Effect of fasting on the pattern of urinary arsenic excretion

Abstract

Millions of people in some of the poorest regions of the world are exposed to high levels of arsenic through drinking contaminated water. It has been reported that development of cancer caused by arsenic exposure in such populations is dependent on dietary and nutritional factors which can modulate arsenic metabolism. Many people in arsenic exposed regions of Bangladesh and India practice fasting for at least one month every year when they refrain from consumption of food and fluid during daylight hours. How such practices may modulate arsenic metabolism has not been previously investigated. This study investigated this issue by determining total arsenic and its species in urine samples from a group of 29 unexposed volunteers at the beginning of the fasting and at the end of approximately 12 h of fasting period. Inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) coupled with ICP-MS was used to measure the total arsenic and arsenic speciation in the urine samples, respectively. The mean total levels of arsenic at the beginning of fasting (18.3 μg g⁻¹ creatinine) and at the end of approximately 12 h of fasting (17.7 μg g⁻¹ creatinine) did not differ significantly (p > 0.05). However, the percentages of urinary arsenic as the methylated arsenic species methylarsonate (MA) were found to be significantly different (p < 0.05) and this species was observed more frequently at the end of fasting, although its overall concentration was similar. There were no significant differences (p > 0.05) in both the concentrations and percentages of other urinary arsenic species detected, namely arsenobetaine (AB) and dimethylarsinate (DMA). Arsenite (As(III)) and arsenate (As(V)) were also analyzed, but were not detected. We conclude that fasting for a period of 12 h results in a significant increase in the percentage of urinary arsenic as MA, and its frequency of detection in the volunteers at the end of the fasting period is almost nine fold higher. This suggests that metabolism of arsenic is altered by fasting.

---

Introduction

Millions of people are at risk of various diseases such as cancer and heart disease resulting from chronic arsenic (As) exposure. A historic poisoning has been reported among tens of millions of the population in West Bengal, India and Bangladesh due to the high concentration of As in their drinking water.^1–4 A recent study by Vahter and co-workers⁵ reported that populations in certain parts of Europe are also at risk from arsenic exposure through drinking water. The As concentration in groundwater in parts of India and Bangladesh has been reported in the range of 10–3200 μg l⁻¹,⁶ exceeding the recommended guideline (10 μg l⁻¹) set by the World Health Organization.⁷ Furthermore, recent studies by Meharg and co-workers⁸ have demonstrated that arsenic contaminated rice is an additional source of exposure in these populations. How the health of these populations is affected by exposure to such high levels of As is an important area of research. It has been previously⁹ reported that As metabolism and toxicity may vary depending on the nutritional status of an individual. This was investigated among the largest population in the world exposed to As in their drinking water, in West Bengal, India and Bangladesh.⁹ They concluded that low intake of animal protein, folate, calcium and fiber can increase the possibility of As-caused skin lesions, although they could not provide clear evidence of a protective effect of overall protein consumption and vegetables against the development of skin lesions.¹⁰ Many people in the As-affected regions of India and Bangladesh practice fasting during the daylight hours for at least one month every year. How this may modulate their pattern of As metabolism has not been previously studied, but is an issue that requires further investigation.

The general definition of Ramadan fasting is refraining from food and beverage intake for approximately 12 h a day during the daylight hours for a month, which start from dawn to sunset every day. Some changes that are associated with Ramadan fasting include slowing down of the rate of metabolism, a small reduction in body mass, dehydration and an increase in uric acid in serum.^11,12 Toda and Morimoto reported¹² that Ramadan fasting has both positive and adverse effects on healthy individuals, although they suggested that adverse effects are unlikely to continue, or lead to further complications, after Ramadan fasting. They concluded their study by stating that healthy individuals can perform Ramadan fasting without any concern about their health. The subject of fasting and its relationship to health is a rapidly growing field of research. Studies by Mattson¹³ have investigated the role of energy intake and meal frequency on health, reporting some positive aspects of intermittent fasting, and caloric restriction, including the suppression of the development of various diseases, and an increase in life span in laboratory animals.

Although there are no previous studies exploring the relationship between fasting and As metabolism, it has been reported that some important body metabolites, such as folic acid and homocysteine that are involved in As metabolism undergo changes under fasting conditions. For example, it has been reported that folate level increases during fasting,¹⁴ whereas homocysteine level decreases.¹⁵ It has been reported¹⁶ that As methylation was dependent on folic acid, which is important since inorganic As is methylated to methylarsonate (MA) and dimethylarsinate (DMA) sequentially within the body.

