Threshold-Dependent Biphasic Association of Blood Cadmium with Testosterone in Men: Implications for Environmental Exposure Risk Assessment

Threshold-Dependent Biphasic Association of Blood Cadmium with Testosterone in Men: Implications for Environmental Exposure Risk Assessment | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Threshold-Dependent Biphasic Association of Blood Cadmium with Testosterone in Men: Implications for Environmental Exposure Risk Assessment Shiwei SONG, Bin ZHANG, Qingzhu LI, Dehui CHANG This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7277696/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Cadmium (Cd) is a widespread reproductive toxicant conventionally known to suppress testosterone synthesis, but this study first identifies a threshold-dependent biphasic association between blood cadmium (BCd) and serum testosterone in a general male population. Using data from 4,458 US adult males in NHANES (2011-2016), we analyzed nonlinear relationships via restricted cubic splines (RCS) and segmented regression, with subgroup analyses to explore susceptibility. Results revealed a significant biphasic association (Pnonlinear=0.03;Ptrend<0.01), with an inflection point at 0.7 μg/L. Below this threshold, each 1 μg/L increase in BCd was associated with a 93.54 ng/dL rise in testosterone (95% CI:54.21–132.88; P<0.001), while above it, the effect attenuated to 18.67 ng/dL (95% CI:2.94–34.39; P=0.020). Subgroup analyses showed stronger effects in non-smokers (β=67.8 vs. smokers’ β=17.7; Pinteraction=0.029), middle-aged men (40–60 years; β=44.0), and low-BMI individuals (<25 kg/m²; β=36.0). This is the first population-level evidence of Cd-induced testosterone hormesis (low-dose stimulation, high-dose suppression), challenging the linear no-threshold model in Cd risk assessment. The identified 0.7 μg/L threshold informs revisions to environmental standards (e.g., China’s GB 2762-2022) and targeted health monitoring for high-risk subgroups. Blood cadmium Testosterone Biphasic association Threshold Restricted cubic splines Environmental exposure risk assessment Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Cadmium (Cd), a persistent environmental contaminant, accumulates in testicular tissue via tobacco, contaminated water, and dietary sources, disrupting reproductive endocrine function [ 1 – 3 ] . Substantial evidence confirms Cd's reproductive toxicity in animal models: high-dose exposure (> 5 µg/L blood Cd) induces Leydig cell apoptosis and suppresses key steroidogenic enzymes (STAR, CYP11A1, CYP17A1, 3β-HSD) [ 4 – 7 ] . Epidemiologic studies consistently associate high Cd exposure with impaired spermatogenesis [ 8 , 9 ] . Paradoxically, a meta-analysis by Zhao et al. reported higher testosterone levels in smokers versus non-smokers (mean difference: 1.53 nmol/L, 95% CI: 1.11–1.96), suggesting potential low-dose stimulatory effects of Cd [ 10 ] . Current evidence remains contradictory: while multiple studies report inverse Cd-testosterone correlations [ 11 – 13 ] , others propose Cd-mediated activation of hypothalamic-pituitary-testicular axis (HPTA) feedback at low doses [ 14 , 15 ] . Although Cd's structural mimicry of zinc may activate cellular signaling pathways [ 16 ] , its dose-response characteristics in human reproductive endocrinology remain unvalidated. Critical limitations persist: overreliance on linear models neglecting threshold effects [ 17 ] , lack of nationally representative data, and insufficient attention to environmentally relevant exposure levels (< 1 µg/L blood Cd). Research Gap & Innovation: Utilizing restricted cubic splines (RCS), we analyze NHANES multi-cycle data to delineate the nonlinear Cd-testosterone dose-response relationship, specifically addressing low-dose biological paradoxes. Our findings directly address China’s "14th Five-Year Plan for Ecological Conservation" (MEE, 2025) mandating heavy metal threshold recalibration. The identified inflection point (0.7 µg/L) provides evidence for revising Cd limits in China’s GB 2762 − 2022 standard. 2. Methods 2.1. Study Design and Data Source This cross-sectional study used publicly available NHANES data (2011-2016 cycles). NHANES employs a stratified multistage probability sampling design to obtain nationally representative US data. Standardized protocols ensured data quality (e.g., analytical method consistency, intra-batch CV <5%) [29]. The 2011-2016 cycles were selected for complete BCd, testosterone, and covariate data with uniform methodologies. 2.2. Study Population Inclusion criteria: Males ≥18 years with complete data on BCd, serum testosterone, and key covariates (age, BMI, smoking status). Exclusion criteria: (1) Female participants;(2) Missing BCd or testosterone measurements; (3) Missing critical covariates (BMI, education, income-poverty ratio); (4) Duplicate records (removed via unique SEQN identifiers) (5) Final analytical sample: 4,458 participants (Figure 1). Figure 1 2.3. Exposure and Outcome Assessment Blood Cadmium (BCd): Quantified by inductively coupled plasma mass spectrometry (ICP-MS; Agilent 7700x). Limit of detection (LOD): 0.01 μg/L; values <LOD imputed as LOD/√2. Intra-/inter-day CVs: 2.1–3.5% and 3.8–5.2%, respectively . Serum Testosterone: Measured via chemiluminescent immunoassay (Beckman Coulter Access 2). LOD: 20 ng/dL; intra-/inter-day CVs <4.0% and <6.0%. Analytical range (20–1600 ng/dL) covered observed concentrations (median: 414.09 ng/dL). 2.4. Covariate Definition and Measurement Demographics: Age (years, continuous), race/ethnicity (non-Hispanic White, non-Hispanic Black, Mexican American, other Hispanic, other race). Lifestyle Factors: Smoking status: Non-smoker (lifetime cigarette use <100), Smoker (≥100 cigarettes) Education: <9th grade, 9-11th grade, high school graduate, some college, college graduate. Socioeconomic Status: Poverty-income ratio (PIR; family income to federal poverty level, continuous). Anthropometrics: Body mass index (BMI; kg/m², continuous). Co-exposures: Blood lead and mercury (μg/dL; measured by ICP-MS using identical protocols). 2.5. Statistical Analysis Analyses were performed using R version 4.2.1 (R Foundation for Statistical Computing) with significance defined as two-tailed α<0.05. Descriptive Statistics: Continuous variables: mean ± SD (normally distributed) or median (IQR) (non-normal) Categorical variables: frequency (%) Group comparisons: Student's t-test, Wilcoxon rank-sum test, or χ² test as appropriate. Nonlinear Association Analysis: Restricted cubic splines (RCS) with three knots (25th, 50th, 75th percentiles of BCd distribution) modeled the BCd-testosterone dose-response relationship. Nonlinearity was assessed using the Wald test (Pnonlinear), with overall trends evaluated by Ptrend. Models adjusted for age, BMI, race, education, PIR, smoking status, blood lead, and mercury. *This innovative application of RCS in endocrine disruptor research overcomes "linear trap" limitations of traditional toxicology models, enabling identification of the inflection point (0.7 μg/L) where biological response transitions from stimulation to suppression.