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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Nutr.</journal-id>
<journal-title>Frontiers in Nutrition</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Nutr.</abbrev-journal-title>
<issn pub-type="epub">2296-861X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fnut.2025.1623490</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Nutrition</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Vitamins improve the effect of heavy metal exposure in arthritis after hysterectomy</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Xu</surname> <given-names>Binkai</given-names></name>
<xref ref-type="author-notes" rid="fn0001"><sup>&#x2020;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3133851/overview"/>
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</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Wu</surname> <given-names>Xian</given-names></name>
<xref ref-type="author-notes" rid="fn0001"><sup>&#x2020;</sup></xref>
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<contrib contrib-type="author" corresp="yes">
<name><surname>Liu</surname> <given-names>Zhiwei</given-names></name>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Yu</surname> <given-names>Bin</given-names></name>
<xref ref-type="corresp" rid="c002"><sup>&#x002A;</sup></xref>
<xref ref-type="author-notes" rid="fn0002"><sup>&#x2021;</sup></xref>
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<aff><institution>Changzhou Maternal and Child Health Care Hospital, Changzhou Medical Center of Nanjing Medical University</institution>, <addr-line>Changzhou</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0003">
<p>Edited by: Ahmed Y. Azzam, Albert Einstein College of Medicine, United States</p>
</fn>
<fn fn-type="edited-by" id="fn0004">
<p>Reviewed by: Djandan Tadum Arthur Vithran, Central South University, China</p>
<p>Mahmoud M. Morsy, October 6 University, Egypt</p>
<p>Dinesh Kumar Lakshmanan, Vinayaka Missions University, India</p>
</fn>
<corresp id="c001">&#x002A;Correspondence: Zhiwei Liu, <email>lzwei117@163.com</email></corresp>
<corresp id="c002">Bin Yu, <email>binyu@njmu.edu.cn</email></corresp>
<fn fn-type="equal" id="fn0001"><p><sup>&#x2020;</sup>These authors have contributed equally to this work</p></fn>
<fn fn-type="other" id="fn0002"><p><sup>&#x2021;</sup>ORCID: Bin Yu, <ext-link ext-link-type="uri" xlink:href="https://orcid.org/0000-0001-7796-7314">orcid.org/0000-0001-7796-7314</ext-link></p></fn>
</author-notes>
<pub-date pub-type="epub">
<day>04</day>
<month>08</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>12</volume>
<elocation-id>1623490</elocation-id>
<history>
<date date-type="received">
<day>06</day>
<month>05</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>14</day>
<month>07</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2025 Xu, Wu, Liu and Yu.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Xu, Wu, Liu and Yu</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec id="sec1">
<title>Background</title>
<p>The interplay between gynaecological surgeries and arthritis pathogenesis remains poorly understood. This study offers new insights into potential health risks associated with post-hysterectomy.</p>
</sec>
<sec id="sec2">
<title>Methods</title>
<p>The cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018, which cannot establish the causation. The effects of five serum heavy metal and nine vitamin intakes were evaluated.</p>
</sec>
<sec id="sec3">
<title>Results</title>
<p>A total of 3,121 participants with complete data from NHANES (2007&#x202F;~&#x202F;2018) were included in this study. The prevalence of arthritis among participants having undergone hysterectomy was significantly increased (58.25% vs. 31.64%, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001). Meanwhile, the levels of blood lead were significantly increased in women having undergone gynaecological surgery (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001) and women with arthritis (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001). After additionally adjusting, hysterectomy was still associated with an increased risk of arthritis (OR&#x202F;=&#x202F;3.33, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.0001). A non-linear (L-shaped) relationship was observed in blood lead, mercury, and cadmium (<italic>p</italic> for non-linearity &#x003C;0.001). Blood lead was the highest weighted quantile sum (WQS) weigh among five heavy metals, with the highest contributions of 0.72. Mediation analysis demonstrated that blood lead accounted for 6.02% of the observed association between hysterectomy and arthritis (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001). The RCS curves confirmed that there was a non-linear (L-shaped) relationship between vitamin K, vitamin D, and the risk of arthritis caused by hysterectomy (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001).</p>
</sec>
<sec id="sec4">
<title>Conclusion</title>
<p>Hysterectomy is associated with an increased risk of arthritis, with a focus on blood lead as a mediating factor and vitamin intake as a potential protective factor. It will contribute to the long-term health management after hysterectomy.</p>
</sec>
</abstract>
<kwd-group>
<kwd>hysterectomy</kwd>
<kwd>arthritis</kwd>
<kwd>heavy metal</kwd>
<kwd>lead</kwd>
<kwd>vitamin</kwd>
</kwd-group>
<counts>
<fig-count count="5"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="37"/>
<page-count count="10"/>
<word-count count="5865"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Clinical Nutrition</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="sec5">
<title>Highlighting</title>
<list list-type="bullet">
<list-item>
<p>The first large-scale epidemiological investigation systematically evaluated the relationship between hysterectomy and arthritis risk in women, with a focus on elucidating the mediating role of serum heavy metals (particularly blood lead) and the protective effects of dietary micronutrients (notably vitamin K and vitamin D).</p>
</list-item>
<list-item>
<p>Hysterectomy, especially when combined with oophorectomy, is independently associated with a 3.3&#x202F;~&#x202F;4.7-fold increased risk of arthritis in women.</p>
</list-item>
<list-item>
<p>Elevated blood lead levels mediate approximately 6% of this association, exhibiting a non-linear threshold effect.</p>
</list-item>
<list-item>
<p>Higher dietary intake of vitamin K and vitamin D significantly attenuates arthritis risk in hysterectomized women, with protective thresholds identified at 212.0mcg/day and 10.8 mcg/day, respectively.</p>
</list-item>
</list>
</sec>
<sec sec-type="intro" id="sec6">
<title>Introduction</title>