Toxicity of As in humans is dependent on its chemical form, with arsenite (As(III)) and arsenate (As(V)) being the most toxic forms, methylarsonate (MA) and dimethylarsinate (DMA) are less toxic, and arsenobetaine (AB), which is mainly found in seafood, is reported to be non-toxic.^17–19 Fasting is one of the factors that may have an influence on As distribution, since it has been associated with changes in some important biological parameters that have an effect on As metabolism.

The aim of this study was to investigate if abstaining from food and fluid for a period of about 12 h results in a modification of As metabolism, as investigated through analysis of urine samples. This study is potentially important since many people in As-affected regions of India and Bangladesh practice Ramadan fasting during the daylight hours for one month every year. The study involved recruitment of 29 Ramadan fasting volunteers living in Leicester, UK.

Materials and methods

Chemicals and reagents

Deionised water (>18 Ω cm⁻¹) was used throughout the study. Stock solutions of As species were prepared and calibrated against an As(V) standard (1000 ± 3 mg l⁻¹, CPI, International, USA). As(III) [(As₂O₃), Sigma-Aldrich, Germany] was dissolved in 4 g l⁻¹ sodium hydroxide and made up to appropriate volume with 2% v/v HNO₃ (UPA, Romil, UK); DMA [(CH₃)₂AsOOH, Sigma-Aldrich, Germany]; MA [(CH₃)₃AsO(OH)₂], Greyhound, Dorset, England] and AB [(C₅H₁₁AsO₂, Fluka, Fisher Chemicals, UK]. All stock solutions were prepared in deionised water and stored in the fridge at 4 °C. Fresh diluted solutions were prepared daily for analysis.

The mobile phase (20 mM NH₄HCO₃) was prepared by dissolving an appropriate amount of ammonium hydrogen carbonate (Fisher Chemicals, UK) in 950 ml of deionised water, adjusted to pH 10.3 with 35% ammonia (Fisher Chemicals, UK), filtered through a 0.45 μm membrane filter before adding 50 ml of methanol (HPLC grade, Fisher Scientific, UK) and degassed with helium. The mobile phase, with slight modification, was used previously by Pedersen and Francesconi.²⁰ Germanium solution was added to the mobile phase as internal standard so as to reach a final concentration of 50 μg l⁻¹ for speciation analysis. In addition, 10 μg l⁻¹ of yttrium (PlasmaCAL, Québec, Canada) was used as internal standard for total As analysis.

Instrumentation

The total As concentration in the urine samples was measured using an Elan DRCII ICP-MS (PerkinElmer SCIEX, Concord, Ontario, Canada) under the following instrumental conditions: RF power 1350 W; gas flows: plasma 15 l min⁻¹, auxiliary flow 1.20 l min⁻¹, nebuliser flow 0.97 l min⁻¹; and nickel sample and skimmer cones. For As speciation measurements, a PEEK Hamilton PRP-X 100 anion exchange column (250 × 4.1 mm id) and Phenomenex Polymerx RP-1 guard column (4 × 3 mm id) were housed in a 790 Personal IC chromatograph (Metrohm, Switzerland), fitted with a 100 μl sample loop. The mobile phase was pumped through the system at 1 ml min⁻¹, with the outlet of the HPLC system coupled directly with PEEK id 90 μm tubing to a PQII ICP-MS (VG Instruments, Winford, UK), which served as the chromatographic detector. Signals at m/z 75, 77 and 51 were monitored in graphic mode. The signal at m/z 51 was used to monitor ³⁵Cl¹⁶O⁺ as an indicator of the presence of Cl⁻ which can cause an isobaric interference (⁴⁰Ar³⁵Cl⁺) with As at m/z 75. The PQII ICP-MS operated under the following conditions: RF power 1350 W; gas flows: plasma 13 l min⁻¹, auxiliary flow 0.95 l min⁻¹, nebuliser flow 0.94 l min⁻¹; and nickel sample and skimmer cones.