* Segmented Regression Analysis: BCd was dichotomized at the RCS-derived inflection point (0.7 μg/L). Separate linear regression models estimated β-coefficients (95% CI) for BCd <0.7 μg/L and ≥0.7 μg/L to quantify threshold-dependent effects. Subgroup Analysis: Multivariable linear regression evaluated BCd-testosterone associations (per 1 μg/L increase) in prespecified subgroups (smoking status, age strata [<40, 40-60, ≥60 years], BMI categories [<25, 25-30, ≥30 kg/m²], race, education, PIR). Interaction terms (e.g., BCd × smoking status) tested effect modification (Pinteraction<0.05). Heterogeneity was visualized using forest plots (forestplot package). Missing Data Handling: Key variables (BCd, testosterone, BMI) had <5% missingness (total missing rate: 3.2%). Complete-case analysis was employed since Little's MCAR test indicated data were missing completely at random (P=0.31). 3. Results 3.1. Baseline Characteristics Participants with high blood cadmium (BCd ≥ 0.7 µg/L) exhibited a notable biological paradox: despite lower socioeconomic status (reduced income-poverty ratio and higher proportion of high school education), this group demonstrated significantly higher serum testosterone levels (451.49 ng/dL vs. 407.01 ng/dL; P < 0.001) compared to the low-BCd group (< 0.7 µg/L). Crucially, the high-BCd group had substantially fewer smokers (5.5% vs. 58.3%; P < 0.001), suggesting smoking may reduce cadmium bioavailability by inducing metallothionein synthesis. Additionally, the high-BCd group had lower BMI (27.42 kg/m² vs. 29.01 kg/m²; P < 0.001), consistent with the physiological link between lean mass and testosterone [18]. After BMI adjustment, the positive BCd-testosterone association persisted (Table 2 ), indicating BMI is not a core confounder (Table 1 ). Table 1 Baseline Characteristics of Study Participants Stratified by Blood Cadmium Threshold (0.7 µg/L) Characteristic Overall (n = 4,458) Low BCd < 0.7 µg/L (n = 3,600) High BCd ≥ 0.7 µg/L (n = 858) P-value BCd (µg/L) 0.43 ± 0.02 0.24 ± 0 1.41 ± 0.04 < 0.001 Testosterone (ng/dL) 414.09 ± 4.07 407.01 ± 4.79 451.49 ± 9.16 < 0.001 Age (years) 46.69 ± 0.51 46.46 ± 0.54 47.9 ± 0.69 0.041 BMI(kg/m²) 28.76 ± 0.13 29.01 ± 0.16 27.42 ± 0.28 < 0.001 Poverty-Income Ratio 3.04 ± 0.06 3.19 ± 0.07 2.23 ± 0.09 < 0.001 Blood Lead (µg/dL) 1.54 ± 0.06 1.39 ± 0.04 2.32 ± 0.18 < 0.001 Blood Mercury (µg/dL) 1.54 ± 0.1 1.58 ± 0.11 1.36 ± 0.12 0.020 Smoking Status < 0.001 Non-smoker 50.1% 41.7% 94.5% smoker 49.9% 58.3% 5.5% Race/Ethnicity 0.015 Mexican American 10.1% 10.7% 6.5% Other Hispanic 7.3% 7.5% 6.2% Non-Hispanic White 82.6% 81.8% 87.3% Education < 0.001 < 9th grade 5.7% 5.5% 6.5% 9-11th grade 9.7% 8.1% 18.4% High school graduate 22.1% 20.3% 31.7% Some college 29.7% 29.3% 31.8% College graduate 32.8% 36.8% 11.6% (Values are mean ± SD or %; comparisons by Student’s t-test, χ² test, or Mann-Whitney U test; α = 0.05) 3.2. Segmented Regression Analysis A threshold-dependent biphasic association between BCd and testosterone was identified, with an inflection point at 0.7 µg/L. Segmented regression revealed dose-dependent effect attenuation: Low-exposure segment (BCd < 0.7 µg/L): Each 1 µg/L increase in BCd associated with a 93.54 ng/dL surge in testosterone (95% CI: 54.21–132.88; P < 0.001). High-exposure segment (BCd ≥ 0.7 µg/L): Effect magnitude decreased sharply to 18.67 ng/dL (95% CI: 2.94–34.39; P = 0.020). This pattern aligns with the classic J-shaped hormesis curve: low-dose Cd may act as a zinc mimetic, competitively binding ZIP8 transporters on Leydig cells to enhance steroidogenesis [ 19 ] , while high-dose Cd accumulation triggers oxidative stress and apoptosis that counteract stimulation [ 20 ] . Toxicologically, the 0.7 µg/L inflection point approximates the US population median BCd (0.4 µg/L), indicating that Cd’s stimulatory effects dominate at environmental exposure levels (Table 2 ). Table 2 Segmented Regression Analysis of Blood Cadmium and Testosterone Association BCd Range β (95% CI) 95% CI P-value N < 0.7 µg/L 93.54 54.21, 132.88 < 0.001 3570 ≥ 0.7 µg/L 18.67 2.94, 34.39 0.020 888 (β: Change in testosterone [ng/dL] per 1 µg/L increase in blood cadmium,Adjusted for age, BMI, race, education, income-poverty ratio, blood lead, mercury, and smoking status.) 3.3. Subgroup Analysis Subgroup heterogeneity identified three susceptible populations: Non-smokers (β = 67.8) vs. smokers (β = 17.7; P interaction = 0.029), as smoking reduces bioavailable Cd via metallothionein binding and suppresses HPTA axis sensitivity via nicotine-induced GnRH inhibition (Fig. 3 ). Middle-aged men (40–60 years) (β = 44.0), potentially reflecting peak HPTA feedback regulation [ 21 , 22 ] .Low-BMI individuals (< 25 kg/m²) (β = 36.0), likely due to reduced adipose Cd sequestration and higher free Cd²⁺ bioavailability. The stimulatory effect of low-dose Cd—potentially mediated through zinc-mimetic activation of Leydig cell proteins (e.g., CYP19A1, StAR)—appeared attenuated in obese, older, or smoking individuals. No significant interactions were observed for BMI or race subgroups (P-interaction > 0.05) (Table 3 ). Table 3 Subgroup Analysis of Blood Cadmium-Testosterone Association Subgroup β (95% CI) P-value P-interaction Overall 22.44 (13.19, 31.69) < 0.001 Age < 40 years 4.51 (-12.40, 21.42) 0.601 0.145 ≥ 60 years 22.90 (10.69, 35.11) < 0.001 40–60 years 44.02 (21.12, 66.92) < 0.001 Bmi < 25 kg/m² 36.04 (18.56, 53.52) < 0.001 0.117 ≥ 30 kg/m² 18.13 (2.22, 34.04) 0.026 25–30 kg/m² 15.87 (0.74, 31.00) 0.040 Education High education 26.11 (5.11, 47.11) 0.015 0.957 Low education 15.81 (-2.80, 34.42) 0.096 Middle education 21.99 (9.57, 34.41) < 0.001 Income-Poverty Ratio PIR 3 19.26 (4.84, 33.68) 0.009 PIR 1–3 17.63 (1.31, 33.95) 0.034 Race Black 34.37 (6.37, 62.37) 0.016 0.097 Other 10.47 (-3.11, 24.05) 0.131 White 30.37 (15.70, 45.04) < 0.001 Smoking Non-smoker 67.81(31.42,104.19) < 0.001 0.029 Smoker 17.75 (7.50, 28.00) < 0.001 (β: Change in testosterone [ng/dL] per 1 µg/L increase in blood cadmium) 3.4. Restricted Cubic Spline (RCS) Analysis The RCS curve demonstrated a monotonically increasing BCd-testosterone relationship (P trend < 0.001), with the steepest slope observed at 0.2–0.7 µg/L (Fig. 1 ). Beyond 1.5 µg/L, the curve plateaued—consistent with effect attenuation in the high-exposure segment (Table 2 ). A latent inflection point at 0.7 µg/L (evidenced by widening confidence intervals) suggests progressive dominance of cytotoxic mechanisms over testosterone stimulation. 