Chronic kidney disease and metabolic syndrome in a general Korean population: the Third Korea National Health and Nutrition Examination Survey (KNHANES III) Study

Abstract

Background

The aims of this study are to examine the prevalence of chronic kidney disease (CKD) with metabolic syndrome (MS) and to investigate the association between CKD and MS after adjustment for socioeconomic position and health behavior factor.

Methods

The random sample used in this study included 5136 Korean subjects ≥20 years of age. We divided the subjects into two groups based on the presence of MS, for which the criteria described in the NCEP ATP III and International Diabetes Federation were used. Also, CKD was defined as an estimated glomerular filtration rate <60 ml/min/1.73 m².

Results

The prevalence of CKD in our study was 6.8%. The age-adjusted prevalence of CKD among those with MS was 9.0% whereas those without MS was 5.6%. After adjusting for age and confounders, people with MS had a 1.77 times greater risk of CKD than those without MS. The adjusted OR increased as the number of MS components increased (P < 0.05).

Conclusion

The age-adjusted prevalence of CKD in the MS group was higher than that in the non-MS group. After adjustment for socioeconomic position and health behavior factor, MS showed significant association with CKD.

chronic kidney disease, metabolic syndrome, prevalence

Introduction

Recently, emerging evidence, suggesting that metabolic syndrome (MS) contributes to an increased risk of developing chronic kidney disease (CKD), has received much more attention¹ as the prevalence of CKD has increased dramatically. According to the Third National Health and Nutrition Examination Survey (NHANES III) data, the prevalence of CKD in the US adults was estimated to be approximately 11% (19.2 million).² The prevalence of CKD in a Southeast Asian cohort (1985–97), over 10%, was similar to the US study.³ A report from the UK, which estimated the cost for the management of CKD by a computer simulation using creatinine values, showed a dramatic growth in the cost of treatment from €17 133 per 10 000 patients in 2002 to €29 790 in 2003.⁴ These costs were consistent with cost analysis data of a large US HMO population (1996–2001).⁵ To make matters worse, CKD prevalence is predicted to increase worldwide.⁶ As CKD is a major risk factor for end-stage renal disease (ESRD), cardiovascular disease and premature death, a risk factor intervention method for the early CKD risk group may be the best approach for preventing and delaying CKD and its complications.

MS is diagnosed based on the presence of at least three of the following five factors: hypertension, abdominal obesity, high triglyceride (TG) levels, low levels of high density lipoprotein (HDL) and high levels of fasting blood sugar (FBS). The National Cholesterol Education Program Adult Treatment Panel III reported that the prevalence of MS in the US adults was 27% in 2005,^7,8 whereas prevalence of MS in the Korean adults was 21% (men 20.1%, women 23.4%) in 2001.⁹ MS is a combination of medical disorders that increases the risk of diabetes and cardiovascular disease. It is also a risk factor associated with atherosclerosis, which can progress to coronary artery disease or cerebrovascular accident.

Recently, a number of studies^10–12 from the US have supported that MS is an independent risk factor for CKD. However, very little is known about the relationship between the risk factors of MS and CKD within the Asian population except for the Japanese. Although it is well established that the prevalence and cause of CKD vary by ethnicity, the majority of this evidence has been gathered from studies performed in Western countries. Moreover, most studies were conducted in hospital-based populations.¹³ Given the increasing prevalence of CKD and the burden of disease¹⁴ in Asian countries, there are pressing needs to investigate the relationship between CKD and MS. Therefore, the aim of this study was to investigate the prevalence of CKD and the association between MS and CKD after adjustment for socioeconomic position and health behavior factors in the Korean general population.

Methods

Study population

Data were collected from the 2005 KNHANES (Korea National Health and Nutrition Examination Survey) conducted by the Korean Ministry of Health and Welfare.¹⁵ The survey applied a stratified multistage probability sampling design from the South Korean population using a two-stage stratified systematic sampling method. Clusters of households were selected from each district and included an average of 20–26 households. The Health Interview Survey sample consisted of 42 780 people, which came from 13 345 households of 600 districts. One of every three health interview survey samples was selected, and both the health behavior survey and health examination were administered to the selected samples. Of those samples, 2515 men and 2621 women were ≥20 years of age.

