|Year : 2022 | Volume
| Issue : 1 | Page : 22-28
The prevalence of thyroid nodules and risk factors of thyroid nodules with metabolic disorder in Beijing: A cross-sectional study
Yuanyuan Zhang1, Alexandra Wehbe2, Xuhong Wang1, Rong Xin Sun1, Zhao Hui Zheng1, Dong Zhao1
1 Department of Endocrinology, Beijing Key Laboratory of Diabetes Prevention and Research, Lu He Hospital, Capital Medical University, Beijing, China
2 Department of Neurosurgery, Wayne State University School of Medicine, Detroit, MI, USA
|Date of Submission||04-Jul-2021|
|Date of Decision||27-Jan-2022|
|Date of Acceptance||17-Feb-2022|
|Date of Web Publication||28-Mar-2022|
Department of Endocrinology, Beijing Key Laboratory of Diabetes Prevention and research, Lu He hospital, Capital Medical University, Beijing
Source of Support: None, Conflict of Interest: None
Background: In recent years, the prevalence of thyroid nodules (TNs) has been increasing, but the relationship between metabolic abnormalities and the incidence of TNs is not well defined, and there is scant data evaluating this relationship stratified by gender. This study aims to analyze the prevalence of TNs and possible risk factors for TNs across gender lines and various metabolic states in Beijing, China.
Patients and Methods: A total of 6001 subjects who underwent thyroid ultrasounds as part of a routine medical checkup at Luhe Hospital between 2017 and 2018 were enrolled in this study. Multivariate adjustment logic was used to analyze possible demographic and clinical risk factors of TN stratified by gender.
Results: The prevalence of TNs was 44.1%, of which 45.9% were female and 40% were male. In general, the prevalence of TNs increased in parallel with advancing age. These findings were even starker among females, with TN prevalences of 37.5%, 46.5%, 52.9%, and 54.1%, among participants in <55-, 55–65-, 65–75-, and >75-year-old age groups, respectively. The prevalence of TNs was significantly higher among patients with obesity (46.8% vs. 43%, P = 0.008), central obesity (45% vs. 40.4%, P = 0.005), hypertension (47.1% vs. 42.4%, P < 0.001), metabolic syndrome (MetS) (46.1% vs. 41%, P < 0.001), and low TSH levels (46.5% vs. 37.1%, P < 0.001). MetS and obesity were independent risk factors for the prevalence of TNs (odds ratio [OR] = 1.167, [1.002–1.277] and (OR = 0.038, [1.01–1.396]), respectively). TSH had a protective effect on the prevalence of TNs (OR = 0.664, [0.585–0.75]).
Conclusions: The present study supports the existing research that contends a strong correlation between older age, MetS, and other clinical risk factors and the prevalence of TNs. This relationship only persisted among women when stratified by gender. These results set the precedent for further research on how gender influences the incidence of TNs, particularly in the setting of other clinical and demographic risk factors.
Keywords: Metabolic disorders, metabolic syndrome, risk factor, thyroid nodule
|How to cite this article:|
Zhang Y, Wehbe A, Wang X, Sun RX, Zheng ZH, Zhao D. The prevalence of thyroid nodules and risk factors of thyroid nodules with metabolic disorder in Beijing: A cross-sectional study. Environ Dis 2022;7:22-8
|How to cite this URL:|
Zhang Y, Wehbe A, Wang X, Sun RX, Zheng ZH, Zhao D. The prevalence of thyroid nodules and risk factors of thyroid nodules with metabolic disorder in Beijing: A cross-sectional study. Environ Dis [serial online] 2022 [cited 2022 May 18];7:22-8. Available from: http://www.environmentmed.org/text.asp?2022/7/1/22/341189
| Introduction|| |
Palpable thyroid nodules (TNs) are a common thyroid disorder found in 4%–7% of the population. However, studies suggest that the true prevalence of TNs is much higher.,,, A previous cross-sectional study conducted among communities in northern China suggests that the prevalence of TNs is almost up to 49%, whereas other studies estimate that up to 70% of patients have TNs found incidentally on imaging. Approximately 5%–15% of TNs are malignant, highlighting the importance of diagnostic follow-up of TNs.
