Evidence map›Paper›PMID 40893949›Full record

ArticleJournal of the Endocrine Society2025

Identifying Geographic Cold Spots of PCOS Diagnosis in Texas: A Spatial Analysis of Underdiagnosis and Rural Disparities.

Ryan Ramphul, Geethika Yalavarthy, Jooyeon Lee

Abstract read
In one paragraph

Article in Journal of the Endocrine Society, 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

5 · Who and what money

Authors and funding

3 authors.

Ryan RamphulDepartment of Epidemiology, UTHealth Houston-School of Public Health, Houston, TX 77030, USA.ORCID https://orcid.org/0000-0001-9415-223X
Geethika YalavarthyDepartment of Epidemiology, UTHealth Houston-School of Public Health, Houston, TX 77030, USA.ORCID https://orcid.org/0000-0002-3714-4863
Jooyeon LeeDepartment of Biostatistics & Data Science, UTHealth Houston-School of Public Health, Houston, TX 77030, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Context: Polycystic ovary syndrome (PCOS) is a common yet underdiagnosed endocrine disorder with substantial reproductive and metabolic consequences. Although disparities in PCOS care have been documented, few studies have employed spatial methods to identify areas of potential underdiagnosis. Objective: This study uses geospatial analysis to detect cold spots of PCOS clinical encounters across Texas and investigates neighborhood characteristics associated with these areas. Methods: We analyzed inpatient and outpatient encounter data from the Texas Public Use Data File (PUDF) between 2018 and 2024 to identify PCOS-related visits (International Classification of Diseases, revision 10: E28.2). ZIP code tabulation area (ZCTA)-level PCOS encounter prevalence was calculated per 1000 females and stabilized using empirical Bayes smoothing to account for rate instability. The Anselin local Moran's I statistic was used to detect spatial clusters. ZCTAs with statistically significant low-prevalence clusters (cold spots) were identified. Logistic regression assessed associations between cold spot status and neighborhood-level variables, including rural-urban commuting area codes, socioeconomic indicators, and health-related factors. Results: Cold spots were concentrated in rural and periurban areas, suggesting potential underdiagnosis in communities with limited health-care access. This highlights the need for targeted public health interventions, including expanded provider training and diagnostic outreach in rural settings. Conclusion: Significant spatial disparities in PCOS diagnosis suggest differential health-care access, diagnostic practices, or population health behaviors across the state. Targeted health interventions in rural communities may improve PCOS recognition and care. Further research is needed to explore the role of infrastructure and provider practices in causing these geographic disparities.

Indexed as

geospatial analysishealth disparitiespolycystic ovary syndromerural healthTexasunderdiagnosis

Identifiers

PMID40893949
PMCPMC12391751

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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.