Intersecting race/ethnicity and gender in physiological dysregulation profiles and associations with socioeconomic status among older adults in the United States.

Xiaoyan Zhang, Danielle M Krobath, Penias Tembo, Adolfo G Cuevas

Abstract read

In one paragraph

Article in SSM - population health, 2025. 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

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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

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

4 authors.

Xiaoyan ZhangDepartment of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, USA.

Danielle M KrobathDepartment of Epidemiology & Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, USA.

Penias TemboDepartment of Epidemiology & Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, USA.

Adolfo G CuevasDepartment of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Allostatic load, a cumulative indicator of physiological wear and tear resulting from chronic stress, is a robust predictor of disease and mortality risk. While prior research has documented racial/ethnic and gender variations in allostatic load, typically assessed by counting biomarkers at extreme levels, few studies have used latent class analysis (LCA) to examine multi-system physiological dysregulation or tested whether these patterns differ across the intersection of race/ethnicity and gender. This study analyzed data from 5743 Black and White adults aged 50 and older in the Health and Retirement Study to address this gap. Based on eight biomarkers representing metabolic, cardiovascular, and inflammatory systems, LCA identified four distinct dysregulation patterns that varied significantly by race and gender. The four classes included: (1) a

Indexed as

Allostatic loadHealth disparitiesIntersectionalityLatent class analysisPhysiological dysregulationRacial disparitiesWeathering hypothesis

Identifiers

PMID40469922

DOI10.1016/j.ssmph.2025.101812

PMCPMC12135385

What Socratic holds

Textmetadata

LicenceCC BY-NC-ND

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Registered trials

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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 Socratic graph.