KSOEM
Articles
- Page Path
- HOME > Ann Occup Environ Med > Volume 29; 2017 > Article
- Research Article Association of arsenobetaine with beta-cell function assessed by homeostasis model assessment (HOMA) in nondiabetic Koreans: data from the fourth Korea National Health and Nutrition Examination Survey (KNHANES) 2008-2009
- Kiook Baek1, Namhoon Lee1, Insung Chung1,2
-
Annals of Occupational and Environmental Medicine 2017;29:31.
DOI: https://doi.org/10.1186/s40557-017-0181-0
Published online: July 10, 2017
1Division of Occupational and Environmental Medicine, Keimyung University Dongsan Medical Center, Daegu, South Korea
2Department of Preventive Medicine, Keimyung University School of Medicine, Daegu, South Korea
• Received: November 3, 2016 • Accepted: June 15, 2017
© The Author(s). 2017
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.
Abstract
-
Background Arsenic is known as an endocrine disruptor that people are exposed to through various sources such as drinking water and indigestion of marine products. Although some epidemiological and animal studies have reported a correlation between arsenic exposure and diabetes development, there are limited studies regarding the toxic effects of organic arsenic including arsenobetaine on the human body. Here, we analyzed the association between urine arsenobetaine and the homeostasis model assessment of β-cell function (HOMA-β), which is an index for predicting diabetes development and reflecting the function of pancreatic β-cells.
-
Methods In the fourth Korea National Health and Nutrition Examination Survey (KNHANES), health and nutrition surveys and screening tests were performed. Of the total survey population, people with confirmed values for urine total arsenic and arsenobetaine were included, and known diabetic patients were excluded. A total 369 participants were finally included in the study. We collected surveys on health, height, body weight, body mass index, blood mercury level, fasting glucose level, and serum insulin level and calculated HOMA index. Owing to sexual discrepancy, we performed sexually stratified analysis.
-
Results Urine total arsenic and total arsenic minus arsenobetaine was not associated with HOMA-IR and HOMA-β in univariate analysis or in sexually stratified analysis. However, urine arsenobetaine showed a statistically significant relationship with HOMA-β in univariate analysis, and only male participants showed a significant correlation in sexually stratified analysis. In the analysis adjusted for age, BMI, smoking, alcohol drinking, physical activity and blood mercury, the HOMA-β value in the group below the 25th percentile of arsenobetaine was significantly higher than the group between 50 and 75th percentile, while no difference was shown for HOMA-IR. In sexually stratified analysis, The value of HOMA-β was significantly higher in male participants with below the 25th percentile urine arsenobetaine than the group between 25 and 50th and between 50 and 75th, while no difference was shown for HOMA-IR. However, female participants did not demonstrate a relationship between HOMA–IR, HOMA-β and urine arsenobetaine.
-
Conclusion This study revealed the association between urine arsenobetaine and pancreatic β-cell function assessed by HOMA-β in the normal population (without diabetes), especially in males, despite adjusting for factors affecting pancreatic β-cell function and diabetes.
-
Electronic supplementary material The online version of this article (doi:10.1186/s40557-017-0181-0) contains supplementary material, which is available to authorized users.
Background
Arsenic is a well-known toxic material that people can be exposed to through various sources. Exposure to inorganic arsenic is mainly through drinking water [1] and to organic arsenic is through marine products and seaweeds [2]. Arsenic is known as an endocrine-disrupting chemical causing various endocrine disorders [3].
Diabetes is reported to develop through two mechanisms: dysfunction of pancreatic β-cells and insulin resistance. The homeostasis model assessment (HOMA) model is widely accepted in epidemiological studies of pancreatic β-cell function and insulin resistance, which includes HOMA-IR for insulin resistance and HOMA-β for pancreatic β-cell function [4].
Many epidemiological and experimental studies have demonstrated the association between arsenic exposure and diabetes [5, 6]. Although there have been some speculative mechanisms of developing insulin resistance and β-cell dysfunction from arsenic exposure, the cellular and molecular mechanisms involved remain unclear [7].
Previous studies have used urine arsenic or urine inorganic arsenic as a marker of biological exposure for evaluating the correlation between arsenic, diabetes, and insulin resistance; however, organic arsenic, such as arsenobetaine, has been observed as a confounding factor [8, 9]. Although previous studies have reported arsenobetaine as the least toxic agent that is almost not absorbed and not metabolized in the body and excreted [10], recent studies have revealed that arsenobetaine could accumulate in human body or transform into toxic inorganic arsenic in the gastrointestinal tract by microorganisms [11, 12]. There have been no studies on the relationships among arsnenobetaine and pancreatic β-cell function.
This study aimed to reveal the effect of arsenobetaine on pancreaic β-cell function by analyzing the association among HOMA index and urine arsenobetaine of non-diabetes population using original data from the Korea National Health and Nutrition Examination Survey (KNHANES) performed in 2008 − 2009.
Methods
This cross-sectional study used original data from the fourth KNHANES performed in 2008 − 2009. The survey was conducted by the Korean Ministry of Health and Welfare to investigate the health and nutrition status of Koreans, which included health and diet surveys as well as laboratory tests. In the fourth KNHANES, a total of 24,871 participants were enrolled. Of these participants, measurement of urine arsenic and speciation analysis of arsenic species of 202 and 200 participants were performed in 2008 and 2009, respectively. Known diabetic patients (n = 23) and participants with a fasting glucose level of over 126 mg/dL (classified as diabetic patients, n = 8) were excluded. Participants with missing data or who answered ‘Don’t know’ in the survey for smoking, drinking, and exercise were also excluded (n = 2). Finally, 369 participants were included in the study.
All blood samples were analyzed within 24 h after sampling. Plasma glucose was measured by Hitachi Automatic Analyser 7600 (Hitachi, Tokyo, Japan). Serum insulin was analyzed by immunoradiometric assay with 1470 WIZARD Gamma Counter (PerkinElmer, Turku, Finland). Blood mercury concentrations were measured by gold amalgam method (DMA-80, Milestone, Italy). The minimal detection limit of blood mercury was 0.05 μg/L.
HOMA-IR and HOMA-β percentage was calculated using the formula: HOMA-β (%) = [360 × fasting insulin (mIU/L)] / [ fasting glucose (mg/dL) – 63 ], HOMA-IR=[fasting glucose (mg/dL) × fasting insulin (mIU/L)]/405 [4].
Speciation analysis of urine arsenic was performed by inductively coupled plasma-mass spectrometry (ICP-MS) with ELAN DRC-e (PerkinElmer, Turku, Finland), adjusted for creatinine. The reagents used were Arsenic Standard solution (Sigma-Aldrich, MO, USA), Triton X-100 (Sigma-Aldrich, MO, USA), and concentrated nitric acid (Dongwoo Fine-Chem, Iksan, Korea). The minimum detection limit of arsenobetaine was 0.11 μg/L. Values below the limit of detection was estimated as 1/2 limit of detection [13, 14].
Categorical data are expressed as numbers of cases and percentages, and continuous data are expressed as means ± standard deviation. Urine arsenic and arsenobetaine did not follow a normal distribution, so the values are expressed as the median, 25th percentile, and 75th percentile. The index for smoking, drinking, and exercise was adopted from the index currently used in KNHANES. For current smoking, participants who currently smoke with a smoking history of 5 packs (100 cigarettes) were classified as “yes”. For monthly drinking rate, participants who drink at least once a month in the recent 1 year were classified as “yes”. For exercise, participants who did moderate activity (moderate physical effort or breathe somewhat harder than normal) for at least 30 min a day and 5 days during the last 1 week or vigorous activity (high physical effort or breathe much harder than normal) for at least 20 min a day and 3 days during the last 1 week were classified as “yes”. Continuous values were analyzed with Student’s t-test, and categorical values were evaluated with chi-square test for the comparison between sexes. The difference of urine total arsenic and arsenobetaine between gender was analyzed with Mann-Whitney test.
