Association Between Thyroid Nodules and Volume and Metabolic Syndrome in an Iodine-Adequate Area: A Large Community-Based Population Study

Abstract

Background:

Given its high incidence, thyroid nodule (TN) warrants public attention. Thyroid volume (TV) has also been associated with multiple factors, such as iodine deficiency and supply and body mass index. It is well known that metabolic syndrome (MetS) comprises many metabolic disturbances, with insulin resistance being its major component.

Materials and Methods:

The aim of this study was to investigate the relationship between TN and TV and MetS and its components in an iodine-adequate area in Asia. All participants were asked to complete a questionnaire. After excluding 938 individuals based on the exclusion criteria, we reviewed data from 927 of 1865 participants. Adopting MetS diagnostic criteria, we found 437 subjects to be MetS positive [MetS(+)] and 490 subjects to be MetS negative [MetS(−)], respectively. Multivariate linear regression was used to assess the relationship between TNs and MetS. Moreover, univariate binary logistic regression analyses were used to calculate odds ratios (ORs), and 95% confidence intervals (CIs) were used to estimate the associations between different variables and TNs.

Results:

A total of 232 females and 205 males were MetS(+), as diagnosed using the International Diabetes Federation criteria. However, there were 330 females and 160 males in the group of MetS(−) individuals. The prevalence of TNs was 38.29% in the MetS(+) group and 17.79% in the MetS(−) group. After adjusting for systolic blood pressure, diastolic blood pressure, and gender, only high-density lipoprotein, waist circumference (WC), and age were related to TNs (OR = 0.45, 95% CI 0.27–0.75, P = 0.0023; OR = 1.04, 95% CI 1.02–1.06, P = 0.0036). The TV of all participants was 13.98 (11.24, 17.01) mL; 13.26 (10.62, 16.17) mL for females and 14.96 (11.83, 18.01) mL for males. It was found that only WC was related to TV, after controlling for sex and age (P = 0.02).

Conclusions:

The morbidity among TN patients in the MetS(+) group was higher than that among the MetS(−) group. High-density lipoprotein cholesterol emerged as a protective factor, and WC was a risk factor for TN. Moreover, TV was related to MetS, and WC was an independent risk factor for TV.

Introduction

Thyroid nodule (TN) is defined as “discrete lesions within the thyroid gland, radiologically distinct from surrounding thyroid parenchyma” by American Thyroid Association.¹ About 60 years ago, the overall incidence of nodules in the thyroid gland in this series was only 2.6%, and clinically solitary nodules were found in 1.6% of the subjects and 1.0% had multinodular glands.² However, in recent years, a high incidence of TNs has been found by ultrasound, which helps distinguish benign from malignant nodules.³ One survey has reported that 33% to 68% of adults have TNs, and that ∼7% to 15% of individuals with TNs harbor thyroid cancer.⁴ Besides, evidence indicates that incidental nodules, palpable and nonpalpable nodules have the same incidence of thyroid cancer.⁵ We still need to examine the predisposing factors leading to this phenomenon.

There are numerous pathologic conditions of the thyroid, including thyroiditis, endocrine dysregulation, autoimmune thyroid disease, and various metabolic abnormalities.^6
–8 Somatic thyroid stimulating hormone (TSH) receptor mutations have been discovered as the most prevalent molecular event in the etiology of autonomously functioning TNs.⁹ It is well known that there are numerous factors associated with the formation of TN and thyroid volume (TV). Moreover, iodine is not only a major component of thyroid hormones but also provides a microenvironment for thyroid cells to thrive. A number of studies have indicated that both iodine deficiency and iodine excess can result in an increased prevalence of thyroid disorders by a U curve.¹⁰

Previous studies have revealed that obesity¹¹ and impaired glucose metabolism¹² are risk factors for thyroid abnormalities. Moreover, some studies have demonstrated that insulin resistance (IR), the central features of metabolic syndrome (MetS), may induce increased thyroid proliferation and nodule formation.^12,13 The MetS involves a cluster of risk factors that increase the risk of heart disease and type 2 diabetes.¹⁴ It has been well established that MetS is characterized by central obesity, hypertension, hyperglycemia, and dyslipidemia.¹⁵ With unhealthy lifestyle changes, the incidence of MetS has been skyrocketing worldwide. A survey has shown that 12.7% of Chinese males and 14.2% of Chinese females have MetS.¹⁶ Therefore, the high prevalence of MetS results in the rising incidence of TN.

