Association Between Female Reproductive Factors and Melanoma Risk: Analysis of NHANES 2009–2023 Data

Association Between Female Reproductive Factors and Melanoma Risk: Analysis of NHANES 2009–2023 Data | 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 Association Between Female Reproductive Factors and Melanoma Risk: Analysis of NHANES 2009–2023 Data Tian Zhao, Ruxin Xie, Chenyu Li, Shiwei Zhang, Ai Zhong, Junjie Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6651241/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 Melanoma remains a significant public health concern, with an increasing incidence in the United States. Recent studies have explored the potential influence of female reproductive factors on melanoma risk, but findings remain inconsistent. This study utilizes nationally representative NHANES data (2009–2023) to examine the associations between estradiol levels, age at menarche, menopause age, and pregnancy history with melanoma risk. Results indicate that low estradiol levels (0–20 pg/mL) are significantly associated with an increased risk of melanoma (adjusted OR: 3.723, 95% CI: 1.495–9.275, P = 0.006), while the high estradiol group (> 750 pg/mL) lacked sufficient melanoma cases for reliable analysis. Additionally, premature menopause (< 40 years) was linked to a reduced melanoma risk (adjusted OR: 0.476, 95% CI: 0.226–1.000, P = 0.050), though early and late menopause did not demonstrate significant associations. Pregnancy history was not significantly correlated with melanoma risk. These findings offer significant insights into the hormonal influences on melanoma risk, highlighting the need for further research to unravel the underlying biological mechanisms. Figures Figure 1 Figure 2 Introduction Melanoma, as an aggressive form of skin cancer, remains a significant challenge in the field of global public health[1]. Epidemiological data indicate that approximately 100,640 new cases of melanoma will be diagnosed in the United States by 2024, resulting in 8,290 related deaths[2]. Notably, the incidence of melanoma in the U.S. population is significantly higher than in other regions[3]. In recent years, numerous studies have explored the potential associations between female reproductive factors and the risk of melanoma development, including age at menarche, menopausal status, pregnancy history, and exogenous hormone use[4–6]. However, existing research has notable limitations[6–9]. Firstly, small sample sizes may undermine statistical power, reducing the reliability of conclusions. Secondly, the considerable racial heterogeneity within study populations may introduce bias, potentially limiting causal inference and the precise assessment of exposure effects. To address these limitations, this study utilizes the nationally representative the National Health and Nutrition Examination Survey (NHANES) database, expanding the sample size and focusing specifically on the U.S. population, with the aim of more accurately evaluating the relationship between female reproductive factors and melanoma risk, thereby providing more robust epidemiological evidence for disease prevention[10]. 1. Materials And Methods 1.1. Data Source This study utilized data from NHANES for the years 2009-2023. NHANES is conducted by the National Center for Health Statistics (NCHS), a division of the Centers for Disease Control and Prevention (CDC). It is a nationally representative, stratified, multistage probability cross-sectional survey designed to assess the health and nutritional status of the U.S. population. All NHANES data are publicly available on the CDC's official website (https://www.cdc.gov/nchs/nhanes/index.htm, accessed April 18, 2024)[10]. The NHANES study protocol has been approved by the NCHS Ethics Review Board (ERB) and adheres to the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants. 1.2. Study Design This study is a cross-sectional study based on NHANES data, aiming to evaluate the impact of female reproductive factors on melanoma prevalence. The study population includes female participants from the NHANES 2009-2023 survey cycles with complete health data. Estradiol data were only available from the NHANES survey cycles 2013-2023 and were included in the analysis accordingly. 1.3. Study Population 1.3.1. Inclusion and Exclusion Criteria Inclusion Criteria: (a) Female participants aged ≥ 20 years. (b) Participants with complete melanoma diagnosis data. (c) Participants with complete reproductive health data, including menarche age, menopause age, pregnancy history, and estradiol. Exclusion Criteria: (a) Participants with missing or incomplete data. (b) Individuals with malignant tumors but lacking detailed medical history. The detailed participant selection process is illustrated in Figure 1, which outlines the inclusion and exclusion criteria applied to the NHANES dataset. 1.3.2. Survey Weighting Given NHANES’s complex sampling design, which incorporates stratification, clustering, and weighting, this study utilized the NHANES-provided sampling weights (WTMEC2YR) to ensure that the findings are representative of the general U.S. population. For the combined 2017–2020 data, a 3.3-year weighting adjustment was applied, while for the 2009–2016 and 2021–2023 data, a 10-year weighting adjustment was used to enhance the accuracy and generalizability of the results. 1.4. Variable Definitions 1.4.1. Outcome Variable Extracting melanoma diagnosis data based on NHANES interview survey data, where melanoma diagnosis is defined as "whether the participant has been diagnosed with melanoma by a doctor." 1.4.2. Exposure Variables Menarche Age: (a) Early menarche (before age 12) (b) Normal menarche (age 12-14) (c) Late menarche (after age 14) Menopause Age: (a) Premature menopause (before age 40) (b) Early menopause (age 40-44) (c) Normal menopause (age 45-54) (d) Late menopause (after age 55) Pregnancy History: (a) Ever pregnant (Yes) (b) Never pregnant (No) Estradiol: (a) Low (0-20) (b) Normal (21-750) (c) High (>750) 1.4.3. Covariates (a) Age (b) Race: Mexican American, Non-Hispanic Black, Non-Hispanic White, Other (c) Marital Status: Married / Unmarried (d) Education Level: High school or below / College or above (e) Smoking Status: Yes / No 1.5. Statistical Analysis This study conducted statistical analyses using R software (version 4.x), considering the impact of NHANES' complex survey design in all analyses. 1.5.1. Descriptive Statistics Baseline Characteristics: categorical variables were presented as frequencies (n, %). Group Comparisons: Categorical variables were compared using the weighted chi-square test (χ² test) [11]. 1.5.2. Correlation Analysis A weighted multivariable logistic regression model was used to assess the association between female reproductive factors and melanoma, calculating odds ratios (OR) and 95% confidence intervals (CI). 1.5.3. Statistical Significance The level of statistical significance was set at two-sided P < 0.05. 2. Result 2.1. Population Characteristics This study separately analyzed the baseline characteristics of the Menstrual Group (2009-2023) and the Estradiol Group (2013-2023), stratified by melanoma diagnosis (Table 1a, Table 1b). In the Menstrual Group (N=7791), melanoma patients (N=75) and non-melanoma participants (N=7716) showed the following differences in demographic and reproductive health factors. Race (P < 0.001): The proportion of Non-Hispanic White individuals was significantly higher among melanoma patients compared to other racial groups (84.0% vs. 44.1%). Education level (P = 0.003): A higher percentage of higher educated individuals (College or above) was observed in the melanoma group (70.7% vs. 52.6%). Age, marital status and smoking status showed no significant differences between the two groups. In the Estradiol Group (N=11716), melanoma patients (N=96) and non-melanoma participants (N=11620) exhibited the following differences in demographics. Age (P < 0.001): Melanoma patients were older, with a significantly higher proportion aged ≥60 years (66.7% vs. 36.1%). Race (P < 0.001): Consistent with the menstrual group, Non-Hispanic Whites (85.4%) were the most predominant among melanoma patients, while Non-Hispanic Blacks and Mexican Americans had lower proportions in the melanoma group. Education level (P = 0.007): The proportion of higher educated individuals (College or above) was significantly higher among melanoma patients (75.0% vs. 61.1%). Marital status and smoking status (P > 0.05) showed no significant differences between the two groups. Characteristic Total (N=7791) No Melanoma (N=7716) Melanoma (N=75) P-value Age (%) 0.110 ≥60 4476(57.5%) 4422(57.3%) 54(72.0%) 20-29 133(1.71%) 132(1.71%) 1(1.33%) 30-39 243(3.12%) 243(3.15%) 0(0.00%) 40-49 677(8.69%) 672(8.71%) 5(6.67%) 50-59 2262(29.0%) 2247(29.1%) 15(20.0%) Race (%) <0.001 Mexican American 907(11.6%) 903(11.7% 4(5.33% Non-Hispanic Black 1716(22.0%) 1714 (22.2%) 2(2.67%) Non-Hispanic White 3469 (44.5%) 3406 (44.1%) 63(84.0%) Other 1699 (21.8%) 1693 (21.9%) 6(8.00%) Marital (%) 0.149 No 3873(49.7%) 3829(49.6%) 44(58.7%) Yes 3918(50.3%) 3887(50.4%) 31(41.3%) Education Level (%) 0.003 College or above 4108(52.7% 4055(52.6%) 53(70.7%) High school or below 3683(47.3%) 3661(47.4%) 22(29.3%) Smoke (%) 0.218 No 4706(60.4%) 4655(60.3%) 51(68.0%) Yes 3085(39.6%) 3061(39.7%) 24(32.0%) Table 1a. Baseline Characteristics of the Menstrual Group (2009-2023), Stratified by Melanoma Status This table presents the baseline characteristics of female participants with complete menstrual-related data from the NHANES 2009-2023 cycles, stratified by melanoma status. Characteristic Total N=11716 No Melanoma N=11620 Melanoma N=96 P-value Age (%) <0.001 ≥60 4254(36.3%) 4190(36.1%) 64(66.7%) 20-29 1694(14.5%) 1692(14.6%) 2(2.08%) 30-39 1922(16.4%) 1916(16.5%) 6(6.25%) 40-49 1896(16.2%) 1888(16.2%) 8(8.33%) 50-59 1950(16.6%) 1934(16.6%) 16(16.7%) Race (%) <0.001 Mexican American 1448(12.4%) 1444 (12.4%) 4(4.17%) Non-Hispanic BLack 2259(19.3%) 2257(19.4%) 2(2.08%) Non-Hispanic White 5004(42.7%) 4922(42.4%) 82(85.4%) Other 3005(25.6%) 2997(25.8%) 8(8.33%) Marital(%) 0.695 No 5442(46.4%) 5395(46.4%) 47(49.0%) Yes 6274(53.6%) 6225(53.6%) 49(51.0%) Education Level (%) 0.007 College or above 7172(61.2%) 7100(61.1%) 72(75.0%) High school or below 4544(38.8%) 4520(38.9%) 24(25.0%) Smoke (%) 0.129 No 7749(66.1%) 7678(66.1%) 71(74.0%) Yes 3967(33.9%) 3942 (33.9%) 25(26.0%) Table 1b. Baseline Characteristics of the Estradiol Group (2013-2023), Stratified by Melanoma Status This table presents the baseline characteristics of female participants with Estradiol measurements from the NHANES 2013-2023 cycles, stratified by melanoma status. 