Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Comparative Study
. 2018 Aug 14;8(1):12094.
doi: 10.1038/s41598-018-30600-9.

Effectiveness of Z-score of log-transformed A Body Shape Index (LBSIZ) in predicting cardiovascular disease in Korea: the Korean Genome and Epidemiology Study

Affiliations
Comparative Study

Effectiveness of Z-score of log-transformed A Body Shape Index (LBSIZ) in predicting cardiovascular disease in Korea: the Korean Genome and Epidemiology Study

Shinje Moon et al. Sci Rep. .

Abstract

Body mass index (BMI) and waist circumference (WC) have limitations in stratifying cardio-metabolic risks. Another obesity measure, A Body Shape Index (ABSI), has been introduced but its applicability remains limited. To address this, the z-score of the log-transformed ABSI (LBSIZ) was recently developed. This study aimed to examine the ability of LBSIZ, compared to that of WC and BMI, to predict cardiovascular disease (CVD) risk. The study included 8,485 participants aged 40-69 years (mean age = 52.1) who were followed for 10 years and recruited from the Korean Genome and Epidemiology Study, a population-based cohort study. The area under the curve was 0.635 (95% confidence interval [CI]: 0.614-0.657) for LBSIZ, 0.604 (95%CI: 0.580-0.627) for WC, and 0.538 (95%CI: 0.514-0.562) for BMI. The AUC of the Framingham risk score (FRS) was 0.680 (95%CI: 0.659-0.701) in comparison. When we added LBSIZ to the model, the integrated AUC significantly improved from 0.680 to 0.692 (95%CI: 0.672-0.713; p value, 0.033), whereas there were no changes with BMI (AUC, 0.678; 95%CI: 0.656-0.699) or WC (AUC, 0.679; 95%CI: 0.658-0.701). In the multivariate Cox regression analysis, LBSIZ but not BMI or WC showed a significant hazard ratio of CVD event compared to 1st decile of each parameter. In the restricted cubic spline regression, BMI and WC showed an overall J-shaped relationship with CVD events whereas LBSIZ showed a linear relationship. LBSIZ is strongly associated with CVD risk and should predict CVD risk better than BMI and WC in the general population.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Receiver operating characteristics curves for cardiovascular events by obesity parameters.
Figure 2
Figure 2
Kaplan–Meier curves of cardiovascular disease events according to the parameters for obesity. Body mass index, (A) Waist circumference, (B) LBSIZ, (C) LBSIZ: z-score of the log-transformed A Body Shape Index (LBSIZ).
Figure 3
Figure 3
Hazard ratio (95% confidence interval) for cardiovascular events by deciles of each obesity parameter. Body mass index, (A) Waist circumference, (B) LBSIZ, (C) Adjusted for age, sex, smoking, systolic blood pressure, hypertension, diabetes mellitus, low-density lipoprotein cholesterol, and medication for dyslipidaemia. LBSIZ: z-score of the log-transformed A Body Shape Index (LBSIZ).
Figure 4
Figure 4
Adjusted hazard ratio of cardiovascular events by each obesity parameter. Body mass index, (A); Waist circumference, (B) LBSIZ, (C) Adjusted for age, sex, smoking, systolic blood pressure, hypertension, diabetes mellitus, low-density lipoprotein cholesterol, and medication for dyslipidaemia. LBSIZ: z-score of the log-transformed A Body Shape Index (LBSIZ).

Similar articles

Cited by

References

    1. World Health Organization. Global Health Risks: Mortality and Burden of Disease Attributable to Selected Major Risks (WHO Press, 2009).
    1. Korean Statistical Information Service. Prevalence of obesity in Korea http://kosis.kr/statHtml/statHtml.do?orgId=117&tblId=DT_11702_N101# (2018).
    1. Solomon CG, Manson JE. Obesity and mortality: a review of the epidemiologic data. Am J Clin Nutr. 1997;66:1044S–1050S. doi: 10.1093/ajcn/66.4.1044S. - DOI - PubMed
    1. Krauss RM, Winston M, Fletcher BJ, Grundy SM. Obesity: impact on cardiovascular disease. Circulation. 1998;98:1472–1476. doi: 10.1161/01.CIR.98.14.1472. - DOI - PubMed
    1. Moon S, et al. The influence of physical activity on risk of cardiovascular disease in people who are obese but metabolically healthy. PLoS One. 2017;12:e0185127. doi: 10.1371/journal.pone.0185127. - DOI - PMC - PubMed

Publication types