Simple anthropometric indexes and cardiovascular risk ... - Nature

International Journal of Obesity (1997) 21, 995±1001 ß 1997 Stockton Press All rights reserved 0307±0565/97 $12.00

Simple anthropometric indexes and cardiovascular risk factors in Chinese GTC Ko,1 JCN Chan,2 J Woo,1 E Lau,3 VTF Yeung,1 C-C Chow,1 HPS Wai,4 JKY Li,1 W-Y So1 and CS Cockram1 Departments of 1 Medicine, 2 Clinical Pharmacology and 3 Community and Family Medicine, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, N.T. Hong Kong and 4 Department of Radiotherapy and Oncology, Nethersole Eastern Hospital, Hong Kong

OBJECTIVE: Obesity is a major public health problem due to its associations with multiple cardiovascular risk factors. Although there are sophisticated methods, such as imaging, to document total body fat and its distributions, anthropometric measurements remain important in clinical practice. We examined the relationships between cardiovascular risk factors and the three commonest anthropometric measurements for obesity, body mass index (BMI), waist±hip ratio (WHR) and waist circumference (WC), in Hong Kong Chinese subjects. DESIGN AND SETTING: The data are obtained from a prevalence survey for glucose intolerance and lipid abnormality in a representative Hong Kong Chinese working population. All employees from a public utility company and a regional hospital were invited to participate. SUBJECTS: There were 1513 subjects (910 men and 603 women, mean age s.e.m.: 37.5 0.2 y). All of them had no signi®cant past medical history. MEASUREMENTS: BMI, WHR and WC of the 1513 subjects were assessed for their relationships with various cardiovascular risk factors. These include blood pressure, fasting and 2 h plasma glucose and insulin, glycated haemoglobin, total cholesterol, triglyceride, high density and low density lipoprotein cholesterol, and urine albumin concentration. RESULTS: After age adjustment, all three anthropometric indexes were signi®cantly correlated with the major cardiovascular risk factors in both men and women. When BMI, WHR and WC were analysed according to quartiles, there was a signi®cant trend for blood pressure, plasma triglyceride, fasting and 2 h plasma glucose and insulin to increase, and high density lipoprotein cholesterol to decrease, with increasing obesity after adjustment for age and smoking. Using stepwise regression analysis with the three indexes as independent variables, most of the variance in blood pressure, plasma lipid, insulin, glucose and urinary albumin concentration were explained either by WC or WHR. In women, BMI was the main explanatory variable for reduced high density lipoprotein cholesterol. CONCLUSIONS: In Hong Kong Chinese, BMI, WHR and WC provide important information in assessing cardiovascular risks. In men, central adiposity as re¯ected by WC and to some extent, WHR, explained most of the variance in blood pressure, plasma glucose, lipid, insulin and albuminuria. In women, all three indexes re¯ecting general and central obesity contribute to the variance in these risk factors. Keywords: anthropometric indexes; Chinese; cardiovascular risk factors

Introduction Obesity is a major public health problem due to its associations with increased cardiovascular risks.1,2 The incidence of coronary death is increased by three times amongst obese subjects. About 21% and 28% of coronary death in men and women, respectively, could be attributed to being overweight (body mass index (BMI) 25 kg/m2).2 Apart from general obesity, regional distribution of body fat as re¯ected by central obesity are also important predictors of cardiovascular death and diabetes mellitus.3 Although there are sophisticated methods such as imaging to document total body fat and its distributions,4,5

Correspondence: Dr Gary TC Ko, Department of Medicine, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, HONG KONG. Received 7 March 1997; revised 20 June 1997; accepted 2 July 1997

anthropometric measurements remain important in clinical practice. In this regard, BMI is often used to re¯ect general obesity while waist±hip ratio (WHR) and waist circumference (WC) are used to assess central adiposity. These measurements have been shown to be associated with cardiovascular risk factors such as blood pressure, plasma lipid, insulin and glucose concentrations in Caucasians6±8 and Asians,9,10 diabetic and non-diabetic subjects,11,12 as well as in adolescents,13 adults1,14 and elderly subjects.10 Although there are reports suggesting that intra-abdominal fat deposition may constitute a greater cardiovascular risk than general obesity,5,15,16 most workers still hold the view that both general and central obesity are important cardiovascular risks and are complementary to each other.7,8,14,17±19 In this study, we examined the relationships between the three commonest anthropometric measurements for obesity, BMI, WHR and WC, and cardiovascular risk factors in 1513 Hong Kong Chinese subjects.

