- Clinical Study
- Waist Circumference as a Marker of Obesity Is More Predictive of Coronary Artery Calcification than Body Mass Index in Apparently Healthy Korean Adults: The Kangbuk Samsung Health Study
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Jongsin Park, Eun Seo Lee, Da Young Lee, Jihyun Kim, Se Eun Park, Cheol-Young Park, Won-Young Lee, Ki-Won Oh, Sung-Woo Park, Eun-Jung Rhee
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Endocrinol Metab. 2016;31(4):559-566. Published online December 20, 2016
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DOI: https://doi.org/10.3803/EnM.2016.31.4.559
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- Background
We aimed to assess the risk for coronary artery calcification (CAC) according to groups subdivided by body mass index (BMI) and waist circumference (WC) in apparently healthy Korean adults. MethodsThirty-three thousand four hundred and thirty-two participants (mean age, 42 years) in a health screening program were divided into three groups according to BMI: <23 kg/m2 (normal), 23 to 25 kg/m2 (overweight), and >25 kg/m2 (obese). In addition, the participants were divided into two groups according to WC. Coronary artery calcium score (CACS) was measured with multi-detector computed tomography in all participants. Presence of CAC was defined as CACS >0. ResultsWhen logistic regression analysis was performed with the presence of CAC as the dependent variable, the risk for CAC increased as BMI increased after adjusting for confounding variables (1.102 [95% confidence interval (CI), 1.000 to 1.216]; 1.284 [95% CI, 1.169 to 1.410]; in the overweight and obese groups vs. the normal weight group). When the participants were divided into six groups according to BMI and WC, the subjects with BMI and WC in the obese range showed the highest risk for CAC (1.321 [95% CI, 1.194 to 1.461]) and those with BMI in the overweight range and WC in the obese range showed the second highest risk for CAC (1.235 [95% CI, 1.194 to 1.461]). ConclusionParticipants with obesity defined by both BMI and WC showed the highest risk for CAC. Those with BMIs in the overweight range but with WC in the obese range showed the second highest risk for CAC, suggesting that WC as a marker of obesity is more predictive of CAC than BMI.
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- Clinical Study
- Association of Waist-Height Ratio with Diabetes Risk: A 4-Year Longitudinal Retrospective Study
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Yoon Jeong Son, Jihyun Kim, Hye-Jeong Park, Se Eun Park, Cheol-Young Park, Won-Young Lee, Ki-Won Oh, Sung-Woo Park, Eun-Jung Rhee
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Endocrinol Metab. 2016;31(1):127-133. Published online March 16, 2016
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DOI: https://doi.org/10.3803/EnM.2016.31.1.127
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Abstract
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- Background
Waist-to-height ratio (WHtR) is an easy and inexpensive adiposity index that reflects central obesity. In this study, we examined the association of various baseline adiposity indices, including WHtR, with the development of diabetes over 4 years of follow-up in apparently healthy Korean individuals. MethodsA total of 2,900 nondiabetic participants (mean age, 44.3 years; 2,078 men) in a health screening program, who repeated the medical check-up in 2005 and 2009, were recruited. Subjects were divided into two groups according to development of diabetes after 4 years. The cut-off values of baseline body mass index (BMI), waist circumference (WC), and WHtR for the development of diabetes over 4 years were calculated. The sensitivity, specificity, and mean area under the receiver operator characteristic curve (AUROC) of each index were assessed. The odds ratio (OR) for diabetes development was analyzed for each of the three baseline adiposity indices. ResultsDuring the follow-up period, 101 new cases (3.5%) of diabetes were diagnosed. The cut-off WHtR value for diabetes development was 0.51. Moreover, WHtR had the highest AUROC value for diabetes development among the three adiposity indices (0.716, 95% confidence interval [CI], 0.669 to 0.763; 0.702, 95% CI, 0.655 to 0.750 for WC; 0.700, 95% CI, 0.651 to 0.750 for BMI). After adjusting for confounding variables, the ORs of WHtR and WC for diabetes development were 1.95 (95% CI, 1.14 to 3.34) and 1.96 (95% CI, 1.10 to 3.49), respectively. No significant differences were observed between the two groups regarding BMI. ConclusionIncreased baseline WHtR and WC correlated with the development of diabetes after 4 years. WHtR might be a useful screening measurement to identify individuals at high risk for diabetes.