China was an iodine-deficient country with 370 million people living in iodine-deficient areas before the year of 1970. As a result, a program of local iodine supplementation was introduced in iodine-deficient areas in 1979.¹⁰ However, recently, a cross-sectional study has demonstrated that the goal of eliminating iodine deficiency has been successfully achieved in China, and proved that Jinan is an adequate iodine intake city.¹⁷ Previous studies have shown that MetS and its components are associated with an increased prevalence of TN in a mild-to-moderate iodine-deficient area in Europe.¹⁸ In this study, we aimed to examine the association between TN and TV and MetS and its components in an iodine-adequate area in Asia.

Materials and Methods

Study subjects

From September 2009 to April 2010, every study participant completed a questionnaire, in which demographic characteristics, family and personal medical history, general health status, and current medications were assessed. All 1875 subjects were >20 years of age (male: female, 1:1.463) and came from the district of Yangguang, Jinan, Shandong in China. This community-based population study was approved by the Ethics Committee of the Shandong Provincial Hospital affiliated with Shandong University. A total of 1741 participants participated in this study. Individuals who had any of the following characteristics were excluded from the study: (1) participants diagnosed with thyroid diseases or thyroid therapy at any time; (2) individuals with some chronic diseases (e.g., hepatic or renal dysfunction, cardiac failure); (3) pregnant or lactating women; and (4) individuals with other endocrine diseases or autoimmune diseases. According to the exclusion criteria and MetS diagnostic criteria, 927 individuals were enrolled in this project.

Definition of MetS

According to the International Diabetes Federation (IDF) guidelines in 2006, participants were diagnosed as MetS(+) or MetS(−).¹⁹ Three or more of the following criteria were used to define MetS: (1) Dyslipidemia found in patients with the MetS presents in routine lipoprotein analysis as raised triglycerides (TGs) and low concentrations of high-density lipoprotein (HDL) cholesterol (HDLC). If the TG is >1.7 mmol/L or reduced HDLC <1.03 mmol/L, 40 mg/dL in men and 1.29 mmol/L, 50 mg/dL in women or specific treatment for these lipid abnormalities; (3) elevated blood pressure (BP) associates with obesity and glucose intolerance, and commonly occurs in insulin-resistant persons. Systolic blood pressure (SBP) is >130 mmHg and/or diastolic blood pressure (DBP) is presented >85 mmHg; (4) fasting plasma glucose is a good test that can be used to help diagnose diabetes or prediabetes. The number >5.6 mmol/L will be recognized as positive for MetS; (5) waist circumference (WC) provides a crude but effective measure of visceral fat. Central obesity defined as a WC ≥80 cm for women and 90 cm for men. All subjects provided signed informed consent form before participating in the study.

Biochemical evaluations

Peripheral venous blood samples were collected from the participants who were asked not to take in anything for at least 12 hours before being tested between 8:00 a.m. and 9:00 a.m. The serum samples were separated into three EP tubes ∼600 μL each after centrifugation and immediately stored at −80°C. Total cholesterol (CHOL), TGs, low-density lipoprotein cholesterol (LDLC), HDLC, and insulin were measured using routine enzymatic methods with an Olympus 5400 analyzer. Using the glucose oxidase method, plasma glucose concentrations were measured. We defined the reference ranges as follows: CHOL 3.6–6.2 mmol/L, HDLC 0.8–1.5 mmol/L, LDLC 0.5–3.36 mmol/L, TG 0.4–1.8 mmol/L, and fasting blood glucose (FBG) 3.9–6.3 mmol/L.

Anthropometric measurements

The heights and weights of the participants without thick clothes and shoes were measured by the same person. WC was measured at the midpoint between the lower costal margin and the iliac crest using the same tape. In addition, BP, including SBP and DBP, was measured three times at 5-minute intervals using a hamnatodynamometer (OMRON HEM7200; OMRON, Japan). The mean of the three measurements were used for statistical analysis.

