Evidence map›Paper›PMID 38693478›Full record

ArticleBMC geriatrics2024

Association between plasma metal exposure and health span in very elderly adults: a prospective cohort study with mixture statistical approach.

Xiaoying Ye, Tingting Xu, Le Yang, Xiangju Hu, Xiaowei Xie, Guohui Lan, Xiaoli Lu, Zelin Huang, Tinggui Wang, Jieyu Wu and 5 more

Open access · goldAbstract read
In one paragraph

Article in BMC geriatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.6field-weighted citation impact, top 19% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

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

15 authors at 4 institutions in 1 country.

Xiaoying Ye *Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
Tingting Xu *Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
Le Yang *Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
Xiangju Hu *Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
Xiaowei XieThe First Clinical Medical School, Shanxi Medical University, Taiyuan, China.
Guohui LanDepartment of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
Xiaoli LuDepartment of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
Zelin HuangDepartment of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
Tinggui WangDepartment of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
Jieyu WuDepartment of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
Jieli LanClinical Research Unit, The Second Affiliated Hospital, Fujian Medical University, Quanzhou, China.
Qian ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
Zhiying ZhanDepartment of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
Yansong GuoDepartment of Cardiology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China. ysguo1234@126.com.
Xiaoxu XieDepartment of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China. xxx@fjmu.edu.cn.
Fujian Medical University · CNFujian Provincial Hospital · CNSecond Affiliated Hospital of Fujian Medical University · CNShanxi Medical University · CN

Funding

National Key Clinical Specialty Construction Project of China Cardiovascular Medicine 2021National Natural Science Foundation of China 82203989Natural Science Foundation of Fujian Province 2021J01729
6 · The paper itself

Abstract

backgroundMetals have been linked to a diverse spectrum of age-related diseases; however, the effects of metal exposure on health span remains largely unknown. This cohort study aims to determine the association between plasma metal and health span in elder adults aged ≥ 90 years.

methodsThe plasma concentrations of seven metals were measured at baseline in 300 elder adults. The end of the health span (EHS) was identified as the occurrence of one of eight major morbidities or mortality events. We used Cox regression to assess hazard ratios (HR). The combined effects of multiple metal mixtures were estimated using grouped-weighted quantile sum (GWQS), quantile g-computation (Q-gcomp), and Bayesian kernel machine regression (BKMR) methods.

resultsThe estimated HR for EHS with an inter-quartile range (IQR) increment for selenium (Se) was 0.826 (95% confidence interval [CI]: 0.737-0.926); magnesium (Mg), 0.806 (95% CI: 0.691-0.941); iron (Fe), 0.756 (95% CI: 0.623-0.917), and copper (Cu), 0.856 (95% CI: 0.750-0.976). The P for trend of Se, Mg, and Fe were all < 0.05. In the mixture analyses, Q-gcomp showed a negative correlation with EHS (P = 0.904), with the sum of the negative coefficients being -0.211.

conclusionHigher plasma Se, Mg, and Fe reduced the risk of premature end of health span, suggesting that essential metal elements played a role in health maintenance in elder adults.

Indexed as

MetalsAged, 80 and overCohort StudiesEnvironmental ExposureFemaleHumansLongevityMaleProspective StudiesSeleniumMetalsSeleniumAgingHealth spanMagnesiumMixturesPlasma metalSelenium

Identifiers

PMID38693478
PMCPMC11064295
OpenAlexW4396546237

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.