<p>As the most common gynecologic operation, approximately 600,000 hysterectomies are performed annually in the United States for common gynaecologic benign indications, such as uterine fibroids, abnormal uterine bleeding, endometriosis, and pelvic organ prolapse (<xref ref-type="bibr" rid="ref1">1</xref>). Although its prevalence has declined recently, hysterectomy continues to carry significant long-term health implications (<xref ref-type="bibr" rid="ref2 ref3 ref4">2&#x2013;4</xref>). Recent studies have suggested that there were associations between hysterectomy and increased risks of cardiovascular disease (<xref ref-type="bibr" rid="ref5">5</xref>), stroke (<xref ref-type="bibr" rid="ref6">6</xref>), metabolic disorders (<xref ref-type="bibr" rid="ref7">7</xref>), kidney stone disease (<xref ref-type="bibr" rid="ref8">8</xref>), and osteoporosis (<xref ref-type="bibr" rid="ref9">9</xref>).</p>
<p>Arthritis, encompassing osteoarthritis (OA), rheumatoid arthritis (RA), and related inflammatory joint diseases, disproportionately affects women (<xref ref-type="bibr" rid="ref10">10</xref>). Hormonal fluctuations, genetic predisposition, obesity, and aging are established contributors. Postmenopausal women, in particular, face elevated risks due to estrogen depletion, which exacerbates joint inflammation and cartilage degradation (<xref ref-type="bibr" rid="ref11">11</xref>). Beyond hormonal factors, environmental exposures, including heavy metals, and nutritional deficiencies have recently emerged as modifiable risk factors (<xref ref-type="bibr" rid="ref12">12</xref>, <xref ref-type="bibr" rid="ref13">13</xref>). However, the interplay between gynaecological surgeries and arthritis pathogenesis remains poorly understood.</p>
<p>Bone health of women after hysterectomy is a brand-new study field. Its potential role in arthritis remains underexplored. Relatively, it is clear at present that hysterectomy is related to female osteoporosis. Seo and Yuk (<xref ref-type="bibr" rid="ref9">9</xref>), Choi et al. (<xref ref-type="bibr" rid="ref14">14</xref>), and Xu et al. (<xref ref-type="bibr" rid="ref15">15</xref>) reported that the risk of osteoporosis was increased in women who had undergone hysterectomy regardless of bilateral oophorectomy status. The adjusted odds ratios (ORs) were 1.28&#x202F;~&#x202F;1.84. However, whether it also increases the risk of fracture was controversial (<xref ref-type="bibr" rid="ref9">9</xref>, <xref ref-type="bibr" rid="ref15">15</xref>). In relation to arthritis, studies are even rarer. In J St&#x00F6;ve&#x2019;s group, 86.2% patients after hysterectomy developed bilateral OA and 33.3% occurred generalized OA (<xref ref-type="bibr" rid="ref16">16</xref>). Recently, a Taiwanese cohort study further identified hysterectomy as an independent risk factor for osteoarthritis, especially knee OA (adjusted OR&#x202F;=&#x202F;1.25, 95%CI&#x202F;=&#x202F;1.13&#x2013;1.38) (<xref ref-type="bibr" rid="ref17">17</xref>). They speculated that it might be related to estrogen deficiency. No further research has been carried out.</p>
<p>In recent years, the role of heavy metals in the occurrence and the development of arthritis have attracted much attention, with primary focus on arsenic, cadmium, zinc, and lead (<xref ref-type="bibr" rid="ref18">18</xref>, <xref ref-type="bibr" rid="ref19">19</xref>). It is generally acknowledged that the high exposure of heavy metals may be a synergistic risk factor associated with arthritis. Interestingly, the intake of some micronutrients may reverse such damage (<xref ref-type="bibr" rid="ref20">20</xref>, <xref ref-type="bibr" rid="ref21">21</xref>). However, there is still a lack of large cohort clinical studies. Meanwhile, hysterectomy may indirectly influence these metals. For instance, estrogen deficiency post-surgery could impair heavy metal detoxification pathways, increasing their long-term exposure (<xref ref-type="bibr" rid="ref22">22</xref>, <xref ref-type="bibr" rid="ref23">23</xref>). In addition, heavy metals may also acts as potent xenoestrogens with the risk to human health (<xref ref-type="bibr" rid="ref24">24</xref>). In summary, the relationship among hysterectomy, arthritis, heavy metals, and micronutrients is highly complicated.</p>
<p>In order to explore this scientific problem, from the National Health and Nutrition Examination Survey (NHANES) (<xref ref-type="bibr" rid="ref25">25</xref>, <xref ref-type="bibr" rid="ref26">26</xref>), we investigated the relationship between hysterectomy and arthritis and explored the role of heavy metals and the protective effect of vitamins. This study offers new insights into potential health risks associated with post-hysterectomy and hope to contribute to improving public health outcomes.</p>
</sec>
<sec sec-type="materials|methods" id="sec7">
<title>Materials and methods</title>
<sec id="sec8">
<title>Data source and study population</title>
<p>The cross-sectional study was from the NHANES, and the cross-sectional design limits the ability to establish causality. The participant&#x2019;s selection is illustrated in <xref ref-type="fig" rid="fig1">Figure 1</xref>. Of 59,842 initial subjects from the NHANES (2007&#x2013;2018), 29,629 were excluded due to gender. A total of 20,198 were excluded due to incomplete data on age, education level, race, poverty ratio, smoking status, drink statue, and body mass index (BMI). A total of 1,865 were excluded due to missing data on hysterectomy and the data on arthritis. A total of 5,029 were excluded due to missing data on blood heavy metals and total nutrient intakes. Finally, 3,121 women were included in this study. According to whether they had undergone hysterectomy and/or oophorectomy, the subjects were divided into four groups: G0 (<italic>n</italic>&#x202F;=&#x202F;2,298, normal control), G1 (<italic>n</italic>&#x202F;=&#x202F;388, only having undergone hysterectomy), G2 (<italic>n</italic>&#x202F;=&#x202F;13, only having undergone oophorectomy), and G3 (<italic>n</italic>&#x202F;=&#x202F;422, having undergone hysterectomy and oophorectomy).</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Flowchart of participant selection from the NHANES 2007&#x2013;2018.</p>
</caption>
<graphic xlink:href="fnut-12-1623490-g001.tif">
<alt-text content-type="machine-generated">Flowchart of sample exclusion criteria for NHANES 2007-2018. Starting with 59,842 participants, 29,629 males are excluded. Remaining 30,213 reduced by 20,198 due to missing demographic and examination data. Sample of 10,015 further reduced by 1,865 due to missing questionnaire data on medical history. Remaining 8,150 reduced by 5,029 due to missing laboratory and dietary data, resulting in a final sample of 3,121.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec9">
