Arsenicosis and Dietary Nutrient Intake Among Men and Women


Abstract


To determine the dietary intake of nutrients and its correlation with manifestations of arsenicosis and gender a cross-sectional study was conducted in India among two groups of participants, Group 1 (108 cases having skin lesions) and Group 2 (exposed controls, 100 cases not having skin lesions) with exposure to arsenic drawn from geographical areas known to have high level of arsenic in ground water (above permissible limit, i.e.[50 lg/L). Fordiet survey, combinations of two methods of diet study i.e. weighment of cooked food and the 24-h diet recall were followed. The nutrients in each food items and calorie consumption were calculated. The mean calorie intake of males was significantly less than that of females in both cases and controls. In both the sexes, mean protein consumption was significantly less than that of the controls. In females, intake of most of the nutrients like thiamin, riboflavin, niacin, magnesium, copper and zinc were less in comparison to controls. In both the sexes mean choline intake was lower significantly in comparison to exposed controls. Riboflavin, copper, zinc and vitamin B6 consumption were below the RDAs in nearly 90 % of the study population. The strongest trend in ORs was for protein (4.28). The present study revealed that low socioeconomic status along with dietary intake of calorie, protein and micronutrients like thiamine, riboflavin, niacin, zinc and choline may have a definite role in increasing the risk of development of arsenicosis.

Keywords Arsenic : Nutrients Arsenicosis Malnutrition Arsenical manifestations.

Introduction


Arsenic exposure through drinking water is a major health problem affecting many countries in the world viz. Bangladesh, India, Argentina, Mongolia, China, Chili, Thailand, Taiwan, Mexico and some parts of USA [1–4]. Prolonged exposure of arsenic of 5–90 lg/kg body weight/day results in arsenicosis; [5] characterized by hyper and hypo pigmentation,keratosis, various systemic manifestations like weakness, anemia, chronic lung disease, peripheral neuropathy, liver fibrosis, gangrene of limbs and cancer of skin, lungs andurinary bladder [6–8]. Studies on populations of Taiwan, India and Argentina exposed to arsenic through drinking water have suggested that malnutrition increases the risk ofarsenic induced diseases [9–13]. Several human studies have identified associations between malnutrition and arsenicinduced skin lesions, skin cancer, and cardiovasculardiseases [12, 14, 15]. Literature surveys indicate arsenic resistance and its relation with nutritional status [16–19]. Laboratory experiments have demonstrated that specific micronutrients can modify arsenic metabolism and toxicity [13]. Inhabitants of Taiwan and the Antofagasta region in northern Chile with severe health effects due to ingestion ofhigh arsenic contaminated drinking water were reported to have a poor nutritional status [20]. Inorganic arsenic is metabolized to monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA), and this methylation facilitates urinary arsenic excretion, which is dependent on availability of S-adenosylmethionine (SAM). The methyl group from SAM may be derived from dietary components such as methonine, choline, folate and other nutrients [21, 22].Dietary protein, iron, zinc and niacin are associated with urinary excretion of MMA and DMA [23]. Previous studies suggest that persons with more complete methylation have alower risk of adverse arsenic-related health outcomes [24]. Diet poor in methionine is likely to decrease the ability to methylate arsenic and increase the arsenic toxicity [25]. Folate and cobalamin (vitamin B12) have been suggested to play an important role in the detoxification of ingested arsenic [26]. Studies done in experimental animals have shown that severe protein deficiencies can impair arsenic methylation and excretion [22]. Vitamin C reduces the toxicity of arsenic [27].

The objective of this study was to determine the dietary intake of nutrients and its correlation with manifestations of arsenicosis and its influence on gender.

Material and Methods


Study Design
Study was carried out from February 2008 to February 2009 both months inclusive and without any temporal or seasonal sampling (methodology) variation. This is a crosssectionalstudy of two groups with exposure to arsenic. Recruitment to the study population was on the basis of likely exposure status as determined by area of residence. Group 1(cases) and 2 (exposed controls) were drawn from geographical areas known to have high levels of arsenic in ground water above permissible limit in India, i.e.[50 lg/L. Group 1 consists of 108 subjects (cases) exhibiting arsenical skin lesions [Diagnosed on the basis of WHO criteria (WHO 2005) and Group 2 consisted of 100 subjects (exposed controls) not exhibiting skin lesions.