3.5. Forest Plot of Subgroup Analysis Forest plots confirmed significant effect modification by smoking: the BCd-testosterone association was 3.8-fold stronger in non-smokers (β = 67.8, 95% CI: 31.4–104.2) than smokers (β = 17.7, 95% CI: 7.5–28.0) (Fig. 2 ). In non-smokers, low-dose Cd likely activates zinc-sensitive signaling pathways in Leydig cells, upregulating steroidogenic enzymes. Conversely, in smokers, Cd preferentially forms inert complexes with tobacco-induced metallothionein, reducing bioavailable Cd. Concurrently, nicotine suppresses hypothalamic gonadotropin-releasing hormone (GnRH) release, blunting HPTA axis sensitivity to Cd.. 4. Discussion This study provides the first population-level evidence of a threshold-dependent biphasic association between blood cadmium (BCd) and serum testosterone in men, with a critical inflection point at 0.7 μg/L. Below this threshold, each 1 μg/L increase in BCd was associated with a 93.54 ng/dL surge in testosterone (P<0.001), reflecting low-dose stimulation. Mechanistically, Cd²⁺ may act as a zinc mimetic, competitively binding ZIP8 zinc transporters on Leydig cells to enhance steroidogenic enzyme activity [19,23,24] . Above 0.7 μg/L, the effect attenuated sharply to 18.67 ng/dL per μg/L BCd (P=0.020), consistent with Cd-induced cytotoxicity via SOD inhibition, oxidative stress [25,26] , and mitochondrial apoptosis. Smoking Modifies Cadmium Bioavailability：Non-smokers exhibited a 3.8-fold stronger BCd-testosterone association (β=67.8 vs. smokers’ β=17.7; P-interaction=0.029). This divergence likely arises from:Metallothionein (MT) induction by tobacco, sequestering Cd into biologically inert complexes [27] . Nicotine-mediated suppression of hypothalamic ARNTL expression, inhibiting pulsatile GnRH release and blunting HPTA axis sensitivity [21,22] .Middle-aged men (40–60 years): Peak effect (β=44.0) potentially reflects optimal HPTA negative-feedback regulation, where Cd may amplify androgen signaling via AR coactivators (e.g., SRC-1) [28,29] . Low-BMI individuals (<25 kg/m²): Enhanced effect (β=36.0) likely stems from reduced adipose Cd storage and elevated free Cd²⁺ bioavailability [30] . While this cross-sectional analysis cannot establish temporality, the identified inflection point (0.7 μg/L) warrants validation: Molecular mechanisms: Examine Cd’s impact on Leydig cell steroidogenic enzymes (StAR, CYP11A1) and epigenetic regulation (e.g., 2.3-fold increase in ZIP8 promoter methylation [31] Subsequent studies should employ prospective cohort studies and cellular experiments (e.g., Leydig cell models) to further validate the underlying mechanisms. Among current internationally accepted standards, the World Health Organization (WHO) has set a provisional guideline value for blood cadmium at 5 μg/L. However, the present study demonstrates that significant dose-dependent changes in male testosterone levels occur when blood cadmium exceeds 0.7 μg/L, supporting the proposal of 0.7 μg/L as an early warning threshold for blood cadmium with respect to endocrine effects. The significant effect modification induced by smoking underscores the necessity of considering smoking status in cadmium risk assessment and monitoring programs. Men with blood cadmium levels >0.7 μg/L, particularly non-smokers, may require surveillance for potential androgen-related health outcomes. Sensitive populations (including middle-aged individuals and those with low BMI) should be prioritized in surveillance efforts. 5. Conclusion This study is the first to confirm that there is a non-monotonic relationship between blood cadmium and testosterone in the general population, characterized by low-dose promotion and high-dose inhibition, with a clear threshold-dependent biphasic effect (inflection point at 0.7 μg/L). Future studies need to further explore the molecular targets through which cadmium activates testosterone synthesis; the molecular mechanisms by which smoking attenuates cadmium's effects via epigenetic regulation (e.g., methylation of metallothionein genes); the establishment of safe thresholds for blood cadmium based on restricted cubic spline (RCS) curves; the need for monitoring the risk of prostate-related diseases associated with elevated testosterone in men with blood cadmium > 0.7 μg/L; and further exploration of the endocrine mechanisms underlying "elevated blood cadmium → compensatory increase in testosterone", so as to provide a scientific basis for the stratified prevention and control of reproductive health risks associated with cadmium exposure. Declarations Funding This work was supported by the Key Project of University Collaborative Innovation (HXLH-XTCX11), the Central University Project (31920240072), the Natural Science Foundation of Gansu Province (22JR5RA001, 22KYLL195, 23JRRA531, 23JRRA001), the Science and Technology Project of Lanzhou City (2023-2-63), and the Departmental Scientific Research Project of Gansu Province (2023KYLL205). The funders had no role in the design of the study, data collection, analysis, decision to publish, or preparation of the manuscript. Author Contribution Author Contributions: Shiwei Song: Conception and design of the study, data analysis and interpretation, drafting the initial manuscript. Bin Zhang: Acquisition of data, assistance with statistical analysis, and critical revision of the manuscript for intellectual content. Chunlei Zhang: Interpretation of results, contribution to the discussion section, and revision of the manuscript. 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Journal of Environmental Pathology, Toxicology and Oncology: Official Organ of the International Society for Environmental Toxicology and Cancer, 2000, 19(3): 275-280. Martin M B, Voeller H J, Gelmann E P, et al. Role of cadmium in the regulation of AR gene expression and activity[J]. Endocrinology, 2002, 143(1): 263-275. Lin H C, Hao W M, Chu P H. Cadmium and cardiovascular disease: An overview of pathophysiology, epidemiology, therapy, and predictive value[J]. Revista Portuguesa de Cardiologia (English Edition), 2021, 40(8): 611-617. Zhang Y, Wang B, Sun W, et al. Paternal exposures to endocrine-disrupting chemicals induce intergenerational epigenetic influences on offspring: A review[J]. Environment International, 2024, 187: 108689. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7277696","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":497847218,"identity":"3bd5b4bb-9906-4c5b-8e27-a83072ba0090","order_by":0,"name":"Shiwei SONG","email":"","orcid":"","institution":"The 940th Hospital of the Joint Logistic Support Force of PLA","correspondingAuthor":false,"prefix":"","firstName":"Shiwei","middleName":"","lastName":"SONG","suffix":""},{"id":497847219,"identity":"8e628a9d-1dd8-4a35-86d3-d0a5d26e3bd5","order_by":1,"name":"Bin ZHANG","email":"","orcid":"","institution":"The 940th Hospital of the Joint Logistic Support Force of PLA","correspondingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"ZHANG","suffix":""},{"id":497847220,"identity":"93d48ffd-d8cf-4f46-ae00-6c4ab2a72ef4","order_by":2,"name":"Qingzhu LI","email":"","orcid":"","institution":"Gansu University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Qingzhu","middleName":"","lastName":"LI","suffix":""},{"id":497847221,"identity":"605e8e52-02e5-4429-b608-8617225072f3","order_by":3,"name":"Dehui CHANG","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAn0lEQVRIiWNgGAWjYDACCQYzBgYDGx5+/gbStKTJSM44QJIWhsM2Bg0JROrgn9287TFPwXkeA4YDjB8+5hBjyZ1j5cY8Brd5zJkbmCVnbiNCi4FEjpk0SItlwwE2Zl4StJzjMTiQQJqWAyRokbiRViY5xyCZR3LGwWbi/MI/I3mbxJs/dvb8/M0HP3wkRgsSYGwgTf0oGAWjYBSMAtwAALM5LztNb8ajAAAAAElFTkSuQmCC","orcid":"","institution":"The 940th Hospital of the Joint Logistic Support Force of PLA","correspondingAuthor":true,"prefix":"","firstName":"Dehui","middleName":"","lastName":"CHANG","suffix":""}],"badges":[],"createdAt":"2025-08-02 10:53:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7277696/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7277696/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88815416,"identity":"8f1330a6-fa06-4ce3-adc7-16bff869d1e4","added_by":"auto","created_at":"2025-08-11 16:13:57","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":121159,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of the selection process for study population from NHANES 2011–2016. NHANES: National Health and Nutrition Examination Survey\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7277696/v1/89d3ce022ea428b2e36a6a76.jpg"},{"id":88816687,"identity":"6f892036-d01f-4ee9-8150-8acd70c79919","added_by":"auto","created_at":"2025-08-11 16:29:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":34767,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 1. Nonlinear Association Between Blood Cadmium and Testosterone (RCS Curve)\u003c/p\u003e\n\u003cp\u003e(Shaded area: 95% confidence band; blue dashed line: inflection point at 0.7 μg/L.)\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7277696/v1/636c35b2d15432bc3bdabdd0.jpg"},{"id":88815426,"identity":"0bd707c5-7dbb-41c8-b651-b1f02048f7c2","added_by":"auto","created_at":"2025-08-11 16:13:58","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":62780,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 2. Forest Plot of Subgroup-Specific Associations Between Blood Cadmium and Testosterone\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7277696/v1/2b7549ae071ad61b1f3fcea6.jpg"},{"id":88816689,"identity":"38379a2b-7f07-4631-8c2b-22ab1869866b","added_by":"auto","created_at":"2025-08-11 16:29:58","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":78353,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 3. Integrated Mechanisms of Cadmium Exposure and Smoking Modulation on Testosterone Synthesis\u003c/p\u003e\n\u003cp\u003eLeft panel: Smoking attenuates cadmium toxicity via metallothionein (MT) chelation and GnRH inhibition.\u003c/p\u003e\n\u003cp\u003eRight panel: Biphasic cadmium effects: Low-dose stimulation (green) via ZIP8-mediated zinc mimicry vs. high-dose inhibition (red) via ROS/mPTP-dependent apoptosis.\u003c/p\u003e\n\u003cp\u003eAbbreviations: MT (Metallothionein), GnRH (Gonadotropin-releasing hormone), ZIP8 (Zrt/Irt-like protein 8), mPTP (mitochondrial permeability transition pore), ROS (reactive oxygen species).\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7277696/v1/899e89c50b1c6805bef5ec8b.jpg"},{"id":88815719,"identity":"687216b3-2582-459f-a60d-f32001e01cbf","added_by":"auto","created_at":"2025-08-11 16:21:57","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":33168,"visible":true,"origin":"","legend":"\u003cp\u003ePolicy Translation Pathways from Key Findings to Reduced Reproductive Disease Burden\u003c/p\u003e\n\u003cp\u003eFigure 4. Policy translation pathways from key study findings to reduced reproductive endocrine disease burden. Left: Three core discoveries (blood cadmium inflection point, non-smoker susceptibility, middle-aged male sensitivity). Middle: Corresponding policy actions (threshold revision, smoking-specific standards, health monitoring guidelines). Right: Final policy outputs (GB 2762-2022 revision, WHO framework addendum, national chronic disease plan) and health impact.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7277696/v1/c209c389331d71b022df0536.jpg"},{"id":103559043,"identity":"23f712b1-0e26-4386-b4bb-0d87ca006f3e","added_by":"auto","created_at":"2026-02-27 05:10:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1064463,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7277696/v1/c5cb0aa1-fd6e-4930-bbcd-e26231f09837.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Threshold-Dependent Biphasic Association of Blood Cadmium with Testosterone in Men: Implications for Environmental Exposure Risk Assessment","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCadmium (Cd), a persistent environmental contaminant, accumulates in testicular tissue via tobacco, contaminated water, and dietary sources, disrupting reproductive endocrine function\u003csup\u003e[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Substantial evidence confirms Cd's reproductive toxicity in animal models: high-dose exposure (\u0026gt;\u0026thinsp;5 \u0026micro;g/L blood Cd) induces Leydig cell apoptosis and suppresses key steroidogenic enzymes (STAR, CYP11A1, CYP17A1, 3β-HSD)\u003c/p\u003e\u003cp\u003e\u003csup\u003e[\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Epidemiologic studies consistently associate high Cd exposure with impaired spermatogenesis \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Paradoxically, a meta-analysis by Zhao et al. reported higher testosterone levels in smokers versus non-smokers (mean difference: 1.53 nmol/L, 95% CI: 1.11\u0026ndash;1.96), suggesting potential low-dose stimulatory effects of Cd \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eCurrent evidence remains contradictory: while multiple studies report inverse Cd-testosterone correlations \u003csup\u003e[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e, others propose Cd-mediated activation of hypothalamic-pituitary-testicular axis (HPTA) feedback at low doses \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Although Cd's structural mimicry of zinc may activate cellular signaling pathways \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, its dose-response characteristics in human reproductive endocrinology remain unvalidated. Critical limitations persist: overreliance on linear models neglecting threshold effects \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e, lack of nationally representative data, and insufficient attention to environmentally relevant exposure levels (\u0026lt;\u0026thinsp;1 \u0026micro;g/L blood Cd).\u003c/p\u003e\u003cp\u003eResearch Gap \u0026amp; Innovation: Utilizing restricted cubic splines (RCS), we analyze NHANES multi-cycle data to delineate the nonlinear Cd-testosterone dose-response relationship, specifically addressing low-dose biological paradoxes. Our findings directly address China\u0026rsquo;s \"14th Five-Year Plan for Ecological Conservation\" (MEE, 2025) mandating heavy metal threshold recalibration. The identified inflection point (0.7 \u0026micro;g/L) provides evidence for revising Cd limits in China\u0026rsquo;s GB 2762\u0026thinsp;\u0026minus;\u0026thinsp;2022 standard.