Evidence map›Paper›PMID 41510216›Full record

ReviewGeoHealth2026

Spatiotemporal Approaches to Assess the Association of Environmental Risk Factors With Cardiovascular Diseases: A Scoping Review.

Vishal Singh, Susanna Cramb, Jialu Wang, Wenbiao Hu, Javier Cortes-Ramirez

Abstract readReview
In one paragraph

Review in GeoHealth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

5 authors.

Vishal SinghSchool of Public Health and Social Work Queensland University of Technology Kelvin Grove QLD Australia.ORCID https://orcid.org/0000-0003-3364-6708
Susanna CrambSchool of Public Health and Social Work Queensland University of Technology Kelvin Grove QLD Australia.ORCID https://orcid.org/0000-0001-9041-9531
Jialu WangSchool of Public Health and Social Work Queensland University of Technology Kelvin Grove QLD Australia.ORCID https://orcid.org/0000-0001-6763-2107
Wenbiao HuSchool of Public Health and Social Work Queensland University of Technology Kelvin Grove QLD Australia.ORCID https://orcid.org/0000-0001-6422-9240
Javier Cortes-RamirezSchool of Public Health and Social Work Queensland University of Technology Kelvin Grove QLD Australia.ORCID https://orcid.org/0000-0002-5876-165X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular diseases (CVDs) remain a leading cause of mortality globally, with environmental risk factors playing a significant role in their prevalence. This review aims to critically evaluate the current methodologies employed in spatiotemporal analyses of CVDs and provides recommendations to enhance the accuracy and practical application of these models. A systematic search of the literature was conducted using Scopus, PubMed, and Embase databases. Studies were selected based on their use of spatiotemporal models to assess the relationship between environmental factors and CVDs. We evaluated the methodological quality of included studies using the Spatial Methodology Appraisal of Research Tool (SMART). Significant challenges were noted, including the need for higher spatial resolution data sets and improved methods for addressing the modifiable areal and temporal unit problems and ecological bias. Additionally, the visualization of spatiotemporal data remains underutilized and underdeveloped, limiting the practical utility of the findings. We also discuss combining parameters to form an indicator that better represents environmental conditions, as well as cases where ground, satellite, or modeled data products are suitable. These recommendations could extend to other acquired chronic diseases and their relationship with environmental risk factors to improve the utility of spatiotemporal models. While spatiotemporal modeling holds considerable promise in understanding and mitigating CVD risks associated with environmental factors, appropriate data selection, addressing methodological pitfalls and reporting spatial and temporal model outcomes are necessary to enhance their reliability and impact.

Indexed as

air pollutiondisease mappingsmall‐area estimationspatial epidemiologyspatiotemporal data visualizationtemperature

Identifiers

PMID41510216
PMCPMC12775574

What Socratic 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 Socratic graph.