PDF
Citation
Print
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.
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.
XML Download