Original Article Korean J Obes 2015 March;24(1): pissn X eissn 당뇨병전기환자에서대사증후군의예측인자로허

Transcription

1 Original Article Korean J Obes 2015 March;24(1): pissn X eissn 당뇨병전기환자에서대사증후군의예측인자로허리 / 신장비의효용성 김지민, 백민경, 주상현, 신민영, 김미주, 박연희, 박광인, 정경혜, 김현진, 구본정 * 충남대학교의과대학내과학교실 Validation of Waist-to-Height Ratio for Predicting Metabolic Syndrome in Patients with Prediabetes Ji Min Kim, Min Kyung Back, Sang Hyeon Ju, Min Young Shin, Mi Joo Kim, Yeon-hee Park, Kwang-In Park, Kyong-Hye Joung, Hyun Jin Kim, Bon Jeong Ku* Department of Internal Medicine, Chungnam National University School of Medicine, Daejeon, Korea Background: Metabolic syndrome is associated with type 2 diabetes and cardiovascular disease in patients with prediabetes. The aim of this study was to investigate and compare WHtR (Waist-to-Height Ratio) as a predictor of metabolic syndrome with other anthropometric indices as in Body Mass Index (BMI), Waist Circumference (WC) and Waist to Hip Ratio (WHR) in prediabetes. Methods: A total of 816 subjects with prediabetes were recruited from a community based Cohort Study. Receiver operating characteristic (ROC) curve was performed to find the optimal cutoff value of WHtR. Area under the curve (AUC) was calculated for each anthropometric index and correlation coefficient between WHtR and various dermographic and clinical factors was calculated. Results: WHtR had a significant correlation with metabolic parameters except for fasting glucose and increased with increasing number of risk factors for metabolic syndrome. AUC of WHtR was significantly higher than that of other anthropometric indices. The optimal cutoff value of WHtR was 0.53 for metabolic syndrome in prediabetes. Conclusion: WHtR may be the simple and effective anthropometric index for predicting metabolic syndrome in prediabetic patients. Key words: Prediabetic state, Metabolic syndrome, Waist-to-height ratio 서론 최근식습관및생활양식의서구화로인해비만인구가급격히늘고있으며, 2011년에국민건강통계에서만 19세이상의 31.9% 가비만에해당하는것으로조사되었다. 1 비만은인슐린저항성이나내피세포기능장애등과관련이있으며, 대사증후군, 당뇨병및심혈관질환의위험인자로잘알려져있다. 2 특히대사증후군의경우에는낮은고밀도지단백콜레스테롤 (high-density lipoprotein cholesterol, HDL- C), 높은중성지방 (triglyceride, TG), 복부비만, 고혈압, 고혈당을보이는만성적인대사장애로복부비만과의연관성이높다. 비만을평가하는지표로는비만도, 체질량지수 (body mass index, BMI), 체성분분석을통한체지방량 (body fat mass), 허리둘레 (waist circumference, WC), 허리 / 엉덩이둘레비 (waist-to-hip ratio, WHR), 허리 / 신장비 (waist-to-height ratio, WHtR) 등여러가지가있으며, 이중에서복부비만을반영하는지표로는허리 / 엉덩이둘레비, 허리 / 신장비, 허리둘레등이있다. 최근연구에서이와같은복부비만을반영하는지표들이대사증후군을예측하는지표로도유용하다고보고하고있다. 3-5 건강검진대상자 2,299명을대상으로진행되었던국내의한연구에서허리둘레및허리 / 신장비가대사증후군의각구성요소와유의한상관관계를보여대사증후군의선별검사지표로사용할 Corresponding author Bon Jeong Ku Department of Internal Medicine, Chungnam National University School of Medicine, 282 Munhwa-ro, Jung-gu, Daejeon , Korea Tel Fax bonjeong@cnu.ac.kr Received May 22, 2014 Reviewed Jun. 6, 2014 Accepted Jul. 10, 2014 Copyright 2015 Korean Society for the Study of Obesity This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. 36