Sample collection and preparation

Urine sample collection and storage were carried out as usually reported in the literature.^21–23 Midstream first morning void urine samples (RF1) were collected from Ramadan fasting (RF) volunteers, at the beginning of fasting period in the morning, while midstream first sunset void urine samples (RF2), at the end of fasting period, for the second time in a day were collected from the same group. The RF group (n = 29) were from Leicester, UK [mean age 31.9 years (one volunteer did not reported his age); 3 women and 26 men]. The ethnicity background of the volunteers was mixed and composed of 9 Asian or Asian British, 10 Black or Black British, 7 Middle Eastern and 3 North African. The sampling time was spread in the middle of the month, approximately one week after the beginning of Ramadan fasting, and one week before the end of Ramadan fasting. All volunteers were asked to refrain from eating fish and seafood for three days prior to sample collection, and to complete a questionnaire which gathered information on age, gender and ethnicity along with lifestyle. The questionnaire was accompanied with a letter explaining the objective of the study and how to deal with the urine samples in terms of collection and storage. All procedures followed were in accordance with the ethical guidelines of the Research Ethics Committee, Faculty of Health and Life Sciences, De Montfort University. Urine samples were collected directly into polyethylene bottles (Fisher, UK). The normality of each sample was checked by using a Combur⁹ test (Roche, Germany) urine test strip. The samples were kept frozen at −20 °C until the analyses were carried out. Prior to analysis, the samples were thawed, filtered through a 0.45 μm syringe filter and diluted up to 5-fold with the mobile phase for speciation analysis, and 5-fold with 2% HNO₃ for total As determination.

Quality control and assurance

Freeze-dried human urine certified reference material (CRM) from the National Institute of Environmental Studies (NIES), Japan was reconstituted by the addition of 9.57 g of deionised water as recommended (CRM No. 18, NIES, Japan). The CRM was used to validate the As speciation and total As methods. The CRM was also analyzed during each analytical run as a quality control (QC) check. A spiking experiment for both total As and As species in urine was carried out and the results indicated that any interference present in the urine samples had no effect on the accuracy of either the total As or speciation analysis methods.

Determination of creatinine

Creatinine adjustment is routinely used to reduce some factors that are not related to As exposure, such as urine concentration and urine volume.²⁴ Creatinine was analysed photometrically by using a Metra Creatinine Assay Kit (Quidel Corporation, USA).

Statistical analysis

The Student t-test was used to evaluate the influence (95% confidence level) of demographic variables such as tea, coffee, soft drinks, alcohol, smoking, age and gender. The differences (95% confidence level) between the two groups (RF1 and RF2) in terms of As species in urine and total As levels in urine samples was evaluated by using Paired Student’s t-test, since all the participants were sampled twice. The difference between RF1 and RF2 for MA in terms of level and percentage was also tested by using the same test (Paired Student’s t-test), by assigning half of the lowest detected concentration or calculated percentage of MA to not-detected MA, because MA was not detected in many samples. Moreover, for analysis of MA frequency of detection, estimates and 95% confidence intervals for the odds ratio (OR) were calculated; the frequency distribution (p-value) for data sets were calculated using the Fisher Exact test.

Results

All the urine samples investigated were found to be normal according to the results of test strip analysis. The pH of all 58 urine samples studied was found to be in the range of 5 to 8. This is within the normal range (4.5–8.0) expected for human urine.²⁵

Quality assurance

The total As concentration determined in CRM No. 18, NIES was 151.0 ± 2.0 μg l⁻¹ (n = 9) compared to the certified value of 137 ± 11.0 μg l⁻¹. A spiking experiment was carried out by adding 50 μg l⁻¹ of total As to a urine sample, then diluted (5-fold) with 2% v/v HNO₃ to achieve 10 μg l⁻¹ total spiked concentration. The recovery of the spiking experiment was 103% (n = 9) for total As. The calibration curve for total As was drawn within the range (1–20 μg l⁻¹).

A spiking experiment was also carried out for speciation analysis by adding 50 μg As l⁻¹ of each As species to a urine sample, then diluted (5-fold) with mobile phase to achieve 10 μg As l⁻¹ total spiked concentration. The spiking experiment had the following recoveries (replicates = 3): AB (90%), DMA (95%), As(III) (86%), MA (95%), and As(V) (98%), suggesting that any interference had no effect on the analysis. Indeed, the HPLC-ICP-MS method employed here provides chromatographic resolution of Cl⁻ from all five As species of interest, allowing for their determination without interference from ⁴⁰Ar³⁵Cl⁺.²⁶ The CRM No. 18 was used to validate the method and the results were as follows: AB 69.7 ± 1.4 μg As l⁻¹ (n = 3) and DMA 38.4 ± 0.6 μg As l⁻¹ (n = 3); the certified values were 69 ± 12 μg l⁻¹ and 36 ± 9 μg l⁻¹, respectively. The calibration curves for As species were drawn within the range of 1–25 μg As l⁻¹.

