Journal of Obesity & Metabolic Syndrome

Search

Article

September, 2022 | Vol.31 No.3

J Obes Metab Syndr 2022; 31(3): 263-271

Published online September 30, 2022 https://doi.org/10.7570/jomes22033

Copyright © Korean Society for the Study of Obesity.

Reference Values for Waist Circumference and Waist–Height Ratio in Korean Children and Adolescents

Jieun Lee1, Sung-Chan Kang2, Obin Kwon3, Seung-sik Hwang2, Jin Soo Moon4,5, Jaehyun Kim4,6,*

1Department of Pediatrics, Inje University Ilsan Paik Hospital, Goyang; 2Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul; 3Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul; 4Department of Pediatrics, Seoul National University College of Medicine, Seoul; 5Department of Pediatrics, Seoul National University Children’s Hospital, Seoul; 6Department of Pediatrics, Seoul National University Bundang Hospital, Seongnam, Korea

Correspondence to:
Jaehyun Kim
https://orcid.org/0000-0002-0203-7443
Department of Pediatrics, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82 Gumi-ro 173beon-gil, Bundang-gu, Seongnam 13620, Korea
Tel: +82-31-787-7287
Fax: +82-31-787-4054
E-mail: pedendo@snubh.org

Received: May 12, 2022; Reviewed : July 28, 2022; Accepted: August 9, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background: Abdominal obesity, which is a strong indicator of cardiometabolic risk, is widely evaluated using waist circumference (WC) and waist–height ratio (WHtR). In Korea, the reference values for WC for children and adolescents were published in 2007 and need to be revised. Moreover, there is no reference for WHtR. The aim of this study was to establish new reference values for WC and WHtR in Korean children and adolescents.
Methods: Data of 20,033 subjects from the Korea National Health and Nutrition Examination Survey (2007–2019) were used. Tables for reference values and the graphs of smoothed percentile curves of WC and WHtR for children and adolescents aged 2–18 years by sex were generated using the LMS method and locally estimated scatterplot smoothing regression analysis after removing extreme values.
Results: Sex-specific reference tables and percentile curves for WC and WHtR were developed. In the new WC curves, the 10th, 50th, and 90th percentile lines were lower than the corresponding lines of the 2007 reference for both sexes. The WHtR curves showed sex-specific differences, although they demonstrated a relative plateau among those aged ≥10 years in both sexes. In the logistic regression analysis, the WC and WHtR z-scores showed higher odds ratios for predicting cardiometabolic risk factors than the body mass index z-score.
Conclusion: New WC and WHtR reference values for Korean children and adolescents aged 2–18 years were developed using the latest statistical methods. These references will help monitor and track WC and WHtR for evaluating abdominal obesity among at-risk children and adolescents in Korea.

Keywords: Waist circumference, Waist–height ratio, Reference, Korea, Children, Adolescents

The prevalence of obesity among children and adolescents is increasing in many countries, accompanied by an increase in associated complications.1,2 This phenomenon has also been observed in Korea.3-5 Body mass index (BMI) has been traditionally used to diagnose obesity,6 with reference values for each population group.7-9 However, BMI has the drawback of not adequately reflecting the proportions of body fat and muscle mass because it is calculated by simply dividing body weight by the square of height.10

Several studies have recently identified pediatric abdominal obesity as a strong predictor of cardiometabolic risk factors and cardiovascular disease in adulthood.11,12 Waist circumference (WC) is the most commonly used method of evaluating abdominal obesity because of its simplicity. For diagnosis of metabolic syndrome (MS) in children and adolescents, as well as in adults, WC rather than BMI is used as a diagnostic criterion.13-15 However, WC is positively associated with height, limiting its accuracy as an indicator of abdominal obesity. Alternatively, the waist–height ratio (WHtR) has been used in recent years because it is consistent according to age and sex and is a good indicator for assessing abdominal obesity.

Because children and adolescents continue to grow physically, the normal values of WC and WHtR differ according to sex and age, necessitating sex- and age-specific reference values.16,17 Furthermore, children and adolescents with abdominal obesity are more likely to be classified as normal if the reference values are derived from data in which the prevalence of obesity is elevated. The currently used WC reference, which was published in the 2007 Korean National Growth Charts, has several drawbacks; specifically, its development did not adopt standardized measurements of WC, only included several percentile values, presented no graphical charts, and did not exclude children and adolescents with severe obesity.18,19

Therefore, a new WC reference needs to be established that adequately considers the increase in obesity using large-scale standardized anthropometric measurement data, and WHtR reference values also need to be developed. The purposes of this study were to present these values in the form of tables and charts and to compare the new reference values to BMI for predicting cardiometabolic risk factors using nationally representative survey data.

