Assessing metal mixture effects on neuropsychological development: A trade-off between complexity and interpretability
Year: 2025
Type: article
Study design: Observational Study
Abstract: Several studies have explored the joint effect of mixtures of metals on health outcomes by using sophisticated statistical techniques such as Bayesian Kernel Machine Regression (BKMR). Although these appealing tools can detect complex relationships between metals, their interpretation is not straightforward. Indeed, BKMR is frequently used jointly with other methods, and final conclusions are simplified in terms of increase/decrease of the risk function at fixed values for individual metals. In this paper, we explore the feasibility and interpretability of such techniques to assess the effect of metal mixture exposures on neuropsychological development in early childhood. This is a cross-sectional study. Initially, we use Principal Components Analysis (PCA) to detect main latent neurodevelopment domains. The scores derived by the BKMR exposure-response function were computed and compared with those provided by traditional linear regression models (LRM). Pearson's correlation coefficients of the estimations obtained by BKMR and LRM accounting for pairwise interactions between metals (lead, molybdenum, and selenium) were 0.95, 0.95 and 0.92, for the three identified latent domains: executive functions, motor functions and visual and verbal functions, respectively. The observed differences between both estimations mainly occurred in participants having low concentrations of lead and low and high values of selenium, which suggest linearity in the associations and not high order interactions between metals. We concluded that, in this case, employing linear regression to model the impact of mixtures on targeted outcomes led to similar results than more complex statistical techniques, allowing a better understanding of both individual and interaction effects between metals.
Institutions: Dartmouth Health, Dartmouth College, Universidad Autónoma de Chile, Universitat Jaume I, Universitat de València, Instituto de Salud Carlos III, Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana, Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública, Universidad de Oviedo, Instituto de Investigación Sanitaria del Principado de Asturias, University of the Basque Country, Biogipuzkoa Health Research Institute, Universitat Pompeu Fabra, Erasmus MC, Barcelona Institute for Global Health, Institut de Recerca Biomèdica Catalunya Sud, Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL)
Language: English
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,800
Funders: Centres de Recerca de Catalunya, European Commission, Deutsche Forschungsgemeinschaft, Generalitat de Catalunya, Eusko Jaurlaritza, Generalitat Valenciana, Ministerio de Ciencia e Innovación, Instituto de Investigación Sanitaria del Principado de Asturias, Instituto de Salud Carlos III, Agencia Estatal de Investigación, Ministerio de Universidades, NextGenerationEU
Awards: G1749994109, G1877160490, G1916465975, G1929206383, G2006876140, G2030817791, G2218018545, G2585906617, G3405515844, G3423777635, G4106119142, G4145846527, G4281347028, G43203158, G4619193523, G4666324886, G5142168144, G521056402, G531955004, G5500999890, G589846866, G6145369101, G6244081246, G6328075693, G6840703489, Exposición prenatal a compuestos orgánicos persistentes y obesidad y síndrome metabólico a los 11 años de edad: Un estudio prospectivo de COHORTE, G6999846316, G7208110030, G7256164011, G73640366, G7507141173, G7666946026, G8219708615, G8563013907, G8804906264, G8964774466, G903740175, G956958452, G984522414
OpenAlex ID: W4415507501