Associations of overweight and obesity with cardiometabolic risk factor clusters among Korean adolescents

This study investigated the association between overweight, obesity, and cardiometabolic risk factor clusters in Korean adolescents. We included 2182 participants (1161 boys and 1021 girls) aged 12–18 years from the Korea National Health and Nutrition Examination Survey (2016–2021). Cardiometabolic risk factors include hypertension, high low-density lipoprotein cholesterol (LDL-C) level, low high-density lipoprotein cholesterol (HDL-C) level, hypertriglyceridemia, high fasting plasma glucose level, elevated alanine aminotransferase level, and hyperuricemia. The average age was 15.1 ± 0.1 years in both boys and girls. The proportion of subjects with ≥ 1, ≥ 2, and ≥ 3 cardiometabolic risk factors was 76.5%, 49.8%, and 22.7% in obese adolescents, and 60.5%, 24.0%, and 9.1%, in overweight adolescents, respectively. Compared to adolescents with underweight/normal weight, the odds ratios (ORs) and 95% confidence intervals for the clustering of cardiometabolic risk factors were at 2.76 (1.74–4.38) for ≥ 1; 3.75 (2.11–6.66) for ≥ 2; and 4.75 (1.70–13.25) for ≥ 3 factors in obese adolescents and 1.88 (1.26–2.81) for ≥ 1 factor in overweight adolescents. Overweight and obese adolescents exhibited high cardiometabolic risk clustering. Prevention and management of overweight/obesity in Korean adolescents are emerging to mitigate health risk associated with this condition.

The worldwide prevalence of overweight and obese adolescents and children increased 4.5 fold between 1975 and 2016 1 .Among American adolescents aged 12-19 years, the prevalence of obesity has risen steadily, while this trend is more pronounced in boys than in girls 2,3 .A climbing prevalence of adolescent obesity has also been reported in South Korea.Rates of overweight/obesity increased from 18.8% (boys: 17.3%; girls: 20.6%) in 2011 to 23.7% (boys: 24.0%; girls: 23.5%) in 2019 4 .Moreover, obese adolescents have an increased risk of obesity-related comorbidities such as cardiometabolic syndrome 5 , obstructive sleep apnea 6 , and non-alcoholic fatty liver disease (NAFLD) 7 .Additionally, medical service utilization and expenditure in children with obesity are more significant than those in children with normal weight, owing to the evaluation and management of comorbidities 8 .
Furthermore, obesity during childhood and adolescence is likely to persist into adulthood.Children who are overweight between 2 and 5 years of age are four times more likely to be obese in adulthood than children of normal weight were 9 .A previous study demonstrated that an increase in body mass index (BMI) among adolescents augments the risk of fatal and nonfatal cardiovascular disease (CVD) in both men and women, as well as mortality in adulthood 10 .In particular, severe obesity is associated with an immediate risk of CVD complications, including elevated blood pressure, blood glucose and lipid levels 11 .Adolescents with NAFLD confer a higher risk of developing fibrosis as adults 12 .Additionally, comorbidities related to overweight/obesity in adolescents lead to a poor quality of life and a large burden on the healthcare system 13 .
Overweight/obese adolescents present a greater tendency to persist into adulthood, compared overweight/ obese children 14 .A previous study showed that adolescents with a high BMI had a 7-10 times risk of overweight/ obesity in adulthood than those with a low BMI 14 .Additionally, the risk of CVD in adulthood increased with age in both sexes 10 .The Bogalusa Heart Study showed that adolescents with obesity have an increased risk of developing clustered cardiometabolic risk factors 15 .Furthermore, prevalence of metabolic syndrome, which is a cluster indicator of cardiometabolic risk, in overweight and obese adolescents was 30.3% in the United States 16 and 40.4% in Germany 17 .A recent study in Korea showed that the prevalence of metabolically unhealthy adolescents among

