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Ann Pediatr Endocrinol Metab > Volume 27(4); 2022 > Article
Kim and Kim: Cardiometabolic risk factors and metabolic syndrome based on severity of obesity in Korean children and adolescents: data from the Korea National Health and Nutrition Examination Survey 2007–2018

Abstract

Purpose

Data regarding cardiometabolic risk factors (CMRFs) and metabolic syndrome (MetS) by body mass index (BMI) category in Korean youth are sparse.

Methods

Among the participants of the Korea National Health and Nutrition Examination Survey 2007–2018, 9,984 youth aged 10–18 years were included in the study. Participants were classified into 4 groups based on BMI status: normal weight, overweight, class I, and class II/III obesity. CMRF prevalence, including total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, blood pressure, fasting glucose, glycated hemoglobin, and MetS, were determined using the International Diabetes Federation (IDF) and modified National Cholesterol Education Program-Adult Treatment Panel (NCEP-ATP) III criteria based on BMI category.

Results

The prevalence of overweight, class I, class II, and class III obesity was 9.52%, 7.73%, 2.10%, and 0.32%, respectively. Mean CMRF values increased with BMI, except high-density lipoprotein cholesterol. Age- and sex-adjusted odds ratios (ORs) for prediction of CMRFs also increased with BMI. Adjusted ORs for MetS among overweight, class I, and class II/II obesity were 54.2, 283.3, and 950.3 for IDF criteria and 9.56, 37.9, and 126.8 for NCEP-ATP III criteria, respectively (all p<0.001).

Conclusions

Class II and III obesity in Korean children and adolescents was associated with significantly increased CMRF and MetS prevalence. Therefore, it can be useful to measure CMRFs in obese children and adolescents. Further studies are required to establish screening guidelines based on obesity severity.

Highlights

· Obesity could be categorized as class I, II and III according to body mass index.
· Values of cardiometabolic risk factors worsened with BMI increase.
· Class II and III obesity in Korean youth was associated with an increased prevalence of cardiometabolic risk factors and metabolic syndrome.

Introduction

The prevalence of obesity and metabolic syndrome (MetS) among children and adolescents is increasing, both in Korea and worldwide [1-5]. According to the Korea National Health and Nutrition Examination Survey (KNHANES) data, in children and adolescents 10–19 years of age, the prevalence of overweight and obesity in 1998, 2001, and 2005 was 16.4%, 23.8%, and 24.2%, respectively [2,4,6]. As the prevalence of obesity has increased, the degree of obesity has been classified in greater detail using several criteria. According to recent guidelines, class I obesity in children and adolescents is defined as a body mass index (BMI; weight [kg] divided by height squared [m2]) ≥ 95th percentile; class II/III obesity is defined as a BMI ≥120% of the 95th percentile for age and sex [7-10].
MetS is defined as a combination of cardiometabolic risk factors (CMRFs) including abnormal waist circumference (WC), blood pressure (BP), triglycerides level, high-density lipoprotein cholesterol (HDL-C) level, and glucose level [11]. MetS increases among individuals with obesity; it is a well-known risk factor for cardiovascular disease, type 2 diabetes mellitus, and hypertension in both children and adults [12-14]. Despite the clinical importance of MetS, uniform consensus cutoff values for MetS components in children and adolescents have not been established. Thus, there are differences in the markers and cutoff values based on set of criteria [15].
In several studies, associations with various CMRFs were reported to increase with increasing obesity severity [4,8,9,16]. Although few studies of Korean children and adolescents have been conducted, the data are outdated and do not reflect the latest criteria. Furthermore, there are sparse data regarding the prevalence of MetS based on degree of obesity [17]. Therefore, in this study, data on CMRF and MetS prevalence based on obesity severity in Korean children and adolescents were analyzed using the latest updated criteria of nationally representative data. Additionally, associations with the prevalence of various CMRFs were examined based on obesity severity.

Materials and methods

1. Study participants

Data used in this study were obtained from the fourth to seventh waves of the KNHANES performed between 2007 and 2018. The KNHANES is a cross-sectional survey that involves nationally representative data collection; it has been conducted since 1998 by the Korea Centers for Disease Control and Prevention. The KNHANES was designed using a stratified multi-stage clustered probability sampling method among noninstitutionalized citizens in Korea. The KNHANES consists of a health interview, nutrition survey, and health examination. Detailed methods for KNHANES data collection are described elsewhere [18].
Among the 97,662 individuals enrolled in the KNHANES during 2007−2018, 9,984 (5,305 boys and 4,709 girls) 10–18 years of age with anthropometric data including height, weight, and BMI were considered as candidates for analysis. The participants analyzed in the study are described in Table 1. Participants with no values for total cholesterol (TC), HDL-C, low-density lipoprotein cholesterol (LDL-C), triglycerides, or fasting glucose were excluded. Participants who fasted <8 hours were also excluded. The non-HDL-C level was calculated as the HDL-C level subtracted from the TC level (non-HDL-C = TC−HDL-C). Participants with no values for BP or glycated hemoglobin (HbA1c) were excluded, as were participants with no values for any component of MetS.

2. Anthropometric measurements

Anthropometric measurements, including height, weight, and WC, were performed 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; G-tech, Seoul, Korea). BMI was calculated as weight (kg) divided by height squared (m2). Height, weight, and BMI were transformed to percentile values using the 2017 Korean National Growth Chart [19]. WC was measured using a flexible tape to the nearest 0.1 cm at the midpoint between the lowermost margin of the rib and the uppermost margin of the iliac crest during the expiratory phase of respiration (Seca 220; Seca). 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 at least 5 minutes in a sitting position (Baumanometer Desk model 0320 in 2007–2012 and Baumanometer Wall Unit 33 [0850] in 2013–2018; W.A. Baum, Copiague, NY, USA). The mean values of the second and third systolic and diastolic BP measurements were used for analyses in this study.

