Association of high-normal thyroid-stimulating hormone levels with metabolic syndrome and abdominal obesity in euthyroid adolescents: insights from the Korea National Health and Nutrition Examination Survey
Article information
Abstract
Purpose
Metabolic syndrome (MetS) is increasingly prevalent among adolescents, and thyroid-stimulating hormone (TSH) levels influence metabolic health. This study investigates whether TSH levels are associated with MetS and its components in euthyroid adolescents.
Methods
We used data from the Korean National Health and Nutrition Examination Survey between 2013 and 2015. The study included 940 euthyroid adolescents aged 10–18 years, who were divided into 2 groups: high-normal TSH group (top 25% of euthyroid TSH levels) and nonhigh TSH group (remaining 75%). We analyzed the association between high-normal TSH levels and MetS and its components.
Results
TSH quartiles were related to MetS (P for trend=0.006). The prevalence of MetS was 3.5% in the high-normal TSH group and 1.9% in the nonhigh group (P=0.1929). Abdominal obesity was more prevalent in the high-normal TSH than in the nonhigh TSH group (16.2% vs. 9.6%, P=0.0153). Other MetS components were more prevalent in the high-normal TSH group, but the difference was not significant. High-normal TSH was significantly associated with abdominal obesity (adjusted odds ratio, 1.975; 95% confidence interval, 1.104–3.531, P=0.0218).
Conclusions
In euthyroid adolescents, a significant trend was observed between TSH quartile and MetS. Specifically, high-normal TSH levels showed a significant association with abdominal obesity, a key component of MetS.
Highlights
· In euthyroid adolescents, high-normal TSH levels showed a higher prevalence of metabolic syndrome and its components.
· Among the components of metabolic syndrome, abdominal obesity showed a significant association with high-normal TSH levels.
· Even within the normal range, high TSH levels may be related to an increased metabolic risk, and abdominal obesity might have a distinct relationship.
Introduction
Metabolic syndrome (MetS) has shown a significant increase in prevalence among young adults and children worldwide, emerging as a mounting health concern that affects not only adults but also these younger populations [1]. Characterized by a cluster of disorders, including abdominal obesity, glucose intolerance, hypertension, and dyslipidemia, MetS significantly raises the risk of developing cardiovascular disease (CVD) and type 2 diabetes [2,3]. This risk is particularly concerning when MetS manifests at a young age because metabolic changes during adolescence can have long-lasting effects on MetS-related disease [4]. Therefore, understanding early metabolic risk factors is critical for designing effective prevention strategies.
Thyroid function, specifically thyroid-stimulating hormone (TSH) level, has been recognized as an important factor in metabolic health [5]. Thyroid dysfunction is associated with an unfavorable lipid profile and other risk factors for CVD, such as hypertension, endothelial dysfunction, and insulin resistance [6,7]. Although overt thyroid dysfunction is well established as a contributor to metabolic disturbances, growing evidence suggests that even subtle variations in TSH levels within the euthyroid range might affect metabolic risk factors [8]. However, most studies exploring the relationship between TSH and MetS have focused on adult populations, leaving a significant gap in understanding how these associations might manifest in younger individuals, particularly adolescents [9,10].
Adolescence is a critical period for the development of MetS because rapid physiological and hormonal changes can significantly influence metabolic processes [11,12]. The relationship between TSH levels within the euthyroid range and MetS in this age group is not yet fully understood, particularly in populations that might have unique genetic, environmental, and lifestyle influences on both thyroid function and metabolic health [13]. A study of Korean adolescents found that those with obesity had higher TSH and lower free T4 levels than adolescents with normal weight [14]. However, although previous studies have examined individual metabolic components in relation to thyroid function, comprehensive analyses of all MetS components in an adolescent population remain scarce [15]. Clarifying these associations could help identify adolescents at high risk of MetS and potentially guide more effective interventions.
Therefore, in this study, we investigate the association between TSH levels and MetS and its components in euthyroid Korean adolescents. By focusing on this specific population, our research provides valuable insights that could inform early detection and prevention strategies for MetS during adolescence and ultimately contribute to better long-term health outcomes.