Many factors may contribute to the development of TNs such as iodine deficiency, radiation exposure, autoimmune disorders, inflammation, or malignancies.,, In recent years, several studies have shown a correlation between the development of TNs in the presence of metabolic syndrome (MetS).,, MetS is a syndrome defined by the International Diabetes Federation (IDF) as the presence of central obesity plus any two of the following four factors: hypertriglyceridemia, low high density lipoprotein cholesterol (HDL) cholesterol, hypertension, and hyperglycemia. MetS has become increasingly common in recent years, with an overall prevalence of approximately 25% worldwide.
Some studies have suggested a strong association between MetS and the development of TNs. A cross-sectional study in China demonstrated a significantly higher prevalence of TNs among patients with MetS compared to those without MetS. Similar findings were found in a case–control study conducted in Turkey, which found that patients with MetS were more likely to have TNs than those without MetS. This study also found that all potential components of MetS were independent risk factors for increased mean thyroid volume. Other studies have also suggested a strong positive correlation of TN development and certain individual components of MetS, such as waist circumference (WC), hypertension, and hyperglycemia.,,,, Despite these findings, the relationship between MetS and the development of TNs is still not well-defined, and there is scant data evaluating the relationship between MetS and the development of TNs along the axes of gender. This cross-sectional study was conducted to assess the relationship of MetS and TN development among community residents in Beijing, stratified by various clinical and demographic factors including gender.
| Patients and Methods|| |
This cross-sectional study was conducted in Tong Zhou, Beijing, a region in northern China. We reviewed the medical records of all patients over the age of 30 who underwent thyroid ultrasounds as part of a routine medical checkup at LuHe hospital from July 2017 to October 2018. Inclusion criteria included being over the age of 30 living in Tong Zhou for at least 1 year. Subjects were excluded if they had any of the following: (1) thyroid-stimulating hormone (TSH) levels beyond the normal range: <0.27 or TSH >4.7 mU/L and (2) subjects with missing data on anthropometry index, demographic variables, or physical examination. A total of 6,772 medical records were reviewed, and 6,001 subjects were enrolled in the study. This study protocol was approved by the Luhe Hospital affiliated to Capital Medical University.
Thyroid US machine
An Esaote Mylab 90 color Doppler ultrasound Acoustic diagnostic instrument, with probe model LA523 and a probe frequency of 5⁓13 MHz, was used for thyroid examination.
Definition of variables
Obesity was defined based on body mass index (BMI) ≥28 kg/m2. Central obesity was defined as a WC ≥80 cm in women and ≥90 cm in men. MetS was defined using the 2005 IDF criteria, which classifies MetS as the presence of central obesity (defined as WC ≥90 cm for men and ≥80 cm for women) plus any two of the following four factors: (1) elevated triglycerides (TG) >150 mg/dl (1.70 mM), or drug treatment for elevated TG, (2) reduced serum high-density lipoprotein cholesterol (HDL-C) <50 mg/dl (1.03 mM) for men and <40 mg/dl (1.29 mM) for women or drug treatment for reduced HDL-C, (3) elevated blood pressure (systolic [SBP] >130 and/or diastolic [DBP] >85 mmHg) or antihypertensive drug treatment in a patient with a history of hypertension, and (4) elevated fasting glucose >100 mg/dl (5.6 mM) or drug treatment for elevated glucose as an alternate indicator.
Participants' height, weight, WC, and hip circumference (HC) were measured and recorded by the clinicians. WC was measured using a folding tape at the natural waistline (the level of the umbilicus) in a horizontal plane. BMI was calculated by dividing a participant's body weight (kg) by his/her height in meters squared. Participants' fasting blood samples were taken after 8 h of fasting overnight. The ARCHITECT c16000 automatic biochemical analyzer was used to determine the levels of fasting plasma glucose (FPG), total cholesterol (TC), alanine aminotransferase, aspartate aminotransferase, blood urea nitrogen, TG, high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), serum creatinine (Scr), and uric acid (UA). TSH levels were measured using an electrochemiluminescence analyzer (Roche Diagnostics, Basel, Switzerland).