Selection of Subjects
Of the 17 arsenic affected blocks in the district of Nadia, two blocks were selected. A village level sampling frame was created from all villages within these two blocks which had at least one tube-well contaminated with arsenic at a level greater than 50 lg/L. Data regarding level of arsenic contamination were obtained from the survey conducted by the Public Health Engineering Department (PHED) of the Government of West Bengal. Of 174 villages in the sampling frame, six were selected, with proportional allocation across the two blocks, giving four villages in block 1 (Chakdah) and two villages in block 2 (Haringhata) as described earlier by Guha Mazumder et al. [28].

Further selection of the villages from each block was carried out using a probability proportional to size sampling technique. To find out the differences in the level ofcontamination between villages, the proportion of arsenic contaminated tube wells in the village as well as the total population count was considered. Household selection within each of the six villages was done through systematic sampling with a random start in the list of households. A total of 212 households were covered in the sample and the total number of inhabitants in these selected households turned out to be 900. Participants for Group 1 (cases) and Group 2 (exposed controls) were selected from these 212 households. Subjects of the first group (Group-1) consisted of 108 arsenicosis cases affected with typical skin lesion of pigmentation and/or keratosis, belonging to 900 arsenic exposed residents of the 212 selected households.

Subjects of the second group (Group-2) consisted of 100 individuals referred as exposed controls without arsenical skin lesion with definite evidence of arsenic exposure [50 lg/L, selected randomly from the remaining 709 individuals residing in the 212 households examined in the two blocks.

Measurement of Skin Lesions
This was carried out as a part of general medical examination by physicians with extensive clinical experience of arsenical skin lesions in West Bengal. Of the 208 exposed recruits 108 (cases) had arsenical skin lesions and were diagnosed with arsenicosis on the basis of WHO criteria (1); 100 (exposed controls) did not have skin lesions.

Measurement of Confounders
At the time of the field study, information from each recruit was collected on potential confounders including demographic characteristics, socio-economic variables (i.e.housing, education and occupation) and history of addiction. BMI was also measured.

Diet Survey
A pre-tested questionnaire was used. Combination of two diet study- weighment of cooked food and 24 h diet recall were followed. Senior woman answerable for making food,and participants was interviewed about details of each and every diet taken starting from evening snacks of the previous day, up to the launch of the date of study. Questionswere also asked about the consumption of fruit and animal proteins such as egg, fish chicken, meat and beef. To estimate the amount of consumed cooked food, SIKAweighing machine and bowls of different volumes (50–1,500 mL) were used. The raw food items, which were used to prepare each meal, were noted in the questionnairealong with their weight in grams. Raw weight of each food item consumed by the participant was calculated by using following formula:

F = (P/Q) x R

where F is intake of raw food by the participant, P is amount (in grams) of each raw food ingredient used for cooking food. Q is volume in milliliter of cooked food. R is volume in milliliter of the cooked food consumed by the participant [29]. Sugar and oil consumption wasassessed using a standard-size spoon. Answers were noted about the details of food consumed outside home, as in work place if any. Milk and water consumption in thehome and working place were noted along with their sources and amount by using a laboratory grade beaker or calibrated plastic jug. In the case of cooking water, onlythe sources were recorded.

Assessment of Nutritional status
Nutrients in each food item (carbohydrate, protein, fat, vitamins, minerals and fiber) and energy consumption were calculated according to ICMR reference standard [30] byusing a spreadsheet program. For this purpose a detailed database was prepared for the nutrient composition per 100 g of raw food items. Nutritive value for ready to eatitems like biscuits was obtained from their packaging. Both cases and exposed controls were stratified by sex for comparison of the nutrient intake with recommended daily allowance (RDA-ICMR) [30] for India to determine the excess or deficient intake and the proportion of cases and exposed controls with nutrient intake below the RDA. Height, Weight and BMI were measured.

Collection of Water Samples
Water samples were collected from present drinking and cooking water source for each respondent in a polyethylene bottle. Total daily water consumption by a participant wasdetermined from self-report on the number of glasses (250 mL capacity) of water the person consumed in 24 h period. Water samples were instantly kept in ice box during shifting from field, till stored at -200 C till further analysis.

Measurement of Exposure
Each recruit was questioned on his or her current and previous sources of drinking and cooking water, and the duration of water use from previous sources. Responseswere used to calculate cumulative arsenic exposure for each respondent. Cumulative arsenic exposure was calculated for each respondent, using following formula:

X(Cix Di)

where Ci is the concentration of arsenic in particular well source water which a study subject had used during the period i and Di is the period of use. Water samples were collected from all available current and previous tube wells used for drinking purposes by each recruited household.

