Background
In 2006, the International Diabetes Federation proposed that central obesity is a prerequisite for the diagnosis of metabolic syndrome (MetS). Central obesity is defined using ethnicity-specific cutoff point of waist circumference (WC) [
1]. The Korean Society for the Study of Obesity (KOSSO) set Korean-specific WC cutoff points of 90 cm for men and 85 cm for women [
2]. These numbers were derived through analysis of data collected during the Korean National Health and Nutrition Examination Survey (KNHANES) 1998 [
3], which is a representative data of non-institutionalized Korean civilians. However, the KOSSO did neither provide the cutoff point for visceral abdominal fat area (VFA) nor did differentiate WC criteria by age group.
Normal aging process is characterized by progressive increase in fat mass and more central distribution of adipose tissue [
4,
5]. These changes can have important consequences on the profile of risk factors for developing MetS. Women are particularly susceptible to increase in visceral fat as they go through menopause [
6]. Considering that the accumulation of visceral fat with aging can be more prominent in women than in men, the gender difference in current Korean-specific criteria for abdominal obesity could be decreased with aging. Recently, a few studies have reported that VFA and WC cutoff points for the identification of subjects at risk for developing MetS differ by age, with older women experiencing higher VFA and WC cutoff points than younger women [
7,
8].
We estimated optimal values for VFA, WC and body mass index (BMI) cutoff points for defining central obesity by comparing the predictive validity of the metabolic risk factors other than WC in elderly Korean men and women in order to verify the adequacy of the current criteria of abdominal obesity in elderly Koreans.
Methods
Study participants
This cross-sectional study was conducted within the framework of the Ansan Geriatric (AGE) Study. The AGE study is an ongoing prospective population-based cohort study including subjects who are at least 60 years old and live in Ansan, a suburb of Seoul, Republic of Korea. A random sample of these elderly Koreans (n = 2,767) was assembled in 2002. The sampling protocol and design of the AGE study has been previously reported [
9]. From this database, we constructed the 1
st wave sample of the AGE cohort study that was age- and sex-stratified [
10,
11]. Briefly, all subjects received a telephone call and a letter 3 times inviting them to attend a comprehensive health screening at the Geriatric Health Clinic and Research Institute, Korea University Hospital, Ansan, Korea. After excluding the subjects who refused to participate or who were not reached at this invitation, a total of 1,391 subjects were recruited between September 2004 and March 2006 and were regarded as the 1
st wave sample. The follow-up assessment (2
nd wave study) was performed two years later (25.6 ± 5.1 months) between April 2006, and January 2008. A total of 841 subjects (2
nd wave sample set) were followed from the 1
st wave sample with the same recruitment protocol of the 1
st wave sample. This study was conducted as a cross-sectional study from the 2
nd wave sample set of the AGE Study because abdominal computed tomography (CT) scan was taken from the 2
nd wave study. Among the 2
nd wave sample set (n = 841), a total of 152 subjects were excluded because they had insufficient clinical data (n = 12) or no available abdominal CT scan (n = 140).
A total of 689 Korean subjects (308 men, 381 women; mean age, 70.8 ± 5.0 years; range, 63-86 years) were ultimately eligible for participation in this analysis. Written informed consent was obtained from each individual. The study protocol was approved by the institutional review board of the AGE study.
Anthropometric measurements and blood tests
Anthropometric measurements for each participant were taken after an overnight fast while the subject wore light clothing and no shoes. Height was determined using a fixed wall-scale measuring device and was measured to the nearest 0.1 cm. Weight was measured to the nearest 0.1 kg using an electronic scale that was calibrated prior to each measurement. BMI was calculated as the weight in kilograms divided by the square of the height in meters. The WC was measured twice to the nearest 0.5 cm in a horizontal plane at the level of the umbilicus at the end of normal expiration. If the variation between these two measurements was greater than 2 cm, a third measurement was taken and the mean was calculated by using the two closest measurements. Blood pressure was measured using a mercury sphygmomanometer (Baumanometer; W.A.Baum, Copiague, NY) in the supine position after at least a 10-min rest period by trained technicians. Three measurements were taken from all the subjects at 2-min intervals, and the average of the last two measurements was used. These were recorded to the nearest 2 mmHg. Blood samples were taken in the morning after an overnight fast. All subjects had a 75 g oral glucose tolerance test (OGTT). We measured fasting and post two hour OGTT-glucose levels. Plasma glucose, serum triglycerides and HDL-cholesterol levels were measured using an autoanalyzer (ADVIA1650; Siemens, NY, USA).