All analyses in this study were performed using SPSS version 22.0 (SPSS Inc., Chicago, IL, USA). Quantitative variables were expressed as median (percentage) and the qualitative variables were presented as percentages. Nonparametric statistical methods were used, including the Wilcoxon test for continuous variables and the Chi-square test for categorical variables. Logistic regression was used to analyze the risk factors for TNs. Statistical significance was defined as a P < 0.05.
| Results|| |
Baseline characteristics of the study population and relationship between anthropometric measurements and thyroid nodules
The clinical population characteristics are demonstrated in [Table 1]. A total of 6,001 individuals (2,650 subjects with TNs and 3,351 subjects without TNs) were included in the present study and were further stratified by gender. The prevalence of TNs in the total population was 44.1%. Females had higher prevalence of TNs than males (44.5% and 40.1%, respectively). Compared to the control group, subjects with TNs were older (P < 0.001) and had higher BMIs (P < 0.05), WC (P < 0.05), HC (P < 0.001), SBP (P < 0.001), TGs (P < 0.05), TC (P < 0.05), and FPG (P < 0.05). Serum TSH in the TNs group was lower than that of the control group (P < 0.001). When stratified by gender, significant differences persisted in the categories of age (P < 0.001), BMI (P < 0.05), WC (P < 0.001), HC (P < 0.001), SBP (P < 0.001), FPG (P < 0.05), and TSH levels (P < 0.001) between the TN group and control group among females, but not among males.
|Table 1: General characteristics of the participants according to the prevalence or absence of thyroid nodules|
Click here to view
[Table 2] shows the prevalence of TNs stratified by various demographic and clinical factors. The prevalence of TNs among those with MetS was higher than among those without MetS (46.1% vs. 41%, respectively, P < 0.0001). In general, the prevalence of TNs increased as age increased: 37.6%, 43.5%, 50%, 48%, among age categories of <55-, 55–65-, 65–75-, and >75-year-old, respectively (P < 0.001). The prevalence of TNs also increased as BMI increased: 42.7%, 44.9%, and 46.4%, among BMI categories of <25.0, 25–30, and >30.0 kg/m2, respectively (P < 0.001). The prevalence of TNs decreased as TSH levels increased: 37.1% in the TSH ≥2.5 mIU/L subgroup and 46.5% in TSH <2.5 mIU/L subgroup (P < 0.001). The prevalence of TNs was higher among those with hypertension, obesity, and central obesity compared to those without (42.4% vs. 47.1%, 43% vs. 46.8%, and 40.4% vs. 45%, respectively, P < 0.05). There were no significant differences in the prevalence of TNs in female and male subgroups stratified by BMI, diabetic status, having central obesity, UA levels, presence of nonalcoholic fatty liver disease, and waist-to-hip ratio.
Logistic regression analysis of risk factors of metabolic disorders in thyroid nodules
The adjusted odds ratio (OR) for the prevalence of TN in all subjects was calculated adjusting for age, sex, BMI, TG, TC, LDL, HDL, and UA. As shown in [Table 3], the binary logistic regression analysis showed that MetS (OR = 1.167, [1.002–1.277]) and obesity (OR = 0.038, [1.01–1.396]) were independent risk factors for the prevalence of TNs. TSH (OR = 0.664, [0.585–0.75]) was a protective factor for the prevalence of TNs [Figure 1].
|Table 3: Logistic regression analysis of risk factors of metabolic disorders in thyroid nodules|
Click here to view
|Figure 1: Logistic regression analysis of risk factors of metabolic disorders in thyroid nodules. The associations were analyzed using logistic regression analysis. The regression models were adjusted for age, sex. BMI: Body mass index, TG: Triglycerides, CHO, LDL-C: Low-density lipoprotein-cholesterol, HDL-C: High-density lipoprotein-cholesterol, UA: Uric acid, TSH: Thyroid-stimulating hormone, NAFLD: Nonalcoholic fatty liver disease|
Click here to view
| Discussion|| |
We performed a cross-sectional analysis in a large community-based population in Beijing. We found that the overall prevalence of TNs in the surveyed population was 44.1%. These findings are similar to the results of another survey which found the prevalence of TNs in Beijing to be 49%. However, our findings are higher compared to a study from Lithuania that found TN prevalence to be 31.2%. These differences may be derived from many factors such as dietary habits, living environment, iodine nutritional status, or genetics.
