Evidence map›Paper›PMID 39113389›Full record

ArticleJMIR public health and surveillance2024

Social Determinants of Health Phenotypes and Cardiometabolic Condition Prevalence Among Patients in a Large Academic Health System: Latent Class Analysis.

Carrie R Howell, Li Zhang, Olivio J Clay, Gareth Dutton, Trudi Horton, Michael J Mugavero, Andrea L Cherrington

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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.

Carrie R HowellDivision of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID 0000-0002-6554-6237
Li ZhangSchool of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID 0000-0003-4132-9382
Olivio J ClayAlzheimer's Disease Research Center, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID 0000-0002-7529-6120
Gareth DuttonDivision of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID 0000-0003-2960-6658
Trudi HortonDivision of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID 0009-0000-1277-7288
Michael J MugaveroDivision of Infectious Diseases, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID 0000-0001-6916-6701
Andrea L CherringtonDivision of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID 0000-0002-8321-3567

Funding

University of Alabama at Birmingham's Diabetes Research CenterP30DK079626 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Stuart J Frank · 2013 to 2026
$19.5M
Harnessing social determinant of health data to identify and engage high risk, socially vulnerable populations for diabetes preventionK01MD017270 · NIMHD · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI HOWELL, CARRIE R. · 2022 to 2025
$513k
American Heart Association-American Stroke Association 931540NIDDK NIH HHS P30 DK079626NIMHD NIH HHS K01 MD017270
6 · The paper itself

Abstract

Background: Adverse social determinants of health (SDoH) have been associated with cardiometabolic disease; however, disparities in cardiometabolic outcomes are rarely the result of a single risk factor. Objective: This study aimed to identify and characterize SDoH phenotypes based on patient-reported and neighborhood-level data from the institutional electronic medical record and evaluate the prevalence of diabetes, obesity, and other cardiometabolic diseases by phenotype status. Methods: Patient-reported SDoH were collected (January to December 2020) and neighborhood-level social vulnerability, neighborhood socioeconomic status, and rurality were linked via census tract to geocoded patient addresses. Diabetes status was coded in the electronic medical record using International Classification of Diseases codes; obesity was defined using measured BMI ≥30 kg/m2. Latent class analysis was used to identify clusters of SDoH (eg, phenotypes); we then examined differences in the prevalence of cardiometabolic conditions based on phenotype status using prevalence ratios (PRs). Results: Complete data were available for analysis for 2380 patients (mean age 53, SD 16 years; n=1405, 59% female; n=1198, 50% non-White). Roughly 8% (n=179) reported housing insecurity, 30% (n=710) reported resource needs (food, health care, or utilities), and 49% (n=1158) lived in a high-vulnerability census tract. We identified 3 patient SDoH phenotypes: (1) high social risk, defined largely by self-reported SDoH (n=217, 9%); (2) adverse neighborhood SDoH (n=1353, 56%), defined largely by adverse neighborhood-level measures; and (3) low social risk (n=810, 34%), defined as low individual- and neighborhood-level risks. Patients with an adverse neighborhood SDoH phenotype had higher prevalence of diagnosed type 2 diabetes (PR 1.19, 95% CI 1.06-1.33), hypertension (PR 1.14, 95% CI 1.02-1.27), peripheral vascular disease (PR 1.46, 95% CI 1.09-1.97), and heart failure (PR 1.46, 95% CI 1.20-1.79). Conclusions: Patients with the adverse neighborhood SDoH phenotype had higher prevalence of poor cardiometabolic conditions compared to phenotypes determined by individual-level characteristics, suggesting that neighborhood environment plays a role, even if individual measures of socioeconomic status are not suboptimal.

Indexed as

Cardiovascular DiseasesLatent Class AnalysisPhenotypeSocial Determinants of HealthAcademic Medical CentersAdultAgedFemaleHumansMaleMiddle AgedPrevalenceRisk Factorscardiometaboliccardiometabolic diseasecardiovascular diseasediabetesEHRelectronic health recordelectronic medical recordEMRlatent class analysisobeseobesityphenotypesrisk factorrisk factorssocial determinantsocial determinantssocial determinants of health

Identifiers

PMID39113389
PMCPMC11322797

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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.