Definitions of obesity and cardiometabolic risk factors
The height of the participants was measured to the nearest 0.1 cm using a stadiometer (SECA 225; Hamburg, Germany).Body weight was measured to the nearest 0.1 kg by using a balance scale (GL-6000-20; Cas, Yangju, Korea).Waist circumference (WC) was measured at the midpoint between the bottom of the subcostal region and the top of the iliac crest using a fiberglass tape.BMI was calculated by dividing the weight in kilograms by the square of height in meters.Participants were classified as underweight/normal weight (BMI < 85th percentile) or overweight (85th percentile ≤ BMI < 95th percentile) or obese (BMI ≥ 95th percentile) according to age-and sex-specific BMI percentiles provided by the 2017 Korean National Growth Charts for children and adolescents 18 .Abdominal obesity was defined as waist circumference divided by height ≥ 0.48 19 .
The cardiometabolic risk factors include hypertension, high low-density lipoprotein cholesterol (LDL-C), low high-density lipoprotein cholesterol (HDL-C), hypertriglyceridemia, high fasting plasma glucose (FPG), elevated alanine aminotransferase (ALT), and hyperuricemia.Systolic and diastolic blood pressure (BP) was measured three times in a sitting position using a standardized method with an internationally certified BP monitor with various cuff sizes, based on arm circumference; the mean values of the second and third BP measurements were determined.Blood samples were collected in the morning after an overnight fast.Hypertension was defined as systolic BP > 95th percentile or diastolic BP > 95th percentile for age, sex, and height, based on the 2017 Korean National Growth Chart for Children and Adolescents 18 .Blood samples were collected in the morning after overnight fasting.To define abnormal lipid profiles, we used the cut-off values for LDL-C (≥ 130 mg/dL), HDL-C (< 40 mg/dL), and triglycerides (≥ 130 mg/dL) 20 .High FPG was defined at ≥ 100 mg/dL 21 and elevated ALT at > 40 IU/L.Hyperuricemia was defined as ≥ 6.0 mg/dL in subjects aged 12 years and ≥ 7.5 mg/dL in subjects aged 13-18 years based on reference values from the Mayo Clinic Laboratories 22 .

Lifestyle factors
Household income levels were divided into first and second quartile groups, and others.Smoking status and alcohol consumption were dichotomized according to a history of smoking or alcohol consumption.Physical activity was categorized into two groups according to whether strength exercise was performed ≥ 3 times/week.A parental family history was defined as adolescents whose parents had at least one of the following conditions: hypertension, diabetes mellitus, or dyslipidemia.Breakfast was divided into whether or not participants had breakfast > 2 times/week and eating out was classified into whether or not participants ate out ≥ 2 times/day.Stress was divided into two groups based on stress recognition.

Statistical analyses
We combined data from the 2016 to 2020 KNHANES using its raw data analysis guidelines.Based on a complex sample design, we conducted all analyses by assigning dispersed stratification estimates, stratification variables, and weighted sample values.Continuous variables were analyzed using a general linear model and presented as means and standard errors.Categorical variables were presented as ratios and standard errors and analyzed using the chi-square test.Furthermore, to determine the association between overweight and obesity, as the independent variable and the clustering of cardiometabolic risk factors, as the dependent variable, we conducted multivariable logistic regression analysis and calculated the odds ratios (ORs) and 95% confidence intervals (CIs) adjusted for sex, age, abdominal obesity, income, alcohol consumption, smoking status, physical activity, family history, breakfast consumption, eating habits, and stress levels.Statistical significance was set at p < 0.05.All analyses were performed using the SPSS software (version 24.0;IBM Corp., Armonk, NY, USA).

Consent to participate
The requirement for informed consent was waived because the data were anonymized and de-identified.

Basic characteristics of the study participants
Table 1 presents the basic characteristics of the adolescents included in this study.The mean age was 15.1 ± 0.1 years.The mean body weight and mean WC were 73.3 ± 0.5 kg and 83.4 ± 0.3 cm, respectively, in boys and 62.3 ± 0.4 kg and 75.6 ± 0.3 cm, respectively, in girls.The mean BMI value was 25.0 ± 0.1 kg/m 2 in boys and 24.1 ± 0.1 kg/m 2 in girls.The mean values of most cardiometabolic risk factors were worse in overweight and obese adolescents than in underweight and normal-weight adolescents.Frequency of positive parental family history was significantly higher in those with increased BMI.Economic status, smoking status, alcohol consumption, eating habits, and stress levels did not differ significantly between individuals with different obesity status.