3. Laboratory tests

Blood samples were collected by trained medical personnel. Fasting blood samples obtained from venipuncture were transported to the Central Laboratory for analysis within 24 hours. Plasma glucose, TC, HDL-C, LDL-C, and triglycerides levels were measured using a Hitachi Automatic Analyzer 7600 (Hitachi, Tokyo, Japan). HbA1c level was measured via highperformance liquid chromatography (HPLC-723G7, Tosoh, Tokyo, Japan), which is the method certified by the National Glycohemoglobin Standardization Program.

4. Definitions of obesity severity, CMRFs, and MetS

The degree of obesity was categorized based on BMI percentile for corresponding sex and age: normal weight as BMI <85th percentile; overweight as BMI ≥85th and <95th percentile; class I obesity as BMI ≥95th and <120% of the 95th percentile; and class II obesity as BMI ≥120% of the 95th percentile or ≥30 kg/m2; and class III obesity as BMI ≥140% of the 95th percentile or ≥35 kg/m2 [19,20].
The definitions of abnormal CMRF values are described in Table 1: TC ≥200 mg/dL, HDL-C <40 mg/dL, LDL-C ≥130 mg/dL, triglycerides ≥150 mg/dL, non-HDL-C ≥145 mg/dL [21,22], systolic BP ≥95th percentile or diastolic BP ≥95th percentile for sex, age, and height [23], fasting glucose ≥100 mg/dL, and HbA1c ≥5.7% [24].
MetS was defined using 2 sets of criteria (Table 1). Using the International Diabetes Federation (IDF) criteria, MetS was defined as central obesity, which is a WC ≥90th percentile for age and sex with 2 or more of the following 4 criteria: triglycerides ≥150 mg/dL, HDL-C <40 mg/dL (boys 10–18 years of age and girls 10–15 years of age) or <50 mg/dL (girls ≥16 years of age), systolic BP ≥130 mmHg or diastolic BP ≥85 mmHg, and/or fasting glucose ≥100 mg/dL [25]. Using the modified National Cholesterol Education Program-Adult Treatment Panel (NCEP-ATP) III criteria, MetS was defined as 3 or more of the 5 following criteria: WC ≥90th percentile for age and sex; triglycerides ≥110 mg/dL; HDL-C <40 mg/dL; systolic or diastolic BP ≥90th percentile for age, sex, and height; and/or fasting glucose ≥110 mg/dL [26].

5. Statistical analyses

Statistical analyses were performed using Stata 16.1 (StataCorp LP, College Station, TX, USA). The svy commands and sample weights were used for all analyses. Results are expressed as either the weighted mean (standard error, SE) or the number of participants (weighted %). TC, HDL-C, LDL-C, triglycerides, and non-HDL-C levels were log-transformed for analyses because they exhibited skewed distributions; they are presented as the geometric mean (SE). Student t-test was used to compare continuous variables between groups. Chi-squared tests were used to compare proportions between groups. Multiple logistic regression analysis was performed to calculate the sex- and age-adjusted odds ratio (OR) with 95% confidence intervals (CIs) for possible associations between CMRFs or MetS and degree of obesity. Multiple regression analysis was performed to determine associations between the prevalence of each CMRF and degree of obesity. A 2-tailed P-value <0.05 was considered statistically significant.

Results

1. Demographic and clinical characteristics of study participants

Table 2 shows demographic and clinical characteristics of study participants. In total, 9,984 individuals were analyzed in this study: 5,289 (53.04%) were boys and 4,695 (46.96%) were girls. The mean values for TC, HDL-C, LDL-C, triglycerides, and non-HDL-C levels were higher in girls (P<0.001), while the mean values for systolic and diastolic BP, as well as fasting glucose, were higher in boys (P<0.001).
The proportion of participants with overweight, class I obesity, class II, or class III obesity was higher in boys than in girls (20.91% for boys and 18.26% for girls, P<0.001). The prevalence of MetS did not differ according to sex, irrespective of definition.
According to IDF criteria, prevalence was higher in girls than in boys (P=0.650); conversely, according to the modified NCEPATP III criteria, the prevalence was higher in boys than in girls (P=0.086).
The proportion of participants with class I, class II, or class III obesity showed an increasing trend between 2007 and 2018 (P=0.025, P=0.105, and P=0.508 in total, boys, and girls, respectively) (Supplementary Table 1).

2. Prevalence of CMRFs and MetS based on BMI category

Table 3 and Fig. 1 showed the prevalence of abnormal CMRFs and MetS by BMI category. Supplementary Table 2 shows the mean values for each CMRF based on BMI category and sex. Mean CMRF values were higher with increasing obesity severity, except for mean HDL-C, which was lower with increasing obesity severity.

3. Adjusted ORs for CMRFs and MetS based on BMI category

Table 4 shows adjusted ORs and 95% CIs for CMRFs and MetS based on BMI category. The ORs of high TC, low HDL-C, high LDL-C, high triglycerides, high non-HDL-C, high BP, and prevalence of MetS were greater among children and adolescents with class II/III obesity than among participants with normal weight; these factors showed tendencies to increase with increasing BMI category. Adjusted OR (95% CI) for TC for class II/III obesity in all participants was 4.11 (2.58–6.55), and adjusted OR (95% CI) for BP for class II/III obesity in all participants was 9.44 (6.53–13.66). In analyses of all participants, the OR for MetS according to IDF criteria was 950.3 (321.6–2,808.3), and the OR for MetS according to modified NCEP-ATP III criteria was 126.8 (77.9–206.5). There were few significant differences in these variables based on BMI category among girls; however, all differences were statistically significant among boys. Overweight children and adolescents had lower ORs for most CMRFs compared with obese participants.

