–161.70) | |
p-value | 0.813 | 0.180 | 0.389 | 0.137 | 0.993 | ||
Mine working history | Yes | 17 | 124.94(92.57–168.63) | 3.29(1.29–8.38) | 0.32(0.09–1.10) | 0.32(0.10–1.02) | 139.92(105.61–185.38) |
No | 101 | 116.66(101.27–134.38) | 1.98(1.28–3.06) | 0.31(0.19–0.49) | 0.38(0.24–0.60) | 133.09(116.44–152.11) | |
p-value | 0.709 | 0.370 | 0.928 | 0.792 | 0.773 | ||
Dietary water | Tap water | 30 | 118.61(96.99–145.05) | 1.72(0.72–4.10) | 0.27(0.11–0.68) | 0.55(0.22–1.37) | 134.40(108.52–166.46) |
Underground water | 64 | 112.52(91.42–138.48) | 2.56(1.44–4.56) | 0.56(0.30–1.05) | 0.55(0.30–1.00) | 133.40(110.23–161.45) | |
p-value | 0.713 | 0.438 | 0.203 | 0.996 | 0.962 | ||
Herbicide | Yes | 73 | 111.02(93.53–131.78) | 2.22(1.30–3.78) | 0.34(0.19–0.61) | 0.52(0.30–-0.93) | 128.19(108.42–151.56) |
No | 31 | 119.48(89.07–160.27) | 1.70(0.75–3.81) | 0.46(0.19–1.13) | 0.33(0.15–0.72) | 137.37(105.42–179.00) | |
p-value | 0.651 | 0.583 | 0.561 | 0.359 | 0.655 | ||
Adjusted geometric means for each province
Adjusted GM(95% CI), μg/L | p-value | |||||||
|---|---|---|---|---|---|---|---|---|
Total | Gangwon/Kyounggi/Inchon | Daegu/Gyeongbuk | Busan/Ulsan/Gyeongnam | Jeonnam/Jeonbuk | Chungnam/Chungbuk | |||
oAs | DMA | 92.04(63.09–134.28) | 108.01(62.46–186.77) | 106.67(54.03–210.59) | 86.67(48.54–154.76) | 98.25(64.67–149.28) | 58.02(33.86–99.43) | 0.161 |
MMA | 4.35(1.36–13.93) | 1.22(0.48-3.11)a | 0.45(0.14–1.44)ac | 0.84(0.31–2.24)ac | 32.80(16.08–66.89)b | 0.24(0.09–0.59)c | <0.001 | |
Subtotal | 106.62(74.49–152.62) | 113.69(68.39–189.02)a | 112.00(59.57–210.56)a | 90.88(53.06–155.66)a | 124.11(84.17–182.98)a | 61.56(37.34–101.48)a | 0.040 | |
iAs | As3+ | 0.84(0.23–3.04) | 0.14(0.04–0.46)a | 0.13(0.03–0.56)a | 0.07(0.02–0.23)a | 6.18(2.50–15.32)b | 0.06(0.02–0.20)a | <0.001 |
As5+ | 0.83(0.24–2.87) | 0.12(0.04–0.34)a | 0.10(0.03–0.36)a | 0.10(0.03–0.28)a | 6.55(3.03–14.17)b | 0.05(0.02–0.15)a | <0.001 | |
Subtotal | 1.84(0.53–6.43) | 0.30(0.11–0.76)a | 0.24(0.07–0.77)a | 0.15(0.06–0.41)a | 15.48(7.51–31.91)b | 0.11(0.04–0.27)a | <0.001 | |
uAs | 115.84(80.17–167.38) | 116.59(70.11–193.87)ac | 113.73(60.47–213.88)ac | 91.91(53.64–157.46)ac | 144.03(97.67–212.39)b | 61.38(37.22–101.21)c | 0.008 | |
The number of samples whose levels exceeded the reference levels of inorganic arsenic in each province
Number | Number of exceed reference levels (%) Inorganic arsenic (>10 μg/L)a | ||
|---|---|---|---|
Total | 119 | 26(21.8) | |
Province | Gangwon/Kyounggi/Inchon | 25 | 2(8.0) |
Daegu/Gyeongbuk | 25 | 0(0.0) | |
Busan/Ulsan/Gyeongnam | 14 | 0(0.0) | |
Jeonnam/Jeonbuk | 36 | 24(66.7) | |
Chungnam/Chungbuk | 19 | 0(0.0) | |
Discussion
This study analyzed urinary arsenic species and their concentration in populations living near abandoned metal mines using HPLC-ICP-MS, and to the best of our knowledge, is the first to do so. The study population comprised only adult, and as participation was voluntary, the demographic data and results presented here are not representative of the general population. A spot urine sample was used for analyses because 24 h urine collection is uncomfortable and often results in improper or incomplete collection. Samples obtained from residents living near one abandoned metal mine located in the Jeonnam/Jeonbuk province alone showed significantly higher concentrations of urinary arsenic and inorganic arsenic. Moreover, life style and demographic status of residents in the Jeonnam/Jeonbuk province was not significantly different compare with other provinces. Potable water and food are important sources of human arsenic exposure, and urinary arsenic concentrations have been reported to be higher in populations living near contaminated areas compared to those residing in uncontaminated area [19–21]. Based on the health risks associated with arsenic exposure, the United States Environmental Protection Agency (USEPA) has established a reference level of 10 μg/L for dietary water [22]. According to the Survey of the Heavy Metals on Farmland Soil and Drainage at Abandoned Mine Area by the National Institute of Environmental