Record Display for the EPA National Library Catalog


Main Title Statistical Issues in Risk Assessment of Reproductive Outcomes with Chemical Mixtures.
Author Hertzberg, V. S. ; Lemasters, G. K. ; Hansen, K. ; Zenick., H. M. ;
CORP Author Health Effects Research Lab., Research Triangle Park, NC. ;Cincinnati Univ., OH. Dept. of Environmental Health.
Publisher c1991
Year Published 1991
Report Number EPA/600/J-91/087;
Stock Number PB91-199992
Additional Subjects Reproduction(Biology) ; Risk assessment ; Toxic substances ; Mixtures ; Occupational exposure ; Wastewater treatment ; Pregnancy outcome ; Spermatozoa ; Infertility ; Spontaneous abortion ; Reprints ; Cross-sectional studies
Library Call Number Additional Info Location Last
NTIS  PB91-199992 Some EPA libraries have a fiche copy filed under the call number shown. 07/26/2022
Collation 7p
Establishing the relationship between a given chemical exposure and human reproductive health risk is complicated by exposures or other concomitant factors that may vary from pregnancy to pregnancy. Moreover, when exposures are to complex mixtures of chemicals, varying with time in number of components, doses of individual components, and constancy of exposure, the picture becomes even more complicated. A pilot study of risk of adverse reproductive outcomes among male wastewater treatment workers and their wives is described. Wives of 231 workers were interviewed to evaluate retrospectively the outcomes of spontaneous early fetal loss and infertility. In addition, 87 workers participated in a cross-sectional evaluation of sperm/semen parameters. Due to the ever-changing nature of exposure and lack of quantification of specific exposures, six dichotomous variables were used for each specific job description to give a surrogate measure of exposure. Hence, no quantitative exposure-response relationships could be modeled. These six variables were independently assigned by two environmental hygienists, and their interrater reliability was assessed. Results are presented and further innovations in statistical methodology are proposed for further applications.