Risk factors

Age was divided into six levels: 20–29, 30–39, 40–49, 50–59, 60–69, and >70 years. Waist circumference (WC) was measured at the narrowest point between the lowest rib and the top of the iliac crest. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured after subjects had rested for 5 min in a sitting position. An average of three blood pressure measurements was used for data analysis. Blood samples, collected from the antecubital vein after overnight nil per os., were measured for total cholesterol (TC), HDL, TG, FBS, hemoglobin and serum creatinine (Cr) levels by enzyme or colorimetric methods. All participating medical institutions were equipped with standardized, high-quality laboratories that had internal and external quality control procedures authorized by the Korean Association of Laboratory Quality Control. Anemia was defined as hemoglobin levels <12 g/dl in women and <13 g/dl in men.¹⁶ Self-reported information on the presence of hypertension and type 2 diabetes, and on education level, monthly household income, family size, smoking behavior, alcohol consumption and the amount of physical exercise per week were also obtained from the interviews. Since the 2005 KNHANES mainly included data on obesity, hypertension, diabetes, dyslipidemia and anemia, but not microalbuminuria, we did not use microalbuminuria as an evidence of chronic kidney damage.

Metabolic syndrome

Diagnosis of MS^17,18 was based on the presence of three or more of the following symptoms: (1) WC ≥90 cm for men or ≥80 cm for women (Asia-pacific guidelines for WC),¹⁹ (2) TG levels ≥150 mg/dl, (3) HDL levels <40 mg/dl for men or <50 mg/dl for women, (4) hypertension, defined as SBP ≥130 mmHg, DBP ≥85 mmHg, or the subject was under active antihypertensive drug therapy, and (5) FBS ≥100 mg/dl, the subject was actively using oral medication or insulin. The subjects were classified into two groups: non-MS subjects including normal subjects (non-MS; n = 3772) and MS subjects (MS; n = 1364).

Chronic kidney disease

The estimated glomerular filtration rate (eGFR), as an indicator of kidney function, was estimated using a formula from the Modification of Diet Renal Disease (MDRD) study:²⁰ GFR (ml/min/1.73 m²) = 186.3 × (serum Cr)^−1.154 × (age)^−0.203 × (0.742 if women) × (1.21 if African-Americans).

The National Kidney Foundation Kidney Disease Outcome Quality Initiative defined CKD as a GFR <60 ml/min/1.73 m².

Socioeconomic factors

The socioeconomic factors used in this study were education level and equivalent household monthly income (equivalent income). Education was classified into three categories: (1) Elementary school: ≤6 years of schooling; (2) Middle/High school: 7–12 years of schooling; (3) College, University: >12 years of schooling. The equivalent income was calculated using the method defined by the Organization for Economic Cooperation and Development,²¹ which is W_ij = Y_i/S_i^ϵ, where Y_i is the ith household income, S_i is the ith household family size and W_ij is the equivalent income of the jth member in the ith household. The equivalent elasticity (ϵ), which means the equivalency of the household size, is set to 0.5. The equivalent income was then calculated by dividing the obtained monthly household income by the square root of the family size. Equivalent income was categorized into three levels: low (<71), middle (71–140) and high (≥141).

Health behavior factors

Subjects were identified as former smokers if they had quitted smoking in the year prior to the survey. Alcohol consumption²² was calculated based on the number of alcohol drinks and the amount of alcohol consumption per day as reported on the health interview questionnaire. We divided the subjects into two groups: (1) drinking ≥30 g per day and (2) <30 g. For physical exercise, we had two groups: (1) 3 or more times per week and (2) less than 3 times.

Statistical analyses

Differences in general characteristics, socioeconomic factors, health behavior factors and clinical data between the MS and non-MS groups were analyzed using the student's t-test for the continuous variables and the χ²-test for the categorical variables. The group-specific age-adjusted prevalence of CKD was calculated based on MS and its components, and other confounders including gender, education, equivalent income, smoking, drinking and exercises; the direct standardized method with estimated Korean population in 2005 was used as the reference. Multiple logistic regression analysis was used to determine the association between MS as an independent variable and CKD as a dependent variable after adjustment for age and confounders. Model I used logistic regression after adjustment for age and Model II used logistic regression after adjustment for age and potential confounders. All analyses applied sample weights proposed by the Korea Institute of Health and Social Affairs to estimate the nationwide prevalence.¹⁵

Results

As shown in Table 1, 26.6% of the overall population had MS. There was a significantly higher proportion of CKD (15.5%) among people with MS than those without MS (3.6%). Generally, people with MS were of older age, with more severe alcohol consumption, lower education and from a relatively higher income level than those without MS (P < 0.001). On the contrary, the proportion of current smokers is similar regardless of MS and the proportion of anemia in the non-MS group was higher than that of the MS group. The mean values of WC, SBP, DBP, TC, TG, FBS and Cr in the MS group were higher than those in the non-MS group (P < 0.001). The mean values of HDL and eGFR were lower for the MS group than those for the non-MS group (P < 0.001).

