Association between metabolically healthy obesity and carotid intima-media thickness in Korean adolescents with overweight and obesity

Sohyun Shin; Hwa Young Kim; Joowon Lee; Young Jin Ryu; Ji Young Kim; Jaehyun Kim

doi:10.6065/apem.2346192.096

Ann Pediatr Endocrinol Metab > Volume 29(4); 2024 > Article

Shin, Kim, Lee, Ryu, Kim, and Kim: Association between metabolically healthy obesity and carotid intima-media thickness in Korean adolescents with overweight and obesity

Original Article

Annals of Pediatric Endocrinology & Metabolism 2024;29(4): 227-233.

Published online: August 31, 2024

DOI: https://doi.org/10.6065/apem.2346192.096

Association between metabolically healthy obesity and carotid intima-media thickness in Korean adolescents with overweight and obesity

Sohyun Shin¹

, Hwa Young Kim^1,²

, Joowon Lee^1,²

, Young Jin Ryu^3,⁴

, Ji Young Kim^3,⁴

, Jaehyun Kim^1,²

¹Department of Pediatrics, Seoul National University Bundang Hospital, Seongnam, Korea

²Department of Pediatrics, Seoul National University College of Medicine, Seoul, Korea

³Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Korea

⁴Department of Radiology, Seoul National University College of Medicine, Seoul, Korea

Address for correspondence: Jaehyun Kim Department of Pediatrics, Seoul National University Bundang Hospital, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam, Gyeonggi-do, 13620, Korea Email: pedendo@snu.ac.kr

Received August 25, 2023 Revised December 17, 2023 Accepted January 15, 2024

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.

Abstract

Purpose

Data regarding the association between metabolically healthy obesity (MHO) and preclinical atherosclerosis in childhood are lacking. Carotid intima-media thickness (cIMT) is a noninvasive method used to assess cardiovascular risk. This study examined the relationships among cIMT, metabolic phenotypes, and cardiometabolic risk factors (CMRFs) in overweight and obese adolescents.

Methods

Anthropometric, biochemical, and cIMT data were collected. The study participants were categorized as MHO or metabolically unhealthy obesity (MUO) based on insulin resistance. CMRFs were assessed using blood pressure (BP); levels of triglycerides, high-density lipoprotein cholesterol (HDL-C), and fasting plasma glucose; or a diagnosis of diabetes mellitus. Differences in cIMT values were evaluated according to the metabolic phenotype and factors associated with cIMT.

Results

Among the 111 participants (80 boys, 72.1%), 23 (20.7%) were classified as MHO and 88 (79.3%) as MUO. The MHO group exhibited lower glycated hemoglobin and triglyceride levels and higher HDL-C levels compared to those exhibited by the MUO group (all P<0.01). The cIMT values did not differ significantly between the MHO and MUO groups. The high cIMT tertile group revealed higher systolic BP compared to that exhibited by the low cIMT tertile group (123.7±2.1 mmHg vs. 116.9±1.6 mmHg, P=0.028). Mean cIMT was positively correlated with age (β=0.009) and body mass index (BMI) (β=0.033) after adjusting for covariates (both P<0.05).

Conclusions

In overweight and obese Korean adolescents, cIMT was associated with age and BMI but not with metabolic phenotype or CMRFs. Further research is warranted to determine the relationship between cIMT during adolescence and cardiovascular outcomes during adulthood.

Keywords: Pediatric obesity, Overweight, Obesity, Metabolically benign, Cardiometabolic risk factors, Carotid intima-media thickness, Adolescent, Korea

Highlights

· This study examined the relationship between carotid intima-media thickness (cIMT) and metabolic health in overweight and obese adolescents.

· cIMT was associated with age and BMI but did not differ significantly between metabolically healthy and unhealthy obesity groups.

