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Prevalence of metabolic syndrome and optimal waist circumference cut-off points for adults in Beijing
diabetes research and clinical practice 88 (2010) 209–216
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Diabetes Research and Clinical Practice journ al h omepage: www .elsevier.co m/lo cate/diabres
Prevalence of metabolic syndrome and optimal waist circumference cut-off points for adults in Beijing Wei Wang a,2, Yanxia Luo a,2, Yunning Liu a, Can Cui b, Lijuan Wu a, Youxin Wang a, Hong Wang a, Puhong Zhang c,d,1,*, Xiuhua Guo a,* a
Department of Epidemiology and Health Statistics, School of Public Health and Family Medicine, Capital Medical University, Beijing 100069, China b School of Statistics, Southwestern University of Finance and Economics, Cheng Du 611130, Sichuan, China c Institute of Chronic and Noncommunicable Disease Control and Prevention, Beijing Center for Disease Control and Prevention, Beijing 100013, China d School of Public Health and Family Medicine, Capital Medical University, Beijing 100069, China
article info
abstract
Article history:
Background: In the modified ATP III definition for metabolic syndrome (MS), the cut-off
Received 11 October 2009
values for central obesity were set to 90 cm for male and 80 cm for women. Recently, a
Received in revised form
new Chinese definition for central obesity was set to 90 cm for male and 85 cm for
11 January 2010
women according to the corresponding BMI value of 25 kg/m2.
Accepted 18 January 2010
Objective: The purpose of this study was to explore the optimal WC cut-off points to reflect
Published on line 11 February 2010
the cluster of multiple risk factors for adults in Beijing. Method: The data collected during the surveillance of risk factors for non-communicable
Keywords:
diseases in Beijing 2005 were used, with a total of 16,711 adults studied. Subjects with two or
Waist circumference
more components from the modified ATP III definition other than central obesity were
Cut-off point
considered to have multiple risk factors.
Metabolic syndrome
Results: The optimal WC cut-off points were 87 cm in men and 80 cm for women. When
Central obesity
applied the WC advised definition for MS, the age-standardized prevalence was 38.0% for
Chinese
male and 32.3% for women, which is significantly higher than using the original one for men (34.7% vs 32.3%, P < 0.001). Conclusion: The present study indicated that optimal waist circumference cut-off points were lower than that proposed in the modified ATP III definition, especially for men. # 2010 Published by Elsevier Ireland Ltd.
1.
Introduction
Metabolic syndrome (MS) is a cluster of multiple, interrelated risk factors of metabolic origin that appear to directly promote the development of atherosclerotic cardiovascular disease such as diabetes and prediabetes, abdominal obesity, high cholesterol, low HDL-C and high blood pressure. It is not clear
whether the MS has a single cause, but the most important of these underlying risk factors are abdominal obesity and insulin resistance [1]. It is generally believed that metabolic syndrome contributes to the onset of cardiovascular disease (CVD) and type 2 diabetes mellitus, and has prognostic value for CVD mortality [2–4]. Ever since the concept of that syndrome was recommend by Reaven [5], many diagnostic
* Corresponding author. Tel.: +86 1083911508; fax: +86 1083911508. E-mail address: [email protected] (X. Guo). 1
Now: National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050, China. Wei Wang and Yanxia Luo are joint first authors. They contributed equally to the work. 0168-8227/$ – see front matter # 2010 Published by Elsevier Ireland Ltd. doi:10.1016/j.diabres.2010.01.022 2
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diabetes research and clinical practice 88 (2010) 209–216
criteria have been proposed. The WHO definition [6], IDF definition [7], NCEP ATP III [8] and the modified ATPIII definition [1] were relatively world-wide applied ones. The consensus for the pathophysiology of MS was arrived on insulin resistance, therefore the importance of central obesity was established. In 2005, the International Diabetes Federation (IDF) in a global consensus statement formulated a new, clinically accessible worldwide definition of metabolic syndrome [7], based on the definition announced by WHO in 1999 [6]. Meanwhile, in an AHA/NHLBI scientific statement, the modified ATPIII definition for MS was released [1], with ethnicity-specific criteria for central obesity and a significantly lowered threshold for glucose than the criteria released in 2001 [8]. Besides, individuals treated for dyslipidemia, hypertension or hyperglycaemia were also included. There used to be only one definition for obesity and central obesity. However, there were evidence indicating that using these would severely underestimate the actual prevalence of obesity and abdominal obesity in the east [9]. The WHO experts then concluded that the proportion of Asian people at high risk for cardiovascular disease is substantial at BMI values lower than the existing WHO cut-off point for overweight [10]. With the same reason, the modified ATPIII definition for metabolic syndrome adopted ethnicity—specific cut-off points for central obesity [1]. The report of International Obesity Task Force proposed the WC values of 90 cm for men and 80 cm for women as Asian-specific WC cut-off points for central obesity [11] and this was adopted in the modified ATP definition and IDF definition [1,7]. A study involving 3289 persons 50–70 years old from Beijing or Shanghai showed that the association between MS and obesity is greater in overweight or obese people in the north than the south [12]. The InterASIA collaborative group’s investigation also showed that the age-standardized prevalence of MS, its components and overweight was higher in the north than in the south [13]. It might indicated that the WC cut-off values be specific not only for gender and ethnicity but also for region. However, as a consequence, it was almost impossible to compare the worldwide prevalence of MS. The Asian-specific central obesity diagnostic criteria were adopted in IDF definition and modified ATPIII definition, however, a new but not universally approved Chinese definition for MS set the cut-off points to 90 cm for men and 85 cm for women based on the findings that 90 cm for men and 85 cm for women were the corresponding waist circumference for a BMI value of 25 kg/m2, which was the cut-off point for BMI in the CDS definition [14] for metabolic syndrome [15]. In The Guide for Prevention and Control for Overweight and Obesity in Chinese Adults, the cut-off value of WC was found at 85 cm for men and 80 cm for women [16]. In all, there seemed to be at least three definitions for central obesity in China, they were set up from different prospective however failed to come to an agreement. Although, several criteria for central obesity were established from many perspectives for Chinese, the results were somewhat not in accordance. Using the results obtained from the surveillance of risk factors for non-communicable diseases in Beijing 2005, the present study examined the prevalence of each parameter and MS when the modified ATP III definition was employed. The validity of the waist
circumference cut-off values in the modified ATP III definition was tested based on an accumulation of these risk factors.
2.
Methods
2.1.
Study population
The Beijing Municipal Health Bureau and the centers for disease control and prevention (CDC) in Beijing conducted the surveillance of risk factors for non-communicable diseases in Beijing 2005 [17]. A proportional multistage cluster random sampling design was used to select subjects aged over 18 and having lived in Beijing for more than 6 months, including residents of communities and employees of companies. We selected no more than one subject from one household. If there are two people meet our requirement, the date of the their birthday was extracted. The one with smaller number of day was engaged in the survey. For two men with the birthday of Jan 1, 1969 and Sep 15, 1986, the older men would be selected. Qualified subjects were selected randomly in companies so that the subjects are relatively concentrated and convenient to be surveyed. In total, 16,711 persons from 53 living communities and 106 functional communities were identified to participate in the survey. Anthropometric measurements were missing for 118 persons. Therefore, complete information was obtained in 16,593 (99.3%) participants (male, 44.96 14.52 years; women, 45.31 13.70 years; gender ratio: women/male, 1.53), which is similar to that of the initial 16,711 individuals recruited for the survey (male, 44.96 14.48 years; women 45.32 13.71 years; gender ratio: women/male, 1.51).
2.2.
Content and methods
The present study was a cross-sectional survey conducted from August to September in 2005, which applied questionnaires, physical test, blood pressure measurement and laboratory examination. The questionnaire included demographic status like age, gender and educational background; risk factors of chronic diseases such as smoking, alcohol intake, diet and physical exercise; prevalence of chronic diseases including hypertension, diabetes, dyslipidemia and overweight. Physicians and public health nurses were in charge of the physical test. Height and body weight were measured in the upright position to the nearest 0.5 cm and 0.1 kg, respectively. The WC measurements were taken at the end of normal expiration and to the nearest 0.1 cm, measuring from the midpoint between the lower borders of the rib cage and the anterior superior iliac spine. Electronic sphygmomanometers were used to measure the blood pressure of each subject in the sitting position after a 10-min rest period. During the 30 min preceding the measurement, the subjects were required to refrain from smoking or consuming caffeine. Three readings each of systolic and diastolic blood pressures were recorded, with an interval of 30 s at least, and the average of each measurement was used for data analysis. Blood samples were obtained from antecubital vein into tubes containing EDTA in the morning after an overnight fasting period. The samples were subsequently analyzed at eight
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certified laboratories. Laboratory test includes fasting plasma glucose, total cholesterol, TG, HDL-C, LDL-C and creatinine, using autoanalyzers (Hitachi 7170; Hitachi, Tokyo, Japan).
