Waist1 77 Waist circumference as a predictor for blood glucose levels in adults May-August, 2009May-August, 2009May-August, 2009May-August, 2009May-August, 2009 Vol.28 - No.2 Vol.28 - No.2 Vol.28 - No.2 Vol.28 - No.2 Vol.28 - No.2 UNIVERSA MEDICINA Shinta L Hardiman*a, Intan Nevita Bernanthus*, Puspa K Rustati* and Eva Susiyanti** *Medical Profession Study Program, Medical Faculty, Trisakti University **Distric Health Center, Cipete Selatan, South Jakarta Correspondence aDr. Shinta L Hardiman Medical Profession Study Program, Medical Faculty, Trisakti University Jl. Kyai Tapa No.260 Grogol Jakarta Univ Med 2009;28:77-82 ABSTRACT Anthropometric indexes such as body mass index (BMI), waist circumference (WC), hip ciucumference (HC), and waist–hip ratio (WHR), are all useful anthropometric measurements to provide important information on blood glucose concentrations. The aim of this study was to determine different anthropometric measurements, in particular BMI, waist circumference, hip circumference and waist-to-hip ratio, in their ability to predict the blood glucose levels in men and women 40 to 60. A cross-sectional study was conducted on a sample of 44 men and 127 women aged 40 to 50 who lived in Cipete Selatan subdistrict, South Jakarta. Blood glucose levels was assessed and anthropometric measurements comprising BMI, WC, HC, WHR were collected. Multiple linear regression analysis was used to determine the best predictor for blood glucose levels. The study showed that the prevalence of DM type 2 was 25.7% and the prevalence was higher in men (40.9%) compared to women (23.5%). The significant predictive variables in the simple regression analysis were age and waist circumference. Multiple linear regression showed that after adjustment for age, WC was positively associated with blood glucose levels. Standardized a value was 0.172 (p=0.026). WC predict blood glucose levels, beyond that explained by traditional diabetic risk factors and BMI. These findings provide support for the recommendation that WC be a routine measure for identification of diabetes mellitus type 2 in men and women aged 40 to 60 years. Keywords: Anthropometric indexes, blood glucose levels, diabetes mellitus type 2 INTRODUCTION The increase in the number of diabetes mellitus (DM) type 2 patients all over the world have been predicted by the experts. (1) The prevalence rate of DM in the developing world, e s p e c i a l l y i n t h e A s i a - P a c i f i c r e g i o n , increasingly compared with other countries. In Thailand the increase in the prevalence of DM type 2 among the population aged ≤35 was 9.6%, 78 Hardiman, Bernanthus, Rustati, et al Waist circumference for blood glucose an increase of 20% over a period of 5 years.(2) According to the survey that was carried out by the World Health Organization (WHO) in the year 2000, Indonesia occupied the 4th place in the number of DM patients in the world after India, China and the United States. During 2000, the prevalence of the DM was 8.4 million and in 2030 will be increased to 21.3 million.(1) Whereas data from the Indonesian Department of Health showed that the number of DM inpatients and outpatients treated in hospitals occupied the first place from all over endocrine disorders.(3) In developing countries the highest prevalence of DM type 2 was in people 45 to 65 years of age.(4) The complications that could result from DM, i n c l u d i n g c o r o n a r y h e a r t d i s e a s e ( C H D ) , necessitate larger expenditures for medical treatment. Therefore, early diagnosis and prevention of DM are very important to prevent CHD as a complication after the onset of diabetes. Several factors that could increase the incidence of DM type 2 are sedentary habits, obesity, excessive consumption of polyunsaturated fats and refined sugars, and smoking. Several studies showed that obesity was correlated with the increase in the p r e v a l e n c e o f h y p e r t e n s i o n , D M a n d dyslipidemia.(5) The importance of obesity as a risk factor for type 2 diabetes and hypertension has been well recognized, but its role as a coronary heart disease (CHD) risk factor in nondiabetic, normotensive individuals has been less well established.(6) Anthropometric indices, s u c h a s b o d y m a s s i n d e x ( B M I ) , w a i s t circumference (WC), and waist-hip ratio (WHR), are anthropometric measurements that could give risk information on DM and CHD.