Association of gender and metabolic factors with thyroid nodules in T2DM: a retrospective study

Introduction

In recent decades, the global incidence of thyroid nodules (TNs) has risen substantially. High-resolution ultrasound, with a detection rate ranging from 20% to 76%, (Durante et al., 2018) is currently the most sensitive method for identifying changes in nodules and detecting new formation. TNs are reported to affect 15–34.1% of Chinese adults (Guo et al., 2014; Xu et al., 2021). Although the majority of TNs discovered during routine physical examination are benign, 7–15% will progress to various types of thyroid cancer (Wong, Farrell & Grossmann, 2018), imposing a substantial burden on patients and society. Thus, a more complete understanding of the risk factors for TNs may help to improve prevention efforts in this population at high risk, particularly if there is evidence that modifying these risk factors can improve clinical outcomes.

Numerous studies have demonstrated a higher incidence of thyroid nodules (TNs) in elderly individuals and females (Kobaly, Kim & Mandel, 2022). Additionally, metabolic conditions such as obesity, diabetes, hypertension, dyslipidemia, hyperuricemia, and fatty liver have been identified as significant risk factors for TNs (Yin et al., 2014; Zhang et al., 2021; Guo et al., 2019; Chen et al., 2018). Notably, the relationship between metabolic diseases and thyroid nodules differs by gender (Zhang et al., 2022). For example, some studies show that metabolic syndrome and diabetes are only strongly associated with the risk of developing TNs in women but not in men (Ding et al., 2017), while others show that central obesity is a risk factor for TNs in men (Zhang et al., 2021) but not in women. However, the mechanism underlying the high incidence of TNs in women remains unknown.

Among the various metabolic risk factors, abnormalities in glucose metabolism are recognized as the most significant contributors to the development of TNs (Gerasimova & Perova, 1985). Reports indicate that the incidence of TNs increases progressively with worsening impairments in glucose metabolism (Chang et al., 2021). As one of the most common chronic metabolic diseases at present, studies have reported a 78% higher incidence of TNs and a 66% higher incidence of thyroid cancer in patients with type 2 diabetes mellitus (T2DM) compared with the normal population (Zhang et al., 2019). Similarly, the prevalence of diabetes in adults with TNs was found to be 24% higher than in those without TNs (Alyousif et al., 2023). Altogether, these studies support a “two-way relationship” between diabetes and TNs and even between thyroid cancer.

The relationship between metabolic syndrome (MetS) and thyroid morphology disorders, including thyroid nodules, can be attributed to multiple interconnected mechanisms. For example, MetS components, such as obesity, dyslipidemia, and hyperglycemia, can cause systemic chronic low-grade inflammation and oxidative stress, which, in turn, disrupt thyroid function and structure. Thyroid hormones are known to influence lipid metabolism, blood pressure regulation, and insulin sensitivity, creating a bidirectional interaction between thyroid morphology and metabolic health (Fussey et al., 2020). Additionally, adipose tissue accumulation, particularly visceral fat, has been linked to altered secretion of adipokines and pro-inflammatory cytokines, which may exacerbate thyroid tissue damage and nodule formation. Thyroid morphology changes, such as increased thyroid volume or nodule formation, have also been associated with MetS components like abdominal obesity and hypertension, further supporting the complex interplay between MetS and thyroid dysfunction (Jakubiak et al., 2024a; Jakubiak et al., 2024b).

Although both T2DM and female sex are recognized as risk factors for TNs, few studies have specifically focused on the risk factors for TNs in female T2DM patients, limiting the understanding of the possible mechanisms underlying the intersection between T2DM and TNs. The aim of the present study was to investigate the risk factors for TNs in male and female T2DM patients, including metabolic markers and obesity markers derived from anthropometric parameters. It is expected that elucidation of these risk factors may help facilitate earlier and more effective preventive interventions.

