Applications of mixture methods in epidemiological studies investigating the health impact of persistent organic pollutants exposures: a scoping review.

Abstract

Persistent organic pollutants (POPs) are environmental chemicals characterized by long half-lives in nature and human bodies, posing significant health risks. The concept of the exposome, encompassing all lifetime environmental exposures, underscores the importance of studying POP as mixtures rather than in isolation. The increasing body of evidence on the health impacts of POP mixtures necessitates the proper application of statisticalmethods. We aimed to summarize studies on the overall effects of POP mixtures, identify patterns in applications of mixture methods-statistical methods for investigating the association of mixtures-and highlight current challenges in synthesizing epidemiologic evidence of POP mixtures on health effects as illustrated through a case study. We conducted a systematic literature search on PubMed and Embase for epidemiological studies published between January 2011 and April 2023. We included 240 studies that met our eligibility criteria. 126 studies focused on per- and polyfluoroalkyl substances (PFAS) mixtures only, while 40 analyzed three or more classes of POPs in mixture analyses. We identified 23 unique mixture methods used to estimate the overall effects of POP mixtures, with Bayesian Kernel Machine Regression (BKMR), a type of response-surface modeling, being the most common. Additionally, 22.9% of studies used a combination of methods, including response-surface modeling, index modeling, dimension reduction, and latent variable models. The most extensively explored health outcome category was body weight and birth sizes (n = 43), and neurological outcomes (n = 41). In the case study of PFAS mixtures and birth weight, 12 studies showed negative associations, while 4 showed null results, and 2 showed positive associations. This scoping review consolidates the existing literature on the overall effects of POP mixtures using statistical methods. By providing a comprehensive overview, our study illuminates the present landscape of knowledge in this field and underscores the methodological hurdles prevalent in epidemiological studies focused on POP mixtures. Through this analysis, we aim to steer future research directions, fostering a more nuanced comprehension of the intricate dynamics involved in assessing the health effects of POP mixtures. Our work stands as a significant contribution to the ongoing exploration of the chemicalexposome.