2.2. Association Between Female Reproductive Factors and Melanoma This study analyzed the relationship between estradiol levels, menarche age, menopause age, and pregnancy history with the risk of melanoma, through multivariable weighted logistic regression analysis. The results are presented using unadjusted odds ratio (Unadjusted OR) and adjusted odds ratio (Adjusted OR), with adjustments for potential confounding factors, including age, race, education level, smoking status, and marital status (Table 2, Figure 2). 2.2.1. Association Between Estradiol Levels and Melanoma In both unadjusted and adjusted models, low estradiol levels (0-20 pg/mL) were significantly associated with an increased risk of melanoma compared to the normal estradiol group (21-750 pg/mL). Unadjusted OR = 5.525 (95% CI: 2.882-10.59, P < 0.001), adjusted OR = 3.723 (95% CI: 1.495-9.275, P = 0.006). This indicates that even after adjusting for demographic and lifestyle factors, low estradiol level remains an independent risk factor for melanoma. On the other hand, the high estradiol group (>750 pg/mL) had too few melanoma cases, resulting in an OR estimate of 0.000 (95% CI: 0.000-0.000, P < 0.001), suggesting that the data sparsity limits reliable statistical inference. 2.2.2. Association Between Menarche Age and Melanoma Using normal menarche age (12-14) as the reference group, late menarche (>14) was significantly associated with an increased risk of melanoma. Unadjusted OR = 2.767 (95% CI: 1.296-5.908, P = 0.009), and adjusted OR = 2.375 (95% CI: 1.136-4.963, P = 0.022). Early menarche (<12 years) was not significantly associated with melanoma risk. Unadjusted OR = 2.085 (95% CI: 0.964-4.510, P = 0.062), and adjusted OR = 1.960 (95% CI: 0.907-4.236, P = 0.086). These findings suggest that late menarche (>14 years) may be an independent risk factor for melanoma, whereas early menarche (<12 years) does not show a significant association. 2.2.3. Association Between Menopause Age and Melanoma Using normal menopause age (45-54) as the reference group, early menopause (40-44) and late menopause (≥55) were not significantly associated with melanoma in either model (P > 0.05). Premature menopause (<40 years) showed a significantly reduced risk of melanoma in the unadjusted model. Unadjusted OR = 0.408 (95% CI: 0.209-0.797, P = 0.009), and adjusted OR = 0.476 (95% CI: 0.226-1.000, P = 0.050). This suggests that premature menopause (<40 years) may be associated with a lower risk of melanoma, but the association was marginally significant (P = 0.050) after adjustment, requiring further investigation. 2.2.4. Association Between Pregnancy History and Melanoma Using never pregnant (No) as the reference group, ever pregnant (Yes) was not significantly associated with melanoma risk in either model (P > 0.05). Unadjusted OR = 0.48 (95% CI: 0.172-1.339, P = 0.159), and adjusted OR = 0.601 (95% CI: 0.204-1.774, P = 0.353). These results indicate that pregnancy history was not significantly associated with melanoma risk. Characteristic Unadjusted OR 95%CI P-value (Unadjusted) Adjusted OR 95%CI P-value (Adjusted) Estradiol Normal(21-750) Ref Ref High(>750) 0.000 0.000-0.000 <0.001 0.000 0.000-0.000 <0.001 Low(0-20) 5.525 2.882-10.59 <0.001 3.723 1.495-9.275 0.006 Menarche Age Normal (12-14) Ref Ref Early (14) 2.767 1.296-5.908 0.009 2.375 1.136-4.963 0.022 Menopause Age Normal (45-54) Ref Ref Early (40-44) 0.876 0.396-1.937 0.742 0.973 0.405-2.336 0.950 Late (≥55) 0.579 0.148-2.270 0.43 0.489 0.124-1.921 0.301 Premature (<40) 0.408 0.209-0.797 0.009 0.476 0.226-1.000 0.050 Pregnancy No Ref Ref Yes 0.48 0.172-1.339 0.159 0.601 0.204-1.774 0.353 OR=Odds Ratio, Cl=Confidence Interval Table 2. Multivariable Weighted Logistic Regression Analysis : Association Between Female Reproductive Factors and Melanoma Risk This table presents the unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for the association between female reproductive factors and melanoma risk. The adjusted model accounts for potential confounders, including age, race, education level, smoking status, and marital status. OR (Odds Ratio): The measure of association between an exposure and outcome. CI (Confidence Interval): The range within which the true effect size is expected to lie with 95% confidence. Ref (Reference Group): The comparison group used as the baseline for calculating ORs. P-value: The probability that the observed association occurred by chance. This figure presents the associations between estrogen levels (Estradiol), menarche age (Menarche Age), menopause age (Menopause Age), and pregnancy history (Pregnancy) with melanoma risk, analyzed using both unadjusted (Unadjusted OR) and adjusted (Adjusted OR) logistic regression models. X-axis: Odds Ratio (OR) and 95% Confidence Interval (CI). Y-axis: Variable categories, including estrogen levels, menarche age, menopause age, and pregnancy history. Black squares: OR values corresponding to each factor. Horizontal lines: 95% Confidence Intervals (CI). Left panel: Unadjusted model (Unadjuste OR) results. Right panel: Adjusted model (Adjuste OR) results, adjusted for age, race, education level, marital status, and smoking status. Reference group: The reference category for each factor. 3. Discussion Melanoma is a highly invasive form of skin cancer and remains a significant public health challenge worldwide. Studies have suggested that female hormone levels may play a crucial role in the occurrence and progression of melanoma. The differential expression of estrogen receptors in melanocytes indicates that fluctuations in female hormones may be associated with the risk of melanoma. However, existing research in this field still has several limitations. First, most studies have small sample sizes, making it difficult to draw robust conclusions. Second, the control of confounding factors remains insufficient, particularly concerning key variables such as socioeconomic status, which are often not adequately adjusted. Additionally, the limited representativeness of certain study populations restricts the generalizability of the findings. To address these shortcomings, this study comprehensively analyzed the association between female reproductive factors, including estradiol levels, menarche age, menopause age, and pregnancy history, with the risk of melanoma using NHANES data from 2009–2023. By increasing the sample size and improving the control of confounding factors, this study aims to provide more precise epidemiological evidence on the relationship between reproductive factors and melanoma, thereby offering valuable insights for the prevention and management of the disease. The key findings suggest that low estradiol level and late menarche are associated with an increased risk of melanoma, while premature menopause may be linked to a reduced risk. However, no significant association was found between pregnancy history and melanoma. Our findings indicate that low estradiol levels (0–20 pg/mL) were significantly associated with an increased risk of melanoma, with an adjusted OR of 3.723 (95% CI: 1.495–9.275, P = 0.006). This suggests that estrogen deficiency may play a role in melanoma development. Estrogen has been implicated in multiple cellular pathways, including anti-inflammatory effects, DNA repair mechanisms, and apoptosis regulation, which may contribute to limit cancer progression[12–15]. Straub et al. demonstrated that estrogen modulates innate immunity by regulating the activity of macrophages, dendritic cells, and NK cells[16].This finding aligns with in vitro studies demonstrating that activation of estrogen receptor beta (ERβ) promotes melanocyte apoptosis[17]. Similar findings have been observed in other cancers, including breast, prostate, ovarian, and colon cancer, where ERβ is believed to play a protective role by suppressing tumor initiation and progression[18, 19]. However, population-based studies have shown significant heterogeneity in results. For instance, Mai et al. did not observe a similar association in their cohort of radiologic technologists, potentially due to confounding by occupational ultraviolet radiation exposure[20]. The significantly lower estradiol levels observed in melanoma patients highlight the need for further investigation into hormonal influences on melanocyte biology. However, The high estradiol group (> 750 pg/mL) had too few melanoma cases, resulting in an OR estimate of 0.000 (95% CI: 0.000–0.000, P < 0.001). This suggests that the number of melanoma cases in this group was insufficient for reliable statistical analysis, needing further studies with larger datasets. We observed a significant positive association between late menarche (> 14 years) and melanoma risk. In the adjusted model, late menarche was associated with an increased risk (OR: 2.375, 95% CI: 1.136–4.963, P = 0.022). These findings suggest that a delayed onset of menstruation may contribute to melanoma susceptibility, potentially due to prolonged childhood estrogen deficiency or differences in pubertal hormone exposure. In contrast, early menarche (< 12 years) was not significantly associated with melanoma risk in the adjusted model (P = 0.086). While some previous studies suggest early menarche may be linked to hormone-driven cancers, our results indicate that melanoma risk does not follow this pattern, at least in this population[20]. Our findings suggest that premature menopause (< 40 years) may be associated with a reduced risk of melanoma, with an adjusted OR of 0.476 (95% CI: 0.226-1.000, P = 0.050). While this association was only marginally significant (P = 