Urine total arsenic, arsenobetaine and total arsenic minus arsenobetaine were classified into four groups according to quartile (overall of 369 participants) to evaluate whether HOMA-β has significant differences among the different groups. The association of urine total arsenic, arsenobetaine, arsenic minus arsenobetaine and fasting glucose, fasting insulin, HOMA-IR and HOMA-β was analyzed with analysis of variance (ANOVA). Bonferroni test was used for post hoc. Because of the significance of sexual discrepancy of general characteristics, every statistical analysis was performed with and without sexual stratification. Then, multivariate analysis was performed for the association between urine arsenobetaine and HOMA-β, which showed a statistically significant association in univariate analysis. HOMA-IR was also analyzed to study pancreatic β-cell function with insulin resistance [15]. In the multivariate analysis, a multiple linear regression method was used, adjusting for factors affecting pancreatic β-cell or diabetes development, such as age [16], smoking [17], drinking [18], body mass index [19], and exercise [20]. Furthermore, blood mercury level, categorized to quartile, was included in the analysis to adjust for effect of seafood intake [21, 22]. Then, analysis was done after stratifying for sex. SPSS 23.00 software (IBM, Chicago, USA) was adopted for statistical analysis.
Results
The general characteristics of participants are shown in Table 1. Among a total of 369 participants, 174 were males, and 195 were females. The average age of all participants was 42.31, whereas that of males was 41.54 and that of females was 42.99. The average value of HOMA-β was 122.67 for all participants, 114.92 for men, and 129.59 for women. The median value of urine total arsenic was 136.89 μg/g_Cr for all participants, 143.61 μg/g_Cr for men, and 123.15 μg/g_Cr for women. The median value of urine arsenobetaine was 72.13 μg/g_Cr for all participants, 94.54 μg/g_Cr for men, and 51.55 μg/g_Cr for women, which were statistically significantly different. The median value of urine total arsenic minus arsenobetaine was 43.16 μg/g_Cr for all participants, 46.41 μg/g_Cr for men, and 37.83 for women (Table 2). Six of the participants showed below the detection limit of urine arsenobetaine, two of them were male and four were female. Thirty seven of participants showed negative value on total arsenic minus arsenobetaine. The negative value was included in the group below the 25th percentile, coded to 0.00. The distribution of urine total arsenic, arsenobetaine and total arsenic minus arsenobetaine is shown in Fig. 1.
Table 1
General characteristics of the study participants
a
p values were from independent t-test and Mann-Whitney test for continous variables and chi-square test for categorical variables
bValues are presented as arithmetic mean ± standard deviation
cSmoking status was indicated as ‘yes’ for participants who had smoked more than five packs of cigarettes during their life and were currently smoking
dAlcohol consumption was indicated as ‘yes’ for participants who consumed at least one glass of alcohol every month over the previous year
eRegular exercise was indicated as ‘yes’ when the participant performed mederate or strenuous exercise on a regular basis (for more than 30 min at a time and more than five times per week in the case of moderate exercise; for more than 20 min at a time in the case of strenuous exercise)
fValues are presented as median (25th percentile, 75th percentile)
Table 2
Urine arsenic and arsenobetaine levels of the study participants
Univariate analysis was performed with ANOVA. Fasting glucose was significantly associated with urine total arsenic level (p < 0.05). Post hoc test result showed the difference from the group between the 25–50th percentile and above the 75th percentile. In sexually stratified analysis, no association was found among fasting glucose, fasting insulin and urine total arsenic in both gender (Additional file 1: Table S1).
Fasting glucose was significantly associated with urine arsenobetaine (p < 0.001), while fasting insulin was not (p = 0.259). The group between the 25–50th percentile showed lowest glucose level. Significant difference was found among the group between the 25–50th percentile, the group between the 50–75th percentile and the group above the 75th percentile. Fasting glucose was also significantly associated with urine arsenobetaine in female (p < 0.05). The group between the 25–50th percentile was significantly different from the group above the 75th percentile (Table 3). No association was shown between fasting glucose, insulin and urine total arsenic minus arsenobetaine (Additional file 2: Table S2).
Table 3
Univariate analysis of the relationship between fasting glucose, insulin and urine arsenobetaine
Univariate analysis was performed with ANOVA, using the percentile-based categorized value of urine total arsenic and urine arsenobetaine as independent variables and HOMA-IR, HOMA-β as a dependent variable. HOMA-IR (p = 0.184) and HOMA-β (p = 0.476) were not significantly associated with total urine arsenic (Additional file 3: Table S3). HOMA-β showed significant differences according to urine arsenobetaine level (p < 0.01). Post hoc showed the significant difference between the group below the 25th percentile, between the 50–75th percentile and above the 75th percentile. HOMA-IR did not showed significant difference (p = 0.41). In sexually stratified analysis, only HOMA-β was significantly different based on urine arsenobetaine only in males (p < 0.05), while HOMA-IR did not (Table 3). Post hoc test was done for HOMA-β and arsenobetaine. The lowest quartile group shows significantly higher HOMA-β than the third and fourth quartile group (Table 4). No significant association was shown between HOMA-β, HOMA-IR and urine total arsenic minus arsenobetaine (Additional file 4: Table S4).
Table 4
Univariate analysis of the relationship between HOMA index and urine arsenobetaine
In multivariate analysis of urine arsenobetaine and HOMA-β, the value of HOMA-β in the group below the 25th percentile of urine arsenobetaine was significantly higher than that in the group between the 50–75th percentile. Among male participants, the value of HOMA-β in the group below the 25th percentile of urine arsenobetaine was significantly higher than that in the group between the 25–50th percentile and 50–75th percentile whereas HOMA-IR was not significant difference; however, there was no significant difference of HOMA-β and HOMA-IR among the groups for female participants (Table 5).
Table 5
Multiple linear regression analysis of the relationship between HOMA-β, HOMA-IR and urine arsenobetaine
Abbreviations: BMI body mass index, C.I confidence interval
aSmoking status was indicated as ‘yes’ for participants who had smoked more than five packs of cigarettes during their life and were currently smoking
bAlcohol consumption was indicated as ‘yes’ for participants who consumed at least one glass of alcohol every month over the previous year
cRegular exercise was indicated as ‘yes’ when the participant performed mederate or strenuous exercise on a regular basis (for more than 30 min at a time and more than five times per week in the case of moderate exercise; for more than 20 min at a time in the case of strenuous exercise)
Discussion
This epidemiological study investigated the association between β-cell function (a predictive factor of diabetes development) and the organic arsenic arsenobetaine (an agent less toxic to humans). Urine arsenobetaine was revealed to be associated with HOMA-β in the normal population (without diabetes), especially in males, even after adjusting for factors affecting diabetes and β-cell function, while no association was shown with HOMA-IR which is associated with insulin resistance.