Statistical Analysis


The arsenic intake from drinking water (lg/day) was calculated by multiplying the arsenic concentration in drinking water of the current drinking source (lg/L) by the water consumption rate (L/day). Descriptive statistics were calculated, including mean ± SD. The authors did two-tailed paired t-tests for the difference in mean nutrient intake in cases and exposed controls. Again the nutrient intake was stratified in quintiles of the distribution of the controls, and odd ratios (ORs) with 95 % confidence intervals (95 % CIs) were estimated for each level taking the highest quintile as the reference group. Tests for trend were based on x2 distribution using the median of each quintile range. As the calorie and nutrient intake vary depending on gender and occupation with varying energy requirement like moderate and sedentary habit, the authors divided the participants into various groups and calculated the calorie requirement on the basis male and female sex and against sedentary and moderate energy requiring occupation.

Results


Among 208 participants aged between 15 and 70 years, there were 108 cases (Group 1) and 100 exposed controls (Group 2). Out of 108 cases (Group 1) there were 66 males(61.11 %) and 42 females (38.89 %) and out of 100 exposed controls (Group 2) there were 60 males (60 %) and 40 females (40 %). Age and sex matching was done for the participants. Duration of arsenic exposure to peak concentration in participants for both cases and exposed controls were 12.87 ± 7.32 and 10.96 ± 7.69 years respectively. 41.67 and 39.81 % of cases belonged to the age group 30–44 and 45–59 years, as compared to exposed controls. 35.19 % of cases and 27 % of exposed controls were underweight as per BMI classification. 74.07 % of cases and 56 % of exposed controls lived in kutcha houses,whereas 10.19 % of cases and 24 % of controls lived in pucca houses and these differences were found to be statistically significant (p0.05). 25 % of cases and 16 % of exposed controls were illiterate. 17.59 % of cases and 36 % of exposed controls received education up to secondary level and above and these differences were found to be statistically significant (p0.05). The number of persons having per capita income less than Rs 500 is reported in 83.5 % cases in comparison to exposed controls (75 %). Significant arsenic exposure was observed through drinking water in the two cohorts studied. No difference wasobserved between the peak arsenic exposure and cumulative arsenic exposure (Tables 1, 2).

tabelDaily consumption of calorie and other nutrients was calculated in respect of RDA of male and female participants doing moderate work, as majority of participants were foundto be farmers or agricultural labours (18). The male participant of both cases and exposed controls were found to be taking less amount of calorie, the mean calorie intake was 2,384.04 ± 1,111.12 and 2,561.85 ± 729.6 kcal/day, respectively, which was below RDA value (2,875 kcal/Day). Female participants of both cases and exposed controls were also taking less amount of calorie, the mean calorie intake was 1,830.11 ± 622.3 and 2,157.39 ± 471.14 kcal/day respectively which was below of RDA value (2,225 kcal/day) and these differences were found to be statistically significant (p0.05). For males, mean protein consumption of cases was 54.26 ± 24.32 g/day and that of exposed controls it was 65.77 ± 24.95 g/day.

This difference was significant statistically (p0.05). In both cases and controls 70 % of males and 72 % of females were taking less amount of calorie compared to RDA level and this difference was found to be statistically significant (p0.01). For males 68 % of cases and 45 % of exposed controls were taking less amount of protein in respect of RDA(60 g/day) (p0.05). For females, mean protein consumption of cases was 40.83 ± 14.99 g/day and that of exposed controls it was 51.5 ± 19.04 g/day. This difference was found to be significant statistically (p0.05). For females, 74 %of cases and 53 %of exposed controls were taking less amount of protein below RDA value (50 g/day) and this difference was statistically significant (p0.05). However animal protein mean intake for male cases was7.76 ± 8.73 g/day, which was significantly low as compared to exposed controls i.e. 15.18 ± 17.41 g/day, (p0.05). For females there was no significant difference in intake of animalprotein. In males 26 %of cases and 12 %of exposed controls were taking magnesium below the RDA of 350 mg/day (mean intake in cases 493.99 ± 388.04) and exposed controls516.59 ± 213.47 mg/day) (p0.05). For females, most of the nutrients like thiamin, riboflavin, niacin, magnesium, copper and zinc intake was less in cases compared to exposedcontrols.