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- Comparison of waist circumference and waist‐to‐height ratio as predictors of clustering of cardiovascular risk factors among middle‐aged people in rural Khanh Hoa, Vietnam
Rachana Manandhar Shrestha, Thuy Thi Phuong Pham, Shohei Yamamoto, Chau Que Nguyen, Ami Fukunaga, Phan Cong Danh, Masahiko Hachiya, Huy Xuan Le, Hung Thai Do, Tetsuya Mizoue, Yosuke Inoue American Journal of Human Biology.2024;[Epub] CrossRef - Novel anthropometric indices for predicting type 2 diabetes mellitus
Erfan Sadeghi, Alireza Khodadadiyan, Seyed Ali Hosseini, Sayed Mohsen Hosseini, Ashraf Aminorroaya, Massoud Amini, Sara Javadi BMC Public Health.2024;[Epub] CrossRef - Association between two novel anthropometric measures and type 2 diabetes in a Chinese population
Di Wang, Ziting Chen, Yinru Wu, Jiaojiao Ren, Dong Shen, Guifang Hu, Chen Mao Diabetes, Obesity and Metabolism.2024; 26(8): 3238. CrossRef - Body Composition and Cardiovascular Risk: A Study of Polish Military Flying Personnel
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Pavol Prokop, Martina Zvaríková, Milan Zvarík, Peter Fedor Current Psychology.2022; 41(2): 697. CrossRef - Waist-to-height ratio has a stronger association with cardiovascular risks than waist circumference, waist-hip ratio and body mass index in type 2 diabetes
Jiang-Feng Ke, Jun-Wei Wang, Jun-Xi Lu, Zhi-Hui Zhang, Yun Liu, Lian-Xi Li Diabetes Research and Clinical Practice.2022; 183: 109151. CrossRef - Diagnostic accuracy of anthropometric indices for discriminating elevated blood pressure in pediatric population: a systematic review and a meta-analysis
Jun-Min Tao, Wei Wei, Xiao-Yang Ma, Ying-Xiang Huo, Meng-Die Hu, Xiao-Feng Li, Xin Chen BMC Pediatrics.2022;[Epub] CrossRef - The utilization of BMI in patients with high WHtR as to cardiovascular risk
Meliha Melin UYGUR Journal of Health Sciences and Medicine.2022; 5(4): 1133. CrossRef - Assessment of obesity indices for prediction of hyperglycemia in adult population of Varanasi (Uttar Pradesh), India
Neha Rai, Hanjabam Barun Sharma, Renu Kumari, Jyotsna Kailashiya Indian Journal of Physiology and Pharmacology.2021; 64: 195. CrossRef - Waist-to-height ratio and metabolic phenotype compared to the Matsuda index for the prediction of insulin resistance
Katharina Lechner, Benjamin Lechner, Alexander Crispin, Peter E. H. Schwarz, Helene von Bibra Scientific Reports.2021;[Epub] CrossRef - Waist-to-Height Ratio (WHtR) in Predicting Coronary Artery Disease Compared to Body Mass Index and Waist Circumference in a Single Center from Saudi Arabia
Mostafa Q. Alshamiri, Faisal Mohd A Habbab, Saad Saeed AL-Qahtani, Khalil Abdullah Alghalayini, Omar Mohammed Al-Qattan, Fayez El-shaer, Anne Knowlton Cardiology Research and Practice.2020; 2020: 1. CrossRef - A simple cut-off for waist-to-height ratio (0·5) can act as an indicator for cardiometabolic risk: recent data from adults in the Health Survey for England
Sigrid Gibson, Margaret Ashwell British Journal of Nutrition.2020; 123(6): 681. CrossRef - Glucose Levels as a Mediator of the Detrimental Effect of Abdominal Obesity on Relative Handgrip Strength in Older Adults