Prevalence of individual and clustered cardiometabolic risk factors according to obesity status
Tables 2 and 3 show the prevalence of individual and clustered cardiometabolic risk factors according to the obesity status of adolescents.The proportion of obese adolescents with hypertriglyceridemia was the highest (31.0%), followed by those with low HDL-C (29.9%) and hyperuricemia (27.2%).Overweight adolescents with hyperuricemia represented 23.0%, followed by those with hypertriglyceridemia (19.8%) and high LDL (14.4%).
In boys, the proportion of obese participants with hyperuricemia was the highest (42.5%), followed by those with low HDL-C (36.7%), hypertriglyceridemia (29.2%), and hypertension (23.5%).Among girls, the proportion of obese subjects with hypertriglyceridemia was the highest (33.5%), followed by those with low HDL-C (20.6%), high FPG (19.6%), and hypertension (15.9%).Excluding high FPG levels in boys and high LDL-C levels in girls, the proportion of all cardiovascular risk factors was higher in both overweight and obese boys and girls than in their underweight/normal-weight counterparts.
The prevalence of overweight and obesity with at least one cardiometabolic risk factor was 60.5% and 76.5%, whereas that of their underweight/normal-weight counterparts was 36.4%.The proportion of boys who were overweight and obese and had at least one cardiometabolic risk factor was 70.2% and 85.0%, whereas that of their underweight/normal-weight counterparts was 43.2%.The proportion of girls who were overweight and obese and had at least one cardiometabolic risk factor was 48.8% and 64.7%, whereas that of their underweight/ normal-weight counterparts was 29.0%.The proportion of subjects with ≥ 2 and ≥ 3 clustering cardiometabolic risk factors were 49.8% and 22.7%, in obese adolescents, and 24.0% and 9.1% in overweight adolescents, while this proportion was 9.0% and 2.0% in underweight/normal weight adolescents, respectively (all p < 0.001).

Discussion
The present study confirmed that overweight and obese adolescents had an increased risk of clustering cardiometabolic risk factors compared with underweight/normal-weight adolescents of both sexes.Surprisingly, 77% of obese adolescents and 61% of overweight adolescents presented more than one cardiometabolic risk factor.Among the cardiometabolic risk factors, the ORs for elevated ALT levels were higher in obese boys and girls than in underweight/normal-weight adolescents.The prevalence of the clustering of cardiometabolic risk factors was significantly higher in overweight and obese boys than girls.
A study in the US showed that overweight/obese adolescents aged 12-19 years have an increased risk of high LDL-C, low HDL-C, high triglyceride levels, low HDL-C levels, high BP, and high glycated hemoglobin and FPG levels 5 .In that study, the proportion of cardiometabolic risk factors among overweight/obese adolescents aged 12-19 years was 4.7% for hypertension, 19.7% for high FPG levels, and 17.5% for high triglycerides.Another study of obese class III adolescents aged 12-17 years in the United States showed that prevalence of 7.7% for hypertension, 6.2% for type 2 diabetes, 9.0% for elevated ALT, 35.2% for dyslipidemia, and 13.6% for obstructive sleep apnea 23 .One study included 2327 obese European class III children and adolescents aged 8-19 years demonstrated that the proportion of hypertension, high FPG, and low HDL-C was 31.2%, 1.2%, and 65.0%, respectively 24 .In our study, the prevalence of cardiometabolic risk factors among overweight/obese Korean adolescents was 17.6% for hypertension, 15.8% for high FPG levels, 16.2% for elevated ALT levels, 23.3% for low HDL-C levels, and 26.9% for hypertriglyceridemia.These findings suggest that Asian adolescents tend to be more vulnerable to cardiometabolic risk factors at each BMI than Western adolescents, as seen in similar findings in adults [25][26][27] .
Odds ratios for obese adolescents with elevated ALT levels were prominent in both sexes.The risk of elevated ALT levels was four times higher in obese boys and approximately 13 times higher in obese girls than in underweight/normal weight adolescents.Approximately 28% of the obese boys and 14% of the obese girls had elevated ALT levels.Furthermore, this study showed that overweight and obese boys and girls conferred an increased risk of hyperuricemia; approximately 40% of obese boys had hyperuricemia.The latter is associated with obesity, high BP, insulin resistance, dyslipidemia, and chronic kidney disease 28,29 .To prevent NAFLD progression and hyperuricemia, early diagnosis and treatment of overweight and obesity in Korean adolescents are required.
Some studies, including those on adolescents in the United States, have shown sex differences in the risk ratio regarding the association between obesity and cardiometabolic risk factors 5 .Our study demonstrated that the risk ratios of cardiometabolic risk factors were higher in obese than in normal-weight boys, although the differences were not significant in girls.In addition, the study suggested that boys tend to develop cardiometabolic risk factors earlier than girls 5 .However, our study showed that both overweight/obese boys and girls had an increased risk ratio for cardiometabolic risk factors compared with adolescents with normal weight.This result suggests that Korean overweight/obese girls are not relatively less susceptible to obesity than overweight/obese boys.The prevalence of low HDL-C levels, elevated ALT levels, and hyperuricemia was much higher in boys than in girls.
Among overweight/obese children and adolescents in the United States, the proportion of those with ≥ 1, ≥ 2, ≥ 3, and ≥ 4 clustering cardiometabolic risk factors was 70%, 39%, 18%, and 5%, whereas this proportion was 51%, 19%, 5%, and 1%, among those with a BMI in the 85 th -94 th percentile, respectively 15 .Nevertheless, our study showed that the prevalence of overweight/obese adolescents with ≥ 1, ≥ 2, and ≥ 3 clustering cardiometabolic risk factors was 70.1%, 40.4%, 17.8%, whereas this prevalence was 36.4%, 9.0%, and 2.0%, in the underweight/normal weight counterparts, respectively.These results indicate that the prevalence of clustering of cardiometabolic risk factors is much higher in Korean overweight/obese adolescents than in Korean underweight/normal-weight adolescents, despite the similar proportions of obese adolescents in the US.Moreover, this finding suggests that overweight/obese Korean adolescents tend to manifest and develop cardiometabolic risk factors earlier in life and seem to be at risk for progression.In addition, the prevalence of clusters 2, 3, and 4 in boys was approximately twice as high as that in girls.As overweight/obese Korean boys have a higher cardiometabolic risk, public-based management and treatment should be enhanced.
Several possible mechanisms are proposed to explain the clustering of cardiometabolic risk factors in obese adolescents.First, obesity increases visceral adiposity and lipolysis, leading to increased insulin resistance and glucose levels in the liver and muscle owing to high levels of free fatty acids and low levels of adiponectin 30 .Hepatic steatosis induces atherogenic dyslipidemia (high levels of triglycerides, small dense LDL-C, and low levels of HDL-C), is proinflammatory, and is associated with endothelial dysfunction and hypertension.In addition, increased lipolysis induces inflammation by increased tumor necrosis factor α (TNF α) and interleukin-6 (IL-6) levels and prothrombotic changes through plasminogen activator inhibitor-1 (PAI-1) secretion.Beta-cell failure and hypoinsulinemia in the pancreas are associated with the risk of type 2 diabetes and atherosclerosis 31 .These mechanisms explain the effect of obesity on clustered cardiometabolic risk factors in adolescents.
One study reported that people who remained obese from adolescence to adulthood had a two-to five-fold higher risk of type 2 diabetes, hypertension, and dyslipidemia than those who maintained a normal weight 32 .However, individuals who were obese or overweight in adolescence but had a normal weight in adulthood had similar risks of these diseases as those who maintained a normal weight from adolescence to adulthood 32 .These facts highlight the importance of weight management in overweight/obese adolescents and prevention of overweight/obesity in adolescence to reduce the risk of cardiovascular and metabolic diseases in adulthood.
The present study had some limitations.First, laboratory tests such as FPG, lipid profiles, and ALT levels were performed only once to define cardiometabolic risk factors, and we could not consider the daily fluctuations of these values.Second, because the health status and lifestyle of the participants were based on self-reported