Thyroid evaluation

Thyroid ultrasonography was performed by the same physician who did not know the clinical conditions of the participants and had at least 3 years of work experience focusing on thyroid diagnoses. Ultrasonography was performed using a Logiq (GE Healthcare, Waukesha, WI) with a high-frequency linear transducer (range 7–10 MHz) with the participants in a supine position, to test whether they had TNs. On ultrasound, TNs are depicted as discrete lesions, as they cause distortion of the homogeneous echo pattern of the thyroid gland.¹ The ultrasound would register the diameter of the TN if it exceeded 3 mm. As a result, all subjects were divided into two groups: a nodule-free group including 732 participants and a group of individuals with at least one nodule including 195 individuals. All types of nodules were recorded, including solid nodules and mixed nodules, excluding pure cystic nodules. The ellipsoid formula [volume (mL) = depth (cm) × length (cm) × width (cm) × π/6] was used to calculate TV (each lobe separately).

Statistical analysis

According to the IDF criteria, 437 individuals met three or four criteria, and they were diagnosed with MetS. A total of 490 individuals were negative. This analysis included 195 individuals with TNs who were MetS positive [MetS(+)] and 74 participants with TNs who were MetS negative [MetS(−)]. All data were analyzed using the SPSS 19.0 software package (SPSS, Inc., Chicago, IL). Using the Kolmogorov–Smirnov test, continuous variables with normal distribution are presented with the mean and standard deviation; the median and interquartile range is shown when a normal distribution was not observed. Comparisons of continuous variables between the two groups were performed with Student's t-test or Mann–Whitney U test. χ² tests were used to analyze percentages. Multivariate linear regression was used to assess the relationship between TNs and MetS. Moreover, univariate and multivariate binary logistic regression analyses were used to calculate odds ratios (ORs), and 95% confidence intervals (CIs) were used to estimate the associations between different variables and TNs. Data not conforming to a normal distribution were log- or ln-transformed. A P value <0.05 indicated significance.

Results

General characteristics of the subjects

This study included 927 participants, including 562 females and 365 males. A total of 232 females and 205 males were MetS(+), as diagnosed using the IDF criteria. However, there were 330 females and 160 males in the group of MetS(−) individuals. One hundred and ninety five individuals were diagnosed as MetS(+) and TNs, including 132 females and 63 males. According to the MetS criteria, Table 1 displays the baseline characteristics of age, lipid profiles, FBG, BP, WC, and TV, and Table 2 shows the data by stratified gender.

Table 1.

Baseline Characteristics of Stratified Gender of the Study Subjects

	Male	Female
Age	46.00 (33.00, 59.00)	45.50 (32.25, 58)
TG	1.59 (0.97, 2.40)	1.04 (0.71, 1.80)
HDLC	1.35 (1.19, 1.55)	1.59 (1.38, 1.86)
FBG	5.32 (4.90, 6.02)	5.09 (4.75, 5.65)
SBP	122 (110, 137)	115 (104, 130)
DBP	80 (74, 90)	78 (70, 84)
WC	89.18 ± 11.11	77.00 (71.00, 85.38)
TN	63	132
TV	14.96 (11.83, 18.01)	13.26 (10.62, 16.17)

DBP, diastolic blood pressure; FBG, fasting blood glucose; HDLC, high-density lipoprotein cholesterol; SBP, systolic blood pressure; TG, triglyceride; TN, thyroid nodule; TV, thyroid volume; WC, waist circumference.

Table 2.

Baseline Characteristics of Stratified Gender of the Study Subjects According to the Metabolic Syndrome Criteria

	Male		Female
	MetS(+)	MetS(−)	MetS(+)	MetS(−)
Age	50 (40, 62)	34.5 (25, 51)	57 (50, 64)	36 (27, 45.25)
TG	2.25 (1.79, 3.02)	0.91 (0.70, 1.21)	1.95 (1.44, 2.59)	0.78 (0.59, 0.98)
HDLC	1.28 ± 0.24	1.52 ± 0.28	1.38 ± 0.31	1.78 ± 0.30
FBG	5.89 (5.36, 7.07)	4.97 (4.71, 5.23)	5.76 (5.29, 6.55)	4.88 (4.60, 5.11)
SBP	130 (125, 143)	112 (108, 120)	130 (120, 142)	108 (100, 112)
DBP	88 (80, 92)	74 (70, 80)	85 (80, 90)	70 (68, 76.5)
WC	96 (92, 100)	80 (75, 86)	87 (83, 92)	72 (69, 76)
TN prevalence	38	25	84	48
TV	16.11 ± 5.21	14.13 (11.32, 16.85)	15.25 (11.43, 17.40)	12.81 (10.23, 15.40)

MetS, metabolic syndrome.

