Evidence map›Paper›PMID 39252793›Full record

ArticleObesity pillars2024

Prevalence of cardiovascular events among transgender adults with obesity: A population-based analysis.

Adhvithi Pingili, Roopeessh Vempati, Madhusha Vemula, Mohit Lakkimsetti, Hasmitha Madhavaram, Athmananda Nanjundappa, Jyotsna Gummadi, Sandeep Singh, Rupak Desai, Praveena Sunkara

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Article in Obesity pillars, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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10 authors.

Adhvithi PingiliDepartment of Internal Medicine, MedStar Union Memorial Hospital, Baltimore, MD, USA.
Roopeessh VempatiDepartment of Internal Medicine, Trinity Health Oakland Hospital, Pontiac, MI, USA.
Madhusha VemulaDepartment of General Medicine, Malla Reddy Institute of Medical Sciences, Hyderabad, Telangana, India.
Mohit LakkimsettiDepartment of General Medicine, Mamata Medical College, Khammam, Telangana, India.
Hasmitha MadhavaramDepartment of Internal Medicine, Morristown Medical Centre, Morristown, NJ, USA.
Athmananda NanjundappaDepartment of Medicine, MedStar Franklin Square Medical Centre, Baltimore, MD, USA.
Jyotsna GummadiDepartment of Medicine, MedStar Franklin Square Medical Centre, Baltimore, MD, USA.
Sandeep SinghUniversity Hospitals of North Midlands MHS Trust, Stroke-on-Trent, UK.
Rupak DesaiIndependent Researcher, Outcomes Research, Atlanta, GA, USA.
Praveena SunkaraDepartment of Internal Medicine, Passion Health Primary Care, Denton, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Although obesity and its impact on cardiovascular (CV) events have been extensively studied in the cisgender population, little is known about its impact on CV events in transgender individuals. Our study aimed to establish the prevalence of obesity and CV events in transgender adults. Methods: We conducted a retrospective cohort comparative study utilizing the U.S. National Inpatient Sample 2020 database. We identified admissions of transgender patients with administrative codes. Later, these patients were divided into obesity and non-obesity cohorts. Multivariable regression analysis was then performed for in-hospital all-cause mortality, acute myocardial infarction, acute ischemic stroke, cardiac arrest, pulmonary embolism and, major adverse cardiovascular and cerebrovascular events (MACCE). Results: In 2020, 19,345 transgender patients were admitted; 16,390 (84.7 %) had no obesity, and 2,955 (15.3 %) had obesity. The median age was 31 years in the non-obesity cohort and 37 years in the obesity cohort. Transgender men comprised 54.5 % of the non-obesity cohort and 47.9 % of the obesity cohort. Common baseline conditions in the non-obesity and obesity cohorts, respectively, included hypertension (20.7 % vs. 43.5 %), diabetes (10.2 % vs. 32.5 %), chronic pulmonary disease (18.9 % vs. 27.7 %), and hyperlipidemia (11.5 % vs. 25 %). MACCE was observed in 2.3 % of the non-obesity cohort compared to 5.4 % in the obesity cohort, and cardiac arrest occurred in 0.2 % of the non-obesity cohort versus 1.2 % in the obesity cohort. A statistically significant association was found in MACCE [odds ratio (OR) 2.1, 95 % confidence interval (CI) 1.24-3.55, p = 0.006] and cardiac arrest [OR 3.92, 95 % CI 1.11-12.63, p = 0.022] among transgender patients with obesity. Conclusion: We observed increased odds of MACCE and cardiac arrest in transgender patients with obesity, possibly due to obesity and CV risk factors like hypertension, diabetes, and hyperlipidemia. Further large-scale comparative studies are needed to better understand obesity's impact on CV outcomes in the transgender population.

Indexed as

Cardiovascular risk factorsGender-affirming careMajor adverse cardiac and cerebrovascular eventsObesityTransgender

Identifiers

PMID39252793
PMCPMC11381998

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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.