Next Article in Journal
Circulating miR-122 and miR-139-3p: Association with Lipid, Inflammatory, and Glycemic Profile in Adolescents with Insulin-Resistant and Overweight
Previous Article in Journal
Sleep Deprivation and Its Impact on Insulin Resistance
Previous Article in Special Issue
Novel Anthropometric Indices: An Allometric Perspective
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Endocrines
Volume 6
Issue 4
10.3390/endocrines6040050
endocrines-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Obesity Is Associated with Larger Thyroid Nodules but Not with Malignant Cytology

by
Stefania Giuliano
1,
Giuseppe Seminara
2,
Stefano Iuliano
3,
Stefania Obiso
2,
Eusebio Chiefari
1,3,
Daniela P. Foti
2,4,
Maria Mirabelli
1,3,* and
Antonio Brunetti
1,3,*
1
Operative Unit of Endocrinology, “R. Dulbecco” University Hospital, 88100 Catanzaro, Italy
2
Department of Experimental and Clinical Medicine, University “Magna Græcia” of Catanzaro, 88100 Catanzaro, Italy
3
Department of Health Sciences, University “Magna Græcia” of Catanzaro, 88100 Catanzaro, Italy
4
Operative Unit of Clinical Pathology, “R. Dulbecco” University Hospital, 88100 Catanzaro, Italy
*
Authors to whom correspondence should be addressed.
Endocrines 2025, 6(4), 50; https://doi.org/10.3390/endocrines6040050
Submission received: 11 August 2025 / Revised: 2 October 2025 / Accepted: 10 October 2025 / Published: 14 October 2025
(This article belongs to the Special Issue Feature Papers in Endocrines 2025)
Versions Notes

Abstract

Background: Obesity has been proposed as a risk factor for differentiated thyroid carcinoma (DTC), though findings in the literature remain conflicting. While some studies suggest an association between elevated body mass index (BMI) and thyroid malignancy, others attribute this link to diagnostic bias. The Calabria region in Southern Italy, historically affected by iodine deficiency and endemic goiter, offers a valuable population for investigating this relationship. Objective: This study aimed to evaluate the association between obesity and clinical, sonographic, and cytological characteristics of thyroid nodules in a Calabrian cohort undergoing fine-needle aspiration biopsy (FNAB). Methods: This retrospective observational study included 1192 patients evaluated at a single endocrine referral center between 2015 and 2024. Patients were stratified by BMI (<30 vs. ≥30 kg/m2). Demographic, biochemical, ultrasound, and cytological data were collected and analyzed. Cytological results were classified according to the SIAPEC 2014 system. Results: Obese patients had significantly larger thyroid nodules in terms of anteroposterior and transverse diameters, as well as overall volume (p < 0.05). However, the distribution of high-risk cytological categories (TIR 3B, TIR 4, and TIR 5) did not differ significantly between obese and non-obese patients (9.4% in both groups). Multivariate analysis confirmed that BMI was not an independent predictor of malignancy risk (OR 0.988; p = 0.723), whereas younger age was inversely associated with malignancy. Conclusions: Obesity appears to influence thyroid nodule size but does not constitute an independent risk factor for cytological malignancy. BMI should not influence indications for FNAB or subsequent treatment decisions. Thyroid nodule management should instead rely on ultrasound risk stratification and cytological findings. Special attention should be given to younger patients as they may carry a higher malignancy risk.

1. Introduction

Thyroid nodules are among the most frequently encountered conditions in endocrine clinical practice. These focal lesions, distinct from the surrounding thyroid parenchyma, are often identified incidentally during ultrasound examinations [1]. Their prevalence in the general adult population is estimated at 50–60%, with higher incidence in females and increasing frequency with age [2]. Although most thyroid nodules are benign and asymptomatic, clinical management focuses on identifying the minority that is malignant, which is approximately 5% of cases [3].
Over recent decades, the incidence of differentiated thyroid carcinoma (DTC), particularly papillary thyroid carcinoma (PTC), has increased globally, often due to the detection of small, indolent microcarcinomas [4]. This trend is largely attributed to widespread use of diagnostic tools such as neck ultrasound and fine-needle aspiration biopsy (FNAB), rather than a true rise in disease prevalence [5]. As a result, concerns about overdiagnosis and overtreatment have emerged, with implications for cost-effectiveness and patient safety [6,7]. Increasing attention has also been directed toward metabolic factors—especially obesity—as potential contributors to thyroid nodule pathogenesis and thyroid cancer development. Obesity, a growing global health issue, is now recognized as a risk factor for several malignancies, including DTC [8,9,10,11]. Multiple large-scale epidemiological studies and meta-analyses have reported a positive association between body mass index (BMI) and thyroid cancer risk [12], possibly mediated by mechanisms such as hyperinsulinemia, chronic low-grade inflammation [8,13], and activation of oncogenic signaling pathways (e.g., IGF-1, leptin, and inflammatory cytokines).
However, not all studies confirm a direct association between obesity and thyroid malignancy. The literature remains inconclusive [14,15,16], with some prospective and retrospective studies finding no increased thyroid cancer prevalence among obese individuals. This raises the possibility of detection bias, as obese patients are more likely to undergo thyroid imaging for unrelated endocrine issues [15,16,17,18]. As a result, debate continues regarding whether BMI independently contributes to thyroid oncogenesis and whether it should influence diagnostic or therapeutic decisions.
The Calabria region of Southern Italy offers a unique epidemiological context to explore these questions. Historically iodine-deficient [19], Calabria has exhibited high rates of endemic goiter [20,21]. Despite recent improvements through national iodine prophylaxis programs, many rural and inland areas continue to report elevated rates of nodular thyroid disease [22,23]. The region’s relative genetic and environmental homogeneity, along with stable dietary patterns, makes it an ideal setting for observational studies investigating thyroid disease.
In this context, the present retrospective observational study aims to examine the relationship between obesity and the clinical, sonographic, and cytological features of thyroid nodules in a cohort of Calabrian patients undergoing FNAB. Specifically, it evaluates whether obesity is associated with increased nodule size and whether BMI serves as an independent risk factor for cytological malignancy. The ultimate goal is to assess the role of BMI in clinical decision-making regarding thyroid nodule management.