Introduction

In recent decades, the prevalence of pediatric obesity has increased globally, as well as in Korea [1,2]. Pediatric obesity is an important health issue associated with several cardiometabolic risk factors (CMRFs), including abdominal obesity, impaired fasting glucose or type 2 diabetes mellitus (T2DM), high blood pressure (BP), and dyslipidemia [3-5]. Furthermore, children exhibiting obesity are more likely to be obese in adulthood, with the relative risk of adult obesity exceeding 5 times that in nonobese children [6]. Since obesity and its associated CMRFs persist into adulthood, early intervention for management of childhood obesity and screening for comorbidities are crucial.

Obesity is increasingly recognized as a heterogeneous condition, with a subset of obese individuals not exhibiting CMRFs [7]. Metabolically healthy obesity (MHO) individuals have preserved insulin sensitivity with normal BP and lipid profiles despite being obese [8,9]. According to the 2011–2019 Korea National Health and Nutrition Examination Survey, the overall prevalence of MHO, defined as the absence of any CMRFs, was 39.2% among overweight and obese Korean adolescents [10]. Previous studies in adults have revealed that MHO individuals demonstrate an increased risk of cardiovascular events compared to the risks in metabolically healthy normal-weight individuals [11-13]. However, information regarding the association between childhood metabolic phenotype and potential risk of cardiovascular disease (CVD) is lacking.

Assessing cardiovascular risk in pediatric populations is difficult because CVDs, such as myocardial infarction and ischemic stroke, rarely occur during this period. Carotid intima-media thickness (cIMT) is one of the various markers of cardiovascular risk even though it is a noninvasive indicator [14]. A meta-analysis of randomized controlled trials in adults revealed that interventions reducing cIMT progression also lower the risk of cardiovascular events [15]. A systematic review that mainly included pediatric population-based observational studies reported a significant association between adiposity and cIMT in adolescents [16]. Additionally, a single-center study of healthy Korean adolescents identified a positive relationship between systolic BP (SBP) and cIMT [17].

However, the correlation between elevated cIMT and metabolic alterations in children and adolescents remains controversial. While mean cIMT values and prevalence of high cIMT varied by weight and metabolic status categories in 5 pediatric population-based studies, another study observed no significant difference in mean cIMT values between MHO and metabolically unhealthy obesity (MUO) individuals [18,19]. The present study investigated whether cIMT was related to the MHO phenotype or metabolic alterations in overweight and obese Korean adolescents.

Materials and methods

1. Participants and anthropometric and biochemical assessments

Available cIMT data were retrospectively reviewed in 111 adolescents aged 10–18 years who were overweight (n=1) or obese (n=110) and visited the Seoul National University Bundang Hospital (SNUBH) between January 2017 and April 2022.

Height was measured to the nearest 0.1 cm using a stadiometer. Weight was measured to the nearest 0.1 kg using an electronic scale. Body mass index (BMI) was calculated by dividing the weight (kg) by height squared (m²). Height, weight, and BMI were converted into standard deviation scores (SDS) based on the 2017 Korean National Growth Charts [20]. Overweight and obesity were defined as BMI in the 85-<95th and ≥95th percentiles, respectively. Waist circumference was measured to the nearest 0.1 cm at the midpoint between the lowest point of the rib and uppermost edge of the iliac crest during exhalation. The waist-to-height ratio was calculated by dividing the waist circumference in centimeters by height in centimeters [21]. BP was measured 3 times after the participants rested for at least 5 minutes in a seated position.

Blood samples were collected from participants after a 12-hour fast. Plasma glucose, serum insulin, serum triglyceride (TG), total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, aspartate aminotransferase, alanine aminotransferase, and glycated hemoglobin (HbA1c) levels were measured using an automated analyzer. The homeostatic model assessment of insulin resistance (HOMA-IR) values were calculated using the following formula: fasting insulin (mIU/L)×fasting glucose (mg/dL)/405 [22].