2.3.
Diagnostic criteria for MS
We largely adopted the criteria for metabolic risk factors proposed by the modified ATP III definition [1]: elevated triacylglycerol, 1.70 mmol/L or with current lipid-lowering treatment; low HDL cholesterol, for male, HDL-C <1.03 mmol/ L or for women, HDL-C <1.30 mmol/L or with current lipidlowering treatment; elevated blood pressure, systolic 130 mmHg and or diastolic 85 mmHg or current use of antihypertensive drugs; elevated plasma glucose, patients for type 2 diabetes mellitus and/or FPG 5.6 mmol/L; and a combination of two to three of these risk factors.
2.4.
Measurement of other covariates
The measurements of other covariates and potential confounders were collected for the participants. Self-reported educational background, living site, alcohol consumption
frequency, and smoking were estimated from the questionnaire. Education level was categorized into 4 groups: 6 years, 7–9 years, 10–12 years, and >12 years. Living site was divided into rural area and urban area. The frequency for alcohol consumption in recent year was collected as never, 1–3 times/ month, 1–2 times/week, 3–5 times/week, almost everyday and more than 1 time/day. Participants were classified into three groups by their smoking status in the latest month: 1 cigarette/day, <1 cigarette/day, and who did not smoke (including ex-smoker and non-smoker).
2.5.
Statistical analysis
A database was established by EpiData 3.02 software. The statistical analyses were carried out using Statistical Package of Social Science for Windows version 13.0 (SPSS Inc., Chicago, IL, USA). Continuous variables were expressed as means and standard deviations, and discrete variables were presented as proportions. The sensitivity and specificity of each WC category (or take WC as a continuous variable) in detecting the presence of low HDL-C, elevated triacylglycerol, blood pres-
Table 1 – Basic characteristics of the study population for the surveillance of risk factors for non-communicable diseases in Beijing 2005. Men (n = 6567)
Women (n = 10,026)
44.96 14.52
45.31 13.70
45.17 14.03
Living site Urban area (%) Rural area (%)
3907 (59.5) 2660 (40.5)
6528 (65.1) 3498 (34.9)
10,435 (62.9) 6158 (37.1)
BMI (kg/m2)a Waist circumference (cm)a
25.16 3.52 87.61 10.12
24.51 3.78 79.71 10.44
24.77 3.70 82.84 11.01
Education level (%) 6 years 7–9 years 10–12 years >12 years
571 (8.7) 1868 (28.5) 1736 (26.5) 2372 (36.2)
1482 2643 2703 3188
2053 4511 4439 5560
Smoking (%) 1 cigarette/day <1 cigarette/day No smoker
3442 (52.4) 375 (5.7) 2748 (41.9)
394 (3.9) 105 (1.1) 9519 (95.0)
3836 (23.1) 480 (2.9) 12,267 (74.0)
Frequency for alcohol consumption (%) Never 1–3 times/month 1–2 times/week 3–5 times/week Almost everyday More than 1 time/day
2388 (36.4) 1263 (19.2) 1147 (17.5) 496 (7.6) 1034 (15.7) 238 (3.6)
8967 (89.6) 664 (6.6) 208 (2.1) 55 (0.5) 106 (1.1) 11 (0.1)
11,355 (68.5) 1927 (11.6) 1355 (8.2) 551 (3.3) 1140 (6.9) 249 (1.5)
87.61 10.12 2305 (35.1) 1812 (27.6) 3979 (60.7) 2012 (30.7) 3065 (46.8) 1431 (21.8)
79.71 10.44 2225 (22.2) 4224 (42.1) 4556 (45.5) 2554 (25.5) 3905 (39.0) 1948 (19.4)
82.84 11.01 4530 (27.3) 6036 (36.4) 8535 (51.5) 4566 (27.5) 6970 (42.1) 3379 (20.4)
Age (year)
a
(14.8) (26.4) (27.0) (31.8)
Total (n = 16,593)
(12.4) (27.2) (26.8) (33.6)
Metabolic risk factors (%)b Waist circumference (cm)a Elevated triacylglycerol Low HDL cholesterol Elevated blood pressure Elevated fasting plasma glucose 2 Risk factors 3 Risk factors a b
The values are presented as means S.D. Metabolic risk factors were defined according to ATP III revised criteria and were above described.
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sure, and fasting plasma glucose; and two to three risk factors were calculated by creating dichotomous variables for each WC value. Additionally, the receiver operating characteristic (ROC) curve was used for each WC value by plotting the truepositive rate (sensitivity) against the false-positive rate (1specificity). The Youden’s index, that is sensitivity + specificy1, was used to determine the optimal WC cut-off points. To identify the optimal WC values to reflect the cluster of metabolic risk factors in men and women, the odds ratios (OR) were calculated by multiple logistic regression analysis with adjustments for age group, living area, smoking status, and alcohol consuming frequencies. The WC values were categorized by 5 cm increments, with <80 cm for men or <75 cm for women as referents. The adjusted ORs were presented together with their 95%CI. The linear trend in ORs across WC categories was evaluated using the likelihood ratio test. All probability values presented were for two-tailed tests, the values of P < 0.05 were considered to indicate statistical significance.
3.
Results
3.1.
Basic characteristics of the subjects
and 42.1% of women; elevated blood pressure was observed in 60.7% of men and 45.5% of women; elevated fasting plasma glucose was seen in 30.7% of men and 25.5% of women. The cluster of two or more metabolic risk factors was detected in 46.8% of men and 39.0% of women, while the cluster of three or more metabolic risk factors was present in 21.8% of men and 19.4% of women. The prevalence for MS with the definition of the modified ATP III definition was 34.7% for men and 32.3% for women, after adjusting for age, while the total was 28.5% after adjusting for gender and age.
3.2. Metabolic risk factors according to waist circumference category When categorized by waist circumference, low HDL cholesterol; elevated plasma triacylglycerol, blood pressure and fasting plasma glucose showed higher prevalence in categories of higher waist circumference values for both men and women (Table 2).
3.3. Cut-off points of waist circumference for predicting the cluster of metabolic risk factors analyzed by adjusted odds ratios
The basic characteristics of the subjects and the prevalence of metabolic risk factors were shown in Table 1. The mean age of all participants was 45.17 years, and the mean BMI value was 24.77. The mean value for waist circumference was 87.61 cm in men and 79.70 cm in women. 59.5% of men and 65.1% of women lived in rural area, while 40.5% of men and 34.9% of women lived in rural area. About 52.4% of men smoked more than one cigarette per day, while 41.9% of men did not smoke in a month. The majority of women, that is 95.0%, did not smoke in a month. 89.6% of women never drank alcohol in the recent year, while for men the number was 36.4%. Elevated triacylglycerol was seen in 35.1% of men and 22.2% of women; low HDL cholesterol was detected in 27.6% of men
With 75 cm for women and 80 cm for men as reference, the presence of metabolic risk factors and the adjusted odds ratios according to WC values categorized by 5-cm increments in men and women are shown in Table 3. The cluster of metabolic risk factors was more obvious in categories of higher waist circumference for both men and women (P < 0.001 for trend).