Despite several conflicting results, arsenic has been reported to be correlated with diabetes in many epidemiological studies [6, 9, 23–31], and arsenic can affect insulin resistance and β-cell function [7]. In some experimental studies, arsenite was found to induce oxidative stress in pancreatic β-cells and reduce insulin transcription and secretion [32, 33], caused by the altered expression of essential genes such as the Pdx1 gene [34, 35] and insulin gene [36] for pancreas development, insulin production, and glucose homeostasis maintenance. Moreover, a study reported that arsenite can affect reactive oxygen species (ROS) production to intervene glucose uptake [37]. Arsenate also reported to affect on glucose homeostasis and ATP-dependent insulin secretion, by forming ADP-arsenite and glucose-6-arsenate [38]. However, DMA or MMA do not perturb phosphate metabolism [38].
This study demonstrated the association among β-cell function and arsenobetaine, one of the organic species of arsenic, by revealing the correlation between urine arsenobetaine and HOMA-β in the normal population (without diabetes). HOMA-β was used in this study as an index reflecting the function of pancreatic β-cells [4]. Also, previous antegrade studies revealed that HOMA-β reduction is an important factor for predicting diabetes development [39–41].
Previous studies showed that arsenobetaine is hardly metabolized in the body and rapidly excreted [42], and the lethal dose (LD) 50 of arsenobetaine is over 10,000 mg/kg [43]. Various studies in animals reported that arsenobetaine is not mutagenic, not cytotoxic, and does not have transforming activity [44]. Following those results, arsenobetaine has been categorized as non-toxic. Therefore, typical studies related to the toxic effect of arsenic have focused on inorganic arsenic, and the sum of inorganic-related species (arsenate, arsenite, dimethylarsinic acid (DMA), and monomethylarsonic acid (MMA)) has been adopted as a biological index of arsenic exposure [45]. Moreover, previous epidemiological studies excluded the indigestion of marine products, which is a main source of arsenobetaine exposure, and investigated the association between diabetes and urine total arsenic after subtracting the value of urine arsenobetaine; as a result, conflicting results were obtained regarding arsenobetaine in a statistical model [5, 9].
However, one study showed the continuous urine excretion of 0.2 ~ 12.2 μg/L of arsenobetaine in several participants 12 days after complete restriction of arsenobetaine indigestion, which suggested that arsenobetaine may be a metabolite of other arsenic species such as inorganic arsenic or DMA or accumulated arsenobetaine is released slowly [46]. Moreover, earlier studies did not confirm whether arsenobetaine can be metabolized in the actual digestive process because most of those studies used only drinking solution [47, 48]. Arsenobetaine can be transformed into toxic forms, such as DMA, by intestinal microorganisms in the actual digestive process when it is absorbed through food. An in vivo experiment demonstrated that arsenobetaine can be degraded into DMA, dimethylarsinoylacetic acid (DMAA), and trimethylarsine oxide (TMAO) in microcosm inoculated with human fecal matter, suggesting that the biocatalytic capability for arsenobetaine exists in the human gastrointestinal tract [12]. A study on humans showed that after ingestion of prawns containing 98.8% arsenobetaine, 0.14% DMA, and 0.96% inorganic acid, 3–5% arsenobetaine was excreted as inorganic arsenic, MA, and DMA [49]. Another study suggests that methylarsonic acid (MA) and DMA can be demethylated in the intestine, thus producing arsenate [50]. Taken together, it appears that arsenobetaine may accumulate in the body and become toxic or may metabolize into other toxic substances, such as arsenate, leading to diabetogenic toxicity; however, the mechanisms involved remain unclear. Further research should be conducted to elucidate the mechanism of arsenobetaine metabolism, especially in the human digestive system. Our result showed that arsenobetaine may have a diabetogenic effect on humans. Further studies are needed to determine whether arsenobetaine is a biomarker with chronic toxicity through metabolism or produced from other toxic arsenic species and to investigate the association among β-cell function, arsenobetaine, and the development of diabetes.
Since general characteristics exhibited sexual discrepancy, sexually stratified analysis was performed. The results of this study were significant only for male participants. The female gender is known to be a protective factor against diabetes. Epidemiologic studies on humans have revealed that females have a lower prevalence of diabetes until the time of menopause [51] despite having less skeletal muscle mass and more adipose mass [52]. Estradiol has been suggested as the protective factor against diabetes in animals and humans [52]. Pancreatic β-cells have ERα receptors, which are associated with glucose metabolism, insulin secretion, and β-cell survival [53]. Various animal studies have been performed to evaluate the effect of estrogen on pancreatic β-cell physiology. One study showed that the upregulation of pancreatic β-cell insulin can be initiated with ERα activation by the endocrine disruptor bisphenol-A as well as ERα and ERβ agonists in mice [54]. Le May et al. [55] suggested that ERα plays a key role in pancreatic β-cell survival from oxidative stress. The metabolic pathway of arsenic is also known to be affected by sex, as indicated in several studies [56–58]. Previous epidemiological studies showed that sex can affect the correlation between diabetes development and arsenic; in the group exposed to inorganic arsenic, men who had a higher incidence of diabetes were below 40, whereas women who had a higher incidence were above 40, especially after menopause [27, 59], which suggest that estrogen status can affect the mechanism of arsenic on developing diabetes. Other studies reported that the pathophysiology of developing diabetes caused by arsenic is affected by estrogen and estrogen receptor, and an experiment on mice showed that inorganic arsenic can influence glucose regulation in the estrogen-deficient state [60, 61]. These findings suggest that the female gender may contribute to the protective effect against arsenic in β-cell function, which can be the cause of sexual discrepancy in our results. Consistently, our study found that the male population appears to be a more sensitive group to arsenobetaine exposure. However, there have been no studies regarding the effect of sex and sexual hormones on the metabolism and toxic effect of arsenobetaine. Further studies are needed to determine whether sex affects the metabolic pathway of arsenobetaine and diabetes development.
In our study, the effect of arsenobetaine on pancreatic β-cell function appears to be non-linear. Rather, arsenobetaine appears to have a hormesis-like effect. In multivariate analysis, the HOMA- β value of the group over the 75th percentile group was not significantly different from that of the 0–25th group, while the value of the 25–50th percentile group and the 50–75th group was significantly lower than that of the 0–25th percentile group. Arsenobetaine may have both negative and positive effects on pancreatic β-cell function through various pathways. Arsenobetaine is an arsenic analog of trimethylglycine, known as betaine. Arsenobetaine is also an osmolyte analog that is accumulated in tissues by the transport system [62]. Organic osmolyte functions to protect cells from stress [63] via various pathways associated with regulation of cellular hydration state [64]. Pancreatic β-cells are modulated by intracellular ATP concentration and volume-sensitive anion-selective channels. Accumulation of intracellular osmolyte is responsible for pancreatic β-cell swelling, associated with anion channel activation and anion efflux [65, 66]. However, although theoretically possible, it has not been proven. Further research should be conducted to elucidate the mechanism of arsenobetaine exposure in human pancreatic β-cells.
