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Exposure to inorganic arsenic in drinking water and total urinary arsenic concentration in a Chilean population. 2005

Dante D Caceres, and Paulina Pino, and Nestor Montesinos, and Eduardo Atalah, and Hugo Amigo, and Dana Loomis
Environmental and Occupational Health Division, School of Public Health, University of Chile, Chile. caceres@email.unc.edu

The relationship of inorganic arsenic exposure through drinking water and total urinary arsenic excretion in a nonoccupationally exposed population was evaluated in a cross-sectional study in three mayor cities of Chile (Antofagasta, Santiago, and Temuco). A total of 756 individuals in three population strata (elderly, students, and workers) provided first morning void urine specimens the day after exposure and food surveys were administered. Arsenic intake from drinking water was estimated from analysis of tap water samples, plus 24-h dietary recall and food frequency questionnaires. Multilevel analysis was used to evaluate the effects of the age group and city factors adjusted by predictor variables. Arsenic levels in drinking water and urine were significantly higher in Antofagasta compared with the other cities. City-and individual-level factors, 12% and 88%, respectively, accounted for the variability in urinary arsenic concentration. The main predictors of urinary arsenic concentration were total arsenic consumption through water and age. These findings indicate that arsenic concentration in drinking water continues to be the principal contributing factor to exposure to inorganic arsenic in the Chilean population.

UI MeSH Term Description Entries
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D002677 Chile A country in southern South America, bordering the South Pacific Ocean, between Argentina and Peru.
D003404 Creatinine Creatinine Sulfate Salt,Krebiozen,Salt, Creatinine Sulfate,Sulfate Salt, Creatinine
D004326 Drinking The consumption of liquids. Water Consumption,Water Intake,Drinkings
D004781 Environmental Exposure The exposure to potentially harmful chemical, physical, or biological agents in the environment or to environmental factors that may include ionizing radiation, pathogenic organisms, or toxic chemicals. Exposure, Environmental,Environmental Exposures,Exposures, Environmental
D004784 Environmental Monitoring The monitoring of the level of toxins, chemical pollutants, microbial contaminants, or other harmful substances in the environment (soil, air, and water), workplace, or in the bodies of people and animals present in that environment. Monitoring, Environmental,Environmental Surveillance,Surveillance, Environmental
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man

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