THE NATIONAL MEDICAL JOURNAL OF INDIA
VOL. 16, NO . 4, 2003
189
Original Articles Waist circumference correlates better with body mass index than waist-to-hip ratio in Asian Indians SUNITA SIMON KURPAD, HIMANSHU TANDON, K. SRINIVASAN
ABSTRACT Background.Waist circumference has been reported to be a better index of android (abdominal) obesity than waist-to-hip ratio. It is likely that the cut-off values that denote medical risk in the Caucasian population cannot be extrapolated to Asian Indians. Methods.This was a hospital-based, cross-sectional study. Anthropometric measurements were taken in 285 subjects (207 men, mean age 37 years, range 18–76 years; and 78 women, mean age 31.5 years, range 18–69 years). The subjects comprised patients under psychiatric care as well as normal individuals. The correlation of waist circumference, hip circumferenceandwaist-to-hipratiowithbodymassindexwasstudied. The prevalence of abdominal obesity using waist circumference was compared to the prevalence of abdominal obesity using waist-to-hipratio.(Boththestandardandthenewrecommended cut-offs for Asians were used.) Results.Waist circumference correlated better with body mass index than waist-to-hip ratio (in menr=0.821 and 0.341, and in women r=0.729 and 0.113; p £ 0.01). Forty-seven per cent of overweight men and 73% of overweight women had abdominal obesity as defined by the standard waist circumference cut-offs compared to none of the men and 47% of overweightwomenusingthewaist-to-hipratio. Conclusion. Waist circumference correlates better with body mass index than waist-to-hip ratio. The prevalence of abdominalobesityusingwaistcircumferenceishigherthanthat withwaist-to-hipratio.ThisisespeciallysoinAsianIndiansasthe new recommendations of both body mass index and waist circumferencecut-offstodetectsubjectsatmedicalriskarelower in them than in Caucasians. Natl Med J India 2003;16:189–92 INTRODUCTION Body mass index (BMI) is a simple measure used to characterize a person as being undernourished, normal or overweight (preobese and obese).1 The medical risks due to obesity have been shown to be linked more to the abdominal distribution of fat, as measured by the waist-to-hip ratio (WHR) and, more recently, by the waist circumference rather than BMI.2,3 Waist circumference has been St John’s Medical College Hospital, Sarjapura Road, Bangalore 560034, India SUNITA SIMON KURPAD, HIMANSHU TANDON, K. SRINIVASAN Department of Psychiatry Correspondence to SUNITA SIMON KURPAD;
[email protected] © The National Medical Journal of India 2003
found to be a better predictor of visceral adipose tissue (VAT) than WHR. 4 This has also been confirmed by methods such as dual-energy X-ray absorptiometry.5 Research studies on cardiovascular diseases, diabetes and obesity in Asian Indians often report that WHR is a risk factor and not waist circumference.6–9 The standard World Health Organization (WHO) recommendations for BMI, waist circumference and WHR cut-offs to detect subjects at risk are based on the Caucasian population, and may not be accurate for Asians, who have more abdominal fat and morbidity for the same BMI.10–12 The recent WHO monograph on obesity has recommended even lower cut-offs for BMI and waist circumference for Asians. In this document, there is no mention of WHR as an index of abdominal obesity in Asians.13 One Indian study on risk factors for coronary heart disease discussed the percentage of subjects who have abdominal obesity as defined by WHR >0.9 in men, and >0.8 in women as being 57.4% and 68.4%, respectively.14 Another study noted that WHR was significantly higher in cases with acute myocardial infarction than controls (0.93 v. 0.89).15 Studies on urban slum populations in north India have shown a high prevalence of abdominal obesity (using WHR), ranging from 9.4% to 22% in men and 16% to 51.1% in women.16,17 Another study on healthy volunteers reported a mean BMI of 21.4, waist circumference of 79.6 cm and a WHR of 0.86 in men, and 23.3, 77.4 cm and 0.82, respectively, in women.11 One study examined how visceral obesity leads to morbidity and reported a mean BMI of 24.5, WHR of 0.88 and waist circumference of 86.2 in 20 Asian Indian men.18 At present, there are no data available on the accuracy of WHR or waist circumference for the detection of abdominal obesity in the Indian population. Our primary aim was to study the correlation between BMI and anthropometric parameters such as waist circumference, hip circumference and WHR in a group of Indian subjects. The secondary aim was to study the comparative prevalence of abdominal obesity (using various cut-offs for WHR compared to waist circumference) in various BMI groups. METHODS This report is part of a larger study on the prevalence of obesity among psychiatrically ill subjects.19 Ethical approval was obtained from our Institution’s Ethical Committee and informed consent was obtained from all subjects. This was a cross-sectional, hospital-based study. Subjects The methodology has been described in detail elsewhere.19 Briefly, the subjects consisted of consecutive adult admissions to the psychiatric ward, 1 in 5 psychiatric outpatients and attenders of patients in
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the Ophthalmology ward (total subjects 285). The exclusion criteria were age 0.85 in women) and lower cut-offs (³0.95 in men and ³0.80 in women).22,3 Both sets of cut-offs have been derived from Caucasian populations. Waist circumference. We used two sets of cut-offs shown to be associated with increased risk of the metabolic consequences of obesity in Caucasians. Cut-offs of ³94 cm in men and ³80 cm in women denote subjects at ‘increased risk’ or action level 1, and ³102 cm in men and ³88 cm in women denote subjects at ‘substantially increased’ risk or action level 2.23 We also analysed the data using the lower cut-offs recommended for Asians (³90 cm in men and ³80 cm in women).13 Comparative prevalence of abdominal obesity We compared the prevalence of abdominal obesity as defined by the above ‘at risk’ values for waist circumference with WHR, in groups of subjects who were classified based on BMI. Statistics Statistical analysis was performed using SPSS for Windows, version 10.1. The relationships between anthropometric measurements were analysed by calculating Pearson’s product–moment correlation coefficients. A p value of