2. Materials and Methods

2.1. Study Design and Setting

We performed a retrospective observational study at the Endocrinology Unit of “Renato Dulbecco” University Hospital, Catanzaro, Italy—the tertiary referral center for nodular thyroid disease and thyroid cancer in Calabria [24]. We included 1192 consecutive Caucasian patients from across the region who underwent ultrasound-guided FNAB between January 2015 and December 2024, after implementation of the SIAPEC 2014 cytology system [25]. Eligibility required the availability of anthropometric measurements and thyroid function tests. Patients were categorized as non-obese (BMI < 30 kg/m2) or obese (BMI ≥ 30 kg/m2), according to the WHO classification [26]. For individuals with multiple biopsied thyroid nodules, we analyzed the nodule with the highest anticipated cytological risk based on the SIAPEC 2014 classification (TIR5 (malignant) > TIR4 (suspicious of malignancy) > TIR3B (high-risk indeterminate) > TIR3A (low-risk indeterminate) > TIR1/1C (non-diagnostic) > TIR2 (benign)) [5,25]. In all cases, indications for thyroid FNAB followed the 2015 American Thyroid Association (ATA) guideline criteria [7].

2.2. Clinical and Laboratory Assessment

At the time of FNAB, we recorded demographics (age, sex), relevant medical history (e.g., autoimmune thyroid disease, family history of thyroid cancer), use of levothyroxine therapy, weight, and height, with BMI calculated as weight in kilograms divided by height in meters squared (Kg/m2). Within three months of FNAB, serum thyroid-stimulating hormone (TSH), free thyroxine (FT4), and free triiodothyronine (FT3) were measured; calcitonin and thyroid autoantibodies (anti-thyroid peroxidase [anti-TPO], anti-thyroglobulin [anti-Tg]) were assessed when indicated at the Clinical Pathology Unit, using previously described methods [27,28]. Data were captured in electronic medical records (FileMaker Pro; FileMaker Inc., Cupertino, CA, USA) and automatically extracted for the purpose of the study. When available, histological results from post-thyroidectomy follow-up patients were collected and classified as malignant (DTC, any subtype) or benign, following the WHO classification of thyroid tumors [29].

2.3. Ultrasound Evaluation and FNAB Procedure

For the entire study period (10 years), cervical ultrasonography was performed by experienced endocrinologists using a high-resolution 10 MHz system (Aplio XG, SSA-790A, Toshiba, Tokyo, Japan). For each biopsied nodule, we recorded lobe location, maximum diameters (anteroposterior, transverse, longitudinal), volume (calculated using the ellipsoid formula), echogenicity, margins, microcalcifications, and vascularity. FNAB was performed under real-time ultrasound guidance with 25–27 G needles, using capillary action for highly vascular lesions or suction for firm/fibrotic nodules. Smears were immediately alcohol-fixed and stained as per the Papanicolaou staining protocol. Cytology was interpreted by expert cytopathologists and classified according to the SIAPEC 2014 system [25]. High-risk categories were defined as TIR 3B, TIR 4, and TIR 5, given their strong correlation with histological malignancy in large surgical Calabrian cohorts [5]. However, because chronic autoimmune thyroiditis may lead to indeterminate cytology [30], and TIR 3B shows variable malignancy rates in real-world clinical scenarios [25], a sub-analysis restricted the definition of malignancy to TIR 4 and TIR 5 categories as diagnostic for malignancy.

2.4. Statistical Analysis

Quantitative variables were expressed as median and interquartile range (IQR), while categorical variables were presented as counts and valid percentages (excluding missing data). Between-group comparisons (non-obese vs. obese patients) were performed using the Mann–Whitney U test for continuous variables and the chi-square test for categorical variables. Spearman’s correlation analysis was used to evaluate associations between continuous variables, including age, BMI, TSH, and nodule size. Multivariable logistic regression was performed to identify independent predictors of high-risk cytology (≥TIR 3B, with a sub-analysis restricted to TIR4 and TIR5). Covariates entered into the model, selected for potential predictive value based on prior literature reports and univariate analysis results, were age, sex, BMI, TSH, nodule volume, use of levothyroxine therapy, and anti-TPO positivity, with additional adjustment for multinodularity at FNAB examination. Statistical significance was set at p < 0.05. All statistical analyses were performed using the JASP software version 0.17.2 (University of Amsterdam, Amsterdam, The Netherlands), based on the R programming language (https://jasp-stats.org/) [Last accessed: 10 August 2025].