Discussion

In this study, KNHANES data from 9,984 Korean children and adolescents (10–18 years of age) were analyzed to examine the associations between obesity severity and CMRFs and MetS. The prevalence of abnormal CMRFs and MetS increased with obesity severity. Notably, class II/III obesity in children and adolescents was associated with high mean values and CMRF prevalence. Additionally, the ORs for CMRFs and prevalence of MetS were higher in children and adolescents with class II/III obesity than in children and adolescents with normal weight.
Recently, several proposals have been suggested regarding the classification of obesity based on BMI. Classification of children and adolescents based on obesity severity provides a more detailed approach to patients at risk of potential complications and health problems [27-29]. According to representative KNHANES data collected from 2007–2018, the prevalence of overweight, class I obesity, and class II/III obesity was 9.52%, 7.73%, and 2.42% in children and adolescents 10–18 years of age, respectively. In the United States, the prevalence of overweight, class I obesity, and class II/III obesity was 14.8%, 11.3%, and 5.1%, respectively, in children and adolescents 2–19 years of age [7]. Although the prevalence of obesity is lower in Korea than in the United States, the prevalence in Korean children and adolescents is increasing compared with results from a Korean study conducted from 2007–2014 [17].
According to Freedman and colleagues, CMRFs (e.g., dyslipidemia, hypertension, and hyperinsulinemia) were more common in children with a BMI in the 99th percentile than in children with a BMI in the 95th percentile. In children and adolescents with a BMI in the 95th percentile (5–17 years), 70%, 39%, and 18% had at least 1, 2, or 3 CMRFs, respectively. Furthermore, in children and adolescents with a BMI in the 99th percentile (defined as severe obesity in this study), 84%, 59%, and 33% had at least 1, 2, or 3 CMRFs, respectively. In the Bogalusa cohort study, the number of CMRFs increased based on BMI percentile in children and adolescents. Among children and adolescents with a BMI in the 95th percentile according to the Centers for Disease Control growth charts, 39% had at least 2 CMRFs. Among individuals with a BMI in the 99th percentile, 59% had at least 2 CMRFs. Based on a previous study of KNHANES data analyzed between 2007 and 2014, the incidence of abnormal CMRFs was higher among individuals with more severe obesity than individuals with less severe obesity [17]. Therefore, it is important to understand the prevalence of CMRFs based on obesity severity classification. Moreover, early recognition and management of obesity based on its severity are important for preventing MetS and complications associated with obesity.
In this study, MetS prevalence differed based on a set of criteria used for obesity evaluation. Unlike adults, children and adolescents have increased insulin resistance because of physiological changes during puberty; therefore, the adult MetS definitions cannot be used for children and adolescents. Currently, there is no established uniform consensus to evaluate risk in children and adolescents [25,30,31]. However, based on these study results, according to both sets of MetS criteria, a relationship was observed between MetS and obesity severity, consistent with our CMRF findings. MetS prevalence increased with increasing obesity severity in both boys and girls.
Early onset of obesity is associated with insulin resistance and MetS in both children and adults and can lead to cardiovascular diseases during adulthood [30,32-34]. Furthermore, obesity is a wellknown cause of MetS, dyslipidemia, type-2 diabetes mellitus, cardiovascular diseases, nonalcoholic fatty liver disease, and mental disorders in both children and adolescents [4,9,27,35]. Consequently, early detection and management of obesity and MetS in children and adolescents are important to prevent cardiovascular disease development in adulthood and associated health consequences [30,31,36,37].
Although this study was conducted using a nationally representative dataset, it had several limitations. First, the sample size was small for some ages, and data for children under 10 years old were not included. Therefore, caution is needed when applying these results to younger children. Second, because of the small sample size, class III obesity (i.e., BMI ≥95th and ≥140% of the 95th percentile) could not be subdivided and analyzed. Third, while only CMRFs and MetS were investigated, other factors associated with obesity development (e.g., birth body weight, family history, physical activity, and detailed dietary habits) were not considered [38]. Therefore, the causal relationships of these associated factors could not be determined.
A study was previously performed based on data obtained from KNHANES for Korean children and adolescents between 2007 and 2014. However, the study findings are outdated, and moreover, they do not reflect the current standards for obesity and hypertension [17]. To our knowledge, this is the first study to investigate CMRF prevalence and associations with obesity in a large, nationally representative sample of Korean children and adolescents. This study is meaningful because CMRF and MetS prevalence was analyzed based on obesity severity in Korean children and adolescents using nationally representative data. This study used the most recent BMI reference data from the Korean population (published in 2018) and the latest definitions of abnormal CMRF values to present current statuses of obesity and its comorbidities. Therefore, these results could be applied to establish screening and management guidelines in clinical practice.
In conclusion, this study demonstrated the prevalence of obesity in Korean children and adolescents. The prevalence of abnormal CMRFs and MetS increased with increasing obesity severity, especially in participants with class II/III obesity. The study results indicate the importance of measuring CMRFs in obese children and adolescents, as well as the need to establish a screening guideline based on obesity severity. Furthermore, guidelines should include obesity severity within clinical criteria for effective medical screening and appropriate management of children and adolescents nationwide.

Ethical statement

Informed consent was obtained from all participants in the KNHANES. The KNHANES protocol was approved by the Institutional Review Board of the Korea Centers for Disease Control and Prevention (2007-02CON-04-P, 2008-04EXP-01-C, 2009-01CON-03-2C, 2010-02CON-21-C, 2011-02CON-06-C, 2012-01EXP-01-2C, 2013-07-CON-03-4C, and 2013-12EXP-03-5C). Since 2015, the KNHANES has not required approval by the Institutional Review Board because surveys performed by the government for public welfare in Korea have been exempt from review by an ethics committee. This study was approved by the Institutional Review Board of Seoul National University Bundang Hospital (X-2105/683-902).