Materials and methods
1. Data source and study population
This nationwide population-based cohort study used data from the Korean National Health and Nutrition Examination Survey (KNHANES). The KNHANES includes a health interview, a health examination survey, and a nutrition survey. The Korean Centers for Disease Control and Prevention (KCDC) has conducted these nationally representative cross-sectional surveys annually since 2007, when it transitioned from a triennial schedule to promptly assess the health and nutrition status of Koreans [16]. The surveys sample non-institutionalized civilians aged 1 year and older using a stratified multistage clustered probability sampling design. For the nutrition survey, biochemical screenings are conducted on participants aged 10 years and older. The KCDC obtained approval from the KCDC Institutional Review Board and collected all samples in accordance with the ethical principles of the Helsinki Declaration for medical research involving human subjects.
From the KNHANES database between 2013 and 2015, we identified 2,425 participants aged 10–18 years. Among them, 1,021 adolescents had undergone thyroid function tests. Because our participants of interest were adolescents in the euthyroid TSH range, 963 participants (94.3%) were included as the study cohort. After excluding participants with incomplete data, the final population consisted of 940 adolescents, 498 of whom were male (Fig. 1, Supplementary Table 1).
Flow diagram of the study population. Data from 2,425 participants aged 10–18 years were collected from the Korean National Health and Nutrition Examination Survey from 2013 to 2015. We then excluded 1,404 participants without thyroid function tests, 58 participants with thyroidstimulating hormone levels <0.62 mIU/L or >6.86 mIU/L and free T4 levels <0.96 ng/dL or >1.60 ng/dL, and 23 participants with incomplete data. Consequently, 940 participants (498 males and 442 females) were included in the final analysis.
2. MetS and its components
The primary outcome was MetS and its components. MetS in adolescents was defined according to the International Diabetes Federation (IDF) guidelines [17]. The new IDF definition of metabolic disease varies by age group, and the following criteria were applied for adolescents. For participants aged 10–15 years, the criteria are abdominal obesity (90th percentile of waist circumference) [18] plus at least 2 other clinical features from the following list: triglycerides ≥150 mg/dL, high-density lipoprotein cholesterol (HDL-C) <40 mg/dL, systolic blood pressure (SBP) ≥130 mmHg or diastolic blood pressure ≥85 mmHg, and fasting plasma glucose (FPG) ≥100 mg/dL or diagnosed type 2 diabetes mellitus. For those aged 16 years and older, the IDF adult criteria were used [19]. The cutoff for abdominal obesity was ≥90 cm for males and ≥80 cm for females.
3. High-normal vs. nonhigh TSH in euthyroid adolescents
Serum TSH and free thyroxine (fT4) levels were measured using an electrochemiluminescence immunoassay (Roche Diagnostics, Germany). The reference interval of serum TSH was defined as the 2.5th to 97.5th percentile of the serum TSH levels of the reference population. The definition of euthyroid in the Korean reference population is a serum TSH concentration of 0.62–6.86 mIU/L and an fT4 of 0.96–1.60 ng/dL [20]. The reference population was defined as subjects with no history of thyroid disease and no history of taking medication that could influence thyroid function. However, because a health interview about thyroid disease history was not conducted for participants aged 10–18 years, we assumed that these young participants within the euthyroid range had no prior history of thyroid disease.
To investigate the relationship between TSH levels within the normal range and MetS and its components, we classified participants within the euthyroid reference range into 4 quartiles. In our study population, nonhigh TSH levels ranged from 0.62 to 3.34 mIU/L, and high-normal TSH levels ranged from 3.35 to 6.86 mIU/L.
4. Clinical information and laboratory analysis
Anthropometry, blood pressure measurement, and blood analysis protocols are well-described in the KNHANES-VI guidelines [21]. Waist circumference was measured at the narrowest point between the lower borders of the rib cage and the iliac crest at the end of normal expiration. Blood pressure was monitored using an oscillometric device 3 times at 30-second intervals after 5 minutes of rest; the average of the second and third measurements was then recorded. Blood samples were obtained in the morning after an overnight fast of at least 8 hours. FPG, total cholesterol, low-density lipoprotein cholesterol, HDL-C, and triglyceride levels were measured with a Hitachi Automatic Analyzer 7600 (Hitachi Ltd., Japan). The reported results for TSH and fT4 met the specifications for accuracy, general chemistry, special immunology, and ligands of the quality control and quality assurance program of the College of American Pathologists [22].
