Evidence map›Paper›PMID 41959832›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Beyond Rurality: Individual Socioeconomic Status and Chronic Disease Prevalence.

Shivani Sabarish, Chung-Il Wi, Madison Beenken, Dave Watson, Christi A Patten, Tabetha A Brockman, Christine M Prissel, Philip Wheeler, Dan Kelleher, Gokhan Anil and 15 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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

25 authors.

Shivani SabarishDepartment of Pediatric and Adolescent Medicine, Mayo Clinic Rochester, MN.ORCID 0009-0003-8373-2185
Chung-Il WiDepartment of Pediatric and Adolescent Medicine, Mayo Clinic Rochester, MN.ORCID 0000-0001-8938-2997
Madison BeenkenPrecision Population Science Lab, Mayo Clinic Rochester, MN.
Dave WatsonPrecision Population Science Lab, Mayo Clinic Rochester, MN.
Christi A PattenDepartment of Psychiatry and Psychology, Mayo Clinic Health System, Eau Claire, Wisconsin.
Tabetha A BrockmanOffice for Community Engagement in Research, Mayo Clinic Rochester, MN.
Christine M PrisselDivision of Epidemiology, Mayo Clinic Rochester, MN.
Philip WheelerPrecision Population Science Lab, Mayo Clinic Rochester, MN.
Dan KelleherDepartment of Pediatric and Adolescent Medicine, Mayo Clinic Rochester, MN.
Gokhan AnilMankato Hospital, Administration, Mayo Clinic Health System.
Trent AndersonDepartment of Family Medicine, Mayo Clinic Health System.
Eunice Y ParkPrecision Population Science Lab, Mayo Clinic Rochester, MN.
Gurpreet SinghDivision of Cardiovascular Medicine, Mayo Clinic Health System.
Nahyr Lugo-FagundoDivision of Cardiology, Mayo Clinic Florida.
James F Howick VDivision of Cardiology, Mayo Clinic Florida.
Cheryl L Walker-McgillCarolina Complete Health, Charlotte, NC.
Brandon H HidakaDepartment of Family Medicine, Mayo Clinic Health System.
Pravesh SharmaDepartment of Psychiatry and Psychology, Mayo Clinic Health System, Eau Claire, Wisconsin.ORCID 0000-0002-9503-5016
Sagar B DuganiDivision of Hospital Internal Medicine, Mayo Clinic Rochester, MN.ORCID 0000-0001-7858-1317
Thanai PongdeeSection of Allergy and Immunology, Department of Medicine, Mayo Clinic Rochester, MN.
Jessica L SossoDepartment of Family Medicine, Mayo Clinic Health System.
Randy M FossDepartment of Family Medicine, Mayo Clinic Health System.
Prathibha VarkeyMayo Clinic Health System Administration.
Vesna D GarovicDivision of Nephrology and Hypertension, Mayo Clinic Rochester.
Young J JuhnDepartment of Pediatric and Adolescent Medicine, Mayo Clinic Rochester, MN.

Funding

Interdisciplinary Infrastructure for Aging Research: Rochester Epidemiology ProjectR33AG058738 · NIA · MAYO CLINIC ROCHESTER · PI LEBRASSEUR, NATHAN K, OLSON, JANET E · 2020 to 2022
$2.4M
Improving the Risk Adjustment Method for Quality Care Measures through Application of an Innovative Individual-Level Socioeconomic MeasureR21AG065639 · NIA · MAYO CLINIC ROCHESTER · PI JUHN, YOUNG J · 2021 to 2022
$437k
Individual Housing Data and Socioeconomic StatusR21HD051902 · NICHD · MAYO CLINIC ROCHESTER · PI JUHN, YOUNG J · 2006 to 2007
$327k
NIA NIH HHS R21 AG065639NIA NIH HHS R33 AG058738NICHD NIH HHS R21 HD051902
6 · The paper itself

Abstract

Importance: Rural-urban disparities in chronic disease prevalence are well established; however, the extent to which individual-level socioeconomic status (SES) contributes to these disparities remains unclear. Objective: To examine the associations of rurality and SES with the prevalence of five most burdensome chronic diseases among adults. Design: We conducted a retrospective cross-sectional study of adults across 27 Upper Midwest counties using the Expanded Rochester Epidemiology Project (E-REP) medical record data linkage system to evaluate associations between rurality, SES and chronic disease prevalence. Prevalence of clinically diagnosed asthma, diabetes, hypertension, coronary heart disease, and mood disorders was identified from International Classification of Diseases ICD9/10 codes over a five-year period (2014-2019). Setting: Population based. Participants: Adults over 18 years residing in the 27 E-REP counties, excluding those missing rural-urban residence status. Exposure: HOUSES index, an individual-level measure of SES, served as the primary measure, while rurality based on Rural Urban Commuting Area (RUCA) codes 4-10 was the secondary measure. Main Outcome: Prevalence of the five clinically diagnosed chronic diseases was identified using ICD9/10 codes from 2014-2019. Mixed effect logistic regression models were used and adjusted for demographics and general medical examination receipt, to assess rural-urban and SES differences for prevalence of each chronic disease. Results: Among 455,802 adults with available HOUSES index, 42.8% lived in rural areas, 53.8% were female and 87.4% were non-Hispanic White. In the unadjusted analysis, rural and urban populations showed comparable asthma and CHD prevalence, while mood disorders, hypertension, and diabetes were more common in urban areas. After adjusting for demographic factors and healthcare utilization, rural-urban differences were no longer statistically significant, whereas SES remained strongly associated with all diseases in a dose response manner (e.g., adjusted Odds Ratio for hypertension (ref: HOUSES index Q4): 1.14, 1.27, and 1.42 for HOUSES index Q3, Q2, and Q1, respectively). Conclusions and Relevance: Individual-level SES measured by the HOUSES index, was more strongly associated with chronic disease prevalence than rurality, supporting its integration into population health assessment and risk stratification.

Identifiers

PMID41959832
PMCPMC13060445

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.