Evidence map›Paper›PMID 36401593›Full record

ArticleHealth services research2023

The social vulnerability metric (SVM) as a new tool for public health.

Loren Saulsberry, Ankur Bhargava, Sharon Zeng, Jason B Gibbons, Cody Brannan, Diane S Lauderdale, Robert D Gibbons

Abstract read
In one paragraph

Article in Health services research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Social vulnerability, access to care, and outcomes in hemophilia.Blood vessels, thrombosis & hemostasis · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Median Income and Clinical Outcomes of Hospitalized Persons With COVID-19 at an Urban Veterans Affairs Medical Center.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2026
    Article
  8. The association of place-based disadvantage and access to deceased donor heart transplantation.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

7 authors.

Loren SaulsberryDepartment of Public Health Sciences, The University of Chicago, Chicago, Illinois, USA.ORCID https://orcid.org/0000-0003-0325-2329
Ankur BhargavaDepartment of Pediatrics, The University of Chicago, Chicago, Illinois, USA.
Sharon ZengPritzker School of Medicine, The University of Chicago, Chicago, Illinois, USA.
Jason B GibbonsDepartment of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Cody BrannanCenter for Health Statistics, The University of Chicago, Chicago, Illinois, USA.
Diane S LauderdaleDepartment of Public Health Sciences, The University of Chicago, Chicago, Illinois, USA.
Robert D GibbonsDepartment of Public Health Sciences, The University of Chicago, Chicago, Illinois, USA.

Funding

Health Equity and Risk Communication in PharmacogenomicsK08HG011505 · NHGRI · UNIVERSITY OF CHICAGO · PI SAULSBERRY, LOREN · 2020 to 2024
$836k
Adaptive Testing of Cognitive Function based on multi-dimensional Item Response TheoryR56AG066127 · NIA · UNIVERSITY OF CHICAGO · PI GIBBONS, ROBERT D · 2019 to 2019
$836k
NHGRI NIH HHS K08 HG011505NIA NIH HHS R56 AG066127
6 · The paper itself

Abstract

objectiveTo derive and validate a new ecological measure of the social determinants of health (SDoH), calculable at the zip code or county level. DATA SOURCES AND STUDY

settingThe most recent releases of secondary, publicly available data were collected from national U.S. health agencies as well as state and city public health departments. STUDY

designThe Social Vulnerability Metric (SVM) was constructed from U.S. zip-code level measures (2018) from survey data using multidimensional Item Response Theory and validated using outcomes including all-cause mortality (2016), COVID-19 vaccination (2021), and emergency department visits for asthma (2018). The SVM was also compared with the existing Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) to determine convergent validity and differential predictive validity. DATA COLLECTION/EXTRACTION

methodsThe data were collected directly from published files available to the public online from national U.S. health agencies as well as state and city public health departments. PRINCIPAL

findingsThe correlation between SVM scores and national age-adjusted county all-cause mortality was r = 0.68. This correlation demonstrated the SVM's robust validity and outperformed the SVI with an almost four-fold increase in explained variance (46% vs. 12%). The SVM was also highly correlated (r ≥ 0.60) to zip-code level health outcomes for the state of California and city of Chicago.

conclusionsThe SVM offers a measurement tool improving upon the performance of existing SDoH composite measures and has broad applicability to public health that may help in directing future policies and interventions. The SVM provides a single measure of SDoH that better quantifies associations with health outcomes.

Indexed as

COVID-19Social VulnerabilityCOVID-19 VaccinesHumansPublic HealthSupport Vector MachineCOVID-19 Vaccinesbiostatistical methodsdeterminants of health/population health/socioeconomic causes of healthhealth care disparitieshealth equityhealth policysocial determinants of health

Identifiers

PMID36401593
PMCPMC10315381

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.