There are several limitations in this study. First, this cross-sectional study was unable to identify a causal relationship of arsenobetaine with pancreatic β-cell function. Second, urine arsenobetaine is easily affected by indigestion of marine products and seaweed, though we were unable to directly analyze the recent intake amount of marine products. Seafood intake is also known to be associated with diabetes [67, 68]. However, we included blood mercury level as an index of seafood intake [21, 22] to adjust for the effect of seafood intake and minimize the effect of seafood intake. Third, we hypothesized that arsenobetaine has diabetogenic toxicity from being metabolized to the inorganic arsenic, which is known to be toxic and diabetogenic. We calculated the ‘total arsenic minus arsenobetaine’ to evaluate the non-arsenobetaine portion of arsenic and glucose metabolism. Although total arsenic minus arsenobetaine includes arsenocholine, arsenosugar, and arsenolipid metabolism and is not an ideal marker of inorganic arsenic [5, 69], it has been used as a marker of inorganic acid in several studies [9, 70, 71]. Total arsenic minus arsenobetaine did not demonstrate a significant association with HOMA index. Arsenate and arsenite, which are known to be directly associated with pancreatic β-cell toxicity and glucose metabolism, could not be appropriately evaluated because 296 (80.2%) of arsenate, 229 (62.1%) of arsenite were below the detection limit value. Methylated arsenic also could not be evaluated sufficiently; 237 (64.2%) of MMA, 37 (10.0%) of DMA were below the limit value. Despite these limitations, this study demonstrated that HOMA-β value, which indicates pancreatic β-cell function, is associated with urine arsenobetaine, especially in males. We suggest that further studies on arsenic and diabetes development should treat urine arsenobetaine and indigestion of marine products as independent variables that can affect the pancreatic β-cell function and developmental process of diabetes instead of excluding or adjusting for them. Moreover, further investigation is needed to assess the metabolism and chronic toxicity of arsenobetaine.
Conclusion
This study revealed the association between urine arsenobetaine and pancreatic β-cell function assessed by HOMA-β in the normal population (without diabetes), especially in males, despite adjusting for factors affecting pancreatic β-cell function and diabetes.
Additional files
Additional file 1: Table S1.
Univariate analysis of the relationship between fasting glucose, insulin and urine total arsenic. (DOCX 20 kb)
Acknowledgements
We would like to thank the Korean Ministry of Health and Welfare for offering raw-data of the fourth Korean National Health and Nutrition Examination Survey. The paper’s contents are solely the responsibility of the author and do not necessarily represent the official vies of the Korean Ministry of Health and Welfare.
Not applicable.
The data of the fourth KNHAES is opened to public, therefore, any researcher can be obtained after request from the website.
KOB (author) designed the study and carried out data analysis. NHL contributed acquisition of data and helped to analysis and interpretation of data. ISC conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Not applicable.
This study used the open data of the Fourth Korea National Health and Nutritional Examiination Survey (KNHANES), 2008-2009, Korea Centers for Disease Control and Prevention. All study participants of the fourth KNHANES agreed to participate the survey and signed a consent. The fourth KNHANES has been approved by the Institutional Review Board (IRB) of the Korea Centers for Disease Control. The approval number of 2008 is 2008-04EXP-01-C, 2009-01CON-03-2C for 2009. This study has been approved by the IRB of Keimyung university Dongsan medical center. The approval number is 2016-10-026.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
-
Electronic supplementary material
The online version of this article (doi:10.1186/s40557-017-0181-0) contains supplementary material, which is available to authorized users.
Abbreviations
ANOVA
Analysis of variance
C.I
Confidence interval
DMA
Dimethyl arsenic acid
DMAA
Dimethylarsonylacetic acid
HOMA
Homeostasis model assessment
ICP-MS
Inductively coupled plasma-mass spectrometry
KNHANES
Korea National Health and Nutrition Examination Survey
MA
Methylarsonic acid
MMA
Monomethylarsonic acid
ROS
Reactive oxygen species
TMAO
Trimethylarsine oxide
- 1. Gebel TW. Arsenic and drinking water contamination. Science 1999;283(5407):1458–1459. 10.1126/science.283.5407.1455e. 10206874.ArticlePubMed
- 2. Edmonds J, et al. Arsenic transformations in short marine food chains studied by HPLC-ICP MS. Appl Organomet Chem 1997;11(4):281–287. 10.1002/(SICI)1099-0739(199704)11:4<281::AID-AOC581>3.0.CO;2-S.Article
- 3. De Coster S, van Larebeke N. Endocrine-disrupting chemicals: associated disorders and mechanisms of action. J Environ Public Health 2012;2012:713696. 10.1155/2012/713696. 22991565.ArticlePubMedPMC
- 4. Matthews D, et al. Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28(7):412–419. 10.1007/BF00280883. 3899825.ArticlePubMedPDF
- 5. Navas-Acien A, et al. Rejoinder: arsenic exposure and prevalence of type 2 diabetes: updated findings from the National Health Nutrition and Examination survey, 2003-2006. Epidemiology 2009;20(6):816–820. 10.1097/EDE.0b013e3181afef88. 19713856.PubMedPMC
- 6. Navas-Acien A, et al. Arsenic exposure and type 2 diabetes: a systematic review of the experimental and epidemiologic evidence. Environ Health Perspect 2006;114(5):641–648. 10.1289/ehp.8551. 16675414.ArticlePubMed
- 7. Tseng CH. The potential biological mechanisms of arsenic-induced diabetes mellitus. Toxicol Appl Pharmacol 2004;197(2):67–83. 10.1016/j.taap.2004.02.009. 15163543.PubMed
- 8. Becker A, Axelrad D. Arsenic and type 2 diabetes: commentary on association of inorganic arsenic exposure with type 2 diabetes mellitus: a meta-analysis by Wang et al. J Epidemiol Community Health 2014;68(5):393–5. 10.1136/jech-2013-203463. 24558058.ArticlePubMed
- 9. Steinmaus C, et al. Low-level population exposure to inorganic arsenic in the United States and diabetes mellitus: a reanalysis. Epidemiology 2009;20(6):807–815. 10.1097/EDE.0b013e3181b0fd29. 19652600.PubMed
- 10. Buchet J-P, Pauwels J, Lauwerys R. Assessment of exposure to inorganic arsenic following ingestion of marine organisms by volunteers. Environ Res 1994;66(1):44–51. 10.1006/enrs.1994.1043. 8013437.ArticlePubMed
- 11. Newcombe C, et al. Accumulation or production of arsenobetaine in humans? J Environ Monit 2010;12(4):832–837. 10.1039/b921588c. 20383363.ArticlePubMed