<title>Definition of hysterectomy and/or oophorectomy</title>
<p>Similar to the previous study (<xref ref-type="bibr" rid="ref8">8</xref>), hysterectomy was measured by the following question: &#x201C;Had a hysterectomy? (RHD280).&#x201D; Women who answered &#x201C;yes&#x201D; were considered having hysterectomy. Similarly, ovaries removed were defined according to the question: &#x201C;Had both ovaries removed? (RHD305).&#x201D; Women who answer &#x201C;yes&#x201D; were considered to have the oophorectomy.</p>
</sec>
<sec id="sec10">
<title>Definition of arthritis</title>
<p>Similar to the previous study (<xref ref-type="bibr" rid="ref27">27</xref>), arthritis was measured with the following question (MCQ160a): Has a doctor or other health professional ever told you that you had arthritis? Women who answered yes were considered to have arthritis.</p>
</sec>
<sec id="sec11">
<title>Measurements of blood heavy metals</title>
<p>The levels of blood heavy metals were obtained from the lead, cadmium, total mercury, selenium and manganese&#x2014;blood (PBCD) dataset of laboratory data, including measurements of blood lead (umol/L), blood cadmium (umol/L), blood mercury (umol/L), blood selenium (umol/L), and blood manganese (umol/L).</p>
</sec>
<sec id="sec12">
<title>Measurements of total nutrient intake</title>
<p>Related dietary parameters were derived from the Dietary Interview&#x2014;Total Nutrient Intakes, First Day (DR1TOT). In this study, we focused on vitamin intake, including the following: vitamin A (mcg), vitamin B1 (mg), vitamin B2 (mg), vitamin B6 (mg), vitamin B12 (mcg), vitamin C (mg), vitamin D (D2&#x202F;+&#x202F;D3) (mcg), vitamin E (mg), and vitamin K (mcg).</p>
</sec>
<sec id="sec13">
<title>Other covariates</title>
<p>Similar to several previous studies (<xref ref-type="bibr" rid="ref28">28</xref>, <xref ref-type="bibr" rid="ref29">29</xref>), age, gender, race education level, race, and poverty ratio were obtained from demographics data. BMI and weight were collected from examination data. Smoking status and drink status were collected during in-home interviews.</p>
</sec>
<sec id="sec14">
<title>Statistical analysis</title>
<p>DecisionLinnc1.0 software (<xref ref-type="bibr" rid="ref30">30</xref>) was used for data analysis, which is a platform that integrates multiple programming language environments. The logistic regression analysis model was used across three distinct models to examine the relationship between hysterectomy and arthritis. Subgroup analyses were also conducted. Next, restricted cubic splines (RCS) were utilized to explore potential non-linear relationships between blood heavy metals, vitamin, and the risk of arthritis caused by hysterectomy. The parallel mediation analysis was performed to clarify their intermediary roles. Weighted quantile sum (WQS) regression was used to explore the overall effect of metals on arthritis. A <italic>p</italic>-value of &#x003C; 0.05 was considered statistically significant.</p>
</sec>
</sec>
<sec sec-type="results" id="sec15">
<title>Results</title>
<sec id="sec16">
<title>Baseline participant characteristics</title>
<p>A total of 3,121 participants with complete data from NHANES (2007&#x202F;~&#x202F;2018) were included in this study. <xref ref-type="table" rid="tab1">Table 1</xref> presents the baseline characteristics of the participants according to hysterectomy. Of 3,121 participants, 1,237 (39.63%) women had arthritis. Compared to the G0 group, the rates of arthritis in the participants having undergone hysterectomy (G1) were significantly increased (58.25% vs. 31.64%, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001). When women who underwent hysterectomy and had their ovaries removed at the same time (G3), her arthritis rate further increased to 65.64%. In addition, among women who had undergone gynecological surgery were generally older (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001) and had a higher BMI (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001), but the smoking rate was significantly reduced (<italic>p</italic>&#x202F;=&#x202F;0.001).</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Baseline participant characteristics according to hysterectomy.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Variable names</th>
<th align="center" valign="top" rowspan="2">Overall</th>
<th align="center" valign="top" colspan="4">Operation mode</th>
<th align="center" valign="top" rowspan="2">p-value</th>
</tr>
<tr>
<th align="center" valign="top">G0</th>
<th align="center" valign="top">G1</th>
<th align="center" valign="top">G2<sup>#</sup></th>
<th align="center" valign="top">G3</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle"><italic>n</italic></td>
<td align="center" valign="middle">3,121</td>
<td align="center" valign="middle">2,298</td>
<td align="center" valign="middle">388</td>
<td align="center" valign="middle">13</td>
<td align="center" valign="middle">422</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Age (year)</td>
<td align="center" valign="middle">49.11&#x202F;&#x00B1;&#x202F;15.98</td>
<td align="center" valign="middle">45.75&#x202F;&#x00B1;&#x202F;15.65</td>
<td align="center" valign="middle">57.40&#x202F;&#x00B1;&#x202F;12.49</td>
<td align="center" valign="middle">58.81&#x202F;&#x00B1;&#x202F;11.56</td>
<td align="center" valign="middle">60.83&#x202F;&#x00B1;&#x202F;11.88</td>
<td align="center" valign="middle">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">20&#x202F;~&#x202F;34</td>
<td align="center" valign="middle">649 (20.79%)</td>
<td align="center" valign="middle">638 (27.76%)</td>
<td align="center" valign="middle">4 (1.03%)</td>
<td align="center" valign="middle">1 (7.69%)</td>
<td align="center" valign="middle">6 (1.42%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">35&#x202F;~&#x202F;44</td>
<td align="center" valign="middle">529 (16.95%)</td>
<td align="center" valign="middle">450 (19.58%)</td>
<td align="center" valign="middle">49 (12.63%)</td>
<td align="center" valign="middle">1 (7.69%)</td>
<td align="center" valign="middle">29 (6.87%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">45&#x202F;~&#x202F;55</td>
<td align="center" valign="middle">650 (20.83%)</td>
<td align="center" valign="middle">468 (20.37%)</td>
<td align="center" valign="middle">97 (25.00%)</td>
<td align="center" valign="middle">2 (15.38%)</td>
<td align="center" valign="middle">83 (19.67%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">&#x202F;&#x003E;&#x202F;=55</td>
<td align="center" valign="middle">1,293 (41.43%)</td>
<td align="center" valign="middle">742 (32.29%)</td>
