A Systematic Review and Meta-Regression Analysis of Lung Cancer Risk and Inorganic Arsenic in Drinking Water.

Center for Epidemiology and Environmental Health, Consultants in Epidemiology and Occupational Health (CEOH), Washington, DC 20016, USA. Steve@CEOH.com. Department of Health Policy and Management, School of Public Health, Johns Hopkins University-Bloomberg, Baltimore, MA 21205, USA. Steve@CEOH.com. Department of Pediatrics, School of Medicine, Georgetown University, Washington, DC 20057, USA. Steve@CEOH.com. Center for Epidemiology and Environmental Health, Consultants in Epidemiology and Occupational Health (CEOH), Washington, DC 20016, USA. Hamid@CEOH.com. Department of Epidemiology and Biostatistics, School of Public Health, George Washington University-Milken Institute, Washington, DC 20052, USA. Hamid@CEOH.com. Center for Epidemiology and Environmental Health, Consultants in Epidemiology and Occupational Health (CEOH), Washington, DC 20016, USA. Elisabeth.Dissen@gmail.com. Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, MA 28217, USA. JLi42@JHMI.edu. Department of Biostatistics, Bioinformatics, and Biomathematics, School of Medicine, Georgetown University, Washington, DC 20057, USA. JA1030@Georgetown.edu.

International journal of environmental research and public health. 2015;(12):15498-515
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Abstract

High levels (> 200 µg/L) of inorganic arsenic in drinking water are known to be a cause of human lung cancer, but the evidence at lower levels is uncertain. We have sought the epidemiological studies that have examined the dose-response relationship between arsenic levels in drinking water and the risk of lung cancer over a range that includes both high and low levels of arsenic. Regression analysis, based on six studies identified from an electronic search, examined the relationship between the log of the relative risk and the log of the arsenic exposure over a range of 1-1000 µg/L. The best-fitting continuous meta-regression model was sought and found to be a no-constant linear-quadratic analysis where both the risk and the exposure had been logarithmically transformed. This yielded both a statistically significant positive coefficient for the quadratic term and a statistically significant negative coefficient for the linear term. Sub-analyses by study design yielded results that were similar for both ecological studies and non-ecological studies. Statistically significant X-intercepts consistently found no increased level of risk at approximately 100-150 µg/L arsenic.

Methodological quality

Publication Type : Meta-Analysis ; Review

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