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1. Study Design and Data Source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis cross-sectional study used publicly available NHANES data (2011-2016 cycles). NHANES employs a stratified multistage probability sampling design to obtain nationally representative US data. Standardized protocols ensured data quality (e.g., analytical method consistency, intra-batch CV \u0026lt;5%) [29]. The 2011-2016 cycles were selected for complete BCd, testosterone, and covariate data with uniform methodologies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. Study Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInclusion criteria: Males \u0026ge;18 years with complete data on BCd, serum testosterone, and key covariates (age, BMI, smoking status).\u003cbr\u003e Exclusion criteria: (1) Female participants;(2) Missing BCd or testosterone measurements; (3) Missing critical covariates (BMI, education, income-poverty ratio); (4) Duplicate records (removed via unique SEQN identifiers)\u003cbr\u003e (5) Final analytical sample: 4,458 participants (Figure 1).\u003c/p\u003e\n\u003cp\u003eFigure 1\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. Exposure and Outcome Assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlood Cadmium (BCd): Quantified by inductively coupled plasma mass spectrometry (ICP-MS; Agilent 7700x). Limit of detection (LOD): 0.01 \u0026mu;g/L; values \u0026lt;LOD imputed as LOD/\u0026radic;2. Intra-/inter-day CVs: 2.1\u0026ndash;3.5% and 3.8\u0026ndash;5.2%, respectively .\u003c/p\u003e\n\u003cp\u003eSerum Testosterone: Measured via chemiluminescent immunoassay (Beckman Coulter Access 2). LOD: 20 ng/dL; intra-/inter-day CVs \u0026lt;4.0% and \u0026lt;6.0%. Analytical range (20\u0026ndash;1600 ng/dL) covered observed concentrations (median: 414.09 ng/dL).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4. Covariate Definition and Measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDemographics: Age (years, continuous), race/ethnicity (non-Hispanic White, non-Hispanic Black, Mexican American, other Hispanic, other race).\u003c/p\u003e\n\u003cp\u003eLifestyle Factors:\u003c/p\u003e\n\u003cp\u003eSmoking status: Non-smoker (lifetime cigarette use \u0026lt;100), Smoker (\u0026ge;100 cigarettes)\u003c/p\u003e\n\u003cp\u003eEducation: \u0026lt;9th grade, 9-11th grade, high school graduate, some college, college graduate.\u003c/p\u003e\n\u003cp\u003eSocioeconomic Status: Poverty-income ratio (PIR; family income to federal poverty level, continuous).\u003c/p\u003e\n\u003cp\u003eAnthropometrics: Body mass index (BMI; kg/m\u0026sup2;, continuous).\u003c/p\u003e\n\u003cp\u003eCo-exposures: Blood lead and mercury (\u0026mu;g/dL; measured by ICP-MS using identical protocols).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5. Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalyses were performed using R version 4.2.1 (R Foundation for Statistical Computing) with significance defined as two-tailed \u0026alpha;\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003eDescriptive Statistics:\u003cbr\u003e Continuous variables: mean \u0026plusmn; SD (normally distributed) or median (IQR) (non-normal)\u003cbr\u003e Categorical variables: frequency (%)\u003cbr\u003e Group comparisons: Student\u0026apos;s t-test, Wilcoxon rank-sum test, or \u0026chi;\u0026sup2; test as appropriate.\u003c/p\u003e\n\u003cp\u003eNonlinear Association Analysis:\u003cbr\u003e Restricted cubic splines (RCS) with three knots (25th, 50th, 75th percentiles of BCd distribution) modeled the BCd-testosterone dose-response relationship. Nonlinearity was assessed using the Wald test (P\u0026lt;sub\u0026gt;nonlinear\u0026lt;/sub\u0026gt;), with overall trends evaluated by P\u0026lt;sub\u0026gt;trend\u0026lt;/sub\u0026gt;. Models adjusted for age, BMI, race, education, PIR, smoking status, blood lead, and mercury. *This innovative application of RCS in endocrine disruptor research overcomes \u0026quot;linear trap\u0026quot; limitations of traditional toxicology models, enabling identification of the inflection point (0.7 \u0026mu;g/L) where biological response transitions from stimulation to suppression.*\u003c/p\u003e\n\u003cp\u003eSegmented Regression Analysis:\u003cbr\u003e BCd was dichotomized at the RCS-derived inflection point (0.7 \u0026mu;g/L). Separate linear regression models estimated \u0026beta;-coefficients (95% CI) for BCd \u0026lt;0.7 \u0026mu;g/L and \u0026ge;0.7 \u0026mu;g/L to quantify threshold-dependent effects.\u003c/p\u003e\n\u003cp\u003eSubgroup Analysis:\u003cbr\u003e Multivariable linear regression evaluated BCd-testosterone associations (per 1 \u0026mu;g/L increase) in prespecified subgroups (smoking status, age strata [\u0026lt;40, 40-60, \u0026ge;60 years], BMI categories [\u0026lt;25, 25-30, \u0026ge;30 kg/m\u0026sup2;], race, education, PIR). Interaction terms (e.g., BCd \u0026times; smoking status) tested effect modification (P\u0026lt;sub\u0026gt;interaction\u0026lt;/sub\u0026gt;\u0026lt;0.05). Heterogeneity was visualized using forest plots (forestplot package).\u003c/p\u003e\n\u003cp\u003eMissing Data Handling:\u003cbr\u003e Key variables (BCd, testosterone, BMI) had \u0026lt;5% missingness (total missing rate: 3.2%). Complete-case analysis was employed since Little\u0026apos;s MCAR test indicated data were missing completely at random (P=0.31).\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Baseline Characteristics\u003c/h2\u003e\u003cp\u003eParticipants with high blood cadmium (BCd\u0026thinsp;\u0026ge;\u0026thinsp;0.7 \u0026micro;g/L) exhibited a notable biological paradox: despite lower socioeconomic status (reduced income-poverty ratio and higher proportion of high school education), this group demonstrated significantly higher serum testosterone levels (451.49 ng/dL vs. 407.01 ng/dL; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to the low-BCd group (\u0026lt;\u0026thinsp;0.7 \u0026micro;g/L). Crucially, the high-BCd group had substantially fewer smokers (5.5% vs. 58.3%; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting smoking may reduce cadmium bioavailability by inducing metallothionein synthesis. Additionally, the high-BCd group had lower BMI (27.42 kg/m\u0026sup2; vs. 29.01 kg/m\u0026sup2;; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), consistent with the physiological link between lean mass and testosterone [18]. After BMI adjustment, the positive BCd-testosterone association persisted (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), indicating BMI is not a core confounder (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBaseline Characteristics of Study Participants Stratified by Blood Cadmium Threshold (0.7 \u0026micro;g/L)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall (n\u0026thinsp;=\u0026thinsp;4,458)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLow BCd\u0026thinsp;\u0026lt;\u0026thinsp;0.7 \u0026micro;g/L (n\u0026thinsp;=\u0026thinsp;3,600)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh BCd\u0026thinsp;\u0026ge;\u0026thinsp;0.7 \u0026micro;g/L (n\u0026thinsp;=\u0026thinsp;858)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBCd (\u0026micro;g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTestosterone (ng/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e414.09\u0026thinsp;\u0026plusmn;\u0026thinsp;4.