0.050), it aligns with the prior studies, suggesting that shorter reproductive lifespan and lower cumulative estrogen exposure may be protective against melanoma. However, early (40–44 years) and late menopause (≥ 55 years) did not show significant associations with melanoma risk. Notably, the cumulative effects of estrogen are not fully reflected in menopause. While early menopause leads to a reduction in lifetime estrogen exposure, it is paradoxically associated with a lower risk of melanoma. This apparent contradiction suggests that the underlying mechanisms may differ. Estrogen’s role in melanoma is complex and dual-faceted, depending on the timing of exposure, receptor subtypes, and other physiological factors. ERβ is generally considered to have a protective, anti-tumor effect, inhibiting cell proliferation and promoting apoptosis[17–19]. In contrast, ERα is thought to be pro-tumorigenic, stimulating cell proliferation and suppressing apoptosis[21]. Therefore, the impact of estrogen on melanoma risk may be influenced not only by cumulative exposure but also by the specific window of hormonal influence. Adolescence is a critical period for skin development and immune system maturation[22]. Prolonged low estrogen levels before puberty may impair DNA repair mechanisms or weaken immune surveillance against tumor cells, thereby increasing melanoma susceptibility in later life[23, 24]. Additionally, the potential protective effect of early menopause may be linked to the influence of endogenous estrogen on skin pigmentation and melanocyte activity[25, 26]. Given these complexities, future research should focus on precisely defining estrogen exposure windows, investigating the relative expression of ERα and ERβ, and further elucidating estrogen’s role in melanoma pathogenesis. Postmenopausal estrogen decline may lead to impaired immune surveillance. Pregnancy history was not significantly associated with melanoma risk (adjusted OR = 0.601, P = 0.353). Pregnancy leads to profound hormonal changes, including increased estrogen and progesterone levels, which have been hypothesized to influence melanoma progression. However, our findings suggest that pregnancy does not have a significant long-term effect on melanoma susceptibility. This may be attributed to the fact that the dramatic surge in estradiol and progesterone levels during pregnancy constitutes only transient exposure, failing to induce persistent phenotypic alterations in melanocytes. Notably, our study did not stratify analyses by parity. It should be incorporated in future investigations. The strengths of this study include the use of a large, nationally representative dataset (NHANES 2009–2023), standardized measurements, and a weighted logistic regression approach to account for the complex survey design[27, 28]. Additionally, both unadjusted and adjusted models were presented to account for potential confounders such as age, race, education level, smoking status, and marital status. However, several limitations should be acknowledged. First, causal relationships cannot be established by cross-sectional design. Second, self-reported melanoma diagnosis may result in potential recall bias. Third, the small number of cases in the high estradiol group is too poor to analyze the effect of high estrogen levels on melanoma. Forth, Information on hormone replacement therapy (HRT) or lifetime estrogen exposure was unavailable. 4. Conclusion In conclusion, this study highlights the potential role of female reproductive factors in melanoma risk, particularly the association between low estradiol levels and increased melanoma susceptibility. Additionally, late menarche was found to be a risk factor, while premature menopause (< 40 years) may have a protective effect. Pregnancy history did not show a significant relationship with melanoma risk. Future research should focus on prospective cohort studies, mechanistic investigations into estrogen’s effects on melanocyte biology, and the potential role of exogenous estrogen use in melanoma risk modulation. Expanding the dataset to include more cases with high estradiol levels will also be crucial for a more comprehensive analysis. Declarations Funding information: This work was supported by Natural Science Foundation of Sichuan Province of China(2023NSFSC0667) Author Contribution T.Z. conceived the study, extracted and cleaned NHANES data, performed statistical analysis in R, and drafted the manuscript. R.X. assisted with methodology design and R code validation. C.L. contributed to data curation and preliminary analysis. S.Z. verified data integrity and prepared figures/tables. A.Z. interpreted results and co-wrote the discussion section. J.C. (Corresponding Author) supervised the project, critically revised the manuscript, and handled submission. All authors reviewed and approved the final version. References Arnold, M., et al., Global Burden of Cutaneous Melanoma in 2020 and Projections to 2040. JAMA Dermatol, 2022. 158 (5): p. 495-503. Siegel, R.L., A.N. Giaquinto, and A. Jemal, Cancer statistics, 2024. CA Cancer J Clin, 2024. 74 (1): p. 12-49. Qian, Y., et al., The ongoing racial disparities in melanoma: An analysis of the Surveillance, Epidemiology, and End Results database (1975-2016). J Am Acad Dermatol, 2021. 84 (6): p. 1585-1593. Mancuso, M., et al., Modulation of basal and squamous cell carcinoma by endogenous estrogen in mouse models of skin cancer. Carcinogenesis, 2009. 30 (2): p. 340-7. Bhupathiraju, S.N., et al., Exogenous Hormone Use: Oral Contraceptives, Postmenopausal Hormone Therapy, and Health Outcomes in the Nurses' Health Study. Am J Public Health, 2016. 106 (9): p. 1631-7. Caini, S., et al., Exogenous sex hormones, menstrual and reproductive history, and risk of non-melanoma skin cancer among women: a systematic literature review and meta-analysis. Sci Rep, 2021. 11 (1): p. 8524. Chiavarini, M., et al., Exogenous Hormone Factors in Relation to the Risk of Malignant Melanoma in Women: A Systematic Review and Meta-Analysis. Cancers (Basel), 2022. 14 (13). Li, L., B. Pei, and Y. Feng, Exogenous hormone therapy and non-melanoma skin cancer (keratinocyte carcinoma) risk in women: a systematic review and meta-analysis. BMC Cancer, 2023. 23 (1): p. 946. Perera, E., et al., Incidence and prevalence of non-melanoma skin cancer in Australia: A systematic review. Australas J Dermatol, 2015. 56 (4): p. 258-67. National Health and Nutrition Examination Survey . Available from: https://www.cdc.gov/nchs/nhanes/index.html. Schober, P. and T.R. Vetter, Chi-square Tests in Medical Research. Anesth Analg, 2019. 129 (5): p. 1193. Liu, X., et al., Anti-inflammatory effects of tanshinone IIA on atherosclerostic vessels of ovariectomized ApoE mice are mediated by estrogen receptor activation and through the ERK signaling pathway. Cell Physiol Biochem, 2015. 35 (5): p. 1744-55. Suba, Z., Compensatory Estrogen Signal Is Capable of DNA Repair in Antiestrogen-Responsive Cancer Cells via Activating Mutations. J Oncol, 2020. 2020 : p. 5418365. Lewis-Wambi, J.S. and V.C. Jordan, Estrogen regulation of apoptosis: how can one hormone stimulate and inhibit? Breast Cancer Res, 2009. 11 (3): p. 206. Soares Junior, J.M., et al., Breast cancer survivals and hormone therapy: estrogen and melatonin. Rev Assoc Med Bras (1992), 2023. 69 (10): p. e6910EDI. Straub, R.H., The complex role of estrogens in inflammation. Endocr Rev, 2007. 28 (5): p. 521-74. Barone, I., L. Brusco, and S.A. Fuqua, Estrogen receptor mutations and changes in downstream gene expression and signaling. Clin Cancer Res, 2010. 16 (10): p. 2702-8. Taylor, A.H. and F. Al-Azzawi, Immunolocalisation of oestrogen receptor beta in human tissues. J Mol Endocrinol, 2000. 24 (1): p. 145-55. Fox, E.M., R.J. Davis, and M.A. Shupnik, ERbeta in breast cancer--onlooker, passive player, or active protector? Steroids, 2008. 73 (11): p. 1039-51. Mai, J.Z., et al., Reproductive factors, hormone use, and incidence of melanoma in a cohort of US Radiologic Technologists. Hum Reprod, 2022. 37 (5): p. 1059-1068. Zhou, J.H., et al., Immunohistochemical expression of hormone receptors in melanoma of pregnant women, nonpregnant women, and men. Am J Dermatopathol, 2014. 36 (1): p. 74-9. Gubbels Bupp, M.R., Sex, the aging immune system, and chronic disease. Cell Immunol, 2015. 294 (2): p. 102-10. Kanda, N. and S. Watanabe, Regulatory roles of sex hormones in cutaneous biology and immunology. J Dermatol Sci, 2005. 38 (1): p. 1-7. Das, P.K., et al., Implications of estrogen and its receptors in colorectal carcinoma. Cancer Med, 2023. 12 (4): p. 4367-4379. Mobasher, P., et al., Catamenial Hyperpigmentation: A Review. J Clin Aesthet Dermatol, 2020. 13 (6): p. 18-21. Natale, C.A., et al., Sex steroids regulate skin pigmentation through nonclassical membrane-bound receptors. Elife, 2016. 5 . Czeyda-Pommersheim, F., et al., Melanoma in pregnancy. Abdom Radiol (NY), 2023. 48 (5): p. 1740-1751. Salvini, C., et al., Melanoma and pregnancy. G Ital Dermatol Venereol, 2017. 152 (3): p. 274-285. 