3.4. Cut-off points of waist circumference for predicting clusters of metabolic risk factors analyzed by ROC curve The 80th percentile for WC values was approximately 96.0 cm in men and 88.5 cm in women. The optimal waist circumference cut-off point was estimated by the ROC curve analysis
Table 2 – Prevalence and adjusted odds ratiosa of metabolic risk factors according to waist circumference category. Waist Case circumference number category (cm)
Elevated triacylglycerol N
OR (95%CI)
Low HDL cholesterol N
OR (95%CI)
Elevated blood pressure N
OR (95%CI)
Elevated fasting plasma glucose N
OR (95%CI)
Men <80 80–85 85–90 90–95 95
1498 1000 1232 1219 1618
155 241 435 549 925
1.00 2.77 4.75 7.10 11.66
(2.22–3.46) (3.87–5.84) (5.78–8.71) (9.57–14.21)
211 189 322 413 677
1.00 1.48 2.30 3.46 4.83
(1.19–1.84) (1.90–2.81) (2.85–4.20) (4.02–5.80)
535 531 772 838 1303
1.00 1.67 2.27 2.97 5.56
(1.41–1.99) (1.93–2.68) (2.51–3.52) (4.70–6.59)
255 273 365 418 701
1.00 1.55 1.57 1.97 2.84
(1.27–1.89) (1.30–1.90) (1.64–2.37) (2.39–3.37)
Women <75 75–80 80–85 85–90 90
3535 1775 1746 1240 1730
216 317 465 456 771
1.00 2.73 4.14 5.90 7.18
(2.26–3.29) (3.47–4.95) (4.90–7.10) (6.02–8.58)
925 722 863 688 1026
1.00 2.10 3.08 4.10 5.01
(1.85–2.37) (2.72–3.49) (3.55–4.73) (4.37–5.75)
704 680 926 860 1386
1.00 1.81 2.88 4.93 7.24
(1.58–2.08) (2.52–3.30) (4.21–5.77) (6.20–8.46)
391 353 516 455 839
1.00 1.53 2.34 2.79 3.93
(1.30–1.80) (2.01–2.73) (2.36–3.29) (3.37–4.58)
a
Adjusted for age group, living site, smoke status and alcohol consuming frequency in recent year and using the data of the surveillance of risk factors for non-communicable diseases in Beijing 2005.
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Table 3 – Prevalence and adjusted odds ratiosa of cluster of metabolic risk factorsb according to waist circumference category. Waist circumference category (cm)
Case number
1 Risk factor N
2 Risk factors
OR (95%CI)
N
OR (95%CI)
3 Risk factors N
OR (95%CI)
Men <80 80–85 85–90 90–95 95
1498 1000 1232 1219 1618
815 736 1012 1083 1534
1.00 1.94 2.92 5.04 11.22
(1.61–2.32) (2.42–3.52) (4.07–6.23) (8.75–14.39)
268 358 573 703 1163
1.00 2.28 3.37 5.32 9.81
(1.89–2.75) (2.82–4.02) (4.45–6.36) (8.24–11.68)
58 115 242 334 682
1.00 2.99 5.39 8.34 15.91
(2.15–4.15) (4.00–7.28) (6.22–11.19) (11.99–21.11)
Women <75 75–80 80–85 85–90 90
3535 1775 1746 1240 1730
1660 1221 1433 1107 1641
1.00 1.99 3.72 5.88 11.43
(1.75–2.25) (3.22–4.30) (4.82–7.17) (9.06–14.43)
435 572 844 773 1281
1.00 2.70 4.80 7.42 11.03
(2.33–3.12) (4.16–5.53) (6.33–8.71) (9.44–12.89)
116 229 384 431 788
1.00 3.45 5.95 9.87 13.47
(2.73–4.37) (4.77–7.42) (7.88–12.37) (10.85–16.72)
a Adjusted for age group, living area, smoke status and alcohol consuming status and using the data of the surveillance of risk factors for noncommunicable diseases in Beijing 2005. b Metabolic risk factors were defined according to ATP III revised criteria and were above described.
based on subjects who fulfilled at least two of the modified ATP III definition for MS (Fig. 1). It turned out that 79.95 cm for women and 86.95 cm for men were the values (Table 4). Based on these findings, the optimal cut-off points for waist circumference were 80 cm for women and 87 cm for men.
lower (P < 0.001) for men. The total prevalence for MS with the modified ATP III definition and the revised modified ATP III definition, after standardized for gender and age was 28.5% and 30.0% respectively.
3.5. Prevalence of MS using the calculated waist circumference cut-off points in the modified ATP III definition for MS
4.
When the criteria for central obesity were set to 87 cm in men and 80 cm for women, and those for others remained the same, age-standardized the prevalence of MS using the revised modified ATP III definition was 38.0% for men and 32.3% for women. Without the revise, the prevalence of MS was 34.7% in men and 32.3% for women, which is significantly
Discussion
Many researches were accomplished as to the optimal cut-off points for WC with various outcome variables. A study of 31,076 Korean adults showed that the cut-off values for detecting myocardial ischemia was 87 cm for men and 74 cm for women, for detecting multiple risk factors for metabolic syndrome it was 83 cm for men and 76 cm for women [18]. For Japanese, using the criteria of Japanese Society of Internal Medicine, the points were not consistent: One research
Fig. 1 – Estimation by ROC curve analysis of the waist circumference cut-off points to predict the cluster of at least two metabolic risk factors using the data of the surveillance of risk factors for non-communicable diseases in Beijing 2005. Metbolic risk factors were defined according to ATP III revised criteria and were above described.
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diabetes research and clinical practice 88 (2010) 209–216
Table 4 – The sensitivity, specificity, and Yuden Index for detecting clusters of at least two metabolic risk factors for each WC cut-off points (the risk factors for non-communicable diseases surveillance in Beijing, 2005). Gender
WC cur-off points (cm)
Sensitivity
Specificity
Men
86.45 86.55 86.65 86.75 86.85 86.95 87.05 87.15 87.25 87.35 87.45
0.7374 0.7321 0.7315 0.7308 0.7308 0.7305 0.7100 0.7083 0.7047 0.7041 0.7018
0.6051 0.6114 0.6131 0.6143 0.6149 0.6163 0.6329 0.6341 0.6375 0.6392 0.6407
0.3425 0.3436 0.3446 0.3451 0.3457 0.3468 0.3429 0.3424 0.3422 0.3433 0.3425
Women
79.45 79.55 79.65 79.75 79.85 79.95 80.05 80.15 80.25 80.35 80.45
0.7488 0.7447 0.7442 0.7437 0.7424 0.7421 0.7129 0.7096 0.7076 0.7060 0.7029
0.6937 0.6979 0.6996 0.7004 0.7015 0.7030 0.7270 0.7287 0.7306 0.7311 0.7331
0.4425 0.4426 0.4437 0.4440 0.4439 0.4451 0.4400 0.4383 0.4382 0.4372 0.4360
reported that the values were 89.8 cm for men and 82.3 cm for women [19]. Another report from Hisayama Study showed the cut-off values as 90 cm for men, 80 cm for women to better predict CVD in general Japanese population in a 14 year followup study [20]. In China, it was reported that for adults in Shanghai the optimal cut-off points for WC were 90 cm for men and 85 cm for women [21]. For a study involving 101,510 employees in Tangshan city in the central north area of China, the cut-off values were 86.5 cm for men and 82.1 cm for women [22]. For a nationally representative sample in a crosssectional study, the cut-off point turned to be 80 cm for both genders [23]. The results were not in agreement. Moreover, few follow-up studies were found so far as to explore the optimal cut-off points for waist circumference in China. Only the result form a 7.3 years’ cohort in the Shanghai Women’s Health Study showed that the optimal cut-off point for women was 84.1 cm for predicting stroke [24]. In our study, the 80th percentile for WC values was 96 cm in men and 88.5 cm in women. The ROC curve analysis indicated that 87 cm for men and 80 cm for women were the optimal cut-off points. It is interesting to note that the mean and median values for sex-specific waist circumference were similar with our optimal points, 80 cm for women or 87 cm for men. The 80th percentile for WC values was fairly higher than our calculated cut-off points for WC. There were 4859 persons (29.3% for all, 33.0% for men and 26.8% for women) with a WC value within the area. They were the ones with high risks to develop metabolic syndrome. It is interesting to note that 35% of men and 22% of women had hypertriglyceridemia, but the prevalence of low HDL-C in men is 27.6% vs 42% in women. Elevated blood pressure was observed in 60.7% of men and 45.5% of women. Several researches reported could be served as reference. In a workforce survey including 101,510 employees in Tangshan (a city 150 km southeast of Beijing), with similar age coverage
Youden’s index
but more men subjects, they reported 31.7% of men and 26.8% of women with hypertriglyceridemia, 6.9% of men and 20.1% of women with low HDL-C, 56.3% of male and 40.1% of women were with elevated blood pressure [22]. In a community-based study involving 2334 aging subjects in Beijing showed that 22.6% of men and 34.1% of women were with hypertriglyceridemia, 16.4% of men and 36.3% of women were with low HDLC, 73.5% of men and 73.3% of women were with elevated blood pressure [25]. Although, for national representatives, the prevalence of hypertension (140/90 mmHg) is 20% for men and 18% for women who were aged over 18 and participated in the China National Nutrition and Health Survey 2002 [26] or 27.2% for adult population from 35 to 74 years old in 2001 [27], the prevalence of hypertension in Beijing is the most serious in provincial capital in China with a rate of 25% for people over 15 years old [28]. In our study the rate for hypertension is 38.3% for men vs 36.7% for women. In all, the prevalence of metabolic disorders was higher than that reported, which might be explained by the different gender ratio, urban/rural ratio or sampling procedure in our study. As to the rate of hypertriglyceridemia and low HDL-C, the specific medicine which the subjects take for blood lipid adjustment was not recorded in our questionnaire, therefore, a person with lipidlowering treatment was considered to have low HDL-C and elevated triacylglycerol. In all, our analysis suggested that the optimal WC cut-off points to reflect the cluster of at least 2 metabolic risk factors were 87 cm for men and 80 cm for women, which was different from the original criteria in the modified ATPIII definition. The prevalence of MS defined by the WC revised modified ATPIII definition were 38.0% for men and 32.3% for women, which is significantly higher then using the original one in men (34.7%). A limitation of this study is its cross-sectional sample population, and the definition of elevated triacylglycerol and
diabetes research and clinical practice 88 (2010) 209–216
low HDL-C. However, this was a relatively representative sample of the general adult population in Beijing. Though the outcome variables were more likely to be insulin resistance, stroke or cardiovascular disease in western world [29,30], there were few similar studies in Chinese population to explore the optimal cut-off points for waist circumference. Further studies as to the optimal WC cut-off points in a representative sample of the adult Chinese population to predict the incidence of insulin resistance, cardiovascular diseases morbidity and mortality, and all-cause mortality are needed prospectively.