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e407.01\u0026thinsp;\u0026plusmn;\u0026thinsp;4.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e451.49\u0026thinsp;\u0026plusmn;\u0026thinsp;9.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI(kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoverty-Income Ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlood Lead (\u0026micro;g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlood Mercury (\u0026micro;g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking Status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-smoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e94.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003esmoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRace/Ethnicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMexican American\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther Hispanic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-Hispanic White\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e82.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e87.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;9th grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9-11th grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school graduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSome college\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollege graduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e(Values are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or %; comparisons by Student\u0026rsquo;s t-test, χ\u0026sup2; test, or Mann-Whitney U test; α\u0026thinsp;=\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Segmented Regression Analysis\u003c/h2\u003e\u003cp\u003eA threshold-dependent biphasic association between BCd and testosterone was identified, with an inflection point at 0.7 \u0026micro;g/L. Segmented regression revealed dose-dependent effect attenuation:\u003c/p\u003e\u003cp\u003eLow-exposure segment (BCd\u0026thinsp;\u0026lt;\u0026thinsp;0.7 \u0026micro;g/L): Each 1 \u0026micro;g/L increase in BCd associated with a 93.54 ng/dL surge in testosterone (95% CI: 54.21\u0026ndash;132.88; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eHigh-exposure segment (BCd\u0026thinsp;\u0026ge;\u0026thinsp;0.7 \u0026micro;g/L): Effect magnitude decreased sharply to 18.67 ng/dL (95% CI: 2.94\u0026ndash;34.39; P\u0026thinsp;=\u0026thinsp;0.020).\u003c/p\u003e\u003cp\u003eThis pattern aligns with the classic J-shaped hormesis curve: low-dose Cd may act as a zinc mimetic, competitively binding ZIP8 transporters on Leydig cells to enhance steroidogenesis \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e, while high-dose Cd accumulation triggers oxidative stress and apoptosis that counteract stimulation\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Toxicologically, the 0.7 \u0026micro;g/L inflection point approximates the US population median BCd (0.4 \u0026micro;g/L), indicating that Cd\u0026rsquo;s stimulatory effects dominate at environmental exposure levels (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSegmented Regression Analysis of Blood Cadmium and Testosterone Association\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBCd Range\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eβ (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.7 \u0026micro;g/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e93.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e54.21, 132.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3570\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;0.7 \u0026micro;g/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.94, 34.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e888\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e(β: Change in testosterone [ng/dL] per 1 \u0026micro;g/L increase in blood cadmium,Adjusted for age, BMI, race, education, income-poverty ratio, blood lead, mercury, and smoking status.)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Subgroup Analysis\u003c/h2\u003e\u003cp\u003eSubgroup heterogeneity identified three susceptible populations:\u003c/p\u003e\u003cp\u003eNon-smokers (β\u0026thinsp;=\u0026thinsp;67.8) vs. smokers (β\u0026thinsp;=\u0026thinsp;17.7; P\u0026thinsp;\u0026lt;\u0026thinsp;sub\u0026thinsp;\u0026gt;\u0026thinsp;interaction\u0026lt;/sub\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;0.029), as smoking reduces bioavailable Cd via metallothionein binding and suppresses HPTA axis sensitivity via nicotine-induced GnRH inhibition (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMiddle-aged men (40\u0026ndash;60 years) (β\u0026thinsp;=\u0026thinsp;44.0), potentially reflecting peak HPTA feedback regulation\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e.Low-BMI individuals (\u0026lt;\u0026thinsp;25 kg/m\u0026sup2;) (β\u0026thinsp;=\u0026thinsp;36.0), likely due to reduced adipose Cd sequestration and higher free Cd\u0026sup2;⁺ bioavailability.\u003c/p\u003e\u003cp\u003eThe stimulatory effect of low-dose Cd\u0026mdash;potentially mediated through zinc-mimetic activation of Leydig cell proteins (e.g., CYP19A1, StAR)\u0026mdash;appeared attenuated in obese, older, or smoking individuals. No significant interactions were observed for BMI or race subgroups (P-interaction\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSubgroup Analysis of Blood Cadmium-Testosterone Association\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSubgroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eβ (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-interaction\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22.44 (13.19, 31.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;40 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.51 (-12.40, 21.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.601\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.145\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;60 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22.90 (10.69, 35.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e40\u0026ndash;60 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e44.02 (21.12, 66.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBmi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;25 kg/m\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36.04 (18.56, 53.