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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-6651241","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":476545081,"identity":"e129a9fb-aa78-4345-b3a3-124666920c76","order_by":0,"name":"Tian Zhao","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Tian","middleName":"","lastName":"Zhao","suffix":""},{"id":476545082,"identity":"811477fa-936a-4ab3-87ce-d7284437be08","order_by":1,"name":"Ruxin Xie","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Ruxin","middleName":"","lastName":"Xie","suffix":""},{"id":476545083,"identity":"e88521e3-b83d-4557-93e3-20d5e1841995","order_by":2,"name":"Chenyu Li","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Chenyu","middleName":"","lastName":"Li","suffix":""},{"id":476545084,"identity":"9bf1eb75-5d75-4371-92a2-cb1d0a2dc43d","order_by":3,"name":"Shiwei Zhang","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Shiwei","middleName":"","lastName":"Zhang","suffix":""},{"id":476545085,"identity":"cc8512bf-6826-4d81-a67c-1cee162fb819","order_by":4,"name":"Ai Zhong","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Ai","middleName":"","lastName":"Zhong","suffix":""},{"id":476545086,"identity":"9736d8c5-224a-4449-9782-698e83b55149","order_by":5,"name":"Junjie Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvklEQVRIiWNgGAWjYFCCAwlAQkKGn5n58AOStPBItrOlGZBkF4/BeR4FCaKU8jceePjoRo0Fj/FhHgYDhhqbaIJaJA4cSDbOOSbBY3aY98ADhmNpuQ2EtBgwHEiTzmEDaeFLMGBsOEyUlvTfOf8keIybeQwkiNWSxpzbJsFjwEysFpBfpHP7JHgkDgMDOYEYv/DPOJP4OedbnRx//+HDDz7U2BDWwiBxJgHBScClCtWa9gNEqRsFo2AUjIIRDAAAFTyesxCNqQAAAABJRU5ErkJggg==","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":true,"prefix":"","firstName":"Junjie","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2025-05-13 04:23:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6651241/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6651241/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85732282,"identity":"640857d2-3ec2-4a57-a7fa-4d00472a2fe3","added_by":"auto","created_at":"2025-07-01 07:33:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":45385,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNHANES Data Inclusion and Exclusion Flowchart\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6651241/v1/67427910fc6158f64f9d09ca.png"},{"id":85731643,"identity":"a667eb7b-f816-4f29-b6ac-70d3defee003","added_by":"auto","created_at":"2025-07-01 07:25:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38675,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest Plot of Estrogen Levels, Menstrual Factors, and Melanoma Risk\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6651241/v1/1f687f068cbb4396115824b6.png"},{"id":96485471,"identity":"259a6d5a-be6b-440b-9b6b-950f3185292f","added_by":"auto","created_at":"2025-11-21 16:08:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1237191,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6651241/v1/ae6bea26-21ae-40c1-adec-49a76d01493a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association Between Female Reproductive Factors and Melanoma Risk: Analysis of NHANES 2009–2023 Data","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMelanoma, as an aggressive form of skin cancer, remains a significant challenge in the field of global public health[1]. Epidemiological data indicate that approximately 100,640 new cases of melanoma will be diagnosed in the United States by 2024, resulting in 8,290 related deaths[2]. Notably, the incidence of melanoma in the U.S. population is significantly higher than in other regions[3]. In recent years, numerous studies have explored the potential associations between female reproductive factors and the risk of melanoma development, including age at menarche, menopausal status, pregnancy history, and exogenous hormone use[4\u0026ndash;6]. However, existing research has notable limitations[6\u0026ndash;9]. Firstly, small sample sizes may undermine statistical power, reducing the reliability of conclusions. Secondly, the considerable racial heterogeneity within study populations may introduce bias, potentially limiting causal inference and the precise assessment of exposure effects.\u003c/p\u003e \u003cp\u003eTo address these limitations, this study utilizes the nationally representative the National Health and Nutrition Examination Survey (NHANES) database, expanding the sample size and focusing specifically on the U.S. population, with the aim of more accurately evaluating the relationship between female reproductive factors and melanoma risk, thereby providing more robust epidemiological evidence for disease prevention[10].\u003c/p\u003e"},{"header":"1. Materials And Methods","content":"\u003cp\u003e\u003cstrong\u003e1.1.\u0026nbsp; \u0026nbsp;\u0026nbsp;Data Source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study utilized data from NHANES for the years 2009-2023. NHANES is conducted by the National Center for Health Statistics (NCHS), a division of the Centers for Disease Control and Prevention (CDC). It is a nationally representative, stratified, multistage probability cross-sectional survey designed to assess the health and nutritional status of the U.S. population. All NHANES data are publicly available on the CDC\u0026apos;s official website (https://www.cdc.gov/nchs/nhanes/index.htm, accessed April 18, 2024)[10].\u003c/p\u003e\n\u003cp\u003eThe NHANES study protocol has been approved by the NCHS Ethics Review Board (ERB) and adheres to the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.2.\u0026nbsp; \u0026nbsp;\u0026nbsp;Study Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is a cross-sectional study based on NHANES data, aiming to evaluate the impact of female reproductive factors on melanoma prevalence. The study population includes female participants from the NHANES 2009-2023 survey cycles with complete health data. Estradiol data were only available from the NHANES survey cycles 2013-2023 and were included in the analysis accordingly.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.3.\u0026nbsp; \u0026nbsp;\u0026nbsp;Study Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.3.1.\u0026nbsp; \u0026nbsp;Inclusion and Exclusion Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInclusion Criteria:\u003c/p\u003e\n\u003cp\u003e(a)\u0026nbsp; \u0026nbsp;\u0026nbsp;Female participants aged \u0026ge; 20 years.\u003c/p\u003e\n\u003cp\u003e(b)\u0026nbsp; \u0026nbsp;Participants with complete melanoma diagnosis data.\u003c/p\u003e\n\u003cp\u003e(c)\u0026nbsp; \u0026nbsp;\u0026nbsp;Participants with complete reproductive health data, including menarche age, menopause age, pregnancy history, and estradiol.\u003c/p\u003e\n\u003cp\u003eExclusion Criteria:\u003c/p\u003e\n\u003cp\u003e(a)\u0026nbsp; \u0026nbsp;\u0026nbsp;Participants with missing or incomplete data.\u003c/p\u003e\n\u003cp\u003e(b)\u0026nbsp; \u0026nbsp;Individuals with malignant tumors but lacking detailed medical history.\u003c/p\u003e\n\u003cp\u003eThe detailed participant selection process is illustrated in Figure 1, which outlines the inclusion and exclusion criteria applied to the NHANES dataset.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.3.2.\u0026nbsp; \u0026nbsp;Survey Weighting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven NHANES\u0026rsquo;s complex sampling design, which incorporates stratification, clustering, and weighting, this study utilized the NHANES-provided sampling weights (WTMEC2YR) to ensure that the findings are representative of the general U.S. population.\u003c/p\u003e\n\u003cp\u003eFor the combined 2017\u0026ndash;2020 data, a 3.3-year weighting adjustment was applied, while for the 2009\u0026ndash;2016 and 2021\u0026ndash;2023 data, a 10-year weighting adjustment was used to enhance the accuracy and generalizability of the results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.4.\u0026nbsp; \u0026nbsp;\u0026nbsp;Variable Definitions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.4.1.\u0026nbsp; \u0026nbsp;Outcome Variable\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExtracting melanoma diagnosis data based on NHANES interview survey data, where melanoma diagnosis is defined as \u0026quot;whether the participant has been diagnosed with melanoma by a doctor.\u0026quot;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.4.2.\u0026nbsp; \u0026nbsp;Exposure Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMenarche Age:\u003c/p\u003e\n\u003cp\u003e(a)\u0026nbsp; \u0026nbsp;\u0026nbsp;Early menarche (before age 12)\u003c/p\u003e\n\u003cp\u003e(b)\u0026nbsp; \u0026nbsp;Normal menarche (age 12-14)\u003c/p\u003e\n\u003cp\u003e(c)\u0026nbsp; \u0026nbsp;\u0026nbsp;Late menarche (after age 14)\u003c/p\u003e\n\u003cp\u003eMenopause Age:\u003c/p\u003e\n\u003cp\u003e(a)\u0026nbsp; \u0026nbsp;\u0026nbsp;Premature menopause (before age 40)\u003c/p\u003e\n\u003cp\u003e(b)\u0026nbsp; \u0026nbsp;Early menopause (age 40-44)\u003c/p\u003e\n\u003cp\u003e(c)\u0026nbsp; \u0026nbsp;\u0026nbsp;Normal menopause (age 45-54)\u003c/p\u003e\n\u003cp\u003e(d)\u0026nbsp; \u0026nbsp;Late menopause (after age 55)\u003c/p\u003e\n\u003cp\u003ePregnancy History:\u003c/p\u003e\n\u003cp\u003e(a)\u0026nbsp; \u0026nbsp;\u0026nbsp;Ever pregnant (Yes)\u003c/p\u003e\n\u003cp\u003e(b)\u0026nbsp; \u0026nbsp;Never pregnant (No)\u003c/p\u003e\n\u003cp\u003eEstradiol:\u003c/p\u003e\n\u003cp\u003e(a)\u0026nbsp; \u0026nbsp;\u0026nbsp;Low (0-20)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(b)\u0026nbsp; \u0026nbsp;Normal (21-750)\u003c/p\u003e\n\u003cp\u003e(c)\u0026nbsp; \u0026nbsp;\u0026nbsp;High (\u0026gt;750)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.4.3.\u0026nbsp; \u0026nbsp;Covariates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a)\u0026nbsp; \u0026nbsp;\u0026nbsp;Age\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(b)\u0026nbsp; \u0026nbsp;Race: Mexican American, Non-Hispanic Black, Non-Hispanic White, Other\u003c/p\u003e\n\u003cp\u003e(c)\u0026nbsp; \u0026nbsp;\u0026nbsp;Marital Status: Married / Unmarried\u003c/p\u003e\n\u003cp\u003e(d)\u0026nbsp; \u0026nbsp;Education Level: High school or below / College or above\u003c/p\u003e\n\u003cp\u003e(e)\u0026nbsp; \u0026nbsp;\u0026nbsp;Smoking Status: Yes / No\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.5.\u0026nbsp; \u0026nbsp;\u0026nbsp;Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study conducted statistical analyses using R software (version 4.x), considering the impact of NHANES\u0026apos; complex survey design in all analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.5.1.\u0026nbsp; \u0026nbsp;Descriptive Statistics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBaseline Characteristics: categorical variables were presented as frequencies (n, %).\u003c/p\u003e\n\u003cp\u003eGroup Comparisons: Categorical variables were compared using the weighted chi-square test (\u0026chi;\u0026sup2; test) [11].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.5.2.\u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCorrelation Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA weighted multivariable logistic regression model was used to assess the association between female reproductive factors and melanoma, calculating odds ratios (OR) and 95% confidence intervals (CI).