5. Statistical analysis
Using weighted data, we compared participant clinical and biochemical characteristics by MetS status to ensure internal validity, identify key differences, and detect potential confounders for subsequent analyses. We conducted 2-sample t-tests for continuous variables to examine whether the characteristics of participants with and without MetS differed significantly. To handle the complexities of survey data with clustering and stratification design, we applied the Rao-Scott chi-square test and assessed differences in categorical variables between the 2 groups by MetS status as well. For that comparison, we weighted the data to ensure the representativeness of the population of interest, correcting for any potential biases in the sample and balancing the distribution of variables in the 2 groups. Because clinical variables such as triglycerides, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) exhibited right-skewed distributions, geometric means were calculated to minimize the influence of outliers. Additionally, log-transformations were applied to these variables to reduce skewness and ensure compatibility with statistical tests assuming normally distributed residuals. Using weighted data, we also conducted analysis of covariance tests to examine the association between MetS and the 4 quartiles of TSH levels, adjusting for relevant covariates. We performed analyses in 3 models: unadjusted, adjusted for age and sex, and further adjusted for log-transformed ALT. We performed t-tests to compare MetS and its components in the high-normal TSH versus nonhigh TSH groups. We further used logistic regression analyses to examine their associations. Covariate adjustment was used with 3 models: model 1 was an unadjusted crude model; model 2 was adjusted for age and sex; and model 3 was further adjusted for log-transformed ALT. We applied a 95% confidence level using a 2-sided test to determine the significance of the P-values. All analyses were performed using the SAS 9.3 (SAS Institute Inc., USA).
6. Ethical statement
This study was approved by the Institutional Review Board of Myongji Hospital (MJH 2018-07-013) in accordance with the Declaration of Helsinki. The requirement for informed consent was waived by the board because this study is retrospective and KNHANES participants provided consent to participate in the surveys.
Results
1. Baseline characteristics between study subjects with and without MetS
Using the weighted data, we compared the clinical and biochemical characteristics of study subjects by MetS status, as shown in Table 1. Compared with the non-MetS group, the MetS group showed significantly higher values in body mass index (BMI) (21.2±0.1 vs. 29.6±0.7 kg/m2), waist circumference (71±0.4 cm vs. 93.3±2.3 cm), SBP (108.5±0.4 mmHg vs. 120.7±2.8 mmHg), triglyceride levels (73.1 mg/dL vs. 179 mg/dL), AST (17.8 IU/L vs. 22.2 IU/L), and ALT (12.7 IU/L vs. 26.8 IU/L), and HDL-C levels were significantly lower in the MetS group (51.9±0.4 mg/dL vs. 38±1.6 mg/dL). Although the differences were not statistically significant, adolescents with MetS also tended to have higher TSH levels (2.71±0.05 mg/dL vs. 2.93±0.33 mg/dL), and a greater percentage of them had high-normal TSH (24.1% vs. 37.4%).
Baseline characteristics of study subjects with and without metabolic syndrome
2. Association between MetS and TSH quartiles in euthyroid adolescents
We examined the association between MetS and TSH levels in euthyroid adolescents by stratifying the TSH levels into 4 quartiles. As shown in Fig. 2, after adjusting for covariates, a significant association with MetS was observed across TSH quartiles. Although the association between MetS and TSH quartiles was not strictly linear, it tended to increase with higher TSH quartiles, reaching its peak in the second quartile (Q2) (Supplementary Table 2). This trend remained significant after adjusting for age and sex (model 2: P for trend=0.012) and further adjusting for log-transformed ALT (model 3: P for trend=0.006), compared with the crude model (model 1: P for trend=0.010).
Association between TSH quartiles and MetS in euthyroid adolescents. The x-axis represents the TSH quartiles, and the y-axis shows the coefficient estimates of MetS. The graph shows a significant association between higher TSH quartiles and an increased risk of MetS after adjusting for age, sex, and log-transformed ALT (P for trend=0.006). Error bars represent standard error. MetS, metabolic syndrome; TSH, thyroid-stimulating hormone; CL, confidence limit; ALT, alanine transaminase.