Materials and Methods

Results

Basic information and prevalence of thyroid nodules in the subjects

A flow diagram of the subjects is shown in Fig. 1. The baseline characteristics of male and female subjects are included in Table 1. There were 474 males (63.45%) and 273 females (36.55%), with a mean age of 54.34 ± 12.83 years. The subjects with TNs showed a high ratio of women to men (52.75% vs. 27.85%), and both men and women with TNs were older (males: 50.83 ± 13.02 vs 54.06 ± 11.4, p < 0.001; females: 54.06 ± 11.70 vs 60.78 ± 11.68, p < 0.001).

Table 1:

Characteristics of patients with type 2 diabetes mellitus according to the presence of thyroid nodules.

	Males			Females
Variables	Unpresent n = 342	Present n = 132	P value	Unpresent n = 129	Present n = 144	P value
Age (years)	50.84 ± 13.02	56.65 ± 11.44	<0.001	54.06 ± 11.70	60.79 ± 11.68	<0.001
DM course (years)	7 (2, 14)	8 (3, 14)	0.331	9 (3, 13)	10 (3.75, 15)	0.075
Smoking (%)	170 (49.7%)	65 (49.2%)	0.928	2 (1.6%)	4 (2.8%)	0.782
Drinking (%)	97 (28.4%)	32 (24.2%)	0.366	0 (0%)	1 (0.7%)	1.000
ASCVD (%)	101 (29.5%)	50 (37.9%)	0.080	45 (34.9%)	65 (45.1%)	0.085
SBP (mmHg)	131.92 ± 15.53	132.96 ± 15.88	0.514	129.59 ± 15.23	134.98 ± 17.05	0.007
DBP (mmHg)	84.37 ± 10.00	83.69 ± 8.77	0.471	79.89 ± 9.68	81.56 ± 10.35	0.171
Metformin (%)	198 (57.9%)	85 (64.4%)	0.196	69 (53.5%)	90 (62.5%)	0.132
Insulin (%)	153 (44.7%)	67 (50.8%)	0.239	67 (51.9%)	65 (45.1%)	0.262
HbA1c (%)	8.87 ± 2.24	8.37 ± 2.01	0.023	8.75 ± 2.11	8.39 ± 2.04	0.157
UA (μmol/L)	319.5 (270, 380)	320 (273.75, 366.5)	0.952	279 (240, 323)	302 (243.5, 367)	0.014
TC (mmol/L)	4.59 ± 1.29	4.36 ± 1.18	0.077	4.70 ± 1.21	4.68 ± 1.07	0.859
TG (mmol/L)	1.69 (1.11, 2.75)	1.53 (1.03, 2.22)	0.008	1.58 (1.05, 1.96)	1.64 (1.19, 2.30)	0.120
HDL-C (mmol/L)	1.04 (0.9, 1.19)	1.02 (0.90, 1.19)	0.888	1.172 ± 0.25	1.18 ± 0.34	0.877
LDL-C (mmol/L)	2.59 ± 0.95	2.45 ± 0.94	0.151	2.55 ± 0.93	2.54 ± 0.85	0.953
TSH (uIU/ml)	1.91 (1.17, 3.04)	1.84 (1.27, 2.54)	0.206	2.24 (1.51, 3.54)	2.19 (1.29, 3.30)	0.856
Weight (kg)	74.76 ± 10.89	76.18 ± 11.45	0.211	62.44 ± 9.29	65.45 ± 10.34	0.012
Body composition
BMI (kg/m2)	25.76 ± 3.23	26.30 ± 3.43	0.107	24.86 ± 3.34	26.01 ± 3.81	0.008
PBF (%)	26.54 ± 6.07	27.38 ± 6.67	0.187	34.29 ± 5.85	36.23 ± 6.56	0.011
WHR	0.92 ± 0.06	0.92 ± 0.07	0.719	0.90 ± 0.05	0.93 ± 0.07	<0.001
SLM (kg)	51.5 ± 5.95	51.78 ± 5.90	0.645	38.33 ± 4.44	38.86 ± 4.06	0.307
FFM (kg)	54.54 ± 6.32	54.84 ± 6.25	0.641	40.70 ± 4.72	41.27 ± 4.31	0.297
SMM (kg)	30.20 ± 3.78	30.37 ± 3.81	0.654	21.84 ± 2.79	22.10 ± 2.58	0.425
VFA (cm3)	94.20 ± 33.31	99.12 ± 37.52	0.188	109.47 ± 37.53	126.33 ± 45.46	<0.001
AC (cm)	32.32 ± 2.75	32.52 ± 2.85	0.480	30.19 ± 2.61	30.99 ± 3.07	0.011
Overweight (%)	232 (67.8%)	98 (74.2%)	0.174	73 (56.6%)	96 (66.7%)	0.087
Obesity (%)	87	40 (30.3%)	0.284	19 (14.7%)	41 (28.5%)	0.006