Supplementary Materials

Supplementary Tables 1-2 can be found viahttps://doi.org/10.6065/apem.2142230.115.

Supplementary Table 1.

Trends of obesity among Korean children and adolescents in KNHANES 2017-2018
apem-2142230-115-suppl1.pdf

Supplementary Table 2.

Cardiometabolic risk factors based on BMI category and sex
apem-2142230-115-suppl2.pdf

Notes

Conflicts of interest

No potential conflict of interest relevant to this article was reported.

Funding

This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

The data that support the findings of this study can be provided by the corresponding author upon reasonable request.

Author contribution

Conceptualization: MK, JK; Data curation: MK, JK; Formal analysis: MK, JK; Methodology: MK, JK; Project administration: MK, JK; Visualization: MK, JK; Writing - original draft: MK, JK; Writing - review & editing: MK, JK

Fig. 1.
Prevalences of CMRFs and MetS based on BMI category. CMRFs, cardiometabolic risk factors; BMI, body mass index; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TG, triglycerides; HbA1c, glycated hemoglobin; MetS, metabolic syndrome; IDF, International Diabetes Federation; NCEP-ATP III, National Cholesterol Education Program-Adult Treatment Panel III.
apem-2142230-115f1.jpg
Table 1.
Numbers of participants and definitions of abnormal values of CMRFs and MetS
Risk factor/MetS No. of participants Estimated population Definition of abnormal values
TC 8,549 4,619,487 ≥200 mg/dL
HDL-C 8,547 4,618,460 <40 mg/dL
LDL-C 8,547 4,618,460 ≥130 mg/dL
Triglycerides 8,549 4,619,487 ≥150 mg/dL
Non-HDL-C 8,547 4,618,460 ≥145 mg/dL
BP 9,984 5,405,947 ≥95th percentile for age, sex, and height
Fasting glucose 8,517 4,603,581 ≥100 mg/dL
HbA1c 5,176 3,094,739 ≥5.7%
MetS (IDF) 8,488 4,588,105 Central obesity plus ≥2 of 4 other criteria
WC ≥90th percentile for age and sex
Triglycerides ≥150 mg/dL
HDL-C <40 mg/dL (boys 10–18 years of age and girls 10–15 years of age) or <50 mg/dL (girls ≥16 years of age)
Systolic BP ≥130 mmHg or diastolic BP ≥85 mmHg
Fasting glucose ≥100 mg/dL
MetS (modified NCEP-ATP III) 8,488 4,588,105 ≥3 of 5 criteria
WC ≥90th percentile for age and sex
Triglycerides ≥110 mg/dL
HDL-C <40 mg/dL
BP ≥90th percentile for age, sex, and height
Fasting glucose ≥110 mg/dL

CMRFs, cardiometabolic risk factors; MetS, metabolic syndrome; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; WC, waist circumference; BP, blood pressure; HbA1c, glycated hemoglobin; IDF, International Diabetes Federation; NCEP-ATP III, National Cholesterol Education Program-Adult Treatment Panel III.

Table 2.
Demographic and clinical characteristics of study participants
Variable Total Boys Girls P-value
No. of participants 9,984 5,289 (53.04) 4,695 (46.96)
Estimated population 5,428,671 2,879,396 2,549,275
Age (yr) 14.14±0.03 14.17±0.04 14.11±0.05 0.312
TC (mg/dL) 157.4±0.4 153.4±0.5 162.2±0.5 <0.001
HDL-C (mg/dL) 49.9±0.1 48.7±0.2 51.4±0.2 <0.001
LDL-C (mg/dL) 89.4±0.3 86.9±0.4 92.3±0.4 <0.001
Triglycerides (mg/dL) 75.4±0.5 73.5±0.7 77.5±0.7 <0.001
Non-HDL-C (mg/dL) 105.8±0.3 103.0±0.5 109.1±0.5 <0.001
Systolic BP (mmHg) 106.7±0.1 108.9±0.2 104.2±0.2 <0.001
Diastolic BP (mmHg) 65.8±0.1 66.3±0.2 65.3±0.2 <0.001
Glucose (mg/dL) 90.1±0.1 90.7±0.1 89.4±0.1 <0.001
HbA1c (%) 5.41±0.01 5.42±0.01 5.40±0.01 0.054
BMI category <0.001
 Normal weight 8,020 (80.33) 4,161 (79.09) 3,859 (81.74)
 Overweight 997 (9.52) 562 (9.89) 435 (9.09)
 Class I obesity 756 (7.73) 425 (7.85) 331 (7.61)
 Class II obesity 182 (2.10) 122 (2.76) 60 (1.34)
 Class III obesity 29 (0.32) 19 (0.41) 10 (0.22)
MetS
 IDF criteria 159 (2.01) 81 (1.93) 78 (2.10) 0.650
 Modified NCEP-ATP III criteria 285 (3.55) 168 (3.93) 117 (3.11) 0.086

Values are presented as mean±standard error or number (%).

TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; BP, blood pressure; HbA1c, glycated hemoglobin; BMI, body mass index; MetS, metabolic syndrome; IDF, International Diabetes Federation; NCEP-ATP III, National Cholesterol Education Program-Adult Treatment Panel III.

