Evidence map›Paper›PMID 40434610›Full record

ArticleCardiovascular toxicology2025

Associations Between Metal-Metal Interaction and the Risk of Hypertension: A Case-Control Study in Chinese Community-Dwelling Elderly.

Meiyan Li, Yihong Di, Siyu Duan, Rui Wang, Pei He, Zhongyuan Zhang, Yuqing Dai, Zhuoheng Shen, Yue Chen, Huifang Yang and 3 more

Abstract read
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Article in Cardiovascular toxicology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Meiyan Li *School of Public Health, Department of Medical Record and Statistics, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, Ningxia, 750004, People's Republic of China.
Yihong Di *School of Public Health, Department of Medical Record and Statistics, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, Ningxia, 750004, People's Republic of China.
Siyu Duan *School of Public Health, Department of Medical Record and Statistics, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, Ningxia, 750004, People's Republic of China.
Rui WangSchool of Public Health, Department of Medical Record and Statistics, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, Ningxia, 750004, People's Republic of China.
Pei HeSchool of Public Health, Department of Medical Record and Statistics, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, Ningxia, 750004, People's Republic of China.
Zhongyuan ZhangSchool of Public Health, Department of Medical Record and Statistics, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, Ningxia, 750004, People's Republic of China.
Yuqing DaiSchool of Public Health, Department of Medical Record and Statistics, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, Ningxia, 750004, People's Republic of China.
Zhuoheng ShenSchool of Public Health, Department of Medical Record and Statistics, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, Ningxia, 750004, People's Republic of China.
Yue ChenSchool of Public Health, Department of Medical Record and Statistics, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, Ningxia, 750004, People's Republic of China.
Huifang YangSchool of Public Health, Department of Medical Record and Statistics, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, Ningxia, 750004, People's Republic of China.
Xiaoyu LiSchool of Public Health, Department of Medical Record and Statistics, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, Ningxia, 750004, People's Republic of China. lxyandpp@foxmail.com.
Jian SunSchool of Public Health, Department of Medical Record and Statistics, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, Ningxia, 750004, People's Republic of China. 20180016@nxmu.edu.cn.
Rui ZhangSchool of Public Health, Department of Medical Record and Statistics, General Hospital of Ningxia Medical University, Ningxia Medical University, Yinchuan, Ningxia, 750004, People's Republic of China. z_zhangrui@163.com.

Funding

the Health Research Project of Ningxia Hui Autonomous Region (2024-NWZC-A030)the Key Research and Development Program Project of Ningxia Hui Autonomous Region (2024FRD05106 and 2023BEG02028)the "Light of the West" Talent Training Plan Project of Chinese Academy of Sciences (XAB2022YW18)the National Natural Science Foundation of China U22A20360the Natural Science Foundation Project of Ningxia, China (2024AAC03772 and 2022AAC05028)
6 · The paper itself

Abstract

Fewer studies have focused on the interaction of metal mixtures with hypertension, especially in Chinese community-dwelling elderly. In addition, the relationship between metal exposure and hypertension may be attenuated or strengthened by the presence of multiple chronic diseases in older adults. In this study, inductively coupled plasma mass spectrometry was used to detect the levels of 12 metals in the urine of 693 elderly people in the Yinchuan community. We employed Directed Acyclic Graphs (DAG) to select variables for adjustment in the model. Conditional logistic regression model and restricted cubic spline analysis (RCS) were used to explore the association between and dose-response relationship between metal concentrations in urine and hypertension. Quantile g-computation and Bayesian kernel machine regression (BKMR) to analyze the association of individual urinary metal concentrations and metal mixtures with hypertension risk. Urinary concentrations of 12 metals (vanadium, iron, cobalt, zinc, copper, arsenic, selenium, molybdenum, cadmium, tellurium, thallium, and lead) were higher in the hypertension group than in the non-hypertension group. In the RCS models, the urinary concentrations of vanadium, iron, and lead showed a linear dose-response relationship with hypertension risk. Quantile g-computation analyses showed cadmium contributed the largest positive weights. The BKMR models showed that the positive slope of lead became steep at higher concentrations of urinary iron when the other three metals were at the median. We found that exposure to metal mixtures was associated with the risk of hypertension and a significant positive interaction between urinary iron and lead. Further research is needed to confirm our findings and elucidate the underlying mechanisms of the interaction between metals and hypertension.

Indexed as

Blood PressureEnvironmental ExposureEnvironmental PollutantsHypertensionIndependent LivingMetalsAgedAged, 80 and overAge FactorsBiomarkersCase-Control StudiesChinaEast Asian PeopleFemaleHumansMaleBiomarkersEnvironmental PollutantsMetalsBayesian kernel machine regressionHypertensionInteraction effectMetal mixturesQuantile g-computation

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.