Evidence map›Paper›PMID 41348357›Full record

ArticleJAMA network open2025

Climate Vulnerability Index and Incident Type 2 Diabetes in a Large Integrated Health Care System.

Jad Ardakani, Izza Shahid, Rakesh Gullapelli, Lindsey Russo, Budhaditya Bose, Juan C Nicolas, Zulqarnain Javed, Weichuan Dong, Jay E Maddock, Arnab K Ghosh and 6 more

Abstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

16 authors.

Jad ArdakaniCenter for Cardiovascular Computational and Precision Health (C3PH), Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, Houston, Texas.
Izza ShahidCenter for Cardiovascular Computational and Precision Health (C3PH), Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, Houston, Texas.
Rakesh GullapelliCenter for Cardiovascular Computational and Precision Health (C3PH), Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, Houston, Texas.
Lindsey RussoDepartment of Medicine, Weill Cornell Medicine, New York, New York.
Budhaditya BoseCenter for Cardiovascular Computational and Precision Health (C3PH), Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, Houston, Texas.
Juan C NicolasCenter for Health Data Science & Analytics, Houston Methodist, Houston, Texas.
Zulqarnain JavedCenter for Cardiovascular Computational and Precision Health (C3PH), Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, Houston, Texas.
Weichuan DongCenter for Cardiovascular Computational and Precision Health (C3PH), Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, Houston, Texas.
Jay E MaddockCenter for Health & Nature, Houston, Texas.
Arnab K GhoshDepartment of Medicine, Weill Cornell Medicine, New York, New York.
Grace Tee LewisEnvironmental Defense Fund, Houston, Texas.
Stephen JonesCenter for Health Data Science & Analytics, Houston Methodist, Houston, Texas.
Archana SadhuDepartment of Medicine, Houston Methodist Hospital, Houston, Texas.
Sanjay RajagopalanHarrington Heart and Vascular Institute, University Hospitals, Cleveland, Ohio.
Khurram NasirCenter for Cardiovascular Computational and Precision Health (C3PH), Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, Houston, Texas.
Sadeer Al-KindiCenter for Cardiovascular Computational and Precision Health (C3PH), Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, Houston, Texas.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Place-based Climate Vulnerability Index (CVI) may shape metabolic risk through environmental and socioeconomic stressors, but its association with incident type 2 diabetes (T2D) is not well characterized. Objective: To determine whether residence in communities with higher CVI is associated with risk of incident T2D. Design, Setting, and Participants: This retrospective cohort study used data from the Houston Methodist Learning Health System Registry, a large integrated health system that primarily serves Greater Houston, Texas. Participants included adults aged 18 years or older without T2D at baseline and with at least 1 outpatient encounter and at least 1 subsequent health care encounter from June 2016 to August 2023. Data analysis was conducted September 2025. Exposures: US census tract-level CVI categorized into quartiles (Q1-Q4). Main Outcomes and Measures: The primary outcome was incident T2D identified by International Statistical Classification of Diseases, Tenth Revision, Clinical Modification codes, antihyperglycemic prescriptions, or hemoglobin A1c 6.5% or higher. Primary measures were incidence rates (cases per 100 person-years) and adjusted hazard ratios (HRs) with 95% CIs comparing Q4 vs Q1 from Cox models adjusted for demographics, insurance, cardiometabolic risk factors, and baseline hemoglobin A1c. Results: Among 1 003 526 participants (mean [SD] age, 50.9 [18.4] years; 605 829 women [60.4%]; 132 451 African American or Black [13.2%]; 71 408 Asian [7.1%]; 156 989 Hispanic or Latinx [15.6%]; 566 632 White [56.5%]; 35 565 other [3.5%]; 42 942 unknown or not reported [4.3%]), 40 152 developed T2D over 2.1 million person-years (overall incidence, 1.88 cases per 100 person-years). Diabetes incidence was higher among participants residing in Q4 vs Q1 CVI areas (2.66 vs 1.48 cases per 100 person-years), and the 7-year risk was 14.1% for Q4 participants vs 8.6% for Q1 participants. Residence in Q4 vs Q1 CVI was associated with higher T2D risk (HR, 1.23; 95% CI, 1.11-1.36), a statistically significant difference. Conclusions and Relevance: In this cohort study of 1 003 526 adults, higher community CVI was associated with greater risk of incident T2D independently of traditional risk factors. Linking geocoded CVI to electronic health records may support targeted prevention, risk stratification, and population health planning.

Indexed as

ClimateDiabetes Mellitus, Type 2AdultAgedDelivery of Health Care, IntegratedFemaleHumansIncidenceMaleMiddle AgedRetrospective StudiesRisk FactorsTexas

Identifiers

PMID41348357
PMCPMC12681038

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.