Study population

Data were obtained from the Korea National Health and Nutrition Examination Survey (KNHANES) conducted between 2007 and 2019. The KNHANES is an ongoing cross-sectional survey that collects nationally representative data. Although it has been conducted since 1998 by the Korean Centers for Disease Control and Prevention, data collected between 2007–2019 were included in the present study because the survey design and detailed methods were updated in 2007. The sampling of KNHANES data among non-institutionalized citizens in Korea employs a stratified, multistage, clustered probability method. Each KNHANES consists of a health interview, an examination, and a nutrition survey. The data collection procedures of KNHANES have been described in detail elsewhere.20 Among the 113,724 individuals enrolled in the KNHANES during 2007−2019, 22,495 (11,613 boys and 10,882 girls) aged ≤20 years with anthropometric data, including height, weight, and WC, were considered as candidates for WC and WHtR reference development in this study. Among them, 20,033 participants aged 2−18 years were finally included in analysis of reference curves and tables. For the reference evaluation, participants aged 10−18 years with blood pressure (BP) or laboratory data (12,158 individuals) were included (Supplementary Fig. 1).

Anthropometric measurements

Height, weight, and WC were measured by trained medical personnel. Height was measured to the nearest 0.1 cm using a stadiometer (Seca 225; Seca, Hamburg, Germany). Weight was measured to the nearest 0.1 kg using an electronic balance (GL-6000-20; Gtech, Seoul, Korea). BMI was calculated as weight (kg) divided by height squared (m2). Height, weight, and BMI values were transformed into z-scores using the 2017 Korean National Growth Chart.9 WC was measured using a flexible tape (Seca 220) to the nearest 0.1 cm at the midpoint between the lowest margin of the rib and the highest margin of the iliac crest during expiration. WHtR was calculated as WC (cm) divided by height (cm). BP was measured three times on the right arm using a mercury sphygmomanometer with a cuff appropriate for arm circumference after the participant had rested for ≥5 minutes in a sitting position (Baumanometer Desk model 0320 in 2007–2012 and Baumanometer Wall Unit 33[0850] in 2013– 2019; W.A. Baum, Copiague, NY, USA). The mean values of the second and third systolic and diastolic BP measurements were analyzed in this study.

Laboratory tests

Blood samples were collected by trained medical personnel. Fasting blood samples obtained from venipuncture were transported to a central laboratory for analysis within 24 hours. Plasma glucose, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride levels were measured using a Hitachi Automatic Analyzer 7600 (Hitachi, Tokyo, Japan). The glycated hemoglobin (HbA1c) level was measured via high-performance liquid chromatography (HPLC-723G7; Tosoh, Tokyo, Japan), which is the method certified by the National Glycohemoglobin Standardization Program.

Definitions of abnormal cardiometabolic risk factors

High BP was defined as systolic or diastolic BP ≥90th percentile for corresponding sex, age, and height. High fasting glucose and elevated HbA1c were defined as fasting glucose ≥100 mg/dL and HbA1c ≥5.7%, respectively. Lipid abnormalities were defined as follows: triglycerides ≥150 mg/dL, LDL-C ≥130 mg/dL, non– HDL-C ≥145 mg/dL (obtained by subtracting HDL-C from TC), and HDL-C <40 mg/dL.

Generation of reference curves and LMS table

To derive reference values for WC and WHtR using data from the KNHANES 2007−2019, growth charts for WC and WHtR were generated through a method similar to that applied for development of the 2017 Korean National Growth Charts.9 Among KNHANES participants 1–20 years of age, those with weight for height <−3 standard deviation (SD) or >+2 SD were excluded. These cutoff values for subject selection were used in previous Korean Growth Charts and are considered appropriate for preventing skewness.9 Using the selected data, reference values for WC and WHtR were generated. The empirically used percentile values of WC and WHtR, including the 3rd, 5th, 10th, 25th, 50th, 75th, 90th, 95th, and 97th percentiles, were calculated by each age and sex. Locally estimated scatterplot smoothing (LOESS) regression was performed to smooth each percentile curve in Stata 16.1 (StataCorp., College Station, TX, USA); “LOESS” defines a process of locally weighted regression for estimating smoothed curves from scattered plots.21

The z-scores and percentile values for WC and WHtR were calculated using Box-Cox transformation and the LMS method, where L, M, and S stand for the power of Box-Cox transformation, the median, and the coefficient of variation, respectively.22,23 A non-linear least-squares analysis was used for estimation of the L, M, and S values. Tables containing L, M, and S values and each percentile value of WC and WHtR according to sex and age were generated. The z-score was calculated using L, M, and S values as z=[(x/M(t)) L(t)−1]/[L(t)S(t)], where x stands for the WC or WHtR value and t stands for age at measurement.