Table 3.
Prevalences of CMRFs and metabolic syndrome based on BMI category and sex
CMRFs BMI category All
Boys
Girls
Participants Prevalence % (95% CI) P-value Participants Prevalence % (95% CI) P-value Participants Prevalence % (95% CI) P-value
TC ≥ 200 mg/dL NW 6,874 6.27 (5.65–6.95) <0.001 3,583 4.21 (3.53–5.00) <0.001 3,291 8.56 (7.54–9.70) <0.001
OW 843 10.83 (8.69–13.42) 473 12.24 (9.17–16.15) 370 9.07 (6.39–12.73)
Class I OB 649 14.48 (11.46–18.13) 362 10.86 (7.52–15.45) 287 18.50 (13.83–24.30)
Class II/III OB 183 18.66 (12.79–26.41) 121 19.54 (12.65–28.94) 62 16.69 (7.58–33.04)
Total 8,549 7.64 (7.00–8.33) 4,539 5.98 (5.22–6.85) 4,010 9.52 (8.53–10.62)
HDL-C<40 mg/dL NW 6,872 9.54 (8.72–10.43) <0.001 3,582 11.76 (10.61–13.02) <0.001 3,290 7.08 (6.10–8.21) <0.001
OW 843 19.29 (16.37–22.59) 473 25.00 (20.65–29.92) 370 12.18 (8.97–16.33)
Class I OB 649 26.13 (22.31–30.34 362 30.75 (25.47–36.58) 287 20.98 (16.11–26.85)
Class II/III OB 183 41.44 (33.54–49.81) 121 38.60 (29.35–48.75) 62 47.63 (33.68–61.97)
Total 8,547 12.52 (11.68–13.42) 4,538 15.36 (14.18–16.62) 4,009 9.30 (8.26–10.45)
LDL-C≥130 mg/ dL NW 6,872 4.53 (4.00–5.12) <0.001 3,582 3.19 (2.62–3.89) <0.001 3,290 6.01 (5.15–7.00) <0.001
OW 843 10.18 (8.09–12.74) 473 10.89 (8.00–14.67) 370 9.29 (6.69–12.78)
Class I OB 649 12.87 (10.03–16.35) 421 9.02 (6.04–13.27) 287 17.15 (12.60–22.92)
Class II/III OB 183 20.32 (14.20–28.21) 62 21.59 (14.46–30.97) 62 17.55 (8.22–33.61)
Total 8,547 6.09 (5.52–6.72) 4,538 4.97 (4.28–5.76) 4,009 7.37 (6.49–8.36)
Triglycerides≥150 mg/dL NW 6,874 6.10 (5.44–6.84) <0.001 3,583 5.82 (4.95–6.82) <0.001 3,291 6.42 (5.53–7.45) <0.001
OW 843 15.48 (12.81–18.58) 473 19.00 (15.01–23.74) 370 11.10 (8.07–15.09)
Class I OB 649 21.20 (17.86–24.98) 362 19.16 (15.06–24.07) 287 23.48 (18.48–29.34)
Class II/III OB 183 27.80 (20.80–36.09) 121 28.66 (20.19–38.96) 62 25.92 (14.99–40.99)
Total 8,549 8.69 (7.97–9.46) 4,539 8.85 (7.88–9.92) 4,010 8.50 (7.55–9.56)
Non-HDL-C≥145 mg/dL NW 6,872 6.04 (5.43–6.72) <0.001 3,582 4.45 (3.77–5.25) <0.001 3,290 7.80 (6.80–8.91) <0.001
OW 843 13.92 (11.47–16.80) 473 15.93 (12.41–20.23) 370 11.42 (8.43–15.28)
Class I OB 649 20.42 (17.02–24.30) 421 16.70 (12.74–21.58) 287 24.56 (19.33–30.68)
Class II/III OB 183 26.45 (19.70–34.51) 62 26.74 (18.77–36.57) 62 25.81 (14.69–41.29)
Total 8,547 8.39 (7.72–9.12) 4,538 7.22 (6.40–8.14) 4,009 9.73 (8.71–10.86)
BP≥95th percentile for sex, age, and height NW 8,020 4.88 (4.35–5.47) <0.001 4,161 4.90 (4.19–5.73) <0.001 3,859 4.85 (4.11–5.73) <0.001
OW 997 10.55 (8.35–13.25) 562 12.26 (9.14–16.25) 435 8.45 (5.83–12.09)
Class I OB 756 13.80 (11.20–16.87) 425 14.31 (10.87–18.62) 331 13.19 (9.44–18.14)
Class II/III OB 211 29.68 (23.11–37.20) 141 28.19 (20.46–37.47) 70 33.07 (21.79–46.71)
Total 9,984 6.71 (6.13–7.34) 5,289 7.11 (6.29–8.02) 4,695 6.26 (5.47–7.15)
Fasting glucose ≥100 mg/dL NW 6,847 6.81 (6.10–7.59) <0.001 3,568 8.41 (7.36–9.60) 0.030 3,279 5.04 (4.27–5.94) <0.001
OW 839 9.69 (7.69–12.14) 471 11.81 (8.90–15.51) 368 7.05 (4.75–10.33)
Class I OB 649 12.24 (9.49–15.64) 361 12.93 (7.93–15.45) 288 11.47 (7.86–16.45)
Class II/III OB 182 13.66 (8.67–20.87) 121 8.98 (4.85–16.04) 61 24.06 (12.79–40.64)
Total 8,517 7.67 (6.98–8.42) 4,521 9.11 (8.14–10.19) 3,996 6.04 (5.23–6.95)
HbA1c ≥5.7% NW 4,128 15.47 (14.12–16.93) <0.001 2,157 16.45 (14.62–18.45) 0.025 1,971 14.40 (12.65–16.33) <0.001
OW 495 17.26 (13.84–21.30) 276 19.64 (14.86–25.51) 219 14.44 (9.97–20.47)
Class I OB 429 21.66 (17.50–26.49) 234 19.79 (14.65–26.19) 195 23.62 (17.38–31.26)
Class II/III OB 124 32.23 (23.73–42.09) 81 28.80 (19.14–40.87) 3,843 39.56 (24.45–56.96)
Total 5,176 16.62 (15.33–17.98) 2,748 17.45 (15.74–19.31) 2,428 15.68 (14.03–17.48)
MetS (IDF) NW 6,824 0.05 (0.02–0.14) <0.001 3,557 0 (0–0) <0.001 3,267 0.11 (0.04–0.29) <0.001
OW 836 2.63 (1.51–4.56) 471 2.06 (0.75–5.49) 365 3.35 (1.80–6.14)
Class I OB 647 12.48 (9.89–15.63) 361 10.98 (7.98–14.93) 286 14.15 (10.09–19.50)
Class II/III OB 181 30.89 (23.64–39.22) 120 28.16 (19.84–38.29) 61 36.92 (23.88–52.20)
Total 8,488 2.01 (1.68–2.40) 4,509 1.93 (1.50–2.49) 3,979 2.10 (1.63–2.70)
MetS (modified NCEP-ATP III) NW 6,824 0.63 (0.44–0.88) <0.001 3,557 0.53 (0.34–0.85) <0.001 3,267 0.72 (0.44–1.17) <0.001
OW 836 5.68 (3.99–8.01) 471 6.57 (4.18–10.19) 365 4.55 (2.53–8.07)
Class I OB 647 18.96 (15.66–22.76) 361 19.91 (15.66–24.98) 286 17.90 (13.29–23.68)
Class II/III OB 181 42.70 (34.53–51.29) 120 42.31 (32.61–52.65) 61 43.55 (30.05–58.07)
Total 8,488 3.55 (3.01–4.06) 4,509 3.93 (3.32–4.65) 3,979 3.11 (2.51–3.86)