Total As analysis in urine samples

The levels of total As in RF1 and RF2 urine samples are shown in Table 1. Total As in RF1 was in the range 5.7–54.9 μg g⁻¹ creatinine with a mean of 18.3 μg g⁻¹ creatinine. For RF2, the range was 2.1–66.8 μg g⁻¹ creatinine with a mean of 17.7 μg g⁻¹ creatinine. There is no statistically significant difference between RF1 and RF2 urine samples with regard to total As levels.

Table 1 Concentration of As species and total As (μg g⁻¹ creatinine) in urine from RF1 and RF2 groups, and a summary of statistical significance p-values when comparing urinary species (AB, DMA and MA), sum of all species and total As among different urine samples types (RF1 and RF2)

Group		AB	DMA	MA	Sum of all As species	Total As
a These p-values are associated with species (AB, DMA and MA) percentages.
RF1 n = 29	Mean	9.0	3.9	0.4	13.3	18.3
	SD	10.1	3.1	0.6	12.4	11.8
	Median	6.1	2.8	<LOD	8.7	15.7
	Minimum	<LOD	<LOD	<LOD	3.1	5.7
	Maximum	38.2	12.2	1.8	46.7	54.9
RF2 n = 29	Mean	7.0	4.0	0.7	11.7	17.7
	SD	7.9	3.3	0.7	9.9	12.5
	Median	5.1	2.8	0.5	9.3	14.6
	Minimum	0.4	<LOD	<LOD	2.3	2.1
	Maximum	42.7	13.1	2.9	52.3	66.8
RF1 vs. RF2	p-values	0.35	0.94	0.09	0.53	0.85
		0.08^a	0.15^a	0.02^a

---

As speciation analysis in urine samples

The actual concentrations of As species detected in RF1 and RF2 samples in μg As g⁻¹ creatinine is calculated from raw instrumental data using the in-house Turbo Pascal programme DBSCORR version 8 (unpublished Turbo Pascal programme, by D. A. Polya). Inorganic As(III) and As(V) were not detected in any urine sample. The measured species percentages in the two different sample types were 68% AB and 29% DMA in RF1, compared to 60% AB and 34% DMA in RF2 (Fig. 1). There were no significant differences (p > 0.05) between the RF1 and RF2 urine sample types regarding total As, As species and percentages, as shown in Table 1, with the exception of the percentage of MA (3% and 6% in RF1 and RF2, respectively; Fig. 1). This difference in MA levels between RF1 and RF2 in percentage is statistically significant (p < 0.05) (Table 1). MA was detected in 86% (25 out of 29) of RF2 samples compared to only 41% (12 out of 29) in RF1 samples. Differences in MA between RF2 and RF1 groups were assessed by comparison of frequency of detection; the odds ratio (OR) was 8.9 (95% CI Q2.44 to 32.12), with a p-value <0.001. This reveals that at the end of fasting (RF2), MA is almost 9 times more likely to be detected than at the beginning of fasting period (RF1).

Fig. 1 Percentages of As species in urine of fasting group (RF): RF1 and RF2 urine samples were collected at the beginning and at the end of fasting period, respectively.

Different demographic variables

Alcohol and smoking have previously been reported^27,28 to have a correlation with the level of As in urine. Here we added for the first time more demographic factors (daily habits e.g. tea, coffee and soft drink intake) to explore their potential correlation with urinary As. Our analysis revealed that demographic variables such as gender, age and coffee, tea and soft drink consumption have no significant influence (p > 0.05) (Table 2) on total As level in the urine samples (RF1 and RF2) we tested.

Table 2 Demographic variables and mean (SD) concentrations (μg g⁻¹ creatinine) of total As in urine samples collected from 29 volunteers at the beginning of fasting (RF1) period and the end of fasting period (RF2)