Conflict of interest
[10]
[11]
[12]
[13]
All the authors have no conflict of interest. [14]
Acknowledgements This study was funded by Beijing Municipal Health Bureau. The authors are grateful to the Chronic Disease Department for Centers of Disease Control and Prevention (CDC) in eighteen districts for their contribution to coordinating with local government and implementing the investigation in the community.
[15]
[16]
references [17]
[1] S.M. Grundy, J.I. Cleeman, S.R. Daniels, K.A. Donato, R.H. Eckel, B.A. Franklin, et al., Diagnosis and management of the metabolic syndrome: an American heart association/ national heart, lung, and blood institute scientific statement, Circulation 112 (2005) 2735–2752. [2] H.M. Lakka, D.E. Laaksonen, T.A. Lakka, L.K. Niskanen, E. Kumpusalo, J. Tuomilehto, et al., The metabolic syndrome and total and cardiovascular disease mortality in middleaged men, JAMA 288 (2002) 2709–2716. [3] M.E. Safar, F. Thomas, J. Blacher, R. Nzietchueng, J.M. Bureau, B. Pannier, et al., Metabolic syndrome and agerelated progression of aortic stiffness, J. Am. Coll. Cardiol. 47 (2006) 72–75. [4] K.C. Sung, S. Ryu, G.M. Reaven, Relationship between obesity and several cardiovascular disease risk factors in apparently healthy Korean individuals: comparison of body mass index and waist circumference, Metabolism 56 (2007) 297–303. [5] G.M. Reaven, Banting lecture 1988. Role of insulin resistance in human disease, Diabetes 37 (1988) 1595–1607. [6] World Health Organization, Definition, diagnosis and classification of diabetes mellitus and its complication, report of a WHO consultation, part I: diagnosis and classification of diabetes mellitus, Geneva, 1999. [7] K.G. Alberti, P. Zimmet, J. Shaw, The metabolic syndrome— a new worldwide definition, Lancet 366 (2005) 1059–1062. [8] Executive summary of the third report of the national cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III), JAMA 285 (2001) 2486–2497. [9] P. Deurenberg, M. Deurenberg-Yap, S. Guricci, Asians are different from Caucasians and from each other in their
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25]
215
body mass index/body fat percent relationship, Obes. Rev. 3 (2002) 141–146. WHO consultation, Expert appropriate body-mass index for Asian populations and its implications for policy and intervention strategies, Lancet 363 (2004) 157–163. The World Health Organization Western Pacific Region, the International Association for the Study of Obesity, the International Obesity Task Force, The Asia-Pacific perspective: redefining obesity and its treatment, health, communications, Australia Melbourne, 2000. Z. Yu, X. Lin, J.D. Haas, O.H. Franco, K.L. Rennie, H. Li, et al., Obesity related metabolic abnormalities: distribution and geographic differences among middle-aged and older Chinese populations, Prev. Med. 48 (2009) 272–278. D. Gu, K. Reynolds, X. Wu, J. Chen, X. Duan, R.F. Reynolds, et al., Prevalence of the metabolic syndrome and overweight among adults in China, Lancet 365 (2005) 1398–1405. Expert panel on metabolic syndrome of Chinese diabetes society, Recommendations on metabolic syndrome of Chinese diabetes society, Chin. J. Diabetes 12 (2004) 156–161. Joint Committee for Developing Chinese Guidelines on Prevention and Treatment of Dyslipidemia in Adults. Chinese guidelines on prevention and treatment of dyslipidemia in adults. Zhonghua Xin Xue Guan Bing Za Zhi 35 (2007) 390–419. B.F. Zhou, Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults—study on optimal cut-off points of body mass index and waist circumference in Chinese adults, Biomed. Environ. Sci. 15 (2002) 83–96. X.H. Guo, P.H. Zhang, Z.C. Zeng, W. Wang, C. Li, Y. Shi, et al., Combination patterns of cardiovascular risks and sequelae at different stage of hypertension in natural hypertensive population in Beijing, Clin. Exp. Hypertens. 31 (2009) 142–155. H.K. Kim, C.H. Kim, J.Y. Park, K.U. Lee, Lower waistcircumference cutoff point for the assessment of cardiometabolic risk in Koreans, Diabetes Res. Clin. Pract. 85 (2009) 35–39. R. Oka, J. Kobayashi, K. Yagi, H. Tanii, S. Miyamoto, A. Asano, et al., Reassessment of the cutoff values of waist circumference and visceral fat area for identifying Japanese subjects at risk for the metabolic syndrome, Diabetes Res. Clin. Pract. 79 (2008) 474–481. Y. Doi, T. Ninomiya, J. Hata, K. Yonemoto, H. Arima, M. Kubo, et al., Proposed criteria for metabolic syndrome in Japanese based on prospective evidence: the Hisayama study, Stroke 40 (2009) 1187–1194. Y. Bao, J. Lu, C. Wang, M. Yang, H. Li, X. Zhang, et al., Optimal waist circumference cutoffs for abdominal obesity in Chinese, Atherosclerosis 201 (2008) 378–384. F. Wang, S. Wu, Y. Song, X. Tang, R. Marshall, M. Liang, et al., Waist circumference, body mass index and waist to hip ratio for prediction of the metabolic syndrome in Chinese, Nutr. Metab. Cardiovasc. Dis. 19 (2009) 542–547. R.P. Wildman, D. Gu, K. Reynolds, X. Duan, J. He, Appropriate body mass index and waist circumference cutoffs for categorization of overweight and central adiposity among Chinese adults, Am. J. Clin. Nutr. 80 (2004) 1129–1136. X. Zhang, X.O. Shu, Y.T. Gao, G. Yang, H. Li, W. Zheng, General and abdominal adiposity and risk of stroke in Chinese women, Stroke 40 (2009) 1098–1104. Y. He, B. Jiang, J. Wang, K. Feng, Q. Chang, L. Fan, et al., Prevalence of the metabolic syndrome and its relation to
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cardiovascular disease in an elderly Chinese population, J. Am. Coll. Cardiol. 47 (2006) 1588–1594. [26] D. Gu, K. Reynolds, X. Wu, J. Chen, X. Duan, P. Muntner, et al., Prevalence, awareness, treatment, and control of hypertension in China, Hypertension 40 (2002) 920–927. [27] Y. Wu, R. Huxley, L. Li, V. Anna, G. Xie, C. Yao, et al., Prevalence, awareness, treatment, and control of hypertension in China: data from the China national nutrition and health survey 2002, Circulation 118 (2008) 2679–2686.
[28] X.H. Pang, S.F. Jiao, L. Huang, J.L. Duan, Z.Y. Ren, Z.J. Liu, Nutrition and health status of the Beijing residents, Chin. J. Prev. Med. 29 (2005) 269–272. [29] C. Zhang, K.M. Rexrode, R.M. van Dam, T.Y. Li, F.B. Hu, Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: sixteen years of follow-up in us women, Circulation 117 (2008) 1658–1667. [30] A. Koster, M.F. Leitzmann, A. Schatzkin, T. Mouw, K.F. Adams, J.T. van Eijk, et al., Waist circumference and mortality, Am. J. Epidemiol. 167 (2008) 1465–1475.