3. Results

The 1192 consecutive patients undergoing thyroid FNAB enrolled in the study were subcategorized into two groups according to BMI: 840 (70.5%) were classified as non-obese (BMI < 30 kg/m2) and 352 (29.5%) as obese (BMI ≥ 30 kg/m2), reflecting the contemporary high prevalence of obesity in the adult population of Calabria [31]. Obese patients subjected to FNAB for suspicious nodular thyroid disease were slightly but significantly older than their non-obese counterparts (median 57.5 [49.0–65.0] vs. 55.0 [44.0–65.0] years; p = 0.021). Serum TSH levels were also significantly higher in the obese group (median 1.380 [0.900–2.070] vs. 1.200 [0.795–1.805] mU/L; p = 0.007). No significant differences were observed between groups in serum FT3 and FT4 levels, nor in the distribution of sex, predominantly female (Table 1). Regarding thyroid nodule characteristics, a statistically significant difference emerged in nodule dimensions. Nodules in obese patients were larger in the anteroposterior and transverse diameters (median 14.0 [10.4–19.0] mm and 17.7 [13.0–24.1] mm, respectively) compared with non-obese individuals (median 13.0 [9.6–17.9] mm and 16.5 [12.3–22.7] mm, respectively). Consequently, nodule volume was greater in the obese group (median 2723 [1010–6523] mm3 vs. 2100 [863–5228] mm3; p = 0.014) (Table 2), suggesting a possible positive association between obesity and thyroid nodule growth.
No significant differences were found between the two groups in family history of thyroid cancer, use of levothyroxine therapy, positivity of thyroid autoantibodies, or ultrasound evidence of chronic autoimmune thyroiditis. Similarly, the distribution of nodules between the right and left lobes did not differ significantly. Nodules located in the isthmus were slightly more common in the obese group (5.4% vs. 3.7%), although this difference did not reach statistical significance (Table 2). Ultrasonographic features of the biopsied nodules did not differ between groups, with comparable echogenicity and vascularization patterns, although microcalcifications were slightly but significantly more common in non-obese patients (17.0% vs. 11.1%; p = 0.009) (Table 2). Cytological evaluation according to the SIAPEC 2014 classification showed no significant differences in the distribution of TIR categories between obese and non-obese patients. The prevalence of high-risk cytological categories was the same in both groups (9.4%, p = 0.987) (Table 3), suggesting that the presence of obesity may not affect the cytological risk of malignancy in the context of nodular thyroid disease. In the subset of patients with available histology (non-obese: n = 63, 44 [69.8%] with DTC; obese: n = 20, 12 [60.0%] with DTC; p = 0.413), no significant differences were observed between groups, corroborating the cytological findings. Malignancy rates were 100% for TIR 5, 96.3% for TIR 4, and 40.6% for TIR 3B, confirming prior findings in surgical Calabrian cohorts that cytologies ≥ TIR 3B are valid surrogate diagnostic indicators for malignancy in this population [5].
Spearman’s correlation analysis demonstrated a significant negative association between TSH levels and all nodule dimensions (anteroposterior diameter, ρ = −0.112, p < 0.001; transverse diameter, ρ = −0.145, p < 0.001; longitudinal diameter, ρ = −0.104, p < 0.001) as well as volume (ρ = −0.129, p < 0.001), with lower TSH values associated with larger nodules, possibly reflecting a trend toward functional autonomy in larger lesions, a phenomenon typical of formerly iodine-deficient regions, especially after introduction of dietary iodine prophylaxis [32]. Patient age showed a positive correlation with all dimensional parameters (anteroposterior diameter, ρ = 0.149, p < 0.001; transverse diameter, ρ = 0.156, p < 0.001; longitudinal diameter, ρ = 0.134, p < 0.001) and nodule volume (ρ = 0.158, p < 0.001), indicating that nodules tend to increase in size with advancing age. BMI also showed a weak but statistically significant positive correlation with nodule dimensions (anteroposterior diameter, ρ = 0.101, p < 0.001; transverse diameter, ρ = 0.088) and volume (ρ = 0.084, p = 0.004), although the association with longitudinal diameter was not statistically significant (ρ = 0.049, p = 0.099). To further investigate the predictors of cytological malignancy, a multivariate logistic regression model was constructed including age, BMI, TSH, nodule volume, use of levothyroxine therapy, and positivity for anti-TPO antibodies. BMI was not significantly associated with increased malignancy risk (odds ratio: 0.985; p = 0.668). Age, instead, emerged as an independent protective factor, with increasing age associated with reduced malignancy risk (odds ratio: 0.952, 95% CI: 0.927–0.978; p < 0.001). No significant associations were found for TSH (p = 0.798), use of levothyroxine therapy (p = 0.133), or anti-TPO antibodies (p = 0.889). These findings remained unchanged when male sex and the presence of multiple nodules undergoing FNAB were included as covariates, and when the outcome variable was restricted to malignant TIR4 and TIR5 categories (Table 4 and Table S1).
Overall, the study shows that while obesity is associated with increased thyroid nodule size, it does not confer a higher cytological risk of malignancy. Age was the only variable independently correlated with malignancy risk, suggesting that younger patients may warrant more careful clinical surveillance. Excess BMI and its consequent metabolic and hormonal alterations may influence thyroid nodule growth, but they do not appear to significantly impact the risk of cytological malignancy.