The metabolic risk factors were defined using the modified NCEP-ATP III criteria, with the exception of WC [
12] as follows: 1) fasting plasma glucose ≥100 mg/dL or post two hour OGTT-glucose ≥ 140 mg/dL or taking medication for previously diagnosed type 2 diabetes; 2) blood pressure ≥ 130/85 mmHg or taking medication for previously diagnosed hypertension; 3) serum triglycerides levels ≥ 150 mg/dL; 4) serum HDL cholesterol levels < 40 mg/dL in men, < 50 mg/dL in women.
Determination of visceral fat area using computed tomography
The abdominal adipose tissue areas were quantified by a single slice computed tomography (CT) scan at a 120 kV exposure (Brilliance 64; Philips, Cleveland, USA). A 5-mm CT slice scan was acquired at the L4-L5 vertebral interspace to measure the total abdominal and visceral abdominal fat areas (VFA) by measuring the mean value of all pixels within the range of -190 to -30 Hounsfield units. The images were converted into files compatible with a commercial software program (EBW; Philips, Cleveland, USA). Subcutaneous abdominal fat area (SFA) was determined by subtracting VFA from total abdominal fat area.
10-year Framingham coronary heart disease risk score
After excluding subjects with a previous history of cardiovascular disease (n = 38), 10-year Framingham coronary heart disease risk score (10-Yr FRS) was calculated as suggested by D'Agostino et al., which estimates risks for coronary heart disease in the next 10 years [
13]. The equation includes risk variables such as age, diagnosis of diabetes, current smoking, categories of systolic/diastolic blood pressure, total cholesterol and HDL cholesterol. The 10-Yr FRS was evaluated as high risk for greater than 20%.
Statistical analysis
Continuous variables were expressed as gender-specific means and standard deviations. Discrete variables were expressed as gender-specific proportions. For continuous variables, a Student's t-test was used to assess differences in means between the groups. For categorical data, a chi-square test was used to assess differences in proportions across the categories.
A receiver operating characteristic (ROC) curve analysis was used to assess the accuracy of VFA, WC, and BMI for identifying at least two of the metabolic risk factors, or for identifying each factor separately. ROC curve analysis for identifying a greater than 20% 10-Yr FRS was performed after excluding subjects with a previous history of cardiovascular disease (n = 38). A comparison of the diagnostic abilities for each test was performed using the area under the curves (AUC). The significance of the difference between the two areas was assessed using the method described by Hanley and McNeil [
14,
15]. The optimal cutoff points were obtained from the point on the ROC curve which was closest to (0, 1). This point was calculated as the minimum value of the square root of [(1-sensitivity)
2+(1-specificity)
2] [
16]. We performed a simple regression analysis to define the correlations between VFA and WC. All reported
p values were two-tailed.
P-values of less than 0.05 were considered statistically significant. Statistical analyses were conducted using SAS version 9.1 for Windows (SAS Institute Inc., Cary, NC).
Discussion
We demonstrated that the optimal WC cutoff points for predicting two or more metabolic risk factors or for identifying a greater than 20% 10-Yr FRS were same in elderly Korean men and women. Optimal VFA and BMI cutoff points were also similar in both genders. Given our findings, WC cutoff points determined for young and middle-aged adults may not appropriately characterize elderly Koreans.