2 수있음을보고하였다. 6 지난 2005년미국당뇨병학회 (American Diabetes Association, ADA) 와유럽당뇨병연구학회 (European Association for the Study of Diabetes, EASD) 는대사증후군을하나의질환으로보고진단및치료하는진료행위를명확한연구결과가나올때까지중단해야한다는성명을발표하였다. 7 이후대사증후군이있는경우당뇨병및심혈관질환의위험성이증가한다는여러연구결과가나오고있지만아직까지모든일반인을대상으로하여대사증후군을예측, 진단하는것을권고하는가이드라인은없다. 하지만당뇨병전기는대사증후군과동반되는경우가많으며, 당뇨병전기에서대사증후군동반시협심증, 심근경색, 뇌경색등의심혈관질환의위험이증가할뿐만아니라인슐린저항성을높여당뇨병으로의진행과도관련이있다 당뇨병에대한교차비를비교했을때공복혈당장애와대사증후군동반시공복혈당장애만있을시에비해당뇨병위험도가 3배가량더높아지는것으로나타났다. 12 그렇기에당뇨병전기환자에서대사증후군을조기에예측하고적절한관리및치료가시행된다면당뇨병및심뇌혈관질환의발생을낮출수있을것이다. 현재대사증후군예측을위한지표로가장많이사용되는것은체질량지수이다. 편리성을고려하여체질량지수가보편적으로사용되고있지만복부비만에대한반영도가부족하여대사증후군의예측에는부적절하다는보고들이있다. 7,13 반면에허리 / 신장비는허리둘레를신장으로보정한수치로체질량지수에비해복부비만을잘반영하는것으로알려져있으며대사성질환의위험도예측에있어더유용하다는연구결과들이있다. 또한허리 / 신장비는허리둘레에비해서도당뇨병및심혈관질환의위험을더잘예측한다는메타분석도있었다. 14 따라서본연구에서는체질량지수, 허리둘레, 허리 / 엉덩이둘레비와허리 / 신장비를비교하여대사증후군예측의지표로서허리 / 신장비의유용성에대해알아보고자하였다. 방법 1. 연구대상및기간 2005년 12월부터 2006년 2월까지지역사회코호트사업에참여한충청남도금산군주민을대상으로하였다. 40세이상 70세이하의주민 1,871명이자발적동의후에사업에참여하였으며, 이중 748 명이 60세이상에해당되었다. 고연령군의비율이높았기에당뇨병전기에해당하는사람이 816명으로많게나타났으며본연구는이들을대상으로하였다. 공복혈당장애 (impaired fasting glucose, IFG) 에해당하는사람은 77명, 내당능장애 (impaired glucose tolerance, IGT) 는 455명, 공복혈당장애와내당능장애에모두해당되는사람은 44명, 그리고공복혈당장애및내당능장애에는해당되지않지만당화혈 색소 (hemoglobin A1c, HbA1c) % 로당뇨병전기로진단된사람은 328명이었다. 2. 연구내용및방법설문조사를통해대상환자의성별, 연령, 기저질환 ( 당뇨병및심뇌혈관질환, 고지혈증유무 ), 복용약제, 흡연및음주등의생활습관을파악하였다. 신장, 체중, 허리둘레, 엉덩이둘레를측정하였으며, 이로부터체질량지수, 허리 / 신장비및허리 / 엉덩이둘레비를계산하였다. 체질량지수는체중 (kg)/ 신장 (m) 2 의공식을이용하여산출하였다. 허리둘레는마지막늑골의하단과장골능선의상단부위의중간지점에서숨을내쉰상태에서줄자를이용하여측정하였으며엉덩이둘레는대퇴골대전자의가장넓은부위에서측정하였다. 혈압측정은디지털혈압계를이용하였으며 10분이상안정상태를취하고 5분이상간격을두고 2회측정하여그평균값으로하였다. 혈액의채취는 8시간이상충분한공복상태에서시행하였으며식후 2시간혈당값을얻기위해 75 g당부하후 2시간째다시혈액을채취하였다. 혈당 (serum glucose), TG, 총콜레스테롤 (total cholesterol, TC), HDL-C를자동분석기 (Hitachi 747, Tokyo, Japan) 를이용하여분석하였고, 저밀도지단백콜레스테롤 (low-density lipoprotein cholesterol, LDL- C) 은다음의공식 15 을이용하여계산하였다. LDL-C =TC-[HDL-C+(TG/5)] 당화혈색소의측정은 Variant II turbo (Turbo; Bio-Rad Laboratories, Inc., Hercules, CA, USA) 를이용한고속액체크로마토그래피 (High-performance liquid chromatography, HPLC) 로측정하였으며인슐린농도는방사면역측정법 (DPC Coat-a-count insulin, LA, USA) 으로측정하였다. 인슐린저항성은공복인슐린과공복혈당을이용한 HOMA-IR (homeostasis model for insulin resistance) 로평가하였으며, 다음공식을이용하였다. HOMA-IR= [ 공복인슐린 (mu/l) 공복혈당 (mmol/l)]/22.5 향후 10년간심혈관질환의위험도는 Framingham risk score를통하여산출하였다 정의당뇨병전기는미국당뇨병학회의진단기준에따라공복혈당장애 ( 공복혈당이 mg/dl 인경우 ), 내당능장애 ( 경구당부하후 2 시간혈당이 mg/dl 인경우 ), 또는당화혈색소가 % 인경우로하였다

3 대사증후군의진단은미국국립콜레스테롤교육프로그램의성인치료패널 III (NCEP ATP-III) 진단기준을이용하였으며, WC는 90 cm ( 남 ) 또는 85 cm ( 여 ) 초과, 혈청 TG 150 mg/dl 이상, 혈청 HDL-C 40 mg/dl ( 남 ) 또는 50 mg/dl ( 여 ) 미만, 수축기혈압 130 mmhg 이상혹은이완기혈압 85 mmhg 이상, 그리고공복혈당 100 mg/dl 이상의 5가지중 3가지이상에해당되는경우로하였다. 18 WC는대한비만학회의기준 ( 남 90 cm, 여 85 cm) 을사용하였다. 19 이상지질혈증은 NCEP ATP-III 지침을참고하여혈청 TG가 150 mg/dl 이상, TC가 200 mg/dl 이상, LDL-C 130 mg/dl 이상, HDL-C 40 mg/dl 미만중하나라도해당되는경우이거나이상지질혈증을진단받고약물복용중인사람도포함하였다 통계분석본연구에서는허리 / 신장비와체질량지수의대사증후군에대한진단력을비교하기위해수용자반응특성 (receiver operating characteristic, ROC) 곡선을이용한곡선하면적 (area under curve, AUC) 값을구하였고, 허리 / 신장비와여러임상지표들사이의상관관계를분석하기위해피어슨상관계수 (Pearson s correlation coefficient) 를이용하였다. 