Contents lists available at ScienceDirect
Diabetes Research and Clinical Practice journ al h omepage: www .elsevier.co m/lo cate/diabres
Prevalence of metabolic syndrome and optimal waist circumference cut-off points for adults in Beijing Wei Wang a,2, Yanxia Luo a,2, Yunning Liu a, Can Cui b, Lijuan Wu a, Youxin Wang a, Hong Wang a, Puhong Zhang c,d,1,*, Xiuhua Guo a,* a
Department of Epidemiology and Health Statistics, School of Public Health and Family Medicine, Capital Medical University, Beijing 100069, China b School of Statistics, Southwestern University of Finance and Economics, Cheng Du 611130, Sichuan, China c Institute of Chronic and Noncommunicable Disease Control and Prevention, Beijing Center for Disease Control and Prevention, Beijing 100013, China d School of Public Health and Family Medicine, Capital Medical University, Beijing 100069, China
article info
abstract
Article history:
Background: In the modified ATP III definition for metabolic syndrome (MS), the cut-off
Received 11 October 2009
values for central obesity were set to 90 cm for male and 80 cm for women. Recently, a
Received in revised form
new Chinese definition for central obesity was set to 90 cm for male and 85 cm for
11 January 2010
women according to the corresponding BMI value of 25 kg/m2.
Accepted 18 January 2010
Objective: The purpose of this study was to explore the optimal WC cut-off points to reflect
Published on line 11 February 2010
the cluster of multiple risk factors for adults in Beijing. Method: The data collected during the surveillance of risk factors for non-communicable
Keywords:
diseases in Beijing 2005 were used, with a total of 16,711 adults studied. Subjects with two or
Waist circumference
more components from the modified ATP III definition other than central obesity were
Cut-off point
considered to have multiple risk factors.
Metabolic syndrome
Results: The optimal WC cut-off points were 87 cm in men and 80 cm for women. When
Central obesity
applied the WC advised definition for MS, the age-standardized prevalence was 38.0% for
Chinese
male and 32.3% for women, which is significantly higher than using the original one for men (34.7% vs 32.3%, P < 0.001). Conclusion: The present study indicated that optimal waist circumference cut-off points were lower than that proposed in the modified ATP III definition, especially for men. # 2010 Published by Elsevier Ireland Ltd.
1.
Introduction
Metabolic syndrome (MS) is a cluster of multiple, interrelated risk factors of metabolic origin that appear to directly promote the development of atherosclerotic cardiovascular disease such as diabetes and prediabetes, abdominal obesity, high cholesterol, low HDL-C and high blood pressure. It is not clear
whether the MS has a single cause, but the most important of these underlying risk factors are abdominal obesity and insulin resistance [1]. It is generally believed that metabolic syndrome contributes to the onset of cardiovascular disease (CVD) and type 2 diabetes mellitus, and has prognostic value for CVD mortality [2–4]. Ever since the concept of that syndrome was recommend by Reaven [5], many diagnostic
* Corresponding author. Tel.: +86 1083911508; fax: +86 1083911508. E-mail address: [email protected] (X. Guo). 1
Now: National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050, China. Wei Wang and Yanxia Luo are joint first authors. They contributed equally to the work. 0168-8227/$ – see front matter # 2010 Published by Elsevier Ireland Ltd. doi:10.1016/j.diabres.2010.01.022 2
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criteria have been proposed. The WHO definition [6], IDF definition [7], NCEP ATP III [8] and the modified ATPIII definition [1] were relatively world-wide applied ones. The consensus for the pathophysiology of MS was arrived on insulin resistance, therefore the importance of central obesity was established. In 2005, the International Diabetes Federation (IDF) in a global consensus statement formulated a new, clinically accessible worldwide definition of metabolic syndrome [7], based on the definition announced by WHO in 1999 [6]. Meanwhile, in an AHA/NHLBI scientific statement, the modified ATPIII definition for MS was released [1], with ethnicity-specific criteria for central obesity and a significantly lowered threshold for glucose than the criteria released in 2001 [8]. Besides, individuals treated for dyslipidemia, hypertension or hyperglycaemia were also included. There used to be only one definition for obesity and central obesity. However, there were evidence indicating that using these would severely underestimate the actual prevalence of obesity and abdominal obesity in the east [9]. The WHO experts then concluded that the proportion of Asian people at high risk for cardiovascular disease is substantial at BMI values lower than the existing WHO cut-off point for overweight [10]. With the same reason, the modified ATPIII definition for metabolic syndrome adopted ethnicity—specific cut-off points for central obesity [1]. The report of International Obesity Task Force proposed the WC values of 90 cm for men and 80 cm for women as Asian-specific WC cut-off points for central obesity [11] and this was adopted in the modified ATP definition and IDF definition [1,7]. A study involving 3289 persons 50–70 years old from Beijing or Shanghai showed that the association between MS and obesity is greater in overweight or obese people in the north than the south [12]. The InterASIA collaborative group’s investigation also showed that the age-standardized prevalence of MS, its components and overweight was higher in the north than in the south [13]. It might indicated that the WC cut-off values be specific not only for gender and ethnicity but also for region. However, as a consequence, it was almost impossible to compare the worldwide prevalence of MS. The Asian-specific central obesity diagnostic criteria were adopted in IDF definition and modified ATPIII definition, however, a new but not universally approved Chinese definition for MS set the cut-off points to 90 cm for men and 85 cm for women based on the findings that 90 cm for men and 85 cm for women were the corresponding waist circumference for a BMI value of 25 kg/m2, which was the cut-off point for BMI in the CDS definition [14] for metabolic syndrome [15]. In The Guide for Prevention and Control for Overweight and Obesity in Chinese Adults, the cut-off value of WC was found at 85 cm for men and 80 cm for women [16]. In all, there seemed to be at least three definitions for central obesity in China, they were set up from different prospective however failed to come to an agreement. Although, several criteria for central obesity were established from many perspectives for Chinese, the results were somewhat not in accordance. Using the results obtained from the surveillance of risk factors for non-communicable diseases in Beijing 2005, the present study examined the prevalence of each parameter and MS when the modified ATP III definition was employed. The validity of the waist
circumference cut-off values in the modified ATP III definition was tested based on an accumulation of these risk factors.
2.
Methods
2.1.
Study population
The Beijing Municipal Health Bureau and the centers for disease control and prevention (CDC) in Beijing conducted the surveillance of risk factors for non-communicable diseases in Beijing 2005 [17]. A proportional multistage cluster random sampling design was used to select subjects aged over 18 and having lived in Beijing for more than 6 months, including residents of communities and employees of companies. We selected no more than one subject from one household. If there are two people meet our requirement, the date of the their birthday was extracted. The one with smaller number of day was engaged in the survey. For two men with the birthday of Jan 1, 1969 and Sep 15, 1986, the older men would be selected. Qualified subjects were selected randomly in companies so that the subjects are relatively concentrated and convenient to be surveyed. In total, 16,711 persons from 53 living communities and 106 functional communities were identified to participate in the survey. Anthropometric measurements were missing for 118 persons. Therefore, complete information was obtained in 16,593 (99.3%) participants (male, 44.96 14.52 years; women, 45.31 13.70 years; gender ratio: women/male, 1.53), which is similar to that of the initial 16,711 individuals recruited for the survey (male, 44.96 14.48 years; women 45.32 13.71 years; gender ratio: women/male, 1.51).
2.2.
Content and methods
The present study was a cross-sectional survey conducted from August to September in 2005, which applied questionnaires, physical test, blood pressure measurement and laboratory examination. The questionnaire included demographic status like age, gender and educational background; risk factors of chronic diseases such as smoking, alcohol intake, diet and physical exercise; prevalence of chronic diseases including hypertension, diabetes, dyslipidemia and overweight. Physicians and public health nurses were in charge of the physical test. Height and body weight were measured in the upright position to the nearest 0.5 cm and 0.1 kg, respectively. The WC measurements were taken at the end of normal expiration and to the nearest 0.1 cm, measuring from the midpoint between the lower borders of the rib cage and the anterior superior iliac spine. Electronic sphygmomanometers were used to measure the blood pressure of each subject in the sitting position after a 10-min rest period. During the 30 min preceding the measurement, the subjects were required to refrain from smoking or consuming caffeine. Three readings each of systolic and diastolic blood pressures were recorded, with an interval of 30 s at least, and the average of each measurement was used for data analysis. Blood samples were obtained from antecubital vein into tubes containing EDTA in the morning after an overnight fasting period. The samples were subsequently analyzed at eight
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certified laboratories. Laboratory test includes fasting plasma glucose, total cholesterol, TG, HDL-C, LDL-C and creatinine, using autoanalyzers (Hitachi 7170; Hitachi, Tokyo, Japan).