Thyroid function and MetS

As shown in Table 3, FT3 and FT4 were not correlated with metabolic syndrome (MetS) using Mann–Whitney analysis, except for TSH. In addition, in the female group, TSH was not correlated with MetS. Conversely, there was an association between TSH and MetS in the male group (P = 0.026).

Table 3.

Mann–Whitney Analysis: Thyroid Function and Insulin

	Male			Female
	MetS(+)	MetS(−)	P	MetS(+)	MetS(−)	P
FT3	5.53 ± 0.61	5.64 ± 0.56	0.083	5.05 ± 0.44	4.97 ± 0.043	0.866
FT4	17.45 ± 2.35	17.02 ± 2.09	0.073	16.15 ± 2.17	16.17 ± 5.04	0.94
TSH	2.59 (1.61, 3.45)	2.38 (1.71, 3.17)	0.026	1.89 (1.35, 2.36)	2.12 (1.46, 2.87)	0.274
INS	10.15 (7.49, 13.98)	6.03 (4.24, 7.99)	<0.01	11.19 (7.39, 15.72)	5.90 (4.09, 8.10)	<0.01
HOMA-IR	2.68 (1.95, 3.96)	1.26 (0.91, 1.80)	<0.01	3.15 (2.21, 4.55)	1.31 (0.86, 1.77)	<0.01

FT3, free T3; FT4, free T4; HOMA-IR, homeostasis model assessment of insulin resistance; INS, insulin; TSH, thyroid stimulating hormone.

TN and MetS and its components

The association between TN and MetS

A χ² test showed that the morbidity of TNs in the MetS(+) group was higher than that of the MetS(−) group (χ² = 22.03, P < 0.05). Specifically, the prevalence of TNs was 38.29% in the MetS(+) group and 17.79% in the MetS(−) group. Univariate binary logistic regression analysis showed that TNs were significantly related to MetS (P < 0.001, OR = 2.153, 95% CI 1.557–2.977).

The association between TN and metabolic components

A total of 195 participants in this study were diagnosed with MetS and TNs, including 63 males and 132 females. As shown in Table 4, using univariate binary logistic regression analysis and adjusting for gender, we found that TG, HDLC, WC, SBP, DBP, FBG, and age were positively related to TN. After adjusting for SBP, DBP, and gender, only HDL, WC was related to TNs (OR = 0.45, 95% CI 0.27–0.75, P = 0.0023; OR = 1.04, 95% CI 1.02–1.06, P = 0.0036; OR = 1.05), as illustrated in Table 5. The fit of the curve shows a dependent relationship between TN and HDLC and WC. Therefore, we maintain that HDLC is a protective factor, and that WC is a risk factor for TN. HDLC was more likely to be a protective factor in females than in males, while WC was possibly associated with a higher risk of TN in females.

Table 4.

Univariate Binary Logistic Regression Analysis in Which the Dependent Variable is Thyroid Nodule

	Model	OR	95% CI for OR	P
Age	1	1.042	1.023–1.061	<0.01
	2	1.055	1.04–1.071	<0.01
	3	1.05	1.038–1.062	<0.01
TG	1	0.986	0.838–1.159	0.860
	2	1.417	1.201–1.672	0.000
	3	1.153	1.039–1.28	0.008
HDLC	1	0.352	0.125–0.993	0.048
	2	0.358	0.201–0.637	0.000
	3	0.357	0.216–0.59	0.000
FBG	1	1.033	0.923–1.157	0.570
	2	1.213	1.065–1.381	0.004
	3	1.103	1.019–1.195	0.016
WC	1	1.015	0.991–1.039	0.219
	2	1.067	1.045–1.089	0.000
	3	1.046	1.029–1.062	0.000
HOMA-IR	1	0.956	0.848–1.078	0.463
	2	1.094	1.005–1.19	0.037
	3	1.037	0.976–1.101	0.246

Model 1: for males, crude; Model 2: for females, crude; Model 3: for participants, after adjusting for gender.

OR, odds ratio.

Table 5.

