Predictors of Urinary Arsenic Levels among Postmenopausal Danish Women

Nina Roswall, Ulla A. Hvidtfeldt, James Harrington, Keith E. Levine, Mette Sørensen, Anne Tjønneland, Jaymie R. Meliker and Ole Raaschou-Nielsen
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Nina Roswall: Danish Cancer Society Research Center, Strandboulevarden 49, 2100 Copenhagen, Denmark
Ulla A. Hvidtfeldt: Danish Cancer Society Research Center, Strandboulevarden 49, 2100 Copenhagen, Denmark
James Harrington: Analytical Sciences Division, Research Triangle Institute, 3040 East Cornwallis Road, PO Box 12194, Research Triangle Park, NC 27709-2194, USA
Keith E. Levine: Analytical Sciences Division, Research Triangle Institute, 3040 East Cornwallis Road, PO Box 12194, Research Triangle Park, NC 27709-2194, USA
Mette Sørensen: Danish Cancer Society Research Center, Strandboulevarden 49, 2100 Copenhagen, Denmark
Anne Tjønneland: Danish Cancer Society Research Center, Strandboulevarden 49, 2100 Copenhagen, Denmark
Jaymie R. Meliker: Program in Public Health, Department of Family, Population, and Preventive Medicine, Stony Brook University, 101 Nicolls Road, Stony Brook, NY 11794, USA
Ole Raaschou-Nielsen: Danish Cancer Society Research Center, Strandboulevarden 49, 2100 Copenhagen, Denmark

IJERPH, 2018, vol. 15, issue 7, 1-15

Abstract: Arsenic is a risk factor for several noncommunicable diseases, even at low doses. Urinary arsenic (UAs) concentration is a good biomarker for internal dose, and demographic, dietary, and lifestyle factors are proposed predictors in nonoccupationally exposed populations. However, most predictor studies are limited in terms of size and number of predictors. We investigated demographic, dietary, and lifestyle determinants of UAs concentrations in 744 postmenopausal Danish women who had UAs measurements and questionnaire data on potential predictors. UAs concentrations were determined using mass spectrometry (ICP-MS), and determinants of the concentration were investigated using univariate and multivariate regression models. We used a forward selection procedure for model optimization. In all models, fish, alcohol, and poultry intake were associated with higher UAs concentration, and tap water, fruit, potato, and dairy intake with lower concentration. A forward regression model explained 35% ( R 2 ) of the variation in concentrations. Age, smoking, education, and area of residence did not predict concentration. The results were relatively robust across sensitivity analyses. The study suggested that UAs concentration in postmenopausal women was primarily determined by dietary factors, with fish consumption showing the strongest direct association. However, the majority of variation in UAs concentration in this study population is still unexplained.

Keywords: arsenic; determinants; predictors; diet; lifestyle; demography (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
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