CMRF, cardiometabolic risk factor; BMI, body mass index; CI, confidence interval; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; BP, blood pressure; HbA1c, glycated hemoglobin; MetS, metabolic syndrome; IDF, International Diabetes Federation; NCEP-ATP III, National Cholesterol Education Program-Adult Treatment Panel III; NW, normal weight; OW, overweight; OB, obesity.

Table 4.
Adjusted ORs for CMRFs and MetS based on BMI category
CMRF BMI category All
Boys
Girls
Participants Adjusted OR (95% CI) P-value Participants Adjusted OR (95% CI) P-value Participants Adjusted OR (95% CI) P-value
TC≥200 mg/dL NW 6,874 (ref) 3,583 (ref) 3,291 (ref)
OW 843 1.85 (1.42–2.41) <0.001 473 3.10 (2.14–4.48) <0.001 370 1.06 (0.71–1.59) 0.759
Class I OB 649 2.60 (1.94–3.48) <0.001 362 2.76 (1.78–4.30) <0.001 287 2.42 (1.66–3.53) <0.001
Class II/III OB 183 4.11 (2.58–6.55) <0.001 121 6.77 (3.90–11.77) <0.001 62 2.14 (0.86–5.34) 0.101
HDL-C<40 mg/dL NW 6,872 (ref) 3,582 (ref) 3,290 (ref)
OW 843 2.25 (1.81–2.81) <0.001 473 2.57 (1.96–3.38) <0.001 370 1.84 (1.26–2.67) 0.001
Class I OB 649 3.37 (2.68–4.25) <0.001 362 3.39 (2.55–4.50) <0.001 287 3.63 (2.51–5.24) <0.001
Class II/III OB 183 6.05 (4.16–8.79) <0.001 121 4.30 (2.77–6.66) <0.001 62 13.13 (7.18–24.03) <0.001
LDL-C≥130 mg/dL NW 6,872 (ref) 3,582 (ref) 3,290 (ref)
OW 843 2.43 (1.85–3.20) <0.001 473 3.64 (2.47–5.37) <0.001 370 1.59 (1.08–2.35) 0.019
Class I OB 649 3.15 (2.31–4.29) <0.001 421 2.99 (1.86–4.80) <0.001 287 3.17 (2.12–4.75) <0.001
Class II/III OB 183 6.05 (3.83–9.54) <0.001 62 9.52 (5.56–16.29) <0.001 62 3.17 (1.31–7.69) 0.011
Triglycerides≥150 mg/dL NW 6,874 (ref) 3,583 (ref) 3,291 (ref)
OW 843 2.81 (2.20–3.59) <0.001 473 3.80 (2.76–5.23) <0.001 370 1.88 (1.27–2.79) 0.002
Class I OB 649 4.24 (3.34–5.40) <0.001 362 3.84 (2.76–5.34) <0.001 287 5.15 (3.65–7.26) <0.001
Class II/III OB 183 6.64 (4.39–10.05) <0.001 121 6.48 (3.93–10.70) <0.001 62 6.87 (3.31–14.25) <0.001
Non-HDL-C≥145 mg/dL NW 6,872 (ref) 3,582 (ref) 3,290 (ref)
OW 843 2.55 (2.00–3.26) <0.001 473 4.00 (2.87–5.59) <0.001 370 1.52 (1.06–2.18) <0.001
Class I OB 649 4.07 (3.17–5.22) <0.001 362 4.29 (3.01–6.12) <0.001 287 3.85 (2.73–5.43) <0.001
Class II/III OB 183 6.35 (423–9.52) <0.001 121 8.79 (5.33–14.50) <0.001 62 4.12 (1.99–8.49) <0.001
BP≥95th percentile for sex, age, and height NW 8,020 (ref) 4,161 (ref) 3,859 (ref)
OW 997 2.28 (1.72–3.02) <0.001 562 2.62 (1.83–3.74) <0.001 435 1.85 (1.18–2.88) 0.007
Class I OB 756 3.20 (2.46–4.15) <0.001 425 3.21 (2.25–4.59) <0.001 331 3.16 (2.09–4.76) <0.001
Class II/III OB 211 9.44 (6.53–13.66) <0.001 141 8.90 (5.59–14.19) <0.001 70 11.05 (6.01–20.29) <0.001
Fasting glucose ≥100 mg/dL NW 6,847 (ref) 3,568 (ref) 3,279 (ref)
OW 839 1.44 (1.10–1.89) 0.009 471 1.43 (1.01–2.02) 0.044 368 1.47 (0.94–2.30) 0.094
Class I OB 649 1.96 (1.45–2.67) <0.001 361 1.61 (1.07–2.41) 0.022 288 2.73 (1.74–4.28) <0.001
Class II/III OB 182 2.41 (1.40–4.14) 0.001 121 1.22 (0.62–2.41) 0.564 61 7.88 (3.50–17.72) <0.001
HbA1c ≥5.7% NW 4,128 (ref) 2,157 (ref) 1,971 (ref)
OW 495 1.15 (0.87–1.51) 0.318 276 1.23 (0.86–1.76) 0.258 219 1.03 (0.66–1.61) 0.889
Class I OB 429 1.60 (1.20–2.12) 0.001 234 1.28 (0.87–1.89) 0.208 195 1.97 (1.29–3.01) 0.002
Class II/III OB 124 2.90 (1.87–4.49) <0.001 81 2.44 (1.40–4.27) 0.002 3843 4.14 (2.02–8.49) <0.001
MetS (IDF) NW 6,824 (ref) 3,557 (ref) 3267 (ref)
OW 836 54.2 (16.9–173.9) <0.001 471 - - 365 32.5 (9.76–108.3) <0.001
Class I OB 647 283.3 (98.9–811.5) <0.001 361 - - 286 154.7 (51.9–461.6) <0.001
Class II/III OB 181 950.3 (321.6–2808.3) <0.001 120 - - 61 549.4 (164.0–1840.0) <0.001
MetS (modified NCEP-ATP III) NW 6,824 (ref) 3,557 (ref) 3267 (ref)
OW 836 9.56 (5.78–15.82) <0.001 471 13.1 (6.7–25.4) <0.001 365 6.7 (3.1–14.6) <0.001
Class I OB 647 37.9 (24.8–57.8) <0.001 361 46.3 (26.7–80.2) <0.001 286 32.1 (17.7–58.1) <0.001
Class II/III OB 181 126.8 (77.9–206.5) <0.001 120 139.5 (73.9–263.5) <0.001 61 123.7 (59.6–256.7) <0.001

