Metabolic risk factors associated with premature myocardial infarction in adults ≤ 35 years: a case-control study

Acute myocardial infarction (AMI) in very young adults (≤ 35 years) represents a distinct clinical entity with limited evidence. This study aimed to characterize metabolic risk factors differentiating young AMI patients from clinic-based controls. This single-center retrospective case–control study included 62 consecutive young adults (aged 18–35 years) with confirmed AMI and 60 clinic-based controls selected from cardiology outpatient clinics during the same study period. Controls were selected using age (± 2 years) and sex restrictions to ensure group-level comparability with the AMI cohort. Metabolic parameters, including body mass index (BMI), LDL cholesterol, and blood glucose, were compared between groups. Effect sizes (Cohen’s d) were calculated to assess clinical significance. Multivariable logistic regression was performed to identify independent predictors of AMI. Correlation analyses (Pearson or Spearman, as appropriate) were performed to examine relationships between metabolic markers. Young AMI patients demonstrated a significantly more unfavorable metabolic profile than controls: median BMI (26.5 vs. 23.9 kg/m², p < 0.001), LDL cholesterol (136.5 vs. 108.0 mg/dL, p = 0.002), and blood glucose (120.0 vs. 95.0 mg/dL, p < 0.001). All three metabolic parameters showed large effect sizes (d > 1.0), indicating clinically substantial differences. In multivariable analysis, BMI (adjusted OR 1.28 per kg/m², 95% CI 1.08–1.52), LDL cholesterol (adjusted OR 1.14 per 10 mg/dL, 95% CI 1.01–1.29), and blood glucose (adjusted OR 1.16 per 10 mg/dL, 95% CI 1.05–1.29) remained independently associated with AMI risk. LDL cholesterol showed a statistically significant, albeit weak, positive association with peak troponin levels (ρ = 0.296, p = 0.020). Among AMI cases, STEMI patients exhibited higher acute glucose levels than NSTEMI patients (p = 0.004). Very young adults (≤ 35 years) with AMI exhibit markedly elevated BMI, LDL cholesterol, and glucose levels compared to age- and sex-comparable controls with large effect sizes supporting clinical significance. Multivariable analysis confirmed independent associations for all three metabolic parameters. These traditional modifiable risk factors continue to be strongly associated with early myocardial infarction, emphasizing the importance of aggressive metabolic screening and early prevention strategies in very young populations.

Authors

Institutions

Publication Details

Journal
BMC Cardiovascular Disorders
Published
2026-03-03
DOI
https://doi.org/10.1186/s12872-026-05662-7
Primary Topic
Cardiovascular Function and Risk Factors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Metabolic risk factors associated with premature myocardial infarction in adults ≤ 35 years: a case-control study

Turgut Dolanbay, Ömer Yüceer, Mustafa Oguz Cumaoğlu, Zafer Elbasan et al.
BMC Cardiovascular Disorders
Cardiovascular Function and Risk Factors
article

Metabolic risk factors associated with premature myocardial infarction in adults ≤ 35 years: a case-control study

Turgut Dolanbay, Ömer Yüceer, Mustafa Oguz Cumaoğlu, Zafer Elbasan, Abdussamed Vural, Sabri Sekme
article en

Abstract

Acute myocardial infarction (AMI) in very young adults (≤ 35 years) represents a distinct clinical entity with limited evidence. This study aimed to characterize metabolic risk factors differentiating young AMI patients from clinic-based controls. This single-center retrospective case–control study included 62 consecutive young adults (aged 18–35 years) with confirmed AMI and 60 clinic-based controls selected from cardiology outpatient clinics during the same study period. Controls were selected using age (± 2 years) and sex restrictions to ensure group-level comparability with the AMI cohort. Metabolic parameters, including body mass index (BMI), LDL cholesterol, and blood glucose, were compared between groups. Effect sizes (Cohen’s d) were calculated to assess clinical significance. Multivariable logistic regression was performed to identify independent predictors of AMI. Correlation analyses (Pearson or Spearman, as appropriate) were performed to examine relationships between metabolic markers. Young AMI patients demonstrated a significantly more unfavorable metabolic profile than controls: median BMI (26.5 vs. 23.9 kg/m², p < 0.001), LDL cholesterol (136.5 vs. 108.0 mg/dL, p = 0.002), and blood glucose (120.0 vs. 95.0 mg/dL, p < 0.001). All three metabolic parameters showed large effect sizes (d > 1.0), indicating clinically substantial differences. In multivariable analysis, BMI (adjusted OR 1.28 per kg/m², 95% CI 1.08–1.52), LDL cholesterol (adjusted OR 1.14 per 10 mg/dL, 95% CI 1.01–1.29), and blood glucose (adjusted OR 1.16 per 10 mg/dL, 95% CI 1.05–1.29) remained independently associated with AMI risk. LDL cholesterol showed a statistically significant, albeit weak, positive association with peak troponin levels (ρ = 0.296, p = 0.020). Among AMI cases, STEMI patients exhibited higher acute glucose levels than NSTEMI patients (p = 0.004). Very young adults (≤ 35 years) with AMI exhibit markedly elevated BMI, LDL cholesterol, and glucose levels compared to age- and sex-comparable controls with large effect sizes supporting clinical significance. Multivariable analysis confirmed independent associations for all three metabolic parameters. These traditional modifiable risk factors continue to be strongly associated with early myocardial infarction, emphasizing the importance of aggressive metabolic screening and early prevention strategies in very young populations.

BMC Cardiovascular DisordersVol. 26(1)
Niğde Ömer Halisdemir Üniversitesi (TR), Malatya Turgut Özal Üniversitesi (TR), Turgut Özal University (TR)
Good health and well-being
Openalex Percentile: Top 42%
Cardiovascular Function and Risk Factors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.