Figure 1 .
Figure 1.Prevalence of the number of clustering cardiometabolic risk factors according to overweight and obesity in adolescents.

Table 2 .
Association of individual and clustered cardiometabolic risk factors with overweight/obesity in Korean adolescents.ALT alanine aminotransferase, FPG fasting plasma glucose, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol.p-values were presented as numbers and percentages (standard errors).ORs and 95% confidence intervals (CIs) were obtained using multivariate logistic regression analysis after adjusting for sex, age, abdominal obesity, income, alcohol consumption, smoking status, physical activity, family history, breakfast consumption, eating habits, and stress level.Significant values are in bold.

Table 3 .
Prevalence of individual and clustered cardiometabolic risk factors according to overweight/obesity status in Korean boys and girls.ALT alanine aminotransferase, FPG fasting plasma glucose, HDL-C highdensity lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol.Values were presented as numbers and percentages (standard errors).

Table 4 .
Adjusted ORs and 95% CIs for individual and clustered cardiometabolic risk factors according to overweight/obesity status in Korean boys and girls.ALT alanine aminotransferase, CI confidence interval, FPG fasting plasma glucose, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol, OR odds ratio.Values were obtained using multivariate logistic regression analysis after adjusting for age, abdominal obesity, income, alcohol consumption, smoking status, physical activity, family history, breakfast consumption, eating habits, and stress levels.Significant values are in bold.