<td align="center" valign="middle">238 (61.34%)</td>
<td align="center" valign="middle">9 (69.23%)</td>
<td align="center" valign="middle">304 (72.04%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Race (%)</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td align="center" valign="middle">0.039</td>
</tr>
<tr>
<td align="left" valign="middle">Mexican American</td>
<td align="center" valign="middle">307 (9.84%)</td>
<td align="center" valign="middle">246 (10.70%)</td>
<td align="center" valign="middle">33 (8.51%)</td>
<td align="center" valign="middle">0 (0.00%)</td>
<td align="center" valign="middle">28 (6.64%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Other Hispanic</td>
<td align="center" valign="middle">260 (8.33%)</td>
<td align="center" valign="middle">206 (8.96%)</td>
<td align="center" valign="middle">34 (8.76%)</td>
<td align="center" valign="middle">1 (7.69%)</td>
<td align="center" valign="middle">19 (4.50%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Non-Hispanic White</td>
<td align="center" valign="middle">1,801 (57.71%)</td>
<td align="center" valign="middle">1,306 (56.83%)</td>
<td align="center" valign="middle">217 (55.93%)</td>
<td align="center" valign="middle">7 (53.85%)</td>
<td align="center" valign="middle">271 (64.22%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Non-Hispanic Black</td>
<td align="center" valign="middle">594 (19.03%)</td>
<td align="center" valign="middle">413 (17.97%)</td>
<td align="center" valign="middle">92 (23.71%)</td>
<td align="center" valign="middle">2 (15.38%)</td>
<td align="center" valign="middle">87 (20.62%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Other race</td>
<td align="center" valign="middle">159 (5.09%)</td>
<td align="center" valign="middle">127 (5.53%)</td>
<td align="center" valign="middle">12 (3.09%)</td>
<td align="center" valign="middle">3 (23.08%)</td>
<td align="center" valign="middle">17 (4.03%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Poverty income ratio</td>
<td align="center" valign="middle">2.74&#x202F;&#x00B1;&#x202F;1.66</td>
<td align="center" valign="middle">2.72&#x202F;&#x00B1;&#x202F;1.68</td>
<td align="center" valign="middle">2.77&#x202F;&#x00B1;&#x202F;1.61</td>
<td align="center" valign="middle">3.61&#x202F;&#x00B1;&#x202F;1.57</td>
<td align="center" valign="middle">2.84&#x202F;&#x00B1;&#x202F;1.58</td>
<td align="center" valign="middle">0.081</td>
</tr>
<tr>
<td align="left" valign="middle">&#x202F;&#x003C;&#x202F;5.0</td>
<td align="center" valign="middle">2,681 (85.90%)</td>
<td align="center" valign="middle">1,967 (85.60%)</td>
<td align="center" valign="middle">337 (86.86%)</td>
<td align="center" valign="middle">10 (76.92%)</td>
<td align="center" valign="middle">367 (86.97%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">&#x202F;&#x003E;&#x202F;=5.0</td>
<td align="center" valign="middle">440 (14.10%)</td>
<td align="center" valign="middle">331 (14.40%)</td>
<td align="center" valign="middle">51 (13.14%)</td>
<td align="center" valign="middle">3 (23.08%)</td>
<td align="center" valign="middle">55 (13.03%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Education level (%)</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td align="center" valign="middle">0.124</td>
</tr>
<tr>
<td align="left" valign="middle">Less than 9th grade</td>
<td align="center" valign="middle">225 (7.21%)</td>
<td align="center" valign="middle">149 (6.48%)</td>
<td align="center" valign="middle">32 (8.25%)</td>
<td align="center" valign="middle">0 (0.00%)</td>
<td align="center" valign="middle">44 (10.43%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">9&#x2013;11th grade</td>
<td align="center" valign="middle">592 (18.97%)</td>
<td align="center" valign="middle">434 (18.89%)</td>
<td align="center" valign="middle">89 (22.94%)</td>
<td align="center" valign="middle">3 (23.08%)</td>
<td align="center" valign="middle">66 (15.64%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">High school graduate</td>
<td align="center" valign="middle">777 (24.90%)</td>
<td align="center" valign="middle">572 (24.89%)</td>
<td align="center" valign="middle">91 (23.45%)</td>
<td align="center" valign="middle">2 (15.38%)</td>
<td align="center" valign="middle">112 (26.54%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Some college</td>
<td align="center" valign="middle">1,028 (32.94%)</td>
<td align="center" valign="middle">748 (32.55%)</td>
<td align="center" valign="middle">131 (33.76%)</td>
<td align="center" valign="middle">5 (38.46%)</td>
<td align="center" valign="middle">144 (34.12%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">College graduate or above</td>
<td align="center" valign="middle">499 (15.99%)</td>
<td align="center" valign="middle">395 (17.19%)</td>
<td align="center" valign="middle">45 (11.60%)</td>
<td align="center" valign="middle">3 (23.08%)</td>
<td align="center" valign="middle">56 (13.27%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">BMI (kg/m<sup>2</sup>)</td>
<td align="center" valign="middle">29.17&#x202F;&#x00B1;&#x202F;7.38</td>
<td align="center" valign="middle">28.88&#x202F;&#x00B1;&#x202F;7.46</td>
<td align="center" valign="middle">30.08&#x202F;&#x00B1;&#x202F;7.12</td>
<td align="center" valign="middle">27.69&#x202F;&#x00B1;&#x202F;6.57</td>
<td align="center" valign="middle">30.10&#x202F;&#x00B1;&#x202F;7.04</td>
<td align="center" valign="middle">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">Normal weight (%)</td>
<td align="center" valign="middle">895 (28.68%)</td>
<td align="center" valign="middle">714 (31.07%)</td>
<td align="center" valign="middle">91 (23.45%)</td>
<td align="center" valign="middle">5 (38.46%)</td>
<td align="center" valign="middle">85 (20.14%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Overweight (%)</td>
<td align="center" valign="middle">882 (28.26%)</td>
<td align="center" valign="middle">629 (27.37%)</td>
<td align="center" valign="middle">106 (27.32%)</td>
<td align="center" valign="middle">1 (7.69%)</td>
<td align="center" valign="middle">146 (34.60%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Obesity (%)</td>
<td align="center" valign="middle">1,344 (43.06%)</td>
<td align="center" valign="middle">955 (41.56%)</td>
<td align="center" valign="middle">191 (49.23%)</td>
<td align="center" valign="middle">7 (53.85%)</td>
<td align="center" valign="middle">191 (45.26%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Smoking statue</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td align="center" valign="top">0.001</td>
</tr>
<tr>
<td align="left" valign="middle">No</td>
<td align="center" valign="top">1,613 (51.68%)</td>
<td align="center" valign="top">1,098 (47.78%)</td>
