Exposure to 17 trace metals in pregnancy and associations with urinary oxidative stress biomarkers

Kim, Stephani S.; Meeker, John D.; Keil, Alexander P.; Aung, Max T.; Bommarito, Paige A.; Cantonwine, David E.; McElrath, Thomas F.; Ferguson, Kelly K.

doi:10.1016/j.envres.2019.108854

Cited by 48 publications

(31 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The GM concentration of Zn in our study (402.5 μg/L) was approximately twice as high as that reported from 380 pregnant women in the LIFECODES cohort study in Boston (median = 203.6 μg/L) (Kim et al 2019). Similarly, we observed a twofold increase in the GM concentration of urinary Se (75.69 μg/L) as compared with the GM concentration (35.4 μg/L) reported by Kim et al from the LIFECODES cohort (Kim et al 2019). It is possible that the differences in results might be affected by different racial/ethnic and socioeconomic composition of study participants.…”

Section: Discussioncontrasting

confidence: 42%

“…However, there is evidence that elevated levels of these compounds may be associated with adverse cardiovascular outcomes such as hypertension (Wu et al 2018;Laclaustra et al 2009). Kim et al (2019) also found a positive association between Se concentrations among the pregnant women in their study and urinary concentrations of 8-isoprostane and 8hydroxydeoxyguanosine (8-OHdG), biomarkers of oxidative stress (Kim et al 2019).…”

Section: Discussionmentioning

confidence: 92%

“…It is possible that the differences in results might be affected by different racial/ethnic and socioeconomic composition of study participants. The population in the Kim et al (2019) consisted of largely well-educated non-Hispanic white women. In contrast, urine specimens in our study were provided by African-American women who sought care from a prenatal clinic that serves primarily Medicaid recipients.…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Characterization of urinary concentrations of heavy metals among socioeconomically disadvantaged black pregnant women

Han

Whitworth

Zhang

et al. 2020

Environ Monit Assess

View full text Add to dashboard Cite

The objective of this study was to characterize exposures to metals using biological samples collected on socioeconomically disadvantaged black pregnant women. We obtained 131 anonymous urine samples provided by black pregnant women visiting a Medicaid-serving prenatal clinic in Houston, TX, from March 27, 2017 to April 11, 2017. We analyzed urine samples for 15 metals including cadmium (Cd), arsenic (As), lead (Pb), and nickel (Ni) and for creatinine and cotinine. We found that median concentrations of zinc (Zn), selenium (Se), and aluminum (Al) among black pregnant women in this study were 1.5 to 3 times higher than levels reported among a cohort of well-educated non-Hispanic white pregnancy planners. We also observed elevated levels of urinary Cd and antimony (Sb) as compared with those reported for a nationally representative sample of adult women in the USA. Based on the results of an exploratory factor analysis, potential sources of metal exposures in this population may arise in home environments or be due to diet, industrial and natural sources, or traffic.

show abstract

Section: Discussioncontrasting

confidence: 42%

Section: Discussionmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Characterization of urinary concentrations of heavy metals among socioeconomically disadvantaged black pregnant women

Han

Whitworth

Zhang

et al. 2020

Environ Monit Assess

View full text Add to dashboard Cite

show abstract

“…We used linear mixed models (LMM) with a random intercept for subject ID to model each prostanoid measure as the dependent variable, with separate models for each exposure biomarker. The crude models included the metal concentration as the exposure and specific gravity as a covariate to adjust for urinary dilution [43,60,61]. The final set of covariates were selected based on a priori knowledge and if their inclusion appreciably changed the effect estimates of metal exposure.…”

Section: Methodsmentioning

confidence: 99%

“…Most metals, including essential metals, are redox-active and therefore have the potential to increase production of ROS and enhance lipid peroxidation [41,42]. To our knowledge, two prior studies explored the direct effects of essential and non-essential trace metals on oxidative stress biomarkers during pregnancy [26,43]. Dashner-Titus et al reported that As is associated with increased levels of urinary 8-iso-PGF2α [26] and Kim et al found positive associations of urinary Se and Cu with oxidative stress markers [43].…”