Multivariate Binary Logistic Regression Analysis in Which the Dependent Variable is Thyroid Nodule

	Model	OR	95% CI for OR	P
Age	1	1.046	1.026–1.067	<0.01
	2	1.053	1.035–1.072	<0.01
	3	1.051	1.037–1.065	<0.01
TG	1	0.968	0.813–1.153	0.717
	2	1.224	1.02–1.471	0.030
	3	1.061	0.947–1.189	0.309
HDLC	1	0.32	0.108–0.945	0.039
	2	0.514	0.284–0.939	0.028
	3	0.448	0.267–0.75	0.002
FBG	1	1.021	0.904–1.153	0.737
	2	1.099	0.958–1.26	0.176
	3	1.045	0.957–1.141	0.330
WC	1	1.017	0.99–1.045	0.218
	2	1.054	1.028–1.08	0.000
	3	1.037	1.018–1.056	0.001

Model 1: for males, after adjusting for SBP and DBP; Model 2: for females, after adjusting for SBP and DBP; Model 3: for participants, after adjusting for SBP, DBP and gender.

TV and MetS and its components

The association between TV and gender

The TV of all participants was 13.98 (11.24, 17.01) mL, 13.26 (10.62, 16.17) mL for females, and 14.96 (11.83, 18.01) mL for males, as shown in Table 1. After the statistical analysis, we observed a difference in TV between females and males (r = −0.156, P < 0.001).

The association between TV and MetS and its components

Multivariate linear regression was used to test the correlation between TV and metabolic components. We found that only WC was related to TV, after controlling for sex and age (P = 0.02 < 0.05). Therefore, we hypothesized that WC was an independent risk factor for TV.

Discussion

Given the high incidence and risk of cancer, it is imperative to explore the etiology of TN. Nevertheless, despite numerous studies investigating this topic, the specific pathophysiologic mechanism is not completely understood. Although some studies indicate a relationship between obesity, IR, and TN prevalence, the association between MetS and its components and TN in an iodine-adequate area is unclear. In our study, we illustrate that MetS components and age are positively related to TN. In addition, after adjusting for SBP and DBP, we conclude that HDLC was a protective factor and WC was a risk factor for TN.

Many studies suggest that TN is related to age; however, we failed to stratify age into different groups. It is possible that the prevalence of TN may increase with increasing age. Guo et al. have demonstrated that individuals >40 years of age have a higher prevalence of TN.²⁰ Zheng et al. have suggested that advanced age contributes to the high rates of TNs in postmenopausal females.²¹ Another article has maintained that thyroid nodular disease increases with age, and that age itself is a risk factor for thyroid cancer.²²

From our results, we found that the detection rate of TNs was higher in females than in males. A previous article has reported that the standardized morbidity rate of TN was 33.70% (31.82% for men and 35.35% for women), which was calculated from the population.²³ A recent cross-sectional analysis of a large community-based population study in rural China demonstrated that the incidence of TN in females is one-third higher than that in males (females: 38.5%; males: 26%).²⁴ However, in our findings, the prevalence of TN was lower than that reported in other studies. Recently, there have been many articles examining the risk factors of TN. However, the reasons why the morbidity of TN in women is higher than that in men are not completely understood. Multiple studies have provided different perspectives on this question. Sex hormones are significant risk factors that may explain this gender disparity. It has been reported that obesity may influence the levels of endogenous sex steroids, particularly after menopause. Sex hormone binding globulin concentrations are correlated with features of MetS, particularly in postmenopausal obese women.²⁵ Therefore, it has been suggested that an ultrasonic inspection should be performed as a fundamental medical checkup for women.

It is well established that the key characteristic of MetS is central obesity, and its key mechanism is IR.¹⁴ Previous studies have shown that the risk of TN in patients with central obesity or IR is higher than that in controls, and people who have IR are at an increased risk of having TN (males: 1.384 times; females: 1.267 times).²⁴ It has been reported that IR is an independent risk factor for TN formation in iodine-sufficient areas.¹⁸ However, another research group has maintained that they have not found a relationship between insulin sensitivity parameters and thyroid nodularity.²⁶ Accordingly, the association between TN and IR is a debatable issue. In our study, we also did not find any other insulin sensitivity parameters that had a relationship with TN.

