Association of albumin to creatinine ratio with urinary arsenic and metal exposure: evidence from NHANES 2015–2016

Rahman, Humairat H; Niemann, Danielle; Munson-McGee, Stuart H.

doi:10.1007/s11255-021-03018-y

Cited by 21 publications

(8 citation statements)

References 59 publications

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“…For example, Ferraro et al (2010) found Cadmium exposure to be associated with increased risk of chronic kidney disease, based on an analysis of NHANES data from 1999-2006. In a recent study, Rahman et al (2022) found Cesium, Cadmium, and Antimony to be associated with kidney damage. The proposed approach detects multiple synergistic and antagonistic interactions between exposures.…”

Section: Resultsmentioning

confidence: 98%

Inferring Synergistic and Antagonistic Interactions in Mixtures of Exposures

Chattopadhyay¹,

Engel²,

Dunson³

2022

Preprint

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There is abundant interest in assessing the joint effects of multiple exposures on human health. This is often referred to as the mixtures problem in environmental epidemiology and toxicology. Classically, studies have examined the adverse health effects of different chemicals one at a time, but there is concern that certain chemicals may act together to amplify each other's effects. Such amplification is referred to as synergistic interaction, while chemicals that inhibit each other's effects have antagonistic interactions. Current approaches for assessing the health effects of chemical mixtures do not explicitly consider synergy or antagonism in the modeling, instead focusing on either parametric or unconstrained nonparametric dose response surface modeling. The parametric case can be too inflexible, while nonparametric methods face a curse of dimensionality that leads to overly wiggly and uninterpretable surface estimates. We propose a Bayesian approach that decomposes the response surface into additive main effects and pairwise interaction effects, and then detects synergistic and antagonistic interactions. Variable selection decisions for each interaction component are also provided. This Synergistic Antagonistic Interaction Detection (SAID) framework is evaluated relative to existing approaches using simulation experiments and an application to data from NHANES.

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Section: Resultsmentioning

confidence: 98%

Inferring Synergistic and Antagonistic Interactions in Mixtures of Exposures

Chattopadhyay¹,

Engel²,

Dunson³

2022

Preprint

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“…The family income-to-poverty ratio was classified as lower than 1.5, 1.5–3.5, and over 3.5. 22 Alcohol intake was categorized as none (<1 drink per week), light (1–3 drinks per week), and heavy (4 drinks or more per week). 23 Serum cotinine was utilized as an indicator of exposure to environmental tobacco smoke.…”

Section: Participants and Methodsmentioning

confidence: 99%

The association between heavy metal exposure and erectile dysfunction in the United States

Wang¹,

Xiang²,

Ma³

et al. 2023

Asian J Androl

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Literature regarding the impacts of heavy metal exposure on erectile dysfunction (ED) is scarce. We aimed to evaluate the correlation between 10 urinary metals and ED in a large, nationally representative adult male sample. The dataset was extracted from the National Health and Nutrition Examination Survey (NHANES) during the period of 2001–2002 and 2003–2004. Weighted proportions and multivariable logistic regression analysis adjusted for confounding variables were utilized to determine the relationship between metal exposure and ED. Weighted quantile sum (WQS) regression was utilized to evaluate the impact of a mixture of urinary metals on ED. A total of 1328 participants were included in our study. In multivariable logistic regression analysis, cobalt (Co) and antimony (Sb) were positively associated with ED (odds ratio [OR]: 1.36, 95% confidence interval [CI]: 1.10–1.73, P = 0.020; and OR: 1.41, 95% CI: 1.12–1.77, P = 0.018, respectively) after full adjustment. Men in tertile 4 for Co (OR: 1.49, 95% CI: 1.02–2.41, P for trend = 0.012) and Sb (OR: 1.53, 95% CI: 1.08–2.40, P for trend = 0.041) had significantly higher odds of ED than those in tertile 1. Furthermore, the WQS index was significantly linked with increased odds of ED after full adjustment (OR: 1.31, 95% CI 1.04–1.72, P < 0.05). Our study expanded on previous literature indicating the possible role of heavy metal exposure in the etiology of ED. The evaluation of heavy metal exposure should be included in the risk assessment of ED.

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“…The tertile with the lowest value of urinary metal concentration was regarded as reference, regression coefficient β and 95% CI were also reported to indicate the association between urinary metal concentration and UACR in each tertile, respectively. Based on prior knowledge and literature accumulation ( 7 , 48 , 49 ), we adjusted age, sex, BMI, education levels, smoking status, drinking status, hypertension and diabetes in the model.…”

Section: Methodsmentioning

confidence: 99%

“…Clinically, UACR has been considered an early and sensitive indicator to determine CKD ( 6 ). UACR is beneficial in that it has low requirements for samples, as it is noninvasive and can be detected using a spot urine sample rather than 24 h urine ( 7 ).…”

Section: Introductionmentioning

confidence: 99%

Association of Metals and Metalloids With Urinary Albumin/Creatinine Ratio: Evidence From a Cross-Sectional Study Among Elderly in Beijing

Zhao

Liu

et al. 2022

Front. Public Health

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BackgroundEnvironmental exposure to toxic elements contributes to the pathogenesis of chronic kidney disease (CKD). Few studies focus on the association of urinary metals and metalloids concentrations with the urinary albumin/creatinine ratio (UACR) among elderly, especially in areas and seasons with severe air pollution.ObjectiveWe aimed to evaluate the associations of urinary metals and metalloids concentration with UACR, which is an early and sensitive indicator of CKD.MethodWe conducted a cross-sectional study among 275 elderly people in Beijing from November to December 2016, which has experienced the most severe air pollution in China. We measured 15 urinary metals and metalloids concentration and estimated their association with UACR using a generalized linear model (GLM). Bayesian kernel machine regression (BKMR) and quantile g-computation (qgcomp) models were also conducted to evaluate the combined effect of metal and metalloid mixtures concentration.ResultsOf the 275 elderly people included in the analysis, we found that higher urinary Cu concentration was positively associated with UACR using GLM (β = 0.36, 95% CI: 0.25, 0.46). Using the BKMR model, we found that the change in UACR was positively associated with a change in urinary Cu concentration from its 25th to 75th percentile value with all other metals and metalloids concentration fixed at their 25th, 50th, or 75th percentile levels. Urinary Cu concentration had the most significant positive contribution (59.15%) in the qgcomp model. Our finding was largely robust in three mixture modeling approaches: GLM, qgcomp, and BKMR.ConclusionThis finding suggests that urinary Cu concentration was strongly positively associated with UACR. Further analyses in cohort studies are required to corroborate this finding.

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Association of albumin to creatinine ratio with urinary arsenic and metal exposure: evidence from NHANES 2015–2016

Cited by 21 publications

References 59 publications

Inferring Synergistic and Antagonistic Interactions in Mixtures of Exposures

Inferring Synergistic and Antagonistic Interactions in Mixtures of Exposures

The association between heavy metal exposure and erectile dysfunction in the United States

Association of Metals and Metalloids With Urinary Albumin/Creatinine Ratio: Evidence From a Cross-Sectional Study Among Elderly in Beijing

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