WC and WHtR curves for children and adolescents aged 1–20 years were produced, but only the curves for those aged 2–18 years were presented to avoid an edge effect at both age extremes.24 Each curve demonstrated the 3rd, 5th, 10th, 25th, 50th, 75th, 90th, 95th, and 97th percentiles of WC and WHtR by sex.

Statistical analysis

All statistical analyses were performed using Stata 16.1. Simple linear regression analysis was applied to evaluate the correlation between WC z-scores and WHtR z-scores. Logistic regression analysis was performed to evaluate the associations between cardiometabolic risk factors and the z-scores of WC, WHtR, and BMI, which were presented as odds ratios (ORs) and 95% confidence intervals (CIs) after adjusting for age and sex. The P-value <0.05 was considered statistically significant.

Ethics statement

The present study protocol was reviewed and approved by the Institutional Review Board of Seoul National University Bundang Hospital (No. X-1909-565-904). All subjects submitted informed consent upon enrollment.

New references for WC and WHtR

The newly developed curves for WC and WHtR for Korean children and adolescents are presented in Figs. 1 and 2. In Tables 1 and 2, the LMS values for z-score calculation and the 3rd, 5th, 10th, 25th, 50th, 75th, 90th, 95th, and 97th percentiles by sex and age are demonstrated. Compared with the WC curves presented in the 2007 growth chart, every line in the new chart was lower than the corresponding line (Fig. 3). The WHtR curves showed sex-specific differences, although they demonstrated a relative plateau among those aged ≥10 years regardless of sex.

Correlation between WC and WHtR

Using the newly developed charts for WC and WHtR, the zscores of WC and WHtR were significantly correlated (r2=0.846, P<0.001 for boys; r2=0.834, P<0.001 for girls) (Supplementary Fig. 2).

ORs for predicting cardiometabolic risk factors by z-scores of WC, WHtR, and BMI

In logistic regression analysis, the WC z-score and WHtR z-score using the newly developed charts revealed higher adjusted ORs for all cardiometabolic risk factors than the BMI z-score (Table 3).

In the present study, new reference values for WC and WHtR in Korean children and adolescents were developed using up-to-date statistical methodology. Age- and sex-specific tables and charts of WC and WHtR were derived. In particular, the LMS values for WC and WHtR were added to calculate the z-score or percentile for the corresponding sex and age, which can help to diagnose abdominal obesity and determine cardiometabolic risk in Korean children and adolescents.

Abdominal obesity is associated with abundant visceral fat, which is an important metabolic factor with a close link to cardiovascular disease. Additionally, abdominal obesity is one of the diagnostic criteria for MS in both children and adults.13-15 WC, which varies according to population, is the most widely used method for diagnosing abdominal obesity. For adults, WC ≥90 cm for men and ≥85 cm for women is the diagnostic criterion for abdominal obesity in Korea.25 In children and adolescents, WC ≥90th percentile for sex and age has been defined as abdominal obesity.13,15,17 In Korea, the 2007 Korean National Growth Charts have been used as a reference for WC.18 However, updates to these charts to address their limitations, including lack of standardized measurements for WC, inclusion of few percentile values, absence of graphical charts, and non-exclusion of children and adolescents of extreme weight, have been overdue.19

Compared with the WC curves presented in the 2007 growth charts, every line in the newly developed chart was lower than the corresponding line (Fig. 3). This result mainly originates from inclusion of extreme values in the 2007 reference. Abdominal obesity might be underestimated if the reference values are derived using raw data containing extreme values. To overcome the drawbacks of previous reference charts, the newly developed WC reference adopted up-to-date statistical methodology, such as the removal of subjects with extreme weight, smoothing of percentile lines, and the LMS estimation method, which was applied in the 2017 Korean National Growth Charts.9 These methods have been used to develop growth charts in other countries.8,26

In a recent study, the prevalence of abdominal obesity in Korean children and adolescents aged 10–18 years was estimated as 9.66% using the 2007 reference values.27 However, this might be an underestimation. Moreover, further research is required because underestimating abdominal obesity might lead to an underestimation of MS, since abdominal obesity is one of the major diagnostic criteria for MS. WHtR, which is calculated as WC divided by height, has been used for diagnosis of abdominal obesity.28 WHtR could be useful for defining abdominal obesity because it is easy to calculate and has a simple cutoff value of ≥0.5.29