Variable	n (%)	Mean (SD)	Variable	n (%)	Mean (SD)
a These factors were not tested due to too few numbers. b One volunteer did not report his age. c These divisions were based on the median value. d These p-values are for RF2.
All	29 (100)	18.3 (11.8)	Soft drinking
		17.7 (12.5)^d	Non-drinker	9 (31)	21.8 (13.1)
Gender					24.1 (17.3)^d
Male	26 (90)	18.6 (12.3)	Drinker	20 (69)	16.7 (11.2)
		17.1 (12.8)^d			14.9 (8.8)^d
Female	3 (3)^a	15.7 (4.5)	p-value		0.30
		23.0(10.1)^d			0.07^d
p-value		0.69	≤1 l week^−1^c	9	12.0 (7.1)
		0.45^d			31.5 (8.1)^d
Age	(28)^b		>1 l week^−1^c	11	20.6(12.7)
≤31^c	14	20.9 (12.1)			13.5 (8.3)^d
		19.1 (9.6)^d	p-value		0.09
>31^c	14	18.0 (11.7)			0.90^d
		16.8 (15.6)^d	Tea
p-value		0.53	Non-drinker	1 (3) ^a
		0.64^d	Drinker	30 (97)
Coffee			≤10 cups/week^c	14	19.6 (11.6)
Non-drinker	19 (66)	16.5 (9.8)			21.2 (15.7)^d
		19.9 (14.6)^d	>10 cups/week^c	14	17.1 (12.7)
Drinker	10 (34)	21.7 (14.9)			13.3 (6.7)^d
		13.6 (5.6)^d	p-value		0.61
p-value		0.28			1.00^d
		0.21^d	Smoking
<7 cups/week^c	6	21.1 (17.4)	Non-smoker	28 (97)
		11.8 (3.0)^d	Smoker	1 (3) ^a
≥7 cups/week^c	4	22.6 (12.9)
		8.0 (7.7)^d
p-value		0.89
		0.28^d

---

A dehydration factor was also investigated, because it may affect the level of As in human urine.¹⁶ The creatinine level was compared between RF1 and RF2, and it showed no significant difference (p > 0.05), indicating no evidence for dehydration. Homocysteine and folic acid measurements were beyond the scope of this project, as it would require blood samples, so for this reason the discussion of their influence on our results is based on the literature.

Discussion

This is the first study to evaluate the effect of fasting on urinary As levels. Our results show that there is a significant difference in the percentage of MA (p < 0.05) at the beginning and end of a 12 h long fast. We observed an increase in the proportion of this more toxic of the two pentavalent methylated As species analysed in the urine samples collected at sunset, just before the termination of the daily fast. However, we found no significant difference (p > 0.05) in both the total As and As species concentration at the beginning (RF1) and at the end (RF2) of the fast. This suggests that fasting has no significant effect on urinary As with regard to the total levels excreted. Similarly, there were no significant differences (p > 0.05) in levels of AB and DMA species and percentages for the two groups of samples.

The increase in the percentage of MA after fasting may be taken to suggest that, during fasting, the human body creates an environment that favours the elimination of the more toxic species (MA) over the non toxic species (AB). Daytime activity, rather than fasting per se, may be the reason for this and is a possible confounding factor that could not be eliminated. However, a recent study comparing spot urine with 24 h urine revealed that no significant differences were observed in urinary As species between these two different points of time collection.²⁴ This suggests that day time activity does not influence urinary As species distribution.

MA was detected in 86% (25 out of 29) of RF2 samples compared to only 41% (12 out of 29) in RF1 samples. The reason for the statistically significant increase in MA percentages and a statistically insignificant decrease in AB percentages in urine samples collected at sunset (RF2), after approximately 12 h fasting, is unlikely to be due to diet since no food was consumed between the two time points of the samples collection. The finding also highlights the need for caution in the use of MA as a biomarker for As exposure, since it appears to be more likely to be detected after prolonged fasting. Furthermore, our findings indicate that the time point of urine sample collection and the nutritional status (fasting/starvation) of the individual should be known.

One possible explanation for the increase in the percentage of MA in Ramadan fasting urine samples (RF2), collected at sunset before the breaking of the fast, could be related to the biomethylation process, attributed to the altered metabolic state of the body caused by the fasting. It has been previously reported that Ramadan fasting results in a reduction of homocysteine levels.¹⁵ Homocysteine is considered as a factor that influences As methylation. An elevated level of homocysteine was reported to negatively impact the biosynthesis of S-adenosylmethionine and glutathione.²⁹ These latter compounds are well known as being essential for As biotransformation in humans. Methylation of As takes place in liver where the trivalent As receives a methyl group from S-adenosylmethionine, in which reduced glutathione is required.³⁰ Since homocysteine is a substrate for methionine, the reduction of homocysteine levels would increase the availability of methionine for the biomethylation of As. This is because homocysteine is normally metabolized through two biochemical pathways: re-methylation and trans-sulfuration. Homocysteine is converted to methionine via the first pathway and to cysteine and taurine through the latter pathway.³¹ Therefore, we suggest that a lowering of the homocysteine level will result in an increase in the percentage of DMA and a significant increase in MA.