2. Definition of metabolic phenotype and CMRFs

Overweight and obese adolescents were classified into 2 groups, MHO and MUO, based on the presence of T2DM and/or insulin resistance using Korean reference data [23]. MUO was defined as a HOMA-IR value in the 95th percentile or above or diagnosis of T2DM, whereas MHO was defined as a HOMA-IR value below the 95th percentile. Other CMRFs were defined as follows: SBP or diastolic BP at or above the 90th percentile based on Korean reference data [24] or treatment with antihypertensive drugs; fasting plasma glucose ≥100 mg/dL or diagnosis of T2DM; TG ≥150 mg/dL; and HDL-C <40 mg/dL [25]. Hypertension and prehypertension were defined as BP at or above the 95th percentile and between the 90th and 95th percentiles, respectively, based on Korean reference data [24]. Prediabetes was defined as a fasting plasma glucose level of 100–125 mg/dL or HbA1c of 5.7%–6.4% [26].

3. Measurement of cIMT

The right and left common carotid arteries were scanned by a radiologist using a color Doppler ultrasonography system (EPIQ 7; Philips Medical Systems, Andover, MA, USA) equipped with a linear high-frequency transducer (5–12 MHz). Participants were scanned in the supine position with the head slightly tilted contralateral to the side being examined. The cIMT measurements were recorded from the far wall, 1 cm proximal to the carotid bulb, and over a length of 1 cm. The cIMT values were calculated using a semiautomated method (Automated; QLAB, Phillips, Crawley, UK), which averaged 3 values from each artery and provided results in micrometers.

4. Statistical analysis

Statistical analyses were conducted using the Stata 17.0 (StataCorp LP, College Station, T X, USA). Continuous variables were presented as mean±standard deviation, while skewed variables were log-transformed and presented as geometric mean with standard error. Categorical variables are expressed as the number of cases and percentage. Differences in anthropometric, cardiometabolic, and cIMT parameters between the MHO and MUO groups were assessed using Student t- and chi-square tests for continuous and categorical variables, respectively. To compare the metabolic parameters according to the cIMT tertile or the number of CMRFs, an analysis of variance was conducted. Linear and logistic regression analyses were performed to identify factors associated with cIMT values. P<0.05 was considered statistically significant.

5. Ethical statement

This study was approved by the Institutional Review Board (IRB) of SNUBH (IRB No. B-2205-757-104).

Results

1. Characteristics of the study participants

Among the 111 overweight and obese adolescents (80 males and 31 females), the mean and maximal cIMT values were 470.1±46.2 μm and 515.4±66.0 μm, respectively. Twenty-three (20.7%) were classified as MHO and 88 (79.3%) as MUO. The clinical characteristics of the participants according to their metabolic phenotypes are presented in Table 1. Compared to the MUO group, participants in the MHO group were younger (12.5±1.4 years vs. 14.4±2.2 years) and exhibited lower HbA1c and TG levels, and higher HDL-C levels (all P<0.01). The cIMT values did not differ between the MHO and MUO groups (mean, 459.7±9.7 μm vs. 470.1±5.8 μm; maximum 506.8±13.6 μm vs. 512.7±6.7 μm). Among the 88 adolescents with MUO, 23 (20.7%) were prediabetic, 48 (43.2%) had T2DM, 53 (47.8%) had elevated BP, 38 (34.2%) had elevated TG levels, while 48 (43.2%) had decreased HDL-C levels. There was no significant difference in the mean cIMT values according to the presence of prediabetes or T2DM: Normal, 462.0±35.8 μm, prediabetes, 467.0±49.2 μm, T2DM, 478.3±51.7 μm, P=0.245). Atheromatic plaques in the carotid arteries were not observed.

2. Comparison of metabolic parameters according to the cIMT category

Table 2 shows the anthropometric and metabolic parameters according to the cIMT category. The participants were categorized into 3 groups based on tertiles of mean cIMT values: 40 (36.0%) low tertile (≤ 445.0 μm), 34 (30.6%) mid tertile (456.7–480.0 μm), and 37 (33.3%) high tertile (≥481.0 μm). The high cIMT tertile group exhibited higher SBP than that demonstrated by the low cIMT tertile group (123.7±2.1 mmHg vs. 116.9±1.6 mmHg, P=0.028). The other metabolic parameters did not differ among the 3 cIMT groups. Among the 23 MHO individuals, 10 (43.5%), 6 (26.1%), and 7 (30.4%) were classified in the low, mid, and high cIMT tertiles, respectively. The proportion of patients with MHO did not significantly differ among the 3 cIMT categories.

