Association between mixed exposure to endocrine-disrupting chemicals and cognitive function in elderly Americans

Q. l Zuo, X. x. Gao, X. h. Fu, L. l. Song, M. q. Cen, S. f. Qin,J. Wu

PUBLIC HEALTH(2024)

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摘要
Objectives: Studies exploring the relationship between mixed exposure to endocrine-disrupting chemicals (EDCs) and cognition are limited, with even more scarce studies conducted in the elderly. The aim of this study was to investigate the association between mixed exposure to five categories of EDCs and cognition in elderly Americans. Study design: Cross-sectional study. Methods: 727 participants from the 2011-2014 National Health and Nutrition Examination Survey were incorporated into this study, and the levels of 47 EDC metabolites were measured. Cognitive function was assessed using immediate recall test (IRT), delayed recall test (DRT), animal fluency test (AFT), and digit symbol substitution test (DSST), and all the cognitive test scores were standardized. The individual and combined effects of EDC metabolites on the cognitive function in older adults were assessed using three analytical methods. Results: The results showed that exposure to perfluorononanoic acid, polychlorinated biphenyl (PCB) 199, and PCB 206 was associated with the z-scores on the cognitive tests. Negative associations between mixed exposure to EDCs and the AFT and Global z-scores and a positive relationship with the DRT z-score were found in the WQS regression. The BKMR results revealed a positive trend between the mixture of EDCs and the DRT z-score. However, compared to the median, exposure to mixtures in the 45th percentile and below was associated with a decreased DRT z-score. Conclusions: Mixed exposure to EDCs may adversely affect the global cognitive function in elderly individuals. Necessary measures are needed to restrict EDCs use to protect the cognitive health of older adults. (c) 2023 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
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关键词
Endocrine -disrupting chemicals,Cognitive function,Elderly,NHANES,Weighted quantile sum regression,Bayesian Kernel machine regression
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