The methylation process of As is a biochemical pathway that is also dependent on folate,¹⁶ which has been reported to increase under fasting conditions.¹⁴ This could also offer an explanation for the observed distribution of As species during Ramadan fasting. DMA has been reported to be positively associated with plasma folate.¹⁶ The increased level of folate in animals was also reported to increase the biomethylation process.³² Thus one can postulate that during Ramadan fasting, the level of folate increases, which results in an increase in the percentage of DMA and a significant increase of detected MA among RF2 urine samples.

It is noteworthy that there was a high percentage of AB in almost all the urine samples of the two types with average percentages of 68% AB in RF1 and 60% AB in RF2, despite all volunteers being asked to refrain from eating fish and seafood for three days prior to sample collection. There was no significant (p > 0.05) difference between RF1 and RF2 regarding the level of AB. It is worth mentioning that previous studies have also reported high levels of AB in urine.^19,33,34 For example, 70% of total urinary As was found as AB in healthy volunteers who refrained from seafood consumption for two days.¹⁹ An explanation for this may be linked to sources of AB in the diet other than seafood. For example it has recently been reported that AB is present in chicken,³⁵ which is widely consumed among the volunteers used in this study based on the data from a questionnaire in our previous study. Consumption of fish ingredients in some products or other AB containing products also cannot be ruled out.¹⁹

Conclusion

Our results suggest that Ramadan fasting has no significant effect on the total level of urinary As detected at the beginning and at the end of a 12 h long fast. However, the statistically significant increase in the percentage of MA suggest that the methylation capacity of the body alters under fasting conditions, favouring the removal of the most toxic methylarsenic species investigated in this study.

Acknowledgements

De Montfort University is thanked for granting a PhD studentship to Eid Brima. Andrew Gault was funded under EPSRC research grant (GR/S30207/01) to David Polya, Jon Lloyd, David Vaughan and Roy Wogelius. Gareth Pearson and Gillian Greenway from The University of Hull are also thanked for providing access to their ICP-MS for the measurement of total As concentration in the urine samples.