4. Discussion

The relationship between obesity and thyroid nodule malignancy has been extensively debated. Several studies suggest that excess adiposity may contribute to thyroid carcinogenesis through mechanisms such as hyperinsulinemia, increased estrogen from peripheral aromatization, chronic low-grade inflammation, and elevated TSH levels, all potentially stimulating follicular cell proliferation [33,34,35,36]. However, epidemiological evidence remains mixed: while some studies report a positive association between BMI and DTC, others do not.
Our findings contribute to this ongoing debate by examining the association between obesity and thyroid nodule characteristics—including size, volume, and cytological malignancy risk—in a large cohort from Calabria, a region historically affected by iodine deficiency. Consistent with previous research, we found that obese patients presented with larger thyroid nodules. BMI was significantly, though weakly, correlated with nodule size and volume, supporting the hypothesis that metabolic and hormonal changes associated with obesity may promote nodule growth via mitogenic pathways involving insulin, IGF-1, or inflammatory mediators. Importantly, while obesity was associated with larger nodules, it did not correlate with increased malignancy risk. High-risk cytological categories (TIR 3B, TIR 4, TIR 5) were similarly distributed between obese and non-obese individuals, and BMI was not a significant predictor of malignancy in multivariate models. These findings align with studies by Rotondi et al. and Ahmadi et al. [15,16], which also found no independent link between BMI and thyroid cancer risk.
Our data also explored the relationship between TSH and nodule size. Consistent with previous reports, obese patients exhibited modestly higher TSH values [37]. Across the cohort as a whole, TSH correlated inversely with all nodule dimensions and volume. In the context of a formerly iodine-deficient region with long-standing prophylaxis, this inverse association likely reflects the emergence of functional autonomy in larger nodules, leading to feedback suppression of TSH [38]. These findings suggest that systemic drivers (e.g., adiposity-related signals) and local thyroidal dynamics (e.g., autonomy) may exert divergent effects on measured TSH levels at the time of FNAB. We also observed an inverse relationship between age and malignancy risk: younger patients were more likely to present with nodules classified as suspicious or malignant. This finding is consistent with the literature indicating that thyroid nodules in younger individuals may display more aggressive features, underscoring the need for age-specific risk assessment [39].
Taken together, our results indicate that BMI should not be used to up- or down-grade malignancy risk in thyroid nodule evaluation. Diagnostic and therapeutic decisions should continue to be guided by ultrasound risk patterns and cytological classification, not by anthropometric measures. The contemporary 2025 ATA guideline does not include BMI as a determinant for FNAB or surgery, and our findings support this position [40]. At the same time, because obese patients tend to harbor larger nodules, they may more often meet size-based thresholds for FNAB or surgery and, by extension, present more frequently with macrocarcinomas rather than microcarcinomas. This remains a testable hypothesis that warrants prospective evaluation, but does not, in itself, justify altering current thresholds based on BMI. Finally, the relatively homogeneous genetic background and environmental exposure in our study population, coupled with consistent iodine intake due to regional prophylactic programs, enhance the internal validity of our findings and may offer insights applicable to other formerly iodine-deficient regions.

Strengths and Limitations

The strengths of this study include the large sample size, the use of a standardized cytological classification (SIAPEC 2014) highly predictive of histological outcomes, especially in TIR 4 and TIR 5 categories, and the consistent FNAB technique and laboratory measurements across all patients. Additionally, anthropometric measurements and cytological sampling were obtained concurrently, ensuring accurate BMI classification at the time of diagnosis. The study’s single-center design helped minimize inter-operator variability in both ultrasound and cytology interpretation [5]. However, the study also has several limitations. First, its retrospective design restricts the ability to infer causality. Second, although cytology generally shows high concordance with final histology, discrepancies may arise, particularly in indeterminate categories such as TIR3B. Importantly, the endocrinologists performing ultrasound assessments and the cytopathologists were aware of patient characteristics (e.g., age, sex, BMI, TSH levels, and clinical indication). Additionally, reflecting real-world clinical practice, the collected dataset contained some missing information. Data on other potentially relevant factors—such as insulin resistance indices, adipokine profiles, and detailed dietary patterns—were also unavailable but could provide further insight into the biological links between obesity and nodular thyroid disease.

5. Conclusions

In conclusion, our findings suggest that while excess body weight may promote nodule growth, it does not appear to increase the likelihood of cytological malignancy. These results reinforce the principle that the diagnostic approach to thyroid nodules should remain guided by ultrasound features and cytological classification, regardless of patient BMI. The identification of younger age as a risk factor for malignancy further underscores the need for heightened clinical vigilance in this subgroup. Future prospective studies incorporating histological follow-up and metabolic profiling are warranted to better elucidate the complex interplay between obesity and thyroid nodular disease.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/endocrines6040050/s1, Table S1: Predictors of malignant cytology (TIR 4 and TIR 5 categories) on thyroid FNAB.

Author Contributions

Conceptualization, M.M.; methodology, S.G.; formal analysis, M.M.; investigation, S.G., G.S., S.I., S.O., E.C. and D.P.F.; data curation, M.M. and A.B.; writing—original draft preparation, S.I. and M.M.; writing—review and editing, D.P.F. and A.B.; project administration, A.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Regione Calabria, Sezione Area Centro, Catanzaro, Italy (protocol code n. 343/2019).

Informed Consent Statement

As the data were analyzed anonymously and the study was observational, the requirement for patient written informed consent was waived.

Data Availability Statement

Data supporting the findings of this study are available from the corresponding authors upon reasonable request, due to ethical and privacy considerations.

