Stratification of population in NHANES 2009–2014 based on exposure pattern of lead, cadmium, mercury, and arsenic and their association with cardiovascular, renal and respiratory outcomes

Yao, Xu; Xu, Xu Steven; Yang, Yaning; Zhu, Zhi Zheng; Zhu, Zhen; Tao, Fangbiao; Yuan, Min

doi:10.1016/j.envint.2021.106410

Cited by 77 publications

(34 citation statements)

References 22 publications

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“…Possible reasons for these discrepancies include differences in population demographics, exposure patterns and levels, mixture components, study designs, biospecimens measured, the timing of exposure and outcome assessment, population-specific unmeasured confounding, CVD outcome definitions, and the statistical approaches used [69]. The majority of studies were either cross-sectional in design (n = 13) [39,[42][43][44][45][46][47][49][50][51][52][53][54] or prospective cohort studies (n = 10) [38,[55][56][57][58][59][60][61][62][63]. Cardiovascular outcomes and risk factors were categorized into four groups: (i) blood pressure (BP) and hypertension, (ii) preeclampsia, (iii) dyslipidemia and serum lipid markers, and (iv) clinical CVD outcomes, including stroke, coronary heart disease (CHD), and myocardial infarction (MI).…”

Section: Resultsmentioning

confidence: 99%

“…Figure 1. Flow chart of literature review and study selection for papers published between 1998 through 1 October 2021.The majority of studies were either cross-sectional in design (n = 13)[39,[42][43][44][45][46][47][49][50][51][52][53][54] or prospective cohort studies (n = 10)[38,[55][56][57][58][59][60][61][62][63]. Cardiovascular outcomes and risk factors were categorized into four groups: (i) blood pressure (BP) and hypertension, (ii) preeclampsia, (iii) dyslipidemia and serum lipid markers, and (iv) clinical CVD outcomes, including stroke, coronary heart disease (CHD), and myocardial infarction (MI).…”

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confidence: 99%

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Exposure to Metal Mixtures in Association with Cardiovascular Risk Factors and Outcomes: A Scoping Review

Yim

Wang

Howe

et al. 2022

Toxics

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Since the National Institute of Environmental Health Sciences (NIEHS) declared conducting combined exposure research as a priority area, literature on chemical mixtures has grown dramatically. However, a systematic evaluation of the current literature investigating the impacts of metal mixtures on cardiovascular disease (CVD) risk factors and outcomes has thus far not been performed. This scoping review aims to summarize published epidemiology literature on the cardiotoxicity of exposure to multiple metals. We performed systematic searches of MEDLINE (PubMed), Scopus, and Web of Science to identify peer-reviewed studies employing statistical mixture analysis methods to evaluate the impact of metal mixtures on CVD risk factors and outcomes among nonoccupationally exposed populations. The search was limited to papers published on or after 1998, when the first dedicated funding for mixtures research was granted by NIEHS, through 1 October 2021. Twenty-nine original research studies were identified for review. A notable increase in relevant mixtures publications was observed starting in 2019. The majority of eligible studies were conducted in the United States (n = 10) and China (n = 9). Sample sizes ranged from 127 to 10,818. Many of the included studies were cross-sectional in design. Four primary focus areas included: (i) blood pressure and/or diagnosis of hypertension (n = 15), (ii) risk of preeclampsia (n = 3), (iii) dyslipidemia and/or serum lipid markers (n = 5), and (iv) CVD outcomes, including stroke incidence or coronary heart disease (n = 8). The most frequently investigated metals included cadmium, lead, arsenic, and cobalt, which were typically measured in blood (n = 15). The most commonly utilized multipollutant analysis approaches were Bayesian kernel machine regression (BKMR), weighted quantile sum regression (WQSR), and principal component analysis (PCA). To our knowledge, this is the first scoping review to assess exposure to metal mixtures in relation to CVD risk factors and outcomes. Recommendations for future studies evaluating the associations of exposure to metal mixtures with risk of CVDs and related risk factors include extending environmental mixtures epidemiologic studies to populations with wider metals exposure ranges, including other CVD risk factors or outcomes outside hypertension or dyslipidemia, using repeated measurement of metals to detect windows of susceptibility, and further examining the impacts of potential effect modifiers and confounding factors, such as fish and seafood intake.