그리고대사증후군의유무에따라두군으로나누어서로비교분석하였고, 이는독립표본 t-검정 (independent t-test) 을이용하였다. 대사증후군과허리 / 신장비의 ROC 곡선을이용하여적절한민감도, 특이도를갖는허리 / 신장비값을산출하였고, 이를기준으로하여대상군을두군으로나누어독립표본 t-검정을이용하여서로비교분석하였다. 통계적분석은 SPSS version 18.0 (SPSS Inc., Chicago, IL, USA), Medcalc version 12.7 (MedCalc Software bvba, Ostend, Belgium) 을이용하였고, P값이 0.05 미만일경우통계적으로유의하다고정의하였다. 결과 1. 연구대상자의일반적특성대상군의평균연령은 57.5 ± 7.4 세였고, 체질량지수는남자는 23.7 ± 3.0 kg/m 2, 여자는 24.9 ± 3.4 kg/m 2 였다. 허리둘레는남자 87.8± 8.5 cm, 여자 86.8±10.3 cm으로양군에차이가없었으나 (P = 0.063), 여자에서복부비만에해당하는비율이높게나타났다. 허리 / 신장비는평균 0.55± 0.06이었고, 남자는 0.53± 0.05, 여자는 0.57± 0.07로여자에게서더높았다 (P< 0.001) (Table 1). 2. 대사증후군환자의특성대사증후군의동반유무에따라서대사증후군동반군인 MetS군과동반하지않은 non-mets군으로구분하였다. 전체 816명중 MetS Table 1. The general characteristics of the study subjects Total (N= 816) 군은 455 명이었으며남자는 163 명 (35.8%), 여자는 292 명 (64.2%) 으로 여자에서더많았다 (P< 0.001). MetS 군의허리 / 신장비는 0.58± 0.06 이 었으며 non-mets 군의허리 / 신장비 0.52 ± 0.06 보다높았다 (P< 0.001). MetS 군과 non-mets 군의 WC 는각각 90.8± 8.2 cm, 82.4 ± 9.2 cm 으 로현저한차이를보였으며 (P< 0.001), TG 는각각 ±106.0 mg/ dl, ± 66.8 mg/dl 로큰차이를보였다 (P< 0.001). 이외에도대사 증후군의진단요소인 LDL-C, 공복혈당역시 MetS 군에서높았으며, HDL-C 는낮았다 (Table 2). Male (N= 349) Female (N= 467) P value* Age (year) 57.5± ± ± Height (cm) 158.5± ± ± 5.8 < Weight (kg) 61.3± ± ± 9.0 < Hip (cm) 81.8± ± ± BMI (kg/m 2 ) 24.4± ± ± 3.4 < WC (cm) 87.1± ± ± SBP (mmhg) 134.7± ± ± DBP (mmhg) 84.1± ± ± Fasting glucose (mg/dl) 95.8± ± ± 9.5 < PP2 (mg/dl) 138.6± ± ± TC (mg/dl) 214.3± ± ± 38.2 < Triglyceride (mg/dl) 173.9± ± ± HDL-C (mg/dl) 45.1± ± ± LDL-C (mg/dl) 127.7± ± ± 32.1 < HbA1c (%) 5.6± ± ± Insulin (µiu/ml) 8.8± ± ± 5.4 < WHtR 0.55± ± ± 0.07 < WHR 1.1± ± ± HOMA-IR 2.08± ± ± 1.37 < Framingham risk score 14.2± ± ± MetS (%) 455 (55.8) 163 (46.7) 292 (62.5) < Dyslipidemia (%) 696 (85.3) 294 (84.2) 402 (86.1) Data was expressed as mean± SD. BMI, body mass index; WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; PP2, 2 hours postprandial glucose; TC, total cholesterol; HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol; WHtR, waist to height ratio; WHR, waist to hip ratio; HOMA-IR, homeostasis model assessment of insulin resistance; MetS, metabolic syndrome. *P value from independent t-test between male and female (except metabolic syndrome), P value from chi-square test between male and female. 3. 대사증후군의위험요소들과허리 / 신장비와의상관관계 대사증후군의각각의위험요소와허리 / 신장비와의상관계수를보 면 HDL-C 가낮을수록허리 / 신장비가높았으며 (P< 0.05), WC, 수축 기혈압, TG, LDL-C 와는양의상관관계를보였다 (P< 0.05) (Table 3). 다음으로대사증후군의위험요소수와허리 / 신장비의상관관계를 알아보았다. 대사증후군의 NCEP ATP-III 진단기준에해당하는 5 가 지구성요소에하나도해당되지않는사람은 33 명으로평균허리 / 신