DOI: 10.7717/peerj.19068/table-1

Notes:

Abbreviations

BMI

body mass index

PBF

percentage of body fat

WHR

waist-hip ratio

SLM

soft lean mass

FFM

fat-free mass

SMM

skeletal muscle mass

VFA

visceral fat area

AC

upper arm circumference

Bold values represent those with P < 0.05.

In male T2DM patients, the subjects in the TNs group had significantly lower HbA1c and TG levels than the subjects in the non-TNs group (P < 0.05), while there were no differences in blood pressure, thyroid function, body weight or body composition or other blood lipid indexes, including TC, HDL-C and LDL-C, among the groups.

SBP, UA, body weight, and other body components, including BMI, WHR, PBF, VFA, and upper AC, were significantly increased in female T2DM patients with TNs compared with non-TNs (P < 0.05). The incidence rate of TNs in obese females was much higher than that in patients without obesity (28.5% vs. 14.7%, p = 0.006). Overweight females also had a higher prevalence of TNs, although the difference was not statistically significant (66.7% vs. 56.6%, p = 0.085). There was no statistically significant difference between HbA1c, thyroid function, and lipid levels.

Association between anthropometric parameters and thyroid nodule risk

In univariable logistic regression analyses, age, HbA1c, and TG were significantly associated with a high risk of TNs in males with T2DM (all p < 0.05; Table S1). The results of the multivariable hierarchical logistic regression analysis indicate that only advanced age (OR=4.141, 95% CI [1.999–8.577]) was an independent risk factor for TNs in males with T2DM (Fig. 2A).

In univariable logistic regression analyses, age, disease course, SBP, UA, obesity, BMI, WHR, PBF, VFA and upper AC were significantly associated with a high risk of TNs in females with T2DM, but skeletal muscle mass (SMM), lean body mass (SLM), or fat-free body mass (FFM) were not (Table S2). The results of the multivariable hierarchical logistic regression analysis indicate that advanced age (OR=3.733, 95% CI [1.704–8.176]), hyperuricemia (OR=1.997, 95% CI [1.030–3.873]), and obesity (OR=2.575, 95% CI [1.227–5.404]) were independent risk factors for TNs in females with T2DM (Fig. 2B). To assess the effect of obesity on TNs in more detail, multiple logistic regression showed that weight (OR=1.042, 95% CI [1.012–1.072]), BMI (OR=1.098, 95% CI [1.018–1.185]), PBF (OR=1.043, 95% CI [1.000–1.087]), WHR (OR=1.065, 95% CI [1.018–1.115]), VFA (OR=1.009, 95% CI [1.002–1.015]), and AC (OR=1.135, 95% CI [1.031–1.251]) were independent risk factors for TNs in females with T2DM (Fig. 2C).

The diameter of the largest thyroid nodule was only slightly correlated with age in females with T2DM (R = 0.226, p < 0.01) (Fig. 3A), whereas there was no association between body weight or other body composition. Among the female T2DM patients with TNs, an increase in the number of larger TNs (≥1 cm) was observed with advancing age (59.04 ± 12.38 vs 65.81 ± 7.46, p < 0.001) (Fig. 3B).

Development and validation of an individualized prediction model

Based on multivariable logistic regression, a simple nomogram was developed for females with T2DM. The nomogram was evaluated using the receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). The final risk score was calculated by adding up the score of each item using the nomogram depicted in Fig. 4A. The term “risk” refers to the presence of TNs in females with T2DM.