Acknowledgments

Part of this work was presented at the 43rd National Congress of the Italian Endocrinology Society (SIE), Turin, Italy, 11–14 June 2025.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Dean, D.S.; Gharib, H. Epidemiology of thyroid nodules. Best Pract. Res. Clin. Endocrinol. Metab. 2008, 22, 901–911. [Google Scholar] [CrossRef] [PubMed]
  2. Guth, S.; Theune, U.; Aberle, J.; Galach, A.; Bamberger, C.M. Very high prevalence of thyroid nodules detected by high frequency (13 MHz) ultrasound examination. Eur. J. Clin. Investig. 2009, 39, 699–706. [Google Scholar] [CrossRef]
  3. Grussendorf, M.; Ruschenburg, I.; Brabant, G. Malignancy rates in thyroid nodules: A long-term cohort study of 17,592 patients. Eur. Thyroid J. 2022, 11, e220027. [Google Scholar] [CrossRef]
  4. Lortet-Tieulent, J.; Franceschi, S.; Dal Maso, L.; Vaccarella, S. Thyroid cancer “epidemic” also occurs in low- and middle-income countries. Int. J. Cancer 2019, 144, 2082–2087. [Google Scholar] [CrossRef]
  5. Giuliano, S.; Mirabelli, M.; Chiefari, E.; Vergine, M.; Gervasi, R.; Brunetti, F.S.; Innaro, N.; Donato, G.; Aversa, A.; Brunetti, A. Malignancy Analyses of Thyroid Nodules in Patients Subjected to Surgery with Cytological- and Ultrasound-Based Risk Stratification Systems. Endocrines 2020, 1, 102–118. [Google Scholar] [CrossRef]
  6. Durante, C.; Costante, G.; Lucisano, G.; Bruno, R.; Meringolo, D.; Paciaroni, A.; Puxeddu, E.; Torlontano, M.; Tumino, S.; Attard, M.; et al. The natural history of benign thyroid nodules. JAMA 2015, 313, 926–935. [Google Scholar] [CrossRef]
  7. Haugen, B.R.; Alexander, E.K.; Bible, K.C.; Doherty, G.M.; Mandel, S.J.; Nikiforov, Y.E.; Pacini, F.; Randolph, G.W.; Sawka, A.M.; Schlumberger, M.; et al. 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer. Thyroid 2016, 26, 1–133. [Google Scholar] [CrossRef]
  8. Pasqual, E.; O’Brien, K.; Rinaldi, S.; Sandler, D.P.; Kitahara, C.M. Obesity, obesity-related metabolic conditions, and risk of thyroid cancer in women: Results from a prospective cohort study (Sister Study). Lancet Reg. Health Am. 2023, 23, 10053. [Google Scholar] [CrossRef] [PubMed]
  9. Kitahara, C.M.; McCullough, M.L.; Franceschi, S.; Rinaldi, S.; Wolk, A.; Neta, G.; Olov Adami, H.; Anderson, K.; Andreotti, G.; Beane Freeman, L.E.; et al. Anthropometric Factors and Thyroid Cancer Risk by Histological Subtype: Pooled Analysis of 22 Prospective Studies. Thyroid 2016, 26, 306–318. [Google Scholar] [CrossRef]
  10. Lauby-Secretan, B.; Scoccianti, C.; Loomis, D.; Grosse, Y.; Bianchini, F.; Straif, K. Body Fatness and Cancer--Viewpoint of the IARC Working Group. N. Engl. J. Med. 2016, 375, 794–798. [Google Scholar] [CrossRef]
  11. Shin, A.; Cho, S.; Jang, D.; Abe, S.K.; Saito, E.; Rahman, M.S.; Islam, M.R.; Sawada, N.; Shu, X.O.; Koh, W.P.; et al. Body Mass Index and Thyroid Cancer Risk: A Pooled Analysis of Half a Million Men and Women in the Asia Cohort Consortium. Thyroid 2022, 32, 306–314. [Google Scholar] [CrossRef]
  12. Laaksonen, M.A.; MacInnis, R.J.; Canfell, K.; Shaw, J.E.; Magliano, D.J.; Banks, E.; Giles, G.G.; Byles, J.E.; Gill, T.K.; Mitchell, P.; et al. Thyroid cancers potentially preventable by reducing overweight and obesity in Australia: A pooled cohort study. Int. J. Cancer 2022, 150, 1281–1290. [Google Scholar] [CrossRef]
  13. Tang, Y.; Yan, T.; Wang, G.; Chen, Y.; Zhu, Y.; Jiang, Z.; Yang, M.; Li, C.; Li, Z.; Yu, P.; et al. Correlation between Insulin Resistance and Thyroid Nodule in Type 2 Diabetes Mellitus. Int. J. Endocrinol. 2017, 2017, 1617458. [Google Scholar] [CrossRef]
  14. Iribarren, C.; Haselkorn, T.; Tekawa, I.S.; Friedman, G.D. Cohort study of thyroid cancer in a San Francisco Bay area population. Int. J. Cancer 2001, 93, 745–750. [Google Scholar] [CrossRef] [PubMed]
  15. Rotondi, M.; Castagna, M.G.; Cappelli, C.; Ciuoli, C.; Coperchini, F.; Chiofalo, F.; Maino, F.; Palmitesta, P.; Chiovato, L.; Pacini, F. Obesity Does Not Modify the Risk of Differentiated Thyroid Cancer in a Cytological Series of Thyroid Nodules. Eur. Thyroid J. 2016, 5, 125–131. [Google Scholar] [CrossRef] [PubMed]
  16. Ahmadi, S.; Pappa, T.; Kang, A.S.; Coleman, A.K.; Landa, I.; Marqusee, E.; Kim, M.; Angell, T.E.; Alexander, E.K. Point of Care Measurement of Body Mass Index and Thyroid Nodule Malignancy Risk Assessment. Front. Endocrinol. 2022, 13, 824226. [Google Scholar] [CrossRef]
