| Autor: |
Bruce Allen, Kan Shao, Kevin Hobbie, William Mendez, Jr., Janice S. Lee, Ila Cote, Ingrid Druwe, Jeff Gift, J. Allen Davis |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
Environment International, Vol 142, Iss , Pp 105810- (2020) |
| Druh dokumentu: |
article |
| ISSN: |
0160-4120 |
| DOI: |
10.1016/j.envint.2020.105810 |
| Popis: |
Meta-analysis approaches can be used to assess the human risks due to exposure to environmental chemicals when there are numerous high-quality epidemiologic studies of priority outcomes in a database. However, methodological issues related to how different studies report effect measures and incorporate exposure into their analyses arise that complicate the pooled analysis of multiple studies. As such, there are “pre-analysis” steps that are often necessary to prepare summary data reported in epidemiologic studies for dose-response analysis. This paper uses epidemiologic studies of arsenic-induced health effects as a case example and addresses the issues surrounding the estimation of mean doses from censored dose- or exposure-intervals reported in the literature (e.g., estimation of mean doses from high exposures that are only reported as an open-ended interval), calculation of a common dose metric for use in a dose-response meta-analysis (one that takes into consideration inter-individual variability), and calculation of response “effective counts” that inherently account for confounders. The methods herein may be generalizable to 1) the analysis of other environmental contaminants with a suitable database of epidemiologic studies, and 2) any meta-analytic approach used to pool information across studies. A second companion paper detailing the use of “pre-analyzed” data in a hierarchical Bayesian dose-response model and techniques for extrapolating risks to target populations follows. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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Full Text from ScienceDirect