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. 2025 May 20:16:1590821.
doi: 10.3389/fendo.2025.1590821. eCollection 2025.

The association between metal element levels and thyroid nodules in oilfield workers: a cross-sectional study

Affiliations

The association between metal element levels and thyroid nodules in oilfield workers: a cross-sectional study

Xinyue Wen et al. Front Endocrinol (Lausanne). .

Abstract

Background: Metal elements affect the physiological processes of the thyroid gland and are associated with the formation of thyroid nodules (TNs). This study aimed to investigate the relationship between metal element levels and TNs in oilfield workers and to provide a preliminary scientific basis.

Methods: The study used a cross-sectional study to collect relevant data in 2022. Spearman's rank correlation was used to analyze the correlation between multiple metal elements. The Logistic regression model and Weighted Quantile Sum (WQS) regression model were used to analyze the association between metal elements and the prevalence of TNs.

Results: A total of 517 oilfield workers were included in this study and the prevalence of TNs was 40.62%. Sex, age, and uric acid levels differed between the two groups (P < 0.05). The correlation analysis showed that most of the metals were correlated with each other to varying degrees. The WQS regression model showed that mixed exposure to seven metal elements was positively associated with the risk of developing TNs. In the total population and males, iron (Fe) and copper (Cu) levels were positively related to the risk of TNs prevalence (P < 0.05).

Conclusions: TNs was found to be very prevalent among oilfield workers. Mixed exposure to metal elements may be associated with an elevated risk of TNs, with Fe and Cu emerging as potential contributors to this association.

Keywords: copper; iron; metal elements; oilfield worker; thyroid nodules.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of the inclusion and exclusion.
Figure 2
Figure 2
Heat map of correlation between metal elements. * P < 0.05, ** P < 0.01. The numbers in the figure indicate the magnitude of the correlation coefficient. “✗” indicates that the correlation between the two metals is not significant.
Figure 3
Figure 3
Estimated weights of each metal elements in the WQS regression model. (A) Positive weight distribution graph. (B) Negative weight distribution graph. The dotted line indicated the position of the reference value, and metal elements with estimated weights exceeding the reference value were considered to have a significant effect on the WQS index.

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