Association Between Metabolic Syndrome Components, Clinical Characteristics, and Telomere Length: Factor Analysis of Mixed Data Based Cluster Analysis of LIPIDOGEN2015 Cross-Sectional Study

Q: What type of study is this?

This is a Cross-Sectional Study study.

Tadeusz Osadnik; Maciej Banach; Anna Goc; Ewa Boniewska‐Bernacka; Anna Pańczyszyn; Marcin Goławski; Martyna Fronczek; Joanna Katarzyna Strzelczyk; Mateusz Lejawa; Marek Gierlotka; Kamila Osadnik; Nikodem Baron; Karol Krystek; Agnieszka Gach; Tomasz Czapor; Natalia Pawlas; Francesco Paneni; Jacek Jerzy Jozwiak

doi:10.1007/s40292-025-00753-6

Key Points

To explore the relationship between components of metabolic syndrome and telomere length through factor analysis.
Cross-sectional study using the LIPIDOGEN2015 dataset
Factor analysis to examine mixed data
Cluster analysis for clinical characteristics
Finds an inverse relationship between clinical characteristics and telomere length
Highlights the role of cardiovascular risk factors in cellular aging
Demonstrates potential metabolic disturbances affecting telomere length

Implication

Cross-sectional study shows inverse relationship between metabolic syndrome components and telomere length, suggesting implications for aging.

Abstract

The pattern of clinical characteristics marked by classical cardiovascular risk factors including components of MetS, is inversely related to telomere length, underlining the potential role of metabolic disturbances in cellular aging.

Discussion

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Cite This Study

Osadnik et al. (2025) studied this question.

synapsesocial.com/papers/69401d732d562116f28f9520 https://doi.org/10.1007/s40292-025-00753-6

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Association Between Metabolic Syndrome Components, Clinical Characteristics, and Telomere Length: Factor Analysis of Mixed Data Based Cluster Analysis of LIPIDOGEN2015 Cross-Sectional Study

Key Points

Implication

Abstract

Discussion

Cite This Study

Association Between Metabolic Syndrome Components, Clinical Characteristics, and Telomere Length: Factor Analysis of Mixed Data Based Cluster Analysis of LIPIDOGEN2015 Cross-Sectional Study

Key Points

Implication

Abstract

Discussion

Cite This Study

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