Miguel Ángel Pérez-Sousa, Jesús del Pozo-Cruz, Carlos A. Cano-Gutiérrez, Atilio J. Ferrebuz, Carolina Sandoval-Cuellar, Mikel Izquierdo, Paula A. Hernández-Quiñonez, Robinson Ramírez-Vélez Journal of Clinical Medicine.2020; 9(8): 2323. CrossRef Abnormal Glucose Metabolism and Associated Risk Factors Among Adults in Mekelle City, Ethiopia Gebremedhin Gebreegziabiher, Tefera Belachew, Dessalegn Tamiru Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy.2020; Volume 13: 4017. CrossRefAnthropometric Indexes for Predicting High Blood Pressure in Vietnamese Adults: A Cross-Sectional Study Quan Nguyen Minh, Minh Hoang Nguyen Vo Integrated Blood Pressure Control.2020; Volume 13: 181. CrossRef- Relation between Baseline Height and New Diabetes Development: A Nationwide Population-Based Study
Eun-Jung Rhee, Jung-Hwan Cho, Hyemi Kwon, Se-Eun Park, Jin-Hyung Jung, Kyung-Do Han, Yong-Gyu Park, Yang-Hyun Kim, Won-Young Lee Diabetes & Metabolism Journal.2019; 43(6): 794. CrossRef - Issues in Measuring and Interpreting Diet and Its Contribution to Obesity
Rachael M. Taylor, Rebecca L. Haslam, Tracy L. Burrows, Kerith R. Duncanson, Lee M. Ashton, Megan E. Rollo, Vanessa A. Shrewsbury, Tracy L. Schumacher, Clare E. Collins Current Obesity Reports.2019; 8(2): 53. CrossRef - Assessment of the validity of multiple obesity indices compared with obesity-related co-morbidities
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Jung Ran Choi, Sang Baek Koh, Eunhee Choi BMC Public Health.2018;[Epub] CrossRef - Comparison of various anthropometric indices for the identification of a predictor of incident hypertension: the ARIRANG study
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- Clinical Study
- The Relationship between 10-Year Cardiovascular Risk Calculated Using the Pooled Cohort Equation and the Severity of Non-Alcoholic Fatty Liver Disease
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Jeong In Lee, Min Chul Kim, Byung Sub Moon, Young Seok Song, Eun Na Han, Hyo Sun Lee, Yoonjeong Son, Jihyun Kim, Eun Jin Han, Hye-Jeong Park, Se Eun Park, Cheol-Young Park, Won-Young Lee, Ki-Won Oh, Sung-Woo Park, Eun-Jung Rhee
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Endocrinol Metab. 2016;31(1):86-92. Published online March 16, 2016
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DOI: https://doi.org/10.3803/EnM.2016.31.1.86
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We investigated the association between the severity of non-alcoholic fatty liver disease (NAFLD) and the estimated 10-year risk of cardiovascular disease (CVD) calculated by Pooled Cohort Equation (PCE) and Framingham risk score (FRS). MethodsA total of 15,913 participants (mean age, 46.3 years) in a health screening program were selected for analysis. The presence and severity of fatty liver was assessed by abdominal ultrasonogram. Subjects who drank alcohol more than three times a week were excluded from the study. ResultsAmong the participants, 57.6% had no NAFLD, 35.4% had grade I, 6.5% had grade II, and 0.5% had grade III NAFLD. Mean estimated 10-year CVD risk was 2.59%, 3.93%, 4.68%, and 5.23% calculated using the PCE (P for trend <0.01) and 4.55%, 6.39%, 7.33%, and 7.13% calculated using FRS, according to NAFLD severity from none to severe (P for trend <0.01). The odds ratio for ≥7.5% estimated CVD risk calculated using the PCE showed a higher correlation with increasing severity of NAFLD even after adjustment for conventional CVD risk factors (1.52, 2.56, 3.35 vs. the no NAFLD group as a reference, P<0.01) compared with calculated risk using FRS (1.65, 1.62, 1.72 vs. no NAFLD group as a reference, P<0.01). ConclusionIn our study of apparently healthy Korean adults, increasing severity of NAFLD showed a higher correlation with estimated 10-year CVD risk when calculated using the PCE than when calculated using FRS.
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