References

1. A. H. Smith, E. O. Lingas and M. Rahman, Bull. W. H. O., 2000, 78, 1093–1103.
2. D. Chakraborti, G. K. Basu, B. K. Biswas, U. K. Chowdury, M. R. Rahman, K. Paul, T. R. Chowdury, C. R. Chanda and D. Lodh, in Arsenic Exposure and Health, ed. W. R. Chappell, C. O. Abernathy, R. L. Calderon, Science and Technology Letters, Northwood, 1994, pp. 27–52.
3. M. R. Rahman, U. K. Chowdhury, S. C. Mukherjee, B. K. Mondal, K. Paul, D. Lodh, B. K. Biswas, C. R. Chanda, G. K. Basu, K. C. Saha, S. Roy, R. Das and S. K. Palit, J. Toxicol., Clin. Toxicol., 2001, 39, 683–700.
4. L. Charlet and D. A. Polya, Elements, 2006, 2, 91–96.
5. A. Lindberg, W. Goessler, E. Gurzau, K. Koppova, P. Rudnai, R. Kumar, T. Fletcher, G. Leonardi, K. Slotova, E. Gheorghiu and M. Vahter, J. Environ. Monit., 2006, 8, 203–208.
6. H. Tokunaga, T. Roychowdhury, N. Chandraskaran, T. Uchino and M. Ando, Appl. Organomet. Chem., 2002, 16, 406–414.
7. WHO, Guidelines for Drinking-water Quality, Vol. 1: Recommendations, World Health Organization, Geneva, 3rd edn, 2004, p. 186.
8. P. N. Williams, M. R. Islam, E. E. Adomako, A. Raab, S. A. Hossain, Y. G. Zhu, J. Feldmann and A. A. Meharg, Environ. Sci. Technol., 2006, 40, 4903–4908.
9. S. R. Mitra, D. N. G. Mazumder, A. Basu, G. Block, R. Haque, S. Samanta, N. Ghosh, M. M. H. Smith, O. S. Ehrenstein and A. H. Smith, Environ. Health Perspect., 2004, 112, 1104–1109.
10. K. M. McCarty, E. A. Houseman, Q. Quamruzzaman, M. Rahman, G. Mahiuddin, T. Smith, L. Ryan and D. C. Christiani, Environ. Health Perspect., 2006, 114, 334–340.
11. R. Roky, I. Houti, S. Moussamih, S. Qotbi and N. Aadil, Ann. Nutr. Metab., 2004, 48, 296–303.
12. M. Toda and K. Morimoto, Soc. Behav. Pers., 2004, 32, 13–18.
13. M. P. Mattson, Annu. Rev. Nutr., 2005, 25, 237–260.
14. E. M. Cahill and M. J. Gibney, Int. J. Vitam. Nutr. Res., 1998, 68, 142–145.
15. F. B. Aksungar, A. Eren, S. Ure, O. Teskin and G. Ates, Ann. Nutr. Metab., 2005, 49, 77–82.
16. M. V. Gamble, X. Liu, H. Ahsan, J. R. Pilsner, V. llievski, V. Slavovich, F. Parvez, D. Levy, P. Factor-livak and J. H. Graziano, Environ. Health Perspect., 2005, 113, 1683–1688.
17. A. Shraim, S. Hairano and H. Yamauchi, Anal. Sci., 2001, 17, i1729–i1732.
18. M. Vahter, G. Concha and B. Nermell, Trace Elem. Med., 2000, 13, 173–184.
19. R. Ritsema, L. Dukan, T. R. Navarro, W. van Leeuwen, N. Oliveria, P. Wolfs and E. Lebret, Appl. Organomet. Chem., 1998, 12, 591–599.
20. S. N. Pedersen and K. A. Francesconi, Rapid Commun. Mass Spectrom., 2000, 14, 641–645.
21. C. Steinmaus, K. Carrigan, D. Kalman, R. Atallah, Y. Yuan and A. H. Smith, Environ. Health Perspect., 2005, 113, 1153–1159.
22. C. Hopenhayn-Rich, M. L. Biggs, A. H. Smith, D. A. Kalman and L. E. Moore, Environ. Health Perspect., 1996, 104, 620–628.
23. M. Vahter, G. Concha, B. Nermell, R. Nilson, F. Dulout and A. T. Natarajan, Eur. J. Pharmacol. Environ. Toxicol. Pharmacol., 1995, 293, 455–462.
24. A. L. Hinwood, M. R. Sim, N. de Klerk, O. Drummer, J. Gerostamoulos and E. B. Bastone, Environ. Res., 2002, 88, 219–224.
25. Y. Chen, C. J. Amarasiriwardena, Y. Hsueh and D. C. Christiani, Cancer Epidemiol., Biomarkers Prev., 2002, 11, 1427–1433.
26. E. I. Brima, P. I. Haris, R. O. Jenkins, D. A. Polya, A. G. Gault and C. F. Harrington, Toxicol. Appl. Pharmacol., 2006, 216, 122–130.
27. C. Hopenhayn-Rich, M. L. Biggs, D. A. Kalman, L. E. Moore and A. H. Smith, Arsenic, Environ. Health Perspect., 1996, 104, 1200–1207.
28. Y. Hsueh, Y. Ko, Y. Hauang, H. Chen, U. Y. Chiou, Y. Haung, M. Yang and C. Chen, Toxicol. Lett., 2003, 37, 46–63.
29. L. Alan, N. D. Miller, S. Gregory and N. D. Kelly, Altern. Med. Rev., 1997, 2, 234–254.
30. M. Vahter, in Arsenic exposure and health, ed. W. R. Chappell, C. O. Abernathy and R. L. Calderon, Science and Technology Letters, Northwood, 1994, pp. 171–179.
31. A. L. Miller, Altern. Med. Rev., 2003, 8, 7–19.
32. O. Spiegelstein, X. Lu, X. C. Le, A. Troen, J. Selhub, S. Melnyk, S. J. James and R. H. Finnell, Toxicol. Lett., 2003, 145, 167–174.
33. V. W. M. Lai, Y. Sun, E. Ting, W. R. Cullen and K. J. Reimer, Toxicol. Appl. Pharmacol., 2004, 198, 297–306.
34. E. I. Brima, R. O. Jenkins and P. I. Haris, Spectroscopy, 2006, 20, 125–151.
35. A. Polatajko and J. Szpunar, J. AOAC Int., 2004, 87, 233–237.

---