Anthropometric indexes in Chinese GTC Ko et al

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Subjects and Methods The data are obtained from a prevalence survey for glucose intolerance and lipid abnormality in a Hong Kong Chinese working population.20 There were 1513 subjects (910 men, 603 women). All subjects were employees from two worksites of a major public utility company and a regional hospital, including all occupational groups from the managers to the labourers. The distribution of occupational groups in these subjects is similar to that recorded in the Hong Kong Census (1991) and is representative of the Hong Kong working population.20 The methodology has been described in detail previously.20 In brief, all subjects attended their worksites after an overnight fast. Demographic data were documented and height and weight (measured to the nearest 0.1 kg) were measured with the subject in light clothing without shoes. Body mass index (BMI) was calculated as the weight (kg) divided by the square of the height (m). Waist circumference (WC) was taken as the minimum circumference between the umbilicus and xiphoid process and measured to the nearest 0.5 cm. Hip circumference was measured as the maximum circumference around the buttocks posteriorly and the symphysis pubis anteriorly and measured to the nearest 0.5 cm. Waist-to-hip ratio (WHR) was then calculated.3 After sitting for at least 5 min, blood pressure (BP) was measured in the right arm by the same research nurse using a standard mercury sphygmomanometer. The Korotkoff sound V was taken as the diastolic BP. The mean value of two readings measured one minute apart was used. Hypertension was de®ned as systolic BP 160 mmHg or diastolic BP 95 mmHg.21 Blood was taken after a 12 h fast, for measurement of plasma glucose (PG), glycated haemoglobin (HbA1c, normal range in our laboratory: 5.1±6.4%), total cholesterol (TC, normal: 3.5±5.2 mmol/L), fasting triglyceride (TG, normal: 0.5±2.1 mmol/L), high density lipoprotein cholesterol (HDL, normal: 0.9 mmol/L) and low density lipoprotein cholesterol (LDL, normal: 1.5±3.5 mmol/L). All subjects underwent a 75 g oral glucose tolerance test (OGTT). Fasting and 2 h PG and insulin were measured during the OGTT. A random spot urine sample was collected for the measurement of urine albumin concentration (Ualb). The various laboratory assays have been described previously.20 The WHO criteria was used for the diagnosis of diabetes and impaired glucose tolerance (IGT).22 Diabetes was de®ned as fasting PG 7.8 mmol/L and/or 2 h PG 11.1 mmol/ L, and IGT was de®ned as fasting PG < 7.8 mmol/l and 2 h PG 7.8 mmol/L and < 11.1 mmol/L.22 Statistical analysis

Statistical analysis was performed using the SPSS (version 6.0) software on an IBM compatible compu-

ter. Plasma TG, insulin concentrations and Ualb were logarithmically transformed due to skewed distributions. All results are expressed as mean s.e.m. or geometric mean (95% con®dence intervals (CI)) where appropriate. The analysis of covariance (ANCOVA) was used for between group comparisons with age and smoking as covariates. The associations between BMI, WHR and WC and other cardiovascular risk factors were tested using age-adjusted partial correlation coef®cients. The stepwise regression analysis was used to examine the variance in cardiovascular risk factor explained independently by each of the three indexes. In each analysis, the three anthropometric indexes were used as independent variables and one of the cardiovascular risk factors was used as the dependent variable. A P-value of < 0.05 (2-tailed) was considered to be signi®cant.

Results The anthropometric and metabolic variables of the study population are shown in Table 1. After adjusting for age and smoking, men had higher WHR, WC, blood pressure, plasma lipid and HbA1c than women. Women had a higher fasting plasma insulin and Ualb than men. There were close associations between BMI, WHR and WC in both men and women (Table 2). After age adjustment, all three anthropometric indexes remained signi®cantly correlated with major cardiovascular risk factors including BP, TG, HDL, fasting and 2 h PG and insulin in both men and women. Urinary albumin concentration was correlated with all three indexes in women, but was only weakly associated with WC in men (Table 2). Table 3 shows the distributions of BMI, WHR and WC in quartiles in both men and women. With increasing BMI, WHR or WC, there was a signi®cant trend for BP, TG, fasting and 2 h PG and insulin as well as prevalence of glucose intolerance, and hypertension to increase and HDL to decrease after adjustment for age and smoking (data not shown). Increasing WHR and WC were also associated with increasing Ualb. Figure 1 and Figure 2 show the relationships between WC in quartiles and various cardiovascular risk factors in men and women. Using stepwise regression analysis with BMI, WHR and WC as independent variables, most of the variance in blood pressure, plasma lipid, insulin, glucose and Ualb were explained either by WC or WHR. In women, BMI was the main explanatory variable for reduced HDL (Table 4).