(7) The WHO and the National Institute of Health have defined BMI, WC, and WHR cut-off levels for white, black and Hispanic American adults; however, these definitions cannot be readily applied to other populations.(8,9) It is beneficial to healthcare to assess which anthropometric measurements are associated with the presence of DM in different populations. Although it is argued that there is no justification for general population screening, early detection of individuals at risk of diabetes could be beneficial because early intervention has the potential to prevent the development of diabetes and its complications. The identification of individuals at risk of diabetes and treatment of risk factors is therefore relevant to prevent cardiovascular disease and mortality in addition to diabetes.(10) The aim of this study was to determine which anthropometric measurements, in particular BMI, WC, and WHR, were able to predict the risk of type 2 diabetes in people 40 to 60 years of age. METHODS Research design We carried out a cross-sectional study during October to November 2007 among people 40 to 60 years of age. Study subjects The subjects of the study were men and women 40 to 60 years of age who lived in Cipete Selatan subdistrict. The inclusion criteria were age 40 to 60 years and no history of diabetes. After exclusion of participants with any history of severe diseases (cancer, liver cirrhosis), mental retardation and lack of communication, data were collected on subject characteristics, such as age, gender, level of education, exercise and occupation. Measurements The anthropometric measurements used to calculate BMI, using standardized procedures, were height and weight. Height was measured using a portable microtoise to the nearest 0.1 cm and weight was measured using sage portable scales to the nearest 0.1 kg. BMI was calculated as the weight (kg) divided by the square of the 79 Univ Med Vol.28 - No.2 height (m). WC was taken as the minimum circumference between the umbilicus and xiphoid process and measured to the nearest 0.5 cm. Hip circumference (HC) was measured as the maximum circumference around the buttocks posteriorly and the symphysis pubis anteriorly and measured to the nearest 0.5 cm. Then WHR was calculated from WC and HC. Blood was taken at any time for measurement of plasma glucose (PG). Blood glucose level was measured using glucotest and glucostrip. The American Diabetes Association criteria were used to diagnose diabetes.(11) Diabetes was defined by the presence of classic DM symptoms and a casual plasma glucose level of > 200 mg/dL (11.1 mmol/L). Statistical analysis Differences between men and women were e x a m i n e d b y St u d e n t ’s t t e s t . To t e s t t h e contribution of age, WC, HP, BMI, WHR on c a s u a l b l o o d g l u c o s e c o n c e n t r a t i o n s a s dependent variable we used a single regression analysis. Furthermore a multiple step-wise regression analysis, including all variables that were significantly (p<0.05) associated with c a s u a l b l o o d g l u c o s e l e v e l s , w a s u s e d t o determine the best predictor of casual blood glucose concentrations. All analyses were performed using the SPSS/PC statistical program (version 11.0 for Windows; SPSS, Inc.Chicago, IL). RESULTS The subjects consisted of 127 (74.3%) women and 44 (25.7%) men. The prevalence of DM type 2 was 25.7%. The age, anthropometric indices, blood glucose levels and prevalence of type 2 DM of the subjects are summarized in Table 1. The means of height and weight were significantly higher in men compared to women. In men, WC (88.3 ± 10.8 cm) was statistically significantly higher compared with women (83.5 ± 9.4 cm) (p=0.005). HC and WHR differences were also statistically significant between men and women, but the difference in blood glucose levels was not statistically significant (p=0.197). Table 2 presents the results of the simple linear regression analysis in which several anthropometric indices were used to predict the blood glucose levels. The analysis showed that age and WC had a statistically significant positive association with casual blood glucose levels, whereas BMI, HC, and WHR were statistically not significantly associated with Anthropometry index Men (n=44) Women (n=127) p value Age (yr) 51.3 (6.3) 47.6 (6.1) 0.001 Height (cm) 162.8 (7.0) 151.8 (5.1) 0.000 Weight (kg) 77.6 (10.3) 59.1 (10.1) 0.000 BMI * 25.2 (3.3) 25.7 (4.1) 0.393 WC (cm) ** 88.3 (10.8) 83.5 (9.4) 0.005 WH ratio *** 0.98 (0.06) 0.93 (0.04) 0.000 HC (cm) **** 92.6 (9.4) 96.2 (9.8) 0.041 Blood glucose level (mg/dl) 136.6 (70.4) 120.8 (69.6) 0.197 DM § 40.9% 23.5% 0.081 Table 1. Anthropometry and prevalence of type 2 DM in the studied population *BMI = body mass index; **WC = waist circumference; ***WHR = waist to hip ratio; **** HC = hip circumference; §DM = diabetes mellitus type 2; Values are expressed as mean and standard deviation (in parentheses). 