Abstract
In the past decade, the incidence of thyroid disorders has been steadily increasing, emerging as a prominent public health concern. Consequently, there is a growing interest in understanding the association between iodine nutritional status and thyroid disorders. We selected 13,487 adults (aged 18–69 years) from the baseline population of Zhejiang Environmental Health Cohort (ZEHC) research. Serum thyroid function indicators, urinary iodine concentration (UIC), and urinary creatinine were measured and an ultrasonography of the thyroid were systematically assessed. Urinary iodine/creatinine ratio (UI/Cr) was calculated to mitigate hydration bias. The median of UIC and UI/Cr were 158.2 (IQR: 97.0–250.5) µg/L and 113.4 (IQR: 69.5–178.4) µg/g, respectively. Excessive iodine intake (UIC ≥ 300 µg/L) increased the risk of subclinical hypothyroidism (adjusted OR 1.451, 95% CI 1.252–1.681), while insufficient iodine intake (UIC < 100 µg/L) reduced this risk (adjusted OR 0.831, 95% CI 0.716–0.965). Conversely, insufficient iodine intake (UIC < 100 µg/L) was associated with elevated thyroid nodule incidence (adjusted OR 1.196, 95% CI 1.099–1.301). After creatinine adjustment, the risk of subclinical hypothyroidism was higher in high (quartile 4) UI/Cr level (adjusted OR 1.520, 95% CI 1.334–1.732), and participants with low (quartile 1) UI/Cr level exhibit a lower risk of subclinical hypothyroidism (adjusted OR 0.624, 95% CI 0.523–0.744). Participants with low (quartile 1) UI/Cr level had a significant increase in the incidence of thyroid nodule (adjusted OR 1.315, 95% CI 1.203–1.437). This large-scale population-based study found that higher iodine level was associated with an increased risk of subclinical hypothyroidism, while lower iodine level was associated with an increased incidence of thyroid nodules.
Supplementary Information
The online version contains supplementary material available at 10.1038/s41598-025-97734-5.
Keywords: Thyroid disorders, Urinary iodine, Creatinine adjustment
Subject terms: Thyroid diseases, Biochemistry, Risk factors
Introduction
Iodine is an essential trace element for the human body and serves as a crucial precursor for the synthesis of thyroid hormones. Insufficient or excessive iodine intake can lead to disruptions in thyroid hormone levels, thereby contributing to the occurrence of thyroid disorders. Severe iodine deficiency can result in goiter and hypothyroidism1–3, while iodine excess increases the risk of hyperthyroidism, hypothyroidism, thyroid nodules, goiter, and autoimmune thyroiditis4–6.
China was previously significantly affected by iodine deficiency diseases (IDD). Since 1995, the country has implemented the universal salt iodization (USI) strategy to address iodine deficiency disorders effectively. However, the incidence of thyroid disorders has been steadily increasing with the implementation of USI7–9, causing the public to raise doubts about the consumption of iodized salt. Monitoring data from Zhejiang Province over the years show that the iodine content in drinking water for residents is < 10 µg/L10. According to the national criteria for the classification of iodine deficiency disease areas, it is classified as an environmentally iodine-deficient area11. According to the 2021 nationwide iodine nutrition survey in China12, the iodized salt coverage rate in Zhejiang province is only 64.24%, significantly below the national standard of > 90% and representing the lowest coverage level nationally. If the public continues to lose confidence in iodized salt, which may eventually result in the re-emerging of IDD13. Therefore, exploring the association between urinary iodine levels and thyroid disorder in this region has become an urgent concern for the public.
Presently, urinary iodine concentration (UIC) is the most commonly employed index for assessing population iodine nutritional status14. Nevertheless, an increasing number of studies have highlighted its limitations15–19, its reliability is susceptible to variations in water intake and diet, reflecting the individual’s hydration status at the time of collection. To mitigate the dependence of urine concentration measurements on hydration status, many studies opt for 24-hour urine samples and creatinine adjustment as alternatives to a spot urine samples20,21. While 24-h urine samples are considered the gold standard for evaluating iodine nutritional status, their feasibility is limited in large-scale population studies due to resource constraints, cumbersome sample collection, and issues related to participant compliance. Creatinine is widely utilized for biomarker correction since it is excreted at a relatively constant rate within 24 h following glomerular filtration, effectively correcting for the impact of urine volume on urinary iodine concentration22. Some studies have suggested that using the urinary iodine/creatinine ratio (UI/Cr) can control for the influence of varying urine volumes on UIC itself23. Consequently, an increasing number of studies are adopting UI/Cr for assessing iodine nutritional status24–26. Therefore, given the controversy surrounding the different indicators, we used both UIC and UI/Cr as indicators for the assessment of iodine nutrition to observe whether differences existed between them.
Therefore, this study based on a large-scale population-based study conducted by our team, aims to provide a comprehensive understanding of the association between urinary iodine levels (UIC and UI/Cr) and thyroid disorders among adults in Zhejiang Province.