3. Prevalence of MetS and its components in the high-normal TSH vs. nonhigh TSH groups
To further investigate how higher TSH levels were associated with an increased risk of MetS and its components, we differentiated between the high-normal TSH group and the nonhigh TSH group (Table 2). The prevalence of MetS was numerically higher in the high-normal TSH group (3.5%) than the nonhigh TSH group (1.9%), but the difference was not statistically significant (P=0.1929). Similarly, the prevalence of some MetS components—elevated blood pressure, hyperglycemia, hypertriglyceridemia, and low HDL-C—varied between the 2 TSH groups; however, none of those differences reached statistical significance. Among the MetS components, only abdominal obesity differed significantly between the high-normal TSH and nonhigh TSH groups, with a higher prevalence in the high-normal TSH group (16.2% vs. 9.6%, P=0.0153).
Prevalence of metabolic syndrome and its components in nonhigh vs. high-normal TSH groups
4. Risk of MetS and its components in high-normal TSH
Table 3 presents the results from logistic regression conducted to determine whether and how the high-normal TSH and nonhigh TSH groups were associated with MetS and its components. The risk of abdominal obesity was significantly higher in the high-normal TSH group than the nonhigh TSH group (model 1: odds ratio [OR], 1.828; 95% confidence interval [CI], 1.115–2.996; P=0.0168; model 2: adjusted OR, 1.896; 95% CI, 1.155–3.122; P=0.011; model 3: adjusted OR, 1.975; 95% CI, 1.104–3.531, P=0.0218). Consistent with the findings in Table 2, however, no significant association was observed between the high-normal TSH group and hypertriglyceridemia, low HDL-C, elevated blood pressure, hyperglycemia, or MetS.
Association of high-normal TSH with metabolic syndrome and its components
Discussion
In this study, we evaluated the relationship between TSH levels and MetS and its components in euthyroid adolescents. We found a statistically significant trend between the quartiles of TSH levels and MetS. The prevalence of MetS, elevated blood pressure, hyperglycemia, hypertriglyceridemia, and low HDL-C tended to be higher in the high-normal TSH group than in the nonhigh TSH group, but those differences were not statistically significant. Notably, abdominal obesity was significantly associated with high-normal TSH levels. Further research is needed to explore the underlying mechanisms linking high-normal TSH levels with MetS components, particularly abdominal obesity.
The relationship between TSH levels and MetS and its components in euthyroid populations has been explored in several studies. In adults, studies on the association between high TSH levels within the normal range and metabolic parameters such as blood pressure, HbA1c, BMI, lipid parameters, and MetS have demonstrated consistent results of significant associations [23,24]. A high-normal TSH level was also linked to a higher prevalence of MetS in euthyroid healthy adults [25]. In children and adolescents, several studies have reported that high-normal TSH is associated with fewer metabolic parameters than in adults [26-28]. Le et al. showed that TSH within the normal range was correlated with total cholesterol and FPG regardless of age, sex, and race [13]. Nader et al. [27] and Zhang et al. [15] revealed that higher triglyceride level was observed in the higher TSH group of euthyroid adolescents. In a study of adolescents aged 12–18 years without thyroid disease, in which only 2% had subclinical hypothyroidism, the highest TSH quartile was associated with increased risk of abdominal obesity and higher metabolic risk [26]. Similarly, in this study, our results show that the risk of MetS tended to increase as the TSH quartiles rose, except for the second TSH quartile. However, among the components of MetS, only abdominal obesity differed significantly between the high-normal TSH and nonhigh TSH groups.
The effects of high TSH levels on MetS and its components in the euthyroid state vary not only between adolescents and adults, but also across studies focused on adolescents. These discrepancies could be attributed to differences in the physiological and hormonal responses to elevated TSH levels across different age groups, as well as variations in study designs, sample sizes, and diagnostic criteria for adolescents. Research has shown that TSH levels tend to increase with age during adolescence [29]; however, most studies have applied a uniform TSH reference range across all age groups in children and adolescents, rather than using age-specific reference ranges [26]. Further studies with age-adjusted TSH levels, a consistent age grouping of adolescents, and a standardized definition of the control TSH group are necessary. Addressing those research gaps could provide more accurate insight into the relationship between TSH levels and MetS and ultimately lead to better-targeted interventions and improved health outcomes for both adolescents and adults.