ROC analysis was performed to calculate the predictive accuracy of the nomogram, and the average area (AUC) of the nomogram was 0.703 (95% CI [0.641–0.703]) (Fig. 4B). Internal validity is a way to measure if the nomogram is sound, and 200 random bootstrap resamplings were performed to reduce overfit bias. Figure 4C shows that the AUC of the random bootstrap resampling was 0.703 (95% CI [0.640–0.765]), indicating that the nomogram had satisfactory sensitivity. Furthermore, the model had good calibration by the Hosmer–Lemeshow statistic (P = 0.4515). The final DCA showed that if the threshold probability of patients was between 35 and 80%, screening strategies based on our nomogram’ TNs risk estimates resulted in an insuperior net benefit than screen-none or screen-all strategies (Fig. 4D).

Discussion

With changes in lifestyle, the incidence of both TNs and T2DM has increased significantly worldwide in recent years. Although studies have suggested that age, gender, prediabetes, diabetes and obesity may be risk factors for TNs and even thyroid cancer (Buscemi et al., 2018; Guo et al., 2014; Morna et al., 2022), the risk factors for TNs in patients with pre-existing diabetes have not yet been explored. Therefore, we investigated whether obesity-related body composition indicators and related metabolic risk factors are associated with the presence of TNs in T2DM patients. Most palpable thyroid nodules are found in older women, and the incidence ratio of males to females is 1:5 (Haugen et al., 2016), but their clinical significance remains unclear. Based on that, differences in incidence rates by sex suggest that risk factors for TNs should be investigated separately for men and women. In the present study, we observed a TNs detection rate of 36.95% in all patients, including 52.75% for women and 27.85% for men, which was significantly higher than that in the nondiabetic population (men 23.2%, women 35.7% (Liang et al., 2023)). Both female sex and advanced age were identified as risk factors for TNs in T2DM patients, consistent with findings in healthy populations (Buscemi et al., 2018).

Obesity is significant concern as is it increases the incidence of T2DM and TNs. Previous studies have reported that 53% of adults with diabetes are obese, and the incidence of T2DM in patients with abdominal obesity was 2.14 times that in those without (Rhee, 2020; Freemantle et al., 2008). Therefore, understanding metabolic and obesity indices is critical for the developing strategies to prevent TNs in T2DM patients. Our study found that the incidence of TNs was significantly higher in obese compared to nonobese T2DM patients. Moreover, obesity remained an independent risk factor for TNs in women with T2DM after adjusting for age and other factors but not in men.

Obesity is a major contributor to insulin resistance, a common pathogenic factor for T2DM and TNs. While obesity is a significant risk factor for T2DM in both sexes, women over the age of 45 years are often overweight or tend to be more obese than men (Beck et al., 2020). As reported, the reduction in estrogen in older women (postmenopausal women) accelerates the development of insulin resistance (Kim et al., 2022). Sex differences in adiposity and insulin resistance likely contribute to the observed sex differences in the development of TNs, whereas there is no significant difference in the incidence of TNs among children who are not influenced by estrogen (Wang et al., 2017).

A study from China reported that crude anthropometric parameters, such as body weight and BMI, can predict the risk of thyroid nodules, especially in adult women (Xu et al., 2015). However, neither body weight nor BMI can differentiate between muscle and fat accumulation or adipose tissue distribution, which limits the predictability of obesity-related diseases (Gomez-Ambrosi et al., 2012). Recent studies have demonstrated a complex relationship between thyroid morphology, metabolic syndrome, and cardiovascular health. For example, thyroid volume and free triiodothyronine (FT3) levels have been shown to correlate with body composition parameters, such as visceral fat and waist circumference, highlighting the potential role of inflammatory and hormonal mechanisms. Moreover, subclinical cardiovascular dysfunction, assessed using markers like the ankle-brachial index (ABI) and toe-brachial index (TBI), has been associated with thyroid morphology and function, suggesting a broader impact of thyroid abnormalities on systemic vascular health. These findings support the hypothesis that thyroid morphology and metabolic syndrome components may interact in ways that influence both cardiovascular risk and TNs, aligning with the gender-specific patterns observed in this study (Jakubiak et al., 2024a; Jakubiak et al., 2024b).

