Nutritional Factors and Susceptibility to Arsenic-Caused Skin Lesions in West Bengal, India
Open Access
- 1 July 2004
- journal article
- Published by Environmental Health Perspectives in Environmental Health Perspectives
- Vol. 112 (10) , 1104-1109
- https://doi.org/10.1289/ehp.6841
Abstract
There has been widespread speculation about whether nutritional deficiencies increase the susceptibility to arsenic health effects. This is the first study to investigate whether dietary micronutrient and macronutrient intake modulates the well-established human risk of arsenic-induced skin lesions, including alterations in skin pigmentation and keratoses. The study was conducted in West Bengal, India, which along with Bangladesh constitutes the largest population in the world exposed to arsenic from drinking water. In this case–control study design, cases were patients with arsenic-induced skin lesions and had < 500 μg/L arsenic in their drinking water. For each case, an age- and sex-matched control was selected from participants of a 1995–1996 cross-sectional survey, whose drinking water at that time also contained < 500 μg/L arsenic. Nutritional assessment was based on a 24-hr recall for major dietary constituents and a 1-week recall for less common constituents. Modest increases in risk were related to being in the lowest quintiles of intake of animal protein [odds ratio (OR) = 1.94; 95% confidence interval (CI), 1.05–3.59], calcium (OR = 1.89; 95% CI, 1.04–3.43), fiber (OR = 2.20; 95% CI, 1.15–4.21), and folate (OR = 1.67; 95% CI, 0.87–3.2). Conditional logistic regression suggested that the strongest associations were with low calcium, low animal protein, low folate, and low fiber intake. Nutrient intake was not related to arsenic exposure. We conclude that low intake of calcium, animal protein, folate, and fiber may increase susceptibility to arsenic-caused skin lesions. However, in light of the small magnitude of increased risks related to these dietary deficiencies, prevention should focus on reducing exposure to arsenic.Keywords
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