<td align="center" valign="top">233 (60.05%)</td>
<td align="center" valign="top">7 (53.85%)</td>
<td align="center" valign="top">275 (65.17%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Yes</td>
<td align="center" valign="top">1,508 (48.32%)</td>
<td align="center" valign="top">1,200 (52.22%)</td>
<td align="center" valign="top">155 (39.95%)</td>
<td align="center" valign="top">6 (46.15%)</td>
<td align="center" valign="top">147 (34.83%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Drinking statue</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td align="center" valign="top">0.076</td>
</tr>
<tr>
<td align="left" valign="middle">No</td>
<td align="center" valign="top">658 (21.08%)</td>
<td align="center" valign="top">452 (19.67%)</td>
<td align="center" valign="top">94 (24.23%)</td>
<td align="center" valign="top">2 (15.38%)</td>
<td align="center" valign="top">110 (26.07%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Yes</td>
<td align="center" valign="top">2,463 (78.92%)</td>
<td align="center" valign="top">1,846 (80.33%)</td>
<td align="center" valign="top">294 (75.77%)</td>
<td align="center" valign="top">11 (84.62%)</td>
<td align="center" valign="top">312 (73.93%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Arthritis</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td align="center" valign="middle">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">No</td>
<td align="center" valign="middle">1,884 (60.37%)</td>
<td align="center" valign="middle">1,571 (68.36%)</td>
<td align="center" valign="middle">162 (41.75%)</td>
<td align="center" valign="middle">6 (46.15%)</td>
<td align="center" valign="middle">145 (34.36%)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Yes</td>
<td align="center" valign="middle">1,237 (39.63%)</td>
<td align="center" valign="middle">727 (31.64%)</td>
<td align="center" valign="middle">226 (58.25%)</td>
<td align="center" valign="middle">7 (53.85%)</td>
<td align="center" valign="middle">277 (65.64%)</td>
<td/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><sup>#</sup>The G2 subgroup (ovariectomy without hysterectomy) includes only <italic>n</italic>&#x202F;=&#x202F;13, limiting statistical power.</p>
</table-wrap-foot>
</table-wrap>
<p><xref ref-type="table" rid="tab2">Table 2</xref> compares the levels of blood heavy metals according to hysterectomy or arthritis, respectively. Notably, the levels of blood lead were significantly increased in women having undergone gynecological surgery (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001). At the same time, the blood lead levels of women with arthritis were also significantly increased (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001).</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>Comparison of blood heavy metals according to hysterectomy and arthritis.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th rowspan="2"/>
<th align="center" valign="top" colspan="5">Hysterectomy</th>
<th align="center" valign="top" colspan="3">Arthritis</th>
</tr>
<tr>
<th align="center" valign="top">G0</th>
<th align="center" valign="top">G1</th>
<th align="center" valign="top">G2<sup>#</sup></th>
<th align="center" valign="top">G3</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
<th align="center" valign="top">No</th>
<th align="center" valign="top">Yes</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Blood lead (umol/L)</td>
<td align="center" valign="middle">0.06&#x202F;&#x00B1;&#x202F;0.04</td>
<td align="center" valign="middle">0.08&#x202F;&#x00B1;&#x202F;0.08</td>
<td align="center" valign="middle">0.08&#x202F;&#x00B1;&#x202F;0.04</td>
<td align="center" valign="middle">0.08&#x202F;&#x00B1;&#x202F;0.05</td>
<td align="center" valign="middle">&#x003C;0.001</td>
<td align="center" valign="middle">0.06&#x202F;&#x00B1;&#x202F;0.04</td>
<td align="center" valign="middle">0.08&#x202F;&#x00B1;&#x202F;0.06</td>
<td align="center" valign="middle">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">Blood mercury (nmol/L)</td>
<td align="center" valign="middle">6.78&#x202F;&#x00B1;&#x202F;9.17</td>
<td align="center" valign="middle">6.29&#x202F;&#x00B1;&#x202F;6.94</td>
<td align="center" valign="middle">7.84&#x202F;&#x00B1;&#x202F;6.09</td>
<td align="center" valign="middle">6.12&#x202F;&#x00B1;&#x202F;6.71</td>
<td align="center" valign="middle">0.306</td>
<td align="center" valign="middle">6.89&#x202F;&#x00B1;&#x202F;9.23</td>
<td align="center" valign="middle">6.22&#x202F;&#x00B1;&#x202F;7.50</td>
<td align="center" valign="middle">0.201</td>
</tr>
<tr>
<td align="left" valign="middle">Blood cadmium (nmol/L)</td>
<td align="center" valign="middle">7.43&#x202F;&#x00B1;&#x202F;7.82</td>
<td align="center" valign="middle">6.99&#x202F;&#x00B1;&#x202F;6.13</td>
<td align="center" valign="middle">5.89&#x202F;&#x00B1;&#x202F;4.94</td>
<td align="center" valign="middle">6.79&#x202F;&#x00B1;&#x202F;5.84</td>
<td align="center" valign="middle">0.749</td>
<td align="center" valign="middle">7.12&#x202F;&#x00B1;&#x202F;7.18</td>
<td align="center" valign="middle">7.59&#x202F;&#x00B1;&#x202F;7.76</td>
<td align="center" valign="middle">0.039</td>
</tr>
<tr>
<td align="left" valign="middle">Blood selenium (umol/L)</td>
<td align="center" valign="middle">2.48&#x202F;&#x00B1;&#x202F;0.45</td>
<td align="center" valign="middle">2.44&#x202F;&#x00B1;&#x202F;0.57</td>
<td align="center" valign="middle">2.31&#x202F;&#x00B1;&#x202F;0.21</td>
<td align="center" valign="middle">2.46&#x202F;&#x00B1;&#x202F;0.34</td>
<td align="center" valign="middle">0.001</td>
<td align="center" valign="middle">2.49&#x202F;&#x00B1;&#x202F;0.47</td>
<td align="center" valign="middle">2.44&#x202F;&#x00B1;&#x202F;0.42</td>
<td align="center" valign="middle">0.274</td>
</tr>
<tr>
<td align="left" valign="middle">Blood manganese (nmol/L)</td>
<td align="center" valign="middle">186.99&#x202F;&#x00B1;&#x202F;71.46</td>
<td align="center" valign="middle">165.82&#x202F;&#x00B1;&#x202F;54.06</td>
<td align="center" valign="middle">177.71&#x202F;&#x00B1;&#x202F;104.66</td>
<td align="center" valign="middle">181.97&#x202F;&#x00B1;&#x202F;85.09</td>
<td align="center" valign="middle">0.007</td>
<td align="center" valign="middle">184.17&#x202F;&#x00B1;&#x202F;69.86</td>
<td align="center" valign="middle">183.71&#x202F;&#x00B1;&#x202F;75.90</td>
<td align="center" valign="middle">0.799</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><sup>#</sup>The G2 subgroup (ovariectomy without hysterectomy) includes only <italic>n</italic>&#x202F;=&#x202F;13, limiting statistical power.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec17">
<title>Associations between hysterectomy and arthritis</title>