2.3.
Diagnostic criteria for MS
We largely adopted the criteria for metabolic risk factors proposed by the modified ATP III definition [1]: elevated triacylglycerol, 1.70 mmol/L or with current lipid-lowering treatment; low HDL cholesterol, for male, HDL-C <1.03 mmol/ L or for women, HDL-C <1.30 mmol/L or with current lipidlowering treatment; elevated blood pressure, systolic 130 mmHg and or diastolic 85 mmHg or current use of antihypertensive drugs; elevated plasma glucose, patients for type 2 diabetes mellitus and/or FPG 5.6 mmol/L; and a combination of two to three of these risk factors.
2.4.
Measurement of other covariates
The measurements of other covariates and potential confounders were collected for the participants. Self-reported educational background, living site, alcohol consumption
frequency, and smoking were estimated from the questionnaire. Education level was categorized into 4 groups: 6 years, 7–9 years, 10–12 years, and >12 years. Living site was divided into rural area and urban area. The frequency for alcohol consumption in recent year was collected as never, 1–3 times/ month, 1–2 times/week, 3–5 times/week, almost everyday and more than 1 time/day. Participants were classified into three groups by their smoking status in the latest month: 1 cigarette/day, <1 cigarette/day, and who did not smoke (including ex-smoker and non-smoker).
2.5.
Statistical analysis
A database was established by EpiData 3.02 software. The statistical analyses were carried out using Statistical Package of Social Science for Windows version 13.0 (SPSS Inc., Chicago, IL, USA). Continuous variables were expressed as means and standard deviations, and discrete variables were presented as proportions. The sensitivity and specificity of each WC category (or take WC as a continuous variable) in detecting the presence of low HDL-C, elevated triacylglycerol, blood pres-
Table 1 – Basic characteristics of the study population for the surveillance of risk factors for non-communicable diseases in Beijing 2005. Men (n = 6567)
Women (n = 10,026)
44.96 14.52
45.31 13.70
45.17 14.03
Living site Urban area (%) Rural area (%)
3907 (59.5) 2660 (40.5)
6528 (65.1) 3498 (34.9)
10,435 (62.9) 6158 (37.1)
BMI (kg/m2)a Waist circumference (cm)a
25.16 3.52 87.61 10.12
24.51 3.78 79.71 10.44
24.77 3.70 82.84 11.01
Education level (%) 6 years 7–9 years 10–12 years >12 years
571 (8.7) 1868 (28.5) 1736 (26.5) 2372 (36.2)
1482 2643 2703 3188
2053 4511 4439 5560
Smoking (%) 1 cigarette/day <1 cigarette/day No smoker
3442 (52.4) 375 (5.7) 2748 (41.9)
394 (3.9) 105 (1.1) 9519 (95.0)
3836 (23.1) 480 (2.9) 12,267 (74.0)
Frequency for alcohol consumption (%) Never 1–3 times/month 1–2 times/week 3–5 times/week Almost everyday More than 1 time/day
2388 (36.4) 1263 (19.2) 1147 (17.5) 496 (7.6) 1034 (15.7) 238 (3.6)
8967 (89.6) 664 (6.6) 208 (2.1) 55 (0.5) 106 (1.1) 11 (0.1)
11,355 (68.5) 1927 (11.6) 1355 (8.2) 551 (3.3) 1140 (6.9) 249 (1.5)
87.61 10.12 2305 (35.1) 1812 (27.6) 3979 (60.7) 2012 (30.7) 3065 (46.8) 1431 (21.8)
79.71 10.44 2225 (22.2) 4224 (42.1) 4556 (45.5) 2554 (25.5) 3905 (39.0) 1948 (19.4)
82.84 11.01 4530 (27.3) 6036 (36.4) 8535 (51.5) 4566 (27.5) 6970 (42.1) 3379 (20.4)
Age (year)
a
(14.8) (26.4) (27.0) (31.8)
Total (n = 16,593)
(12.4) (27.2) (26.8) (33.6)
Metabolic risk factors (%)b Waist circumference (cm)a Elevated triacylglycerol Low HDL cholesterol Elevated blood pressure Elevated fasting plasma glucose 2 Risk factors 3 Risk factors a b
The values are presented as means S.D. Metabolic risk factors were defined according to ATP III revised criteria and were above described.
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sure, and fasting plasma glucose; and two to three risk factors were calculated by creating dichotomous variables for each WC value. Additionally, the receiver operating characteristic (ROC) curve was used for each WC value by plotting the truepositive rate (sensitivity) against the false-positive rate (1specificity). The Youden’s index, that is sensitivity + specificy1, was used to determine the optimal WC cut-off points. To identify the optimal WC values to reflect the cluster of metabolic risk factors in men and women, the odds ratios (OR) were calculated by multiple logistic regression analysis with adjustments for age group, living area, smoking status, and alcohol consuming frequencies. The WC values were categorized by 5 cm increments, with <80 cm for men or <75 cm for women as referents. The adjusted ORs were presented together with their 95%CI. The linear trend in ORs across WC categories was evaluated using the likelihood ratio test. All probability values presented were for two-tailed tests, the values of P < 0.05 were considered to indicate statistical significance.
3.
Results
3.1.
Basic characteristics of the subjects
and 42.1% of women; elevated blood pressure was observed in 60.7% of men and 45.5% of women; elevated fasting plasma glucose was seen in 30.7% of men and 25.5% of women. The cluster of two or more metabolic risk factors was detected in 46.8% of men and 39.0% of women, while the cluster of three or more metabolic risk factors was present in 21.8% of men and 19.4% of women. The prevalence for MS with the definition of the modified ATP III definition was 34.7% for men and 32.3% for women, after adjusting for age, while the total was 28.5% after adjusting for gender and age.
3.2. Metabolic risk factors according to waist circumference category When categorized by waist circumference, low HDL cholesterol; elevated plasma triacylglycerol, blood pressure and fasting plasma glucose showed higher prevalence in categories of higher waist circumference values for both men and women (Table 2).
3.3. Cut-off points of waist circumference for predicting the cluster of metabolic risk factors analyzed by adjusted odds ratios
The basic characteristics of the subjects and the prevalence of metabolic risk factors were shown in Table 1. The mean age of all participants was 45.17 years, and the mean BMI value was 24.77. The mean value for waist circumference was 87.61 cm in men and 79.70 cm in women. 59.5% of men and 65.1% of women lived in rural area, while 40.5% of men and 34.9% of women lived in rural area. About 52.4% of men smoked more than one cigarette per day, while 41.9% of men did not smoke in a month. The majority of women, that is 95.0%, did not smoke in a month. 89.6% of women never drank alcohol in the recent year, while for men the number was 36.4%. Elevated triacylglycerol was seen in 35.1% of men and 22.2% of women; low HDL cholesterol was detected in 27.6% of men
With 75 cm for women and 80 cm for men as reference, the presence of metabolic risk factors and the adjusted odds ratios according to WC values categorized by 5-cm increments in men and women are shown in Table 3. The cluster of metabolic risk factors was more obvious in categories of higher waist circumference for both men and women (P < 0.001 for trend).
3.4. Cut-off points of waist circumference for predicting clusters of metabolic risk factors analyzed by ROC curve The 80th percentile for WC values was approximately 96.0 cm in men and 88.5 cm in women. The optimal waist circumference cut-off point was estimated by the ROC curve analysis
Table 2 – Prevalence and adjusted odds ratiosa of metabolic risk factors according to waist circumference category. Waist Case circumference number category (cm)
Elevated triacylglycerol N
OR (95%CI)
Low HDL cholesterol N
OR (95%CI)
Elevated blood pressure N
OR (95%CI)
Elevated fasting plasma glucose N
OR (95%CI)
Men <80 80–85 85–90 90–95 95
1498 1000 1232 1219 1618
155 241 435 549 925
1.00 2.77 4.75 7.10 11.66
(2.22–3.46) (3.87–5.84) (5.78–8.71) (9.57–14.21)
211 189 322 413 677
1.00 1.48 2.30 3.46 4.83
(1.19–1.84) (1.90–2.81) (2.85–4.20) (4.02–5.80)
535 531 772 838 1303
1.00 1.67 2.27 2.97 5.56
(1.41–1.99) (1.93–2.68) (2.51–3.52) (4.70–6.59)
255 273 365 418 701
1.00 1.55 1.57 1.97 2.84
(1.27–1.89) (1.30–1.90) (1.64–2.37) (2.39–3.37)
Women <75 75–80 80–85 85–90 90
3535 1775 1746 1240 1730
216 317 465 456 771
1.00 2.73 4.14 5.90 7.18
(2.26–3.29) (3.47–4.95) (4.90–7.10) (6.02–8.58)
925 722 863 688 1026
1.00 2.10 3.08 4.10 5.01
(1.85–2.37) (2.72–3.49) (3.55–4.73) (4.37–5.75)
704 680 926 860 1386
1.00 1.81 2.88 4.93 7.24
(1.58–2.08) (2.52–3.30) (4.21–5.77) (6.20–8.46)
391 353 516 455 839
1.00 1.53 2.34 2.79 3.93
(1.30–1.80) (2.01–2.73) (2.36–3.29) (3.37–4.58)
a
Adjusted for age group, living site, smoke status and alcohol consuming frequency in recent year and using the data of the surveillance of risk factors for non-communicable diseases in Beijing 2005.