Previous studies,, have demonstrated that TNs are closely associated with metabolic abnormalities. Our results demonstrate that TNs were more common among participants with abnormal metabolic parameters, such as higher BMI, WC, HC, hypertension, hyperglycemia, and dyslipidemia, further reinforcing the findings from previous studies. Furthermore, we found that obesity and MetS were independent risk factors for the occurrence of TNs.
In addition, we observed that individuals who were obese or those who had central obesity, hypertension, or MetS had a higher TN prevalence in the total population and among women when compared to that of the control group. However, these associations did not persist among the strata of men. Another study also reported a higher prevalence of nodules in obese subjects. Further, a study conducted by Wang et al. found that age, female gender, BMI, and serum homocysteine level were the independent risk factors for TNs. Some literature speculates that the incidence of TN is higher in females than male,because normal thyroid tissue expresses estrogen receptors, and the increase of serum estrogen levels in women directly affects the thyroid gland. Studies have shown that estrogen stimulates the proliferation of thyroid cells up to double that in males, leading to cell proliferation and the development of TNs., Another possible explanation is that hormones may protect against the harmful effects of metabolic disorders. Hormonal differences in gender may influence the susceptibility of TN development. After adjusting for factors of gender and age, MetS was found to be a risk factor for TNs, which is consistent with most reports of increased prevalence of TN in MetS or insulin resistance.,,, Hyper-insulinemia and insulin resistance are known to commonly accompany MetS. Insulin resistance is accompanied by compensatory hyperinsulinemia and elevated levels of IGF-1, which is the growth factor that stimulates cell proliferation., These hormones are thought to regulate the proliferation and differentiation of thyroid cells,, thus contributing to the formation of TNs. The association between TN nodules and metabolic abnormalities in our study suggests that the thyroid gland may be another target organ associated with insulin resistance syndrome.
Our study found that subjects with TNs had lower TSH levels than the controls. Within the normal range of TSH level, we observed that the higher the TSH level, the lower the chance of TNs. Similarly, Shin et al. and Ding et al. also reported that higher TSH levels were associated with a decreased risk of TNs. Some literature indicates that higher TSH levels can increase the risk of differentiated thyroid carcinoma among patients with nodular thyroid diseases;, however, few research studies have focused on the relationship between benign TNs and increased TSH levels. One possible explanation for this phenomenon is the autonomous secretion of thyroid hormone by TNs, resulting in low TSH levels due to negative feedback. However, further research on this specific relationship should be conducted.
One limitation of our study is that it is a cross-sectional study, from which we cannot deduce causal associations. Furthermore, the subjects of our study were from the same community, thus the results may not be easily generalizable to other populations. In addition, our study assessed the population at one particular time point, and thus we were not able to assess how the data would change over time or account for a dynamic population. Lastly, thyroid hormone levels were not recorded in the research and a future study could provide valuable insight into the physiologic mechanisms relating TSH and the development of TNs. Further research that accounts for these factors should be conducted to create a more comprehensive picture of the relationship between MetS and the development of TNs.
Our data revealed a high prevalence of TNs in northern China. The prevalence of TNs was higher among women than among men. Older age, female gender, and MetS were found to be independent risk factors for TNs. TSH is negatively correlated with the prevalence of TNs. We suggest that TSH levels <2.5 mU/L should be assessed for the presence of TNs even if their TSH level is within the normal range. Our results support a relationship between the presence of metabolic abnormalities and the prevalence of TNs. Further clarifying the relationship between MetS and TNs may help us better understand the clinical significance of TNs.