- 12. Harrington CF, Brima EI, Jenkins RO. Biotransformation of arsenobetaine by microorganisms from the human gastrointestinal tract. Chem Speciation Bioavailability 2008;20(3):173–180. 10.3184/095422908X347278.Article
- 13. Hornung RW, Reed LD. Estimation of average concentration in the presence of nondetectable values. Appl Occup Environ Hyg 1990;5(1):46–51. 10.1080/1047322X.1990.10389587.Article
- 14. Nehls GJ, Akland GG. Procedures for handling aerometric data. J Air Pollut Control Assoc 1973;23(3):180–184. 10.1080/00022470.1973.10469762.Article
- 15. Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care 2004;27(6):1487–1495. 10.2337/diacare.27.6.1487. 15161807.PubMed
- 16. Chiu KC, et al. Beta cell function declines with age in glucose tolerant Caucasians. Clin Endocrinol 2000;53(5):569–575. 10.1046/j.1365-2265.2000.01132.x.ArticlePubMedPDF
- 17. Ostgren C, et al. Associations between smoking and beta-cell function in a non-hypertensive and non-diabetic population. Skaraborg hypertension and diabetes project. Diabetic Med 2000;17(6):445–450. 10.1046/j.1464-5491.2000.00294.x. 10975213.PubMed
- 18. Howard AA, Arnsten JH, Gourevitch MN. Effect of alcohol consumption on diabetes mellitus: a systematic review. Ann Intern Med 2004;140(3):211–219. 10.7326/0003-4819-140-6-200403160-00011. 14757619.ArticlePubMed
- 19. Chen G, et al. Overweight, obesity, and their associations with insulin resistance and β-cell function among Chinese: a cross-sectional study in China. Metabolism 2010;59(12):1823–1832. 10.1016/j.metabol.2010.06.009. 20655552.Article
- 20. Riddell MC, Sigal RJ. Physical activity, exercise and diabetes. Can J Diabetes 2013;37(6):359–360. 10.1016/j.jcjd.2013.10.001. 24321713.ArticlePubMed
- 21. Rhee SY, et al. Arsenic exposure and prevalence of diabetes mellitus in Korean adults. J Korean Med Sci 2013;28(6):861–868. 10.3346/jkms.2013.28.6.861. 23772150.ArticlePubMedPMCPDF
- 22. Navas-Acien A, et al. Arsenic exposure and prevalence of type 2 diabetes in US adults. JAMA 2008;300(7):814–822. 10.1001/jama.300.7.814. 18714061.PubMed
- 23. Maull EA, et al. Evaluation of the association between arsenic and diabetes: a National Toxicology Program workshop review. Environ Health Perspect 2012;120(12):1658. 10.1289/ehp.1104579. 22889723.ArticlePubMedPMC
- 24. Park SK, et al. Arsenic exposure is associated with diminished insulin sensitivity in non-diabetic Amish adults. Diabetes Metab Res Rev 2016;32(6):565–571. 10.1002/dmrr.2769. 26663816.ArticlePubMedPMC
- 25. Islam R, et al. Association between type 2 diabetes and chronic arsenic exposure in drinking water: a cross sectional study in Bangladesh. Environ Health 2012;11:38. 10.1186/1476-069X-11-38. 22676249.ArticlePubMedPMCPDF
- 26. Kim Y, Lee B-K. Association between urinary arsenic and diabetes mellitus in the Korean general population according to KNHANES 2008. Sci Total Environ 2011;409(19):4054–4062. 10.1016/j.scitotenv.2011.06.003. 21723589.PubMed
- 27. Lai MS, et al. Ingested inorganic arsenic and prevalence of diabetes mellitus. Am J Epidemiol 1994;139(5):484–492. 10.1093/oxfordjournals.aje.a117031. 8154472.ArticlePubMed
- 28. Chen Y, et al. No association between arsenic exposure from drinking water and diabetes mellitus: a cross-sectional study in Bangladesh. Environ Health Perspect 2010;118(9):1299–1305. 10.1289/ehp.0901559. 20813654.Article
- 29. Zierold KM, Knobeloch L, Anderson H. Prevalence of chronic diseases in adults exposed to arsenic-contaminated drinking water. Am J Public Health 2004;94(11):1936–1937. 10.2105/AJPH.94.11.1936. 15514231.ArticlePubMedPMC
- 30. Peng Q, Harlow SD, Park SK. Urinary arsenic and insulin resistance in US adolescents. Int J Hyg Environ Health 2015;218(4):407–413. 10.1016/j.ijheh.2015.03.006. 25845984.PubMedPMC
- 31. Ruiz-Navarro ML, et al. Urine arsenic concentrations in healthy adults as indicators of environmental contamination: relation with some pathologies. Sci Total Environ 1998;216(1-2):55–61. 10.1016/S0048-9697(98)00136-3. 9618928.ArticlePubMed
- 32. Hectors T, et al. Environmental pollutants and type 2 diabetes: a review of mechanisms that can disrupt beta cell function. Diabetologia 2011;54(6):1273–1290. 10.1007/s00125-011-2109-5. 21442161.ArticlePubMedPDF
- 33. Izquierdo-Vega JA, et al. Diabetogenic effects and pancreatic oxidative damage in rats subchronically exposed to arsenite. Toxicol Lett 2006;160(2):135–142. 10.1016/j.toxlet.2005.06.018. 16111841.ArticlePubMed
- 34. Paul DS, et al. Examination of the effects of arsenic on glucose homeostasis in cell culture and animal studies: development of a mouse model for arsenic-induced diabetes. Toxicol Appl Pharmacol 2007;222(3):305–314. 10.1016/j.taap.2007.01.010. 17336358.ArticlePubMedPMC
- 35. Díaz-Villaseñor A, et al. Arsenic-induced alteration in the expression of genes related to type 2 diabetes mellitus. Toxicol Appl Pharmacol 2007;225(2):123–133. 10.1016/j.taap.2007.08.019. 17936320.PubMed
- 36. Díaz-Villaseñor A, et al. Sodium arsenite impairs insulin secretion and transcription in pancreatic β-cells. Toxicol Appl Pharmacol 2006;214(1):30–34. 10.1016/j.taap.2005.11.015. 16413591.ArticlePubMed
- 37. Fu J, et al. Low-level arsenic impairs glucose-stimulated insulin secretion in pancreatic beta cells: involvement of cellular adaptive response to oxidative stress. Environ Health Perspect 2010;118(6):864. 10.1289/ehp.0901608. 20100676.ArticlePubMedPMC
- 38. Gresser MJ. ADP-arsenate. Formation by submitochondrial particles under phosphorylating conditions. J Biol Chem 1981;256(12):5981–5983. 7240187.ArticlePubMed
- 39. Song Y, et al. Insulin sensitivity and insulin secretion determined by homeostasis model assessment and risk of diabetes in a multiethnic cohort of women: the Women’s Health Initiative observational study. Diabetes Care 2007;30(7):1747–1752. 10.2337/dc07-0358. 17468352.ArticlePubMedPDF
- 40. Choi E-S, et al. Insulin sensitivity and insulin secretion determined by homeostasis model assessment and future risk of diabetes mellitus in Korean men. Korean Diabetes J 2008;32(6):498–505. 10.4093/kdj.2008.32.6.498.
- 41. Bonora E, et al. Population-based incidence rates and risk factors for type 2 diabetes in white individuals: the Bruneck study. Diabetes 2004;53(7):1782–1789. 10.2337/diabetes.53.7.1782. 15220202.Article
- 42.
- 43. Kaise T, Fukui S. The chemical form and acute toxicity of arsenic compounds in marine organisms. Appl Organomet Chem 1992;6(2):155–160. 10.1002/aoc.590060208.Article
- 44. Borak J, Hosgood HD. Seafood arsenic: implications for human risk assessment. Regul Toxicol Pharmacol 2007;47(2):204–212. 10.1016/j.yrtph.2006.09.005. 17092619.ArticlePubMed
- 45. Hygienists(ACGIH), A.C.o.G.I. Documentation of the threshold limit values and biological exposure indices (7th Ed.). 2007, Cincinnati: ACGIH.