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.117\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;30 kg/m\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18.13 (2.22, 34.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026ndash;30 kg/m\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15.87 (0.74, 31.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26.11 (5.11, 47.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.957\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15.81 (-2.80, 34.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiddle education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21.99 (9.57, 34.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncome-Poverty Ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePIR\u0026thinsp;\u0026lt;\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30.61 (11.78, 49.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.247\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePIR\u0026thinsp;\u0026gt;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19.26 (4.84, 33.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePIR 1\u0026ndash;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17.63 (1.31, 33.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.034\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRace\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlack\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e34.37 (6.37, 62.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.097\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10.47 (-3.11, 24.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.131\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30.37 (15.70, 45.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-smoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e67.81(31.42,104.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17.75 (7.50, 28.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e(β: Change in testosterone [ng/dL] per 1 \u0026micro;g/L increase in blood cadmium)\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.4. Restricted Cubic Spline (RCS) Analysis\u003c/h2\u003e\u003cp\u003eThe RCS curve demonstrated a monotonically increasing BCd-testosterone relationship (P\u0026thinsp;\u0026lt;\u0026thinsp;sub\u0026thinsp;\u0026gt;\u0026thinsp;trend\u0026lt;/sub\u0026thinsp;\u0026gt;\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with the steepest slope observed at 0.2\u0026ndash;0.7 \u0026micro;g/L (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Beyond 1.5 \u0026micro;g/L, the curve plateaued\u0026mdash;consistent with effect attenuation in the high-exposure segment (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). A latent inflection point at 0.7 \u0026micro;g/L (evidenced by widening confidence intervals) suggests progressive dominance of cytotoxic mechanisms over testosterone stimulation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.5. Forest Plot of Subgroup Analysis\u003c/h2\u003e\u003cp\u003eForest plots confirmed significant effect modification by smoking: the BCd-testosterone association was 3.8-fold stronger in non-smokers (β\u0026thinsp;=\u0026thinsp;67.8, 95% CI: 31.4\u0026ndash;104.2) than smokers (β\u0026thinsp;=\u0026thinsp;17.7, 95% CI: 7.5\u0026ndash;28.0) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In non-smokers, low-dose Cd likely activates zinc-sensitive signaling pathways in Leydig cells, upregulating steroidogenic enzymes. Conversely, in smokers, Cd preferentially forms inert complexes with tobacco-induced metallothionein, reducing bioavailable Cd. Concurrently, nicotine suppresses hypothalamic gonadotropin-releasing hormone (GnRH) release, blunting HPTA axis sensitivity to Cd..\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study provides the first population-level evidence of a\u0026nbsp;threshold-dependent biphasic association\u0026nbsp;between blood cadmium (BCd) and serum testosterone in men, with a critical inflection point at\u0026nbsp;0.7 \u0026mu;g/L. Below this threshold, each 1 \u0026mu;g/L increase in BCd was associated with a\u0026nbsp;93.54 ng/dL surge\u0026nbsp;in testosterone (P\u0026lt;0.001), reflecting low-dose stimulation. Mechanistically, Cd\u0026sup2;⁺ may act as a zinc mimetic, competitively binding ZIP8 zinc transporters on Leydig cells to enhance steroidogenic enzyme activity\u003csup\u003e[19,23,24]\u003c/sup\u003e. Above 0.7 \u0026mu;g/L, the effect attenuated sharply to\u0026nbsp;18.67 ng/dL per \u0026mu;g/L BCd\u0026nbsp;(P=0.020), consistent with Cd-induced cytotoxicity via SOD inhibition, oxidative stress\u003csup\u003e[25,26]\u003c/sup\u003e, and mitochondrial apoptosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSmoking Modifies Cadmium Bioavailability：Non-smokers exhibited a 3.8-fold stronger BCd-testosterone association (\u0026beta;=67.8 vs. smokers\u0026rsquo; \u0026beta;=17.7; P-interaction=0.029). This divergence likely arises from:Metallothionein (MT) induction by tobacco, sequestering Cd into biologically inert complexes \u003csup\u003e[27]\u003c/sup\u003e. Nicotine-mediated suppression of hypothalamic ARNTL expression, inhibiting pulsatile GnRH release and blunting HPTA axis sensitivity\u003csup\u003e[21,22]\u003c/sup\u003e .Middle-aged men (40\u0026ndash;60 years): Peak effect (\u0026beta;=44.0) potentially reflects optimal HPTA negative-feedback regulation, where Cd may amplify androgen signaling via AR coactivators (e.g., SRC-1) \u003csup\u003e[28,29]\u003c/sup\u003e. Low-BMI individuals (\u0026lt;25 kg/m\u0026sup2;): Enhanced effect (\u0026beta;=36.0) likely stems from reduced adipose Cd storage and elevated free Cd\u0026sup2;⁺ bioavailability \u003csup\u003e[30]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWhile this cross-sectional analysis cannot establish temporality, the identified inflection point (0.7 \u0026mu;g/L) warrants validation: Molecular mechanisms: Examine Cd\u0026rsquo;s impact on Leydig cell steroidogenic enzymes (StAR, CYP11A1) and epigenetic regulation (e.g., 2.3-fold increase in ZIP8 promoter methylation\u003csup\u003e[31]\u003c/sup\u003eSubsequent studies should employ prospective cohort studies and cellular experiments (e.g., Leydig cell models) to further validate the underlying mechanisms. Among current internationally accepted standards, the World Health Organization (WHO) has set a provisional guideline value for blood cadmium at 5\u0026nbsp;\u0026mu;g/L. However, the present study demonstrates that significant dose-dependent changes in male testosterone levels occur when blood cadmium exceeds 0.7\u0026nbsp;\u0026mu;g/L, supporting the proposal of 0.7\u0026nbsp;\u0026mu;g/L as an early warning threshold for blood cadmium with respect to endocrine effects.