Materials and methods
Study population
The study population was selected from adults in the baseline population of Zhejiang Environmental Health Cohort (ZEHC), an ongoing cohort designed by our team to examine the associations between environment and health in Zhejiang Province, China. Between March 2022 to August 2023, we recruited 17,669 participants from four representative cities in Zhejiang: Huzhou, Jinhua, Taizhou, and Lishui, based on geographic location and economic conditions. Participants were recruited through a stratified multistage random sampling strategy to ensure representativeness of Zhejiang’s adult population. The recruit strategy of study participants was performed as follows: (1) 3–5 subdistricts or towns were randomly chosen per city; (2) 5 communities or villages (east, west, south, north, central) were selected per subdistrict or town; and (3) 100–300 individuals were enrolled per community or village based on the population composition of 2010 census data27. Inclusion criteria for ZEHC: (1) local resident population aged 6–69 years; (2) participants with no newly detected or being treated for tumors; (3) participants with no mental illness or cognitive impairment; and (4) participants who had not received any iodine-containing drugs or contrast agents in the previous three months. For our study, we only focused on adults (age ≥ 18), so minors (age < 18) were excluded (n = 3521). Additionally, those without thyroid function data (n = 149), urine data (e.g., pregnant women, menstruation women, no urine samples, n = 125), questionnaire (n = 81), medical examination (n = 101), and using thyroid interfering medication (n = 5) were also excluded. Finally, 13,487 adults (age ≥ 18) were included in the analysis. Participant survey flowchart is shown in Fig. 1.
Fig. 1.
Flowchart for the selection of the study population.
All participants signed the informed consent at the baseline enrollment. The ZEHC was approved by Zhejiang Provincial Center for Disease Control and Prevention (2020-040-01).
Data collection
All participants underwent standardized questionnaires and medical examination by professional technicians, who had been trained and evaluated. The medical examination included anthropometric measurements, routine examinations, and imaging tests. Of these, thyroid ultrasound was performed using a MicroMaxx portable color doppler ultrasound diagnostic instrument (FUJIFILM SonoSite, Inc., Washington, USA), with a transducer probe frequency of 7.5 MHz. Thyroid nodule is diagnosed by registered doctors holding ultrasonography professional certificates issued by the Ministry of Health of China through thyroid ultrasonography.
At the day for medical examination, fasting blood and morning urine samples were collected at the local health clinic. Serum samples was gained via centrifugation within 2 h of collection for thyroid function detection. To avoid iodine contamination during blood collection, alcohol disinfection was used instead of iodophor disinfection. Urine samples were collected in sterile urine cups for UIC and urinary creatinine detection. Following the completion of the survey and specimen collection, all samples were transported on the same day via a cold chain system to the central laboratory in Hangzhou, China, for immediate centralized testing.
Laboratory measurements
Serum thyroid stimulating hormone (TSH), free triiodothyronine (FT3), total triiodothyronine (TT3), free thyroxine (FT4), total thyroxine (TT4), thyroglobulin (Tg), thyroglobulin antibody (TgAb), and thyroid peroxidase antibody (TPOAb) were measured using electrochemiluminescence immunoassays with a Cobas e601 analyzer (Roche Diagnostics GmbH, Mannheim, Germany), in combination with the appropriate calibration materials, reagents, and quality controls. Quality control procedure was carried out in accordance with the manufacturer’s instructions before, during, and after the testing. The coefficient of variation (CV) of control samples (PreciControl Universal & PreciControl ThyroAB, Roche, Germany) was as follows: TSH 2.75–5.57%, FT3 3.44–5.26%, TT3 3.55–5.03%, FT4 2.26–4.23%, TT4 4.50–5.17%, Tg 3.01–4.27%, TgAb 3.83–6.63%, and TPOAb 5.41–8.33%. Thyroid dysfunctions included overt hyperthyroidism, subclinical hyperthyroidism, overt hypothyroidism, subclinical hypothyroidism, TgAb positive, TPOAb positive, and positive thyroid antibodies. Detailed diagnostic criteria were provided in Table 1.
Table 1.
Diagnostic criteria for thyroid dysfunctions.
| No. | Thyroid dysfunctions | Diagnostic criteria* |
|---|---|---|
| 1 | Overt hypothyroidism | TSH > 4.2 mIU/L and FT4 < 12 pmol/L |
| 2 | Subclinical hypothyroidism | TSH > 4.2 mIU/L and FT4 within the normal reference range |
| 3 | Overt hyperthyroidism | TSH < 0.27 mIU/L, FT4 > 22 pmol/L and/or FT3 > 6.8 pmol/L |
| 4 | Subclinical hyperthyroidism | TSH < 0.27 mIU/L, FT4 and FT3 within the normal reference range |
| 5 | Positive TPOAb | TPOAb ≥ 34 IU/ml |
| 6 | Positive TgAb | TgAb ≥ 115 IU/ml |
| 7 | Positive thyroid antibodies | TPOAb ≥ 34 IU/ml or TgAb ≥ 115 IU/ml |
*The normal reference values were based on the Roche’s reference intervals as follows: TSH 0.27–4.2 µIU/mL, FT3 3.1–6.8 pmol/L, FT4 12–22 pmol/L, TgAb < 115 IU/mL, and TPOAb < 34 IU/mL. Abbreviations: TSH, thyroid stimulating hormone; FT3, free triiodothyronine; FT4, free thyroxine; TgAb, thyroglobulin antibody; TPOAb, thyroid peroxidase antibody.
UIC was measured using inductively coupled plasma - mass spectrometry (ICP-MS; ICAPR02041, Thermo Fisher Scientific, Bremen, GmbH). CV of quality control samples (Standard lyophilized human serum reference material, Trace Elements Urine L-1 RUO, Seronorm, Norway) was 3.17–4.24%. Urinary creatinine was determined by the creatine oxidase method using a Beckman AU480 fully automated biochemistry (Beckman Instruments, Brea, CA). CV of quality control samples (Assayed urine chemistry control, AU2353, Randox Laboratories, Crumlin, UK) was 1.58–2.26%.