In recent years, body composition has emerged as an alternative to traditional indicators, such as PBF, VFA, and upper AC, which can assist in identifying abnormal fat distribution. Among these, upper AC has been found to be positively correlated with metabolic syndrome in a population of middle-aged and older adults (Shi et al., 2020) and is regarded as a simple and effective index for detecting central obesity and IR (Zhu et al., 2020; Musa, Omar & Adam, 2022). Consistent with other studies, our findings revealed of TNs in female obese patients was significantly higher than in nonobese patients. After further adjusting for age, UA and other metabolic indicators, body weight, BMI, and WHR remained independent risk factors for TNs. Furthermore, our study suggests that other obesity-related measures, including PBF, VFA, and upper AC, may serve as potential risk indicators for TNs in women with T2DM. Notably, a significant correlation between TNs and these obesity-related indicators was observed in women only, not in men. Collectively, these findings highlight the importance of identifying high-risk groups among women with T2DM and understanding the underlying sex differences, which may provide critical insights for effective management. Nevertheless, further research is warranted to elucidate the mechanisms underlying these associations.

The 2023 European Thyroid Association (ETA) Clinical Practice Guidelines for thyroid nodule management suggest that further evaluation of thyroid nodules with a diameter of ≥1 cm may be more beneficial for improving patient prognosis (Durante et al., 2023). Thus, more attention should be given to thyroid nodules with a diameter of ≥1 cm. Although several studies have reported that obesity is associated with thyroid nodule size, our studies showed a positive correlation between age and the maximum nodule diameter but not with obesity-related indicators. This suggests that obesity may be more associated with an increased risk of developing TNs than the risk of further development of larger nodules. We should pay more attention to TNs in elderly women with T2DM because larger nodules were consistently more prevalent in female T2DM patients at a more advanced age (Rezzonico et al., 2011; Ayturk et al., 2009). Although studies have reported that metformin use or TSH levels are associated with thyroid nodule size, our study did not find such a correlation (Table S3).

Among the relevant metabolic markers, UA is an independent risk factor for TNs in females with T2DM, even after adjustment for age, weight, and other metabolic factors. but not in men. Previous studies have shown that the correlation between UA and TNs also has gender differences, which found that uric acid has a protective effect in men over 30 years of age (Liu et al., 2017) but is a risk factor in both women and men under the age of 30 years. In addition, the results diverged from the findings in some previous studies, and systolic blood pressure was ultimately not identified as a risk factor independently associated with the incidence of TNs. This may be due to the limited sample size, and a future prospective cohort study with a larger sample size should be conducted to confirm these observations.

The limitations of this study include its single-center design with a relatively small sample size, the exclusive focus on type 2 diabetes patients without including a normal population for comparison, and the lack of consideration for certain potential predictors such as dietary status and iodine nutrition. Additionally, the use of two-dimensional ultrasound limited the assessment of thyroid nodule characteristics to maximum diameter, which does not fully reflect their three-dimensional structure or biological behavior. Furthermore, due to the high proportion of missing data for anti-thyroid peroxidase (anti-TPO) and anti-thyroglobulin (anti-TG) antibody measurements, we were unable to assess their potential influence on thyroid gland size, which remains a limitation of the study. Finally, as a cross-sectional study, causal relationships between obesity and thyroid nodules cannot be established, and external validation of the nomogram’s performance is still required.

Conclusion

Despite well-documented sex differences, few studies have explored the variations in the clinical presentation of TNs between men and women with T2DM. Our findings indicate that obesity and hyperuricemia have a much stronger influence on TNs in women than in men with T2DM. Specifically, weight, BMI, WHR, PBF, VFA, and upper AC are independent risk factors for TNs in women with T2DM. Furthermore, nodule size is associated with age but not with obesity. These findings highlight potential metabolic mechanisms underlying sex differences in nodule formation and provide a simplified nomogram to aid in screening high-risk populations among women with T2DM. For women with T2DM, in addition to glycemic control, managing body weight is crucial for the prevention of TNs.

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