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.5.3.\u0026nbsp; \u0026nbsp;Statistical Significance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe level of statistical significance was set at two-sided P \u0026lt; 0.05.\u003c/p\u003e"},{"header":"2.\tResult","content":"\u003cp\u003e\u003cstrong\u003e2.1.\u0026nbsp;\u0026nbsp;\u0026nbsp; Population Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study separately analyzed the baseline characteristics of the Menstrual Group (2009-2023) and the Estradiol Group (2013-2023), stratified by melanoma diagnosis (Table 1a, Table 1b).\u003c/p\u003e\n\u003cp\u003eIn the Menstrual Group (N=7791), melanoma patients (N=75) and non-melanoma participants (N=7716) showed the following differences in demographic and reproductive health factors. Race (P \u0026lt; 0.001): The proportion of Non-Hispanic White individuals was significantly higher among melanoma patients compared to other racial groups (84.0% vs. 44.1%). Education level (P = 0.003): A higher percentage of higher educated individuals (College or above) was observed in the melanoma group (70.7% vs. 52.6%). Age, marital status and smoking status showed no significant differences between the two groups.\u003c/p\u003e\n\u003cp\u003eIn the Estradiol Group (N=11716), melanoma patients (N=96) and non-melanoma participants (N=11620) exhibited the following differences in demographics. Age (P \u0026lt; 0.001): Melanoma patients were older, with a significantly higher proportion aged \u0026ge;60 years (66.7% vs. 36.1%). Race (P \u0026lt; 0.001): Consistent with the menstrual group, Non-Hispanic Whites (85.4%) were the most predominant among melanoma patients, while Non-Hispanic Blacks and Mexican Americans had lower proportions in the melanoma group. Education level (P = 0.007): The proportion of higher educated individuals (College or above) was significantly higher among melanoma patients (75.0% vs. 61.1%). Marital status and smoking status (P \u0026gt; 0.05) showed no significant differences between the two groups.\u003c/p\u003e\n\u003ctable width=\"567\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e\u003cstrong\u003eTotal\u003cbr /\u003e (N=7791)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e\u003cstrong\u003eNo Melanoma\u003cbr /\u003e (N=7716)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e\u003cstrong\u003eMelanoma\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(N=75)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eAge (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e0.110\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003e\u0026ge;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e4476(57.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e4422(57.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e54(72.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003e20-29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e133(1.71%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e132(1.71%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e1(1.33%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003e30-39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e243(3.12%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e243(3.15%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e0(0.00%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003e40-49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e677(8.69%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e672(8.71%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e5(6.67%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003e50-59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e2262(29.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e2247(29.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e15(20.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eRace (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eMexican American\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e907(11.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e903(11.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e4(5.33%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e1716(22.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e1714 (22.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e2(2.67%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eNon-Hispanic White\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e3469 (44.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e3406 (44.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e63(84.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eOther\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e1699 (21.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e1693 (21.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e6(8.00%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eMarital (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e0.149\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e3873(49.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e3829(49.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e44(58.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e3918(50.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e3887(50.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e31(41.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eEducation Level (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eCollege or above\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e4108(52.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e4055(52.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e53(70.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eHigh school or below\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e3683(47.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e3661(47.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e22(29.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eSmoke (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e0.218\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e4706(60.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e4655(60.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e51(68.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"168\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"106\"\u003e\n\u003cp\u003e3085(39.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e3061(39.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e24(32.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1a. Baseline Characteristics of the Menstrual Group (2009-2023), Stratified by Melanoma Status\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis table presents the baseline characteristics of female participants with complete menstrual-related data from the NHANES 2009-2023 cycles, stratified by melanoma status.\u003c/p\u003e\n\u003ctable width=\"587\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e\u003cstrong\u003eTotal\u003cbr /\u003e N=11716\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e\u003cstrong\u003eNo Melanoma\u003cbr /\u003e N=11620\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e\u003cstrong\u003eMelanoma\u003cbr /\u003e \u0026nbsp;N=96\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"100\"\u003e\n\u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eAge (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"100\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003e\u0026ge;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e4254(36.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e4190(36.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e64(66.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003e20-29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e1694(14.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e1692(14.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e2(2.08%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003e30-39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e1922(16.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e1916(16.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e6(6.25%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003e40-49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e1896(16.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e1888(16.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e8(8.33%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003e50-59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e1950(16.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e1934(16.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e16(16.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eRace (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"100\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eMexican American\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e1448(12.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e1444\u0026nbsp; (12.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e4(4.17%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eNon-Hispanic BLack\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e2259(19.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e2257(19.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e2(2.08%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eNon-Hispanic White\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e5004(42.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e4922(42.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e82(85.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eOther\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e3005(25.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e2997(25.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e8(8.33%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eMarital(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"100\"\u003e\n\u003cp\u003e0.695\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e5442(46.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e5395(46.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e47(49.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e6274(53.