Table 1

General characteristics, socioeconomic position, health behaviors, chronic kidney disease and estimated glomerular filtration rate of participants compared by MS (n = 5136)

Variables	Non-MS	MS	P-value*
n (%)	3772 (73.4)	1364 (26.6)
	Percentage
Chronic kidney disease (<60 ml/min/1.73 m2)	3.6	15.5	<0.001
Age, year-old, mean ± SD	40.0 ± 14.5	52.8 ± 13.4	<0.001
20–29	27.1	3.7	<0.001
30–39	27.6	15.4
40–49	23.0	23.5
50–59	11.1	24.6
60–69	6.8	19.0
≥70	4.4	13.7
Gender, men	48.3	50.8	0.110
Anemia	10.6	7.0	<0.001
Smoking
Non	57.0	50.5	<0.001
Former	17.0	23.4
Current	26.0	26.1
Alcohol consumption
Over 30 g/day	6.3	10.4	<0.001
Physical exercise
Over 3 times/week	16.7	15.8	0.421
Education level
College, University	42.1	20.4	<0.001
Middle/high school	45.3	46.1
Elementary school	12.6	33.5
Income levela
High	16.3	21.6	<0.001
Middle	16.7	17.5
Lower	67.0	60.9
	Mean ± SD
WC (cm)	77.6 ± 8.6	89.4 ± 7.2	<0.001
SBP (mmHg)	113.9 ± 14.9	130.7 ± 16.5	<0.001
DBP (mmHg)	74.9 ± 10.0	84.1 ± 9.9	<0.001
TC (mg/dl)	179.1 ± 33.8	195.9 ± 34.6	<0.001
TG (mg/dl)	104.2 ± 63.4	218.3 ± 173.4	<0.001
HDL (mg/dl)	47.1 ± 10.8	38.8 ± 7.2	<0.001
FBS (mg/dl)	89.1 ± 13.9	107.2 ± 28.8	<0.001
eGFR (ml/min/1.73 m2)	79.8 ± 12.3	73.2 ± 11.8	<0.001
Men	84.1 ± 12.0	79.2 ± 0.9	<0.001
Women	75.8 ± 11.3	67.0 ± 9.7	<0.001
Cr (mg/dl)	0.98 ± 0.18	1.02 ± 0.19	<0.001
Men	1.07 ± 0.22	1.09 ± 0.15	0.041
Women	0.90 ± 0.10	0.95 ± 0.19	<0.001

eGFR, Estimated glomerular filtration rate (ml/min/1.73 m²).

^aEquivalent household monthly income.

*Student's t-test for continuous variables or χ²-test for descriptive variables between metabolic status and each variable.

As seen in Table 2, age-adjusted prevalence of CKD in the MS group was 9.0% (95% confidence interval (CI): 7.8–10.1), whereas those in the non-MS group was 5.6% (95% CI: 4.7–6.2).

Table 2

Age-adjusted prevalence^a (95% CI) and their OR (and 95% CI) for chronic kidney disease with and without MS or MS components, after adjusting for age (model 1) and age and confounders (model II)^b