3. Factors associated with cIMT

Mean cIMT was positively associated with age and BMI SDS in univariable analysis (all P<0.05), both of which remained significant in the multivariate analysis (age: β=0.009, P=0.022; BMI SDS: β=0.033, P=0.040). cIMT was not associated with CMRFs or MHO in either univariate or multivariate analysis (Table 3). In addition, cIMT did not differ according to number of accompanying CMRFs (Fig. 1).

Discussion

In this study, cIMT values did not differ according to metabolic phenotype or presence of CMRFs. However, participants in the high cIMT category exhibited a higher SBP compared to those participants in the low cIMT category. Among overweight and obese Korean adolescents, age and BMI were independent predictors of increased cIMT.

Atherosclerosis is hypothesized to begin during childhood and results in CVD in adulthood [27]. cIMT is considered a surrogate marker of atherosclerosis, allowing assessment of vascular changes at an early stage [28]. Increased cIMT has been reported in obese children compared to children of normal weight [29,30]. cIMT measurements are recommended for CVD prevention in children with obesity [31]. Several studies have reported normative values in children and adolescents [32-35]. A study involving 1,155 children aged 6–18 years reported 50th percentiles of cIMT between 360 μm (at 6 years) and 400 μm (at 18 years old) [33], while another large study of 263 healthy adolescents aged 15–20 years revealed the 75th percentile of cIMT at 449 μm (at 15 years of age) [34]. In our study, the mean cIMT in adolescents aged 10–18 years who were overweight and obese (470.1 μm) was higher than the previously reported normative values in the same age group [31].

Growing evidence suggests a positive relationship between adiposity and cIMT in pediatric populations. A systematic review of 5 population-based observational studies in children aged 5–15 years reported that adiposity may be associated with cIMT in adolescents but not in preadolescents, suggesting that obesity-related thickening of the carotid artery may only become detectable in late childhood, and that age-related arterial changes may be accelerated by adiposity [16]. In the present study, cIMT was positively associated with age and BMI SDS, in line with previous studies in pediatric populations. Furthermore, a study investigating cIMT reference values in children aged 6–18 years reported a positive correlation between age and cIMT [33]. Additionally, a study involving 291 healthy children and adolescents aged 6–18 years demonstrated a positive correlation between BMI and cIMT [36]. Moreover, a study of 204 pediatric participants with obesity revealed that cIMT was significantly higher in obese patients, even in those without metabolic alterations, compared to those in normal-weight children [19]. These findings suggest that the duration and degree of adiposity, rather than metabolic phenotype, may have an important effect on vascular changes.

Nevertheless, overweight and obese adolescents in the high cIMT tertile group exhibited significantly higher SBP compared to those demonstrated by participants in the low cIMT tertile group. Moreover, hypertension and obesity were associated with a higher risk of cIMT above the 75th percentile in an 11-year follow-up study of 4,709 German subjects aged 14–28 years [37]. In a systematic review of 8 population-based studies in healthy children, BP and cIMT revealed an independent positive association even after adjusting for other CMRFs in 6 studies [38]. Although a positive linear association between cIMT and SBP was observed in our study participants, it was not significant after adjusting for other CMRFs. This may be partly explained by the strong correlation between multiple CMRFs, which could result in overadjustment [38]. Although the underlying mechanism associating BP with cIMT remains unclear, BP, and especially SBP, may contribute to pressure overload in the vascular beds, leading to vascular endothelial changes. Overall, cIMT measurements can provide insights into early signs of atherosclerosis in the pediatric population in a noninvasive manner and help assess the risk of CVD [39].

This study had several limitations. First, as it was conducted at a single tertiary center and included only overweight and obese individuals who underwent cIMT measurements, selection bias may have occurred. Second, owing to the retrospective and cross-sectional study design involving a limited number of subjects with a relatively short obesity duration, the temporal relationship between obesity duration and cIMT remains uncertain. Third, due to the lack of normal-weight control subjects and normative values for Korean adolescents, we could only evaluate the relative associations between cIMT and metabolic parameters. Nevertheless, this is the first study to explore the associations between cIMT and metabolic phenotypes, as well as the accompanying CMRFs, in overweight and obese Korean adolescents.

