Affiliations 

  • 1 Center for Cohort Studies, Total Healthcare Screening Center, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea
  • 2 Center for Cohort Studies, Total Healthcare Screening Center, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea; Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea
  • 3 Center for Cohort Studies, Total Healthcare Screening Center, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea; Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea. Electronic address: [email protected]
  • 4 Center for Cohort Studies, Total Healthcare Screening Center, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea; Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea; Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
  • 5 Department of Preventive Medicine, College of Medicine, Hanyang University, Seoul, South Korea
  • 6 Division of Cardiovascular and Rare Diseases, Center for Biomedical Sciences, National Institute of Health, Chungbuk, South Korea
  • 7 Department of Food and Nutrition, Sookmyung Women's University, Seoul, South Korea
  • 8 Center for Cohort Studies, Total Healthcare Screening Center, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea; Department of Family Medicine, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea
  • 9 Center for Cohort Studies, Total Healthcare Screening Center, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea; Division of Medical Nutrition, Total Healthcare Screening Center, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea
  • 10 Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Department of Social and Preventive Medicine, Julius Centre University of Malaya, University of Malaya Faculty of Medicine, Kuala Lumpur, Malaysia
  • 11 Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
  • 12 National Center for Epidemiology, Carlos III Institute of Health and Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
  • 13 Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, Maryland
  • 14 Center for Cohort Studies, Total Healthcare Screening Center, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea; Department of Radiology, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea
Am J Cardiol, 2015 Aug 15;116(4):520-6.
PMID: 26073677 DOI: 10.1016/j.amjcard.2015.05.005

Abstract

The relation between glycemic index, glycemic load, and subclinical coronary atherosclerosis is unknown. The aim of the study was to evaluate the associations between energy-adjusted glycemic index, glycemic load, and coronary artery calcium (CAC). This study was cross-sectional analysis of 28,429 asymptomatic Korean men and women (mean age 41.4 years) without a history of diabetes or cardiovascular disease. All participants underwent a health screening examination between March 2011 and April 2013, and dietary intake over the preceding year was estimated using a validated food frequency questionnaire. Cardiac computed tomography was used for CAC scoring. The prevalence of detectable CAC (CAC score >0) was 12.4%. In multivariable-adjusted models, the CAC score ratios (95% confidence intervals) comparing the highest to the lowest quintile of glycemic index and glycemic load were 1.74 (1.08 to 2.81; p trend = 0.03) and 3.04 (1.43 to 6.46; p trend = 0.005), respectively. These associations did not differ by clinical subgroups, including the participants at low cardiovascular risk. In conclusion, these findings suggest that high dietary glycemic index and glycemic load were associated with a greater prevalence and degree of CAC, with glycemic load having a stronger association.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.