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e6225(53.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e49(51.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eEducation Level (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"100\"\u003e\n\u003cp\u003e0.007\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eCollege or above\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e7172(61.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e7100(61.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e72(75.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eHigh school or below\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e4544(38.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e4520(38.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e24(25.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eSmoke (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"100\"\u003e\n\u003cp\u003e0.129\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e7749(66.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e7678(66.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e71(74.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"16\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"153\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e3967(33.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e3942\u0026nbsp; (33.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"93\"\u003e\n\u003cp\u003e25(26.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1b. Baseline Characteristics of the Estradiol Group (2013-2023), Stratified by Melanoma Status\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis table presents the baseline characteristics of female participants with Estradiol measurements from the NHANES 2013-2023 cycles, stratified by melanoma status.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.\u0026nbsp;\u0026nbsp;\u0026nbsp; Association Between Female Reproductive Factors and Melanoma\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study analyzed the relationship between estradiol levels, menarche age, menopause age, and pregnancy history with the risk of melanoma, through multivariable weighted logistic regression analysis. The results are presented using unadjusted odds ratio (Unadjusted OR) and adjusted odds ratio (Adjusted OR), with adjustments for potential confounding factors, including age, race, education level, smoking status, and marital status (Table 2, Figure 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.1.\u0026nbsp;\u0026nbsp; Association Between Estradiol Levels and Melanoma\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn both unadjusted and adjusted models, low estradiol levels (0-20 pg/mL) were significantly associated with an increased risk of melanoma compared to the normal estradiol group (21-750 pg/mL). Unadjusted OR = 5.525 (95% CI: 2.882-10.59, P \u0026lt; 0.001), adjusted OR = 3.723 (95% CI: 1.495-9.275, P = 0.006). This indicates that even after adjusting for demographic and lifestyle factors, low estradiol level remains an independent risk factor for melanoma. On the other hand, the high estradiol group (\u0026gt;750 pg/mL) had too few melanoma cases, resulting in an OR estimate of 0.000 (95% CI: 0.000-0.000, P \u0026lt; 0.001), suggesting that the data sparsity limits reliable statistical inference.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.2.\u0026nbsp;\u0026nbsp; Association Between Menarche Age and Melanoma\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing normal menarche age (12-14) as the reference group, late menarche (\u0026gt;14) was significantly associated with an increased risk of melanoma. Unadjusted OR = 2.767 (95% CI: 1.296-5.908, P = 0.009), and adjusted OR = 2.375 (95% CI: 1.136-4.963, P = 0.022). Early menarche (\u0026lt;12 years) was not significantly associated with melanoma risk. Unadjusted OR = 2.085 (95% CI: 0.964-4.510, P = 0.062), and adjusted OR = 1.960 (95% CI: 0.907-4.236, P = 0.086). These findings suggest that late menarche (\u0026gt;14 years) may be an independent risk factor for melanoma, whereas early menarche (\u0026lt;12 years) does not show a significant association.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.3.\u0026nbsp;\u0026nbsp; Association Between Menopause Age and Melanoma\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing normal menopause age (45-54) as the reference group, early menopause (40-44) and late menopause (\u0026ge;55) were not significantly associated with melanoma in either model (P \u0026gt; 0.05). Premature menopause (\u0026lt;40 years) showed a significantly reduced risk of melanoma in the unadjusted model. Unadjusted OR = 0.408 (95% CI: 0.209-0.797, P = 0.009), and adjusted OR = 0.476 (95% CI: 0.226-1.000, P = 0.050). This suggests that premature menopause (\u0026lt;40 years) may be associated with a lower risk of melanoma, but the association was marginally significant (P = 0.050) after adjustment, requiring further investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.4.\u0026nbsp;\u0026nbsp; Association Between Pregnancy History and Melanoma\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing never pregnant (No) as the reference group, ever pregnant (Yes) was not significantly associated with melanoma risk in either model (P \u0026gt; 0.05). Unadjusted OR = 0.48 (95% CI: 0.172-1.339, P = 0.159), and adjusted OR = 0.601 (95% CI: 0.204-1.774, P = 0.353). These results indicate that pregnancy history was not significantly associated with melanoma risk.\u003c/p\u003e\n\u003ctable width=\"567\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u003cstrong\u003eUnadjusted OR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u003cstrong\u003eP-value (Unadjusted)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003eAdjusted OR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e\u003cstrong\u003eP-value (Adjusted)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003eEstradiol\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eNormal(21-750)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eHigh(\u0026gt;750)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.000-0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.000-0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eLow(0-20)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e5.525\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e2.882-10.59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e3.723\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e1.495-9.275\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.006\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003eMenarche Age\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;Normal (12-14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;Early\u0026nbsp; (\u0026lt;12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e2.085\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.964-4.510\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e0.062\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.960\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.907-4.236\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.086\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;Late (\u0026gt;14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e2.767\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e1.296-5.908\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e0.009\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.375\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e1.136-4.963\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.022\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003eMenopause Age\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Normal (45-54)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Early (40-44)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.876\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.396-1.937\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e0.742\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.973\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.405-2.336\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.950\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Late (\u0026ge;55)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.579\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.148-2.270\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e0.43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.489\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.124-1.921\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.301\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;Premature (\u0026lt;40)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.408\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.209-0.797\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e0.009\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.476\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.226-1.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.050\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003ePregnancy\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; No\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; Yes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.172-1.339\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e0.159\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.601\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.204-1.774\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.353\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\" width=\"567\"\u003e\n\u003cp\u003eOR=Odds Ratio, Cl=Confidence Interval\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Multivariable Weighted Logistic Regression Analysis : Association Between Female Reproductive Factors and Melanoma Risk\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis table presents the unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for the association between female reproductive factors and melanoma risk. The adjusted model accounts for potential confounders, including age, race, education level, smoking status, and marital status. OR (Odds Ratio): The measure of association between an exposure and outcome. CI (Confidence Interval): The range within which the true effect size is expected to lie with 95% confidence. Ref (Reference Group): The comparison group used as the baseline for calculating ORs. P-value: The probability that the observed association occurred by chance.