Financial support and sponsorship
This research was supported by the capital funds for healthy improvements and research (Grant #2020-4-7082).
Conflicts of interest
There are no conflicts of interest.
| References|| |
Hegedüs L. Clinical practice. The thyroid nodule. N Engl J Med 2004;351:1764-71.
Ezzat S, Sarti DA, Cain DR, Braunstein GD. Thyroid incidentalomas. Prevalence by palpation and ultrasonography. Arch Intern Med 1994;154:1838-40.
Brander A, Viikinkoski P, Nickels J, Kivisaari L. Thyroid gland: US screening in a random adult population. Radiology 1991;181:683-7.
Reiners C, Wegscheider K, Schicha H, Theissen P, Vaupel R, Wrbitzky R, et al.
Prevalence of thyroid disorders in the working population of Germany: Ultrasonography screening in 96,278 unselected employees. Thyroid 2004;14:926-32.
Mortensen JD, Woolner LB, Bennett WA. Gross and microscopic findings in clinically normal thyroid glands. J Clin Endocrinol Metab 1955;15:1270-80.
Jiang H, Tian Y, Yan W, Kong Y, Wang H, Wang A, et al.
The prevalence of thyroid nodules and an analysis of related lifestyle factors in Beijing communities. Int J Environ Res Public Health 2016;13:442.
Burman KD, Wartofsky L. Clinical practice. Thyroid nodules. N Engl J Med 2015;373:2347-56.
Alexander EK, Marqusee E, Orcutt J, Benson CB, Frates MC, Doubilet PM, et al.
Thyroid nodule shape and prediction of malignancy. Thyroid 2004;14:953-8.
Knudsen N, Laurberg P, Perrild H, Bülow I, Ovesen L, Jørgensen T. Risk factors for goiter and thyroid nodules. Thyroid 2002;12:879-88.
Carlé A, Krejbjerg A, Laurberg P. Epidemiology of nodular goitre. Influence of iodine intake. Best Pract Res Clin Endocrinol Metab 2014;28:465-79.
Akarsu E, Akçay G, Capoğlu I, Unüvar N. Iodine deficiency and goiter prevalence of the adult population in Erzurum. Acta Medica (Hradec Kralove) 2005;48:39-42.
Jin M, Zhang Z, Li Y, Teng D, Shi X, Ba J, et al.
U-shaped associations between urinary iodine concentration and the prevalence of metabolic disorders: A cross-sectional study. Thyroid 2020;30:1053-65.
Zhang J, Gao Y, Li Y, Teng D, Xue Y, Yan L, et al.
The presence of serum TgAb suggests lower risks for glucose and lipid metabolic disorders in Euthyroid General Population from a National Survey. Front Endocrinol (Lausanne) 2020;11:139.
He J, Lai Y, Yang J, Yao Y, Li Y, Teng W, et al.
The relationship between thyroid function and metabolic syndrome and its components: A cross-sectional study in a Chinese population. Front Endocrinol (Lausanne) 2021;12:661160.
Alberti KG, Zimmet P, Shaw J, IDF Epidemiology Task Force Consensus Group. The metabolic syndrome – A new worldwide definition. Lancet 2005;366:1059-62.
Saklayen MG. The global epidemic of the metabolic syndrome. Curr Hypertens Rep 2018;20:12.
Feng S, Zhang Z, Xu S, Mao X, Feng Y, Zhu Y, et al.
The prevalence of thyroid nodules and their association with metabolic syndrome risk factors in a moderate iodine intake area. Metab Syndr Relat Disord 2017;15:93-7.
Ayturk S, Gursoy A, Kut A, Anil C, Nar A, Tutuncu NB. Metabolic syndrome and its components are associated with increased thyroid volume and nodule prevalence in a mild-to-moderate iodine-deficient area. Eur J Endocrinol 2009;161:599-605.
Yin J, Wang C, Shao Q, Qu D, Song Z, Shan P, et al.
Relationship between the prevalence of thyroid nodules and metabolic syndrome in the iodine-adequate area of Hangzhou, China: A cross-sectional and cohort study. Int J Endocrinol 2014;2014:675796.