In conclusion, cIMT is related to age and adiposity rather than to the metabolic phenotype or the accompanying CMRFs in overweight and obese Korean adolescents. Further studies are warranted to determine the long-term effects of increased cIMT on cardiovascular events later in life, using cIMT reference values derived from the healthy Korean pediatric population.

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: SS, JL, JK; Data curation: SS, JL; Formal analysis: SS; Methodology: SS, HYK, JL; Project administration: JK; Visualization: SS; Writing - original draft: SS, YJR; Writing - review & editing: HYK, JYK, JK

Fig. 1.

Carotid intima-media thickness according to the number of cardiometabolic risk factors. cIMT, carotid intima-media thickness.

Table 1.

Clinical characteristics of participants according to metabolic phenotype

Characteristic	MHO (n=23)	MUO (n=88)	P-value
Age (yr)	12.5±1.4	14.4±2.2	<0.001
Male sex	19 (82.6)	61 (69.3)	0.206
Weight SDS	2.2±0.7	2.5±0.7	0.063
Height SDS	0.7±0.8	1.0±1.3	0.319
BMI (kg/m²)	29.7±3.7	31.0±4.2	0.107
BMI SDS	2.2±0.5	2.4±0.6	0.246
Waist circumference SDS	2.5±0.5	2.8±0.6	0.128
WHtR SDS	2.6±0.5	2.7±0.7	0.741
Systolic blood pressure (mmHg)^*	120.5±2.5	120.9±1.3	0.892
Diastolic blood pressure (mmHg)^*	66.4±1.6	68.3±1.1	0.390
Fasting glucose (mg/dL)	99.3±3.5	104.8±2.9	0.252
HbA1c (%)^*	5.4±0.1	7.4±0.3	<0.001
HOMA-IR^*	3.2±0.1	8.1±0.7	<0.001
Total cholesterol (mg/dL)^*	163.2±8.7	172.0±4.1	0.334
LDL-C (mg/dL)	103.4±30.0	110.6±29.9	0.309
HDL-C (mg/dL)^*	47.8±1.9	41.0±0.9	0.001
Triglyceride (mg/dL)^*	100.5±10.0	137.2±7.3	0.001
Uric acid (mg/dL)	6.8±0.2	6.9±0.2	0.787
AST (IU/L)^*	39.2±5.5	42.3±3.0	0.634
ALT (IU/L)^*	48.8±10.4	64.5±6.2	0.204
cIMT mean (μm)^*	459.7±9.0	470.1±5.8	0.321
cIMT max (μm)^*	506.8±13.6	512.7±6.7	0.688
Normal/prehypertension /hypertension	10:4:9 (43.5:17.4:39.1)	48:12:28 (54.6:13.6:31.8)	0.638
Normal/prediabetes/T2DM	16:7:0 (69.6:30.4:0)	24:16:48 (27.3:18.2:54.6)	<0.001
Elevated triglyceride	4 (17.4)	34 (38.6)	0.056
Low HDL-C	6 (26.1)	42 (47.7)	0.062

Values are presented as mean±standard deviation or number (%) except for log-transformed variables.

MHO, metabolically healthy obesity; MUO, metabolically unhealthy obesity; SDS, standard deviation score; BMI, body mass index; WHtR, waist-to-height ratio; HbA1c, glycated hemoglobin; HOMA-IR, homeostasis model assessment of insulin resistance; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; AST, aspartate transaminase; ALT, alanine aminotransferase; cIMT, carotid intima-media thickness; T2DM, type 2 diabetes mellitus.

^* Log-transformed values were used for the analysis and expressed as geometric mean±standard error.

Table 2.