\u003c/p\u003e\n\u003cp\u003eThis figure presents the associations between estrogen levels (Estradiol), menarche age (Menarche Age), menopause age (Menopause Age), and pregnancy history (Pregnancy) with melanoma risk, analyzed using both unadjusted (Unadjusted OR) and adjusted (Adjusted OR) logistic regression models. X-axis: Odds Ratio (OR) and 95% Confidence Interval (CI). Y-axis: Variable categories, including estrogen levels, menarche age, menopause age, and pregnancy history. Black squares: OR values corresponding to each factor. Horizontal lines: 95% Confidence Intervals (CI). Left panel: Unadjusted model (Unadjuste OR) results. Right panel: Adjusted model (Adjuste OR) results, adjusted for age, race, education level, marital status, and smoking status. Reference group: The reference category for each factor.\u003c/p\u003e"},{"header":"3. Discussion","content":"\u003cp\u003eMelanoma is a highly invasive form of skin cancer and remains a significant public health challenge worldwide. Studies have suggested that female hormone levels may play a crucial role in the occurrence and progression of melanoma. The differential expression of estrogen receptors in melanocytes indicates that fluctuations in female hormones may be associated with the risk of melanoma. However, existing research in this field still has several limitations. First, most studies have small sample sizes, making it difficult to draw robust conclusions. Second, the control of confounding factors remains insufficient, particularly concerning key variables such as socioeconomic status, which are often not adequately adjusted. Additionally, the limited representativeness of certain study populations restricts the generalizability of the findings.\u003c/p\u003e \u003cp\u003eTo address these shortcomings, this study comprehensively analyzed the association between female reproductive factors, including estradiol levels, menarche age, menopause age, and pregnancy history, with the risk of melanoma using NHANES data from 2009\u0026ndash;2023. By increasing the sample size and improving the control of confounding factors, this study aims to provide more precise epidemiological evidence on the relationship between reproductive factors and melanoma, thereby offering valuable insights for the prevention and management of the disease. The key findings suggest that low estradiol level and late menarche are associated with an increased risk of melanoma, while premature menopause may be linked to a reduced risk. However, no significant association was found between pregnancy history and melanoma.\u003c/p\u003e \u003cp\u003eOur findings indicate that low estradiol levels (0\u0026ndash;20 pg/mL) were significantly associated with an increased risk of melanoma, with an adjusted OR of 3.723 (95% CI: 1.495\u0026ndash;9.275, P\u0026thinsp;=\u0026thinsp;0.006). This suggests that estrogen deficiency may play a role in melanoma development. Estrogen has been implicated in multiple cellular pathways, including anti-inflammatory effects, DNA repair mechanisms, and apoptosis regulation, which may contribute to limit cancer progression[12\u0026ndash;15]. Straub et al. demonstrated that estrogen modulates innate immunity by regulating the activity of macrophages, dendritic cells, and NK cells[16].This finding aligns with in vitro studies demonstrating that activation of estrogen receptor beta (ERβ) promotes melanocyte apoptosis[17]. Similar findings have been observed in other cancers, including breast, prostate, ovarian, and colon cancer, where ERβ is believed to play a protective role by suppressing tumor initiation and progression[18, 19]. However, population-based studies have shown significant heterogeneity in results. For instance, Mai et al. did not observe a similar association in their cohort of radiologic technologists, potentially due to confounding by occupational ultraviolet radiation exposure[20]. The significantly lower estradiol levels observed in melanoma patients highlight the need for further investigation into hormonal influences on melanocyte biology. However, The high estradiol group (\u0026gt;\u0026thinsp;750 pg/mL) had too few melanoma cases, resulting in an OR estimate of 0.000 (95% CI: 0.000\u0026ndash;0.000, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This suggests that the number of melanoma cases in this group was insufficient for reliable statistical analysis, needing further studies with larger datasets.\u003c/p\u003e \u003cp\u003eWe observed a significant positive association between late menarche (\u0026gt;\u0026thinsp;14 years) and melanoma risk. In the adjusted model, late menarche was associated with an increased risk (OR: 2.375, 95% CI: 1.136\u0026ndash;4.963, P\u0026thinsp;=\u0026thinsp;0.022). These findings suggest that a delayed onset of menstruation may contribute to melanoma susceptibility, potentially due to prolonged childhood estrogen deficiency or differences in pubertal hormone exposure. In contrast, early menarche (\u0026lt;\u0026thinsp;12 years) was not significantly associated with melanoma risk in the adjusted model (P\u0026thinsp;=\u0026thinsp;0.086). While some previous studies suggest early menarche may be linked to hormone-driven cancers, our results indicate that melanoma risk does not follow this pattern, at least in this population[20].\u003c/p\u003e \u003cp\u003eOur findings suggest that premature menopause (\u0026lt;\u0026thinsp;40 years) may be associated with a reduced risk of melanoma, with an adjusted OR of 0.476 (95% CI: 0.226-1.000, P\u0026thinsp;=\u0026thinsp;0.050). While this association was only marginally significant (P\u0026thinsp;=\u0026thinsp;0.050), it aligns with the prior studies, suggesting that shorter reproductive lifespan and lower cumulative estrogen exposure may be protective against melanoma. However, early (40\u0026ndash;44 years) and late menopause (\u0026ge;\u0026thinsp;55 years) did not show significant associations with melanoma risk. Notably, the cumulative effects of estrogen are not fully reflected in menopause. While early menopause leads to a reduction in lifetime estrogen exposure, it is paradoxically associated with a lower risk of melanoma. This apparent contradiction suggests that the underlying mechanisms may differ. Estrogen\u0026rsquo;s role in melanoma is complex and dual-faceted, depending on the timing of exposure, receptor subtypes, and other physiological factors. ERβ is generally considered to have a protective, anti-tumor effect, inhibiting cell proliferation and promoting apoptosis[17\u0026ndash;19]. In contrast, ERα is thought to be pro-tumorigenic, stimulating cell proliferation and suppressing apoptosis[21]. Therefore, the impact of estrogen on melanoma risk may be influenced not only by cumulative exposure but also by the specific window of hormonal influence. Adolescence is a critical period for skin development and immune system maturation[22]. Prolonged low estrogen levels before puberty may impair DNA repair mechanisms or weaken immune surveillance against tumor cells, thereby increasing melanoma susceptibility in later life[23, 24]. Additionally, the potential protective effect of early menopause may be linked to the influence of endogenous estrogen on skin pigmentation and melanocyte activity[25, 26]. Given these complexities, future research should focus on precisely defining estrogen exposure windows, investigating the relative expression of ERα and ERβ, and further elucidating estrogen\u0026rsquo;s role in melanoma pathogenesis. Postmenopausal estrogen decline may lead to impaired immune surveillance.\u003c/p\u003e \u003cp\u003ePregnancy history was not significantly associated with melanoma risk (adjusted OR\u0026thinsp;=\u0026thinsp;0.601, P\u0026thinsp;=\u0026thinsp;0.353). Pregnancy leads to profound hormonal changes, including increased estrogen and progesterone levels, which have been hypothesized to influence melanoma progression. However, our findings suggest that pregnancy does not have a significant long-term effect on melanoma susceptibility. This may be attributed to the fact that the dramatic surge in estradiol and progesterone levels during pregnancy constitutes only transient exposure, failing to induce persistent phenotypic alterations in melanocytes. Notably, our study did not stratify analyses by parity. It should be incorporated in future investigations.\u003c/p\u003e \u003cp\u003eThe strengths of this study include the use of a large, nationally representative dataset (NHANES 2009\u0026ndash;2023), standardized measurements, and a weighted logistic regression approach to account for the complex survey design[27, 28]. Additionally, both unadjusted and adjusted models were presented to account for potential confounders such as age, race, education level, smoking status, and marital status.\u003c/p\u003e \u003cp\u003eHowever, several limitations should be acknowledged. First, causal relationships cannot be established by cross-sectional design. Second, self-reported melanoma diagnosis may result in potential recall bias. Third, the small number of cases in the high estradiol group is too poor to analyze the effect of high estrogen levels on melanoma. Forth, Information on hormone replacement therapy (HRT) or lifetime estrogen exposure was unavailable.\u003c/p\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eIn conclusion, this study highlights the potential role of female reproductive factors in melanoma risk, particularly the association between low estradiol levels and increased melanoma susceptibility. Additionally, late menarche was found to be a risk factor, while premature menopause (\u0026lt;\u0026thinsp;40 years) may have a protective effect. Pregnancy history did not show a significant relationship with melanoma risk.