Variables	n	Prevalence (95% CI)	Model Ic (95% CI)	Model IId (95% CI)
MS
No	3772	5.6 (4.7–6.2)	1.0	1.0
Yes	1364	9.0 (7.8–10.1)	2.07 (1.60–2.70)	1.77 (1.34–2.34)
Abdominal obesitye
No	3555	5.9 (5.0–6.8)	1.0	1.0
Yes	1881	8.8 (7.6–9.9)	1.73 (1.34–2.25)	1.27 (0.96–1.68)
High TGf
No	3709	7.0 (6.1–7.8)	1.0	1.0
Yes	1427	7.8 (6.5–9.1)	1.23 (0.94–1.61)	1.32 (0.99–1.75)
Low HDLg
No	2357	5.4 (4.4–6.5)	1.0	1.0
Yes	2779	8.6 (7.6–9.6)	1.82 (1.38–2.40)	1.36 (1.02–1.83)
High BPh
No	3410	6.3 (5.1–7.5)	1.0	1.0
Yes	1726	7.9 (6.9–8.8)	1.29 (0.98–1.70)	1.33 (0.99–1.78)
High FBSi
No	4111	6.7 (5.9–7.6)	1.0	1.0
Yes	1025	8.0 (6.8–9.3)	1.50 (0.98–1.70)	1.70 (1.29–2.24)
0 components	1131	5.2 (2.7–7.6)	1.0	1.0
1 componentsj	1564	4.1 (2.9–5.3)	1.04 (0.57–1.89)	0.96 (0.53–1.74)
2 componentsj	1078	6.5 (5.1–7.9)	1.31 (0.74–2.23)	1.21 (0.69–2.14)
3 componentsj	792	8.8 (7.1–10.5)	2.26 (1.30–3.94)	1.81 (1.03–3.18)
4 and 5 componentsj	571	9.0 (7.4–10.7)	2.56 (1.47–4.46)	2.34 (1.16–3.57)
Age	5136	—	—	1.13 (1.11–1.15)
Gender
Men	2515	3.4 (2.6–4.2)	1.0	1.0
Women	2621	9.9 (8.9–11.0)	3.73 (2.77–5.00)	3.53 (2.42–5.15)
Anemia
No	4642	7.2 (6.4–8.0)	1.0	1.0
Yes	493	9.0 (6.6–11.4)	1.03 (0.70–1.53)	1.06 (0.71–1.59)
Smoking
None	2848	9.2 (8.1–10.3)	1.0	1.0
Former	954	4.9 (3.6–6.1)	0.40 (0.28–0.56)	0.91 (0.58–1.43)
Current	1334	4.7 (3.3–6.2)	0.38 (0.26–0.55)	0.83 (0.52–1.33)
Alcohol consumption
Less 30 g/day	4756	7.6 (6.9–8.4)	1.0	1.0
Over 30 g/day	380	2.1 (0.5–3.6)	0.23 (0.10–0.53)	0.45 (0.19–1.05)
Physical exercise
Over 3 times/week	846	4.6 (2.7–6.5)	1.0	1.0
Less 3 times/week	4290	7.5 (6.8–8.3)	1.49 (0.96–2.33)	0.60 (0.34–1.08)
Education level
College, University	930	2.4 (1.2–3.6)	1.0	1.0
Middle/high school	2339	5.2 (3.8–6.6)	1.26 (0.75–2.11)	0.99 (0.58–1.69)
Elementary school	1867	7.7 (6.8–8.7)	1.99 (1.17–3.39)	1.04 (0.58–1.86)
Income levelk
High	3359	5.3 (2.6–8.0)	1.0	1.0
Middle	867	3.6 (2.4–4.8)	0.64 (0.37–1.12)	0.60 (0.64–1.08)
Lower	910	8.0 (7.2–8.9)	1.48 (0.97–2.27)	0.71 (0.44–1.15)

^aAge-adjusted prevalence rates of CKD were calculated with age adjustment to 5-year age groups according to the direct method with estimated Korean population in 2005 being referent.

^bNon-CKD group: n = 4787, CKD group: n = 349.

^cLogistic regression after adjustment for age.

^dAdjusted for age, gender, anemia, smoking, alcohol consumption, physical exercise, equivalent household monthly income and education levels.

^eWC ≥90 cm in men or ≥80 cm in women.

^fTriglyceride levels ≥150 mg/dl.

^gHDL <40 mg/dl in men or <50 mg/dl in women.

^hBlood pressure ≥130/85 mmHg or use of antihypertensive drug therapy.

ⁱFBS ≥100 mg/dl or use of oral hypoglycemic agents or insulin.

^jCompared with those with 0 components.

^kEquivalent household monthly income.

Overall, the higher age-adjusted prevalence of CKD was observed in persons with MS, abdominal obesity, high TG, low HDL, high BP and high FBS. The age-adjusted prevalence of CKD according to the number of MS components from 0, 1, 2, 3 and 4 and 5 was 5.2, 4.1, 6.5, 8.8 and 9.0%, respectively.