However, there are several concerns regarding the use of WHtR of 0.5 as a criterion for abdominal obesity in children and adolescents.30 According to a recent study of Korean adolescents 13−18 years of age, the cutoff value of WHtR for diagnosing abdominal obesity was 0.48, which is lower than 0.5.19 For Japanese children aged 9−11 years, WHtR values of 0.519 for boys and 0.499 for girls were determined to be the most appropriate cutoffs for diagnosing abdominal obesity.31 International studies have also shown that the WHtR cutoff of 0.5, which is mainly used in adults, is not applicable to children or adolescents, who are still growing, and that it would be better to use WHtR percentiles that are specific for age and sex.16,32 As shown in the newly created graph in this study, it is difficult to apply this criterion because of the high WHtR values in young ages, especially those younger than 6 years. Therefore, children and adolescents with WHtR ≥0.5 are highly likely to have abdominal obesity, so further evaluation may be necessary. However, in children and adolescents, it seems more appropriate to evaluate WHtR using percentiles rather than a single value.

A recent study using KNHANES data to analyze WHtR in children and adolescents aged 10−18 years showed LMS data and percentile values, but it was limited by the lack of data from subjects under the age of 10, that the analysis was conducted without removing extreme values, and the possibility of WHtR variability at both ends of the age spectrum.33 In the present study, reference data and charts were presented to compensate for those shortcomings.

WC is the most widely used indicator of abdominal obesity; however, it has a positive correlation with height. Therefore, it may be more reasonable to define abdominal obesity using WHtR than WC, but further research is needed to determine the optimal cutoff point. WC and WHtR are important abdominal obesity-related indicators associated with cardiometabolic risk factors and MS.12 It is not clear which of these indicators is superior, although a study has shown that WHtR reflects body fat better than WC in children and adolescents.34 WHtR may be widely used as a screening risk factor for cardiometabolic risk due to its simplicity of calculation, even if it is not superior to WC.11 In this study, WC and WHtR had a similar ability to predict cardiometabolic risk factors (Table 3).

There were several limitations of the present study. First, the charts were derived from cross-sectional data. Second, the WC and WHtR values from the KNHANES data were presented according to ages in years, not months, limiting the degree to which the reference values could be precisely applied for more narrowly defined age groups.

In conclusion, WC and WHtR reference values were developed using up-to-date methodology and the latest nationally representative anthropometric data. Sex-specific tables and charts for children and adolescents aged 2–18 years were presented with LMS values for calculating z-scores or percentiles. The newly developed WC and WHtR reference values are expected to be widely used in clinical practice to monitor and track abdominal obesity, cardiometabolic risk, and MS among at-risk children and adolescents in Korea.

This research was supported by grant no. 09-2019-0008 from the Seoul National University Bundang Hospital Research Fund.

Study concept and design: JK; acquisition of data: JL and JK; analysis and interpretation of data: SCK and SSH; drafting of the manuscript: JL, OK, and JK; critical revision of the manuscript; JL, SCK, OK, SSH, and JSM; statistical analysis: SCCK and SSH; funding acquisition: JK; administrative, technical, or material support: JK; and study supervision: JK and JSM.

Fig. 1. Reference curves for waist circumference of (A) boys and (B) girls aged 2–18 years.
Fig. 2. Reference curves for the waist–height ratio of (A) boys and (B) girls aged 2–18 years.
Fig. 3. Comparison of waist circumference curves for (A) boys and (B) girls between the 2007 growth charts and newly developed curves.

LMS and percentile table for waist circumference in Korean children and adolescents