Discussion The prognostic signi®cance of obesity in cardiovascular death is mainly accounted for by its close associations with hypertension, dyslipidaemia, hyper-


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Table 1 The anthropometric and metabolic variables of Chinese male and female subjects Variables Age (y) BMI (kg/m2) WHR WC (cm) Hip (cm) Systolic BP (mmHg) Diastolic BP (mmHg) Cholesterol (mmol/L) Triglyceride (mmol/L)a HDL (mmol/L) LDL (mmol/L) Fasting PG (mmol/L) 2 h PG (mmol/L) HbA1c (%) Fasting insulin (mU/ml)a 2-hour insulin (mU/ml)a Ualb (mg/L)a Diabetes (%) IGT (%) Hypertension (%) Smoking (%)

men (n 910)

women (n 603)

P-values

P-values after adjusting for age and smoking

36.7 0.3 23.4 0.1 0.87 0.01 80.8 0.3 92.3 0.2 123.5 0.4 78.8 0.3 5.25 0.03 1.14 (1.09, 1.19) 1.24 0.01 3.39 0.03 4.9 0.1 5.5 0.1 4.99 0.02 7.3 (7.0, 7.6) 39.7 (37.3, 42.1) 3.3 (3.1, 3.6) 5.1 0.7 7.4 0.9 3.0 0.6 22.9 1.4

38.6 0.4 23.3 0.1 0.80 0.01 74.9 0.3 93.3 0.2 110.4 0.6 70.3 0.4 4.79 0.04 0.75 (0.72, 0.78) 1.53 0.02 3.06 0.03 5.0 0.1 5.8 0.1 4.56 0.03 8.4 (8.1, 8.8) 38.9 (36.6, 41.3) 4.5 (4.1, 5.0) 3.8 0.8 7.1 1.1 1.3 0.5 1.8 0.6

< 0.001 0.568 < 0.001 < 0.001 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.352 0.004 < 0.001 < 0.001 0.701 < 0.001 0.245 0.865 0.025 < 0.001

Ð 0.271 < 0.001 < 0.001 0.006 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.918 0.252 < 0.001 < 0.001 0.089 < 0.001 0.189 0.311 0.006 Ð

Mean s.e.m. or a geometric mean (95%CI) BMI: body mass index; WHR: waist±hip ratio; WC: waist circumference; BP: blood pressure; HDL: high-density lipoprotein; LDL: low-density lipoprotein; PG: plasma glucose; HbA1c: glycated haemoglobin; Ualb: spot urine albumin; IGT: impaired glucose tolerance.

Table 2 Age adjusted partial correlation coef®cients between anthropometric indexes and cardiovascular risk factors in male and female subjects BMI

WHR

WC

r

P

r

P

r

P

Men BMI WHR WC Hip circumference Systolic BP Diastolic BP Cholesterol Triglyceride HDL LDL Fasting PG 2h PG HbA1c Fasting insulin 2 h insulin Ualb

Ð 0.625 0.899 0.819 0.264 0.318 0.070 0.327 70.325 0.071 0.141 0.210 0.084 0.511 0.341 0.069

Ð < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.040 < 0.001 < 0.001 0.037 < 0.001 < 0.001 0.013 < 0.001 < 0.001 0.043

0.625 Ð 0.795 0.306 0.170 0.202 0.077 0.348 70.323 0.065 0.132 0.217 0.089 0.432 0.350 0.074

< 0.001 Ð < 0.001 < 0.001 < 0.001 < 0.001 0.026 < 0.001 < 0.001 0.054 < 0.001 < 0.001 0.009 < 0.001 < 0.001 0.029

0.889 0.795 Ð 0.819 0.256 0.317 0.078 0.374 70.358 0.074 0.176 0.235 0.085 0.554 0.381 0.085

< 0.001 < 0.001 Ð < 0.001 < 0.001 < 0.001 0.021 < 0.001 < 0.001 0.029 < 0.001 < 0.001 0.013 < 0.001 < 0.001 0.012

Women: BMI WHR WC Hip circumference Systolic BP Diastolic BP Cholesterol Triglyceride HDL LDL Fasting PG 2 h PG HbA1c Fasting insulin 2 h insulin Ualb