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Table 3 – Prevalence and adjusted odds ratiosa of cluster of metabolic risk factorsb according to waist circumference category. Waist circumference category (cm)
Case number
1 Risk factor N
2 Risk factors
OR (95%CI)
N
OR (95%CI)
3 Risk factors N
OR (95%CI)
Men <80 80–85 85–90 90–95 95
1498 1000 1232 1219 1618
815 736 1012 1083 1534
1.00 1.94 2.92 5.04 11.22
(1.61–2.32) (2.42–3.52) (4.07–6.23) (8.75–14.39)
268 358 573 703 1163
1.00 2.28 3.37 5.32 9.81
(1.89–2.75) (2.82–4.02) (4.45–6.36) (8.24–11.68)
58 115 242 334 682
1.00 2.99 5.39 8.34 15.91
(2.15–4.15) (4.00–7.28) (6.22–11.19) (11.99–21.11)
Women <75 75–80 80–85 85–90 90
3535 1775 1746 1240 1730
1660 1221 1433 1107 1641
1.00 1.99 3.72 5.88 11.43
(1.75–2.25) (3.22–4.30) (4.82–7.17) (9.06–14.43)
435 572 844 773 1281
1.00 2.70 4.80 7.42 11.03
(2.33–3.12) (4.16–5.53) (6.33–8.71) (9.44–12.89)
116 229 384 431 788
1.00 3.45 5.95 9.87 13.47
(2.73–4.37) (4.77–7.42) (7.88–12.37) (10.85–16.72)
a Adjusted for age group, living area, smoke status and alcohol consuming status and using the data of the surveillance of risk factors for noncommunicable diseases in Beijing 2005. b Metabolic risk factors were defined according to ATP III revised criteria and were above described.
based on subjects who fulfilled at least two of the modified ATP III definition for MS (Fig. 1). It turned out that 79.95 cm for women and 86.95 cm for men were the values (Table 4). Based on these findings, the optimal cut-off points for waist circumference were 80 cm for women and 87 cm for men.
lower (P < 0.001) for men. The total prevalence for MS with the modified ATP III definition and the revised modified ATP III definition, after standardized for gender and age was 28.5% and 30.0% respectively.
3.5. Prevalence of MS using the calculated waist circumference cut-off points in the modified ATP III definition for MS
4.
When the criteria for central obesity were set to 87 cm in men and 80 cm for women, and those for others remained the same, age-standardized the prevalence of MS using the revised modified ATP III definition was 38.0% for men and 32.3% for women. Without the revise, the prevalence of MS was 34.7% in men and 32.3% for women, which is significantly
Discussion
Many researches were accomplished as to the optimal cut-off points for WC with various outcome variables. A study of 31,076 Korean adults showed that the cut-off values for detecting myocardial ischemia was 87 cm for men and 74 cm for women, for detecting multiple risk factors for metabolic syndrome it was 83 cm for men and 76 cm for women [18]. For Japanese, using the criteria of Japanese Society of Internal Medicine, the points were not consistent: One research
Fig. 1 – Estimation by ROC curve analysis of the waist circumference cut-off points to predict the cluster of at least two metabolic risk factors using the data of the surveillance of risk factors for non-communicable diseases in Beijing 2005. Metbolic risk factors were defined according to ATP III revised criteria and were above described.
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diabetes research and clinical practice 88 (2010) 209–216
Table 4 – The sensitivity, specificity, and Yuden Index for detecting clusters of at least two metabolic risk factors for each WC cut-off points (the risk factors for non-communicable diseases surveillance in Beijing, 2005). Gender
WC cur-off points (cm)
Sensitivity
Specificity
Men
86.45 86.55 86.65 86.75 86.85 86.95 87.05 87.15 87.25 87.35 87.45
0.7374 0.7321 0.7315 0.7308 0.7308 0.7305 0.7100 0.7083 0.7047 0.7041 0.7018
0.6051 0.6114 0.6131 0.6143 0.6149 0.6163 0.6329 0.6341 0.6375 0.6392 0.6407
0.3425 0.3436 0.3446 0.3451 0.3457 0.3468 0.3429 0.3424 0.3422 0.3433 0.3425
Women
79.45 79.55 79.65 79.75 79.85 79.95 80.05 80.15 80.25 80.35 80.45
0.7488 0.7447 0.7442 0.7437 0.7424 0.7421 0.7129 0.7096 0.7076 0.7060 0.7029
0.6937 0.6979 0.6996 0.7004 0.7015 0.7030 0.7270 0.7287 0.7306 0.7311 0.7331
0.4425 0.4426 0.4437 0.4440 0.4439 0.4451 0.4400 0.4383 0.4382 0.4372 0.4360
reported that the values were 89.8 cm for men and 82.3 cm for women [19]. Another report from Hisayama Study showed the cut-off values as 90 cm for men, 80 cm for women to better predict CVD in general Japanese population in a 14 year followup study [20]. In China, it was reported that for adults in Shanghai the optimal cut-off points for WC were 90 cm for men and 85 cm for women [21]. For a study involving 101,510 employees in Tangshan city in the central north area of China, the cut-off values were 86.5 cm for men and 82.1 cm for women [22]. For a nationally representative sample in a crosssectional study, the cut-off point turned to be 80 cm for both genders [23]. The results were not in agreement. Moreover, few follow-up studies were found so far as to explore the optimal cut-off points for waist circumference in China. Only the result form a 7.3 years’ cohort in the Shanghai Women’s Health Study showed that the optimal cut-off point for women was 84.1 cm for predicting stroke [24]. In our study, the 80th percentile for WC values was 96 cm in men and 88.5 cm in women. The ROC curve analysis indicated that 87 cm for men and 80 cm for women were the optimal cut-off points. It is interesting to note that the mean and median values for sex-specific waist circumference were similar with our optimal points, 80 cm for women or 87 cm for men. The 80th percentile for WC values was fairly higher than our calculated cut-off points for WC. There were 4859 persons (29.3% for all, 33.0% for men and 26.8% for women) with a WC value within the area. They were the ones with high risks to develop metabolic syndrome. It is interesting to note that 35% of men and 22% of women had hypertriglyceridemia, but the prevalence of low HDL-C in men is 27.6% vs 42% in women. Elevated blood pressure was observed in 60.7% of men and 45.5% of women. Several researches reported could be served as reference. In a workforce survey including 101,510 employees in Tangshan (a city 150 km southeast of Beijing), with similar age coverage
Youden’s index
but more men subjects, they reported 31.7% of men and 26.8% of women with hypertriglyceridemia, 6.9% of men and 20.1% of women with low HDL-C, 56.3% of male and 40.1% of women were with elevated blood pressure [22]. In a community-based study involving 2334 aging subjects in Beijing showed that 22.6% of men and 34.1% of women were with hypertriglyceridemia, 16.4% of men and 36.3% of women were with low HDLC, 73.5% of men and 73.3% of women were with elevated blood pressure [25]. Although, for national representatives, the prevalence of hypertension (140/90 mmHg) is 20% for men and 18% for women who were aged over 18 and participated in the China National Nutrition and Health Survey 2002 [26] or 27.2% for adult population from 35 to 74 years old in 2001 [27], the prevalence of hypertension in Beijing is the most serious in provincial capital in China with a rate of 25% for people over 15 years old [28]. In our study the rate for hypertension is 38.3% for men vs 36.7% for women. In all, the prevalence of metabolic disorders was higher than that reported, which might be explained by the different gender ratio, urban/rural ratio or sampling procedure in our study. As to the rate of hypertriglyceridemia and low HDL-C, the specific medicine which the subjects take for blood lipid adjustment was not recorded in our questionnaire, therefore, a person with lipidlowering treatment was considered to have low HDL-C and elevated triacylglycerol. In all, our analysis suggested that the optimal WC cut-off points to reflect the cluster of at least 2 metabolic risk factors were 87 cm for men and 80 cm for women, which was different from the original criteria in the modified ATPIII definition. The prevalence of MS defined by the WC revised modified ATPIII definition were 38.0% for men and 32.3% for women, which is significantly higher then using the original one in men (34.7%). A limitation of this study is its cross-sectional sample population, and the definition of elevated triacylglycerol and
diabetes research and clinical practice 88 (2010) 209–216
low HDL-C. However, this was a relatively representative sample of the general adult population in Beijing. Though the outcome variables were more likely to be insulin resistance, stroke or cardiovascular disease in western world [29,30], there were few similar studies in Chinese population to explore the optimal cut-off points for waist circumference. Further studies as to the optimal WC cut-off points in a representative sample of the adult Chinese population to predict the incidence of insulin resistance, cardiovascular diseases morbidity and mortality, and all-cause mortality are needed prospectively.