\u003c/p\u003e\n\u003cp\u003eThe significant effect modification induced by smoking underscores the necessity of considering smoking status in cadmium risk assessment and monitoring programs. Men with blood cadmium levels \u0026gt;0.7 \u0026mu;g/L, particularly non-smokers, may require surveillance for potential androgen-related health outcomes. Sensitive populations (including middle-aged individuals and those with low BMI) should be prioritized in surveillance efforts.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study is the first to confirm that there is a non-monotonic relationship between blood cadmium and testosterone in the general population, characterized by low-dose promotion and high-dose inhibition, with a clear threshold-dependent biphasic effect (inflection point at 0.7 \u0026mu;g/L). Future studies need to further explore the molecular targets through which cadmium activates testosterone synthesis; the molecular mechanisms by which smoking attenuates cadmium\u0026apos;s effects via epigenetic regulation (e.g., methylation of metallothionein genes); the establishment of safe thresholds for blood cadmium based on restricted cubic spline (RCS) curves; the need for monitoring the risk of prostate-related diseases associated with elevated testosterone in men with blood cadmium \u0026gt; 0.7 \u0026mu;g/L; and further exploration of the endocrine mechanisms underlying \u0026quot;elevated blood cadmium \u0026rarr; compensatory increase in testosterone\u0026quot;, so as to provide a scientific basis for the stratified prevention and control of reproductive health risks associated with cadmium exposure.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the Key Project of University Collaborative Innovation (HXLH-XTCX11), the Central University Project (31920240072), the Natural Science Foundation of Gansu Province (22JR5RA001, 22KYLL195, 23JRRA531, 23JRRA001), the Science and Technology Project of Lanzhou City (2023-2-63), and the Departmental Scientific Research Project of Gansu Province (2023KYLL205). The funders had no role in the design of the study, data collection, analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAuthor Contributions: Shiwei Song: Conception and design of the study, data analysis and interpretation, drafting the initial manuscript. Bin Zhang: Acquisition of data, assistance with statistical analysis, and critical revision of the manuscript for intellectual content. Chunlei Zhang: Interpretation of results, contribution to the discussion section, and revision of the manuscript. Dehui Chang (corresponding author): Supervision of the entire study, final approval of the manuscript, and responsibility for all aspects of the work to ensure accuracy and integrity. All authors have read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKumar S, Sharma A. 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Molecular Pharmacology, 2006, 70(1): 171-180.\u003c/li\u003e\n\u003cli\u003eYazğan Y, Keleş \u0026Ouml; F, Bayir M H, et al. Selenium Reduces Cadmium-Induced Cardiotoxicity by Modulating Oxidative Stress and the ROS/PARP-1/TRPM2 Signalling Pathway in Rats[J]. Toxics, 2025, 13(8): 611.\u003c/li\u003e\n\u003cli\u003eM\u0026uuml;ller L. Consequences of cadmium toxicity in rat hepatocytes: mitochondrial dysfunction and lipid peroxidation[J]. Toxicology, 1986, 40(3): 285-295.\u003c/li\u003e\n\u003cli\u003eGenome-Wide Identification and Expression Analysis of Heavy Metal Stress\u0026ndash;Responsive Metallothionein Family Genes in Nicotiana tabacum | Plant Molecular Biology Reporter[EB/OL]. [2025-07-25]. \u003c/li\u003e\n\u003cli\u003eYe J, Wang S, Barger M, et al. Activation of androgen response element by cadmium: a potential mechanism for a carcinogenic effect of cadmium in the prostate[J]. Journal of Environmental Pathology, Toxicology and Oncology: Official Organ of the International Society for Environmental Toxicology and Cancer, 2000, 19(3): 275-280.\u003c/li\u003e\n\u003cli\u003eMartin M B, Voeller H J, Gelmann E P, et al. Role of cadmium in the regulation of AR gene expression and activity[J]. Endocrinology, 2002, 143(1): 263-275.\u003c/li\u003e\n\u003cli\u003eLin H C, Hao W M, Chu P H. Cadmium and cardiovascular disease: An overview of pathophysiology, epidemiology, therapy, and predictive value[J]. Revista Portuguesa de Cardiologia (English Edition), 2021, 40(8): 611-617.\u003c/li\u003e\n\u003cli\u003eZhang Y, Wang B, Sun W, et al. Paternal exposures to endocrine-disrupting chemicals induce intergenerational epigenetic influences on offspring: A review[J]. Environment International, 2024, 187: 108689.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Blood cadmium, Testosterone, Biphasic association, Threshold, Restricted cubic splines, Environmental exposure risk assessment","lastPublishedDoi":"10.21203/rs.3.rs-7277696/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7277696/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCadmium (Cd) is a widespread reproductive toxicant conventionally known to suppress testosterone synthesis, but this study first identifies a threshold-dependent biphasic association between blood cadmium (BCd) and serum testosterone in a general male population. Using data from 4,458 US adult males in NHANES (2011-2016), we analyzed nonlinear relationships via restricted cubic splines (RCS) and segmented regression, with subgroup analyses to explore susceptibility. Results revealed a significant biphasic association (Pnonlinear=0.03;Ptrend\u0026lt;0.01), with an inflection point at 0.7 μg/L. Below this threshold, each 1 μg/L increase in BCd was associated with a 93.54 ng/dL rise in testosterone (95% CI:54.21–132.88; P\u0026lt;0.001), while above it, the effect attenuated to 18.67 ng/dL (95% CI:2.94–34.39; P=0.020). Subgroup analyses showed stronger effects in non-smokers (β=67.8 vs. smokers’ β=17.7; Pinteraction=0.029), middle-aged men (40–60 years; β=44.0), and low-BMI individuals (\u0026lt;25 kg/m²; β=36.0). This is the first population-level evidence of Cd-induced testosterone hormesis (low-dose stimulation, high-dose suppression), challenging the linear no-threshold model in Cd risk assessment. The identified 0.7 μg/L threshold informs revisions to environmental standards (e.g., China’s GB 2762-2022) and targeted health monitoring for high-risk subgroups.\u003c/p\u003e","manuscriptTitle":"Threshold-Dependent Biphasic Association of Blood Cadmium with Testosterone in Men: Implications for Environmental Exposure Risk Assessment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-11 16:13:53","doi":"10.21203/rs.3.rs-7277696/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f5d8aed4-82ad-4b96-92b2-b56e77e89980","owner":[],"postedDate":"August 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-27T05:09:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-11 16:13:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7277696","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7277696","identity":"rs-7277696","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}