4 Table 2. Comparison of various clinical factors between MetS group and non- MetS group 장비는 였다. 반면에 5 가지의구성요소에모두해당되는 40 명의 평균허리 / 신장비는 로차이를보였다. 해당되는구성요소의개 수가 1,2,3,4 개인군의평균허리 / 신장비는각각 0.512, 0.527, 0.567, 로진단기준에많이해당될수록허리 / 신장비가증가됨을알수 있었다 (P< 0.001) (Fig. 1). 4. 대사증후군예측에있어허리 / 신장비와다른지표들과의비교 AUC 값을이용하여여러지표들의대사증후군진단력을비교하 여보았다. 허리 / 신장비의 AUC 값은 0.76 으로체질량지수 0.72, 허리 둘레 0.75, 허리 / 엉덩이둘레비 0.66 인것에비해높게나타났으며, 허 리둘레를제외하고는남, 녀모두에서비슷한차이를보였다. 허리 / 신 장비는전체에서허리둘레보다높은 AUC 값을보였으나차이는크 지않았으며남, 녀나누어비교시에는허리둘레가더높은 AUC 값 을보였다 (Table 4). 5. 허리 / 신장비의절단값 (cut off value) 및허리 / 신장비에따른 특성 Non-MetS (N= 361) MetS (N= 455) P value* Age (year) 57.8± ± Height (cm) 158.9± ± Weight (kg) 58.3± ± 10.1 < Hip (cm) 82.5± ± BMI (kg/m 2 ) 23.1± ± 3.2 < WC (cm) 82.4± ± 8.2 < SBP (mmhg) 129.6± ± 15.7 < DBP (mmhg) 81.6± ± 9.9 < Fasting glucose (mg/dl) 93.1± ± 10.2 < PP2 (mg/dl) 137.1± ± TC (mg/dl) 213.3± ± Triglyceride (mg/dl) 127.7± ± < HDL-C (mg/dl) 49.6± ± 8.2 < LDL-C (mg/dl) 126.9± ± HbA1c (%) 5.6± ± Insulin (µiu/ml) 7.7± ± 4.6 < WHtR 0.52± ± 0.06 < WHR 1.04± ± 0.28 < HOMA-IR 1.79± ± 1.15 < Framingham risk score 13.3± ± 3.1 < Data was expressed as mean± SD. BMI, body mass index; WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; PP2, 2 hours postprandial glucose; TC, total cholesterol; HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol; WHtR, waist to height ratio; WHR, waist to hip ratio; HOMA-IR, homeostasis model assessment of insulin resistance; MetS, metabolic syndrome. *P value from independent t test between MetS group and non-mets group. 적정민감도, 특이도를나타내는허리 / 신장비의절단값을찾기위해 Table 3. Pearson s correlations between WHtR and various variables Total Male Female Age (year) * * Height (cm) * * * Weight (kg) 0.325* 0.476* 0.482* Hip (cm) * * * WC (cm) 0.881* 0.925* 0.948* SBP (mmhg) 0.074* * DBP (mmhg) Fasting glucose (mg/dl) * PP2 (mg/dl) 0.196* 0.106* 0.238* TC (mg/dl) Triglyceride (mg/dl) 0.089* 0.200* 0.091* HDL-C (mg/dl) * * * LDL-C (mg/dl) 0.114* HbA1c (%) * * Insulin (µiu/ml) 0.123* 0.133* WHR 0.636* 0.686* 0.727* HOMA-IR 0.113* 0.127* Framingham risk score 0.103* WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; PP2, 2 hours postprandial glucose; TC, total cholesterol; HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol; WHtR, waist to height ratio; WHR, waist to hip ratio; HOMA-IR, homeostasis model assessment of insulin resistance. *P value < WHtR Total Male Female Number of risk factors for MetS Fig. 1. Correlation for waist to height ratio (WHtR) and number of risk factors for metabolic syndrome (MetS). WHtR were in a group that had no metabolic risk factor, and in a group that had 5 metabolic risk factors, respectively. WHtR increased with increasing number of risk factors for metabolic syndrome. Total: r= 0.448, P value < 0.001, Male: r= 0.448, P value< 0.001, Female: r= 0.423, P value < ROC 곡선을사용하였다. 허리 / 신장비가 0.53 일때민감도및특이도 가각각 81.3% 및 60.9% 로가장적정한값을얻을수있었으며, MetS 군 455 명중 81.5% 인 371 명에서허리 / 신장비가 0.53 이상으로나타났다. 허리 / 신장비가 0.53 이상인군과미만인군을비교하였을때 0.53 미만인군의평균체중은 58.0 ± 8.7 kg, 0.53 이상인군의평균체중은 63.3±10.1 kg 이었으며, 체질량지수는각각 22.5± 2.5 kg/m 2, 25.5±