Research in Korea (NIER, 2008), arsenic contamination of farmland soil and water within a distance of 2 km from an abandoned metal mine in the Jeonnam/Jeonbuk province exceeded both the preliminary standard and countermeasure standard for arsenic concentration. The Korean National Environmental Health Survey [23] has reported urinary arsenic concentrations of 35.0 μg/L (GM; 95% CI, 33.8–36.2 μg/L) in the general population aged over 20 years: using the hydride generation method. However, we show that mean urinary arsenic concentration (GM) in populations living near abandoned metal mines is significantly higher than that reported in the NIER survey. This discrepancy could be due to food consumption patterns, as food is an important source of organic arsenic (DMA and MMA) and a possible confounding factor during urinary arsenic species analysis. DMA is found in food as it is the end product of the arsenic metabolic pathway, irrespective of the arsenic species entering the living organism. In addition, seaweed and seafood contain arsenosugars that are converted to DMA after consumption and is excreted as such in urine [24]. Even though we recommended that all participants refrain from seaweed and seafood consumption for at least 3 days prior to sampling, it could not be strictly enforced. We observed that women had significantly higher DMA concentrations than men (P = 0.044), probably because available literature suggests that women can more efficiently methylate arsenic compared to men [25–27]. Our data show that DMA is the predominant arsenic metabolite in urine (69.2–95%) followed by MMA (1.2–14%), and inorganic arsenic (0.3–7.7%). Previous studies have reported similar results where DMA contributed to 84–86% of the urinary arsenic species [28, 29]. In 2000, a WHO report estimated that the arsenic content of cigarette smoke was 40–120 ng per cigarette [30]. However, we observed that smoking was not a significant determinant of urinary arsenic species concentration.
Conclusion
We show that residents living near abandoned metal mines are not markedly overexposed to arsenic except in the case of one abandoned metal mine in the Jeonnam/Jeonbuk province. A probable reason for this observation is consumption of arsenic-contaminated ground water from near the abandoned metal mine.
A limitation of our study is that the arsenic exposed group did not have comparable control subjects. Further, only 10% of the 974 samples were subjected to arsenic species analyses. We, therefore, suggest that all future studies implement arsenic species analysis in all samples rather than only in a subset. We, meanwhile, could not survey the consumption of seafood and seaweed at that time. But, we are going to consider assessment the relationship between arsenic concentration and seafood consumption in the next study. As there are no reports on the analysis of urinary arsenic species using HPLC-ICP-MS in populations living near abandoned metal mines in Korea, this study provides valuable data on the prevalence and concentration of urinary arsenic species in arsenic exposed populations, especially abandoned metal mine area.
Declarations
Acknowledgements
This study was conducted by the Heavy Metal Exposure Environmental Health Center Research Fund at the Dong-A University supported by the Ministry of Environment, Korea.
Authors’ contributions
JY is the first author of this article and had drafted the manuscript. YS is the corresponding author and JW performed statistical analysis of this article. HJ performed urinary arsenic species analysis using HPLC-ICP-MS. BG, BK, JD, JS, MJ, JD, BS, NS, SD, and BJ contributed to the data collection and exposure assessment. All authors revised this manuscript critically. All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
Not applicable.
Ethics approval and consent to participate
This research was approved by the Dong-A University Institutional Review Board (No. 2-1040709-AB-N-01-201404-BR-04-04).
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Authors’ Affiliations
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