Sex Age (yr) n L M (50p) S 3p 5p 10p 25p 50p 75p 90p 95p 97p
Boy 2 586 −0.46160 46.17471 0.064427 41.0 41.6 42.6 44.2 46.2 48.2 50.2 51.5 52.3
3 591 −1.80538 47.66428 0.070499 42.3 42.9 43.8 45.5 47.7 50.1 52.6 54.3 55.5
4 580 −2.18294 49.45274 0.077562 43.6 44.2 45.2 47.1 49.5 52.3 55.3 57.4 58.9
5 629 −2.04301 51.49984 0.085952 44.8 45.5 46.6 48.8 51.5 54.8 58.3 60.9 62.7
6 643 −1.74740 53.71601 0.094680 46.0 46.8 48.1 50.6 53.7 57.5 61.6 64.4 66.5
7 682 −1.46010 56.01971 0.102807 47.2 48.2 49.7 52.4 56.0 60.3 64.8 68.0 70.3
8 669 −1.20933 58.38451 0.109967 48.5 49.6 51.3 54.4 58.4 63.1 68.1 71.6 74.1
9 674 −1.00680 60.78231 0.115709 49.9 51.1 52.9 56.4 60.8 65.9 71.4 75.1 77.7
10 700 −0.85857 63.13635 0.119684 51.4 52.6 54.7 58.4 63.1 68.6 74.4 78.3 81.1
11 711 −0.76233 65.35514 0.121891 52.9 54.2 56.4 60.3 65.4 71.1 77.2 81.2 84.1
12 685 −0.71640 67.36473 0.122568 54.4 55.8 58.0 62.2 67.4 73.4 79.6 83.8 86.7
13 665 −0.72126 69.13278 0.121981 55.9 57.3 59.6 63.8 69.1 75.3 81.6 85.9 88.8
14 619 −0.76276 70.66959 0.120405 57.3 58.8 61.1 65.3 70.7 76.8 83.3 87.6 90.6
15 566 −0.82339 72.00486 0.118372 58.7 60.1 62.4 66.6 72.0 78.2 84.7 89.0 92.1
16 507 −0.89788 73.17873 0.116209 59.9 61.3 63.6 67.8 73.2 79.4 85.9 90.3 93.3
17 528 −0.94784 74.23581 0.114288 61.0 62.4 64.7 68.9 74.2 80.4 86.9 91.3 94.4
18 473 −0.93330 75.21364 0.113025 62.0 63.4 65.7 69.9 75.2 81.4 87.9 92.3 95.3
Girl 2 535 −0.79872 45.59727 0.066008 40.5 41.1 42.0 43.6 45.6 47.7 49.8 51.1 52.0
3 535 −1.21909 47.13511 0.070592 41.7 42.3 43.3 45.0 47.1 49.5 51.9 53.4 54.5
4 543 −1.43154 48.75516 0.076615 42.8 43.4 44.5 46.4 48.8 51.4 54.2 56.0 57.3
5 551 −1.47393 50.48406 0.083117 43.9 44.6 45.7 47.8 50.5 53.5 56.7 58.8 60.3
6 586 −1.45031 52.29172 0.089422 45.0 45.8 47.0 49.4 52.3 55.7 59.3 61.7 63.4
7 687 −1.42062 54.14407 0.095149 46.2 47.0 48.4 50.9 54.1 57.9 61.9 64.6 66.6
8 630 −1.39762 56.02879 0.099925 47.4 48.3 49.8 52.5 56.0 60.1 64.5 67.5 69.7
9 641 −1.38122 57.93044 0.103242 48.8 49.7 51.3 54.2 57.9 62.3 67.0 70.3 72.6
10 629 −1.36602 59.79364 0.104943 50.2 51.2 52.8 55.9 59.8 64.4 69.4 72.8 75.3
11 604 −1.34078 61.55038 0.105249 51.6 52.7 54.4 57.5 61.6 66.3 71.4 75.0 77.5
12 577 −1.30320 63.14767 0.104503 53.0 54.1 55.8 59.0 63.1 68.0 73.2 76.7 79.2
13 568 −1.25131 64.56843 0.103117 54.3 55.4 57.1 60.4 64.6 69.4 74.6 78.1 80.6
14 560 −1.18309 65.79813 0.101334 55.4 56.5 58.3 61.6 65.8 70.7 75.8 79.2 81.7
15 488 −1.08787 66.83626 0.099396 56.4 57.5 59.3 62.6 66.8 71.7 76.7 80.0 82.4
16 489 −0.95484 67.70425 0.097553 57.2 58.3 60.2 63.5 67.7 72.5 77.3 80.6 82.8
17 491 −0.78421 68.41050 0.096235 57.8 58.9 60.8 64.2 68.4 73.1 77.9 81.0 83.2
18 411 −0.58900 68.99906 0.095783 58.1 59.3 61.3 64.8 69.0 73.7 78.4 81.4 83.5

L, M, and S indicate the power of Box-Cox transformation, the median, and the coefficient of variation, respectively.

p, percentile.

LMS and percentile table for waist–height ratio in Korean children and adolescents

