Evidence map›Paper›PMID 42370284›Full record

ArticleResearch square2026

Associations Between Hair Heavy Metal Concentrations and Frailty in Mexican Adults: a Cross-Sectional Study.

Mario Ulises Pérez-Zepeda, Karla Julieta Esquivel-García, María José Pérez-Guzmán, Natalia Sánchez-Garrido, Miguel Germán Borda

Abstract readPreprint
In one paragraph

Article in Research square, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Mario Ulises Pérez-Zepeda
Karla Julieta Esquivel-García
María José Pérez-Guzmán
Natalia Sánchez-Garrido
Miguel Germán Borda

Funding

The Mexican Health and Aging Study - IIR01AG018016 · NIA · UNIVERSITY OF TEXAS MED BR GALVESTON · PI Rebeca Wong · 1999 to 2026
$22.6M
NIA NIH HHS R01 AG018016
6 · The paper itself

Abstract

Background: Exposure to heavy metals is increasingly recognized as a potential risk factors for health conditions and its accumulation across life has become of interes in older adults. Older adults may be susceptible because of accumulated exposure, reduced clearance, and greater vulnerability. Whether heavy metals contribute to frailty in community-dwelling adults, and whether their effect is modified by social vulnerability or sex, remains unclear. Methods: Cross-sectional analysis of 2018 wave of the Mexican Health and Aging Study (MHAS). Hair samples from 2,671 participants aged 18 to 99 years were analyzed (EPA method 6020B). Frailty was operationalized with a 60-item frailty index (FI). Associations between each log-metal and FI were estimated with crude and covariate-adjusted linear (OLS) regression with heteroscedasticity-consistent (HC3) standard errors, and with fractional-logit regression. False-discovery-rate correction was applied. Effect modification by SVI and by sex was assessed. Results: 2,590 participants had a valid FI. In crude analyses, most metals were inversely associated with the FI. After adjustment, only cobalt retained inversely associated, which did not survive FDR correction. No metals were significant in multivariable models. Inverse association of vanadium and copper with the FI was confined to participants with higher social vulnerability; at low SVI these slopes were null or positive. Conclusions: In this sample, individual hair concentrations of heavy metals were not robustly associated with frailty after adjustment. The results suggest that the relationship between trace metals and frailty may be small and highly context-dependent.

Indexed as

frailtyheavy metalsOlder adultssocial vulnerability

Identifiers

PMID42370284
PMCPMC13308406

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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.