According to the United Nations Children’s Fund (UNICEF)28, UIC < 100 µg/L is insufficient iodine intake, UIC 100–299 µg/L is adequate iodine intake, and UIC > 300 µg/L is excessive iodine intake.
Covariates
Demographic characteristic, lifestyle characteristics, and medication and disease history status were collected with questionnaires by trained interviewers. The demographic characteristics included age (years), gender (male or female), ethnicity (Han Chinese or others), and educational attainment (primary school or below, junior or senior high school, university or higher). The lifestyle characteristics, such as cigarette smoking (current, former and never), alcohol consumption (current, former and never) and salt utilization (iodized, non-iodized and both) habits were investigated. Height and weight were measured. Anthropometric measurements, such as height and weight, were collected by trained health technicians. Body mass index (BMI) was calculated as weight (kg) divided by height squared (m2).
Statistical analyses
R Statistical Computing Software version 4.3.0 (R Foundation for Statistical Computing, Vienna, Austria) were used for data processing and statistical analyses. The Kolmogorov–Smirnov method was used to test continuous variable distribution normality. Normally distributed data are expressed as the mean ± standard deviation (SD), and non-normally distributed data are expressed as the median with the interquartile range (IQR: 25th–75th percentiles).
We tested the associations among UIC, UI/Cr and thyroid function indicators using Spearman correlation, and calculated the correlation coefficients (r). Further, non-linear relationships were explored using restricted cubic spline (RCS) with three knots (25th, 50th and 75th percentiles of UIC and UI/Cr levels). UIC, UI/Cr, TSH, FT3, TT3, FT4, TT4, and Tg were log transformed. UIC was stratified according to WHO criteria for assessing iodine status in the general population, while UI/Cr was stratified based on quartiles. Thyroid indicators were compared using the Kruskal-Wallis analysis for group comparisons, and the prevalence of thyroid disorders were performed using the chi-square (χ2) test or Fisher’s exact test in groups. Logistic and Poisson regression analyses were used to explore the effect of iodine status on thyroid disorders, using the iodine-appropriate group as a reference. The results were expressed with odds ratios (ORs) and 95% confidence intervals (CIs). The adjustment included in the model were age, gender, BMI, ethnicity, educational attainment, cigarette smoking, alcohol consumption and salt utilization. All tests were two-tailed cutoffs, and significance was set at a 0.05 level (p < 0.05).
Results
Study population characteristics
Descriptive characteristics of 13,487 participants in this study were shown in Table 2. The mean ± SD of participants’ age and BMI were 52.4 ± 12.7 years and 23.9 ± 3.3 kg/m2, respectively. The majority (98.8%) of the participants were Han Chinese, 60.7% were females, and 47.5% had junior or senior high school. In addition, in term of lifestyle habits, 15.1% of participants reported current smoking, 20.2% reported current alcohol consumption, and 49.7% reported using iodized salt. The median (IQR) of UIC and UI/Cr were 158.2 (97.0–250.5) µg/L and 113.4 (69.5–178.4) µg/g.
Table 2.
Descriptive characteristics of the study population (n = 13487 adults).
| Characteristic | Values |
|---|---|
| Age, years, mean ± SD | 52.4 ± 12.7 |
| BMI, kg/m2, mean ± SD | 23.9 ± 3.3 |
| Gender, n (%) | |
| Male | 5294 (39.3) |
| Female | 8193 (60.7) |
| Ethnicity, n (%) | |
| Han Chinese | 13,330 (98.8) |
| Others | 157 (1.2) |
| Educational attainment, n (%) | |
| Primary school or below | 5549 (41.1) |
| Junior or senior high school | 6404 (47.5) |
| University or higher | 1534 (11.4) |
| Cigarette smoking, n (%) | |
| Current | 2032 (15.1) |
| Former | 346 (2.6) |
| Never | 11,109 (82.4) |
| Alcohol consumption, n (%) | |
| Current | 2724 (20.2) |
| Former | 125 (0.9) |
| Never | 10,638 (78.9) |
| Salt utilization, n (%) | |
| Iodized | 6698 (49.7) |
| Non-iodized | 1477 (11.0) |
| Both | 5312 (39.4) |
| TSH, µIU/mL, median (IQR) | 2.0 (1.4, 2.9) |
| FT3, pmol/L, median (IQR) | 5.0 (4.6, 5.5) |
| TT3, nmol/L, median (IQR) | 1.9 (1.7, 2.2) |
| FT4, pmol/L, median (IQR) | 16.9 (15.3, 18.5) |
| TT4, nmol/L, median (IQR) | 110.8 (97.8, 125.1) |
| Tg, ng/mL, median (IQR) | 10.3 (5.5, 17.7) |
| UIC, µg/L, median (IQR) | 158.2 (97.0, 250.5) |
| UI/Cr, µg/g, median (IQR) | 113.4 (69.5, 178.4) |
SD, standard deviation; BMI, body mass index; IQR, interquartile range; TSH, thyroid stimulating hormone; FT3, free triiodothyronine; TT3, total triiodothyronine; FT4, free thyroxine; TT4, total thyroxine; Tg, thyroglobulin; UIC, urinary iodine concentration; UI/Cr, urinary iodine/ creatinine ratio.