Ð 0.556 0.889 0.833 0.118 0.182 70.007 0.268 70.395 0.143 0.237 0.272 0.050 0.368 0.156 0.154

Ð < 0.001 < 0.001 < 0.001 0.006 < 0.001 0.864 < 0.001 < 0.001 0.001 < 0.001 < 0.001 0.248 < 0.001 < 0.001 < 0.001

0.556 Ð 0.780 0.228 0.150 0.132 0.078 0.293 70.359 0.216 0.225 0.254 0.158 0.323 0.171 0.127

< 0.001 Ð < 0.001 < 0.001 0.001 0.002 0.089 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.003

0.889 0.780 Ð 0.785 0.124 0.171 0.011 0.294 70.405 0.167 0.253 0.283 0.128 0.398 0.156 0.173

< 0.001 < 0.001 Ð < 0.001 0.004 < 0.001 0.807 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.003 < 0.001 < 0.001 < 0.001

Mean s.e.m. or a geometric mean (95%CI) BMI: body mass index; WHR: waist±hip ratio; WC: waist circumference; BP: blood pressure; HDL: high-density lipoprotein; LCL: lowdensity lipoprotein; PG: plasma glucose; HbA1c: glycated haemoglobin; Ualb: spot urine albumin; IGT: impaired glucose tolerance.


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{

Figure 1 Waist circumference in quartiles in men and their relationships with various cardiovascular risk factors. WC, waist circumference; TC, total cholesterol; TG, fasting triglyceride; HDL and LDL, high- and low-density lipoprotein; PG, plasma glucose; HbA1c, glycated haemoglobin; OGTT, oral glucose tolerance test; HT, hypertension; IGT, impaired glucose tolerance; u Quartiles 1: WC 63.6±75.3 cm (n 226) u Quartiles 2: WC 75.4±80.0 cm (n 226) u Quartiles 3: WC 80.1±86.0 cm (n 232) u Quartiles 4: WC 86.1± 125.5 cm (n 226) ANCOVA for trend: * P-value < 0.001 after adjusting for age and smoking; { P-value < 0.05 after adjusting for age and smoking; # P-value < 0.001 before, but > 0.05 after adjusting for age and smoking.

{

Figure 2 Waist circumference in quartiles in women and their relationships with various cardiovascular risk factors. WC, waist circumference; TC, total cholesterol; TG, fasting triglyceride; HDL and LDL, high- and low-density lipoprotein; PG, plasma glucose; HbA1c, glycated haemoglobin; OGTT, oral glucose tolerance test; HT, hypertension; IGT, impaired glucose tolerance; u Quartiles 1: WC 55.9±68.9 cm (n 147) u Quartiles 2: WC 69.0±74.0 cm (n 156) u Quartiles 3: WC 74.1±80.1 cm (n 151) u Quartiles 4: WC 80.2± 105.5 cm (n 149) ANCOVA for trend: * P-value < 0.001 after adjusting for age and smoking; { P-value < 0.01 after adjusting for age and smoking; # P-value < 0.001 before, but > 0.05 after adjusting for age and smoking.


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Table 3 Distribution of body mass index (BMI), waist±hip ratio (WHR) and waist circumference (WC) in Chinese men and women shown in quartiles BMI (kg/m2) Men: Quartile Quartile Quartile Quartile Women: Quartile Quartile Quartile Quartile

WHR

WC (cm)

1: 2: 3: 4:

16.1±21.4 21.5±23.1 23.2±25.3 25.4±42.5

(n 229) (n 223) (n 231) (n 227)

0.74±0.83 0.84±0.87 0.88±0.91 0.92±1.21

(n 223) (n 225) (n 222) (n 210)

63.6±75.3 (n 226) 75.4±80.0 (n 226) 80.1±86.0 (n 232) 86.1±125.5 (n 226)

1: 2: 3: 4:

14.7±20.7 20.8±23.0 23.1±25.3 25.4±39.2

(n 151) (n 152) (n 150) (n 150)

0.65±0.76 0.77±0.80 0.81±0.84 0.85±1.00

(n 167) (n 173) (n 142) (n 121)

55.9±68.9 (n 147) 69.0±74.0 (n 156) 74.1±80.1 (n 151) 80.2±105.5 (n 149)

Table 4 The variances in cardiovascular risk factors explained by waist circumference (WC), body mass index (BMI), and waist hip ratio (WHR) using stepwise regression analysis BMI