<p>We have established three models before and after adjusting for confounding factors. As shown in <xref ref-type="table" rid="tab3">Table 3</xref>, these three models established a statistically significant association between hysterectomy and arthritis. In the unadjusted model (Model 1), the risk of arthritis for women who had undergone hysterectomy was significantly increased. The odds ratio (OR) and 95% confidence intervals (CIs) were 3.55 (2.49, 5.04) (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.0001). After additionally adjusting for general data confounding factors such as race, education, poverty&#x2013;income ratio (Model 2), hysterectomy was still associated with an increased risk of arthritis (OR&#x202F;=&#x202F;3.47, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.0001). Furthermore, Model 3 still showed this trend of increased risk after additionally adjusting for BMI, smoking status, and drinking status (OR&#x202F;=&#x202F;3.33, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.0001). The risk would further increase when woman underwent hysterectomy and oophorectomy. The ORs were 5.08, 4.94, and 4.67, respectively (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.0001).</p>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption>
<p>Multivariable-adjust ORs and 95%CI of hysterectomy and arthritis.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Hysterectomy</th>
<th align="center" valign="top" colspan="2">Model 1</th>
<th align="center" valign="top" colspan="2">Model 2</th>
<th align="center" valign="top" colspan="2">Model 3</th>
</tr>
<tr>
<th align="center" valign="top">OR (95%CI)</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
<th align="center" valign="top">OR (95%CI)</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
<th align="center" valign="top">OR (95%CI)</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" colspan="7">Overall (<italic>n</italic> =&#x202F;3,121)</td>
</tr>
<tr>
<td align="left" valign="middle">G0</td>
<td align="center" valign="middle">Reference</td>
<td/>
<td align="center" valign="middle">Reference</td>
<td/>
<td align="center" valign="middle">Reference</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">G1</td>
<td align="center" valign="middle">3.55 (2.49, 5.04)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
<td align="center" valign="middle">3.47 (2.46, 4.90)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
<td align="center" valign="middle">3.33 (2.36, 4.70)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="middle">G2<sup>#</sup></td>
<td align="center" valign="middle">2.08 (0.53, 8.21)</td>
<td align="center" valign="middle">0.2917</td>
<td align="center" valign="middle">2.12 (0.52, 8.55)</td>
<td align="center" valign="middle">0.2854</td>
<td align="center" valign="middle">2.23 (0.59, 8.41)</td>
<td align="center" valign="middle">0.2337</td>
</tr>
<tr>
<td align="left" valign="middle">G3</td>
<td align="center" valign="middle">5.08 (3.76, 6.86)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
<td align="center" valign="middle">4.94 (3.63, 6.72)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
<td align="center" valign="middle">4.67 (3.41, 6.39)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Model 1 without adjustments. Model 2 was additionally adjusted for race, education level, and poverty. Model 3 was additionally adjusted for BMI, smoking status, and drink statue. <sup>#</sup>The G2 subgroup (ovariectomy without hysterectomy) includes only <italic>n</italic>&#x202F;=&#x202F;13, limiting statistical power.</p>
</table-wrap-foot>
</table-wrap>
<p>To examine potential differences in the relationship between hysterectomy and arthritis in specific populations, we conducted subgroup analyses and interaction tests by age, race, education level, poverty ratio, BMI, smoking status, and drinking status. As shown in <xref ref-type="fig" rid="fig2">Figure 2</xref>, significant interactions were found between race, BMI, and drink status.</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Subgroup analysis of the associations between hysterectomy and arthritis.</p>
</caption>
<graphic xlink:href="fnut-12-1623490-g002.tif">
<alt-text content-type="machine-generated">Forest plot showing odds ratios and confidence intervals for various demographic variables. Variables include age groups, race, education level, poverty income ratio, BMI, smoking status, and drinking status. The odds ratio ranges from 1.53 to 6.55, with p-values indicating statistical significance. Notable interactions are highlighted with arrows and p-values, suggesting differences in effect size across subgroups. The plot assesses associations with a reference line at 1.0.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec18">
<title>Effects of blood heavy metals</title>
<p>First, the RCS curves were employed to display the association between the levels of blood heavy metals and the risk of arthritis caused by hysterectomy. After adjusting for multiple variables, evidence of a non-linear (L-shaped) relationship were observed in blood lead, mercury, and cadmium (<italic>p</italic> for non-linearity &#x003C;0.001) (<xref ref-type="fig" rid="fig3">Figures 3A</xref>&#x2013;<xref ref-type="fig" rid="fig3">C</xref>). However, there was no non-linear (L-shaped) relationship between blood selenium, manganese, and the odds ratio (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure 1</xref>). Second, WQS regression models were used to evaluate the impact of blood heavy metals on the risk of arthritis caused by hysterectomy. Among the five heavy metals, blood lead was the highest WQS weight, with the highest contribution at 0.72 (<xref ref-type="fig" rid="fig3">Figure 3D</xref>). Third, smooth curve fitting was used to clarify the relationship between blood lead and arthritis risk (<xref ref-type="fig" rid="fig4">Figure 4A</xref>). An inflection point (0.10&#x202F;&#x03BC;mol/L) was determined by threshold effect analysis. It was particularly noteworthy that each unit intake increase in blood lead amplified the risk of arthritis by 32% (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001) below this level. Next, to clarify whether blood lead plays an intermediary role between hysterectomy and arthritis, the parallel mediation analysis was carried out. Mediation analysis demonstrated that blood lead accounted for 6.02% of the observed association between hysterectomy and arthritis (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001, <xref ref-type="fig" rid="fig4">Figure 4B</xref>). No significant mediated effects were found on other heavy metals.</p>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p>Association between blood heavy metals and the risk of arthritis caused by hysterectomy. <bold>(A)</bold> Restricted cubic splines curves of lead. <bold>(B)</bold> Restricted cubic splines curves of mercury. <bold>(C)</bold> Restricted cubic splines curves of cadmium. <bold>(D)</bold> WQS regression model of blood heavy metals. Results were adjusted for race, education level, smoking status, drink statue, and BMI.</p>
