Risk Factors for Premature Myocardial Infarction: A Systematic Review and Meta-analysis of 77 Studies

Sagar B Dugani; Yousif M Hydoub; Ana Patricia Ayala; Roger Reka; Tarek Nayfeh; Jingyi Francess Ding; Shannon N McCafferty; Muayad Alzuabi; Medhat Farwati; M Hassan Murad; Alawi A Alsheikh-Ali; Samia Mora

doi:10.1016/j.mayocpiqo.2021.03.009

Risk Factors for Premature Myocardial Infarction: A Systematic Review and Meta-analysis of 77 Studies

Mayo Clin Proc Innov Qual Outcomes. 2021 Jun 23;5(4):783-794. doi: 10.1016/j.mayocpiqo.2021.03.009. eCollection 2021 Aug.

Authors

Sagar B Dugani^{1

2}, Yousif M Hydoub³, Ana Patricia Ayala⁴, Roger Reka⁴, Tarek Nayfeh⁵, Jingyi Francess Ding⁵, Shannon N McCafferty⁶, Muayad Alzuabi⁵, Medhat Farwati⁵, M Hassan Murad⁵, Alawi A Alsheikh-Ali⁷, Samia Mora^{2

8

9}

Affiliations

¹ Division of Hospital Internal Medicine, Mayo Clinic, Rochester, MN.
² Center for Lipid Metabolomics, Brigham and Women's Hospital, Boston, MA.
³ Al-Mafraq Hospital, Abu Dhabi, United Arab Emirates.
⁴ Gerstein Science Information Centre, University of Toronto, Toronto, Ontario, Canada.
⁵ Evidence-Based Practice Center, Mayo Clinic, Rochester, MN.
⁶ University of Pittsburgh, Pittsburgh, PA.
⁷ College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates.
⁸ Division of Preventive, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
⁹ Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.

Abstract

Objective: To evaluate the magnitude of the association between risk factors and premature myocardial infarction (MI) (men aged 18-55 years; women aged 18-65 years).

Patients and methods: We searched MEDLINE and other databases from inception through April 30, 2020, as well as bibliography of articles selected for data extraction. We selected observational studies reporting the magnitude of the association of at least 1 risk factor (demographic characteristics, lifestyle factors, clinical risk factors, or biomarkers) with premature MI and a control group. Pooled risk estimates (random effects) from all studies unadjusted and adjusted for risk factors were reported as summary odds ratios (ORs) with 95% CIs.

Results: From 35,320 articles of 12.7 million participants, we extracted data on 19 risk factors from 77 studies across 58 countries. Men had a higher risk of premature MI (OR, 2.39; 95% CI, 1.71 to 3.35) than did women. Family history of cardiac disease was associated with a higher risk of premature MI (OR, 2.67; 95% CI, 2.29 to 3.27). Major modifiable risk factors associated with higher risk were current smoking (OR, 4.34; 95% CI, 3.68 to 5.12 vs no/former), diabetes mellitus (OR, 3.54; 95% CI, 2.69 to 4.65), dyslipidemia (OR, 2.94; 95% CI, 1.76 to 4.91), and hypertension (OR, 2.85; 95% CI, 2.48 to 3.27). Higher body mass index carried higher risk (OR, 1.46; 95% CI, 1.24 to 1.71 for ≥25 kg/m² vs <25 kg/m²). Biomarkers associated with 2- to 3-fold higher risk were total cholesterol levels greater than 200 mg/dL, triglyceride levels higher than 150 mg/dL, and high-density lipoprotein cholesterol levels less than 60 mg/dL (to convert to mmol/L, multiply by 0.0259).

Conclusion: Major risk factors for premature MI are mostly amenable to patient, population, and policy level interventions. Mild elevations in body mass index and triglyceride levels were associated with higher risk, which has implications for the growing worldwide epidemic of cardiometabolic diseases.

Keywords: BMI, body mass index; HDL, high-density lipoprotein; IHD, ischemic heart disease; LDL, low-density lipoprotein; MI, myocardial infarction; OR, odds ratio; RoB, risk of bias.

Abstract

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