WHR

b

p

R

b

p

Men Age Hip circumference Systolic BP Diastolic BP Cholesterol Triglyceride HDL LDL Fasting PG 2 h PG HbA1c Fasting insulin 2 h insulin Ualb Smoking

0.029 0.658a Ð Ð Ð Ð Ð Ð Ð Ð Ð Ð Ð Ð Ð

70.676 1.451 Ð Ð Ð Ð Ð Ð Ð Ð Ð Ð Ð Ð Ð

< 0.001 < 0.001 Ð Ð Ð Ð Ð Ð Ð Ð Ð Ð Ð Ð Ð

0.167a 0.080 Ð Ð 0.031a 0.015 Ð 0.021a 0.064a 0.094a 0.042a Ð Ð 0.011a 0.016a

69.49 735.73 Ð Ð 3.243 2.094 Ð 2.545 4.376 12.716 2.709 Ð Ð 2.340 101.87

< 0.001 < 0.001 Ð Ð < 0.001 < 0.001 Ð < 0.001 < 0.001 < 0.001 < 0.001 Ð Ð 0.001 < 0.001

Ð 0.256 0.096a 0.141a Ð 0.169a 0.138a Ð Ð 0.004 Ð 0.299a 0.144a Ð Ð

Ð 1.130 0.529 0.440 Ð 0.029 70.015 Ð Ð 0.037 Ð 0.034 0.040 Ð Ð

Ð < 0.001 < 0.001 < 0.001 Ð < 0.001 < 0.001 Ð Ð 0.017 Ð < 0.001 < 0.001 Ð Ð

Women: Age Hip circumference Systolic BP Diastolic BP Cholesterol Triglyceride HDL LDL Fasting PG 2 h PG HbA1c Fasting insulin 2 h insulin Ualb Smoking

0.013 0.727a Ð Ð Ð Ð 0.146a Ð Ð Ð Ð Ð Ð Ð Ð

70.520 1.414 Ð Ð Ð Ð 70.041 Ð Ð Ð Ð Ð Ð Ð Ð

< 0.001 < 0.001 Ð Ð Ð Ð < 0.001 Ð Ð Ð Ð Ð Ð Ð Ð

0.352a 0.061 0.135a Ð 0.041a 0.164a 0.014 0.103a Ð 0.061 0.054a Ð 0.033a Ð Ð

94.36 733.10 93.68 Ð 3.209 3.858 71.059 4.778 Ð 5.337 3.265 Ð 2.614 Ð Ð

< 0.001 < 0.001 < 0.001 Ð < 0.001 < 0.001 0.001 < 0.001 Ð 0.023 < 0.001 Ð < 0.001 Ð Ð

0.010 0.206 Ð 0.114a Ð 0.011 Ð Ð 0.121a 0.138a Ð 0.205a Ð 0.017a Ð

0.227 1.231 Ð 0.404 Ð 0.014 Ð Ð 0.036 0.083 Ð 0.032 Ð 0.018 Ð

< 0.001 < 0.001 Ð < 0.001 Ð 0.002 Ð Ð < 0.001 < 0.001 Ð < 0.001 Ð < 0.001 Ð

Dependent variable

R

2

WC

2

2

R

b

p

Independent variables: BMI, WHR and WC. the ®rst independent variable which enters the regression analysis. BP: blood pressure; HDL: high-density lipoprotein; LDL: low-density lipoprotein; PG: plasma glucose; HbA1c: glycated haemoglobin; Ualb: spot urine albumin.

a

insulinaemia and glucose intolerance.1,6±14 Although there are many methods to assess the amount of adipose tissue and its distributions, anthropometric measurement remains the most widely used method in clinical practice. BMI is often used to re¯ect general obesity while WHR, and more recently WC and abdominal sagittal diameter, are used as markers of central adiposity.5,14 In this study, we found close associations between BMI, WHR and WC with multiple cardiovascular factors, analysed either as continuous variables or in quartiles. Furthermore, most of

these relationships were independent of age and smoking, and were non-linear with some of the risk factors increasing markedly in the top quartile. According to the National Diabetes Data Group criteria,23 obesity was de®ned as a BMI 25 kg/m2 in women and 27 kg/m2 in men. In this study population, obesity was more prevalent in women, 27.9% (n 168) of whom had a BMI greater than 25 kg/m2. On the other hand, only 10% (n 91) of men had a BMI greater than 27 kg/m2. More recently, in the USA, the National Health and Nutrition Examination