Blanc E, Ponce C, Brodschi D, Nepote A, Barreto A, Schnitman M, et al.
Association between worse metabolic control and increased thyroid volume and nodular disease in elderly adults with metabolic syndrome. Metab Syndr Relat Disord 2015;13:221-6.
Kwong N, Medici M, Angell TE, Liu X, Marqusee E, Cibas ES, et al.
The influence of patient age on thyroid nodule formation, multinodularity, and thyroid cancer risk. J Clin Endocrinol Metab 2015;100:4434-40.
Frates MC, Benson CB, Doubilet PM, Cibas ES, Marqusee E. Can color Doppler sonography aid in the prediction of malignancy of thyroid nodules? J Ultrasound Med 2003;22:127-31.
Dauksiene D, Petkeviciene J, Klumbiene J, Verkauskiene R, Vainikonyte-Kristapone J, Seibokaite A, et al.
Factors associated with the prevalence of thyroid nodules and goiter in middle-aged euthyroid subjects. Int J Endocrinol 2017;2017:8401518.
Moon JH, Hyun MK, Lee JY, Shim JI, Kim TH, Choi HS, et al.
Prevalence of thyroid nodules and their associated clinical parameters: A large-scale, multicenter-based health checkup study. Korean J Intern Med 2018;33:753-62.
Shin J, Kim MH, Yoon KH, Kang MI, Cha BY, Lim DJ. Relationship between metabolic syndrome and thyroid nodules in healthy Koreans. Korean J Intern Med 2016;31:98-105.
Ding X, Xu Y, Wang Y, Li X, Lu C, Su J, et al.
Gender disparity in the relationship between prevalence of thyroid nodules and metabolic syndrome components: The SHDC-CDPC community-based study. Mediators Inflamm 2017;2017:8481049.
Sousa PA, Vaisman M, Carneiro JR, Guimarães L, Freitas H, Pinheiro MF, et al.
Prevalence of goiter and thyroid nodular disease in patients with class III obesity. Arq Bras Endocrinol Metabol 2013;57:120-5.
Pan Q, Wang Y, Wang G. The association between hyperhomocysteinemia and thyroid nodule prevalence in an adult population. Metab Syndr Relat Disord 2020;18:368-72.
Xu S, Chen G, Peng W, Renko K, Derwahl M. Oestrogen action on thyroid progenitor cells: Relevant for the pathogenesis of thyroid nodules? J Endocrinol 2013;218:125-33.
Kim MH, Park YR, Lim DJ, Yoon KH, Kang MI, Cha BY, et al.
The relationship between thyroid nodules and uterine fibroids. Endocr J 2010;57:615-21.
Rezzonico J, Rezzonico M, Pusiol E, Pitoia F, Niepomniszcze H. Introducing the thyroid gland as another victim of the insulin resistance syndrome. Thyroid 2008;18:461-4.
Vella V, Sciacca L, Pandini G, Mineo R, Squatrito S, Vigneri R, et al.
The IGF system in thyroid cancer: New concepts. Mol Pathol 2001;54:121-4.
Mohan S, Baylink DJ, Pettis JL. Insulin-like growth factor (IGF)-binding proteins in serum-do they have additional roles besides modulating the endocrine IGF actions? J Clin Endocrinol Metab 1996;81:3817-20.
Santisteban P, Acebrón A, Polycarpou-Schwarz M, Di Lauro R. Insulin and insulin-like growth factor I regulate a thyroid-specific nuclear protein that binds to the thyroglobulin promoter. Mol Endocrinol 1992;6:1310-7.
Zafón C, Obiols G, Mesa J. Preoperative TSH level and risk of thyroid cancer in patients with nodular thyroid disease: Nodule size contribution. Endocrinol Nutr 2015;62:24-8.
Al-Bader A, Zawawi F, Singer Z, Mlynarek A, Hier M, Tamilia M, et al.
Preoperative TSH and thyroglobulin levels: Would it predict thyroid cancer? Otolaryngol Pol 2015;69:21-5.
[Table 1], [Table 2], [Table 3]