As shown in Table 5, after adjusting for SBP, DBP, and gender, our study found that HDLC was an independent protective factor and WC was an independent risk factor for TN. HDLC was more likely to be a protective factor in females than in males, while WC might be associated with higher risks of TN in females. Ji et al. have found that reduced HDLC concentrations in MetS are associated with an increased risk of diabetes and cardiovascular disease,²⁷ but no previous study has found a relationship between HDLC and TN. Getz and Reardon discovered the interaction between HDLC and its constituent apoproteins, with beta cell ATP-binding cassette (ABC) transporters yielding a complex series of responses affecting insulin production, which may well be pathophysiologically relevant to MetS.²⁸ We have not found any studies examining the precise mechanism MetS of these interactions. Moreover, it has been reported that a larger WC and gradually increasing TG levels are risk factors for new TN, and a larger WC is an independent risk factor for TN.²³ The previously mentioned consequences suggest that individuals with high HDLC or larger WC are expected to undergo thyroid inspection by ultrasound every year. However, our study did not analyze the concrete number or specific range, which merits more intensive examination in future studies.

As for TV, for all participants, we found that the volume for women was larger than that for men. Among the two groups, we found that MetS(+) women had a larger volume than MetS(−) women, and that MetS(+) men did not have a larger TV than MetS(−) men. The factors affecting the volume may be explained. There is no doubt that iodine plays a significant role in thyroid function and structure. In iodine-deficient areas, there is a negative correlation between iodine intake and TV.²⁹ Knudsen et al. have noted that women were 2- to 10-fold more likely to have goiters than men.³⁰ Sex hormones could explain this phenomenon, according to previous research. One article has suggested that pregnancy increases TV, particularly in women who smoke tobacco.³¹ However, our study failed to find any relationship between smoking and goiters. It has been shown that TV increases with increasing body mass index (BMI) or body surface area.³² High BMI results in hyperinsulinemia and IR, which in turn leads to increased thyroid cell proliferation and goiter formation.³³ A recent study has shown that increased WC and BP were the most highly prevalent components in subjects with MetS.³⁴ Based on all studies, we believe that WC has a great impact on TV.

Our study has some limitations. First, the serum samples were tested only once, and they may have had discrepancies that could have affected the outcomes. Second, our study did not analyze the number of TNs and the volume of the nodules. More details about the nodules may provide information for future investigations. Finally, we analyzed only the effects of age, and we failed to stratify age into different groups to examine the topic in more detail. However, we found a clear relationship between TNs and MetS and its components.

Conclusions

Our research demonstrated an association between TN and age, and found that the prevalence of TNs in women was higher than that in men. HDLC was an independent protective factor for TN. WC was an independent risk factor for TN and TV.

Footnotes

Acknowledgments

The authors acknowledge the Ministry of Public Health of Shandong who performed this study. This work was supported by grants from the National Natural Science Foundation of China (81370892), key research and development project of Shandong Province (2016GSF201025, 2016GGH3118), and the Tarzan scholars project special funds. They thank all study participants and staff members who assisted with this analysis.

Author Disclosure Statement

No conflicting financial interests exist.

References

Cooper

, Doherty

, Haugen

, et al. Revised American Thyroid Association management guidelines for patients with thyroid nodules and differentiated thyroid cancer. Thyroid, 2009; 19:1167–1214.

Slater

. The occurrence of thyroid nodules in the general population. AMA Arch Intern Med, 1956; 98:175–180.

Xie

, Cox

, Taylor

, et al. Ultrasonography of thyroid nodules: A pictorial review. Insights Imaging, 2016; 7:77–86.

Mandel

. A 64-year-old woman with a thyroid nodule. JAMA, 2004; 292:2632–2642.

Hoang

, Raduazo

, Yousem

, et al. What to do with incidental thyroid nodules on imaging? An approach for the radiologist. Semin Ultrasound CT MR, 2012; 33:150–157.

Smith

, Chen

, Schneider

, et al. Toxic nodular goiter and cancer: A compelling case for thyroidectomy. Ann Surg Oncol, 2013; 20:1336–1340.

Reverter

, Fajardo

, Resmini

, et al. Benign and malignant nodular thyroid disease in acromegaly. Is a routine thyroid ultrasound evaluation advisable?. PLoS One, 2014; 9:e104174.

Canete

, Sison-Pena

, Jimeno

. Clinicopathological, biochemical, and sonographic features of thyroid nodule predictive of malignancy among adult Filipino patients in a Tertiary Hospital in the Philippines. Endocrinol Metab, 2014; 29:489–497.