Normal weight is the reference group.

OR, odds ratio; CMRF, cardiometabolic risk factor; MetS, metabolic syndrome; BMI, body mass index; CI, confidence interval; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; HbA1c, glycated hemoglobin; BP, blood pressure; NW, normal weight; OW, overweight; OB, obesity.

* Adjusted for age and sex.

OR of MetS in boys could not be estimated because no participants exhibited MetS in the normal weight group.

References

1. 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 population-based measurement studies in 128·9 million children, adolescents, and adults. Lancet 2017;390:2627–42.
pmid pmc
2. Kim JH, Moon JS. Secular trends in pediatric overweight and obesity in Korea. J Obes Metab Syndr 2020;29:12–7.
crossref pmid pmc
3. Lim S, Jang HC, Park KS, Cho SI, Lee MG, Joung H, et al. Changes in metabolic syndrome in American and Korean youth, 1997-2008. Pediatrics 2013;131:e214–22.
crossref pmid pdf
4. Park MJ, Boston BA, Oh M, Jee SH. Prevalence and trends of metabolic syndrome among Korean adolescents: from the Korean NHANES survey, 1998-2005. J Pediatr 2009;155:529–34.
crossref pmid
5. Park SI, Suh J, Lee HS, Song K, Choi Y, Oh JS, et al. Tenyear trends of metabolic syndrome prevalence and nutrient intake among Korean children and adolescents: a population-based study. Yonsei Med J 2021;62:344–51.
crossref pmid pmc pdf
6. Oh K, Jang MJ, Lee NY, Moon JS, Lee CG, Yoo MH, et al. Prevalence and trends in obesity among Korean children and adolescents in 1997 and 2005. Korean J Pediatr 2008;51:950–5.
crossref
7. Skinner AC, Skelton JA. Prevalence and trends in obesity and severe obesity among children in the United States, 1999-2012. JAMA Pediatr 2014;168:561–6.
crossref pmid
8. 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.
crossref pmid
9. Valerio G, Maffeis C, Balsamo A, Del Giudice EM, Brufani C, Grugni G, et al. Severe obesity and cardiometabolic risk in children: comparison from two international classification systems. PLoS One 2013;8:e83793.
crossref pmid pmc
10. US Preventive Services Task Force; Barton M. Screening for obesity in children and adolescents: US Preventive Services Task Force recommendation statement. Pediatrics 2010;125:361–7.
crossref pmid pdf
11. Kassi E, Pervanidou P, Kaltsas G, Chrousos G. Metabolic syndrome: definitions and controversies. BMC Med 2011;9:48.
crossref pmid pmc pdf
12. DeFronzo RA, Ferrannini E. Insulin resistance. A multifaceted syndrome responsible for NIDDM, obesity, hypertension, dyslipidemia, and atherosclerotic cardiovascular disease. Diabetes Care 1991;14:173–94.
crossref pmid pdf
13. Magnussen CG, Koskinen J, Chen W, Thomson R, Schmidt MD, Srinivasan SR, et al. Pediatric metabolic syndrome predicts adulthood metabolic syndrome, subclinical atherosclerosis, and type 2 diabetes mellitus but is no better than body mass index alone: the Bogalusa Heart Study and the Cardiovascular Risk in Young Finns Study. Circulation 2010;122:1604–11.
crossref pmid pmc
14. Morrison JA, Friedman LA, Wang P, Glueck CJ. Metabolic syndrome in childhood predicts adult metabolic syndrome and type 2 diabetes mellitus 25 to 30 years later. J Pediatr 2008;152:201–6.
crossref pmid
15. Reisinger C, Nkeh-Chungag BN, Fredriksen PM, Goswami N. The prevalence of pediatric metabolic syndrome-a critical look on the discrepancies between definitions and its clinical importance. Int J Obes (Lond) 2021;45:12–24.
crossref pmid pmc pdf
16. Skelton JA, Cook SR, Auinger P, Klein JD, Barlow SE. Prevalence and trends of severe obesity among US children and adolescents. Acad Pediatr 2009;9:322–9.
crossref pmid pmc
17. Cho WK, Han K, Ahn MB, Park YM, Jung MH, Suh BK, et al. Metabolic risk factors in Korean adolescents with severe obesity: results from the Korea National Health and Nutrition Examination Surveys (K-NHANES) 2007-2014. Diabetes Res Clin Pract 2018;138:169–76.
crossref pmid pmc
18. 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.
crossref pmid pmc
19. 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.
crossref pmid pmc pdf
20. 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.
crossref pmid pmc pdf
21. Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents; National Heart, Lung, and Blood Institute. Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents: summary report. Pediatrics 2011;128 Suppl 5(Suppl 5):S213–56.
crossref pmid pmc pdf
22. Lim JS, Kim EY, Kim JH, Yoo JH, Yi KH, Chae HW, et al. 2017 Clinical practice guidelines for dyslipidemia of Korean children and adolescents. Clin Exp Pediatr 2020;63:454–62.
crossref pmid pmc pdf
23. Kim SH, Park Y, Song YH, An HS, Shin JI, Oh JH, et al. Blood pressure reference values for normal weight Korean children and adolescents: data from the Korea National Health and Nutrition Examination Survey 1998-2016: The Korean Working Group of Pediatric Hypertension. Korean Circ J 2019;49:1167–80.
crossref pmid pmc pdf
24. American Diabetes Association. 2. Classification and diagnosis of diabetes: standards of medical care in diabetes-2021. Diabetes Care 2021;44(Suppl 1):S15–33.