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Survey24 de®ned overweight as a BMI 27.8 kg/m2 for men and 27.3 kg/m2 for women. Using this de®nition, 33% of US adults aged 20 y were considered to be overweight. However, in this study, only 14.1% (n 85) of female subjects had a BMI 27 kg/ m2 giving a total of 11.6% of the subjects with a BMI 27 kg/m2. Only 2.2% (n 20) of men and 4.8% (n 29) of women had severe obesity as de®ned by a BMI 30 kg/m2. Hence, compared to the Americans, Asian populations such as the Chinese, are often considered as non-obese populations. Compared to Caucasians, Chinese subjects also had less central adiposity. In one UK study,25 the mean WHR and WC were 0.93 and 93.3 cm in Caucasian men, 0.80 and 82.0 cm in Caucasian women, respectively. These ®gures are much higher than that reported in the present study (Table 1). In addition, using WHR of 0.95 for men and 0.80 for women as cut-off values, 37.6% of men and 48.2% of women in the UK were centrally obese,25 while 9.3% of men and 48.1% of women in our study were centrally obese. Similarly, using WC of 94 cm for men and 80 cm for women as cut-off values, 46.7% of men and 50.9% of women in UK,25 as compared with 4.5% of men and 25.5% of women in our study were centrally obese. Despite the apparently lower prevalence of obesity in our population, when compared to Caucasians, our data clearly show that as BMI, WHR and WC increase, cardiovascular risks also increase. Prospective studies are required to examine the relationships between these associations and subsequent clinical events. Nevertheless, using the widely accepted WHO criteria, subjects in the top quartile of obesity had the highest prevalence of glucose intolerance,22 hypertension21 and an atherogenic lipid pro®le.26 These ®ndings therefore emphasise the importance of establishing epidemiological data in different racial groups for more valid assessment of cardiovascular risks. There are now much data to con®rm the importance of central adiposity as a cardiovascular risk factor.5,15,16,27 This is mainly due to the increased lipolytic activity of visceral adipose tissue which can lead to increased production of free fatty acids. The latter can induce insulin resistance by enhancing gluconeogenesis and reducing glucose uptake in muscle with metabolic and vascular consequences.28 In one study, after adjustment for age, BMI and plasma lipid, WHR remained a signi®cant factor in both Caucasian men and women con®rmed angiographically to have coronary atherosclerosis.29 In another study, abdominal sagittal diameter used as a marker for central adiposity, explained most of the variations in cardiovascular risk factors. The effects of general obesity (BMI) on these factors disappeared when abdominal obesity was taken into account.16 Other workers have also reported independent associations between central obesity and blood pressure, plasma lipid and glucose concentrations in Caucasians,30,31

Chinese32 and Japanese.9 In agreement with these studies, we also found that most of the variance in cardiovascular risk factors were explained either by WC or WHR. However, BMI remained an important explanatory variable for reduced HDL in women. Despite the close associations between central adiposity and cardiovascular risks,27 there remains some controversy regarding the best anthropometric index of central adiposity. Some workers have shown that WC was a better correlate of cardiovascular risk factors, including BP and lipid parameters, than WHR.31 Using computed tomographic scanning to measure adipose tissues, WC and abdominal sagittal diameter were found to be better correlates of abdominal visceral adipose accumulation than the WHR.5 Similarly, in another study, WC and age predicted 74% while WHR, abdominal sagittal diameter and age explained 76.6% of the variance in the amount of deep abdominal adipose tissue.33 WC and abdominal sagittal diameter were also more closely related to cardiovascular risk factors including plasma TG, HDL, insulin and glucose as compared to WHR, especially in women.5 In agreement with these ®ndings, our results also support the superior effects of WC and WHR over BMI in terms of correlation with risk factors. In men, central adiposity as re¯ected by WC, and to some extent, WHR, explained most of the variance in blood pressure, plasma glucose, lipid, insulin and albuminuria. However, BMI re¯ecting general obesity also provides important information, especially in women, where BMI was the major explanatory variable for the reduced HDL. We have previously reported34 that WC was not a sensitive measurement to detect obesity, as de®ned by BMI and WHR, in Chinese. However, the present analysis shows that WC itself is informative on health risk. As in most studies,1,7,8 all three anthropometric indexes provide useful information on cardiovascular risks, although with varying degrees of importance. We suggest that in the initial assessment of cardiovascular risks, WC, WHR and BMI should all be documented.

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