Conflict of interest
[10]
[11]
[12]
[13]
All the authors have no conflict of interest. [14]
Acknowledgements This study was funded by Beijing Municipal Health Bureau. The authors are grateful to the Chronic Disease Department for Centers of Disease Control and Prevention (CDC) in eighteen districts for their contribution to coordinating with local government and implementing the investigation in the community.
[15]
[16]
references [17]
[1] S.M. Grundy, J.I. Cleeman, S.R. Daniels, K.A. Donato, R.H. Eckel, B.A. Franklin, et al., Diagnosis and management of the metabolic syndrome: an American heart association/ national heart, lung, and blood institute scientific statement, Circulation 112 (2005) 2735–2752. [2] H.M. Lakka, D.E. Laaksonen, T.A. Lakka, L.K. Niskanen, E. Kumpusalo, J. Tuomilehto, et al., The metabolic syndrome and total and cardiovascular disease mortality in middleaged men, JAMA 288 (2002) 2709–2716. [3] M.E. Safar, F. Thomas, J. Blacher, R. Nzietchueng, J.M. Bureau, B. Pannier, et al., Metabolic syndrome and agerelated progression of aortic stiffness, J. Am. Coll. Cardiol. 47 (2006) 72–75. [4] K.C. Sung, S. Ryu, G.M. Reaven, Relationship between obesity and several cardiovascular disease risk factors in apparently healthy Korean individuals: comparison of body mass index and waist circumference, Metabolism 56 (2007) 297–303. [5] G.M. Reaven, Banting lecture 1988. Role of insulin resistance in human disease, Diabetes 37 (1988) 1595–1607. [6] World Health Organization, Definition, diagnosis and classification of diabetes mellitus and its complication, report of a WHO consultation, part I: diagnosis and classification of diabetes mellitus, Geneva, 1999. [7] K.G. Alberti, P. Zimmet, J. Shaw, The metabolic syndrome— a new worldwide definition, Lancet 366 (2005) 1059–1062. [8] Executive summary of the third report of the national cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III), JAMA 285 (2001) 2486–2497. [9] P. Deurenberg, M. Deurenberg-Yap, S. Guricci, Asians are different from Caucasians and from each other in their
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25]
215
body mass index/body fat percent relationship, Obes. Rev. 3 (2002) 141–146. WHO consultation, Expert appropriate body-mass index for Asian populations and its implications for policy and intervention strategies, Lancet 363 (2004) 157–163. The World Health Organization Western Pacific Region, the International Association for the Study of Obesity, the International Obesity Task Force, The Asia-Pacific perspective: redefining obesity and its treatment, health, communications, Australia Melbourne, 2000. Z. Yu, X. Lin, J.D. Haas, O.H. Franco, K.L. Rennie, H. Li, et al., Obesity related metabolic abnormalities: distribution and geographic differences among middle-aged and older Chinese populations, Prev. Med. 48 (2009) 272–278. D. Gu, K. Reynolds, X. Wu, J. Chen, X. Duan, R.F. Reynolds, et al., Prevalence of the metabolic syndrome and overweight among adults in China, Lancet 365 (2005) 1398–1405. Expert panel on metabolic syndrome of Chinese diabetes society, Recommendations on metabolic syndrome of Chinese diabetes society, Chin. J. Diabetes 12 (2004) 156–161. Joint Committee for Developing Chinese Guidelines on Prevention and Treatment of Dyslipidemia in Adults. Chinese guidelines on prevention and treatment of dyslipidemia in adults. Zhonghua Xin Xue Guan Bing Za Zhi 35 (2007) 390–419. B.F. Zhou, Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults—study on optimal cut-off points of body mass index and waist circumference in Chinese adults, Biomed. Environ. Sci. 15 (2002) 83–96. X.H. Guo, P.H. Zhang, Z.C. Zeng, W. Wang, C. Li, Y. Shi, et al., Combination patterns of cardiovascular risks and sequelae at different stage of hypertension in natural hypertensive population in Beijing, Clin. Exp. Hypertens. 31 (2009) 142–155. H.K. Kim, C.H. Kim, J.Y. Park, K.U. Lee, Lower waistcircumference cutoff point for the assessment of cardiometabolic risk in Koreans, Diabetes Res. Clin. Pract. 85 (2009) 35–39. R. Oka, J. Kobayashi, K. Yagi, H. Tanii, S. Miyamoto, A. Asano, et al., Reassessment of the cutoff values of waist circumference and visceral fat area for identifying Japanese subjects at risk for the metabolic syndrome, Diabetes Res. Clin. Pract. 79 (2008) 474–481. Y. Doi, T. Ninomiya, J. Hata, K. Yonemoto, H. Arima, M. Kubo, et al., Proposed criteria for metabolic syndrome in Japanese based on prospective evidence: the Hisayama study, Stroke 40 (2009) 1187–1194. Y. Bao, J. Lu, C. Wang, M. Yang, H. Li, X. Zhang, et al., Optimal waist circumference cutoffs for abdominal obesity in Chinese, Atherosclerosis 201 (2008) 378–384. F. Wang, S. Wu, Y. Song, X. Tang, R. Marshall, M. Liang, et al., Waist circumference, body mass index and waist to hip ratio for prediction of the metabolic syndrome in Chinese, Nutr. Metab. Cardiovasc. Dis. 19 (2009) 542–547. R.P. Wildman, D. Gu, K. Reynolds, X. Duan, J. He, Appropriate body mass index and waist circumference cutoffs for categorization of overweight and central adiposity among Chinese adults, Am. J. Clin. Nutr. 80 (2004) 1129–1136. X. Zhang, X.O. Shu, Y.T. Gao, G. Yang, H. Li, W. Zheng, General and abdominal adiposity and risk of stroke in Chinese women, Stroke 40 (2009) 1098–1104. Y. He, B. Jiang, J. Wang, K. Feng, Q. Chang, L. Fan, et al., Prevalence of the metabolic syndrome and its relation to
216
diabetes research and clinical practice 88 (2010) 209–216
cardiovascular disease in an elderly Chinese population, J. Am. Coll. Cardiol. 47 (2006) 1588–1594. [26] D. Gu, K. Reynolds, X. Wu, J. Chen, X. Duan, P. Muntner, et al., Prevalence, awareness, treatment, and control of hypertension in China, Hypertension 40 (2002) 920–927. [27] Y. Wu, R. Huxley, L. Li, V. Anna, G. Xie, C. Yao, et al., Prevalence, awareness, treatment, and control of hypertension in China: data from the China national nutrition and health survey 2002, Circulation 118 (2008) 2679–2686.
[28] X.H. Pang, S.F. Jiao, L. Huang, J.L. Duan, Z.Y. Ren, Z.J. Liu, Nutrition and health status of the Beijing residents, Chin. J. Prev. Med. 29 (2005) 269–272. [29] C. Zhang, K.M. Rexrode, R.M. van Dam, T.Y. Li, F.B. Hu, Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: sixteen years of follow-up in us women, Circulation 117 (2008) 1658–1667. [30] A. Koster, M.F. Leitzmann, A. Schatzkin, T. Mouw, K.F. Adams, J.T. van Eijk, et al., Waist circumference and mortality, Am. J. Epidemiol. 167 (2008) 1465–1475.