Differential Clustering of Cardiovascular-Kidney-Metabolic Risk Factors by Sex: A Factor Analysis Approach

Certificate Output Instructions

For best output, select "Paper Size" as "A4" and "Margin" as "0" or "None".

To save or print to PDF, please select Print Destination > Save as PDF, enable Background Graphics under "More Settings", then click "Save".

Presented the abstract " "
(Abstract co-author(s): )

Back

E-Poster Presentation

During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center.

Preparing your E-Poster

Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.

E-Poster Submission Deadline

Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.

E-Poster Format Requirements

PDF file
Layout: Portrait (vertical orientation)
One page only (Dim A4: 210 x 297mm or PPT)
E-Poster can be prepared in PowerPoint (one (1) PowerPoint slide) but must be saved and submitted as PDF file.
File Size: Maximum file size is 2 Megabytes (2 MB)
No hyperlinks, animated images, animations, and slide transitions
Language: English
Include your abstract number
E-posters can include QR codes, tables and photos

E-Poster

https://storage.unitedwebnetwork.com/files/1099/5adfa50692001342ace6737223bac340.pdf

Abstract Title *

Differential Clustering of Cardiovascular-Kidney-Metabolic Risk Factors by Sex: A Factor Analysis Approach

Please follow the instructions below to input your abstract title.

Abstract titles should be brief and reflect the content of the abstract.

The title will not be accepted if it exceeds 25 words.
Type in CAPITAL LETTERS.
Lowercase may be used for abbreviations only, for example, mRNA.

Co-author 1

Jennifer Bragg-Gresham jennb@med.umich.edu University of Michigan Internal Medicine, Nephrology Ann Arbor, MI United States *

Co-author 2

Ana Laura Licon alicon@med.umich.edu University of Michigan Internal Medicine, Neprhology Ann Arbor, MI United States -

Co-author 3

Rajiv Saran rsaran@med.umich.edu University of Michigan Internal Medicine, Nephrology Ann Arbor, MI United States -

Co-author 4

Co-author 5

Co-author 6

Co-author 7

Co-author 8

Co-author 9

Co-author 10

Co-author 11

Co-author 12

Co-author 13

Co-author 14

Co-author 15

Introduction

Significant mortality risk differences have been observed by Cardiovascular-Kidney-Metabolic (CKM) Syndrome stages between males and females, suggesting a greater increase in hazards of mortality by higher CKM stage for females. We investigated whether this may be due to differential clustering (and therefore impact) of components within each CKM stage, by sex.

Methods

Examining 20 years of National U.S. data (National Health and Nutrition Survey [NHANES] 2001-2020), we analyzed data from 50,091 non-pregnant adults aged 20 year and older with complete data for CKM syndrome risk factors. Principal components factor analysis was employed to identify underlying, unobservable constructs that may explain the relationships and shared variance among CKM syndrome components. Stage 1 CKM factors included: obesity, large waist circumference, or prediabetes; Stage 2 included: diabetes, hypertension, hypertriglyceridemia, metabolic syndrome, or moderate to high-risk chronic kidney disease (CKD); Stage 3 included: high risk of cardiovascular outcomes (10-year PREVENT CVD risk ≥ 20%); and Stage 4 included diagnosed congestive heart failure, cardiovascular disease, myocardial infarction, coronary heart disease, stroke, or very high risk CKD.

Results

The average age of the sample was 50 years, with 49.7% males. Factor loadings for the principal component are displayed in the table, showing that risk factors cluster differently by sex. Male adults show high loadings for high predicted cardiovascular risk, as well as all diagnosed cardiovascular conditions and metabolic syndrome. The high loadings for females were seen among metabolic factors, including metabolic syndrome and large waist, along with hypertension and diagnosed cardiovascular disease.

Conclusion

The observed differential clustering of CKM components by sex suggests that the more clinically manifested/severe CKM components are clustered at higher levels of loading among males as compared with females. Further work is needed to examine the implications of this finding as it relates to population level risk of adverse CKM outcomes by sex, and as it relates to individual-level risk and disease progression rates, given similar CKM components profiles by sex.

Kewords