Correlation of UIC and UI/Cr with thyroid function indicators
Spearman correlation analysis revealed negligible monotonic correlation (|r| < 0.2 for all) between UIC and thyroid function indicators, similar results were found between UI/Cr and thyroid function indicators (Supplementary Table 1). Therefore, we further utilized RCS to assess potential non-linear correlation associations of UIC and UI/Cr with thyroid function indicators (Fig. 2). In detail, UIC with FT3, TT3, Tg exhibited negative non-linear associations and UI/Cr with FT3, TT3 observed negative non-linear associations. The positive non-linear associations of UIC with FT4, and UI/Cr with TSH. U-shaped trends of UI/Cr with Tg, and UIC with TSH were observed. In contrast, inverted U-shaped trends of UI/Cr with FT4, TT4 were observed. Subsequently, the UIC and UI/Cr were further stratified, and the distributions of median concentrations for thyroid function indicators were observed (Table 3). FT3, TT3, FT4, TSH and Tg showed statistically significant differences across different UIC and UI/Cr levels (p ≤ 0.001), while TT4 did not (UIC: p = 0.097, UI/Cr: p = 0.980).
Fig. 2.
Associations of UIC and UI/Cr with thyroid function indicators. Analyses were performed by restricted cubic spline. UIC, UI/Cr, TSH, FT3, TT3, FT4, TT4, and Tg were log transformed. TSH, thyroid stimulating hormone; FT3, free triiodothyronine; TT3, total triiodothyronine; FT4, free thyroxine; TT4, total thyroxine; Tg, thyroglobulin; UIC, urinary iodine concentration; UI/Cr, urinary iodine/ creatinine ratio.
Table 3.
Distribution of thyroid function indexes in different UIC and UI/Cr levels.
| N | FT3 | TT3 | FT4 | TT4 | TSH | Tg | |
|---|---|---|---|---|---|---|---|
| UIC (µg/L) | |||||||
| < 100 | 3481 | 5.02 (4.56, 5.65) | 1.95 (1.73, 2.23) | 16.71 (15.13, 18.40) | 111.60 (98.40, 125.25) | 2.01 (1.41, 2.85) | 12.90 (6.84, 22.00) |
| 100–299 | 7712 | 4.98 (4.56, 5.47) | 1.90 (1.70, 2.13) | 16.90 (15.36, 18.58) | 110.60 (97.72, 125.00) | 2.01 (1.37, 2.91) | 9.78 (5.22, 16.73) |
| ≥ 300 | 2294 | 4.96 (4.54, 5.39) | 1.88 (1.69, 2.10) | 16.97 (15.46, 18.52) | 110.30 (96.93, 125.30) | 2.17 (1.48, 3.17) | 8.76 (4.72, 14.52) |
| p | 0.032 | 0.000 | 0.002 | 0.086 | 0.000 | 0.000 | |
| UI/Cr (µg/g) | |||||||
| < 69.5 (Quartile 1) | 3370 | 5.03 (4.58, 5.63) | 1.94 (1.74, 2.20) | 16.61 (15.04, 18.33) | 110.80 (97.88, 124.00) | 1.86 (1.32, 2.62) | 13.65 (7.29, 22.81) |
| 69.5-113.4 (Quartile 2) | 3376 | 5.03 (4.57, 5.52) | 1.91 (1.70, 2.14) | 17.03 (15.38, 18.72) | 110.70 (97.36, 125.00) | 1.95 (1.36, 2.81) | 10.37 (5.70, 17.40) |
| 113.4-178.4 (Quartile 3) | 3373 | 5.00 (4.57, 5.52) | 1.91 (1.70, 2.15) | 17.00 (15.50, 18.68) | 110.90 (97.71, 125.50) | 2.11 (1.44, 3.02) | 9.06 (4.72, 15.62) |
| > 178.4 (Quartile 4) | 3368 | 4.91 (4.50, 5.34) | 1.88 (1.68, 2.11) | 16.84 (15.36, 18.36) | 110.90 (98.13, 126.20) | 2.23 (1.51, 3.31) | 8.80 (4.56, 15.06) |
| p | 0.000 | 0.000 | 0.000 | 0.980 | 0.000 | 0.000 | |
Thyroid function indexes are expressed as median (interquartile range).
TSH, thyroid stimulating hormone; FT3, free triiodothyronine; TT3, total triiodothyronine; FT4, free thyroxine; TT4, total thyroxine; Tg, thyroglobulin; UIC, urinary iodine concentration; UI/Cr, urinary iodine/ creatinine ratio.
Associations between urinary iodine levels and thyroid disorders prevalence
Tables 4 and 5 show the prevalence of thyroid disorders across different UIC and UI/Cr levels. The prevalence of subclinical hypothyroidism exhibited an increasing trend as UIC and UI/Cr levels increased (UIC: χ2 = 40.470, p < 0.001; UI/Cr: χ2 = 161.513, p < 0.001). The prevalence of thyroid nodules differed significantly across subgroups with different UIC and UI/Cr levels (UIC: χ2 = 95.932, p < 0.001; UI/Cr: χ2 = 92.436, p < 0.001), with the highest prevalence observed at low iodine levels (55.6% for UIC < 100 µg/L; 55.5% for UI/Cr < 69.5 µg/g). In addition, subclinical hyperthyroidism showed significant variation among UIC levels (χ2 = 6.463, p = 0.039), with the lowest prevalence at UIC < 100 µg/g level (0.3%). Overt hyperthyroidism showed significant variation among UI/Cr levels (χ2 = 8.280, p = 0.041), with the highest prevalence at UI/Cr > 178.4 µg/g level (1.0%).