</caption>
<graphic xlink:href="fnut-12-1623490-g003.tif">
<alt-text content-type="machine-generated">Three RCS prediction plots and one bar plot illustrate a study's findings. Plots A, B, and C show the odds ratio versus blood levels of lead, mercury, and cadmium, respectively, with p-values for overall and nonlinear effects. Plot D presents a weighted quantile sum (WQS) regression model bar plot displaying mean weights for blood elements. Blood lead has the highest mean weight of 0.72, followed by manganese at 0.12, mercury at 0.09, cadmium at 0.05, and selenium at 0.02.</alt-text>
</graphic>
</fig>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p>Mediation of blood lead in the association between hysterectomy and arthritis. <bold>(A)</bold>. Smooth curve fitting of blood lead. <bold>(B)</bold>. Mediation analysis of blood lead. Results were adjusted for race, education level, smoking status, drink statue, and BMI.</p>
</caption>
<graphic xlink:href="fnut-12-1623490-g004.tif">
<alt-text content-type="machine-generated">Panel A shows a curve smoothing plot with blood lead levels (0 to 0.16 micromoles per liter) on the x-axis and fit values (0 to 1) on the y-axis. A red line with blue dashed confidence intervals depicts the trend. Panel B illustrates a mediation model with "Blood Lead" leading to "Hysterectomy" and "Arthritis." Indirect, direct, and total effects, along with confidence intervals and p-values, are shown. The proportion of mediation is given as 6.02% with a p-value less than 0.001.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec19">
<title>Improvement of nutrient intake</title>
<p>We evaluated the potential of nine vitamin intakes in reducing the risk of arthritis caused by hysterectomy. The RCS curves confirmed that there was a non-linear (L-shaped) relationship between vitamin K, vitamin D, and the odds ratio of the risk of arthritis caused by hysterectomy (<italic>p</italic> for non-linearity &#x003C;0.001) (<xref ref-type="fig" rid="fig5">Figures 5A</xref>,<xref ref-type="fig" rid="fig5">B</xref>). Additionally, smooth curve fitting also clarified that arthritis after hysterectomy would be reduced with the intake of vitamin K and vitamin D (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure 2</xref>). With threshold effect analysis, both optimal inflection points were 212.0 mcg/day for vitamin K and 10.8 mcg/day for vitamin D, respectively. Beyond this level, each additional unit of intake would significantly reduce the risk of arthritis by 20 and 53%, respectively (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001).</p>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p>Dietary fiber intake reduces the risk of arthritis. <bold>(A)</bold>. Restricted cubic splines curves of vitamin K. <bold>(B)</bold>. Restricted cubic splines curves of vitamin D. Results were adjusted for gender, race, education level, smoking status, and BMI.</p>
</caption>
<graphic xlink:href="fnut-12-1623490-g005.tif">
<alt-text content-type="machine-generated">Panel A and B show RCS prediction plots for Vitamin K and D intake, respectively. Panel A depicts the odds ratio for Vitamin K intake against a threshold of two hundred twelve micrograms per day, showing a nonlinear trend with p-values of 0.018 and 0.005. Panel B illustrates the odds ratio for Vitamin D intake with a threshold of ten point eight micrograms per day, also indicating nonlinearity with p-values of 0.01 and 0.003. Both panels display histograms in the background.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec sec-type="discussion" id="sec20">
<title>Discussion</title>
<p>The present study represents the first large-scale epidemiological investigation to systematically evaluate the relationship between hysterectomy and arthritis risk in women, with a focus on elucidating the mediating role of serum heavy metals (particularly blood lead) and the protective effects of dietary micronutrients (notably vitamin K and vitamin D). Leveraging data from the NHANES cohort (2007&#x2013;2018), our findings revealed three key observations: (1) hysterectomy, especially when combined with oophorectomy, is independently associated with a 3.3&#x202F;~&#x202F;4.7-fold increased risk of arthritis in women; (2) elevated blood lead levels mediate approximately 6% of this association, exhibiting a non-linear threshold effect; and (3) higher dietary intake of vitamin K and vitamin D significantly attenuates arthritis risk in hysterectomized women, with protective thresholds identified at 16.7 mcg/day and 1.3 mcg/day, respectively. These results advance our understanding of the long-term musculoskeletal consequences of hysterectomy and highlight actionable targets for mitigating post-surgical morbidity.</p>
<p>Our analysis corroborates emerging evidence linking hysterectomy to arthritis morbidity. The adjusted odds ratio (OR&#x202F;=&#x202F;3.33, 95%CI: 2.49&#x2013;5.04) for arthritis in hysterectomized women aligns with prior reports, such as the Taiwanese cohort study identifying a 25% increased risk of knee osteoarthritis (OA) post-hysterectomy (adjusted OR&#x202F;=&#x202F;1.25). Notably, the risk escalated further in women who underwent concurrent oophorectomy (OR&#x202F;=&#x202F;4.67), underscoring the compounded effects of estrogen depletion. Mechanistically, the uterus is not merely a reproductive organ but an endocrine-active tissue contributing to extra-ovarian estrogen synthesis and immunomodulation. Its removal disrupts systemic estrogen signalling, which regulates cartilage homeostasis, synovial inflammation, and osteoclast activity (<xref ref-type="bibr" rid="ref31">31</xref>). Estrogen deficiency post-hysterectomy may accelerate joint degeneration via upregulation of matrix metalloproteinases (MMPs) (<xref ref-type="bibr" rid="ref32">32</xref>) and interleukin-1&#x03B2; (IL-1&#x03B2;) (<xref ref-type="bibr" rid="ref33">33</xref>), pathways implicated in both OA and rheumatoid arthritis (RA) pathogenesis. Furthermore, surgical trauma and postoperative inflammation could induce epigenetic modifications in joint tissues, priming them for accelerated aging.</p>