These differences were found to be statistically significant (p0.05). For thiamin, mean intake of cases was 1.12 ± 0.4 mg/day and for exposed controls it was1.34 ± 0.41 mg/day and 50 % of cases and 28 % of exposed controls were taking the thiamin below the RDA, (1.1 mg/ day). In both male and female choline intake was foundsignificantly (p0.05) lower in cases (mean intake in male 261.34 ± 192.79 and in females 252.56 ± 180.29 mg/day) in comparison to exposed controls (mean intake in male 500.28 ± 585.57 and in females 363.55 ± 293.63 mg/day). For males 92 % of cases and 73 % of exposed controls were taking choline below the RDA of 550 mg/day (p0.05). Riboflavin, copper, zinc and vitamin B6 consumption were below the RDAs in nearly 90 % of males and females of both cases and exposed controls (Table 3).

.Intake of each nutrient stratified was into quintiles. ORs and 95 %CLs were computed for each stratum, using the highest quintile as the reference group. The strongest trendin ORs was for protein. At the lowest quintile of intake, the ORs are as follows: protein (4.28), thiamin (1.82), niacin (2.33), folic acid (2.03) and fibre (2.31). The trend was alsofound in energy (2.29) and fat (2.03) (Table 4).

Discussion


Relation between dietary intake of nutrients and arsenical manifestations was evident from this study. The socioeconomic status of cases was significantly low as comparedto exposed controls. Higher number of cases lived in kutcha houses and the persons having per capita incomeRs 500 were more in cases as compared to controls.

Most of the participants of this study belonged to the age group of 30–44 year. The reference daily intake or recommended daily allowance (RDA) is the daily intake level of a nutrient that is considered to be sufficient to meet the requirements of 97–98 % of healthy individuals. Nutrition surveys in eight states of India conducted by the NationalNutrition Bureau of India revealed calorie consumption to be less than the RDA of energy (male 2,875 and female 2,225 kcal/day) [31]. In the present study calorie consumption of more than 70 % and 90 % of males and females were found to be below RDA of energy. Studies in Murshidabad district of West Bengal revealed that morethan 50 % of household surveyed families with poor nutrition suffer more from arsenic toxicity [27]. Other studies also revealed that under nourishment was found to increase the risk of skin lesions and skin cancer in arsenic exposed populations [9, 11, 15].

In Western States like Alaska, studies revealed that populations consuming highconcentrations of arsenic from their drinking water often did not show arsenical skin lesions. The reason may be their nutritional status [32]. In the present study it was found that there was a widespread nutrient deficiency in both cases and exposed controls in respect to their RDA values. Experimental research in animals has also shown that low protein and amino acids in diet increase risks of arsenic related health effects [12, 22, 28, 32–34]. Intake of carbohydrate, protein, animal protein, fat, vitamins and minerals was estimated from a diet survey by 24 h recall method in arsenic exposed study population of south 24 Parganas and it was found that deficiencies of some nutrients like animal protein, calcium, fiber, folate and vitamin C may increase the risk of arsenic induced skin lesions [29]. In the present study, statistically significant differences were found in intake of protein between cases and exposed controls in both male and female participants (p0.01). Also the protein consumption of cases for both male and femaleparticipants were found to be significantly below the RDA as compared to exposed controls (p0.01). Animal protein intake was also significantly low in cases as compared to exposed controls for males in the present study (p0.01). Some researchers have postulated that deficiencies in some nutrients such as beta-carotene, methonine and zinc may increase susceptibility to arsenic induced health effects [13]. Experimental animals with a low dietary intake of methonine, choline and protein were found to have lowered methylation of inorganic arsenic [22]. For choline, all cases in the present study had intake below the RDA. Among the cases higher percentages of males ([90 %) were taking less amount of choline as compared to the exposed controls.

