Association of multiple metals with lipid markers against different exposure profiles: A population-based cross-sectional study in China

Li, Zhaoyang; Xu, Yajuan; Huang, Zhijun; Wei, Yonggang; Hou, Jian; Long, Tengfei; Wang, Fei; Cheng, Xu; Duan, Yanying; Chen, Xiang; Yuan, Hong; Shen, Min; He, Meian

doi:10.1016/j.chemosphere.2020.128505

Cited by 39 publications

(26 citation statements)

References 69 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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Section: Methodsmentioning

confidence: 99%

“…(2) Rural residents from Huayuan, Shimen, Hengyang, and Zhuzhou cities or counties of Hunan province who are participants of the Hunan Rural Resident Chronic Disease Study(17,18): the study was established in 2016 and recruited residents in rural regions through cluster sampling by the village. (3) Civil servants from Changsha city of Hunan province who are participants of the Hunan Government Employee Health Study(19,20): the study was established in 2017 and recruited civil servants in urban regions through cluster sampling by institutions.…”

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confidence: 99%

Processed Food and Atopic Dermatitis: A Pooled Analysis of Three Cross-Sectional Studies in Chinese Adults

Luo

et al. 2021

Front. Nutr.

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Objective: The effect of processed foods on atopic dermatitis (AD) in adults is unclear. This study was to evaluate the association between processed foods and AD in the Chinese adult population.Design: This study included three population-based cross-sectional studies using cluster sampling by villages, institutions, or factories. Participants underwent dermatological examinations by certificated dermatologists and a food frequency questionnaire survey. A spot urine sample was collected to estimate the daily sodium intake. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were presented as the effect size.Setting: Shiyan city of Hubei province, and Huayuan, Shimen, Hengyang, Zhuzhou, and Changsha of Hunan province.Participants: Automobile manufacture workers from Shiyan of Hubei province, and rural residents and civil servants from Hunan.Results: A total of 15,062 participants, including 3,781 rural residents, 5,111 civil servants, and 6,170 workers, completed all evaluations. Compared to those hardly consumed pickles, consumption of pickles 1–3 times per week was significantly associated with AD (aOR: 1.35; 95% CI: 1.06–1.70). The intake of processed meats 1–3 times per month (aOR: 1.29; 95% CI: 1.05–1.58) and 1–3 times per week (aOR: 1.44; 95% CI: 1.11–1.87) were associated with AD dose-dependently when compared with those who rarely ate processed meats. Compared with non-consumers, the consumption of any processed foods 1–3 times per week (aOR: 1.39; 95% CI: 1.08–1.80) and ≥4 times per week (aOR: 1.41; 95% CI: 1.05–1.89) showed increased risks of AD. A positive association of estimated sodium intake with AD was also observed.Conclusion: Intake of processed foods is associated with AD in Chinese adults.

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“…However, the GLM has some limitations, including its ine ciency in investing in the overall effect, interaction effects, potential multicollinearity problems, and non-linear exposure-response relationship. Bayesian kernel machine regression (BKMR) model has been investigated in the environmental co-exposure factors to health effects (Bobb et al 2018;Hu et al 2021;Li et al 2021). It not only has a good identi cation effect on the major environmental factors that harm health but also can use the kernel function to estimate the relationship between the overall effect generated by joint exposure and the nonlinear exposure-response relationship and nd meaningful conclusions that are di cult to nd by GLM (Bellavia et al 2019;Bobb et al 2018;Bobb et al 2015).…”

Section: Introductionmentioning

confidence: 99%

The association between urine elements and fasting glucose levels in a community-based elderly people in Beijing

Liu

et al. 2022

Environ Sci Pollut Res

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Epidemiological studies have demonstrated that various kinds of urinary element concentrations were different between healthy, prediabetes, and diabetes patients. Meanwhile, many studies have explored the relationship between element concentration and fasting blood glucose (FBG), but the association between joint exposure to co-existing elements and FBG level has not been well understood. The study explored the associations of joint exposure to co-existing urinary elements with FBG level in a crosssectional design. 275 retired elderly people were recruited from Beijing, China. The questionnaire survey was conducted, and biological samples were collected. The generalized linear model (GLM) and twophase Bayesian kernel machine regression (BKMR) model were used to perform in-depth association analysis between urinary elements and FBG. The GLM analysis showed that Zn, Sr, and Cd were signi cantly correlated with the FBG level, under control potential confounding factors. The BKMR analysis demonstrated 8 elements (Zn, Se, Fe, Cr, Ni, Cd, Mn, and Al) had a higher in uence on FBG (Posterior inclusion probabilities >0.1). Further intensive analyses result of the BKMR model indicated that the overall estimated exposure of 8 elements was positively correlated with the FBG level and was statistically signi cant when all element concentrations were at their 65th percentile. Meanwhile, the BKMR analysis showed that Cd and Zn had a statistically signi cant association with FBG levels when other co-existing elements were controlled at different levels (25th, 50th or 75th percentile), respectively.The results of the GLM and BKMR model were inconsistent. The BKMR model could exibly calculate the joint exposure to co-existing elements, evaluate the possible interaction effects and nonlinear correlations. The meaningful conclusions were found that it was di cult to get by traditional methods. This study will provide methodological reference and experimental evidence for the association between joint exposure to co-existing elements and FBG in elderly people. Materials And Methods Research Design and Study PopulationA cross-sectional study design was implemented. The retired elderly people (aged above age 60 or more) recruited from the community-based in Beijing, in 2016. This study was approved by the Ethics Committee of the Institute of Basic Medical Sciences, Peking Union Medical College (Beijing, China), and all participants had signed informed consent before the interviews.Personal information was collected using a structured questionnaire through face-to-face communication by the investigator, including gender, age, smoking status, alcohol drinking status, and body mass index (BMI). Medical records were used to gather information on whether the subjects had diabetes and medication use related to blood sugar control.The vein blood (4 mL) was collected from each subject after overnight fasting and used to measure FBG. Blood samples were collected in vacuum tubes containing a thixotropic gel barrier (BD Vacutainer SST II, REF 367...

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Association of multiple metals with lipid markers against different exposure profiles: A population-based cross-sectional study in China

Cited by 39 publications

References 69 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

Processed Food and Atopic Dermatitis: A Pooled Analysis of Three Cross-Sectional Studies in Chinese Adults

The association between urine elements and fasting glucose levels in a community-based elderly people in Beijing

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