Association between experience of insulin resistance and long-term cardiovascular disease risk: findings from the Korean Genome and Epidemiology Study (KOGES)

Jong Hee Lee, Hye Sun Lee, Soyoung Jeon, Yong Jae Lee, Byoungjin Park, Jun Hyuk Lee, Yu Jin Kwon

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1 Citation (Scopus)

Abstract

Purpose: Although the correlation between insulin resistance (IR) and cardiovascular disease (CVD) risk is well-established, the impact of changes in IR status over time has received little attention. This study aimed to investigate the effect of IR on CVD risk in a large prospective cohort of middle-aged Korean adults. Methods: We assessed 3597 participants from the Korean Genome and Epidemiology Study (KoGES). Participants were categorized as having IR if their HOMA-IR was ≥2.5 at least once during the exposure period. Multivariate Cox proportional hazards regression analysis was performed to assess hazard ratios (HRs) with 95% CIs for incident CVD after adjusting for confounders. Results: Among a total of 3597 participants, 2259 did not have IR and 1138 had IR. The cumulative incidence rate of CVD in the IR group was significantly higher than that in the non-IR group (log-rank test, p = 0.015). Compared to the non-IR group, the HR and 95% CI for incident CVD in the IR group was 1.40 (1.07–1.83) in the unadjusted model. The presence of IR during the exposure period was significantly associated with a higher risk of incident CVD after adjusting for age, sex, body mass index, diabetes, hypertension, dyslipidemia, C-reactive protein, physical activity, alcohol intake, and smoking status (HR = 1.37; 95% CI: 1.01–1.84). Conclusion: Individuals who have experienced IR have a consistently higher likelihood of developing CVD than those who have never had IR. More intensive efforts should be made to prevent IR in middle-aged and older adults.

Original languageEnglish
Pages (from-to)481-489
Number of pages9
JournalEndocrine
Volume84
Issue number2
DOIs
Publication statusPublished - 2024 May

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.

All Science Journal Classification (ASJC) codes

  • Endocrinology, Diabetes and Metabolism
  • Endocrinology

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