- 46. Goessler W, et al. Can humans metabolize arsenic compounds to arsenobetaine? Appl Organomet Chem 1997;11(4):327–335. 10.1002/(SICI)1099-0739(199704)11:4<327::AID-AOC589>3.0.CO;2-Q.Article
- 47. Brown RM, et al. Human metabolism of arsenobetaine ingested with fish. Hum Exp Toxicol 1990;9(1):41–46. 10.1177/096032719000900109. 2328148.ArticlePubMedPDF
- 48. Yamauchi H, Kaise T, Yamamura Y. Metabolism and excretion of orally administered arsenobetaine in the hamster. Bull Environ Contam Toxicol 1986;36(1):350–355. 10.1007/BF01623519. 3955245.PubMed
- 49. Yamauchi H, Yamamura Y. Metabolism and excretion of orally ingested trimethylarsenic in man. Bull Environ Contam Toxicol 1984;32(6):682–687. 10.1007/BF01607556. 6743858.ArticlePubMedPDF
- 50. Chavez-Capilla T, et al. Bioaccessibility and degradation of naturally occurring arsenic species from food in the human gastrointestinal tract. Food Chem 2016;212:189–197. 10.1016/j.foodchem.2016.05.163. 27374523.ArticlePubMed
- 51. Wild S, et al. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care 2004;27(5):1047–1053. 10.2337/diacare.27.5.1047. 15111519.ArticlePDF
- 52. Louet JF, LeMay C, Mauvais-Jarvis F. Antidiabetic actions of estrogen: insight from human and genetic mouse models. Curr Atheroscler Rep 2004;6(3):180–185. 10.1007/s11883-004-0030-9. 15068742.ArticlePubMedPDF
- 53. Nadal A, et al. The pancreatic beta-cell as a target of estrogens and xenoestrogens: implications for blood glucose homeostasis and diabetes. Mol Cell Endocrinol 2009;304(1-2):63–68. 10.1016/j.mce.2009.02.016. 19433249.PubMed
- 54. Alonso-Magdalena P, et al. Pancreatic insulin content regulation by the estrogen receptor ERα. PLoS One 2008;3(4):e2069. 10.1371/journal.pone.0002069. 18446233.ArticlePubMedPMC
- 55. Le May C, et al. Estrogens protect pancreatic beta-cells from apoptosis and prevent insulin-deficient diabetes mellitus in mice. Proc Natl Acad Sci U S A 2006;103(24):9232–9237. 10.1073/pnas.0602956103. 16754860.PubMedPMC
- 56. Vahter M, et al. Gender differences in the disposition and toxicity of metals. Environ Res 2007;104(1):85–95. 10.1016/j.envres.2006.08.003. 16996054.ArticlePubMed
- 57.
- 58. Loffredo CA, et al. Variability in human metabolism of arsenic. Environ Res 2003;92(2):85–91. 10.1016/S0013-9351(02)00081-6. 12854687.ArticlePubMed
- 59. Tsai SM, Wang TN, Ko YC. Mortality for certain diseases in areas with high levels of arsenic in drinking water. Arch Environ Health 1999;54(3):186–193. 10.1080/00039899909602258. 10444040.PubMed
- 60. Huang CF, et al. Arsenic exposure and glucose intolerance/insulin resistance in estrogen-deficient female mice. Environ Health Perspect 2015;123(11):1138–1144. 10.1289/ehp.1408663. 25859628.ArticlePubMedPMC
- 61. Watson WH, Yager JD. Arsenic: extension of its endocrine disruption potential to interference with estrogen receptor-mediated signaling. Toxicol Sci 2007;98(1):1–4. 10.1093/toxsci/kfm111. 17650541.PubMed
- 62. Lenky CC, McEntyre CJ, Lever M. Measurement of marine osmolytes in mammalian serum by liquid chromatography-tandem mass spectrometry. Anal Biochem 2012;420(1):7–12. 10.1016/j.ab.2011.09.013. 21982861.ArticlePubMed
- 63.
- 64. Craig SA. Betaine in human nutrition. Am J Clin Nutr 2004;80(3):539–549. 15321791.PubMed
- 65. Best L, Miley HE, Yates AP. Activation of an anion conductance and beta-cell depolarization during hypotonically induced insulin release. Exp Physiol 1996;81(6):927–933. 10.1113/expphysiol.1996.sp003993. 8960699.PubMed
- 66. Best L, Speake T, Brown P. Functional characterisation of the volume-sensitive anion channel in rat pancreatic beta-cells. Exp Physiol 2001;86(2):145–150. 10.1113/eph8602118. 11429628.PubMed
- 67. Nkondjock A, Receveur O. Fish-seafood consumption, obesity, and risk of type 2 diabetes: an ecological study. Diabetes Metab 2003;29(6):635–642. 10.1016/S1262-3636(07)70080-0. 14707894.ArticlePubMed
- 68. Patel PS, et al. Association between type of dietary fish and seafood intake and the risk of incident type 2 diabetes. Diabetes Care 2009;32(10):1857–1863. 10.2337/dc09-0116. 19592633.PubMedPMC
- 69. Navas-Acien A, et al. Seafood intake and urine concentrations of total arsenic, dimethylarsinate and arsenobetaine in the US population. Environ Res 2011;111(1):110–118. 10.1016/j.envres.2010.10.009. 21093857.ArticlePubMed
- 70. Gamble MV, et al. Folate, homocysteine, and arsenic metabolism in arsenic-exposed individuals in Bangladesh. Environ Health Perspect 2005;113(12):1683–1688. 10.1289/ehp.8084. 16330347.PubMedPMC
- 71. Ahsan H, et al. Arsenic metabolism, genetic susceptibility, and risk of premalignant skin lesions in Bangladesh. Cancer Epidemiol Prevent Biomarkers 2007;16(6):1270–1278. 10.1158/1055-9965.EPI-06-0676.ArticlePDF
References
Figure & Data
REFERENCES
Citations
Citations to this article as recorded by 
- Research for type 2 diabetes mellitus in endemic arsenism areas in central China: role of low level of arsenic exposure and KEAP1 rs11545829 polymorphism
Chenlu Fan, Zaihong Zhan, Xin Zhang, Qun Lou, Ning Guo, Mengyao Su, Yue Gao, Ming Qin, Liaowei Wu, Wei Huang, Meichen Zhang, Fanshuo Yin, Yanhui Wu, Jingbo Pi, Yuanyuan Xu, Yanmei Yang, Yanhui Gao
Archives of Toxicology.2022; 96(6): 1673. CrossRef - Arsenic exposure during pregnancy and postpartum maternal glucose tolerance: evidence from Bangladesh
Abby F. Fleisch, Sudipta Kumer Mukherjee, Subrata K. Biswas, John F. Obrycki, Sheikh Muhammad Ekramullah, D. M. Arman, Joynul Islam, David C. Christiani, Maitreyi Mazumdar
Environmental Health.2022;[Epub] CrossRef - Maternal and childhood exposure to inorganic arsenic and airway allergy – A 15-Year birth cohort follow-up study
Tsung-Lin Tsai, Wei-Te Lei, Chin-Chi Kuo, Hai-Lun Sun, Pen-Hua Su, Shu-Li Wang