  17. Samanic, C.; Chow, W.H.; Gridley, G.; Jarvholm, B.; Fraumeni, J.F., Jr. Relation of body mass index to cancer risk in 362,552 Swedish men. Cancer Causes Control 2006, 17, 901–909. [Google Scholar] [CrossRef] [PubMed]
  18. Rapp, K.; Schroeder, J.; Klenk, J.; Stoehr, S.; Ulmer, H.; Concin, H.; Diem, G.; Oberaigner, W.; Weiland, S.K. Obesity and incidence of cancer: A large cohort study of over 145,000 adults in Austria. Br. J. Cancer 2005, 93, 1062–1067. [Google Scholar] [CrossRef]
  19. Belfiore, A.; La Rosa, G.L.; La Porta, G.A.; Giuffrida, D.; Milazzo, G.; Lupo, L.; Regalbuto, C.; Vigneri, R. Cancer risk in patients with cold thyroid nodules: Relevance of iodine intake, sex, age, and multinodularity. Am. J. Med. 1992, 93, 363–369. [Google Scholar] [CrossRef]
  20. Costante, G.; Grasso, L.; Schifino, E.; Marasco, M.F.; Crocetti, U.; Capula, C.; Chiarella, R.; Ludovico, O.; Nocera, M.; Parlato, G.; et al. Iodine deficiency in Calabria: Characterization of endemic goiter and analysis of different indicators of iodine status region-wide. J. Endocrinol. Investig. 2002, 25, 201–207. [Google Scholar] [CrossRef]
  21. Giordano, C.; Barone, I.; Marsico, S.; Bruno, R.; Bonofiglio, D.; Catalano, S.; Andò, S. Endemic Goiter and Iodine Prophylaxis in Calabria, a Region of Southern Italy: Past and Present. Nutrients 2019, 11, 2428. [Google Scholar] [CrossRef] [PubMed]
  22. Olivieri, A.; Andò, S.; Bagnasco, M.; Meringolo, D.; Mian, C.; Moleti, M.; Puxeddu, E.; Regalbuto, C.; Taccaliti, A.; Tanda, M.L.; et al. The iodine nutritional status in the Italian population: Data from the Italian National Observatory for Monitoring Iodine Prophylaxis (OSNAMI) (period 2015–2019). Am. J. Clin. Nutr. 2019, 110, 1265–1266. [Google Scholar] [CrossRef]
  23. Chiefari, E.; Innaro, N.; Gervasi, R.; Mirabelli, M.; Giuliano, S.; Donnici, A.; Obiso, S.; Brunetti, F.S.; Foti, D.P.; Brunetti, A. Incidental thyroid carcinoma in an endemic goiter area in Italy: Histopathological features and predictors of a common finding. Endocrine 2024, 84, 589–597. [Google Scholar] [CrossRef] [PubMed]
  24. Italian Thyroid Cancer Observatory (ITCO). Thyroid Cancer Monitor—First ITCO Report 2025. Available online: https://issuu.com/raffaelecreativagroupcom/docs/report_itco_agg13-2-2025 (accessed on 10 August 2025).
  25. Nardi, F.; Basolo, F.; Crescenzi, A.; Fadda, G.; Frasoldati, A.; Orlandi, F.; Palombini, L.; Papini, E.; Zini, M.; Pontecorvi, A.; et al. Italian consensus for the classification and reporting of thyroid cytology. J. Endocrinol. Investig. 2014, 37, 593–599. [Google Scholar] [CrossRef]
  26. World Health Organization. Obesity and Overweight. Available online: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight (accessed on 10 August 2025).
  27. Donnici, A.; Mirabelli, M.; Giuliano, S.; Misiti, R.; Tocci, V.; Greco, M.; Aiello, V.; Brunetti, F.S.; Chiefari, E.; Aversa, A.; et al. Coexistence of Hashimoto’s Thyroiditis in Differentiated Thyroid Cancer: Post-Operative Monitoring of Anti-Thyroglobulin Antibodies and Assessment of Treatment Response. Diagnostics 2024, 14, 166. [Google Scholar] [CrossRef] [PubMed]
  28. Tripolino, O.; Mirabelli, M.; Misiti, R.; Torchia, A.; Casella, D.; Dragone, F.; Chiefari, E.; Greco, M.; Brunetti, A.; Foti, D.P. Circulating Autoantibodies in Adults with Hashimoto’s Thyroiditis: New Insights from a Single-Center, Cross-Sectional Study. Diagnostics 2024, 14, 2450. [Google Scholar] [CrossRef]
  29. Baloch, Z.W.; Asa, S.L.; Barletta, J.A.; Ghossein, R.A.; Juhlin, C.C.; Jung, C.K.; LiVolsi, V.A.; Papotti, M.G.; Sobrinho-Simões, M.; Tallini, G.; et al. Overview of the 2022 WHO Classification of Thyroid Neoplasms. Endocr. Pathol. 2022, 33, 27–63. [Google Scholar] [CrossRef]
  30. Gao, L.; Ma, B.; Zhou, L.; Wang, Y.; Yang, S.; Qu, N.; Gao, Y.; Ji, Q. The impact of presence of Hashimoto’s thyroiditis on diagnostic accuracy of ultrasound-guided fine-needle aspiration biopsy in subcentimeter thyroid nodules: A retrospective study from FUSCC. Cancer Med. 2017, 6, 1014–1022. [Google Scholar] [CrossRef]
