Evidence map›Paper›PMID 38978670›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Social Vulnerability and Biological Aging in New York City: An Electronic Health Records-Based Study.

Pablo Knobel, Elena Colicino, Itai Klog, Rachel Litke, Kevin Lane, Alex Federman, Charles Mobbs, Maayan Yitshak Sade

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. 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

5 · Who and what money

Authors and funding

8 authors.

Funding

Delay of Alzheimer's phenotypes by interventions that increase lifespanR01AG062303 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI MOBBS, CHARLES V · 2018 to 2022
$2.1M
NIA NIH HHS R01 AG062303
6 · The paper itself

Abstract

Chronological age is not an accurate predictor of morbidity and mortality risk, as individuals' aging processes are diverse. Phenotypic age acceleration (PhenoAgeAccel) is a validated biological age measure incorporating chronological age and biomarkers from blood samples commonly used in clinical practice that can better reflect aging-related morbidity and mortality risk. The heterogeneity of age-related decline is not random, as environmental exposures can promote or impede healthy aging. Social Vulnerability Index (SVI) is a composite index accounting for different facets of the social, economic, and demographic environment grouped into four themes: socioeconomic status, household composition and disability, minority status and language, and housing and transportation. We aim to assess the concurrent and combined associations of the four SVI themes on PhenoAgeAccel and the differential effects on disadvantaged groups. We use electronic health records data from 31,913 patients from the Mount Sinai Health System (116,952 person-years) and calculate PhenoAge for years with available laboratory results (2011-2022). PhenoAge is calculated as a weighted linear combination of lab results and PhenoAgeAccel is the differential between PhenoAge and chronological age. A decile increase in the mixture of SVI dimensions was associated with an increase of 0.23 years (95% CI: 0.21, 0.25) in PhenoAgeAccel. The socioeconomic status dimension was the main driver of the association, accounting for 61% of the weight. Interaction models revealed a more substantial detrimental association for women and racial and ethnic minorities with differences in leading SVI themes. These findings suggest that neighborhood-level social vulnerability increases the biological age of its residents, increasing morbidity and mortality risks. Socioeconomic status has the larger detrimental role amongst the different facets of social environment.

Identifiers

PMID38978670
PMCPMC11230307

What OpenQuestion holds

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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 OpenQuestion graph.