The study done among residents of California where arsenic level in the drinking water supplies had been near 100 mcg/l suggests that low intake of dietary protein, iron, zinc and niacin lead to decreased production of DMA and increased level of MMA in arsenic exposed individuals [35]. Studies showed that consumption of high level of niacin (vitamin B3) was associated with arsenic methylation [35]. In the present study intake of zinc and niacin among female cases fall below the RDA and their intake is also less in comparison to exposed controls. There are studies indicating that consumption of a diet rich in riboflavin, pyridoxin, vitamin A, C and E can significantly reduce the harmfuleffects of developments of skin lesions [26]. Other nutrients like niacin, iron, calcium, protein, and thiamin were also reported to be protective against arsenic toxicity [36].Severely low intake of riboflavin, thiamin, niacin, magnesium and copper was found in female cases as compared to exposed controls in this study. Inadequate intake of folate,methionine, cysteine, vitamin B6 and B12, calories and proteins are associated with arsenic related health effects in humans [12, 22, 28, 33, 36–38]. It was experimentallyproved that low zinc concentrations were found in blood and urine of arsenic affected patients [39]. It was also found in the present study that calorie and fiber consumption was also significantly low in cases as compared to exposed controls for female participants. The average intake of retinol, vitamin B6 and iron were also inadequate for all the participants. The calcium consumption for male participants was higher than RDAs but the corresponding values for females were low.

It was evident that there was only significant trend in OR only for protein at 5 % level. Also, no other nutrient had significant trend in OR. Similar findings were obtained in a study in south 24 Parganas [29]. Women of all groups generally have lower status and less social value than men. Women tend to eat last and least in their household. Therefore if they live in poor families they are the most likely family members to be malnourished. Women are on average less well educated, younger, and have less earning power than their husbands. Epidemiological studies to date present somewhat contradictory information on the different ways that arsenic tends to affect males and females. Studies of large populations find prevalence of arsenicosis symptoms to be significantly higher among males than the females [7, 40]. One smaller study, however, has identified larger percentage of women than men among arsenic-affected patients in Bhanga Upazila, Faridpur District (58.6 % of 488 patients), and in Barura Upazila, Comilla (62 % of 58 patients) (WHO 2002).

The cohort study conducted in south 24 Parganas district of West Bengal finds age-adjusted prevalence of skin lesions to be much higher for men than for women at every dose level. For example, among those consuming 263–864 lg/L of arsenic in their drinking water, the prevalence of skin lesions for men is well over 20/1,000, but the prevalence for women is only slightly over 5/1,000 [40]. Arsenic content in duplicate diets for males were higher than females. Daily arsenic intake (lg/day) from male samples were statistically higher than that of female (p0.05). However, arsenic intake based on lg/kg body weight/d was not statistically different [41–43].

tabel-3

Conclusion


A cross sectional study was conducted in Chakdah and Haringhata block of Nadia district of West Bengal to determine the dietary intake of nutrients and its correlationwith manifestations of arsenicosis.

The study revealed that low socio-economic status along with less dietary intake of calorie, protein and micronutrients may have a definite role in increasing the risk ofdeveloping arsenicosis. In the present study it was evident that calorie consumption and consumption of most of the macro and micronutrients was less than RDA in both casesand controls of study population. But there was significant difference in intake of protein along with micronutrients like thiamine, riboflavin, niacin, zinc and choline in the dietof cases compared to exposed controls in both the sexes, indicating the probable role of above nutrients in development of diseases. Based on the above findings the villagerswere advised to consume a variety of green leafy vegetables, locally available pulses and fruits rich in antioxidants and other micronutrients along with low cost animal protein like egg and fish to decrease the susceptibility from arsenic related health effects.