Women had a prevalence of CKD 3 times higher than that of men. For health behaviors, the prevalence of CKD among non-smokers and light drinkers was approximately 2–3 times higher than the prevalence among current smokers and heavy drinkers. In contrast, people who exercised less than 3 times per week had up to a 1.5 times higher risk of CKD than those who exercised regularly. Also, lower education and lower income persons were at a higher CKD risk. And there were 349 subjects with CKD in our study (Table 2).

The age-adjusted risk excess [odds ratio (OR)] of CKD, which ranged from 1.73 to 2.07, was statistically significant in MS, abdominal obesity and low HDL. People with a greater number of MS components, more than 3, showed a greater risk of CKD (P < 0.001). After adjustment for potential confounders, CKD was associated with individual and multiple MS components. Adjusted OR for MS [1.77 (95% CI: 1.34–2.34)], high FBS [1.70 (95% CI: 1.29–2.24)] and low HDL [1.36 (95% CI: 1.02–1.83)] groups were positively associated with CKD. In addition, OR of 3 and ≥4 of MS components was 1.81 (95% CI: 1.03–3.18) and 2.34 (95% CI: 1.16–3.57), respectively (P < 0.001) compared with the 0 number of MS components (Table 2).

In the additional analysis, the proportions of hypertension, diabetes, chronic kidney disease and chronic renal failure in the data were 14, 5, 6.8 and 0.6%, respectively.

Discussion

Main findings

After adjustment for socioeconomic position and health behavior factor, MS was significantly associated with CKD in the Korean population. For example, age-adjusted prevalence of CKD in the MS group was significantly higher than that in the non-MS group. The risk for CKD increased as the number of MS components increased.

What is already known on this topic

A number of studies from the USA^10–12 and Japan^23,24 have supported that MS is associated with CKD. Various studies have also demonstrated that the prevalence of CKD in the USA² and Japan^23,25 was over 10%, and the prevalence of MS in adults in the USA,⁸ Canada,²⁶ Norway²⁷ and Korea⁹ was over 25%. In the UK²⁸ and USA,^29,30 the prevalence of CKD was higher in lower socioeconomic and lower physical activity groups, which is similar to our results. The prevalence of CKD showed gender difference in the UK,³¹ USA³² and Norway.³³ Also some researchers have shown the prevalence of CKD varies depending on the race and ethnicity.^34–36 The prevalence of CKD in the MS group was also known to be significantly higher than that in the non-MS.^10,11 Furthermore, the risk for CKD increased as the number of MS components increased.^13,37

What this study adds

We investigated the prevalence of CKD and CKD with MS, as well as the association between MS and CKD for the general population of Korea. This study confirmed that MS has excessive risk for CKD after adjusting for health behavior factors and socioeconomic position as MS risk factors. Few studies, however, have made adjustments for them in analyzing the Korean population data.

The age-adjusted prevalence of CKD with MS was 9.0% and the prevalence of CKD was 6.8% in this study. Although the difference in the age-adjusted prevalence of CKD by MS status was statistically significant, the gap was not higher than that reported by the United States Renal Data System. The general prevalence of CKD in other studies^31,32,38 was around 10%.

Our findings are consistent with previous studies that revealed a significant association between MS and CKD.^11,39 For instance, in NHANES III,¹¹ CKD was present in 1.2% of the subjects without MS and in 6.0% of the subjects with MS. The possible reason for why the lower prevalence of CKD in the USA (6.0%, 1988–94) than that in Korea (9.0%, 2005) might be the time gap between those two surveys.

Our findings also showed that low HDL, high FBS and gender were strong predictors for CKD.³⁸ Low HDL and high LDL are common in patients with ESRD.⁴⁰ In particular, low HDL has been shown to predict an increased risk of renal dysfunction.^41–43

Epidemiologic studies have documented that diabetes is the major risk factor for the development and progression of CKD. For example, the Framingham Heart Study⁴⁴ and Japanese population study⁴⁵ supported the link between hyperinsulinemia and renal dysfunction. Our findings are consistent with these previous studies. These findings have very important implications for public health particularly because diabetic nephropathy is thought to be a microvascular complication of diabetes. Fox et al.⁴⁶ showed that CKD, during pre-diabetes, may be considered an additional complication of macrovascular atherosclerosis.