Anthropometric and metabolic parameters according to the cIMT categories

Characteristic	Low cIMT tertile (n=40)	Mid cIMT tertile (n=34)	High cIMT tertile (n=37)	P-value
cIMT mean (μm)^*	426.3±2.3	464.0±1.7	521.4±5.7	<0.001
cIMT max (μm)^*	452.1±4.4	509.4±4.9	575.4±9.1	<0.001
Age (yr)	13.7±2.3	13.6±2.2	14.7±2.1	0.060
Male sex	27 (67.5)	26 (76.5)	27 (73.0)	0.685
Weight SDS	2.3±0.8	2.5±0.6	2.5±0.8	0.219
Height SDS	0.7±1.1	1.0±1.2	1.0±1.2	0.623
BMI (kg/m²)	30.0±4.2	31.2±3.0	31.6±4.8	0.187
BMI SDS	2.2±0.6	2.4±0.5	2.4±0.6	0.319
Waist Circumference SDS	2.7±0.7	2.8±0.5	2.7±0.7	0.839
WHtR SDS	2.7±0.6	2.7±0.6	2.6±0.7	0.689
Systolic blood pressure (mmHg)^*	116.9±1.6	122.5±2.2	123.7±2.1^†	0.028
Diastolic blood pressure (mmHg)^*	66.2±1.4	67.9±1.7	70.1±1.6	0.202
Fasting glucose	102.6±3.6	101.1±4.2	105.0±4.1	0.789
HOMA-IR^*	6.4±0.7	6.7±0.8	7.1±1.3	0.874
HbA1c (%)^*	7.0±0.4	6.7±0.4	7.2±0.4	0.678
Total cholesterol (mg/dL) ^*	167.7±6.5	172.5±6.7	170.6±6.2	0.867
LDL-C (mg/dL)	104.6±30.0	111.0±31.7	112.2±28.6	0.495
HDL-C (mg/dL)^*	43.8±1.5	40.8±1.5	42.1±1.3	0.317
Triglyceride (mg/dL)^*	128.1±11.9	132.9±10.6	125.5±9.6	0.894
Uric acid (mg/dL)	6.8±1.7	7.0±1.3	6.8±1.9	0.931
AST (IU/L)^*	44.6±5.1	40.0±4.1	40.0±4.7	0.718
ALT (IU/L)^*	64.7±10.4	58.7±8.3	58.8±9.2	0.827
Normal/prehypertension /hypertension	24:6:10 (60:15:25)	15:6:13 (44.1:17.7:38.2)	19:4:14 (51.4:10.8:37.8)	0.594
Normal/prediabetes/T2DM	16:8:16 (40:20:40)	14:7:13 (41.2:20.6:38.3)	10:8:19 (27.0:21.6:51.4)	0.710
Elevated triglyceride	14 (35.0)	13 (38.2)	11 (29.7)	0.746
Low HDL-C	14 (35.0)	20 (58.8)	14 (37.84)	0.086
MHO	10 (43.5)	6 (26.1)	7 (30.4)	0.700

Values are presented as mean±standard deviation or number (%) except for log-transformed variables.

cIMT, carotid intima-media thickness; SDS, standard deviation score; BMI, body mass index; WHtR, Waist-to-height ratio; HOMA-IR, homeostasis model assessment of insulin resistance; HbA1c, glycated hemoglobin; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; AST, aspartate transaminase; ALT, alanine aminotransferase; T2DM, type 2 diabetes mellitus.

^* Log-transformed values were used for the analysis and expressed as geometric mean±standard error.

^† P<0.05 compared with lower cIMT tertile group.

Table 3.

Factors associated with carotid intima-media thickness

Variable	Univariate		Multivariate
Variable	β±SE	P-value	β±SE	P-value
Age	0.010±0.004	0.019	0.009±0.004	0.022
Male sex	0.013±0.020	0.528	-	-
BMI SDS	0.035±0.016	0.036	0.033±0.016	0.040
Hypertension	0.015±0.018	0.405	-	-
Elevated triglyceride	0.007±0.019	0.714	-	-
Low HDL-C	0.000±0.018	0.990	-	-
Dysglycemia	0.024±0.019	0.200	-	-
MHO	-0.022±0.022	0.321	-	-

SE, standard error; BMI, body mass index; SDS, standard deviation score; HDL-C, high-density lipoprotein cholesterol; MHO, metabolically healthy obesity.

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