Krohn

, Paschke

. Clinical review 133: Progress in understanding the etiology of thyroid autonomy. J Clin Endocrinol Metab, 2001; 86:3336–3345.

10.

Sun

, Shan

, Teng

. Effects of increased iodine intake on thyroid disorders. Endocrinol Metab, 2014; 29:240–247.

11.

Sari

, Balci

, Altunbas

, et al. The effect of body weight and weight loss on thyroid volume and function in obese women. Clin Endocrinol, 2003; 59:258–262.

12.

Anil

, Akkurt

, Ayturk

, et al. Impaired glucose metabolism is a risk factor for increased thyroid volume and nodule prevalence in a mild-to-moderate iodine deficient area. Metabolism, 2013; 62:970–975.

13.

Yasar

, Ertugrul

, et al. Insulin resistance in nodular thyroid disease. Endocr Res, 2011; 36:167–174.

14.

Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP). [Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III)]. JAMA, 2001; 285:2486–2497.

15.

Eckel

, Grundy

, Zimmet

. The metabolic syndrome. Lancet, 2005; 365:1415–1428.

16.

Cheng

. Metabolic syndrome in China. Circulation, 2004; 109:e180.

17.

Shan

, Chen

, Lian

, et al. Iodine status and prevalence of thyroid disorders after introduction of mandatory universal salt iodization for 16 years in China: A cross-sectional study in 10 cities. Thyroid, 2016; 26:1125–1130.

18.

Ayturk

, Gursoy

, Kut

, et al. 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.

19.

Alberti

, Zimmet

, Shaw

. Metabolic syndrome—A new world-wide definition. A consensus statement from the International Diabetes Federation. Diabet Med, 2006; 23:469–480.

20.

Guo

, Sun

, He

, et al. The prevalence of thyroid nodules and its relationship with metabolic parameters in a Chinese community-based population aged over 40 years. Endocrine, 2014; 45:230–235.

21.

Zheng

, Yan

, Kong

, et al. An epidemiological study of risk factors of thyroid nodule and goiter in Chinese women. Int J Environ Res Public Health, 2015; 12:11608–11620.

22.

Rezzonico

, Rezzonico

, Pusiol

, et al. Introducing the thyroid gland as another victim of the insulin resistance syndrome. Thyroid, 2008; 18:461–464.

23.

Yin

, Wang

, Shao

, 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.

24.

Ding

, Xu

, Wang

. 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.

25.

Akin

, Bastemir

, Alkis

, et al. SHBG levels correlate with insulin resistance in postmenopausal women. Eur J Intern Med, 2009; 20:162–167.

26.

Blanc

, Ponce

, Brodschi

, 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; 13:221–226.

27.

, Watts

, Johnson

, et al. High-density lipoprotein (HDL) transport in the metabolic syndrome: Application of a new model for HDL particle kinetics. J Clin Endocrinol Metab, 2006; 91:973–979.

28.

Getz

, Reardon

. High-density lipoprotein function in regulating insulin secretion: Possible relevance to metabolic syndrome. Arterioscler Thromb Vasc Biol, 2010; 30:1497–1499.

29.

Vejbjerg

, Knudsen

, Perrild

, et al. Effect of a mandatory iodization program on thyroid gland volume based on individuals' age, gender, and preceding severity of dietary iodine deficiency: A prospective, population-based study. J Clin Endocrinol Metab, 2007; 92:1397–1401.

30.

Knudsen

, Laurberg

, Perrild

, et al. Risk factors for goiter and thyroid nodules. Thyroid, 2002; 12:879–888.

31.

Knudsen

, Bulow

, Laurberg

, et al. Parity is associated with increased thyroid volume solely among smokers in an area with moderate to mild iodine deficiency. Eur J Endocrinol, 2002; 146:39–43.

32.

Turcios

, Lence-Anta

, Santana

, et al. Thyroid volume and its relation to anthropometric measures in a healthy cuban population. Eur Thyroid J, 2015; 4:55–61.

33.

Dauksiene

, Petkeviciene

. Factors associated with the prevalence of thyroid nodules and goiter in middle-aged euthyroid subjects. Int J Endocrinol, 2017; 2017:1–8.

34.

Siani

, Cappucco

, Barba

, et al. The relationship of waist circumference to blood pressure: the Olivetti Heart Study. Am J Hypertens, 2002; 15:780–786.