25. 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.
crossref pmid
26. 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.
crossref pmid
27. Czeczelewski M, Czeczelewski J, Czeczelewska E, Galczak-Kondraciuk A. Association of body composition indexes with cardio-metabolic risk factors. Obes Med 2020;17:100171.
crossref
28. Inge TH, King WC, Jenkins TM, Courcoulas AP, Mitsnefes M, Flum DR, et al. The effect of obesity in adolescence on adult health status. Pediatrics 2013;132:1098–104.
crossref pmid pmc pdf
29. Kelly AS, Barlow SE, Rao G, Inge TH, Hayman LL, Steinberger J, et al. Severe obesity in children and adolescents: identification, associated health risks, and treatment approaches: a scientific statement from the American Heart Association. Circulation 2013;128:1689–712.
crossref pmid
30. Chu SY, Jung JH, Park MJ, Kim SH. Risk assessment of metabolic syndrome in adolescents using the triglyceride/ high-density lipoprotein cholesterol ratio and the total cholesterol/high-density lipoprotein cholesterol ratio. Ann Pediatr Endocrinol Metab 2019;24:41–8.
crossref pmid pmc pdf
31. Lee SH, Ahn MB, Choi YJ, Kim SK, Kim SH, Cho WK, et al. Comparison of different criteria for the definition of insulin resistance and its relationship to metabolic risk in children and adolescents. Ann Pediatr Endocrinol Metab 2020;25:227–33.
crossref pmid pmc pdf
32. Geserick M, Vogel M, Gausche R, Lipek T, Spielau U, Keller E, et al. Acceleration of BMI in early childhood and risk of sustained obesity. N Engl J Med 2018;379:1303–12.
crossref pmid
33. Dai XY, Zheng YY, Tang JN, Yang XM, Guo QQ, Zhang JC, et al. Triglyceride to high-density lipoprotein cholesterol ratio as a predictor of long-term mortality in patients with coronary artery disease after undergoing percutaneous coronary intervention: a retrospective cohort study. Lipids Health Dis 2019;18:210.
crossref pmid pmc pdf
34. Castorani V, Polidori N, Giannini C, Blasetti A, Chiarelli F. Insulin resistance and type 2 diabetes in children. Ann Pediatr Endocrinol Metab 2020;25:217–26.
crossref pmid pmc pdf
35. Jeon YJ, Jung IA, Kim SH, Cho WK, Jeong SH, Cho KS, et al. Serum ferritin level is higher in male adolescents with obesity: results from the Korean National Health and Nutrition Examination Survey 2010. Ann Pediatr Endocrinol Metab 2013;18:141–7.
crossref pmid pmc
36. Ward ZJ, Long MW, Resch SC, Giles CM, Cradock AL, Gortmaker SL. Simulation of growth trajectories of childhood obesity into adulthood. N Engl J Med 2017;377:2145–53.
crossref pmid pmc
37. Kim JY, Jeon JY. Role of exercise on insulin sensitivity and beta-cell function: is exercise sufficient for the prevention of youth-onset type 2 diabetes? Ann Pediatr Endocrinol Metab 2020;25:208–16.
crossref pmid pmc pdf
38. Cunningham SA, Kramer MR, Narayan KM. Incidence of childhood obesity in the United States. N Engl J Med 2014;370:403–11.
crossref pmid pmc


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