Abstract
Abstract
In this issue of the Journal, Upson et al. (Am J Epidemiol. 2021;190(1):116–124) assess urinary cadmium level as a potential environmental influence on ovarian reserve, as measured using serum follicle-stimulating hormone, in data from 1,681 US women (1988–1994). They compare 3 methods for modeling urinary proxy exposures—standardization, covariate adjustment, and covariate-adjusted standardization. Observing positive associations with all 3 approaches but higher-magnitude estimates using covariate adjustment as compared with standardization and covariate-adjusted standardization—proposed to be the result of collider-stratification bias—the authors conclude that cadmium may affect ovarian aging, and they recommend careful consideration of modeling approach. Comparisons of methodology in practice using real data are not straightforward, and additional complication arises from using a proxy outcome—serum follicle-stimulating hormone level to represent diminished ovarian reserve. In this commentary, I describe the theoretical basis for approaches for modeling urinary proxy exposures; consider potential explanations for why the approaches may yield different results in practice and describe why measurement error may play a larger role than collider-stratification bias; discuss challenges related to studies of ovarian reserve; and emphasize the importance of addressing both theoretical concerns and real-world challenges in methodological research and epidemiologic studies of ovarian reserve.
Publisher
Oxford University Press (OUP)