5 Table 4. Area under curve (AUC) for various anthropometric indices to predict metabolic syndrome WHtR WHR BMI WC Total ( )* ( )* ( )* ( )* Male ( )* ( )* ( )* ( )* Female ( )* ( )* ( )* ( )* Data are AUC (95% confidence interval). WHtR, waist to height ratio; WHR, waist to hip ratio; BMI, body mass index; WC, waist circumference. *P value< Table 5. The comparison of various clinical factors according to the WHtR cut-off value 3.2 kg/m 2 으로 0.53 이상인군에서유의하게높았다 (P< 0.001). 또한 WC, TG, 공복혈당, 모두허리 / 신장비가 0.53 이상인군에서통계적 으로유의하게높았으며, HDL-C 는더낮게나타났다 (Table 5). 고찰 0.53 (N= 304) > 0.53 (N= 512) P value* Age (year) 58.2± ± Height (cm) 160.3± ± 8.6 < Weight (kg) 58.0± ± 10.1 < Hip (cm) 88.0± ± 14.8 < BMI (kg/m 2 ) 22.5± ± 3.2 < WC (cm) 78.1± ± 6.8 < SBP (mmhg) 134.0± ± DBP (mmhg) 84.9± ± Fasting glucose (mg/dl) 94.7± ± PP2 (mg/dl) 132.2± ± 30.2 < TC (mg/dl) 215.1± ± Triglyceride (mg/dl) 158.8± ± HDL-C (mg/dl) 48.5± ± 9.6 < LDL-C (mg/dl) 125.7± ± HbA1c (%) 5.7± ± 0.4 < Insulin (µiu/ml) 5.7± ± HOMA-IR 1.98± ± Framingham risk score 14.0± ± Data was expressed as mean± SD. BMI, body mass index; WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; PP2, 2 hours postprandial glucose; TC, total cholesterol; HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol; HOMA- IR, homeostasis model assessment of insulin resistance. *P value from independent t-test. 본연구에서는당뇨병전기환자에게서대사증후군의예측인자로 허리 / 신장비의효용성에대해알아보았다. 허리둘레, 체질량지수, 허 리 / 엉덩이둘레비, 허리 / 신장비와대사증후군사이의상관계수및 AUC 값을비교하였을때, 대사증후군을예측하는데있어유용한 지표로허리 / 신장비를이용할수있음을알수있었다. 체질량지수는현재임상에서가장흔하게사용되는비만을평가 하는지표이나체내지방분포를제대로반영하지못하는단점이있 다. 또한인종에따라체지방의차이를보이며, 체질량지수가동일하여도동양인에서서양인보다체지방량이높은것으로나타나체질량지수와비만및연관질환과의관련성이유의하지않다는것이보고되고있다 체질량지수, 허리 / 신장비와여러요소들의상관계수를비교하였을때에도, 체질량지수의경우에는체중과는높은상관관계를보이고있으나허리둘레와의상관관계는허리 / 신장비에비해높지않음을알수있다. 이는체질량지수가비만의지표로는유용하나복부비만은잘반영하지못한다는것을나타내며복부비만이인슐린저항성및만성대사질환과더관련이높음을고려할때 24,25 체질량지수는대사증후군을예측하기에한계가있음을의미한다. 대사증후군의진단기준에허리둘레가포함되어있어허리둘레및허리 / 신장비의 AUC 값이과평가되었다는제한점은있으나본연구에서도대사증후군진단에있어서허리둘레및허리 / 신장비가체질량지수보다높은 AUC 값을보였다. 또한대사증후군에해당되는 455명중체질량지수가 25 kg/m 2 이상인사람은 243명이었고 30 kg/m 2 이상인사람은 32명밖에되지않아정상체질량지수에서도대사증후군이발생할수있으며체질량지수가대사증후군의예측인자로는바람직하지못하다는것을생각해볼수있다. 반면에허리둘레, 허리 / 엉덩이둘레비, 허리 / 신장비는복부비만의임상적지표로서체질량지수보다비만연관질환을예측하는데유용한예측인자로사용될수있음이알려져있다. 하지만본연구에서허리 / 엉덩이둘레비는허리둘레및허리 / 신장비에비해낮은 AUC 값을보여대사증후군진단에있어허리둘레, 허리 / 신장비만큼유용하지는못함을알수있었다. 현재복부비만의지표로허리 / 신장비보다는허리둘레가주로사용되고있으나, 허리둘레가개개인의신장에따라달라짐을고려할때신장이작은동양인에게서양인에서와같은절단값을적용하기는어렵다. National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) 에서복부비만의기준을남자는허리둘레 102 cm 이상, 여자는허리둘레 88 cm 이상으로제시하였지만, 2000년도 World Health Organization (WHO)/International Association for the Study of Obesity (IASO)/International Obesity Task Force (IOTF) 기준에서는아시아인은비만의정도가서양인보다낮은상태에서도건강위험도가높음을제시하면서아시아, 태평양지역사람을

