SavedAdd your journal

Journals / Dicle Tıp Dergisi / 2026 / Cilt: 43 Sayı: 1

Association of Anthropometric Measurement Methods with Cardiovascular Disease Risk in Turkey

Kaan Sözmen
Belgin Ünal
Sibel Sakarya
Gönül Dinç
Nazan Yardım
Bekir Keskinkılıç
Gül Ergör
Pages
99–106
Publication Date
2016-03-01
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Key words: Obesity, Framingham risk score, coronary heart disease

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Objective: The aim of this study is to compare the predictive power of anthropometric indices for risk of developing Coronary Heart Disease (CHD) or CHD death.
📊
Key Findings & Data:Methods: We used cross-sectional data from nationally representative Chronic Diseases and Risk Factors Survey conducted by the Ministry of Health in 2011.
💡
Conclusion & Impact:Key words: Obesity, Framingham risk score, coronary heart disease
🔬Design:Survey & Empirical Study
📍Scope:2011 Verileri
⚙️Variables:Obezite · Framingham risk skoru · koroner kalp hastalığı

Özet

Objective: The aim of this study is to compare the predictive power of anthropometric indices for risk of developing Coronary Heart Disease (CHD) or CHD death. Methods: We used cross-sectional data from nationally representative Chronic Diseases and Risk Factors Survey conducted by the Ministry of Health in 2011. Body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist to height ratio (WHtR), body adiposity index (BAI) and A Body Shape Index (ABSI) formed the anthropometric measures. For each participant risk of developing CHD or dying from CVDs were calculated based on Framingham and SCORE risk equations. Predictive ability of anthropometric measurements was assessed by receiver operating characteristic (ROC) curves. Results: Anthropometric measurements of central obesity recorded higher area under the ROC curve (AUC) values than BMI in both men and women. While ABSI had the highest AUC values for Framingham 10-year predicted risk (FRS) for CHD death (AUC = 0.613), SCORE 10-year risk for CVD death (AUC = 0.633), in women AUC for ABSI was the highest for only SCORE risk threshold (AUC = 0.705). Among women, WHtR was found to be the best indicator for estimating CHD incidence (AUC = 0.706) and death from CVD (AUC = 0.696). Conclusion: Compared to traditional anthropometric measurements such as BMI, ABSI was a better indicator for given thresholds for estimating the risk of developing CHD and CVD death in men. Among women WHtR made better predictions for FRS thresholds, however, ABSI was better for predicting 10-year risk of CVD death calculated by SCORE risk equation. Key words: Obesity, Framingham risk score, coronary heart disease

🔖

Cite This Article

Sözmen, K., Ünal, B., Sakarya, S., Dinç, G., Yardım, N., Keskinkılıç, B., Ergör, G. (2016). Association of Anthropometric Measurement Methods with Cardiovascular Disease Risk in Turkey. Dicle Tıp Dergisi, Cilt: 43 Sayı: 1, 99–106. https://doi.org/10.5798/diclemedj.0921.2016.01.0646

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (33)

  1. Obesity and overweight. Secondary obesity and overweight
  2. [http://www.who.int/mediacentre/factsheets/fs311/en/]
  3. Klein S, Allison DB, Heymsfield SB, et al. Waist circumference
  4. and cardiometabolic risk: a consensus statement from Shaping America’s Health: Association for Weight Management and Obesity Prevention; NAASO, The Obesity Society; the American Society for Nutrition; and the American Diabetes Association. Am J Clin Nutr 2007;85:1197-1202.
  5. Stevens GA, Singh GM, Lu Y, et al. National, regional, and global trends in adult overweight and obesity prevalences. Popul Health Metr 2012;10:22.
  6. Satman I, Omer B, Tutuncu Y et al. Twelve-year trends in the
  7. prevalence and risk factors of diabetes and prediabetes in Turkish adults. Eur J Epidemiol 2013;28:169-180.
  8. Nelson MR. Management of high blood pressure in those without overt cardiovascular disease utilizing absolute risk scores. Int J Hypertension 2011;21:235-340.
  9. Conroy RM, Pyorala K, Fitzgerald AP, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 2003, 24:987-1003.
  10. Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better
  11. screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Rev 2012;13:275-286.
  12. Bergman RN, Stefanovski D, Buchanan TA, et al. A better index of body adiposity. Obesity (Silver Spring) 2011;19:1083-1089.
  13. Krakauer NY, Krakauer JC. A new body shape index predicts
  14. mortality hazard independently of body mass index. PLoS One. 2012;7:e39504.
  15. Meseri R, Ucku R, Unal B. Waist:height ratio: a superior index in estimating cardiovascular risks in Turkish adults. Public Health Nutr 2014;17:2246-2252.
  16. Türkiye Kronik Hastalıklar ve Risk Faktörleri Sıklığı Çalışması, Sağlık Bakanlığı, Ankara 2013;909
  17. Mancia G, De Backer G, Dominiczak A, et al. 2007 Guidelines
  18. for the Management of Arterial Hypertension: The Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens 2007;25:1105-1187.
  19. Wilson PW, D’Agostino RB, Levy D, et al. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97:1837-1847.
  20. Freedman DS, Ogden CL, Goodman AB, et al. Skinfolds and coronary heart disease risk factors are more strongly associated with BMI than with the body adiposity index. Obesity (Silver Spring) 2013;21:E64-70.
  21. Balkau B, Deanfield JE, Després J-P, et al. International Day for the Evaluation of Abdominal Obesity (IDEA): a study of waist circumference, cardiovascular disease, and diabetes mellitus in 168,000 primary care patients in 63 countries. Circulation 2007;116:1942-1951.
  22. Winter Y, Rohrmann S, Linseisen J, et al. Contribution of obesity and abdominal fat mass to risk of stroke and transient ischemic attacks. Stroke. 2008;39:3145-3151.
  23. Taylor AE, Ebrahim S, Ben-Shlomo Y, et al. Comparison of the associations of body mass index and measures of central adiposity and fat mass with coronary heart disease, diabetes, and all-cause mortality: a study using data from 4 UK cohorts. Am J Clin Nutr 2010;91:547-556.
  24. Lapidus L, Bengtsson C, Larsson B, et al. Distribution of adipose tissue and risk of cardiovascular disease and death: a 12 year follow up of participants in the population study of women in Gothenburg, Sweden. Br Med J (Clin Res Ed) 1984;289:1257-1261.
  25. Pischon T, Boeing H, Hoffmann K, et al. General and abdominal
  26. adiposity and risk of death in Europe. N Engl J Med 2008;359:2105-2120.
  27. Browning LM, Hsieh SD, Ashwell M. A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0.5 could be a suitable global boundary value. Nutr Res Rev 2010;23:247-269.
  28. Can AS, Bersot TP, Gonen M et al. Anthropometric indices and
  29. their relationship with cardiometabolic risk factors in a sample of Turkish adults. Public Health Nutr 2009;12:538-546.
  30. Bennasar-Veny M, Lopez-Gonzalez AA, Tauler P, et al. Body Adiposity Index and Cardiovascular Health Risk Factors in Caucasians: A Comparison with the Body Mass Index and Others. PLoS ONE 2013;8:e63999.
  31. Dhaliwal SS, Welborn TA, Goh LG, et al. Obesity as assessed
  32. by body adiposity index and multivariable cardiovascular disease risk. PLoS One 2014;9:e94560.
  33. Haghighatdoost F, Sarrafzadegan N, Mohammadifard N, et al. Assessing body shape index as a risk predictor for cardiovascular diseases and metabolic syndrome among Iranian adults. Nutrition 2014;30:636-644.