Section: Introductionmentioning

confidence: 99%

Maternal Urinary Metal and Metalloid Concentrations in Association with Oxidative Stress Biomarkers

Ashrap¹,

Watkins²,

Milne³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Metal exposure has been associated with a wide range of adverse birth outcomes and oxidative stress is a leading hypothesis of the mechanism of action of metal toxicity. We assessed the relationship between maternal exposure to essential and non-essential metals and metalloids in pregnancy and oxidative stress markers, and sought to identify windows of vulnerability and effect modification by fetal sex. In our analysis of 215 women from the PROTECT birth cohort study, we measured 14 essential and non-essential metals in urine samples at three time points during pregnancy. The oxidative stress marker 8-iso-prostaglandin F2α (8-iso-PGF2α) and its metabolite 2,3-dinor-5,6-dihydro-15-15-F2t-IsoP, as well as prostaglandin F2α (PGF2α), were also measured in the same urine samples. Using linear mixed models, we examined the main effects of metals on markers of oxidative stress as well as the visit-specific and fetal sex-specific effects. After adjustment for covariates, we found that a few urinary metal concentrations, most notably cesium (Cs) and copper (Cu), were associated with higher 8-iso-PGF2α with effect estimates ranging from 7.3 to 14.9 % for each interquartile range, increase in the metal concentration. The effect estimates were generally in the same direction at the three visits and a few were significant only among women carrying a male fetus. Our data show that higher urinary metal concentrations were associated with elevated biomarkers of oxidative stress. Our results also indicate a potential vulnerability of women carrying a male fetus.

show abstract

Modeling variation in mixture effects over space with a Bayesian spatially varying mixture model

Boyle,

Ward,

Cerhan

et al. 2024

Statistics in Medicine

View full text Add to dashboard Cite

Mixture analysis is an emerging statistical tool in epidemiological research that seeks to estimate the health effects associated with mixtures of several exposures. This approach acknowledges that individuals experience many simultaneous exposures and it can estimate the relative importance of components in the mixture. Health effects due to mixtures may vary over space driven by to political, demographic, environmental, or other differences. In such cases, estimating a global mixture effect without accounting for spatial variation would induce bias in effect estimates and potentially lower statistical power. To date, no methods have been developed to estimate spatially varying chemical mixture effects. We developed a Bayesian spatially varying mixture model that estimates spatially varying mixture effects and the importance weights of components in the mixture, while adjusting for covariates. We demonstrate the efficacy of the model through a simulation study that varies the number of mixtures (one and two) and spatial pattern (global, one‐dimensional, radial) and magnitude of mixture effects, showing that the model is able to accurately reproduce the spatial pattern of mixture effects across a diverse set of scenarios. Finally, we apply our model to a multi‐center case‐control study of non‐Hodgkin lymphoma (NHL) in Detroit, Iowa, Los Angeles, and Seattle. We identify significant spatially varying positive and inverse associations with NHL for two mixtures of pesticides in Iowa and do not find strong spatial effects at the other three centers. In conclusion, the Bayesian spatially varying mixture model represents a novel method for modeling spatial variation in mixture effects.

show abstract

Exposure to 17 trace metals in pregnancy and associations with urinary oxidative stress biomarkers

Cited by 48 publications

References 64 publications

Characterization of urinary concentrations of heavy metals among socioeconomically disadvantaged black pregnant women

Characterization of urinary concentrations of heavy metals among socioeconomically disadvantaged black pregnant women

Maternal Urinary Metal and Metalloid Concentrations in Association with Oxidative Stress Biomarkers

Modeling variation in mixture effects over space with a Bayesian spatially varying mixture model

Contact Info

Product

Resources

About