Heart rate variation and human body burdens of environmental mixtures in the Cree First Nation communities of Eeyou Istchee, Canada

Introduction: Heart rate variability (HRV) is a measure of cardiac autonomic regulation that examines the variation in beat-to-beat fluctuations in heart rate. While many exposure-based studies have examined the effects of single or similar groups of contaminants on HRV parameters, none have examine...

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Bibliographic Details
Main Authors: Eric Liberda, Aleksandra M. Zuk, Leonard J. S. Tsuji
Format: Article in Journal/Newspaper
Language:unknown
Published: 2023
Subjects:
Online Access:https://doi.org/10.32920/22782713.v1
https://figshare.com/articles/journal_contribution/Heart_rate_variation_and_human_body_burdens_of_environmental_mixtures_in_the_Cree_First_Nation_communities_of_Eeyou_Istchee_Canada/22782713
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Summary:Introduction: Heart rate variability (HRV) is a measure of cardiac autonomic regulation that examines the variation in beat-to-beat fluctuations in heart rate. While many exposure-based studies have examined the effects of single or similar groups of contaminants on HRV parameters, none have examined the association between complex environmental mixtures, including organic and elemental contaminants, and HRV. Methods: Using data collected from the Multi-Community Environment-and-Health Study in Eeyou Istchee (Quebec, Canada), we assessed HRV in two time domain measures: root mean square of successive differences (RMSSD) and standard deviation of the N-N (RR) intervals (SDNN); and in three frequency domains: high frequency (HF), low-frequency (LF), and very-low frequency (VLF) in 443 participants. We first examined mixture effects of nineteen organic and metal contaminants in blood using principal component analysis (PCA) and a multivariable general linear regression on HRV responses, adjusting for age, sex, body mass index, smoking status, and kidney disease covariates. We subsequently assessed HRV outcome response variables using Bayesian kernel machine regression (BKMR) to further examine individual contaminant contribution and overall mixture effects. Results: In the PCA, a significant positive association was observed between RMSSD and principal component (PC) axis 2, which was highly positively-loaded for nickel and moderately negatively-loaded for mercury. A negative association between SDNN and PC-1, which was highly positively-loaded for all PCBs (polychlorinated biphenyls) and organochlorines and moderately positively-loaded for mercury, was observed. Additionally, a significant and positive association was observed between PC-2 and SDNN and a significant and negative association between PC-3 (negatively loaded for cadmium) and LF. Associations with contaminants were not observed for HF or VLF. BKMR results suggest that trans-nonachlor and cis-nonachlor are primarily responsible for reductions in HRV; ...