In 2006, KOSSO (the Korean Society for the Study of Obesity) set WC criteria for central obesity at 90 cm for men and 85 cm for women. These numbers are based on the upper 80th percentile for WC values in middle-aged Koreans [
2]. In the present study, we found that the WC cutoff point was similar in both genders when using the 80
th percentile of WC. This is because the mean WC of men was not different from that of women. Young men typically have a higher WC compared to women. Although there are some ethnic differences [
17,
18], these differences become smaller with age. In our elderly subjects, women had similar mean WC and even slightly higher BMI compared to men. We confirmed that the difference of mean WC between genders decreased with age in the Third KNHANES, a nationwide survey which was conducted in 2005 (mean WC in subjects with 20-63 years old (n = 6480), 76.3 cm in men and 72.0 cm in women; vs. in subjects ≥63 years (n = 1069), 85.0 cm in men and 83.2 cm in women, unpublished data). Another study in Chinese population demonstrated the same feature. Younger Chinese men had higher mean WC and BMI than younger Chinese women but older Chinese men had comparable or even lower mean WC and BMI than older Chinese women [
19]. When comparing the present study and the recent publication with 816 middle-aged Korean subjects who underwent routine health examinations [
20], appropriate VFA cutoff points for middle-aged men in their study was comparable to those for elderly men in this study (100 cm
2 vs. 93 cm
2), whereas cutoff points for young women was lower than those for elderly women in this study (70 cm
2 vs. 89 cm
2). It could be from that women have a relatively greater increase in visceral fat after menopause [
21]. Changes in sex hormones, dietary intake, and energy expenditure during menopause can be related to increase in visceral fat and prevalence of obesity in senescence [
6,
22]. Considering these changes in body composition and metabolism in elderly women, the cardiovascular risk associated with central obesity may be different from that of younger women. Some Asian reports have indicated that the WC cutoff points for a middle aged population are different from those of older population [
8,
19]. It should be further investigated whether age-related changing pattern of obesity is specific to Asians.
The prevalence of MetS in men was greater than in women until the fifth decade in KNHANES 1998 [
3], using the definition of abdominal obesity recommended by the WHO Western Pacific Region of WC ≥90 cm in men and ≥80 cm in women [
23,
24]. However, after that period, women had a significantly higher prevalence of MetS than men. These results may be partially explained by relatively lower cutoff point of WC for women. When we used higher WC cutoff point for women such as the KOSSO criteria for abdominal obesity (WC ≥90 cm in men, ≥85 cm in women), the prevalence of MetS was still higher in women (48.1% in men and 64.3% in women). However, it was not different according to gender with the optimal WC cutoff points that we identified (61.0% in men and 61.4% in women). These results indicate that age-specific WC criteria which may reflect age-associated body compositional change will more consistently identify high risk subjects, especially in old age population compared to the uniform criteria. However, this feature is not evident in certain populations. In the Third National Health and Nutrition Examination Survey III (NHANES III) of American adults, the prevalence of MetS was similar between genders throughout all age groups despite using the same cutoff points for central obesity in both young and old populations [
25]. This could be due to continued differences in the mean WC between men and women throughout their entire lifespan in certain ethnics [
26].
The predictability of WC for identifying the risk of MetS was comparable to that of VFA in our study. Some studies in Japanese subjects reported that VFA was better than WC and BMI for identification of subjects with two or more components of MetS [
8,
27]. In contrast, a Korean study in obese middle-aged women showed that the VFA is not superior to WC for predicting metabolic risk factors [
28]. Another Japanese study has shown that VFA does not have better correlation with carotid intima-media thickness as a surrogate measurement of atherosclerosis than waist-hip-ratio or WC [
29]. It should be investigated in the future whether VFA is really superior to WC for predicting the clustering of metabolic risk factors in general population. Because WC is an inexpensive and clinically feasible measurement compared to the direct imaging required for assessing visceral fat, we suggest that WC measurements are sufficient for the detection of central obesity in correlation with the risk of MetS in elderly Koreans.
Although the present study is the first population-based cohort report in Korea that addresses the VFA cutoff point, it has some limitations. Firstly, we only showed the cross-sectional association between WC, VFA and MetS. Further investigation with prospective design is needed to clarify more reliable cutoff points of WC and VFA, above which the development of cardiovascular diseases increase. Secondly, we cannot provide comparative data between young and elderly subjects to estimate different WC and VFA criteria according to changes in body composition. However, the present study may reliably present metabolic features in elderly due to relatively large number of elderly subjects.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
The first author, JS designed this study, interpreted the data and wrote this manuscript. BK contributed to the analysis. HC contributed to the analysis. HK contributed to the analysis. JP contributed to the analysis, interpretation of data. SB contributed to the discussion. DC contributed to the discussion. MP contributed to the discussion and edited the manuscript. CH contributed to the discussion and edited the manuscript. SJ contributed to design the cohort, collect the data and edit the manuscript. YK contributed to design the cohort, collect the data and edit the manuscript. NK guided the study design, analysis, interpretation of data, discussion, and revised the manuscript critically. All authors read and approved the final manuscript.