6 위한비만기준에서복부비만의기준을남자는허리둘레 90 cm 이상, 여자는허리둘레 80 cm 이상으로할것을권고하였다. 26,27 또한대한비만학회에서는한국인에서의절단값을남자는허리둘레 90 cm 이상, 여자는허리둘레 85 cm 이상으로할것을제시하였다. 19 허리둘레는인종, 성별뿐만아니라나이에따라서도절단값이달라져야한다. 하지만허리 / 신장비는신장으로허리둘레를보정하여성별, 연령, 인종에상관없이공통적으로사용할수있다는장점이있다. 28,29 특히이전연구들에서동양인에서당뇨발병위험도가서양인에비해 2-5배높으며주요요인으로복부비만을제시하였던것을고려할때허리 / 신장비는한국인에게유용한대사질환의예측인자로사용될수있다. 30,31 그러나아직허리 / 신장비의적절한절단값에대해확정된것은없다. 이전논문들에서 Browning 등 32 은허리 / 신장비의절단값을 0.5로제시하였고, 중국에서시행한한연구에서는대사증후군예측을위한허리 / 신장비의절단값으로 0.52를주장하였다. 33 앞서언급한것처럼허리 / 신장비는인종에상관없이공통적으로사용할수있기에본연구에서도우선 Browning 등 32 이제시한 0.5를절단값으로하여분석을시행하였다. 허리 / 신장비의절단값을 0.5로할경우허리 / 신장비가 0.5 이상인 654명중 424 (64.8%) 명이대사증후군에해당되었으며 0.5 미만인군에서는 19.1% 가대사증후군으로나타났다. 허리 / 신장비가 0.52 이상인 556명중에서는 391명 (70.3%) 이대사증후군에해당되었다. 본연구에서는 ROC 곡선을이용하여얻은절단값 0.53을이용하였을때허리 / 신장비가 0.53 이상인 512명중 371명 (72.5%) 이대사증후군으로나타났으며, 대사증후군 455명중약 81.5% 가해당되었다. 본연구에서허리 / 신장비가실제로인슐린저항성및심혈관질환의예측인자로유용한지평가를위해 HOMA-IR 값및 Framingham risk score와허리 / 신장비와의상관관계를분석하였다. 인슐린저항성을의미하는 HOMA-IR 값은허리 / 신장비와상관관계를보였다. 남, 녀나누어비교시에는여자에서유의한상관관계를보이지않았으나이는성별에따른인슐린저항성의차이가관련이있을것으로생각된다. 34,35 Framingham risk score 역시전체집단에서는허리 / 신장비와상관관계를보였으나남, 녀나누어비교시에는통계적으로유의하지않았다. Framingham risk score는비만, 고중성지방혈증, hs-crp의상승같이심혈관질환의독립적위험인자를포함하지않고있으며실제로 Framingham risk score가대사증후군여부보다심혈관질환을더잘예측할지에대한것은아직논란이있다. 또한 Framingham risk score 는서양인을대상으로한것으로동양인에게똑같이적용하기어렵다는점이있을수있으며 36 이런것들로인해남, 녀의하위그룹분석에서상관성이없게나왔을가능성이있다. 이전의메타분석에서는허리 / 신장비가심혈관질환의예측인자로유용하다는보고가있었으며 37 허리 / 신장비를통한대사증후군예측이실제로당뇨병 및심혈관질환발생위험도를낮출수있는지에대해서는추후연구가필요할것으로생각된다. 또한본연구는당뇨병전기에해당되는사람만을대상으로하였기에일반인에게동일한허리 / 신장비의절단값을적용할수있을지에대해서도추가적인연구가필요할것으로생각된다. 그리고이번연구가특정지역, 40세이상, 70세이하의특정연령군만을대상으로하였다는점도하나의제한점이될수있다. 대사증후군은여러위험요소들을평가하여진단하는하나의증후군이기때문에실제로임상에서진단이간단하지않으며간과하기쉽다. 하지만허리 / 신장비는쉽게측정이가능하여대사증후군의예측및이후대사관련질환의추적관찰지표로도간단하게사용할수있다. 또한환자스스로도측정이가능하기에치료에있어환자의참여도와순응도를높이는데에도유용할것으로생각된다. 결론적으로당뇨병전기환자에서대사증후군을예측하는지표로써허리 / 신장비를이용할수있으며, 적정절단값은 0.53이었다. 본연구는당뇨병전기환자에서단면조사연구로진행되었기때문에추후전향적이며일반인을대상으로한연구가필요할것으로사료된다. 요약 배경 : 당뇨병전기환자에게서대사증후군동반시당뇨병및심혈관질환이증가하는것으로알려져있으나대사증후군을예측하는지표로명확하게제시된것은없다. 본연구에서는체질량지수및다른임상적지표와허리 / 신장비를비교하여대사증후군의예측지표로써허리 / 신장비의유용성에대해알아보고자하였다. 방법 : 2005년 12월부터 2006년 2월까지지역사회코호트사업을위해참여한충청남도금산군주민중당뇨병전기에해당하는총 816명을대상으로하였다. 곡선하면적 (area under curve, AUC) 값을통해허리 / 신장비와다른지표들의대사증후군에대한진단력을비교하였으며허리 / 신장비와여러임상요소들사이의상관관계를분석하였다. 결과 : 공복혈당을제외한대사증후군각각의위험요소는허리 / 신장비와유의한상관관계를보였으며, 대사증후군의진단기준에많이해당될수록허리 / 신장비또한증가를보였다 (P< 0.001). AUC 값을이용하여대사증후군의진단력을비교시허리 / 신장비가다른지표들에비해우수하였다. 대사증후군의예측에있어서허리 / 신장비의적정절단값은 0.53으로나타났다. 결론 : 당뇨병전기환자에서대사증후군의간단하고유용한예측지표로써허리 / 신장비를이용할수있겠다. 중심단어 : 당뇨병전기, 대사증후군, 허리 / 신장비

7 Conflicts of Interest The authors have no conflicts of interest to declare. References 1. Korea Centers for Disease Control and Prevention. Korea Health Statistics 2011: Korea National Health and Nutrition Examination Survey (KNHANES V-2). Seoul: Korea Centers for Disease Control and Prevention; National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). 