Environment International.2021; 146: 106243. CrossRef - Joint effect of urinary arsenic species and serum one-carbon metabolism nutrients on gestational diabetes mellitus: A cross-sectional study of Chinese pregnant women
Qiang Zhang, Xumei Zhang, Shuying Li, Huihuan Liu, Liangpo Liu, Qingyu Huang, Yaxing Hou, Xiaoshan Liang, Bo Cui, Ming Zhang, Liting Xia, Liwen Zhang, Chen Li, Jing Li, Guifan Sun, Naijun Tang
Environment International.2021; 156: 106741. CrossRef - Insulin resistance and pancreatic β cell dysfunction are associated with thyroid hormone functions: A cross-sectional hospital-based study in Turkey
Evin Kocatürk, Ezgi Kar, Zeynep Küskü Kiraz, Özkan Alataş
Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2020; 14(6): 2147. CrossRef - Endocrine disruption and obesity: A current review on environmental obesogens
Radhika Gupta, Prashant Kumar, Nighat Fahmi, Bhaskar Garg, Sriparna Dutta, Shilpee Sachar, Avtar S. Matharu, Karani S. Vimaleswaran
Current Research in Green and Sustainable Chemistry.2020; 3: 100009. CrossRef - Circulating miRNA-126, -145 and -155 levels in Mexican women exposed to inorganic arsenic via drinking water
Tania Ruíz-Vera, Ángeles C. Ochoa-Martínez, Sergio Zarazúa, Leticia Carrizales-Yáñez, Iván N. Pérez-Maldonado
Environmental Toxicology and Pharmacology.2019; 67: 79. CrossRef - The role of arsenic in obesity and diabetes
Tahereh Farkhondeh, Saeed Samarghandian, Mohsen Azimi‐Nezhad
Journal of Cellular Physiology.2019; 234(8): 12516. CrossRef - Arsenic and fasting blood glucose in the context of other drinking water chemicals: a cross-sectional study in Bangladesh
Shadassa Ourshalimian, Abu Mohd Naser, Mahbubur Rahman, Solaiman Doza, Jennifer Stowell, K.M. Venkat Narayan, Mohammad Shamsudduha, Matthew O. Gribble
Environmental Research.2019; 172: 249. CrossRef
PubReader
ePub Link
Cite
XML Download- Figure
-
- Related articles
-
- Exploring the impact of age and socioeconomic factors on health-related unemployment using propensity score matching: results from Korea National Health and Nutrition Examination Survey (2015–2017)
- Association between long working hours and liver enzymes: evidence from the Korea National Health and Nutrition Examination Survey, 2007–2017
- Poor worker’s long working hours paradox: evidence from the Korea National Health and Nutrition Examination Survey, 2013-2018
Association of arsenobetaine with beta-cell function assessed by homeostasis model assessment (HOMA) in nondiabetic Koreans: data from the fourth Korea National Health and Nutrition Examination Survey (KNHANES) 2008-2009
Fig. 1 The distribution of (a) urine total arsenic, (b) arsenobetaine and (c) total arsenic minus arsenobetaine among participants
Fig. 1
Association of arsenobetaine with beta-cell function assessed by homeostasis model assessment (HOMA) in nondiabetic Koreans: data from the fourth Korea National Health and Nutrition Examination Survey (KNHANES) 2008-2009
| Variables | Total | Male | Female | p valuea |
|---|---|---|---|---|
| Number | 369 | 174 | 195 | |
| Age, years | 42.31 ± 15.18b | 41.54 ± 14.62 | 42.99 ± 15.67 | 0.361 |
| Height, cm | 164.06 ± 9.31 | 171.28 ± 6.54 | 157.62 ± 6.14 | <0.001 |
| Weight, kg | 62.83 ± 11.69 | 70.14 ± 10.55 | 56.3 ± 8.32 | <0.001 |
| Waist circumference, cm | 79.73 ± 9.64 | 83.37 ± 9.19 | 76.48 ± 8.85 | <0.001 |
| BMI, kg/cm2 | 23.24 ± 3.22 | 23.9 ± 3.28 | 22.66 ± 3.06 | <0.001 |
| Fasting plasma glucose, mg/dL | 92.35 ± 9.09 | 94.13 ± 9.51 | 90.76 ± 8.4 | <0.001 |
| Blood insulin, mIU/l | 9.28 ± 3.68 | 9.23 ± 4.07 | 9.32 ± 3.31 | 0.828 |
| HOMA-β, % | 122.67 ± 57.85 | 114.92 ± 58.62 | 129.59 ± 56.41 | <0.01 |
| Smoking statusc | <0.001 | |||
| Yes | 104 (28.2%) | 82 (47.1%) | 22 (11.3%) | |
| No | 265 (71.8%) | 92 (52.9%) | 173 (88.7%) | |
| Alcohol consumptiond | <0.001 | |||
| Yes | 224 (60.7%) | 131 (75.3%) | 93 (47.7%) | |
| No | 145 (39.3%) | 43 (24.7%) | 102 (52.3%) | |
| Regular excersicee | 0.065 | |||
| Yes | 106 (28.7%) | 58 (33.3%) | 48 (24.6%) | |
| No | 263 (71.3%) | 116 (66.7%) | 147 (75.4%) | |
| Blood mercury, μg/L | 4.461 (2.982, 5.956)f | 5.465 (3.469, 8.886) | 3.880 (2.782, 5.698) | <0.001 |
| Variables | Total | Male | Female | p valuea |
|---|---|---|---|---|
| urine total arsenic (μg/g_cr) | 136.89 (35.29, 521.39)b | 143.61 (46.97, 563.24) | 123.15 (27.91, 470.27) | 0.055 |
| urine arsenobetaine (μg/g_cr) | 72.13 (16.64, 325.60) | 94.54 (28.46, 369.85) | 51.55 (12.40, 232.58) | <0.05 |
| urine total arsenic minus arsenobetaine (μg/g_cr) | 43.16 (14.53, 106.36) | 46.41 (17.70, 104.80) | 37.83 (13.60, 37.83) | 0.686 |
| Urine arsenobetaine (μg/g_cr) | Total | Male | Female | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Number | Fasting glucose (mg/dL) | p valuea | Post Hocb | Insulin (mIU/L) | p value | Number | Fasting glucose (mg/dL) | p value | Insulin (mIU/L) | p value | Number | Fasting glucose (mg/dL) | p value | Post hoc | Insulin (mIU/L) | p value | |
| 1st quartile (Undetectable-16.36) | 92 | 91.38 ± 8.56c | <0.001 | 1.000 | 9.90 ± 4.04 | 0.259 | 34 | 92.54 ± 8.65 | 0.175 | 10.88 ± 5.20 | 0.055 | 58 | 90.67 ± 8.50 | <0.05 | 0.702 | 9.30 ± 3.04 | 0.947 |
| 2nd quartile (16.91–70.70) | 92 | 89.84 ± 8.22 | Reference | 9.15 ± 3.53 | 47 | 92.56 ± 9.93 | 8.59 ± 3.29 | 45 | 88.24 ± 6.61 | Reference | 9.47 ± 3.66 | ||||||
| 3rd quartile (71.57–321.71) | 92 | 93.39 ± 8.44 | <0.05 | 8.85 ± 3.46 | 45 | 94.03 ± 8.84 | 8.73 ± 3.60 | 47 | 92.29 ± 7.73 | 1.00 | 9.04 ± 3.26 | ||||||
| 4th quartile (324.19–2620.78) | 93 | 94.75 ± 10.31 | <0.001 | 9.21 ± 3.64 | 48 | 96.55 ± 10.39 | 9.08 ± 3.99 | 45 | 92.91 ± 10.02 | <0.05 | 9.34 ± 3.29 | ||||||
| Urine arsenobetaine (μg/g_cr) | Total | Male | Female | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Number | HOMA-β (%) | p valuea | Post hocb | HOMA-IR | p value | Number | HOMA-β (%) | p value | Post hoc | HOMA-IR | p value | Number | HOMA-β (%) | p value | HOMA-IR | p value | |