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Section: Resultsmentioning

confidence: 99%

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confidence: 99%

Exposure to Metal Mixtures in Association with Cardiovascular Risk Factors and Outcomes: A Scoping Review

Yim

Wang

Howe

et al. 2022

Toxics

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“…Once individuals are grouped into pattern-based clusters, it is possible to compare the incidence of health outcomes of interest across clusters. Clustering enables the identification of the collection of exposures that contribute to the greatest risk of outcomes of interest and can inform-the development of multifactorial interventions and policies [17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Multi-Level Socioenvironmental Contributors to Childhood Asthma in New York City: a Cluster Analysis

et al. 2021

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Childhood asthma exacerbation remains the leading cause of pediatric emergency department visits and hospitalizations and disproportionately affects Latinx and Black children, compared to non-Latinx White children in NYC. Environmental exposures and socioeconomic factors may jointly contribute to childhood asthma exacerbations; however, they are often studied separately. To better investigate the multiple contributors to disparities in childhood asthma, we compiled data on various individual and neighborhood level socioeconomic and environmental factors, including education, race/ethnicity, income disparities, gentrification, housing characteristics, built environment, and structural racism, from the NYC Department of Health’s KIDS 2017 survey and the US Census’ American Community Survey. We applied cluster analysis and logistic regression to first identify the predominant patterns of social and environmental factors experienced by children in NYC and then estimate whether children experiencing specific patterns are more likely to experience asthma exacerbations. We found that housing and built environment characteristics, such as density and age of buildings, were the predominant features to differentiate the socio-environmental patterns observed in New York City. Children living in neighborhoods with greater proportions of rental housing, high-density buildings, and older buildings were more likely to experience asthma exacerbations than other children. These findings add to the literature about childhood asthma in urban environments, and can assist efforts to target actionable policies and practices that promote health equity related to childhood asthma.

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“…Indeed, biomonitoring of metals exposure is non-invasively performed by determination of their concentration in urine (Muñoz et al 2019 ; Renzetti et al 2021 ; Zeng et al 2021 ). Elevated urinary levels of 3 heavy metals (total arsenic, lead, cadmium) were associated with higher total, malignant neoplasms and nephritis-related, mortality as well as higher gamma-glutamyl transferase (Yao et al 2021 ). Moreover, urinary arsenic showed an impact on anxiety and depression, somatic problems, attention problems, and rule-breaking behavior (Renzetti et al 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Biomonitoring of urinary metals in athletes according to particulate matter air pollution before and after exercise

Cauci

Tavano

Curcio

et al. 2021

Environ Sci Pollut Res

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Exposure to air pollution during physical exercise is a health issue because fine particulate matter (dimension < 10 μm; PM 10 ) includes several inhalable toxic metals. Body metal changes in athletes according to air pollution are poorly known. Urinary concentrations of 15 metals: beryllium (Be 9 ), aluminum (Al 27 ), vanadium (V 51 ), chromium (Cr 51 + Cr 52 ), manganese (Mn 55 ), cobalt (Co 59 ), nickel (Ni 61 ), copper (Cu 63 ), zinc (Zn 61 ), arsenic (As 75 ), selenium (Se 82 ), cadmium (Cd 111 + Cd 112 ), thallium (Tl 125 ), lead (Pb 207 ), and uranium (U 238 ) were measured before and after ten 2-h training sessions in 8 non-professional Italian American-football players (18–28 years old, body mass index 24.2–33.6 kg/m 2 ). Collectively, post-training sessions, urinary concentrations of As, Cd, Co, Cu, Mn, Ni, Pb, Se, Tl, and Zn were higher than pre-training sessions; Al, Be, Cr, and U did not change; conversely, V decreased. Subdividing training sessions according to air PM 10 levels: low (< 20 μg/m 3 ), medium (20–40 μg/m 3 ), and high (> 40 μg/m 3 ), pre-session and post-session urinary concentrations of Be, Cd, Cu, and Tl were significantly higher ( p < 0.05) in more polluted days, whereas V concentrations were lower ( p < 0.001). All the remaining metals were unaffected. We first showed that PM 10 levels modulate urinary excretion of some toxic metals suggesting an effect of air pollution. The effects of toxic metals inhaled by athletes exercising in polluted air need further studies.

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Stratification of population in NHANES 2009–2014 based on exposure pattern of lead, cadmium, mercury, and arsenic and their association with cardiovascular, renal and respiratory outcomes

Cited by 77 publications

References 22 publications

Exposure to Metal Mixtures in Association with Cardiovascular Risk Factors and Outcomes: A Scoping Review

Exposure to Metal Mixtures in Association with Cardiovascular Risk Factors and Outcomes: A Scoping Review

Multi-Level Socioenvironmental Contributors to Childhood Asthma in New York City: a Cluster Analysis

Biomonitoring of urinary metals in athletes according to particulate matter air pollution before and after exercise

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