80 Hardiman, Bernanthus, Rustati, et al Waist circumference for blood glucose Predictors B p Age 1.684 0.048 BMI* 0.383 0.827 WC** 1.351 0.011 HC*** 0.491 0.303 WHR**** 103.371 0.345 Table 2. Simple regression analysis for predictors of blood glucose levels in men and women *BMI = body mass index; **WC = waist circumverence; ****WHR = waist to hip ratio; *** HC = hip circumference Table 3. Multiple linear regression model for age and WC on blood glucose levels Model â Standardized â p Aged 1.348 0.121 0.115 WC* 1.202 0.152 0.026 *WC = waist circumference casual blood glucose levels. Multiple linear regression models showed that WC was the best predictor for casual blood glucose levels among men and women 40 to 60 years of age. WC had a statistically significant positive association with casual blood glucose levels (p=0.026) (Table 3). DISCUSSION In the present study the prevalence of DM type 2 was 25.7% among men and women 40 to 60 years of age. This result was similar with that of a survey in Mexico, where the prevalence of DM type 2 among men and women over 20 was 26.6%.(12) However, the prevalence of DM in our study was higher than that found in the American survey (DM 7.8% in both genders), probably because in the latter the data were analyzed based on age groups and not on gender, whereas in our study the analysis was on gender and not on age groups.(13) The primary finding of our study is that WC significantly predicts the levels of blood glucose. The study by Janiszewski et al(14) of approximately 3,000 men and 2,800 women showed similar results. After controlling for age, sex, race, smoking status, cardiometabolic risk factors, and BMI, patients with WC in the medium and high categories had a twofold and fivefold increased risk of diabetes, respectively. Schulze e t a l . s h o w e d t h a t W C h a d t h e s t r o n g e s t association of single anthropometric measures for type 2 DM.(15) Several previous cohort studies(16- 19) that compared different anthropometric measurements with regard to diabetes risk p r e d i c t i o n s u g g e s t t h a t a n t h r o p o m e t r i c m e a s u r e m e n t s t h a t d e s c r i b e c e n t r a l f a t distribution, in particular WC, may be superior to measurements of general adiposity. A study in Central Jakarta on men and women 35 to 55 years of age, showed a similar result, namely that WC was the best predictor for screening DM type 2, compared with BMI, waist to height ratio and WHR.(20) WC by itself was also strongly related to risk of myocardial infarction, and this association remained significant after adjustment for other risk factors.(21) In the present study, WC significantly predicted the levels of blood glucose, but BMI did not predict diabetes after consideration of common diabetic risk factors and WC. The recent consensus statement of the American Diabetes Association, the Obesity Society, and the American Society for Nutrition questions the sequence of clinical measures of diabetes mellitus and more importantly, the relevance of WC measurement in clinical practice.(22) One of the limitations of this study was that we were unable to include the fasting and 2 hour glucose concentration to determine a better diagnosis for DM type 2. The simplest parameter for identifying those at risk of diabetes is WC, beyond that explained by commonly evaluated 81 Univ Med Vol.28 - No.2 diabetic risk factors such as weight, BMI and WHR. CONCLUSIONS We found that among men and women, WC appeared to be the best predictor than any other single direct measure. WC was a better predictor of diabetes occurrence than BMI among men and w o m e n . G e n e r a l l y, m e a s u r e m e n t o f anthropometric characteristics beyond WC had little predictive information. WC can be used for early intervention to delay or prevent type 2 DM. ACKNOWLEDGEMENT We hereby wish to extend our heartfelt gratitude to all men and women who graciously participated in this study, to Drg. Eva Susiyanti as Head of Cipete Selatan health center and to all staff of the health center, for their support of this study. And last but not least, we thank Prof. Dr. dr. Adi Hidayat, MS for editing and revising the manuscript. REFERENCES 1. Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care 2004;27: 1047-53. 2 Aekplakorn W, Stolk RP, Neal B, Suriyawongpaisal P, Chongsuvivawong V, Cheepudomwit S, et al. The prevalence and management of diabetes in Thai adults: the International Collaborative Study of Cardiovascular Disease in Asia. Diabetes Care 2003;26:2758–63. 3. Departemen Kesehatan Republik Indonesia. Jumlah penderita diabetes Indonesia ranking ke-4 di dunia. 5 September 2005. Available at: http://www. depkes.go.id/index.php?option=news&task= viewarticle&sid=1183. Accessed August 12, 2007. 4. Wild S, Roglic G., Green A. Global prevalence of diabetes. Diabetes Care 2004;27:1047-53. 5. Griffin SJ, Little PS, Hales CN, Kinmonth AL, Wareham NJ. Diabetes risk score: towards earlier detection of type 2 diabetes in general practice. Diabetes Metab Res Rev 2000;16:164-71. 6. Abbasi F, Brown Jr BW, Lamendola C, McLaughlin T, Reaven GM. Relationship between obesity, insulin resistance, and coronary heart disease risk. J Am Coll Cardiol 2002;40:937–43. 7. US National Institutes of Health. Clinical guidelines for the identification, evaluation, and treatment of overweight and obesity in adults. National Institutes of Health: Bethesda, MD;1998. 8. World Health Organization. Obesity. Preventing and managing the global epidemic. Report of a WHO Consultation on Obesity, Geneva, 3 – 5 June. World Health Organization: Geneva;1998. 9 Okosun IS, Liao Y, Rotimi CN, Choi S, Cooper RS. Predictive values of waist circumference for dyslipidaemia, type 2 diabetes and hypertension in overweight white, black, and hispanic American adults. J Clin Epidemiol 2000;53:401-8. 10. Nijhof N, ter Hoeven CL, de Jong MDT. Determinants of the use of a diabetes risk-screening test. J Comm Health 2008;33:313-7. 11. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 2005;28 (Suppl 1):S37-S42. 12. Berber A , Go´mez-Santos R, Fanghänel G, Sanchez- Reyes L. Anthropometric indexes in the prediction of type 2 diabetes mellitus, hypertension and dyslipidaemia in a Mexican population. Int J Obes 2001;25:1794–9. 13. Harris MI, Flegal KM, Cowie CC, Eberhardt MS, Goldstein DE, Little RR, et al. Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in U.S. adults. Third National Health and Nutrition Examination Survey, 1988 – 1994. Diabetes Care 1998;21:518-24. 14. Janiszewski PM, Janssen I, Ross R. Does waist circumference predict diabetes and cardiovascular disease beyond commonly evaluated cardiometabolic risk factors? Diabetes Care 2007;30:3105-9. 15. Schulze MB, Heidemann C, Schienkiewtz A, Bergmann MM, Hoffmann K, Boeing H. Comparison of anthropometric characteristics in predicting the incidence of type 2 diabetes in the EPIC-Potsdam study. Diabetes Care 2006;29:1921- 3. 16. Stevens J, Couper D, Pankow J, Folsom AR, Duncan BB, Nieto FJ, et al. Sensitivity and specificity of anthropometrics for the prediction of diabetes in a biracial cohort. Obes Res 2001;9:696-705. 82 Hardiman, Bernanthus, Rustati, et al Waist circumference for blood glucose 17. Snijder MB, Dekker JM, Visser M, Bouter LM, Stehouwer CD, Kostense PJ, et al. Associations of hip and thigh circumferences independent of waist circumference with the incidence of type 2 diabetes: the Hoorn Study. Am J Clin Nutr 2003;77:1192–7. 18. Sargeant LA, Bennett FI, Forrester TE, Cooper RS, Wilks RJ. Predicting incident diabetes in Jamaica: the role of anthropometry. Obes Res 2002;10:792– 8. 19. Castillo S, Monroy V. Anthropometric cut off points for predicting chronic diseases in the Mexican National Health Survey 2000. Obes Res 2003;11: 442-51. 20. Delima. Indeks antropometri sebagai uji diagnostic diabetes mellitus tipe 2. Avaiable at: http:// digilib.litbang.depkes.go.id/go.php?id=jkpkbppk- gdl-res-2002-delima-1134-diabetes&q=indeks+ antropometri. Accessed September 1, 2008. 21. Walling AD. Waist-to-hip ratio better predictor of disease than BMI. Am Fam Physician 2006; 73: 2046-7. 22. Klein S, Allison DB, Heymsfield SB, Kelley DE, Leibel RL, Nonas C, et al. Waist circumference 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. Diabetes Care 2007;30:1647–52.