\u003c/p\u003e \u003cp\u003eFuture research should focus on prospective cohort studies, mechanistic investigations into estrogen\u0026rsquo;s effects on melanocyte biology, and the potential role of exogenous estrogen use in melanoma risk modulation. Expanding the dataset to include more cases with high estradiol levels will also be crucial for a more comprehensive analysis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding information:\u003c/h2\u003e \u003cp\u003eThis work was supported by Natural Science Foundation of Sichuan Province of China(2023NSFSC0667)\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eT.Z. conceived the study, extracted and cleaned NHANES data, performed statistical analysis in R, and drafted the manuscript. R.X. assisted with methodology design and R code validation. C.L. contributed to data curation and preliminary analysis. S.Z. verified data integrity and prepared figures/tables. A.Z. interpreted results and co-wrote the discussion section. J.C. (Corresponding Author) supervised the project, critically revised the manuscript, and handled submission. All authors reviewed and approved the final version.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArnold, M., et al., \u003cem\u003eGlobal Burden of Cutaneous Melanoma in 2020 and Projections to 2040.\u003c/em\u003e JAMA Dermatol, 2022. \u003cstrong\u003e158\u003c/strong\u003e(5): p. 495-503.\u003c/li\u003e\n\u003cli\u003eSiegel, R.L., A.N. Giaquinto, and A. Jemal, \u003cem\u003eCancer statistics, 2024.\u003c/em\u003e CA Cancer J Clin, 2024. \u003cstrong\u003e74\u003c/strong\u003e(1): p. 12-49.\u003c/li\u003e\n\u003cli\u003eQian, Y., et al., \u003cem\u003eThe ongoing racial disparities in melanoma: An analysis of the Surveillance, Epidemiology, and End Results database (1975-2016).\u003c/em\u003e J Am Acad Dermatol, 2021. \u003cstrong\u003e84\u003c/strong\u003e(6): p. 1585-1593.\u003c/li\u003e\n\u003cli\u003eMancuso, M., et al., \u003cem\u003eModulation of basal and squamous cell carcinoma by endogenous estrogen in mouse models of skin cancer.\u003c/em\u003e Carcinogenesis, 2009. \u003cstrong\u003e30\u003c/strong\u003e(2): p. 340-7.\u003c/li\u003e\n\u003cli\u003eBhupathiraju, S.N., et al., \u003cem\u003eExogenous Hormone Use: Oral Contraceptives, Postmenopausal Hormone Therapy, and Health Outcomes in the Nurses' Health Study.\u003c/em\u003e Am J Public Health, 2016. \u003cstrong\u003e106\u003c/strong\u003e(9): p. 1631-7.\u003c/li\u003e\n\u003cli\u003eCaini, S., et al., \u003cem\u003eExogenous sex hormones, menstrual and reproductive history, and risk of non-melanoma skin cancer among women: a systematic literature review and meta-analysis.\u003c/em\u003e Sci Rep, 2021. \u003cstrong\u003e11\u003c/strong\u003e(1): p. 8524.\u003c/li\u003e\n\u003cli\u003eChiavarini, M., et al., \u003cem\u003eExogenous Hormone Factors in Relation to the Risk of Malignant Melanoma in Women: A Systematic Review and Meta-Analysis.\u003c/em\u003e Cancers (Basel), 2022. \u003cstrong\u003e14\u003c/strong\u003e(13).\u003c/li\u003e\n\u003cli\u003eLi, L., B. Pei, and Y. Feng, \u003cem\u003eExogenous hormone therapy and non-melanoma skin cancer (keratinocyte carcinoma) risk in women: a systematic review and meta-analysis.\u003c/em\u003e BMC Cancer, 2023. \u003cstrong\u003e23\u003c/strong\u003e(1): p. 946.\u003c/li\u003e\n\u003cli\u003ePerera, E., et al., \u003cem\u003eIncidence and prevalence of non-melanoma skin cancer in Australia: A systematic review.\u003c/em\u003e Australas J Dermatol, 2015. \u003cstrong\u003e56\u003c/strong\u003e(4): p. 258-67.\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eNational Health and Nutrition Examination Survey\u003c/em\u003e. Available from: https://www.cdc.gov/nchs/nhanes/index.html.\u003c/li\u003e\n\u003cli\u003eSchober, P. and T.R. Vetter, \u003cem\u003eChi-square Tests in Medical Research.\u003c/em\u003e Anesth Analg, 2019. \u003cstrong\u003e129\u003c/strong\u003e(5): p. 1193.\u003c/li\u003e\n\u003cli\u003eLiu, X., et al., \u003cem\u003eAnti-inflammatory effects of tanshinone IIA on atherosclerostic vessels of ovariectomized ApoE mice are mediated by estrogen receptor activation and through the ERK signaling pathway.\u003c/em\u003e Cell Physiol Biochem, 2015. \u003cstrong\u003e35\u003c/strong\u003e(5): p. 1744-55.\u003c/li\u003e\n\u003cli\u003eSuba, Z., \u003cem\u003eCompensatory Estrogen Signal Is Capable of DNA Repair in Antiestrogen-Responsive Cancer Cells via Activating Mutations.\u003c/em\u003e J Oncol, 2020. \u003cstrong\u003e2020\u003c/strong\u003e: p. 5418365.\u003c/li\u003e\n\u003cli\u003eLewis-Wambi, J.S. and V.C. Jordan, \u003cem\u003eEstrogen regulation of apoptosis: how can one hormone stimulate and inhibit?\u003c/em\u003e Breast Cancer Res, 2009. \u003cstrong\u003e11\u003c/strong\u003e(3): p. 206.\u003c/li\u003e\n\u003cli\u003eSoares Junior, J.M., et al., \u003cem\u003eBreast cancer survivals and hormone therapy: estrogen and melatonin.\u003c/em\u003e Rev Assoc Med Bras (1992), 2023. \u003cstrong\u003e69\u003c/strong\u003e(10): p. e6910EDI.\u003c/li\u003e\n\u003cli\u003eStraub, R.H., \u003cem\u003eThe complex role of estrogens in inflammation.\u003c/em\u003e Endocr Rev, 2007. \u003cstrong\u003e28\u003c/strong\u003e(5): p. 521-74.\u003c/li\u003e\n\u003cli\u003eBarone, I., L. Brusco, and S.A. Fuqua, \u003cem\u003eEstrogen receptor mutations and changes in downstream gene expression and signaling.\u003c/em\u003e Clin Cancer Res, 2010. \u003cstrong\u003e16\u003c/strong\u003e(10): p. 2702-8.\u003c/li\u003e\n\u003cli\u003eTaylor, A.H. and F. Al-Azzawi, \u003cem\u003eImmunolocalisation of oestrogen receptor beta in human tissues.\u003c/em\u003e J Mol Endocrinol, 2000. \u003cstrong\u003e24\u003c/strong\u003e(1): p. 145-55.\u003c/li\u003e\n\u003cli\u003eFox, E.M., R.J. Davis, and M.A. Shupnik, \u003cem\u003eERbeta in breast cancer--onlooker, passive player, or active protector?\u003c/em\u003e Steroids, 2008. \u003cstrong\u003e73\u003c/strong\u003e(11): p. 1039-51.\u003c/li\u003e\n\u003cli\u003eMai, J.Z., et al., \u003cem\u003eReproductive factors, hormone use, and incidence of melanoma in a cohort of US Radiologic Technologists.\u003c/em\u003e Hum Reprod, 2022. \u003cstrong\u003e37\u003c/strong\u003e(5): p. 1059-1068.\u003c/li\u003e\n\u003cli\u003eZhou, J.H., et al., \u003cem\u003eImmunohistochemical expression of hormone receptors in melanoma of pregnant women, nonpregnant women, and men.\u003c/em\u003e Am J Dermatopathol, 2014. \u003cstrong\u003e36\u003c/strong\u003e(1): p. 74-9.\u003c/li\u003e\n\u003cli\u003eGubbels Bupp, M.R., \u003cem\u003eSex, the aging immune system, and chronic disease.\u003c/em\u003e Cell Immunol, 2015. \u003cstrong\u003e294\u003c/strong\u003e(2): p. 102-10.\u003c/li\u003e\n\u003cli\u003eKanda, N. and S. Watanabe, \u003cem\u003eRegulatory roles of sex hormones in cutaneous biology and immunology.\u003c/em\u003e J Dermatol Sci, 2005. \u003cstrong\u003e38\u003c/strong\u003e(1): p. 1-7.\u003c/li\u003e\n\u003cli\u003eDas, P.K., et al., \u003cem\u003eImplications of estrogen and its receptors in colorectal carcinoma.\u003c/em\u003e Cancer Med, 2023. \u003cstrong\u003e12\u003c/strong\u003e(4): p. 4367-4379.\u003c/li\u003e\n\u003cli\u003eMobasher, P., et al., \u003cem\u003eCatamenial Hyperpigmentation: A Review.\u003c/em\u003e J Clin Aesthet Dermatol, 2020. \u003cstrong\u003e13\u003c/strong\u003e(6): p. 18-21.\u003c/li\u003e\n\u003cli\u003eNatale, C.A., et al., \u003cem\u003eSex steroids regulate skin pigmentation through nonclassical membrane-bound receptors.\u003c/em\u003e Elife, 2016. \u003cstrong\u003e5\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eCzeyda-Pommersheim, F., et al., \u003cem\u003eMelanoma in pregnancy.\u003c/em\u003e Abdom Radiol (NY), 2023. \u003cstrong\u003e48\u003c/strong\u003e(5): p. 1740-1751.\u003c/li\u003e\n\u003cli\u003eSalvini, C., et al., \u003cem\u003eMelanoma and pregnancy.\u003c/em\u003e G Ital Dermatol Venereol, 2017. \u003cstrong\u003e152\u003c/strong\u003e(3): p. 274-285.\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":"","lastPublishedDoi":"10.21203/rs.3.rs-6651241/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6651241/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMelanoma remains a significant public health concern, with an increasing incidence in the United States. Recent studies have explored the potential influence of female reproductive factors on melanoma risk, but findings remain inconsistent. This study utilizes nationally representative NHANES data (2009\u0026ndash;2023) to examine the associations between estradiol levels, age at menarche, menopause age, and pregnancy history with melanoma risk. Results indicate that low estradiol levels (0\u0026ndash;20 pg/mL) are significantly associated with an increased risk of melanoma (adjusted OR: 3.723, 95% CI: 1.495\u0026ndash;9.275, P\u0026thinsp;=\u0026thinsp;0.006), while the high estradiol group (\u0026gt;\u0026thinsp;750 pg/mL) lacked sufficient melanoma cases for reliable analysis. Additionally, premature menopause (\u0026lt;\u0026thinsp;40 years) was linked to a reduced melanoma risk (adjusted OR: 0.476, 95% CI: 0.226\u0026ndash;1.000, P\u0026thinsp;=\u0026thinsp;0.050), though early and late menopause did not demonstrate significant associations. Pregnancy history was not significantly correlated with melanoma risk. These findings offer significant insights into the hormonal influences on melanoma risk, highlighting the need for further research to unravel the underlying biological mechanisms.\u003c/p\u003e","manuscriptTitle":"Association Between Female Reproductive Factors and Melanoma Risk: Analysis of NHANES 2009–2023 Data","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-01 07:25:43","doi":"10.21203/rs.3.rs-6651241/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":"b8b9fc88-766c-47d5-83a2-b6bddfad9556","owner":[],"postedDate":"July 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-21T16:08:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-01 07:25:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6651241","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6651241","identity":"rs-6651241","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}