  31. Donfrancesco, C.; Profumo, E.; Lo Noce, C.; Minutoli, D.; Di Lonardo, A.; Buttari, B.; Vespasiano, F.; Vannucchi, S.; Galletti, F.; Onder, G.; et al. Trends of overweight, obesity and anthropometric measurements among the adult population in Italy: The CUORE Project health examination surveys 1998, 2008, and 2018. PLoS ONE 2022, 17, e0264778. [Google Scholar] [CrossRef]
  32. Giovanella, L.; D’Aurizio, F.; Campenni’, A.; Ruggeri, R.M.; Baldari, S.; Verburg, F.A.; Trimboli, P.; Ceriani, L. Searching for the most effective thyrotropin (TSH) threshold to rule-out autonomously functioning thyroid nodules in iodine deficient regions. Endocrine 2016, 54, 757–761. [Google Scholar] [CrossRef]
  33. Banu, K.S.; Govindarajulu, P.; Aruldhas, M.M. Testosterone and estradiol have specific differential modulatory effect on the proliferation of human thyroid papillary and follicular carcinoma cell lines independent of TSH action. Endocr. Pathol. 2001, 12, 315–327. [Google Scholar] [CrossRef]
  34. Tsatsoulis, A. The Role of Insulin Resistance/Hyperinsulinism on the Rising Trend of Thyroid and Adrenal Nodular Disease in the Current Environment. J. Clin. Med. 2018, 7, 37. [Google Scholar] [CrossRef] [PubMed]
  35. Barrea, L.; Gallo, M.; Ruggeri, R.M.; Giacinto, P.D.; Sesti, F.; Prinzi, N.; Adinolfi, V.; Barucca, V.; Renzelli, V.; Muscogiuri, G.; et al. Nutritional status and follicular-derived thyroid cancer: An update. Crit. Rev. Food Sci. Nutr. 2021, 61, 25–59. [Google Scholar] [CrossRef]
  36. Biondi, B.; Filetti, S.; Schlumberger, M. Thyroid-hormone therapy and thyroid cancer: A reassessment. Nat. Clin. Pract. Endocrinol. Metab. 2005, 1, 32–40. [Google Scholar] [CrossRef]
  37. Biondi, B. Subclinical Hypothyroidism in Patients with Obesity and Metabolic Syndrome: A Narrative Review. Nutrients 2023, 16, 87. [Google Scholar] [CrossRef] [PubMed]
  38. Moretti, F.; Nanni, S.; Pontecorvi, A. Molecular pathogenesis of thyroid nodules and cancer. Baillieres Best Pract. Res. Clin. Endocrinol. Metab. 2000, 14, 517–539. [Google Scholar] [CrossRef] [PubMed]
  39. Leite-Almeida, L.; Silva, R.S.; Vicente-Ferreira, M.; Costa, C.; Estevinho, N.; Castro-Correia, C.; Ferreira, S.; Bom-Sucesso, M. Age-related characteristics in differentiated thyroid cancer: A 20-year single-center retrospective analysis in pediatric and adolescent patients. Arch. Endocrinol. Metab. 2025, 69, e240333. [Google Scholar] [CrossRef]
  40. Ringel, M.D.; Sosa, J.A.; Baloch, Z.; Bischoff, L.; Bloom, G.; Brent, G.A.; Brock, P.L.; Chou, R.; Flavell, R.R.; Goldner, W.; et al. 2025 American Thyroid Association Management Guidelines for Adult Patients with Differentiated Thyroid Cancer. Thyroid 2025, 35, 841–985. [Google Scholar] [CrossRef]
Table 1. Comparison of clinical and biochemical characteristics between non-obese (BMI < 30 kg/m2) and obese patients (BMI ≥ 30 kg/m2) subjected to FNAB for nodular thyroid disease.
Table 1. Comparison of clinical and biochemical characteristics between non-obese (BMI < 30 kg/m2) and obese patients (BMI ≥ 30 kg/m2) subjected to FNAB for nodular thyroid disease.
Patient CharacteristicsNon-Obese (n = 840)Obese (n = 352)p Value
Age, years55.0 (44.0–65.0)57.5 (49.0–65.0)0.021
Female sex, n616 (73.3%)251 (71.3%)0.474
Weight, Kg67 (60–75)89 (80–100)<0.001
Height, m1.64 (1.60–1.70)1.62 (1.56–1.69)<0.001
BMI, Kg/m225.0 (22.9–27.2)33.2 (31.2–36.6)<0.001
Family history of thyroid cancer, n54 (6.4%)22 (6.3%)0.908
Levothyroxine use, n124 (14.8%)60 (17.0%)0.269
TSH, mU/L1.200 (0.795–1.805)1.380 (0.900–2.070)0.007
FT3, pg/mL3.29 (2.96–3.60)3.29 (2.92–3.63)0.980
FT4, ng/mL1.16 (1.00–1.35)1.17 (1.01–1.40)0.395
Positive anti-TPO, n68 (8.1%)88 (25.0%)0.481
Positive anti-Tg, n 19 (2.3%)8 (2.3%)0.871
Data are reported as medians and IQRs, or absolute numbers (n) and valid percentages (%), as appropriate. TSH: thyroid-stimulating hormone; FT3: free triiodothyronine; FT4: free thyroxine; anti-TPO: anti-thyroid peroxidase antibodies; anti-Tg: anti-thyroglobulin antibodies.
Table 2. Ultrasonographic features of the thyroid nodule and surrounding thyroid parenchyma according to patient BMI (non-obese, BMI < 30 kg/m2 vs. obese, BMI ≥ 30 kg/m2).
Table 2. Ultrasonographic features of the thyroid nodule and surrounding thyroid parenchyma according to patient BMI (non-obese, BMI < 30 kg/m2 vs. obese, BMI ≥ 30 kg/m2).
Thyroid Nodule: Ultrasound CharacteristicsNon-Obese (n = 840)Obese (n = 352)p Value
Anteroposterior diameter, mm13.0 (9.6–17.9)14.0 (10.4–19.0)0.007