With regard to gender, our study showed that women had a higher risk of CKD than men. Similarly, Plantinga's study⁴⁷ had a higher percentage for women than for men. However, another study⁴⁸ showed no significant gender difference for CKD.

Interestingly, our study showed that abdominal obesity, high BP and high TG demonstrated little association with CKD after adjusting for possible confounders. Our analysis indicated that abdominal obesity showed no clear association with CKD,³ whereas a number of studies in the USA¹¹ and Iran⁴⁹ have indicated that adjusted OR for obesity is associated with CKD. This controversial finding may be explained by race or ethnic differences.

Hypertension is the most common underlying cause of CKD. The relationship between hypertension and progression of CKD has been well established in several epidemiologic studies.⁵⁰ The US studies have also showed an association between hypertension,¹¹ or mildly elevated blood pressure² (SBP ≥130 mmHg and DBP ≥85 mmHg) and CKD. Consistent with findings from our study, a Chinese study performed by Chen et al.³⁸ showed no significant difference between mildly elevated blood pressure and CKD. Glomerulonephritis is the most common cause of CKD in China,³⁸ but in Korea, it is not a known cause of CKD. Therefore, further longitudinal research on the cause of CKD is needed.

High TG levels predicted a decline in renal function and appeared to be a risk factor for developing CKD.⁵¹ However, Japanese⁵² and Chinese³⁸ studies showed no association between high TG and CKD. Our finding was consistent with the aforementioned Asian studies,^38,52 whereas inconsistent with a western study.¹¹

Unexpectedly, current smokers and heavy drinkers had a lower risk for CKD than non-smokers and light drinkers in our study. Lower education or lower income groups showed a higher age-standardized prevalence and a higher risk for CKD than higher education and higher income groups. However, these effects disappeared after other potential risk factors for CKD were controlled. CKD is prevalent in individuals of lower socioeconomic position but there is little research that has examined this relationship. Therefore, future longitudinal research on the CKD risks of smoking or drinking and socioeconomic status is needed.

Anemia, a typical characteristic of ESRD, was recently shown to develop in the earlier course of the disease.^2,53 However, our results did not show a significant association between anemia and CKD.

Based on the fact that a quarter of Korea's population has MS,⁹ the risk of CKD would be considered high in Korea resulting in higher medical cost. Furthermore, the worldwide ageing trend gives us a warning for the increasing prevalence of MS and CKD. It is critical for aging and aged societies to put effort to prevent MS and CKD, to manage CVD risk factors, so as to the development and/or progression of CVD, and to decrease CVD mortality. The primary preventive strategies such as effective health education, a well-balanced diet, physical activity and more attention to individuals with a familial history of CVD can reduce the MS risk factors and the development of MS and CKD. The secondary preventive strategies pursue the successful management of MS and CKD by early medical examination including pharmacotherapy and extensive clinical evaluation. Such primary and secondary preventive strategies should be performed at the same time.

Limitations and strengths of this study

There are several limitations to our study. First, it is difficult to explain the causality between MS and the development CKD in this cross-sectional study design. Second, due to the limited information in our data, we could not investigate the effects of microalbuminuria or pharmaceutical drug use, such as non-steroidal anti-inflammatory drug use, which may aggravate renal disease. Therefore, this is an additional area in which future research is necessary. Third, eGFR, based on the MDRD study equation, has not been validated for use with the Korean population. Although it has not been validated for Koreans, we used the MDRD equation because it has been widely used in epidemiological studies and clinical practice.

One strength of this study is a high degree of representation of Korean population with a high response rate (89.9%). Additionally, our result is based on objective measures including blood tests for a large random sample of the Korean population.

Conclusions

The age-adjusted prevalence of CKD in the MS group was higher than that in the non-MS group. After adjustment for socioeconomic position and health behavior factor, there is a significant association between MS and CKD in the Korean population.

Acknowledgements

The author thanks Professor Kunitoshi Iseki at the dialysis unit in the university hospital of Ryukyus, Professor Charlotte Thomas-Hawkins and Professor Jiyoung Ahn at college of nursing, Rutgers in The State University of New Jersey and Dr Terry A. Klein and Sunny Kwon in 18th MEDCOM, USA for review and comments on this paper. We also thank Woon Young Jang for his contribution toward the completion of this study.