Table 4.
Prevalence of thyroid disorders in different UIC levels.
| Thyroid disorders | Total | UIC (µg/L) | |||||
|---|---|---|---|---|---|---|---|
| < 100 | 100–299 | ≥ 300 | χ2 | p-Value | |||
| N | 13,487 | 3481 | 7712 | 2294 | |||
| Overt hypothyroidism, n (%) | 78 (0.6) | 28 (0.8) | 37 (0.5) | 13 (0.6) | 4.401 | 0.111 | |
| Subclinical hypothyroidism, n (%) | 1254 (9.3) | 272 (7.8) | 692 (9.0) | 290 (12.6) | 40.470 | 0.000 | |
| Overt hyperthyroidism, n (%) | 84 (0.6) | 16 (0.5) | 49 (0.6) | 19 (0.8) | 3.081 | 0.214 | |
| Subclinical hyperthyroidism, n (%) | 69 (0.5) | 9 (0.3) | 44 (0.6) | 16 (0.7) | 6.463 | 0.039 | |
| Positive thyroid antibodies, n (%) | 1965 (14.6) | 535 (15.4) | 1117 (14.55) | 313 (13.6) | 3.411 | 0.182 | |
| Positive TPOAb, n (%) | 1392 (10.3) | 399 (11.5) | 773 (10.0) | 220 (9.6) | 6.960 | 0.031 | |
| Positive TgAb, n (%) | 1288 (9.5) | 339 (9.7) | 738 (9.6) | 211 (9.2) | 0.476 | 0.788 | |
| Thyroid nodule, n (%) | 6559 (48.6) | 1937 (55.6) | 3602 (46.7) | 1020 (44.5) | 95.932 | 0.000 | |
Categorical variables using chi-square test, χ2 for test statistic.
UIC, urinary iodine concentration; TgAb, thyroglobulin antibody; TPOAb, thyroid peroxidase antibody.
Significant values are in bold.
Table 5.
Prevalence of thyroid disorders in different UI/Cr levels.
| Thyroid disorders | Total | UI/Cr (µg/g) | |||||
|---|---|---|---|---|---|---|---|
| < 69.5 (Quartile 1) | 69.5-113.4 (Quartile 2) | 113.4-178.4 (Quartile 3) | > 178.4 (Quartile 4) | χ2 | p-Value | ||
| N | 13,487 | 3370 | 3376 | 3373 | 3368 | ||
| Overt hypothyroidism, n (%) | 78 (0.6) | 24 (0.7%) | 16 (0.5%) | 19 (0.6%) | 19 (0.6%) | 1.715 | 0.634 |
| Subclinical hypothyroidism, n (%) | 1254 (9.3) | 182 (5.4%) | 263 (7.8%) | 336 (10.0%) | 473 (14.0%) | 161.513 | 0.000 |
| Overt hyperthyroidism, n (%) | 84 (0.6) | 16 (0.5%) | 16 (0.5%) | 20 (0.6%) | 32 (1.0%) | 8.280 | 0.041 |
| Subclinical hyperthyroidism, n (%) | 69 (0.5) | 11 (0.3%) | 20 (0.6%) | 13 (0.4%) | 25 (0.7%) | 7.280 | 0.063 |
| Positive thyroid antibodies, n (%) | 1965 (14.6) | 477 (14.2%) | 478 (14.2%) | 475 (14.1%) | 535 (15.9%) | 6.248 | 0.100 |
| Positive TPOAb, n (%) | 1392 (10.3) | 355 (10.5%) | 341 (10.1%) | 323 (9.6%) | 373 (11.1%) | 4.432 | 0.218 |
| Positive TgAb, n (%) | 1288 (9.5) | 314 (9.3%) | 314 (9.3%) | 299 (8.9%) | 361 (10.7%) | 7.612 | 0.055 |
| Thyroid nodule, n (%) | 6559 (48.6) | 1872 (55.5%) | 1599 (47.4%) | 1503 (44.6%) | 1585 (47.1%) | 92.436 | 0.000 |
Categorical variables using chi-square test, χ2 for test statistic.
UI/Cr, urinary iodine/ creatinine ratio; TgAb, thyroglobulin antibody; TPOAb, thyroid peroxidase antibody.
Significant values are in bold.
Since the prevalence of overt hypothyroidism, overt hyperthyroidism, and subclinical hyperthyroidism was < 1%, Poisson regression was used to explore the association of thyroid disorders with different UIC and UI/Cr levels. The results are shown in Supplementary Table 2, only participants with UIC < 100 µg/L was inversely associated with subclinical hyperthyroidism (adjusted OR = 0.395, 95% CI = 0.192–0.813). In addition, other thyroid disorders were observed by binary logistic regression analysis (Table 6). At different levels of UIC, participants with high UIC level (≥ 300 µg/L) were at a higher risk of subclinical hypothyroidism (adjusted OR = 1.451, 95% CI = 1.252–1.681), whereas the risk was decreased in the UIC < 100 µg/L level (adjusted OR = 0.831, 95% CI = 0.716–0.965). Increased risk of thyroid nodule was observed in the UIC < 100 µg/L level (adjusted OR = 1.196, 95% CI = 1.099–1.301). In the unadjusted model, participants with low UIC level (< 100 µg/L) were at a higher risk of positive TPOAb (unadjusted OR = 1.162, 95% CI = 1.022–1.321), but after adjusting for other factors, the correlation was non-significant (p > 0.05).All these results were compared with the UIC 100–299 µg/L level.
