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February 6, 2026European Heart Journal0 citations

Associations of serum insulin level trajectories with cardiovascular disease incidence and mortality: a two-decade population-based study

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FEFarzad EsmaeiliResearch Institute for Endocrine SciencesMTMaryam TohidiResearch Institute for Endocrine SciencesFAF AziziShahid Beheshti University of Medical Sciences

Key Points

  • This research aims to explore how changes in serum insulin levels over time affect the risk of developing cardiovascular diseases and mortality.
  • Included 4084 participants without CVD at baseline
  • Measured serum insulin levels at least three times during the exposure period
  • Classified participants into four insulin trajectory groups: stable, decreasing, slow-rising, rapid-rising
  • Employed logistic regression and Cox proportional hazard models to analyze associations
  • 282 participants developed CVD during an average follow-up of 10.2 years
  • Rapid-rising insulin trajectory significantly increased CVD risk (OR=1.39)
  • Slow-rising trajectory showed a moderately increased risk of CVD (OR=1.27)
  • Rapid-rising trajectory was associated with a higher risk of CVD mortality (HR=1.96)

Abstract

Abstract Background/Introduction Insulin resistance is a well-established risk factor for cardiovascular diseases (CVD). However, the long-term impact of insulin level alterations on CVD incidence remains unclear. Identifying patterns of insulin resistance progression may enhance early risk stratification and preventive interventions. Purpose To examine the association between longitudinal serum insulin trajectories and the risk of CVD incidence and mortality in a population-based cohort. Methods This trajectory analysis included 4084 participants (1917 male) all without CVD at baseline and with at least three serum insulin measurements during the exposure period. The study was divided into two distinct phases: (1) an exposure period ending at index year, during which insulin levels were measured longitudinally to classify participants into trajectory groups, and (2) an event accrual period, during which CVD incidence and mortality were recorded. Using group-based trajectory modelling, individuals were classified into four insulin trajectory groups: stable, decreasing, slow-rising, and rapid-rising. Multivariable logistic regression models were used to assess the association between insulin trajectories and CVD incidence, presenting odds ratios (OR) and 95% confidence interval (CI). Additionally, Cox proportional hazard regression models were employed to assess the association between insulin trajectories and CVD mortality, presenting hazard ratios (HR) and 95%CI. All analyses were adjusted for age, sex, body mass index, systolic blood pressure, antihypertensive and lipid-lowering drug use, smoking, physical activity, and fasting plasma glucose and insulin levels at index year. Results During an average 10.2-year event accrual period, 282 participants developed CVD. Compared to the stable trajectory, the rapid-rising insulin trajectory was associated with a significantly higher risk of CVD (OR= 1.391.09–2.96, p=0.02 in fully adjusted model). The slow-rising trajectory also showed a moderately increased risk (OR= 1.271.01–2.51, p=0.05). The decreasing trajectory was not significantly associated with CVD risk (OR= 1.050.91–2.37, p=0.08). For CVD mortality, 93 deaths were recorded during follow-up. The rapid-rising insulin trajectory was independently associated with a significantly higher risk of CVD mortality (HR= 1.961.39–2.76, p0.01 in fully adjusted model). The slow-rising trajectory showed association with CVD mortality which was attenuated in fully adjusted model (HR= 1.360.95–1.96, p=0.07). The decreasing trajectory was not significantly associated with CVD mortality (HR= 1.020.31–1.83, p=0.09). Conclusion A rising trajectory of insulin levels, particularly a rapid rise, was significantly associated with a higher risk of CVD incidence and mortality. These findings underscore the importance of monitoring insulin resistance progression over time and implementing early preventive strategies in individuals at risk.Figure1:Cases Flowchart & Study Phases Figure2:Analysis Results & Trajectories

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Cite This Study

Esmaeili et al. (2025) studied this question.

synapsesocial.com/papers/698585fe8f7c464f23009c2ehttps://doi.org/10.1093/eurheartj/ehaf784.3811
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