References
1. WHO (2001) Arsenic and arsenic compounds. Environmental health criteria, vol 224. International Programme on Chemical Safety, Geneva
2. Thornton I, Farago M (1997) The geochemistry of arsenic. In: Abernathy CO, Calderon RL, Chappell WR (eds) Arsenic exposure and health effects. Chapman & Hall, London, pp 1–16
3. Alam MGM, Snow ET, Tanaka A (2003) Arsenic and heavy metal contamination of rice, pulses and vegetables grown in Samta village, Bangladesh. In: Chappell WR, Abernathy CO, Calderon RL, Thomas DJ (eds) Arsenic exposure and health effects V, vol 8. Elsevier, London, pp 103–114
4. NRC (National Research Council) (1999) Arsenic in drinking water. National Academic Press, Washington DC
5. WHO Technical Publication (2005) In: Caussy D (ed) A field guide for detection, management and surveillance of arenicosis cases, vol 30. WHO Regional Office for South East Asia, New Delhi, p 19–22
6. Guha Mazumder DN (2003) Criteria for case definition of arsenocosis. In: Chappell WR, Abernathy CO, Calderon RL, Thomas DJ (eds) Arsenic exposure and health effects V vol 9. Elsevier BV, London, pp 117–133
7. Guha Mazumder DN et al (2001) Clinical aspects of chronic arsenic toxicity. J Assoc Phys India 49:650–655
8. Saha KC (2003) Saha’s grading of arsenicosis progression and treatment. In: Chappell WR, Abernathy CO, Calderon RL, Thomas DJ (eds) Arsenic exposure and health effects V, vol 30. Elsevier BV, London, pp 391–414
9. Guha Mazumder, D.N., Chakraborty, A.K. Ghose A.Et Al. (1998) Chronic arsenic toxicity from drinking tubewell water in rural West Bengal. Bull. Wild Health Org. 66:499–506
10. Zaldivar R (1978) Arsenic contamination of drinking water and foodstuffs causing endemic chronic poisoning. Beitr Pathol 151:384–400
11. Hsueh YM, Cheng GS, Wu MM, Yu HS, Kuo TL, Chen CJ (1995) Multiple risk factors associated with arsenic induced skin cancer: effects of chronic liver disease and malnutritional status. Br J Cancer 71:109–114
12. Chen, C-J, Kuo, T. L., WU, M.M. Arsenic and cancers (letter). Lancet, II, 1988; 414-415
13. Chung JS, Haque R, Guha Mazumder DN, Moore LE, Ghosh N, Samanta S, Mitra S, Hira-Smith MM, Ehrenstein OV, Basu A, Liaw J, Smith AH (2006) Blood concentrations of methionine, selenium, beta-caroteneand other micronutrients in a case controlstudy of arsenic induced skin lesions in West Bengal, India. Environ Res 101(2):230–237
14. Pal A, Chowdhury U, Mandal D, Nayak B (2009) Arsenic Burden from cooked rice in the population of arsenic affected and non affected areas and Kolkata city in West Bengal, India. Environ Sci Technol 43(9):3349–3355
15. Mazumder DNG, Haque R, Ghosh N, De BK, Santra A, Chakraborty D, Smith AH (1998) Arsenic levels in drinking water and the prevalence of skin lesions in West Bengal, India. Int J Epidemiol 27:871–877
16. Johnson JL, Rajagopalan KV (1978) The interaction of arsenic with the molybdenum center of chicken liver xanthene dehydrogenese. Bioinorg Chem 8:439–444
17. Calabrese EJ (1980) Nutrition and environmental health. Wiley, New York
18. Harding-Barlow I (2003) In: Lederer WH, Fensterheim RJ (eds) Arsenic: industrial, biomedical, environmental perspective. Van Nostrand Reinhold, New York
19. US EPA (1988) Special report on ingested inorganic arsenic. Skin cancer, nutritional essentially (EPA/625/3-87/013). Environmental Protection Agency, Washington, DC
20. Vahter M (2000) Genetic polymorphism in the biotransformation of inorganic arsenic and its role in toxicity. Toxicol Lett 2000:112–113 and 209–217
21. Maity S, Chatterjee AK (2000) Differential response of cellular antioxidant mechanism of liver and kidney to arsenic exposure and its relation to dietary protein deficiency. Environ Pharmacol Toxicol 8(4):227–235
22. Vahter M, Marafante E (1987) Effects of low dietary intake of methionine, choline or proteins on the biotransformation of arsenite in the rabbit. Toxicol Lett 37:41–46
23. Steinmaus C, Carrigan K, Kalman D, Atallah R, Yuan Y, Smith AH (2005) Dietary intake and arsenic methylation in a U.S. population. Environ Health Perspect 113:1153–1159
24. Vahter M (1999) Methylation of inorganic arsenic in different mammalian species and population groups. Sci Prog 82(Pt.1):69–88 25. Heck JE, Nieves JW, Chen Y, Parvez F, Brandt-Rauf PW, Graziano JH, Slavkovich V, Howe GR, Ahsan H (2009) Dietaryintake of metionine, cysteine and protein and urinary arsenic excretion in Bangladesh. Environ Health Perspect 117:99–104