Table 6.
Logistic regression exploring the effect of UIC levels on thyroid disorders.
| Thyroid disorder | UIC (µg/L) | |||||
|---|---|---|---|---|---|---|
| < 100 | 100–299 | ≥ 300 | ||||
| OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | |
| Subclinical hypothyroidism | ||||||
| Unadjusted model | 0.860 (0.743–0.995) | 0.043 | 1(reference) | 1.468 (1.269–1.698) | 0.000 | |
| Adjusted modela | 0.831 (0.716–0.965) | 0.015 | 1(reference) | 1.451 (1.252–1.681) | 0.000 | |
| Thyroid nodule | ||||||
| Unadjusted model | 1.431 (1.321–1.551) | 0.000 | 1(reference) | 0.914 (0.832–1.003) | 0.059 | |
| Adjusted modela | 1.196 (1.099–1.301) | 0.000 | 1(reference) | 0.965 (0.875–1.064) | 0.472 | |
| Positive thyroid antibodies | ||||||
| Unadjusted model | 1.072 (0.959–1.199) | 0.222 | 1(reference) | 0.933 (0.815–1.068) | 0.313 | |
| Adjusted modela | 0.969 (0.864–1.088) | 0.595 | 1(reference) | 0.961 (0.837–1.102) | 0.566 | |
| Positive TPOAb | ||||||
| Unadjusted model | 1.162 (1.022–1.321) | 0.021 | 1(reference) | 0.952 (0.813–1.115) | 0.542 | |
| Adjusted modela | 1.058 (0.928–1.207) | 0.398 | 1(reference) | 0.985 (0.840–1.155) | 0.851 | |
| Positive TgAb | ||||||
| Unadjusted model | 1.020 (0.891–1.167) | 0.779 | 1(reference) | 0.957 (0.815–1.124) | 0.594 | |
| Adjusted modela | 0.936 (0.814–1.076) | 0.349 | 1(reference) | 0.976 (0.829–1.149) | 0.772 | |
BMI, body mass index; UIC, urinary iodine concentration; TgAb, thyroglobulin antibody; TPOAb, thyroid peroxidase antibody.
aMultivariable models are adjusted for age, gender, BMI, ethnicity, educational attainment, cigarette smoking, alcohol consumption and salt utilization.
Significant values are in bold.
Meanwhile, we analyzed the risk of thyroid disorders based on UI/Cr levels categorization (Table 7). Compared with moderate (quartile 2 + 3) UI/Cr levels, participants with high (quartile 4) UI/Cr level were at increased risk for subclinical hypothyroidism (adjusted OR = 1.520, 95% CI = 1.334–1.732), whereas participants with low (quartile 1) UI/Cr level was inversely associated with subclinical hyperthyroidism (adjusted OR = 0.624, 95% CI = 0.523–0.744). Participants with low (quartile 1) UI/Cr level were at a higher risk of thyroid nodule (adjusted OR = 1.315, 95% CI = 1.203–1.437). In the unadjusted model, participants with low UI/Cr level (quartile 1) were at a higher risk of positive thyroid antibodies (unadjusted OR = 1.149, 95% CI = 1.024–1.289) and positive TgAb (unadjusted OR = 1.202, 95% CI = 1.048–1.378), but after adjusting for other factors, the correlation was non-significant (p > 0.05).
Table 7.
Logistic regression exploring the effect of UI/Cr levels on thyroid disorders.
| Thyroid disorder | UI/Cr (µg/g) | |||||
|---|---|---|---|---|---|---|
| < 69.5 (Quartile 1) | 69.5-178.4 (Quartile 2 + Quartile 3 ) | > 178.4 (Quartile 4 ) | ||||
| OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | |
| Subclinical hypothyroidism | ||||||
| Unadjusted model | 0.586 (0.494–0.696) | 0.000 | 1(reference) | 1.677 (1.475–1.907) | 0.000 | |
| Adjusted modela | 0.624 (0.523–0.744) | 0.000 | 1(reference) | 1.520 (1.334–1.732) | 0.000 | |
| Thyroid nodule | ||||||
| Unadjusted model | 1.469 (1.352–1.597) | 0.000 | 1(reference) | 1.045 (0.962–1.135) | 0.297 | |
| Adjusted modela | 1.315 (1.203–1.437) | 0.000 | 1(reference) | 0.927 (0.850–1.012) | 0.089 | |
| Positive thyroid antibodies | ||||||
| Unadjusted model | 1.003 (0.891–1.129) | 0.963 | 1(reference) | 1.149 (1.024–1.289) | 0.018 | |
| Adjusted modela | 1.032 (0.912–1.169) | 0.617 | 1(reference) | 1.043 (0.927–1.174) | 0.480 | |
| Positive TPOAb | ||||||
| Unadjusted model | 1.079 (0.942–1.236) | 0.273 | 1(reference) | 1.141 (0.998–1.305) | 0.053 | |
| Adjusted modela | 1.092 (0.948–1.258) | 0.222 | 1(reference) | 1.065 (0.929–1.221) | 0.367 | |
| Positive TgAb | ||||||
| Unadjusted model | 1.028 (0.892–1.186) | 0.700 | 1(reference) | 1.202 (1.048–1.378) | 0.009 | |
| Adjusted modela | 1.116 (0.961–1.296) | 0.149 | 1(reference) | 1.062 (0.923–1.222) | 0.398 | |
BMI, body mass index; UI/Cr, urinary iodine/creatinine ratio; TgAb, thyroglobulin antibody; TPOAb, thyroid peroxidase antibody.
aMultivariable models are adjusted for age, gender, BMI, ethnicity, educational attainment, cigarette smoking, alcohol consumption and salt utilization.
