Anthropometric indices as predictors of hypertension among men and women aged 40–69 years in the Korean population: the Korean Genome and Epidemiology Study

Abstract

BackgroundObesity is one of the most significant risk factors for hypertension. However, there is controversy regarding which measure is the best predictor of hypertension risk. We compared body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) in subjects as predictive indicators for development of hypertension.MethodsThe data were obtained from the Korean Genome and Epidemiology Study (KoGES), a large population-based prospective cohort study. A total of 4,454 subjects (2,128 men and 2,326 women) aged 40–69 years who did not have hypertension at baseline were included in this study. Incident hypertension was defined as systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg, or anti-hypertensive medication use during the 4-year follow up. Receiver operating characteristic (ROC) analysis was used to compare discrimination abilities for anthropometric indices for hypertension. Hazard ratios were calculated by Cox proportional hazard model with adjustment for age, smoking status, alcohol consumption, diabetes and family history of hypertension by sexes.ResultsIn men, the area under the ROC curve (AROC) was 0.62 for WC, WHR, and WHtR and 0.58 for BMI. In women, the AROCs for BMI, WC, WHR, and WHtR were 0.57, 0.66, 0.68, and 0.68, respectively. After adjustment for risk factors, a 1 standard deviation increase in BMI, WC, WHR, WHtR were significantly related to incident hypertension, respectively (hazard ratio: 1.39, 1.50, 1.40 and 1.49 in men, 1.31, 1.44, 1.35 and 1.48 in women).ConclusionsThe central obesity indices WC, WHR, and WHtR were better than BMI for the prediction of hypertension in middle-aged Korean people. WHtR facilitates prediction of incident hypertension because of the single standard regardless of sex, ethnicity, and age group. Therefore, WHtR is recommended as a screening tool for the prediction of hypertension.

The influence of gender on selected risk factors for chronic non-communicable diseases in patients hospitalized in surgical wards: A cross-sectional study

“…22,23,25 It was also shown that WC >80 cm for women and >94 cm for men is a strong predictor for the development of HTN, DM and dyslipidemia, and strongly correlated with increased mortality due to CVD and chronic respiratory diseases in particular. 33,[56][57][58][59][60] In the present study, 74.6% of women and 62.9% of men were characterized by abdominal obesity. Similar results were also obtained by other authors.…”

An Overview on Cardiovascular Risks Definitions by Using Survival Analysis Techniques-Tehran Lipid and Glucose Study: 13-Year Follow-Up Outcomes

“…In addition to the factors considered in this study there are other cardiovascular predictors such as waist circumference, hypertriglycemic waist, and waist to hip ratio (WHR) (Lee et al, 2015). Assessment of these factors remains to be studied further.…”

“…In so far as heart disease is one of the most important causes of death in the world, as well as in Iran (Smith, Greenland, & Grundy, 2000;Shakeri et al, 2011), it is necessary to conduct more precise research on its risk factors, such as diabetes, high blood pressure, the blood cholesterol level, and obesity (Pastor-Barriuso et al, 2003;Woo, Ho, & Yu, 2002;Kang et al, 2009;Leon et al, 2005;DECODE Study Group, 2003;Lee et al, 2015).…”

Preditores antropométricos de hipertensão arterial sistêmica em mulheres afrodescendentes

“…Em contrapartida, outros autores encontraram a RCE, que consiste num marcador de obesidade abdominal e está fortemente relacionado com a gordura visceral, como o melhor preditor de HAS, sendo RCE ≥0,53 (AUC 0,76; IC95% 0,73-0,79) e RCE ≥0,51 (AUC 0,68; IC95% 0,66-0,70) os melhores pontos de corte para mulheres brasileiras da cidade de Vitória e mulheres coreanas, respectivamente [32,35]. Esses pontos de corte foram menores do que o encontrado neste estudo.…”

“…Diversos trabalhos têm utilizado as curvas ROC procurando identificar os melhores pontos de corte de diferentes parâmetros antropométricos para a predição da HAS em diferentes populações [8][9][10][33][34][35], em virtude da magnitude dessa doença e de que os pontos de corte propostos pela OMS foram estabelecidos para caucasianos [14]. Nesse sentido, destaca-se que o presente estudo foi o primeiro que visou identificar o melhor preditor antropométrico de HAS em mulheres de comunidades remanescentes de quilombos.…”