26. Zablotska LB, Chen Y, Graziano JH, Parvez F, Geen AV, Howe GR, Ahsan H (2008) Protective effects of B vitamins antioxidants on the risk of arsenic related skin lesions in Bangladesh. Environ Health Perspect 116:1056–1062
27. Roychowdhury T, Uchino T, Tokunaga H, Ando M (2002) Survey of arsenic in food composites from an arsenic-affected area of West Bengal, India. Food Chem Toxicol 40:1611–1621
28. Mazumder DNG, Ghosh A, Majumdar KK, Ghosh N, Saha C, Mazumder RNG (2010) Arsenic contamination of ground water and its health impact on population of district of Nadia, West Bengal, India. Indian J Community Med 35:331–338
29. Mitra SR, Mazumder DNG, Basu A, Blosk G, Haque R, Samanta S, Ghosh N, Smith MMH, Ehrenstein OSV, Smith H (2004) Nutritional Factors and susceptibility to arsenic caused skin lesions in West Bengal, India. Environ Med 112:1104–1109 30. Gopalan C, Sastri BVR, Balasubramanian SC (1996) Nutritive value of Indian foods. National Institute of Nutrition, Indian Council of Medical Research, Hyderabad, p 47–98
31. Bamji MS (1983) Vitamin deficiencies in rice-eating populations: effects of B-vitamin supplements. Experientia Suppl 44:245–263
32. Harrington JM, Middaugh JP, Morse DL, Houseworth J (1978) A survey of a population exposed to high concentrations of arsenicin well, water, in Fairbanks, Alaska. Am J Epidemol 108: 337–385
33. Maity S, Chatterjee AK (2001) Effects on levels on glutathione and some related enzymes in tissues after an acute arsenic exposure in rats and their relationship to dietary protein deficiency. Arch Toxicol 75:531–537
34. Yang YH, Blackwell RQ (1961) Nutritional and environmental conditions in the endemic black foot area. Formos Sci 15: 101–129
35. Steinmaus CM, Yuan Y, Smith AH (2005) The temporal stability of arsenic concentrations in well water in western Nevada. Environ Res 99:164–168
36. Heck JE, Gamble MV, Chen Y, Graziano JH, Slavonic V, Parvez F, Baron JA, Howe GR, Ahsan H (2007) Consumption of folaterelated nutrients and metabolism of arsenic in Bangladesh. Am J Clin Nutr 85(5):1367–1374
37. Hoffman DJ, Sanderson CJ, LeCaptain LJ, Cromartie E, Pendleton GW (1992) Interactive effects of arsenate, selenium and dietary protein on survival, growth and physiology in mallard ducklings. Arch Environ Contam Toxicol 22:55–62
38. Lammon CA, Hood RD (2004) Effects of protein deficient diets on the developmental toxicity of inorganic arsenic in mice. Birth Defects Res B Dev Report Toxicol 71:124–134
39. Kreppel H, Liu J, Liu Y, Reichl FX, Klassen CD (1994) Zinc induced arsenic tolerance in mice. Fundam Appl Toxicol 23:32–37
40. Haque R, Mazumder DNG, Samanta S, Ghosh N, Kalman D, Smith MM, Mitra S, Santra A, Lahiri S, Das S, De BK, Smith AH (2003) Arsenic in drinking water and skin lesions: dose response data from West Bengal, India. Epidemiology 14:174–182
41. Roychowdhury T, Tokunaga H, Ando M (2003) Survey of arsenic and other heavy metals in food composites and drinking water and estimation of dietary intake by the villagers from an arsenic affected area of West Bengal, India. Sci Total Environ 308:15–35
42. Watanabe C, Kawata A, Sudo N, Inaoka T, Bae M, Ohtsuka A (2004) Water intake in an Asian population living in arseniccontaminated area. Toxicol Appl Pharmacol 198:272–282
43. Tao SS, Bolger PM (1999) Dietary arsenic intake in the United States; FDA total diet study, September 1991-December 1996. Food Addit Contam 16:465–472

D. Deb D. N. G. Mazumder
DNGM Research Foundation, Kolkata, India, e-mail: mrs.debasree@yahoo.com

D. N. G. Mazumder
e-mail: guhamazumder@yahoo.com
D. Deb
Department of Home Science (Food and Nutrition), University of Calcutta, Kolkata, West Bengal, India

K. K. Majumdar (&)
Department of Community Medicine, KPC Medical College & Hospital, Jadavpur, Kolkata 700 032, West Bengal, India, e-mail: kunalmajumdar1@gmail.com

D. N. G. Mazumder
Department of Medicine and Gastroenterology, Institute of Post Graduate Medical Education and Research, DNGM Research Foundation, Kolkata 700 053, India

Posted by
Get the latest news on water, straight to your inbox
Subscribe Now
Continue reading