Sex Age (yr) n L M (50p) S 3p 5p 10p 25p 50p 75p 90p 95p 97p
Boy 2 586 −0.68803 0.511707 0.065541 0.455 0.461 0.472 0.490 0.512 0.535 0.558 0.572 0.582
3 591 −1.22103 0.492246 0.067275 0.438 0.444 0.454 0.471 0.492 0.516 0.539 0.554 0.565
4 580 −1.54083 0.477128 0.070717 0.423 0.429 0.438 0.456 0.477 0.501 0.526 0.542 0.554
5 629 −1.60893 0.465715 0.075712 0.410 0.416 0.426 0.443 0.466 0.491 0.518 0.535 0.547
6 643 −1.51497 0.457052 0.081728 0.398 0.404 0.415 0.433 0.457 0.484 0.512 0.531 0.544
7 682 −1.38026 0.450268 0.088185 0.388 0.395 0.405 0.425 0.450 0.479 0.509 0.529 0.544
8 669 −1.23371 0.445333 0.094751 0.379 0.386 0.398 0.419 0.445 0.476 0.508 0.529 0.545
9 674 −1.08910 0.441869 0.100854 0.372 0.379 0.392 0.414 0.442 0.474 0.508 0.531 0.546
10 700 −0.96423 0.439259 0.105908 0.366 0.374 0.387 0.410 0.439 0.473 0.508 0.532 0.548
11 711 −0.87059 0.437063 0.109668 0.362 0.370 0.383 0.407 0.437 0.472 0.508 0.532 0.549
12 685 −0.80736 0.435027 0.112101 0.358 0.366 0.380 0.404 0.435 0.470 0.507 0.531 0.548
13 665 −0.78237 0.433102 0.113295 0.356 0.364 0.377 0.402 0.433 0.469 0.505 0.530 0.547
14 619 −0.78232 0.431529 0.113374 0.354 0.363 0.376 0.401 0.432 0.467 0.503 0.528 0.545
15 566 −0.77991 0.430563 0.112740 0.354 0.362 0.375 0.400 0.431 0.466 0.502 0.526 0.543
16 507 −0.76308 0.430446 0.111749 0.354 0.362 0.376 0.400 0.430 0.465 0.501 0.525 0.541
17 528 −0.70319 0.431689 0.110815 0.355 0.364 0.377 0.401 0.432 0.466 0.501 0.525 0.541
18 473 −0.59452 0.434435 0.110293 0.357 0.366 0.379 0.404 0.434 0.469 0.504 0.526 0.542
Girl 2 535 −0.78899 0.513219 0.066771 0.455 0.462 0.472 0.491 0.513 0.537 0.561 0.576 0.586
3 535 −0.86703 0.492829 0.068611 0.436 0.443 0.453 0.471 0.493 0.517 0.540 0.555 0.565
4 543 −0.99313 0.475781 0.071779 0.419 0.426 0.436 0.454 0.476 0.500 0.524 0.539 0.550
5 551 −1.04975 0.461727 0.075721 0.404 0.411 0.421 0.439 0.462 0.487 0.511 0.528 0.539
6 586 −1.09436 0.449887 0.080062 0.391 0.398 0.408 0.427 0.450 0.476 0.502 0.519 0.530
7 687 −1.15661 0.439914 0.084519 0.380 0.387 0.397 0.416 0.440 0.467 0.494 0.512 0.524
8 630 −1.22057 0.432243 0.088818 0.371 0.378 0.389 0.408 0.432 0.460 0.489 0.508 0.521
9 641 −1.25775 0.426862 0.092434 0.365 0.371 0.382 0.402 0.427 0.455 0.485 0.505 0.519
10 629 −1.25050 0.423371 0.095086 0.360 0.367 0.378 0.398 0.423 0.453 0.483 0.504 0.518
11 604 −1.20196 0.421313 0.096754 0.357 0.364 0.375 0.396 0.421 0.451 0.482 0.503 0.517
12 577 −1.13585 0.420265 0.097539 0.356 0.363 0.374 0.394 0.420 0.450 0.481 0.502 0.516
13 568 −1.07927 0.419971 0.097671 0.355 0.362 0.373 0.394 0.420 0.450 0.480 0.501 0.515
14 560 −1.03214 0.420323 0.097327 0.355 0.362 0.374 0.394 0.420 0.450 0.480 0.501 0.515
15 488 −0.95745 0.421321 0.096743 0.356 0.363 0.375 0.395 0.421 0.451 0.481 0.501 0.515
16 489 −0.83567 0.422940 0.096131 0.357 0.365 0.376 0.397 0.423 0.452 0.482 0.501 0.515
17 491 −0.69290 0.424982 0.095723 0.359 0.366 0.378 0.399 0.425 0.454 0.483 0.502 0.515
18 411 −0.55851 0.427279 0.095646 0.360 0.367 0.380 0.401 0.427 0.456 0.485 0.504 0.516

L, M, and S indicate the power of Box-Cox transformation, the median, and the coefficient of variation, respectively.

p, percentile.