Significant values are in bold.
Discussion
This study represents, to the best of our knowledge, the largest population-based investigation conducted in the Zhejiang province of China thus far, aiming to elucidate the association between urinary iodine levels and thyroid disorders. The study reveals a significant correlation between UIC, UI/Cr, and thyroid function indicators, with some differences in the detailed correlations. However, in evaluating the association between urinary iodine levels and thyroid disorders, the conclusions drawn from these two indicators are generally consistent. In particular, high iodine levels were identified as a risk factor for subclinical hypothyroidism and low iodine levels as a risk factor for thyroid nodules.
Our investigation discloses that the UIC level among adults in Zhejiang province is 158.2 (IQR 97.0-250.5) µg/L, and the UI/Cr level is 113.4 (IQR 69.5-178.4) µg/g, both falling within the WHO-recommended optimal iodine nutritional range. This indicates that adults in Zhejiang province maintain adequate iodine nutritional status, consistent with our prior research findings29, further confirming the effectiveness of the USI strategy. According to the 2021 nationwide iodine nutrition survey in China12, our results were similar to those of residents in coastal areas nationwide (163.3 µg/L, IQR 105.97–248.29 µg/L) and lower than those in inland regions nationwide (189.0 µg/L, IQR 128.10–275.80 µg/L). Despite our study indicating that adults in Zhejiang province maintain sufficient iodine nutritional status, ongoing issues such as environmental iodine deficiency and low iodized salt coverage persist, necessitating continuous monitoring and optimization of iodine nutritional status in the region.
We observe statistically significant differences in the distribution of FT3, TT3, FT4, TSH, and Tg among different groups defined by UIC and UI/Cr. Furthermore, our research reveals a non-linear correlation between UIC, UI/Cr, and thyroid function indicators, with subtle differences in their specific correlations. Our findings are consistent with the thyroid adaptation mechanisms proposed by Glinoer30,31. Under moderate to severe iodine deficiency, the thyroid prioritizes T3 synthesis over T4 to optimize limited iodine utilization, a mechanism that explains the negative non-linear associations of both UIC and UI/Cr with FT3 and TT3. T3 is an important indicator for diagnosing thyroid dysfunction, particularly in hyperthyroidism. In hyperthyroid states, serum T3 levels provide a more sensitive indicator of thyroid function than T4 32. This implies that changes in T3 levels may exhibit greater clinical significance than T4 when assessing thyroid function in hyperthyroid patients, particularly during or following radioactive iodine therapy or anti-thyroid medication treatment. Concurrently, both prolonged insufficient iodine intake (leading to moderate to severe iodine deficiency) and excessive iodine intake (that predisposed to diminished T3 and T4 production from the thyroid gland) reduce T4 synthesis and disrupt negative feedback regulation, leading to elevated TSH level, which aligns with the U-shaped relationship between UIC and TSH, and the inverse U-shaped trend between UI/Cr and FT4 observed in our study. Furthermore, we find the U-shaped trend of Tg with UI/Cr aligns with Glinoer’s proposition, further underscores Tg’s role as a biomarker of long-term iodine exposure. During iodine deficiency, thyroid hyperplasia stimulates Tg release due to compensatory follicular proliferation. Conversely, iodine excess induces Tg elevation through oxidative stress. These findings highlight Tg’s utility as a sensitive indicator for monitoring chronic iodine imbalance in populations, addressing the limitations of spot urinary iodine measurements, which primarily reflect short-term iodine intake. This finding suggests that while both indicators are associated with thyroid function, they exhibit distinct sensitivities and specificities. It also implies that iodine can disrupt thyroid homeostasis by influencing thyroid function, thereby contributing to thyroid disorders.
Our study provides insights into the prevalence of thyroid disorders in the Zhejiang region, with rates of overt hypothyroidism, subclinical hypothyroidism, overt hyperthyroidism, subclinical hyperthyroidism, positive TPOAb, positive TgAb, positive thyroid antibodies, and thyroid nodules recorded at 0.6%, 9.3%, 0.6%, 0.5%, 10.3%, 9.5%, 14.6%, and 48.6%, respectively. The similar prevalence of thyroid disorders was also reported by many studies in China9,16,33,34. In our study, the low prevalence (< 1%) of clinical hypothyroidism, clinical hyperthyroidism, and subclinical hyperthyroidism may limit statistical power for analyses. Therefore, this study focused on high prevalence thyroid disorders (e.g., subclinical hyperthyroidism, positive TPOAb, positive TgAb, positive thyroid antibodies, and thyroid nodules), which hold significant clinical and public health relevance in populations. Thyroid nodules stand out as the most prevalent among thyroid disorders and represent one of the most common thyroid diseases. Our investigation reveals a heightened risk of thyroid nodules associated with lower levels of UIC (< 100 µg/L) and UI/Cr (< 69.5 µg/g). This finding is mechanistically supported by global studies demonstrating that chronic iodine deficiency stimulates thyroid hyperplasia through increased TSH-driven follicular cell proliferation, thereby elevating nodule formation risk35,36. In China, a nationwide study similarly reported that reduced iodine intake significantly increases the incidence of thyroid nodules37. Beyond iodine intake, the widespread adoption of screening technologies (e.g., high-frequency ultrasound) and improvements in diagnostic sensitivity have substantially enhanced the detection of subclinical nodules38,39. Furthermore, the fast-paced lifestyle of modern society leads to increasing psychological stress, and the generation of negative emotions such as psychological stress causes changes in neurotransmission in the cerebral cortex and hypothalamus40, which directly or indirectly weakens the immune system and leads to an increase in the incidence of malignant nodules.