| 1st quartile (Undetectable-16.36) | 92 | 135.97 ± 68.01c | <0.01 | Reference | 2.24 ± 1.00 | 0.41 | 35 | 143.74 ± 79.33 | <0.01 | Reference | 2.50 ± 1.27 | 0.146 | 57 | 131.2 ± 60.29 | 0.064 | 2.09 ± 0.76 | 0.966 |
| 2nd quartile (16.91–70.70) | 92 | 132.12 ± 60.6 | 1.000 | 2.04 ± 0.90 | 34 | 112.46 ± 49.85 | 0.146 | 1.99 ± 0.89 | 58 | 143.64 ± 63.7 | 2.08 ± 0.91 | ||||||
| 3rd quartile (71.57–321.71) | 92 | 110.76 ± 48.41 | <0.05 | 2.05 ± 0.97 | 58 | 109.19 ± 53.81 | <0.05 | 2.04 ± 0.90 | 34 | 113.97 ± 38.01 | 2.08 ± 0.87 | ||||||
| 4th quartile (324.19–2620.78) | 93 | 111.76 ± 48.34 | <0.05 | 2.18 ± 0.94 | 47 | 102.29 ± 45.38 | <0.01 | 2.16 ± 1.04 | 46 | 121.44 ± 49.84 | 2.15 ± 0.85 | ||||||
| Variables | Total | Male | Female | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| HOMA-β (%) | HOMA-IR | HOMA-β (%) | HOMA-IR | HOMA-β (%) | HOMA-IR | |||||||
| Coefficient (95% C.I) | p value | Coefficient (95% C.I) | p value | Coefficient (95% C.I) | p value | Coefficient (95% C.I) | p value | Coefficient (95% C.I) | p-value | Coefficient (95% C.I) | p value | |
| Urine arsenobetaine (μg/g_cr) | ||||||||||||
| 1st quartile (Undetectable-16.36) | Reference | Reference | Reference | Reference | Reference | Reference | ||||||
| 2nd quartile (16.91–70.70) | −9.613 (−24.490, 5.264) | 0.205 | −0.208(−0.449, 0.033) | 0.091 | −30.043(−53.954, −6.133) | <0.05 | −0.405(−0.835, −0.025) | 0.065 | 5.394(−13.276, 24.064) | 0.571 | −0.059(−0.329, 0.211) | 0.668 |
| 3rd quartile (71.57–321.71) | −17.796(−33.257, −2.334) | <0.05 | −0.219(−0.469, 0.031) | 0.086 | −22.382(−44.023, −0.742) | <0.05 | −0.343(−0.732, 0.046) | 0.084 | −12.575(−35.104, 9.954) | 0.274 | −0.071(−0.397, 0.254) | 0.667 |
| 4th quartile (324.19–2620.78) | −8.368(−24.891, 8.056) | 0.318 | −0.038(−0.304,0.228) | 0.779 | −14.950(−39.251, 9.351) | 0.228 | −0.027(−0.464, 0.410) | 0.902 | −3.857(−25.647, 17.932) | 0.729 | −0.055(−0.370, 0.259) | 0.731 |
| Age (years) | 01.117(−1.486,0.748) | <0.001 | −0.004(−0.010, 0.002) | 0.172 | −1.211(−1.752, −0.671) | <0.001 | −0.006(−0.015, 0.004) | 0.258 | −1.052(−1.558, −0.546) | <0.001 | −0.003(−0.011, 0.004) | 0.376 |
| BMI (kg/cm2) | 5.188 (3.523, 6.853) | <0.001 | 0.136 (0.109, 0.163) | <0.001 | 5.465 (3.075,7.855) | <0.001 | 0.149 (0.106, 0.192) | <0.001 | 5.565 (3.184, 7.946) | <0.001 | 0.132 (0.097, 0.166) | <0.001 |
| Smokinga | −10.452(−22.42, 1.515) | 0.087 | −0.114(−0.308, 0.080) | 0.248 | −11.827(−27.403,3.750) | 0.137 | −0.251(−0.531, 0.029) | 0.079 | 8.524 (−14.362, 31.410) | 0.465 | 0.242(−0.088, 0.572) | 0.151 |
| Alcohol consumptionb | −14.864(−26.291, −3.436) | <0.05 | 0.065(−0.120, 0.250) | 0.492 | −18.557(−37.121, 0.006) | 0.050 | 0.077(−0.256, 0.411) | 0.650 | −9.699(−24.618, 5.219) | 0.203 | 0.045(−0.170, 0.261) | 0.680 |
| Regular exercisec | −4.067(−15.791, 7.657) | 0.497 | −0.137(−0.327, 0.053) | 0.157 | −2.490(−18.472, 13.492) | 0.760 | −0.031(−0.318, 0.256) | 0.833 | −4.731(−21.725, 12.264) | 0.585 | −0.260(−0.505, −0.015) | <0.05 |
| Blood mercury (μg/L) | ||||||||||||
| 1st quartile (1.188–2.977) | Reference | Reference | Reference | Reference | Reference | Reference | ||||||
| 2nd quartile (2.987–4.598) | 15.686 (1.036,30.337) | <0.05 | −0.046(−0.283, 0.191) | 0.705 | −0.415(−25.210, 24.381) | 0.974 | −0.264(−0.710, 0.182) | 0.246 | 27.067 (8.938, 45.197) | <0.01 | 0.108(−0.153, 0.370) | 0.417 |
| 3rd quartile (4.625–6.969) | 5.642(−10.252, 21.536) | 0.487 | 0.023(−0.235, 0.280) | 0.862 | −2.752(−27.702, 22.197) | 0.829 | −0.388(−0.836, 0.061) | 0.090 | 11.404(−9.568, 32.377) | 0.287 | 0.304 (0.001, 0.607) | <0.05 |
| 4th quartile (6.997–37.654) | −15.172(−32.179, 1.835) | 0.08 | −0.165(−0.440, 0.110) | 0.240 | −27.387(−52.474, −2.300) | <0.05 | −0.524(−0.975, −0.073) | <0.05 | 3.667(−21.177, 28.512) | 0.772 | 0.178(−0.181, 0.536) | 0.332 |
Table 1 General characteristics of the study participants
a
bValues are presented as arithmetic mean ± standard deviation
cSmoking status was indicated as ‘yes’ for participants who had smoked more than five packs of cigarettes during their life and were currently smoking
dAlcohol consumption was indicated as ‘yes’ for participants who consumed at least one glass of alcohol every month over the previous year
eRegular exercise was indicated as ‘yes’ when the participant performed mederate or strenuous exercise on a regular basis (for more than 30 min at a time and more than five times per week in the case of moderate exercise; for more than 20 min at a time in the case of strenuous exercise)
fValues are presented as median (25th percentile, 75th percentile)
Table 2 Urine arsenic and arsenobetaine levels of the study participants
a
bValues are presented as median (25th percentile, 75th percentile)
Table 3 Univariate analysis of the relationship between fasting glucose, insulin and urine arsenobetaine
a
bPost hoc by Bonferroni test
cValues are presented as arithmetic mean ± standard deviation
Table 4 Univariate analysis of the relationship between HOMA index and urine arsenobetaine
a
bPost hoc by Bonferroni test
cValues are presented as arithmetic mean ± standard deviation
Table 5 Multiple linear regression analysis of the relationship between HOMA-β, HOMA-IR and urine arsenobetaine
aSmoking status was indicated as ‘yes’ for participants who had smoked more than five packs of cigarettes during their life and were currently smoking
bAlcohol consumption was indicated as ‘yes’ for participants who consumed at least one glass of alcohol every month over the previous year
cRegular exercise was indicated as ‘yes’ when the participant performed mederate or strenuous exercise on a regular basis (for more than 30 min at a time and more than five times per week in the case of moderate exercise; for more than 20 min at a time in the case of strenuous exercise)