Transverse diameter, mm)16.5 (12.3–22.7)17.7 (13.0–24.1)0.009
Longitudinal diameter, mm19.4 (14.1–26.2)20.1 (14.8–27.4)0.145
Nodule volume, mm32100 (863–5228)2723 (1010–6523)0.014
Nodule in right lobe, n444 (52.9%)159 (45.2%)0.086
Nodule in left lobe, n357 (42.5%)170 (48.3%)
Isthmic nodule, n31 (3.7%)19 (5.4%)
Uncommon or unknown nodule location *, n8 (0.9%)4 (1.1%)
Microcalcifications, n143 (17.0%)39 (11.1%)0.009
Markedly hypoechoic, n245 (34.9%) 110 (36.1%)0.995
Hypoechoic, n314 (44.7%)134 (43.9%)
Isoechoic, n135 (16.1%)57 (18.7%)
Hyperechoic, n2 (0.3%)1 (0.3%)
Mixed echogenicity, n6 (0.9%)3 (1.0%)
Avascular lesion, n240 (28.6%)120 (34.1%)0.058
Ill-defined or irregular margins, n72 (17.0%)31 (20.5%)0.334
Chronic autoimmune thyroiditis, n89 (10.6%)43 (12.2%)0.702
Data are reported as medians and IQRs, or absolute numbers (n) and valid percentages (%), as appropriate. “*” refers to uncommon nodule locations (within the pyramidal lobe or in ectopic thyroid tissue) or cases with missing information.
Table 3. SIAPEC 2014 cytological category of the thyroid nodule according to patient BMI (non-obese, BMI < 30 kg/m2 vs. obese, BMI ≥ 30 kg/m2).
Table 3. SIAPEC 2014 cytological category of the thyroid nodule according to patient BMI (non-obese, BMI < 30 kg/m2 vs. obese, BMI ≥ 30 kg/m2).
Thyroid Nodule: Cytological CategoryNon-Obese (n = 840)Obese (n = 352)p Value
TIR 1, n90 (10.7%)43 (12.2%)0.453
TIR 2, n568 (67.6%)234 (66.5%)0.701
TIR 3A, n103 (12.3%)42 (11.9%)0.873
TIR 3B, n39 (4.6%)21 (6.0%)0.908
TIR 4, n28 (3.3%)11 (3.1%)0.853
TIR 5, n12 (1.4%)1 (0.3%)0.082
Total high-risk cytological categories (≥TIR 3B) *79 (9.4%)33 (9.4%)0.987
Data are reported as absolute numbers (n) and valid percentages (%). SIAPEC 2014 cytological categories: TIR 1: non-diagnostic; TIR 2: benign; TIR 3A: low-risk indeterminate; TIR 3B: high-risk indeterminate; TIR 4: suspicious for malignancy; TIR 5: malignant. “*” refers to the sum of thyroid nodules classified as TIR 3B, TIR 4 and TIR 5. In patients with multiple thyroid nodules undergoing FNAB (non-obese: n = 50, 6.0%; obese: n = 21, 6.0%), analysis was restricted to the nodule with the highest anticipated cytological risk, according to the SIAPEC 2014 classification.
Table 4. Predictors of high-risk cytology (TIR 3B, TIR 4 and TIR 5) on thyroid FNAB: sex-adjusted logistic regression.
Table 4. Predictors of high-risk cytology (TIR 3B, TIR 4 and TIR 5) on thyroid FNAB: sex-adjusted logistic regression.
Parameter Standardized
Estimate		Odds
Ratio		Lower Bound 95% CIUpper Bound
95%CI		p Value
Age, years−0.6610.9510.9260.977<0.001
TSH, mU/L−0.0290.9800.7561.2700.878
BMI, Kg/m2−0.0670.9880.9221.0580.723
Levothyroxine use0.0692.0990.7505.8770.158
Positive anti-TPO0.7421.1420.4682.7890.771
Nodule volume, mm30.0601.0001.0001.0000.740
Male sex0.5581.7470.7903.8610.168
Multinodularity detected on FNAB was included as an additional covariate in the logistic regression model. Odds ratios with corresponding 95% confidence intervals (CIs) are reported. TSH: thyroid-stimulating hormone; BMI: body mass index; anti-TPO: anti-thyroid peroxidase antibodies.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Giuliano, S.; Seminara, G.; Iuliano, S.; Obiso, S.; Chiefari, E.; Foti, D.P.; Mirabelli, M.; Brunetti, A. Obesity Is Associated with Larger Thyroid Nodules but Not with Malignant Cytology. Endocrines 2025, 6, 50. https://doi.org/10.3390/endocrines6040050

AMA Style

Giuliano S, Seminara G, Iuliano S, Obiso S, Chiefari E, Foti DP, Mirabelli M, Brunetti A. Obesity Is Associated with Larger Thyroid Nodules but Not with Malignant Cytology. Endocrines. 2025; 6(4):50. https://doi.org/10.3390/endocrines6040050

Chicago/Turabian Style

Giuliano, Stefania, Giuseppe Seminara, Stefano Iuliano, Stefania Obiso, Eusebio Chiefari, Daniela P. Foti, Maria Mirabelli, and Antonio Brunetti. 2025. "Obesity Is Associated with Larger Thyroid Nodules but Not with Malignant Cytology" Endocrines 6, no. 4: 50. https://doi.org/10.3390/endocrines6040050

APA Style

Giuliano, S., Seminara, G., Iuliano, S., Obiso, S., Chiefari, E., Foti, D. P., Mirabelli, M., & Brunetti, A. (2025). Obesity Is Associated with Larger Thyroid Nodules but Not with Malignant Cytology. Endocrines, 6(4), 50. https://doi.org/10.3390/endocrines6040050

Article Metrics

Back to TopTop