Odds ratios and 95% CIs for cardiometabolic risk factors by z-scores of WC and WHtR

Cardiometabolic risk factor z-score Odds ratio* 95% CI
High blood pressure (n = 11,278) WC 1.47 1.39–1.56
WHtR 1.48 1.40–1.57
BMI 1.42 1.35–1.49
High fasting glucose (n = 9,686) WC 1.35 1.24–1.46
WHtR 1.34 1.24–1.46
BMI 1.30 1.22–1.38
Elevated glycated hemoglobin (n = 6,369) WC 1.21 1.12–1.30
WHtR 1.19 1.10–1.28
BMI 1.17 1.09–1.24
High triglycerides (n = 9,715) WC 2.01 1.85–2.18
WHtR 1.95 1.80–2.11
BMI 1.68 1.57–1.79
High LDL-C (n = 9,715) WC 1.61 1.46–1.78
WHtR 1.70 1.55–1.86
BMI 1.53 1.42–1.64
High non–HDL-C (n = 9,930) WC 1.80 1.65–1.96
WHtR 1.89 1.74–2.05
BMI 1.66 1.55–1.77
Low HDL-C (n = 9,930) WC 1.62 1.52–1.72
WHtR 1.60 1.51–1.70
BMI 1.49 1.42–1.57

*Adjusted for age and sex.

CI, confidence interval; WC, waist circumference; WHtR, waist–height ratio; BMI, body mass index; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol.