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) final report. Circulation 2002;106: Jia WP, Lu JX, Xiang KS, Bao YQ, Lu HJ, Chen L. Prediction of abdominal visceral obesity from body mass index, waist circumference and waist-hip ratio in Chinese adults: receiver operating characteristic curves analysis. Biomed Environ Sci 2003;16: Shao J, Yu L, Shen X, Li D, Wang K. Waist-to-height ratio, an optimal predictor for obesity and metabolic syndrome in Chinese adults. J Nutr Health Aging 2010;14: Park YS, Kim JS. Association between waist-to-height ratio and metabolic risk factors in Korean adults with normal body mass index and waist circumference. Tohoku J Exp Med 2012;228: Kim JI, Yu BC, Jeon MJ, Kim JM, Choi JS, Park JY, et al. Correlation of metabolic syndrome with waist circumference and waist-toheight ratio. Korean J Obes 2009;18: Kahn R, Buse J, Ferrannini E, Stern M; American Diabetes Association; European Association for the Study of Diabetes. The metabolic syndrome: time for a critical appraisal: joint statement from the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care 2005;28: Isomaa B, Almgren P, Tuomi T, Forsén B, Lahti K, Nissén M, et al. Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care 2001;24: Alexander CM, Landsman PB, Teutsch SM, Haffner SM; Third National Health and Nutrition Examination Survey (NHANES III); National Cholesterol Education Program (NCEP). NCEP-defined metabolic syndrome, diabetes, and prevalence of coronary heart disease among NHANES III participants age 50 years and older. Diabetes 2003;52: Hunt K, Resendez RG, Williams K, Haffner SM, Stern MP; San Antonio Heart Study. National Cholesterol Education Program versus World Health Organization metabolic syndrome in relation to allcause and cardiovascular mortality in the San Antonio Heart Study. Circulation 2004;110: Lakka HM, Laaksonen DE, Lakka TA, Niskanen LK, Kumpusalo E, Tuomilehto J, et al. The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. JAMA 2002;288: Lorenzo C, Williams K, Hunt KJ, Haffner SM. The National Cholesterol Education Program-Adult Treatment Panel III, International Diabetes Federation, and World Health Organization definitions of the metabolic syndrome as predictors of incident cardiovascular disease and diabetes. Diabetes Care 2007;30: Park HS, Oh SW, Kang JH, Park YW, Choi JM, Kim YS, et al. Prevalence and associated factors with metabolic syndrome in South Korea -from the Korean National Health and Nutrition Examination Survey, Korean J Obes 2003;12: Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Rev 2012;13: Park JH, Lim S, Lim JY, Kim KI, Han MK, Yoon IY, et al. An overview of the Korean longitudinal study on health and aging. Psychiatry Investig 2007;4: D Agostino RB Sr, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation 2008;117: American Diabetes Association. Standards of medical care in diabetes Diabetes Care 2014;37 Suppl 1: Lim DM, Park KY, Koh GP. The biochemical markers of coronary heart disease correlates better to metabolic syndrome defined by WHO than by NCEP-ATP III or IDF in Korean type 2 diabetic patients. Korean Diabetes J 2008;32: Lee SY, Park HS, Kim DJ, Han JH, Kim SM, Cho GJ, et al. Appropriate waist circumference cutoff points for central obesity in Korean adults. Diabetes Res Clin Pract 2007;75:

8 20. Daniels SR, Khoury PR, Morrison JA. The utility of body mass index as a measure of body fatness in children and adolescents: differences by race and gender. Pediatrics 1997;99: Quak SH, Furnes R, Lavine J, Baur LA; Obesity Working Group. Obesity in children and adolescents. J Pediatr Gastroenterol Nutr 2008;47: Yoo SY, Kim M, Kim S, Kim SH, Ko SJ, Beom JW, et al. Relationship between obesity indices and cardiovascular risk score in Korean type 2 diabetes patients. Korean J Obes 2013;22: Wang J, Thornton JC, Russell M, Burastero S, Heymsfield S, Pierson RN Jr. Asians have lower body mass index (BMI) but higher percent body fat than do whites: comparisons of anthropometric measurements. Am J Clin Nutr 1994;60: Després JP. Abdominal obesity as important component of insulinresistance syndrome. Nutrition 1993;9: Ritchie SA, Connell JM. The link between abdominal obesity, metabolic syndrome and cardiovascular disease. Nutr Metab Cardiovasc Dis 2007;17: Tan CE, Ma S, Wai D, Chew SK, Tai ES. Can we apply the National Cholesterol Education Program Adult Treatment Panel definition of the metabolic syndrome to Asians? Diabetes Care 2004;27: World Health Organization Western Pacific Region; International Association for the Study of Obesity; International Obesity Task Force. The Asia-Pacific perspective: redefining obesity and its treatment. Sydney: Health Communications Australia Pty Limited; Ashwell M, Lejeune S, McPherson K. Ratio of waist circumference to height may be better indicator of need for weight management. BMJ 1996;312: Hsieh SD, Yoshinaga H, Muto T, Sakurai Y, Kosaka K. Health risks among Japanese men with moderate body mass index. Int J Obes Relat Metab Disord 2000;24: Chowdhury TA, Grace C, Kopelman PG. Preventing diabetes in south Asians. BMJ 2003;327: Misra A, Khurana L. Obesity-related non-communicable diseases: South Asians vs White Caucasians. Int J Obes (Lond) 2011;35: Browning LM, Hsieh SD, Ashwell M. A systematic review of waistto-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0 5 could be a suitable global boundary value. Nutr Res Rev 2010;23: Liu L, Ping Z, Li L, Yang Y, Li C, Zhang M. Power and the cutoff value of waist-to-height ratio predicting metabolism syndrome. Wei Sheng Yan Jiu 2012;41: Macotela Y, Boucher J, Tran TT, Kahn CR. Sex and depot differences in adipocyte insulin sensitivity and glucose metabolism. Diabetes 2009;58: Otsuki M, Kasayama S, Saito H, Mukai M, Koga M. Sex differences of age-dependent changes of insulin sensitivity in Japanese nondiabetic subjects. Diabetes Care 2005;28: Bansal M, Shrivastava S, Mehrotra R, Agarwal V, Kasliwal RR. Low Framingham risk score despite high prevalence of metabolic syndrome in asymptomatic North-Indian population. J Assoc Physicians India 2009;57: Lee CM, Huxley RR, Wildman RP, Woodward M. Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: a meta-analysis. J Clin Epidemiol 2008;61: