Exposure to a high selenium environment in Punjab, India: Effects on blood chemistry

Many studies have shown that overexposure to environmental selenium may exert a wide pattern of adverse effects on human health, but much uncertainty still surrounds some of them as well as the exact amounts of exposure involved. In particular, very few studies have addressed the possible changes in blood chemistry following high selenium exposure. In a Northeastern part of Punjab, India, very high soil selenium content has been documented, with a value exceeding 2 mg/kg (up to 5) as compared with the <0.5 mg/kg selenium content characterizing the surrounding referent areas. In seven villages located in that seleniferous areas, we carried out a survey by recruiting volunteers and sampling blood, hair and nail specimens. We administered a questionnaire to the participants and analyzed the specimens for the selenium, along with a series of biochemical and haematological parameters in blood. We included 680 adult volunteers (267 men and 413 women), who showed median selenium levels of 171.30 µg/L in serum, 1.25 µg/g in hair, and 5.7 µg/g in nails. Overall, increasing selenium exposure tended to correlate with higher levels of total cholesterol, albumin, free triiodothyronine, deionidase activity, and with red cell and platelet counts. After stratifying the subjects according to category of selenium exposure, we observed a dose-response relation between serum selenium and risk of high total cholesterol, and between hair selenium and risk of high total and low-density lipoprotein cholesterol, high pancreatic lipase, altered thyroid-stimulating hormone and free triiodothyronine levels. Nail selenium exposure category positively correlated with risk of high alanine-aminotransferase, altered albumin levels, high pancreatic lipase and low levels of thyroid-stimulating hormone. Chronic selenium overexposure appears to adversely affect lipid profiles and pancreatic, liver, and thyroid function, with selenium biomarkers having different abilities to predict such effects.