  1. Skinner AC, Perrin EM, Moss LA, Skelton JA. Cardiometabolic risks and severity of obesity in children and young adults. N Engl J Med 2015;373:1307-17.
    Pubmed CrossRef
  2. NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 populationbased measurement studies in 128·9 million children, adolescents, and adults. Lancet 2017;390:2627-42.
  3. Kim JH, Moon JS. Secular trends in pediatric overweight and obesity in Korea. J Obes Metab Syndr 2020;29:12-7.
    Pubmed KoreaMed CrossRef
  4. Lee J, Kim JH. Endocrine comorbidities of pediatric obesity. Clin Exp Pediatr 2021;64:619-27.
    Pubmed KoreaMed CrossRef
  5. Seo MY, Kim SH, Park MJ. Changes in anthropometric indices among Korean school students based on the 2010 and 2018 Korea School Health Examination Surveys. Ann Pediatr Endocrinol Metab 2021;26:38-45.
    Pubmed KoreaMed CrossRef
  6. Styne DM, Arslanian SA, Connor EL, Farooqi IS, Murad MH, Silverstein JH, et al. Pediatric obesity-assessment, treatment, and prevention: an Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab 2017;102:709-57.
    Pubmed KoreaMed CrossRef
  7. Freeman JV, Cole TJ, Chinn S, Jones PR, White EM, Preece MA. Cross sectional stature and weight reference curves for the UK, 1990. Arch Dis Child 1995;73:17-24.
    Pubmed KoreaMed CrossRef
  8. Ogden CL, Kuczmarski RJ, Flegal KM, Mei Z, Guo S, Wei R, et al. Centers for Disease Control and Prevention 2000 growth charts for the United States: improvements to the 1977 National Center for Health Statistics version. Pediatrics 2002;109:45-60.
    Pubmed CrossRef
  9. Kim JH, Yun S, Hwang SS, Shim JO, Chae HW, Lee YJ, et al. The 2017 Korean National Growth Charts for children and adolescents: development, improvement, and prospects. Korean J Pediatr 2018;61:135-49.
    Pubmed KoreaMed CrossRef
  10. Kim JH. Overview of pediatric obesity: diagnosis, epidemiology, and significance. J Korean Med Assoc 2021;64:401-9.
    CrossRef
  11. Lo K, Wong M, Khalechelvam P, Tam W. Waist-to-height ratio, body mass index and waist circumference for screening paediatric cardio-metabolic risk factors: a meta-analysis. Obes Rev 2016;17:1258-75.
    Pubmed CrossRef
  12. Seo JY, Kim JH. Validation of surrogate markers for metabolic syndrome and cardiometabolic risk factor clustering in children and adolescents: a nationwide population-based study. PLoS One 2017;12:e0186050.
    Pubmed KoreaMed CrossRef
  13. Cook S, Weitzman M, Auinger P, Nguyen M, Dietz WH. Prevalence of a metabolic syndrome phenotype in adolescents: findings from the third National Health and Nutrition Examination Survey, 1988-1994. Arch Pediatr Adolesc Med 2003;157:821-7.
    Pubmed CrossRef
  14. de Ferranti SD, Gauvreau K, Ludwig DS, Neufeld EJ, Newburger JW, Rifai N. Prevalence of the metabolic syndrome in American adolescents: findings from the Third National Health and Nutrition Examination Survey. Circulation 2004;110:2494-7.
    Pubmed CrossRef
  15. Zimmet P, Alberti KG, Kaufman F, Tajima N, Silink M, Arslanian S, et al. The metabolic syndrome in children and adolescents: an IDF consensus report. Pediatr Diabetes 2007;8:299-306.
    Pubmed CrossRef
  16. Sharma AK, Metzger DL, Daymont C, Hadjiyannakis S, Rodd CJ. LMS tables for waist-circumference and waist-height ratio Z-scores in children aged 5-19 y in NHANES III: association with cardio-metabolic risks. Pediatr Res 2015;78:723-9.
    Pubmed CrossRef
  17. Xi B, Zong X, Kelishadi R, Litwin M, Hong YM, Poh BK, et al. International waist circumference percentile cutoffs for central obesity in children and adolescents aged 6 to 18 years. J Clin Endocrinol Metab 2020;105:e1569-83.
    Pubmed CrossRef
  18. Moon JS, Lee SY, Nam CM, Choi JM, Choe BK, Seo JW, et al. 2007 Korean National Growth Charts: review of developmental process and an outlook. Korean J Pediatr 2008;51:1-25.
    CrossRef
  19. Kim MS, Kim SY, Kim JH. Secular change in waist circumference and waist-height ratio and optimal cutoff of waist-height ratio for abdominal obesity among Korean children and adolescents over 10 years. Korean J Pediatr 2019;62:261-8.
    Pubmed KoreaMed CrossRef
  20. Kweon S, Kim Y, Jang MJ, Kim Y, Kim K, Choi S, et al. Data resource profile: the Korea National Health and Nutrition Examination Survey (KNHANES). Int J Epidemiol 2014;43:69-77.
    Pubmed KoreaMed CrossRef
  21. Cleveland WS. Robust locally weighted regression and smoothing scatterplots. J Am Stat Assoc 1979;74:829-36.
    CrossRef
  22. Box GE, Cox DR. An analysis of transformations. J R Stat Soc Series B Methodol 1964;26:211-43.
    CrossRef
  23. Cole TJ. The LMS method for constructing normalized growth standards. Eur J Clin Nutr 1990;44:45-60.
  24. Borghi E, de Onis M, Garza C, Van den Broeck J, Frongillo EA, Grummer-Strawn L, et al. Construction of the World Health Organization child growth standards: selection of methods for attained growth curves. Stat Med 2006;25:247-65.
    Pubmed CrossRef
  25. Kim BY, Kang SM, Kang JH, Kang SY, Kim KK, Kim KB, et al. 2020 Korean Society for the Study of Obesity Guidelines for the management of obesity in Korea. J Obes Metab Syndr 2021;30:81-92.
    Pubmed KoreaMed CrossRef
  26. Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z, et al. 2000 CDC Growth Charts for the United States: methods and development. Vital Health Stat 11 2002;246:1-190.
  27. Park SI, Suh J, Lee HS, Song K, Choi Y, Oh JS, et al. Ten-year trends of metabolic syndrome prevalence and nutrient intake among Korean children and adolescents: a population-based study. Yonsei Med J 2021;62:344-51.
    Pubmed KoreaMed CrossRef
  28. McCarthy HD, Ashwell M. A study of central fatness using waist-to-height ratios in UK children and adolescents over two decades supports the simple message: 'keep your waist circumference to less than half your height'. Int J Obes (Lond) 2006;30:988-92.
    Pubmed CrossRef
  29. 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;13:275-86.
    Pubmed CrossRef
  30. Bacopoulou F, Efthymiou V, Landis G, Rentoumis A, Chrousos GP. Waist circumference, waist-to-hip ratio and waist-toheight ratio reference percentiles for abdominal obesity among Greek adolescents. BMC Pediatr 2015;15:50.
    Pubmed KoreaMed CrossRef
  31. Fujita Y, Kouda K, Nakamura H, Iki M. Cut-off values of body mass index, waist circumference, and waist-to-height ratio to identify excess abdominal fat: population-based screening of Japanese school children. J Epidemiol 2011;21:191-6.
    Pubmed KoreaMed CrossRef
  32. Roswall J, Bergman S, Almqvist-Tangen G, Alm B, Niklasson A, Nierop AF, et al. Population-based waist circumference and waist-to-height ratio reference values in preschool children. Acta Paediatr 2009;98:1632-6.
    Pubmed CrossRef
  33. Lee HJ, Shim YS, Yoon JS, Jeong HR, Kang MJ, Hwang IT. Distribution of waist-to-height ratio and cardiometabolic risk in children and adolescents: a population-based study. Sci Rep 2021;11:9524.
    Pubmed KoreaMed CrossRef
  34. Brambilla P, Bedogni G, Heo M, Pietrobelli A. Waist circumference-to-height ratio predicts adiposity better than body mass index in children and adolescents. Int J Obes (Lond) 2013;37:943-6.
    Pubmed CrossRef