<p>A groundbreaking finding of this study is the identification of blood lead as a partial mediator (6.02%, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001) of the hysterectomy-arthritis relationship. Women with hysterectomy exhibited significantly higher levels of blood lead. Blood lead exposure amplified arthritis risk disproportionately, suggesting that even subclinical elevations may synergize with post-surgical metabolic shifts to harm joint health. Lead&#x2019;s role in arthritis pathogenesis is well documented. Our mediation analysis suggested that hysterectomy exacerbated lead retention and further led to the occurrence and development of arthritis. However, the exact reason is still unclear. Studies have found that the expression of metallothionein I (MT-I) shows estrogen-dependent characteristics (<xref ref-type="bibr" rid="ref34">34</xref>), while metallothionein has a broad potential for application in alleviating environmental heavy metal pollution (<xref ref-type="bibr" rid="ref35">35</xref>). This might be one reason for the storage of blood lead due to estrogen deficiency after a hysterectomy. Interestingly, for blood lead, the inflection point at 0.10&#x202F;&#x03BC;mol/L represents a toxicity threshold: below this level, each unit increase in lead amplified arthritis risk greatly. The threshold effect (0.10&#x202F;&#x03BC;mol/L) corresponds to blood lead levels observed in populations with environmental or occupational exposure, highlighting the need for stricter monitoring in hysterectomized women. Public health interventions targeting lead reduction could mitigate arthritis risks in this vulnerable group, such as minimizing exposure to contaminated water, cosmetics, or ceramics.</p>
<p>Our study pioneers the exploration of dietary micronutrients as modifiers of hysterectomy-associated arthritis. Hysterectomy induces a dual deficiency state: estrogen loss impairs vitamin D activation, while an altered gut microbiota reduces vitamin bioavailability. Hysterectomized women may face additional barriers to adequate intake, such as post-surgical dietary restrictions or gut dysbiosis. The uterus and ovaries interact with the gut microbiota through estrogen-mediated modulation of intestinal permeability. Hysterectomy disrupts this axis, potentially impairing fat-soluble vitamin absorption (e.g., vitamins K and D). Dietary interventions emphasizing leafy greens (rich in vitamin K) and fortified dairy products (vitamin D sources) could counteract these deficits. Vitamin K emerged as a potent protective factor, with intake above 212.0 mcg/day reducing arthritis odds by 20% (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001). Vitamin D exhibited similar benefits with the optimal inflection points 212.0 mcg/day The protective threshold of vitamin K, particularly through matrix Gla-protein (MGP), is essential for bone health and may help prevent joint calcification and inflammation (<xref ref-type="bibr" rid="ref36">36</xref>, <xref ref-type="bibr" rid="ref37">37</xref>). Additionally, hysterectomy may induce vitamin D deficiency through estrogen, thus indicating that even moderate intake confers benefits. The non-linear dose&#x2013;response relationships suggest that optimal&#x2014;rather than maximal&#x2014;intake confers protection.</p>
<p>However, there are some limitations to the present study. The study&#x2019;s cross-sectional design limits the ability to establish causality. We did not further classify arthritis, such as osteoarthritis and rheumatoid arthritis. There was the potential for selection bias due to exclusion of participants with missing data (&#x003E;50% of the initial sample). We could not clarify the arthritis that occurred after uterine surgery due to a large number of missing data. We could only analyze the average ages of the two events that occurred, which were 40.85 (age when had hysterectomy) and 57.87 (age when told you had arthritis), respectively. The sample size of G2 (only having undergone ovaries removal) was too small, which might affect the analysis results of the subsequent group. However, in the results section, we focused on women who underwent hysterectomy (G1 and G3). The measurement of main variables (such as hysterectomy, arthritis, and dietary vitamin intake) relies on self-reported data, which is susceptible to recall bias. Additionally, despite adjusting for several potential confounders, the absence of important covariates (such as menopausal status, hormone replacement therapy, and time since surgery) could influence the results.</p>
<p>In conclusion, hysterectomy is associated with an increased risk of arthritis, with focus on blood lead as a mediating factor and vitamin intake as a potential protective factor. It will contribute to long-term health management after hysterectomy.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec21">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM1">Supplementary material</xref>, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec sec-type="ethics-statement" id="sec22">
<title>Ethics statement</title>
<p>Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the (patients/participants or patients/participants legal guardian/next of kin) was not required to participate in this study in accordance with the national legislation and the institutional requirements.</p>
</sec>
<sec sec-type="author-contributions" id="sec23">
<title>Author contributions</title>
<p>BX: Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing, Investigation, Methodology. XW: Writing &#x2013; review &#x0026; editing, Methodology, Investigation. ZL: Project administration, Writing &#x2013; review &#x0026; editing, Methodology, Investigation. BY: Project administration, Writing &#x2013; original draft, Investigation, Writing &#x2013; review &#x0026; editing, Methodology, Funding acquisition.</p>
</sec>
<sec sec-type="funding-information" id="sec24">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. This study was funded by project funding for the training of high level health professionals in Changzhou (2022CZZY007).</p>
</sec>
<ack>
<p>We thank all of the project participants for their contributions.</p>
</ack>
<sec sec-type="COI-statement" id="sec25">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="sec26">
<title>Generative AI statement</title>
<p>The author(s) declare that no Gen AI was used in the creation of this manuscript.</p>
</sec>
<sec sec-type="disclaimer" id="sec27">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec sec-type="supplementary-material" id="sec28">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/fnut.2025.1623490/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fnut.2025.1623490/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Image_1.pdf" id="SM1" mimetype="application/pdf" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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