We analyzed TSH levels concurrently with MetS and its individual components in euthyroid adolescents, which distinguishes our work from previous research examining thyroid function in relation to either MetS or its individual components separately. Our results show no significant associations between TSH levels and MetS and most of its components, but we did find statistically significant associations between abdominal obesity and TSH levels. This suggests an association between TSH levels and abdominal obesity that is distinct from other parameters. Given the complexity of MetS and its components, understanding the underlying mechanisms that link abdominal obesity to thyroid function is crucial [30]. Although our study provides valuable insight into this specific relationship, further investigations are needed to explore the potential biological mechanisms underlying the association between thyroid function and abdominal obesity in adolescents.
Recent research has shown that obesity can influence the function of the thyroid gland, usually leading to increased TSH levels within the normal range [30]. The etiology of these changes remains unclear; however, several mechanisms have been proposed, including an adaptive process to increase energy expenditure, hyperleptinemia, changes in the activity of deiodinases, the presence of thyroid hormone resistance, chronic low-grade inflammation, and insulin resistance [31,32]. A Mendelian randomization study revealed that genetically determined TSH levels do not causally result in obesity, but genetically determined high BMI can cause elevated TSH levels [33]. In short, thyroid dysfunction can lead to obesity, and obesity might increase TSH levels as a compensatory metabolic mechanism. Although the clinical implications have not been clarified, other studies have shown an association between TSH levels and obesity in adolescents. A cross-sectional study observed elevated TSH levels in obese children and adolescents [34]. Another study found that TSH levels correlated with BMI and the degree of abdominal obesity, suggesting that higher TSH levels were directly related to the severity of obesity, especially abdominal obesity [35].
This study has several limitations. First, due to its cross-sectional design, causal relationships cannot be discerned. Second, only a single-point serum TSH test was performed because the study population consisted of healthy adolescents. Third, age-specific TSH reference ranges were not applied. Fourth, we did not adjust for confounding factors other than age, sex, and ALT levels. Fifth, our findings might be constrained by the Korean adolescent population. A larger and more diverse sample could improve the generalizability of the results. Nonetheless, this study provides valuable insights into TSH levels and abdominal obesity specifically in healthy adolescents. Further longitudinal studies are warranted to understand the long-term effects of high-normal TSH on metabolic health.
In conclusion, a stronger association with MetS was observed at higher TSH levels, and the high-normal TSH group in euthyroid adolescents tended to show a higher prevalence of MetS and its components. However, among the metabolic components, only abdominal obesity showed a significant difference between the high-normal and nonhigh TSH groups. These findings suggest that thyroid function, even within the euthyroid range, might affect certain aspects of metabolic health in Korean adolescents. Moreover, abdominal obesity could have a distinct relationship with high-normal TSH levels, compared with other metabolic parameters. Further research is needed to explore the relationship between high-normal TSH levels and MetS components in adolescents more comprehensively. Investigating these relationships could help refine screening practices and strategies to prevent metabolic disease in adolescents.
Supplementary materials
Supplementary Tables 1-2 are available at https://doi.org/10.6065/apem.2448324.162.
Baseline characteristics of study subjects by sex
Association of TSH quartiles and metabolic syndrome
Notes
Conflicts of interest
No potential conflict of interest relevant to this article was reported.
Funding
This work was supported by the Technology Innovation Program (20008924), funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea).
Data availability
The data that support the findings of this study are available from the Korean Centers for Disease Control and Prevention. Restrictions apply to the availability of these data, which were used under license for this study. Data are available from https://knhanes.cdc.go.kr/knhanes/eng/ with the permission of the Korean Centers for Disease Control and Prevention.
Author contribution
Conceptualization: KH, MKL; Data curation: KH; Formal analysis: KH; Funding acquisition: MKL; Writing - original draft: JH; Writing - review & editing: JH, HO, MKL