In our study, the prevalence of subclinical hypothyroidism increases with rising urinary iodine levels. Specifically, participants with insufficient iodine (UIC < 100 µg/L) exhibit a lower risk, while those with excessive iodine intake (UIC ≥ 300 µg/L) face an elevated risk of subclinical hypothyroidism. A similar association trend was observed in the analysis of UI/Cr. A study focusing on mainland China similarly found a higher risk of subclinical hypothyroidism in regions with iodine sufficiency or excess compared to iodine deficiency areas33. A review on thyroid function decline suggests that the prevalence of subclinical hypothyroidism increases as iodine intake transitions from mild deficiency to adequacy or excess41. Since the implementation of universal salt iodization (USI) in 1995, the incidence of subclinical hypothyroidism has shown an upward trend, suggesting a potential increase in subclinical hypothyroidism associated with iodine fortification42. Additionally, animal experiments indicate that prolonged high iodine intake can suppress pituitary type 2 deiodinase activity, resulting in reduced T4 to T3 conversion and increased TSH production43.
Thyroid antibodies serve as crucial markers for diagnosing Autoimmune Thyroid Disease (AITD) and can guide clinical treatment to a certain extent44. Existing research on the association between iodine nutrition and thyroid antibodies yields inconsistent conclusions. Many national studies find that the prevalence of thyroid antibodies increases with urinary iodine levels after salt iodization45–47. Animal experiments also reveal that mice fed a high-iodine diet develop spontaneous thyroiditis and thyroid autoantibodies48. However, a Chinese study suggests a decrease in the positivity rate of thyroid antibodies with increasing iodine intake, indicating that more than adequate and excessive iodine intake acts as protective factors49. Some studies even find no correlation between iodine intake and thyroid autoimmunity50,51. In our study, participants with a high (quartile 4) UI/Cr level had a higher risk of thyroid antibody positivity in unadjusted models, but upon adjusting for age, gender, BMI, ethnicity, educational attainment, cigarette smoking, alcohol consumption, and salt utilization, the correlation became non-significant. Since the pathogenesis of AITD is very complex, many other factors also play a non-negligible role in its development. Thus, a more in-depth and comprehensive investigation is required to explore the association between iodine nutritional status and thyroid antibodies.
Our study’s strengths lie in the large number of participants and substantial sample size, making it the most extensive population-based study in the Zhejiang region of China to date. Furthermore, the inclusion of creatinine adjustment in assessing urinary iodine enhances the comprehensiveness and accuracy of our study results. However, several limitations exist. Firstly, the current study is in the baseline survey phase and, as a cross-sectional investigation, cannot directly establish causation between urinary iodine levels and thyroid disorders. As the cohort study proceeds, more longitudinal data will be collected for more in-depth analysis. Secondly, salt utilization data was collected through a questionnaire survey, which may lead to certain deviations from the actual situation. Third, certain thyroid-related confounding factors were not comprehensively collected in the current study. Our follow-up studies will collect detailed data on medication history, surgical history, and neck irradiation.
Conclusions
In conclusion, our large-scale population-based study highlighted the association between urinary iodine levels and thyroid disorders, revealing that higher iodine level was associated with an increased risk of subclinical hypothyroidism, while lower iodine level was associated with an increased incidence of thyroid nodules. These findings underscore the necessity of establishing precision-based iodine supplementation guidelines to maintain population-level iodine intake within an optimal range, thereby minimizing thyroid disease risks linked to prolonged iodine imbalance. We propose implementing regionally adaptive monitoring systems that integrate periodic urinary iodine assessments with dietary intervention strategies, ensuring targeted adjustments to iodized salt policies and fortified food supplies.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
The authors would like to express their sincere thanks to the participants of this study. We also appreciate the support provided by the Zhejiang Provincial Project for Medical Research and Health Sciences (Grant No. 2025KY758 and 2024KY910); Zhejiang Science and Technology Plan for Disease Prevention and Control (Grant No. 2025JK158); Science Foundation of National Health Commission of the People’s Republic of China (Grant No. WKJ-ZJ-2332); Science and Technology Project of Zhejiang Provincial Department of Water Resources (RC2242); National Natural Science Foundation of China (Grant No. 42407553).
Author contributions
Conceptualization, Z.C.; methodology, X.L., M.X. and Z.C.; formal analysis, X.L., P.T., X.W. and Z.M.; investigation, X.L., M.X. (Mingluan Xing), L.W. and H.N.; data curation, X.L., M.X. (Manjin Xu), Y.X. and L.W.; writing-original draft preparation, X.L. and M.X. (Mingluan Xing); writing-review and editing, X.L. and P.T.; supervision, Z.C., Z.M., and X.W.; project administration, X.W., L.W., Z.M. and Z.C.
Data availability
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Xueqing Li and Mingluan Xing contributed equally to this work.
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Associated Data
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Supplementary Materials
Data Availability Statement
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.